Abstract
Introduction
There is a high prevalence of at-risk drinking in the U.S. military. Among HIV-infected individuals, alcohol abuse confers additional risk for adverse health outcomes. In the military, however, the characteristics of HIV-infected individuals who engage in high-risk drinking are not well defined. The purpose of this study was to assess risk factors associated with at-risk drinking in an HIV-positive longitudinal cohort of DoD beneficiaries.
Materials and Methods
Annual prevalence of at-risk drinking was calculated for members of the U.S. Military HIV Natural History Study who initiated highly active antiretroviral therapy (HAART) during or after January 2006 through May 2014; each participant completed at least one self-reported alcohol survey within a year of HAART initiation. Univariate and multivariable logistic regression was used to analyze factors associated with at-risk drinking.
Results
Sixty-six percent of subjects (495/752) reported at-risk drinking on at least one survey after HAART initiation. At-risk drinkers were more likely to be Active Duty compared to Retired (OR 0.65 95% CI [0.46, 0.92]). In multivariate models, Caucasian race (OR 3.30 95% CI [2.31, 4.71]); Hispanic/other race (OR 2.17 95% CI [1.51, 3.14]) and younger age (OR 0.61 per 10 years older, [95%CI 0.49, 0.75]) were significantly associated with at-risk drinking. Single relationship status (OR 1.51 95% CI [1.08, 2.13]) was also associated with at-risk drinking.
Conclusions
Consistent with general alcohol consumption patterns in the military, we found a high prevalence of at-risk drinking among individuals with HIV infection, which was associated most closely with young, non-African Americans. Targeting interventions toward this group will be important to reduce at-risk drinking and its potential for HIV-related complications.
Keywords: HIV, Military, At-Risk Drinking, Alcohol
INTRODUCTION
In the U.S. military, the prevalence of binge and heavy drinking is high, particularly among younger-aged individuals.1–3 Prior reports have found that up to two-thirds of active duty military personnel below 25 years of age reported binge drinking, placing them at risk for alcohol-related harm.4 Recent data further suggest that at-risk drinking, particularly binge drinking, has increased between 1998 and 2008, and in the 2011 Department of Defense (DoD) Survey of Health Related Behaviors among Military Personnel Survey, 11.3% of current drinkers were classified as “hazardous drinkers” via the Alcohol Use Disorders Identification Test (AUDIT).1 Last, a study from the Millennium Cohort found that alcohol-related problems among active duty were significantly associated with suicide, as opposed to military-specific variables (e.g., combat).5
Excessive drinking is commonly associated with sexual risk-taking in the military6 and among HIV-infected persons,7,8 however, the patterns of alcohol consumption among HIV-infected military have not been described. Aside from alcohol-related harm, a number of studies have found deleterious effects of alcohol among individuals living with HIV infection.9,10 We have previously reported on virologic outcomes among at-risk drinkers in a cohort of U.S. active duty and retired personnel initiating antiretroviral therapy.11 Here, we analyze the factors associated with at-risk drinking in our longitudinal cohort in order to better understand at risk alcohol use among this highly active antiretroviral therapy (HAART)-treated population.
MATERIALS AND METHODS
The U.S. Military HIV Natural History Study (NHS) is a prospective observational cohort of consenting HIV-infected military personnel and beneficiaries. Since 1986, more than 6,000 participants have enrolled in the NHS, with visits occurring approximately every 6 months as previously described.12 Beginning in 2006, we have conducted interview-administered surveys on self-reported alcohol use, including the typical and a maximum number of drinks by volume consumed on a single day and the number of drinking days per week. We define at-risk drinking using criteria established by the National Institute for Alcohol Abuse and Alcoholism (NIAAA),13 with greater than four drinks in a 24-hour period or 14 drinks/week for men, and greater than three drinks in a 24-hour period or greater than seven drinks/week for women. For this analysis, only one alcohol questionnaire was used per the calendar year, with the latest date chosen if there were more than one. To analyze potential changes in drinking patterns, we examined consecutive (annual) pairwise risk scores within subjects to estimate the percentage of at-risk drinkers who consistently remained at-risk drinkers.
