Poverty status and health equity: Evidence from rural Bangladesh

Transcription

1 Public Health (2006) 120, ORIGINAL RESEARCH Poverty status and health equity: Evidence from rural Bangladesh F. Karim*, A. Tripura, M.S. Gani, A.M.R Chowdhury Research and Evaluation Division, BRAC, 75 Mohakhali, Dhaka 1212, Bangladesh Received 16 September 2004; received in revised form 9 May 2005; accepted 9 August 2005 Available online 24 January 2006 KEYWORDS Extreme poor; Moderate poor; Non poor; Health equity; Use of services; Bangladesh Summary Many studies have examined the health inequities between different social groups, often measured by individual independent variables, such as education, gender, ethnicity, geography, rich, poor, etc. Although inequities are increasingly widening, a few studies have looked at the health inequity between different poverty groups within the poor. The present study, using equity terms, examined the use of health services in two rural areas of Bangladesh. Using a multistage sampling method, a total of 80 villages were selected from the Bogra and Dinajpur sadar thanas (subdistricts) for the study. A total of 4003 households in these villages were visited for data collection on mortality and fertility, while data related to use of health services was collected from a subsample of 1032 households. A poverty index, constructed using three variables (household landholding, education level of head of household, and self-rated categorization of household s annual food security), categorized the households into three groups: extreme poor, moderate poor and non-poor. Overall, the data revealed considerable inequities in many study indicators between the poor and the non-poor. However, inequities of varying degrees were also found between the extreme poor and the moderate poor. Lower levels of inequities were found between the poor and the non-poor in the use of health services, which were easily accessible and free of charge (immunization, vitamin A capsule, etc.). On the whole, the extreme poor were less likely to use health services than the moderate poor and the non-poor, suggesting the need for a more appropriate programme to address their pressing health needs. Q 2005 The Royal Institute of Public Health. Published by Elsevier Ltd. All rights reserved. Introduction Backdrop * Corresponding author. Tel.: C / address: karim.f@brac.net (F. Karim). No country in the world seems to be immune to health inequalities, but the increasing concern is that the health gaps between different social /$ - see front matter Q 2005 The Royal Institute of Public Health. Published by Elsevier Ltd. All rights reserved. doi: /j.puhe

2 194 groups are widening worldwide. Eyob Zere and McIntyre 1 reported higher usage levels of doctors and hospital services by the rich, relative to their levels of reported illness, in South Africa. Socioeconomic, geographic, residence and gender divides in the use of immunization services are widespread in Bangladesh. 2 5 Ethnic disparity in the use of preventive and promotive health services is also evident 6 and is a serious concern. To address the particular health needs of the Bangladeshi poor, a host of non-government organizations (NGOs) have been trying to reach the poor with basic health services. However, they tend to address only the needs of the poor who participate in their development interventions, while those who do not or cannot participate are often excluded. Moreover, the poor are not a homogeneous group. Thus, there seems to be a large disparity among the poor in accessing health services, and this has been relatively unexplored. In fact, the health of these disadvantaged groups is extremely sensitive to the socio-economic and political development of Bangladesh. Many researchers have attempted to examine the socio-economic inequalities in health in Bangladesh. Mannan 7 analysed inequity in health by background variables, e.g. land, and found that 84% of the rural landless women did not eat any special food during their last pregnancy or whilst breastfeeding. The Bangladesh Bureau of Statistics (BBS) 8 and Rahman et al. 9 divided the households into poor, medium and rich, and thus found a wide gap between the poor and the rich in terms of usage of different health services. Analysing by wealth quintile, Gwatkin et al. 5 found that uptake of childhood immunization was lower among the poorest people in Bangladesh. Sen and Begum 10 subdivided the poor into extreme poor and moderate poor. This analysis revealed a disparity in health among the poverty groups. The Millennium Development Goals emphasize the need to reduce health inequalities between different social groups, but Gwatkin 11 argued that unless the special needs of the extreme poor and moderate poor are effectively addressed, the achievement would be at stake. However, alongside the government, many NGOs have been trying to improve the quality of lives of the poor in Bangladesh by organizing them into development groups and giving them various services, including health services. It will be interesting to see whether the health gaps have narrowed between different poverty groups as a result of these pro-poor interventions, and if so, how did this happen? This study explored the status F. Karim et al. of health inequities among different poverty groups in rural Bangladesh. Introducing the BRAC Reproductive Health and Disease Control Programme (RHDC) BRAC (Bangladesh Rural Advancement Committee) is an innovative NGO concerned with growing health