ArticleHeliyon2020
Estimating lifetime malnourished period and its statistics based on the concept of Markov chain with reward.
Article in Heliyon, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- A deep learning approach for classifying and predicting children's nutritional status in Ethiopia using LSTM-FC neural networks.BioData mining · 2025Article
- Multistate Markov chain modeling for child undernutrition transitions in Ethiopia: a longitudinal data analysis, 2002-2016.BMC medical research methodology · 2024Article
- Dynamic Bayesian network modeling for longitudinal data on child undernutrition in Ethiopia (2002-2016).Frontiers in public health · 2024Article
- Lifetime impact of being underweight or overweight/obese during childhood in Vietnam.BMC public health · 2022Article
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Authors and funding
3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Malnutrition among women, accessed through body mass index, has great consequences for achieving key national targets. This study introduces the concept of lifetime malnourished period (LMP): the number of years a woman would remain malnourished, either as underweight or overweight given that she is currently malnourished, and its measures of variation. Markov chain with rewards was used to compute the moments of LMP based on age-specific mortality rates and proportion of women of reproductive age that were either underweight or overweight using data from the 2013 Nigeria Demographic and Health Survey. Each of the two malnutrition status was treated as a Bernoulli-distributed reward with probability taken as the proportion of overweight or underweight women at specific age. Findings indicate that the average LMP for an underweight woman in Nigeria at age 15 years is 2.3 years but 5.8 for overweight. The remaining LMP for underweight is lower among women who attain higher level of education than for those with no or primary level of education with standard deviation reducing with age. Further, we found overweight women from the richest households and those from urban areas to have longer years of remaining in that state of health than their other counterparts, and that longevity contributes more to the variance in LMP for overweight than for underweight women.
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