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Purpose. To investigate the relationship between duration and intensity of physical activity and disability 10 years later, and to investigate the possible effect of selective mortality.Method. Longitudinal data of 560 men aged 70-89 years, without disability at baseline from the Finland, Italy and The Netherlands Elderly (FINE) Study was used. Physical activity in 1990 was based on activities like walking, bicycling and gardening. Disability severity (three categories) in 1990 and 2000 was based on instrumental activities, mobility and basic activities of daily living.Results. Men in the highest tertile of total physical activity had a lower risk of disability than men in the lowest tertile (odds ratio (OR) 0.46; 95% confidence interval (CI): 0.26-0.84). This was due to duration of physical activity (OR highest tertile 0.42; 95% CI: 0.23-0.78 compared to the lowest tertile). Intensity of physical activity was not associated with disability. Addition of deceased men as fourth category leaded to weaker associations between physical activity and disability (OR highest tertile 0.67; 95% CI: 0.44-1.02).Conclusions. Even in old age among relatively healthy men, a physically active lifestyle was inversely related to disability. To prevent disability duration of physical activity seems to be more important than intensity. [ABSTRACT FROM AUTHOR]

STUDY OBJECTIVE: To study the effect of using a mail questionnaire or home interviews on the size and the selectivity of response to national health surveys. DESIGN: The interview survey and the mail survey were both carried out in the same country (the Netherlands) using the same sample frame, the same study period (1998) and collected partly the same data on demographic, socioeconomic and health characteristics. SETTING: The Netherlands. PARTICIPANTS: Dutch non-institutionalised inhabitants aged 25 years and over. MAIN RESULTS: Response to the mail survey was lower (46.9%, n=3664) than to the interview survey (58.5%, n=6061). The mail survey gave higher response rates for women and lower response rates for persons with lower levels of education. Respondents to the mail survey reported lower rates of smoking but a slightly worse health status and higher figures on the use of health care services. No differences by method of data collection were found for age, marital status, region, household composition, work status and categories of body mass index. CONCLUSION: Although the response of the mail survey was lower than the home interview survey, respondents showed generally small differences, with exception of level of education. [ABSTRACT FROM AUTHOR]

Purpose: Differences in respondent characteristics may lead to bias in prevalence estimates and bias in associations. Both forms of non-response bias are investigated in a study on psychosocial factors and cancer risk, which is a sub-study of a large-scale monitoring survey in the Netherlands.Methods: Respondents of a cross-sectional monitoring project (MORGEN; N = 22,769) were also asked to participate in a prospective study on psychosocial factors and cancer risk (HLEQ; N = 12,097). To investigate diverse aspects of non-response in the HLEQ on prevalence estimates and associations are studied, based on information gathered in the MORGEN-project.Results: A response percentage of 45% was obtained in the MORGEN-project. Response rates were found to be lower among men and younger people. The HLEQ showed a response percentage of 56%, and respondents reported higher socioeconomic status, better subjective health and healthier lifestyle behaviors than non-respondents. However, associations between smoking status and either socioeconomic status or subjective health based on respondents only were not statistically different from those based on the entire MORGEN-population.Conclusion: Non-response leads to bias in prevalence estimates of current smoking, current alcohol intake, and low physical activity or poor subjective health. However, non-response did not cause bias in the examined associations. [ABSTRACT FROM AUTHOR]

