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The study dataset contains weight factors that should be employed in any data analysis. Typically weights are used in an attempt to assure that the survey sample more accurately represents the population. The weight variable in this study is WEIGHT.The survey data were weighted to adjust for the fact that not all survey respondents were selected with the same probabilities and account for systematic nonresponse along known population parameters. Weighting involved several stages: 1) adjustment for likelihood of selection (base-weight), 2) post-stratification weighting (raking) by split-sample, and 3) truncating weights ("trimming") to make adjustments to control variance among weights.