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The socio-economic determinants of maternal health care utilization in Turkey
Social Science & Medicine 50 (2000) 1797±1806
www.elsevier.com/locate/socscimed
The socio-economic determinants of maternal health care utilization in Turkey Yusuf Celik a, 1, David R. Hotchkiss b,* a
School of Health Administration, Hacettepe University, Ankara, Turkey Department of International Health and Development, School of Public Health and Tropical Medicine, Tulane University, 1440 Canal Street, Suite 2200, New Orleans, LA 70112, USA
b
Abstract The purpose of this study is to investigate the individual-, household- and community-level factors that aect women's use of maternal health care services in Turkey. The data used for the study come from the 1993 Turkey Demographic and Health Survey (TDHS), a nationally representative survey of ever married women 15 to 49 years of age. In order to assess the impact of socio-economic factors on maternal health care utilization, we use logistical regression techniques to estimate models of the prenatal care use and birth delivery assistance among women who have had at least one birth in the three years prior to the survey. Separate models are also estimated for urban and rural women. The results indicate that educational attainment, parity level, health insurance coverage, ethnicity, household wealth and geographic region are statistically signi®cant factors that aect the use of health care services thought essential to reduce infant and child mortality rates. The results of the model are used to provide insights for both micro- and macro-level planning of maternal health service delivery. 7 2000 Elsevier Science Ltd. All rights reserved. Keywords: Maternal health services; Health care utilization; Turkey
Introduction Over the past two decades, Turkey has made remarkable progress in improving health outcomes among its population, particularly among children and pregnant women. From 1983 to 1993, for example, the infant mortality rate dropped by 35% and from 1974 to 1995, the maternal mortality rate decreased by 53%
* Corresponding author. Tel.: +1-504-585-6157; fax: +1504-584-3653. E-mail addresses: [email protected] (Y. Celik), david. [email protected] (D.R. Hotchkiss). 1 Tel.: +90-312-311-5506; fax: +90-312-309-3625
(Ministry of Health et al. 1994; Ministry of Health, 1997a). Although there have not been any careful studies of this mortality decline in Turkey, increased purchasing power among households, improved educational opportunities and improved health care services may have been largely responsible. While this health trend is encouraging, the current levels of infant and maternal mortality remain unacceptably high. In 1993, the infant mortality rate was estimated to be 53 per 1000 live births and in 1995, the maternal mortality rate was estimated to be 100 per 100,000 live births. Moreover, inequities by urban/ rural status, by geographic region and by ethnicity remain large. For example, infant mortality among
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rural infants is estimated to be 1.5 times higher than among urban infants (Ministry of Health et al., 1994; Ministry of Health, 1997a; Tuncbilek, 1988). One explanation for poor health outcomes among women and children concerns the nonuse of modern health care services by a sizable number of women. For example, in 1993, 37% of children in Turkey were born to mothers who did not use prenatal care and 24% of births were not assisted by medical professionals (Ministry of Health et al., 1994). Many studies in both developed and developing countries suggest that prenatal care is an important determinant of improved health outcomes among infants (Tuncbilek, 1988; Ahmad et al., 1991; Boerma and Bicego 1992; Adetunji, 1994; Forste, 1994; Panis and Lillard, 1994; Panis and Lillard, 1995) and that birth delivery assistance from a trained and well-equipped provider is necessary to reduce maternal mortality (Maine and Rosenfeld, 1999). Although improvements in maternal health care utilization are essential for further progress in this area, there have not been any studies that identify the causal factors that lead to the improved use of services by women in Turkey. This paper seeks to ®ll this gap. Using the 1993 Turkey Demographic and Health Survey (TDHS), a nationally representative sample of women of childbearing age, we investigate the individual-, household- and community-level factors that in¯uence women to use maternal services. The analysis uses a logistic regression model of the use of prenatal care and a multinomial logistic regression model of the use of birth delivery assistance. The rest of this paper is organized as follows: the next section provides a brief overview of the maternal health care supply environment; the third section discusses the logistic regression models used in the analysis; the fourth section describes the data; the ®fth section provides the multivariate results; and the ®nal section uses the results to provide insights for policy makers responsible for planning the delivery of maternal services.
Maternal service delivery in Turkey Maternal health care services in Turkey are mostly provided by the government-run referral system, composed of health stations in rural areas, health posts in urban areas, health centers and hospitals. With the passage of the socialization law in 1964, the government began building village health stations and health posts, which now total 11,877. Each facility employs at least one midwife. Though midwifes have some responsibilities in providing preventive health care services, their most important role is to monitor the women's pregnancies, to vaccinate children in their service areas
and to provide family planning services. Maternal and Child Health/Family Planning (MCH/FP) Centers, administered by Department of Maternal and Child Health Services, are also common places where pregnant women can access care. There are 274 MCH/FP Centers in the country built for the primary purpose of improving maternal and child health status. An important characteristic of the public health care sector is the discrepancy between the Western and the Eastern regions with respect to the availability and quality of health care services (Ministry of Health, 1997b). Midwifes tend to be more concentrated in the West, the region of Turkey which is the most developed. For example, of the total number of midwives (39,551), 18.5% work in the three largest cities of Turkey Ð Istanbul, Izmir and Ankara Ð while only 14.5% work in the 23 provinces of the East region, where the level of unmet need is higher. Health care facilities are also more concentrated in urban areas than in rural areas. Because of the disparities in the distribution of health care personnel, the quality of service delivery and also because of social unrest in the East region, the utilization of services from village health stations is frequently reported to be quite low. Overall, the private sector plays a relatively minor role in the delivery of maternal health care services. The sector consists mostly of public physicians who are allowed to work in their private practices in the afternoons and part-time practitioners. Of the total number of hospital beds in Turkey, only 3.5% are within private facilities, although there are concerns about the reliability of this estimate (Tatar and Tatar, 1997). While relatively small on average, the private sector is an important source of care in large urban areas and in the Western part of the country. In rural areas, traditional birth attendants are also important sources of birth delivery care.
Statistical methods In order to estimate the eects of socio-economic factors on maternal health care utilization, two dependent variables were used in this study: the use of prenatal services from a trained provider and the use of trained birth delivery assistance. In the case of prenatal care, a dichotomous dependent variable was constructed to indicate whether or not the woman used services from a trained provider. Because the indicator is dichotomous, a logistic regression model was estimated. Logistic regression models make it possible to estimate the probability of using health care, conditional on the independent variables included in the model. The speci®cation of the prenatal care model is the following:
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log pi2 =pi1 a0 a1 Xij a2 Yij a3 Zj E1ij
1
The dependent variable is the log odds that individual i will chose alternative j relative to alternative 1, where alternative 1 is no use of prenatal care from a trained provider and alternative 2 is a consultation with trained provider, either in the woman's home or in a health care facility. The independent variables are classi®ed into three groups: individual-, householdand community-level factors, represented by the vectors X, Y and Z, respectively and the as represent the net eects of these variables on the probabilities of using health care. The term E1 represents unobserved determinants of prenatal care utilization and follows a logistic distribution. To construct the indicator of birth delivery assistance, women were classi®ed into three groups Ð those who delivered at home without trained assistance, those who delivered at home with trained assistance and those who delivered in a health care facility. Because the variable is trichotomous, the following multinomial logistical regression model was estimated: log pij =pi1 b0 b1j Xij b2j Yij b3j Zj E2ij
2
The dependent variable is the log odds that individual i will chose delivery alternative j j 2, 3 relative to alternative 1, where alternative 1 is a home delivery without the assistance of a trained provider, 2 is a home delivery with the assistance of a trained provider and 3 is a facility delivery with the assistance of a trained provider. Like the previous model, the independent variables consist of individual-, household- and community-level factors, represented by the vectors X, Y and Z, respectively. The bs vary by type of alternative and represent the net eects of the independent variables on the probabilities of choosing birth delivery assistance. The term E2 represents unobserved determinants of birth delivery choice and is assumed to be independently and identically distributed as a log Weibull distribution.