Objective: To examine (a) the association between metabolic factors and chronic musculoskeletal pain (CMP), (b) metabolic predictors of CMP 10 years later, and (c) the association and evolution of metabolic factors across different CMP trajectory groups., Design: Data from the longitudinal Doetinchem Cohort Study were used. We used round 4 (2003-2007), with 4519 participants aged 36-75 years, as the baseline for the present study, with follow-up measurements in round 5 (2008-2012), and 6 (2013-2017), including self-reported pain and metabolic factors, which were measured either via self-report or physical assessment. For the three research aims, (a) generalized linear mixed-effects models, (b) binary logistic regression analyses and (c) linear mixed-effects models were used., Results: (a) Female sex, higher age, presence of diabetes, higher BMI, lower diastolic blood pressure (BP), and elevated cystatin C were significantly associated with CMP in multivariable logistic analyses. (b) Female sex and elevated BMI were predictors of CMP 10 years later. (c) Those pain-free for 10 years had the lowest BMI levels compared to other CMP groups (development, recovery, persistent, and recurrent CMP). BMI was higher in the persistent CMP group than in the development and recovery groups. The pain-free group had higher diastolic BP compared to those in the persistent CMP group. Participants in the persistent CMP group had higher Cystatin C levels than the free, development and recovery CMP groups. Regarding the evolution of metabolic factors over time, BMI, glucose and diastolic BP evolved differently across the CMP trajectory groups., Conclusion: Our findings indicate the importance of metabolic factors, especially BMI, in the onset and progression of CMP. These findings underscore the need to consider metabolic health in the prevention and treatment of CMP. Key Points • Metabolic factors are associated with the presence of chronic musculoskeletal pain. • Female sex and elevated BMI are predictive of musculoskeletal pain (MP) 10 years later. • Metabolic factors evolve differently over time across different pain trajectory groups, with variations in BMI, glucose, and diastolic blood pressure., Competing Interests: Declarations. Conflict of interest: The authors declare that they have no conflict of interest., (© 2024. The Author(s), under exclusive licence to International League of Associations for Rheumatology (ILAR).)

Skin autofluorescence (SAF), reflecting advanced glycation end-products' accumulation in tissue, has been proposed as a non-invasive aging biomarker. Yet, SAF has not been compared to well-established blood-based aging biomarkers such as MetaboHealth in association with frailty. Furthermore, no previous study determined the longitudinal association of SAF with frailty. We used 2382 Doetinchem Cohort Study participants' (aged 46.0 to 85.4) cross-sectional data, of whom 1654 had longitudinal SAF measurements. SAF was measured using the AGE reader™. MetaboHealth was calculated on 1H-NMR-metabolomics. Linear regressions were used for the associations of SAF and MetaboHealth on the 36-deficit frailty index and logistic regressions for being pre-frail or frail as determined by the frailty phenotype. Longitudinal associations were determined by an interaction term between age and SAF in a linear mixed model. SAF and MetaboHealth were associated with higher odds of pre-frailty (odd ratios per standard deviation SAF: 1.21(1.10;1.32), MetaboHealth: 1.35(1.24;1.49)) and frailty (SAF: 1.70(1.41;2.06), MetaboHealth: 1.90(1.57;2.32)). When mutually adjusted, both aging biomarkers remained associated with pre-frailty (SAF: 1.16(1.05;1.27), MetaboHealth 1.33(1.21;1.46)) and frailty (SAF: 1.52(1.25;1.85), MetaboHealth: 1.75(1.43;2.14)). Additionally, SAF and MetaboHealth were associated with higher frailty index scores (percentage increase per standard deviation SAF:1.35(1.00;1.70), MetaboHealth: 1.87(1.54;2.20)), also after mutual adjustment (SAF: 1.02(0.68;1.37), MetaboHealth: 1.69(1.35;2.02)). SAF was also longitudinally associated with the frailty index (percentage per unit/year increase 0.12(0.07;0.16)). The mutual independence of SAF and MetaboHealth implies they capture distinct aspects of the aging process. Altogether, these findings emphasize SAF's clinical potential as an age-related decline biomarker, which could be further enhanced when combined with MetaboHealth., (© The Author(s) 2024. Published by Oxford University Press on behalf of The Gerontological Society of America.)

