{"title":"Demographic and Socio-economic Characteristics Impact on Fertility in Pakistan","authors":"","doi":"10.51709/19951272/summer2022/10","DOIUrl":null,"url":null,"abstract":"Fertility is the actual reproductive performance of an individual, a couple\nwhich determines the country’s population size. Pakistan is the 5th most\nPopulus country in the world with high fertility rate in regional countries.\nThe trustworthy secondary data were taken from National Institute of\nPopulation Studies, Pakistan and analyzed. The mean and standard\ndeviation of children ever born (CEB) was estimated 3.2±2.41. Poisson\nand logistic regression models were applied to study the substantial role of\neight socio-economic and demographic variables regarding CEB. Poisson\nregression illustrated that contraceptive and length of marriage positively\ncorrelated with CEB, whereas the women education, age at marriage and\nwealth index showed an inverse relationship with CEB. The women\neducation i.e., illiterate, primary education, secondary education and\nhigher education is 50%, 13.9%, 20.8% and 15.3% and the corresponding\nmean CEB are 2.73, 2.48, 2.34, and 2.16, respectively. The logistic\nregression model demonstrated the negative relation between the odds\nratio and women education and age at marriage while the family size and\nlength of the marriage were found to be positively correlated. If the\nrespondent remains married for 10+ years, the odds ratio of having a large\nfamily is increased by a factor of 21.352 keeping the effect of other\nvariables kept constant. The fitted parsimonious logistic regression\nmodel’s correct classification for small family, large family and overall are\n82.3%, 83% and 82.7% respectively. The findings, thus, have enormous\nimplications for the Government and Population welfare Departments\nabout policies formulations","PeriodicalId":43392,"journal":{"name":"FWU Journal of Social Sciences","volume":" ","pages":""},"PeriodicalIF":0.8000,"publicationDate":"2022-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"FWU Journal of Social Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.51709/19951272/summer2022/10","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"SOCIAL SCIENCES, INTERDISCIPLINARY","Score":null,"Total":0}
引用次数: 1
Abstract
Fertility is the actual reproductive performance of an individual, a couple
which determines the country’s population size. Pakistan is the 5th most
Populus country in the world with high fertility rate in regional countries.
The trustworthy secondary data were taken from National Institute of
Population Studies, Pakistan and analyzed. The mean and standard
deviation of children ever born (CEB) was estimated 3.2±2.41. Poisson
and logistic regression models were applied to study the substantial role of
eight socio-economic and demographic variables regarding CEB. Poisson
regression illustrated that contraceptive and length of marriage positively
correlated with CEB, whereas the women education, age at marriage and
wealth index showed an inverse relationship with CEB. The women
education i.e., illiterate, primary education, secondary education and
higher education is 50%, 13.9%, 20.8% and 15.3% and the corresponding
mean CEB are 2.73, 2.48, 2.34, and 2.16, respectively. The logistic
regression model demonstrated the negative relation between the odds
ratio and women education and age at marriage while the family size and
length of the marriage were found to be positively correlated. If the
respondent remains married for 10+ years, the odds ratio of having a large
family is increased by a factor of 21.352 keeping the effect of other
variables kept constant. The fitted parsimonious logistic regression
model’s correct classification for small family, large family and overall are
82.3%, 83% and 82.7% respectively. The findings, thus, have enormous
implications for the Government and Population welfare Departments
about policies formulations