Women’s Health and Pregnancy Outcomes: Do Services Make a Difference?* March 2001 Elizabeth Frankenberg Duncan Thomas *Elizabeth Frankenberg, RAND, 1700 Main Street, Santa Monica, CA 90407; E-mail: efranken@rand.org Duncan Thomas, RAND and University of California at Los Angeles; Email: dt@ucla.edu This work was supported by NICHD grants P50HD12639, R29HD32627, and P01HD28372, by NIA grant P30AG12815, and by the POLICY Project We gratefully acknowledge the comments of Bondan Sikoki, Wayan Suriastini, and participants at seminars at the University of California at Los Angeles, the Gadjah Mada University, the University of Maryland, the University of Michigan, the University of Pennsylvania, and the University of Washington ABSTRACT We use data from the Indonesia Family Life Survey to investigate the impact of a major expansion in access to midwifery services on health and pregnancy outcomes for women of reproductive age Between 1990 and 1998 Indonesia trained some 50,000 midwives Between 1993 and 1997 these midwives tended to be placed in relatively poor communities that were relatively distant from health centers We show that additions of village midwives to communities between 1993 and 1997 are associated with a significant increase in body mass index in 1997 relative to 1993 for women of reproductive age, but not for men or for older women The presence of a village midwife during pregnancy is also associated with increased birthweight Both results are robust to the inclusion of community-level fixed effects, a strategy that addresses many of the concerns about biases because of nonrandom program placement Decline in mortality is among the most fundamental demographic changes experienced by developing countries over the past half-century Today, individuals are leading longer and healthier lives than did their parents and grandparents In part these changes reflect investments in human resources by both individuals and governments In virtually every developing country, governments have built, stocked, and staffed schools, health facilities, and family planning clinics, albeit with varying degrees of success Although clinical studies have demonstrated that some health interventions in fact improve health, researchers have long debated about the contribution of public health investments to health improvements and mortality decline Most macro-level studies conclude that the effect of public spending on health is small (Filmer and Pritchett 1999; Musgrove 1996) At the micro level, some studies have concluded that investments in providing public health services have a positive causal effect on health outcomes (Caldwell 1986; Jamison et al 1993) The majority of studies, however, indicate that increases in public spending have little or no impact on health; in some cases, public-sector investments are even associated with poorer health outcomes (For a discussion, see Strauss and Thomas 1995.) At least two critical problems have plagued this literature The first, and perhaps the more difficult to address, is that public health investments are not likely to be located at random with respect to health outcomes For example, if programs are carefully targeted they will be placed where health outcomes are poor and/or utilization of services is low If all program placement decisions are based on observable characteristics that are controlled in an evaluation of the program, such targeting poses no conceptual difficulty Yet insofar as program placement is associated with characteristics that are not observed, failure to take account of nonrandom placement will generally lead to biased estimates of the impact of the investment (Angeles, Guilkey, and Mroz 1998) Rosenzweig and Wolpin (1986), for example, show that in a cross-section regression, children’s nutritional status is negatively associated with exposure to public health programs in Laguna, The Philippines In contrast, these authors find a positive and significant effect when they examine how changes in nutritional status respond to changes in exposure to public health programs They attribute the negative correlation in the cross-section estimates to the nonrandom placement of programs A second major stumbling block in this literature is the lack of adequate data, on several dimensions Measurement of health investments is not straightforward; this surely contributes to the weakness of evidence in the macro literature In the micro literature, the shortcomings of community-level data on the accessibility and quality of health services that can be linked to individual-level information are well known (Akin, Guilkey, and Denton 1995; Pullum 1991; Thomas and Maluccio 1996), although recent advances in geographical information systems have facilitated the combination of administrative data with sociodemographic surveys (Entwisle et al 1997) Detailed community-level data linked to individual-level data are not always sufficient: the application of methods that control community- or individual-specific unobservables requires repeated observations on health outcomes, and very few longitudinal surveys contain that information on respondents as well as on the health services and other services to which they have access We use data from a new, extremely rich longitudinal survey from Indonesia to evaluate whether government efforts to provide health care have an impact on the populations targeted by the programs Specifically, we consider the Village Midwife program, which was initiated in the 1990s and is estimated to have posted some 50,000 midwives throughout the country (Gani 1996; Kosen and Gunawan 1996; Sweet, Tickner, and