1 Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
2 The World Bank, Washington, DC, USA
3 Badan Pusat Statistik, Jakarta, Indonesia
4 The World Bank, New Delhi, India
Correspondence: Hugh Waters, Department of International Health, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe St, Room 8132, Baltimore, MD 21205, USA. E-mail: hwaters{at}jhsph.edu
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Abstract |
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Methods A pooled cross-sectional dataset of 163 986 children <5 years of age from the 1992, 1995, 1998, and 1999 Indonesia Socioeconomic Household Surveys was analysed using multivariate logistic regression, and by running separate pooled regressions to calculate the effect of the each of the principal independent variables separately for each year. Robust regression techniques corrected for non-constant variance resulting from multilevel modelling.
Results The overall percentage of children <5 years that are underweight decreased from 37.7% in 1992 to 28.5% in 1999. Nearly all of the gains occurred in children over one year of age. Child nutritional status improved for all major social groups in Indonesia. There was no measurable general effect of the 19971999 East Asian economic crisis on levels of underweight children.
Conclusions Disparities among social and economic groups have narrowed over time in Indonesia; the relatively high risk of male children compared with females has also decreased. Maternal education and economic statusas measured by quintile of adjusted per-capita household expenditureshave continued to be very strong predictors of children's nutritional outcomes.
Accepted 17 November 2003
Indonesia has realized impressive public health gains in recent decades. Life expectancy at birth increased from 48 to 64 years in just 20 years, from 1975 to 1995. This article looks in detail at the improvements made in child malnutrition, measured as the percentage of children who are underweight, during the time period 19921999. The article teases apart factors at the individual and household levels that influence children's nutritional statusin order to determine which factors have been the most important in influencing this substantial decline in malnutrition.
Household-level variables that have been found to be important predictors of children's weight-for-age nutritional status include family income, mothers' education, and source of water.1,2 Earlier studies in Indonesia have shown an important relationship between mothers' employment status and child malnutrition. In Surabaya, children of non-working mothers were found to better nourished than children whose mothers workedchildren of mothers working in the informal employment sector were found to be at particularly high risk for malnutrition.3
Analysis of the 1989 national Indonesia Socio-Economic Household Survey (SUSENAS) has shown that the level of mothers' education is an important predictor of child nutrition levels in Indonesia, especially for boys.4 A separate study in West Java in Indonesia found that community-level factorsincluding vaccination programmes, child care services, and environmental sanitation and latrinesare strongly associated with children's growth.5
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Methods |
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Each year the survey contains a core individual-level questionnaire including demographic and education information on all household members, supplemented by modules covering about 60 000 households that are rotated over time and include health care and nutrition, household income and expenditure, and work force experience. Child anthropometric indicators, generally included every 3 years, are in the 1992, 1995, and 1998 surveys. Child anthropometric measures were also added to the 1999 survey in order to be able to measure the effects of the 19971999 East Asian economic crisis on child malnutrition.
The terms underweight children and weight-for-age malnutrition are used interchangeably in this article. They both refer to children with standardized normal weight-for-age Z-scores (WAZ scores) below 2.0, a condition also known as undernutrition. Underweight children are those who have a WAZ score that is more than two standard deviations below the mean for a well-nourished population. Weight-for-age measures were converted to WAZ scores using the reference growth curves developed by the US National Center for Health Statistics (NCHS) and recommended for international use by WHO.7 Severe malnutrition is defined as less than three standard deviations below the international standard. WAZ values >6.0 or 6.0 were considered to be extreme values and are deleted from the analysisthese values accounted for less than 1% of the full 4-year sample. Epi Info 2002 software, developed by the Centers for Disease Control (CDC), was used to compare the WAZ score of each child with international standards for children of the same age and sex.8
Since malnutrition measured in this manner is a dichotomous 0/1 outcome, the pooled regression analyses were estimated using multivariate logistic regression. The survey year (1992, 1995, 1998, or 1999) was included as a separate variable in the regression. Separate regression equations were modelled to test for the effect of selected variables by year by using interaction terms between these variables and a dummy variable for year. We then separately calculated the corresponding odds ratio (OR) for these variables for each survey year. Stata statistical software, Version 7, was used to perform the multivariate logistic regression analysis.9
At the individual level, the child's sex, age, and birth order within the family can feasibly influence feeding patterns, health care, and nutritional status. At the household level, variables potentially affecting children's nutritional status include the household's expenditure quintile; the main source of household income; the parents' education level; the number of children under age 5 and total household size; whether or not the head of the household is female; and the region and area (urban-rural) of residence. The household's physical environment is represented by variables for water supply and the type of flooring material.
