Department of Biostatistics, All India Institute of Medical Sciences, Ansari Nagar, New Delhi-110029, India.
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Abstract |
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Methods The data from an Indian State, Uttar Pradesh (UP), collected by the National Family Health Survey (NFHS) conducted during 10 October 1992 to 22 February 1993 was used. For model I, 7851 currently married women who were neither pregnant nor had continuing post-partum amenorrhoea (PPA) were considered. For model II, these women with at least one child (n = 6748) were used. Two-level logistic regression analysis was carried out for which women's level (level 1) and PSU (Primary Sampling Unit) level (level 2) variables were considered. The results were considered significant at the 5% level of significance. Simulation analysis using each model was also carried out.
Results Model I reveals that those more likely to adopt contraception were women exposed to a TV message (odds ratio [OR] = 1.3; 95% CI : 1.11.6); whose houses were pucca (bricks and mortar) (OR = 1.3; 95% CI : 1.11.5); who were educated to high school level and above (OR = 2.9; 95% CI : 2.23.7); whose husbands were literate with schooling of 11 years (OR = 1.7; 95% CI : 1.42.1); and who had
2 living sons (OR = 2.2; 95% CI : 1.14.4). Muslim and other religious women were less likely than Hindu women to adopt contraception (OR = 0.5; 95% CI : 0.40.6). Also, the PSU level availability of all weather road was positively associated with contraceptive adoption (OR = 1.4; 95% CI : 1.11.7). The PSU level variance, which is the unexplained PSU level variation after controlling for the considered characteristics, was significantly higher. The simulation results revealed that public health education (a TV message) was found to be more effective among less educated women. The PSU level availability of all weather road was as effective as public health education. Similar results were evident from the analysis of second data set (model II) with the noticeable finding that those whose last child is surviving are most likely to adopt contraception (OR = 8.82; 95% CI : 1.0177.38).
Conclusions These results reveal that the survival status of the last child has a marked effect on the adoption of contraception in UP. They further support the idea that public health education (a TV message) is more effective among less educated women. Also, the PSU level presence of all weather road is equally effective. Consideration of higher level variables provides not only more accurate results but also important public health clues to help the policy planners.
Keywords Multilevel analysis, hierarchical, currently married, post-partum amenorrhoea, significant, PSU level
Accepted 30 September 1999
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Introduction |
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Raising contraceptive prevalence is viewed as one mechanism to lower fertility levels and eventually reduce population growth. However, despite the efforts of the National Family Planning Program to increase contraceptive uptake, the national average remains at 40.6%.2 As India's largest state, UP merits special attention from the family planning programme because of its high contribution to the Indian population growth and also has the lowest current contraceptive adoption (19.8%) among currently married women (other than Nagaland, 13.0%). This justifies USAID's special efforts in UP: (i) the Innovations in Family Planning Services (IFPS) project;4 (ii) the UP District Level Baseline Surveys;5 (iii) the PERFORM Evaluation System project;3 and (iv) the Male Reproductive Health Survey (MRHS),6 along with other operation research programmes.
Contraceptive use is the result of interactions among a complex set of demand and supply aspects of family planning. Even the most recent research does not draw clear conclusions as to which aspects are most effective.7,8 The answer is likely to be very region-specific. A number of international, national and voluntary research organizations remain committed to data gathering and utilization. Considering secondary and/or primary data, a number of publications912 based on micro/macro data analysis are available mainly dealing with differentials, regional variations and its determinants. They have emphasized the need for regional studies. Since it is not clear what factors are most effective in achieving the goal of higher contraceptive uptake, especially in UP, there is a need to understand the epidemiology.