Descriptive statistics at baseline are provided (Table I) for the at-risk and not at risk participants. Comparisons were performed with Chi-square analysis on categorical variables and Mann–Whitney U test for continuous variables. To assess risk factors for at-risk drinking, we used univariate and multivariate GEE logistic regression with age (per 10 year increases), CD4 count and log VL as time-updated variables. All covariates with significance levels of p < 0.10 in independent tests were included into the multivariate model and removed in stepwise selection for p > 0.25. The binomial outcome variable for this model was yearly alcohol risk group (at risk vs. not at risk or non-user as defined by NIAAA). For this study, the analysis was limited to those study participants who initiated HAART during or after January 2006 through May 2014 and who had at least one alcohol risk survey within a year of HAART initiation. In preparing the multivariate model, we found that a number of subjects missed at least 1 year of alcohol screening during follow-up, owing to slow uptake of the survey at clinical sites, as opposed to the non-response of participants. To identify the potential impact of missing data, we conducted exploratory analyses comparing participants with and without alcohol survey data, along with sensitivity analyses, including Bayesian and inverse probability weighting. All analyses were performed using SAS version 9.4.
TABLE I.
Baseline Characteristics of HIV-Infected Individuals Who Completed at Least At-Risk Drinking Survey
| Total N (%) or Median (IQRa) | Never At-Risk | Ever At-Risk | p-Value | |
|---|---|---|---|---|
| 752 | 257 | 495 | ||
| Age at HAART Initiation | 29.5 (24.8, 38.2) | 33.2 (26.5, 42.6) | 28.3 (24.3, 35.7) | <0.001 |
| Sex | ||||
| Male | 726 (96.5%) | 247 (96.1%) | 479 (96.8%) | 0.640 |
| Female | 26 (3.5%) | 10 (3.9%) | 16 (3.2%) | |
| Race | ||||
| Caucasian | 274 (36.4%) | 81 (31.5%) | 193 (39.0%) | <0.001 |
| African-American | 292 (38.8%) | 131 (51.0%) | 161 (32.5%) | |
| Hispanic/other | 186 (24.7%) | 45 (17.5%) | 141 (28.5%) | |
| Duty status, currenta | ||||
| Active duty | 607 (80.7%) | 195 (75.9%) | 412 (83.2%) | 0.052 |
| Retired | 119 (15.8%) | 53 (20.6%) | 66 (13.3%) | |
| Dependent | 12 (1.60%) | 3 (1.17%) | 9 (1.82%) | |
| Othera | 14 (1.86%) | 6 (2.33%) | 8 (1.62%) | |
| Service | 0.071 | |||
| Air Force | 179 (23.8%) | 52 (20.2%) | 127 (25.7%) | |
| Army | 136 (18.1%) | 58 (22.6%) | 78 (15.8%) | |
| Marines | 69 (9.2%) | 19 (7.4%) | 50 (10.1%) | |
| Navy | 336 (44.7%) | 114 (44.4%) | 222 (44.9%) | |
| Other | 32 (4.2%) | 14 (5.5%) | 18 (3.6%) | |
| Rank | 0.152 | |||
| Enlisted | 646 (85.9%) | 212 (82.5%) | 434 (87.7%) | |
| Officer/Warrant | 82 (10.9%) | 35 (13.6%) | 47 (9.5%) | |
| N/A | 24 (3.2%) | 10 (3.9%) | 14 (2.8%) | |
| Depression | 0.220 | |||
| No | 667 (88.7%) | 233 (90.7%) | 434 (87.7%) | |
| Yes | 85 (11.3%) | 24 (9.3%) | 61 (12.3%) | |
| Marital status | 0.005 | |||
| Single | 507 (72.7%) | 158 (66.1%) | 349 (76.2%) | |
| Married | 190 (27.26%) | 81 (33.9%) | 109 (23.8%) | |
| CD4 at HAART initiation | 363.0 (278.0, 472.0) | 343.0 (263.0, 459.0) | 368.5 (290.0, 476.0) | 0.059 |
| Log10 VL at HAART initiation | 4.5 (4.0, 5.0) | 4.5 (4.1, 5.0) | 4.5 (4.0, 5.0) | 0.923 |
| Follow-up after HAART initiation (Years) | 2.3 (1.1, 4.0) | 2.0 (0.9,4.0) | 2.5 (1.3,4.0) | 0.049 |
aOther: Reservist, Limited Duty, National Guard, Transitional Status with active benefits.
