Abstract：
OBJECTIVE: To determine the suitability of 11 basic statistical models for estimating child-growth of under-five children and to bring-forth estimated growth curves for mean height & mean weight by their selected birth-weight categories for Central Region of India.
METHODS: The study used fourth round of National Family Health Survey-4 (NFHS-4) data of India, consisting of 75,645 under-five children, belonging to 3 Indian States - Chhattisgarh, Madhya Pradesh & Uttar Pradesh. The children of the Region were first divided into 4 sub categories according to their birth-weight: (i) < 2000 gm, (ii) 2000-2499 gm, (iii) 2500-2999 gm (iv) 3000+gm, growth curve for mean height and mean weight were estimated for two sexes.
RESULTS: The significant association of 7 socio-demographic factors studied, namely - age & sex of child, birth-order, BMI, mother\'s highest level of education, place of residence and wealth index. Further, Cubic Model and Power Model, demonstrated best-fit to height & weight data of under-five children, belonging to different birth-weight categories, for estimating growth of boys & girls separately. These models enabled us to estimate mean height and mean weight, with 95% CI, for boys and girls separately by different birth-weight categories.
CONCLUSIONS: Study concluded that 7 socio-demographic factors were significantly associated with birth-weight. Further, Cubic Model and Power Model were most suitable for estimating child growth in terms of mean height & mean weight for boys and girls - considering specific birth-weight categories.
METHODS: The study used fourth round of National Family Health Survey-4 (NFHS-4) data of India, consisting of 75,645 under-five children, belonging to 3 Indian States - Chhattisgarh, Madhya Pradesh & Uttar Pradesh. The children of the Region were first divided into 4 sub categories according to their birth-weight: (i) < 2000 gm, (ii) 2000-2499 gm, (iii) 2500-2999 gm (iv) 3000+gm, growth curve for mean height and mean weight were estimated for two sexes.
RESULTS: The significant association of 7 socio-demographic factors studied, namely - age & sex of child, birth-order, BMI, mother\'s highest level of education, place of residence and wealth index. Further, Cubic Model and Power Model, demonstrated best-fit to height & weight data of under-five children, belonging to different birth-weight categories, for estimating growth of boys & girls separately. These models enabled us to estimate mean height and mean weight, with 95% CI, for boys and girls separately by different birth-weight categories.
CONCLUSIONS: Study concluded that 7 socio-demographic factors were significantly associated with birth-weight. Further, Cubic Model and Power Model were most suitable for estimating child growth in terms of mean height & mean weight for boys and girls - considering specific birth-weight categories.
摘要：
目的：确定11个基本统计模型用于估计五岁以下儿童的儿童生长的适用性，并根据选定的出生体重类别得出平均身高和平均体重的估计生长曲线。印度中部地区。
方法：该研究使用了印度的第四轮全国家庭健康调查-4（NFHS-4）数据，由75,645名五岁以下儿童组成，属于3个印度州-恰蒂斯加尔邦，中央邦和北方邦。该地区的儿童首先根据其出生体重分为4个子类别：（i）<2000gm，(ii)2000-2499gm，(iii)2500-2999gm(iv)3000+gm,估计了两种性别的平均身高和平均体重的生长曲线。
结果：所研究的7个社会人口统计学因素的显着关联，即孩子的年龄和性别，出生顺序,BMI,母亲的最高教育水平，居住地和财富指数。Further,三次模型和Power模型，证明最适合五岁以下儿童的身高和体重数据，属于不同的出生体重类别，分别估计男孩和女孩的成长。这些模型使我们能够估计平均身高和平均体重，95%CI，分别为男孩和女孩按不同的出生体重类别。
结论：研究得出结论，7个社会人口统计学因素与出生体重显著相关。Further,考虑到特定的出生体重类别，立方模型和Power模型最适合根据男孩和女孩的平均身高和平均体重来估计儿童的生长。
方法：该研究使用了印度的第四轮全国家庭健康调查-4（NFHS-4）数据，由75,645名五岁以下儿童组成，属于3个印度州-恰蒂斯加尔邦，中央邦和北方邦。该地区的儿童首先根据其出生体重分为4个子类别：（i）<2000gm，(ii)2000-2499gm，(iii)2500-2999gm(iv)3000+gm,估计了两种性别的平均身高和平均体重的生长曲线。
结果：所研究的7个社会人口统计学因素的显着关联，即孩子的年龄和性别，出生顺序,BMI,母亲的最高教育水平，居住地和财富指数。Further,三次模型和Power模型，证明最适合五岁以下儿童的身高和体重数据，属于不同的出生体重类别，分别估计男孩和女孩的成长。这些模型使我们能够估计平均身高和平均体重，95%CI，分别为男孩和女孩按不同的出生体重类别。
结论：研究得出结论，7个社会人口统计学因素与出生体重显著相关。Further,考虑到特定的出生体重类别，立方模型和Power模型最适合根据男孩和女孩的平均身高和平均体重来估计儿童的生长。