Background: Metabolomic scores based on age (MetaboAge) and mortality (MetaboHealth) are considered indicators of overall health, but their association with cognition in the general population is unknown. Therefore, the association between MetaboAge/MetaboHealth and level and decline in cognition was studied, as were differences between men and women., Methods: Data of 2821 participants (50% women, age range 45-75) from the Doetinchem Cohort Study was used. MetaboAge and MetaboHealth were calculated from 1H-NMR metabolomics data at baseline. Cognitive domain scores (memory, flexibility and processing speed) and global cognitive functioning were available over a 10-year period. The association between MetaboAge/MetaboHealth and level of cognitive functioning was studied using linear regressions while for the association between MetaboAge/MetaboHealth and cognitive decline longitudinal linear mixed models were used. Analyses were adjusted for demographics and lifestyle factors., Results: Higher MetaboAge, indicating poorer metabolomic ageing, was only associated with lower levels of processing speed in men. Higher MetaboHealth, indicating poorer immune-metabolic health, was associated with lower levels of cognitive functioning for all three domains and global cognitive functioning in both men and women. Only in men, MetaboHealth was also associated with 10-year decline in flexibility, processing speed and global cognition. Metabolites that contributed to the observed associations were in men mainly markers of protein metabolism, and in women mainly markers of lipid metabolism and inflammatory metabolites., Conclusions: MetaboHealth, not MetaboAge, was associated with cognitive functioning independent of conventional risk factors. Individual metabolites affect cognitive functioning differently in men and women, suggesting sex-specific pathophysiological pathways underlying cognitive functioning., (© The Author(s) 2024. Published by Oxford University Press on behalf of the British Geriatrics Society.)

Background: Obesity may affect an individual's immune response and subsequent risk of infection, such as a SARS-CoV-2 infection. It is less clear whether overweight and long-term obesity also constitute risk factors. We investigated the association between the degree and duration of overweight and obesity and SARS-CoV-2 infection., Methods: We analyzed data from nine prospective population-based cohorts of the Netherlands Cohorts Consortium, with a total of 99,570 participants, following a standardized procedure. Body mass index (BMI) and waist circumference (WC) were assessed two times before the pandemic, with approximately 5 years between measurements. SARS-CoV-2 infection was defined by self-report as a positive PCR or rapid-antigen test or as COVID-19 ascertained by a physician between March 2020 and January 2023. For three cohorts, information on SARS-CoV-2 infection by serology was available. Results were pooled using random-effects meta-analyses and adjusted for age, sex, educational level, and number of SARS-CoV-2 infection measurements., Results: Individuals with overweight (25 ≤ BMI < 30 kg/m 2 ) (odds ratio (OR) = 1.08, 95%-confidence interval (CI) 1.04-1.13) or obesity (BMI ≥ 30 kg/m 2 ) (OR = 1.43, 95%-CI 1.18-1.75) were more likely to report SARS-CoV-2 infection than individuals with a healthy body weight. We observed comparable ORs for abdominal overweight (men: 94 cm≤WC < 102 cm, women: 80 cm≤WC < 88 cm) (OR = 1.09, 95%-CI 1.04-1.14, I 2  = 0%) and abdominal obesity (men: WC ≥ 102 cm, women: WC ≥ 88 cm) (OR = 1.24, 95%-CI 0.999-1.55, I 2  = 57%). Individuals with obesity long before the pandemic, but with a healthy body weight or overweight just before the pandemic, were not at increased risk., Conclusion: Overweight and obesity were associated with increased risk of SARS-CoV-2 infection with stronger associations for obesity. Individuals with a healthier weight prior to the pandemic but previous obesity did not have an increased risk of SARS-CoV-2, suggesting that weight loss in those with obesity reduces infection risk. These results underline the importance of obesity prevention and weight management for public health., (© 2024. The Author(s).)