The level of per-capita household expenditures is the principal measure of households' economic status. All types of household expenditures are included in this measure, and not just those on health care. The level of expenditures is generally recognized as a better measure of economic status than income, since income does not reflect permanent wealth and can be seasonally variable. Households were placed in expenditure quintiles based on their level of overall expenditures per household member; children <5 years of age count as one-half of a household member for these calculations. The first quintile contains the 20% of households with the lowest per-capita expenditures on a nationwide basis; the fifth quintile has the most expenditures. For the multiyear regression analysis, household expenditures were standardized across years using the official Indonesian consumer price index.
There is a clear potential in this study for heteroskedasticityor non-constant varianceresulting from multiple level analysis, since there are variables from the individual, household, and regional levels in the same equation. Because explanatory variables are correlated across observations, the regression residual will also be correlated. Correlated residual values across observations cause biased and inconsistent results in non-linear regression analyses, including logistic regression.10,11 The Huber-White sandwich variance estimator was used to correct for correlated residual values. The estimator is based on the variance of the scores, using the fact that the variance of the sum of the scores is equal to the sum of the variances of the independent scores plus all the covariances between pairs of scores that are not independent. This correction treats clusters as super observations, and allows for any type of variance correlation within clusters. It therefore accommodates for clusters that have sub-clusters within them, as is the case in this study.12
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Results |
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Multivariate logistic regression analysis of the pooled dataset shows that males were 1.27 times more likely to be underweight than females (P < 0.001) over the time period covered by the surveys (Table 2). After accounting for the effects of the other variables in the model, children in 1995 were 0.92 as likely as those in 1992 to be underweight (P < 0.1). Children in 1998 and 1999 were 0.82 and 0.75 times as likely to be underweight, respectively, as children in 1992 (P < 0.001 for both). There were also clear secular improvements over timeindicator variables for survey year have a statistically significant impact on the probability that children are underweight.
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Mothers' education has very strong protective effects. In 1999, the prevalence of weight-for-age malnutrition among children of mothers who had not completed primary education was 34%, compared with 23% for children of mothers with a secondary or higher education (Figure 2). This effect is also apparent in the multiyear regression analysis, where the OR associated with secondary level maternal education compared with less than primary level is 0.72 (P < 0.001) (Table 2).
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Multivariate logistic regression analysis of the pooled dataset, with separate regressions for each independent variable interacted with each survey year, shows a similar pattern. Secondary or higher maternal education had a strongly protective baseline (1992) effect on weight-for-age malnutritionan OR of 0.63 in comparison with mothers with less than primary education (Table 3). The equivalent OR for secondary or higher maternal education in 1995, 1998, and 1999 were 0.77, 0.72, and 0.79 respectively (all significant at P < 0.05). The impact of lower secondary maternal education compared with less than primary education likewise decreased over time.
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But as with maternal education, the advantage of the wealthiest expenditure quintile has narrowed over timefrom an OR of 0.65 in 1992 to 0.73 in 1999. These patterns are somewhat different in urban and rural areas. In Indonesia's cities, differences in child weight-for-age malnutrition rates by expenditure quintile narrowed substantially between 1992 and 1999as the prevalence among the poorest quintile in urban areas fell from 42.6% to 29.7% (95% CI: 39.3%, 45.9% for 1992; 27.7%, 31.7% for 1998).
Overall, the advantage of urban children in nutritional status disappeared after 1992 after controlling for other factors. In the regression analysis isolating the effect of the principal variables by year, urban residence showed an OR of 0.83 compared with rural residence in 1992 (P < 0.001). This protective effect was nullified in the subsequent years, as shown by insignificant OR for urban residence in 1995, 1998, and 1999 of 1.04, 0.99, and 1.04, respectively (Table 3).
