A NATIONAL SURVEY ON THE USE OF - … A NATIONAL SURVEY ON THE USE OF MEDICINES (NSUM) BY MALAYSIAN...

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A NATIONAL SURVEY ON THE USE OF MEDICINES (NSUM) BY MALAYSIAN

CONSUMERS

Edited and prepared by: Mohamed Azmi H, Fahad S

With contributions from: Mohd Dziehan M, Che Pun B, Salmiah MA, Siti Fauziah A, Norazlin AK, Abdul Haniff MY,

Kamarudin A, Siew LJ , Lai ST

A publication of the

Pharmaceutical Services Division

Ministry of Health Malaysia

3

Jun 2016

© Ministry of Health Malaysia

Published by:

Quality Use of Medicines

Pharmaceutical Services Division

Ministry of Health Malaysia

Lot 36, Jalan Universiti,

46350 Petaling Jaya,

Selangor Darul Ehsan,

Malaysia.

Tel : (603) 7841 3200

Fax : (603) 7968 2222

Website : http://www.pharmacy.gov.my

This report is copyrighted. Reproduction and dissemination of this report in part or in whole for

research, educational or other non-commercial purposes are authorised without any prior

written permission from the copyright holders provided the source is fully acknowledged.

Suggested citation is: Pharmaceutical Services Division, Ministry of Health Malaysia. A

National Survey on the Use of Medicines (NSUM) by Malaysian Consumers 2015.

This report is also published electronically on the website of the Pharmaceutical Services

Division at: http://www.pharmacy.gov.my.

NMRR ID:

The National Survey on the Use of Medicines (NSUM) by Malaysian Consumers 2015 had

been registered at National Medical Research Registry with the given ID No.: NMRR- 15-265-

24824.

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CONTENTS PAGE

Acknowledgement 5

Executive Summary 6

NSUM Project Team 9

Data Collectors 10

List of tables 13

1.0 Introduction 15

2.0 Objectives 17

3.0 Methodology 17

3.1 Sample size 18

3.2 Sampling method 18

3.3 Ethical issue 19

4.0 Results 19

4.1 Demographic data 19

4.2 Pattern of medicines use 22

4.3 Access to healthcare professionals 23

4.4 Access to medicines 25

4.5 Perceptions towards medicines labelling 33

4.6 Awareness towards appropriate use of medicines 47

4.7 Assessment towards medication compliance 64

4.8 Assessment of medicine information resources 67

4.9 Awareness on ‘Know Your Medicines’ programme 79

5.0 Discussions 84

6.0 Conclusions 89

7.0 Limitations 89

References 90

Appendixes 94

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ACKNOWLEDGEMENT

First and foremost we would like to express our most gratitude to the Director General of Health Malaysia for the permission in publishing this report. Sincere appreciation also to the Ministry of Health Malaysia (MOH) for giving us the opportunity to collaborate in this project and coming up with the third report after eight years Quality Use of Medicines-Consumer campaign was launched.

To evaluate the performance of the campaign, A National Survey on the Use of Medicines (NSUM) by Malaysian Consumers were conducted in year 2015. Indeed it was a great effort by all the parties involved in the survey until this report is published.

We also would like to thank all the data collectors from the various parts of the nation whose enthusiasm, determination and perseverance shown during the training and data collecting sessions which yielded excellent data to be used in this report. Finally, we would like to thank all our colleagues from MOH, Universiti Sains Malaysia (USM) for the excellent intellectual inputs in making this research project a success. We really hope that the output of this report could be utilized by those interested parties in improving consumer use of medicines.

Pharmaceutical Services Division Ministry of Health Malaysia

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EXECUTIVE SUMMARY

Quality Use of Medicines (QUM) is one of the central objectives of Malaysia’s National

Medicines Policy. Within the context of QUM framework, it is crucial to get current data

from the general population in order to assess their understanding on issues related

to rational use of medicines. In addition, information from the survey will help the policy

makers to evaluate the impact of strategies that had been taken in order to improve

quality use of medicines among consumers in this country. Furthermore, the data gain

from such survey will be useful for devising future strategies to further enhance quality

use of medicines among Malaysian population.

In order to get in-depth data and information on issues related to medicines use among

Malaysian consumers, a cross sectional national survey for a period of 3 months

(June-August 2015) was conducted among 3,081 consumers across the country. The

study findings showed that:

Malaysian consumers were found to be using some form of pharmaceuticals,

traditional health compounds and beauty products in their everyday life to manage

their health, general well-being and appearance. Of these,

30.3% were on chronic medications,

21.5-31.8% were using vitamins, minerals & supplements,

7.9-16.8% were using traditional medicines in the form of herbal beverages,

processed and non-processed herbs, and

10.9% were using beauty products.

Spending on medicines obtained from private hospitals recorded an average of

RM296.98 monthly while in private pharmacies was average RM135.20 monthly.

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Despite extensive use of pharmaceuticals,

18.6% did not fully understand the proper use of their medicines,

46.8% were not able to identify the trade or generic name of their medicines,

17.0% had no knowledge on proper medicine storage,

29.7% were not aware of common side effects of their medicines and

31.6% were not aware of the possible interactions between traditional and modern

medicines.

The study also found that;

Doctors were the respondents’ first point of reference when experiencing problems

with health, with slightly more than half of them (58.6%) opted to consult a doctor

in the government sector.

The three most common facilities where consumers obtained their medicines were

clinics (88.4%), hospitals (80.3%) and community pharmacies (76.1%).

Over 90% of respondents perceived medicines labels as adequate and did not

report any difficulties in reading the labels.

75.2% of the respondents considered price of medicine as an essential element to

be displayed on the label. Furthermore, 59.4% of the respondents rated price as a

factor in maintaining medication compliance.

Although an increasing proportion of consumers were more aware of the safety

and regulatory issues of medicines, compliance remained a problem, whereby

73.1% of the respondents were declared as non-compliant where they admitted

forgotten to take their prescribed medication.

An emerging problem with sharing of medicines can be anticipated with as many

as 33.9% of consumers reported to be sharing medications.

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When acquiring medicines information, consumers’ first point of reference was the

doctors (49.6%) followed by the pharmacists (31.1%).

75.1% of the consumers preferred additional written information on medicines.

70.8% of the consumers stated that they require additional medicines counselling

sessions with pharmacists in order to understand and overcome problems

pertaining to their medicines.

Awareness of the national effort to promote quality use of medicines via the ‘Know

Your Medicines’ programme among consumers was marginally good but

participation remains relatively low.

Of those who had participated in the ‘Know Your Medicines’ programme, majority

of the respondents were satisfied with the campaign activities.

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NSUM PROJECT TEAM Advisor Pn. Abida Haq Binti Syed M.Haq

Director of Pharmacy Practice & Development Pharmaceutical Services Division Ministry of Health, Malaysia

Consultants Prof. Dr. Mohamed Azmi bin Ahmad Hassali Deputy Dean, School of Pharmaceutical Sciences Universiti Sains Malaysia Dr. Fahad Saleem Senior Lecturer Ph.D (Social Pharmacy) School of Pharmaceutical Sciences Universiti Sains Malaysia Prof. Dr. Salmiah binti Mohd. Ali Deputy Dean (Research and Development) Head of Department & Professor of Pharmacy Practice MAHSA University

Principal Investigator Mr. Mohd. Dziehan bin Mustapa Senior Principal Assistant Director Pharmaceutical Services Division Ministry of Health, Malaysia

Co-Investigators Madam Che Pun binti Bujang Deputy Director of Pharmacy Practice and Development, Pharmaceutical Services Division Ministry of Health, Malaysia Ms. Siti Fauziah binti Abu Deputy Director Pharmacy Policy & Strategic Planning Division Ministry of Health, Malaysia Madam Norazlin binti Abd. Kadir Senior Principal Assistant Director Pharmaceutical Services Division Ministry of Health, Malaysia Mr. Abdul Haniff bin Mohamad Yahaya Pharmacist U52 Teluk Intan Hospital, Perak

Mr. Kamarudin Bin Ahmad Pharmacist U52 Miri Hospital, Sarawak Madam Siew Lee Jin Senior Assistant Director Pharmaceutical Services Division Ministry of Health, Malaysia

Madam Lai Sook Tze Senior Assistant Director Pharmaceutical Services Division, Sarawak

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DATA COLLECTORS

PERLIS

Wan Irnayufzan Hani Wan Ab Rahman

Pharmacist Pharmaceutical Services Division, Perlis

Tan Yean Yong Pharmacist

Kampung Gial Health Clinic

Nurul Hidayah Mahamud Pharmacist

Pharmaceutical Services Division, Perlis

KEDAH

Edi Aswad Mohd Nain

Pharmacist Sultanah Bahiyah Hospital

Noraishah Abu Bakar

Pharmacist Pharmaceutical Services Division, Kedah

Saravanapriya a/p Thillaivanam

Pharmacist Kulim Hospital

Khor Chee Hau

Pharmacist Baling Hospital

PENANG

Shirley Lim Sheh Lee

Pharmacist Pulau Pinang Hospital

Kong Kee Foong

Pharmacist Seberang Jaya Hospital

Tan Moi Kiang

Pharmacist District Health Office, Seberang Perai Selatan

Look Chun Hua

Pharmacist District Health Office, Timur Laut, Pulau

PERAK

Nor Fadhilahanim Ramli

Pharmacist Pharmaceutical Services Division, Perak

Nurul Akma Harun

Pharmacist Batu Gajah Hospital

Shahrunnisak Abdul Karim

Pharmacist Taiping Health Clinic

Kong Pui Chin Pharmacist

Slim River Hospital

Hema a/p Krishnan Pharmacist

Gunung Rapat Health Clinic

SELANGOR

Brendan Su Hau Teck

Pharmacist Pharmaceutical Services Division, Selengor

P’ng Xiu Wen

Pharmacist Tengku Ampuan Rahimah Hospital

Muhammad Shafiq Aziz

Pharmacist Kajang Hospital

Nurul Nadiah Abu Bakar

Pharmacist Rawang Health Clinic

Ahmad Firdaus An-Nasr Nasri

Pharmacist Dengkil Health Clinic

Nurul Syazwani Mohamad

Pharmacist Telok Panglima Garang Health Clinic

Thiagarajan a/l Chandra Sekaran

Pharmacist Ijok Health Clinic

Abdul Aziz Ahmad Adli

Pharmacist Sekinchan Health Clinic

Poon Sook Fun

Pharmacist Rasa Health Clinic

Omar Othman

Pharmacist Kalumpang Health Clinic

KUALA LUMPUR

Nuruz Zakiah Md Zin Pharmacist

Pharmaceutical Services Division, JKWP KL

Gan Chin Bao Pharmacist

Cheras Health Clinic

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Nurul Nafisah Hassan Pharmacist

Putrajaya Presnit 18 Health Clinic

Nur Fathiah Md Isa Pharmacist

Pharmaceutical Services Division, JKWP KL

Abdul Qayyum Zainal Pharmacist

Kuala Lumpur Hospital

NEGERI SEMBILAN

Teong Seng Chew Pharmacist

Pharmaceutical Services Division, Negeri Sembilan

Muhammad Fikri Abdul Halim Pharmacist

Tuanku Jaafar Hospital

Siow Yee Zhen Pharmacist

Bahau Health Clinic

MELAKA

Nurul Hayani Norddin

Pharmacist Pharmaceutical Services Division, Melaka

Fakarrudin Karim

Pharmacist Melaka Hospital

Nurul Izaty Othaman

Pharmacist Padang Sebang Health Clinic

JOHOR

Raudhatun Sa'adiah Ithnin

Pharmacist Pharmaceutical Services Division, Johor

Ahmad Nizamuddin Malek Reedzwan

Pharmacist Pharmaceutical Services Division, Johor

Mohd Norhafizi Abdul Hamid

Pharmacist Kota Tinggi Hospital

Amiruddin Mad Yusuf

Pharmacist Chaah Health Clinic

Nor Lailah Mohamad

Pharmacist Enche’ Besar Hajjah Khalsom Hospital

Mohd Azmer Lias Pharmacist

Tenggaroh Health Clinic

PAHANG Prasyaanth a/l Nadarajan

Pharmacist Pharmaceutical Services Division, Pahang

Yasodha a/p Govindasamy

Pharmacist Raub Hospital

Juliza Yahya

Pharmacist Bandar Kuantan Health Clinic

Nurhazirah Saridin

Pharmacist Chini Health Clinic

KELANTAN

Nur Haida Muhamad Pharmacist

Pharmaceutical Services Division, Kelantan

Lim Ee Laine Pharmacist

Raja Perempuan Zainab II Hospital

Mohamad Zaid Md Nor Pharmacist Jeli Hospital

Nurul Hasikin Mohd Taib

Pharmacist Tanah Merah Hospital

TERENGGANU

Nurul Fatimah Sulaiman Pharmacist

Pharmaceutical Services Division, Terengganu

Norsyaheera Young Rockie Pharmacist

Bukit Payong Health Clinic

Nor Idamarlini Mohamad Pharmacist

Kemaman Hospital

Tun Maizatul Hafiza Tuan Ahmad Pharmacist

Hulu Terengganu Hospital

SARAWAK

Heriman Mahali

Pharmacist Makmal Ubat & Stor Miri

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Yong Hui Chu Pharmacist

Kota Sentosa Health Clinic

Vaisnavi a/p Kanthabalan Pharmacist

Sri Aman Hospital

Law Meng Hong Pharmacist

Makmal Ubat & Stor Bahagian Sarikei

Nikki Wong Shin Chyn Pharmacist

Sematan Health Clinic

SABAH

Noor Fazreen Mohd Aris

Pharmacist Pharmaceutical Services Division, Sabah

Lam Wai Hang

Pharmacist Duchess Of Kent Hospital

Dipisha a/p Babu

Pharmacist Tawau Hospital

Woo Chee Yen

Pharmacist Keningau Hospital

Tong See Nee

Pharmacist Kudat Hospital

Hana Fariza Muhammad Yunus

Pharmacist Kuala Penyu Hospital

LABUAN

Chan Chiew Ting Pharmacist

Pharmaceutical Services Division, Labuan

Tan Chee Hoong Pharmacist

Pharmaceutical Services Division, Labuan

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LIST OF TABLES

Table 1 Demographic characteristics of respondents

Table 2 Pattern of medicine use among respondents

Table 3 General spending on prescription and non-prescription medicines

in the last 3 months

Table 4 First action taken by respondents if experiencing any health problems

Table 5 Association between consumers’ first action taken by respondents if experiencing any health problems and demographics

Table 6 Consumers’ choice of facilities to obtain medicines

Table 7 (a) Factors associated with consumers’ choice of facilities to obtain medicines

Table 7 (b) Factors associated with consumers’ choice of facilities to obtain medicines

Table 8 Consumers' perceptions towards medicines labelling

Table 9 Factors affecting medicine-label reading and consumers’ perceived labelling adequacy

Table 10 Consumers' perceptions towards medicine pricing

Table 11 Association between medicine pricing and demographic characteristics

Table 12 Consumers' perceptions towards difficulties in reading medicine labels

Table 13 Association between difficulties in reading medicine labels with demographic characteristics

Table 14 Association between labelling satisfaction with demographic characteristics

Table 15 Association between ability to identify medicines by trade/generic name with demographic characteristics

Table 16 Association between the knowledge on proper use and storage of medicine with demographic characteristics

Table 17 Association between the awareness on the side effects and shelf life of medicines with demographic characteristics

Table 18 Factors affecting the awareness on food-medicines and modern-traditional medicines interaction

Table 19 Factors Affecting medication disposal

Table 20 Response to “Did you know that all modern and traditional medicines should be registered with Ministry of Health?” based on demographic characteristics

Table 21 Factors affecting knowledge on Meditag® availability

Table 22 Association between medication adherence and demographic characteristics

Table 23 First person to contact in case of medicine related concern

Table 24 Ease of obtaining medicines related information

Table 25 Frequency of obtaining medicines information from various information sources among Malaysian consumers

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Table 26 (a) Response to “How often do you obtain medicines information from printed materials/ internet, common information channels?” based on demographic characteristics

Table 26 (b): Response to “How often do you obtain medicines information from modern healthcare professionals/ traditional & complimentary practitioners/ friends, family or friends?” based on demographic characteristics

Table 27 Consumers’ Response to “Do you need written medicines information?” based on demographic characteristics

Table 28 Responses to “Do you require additional counselling from your pharmacists?” based on demographic characteristics

Table 29 Consumers’ Awareness of “Know Your Medicine” Campaign

Table 30 Consumers’ sources of information about the “Know Your Medicines” Campaign

Table 31 Attendance for “Know Your Medicine” Campaign Activities

Table 32 Responses to “Have you attended any of the campaign’s activities?” based on demographic characteristics

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1.0 INTRODUCTION

The discovery and use of medicines is associated with human evolution. It is also the everyday

task of hundreds of thousands of physicians, pharmacists and researchers worldwide. While

medications can help keep people healthy, they also can cause serious problems when used

incorrectly (1). It was estimated that 60% of medicines in public health facilities and 70% of

medicines in private facilities were prescribed and sold inappropriately in developing countries

(2). This inapt use of medicines results in not only reduced safety and quality of health care but

also increase the enormous wastage of health resources. Selection of medicines without

consideration for cost-effectiveness and efficacy, inefficient procurement of unnecessarily

expensive drugs, failure to prescribe medicines in accordance with standard treatment protocols,

poor dispensing practices resulting in medication errors, improper patients adherence to dosing

schedules and treatment regimens, and inappropriate self-medication are key issues associated

with irrational medicine use (3, 4). Inline to what is reported, Pirmohamed et al reported that

irrational use of medicines cost US$870 million to provide care and treatment for those who

were admitted to the hospital due to adverse medical events in the UK (5). Additionally,

irrational use of medicines was listed among the top 10 causes of morbidity and mortality in

the USA (6).

As a general concept, ‘‘Quality Use of Medicines (QUM)’’ is defined as ‘‘patients receive

medications appropriate to their clinical needs, in doses that meet their own individual

requirements for an adequate period of time, and the lowest cost to them and their community’’

(7, 8). It is now acknowledged that inappropriate use of drugs can relate to poor or negative

health outcomes, increase adverse events and health costs among healthcare consumers around

the world (9-12). This inappropriate medication use in the community is a complex issue with

no single factor being responsible. Minimising the risk of medications errors involves doctors,

patients, the practice and broader system based approaches to promote patient safety.

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Medication errors are estimated to affect around 10% of general practice patients and up to 25%

of high risk patients who report medicine adverse events (13).

In order to achieve a holistic process of medication use, the concept of ‘Quality Use of

Medicines’ (QUM) is been widely recognized and used around the world. The very concept

not only applies to medicines in the general practice setting, but also to all medicines used by

individual patients that can affect their health.

This whole-health system view is necessary as general practice patients obtain their

medications from a range of sources such as those initiated by themselves, other general

practitioners, other medical specialists, pharmacists and complementary therapists (14). Within

this context, it was reported that 55.6% of Malaysian consumers did not understand the proper

use of their medicines (15).

