Sex Differences in Physical, Behavioral, and Mental Factors Related to Alcohol Use Among American Indians

Background and Purpose:  American Indian and Alaska Native (AI/AN) Men and Women mortality Rates approaching 50% higher than non-Hispanic Whites (CDC, 2014). Psychosocial determinants of Alcohol Use (AU) are important, yet virtually invisible in research. Because AU is a known risk factor for the top causes of death (e.g., cardiovascular disease (CVD), diabetes, injuries, suicide, cancer) among American Indians (AI) the purpose of this article is to understand the physical, behavioral, and mental factors related to AU among AI Males and Females. We addressed the following hypothesis (a) Physical factors: Lower BMI and higher cardiovascular risk factors will be positively associated with alcohol use; (b) Behavioral factors: Smoking will be positively associated with alcohol use, whereas health self-efficacy will be negatively associated with alcohol use; (c) Mental factors: Depression will be positively associated with alcohol use.

Methods:  Data were drawn from a cross-sectional survey with 479 AI adults resided in South Dakota. We employed a series of regression analyses to assess the associations of demographic (sex, age, marital status, income, and educational attainment), physical (Body Mass Index [BMI] and cardiovascular risk), behavioral (smoking and health practices self-efficacy) and mental (depressive symptoms) factors with alcohol use. We ran the following four models: (a) Males only; (b) Females only; (c) Data with Female and AU interaction term; and (d) Males and Females.

Results: The prevalence of CVD (42%), diabetes (22%), smoking (53%), and average BMI (29.8) were much higher than national statistics for the general U.S. population. Males reported AU at three times that of females. For the regression analysis, in the first model, significant factors for higher male AU included:  Lower income, lower health practices self-efficacy, and depression (R² = .29, F (1, 9) = 6.4, p < .001). In the second model, factors for higher females AU included: smoking and depression (R² = .07, F (1, 9) = 1.9, p < .001). The third model indicated a significant interaction for sex with AU and males drinking more, along with lower BMI and depression being significant (R² = .43, F(1, 11) = 24.76, p < .001). Finally, the fourth model indicated that males, lower income, smoking, and depression all predicted higher AU (R² = .22, F (1, 10) = 10.57, p < .001).

Conclusions & Implications: CVD, diabetes, smoking, and BMI are concerning high for AI participants in this sample. Sex differences were present across models. Income persisted as an important sociodemographic factor and BMI was only significant in the interaction model. Health Practices Self-Efficacy was significant for males, whereas smoking was significant for females. Depression was significant across models. Holistic, multidimensional sex-specific analyses related to AU are needed. Sex specific investigations of risk and protective factors across multiple dimensions of wellness are needed to comprehensively address behavioral health in treatment modalities.