Data This data used in the study come from the 1993 Turkey Demographic and Health Survey (TDHS), a nationally representative survey of ever-married women 15 to 49 years of age. Data were collected from 6519 ever-married women on their reproductive histories, fertility, use of health care and family planning services and the health of their children. The survey also includes a wide variety of socio-economic and demographic indicators at the individual-, householdand community-level. The sample used for this study were those women who had at least one birth in the
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three years prior to the survey interview. For those who had more than one birth, only utilization behavior associated with the most recent pregnancy was considered. The rationale for only including women who gave birth during the three-year period is that mothers may not be able to accurately answer questions asked about births that occurred prior to this interval. As a result of these inclusion restrictions, our sample consists of 2002 women. Table 1 contains descriptive statistics for the two dependent variables used in the study. Of the total sample of women who gave birth in the three years prior to the survey, 69.2% received prenatal care by health care professionals including physician and trained midwife/nurses. As expected, urban women were more likely to have at least one prenatal care consultation than rural women (77.6 vs. 56.3%). With respect to the birth delivery, 65.4% reported delivering their last birth in a health care facility, 15.4% delivered at home with the assistance of a doctor, nurse, or trained midwife, or 19.3% delivered at home without the assistance of a health care professional. Rural women were found to be three times more likely to have traditional home deliveries than urban women (33.0 vs. 10.1%). Table 2 presents descriptive statistics for the independent variables. The women's characteristics that were included in the models were age at the time of the last child's birth, educational attainment and parity level. The age of the mother is considered to be one of the most important factors aecting health care utilization and child survival. In order to capture the eects of age, women were classi®ed into four groups: 20 years of age and younger (25.2%), 21±25 years old (34.1%), 26±30 years old (23.4%), or 31 years of age and older (17.3%). The reference group consists of woman 20 years of age and younger. The other individual-level characteristics included in the model were maternal education and parity level. In our sample, 26.8% of women report that they have no formal education, 56.1 have one to ®ve years of schooling and 17.1% have six years or more of schooling. Two dichotomous indicators measure parity: whether the woman's last birth was her ®rst birth (34% of woman) and whether the woman's last birth was her second birth (26% of woman). The reference category consists of woman whose last birth was her third or more. The household-level factors consist of the occupation of the household head, whether the household was covered by a health insurance plan, ethnicity and household wealth. With respect to occupation, the TDHS collected information on nine employment categories. The dummy indicator on the employment status was coded as one if the husband was primarily engaged in clerical, sales, service and skilled manual
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work and zero if the husband was primarily engaged in other activities (agriculture, household domestic work, unskilled/manual work, or did not work). Of the 2000 woman in the sample, 45% had husbands in the ®rst group while the remaining 55% had husbands in the second group. Ethnicity may also have a potentially important eect on service utilization. Respondents were grouped into three ethnicity categories: Turkish, Kurdish and others. The majority of respondents (80.5%) reported themselves as Turkish, while the remaining respondents were from other groups (16.6% Kurdish and 2.8 other ethnic groups). Health insurance coverage was also included as an independent variable thought to be a potentially important determinant of service utilization. It is expected that coverage would improve service utilization by reducing the out-of-pocket costs associated with service use. The TDHS collected information on the health insurance status of the father. Half of the total number of respondents was covered by some type of health insurance, although information on which services were covered and the level of coverage were not collected in the TDHS. Household income and assets may increase the ability and willingness of households to pay for health care services. Like all of the USAID-sponsored Demographic and Health Surveys, the TDHS did not include questions on household income. However, information on household assets was collected. In this study, we use three indicators of household wealth: car ownership, the type of sanitation facilities used by the household members and the type of ¯oor in the woman's house. Over 80% of the respondents (1617 women) reported that their household did not own a car. The type of ¯oor was categorized into two groups: natural and modern. Almost two-thirds of respondents (64.6) reported living in a house with a modern ¯oor, which we classi®ed as being constructed of cement, wood, vinyl, asphalt, ceramic, or carpet. The responses on the type of sanitation used by the household were grouped into two categories: (1) ¯ush toilet and (2) pit and
others. The majority of women resided in households that had a ¯ush toilet (54.9%). The community-level factors included in the model consist of two indicators of the location of the woman's household: urban/rural status and geographic region. As presented in Table 2, 60.3% of total respondents reside in urban areas and 39.6% reside from rural areas. With respect to region, 22.8% live in the West, 20.3% live in the South, 21.3% live in Central Anatolia, 16.1% live in the North and 19.2% live in the East region of Turkey. In Turkey, policy discussions often include the issue of the disparate utilization rates between urban and rural areas and between the eastern and western portion of the country. One of the primary aims of this study is to investigate how health care utilization varies by geographic region in order to provide recommendation on how resources can be better allocated to reduce geographic dierences in health outcomes.
Multivariate results In this section, we discuss the logistic regression results of the models predicting the utilization of prenatal care and birth delivery assistance. For each type of health care utilization, models were ®tted for all women who had a birth delivery in the three years prior to the survey, for urban women and for rural women. For each model, we display the coecients, standard errors and odds ratios, which are calculated by exponentiating the respective coecients. Prenatal care use The results of the prenatal care model are presented in Table 3. Of the individual-level characteristics considered in the analysis, the educational attainment of the woman has a positive and statistically signi®cant impact on the use of prenatal care. For example, both women with one to ®ve years of schooling and women with six or more years of schooling were substantially
Table 1 Used prenatal care and distribution of birth delivery choice Variable
Total N
Urban %
N
Rural %
N
%
Used prenatal care
1385
69.2
938
77.6
447
56.3
Birth Delivery Home/untrained assistance Home/trained assistance Facility
1996 383 308 1305
100.0 19.2 15.4 65.4
1205 122 161 922
100.0 10.1 13.4 76.5
791 261 147 383
100.0 33.0 18.6 48.4
Y. Celik, D.R. Hotchkiss / Social Science & Medicine 50 (2000) 1797±1806
more likely to use prenatal care than women without any schooling. With respect to parity, women who were pregnant with their ®rst child were also more likely to use prenatal care than woman who have had two or more previous pregnancies, after controlling for the other variables in the model. Both education and parity are signi®cant in both the urban and rural models as well. The remaining individual characteristic,
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the age of the woman at the time of the child's birth, was not found to have a signi®cant eect on prenatal care use. With respect to household-level characteristics, having health insurance coverage was found to have a positive and signi®cant impact on using prenatal care, after controlling for the other factors in the model. In addition, household wealth was also found to be as-
Table 2 Descriptive statistics for independent variables Variable
N
%
Individual-level characteristics Age at last birth 20 yr and younger 21±25 yr 26±30 yr 31 yr and older Education attended No education Primary school Secondary and more Birth order First child Second child Third child or more Ethnicity Turkish Kurdish Other
2002 505 683 468 346 2002 536 1123 343 2002 680 520 802 2002 1613 333 56
100.00 25.20 34.10 23.40 17.30 100.00 26.80 56.10 17.10 100.00 33.97 25.97 40.06 100.00 80.57 16.63 2.80
Household-level characteristics Husband's occupation Agriculture/never worked/household domestic/unskilled manual Clerical/sales/services/skilled manual Husband's health insurance No Yes Car ownership No Yes Type of ¯oor Natural Modern Type of toilet Flush Pit and others
2000 1100 900 2002 1000 1002 2002 1617 385 2002 207 1795 1998 1099 899
100.00 54.95 44.96 100.00 49.95 50.05 100.00 80.77 19.23 100.00 10.34 89.66 99.80 54.90 44.91
Community-level characteristics Urban-rural status Urban Rural Region West South Central North East
2002 1208 794 2002 457 408 428 324 385
100.00 60.34 39.66 100.00 22.83 20.38 21.38 16.18 19.23
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sociated with prenatal care use. For example, owning a car, having a ¯ush toilet and having a modern ¯oor were all positively associated with prenatal care use. However, the latter eect was not statistically signi®cant. With respect to ethnicity, the logistic regression results of all three prenatal care models shows that Kurdish women are less likely to use prenatal care services, after other determinants are held constant. However, the eect is statistically signi®cant only for the model based on the total sample of women. With respect to occupational status, women who reported that they were married to husbands in skilled and service-related occupations were signi®cantly less likely to have used prenatal services. Interestingly, this eect was negative and signi®cant in model speci®cations that excluded the community-level variables (which are not reported). When the eects of living in dierent geographic regions of Turkey were examined, it was found that living in the relatively developed regions of the
country, compared to living in the East, was positively and signi®cantly associated with prenatal care utilization. The impact of living in the Western region of the country is particularly strong. This may re¯ect the fact that health care is likely to be more accessible in the West, compared to the East. The other community-level factor considered, urban/ rural status, did not emerge as statistically signi®cant, after holding constant regional status and the other variables in the model. Moreover, it is interesting to note that the results that emerge from the separate urban and rural models are very similar to those based on the total sample. The only exception is the impact of car ownership, which was found to be signi®cant among urban women but not rural women. Birth delivery assistance The results of the multinomial logistic regression model are presented in Table 4. The results show the eects of the independent variables on the probability
Table 3 Logistic regression results on the determinants of using prenatal carea Variable
Total beta
Age at birth 21±25 yr 26±30 yr 31+ yr Education attended 1±5 yr 6+ yr Child's birth order 1st child 2nd child Husband's occupation Health insurance Ethnicity Kurdish Other Car ownership Modern ¯oor Flush toilet Urban Region West South Central North Intercept N Psuedo R 2 a
Urban exp(B)
S.E.
beta
Rural exp(B)
S.E.
beta
exp(B)
S.E.