In order to embark upon the unsafe use of medicines in Malaysia, the Malaysian Government,

through the Ministry of Health (MOH) developed a comprehensive National Strategy for

Quality Use of Medicines-Consumers (QUM-C). A key principle of the strategy was the

primacy of consumers in any initiative to promote QUM through effective self-care practices

via “Know Your Medicines” campaign. Whereas patients and health care providers have

always shared these decisions to some extent, the current availability medications, both

prescriptions and non-prescriptions items allows greater potential range of decision making for

patients acting with and without direct provider guidance.

Therefore, this strategy was planned in tandem with the aspiration of one of the important

components in the Malaysian National Medicines Policy that directly stresses the importance

of the QUM concept among consumers of this nation. Thus, in order to understand how

effective Malaysian healthcare consumers use their medicines and the impact on promoting the

QUM campaign, it is essential to get current data so that the health authorities can plan

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necessary strategies to enhance consumers understanding on the concept of rational use of

drugs which is one of the main agenda in the Malaysian National Medicines Policy (16).

2.0 OBJECTIVES

i. To identify prescription and non-prescription medicine use pattern among consumers,

ii. To explore current knowledge of consumers on medicines usage,

iii. To document sources of medicines information channels that widely been used by

consumers and

iv. To evaluate consumers’ awareness toward educational programs on use of medicines.

3.0 METHODOLOGY

In order to achieve objectives of Survey, a cross sectional survey for a period of 3 months

(Starting from 1st June– 31st August 2015) was conducted with potential respondents across the

country. The questionnaire that was used in this study had been developed via consultation

with all the selected representatives involved with the “Malaysian Comprehensive National

Project on the Rational Use of Drugs” and extensive review of available literatures pertaining

to consumer surveys on rational use of medicines conducted elsewhere. The developed

questionnaire was tested for its content validity by engaging 250 patients from different

socioeconomic status and 50 pharmacists practicing in government health centres. The final

version of questionnaire consisted of six major domains, which includes demographic profile

of respondents (7 items), pattern of medicines use (3 items), access to medicines (2 items),

patient understanding on medicines (part 1 – 5 items, part 2 – 9 items, part 3 – 3 items), sources

of medicines information (5 items) and awareness of Know Your Medicines campaign (5

items). Distribution of the final version of the questionnaire was made via all the trained data

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collectors that had been appointed by the Pharmaceutical Services Department, The Ministry

of Health Malaysia.

Inclusion criteria

i. Age 18 years and above,

ii. Non-hospitalized,

iii. Able to read, write and listen (for those who are illiterate), and

iv. Provide written consent to participate (ethical requirement)

3.1 Sample size

A cross sectional survey-involving consumers from both urban and rural areas in Malaysia was

undertaken by trained data collectors in each state. For each state, consumers were approached

for participation base on ratio of rural: urban (3:1). Based on the 95% confidence interval and

margin of error of 5%, using sample size calculator, 385 participants were needed (17). As a

national survey with an estimation of 70% participation rate, individual data collectors in each

state administered the survey, the estimated sample size was 641. By applying a common

design effect of 4 for large sample surveys, the actual sample size of population that needs to

be surveyed was 2,564 (18). For the purpose on this study, 3,081 respondents were surveyed.

3.2 Sampling method

One stage random cluster sampling technique was employed to conduct this survey.

Respondents were approached in each state based on urban to rural ratio, which was 3:1 as

from population dataset available from Malaysian Department of Statistics. By using this

method, 2,250 respondents were surveyed from urban areas whereas 750 respondents were

surveyed from rural areas. In each state, 50-250 respondents were surveyed in each cluster

(rural and urban) based on population density respectively. As for Selangor, Sabah, and Johor,

which have a higher population density in Malaysia, a larger sample size was included for

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sampling purposes. For Selangor, sampling size was adjusted to 580 respondents and for Sabah

and Johor, around 350 respondents were surveyed (rural and urban) respectively. The public

areas, centres or recreational parks in each selected urban or rural cluster served as a point for

the conduct of the survey. The respective assigned data collectors surveyed those who visit to

this reference point randomly.

3.3 Ethical issue

The survey was approved by the Medical Research & Ethics Committee, Ministry of health

Malaysia (NMRR-15-265-24824). A written consent was obtained from each respondent

before the start of the survey. No findings, which could identify any individual participant, was

published. Participation in this research was entirely voluntary.

4.0 RESULTS

4.1 Demographic data

3081 responses were included in the final analysis. The mean age of the respondents was 39.81

(14.58) years. The cohort was dominated by females (1872, 60.8%) and 73.7% of the

respondents belonged to the urban locality. Preponderance of the respondents were reported

from the state of Selangor (581, 18.9%) followed by Sabah (359, 11.7%) and Johor (350,

11.4%). Malay participants consisted of 63.6% (n=1959) of the whole sample while 553

(17.9%) of the participants were Chinese followed by 374 (12.1%) belonging to the others

ethnic groups and 195 (6.3%) from the Indian ethnic group.

In terms of level of education, 1395 (45.3%) of the respondents received tertiary level of

education, while 1329 (43.1%) received the secondary level. Only 280 (9.1%) had primary

level of education and 77 (2.5%) had no formal education. 37% (n=1139) of the participants

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were government employee while private sector employee made up of 34.2% (n= 1054) of the

participants. Majority of the participants (n=2551, 82.8%) lived with their families. 16.0% of

the respondents had monthly income of more than 5000 Ringgit Malaysia (RM) followed by

473 (15.4%) and 385 (12.5%) having RM 1001-1500 and RM 2001-2500 of monthly income

respectively

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Table 1: Demographic characteristics of respondents

Characteristics Frequency (N) Percentage (%)

Age (39.81±14.58) years

18-27

28-37

38-47

48-57

58-67

68-77

> 77

734

913

472

485

357

101

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23.8

29.6

15.3

15.7

11.6

3.3

0.6

Gender

Male

Female

1209

1872

39.2

60.8

Locality

Urban

Rural

2271

810

73.7

26.3

State

Johor

Kedah

Kelantan

Melaka

Negeri Sembilan

Pahang

Perak

Perlis

Penang

Sabah

Sarawak

Selangor

Terengganu

WP Kuala Lumpur

WP Labuan

350

209

178

85

115

153

218

55

168

359

267

581

112

180

51

11.4

6.8

5.8

2.8

3.7

5.0

7.1

1.8

5.5

11.7

8.7

18.9

3.6

5.8

1.7

Ethnicity

Malay

Chinese

Indian

Others

1959

553

195

374

63.6

17.9

6.3

12.1

Educational level

Primary

Secondary

Tertiary

Non-formal

280

1329

1395

77

9.1

43.1

45.3

2.5

Occupation

Government

Private

Retired

Student

Unemployed

1139

1054

206

180

502

37.0

34.2

6.7

5.8

16.3

Living status

Alone

With family

With non family

467

2551

63

15.1

82.8

2.0

Monthly household income (Ringgit Malaysia)

<500

501-1000

1001-1500

1501-2000

2001-2500

2501-3000

3001-3500

3501-4000

4001-4500

4501-5000

>5000

278

264

473

222

385

172

314

116

233

132

492

9.0

8.6

15.4

7.2

12.5

5.6

10.2

3.8

7.6

4.3

16.0

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4.2 Pattern of medicines use

Table 2 shows the types of medicine used by consumers. Approximately, 30.3% of the

respondents reported to be on chronic medicines. Meanwhile 31.8% of the respondents were

taking vitamins, followed by minerals and supplements (21.5%). The use of non-processed and

processed herbs was reported in 7.9% and 11.5% of the respondents respectively. In addition,

16.8% of the respondents were taking herbal beverages and 10.9% of them were using beauty

care products.

Table 2: Pattern of medicine use among respondents

Items in questionnaire Frequency (N) Percentage (%)

Chronic medications

Yes

No

935

2146

30.3

69.7

Vitamins

Yes

No

980

2101

31.8

68.2

Minerals

Yes

No

661

2420

21.5

78.5

Non-processed herbs

Yes

No

244

2837

7.9

92.1

Processed herbs

Yes

No

355

2726

11.5

88.5

Herbal beverages

Yes

No

518

2563

16.8

83.2

Beauty care products derived from herbs, supplements, chemicals or

animals

Yes

No

337

2744

10.9

89.1

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Table 3 shows the general spending on prescription and non-prescription medicines in the last

3 months. Malaysian consumers spent the most for their medicines in private hospitals

(mean=RM296.98, SD=RM585.73), (Table 3). Medicines obtained from private pharmacies

constitute the second highest spending on medicines (mean=RM135.20, SD=RM171.63). An

average of RM127.72 (SD=RM187.07) was spent on medicines obtained from non-pharmacy

premises. Spending on medicines obtained from private clinics constitute the lowest

expenditure among Malaysian consumers (mean=RM127.50, SD=RM139.12). For the purpose

of data analysing, three data (>RM5000) were considered as extreme value and excluded in the

calculation.

Table 3. General spending on prescription and non-prescription medicines in the last 3 months

Medicines expenditure Mean (RM) SD

(RM)

Median

(RM)

IQR

(RM)

Medicines obtained from private clinic

(n= 692)

127.50 139.12 100.00 100.00

Medicines obtained from private hospital

(n=53)

296.98 585.73 100.00 225.00

Medicines obtained from private

pharmacy

(n=537)

135.20 171.63 100.00 105.00

Medicines obtained from non-pharmacy

(n=690)

127.72 187.07 70.00 130.00

4.3 Access to healthcare professionals

From Table 4, more than half of the respondents (1807, 58.6%) claimed that they prefer to

consult government doctor when are experienced with health problems. 23.9% and 12.1% of

the respondents claimed that they would consult a private doctor and self-medicate respectively.

Only 5.0% of the respondents claimed that they would consult retail pharmacists if they

experience any health problems. Consultation with traditional practitioner was the least

favoured by the respondents (9, 0.3%).

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Table 4: First action taken by respondents if experiencing any health problems

If you experience any health problems, what is the FIRST action that you’ll take? N (%)

Consult government doctor 1807 (58.6)

Consult private doctor 736 (23.9)

Consult pharmacist at pharmacy outlet 155 (5.0)

Consult traditional practitioner 9 (0.3)

Self-medication 374 (12.1)

The association between consumers’ first point of reference when experiencing any health

problems and demographic variables is reported in Table 5. The first reference point was found

to be significantly associated (p<0.001) with participants’ age, locality, ethnicity, educational

level, occupation, living status and monthly household income with effect size (φc) ranging

from 0.057 to 0.212 indicating a positive week relationship between demographics and related

study variable.

Table 5: Association between consumers’ first action taken by respondents if experiencing any health

problems and demographics

Statement p-value*

Age Gender Locality Ethnicity Educational

level

Occupation Living

status

Household

income

First action

taken by respondents if

experiencing

any health problem

<0.001

(φc=0.107)

0.081 <0.001

(φc=0.212)

<0.001

(φc=0.137)

<0.001

(φc=0.149)

<0.001

(φc=0.134)

0.012

(φc=0.057)

<0.001

(φc=0.149)

*Significant at p < 0.05; *Chi square test

25

4.4 Access to medicines

Table 6 presents consumers’ choice of facilities to obtain medicines. It was found that majority

of the respondents usually obtained their medicines from clinics (88.4%), hospitals (80.3%)

and community pharmacies (76.1%). A small proportion of consumers obtained medicines

from grocery shops (13.3%) traditional medicine outlet (7.3%), direct sales facilities (6.6%)

and night market (0.2%).

Table 6: Consumers’ choice of facilities to obtain medicines

Facility Preferred choice

N (%)

Non-preferred choice

N (%)

Hospital 2474 (80.3) 607 (19.7)

Clinic 2725 (88.4) 353 (11.5)

Community pharmacy 2346 (76.1) 733 (23.8)

Traditional medicines outlet 226 (7.3) 2855 (92.7)

Direct sales 204 (6.6) 2877 (93.4)

Grocery shop 411 (13.3) 2670 (86.7)

Night market 6 (0.2) 3075 (99.8)

Others 24 (0.8) 3057 (99.2)

Table 7 summarize the factors associated with consumers’ choice of facilities to obtain

medicines. Consumers’ age, area of settlement, ethnicity, education, occupation, living status

and monthly household income were found to significantly (p<0.05) affect their choice to

obtain medicines from hospitals. Rural dwellers (83.1%) and Indian respondents (89.2%),

preferred to obtain their medicines from hospitals. Additionally, hospital was also preferred as

a source of medicines by retirees (85.4%), having primary education (86.4%), living with

families (81.5%) and with monthly household income of RM 501-1000 (87.5%).

Consumers’ choice to obtain medicines from clinic was associated with majority of the

demographic variables. It was found that a higher proportion of consumers living in the urban

26

area (89.0%), females (88.7%), having college/university education and working with

government sector claimed to obtain their medicines from clinic compared to their counter

parts. On the other hand, consumers’ choice to obtain medicines from community pharmacy

were found to be influenced by the locality, age, ethnicity, education level, occupation and

monthly income. Respondents who lived in urban area (80.4%), aged between 18 to 27 years

(82.4%), of Indian ethnicity (82.5%) and with college/university education (84.7%) were

found to be more prone to choose community pharmacy as their source of medicine.

As for traditional medicine outlet, the number of respondents who prefer to obtain medicines

from this facility was significantly affected by their ethnicity, education and occupation.

Chinese respondents (13.9%) and those with no formal education (16.9%) obtained medicines

from traditional medicine outlet. Additionally, urban consumers (7.6%), females (7.8%)

and belonging to the Chinese ethnic group (7.8%) were found to independently influence

Malaysian consumers’ preferences to obtain their medicines from direct sales facilities.

Besides that, consumers’ locality, age, gender, ethnicity, education level, occupation and

monthly income were also found to significantly affect the participants’ choice in obtaining

medicines from a grocery shop. Participants from urban area (14.1%), of Malay ethnicity

(15.1%) and with no formal education (19.5%) claimed to prefer to obtain medicines from a

grocery shop. Educational status was also found to affect those who have chosen night market

as their source of medicine. Consumers with no formal education (2.6%) were found to prefer

to obtain their medicines from night market compared to the other respondents.

27

Table 7 (a): Factors associated with consumers’ choice of facilities to obtain medicines

Demographic

Characteristics

Consumers’ Choice of Facilities to Obtain Medicines

Hospital Clinic Community pharmacy Traditional medicine outlet

Chosen Not

chosen p-value* Chosen

Not


Not


Not

chosen p-value*

Locality

Urban 1801

(72.8)

470

(27.2) 0.020 2022

(89.0)

247

(10.9)

0.096 1825

(80.4)

444

(19.6) <0.001 172

(7.6)

2099

(92.4)

0.395

Rural 673

(83.1)

137

(16.9)

703

(86.8)

106

(13.1)

521

(64.3)

289

(35.7)

54

(6.7)

756

(93.3)

Age

18-27 557

(75.8)

177

(24.2) 0.013 657

(89.6)

76

(10.4) 0.033 598

(82.4)

136

(17.6) <0.001 45

(6.2)

689

(93.8)

0.088

28-37 755

(82.6)

158

(17.4)

822

(90.0)

91

(10.0)

721

(78.9)

192

(21.1)

58

(6.3)

855

(93.6)

38-47 370

(78.3)

102

(21.7)

416

(88.5)

54

(11.5)

362

(77.0)

108

(23.0)

31

(6.5)

441

(93.4)

48-57 398

(82.0)

87

(18.0)

422

(87.0)

63

(13.0)

348

(71.7)

137

(28.3)

46

(9.4)

439

(90.5)

58-67 296

(82.9)

61

(17.1)

300

(84.0)

57

(16.0)

242

(67.7)

115

(32.3)

36

(10.0)

321

(90.0)

68-77 83

(80.1)

18

(19.9)

89

(88.1)

12

(11.9)

60

(59.4)

41

(40.6)

9

(8.9)

92

(91.0)

> 77 15

(78.9)

4

(21.1)

19

(100.0)

0

(0)

15

(78.9)

4

(21.1)

1

(5.2)

18

(94.7)

Gender

Male 983

(81.3)

226

(18.6)

0.258 1066

(88.2)

142

(11.8)

0.675 915

(75.7)

293

(24.2)

0.653 96

(7.9)

1113

(92.1)

0.301

Female 1491

(79.6)

381

(20.4)

1659

(88.7)

211

(11.2)

1431

(76.4)

440

(23.6)

130

(6.9)

1742

(93.1)

Ethnicity

Malay 1574

(80.3)

385

(19.7)

<0.001 1772

(90.5)

184

(9.5)

<0.001 1505

(76.9)

452

(23.1)

<0.001 133

(6.7)

1826

(93.2)

<0.001

Chinese 402

(72.6)

151

(27.3)

497

(89.8)

56

(10.1)

440

(79.5)

113

(20.4)

77

(13.9)

476

(86.1)

Indian 174

(89.2)

21

(10.7)

171

(87.6)

24

(12.3)

161

(82.5)

34

(17.4)

12

(6.1)

183

(93.8)

Others 324

(86.0)

50

(14.0)

285

(76.2)

89

(23.7)

240

(64.1)

134

(35.8)

4

(1.1)

370

(98.9)

28

Demographic

Characteristics



Chosen Not


Not


Not


Not

chosen p-value*

Education Level

Primary School 242

(86.4)

38

(13.7) <0.001 230

(82.1)

50

(17.9) <0.001 174

(62.1)

106

(37.7) <0.001 18

(6.4)

262

(93.6) 0.013

Secondary School 1100

(82.7)

229

(17.2)

1150

(86.6)

178

(13.4)

952

(71.7)

376

(28.3)

94

(7.0)

1235

(93.0)

College/ University 1070

(76.7)

325

(23.2)

1282

(92.0)

111

(8.0)

1181

(84.7)

213

(15.3)

101

(7.2)

1294

(92.8)

No Formal Education 62

(80.5)

15

(19.5)

63

(81.8)

14

(18.2)

39

(50.6)

38

(49.4)

13

(16.9)

64

(83.1)

Occupation

Government 919

(80.1)

220

(19.9) 0.006 1027

(90.4)

109

(9.6) 0.005 933

(82.0)

204

(18.0) <0.001 74

(6.5)

1065

(93.5) 0.008

Private/Self Employed 835

(79.2)

219

(20.8)

928

(88.0)

126

(12.0)

805

(76.4)

249

(23.7)

71

(6.7)

983

(93.3)

Retired 176

(85.4)

30

(14.6)

176

(85.4)

30

(14.6)

133

(64.6)

73

(35.4)

28

(12.3)

178

(87.7)

Student 129

(71.7)

51

(28.3)

166

(88.2)

14

(11.8)

157

(87.2)

23

(12.8)

15

(8.3)

165

(91.7)

Unemployed 415

(82.7)

87

(17.3)

428

(85.2)