inequalities and their consequences. In order to offer health services to those most in need, BRAC has initiated health programmes in many parts of Bangladesh. The RHDC programme, which covers over 9.7 million people, was the successor to BRAC s earlier Women s Health and Development Programme (WHDP), which was implemented between 1992 and The RHDC directly offers a wide range of health services such as pregnancy care, reproductive tract infection, sexually transmitted diseases, education on human immunodeficiency virus/acquired immunodeficiency syndrome, adolescent reproductive health education, nutritional supplementation for children and pregnant women, community-based control of acute respiratory infections and tuberculosis, and deworming. The RHDC also facilitates a number of government services for more equitable access to its services such as satellite clinics, EPI, family planning, vitamin A capsule distribution, water and sanitation. In addition, BRAC Health Centres (BHCs) offer all primary and secondary clinical support and referral services: outpatient counselling, consultation, treatment, drugs, microscopic and nonmicroscopic laboratory services, sexually transmitted diseases/reproductive tract infection services, safe delivery, menstruation regulation, postabortion care, and other domiciliary care. Initially, the BRAC health services were open to all members of the community. However, in August 1997, BRAC shifted its approach to focus on the pressing health needs of the poor, especially those who joined the NGOs microfinance activities including BRAC, to improve human capital and productivity, and to prevent income erosion stemming from different health emergencies. Many NGOs including BRAC provide microcredit (small loans for income and employment generation) services to the poor in Bangladesh for poverty alleviation. BRAC identifies poor households that fulfil the following criteria: (i) a household with less than 50 decimals of cultivable land; and (ii) any adult household member sells manual labour for at least 100 days a year for survival, and forms groups with them in each village. These groups are designated as village organizations (VO), whilst the households who do not fulfil the above criteria

3 Poverty status and health equity: Evidence from rural Bangladesh 195 are known as non-target (NTG). The VOs are given training and microcredit for poverty alleviation. BRAC spent over US$153 million, 20% of which came from donors contributions. Between 1991 to 1996, BRAC/WHDP provided services free of charge. Since 1997, BRAC/RHDC introduced service charges towards financial sustainability. The extent of charges varies by the type of services and the socio-economic conditions of the recipients (Table 1). VO members are charged Tk 10 (57.5 TkZ1 US$) for a consultation fee, whereas NTG members are charged Tk 20. Required drugs are sold to everyone at cost price. For each encounter of antenatal care, a VO member pays Tk 10 and an NTG member pays Tk 15. For each child delivered at a BHC, both VO and NTG members are charged Tk 250. Tk is charged for menstruation regulation. BRAC also produces and sells slab latrines at Tk per set. BRAC does not provide immunization directly; VAC facilitates these government services. However, regardless of VO membership, BRAC gives the extreme poor a 20% subsidy on the total costs incurred in every encounter. In addition, the extreme poor who are unable to pay are given free services. A similar package of services is also available at the government facilities, and these are mainly free of charge. The poor have no easy access to these services due to distance and unacceptable behaviour of the providers. In addition, there are hidden costs involved in availing these services which sometimes surpass the market costs. 12 Moreover, the quality and availability of necessary services at government sources are poor. This study, as part of a more Table 1 Service charges for type of services and recipients. Services Amount by type of socio-economic group (Tk) Village organization Non-target Consultation fee (per encounter) Antenatal care fee (per encounter) Child delivery at BRAC Health Centre Menstruation regulation Slab latrine (per set) Tk 57.5Z1 US$. comprehensive study on the impact of the RHDC programme, focuses on the equity aspects of different health service users in two rural RHDC areas. Methods and materials Study area and sample design Employing a multistage sampling method, 80 villages of the Bogra and Dinajpur sadar thanas (subdistricts) were chosen for this study. A total of 4003 households were surveyed using a cluster survey method between May and July 2000 in order to collect data on mortality and fertility. Health-service-related data were collected from a subsample of 1032 systematically selected households (25% of total). Primarily, responsible and competent mothers were interviewed using a pretested standard questionnaire containing structured and openended questions. Information about sensitive variables such as landholding, etc. was cross-checked with other competent household members, such as head of household or elders. Under the direct supervision of four field supervisors, 20 trained field investigators worked in four teams to collect data. Five percent of the households covered by the interviewers were spot-checked or re-interviewed for data consistency and completeness. The questionnaires were rigorously verified and edited at Head Office for consistency and completeness. Data