Maclean 1995) Our goal is to provide evidence on the effectiveness of this large and important community-based public health service intervention that is targeted explicitly to reproductive-age women in underserved communities Our results are of general interest because these types of programs have been implemented in many developing countries To measure the effect on health status of the introduction of a new health worker in a community, we draw on the “quasi-experiment” that occurred in Indonesia by comparing changes in health status in communities that gained a health worker with such changes in communities that did not We recognize that unobserved factors may influence the introduction of a health worker to a community, which would cause bias in these “fixed-effects” estimates of the impact of health workers on health outcomes; thus we take an additional step in the analysis Because the health workers are midwives who were trained primarily to serve women of reproductive age, we contrast the impact on the health of these women (the “treated”) with that of other adults (the “controls”) who live in the same community into which the midwife was introduced Our main results focus on the effects of introducing a village midwife on a general measure of adults’ health, the body mass index (BMI) After controlling community-level heterogeneity, we find that among reproductive-age women, BMI increases significantly in communities that gained a village midwife and that the increase is substantively important In contrast, men and older women (our “control” groups) not experience as large an increase in BMI For women of reproductive age, the benefits of access to midwives extend to pregnancy outcomes: we also find that the introduction of a midwife is associated with increases in birthweight We conclude that the expansion of the Village Midwife program has yielded significant improvements in health, particularly for women of reproductive age BACKGROUND Notwithstanding the economic crisis of the late 1990s, socioeconomic development in Indonesia has improved substantially over the past three decades From 1967 to 1997 Indonesia’s per capita gross domestic product (GDP) increased by almost 5% per year At the same time, Indonesia achieved nearly universal enrollment in primary school and substantial increases in secondaryschool enrollment Since the early 1960s, several indicators of health status in Indonesia also have shown major improvements The infant mortality rate has declined steadily, and by the mid1990s life expectancy surpassed 60 years Maternal mortality, however, had not shown such impressive gains as of the early 1990s, and the Indonesian government expressed considerable concern about this dimension of health outcomes At 390 to 650 deaths per 100,000 live births, this rate was the highest in any of the ASEAN nations (Handayani et al 1997; Mukti 1996; UNICEF 2000a, 2000b) In fact, for much of the 1990s Indonesia’s statistics for maternal mortality were on a par with those in India and Bangladesh, even though the per capita GDP in Indonesia was about 50% higher than in India and about twice as high as in Bangladesh (Sarwono, Mundiharno, and Fortney 1997) To address poor maternal health, the Ministry of Health (MOH) embarked on an ambitious program to make midwifery services more widely available by training midwives and posting them to villages throughout Indonesia (Handayani et al 1997; Kosen and Gunawan 1996; MOH 1994) Between 1990 and 1996 the Government of Indonesia planned to provide a midwife in every nonmetropolitan village or township (MOH 1994) Midwives typically were recruited from three-year nursing academies and received one additional year of midwifery training (Sweet et al 1995) By 1998, 54,000 midwives had been trained; between 1986 and 1996 the number of midwives per 10,000 population increased more than tenfold from 0.2 to 2.6 (Hull et al 1998; MOH 2000; Reproductive Health Focus 2000) Once assigned to a community, the midwives are paid a salary by the Government of Indonesia for three to six years (Hull et al 1998) They maintain a public practice during normal working hours and are allowed to practice privately after hours It is expected that midwives will build up a client base while working for the government; thus, when their contract ends, they can maintain their practice in the village without a government salary (Gani 1996; MOH 1994) The role of the village midwife, as described by the Indonesian MOH, suggests that she will affect health status, particularly of reproductive-age women Her duties include promoting community participation in health, providing health and family planning services, working with traditional birth attendants, and referring complicated obstetric cases to health centers and hospitals She is to serve as a health resource in her community, actively seeking out patients and visiting them in their homes rather than waiting passively until they come to her (MOH 1994) These activities bring a village midwife into contact with a wide array of community residents in a variety of settings, and provide her with opportunities to advise clients on nutrition, food preparation, sanitation, and other health-promoting behaviors Village midwives provide general services in addition to those oriented toward maternal and well-baby care, as supported by research in central Java (Mukti et al 1997) On the basis of interviews, record abstraction, and client observations with 19 village midwives, the study finds that although reproductive-age women are the primary clients, midwives also treat nonobstetric