The association of overweight, obesity, and long-term obesity with SARS-CoV-2 infection: a meta-analysis of 9 population-based cohorts from the Netherlands Cohorts Consortium.

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/m2) (odds ratio (OR) = 1.08, 95%-confidence interval (CI) 1.04-1.13) or obesity (BMI ≥ 30 kg/m2) (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, I2 = 0%) and abdominal obesity (men: WC ≥ 102 cm, women: WC ≥ 88 cm) (OR = 1.24, 95%-CI 0.999-1.55, I2 = 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.

Self-Rated Health among Older Adults: Longitudinal Analyses Examining Sex Differences across Different Birth Cohorts and Educational Levels.

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.

Health characteristics associated with persistence of SARS-CoV-2 antibody responses after repeated vaccinations in older persons over time: the Doetinchem cohort study.

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.

Genomics Research of Lifetime Depression in the Netherlands: The BIObanks Netherlands Internet Collaboration (BIONIC) Project.

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.

Potential determinants of antibody responses after vaccination against SARS-CoV-2 in older persons: the Doetinchem Cohort Study.

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 (RT1 = -0.095, PT1 = 0.05; RT2 = -0.11, PT2 = 0.02) and women (RT1 = -0.24, PT1 < 0.01; RT2 = -0.15, PT2 < 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 (ß = 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.

Predictors of healthy physiological aging across generations in a 30-year population-based cohort study: the Doetinchem Cohort Study.

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 R2 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.

Epigenome-wide association study of incident type 2 diabetes: a meta-analysis of five prospective European cohorts.

AIMS/HYPOTHESIS: Type 2 diabetes is a complex metabolic disease with increasing prevalence worldwide. Improving the prediction of incident type 2 diabetes using epigenetic markers could help tailor prevention efforts to those at the highest risk. The aim of this study was to identify predictive methylation markers for incident type 2 diabetes by combining epigenome-wide association study (EWAS) results from five prospective European cohorts. METHODS: We conducted a meta-analysis of EWASs in blood collected 7-10 years prior to type 2 diabetes diagnosis. DNA methylation was measured with Illumina Infinium Methylation arrays. A total of 1250 cases and 1950 controls from five longitudinal cohorts were included: Doetinchem, ESTHER, KORA1, KORA2 and EPIC-Norfolk. Associations between DNA methylation and incident type 2 diabetes were examined using robust linear regression with adjustment for potential confounders. Inverse-variance fixed-effects meta-analysis of cohort-level individual CpG EWAS estimates was performed using METAL. The methylGSA R package was used for gene set enrichment analysis. Confirmation of genome-wide significant CpG sites was performed in a cohort of Indian Asians (LOLIPOP, UK). RESULTS: The meta-analysis identified 76 CpG sites that were differentially methylated in individuals with incident type 2 diabetes compared with control individuals (p values <1.1 × 10-7). Sixty-four out of 76 (84.2%) CpG sites were confirmed by directionally consistent effects and p values <0.05 in an independent cohort of Indian Asians. However, on adjustment for baseline BMI only four CpG sites remained genome-wide significant, and addition of the 76 CpG methylation risk score to a prediction model including established predictors of type 2 diabetes (age, sex, BMI and HbA1c) showed no improvement (AUC 0.757 vs 0.753). Gene set enrichment analysis of the full epigenome-wide results clearly showed enrichment of processes linked to insulin signalling, lipid homeostasis and inflammation. CONCLUSIONS/INTERPRETATION: By combining results from five European cohorts, and thus significantly increasing study sample size, we identified 76 CpG sites associated with incident type 2 diabetes. Replication of 64 CpGs in an independent cohort of Indian Asians suggests that the association between DNA methylation levels and incident type 2 diabetes is robust and independent of ethnicity. Our data also indicate that BMI partly explains the association between DNA methylation and incident type 2 diabetes. Further studies are required to elucidate the underlying biological mechanisms and to determine potential causal roles of the differentially methylated CpG sites in type 2 diabetes development.

Sex Differences in Cognitive Functioning with Aging in the Netherlands.

INTRODUCTION: Dementia prevalence in older women is higher than that in men. The purpose of the present study was to investigate whether there is a female disadvantage in cognitive functioning at adult age and/or whether a female disadvantage develops with age. METHODS: Data of 5,135 women and 4,756 men from the Longitudinal Aging Study Amsterdam (LASA) and the Doetinchem Cohort Study (DCS) were used. In the LASA, memory, processing speed, fluid intelligence, and global cognitive function were measured every 3-4 years since 1992 in persons aged 55+ years for up to 23 years. In the DCS, memory, processing speed, cognitive flexibility, and global cognitive function were measured every 5 years since 1995 in persons aged 45+ years for up to 20 years. Sex differences in cognitive aging were analyzed using linear mixed models and also examined by the 10-year birth cohort or level of education. RESULTS: Women had a better memory, processing speed, flexibility, and, in the DCS only, global cognitive function than men (p's < 0.01). However, women showed up to 10% faster decline in these cognitive domains, except for flexibility, where women showed 9% slower decline. In the LASA, women scored poorer on fluid intelligence (p < 0.01), but their decline was 10% slower than that in men. Female advantage was larger in later born cohorts; adjustment for the educational level increased the female advantage. CONCLUSION: Women have better memory and processing speed than men at middle age. This female advantage becomes smaller with aging and has increased in more recent birth cohorts.

