Naz Lubna, Ali Amjad, Yasmin Sabina, Trueha Kassahun
School of Economics and Social Sciences, Institute of Business Administration (IBA), 75270 University Road, Karachi, Pakistan.
Department of Development Studies, Karakoram International University (Hunza Campus), 15700, Shanokushal, Karimabad, Hunza, Hunza, Pakistan.
BMC Womens Health. 2025 May 14;25(1):225. doi: 10.1186/s12905-025-03752-w.
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.
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.
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).
Findings underscore the need for targeted interventions to address the complex and varied challenges posed by women's malnutrition.
在发展中国家，孕产妇营养不良的地区差异是发展的主要障碍。妇女营养不足和健康状况不佳不仅影响她们的生活质量，还影响其子女的福祉，危及国家的未来一代。本研究使用贝叶斯加法分位数回归，考察了巴基斯坦妇女体重指数极端分位数处营养不良的空间分布——较低分位数处的严重消瘦和体重不足，以及较高分位数处的超重和肥胖——以及相关风险因素。
从2017 - 2018年巴基斯坦人口与健康调查中抽取了5252名年龄在15 - 49岁的非孕非哺乳期已婚妇女作为样本。反应变量是用妇女体重指数（体重千克数/身高米数的平方）衡量的妇女营养状况。按照世界卫生组织的指南，我们使用了体重指数的四个指标，如下：严重消瘦（体重指数<16千克/平方米）；体重不足（体重指数<18.5千克/平方米）；超重（体重指数>24千克/平方米）；肥胖（体重指数≥30千克/平方米）。一组包括妇女特征和家庭相关变量的解释变量被用来评估它们与各种形式营养不良可能性的关联。采用结构化贝叶斯地理加法分位数回归方法来考察解释变量与反应变量整个条件分布的关联。
发现育龄妇女的营养不良存在相当大的地区差异。与农村妇女相比，城市地区的妇女超重的可能性更大（均值：0.3；95%置信区间：0.06，0.58）。职业女性患肥胖症的可能性较小（均值：-0.51；95%置信区间：-0.79，-0.23）。使用未改善厕所的妇女超重的可能性更大（均值：0.7；95%置信区间：0.34，1.04），肥胖的可能性更大（均值：0.90；95%置信区间：0.48，1.33）。
研究结果强调需要采取有针对性的干预措施，以应对妇女营养不良带来的复杂多样的挑战。
