UK Data Servicedoc.ukdataservice.ac.uk/doc/5295/mrdoc/pdf/5295userguide.pdf · 2006-01-27 ·...

Anthropology Department University of Sussex Falmer, Brighton BN1 9SJ www.sussex.ac.uk/anthropology Telephone: (01273) 873392 Email: [email protected]

MMR in Brighton and Hove – Making your views count

? Problems Reading? Call Mike on 01273 873392.

Dear Re: Your child XXXXXXX We would like to invite you to take part in a study about parents’ experiences of the MMR vaccine. We have developed the enclosed questionnaire out of conversations with Brighton and Hove parents to include more people’s views. If you have problems reading, call Mike (01273 873392) and you can do the questionnaire by phone. We are inviting parents or guardians of children between 15 and 24 months of age in Brighton and Hove who have been randomly chosen to take part in the study. We do hope you will take this opportunity to fill in the questionnaire to make your own views and experiences count. We are not taking a view either for or against MMR vaccination. Even if you don't feel you have a strong opinion on the issue, your experience is very important to the overall aim of improving communication between parents and health professionals. The study is trying to find out more about parents’ thoughts and experiences about vaccination jabs. The research is based at the University of Sussex and funded by a grant from the Economic and Social Research Council. You can find out more about our funders at their website (http://www.esrc.ac.uk). We appreciate that as a parent with a small child you may be pressed for time. Our survey covers the many issues that different parents have considered important, and we do hope that filling in this questionnaire will be interesting for you. All information given will be treated confidentially, and your name will not be linked to it. No individual information will be given to anyone. Your doctor will not know whether you took part in the study or not, and your participation will have no effect on any treatment. The findings will be studied in relation to patterns of immunisation but at no point will we be analysing named individual data. The analysis will be carried out by Dr Jackie Cassell. When the results are processed in a few months' time they will be publicly available (on the internet [www.ids.ac.uk/ids/env/vaccination.html] or by request from the above address) and will help shape local and national approaches to ensuring children’s health. Two questionnaires are enclosed. The cream one is for mothers (or female guardians) to fill in. If you can, please pass the second, green questionnaire to the child's father. Two FREEPOST envelopes are enclosed for returning the questionnaires. We look forward to receiving your reply. Yours sincerely, Dr Mike Poltorak, Dr Jackie Cassell, Professor Melissa Leach, Professor James Fairhead

Q. Code:……….

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MMR in Brighton and Hove – Making your views count QUESTIONNAIRE FOR MOTHERS AND FEMALE GUARDIANS

First we would like to know a little about you and your relationship to the child named on this letter.

1. Are you the child’s mother? guardian? Other - please specify…………………………………………. ………………………………………… 2. Is the child named on the letter your first child? Yes

No If no, please can you tell us the ages of your older children?

years years years years years 3. Before answering our questions, could you tell us what you felt were the most important issues for you concerning whether or not your child should have the MMR vaccination?

………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………

Please could you answer the following questions on how decision making about MMR has related to the process of raising your child?

4. Did you attend any classes about birth or parenting, for any of your children? Please tick all that apply to you

Parentcraft classes run by the NHS Classes run by health visitor Classes run by NCT Yoga for childbirth Classes at the hospital I didn’t go to any classes Other……………………………………………..

5. Was the birth of this child as you planned it to be?

I had no particular plans Not at all as I planned More or less as I planned Very much what I planned

6. Please can you tell us more about what you planned? ……………………………………………………………………………………………………….

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7. Did you feel you were given enough control over the birth at the points you wanted it? On a scale of 0-10, please tick the box that applies to you

The midwives/doctors I was in control controlled me completely completely

0 1 2 3 4 5 6 7 8 9 10 8. Did your child have the Vitamin K injection after birth?

Yes No Don't know

9. How would you describe your child's health since he/she was born?

Generally strong Weak Don’t know

Please can you tell us a bit more about this?…………………………………………………… ……………………………………………………………………………………………………………………………………………………………………………………

10. Does your child have any of the following problems? Yes No

Eczema Allergies Sleep problem Breathing problem Eating problem another problem - please say what …………………………… ………………………………………………………

11. Have you consulted any of the following about your child's health? Please tick all that apply

Homeopath Herbalist Cranial osteopath Acupuncturist Ayurvedic practitioner Kinesiologist Other complementary practitioner - please specify_________________________________

12. When do you remember first thinking about MMR, for this child? Tick one box only

When he/she was due for MMR When he/she was due for the first baby jabs Around the time when he/she was born Before he/she was born Not sure A different time – please say when …………………………….

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13. Are there any aspects of your family's health history which affected your thinking about MMR?

Yes No Don't know If you answered yes, can you tell us a bit more about this?…………………………………………. ………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………

14. As a childhood illness, how serious do you think measles is?

Very serious Quite serious Mild Don't know

Other Please can you explain? ……………………………………………. ………………………………………………

15. These are some of the things that other parents in Brighton and Hove have said when discussing their

thinking about MMR. How much does each reflect your view or experience? On a scale of 1-5, please tick the box that applies to you next to each statement.

Not my

view/experience at all Strongly my

view/experience 1 2 3 4 5

I’ve had personal experience or know someone who suffered serious effects from these illnesses (measles, mumps or rubella).

My experience of hospitals and/or health professionals has undermined my faith in the medical profession.

I know parents whose children have been knocked back by the MMR. Friends and family have had the MMR and they were fine. I have friends or family who have autistic children. I know people who have older children who they didn’t vaccinate, and they’re fine.

I heard lots of stories of ‘my son or my daughter were great until they had the MMR’.

Vaccinating your child with MMR shows your responsibility to the community.

There is a chance of serious side effects from MMR if there is a weakness in that child.

Each child’s immune system is different. My child needs to be immunised, he/she can’t live in isolation. MMR is fine for most children but not for my child. What I do to one child I tend do to them all. I worry about the MMR because of my child's behaviour.

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16. Which of these sources of information about the MMR vaccine have you come across?

Please tick all that apply

Information that you found on the internet Information that someone else found on the internet Videos NCT Newsletter ABC magazine Public meetings about immunisation Newspaper articles Leaflets Television or radio news or adverts Television or radio documentaries Books Research papers Childcare magazine articles

16. Who did you talk to about the MMR? Please tick all that apply, showing on a scale of 1-5 how supportive they were in helping you think the issue through.

Very Unsupportive Very Supportive 1 2 3 4 5

Partner or husband Child's father Your GP Another doctor you went to see Health Visitor Your mother Your father Your sister Your brother Other mothers you know well Other mothers you don't know well Fathers you know well Fathers you don't know well Practice nurse Homeopath Other alternative health practitioner Your partner's relatives Work colleagues Other - please say who 1._________________________________. 2. _________________________________ 3. _________________________________. I didn't talk to anyone

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17. Did discussing with any of these people particularly influence what you did or plan to do about MMR? If

so please can you tell us a bit more about this? ……………………………………………………………….………………………………………………………………………………………………………………………………………………………………………………………………………………………

18. Here are some things that Brighton and Hove parents have said about their research and discussions on

MMR. How much does each of these reflect your view? On a scale of 1-5, please tick the box that applies to you next to each statement.

Not my view at all Strongly my view

1 2 3 4 5 The MMR is necessary to protect children from getting serious diseases.

You can get bogged down in the detail, too much research and you don't do anything.

There is no scientific proof that the MMR vaccine causes autism or any other problems.

Single vaccinations concern me too but not as much at the MMR. The MMR is too much in one go. All the stuff you hear about the negative effects of the MMR is media hype.

It’s better to get immunity naturally. Not enough research has been done on the MMR. I tend to avoid talking to my friends about the MMR issue. I don’t feel we have enough information to make an informed decision.

19. Who decides whether your child has the MMR or not? Tick one box

Me Me and my partner/husband My partner/husband Someone else please say who ……………………………………. Not sure

20. What was decided?

To have the MMR To delay the MMR To have single jabs To have neither MMR nor single jabs Not sure/undecided

21. Do you think your own reasons for your choice about MMR are different to most people you know? Yes No

Not sure

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Can you tell us a bit more about this?…………………………………………………………. ………………………………………………………………………………………………………

22. What views do you think other people would have about your decision (or indecision) on the MMR? They would They would They would Don't know

approve disapprove not mind

Your GP or Surgery Your Health Visitor Partner or husband Your mother Your father Practice nurse Social workers

23. Do you feel certain you made the right decision? On a scale of 0-10, please tick the box that applies to you

No, not at all certain Yes, completely certain 0 1 2 3 4 5 6 7 8 9 10

Still undecided

24. Here are some more statements from other Brighton and Hove parents, this time about how they felt about their actual MMR decisions. How much does each of these reflect your view or experience? On a scale of 1-5, please tick the box that applies to you next to each statement.

Not my



I/We just went along and had them done, we’ve never had any problem with the idea of immunisation.

I felt very vulnerable at the time and knew I couldn’t cope if my child got measles.

I would rather have the single vaccination but cannot afford it . I’d have to be a lot more knowledgeable not to have the MMR. To be honest, I haven’t thought about it (or looked into it) too much. I’d have to be a lot more confident not to have the MMR. If my child ever got measles, I’d never forgive myself. People would think I was a bad parent if my children weren't vaccinated.

It would be so much easier if you were just told, and it wasn't your decision.

I couldn’t forgive myself if she got autism or any other side effects. We just didn’t get around to having it done. We sway one way and then the other and find it difficult to decide. At the end of the day whether you vaccinate or not is a gamble. I had them vaccinated straightaway because I heard about an epidemic of measles.

You just have to go with your own personal feelings.

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25. Do you feel you understand the issues about MMR well enough?

On a scale of 0-10, please tick the box that applies to you.

No, not well enough at all Yes, very well. 0 1 2 3 4 5 6 7 8 9 10

26. Is there anything else you would have wanted to know about the MMR vaccine to help you make a

decision? Yes

No If you answered yes, please can you tell us a bit more about this? …………………………………… ……………………………………………………………………………………………………………………………………………………………………………………

27. When deciding about MMR for your child, did you consider possible benefits to other children? Yes

No Not sure

If you answered yes, please can you tell us a bit more about this? …………………………………… ……………………………………………………………………………………………………………………………………………………………………………………

28. Is it right for health professionals to advise parents to have their child vaccinated for the benefit of other

children?

Yes No Not sure

29. Parents in Brighton and Hove said the following about trust and government - how much does each of these reflect your view? On a scale of 1-5, please tick the box that applies to you next to each statement.


1 2 3 4 5 It is the government's responsibility to decide whether children should be vaccinated.

You can't trust the government over science.

I am suspicious of the influence of the pharmaceutical companies. You’ve got to trust in the medical profession, what else is there? I tend to trust professional people and what they say. When it comes to the government telling us MMR is safe, there’s no smoke without fire.

The most important thing is that parents have the choice. I see it as a cost thing. MMR is financially led, it's in the government's interests.

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30. Do you feel tempted to buy organic food for your family?

Often Sometimes Never Don't know

31. Do you check food labels to see if they contain genetically-modified ingredients (GMOs)?

Always Sometimes Never Don't know

32. Did you stop or reduce eating beef because of BSE (Mad Cow Disease)?

Yes No I was already vegetarian

Finally could you tell us a bit more about yourself?

33. Which newspaper do you read most often?

I don’t read newspapers Sun Mirror Mail Express Telegraph Independent Guardian Times Other – please say which_____________________________________

34. Is English your first language? Yes No

If No, what is your first language _______________________

35. Apart from looking after your child, are you currently working? Full time Part time On maternity leave

Taking a break for parenting No

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36. What is your highest educational qualification?

Degree or higher degree A level / AS level / Higher School Certificate GCSE / O level NVQ levels 1-3 / GNVQ NVQ levels 4-5/ HNC / HND Other qualifications - please specify………………… No qualifications

Thank you very much for completing this questionnaire

Do you have any comments or anything else you would like to tell us?…………………………… ……………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………

Could you please return the questionnaire in the Freepost envelope provided or post it in an envelope to the following address. You will not need to pay any postage. Dr Mike Poltorak FREEPOST NAT 12538 BRIGHTON BN1 9BR

If you have any questions, please contact: Dr Mike Poltorak 01273 873392 Anthropology Department [email protected] University of Sussex Falmer, Brighton BN1 9SJ

gambiafullquestionnaire17oct03 Page 1 of 13

CHILDHOOD VACCINATION AND SOCIETY QUESTIONNAIRE Respondent number______________ Enumeration area_________________

Date of interview__________________

Study explained and verbal consent to proceed with interview given? _______________________________(fieldworker to sign and give initials)

Name of child _____________________________________ Age of child in months Name of mother/main carer ___________________________________

If not birth mother, what is relationship to child?___________________ how old (in months) was child when care started? months. I SOCIAL PROFILE 1. Appearance of compound (interviewer to note; tick which applies)

_______ 1 Wealthy (solid, well-decorated buildings; car; satellite dish; solar panels; generator…) _______ 2 Medium _______ 3 Poor (cramped, family in 1-2 rooms; mud block, incomplete or broken buildings….)

2. Mother's category of reproductive life (interviewer to note, check with mother if necessary; tick which applies)

Tick here

Mandinka Wollof Fula

1 Young woman Sunkuto Jankhaa Surkaajo/Giwo 2 Newly married with few children Foro musu dindingo Sait Jombaajo 3 Woman in middle of reproduction Foro muso Jongoma/Jeggamar Nyanyoma 4 Woman at end of reproduction Sarifo Jegg Mawdo debo 5 Old woman Musu keba Magett Nayeejo

3. How many children do you have? __________________ (Enter number) 4. What is your ethnic group?

_______ 1 Mandinka _______ 4 Serrehuli _______ 2 Fula _______ 5 Jola _______ 3 Wolof _______ 6 Other (please specify)_____________________________________________


5. Are you currently married?

_______ 1 Married – first husband _______ 4 Widowed _______ 2 Married – second (or later) husband _______ 5 Inherited widow _______ 3 Separated/divorced _______ 6 Never married

6. Who does the compound you are living in now belong to?

_______ 1 Husband’s extended family _______ 5 Rented from a landlord _______ 2 Woman's extended family _______ 6 Other (please specify) _______ 3 Husband _______ 4 Woman

7. Is there a telephone or mobile telephone in the compound?

_______ 1 Yes _______ 2 No _______ 9 Don’t know

8. Have you been to school?

_______ 1 Yes _______ 2 No If yes: How many years Western/Tubab school? ____________(Enter number) Don't know______ 999

How many years Koranic school ? __________________(Enter number) Don't know______ 999 Any further education? _________________ (level)

9. Do you yourself do any activities that earn income in money? (Please tick all that apply)

_______ 1 Farming _______ 5 Business or long-distance trade _______ 2 Vegetable gardening _______ 6 Teacher/professional _______ 3 Petty trading _______ 7 Other (please specify)_____________________________________________ _______ 4 Fish processing

If no current husband, skip to 13

10. Has your husband been to school? _______ 1 Yes _______ 2 No _______ 9 Don’t know If yes: How many years Western/Tubab school? ____________(Enter number) Don't know______ 999

How many years Koranic school ? __________________(Enter number) Don't know______ 999 Any further education? _________________ ( write in level)


11 . What is your husband's usual work? (Please tick all that apply)

_______ 1 Farmer _______ 7 Trade or craft (e.g. mason) _______ 2 Trader _______ 8 Student or apprentice _______ 3 Fisherman _______ 9 Retired _______ 4 Alkalo _______ 10 Other (please specify)____________________________________ _______ 5 Imam/Marabout _______ 11 Don't know _______ 6 Teacher/professional

12. Does your husband travel away to work?

_______ 1 Yes If yes, please say where__________________________________________ _______ 2 No

II CHILD HEALTH BIOGRAPHY Now we would like to ask you some questions about the health of your child 13. How has the child’s health been since it was born? Have you had any particular worries or problems? Please explain (narrative - write

down in mother's exact words) 14. When the child was born, was it taken out of the house before its naming ceremony?

_______ 1 Yes If yes, where was it taken? ______________________________________________(skip to 16) _______ 2 No _______ 9 Don't know


15. Why was the child kept in? (please tick all that apply) _______ 1 Because it is custom not to go out before naming ceremony _______ 4 Fear of djinn _______ 2 Because elders said to stay in _______ 5 Because there was no need to go out _______ 3 Fear of witches or bad people _______ 6 Other (please specify)_________________ ____________________________________________ 16. Has your child ever been taken to the Infant Welfare Clinic (IWC - nurse)?

_______ 1 Yes (skip to 18) _______ 2 No _______ 9 Don't know

17. What has prevented the child from ever being taken to the IWC? (narrative - write down in mother's exact words. Then skip to 42)


III EXPECTATIONS OF IMMUNISATION 18. What do you think the injections given to children at the IWC are for? (narrative - write down in mother's exact words. Probe: how might

they strengthen or protect child, what sort of health do they bring) 19. What diseases do you think injections at the IWC can protect your child against? (list disease named by mother; prompt 'and what else'?)


IV IWC/IMMUNISATION BIOGRAPHY 20. How old was the child when he/she first went to the IWC? ____________ (enter age in weeks) 21. Which clinic was this? _______________________________________ (enter name or place of clinic) 22. What happened at this first visit? (please tick all that apply) _______ 1 Registration/change cards _______ 5 Visiting MRC

_______ 2 Weighing _______ 6 Child seen/treated for illness _______ 3 Injections _______ 7 Other (please specify)______________________________________ _______ 4 Knew myself/always known If cards not changed, ask 23, otherwise skip to 24

23. How old was the child when its cards were changed? (enter age in weeks) 24. Where did you get the idea to take the child to the IWC? (please tick all that apply)

_______ 1 Knew importance from earlier children _______ 6 Mother in law _______ 2 Other mothers _______ 7 Health centre staff at delivery _______ 3 Own mother _______ 8 TBA or VHW _______ 4 Husband _______ 9 Don’t know _______ 5 I knew myself/always known _______ 10 MRC worker

_______ 11 Other (please specify)_______________________________ 25. Do you feel your child had the first injections at a good time?

_______ 1 Yes _______ 2 No _______ 9 Don't know Can you say a bit more? (narrative - write down in mother's exact words)

26 A Did the child first go to the IWC at the usual time? _______ 1 Yes (skip to 27) _______ 2 No (go to 26B) _______ 9 Don't know


26 B Can you tell us why? (please tick all that apply)

_______ 1 I had to travel _______ 7 Childcare/ problems with older children _______ 2 I was unwell _______ 8 Public holiday _______ 3 Child was unwell _______ 9 Too much work _______ 4 Financial problems _______ 10 Problems with IWC (please specify)__________________________ _______ 5 Distance/transport problems _______ 11 Other (please specify)_____________________________________ _______ 6 Family event (e.g. bereavement, ceremony) _______ 12 Went at usual time

27. On this first visit, how was your interaction with clinic staff?

_______ 1 They were friendly/respectful _______ 4 They were rude _______ 2 They embarrassed me _______ 5 Some were not there _______ 3 They were helpful _______ 6 Other (please specify) ____________________________________________

Can you say a bit more? (narrative - write down in mother's exact words)

28. Did the baby have its '3 month injections'? _______ 1 Yes skip to 30 _______ 2 No If child did not receive any of the 3 month injections, ask 29, then skip to 34 _______ 9 Don’t know skip to 30

29. Why didn't your child receive any of the 3 month injections? (narrative - write down in mother's exact words) 30. Which clinic was this? ________________________________ (enter name or place of clinic)


31. Did your child have any reaction to the injections? (please tick all that apply)

_______ 0 No reaction/effect _______ 5 Mild crying _______ 1 Mild fever _______ 6 Serious crying _______ 2 Serious fever _______ 7 Another effect (please specify)____________________________________________ _______ 3 Mild swelling _______ 8 A delayed effect (please specify)___________________________________________

_______ 4 Serious swelling 32. Do you feel these reactions were normal?

_______ 1 Yes _______ 2 No _______ 9 Don’t know

If no, please say a bit more (probe - anything particular about child that affected its reactions or non-reactions?) 33. Do you feel your baby was given the right number of injections each time?

_______ 1 Yes _______ 2 No _______ 9 Don’t know Can you say a bit more? (narrative - write down in mother's exact words)

34. Was it easy or difficult for the child to attend the clinic around the time of the 3 month injections? _______ 1 Easy (skip to 36) _______ 2 Difficult _______ 9 Don’t know


35. If it was difficult, why was that? (please tick all that apply) _______ 1 I had to travel _______ 7 Childcare/ problems with older children _______ 2 I was unwell _______ 8 Public holiday _______ 3 Child was unwell _______ 9 Too much work _______ 4 Financial problems _______ 10 Problems with IWC (please specify)__________________________ _______ 5 Distance/transport problems _______ 11 Other (please specify)_____________________________________ _______ 6 Family event (e.g. bereavement, ceremony)

36. Did the child miss any clinic sessions around this time?

_______ 1 Yes _______ 2 No (skip to 38) _______ 9 Don’t know

37. If the child missed sessions, did this worry you? why? _______ 1 Not worried _______ 3 Worry about multiple injections

_______ 2 Worry about reactions of staff _______ 4 Other (please specify)____________________________________________ Can you say a bit more? (narrative - write down in mother's exact words)

38. Has your child had the 9 month injections?

_______ 1 Yes At which clinic?____________________________________________ _______ 2 No _______ 9 Don’t know

39. Has your child had the 1 year injections? _______ 1 Yes At which clinic?____________________________________________ _______ 2 No _______ 9 Don’t know

If answer to 38 or 39 is no, ask: 40. Why did your child not have these injections? (narrative - write down in mother's exact words)


V EXPERIENCES AND PERCEPTIONS OF DIFFERENT HEALTH PROVIDERS 41. What do you see as the main benefits of attending the Infant Welfare Clinic? (narrative - write down in mother's exact words) 42. What are the main problems with the IWC? How do you cope with these? (narrative - write down in mother's exact words. Then probe

each of possible answers: tick all those that apply, and add explanations to narrative) _______ 0 No problems _______ 1 Travel problems _______ 5 Disrespectful staff _______ 2 Effects of sun/rain in travel _______ 6 Financial problems _______ 3 Crowds, long waits _______ 7 Links with family planning _______ 4 Bad people or witches _______ 8 Discouragement from husband or family 43. How might these problems be improved? (narrative - write down in mother's exact words) 44. Who else has given protection or treatment to this child? (please tick all that apply)

_______ 0 No one _______ 4 Elderly women or men _______ 1 Herbalist _______ 5 Family doctor/private clinic _______ 2 MRC _______ 6 Other (please specify)___________________________________________________ _______ 3 Marabout _______ 9 Don't know


45. Please could you describe any health protection given to your child by herbalists or other women or men? (narrative - write down in mother's exact words)

46. Is your child wearing a talisman (juju) today?

_______ 1 Yes _______ 2 No

47. Do you like the child to wear a talisman (juju) to visit the IWC?

_______ 1 Yes _______ 2 No Can you say a bit more? (narrative - write down in mother's exact words)

48. Has this child been asked to participate in an MRC study?

_______ 1 Yes _______ 2 No (skip to 53) _______ 9 Don’t know (skip to 53)

49. Did he or she join?

_______ 1 Yes _______ 2 No

50. Who made the decision? _______ 1 Myself _______ 4 Compound head _______ 2 Husband _______ 5 Other (please specify)___________________________________________________ _______ 3 Joint - husband & wife

51. Please explain how the decision was made and who was involved or had influence (narrative - write down in mother's exact words)


52. What do you think the MRC study that your child was invited to join is about? (narrative - write down in mother's exact words) 53. Have you heard any negative ideas or bad things about having a child registered with MRC?

