THE EFFECTS OF SOCIAL ASSISTANCE PROGRAMS ON STUNTING PREVALENCE RATES IN INDONESIA

Background: Social assistance, such as Non-Cash Food Assistance (BPNT) and the Family Hope Program (PKH), is among the instruments used to eradicate stunting in the short and long term. Therefore, it is important to ensure that individuals effectively use it.
Aims: This study aimed to review the effect of social assistance on stunting prevalence rates in Indonesia.
Methods: This research employs a quantitative approach, utilizing numerical measurements and statistical analysis. The data is secondary and sourced from the Central Bureau of Statistics and the Ministry of Finance. The specific method applied is the generalized method of moments (GMM) dynamic panel regression. The research sample encompasses panel data from 34 provinces from 2015 to 2021. This study utilizes the indicator of very short height for children less than five years of age as a proxy for stunting. Furthermore, low height in children is adopted as a measure of stunting. Furthermore, this study adopted a measure of low height in children to indicate stunting.
Results: The results showed that social assistance negatively affected stunting, supported by various other indicators such as the proportion of proper sanitation, the average length of schooling, protein consumption, and drinking water sources. Meanwhile, excessive calorie consumption increases stunting in a certain period.
Conclusion: In this condition, government social assistance was urgently needed since access to the lowest decile households increased stunting rates. The practical implications for policy derived from these findings involve optimizing the efficiency of social assistance initiatives, emphasizing the significance of addressing environmental factors in programs aimed at preventing stunting, integrating health and nutrition initiatives, and implementing educational campaigns within communities to raise awareness about calorie consumption.
Keywords: child health, social assistance, stunting, toddlers
Introduction
Parents are expected to anticipate exceptional growth and development of their children. However, the expectation is not achieved due to malnutrition-related challenges. In a study conducted by the Ministry of Health, 10.2% of Indonesian children weighed less than 2500 grams, 19.6% exhibited abnormal weight indicative of malnourishment, while 32.2% experienced stunting(Health, 2018). The developmental delays were experienced due to malnutrition, and the impact resulted in stunting. According to the World Health Organization (WHO) definition, stunting is manifested when the height of children is minus two standard deviations of the growth median for their age(W.H.O., 2022). Consequently, stunting children are shorter than their peers of the same age group.
The Indonesian Nutrition Status Survey (SSGI) showed that the prevalence of stunting decreased from 24.4% in 2021 to 21.6% in 2022(Health RI, 2023). Even though a decrease was experienced in 2022, the condition remained a severe problem for children health.(Wardani et al., 2022)stated that stunting causes a decline in cognitive, language, and motor functions as well as several degenerative diseases. This statement was supported by President Joko Widodo at the BKKBN National Work Meeting, where the condition was reported to be dangerous for children’s development, leading to poor learning abilities, mental retardation, and chronic diseases(Communication & Service, 2023).(Tampy & , 2020)stated that normal children could improve their cognitive abilities. Therefore, the condition can affect the quality of human resources in the future.
The causes of stunting are very complex and previous studies showed that there was the influence of maternal factors such as height, age during pregnancy, duration of breastfeeding, dietary nutrition during pregnancy, and maternal education level on the increased risk(Beal et al., 2018);(Nurbiah et al., 2019);(Tyas & Setyonaluri, 2022);(Wardani et al., 2022). Furthermore, stunted mothers with low education increase the likelihood of stunting(Widyaningsih et al., 2022). A large number of children living at home under age five and the lack of mothers attending antenatal care services can also increase the risk(Titaley et al., 2019).
In another study,(Kandpal et al., 2016)examined the Conditional Cash Transfer (CCT) program, one of which was Pantawid for stunting in the Philippines. The program had a significant effect on reducing stunting by using cross-sectional data and providing cash transfers to poor households for education, children’s health, and maternal health services. Meanwhile,(Muhtar et al., 2022)showed that social assistance programs, as measured through the Family Hope Program (PKH) and the Staple Food Program, reduced stunting in Blora, Central Java.
