{"title":"Potential independent factors of variability of biological status and reproductive history of Yucatecan women.","authors":"F Dickinson","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>In this paper, we report the results of the application of principal component analysis (PCA) in a study of the human ecology of rural-to-urban migrantion in Yucatan, Mexico. Socioeconomic, reproductive and anthropometric data from 216 women 32 years of age or older, were obtained in 1989-1990. Seventeen socioeconomic, demographic and environmental properties of the families of such women, plus migrant status, were employed in a PCA, which yielded five independent factors, explaining 57.1% of the total variance of such properties. These factors were employed to made a multiple regression analysis on 19 anthropometric and 21 reproductive traits, age adjusted. According to the multiple regression of women's biological status to independent factors, we found that in better living conditions (Factor 3), women are heavier, taller, with more body surface and subcutaneous fat in the trunk and in the upper extremity, than in worse living conditions. Better educational level of wife and husband (Factor 2) is associated with lower number of pregnancies and alive born children, as well as less reproductive losses. Women living in families with higher income (Factor 4), have a younger age at the first pregnancy, older age at the last pregnancy, greater number of pregnancies, alive born children and alive offspring at the interview, and they experience less reproductive losses in relation to the number of pregnancies. This fact suggests that for the families in this sample, big families are a strategy to cope with poverty and uncertainty in employment and income. Our results are discussed against the reports in the literature.</p>","PeriodicalId":77401,"journal":{"name":"Studies in human ecology","volume":"11 ","pages":"31-54"},"PeriodicalIF":0.0000,"publicationDate":"1994-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Studies in human ecology","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, we report the results of the application of principal component analysis (PCA) in a study of the human ecology of rural-to-urban migrantion in Yucatan, Mexico. Socioeconomic, reproductive and anthropometric data from 216 women 32 years of age or older, were obtained in 1989-1990. Seventeen socioeconomic, demographic and environmental properties of the families of such women, plus migrant status, were employed in a PCA, which yielded five independent factors, explaining 57.1% of the total variance of such properties. These factors were employed to made a multiple regression analysis on 19 anthropometric and 21 reproductive traits, age adjusted. According to the multiple regression of women's biological status to independent factors, we found that in better living conditions (Factor 3), women are heavier, taller, with more body surface and subcutaneous fat in the trunk and in the upper extremity, than in worse living conditions. Better educational level of wife and husband (Factor 2) is associated with lower number of pregnancies and alive born children, as well as less reproductive losses. Women living in families with higher income (Factor 4), have a younger age at the first pregnancy, older age at the last pregnancy, greater number of pregnancies, alive born children and alive offspring at the interview, and they experience less reproductive losses in relation to the number of pregnancies. This fact suggests that for the families in this sample, big families are a strategy to cope with poverty and uncertainty in employment and income. Our results are discussed against the reports in the literature.