_______ 1 Yes _______ 2 No (skip to 55)

________ 9 Don't know

If yes, what were these? (narrative - write down in mother's exact words) 54. Where did you hear these ideas? (please tick all that apply)

_______ 1 Husband _______ 5 Relatives abroad _______ 2 Compound head _______ 6 Radio/TV _______ 3 Neighbours _______ 7 Newspapers _______ 4 Relatives elsewhere in the Gambia _______ 9 Don't know _______ 10 Other (please specify)_______________________________

55. What benefits do you think there are in having a child registered with MRC? (narrative - write down in mother's exact words)


56. Finally, could we please see this child's health card? _______ 1 Health card available _______ 2 Health card lost

_______ 3 Has never had a card _______ 4 not willing to show health card

Copy details from front of card onto attached sheet Note from back of card:

57. Number of visits for weighing recorded since birth (Count number of dots) 58. Child's weight at 1 year (if no record for 1 year, note nearest and age of child at this weighing)

. kilograms

at months old

ECONOMIC AND SOCIAL RESEARCH COUNCIL POLARIS HOUSE

NORTH STAR AVENUE SWINDON SN2 1UJ

Tel: 01793 413000 Fax: 01793 413001

GTN 1434

REFERENCE NUMBER L14430100102

TITLE Childhood Vaccination: Science and public engagement in international

perspective

INVESTIGATORS Professor James Fairhead and Professor Melissa Leach

INSTITUTION Department of Anthropology, University of Sussex and Institute of Development Studies,

University of Sussex

This is the ESRC End of Award Report Form. The form should be completed and returned to: The Evaluation Reports Officer, Communications & Information Directorate at the ESRC on or before the due date. Please note that the Report can only be accepted if all sections have been completed in full, and all award-holders have signed declaration one. Award holders should also submit seven additional copies of this Form, and eight copies of the research report and any nominated outputs to be evaluated along with the Report. A copy of the complete Report, comprising this form and the research report, should be formatted as a single document and sent as an email attachment to [email protected]. Please enter the Award Reference Number as the email subject.

CHILDHOOD VACCINATION: PUBLIC ENGAGEMENT WITH SCIENCE AND

DELIVERY

RESEARCH REPORT

James Fairhead and Melissa Leach

1. Background Across the globe, childhood vaccination is widely regarded to epitomise the effective (and cost-effective) application of science and technology to current public health problems. It is central to future hopes in tackling diseases both of poverty and of excess. The production and delivery of new vaccines, combinations and applications has become a major focus of research and funding within a highly globalised field. Multi-national pharmaceutical companies, NGOs, research institutes, foundations and global health organisations now interact with wealthy and poor governments in initiatives and new forms of partnership which are extending vaccines to every person on the planet, and moulding health services in the process. Recent, high-profile controversies nevertheless point to public anxieties around the application of vaccine technologies. In the UK, parental concerns over possible adverse effects of the measles, mumps and rubella vaccine (MMR) since the early 1990s have built into a movement interplaying with scientific and media debate, and MMR uptake levels have, in some localities, fallen by 30%. In Northern Nigeria in 2003-4, parents and their communities refused the Oral Polio Vaccine, associating it variously with HIV transmission, infertility and international and national genocidal politics. The global polio eradication programme stalled, and polio reappeared throughout West Africa. Whether in Europe or Africa, such controversies - at the broadest level - can be understood as emerging where the rapidly advancing, globalised health technology and technocracy involved with vaccines and their delivery encounters the deeply intimate personal, cultural and social worlds of parenting and childcare. It is perhaps inevitable that childhood vaccination has become a key issue around which debates over public engagement and trust in science and technology proliferate. As these debates have unfolded in social science literature, public health discourse and popular commentary, recurring themes and contrasts have emerged which link vaccine-specific anxieties to broader dimensions of society, and science-society relations. First, a strong contrast is drawn between 'North' and 'South': the idea being that a concern with vaccine side effects is a luxury of those in the north no longer familiar with the childhood diseases ravaging the south, where the more important clamour is for vaccine access (Obaro and Palmer 2003, Streefland 2001). This evokes a broader contrast between late-industrialised 'risk society' (Beck 1992) and a still-to-modernise 'underdeveloped society'. Second, and relatedly, a contrast is drawn between the anxious middle classes, as against a more compliant poor (e.g. Pareek and Pattinson 2000). A third contrast turns on irrationality vs. rationality, associating vaccine anxieties in the south with incomplete (rising) scientific rationality in settings where 'traditional' beliefs still predominate and in the north, with a 'rise of irrationality' in society, as evidenced for instance in the increasing popularity of alternative medicine (e.g. Fitzpatrick 2004). Other debates turn on the role of knowledge and information. Fourth, then, low vaccine uptake is linked to public ignorance, or deficit in scientific understanding, of the value of vaccination or evidence of vaccine safety (e.g. Elliman and Bedford 2001), and to misinformation and rumour spread by irresponsible media and pressure groups (Andre 2003, Hargreaves et al 2002, UNICEF 2003). Fifth, and relatedly, reason (driving evidence-based decisions or governance) is contrasted with emotion (as driving some parents' personal choices). Finally, vaccine anxieties in the north are being cast as part of a generalised breakdown of trust in public institutions (Fitzpatrick 2004, Hobson-West 2003), evidence of

growing critical public engagement with scientific expertise (Irwin and Wynne 1996). In contrast, southern analytical traditions stressing the non- or incomplete integration of expert science with 'indigenous knowledge' and beliefs tend to attribute vaccine anxieties to collective resistance based on religion or traditional beliefs (Streefland 1999). These contrasts and stereotypes - which often pass for ‘explanation’ of vaccine refusal - can be seen, in part, as rooted in scientific and public health frustrations with non-compliant publics, and research framed by these. They are also rooted in long-established differences between the analytical traditions that reflect on science-society relations in European and African settings, respectively. Our research set out to consider these terms of debate from a different perspective, rooted in ethnographic and anthropological understanding of how parents are thinking and deciding about vaccination, amidst diverse personal experiences, cultural knowledges and perspectives, social relations, and experiences of national and international institutions. It explored how parents in localities in Britain and West Africa are engaging not just with routine vaccination, but with issues involving vaccine science and scientific controversy.

2. Objectives The overall objective of the research was to develop comparative insights into science-society relations in European and African settings which have conventionally been theorised very differently, through the case of childhood vaccination research and regimes. This objective has been addressed in a preliminary way through drawing key comparative themes and insights from the country-specific analyses, as reported in section 4.3. This comparative work, which is necessarily at a broad level given the stark differences of context between Britain and West Africa, will continue in post-award analysis in engagement with wider literatures and be presented in full in the proposed book output from the research. To do so, it focused on the intersection of routine vaccination with the MMR controversy in the UK and with MRC-orchestrated vaccine research in The Gambia, aiming in each context to:

• Identify how public concerns with vaccination research/regimes are socially differentiated and shaped by diverse conceptual frameworks and knowledges around infection, disease and immunity, and experiences of the state and of science in other domains. This was addressed and met fully through ethnographic and survey research with parents in Brighton, UK and The Gambia, reported in sections 4.1 and 4.2 respectively;

• Specify how different people consider trade-offs between social and individual benefits and risks, the differentiated notions of ‘community’ and ‘communities of trust’ implied, and how this influences socio-political organisation around vaccination. Again, this was successfully met through ethnographic and survey research with parents in Brighton, UK and The Gambia, reported in sections 4.1 and 4.2 respectively, as well as through a focused case study of the parental movement around MMR.

• Identify how vaccine scientists and public health professionals conceive of public knowledge and attitudes towards vaccination programmes, and how 'frontline’ staff mediate professional and public views. This was addressed and met successfully through interviews with scientists, public health professionals, and fieldworkers nationally and locally, reported for the UK in section 4.1 and for The Gambia in section 4.2. International public health and scientific discourses (summarised in Background above, and to be documented more fully in forthcoming book) were gauged through participation in several conferences and networks, e-mail discussion and literature study.

Further, the research aimed to support the development of new approaches to public involvement in research into vaccine technologies targeted at children, their delivery and promotion. This objective was addressed through (a) working collaboratively with local and national governmental and research organisations (detailed in Activities and Achievements Questionnaire 2B), with whom intensive discussions were held throughout the research; (b) feedback workshops to a wider set of users in each country, and (c) proactive seeking-out of new citizen-participatory approaches and 'experiments' in each country context. In both settings, these interactions have led successfully to some minor shifts of approach and communication strategy by established institutions, as indicated in section 7. However, as embracing new participatory approaches involves challenges to powerful public health and bioethical discourses, encouraging these is a long-term

challenge which will necessarily extend beyond the project's timeframe. In this context, innovative experiments that we might interact with have proved rare. An exception in the UK context is the New Economics Foundation's 'DEMOCS' gaming approach which has developed an MMR pack, and where we made advisory inputs based on our research.

3. Methods Our research approach was characterised by its meta-level comparative framework, its collaborative context, and its combination of qualitative and quantitative methods. The Gambia and southern England were chosen not with any claim to be fully representative of African and British conditions, but as places where pressing controversies around public engagement with vaccine science are ongoing, allowing the generation of context-specific insights which could then be drawn together in broader comparative discussion. The Gambia has been the locus of British Medical Research Council (MRC)-orchestrated medical research and vaccine trials for the past fifty years, with research stations throughout the country engaging a large proportion of the population as actual or potential 'study subjects', alongside the administration of routine vaccination through the country's relatively strong primary health care infrastructure. The research focused on rural Upper River Division (URD), the site of the joint MRC-Gambia Government Pneumococcal Vaccine Trial, and on urban Western Division, where some parents had engaged with the MRC Sukuta Birth Cohort study researching infant immunity and responses to infection. These two sites also enabled a comparison of rural and urban settings, an important distinction in rapidly-urbanising West Africa. The research was developed in collaboration with local and national staff of MRC and the Gambian Government Expanded Programme on Immunisation, through preliminary discussions, a methodology meeting and preliminary feedback workshops. Approvals were obtained from the MRC Scientific Co-ordinating Committee and the joint Gambian Government-MRC Ethics Committee. In the UK, the research focused on the city of Brighton and Hove, chosen for its locality to the researchers and its particularly sharp decline in MMR coverage. Collaborative partnerships were developed with the Brighton and Hove Primary Care Trust and a Stakeholder Advisory panel comprised of key national policy-making, health professional and parents' organisations (see Activities and Achievements Questionnaire section 2B) who participated in preliminary discussions, a methodology meeting and preliminary feedback workshop. The study was approved by the East Sussex, Brighton and Hove Local Research Ethics Committee and appropriate research permissions given by South Downs NHS Trust and Brighton and Hove City PCT. In each country, a first phase of in-depth qualitative research was conducted using ethnographic methods. In The Gambia, this took place during March - November 2003, with ML and JF spending 3 months and Gambian Research Officer Mary Small completing the work. Ethnography focused on the peri-urban settlement of Sukuta, rapidly-growing from an old Mandinka settlement, and on the rural Mandinka village of Tambasansang in Upper River Division (URD). In the UK, ethnographic research took place during February - October 2003, conducted primarily by Research Officer Mike Poltorak but with major inputs also from ML, and focused on the catchment areas of two collaborating GP practices: Whitehawk, a stereotypically 'deprived' area, and Fiveways/Preston Park, a stereotypically 'middle class' area - thus illustrating contrasts which have been significant in popular debate over MMR. Ethnographic methods included participant observation in social settings where parents take infants (Gambian compounds, clinics and markets; 5 Brighton carer and toddler groups), recorded focus group discussions (9 in The Gambia, 4 in Brighton), observation of clinic interactions and interviews with frontline health professionals (12 nurses and 18 MRC fieldworkers in The Gambia, 8 GPs, 3 practice nurses and 6 Health Visitors in Brighton), and narrative interviews with mothers identified through participant observation (100 in The Gambia, 23 in Brighton). Initial interviews in both settings suggested the value of an open-ended biographical format to allow mothers to speak openly about the processes and issues surrounding their decision-making, so narratives took the form of 'child health and immunisation biographies'. These were tape recorded and fully transcribed in Brighton, and noted by hand and later fully typed up in the

Gambia where recording is socially sensitive, and analysed by drawing out key narrative themes. All have been stored confidentially. In the second, quantitative phase, a survey questionnaire was developed for each country to explore the significance of the key narrative themes amongst wider populations, and in relation to social variables (see Annexes 1 and 3). Survey design and methods were adapted to the particular issues and logistical possibilities in each country context. In the UK, the sampling frame consisted of all children aged 15-24 months listed on the Child Health Dataset held by South Downs Community NHS Trust as resident in the catchment of Brighton and Hove City PCT, on the date of record extraction in early March 2004. Children were categorised into those who had and had not had an MMR immunisation recorded, and of the 1800 children eligible, a sample of 1000 MMR uptakers and non-uptakers in a ratio of 1:1 was randomly drawn, using the statistical programme STATA 8. All the 135 registered children who had had no vaccination events recorded were also identified. A postal questionnaire addressed to the mother or guardian of each child was sent in March 2004. This contained a questionnaire for the mother, and also one to be passed where possible to the father of the child. A follow-up letter with a second questionnaire was sent after 3-4 weeks to non-responders. The questionnaire explored rank of child within the family, sources of information on parenting and immunisations; early health of the child (including its birth); views on the risks associated with measles and the MMR; interactions with health care professionals and others in relation to MMR; the process of decision making, including attitudes to public bodies and governments as sources of advice and influence. In addition, a range of specific statements made by Brighton parents as part of the ethnographic phase were offered for agreement or disagreement. Completed questionnaires were linked with children’s data as recorded on the child health database, from which additional information was derived relating to: gestational age, birth rank, prematurity, age of mother at child’s birth, and immunisations given within the NHS. Apart from mailing lists, all person-identifiable data was handled only on secure NHS servers with appropriate permissions. 452 of 1135 mothers’ questionnaires were returned, representing an overall response rate of 39.8% (Annex 2 table 1), as well as 257 Fathers' questionnaires. Data were entered by the firm Abacus, and analysed using STATA software, especially to explore differences between mothers who complied (reported choosing to have MMR on time) and who did not comply (choosing to delay MMR, not to vaccinate with MMR, to obtain single jabs, or who remained undecided). Analysis of Fathers' data and paired Mother-Father responses to draw out gender differences and negotiations is yet to be carried out. In The Gambia, we drew half of the respondents from three rural districts of URD (Fulladu, Wuli West and Sandu) which were covered by the MRC Pneumococcal Vaccine trial and had received MRC-related support to immunisation infrastructure, and half from the two more urbanised districts of Western Division (WD) (Kombo St. Mary and Kombo North) which have been the foci of rapid immigration. All children aged 12-24 months resident in these Divisions at the time of survey (October - December for WD, January - March 2004 for URD) were eligible. We used a two-stage stratified sampling process to select 800 respondents in URD and 800 in WD. Enumeration areas used for the 1993 Census were identified within the chosen districts, separately within URD and WD. 35 enumeration areas in each Division were then randomly selected using a random number list. The sampling method within enumeration areas was based on a random walk method well established in immunisation coverage surveys. A team of five fieldworkers employed through MRC and supervised by Mary Small aimed to interview the mothers of a target number of children identified by random walk. The questionnaire explored mother's immunisation understandings and practices as part of broader notions of protecting child health, the process and timing of immunisation decisions, and perspectives on engagement with MRC studies. Fieldworkers also copied data from the child's health record card when available. The response rate was near 100% (only 3 mothers refused to be interviewed). The completed paper questionnaires were returned to a central MRC office where coded survey data were double entered into a database by clerical staff, and free-text data entered once. Quantitative data were stratified into responses from the urban west and the rural east, and analysed using STATA software. Free text was coded by ML and JF where appropriate.

4. Results The research has generated an enormous wealth of ethnographic and quantitative data and analysis has generated findings which speak to a range of debates concerning vaccination, medical research ethics and science-society relations. These are being written up in full in outputs targeted to a range of audiences (see section 6). Statistical tables are included in Annexes 2 and 4. This section gives only a brief summary of some of the most significant findings, first for Brighton, then for The Gambia, and then comparatively. 4.1 Findings - Brighton In the UK, research and policy discussions focussing on parents' engagement with MMR has been dominated by analysis of the proximate influences on their choices, and in particular scientific and media information. This has led health policy to focus on information and education campaigns. Most health professionals also reiterate the policy stereotype that MMR-anxiety is primarily a middle-class phenomenon. Nevertheless as our interviews also revealed, local health professionals frequently face two dilemmas: between their felt institutional obligations to deliver information that MMR is safe and their own uncertainties, and between advice to vaccinate for the social good of herd immunity and encouragement to personal choice - leading to a wide variety of interactions in practice. The Brighton ethnography questions such reasoning in showing how wider personal and social issues shape parents' immunisation actions. It indicates anxiety about MMR amongst mothers from a wide variety of social backgrounds; what some mothers from 'deprived' Whitehawk lack is rather the confidence to go against professional expectations. The narratives by mothers reveal rationalities rooted in a particular child's health, behaviour and genetic history, not in generic ideas of risk. This contrast is encapsulated in the statement 'MMR may be safe but not for my child'. Vaccination outcomes depend not on a singular deliberative calculus which information might influence, but on unfolding personal and social circumstances into which information plays. Personal histories, birth experiences and related feelings of control, particular engagements with health services, and friendships and conversations with others are all relevant here. Whilst many see vaccination as a personal decision which must respond to the particularities of a child's immune system, 'MMR talk', in which these concepts are discussed and which articulates parenting values and ideas of responsibility, has become a social phenomenon in itself now integral to wider socialising. Within this, there is high social acceptance of those who decide differently, and high tolerance of personal choice in negotiating scientific uncertainties and pro- and anti-MMR advice. People assume personal responsibility and blame (for the consequences of both vaccination and non-vaccination). The survey results (to data analysed only for mothers) confirm that class is relatively unimportant. Neither graduate status, nor newspaper readership (as proxies for class) were significantly associated with the decision whether to have MMR at the recommended time (Annex 2 table 5). The 13.3% of mothers who reported that they had chosen “single jabs” (i.e. separate measles, mumps and rubella antigens, available only privately or overseas) were more likely to be graduates, however (P=0.043), (Annex 2 table 6). The survey confirmed ways in which personalised ideas of immunity and vulnerability shape thinking about MMR (Annex 2 table 14). Most mothers agreed that each child's immune system was different (although significantly more non-compliant mothers - 79% - strongly agreed with this, compared with 61% of those who complied). What is different, however, is how mothers evaluate how MMR plays into this, with 86% of mothers who did not comply strongly agreeing that 'the MMR is too much in one go' compared with only 21% of those who complied. Equally, more than half of the non-compliers agreed that there is a chance of serious side effects from MMR if there is a weakness in that child, compared to only 18% of those who complied. 46% of mothers who did not comply strongly agreed that it was better to get immunity naturally, compared with only 5% of those who complied. Interactions with 'alternative' therapists were also significant: 21.1% of noncompliant mothers had consulted a homeopath, by contrast with 9.4% of compliers (P=0.001). Those who did not comply are significantly more likely to have had their thinking influenced by family health history. In explaining more about this, seven mentioned a family history of asperger's syndrome; two mentioned autism in the family; three mentioned experiences

of autism onset following MMR in the family; thirteen referred to relatives reacting badly to vaccines; ten referred to a family history of eczema, asthma or arthritis; five referred to a family history of irritable bowels, and several gave examples referring to neurological problems, auto-immune problems or ME. Of the 15% of mothers who rejected the Vitamin K injection at birth, almost 80% went on not to comply with the MMR regime. Overall, the survey found the strong significance of a cluster of variables linking ideas about immune system susceptibility and family health history, early thinking about MMR, and personal responsibility, associated with MMR non-compliance (Annex 2 table 19). The survey confirmed mothers' strong sense of personal responsibility for vaccination decisions and their consequences amongst both those who did and did not comply with the MMR regime, although unsurprisingly those who complied expressed their personal responsibility more in worry about measles that about possible MMR side-effects (Annex 2 table 15). Importantly, few mothers (11-12%) agreed that they considered possible benefits to other children in their calculus about MMR. It does not appear to be the case, therefore, that the social good from 'herd immunity' is important in mother's choices. Rather than take this to indicate 'contemporary selfishness', this - taken with the high sense of personal responsibility evident in mother's responses - suggests that the MMR issue has become so important that personal parenting concerns are paramount, leaving less space for wider social considerations. Nevertheless a much higher proportion (70% of those who complied, and 33% of those who did not) felt that it was right for health professionals to push the social message. Wider issues of trust in government and science are nevertheless significant to mothers' MMR thinking and practice (Annex 2 table 16). 74% of those who did not comply, but even 31% of those who did, strongly agreed that 'you can't trust the government over science'. Even higher proportions of mothers strongly expressed suspicion of the influence of pharmaceutical companies over the MMR issue (52% of those who complied, and 81% of those who did not). The survey extended this consideration of how mothers relate to public issues involving science by exploring attitudes and practices around BSE and genetically-modified foods. A significantly higher proportion of those who did not comply with MMR claimed to have stopped eating beef because of BSE (41%, compared with 35% of those who did comply) - and this proportion might have been higher still but for the fact that 37% of non-compliers were vegetarian already (compared with only 17% of those who did comply). 86% of those who did not comply with MMR, and 56% of those who did, claimed that they checked food labels to see if they contain GMOs - again, a statistically significant difference. These findings suggest that while many mothers across the vaccination spectrum may be taking a precautionary approach around these other issues of scientific uncertainty, there is a cluster of those who do not comply with MMR whose views of food and vaccination issues may be similar, and mutually-reinforcing. Further statistical analysis will probe this. While our UK study focuses on a single locality which has particularly low rates of MMR uptake, and in offering an “alternative” lifestyle may not be representative of the UK as a whole, there is no reason to think that the social factors causing low uptake in Brighton are different in kind from those operating elsewhere, even if their distribution is different. A response rate of 39.8%, though lower than desirable, is slightly higher than average for postal surveys of the public. The potential biases of self-selecting postal respondents have been assessed and controlled for. Overall, then, these findings can be taken to suggest the importance of public discourses about individual responsibility and lay perspectives on immunity for shaping parental anxiety about the MMR regime in the UK. They suggest the contemporary significance in the UK context of what has been identified by anthropologists as an 'age of immunity' (Martin 1994, Napier 2003). The findings suggest that health professionals and immunisation policy-makers will need to develop forms of discourse and dialogue that acknowledge these perspectives if they are to engage effectively with parents. That parental perspectives correspond with certain strands in the high-profile scientific and activist debate over MMR also carries with implications for how the controversy is playing out.

4.2 Findings - The Gambia As in the UK, our ethnographic work in The Gambia revealed a range of contrasts between the perspectives of health institutions and of parents. Findings concerning conceptualisations and experiences of child health and routine vaccination are important for understanding parents' engagement with vaccine trials, and hence are initially outlined here. Concerning routine vaccination, our interviews with immunisation policy-makers and community nurses revealed a powerful discourse associating vaccination acceptance with the acquisition of modern scientific and biomedical knowledge, and a prioritising of modern health care. Professionals see the (relatively few) 'defaulters' in this high-uptake setting as neglectful, either through ignorance or by prioritising travel or trade over health. The Gambian ethnography found, in contrast, that parents view immunisation as one of a set of complementary practices for promoting infant strength and health, including the use of a variety of Islamic talismen, herbal medicines, daily care practices and adherence to moral codes. Individual infants are seen to have unique pathways through the diverse physical, social and spiritual hazards that can afflict them. Core ideas concerning strength and wellbeing centre on an economy of blood and body fluids, which vaccinations can influence positively. These conceptualisations underpin a widespread desire for vaccinations. In this context, occasions of 'default' or lateness usually arise through contingent events that could affect anyone, such as family misfortune, temporary work overload or practical difficulties in getting to the clinic. There, default is sometimes compounded as conflicts with clinic staff and worries about multiple vaccines 'stacking up' deter future attendance. The ethnography also revealed how vaccination uptake is not just a matter of individual dispositions, but shaped by social processes. Thus Infant Welfare Clinic days are enjoyable social occasions for some women, encouraging attendance, while others feel excluded or worried by them due to their social circumstances, the health of their child and the judgement of others about these. Women also negotiate clinic attendance with husbands and older female relatives in ways shaped by age and household circumstances. The parts of the survey dealing with routine immunisation confirmed and extended many of the ethnographic findings. For instance, for 47% in the urban west and 59% in the rural east, immunisations were seen to play a general role in giving a child 'strength' or 'power'. When asked about their expectations of protection by immunization in relation to disease, 29% of mothers in the urban west, and 48% in the rural east, reported no “correct” diseases, while many of those reporting “correct” disease also mentioned others (e.g. malaria and diarrhoea), suggesting a generalised conceptual link between immunisation and common childhood illness (Annex 2 table 8). Mothers with higher western educational status named more diseases (Annex 4 table 9), regardless of whether they are correct; suggesting that education is associated with a more disease specific perspective but also with an increase in knowledge that from a biomedical point of view is inaccurate. Findings confirmed that traditional practices are used in the interpretation and encountering of immunization practices, and are not an alternative to or opposite of such encounters. For example at interview, 57% of children in the urban west and 51 % in the rural east were wearing an Islamic talisman; this did not vary significantly according to education (Annex 4 table 12). Very few social factors are significantly associated with default in the rural east (not ethnicity, not number of children, not age, not occupation and not wealth). In contrast, a cluster of poverty related factors emerge as significantly associated with general defaulting in the urban west (poor compound, rented compound, no mobile phone, non-Mandinka - indicating higher likelihood of being a recent immigrant) (Annex 4 table 3). Survey findings suggest that the routinized and social role of the Infant Welfare Clinic is important in supporting uptake in the rural areas, but that this is lacking in the more socially-fragmented urban context where negative experiences of interaction with other women and with clinic staff are also more common for poorer, less socially-integrated mothers. Our detailed analysis of the relationships between defaulting on different immunisations suggests, inter alia, that default on the first (BCG) vaccination is more likely to signal a repeated default pattern for urban mothers than it is for rural ones (Annex 4 table 7).