Background: Older persons elicit heterogeneous antibody responses to vaccinations that generally are lower than those in younger, healthier individuals. As older age and certain comorbidities can influence these responses we aimed to identify health-related variables associated with antibody responses after repeated SARS-CoV-2 vaccinations and their persistence thereafter in SARS-CoV-2 infection-naïve and previously infected older persons., Method: In a large longitudinal study of older persons of the general population 50 years and over, a sub-cohort of the longitudinal Doetinchem cohort study (n = 1374), we measured IgG antibody concentrations in serum to SARS-CoV-2 Spike protein (S1) and Nucleoprotein (N). Samples were taken following primary vaccination with BNT162b2 or AZD1222, pre- and post-vaccination with a third and fourth BNT162b2 or mRNA-1273 (Wuhan), and up to a year after a fifth BNT162b2 bivalent (Wuhan/Omicron BA.1) vaccine. Associations between persistence of antibody concentrations over time and age, sex, health characteristics including cardiometabolic and inflammatory diseases as well as a frailty index were tested using univariable and multivariable models., Results: The booster doses substantially increased anti-SARS-CoV-2 Spike S1 (S1) antibody concentrations in older persons against both the Wuhan and Omicron strains. Older age was associated with decreased antibody persistence both after the primary vaccination series and up to 1 year after the fifth vaccine dose. In infection-naïve persons the presence of inflammatory diseases was associated with an increased antibody response to the third vaccine dose (Beta = 1.53) but was also associated with reduced persistence over the 12 months following the fifth (bivalent) vaccine dose (Beta = -1.7). The presence of cardiometabolic disease was associated with reduced antibody persistence following the primary vaccination series (Beta = -1.11), but this was no longer observed after bivalent vaccination., Conclusion: Although older persons with comorbidities such as inflammatory and cardiometabolic diseases responded well to SARS-CoV-2 booster vaccinations, they showed a reduced persistence of these responses. This might indicate that especially these more vulnerable older persons could benefit from repeated booster vaccinations., (© 2024. The Author(s).)

Biological age uses biophysiological information to capture a person's age-related risk of adverse outcomes. MetaboAge and MetaboHealth are metabolomics-based biomarkers of biological age trained on chronological age and mortality risk, respectively. Lifestyle factors contribute to the extent chronological and biological age differ. The association of lifestyle factors with MetaboAge and MetaboHealth, potential sex differences in these associations, and MetaboAge's and MetaboHealth's sensitivity to lifestyle changes have not been studied yet. Linear regression analyses and mixed-effect models were used to examine the cross-sectional and longitudinal associations of scaled lifestyle factors with scaled MetaboAge and MetaboHealth in 24,332 middle-aged participants from the Doetinchem Cohort Study, Rotterdam Study, and UK Biobank. Random-effect meta-analyses were performed across cohorts. Repeated metabolomics measurements had a ten-year interval in the Doetinchem Cohort Study and a five-year interval in the UK Biobank. In the first study incorporating longitudinal information on MetaboAge and MetaboHealth, we demonstrate associations between current smoking, sleeping ≥8 hours/day, higher BMI, and larger waist circumference were associated with higher MetaboHealth, the latter two also with higher MetaboAge. Furthermore, adhering to the dietary and physical activity guidelines were inversely associated with MetaboHealth. Lastly, we observed sex differences in the associations between alcohol use and MetaboHealth., Competing Interests: Declaration of Competing Interest The authors declare that they have no competing interests., (Copyright © 2024. Published by Elsevier B.V.)

A risk factor model of body mass index (BMI) is an important building block of health simulations aimed at estimating government policy effects with regard to overweight and obesity. We created a model that generates representative population level distributions and that also mimics realistic BMI trajectories at an individual level so that policies aimed at individuals can be simulated. The model is constructed by combining several datasets. First, the population level distribution is extracted from a large, cross-sectional dataset. The trend in this distribution is estimated from historical data. In addition, longitudinal data are used to model how individuals move along typical trajectories over time. The model faithfully describes the population level distribution of BMI, stratified by sex, level of education and age. It is able to generate life course trajectories for individuals which seem plausible, but it does not capture extreme fluctuations, such as rapid weight loss., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.)

In this cohort profile article we describe the lifetime major depressive disorder (MDD) database that has been established as part of the BIObanks Netherlands Internet Collaboration (BIONIC). Across the Netherlands we collected data on Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition ( DSM-5 ) lifetime MDD diagnosis in 132,850 Dutch individuals. Currently, N = 66,684 of these also have genomewide single nucleotide polymorphism (SNP) data. We initiated this project because the complex genetic basis of MDD requires large population-wide studies with uniform in-depth phenotyping. For standardized phenotyping we developed the LIDAS (LIfetime Depression Assessment Survey), which then was used to measure MDD in 11 Dutch cohorts. Data from these cohorts were combined with diagnostic interview depression data from 5 clinical cohorts to create a dataset of N = 29,650 lifetime MDD cases (22%) meeting DSM-5 criteria and 94,300 screened controls. In addition, genomewide genotype data from the cohorts were assembled into a genomewide association study (GWAS) dataset of N = 66,684 Dutch individuals (25.3% cases). Phenotype data include DSM-5 -based MDD diagnoses, sociodemographic variables, information on lifestyle and BMI, characteristics of depressive symptoms and episodes, and psychiatric diagnosis and treatment history. We describe the establishment and harmonization of the BIONIC phenotype and GWAS datasets and provide an overview of the available information and sample characteristics. Our next step is the GWAS of lifetime MDD in the Netherlands, with future plans including fine-grained genetic analyses of depression characteristics, international collaborations and multi-omics studies.

