A latent profile analysis of the link between sociocultural factors and health-related risk-taking among U.S. adults

Abstract

Background Research suggests that health/safety behaviors (e.g., drinking heavily) and medical behaviors (e.g., donating blood) may be perceived as inherently risky, and further suggests there is substantial variation in the likelihood of engaging in a particular health-related risk behavior across people. Research examining demographic and sociocultural factors related to both health/safety and medical risk-taking is highly limited. Importantly, with very few exceptions the literature examining health risks characterized by potentially hazardous health behaviors (e.g, heavy alcohol use, driving without a seatbelt) is kept separate from the literature examining health risks characterized by potentially beneficial medical behaviors (e.g., donating blood, taking medication). In the interest of health promotion, it is critical for researchers to identify – and describe – individuals who are less inclined to engage in health-harming behaviors while at the same time being more inclined to engage in health-benefiting behaviors. Identifying such a subtype of individuals was the guiding aim for this study. Method A national sample of adults in the United States responded to a survey on sociocultural and demographic correlates of health behaviors. Health-related risk-taking indicators were measured using the items from the health/safety and medical subscales of the DOSPERT-M. Subtypes of risk-takers were identified using latent profile analysis (LPA). Follow-up analyses to describe subtype demographic characteristics were conducted. Results LPA identified four subtypes of risk-takers, including a subtype (n = 565, 45% of the sample; labeled “divergent”) that was comprised of individuals who highly endorsed medical risk-taking (e.g., taking medicine, giving blood) and minimally endorsed health/safety risk-taking (e.g., drinking heavily, unprotected sex). Subsequent analyses suggested that, among other findings, divergent profile members were likely to be married, endorse familial interdependence, and orient toward masculinity rather than femininity. Conclusion By examining potentially modifiable factors related to individuals’ inclinations to engage in health protective behaviors, this study is an important step toward improving current health behavior interventions among U.S. adults.

Human studies of mitochondrial biology demonstrate an overall lack of binary sex differences: A multivariate meta‐analysis

“…This finding suggests that variation in hormone levels—including between individuals with the same chromosomal sex—could influence mitochondrial behavior regardless of sex assigned at birth. Moreover, independent of biological sex, gender (e.g., identifying as a woman, man, or another identity; being more traditionally masculine or feminine) influences diet, 60–62 physical activity, 63–66 sleep, 67–69 and other health behaviors 70–72 . In turn, these factors can drive physiological differences in mitochondrial biology.…”

Blackouts and hangover experiences among Hispanic and Non-Hispanic White college students

“…Finally, spiritual influences were positively related to blackouts in the whole sample. This may reflect a spiritually-oriented fatalism or God Locus of Control that is linked to health risk behaviors ( Perrotte et al, 2021 ).…”

Human studies of mitochondrial biology demonstrate an overall lack of binary sex differences: A multivariate meta-analysis

“…This finding suggests that variation in hormone levels – including between individuals with the same chromosomal sex – could influence mitochondrial behavior regardless of sex assigned at birth. Moreover, well-documented influences of gender as a social position on one’s diet (58–60), physical activity (61–64), sleep (65–67), and other health behaviors (68–70) are not captured by a binary sex classification, and may be responsible for physiological differences otherwise superficially attributed to biological sex (30). Sexual characteristics can also vary within a single person over time: gender role-related health behaviors change with marital status (71–73), and sex hormones are altered with parental role transitions (74), common conditions like polycystic ovary syndrome (PCOS) (75), and due to menopause or andropause (49, 76).…”