In many areas of public health research including contraceptive adoption, the data structures are often hierarchical in nature. Until recently, there has been generally two classical statistical procedures to deal with them. The first is to disaggregate all higher order variables to the individual level and carry out the analysis at individual level. Thus, the assumption of the independence of observations that is basic to classical statistical technique becomes invalid. On the other hand, the second is to aggregate individual level variables to a higher level and do the analysis at the higher level. Thus, all the within-group information, which may account for as much as 80% or 90% of the total variation, is discarded before the analysis is carried out. As a consequence, relations between aggregated variables are often much stronger giving distorted interpretation at the individual level.1320 Also, a number of qualitative/ behavioural characteristics may not be either available or adequately measured, particularly those as perceived by the client/community. Almost all survey data sets involve some type of cluster sampling where groups of individuals from randomly chosen segments of a population are interviewed. However, generally, statistical methods are used that assume that the data were obtained from a simple random sample. A number of recent papers in the epidemiological literature contend that ignoring the above issues (unobserved community effects) in data analysis produces downward biases in the standard errors of the estimated parameters which leads to erroneous estimates of the impact of individual variables.1517 However, these issues, which are considered to be of great importance in epidemiological studies, are rarely addressed in analysis.
This study deals with relatively newly developed multilevel analysis that takes hierarchical structure into account and makes it possible to incorporate variables from all levels which leads to correct analysis and proper interpretation of the data. Unobserved community effects are also taken into account. It also takes into account the relative importance of a woman's individual characteristics and those of the area in which she lives which gives important clues to strengthening ensuing public health programmes. The main objectives of the present study were: (i) to work out models for contraceptive adoption in UP using a relatively new technique, Multilevel Analysis; and (ii) to use the developed models in simulation analysis leading to better epidemiological understanding.
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Materials and Methods |
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The NFHS in UP was conducted between 10 October 1992 and 22 February 1993, in 242 selected rural area Primary Sampling Units (PSU) and 96 urban area PSU. In rural areas, the 1981 Census list of villages served as the sampling frame, and a two-stage sample design was adopted with the selection of villages (PSU) as the first stage and households in selected villages as the next stage. In urban areas, the list of Census Enumeration Blocks provided by the Registrar General of India for 1991 served as the sampling frame. Accordingly, a two-stage sample design was adopted: selection of Census Enumeration Blocks (PSU) followed by selection of households in each of the selected PSU. The selection of PSU was systematic with probability proportional to size (PPS). The households to be interviewed were selected from the household lists using systematic sampling with equal probability. On an average, in a rural area, 30 households were selected from PSU with <300 households, and 40 from larger PSU with 300 households. In urban areas, on an average, 20 households per PSU were selected. In total, 11 438 ever-married women aged 1349 from 10 110 households were interviewed. More details are available in the state level report for UP released in October 1994.21
For the present study, two data sets were used: (i) all currently married women who were neither pregnant nor had continuing post-partum amenorrhoea (PPA); and (ii) all currently married women with at least one child who were neither pregnant nor had continuing PPA. Only women whose records were complete for all variables considered in the analysis were included. There were, however, very few women with incomplete records (less than one per thousand). Accordingly, 7851 (set I) and 6748 (set II) currently married women were included in analysis who were neither pregnant nor had continuing PPA. In addition, the second set of women had at least one child making it possible to assess the impact of survival status of the last child on contraceptive use.
In view of poor contraceptive adoption in UP with the majority of couples going for sterilization and also taking into account the results from a series of exploratory models, in order to have meaningful observations, current contraceptive use (including sterilization, modern methods etc) was considered a dependent variable. Similarly, taking into account theoretical considerations as well as the results from a series of exploratory models, individual level variables considered in the analysis were: woman's present age in years; length of marriage in years; residential status (rural/urban); religion (Hindu/others); type of house (kuchcha + semi-pucca/pucca [built from bricks and mortar]); electricity in the house (no/yes); hearing a TV message about contraception (no/yes); working status (no/yes); education (illiterate/primary school/middle school/high school); husband's education (illiterate, 14/57/810/
11 years); number of living sons (0/1/2/
3) and number of ever born male children (0/1/2/3/
4). The survey, in addition to the standard set of questions on individual level socio-demographic and other variables, included higher level questions on households/PSU/ district/state. Since the higher level data were being organized by Macro International (USA), the available data did not allow us to consider district level variables. However, PSU level data could be obtained and considered in the analysis. These were: availability of all weather road in the locality (no/yes); distance of locality from primary school (
2 km/<2 km) and distance of locality from health centre (
3 km/<3 km). After much exploration with alternative forms, it was decided that these forms of the variables were most appropriate. In this study, household level characteristics were not considered because the sample sizes within each household were too small to permit meaningful estimates. In the analysis of the second data set an additional variable, namely survival status of last child, was also included.
