Determinants of socioeconomic and rural-urban disparities in stunting: evidence from Indonesia.

INTRODUCTION: Stunting continues to be a prominent health problem in Indonesia. Stunting prevalence is higher in children from poor families or living in rural areas; however, there has been a lack of information on predictors of stunting disparities and stunting risk factors by socioeconomic status (SES) and location of residence (rural or urban). This study aims to examine the factors associated with stunting by SES and rural-urban status, and to assess determinants of stunting disparities by SES and rural-urban status in Indonesia. METHODS: This study analysed data from the Indonesian Family and Life Survey (IFLS) wave 5, conducted in 2014. Data for 3887 children aged 0-59 months, including individual, family and community variables, were analysed. Stratified logistic regression was conducted to assess differences in determinants of stunting by household expenditure (poor or non-poor, representing SES) and rural-urban status. The Oaxaca-Blinder decomposition method was used to assess determinants of stunting disparities by household expenditure and rural-urban status. RESULTS: The analyses showed differences in factors associated with stunting among children in rural versus urban areas, or children in poor versus non-poor households. Mother's short stature and low education level increased the odds of stunting across all groups. However, in children of families with a higher household expenditure, unhealthy snacks were a significant predictor of stunting (adjusted odds ratio (aOR) 1.23, 95% confidence interval (CI) 1.04-1.47). This finding was not found in other groups. Good sanitation significantly reduced stunting in children in families with higher household expenditure and children from urban communities. Nutrition services were significantly associated with stunting in poor children and children from urban areas. The decomposition analyses showed that differences in characteristics explained 55.35% stunting disparity by household expenditure. Meanwhile, rural-urban disparity was mostly explained by differences in responses (56.20%), with low birth weight and unexplained variables as predominant contributors. CONCLUSION: There were slight differences in stunting determinants by household expenditure and rural-urban status in Indonesia. Stunting disparities were attributed to differences in characteristics and responses between the less and more advantaged populations. To improve the effectiveness of stunting reduction programs, specific interventions tailored to address the differences between the more and less advantaged population are needed.

Beyond personal factors: Multilevel determinants of childhood stunting in Indonesia.

BACKGROUND: Stunting is still a major public health problem in low- and middle-income countries, including Indonesia. Previous studies have reported the complexities associated with understanding the determinants of stunting. This study aimed to examine the household-, subdistrict- and province-level determinants of stunting in Indonesia using a multilevel hierarchical mixed effects model. METHODS: We analyzed data for 8045 children taken from the 2007 and 2014 waves of the Indonesian Family and Life Surveys (IFLS). We included individual-, family-/household- and community-level variables in the analyses. A multilevel mixed effects model was employed to take into account the hierarchical structure of the data. Moreover, the model captured the effect of unobserved household-, subdistrict- and province-level characteristics on the probability of children being stunted. RESULTS: Our findings showed that the odds of childhood stunting vary significantly not only by individual child- and household-level characteristics but also by province- and subdistrict-level characteristics. Among the child-level covariates included in our model, dietary habits, neonatal weight, a history of infection, and sex significantly affected the risk of stunting. Household wealth status and parental education are significant household-level covariates associated with a higher risk of stunting. Finally, the risk of stunting is higher for children living in communities without access to water, sanitation and hygiene. CONCLUSIONS: Stunting is associated with not only child-level characteristics but also family- and community-level characteristics. Hence, interventions to reduce stunting should also take into account family and community characteristics to achieve effective outcomes.