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PLoS One. 2018 Nov 27;13(11):e0207932. doi: 10.1371/journal.pone.0207932. eCollection 2018.

A model investigating environmental factors that play a role in female fecundity or birth rate.

Boland MR1,2,3,4.

Author information

1
Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America.
2
Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, PA, United States of America.
3
Center for Excellence in Environmental Toxicology, University of Pennsylvania, Philadelphia, PA, United States of America.
4
Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, PA, United States of America.

Abstract

OBJECTIVE:

Over 12% of women in the United States have reduced fertility and/or fecundity. Environmental factors, such as temperature, and socioeconomic factors have been implicated in reducing female fecundity. The purpose of this study is to investigate the effect of environmental factors coupled with socioeconomic factors on birth rate at the country-level. We use birth rate as a proxy for female fecundity. This will enable us to identify the most important factors affecting female fecundity.

METHODS:

Using country-specific data from 182 countries, we constructed a regression model of the effects of environmental and socioeconomic factors on birth rate at the country-level. Our model assesses the role of temperature, Gross Domestic Product (GDP) per capita, fine air particulate matter (PM 2.5), and prevalence of male and female Body Mass Index (BMI) > = 25 (age-standardized) on birth rate per country. Because many of these factors are inter-dependent, we include all possible two-way interaction terms to assess the role of individual factors and interactions between multiple factors in the model.

RESULTS:

In the full regression model, we found that GDP per capita along with 5 interaction terms were significant after adjusting for multiple testing. Female BMI was only nominally significant. GDP per capita was independently associated with birth rate (adjusted p-value <0.001). Prevalence of BMI > = 25 age-standardized in males and females were also significant when interacting with air pollution or GDP on female fecundity (birth rate). Temperature did not affect birth rate either independently or as an interaction unless BMI was removed from the model.

CONCLUSION:

A country's economic wealth was the most significant factor in predicting birth rate in a statistical model that includes environmental and socioeconomic variables. This is important for future studies investigating environmental factors involved in increasing or decreasing female fecundity.

Conflict of interest statement

The authors have declared that no competing interests exist.

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