Methodology
As a special case of the general framework,14,18 and as used by others,12,17 this study used multilevel logistic regression to estimate the individual and area factors that influence current contraceptive use. The model fitted takes the form
log[pij/(1 pij)] = xij a + wj b + uj + eij
where pij is the probability that woman i in PSU j uses some method of contraception; xij and wj are vectors of individual and PSU level characteristics respectively; and a and b are vectors of estimated parameter coefficients. uj (~N(0, u2)) is an error term at the PSU level and eij (~N(0,
2)) is an error term at individual level. This model is an example of what is called a two-level modelindividual women (level 1) are nested within PSU (level 2). The purpose of this approach is to control for the correlation between women in a particular PSU. The PSU error term (uj) in the model gives an indication of the variation after controlling for the individual level characteristics. In this study, the model is estimated using the computer program MLn for multilevel analysis.22 However, univariate analysis including rate ratio (RR) and 95% CI was carried out using STATA software.23 The results were considered significant at 5% level of significance.
Under the simulation analysis using models I and II, the estimated probabilities of contraceptive use for a particular variable were calculated by holding all other variables at their mean. Similarly, these probabilities for a particular combination of variables are also calculated by holding all remaining variables at their mean.
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Results |
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Table 1 shows the percentage of contraceptive users in every sub-category of variable in relation to data set I. This Table also displays the unadjusted RR and its 95% CI estimate of contraceptive use in various categories of a variable compared to the reference category. Table 1
clearly indicates that urban dwellers were more likely to use contraceptives than their rural counterparts (RR = 2.18; 95% CI : 2.012.36). Similarly, women living in pucca houses (RR = 2.41; 95% CI : 2.232.61), who had electricity (RR = 2.11; 95% CI : 1.952.29), and who received a TV message on contraception (RR = 2.70; 95% CI : 2.522.90), were more likely to use contraceptive methods. Also, contraceptive adoption was highly associated positively with the number of living sons and number of ever born male children. Husband's education also had a significant positive association with contraceptive adoption. Working women had a significantly higher chance (14%) of contraceptive adoption but women who were not Hindu had 46% less chance (significant) of contraceptive use (Table 1
). The PSU level characteristics such as presence of all weather road (RR = 1.89; 95% CI : 1.742.05); primary school
2 km (RR = 1.65; 95% CI : 1.501.81); and health centre
3 km (RR = 1.58; 95% CI : 1.441.74) showed significant positive relationships with contraceptive adoption.
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Conclusions |
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This study provides the central finding that those women whose last child is surviving, were nine times more likely to adopt contraception. However, looking at the 95% CI, the very high upper confidence limit indicates instability in the adjusted RR. This may be because in the north Indian population until a couple has achieved at least a living son, a surviving last daughter does not encourage contraceptive adoption. The instability in view of the very high upper confidence limit is also evident from the non-significant results related to number of ever born male children in model II; contrary to the significant results in model I. Also, those likely to adopt contraception had 2 living sons; were educated to high school level and above; had literate husbands with schooling of
11 years; and were exposed to a TV message. Muslim and other religious women were less likely than Hindu women to adopt contraception. The simulation results further reveal that public health education (a TV message) was found to be more effective among less educated women.
The PSU level availability of all weather road was positively associated with contraceptive adoption. This may be attributed to the fact that availability of all weather road may be an indication of supply of as well use of facilities related to family welfare programme and health. Further, this was as effective as public health education. The PSU level variance, which is the unexplained PSU level variation after controlling for the considered characteristics, was found to be significantly higher. In summary, there is need to consider more PSU level variables. Also, consideration of district level variables in the analysis may further refine the results.
These analyses can not fully identify the pathways by which these variables influence contraceptive use. For example, family planning programmes may not be targetted so strongly in areas with high levels of religious practice because of the antipathy of religious and local leaders, or an aversion to change may exist among the population.12 However, these analyses do suggest that contraceptive adoption depends on the current levels of willingness to accept and to institute change in a community, which may be affected by literacy and utilization of health facilities.
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Acknowledgments |
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References |
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