The final sample consisted of 6662 individuals ages 65 to 90. This included 3316 men (737 men ages 65 to 69, 737 ages 70 to 74, 1330 ages 75 to 79, 351 ages 80 to 84, and 161 ages 85 to 90) and 3346 women (803 ages 65 to 69, 750 ages 70 to 74, 1329 ages 75 to 79, 330 ages 80 to 84, and 134 ages 85 to 90). Based on weighted data, participants had a mean age of 73.7 (sd = 6.3). Ethnicity data were available for 92% of the sample. Among men, respondents were 82.5% white, 5.0% African American, 5.6% Latino, and 6.9% Asian American. Among women, respondents were 79.4% white, 5.2% African American, 7.2% Latino, and 8.2% Asian American. A small percentage (2 %) reporting Pacific Islander, Native American or “other” were excluded from analyses by ethnicity.
Patterns of Alcohol Consumption
Drinking data were available for 6116 participants (3081 men and 3035 women) with 546 missing (8%) due to nonresponse on one or more drinking items. Those with missing data were older (P<.001) and more likely to be female (P<.001) and nonwhite (P<.001) than were those without missing data.
Results found that 12.1% of men and 16.6% of women drank over recommended limits. Of these, men reported an average of 3.8 (sd = 1.53) drinks and women an average of 2.2 (sd = 0.59) drinks consumed on days when they drank alcohol (not shown). There were significant overall effects on drinking category by age-group, ethnicity, and relationship status (). Among both men and women, overlimit drinking was lower in the older age-groups (eg, ages 80 to 90 vs 65–74 or 75–79), whereas ≥12-month abstinence was higher in older age-groups. Whites and Latinos had the highest percentages of overlimit drinkers and Asians the lowest percentages, and African Americans higher percentages of 12-month abstainers than other ethnic groups. Less educated men and women were more likely to report long-term abstinence or 12-month abstinence than were those with higher levels of education.
Drinking Patterns of Demographic Subgroups Among Adults Ages 65 to 90
Medical Conditions and Behavioral Health Risks
Medical conditions and behavioral health risks were examined for men and women. Overall group differences by drinking category were examined using chi square (). Logistic regression analyses examined odds of having health conditions, fair or poor self-reported health (vs good, very good, or excellent), and behavioral health risks among those who reported overlimit drinking in the prior 12 months vs moderate drinkers, adjusting for age and ethnicity. Medical conditions were also adjusted for BMI. Few significant relationships were found between overlimit drinking and prevalence of major medical conditions. Contrary to expectation, men who drank over limits had lower prevalence of heart problems (OR = 0.71, CI = 0.51, 0.99), and high cholesterol (OR = 0.71, CI = 0.53, 0.95) than that of moderate drinkers. Women who drank over limits had lower prevalence of heart problems (OR = 0.61, CI = 0.41, 0.93) and high cholesterol (OR = 0.75, CI = 0.57, 0.99) than that of moderate drinkers. When compared with moderate drinking, overlimit drinking was associated with poorer dietary habits (not trying to eat reduced-fat foods) among men (OR = 1.58, CI = 1.21, 2.06) and with current cigarette smoking among women (OR = 2.36, CI = 1.56, 3.57) and men (OR = 2.35, CI = 1.56, 3.53). Among women, overlimit drinking was associated with greater likelihood of being sedentary (OR = 1.49, CI = 1.09, 2.06), but lower likelihood of being overweight (BMI ≥30), (OR = 0.61, CI = 0.43, 0.85).
Prevalence of Medical Conditions, Self-reported Health and Behavioral Health Risks Among Men and Women Ages 65 to 90 in 4 Drinking Pattern Categories
When the relationship of drinking level with medical problems was examined using the lower recommended drinking limit for men (no more than one drink per day), as expected a much larger number of individuals were categorized as overlimit drinkers (32.2% of male study participants, rather than 12.1%). However, only one health correlate changed: overall effect of drinking level on having a lower rate of heart problems became significant (P = .002, not shown).
A subanalysis compared health conditions of male heavy drinkers (n=131), who consumed over 4 drinks per day, to currently drinking males who drank less than this amount. The small number of heavy drinkers resulted in limited statistical power for this analysis within men and precluded any such comparisons for women (n=17) heavy drinkers. The only statistically significant difference was that heavy drinkers were less likely to report having or being treated for high cholesterol than were other drinkers (39.1% vs 22.1%, P = .001).
Health Factors Associated With Drinking Cessation
Logistic regression analyses examined odds of having health conditions, fair or poor self-reported health (vs good, very good, or excellent), and behavioral health risks among those who reported moderate drinking vs those who reported no drinking in the prior 12 months vs adjusting for age and ethnicity (see post hoc comparisons reported on ). Medical conditions were also adjusted for BMI. Variables associated with moderate drinking vs ≥12-month abstinence included lower likelihood of having diabetes (OR = 0.55, CI = 0.41, 0.75), depression (OR = 0.55, CI = 0.36, 0.83), anxiety (OR = 0.45, CI = 0.24, 0.85), fair or poor health (OR = 0.41, CI = 0.31, 0.53), smoking cigarettes (OR = 0.53, CI = 0.35, 0.80), and being sedentary (OR = 0.60, CI = 0.44, 0.83) among men; and heart problems (OR = 0.47, CI = 0.33, 0.66), diabetes (OR = 0.35, CI = 0.24, 0.52), arthritis (OR = 0.73, CI = 0.55, 0.97), depression (OR = 0.50, CI = 0.34, 0.72), fair or poor health (OR = 0.25, CI = 0.19, 0.34), smoking (OR = 0.48, CI = 0.30, 0.77) and being sedentary (OR = 0.37, CI = 0.26, 0.51) among women.
Predictors of Drinking Cessation
In logistic regression analysis, predictors of having quit drinking (≥12-month abstinence among former alcohol consumers) vs any level of current drinking were examined separately for men and women. To select variables for the model, bivariate chi-square analyses were used to compare demographic factors and health conditions of current drinkers to those of participants who had abstained for ≥12-months. Individuals who never drank as adults were excluded. Factors significant at the P<.10 level were included in the initial model: Age-group, ethnicity (African American, Hispanic, and Asian American vs white), marital status, education, self-reported health, diabetes, and heart problems were in the models for both genders; high blood pressure and high cholesterol were in the initial model for women only. Results of the final model found that among both men and women, drinking cessation was predicted by ethnicity (African American vs white), lower education, diabetes, and worse self-reported health. Depression was significant among men only. Heart problems were significant among women only (). Age-group was not significant in either final model.
Logistic Regression Analysis of Predictors of Having Quit Drinking (≥12-Month Abstinence) in Men and Women
To estimate overall discriminative power of the model in separating current drinkers from those who had quit drinking, we calculated the c
statistic, which is equivalent to the area under the ROC curve for the model.41
For men, c
= 0.641; for women, c
= 0.718. Results indicate the probability that the model would correctly assign possible cases involving the dependent variable 64.1% of the time for men and 71.8% of the time for women. For the overall model, pseudo-R-squared = .04 for men, P<.001, and .08 for women, P<.001.