Out of the 11,478 children under 6 months of age included in MICS-6 (Pakistan), 3,655 children (1,831 males and 1,824 females) met the specified criteria and were selected using the \"Novel Case Selection Method\". The sample was distributed across provinces as follows: 841 (23.0%) from KPK, 1,464 (40.1%) from Punjab, 819 (22.4%) from Sindh, and 531 (14.5%) from Balochistan. This sample encompassed both rural (76.4%) and urban (23.6%) populations. Following data cleaning and outlier removal, a total of 3,540 records for weight (1,768 males and 1,772 females) and 3,515 records for height (1,759 males and 1,756 females) were ultimately available for the development of standard charts. The Bayesian Information Criterion (BIC) was employed to determine the optimal degrees of freedom for L, M, and S using RefCurv_0.4.2. Three families within the gamlss class-namely, Box Cox Cole and Green (BCCG), Box Cox T (BCT), and Box Cox Power Exponential (BCPE)-were applied, each with three smoothing techniques: penalized splines (ps), cubic splines (cs), and polynomial splines (poly). The best-fitted model was selected from these nine combinations based on the Akaike Information Criteria.
The Novel Case Selection Method yielded 3655 cases as per criteria. After cleaning the data, this method lead to selection of 3540 children for \"weight for age\" (W/A) and 3515 children for \"height for age\" (H/A). The \"BCPE\" family and \"ps\" as smoothing method proved to be best on AIC for all four curves, i.e. the W/A male, W/A female, H/A male, and H/A female. The optimum selected degrees of freedom for the curve \"W/A\", for both genders were (M = 1, L = 0, S = 0). The optimum degrees of freedom for H/A male were again (M = 1, L = 0, S = 0), but for females the selected degrees of freedom were (M = 1, L = 1, S = 1). The indigenous fitted standard curves for Pakistan were on lower trajectory in comparison to WHO standards.
This study uses the Novel Case Selection Method with introduced algorithms to construct tailored growth charts for lower and middle-income countries. Leveraging extensive MICS data, the methodology ensures representative national samples. The resulting charts hold practical value and await validation from established data sources, offering valuable tools for policy makers and clinicians in diverse global contexts.
方法:在MICS-6(巴基斯坦)中包括的11,478名6个月以下儿童中,3,655名儿童(1,831名男性和1,824名女性)符合指定标准,并使用“新型病例选择方法”进行选择。样本分布在各省如下:来自KPK的841(23.0%),旁遮普1,464(40.1%),819(22.4%)来自信德省,531人(14.5%)来自俾路支省。该样本涵盖了农村(76.4%)和城市(23.6%)人口。在数据清理和异常值删除之后,总共有3,540份体重记录(男性1,768份,女性1,772份)和3,515份身高记录(男性1,759份,女性1,756份),采用贝叶斯信息准则(BIC)来确定L的最佳自由度,M,和S使用RefCurv_0.4.2。gamlss类中的三个家庭-即,BoxCoxColeandGreen(BCCG),BoxCoxT(BCT),并应用了BoxCox幂指数(BCPE),每个都有三种平滑技术:惩罚样条(ps),三次样条(cs),和多项式样条(聚)。根据Akaike信息标准从这9种组合中选择最佳拟合模型。
结果:根据标准,新的病例选择方法产生了3655例。清理数据后,这种方法导致选择3540名儿童为“年龄体重”(W/A),选择3515名儿童为“年龄身高”(H/A)。对于所有四条曲线,“BCPE”族和“ps”作为平滑方法被证明在AIC上是最好的,即W/A男性,W/A女性,H/A男性,和H/A女性。曲线“W/A”的最佳选择自由度,男女均为(M=1,L=0,S=0)。H/A男性的最佳自由度再次为(M=1,L=0,S=0),但是对于女性,选择的自由度为(M=1,L=1,S=1)。与世卫组织标准相比,巴基斯坦的土著拟合标准曲线处于较低的轨道。
结论:本研究使用新的案例选择方法和引入的算法,为中低收入国家构建量身定制的增长图。利用广泛的MICS数据,该方法确保具有代表性的国家样本。生成的图表具有实用价值,并等待已建立数据源的验证,在不同的全球背景下,为政策制定者和临床医生提供有价值的工具。