Turning to engagement with MRC studies, our interviews revealed discourses amongst trial administrators and fieldworkers that echo public health discourses around routine vaccination. Thus MRC workers assume people to perceive MRC studies as a distinct, scientific activity, and those who accept to participate are assumed to have understood study aims and procedures and to have given their 'informed consent' according to bioethical protocol. Acceptance (or not) is assumed to reflect people's relative trust in MRC and appreciation of science and modernity - with 'refusers' understood as people of particular social or ethnic categories; ignorant; irrational, over-traditional, or susceptible to ill-founded rumour. In contrast, our ethnographic work on people's engagement with the Pneumococcal Vaccine Trial (PVT) revealed that people treat medical studies less as a separate scientific entity and more as part of normal health practices. In this context registering with MRC had become a further complementary way to secure infant health, along with visits to government infant welfare clinics, herbal and Islamic healers. Parents had very little understanding of the nature and aims of this particular trial, and attached little significance to the informed consent process; rather, their reflections about participation were framed within broader perceptions and historical experiences of MRC as an institution. Acceptance (or not) reflected a calculus of benefits vs. danger, which were negotiated through social processes, gender and power relations in various ways, to produce a diversity of outcomes. Benefits and dangers are conceptualised in relation to prevailing ideas about an economy of blood. Thus engaging with MRC is seen to involve balancing its 'good treatment', involving strength-giving, blood-enhancing vaccines and medicines which people perceive as coming free to study subjects, with its 'stealing' of blood. In many cases, people interpret blood sampling and laboratory practices as evidence of MRC's wish to accumulate blood, presumably for sale in Europe where it is felt that 'strong' African blood is desired. This blood is not paid for, unlike commercialised blood in Gambian hospitals, enhancing the sense of an unjust economy. The part of the survey addressing relationships with MRC confirms many of these findings. The rural East survey population were all potential PVT study subjects. 464 had been invited to participate, and of these 15.3% refused. Refusal was not significantly associated with any social, ethnic or educational variables (Annex 4 table 10). Of those who were invited, 45% had no idea what the study was about; 30% said it was for improved child health; 18% said that it concerned free checking and treatment for their children, and only 6% mentioned pneumonia or the term 'pneumococcal vaccine trial' (Annex 4 table 15). Trial participants and refusers alike named both positive and negative aspects of engaging with MRC, hinging, as in the ethnography, on good/free treatment vs. blood-taking (Annex 4 table 13). This research shows that trial communication processes and debates around informed consent need to move beyond just the moment of decision, and consider the wider social context, including the prevailing discourses through which people frame their engagements with scientific institutions. Taken along with the findings concerning routine vaccination, the Gambian data show that the categories of vaccination 'complier' and 'defaulter' and trial 'acceptor' and 'refuser' obscure the range of experiences, concerns and dilemmas faced by parents as they seek to raise their infants and keep them healthy. 4.3 Comparative perspectives In both British and Gambian settings, then, the research has shown how parents think about and discuss vaccination issues as part of wider reasoning concerning child wellbeing, which interplays with intense parental observation and evaluation of a child’s particular health history, strength and vulnerability. Public engagement with (globalised) vaccine technologies is strongly mediated through this, rather than being more straightforwardly a matter of generalised risk perceptions or political imagination of, and trust in/distrust of, state, scientific, corporate and global institutions. Similarities across the Gambian and British settings in these respects, and in the integration of vaccine engagements with a variety of biomedical and non-biomedical forms of knowledge and practice, undermine dichotomies which cast Southern societies as becoming biomedicalised, post-traditional, and rational/modern, and Northern societies as becoming de-medicalised, post-modern and more irrational.

In both settings, debates and controversies about vaccine science appear to be playing into current conceptualisations of health and social relations - an 'age of personalised immunity' in Britain, and what we would dub an 'age of blood' in West Africa - in ways which feed, and may lay the ground for further, controversy. The research suggests that science-policy approaches, even those seeking participation, deliberation and dialogue, need to appreciate such dynamics or they can badly misfire.

5. Activities Phase I: Preparation (October 2002 - February 2003) Literature research Consultations with users Creation of collaborative arrangements and UK Stakeholder Advisory Panel Creation of project web pages Phase II: Ethnography (February - November 2003) Ethnographic research in Brighton and urban and rural Gambia Recruitment and capacity-building of British and Gambian research Officers Preparation and publication of two ethnographic working papers 2 feedback workshops/survey methodology meetings (held in Brighton and at MRC, The Gambia) Feedback/training meeting for Health Visitors in Brighton Presentation to GP learning group, Brighton and Hove City PCT Phase III: Survey (November 2003 - August 2004) Design and conduct of postal survey in Brighton Recruitment and training of MRC fieldworker team Design and conduct of interviewer-administered survey in The Gambia Second presentation to GP learning group, Brighton and Hove City PCT Presentation to Brighton and Sussex Medical School Research Day Research and writing of paper on mobilisation around MMR, with co-funding from IDS-based DFID-funded Development Research Centre on Citizenship Survey data entry and analysis Phase IV: Dissemination (September 2004 - March 2005) Survey feedback discussions with British Stakeholder Advisory Panel 2 survey feedback workshops in The Gambia, one to government staff, one to MRC staff Preparation of written outputs Interaction with New Economics Foundation in development of MMR-focused 'DEMOCS' Participation in new international network on Vaccine Innovation systems (to continue) Interaction with IDS initiative on 'Future Health Systems' (to continue)

6. Outputs Dataset on Childhood Vaccination in The Gambia (offered to Data Archive) Dataset on MMR in Brighton and Hove (offered to Data Archive) Poltorak, M., M. Leach, J. Fairhead and J. Cassell, in press 2005, '"MMR talk" and vaccination choices: an ethnographic study in Brighton', Social Science and Medicine.

Fairhead, J., M. Leach and M. Small, 2004, 'Childhood Vaccination and Society in The Gambia: Public engagement with science and delivery'. IDS Working Paper 218. Brighton: Institute of Development Studies.

Poltorak, M., M. Leach and J. Fairhead, 2004, 'MMR 'choices' in Brighton: Understanding public engagement with vaccination science and delivery. IDS Working Paper. Brighton: Institute of Development Studies. Fairhead, J. and M. Leach, forthcoming, 'Engaging with science? An ethnography of a West African vaccine trial', Journal of Biosocial Science, special issue on Anthropology and Public Health Leach, M., forthcoming, 'MMR mobilisation: Citizens and science in a British vaccine controversy', IDS Working Paper. Fairhead, J. and M. Leach, in prep, 'Fluid anxieties: technoscience and the economy of blood in The Gambia', paper presented to Anthropology seminars at LSE and Brunel University, under revision for journal submission J A Cassell, M A Poltorak, M Leach, J R Fairhead, C H Mercer and A Iversen, submitted, 'Putting MMR non-compliance in context – a quantitative survey of mothers based on ethnography', Vaccine. J.A. Cassell, J. Fairhead, M. Leach, M. Small and C.H. Mercer, in prep, 'Vaccine uptake in rural and urban areas of The Gambia - a quantitative survey of mothers based on ethnography (provisional title), for submission to Health Policy and Planning Fairhead, J. and M. Leach, in prep, Vaccine Anxieties. Book manuscript in preparation for Science in Society series, Earthscan. Seminar and conference presentations to: Department of Anthropology, London School of Economics; Training day, Anthropology, University College London; Department of Medical Anthropology, Brunel University; Institute of Child Health, London; London School of Hygiene and Tropical Medicine; Research Day, Brighton and Sussex Medical School; School of Oriental and African Studies.

7. Impacts In Brighton, the research findings MMR have fed into discussions amongst GPs and Health Visitors concerning the ways they communicate with parents. In particular, the PCT Immunisation co-ordinator has incorporated key findings (e.g. re. early thinking about MMR, and the relevance of birth experiences and homeopathy) into the talks she gives to Health Visitors. In the UK nationally, our findings have helped shape the development of an MMR pack for the citizen-deliberation card game DEMOCS, designed by the New Economics Foundation with funding from the Wellcome Trust. This will be piloted and used during 2005 with the aim of clarifying public opinion on MMR policy choices, and feeding the results to the Department of Health and key vaccine policy-makers. In The Gambia, the research findings, communicated to government and MRC staff through feedback workshops and briefings, are feeding into ongoing deliberation about improving uptake of immunisation services, and improving the communication processes used in trials. Inevitably, bringing about change in established discourses and practices in medical research and health institutions is a slow process, especially where these discourses are strongly entrenched and polarised, as with vaccination. We hope that further examples of application and impact will emerge as the study

findings continue to be published and disseminated, and to feed through media communication into wider public debate.

8. Future Research Priorities Immediate future priorities, drawing on research data from this project, include (a) analysis of gender-differentiated and paired mother-father perspectives on MMR vaccination, in relation to existing literature on gender and public engagement with science, and (b) further comparative analysis of British and African issues in public engagement with science, in relation to current discussions of science, citizens and globalisation. The project suggests a number of further lines of research, which we hope to take forward in interaction with other colleagues, partners and funding sources over the next few years. These include:

• Investigation of the experiences, imaginations and politics of science involved with contemporary 'anti-vaccination rumours' in diverse contexts globally;

• Investigation of how publics perceive and might participate in the global policy processes around vaccine development, including new public-private partnerships;

• Comparative study of the citizen-science and governance issues involved with new health technologies such as vaccination, and new technologies in other fields (agriculture, environment);

• Further investigation of the rapidly-changing, plural health systems which this study has shown to be relevant in both British and African settings, examining user perspectives, interactions, and issues of trust and regulation, towards achieving better health outcomes, especially for the poor.

References André, F. (2003). Vaccinology: past achievements, present roadblocks and future promises. Vaccine, 21:

593–595. Beck, U. (1992). Risk Society: Towards a new modernity. London: Sage. Elliman, D. & Bedford, H. (2001). MMR vaccine-worries are not justified. Arch Dis Child, 85: 271-274. Fitzpatrick, M., 2004, MMR and Autism: What parents need to know. London: Routledge. Hargreaves, I., Lewis, J. & Spears, T. (2002). Towards a better map: Science, the public and the media. Swindon:

ESRC. Hobson-West, P. (2003). Understanding vaccination resistance: moving beyond risk. Health, Risk and

Society 5(3): 273-283. Irwin, A. & Wynne, B. (1996). Misunderstanding Science? Cambridge: Cambridge University Press. Martin, E. (1994). Flexible Bodies: Tracking Immunity in American Culture from the Days of Polio to the Age of

AIDS, Boston Beacon Press. Napier, D., 2003, The Age of Immunology: Conceiving a future in an alienating world. Chicago: University of

Chicago Press. Obaro, S.K. and A. Palmer A, 2003, 'Vaccines for children: policies, politics and poverty',

Vaccine 21:1423-1431 Pareek, M. & Pattinson, H. (2000). The two-dose measles, mumps and rubella (MMR) immunisation

schedule: factors affecting maternal intention to vaccinate. British Journal of General Practice, 50: 969-971.

Streefland, P., A.M.R. Chowdhury and P. Ramos-Jimenez, 1999, ‘Patterns of vaccination acceptance’, Social Science and Medicine 49: 1705-1716.

Streefland, P., 2001, 'Public doubts about vaccination safety and resistance against vaccination', Health policy 55 (2001): 159-172.

UNICEF, 2003, Combatting antivaccination rumours: lessons learned from case studies in east Africa. Eastern and Southern Africa Regional Office. Nairobi: UNICEF.

ANNEX 1

Mother's questionnaire for Brighton survey (Father's questionnaire the same, with appropriate adaptations for gender specificity)

Q. Code:……….

15

MMR in Brighton and Hove – Making your views count QUESTIONNAIRE FOR MOTHERS AND FEMALE GUARDIANS

First we would like to know a little about you and your relationship to the child named on this letter.

1. Are you the child’s mother? guardian? Other - please specify…………………………………………. ………………………………………… 2. Is the child named on the letter your first child? Yes

No If no, please can you tell us the ages of your older children?

years years years years years 3. Before answering our questions, could you tell us what you felt were the most important issues for you concerning whether or not your child should have the MMR vaccination?

………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………

Please could you answer the following questions on how decision making about MMR has related to the process of raising your child?

4. Did you attend any classes about birth or parenting, for any of your children?

Please tick all that apply to you

Parentcraft classes run by the NHS Classes run by health visitor Classes run by NCT Yoga for childbirth Classes at the hospital I didn’t go to any classes Other……………………………………………..

5. Was the birth of this child as you planned it to be?

I had no particular plans Not at all as I planned More or less as I planned Very much what I planned

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6. Please can you tell us more about what you planned? ……………………………………………………………………………………………………….

7. Did you feel you were given enough control over the birth at the points you wanted it?

On a scale of 0-10, please tick the box that applies to you

The midwives/doctors I was in control controlled me completely completely

0 1 2 3 4 5 6 7 8 9 10 8. Did your child have the Vitamin K injection after birth?

Yes No Don't know

9. How would you describe your child's health since he/she was born?

Generally strong Weak Don’t know

Please can you tell us a bit more about this?…………………………………………………… ……………………………………………………………………………………………………………………………………………………………………………………

10. Does your child have any of the following problems? Yes No

Eczema Allergies Sleep problem Breathing problem Eating problem another problem - please say what …………………………… ………………………………………………………

11. Have you consulted any of the following about your child's health? Please tick all that apply

Homeopath Herbalist Cranial osteopath Acupuncturist Ayurvedic practitioner Kinesiologist Other complementary practitioner - please specify_________________________________

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12. When do you remember first thinking about MMR, for this child? Tick one box only

When he/she was due for MMR When he/she was due for the first baby jabs Around the time when he/she was born Before he/she was born Not sure A different time – please say when …………………………….

13. Are there any aspects of your family's health history which affected your thinking about MMR?

Yes No Don't know If you answered yes, can you tell us a bit more about this?…………………………………………. ………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………

14. As a childhood illness, how serious do you think measles is? Very serious Quite serious Mild Don't know

Other Please can you explain? ……………………………………………. ………………………………………………

15. These are some of the things that other parents in Brighton and Hove have said when discussing their

thinking about MMR. How much does each reflect your view or experience? On a scale of 1-5, please tick the box that applies to you next to each statement.

Not my



I’ve had personal experience or know someone who suffered serious effects from these illnesses (measles, mumps or rubella).

My experience of hospitals and/or health professionals has undermined my faith in the medical profession.

I know parents whose children have been knocked back by the MMR. Friends and family have had the MMR and they were fine. I have friends or family who have autistic children. I know people who have older children who they didn’t vaccinate, and they’re fine.

I heard lots of stories of ‘my son or my daughter were great until they had the MMR’.

Vaccinating your child with MMR shows your responsibility to the community.

There is a chance of serious side effects from MMR if there is a weakness in that child.

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Each child’s immune system is different. My child needs to be immunised, he/she can’t live in isolation. MMR is fine for most children but not for my child. What I do to one child I tend do to them all. I worry about the MMR because of my child's behaviour.

16. Which of these sources of information about the MMR vaccine have you come across?

Please tick all that apply

Information that you found on the internet

Information that someone else found on the internet Videos NCT Newsletter ABC magazine Public meetings about immunisation Newspaper articles Leaflets Television or radio news or adverts Television or radio documentaries Books Research papers Childcare magazine articles

16. Who did you talk to about the MMR? Please tick all that apply, showing on a scale of 1-5 how supportive they were in helping you think the issue through.

Very Unsupportive Very Supportive

1 2 3 4 5

Partner or husband

Child's father Your GP Another doctor you went to see Health Visitor Your mother Your father Your sister Your brother Other mothers you know well Other mothers you don't know well

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Fathers you know well Fathers you don't know well Practice nurse Homeopath Other alternative health practitioner Your partner's relatives Work colleagues Other - please say who 1._________________________________. 2. _________________________________ 3. _________________________________. I didn't talk to anyone

17. Did discussing with any of these people particularly influence what you did or plan to do about MMR? If so please can you tell us a bit more about this? ……………………………………………………………….………………………………………………………………………………………………………………………………………………………………………………………………………………………

18. Here are some things that Brighton and Hove parents have said about their research and discussions on

MMR. How much does each of these reflect your view? On a scale of 1-5, please tick the box that applies to you next to each statement.


1 2 3 4 5 The MMR is necessary to protect children from getting serious diseases.

You can get bogged down in the detail, too much research and you don't do anything.

There is no scientific proof that the MMR vaccine causes autism or any other problems.

Single vaccinations concern me too but not as much at the MMR. The MMR is too much in one go. All the stuff you hear about the negative effects of the MMR is media hype.

It’s better to get immunity naturally. Not enough research has been done on the MMR. I tend to avoid talking to my friends about the MMR issue. I don’t feel we have enough information to make an informed decision.

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19. Who decides whether your child has the MMR or not? Tick one box

Me Me and my partner/husband My partner/husband Someone else please say who ……………………………………. Not sure

20. What was decided?

To have the MMR To delay the MMR To have single jabs To have neither MMR nor single jabs Not sure/undecided

21. Do you think your own reasons for your choice about MMR are different to most people you know? Yes No

Not sure Can you tell us a bit more about this?…………………………………………………………. ………………………………………………………………………………………………………

22. What views do you think other people would have about your decision (or indecision) on the MMR? They would They would They would Don't know

approve disapprove not mind

Your GP or Surgery Your Health Visitor Partner or husband Your mother Your father Practice nurse Social workers

23. Do you feel certain you made the right decision? On a scale of 0-10, please tick the box that applies to you

No, not at all certain Yes, completely certain 0 1 2 3 4 5 6 7 8 9 10

Still undecided

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24. Here are some more statements from other Brighton and Hove parents, this time about how they felt about their actual MMR decisions. How much does each of these reflect your view or experience? On a scale of 1-5, please tick the box that applies to you next to each statement.

Not my



I/We just went along and had them done, we’ve never had any problem with the idea of immunisation.

I felt very vulnerable at the time and knew I couldn’t cope if my child got measles.

I would rather have the single vaccination but cannot afford it I’d have to be a lot more knowledgeable not to have the MMR. To be honest, I haven’t thought about it (or looked into it) too much. I’d have to be a lot more confident not to have the MMR. If my child ever got measles, I’d never forgive myself. People would think I was a bad parent if my children weren't vaccinated.

It would be so much easier if you were just told, and it wasn't your decision.

I couldn’t forgive myself if she got autism or any other side effects. We just didn’t get around to having it done. We sway one way and then the other and find it difficult to decide. At the end of the day whether you vaccinate or not is a gamble. I had them vaccinated straightaway because I heard about an epidemic of measles.

You just have to go with your own personal feelings.

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25. Do you feel you understand the issues about MMR well enough?

On a scale of 0-10, please tick the box that applies to you.

No, not well enough at all Yes, very well.

0 1 2 3 4 5 6 7 8 9 10

26. Is there anything else you would have wanted to know about the MMR vaccine to help you make a decision?

Yes No

If you answered yes, please can you tell us a bit more about this? ……………………………………

……………………………………………………………………………………………………………………………………………………………………………………

27. When deciding about MMR for your child, did you consider possible benefits to other children?

Yes No Not sure

If you answered yes, please can you tell us a bit more about this? ……………………………………

……………………………………………………………………………………………………………………………………………………………………………………

28. Is it right for health professionals to advise parents to have their child vaccinated for the benefit of

other children?

Yes

No Not sure

29. Parents in Brighton and Hove said the following about trust and government - how much does each

of these reflect your view? On a scale of 1-5, please tick the box that applies to you next to each statement.

23


1 2 3 4 5 It is the government's responsibility to decide whether children should be vaccinated.

You can't trust the government over science.

I am suspicious of the influence of the pharmaceutical companies. You’ve got to trust in the medical profession, what else is there? I tend to trust professional people and what they say. When it comes to the government telling us MMR is safe, there’s no smoke without fire.

The most important thing is that parents have the choice. I see it as a cost thing. MMR is financially led, it's in the government's interests.

30. Do you feel tempted to buy organic food for your family?

Often Sometimes Never Don't know

31. Do you check food labels to see if they contain genetically-modified ingredients (GMOs)?

Always Sometimes Never Don't know

32. Did you stop or reduce eating beef because of BSE (Mad Cow Disease)?

Yes No I was already vegetarian

Finally could you tell us a bit more about yourself?

33. Which newspaper do you read most often?

I don’t read newspapers Sun Mirror Mail Express Telegraph Independent Guardian Times

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Other – please say which_____________________________________ 34. Is English your first language? Yes No

If No, what is your first language _______________________

35. Apart from looking after your child, are you currently working? Full time Part time On maternity leave

Taking a break for parenting No 36. What is your highest educational qualification?