were analysed using SPSS software. Chi-square tests were performed to measure the significance of differences between the variables/indicators. Only the significant differences between the variables/indicators were specified in the results (p!0.05, 0.01 and 0.001). Measuring the poverty status of rural households Measuring the poverty status of rural households either directly (e.g. measurement of daily calorie intake) or indirectly (e.g. measurement of income expenditures) was operationally difficult, and posed a challenge to subdivide the poor into different subgroups. This is crucial to measure the levels of health inequities among different poverty groups (extreme and moderate poor). However, a single variable/indicator such as landholding, sex of head of household, etc. is not sufficient to assess the poverty status of

4 196 Table 2 Distribution of households by socio-economic variables/indicators (nz1032). Socio-economic No. of households % variables/indicators Landholding (decimals) C Sex of head of household Male Female Education (years) C No. of meals usually taken per day by household members No. of meals eaten yesterday by all household members Frequency of rice (meals) eaten yesterday Mode of procuring rice yesterday Purchase Own production Borrowing Donation Food security status Deficit Breakeven Surplus a rural household, 13 so construction of an index was necessary. In the present study, data on eight variables/indicators were collected in order to compose an index to assess the poverty status of the study households (Table 2). The data showed that the cell frequencies of some indicators (sex of head of household, number of daily meals usually consumed by household members, number of meals taken by all household members in the last 24 h, frequency of rice (meals) eaten by household members in the last 24 h, and mode of procuring rice for cooking) were too small for meaningful analysis. Therefore, three variables (landholding, education level of head of household, and food security status) were selected to construct an index of poverty status of the study households. F. Karim et al. Rationales for constructing a poverty index Microcredit organizations widely use landholding to target landless households (with!50 decimals). 10 The study revealed that this group of households contains 71% of the extreme poor rural households. However, not all households with this amount of land can be defined as extreme poor. About 57% of the moderate poor households also belong to this category. A study performed by the World Bank 14 found that six out of 10 households possessing!50 decimals of land were very poor. In contrast, only one of 40 households owning 7.5 acres of land or more was poor. Land alone is not enough to define the poverty status of a household. Educational attainment of the head of household is also strongly correlated with the socio-economic status of households. It is evident that the incidence of poverty is higher among illiterate households. 10,14 The human capital theory explains the positive relationship between an individual s educational attainment and income. So, the level of education of the head of household is a good proxy of his/her income and the economic status of the household. Sen et al. 10 found that self-categorization of annual food security was a sensitive indicator to determine the poverty status of a household. Based on the annual food supply status, the respondents categorized their households as experiencing a chronic deficit, an occasional deficit, a breakeven or a surplus of food. Such self-categorization also addresses the seasonal fluctuations of food security in a household. In view of this, the variable household food security status was selected for use in the present study. All three variables, i.e. land, education level of head of household, and food security, serve as a basis of measuring the poverty of a rural household. However, in this study, the Pearson correlation co-efficient was calculated to determine the correlation among these variables. The levels of correlation were as follows: between household landholding and education level of head of household 0.376; between household landholding and food security status 0.297; and between education level of head of household and food security status Although, there was moderate correlation between the variables, these were statistically significant at the 1% level. Thus, it was decided to use these three variables to compose an index of poverty status of the study households. The households were categorized into the three poverty categories as shown below. Extreme poor: households with 0 10 decimals of land, head of household with 0 2 years of