74

(14.8)

318

(63.3)

184

(36.7)

38

(7.6)

464

(92.4)

Living Status

Alone 348

(74.5)

119

(25.5) 0.002 417

(89.3)

50

(10.7)

0.786 354

(75.8)

113

(24.2)

0.331 40

(8.6)

427

(91.4)

0.417

With Family 2078

(81.5)

473

(18.5)

2251

(88.3)

297

(11.7)

1939

(76.0)

610

(24.0)

183

(7.2)

2368

(92.8)

With Non-Family 48

(76.2)

15

(23.8)

57

(90.5)

6

(9.5)

53

(84.1)

10

(15.9)

3

(4.8)

60

(95.2)

Monthly Income

≤RM 500 223

(80.5)

54

(19.5) <0.001 230

(83.0)

47

(17.0) <0.001 187

(67.5)

90

(32.5) <0.001 19

(6.9)

258

(93.1)

0.999

RM 501-1,000 231

(87.5)

33

(12.5)

204

(77.3)

60

(22.7)

157

(59.4)

107

(40.5)

20

(7.6)

244

(92.4)

RM 1,001-1,500 387

(81.8)

86

(18.2)

418

(88.4)

54

(11.6)

332

(70.2)

140

(29.8)

36

(7.7)

437

(92.3)

RM 1,501-2,000 191

(86.0)

31

(14.0)

196

(88.3)

26

(11.7)

161

(72.5)

61

(27.4)

17

(7.7)

205

(92.3)

29

Demographic

Characteristics



Chosen Not


Not


Not


Not

chosen p-value*

RM 2,001-2,500 320

(83.1)

65

(16.9)

342

(88.8)

42

(11.2)

300

(77.9)

84

(22.1)

25

(6.5)

360

(93.5)

RM 2,501-3,000 138

(80.2)

34

(19.8)

160

(93.0)

12

(7.0)

132

(76.7)

40

(23.3)

14

(8.2)

158

(91.8)

RM 3,001-3,500 247

(78.7)

67

(21.3)

281

(89.5)

32

(10.5)

256

(81.5)

58

(18.5)

24

(7.6)

290

(92.3)

RM 3,501-4,000 83

(71.6)

33

(28.4)

101

(87.1)

15

(12.9)

90

(77.5)

26

(22.5)

10

(8.7)

106

(91.3)

RM 4,001-4,500 184

(79.0)

49

(21.0)

216

(92.7)

17

(7.3)

200

(85.8)

33

(14.2)

17

(7.3)

216

(92.7)

RM 4,501-5,000 104

(78.8)

28

(21.2)

124

(94.0)

8

(6.0)

114

(86.4)

18

(13.6)

11

(8.4)

121

(91.6)

> RM 5,000 365

(74.2)

127

(25.8)

452

(91.9)

40

(8.1)

416

(84.6)

76

(15.4)

33

(6.8)

459

(93.2)

*Significant at p < 0.05

30

Table 7 (b): Factors associated with consumers’ choice of facilities to obtain medicines

Demographic

Characteristics


Direct Sale Grocery Shop Night market Others

Chosen Not


Not


Not


Not

chosen p-value*

Locality

Urban 172

(7.6)

2099

(92.4) <0.001 320

(14.1)

1951

(85.9) 0.040 3

(0.2)

2268

(99.)

0.187 18

(0.8)

2253

(99.2)

0.885

Rural 32

(4.0)

778

(96.0)

91

(11.2)

719

(88.8)

3

(0.4)

807

(99.6)

6

(0.8)

804

(99.2)

Age

18-27 36

(5.0)

698

(95.0)

0.241 133

(18.2)

601

(81.8) 0.002 2

(0.3)

732

(99.7)

0.652 3

(0.5)

731

(99.5)

0.361

28-37 66

(7.3)

847

(92.7)

106

(11.7)

807

(88.3)

1

(0.2)

912

(99.8)

7

(0.8)

906

(99.2)

38-47 32

(6.8)

440

(93.2)

61

(13.0)

411

(87.0)

0

(0)

472

(100.0)

5

(1.1)

467

(98.9)

48-57 42

(8.7)

443

(91.3)

54

(11.2)

431

(88.8)

1

(0.3)

484

(99.7)

2

(0.5)

483

(99.5)

58-67 22

(6.2)

335

(93.8)

45

(12.7)

312

(87.3)

2

(0.6)

355

(99.4)

6

(1.7)

351

(98.3)

68-77 5

(5.0)

96

(95.0)

9

(9.0)

92

(91.0)

0

(0)

101

(100.0)

1

(1.0)

100

(99.0)

> 77 1

(5.3)

18

(94.7)

3

(15.8)

16

(84.2)

0

(0)

19

(100.0)

0

(0)

19

(100.0)

Gender

Male 59

(4.9)

1150

(95.1) 0.002 184

(15.3)

1025

(84.7) 0.014 4

(0.4)

1205

(99.6)

0.169 9

(0.8)

1200

(99.2)

0.861

Female 145

(7.8)

1727

(92.2)

227

(12.2)

1645

(87.8)

2

(0.2)

1870

(99.8)

15

(0.9)

1857

(99.1)

Ethnicity

Malay 138

(7.1)

1821

(92.9) 0.046 294

(15.1)

1665

84.9() 0.003 4

(0.3)

1955

(99.7)

0.624 17

(0.9)

1942

(99.1)

0.650

Chinese 43

(7.8)

510

(92.2)

55

(10.0)

498

(90.0)

1

(0.2)

552

(99.8)

4

(0.8)

549

(99.2)

Indian 7

(3.6)

188

(96.4)

25

(12.9)

170

(87.1)

1

(0.6)

194

(99.4)

2

(1.1)

193

(98.9)

Others 16

(4.3)

358

(95.7)

37

(9.9)

337

(90.1)

0

(0)

374

(100.0)

1

(0.3)

373

(99.7)

31

Demographic

Characteristics



Chosen Not


Not


Not


Not

chosen p-value*

Education Level

Primary School 19

(6.8)

261

(93.2)

0.730 25

(9.0)

255

(91.0) 0.023 1

(0.4)

279

(99.6) <0.001 1 (4.2)

(0.4)

279

(99.6) 0.014

Secondary School 85

(6.4)

1244

(93.6)

194

(14.6)

1135

(85.4)

0

(0)

1329

(100.0)

11

(0.9)

1318

(99.1)


(7.0)

1298

(93.0)

177

(12.7)

1218

(87.3)

3

(0.3)

1392

(99.7)

9

(0.7)

1386

(99.3)


(3.9)

74

(96.1)

15

(19.5)

62

(80.5)

2

(2.6)

75

(97.4)

3

(3.9)

74

(96.1)

Occupation

Government 78

(6.9)

1061

(93.1)

0.811 113

(10.0)

1026

(90.0) <0.001 2

(0.2)

1137

(99.8)

0.578 9

(0.8)

1130

(99.2)

0.205


(6.3)

988

(93.7)

161

(15.3)

893

(84.7)

1

(0.1)

1053

(99.9)

6

(0.6)

1048

(99.4)

Retired 12

(5.9)

194

(94.1)

25

(12.2)

181

(87.8)

1

(0.5)

205

(99.5)

4

(2.0)

202

(98.0)

Student 10

(5.6)

170

(94.4)

42

(23.4)

138

(76.6)

0

(0)

180

(100.0)

0

(0)

180

(100.0)

Unemployed 38

(7.6)

464

(92.4)

70

(14.0)

432

(86.0)

2

(0.4)

500

(99.6)

5

(1.0)

497

(99.0)

Living Status

Alone 31

(6.7)

436

(93.3)

0.349 70

(15.0)

397

(85.0)

0.419 2

(0.5)

465

(99.5)

0.444 4

(0.9)

463

(99.1)

0.767

With Family 166

(6.6)

2385

(93.4)

331

(13.0)

2220

(87.0)

4

(0.2)

2547

(99.8)

20

(0.2)

2531

(99.2)

With Non-Family 7

(11.2)

56

(88.8)

10

(15.9)

53

(84.1)

0

(0)

63

(100.0)

0

(0)

63

(100.0)

Monthly Income

≤RM 500 13

(4.7)

264

(95.3)

0.143 36

(13.0)

241

(87.0) 0.020 0

(0)

277

(100.0)

0.613 4

(1.5)

273

(98.5)

0.716

RM 501-1,000 10

(3.8)

254

(96.2)

44

(16.4)

220

(83.3)

0

(0)

264

(100.0)

2

(0.8)

262

(99.2)

RM 1,001 1,500 25

(5.3)

448

(94.7)

80

(17.0)

393

(83.0)

1

(0.3)

472

(99.7)

2

(0.5)

471

(99.5)

RM 1,501-2,000 15

(6.8)

207

(93.2)

31

(14.0)

191

(86.0)

0

(0)

222

(100.0)

1

(0.5)

221

(99.5)

RM 2,001-2,500 22

(5.8)

363

(94.2)

48

(12.5)

337

(87.5)

2

(0.6)

383

(99.4)

5

(1.3)

380

(98.7)

32

Demographic

Characteristics



Chosen Not


Not


Not


Not

chosen p-value*

RM 2,501-3,000 13

(7.6)

159

(92.4)

18

(10.5)

154

(89.5)

0

(0)

172

(100.0)

2

(1.2)

170

(98.8)

RM 3,001-3,500 22

(7.1)

292

(92.9)

38

(12.2)

276

(87.8)

1

(0.4)

313

(99.6)

2

(0.7)

312

(99.3)

RM 3,501-4,000 8

(6.9)

108

(93.1)

21

(18.2)

95

(81.8)

0

(0)

116

(100.0)

0

(0)

116

(100.0)

RM 4,001-4,500 19

(8.2)

214

(91.8)

22

(9.5)

211

(90.5)

1

(0.5)

232

(99.5)

1

(0.5)

232

(99.5)

RM 4,501-5,000 13

(9.9)

119

(90.1)

8

(6.1)

124

(93.9)

1

(0.8) 131

(99.2)

0

(0)

132

(100.0)

> RM 5,000 44

(9.0)

448

(91.0)

65

(13.3)

427

(86.7)

0

(0)

492

(100.0)

5

(1.1)

487

(98.9)


33

4.5 Perceptions towards medicines labelling

As reported in table 8, majority (90.3%) of the respondents agreed that they are provided with

adequate information regarding medication labels. Moreover, 93.2% of the respondents agreed

that they read the information on the medicine labels before consuming the medicine.

Table 8: Consumers' perceptions towards medicines labelling

Statements Yes

(n, %)

No

(n, %)

Every time you are supplied with medicines, are you given adequate information on

your medicines label?

2783 (90.3) 298 (9.7)

Before taking your medicines, do you read the information on your medicines label? 2873 (93.2) 208 (6.8)

Table 9 summarizes the consumers’ perception towards medicines labelling. Consumers’

perceived labelling adequacy was significantly associated with the locality, age, gender,

ethnicity, education level, occupation and monthly income (P < 0.05). Meanwhile, the habit

of reading a label prior to using a medicine was found to be associated with consumers’ age,

gender, ethnicity, education level, occupation, living status and monthly income.

34

Table 9: Factors affecting medicine-label reading and consumers’ perceived labelling adequacy

Demographic

Characteristics

Outcome

Labelling adequacy Read Label

Yes

n (%)

No

n (%)

p-value* Yes

n (%)

No

n (%)

p-value*

Locality

Urban

Rural

2023 (89.0)

760 (93.8)

248 (11.0)

50 (6.2) <0.001 2115 (93.1)

758 (93.5)

156 (6.9)

52 (6.5)

0.662

Age

18-27

28-37

38-47

48-57

58-67

68-77

> 77

637 (86.8)

820 (89.8)

430 (91.1)

452 (93.1)

331 (92.7)

95 (94.0)

18 (94.7)

97 (13.2)

93 (10.2)

42 (8.9)

33 (6.9)

26 (7.3)

6 (6.0)

1 (5.3)

0.003 691 (94.1)

871 (95.3)

444 (94.0)

445 (91.7)

325 (91.0)

81 (80.2)

16 (84.2)

43 (5.9)

42 (4.7)

28 (6.0)

40 (8.3)

32 (9.0)

20 (19.8)

3 (15.8)

<0.001

Gender

Male

Female

1074 (88.8)

1709 (91.2)

135 (11.2)

163 (8.8) 0.024 1109 (91.7)

1764 (94.2)

100 (8.3)

108 (5.8) 0.007

Ethnicity

Malay

Chinese

Indian

Others

1798 (91.7)

468 (84.6)

168 (86.1)

349 (93.3)

161 (8.3)

85 (15.4)

27 (13.9)

25 (6.7)

<0.001 1849 (94.3)

488 (88.2)

182 (93.3)

354 (94.6)

110 (5.7)

65 (11.8)

13 (6.7)

20 (5.4)

<0.001

Education Level

Primary School

Secondary School

College/ University

No Formal Education

258 (92.1)

1236 (93.0)

1217 (87.2)

72 (93.5)

22 (7.9)

93 (7.0)

178 (12.8)

5 (6.5)

<0.001 241 (86.0)

1239 (93.2)

1329 (95.2)

64 (83.1)

39 (14.0)

90 (6.8)

66 (4.8)

13 (16.9)

<0.001

Occupation

Government

Private/Self Employed

Retired

Student

Unemployed

1018 (89.3)

944 (89.5)

198 (96.1)

152 (84.4)

471 (93.8)

121 (10.7)

110 (10.6)

8 (3.9)

28 (15.6)

31 (6.2)

<0.001 1103 (96.8)

970 (92.0)

187 (90.7)

167 (92.7)

446 (88.8)

36 (3.2)

84 (8.0)

19 (9.3)

13 (7.3)

56 (11.2)

<0.001

Living Status

Alone

With Family

With Non-Family

420 (89.9)

2305 (90.3)

58 (92.0)

47 (10.1)

246 (9.7)

5 (8.0)

0.860 448 (95.9)

2369 (92.8)

56 (88.8)

19 (4.1)

182 (7.2)

7 (11.2)

0.020

Monthly Income

≤RM 500

RM 501-1,000

RM 1,001-1,500

RM 1,501-2,000

RM 2,001-2,500

RM 2,501-3,000

RM 3,001-3,500

RM 3,501-4,000

RM 4,001-4,500

RM 4,501-5,000

> RM 5,000

255 (92.0)

240 (90.9)

441 (93.2)

209 (94.1)

339 (88.0)

156 (90.6)

287 (91.4)

103 (88.7)

210 (90.1)

115 (87.1)

427 (86.7)

22 (8.0)

24 (9.1)

32 (6.8)

13 (5.9)

46 (12.0)

16 (9.4)

27 (8.6)

13 (11.3)

23 (9.9)

17 (12.9)

65 (13.3)

0.021 246 (88.8)

241 (91.2)

446 (94.2)

211 (95.0)

361 (93.7)

170 (98.8)

289 (92.0)

104 (89.6)

218 (93.5)

125 (94.6)

461 (93.6)

31 (11.2)

23 (8.8)

27 (5.8)

11 (5.0)

24 (6.3)

2 (1.2)

25 (8.0)

12 (10.4)

15 (6.5)

7 (5.4)

31 (6.4)

0.006


35

According to three quarter of the respondents (75.2%), price-related information necessary to

be displayed on the medicine label (Table 10). 68.5% of the respondents rated price as a key

variable in selection and purchasing of medicines. However, 1251 (40.6%) of the respondents

claimed that price of medicine has no impact on their medication taking behaviour.

Table 10: Consumers' perceptions towards medicine pricing

Statements Yes

(n, %)

No

(n, %)

Is price information necessary to be displayed on the medicines label? 2316 (75.2) 765 (24.8)

Does price information on medicines label improve your adherence to medication? 1830 (59.4) 1251 (40.6)

Does price information on medicines label help you to make choices when

purchasing medicines?* 2112 (68.5) 965 (31.3)

*Missing value=4

The associations between price-related issues and demographic variables are presented in Table

11. The importance of pricing information on medicine label was significantly associated with

age, gender, ethnicity, educational level, occupation, living status and monthly income.

Additionally, the correlation among medicine price and medication adherence was also

significant in terms of respondents’ locality, age, ethnicity, and occupation. In relation to price

and buying behaviour, all demographic variables reported a significant association as shown in

Table 11.

36

Table 11: Association between medicine pricing and demographic characteristics

Demographic

Characteristics

Outcome

Is price information necessary to be displayed

on the medicines label?

Does price information on medicines label

improve your adherence to medication?

Does price information on medicines label help

you to make choices when purchasing

medicines?

Yes No p-value* Yes No p-value* Yes No p-value*

Locality

Urban 1689

(74.3)

582

(25.7) 0.086

1289

(56.7)

982

(43.3) <0.001

1526

(67.1)

741

(32.9) 0.011

Rural 627

(77.4)

183

(22.6)

541

(66.7)

269

(33.3)

586

(72.3)

224

(27.7)

Age

18-27 555

(75.6)

179

(24.4)

<0.001

420

(57.2)

314

(42.8)

0.008

513

(69.9)

221

(30.2)

<0.001

28-37 734

(80.3)

179

(19.7)

556

(60.8)

357

(39.2)

676

(74.0)

236

(26.0)

38-47 354

(75.0)

118

(25.0)

299

(63.3)

173

(36.7)

319

(67.5)

153

(32.5)

48-57 348

(71.7)

137

(28.3)

284

(58.5)

201

(41.5)

318

(65.5)

166

(34.5)

58-67 253

(70.8)

104

(29.2)

215

(60.2)

142

(39.8)

235

(65.8)

121

(34.2)

68-77 62

(61.3)

39

(38.7)

51

(50.4)

50

(49.6)

45

(44.5)

56

(55.6)

> 77 10

(52.6)

9

(47.4)

5

(26.3)

14

(73.7)

7

(36.8)

12

(63.2)

Gender

Male 870

(71.9)

339

(28.1) 0.001

703

(58.1)

506

(41.9) 0.257

804

(66.5)

404

(33.5) 0.041

Female 1446

(77.2)

426

(22.8)

1127

(60.2)

745

(39.8)

1308

(69.8)

561

(30.2)

Ethnicity

Malay 1489

(76.0)

470

(24.0)

0.005

1208

(61.6)

751

(38.4)

<0.001

1347

(68.7)

608

(31.3)

0.033

Chinese 390

(70.5)

163

(29.5)

276

(49.9)

277

(50.1)

368

(66.5)

185

(33.5)

Indian 139

(71.2)

56

(28.8)

107

(54.8)

88

(45.2)

122

(62.5)

73

(37.5)

Others 298

(79.6)

76

(20.4)

239

(63.9)

135

(36.1)

275

(73.5)

99

(26.5)

37

Demographic

Characteristics

Outcome







medicines?