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Discussion |
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Nearly all of the gains in children's nutritional status have occurred for children between the ages of 12 and 60 months. For those less than a year old, there has been little or no improvement. For both males and females, the biggest increases in levels of underweight children correspond to the ages when children are being progressively weaned from breast milk and new foods and liquids are introduced into the diet. WHO recommends exclusive breastfeeding, without supplementary feeding or liquids, for the first 6 months of the child's life. Weight-for-age malnutrition levels increase dramatically from the 05 month age group to the 611 month groupa time when children should be receiving substantial additional foods and proteins. These findings emphasize the importance of correct weaning and infant feeding practices in Indonesia.
The effects of the 19971999 economic crisis
The economic crisis that struck East Asia in 1997 had particularly strong effects in Indonesia. From July 1997 to January 1998 Indonesia's currency, the Rupiah, lost 50% of its value against the US dollar.13 Resulting inflation was highand food prices increased by an estimated 80% over the course of 1998.14 The poverty rate escalated from 11.3% in 1996 to an estimated 20% in 1999.15 Unemployment also increased substantially, from 8% to 15% by mid-1998.13,16
Child malnutrition is an important indicator of the human effects of an economic crisis. The data for the 1998 SUSENAS survey were collected during the time period December 1997January 1998. The economic crisis had already started by this time, but had not yet reached its peak. The 1999 data collection occurred while the crisis itself was easing, but the economic and social effects were still being acutely felt. Any effects on children's nutritional status should still have been in evidence. As a result, a comparison of the two surveys presents an estimation of the impact of the crisis on malnutrition levels.
There is no general effect of the crisis on the percentage of children who are underweight. Overall levels of underweight children <5 years of age in Indonesia continued their downward trend during this time periodfrom 29.8% in 1998 to 28.5% in 1999 (95% CI: 29.2%, 30.4% for 1998; 28.2%, 28.8% for 1999). Specific pockets of the population may have been adversely impacted by the crisis. Children's nutrition status slightly worsened for families gaining their living from the financial, insurance, and construction industriesfrom 27.0% to 27.5% underweight prevalencebut this effect is not statistically significant.
A separate data source, the Indonesia Family Life Survey (IFLS), reinforces the finding that there was no widespread impact of the economic crisis on child nutrition levels. The IFLS2 survey was conducted in late 1997, and a special follow-up survey, the IFLS2+, was implemented in a subsample of the IFLS survey design in July 1998in order to monitor the effects of the crisis. These surveys do not show strong impacts of the crisis on child malnutrition. In the geographical areas covered by the IFLS2+, weight-for-age malnutrition among children actually decreasedfrom 50.7% in 1997 to 45.7% in 1998.17
The prevalence of adult malnutrition, measured by a body mass index <18, did increase slightly from 1997 to 1998from 14.1% to 14.7%with poor women particularly affected. Body mass index has been shown to be a health indicator that is sensitive to economic change.18 These data could indicate that adults sought to protect the nutritional status of their children at their own expense.19 A separate study of the health impact of the US economic embargo of Cuba found that the brunt of the impact, in nutritional terms, falls on adult men and the elderly.20
There are limitations in the interpretation of our analyses. Weight-for-age malnutrition combines elements of weight-for-height malnutrition (wasting) and height-for-age malnutrition (stunting). The prevalence of wasting among children would be a more sensitive indicator of the short-term effects of an economic crisis than the prevalence of weight-for-age malnutrition, but data on children's height are generally not collected in large-sample household surveys. The WAZ scores used internationally and in the Epi Info 2002 software are developed using reference growth curves from the US. Children's growth patterns may differ in Indonesia, where feeding and breastfeeding patterns vary from those in the US.
WHO has established international standards for child malnutrition prevalence, as measured by weight-for-age. Malnutrition prevalence of <10% is considered low, 1020% medium, 2030% high, and a prevalence of >30% is considered to be very high.21,22 By these standards, weight-for-age malnutrition levels in Indonesia are still in the high range. Indonesia's results are comparable with estimates from other Southeast Asian countriesincluding Thailand (25%), the Philippines (33%), Cambodia (40%), and Vietnam (40%).23
Despite the improvements documented in this article, poorer and rural Indonesians still suffer from high levels of child malnutrition as measured by weight-for-age. Earlier studies, including one from Indonesia, have shown clearly that malnutrition is a strong contributor to child mortality.24,25 Malnutrition makes children more susceptible to infectious diseases, and in turn worsens the effects of these diseases. Although greatly reduced through in the 1990s, child malnutrition remains a serious problem in Indonesia.
KEY MESSAGES
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Acknowledgments |
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References |
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