OBJECTIVE: To describe common 10-year drinking trajectories followed by men age 50 years or older and identify risk factors for those trajectories. DESIGN: Longitudinal data were used to derive a semiparametric group-based model. PARTICIPANTS: Men from the Health and Retirement Study age 50-65 years in 1998 who completed three or more of the six interviews conducted from 1998 to 2008, including our 1998 baseline interview. MEASUREMENTS: Biannual data on number of drinks per drinking day were used to derive drinking trajectories. Risk factors included baseline age, race, ethnicity, education, marital status, retirement, smoking, binge drinking, vigorous exercise, body mass index, depression, pain, self-reported health, and chronic disease. RESULTS: The best-fitting model included consistent infrequent drinkers and nondrinkers (40.6% of cohort), increasing drinkers (5.5%), decreasing drinkers (7.6%), consistent at-risk drinkers (15.6%), and consistent moderate drinkers (30.7%). Adjusted logistic regression models comparing men with similar 1998 drinking levels who subsequently followed different trajectories identified significant risks associated with age, education, smoking, binge drinking, depression, pain, and self-reported health. To illustrate, odds ratios (ORs) and 95% confidence intervals (95% CIs) suggest that baseline infrequent drinkers were less likely to follow an increasing drinkers trajectory if they were older (OR: 0.57, 95% CI: 0.38-0.82) and smoked cigarettes (OR: 0.47, 95% CI: 0.30-0.74). Baseline drinkers were less likely to follow a decreasing trajectory if they reported more than 12 years of education (OR: 0.58, 95% CI: 0.42-0.82) and thought that their health was excellent or very good (OR: 0.54, 95% CI: 0.39-0.76). CONCLUSION: Only 30.7% of older men in this cohort were moderate drinkers throughout the follow-up. Many older men may benefit from brief counseling on the risks and benefits of drinking.
OBJECTIVE: To describe common 10-year drinking trajectories followed by men age 50 years or older and identify risk factors for those trajectories. DESIGN: Longitudinal data were used to derive a semiparametric group-based model. PARTICIPANTS: Men from the Health and Retirement Study age 50-65 years in 1998 who completed three or more of the six interviews conducted from 1998 to 2008, including our 1998 baseline interview. MEASUREMENTS: Biannual data on number of drinks per drinking day were used to derive drinking trajectories. Risk factors included baseline age, race, ethnicity, education, marital status, retirement, smoking, binge drinking, vigorous exercise, body mass index, depression, pain, self-reported health, and chronic disease. RESULTS: The best-fitting model included consistent infrequent drinkers and nondrinkers (40.6% of cohort), increasing drinkers (5.5%), decreasing drinkers (7.6%), consistent at-risk drinkers (15.6%), and consistent moderate drinkers (30.7%). Adjusted logistic regression models comparing men with similar 1998 drinking levels who subsequently followed different trajectories identified significant risks associated with age, education, smoking, binge drinking, depression, pain, and self-reported health. To illustrate, odds ratios (ORs) and 95% confidence intervals (95% CIs) suggest that baseline infrequent drinkers were less likely to follow an increasing drinkers trajectory if they were older (OR: 0.57, 95% CI: 0.38-0.82) and smoked cigarettes (OR: 0.47, 95% CI: 0.30-0.74). Baseline drinkers were less likely to follow a decreasing trajectory if they reported more than 12 years of education (OR: 0.58, 95% CI: 0.42-0.82) and thought that their health was excellent or very good (OR: 0.54, 95% CI: 0.39-0.76). CONCLUSION: Only 30.7% of older men in this cohort were moderate drinkers throughout the follow-up. Many older men may benefit from brief counseling on the risks and benefits of drinking.
Authors: Cynthia I Campbell; Andrea H Kline-Simon; Michael Von Korff; Kathleen W Saunders; Constance Weisner Journal: Subst Use Misuse Date: 2017-03-27 Impact factor: 2.164
Authors: Ellen W Yeung; Matthew R Lee; Yoanna McDowell; Kenneth J Sher; Ian R Gizer Journal: Alcohol Clin Exp Res Date: 2020-02-18 Impact factor: 3.455