The use of uncertain exposure-A method to define switching and add-on in pharmacoepidemiology

PURPOSE

When defining exposure to pharmacological treatments in pharmacoepidemiology, register data often do not provide information regarding if a pharmacological treatment is a switch or an add-on. This study aims to compare two methods defining switching and add-on therapies and their impact on exposure-outcome associations. Additionally, to guide bias reduction, it aims to describe how the methods relate to immortal time bias and selection bias.

METHODS

Cohort study using Swedish population-based health registers to identify antidepressant (AD) prescriptions as exposures while hospitalizations for psychiatric reasons were used as an empirical outcome example. The first method for exposure definition used conditioning on future exposure (FE), the second used the concept of uncertain exposure (UE). To estimate associations between outcome and exposure categories "Use of one AD," "Use of two or more ADs", and "UE" compared to "Unexposed," hazard ratios (HRs) and 95% confidence intervals were estimated using Cox regression adjusted for age and sex.

RESULTS

Using the UE method, 7.2% of time periods were classified as "UE" with a notable proportion of psychiatric hospitalizations (7.7%) occurring during this time, while when using the FE method these hospitalizations were distributed over unexposed time and AD use time. The FE method resulted in slightly higher associations than the UE method. The highest HR was found during "UE": HR (95% CI) 5.54 (5.06-6.07).

CONCLUSIONS

This study suggests that to reduce the potential immortal time bias, selection bias, and exposure misclassification inherent to the FE method, the UE method could be used for identifying switching and add-on therapies. If not used as a main exposure definition, the UE method may be used to investigate the impact of UE time in a sensitivity analysis.

Comparing Different Residential Neighborhood Definitions and the Association Between Density of Restaurants and Home Cooking Among Dutch Adults

The definition of neighborhoods as areas of exposure to the food environment is a challenge in food environment research. We aimed to test the association of density of restaurants with home cooking using four different definitions of residential neighborhoods. We also tested effect modification by age, length of residency, education, and income. This innovative cross-sectional study was conducted in the Netherlands (N = 1245 adults). We calculated geographic information system-based measures of restaurant density using residential administrative neighborhood boundaries, 800 m and 1600 m buffers around the home and respondents' self-defined boundaries (drawn by the respondents on a map of their residential area). We used adjusted Poisson regression to test associations of restaurant density (tertiles) and the outcome "weekly consumption of home-cooked meals" (six to seven as compared to five days per week (day/week) or fewer). Most respondents reported eating home-cooked meals for at least 6 day/week (74.2%). Regardless of the neighborhood definition used, no association between food environment and home cooking was observed. No effect modification was found. Although exposure in terms of density of restaurants was different according to the four different neighborhood definitions, we found no evidence that the area under study influences the association between density of restaurants and home cooking among Dutch adults.