0.26 0.23 ÿ0.13
1.30 1.25 0.87
0.32 0.29 0.24
0.20 0.30 0.08
1.23 1.35 1.09
0.22 0.20 0.17
0.10 0.34 0.27
1.11 1.40 1.30
0.31 0.28 0.24
1.52 0.59
4.57 1.80
0.27 0.14
1.36 0.59
3.91 1.80
0.32 0.21
2.04 0.60
7.70 1.82
0.65 0.20
0.80 0.27 ÿ0.15 0.58
2.23 1.32 0.86 1.79
0.18 0.16 0.12 0.12
0.88 0.32 ÿ0.14 0.64
2.41 1.38 0.87 1.90
0.26 0.22 0.16 0.17
0.72 0.13 ÿ0.16 0.51
2.05 1.13 0.85 1.67
0.26 0.24 0.19 0.18
ÿ0.39 0.25 0.40 0.25 0.43 0.23
0.67 1.28 1.50 1.28 1.54 1.26
0.18 0.35 0.17 0.19 0.16 0.16
ÿ0.33 0.03 0.54 ÿ0.01 0.37
0.72 1.03 1.72 0.99 1.45
0.25 0.51 0.25 0.37 0.20
ÿ0.38 0.43 0.33 0.24 0.68
0.68 1.53 1.39 1.27 1.98
0.27 0.49 0.25 0.23 0.27
1.57 1.03 0.24 0.55 ÿ1.48
4.79 2.81 1.27 1.74 0.30
1.78 1.38 0.05 0.55
5.92 3.96 1.05 1.73
0.38 0.32 0.27 0.29
1996 0.24
p < 0.01,p < 0.5, p < 0.10.
0.22 0.19 0.18 0.21 ÿ1.09
1.50 0.87 0.44 0.67 0.50 1205 0.20
4.48 2.39 1.55 1.95 ÿ1,37
0.28 0.25 0.27 0.36
0,42
791 0.22
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Table 4 Multinominal logistic regression results of the determinants of birth delivery choicea Variable
Total beta
Urban exp(B)
S.E.
Facility delivery vs. home delivery without trained providers Age at birth 21±25 yr 0.65 0.29 1.92 26±30 yr 0.36 0.27 1.44 31+ yr 0.10 0.23 1.10 Education attended 1±5 yr 1.95 0.54 7.01 6+ yr 0.74 0.17 2.09 Child's birth order 1st child 1.93 0.25 6.90 2nd child 1.00 0.22 2.73 Husband's occupation ÿ0.18 0.16 0.83 Health insurance 1.03 0.16 2.79 Ethnicity Kurdish ÿ1.24 0.23 0.29 Other 0.03 0.47 1.03 Car ownership 0.85 0.26 2.33 Modern ¯oor 0.21 0.23 1.24 Flush toilet 0.84 0.21 2.33 Urban 1.04 0.21 2.83 Region West 1.22 0.30 3.39 South 0.43 0.25 1.54 Central 0.37 0.24 1.44 North 0.73 0.28 2.07 Intercept ÿ1.98 0.39 0.00
Rural
beta
exp(B)
S.E.
beta
exp(B)
S.E.
0.41 0.40 ÿ0.04
0.47 0.45 0.40
1.51 1.49 0.96
0.72 0.21 0.09
0.37 0.34 0.29
2.05 1.24 1.09
2.10 1.03
0.77 0.29
8.20 2.81
1.78 0.54
0.80 0.23
5.96 1.71
2.54 1.25 ÿ0.39 1.27
0.46 0.36 0.25 0.26
12.70 3.49 0.68 3.57
1.69 0.82 ÿ0.03 0.86
0.32 0.29 0.22 0.22
5.44 2.27 0.97 2.37
ÿ1.54 0.72 0.95 ÿ0.28 0.72
0.35 1.10 0.48 0.53 0.28
0.21 2.05 2.60 0.75 2.05
ÿ1.08 ÿ0.18 0.99 0.16 1.15
0.33 0.55 0.32 0.26 0.37
0.34 0.83 2.69 1.17 3.16
0.22 ÿ0.05 ÿ0.24 ÿ0.17 0.75
0.41 0.37 0.45 0.62 ÿ2.14
1.25 0.95 0.78 0.84 0.50
2.23 0.80 0.60 1.16
0.49 0.37 0.32 0.35
9.32 2.22 1.82 3.17
Home delivery with trained Age at birth 21±25 yr 26±30 yr 31+ yr Education attended 1±5 yr 6+ yr Child's birth order 1st child 2nd child Husband's occupation Health insurance Ethnicity Kurdish Other Car ownership Modern ¯oor Flush toilet Urban Region West South Central North Intercept
providers vs home delivery without trained providers
N Psuedo R 2
1996 0.34
a
p < 0.01,
0.13 ÿ0.02 ÿ0.09
0.31 0.29 0.25
1.14 0.98 0.91
ÿ0.40 ÿ0.29 ÿ0.57
0.50 0.48 0.42
0.67 0.75 0.57
0.58 0.23 0.37
0.43 0.40 0.33
1.79 1.26 1.45
1.66 0.37
0.57 0.20
5.26 1.45
1.72 0.49
0.80 0.33
5.61 1.62
1.27 0.40
0.87 0.26
3.55 1.50
0.91 0.66 ÿ0.24 0.55
0.28 0.24 0.18 0.19
2.47 1.94 0.79 1.73
1.43 1.09 ÿ0.37 0.70
0.50 0.39 0.27 0.29
4.16 2.96 0.69 2.01
0.82 0.28 ÿ0.19 0.52
0.36 0.33 0.25 0.26
2.26 1.32 0.83 1.69
ÿ0.81 0.13 0.42 0.44 0.03 0.65
0.25 0.51 0.29 0.26 0.23 0.23
0.44 1.14 1.51 1.55 1.03 1.92
ÿ1.42 0.90 0.76 ÿ0.66 ÿ0.21
0.40 1.15 0.51 0.55 0.30
0.24 2.46 2.15 0.52 0.81
ÿ0.33 ÿ0.13 0.14 0.67 0.71
0.33 0.63 0.39 0.31 0.42
0.72 0.88 1.15 1.95 2.04
0.52 0.12 ÿ0.45 ÿ0.37 ÿ1.15
0.33 0.27 0.27 0.32 0.42
1.69 1.13 0.64 0.69
ÿ0.61 ÿ0.53 ÿ1.43 ÿ1.19 1.58
0.46 0.41 0.51 0.70 0.79
0.54 0.59 0.24 0.30
1.60 0.65 0.02 0.04 ÿ2.11
0.52 0.38 0.34 0.39 0.56
4.97 1.91 1.02 1.04
p < 0.5, p < 0.10.
