World Health Survey, 2003 WEST BENGAL

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Oct 14, 2004 - Ms. Nandini Das. Mr. Subrata Mohanti. Ms. Jomini Jose. Mr. Sanjay ... Mr. Chandra Chakraborty. Ms. Namita Mukherji. Ms. Bejoy Kumar Bose.

World Health Survey, 2003

WEST BENGAL

International Institute for Population Sciences (IIPS), Mumbai

World Health Organisation (WHO), Geneva

World Health Organisation - India - WR Office, New Delhi

2006

Contact Information : International Institute for Population Sciences Govandi Station Road, Deonar, Mumbai - 400088. Tel.: 91-22-25575206, 91-22-25563254/55/56 Fax: 91-22-25563257

CONTRIBUTORS H. Lhungdim T.K. Roy M. Guruswamy P. Arokiasamy

Contents

LIST OF TABLES

iv

LIST OF FIGURES PREFACE ACKNOWLEDGEMENTS FACT SHEET SUMMARY OF FINDINGS

vii ix xi xiii xv

CHAPTER 1 INTRODUCTION 1.1 Health system performance in India 1.2 Share of public and private facilities in health care 1.3 Health system goals 1.4 New health policy in India 1.5 Health related surveys in India 1.6 The World Health Survey (WHS) - 2003 1.7 Socio-demographic profile of West Bengal 1.8 Health profile of West Bengal

1 1 1 2 3 3 4 5 5

CHAPTER 2 METHODOLOGY 2.1 National sampling 2.2 Sampling for West Bengal 2.3 Questionnaire 2.4 Geographic information system (GIS) 2.5 Training, data collection and quality assurance 2.6 Field experience of the investigators 2.7 Limitation of the data/study 2.8 Survey metrics 2.9 Response rate 2.10 Reliability 2.11 Weighting

7 7 8 9 11 11 12 12 12 13 13 13

CHAPTER 3 SOCIO-DEMOGRAPHIC PROFILE OF HOUSEHOLD POPULATION AND RESPONDENTS 3.1 Household population profile 3.1.1 Age-sex distribution

15 15 15

i

3.1.2 3.1.3 3.1.4 3.2 3.2.1 3.2.2 3.2.3 3.2.4 3.2.5

Marital status Educational status Household size Profile of Individual respondents Age-sex distribution Marital status Education status Religion Mother tongue

15 16 16 16 16 18 18 18 19

CHAPTER 4 RISK FACTORS 4.1 Tobacco consumption 4.2 Alcohol consumption 4.3 Nutrition and Physical activities 4.4 Access to improved water sources 4.5 Access to improved sanitation 4.6 Solid fuel use

20 20 22 22 25 27 28

CHAPTER 5 MORBIDITY PREVALENCE 5.1 Communicable diseases 5.1.1 Tuberculosis and HIV/ AIDS 5.1.2 Malaria and diarrhoea 5.2 Maternal and reproductive health 5.3 Non-communicable diseases 5.3.1 Asthma, Arthritis, Angina, 5.3.2 Diabetics, psychosis and depression 5.4 Vision care 5.5 Oral health and injuries

30 30 31 32 33 36 36 37 38 39

CHAPTER 6 HEALTH STATE VALUATIONS 6.1 Health state description 6.2 General health rating 6.3 Work and household activities 6.4 Mobility 6.5 Self care 6.6 Pain and discomfort 6.7 Cognition 6.8 Interpersonal activities 6.9 Vision 6.10 Sleep and energy 6.11 Affect

41 41 41 43 43 47 49 51 55 58 59 62

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CHAPTER 7 HEALTH SYSTEM RESPONSIVENESS 7.1 Self-assessed need for health care 7.2 Self-assessed need for different types of health care services 7.2.1 Self-assessed need for inpatient care 7.2.2 Self-assessed need for out patient care 7.3 Health system responsiveness 7.3.1 Responsiveness for inpatient treatment 7.3.2 Responsiveness for out patient treatment

65 66 67 68 69 70 71 72

CHAPTER 8 HEALTH EXPENDITURE, INSURANCE AND HUMAN RESOURCES FOR HEALTH 8.1 Health Expenditure 8.1.1 Household health expenditure by type of services and income 8.1.2 Sources of health expenditure 8.1.3 Catastrophic spending on health 8.1.4 Out of pocket expenditure on health 8.1.5 Impoverishment (IMPOOR) 8.2 Insurance 8.2.1 Insurance coverage 8.3 Human resources for health

74 74 74 75 76 77 77 78 79 80

REFERENCES GLOSSARY APPENDIX – A: LIST OF CONTRIBUTORS APPENDIX – B: RESEARCH TEAM AND STAFF

84 86 89 90

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Tables

Page Table 1.1

Trends in health expenditure in India, 1997-2001

2

Table 1.2

Selected socio-demographic indicators for India and West Bengal

5

Table 1.3

Selected health status and infrastructure indicators for India and West Bengal

6

Table 2.1

Classification of states by region and levels of development

7

Table 2.2

Response and non-response rate in West Bengal, 2003

14

Table 3.1

Percent distribution of household population profile by socio-demographic characteristics, West Bengal 2003

17

Percent distribution of respondents by socio-demographic characteristics, West Bengal 2003

19

Table 4.1

Percent of respondents consuming tobacco [smoke, chew] in West Bengal, 2003

21

Table 4.2

Prevalence of infrequent and frequent heavy drinking in West Bengal, 2003

23

Table 4.3

Prevalence of insufficient intake of fruits and vegetables and insufficient physical activity in West Bengal, 2003

24

Table 4.4

Height and weight of women in West Bengal, 2003

26

Table 4.5

Height and weight of men in West Bengal, 2003

27

Table 4.6

Access to improved drinking water in West Bengal, 2003

28

Table 4.7

Access to improved sanitation in West Bengal, 2003

29

Table 4.8

Types of fuel used for cooking in West Bengal, 2003

29

Table 5.1

Coverage for communicable diseases in West Bengal, 2003

31

Table 5.2

Percent of children with episode of malaria and diarrhoea and percent treated in West Bengal, 2003

32

Percent of women screened for cancer in West Bengal, 2003

33

Table 3.2

Table 5.3

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Table 5.4

Percent of mothers who received antenatal care in the last five years and children under-5 years who received health care in West Bengal, 2003

35

Percent of respondents who need (diagnosed) and covered (treated) for noncommunicable diseases (angina, arthritis asthma) in West Bengal, 2003

36

Percent of respondents who need (diagnosed) and covered (treated) for noncommunicable diseases (diabetes, psychosis, depression) in West Bengal, 2003

37

Table 5.7

Need and coverage for vision in West Bengal, 2003

38

Table 5.8

Coverage for oral health and injuries in West Bengal, 2003

39

Table 6.1

Respondents rating their health in general in West Bengal, 2003

42

Table 6.2

Difficulty with work or household activities in last 30 days in West Bengal, 2003

44

Table 6.3

Difficulty with moving around in the last 30 days in West Bengal, 2003

45

Table 6.4

Difficulty with vigorous activities in the last 30 days in West Bengal, 2003

46

Table 6.5

Difficulty with self-care (washing/dressing) in the last 30 days in West Bengal, 2003

48

Table 6.6

Difficulty in taking care of and maintaining general appearance in the last 30 days in West Bengal, 2003

49

Table 6.7

Bodily aches or pains in the last 30 days in West Bengal, 2003

50

Table 6.8

Bodily discomfort in the last 30 days in West Bengal, 2003

52

Table 6.9

Difficulty in concentrating or remembering things in the last 30 days in West Bengal, 2003

53

Table 6.10

Difficulty in learning a new task in the last 30 days in West Bengal, 2003

54

Table 6.11

Difficulty with personal relationships or participation in the community in the last 30 days in West Bengal, 2003

56

Difficulty in dealing with conflicts and tensions in the last 30 days in West Bengal, 2003

57

Difficulty in seeing and recognizing a person across the road (20m) in the last 30 days in West Bengal, 2003

59

Difficulty in seeing an object at arm’s length or in reading in the last 30 days in West Bengal, 2003

60

Table 6.15

Difficulty in sleeping in the last 30 days in West Bengal, 2003

61

Table 6.16

Difficulty in feeling rested and refreshed in the last 30 days in West Bengal, 2003

62

Table 5.5

Table 5.6

Table 6.12

Table 6.13

Table 6.14

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Table 6.17

Respondents feeling sad, low or depressed in the last 30 days in West Bengal, 2003

63

Table 6.18

Respondents reporting difficulty with worry or anxiety in the last 30 days in West Bengal, 2003

64

Percent distribution of respondents needing health care by selected characteristics in West Bengal, 2003

66

Percent distribution of respondents with self-reported need (diagnosed) for health care in the previous 12 months by type of services in West Bengal, 2003

67

Percent distribution of respondents with self-assessed need for inpatient care in the previous 5 years in West Bengal, 2003

68

Percent distribution of respondents with self-assessed need for outpatient care in the previous 5 years in West Bengal, 2003

69

Mean scores for various domains of responsiveness for inpatient services in the last 12 months in West Bengal, 2003

71

Mean scores for various domains of responsiveness for outpatient services in the last 12 months in West Bengal, 2003

73

Table 8.1

Household health expenditures by types of services and income in West Bengal, 2003

75

Table 8.2

Percent of households by source of health expenditures in West Bengal, 2003

76

Table 8.3

Household economic status and catastrophic spending on health by type of services and Income in West Bengal, 2003 (in Rupees)

77

Table 8.4

Share of individuals by insurance coverage and household income in West Bengal, 2003

79

Table 8.5

Profile of human resources for health per 100,000 population by selected characteristics in West Bengal, 2003

80

Percent of health professionals by their current work status in West Bengal, 2003

82

Table 7.1

Table 7.2

Table 7.3

Table 7.4

Table 7.5

Table 7.6

Table 8.6

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Figures

Page Figure 2.1

Distribution of primary sampling units (PSUs) in West Bengal, 2003

11

Figure 2.2

Sample deviation index (SDI) for household population in West Bengal, 2003

13

Figure 2.3

Sample deviation index (SDI) for individual respondents in West Bengal, 2003

14

Figure 3.1

Population pyramid for West Bengal, 2003

16

Figure 3.2

Age distribution of respondents by residence for West Bengal, 2003

18

Figure 4.1

Tobacco use by age and sex in West Bengal, 2003

22

Figure 7.1

Mean scores of responsiveness for various domains of inpatient and outpatient cares in West Bengal, 2003

70

Figure 8.1

Structure of out of pocket health payments in West Bengal, 2003

78

Figure 8.2

Percent of out of pocket expenditure as a share of capacity to pay in West Bengal, 2003

78

Figure 8.3

Percent of households with catastrophic expenditure and impoverished due to payment of health services by expenditure deciles in West Bengal, 2003

79

Figure 8.4

Distribution of human resources for health in West Bengal, 2003

81

Figure 8.5

Age distribution of health professionals by occupation in West Bengal, 2003

81

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Preface

The World Health Organization initiated a multi-country world health survey programme in 70 countries to provide evidence based health information for health interventions. The core objective of the survey is to strengthen the health information system of the country and develop the capacity of policy makers to monitor health system performance in terms of three major components namely burden of disease, health financing and health system performance. The key objective is to provide data on a wide range of population health indicators such as health financing, health insurance, human resources for health, health state valuation, risk factors, mortality by cause, morbidity prevalence, reproductive and sexual health care and health system responsiveness relating to inpatient and outpatient care. The World Health Organization and the Ministry of Health and Family Welfare designated the International Institute for Population Sciences to undertake the World Health Survey in India. Funding and technical assistance were provided by the WHO, Geneva. Additional funding was provided by WHO, India Office, New Delhi. The World Health Survey covered six major states of India namely Assam, Karnataka, Maharashtra, Rajasthan, Uttar Pradesh and West Bengal, which comprise about 47 percent of the country’s population. The WHS–India covered a representative sample for each state. The pooled sample for India was 10,279 households. The health information questionnaire covered a randomly selected sample of 9994 adult individuals in the ages 18 and above. In West Bengal, the survey covered a representative sample of 2111 households and 1925 adult individuals. The WHS used standardized household and individual questionnaires in all the six states, which is also used in 70 other countries. The fieldwork for the survey was completed during February to June 2003. The instruments, sampling design, tabulations and structure of state and combined India report were finalized in various regional and international workshops conducted by the WHO. A Steering Committee, comprising officials from MOHFW and researchers in the area of population health, guided the conduct of the survey. Six state and India reports are presented to provide key population health indicators to health policy makers and researchers. For the first time in India, data is provided on a variety of population health indicators based on updated definitions of health. There are several other unique features that the report unfolds. We hope it will be useful for demanding a framework for health policy interventions and further research.