5 Poverty status and health equity: Evidence from rural Bangladesh 197 education and a deficit in annual food supply. Moderate poor: households with decimals of land, head of household with 3 5 years of education and breakeven in annual food supply. Non-poor: households with 51 or more decimals of land, head of household with 6 or more years of education and a surplus annual food supply. However, many households did not satisfy all of these conditions in order to be included in any of the above categories. Therefore, a score was assigned for each variable ranging from one to three. In this process, a household had a probability of obtaining a maximum score of three and a minimum score of one, where one was the highest and three was the lowest probability of being extreme poor. The resultant frequencies are shown in Table 3. The scores for each variable were added together for each household. The maximum possible score was 9. The total range of scores was divided into three intervals, and all of the households were allocated to the three groups depending on their score (Table 4). Households that obtained a score of 1 3 were classed as extreme poor (36.3%), those that obtained a score of 4 or 5 were considered to be moderate poor (24.8%), and those household with a score of 6 or more were classed as non-poor (38.9%). The resulting proportions of households were almost comparable to those of the BBS Household Expenditure Survey 2000 data. 15 Based on the per day per capita kilo calorie intake, BBS found that about 19, 42 and 39% of the rural households were extreme poor, moderate poor and non-poor, respectively. 15 Table 3 Distribution of households by level of score assigned and poverty status (nz1032). Socioeconomic variables No. of households Poverty status Landholdings (decimals) Extreme poor Moderate poor 2 51C 306 Non-poor 3 Education (years) Extreme poor Moderate poor 2 6C 297 Non-poor 3 Food security status Deficit 307 Extreme poor 1 Breakeven 406 Moderate poor 2 Surplus 319 Non-poor 3 Score Table 4 Distribution of households by poverty status and score. Poverty status Score No. of % household Extreme poor Moderate poor Non-poor 6 or more Total Results Use of pre- and postnatal services Table 5 depicts that less than one-tenth of deliveries among different groups of the poor took place in hospitals and/or clinics (termed institutional facilities ) (extreme poor 9.3%, moderate poor 8.6%), compared with over one-quarter for the non-poor (26%) (p!0.001). The proportion of moderate poor mothers (34.6%) who had been ill during their last pregnancy and who received treatment from qualified/trained physicians was lower than that for the extreme poor (50%) and the non-poor (72%). The difference between the groups was significant (non-poor vs extreme poor p!0.05, non-poor vs moderate poor p!0.01). The majority of the remaining mothers, regardless of their poverty status, visited the village doctors for treatment (extreme poor 37.5%, moderate poor 34.6%, non-poor 22.2%). Other illnesses were not treated. Most mothers, irrespective of poverty status, received two or more doses of TT vaccine during their last pregnancy (extreme poor 78.6%, moderate poor 66.4%, non-poor 84.7%). The moderate poor had a significantly lower coverage compared with the non-poor (p!0.001). The proportion of deliveries of the extreme poor that occurred at home and which were attended by trained traditional birth attendants (TBAs) was lower (40%) than those for the moderate poor (45.3%) and the non-poor (51.3%). Unlike the nonpoor (90.9%), all infants (0 6 months) of extreme poor and moderate poor mothers were given colostrum within 24 h of birth. A lower proportion of non-poor infants (40.9%) were exclusively breastfed compared with extreme poor (55.6%) and moderate poor (57.1%) infants. Use of general health services Table 6 shows that the moderate poor (35.7%) were more likely to use oral saline (packet ORS or

6 198 F. Karim et al. Table 5 Use of selective pre- and postnatal services by poverty status. Indicators Poverty status Extreme poor Moderate poor Non-poor Hospital-/clinic-based childbirth (%) 9.3 (17) 8.6 (10) 26.1 (41) n Illness in last pregnancy treated by qualified/ 50.0 (24) 34.6 (9) 72.2 (26) trained physician(%) n Women received two or more doses of TT vaccine 78.6 (143) 66.4 (77) 84.7 (133) in last pregnancy (%) n Childbirth at home attended by a trained traditional 40.0 (66) 45.3 (48) 51.3 (60) birth attendant (%) n Colostrum fed (% of infants 0 6 months) (18) (7) 90.9 (20) n Exclusivly breastfed (% of infants 0 6 months) 55.6 (10) 57.1 (4) 40.9 (9) n Figures in parentheses indicate cell frequency. c 2 significance: childbirth in hospital: Col. 1 vs 3 P!0.001, 2 vs 3 p! Illnesses in last pregnancy treated by qualified physicians: Col. 1 vs 3 P!0.05, 2 vs 3 p!0.01. Women s TT in last pregnancy: Col. 2 vs. 3 p! homemade fluids) than the extreme poor (24.6%) and the non-poor (33.1%) to treat diarrhoea. Contrary to this, most diarrhoea episodes received allopathic treatment regardless of poverty status (extreme poor 70.7%, moderate poor 71%, non-poor 69%). The proportion of patients receiving no treatment for diarrhoea was highest amongst the extreme poor (18.6%) and lowest amongst the moderate poor (13.3%), followed by the non-poor (13.9%). The majority of patients across different groups with general illnesses (other than diarrhoea) sought treatment from the village doctors (extreme Table 6 Use of general health services by poverty status. Indicators Poverty status Extreme poor Moderate poor Non-poor Oral saline used in diarrhoea (%) 24.6 (41) 35.7 (35) 33.1 (50) n General illnesses treated by qualified/trained 37.1 (136) 30.6 (74) 44.7 (189) physician (%) n Children (12 23 months) fully immunized (%) 89.7 (61) 94.3 (33) 91.8 (45) n Women (15 49 years) received two or more doses 77.5 (321) 79.5 (225) 78.0 (372) TT vaccine (%) n Children (6 71 months) received VAC (%) 92.8 (310) 92.5 (196) 95.8 (277) n Family planning method used (% of currently 58.6 (231) 57.1 (149) 55.6 (247) married women years) n Pneumonia treatment (%) Allopathic treatment 73.8 (31) 60.6 (20) 78.0 (32) No treatment 11.9 (5) 27.3 (9) 4.9 (2) n Figures in parentheses indicate cell frequency. c 2 significance: general illnesses treated by qualified physician: Col. 1 vs 3 p!0.05, 2vs3p!0.01.

