目的:确定膳食模式并分析与社会弱势儿童消费状况相关的因素,Maceió,阿拉戈斯州,巴西,2019年8月至2021年12月。
方法:这是一项横断面研究;社会人口统计学,收集人体测量和食物消耗变量,使用因子分析确定膳食模式;使用泊松回归分析相关性.
结果:在研究的567名儿童中,确定了两种饮食模式,健康和不健康;年龄≥24个月(PR=2.75;95CI1.83;4.14),健康模式中男性(PR=0.66;95CI0.49;0.87)和母亲受教育年限≤9年(PR=0.61;95CI0.46;0.81)较高;不健康模式与年龄≥24个月(PR=1.02;95CI1.01;1.03)和男性(PR=1.46;95CI1.08;1.98)相关.
结论:健康模式在年龄≥24个月的儿童中更为常见,在受教育程度低的男性儿童和母亲中频率较低;年龄≥24个月的儿童和男性表现出更高的不健康模式患病率。
结果:定义了两种膳食模式,健康和“不健康”,与男性有关,年龄≥24个月,母亲受教育时间≤9年。
■研究数据可以帮助致力于初级医疗保健服务的卫生专业人员,比如营养学家,计划干预措施,以促进儿童的健康饮食习惯。
结论:有必要对这些人群进行前瞻性研究,以评估本研究中发现的关联的因果关系。计划更有效的公共卫生行动。
OBJECTIVE: To identify dietary patterns and analyze factors associated with the consumption profile of socially vulnerable children, Maceió, state of Alagoas, Brazil, August 2019 to December 2021.
METHODS: This was a cross-sectional study; sociodemographic, anthropometric and food consumption variables were collected, factor analysis was used to identify dietary patterns; associations were analyzed using Poisson regression.
RESULTS: Among the 567 children studied, two dietary patterns were identified, healthy and unhealthy; age ≥ 24 months (PR = 2.75; 95%CI 1.83;4.14), male gender (PR = 0.66; 95%CI 0.49;0.87) and maternal schooling ≤ 9 years (PR = 0.61; 95%CI 0.46;0.81) was higher in the healthy pattern; the unhealthy pattern was associated with age ≥ 24 months (PR = 1.02; 95%CI 1.01;1.03) and male gender (PR = 1.46; 95%CI 1.08;1.98).
CONCLUSIONS: The healthy pattern was more frequent in children aged ≥ 24 months, less frequent in male children and mothers with low level of schooling; children aged ≥ 24 months and males showed a higher prevalence of the unhealthy pattern.
RESULTS: Two dietary patterns were defined, healthy and \"unhealthy\", which were associated with male gender, age ≥ 24 months and maternal schooling ≤ 9 years of study.
UNASSIGNED: The study data can assist health professionals dedicated to primary healthcare services, such as nutritionists, in planning interventions to promote healthy eating habits aimed at children.
CONCLUSIONS: Prospective studies with these populations are necessary to assess the causality of the associations found in this study, aiming to plan more effective public health actions.