Education Level

Primary School 183

(65.3)

97

(34.7)

<0.001

163

(58.2)

117

(41.8)

0.074

165

(58.9)

114

(41.1)

<0.001


(74.7)

336

(25.3)

803

(60.4)

526

(39.6)

867

(65.2)

459

(34.8)


(78.4)

301

(21.6)

829

(59.4)

566

(40.6)

1045

(74.9)

350

(25.1)


(59.7)

31

(40.3)

35

(45.4)

42

(54.6)

35

(45.4)

42

(54.6)

Occupation

Government 945

(82.9)

194

(17.1)

<0.001

752

(66.0)

387

(34.0)

<0.001

847

(74.3)

292

(25.7)

<0.001


(71.8)

297

(28.2)

581

(55.1)

473

(44.9)

699

(66.3)

354

(33.7)

Retired 134

(65.0)

72

(35.0)

118

(57.2)

88

(42.8)

127

(61.6)

78

(38.4)

Student 127

(70.5)

53

(29.5)

96

(53.3)

84

(46.7)

121

(67.2)

59

(32.8)

Unemployed 353

(70.3)

149

(29.7)

283

(56.3)

219

(43.7)

318

(63.3)

182

(36.7)

Living status

Alone 372

(79.6)

95

(20.4)

0.044

298

(63.8)

169

(36.2)

0.094

351

(75.1)

116

(24.9)

0.005 With Family 1899

(74.4)

652

(25.6)

1493

(58.5)

1058

(41.5)

1719

(67.3)

828

(32.7)

With Non-Family 18

(28.5)

45

(71.5)

39

(61.9)

24

(38.1)

42

(66.6)

21

(33.4)

Monthly income

0.002

0.480

0.006

≤RM 500 185

(66.7)

92

(33.3)

151

(54.5)

126

(45.5)

174

(62.8)

103

(37.2)

RM 501-1000 180

(68.1)

84

(31.9)

150

(56.8)

114

(43.2)

162

(61.3)

100

(38.7)

RM 1001- 1500 353

(74.6)

120

(25.4)

286

(60.4)

187

(39.6)

300

(63.4)

172

(36.6)

RM 1501- 2000 167

(75.2)

55

(24.8)

138

(62.1)

84

(37.9)

153

(68.9)

69

(31.1)

38

Demographic

Characteristics

Outcome







medicines?


RM 2001- 2500 299

(77.6)

86

(22.4)

236

(61.2)

149

(38.8)

268

(69.6)

116

(30.4)

RM 2501-3000 134

(77.9)

38

(22.1)

110

(63.9)

62

(36.1)

119

(69.1)

53

(30.9)

RM 3001-3500 251

(79.9)

63

(20.1)

189

(60.1)

125

(39.9)

233

(74.2)

81

(25.8)

RM 3501-4000 87

(75.0)

29

(25.0)

64

(55.1)

52

(44.9)

85

(73.2)

31

(26.8)

RM 4001-4500 187

(80.2)

46

(19.8)

141

(60.5)

92

(39.5)

165

(70.8)

68

(29.2)

RM 4501-5000 106

(80.3)

26

(19.7)

84

(63.6)

48

(36.4)

97

(73.4)

35

(26.6)

> RM 5000 366

(74.3)

126

(25.7)

281

(57.1)

211

(42.9)

355

(72.1)

137

(27.9)


39

Table 12 presents the respondents’ perception towards difficulties in reading medicine labels.

Majority (n=2600, 84.4%) reported no problem in reading medicine labels supplied from public

hospitals or clinics. In terms of non-adequacy, medicine labels issued from private clinics were

rated as unsatisfactory, as 446 (14.5%) of the respondents had problems in understanding

medicine labels.

Respondents were found satisfied with the labelling information provided by public hospitals

and clinics (n=2664, 86.5%). Dissatisfaction with labelling information was reported from

private clinics whereby 16.6% of the respondents were not satisfied with the information received

from the private clinics.

Table 12: Consumers' perceptions towards difficulties in reading medicine labels

Statements Yes

(n, %)

No

(n, %)

Do you have trouble reading label for medicines supplied from:*

Government hospital/clinic

Private hospital

Private clinics

Community pharmacy

328 (10.6)

245 (8.0)

446 (14.5)

327 (10.6)

2600 (84.4)

1544 (50.1)

1908 (61.9)

1937 (62.9)

Are you satisfied with the information written on the labels given by:**

Government hospital/clinic

Private hospital

Private clinics

Community pharmacy

2664 (86.5)

1486 (48.2)

1813 (58.8)

1807 (58.6)

251 (8.1)

269 (8.7)

510 (16.6)

429 (13.9)

Missing values: *=153, 1292, 727, 817 and **166, 1326, 758, 845 respectively

40

Further exploration to identify factors that were associated with difficulties in reading medicines

label found that consumers’ locality, age, ethnicity, education level, occupation, living status and

monthly income level were among the factors that affect consumers’ perceived difficulty in

reading medicines label obtained from various health institutions (Table 13). Respondents who

had primary education, privately employed and with income RM 501-1000 generally perceived

more difficulty in reading medicines label obtained from government facilities. Nevertheless, we

found that age, education level and living status were not significantly associated with difficulties

in reading medicines label in public hospitals/clinics.

From Table 14, significant association between satisfaction with the information written in the

labels by various healthcare institutes and demographic variables were reported. The study found

that for public hospitals/clinics, respondents’ ethnicity and occupation were significantly

associated with labelling satisfaction. Nevertheless, factors associated with satisfaction with the

labelling from private hospitals, private clinics and community pharmacies were participants’

locality, age, ethnicity, education level, occupation, living status and monthly income.

41

Table 13: Association between difficulties in reading medicine labels with demographic characteristics

Demographic

Characteristics

Outcome

Difficulties in Reading Medicines

Label from Government Hospital/

Clinics


Label Private Hospitals


Label from Private Clinics

Difficulties in Reading Medicines Label

from Community Pharmacies

Yes No p-value* Yes No p-value* Yes No p-value* Yes No p-value*

Locality

Urban 240

(10.6)

1893

(83.4) 0.003

182

(8.0)

1201

(52.9) <0.

001

345

(15.2)

1502

(66.1) <0.001

260

(11.4)

1485

(65.4) <0.001

Rural 88

(10.9)

707

(87.3)

63

(7.8)

343

(42.3)

101

(12.5)

406

(50.1)

67

(8.3)

452

(55.8)

Age

18-27 83

(11.3)

604

(82.3)

0.255

72

(9.8)

424

(57.8)

<0.001

111

(15.1)

503

(68.5)

<0.001

81

(11.0)

508

(69.2)

<0.001

28-37 89

(9.7)

791

(86.6)

87

(9.5)

538

(58.9)

155

(17.0)

618

(67.7)

93

(10.2)

636

(69.7)

38-47 41

(8.7)

400

(84.7)

29

(6.1)

230

(48.7)

54

(11.4)

302

(64.0)

42

(8.9)

306

(64.8)

48-57 57

(11.8)

404

(83.3)

34

(7.0)

204

(42.1)

77

(15.9)

257

(53.0)

65

(13.4)

266

(54.8)

58-67 42

(11.8)

299

(83.8)

17

(4.8)

114

(31.9)

39

(10.9)

167

(46.8)

35

(9.8)

169

(47.3)

68-77 13

(12.9)

87

(86.1)

6

(5.9)

31

(30.7)

10

(9.9)

47

(46.5)

11

(10.9)

39

(38.6)

> 77 3

(15.8)

15

(78.9)

0

(0)

3

(15.8)

0

(0)

14

(73.7)

0

(0)

13

(68.4)

Gender

Male 129

(10.7)

1014

(83.9) 0.486

96

(7.9)

611

(50.5) 0.696

173

(14.3)

746

(61.7) 0.775

127

(10.5)

745

(61.6) 0.199

Female 199

(10.6)

1586

(84.7)

149

(8.0)

933

(49.8)

273

(14.6)

1162

(62.1)

200

(10.7)

1192

(63.7)

Ethnicity

Malay 187

(9.5)

1712

(87.4)

<0.001

165

(8.4)

1014

(51.8)

<0.001

297

(15.2)

1264

(64.5)

<0.001

217

(11.1)

1272

(64.9)

<0.001

Chinese 58

(10.5)

421

(76.1)

40

(7.2)

293

(53.0)

86

(15.6)

354

(64.0)

60

(10.8)

357

(64.6)

Indian 33

(16.9)

158

(81.0)

21

(10.8)

95

(48.7)

41

(21.0)

102

(52.3)

26

(13.3)

117

(60.0)

Others 50

(13.4)

309

(82.6)

19

(5.1)

142

(38.0)

22

(5.9)

188

(50.3)

24

(6.4)

191

(51.1)

42

Demographic

Characteristics

Outcome



Clinics








Education Level

Primary School 38

(13.6)

238

(85.0)

0.475

18

(6.4)

75

(26.8)

<0.001

32

(11.4)

109

(38.9)

<0.001

25

(8.9)

118

(42.1)

<0.001


(11.9)

1105

(83.1)

90

(6.8)

599

(45.1)

172

(12.9)

786

(59.1)

140

(10.5)

769

(57.9)


(8.8)

1192

(85.4)

134

(9.6)

856

(61.4)

235

(16.8)

987

(70.8)

154

(11.0)

1026

(73.5)

No Formal

Education

9

(11.7)

65

(84.4)

3

(3.9)

14

(18.2)

7

(9.1)

26

(33.8)

8

(10.4)

24

(31.2)

Occupation

Government 95

(8.3)

1017

(89.3)

<0.001

114

(10.0)

656

(57.6)

<0.001

199

(17.5)

753

(66.1)

<0.001

122

(10.7)

817

(71.7)

<0.001

Private/Self

Employed

134

(12.7)

827

(78.5)

79

(7.5)

550

(52.2)

146

(13.9)

673

(63.9)

123

(11.7)

643

(61.0)

Retired 24

(11.7)

181

(87.9)

11

(5.3)

89

(43.2)

18

(8.7)

108

(52.4)

21

(10.2)

107

(51.9)

Student 20

(11.1)

145

(80.6)

15

(8.3)

99

(55.0)

25

(13.9)

126

(70.0)

16

(8.9)

125

(69.4)

Unemployed 55

(11.0)

430

(85.7)

26

(5.2)

150

(29.9)

58

(11.6)

248

(49.4)

45

(9.0)

245

(48.8)

Living Status

Alone 43

(9.2)

402

(86.1)

0.477

40

(8.6)

281

(60.2)

<0.001

69

(14.8)

326

(69.8)

<0.001

45

(9.6)

328

(70.2)

<0.001 With Family 275

(10.8)

2147

(84.2)

201

(7.9)

1231

(48.3)

369

(14.5)

1535

(60.2)

275

(10.8)

1560

(61.2)

With Non-Family 10

(15.9)

51

(81.0)

4

(6.3)

32

(50.8)

8

(12.7)

47

(74.6)

7

(11.1)

49

(77.8)

Monthly Income

≤RM 500 34

(12.3)

233

(84.1)

0.066

24

(8.7)

99

(35.7)

<0.001

36

(13.0)

131

(47.3)

<0.001

28

(10.1)

145

(52.3)

<0.001 RM 501-1000 42

(15.9)

214

(81.1)

15

(5.7)

76

(28.8)

18

(6.8)

114

(43.2)

24

(9.1)

120

(45.5)

RM 1001- 1500 57

(12.1)

399

(84.4)

32

(6.8)

233

(49.3)

67

(14.2)

281

(59.4)

44

(9.3)

281

(59.4)

43

Demographic

Characteristics

Outcome



Clinics








RM 1501- 2000 21

(9.5)

196

(88.3)

18

(8.1)

119

(53.6)

23

(10.4)

152

(68.5)

22

(9.9)

135

(60.8)

RM 2001- 2500 36

(9.4)

337

(87.5)

30

(7.8)

208

(54.0)

55

(14.3)

250

(64.9)

38

(9.9)

266

(69.1)

RM 2501-3000 22

(12.8)

144

(83.7)

13

(7.6)

90

(52.3)

24

(14.0)

111

(64.5)

21

(12.2)

103

(59.9)

RM 3001-3500 29

(9.2)

271

(86.3)

27

(8.6)

175

(55.7)

61

(19.4)

203

(64.6)

53

(16.9)

199

(63.4)

RM 3501-4000 11

(9.5)

100

(86.2)

8

(6.9)

66

(56.9)

16

(13.8)

87

(75.0)

7

(6.0)

83

(71.6)

RM 4001-4500 21

(9.0)

198

(85.0)

25

(10.7)

128

(54.9)

41

(17.6)

158

(67.8)

27

(11.6)

166

(71.2)

RM 4501-5000 11

(8.3)

112

(84.8)

8

(6.1)

76

(57.6)

10

(7.6)

91

(68.9)

6

(4.5)

99

(75.0)

> RM 5000 44

(8.9)

395

(80.3)

45

(9.1)

274

(55.7)

95

(19.3)

329

(66.9)

57

(11.6)

339

(68.9)


44

Table 14: Association between labelling satisfaction with demographic characteristics

Demographic

Characteristics

Outcome

Are you satisfied with the

information written on the labels

given by Government hospital or

clinic?

Are you satisfied with the information

written on the labels given by Private

hospital?



given by Private clinics?


written on the labels given by

Community pharmacy?


Locality

Urban 1921

(84.6)

202

(8.9) 0.372

1152

(50.7)

208

(9.2) <0.001

1430

(63.0)

399

(17.6) <0.001

1397

(61.5)

330

(14.5) <0.001

Rural 743

(91.7)

49

(6.0)

334

(41.2)

61

(7.5)

383

(47.3)

111

(13.7)

410

(50.6)

99

(12.2)

Age

18-27 604

(82.3)

79

(10.8)

0.130

403

(54.9)

82

(11.2)

<0.001

457

(62.3)

147

(20.0)

<0.001

453

(61.7)

130

(17.7)

<0.001

28-37 799

(87.5)

79

(8.7)

522

(57.2)

88

(9.6)

591

(64.7)

172

(18.8)

595

(65.2)

124

(13.6)

38-47 405

(85.8)

33

(7.0)

216

(45.8)

39

(8.3)

279

(59.1)

70

(14.8)

287

(60.8)

54

(11.4)

48-57 427

(88.0)

32

(6.6)

196

(40.4)

39

(8.0)

257

(53.0)

75

(15.5)

259

(53.4)

68

(14.0)

58-67 322

(90.2)

18

(5.0)

115

(32.2)

15

(4.2)

169

(47.3)

36

(10.1)

163

(45.7)

40

(11.2)

68-77 91

(90.1)

8

(7.9)

31

(30.7)

6

(5.9)

46

(45.5)

10

(9.9)

38

(37.6)

12

(11.9)

> 77 16

(84.2)

2

(10.5)

3

(15.8)

0

(0)

14

(73.7)

0

(0)

12

(63.2)

1

(5.3)

Gender

Male 1024

(84.7)

112

(9.3) 0.554

583

(48.2)

116

(9.6) 0.256

699

(57.8)

206

(17.0) 0.943

703

(58.1)

164

(13.6) 0.372

Female 1640

(87.6)

139

(7.4)

903

(48.2)

153

(8.2)

1114

(59.5)

304

(16.2)

1104

(59.0)

265

(14.2)

Ethnicity

Malay 1749

(89.3)

146

(7.5)

<0.001

985

(50.3)

173

(8.8)

<0.001

1214

(62.0)

324

(16.5)

<0.001

1188

(60.6)

279

(14.2)

<0.001

Chinese 419

(75.8)

56

(10.1)

282

(51.0)

46

(8.3)

322

(58.2)

112

(20.3)

329

(59.5)

85

(15.4)

Indian 168

(86.2)

20

(10.3)

84

(43.1)

29

(14.9)

92

(47.2)

50

(25.6)

108

(55.4)

35

(17.9)

Others 328

(87.7)

29

(7.8)

135

(36.1)

21

(5.6)

185

(49.5)

24

(6.4)

182

(48.7)

30

(8.0)

45

Demographic

Characteristics

Outcome




clinic?



hospital?






Community pharmacy?


Education Level

Primary School 259

(92.5)

16

(5.7)

0.305

79

(28.2)

13

(4.6)

<0.001

113

(40.4)

24

(8.6)

<0.001

117

(41.8)

24

(8.6)

<0.001


(88.1)

89

(6.7)

579

(43.6)

94

(7.1)

769

(57.9)

178

(13.4)

741

(55.8)

157

(11.8)


(83.5)

142

(10.2)

816

(58.5)

156

(11.2)

906

(64.9)

299

(21.4)

925

(66.3)

240

(17.2)

No Formal

Education

69

(89.6)

4

(5.2)

12

(15.6)

6

(7.8)

25

(32.5)

9

(11.7)

24

(31.2)

8

(10.4)

Occupation

Government 1011

(88.8)

97

(8.5)

0.001

611

(53.6)

134

(11.8)

<0.001

687

(60.3)

245

(21.5)

<0.001

725

(63.7)

192

(16.9)

<0.001

Private/Self

Employed

860

(81.6)

94

(8.9)

549

(52.1)

78

(7.4)

657

(62.3)

157

(14.9)

624

(59.2)

138

(13.1)

Retired 190

(92.2)

14

(6.8)

88

(42.7)

13

(6.3)

108

(52.4)

17

(8.3)

103

(50.0)

25

(12.1)

Student 143

(79.4)

22

(12.2)

94

(52.2)

16

(8.9)

110

(61.1)

37

(20.6)

112

(62.2)

27

(15.0)

Unemployed 460

(91.6)

24

(4.8)

144

(28.7)

28

(5.6)

251

(50.0)

54

(10.8)

243

(48.4)

47

(9.4)

Living Status

Alone 396

(84.8)

47

(10.1)

0.375

279

(59.7)

36

(7.7)

<0.001

319

(68.3)

72

(15.4)

0.010

300

(64.2)

66

(14.1)


(86.7)

200

(7.8)

1178

(46.2)

228

(8.9)

1451

(56.9)

428

(16.8)

1461

(57.3)

353

(13.8)

With Non-Family 57

(90.5)

4

(6.3)

29

(46.0)

5

(7.9)

43

(68.3)

10

(15.9)

46

(73.0)

10

(15.9)

Monthly Income

≤RM 500 245

(88.4)

21

(7.6)

0.201

103

(37.2)

18

(6.5)

<0.001

134

(48.4)

30

(10.8)

<0.001

140

(50.5)

32

(11.6)

<0.001 RM 501-1000 237

(89.8)

20

(7.68)

74

(28.0)

17

(6.4)

108

(40.9)

25

(9.5)

114

(43.2)

26

(9.8)

RM 1001- 1500 422

(89.2)

31

(6.6)

231

(48.8)

28

(5.9)

285

(60.3)

58

(12.3)

267

(56.4)

51

(10.8)

46

Demographic

Characteristics

Outcome




clinic?



hospital?






Community pharmacy?


