Anthropometry as Indicator of the Family Economic Condition
Abstract
The prevalence of Indonesian population experiencing hunger reaches 20.1%.Anthropometry is considered capable to measure socio-economic conditionsbecause it is directly related to the financial purchasing power of food that affectsintake patterns. The aim of this study is to test the reliability of the familyanthropometry using Height for Age Z Score (HAZ) index and Body Mass Index ZScore (BMIZ) as indicator of the family economic condition. This cross-sectionalstudy design located in Astanajapura (Rural) and Kesambi (Urban) Subdistrict,Cirebon, West Java. The stratification sampling method was held to obtainsamples from all main family members of the selected households (1,999persons) from 405 families. Data analysis used ROC method to obtain the cut-offpoints of anthropometry index, validity test for sensitivity and specificity, andKappa test for the reliability test. The findings indicate that the family HAZanthropometry index could represent the family economic condition better thanthe BMIZ and it is reliable to become an indicator for the economic condition bothin rural and urban areas. There is a positive correlation between consumption percapita and the HAZ index where the higher the family HAZ z score is, the higherthe family consumption per capita. The method can be used to measure the poorprevalence in macro level and select the target of poor families in the micro levelusing the family HAZ anthropometry index. It is recommended to use HAZ indexto estimate prevalence of poor families within the micro level, but the processmust not include children under two years old due to the technical obstacleduring measurement and other substance factors. Further research is needed toproduce a more accurate method in using the family anthropometry as anindicator of family economic condition.
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34. WHO. WHO Child Growth Standards. Geneva: WHO Press; 2007.
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2. UNICEF. World Hunger is Still Not Going Down after Three Years and Obesity is Still Growing–UN Report. 2019.
3. The Central Statistics Agency. The Official News of Indonesian Statistics. Jakarta, Indonesia: The Central Statistics Agency; 2019.
4. Global Hunger Index. 2019 Global Hunger Index by Severity. 2019.
5. Delisle H, Batal M. The Double Burden of Malnutrition Associated with Poverty. The Lancet. 2016;387(10037):2504–2505.
6. FAO, World Bank. Food Data Collection in Household Consumption and Expenditure Surveys : Guidelines for Low and Middle Income Countries. Food and Agriculture OeganizationThe World Bank Group; 2018.
7. Kim R, Rajpal S, Joe W, Corsi DJ, Sankar R, Kumar A, et al. Assessing Associational Strength of 23 Correlates of Child Anthropometric Failure: An Econometric Analysis of the 2015-2016 National Family Health Survey, India. Social Science Medicine. 2019;238(112374):1-10.
8. Tyrrell J, Astley CM, Tuke M, Hirschhorn JN, Weedon MN. Height, Body Mass Index, and Socio Economic Status: Mendelian Randomisation Study in UK Biobank. BMJ. 2016;352(582):1-10.
9. Asiseh F, Yao J. Family Income and Body Mass Index – What Have We Learned From China. Health Economics Review. 2016; 6(52):1-10.
10. Bommer C, Vollmer S, Subramanian S V. How Socioeconomic Status Moderates the Stunting-Age Relationship in Low Income and Middle-Income Countries. BMJ Global Health. 2019;4(1):1–10.
11. Mary S. How Much Does Economic Growth Contribute to Child Stunting Reductions? Economies. 2018;6(4):1-8.
12. The Central Statistics Agency. District/City Poverty Data and Information in 2018. Jakarta, Indonesia: Central Statistics Agency; 2018.
13. The Central Statistics Agency. Poverty Line Calculation, Percentage of Poor Population and Poverty Severity Index. Jakarta, Indonesia: Central Statistics Agency; 2019.
14. Petca A, Colceriu AD, Bălăianu A, Diac I, Dogăroiu C. Anthropometric Measurements Illustrating the Socio-Economic Effects on Growth and Development in a Subadult Sample Population in Romania. Romanian Society of Legal Medicine. 2019;27(2):130–135.
15. Herzog B, Lacruz ME, Haerting J, Hartwig S, Tiller D, et al. Socio-Economic Status and Anthropometric Changes - A Meta-Analytic Approach from Seven German Cohorts. Obesity. 2016;24(3):710–718.
16. Parikka S, Mäki P, Levälahti E, Lehtinen Jacks S, Martelin T, Laatikainen T. Associations Between Parental BMI, Socioeconomic Factors, Family Structure and Overweight in Finnish Children: A Path Model Approach Disease Epidemiology Chronic. BMC Public Health. 2015;15(1):1–10.
17. Haryanto T, Umar U. Kondisi Sosial Ekonomi Rumah Tangga dan Masalah Stunting Balita di Indonesia. Media Trend Berkala Kajian Ekonomi & Studi Pembangunan. 2019;14 (1):41–48.