Degree or higher degree A level / AS level / Higher School Certificate GCSE / O level NVQ levels 1-3 / GNVQ NVQ levels 4-5/ HNC / HND Other qualifications - please specify………………… No qualifications

Thank you very much for completing this questionnaire

Do you have any comments or anything else you would like to tell us? …………………… ……………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………

Could you please return the questionnaire in the Freepost envelope provided or post it in an envelope to the following address. You will not need to pay any postage. Dr Mike Poltorak FREEPOST NAT 12538 BRIGHTON

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ANNEX 2

STATISTICAL TABLES FOR BRIGHTON MMR SURVEY

Table 1: response rate

n % Total Responded 452 39.8 1135 Non vaccinators responded 40 29.6 135 Table 2: Characteristics of responders and non-responders

Responder Nonresponder Total n=452 n=683 N=1135 n (%) n (%)

Age at birth of this child Base <18 1 (0.23) 13 (2.0)

18-20 5 (1.14) 45 (7.0) 21-24 28 (6.4) 71 (11.1) 25-34 201 (45.9) 287 (287)

35+ 203 (46.4) 225 (35.1) 1079 mean (SD) mean (SD)

Previous live births 0.74 (0.92) 0.9 (1.2) 1069 n (%) n (%)

Male sex (this child) 237 (52.4) 343 (50.2) 1135 MMR before 15 months according to child health records

Yes, had MMR 225 (49.8) 275 (20.3) 1135 No, but had some other vaccinations 187 (41.4) 313 (45.8)

No vaccinations recorded 40(8.9) 95 (13.9) Not applicable

Born 36 weeks or less gestation 32 (7.3) 45 (7.0) 1077

Table 3: Characteristics of vaccinators v complete nonvaccinators

Nonvaccinator Vaccinator Total n=135 n=1000 N=1135 n (%) n (%)

Age at birth of this child Base <18 0 (0) 14 (1.4)

18-20 3 (2.2) 47 (4.7) 21-24 6 (4.4) 93 (3.3) 25-34 53 (39.3) 495 (49.5)

35+ 51 (37.8) 3317 (31.7) 1079 mean (SD) mean (SD)

Previous live births 1.1 (1.6) 0.8 (1.0) 1069 Male sex (this child) 81 (60) 499 (49.9) 1135 Born 36 weeks or less gestation 9 (7.8) 68 (7.1) 1077

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Table 4: Vaccination decision in relation to child health dataset

MMR recorded MMR not recorded, but at least one other

vacc given

Non vaccinator Base P value for significant difference

n (%) n (%) n (%) N To have MMR 163 (72.4) 26 (13.9) 2 (5) 452 To delay MMR 5 (2.2) 31 (16.6) 1 (2.5) Singlejabs 0 60 (32.1) 0 No MMR or single 0 12 (6.4) 37 (92.5) Not sure/undecided 0 12 (6.4) 0 <0.001 Table 5: Vaccination decision in relation to characteristics

Have MMR

Delay MMR Single jabs None Not sure/undeci

ded

Base P value for difference

n (%) n (%) n (%) n (%) N (missing)

Graduate 98 (52.4) 22 (11.8) 32 (17.1) 30 (16.0) 5 (2.7) Non-graduate 93 (57.4) 15 (9.3) 28 (17.3) 19 (11.7) 7 (4.3) 349 0.6

Maternal age 0.57

<18 1 (100) 0 0 0 0 18-20 4 (100) 0 0 0 0 21-24 9 (50) 1 (5.6) 5 (27.8) 2 (11.1) 1 (5.6) 25-34 89 (56.7) 12 (7.6) 32 (20.4) 19 (12.1) 5 (3.2)

35+ 81 (51.3) 23 (14.6) 23 (14.6) 25 (15.8) 6 (3.8) 338 0.758 First child

Yes 100 (58.1) 7 (4.1) 33 (19.2) 27 (15.7) 5 (2.9) No 91 (51.4) 30 (17.0) 27 (15.3) 22 (12.4) 7 (4) 349 0.003

Table 6: Who chooses single jabs

Singlejabs Other Base P value for difference

n (%) n (%) N All 60(13.3) 392 (86.7) 452 Graduate 32 (17.1) 155 (82.9) Non-graduate 28 (10.6) 237 (89.4) 452* 0.043

Maternal age

<18 0 1 (100) 18-20 0 5 (100) 21-24 5 (17.9) 23 (82.1) 25-34 32 (15.9) 169 (84.1)

35+ 23 (11.3) 180 (88.7) 438 0.53 First child

Yes 33 (19.1) 140 (80.9) No 27 (15.3) 150 (84.8) 350 0.343

* Labelled "graduate" if ticked - otherwise assumed to be non-graduate

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Table 7: Compliance and child health since birth

Compliant Noncompliant N (missing)

P value for difference

n (%) n (%) Child's health since birth

Strong 183 (96.3) 146 (92.4) Weak 4 (2.1) 8 (5.1)

Don't know 3 (1.6) 4 (2.5) 348 (4) 0.257

Vitamin K injection at birth Yes 167 (88.8) 112 (70.9) No 11 (5.6) 40 (25.3)

Don't know 10 (5.3) 6 (3.8) 346 (106) <0.001*

Childhealthproblems Eczema 55 (30.6) 31 (22.1) 320 0.09

Allergies 11 (7.0) 9 (7.0) 286 0.9 Breathing problems 8 (5.2) 8 (6.1) 287 0.7

Eatingproblems 8 (5.1) 6 (4.6) 287 0.8 "I worry about the MMR because of my child's behaviour"

Strongly agree 7 (3.7) 13 (8.2) 349 (113) 0.04 Table 8: Use of alternative therapy for child



n (%) n (%) Alternative therapy

Consulted homeopath 18 (9.4) 55 (21.1) NA 0.001 Consulted herbalist 4 (2.1) 13 (5.0) 0.111

Consulted acupuncturist 1 (0.5) 3 (1.2) 0.483 Consulted ayurvedic 3 (1.6) 1 (0.4) 0.183

Consulted kinesiologist 1 (0.5) 5 (1.92) 0.201 Yogaforchildbirth 46 (24.8) 75 (28.7) 0.270

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Table 9: When MMR became a concern and process of decision making

Compliant Noncompliant


n (%) n (%) N Time MMR became a concern

When MMR due 58 (31.4) 15 (10.3) When baby jabs due 66 (35.70) 35 (24.0)

At time of birth 14 (7.6) 11 (7.5) Before birth 42 (22.7 83 (56.9)

Not sure 5 (2.7) 2 (1.4) 331 <0.001 Conern about family health in relation to MMR

Yes 28 (14.7) 49 (30.8) No 161 (84.7) 109 (68.6)

Don't know 1 (0.5) 1 (0.6) 349 0.001 How serious is measles seen to be

Very or quite 179 (93.7) 123 (77.4) Mild 7 (3.7) 11 (6.9)

Don't know 1 (0.5) 3 (1.9) Other 4 (2.1) 22 (13.8) <0.001

Who decides Me 43 (22.5) 37 (23.3)

Me and partner 146 (76.4) 122 (76.7) Partner 2 (1.1) 0 0.430

Who approves health visitor approves 171 (91.4) 13 (8.5) 340 <0.001

GP approves 175 (94.1) 13 (8.4) 341 <0.001 Reasons for choice different most people you know

Yes 24 (12.8) 65 (40.9) 347 <0.001 Table 10: Mothers' views of Health Visitor and GP attitudes HV view approve disapprov not mind dontknow Total

n n n n n (%) (%) (%) (%) (%)

approve 9 2 2 0 13 69.23 15.38 15.38 0 100

disapprove 1 62 5 2 70 1.43 88.57 7.14 2.86 100

notmind 2 25 25 3 55 3.64 45.45 45.45 5.45 100

dontknow 1 4 0 10 15 6.67 26.67 0 66.67 100

Total 13 93 32 15 153 8.5 60.78 20.92 9.8 100 χ2 test P<0.001

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Table 11: General views on MMR



n (%) n (%) N I know parents whose children have been knocked back by the MMR (q15c)

Strongly my view 12 (6.4) 53 (33.5) 347 <0.001 Friends and family have had the MMR and they were fine (q15d)

Strongly my view 165 (87.3) 85 (54.5) 345 <0.001 You can get bogged down in the detail, too much research and you don't do anything (q19b)

Strongly my view 82 (44.6) 42 (27.6) 336 <0.001 There is no scientific proof that the MMR vaccine causes autism or any other problems (q19c)

Strongly my view 123 (65.8) 23 (14.9) 341 <0.001 Single vaccinations concern me too but not as much as the MMR (Q19d)

Strongly my view 38 (20.2) 79 (50.6) 344 <0.001 All the stuff you hear about the negative effects of the MMR is media hype (q19f)

Strongly my view 70 (36.8) 12 (7.6) 347 <0.001 Not enough research has been done on the MMR (q19h)

Strongly my view 58 (31.0) 128 (81.5) 344 <0.001 I tend to avoid talking to my friends about the MMR issue** (q19i)

22 (11.8) 21 (13.6) 342 0.355 I don't feel we have enough information to make an informed decision (q19j)

38 (20.4) 96 (61.2) 343 <0.001 * mhodds still highly significant after controlling for firstchild ** By contrast, 10 (25%) of nonvaccinators strongly agreed, compared with 33 (10.9%) of vaccinators P=0.01

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Table 12: The importance of freedom of choice



n (%) n (%) N It would be so much easier if you were just told, and it wasn't your decision (Q25i)

Strongly my view 23 (12.2) 9 (5.7) 346 <0.001 The most important thing is that parents have the choice (Q30g)

Strongly my view 139 (73.2) 145 (91.2) 349 <0.001 Table 13: Certainty in decision made

Compliant Noncompliant Base P value for difference

n (%) n (%) N Do you feel certain you made the right decision?*

Very certain, or fairly certain 172 (93.5) 116 (85.9)

Not very certain 4 (2.2) 8 (5.9) 319 0.07 Is there anything else you would have wanted to know about MMR to help you make a decision

Yes 130 (71.4) 69 (44.5) No 52 (28.6) 86 (55.5) 337 <0.001

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Table 14: Emerging views of immunity



Note

n (%) n (%) There is a chance of serious side effects from MMR if there is a weakness in that child (q15i)

Strongly agree 35 (18.3) 86 (54.8) 348 <0.001 Each child's immune system is different (q15j)

Strongly agree 116 (60.7) 124 (79.0) 348 <0.001 Single vaccines concern me but not as much as MMR (q19d)

Strongly agree 38 (32.5) 79 (67.5) 344 <0.001 The MMR is too much in one go (q19e)

Strongly agree 39 (21.0) 131 (86.2) 338 <0.001 It's better to get immunity naturally (q19g)

Strongly agree 10 (5.3) 70 (45.6) 342 <0.001

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Table 15: Personal v social responsibility



n (%) n (%) If my child ever got measles, I couldn't forgive myself (q25g)

Strongly agree 117 (61.9) 49 (31.8) 343 <0.001 I couldn't forgive myself if she got autism or any other side effects (q25j)

Strongly agree 85 (45.2) 144 (91.7) 345 <0.001 When deciding about MMR…did you consider possible benefits to other children (Q28)

Yes 23 (12.1) 18 (11.4) 348 <0.815 Is it right for health professionals to advise parents to have their child vaccinated for the benefit of other children* (q29)

Yes 132 (69.5) 51 (32.7) No 24 (12.6) 66 (42.3)

Not sure 34 (17.9) 39 (25.0) 346 <0.001 Table 16: Trust in government and the state's role



n (%) n (%) It is the government's responsibility to decide whether children should be vaccinated (Q30a)

Strongly agree 30 (15.9) 6 (3.8) 346 <0.001 You can't trust the government over science (q30b)

Strongly agree 60 (31.4) 117 (73.6) 350 <0.001 I am suspicious of the influence of the pharmaceutical companies (Q30c)

Strongly agree 98 (51.9) 128 (80.5) 348 <0.001 The most important thing is that parents have the choice

Strongly agree 139 (73.2) 145 (91.2) 349 <0.001

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Table 17: Attitudes to health risk in food



n (%) n (%) Did you stop or reduce eating beef because of BSE

Yes 66 (34.7) 65 (41.1) No 92 (48.4) 35 (22.2)

Already vegetarian 32 (16.8) 58 (36.7) 348 (104) <0.001 Do you check food labels to see if they contain GMOs

Always/sometimes 106 (55.8) 136 (86.1) 348 (104) <0.001 Table 18: Information-seeking behaviour Information about MMR respondent had come across



n (%) n (%) Information which found on the internet by self

65 (34.0) 84 (32.2) N/A 0.68

Information found on internet by others

30 (15.7) 33 (12.6) 0.35

NCT newsletter 24 (12.6) 20 (7.7) 0.08 ABC magazine 119 (62.3) 106 (40.6) <0.001 Public meeting on immunisation

5 (2.6) 41 (15.7) <0.001

Newspaper articles 152 (79.6) 134 (51.3) <0.001 Television or radio news 132 (69.1) 105 (40.2) <0.001 Television or radio documentary

107 (56.0) 104 (39.9) 0.001

Books 21 (11.0) 55 (21.1) 0.005 Research papers 42 (22.0) 63 (24.1) 0.59

34

Table 19: % reporting compliance with MMR for 5 key variables Variable % reporting

compliance Crude OR (95% CI)

for compliance

Adjusted 1 OR (95% CI)

for compliance

Number of cases 2

All 53.8% - - 320 Vitamin K injection at birth p<.0001 p=.001

Yes 59.4% 1.00 1.00 271 No 22.5% 0.20 (0.10-0.40) 0.26 (0.12-0.56) 49

Mother is a graduate 3 p=.116 p=.924

No 58.5% 1.00 1.00 147 Yes 49.7% 0.70 (0.45-1.09) 0.97 (0.58-1.64) 173

Used a homeopath p<.0001 p<.0001

No 61.0% 1.00 1.00 254 Yes 25.8% 0.22 (0.12-0.41) 0.25 (0.13-0.48) 66

Mother’s first child p=.301 p=.241

Yes 56.7% 1.00 1.00 157 No 50.9% 0.79 (0.51-1.23) 0.73 (0.44-1.23) 163

Mother’s age 4 p=.328 p=.703

<30 65.4% 1.00 1.00 52 30-34 53.1% 0.60 (0.30-1.18) 0.65 (0.31-1.37) 113 35-39 50.0% 0.53 (0.27-1.06) 0.67 (0.31-1.43) 102

40+ 51.4% 0.56 (0.23-1.34) 0.73 (0.27-1.96) 35 Notes for table: 1. Adjusted OR net of the effect of the other variables in the table. 2. There were 320 respondents with valid responses to all 6 variables so the estimates in the table are all based

on these 320 respondents. 3. Whether or not the mother was a graduate is significantly associated with compliance when using all

available cases (n=452; odds ratio for compliance if a graduate vs. not being a graduate: 2.04, 95% CI 1.39-2.98). Thus, the 452-320=132 respondents who do not have valid responses for the other variables used for this analysis are significantly different in terms of the % who are graduates.

4. It is probably easier to interpret the effect of age on compliance when age is categorised. NB: there is no significant association regardless of whether age is expressed as a continuous or a categorical variable.

Interpretation: The most statistically significantly factors associated with whether or not mothers complied with having the MMR vaccination are reporting that their child did not have the vitamin K injection at birth and reporting using a homeopath. Respondents reporting either of these outcomes were significantly less likely to have complied in terms of MMR. (Note: there is no statistically significant interaction between not having the vitamin K injection at birth and reporting using a homeopath. Thus, the effect of not having the vitamin K injection at birth is not any greater if the respondent also reported using a homeopath.)

35

ANNEX 3

QUESTIONNAIRE FOR GAMBIA SURVEY

36

CHILDHOOD VACCINATION AND SOCIETY QUESTIONNAIRE Respondent number______________ Enumeration area_________________

Date of interview__________________

Study explained and verbal consent to proceed with interview given? _______________________________(fieldworker to sign and give initials)

Name of child _____________________________________ Age of child in months Name of mother/main carer ___________________________________

If not birth mother, what is relationship to child?___________________ how old (in months) was child when care started? months. I SOCIAL PROFILE 1. Appearance of compound (interviewer to note; tick which applies)

_______ 1 Wealthy (solid, well-decorated buildings; car; satellite dish; solar panels; generator…) _______ 2 Medium _______ 3 Poor (cramped, family in 1-2 rooms; mud block, incomplete or broken buildings….)

2. Mother's category of reproductive life (interviewer to note, check with mother if necessary; tick which applies)

Tick here

Mandinka Wollof Fula

1 Young woman Sunkuto Jankhaa Surkaajo/Giwo 2 Newly married with few children Foro musu dindingo Sait Jombaajo 3 Woman in middle of reproduction Foro muso Jongoma/Jeggamar Nyanyoma 4 Woman at end of reproduction Sarifo Jegg Mawdo debo 5 Old woman Musu keba Magett Nayeejo

37

3. How many children do you have? __________________ (Enter number) 4. What is your ethnic group?

_______ 1 Mandinka _______ 4 Serrehuli _______ 2 Fula _______ 5 Jola _______ 3 Wolof _______ 6 Other (please specify)_____________________________________________

5. Are you currently married?

_______ 1 Married – first husband _______ 4 Widowed _______ 2 Married – second (or later) husband _______ 5 Inherited widow _______ 3 Separated/divorced _______ 6 Never married

6. Who does the compound you are living in now belong to?

_______ 1 Husband’s extended family _______ 5 Rented from a landlord _______ 2 Woman's extended family _______ 6 Other (please specify) _______ 3 Husband _______ 4 Woman

7. Is there a telephone or mobile telephone in the compound?

_______ 1 Yes _______ 2 No _______ 9 Don’t know

8. Have you been to school?

_______ 1 Yes _______ 2 No If yes: How many years Western/Tubab school? ____________(Enter number) Don't know______ 999

How many years Koranic school ? __________________(Enter number) Don't know______ 999 Any further education? _________________ (level)

9. Do you yourself do any activities that earn income in money? (Please tick all that apply)

_______ 1 Farming _______ 5 Business or long-distance trade _______ 2 Vegetable gardening _______ 6 Teacher/professional

38

_______ 3 Petty trading _______ 7 Other (please specify)_____________________________________________ _______ 4 Fish processing

If no current husband, skip to 13

10. Has your husband been to school? _______ 1 Yes _______ 2 No _______ 9 Don’t know If yes: How many years Western/Tubab school? ____________(Enter number) Don't know______ 999

How many years Koranic school ? __________________(Enter number) Don't know______ 999 Any further education? _________________ ( write in level) 11 . What is your husband's usual work? (Please tick all that apply)

_______ 1 Farmer _______ 7 Trade or craft (e.g. mason) _______ 2 Trader _______ 8 Student or apprentice _______ 3 Fisherman _______ 9 Retired _______ 4 Alkalo _______ 10 Other (please specify)____________________________________ _______ 5 Imam/Marabout _______ 11 Don't know _______ 6 Teacher/professional

12. Does your husband travel away to work?

_______ 1 Yes If yes, please say where__________________________________________ _______ 2 No

II CHILD HEALTH BIOGRAPHY Now we would like to ask you some questions about the health of your child 13. How has the child’s health been since it was born? Have you had any particular worries or problems? Please explain (narrative - write down in

mother's exact words)

39

14. When the child was born, was it taken out of the house before its naming ceremony?

_______ 1 Yes If yes, where was it taken? ______________________________________________(skip to 16) _______ 2 No _______ 9 Don't know

15. Why was the child kept in? (please tick all that apply) _______ 1 Because it is custom not to go out before naming ceremony _______ 4 Fear of djinn _______ 2 Because elders said to stay in _______ 5 Because there was no need to go out _______ 3 Fear of witches or bad people _______ 6 Other (please specify)_________________ ____________________________________________ 16. Has your child ever been taken to the Infant Welfare Clinic (IWC - nurse)?

_______ 1 Yes (skip to 18) _______ 2 No _______ 9 Don't know

17. What has prevented the child from ever being taken to the IWC? (narrative - write down in mother's exact words. Then skip to 42)

40

III EXPECTATIONS OF IMMUNISATION 18. What do you think the injections given to children at the IWC are for? (narrative - write down in mother's exact words. Probe: how might they

strengthen or protect child, what sort of health do they bring) 19. What diseases do you think injections at the IWC can protect your child against? (list disease named by mother; prompt 'and what else'?)

41

IV IWC/IMMUNISATION BIOGRAPHY 20. How old was the child when he/she first went to the IWC? ____________ (enter age in weeks) 21. Which clinic was this? _______________________________________ (enter name or place of clinic) 22. What happened at this first visit? (please tick all that apply) _______ 1 Registration/change cards _______ 5 Visiting MRC

_______ 2 Weighing _______ 6 Child seen/treated for illness _______ 3 Injections _______ 7 Other (please specify)______________________________________ _______ 4 Knew myself/always known If cards not changed, ask 23, otherwise skip to 24

23. How old was the child when its cards were changed? (enter age in weeks) 24. Where did you get the idea to take the child to the IWC? (please tick all that apply)

_______ 1 Knew importance from earlier children _______ 6 Mother in law _______ 2 Other mothers _______ 7 Health centre staff at delivery _______ 3 Own mother _______ 8 TBA or VHW _______ 4 Husband _______ 9 Don’t know _______ 5 I knew myself/always known _______ 10 MRC worker

_______ 11 Other (please specify)_______________________________ 25. Do you feel your child had the first injections at a good time?

_______ 1 Yes _______ 2 No _______ 9 Don't know Can you say a bit more? (narrative - write down in mother's exact words)

42

26 A Did the child first go to the IWC at the usual time? _______ 1 Yes (skip to 27) _______ 2 No (go to 26B) _______ 9 Don't know 26 B Can you tell us why? (please tick all that apply)

_______ 1 I had to travel _______ 7 Childcare/ problems with older children _______ 2 I was unwell _______ 8 Public holiday _______ 3 Child was unwell _______ 9 Too much work _______ 4 Financial problems _______ 10 Problems with IWC (please specify)__________________________ _______ 5 Distance/transport problems _______ 11 Other (please specify)_____________________________________ _______ 6 Family event (e.g. bereavement, ceremony) _______ 12 Went at usual time

27. On this first visit, how was your interaction with clinic staff?

_______ 1 They were friendly/respectful _______ 4 They were rude _______ 2 They embarrassed me _______ 5 Some were not there _______ 3 They were helpful _______ 6 Other (please specify) ____________________________________________

Can you say a bit more? (narrative - write down in mother's exact words)

28. Did the baby have its '3 month injections'? _______ 1 Yes skip to 30 _______ 2 No If child did not receive any of the 3 month injections, ask 29, then skip to 34

43

_______ 9 Don’t know skip to 30 29. Why didn't your child receive any of the 3 month injections? (narrative - write down in mother's exact words) 30. Which clinic was this? ________________________________ (enter name or place of clinic) 31. Did your child have any reaction to the injections? (please tick all that apply)

_______ 0 No reaction/effect _______ 5 Mild crying _______ 1 Mild fever _______ 6 Serious crying _______ 2 Serious fever _______ 7 Another effect (please specify)____________________________________________ _______ 3 Mild swelling _______ 8 A delayed effect (please specify)___________________________________________

_______ 4 Serious swelling 32. Do you feel these reactions were normal?

_______ 1 Yes _______ 2 No _______ 9 Don’t know

If no, please say a bit more (probe - anything particular about child that affected its reactions or non-reactions?)

44

33. Do you feel your baby was given the right number of injections each time?

_______ 1 Yes _______ 2 No _______ 9 Don’t know Can you say a bit more? (narrative - write down in mother's exact words)

34. Was it easy or difficult for the child to attend the clinic around the time of the 3 month injections? _______ 1 Easy (skip to 36) _______ 2 Difficult _______ 9 Don’t know

35. If it was difficult, why was that? (please tick all that apply)

_______ 1 I had to travel _______ 7 Childcare/ problems with older children _______ 2 I was unwell _______ 8 Public holiday _______ 3 Child was unwell _______ 9 Too much work _______ 4 Financial problems _______ 10 Problems with IWC (please specify)__________________________ _______ 5 Distance/transport problems _______ 11 Other (please specify)_____________________________________ _______ 6 Family event (e.g. bereavement, ceremony)

36. Did the child miss any clinic sessions around this time?

_______ 1 Yes _______ 2 No (skip to 38) _______ 9 Don’t know

45

37. If the child missed sessions, did this worry you? why? _______ 1 Not worried _______ 3 Worry about multiple injections

_______ 2 Worry about reactions of staff _______ 4 Other (please specify)____________________________________________ Can you say a bit more? (narrative - write down in mother's exact words)

38. Has your child had the 9 month injections?

_______ 1 Yes At which clinic?____________________________________________ _______ 2 No _______ 9 Don’t know

39. Has your child had the 1 year injections? _______ 1 Yes At which clinic?____________________________________________ _______ 2 No _______ 9 Don’t know

If answer to 38 or 39 is no, ask: 40. Why did your child not have these injections? (narrative - write down in mother's exact words) V EXPERIENCES AND PERCEPTIONS OF DIFFERENT HEALTH PROVIDERS 41. What do you see as the main benefits of attending the Infant Welfare Clinic? (narrative - write down in mother's exact words)

46

42. What are the main problems with the IWC? How do you cope with these? (narrative - write down in mother's exact words. Then probe each of

possible answers: tick all those that apply, and add explanations to narrative) _______ 0 No problems _______ 1 Travel problems _______ 5 Disrespectful staff _______ 2 Effects of sun/rain in travel _______ 6 Financial problems _______ 3 Crowds, long waits _______ 7 Links with family planning _______ 4 Bad people or witches _______ 8 Discouragement from husband or family 43. How might these problems be improved? (narrative - write down in mother's exact words) 44. Who else has given protection or treatment to this child? (please tick all that apply)

_______ 0 No one _______ 4 Elderly women or men _______ 1 Herbalist _______ 5 Family doctor/private clinic _______ 2 MRC _______ 6 Other (please specify)___________________________________________________ _______ 3 Marabout _______ 9 Don't know

47

45. Please could you describe any health protection given to your child by herbalists or other women or men? (narrative - write down in mother's exact words)

46. Is your child wearing a talisman (juju) today?

_______ 1 Yes _______ 2 No

47. Do you like the child to wear a talisman (juju) to visit the IWC?

_______ 1 Yes _______ 2 No Can you say a bit more? (narrative - write down in mother's exact words)

48. Has this child been asked to participate in an MRC study?

_______ 1 Yes _______ 2 No (skip to 53) _______ 9 Don’t know (skip to 53)

49. Did he or she join?

_______ 1 Yes _______ 2 No

50. Who made the decision? _______ 1 Myself _______ 4 Compound head _______ 2 Husband _______ 5 Other (please specify)___________________________________________________ _______ 3 Joint - husband & wife

48

51. Please explain how the decision was made and who was involved or had influence (narrative - write down in mother's exact words) 52. What do you think the MRC study that your child was invited to join is about? (narrative - write down in mother's exact words) 53. Have you heard any negative ideas or bad things about having a child registered with MRC?