Prof P.N. Mari Bhat Director & Senior Professor International Institute for Population Sciences, Mumbai

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Acknowledgements The World Health Survey-India 2003 was successfully implemented in six states in the country due to collaborative efforts of the Evidence, Information and Policy Division of the WHO, Geneva and the WHO-WR, New Delhi, and International Institute for Population sciences (IIPS), Mumbai and a number of state level research organizations and researchers in the area of population health. Dr. Chris Murray, the then Executive Director and Mr. David Evans, the current Executive Director of the EIP Division provided overall leadership to the WHO- WHS multi-country survey in 70 countries. Dr. U.B. Ustun, the survey coordinator and Dr. Somnath Chatterji, senior scientist guided the India team both in technical and operational aspects of the survey. Dr. T.K. Roy, the then Director, IIPS, Dr. G. Rama Rao, as officiating Director and Prof. P.N. Mari Bhat, Director, IIPS also provided unreserved support at various stages of the survey in India. Dr. Russel Blamey, quality assurance advisor for WHO and Dr. Nanjamma Chinappa, sampling advisor for WHO-WHS, deserve special thanks for their suggestions and support. We also thank the Office of the Registrar General and Census Commissioner, Government of India, New Delhi, and the state Census officials for their support in providing of data and the maps during the preparatory stage of the survey. We express our sincere thanks to the World Health Organisation, Geneva, for entrusting us with the task of conducting this survey in India. Special thanks are due to Mr. Sunil Nandraj, National Professional Officer, WR, India, for initiating the project, for being a member of Steering Committee and regularly interacting with us at various stages of the survey. Our sincere thanks are due to the members of the project Steering Committee for their guidance, support and encouragement: Mr. K.V. Krishnan, formerly Economic Advisor to the Ministry of Health and Family Welfare, Government of India; Smt. Ganga Murthy, Economic Advisor to the Ministry of Health and Family Welfare, Government of India; Dr. K. V. Rao, formerly Chief Director, Ministry of Health and Family Welfare, Government of India; Mr. D.K. Joshi, formerly Chief Director, Ministry of Health and Family Welfare, Government of India; Mr. P. Chattopadhyay, Chief Director, Ministry of Health and Family Welfare, Government of India; Prof. P. M. Kulkarni, Centre for the Study of Regional Development, Jawaharlal Nehru University, New Delhi; Prof. C.A.K. Jesudian, Tata Institute of Social Sciences, Mumbai; Dr. Subhash Salunke, Director of Health Services, Government of Maharashtra. It should be mentioned that a small army of people at various levels and in various places contributed towards the completion of the survey. A research team at IIPS, Mumbai spent seemingly endless hours in preparatory work for the survey, data entry and data cleaning, in tabulation and in drafting the reports. We sincerely thank all of them. We also express our sincere gratitude to all the respondents, local resource persons including the concerned state government officials and headmen/chiefs of the various villages, who had contributed at various stages and made the survey a success in Assam. We express our sincere thanks to Dr. A.K. Roy and Mr. B.M. Bhattacharya of Economic Information Technology (EIT), Kolkata, for their overall support and assistance in monitoring the teams during the fieldwork in different parts of West Bengal. H. Lhungdim T.K. Roy M. Guruswamy P. Arokiasamy August 2006, Principal Investigators IIPS, Mumbai-88. WHO-WHS (INDIA) 2003

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Fact Sheet – West Bengal World Health Survey-India, 2003 Population (sample) Households covered Individuals interviewed Number of PSUs Urban Rural

Morbidity (in percent) Tuberculosis screening5 Counselling for HIV/AIDS6 Condom use

8874 1925 1675 18 52

Risk Factors (in percent) Prevalence of tobacco consumption Urban Rural

37.4 25.1 36.5

Never had a drink1 Urban Rural Access to piped water Urban Rural

88.3 88.3 88.3 12 37.6 6.2

Access to other sources of improved drinking water2 Urban Rural

72 58.6 75.0

No access to safe water Urban Rural

2.9 0.2 6.3

Malaria7 Diarrhoea Cervical cancer screening8 Breast cancer screening9

2.3 19.3 13.0 1.4

Maternal Health (in percent) Full antenatal care10 Care for delivery

60.3 41.1

Immunization11 (in percent) DPT3 Measles Non-communicable diseases12 (in percent) Angina Need (diagnosed) Coverage (treated)

23.5 16.6 5.9 71.0

16.1 3.8 18.7

Arthritis Need (diagnosed) Coverage (treated) Asthma Need (diagnosed) Coverage (treated)

6.6 78.1

1.8 5.7 0.9

Diabetes Need (diagnosed) Coverage (treated)

3.9 78.5

Access to other improved toilet facilities3 Urban Rural

34.7 64.7 28.1

Depression Need (diagnosed) Coverage (treated)

11.7 17.8

No access to improved sanitation Urban Rural

63.6 29.9 71.1

Psychosis Need (diagnosed) Coverage (treated)

1.8 66.5

Fuel Use (in percent) Cooking with electricity/gas Urban Rural

16.9 58.2 7.8

Cataracts (ages 60+) Need (diagnosed) Coverage (treated)

21.2 55.5

Cooking with kerosene Urban Rural

3.0 10.1 1.5

Cooking with solid fuel4 Urban Rural

80.0 31.7 90.7

Oral health problems Need (diagnosed) Coverage (treated) Needed emergency care for road traffic injuries Needed emergency care for other injuries

42.2 38.3 4.5 2.7

Sanitation (in percent) Access to flush toilet to sewage system Urban Rural

General health rating13 (in percent) Very Good

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35.3 58.2

Overall Male Female Urban Rural

5.9 8.5 3.3 7.6 5.5

Very Bad Overall Male Female Urban Rural

6.4 5.8 6.9 5.3 6.6

Mobility No difficulty Extreme difficulty

44.6 4.0

Vigorous activity No difficulty Extreme difficulty

27.1 16.1

Self care No difficulty Extreme difficulty

49.9 6.6

Bodily aches or pains No difficulty Extreme difficulty

29.2 5.0

Bodily discomfort No difficulty Extreme difficulty

31.4 4.8

Cognition/concentration or remembering No difficulty Extreme difficulty

41.2 5.1

Inter-personal activities No difficulty Extreme difficulty

54.3 6.0

Vision - seeing/recognizing a person across the road (20m) No difficulty Extreme difficulty

61.7 6.1

Seeing an object at arm’s length or reading No difficulty Extreme difficulty

65.8 4.0

Sleep No difficulty Extreme difficulty

44.9 4.3

Depression No difficulty Extreme difficulty

36.9 4.1

Health System Responsiveness Rating14 Inpatient Services Overall Autonomy Choice Communication Confidentiality Dignity Prompt attention

52.3 51.5 49.0 59.4 54.8 72.9 36.7

Outpatient Services Overall Autonomy Choice Communication Confidentiality Dignity Basic Amenities Prompt attention

65.4 61.6 63.5 75.5 67.9 78.9 49.3 61.1

Health Expenditure (in Rupees) 15 Total Inpatient care Outpatient care Traditional medical practitioners Drugs Others

138.2 2.1 44.0 4.4 70.9 16.7

Catastrophic spending (in Rs.)

223.8

Insurance coverage Overall Mandatory Voluntary Urban (total coverage) Rural (total coverage)

6.0 4.6 1.4 10.2 1.8

Human resources for health (per 100,000 population) Physicians Nursing and Midwifery personnel Other health related and support occupation

11 214 169

8. 9. 10. 11.

Note : 1. In last 7 days. 2. Public standpipe, protected tube well, bore well,dug well or spring, rainwater etc. 3. Pour flush toilet, covered dry latrine etc. 4. Coal, charcoal, wood, agriculture/crop, animal dung, shrubs/ grass etc.

12. 13. 14.

5. Reference period is last one year. 6. Corresponds to all females of age 18-49, pregnant in last 5 years.

15.

7. Reference period is last one year for children under 5 years.

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Applies to females of age 18-69. Females of age 40-69. Reference period is last five years for women in ages 18 - 49. Immunization corresponds to children under 5 years, only for cases for which card is shown. Reference period is one year prior to the survey. Rating on the day of survey. Responsiveness varies in the range of scores of 0-100; Reference period is last 12 months. Reference period is last one month.

Summary of Findings

The salient findings of the World Health Survey in West Bengal are as follows:



Over half the females in the sample had no formal education (51 percent) compared to males (25 percent). At each level of education, there are more males than females. Only about three percent of females completed college or university education compared to six percent among males.



Religious affiliations of respondents indicate that threefourths are Hindu, 19 percent are Muslim and six percent belong to other religions.



Over four-fifths (83 percent) of the respondents speak Bengali, two percent speak Hindi and about 14 percent speak other dialects or languages.

1. SOCIO-DEMOGRAPHIC PROFILE OF HOUSEHOLD MEMBERS AND INDIVIDUAL RESPONDENTS •

The overall household population of the sample is 8874 persons and over half (52 percent) of the population are males. The elderly persons (60+ years) account for about 10 percent. Two-thirds (66 percent) are currently married, 26 percent were never married and about eight percent widowed or divorced.



The total urban household population is 2611 persons and accounts for about 29 percent.



The mean number of households is 5.2 persons.



About 21 percent of males and about 35 percent of females in the sample had no formal schooling. Among those who had attended school, a majority had completed primary school (33 among males and 24 percent among females). In the case of higher education (high school and above), the proportion is higher among males (14 percent) compared with females (eight percent).

2. RISK FACTORS Information collected on risk factors pertains to household environment (access to safe water, sanitation and fuel) and individuals (use of tobacco, alcohol consumption, physical activities, nutritional status). Use of tobacco

Information about the selected respondents included their age, sex, marital status, educational status, ethnicity and language spoken. In all, the survey covered 1675 individuals (excluding non-responses). •

Both males and females are represented equally (about half each).



About 29 percent respondents are from the urban areas. The proportion of females covered in the urban areas was higher (52 percent) than males (47 percent).



About 74 percent were currently married, 16 percent unmarried and 10 percent were widowed or divorced.

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Prevalence of tobacco use is about 37 percent. Higher proportion of tobacco users are in rural areas (37 percent) than in urban areas (25 percent).



More than twice the men (48 percent) use tobacco compared to women (21 percent).



The proportion of tobacco users is highest (49 percent) among those age 65 and over than among the youth (19 percent). Among males, consumption level of tobacco is the highest among ages 35-44 and 65+ (both over 66 percent) but among females the level increases at higher ages (from 13 percent among ages 18-24 to 34 percent among ages 65+).



Use of tobacco increases with age but decreases with income levels (42 percent in the lowest income quintile compared to 18 percent among the highest income quintile).

Alcohol consumption •

About 88 percent respondents reported that they never had a drink in the past one week and about 12 percent are primarily infrequent heavy drinkers (one standard drink in 1-3 days in the past one week).



There is a higher proportion of infrequent drinkers among males (18 percent) than among females (four percent).



No difference was found in the proportion of infrequent heavy drinkers by residence (10 percent in both rural and urban areas).





Access to drinking water •

Eighty-four percent of households have access to improved drinking water from any sources. Only 12 percent households have access to drinking water piped to their households. Overall, 16 percent had no access at all to improved water sources.



In case of weight-for-height (BMI), a higher proportion of men (21 percent) have BMI below 18.5 Kg/m 2 compared to females (19 percent). The proportion overweight (BMI 30Kg/m2) is also higher among females.

The proportion of households with no access to improved water sources is about six times higher in rural areas (19 percent). Drinking water piped to households is available in over one-third of urban households (38 percent) compared to only six percent of rural households.



The proportion with low nutritional status is higher in the rural areas than in the urban areas for both males and females.

Over one-fifth households (23 percent) in the lowest income quintile have no access to improved water compared to 10 percent among the highest income quintile.

Sanitation

Alcohol consumption is the least among ages 18-29 (five percent) and ages 70+ (six percent). Persons reportedly drinking more frequently are in ages 4559 (16 percent).

Nutritional status The mean height of males is 161 cm and 151 cm for females. Over one quarter (26 percent) females are below 145 cm and 13 percent males are below 152 cm. •





Overall, 16 percent of females compared to 10 percent of males have BMI of 25 Kg/m2 or more.



Variation in BMI is indicated by economic status. A higher proportion of adults, both males and females, with BMI below 18.5 Kg/m2 are found in the first and second income quintiles than in the fifth income quintile.





About one-third adults (33 percent) have reported inadequate physical activities, i.e. less than 150 minutes of activity per week). The proportion with inadequate physical activities is higher among females (38 percent) than males, among urban respondents (42 percent) than rural respondents, among the higher income quintiles (fourth and fifth) than among the lower income groups, and among the elderly persons than among the younger persons.

About 95 percent reported insufficient in-take of fruits and vegetables. No difference was found among males and females but insufficiency is higher in rural areas (96 percent) than in the urban areas (91 percent).



Over three-fifth households (64 percent) have no access to improved sanitation and very few households have the privilege of owning flush toilets (two percent). Flush toilet to sewage system is mainly available in the urban areas and among the higher income groups.



Other improved toilet facilities (other than flushed toilet) is available to 64 percent households in urban areas and 28 percent in rural households.

Solid fuel •

Insufficient in-take of fruits/vegetables is common among various age groups but higher among those aged 70 and over.

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Four-fifths of the households used solid fuel for cooking. The proportion using solid fuel for cooking is very high in the rural areas (91 percent) and among the lower income quintiles (ranging from 91-99 percent in the first, second and third quintiles).





Overall, 17 percent households use electricity or gas for cooking. However, it is the main fuel/energy used for cooking mainly in the urban areas (58 percent) and among the higher income quintiles (85 percent of fifth income quintile).



All the girls who had malaria got treatment (93 percent of boys) and there is no variation in treated cases by income levels, except in the lowest income quintile (78 percent treated).



Episodes of diarrhoea were reported more among girls (20 percent) than among the boys (18 percent). Diarrhoea cases were higher in the rural areas (21 percent) than in the urban areas (about 10 percent).



Diarrhoeal cases were prevalent among all income groups (ranging from 17-26 percent), except in the highest income quintile (only four percent).

Kerosene is not popular for cooking in West Bengal (used by three percent households) and is used more in urban areas.

3. MORBIDITY PREVALENCE (NEED AND COVERAGE) Health coverage refers to the probability of receiving a health service conditional on the presence of the health care needs. This definition is based on three main premises: a) presence of health care need is a precondition for receiving an intervention; b) coverage is defined at the individual level; and c) coverage refers to the anticipation of a certain outcome of the interaction between the individual and the health system when health care need emerges.

Maternal and child health •

Thirteen percent females (ages 18-69) had been screened for cervical cancer. These women are primarily from the urban areas (15 percent) and higher income group (18 percent).



