Logistic Regression Model on Nutritional Status Based on Body Mass Index (BMI) in Women of Reproductive Age (WRA) in Indonesia

Chumairoh; Muhammad Nur Aidi; Anang Kurnia; Efriwati

doi:10.32628/IJSRSET24115127

Authors

Chumairoh Department of Statistics, IPB University, Bogor, Indonesia Author
Muhammad Nur Aidi Department of Statistics, IPB University, Bogor, Indonesia Author
Anang Kurnia Department of Statistics, IPB University, Bogor, Indonesia Author
Efriwati Department of Statistics, IPB University, Bogor, Indonesia Author

DOI:

https://doi.org/10.32628/IJSRSET24115127

Keywords:

Riskesdas Data, Nutritional Status, BMI, WRA, Logistic Regression

Abstract

The aggregate analysis of Riskesdas data in Indonesia revealed that nearly all provinces face a serious double burden of malnutrition. Both undernutrition and overnutrition negatively affect the quality of human resources, especially when they occur in adolescent girls, Women of Reproductive Age (WRA), and pregnant and breastfeeding women, as this can lead to intergenerational nutritional problems. Body Mass Index (BMI) is a nutritional status measurement technique recommended by WHO. Nutritional problems occur when BMI is abnormal or not ideal, categorized as underweight (<18.5 kg/m²), pre-obesity (25-29.9 kg/m²), obesity class I (30-34.9 kg/m²), obesity class II (35-39.9 kg/m²), and obesity class III (>40 kg/m²). Data from laboratory results completed up to 2017, based on selected samples from the 2013 Basic Health Research (Riskesdas), were used to assess the nutritional status of the Indonesian population. This study used 9,418 respondent data samples from 33 provinces in Indonesia. Logistic regression analysis was applied because the response variable in this study is binary, representing ideal BMI (1) and non-ideal BMI (0). The independent variables used in this study include Hemoglobin level, Ferritin level, CRP level, age group, physical activity, living location, marital status, education, and risky food consumption patterns. All independent variables are categorical. The study found that the factors influencing nutritional status based on BMI in WRA are Hemoglobin level, Ferritin level, CRP level, age, and location. The resulting logit model is logit (π)=0.27695-0.1491 (Non-anemic Hemoglobin level)-0.1721 (Normal Ferritin level)+0.741 (Non-infectious CRP level)-0.2933 (Adult age group)-0.0976 (rural location). logit (π)=0.27695-0.1491 (Non-anemic Hemoglobin level)-0.1721 (Normal Ferritin level)+0.741 (Non-infectious CRP level)-0.2933 (Adult age group)-0.0976 (rural location). The largest odds ratio The largest odds ratio was produced by the CRP level variable, indicating that CRP level is the most influential factor affecting nutritional status based on BMI in WRA, where non infectious CRP compared to infectious CRP increases the likelihood of WRA having an ideal BMI.

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