The effects of town level variables before and after adjustment for individual level variables
| Town level variable | Analysis A3-150 | Analysis B3-150 | ||||||
|---|---|---|---|---|---|---|---|---|
| Town variance, after fitting each variable on its own (plus age) | % of town variance explained, after age adjustment | Odds ratio for effect of town level variable, per SD increase (95% CI) | Town variance, after fitting each variable plus all subject level variables | % of town variance explained, after adjustment for all subject level variables | Odds ratio for effect of town level variable (95% CI) | |||
| Water hardness | 0.0200 | 30 | 0.91 (0.83 to 1.00) | 0.0128 | 9 | 0.96 (0.88 to 1.05) | ||
| Average maximum temperature | 0.0116 | 59 | 0.88 (0.81 to 0.95) | 0.0098 | 30 | 0.93 (0.86 to 1.02) | ||
| Average minimum temperature | 0.0243 | 14 | 0.94 (0.85 to 1.03) | 0.0114 | 19 | 0.95 (0.87 to 1.03) | ||
| Average daily sunshine | 0.0157 | 45 | 0.89 (0.82 to 0.98) | 0.0112 | 21 | 0.95 (0.87 to 1.03) | ||
| Annual rainfall | 0.0192 | 32 | 1.10 (1.01 to 1.21) | 0.0125 | 11 | 1.04 (0.96 to 1.14) | ||
↵3-150 In analysis A, each variable is adjusted for age alone. In analysis B, each variable is adjusted for all eight subject level variables: age, smoking, physical activity, BMI, alcohol intake, systolic blood pressure, cholesterol, social class, and height. The percentage of town variance explained is the percentage reduction in the variance for a model that includes the particular town level variable from that given for a model not including that town level variable.