{"title":"坦桑尼亚五岁以下儿童人体测量相关结果分析。","authors":"Edgar E Pallangyo, Amina S Msengwa","doi":"10.1177/23333928241228916","DOIUrl":null,"url":null,"abstract":"<p><p>The study aimed at applying Multivariate Generalized Linear Mixed Models to examine factors associated with correlation outcomes, in particular, anthropometric measurements among under-five children in Tanzania. Three anthropometric measurements: weight-for-age (WAZ), height-for-age (HAZ), and weight-for-height (WHZ) among under-five children in Tanzania were jointly modeled to identify common factors associated with childhood malnutrition. A total of 9052 children with valid measures of height and weight were processed and analyzed. The results indicate that WAZ was correlated with HAZ (<i>P</i>-value < 2e-16) and WHZ (<i>P</i>-value < 2e-16). The Multivariate Ordered Logit Model has lower AIC = 53213.92 and BIC = 52727.95, indicating better model fit than the Multivariate Ordered Probit Model. In Tanzania, the age of the child, birth order, mother education level, child gender, mother working status, wealth index, marital status, and mother body mass index are important determinants of malnutrition among children under the age of five. Moreover, the common factors were child's age, Birth order, Mother's education attainment, child's sex, Mother working status, wealth index, Marital status, and Mother's Body Mass Index. As a result, emphasis should be placed on analyzing correlated health outcomes in order to draw conclusions about the factors that may have a mutual effect on anthropometric measurements.</p>","PeriodicalId":12951,"journal":{"name":"Health Services Research and Managerial Epidemiology","volume":"11 ","pages":"23333928241228916"},"PeriodicalIF":1.5000,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10854380/pdf/","citationCount":"0","resultStr":"{\"title\":\"Analysis of Correlated Outcomes of Anthropometric Measurements for Under-Five Children in Tanzania.\",\"authors\":\"Edgar E Pallangyo, Amina S Msengwa\",\"doi\":\"10.1177/23333928241228916\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The study aimed at applying Multivariate Generalized Linear Mixed Models to examine factors associated with correlation outcomes, in particular, anthropometric measurements among under-five children in Tanzania. Three anthropometric measurements: weight-for-age (WAZ), height-for-age (HAZ), and weight-for-height (WHZ) among under-five children in Tanzania were jointly modeled to identify common factors associated with childhood malnutrition. A total of 9052 children with valid measures of height and weight were processed and analyzed. The results indicate that WAZ was correlated with HAZ (<i>P</i>-value < 2e-16) and WHZ (<i>P</i>-value < 2e-16). The Multivariate Ordered Logit Model has lower AIC = 53213.92 and BIC = 52727.95, indicating better model fit than the Multivariate Ordered Probit Model. In Tanzania, the age of the child, birth order, mother education level, child gender, mother working status, wealth index, marital status, and mother body mass index are important determinants of malnutrition among children under the age of five. Moreover, the common factors were child's age, Birth order, Mother's education attainment, child's sex, Mother working status, wealth index, Marital status, and Mother's Body Mass Index. As a result, emphasis should be placed on analyzing correlated health outcomes in order to draw conclusions about the factors that may have a mutual effect on anthropometric measurements.</p>\",\"PeriodicalId\":12951,\"journal\":{\"name\":\"Health Services Research and Managerial Epidemiology\",\"volume\":\"11 \",\"pages\":\"23333928241228916\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2024-02-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10854380/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Health Services Research and Managerial Epidemiology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/23333928241228916\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q3\",\"JCRName\":\"HEALTH POLICY & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Health Services Research and Managerial Epidemiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/23333928241228916","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"HEALTH POLICY & SERVICES","Score":null,"Total":0}
Analysis of Correlated Outcomes of Anthropometric Measurements for Under-Five Children in Tanzania.
The study aimed at applying Multivariate Generalized Linear Mixed Models to examine factors associated with correlation outcomes, in particular, anthropometric measurements among under-five children in Tanzania. Three anthropometric measurements: weight-for-age (WAZ), height-for-age (HAZ), and weight-for-height (WHZ) among under-five children in Tanzania were jointly modeled to identify common factors associated with childhood malnutrition. A total of 9052 children with valid measures of height and weight were processed and analyzed. The results indicate that WAZ was correlated with HAZ (P-value < 2e-16) and WHZ (P-value < 2e-16). The Multivariate Ordered Logit Model has lower AIC = 53213.92 and BIC = 52727.95, indicating better model fit than the Multivariate Ordered Probit Model. In Tanzania, the age of the child, birth order, mother education level, child gender, mother working status, wealth index, marital status, and mother body mass index are important determinants of malnutrition among children under the age of five. Moreover, the common factors were child's age, Birth order, Mother's education attainment, child's sex, Mother working status, wealth index, Marital status, and Mother's Body Mass Index. As a result, emphasis should be placed on analyzing correlated health outcomes in order to draw conclusions about the factors that may have a mutual effect on anthropometric measurements.