Screening for breast cancer was reported by about one percent of adult females ages 40-69, mostly from the urban areas (three percent) and from all income quintiles.



About 60 percent women received full antenatal care (three time pregnancy checks, blood pressure measurement or testing of blood for complications). However, 41 percent received care for delivery at any health facility or by health personnel.



More women from urban areas, the educated, the insured persons and higher income quintiles receive ANC and care for delivery.



About 24 percent children below 5 years received DPT3 immunization. The coverage is higher for children in the urban areas (29 percent) than the rural areas (23 percent).



The coverage for measles immunization of children less than five years is about 17 percent. Overall coverage is higher for female children (24 percent) and among children in the urban areas (29 percent).



Mother’s educational status was found to influence coverage of antenatal care, care for delivery and immunization for children. Mothers educated above high school level reported three to four times higher immunization of their children for DPT 3 and measles and about twice higher for full ANC.

Screening for Tuberculosis and HIV/AIDS •

About three percent women were screened for tuberculosis (TB). The proportion screened for TB higher among males, among rural residents and among the lower income groups.



Only very few pregnant women had voluntary testing for HIV/AIDS and those who had been tested are mainly from the urban areas.

Condom use •

About six percent adults reported using condoms. The reported condom use is the same among males and females (about six percent) and its use is higher in the urban areas.



The proportion using condoms is higher among the uninsured individuals (17 percent) and in the highest income quintile (14 percent).

Malaria and Diarrhoea among children (below 5 years) •

Two percent of children below 5 years had episodes of malaria in the last one year and both boys and girls are equally likely to get malaria. A majority of those who had malaria received treatment (96 percent).

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percent), the insured (46 percent) and among the highest income groups (59 percent).

Coverage of non-communicable diseases •





The highest need (diagnosed) was for arthritis (35 percent) followed by depression (12 percent). The prevalence of angina and asthma is about the same (six percent), four percent for diabetes and two percent for psychosis. Among those suffering from the different diseases, coverage is higher for asthma and diabetes (78 percent each) and angina (71 percent). Despite high need for arthritis, the coverage is low (58 percent). No sharp difference was found in the proportion diagnosed with diseases like angina, asthma, and psychosis between males and females, among income groups or residence. But more males reported depression and diabetes than females while more females reported arthritis than males.

Coverage of vision (among over 60 years) •



About 21 percent elderly persons were diagnosed with cataracts. The problem is higher in the urban areas (43 percent) than in the rural areas (14 percent) and among females (26 percent) than among males (17 percent). More cases are reported from the insured persons (25 percent) than among the uninsured persons (21 percent) and in the highest income quintile (38 percent). The coverage (of surgery) for cataracts is about 56 percent. More elderly persons in the urban areas, insured and females are treated for cataracts. Coverage for cataracts is higher in the lowest income quintile (82 percent) than among the fifth income quintile (48 percent).



About five percent needed emergency care due to road traffic accidents and three percent needed care for other injuries. The males, urban residents and uninsured adults are more likely to need such emergency care than their counterparts.

4. HEALTH STATE VALUATIONS Health state valuation by individuals relates to rating of their current physical and mental health. The health domains pertain to mobility, self-care, pain and discomfort, cognition, interpersonal activities, vision, sleep and energy and affect. Respondents were asked two questions in each category with a reference period of 30 days prior to the survey. The reported difficulties are rated on a five-point scale such as none (no difficulty), mild, moderate, severe and extreme. General health rating •

Only six percent rated their general health condition as ‘very good’ and 28 percent as ‘good’. Overall, about 34 percent respondents rate themselves as healthy.



Twenty-seven percent consider their health in unhealthy state (bad and very bad conditions).



The elderly persons, rural residents and females are more likely to rate their health as ‘bad’ or ‘very bad’ compared with their counterparts.

Work or household activities

Coverage of oral health and emergency care for traffic injuries

Respondents were asked to rate the difficulty with their work or household activities in the last 30 days. The rating options were none, mild, moderate, severe and extreme.



Over two-fifths (42 percent) respondents reported oral health problems. The problem has been more prevalent among females (43 percent) than males (42 percent), in the rural areas (43 percent) than in urban areas (39 percent) and in the lowest income quintile (44 percent) than in the highest income quintile (38 percent).



About 32 percent of respondents reported having no difficulty at all with either work or household activities while about 46 percent reported mild difficulty and 24 percent had moderate difficulty.



Close to 22 percent had reported severe and extreme difficulty in their work or household activities, with six percent reporting extreme difficulty.

Only 38 percent receive treatment for oral problems in the last one year. The overall coverage is higher for females (41 percent), among urban residents (46



Over one-third (37 percent) of males compared to 28 percent among females reported no such problems. More females reported mild and severe



xviii

difficulties with their work or household activities than males.

Pain and discomfort The health state module contains two questions on pain and discomfort, namely the extent of bodily aches or pains and extent of bodily discomfort.

Mobility This health state module of the World Health Survey asked two questions to the respondents regarding mobility: (a) difficulties in moving around and (b) difficulties in engaging in vigorous activities. •



Over two-fifths of the respondents (45 percent) have no difficulty in moving around and about 16 percent reported severe to extreme difficulty. The remaining 39 percent had mild to moderate difficulty. A higher proportion of respondents having no difficulty in moving around are males, ages below 30 years, urban residents and educated persons (above 11 years of schooling).



Twenty-seven percent of respondents have no difficulty with vigorous activities and 38 percent reported severe to extreme difficulty.



Besides the elderly persons, rural residents and females reported more of severe to extreme difficulty with vigorous activities.







Severe to extreme bodily ache is reported more by females and rural residents.



Overall, 31 percent do not have any bodily discomfort while 22 percent reported severe to extreme of such difficulty.



The proportion with no bodily discomfort is 37 percent among males and 26 percent among females. It is also found that no bodily discomfort is reported to be much higher in the urban (42 percent) compared to rural areas (29 percent).

The cognition section of the health state module assessed the difficulty of the respondents in (a) concentrating or remembering things and (b) difficulties in learning a new task in the last 30 days.

The extent of difficulty with personal care relates to (a) self-care and (b) maintaining the general appearance, both in the last 30 days.



Only 29 percent reported not having any bodily aches or pain and about 26 percent have severe to extreme such pains in the body. The proportion with no such aches or pain is about 26 percent among the females compared to 40 percent among males.

Cognition

Self-care





About half of the respondents do not have any difficulty with self-care and 17 percent have severe to extreme difficulty with self-care. Three-fifths of males do not have any such difficulty, compared to one-fifth females. A majority of urban residents (53 percent), those with higher education (69 percent) and younger persons below 30 years (65 percent) do not have any difficulty with self-care. The proportion is about 19 percent among the oldest group (70-79 years). Overall, 58 percent do not have any difficulty in maintaining their general appearance, but about 10 percent reported severe to extreme difficulty. More females, elderly persons, illiterates and rural residents have difficulty in maintaining general appearances.

xix



Over two-fifths of the respondents (41 percent) have no difficulty in concentration or remembering things but 16 percent have severe to extreme difficulty.



The proportion without any difficulty in concentration or remembering things is 38 percent among females compared to 45 percent among males. Similarly, more of urban residents have no such difficulty (52 percent) than rural residents (39 percent).



Forty-six percent of the respondents have no difficulty in learning a new task but 15 percent reported severe to moderate difficulty.



Fifty-one percent of males compared to 40 percent of females reported no difficulty in learning a new task. The proportion with no such difficulty decreases with age and it is only five percent in the oldest age group (over 80 years).

Interpersonal activities



Individual respondent’s ability to deal with interpersonal relationship was assessed by two questions. First, the extent of active roles played by respondents in maintaining personal relationships or in community activities, and secondly, an assessment was made to know whether the respondents have any difficulty in dealing with conflicts and tensions.

Sixty-two percent do not have any difficulty in seeing or recognizing a person across the road whereas 14 percent reported severe to extreme difficulty.



Persons reporting such difficulty are more among the elderly persons, females and urban residents. Such vision problems were reported by over twofifths of females (44 percent) and 18 percent have severe to extreme difficulty. Severe to extreme difficulty in seeing is as high as 42 percent among elder persons over 80 years.



A similar pattern found with difficulty in seeing an object at arm’s length or reading. About 66 percent do not have any such difficulty and the proportion reporting severe to extreme difficulty is 10 percent.



Severe to extreme difficulty in seeing an object at arm’s length is more pronounced among females (11 percent) than males (eight percent) and among rural by about twice (15 percent) than urban residents (eight percent).









Fifty-four percent do not have any difficulty in personal relationships or participating in the community level activities, while 14 percent reported severe to extreme difficulty. Half the female respondents, 52 percent of rural residents, one-fifth of ages over 80 years and 44 percent of those with no formal education have no difficulty in personal or community level activities. The proportion having no such difficulty is much greater among males (59 percent), urban residents (64 percent), younger age groups (65 percent) and those with over 11 years of schooling (69 percent). In the case of dealing with situations involving conflicts and tensions, 49 percent do not have any difficulty and about 16 percent reported severe to extreme difficulty in dealing with conflicts and tensions.

Sleep and energy Information was collected in the health state module to know how much difficulty the respondents have with sleep such as inability to fall asleep, interrupted sleep or waking up too early in the morning than a person would usually wake up in the last 30 days. Also, an assessment was made to know whether the respondents are feeling tired or having less energy.

Visible differences are found between men and women, by residence age and educational status in dealing with conflicts and tensions. About 42 percent women compared to 56 percent of men, 54 percent in urban against 48 percent in rural areas, 57 percent among younger persons (18-29 years) compared to 20 percent among the oldest ages (over 80 years) and 39 percent among the illiterates compared to 64 percent among those who have over 11 years of schooling have no such difficulty.



Over half the respondents (55 percent) reported difficulty with sleeping and 16 percent have severe to extreme difficulty associated with sleep.



Problem with sleep is more among the elderly persons (41 percent of ages 70-79), females (about 20 percent) and rural residents (17 percent).

Vision



The overall difficulty in vision is assessed by asking (a) whether any difficulty in seeing and recognizing a person across the road and (b) the extent of difficulty in seeing and recognising an object at arm’s length or in reading in the last 30 days.

Regarding feeling rested and refreshed, only 45 percent reported no such problem and 14 percent have severe to extreme problems.



The problem with feeling rested and refreshed is more common among females (59 percent), rural respondents (58 percent) and elderly persons.

xx

Affect

Self-assessed need for health care

The case of affect asked to respondents in the health state module pertains to the extent of feeling sad/ depression and worry/anxiety.

Respondents who assessed the need for self health care are classified as those who need health care services during the 1) past 12 month, 2) 1-5 years, 3) more than 5 years and 4) those who did not need heath care at the time of the survey.



Substantial proportion of respondents (69 percent) reported feeling sad, low or depressed and 16 percent have severe to extreme levels of such problem.



The feeling of depression/sadness is more among females (68 percent), rural residents (66 percent) and the elderly persons (79 percent).



Problem related to worry or anxiety is also quite pronounced in the state. Only 31 percent do not have any problem and 22 percent reported severe to extreme levels of worry or anxiety. This problem is reported by both sexes but is much higher among females (72 percent), less educated (75 percent) and rural residents (71 percent).



Over 70 percent of respondents needed health for themselves or for their children in the last 12 months. Of this reported need, 59 percent was for self health care and 13 percent for their children.



Between 1 and 5 years before the survey, 16 percent was for self health care and one percent for their children’s health care. More than five years back, the proportion for self care was about three percent and very little for child care. Close to eight percent did not need any heath care.



Over the years, no significant difference was found in need for health care among the adults of both the sexes and also for the children. But a little higher need for health care was reported for adult females and boys, especially in the past one year.



In the last 12 months, about 61 percent of females needed health care compared to about 58 percent among the males. During the same period, girls needed more health care (14 percent) compared to 12 percent boys.



In the past five years, more males needed health care than females among both adults and children. The proportion that did not need health care is more among the males (nine percent) than among the females (six percent).



Health care need differs by residence and age for both males and females. For instance, the health care need for younger adults (18-29 years) is over three times higher than that of the children but at the older ages, say 70+ years, need for health care is concentrated among the older persons than the children.



The need for health care increases with age, whereas the need for their children’s health declines with age which indicates improvement in children’s health over the years.

5. SELF-ASSESSED NEED FOR HEALTH CARE AND RESPONSIVENESS The health system responsiveness covers eight domains that vary from context to context. For example, the quality of health care system and its response to patients need may improve utilisation patterns, and thereby directly affect health outcomes. On the other hand, being responsive to citizens by providing them with timely information (e.g. about disease outbreaks) may contribute the public’s trust in health care system and their willingness to pay taxes to fund it. Institutions in health sector, whether they are in private or public sector, aims to improve the health status of the population. The response of these institutions towards the requirement of health needs can be defined as health system responsiveness. It is the people’s experience of their interactions in health system on a set of domains that are important to them. The WHO has identified eight major domains of health system responsiveness such as autonomy, confidentiality, communication, dignity, prompt attention, access to support, quality of basic amenities, and choice of health care provider and institutions. The responsiveness of health system is measured by the ability of the health system to meet the health requirement of its population.

xxi

Self-assessed need for inpatient care in the previous 5 years •

About 85 percent of the respondents need inpatient services for acute diseases such as high fever, diarrhoea, cough, including dental care and minor surgery. About one percent needed care for non-communicable (chronic) diseases, nine percent for child health and about five percent for maternal health.



A substantial proportion of both males (87 percent) and females (82 percent) needed care for acute diseases.



The reported need for child health inpatient care is higher for male children (11 percent) compared to female children (eight percent).



