g., chain smoking), (f) the necessity to give up activities in favor of nicotine use, and (g) continued use despite recurrent physical or psychological problems likely to have been caused by nicotine use. Nicotine withdrawal was assessed as a syndrome as described by the DSM-IV based on four symptoms: (a) the use of nicotine upon waking, (b) the use of nicotine after being in a situation in selleck chem which nicotine was restricted, (c) the use of nicotine to relieve or avoid withdrawal symptoms, and (d) the need to wake up in the middle of the night to use nicotine. The reliability and validity of the nicotine dependence diagnosis was assessed via random subsample of 347 respondents who were reinterviewed with the nicotine dependence module up to 10 weeks after initial appraisal (Grant, Moore, & Kaplan, 2003).
The reliability of the previous 12-month (i.e., current) diagnosis was good (k = .63). Furthermore, a series of linear regression analyses were used to validate the diagnoses by examining the association between nicotine dependence and Short-Form-12v2 (an often used measure of generic quality of life which generates 10 component and profile scores assessing various dimensions of physical and mental disability; Ware, Kosinkski, Turner-Bowker, & Gandek, 2002) physical disability scores. Lifetime nicotine dependence (vs. no lifetime nicotine dependence) was measured as a binary variable. Smoking Smoking was measured with two binary variables: current smoking (vs. never smoking) and former smoking (lifetime, but not current smoking vs. never smoking).
Demographic Variables Age, sex, marital status (never married, married/cohabitating, separated/divorced/widowed), and race/ethnicity (non-Hispanic Whites, Blacks, Hispanics, and other) were the demographic factors examined as covariates. Data Analysis Statistical Package for Social Sciences (SPSS) Version 14.0 for Windows was used for all analyses (Nelson & Wittchen, 1998). Frequency distributions and measures of central tendency were conducted to characterize the study sample. Chi-square analyses were conducted to compare individuals with and without COPD on demographic Batimastat characteristics and mental disorders. Logistic regression analyses were used to examine the relationships between current smoking, former smoking, and nicotine dependence and COPD, adjusting for differences in demographics. The same procedure was then used to examine the relationship between COPD and depressive and anxiety disorders, adjusting for sociodemographic factors and current smoking. Analyses were then adjusted for former smoking, and subsequently lifetime nicotine dependence was added to the model. All analyses were evaluated using the two-tailed 0.