Rezaeizadeh Golnaz, Mansournia Mohammad Ali, Sharafkhah Maryam, Daniali Seyede Shahrbanoo, Danaei Navid, Mehrparvar Amir Houshang, Sakhvidi Mohammad Javad Zare, Hakimi Hamid, Mohammadi Zahra, Kelishadi Roya, Poustchi Hossein
Digestive Diseases Research Center, Digestive Diseases Research Institute, Tehran University of Medical Sciences, Tehran, Iran.
Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Sci Rep. 2025 Apr 28;15(1):14893. doi: 10.1038/s41598-025-97619-7.
In low- and middle-income countries, undernutrition often coexists with rising obesity, creating a double burden of malnutrition (DBM). Our study employs a mathematical approach to examine how maternal socioeconomic status (SES) impacts child growth in Iranian children from infancy to age two, offering new insights into strategies for tackling both undernutrition and obesity. We used data from the PERSIAN Birth Cohort. SES was divided into quintiles using multiple correspondence analysis (MCA), and child growth was assessed with eight indicators. Missing data were handled via multiple imputation (MI). SES impacts on growth were analyzed using Generalized Estimating Equations (GEE), and BMI-Z was predicted from WAZ and HAZ through linear regression by SES and age. We explored obesity risk by comparing HAZ-to-WAZ ratios from GEE models with WAZ-to-HAZ beta ratios from regressions. Sensitivity analyses compared MI with complete-case analyses (CCA). 7169 neonates were assessed at 2, 4, 6, 12, and 24 months. SES increasingly improved WAZ with age, preventing underweight in higher SES groups. SES consistently improved HAZ, significantly enhancing stunting prevention in higher SES groups. The impact on BMI-Z increased with age, peaking in Very High SES, which shows a significant rise in obesity risk by 24 months. Comparing ratios from GEE and regression models, we found that GEE ratios were lower where BMI-Z increased. Sensitivity analysis confirmed MI and CCA consistency. Addressing DBM requires understanding how imbalanced increases in HAZ and WAZ heighten obesity risk. Future research should focus on targeted interventions to manage DBM effectively.
在低收入和中等收入国家，营养不良往往与肥胖率上升并存，形成了营养不良双重负担（DBM）。我们的研究采用数学方法，研究母亲社会经济地位（SES）如何影响伊朗儿童从婴儿期到两岁的生长发育，为应对营养不良和肥胖问题的策略提供了新的见解。我们使用了来自波斯出生队列的数据。通过多重对应分析（MCA）将SES分为五个等级，并使用八个指标评估儿童生长发育情况。通过多重填补（MI）处理缺失数据。使用广义估计方程（GEE）分析SES对生长发育的影响，并通过SES和年龄的线性回归从WAZ和HAZ预测BMI-Z。我们通过比较GEE模型中的HAZ与WAZ比率和回归中的WAZ与HAZβ比率来探索肥胖风险。敏感性分析将MI与完全病例分析（CCA）进行了比较。对7169名新生儿在2、4、6、12和24个月时进行了评估。随着年龄增长，SES对WAZ的改善作用越来越大，防止了较高SES组出现体重不足。SES持续改善HAZ，显著增强了较高SES组预防发育迟缓的能力。对BMI-Z的影响随年龄增加，在极高SES组达到峰值，这表明到24个月时肥胖风险显著上升。比较GEE和回归模型的比率，我们发现BMI-Z增加的地方GEE比率较低。敏感性分析证实了MI和CCA的一致性。应对DBM需要了解HAZ和WAZ的不平衡增加如何加剧肥胖风险。未来的研究应侧重于有针对性的干预措施，以有效管理DBM。