A higher proportion of males needed inpatient health care for non-communicable diseases (two percent) compared to females (one percent). About nine percent of female respondents require inpatient maternal health services.



Rural-urban difference in self-assessed need for inpatient care is negligible, except for chronic diseases. About 83 percent of rural and 85 percent of urban respondents have a self-assessed need for inpatient care due to acute diseases. About five percent urban compared to one percent rural respondents have a selfassessed need for inpatient care for chronic diseases.



(11 percent). About six percent of female respondents require outpatient maternal health services. •

A significant rural-urban difference prevails in terms self-assessed outpatient care requirements. About 78 percent of rural and 74 percent of urban respondents have a self-assessed need for outpatient care due to acute diseases. About 17 percent urban compared to 11 percent rural respondents have a self-assessed need for outpatient treatment care for non-communicable diseases.



The self assessed need for child health is higher among the respondents in the ages 30-44 years than any other age group and the proportion declines in the older ages. On the other hand, while the self assessed need for outpatient care in terms of acute decreases at higher ages, for non-communicable diseases it increases at the higher ages compared to younger ages.

Responsiveness for inpatient treatment •

Overall, the domains of responsiveness for inpatient care score 52, but a wide variation was found for each attribute across sub-populations.



The most important attribute of responsiveness is dignity (respectful treatment), with 73 followed by communication (59), confidentiality (55) and autonomy (52). Attributes with lower ratings of responsiveness are prompt attention (37), basic amenities (42), and choice (49).



A substantial proportion of males and females give dignity the highest rating in health care (over 70), more so by the males (75). The other important ones mentioned by males are communication (59) and autonomy (53). For females, dignity is followed by communication (60) and confidentiality (58). Both males and females gave lower ratings to prompt attention, basic amenities and choice.



Rural-urban difference is quite visible in the ratings of these domains. The overall importance assigned to these attributes of care is the lowest by the rural respondents (49) compared to 66 by the urban respondents.



In the urban areas, dignity received the highest rating (82), followed by communication (78) and autonomy

The self assessed need for child health is higher among the respondents in the ages 30-44 years than any other age group and the proportion declines in the older ages.

Self-assessed need for outpatient care in the previous 5 years •

About 77 percent of the respondents need outpatient services for acute diseases such as high fever, diarrhoea, cough, including dental care and minor surgery. About 12 percent needed care for non-communicable diseases, eight percent for child health and three percent for maternal health.



A substantial proportion of both males (78 percent) and females (76 percent) needed care for acute diseases.



The reported need for child health outpatient care is about two times higher for male children (11 percent) compared to female children (six percent).



More females needed outpatient health care for noncommunicable diseases (13 percent) compared to males

xxii

who use private facility (86), the insured persons (85), those educated above high school level (81) and urban residents (79).

(71). The lowest rating is assigned to prompt attention (34) and basic amenities (58). •

To the rural residents, dignity (71) has the highest rating followed by communication (55) and confidentiality (54). Those assigned low scores are prompt attention (34), basic amenities (38), choice (45) and autonomy (47).



Across all sub-populations and categories, the three domains rated highly are dignity, communication and confidentiality. Dignity receives the highest rating and basic amenities the lowest.



The pattern differs when considering residence, educational status, insurance and governance. The level of importance assigned to the three frequently mentioned domains of responsiveness (dignity, communication and confidentiality) showed a wide gap between the illiterates and those with high school or above education. The illiterates are less likely to acknowledge their importance in health care (60) compared to the educated persons (81). A sharp contrast in rating given to the domains was found between urban (80) and rural residents (62) and among insured (85) and uninsured persons (64 points). Also, those who had utilised the government facility rate basic amenities and confidentiality more highly than any other services.



Illiterates and those educated up to secondary level gave high ratings to dignity and communication. However, among respondents with high school and above education, communication gets the highest rating (87), followed by dignity (84) and autonomy (83).



It is evident that education has an impact in an assessment of the responsiveness factors. In all the attributes mentioned, the educated persons have assigned higher scores for each, compared to the illiterates. The overall score is as high as 71 points by those respondents with high school and above education, against the score of 50 points by the illiterates.



Considering general health, major health conditions and governance, it is found that dignity (respectful treatment) is given the top score. Those who assigned high score to dignity are persons with chronic diseases (96), worse health condition (74), and those treated in private facility (92).

6. HEALTH EXPENDITURE, INSURANCE AND HUMAN RESOURCES



Household health expenditure

Responsiveness for outpatient treatment

Besides the main sources of household expenditures in last one year, information on other expenditure on health was also collected related to payments for different health services such as treatment cost, drugs, and overall expenditure in the last one-month.



For respondents in West Bengal who had sought outpatient care, the most important domain of responsiveness is dignity/respectful treatment (79), followed by communication (76), confidentiality (68) and choice (64). The one attribute considered low in importance is basic amenities (49).





Overall, it is clearly indicated that compared to those adults who had received inpatient cares, those who sought outpatient cares attached higher ratings to each of the seven domains of responsiveness.

Over four-fifths (84 percent) of payments for health expenditures come from current income, 22 percent from borrowed money, 14 percent from outside sources, 12 percent from savings, and eight percent respondents sold their household items for such payments. Insurance accounted for one percent of payment of health expenses.



Higher the health spending, greater is the share of contribution from current income (over 90 percent) and borrowed money.



Monthly health spending of a household on average is Rs.138. This includes spending on inpatient and





Overall, those who had chronic diseases, insurance, highly educated and utilised private facility gave higher ratings to each domain of health system responsiveness.

Generally, ratings assigned to the domains of responsiveness is found to be very high among those

xxiii

outpatient care, utilisation of traditional practitioners and purchase of drugs. Expenditure on outpatient treatment amounts to Rs.30, compared to Rs.2 for inpatient services. •

health related occupation such as physicians, nursing and midwifery professionals and the other health related and support occupations. •

Over four percent work in health and other related professions. A majority of them are in nursing and midwifery followed by other support services. There are about 11 physicians per 100,000 population and 20 persons in nursing and midwifery and 105 persons in health related support staff.



There are more females (510 per 100,000) than males in the health related professions. Likewise, most the urban areas have more of persons engaged in health services compared to rural areas. Majority of those engaged in health professions are below 35 years and over 55 years. Similarly, a majority of them have educational level of secondary or college/university.



A majority of physicians are male (very less number of females returned from the survey) and are found more in urban areas. They are mostly above 55 years and in the highest income quintile. In case of nursing and midwifery, majority are females (394/100000) and more concentration is in the urban areas (460/100000). Most of them are in the age group 18-34 years, belonging to third and fifth income quintiles and also highly educated (with university degree).



Age pattern indicates that a majority of the physicians are in age group of 55 and above. In contrast, over half of those in nursing and midwifery (58 percent) and other health/support occupations (53 percent) are below 35 years.



About 74 percent health professionals were working last year and mostly in the public health facility (45 percent), followed by private facility (36 percent). Interestingly, over 70 percent are working in health education/research services. However, about 22 percent in nursing/ midwifery and 32 percent in other health related/ support professions were not working in the last 12 months.



Only 50 percent of physicians work in public facility and all the physicians were reported to be working in the past one year.

Maximum spending is on purchase of drugs (Rs.71). The expenditure on drugs does not vary much among different income groups. Although a lesser amount is spent by the lowest income groups the amount accounts for about 58 percent of their total health spending.

Catastrophic spending on health (>40 percent) •

About 10 percent of households incurred catastrophic spending on health and the average catastrophic expenditure amounts to Rs.224.



Among the households that had catastrophic spending, drugs and outpatient fees account for two-thirds of the total spending and 21 percent for other expenses.

Out of pocket expenditure (OOP) •

In West Bengal, in over three-fifths (61 percent) of the households the share of household expenditure for out of pocket capacity to pay (OOPCTP) for health is less than 10 percent, compared to six percent of households whose household capacity to pay exceeded 40 percent and constitutes catastrophic health payments.



In 14 percent of households, the out of pocket capacity to pay ranges between 20 and 40 percent.



The highest share of out of pocket health payment is for drugs (61 percent), followed by payments for outpatient treatment (32 percent) and 12 percent spent on others.

Insurance •

About 95 percent individuals in the sample have no insurance and few persons who are insured have voluntary insurance. More insured persons are from urban areas.

7. HEALTH RESOURCES/OCCUPATION In the survey, information was collected about the number of trained health professionals in the household. A question was asked to each individual if they were trained in any

xxiv

Chapter 1

Introduction

1.1 HEALTH SYSTEM PERFORMANCE IN INDIA Health systems deserve the highest priority in the endeavour to improve the health of the people as they provide the critical inference between life saving and life enhancing interventions and the people who need them (Sankar and Kathuria, 2004). The World Health Organisation (2000) made an attempt to measure the efficiency of health systems in 191 countries across the globe using five performance indicators and found that regions vary enormously in their levels of development in health outcomes, at times, in spite of similar levels of income and educational attainment. An assessment of the health system performance in India in terms of health outcome indicators shows tremendous improvement in the last 50 years. Life expectancy has risen from 36 years in 1951 to 62.1 years in 19952000 (United Nations, 2003). Infant mortality has been halved from 146 in 1951 to 66 in 2001. Crude death rate has been reduced from 26.1 in 1970 to 8.4 in 2001 (Sample Registration System, 2003). The factors contributing to such vast improvements in health have been the three tier system of community health centres, primary health centres and primary health sub-centres, countrywide immunization drives and improvements in determinants such as water supply, sanitation and socio-economic conditions. However, this achievement has been very meagre compared to our health policy goals. More importantly, very slow progress is seen in the 1990s in health status improvement, as several of the above indicators show plateauing. Moreover, the improvement in health status has been very uneven across the country, where states such as Kerala have

health indicators comparable with the middle-income countries and other states such as Uttar Pradesh, Madhya Pradesh and Orissa are at the lower end levels comparable to Sub-Saharan Africa. It is therefore necessary to understand the potential for health system improvements in the states. Health system performance needs to be assessed not only by the health sector endowments but also by its efficient use. 1.2 SHARE OF PUBLIC AND PRIVATE FACILITIES IN HEALTH CARE In India, the public sector plays an important role in the rural health delivery system. In urban area the public and private health systems complement each other. Rural health system performance determines the overall health outcome of the states. Thus, the performance of public health system is of great significance in rural areas. In India, patients from both rural and urban areas overwhelmingly choose public facilities (Government hospitals, Community Health Centres and Primary Health Centres) for inpatient care. The reliance on public hospitals for inpatient care is greater in hilly and backward states, among scheduled castes and tribes and those belonging to the lower monthly per capita expenditure quintile. Total health expenditure was 5.3 percent of the Gross Domestic Product (GDP) of India in 1997 and 5.1 percent in 2001. This indicates a decline in the proportion of health expenditure as a percent of GDP. Private health expenditure as a percent of total expenditure on health was 84 percent in 1997 and 82 percent in 2001. On average, a household spends Rs. 250 per capita per

Introduction

1

annum on health services. This health expenditure is 40 percent higher in urban households than in rural households. The health expenditure is also positively related to overall household expenditure (NCAER, 1993). Private health spending in India is one of the highest in the world and indicates an inefficient way of financing healthcare that leaves people highly vulnerable. Government expenditure on health as a proportion of total government expenditure was 3.2 percent in 1997 and 3.1 percent in 2001. Table 1.1 presents the trends in health expenditure in India under different domains. Private facilities are used largely in urban India. However, private practitioners are well spread and found even in remote and backward areas, and they are usually contacted for day to day health care needs before availing distantly located public facilities. In the public sector, 70 percent of hospitals and 85 percent of hospital beds are located in urban areas. These facilities are used more often in cases of severe and catastrophic illness, which the private practitioners are reluctant to handle. The growth of corporate hospitals has taken place because of the development of a health care market in which investment in state-of-the-art medical technology can yield a good return. Although the private sector accounts for a significant portion of the health system facilities, human resources and expenditure in India, no adequate mechanism has been developed for monitoring and regulating the private health sector. There is a need to generate a systematic information database through an effective interface between

nursing homes and the local supervising authority to collect data on disease patterns for taking policy decisions on public health matters. In most countries health sector reform involves a change in the respective shares of tax revenue, social or private insurance, user fees and external aid in financing the health sector. Also, the range of services provided in the public and private sector tend to differ. A shift takes place in the role that the state plays in the regulation and provision of health care services and the development of various types of public-private partnerships. Decentralisation, integration of services, including sector-wide approaches and reforms in logistics occur. The reform process is also affected by the geopolitical context in which a health system is embedded. This includes the bargaining position of the country in the international setting, the level of external debt and financial stability of the country and the impact of the past political structure on the health care system. 1.3

HEALTH SYSTEM GOALS

The main goals of the health system in India are health responsiveness and fairness in financing. The health of the population should reflect the health of individuals throughout the life course and include prevention of both premature mortality and non-fatal health outcomes as key components. Responsiveness has two key sub-components: respect of persons and client orientation (WHO, 2002). Respect of persons involves the elements of dignity, autonomy and confidentiality and captures aspects of the interaction of individuals with the health system that often have an important ethical dimension.

