The relationship between neighborhood poverty and alcohol use: estimation by marginal structural models.
dc.contributor.author | Cerda, M | |
dc.contributor.author | Diez Roux, Ana V. | |
dc.contributor.author | Tohetgen, ET | |
dc.contributor.author | Gordon-Larsen, P | |
dc.contributor.author | Kiefe, C. I. | |
dc.date.accessioned | 2010-11-29T16:17:48Z | |
dc.date.available | 2010-11-29T16:17:48Z | |
dc.date.issued | 2010-07 | |
dc.identifier.citation | Epidemiology. 2010 Jul;21(4):482-9. <http://hdl.handle.net/2027.42/78334> | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/78334 | |
dc.description.abstract | BACKGROUND: Previous studies on the relationship of neighborhood disadvantage with alcohol use or misuse have often controlled for individual characteristics on the causal pathway, such as income-thus potentially underestimating the relationship between disadvantage and alcohol consumption. METHODS: We used data from the Coronary Artery Risk Development in Young Adults study of 5115 adults aged 18-30 years at baseline and interviewed 7 times between 1985 and 2006. We estimated marginal structural models using inverse probability-of-treatment and censoring weights to assess the association between point-in-time/cumulative exposure to neighborhood poverty (proportion of census tract residents living in poverty) and alcohol use/binging, after accounting for time-dependent confounders including income, education, and occupation. RESULTS: The log-normal model was used to estimate treatment weights while accounting for highly-skewed continuous neighborhood poverty data. In the weighted model, a one-unit increase in neighborhood poverty at the prior examination was associated with a 86% increase in the odds of binging (OR = 1.86 [95% confidence interval = 1.14-3.03]); the estimate from a standard generalized-estimating-equations model controlling for baseline and time-varying covariates was 1.47 (0.96-2.25). The inverse probability-of-treatment and censoring weighted estimate of the relative increase in the number of weekly drinks in the past year associated with cumulative neighborhood poverty was 1.53 (1.02-2.27); the estimate from a standard model was 1.16 (0.83-1.62). CONCLUSIONS: Cumulative and point-in-time measures of neighborhood poverty are important predictors of alcohol consumption. Estimators that more closely approximate a causal effect of neighborhood poverty on alcohol provided a stronger estimate than estimators from traditional regression models. | en_US |
dc.format.extent | 306566 bytes | |
dc.format.mimetype | application/pdf | |
dc.language.iso | en_US | en_US |
dc.title | The relationship between neighborhood poverty and alcohol use: estimation by marginal structural models. | en_US |
dc.type | Article | en_US |
dc.subject.hlbsecondlevel | Public Health | |
dc.subject.hlbtoplevel | Health Sciences | |
dc.contributor.affiliationum | Epidemiology, Department of | en_US |
dc.contributor.affiliationumcampus | Ann Arbor | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/78334/1/CerdaDiezRoux2010_Epidemiology.pdf | |
dc.owningcollname | Epidemiology, Department of (SPH) |
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