Factors Influencing Stunting in Indonesia 2018 With Geographically Weighted Regression Analysis
DOI:
https://doi.org/10.32628/IJSRSET25122143Keywords:
Stunting, Quadran Method, Global Regression, Geographically Weighted RegressionAbstract
Stunting is a health issue with long-term effects on human resource quality. This study analyzes factors influencing stunting prevalence in Indonesia using the Geographically Weighted Regression (GWR) approach. Using 2018 provincial-level data, the study examines the impact of social, health, and education factors on stunting rates, categorized by gender. Analysis employs Global Regression to identify key explanatory variables before applying GWR to capture spatial variations. Results reveal significant regional differences, where factors such as Insurance, Participation School, Immunization, Happiness, Water, and Years School exhibit varying influences. The GWR model outperforms global regression, achieving R-squared values of 0.6641 (males) and 0.6589 (females), with AIC values of 506.871 and 499.160, respectively. These findings highlight the importance of localized policies to address stunting effectively.
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References
Aidi MN and Widodo Y. 2018. Stunting Dataset from Basic Health Research [Unpublished dataset]. Ministry of Health Indonesia.
Agustina, M., Abapihi, B., Wibawa, G. N. A., and Yahya, I. 2022. Modeling the Factors Influencing the Open Unemployment Rate in Indonesia Using a Spatial Regression Approach. In Seminar Nasional Sains dan Terapan VI. 56-70.
Akolo, I. R. (2022). Comparison of the rook and queen contiguity weight matrices in spatial autoregressive model and spatial error model.. Jambura Journal of Probability and Statistics. 3(1):11-18.
Anselin, L. (1995). Local Indicators of Spatial Association—LISA. Geographical Analysis, 27(2): 93-115.
Black RE, Victora CG, Walker SP, Bhutta ZA, Christian P, Onis MD, Ezzati M, Grantham-Mcgregor S, Katz J, Martorell R, Uauy R. 2013. Maternal and child undernutrition and overweight in low-income and middle-income countries. The Lancet, 382(9890), 427-451
Boots, B. N. & Getis A. (1988). Point pattern analysis. SAGE Publications.
Breusch, T. S., and Pagan, A. R. (1979). A Simple Test for Heteroscedasticity and Random Coefficient Variation. Econometrica, 47(5): 1287-1294.
Brunsdon, C., Fotheringham, A. S., & Charlton, M. E. (1996). Geographically weighted regression: a method for exploring spatial nonstationarity. Geographical analysis, 28(4), 281-298.
de Onis M, Borghi E, Arimond M, Webb P, Croft T, Saha K, De-Regil LM, Thuita F, Heidkamp R, Krasevec J, Hayashi C, Flores-Ayala R. Prevalence thresholds for wasting, overweight and stunting in children under 5 years. 2019. Public Health Nutr. 22(1):175-179.
Fadliana, A. & Drajat, P.P., 2021. Mapping of stunting risk factors based on geographic information systems using the Geographically Weighted Regression method. J IKRAITH INFORMATIKA. 5(3):91-102.
Fotheringham, A. S. (2002). Geographically weighted regression: the analysis of spatially varying relationships. John Wily and Sons Ltd.
Lesage JP and Pace RK. (2009). Introduction to Spatial Econometrics. Chapman and Hall/CRC.
Ministry of Health Indonesia. (2019). National Basic Health Research Report 2018. Kemenkes RI.
Ministry of Health Indonesia. (2021). National Basic Health Research Report 2021. Kemenkes RI.
Nakaya T, Fotheringham AS, Brunsdon C, and Charlton M. (2005). Geographically weighted Poisson regression for disease association mapping. Statistics in Medicine, 24(17), 2695-2717.
Pfeiffer, D. U., Robinson, T. P., Stevenson, M., Stevens, K. B., Rogers, D. J., & Clements, A. C. 2008. Spatial analysis in epidemiology (Vol. 142, No. 10.1093). Oxford: Oxford university press.
Statistics Indonesia. (2022). Profile of Indonesian Children 2022. BPS RI.
Sarkar, Debaprasad and Haldar, Sushil Kumar. 2014. Socioeconomic Determinants of Child Malnutrition in India: Evidence from NFHS-III. Economic & Political Weekly. 49(44):73-77.
Purwanti R and Nurfita D. 2019. Review literatur: Analysis of the socio-demographic determinants of stunting occurrences in young children across various developing countries. Health Research Bulletin. 47(3):153-164.
UNICEF. (2019). The State of the World’s Children: Children, food and nutrition. United Nations Children’s Fund.
UNICEF, WHO, & World Bank. (2021). Levels and Trends in Child Malnutrition. Geneva: World Health Organization.
Wamani H, Astrøm AN, Peterson S, Tumwine JK, Tylleskär T. Boys are more stunted than girls in Sub-Saharan Africa: A meta-analysis of 16 demographic and health surveys. BMC Pediatrics, 7(1): 17.
WHO. (2006). WHO Child Growth Standards: Length/height-for-age, weight-for-age, weight-for-length, weight-for-height, and body mass index-for-age: Methods and development. Geneva: World Health Organization.
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