People age differently. Differences in aging might be reflected by metabolites, also known as metabolomic aging. Predicting metabolomic aging is of interest in public health research. However, the added value of longitudinal over cross-sectional predictors of metabolomic aging is unknown. We studied exposome-related exposures as potential predictors of metabolomic aging, both cross-sectionally and longitudinally in men and women. We used data from 4 459 participants, aged 36-75 of Round 4 (2003-2008) of the long-running Doetinchem Cohort Study (DCS). Metabolomic age was calculated with the MetaboHealth algorithm. Cross-sectional exposures were demographic, biological, lifestyle, and environmental at Round 4. Longitudinal exposures were based on the average exposure over 15 years (Round 1 [1987-1991] to 4), and trend in these exposure over time. Random Forest was performed to identify model performance and important predictors. Prediction performances were similar for cross-sectional and longitudinal exposures in both men (R2 6.8 and 5.8, respectively) and women (R2 14.8 and 14.4, respectively). Biological and diet exposures were most predictive for metabolomic aging in both men and women. Other important predictors were smoking behavior for men and contraceptive use and menopausal status for women. Taking into account history of exposure levels (longitudinal) had no added value over cross-sectionally measured exposures in predicting metabolomic aging in the current study. However, the prediction performances of both models were rather low. The most important predictors for metabolomic aging were from the biological and lifestyle domain and differed slightly between men and women., (© The Author(s) 2023. Published by Oxford University Press on behalf of The Gerontological Society of America.)

Background: Although being a woman and having a migration background are strong predictors of poor self-rated health among (older) adults, research on the sex difference in self-rated health among (older) migrants remains limited. This study therefore aims to investigate this topic and explore the contributing role of determinants of self-rated health., Methods: Cross-sectional data from 360 Turkish-Dutch and Moroccan-Dutch adults aged 55-65 as part of the Longitudinal Aging Study Amsterdam (LASA) were used. Self-rated health (good versus poor) was measured by a single item question. Univariate age-adjusted logistic regression analysis was used to investigate the sex difference in self-rated health and the contribution of sex differences in sensitivity (strength of the association) and/or exposure (prevalence) to socio-demographic, social, lifestyle or health-related determinants of self-rated health., Results: Women had a 0.53 times lower odds (95%CI:0.40-0.82, p = 0.004) on good self-rated health compared to men. Women more often having a lower education level, living alone and having a higher prevalence of depressive symptoms, chronic diseases and especially functional limitations contributed to the lower self-rated health among women. In contrast, men were more sensitive to the impact of memory complaints, depressive symptoms, visual difficulties and functional limitations., Conclusions: Older Turkish-Dutch and Moroccan-Dutch women have a significant lower self-rated health compared to men. Women having a higher exposure to both socio-demographic and health-related determinants of self-rated health, which contributed to the sex difference. Future research should take these differences in self-rated health and determinants between women and men into account when investigating health among older migrants., (© 2023. The Author(s).)

