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美国大学生的生活方式行为模式及社会人口统计学预测因素:对慢性病风险和公共卫生干预措施的启示

Lifestyle Behavior Patterns and Socio-Demographic Predictors Among US College Students: Implications for Chronic Condition Risk and Public Health Interventions.

作者信息

Peterson Keegan T, Bopp Melissa

机构信息

Department of Kinesiology, The Pennsylvania State University, University Park, PA, USA (KTP, MB).

出版信息

Am J Lifestyle Med. 2025 Jul 3:15598276251357526. doi: 10.1177/15598276251357526.

Abstract

College students are uniquely positioned to develop healthy lifestyle behaviors that reduce chronic condition risk; however, disparities exist, and certain socio-demographic characteristics may impact behavior participation. Data were collected from a large, Northeastern US university from 2018-2024. Participants (n = 6197) self-reported their demographics, physical activity (PA: aerobic and muscle-strengthening (MS)), diet, sleep, and alcohol and substance use, which informed 6 latent class indicators: independently meeting aerobic and MS guidelines, meeting diet guidelines, obtaining frequent restful sleep, heavy alcohol use, and substance use. A four-class latent class model was deemed best for data fit. Regression covariates of sexual orientation, gender identity, certain racial/ethnic identities were included in models. Four classes were identified: (1) healthy partygoer (36.8%), (2) balanced health seeker (9.6%), (3; referent) risky lifestyler (43.5%), (4) sedentary but health-conscious (10.0%). Identifying as a man, a sexual minority, and specific race/ethnicities significantly predicted class membership. A moderate proportion of college students were classified as risky lifestylers and participated in health-diminishing behaviors over health-enhancing behaviors. Gender, sexual orientation, and race/ethnicity predicted membership in classes that may increase risk of chronic conditions, emphasizing the importance of tailored approaches to reduce threats to public health.

摘要

大学生在养成有助于降低慢性病风险的健康生活方式方面具有独特优势;然而,存在差异,某些社会人口特征可能会影响行为参与度。数据收集于2018年至2024年期间美国东北部的一所大型大学。参与者(n = 6197)自行报告了他们的人口统计学信息、身体活动(PA:有氧运动和肌肉强化运动(MS))、饮食、睡眠以及酒精和药物使用情况,这些信息构成了6个潜在类别指标:独立达到有氧运动和MS指南要求、符合饮食指南、经常获得安稳睡眠、大量饮酒以及使用药物。一个四类潜在类别模型被认为最适合数据拟合。模型中纳入了性取向、性别认同、某些种族/族裔身份等回归协变量。确定了四类:(1)健康派对参与者(36.8%),(2)平衡健康追求者(9.6%),(3;参照组)高风险生活方式者(43.5%),(4)久坐但注重健康者(10.0%)。自我认同为男性、性少数群体以及特定种族/族裔显著预测了类别归属。相当一部分大学生被归类为高风险生活方式者,且参与的是有损健康而非增进健康的行为。性别、性取向和种族/族裔预测了可能增加慢性病风险的类别归属,强调了采用针对性方法以减少对公众健康威胁的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd02/12226531/eff7195bd359/10.1177_15598276251357526-fig1.jpg

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