饮食质量和体重状况由联邦营养援助计划参与、健康和人口统计预测

IF 3.2 Q2 NUTRITION & DIETETICS

Current Developments in Nutrition Pub Date : 2025-07-09 DOI:10.1016/j.cdnut.2025.107505

Lauren E Au , Charles D Arnold , Christabel Domfe , Lorrene D Ritchie , Shannon E Whaley , Marianne Bitler , Edward A Frongillo

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引用次数: 0

摘要

医疗补助计划、补充营养援助计划和妇女、婴儿和儿童特别补充营养计划（WIC）等计划提供了获得重要医疗和营养服务的途径。很少有研究调查健康的人口、社会和经济决定因素，包括花在这些项目上的时间长短，是否与儿童早期的饮食质量和体重状况有关。目的采用机器学习方法分类回归树分析确定健康预测因素，以确定饮食质量较高与较低、体重较高与较低的儿童的模式。方法采用WIC婴幼儿喂养实践研究-2(未加权N = 3051；加权N = 413,211)，分类和回归树识别出最能区分健康饮食指数-2020 (HEI-2020；范围0-100)和HEI-2020子量表（充分性和适度性），以及体重指数（体重指数单位为kg/m2） z-score在2-5 y的预测因子，包括母亲体重指数、儿童出生体重、社会人口统计学和在安全网计划上花费的时间。较高的HEI-2020分数主要由种族和族裔（如西班牙裔、西班牙裔或非西班牙裔白人）预测，WIC较长，补充营养援助计划持续时间较短。在检查HEI-2020子量表时，较高的HEI充分性主要由高等教育、母亲年龄较大、WIC持续时间较长以及种族和民族预测。较高的HEI调节主要由种族和民族以及较长的WIC持续时间预测。较高的BMI z-score主要由较高的出生体重预测。结论儿童饮食质量和体重状况与不同的健康社会决定因素有关，包括母亲体重状况、种族和民族、粮食援助计划参与情况，特别是WIC。

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Diet Quality and Weight Status are Predicted by Federal Nutrition Assistance Program Participation, Health, and Demographics

Background

Programs, such as Medicaid, the Supplemental Nutrition Assistance Program, and the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC), provide access to vital medical and nutrition services. Few studies have investigated whether demographic, social, and economic determinants of health, including length of time spent on these programs, are associated with diet quality and weight status in early childhood.

Objectives

Classification and regression tree analysis, a machine learning method, was used to determine health predictors to identify patterns of children with higher compared with lower diet quality and higher compared with lower weight status.

Methods

Using the WIC infant and toddler feeding practices study-2 (unweighted N = 3051; weighted N = 413,211), classification and regression tree identified the sequence of binary splits that best differentiated the sample on Healthy Eating Index-2020 (HEI-2020; range 0–100) and HEI-2020 subscales (adequacy and moderation), and body mass index (BMI in kg/m²) z-score at 2–5 y. Predictors, including maternal BMI, child birthweight, sociodemographics, and length of time spent on safety net programs, were considered.

Results

Higher HEI-2020 scores were primarily predicted by race and ethnicity (e.g., Hispanic, Spanish, or non-Hispanic White), and longer WIC and shorter Supplemental Nutrition Assistance Program duration. In examining HEI-2020 subscales, higher HEI adequacy was primarily predicted by higher education, older maternal age, longer WIC duration, and race and ethnicity. Higher HEI moderation was primarily predicted by race and ethnicity and longer WIC duration. Higher BMI z-score was primarily predicted by higher birth weight.

Conclusions

Child diet quality and weight status were associated with different social determinants of health, which included maternal weight status, race and ethnicity, and food assistance program participation, particularly WIC.

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