1

Internal Migration and 'Rural/Urban‘

Households in China:

Implications for Health care

2

Origins of POVILL Research

• Anecdotal evidence from poor villages:

Elderly + young children

High prevalence of chronic illness

Vulnerability

• New Cooperative Medical Scheme (NCMS)

Government subsidy

Risk fund for inpatient care

• ‘Catastrophic healthcare expenditure’

Model: Get sick – Buy care – Get well

Extreme reductionism (Dennett)

3

The Limits of ‘Catastrophic

Healthcare Expenditure• High expenditure on healthcare (even relative to

income) not necessarily ‘catastrophic’.

• Adoption of approach by policy makers encouraged a

excessive focus on hospital inpatient expenditures

• Variety of mechanisms through which health shocks

and poverty may interact: Acute events requiring costly hospital care

Chronic illness requiring long-term medication

Less serious but often recurring acute illnesses

Long-term, possibly progressive, conditions that completely or

partially disable the sufferer

Stigmatising illnesses may induce loss of status, isolation, rejection

and persecution.

• Poorest often cannot afford ‘catastrophic health

expenditure’.

4

Illness-Poverty Links(China National Heath Service Survey 2008)

0 5 10 15 20 25 30

Lack labour

Natural conditions/disaster

Disease: low productivity

Disease: treatment cost

Unemployment

Man made causes

Other

5

The POVILL project• Aims:

Understand the potentially complex impacts of

major illness on household livelihoods for a

substantial number of households

Select households using a probability sampling

approach to make valid statistical inferences to the

overall study area populations.

• Major illness conceived very broadly: health problems

which had the potential to seriously damage household

livelihood strategies.

• Primary causal pathways to impoverishment seen as:

Increased expenditures on healthcare

Limitations on household activities, linked to illness-

induced changes in labour demand and supply.

6

Research Methods• Existing knowledge mainly derived from questionnaire

surveys that collect information on illness, care seeking

behaviour and expenditure, typically on the basis of a

two-week recall for acute illness episodes and a one

year recall for inpatient treatments.

• Even panel surveys have limited ability to capture the

step-by-step process whereby households cope, or fail

to cope, with consequences of ill-health.

• Alternatives:

Case studies: fascinating but limited scale

Monitoring surveys: increased reliability but limited

to relatively simple data and modest sample size

Demographic surveillance sites: interesting

possibility (if one exists), difficult ethical problems.

7

POVILL Approach

• Rapid and reasonably large-scale household

questionnaire survey using cluster sampling of

households within selected study areas:

identify households substantially affected by

different categories of serious health problem

estimate the proportions of such households in the

population.

• Sampled households stratified using survey data.

• Probability sample of households within selected strata

• In-depth studies (1-2 person days) of these household

undertaken by teams of social scientists

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In-Depth Studies

• Collected both quantitative and qualitative data. Specific

intention to derive reasonably reliable estimates of

incomes, expenditures, health care cost, financial

support received, duration of illness or disability, etc.

• Underlying framework was an ‘illness narrative’ to

document the history of each health problem addressed.

• Four main components:

Narrative and construction of one year time line

Identification of ‘events’: start points for changes in

health status, treatment, assistance, assets, other.

Detailed description of events

Dating/quantifying events to the extent possible

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Illustrative One-Year Timeline

2006 2007 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Back Village Condition Township Borrow money County pain. Health worse. Unable Hospital to buy drugs. Hospital limits Station to farm. Son activity returns to help

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Three Transitions

• Demographic

Low mortality and low Fertility

•Epidemiological

Acute infectious disease → chronic NCDs

•Economic

Planned → ‘Socialist Market’

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Resident and Migrant

PopulationsTotal

Population

Resident at

least 6 months

Absent more

than 6 months

0-14 15.9 20.2 7.6

15-19 9.2 5.9 15.5

20-39 29.9 12.8 63.4

40-49 12.8 14.4 9.6

50-59 15.3 21.5 3.1

60-69 10.2 15.1 0.7

70+ 6.8 10.1 0.2

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Resident and Migrant

Populations

• Internal migration: 30% of rural population.

• 90% of men and 70% of women between the ages of 20 and 35 reported as living away from home for part of year (90% migrate 6 months or longer).

• So the resident population is dominated by those under 15 (21%) or over 50 (48%).

• 16.6% of rural residents aged 65 and over (UK:16%). 0

10

20

30

40

60

70

80

90

100

age

600 500 400 300 200 100 100 200 300 400 500 600Population

Male

Female

M-living away

F-living away

Population and living away from home

The countryside is exporting good

health and re-importing ill-health.

• First, young and healthy people are more

likely to migrate than elderly people,

leaving the weak and sick at home.

• Second, more serious and incapacitating

diseases and intensive-care conditions

result in a migrant’s return to the home in

the village to seek family support and to

avoid the high medical and living costs in

cities.

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Reason given by migrants for

returning home

0 5 10 15 20 25 30

investment

marriage

can't find job

Pregnancy, delivery & upbring

take Care of family member

Too old

illhealth

%

15

Self reported serious illness

over previous year0

51

01

52

02

53

03

54

04

55

0p

rop

ort

ion

of p

op

ula

tio

n(%

)

15 20 25 30 35 40 45 50age

migration left behind

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‘Rural/urban’ Households

Traditional

household

Return due

to illness

Return to care

for others

Rural/urban

household

Reunited in

urban area

Members left-

behind

Elde

rly on

ly

Thre

e ge

ne

ration

Migrants

Nuclear

family

Extended

family

Elde

rly + ch

ildre

n

Pare

nt +

child

ren

single

cou

ple

40% 60%

14% 23% 11% 12%

56%

44%

17

Four main health insurance

schemes in China

• Government staff(free medical service,FMS)

5% population 100% coverage

• Basic Medical Insurance (BMI)

Urban employees, 28% coverage 2006

• Urban Basic Medical Insurance (UBMI)

Other urban residents, aim: 100% coverage by 2010

• New Community Medical Scheme (NCMS)

Rural residents, 57% population, 87% coverage 2007

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Heath insurance scheme

coverage for migrants in Beijing

none46%NCMS

41%

CI6%

BMIS2%

FMS2%

other3%

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Reimbursement of NCMS

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Chronic illness healthcare costs

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Urban/Rural and Decentralisation

Poor county

Healthy labor exported

Less enterprises and jobs

Very limited govt revenue

Elderly less-healthy remain joined by returning ill migrants

Shanghai

Healthy labor imported

More enterprises and jobs

High government revenue

Well funded health insurance

demand

supplysupply

demand

Limited health insurance

Younger, healthier population

health

Ill-health

Shanghai compared to

Western provinces

• In Shanghai, the government plus

personal financial contribution to the rural

NCMS was around 450 yuan per person

• Compared with only 50 yuan per person

in most provinces in Western China.

22

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Questions

• Can segmented (urban/rural) and highly

decentralised health care and health

insurance systems cope with these new

ways of constructing family units?

• What happens next?

• What are the implications for the Chinese

economy?

• How do we conduct research on these

new ‘households’?