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3305. The intersection of sex, age, and household socioeconomic status in the multimorbidity of malaria, anaemia, and malnutrition among children 6-59 months of age in Nigeria
Invited abstract in session MB-15: Machine learning and analytics in healthcare, stream OR in Health Services (ORAHS).
Monday, 10:30-12:00Room: 18 (building: 116)
Authors (first author is the speaker)
1. | Phillips Edomwonyi Obasohan
|
Liberal Studies, Niger State Polytechnic |
Abstract
Multimorbidity of malaria, anaemia, and malnutrition (MAMM) is a condition an individual cohabits with two or more of these health outcomes and is becoming an emergent public health concern in sub-Saharan African countries. In addition, the independent associations of child’s sex, age, and socioeconomic disparities with child’s health outcomes and MAMM have been established in literature. But, the effects of the intersection of these factors, while accounting for other covariates have not been studied. Therefore, this study aimed to determine how child’s sex, age and socioeconomic status interact to explain the variations in MAMM among children age 6-59 months in Nigeria. Data from the 2018 Nigeria Demographic and Health Survey was used. A multilevel mixed effect ordinal logistic regression model was used. Five models were created in this scenario. Model 1 is the interaction between child's sex and wealth status; model 2, child's sex and age; model 3 is between child's age and wealth status; model 4 has the three 2-way interactions of child's sex, age, and household wealth status, and model 5 includes model 4 and the 3-way interactions between a child's sex, age, and wealth quintiles. Model 3 was however the model of best fit compared with other models, So, the two-way interaction effects of a child's age and wealth status are relevant in the model prediction. Thus, the variation in MAMM over a child's age differs depending on the household wealth quintile.
Keywords
- Health Care
- Logistics
- Sustainable Development
Status: accepted
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