Women’s Literacy a Major Predictor of Population Size: Findings from National Family Health Survey-5

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.

[1]  T. Guinnane,et al.  The Introduction of Bismarck's Social Security System and its Effects on Marriage and Fertility in Prussia , 2021, Population and Development Review.

[2]  G. Aryal Methods of Population Estimation and Projection , 2020 .

[3]  Zheng Shen,et al.  The fertility effects of public pension: Evidence from the new rural pension scheme in China , 2020, PloS one.

[4]  S. Yaya,et al.  Prevalence of child marriage and its impact on fertility outcomes in 34 sub-Saharan African countries , 2019, BMC international health and human rights.

[5]  K. K. Singh,et al.  The role of change in fertility desire on change in family planning use: A longitudinal investigation in urban Uttar Pradesh, India , 2019, Gates open research.

[6]  T. Loney,et al.  Is Educating Girls the Best Investment for South Asia? Association Between Female Education and Fertility Choices in South Asia: A Systematic Review of the Literature , 2018, Front. Public Health.

[7]  A. Chari,et al.  The causal effect of maternal age at marriage on child wellbeing: Evidence from India , 2017 .

[8]  S. Sarkar,et al.  Female Literacy Rate is a Better Predictor of Birth Rate and Infant Mortality Rate in India , 2013, Journal of family medicine and primary care.

[9]  Blessing Mberu,et al.  Global population trends and policy options , 2012, The Lancet.

[10]  Susheela Singh,et al.  Adding It Up: The Costs and Benefits of Investing In Family Planning and Maternal and Newborn Health , 2009 .

[11]  M. Dibley,et al.  Factors associated with non-utilisation of postnatal care services in Indonesia , 2009, Journal of Epidemiology & Community Health.

[12]  A. Worku,et al.  Differentials of fertility in North and South Gondar zones, northwest Ethiopia: A comparative cross-sectional study , 2008, BMC public health.

[13]  Pathak Kb,et al.  National Family Health Survey. , 1993, Population research abstract : a contribution to research on India's population.

[14]  K. K. Singh,et al.  The role of change in fertility desire on change in family planning use: A longitudinal investigation in urban Uttar Pradesh, India , 2019, Gates open research.

[15]  Sebsib Muanenda Determinants of Modern Contraceptive Methods among Reproductive Age Women in Ayssaita District, Afar National Regional State, Ethiopia , 2018 .