18. Fikrina LT. Hubungan Tingkat Sosial Ekonomi Dengan Kejadian Stunting Pada Balita Usia 24-59 Bulan Di Desa Karangrejek Wonosari Gunung Kidul. Yogyakarta: Fakul-tas Ilmu Kesehatan Universitas ‘Aisyiyah Yogyakarta; 2017.
19. Devakumar D, Kular D, Shrestha BP, Grijalva-Eternod C, Daniel RM, Saville NM, et al. Socioeconomic Determinants of Growth in a Longitudinal Study in Nepal. Maternal Child Nutrition. 2017;14(1):1–8.
20. Aryastami NK, Shankar A, Kusumawardani N, Besral B, Achadi E, Jauhari AB. Low Birth Weight Was the Most Dominant Predictor Associated with Stunting Among Children Aged 12–23 Months in Indonesia. BMC Nutrition. 2017;3(16):1–6.
21. Titaley CR, Ariawan I, Hapsari D, Muasyaroh A, Dibley MJ. Determinants of the Stunting of Children Under Two Years Old in Indonesia: A Multilevel Analysis of the 2013 Indonesia Basic Health Survey. Nutrients. 2019;11(5): 1-13.
22. Marty L, Dubois C, Gaubard MS, Maidon A, Lesturgeon A, Gaigi H, et al. Higher Nutritional Quality at No Additional Cost among Low-Income Households: Insights from Food Purchases of “Positive Deviants”. American Journal of Clinical Nutrition. 2015;102(1):190–198.
23. Poirier MJP, Grépin KA, Grignon M. Approaches and Alternatives to the Wealth Index to Measure Socioeconomic Status Using Survey Data: A Critical Interpretive Synthesis. Social Indicators Research. 2020;148:1-46.
24. Moeed MA, Azam I, Naz F, Salman M. Social Determinants of Anthropometric Outcomes: A Differentiation and Correlation Study. International Journal of Scientific Research. 2017;6(10):337–340.
25. Ajayi OR, Matthews G, Taylor M, Kvalsvig JD, Davidson LL, Kauchali S, et al. Association of Anthropometric Status and Residential Locality Factors with Cognitive Scores of 4–6-Year-Old Children in Kwazulu-Natal, South Africa. South African Journal Clinical Nutrition. 2019;33(4):1-9.
26. Ervin PA, Bubak V. Closing the Rural-Urban Gap in Child Malnutrition: Evidence from Paraguay, 1997–2012. Economics Human Biology. 2019;32:1–10.
27. Noviana U, Ekawati H. Analisis Faktor Berat Badan Lahir, Status Ekonomi Sosial, Tinggi Badan Ibu Dan Pola Asuh Makan
dengan Kejadian Stunting. Prosiding Seminar Nasional Poltekkes Karya Husada Yogyakarta. 2019;1(1):31–45.
28. Fitriahadi E. Hubungan Tinggi Badan Ibu dengan Kejadian Stunting pada Balita Usia 24-59 Bulan. Jurnal Kebidanan dan Keperawatan Aisyiyah. 2018;14(1):15–24.
29. World Bank. Classifying Countries by Income. World Bank Group; 2019. 30. Mejía-Guevara I, Corsi DJ, Perkins JM, Kim R, Subramanian S V. Variation in Anthropometric Status and Growth Failure in Low and Middle-Income Countries. Pediatrics. 2018; 141(3):1-9.
31. Rahmariza E, Tanziha I, Sukandar D. Analisis Determinan Karakteristik Keluarga Dan Pemenuhan Hak Kesehatan Anak Serta Dampaknya Terhadap Status Gizi. Media Kesehatan Masyarakat Indonesia. 2016;12 (3):153–160.
32. Grasgruber P, Hrazdíra E. Nutritional and Socio-Economic Predictors oAdult Height in 152 World Populations. Economics Human Biology. 2020;37.
33. Dewey KG. Reducing Stunting by Improving Maternal, Infant and Young Child Nutrition in South Asia: Evidence, Challenges and Opportunities. Maternal & Child Nutrition. 2016;12(1):27–38.
34. WHO. WHO Child Growth Standards. Geneva: WHO Press; 2007.
35. Kemenkes RI. Peraturan Menteri Kesehatan Nomor 73 tahun 2014 tentang Angka Kecukupan Gizi yang Dianjurkan untuk Bangsa Indonesia. Jakarta: Kementerian Kesehatan RI; 2014.
36. Pusat Informasi Harga Pangan Strategis Nasional. Perkembangan Harga Pangan Berdasarkan Daerah. Indonesia; 2018.
Authors
Wahyuniar, L., Sutrisna, B., Djauhari, A. B., & Djuwita, R. (2020). Anthropometry as Indicator of the Family Economic Condition. Media Kesehatan Masyarakat Indonesia, 16(4), 477-489. https://doi.org/10.30597/mkmi.v16i4.11025
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