{"title":"Women’s Literacy a Major Predictor of Population Size: Findings from National Family Health Survey-5","authors":"Pallavi Lohani, Arshad Ayub, Nitika, Neeraj Agarwal","doi":"10.47203/ijch.2023.v35i02.010","DOIUrl":null,"url":null,"abstract":"Background: The global population continues to rise at different rates in different parts of the world. While some countries are seeing a fast population increase, others are experiencing population loss. Significant ramifications of such changes in the global population distribution would be felt, as they are critical for meeting the Sustainable Development Goals (SDGs), or we might say that rapid population expansion poses obstacles to sustainable development.\nEstimating the population size and composition by age, sex, and other demographic parameters is crucial for analyzing the country’s future influence on poverty, sustainability, and development. This study tries to look at these parameters covered by the National Family Health Survey- 5 (NFHS 5) to see how accurate and trustworthy the predictors of district population size are.\nMethodology: The study assessed the predictors of the population size of any district. It was conducted using the secondary data of phase 1 of NFHS-5. The outcome variable is the population of each district. Household profiles, literacy among women, their marriage and fertility, contraceptive usage, and unmet need for family planning were considered to assess their potential as a predictor of the district’s population size. Principal component analysis (PCA) was conducted to identify the predictors.\nResult: PCA was conducted on 18 variables, resulting in 7 principal components. Cumulatively, these components explained 77.6% of the total variation in data. On multiple linear regression, four principal components were found significant and these were related to women’s literacy, contraceptive usage, early pregnancy, the marriage of fewer than 18 years, and those using health insurance.\nConclusion: Thus, women’s literacy plays a pivotal role in determining a region’s population size.","PeriodicalId":13363,"journal":{"name":"Indian Journal of Community Health","volume":" ","pages":""},"PeriodicalIF":0.2000,"publicationDate":"2023-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Indian Journal of Community Health","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47203/ijch.2023.v35i02.010","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
引用次数: 0
Abstract
Background: The global population continues to rise at different rates in different parts of the world. While some countries are seeing a fast population increase, others are experiencing population loss. Significant ramifications of such changes in the global population distribution would be felt, as they are critical for meeting the Sustainable Development Goals (SDGs), or we might say that rapid population expansion poses obstacles to sustainable development.
Estimating the population size and composition by age, sex, and other demographic parameters is crucial for analyzing the country’s future influence on poverty, sustainability, and development. This study tries to look at these parameters covered by the National Family Health Survey- 5 (NFHS 5) to see how accurate and trustworthy the predictors of district population size are.
Methodology: The study assessed the predictors of the population size of any district. It was conducted using the secondary data of phase 1 of NFHS-5. The outcome variable is the population of each district. Household profiles, literacy among women, their marriage and fertility, contraceptive usage, and unmet need for family planning were considered to assess their potential as a predictor of the district’s population size. Principal component analysis (PCA) was conducted to identify the predictors.
Result: PCA was conducted on 18 variables, resulting in 7 principal components. Cumulatively, these components explained 77.6% of the total variation in data. On multiple linear regression, four principal components were found significant and these were related to women’s literacy, contraceptive usage, early pregnancy, the marriage of fewer than 18 years, and those using health insurance.
Conclusion: Thus, women’s literacy plays a pivotal role in determining a region’s population size.