How sensitive are multilevel regression findings to defined area of context?: a case study of mammography use in California.

The authors develop a hybrid model of health care use that blends features of the traditional Aday-Andersen behavioral model with the socioecological modeling perspective. They use the model to conceptualize the various levels of influence expected from socioecological variables in individuals' mammography use decisions, build contextual variables from fine-grained data into four different types of geographic areas, and then use two- and three-level modeling of personal and area-level contextual factors to explain observed behavior. The central focus is on whether differentiating the conceptualized levels of influence seems to materially affect regression findings. The test could conceivably be confounded by the modifiable areal unit problem, but little evidence for this is found. Findings for California women suggest that distinctions do matter in how the levels of influence are defined for local neighborhood contextual factors. Studies using only county-level contextual factors will miss some meaningful associations related to interpersonal/proximate-level factors.