1205 0.28
791 0.31
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of choosing either a facility delivery or a home delivery with the assistance of a trained practitioner vs. a traditional home delivery without trained assistance. With respect to the individual-level characteristics, women with higher educational attainment levels and lower parity levels were found to be signi®cantly more likely to choose a facility delivery vs. a traditional home delivery and a modern home delivery vs. a traditional home delivery. As in the prenatal care model, the age of the woman at the time of the last birth was not found to be signi®cantly associated with the choice of birth delivery alternative. Of the household-level characteristics, the multivariate results provide strong evidence that having insurance coverage increases the probability of choosing a modern delivery vs. a traditional home delivery. This ®nding is consistent with the results of a previous study by the Ministry of Health (1994), which showed that having health insurance increased the use of health care services independent of the other factors. Moreover, household wealth was also found to be positively and signi®cantly associated with choosing either facility deliveries or modern home deliveries. When the eect of ethnicity was examined, it was found that Kurdish women were substantially less likely to have had facility deliveries vs. traditional home deliveries and modern home deliveries vs. traditional home deliveries. This ethnicity eect, which was statistically signi®cant for each of the models estimated Ð all women, urban women and rural women Ð indicates that Kurdish women are not as likely to use assistance from health care professionals, perhaps due to cultural and economic factors that we were not able to control in this study, or because the quality of health care services is poor. With respect to the indicators of geographic location, urban women were found to be more likely than rural women to choose a facility delivery vs. a traditional home delivery and a modern home delivery vs. a traditional home delivery. In addition, regional status also emerged as an important determinant of birth delivery choice. For example, for the model based on all women, living in the Eastern region of Turkey, compared to living in the Western and Northern regions, signi®cantly decreased the probability of choosing a facility delivery vs. a traditional home delivery. In the model based on rural women, living in the East also decreased the probability of choosing a modern home delivery vs. a traditional home delivery. We also estimated models that compared the probability of choosing a facility delivery vs. a home delivery that was assisted by a trained practitioner. The results, which are not presented here in order to save space, indicate that wealth, insurance coverage, living in an urban area and living in the Western, Central and Northern regions, are signi®cantly and positively
associated with choosing to deliver in a health care facility.
Summary and conclusions Despite the progress that has been made in Turkey in improving maternal and child health outcomes in recent decades, maternal and infant mortality rates remain unacceptably high and regional and ethnic disparities remain unacceptably wide. While many factors contribute to maternal and child health outcomes, the use of maternal health care services from well-trained and well-equipped medical professionals is widely recognized as an important causal factor. This study has investigated the social and economic determinants of the use of prenatal care and birth delivery services, with the aim of improving the information that is available to decision-makers responsible for planning and administering maternal care programs. This study has identi®ed a number of individual-, household- and regional-level factors that have important in¯uences on maternal service utilization. The individual-level characteristics found to be particularly important are educational attainment and parity level. Many previous studies conducted in other developing countries have found maternal education to be among the most important determinants of maternal health care utilization, after controlling for other factors (Elo, 1992; Pebley et al., 1996; Raghupathy, 1996; Hotchkiss, 1998). Moreover, in three studies of the determinants of overall health service utilization in Turkey, education was found to have a large impact (Ulusoy 1988; Yasamis, 1991; Ministry of Health, 1995). There are a number of explanations for why education is a key determinant of demand. Education is likely to enhance female autonomy so that women develop greater con®dence and capabilities to make decisions regarding their own health, as well as that of their children (Raghupathy, 1996). Its also likely that educated women seek out higher quality services and have a greater ability to use health care inputs to produce better health. This is consistent with research by Streat®eld et al. (1990), who found that more educated women are more likely to be aware of the bene®ts of health care and as a result, are more likely to use preventive health care services. While there are many pathways that may be at work in the relationship between education and service use, the data that we have available does not allow us to identify the relative importance of these pathways among our sample. With respect to parity, women who delivered their ®rst child were also found to be signi®cantly more likely to use prenatal care and trained assistance during the birth delivery than women at higher parity
Y. Celik, D.R. Hotchkiss / Social Science & Medicine 50 (2000) 1797±1806
levels. This result is consistent with those of previous studies carried out by Pebley et al. (1996) and Raghupathy (1996). One possible explanation for this result is that women pregnant with their ®rst child were more cautious about their pregnancies and therefore sought out trained professionals and that women who have had at least three pregnancies may tend to believe that modern health care is not as necessary due to the experience and knowledge accumulated from previous pregnancies and births. A number of enabling factors were also found to be important determinants of health care utilization. One factor that has important policy implications concerns health insurance coverage. Having health insurance was found to have an important in¯uence in increasing the probability of both prenatal care use and birth delivery assistance. Health insurance coverage emerged as statistically signi®cant in the models based on all women, urban women and rural women. With respect to the indicators of household wealth, owning a car was a signi®cant predictor of maternal care utilization. While the impact of car ownership may be due to the increased ability of the women to travel to health care facilities, it may also re¯ect the woman's ability and willingness to pay the out-of-pocket expenditures that are associated with health care utilization. This may also explain why women who lived in homes with toilets were found to be more likely to use maternal services. Health care policy makers frequently discuss regional disparities in the delivery of health care services. With respect to this equity issue, our ®ndings regarding the eects of urban/rural status, geographic region and ethnicity are of particular interest. Living in urban areas was found to have a positive eect on the probability of using trained professionals for birth deliveries, but we found no signi®cant urban/rural dierence with respect to use of prenatal care. Geographic region was found to be a particularly important predictor of service utilization, as women living in the Eastern region of the country were signi®cantly less likely to use both types of prenatal care and birth delivery assistance than women from the Western region. One possible explanation for this pattern concerns the inequitable accessibility of health care services. Many studies in other countries indicate the large in¯uence of the health care supply environment on maternal health care utilization. For example, Pebley et al. (1996) found that distance to the nearest clinic was signi®cantly and negatively related to both prenatal care and delivery assistance in Guatemala. While a previous survey of health services utilization in Turkey (1994) showed that distance and travel time had a deterrent eect on health services utilization (Ministry of Health, 1995), relevant studies on this issue are rare and mostly descriptive.
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The disparity in the use of health care services between Kurdish and Turkish citizens is also an area of concern. Our results indicate that Kurdish women are signi®cantly less likely than Turkish women to utilize prenatal care and birth delivery assistance, after other demand determinants are controlled. Again, this ®nding may be possibly be due to inequities in the health care supply environment Ð services that are oered to Kurdish women may be of lower quality compared to those oered to Turkish women. A number of previous studies in other countries have found ethnicity to be an important determinant of service utilization (Pebley et al., 1996). The nonuse of health care services, especially formal care, may re¯ect socially- and culturally-imposed constraints as well as poor organizational policies and practices (Raghupathy, 1996). The results of this study provide a basis for a number of policy recommendations. First, that education was found to have an important impact on the use of health care suggests that improving educational opportunities to women may have a large impact on improving utilization of maternal health care services in the future. Second, that women at higher parity levels were found to be less likely to have deliveries assisted by modern professionals suggests that parity should be used as a criterion for targeting educational campaigns on the bene®ts of safe motherhood programs. Third, that regional status and ethnicity were found to be signi®cant predictors of using modern maternal services suggests that the government's maternal health care programs should be intensi®ed in the Eastern region of Turkey and among Kurdish women in all regions in order to further reduce disparities in health care utilization.
References Adetunji, J.A., 1994. Infant mortality in Nigeria: eects of place of birth, mother's education and region of residence. J. Biosoc. Sci. 26, 469±477. Ahmad, O.B., Eberstein, I.W., Sly, D.F., 1991. Proximate determinants of child mortality in Liberia. J. Biosoc. Sci. 23, 313±326. Boerma, J.T., Bicego, G.T., 1992. Preceding birth intervals and child survival: searching for pathways of in¯uence. Stud. Fam. Plann. 23 (4), 243±256. Elo, I.T., 1992. Utilization of maternal health-care services in Peru: the role of women's education. Health Transition Rev. 2 (1), 49±70. Forste, R., 1994. The eects of breastfeeding and birth spacing of infant and child mortality in Bolivia. Popul. Stud. 48, 497±511. Hotchkiss, D.R., 1998. The tradeo between price and quality of services in the Philippines. Soc. Sci. Med. 46 (2).