patients, including men Additional evidence about the role of village midwives comes from interviews with 157 village midwives, which were conducted as part of the Community and Facility component of the Indonesia Family Life Survey (IFLS) in 1997 (described further below) Table summarizes some of the results from those interviews In regard to service provision, the village midwives offer their communities more than prenatal care, delivery assistance, and family planning; about half also provide child immunizations The great majority of village midwives provide more general curative care, and stitch wounds About one-third say they can incise and drain abscesses Almost all village midwives dispense medications such as antibiotics, cough medicine, vitamins, and supplements of micronutrients such as iron and Vitamin A The comprehensiveness of services offered by village midwives suggests some of the pathways through which availability of a village midwife may improve health For example, if a village midwife provides curative care, her presence may reduce durations of illness from diarrheal and respiratory diseases and thus may limit the weight loss associated with such illnesses Because of the midwife’s years of health training and her ability to offer an array of curative and preventive services, coupled with nutrition education and distribution of vitamins and micronutrients, her arrival in a community may well lead to improvements in her clients’ nutritional status The Village Midwife program builds on the public health system of clinics and outreach activities established in Indonesia during the 1970s and 1980s The backbone of this system is the community health center (puskesmas) The health center provides an array of services and is a basic source of subsidized outpatient care Health centers generally are headed by a doctor, who oversees a midwife and various paramedical workers (MOH 1990) In better-off areas the center’s staff may include several doctors, as well as one or two dentists Each subdistrict (kecamatan), consisting of 20 to 40 villages or townships, has one or more health centers Staff members of the health center, in conjunction with family planning fieldworkers, are responsible for conducting outreach activities, such as supervision of posyandus (neighborhood health posts), within the villages and townships in their catchment area The posyandu is held monthly and is attended by children under five and their mothers It is staffed by neighborhood volunteers and (if possible) by staff members from the health centers or by family planning fieldworkers (The latter also provide contraceptive supplies to workers from the health centers and to posyandus.) When health workers attend, the posts generally provide prenatal care, immunization, and contraceptive injections (Kosen and Gunawan 1996) When helath workers not attend, services are limited to provision of vitamins and oral rehydration solution, nutritional screening, and oral contraceptives Private practitioners also are an important source of health care in Indonesia Private services are more widely available in urban than in rural areas, but because employees of the health center generally offer private services in off-hours, private practitioners are found in rural areas as well (Brotowasisto et al 1988; Gani 1996; World Bank 1990) CONCEPTUAL FRAMEWORK In Indonesia as in other countries, improvements in health outcomes and expansion in health services have occurred simultaneously This fact, however, does not tell us whether the investments in services caused the improvements in health It is plausible that other factors that have changed, including economic growth, are correlated both with improvements in health and with greater access to services In an effort to isolate the role of health services, a number of studies have contrasted spatial variation in program availability or strength with spatial variation in health outcomes Yet a correlation between access and health outcomes at a point in time does not identify the direction of causality Services may be provided in a particular location in response to demand for those services, or people who want services may move to places where they are provided (Rosenzweig and Wolpin 1986, 1988) Either scenario yields a spurious correlation between access to services and health outcomes because the relationship is governed by a common (unobserved) factor It is also possible that governments target particular types of communities for interventions Targeting will not bias estimates of the effects of the intervention if it is based on characteristics that are observed and controlled in a regression context If targeting is based on unobserved characteristics, however (or if the full set of characteristics used for targeting is not controlled in the regression), and if those unobserved characteristics are correlated with the outcome of interest, estimated effects of the intervention will be biased The direction of that bias is ambiguous To illustrate, imagine that government services are provided in communities that are underserved by private providers and that health status in those communities is relatively poor, everything else held equal Unless all characteristics that underlie the placement of the program are controlled, the estimated impact of the intervention will be biased negatively, and the bias will be greatest for the interventions targeted to the people who need them most This issue of selective program placement is important in the context of health policies in Indonesia (Frankenberg 1992; Gertler and Molyneaux 1994; Pitt, Rosenzweig, and