_______ 1 Yes _______ 2 No (skip to 55)

________ 9 Don't know

If yes, what were these? (narrative - write down in mother's exact words) 54. Where did you hear these ideas? (please tick all that apply)

_______ 1 Husband _______ 5 Relatives abroad _______ 2 Compound head _______ 6 Radio/TV _______ 3 Neighbours _______ 7 Newspapers

49

_______ 4 Relatives elsewhere in the Gambia _______ 9 Don't know _______ 10 Other (please specify)_______________________________

55. What benefits do you think there are in having a child registered with MRC? (narrative - write down in mother's exact words) 56. Finally, could we please see this child's health card? _______ 1 Health card available _______ 2 Health card lost

_______ 3 Has never had a card _______ 4 not willing to show health card

Copy details from front of card onto attached sheet Note from back of card:

57. Number of visits for weighing recorded since birth (Count number of dots) 58. Child's weight at 1 year (if no record for 1 year, note nearest and age of child at this weighing)

. kilograms

at months old

50

ANNEX 4

Statistical tables for Gambia survey

51

Table 1: Social profile of respondents, by district

District: Urban/peri-urban Rural Base 800 800 Mean (95% CI) Mean (95% CI) p=.0063 Mean age of child in months 17.6 (17.4-17.9) 17.1 (16.7-17.5) Column % (95% CI) Column % (95% CI) Appearance of compound (qn01) p=.0004

Wealthy 15.3% (11.4%-20.1%) 8.7% (5.4%-13.7%) Medium 41.7% (37.3%-46.2%) 27.6% (21.0%-35.4%)

Poor 43.1% (38.4%-47.8%) 63.7% (53.8%-72.6%) Total 100.0% 100.0%

Mother’s category of reproductive life (qn02) p=.0061

Young woman 13.8% (10.8%-17.3%) 7.9% (5.4%-11.6%) Newly married with few children 43.7% (38.8%-48.7%) 39.9% (34.15-45.9%)

Woman in middle of reproduction 32.7% (28.3%-37.4%) 36.4% (31.8%-41.3%) Woman at end of reproduction 9.6% (7.7%-12.0%) 15.2% (12.3%-18.5%)

Old woman 0.3% (0.1%-1.0%) 0.7% (0.3%-1.5%) Total 100.0% 100.0%

Number of children (qn03) p<.0001

Mean (95% CI) 3.1 (3.0-3.3) 3.8 (3.6-3.9) Median (lower and upper quartiles) 1.75 (3, 4) 2 (3, 5)

p<.0001 1 13.8% (10.8%-17.3%) 8.4% (5.7%-12.2%) 2 25.9% (22.8%-29.2%) 19.6% (17.2%-22.2%) 3 20.3% (17.4%-23.5%) 17.0% (14.6%-19.8%) 4 14.2% (12.0%-16.7%) 17.0% (13.9%-20.7%) 5 10.9% (8.8%-13.3%) 13.9% (11.5%-16.7%)

6+ 15.1% (12.4%-18.2%) 24.1% (21.6%-26.8%) Total 100.0% 100.0%

Ethnic group (qn04) p<.0001

Mandinka 31.6% (25.8%-38.1%) 30.9% (20.5%-43.5%) Fula 20.6% (16.5%-25.5%) 38.2% (27.4%-50.3%)

Wolof 11.0% (8.4%-14.3%) 0.8% (0.2%-3.1%) Serrehuli 3.6% (1.9%-6.8%) 27.1% (15.8%-42.4%)

Jola 17.5% (13.5%-22.4%) 0.4% (0.1%-1.2%) Other 15.6% (10.7%-22.4%) 2.7% (1.5%-4.8%) Total 100.0% 100.0%

Currently married (qn05) p<.0001

Married 1st husband 78.5% (74.2%-82.3% 84.4% (81.5%-87.0%) Married 2nd+ husband 11.3% (9.4%-13.5%) 13.6% (11.2%-16.4%)

Separated/divorced 1.8% (1.1%-2.8%) 0.1% (0.0%-1.0%) Widowed 1.0% (0.5%-1.9%) 0.8% (0.4%-1.7%)

Inherited widow 0 0.1% (0.0%-1.0%) Never married 7.5% (5.2%-10.8%) 0.9% (0.4%-2.5%)

Total 100.0% 100.0%

52

Table 1 (continued): Social profile of respondents, by district District: Urban/peri-urban Rural Base 800 800 Column % (95% CI) Column % (95% CI) Compound belongs to (qn06) p<.0001

Husband’s extended family 25.8% (22.7%-29.1%) 46.3% (39.4%-53.4%) Wife’s extended family 15.0% (11.9%-18.7%) 8.7% (6.3%-11.7%)

Husband 13.6% (9.9%-18.5%) 35.6% (29.8%-41.8%) Woman 1.0% (0.5%-2.2%) 0.1% (0.0%-1.0%)

Rented from a landlord 40.0% (34.5%-45.8%) 8.5% (3.6%-18.7%) Other 4.6% (2.8%-7.5%) 0.8% (0.3%-1.9%) Total 100.0% 100.0%

(Mobile) phone in compound (qn07) p<.0001

Yes 73.5% (67.4%-78.8%) 35.7% (26.3%-46.5%) No 26.5% (21.2%-32.6%) 64.3% (53.5%-73.7%)

Total 100.0% 100.0%

Years of education (derived from qn08, qn08a, qn08b) p<.0001 None 42.2% (37.0%-47.6%) 63.8% (55.8%-71.2%)

1-5 years 18.3% (15.8%-21.1%) 21.3% (16.4%-27.2%) >5 years 36.8% (31.8%-42.1%) 12.1% (9.0%-16.1%)

Been to school but unspecified for how many years 1 2.8% (1.8%-4.1%) 2.8% (1.6%-4.8%) Total 100.0% 100.0%

Years of Western/Tubab education (derived from qn08, qn08a)

p<.0001

None 55.1% (50.3%-59.8%) 84.6% (79.5%-88.6%) 1-5 years 10.9% (9.0%-13.1%) 5.9% (3.6%-9.3%) >5 years 31.3% (26.5%-36.5%) 6.8% (4.5%-10.1%)

Been to school but unspecified for how many years of Western/Tubab education 1

2.8% (1.8%-4.1%)

2.8% (1.6%-4.9%)

Total 100.0% 100.0%

Years of Koranic education (derived from qn08, qn08b)

p=.3202

None 76.4% (72.6%-79.8%) 74.2% (65.6%-81.2%) 1-5 years 14.5% (12.1%-17.3%) 18.2% (12.9%-25.2%) >5 years 6.4% (4.6%-8.9%) 4.8% (3.1%-7.4%)

Been to school but unspecified for how many years of Koranic education 2

2.8% (1.8%-4.1%)

2.8% (1.6%-4.9%)

Total 100.0% 100.0%

53

Table 1 (continued): Social profile of respondents, by district District: Urban/peri-urban Rural Base 800 800 Column % (95% CI) Column % (95% CI) Do any activities that earn income in money? (qn09) 3

p<.0001 Farming 1.3% (0.5%-3.0%) 76.7% (63.9%-86.0%)

p=.0096 Vegetable gardening 6.4% (2.6%-14.8%) 20.9% (13.7%-30.6%)

p=.0014 Petty trading 40.3% (35.9%-44.8%) 23.1% (16.1%-32.1%)

p=.0008 Fish processing 2.8% (0.6%-11.0%) 0.1% (0.0%-1.0%)

p=.0976 Business or long-distance trade 2.0% (1.2%-3.3%) 6.6% (0.2%-2.4%)

p=.1316 Teacher/professional 1.1% (0.6%-2.0%) 0.3% (0.0%-1.9%)

p<.0001 Other 51.2% (44.7%-57.7%) 24.2% (18.7%-30.7%)

Husband’s years of education (qn10, qn10a, qn10b) 4, 5 p=.0001

None 18.7% (14.3%-24.1%) 32.2% (24.5%-40.9%) 1-5 years 3.6% (2.6%-5.1%) 7.1% (4.7%-10.5%) 5+ years 28.2% (24.8%-31.8%) 14.9% (11.0%-19.9%)

Husband has been to school but don’t know no. of years of schooling

48.3% (42.3%-54.3%)

44.1% (36.5%-52.0%)

Don’t know if husband has been to school 1.3% (0.6%-2.6%) 1.8% (0.9%-3.4%) Total 100.0% 100.0%

Husband’s years of Western/Tubab education (derived from qn10, qn10a) 4, 5

p<.0001

None 19.0% (14.5%-24.5%) 32.2% (24.5%-40.9%) 1-5 years 2.8% (1.9%-4.1%) 2.9% (1.8%-4.6%) 5+ years 24.1% (20.7%-28.0%) 4.9% (3.1%-7.7%)


52.9% (46.9%-58.8%)

58.2% (49.9%-66.1%)


Husband’s years of Koranic education (derived from qn10, qn10b) 4, 6

p<.0001

None 19.1% (14.6%-24.7%) 32.2% (24.5%-41.0%) 1-5 years 3.1% (1.9%-4.9%) 5.2% (3.3%-8.1%) 5+ years 4.6% (3.0%-6.9%) 10.6% (7.6%-14.6%)


72.0% (65.5%-77.6%)

50.3% (42.6%-58.0%)


54

Table 1 (continued): Social profile of respondents, by district

District: Urban/peri-urban Rural Base 800 800 Column % (95% CI) Column % (95% CI)

Husband’s usual work (qn11) 3, 4 p<.0001

Farmer 2.4% (1.1%-5.0%) 59.0% (48.3%-68.9%) p=.1214

Trader 18.8% (15.5%-22.6%) 14.4% (10.8%-19.1%) p=.0485

Fisherman 3.8% (0.8%-15.3%) 0.8% (0.4%-1.7%) p=.3152

Alkalo 0.1% (0.0%-1.0%) 0 p=.8063

Imam/Marabout 3.1% (1.9%-4.9%) 3.4% (1.7%-6.8%) p=.0071

Teacher/professional 8.4% (6.2%-11.3%) 3.7% (2.2%-6.2%) p=.0080

Trade or craft (e.g. mason) 20.2% (17.8%-22.9%) 12.9% (9.4%-17.5%) p=.3013

Student or apprentice 0.4% (0.1%-1.3%) 0.1% (0.0%-1.0%) p=.0070

Retired 1.5% (0.6%-4.0%) 0.1% (0.0%-1.0%) p=.0124

Other 40.2% (35.6%-45.0%) 29.8% (24.0%-36.4%) p=.0013

Don’t know 3.1% (2.0%-4.6%) 0.8% (0.4%-1.7%) Husband travels away to work 4 p<.0001

No 96.9% (95.4%-98.0%) 99.2% (98.3%-99.6%) Yes 3.1% (2.0%-4.6%) 0.8% (0.4%-1.7%)

Total 100.0% 100.0%

Notes for Table 1: 1. There remains a highly statistically significant association between districts whether/not women who

reported going to school but who did not specify the number of years of education they had received, are in/excluded (p<.0001).

2. There is no statistically significant association between districts whether/not women who reported going to school but who did not specify the number of years of education they had received, are in/excluded (p=.4392 and p=.3324).

3. Respondents could reported more than one response so column % do not sum to 100%. 4. Among women reporting that they were currently married to either their 1st, 2nd or a later husband. 5. There remains a highly statistically significant association between districts whether/not women who

reported that their husbands went to school but who did not specify the number of years of education they had received, are in/excluded (p<=.0001).

6. Excluding women who reported that their husbands went to school but who did not specify the number of years of education they had received results in a non-statistically significant association (p=.6017).

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Table 2: Timing of vaccinations, by district

District: Urban/peri-urban Rural Vaccination

Timing

Column % (95% CI)

Column % (95% CI)

BCG Base: 761 764

p<.0001 Upto and including 6 weeks after birth 77.8% (74.6%-80.7%) 77.1% (73.5%-80.3%)

After 6 weeks after birth 11.7% (9.5%-14.4%) 20.1% (17.3%-23.3%) Not at all (by interview) 9.1% (7.1%-11.5%) 2.1% (1.1%-4.1%)

Vaccination date erroneous 1.5% (0.8%-2.7%) 0.7% (0.3%-1.9%) Total: 100.0% 100.0%

BCG summary measure of defaulting: Base: 750 759

p=.5525 ‘non-defaulter’ (upto and including 6 weeks after birth) 78.9% (76.0%-81.6%) 77.6% (74.1%-80.8%)

‘defaulter’ (after 6 weeks after birth/not at all by interview) 21.1% (18.4%-24.0%) 22.4% (19.2%-25.9%) Total: 100.0% 100.0%

DTP (3 month injections) Base: 761 764

p<.0001 Upto and including 8 months after birth 49.4% (43.7%-55.1%) 78.2% (74.6%-81.4%)

After 8 months after birth 32.6% (28.6%-36.8%) 12.4% (10.1%-15.2%) Not had all (by interview) 17.4% (14.6%-20.6%) 8.8% (6.1%-12.6%)

Vaccination date(s) erroneous 0.7% (0.3%-1.5%) 0.4% (0.1%-1.3%) Child aged under 8 months 0% 0.1% (0.0%-1.0%)

Total: 100.0% 100.0% DTP (3 month injections) summary measure of defaulting: Base: 756 760

p<.0001 ‘non-defaulter’ (upto and including 8 months after birth) 49.7% (44.1%-55.4%) 78.7% (75.1%-81.8%)

‘defaulter’ (after 8 months after birth/not at all by interview) 50.3% (44.6%-56.0%) 21.4% (18.2%-24.9%) Total: 100.0% 100.0%

Measles Base: 761 764

p=.0019 Upto and including 12 months after birth 71.0% (66.0%-75.5%) 81.0% (77.1%-84.4%)

12-15 months after birth 11.7% (9.0%-15.1%) 8.8% (6.5%-11.8%) >15 months after birth 4.1% (2.9%-5.8%) 1.8% (1.1%-3.1%)

Not at all (by interview) 12.0% (9.8%-14.5%) 7.0% (4.9%-9.8%) Vaccination date erroneous 0% 0%

Child aged under 12 months 1.3% (0.7%-2.4%) 1.4% (0.7%-2.9%) Total: 100.0% 100.0%

Measles summary measure of defaulting: Base: 751 754

p=.0007 ‘non-defaulter’ (upto and including 12 months after birth) 71.9% (67.0%-76.4%) 82.2% (78.4%-85.4%)

‘defaulter’ (after 12 months after birth/not at all by interview) 28.1% (23.6%-33.0%) 17.9% (14.6%-21.6%) Total:

57

Table 3: Social factors associated with general defaulting 1 District: Urban/peri-urban Rural Base Base Mean (95% CI) Mean (95% CI) Age of child in months p=.0131 - p=.5059 -

Non-defaulter 17.4 (17.1-17.7) 514 17.2 (16.8-17.6) 618 Defaulter 18.1 (17.5-18.7) 197 17.0 (16.5-17.6) 126

Row % (95% CI) OR (95% CI) Row % (95% CI) OR 95% CI) All 28.1% (23.6%-33.0%) - 751 17.9% (14.6%-21.6%) - 754 Appearance of compound (qn01) p=.0179 p=.0153 p=.0892 p=.1484

Wealthy 27.4% (17.8%-39.7%) 1.00 113 26.7% (17.7%-38.1%) 1.00 63 Medium 21.3% (15.6%-28.4%) 0.72 (0.38-1.36) 305 15.7% (11.3%-21.4) 0.51 (0.25-1.03) 212

Poor 34.3% (27.5%-41.8%) 1.38 (0.72-2.63) 321 17.3% (14.4%-21.6%) 0.58 (0.33-1.02) 468 Mother’s category of reproductive life (qn02)

p=.0499

p=.0184

p=.0209

p=.0444

Young woman 18.0% (11.5%-27.1%) 1.00 100 11.5% (6.1%-20.9%) 1.00 65 Newly married with few children 26.8% (21.2%-33.3%) 1.67 (0.86-3.21) 325 15.0% (11.3%-19.7%) 1.35 (0.69-2.67) 290

Woman in middle of reproduction 30.8% (24.3%-38.2%) 2.02 (1.11-3.69) 234 23.4% (18.5%-29.2%) 2.35 (1.15-4.79) 268 Woman at end of reproduction/old woman 36.6% (25.0%-50.1%) 2.63 (1.38-5.01) 71 16.2% (9.6%-26.0%) 1.48 (0.60-3.67) 124

Number of children (qn03) p=.0214 p=.0138 p=.0539 p=.1818

1 16.7% (10.1%-26.3%) 1.00 90 12.2% (6.5%-21.9%) 1.00 57 2 25.3% (18.8%-33.1%) 1.69 (0.82-3.49) 166 9.9% (5.6%-17.1%) 0.79 (0.39-1.61) 135 3 35.65 (26.6%-45.8%) 2.76 (1.25-6.13) 132 17.6% (11.3%-26.3%) 1.53 (0.63-3.72) 109 4 25.8% (17.4%-36.5%) 1.74 (0.77-3.92) 93 21.9% (14.8%-31.2%) 2.01 (0.86-4.71) 109 5 34.8% (25.9%-44.9%) 2.67 (1.39-5.13) 69 25.3% (16.3%-37.0%) 2.42 (1.09-5.41) 97

6+ 34.0% (24.3%-45.4%) 2.58 (1.38-4.83) 97 17.8% (11.9%-25.6%) 1.55 (0.69-3.45) 166

58

Table 3 (continued): Social factors associated with general defaulting 1 District: Urban/peri-urban Rural Base Base Row % (95% CI) OR (95% CI) Row % (95% CI) OR 95% CI) Ethnic group (qn04) p=.0282 p=.0505 p=.8906 p=.8876

Mandinka 22.0% (16.7%-28.4%) 1.00 241 18.6% (13.6%-24.8%) 0.88 (0.50-1.55) 247 Fula 38.7% (29.7%-48.6%) 2.24 (1.33-3.77) 155 16.7% (11.4%-24.0%) 0.88 (0.06-13.5) 265

Wolof 32.9% (23.4%-44.1%) 1.74 (0.99-3.05) 82 [16.7% (1.4%-74.5%)] [N/A]] [6] Serrehuli 28.6% (13.7%-50.2%) 1.42 (0.53-3.79) 28 17.9% (12.9%-24.2%) 0.95 (0.57-1.60) 215

Jola 25.8% (17.4%-36.5%) 1.23 (0.66-2.29) 128 [0%] [N/A] 2 Other 28.1% (23.5%-33.2%) 1.22 (0.70-2.15) 117 [27.8% (10.2%-56.6%)] [1.69 (0.50-5.70) ] 19

Currently married (qn05) p=.7504 p=.7867 p=.0152 p=.0172

Married 1st husband 29.1% (24.3%-34.5%) 1.00 587 16.3% (13.1%-20.0%) 1.00 642 Married 2nd+ husband 24.4% (15.8%-35.7%) 0.79 (0.46-1.35) 86 29.4% (20.4%-40.3%) 2.14 (1.29-3.53) 97

Previously married 23.8% (9.2%-49.2%) 0.76 (0.26-2.23) 21 [12.5% (1.5%-57.6%)] [0.73 (0.08-7.15)] [10] Never married 25.0% (13.6%-41.5%) 0.81 (0.37-1.77) 56 [0%] [N/A] [5]

Compound belongs to (qn06) p=.0355 p=.0355 p=.8478 p=.9686

Husband’s extended family 24.1% (18.6%-30.6%) 1.00 191 17.3% (12.9%-22.9%) 1.00 368 Wife’s extended family 25.4% (17.7%-35.1%) 1.08 (0.68-1.69) 114 17.7% (10.1%-29.3%) 1.03 (0.50-2.12) 71

Husband 23.1% (15.2%-33.5%) 0.95 (0.57-1.58) 104 18.4% (13.3%-25.0%) 1.08 (0.66-1.76) 249 Woman [12.5% (2.0%-50.2%)] [0.45 (0.06-3.35)] [8] [0] [N/A] [1]

Rented from a landlord 34.3% (28.9%-40.2%) 1.65 (1.21-2.24) 300 19.3% (14.0%-26.0%) 1.14 (0.67-1.94) 57 Other 23.5% (12.0%-41.0%) 0.97 (0.40-2.34) 34 [0] [N/A] [7]

(Mobile) phone in compound (qn07) p=.0062 p=.007 p=.7781 p=.778

Yes 24.6% (19.8%-30.0%) 1.00 550 17.3% (12.4%-23.5%) 1.00 269 No 37.8% (29.5%-46.9%) 1.87 (1.21-2.90) 201 18.3% (14.1%-23.3%) 1.07 (0.65-1.76) 483

59

Table 3 (continued): Social factors associated with general defaulting 1 District: Urban/peri-urban Rural Base Base Row % (95% CI) OR (95% CI) Row % (95% CI) OR 95% CI)

Years of (any) education (derived from qn08, qn08a, qn08b) 2

p=.0069

p=.0002

p=.4592

p=.5339

None 31.7% (26.7%-37.3%) 1.00 312 19.2% (15.4%-23.7%) 1.00 471 1-5 32.6% (24.6%-41.9%) 1.04 (0.76-1.43) 141 14.1% (8.7%-22.1%) 0.69 (0.38-1.25) 170 >5 21.5% (16.9%-26.8%) 0.59 (0.46-0.75) 275 15.9% (10.8%-22.6%) 0.79 (0.50-1.24) 88

Been to school but unspecified for how many years

31.8% (16.3%-52.8%)

1.00 (0.41-2.47)

22

23.8% (7.3%-55.3%)

1.31 (0.33-5.20)

25

Years of Western/Tubab education (derived from qn08, qn08a) 2

p=.0004

p=.0001

p=.6799

p=.5851

None 32.4% (27.1%-38.3%) 1.00 410 17.6% (14.3%-21.5%) 1.00 639 1-5 32.6% (23.5%-43.2%) 1.01 (0.66-1.52) 86 13.6% (5.9%-28.3%) 0.74 (0.29-1.85) 44 >5 18.5% (14.3%-23.7%) 0.47 (0.36-0.63) 232 20.5% (13.6%-29.5%) 1.20 (0.74-1.93) 45

Been to school but unspecified how many years of Western/Tubab education

31.8% (16.3%-52.8%)

0.97 (0.38-2.45)

22

23.8% (14.5%-21.6%)

1.46 (0.36-5.92)

25

Years of Koranic education (derived from qn08, qn08b) 2

p=.9300

p=.8732

p=.2653

p=.3334

None 27.7% (23.1%-32.9%) 1.00 570 19.3% (15.7%-23.6%) 1.00 542 1-5 28.4% (19.5%-39.4%) 1.04 (0.66-1.64) 109 12.0% (6.5%-21.3%) 0.57 (0.28-1.18) 147 >5 30.6% (17.7%-47.5%) 1.15 (0.58-2.28) 49 11.8% (5.2%-24.5%) 0.56 (0.22-1.39) 39

Been to school but unspecified how many years of Koranic education

31.8% (16.3%-52.8%)

1.22 (0.50-2.96)

22

23.8% (7.3%-55.3%)

1.30 (0.33-5.12)

25

60


Do any activities that earn income in money? (qn09) 3

[p=.6637] [p=.665] p=.052 p=.053 Farming [33.3% (13.2%-62.2%)] [1.29 (0.40-4.21)] [9] 16.4% (13.1%-20.5%) 0.67 (0.44-1.01) 592

p=.0688 p=.665 p=.6535 p=.654 Vegetable gardening 12.5% (4.3%-31.3%) 0.35 (0.11-1.14) 48 16.7% (11.0%-24.4%) 0.90 (0.57-1.43) 166

p=.6929 p=.665 p=.5379 p=.538 Petty trading 28.8% (22.7%-35.9%) 1.07 (0.76-1.50) 302 15.9% (10.1%-24.2%) 0.84 (0.47-1.49) 166

[p=.5845] [p=.585] p=.6412 [N/A] Fish processing [31.8% (18.3%-49.3%)] [1.21 (0.60-2.41)] [22] [0%] [N/A] [1]

[p=.0961] [p=.134] [p=.8301] [p=.830] Business or long-distance trade [7.1% (0.9%-40.6%)] [0.19 (0.02-1.70)] [14] [20.0% (6.6%-47.0%)] [1.15 (0.30-4.37)] [5]

[p=.7024] [p=.665] [p=.6432] [N/A] Teacher/professional [22.2% (5.2%-59.9%)] [0.73 (0.14-3.82)] [9] [0%] [N/A] [2]

p=.5369 p=.537 p=.0228 p=.024 Other 29.2% (23.7%-35.5%) 1.13 (0.75-1.71) 383 23.7% (18.2%-30.3%) 1.64 (1.07-2.50) 182