7 Poverty status and health equity: Evidence from rural Bangladesh 199 poor 45%, moderate poor 48%, non-poor 37%). A significantly higher proportion (45%) of non-poor patients received treatment from qualified/trained physicians than extreme poor patients (37%, P! 0.01) and moderate poor patients (31%, P!0.001). Although an overwhelming majority of children (12 23 months) received all doses of all six EPI vaccine antigens, the proportion was lower for the extreme poor (89.7%) than the moderate poor (94.3%) and the non-poor (91.8%). The majority of women of reproductive age (15 49 years) received two or more doses of TT vaccine. The proportion was slightly lower among the extreme poor (77.5%) compared with the moderate poor (79.5%) and the non-poor (78.0%). A large majority of children (6 71 months) received vitamin A capsules (92%) during a 6-month recall period, with trivial differences across the study groups. However, coverage was highest among non-poor children (95.8%). A slightly lower proportion (56%) of the currently married nonpoor women (15 49 years) used family planning methods than the moderate poor (57%) and the extreme poor (59%). About 74% of the extreme poor patients resorted to allopathic treatment for pneumonia compared with 78% of the non-poor and 61% of the moderate poor. The use of homeopathic treatment appeared to be the second most favoured mode of treatment for pneumonia among all the groups, with the lowest uptake among the moderate poor (extreme poor 19%, moderate poor 12%, non-poor 22%). Notably, a substantial proportion of pneumonia cases among two groups of the poor were not treated at all (extreme poor 12%, moderate poor 27%). Practice of personal hygiene Table 7 shows that the proportion of people defaecating in slab latrines was lower for extreme poor households (16%) compared with moderate poor (21.5%) and non-poor (29.7%) households. The differences between the non-poor and the other two groups were significant (extreme poor vs nonpoor P!0.001, moderate poor vs non-poor P! 0.05). Use of pit latrines also demonstrated a similar pattern across all three study groups. The extent of pit latrine use revealed a significant difference between the study groups (extreme poor vs moderate poor and non-poor P!0.001, moderate poor vs non-poor P!0.01). A great majority of respondents, irrespective of their poverty status, stated that they cleaned their teeth every day, but the proportion was lowest for the extreme poor (94%) compared with the moderate poor (97%) and the non-poor (98%). The differences between the groups were significant (extreme poor vs moderate poor P!0.05, moderate poor vs non-poor P!0.01). Impact status by poverty groups Table 8 depicts a higher infant morfality rate per 1000 live births among the moderate poor (86/1000 live births) than the extreme poor (65/1000 live births) and the non-poor (38/1000 live births). The crude death rate (CDR) per 1000 population was higher (8/1000 population) among both the extreme poor and the moderate poor compared with the non-poor (6/1000 population). While the crude birth rate (CBR) per 1000 population was significantly higher among the extreme poor Table 7 Practice of personal hygiene by poverty status. Indicators Poverty status Extreme poor Moderate poor Non-poor Place of defaecation (% of households) Slab latrines 16.0 (60) 21.5 (55) 29.7 (119) Pit latrines 8.3 (31) 19.9 (51) 29.2 (117) n Presence of ash/soap near latrine (% of households) 54.6 (130) 60.1 (113) 77.4 (250) n Handwashing before meals (% of respondents) 99.7 (373) (258) 99.7 (399) n Teeth cleaning every day (% of respondents) 93.6 (350) 97.3 (251) 97.5 (390) n Figures in parentheses indicate cell frequency. c 2 significance: slab latrines: Col. 1 vs 3 P!0.001, 2 vs 3 P!0.05. Pit latrines: Col. 1 vs 2 P!0.001, 1 vs 3 P!0.001, 2 vs 3 P!0.01. Presence of ash/soap: Col. 1 vs 2 P!0.001,1 vs 3 P!0.001, 2 vs 3 P!0.01. Teeth cleaning: Col.1 vs 2 P!0.05, 1 vs 3 P!0.01.

