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Background: Predicting healthy physiological aging is of major interest within public health research. However, longitudinal studies into predictors of healthy physiological aging that include numerous exposures from different domains (i.e. the exposome) are scarce. Our aim is to identify the most important exposome-related predictors of healthy physiological aging over the life course and across generations., Methods: Data were used from 2815 participants from four generations (generation 1960s/1950s/1940s/1930s aged respectively 20-29/30-39/40-49/50-59 years old at baseline, wave 1) of the Doetinchem Cohort Study who were measured every 5 years for 30 years. The Healthy Aging Index, a physiological aging index consisting of blood pressure, glucose, creatinine, lung function, and cognitive functioning, was measured at age 46-85 years (wave 6). The average exposure and trend of exposure over time of demographic, lifestyle, environmental, and biological exposures were included, resulting in 86 exposures. Random forest was used to identify important predictors., Results: The most important predictors of healthy physiological aging were overweight-related (BMI, waist circumference, waist/hip ratio) and cholesterol-related (using cholesterol lowering medication, HDL and total cholesterol) measures. Diet and educational level also ranked in the top of important exposures. No substantial differences were observed in the predictors of healthy physiological aging across generations. The final prediction model's performance was modest with an R 2 of 17%., Conclusions: Taken together, our findings suggest that longitudinal cardiometabolic exposures (i.e. overweight- and cholesterol-related measures) are most important in predicting healthy physiological aging. This finding was similar across generations. More work is needed to confirm our findings in other study populations., (© 2023. The Author(s).)

Background: To explore whether differences between men and women in the sensitivity to (strength of the association) and/or in the exposure to determinants (prevalence) contribute to the difference in physical functioning, with women reporting more limitations., Methods: Data of the Doetinchem Cohort Study was used (n = 5856, initial ages 26-70 years), with follow-up measurements every 5 years (up to 20). Physical functioning (subscale SF-36, range:0-100), sex (men or women) and a number of socio-demographic, lifestyle- and health-related determinants were assessed. Mixed-model multivariable analysis was used to investigate differences between men and women in sensitivity (interaction term with sex) and in exposure (change of the sex difference when adjusting) to determinants of physical functioning., Results: The physical functioning score among women was 6.55 (95%CI:5.48,7.61) points lower than among men. In general, men and women had similar determinants, but pain was more strongly associated with physical functioning (higher sensitivity), and also more prevalent among women (higher exposure). The higher exposure to low educational level and not having a paid job also contributed to the lower physical functioning score among women. In contrast, current smoking, mental health problems and a low educational level were more strongly associated with a lower physical functioning score among men and lower physical activity and higher BMI were more prevalent among men., Conclusions: Although important for physical functioning among both men and women, our findings provide no indications for reducing the difference in physical functioning by promoting a healthy lifestyle but stress the importance of differences in pain, work and education., (© 2022. The Author(s).)

Background: This study explores whether a sex difference in sensitivity to (strength of the association) and/or in exposure to (prevalence) determinants of gait speed contributes to the observed lower gait speed among older women compared to men., Methods: Data from the Longitudinal Aging Study Amsterdam (LASA) were used. In total 2407 men and women aged 55-81 years were included, with baseline measurements in 1992/2002 and follow-up measurements every 3-4 years for 15/25 years. Multivariable mixed model analysis was used to investigate sex differences in sensitivity (interaction term with sex) and in exposure to (change of the sex difference when adjusted) socio-demographic, lifestyle, social and health determinants of gait speed., Results: Women had a 0.054 m/s (95 % CI: 0.076 - 0.033, adjusted for height and age) lower mean gait speed compared to men. In general, men and women had similar determinants of gait speed. However, higher BMI and lower physical activity were more strongly associated with lower gait speed in women compared to men (i.e. higher sensitivity). More often having a lower educational level, living alone and having more chronic diseases, pain and depressive symptoms among women compared to men also contributed to observed lower gait speed in women (i.e. higher exposure). In contrast, men more often being a smoker, having a lower physical activity and a smaller personal network size compared to women contributed to a lower gait speed among men (i.e. higher exposure)., Conclusions: Both a higher sensitivity and higher exposure to determinants of gait speed among women compared to men contributes to the observed lower gait speed among older women. The identified (modifiable) contributing factors should be taken into account when developing prevention and/or treatment strategies aimed to enhance healthy physical aging. This might require a sex-specific approach in both research and clinical practice, which is currently often lacking.

Background: Many older adults have low levels of health literacy which affects their ability to participate optimally in healthcare. It is unclear how cognitive decline contributes to health literacy. To study this, longitudinal data are needed. The aim of this study was therefore to assess the associations of cognitive functioning and 10-years' cognitive decline with health literacy in older adults., Methods: Data from 988 participants (mean age = 65.3) of the Doetinchem Cohort Study were analyzed. Health literacy was measured by the Brief Health Literacy Screening. Memory, mental flexibility, information processing speed, and global cognitive functioning were assessed at the same time as health literacy and also 10 years earlier. Logistic regression analyses were performed, adjusted for age, gender, and educational level., Results: Higher scores on tests in all cognitive domains were associated with a lower likelihood of having low health literacy after adjustment for confounders (all ORs < 0.70, p-values<.001). Similar associations were found for past cognitive functioning (all ORs < 0.75, p-values<.05). Before adjustment, stronger cognitive decline was associated with a greater likelihood of having low health literacy (all ORs > 1.37, p-values<.05). These associations lost significance after adjustment for educational level, except for the association of memory decline (OR = 1.40, p = .023, 95% CI: 1.05 to 1.88)., Conclusion: Older adults with poorer cognitive functioning and stronger cognitive decline are at risk for having low health literacy, which can affect their abilities to promote health and self-manage disease. Low health literacy and declining cognitive functioning might be a barrier for person-centered care, even in relatively young older adults.

Background: Accumulation of problems in physical, psychological, cognitive, or social functioning is characteristic for frail individuals. Using a four-domain approach of frailty, this study explored how sociodemographic and lifestyle factors, life events and health are associated with frailty., Methods: The study sample included 4019 men and women (aged 40-81 years) examined during the fifth round (2008-2012) of the Doetinchem Cohort Study. Four domains of frailty were considered: physical (≥4 of 8 criteria: unintentional weight loss, exhaustion, strength, perceived health, walking, balance, hearing and vision impairments), psychological (2 criteria: depressive symptoms, mental health), cognitive (<10th percentile on global cognitive functioning), and social frailty (≥2 of 3 criteria: loneliness, social support, social participation). Logistic regression was used to study the cross-sectional association of sociodemographic factors, lifestyle, life events and chronic diseases with frailty domains., Results: About 17% of the population was frail on one or more domains. Overlap between the frailty domains was limited since 82% of the frail population was frail on one domain only. Low educated respondents were at higher risk of being psychologically and socially frail. Having multiple diseases was associated with a higher risk of being physically and psychologically frail. Being physically active was consistently associated with a lower risk of frailty on each of the four domains. Short or long sleep duration was associated with a higher risk of being physically, psychologically, and socially frail., Conclusions: Sociodemographic factors, lifestyle and multimorbidity contributed differently to the four frailty domains. It is important to consider multiple frailty domains since this helps to identify different groups of frail people, and as such to provide tailored care and support. Lifestyle factors including physical activity, smoking and sleep duration were associated with multiple domains of frailty.