Introduction: Given the known female disadvantage in physical and mental health, this study aimed to investigate sex differences in self-rated health (SRH) among older adults, considering the longitudinal course by age, birth cohort, and educational level., Methods: Data from birth cohort 1911-1937 with baseline age 55-81 years (n = 3,107) and birth cohort 1938-1947 with baseline age 55-65 years (n = 1,002) from the Longitudinal Aging Study Amsterdam (LASA) were used. Mixed model analyses were used to examine sex differences in SRH (RAND General Health Perception Questionnaire [RAND-GHPQ], range 0-16) over the age course, testing for effect modification by the birth cohort and educational level (low, middle, high)., Results: For both sexes, a decline in SRH was seen with increasing age. Over the age course, there was no significant sex difference in SRH within the older (1911-1937) birth cohort (0.13 lower score on SRH for women compared to men, 95% CI: -0.35 to 0.09) and only a small sex difference in the more recent (1938-1947) birth cohort (0.35 lower score on SRH for women compared to men [95% CI: -0.69 to -0.02], p = 0.04). There was no significant cohort difference in the size of the sex difference (p = 0.279). Those with a higher level of education reported a higher SRH, but between educational levels, there was no significant difference in the size of the sex difference in SRH., Discussion: In this study, no relevant sex difference in SRH over the age course was observed among older adults. Future research on SRH trajectories by sex during aging should take health-related, cognitive, psychosocial, and behavioral factors into account., (© 2024 The Author(s). Published by S. Karger AG, Basel.)

Background: Immune responses to vaccination vary widely between individuals. The aim of this study was to identify health-related variables potentially underlying the antibody responses to SARS-CoV-2 vaccination in older persons. We recruited participants in the long-running Doetinchem Cohort Study (DCS) who underwent vaccination as part of the national COVID-19 program, and measured antibody concentrations to SARS-CoV-2 Spike protein (S1) and Nucleoprotein (N) at baseline (T0), and a month after both the first vaccination (T1), and the second vaccination (T2). Associations between the antibody concentrations and demographic variables, including age, sex, socio-economic status (SES), comorbidities (cardiovascular diseases and immune mediated diseases), various health parameters (cardiometabolic markers, inflammation markers, kidney- and lung function) and a composite measure of frailty ('frailty index', ranging from 0 to 1) were tested using multivariate models., Results: We included 1457 persons aged 50 to 92 years old. Of these persons 1257 were infection naïve after their primary vaccination series. The majority (N = 954) of these individuals were vaccinated with two doses of BNT162b2 (Pfizer) and their data were used for further analysis. A higher frailty index was associated with lower anti-S1 antibody responses at T1 and T2 for both men (R T1  = -0.095, P T1  = 0.05; R T2  = -0.11, P T2  = 0.02) and women (R T1  = -0.24, P T1  < 0.01; R T2  = -0.15, P T2  < 0.01). After correcting for age and sex the frailty index was also associated with the relative increase in anti-S1 IgG concentrations between the two vaccinations (β = 1.6, P < 0.01). Within the construct of frailty, history of a cardiac catheterization, diabetes, gastrointestinal disease, a cognitive speed in the lowest decile of the population distribution, and impaired lung function were associated with lower antibody responses after both vaccinations., Conclusions: Components of frailty play a key role in the primary vaccination response to the BNT162b2 vaccine within an ageing population. Older persons with various comorbidities have a lowered immune response after their first vaccination, and while frail and sick older persons see a stronger increase after their second vaccination compared to healthy people, they still have a lower antibody response after their second vaccination., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Background: Women have a higher life expectancy than men but experience more years with physical disabilities in daily life at older ages, especially women with a migration background. This pinpoints older women as an important target group for strategies that stimulate healthy lifestyle, which benefits healthy aging. Our study investigates motivators and barriers for healthy lifestyles and perspectives on determinants of healthy aging of older women. This provides essential information for developing targeted strategies., Methods: Data was collected by semi-structured digital interviews from February till June 2021. Women aged 55 years and older living in the Netherlands (n = 34) with a native Dutch (n = 24), Turkish (n = 6) or Moroccan (n = 4) migration background were included. Two main subjects were investigated: (1) motivators and barriers on their current lifestyles regarding smoking, alcohol consumption, physical activity, diet and sleep and (2) perspectives on determinants of healthy aging. Interviews were analyzed using Krueger's framework., Results: Personal health was the most common motivator for a healthy lifestyle. In addition, peer pressure and being outdoors were specific motivators for physical activity. Bad weather conditions and personal dislike to be active were specific barriers. The social environment, personal preferences and personal belief to compensate with other healthy lifestyle behaviors were barriers for low alcohol consumption. Personal preferences (liking unhealthy food and not making time) were the main barriers for a healthy diet. Sleep was not perceived as a form of lifestyle behavior, but rather as a personal trait. Since there were no smokers, specific barriers were not mentioned. For Turkish-Dutch and Moroccan-Dutch women, additional barriers and motivators were culture and religion. These were strong motivators to abstain from alcohol consumption and smoking, but a barrier for a healthy diet. With regard to perspectives on determinants of healthy aging, positive views on aging and being physically active were perceived as most important. Women often wanted to increase their physical activity or healthy diet to stimulate healthy aging. Among Turkish-Dutch and Moroccan-Dutch women, healthy aging was also perceived as something in the hands of God., Conclusions: Although motivators and barriers for a healthy lifestyle and perspectives on healthy aging vary for distinct lifestyles, personal health is a common motivator across all lifestyles. Having a migration background added culture and religion as distinct barriers and motivations. Strategies to improve lifestyle among older women should therefore have a tailored, culture sensitive approach (if applicable) for distinct lifestyle factors., (© 2023. The Author(s).)

