Profiles of modifiable dementia risk factors in later midlife: a latent class analysis

Background In 2020, the Lancet Commission identified 12 modifiable risk factors that may increase dementia risk at the population level. At the individual level, these risk factors may co‐occur; therefore, this study aimed to identify profiles of dementia risk factors in later midlife, and to explore differences in biological markers associated with those profiles. Methods Participants aged 60‐64 without dementia at baseline and who identified as Caucasian were identified from the UK Biobank. Data for each risk factor (education, hearing loss, traumatic brain injury, hypertension, alcohol consumption, obesity, smoking, depression, social isolation, physical inactivity, air pollution, and diabetes) were collected using a standardized clinical assessment or through linkage of inpatient records. Latent class analysis was performed to identify latent classes of individuals; missing data were handled using full information maximum likelihood. A multigroup analysis was used to consider differences by self‐reported sex. Associations between the classes and a panel of 29 blood biomarkers across six broad categories (hormonal, inflammatory, kidney, liver, lipids, and metabolic) were explored using the Bolck, Croon, and Hagenaars (BCH) method, considering sex and controlling for age; pairwise comparisons between classes were made using z‐tests. Results Among n = 117,275 participants (males: n = 53,426, females: n = 63,849), a 4‐class solution was identified based on model fit statistics. Invariance testing revealed significantly different class solutions between sexes (Δχ2 = 11,615, Δdf = 52, p < 0.001). In general, the following four groups were identified in both males and females: low risk, psychosocial risk, cardiometabolic risk, and risk related to substance use (Figure 1). These classes differed in their blood biomarkers in both males and females, with the greatest differences observed in females. Specifically, the largest differences were observed between the cardiometabolic risk class vs. other classes, and in biomarkers for inflammation and metabolism (e.g. c‐reactive protein, triglyceride:HDL cholesterol ratio). Conclusion In both males and females in later midlife, four classes defined by modifiable dementia risk factors were identified. These profiles were associated with unique biomarker signatures. might further examine the effects of these risk factor profiles on dementia‐related pathophysiological changes.