Gibbons 1993) In theory, these complicating issues are sidestepped by social experiments involving random assignment of subjects to treatment and control groups Although such experiments have produced valuable findings regarding some policy questions (see, for example, Berggren, Ewbank, and Berggren 1981; Dow et al 1999; Faveau et al 1991; Newhouse 1994), they have their own drawbacks They tend to be small in scale and to involve homogeneous populations; thus their generalizability is limited (Ewbank 1994) They are typically expensive, take a long time to complete, and can be difficult to implement In some instances, experiments induce behavioral responses (such as migration to areas that are served in the trial) that substantially complicate evaluation of the intervention In our view, observational data are an important complement to evaluations of interventions based on randomized trials Of course, studies based on observational data cannot ignore the complicating issues discussed above We adopt a quasi-experimental approach to evaluate the effects of an expansion in access to midwifery services and health outcomes in Indonesia Using longitudinal household survey data, we compare an individual’s health before the introduction of a midwife in a community with the same individual’s health after the intervention In doing so, we sweep out of the model all factors that are fixed at the individual and community level and enter the model additively, including any fixed characteristics that are correlated with the placement of midwives This “fixed-effects” model has been used extensively in the program evaluation literature (for a discussion, see Heckman and Robb 1985) We are contrasting changes in health of the “treated” with changes in health of a control group, namely respondents in communities where midwives were not introduced: ∆θi = α + βMc + εic , where ∆θi is the change in health of individual i and Mc is an indicator variable for whether or not a village midwife was introduced in community c Time-varying unobserved heterogeneity that affects changes in health is captured in εic The intercept, α, reflects changes in health of the population between the two waves of the survey that are not related to the introduction of a midwife β measures the difference in changes in health status of those living in communities where a midwife was introduced relative to other communities This is an “average treatment effect,” calculated over all people living in the “treated” communities The Village Midwife program was conceived out of concern for maternal mortality Because reproductive-age women are likely to benefit most from the introduction of a midwife, we refine the treatment group to include only those women in the treated communities We compare the effect of introducing a midwife on their health with the effect on the health of men of the same age living in the same communities: ∆θi = α1Iipf + α2Iipm + β1Mc * Iipf + β2Mc * Iipm + εic , where Iipf is an indicator variable for prime-age females and Iipm is defined analogously for prime-age males The coefficient on the interaction between the prime-age female and midwife indicator variables, β1, is an estimate of the change in the health of a prime-age woman in a “treated” community relative to the change in health of a similar woman in a community where a midwife was not introduced If the introduction of a midwife in a village is uncorrelated with time-varying unobserved heterogeneity, εic , then this model will provide an unbiased estimate of the effect of the program Below, however, we show that midwives are more likely to be introduced in poorer communities with little infrastructure If changes in health differ between poorer and better-off communities, negatively for the other demographic groups The negative correlation is significant for older men We not interpret the negative effects as indicating that midwives hurt everyone except young women, but rather that these results capture the “program placement” effects; thus they reflect the fact that midwives are allocated to communities where improvements in health status are unlikely As discussed above, the difference-in-differences address this concern The pertinent estimates, reported in panel C, indicate that the presence of a midwife is associated with significantly improved health in women of reproductive age relative to the health of other demographic groups This result persists when we include observable characteristics of the respondents and their communities (Model 3), although the differential effect on older and younger women is slightly smaller (and significant only at 10%) The fact that residence in a community that gained a village midwife is associated with improved BMI only among prime-age women suggests that the relationship is causal If placement of village midwives occurred in communities where nutritional status improved for other reasons, one would expect a positive correlation with the introduction of a village midwife for all demographic groups Our final specification (Model 4) goes one step further We include a community-specific time trend to ask whether, within communities that gained a village midwife, the health of reproductive-age women improved more than that of other adults The difference-in-difference estimates (panel C) indicate that the answer is affirmative in regard to men: BMI improved by about 0.20 more for reproductive-age women in these communities than for older or younger men, and these differences are significant Although the difference is slightly larger for older men, in keeping with our expectation