RESULTS
Of 801 subjects who initiated HAART on or after January 1, 2006, 752 had data on alcohol risk at HAART initiation and were included in the analysis. Baseline characteristics of the analyzed cohort are provided in Table I. In total, 66% (n = 495) of subjects met criteria for at-risk drinking on at least one survey. The median follow-up time after HAART initiation was 2.3 years (interquartile range (IQR) 1.1, 4.0). The study population was 96.5% male, 36.4% Caucasian, 38.8% African American, a median age of 29.5 years (IQR 23.5, 34.4), and 80.7% were active duty at last follow-up visit. 56.9% (n = 428) of the study population was categorized as binge drinking, accounting for 86.5% of at risk drinkers. Lastly, we found that 67% of individuals identified as at-risk drinkers during 1 year met criteria in a subsequent, although not necessarily consecutive, year.
In univariate analysis (Table II), African-Americans were significantly less likely to be at-risk drinkers than Caucasian race (OR 2.26 95% CI [1.66, 3.06]) or Hispanic/Other (OR 1.95 95%CI [1.40, 2.71]). At-risk drinkers were more likely to be Active Duty compared to Retired (OR 0.65 95% CI [0.46, 0.92]), single vs. married (OR 1.43 95% CI [1.05, 1.97]) and to be younger (OR per 10 years 0.70 95% CI [0.61, 0.81]). In addition, at-risk drinking was associated with higher viral load (OR per 1.0 log10VL 1.16 95% CI [1.09, 1.24]) and less time on HAART (OR per year 1.19 95% CI [1.12, 1.26]). The at-risk and not at-risk drinking groups also did not significantly differ with respect to military service, rank, gender, CD4 count, or depression diagnosis at HAART initiation.
TABLE II.
Univariate and Multivariate Analyses Predicting At-Risk Drinking
| Unadjusted Odds Ratios | Adjusted Odds Ratios | |||||||
|---|---|---|---|---|---|---|---|---|
| Alcohol Risk Variable | OR | [95% CI] | p-Value | OR | [95% CI] | p-Value | ||
| Current age per 10 years | 0.70 | 0.61 | 0.81 | <0.0001 | 0.61 | 0.49 | 0.75 | <0.0001 |
| Age group categories | ||||||||
| 18–25 | Ref | |||||||
| 26–32 | 0.94 | 0.71 | 1.25 | 0.6647 | ||||
| 33–39 | 0.49 | 0.34 | 0.71 | 0.0002 | ||||
| 40+ | 0.53 | 0.37 | 0.77 | 0.0007 | ||||
| Sex | ||||||||
| Male | Ref | |||||||
| Female | 0.79 | 0.42 | 1.49 | 0.4721 | ||||
| Race | ||||||||
| African-American | Ref | Ref | ||||||
| Caucasian | 2.26 | 1.66 | 3.06 | <0.0001 | 3.30 | 2.31 | 4.71 | <0.0001 |
| Hispanic/Other | 1.95 | 1.40 | 2.71 | <0.0001 | 2.17 | 1.51 | 3.14 | <0.0001 |
| Duty Status | ||||||||
| Active | Ref | Ref | ||||||
| Retired | 0.65 | 0.44 | 0.93 | 0.0183 | 0.73 | 0.45 | 1.19 | 0.2051 |
| Dependent | 0.55 | 0.24 | 1.24 | 0.1499 | 0.50 | 0.22 | 1.12 | 0.0922 |
| Other | 0.57 | 0.25 | 1.30 | 0.1824 | 0.52 | 0.24 | 1.11 | 0.0890 |
| Service | ||||||||
| Navy | Ref | |||||||
| Army | 0.76 | 0.50 | 1.15 | 0.1929 | ||||
| Air Force | 1.28 | 0.76 | 2.17 | 0.3513 | ||||
| Marines | 0.84 | 0.61 | 1.14 | 0.2645 | ||||
| Other | 0.76 | 0.37 | 1.56 | 0.4515 | ||||
| Rank | ||||||||
| Enlisted | Ref | |||||||
| Officer | 0.78 | 0.51 | 1.19 | 0.2509 | ||||
| Depression | ||||||||
| No | Ref | |||||||
| Yes | 1.37 | 0.94 | 2.00 | 0.0986 | 1.49 | 0.99 | 2.24 | 0.0569 |
| Marital status | ||||||||
| Married | Ref | Ref | ||||||
| Single | 1.43 | 1.05 | 1.97 | 0.0255 | 1.51 | 1.08 | 2.13 | 0.0170 |
| CD4 per 100 | 0.99 | 0.95 | 1.04 | 0.761 | 1.04 | 0.98 | 1.11 | 0.1755 |
| Time updated Log VL | 1.19 | 1.12 | 1.26 | <0.0001 | 1.08 | 0.99 | 1.17 | 0.0922 |
| Time on HAART, year | 0.86 | 0.81 | 0.92 | <0.0001 | 0.42 | 0.17 | 1.02 | 0.0541 |
In multivariate analysis (Table II), Race (Caucasian: OR 3.30 95% CI [2.31, 4.71]; Hispanic/other: OR 2.17 95% CI [1.51, 3.14]), younger age (OR 0.61 per 10 years, [95% CI 0.49, 0.74]) and single relationship status (OR 1.51 95% CI [1.08, 2.13]) were independently associated with at-risk drinking, after adjusting for current duty status, depression at HAART, log VL, CD4 count, and time on HAART.