RM 1501- 2000 207

(93.2)

10

(4.5)

115

(51.8)

15

(6.8)

142

(64.0)

26

(11.7)

128

(57.7)

26

(15.1)

RM 2001- 2500 338

(87.8)

32

(8.3)

198

(51.4)

36

(9.4)

225

(58.4)

74

(19.2)

240

(62.3)

61

(15.8)

RM 2501-3000 146

(84.9)

19

(11.0)

82

(47.7)

17

(9.9)

105

(61.0)

27

(15.7)

95

(55.2)

26

(15.1)

RM 3001-3500 278

(88.5)

22

(7.0)

171

(54.5)

30

(9.6)

196

(62.4)

68

(21.7)

189

(60.2)

63

(20.1)

RM 3501-4000 98

(84.5)

11

(9.5)

55

(47.4)

14

(12.1)

69

(59.5)

28

(24.1)

73

(62.9)

16

(13.8)

RM 4001-4500 186

(79.8)

30

(12.9)

121

(51.9)

30

(12.9)

145

(62.2)

53

(22.7)

148

(63.5)

40

(17.2)

RM 4501-5000 111

(84.1)

11

(8.3)

71

(53.8)

10

(7.6)

86

(65.2)

14

(10.6)

87

(65.9)

17

(12.9)

> RM 5000 395

(80.3)

44

(8.9)

265

(53.9)

54

(11.0)

317

(64.4)

107

(21.7)

325

(66.1)

71

(12.9)


47

4.6 Awareness towards appropriate use of medicines

Only half of the respondents (n=1639, n=53.2%) claimed that they were able to identify

medicines by the trade or generic name. This ability was found to be associated with consumers’

locality, age, gender, education level, occupation, living status and monthly income. Consumers

from urban area (55.4%), falling in the age group of 18-27 years (60.2%), who have received

tertiary education (67.0%), were government employee (70.1%), living alone (59.3%) and of

higher income group were more able to identify medicines by the trade or generic name (Table

15).

48

Table 15: Association between ability to identify medicines by trade/generic name with demographic

characteristics

Demographic Characteristics Ability to identify medicines by trade/ generic name

Yes No p-value*

Total (N) 1639 (53.2) 1442 (46.8) -

Locality

Urban 1257 (55.4) 1014 (44.6) <0.001

Rural 382 (47.2) 428 (52.8)

Age

18-27 442 (60.2) 292 (39.8) <0.001

28-37 554 (60.1) 359 (39.9)

38-47 266 (56.4) 206 (43.6)

48-57 215 (44.3) 270 (55.7)

58-67 139 (38.9) 218 (61.1)

68-77 19 (18.8) 82 (81.2)

> 77 4 (21.0) 15 (79.0)

Gender

Male 566 (46.8) 643 (53.2) <0.001

Female 1073 (57.3) 799 (42.7)

Ethnicity

Malay 1065 (54.3) 894 (45.7) 0.216

Chinese 293 (53.0) 260 (47.0)

Indian 95 (48.8) 100 (51.2)

Others 186 (49.7) 188 (50.3)

Education Level

Primary School 63 (22.5) 217 (77.5) <0.001

Secondary School 630 (47.4) 699 (52.6)

College/ University 936 (67.0) 459 (33.0)

No Formal Education 10 (13.0) 67 (87.0)

Occupation

Government 799 (70.1) 340 (29.9) <0.001

Private/Self Employed 477 (45.2) 577 (54.8)

Retired 87 (42.2) 119 (57.8)

Student 103 (57.2) 77 (42.8)

Unemployed 173 (34.4) 329 (65.5)

Living Status

Alone 277 (59.3) 190 (40.7) 0.014

With Family 1331 (52.2) 1220 (47.8)

With Non-Family 31 (49.2) 32 (50.8)

Monthly Income

≤RM 500 88 (31.7) 189 (68.3) <0.001

RM 501-1,000 77 (29.2) 187 (70.8)

RM 1,001-RM 1,500 219 (46.6) 254 (53.7)

RM 1,501-RM 2,000 107 (48.2) 115 (51.8)

RM 2,001- RM 2,500 210 (54.5) 175 (45.5)

RM 2,501- RM 3,000 96 (55.8) 76 (44.2)

RM 3,001-RM 3500 197 (62.7) 117 (37.3)

RM 3,501-RM 4,000 67 (57.7) 49 (42.3)

RM 4,001-RM 4,500 157 (67.3) 76 (32.7)

RM 4,501-RM 5,000 92 (69.6) 40 (30.4)

> RM 5,000 329 (66.8) 163 (33.2)

Significant at p < 0.05

49

It was found that up to 81.4% of the respondents claimed that they really understood the proper

use of medicine. The consumers’ understanding was significantly associated with their ethnicity,

education level and living status. The study also found that 83.0% of the respondents had good

knowledge on proper medicine storage. This was significantly associated with respondents’

gender, education level, occupation and the consumer’s monthly household income as shown

in Table 16.

50

Table 16: Association between the knowledge on proper use and storage of medicine with demographic characteristics

Demographic Characteristics Understand the Proper Use of Medicine Knowledge on proper medicine storage

Don't

Understand

n (%)

Partially

Understand

n (%)

Understand

n (%)

p-value* No

n (%)

Yes

n (%)

p-value*

Total=N 169 (5.5) 403 (13.1) 2509 (81.4) 524 (17.0) 2557 (83.0)

Locality

Urban 107 (4.7) 279 (12.3) 1885 (83.0) 0.851 389 (17.3) 1882 (82.9) 0.764

Rural 62 (7.7) 124 (15.3) 624 ( 77.0) 135 (16.7) 675 (83.3)

Age

18-27 47 (6.4) 117 (15.9) 570 (77.7) 0.184 124 (16.9) 610 (83.1) 0.144

28-37 56 (6.1) 112 (12.3) 745 (81.6) 133 (14.6) 780 (85.4)

38-47 12 (2.5) 50 (10.6) 410 (86.9) 89 (18.9) 383 (81.1)

48-57 33 (6.8) 57 (11.8) 395 (81.4) 86 (17.7) 399 (82.3)

58-67 11 (3.1) 43 (12.0) 303 (84.9) 66 (18.5) 291 (81.5)

68-77 10 (9.9) 19 (18.8) 72 (71.3) 24 (23.8) 77 (76.2)

> 77 0 (0) 5 (26.3) 14 (73.7) 2 (10.5) 17 (86.5)

Gender

Male 77 (6.4) 172 (14.2) 960 (76.4) 0.719 256 (21.2) 953 (78.8) <0.001

Female 92 (4.9) 231 (12.3) 1549 (82.7) 268 (14.3) 1604 (85.7)

Ethnicity

Malay 126 (6.4) 264 (13.5) 1569 (80.1) 0.017

327 (16.7) 1632 (83.3) 0.606

Chinese 24 (4.3) 92 (16.6) 437 (79.0) 100 (18.1) 453 (81.9)

Indian 9 (4.6) 21 (10.8) 165 (84.6) 38 (19.5) 157 (80.5)

Others 10 (2.7) 26 (7.0) 338 (90.4) 59 (15.8) 315 (84.2)

Education Level

Primary School 19 (6.8) 52 (18.6) 209 (74.6) 0.037 59 (21.1) 221 (78.9) <0.001

Secondary School 70 (5.3) 165 (12.4) 1094 (82.3) 249 (18.7) 1080 (81.3)

College/University 69 (4.9) 178 (12.8) 1148 (82.3) 193 (13.8) 1202 (86.2)

No formal education 11 (14.3) 8 (10.4) 58 (75.3) 23 (29.9) 54 (70.1)

Occupation

Government 49 (4.3) 115 (10.1) 975 (85.6) 0.082 151 (13.3) 988 (86.7) <0.001

Private/ Self Employed 59 (5.6) 163 (15.5) 832 (78.9) 221 (21.0) 833 (79.0)

Retired 13 (6.3) 30 (14.6) 163 (79.1) 35 (17.0) 171 (83.0)

Student 11 (6.1) 31 (17.2) 138 (76.7) 29 (16.1) 151 (83.9)

Unemployed 37 (7.4) 64 (12.7) 401 (79.9) 88 (17.5) 414 (82.5)

51

Demographic Characteristics Understand the Proper Use of Medicine Knowledge on proper medicine storage

Don't

Understand

n (%)

Partially

Understand

n (%)

Understand

n (%)

p-value* No

n (%)

Yes

n (%)

p-value*

Living Status

Alone 26 (5.6) 76 (16.3) 365 (78.2) 0.030 78 (16.7) 389 (83.3) 0.534

With Family 142 (5.6) 315 (12.3) 2094 (82.1) 432 (16.9) 2119 (83.1)

With Non-family 1 (1.6) 12 (19.0) 50 (79.4) 14 (22.2) 49 (77.8)

Monthly Household Income

< RM500 20 (7.2) 40 (14.4) 217 (78.3) 0.829 54 (19.5) 223 (80.5) 0.001

RM501-RM1,000 19 (7.2) 35 (13.3) 210 (79.5) 56 (21.2) 208 (78.8)

RM1,001-RM1,500 30 (6.3) 66 (14.0) 377 (79.7) 98 (20.7) 375 (79.3)

RM1,501-RM2,000 14 (6.3) 31 (14.0) 177 (79.7) 48 (21.6) 174 (78.4)

RM2,001-RM2,500 14 (3.6) 43 (11.2) 328 (85.2) 60 (15.6) 325 (84.4)

RM2,501-RM3,000 7 (4.1) 25 (14.5) 140 (81.4) 33 (19.2) 139 (80.8)

RM3,001-RM3,500 25 (8.0) 40 (12.7) 249 (79.3) 39 (12.4) 275 (87.6)

RM3,501-RM4,000 6 (5.2) 17 (14.7) 93 (80.2) 18 (15.5) 98 (84.5)

RM4,001-RM4,500 10 (4.3) 21 (9.0) 202 (86.7) 44 (18.9) 189 (81.1)

RM4,501-RM5,000 4 (3.0) 20 (15.2) 108 (81.8) 15 (11.4) 117 (88.6)

> RM5,000 20 (4.1) 65 (13.2) 407 (82.7) 59 (12.0) 433 (88.0)


52

70.3% (n=2167) of the respondent were generally aware of the side effects of medicines.

Respondents of age group 28-37 (74.8%), tertiary level of education (75.6%) and >RM 5000

income level (76.2%) were found to have better awareness of medicines side effect (Table 16).

Meanwhile, up to 90.8% (n= 2797) of respondents were aware of medicine’s expiry date. This

was found to be associated with the consumers’ age, level of education, occupation and income

level (Table 17).

53

Table 17: Association between the awareness on the side effects and shelf life of medicines with demographic characteristics

Demographic Characteristics

Aware of medicine's side effect Aware of medicine's expiry date

Yes

n (%)

No

n (%) p-value*

Yes

n (%)

No

n (%) p-value*

Total (N) 2167 (70.3) 914 (29.7) - 2797 (90.8) 284 (9.2) -

Locality Urban 1590 (70.0) 681 (30.0) 0.514

2068 (91.1) 203 (8.9) 0.370

Rural 577 (71.2) 233 (28.8) 729 (90.0) 81 (10.0)

Age 18-27 524 (71.4) 210 (28.6)

<0.001

666 (90.7) 68 (9.3)

<0.001

28-37 683 (74.8) 230 (25.2) 857 (93.9) 56 (6.1)

38-47 346 (73.3) 126 (26.7) 440 (93.2) 32 (6.8)

48-57 324 (66.8) 161 (33.2) 435 (89.7) 50 (10.3)

58-67 232 (65.0) 125 (35.0) 312 (87.4) 45 (12.6)

68-77 50 (49.5) 51 (50.5) 72 (71.3) 29 (28.7)

> 77 8 (42.1) 11 (57.9) 15 (78.9) 4 (21.1)

Gender Male 803 (66.4) 406 (33.6) <0.001

1089 (90.1) 120 (9.9) 0.275

Female 1364 (72.9) 508 (27.1) 1708 (91.2) 164 (8.8)

Ethnicity Malay 1434 (73.2) 525 (26.8)

<0.001

1781 (90.9) 178 (9.1)

0.954 Chinese 345 (62.4) 208 (37.6) 503 (91.0) 50 (9.0)

Indian 125 (64.1) 70 (35.9) 176 (90.3) 19 (9.7)

Others 263 (70.3) 111 (29.7) 337 (90.1) 37 (9.9)

Education Level Primary School 148 (52.9) 132 (47.1)

<0.001

229 (81.8) 51 (18.2)

<0.001 Secondary School 934 (70.3) 395 (29.7) 1211 (91.1) 118 (8.9)

College/ University 1055 (75.6) 340 (24.4) 1310 (93.9) 85 (6.1)

No formal education 30 (39.0) 47 (61.0) 47 (61.0) 30 (39.0)

Occupation Government 910 (79.9) 229 (20.1)

<0.001

1081 (94.9) 58 (5.1)

<0.001

Private/ Self Employed 700 (66.4) 354 (33.6) 941 (89.3) 113 (10.7)

Retired 131 (63.6) 75 (36.4) 180 (87.4) 26 (12.6)

Student 116 (64.4) 64 (35.6) 168 (93.3) 12 (6.7)

Unemployed 310 (61.8) 192 (38.2) 427 (85.1) 75 (14.9)

Living Status Alone 344 (73.7) 123 (26.3)

0.197

429 (91.9) 38 (8.1)

0.681

With Family 1777 (69.7) 774 (30.3) 2311 (90.6) 240 (9.4)

With Non-family 46 (73.0) 17 (27.0) 57 (90.5) 6 (9.5)

Monthly Household

Income

<RM 500 161 (58.1) 116 (41.9)

<0.001

236 (85.2) 41 (14.8)

<0.001

RM 501-1,000 159 (60.2) 105 (39.8) 217 (82.2) 47 (17.8)

RM 1,001-1,500 327 (69.1) 146 (30.9) 419 (88.6) 54 (11.4)

RM 1,501-2,000 153 (68.9) 69 (31.1) 199 (89.6) 23 (10.4)

RM 2,001-2,500 287 (74.5) 98 (25.5) 364 (94.5) 21 (5.5)

54


Aware of medicine's side effect Aware of medicine's expiry date

Yes

n (%)

No

n (%) p-value*

Yes

n (%)

No

n (%) p-value*

RM 2,501-3,000 127 (73.8) 45 (26.2)

156 (90.7) 16 (9.3)

RM 3,001-3,500 229 (72.9) 85 (27.1) 290 (92.4) 24 (7.6)

RM 3,501-4,000 78 (67.2) 38 (32.8) 106 (91.4) 10 (8.6)

RM 4,001-4,500 171 (73.4) 62 (26.6) 223 (95.7) 10 (4.3)

RM 4,501-5,000 100 (75.8) 32 (24.2) 122 (92.4) 10 (7.6)

>RM 5,000 375 (76.2) 117 (23.8) 464 (94.3) 28 (5.7)


55

71.8% of the respondents were aware of the potential interaction between foods with medicines.

Females (75.1%), respondents of the age group 18-27 (74.0%), having tertiary educational level

(73.7%), publically employed (76.4%) and having income levels of RM2,001-RM2,500 (77.9%)

were significantly associated with the knowledge on interaction between foods and medicine

(Table 17). Besides that, 68.4% of the respondents were aware of interaction between modern

and traditional medicines. This awareness was significantly associated with respondents’ age,

gender, ethnicity, occupation and living status (p<0.05) as reported in Table 18.

56

Table 18: Factors affecting the awareness on food-medicines and modern-traditional medicines interaction


Awareness of Interactions between modern medicines and food Awareness of Interactions between modern and traditional medicines

Yes n (%) No n (%) p-value* Yes n (%) No n (%) p-value*

Total (N) 2213 (71.8) 868 (28.2) - 2107 (68.4) 974 (31.6) -

Locality

Urban 1638 (72.1) 633 (27.9) 0.536 1546 (68.1) 725 (31.9) 0.534

Rural 575 (71.0) 235 (29.0) 561 (69.3) 249 (30.7)

Age

18-27 543 (74.0) 191 (26.0) <0.001 469 (63.9) 265 (36.1) 0.002

28-37 675 (73.9) 238 (26.1) 617 (67.6) 296 (32.4)

38-47 349 (73.9) 123 (26.1) 335 (71.0) 137 (29.0)

48-57 327 (67.4) 158 (32.6) 345 (71.1) 140 (28.9)

58-67 251 (70.3) 106 (29.7) 268 (75.1) 89 (24.9)

68-77 55 (54.5) 46 (45.5) 62 (61.4) 39 (38.6)

> 77 13 (68.4) 6 (31.6) 11 (57.9) 8 (42.1)

Gender

Male 807 (66.7) 402 (33.3) <0.001 772 (63.9) 437 (36.1) <0.001

Female 1406 (75.1) 466 (24.9) 1335 (71.3) 537 (28.7)

Ethnicity

Malay 1411 (72.0) 548 (28.0) 0.172 1276 (65.1) 683 (34.9) <0.001

Chinese 387 (70.0) 166 (30.0) 432 (78.1) 121 (21.9)

Indian 152 (77.9) 43 (22.1) 139 (71.3) 56 (28.7)

Others 263 (70.3) 111 (29.7) 260 (69.5) 114 (30.5)

Education Level

Primary School 190 (67.9) 90 (32.1) 0.003 199 (71.1) 81 (28.9) 0.659

Secondary School 952 (71.6) 377 (28.4) 912 (68.6) 417 (31.4)

College/ University 1028 (73.7) 367 (26.3) 946 (67.8) 449 (32.2)

No Formal Education 43 (55.8) 34 (44.2) 50 (64.9) 27 (35.1)

Occupation

Government 870 (76.4) 269 (23.6) 0.001 798 (70.1) 341 (29.9) 0.009

Private/Self Employed 720 (68.3) 334 (31.7) 695 (65.9) 359 (34.1)

Retired 145 (70.4) 61 (29.6) 159 (77.2) 47 (22.8)

Student 129 (71.7) 51 (28.3) 115 (63.9) 65 (36.1)

Unemployed 349 (69.5) 153 (30.5) 340 (67.7) 162 (32.3)

57


Awareness of Interactions between modern medicines and food Awareness of Interactions between modern and traditional medicines

Yes n (%) No n (%) p-value* Yes n (%) No n (%) p-value*

Living Status

Alone 344 (73.4) 123 (26.3) 0.328 306 (65.5) 161 (34.5) 0.045

With Family 1828 (71.7) 723 (26.3) 1765 (69.2) 786 (30.8)

With Non-Family 41 (65.1) 22 (34.9) 36 (57.1) 27 (42.9)

Monthly Income

≤RM 500 194 (70.0) 83 (30.0) 0.004 195 (70.4) 82 (29.6) 0.802

RM 501-RM1,000 170 (64.4) 94 (35.6) 184 (69.7) 80 (30.3)

RM1,001-RM1,500 349 (73.8) 124 (26.2) 315 (66.6) 158 (33.4)

RM1,501-RM2,000 152 (68.5) 70 (31.5) 146 (65.8) 76 (34.2)

RM2,001-RM2,500 300 (77.9) 85 (22.1) 263 (68.3) 122 (31.7)

RM2,501-RM3,000 131 (76.2) 41 (23.8) 113 (65.7) 59 (34.3)

RM3,001-RM3,500 220 (70.1) 94 (35.3) 220 (70.1) 94 (29.9)

RM3,501-RM4,000 75 (64.7) 41 (35.3) 74 (63.8) 42 (36.2)

RM4,001-RM4,500 164 (70.4) 69 (29.6) 166 (71.2) 67 (28.8)

RM4,501-RM5,000 95 (72.0) 37 (28.0) 90 (68.2) 42 (31.8)

> RM 5,000 362 (73.6) 130 (26.4) 340 (69.1) 152 (30.9)


58

A salient feature of the survey reported that 67.7% (n=2086) of the respondents had no

information about medicine disposal (Table 19). The response was significantly associated with

consumers’ locality, gender, ethnicity, education level, occupation and living status. Male

respondents (70.8%), rural residencies (71.9%), no formal education (81.9%) and privately

employed (74.5%) had poor knowledge towards medicine disposal.