8 200 F. Karim et al. Table 8 Impact status by poverty groups. Indicators Poverty status Extreme poor Moderate poor Non-poor IMR/1000 live births 65 (13) 86.2 (10) 38.2 (6) Crude death rate/1000 population 7.9 (47) 8.0 (38) 6.1 (48) Crude birth rate/1000 population 31.7 (186) 24.7 (117) 20.3 (159) Live birth (%) 100 (182) 99.1 (116) 98.7 (157) n Diarrhoea prevalence (%) 10.5 (167) 8.2 (98) 7.7 (151) n Prevalence of general illnesses (%) 23.2 (367) 20.3 (242) 21.6 (423) n Mother s illness incidence during last 26.4 (48) 22.4 (26) 22.9 (36) pregnancy (%) n Figures in parentheses indicate cell frequency. c 2 significance: crude birth rate: Col. 1 vs 2 P!0.05, 1 vs 3 P! Diarrhoea: Col. 1vs2P!0.05, 1 vs 3 P!0.01. (32/1000 population), followed by the moderate poor (25/1000 population), it was the lowest among the non-poor (20/1000 population). The difference between the extreme poor compared with the moderate poor and the non-poor was significant (P!0.05 and 0.001, respectively). All births among the extreme poor (100%) were live compared with the moderate poor (99.1%) and the non-poor (98.7%). The prevalence of diarrhoea increased with the increase in poverty level (extreme poor 10.5%, moderate poor 8.2%, non-poor 7.7%). The differences between the groups were significant (P!0.05 for the extreme poor vs moderate poor, P!0.01 for the non-poor vs extreme poor). The prevalence of general illnesses (other than diarrhoea) was higher amongst the extreme poor (23%) than the moderate poor (20%) and the non-poor (22%). About % of mothers, regardless of their poverty status, had incidence of illnesses during their last pregnancy. The proportion was highest among the extreme poor (26%) followed by the moderate poor (22%) and the non-poor (23%). Discussion Overall, the data primarily revealed varying degrees of inequities in key health indicators among all the study groups. When comparing the extreme and moderate poor separately against the non-poor, the degree of differentiation across various health indicators was even greater. This may be the general trend in countries where equity objectives are not set or no policy mechanisms exist for increasing health equity. In fact, while examining different indicators by poverty status, the data indicated that the extreme poor had the highest use of family planning methods, the highest incidence of crude births, and the highest incidence of illnesses of women during their last pregnancy. The prevalence of diarrhoea and general illnesses was also highest among this group. Use of oral saline in diarrhoea and immunization for children and women were highest among the moderate poor. They also had the highest IMR. However, in contrast to all other study groups, the non-poor were the greatest users of most services examined in the study, and had the lowest incidence of IMR, CDR, CBR and diarrhoea. Out of 26 indicators, the non-poor registered a higher level of use in 16 indicators, compared with the extreme poor in three indicators and the moderate poor in seven indicators. However, the comparisons between the extreme poor and the moderate poor by number of study indicators showed that the extreme poor performed better in eight indicators as opposed to 12 indicators of the moderate poor. Incidentally, these two groups were the targets of BRAC interventions on health and microcredit. In fact, in the absence of any benchmark status, it is difficult to draw any conclusions about the differences among the poverty groups. Instead, this analysis reflects the present situation of equity. However, an obvious question may arise as to how to explain the visible differences between the extreme and moderate poor in some indicators. By applying Chi-squared test, those indicators with significant differences

9 Poverty status and health equity: Evidence from rural Bangladesh 201 Table 9 Differential use of health services/facilities, where user payment, physical access and knowledge/- attitude are most important factors by poverty groups. Parameters Differences between poverty groups Extreme poor vs moderate poor Services/facilities where user payment was most important Moderate poor vs non-poor Hospital-/clinic-based childbirth **** **** Illness in last pregnancy treated by ** * qualified/trained physician General illnesses treated by qualified/trained physician *** ** Services/facilities where access was most important Women received two or more doses ** *** of TT vaccine in last pregnancy Childbirth at home attended by a * trained traditional birth attendant Use of slab latrines * *** Use of pit latrines *** ** *** Oral saline used in diarrhoea * Services/facilities where knowledge/attitude was most important Presence of ash/soap near latrines *** *** for handwashing Daily teeth cleaning * ** Extreme poor vs non-poor Chi-square test was performed for significance. ****Significant at 0.1% level, ***significant at 1% level, **significant at 5% level, *Significant at 10% level. were identified (Table 9). Based on some features of the services, these indicators were divided into three groups regarding services/facilities where: (i) payment by user is most important; (ii) physical access is most important; and (iii) knowledge/attitude is most important. The analysis considering these features showed significant differences between the extreme and moderate poor in the use of the services/facilities where physical access and improved knowledge/attitude were most important for them. However, compared with the moderate poor, the extreme poor women were significantly more likely to have received two or more doses of TT in their last pregnancy. In contrast, in comparison with the extreme poor, the moderate poor were significantly more likely to use oral saline in diarrhoea episodes and slab latrines, and to clean their teeth daily. These services are provided free of charge by the government, while NGOs provide extensive health education free of charge and supply low-cost slab latrines. It should be noted that the poor are the main target for the NGOs services. However, the important fact is that the use of services/facilities that require payment by the user did not show any significant differences between the extreme and moderate poor, implying that neither of these groups are able to afford these services. Furthermore, a propensity of narrowing gaps between the poor and the non-poor in some indicators, such as childhood immunization, TT vaccination for women of reproductive age, VAC coverage and use of family planning, handwashing before taking meals, dental care, and incidence of CDR, live births and general illnesses, was also