Many lifestyle behaviors-including smoking, alcohol consumption, and engagement in physical activity and social activity-have been identified as potential determinants of the risk of cognitive impairment. Understanding how those lifestyle behavior patterns in older adults affect cognitive function is crucial for developing targeted interventions. This study examined the lifestyle behavior patterns of Chinese community-dwelling older adults and their associations with cognitive impairment. A cross-sectional study was conducted with 2060 community-dwelling older adults in Beijing, China. Latent class analysis identified distinct lifestyle behavior patterns based on unhealthy lifestyle behaviors (smoking and alcohol consumption) and healthy behaviors (physical activity and social activity). Cognitive function was evaluated using the Mini-Mental State Examination. Multiple logistic regression was conducted to examine the associations between lifestyle behavior patterns and cognitive impairment. Three distinct lifestyle behavior patterns emerged: (1) high control-high engagement (685/2060, 33.3%), (2) high control-low engagement (1210/2060, 58.7%), and (3) low control-low engagement (165/2060, 8.0%). The high control-high engagement group, characterized by non-smoking, low-to-moderate alcohol consumption, and frequent engagement in physical and social activities, exhibited the lowest risk of cognitive impairment. In contrast, participants in the high control-low engagement group (OR 1.852, 95% CI 1.314-2.655) and low control-low engagement group (OR 2.905, 95% CI 1.670-5.001) exhibited significantly higher risks. Subgroup analyses revealed that males and hypertensive individuals within the high control-low engagement group were at an even greater risk. Our findings revealed that both avoiding harmful behaviors and actively engaging in health-promoting activities are important for cognitive health in older adults. Based on the results, we propose adopting a dual-pathway intervention model in policy making, simultaneously optimizing risk behaviors management and healthy behaviors promotion mechanisms.
Hu et al. (Tue,) studied this question.