59

Table 19: Factors Affecting medication disposal


Outcome

Knowledge of Medication Disposal

Yes, n (%) No, n (%) p-value*

Total (N) 995 (32.3) 2086 (67.7) -

Locality

Urban 767 (33.7) 1504 (66.3) 0.003

Rural 228 (28.1) 582 (71.9)

Age

18-27 253 (34.4) 481 (65.6) 0.064

28-37 307 (33.6) 606 (66.4)

38-47 144 (30.5) 328 (69.5)

48-57 143 (29.4) 342 (70.6)

58-67 121 (33.8) 236 (66.2)

68-77 25 (24.7) 76 (75.3)

> 77 2 (10.5) 17 (89.5)

Gender

Male 354 (29.2) 855 (70.8) 0.004

Female 641 (34.2) 1231 (65.8)

Ethnicity

Malay 675 (34.4) 1284 (65.6) 0.001

Chinese 168 (30.3) 385 (69.7)

Indian 63 (32.3) 132 (67.7)

Others 89 (23.7) 285 (76.3)

Education Level

Primary School 75 (26.7) 205 (73.3) <0.001




Occupation

Government 467 (41.0) 672 (59.0) <0.001


Retired 70 (34.0) 136 (66.0)

Student 60 (33.3) 120 (66.7)

Unemployed 129 (25.6) 373 (74.4)

Living Status

Alone 171 (36.6) 296 (63.4) 0.027

With Family 810 (31.7) 1741 (68.3)

With Non-Family 14 (22.2) 49 (77.8)

Monthly Income

≤RM 500 76 (27.4) 201 (72.6) 0.059

RM 501-1,000 74 (28.0) 190 (72.0)

RM 1,001-RM 1,500 147 (31.0) 326 (69.0)

RM 1,501-RM 2,000 60 (27.0) 162 (73.0)

RM 2,001- RM 2,500 145 (37.6) 240 (62.4)

RM 2,501-RM 3,000 62 (36.0) 110 (64.0)

RM 3,001-RM 3,500 101 (32.1) 213 (67.9)

RM 3,501-RM 4,000 37 (31.8) 79 (68.2)

RM 4,001-RM 4,500 85 (36.4) 148 (63.6)

RM 4,501-RM 5,000 39 (29.5) 93 (70.5)

> RM 5,000 169 (34.3) 323 (55.7)


60

Up to 86.2% of the participants were aware of the requirement for registration with the Ministry

of Health Malaysia for all modern and traditional medicines prior to marketing. Consumers

who were females (88.0%), from the age group of 28 to 37 years (91.8%), belonging to the

Malay ethnic group (89.1%), with tertiary education (91.1%), government employee

(94.7%)and with RM4501-5000 (93.9%) income were more aware of this medicines’

registration requirement (Table 20). Age, gender, ethnicity, education, occupation and monthly

income was reported to have a significant association (p < 0.05) against the knowledge towards

registration of medicines with Ministry of Health, Malaysia.

61

Table 20: Response to “Did you know that all modern and traditional medicines should be registered with

Ministry of Health?” based on demographic characteristics


Outcome

“Did you know that all modern and traditional medicines should be registered

with Ministry of Health?”

Yes, n(%) No, n(%) p-value*

Total (N) 2657 (86.2) 424 (13.8) -

Locality

Urban 1960 (86.3) 311 (13.7) 0.856

Rural 697 (86.0) 113 (14.0)

Age

18-27 649 (88.4) 85 (11.6) <0.001

28-37 839 (91.8) 74 (8.2)

38-47 414 (87.7) 58 (12.3)

48-57 411 (84.7) 74 (15.3)

58-67 273 (76.4) 84 (23.6)

68-77 59 (58.4) 42 (41.6)

> 77 12 (63.3) 7 (36.8)

Gender

Male 1008 (83.3) 201 (16.7) <0.001

Female 1649 (88.0) 223 (12.0)

Ethnicity

Malay 1747 (89.1) 212 (10.8) <0.001

Chinese 441 (79.7) 112 (20.3)

Indian 162 (83.0) 33 (17.0)

Others 307 (82.0) 67 (18.0)

Education Level

Primary School 192 (68.5) 88 (31.5) <0.001




Occupation

Government 1079 (94.7) 60 (5.3) <0.001


Retired 149 (72.3) 57 (27.7)

Student 151 (83.8) 29 (16.2)

Unemployed 386 (76.9) 116 (23.1)

Living Status

Alone 414 (88.6) 53 (11.4) 0.089

With Family 2185 (85.6) 366 (14.4)

With Non-Family 58 (92.0) 5 (8.0)

Monthly Income

≤RM 500 204 (73.6) 73 (26.4) <0.001

RM 501-1,000 199 (75.3) 65 (24.7)

RM 1,001-RM 1,500 404 (85.4) 69 (14.6)

RM 1,501-RM 2,000 195 (87.8) 27 (12.2)

RM 2,001- RM 2,500 350 (90.9) 35 (9.1)

RM 2,501-RM 3,000 149 (86.6) 23 (13.4)

RM 3,001-RM 3,500 267 (85.0) 47 (15.0)

RM 3,501-RM 4,000 105 (90.5) 11 (9.5)

RM 4,001-RM 4,500 212 (90.9) 21 (9.1)

RM 4,501-RM 5,000 124 (93.9) 8 (6.1)

> RM 5,000 447 (90.8) 45 (9.2)


62

Only 46.4% of the participants were aware of Meditag® availability. This knowledge was

found to be influenced by the participants’ age (p<0.05) and education level (p<0.05).

Participants of age between 28 to 37 years (64.1%) and having tertiary education (62.2%) were

more aware of the Meditag® availability as shown in Table 21.

63

Table 21: Factors affecting knowledge on Meditag® availability

Demographic

Characteristics

Outcome

Knowledge of Meditag Availability?

Yes, n(%) No, n(%) p-value**

Total (N)* 1429 (46.4) 1216 (39.5) -

Locality

Urban 1071 (54.9) 879 (45.1) 0.253

Rural 358 (51.5) 337 (48.5)

Age

18-27 356 (55.1) 289 (44.9) 0.011

28-37 536 (64.1) 300 (35.9)

38-47 237 (57.3) 176 (42.7)

48-57 178 (43.6) 230 (56.4)

58-67 104 (38.0) 169 (62.0)

68-77 11 (18.9) 47 (81.1)

> 77 7 (58.3) 5 (41.7)

Gender

Male 511 (51.1) 489 (48.9) 0.369

Female 918 (55.8) 727 (44.2)

Ethnicity

Malay 978 (56.1) 763 (43.9) 0.271

Chinese 214 (48.7) 225 (51.3)

Indian 76 (48.1) 82 (51.9)

Others 161 (52.4) 146 (47.6)

Education Level

Primary School 54 (28.2) 137 (71.8) <0.001




Occupation

Government 712 (66.2) 363 (33.8) 0.309


Retired 55 (37.1) 93 (62.9)

Student 79 (52.6) 71 (47.4)

Unemployed 160 (41.4) 226 (58.6)

Living Status

Alone 247 (59.8) 166 (40.2) 0.702

With Family 1145 (52.6) 1029 (47.4)

With Non-Family 37 (63.7) 21 (36.3)

Monthly Income

≤RM 500 84 (41.3) 119 (58.7) 0.203

RM 501-1,000 72 (36.1) 127 (63.9)

RM 1,001-RM 1,500 188 (46.8) 213 (53.2)

RM 1,501-RM 2,000 103 (53.0) 91 (47.0)

RM 2,001- RM 2,500 201 (57.5) 148 (42.5)

RM 2,501-RM 3,000 80 (53.6) 69 (46.7)

RM 3,001-RM 3,500 160 (60.6) 104 (39.4)

RM 3,501-RM 4,000 59 (56.1) 46 (43.9)

RM 4,001-RM 4,500 136 (64.1) 76 (35.9)

RM 4,501-RM 5,000 72 (58.0) 52 (42.0)

> RM 5,000 273 (61.4) 171 (38.6)

*Missing data=436; **Significant at p < 0.05

64

4.7 Assessment towards medication compliance

Up to 73.1% (n= 2251) of the respondents admitted forgotten to take their prescribed

medication. This study found that the respondents' age, gender, ethnicity, education level,

occupation, and monthly income were significantly (p<0.05) associated with consumers’

compliance to prescribed medications (Table 22). Furthermore, less than half of the respondents

(n= 1303, 42.3%) admitted to have consciously chosen not to take prescribed medicines.

Respondents who were from the age group of 18-27 years (52.6%), Chinese ethnicity (43.9%),

tertiary education (50.0%) and from higher income group were more likely to choose not to

take prescribed medications (Table 22).

Additionally, sharing of medications was less common among consumers (n=1045, 33.9%).

Other then gender, sharing medications was reported to a have a significant association (p <

0.05) with all demographic variables as shown in Table 22.

65

Table 22: Association between medication adherence and demographic characteristics

Demographic

Characteristics

Outcome

Have you ever forgotten to take prescribed

medicines as indicated?

Have you ever chosen not to take a prescribed

medicine?

Have you ever shared any medicines with

others?

Yes

n (%)

No

n (%) p-value*

Yes

n (%)

No

n (%) p-value*

Yes

n (%)

No

n (%) p-value*

Total (N) 2251 (73.1) 830 (26.9) 1303 (42.3) 1778 (57.7) 1045 (33.9) 2036 (66.1)

Locality

Urban 1661 (73.1) 610 (26.9) 0.869

1010 (44.5) 1261 (55.5) <0.001

805 (35.4) 1466 (64.6) 0.003

Rural 590 (72.8) 220 (27.2) 293(36.2) 517 (63.8) 240 (29.6) 570 (70.4)

Age

18-27 582 (79.3) 152 (20.7)

<0.001

386 (52.6) 348 (47.4)

<0.001

357 (48.6) 377 (51.4)

<0.001

28-37 681 (74.6) 232 (25.4) 424 (46.4) 489 (53.6) 358 (39.2) 555 (60.8)

38-47 342 (72.5) 130 (27.5) 185 (39.2) 287 (60.8) 125 (26.5) 347 (73.5)

48-57 354 (72.5) 131 (27.0) 187 (38.6) 298 (61.4) 124 (25.6) 361 (74.4)

58-67 215 (60.2) 142 (39.8) 85 (23.8) 272 (76.2) 62 (17.4) 295 (82.6)

68-77 62 (61.4) 39 (38.6) 31 (30.7) 70 (69.3) 16 (15.8) 85 (84.2)

> 77 15 (78.9) 4 (21.1) 5 (26.3) 14 (73.7) 3 (15.8) 16 (84.2)

Gender

Male 848 (70.1) 361 (29.9) 0.003

479 (39.6) 730 (60.4) 0.016

403 (33.3) 806 (66.7) 0.582

Female 1403 (74.9) 469 (25.1) 824 (44.0) 1048 (56.0) 642 (34.3) 1230 (65.7)

Ethnicity

Malay 1476 (75.3) 483 (24.7)

0.003

858 (43.8) 1101 (56.2)

0.002

742 (37.9) 1217 (62.1)

<0.001 Chinese 383 (69.3) 170 (30.7) 243 (43.9) 310 (56.1) 166 (30.0) 387 (70.0)

Indian 135 (69.2) 60 (30.8) 77 (39.5) 118 (60.5) 44 (22.6) 151 (77.4)

Others 257 (68.7) 117 (31.3) 125 (33.4) 249 (66.6) 93 (24.9) 281 (75.1)

Education Level

Primary School 169 (60.4) 111 (39.6)

<0.001

84 (30.0) 196 (70.0)

<0.001

63 (22.5) 217 (77.5)

<0.001 Secondary School 937 (70.5) 392 (29.5) 500 (37.6) 829 (62.4) 364 (27.4) 965 (72.6)

College/ University 1100 (78.9) 295 (21.1) 698 (50.0) 697 (50.0) 601 (43.1) 794 (56.9)

No Formal Education 45 (58.4) 32 (41.6) 21 (27.3) 56 (72.7) 17 (22.1) 60 (77.9)

Occupation

Government 881 (77.3) 258 (22.7)

<0.001

511 (44.9) 628 (55.1)

<0.001

413 (36.3) 726 (63.7)

<0.001

Private/Self Employed 775 (73.5) 279 (26.5) 481 (45.6) 573 (54.4) 368 (34.9) 686 (65.1)

Retired 125 (60.7) 81 (39.3) 51 (24.8) 155 (75.2) 36 (17.5) 170 (82.5)

Student 136 (75.6) 44 (24.4) 96 (53.3) 84 (46.7) 102 (56.7) 78 (43.3)

Unemployed 334 (66.5) 168 (33.5) 164 (32.7) 338 (67.3) 126 (25.1) 376 (74.9)

66

Demographic

Characteristics

Outcome

Have you ever forgotten to take prescribed

medicines as indicated?

Have you ever chosen not to take a prescribed

medicine?

Have you ever shared any medicines with

others?

Yes

n (%)

No

n (%) p-value*

Yes

n (%)

No

n (%) p-value*

Yes

n (%)

No

n (%) p-value*

Living status

Alone 354 (75.8) 113 (24.2)

0.069

218 (46.7) 249 (53.3)

0.036

175 (37.5) 292 (62.5)

0.001 With Family 1845 (72.3) 706 (27.7) 1053 (41.3) 1498 (58.7) 837 (32.8) 1714 (67.2)

With Non-Family 52 (82.5) 11 (17.5) 32 (50.8) 31 (49.2) 33 (52.4) 30 (47.6)

Monthly income

<0.001

<0.001

0.003

≤RM 500 182 (65.7) 95 (34.3) 96 (34.7) 181 (65.3) 72 (26.0) 205 (74.0)

RM 501-1000 171 (64.8) 93 (35.2) 105 (39.8) 159 (60.2) 72 (27.3) 192 (72.7)

RM 1001- 1500 346 (73.2) 127 (26.8) 163 (34.5) 310 (65.5) 151 (31.9) 322 (68.1)

RM 1501- 2000 150 (67.6) 72 (32.4) 87 (39.2) 135 (60.8) 73 (32.9) 149 (67.1)

RM 2001- 2500 282 (73.2) 103 (26.8) 163 (42.3) 222 (57.7) 127 (33.0) 258 (67.0)

RM 2501-3000 121 (18.1) 51 (29.7) 68 (39.5) 104 (60.5) 59 (34.3) 113 (65.7)

RM 3001-3500 240 (76.4) 74 (23.6) 140 (44.6) 174 (55.4) 115 (36.6) 199 (63.4)

RM 3501-4000 95 (81.9) 21 (18.1) 53 (45.7) 63 (54.6) 46 (39.7) 70 (60.3)

RM 4001-4500 190 (81.5) 43 (18.5) 121 (51.9) 112 (48.1) 82 (35.2) 151 (64.8)

RM 4501-5000 90 (68.2) 42 (31.8) 58 (43.9) 74 (56.1) 49 (37.1) 83 (62.9)

> RM 5000 383 (77.8) 109 (22.2) 249 (50.6) 243 (49.4) 199 (40.4) 293 (59.6)


67

4.8 Assessment of medicine information resources

About half of the participants (n=1528, 49.6%) claimed that they will consult the doctor as their

first point of referral when they have any concerns about medicine while 958 (31.1%)

participants claimed they will consult the pharmacists (Table 23). A small proportion of the

participants claimed they will seek the nurses (2.4%), medical assistants (1.7%), friends (2.5%)

and family members (10.8%).

Table 23: First person to contact in case of medicine related concern

Statement Frequency (N) Percentage (%)

First person to contact in case of medicine related concern

Doctor

Pharmacist

Nurse

Medical assistant

Friends or neighbours

Family members

Not applicable

1528

958

74

52

78

333

58

49.6

31.1

2.4

1.7

2.5

10.8

1.9

Most of the respondents (n=2295, 74.5%) stated that it is easier to get medicine related

information from government pharmacists followed by government physician (n=2166, 70.3%)

(Table 24). Almost half of the respondents reported that it is easy to get medicine related

information from community pharmacist (n=1728, 56.1%) and private physicians (n=1578,

51.2%).

Table 24: Ease of obtaining medicines related information

Statement Frequency (%)

Is it easy to obtain medicine related information from: Yes No

Government physician*

Private physician**

Government pharmacist***

Community pharmacist****

2166 (70.3)

1578 (51.2)

2295 (74.5)

1728 (56.1)

643 (20.9)

592 (19.2)

372 (12.1)

420 (13.6)

Missing information*=272, **=910, ***414, ****939

68

More than half of the respondents (n=1821, 59.1%) consulted a healthcare professional for

medicine related inquiries. Internet was rated as the second most favourable source of

information (n=1134, 36.8%) followed by friends, family and neighbours (n=904, 29.3%) and

printed materials (n=666, 21.6%). There are 66.5% (n=2049) of the respondents never obtained

medicine information from traditional & complimentary practitioners as shown in Table 25.

Table 25: Frequency of obtaining medicines information from various information sources among

Malaysian consumers

Information source Frequency n (%)

Printed materials (magazines, newspaper)

Often 666 (21.6)

Seldom 1515 (49.2)

Never 899 (29.2)

Internet Often 1134 (36.8)

Seldom 955 (31.0)

Never 991 (32.2)

Common information and entertainment channels (TV, radio) Often 800 (26.0)

Seldom 1440 (46.7)

Never 840 (27.3)

Modern healthcare professionals (doctors, pharmacists, nurses) Often 1821 (59.1)

Seldom 1003 (32.6)

Never 256 (8.3)

Traditional and complimentary practitioners (shaman, sinseh) Often 155 (5.0)

Seldom 876 (28.4)

Never 2049 (66.5)

Friends, family and neighbours Often 904 (29.3)

Seldom 1414 (45.9)

Never 761 (24.7)

From Table 26 (a) and 26 (b), frequency in obtaining medicine information from printed

materials, internet and common information channels was significantly related with consumers’

locality, age, ethnicity, education level, occupation, living status and monthly household

income. Meanwhile, frequency in obtaining medicine information from friends and family

members and traditional practitioners were significantly related with consumers’ age, education

level, occupation, living status and monthly household income. However, there was no

significant association reported between frequency in obtaining medicine information from

modern healthcare professionals and all demographic variables.