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Maine, D., Rosen®eld, A., 1999. The safe motherhood initiative: why has it stalled? Am. J. Public Health 89, 480±482. Ministry of Health, Hacettepe University Institute of Population Studies, Macro International Inc., 1994. Turkiye Nufus ve Saglik Arastirmasi 1993 (Turkey Demographic and Health Survey 1993) Ankara, Turkey. Ministry of Health, 1995. Health Services Utilization Survey in Turkey, ®rst ed., December, Ankara, Turkey. Ministry of Health, 1997. Health Sector Reforms in Turkey, 1997. Ankara. Ministry of Health, 1997. Health Statistics 1996. October, Ankara. Panis, C.W.A., Lillard, L.A., 1994. Health inputs and child mortality: Malaysia. J. Health Econ. 13, 455±589. Panis, C.W.A., Lillard, L.A., 1995. Child mortality in Malaysia: explaining ethnic dierences and the recent decline. Popul. Stud. 49, 463±479. Pebley, A.R., Goldman, N., Rodriguez, G., 1996. Prenatal and delivery care and childhood immunization in
Guatemala: do family and community matter? Demography 33 (2), 231±247. Raghupathy, S., 1996. Education and the use of maternal health care in Thailand. Soc. Sci. Med. 43 (4), 459±471. Streat®eld, K., Singarimbun, M., Diamond, I., 1990. Maternal education and child immunization. Demography 27 (3), 447±455. Tatar, M., Tatar, F., 1997. Primary Health Care in Turkey: A Passing Fashion. Health Policy Plann. 12 (3), 224±233. Tuncbilek, E., 1988. Infant Mortality in Turkey: Basic Factors. Semih Ofset Matbaacilik, Ankara. Ulusoy, M., 1988. Turkiye'de Cocuk Olumlerini Etkileyen Faktorlerin Regresyon Analizi ile Irdelenmes (The investigation of factors aecting child survival in turkey by using regression analysis). Nufus Bilim Dergisi (Turkish Journal of Population Studies) 10, 5±20 (in Turkish). Yasamis, F.D., 1991. The Environmental Reasons of Infant Mortality in Metropolitan Ankara, 1989. Lider Matbaacilik, Ankara.
www.elsevier.com/locate/socscimed
The socio-economic determinants of maternal health care utilization in Turkey Yusuf Celik a, 1, David R. Hotchkiss b,* a
School of Health Administration, Hacettepe University, Ankara, Turkey Department of International Health and Development, School of Public Health and Tropical Medicine, Tulane University, 1440 Canal Street, Suite 2200, New Orleans, LA 70112, USA
b
Abstract The purpose of this study is to investigate the individual-, household- and community-level factors that aect women's use of maternal health care services in Turkey. The data used for the study come from the 1993 Turkey Demographic and Health Survey (TDHS), a nationally representative survey of ever married women 15 to 49 years of age. In order to assess the impact of socio-economic factors on maternal health care utilization, we use logistical regression techniques to estimate models of the prenatal care use and birth delivery assistance among women who have had at least one birth in the three years prior to the survey. Separate models are also estimated for urban and rural women. The results indicate that educational attainment, parity level, health insurance coverage, ethnicity, household wealth and geographic region are statistically signi®cant factors that aect the use of health care services thought essential to reduce infant and child mortality rates. The results of the model are used to provide insights for both micro- and macro-level planning of maternal health service delivery. 7 2000 Elsevier Science Ltd. All rights reserved. Keywords: Maternal health services; Health care utilization; Turkey
Introduction Over the past two decades, Turkey has made remarkable progress in improving health outcomes among its population, particularly among children and pregnant women. From 1983 to 1993, for example, the infant mortality rate dropped by 35% and from 1974 to 1995, the maternal mortality rate decreased by 53%
* Corresponding author. Tel.: +1-504-585-6157; fax: +1504-584-3653. E-mail addresses: [email protected] (Y. Celik), david. [email protected] (D.R. Hotchkiss). 1 Tel.: +90-312-311-5506; fax: +90-312-309-3625
(Ministry of Health et al. 1994; Ministry of Health, 1997a). Although there have not been any careful studies of this mortality decline in Turkey, increased purchasing power among households, improved educational opportunities and improved health care services may have been largely responsible. While this health trend is encouraging, the current levels of infant and maternal mortality remain unacceptably high. In 1993, the infant mortality rate was estimated to be 53 per 1000 live births and in 1995, the maternal mortality rate was estimated to be 100 per 100,000 live births. Moreover, inequities by urban/ rural status, by geographic region and by ethnicity remain large. For example, infant mortality among
0277-9536/00/$ - see front matter 7 2000 Elsevier Science Ltd. All rights reserved. PII: S 0 2 7 7 - 9 5 3 6 ( 9 9 ) 0 0 4 1 8 - 9
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rural infants is estimated to be 1.5 times higher than among urban infants (Ministry of Health et al., 1994; Ministry of Health, 1997a; Tuncbilek, 1988). One explanation for poor health outcomes among women and children concerns the nonuse of modern health care services by a sizable number of women. For example, in 1993, 37% of children in Turkey were born to mothers who did not use prenatal care and 24% of births were not assisted by medical professionals (Ministry of Health et al., 1994). Many studies in both developed and developing countries suggest that prenatal care is an important determinant of improved health outcomes among infants (Tuncbilek, 1988; Ahmad et al., 1991; Boerma and Bicego 1992; Adetunji, 1994; Forste, 1994; Panis and Lillard, 1994; Panis and Lillard, 1995) and that birth delivery assistance from a trained and well-equipped provider is necessary to reduce maternal mortality (Maine and Rosenfeld, 1999). Although improvements in maternal health care utilization are essential for further progress in this area, there have not been any studies that identify the causal factors that lead to the improved use of services by women in Turkey. This paper seeks to ®ll this gap. Using the 1993 Turkey Demographic and Health Survey (TDHS), a nationally representative sample of women of childbearing age, we investigate the individual-, household- and community-level factors that in¯uence women to use maternal services. The analysis uses a logistic regression model of the use of prenatal care and a multinomial logistic regression model of the use of birth delivery assistance. The rest of this paper is organized as follows: the next section provides a brief overview of the maternal health care supply environment; the third section discusses the logistic regression models used in the analysis; the fourth section describes the data; the ®fth section provides the multivariate results; and the ®nal section uses the results to provide insights for policy makers responsible for planning the delivery of maternal services.
Maternal service delivery in Turkey Maternal health care services in Turkey are mostly provided by the government-run referral system, composed of health stations in rural areas, health posts in urban areas, health centers and hospitals. With the passage of the socialization law in 1964, the government began building village health stations and health posts, which now total 11,877. Each facility employs at least one midwife. Though midwifes have some responsibilities in providing preventive health care services, their most important role is to monitor the women's pregnancies, to vaccinate children in their service areas
and to provide family planning services. Maternal and Child Health/Family Planning (MCH/FP) Centers, administered by Department of Maternal and Child Health Services, are also common places where pregnant women can access care. There are 274 MCH/FP Centers in the country built for the primary purpose of improving maternal and child health status. An important characteristic of the public health care sector is the discrepancy between the Western and the Eastern regions with respect to the availability and quality of health care services (Ministry of Health, 1997b). Midwifes tend to be more concentrated in the West, the region of Turkey which is the most developed. For example, of the total number of midwives (39,551), 18.5% work in the three largest cities of Turkey Ð Istanbul, Izmir and Ankara Ð while only 14.5% work in the 23 provinces of the East region, where the level of unmet need is higher. Health care facilities are also more concentrated in urban areas than in rural areas. Because of the disparities in the distribution of health care personnel, the quality of service delivery and also because of social unrest in the East region, the utilization of services from village health stations is frequently reported to be quite low. Overall, the private sector plays a relatively minor role in the delivery of maternal health care services. The sector consists mostly of public physicians who are allowed to work in their private practices in the afternoons and part-time practitioners. Of the total number of hospital beds in Turkey, only 3.5% are within private facilities, although there are concerns about the reliability of this estimate (Tatar and Tatar, 1997). While relatively small on average, the private sector is an important source of care in large urban areas and in the Western part of the country. In rural areas, traditional birth attendants are also important sources of birth delivery care.