Table 1.1 Trends in health expenditure in India, 1997-2001 Health Expenditure/Year Total expenditure on health (as a percent of GDP) General government expenditure on health (as a percent of total expenditure on health) Private expenditure on health (as a percent of total expenditure on health) General government expenditure on health (as a percent of total government expenditure) External resources for health (as a percent of total expenditure on health) Out of pocket expenditure (as a percent of private expenditure on health) Source : World Health Report, 2003

2

Health System Performance Assessment

1997

1998

1999

2000

2001

5.3 15.7

5.0 18.4

5.2 17.9

5.1 17.6

5.1 17.9

84.3

81.6

82.1

82.4

82.1

3.2

3.5

3.3

3.1

3.1

2.3 100

2.4 100

2.2 100

2.2 100

0.4 100

Client orientation includes prompt attention to health needs, basic amenities of health services such as clean waiting rooms or adequate beds and food in hospitals, access to social support networks for individuals receiving care and choice of institution and individual providing care. There are also cross-system goals to evaluate how much the health system helps or hinders education, democratic participation, economic production etc. One of the more important cross-system goals that should be emphasised is the contribution of the health system to economic production and social aspects like education. 1.4

NEW HEALTH POLICY IN INDIA

The National Health Policy (2002) of India noted that improvement in health status in terms of indicators such as infant mortality rate, morbidity prevalence and life expectancy has been very uneven across the rural-urban areas. Also the statistics reveal wide differences between the attainments of health goals in the better performing states (Kerala, Maharashtra, Tamil Nadu) compared to the lowperforming states (Rajasthan, Uttar Pradesh, Orissa, Bihar, Madhya Pradesh). However, the national average of health indices hides the wide disparities in public health. Given a situation in which the national averages in respect of most indices are themselves at unacceptably low levels, the wide inter-state disparities imply that for vulnerable

sections of society in several states, access to public health services is nominal and health standards are grossly inadequate. There is also a big divide with respect to health care access between the poor and the rich and by many indicators of socio economic development. In the wider context of health system goals, a new National Health Policy was formulated in 2002 to cater to the changes in determinant factors relating to the health sector since the National Health Policy of 1983. The old health policy was revised and restructured based on the United Nations Millennium Development Goals. The main objective of the National Health Policy 2002 is to achieve an acceptable standard of good health amongst the general population of the country. The approach would be to increase access to the decentralised public health system by establishing new infrastructure in the existing institutions. A comprehensive evidence base is an important input for effective health policy interventions. The lack of evidence base from routine health information system is a common limitation in many developing countries including India. Given this background, the World Health Survey intends to provide evidence on the health status of Indian population. 1.5

HEALTH-RELATED SURVEYS IN INDIA

In India, the Census and Sample Registration System (SRS) provide reliable data on several social-economic

The new National Health Policy (2002) has specified the following goals: GOALS • • • • • • • • • • • • • •

YEAR

Eradicate Polio and Yaws. Eliminate Leprosy. Eliminate Kala Azar. Eliminate Lymphatic Filariasis. Achieve zero level growth of HIV/AIDS. Reduce mortality by 50 percent on account of TB, malaria and other vector and water borne diseases. Reduce prevalence of blindness to 0.5 percent. Reduce IMR to 30/1000 and MMR to 100/lakh. Increase utilisation of public health facilities from current level of 75 percent. Establish an integrated system of Surveillance, National health accounts and Health Statistics. Increase health expenditure by government as a percent of GDP from the existing 0.9 percent to 2.0 percent. Increase share of central grants to constitute at least 25 percent of total health spending. Increase state sector health spending from 5.5 percent to 7 percent of the budget. Further increase state sector health spending to 8 percent of the budget.

2005 2005 2010 2015 2007 2010 2010 2010 2010 2005 2010 2010 2005 2010

Source : National Health Policy, 2002, New Delhi, Government of India.

Introduction

3

and demographic aspects of the population. However, very little information is available on population health, morbidity and health system performance indicators. In view of lack of routine health information, organisations such as the National Sample Survey Organisation (NSSO) and the National Council of Applied Economic Research (NCAER) undertook surveys on morbidity and health care. The NSSO survey gathered information on physical and mental disability, morbidity, maternal and child health, utilisation of medical services, medical expenditure on different treatments and injuries in different rounds of the health and morbidity survey. Micro and macro level information on medical care, health care needs of population in different states were assessed in NCAER survey. More recent are the National Family Health Survey (NFHS) and Rapid Household Survey (RCH-RHS). The two rounds of NFHS (1992-93; 1998-99) focus on the women in the ages 15-44 and provide availability of information on the use of family planning methods, infant and child mortality, immunisation, morbidity pattern including the prevalence of diarrhoea, malaria, leprosy, physical handicap, nutritional status of women and children, maternal and child health and quality of care. The RCH surveys are designed to provide data at the district level on maternal and child health and various health infrastructure facilities covering primary health sub-centres, primary health centres (PHC), community health centres (CHC), first referral units (FRU) and hospitals (RCH, 1997-98; 2001-02). In a nutshell, all these survey are focussed on variety of demographic indicators, general morbidity prevalence rates and maternal and child health indicators. The NSSO although focuses on morbidity prevalence, it is not sufficient to assess the health system performance of a country. 1.6 THE WORLD HEALTH SURVEY (WHS) 2003 The World Health Survey is a multi-country survey program with the primary objective of collecting good quality baseline information on health outcomes in a population as a result of investment in health systems.

4

Health System Performance Assessment

The broad objectives of the survey programme are: 1) To provide low cost information that would supplement the information provided by the health information systems of a country, and 2) To develop the capacity of policy makers to monitor the performance of the health system. The survey has adopted a modular approach with the survey instrument divided into separate modules for various health and mortality components. The modules cover the following important aspects of health at the household and individual levels e.g. health expenditure, socio demographics, health states of population, risk factors, mortality, morbidity prevalence, health system responsiveness for inpatient and outpatient care and social capital. An eventual outcome of the survey is to assess health status of the population using the following three summary measures (a) Disability adjusted life years (DALY), (b) Disability adjusted life expectancy (DALE) and care (e.g. Child survival) and (c) Equality in health. In the past, health status assessment concentrated on morbidity and mortality statistics along with the incidence and prevalence of communicable diseases. Now, with the epidemiological transition from communicable to non - communicable diseases, measuring chronic diseases and injuries that are non fatal has become more relevant in understanding the health status of populations (World Health Report, 2002). In India, the survey covered a representative sample of 10750 households in six states namely Assam, Karnataka, Maharashtra, Rajasthan, Uttar Pradesh and West Bengal. In West Bengal, the survey covered a representative sample of 1998 households. This database gathered on West Bengal is to be used to create a state health policy to ensure better monitoring of health status of the population, responsiveness of the health system and measurement of health related parameters. This is also an attempt to understand how people perceive and report their health status and measure the performance of the health system. A comparative profile of health status

and socio economic conditions in India and West Bengal are provided as a background for presenting the health system assessment survey findings.

of any method is nearly 67 percent and of any modern method is 47 percent. 1.8.

1.7 SOCIO-DEMOGRAPHIC PROFILE OF WEST BENGAL Table 1.2 presents the socio-demographic profile of the state. West Bengal has an area of 88752 km 2 and comprises 18 districts. The total population is approximately eight per cent of the countr y’s population. The density of population is 904 individuals per sq. km. The sex ratio in the state is 934 females per 1000 males. The state is still predominantly rural with only 28 percent of its population residing in urban areas. Seventy-six per cent of the households are Hindu, while the percentage of Muslim households is 22 percent. The literacy rate is 69.2 percent. Males have a higher rate of 78 percent compared with 60 percent for females, which reflects gender disparity (Census 2001). The median age at marriage among women ages 20-49 is 17 years and the median age at first birth is 19 years (NFHS-2). The TFR is 2.3 and the mean ideal number of children is 2 children. The contraceptive prevalence rate (CPR) is about 34 percent as compared to the national figure of 45.4. The current contraceptive use

HEALTH PROFILE OF WEST BENGAL

Table 1.3 provides data on selected health status, including maternal and child health and health infrastructure for India and West Bengal. The male life expectancy at birth at 64.5 years is much higher than the national figure of 62.4 years. The same holds true for female life expectancy at birth of 67.2 years as against 63.4 years for the country’s population. In a span of 6 years, the infant mortality rate has declined to 49 per 1000 live births (1992-93 to 199899). The under-5 mortality rate is relatively high at 68 per 1000. In the case of maternal and child health, West Bengal shows a situation better than the national level. Ninety percent of women received at least one antenatal care (ANC). About 82 percent of the mothers reported receiving two doses of tetanus toxoid vaccine. Despite the low infant mortality, the level of immunisation is still low, about 44 percent of the children received all vaccinations (BCG, measles and 3 doses each of DPT and polio vaccines). Also, while 42 percent of the deliveries at the all India level were conducted in medical institutions, in West Bengal it is about 40 percent. About 44 percent of deliveries were assisted by health professionals compared to 42 percent for all-India (NFHS-

Table 1.2 Selected socio-demographic indicators for India and West Bengal Socio-demographic indicators Population 1(2001) Annual Population growth rate1 (1991-2001) Density of Population per sq. Km1 (2001) Percent Tribal Population Percent Urban1 (2001) Sex Ratio1 (Females per 1000 males) Literacy Rate1 (2001)

Crude Birth Rate1 (per 1000) Total Fertility Rate2 (15 – 49) (per woman) Contraceptive Prevalence Rate2 (percent)

Total Male Female

India

West Bengal

1,027,015,247 1.93 324 8.2 27.78 933 64.8 75.3 53.7 25.9 2.9 45.4

80,221,171 1.64 904 28.03 934 69.2 77.6 60.2 20.8 2.3 33.8

Sources : 1. Census of India 2001, Primary Census Abstract (New Delhi: Office of the Register General and Census Commissioner). 2. International Institute for Population Sciences (IIPS) and ORC Macro. 2000, National Family Health Survey (NFHS- 2), 1998-99 (IIPS, Mumbai).

Introduction

5

Table 1.3 Selected health status and health infrastructure indicators for India and West Bengal Health status and health infrastructure indicators Crude Death Rate1 Child Mortality Rate1 Infant Mortality Rate1 Under 5 mortality rate1 Life Expectancy at Birth3 (1996–2001)

Males Females

Percent of women who received ante natal care (ANC)1 Percent of mothers who received 2 doses of tetanus toxoid vaccine1 Percent of births delivered in medical institution1 Percent of deliveries assisted by health professionals1 Percent of children fully immunized1 Hospital Beds per lakh population2 Number of allopathic doctors registered under Indian Medical Council (IMC) and with State Medical Council2 Number of allopathic Hospitals2 Number of Dispensaries4

India

West Bengal

9.7 29.3 67.6 94.9 62.4 63.4 65.4 66.8 33.6 42.3 42.0 67

8.3 19.9 48.7 67.6 64.5 67.2 90.0 82.4 40.1 44.2 43.8 69

605840 15393* —

50794 411 551

Sources : 1. International Institute for Population Sciences (IIPS) and ORC Macro, 2000, National Family Health Survey-2 (NFHS-2), 1998-99 (IIPS, Mumbai). 2. Health Information of India (2002). 3. Sample Registration System (2003). 4. Family Welfare Yearbook (1998), Ministry of Health and Family Welfare. * The total number of hospitals reduced from 2001 due to exclusion of Community Health Centres and non-reporting.

2). In 1998, the state has over 47000 recognised medical practitioners and 399 hospitals. By 2002, West Bengal has 50794 allopathic doctors who are registered under Indian Medical Council (IMC), 42031 general nursing and midwives, and 11078 health visitors and supervisors.

6

Health System Performance Assessment

The number of doctors per 100,000 populations is about 63, which is higher than the all-India level of 59 doctors. The number of hospitals (public) has also increased to 411, equipped with 55,279 hospital beds (Health Information of India, 2002).

Chapter 2

Methodology

2.1

NATIONAL SAMPLING

A target sample of 10,000 households was planned for the WHS in India. Since it was decided to focus the survey at the state level, six states namely Assam, Karnataka, Maharashtra, Rajasthan, Uttar Pradesh and West Bengal were selected based on both development indicators and geography. The selection of states was done considering their geographic location and the level of development. All the states with a population five million and above except Jammu and Kashmir) of India were sub divided into six region as north, central, east, north east, west and south. The level of development was measured considering four indicators, namely, infant mortality rate, female literacy rate, percentage of safe delivery and per capita income. All these indicators have wide socio-economic implications. For instance, infant mortality rate is a good barometer of a country’s level of development in terms of mortality and health transition. Female literacy rate is an important determinant of fertility and mother’s utilization of different health care

services and is also a proxy for whether her family utilises the available health care services. Percentage of safe deliveries indicates the extent of maternal morbidity and utilization of health care services. Per capita income indicates economic development. A composite index of the level of development was computed by giving equal weights to the above four indicators. The states were classified into six levels (in decreasing order) of development based on the composite index shown in table 2.1. The states were selected purposively in such a manner that one state is selected from each region as well as from each level of development category. The state of West Bengal is in the east and also represents the third level of development category. The other five states ranked according to level of development are Assam (North east), Karnataka (south), Maharashtra (west), Rajasthan (north) and Uttar Pradesh (central). Allocation of households among six states was done comparing their population size and the fact that we need

Table 2.1 Classification of states by region and levels of development Region I North

II Punjab

Central East North East West South

Maharashtra Gujarat Kerala, Karnataka Tamilnadu Note: States in bold were selected for the survey.