that spillover benefits of a midwife would be smallest for this group, the difference between the effect on younger and older men is small and not significant Midwives, however, apparently are associated with spillover benefits for older women: although the latter benefit less than women of reproductive age, that difference-indifference is not significant 17 Inferences drawn from the difference-in-difference results are remarkably consistent across the three empirical specifications The evidence suggests that unobserved heterogeneity contaminates the estimates, particularly among older respondents; thus we are inclined to place the greatest weight on the estimates in Model Because we are using observations on individuals at two points in time, we cannot explore dynamics underlying the effect of a midwife in a community Rather, in a linear and additive framework, we are measuring the cumulative effect, by 1997, of a midwife introduced to the community between 1993 and 1997 If all the gains in BMI associated with the introduction of a village midwife accrued to people with a BMI in the normal range, the benefits of expansion of the village midwife would not be obvious Therefore we reestimated the models, restricting the sample to respondents whose BMI was 21 or below in 1993 (roughly half the sample) Panel D of Table reports the estimated difference-in-differences, which are larger than for the entire sample.4 These results indicate that individuals with lower BMI benefit more from the introduction of a village midwife.5 The results indicate that increased access to village midwives between 1993 and 1997 has had a positive impact on women’s health, particularly for women of reproductive age These effects are greater for women whose BMI was low in 1993 Because no similar effect occurs for males, we conclude that the effect for women does not reflect placement of midwives in communities where health would have improved in any case We cannot rule out the possibility that midwives were placed in communities where young women’s health would have improved relative to men’s Although that scenario strikes us 4We prefer this to an alternative specification that focuses on whether a respondent is above or below a particular cutoff point The 1993 IFLS data contain evidence of a positive association between BMI and greater functioning, better health, and reduced morbidity among people with BMI below 21 (Strauss and Thomas 1998) Moreover, for reproductive-age women at risk of becoming pregnant, a low BMI is a particular disadvantage because it increases the amount of weight they must gain to achieve a healthy pregnancy (Krasovec and Anderson 1991) A discrete outcome would discard much of the information about improvements in health and would tend to bias the estimates toward not finding program effects that exist 5We also explored whether gaining a village midwife particularly benefits women who are similar to the midwife in age and education, as suggested by Rogers and Solomon (1975) with respect to traditional midwives Our results show that the midwife’s age relative to her client’s has no impact on her effectiveness Midwives, who themselves are quite well educated, appear to exert a slightly larger effect on the BMI of women with little education; this point suggests that socioeconomic similarity between a midwife and her potential clients is not the force governing her effectiveness 18 as unlikely, we can explore its relevance by assessing whether the timing of the introduction of a midwife to a community affects women’s reproductive health Therefore we now contrast the birthweight of babies born before and after a midwife is introduced into a community Midwives and Birthweight We use birthweight as a measure of pregnancy outcome Birthweight is not only a marker of a successful pregnancy; it also affects the child’s subsequent health Data from the Philippines have shown that birthweight is correlated both with survival during the neonatal period and with the risk of stunting in the first two years of life (Adair and Guilkey 1997; Popkin et al 1993) In both rounds of the IFLS, women were asked to provide detailed accounts of all pregnancies that occurred in the five years before the survey, including birthweight (if the baby was weighed) We pool the data from IFLS1 and IFLS2 to obtain information on 5,155 pregnancies (reported by 3,445 women) that occurred between 1988 and 1997 and ended in live births The mothers reported birthweights for a total of 3,315 births (64% of all births) Mean birthweight was 3,162 grams; 8.5% of infants were reported as weighing less than 2,500 grams (the standard cutoff for low birthweight) Another 6.3% were reported as weighing exactly 2,500 grams The distribution of reported birthweights in the IFLS data does not suggest unusually high or low proportions of low-birthweight babies relative to those in other developing countries or relative to other data from Indonesia (Boerma et al 1996) We observe heaping on weights (in kilograms) that end in or 5, as has been observed in other data sets from developing countries with retrospectively reported birthweight data (Robles and Goldman 1999) The heaping indicates measurement error in the reported birthweights; such error, for our purposes, will inflate standard errors but will not bias the estimated effect of a midwife We also examined the correlates of reporting a birthweight (results not shown) The probability that a birthweight is reported increases with the mother’s age (up to age 35) and, as one might expect, with level of education and with household per capita expenditure