Both (biological) sex and (socio-cultural) gender are relevant for health but in large-scale studies specific gender measures are lacking. Using a masculine gender-score based on 'traditional masculine-connotated aspects of everyday life', we explored how masculinity may affect sex differences in the prevalence of chronic health problems. We used cross-sectional data (2008-2012) from the Doetinchem Cohort Study to calculate a masculine gender-score (range 0-19) using information on work, informal care, lifestyle and emotions. The sample consisted of 1900 men and 2117 women (age: 40-80). Multivariable logistic regressions including age and SES were used to examine the role of masculine gender on sex differences in the prevalence of diabetes, coronary heart disease, CVA, arthritis, chronic pain and migraine. Men had higher masculine gender-scores than women (12.2 vs 9.1). For both sexes, a higher masculine gender-score was associated with lower prevalence of chronic health problems. Diabetes, CHD, and CVA were more prevalent in men, and gender-adjustment resulted in greater sex differences: e.g. for diabetes the OR sex  changed from 1.21 (95 %CI 0.93-1.58) to 1.60 (95 %CI 1.18-2.17). Arthritis, chronic pain, and migraine were more prevalent in women, and gender-adjustment resulted in smaller sex differences: e.g. for chronic pain the OR sex  changed from 0.53 (95 %CI 0.45-0.60) to 0.73 (95 %CI 0.63-0.86). Gender measured as 'everyday masculinity' is associated with lower prevalence of chronic health problems in both men and women. Our findings also suggest that the commonly found sex differences in the prevalence of chronic health problems have a large gender component., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)