Statistical methods In order to estimate the eects of socio-economic factors on maternal health care utilization, two dependent variables were used in this study: the use of prenatal services from a trained provider and the use of trained birth delivery assistance. In the case of prenatal care, a dichotomous dependent variable was constructed to indicate whether or not the woman used services from a trained provider. Because the indicator is dichotomous, a logistic regression model was estimated. Logistic regression models make it possible to estimate the probability of using health care, conditional on the independent variables included in the model. The speci®cation of the prenatal care model is the following:
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log pi2 =pi1 a0 a1 Xij a2 Yij a3 Zj E1ij
1
The dependent variable is the log odds that individual i will chose alternative j relative to alternative 1, where alternative 1 is no use of prenatal care from a trained provider and alternative 2 is a consultation with trained provider, either in the woman's home or in a health care facility. The independent variables are classi®ed into three groups: individual-, householdand community-level factors, represented by the vectors X, Y and Z, respectively and the as represent the net eects of these variables on the probabilities of using health care. The term E1 represents unobserved determinants of prenatal care utilization and follows a logistic distribution. To construct the indicator of birth delivery assistance, women were classi®ed into three groups Ð those who delivered at home without trained assistance, those who delivered at home with trained assistance and those who delivered in a health care facility. Because the variable is trichotomous, the following multinomial logistical regression model was estimated: log pij =pi1 b0 b1j Xij b2j Yij b3j Zj E2ij
2
The dependent variable is the log odds that individual i will chose delivery alternative j j 2, 3 relative to alternative 1, where alternative 1 is a home delivery without the assistance of a trained provider, 2 is a home delivery with the assistance of a trained provider and 3 is a facility delivery with the assistance of a trained provider. Like the previous model, the independent variables consist of individual-, household- and community-level factors, represented by the vectors X, Y and Z, respectively. The bs vary by type of alternative and represent the net eects of the independent variables on the probabilities of choosing birth delivery assistance. The term E2 represents unobserved determinants of birth delivery choice and is assumed to be independently and identically distributed as a log Weibull distribution.
Data This data used in the study come from the 1993 Turkey Demographic and Health Survey (TDHS), a nationally representative survey of ever-married women 15 to 49 years of age. Data were collected from 6519 ever-married women on their reproductive histories, fertility, use of health care and family planning services and the health of their children. The survey also includes a wide variety of socio-economic and demographic indicators at the individual-, householdand community-level. The sample used for this study were those women who had at least one birth in the
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three years prior to the survey interview. For those who had more than one birth, only utilization behavior associated with the most recent pregnancy was considered. The rationale for only including women who gave birth during the three-year period is that mothers may not be able to accurately answer questions asked about births that occurred prior to this interval. As a result of these inclusion restrictions, our sample consists of 2002 women. Table 1 contains descriptive statistics for the two dependent variables used in the study. Of the total sample of women who gave birth in the three years prior to the survey, 69.2% received prenatal care by health care professionals including physician and trained midwife/nurses. As expected, urban women were more likely to have at least one prenatal care consultation than rural women (77.6 vs. 56.3%). With respect to the birth delivery, 65.4% reported delivering their last birth in a health care facility, 15.4% delivered at home with the assistance of a doctor, nurse, or trained midwife, or 19.3% delivered at home without the assistance of a health care professional. Rural women were found to be three times more likely to have traditional home deliveries than urban women (33.0 vs. 10.1%). Table 2 presents descriptive statistics for the independent variables. The women's characteristics that were included in the models were age at the time of the last child's birth, educational attainment and parity level. The age of the mother is considered to be one of the most important factors aecting health care utilization and child survival. In order to capture the eects of age, women were classi®ed into four groups: 20 years of age and younger (25.2%), 21±25 years old (34.1%), 26±30 years old (23.4%), or 31 years of age and older (17.3%). The reference group consists of woman 20 years of age and younger. The other individual-level characteristics included in the model were maternal education and parity level. In our sample, 26.8% of women report that they have no formal education, 56.1 have one to ®ve years of schooling and 17.1% have six years or more of schooling. Two dichotomous indicators measure parity: whether the woman's last birth was her ®rst birth (34% of woman) and whether the woman's last birth was her second birth (26% of woman). The reference category consists of woman whose last birth was her third or more. The household-level factors consist of the occupation of the household head, whether the household was covered by a health insurance plan, ethnicity and household wealth. With respect to occupation, the TDHS collected information on nine employment categories. The dummy indicator on the employment status was coded as one if the husband was primarily engaged in clerical, sales, service and skilled manual
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work and zero if the husband was primarily engaged in other activities (agriculture, household domestic work, unskilled/manual work, or did not work). Of the 2000 woman in the sample, 45% had husbands in the ®rst group while the remaining 55% had husbands in the second group. Ethnicity may also have a potentially important eect on service utilization. Respondents were grouped into three ethnicity categories: Turkish, Kurdish and others. The majority of respondents (80.5%) reported themselves as Turkish, while the remaining respondents were from other groups (16.6% Kurdish and 2.8 other ethnic groups). Health insurance coverage was also included as an independent variable thought to be a potentially important determinant of service utilization. It is expected that coverage would improve service utilization by reducing the out-of-pocket costs associated with service use. The TDHS collected information on the health insurance status of the father. Half of the total number of respondents was covered by some type of health insurance, although information on which services were covered and the level of coverage were not collected in the TDHS. Household income and assets may increase the ability and willingness of households to pay for health care services. Like all of the USAID-sponsored Demographic and Health Surveys, the TDHS did not include questions on household income. However, information on household assets was collected. In this study, we use three indicators of household wealth: car ownership, the type of sanitation facilities used by the household members and the type of ¯oor in the woman's house. Over 80% of the respondents (1617 women) reported that their household did not own a car. The type of ¯oor was categorized into two groups: natural and modern. Almost two-thirds of respondents (64.6) reported living in a house with a modern ¯oor, which we classi®ed as being constructed of cement, wood, vinyl, asphalt, ceramic, or carpet. The responses on the type of sanitation used by the household were grouped into two categories: (1) ¯ush toilet and (2) pit and
others. The majority of women resided in households that had a ¯ush toilet (54.9%). The community-level factors included in the model consist of two indicators of the location of the woman's household: urban/rural status and geographic region. As presented in Table 2, 60.3% of total respondents reside in urban areas and 39.6% reside from rural areas. With respect to region, 22.8% live in the West, 20.3% live in the South, 21.3% live in Central Anatolia, 16.1% live in the North and 19.2% live in the East region of Turkey. In Turkey, policy discussions often include the issue of the disparate utilization rates between urban and rural areas and between the eastern and western portion of the country. One of the primary aims of this study is to investigate how health care utilization varies by geographic region in order to provide recommendation on how resources can be better allocated to reduce geographic dierences in health outcomes.
Multivariate results In this section, we discuss the logistic regression results of the models predicting the utilization of prenatal care and birth delivery assistance. For each type of health care utilization, models were ®tted for all women who had a birth delivery in the three years prior to the survey, for urban women and for rural women. For each model, we display the coecients, standard errors and odds ratios, which are calculated by exponentiating the respective coecients. Prenatal care use The results of the prenatal care model are presented in Table 3. Of the individual-level characteristics considered in the analysis, the educational attainment of the woman has a positive and statistically signi®cant impact on the use of prenatal care. For example, both women with one to ®ve years of schooling and women with six or more years of schooling were substantially
Table 1 Used prenatal care and distribution of birth delivery choice Variable
Total N
Urban %
N
Rural %
N
%
Used prenatal care
1385
69.2
938
77.6
447
56.3
Birth Delivery Home/untrained assistance Home/trained assistance Facility
1996 383 308 1305
100.0 19.2 15.4 65.4
1205 122 161 922
100.0 10.1 13.4 76.5
791 261 147 383
100.0 33.0 18.6 48.4
Y. Celik, D.R. Hotchkiss / Social Science & Medicine 50 (2000) 1797±1806
more likely to use prenatal care than women without any schooling. With respect to parity, women who were pregnant with their ®rst child were also more likely to use prenatal care than woman who have had two or more previous pregnancies, after controlling for the other variables in the model. Both education and parity are signi®cant in both the urban and rural models as well. The remaining individual characteristic,
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the age of the woman at the time of the child's birth, was not found to have a signi®cant eect on prenatal care use. With respect to household-level characteristics, having health insurance coverage was found to have a positive and signi®cant impact on using prenatal care, after controlling for the other factors in the model. In addition, household wealth was also found to be as-
Table 2 Descriptive statistics for independent variables Variable
N
%
Individual-level characteristics Age at last birth 20 yr and younger 21±25 yr 26±30 yr 31 yr and older Education attended No education Primary school Secondary and more Birth order First child Second child Third child or more Ethnicity Turkish Kurdish Other
2002 505 683 468 346 2002 536 1123 343 2002 680 520 802 2002 1613 333 56
100.00 25.20 34.10 23.40 17.30 100.00 26.80 56.10 17.10 100.00 33.97 25.97 40.06 100.00 80.57 16.63 2.80
Household-level characteristics Husband's occupation Agriculture/never worked/household domestic/unskilled manual Clerical/sales/services/skilled manual Husband's health insurance No Yes Car ownership No Yes Type of ¯oor Natural Modern Type of toilet Flush Pit and others
2000 1100 900 2002 1000 1002 2002 1617 385 2002 207 1795 1998 1099 899
100.00 54.95 44.96 100.00 49.95 50.05 100.00 80.77 19.23 100.00 10.34 89.66 99.80 54.90 44.91
Community-level characteristics Urban-rural status Urban Rural Region West South Central North East
2002 1208 794 2002 457 408 428 324 385
100.00 60.34 39.66 100.00 22.83 20.38 21.38 16.18 19.23
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sociated with prenatal care use. For example, owning a car, having a ¯ush toilet and having a modern ¯oor were all positively associated with prenatal care use. However, the latter eect was not statistically signi®cant. With respect to ethnicity, the logistic regression results of all three prenatal care models shows that Kurdish women are less likely to use prenatal care services, after other determinants are held constant. However, the eect is statistically signi®cant only for the model based on the total sample of women. With respect to occupational status, women who reported that they were married to husbands in skilled and service-related occupations were signi®cantly less likely to have used prenatal services. Interestingly, this eect was negative and signi®cant in model speci®cations that excluded the community-level variables (which are not reported). When the eects of living in dierent geographic regions of Turkey were examined, it was found that living in the relatively developed regions of the
country, compared to living in the East, was positively and signi®cantly associated with prenatal care utilization. The impact of living in the Western region of the country is particularly strong. This may re¯ect the fact that health care is likely to be more accessible in the West, compared to the East. The other community-level factor considered, urban/ rural status, did not emerge as statistically signi®cant, after holding constant regional status and the other variables in the model. Moreover, it is interesting to note that the results that emerge from the separate urban and rural models are very similar to those based on the total sample. The only exception is the impact of car ownership, which was found to be signi®cant among urban women but not rural women. Birth delivery assistance The results of the multinomial logistic regression model are presented in Table 4. The results show the eects of the independent variables on the probability
Table 3 Logistic regression results on the determinants of using prenatal carea Variable
Total beta
Age at birth 21±25 yr 26±30 yr 31+ yr Education attended 1±5 yr 6+ yr Child's birth order 1st child 2nd child Husband's occupation Health insurance Ethnicity Kurdish Other Car ownership Modern ¯oor Flush toilet Urban Region West South Central North Intercept N Psuedo R 2 a
Urban exp(B)
S.E.