Husband’s years of (any) education (derived from qn08, qn08a, qn08b) 4, 5

p=.0136

p=.0282

p=.3755

p=.3752

None 33.3% (25.8%-41.9%) 1.00 123 17.6% (12.5%-24.1%) 1.00 230 1-5 38.5% (22.0%-58.0%) 1.25 (0.55-2.86) 26 18.0% (9.2%-32.2%) 1.03 (0.43-2.49) 53 >5 19.8% (12.9%-29.1%) 0.49 (0.30-0.80) 187 11.8% (6.5%-20.3%) 0.63 (0.30-1.29) 113


30.5% (25.7%-35.7%)

0.88 (0.58-1.32)

328

20.1% (15.7-25.5)

1.18 (0.71-1.96)

329

Don’t know whether/not husband went to school

44.4% (23.9%-33.6%)

1.6 (0.53-4.79)

9

25.0% (9.0%-52.9%)

1.56 (0.43-5.66)

14

61


Husband’s years of Western/Tubab education (derived from qn08, qn08a) 4, 5

p=.0007

p=.0137

p=.7379

p=.3122

None 33.9% (26.0%-42.8%) 1.00 124 17.6% (12.5%-24.1%) 1.00 230 1-5 35.0% (18.1%-56.8%) 1.05 (0.40-2.78) 20 20.0% (5.5%-51.9%) 1.17 (0.27-5.01) 20 >5 16.2% (10.1%-24.8%) 0.38 (0.22-0.65) 161 9.4% (2.9%-26.3%) 0.49 (0.14-1.71) 35


31.5% (26.7%-36.7%)

0.90 (0.60-1.33)

359

18.7% (14.6%-23.5%)

1.08 (0.66-1.77)

439


44.4% (22.2%-69.2%)

1.56 (0.52-4.69)

9

23.1% (8.2%-50.1%)

1.41 (0.39-5.04)

15

Husband’s years of Koranic education (derived from qn08, qn08b) 4, 5

p=.1874

p=.2769

p=.8386

p=.8241

None 33.6% (25.8%-42.4%) 1.00 125 17.6% (12.5%-24.1%) 1.00 230 1-5 28.6% (12.7%-52.3%) 0.79 (0.31-1.99) 21 18.9% (8.6%-36.7%) 1.09 (0.39-3.09) 40 >5 38.7% (21.8%-58.8%) 1.25 (0.55-2.81) 31 13.9% (7.6%-24.0%) 0.76 (0.36-1.60) 82

Been to school but unspecified how many years of Koranic education

26.3% (21.5%-31.7%)

0.70 (0.46-1.07)

487

18.9% (14.6%-24.1%)

1.09 (0.66-1.79)

372


44.4% (22.2%-69.2%)

1.58 (0.53-4.75)

9

23.1% (8.2%-50.1%)

1.41 (0.39-5.04)

15

Husband travels away to work 4 p=.6861 p=.686 p=.0422 p=.043

Yes 29.1% (23.4%-35.6%) 1.00 395 21.2% (16.1%-27.4%) 1.00 265 No 27.7% (22.2%-33.9%) 0.93 (0.65-1.33) 264 16.0% (12.7%-19.9%) 0.71 (0.51-0.99) 467

62

Table 3 (continued): Social factors associated with general defaulting 1 District: Urban/peri-urban Rural Base Base Row % (95% CI) OR (95% CI) Row % (95% CI) OR 95% CI) Husband’s usual work (qn11) 3, 4 p=.0803 p=.116 p=.3307 p=.331

Farmer [7.1% (0.9%-39.0%)] [0.19 (0.02-1.54)] [14] 16.9% (13.0%-21.7%) 0.84 (0.59-1.20) 442 p=.2936 p=.294 p=.2074 p=.209

Trader 32.3% (23.9%-42.1%) 1.25 (0.82-1.90) 127 22.3% (14.8%-32.2%) 1.39 (0.83-2.33) 105 p=.6709 p=.671 [p=.3097] [N/A]

Fisherman 26.9% (23.9%-33.6%) 0.92 (0.62-1.37) 26 [0%] [N/A] [8] p=.5297 [N/A] [N/A] [N/A]

Alkalo [0%] [N/A] [1] [N/A] [N/A] 0 p=.7518 p=.752 p=.0060 p=.008

Imam/Marabout 31.8% (14.5%-56.3%) 1.18 (0.42-3.30) 22 34.8% (21.4%-51.2%) 2.54 (1.30-4.94) 26 p=.8822 p=.882 p=.1256 p=.140

Teacher/professional 27.6% (16.2%-42.9%) 0.95 (0.47-1.90) 58 7.7% (2.1%-24.8%) 0.37 (0.10-1.41) 28 p=.5352 p=.535 p=.9605 p=.960

Trade or craft (e.g. mason) 30.8% (23.4%-39.4%) 1.15 (0.73-1.80) 133 17.8% (11.1%-27.3%) 0.99 (0.58-1.68) 96 [p=.2748] [N/A] [p=.6474] [N/A]

Student or apprentice [0%] [N/A] [3] [0%] [N/A] 1 [p=.0693] [p=.089] [p=.6474] [N/A]

Retired 10.0% (2.5%-32.9%) [0.27 (0.06-1.23)] [11] [0%] [N/A] 1 p=.5406 p=.541 p=.3337 p=.334

Other 27.2% (20.6%-34.9%) 0.90 (0.63-1.28) 272 16.0% (12.1%-20.9%) 0.83 (0.56-1.23) 225 [p=.2045] [p=.209] [p=.3373] [p=.351]

Don’t know [40.0% (22.2%-61.0%)] [1.70 (0.73-3.94)] [20] [33.3% (7.7%-75.0%)] [2.31 (0.38-13.9)] [6] Child wearing a Talisman/juju at interview (qn46) 5

p=.4337

p=.434

p=.6389

p=.684

No 29.5% (24.0%-35.7%) 1.00 322 18.5% (14.5%-23.3%) 1.00 372 Yes 26.5% (20.8%-33.1%) 0.86 (0.59-1.26) 438 17.0% (12.1%-23.4%) 0.90 (0.55-1.49) 392

63

Table 3 (continued): Social factors associated with general defaulting 1 District: Urban/peri-urban Rural Base Base Column % (95% CI) OR (95% CI) Column % (95% CI) OR 95% CI) Who else has given protection/treatment to child? (qn44) 3, 6

p=.1946 p=.195 p=.5351 p=.535 No-one 31.5% (25.5%-38.1%) 1.24 (0.89-1.74) 159 19.5% (14.0%-26.5%) 1.15 (0.72-1.84) 140

p=.4666 p=.467 p=.2098 p=.214 Herbalist 31.8% (20.4%-45.9%) 1.23 (0.70-2.17) 66 11.8% (6.1%-21.8%) 0.59 (0.26-1.37) 84

p=.0876 p=.089 p=.4387 p=.439 MRC 21.8% (14.7%-31.0%) 0.66 (0.41-1.07) 170 16.4% (12.4%-21.4%) 0.85 (0.55-1.31) 321

p=.6274 p=.627 p=.9828 p=.983 Marabout 26.8% (20.5%-34.3%) 0.91 (0.63-1.33) 291 17.7% (12.2%-25.0%) 0.99 (0.59-1.67) 277

p=.0804 p=.081 p=.5208 p=.521 Elderly woman/man 22.3% (16.0%-30.2%) 0.68 (0.44-1.05) 175 16.1% (10.7%-23.55) 0.86 (0.53-1.39) 200

p=.0535 p=.054 p=.4365 p=.440 Family doctor/private clinic 31.6% (25.2%-38.9%) 1.32 (1.00-1.75) 256 12.5% (4.4%-30.5%) 0.64 (0.20-2.05) 64

p=.5424 p=.543 p=.6078 p=.609 Other 31.9% (19.3%-47.9%) 1.23 (0.62-2.42) 47 14.3% (5.3%-33.2%) 0.76 (0.26-2.22) 48

[p=.4963] [p=.512] [p=.6424] [-] Don’t know [50.0% (5.1%-94.9%)] [2.59 (0.14-48.1)] [2] [0.0%] [-] [2]

64

Table 3 (continued): Social factors associated with general defaulting 1 District: Urban/peri-urban Rural Base Base Column % (95% CI) OR (95% CI) Column % (95% CI) OR 95% CI) What are the main problems with the IWC? (qn42) 3, 6

p=.8807 p=.881 p=.6455 p=.646 No problems 27.2% (22.7%-32.3%) 1.03 (0.72-1.46) 481 18.2% (14.3%-22.8%) 1.12 (0.68-1.84) 451

[p=.2085] [p=.219] p=.3124 p=.314 Travel problems [15.0% (5.2%-36.3%)] [0.47 (0.14-1.60)] [20] 14.0% (8.0%-23.3%) 0.70 (0.37-1.38) 129

[p=.6800] [p=.8807] p=.2942 p=.296 Effects of sun/rain in travel [33.3% (10.4%-68.2%)] [1.35 (0.31-5.91)] [6] 14.0% (9.0%-21.0%) 0.75 (0.43-1.30) 45

p=.3052 p=.306 p=.6622 p=.662 Crowds, long waits 30.1% (22.4%-39.0%) 1.21 (0.83-1.76) 163 16.2% (10.5%-24.2%) 0.89 (0.51-1.55) 153

p=.3882 - Bad people or witches 0.0% - [2] 0

p=.1560 p=.158 [p=.2523] [p=.279] Disrespectful staff 20.6% (12.6%-31.7%) 0.68 (0.39-1.17) 68 [6.3% (0.7%-38.5%)] [0.31 (0.03-2.72)] [17]

p=.9965 p=.997 [p=.1198] [p=.129] Financial problems 27.0% (13.4%-47.1%) 1.00 (0.44-2.29) 37 [31.6% (13.8%-57.2%)] [2.23 (0.78-6.36)] [22]

- - - - Link with family planning - - 0 - - 0

- - - - Discouragement from husband or family - - 0 - - 0

65

Notes for Table 3: 1. Defined as date of measles vaccination more than 12 months after date of birth 2. In earlier version of this Table those who reported that they had been to school but who did not report the number of years of education they had received

were coded as ‘none’ for these derived categorical variables, but in this version of the table these respondents are considered in a separate category. The statistical significance of these associations largely remains unchanged. Also note 5: as in note 3 but with respect to the husband’s education

3. Respondents could report more than one response. 4. Among respondents who reported that they were currently married. 5. Interpretation example: of those urban/peri-urban respondents who reported that their child was wearing a Talisman/juju, 29.5% reported measles defaulting

in comparison to 26.5% of those urban/peri-urban respondents who reported that their child was not wearing a Talisman/juju. This is not a statistically significant difference (p=.434).

6. Interpretation example: of those urban/peri-urban respondents who reported that no-one had given their child protection/treatment, 31.5% reported measles defaulting. This is not statistically significantly different to those who reported that someone had given their child protection/treatment (100%-31.5%, p=.1946).

66

Table 3a: Reasons for not going to the IWC at the usual time (qn26 B), by district (Of those reporting not to have gone to the IWC at the usual time –caution: small numbers!)

Urban/peri-urban Rural

n=14 n=20 Row % (95% CI) Row % (95% CI) p=.3498

I had to travel 14.3% (3.2%-46.0%) 5.3% (0.9%-26.2%) p=.6696

I was unwell 21.4% (6.3%-52.6%) 15.8% (5.7%-36.6%) p=.7814

Child was unwell 21.4% (7.1%-49.4%) 26.3% (7.2%-62.2%) p=.1114

Financial problems 14.3% (3.2%-46.0%) 0.0% p=.2079

Distance/transport problems 7.1% (1.0%-36.9%) 0.0% p=.4283

Family event 0.0% 5.3% (0.6%-34.3%) -

Childcare/problems with older children 0.0% 0.0% -

Public holiday 0.0% 0.0% p=.7812

Too much work 7.1% (0.8%-41.1%) 10.5% (1.2%-52.6%) p=.4283

Problems with IWC 0.0% 5.3% (0.6%-34.3%) p=.6306

Other 28.6% (10.0%-59.1%) 36.8% (18.3%-60.4%)

67

Table 4: BCG-specific factors associated with defaulting on the BCG vaccination, by district

District: Urban/peri-urban Rural Base Base Mean (95% CI ) - Mean (95% CI) - Age of child in weeks when first went to IWC (qn20)

p=.0074 - p=.0009 -


Row % (95% CI) OR (95% CI) Row % (95% CI) OR (95% CI) Activities at first visit to IWC (qn22) 1

p=.0002 p<.0001 p=.0603 p=.072 Registration/change cards 18.8% (16.2%-21.8%) 0.41 (0.26-0.65) 653 22.0% (18.6%-25.7%) 0.34 (0.10-1.11) 744

p=.3204 p=.326 p=.2011 N/A Weighing 20.7% (18.0%-23.8%) 0.59 (0.20-1.73) 724 22.5% (19.2%-26.2%) N/A 748

p=.4977 p=.499 p=.8597 p=.860 Injections 20.7% (17.7%-24.1%) 0.77 (0.35-1.69) 695 22.3% (19.0%-25.9%) 0.86 (0.15-4.86) 741

[N/A] [N/A] [N/A] [N/A] Visiting MRC [N/A] [N/A] [0] [0%] [N/A] [9]

[p=.0239] [p=.041] [p=.6512] [p=.655] Child seen/treated for illness [57.1% (21.6%-86.6%)] [5.10 (1.08-24.1)] [7] [33.3% (3.8%-86.3%)] [1.75 (0.14-21.6)] [3]

[p=.5074] [p=.514] [p=.7831] [p=.783] Other [12.5% (2.1%-49.1%)] 0.53 (0.08-3.72) [8] [25.0% (9.4%-51.8%)] 1.16 (0.38-3.54) [13]

Mean (95% CI) - Mean (95% CI ) -

Age of child in weeks when cards changed (qn23) 2

-

p=.1990

-


68

Table 4 (continued): BCG-specific factors associated with defaulting on the BCG vaccination, by district

District: Urban/peri-urban Rural Base Base

Row % (95% CI) OR (95% CI) Row % (95% CI) OR (95% CI) Where got idea from to take child to IWC (qn24) 1

p=.1334 p=.134 p=.3637 p=.364 Knew importance from earlier education 24.6% (18.7%-31.5%) 1.34 (0.91-1.99) 224 24.5% (18.6%-31.6%) 1.17 (0.82-1.67) 224

p=.4458 p=.446 p=.1957 p=.197 Other mothers 19.4% (15.4%-24.2%) 0.87 (0.61-1.25) 201 26.4% (19.7%-34.55) 1.35 (0.85-2.16) 223

p=.2666 p=.268 p=.2833 p=.288 Own mother 16.8% (10.7%-25.55) 0.73 (0.42-1.29) 101 15.4% (6.6%-31.8%) 0.60 (0.23-1.56) 74

p=.9118 p=.912 p=.3732 p=.374 Husband 21.6% (12.3%-35.2%) 1.04 (0.52-2.07) 37 27.2% (16.3%-41.6%) 1.33 (0.70-2.56) 81

p=.7657 p=.766 p=.6056 p=.606 I knew myself/always known 21.5% (17.5%-26.1%) 1.05 (0.76-1.44) 312 23.3% (18.8%-28.4%) 1.11 (0.74-1.65) 412

[p=.6135] [p=.619] [p=.7633] [p=.765] Mother in law [33.3% (3.9%-86.2%)] [1.88 (0.14-24.6)] [3] [16.7% (1.6%-70.5%)] 0.69 (0.06-8.52) [6]

p=.0196 p=.021 p=.2366 p=.239 Health care staff at delivery 14.6% (10.0%-20.7%) 0.57 (0.35-0.91) 185 17.0% (9.7%-28.0%) 0.67 (0.33-1.33) 120

[p=.0554] [N/A] p=.9279 p=.928 TBA or VHA [100.0%] [N/A] [1] 21.7% (9.1%-43.5%) 0.96 (0.35-2.59) 61

[p=.0430] [p=.059] [p=.3689] [N/A] Don’t know [50.0% (20.2%-79.8%)] [3.81 (0.90-15.3)] [6] [0%] [N/A] [6]

[N/A] [N/A] [p=.2634] [N/A] MRC worker [N/A] [N/A] [0] [0%] [N/A] [4]

p=.8652 p=.865 p=.0416 p=.045 Other 21.9% (12.8%-34.7%) 1.06 (0.55-2.05) 64 35.0% (22.1%-50.6%) 1.94 (1.02-3.71) 43

Feel that child had the first injections at a good time (qn25)

p=.1764

p=.1023

p=.5297

p=.5933

Yes 20.5% (17.9%-23.5%) 1.00 706 22.3% (19.1%-25.8%) 1.00 670 No 35.3% (19.6%-55.0%) 2.11 (0.99-4.52) 17 19.2% (10.8%-31.8%) 0.83 (0.41-1.67) 26

Don’t know 25.0% (12.4%-44.0%) 1.29 (0.54-3.09) 24 28.0% (14.8%-46.6%) 1.36 (0.62-2.97) 52

69

Table 4 (continued): BCG-specific factors associated with defaulting on the BCG vaccination, by district

Interaction with clinic staff on first visit (qn27) 1, 4

p=.0217 p=.022 p=.2195 p=.220 They were friendly/ respectful 16.8% (13.1%-21.4%) 0.64 (0.44-0.94) 303 24.2% (20.1%-29.0%) 1.25 (0.87-1.78) 342

[p=.7482] [p=.749] [p=.0322] [p=.036] They embarrassed me [25.0% (7.3%-58.4%)] [1.26 (0.30-5.29)] [16] [38.5% (23.1%-56.5%)] [2.22 (1.06-4.68)] [14]

p=.5033 p=.504 p=.3433 p=.344 They were helpful 21.6% (18.5%-25.1%) 1.21 (0.68-2.15) 601 23.0% (19.4%-27.1%) 1.25 (0.78-2.01) 602

[p=.6409] [p=.642] [p=.6965] [p=.698] They were rude [16.7% (5.2%-42.4%)] [0.75 (0.21-2.67)] [18] [16.7% (3.1%-56.0%)] [0.70 (0.11-4.57)] [6]

[p=.3298] [p=.364] [p=.6076] [N/A] Some were not there [50.0% (5.1%-94.9%)] [3.77 (0.20-70.5)] [2] [0%] [N/A] [2]

Notes for Table 4:

1. Respondents could report more than one response. 2. If cards not changed on first visit 3. Among respondents who reported that their child did not go to the IWC at the usual time. 4. Among all respondents.

70

Table 5: DTP-specific factors associated with defaulting on the DTP vaccination, by district

District: Urban/peri-urban Rural Base Base Row % (95% CI) OR (95% CI) Row % (95% CI) OR (95% CI) Did the baby have its ‘3 month injections’ (qn28)

p=.2510

p=.3197

p=.1283

p=.661

Yes 50.2% (44.3%-56.1%) 1.00 749 21.7% (18.4%-25.4%) 1.00 745 No [80.0% (28.5%-97.6%)] [3.97 (0.38-471.9)] [5] [100.0%] [N/A] [1]

Don’t know [71.4% (30.8%-93.4%)] [2.48 (0.43-14.3)] [7] [17.7% (6.2%-41.0%)] [0.77 (0.24-2.50)] [17]

Did child have any reactions to the injections (qn31) 1, 2

p=.4990 p=.499 p=.3469 p=.348 No reaction/effect 53.2% (42.6%-63.5%) 1.16 (0.75-1.77) 141 25.0% (17.1%-35.0%) 1.25 (0.77-2.04) 130

p=.1226 p=.123 p=.7463 p=.746 Mild fever 48.0% (41.3%-54.7%) 0.77 (0.55-1.08) 488 21.4% (18.0%-25.4%) 0.95 (0.68-1.32) 539

p=.0835 p=.087 p=.2073 p=.217 Serious fever 62.8% (47.9%-75.5%) 1.73 (0.92-3.24) 51 12.0% (4.2%-30.0%) 0.48 (0.15-1.57) 27

p=.3610 p=.361 p=.4215 p=.422 Mild swelling 47.5% (39.7%-55.4%) 0.86 (0.62-1.20) 202 23.4% (19.2%-28.2%) 1.15 (0.81-1.61) 216

[p=.4627] [p=.465] [p=.3799] [p=.396] Serious swelling [59.1% (34.6%-79.8%)] [1.44 (0.53-3.97)] [22] [10.0% (1.2%-49.6%)] [0.40 (0.04-3.54)] [10]

p=.87.13 p=.871 p=.7939 p=.794 Mild crying 49.8% (42.0%-57.7%) 0.97 (0.68-1.39) 305 21.4% (17.8%-25.6%) 0.92 (0.71-1.30) 443

p=.2533 p=.255 p=.5009 p=.503 Serious crying 43.1% (30.8%-56.4%) 0.74 (0.43-1.26) 51 16.7% (7.1%-34.3%) 0.71 (0.26-1.96) 26

[p=.1773] [p=.184] [p=.8712] [p=.871] Another effect [65.1% (41.9%-82.7%)] [1.87 (0.73-4.76)] [20] [23.5% (7.7%-53.2%)] [1.11 (0.29-4.27)] [20]

[p=.6320] [p=.639] [p=.5976] [N/A] A delayed effect [66.7% (44.4%-56.1%)] [1.98 (0.11-37.4)] [3] [0%] [N/A] [1]

71

Table 5 (continued): DTP-specific factors associated with defaulting on the DTP vaccination, by district

District: Urban/peri-urban Rural Base Base Row % (95% CI) OR (95% CI) Row % (95% CI) OR (95% CI) Feel that reactions were normal (qn32) 1

p=.1181

p=.2100

p=.0678

p=.1410

Yes 48.7% (42.8%-54.7%) 1.00 585 20.6% (17.4%-24.2%) 1.00 614 No 47.4% (29.1%-66.4%) 0.95 (0.46-1.96) 38 [20.0% (6.0%-49.6%)] [0.97 (0.23-4.12)] [10]

Don’t know [87.5% (42.6%-98.5%)] [7.37 (0.81-67.2)] [8] [50.0% (20.1%-79.9%)] [3.86 (0.98-15.2)] [13]

Feel that baby was given the right number of injections each time (qn33) 1

p=.4311

p=.4999

p=.0707

p=.0986

Yes 50.0% (44.0%-56.1%) 1.00 654 20.9% (17.8%-24.4%) 1.00 669 No 49.3% (37.4%-61.4%) 0.97 (0.63-1.50) 75 18.0% (9.7%-30.8%) 0.83 (0.39-1.75) 42

Don’t know 62.5% (42.5%-79.0%) 1.67 (0.70-3.95) 24 33.3% (21.2%-48.2%) 1.89 (1.03-3.46) 50

Easy/difficult for child to attend clinic around the time of the 3 month injections (qn34) 3

p=.9210

p=.9215

p=.5889

p=.5663

Easy 50.5% (44.6%-56.4%) 1.00 695 21.3% (18.0%-24.9%) 1.00 670 Difficult 50.9% (35.8%-65.8%) 1.01 (0.56-1.83) 59 25.6% (17.9%-35.2%) 1.27 (0.80-2.02) 84

Don’t know [60.0% (18.6%-90.8%)] [1.47 (0.22-10.0)] [5] [25.0% (3.0%-78.4%)] [1.23 (0.12-12.9)] [5]

72

Table 5 (continued): DTP-specific factors associated with defaulting on the DTP vaccination, by district

District: Urban/peri-urban Rural Base Base Row % (95% CI) OR (95% CI) Row % (95% CI) OR (95% CI)

Did child miss any clinic sessions around this time? (qn36) 3

p=.0117

p=.012

p=.1474

p=.148

Yes 56.7% (50.2%-63.0%) 1.00 275 25.8% (19.3%-33.6%) 1.00 188 No 47.1% (40.2%-54.1%) 0.68 (0.50-0.91) 480 20.1% (16.4%-24.4%) 0.72 (0.46-1.13) 558

If yes, did this worry you? (qn37) 5 p=.0504 p=.0793 p=.1860 p=.2304

Not worried 63.0% (48.1%-75.8%) 1.00 46 29.7% (17.9%-45.1%) 1.00 37 Worry about reactions of staff 60.0% (47.3%-71.5%) 0.88 (0.39-1.97) 50 20.0% (6.5%-47.3%) 0.59 (0.15-2.26) 15

Worry about multiple injections 45.2% (32.8%-58.2%) 0.48 (0.23-1.03) 73 40.0% (26.7%-55.0%) 1.58 (0.65-3.84) 27 Other 65.9% (55.2%-75.1%) 1.13 (0.49-2.60) 82 22.3% (14.0%-33.7%) 0.68 (0.30-1.52) 94

Notes for Table 5:

1. Among respondents who reported that their child had had its ‘3 month injections’. 2. Respondents could report more than one response. 3. Among all respondents. 4. Among respondents who reported that it was difficult for the child to attend the clinic around the time of the 3 month injections. 5. Among respondents who reported that their child missed some clinic sessions around the time of the 3 month injections.