States by level of development* III IV Himachal Pradesh, Uttaranchal West Bengal

Haryana

V

VI

Rajasthan

Madhya Pradesh Chhattisgarh Bihar

Uttar Pradesh Orissa, Jharkhand

Assam Andhra Pradesh

Methodology

7

to have separate estimates for each of them. The households to be selected in a state were distributed among its rural and urban areas in proportion to their state population. 2. 2 SAMPLING FOR WEST BENGAL In West Bengal, the target sample size was 1840 households, which is distributed accordingly based on the urban-rural proportion. The total primary sampling units (PSU) covered in West Bengal was 70 PSUs, 52 in rural and 18 in urban areas. A sample of 25 households in each rural PSU and 30 households in each urban PSU were covered. However, experiences from large-scale surveys prompted the need to over sample by at least 10 percent to cover non-responses. Besides, 10 percent of total sample were again selected and these PSUs were revisited for a retest. Ultimately, the total number of households covered in West Bengal stood at 1925 households and re-test done in 184 households. Sampling for Rural Areas A two stage stratified sampling design was used for the selection of the households in rural areas. The villages or group of villages (in case of small linked villages) were considered as the primary sampling units. For West Bengal, the target sample size for the rural areas was 1300 households. It was decided that 25 households would be covered in each selected PSU, which resulted in the selection of 52 PSUs in the state. The selection of villages was done by the probability proportional to size method (PPS). The village size was obtained from 1991 census, later reconfirmed with 2001 census village directory. Before selection, villages were stratified on the basis of geographic region and village size. The 18 districts of West Bengal (1991 Census) were classified into six contiguous regions as follows: Region I

Jalpaiguri, Darjeeling

Region II

Koch Bihar, West Dinajpur (comprising of Uttar Dinajpur and Dakshin Dinajpur), Maldah, Murshidabad

Region III

Nadia, Howrah, Hugli, North Twenty-four Parganas, South twentyfour Parganas, Bardhaman

Region IV

Medinipur, Banhura, Birbhum

Region V

Puruliya

8

Health System Performance Assessment

In each region, villages were further classified by their size and categorised as follows: (a) less than 250 households, (b) between 250 and 500 households, and (c) more than 500 households. The level of female literacy was finally used for implicit stratification. This meant that villages within each stratum were ordered according to the level of female literacy. Villages having less than five households were deleted from the list, and those of size between five and 50 were linked with nearby villages to form a PSU. Fifty-two PSUs were selected systematically from the list using probability proportional to size. For each selected PSU, the name, location and household size were considered based on 2001 Census. Considering the non-response rate, a uniform number of 28 households were selected from each selected PSU systematically. The total number of households covered in the rural areas of West Bengal was 1456 households. Sampling for Urban Areas In the urban areas, a three-stage sample design was used with the selection of wards, census enumeration blocks and households in that order. All the urban wards in the state were arranged according to the size of the city/town and geographic region. The cities/towns were classified on the basis of their population, using the 1991 census. The following four classes were considered. •

Group 1: Cities with population more than 1 million



Group 2: Towns with population between 2 to 10 lakhs



Group 3: Towns with population between 50,000 and 2lakhs



Group 4: Towns with population less than 50,000.

The census enumeration block (CEB) was taken as PSU in the urban areas. It was decided that 30 households (plus three for non-response) would be covered in each selected PSU, which resulted in the selection of nine wards and 2 PSUs from each ward, i.e. 18 PSU (CEBs) in the state. Two census enumeration blocks (as per 2001 census) were selected from each selected ward based on the probability proportional to size. The total number of households covered in the urban areas of West Bengal was 594 households.

Selection of households and individuals From each PSU a fixed number of 25 (+3) households in rural areas and 30 (+3) households in urban areas were selected. In each household a general information table was filled for all adult members, segregated by sex. A key informant of the household answered all queries about himself (or herself ), and about the family members and the household questionnaire. From the household list of all adults (18+ years), an adult member of the household was randomly selected using KISH tables for canvassing/answering the individual questionnaire modules. The KISH table is a statistical tool to facilitate randomness while selecting one adult member per family, to avoid taking the head of the family each time as the respondent. A total sample of 2050 households and 1925 adult individuals 18+ were covered in West Bengal. The pooled sample for India from six states is 10,279 households and 9994 adult respondents for the individual questionnaire. 2.3

QUESTIONNAIRE

The Survey was conducted with the face-to-face interview technique using two instruments provided by the WHO after extensive pre-testing and standardization. Household questionnaire The first part of the questionnaire pertains to the household. The first section called the coversheet is structured to collect data on sampling, geo-coding as well as contact and re-contact. The household roster lists all the residents in the selected household along with details about their relationship, age, education, marital status and whether the person had worked or been trained in a health related field. The roster is used to select respondents eligible for application of the individual questionnaire. The KISH tables are used to select one person from the list of those eligible. The second section contains the household consent form, data on malaria prevention and the use of bed nets, health insurance and community health insurance programs, permanent income indicators, household expenditure on food, housing, education and

health care expenditure. The final part of this questionnaire contains data on health occupations. Individual questionnaire The individual questionnaire uses the modular approach and is divided into nine sections. In the first module the individual consent is first obtained and questions about the respondent’s socio demographic characteristics are then asked. The second module is on health state descriptions where the respondent is asked to rate his physical and mental health. This section covers health states in terms of mobility, self-care, pain and discomfort, cognition, interpersonal activities, vision, sleep and energy and affect. This module also contains ten vignettes about health state descriptions. The next module pertaining to health state valuations contains two record sets, which are used in the specified manner. The first record set contains data on amputation, alcohol dependence, limited long distance vision, chronic pain and total blindness. After a series of fourteen questions, an ordinal ranking exercise is carried out where the respondents are asked to rank these health states from best to worst. The second record set contains questions on amputation, insomnia, arthritis, major depression and quadriplegia. A similar ranking exercise was also carried out. The fourth module contains questions related to risk factors such as consumption of tobacco and alcohol, nutrition, physical activity including both vigorous and moderate activity and environmental risk factors related to water, sanitation and the fuel used. The fifth module contains questions related to mortality. The first section in this module contains questions on birth history to assess infant and child mortality while the second section deals with an assessment of adult mortality including sibling survivorship and a verbal autopsy to assess cause of death. In the sixth module questions about coverage are asked. The first section deals with the diagnosis and treatment of chronic conditions such as arthritis, back pain, angina, asthma, depression, schizophrenia, diabetes, HIV/AIDS

Methodology

9

and tuberculosis. This section also contains an inventory of medicines and drugs. The next section in this module contains questions on cervical and breast cancer followed by questions on maternal health care. The section on child health includes questions on both preventive and curative care. This module also contains questions on reproductive and sexual health care, vision care, oral health care, and care for road traffic and other injuries. The seventh module deals with health system responsiveness. Starting with a general evaluation of health systems, the module covers areas such as the importance of health care, seeing health care providers, outpatient and care at home and inpatient hospital care. This module also has ten vignettes related to the questions. The eighth module contains questions on health goals and social capital and has an ordinal ranking exercise for health system goals. This module also has ten vignettes. The ninth and final module contains interviewer’s observations about health problems noticed during the course of the interview. Vignettes The responsiveness section of World Health Survey focused on the vignette linked questions for cross population comparability, which illustrate differences when making comparisons of measurements derived from self reports. The self-assessed experience of respondents across populations could vary due to differences in characteristics of the populations. The linkage to vignettes for these particular question means that individual’s response can be made comparable across both sub groups within countries and across counties. The responses on the health system performances by the respondents were ranked on an ordinal scale (very good1, good-2, moderate-3, bad-4, very bad-5). It provides the scale cardinal properties so that the differences between one and two and two and three for example, have the same meaning. This is an essential step to say whether the differences between “very good” (labelled five) and good (labelled four) are the same as the difference between “good” and “moderate” (labelled three). Secondly, the responses on each domain are rescaled from zero to 100, by setting all the responses equal to and

10

Health System Performance Assessment

better than the experience described in the best vignette to 100, and all responses described as equal to or worse than the experience in the worst vignette, to zero. Income quintile The quintiles used in this analysis reflect relative inequalities in income within each state. In this report, the income quintile is based on possession of 20 permanent income (assets) such as number of rooms in the house, chairs, tables, cars, electricity, bicycle, clock, bucket, washing machine for dishes, washing machine for clothes, refrigerator, telephone, mobile/cellular telephone, television, computer, moped/ scooter/motorcycle, livestock (cattle only), sewing machine, radio/transistor/tape-recorder and bullock cart. Quintile is a statistical division of sample households based on income (assets) distribution of the total sample into five equal parts. The variable takes on the values 1-5 with 1 being the quintile with the poorest households and 5 being the quintile with the richest households. The analysis comparing the bottom quintile to the top quintile within each data set will be reflecting those in relative poverty. The quintile division has been done for 10578 households for which income data was collected. Each quintile has an equal number of 2116 households. 2.4 GEOGRAPHIC INFORMATION SYSTEM (GIS) A new dimension of the WHS is the Geographic information, which is useful to analyse and display data related to positions of the clusters sampled for the survey. The location of each surveyed cluster was obtained with the highest precision using global positioning system (GPS) device. The latitude and longitude of every household surveyed were recorded. The readings were taken in degrees and decimal degrees up to five decimal points. This ensured that every household was distinctly located in the GIS. This data will be useful to digitally map the location of PSUs and households and for creating thematic maps and perform spatial analysis. Using the GIS device, the exact location of each sample unit is known. The distribution of all the selected sample units is presented in figure 1, indicating that the sample units are well spread all over the state.

2.5 TRAINING, DATA COLLECTION AND QUALITY ASSURANCE The training for the investigators and supervisors were conducted for eight days in March 2003 at the Economic Information Technology (EIT), Kolkata. All the investigators for the World Health Survey in West Bengal were graduates and have had previous experience in similar large-scale surveys. During the training programme the investigators were provided with the background, rationale of the study, techniques of interview and a thorough understanding of each question of the instrument. The roles and responsibilities of the investigators were explained in detail. The training sessions were conducted by the principal investigators, which include presentations and discussions by medical experts and WHO advisors. The training also contained video presentations and mock interviews. At the end of training, a pilot test and field training was organised for the investigators followed by an interactive sessions to discuss feedbacks from field training.

In West Bengal, three field teams, each comprising of one supervisor and four investigators completed the survey during March-May 2003. One principal investigator, two resource persons and a research team supervised the three field teams. Double entry of data in all the filled in questionnaires was done at the International Institute for Population Sciences, Mumbai. The World Health Organisation deputed a quality assurance advisor to monitor the progress of the survey in India in accordance with the recommended plans with respect to sampling, instrument, training of investigators, pilot test, retest and survey implementation. The advisor submitted an overall assessment to the WHO, stating that that WHS in India was progressing well. 2.6 FIELD EXPERIENCE INVESTIGATORS

OF

THE

The first reaction of the investigators when they saw the questionnaire was one of disbelief because most of them had never seen such a lengthy instrument before. However,

Figure 2.1: Distribution of primary sampling units (PSUs) in West Bengal, 2003 INDIA WHS 2003 Sampling Distribution West Bengal

Data Source: - Cluster Location : Collected with GPS devices during WHS 2003 - Administrative Boundaries : SALB Data set 2000

• Surveyed cluster Population 0-2 3-5 6-25 26-50 51-100 101-500 501-2500 2501-5000 5001-130000 Administrative Border

- Population figures : Extracted from Landscan database

the

Map Projection : UN – projected (Geographic) Reference System: WGS 84 datum Map created 14 October 2004

The boundaries and names shown and the designations used on this map do not imply the expression of any opinion whatsoever on the part of the World Health Organisation concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries Dotted lines on maps represent approximate border lines for which there may not yet be full agreement. @ WHO 2004. All rights reserved.

Methodology

11

through rigorous training with detailed explanations and examples, they grasped the content of the questionnaire at the end of the training programme. When the investigators were taken to the field for practice interviews, it was found that they frequently had to refer to the question-by-question manual provided by the WHO. Consequently, the interviews took longer than expected and fatigue set in by the end of the second interview. However, this stage was passed after a few interviews, and as the investigators became familiar with the questionnaire and the interview could be completed in the expected duration of about 90 minutes. Initial challenges of the investigators were to keep the respondents interested in the interview and to complete the interview in one session or in a subsequent session. A problem faced by the investigators was questions from those who were not selected in the sample. The investigators had to explain why everybody in the village could not be interviewed and how sampling was done. It was a policy of IIPS not to pay any monetary incentive to the respondents. This was beneficial, as otherwise individuals not selected would have demanded interview and payments. A practical problem was that of carrying the bundles of questionnaires from place to place. But this was overcome as each research team was provided with a vehicle throughout the survey. The overall response in West Bengal was very good, however, response in urban areas was slightly less enthusiastic than in rural areas. 2.7

LIMITATIONS OF THE DATA/STUDY

The information collected in World health Survey is self-reported by the respondents and therefore caution is needed when interpreting the data on morbidity and health state valuations. A few of this are mentioned below. 1. The data on morbidity prevalence depends on the extent of accuracy of respondents reporting. 2. The estimates relating to age-sex distributions, child and adult mortality may be affected by underreporting or by smaller number of cases.