beta
Rural exp(B)
S.E.
beta
exp(B)
S.E.
0.26 0.23 ÿ0.13
1.30 1.25 0.87
0.32 0.29 0.24
0.20 0.30 0.08
1.23 1.35 1.09
0.22 0.20 0.17
0.10 0.34 0.27
1.11 1.40 1.30
0.31 0.28 0.24
1.52 0.59
4.57 1.80
0.27 0.14
1.36 0.59
3.91 1.80
0.32 0.21
2.04 0.60
7.70 1.82
0.65 0.20
0.80 0.27 ÿ0.15 0.58
2.23 1.32 0.86 1.79
0.18 0.16 0.12 0.12
0.88 0.32 ÿ0.14 0.64
2.41 1.38 0.87 1.90
0.26 0.22 0.16 0.17
0.72 0.13 ÿ0.16 0.51
2.05 1.13 0.85 1.67
0.26 0.24 0.19 0.18
ÿ0.39 0.25 0.40 0.25 0.43 0.23
0.67 1.28 1.50 1.28 1.54 1.26
0.18 0.35 0.17 0.19 0.16 0.16
ÿ0.33 0.03 0.54 ÿ0.01 0.37
0.72 1.03 1.72 0.99 1.45
0.25 0.51 0.25 0.37 0.20
ÿ0.38 0.43 0.33 0.24 0.68
0.68 1.53 1.39 1.27 1.98
0.27 0.49 0.25 0.23 0.27
1.57 1.03 0.24 0.55 ÿ1.48
4.79 2.81 1.27 1.74 0.30
1.78 1.38 0.05 0.55
5.92 3.96 1.05 1.73
0.38 0.32 0.27 0.29
1996 0.24
p < 0.01,p < 0.5, p < 0.10.
0.22 0.19 0.18 0.21 ÿ1.09
1.50 0.87 0.44 0.67 0.50 1205 0.20
4.48 2.39 1.55 1.95 ÿ1,37
0.28 0.25 0.27 0.36
0,42
791 0.22
Y. Celik, D.R. Hotchkiss / Social Science & Medicine 50 (2000) 1797±1806
1803
Table 4 Multinominal logistic regression results of the determinants of birth delivery choicea Variable
Total beta
Urban exp(B)
S.E.
Facility delivery vs. home delivery without trained providers Age at birth 21±25 yr 0.65 0.29 1.92 26±30 yr 0.36 0.27 1.44 31+ yr 0.10 0.23 1.10 Education attended 1±5 yr 1.95 0.54 7.01 6+ yr 0.74 0.17 2.09 Child's birth order 1st child 1.93 0.25 6.90 2nd child 1.00 0.22 2.73 Husband's occupation ÿ0.18 0.16 0.83 Health insurance 1.03 0.16 2.79 Ethnicity Kurdish ÿ1.24 0.23 0.29 Other 0.03 0.47 1.03 Car ownership 0.85 0.26 2.33 Modern ¯oor 0.21 0.23 1.24 Flush toilet 0.84 0.21 2.33 Urban 1.04 0.21 2.83 Region West 1.22 0.30 3.39 South 0.43 0.25 1.54 Central 0.37 0.24 1.44 North 0.73 0.28 2.07 Intercept ÿ1.98 0.39 0.00
Rural
beta
exp(B)
S.E.
beta
exp(B)
S.E.
0.41 0.40 ÿ0.04
0.47 0.45 0.40
1.51 1.49 0.96
0.72 0.21 0.09
0.37 0.34 0.29
2.05 1.24 1.09
2.10 1.03
0.77 0.29
8.20 2.81
1.78 0.54
0.80 0.23
5.96 1.71
2.54 1.25 ÿ0.39 1.27
0.46 0.36 0.25 0.26
12.70 3.49 0.68 3.57
1.69 0.82 ÿ0.03 0.86
0.32 0.29 0.22 0.22
5.44 2.27 0.97 2.37
ÿ1.54 0.72 0.95 ÿ0.28 0.72
0.35 1.10 0.48 0.53 0.28
0.21 2.05 2.60 0.75 2.05
ÿ1.08 ÿ0.18 0.99 0.16 1.15
0.33 0.55 0.32 0.26 0.37
0.34 0.83 2.69 1.17 3.16
0.22 ÿ0.05 ÿ0.24 ÿ0.17 0.75
0.41 0.37 0.45 0.62 ÿ2.14
1.25 0.95 0.78 0.84 0.50
2.23 0.80 0.60 1.16
0.49 0.37 0.32 0.35
9.32 2.22 1.82 3.17
Home delivery with trained Age at birth 21±25 yr 26±30 yr 31+ yr Education attended 1±5 yr 6+ yr Child's birth order 1st child 2nd child Husband's occupation Health insurance Ethnicity Kurdish Other Car ownership Modern ¯oor Flush toilet Urban Region West South Central North Intercept
providers vs home delivery without trained providers
N Psuedo R 2
1996 0.34
a
p < 0.01,
0.13 ÿ0.02 ÿ0.09
0.31 0.29 0.25
1.14 0.98 0.91
ÿ0.40 ÿ0.29 ÿ0.57
0.50 0.48 0.42
0.67 0.75 0.57
0.58 0.23 0.37
0.43 0.40 0.33
1.79 1.26 1.45
1.66 0.37
0.57 0.20
5.26 1.45
1.72 0.49
0.80 0.33
5.61 1.62
1.27 0.40
0.87 0.26
3.55 1.50
0.91 0.66 ÿ0.24 0.55
0.28 0.24 0.18 0.19
2.47 1.94 0.79 1.73
1.43 1.09 ÿ0.37 0.70
0.50 0.39 0.27 0.29
4.16 2.96 0.69 2.01
0.82 0.28 ÿ0.19 0.52
0.36 0.33 0.25 0.26
2.26 1.32 0.83 1.69
ÿ0.81 0.13 0.42 0.44 0.03 0.65
0.25 0.51 0.29 0.26 0.23 0.23
0.44 1.14 1.51 1.55 1.03 1.92
ÿ1.42 0.90 0.76 ÿ0.66 ÿ0.21
0.40 1.15 0.51 0.55 0.30
0.24 2.46 2.15 0.52 0.81
ÿ0.33 ÿ0.13 0.14 0.67 0.71
0.33 0.63 0.39 0.31 0.42
0.72 0.88 1.15 1.95 2.04
0.52 0.12 ÿ0.45 ÿ0.37 ÿ1.15
0.33 0.27 0.27 0.32 0.42
1.69 1.13 0.64 0.69
ÿ0.61 ÿ0.53 ÿ1.43 ÿ1.19 1.58
0.46 0.41 0.51 0.70 0.79
0.54 0.59 0.24 0.30
1.60 0.65 0.02 0.04 ÿ2.11
0.52 0.38 0.34 0.39 0.56
4.97 1.91 1.02 1.04
p < 0.5, p < 0.10.
