BACKGROUND: Despite its limitations, ecological study design is widely applied in epidemiology. In most cases, adjustment for age is necessary, but different methods may lead to different conclusions. To compare three methods of age adjustment, a study on the associations between @entity3494 in drinking water and incidence of @entity150 in 243 townships in Taiwan was used as an example. METHODS: A total of 3068 cases of @entity150 , including 2276 @entity1 and 792 @entity1 , were identified during a ten-year study period in the study townships. Three methods were applied to analyze the same data set on the ten-year study period. The first (Direct Method) applied direct standardization to obtain standardized incidence rate and then used it as the dependent variable in the regression analysis. The second (Indirect Method) applied indirect standardization to obtain standardized incidence ratio and then used it as the dependent variable in the regression analysis instead. The third (Variable Method) used proportions of residents in different age groups as a part of the independent variables in the multiple regression models. RESULTS: All three methods showed a statistically significant positive association between @entity3494 exposure above 0.64 mg/L and incidence of @entity150 in @entity1 and @entity1 , but different results were observed for the other exposure categories. In addition, the risk estimates obtained by different methods for the same exposure category were all different. CONCLUSIONS: Using an empirical example, the current study confirmed the argument made by other researchers previously that whereas the three different methods of age adjustment may lead to different conclusions, only the third approach can obtain unbiased estimates of the risks. The third method can also generate estimates of the risk associated with each age group, but the other two are unable to evaluate the effects of age directly.

Age adjustment in ecological studies: using a study on @entity3494 ingestion and XXXX as an example.

@entity1 :: ('9606', 'Species') :: ['women', 'men'] @entity3494 :: ('MESH:D001151', 'Chemical') :: ['arsenic'] @entity150 :: ('MESH:D001749', 'Disease') :: ['bladder cancer']
@entity150 :: (MESH:D001749,Disease) :: ['bladder cancer']