evident. Among these services, child and women s immunization, VAC and contraceptives are provided at the doorstep free of charge. Perhaps for these reasons, equity in the use of these services is improving gradually than other services, where user payment is most important, irrespective of their sources. Health education and social mobilization by BRAC and other NGOs on personal hygiene are also accessible to the people, irrespective of their poverty status. These factors may have helped to improve the personal hygiene behaviour, e.g. handwashing before taking meals, daily teeth cleaning, and reduction in the incidence of general illnesses. On the other hand, delivery in hospitals, treatment of illnesses by trained/qualified doctors and installation of slab latrines incurs direct costs. Seemingly, the extreme poor are usually unable to afford these services, resulting in low utilization. Although the use of pit latrines does not incur much cost, its use among the extreme poor was the lowest. Pit latrine installation requires space

10 202 around the homestead, and many households do not have such space for this purpose. Use of trained TBA services in childbirth incurs indirect costs in terms of the tradition of providing a gift or cash, and many people, especially the poor, rely on family members as delivery attendants. For these reasons, the use of trained TBAs was lower among the extreme poor. The reason for the better use of some services, e.g. use of trained/qualified physician for treating general illnesses, use of allopathic treatment for pneumonia, etc. by the extreme poor compared with the moderate poor can be explained by the fact that some agencies, including NGOs, offer free or highly subsidized health services to the extreme poor. Such provisions may have resulted in increased use of particular services by the extreme poor. BRAC s provision of allopathic treatment for general illnesses and pneumonia is a good example in this regard. No hard data are available to explain the reasons for less IMR and higher live births among the extreme poor compared with the moderate poor. Further research is needed to explore the reasons for such differences between these poverty groups. Evidence shows that there are many strategic flaws in defining and identifying the neediest population in order to reach them with health and development services; this contributes to the inequality in health. Although both government and non-government agencies run a number of development interventions including health in Bangladesh, many do not fully succeed in reaching the poorest members of the population. A study by Hashemi 16 found that the microcredit programmes of Grameen Bank (a national microcredit NGO) and other NGOs failed to effectively target and identify the extreme poor for intervention. It may have been the case that the strategy, along with the operational definition of the target population, used in these microcredit programmes was not sensitive enough to detect and include the extreme poor in the programmes. Moreover, the extreme poor were not considered to be microcredit worthy. Thus, the microcredit programmes systematically miss out this group. Similar things may be happening in the delivery of health services. Therefore, there is a strong imperative to redefine the target population and undertake special strategies to address the pressing needs of the extreme poor. Otherwise, the achievements of community development may backfire and intensify socio-economic disparities despite significant improvement in the position of the individual programme participants (group members). Chowdhury et al. 17 found that F. Karim et al. the standard BRAC programme had not been very successful in enrolling the poorest of the poor effectively. However, the poor who were enrolled in BRAC programmes gained substantial socioeconomic benefits. Studies indicated that the programmes that used a targeted approach for development (special service provision for the targeted segment of the poor who need health services more than other segments) had been successful in improving the well-being of the programme participants, including nutrition and mortality status, as well as reducing the inequity in health between poor and non-poor programme participants. 18,19 However, the daunting challenge is how to maximize enrolment of the extreme poor into health programmes. As discussed earlier, the poor are more likely to use services that are easily accessible and free of charge, such as child immunization, woman s TT vaccination, family planning and VAC. Increasing equity in preventive programmes has been found to have a greater potential than curative programmes for improving the health of the population. 20 BRAC s Income Generation for Vulnerable Group Development (IGVGD) programme and Challenging the Frontiers of Poverty Reduction/- Targeting the Ultra Poor (CFPR/TUP) programme are good examples of programmes that effectively identify and address the special needs of the destitute. 16,21 BRAC may model its health programmes based on lessons learned from IGVGD and CFPR/TUP, and make provisions for a needbased health package for the poor, including social health insurance. This approach can be continued until the extreme poor are alleviated from their present status of low health service utilization. BRAC s CFPR/TUP programme, initiated in 2002, offers a special health service package for the ultra poor, including health and nutrition education, installation of latrines and tube-wells free of charge, free pregnancy care/- child immunization, basic curative care for common illnesses at cost prices, financial assistance for moderate/severe illnesses, and an identity card for privileged access to formal public sector health care. Sharif 22 suggested that an effective poverty reduction strategy should keep three levels of poverty in mind when developing appropriate mechanisms to cater for the pressing needs of different poverty groups. The over-riding goal will be to lead people out of their respective poverty levels until they are freed from poverty altogether. The poverty status of a household is a major determinant of health service utilization. According