CONCLUSION
In our survey of individuals who had initiated antiretroviral therapy, we found a high proportion of at-risk drinking (67%), where it was significantly associated with younger age and non-African American race. The observed high level of at-risk alcohol use reflects a large proportion of binge drinking, given the NIAAA definition that incorporates both episodic and typical drinking patterns over a prior year.
These patterns are consistent with typical patterns of military drinking.1–3 Surveys of drinking behavior show active duty military personnel under age 35 were significantly more likely to have engaged in heavy drinking than their civilian counterparts.2 Single relationship status and younger age have also been associated with alcohol-related problems among individuals recently deployed to Afghanistan or Iraq.14,15 Our observed association of Caucasian race with at-risk drinking is consistent with general patterns observed within the military. In the 2011 DoD Health Related Behaviors survey, 28% of Caucasian military personnel were moderate or heavy drinkers, compared with 25% of Hispanic/other individuals and 20% of African Americans.16
The persistence of at-risk drinking in our cohort suggests missed opportunities for identification and treatment of at-risk alcohol use in the military. Here, our findings echo an earlier study of U.S. Navy personnel, where the overall prevalence of frequent heavy drinking had not changed significantly from prior measurements taken at the time of service entry.17 The DoD Health Related Behaviors survey reported that 13% of currently drinking active duty military were not familiar with easily accessible services available through OneSource and Residential Treatment.16 Fortunately, new approaches, including brief web-based educational interventions, have managed to reduce multiple measures of alcohol use, including an average number of drinks consumed per occasion and status as a frequent heavy drinker.18,19 Wider implementation of these interventions in the military, and among vulnerable subpopulations, may demonstrate similar success.
Our study had several limitations. Data were collected by self-report, and our measure of at-risk drinking, which included episodes of binge drinking over a 1-year time frame, may not have accounted for behavioral change during the study period. Survey data for at-risk drinking were missing for 49 participants; however, sensitivity analyses to explore effects of missing survey revealed no effect on our results. Last, a high proportion of women were identified as at-risk drinkers, though the number of females participants available in the study overall was low (3.5%). While this is not consistent with other studies, where 24–33% of current or former active duty women reported recent binge drinking over more recent time frames,9,10 the current data on risk behavior of women in the military are limited, compared with men and confirms the essential need to address contributing factors to at-risk drinking for women.
In conclusion, we found a high prevalence of at-risk drinking among individuals with HIV infection, and at-risk drinking was associated most closely with young, non-African Americans. Targeting interventions toward this group, particularly those of single marital status, will be important to reduce at-risk drinking and its potential for HIV-related complications.
Funding
Financial Support for this work (IDCRP-000-26) was provided by the Infectious Disease Clinical Research Program (IDCRP), a Department of Defense (DoD) program executed through the Uniformed Services University of the Health Sciences. This project has been funded in whole, or in part, with federal funds from the National Institute of Allergy and Infectious Diseases, National Institutes of Health (NIH), under Inter-Agency Agreement HT9404-12-2-0004.
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