12

Health System Performance Assessment

3. Indicators in this report although may be similar to those used in NFHS and NSSO not that the method of calculation might vary and therefore the estimates may vary. 4. The seasonal variations could affect the availability and thereby the intake of fruits and vegetables. The survey was carried out during the February to May. Also, observance of religious customs and practices could influence the intake of fruits and vegetables on particular days of intake. 5. No height measuring board and weighing scale were used for measuring height and weight. Height and weight data were collected only from those respondents who knew and reported their height and weight. So the data does not represent the full sample and is subject to reporting errors. Nonetheless, results are consistent with the findings of other studies. 2.8 SURVEY METRICS The survey metrics section deals with an assessment of quality of data in terms of household and individual sample deviation index, response rate, comparison of test and re test estimates and kappa values that plot the item responses. Sample deviation index (SDI) The representativeness of the surveyed population is assessed in terms of sample deviation index (SDI). It is divided into two, viz. household sample deviation index and individual sample deviation index. Household sample deviation index When a multi-stage cluster stage sampling is employed, where homogeneity is large within clusters and small between clusters, representativeness is a concern. The sample deviation index for each category is the ratio of the proportion of a sub group in the sample to that in the population. The sub groups used in this survey include age group and sex. The Sample Deviation Index in figure 2.2 presents three different lines on the graph showing the sample deviation index for the households’ population in West Bengal. A ratio close to 1 indicates

that the sample is representative of the population considering sex and age. The p value is 0.00 showing a significant difference between the sample and population, but this may be due to the large sample size (N=8874). The pi-star value is small (0.15) and indicates that only 15 percent of the sample does not follow the characteristics in age. So the sample can be considered as representative. The index indicates slight over representation in the ages 25-29, 35-39, 45-49 and much higher in older ages (80+ years). Overall, deviation is more pronounced for females than males. 2.9

RESPONSE RATE

The response rate for household and individual questionnaire indicates the extent of response from household key informant and adult respondents respectively. The response rate has a direct relationship with the degree of representativeness of the sample. In the World Health Survey India, the final result codes with respect to completion of questionnaire are 1) interview completed 2) interview partially completed 3) interview refused 4) interview not conducted. Response rate is the percent of interview fully and partially completed out of all households contacted i.e., (1+2)/(1+2+3+4). Non-response rate is percent of households who refused to answer or cannot be contacted (3+4)/(1+2+3+4). As found in other largescale surveys, the overall response rate of 94 percent is very good. However, this may mask the variations in

response rates by socio-demographic characteristics of the respondents. To study such variations, non-response rate have been examined for selected characteristics such as place of residence, age, sex, and education. In the case of individuals interviewed, the response rate is found to vary by their characteristics. For instance, the response rate is better in the rural areas (88 percent), among females (95 percent), the older ages such as above 30 years (89-93 percent) and among the illiterates (94 percent). Similarly, the non-response rate is higher in the urban areas (15 percent), about three times higher among males (15 percent) and among the literate persons (12 percent). 2.10 RELIABILITY The World Health Survey has provided an inbuilt retest mechanism to check the reliability of data. In West Bengal, retest interview was conducted in 10 percent of the total households. The retest was conducted in randomly selected PSUs out of total PSUs covered. Different teams of investigators were used for retest. A statistical comparison on selected indicators of data from first interview and retest interview showed no significant difference. 2.11 WEIGHTING The World Health Survey (India) adopted a multistage stratified cluster sample design. Design weights were calculated taking the specific sample design into consideration. Both household and individual weights were calculated to perform analysis at the household

Methodology

13

Figure 2.3: Sample deviation index (SDI) for individual respondents in West Bengal, 2003

and individual level. The distribution of these weights was then inspected and outlier weights that were below 1% and over 99% of the distribution were trimmed such that weights below the 1st percentile were set to the weight of the 1st percentile and weights over the 99th percentile were set to the weight of the 99th percentile. Post stratification corrections were made to

these weights to compensate for undercoverage. The UN 2000 population figures for India were used as the reference population. All analyses that are reported are carried out using these normalized probability weights and variance estimations take into account the complex design with the Taylor series method implemented in STATA.s

Table 2.2 Response and non-response rate in West Bengal, 2003 Characteristics Residence Urban Rural Missing Sex Male Female Missing1 Age group 15-29 30-39 40-49 50-59 60-69 70+ Missing1 Education Illiterate Literate Missing1 Total

Response rate Percent

Total

85.4 87.7 -

479 1196 -

14.6 12.3 -

82 168 -

561 1364 -

85.0 94.7 -

798 877 -

15.0 5.3 -

141 49 60

939 926 60

87.8 91.0 88.9 91.4 91.4 93.5 -

489 452 295 190 148 101 -

12.2 9.1 11.1 8.7 8.6 6.5 -

68 45 37 18 14 7 61

557 497 332 208 162 108 61

93.8 87.7 -

615 1060 -

6.3 12.3 -

41 149 60

656 1209 60

87.0

1675

13.0

250

1925

Note : - No cases reported. 1 Characteristics are not available.

14

N

Non-response rate Percent N

Health System Performance Assessment

Chapter 3

Socio-Demographic Profile of Household Population and Individual Respondents The World Health Survey in West Bengal collected information on the socio-demographic profile of the household population and of the individual respondents. The individual members are the respondents from whom a comprehensive range of health information is generated. 3.1

HOUSEHOLD POPULATION PROFILE

This section provides the distribution of sample household population characteristics namely age, sex, marital status and education. A household roster was administered to a key informant of the household. The age-sex distribution covers the population of all the ages, marital status is calculated for the population aged 15 and above and educational status for aged six and above. The information was collected from 1925 households. The total population in sample households is 8874 persons with males constituting 52 percent. About 71 percent of the household population belongs to the rural areas. 3.1.1 AGE-SEX DISTRIBUTION Figure 3.1 presents the age-sex distribution (population pyramid) of the household population and Table 3.1 shows the socio-demographic characteristics of the population by age, sex, marital status, and educational status. The age–sex structure is presented by three major age groups of 0-14, 15-59 and 60 above (Table 3.1). Of the total household population, 28 percent of the population are in the younger ages of less than 15, 63 percent in the ages 15-59 and over nine percent in the older ages of 60 and above. Urban areas have lesser young population (about 20 percent) belonging to ages

0-14 compared to rural areas (29 percent). The population belonging to the working age group (1559) in the urban areas is 67 percent and 62 percent in the rural areas. The elderly population (aged 60+) is over nine percent, much higher in urban (14 percent) compared to the rural areas (9 percent). In rural areas females account for 48 percent of the population. However, in the urban areas, the proportion of males and females is about the same. The population pyramid (Figure 3.1) depicts the agesex distribution of household population covered in West Bengal for all ages in five-year age group from ages 0-5 to 75+ years. The pyramid indicates a gradual fall in fertility over the years. The youngest age group (0-4 years) is about 8 percent compared to over nine percent for ages 5-9 and about 12 percent for ages 1014. However, overall, the state has a young or youthful population. The pyramid also indicates more females than males in the ages 25-29, 35-39, 60-64 and 65-69 years. Among the age groups, those with larger population are ages 10-14 and 15-19 years (each over 11 percent), 5-9 (over nine percent), 20-24 and 25-29 (over eight percent). The age groups with the lowest proportion are ages 70-74 and 75+ years (both less than 2 percent). 3.1.2 MARITAL STATUS Information on marital status of the household population aged 15 and above was collected. The sample population indicates that 26 percent of the population is never married while the currently married persons are about 66 percent. The proportion of population widowed is about seven percent and the separated, cohabiting and divorced constitute about one percent.

Socio-Demographic Profile of Household and Individual Respondents

15

The proportion of never married population (and also widowed) is larger in urban areas, 30 percent in urban areas compared to about 25 percent in rural areas. The population currently married in rural areas is 67 percent and in urban areas 61 percent.

overall mean size of household is about five persons. The mean number of household size is 5.4 in rural areas and 4.7 in the urban areas, with an overall average of 5.2 persons. Bigger household size of 6-10 persons is more common in rural areas (52 percent) than in the urban areas (48 percent).

3.1.3 EDUCATIONAL STATUS

3.2 PROFILE OF INDIVIDUAL RESPONDENTS

The educational status of household population in ages six and above is presented in Table 3.1. More males (79 percent) than females are literate (64 percent) and at each level of schooling, the male-female difference is quite pronounced and is in favour of males. Differences in educational attainment by place of residence are also found. Rural areas have more persons with no formal schooling and lesser proportion beyond primary level for females and beyond secondary level for males.

One adult member of age 18 and above was selected from each household from whom health and other information were obtained through the individual questionnaire. This section provides the characteristics of these respondents by age, sex, marital status, educational, religion and ethnic status (Table 3.2). Information was collected from 1675 individuals, of which 798 are males and 877 are females. Twenty-nine percent are from urban areas and 71 percent from the rural areas.

3.1.4 HOUSEHOLD SIZE In about 34 percent households in West Bengal, household size is less than five members and in 51 percent of households, the household size is about 6-10 members. In about 15 percent households, the size is more than 10 persons. The

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Health System Performance Assessment

3. 2.1 AGE-SEX DISTRIBUTION Figure 3.2 shows the socio-demographic characteristics of respondents by age, sex, and residence. In West Bengal the age group 20-29 years has the largest population (27

percent). This age group is also the largest in the urban areas (28 percent) but in the rural areas it is 30-39 years age group (23 percent).

As presented in Table 3.2, those below 20 years comprised about six percent of the population, while those in the twenties were 27 percent. The proportion between ages

Table 3.1 Percent distribution of household population profile by selected socio-demographic characteristics, West Bengal 2003 Characteristics

Urban

Rural

Total

Sex1 Male Female

50.3 49.7

52.1 47.9

51.8 48.2

Age group in years1 0-14 15-59 60+

19.5 66.7 13.8

29.4 62.0 8.6

27.7 62.8 9.5

Marital status2 Never married Currently married Separated Divorced Widowed Cohabiting Missing

29.7 61.4 0.6 0.1 7.4 0.9

24.7 66.5 0.6 0.3 6.7 0.1 1.0

25.6 65.6 0.6 0.3 6.9 0.1 1.0

Education status3 Male No formal schooling Less than primary school Primary school completed Secondary school completed High school completed College completed Post graduate degree completed Missing Female No formal schooling Less than primary school Primary school completed Secondary school completed High school completed College completed Post graduate degree completed Missing

9.4 14.0 31.7 15.6 14.1 12.4 2.7 -

23.6 23.0 33.1 9.4 4.9 4.3 1.7 -

21.1 21.5 32.8 10.5 6.5 5.7 1.9 -

20.6 16.2 30.2 14.0 8.6 8.4 2.1 -

39.2 25.7 23.2 6.2 2.0 2.1 1.6 0.04

35.8 24.0 24.4 7.6 3.2 3.2 1.7 0.03

Household size1 1-5 6-10 11+

39.0 48.1 13.0

33.3 51.6 15.1

34.2 51.0 14.8

Mean number of HH

4.7

5.4

5.2

Population in all ages Population in ages 6+ Population in ages 15+

2611 2408 2040

6263 5560 4230

8874 7968 6270

Note :

1

Age, sex and household size distribution is calculated for the total population (all ages). Marital status distribution is calculated for the population in ages 15+. 3 Education status distribution is calculated for the population in ages 6+. - No cases reported. 2

Socio-Demographic Profile of Household and Individual Respondents

17

30-39 is 23 percent, ages 60-69 is 10 percent and the proportion aged (70+ years) is six percent (Figure 3.2). There is not much variation in the urban-rural distribution of the different age groups. However, a larger proportion of the younger ages (below 40 years) in the sample come from the rural areas. 3.2.2 MARITAL STATUS About 16 percent of the respondents were ‘never married’, while those currently married constitute nearly three-fourths (74 percent). About 76 percent of respondents in rural areas and 66 percent in urban areas were married. The proportion of widowed and separated formed about 10 percent. The never married population is larger (22 percent) in urban areas compared to the rural areas (14 percent). 3.2.3 EDUCATION STATUS Information was collected about the educational status of individual respondents aged 18 and above. About 75 percent of the male respondents are literate whereas 49 percent females are literate. However, the gender difference is quite visible among the respondents. For instance, more males than females are found as the level of education increases. Also, at each level of completed schooling more males are found, until post-graduate level. The education level of females is even worse in the rural areas. There are about 57 percent females with no formal education in the rural areas as against about 26 percent in the urban areas. Interestingly, the proportion of

18

Health System Performance Assessment

females with primary level education is the same in both urban and rural areas. Also, while there are few females at the higher levels, 11 percent of females completed college education and another three percent have post-graduate education in the urban areas. Among the males, close to one-fifth (19 percent) have college education and about six percent have post-graduate education in the urban areas. Difference in educational attainment by residence is even sharper when comparing the proportion with no formal education. Males in the rural areas are also not faring well in education. About 27 percent have no formal education compared with 12 percent in urban areas. 3.2.4 RELIGION Three-fourths (75 percent) of the population are Hindu, 19 percent are Muslim and six percent belong to other religions (Table 3.2). The population of Hindu is slightly higher in the urban areas (77 percent) than in the rural areas (75 percent). A similar pattern is also seen for those belonging to other religions; more in urban areas (about nine percent). However, in the case of Muslims, the proportion is higher (about 20 percent) in the rural areas than in urban areas (14 percent). 3.2.5 MOTHER TONGUE Eighty-three percent of adult respondents speak Bengali and two percent speak Hindi. Speakers of other languages account for over 14 percent. Eighty-four percent of the rural respondents and 79 percent of the urban respondents

Table 3.2 Percent distribution of respondents by socio-demographic characteristics, West Bengal 2003 Characteristics

Urban

Rural

Total

Age group in years 18-19 20-29 30-39 40-49 50-59 60-69 70+

4.2 20.8 22.5 19.2 10.4 13.3 9.7

6.2 27.8 23.1 14.7 13.1 9.5 5.6

5.9 26.5 23.0 15.5 12.6 10.2 6.4

Sex Male Female

47.1 52.9

50.2 49.8

49.6 50.4

Marital status Never married Currently married Separated Divorced Widowed Cohabiting

22.3 66.4 0.2 11.1 -

14.1 75.5 0.2 0.3 9.8 0.1

15.6 73.8 0.2 0.2 10.1 0.1

12.1 6.4 33.3 12.8 11.2 18.6 5.6

27.4 18.6 36.1 12.8 2.9 2.0 0.4

24.7 16.5 35.6 12.8 4.3 4.9 1.3

Education status Male No formal schooling Less than primary school Primary school completed Secondary school completed High school completed College completed Post graduate degree completed Female No formal schooling Less than primary school Primary school completed Secondary school completed High school completed College completed Post graduate degree completed Religion Hindu Muslim Others1

25.5 10.1 26.4 17.9 5.5 11.8 2.9

56.8 11.0 28.1 3.6 0.4 0.1 -

50.9 10.8 27.8 6.3 1.4 2.3 0.6

76.9 14.2 8.9

74.7 19.6 5.7

75.1 18.6 6.3

Mother tongue Bengali Hindi Others2

78.8 10.9 10.4

84.2 0.4 15.3

83.3 2.3 14.4

Total

479

1196

1675

Note :

1

Others include Christian, Sikh, Buddhists, Jains, others etc. Others include (in order with their proportion) Nepali, Santhali, Sadri, Rajbanshi, Urdu etc. – No cases reported 2

speak Bengali. Hindi speakers are mainly found in urban areas (11 percent) while respondents speaking ‘other languages’ are concentrated more in the rural (15 percent)

compared to urban areas (10 percent). Among other languages, the prominent mother tongues are Nepali, Santhali, Sadri and Urdu.

