Table 1.
Global data containing variables included in the fertility–temperature models.
Fig 1.
Correlation plots for birth rate and other factors known to affect birth rate including: Temperature, GDP, PM 2.5, BMI among Males (M) and females (F) On a global scale.
Birth rate was correlated or anti-correlated with each factor known to play a role in female fecundity. 182 countries across the globe were included in this analysis. The red lines in the scatterplots located in the lower quadrant are lines derived using Locally Weighted Scatterplot Smoothing (LOWESS). These lines provide the overall shape of the distribution.
Fig 2.
Global variation is evident in birth rate (i.e., fecundity), annual temperature, GDP, air pollution (PM 2.5) and body mass index (BMI) in both males and females.
Many variables that affect fertility vary across the globe along with birth rate. Therefore, statistical models that explain this variation can help inform our understanding of the factors underlying the female fertility–birth season relationship.
Table 2.
Regression model with BMI Included as confounder.
Table 3.
Regression model results for factors that influence birth rate without including BMI.