Ramaswamy, M. & Kelly, P. (2015). Sexual Health Risk and the Movement of Women of Women Between Disadvantaged Communities and Local Jails, Behavioral Medicine, 41:3, 115-122 https://www.ncbi.nlm.nih.gov/pubmed/26332929
The unit of clustering for this study was zip codes - the 13 most disadvantaged zip codes in Kansas City Kansas and Missouri which overlapped with areas of high incarceration compared to other zip codes with low incarceration rates.
The researchers hypothesize that fears and insecurities at the community level reflect the reality of disadvantage, serving as barriers to preventative health care which minimized risk. The exposures - fear of one's neighborhood, level of neighborhood violence, and victimization by neighborhood violence, were measured as level 1 variables - through surveys of incarcerated women.
Bivariate tests and logistic regression were used to determine relationships between the variables of interest. It seems to me that there are other methods which would provide a richer understanding of the relationships in addition to these straightforward analysis. GEE may be appropriate because of the ability to describe risk in a population instead of an individual. Not that I want it to be more complicated, but the independent variables were neighborhood-level violence, social capital and trust, and incarceration density which are complex concepts which may require a different approach?