73

Table 5a: Reasons for difficulty in attending the IWC around the time of the child’s 3-month injections (qn35 B), by district (Of those reporting that it was difficult for the child to attend the clinic around the time of the 3-month injections)

Urban/peri-urban Rural n=55 n=89 Column % (95% CI) Column % (95% CI) p=.0510

I had to travel 16.4% (8.7%-28.7%) 37.9% (19.5%-60.7%) p=.3805

I was unwell 5.5% (1.3%-20.6%) 2.3% (0.5%-9.2%) p=.3689

Child was unwell 5.5% (1.3%-20.0%) 2.3% (0.6%-8.9%) p=.0080

Financial problems 14.6% (7.1%-27.6%) 2.3% (0.6%-8.9%) p=.6063

Distance/transport problems 27.3% (16.4%-41.8%) 33.3% (16.8%-55.3%) p=.4625

Family event 0.0% 1.2% (0.1%-8.6%) p=.0045

Childcare/problems with older children 9.1% (4.0%-19.6%) 0.0% p=.4476

Public holiday 0.0% 1.2% (0.2%-8.3%) p=.5971

Too much work 25.5% (12.7%-44.5%) 32.2% (16.1%-54.1%) p=.5955

Problems with IWC 18.2% (9.8%-31.2%) 13.8% (5.5%-30.6%) p=.0107

Other 21.8% (13.3%-33.8%) 4.6% (1.3%-15.3%)

74

Table 6: Measles-specific factors associated with defaulting on the measles vaccination, by district

District: Urban/peri-urban Rural Row% (95% CI) OR (95% CI) Base Row % (95% CI) OR (95% CI) Base Has your child had the 9 month? injections (qn38)

p<.0001 p<.0001 p=.0170 p=.1128

Yes 25.2% (20.9%-30.1%) 1.00 711 17.1% (13.7%-21.0%) 1.00 698 No 73.5% (56.1%-85.8%) 8.26 (3.81-17.9) 34 [60.0% (18.3%-91.0%)] [7.30 (1.13-47.2)] [10]

Don’t know [43.85 924.0%-65.7%)] [2.31 (0.93-5.72)] [16] 18.8% (12.3%-27.5%) 1.12 (0.67-1.87) 55 Has your child had the 1 year injections? (qn39)

p=.1240 p=.1099 p=.1065 p=.0730

Yes 25.8% (21.3%-30.9%) 1.00 562 17.2% (13.7%-21.4%) 1.00 650 No 33.2% (25.8%-41.5%) 1.43 (1.01-2.02) 178 26.0% (17.8%-36.2%) 1.69 (1.07-2.66) 52

Don’t know 35.0% (16.7%-59.1%) 1.55 (0.56-4.29) 20 16.7% (10.3%-25.8%) 0.96 (0.52-1.79) 60

75

Table 7: Association between defaulting, by district

District: Urban/peri-urban Rural Column % (95% CI) Column % (95% CI) Number of times a defaulter

Base n=761 n=763 0 (none) 37.8% (32.4%-43.6%) 55.9% (51.7%-60.1%)

1 31.1% (27.8%-34.7%) 29.8% (26.7%-33.1%) 2 23.7% (20.0%-27.7%) 10.5% (8.7%-12.5%)

3 (all) 7.4% (5.5%-9.7%) 3.8% (2.6%-5.5%) Total 100.0% 100.0%

Of defaulters who default only once:

Base n=237 n=228 % BCG defaulters (only) 17.3% (12.5%-23.4%) 43.7% (36.2%-51.4%)

% 3 month defaulters (only) 69.2% (63.0%-74.8%) 34.7% (28.5%-41.6%) % measles defaulters (only) 13.5% (9.3%-19.2%) 21.6% (16.6%-27.6%)

Total 100.0% 100.0% Of defaulters who default twice:

Base n=180 n=76 % not BCG defaulters 60.0% (52.8%-66.8%) 42.7% (32.9%-53.1%)

% not 3 month defaulters 8.3% (4.7%-14.4%) 28.0% (18.4%-40.2%) % not measles defaulters 31.7% (25.0%-39.2%) 29.3% (19.6%-41.4%)

Total 100.0% 100.0% Of BCG defaulters:

Base n=169 n=168 % who do not default again 24.3% (18.5%-31.1%) 57.1% (50.6%-63.3%)

% who default at 3 month vaccinations (only)

33.7% (26.8%-41.5%)

13.5% (8.8%-20.1%)

% who default at measles vaccination (only)

8.9% (5.1%-15.0%)

12.9% (8.3%-19.5%)

% who default at 3 month vaccinations and measles

vaccination

33.1% (26.1%-41.0%)

16.6% (11.5%-23.4%) Total 100.0% 100.0%

Of 3 month vaccination defaulters:

Base: n=385 n=163 % who default at measles

vaccination (only)

42.6% (37.6%-47.8%)

38.1% (30.3%-46.5%)

76

Table 8: Expectations of immunization, by district

District: Urban/peri-urban Rural Base: 800 800

Column % (95% CI) Column % (95% CI) Diseases reported

p=.8383 Tuberculosis 14.0% (11.2%-17.4%) 13.4% (9.5%-18.7%)

p<.0001 Polio 48.9% (39.3%-48.6%) 22.5% (17.7%-28.0%)

p=.3362 Hepatitis 0.1% (0.0%-0.9%) 0%

p=.1441 Diphtheria 1.4% (0.7%-2.6%) 0.5% (0.2%-1.7%)

p=.0003 Whooping cough 22.1% (19.5%-25.0%) 10.4% (6.9%-15.3%)

p=.0101 Neonatal tetanus 14.1% (11.6%-17.1%) 8.6% (6.2%-11.9%)

p=.0014 Measles 40.6% (36.0%-45.4%) 26.3% (20.3%-33.4%)

p<.0001 Yellow fever 15.8% (12.5%-19.7%) 4.4% (2.8%-6.9%)

p=.1067 Malaria 36.8% (32.2%-41.6%) 42.3% (37.5%-47.2%)

p=.4575 Meningitis 19.5% (16.6%-22.8%) 17.2% (12.5%-23.1%)

p<.0001 Diarrhoea 25.0% (22.5%-29.8%) 42.4% (37.7%-47.3%)

p<.0001 Other 37.5% (33.5%-41.7%) 65.6% (60.6%-70.2%)

% reporting malaria and/or diarrhoea

p<.0001

Of all respondents 48.3% (43.3%-53.3%) 69.3% (64.5%-73.7%) p=.0066

Of respondents reporting 3+ correct diseases

34.9% (26.8%-43.8%)

58.1% (43.9%-71.0%)

% of women who only reported correct diseases 1

p<.0001

33.0% (28.6%-37.7%) 13.7% (10.2%-18.2%)

Number of ‘correct diseases’ reported 1

p<.0001

0 28.6% (24.6%-33.0%) 47.9% (41.3%-54.6%) 1 24.6% (21.8%-27.7%) 28.7% (24.4%-33.5%) 2 24.9% (21.8%-28.2%) 15.2% (11.7%-19.4%) 3 13.6% (11.3%-16.3%) 6.5% (4.5%-9.3%)

4+ 8.3% (6.3%-10.8%) 1.7% (0.9%-3.2%) Total 100% 100%

Note for Table 8:

1. ‘Correct diseases’ include: Tuberculosis, polio, hepatitis, diphtheria, whooping cough, neonatal tetanus, measles, and yellow fever

77

Table 8a: % who defaulted on the measles vaccination by knowledge of correct immunizable diseases1, by district

District: Urban/peri-urban Rural Base:

Row% (95% CI) OR (95% CI) Base Row % (95% CI) OR (95% CI) Base Named 3+ ‘correct diseases’ 2

p=.0174

p=.018

p=.3567

p=.359

none or <3 29.9% (25.0%-35.3%) 1.00 596 17.3% (14.0%-21.2%) 1.00 698 3+ 20.0% (13.9%-27.9%) 0.59 (0.38-0.91) 165 22.8% (12.4%-38.1%) 1.41 (0.66-3.01) 66

Named no correct diseases 3

p=.3065

p=.307

p=.4283

p=.429

named 1+ 26.6% (21.6%-32.3%) 1.00 542 16.4% (12.3%-21.7%) 1.00 398 named none 30.6% (23.9%-38.3%) 1.22 (0.83-1.79) 219 19.1% (14.5%-24.8%) 1.20 (0.75-1.92) 366

Note for Table 8a: 2. ‘Correct diseases’ include: Tuberculosis, polio, hepatitis, diphtheria, whooping cough, neonatal tetanus, measles, and yellow fever 3. Interpretation example: Of those urban/peri-urban respondents who could not name 3+ correct diseases, 29.9% were measles defaulters. In comparison, of those

urban/peri-urban respondents who could name 3+ correct diseases, 20.0% were measles defaulters. This is a statistically significant association suggesting that those with better knowledge of vaccinations are less likely to be measles defaulters.

4. Interpretation example: Of those urban/peri-urban respondents who could did name at least one correct diseases, 26.6% were measles defaulters. In comparison, of those urban/peri-urban respondents who could not name any correct diseases, 30.6% were measles defaulters. This is not a statistically significant difference suggesting that not knowing any correct diseases is not associated with being a measles defaulter.

78

Table 9: Expectations of immunization, by level of education (any) and district

District: Urban/peri-urban Rural 1+ years of Western/Tubab/Koranic education 1+ years of Western/Tubab/Koranic education None 1-4 years 5+ years None 1-4 years 5+ years

Base: 337 166 296 504 199 97 Column % (95% CI) Column % (95% CI) Column % (95% CI) Column % (95% CI) Column % (95% CI) Column % (95% CI) Diseases reported:

p=.0046 p=.8665 Tuberculosis 8.3% (5.4%-12.5%) 18.1% (11.5%-27.2%) 18.2% (13.8%-23.8%) 12.9% (8.3%-19.5%) 14.4% (9.0%-22.1%) 14.3% (8.3%-23.4%)

p<.0001 p=.0128 Polio 33.2% (27.9%-39.0%) 45.2% (36.4%-54.3%) 55.4% (49.6%-61.1%) 18.8% (13.4%-25.6%) 25.4% (16.8%-36.5%) 36.3% (28.6%-44.7%)

p=.4764 p N/A Hepatitis 0% 0% 0.3% (0.0%-2.5%) 0% 0% 0%

p=.1321 p=.0723 Diphtheria 0.6% (0.1%-2.5%) 1.2% (0.3%-4.8%) 2.4% (1.2%-4.6%) 0.4% (0.0%-1.7%) 0% 2.2% (0.5%-9.1%)

p=.0570 p=.8091 Whooping cough 18.7% (14.4%-24.0%) 28.9% (22.3%-36.6%) 22.3% (18.1%-27.1%) 9.8% (6.1%-15.4%) 11.1% (6.3%-18.6%) 12.1% (5.0%-26.4%)

p=.1203 p=.6073 Neonatal tetanus 11.3% (7.9%-15.8%) 15.1% (10.6%-20.9%) 16.9% (12.7%-22.2%) 8.8% (5.7%-13.2%) 7.2% (4.0%-12.7%) 11.0% (5.9%-19.5%)

p=.0005 p=.0012 Measles 34.4% (28.5%-40.9%) 36.8% (29.7%-44.5%) 50.0% (43.2%-56.9%) 21.7% (14.9%-30.3%) 29.3% (21.6%-38.3%) 45.1% (21.6%-38.3%)

p<.0001 p=.0175 Meningitis 13.4% (10.6%-16.8%) 15.1% (10.4%-21.4%) 29.1% (24.7%-33.8%) 14.8% (10.2%-20.9%) 18.2% (11.8%-27.1%) 27.5% (18.1%-39.4%)

p<.0001 p=.0029 Yellow fever 8.9% (6.3%-12.5%) 12.7% (8.1%-19.1%) 25.3% (19.3%-32.6%) 2.5% (1.2%-5.2%) 5.5% (2.3%-12.6%) 12.1% (7.1%-19.9%)

p=.4074 p=.7238 Malaria 34.1% (27.5%-41.4%) 38.0% (31.0%-45.4%) 39.2% (32.8%-46.0%) 42.3% (36.4%-48.5%) 40.3% (31.0%-50.4%) 46.2% (35.8%-56.9%)

p=.0692 p=.3277 Diarrhoea 21.7% (17.1%-27.0%) 27.7% (21.2%-35.4%) 30.1% (24.2%-36.7%) 42.1% (36.1%-48.3%) 39.8% (31.3%-48.9%) 49.5% (40.2%-58.8%)

p=.0173 p=.0775 Other 31.2% (26.4%-36.4%) 41.0% (33.2%-49.3%) 42.9% (35.7%-50.5%) 68.3% (63.1%-73.2%) 59.1% (50.0%-67.6%) 63.7% (52.9%-73.3%)

79

Table 9 (continued): Expectations of immunization, by level of education and district

District: Urban/peri-urban Rural 1+ years of Western/Tubab/Koranic education 1+ years of Western/Tubab/Koranic education None 1-4 years 5+ years None 1-4 years 5+ years

Base: 337 166 296 504 199 97 Column % (95% CI) Column % (95% CI) Column % (95% CI) Column % (95% CI) Column % (95% CI) Column % (95% CI) % reporting malaria and/or diarrhoea

p=.1764

p=.7579 Of all respondents 44.2% (36.9%-51.8%) 50.6% (43.8%-57.4%) 51.7% (44.3%-59.0%) 69.4% (64.2%-74.1%) 68.0% (58.8%-76.0%) 71.4% (63.8%-78.0%)

p=.5020 p=.2919 Of respondents

reporting 3+ correct diseases

38.5% (25.8%-53.0%)

40.0% (22.1%-61.0%)

30.7% (21.9%-41.1%)

48.0% (29.4%-67.2%)

70.0% (42.8%-87.9%)

58.8% (35.9%-78.5%)

% of women who only reported correct diseases 1

p=.0052

p=.2919 27.0% (21.9%-32.8%) 33.1% (26.8%-40.2%) 39.9% (32.7%-47.5%) 52.0% (32.8%-70.6%) 30.0% (12.1%-57.3%) 41.2% (21.6%-64.1%)

Number of ‘correct diseases’ reported 1

p.<.0001

p=.0025

0 40.4% (34.7%-46.3%) 24.7% (18.2%-32.6%) 17.2% (12.7%-22.9%) 50.8% (42.9%-58.8%) 47.5% (38.5%-56.7%) 33.0% (22.5%-45.4%) 1 23.2% (19.6%-27.2%) 23.5% (17.3%-31.1%) 27.0% (22.0%-32.8%) 30.0% (24.8%-35.8%) 26.5% (19.9%-34.4%) 26.4% (16.5%-39.4%) 2 21.1% (16.9%-26.0%) 30.7% (24.4%-37.9%) 26.0% (21.7%-30.9%) 14.0% (10.1%-19.1%) 14.9% (10.1%-21.4%) 22.0% (13.9%-33.0%) 3 11.9% (9.4%-14.9%) 15.1% (9.7%-22.6%) 14.9% (10.7%-20.3%) 4.4% (2.5%-7.6%) 8.3% (4.9%-13.6%) 14.3% (8.5%-23.1%)

4+ 3.6% (1.9%-6.7%) 6.0% (3.2%-11.0%) 14.9% (10.5%-20.7%) 0.8% (0.3%-2.2%) 2.8% (1.0%-7.2%) 4.4% (1.7%-10.9%) Total 100% 100% 100% 100% 100.0% 100.0%

Note for Table 9:

5. ‘Correct diseases’ include: Tuberculosis, polio, hepatitis, diphtheria, whooping cough, neonatal tetanus, measles, and yellow fever

80

Table 10: Variations in the profile of respondents asked to participate in MRC study by whether or not they participated (and by district)

District: Urban/peri-urban 3 Rural Participated

Column % (95% CI) Did not participate

Column % (95% CI) Participated


Column % (95% CI) Base: 22 9 393 71 Appearance of compound (qn01) p=.3591 p=.5425

Wealthy 22.7% (10.2%-43.2%) 11.1% (1.3%-55.2%) 8.9% (5.1%-14.9%) 4.8% (1.7%-12.8%) Medium 50.0% (31.3%-68.7%) 33.3% (9.8%-69.7%) 27.9% (20.6%-36.6%) 27.0% (14.7%-44.3%)

Poor 27.3% (10.9%-53.6%) 55.6% (22.7%-84.2%) 63.3% (53.2%-72.3%) 68.3% (49.1%-82.7%) Total 100% 100% 100% 100%

Ethnic group (qn04) p=.3333 p=.5832

Mandinka 47.8% (29.3%-67.0%) 22.2% (4.9%-61.5%) 33.3% (20.3%-49.6%) 22.2% (10.5%-40.9%) Fula 8.7% (1.9%-32.1%) 33.3% (9.9%-69.5%) 34.4% (22.3%-48.9%) 38.1% (20.9%-58.9%)

Wolof 8.7% (2.7%-24.4%) 0% 1.3% (0.4%-5.0%) 0% Serrehuli 13.0% (3.0%-42.0%) 0% 27.5% (15.1%-44.6%) 33.3% (13.9%-60.8%)

Jola 8.7% (1.8%-33.0%) 22.2% (4.9%-61.5%) 0.5% (0.1%-2.2%) 0% Other 13.0% (3.4%-39.2%) 22.2% (4.9%-61.5%) 2.9% (1.2%-6.9%) 6.4% (1.9%-19.0%) Total 100% 100% 100% 100%

Years of (any) education (derived from qn08, qn08a, qn08b)

p=.2990

p=.7066

None 60.9% (34.6%-82.1%) 33.3% (9.9%-69.5%) 62.4% (52.8%-71.1%) 66.7% (49.7%-80.2%) 1-5 21.7% (10.1%-40.9%) 22.2% (4.9%-61.5%) 26.4% (19.6%-34.5%) 25.4% (15.25-39.2%) >5 17.4% (5.5%-43.1%) 44.4% (15.9%-77.2%) 11.2% (7.7%-16.1%) 7.9% (2.8%-20.7%)

Total 100% 100% 100% 100% Years of Western/Tubab education (derived from qn08, qn08a)

p=.4934

p=.4003

None 78.3% (55.6%-91.2%) 55.6% (22.8%-84.1%) 89.1% (83.6%-92.9%) 93.7% (80.1%-98.2%) 1-5 4.4% (0.4%-31.8%) 11.1% (1.3%-54.9%) 6.1% (3.4%-10.8%) 1.6% (0.2%-11.6%) >5 17.4% (5.5%-43.1%) 33.3% (9.9%-69.5%) 4.8% (2.7%-8.4%) 4.8% (1.0%-19.3%)

Total 100% 100% 100% 100%

81

REVISED Table 10 (continued): Variations in the profile of respondents asked to participate in MRC study by whether or not they participated (and by district)





Column % (95% CI) Base: 22 9 393 71 Years of Koranic education (derived from qn08, qn08b)

p=.2734

p=.7360

None 82.6% (63.9%-92.7%) 77.8% (38.5%-95.1%) 74.1% (65.4%-81.3%) 74.6% (60.0%-85.2%) 1-5 17.45 (7.3%-36.1%) 11.1% (1.3%-54.9%) 20.5% (14.6%-28.2%) 22.2% (12.4%-36.6%) >5 0% 11.1% (1.3%-54.9%) 5.3% (2.9%-9.5%) 3.2% (0.8%-12.3%)

Total 100% 100% 100% 100%

Husband’s years of (any) education (derived from qn08, qn08a, qn08b) 2

p=.1486

p=.6487

None 4.8% (0.6%-31.2%) 25.0% (5.5%-65.8%) 28.0% (20.1%-37.7%) 33.3% (19.5%-50.8%) 1-5 76.2% (53.6%-89.9%) 37.5% (11.1%-74.2%) 62.5% (54.8%-69.7%) 60.0% (44.2%-73.9%) >5 19.1% (5.9%-46.9%) 37.5% (11.1%-74.2%) 9.4% (6.0%-14.6%) 6.7% (2.5%-16.7%)

Total 100% 100% 100% 100% Husband’s years of Western/Tubab education (derived from qn08, qn08a) 2

p=.1408

p=.6329

None 57.1% (35.1%-76.7%) 87.5% (41.3%-98.6%) 91.2% (85.6%-94.8%) 89.7% (75.8%-96.0%) 1-5 0% 0% 2.8% (1.5%-5.0%) 5.2% (1.6%-15.9%) >5 42.9% (23.4%-64.9%) 12.5% (1.4%-58.7%) 6.0% (3.1%-11.4%) 5.2% (1.7%-15.0%)

Total 100% 100% 100% 100%

Husband’s years of Koranic education (derived from qn08, qn08b) 2

p=.9077

p=.8286

None 85.7% (55.9%-96.6%) 87.5% (41.3%-98.6%) 83.0% (76.3%-88.1%) 86.2% (72.5%-93.7%) 1-5 0% 0% 7.7% (4.7%-12.4%) 5.2% (1.1%-21.2%) >5 14.3% (3.4%-44.1%) 12.5% (1.4%-58.7%) 9.3% (6.1%-14.0%) 8.6% (3.3%-20.7%)

Total 100% 100% 100% 100%

82

REVISED Table 10 (continued): Variations in the profile of respondents asked to participate in MRC study by whether or not they participated (and by district)





Column % (95% CI) Base: 22 9 393 71 Husband travels away to work 2 p=.5044 p=.3150

Yes 57.1% (34.4%-77.2%) 71.4% (29.1%-93.8%) 33.8% (27.2%-41.0%) 40.7% (28.9%-53.7%) No 42.9% (22.8%-65.6%) 28.6% (6.2%-70.9%) 66.2% (59.0%-72.8%) 59.3% (46.4%-71.1%)

Total 100% 100% 100% 100%

Notes for Table 10:

1. Among respondents who were asked to participate in MRC studies 2. Among respondents who reported that they were currently married. 3. Interpret with care due to the small numbers of urban/peri-urban respondents in each group.