In several previous studies, stunting has often focused on socioeconomic factors and household characteristics(Source Title, 2021), as well as maternal(Beal et al., 2018);(Nurbiah et al., 2019);(Tyas & Setyonaluri, 2022);(Wardani et al., 2022)and environmental factors(Irianti et al., 2019);(Cameron et al., 2021);(Nizaruddin & Ilham, 2022). Furthermore, there are studies linking stunting to food prices(Ilman & Wibisono, 2019). While only a few studies have directly linked cases of stunting to cash assistance programs like Indonesia's PKH, the program does contain elements that can potentially contribute to addressing stunting. Though not specifically designed to tackle stunting, PKH provides financial assistance to households, which can improve their access to nutritious food and essential health services. Therefore, the impact of direct assistance on stunting in Indonesia was examined. This study contributes to the reduction of stunting and provides an overview of the importance of direct cash assistance to improve children’s nutritional status, impacting health and decreasing the condition.
Variable | Acronym | Definition | Unit | Source | |
---|---|---|---|---|---|
Dependent | Stunting | 𝑆𝑡𝑢𝑛𝑡𝑖𝑛𝑔𝑖𝑡 | The prevalence of (very short) in children under 5 years/children | Percentage | BPS |
Independent | Social Assistance | 𝑆𝐴𝑖𝑡 | Realization of social assistance funds for each province | Percentage | Ministry of Finance |
Sanitation | 𝑆𝑎𝑛𝑖𝑡𝑎𝑡𝑖𝑜𝑛𝑖𝑡 | Households by province and have access to proper sanitation | Percentage | BPS | |
Sanitary Proportion | 𝑆𝑎𝑛𝑖𝑡𝑎𝑟𝑦_𝑃𝑟𝑜𝑝𝑖𝑡 | Proportion of households that have access to proper sanitation services | Percentage | BPS | |
Mean Years School | 𝑀𝑌𝑆𝑖𝑡 | The average number of years spent by residents aged 15 and over | Years | BPS | |
Prevalence of Undernourishment | 𝑃𝑜𝑈𝑖𝑡 | An estimate of the proportion of a given population, for which the usual daily energy consumption from food is not sufficient to meet the required energy level | Percentage | BPS | |
Average calorie consumption | 𝐶𝑎𝑙𝑜𝑟𝑖𝑒𝑖𝑡 | Average calorie consumption for each province | Percentage | BPS | |
Average protein consumption | 𝑃𝑟𝑜𝑡𝑒𝑖𝑛𝑖𝑡 | Average protein consumption for each province | Percentage | BPS | |
Internet access | 𝐼𝑛𝑡𝑒𝑟𝑛𝑒𝑡_𝑢𝑟𝑏𝑎𝑛𝑖𝑡 | Households that have accessed the internet in 3 last month in urban | Percentage | BPS | |
𝐼𝑛𝑡𝑒𝑟𝑛𝑒𝑡_𝑟𝑢𝑟𝑎𝑙𝑖𝑡 | Households that have accessed the internet in 3 last month in the rural | Percentage | BPS | ||
Source of drinking water | 𝑆𝐷𝑊𝑖𝑡 | Households with an adequate source of drinking water in urban and rural | Percentage | BPS | |
𝑆𝐷𝑊_𝑢𝑟𝑏𝑎𝑛𝑖𝑡 | Households with an adequate source of drinking water in urban | Percentage | BPS | ||
𝑆𝐷𝑊_𝑟𝑢𝑟𝑎𝑙𝑖𝑡 | Households with an adequate source of drinking water in rural | Percentage | BPS |
Method
In this study, a quantitative method was used with a stochastic model to consider the existence of variables with a probability distribution(Gujarati, 2004). In addition, Generalized Method of Moments (GMM) was used to estimate parameters in dynamic panel data and overcome autocorrelation as well as heteroscedasticity problems. GMM equated the moment from the sample condition to the population. Robustness check was
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