1205 0.28
791 0.31
1804
Y. Celik, D.R. Hotchkiss / Social Science & Medicine 50 (2000) 1797±1806
of choosing either a facility delivery or a home delivery with the assistance of a trained practitioner vs. a traditional home delivery without trained assistance. With respect to the individual-level characteristics, women with higher educational attainment levels and lower parity levels were found to be signi®cantly more likely to choose a facility delivery vs. a traditional home delivery and a modern home delivery vs. a traditional home delivery. As in the prenatal care model, the age of the woman at the time of the last birth was not found to be signi®cantly associated with the choice of birth delivery alternative. Of the household-level characteristics, the multivariate results provide strong evidence that having insurance coverage increases the probability of choosing a modern delivery vs. a traditional home delivery. This ®nding is consistent with the results of a previous study by the Ministry of Health (1994), which showed that having health insurance increased the use of health care services independent of the other factors. Moreover, household wealth was also found to be positively and signi®cantly associated with choosing either facility deliveries or modern home deliveries. When the eect of ethnicity was examined, it was found that Kurdish women were substantially less likely to have had facility deliveries vs. traditional home deliveries and modern home deliveries vs. traditional home deliveries. This ethnicity eect, which was statistically signi®cant for each of the models estimated Ð all women, urban women and rural women Ð indicates that Kurdish women are not as likely to use assistance from health care professionals, perhaps due to cultural and economic factors that we were not able to control in this study, or because the quality of health care services is poor. With respect to the indicators of geographic location, urban women were found to be more likely than rural women to choose a facility delivery vs. a traditional home delivery and a modern home delivery vs. a traditional home delivery. In addition, regional status also emerged as an important determinant of birth delivery choice. For example, for the model based on all women, living in the Eastern region of Turkey, compared to living in the Western and Northern regions, signi®cantly decreased the probability of choosing a facility delivery vs. a traditional home delivery. In the model based on rural women, living in the East also decreased the probability of choosing a modern home delivery vs. a traditional home delivery. We also estimated models that compared the probability of choosing a facility delivery vs. a home delivery that was assisted by a trained practitioner. The results, which are not presented here in order to save space, indicate that wealth, insurance coverage, living in an urban area and living in the Western, Central and Northern regions, are signi®cantly and positively
associated with choosing to deliver in a health care facility.
Summary and conclusions Despite the progress that has been made in Turkey in improving maternal and child health outcomes in recent decades, maternal and infant mortality rates remain unacceptably high and regional and ethnic disparities remain unacceptably wide. While many factors contribute to maternal and child health outcomes, the use of maternal health care services from well-trained and well-equipped medical professionals is widely recognized as an important causal factor. This study has investigated the social and economic determinants of the use of prenatal care and birth delivery services, with the aim of improving the information that is available to decision-makers responsible for planning and administering maternal care programs. This study has identi®ed a number of individual-, household- and regional-level factors that have important in¯uences on maternal service utilization. The individual-level characteristics found to be particularly important are educational attainment and parity level. Many previous studies conducted in other developing countries have found maternal education to be among the most important determinants of maternal health care utilization, after controlling for other factors (Elo, 1992; Pebley et al., 1996; Raghupathy, 1996; Hotchkiss, 1998). Moreover, in three studies of the determinants of overall health service utilization in Turkey, education was found to have a large impact (Ulusoy 1988; Yasamis, 1991; Ministry of Health, 1995). There are a number of explanations for why education is a key determinant of demand. Education is likely to enhance female autonomy so that women develop greater con®dence and capabilities to make decisions regarding their own health, as well as that of their children (Raghupathy, 1996). Its also likely that educated women seek out higher quality services and have a greater ability to use health care inputs to produce better health. This is consistent with research by Streat®eld et al. (1990), who found that more educated women are more likely to be aware of the bene®ts of health care and as a result, are more likely to use preventive health care services. While there are many pathways that may be at work in the relationship between education and service use, the data that we have available does not allow us to identify the relative importance of these pathways among our sample. With respect to parity, women who delivered their ®rst child were also found to be signi®cantly more likely to use prenatal care and trained assistance during the birth delivery than women at higher parity
Y. Celik, D.R. Hotchkiss / Social Science & Medicine 50 (2000) 1797±1806
levels. This result is consistent with those of previous studies carried out by Pebley et al. (1996) and Raghupathy (1996). One possible explanation for this result is that women pregnant with their ®rst child were more cautious about their pregnancies and therefore sought out trained professionals and that women who have had at least three pregnancies may tend to believe that modern health care is not as necessary due to the experience and knowledge accumulated from previous pregnancies and births. A number of enabling factors were also found to be important determinants of health care utilization. One factor that has important policy implications concerns health insurance coverage. Having health insurance was found to have an important in¯uence in increasing the probability of both prenatal care use and birth delivery assistance. Health insurance coverage emerged as statistically signi®cant in the models based on all women, urban women and rural women. With respect to the indicators of household wealth, owning a car was a signi®cant predictor of maternal care utilization. While the impact of car ownership may be due to the increased ability of the women to travel to health care facilities, it may also re¯ect the woman's ability and willingness to pay the out-of-pocket expenditures that are associated with health care utilization. This may also explain why women who lived in homes with toilets were found to be more likely to use maternal services. Health care policy makers frequently discuss regional disparities in the delivery of health care services. With respect to this equity issue, our ®ndings regarding the eects of urban/rural status, geographic region and ethnicity are of particular interest. Living in urban areas was found to have a positive eect on the probability of using trained professionals for birth deliveries, but we found no signi®cant urban/rural dierence with respect to use of prenatal care. Geographic region was found to be a particularly important predictor of service utilization, as women living in the Eastern region of the country were signi®cantly less likely to use both types of prenatal care and birth delivery assistance than women from the Western region. One possible explanation for this pattern concerns the inequitable accessibility of health care services. Many studies in other countries indicate the large in¯uence of the health care supply environment on maternal health care utilization. For example, Pebley et al. (1996) found that distance to the nearest clinic was signi®cantly and negatively related to both prenatal care and delivery assistance in Guatemala. While a previous survey of health services utilization in Turkey (1994) showed that distance and travel time had a deterrent eect on health services utilization (Ministry of Health, 1995), relevant studies on this issue are rare and mostly descriptive.
1805
The disparity in the use of health care services between Kurdish and Turkish citizens is also an area of concern. Our results indicate that Kurdish women are signi®cantly less likely than Turkish women to utilize prenatal care and birth delivery assistance, after other demand determinants are controlled. Again, this ®nding may be possibly be due to inequities in the health care supply environment Ð services that are oered to Kurdish women may be of lower quality compared to those oered to Turkish women. A number of previous studies in other countries have found ethnicity to be an important determinant of service utilization (Pebley et al., 1996). The nonuse of health care services, especially formal care, may re¯ect socially- and culturally-imposed constraints as well as poor organizational policies and practices (Raghupathy, 1996). The results of this study provide a basis for a number of policy recommendations. First, that education was found to have an important impact on the use of health care suggests that improving educational opportunities to women may have a large impact on improving utilization of maternal health care services in the future. Second, that women at higher parity levels were found to be less likely to have deliveries assisted by modern professionals suggests that parity should be used as a criterion for targeting educational campaigns on the bene®ts of safe motherhood programs. Third, that regional status and ethnicity were found to be signi®cant predictors of using modern maternal services suggests that the government's maternal health care programs should be intensi®ed in the Eastern region of Turkey and among Kurdish women in all regions in order to further reduce disparities in health care utilization.
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