83

Table 11: Factors associated with being asked to participate in a MRC study, by district

District: Urban/peri-urban Rural Base Base Row % (95% CI) OR (95% CI) Row % (95% CI) OR 95% CI) All 4.0% (2.2%-6.9%) - 783 59.0% (48.7%-68.7%) - 784 Appearance of compound (qn01) p=.6300 p=.7448 p=.8327 p=.8051

Wealthy 5.1% (1.8%-13.7%) 1.00 118 54.7% (42.2%-66.6%) 1.00 67 Medium 4.3% (2.0%-9.0%) 0.83 (0.34-2.04) 327 60.1% (48.3%-70.9%) 1.25 (0.62-2.52) 223

Poor 3.3% (1.8%-5.7%) 0.63 (0.18-2.16) 338 59.0% (48.7%-68.7%) 1.19 (0.64-2.23) 494 Ethnic group (qn04) p=.3312 p=.2267 p=.3078 p=.1733

Mandinka 5.2% (2.3%-11.0%) 1.00 252 59.9% (47.1%-71.5%) 1.00 258 Fula 3.0% (1.1%-8.2%) 0.57 (0.25-1.30) 165 53.2% (40.7%-65.2%) 0.76 (0.40-1.43) 287

Wolof 2.3% (0.5%-9.8%) 0.43 (0.11-1.67) 87 [83.3% (64.5%-93.2%)] [3.35 (1.12-9.97)] [6] Serrehuli 10.3% (3.9%-24.9%) 2.12 (0.52-8.70) 29 60.8% (50.2%-70.5%) 1.04 (0.55-1.97) 223

Jola 2.9% (1.2%-6.9%) 0.54 (0.17-1.76) 140 [66.7% (13.7%-96.2%)] [1.34 (0.10-17.2)] [3] Other 4.1% (1.6%-9.9%) 0.78 (0.22-2.76) 123 80.0% (54.7%-93.0%) 2.68 (0.73-9.87) 21


p=.4659

p=.4744

p=.2423

p=.1193

None 5.1% (3.0%-8.5%) 1.00 334 57.8% (49.2%-66.0%) 1.00 503 1-5 4.1% (1.6%-10.0%) 0.80 (0.33-1.97) 145 63.1% (53.5%-71.8%) 1.25 (0.91-1.72) 174 >5 2.7% (1.1%-6.5%) 0.52 (0.22-1.28) 294 50.6% (38.5%-62.6%) 0.75 (0.47-1.19) 97


4.6% (0.6%-28.8%)

0.89 (0.09-8.67)

22

66.7% (37.2%-87.1%)

1.46 (0.48-4.44)

24


p=.4187

p=.4301

p=.0441

p=.0119

None 5.1% (2.9%-8.5%) 1.00 436 59.9% (51.6%-67.8%) 1.00 677 1-5 2.3% (0.6%-8.8%) 0.44 (0.10-2.02) 87 54.6% (38.1%-70.1%) 0.80 (0.45-1.44) 44 >5 2.8% (1.0%-7.4%) 0.54 (0.24-1.23) 250 39.2% (27.0%-53.0%) 0.43 (0.24-0.76) 52

Been to school but unspecified for how many years of Western/Tubab education

4.6% (0.6%-28.8%)

0.90(0.09-8.73)

22

66.7% (37.2%-87.1%)

1.34 (0.43-4.17)

24

84

Table 11 (continued): Factors associated with being asked to participate in a MRC study, by district

District: Urban/peri-urban Rural Base Base Row % (95% CI) OR (95% CI) Row % (95% CI) OR 95% CI) All 4.0% (2.2%-6.9%) - 783 59.0% (48.7%-68.7%) - 784 Years of Koranic education (derived from qn08, qn08b)

p=.8798

p=.9078

p=.1806

p=.1126

None 4.1% (2.4%-7.0%) 1.00 607 55.9% (47.4%-64.1%) 1.00 581 1-5 4.4% (1.6%-11.4%) 1.06 (0.45-2.51) 115 66.4% (57.0%-74.7%) 1.55 (1.05-2.31) 151 >5 2.0% (0.3%-12.8%) 0.47 (0.06-3.87) 51 61.1% (41.7%-77.6%) 1.24 (0.59-2.61) 41

Been to school but unspecified for how many years of Koranic education

4.6% (0.6%-28.8%)

1.11 (0.11-10.7)

22

66.7% (37.2%-87.1%)

1.58 (0.51-4.87)

24

85


p=.1797

p=.1098

p=.0506

p=.0641

None 2.2% (0.8%-6.5%) 1.00 132 52.3% (40.3%-64.1%) 1.00 245 1-5 0.0% - 26 78.9% (65.0%-88.2%) 3.40 (1.50-7.67) 55 >5 6.9% (3.7%-12.6%) 3.20 (0.82-12.6) 202 55.5% (43.1%-67.1%) 1.13 (0.63-2.03) 121


3.5% (1.7%-7.1%)

1.55 (0.42-5.71)

344

60.6% (52.0%-69.0%)

1.40 (0.86-2.30)

345

Don’t know if husband has been to school 0.0% - 9 61.5% (31.4%-84.9%) 1.46 (0.40-5.29) 15 Husband’s years of Western/Tubab education (derived from qn08, qn08a) 1

p=.5002

p=.4178

p=.2429

p=.1778

None 2.2% (0.8%-6.5%) 1.00 134 52.3% (40.3%-64.1%) 1.00 245 1-5 0% - 20 61.9% (46.6%-75.2%) 1.48 (0.74-2.96) 21 >5 5.8% (2.5%-12.9%) 2.68 (0.61-11.7) 173 69.4% (51.6%-82.9%) 2.07 (0.91-4.70) 39


4.2% (2.4%-7.3%)

1.94 (0.56-6.73)

377 60.6% (52.2%-68.5%)

1.40 (0.86-2.28)

460

Don’t know if husband has been to school 0.0% - 9 64.3% (34.6%-86.0%) 1.64 (0.47-5.667) 16

Husband’s years of Koranic education (derived from qn08, qn08b) 1

p=.1587

p=.0709

p=.0114

p=.0329

None 2.2% (0.7%-6.5%) 1.00 135 52.3% (40.3%-64.1%) 1.00 245 1-5 0% - 22 81.6% (65.9%-91.1%) 4.04 (1.58-10.3) 41 >5 12.1% (5.2%-25.8%) 6.07 (1.29-28.6) 33 50.0% (36.1%-63.9%) 0.91 (0.48-1.74) 88


4.3% (2.2%-8.3%)

1.97 (0.52-7.37)

514

61.6% (53.2%-69.4%)

1.46 (0.91-2.36)

391

Don’t know if husband has been to school 0.0% - 9 64.3% (34.6%-86.0%) 1.64 (0.47-5.67) 16 Husband travels away to work 1 p=.9366 p=.937 p=.4008 p=.401

Yes 4.1% (2.4%-6.8%) 1.00 419 55.9% (46.9%-64.5%) 1.00 277 No 3.9% (1.7%-9.0%) 0.97 (0.41-2.27) 280 59.6% (50.2%-68.4%) 1.16 (0.81-1.68) 497

Note for Table 11: 1. Among respondents who reported that they were currently married.

86

Table 12: Factors associated with the child wearing a Talisman/juju at interview, by district

District: Urban/peri-urban Rural Base Base Row % (95% CI) OR (95% CI) Row % (95% CI) OR 95% CI) All 57.5% (52.0%-62.7%) - 799 51.1% (42.1%-60.0%) - 800 Ethnic group (qn04) p=.0034 p=.0009 p<.0001 p=.0001

Mandinka 67.5% (61.8%-72.7%) 1.00 252 66.0% (58.8%-72.5%) 1.00 258 Fula 52.7% (44.7%-60.6%) 0.54 (0.33-0.87) 165 64.5% (55.3%-72.6%) 0.94 (0.58-1.50) 289

Wolof 59.1% (47.8%-69.5%) 0.70 (0.42-1.15) 87 [50.0% (27.4%-72.6%)] [0.52 (0.18-1.50)] [6] Serrehuli 13.8% (6.1%-28.3%) 0.08 (0.03-0.20) 29 14.7% (8.3%-24.8%) 0.09 (0.04-0.19) 223

Jola 61.4% (53.5%-68.8%) 0.77 (0.50-1.18) 140 [33.3% (3.8%-86.3%)] [0.26 (0.02-3.55)] [3] Other 48.0% (28.4%-68.2%) 0.45 (0.19-1.06) 123 60.0% (39.4%-77.6%) 0.77 (0.33-1.83) 21


p=.8286

p=.7520

p=.2648

p=.2929

None 57.6% (48.4%-66.2%) 1.00 337 49.2% (38.6%-59.8%) 1.00 504 1-5 54.5% (46.5%-62.3%) 0.88 (0.59-1.32) 145 53.8% (45.0%-62.3%) 1.20 (0.79-1.83) 174 >5 58.8% (53.7%-63.8%) 1.05 (0.70-1.58) 294 59.3% (44.8%-72.4%) 1.51 (0.87-2.62) 97


54.6% (33.0%-74.6%)

0.88 (0.37-2.13)

22

38.1% (17.9%-63.45)

0.64 (0.23-1.75)

25


p=.4895

p=.4961

p=.1715

p=.2438

None 56.2% (48.8%-63.2%) 1.00 440 50.1% (40.3%-59.9%) 1.00 678 1-5 53.5% (42.0%-64.6%) 0.90 (0.55-1.46) 86 56.8% (43.1%-69.6%) 1.31 (0.68-2.54) 44 >5 61.2% (55.8%-66.4%) 1.23 (0.88-1.72) 250 64.7% (48.2%-78.3%) 1.83 (0.90-3.72) 52

Been to school but unspecified for how many years of Western/Tubab education

54.6% (33.0%-74.6%)

0.94 (0.39-2.23)

22

38.1% (17.9%-63.4%)

0.61 (0.23-1.65)

25

87

Table 12 (continued): Factors associated with the child wearing a Talisman/juju at interview, by district

District: Urban/peri-urban Rural Base Base Row % (95% CI) OR (95% CI) Row % (95% CI) OR 95% CI) All 57.5% (52.0%-62.7%) - 799 51.1% (42.1%-60.0%) - 800 Years of Koranic education (derived from qn08, qn08b)

p=.7435

p=.7635

p=.8658

p=.6801

None 56.8% (50.4%-63.0%) 1.00 609 51.0% (41.2%-60.7%) 1.00 582 1-5 62.1% (52.8%-70.5%) 1.24 (0.79-1.97) 116 53.3% (43.0%-63.4%) 1.10 (0.69-1.75) 151 >5 54.9% (40.5%-68.5%) 0.93 (0.49-1.76) 51 52.8% (29.5%-74.9%) 1.07 (0.44-2.62) 41

Been to school but unspecified for how many years of Koranic education

54.6% (33.0%-74.6%)

0.91 (0.39-2.15)

22

38.1% (17.9%-63.4%)

0.59 (0.21-1.63)

25


p=.2867

p=.2845

p=.5343

p=.4514

None 53.7% (41.3%-65.8%) 1.00 134 51.1% (38.0%-64.0%) 1.00 245 1-5 73.1% (52.6%-86.9%) 2.34 (0.94-5.84) 26 61.5% (47.4%-74.0%) 1.53 (0.83-2.84) 55 >5 60.2% (52.4%-67.5%) 1.30 (0.82-2.07) 201 55.5% (40.2%-69.8%) 1.19 (0.57-2.49) 121


55.2% (49.9%-60.4%)

1.06 (0.66-1.71)

346

49.5% (40.2%-58.9%)

0.94 (0.57-1.56)

346

Don’t know if husband has been to school 66.7% (33.6%-88.8%) 1.72 (0.38-7.78) 9 38.5% (16.3%-66.8%) 0.60 (0.20-1.84) 15 Husband’s years of Western/Tubab education (derived from qn08, qn08a) 1

p=.2553

p=.1960

p=.7285

p=.6873

None 53.7% (41.5%-65.5%) 1.00 136 51.1% (38.0%-64.0%) 1.00 246 1-5 75.0% (53.2%-88.8%) 2.59 (1.04-6.44) 20 66.7% (41.8%-84.8%) 1.92 (0.70-5.18) 21 >5 61.1% (52.8%-68.7%) 1.35 (0.88-2.09) 172 55.6% (37.1%-72.6%) 1.20 (0.49-2.94) 39


55.4% (50.1%-60.6%)

1.07 (0.67-1.72)

379

51.1% (41.3%-60.8%)

1.00 (0.60-1.68)

461

Don’t know if husband has been to school 66.7% (33.6%-88.8%) 1.73 (0.38-7.76) 9 42.9% (19.4%-70.0%) 0.72 (0.25-2.09) 16

88

Table 12 (continued): Factors associated with the child wearing a Talisman/juju at interview, by district

District: Urban/peri-urban Rural Base Base Row % (95% CI) OR (95% CI) Row % (95% CI) OR 95% CI) All 57.5% (52.0%-62.7%) - 799 51.1% (42.1%-60.0%) - 800 Husband’s years of Koranic education (derived from qn08, qn08b) 1

p=.6304

p=.7652

p=.8488

p=.7677

None 53.3% (41.2%-65.0%) 1.00 137 51.1% (38.0%-64.0%) 1.00 245 1-5 72.7% (43.8%-90.1%) 2.38 (0.60-9.17) 22 60.5% (44.4%-74.7%) 1.47 (0.71-3.06) 41 >5 57.6% (34.5%-77.8%) 1.19 (0.41-3.42) 33 52.6% (32.4%-71.9%) 1.06 (0.43-2.64) 88


57.3% (52.2%-62.2%)

1.18 (0.78-1.78)

515

51.1% (42.2%-59.9%)

1.00 (0.61-1.63)

392

Don’t know if husband has been to school 66.75 (33.6%-88.8%) 1.75 (0.39-7.87) 9 42.9% (19.4%-70.0%) 0.72 (0.25-2.09) 16 Like child to wear Talisman/juju to IWC

Of all respondents 2 53.3% (40.2%-66.0%) - 796 46.7% (34.0%-59.8%) - 796 Of respondents wearing Talisman/juju at

interview 3

53.7% (40.5%-66.4%) -

457

46.3% (33.7%-59.5%)

- 403

Notes for Table 12: 1. Among respondents who reported that they were currently married. 2. No significant difference exists between urban/peri-urban and ‘upcountry’ districts in terms of the proportion of respondents who reported that they like their child to wear Talisman/juju to

the IWC (p=.4795) 3. No significant difference exists between urban/peri-urban and ‘upcountry’ districts in terms of the proportion of respondents whose child was wearing Talisman/juju at interview, who

reported that they like their child to wear Talisman/juju to the IWC (p=.0612).

89

Table 13a: What benefits do you think there are in having a child registered with MRC (qn 55) by whether or not participated (Rural areas only) (of those invited to participate) District: Urban/peri-urban 3 Rural Participated Did not participate Participated Did not participate Base: 23 5 393 71

Not applicable p.<.0001

What benefits do you think there are in having a child registered with MRC?

Row % (95% CI) Row % (95% CI)

Good treatment/care/medicines 88.8% (83.4%-92.7%) 11.2% (7.3%-16.6%) Free (and good) treatment 90.2% (82.3%-94.8%) 9.8% (5.2%-17.7%)

Food (and good free treatment) 80.0% (26.1%-97.8%) 20.0% (2.2%-73.9%) Transport (and good free treatment) 86.2% (68.0%-94.9%) 13.8% (5.2%-32.1%)

Privileged access to new/experimental vaccines 0.0% 0.0% Don’t know/never heard 15.8% (3.7%-48.1%) 84.2% (51.9%-96.4%)

Other 100.0% 0.0%

Heard negative things about the MRC? Column % (95% CI) Column % (95% CI)


Food (and good free treatment) 1.1% (0.3%-3.6%) 1.6% (2.1.%-10.9%) Transport (and good free treatment) 13.4% (8.0%-21.5%) 12.7% (6.0%-24.8%)


Other 0.3% (0.0%-2.1%) 0.0%

90

Table 13b: What benefits do you think there are in having a child registered with MRC (qn 55) by whether or not invited to participate (Rural areas only) District: Urban/peri-urban 3 Rural Invited Not invited Invited Not invited Base: 465 332



Row % (95% CI) Row % (95% CI)




Other 16.7% (3.1%-56.0%) 83.3% (44.0%-97.0%)




Privileged access to new/experimental vaccines 0.0% 0.3% (0.0%-2.4%) Don’t know/never heard 4.4% (2.4%-7.9%) 31.0% (21.8%-41.9%)

Other 0.2% (0.0%-1.8%) 1.6% (0.7%-3.6%)

91

Table 13c: What benefits do you think there are in having a child registered with MRC (qn 55) by whether or not heard negative things about the MRC study (Rural areas only) District: Urban/peri-urban 3 Rural Heard negative things about the MRC Heard negative things about the MRC No Yes No Yes Base: 23 5 393 71



Row % (95% CI) Row % (95% CI)




Other 100.0% 0.0%



Food (and good free treatment) 1.1% (0.3%-3.6%) 1.6% (2.1.%-10.9%) Transport (and good free treatment) 13.4% (8.0%-21.5%) 12.7% (6.0%-24.8%)


Other 0.3% (0.0%-2.1%) 0.0%

92

Table 14a: Who made the decision about participation in the MRC study, by district

District: Urban/peri-urban 3 Rural Participated Did not participate Participated Did not participate Base: 23 5 393 71 p=.3105 p<.0001 Who made decision about participating Row % (95% CI) Row % (95% CI) Row % (95% CI) Row % (95% CI)

Myself 76.9% (41.3%-94.0%) 23.1% (6.0%-58.7%) 81.8% (71.5%-89.0%) 18.2% (11.0%-28.5%) Husband 60.0% (13.9%-93.3%) 40.0% (6.7%-86.1%) 88.5% (78.0%-94.3%) 11.5% (5.7%-22.0%)

Jointly with husband 100.0% 0.0% 99.0% (92.2%-99.9%) 1.0% (0.1%-7.8%) Compound 0.0% 0.0% 100.0% 0.0

Other 100.0% 0.0% 40.0% (21.1%-62.5%) 60.0% (37.5%-78.9%) All 82.1% (56.3%-94.3%) 17.9% (5.7%-43.7%) 86.6% (80.5%-91.0%) 13.4% (9.0%-19.6%)

Who made decision about participating Column % (95% CI) Column % (95% CI) Column % (95% CI) Column % (95% CI)

Myself 43.5% (27.0%-61.5%) 60.0% (17.1%-91.6%) 17.2% (11.6%-24.6%) 24.6% (15.3%-37.1%) Husband 13.0% (4.4%-32.8%) 40.0% (8.4%-82.9%) 50.1% (39.7%-60.6%) 42.1% (26.4%-59.5%)

Compound 0.0% 0.0% 27.3% (18.2%-38.7%) 1.8% (0.2%-11.9%) Jointly with husband 39.1% (24.5%-56.0%) 0.0% 2.2% (0.9%-5.1%) 0.0%

Other 4.4% (0.4%-32.2%) 0.0% 3.3% (1.7%-6.3%) 31.6% (17.4%-50.3%)

93

Table 14b: Who made the decision about participation in the MRC study, grouped, by district

District: Urban/peri-urban 3 Rural Participated Did not participate Participated Did not participate Base: 23 5 393 71 p=.2657 p=.0393 Who made decision about participating Row % (95% CI) Row % (95% CI) Row % (95% CI) Row % (95% CI)

Husband/others 66.7% (20.8%-93.8%) 33.3% (6.2%-79.2%) 82.9% (73.3%-89.6%) 17.1% (10.4%-26.7%) Myself/jointly 86.4% (59.6%-96.5%) 13.6% (3.6%-40.4%) 91.6% (85.4%-95.3%) 8.4% (4.7%-14.7%)

Who made decision about participating Column % (95% CI) Column % (95% CI) Column % (95% CI) Column % (95% CI)

Husband/others 17.4% (7.2%-36.4%) 40.0% (10.2%-39.7%) 55.6% (45.5%-65.3%) 73.7% (60.6%-83.6%) Myself/jointly 82.6% (63.6%-92.8%) 60.0% (17.1%-91.6%) 44.4% (34.7%-54.5%) 26.3% (16.4%-39.4%)

94

Table 14c: Variations in who made the decision about participation in the MRC study (grouped), by mother’s category of reproductive life (qn02) (and district)

District: Urban/peri-urban 3 Rural Who made decision about participating: Husband/others Myself/jointly Husband/others Myself/jointly

Base: 6 19 254 190 p=.0204 p=.0052 Mother’s category of reproductive life Row % (95% CI) Row % (95% CI) Row % (95% CI) Row % (95% CI)

Young women 25.0% (5.3%-66.5%) 75.0% (33.5%-94.7%) 60.9% (42.8%-76.4%) 39.1% (23.6%-57.2%) Newly married with few children 55.6% (22.4%-84.4%) 44.4% (15.6%-77.6%) 66.1% (56.9%-56.9%) 33.9% (25.8%-43.1%)

Woman in middle of reproduction 0.0% 100.0% 56.3% (43.8%-68.0%) 43.8% (32.0%-56.2%) Woman at end of reproduction/old woman 0.0% 100.0% 41.8% (30.4%-54.2%) 58.2% (33.7%-50.5%)

p=.0204 p=.0052 Mother’s category of reproductive life Column % (95% CI) Column % (95% CI) Column % (95% CI) Column % (95% CI)

Young women 16.7% (2.8%-58.5%) 15.8% (6.3%-34.5%) 5.8% (3.5%-9.3%) 5.1% (2.5%-10.5%) Newly married with few children 83.3% (41.5%-97.3%) 21.1% (5.7%-54.0%) 45.7% (37.5%-54.1%) 32.6% (24.6%-41.7%)

Woman in middle of reproduction 0.0% 52.6% (31.9%-72.5%) 37.0% (29.3%-45.5%) 40.0% (33.2%-47.2%) Woman at end of reproduction/old woman 0.0% 10.5% (3.2%-29.6%) 11.5% (7.9%-16.4%) 22.3% (16.6%-29.3%)

Total 100.0% 100.0% 100.0% 100.0%

95

Table 14d: Variations in who made the decision about participation in the MRC study (grouped), by mother’s Toubab education (and district)

District: Urban/peri-urban 3 Rural Who made decision about participating: Husband/others Myself/jointly Husband/others Myself/jointly

Base: 6 19 254 190 p=.8257 p=.6572 Years of Western/Tubab education (derived from qn08, qn08a) 2

Row % (95% CI)

Row % (95% CI)

Row % (95% CI)

Row % (95% CI)

None 23.8% (9.8%-47.5%) 76.2% (52.5%-90.3%) 57.5% (48.3%-66.1%) 42.6% (33.9%-51.7%) 1-5 0.0% 100.0% 54.2% (33.9%-73.2%) 45.8% (26.9%-66.1%) >5 16.7% (1.5%-73.0%) 83.3% (27.0%-98.5%) 65.0% (44.5%-81.1%) 35.0% (18.9%-55.5%)


0.0%

0.0%

72.7% (37.5%-92.2%)

27.3% (7.8%-62.5%)

Years of Western/Tubab education (derived from qn08, qn08a) 2

Column % (95% CI)

Column % (95% CI)

Column % (95% CI)

Column % (95% CI)

None 83.3% (30.0%-98.3%) 72.7% (44.3%-89.9%) 86.2% (79.7%-90.8%) 88.2% (81.1%-92.9%) 1-5 0.0% 4.6% (0.5%-30.2%) 5.3% (2.8%-9.8%) 6.2% (2.6%-14.0%) >5 16.7% (1.7%-70.0%) 22.7% (8.1%-49.4%) 5.3% (3.0%-9.1%) 3.9% (1.7%-8.9%)


0.0%

0.0%

3.3% (1.5%-6.8%)

1.7% (0.6%-4.8%)

Total 100.0% 100.0% 100.0% 100.0%

96

Table 15: What do you think the MRC study is about? (qn 52) (Rural area only)

District: Urban/peri-urban 3 Rural Participated Did not participate Participated Did not participate Base: 23 5 393 71

Not applicable p=.7323

What do you think the MRC study is about?

Row % (95% CI) Row % (95% CI)

Don’t know/wasn’t told/forgot 84.7% (71.1%-92.5%) 15.3% (7.5%-28.9%) Improved child health/good health 90.6% (83.2%-95.0%) 9.4% (5.0%-16.8%)

Free checking & treatment for your child 89.2% (80.9%-94.1%) 10.8% (5.9%-19.1%) Pneumonia 100.0% 0.0%

Pneumococcal vaccine trial 100.0% 0.0% Other 100.0% 0.0%

What do you think the MRC study is about?

Column % (95% CI) Column % (95% CI)

Don’t know/wasn’t told/forgot 42.9% (30.0%-56.9%) 59.2% (40.7%-75.4%) Improved child health/good health 31.1% (19.8%-45.2%) 24.5% (12.3%-42.8%)

Free checking & treatment for your child 17.7% (10.2%-29.0%) 16.3% (8.1%-30.3%) Pneumonia 1.3% (0.2%-9.5%) 0.0%

Pneumococcal vaccine trial 6.2% (1.5%-22.7%) 0.0% Other 0.8% (0.3%-2.5%) 0.0%

97

Table 16: Whether heard negative things about the MRC by whether or not participated in the study (qn 53) (of those invited to participate)

District: Urban/peri-urban 3 Rural Participated Did not participate Participated Did not participate Base: 23 5 393 71

p=.6129 p=.1708

Heard negative things about the MRC? Row % (95% CI) Row % (95% CI) Row % (95% CI) Row % (95% CI)

Yes 76.9% (46.7%-92.7%) 23.1% (7.3%-53.3%) 89.4% (82.3%-93.8%) 10.6% (6.2%-17.7%) No 68.4% (34.5%-89.9%) 31.6% (10.1%-65.5%) 83.8% (75.6%-89.6%) 16.3% (10.5%-24.4%)

Heard negative things about the MRC? Column % (95% CI) Column % (95% CI) Column % (95% CI) Column % (95% CI)

Yes 43.5% (24.1%-65.1%) 33.3% (9.9%-69.5%) 38.1% (31.4%-45.4%) 61.9% (54.6%-68.6%) No 56.5% (34.9%-76.0%) 66.7% (30.5%-90.1%) 27.4% (16.4%-42.1%) 72.6% (57.9%-83.6%)

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