Birthweights also are much more likely to be reported for first births and for infants delivered either in a medical setting or at home with the attendance of a biomedically trained assistant than for infants delivered at home with the assistance of traditional birth attendants Birthweight is 19 more likely to be reported for more recent births, but there is no association between the presence of a village midwife in the community during the pregnancy and whether a birthweight was reported (This finding holds across all communities and in only those communities that had a village midwife by 1997.) In analyzing the relationship between birthweight and access to a village midwife, we used data from the IFLS2 Community-Facility Survey on the number of years a village midwife had been present in the community, combined with information on the time of conception, to construct a variable indicating whether a village midwife was present in the community during the pregnancy In communities that had received a village midwife by 1997, 63% of pregnancies occurred before the village midwife arrived; 37% occurred after her arrival This withincommunity variation in exposure to the program can be used to estimate the effect of the village midwife’s presence on birthweight, net of aspects of the community that are fixed over time and affect both the allocation of midwives and pregnancy outcomes Table presents results from these fixed-effects analyses of birthweight The first column provides the coefficients for the relationship between birthweight and the presence of a village midwife during the pregnancy, with no controls Column adds a variety of pregnancy-specific, mother-specific, and community-specific controls For each pregnancy we include markers for whether the pregnancy was the woman’s first and for the infant’s sex, as well as an indicator of year of birth We also include measures of the mother’s height, her educational level, and the (log of) per capita household expenditure At the community level, we include distance to public and private health services, whether roads are paved, presence of a public phone, and monthly visits from health center staff members Children born before October 1995 were matched to the 1993 community data; those born in October 1995 or later were matched to the 1997 community data In both specifications, birthweights are significantly greater in a community after a midwife is introduced than before To attribute this finding to a program placement effect, one would have to argue that midwives were allocated to areas where birthweight would have improved even in the absence of midwives; this seems very unlikely 20 To capture any time trends in birthweight, we also include in Model a term for the year when the baby was born It is potentially difficult to disentangle an effect of time on birthweight from an effect of the presence of village midwife because village midwives were phased into communities over time Thus, as year of birth increases, so does the probability that a village midwife was present in the community The coefficient on year of birth does not indicate evidence of a significant time trend in birthweights We also estimated the time trend for birthweight separately by whether a village midwife was ever posted to the community, but the time trends were not statistically significant for either type of community; nor did the trends differ from one another CONCLUSION Both the results for change in body mass index and the results for birthweight suggest that gaining access to a village midwife is associated with improvements in health outcomes for women of reproductive age, and for their babies The impact of the midwife’s presence on adult health status is limited to women, primarily those between ages 20 and 45 In communities that gained a village midwife, the change in reproductive-age women’s BMI is significantly larger than men’s For reproductive-age women whose 1993 BMI was 21 or lower, the difference-indifference estimates suggest that the addition of a village midwife was accompanied by an increase in BMI equaling at least 0.2 If 0.2 is added to the 1993 BMI of women of reproductive age, the percentage whose BMI is less than 21 declines from 44% to 41.3% (a decrease of 6%), while the percentage whose BMI is less than 18.5 declines from 12.8% to 10.9% (a decrease of nearly 15%) The estimated effect of gaining a village midwife is to increase birthweight by about 80 grams The fraction of infants who benefit by a gain of 80 grams depends on the range of weights for which a gain of 80 grams is assumed to improve health About 8.5% of the babies for whom weights are reported weighed less than 2,500 grams It is likely that all of these infants would have been at least somewhat better off if they had been 80 grams heavier at birth, even if they remained below the 2,500-gram threshold for normal birthweight In addition, a gain of 80 21 grams is likely to improve the health of the babies whose weight was reported as exactly 2,500 grams (6.3%) and who therefore were at the threshold of normal birthweight, and for babies just above the threshold but still relatively light In this paper we have focused on developing and implementing a statistical strategy for estimating the size, direction, and statistical significance of the association between access to village midwives and health outcomes Our results reveal that gaining a village midwife has a effect on the body mass index of women of reproductive age This effect is larger for women whose BMI was low in 1993 We also find 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