Geospatial inequalities in women’s malnutrition in Pakistan
Abstract Background In developing countries, regional disparities in maternal malnutrition are a major deterrent to development. Inadequate nutrition and poor health among women not only affect their quality of life but also the well-being of their children, risking the future generation of the coun...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-05-01
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| Series: | BMC Women's Health |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12905-025-03752-w |
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| Summary: | Abstract Background In developing countries, regional disparities in maternal malnutrition are a major deterrent to development. Inadequate nutrition and poor health among women not only affect their quality of life but also the well-being of their children, risking the future generation of the country. This study examines the spatial distribution of malnutrition at the extreme quantiles of Body Mass Index—severe thinness and underweight at the lower quantile and over-weight and obese at the upper quantile— and associated risk factors among women in Pakistan using Bayesian additive quantile regression. Methods A sample of 5,252 of the currently non-pregnant and non-lactating married women aged 15–49 was taken from Pakistan Demographic and Health Survey 2017–18. The response variable was the women’s nutritional status measured in body mass index (weight in kilograms/height in meters squared) of women. Following WHO guidelines, we used four indicators of BMI, as follows: severe thinness (BMI < 16 kg/m2); underweight (BMI < 18.5 kg/m2); Overweight (BMI > 24 kg/m2); and obese (BMI > = 30 kg/m2). A set of explanatory variables comprising women’s characteristics and household related variables were used to assess their association with the likelihood of various forms of malnutrition. The structured Bayesian Geo-additive Quantile regression approach was employed to examine the association of the explanatory variables with the entire conditional distribution of the response variable. Results The sizable regional variation was found in malnutrition among reproductive age women. Women living in urban areas are more likely to become overweight (mean: 0.3; 95% CI: 0.06, 0.58) than their rural counterparts. Working women are less prone to obesity (mean: -0.51; 95% CI: -0.79, -0.23). Women with unimproved toilet are more likely to become overweight (mean: 0.7; 95%CI: 0.34., 1.04) and obese (mean: 0.90; 95%CI: 0.48, 1.33). Conclusions Findings underscore the need for targeted interventions to address the complex and varied challenges posed by women’s malnutrition. |
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| ISSN: | 1472-6874 |