69

Table 26 (a): Response to “How often do you obtain medicines information from printed materials/ internet, common information channels?” based on demographic

characteristics

Demographic

Characteristics

Obtaining Medicines Information from Various Sources

Printed Materials Internet Common information channel

Often

n (%)

Seldom

n (%)

Never

n (%)

p-

value*

Often

n (%)

Seldom

n (%)

Never

n (%)

p-

value*

Often

n (%)

Seldom

n (%)

Never

n (%)

p-

value*

Area

Urban 479

(21.1)

1152

(50.7)

639

(28.1) 0.003

889

(39.1)

707

(31.1)

674

(29.7) 0.004

575

(25.3)

1091

(48.0)

604

(26.6) 0.022

Rural 187

(23.1)

363

(44.8)

260

(32.1)

245

(30.2)

248

(30.6)

317

(39.1)

225

(27.8)

349

(43.1)

236

(29.1)

Age

18-27 161

(21.9)

399

(54.4)

174

(23.7)

<0.001

390

(53.1)

229

(31.2)

115

(15.7)

<0.001

192

(26.2)

371

(50.5)

171

(23.3)

<0.001

28-37 217

(23.8)

477

(52.2)

219

(24.0)

449

(49.2)

310

(34.0)

154

(16.9)

242

(26.5)

447

(49.0)

224

(24.5)

38-47 109

(23.1)

227

(48.1)

135

(28.6)

150

(31.8)

171

(36.2)

150

(31.8)

135

(28.6)

217

(46.0)

119

(25.2)

48-57 94

(19.4)

235

(48.5)

156

(32.2)

99

(20.4)

153

(31.5)

233

(48.0)

127

(26.2)

220

(45.4)

138

(28.5)

58-67 65

(18.2)

146

(40.9)

146

(40.9)

41

(11.5)

72

(20.2)

244

(68.3)

79

(22.1)

148

(41.5)

130

(36.4)

68-77 17

(16.8)

26

(25.7)

58

(57.4)

5

(5.0)

17

(16.8)

79

(78.2)

22

(21.8)

29

(28.7)

50

(49.5)

> 77 3

(15.8)

5

(26.3)

11

(57.9)

0

(0.0)

3

(15.8)

16

(84.2)

3

(15.8)

8

(42.1)

8

(42.1)

Gender

Male 247

(20.4)

587

(48.6)

374

(30.9) 0.286

391

(32.3)

390

(32.3)

427

(35.3) 0.298

311

(25.7)

531

(43.9)

366

(30.3) 0.003

Female 419

(22.4)

928

(49.6)

525

(28.0)

743

(39.7)

565

(30.2)

564

(30.1)

489

(26.1)

909

(48.6)

474

(25.3)

Ethnicity

Malay 446

(22.8)

976

(49.8)

536

(27.4)

<0.001

735

(37.5)

644

(32.9)

579

(29.6)

<0.001

556

(28.4)

942

(48.1)

460

(23.5)

<0.001

Chinese 132

(23.9)

278

(50.3)

143

(25.9)

213

(38.5)

159

(28.8)

181

(32.7)

120

(21.7)

259

(46.8)

174

(31.5)

Indian 28

(14.4)

102

(52.3)

65

(33.3)

66

(33.8)

55

(28.2)

74

(37.9)

32

(16.4)

98

(50.3)

65

(33.3)

Others 60

(16.0)

159

(42.5)

155

(41.4)

120

(32.1)

97

(25.9)

157

(42.0)

92

(24.6)

141

(37.7)

141

(37.7)

70

Demographic

Characteristics



Often

n (%)

Seldom

n (%)

Never

n (%)

p-

value*

Often

n (%)

Seldom

n (%)

Never

n (%)

p-

value*

Often

n (%)

Seldom

n (%)

Never

n (%)

p-

value*

Education Level

Primary School 34

(12.1)

95

(33.9)

150

(53.6)

<0.001

12

(4.3)

41

(14.6)

226

(80.7)

<0.001

66

(23.6)

106

(37.9)

107

(38.2)

<0.001

Secondary

School

280

(21.1)

634

(47.7)

415

(31.2)

342

(25.7)

453

(34.1)

534

(40.2)

359

(27.0)

609

(45.8)

361

(27.2)

College/

University

348

(24.9)

773

(55.4)

274

(19.6)

779

(55.8)

453

(32.5)

163

(11.7)

369

(26.5)

701

(50.3)

325

(23.3)

No Formal

Education

4

(5.2)

13

(16.9)

60

(77.9)

1

(1.3)

8

(10.4)

68

(88.3)

6

(7.8)

24

(31.2)

47

(61.0)

Occupation

Government 295

(25.9)

627

(55.0)

216

(19.0)

<0.001

556

(48.8)

412

(36.2)

170

(14.9)

<0.001

326

(28.6)

589

(51.7)

223

(19.6)

<0.001

Private/Self

Employed

214

(20.3)

512

(48.6)

328

(31.1)

384

(36.4)

310

(29.4)

360

(34.2)

259

(24.6)

468

(44.4)

327

(31.0)

Retired 50

(24.3)

77

(37.4)

79

(38.3)

33

(16.0)

48

(23.3)

125

(60.7)

49

(23.8)

88

(42.7)

69

(33.5)

Student 35

(19.4)

92

(51.1)

53

(29.4)

83

(46.1)

67

(37.2)

30

(16.7)

43

(23.9)

94

(52.2)

43

(23.9)

Unemployed 72

(14.3)

207

(41.2)

223

(44.4)

78

(15.5)

118

(23.5)

306

(61.0)

123

(24.5)

201

(40.0)

178

(35.5)

Living Status

Alone 128

(27.4)

238

(51.0)

101

(21.6)

0.034

222

(47.5)

148

(31.7)

97

(20.8)

0.002

138

(29.6)

232

(49.7)

97

(20.8)


(20.7)

1240

(48.6)

781

(30.6)

881

(34.5)

791

(31.0)

878

(34.4)

652

(25.6)

1181

(46.3)

717

(28.1)

With Non-

Family

9

(14.3)

37

(58.7)

17

(27.0)

31

(49.2)

16

(25.4)

16

(25.4)

10

(15.9)

27

(42.9)

26

(41.3)

Monthly Income

≤RM 500 42

(15.2)

106

(38.3)

129

(46.6)

<0.001

60

(21.7)

56

(20.2)

161

(58.1)

<0.001

63

(22.7)

115

(41.5)

99

(35.7)

<0.001

RM 501-1,000 34

(12.9)

96

(36.4)

134

(50.8)

37

(14.0)

59

(22.3)

168

(63.6)

62

(23.5)

96

(36.4)

106

(40.2)

RM 1,001-1,500 101

(21.4)

224

(47.4)

147

(31.1)

116

(24.5)

160

(33.8)

196

(41.4)

127

(26.8)

225

(47.6)

120

(25.4)

RM 1,501-2,000 36

(16.2)

122

(55.0)

64

(28.8)

65

(29.3)

79

(35.6)

78

(35.1)

52

(23.4)

111

(50.0)

59

(26.6)

71

Demographic

Characteristics



Often

n (%)

Seldom

n (%)

Never

n (%)

p-

value*

Often

n (%)

Seldom

n (%)

Never

n (%)

p-

value*

Often

n (%)

Seldom

n (%)

Never

n (%)

p-

value*

RM 2,001-2,500 92

(23.9)

200

(51.9)

93

(24.2)

161

(41.8)

133

(34.5)

91

(23.6)

110

(28.6)

192

(49.9)

83

(21.6)

RM 2,501-3,000 37

(21.5)

77

(44.8)

58

(33.7)

58

(33.7)

58

(33.7)

56

(32.6)

48

(27.9)

69

(40.1)

55

(32.0)

RM 3,001-3,500 87

(27.7)

163

(51.9)

64

(20.4)

128

(40.8)

111

(35.4)

75

(23.9)

95

(30.3)

143

(45.5)

76

(24.2)

RM 3,501-4,000 35

(30.2)

56

(48.3)

25

(21.6)

65

(56.0)

29

(25.0)

22

(19.0)

31

(26.7)

56

(48.3)

29

(25.0)

RM 4,001-4,500 68

(29.2)

121

(51.9)

44

(18.9)

131

(56.2)

68

(29.2)

34

(14.6)

64

(27.5)

121

(51.9)

48

(20.6)

RM 4,501-5,000 31

(23.5)

80

(60.6)

21

(15.9)

73

(55.3)

39

(29.5)

20

(15.2)

40

(30.3)

58

(43.9)

34

(25.8)

> RM 5,000 103

(20.9)

270

(54.9)

119

(24.2)

240

(48.8)

163

(33.1)

89

(18.1)

108

(22.0)

254

(51.6)

130

(26.4)


72

Table 26 (b): Response to “How often do you obtain medicines information from modern healthcare professionals/ traditional & complimentary practitioners/

friends, family or friends?” based on demographic characteristics

Demographic

Characteristics


Modern Healthcare Professionals Traditional practitioners Friends/ Family/ Neighbours

Often n

(%)

Seldom n

(%)

Never n

(%) p-value*

Often n

(%)

Seldom n

(%)

Never n

(%) p-value*

Often n

(%)

Seldom n

(%)

Never n

(%) p-value*

Area

Urban 1340

(59.0)

745

(32.8)

185

(8.1) 0.513

118

(5.2)

662

(29.2)

1490

(65.6) 0.084

674

(29.7)

1082

(47.6)

513

(22.6) <0.001

Rural 481

(59.4)

258

(31.8)

71

(8.8)

37

(4.6)

214

(26.4)

559

(69.0)

230

(28.4)

332

(41.0)

248

(30.6)

Age

18-27 419

(57.1)

254

(34.6)

61

(8.3)

0.563

47

(6.4)

233

(31.7)

454

(61.9)

<0.001

257

(35.0)

363

(49.5)

114

(15.5)

<0.001

28-37 547

(59.9)

290

(31.8)

76

(8.3)

47

(5.1)

292

(32.0)

574

(62.9)

257

(28.1)

440

(48.2)

216

(23.7)

38-47 273

(57.8)

162

(34.3)

36

(7.6)

18

(3.8)

122

(25.8)

331

(70.1)

113

(23.9)

225

(47.7)

133

(28.2)

48-57 279

(57.5)

160

(33.0)

46

(9.5)

18

(3.7)

133

(27.4)

334

(68.9)

130

(26.8)

211

(43.5)

144

(29.7)

58-67 228

(63.9)

100

(28.0)

29

(8.1)

22

(6.2)

68

(19.0)

267

(74.8)

106

(29.7)

136

(38.1)

115

(32.2)

68-77 65

(64.4)

31

(30.7)

5

(8.0)

2

(2.0)

24

(23.8)

75

(74.3)

36

(35.6)

32

(31.7)

32

(31.7)

> 77 10

(52.6)

6

(31.6)

3

(15.8)

1

(5.3)

4

(21.1)

14

(73.7)

5

(26.3)

7

(36.8)

7

(36.8)

Gender

Male 691

(57.2)

404

(33.4)

113

(9.3) 0.892

67

(5.5)

368

(30.4)

773

(63.9) 0.018

351

(26.1)

541

(44.7)

315

(26.1) 0.221

Female 1130

(60.4)

599

(32.0)

143

(7.6)

88

(4.7)

508

(27.1)

1276

(68.2)

553

(29.5)

873

(46.6)

446

(23.8)

Ethnicity

Malay 1158

(59.1)

654

(33.4)

146

(7.5)

0.240

89

(4.5)

570

(29.1)

1299

(66.3)

<0.001

602

(30.7)

887

(45.3)

468

(23.9)

0.015

Chinese 338

(61.1)

169

(30.6)

46

(8.3)

49

(8.9)

187

(33.8)

317

(57.3)

155

(28.0)

279

(50.5)

119

(21.5)

Indian 114

(58.5)

62

(31.8)

19

(9.7)

7

(3.6)

48

(24.6)

140

(71.8)

52

(26.7)

88

(45.1)

55

(28.2)

Others 211

(56.4)

118

(31.6)

45

(12.0)

10

(2.7)

71

(19.0)

293

(78.3)

95

(25.4)

160

(42.8)

119

(31.8)

73

Demographic

Characteristics



Often n

(%)

Seldom n

(%)

Never n

(%) p-value*

Often n

(%)

Seldom n

(%)

Never n

(%) p-value*

Often n

(%)

Seldom n

(%)

Never n

(%) p-value*

Education Level

Primary School 168

(60.0)

84

(30.0)

27

(9.6)

0.133

17

(6.1)

54

(19.3)

208

(74.3)

<0.001

71

(25.4)

114

(40.7)

94

(33.6)

<0.001


(57.7)

426

(32.1)

136

(10.2)

54

(4.1)

353

(26.6)

922

(69.4)

353

(26.6)

566

(42.6)

409

(30.8)


(60.6)

466

(33.4)

83

(5.9)

76

(5.4)

459

(32.9)

860

(61.6)

452

(32.4)

714

(51.5)

229

(16.4)


(51.9)

27

(35.1)

10

(13.0)

8

(10.4)

10

(13.0)

59

(76.6)

28

(36.4)

20

(26.0)

29

(37.7)

Occupation

Government 703

(61.7)

362

(31.8)

73

(6.4)

0.191

56

(4.9)

375

(32.9)

707

(62.1)

<0.001

281

(24.7)

606

(53.2)

251

(22.0)

<0.001


(54.8)

370

(35.1)

106

(10.1)

57

(5.4)

287

(27.2)

710

(67.4)

304

(28.8)

476

(45.2)

274

(26.0)

Retired 122

(59.2)

70

(34.0)

14

(6.8)

11

(5.3)

51

(24.8)

144

(69.9)

66

(32.0)

79

(38.3)

60

(29.1)

Student 98

(54.4)

63

(35.0)

19

(10.6)

13

(7.2)

52

(28.9)

115

(63.9)

84

(46.7)

76

(42.2)

20

(11.1)

Unemployed 320

(63.7)

138

(27.5)

44

(8.8)

18

(3.6)

111

(22.1)

373

(74.3)

169

(33.7)

177

(35.3)

156

(31.1)

Living Status

Alone 261

(55.9)

173

(37.0)

33

(7.1)

0.068

19

(4.1)

169

(36.2)

279

(59.7)

0.001

132

(28.3)

232

(49.7)

103

(22.1)


(59.7)

811

(31.8)

217

(8.5)

134

(5.3)

692

(27.1)

1724

(67.6)

755

(29.6)

1146

(44.9)

648

(25.4)

With Non-Family 38

(60.3)

19

(30.2)

6

(9.5)

2

(3.2)

15

(23.8)

46

(73.0)

17

(27.0)

36

(57.1)

10

(15.9)

Monthly Income

≤RM 500 158

(57.0)

90

(32.5)

29

(10.5) 0.058

14

(5.1)

58

(20.9)

205

(74.0) <0.001

95

(34.3)

96

(34.7)

86

(31.0) <0.001

RM 501-RM 1,000 146

(55.3)

83

(31.4)

35

(13.3)

7

(2.7)

60

(22.7)

197

(74.6)

68

(25.8)

105

(39.38)

90

(34.1)

74

Demographic

Characteristics



Often n

(%)

Seldom n

(%)

Never n

(%) p-value*

Often n

(%)

Seldom n

(%)

Never n

(%) p-value*

Often n

(%)

Seldom n

(%)

Never n

(%) p-value*

RM 1001-1500 265

(56.0)

155

(32.8)

52

(11.0)

28

(5.9)

121

(25.6)

323

(68.3)

119

(25.2)

215

(45.5)

138

(29.2)

RM 1,501-RM 2,000 136

(61.3)

68

(30.6)

18

(8.1)

6

(2.7)

70

(31.5)

146

(65.8)

65

(29.3)

97

(43.7)

60

(27.0)

RM 2001-RM 2,500 219

(56.9)

137

(35.6)

29

(7.5)

16

(4.2)

113

(29.4)

256

(66.5)

114

(29.6)

183

(47.5)

88

(22.9)

RM 2,501-RM 3,000 103

(59.9)

49

(28.5)

20

(11.6)

12

(7.0)

41

(23.8)

119

(69.2)

55

(32.0)

62

(36.0)

55

(32.0)

RM 3,001-RM 3,500 173

(55.1)

121

(38.5)

20

(6.4)

20

(6.4)

95

(30.3)

199

(63.4)

91

(29.0)

154

(49.0)

69

(22.0)

RM 3,501-RM 4,000 72

(62.1)

37

(31.9)

7

(6.0)

6

(5.2)

43

(37.1)

67

(57.8)

33

(28.4)

62

(53.4)

21

(18.1)

RM 4,001-RM 4,500 159

(68.2)

61

(26.2)

13

(5.6)

21

(9.0)

73

(31.3)

139

(59.7)

76

(32.6)

114

(48.9)

43

(18.5)

RM 4,501-RM 5,000 90

(68.2)

34

(25.8)

8

(6.1)

7

(5.3)

26

(19.7)

99

(75.0)

39

(29.5)

73

(55.3)

20

(15.2)

> RM 5,000 299

(60.8)

168

(34.1)

25

(5.1)

18

(3.7)

176

(35.8)

298

(60.6)

149

(30.3)

253

(51.4)

90

(18.3)


75

As presented in Table 27, almost three quarter of the respondents (75.1%) felt that they need

written medicine information and this was significantly associated with their age, ethnicity,

education level, occupation, living status and monthly income. The findings suggested that

most respondents from the age of 18-27 years (79.9%), with tertiary education (80.8%),

government sector (81.5%), living with non-family (84.1%) and with income of RM 1001-

1500 (82.0%) required additional written medicines information.

76

Table 27: Consumers’ Response to “Do you need written medicines information?” based on demographic

characteristics


Need Written Medicine Information?