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: In a substantial subgroup of depressed patients, atypical, energy-related depression symptoms (e.g. increased appetite/weight, hypersomnia, loss of energy) tend to cluster with immuno-metabolic dysregulations (e.g. increased BMI and inflammatory markers). This clustering is proposed to reflect a more homogeneous depression pathology. This study examines to what extent energy-related symptoms are associated and share sociodemographic, lifestyle and clinical characteristics., Methods: Data were available from 13,965 participants from eight Dutch cohorts with DSM-5 lifetime major depression assessed by the Lifetime Depression Assessment Self-report (LIDAS) questionnaire. Information on four energy-related depression symptoms were extracted: energy loss, increased appetite, increased weight, and hypersomnia. Tetrachoric correlations between these symptoms, and associations of these symptoms with sociodemographic (sex, age, education), lifestyle (physical activity, BMI, smoking) and clinical characteristics (age of onset, episode duration, history, treatment and recency, and self-reported comorbidity) were computed., Results: Correlations between energy-related symptoms were overall higher than those with other depression symptoms and varied from 0.90 (increased appetite vs increased weight) to 0.11 (increased appetite vs energy loss). All energy-related symptoms were strongly associated with higher BMI and a more severe clinical profile. Patients with increased appetite were more often smokers, and only patients with increased appetite or weight more often had a self-reported diagnosis of PTSD (OR = 1.17, p = 2.91E-08) and eating disorder (OR = 1.40, p = 4.08E-17)., Conclusions: The symptom-specific associations may have consequences for a profile integrating these symptoms, which can be used to reflect immuno-metabolic depression. They indicate the need to study immuno-metabolic depression at individual symptom resolution as a starting point., Competing Interests: Conflicts of interest BP has received research funding (not related to the current paper) from Boehringer Ingelheim and Jansen Research., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Older adults are at increased risk for adverse health outcomes when having an influenza, pneumococcal disease, pertussis, or herpes zoster infection. Despite the ability of vaccinations to prevent these adverse outcomes, vaccination coverage is low in the European Union. This study aimed to explore the sociodemographic, lifestyle, and health-related characteristics associated with vaccination willingness for these vaccine-preventable diseases., Methods: Cross-sectional data from wave 6 (years 2013-2017) of the population-based Doetinchem Cohort Study was analysed, with 3063 participants aged 46-86 years included. The outcome was the self-reported willingness to get vaccinated against influenza, pneumococcal disease, pertussis, and herpes zoster (willing, neutral, not willing). Multinomial logistic regression was used to investigate the socio-demographic, lifestyle and health characteristics associated with vaccination willingness., Results: For influenza 36 % was willing to get vaccinated, 35 % was neutral and 28 % was not willing to get vaccinated. The willingness to get vaccinated for the relatively unfamiliar vaccine-preventable diseases was lower: 26 % for pneumococcal disease (neutral: 50 %, not willing: 23 %), 26 % for pertussis (neutral 53 %, not willing: 22 %), and 23 % for herpes zoster (neutral 54 %, not willing: 24 %). A relative lower willingness was found among those 46-64 years old (compared to those 65 years or older). Women, having a high SES, being employed and having a good health were all associated with lower willingness to get vaccinated, which was the case for all vaccine-preventable diseases., Conclusions: Older adults were generally more willing to get vaccinated against influenza than for the three less familiar diseases. Characteristics of those less willing may be used to improve strategies to increase vaccination coverage. Additional studies are needed to investigate the willingness to get vaccinated during and after the COVID-19 pandemic that may have changed the feel of urgency for vaccination., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Although it is known that health literacy (HL) plays an explanatory role in educational inequalities in health, it is unknown whether this role varies across age groups., Objective: The purpose of this study was to investigate whether the mediating role of HL in educational inequalities in four health outcomes varies across age groups: age 46 to 58 years, age 59 to 71 years, and age 72 to 84 years., Methods: We used data from the Dutch Doetinchem Cohort Study, which included 3,448 participants. We included years of education as predictor, chronic illness prevalence and incidence, mental and self-perceived health as outcomes, and HL, based on self-report, as mediator. We used multiple-group mediation models to compare indirect effects across age groups., Key Results: In the complete sample without age stratification, HL partly mediated the effect of education on all health outcomes except for incidence of chronic diseases. These indirect effect estimates were larger for subjective (self-perceived health, proportion mediated [PM] = 37%, and mental health, PM = 37%) than for objective health outcomes (prevalence of chronic disease, PM = 17%). For the prevalence of chronic disease, the indirect effect estimate was significantly larger among individuals age 46 to 58 years compared to individuals age 59 to 71 years and for incidence of chronic disease also compared to individuals age 72 to 84 years. All other indirect effect estimates did not differ significantly between age groups. Using an alternative cut-off point for HL or adjusting for cognitive functioning did not meaningfully change the results., Conclusions: Overall, we found that the explanatory role of HL in educational inequalities in mental and subjective health was stable but that it varied across age groups for chronic diseases, where it was largest among individuals age 46 to 58 years. Future studies may investigate the benefits of starting to intervene on HL from a younger age but means to improve HL may also benefit the subjective health of older adults with lower education. [ HLRP: HL Research and Practice . 2023;7(1):e26-e38.] Plain Language Summary: This study examined age-group differences in the mediating role of HL in the relationship between education and health. Overall, we found that the explanatory role of HL in educational inequalities in mental and subjective health was stable but that it varied across age groups for chronic diseases, where it was largest among individuals age 46 to 58 years compared to individuals age 59 to 71 years and individuals age 72 to 84 years.