Table 4.

Results of Stepwise Multiple Linear Regression Analyses to Sort Significant Predictors of Prostate Cancer Incidence

	Excluding meats			Including meat
Rank	Variables Entered	Adjusted R Squared	Rank	Variables Entered	Adjusted R Squared
1	Ageing	0.31	1	Meat	0.332
2	Urbanization	0.354	2	Ageing	0.386
3	Ibs	Not a major predictor	3	Is	0.404
4	GDP PPP	Not a major predictor	4	Urbanization	0.417
5	Obesity %	Not a major predictor	5	GDP PPP	Not a major predictor
			6	Obesity	Not a major predictor

Stepwise multiple linear regression modelling is reported. Contribution of variables is listed in order of how much they contribute to prostate cancer incidence; Meat intake (kg/capita/year) sourced from the Food and Agriculture Organization; Ageing (percent of males ages 65 and above) and GDP PPP (gross domestic product converted to international dollars using purchasing power parity rates) and urbanization (the percent of males living in urban areas) were sourced from the World Bank. Male obesity prevalence (percent of males aged 18+ with BMI ≥ 30 kg/m²); Is was extracted from previous publications.