Bureau of Statistics, Government of the Punjab Lahore, Lahore, Pakistan.
Department of Statistics, GC University Lahore, Lahore, Pakistan.
BMC Public Health. 2020 Nov 30;20(1):1817. doi: 10.1186/s12889-020-09675-5.
Underweight prevalence continues to be major public health challenge worldwide, particularly in developing countries like Pakistan. This study is focused on socio-economic and demographic aspects of underweight prevalence among children under-five in Punjab.
In this study, several socioeconomic and demographic factors are considered using MICS-4 data-set. Only those variables which are usually described in the nutritional studies of children were picked. Covariates include: the age of children, sex of the children, age of mother, total number of children born to women, family wealth index quintile, source of drinking water, type of sanitation, place of residence, parents' education and occupation. All Categorical variables are effect coded. The child's age and the mother's age are assumed to be nonlinear, geographical region is spatial effect, while other variables are parametric in nature. Since, the response is binary, covariate comprises linear terms, nonlinear effects of continues covariates and geographic effects, so we have use Geo-additive models (based on Fully Bayesian approach) with binomial family under logit link. Statistical analysis is performed on Statistical package R using Bayes X and R2 Bayes X Libraries.
Underweight status of children was found to be positively associated with number of under-five children in household, total number of children ever born to women and age of mother when the child was born. Whereas, it negatively associated with place of residence, parent's education and family wealth index quintile. On the regional effect, the Southern Punjab has higher prevalence of underweight compared to Central and Northern Punjab.
Similarity of our results with several other studies demonstrate that the Geo-additive models are an ideal substitute of other statistical models to analyze the underweight prevalence among children. Moreover, our findings suggest the Punjab Government, to introduce target-oriented programs such as poverty reduction and enhancement of education and health facilities for poor population and disadvantaged regions, especially Southern Punjab.
全球范围内,消瘦的流行仍然是一个主要的公共卫生挑战,尤其是在巴基斯坦等发展中国家。本研究主要关注旁遮普省五岁以下儿童消瘦的社会经济和人口统计学方面。
在这项研究中,使用 MICS-4 数据集考虑了多个社会经济和人口统计学因素。只选择了通常在儿童营养研究中描述的变量。协变量包括:儿童的年龄、儿童的性别、母亲的年龄、妇女所生孩子的总数、家庭财富指数五分位数、饮用水来源、卫生类型、居住地点、父母的教育和职业。所有分类变量均采用效应编码。假设儿童的年龄和母亲的年龄是非线性的,地理区域是空间效应,而其他变量则具有参数性质。由于响应是二进制的,协变量包括线性项、连续协变量的非线性效应和地理效应,因此我们使用基于完全贝叶斯方法的地理加性模型(Geo-additive models),采用二项式家族,在对数链接下使用逻辑回归。统计分析使用 R 软件包中的 Bayes X 和 R2 Bayes X 库进行。
儿童消瘦状况与家庭中五岁以下儿童的数量、妇女所生孩子的总数以及孩子出生时母亲的年龄呈正相关,而与居住地点、父母的教育程度和家庭财富指数五分位数呈负相关。在区域效应方面,与旁遮普省的中部和北部相比,南部旁遮普省的消瘦流行率更高。
与其他几项研究的结果相似,地理加性模型是分析儿童消瘦流行率的理想替代统计模型。此外,我们的研究结果表明,旁遮普省政府应引入有针对性的计划,如减少贫困、提高教育和卫生设施,以惠及贫困人口和弱势地区,特别是南部旁遮普省。