孟加拉国农村地区24-59个月儿童的营养状况:以BMI指数衡量的评估

Mosiur Rahman, G. Mostofa, Sarker Obaida Nasrin
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引用次数: 33

摘要

本研究采用统计方法确定与孟加拉国农村地区24-59个月儿童营养状况相关的因素。本研究使用2004年孟加拉国人口健康调查数据(N=652)。根据体重指数(BMI\wt单位kg/ht单位m2)定义儿童的营养状况。采用描述性和多元逻辑回归方法对数据进行分析。据观察,女孩比男孩体重更轻。本研究表明,尽管24-59月龄的儿童(包括男孩和女孩)体重健康的人数最多,但其中很大一部分体重不足。双变量分析表明,与青春期(<20岁)和较高年龄组(≥30岁)的母亲相比,在中年组(20-30岁)分娩的母亲有更多健康的男孩(61.7%)和女孩(56.1%)。多变量逻辑回归分析表明,为钱工作的妇女比不为钱工作的母亲生下健康体重的孩子的可能性高2.5倍。研究还发现,体重不足的儿童比例在没有补充维生素A的儿童中明显更高。可能影响24 ~ 59月龄儿童营养状况的其他主要影响因素为被调查者的受教育程度、丈夫的受教育程度和职业、家庭资产指数和母亲的最后分娩年龄。
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Nutritional status among children aged 24-59 months in rural Bangladesh: An assessment measured by BMI index
This study employs statistical methods to identify the factors associated with nutritional status among children aged 24-59 months in rural Bangladesh. Bangladesh Demographic Health Survey data 2004 (N=652) were used for this study. Child’s nutritional status was defined in terms of Body Mass Index (BMI\wt in kg/ht in m2). Descriptive and multivariate logistic regression methods were employed in analyzing the data. It was observed that that girl children’s were more under weighted than the boys. This study elucidates that although maximum numbers of children (both boys and girls) aged 24-59 months have healthy weight a large portion of them were under weighted .Bivariate analysis shows that mothers who gave last birth in their middle age group (20-30 years) have more healthy boys (61.7%) and girls (56.1%) children as compared the mothers who gave their first birth during adolescence (<20 years) and women with higher age group (≥30 years). Multivariate logistic regression analysis shows that women who worked for cash were two-and-a-half times more probability of having healthy weighted child than among the mothers who did not work for cash. It was also found that proportion of under weighted children was significantly greater among those who had not taken vitamin A supplementation. The other main contributing factors likely to affect nutritional status of children aged 24-59 months were respondent’s education, husband’s education and occupation, household assets index and mothers’ age at last birth,
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