Socio-Demographic Profile of Household and Individual Respondents

19

Chapter 4

Risk Factors

People are exposed to an almost limitless array of risks to their health throughout their lives in the form of communicable and non-communicable diseases. They are also exposed to injury, violence and natural catastrophes. Risk factors are defined as the attributes, characteristics or exposure that increase the likelihood of developing a disease. In the context of public health, population measures of risk factors are used to describe the distribution of future disease in a population, rather than predicting the health of a specific individual. Knowledge of risk factors can then be applied to shift population distributions of these factors and to reduce the risks for the people, especially where individuals have very little control over their exposure to risks. This chapter identifies the risk to health and measures how these risks are distributed in the population and how they are linked to health outcomes. It is necessary that to identify risks to focus on the interventions that can improve health of future populations through the effective inter-sectoral collaborations. The rationales behind the inclusion of risk factors in the World Health survey are (1) it has the greatest impact on mortality and morbidity from non communicable diseases, and (2) modification is possible through effective primary prevention if measurement of risk factors is valid and reliable. Data have been collected on five major risk factors such as use of tobacco, alcohol consumption, nutrition, categories of physical activities and environmental related risk factors. The use of tobacco and liquor has considerable impact on the health of individual because of their detrimental effects on health. The nutrition content of the food, vegetables and the level of physical activity etc, are directly associated with health.

20

Health System Performance Assessment

The environmental risk factors such as access to improved drinking water, improved sanitation facilities and the use of fuel for cooking etc. are crucial determinants of human health. Environmental challenges in the home, work place, out door and transportation environments vary considerably between countries and within a given country. Interventions towards safe environments offer a large potential for disease prevention and can help reduce health inequalities. The questions in the risk factor module were asked to all respondents in ages 18 and above. 4.1 TOBACCO CONSUMPTION Smoking is the main way tobacco is used world wide, and the manufactured filter tipped cigarette is becoming increasingly dominant as the major tobacco product. Other forms of smoked tobacco are potentially as dangerous, although the adverse consequences of some of them are more limited because the smoke is not usually inhaled. In certain cultures tobacco is chewed, sucked or inhaled with adverse effects on the local tissues. Chewing tobacco is the most widespread form of tobacco consumption in India. All forms of tobacco consumption are dangerous, whether smoked or chewed. Table 4.1 presents the percentages of men and women ages 18 and above who use tobacco in West Bengal. Among the 1675 respondents, a little more than onethird (37 percent) use tobacco daily either by smoking or chewing. The proportion of tobacco users among males (48 percent) is more than two times higher than among females (21 percent). Tobacco consumption is more among the rural population (37 percent) than among the urban population (25 percent). The second round of the National Family Health

Table 4.1 Percent of respondents consuming tobacco [smoke, chew] in West Bengal, 2003 Characteristics

Persons with daily consumption

Prevalence (%)

N

Sex Male Female

392 162

47.9 21.2

798 877

Residence Urban Rural

125 429

25.1 36.5

479 1196

Income quintiles Q1 Q2 Q3 Q4 Q5

202 153 77 75 47

42.3 38.4 29.0 33.6 18.1

493 402 289 251 240

Age group 18-24 25-34 35-44 45-54 55-64 65+

43 107 167 98 69 70

19.3 28.4 42.7 36.8 42.3 48.8

280 408 389 272 158 168

Total

554

37.4

1675

Note : Applicable to all persons in the ages 18 and above.

Survey (NFHS-2) also reported that chewing of panmasala or tobacco is more common in rural areas than in urban areas (NFHS-2, 1998-99). Tobacco consumption is found to decrease with increasing income quintiles* . A little over two-fifths (42 percent) of the respondents in the lowest income quintile reported use of tobacco compared to 34 percent and 18 percent in the fourth and fifth quintiles. Therefore, tobacco consumption in West Bengal is mainly concentrated among the first and second income quintile groups. These two income groups also account for 53 percent of the adult respondents. Similarly, the proportion of consumers increases with age, the older ages with the highest level of consumption. For instance, consumption level increases from about 19 percent among the youth (below 25 years), 28 percent among 25-34 age groups, 43 percent among 35-44 years, to 49 percent among those 65 and above years.

Figure 4.1 presents the variation in tobacco use by sex in West Bengal. It is evident that in West Bengal the level of tobacco use at all ages is much higher among the males. However, a sharp decline in tobacco use is observed among those in their late forties and early fifties (ages 45-54). Again, the consumption level increases from among those aged 55-64 years. The male-female gap in tobacco use becomes more pronounced among adults in the age groups 35-44 years and 65+ years. Males in the age groups 35-44, 55-54 and 65+ years are more likely to use tobacco than any other age groups. In fact, they are about twice more likely to use tobacco than their female counterparts. Interestingly, tobacco consumption shows a steady increase at higher ages among females, up to ages 55-64 years. The level of tobacco consumption decreases slightly among females over 65 years (Figure 4.1).

* Quintile is a statistical division of the sample households into five parts based on permanent income indicators measured by the assets distribution in the households. The variable takes the value q1 to q5 with q1 being the poorest household and q5 being the richest household. The comparison between q12 and q5 reflects the poverty of the household.

Risk Factors

21

Figure 4.1: Tobacco use by age and sex in West Bengal, 2003

4.2

ALCOHOL CONSUMPTION

Studies have indicated that alcohol consumption has a U-shaped relationship with ischaemic heart disease and is a strong risk factor for hepatic cirrhosis and many other types of injury (particularly motor vehicle accidents). Alcohol has also been found to be positively associated with cancers such as breast cancer (WHO, 2004). The pattern of alcohol consumption (drinking) itself strongly influences the risk of non-communicable diseases, with occasional heavy drinking associated with injury and with hemorrhagic stroke. It is very difficult to obtain the exact statistics regarding the consumption of alcohol because it varies from culture to culture and from society to society. So, in order to avoid the difficulties, the survey has collected the information on the amount of drink consumed by an individual in the past seven days. The data collection was done by days of the week. The World Health Survey classified alcohol drinkers into two categories such as infrequent heavy drinkers who had drinks for two days in a week and frequent heavy drinkers who had drinks more than four days in a week. It needs to be mentioned that the social stigma attached to drinking, if any, might result in underreporting of the event. Such under-reporting is likely to be linked to the socio-economic and demographic characteristics of individuals. The proportion reporting never had alcohol is about 88 percent, 11 percent are infrequent heavy drinkers and heavy drinkers are insignificant (one percent). Among

22

Health System Performance Assessment

males, little less than one-fifth (18 percent) and among females only four percent of females can be termed as infrequent heavy drinkers (Table 4.2). The level of alcohol consumption is also found to be similar in both the urban and rural areas, by age and income level. However, alcohol consumption is higher among adults (over 30 years) and in the fourth income quintile group. The proportion of heavy infrequent drinkers is highest among those in the fourth income quintiles (16 percent) than any other groups. Similarly, infrequent alcohol consumption varies by age. Among the different age groups, more of those in their forties and fifties indicate consumption of alcohol than others. About 16 percent in the age group 45-59 years and 13 percent in 30-44 years are infrequent heavy drinkers of alcohol in the state. 4.3

NUTRITION AND PHYSICAL ACTIVITIES

Intake of Fruits and Vegetables Information on dietary habits and its changing pattern are ver y important for rational planning and improvement on nutrition related health policies and programmes. Information on fruits and vegetables and their intake can provide an idea of a causal association of consumption and the reduction in cardio vascular diseases and certain cancers. The measurement of certain selected items such as fruits and vegetables have been considered to indicate the availability of nutrition since data is not collected

on overall food intake. The WHO recommended two levels of intake of fruits and vegetables such as sufficient (five or more servings per one typical day) and insufficient (less than five servings per one typical day) intake. However, it is worth mentioning that availability of fruits and vegetables is seasonal and may influence the results.

mentioned here that in India intake of fruits and vegetables, particularly in rural areas, depends largely on what is locally grown and available free of cost and is therefore purely seasonal in nature. Overall, the level of insufficient intake of fruits and vegetables is low, even by income levels. Not much difference is found among the income quintiles, 97 percent in the first quintile and 92 percent in the fourth income quintile. The level is a little lower among the fifth income quintile (89 percent).

Table 4.3 presents the proportion of population with insufficient intake of fruits and vegetables in West Bengal. It also presents the level of insufficient physical activities in the state. A very high proportion of adult respondents in West Bengal (95 percent) do not have sufficient intake of fruits and vegetables, slightly higher among the females. The proportion with insufficient intake of fruits and vegetables is 94 percent for males and 95 percent for females. In rural areas, 91 percent of the population have insufficient intake of fruits and vegetables compared to 96 percent among the urban population. It needs to be

Physical activities Physical activities refer to the activities undertaken at work, around the home and garden, to get to and from places (i.e. for transport) and for recreation, fitness exercise or sports. Regular physical activity has a significant protective effect against ischaemic heart diseases, ischaemic stroke, type-two diabetes mellitus, breast cancer and colon cancer.

Table 4.2 Prevalence of infrequent and frequent heavy drinking in West Bengal, 2003 Characteristics

Sex Male Female Residence Urban Rural Income quintiles Q1 Q2 Q3 Q4 Q5 Age group 18-29 30-44 45-59 60-69 70-79 80+ Total

Never had a drink

Number of in frequent heavy drinkers1

Number of frequent heavy drinkers2

N

Number

Prevalence (%)

Number

Prevalence (%)

Number

Prevalence (%)

632 846

80.7 95.9

151 27

17.6 3.9

15 -

1.7 -

798 877

424 1054

88.3 88.3

47 131

10.2 10.8

8 11

1.5 0.9

479 1196

427 360 257 215 219

87.1 90.4 91.1 83.4 88.9

57 40 29 33 19

11.7 9.5 8.2 16.0 8.1

9 -

1.3 -

493 402 289 251 240

467 492 297 132 70 20 1478

93.3 85.8 83.1 88.3 94.3 87.3 88.3

34 86 47 15 8 193

5.3 13.2 16.4 11.1 5.7 10.7

15

1.0

489 588 349 148 78 23 1675

Note : All percentages are weighted and numbers are not weighted. 1 Infrequent heavy drinkers: 1 to 3 days with 5+ standard drinks per one week (in last 7 days). 2 Frequent heavy drinkers: 4+ days with 5+ standard drinks per one week (in last 7 days). - No cases reported/less than 5 cases.

Risk Factors

23

Emerging evidence indicates that physical activity is important in preserving the residual fraction once peripheral arterial disease and chronic airways disease have developed, increases sensitivity to insulin, raises HDL cholesterol levels and reduces blood pressure. In addition, recreational physical activity helps to reduce minor anxiety, depression and weight. The World Health Survey considers only activities meeting specific thresholds of intensity that were undertaken in the seven days preceding the survey. As shown in table 4.3, in West Bengal one-third of respondents (33 percent) are found to have inadequate physical activity and the proportion is higher among the females. About 28 percent males and 38 percent females reported inadequate physical activities. The proportion with inadequate physical activity is much higher among urban residents (42 percent) compared to 31 percent in the rural areas. Another pattern found

is that insufficient physical activity also increases at higher income levels and at higher ages. For instance, while the proportion is about 30 percent in the lowest income quintile, it is about 40 percent in the highest income group. Among those in the second quintile it is the lowest with 28 percent. Similarly, age is also associated with physical inactivity. The population in ages 30-44 are the most active (22 percent with inadequate physical activity), compared to above 70 percent among those over age 70 years. Height and weight by sex Information on weight and height was collected from both males and females and the data used to assess their nutritional status. Variation in nutritional status of women is found across socio-economic characteristics such as income and educational status. One important measure that reflects the nutritional status is the body

Table 4.3 Prevalence of insufficient intake of fruit & vegetables and insufficient physical activity in West Bengal, 2003 Characteristics

Persons with insufficient intake of fruits & vegetables1

Persons with inadequate physical activities2

N

Number

Prevalence (%)

Number

750 826

94.2 95.1

281 359

27.7 37.8

798 877

434 1142

90.8 95.6

181 459

41.8 30.8

479 1196

Income quintiles Q1 Q2 Q3 Q4 Q5

476 387 276 229 208

96.8 96.8 94.6 92.2 89.1

179 140 114 94 113

30.1 27.1 33.7 39.8 40.3

493 402 289 251 240

Age group 18-29 30-44 45-59 60-69 70-79 80+

460 554 324 139 76 23

95.1 94.3 93.4 94.9 98.2 100.0

184 158 141 80 56 21

28.3 22.2 33.7 49.4 72.3 90.2

489 588 349 148 78 23

1576

94.7

640

32.8

1675

Sex Male Female Residence Urban Rural

Total

Prevalence (%)

Note : All percentages are weighted and numbers are not weighted. 1 Fruit & Vegetables: 5 or more servings per one typical day. Insufficient intake of fruits and vegetables: less than 5 servings per one typical day. 2 Physical Activity: Sufficiently active for health: ‘time’>=150 minutes. Insufficiently active 1