评估印尼巴淡岛学龄儿童营养不良双重负担中的社会人口、行为和母亲因素。

Narra J Pub Date : 2025-04-01 Epub Date: 2025-02-21 DOI:10.52225/narra.v5i1.2049
Roza Erda, Dachriyanus Hamidi, Desmawati Desmawati, Rosfita Rasyid, Rika Sarfika
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引用次数: 0

摘要

城市工业环境中学龄儿童的营养不良表现出营养不足和营养过剩的双重负担。本研究旨在探讨影响印尼巴淡岛小学生营养状况之因素。在巴淡岛进行了一项病例对照研究,重点关注6-12岁营养不良病例(营养不足和营养过剩)和营养良好对照的儿童及其母亲。调查对象是通过分层随机抽样从公立小学中选取的。纳入标准包括在这些学校注册的儿童,而排除标准涉及患有慢性疾病的儿童。数据通过结构化访谈收集,利用有效的问卷,人体测量评估(年龄体重和年龄身高),以及父母报告的社会经济、行为和家庭特征。统计分析采用二元逻辑回归来确定与营养不良相关的重要危险因素。共有188名儿童,包括94名营养不良病例(40名营养不足,54名营养过剩)和94名营养良好对照。研究结果显示,在社会经济因素(零花钱(p = 0.027)、家庭收入(p = 0.042))、行为因素(久坐活动(p = 0.019)、饮食习惯(p = 0.037))和家庭因素(母亲体重指数,p = 0.011;孕产妇营养知识,p = 0.004;父母教养方式,p = 0.035)。营养不良(营养不足或营养过剩)的主要危险因素包括不良的饮食习惯(调整优势比(aOR): 0.451;95%置信区间:0.225—-0.901;p = 0.024),产妇肥胖II级(aOR: 0.126;95%置信区间:0.030—-0.535;p = 0.005),孕产妇营养知识水平低(aOR: 0.294;95%置信区间:0.124—-0.696;p = 0.005)。因此,建议针对这一问题采取以家庭为中心、注重饮食习惯和孕产妇教育的干预措施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluating socio-demographic, behavioral, and maternal factors in the dual burden of malnutrition among school-aged children in Batam, Indonesia.

Malnutrition among school-aged children in urban-industrial settings presents a dual burden of undernutrition and overnutrition. The aim of this study was to examine factors influencing the nutritional status of elementary school children in Batam, Indonesia. A case-control study was conducted in Batam, focusing on children aged 6-12 years, with malnourished cases (undernutrition and overnutrition) and well-nourished controls, along with their mothers. Respondents were selected through stratified random sampling from public elementary schools. Inclusion criteria encompassed children enrolled in these schools, while exclusion criteria involved children with chronic health conditions. Data were collected via structured interviews utilizing validated questionnaires, anthropometric assessments (weight-for-age and height-for-age), and parent-reported socioeconomic, behavioral and family characteristics. Statistical analysis involved binary logistic regression to identify significant risk factors associated with malnutrition. A total of 188 children, including 94 malnourished cases (40 undernutrition and 54 overnutrition) and 94 well-nourished controls. The findings revealed significant differences between cases and controls in socioeconomic factors (pocket money (p = 0.027), family income (p = 0.042)), behavioral factors (sedentary activity (p = 0.019), dietary habits (p = 0.037)) and family factors (maternal BMI, p = 0.011; maternal nutritional knowledge, p = 0.004; parenting style, p = 0.035). Dominant risk factors for malnutrition (undernutrition or overnutrition) included poor dietary habits (adjusted odds ratio (aOR): 0.451; 95%CI: 0.225-0.901; p = 0.024), maternal obesity class II (aOR: 0.126; 95%CI: 0.030-0.535; p = 0.005), and low maternal nutritional knowledge (aOR: 0.294; 95%CI: 0.124-0.696; p = 0.005). Targeted family-centered interventions focusing on dietary practices and maternal education are therefore recommended to address this issue.

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