Nutritional status of tribal and non-tribal adults in rural Bangladesh: A comparative study

Karim, Md. Reazul; Mamun, Abu Sayed Md. Al; Hossain, Md. Ripter; Islam, Md. Nurul; Rana, Md. Masud; Wadood, Abdul; Bose, Kaushık; Bharati, Premananda; Hossain, Md. Golam

doi:10.1371/journal.pone.0287625

Cited by 2 publications

(1 citation statement)

References 27 publications

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“…Calculate the BMI for each respondent in the study using the formula (pre-pregnancy weight in kg/height in meters squared), which categorizes as underweight (<18.5 kg/m2), normal weight (18.5�BMI�24.9 kg/m2), and overweight (�25.0 kg/m2). Previous literature conducted in Asian countries has used the BMI categories recommended by the World Health Organization (WHO) [2,[29][30][31][32][33]. Following this literature, we have used the WHO-recommended BMI categories in our analysis.…”

Section: Study Variables and Measurementmentioning

confidence: 99%

Machine learning prediction of nutritional status among pregnant women in Bangladesh: Evidence from Bangladesh demographic and health survey 2017–18

Begum,

Rahman,

Omar Faruk

2024

PLoS ONE

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Aim Malnutrition in pregnant women significantly affects both mother and child health. This research aims to identify the best machine learning (ML) techniques for predicting the nutritional status of pregnant women in Bangladesh and detect the most essential features based on the best-performed algorithm. Methods This study used retrospective cross-sectional data from the Bangladeshi Demographic and Health Survey 2017–18. Different feature transformations and machine learning classifiers were applied to find the best transformation and classification model. Results This investigation found that robust scaling outperformed all feature transformation methods. The result shows that the Random Forest algorithm with robust scaling outperforms all other machine learning algorithms with 74.75% accuracy, 57.91% kappa statistics, 73.36% precision, 73.08% recall, and 73.09% f1 score. In addition, the Random Forest algorithm had the highest precision (76.76%) and f1 score (71.71%) for predicting the underweight class, as well as an expected precision of 82.01% and f1 score of 83.78% for the overweight/obese class when compared to other algorithms with a robust scaling method. The respondent’s age, wealth index, region, husband’s education level, husband’s age, and occupation were crucial features for predicting the nutritional status of pregnant women in Bangladesh. Conclusion The proposed classifier could help predict the expected outcome and reduce the burden of malnutrition among pregnant women in Bangladesh.

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Section: Study Variables and Measurementmentioning

confidence: 99%

Machine learning prediction of nutritional status among pregnant women in Bangladesh: Evidence from Bangladesh demographic and health survey 2017–18

Begum,

Rahman,

Omar Faruk

2024

PLoS ONE

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Association of child marriage and nutritional status of mothers and their under-five children in Bangladesh: a cross-sectional study with a nationally representative sample

Mim,

Al Mamun,

Sayem

et al. 2024

BMC Nutr

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Background Child marriage remains an important problem around the world with young mothers and their under-five children often experiencing under-nutrition. The problem is rarely studied in the Bangladeshi population. This paper was designed to identify the association between child marriage and nutritional status of mothers and their under-five children in Bangladesh. Methods Nationally representative secondary data was used for this study, data was extracted from the Bangladesh Demographic and Health Survey (BDHS) 2017–18. The sample consisted of 7235 mothers aged 18–49 years and their under-five children. The mothers were classified into two classes according to their age at first marriage: (i) child marriage (marriage at < 18 years) and (ii) not child marriage (marriage at ≥ 18 years). The nutritional status of mothers was measured by body mass index (BMI), and under-five children’s nutritional status was measured by (i) height-for-age (z-score) (stunting), (ii) weight-for-age (z-score) (underweight), and (iii) weight-for-height (z-score) (wasting). The chi-square test and two-level logistic regression model were used for data analysis using SPSS software (IBM version 20). Results The prevalence of child marriage among Bangladeshi women was 69.0%, with the mean and median of age at the first marriage being 16.57 ± 2.83 years and 16 years, respectively. Of the mothers, 15.2% suffered from chronic energy deficiency (underweight), and 72.8% were married at < 18 years. The prevalence of stunting, underweight, and wasting among under-five children in Bangladesh was 31.0%, 22.0%, and 8.5%, respectively. Compared to women married at the age of ≥ 18 years, there was a significantly higher likelihood of chronic energy deficiency among women who married at < 18 years [Adjusted OR = 1.27, CI: 1.05–1.82; p < 0.05]. Under-five children of mothers married before the age of 18 were more likely to have stunting [Adjusted OR = 1.201, CI: 1.11–1.72; p < 0.05], wasting [Adjusted OR = 1.519, CI: 1.15-2.00; p < 0.01], and underweight [Adjusted OR = 1.150, CI: 1.09–1.82; p < 0.05] compared to children of mothers who married at age ≥ 18. Conclusion The rate of child marriage among Bangladeshi women is high, and it is significantly associated with malnutrition among mothers and their under-five children. The Bangladesh government can use the findings of this study to prevent and reduce child marriage and malnutrition among mothers and their under-five children to achieve sustainable development goals by 2030.

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Nutritional status of tribal and non-tribal adults in rural Bangladesh: A comparative study

Cited by 2 publications

References 27 publications

Machine learning prediction of nutritional status among pregnant women in Bangladesh: Evidence from Bangladesh demographic and health survey 2017–18

Machine learning prediction of nutritional status among pregnant women in Bangladesh: Evidence from Bangladesh demographic and health survey 2017–18

Association of child marriage and nutritional status of mothers and their under-five children in Bangladesh: a cross-sectional study with a nationally representative sample

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