Yes

n (%)

No

n (%) p-value*

Total (N) 2315 (75.1) 765 (24.8) -

Locality

Urban 1709 (75.2) 562 (24.8) 0.900

Rural 606 (74.8) 203 (25.2)

Age

18-27 587 (79.9) 147 (20.1)

<0.001

28-37 709 (77.6) 204 (22.4)

38-47 347 (73.5) 125 (26.5)

48-57 362 (74.6) 123 (25.4)

58-67 236 (66.1) 120 (33.9)

68-77 63 (62.3) 38 (37.7)

> 77 11 (57.8) 8 (42.2)

Gender

Male 887 (73.3) 321 (26.7) 0.082

Female 1428 (76.2) 444 (23.8)

Ethnicity

Malay 1484 (75.7) 475 (24.3)

<0.001 Chinese 388 (70.1) 165 (29.9)

Indian 139 (71.2) 56 (28.8)

Others 304 (81.2) 69 (18.8)

Education Level

Primary School 190 (67.8) 90 (32.2)

<0.001 Secondary School 952 (71.6) 377 (28.4)



Occupation

Government 929 (81.5) 210 (18.5)

<0.001


Retired 127 (61.6) 78 (38.4)

Student 144 (80.0) 36 (20.0)

Unemployed 351 (69.9) 151 (30.1)

Living Status

Alone 372 (79.6) 95 (20.4)

0.010 With Family 1890 (74.0) 660 (26.0)

With Non-Family 53 (84.1) 10 (15.9)

Monthly Income

≤RM 500 197 (71.1) 80 (28.9)

0.004

RM 501-RM 1,000 178 (67.4) 86 (32.6)

RM 1,001-RM 1,500 338 (82.0) 135 (18.0)

RM 1,501-RM 2,000 166 (74.7) 56 (25.3)

RM 2,001-RM 2,500 288 (74.8) 97 (25.2)

RM 2501-RM 3,000 134 (77.9) 38 (22.1)

RM 3,001-RM 3,500 247 (78.6) 66 (21.4)

RM 3,501-RM 4,000 91 (78.4) 25 (21.6)

RM 4,001-RM 4,500 179 (76.8) 54 (23.2)

RM 4,501-RM 5,000 105 (79.5) 27 (20.5)

> RM 5000 392 (79.6) 100 (20.4)


77

Up to 70.8% of respondents reported that they require additional counselling from their

pharmacists (Table 28). This need was significantly associated with ethnicity and monthly

income. This study found that the proportion of gender and locality requiring additional

counselling from their pharmacists was almost equal. Consumers from other ethnic groups

(74.5%) were also found to require additional counselling from pharmacists. In addition, 72.1%

of those working in the private sector also claimed that they require additional counselling from

their pharmacists.

78

Table 28: Responses to “Do you require additional counselling from your pharmacists?” based on

demographic characteristics


Outcome

Require additional counselling from pharmacists?

Yes

n (%)

No

n (%) p-value*

Total (N) 2181 (70.8) 899 (29.2) -

Locality

Urban 1599 (70.4) 671 (29.6) 0.463

Rural 582 (71.8) 228 (28.2)

Age

18-27 520 (70.8) 214 (29.2)

0.308

28-37 661 (72.3) 251 (27.7)

38-47 332 (70.3) 140 (29.7)

48-57 342 (70.5) 143 (29.5)

58-67 246 (68.9) 111 (31.1)

68-77 71 (70.2) 30 (29.8)

> 77 9 (47.3) 10 (52.7)

Gender

Male 857 (70.8) 352 (29.2) 0.968

Female 1324 (70.7) 547 (29.3)

Ethnicity

Malay 1395 (71.2) 564 (28.8)

0.030 Chinese 383 (69.2) 170 (30.3)

Indian 124 (63.5) 71 (36.5)

Others 279 (74.5) 94 (25.5)

Education Level

Primary School 197 (70.3) 83 (29.7)

0.540 Secondary School 934 (70.2) 395 (29.8)



Occupation

Government 811 (71.2) 328 (28.8)

0.404


Retired 136 (66.0) 70 (34.0)

Student 125 (69.4) 55 (30.6)

Unemployed 349 (69.5) 153 (30.1)

Living Status

Alone 347 (74.3) 119 (25.7)

0.081 With Family 1786 (70.1) 765 (29.9)

With Non-Family 48 (76.1) 15 (23.9)

Monthly Income

≤RM 500 184 (66.4) 93 (33.6)

0.042

RM 501-1,000 181 (68.5) 83 (31.5)

RM 1,001-RM 1,500 335 (70.8) 138 (29.2)

RM 1,501-RM 2,000 165 (74.3) 57 (25.7)

RM 2,001- RM 2,500 276 (71.6) 109 (28.4)

RM 2,501- RM 3,000 107 (62.2) 65 (37.8)

RM 3,001-RM 3,500 232 (73.8) 82 (26.2)

RM 3,501-RM 4,000 85 (73.2) 31 (26.8)

RM 4,001-RM 4,500 154 (66.0) 79 (34.0)

RM 4,501-RM 5,000 95 (71.9) 37 (28.1)

> RM 5,000 366 (74.3) 125 (25.7)


79

4.9 Awareness on ‘Know Your Medicines’ programme

Almost half of the respondents (51.9%, n= 1600) claimed that they were aware of the “Know

Your Medicine” campaign. This awareness was found to be significantly associated with all

demographic variables (Table 29). Respondents from the age group of 28-37 years, with

tertiary education, rural residencies, government sector, living alone and income more than

RM1000 had higher awareness of “Know Your Medicines” campaign.

80

Table 29: Consumers’ Awareness of “Know Your Medicine” Campaign


Outcome

Aware of Know your Medicine Campaign?

Yes

n (%)

No

n (%) p-value*

Total (N) 1600 (51.9) 1481 (48.1) -

Locality Urban 1150 (50.6) 1121 (49.4) 0.016

Rural 450 (55.5) 360 (44.5)

Age 18-27 409 (55.7) 325 (44.3)

<0.001

28-37 558 (61.1) 355 (38.9)

38-47 249 (52.7) 223 (47.3)

48-57 219 (45.1) 266 (54.9)

58-67 143 (40.0) 214 (60.0)

68-77 17 (16.8) 84 (83.2)

> 77 5 (26.3) 14 (73.7)

Gender Male 555 (45.9) 654 (54.1) <0.001

Female 1045 (55.8) 827 (44.2)

Ethnicity

Malay 1153 (58.8) 806 (41.2)

<0.001 Chinese 176 (31.8) 377 (68.2)

Indian 82 (42.0) 113 (58.0)

Others 189 (50.5) 185 (49.5)

Education Level Primary School 72 (25.7) 208 (74.3)

<0.001 Secondary School 690 (51.9) 639 (48.1)



Occupation Government 842 (73.9) 297 (26.1)

<0.001


Retired 80 (38.8) 126 (61.2)

Student 75 (41.6) 105 (58.4)

Unemployed 195 (38.8) 307 (51.2)

Living Status Alone 281 (60.1) 186 (39.9)

<0.001 With Family 1290 (50.5) 1261(49.5)

With Non-Family 29 (46.0) 34 (54.0)

Monthly Income ≤RM 500 93 (33.5) 184 (66.5)

<0.001

RM 501-1000 104 (39.3) 160 (60.7)

RM 1001- 1500 250 (52.8) 223 (47.2)

RM 1501- 2000 121 (54.5) 101 (45.5)

RM 2001- 2500 215 (55.8) 170 (44.2)

RM 2501-3000 87 (50.5) 85 (49.5)

RM 3001-3500 190 (60.5) 124 (39.5)

RM 3501-4000 68 (58.6) 48 (41.4)

RM 4001-4500 138 (59.2) 95 (40.8)

RM 4501-5000 73 (55.3) 59 (44.7)

> RM 5000 261 (53.0) 231 (47.0)


81

Table 30 summarizes the consumers’ sources of information about the “Know Your Medicines”

Campaign. Most of the respondents obtained their information of the campaign from brochure/

information from health facilities (41.2%) followed by road banners (27.5%) and common

information channels (26.3%).

Table 30: Consumers’ sources of information about the “Know Your Medicines” Campaign

Sources of Information about campaign Yes

n (%)

No

n (%)

Common Information Channel 810 (26.3) 760 (24.7)

Family/ Friends/ Neighbour 699 (22.7) 858 (27.8)

Road Banner 846 (27.5) 722 (23.4)

Internet 716 (23.2) 842 (27.3)

Brochure/ information from health facilities 1270 (41.2) 314 (10.2)

Others 109 (3.5) 1133 (36.8)

We found 54.8% of the participants reported to have attended “Know your Medicine’ campaign

activities. Out of those who have attended the activities, (n=759, 86.7%) attended exhibitions

followed by talks (68.8%) and road shows (15.3%) as shown in Table 31. Furthermore, the

attendance to “Know Your Medicines” campaign was significantly influenced by all

demographic variables except locality, gender and ethnicity (Table 32).

Table 31: Attendance for “Know Your Medicine” Campaign Activities

Variables N (%)

Attendance to campaign’s activities Yes 873 (54.8)

No 721 (45.2)

Types of campaign activities Talk 602 (68.8)

Exhibition 759 (86.7)

Road show 134 (15.3)

Level of satisfaction Very satisfied 251 (28.7)

Satisfied 545 (62.3)

Neither 70 (8.0)

Not satisfied 7 (0.8)

Is the campaign beneficial? Yes 867 (99.3)

No 6 (0.7)

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Table 32: Responses to “Have you attended any of the campaign’s activities?” based on demographic

characteristics

Demographic Characteristics Attended Campaign Activities?

Yes

n (%)

No

n (%)

p-value*

Locality

Urban 622 (54.5) 520 (45.5) 0.07

Rural 251 (55.5) 201 (44.5)

Age

18-27 221 (54.4) 185 (45.6) <0.001

28-37 294 (53.2) 259 (46.8)

38-47 155 (63.3) 90 (36.7)

48-57 122 (55.7) 97 (44.3)

58-67 67 (47.5) 74 (52.5)

68-77 9 (52.9) 8 (47.1)

> 77 1 (20.0) 4 (80.0)

Gender

Male 294 (52.9) 262 (47.1) 0.07

Female 579 (55.8) 459 (44.2)

Ethnicity

Malay 622 (54.1) 528 (45.9) 0.43

Chinese 104 (59.8) 70 (40.2)

Indian 40 (49.4) 41 (50.6)

Others 107 (56.6) 82 (43.4)

Education Level

Primary School 32 (45.1) 39 (54.9) 0.03


College/ University 436 (53.0) 387(47.0)


Occupation

Government 510 (61.2) 324 (38.8) <0.001


Retired 38 (47.5) 42 (52.5)

Student 42 (51.2) 40 (48.8)

Unemployed 88 (45.8) 104 (54.2)

83

Living Status

Alone 179 (63.9) 101 (36.1) 0.01

With Family 677 (52.7) 608 (47.3)

With Non-Family 17 (58.6) 12 (41.4)

Monthly Income

≤RM 500 45 (48.4) 48 (51.6) <0.001

RM 501 - RM 1,000 56 (54.4) 47 (45.6)

RM 1,001 - RM 1,500 132 (52.6) 119 (47.4)

RM 1,501 - RM 2,000 67 (54.5) 56 (45.5)

RM 2,001- RM 2,500 128 (59.5) 87 (40.5)

RM 2,501 – RM 3,000 50 (58.1) 36 (41.9)

RM 3,001 - RM 3,500 94 (50.3) 93 (49.7)

RM 3,501 – RM 4,000 43 (63.2) 25 (36.8)

RM 4,001- RM 4,500 75 (54.7) 62 (45.3)

RM 4,501 – RM 5,000 43 (59.7) 29 (40.3)

> RM 5,000 140 (54.1) 119 (45.9)

*Chi Square, significant at p < 0.05

84

5.0 DISCUSSIONS

Medicines use and expenditure among Malaysian consumers

A great challenge for the rational use of medicines is the cost containment of chronic of

medicines. National Health Morbidity Survey 2015 found an increasing prevalence of chronic

illnesses in Malaysia. Among the non-communicable diseases found across the country,

hypercholesterolemia was reported to be of the highest prevalence followed by hypertension

and diabetes mellitus (20). Such disease patterns found in Malaysia resembled closely to what

is reported from literature around the globe (21, 22). The increase in chronic illnesses has

resulted a rise of healthcare spending in the country has seriously compromised people's

healthy lifestyle choices and practices as predicted by the pattern of chronic diseases in the

country (19).

The use of traditional medicines is surprisingly small which is similar with the findings in

National Survey on the Use of Medicines (NSUM) 2012 (23). The minor group of people use

herbal and supplements not only to maintain their health but also to enhance their vitality and

appearance. There remained some proportion of consumers who sought consultation and

medicines information from traditional and complimentary (TCM) practitioners. Malaysia has

a diverse pool of traditional medicines practices as the country is made up of multi-ethnic

groups that carry with them different cultures, theories, beliefs and experiences. Although the

use of herbal products is not illegitimate, it is essential that the consumers are kept informed of

the policies and legislation governing TCMs to ensure that they access only safe and effective

products and services.

In recent years, public out-of-pocket healthcare expenditure in Malaysia has increased steadily.

Within this context, Ministry of Health, Malaysia is the main provider of health care services

in the country. The public health care system largely funded by the government and financed

mainly from public tax revenue. The private health care sector provides services on a

85

nonsubsidized, fee-for-service basis, and mainly serves for those who can afford to pay. Health

care services by private sectors are funded mainly by private health insurance, consumers’ out-

of-pocket payment, and non-profit institution. Therefore, a universal health financing system

must be established by transforming the role of budget funding from directly subsidizing

provision to subsidizing the purchase of services on behalf of the entire population. The

integration of services between the public and private sector is very much needed, at a cost the

people can afford (24).

Knowledge of medicines use

The extensive pharmaceutical use among the survey respondents and they claimed that

understand the proper use of medicines. However, many were unable to identify their own

medicines by the trade or generic name. This may be due to lower educational and income

level, unemployment and elderly had more problems in identifying brand and generic

medicines name than other groups. Nonetheless, most of the Malaysian consumers were aware

of the side effect, possible food-drug and drug-drug interactions, medicines’ shelf life and

storage condition.

On the other hand, many of the respondents were unaware about disposal of damaged or

expired medicines. The proper well-run disposal system and collection programs are

paramount in ensuring safety of humans and the natural environment. The awareness regarding

impact of improper disposal of pharmaceutical is still a cornered issue and need to be roused.

The current practices of collection and disposal of unwanted pharmaceuticals are not optimal;

it is highlighting the role of pharmacists towards the issue. Policies and programs need to be

established to educate the problem, minimising the risks and to protect environment and the

lives.

86

Self-assessed use of medicines

In the broader context of medicine use, non-compliance to treatment regimen is well reported

in literature (25). Prior reviews have estimated the extent of patient default at 20% to 82% (26,

27). Current results shows many reported that they had ever forgotten to take their medication

at some point in their lives. They also agreed that they had decided not to take a prescribed

medicine during some point of their treatment plan. In general, medication compliance is

affected by a multitude of factors (28) and from this survey, it was found that self-reported

non-compliance is dependent upon a number of variables. However, as the assessment of

compliance in the present survey was based upon self-reporting, the results may not reflect the

actual medication taking behaviour.

The negative implication of sharing medicines is equivalent of using medicines without

prescription. While self-medication is considered beneficial to a certain extent, sharing of

medications without professional supervision exposes patients at an increased risk of harm

arising from medication error (29). In this survey, some of the respondents were found to have

shared their medicines and was more prevalent in respondents living in the urban area, of

younger age group, tertiary education and higher income level.

We introduce price component in NSUM III which was not highlighted in the previous versions.

Where three quarter of the respondents agreed that price is an important component to be

displayed on medication labels, some think price has no effect on their medication taking

behaviour. Many respondents however think that price information of the labels helps them to

make choices when purchasing medicines which is also evident from literature (31, 32). It is

well known that many patients engage in an implicit cost–benefit analysis in which beliefs

about the necessity of their medication are weighed against concerns about the potential

87

adverse effects of taking it and that these beliefs are related to medication compliance and not

to the price (30).

Sources of information

The current survey reported that more than half of the respondents still prefer to consult the

doctors as their reference point on issues concerning medicines and health-related problems.

This could be explained in part by the growth of healthcare profession in Malaysia which is

largely dominated by the heavily subsidized public sector (33). However, when asked about

the ease of obtaining information on medicines, this survey shows consumers felt that it is

easier to obtain information from government pharmacists when compared with government

doctors and private physicians, community pharmacists and private doctors.

Most respondents obtained medicines information from the internet, friends, family and

neighbours, printed materials, and common information channels. This is due to introduction

of information technology and social media, medicine-related information if freely and readily

available. While little can be done to control and constrain the information available in the

World Wide Web and mass media, there is an urgent need to educate consumers about the

credibility and reliability of information obtained from sources other than the mainstream

healthcare providers. To overcome this issue, the Pharmaceutical Services Division developed

an online portal for consumers to submit medicines enquiries and complaints of

pharmaceuticals as part of the national “Know Your Medicines” programme. However, survey

found many still unaware of this service.

More than half of the respondents had attended the campaign activities and almost all of them

were satisfied with the movement. Therefore, a rigorous effort is needed to spread the news

about the campaign so that people can take maximum benefits and know how about rational

medicine use.

88

Most respondents needed additional written medicines information and this was associated

with their age, ethnicity, education, occupation, living status and income level. This is a

positive indication whereby the Malaysian consumers are willing to know more about their

medication use.

70.8% of the respondents reported that they require additional counselling from their

pharmacists. This is a reflective of the expansion of pharmacists’ role in patient care in the

healthcare system in Malaysia. The increase in the number of pharmacists in both public and

private workforce has translated into the provision of more pharmaceutical care services such

as medication management therapy. Malaysian consumers now view pharmacists as an

important player in the healthcare system that is evident from literature (34).

Know your medicines programme

The “Know Your Medicines” programme is a national project jointly organized by the Ministry

of Health (MOH) and the Consumers Association of Malaysia (FOMCA) aiming to improve

quality use of medicines among consumers in the country. Eight years into the programme, up

to half of the consumers participated in this survey were aware of the programme’s existence

and had participated in the programme activities. The findings are similar to what was reported

in NSUM II (23) indicating the continuous advertisement and efforts of the Pharmaceutical

Services Division.

Majority of the respondents who had participated in the programme activities were satisfied

with the programme and felt that it was beneficial for them.

89

6.0 CONCLUSIONS

As a whole, the pattern and practices of medication-related information and medicine usage is

not remarkably different to what was reported in NSUM II. The use of pharmaceuticals is

common among consumers in Malaysia. Majority of consumers felt that medicines labelling is

adequate and did not expressed any difficulty in reading the labels of medicines obtain from

various health facilities in Malaysia. However, the ability of identify medicines by their trade

or generic name is still lacking in Malaysian population. The information seeking behaviour of

consumers in Malaysia has evolved over the years with more consumers consulting the

mainstream healthcare providers such as doctors and pharmacists as well as accessing

information through the use of technologies such as internets. Although generally consumers’

awareness of the national “Know Your Medicines” programme is widespread, participation

uptake is still relatively low. Overall, it can be observed that Malaysian consumers’ medicines

taking and information seeking behaviour has evolved over time as captured by the NSUM II.

This periodic mapping of pharmaceuticals use among consumers in Malaysia is indeed an

important effort to explore issues on quality use of medicines and make plans for future

interventions and policies.

7.0 LIMITATIONS

The evaluation of consumers’ awareness, knowledge and understanding of quality use of

medicines were based on a self-reported assessment and hence actual consumer behaviour

cannot be verified. Public’s out-of-pocket expenditure and medication compliance was an

estimation that was based on consumer recall and hence poses recall bias to the survey findings.

90

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