11 Poverty status and health equity: Evidence from rural Bangladesh 203 to Skold, 23 poverty is both the cause of ill health and vulnerability in people, and an obstacle for delivering effective health care. Reduced demand for services, lack of continuity or compliance with medical treatment, and increased transmission of infectious diseases are the result. Case studies 24 have revealed that increases in user fees or the price of health care tend to re-inforce existing inequalities in accessing health services, unless exemptions are made to protect the poor. In Bangladesh, it is likely that a lack of money to pay for transport prevents the disadvantaged from accessing health services, even those that are provided free of charge (such as immunization, etc.). More importantly, high social costs in terms of the distance to health facilities and many hours away from paid work may also prevent the poor from seeking sufficient health services. This is compounded by the differential behaviour of the providers and intimidation. 25 These factors eventually lead the poor towards self-exclusion. However, the link between poverty and health is tangible. Poverty undermines health, renders people more vulnerable, and reduces work capacity and productivity resulting in low income. Again, low income leads to poverty and poor health. Many researchers have found that an individual s position within society is indicative of health status. A paper by the British Medical Association 26 noted that inequalities in health run right across the whole society regardless of economic status. Macintyre 27 remarked that the relationship between socioeconomic status and health exists in all societies and is apparent throughout. There exists a linear relationship between socio-economic circumstances and health, even amongst those with higher socio-economic status. The inequality in health service utilization cannot be explained by a single factor. Rather, it is likely to be the result of a complex interplay between a number of genetic, biological, social, environmental, cultural and behavioural factors. Most health and development policy makers and managers have not taken sufficient action to actively address these factors for enhanced participation of the poorest members of the population in their initiatives. Unless all development programmes make a special provision for the most needy, it will be difficult to achieve equity in health development. Sen 28 advocated that the poorest and the most vulnerable merit separate attention in the overall context of community-based intervention strategies, so that they could be visibilized and their voices and specific needs could be heard. In this study, three variables were used to compose a poverty index. Using this, two sub-groups were identified within the poor (extreme and moderate poor), and a non-poor group was also identified; these were used to measure health equity by poverty status. However, inclusion of more indicators, such as quality of dwellings, occupation of head of household, economic dependency, etc., may help to reveal a more precise poverty status of the rural households. These were very difficult to measure given the resources and the time constraints of the study. Moreover, the main thrust of determining the poverty status of the study households was to assess the extent of equity in health service utilization by different poverty groups (the groups within the poor and the non-poor). The health service measures in this study are provided by different agencies including the government. BRAC policy attempts to recover the costs of services, especially those that are given through BHCs. BHCs have an equity pricing strategy. Government services are provided free of charge but these have access problems. This study did not attempt to measure the sources of services used, and this could provide a better indication of the exact health equity and the barriers towards equity. To address this, a separate study will be very useful. Conclusion In conclusion, this study demonstrated health inequities between different subgroups within the poor and the non-poor. In particular, the use of services/facilities that require payment by the user was low among both groups of the poor, implying that they are unable to afford these. The moderate poor appeared to be considerably better in many study indicators compared with the extreme poor. However, a propensity of narrowing the gaps between the poor and the non-poor in some indicators such as childhood immunization, women s TT vaccination, VAC coverage and use of family planning was also evident. Indeed, these services are available at the doorstep free of charge. This means that services which are easily accessible are being equitably used by the poor. BRAC and other NGOs are performing social mobilization and educating people to use these services. Perhaps for these reasons, the gaps between the study groups have narrowed in the use of these services. Thus, this necessitates the integration of health education into the health service package. Moreover, the lack of a measurable difference between the groups in some other

12 204 indicators may indicate the impact of BRAC s interventions, but this needs to be explored further. The overall condition of the extreme and moderate poor warrants a special policy, strategy and pro-poor programme with a more appropriate safety net to addressing the pressing health needs of the different subgroups of the poor. A cost recovery programme towards sustainability may have a negative impact on the health of many poor people who are no longer able to afford the costs. Respective agencies should review their cost recovery policy, keeping in mind the condition of the rural poor. BRAC and other agencies working in the same line should continue to provide free services to the extreme poor. Acknowledgements The authors are grateful to BRAC s Health, Nutrition and Population Programme for financing the study out of a donation received from the Department for International Development, UK. They are very appreciative of the assistance given by Dr Shantana R Halder, Senior Research Economist of BRAC Research and Evaluation Division (RED) in various stages of the study. They would also like to thank the field investigators who worked in adverse conditions for data collection, and the respondents for providing valuable data for the study. Lastly, the authors are grateful to Dr Imran Matin, Director, BRAC Research and Evaluation Division, Ms. Shayna Strom, Yale University, USA and Mr. Hasan Shareef Ahmed, Chief Editor, RED for their comments and suggestions for improving the paper. References 1. Zere E, McIntyre D. Equity in self-reported adult illness and use of health service in South Africa: inter-temporal comparison. J Health Popul Nutr 2003;21: Chowdhury AMR, Bhuiya A, Mahmud S, Salam AKMA, Karim F. Immunization divide: who do get vaccinated in Bangladesh? J Health Popul Nutr 2003; 21(3): Bhuiya A, Bhuiya I, Chowdhury M. 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