Impaired JAK-STAT pathway signaling in leukocytes of the frail elderly.

BACKGROUND: Elderly often show reduced immune functioning and can develop chronic low-grade inflammation. Why some elderly are more prone to become frail is unknown. We investigated whether frailty is associated with altered cytokine signaling through the JAK-STAT pathway in leukocytes of 34 individuals aged 65-74 years. In addition, we investigated how this relation is affected by chronic low-grade inflammation during the previous 20 years. Cytokine signaling was quantified by measuring intracellular STAT1, STAT3, and STAT5 phosphorylation in monocytes, B cells, CD4+ T cells and CD8+ T cells upon stimulation with IL-2, IL-6, IL-10, IFNα and IFNγ, using phospho-flow cytometry. Presence of chronic low-grade inflammation was investigated by evaluating 18 different plasma inflammatory markers that had been measured repeatedly in the same individuals over the previous 20 years. Frailty was assessed as a score on a frailty index. RESULTS: We found that lower cytokine-induced pSTAT responsiveness in the various cell subsets was seen with higher frailty scores in both men and women, indicative of dysfunctional pSTAT responses in frailer individuals. Associations differed between men and women, with frailer women showing lower pSTAT1 responses in monocytes and frailer men showing lower pSTAT5 responses in CD4+ and CD8+ T cells. Notably, lower IL-10-induced pSTAT3 responses in men were related to both higher frailty scores and higher CRP levels over the past 20 years. This might indicate poor resolution of low-grade inflammation due to defective regulatory pSTAT signaling in older men. CONCLUSIONS: Our results emphasize the importance of preserved JAK-STAT pathway signaling in healthy aging and reveal cellular pSTAT levels as a candidate biomarker of frailty.

Exploring the difference between men and women in physical functioning: How do sociodemographic, lifestyle- and health-related determinants contribute?

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.

20-year individual physical activity patterns and related characteristics.

BACKGROUND: This study aims to describe individual leisure-time physical activity patterns among Dutch adults over a 20-year period, and to compare baseline characteristics of participants with different patterns. METHODS: The study population consisted of 2,518 adults (53% women) aged 26-65 years at baseline, measured every 5 years over a 20-year period. Self-reported physical activity measurements (from 1994 to 2017) were used to compose five (predefined) patterns: stable active, becoming active, becoming inactive, stable inactive, and varying physical activity. Multivariate logistic regression analyses were used to compare baseline socio-demographic, lifestyle, and health-related characteristics of these patterns. RESULTS: The total population shows a stable percentage being active in each round (between 55 and 58%). However over a period of 20 years, 32.6% of the participants were stable active, 19.9% were stable inactive, 15.2% became active, 11.6% became inactive, and 20.8% had varying physical activity behaviour. Compared to participants who were stable active, becoming active was associated with being 46-55 years old, having an intermediate level of education, and smoking, at baseline. Participants who became inactive were less likely to be 46-55 years old and more likely to be obese. Stable inactivity was associated with an intermediate level of education, low adherence to dietary guidelines, smoking, low levels of alcohol use and a moderate/poor perceived health. Participants with a varying physical activity level were more likely to have low adherence to dietary guidelines and to smoke. CONCLUSIONS: Almost half of the participants changed their physical activity behaviour over 20 years. Baseline age, level of education, smoking, alcohol consumption, adherence to dietary guidelines, weight status and perceived health were associated with different physical activity patterns.

Anti-Müllerian hormone levels and risk of type 2 diabetes in women.

AIMS/HYPOTHESIS: Given its role in ovarian follicle development, circulating anti-Müllerian hormone (AMH) is considered to be a marker of reproductive ageing. Although accelerated reproductive ageing has been associated with a higher risk of type 2 diabetes, research on the relationship between AMH and type 2 diabetes risk is scarce. Therefore, we aimed to investigate whether age-specific AMH levels and age-related AMH trajectories are associated with type 2 diabetes risk in women. METHODS: We measured AMH in repeated plasma samples from 3293 female participants (12,460 samples in total), aged 20-59 years at recruitment, from the Doetinchem Cohort Study, a longitudinal study with follow-up visits every 5 years. We calculated age-specific AMH tertiles at baseline to account for the strong AMH-age correlation. Cox proportional hazards models adjusted for confounders were used to assess the association between baseline age-specific AMH tertiles and incident type 2 diabetes. We applied linear mixed models to compare age-related AMH trajectories for women who developed type 2 diabetes with trajectories for women who did not develop diabetes. RESULTS: During a median follow-up of 20 years, 163 women developed type 2 diabetes. Lower baseline age-specific AMH levels were associated with a higher type 2 diabetes risk (HRT2vsT3 1.24 [95% CI 0.81, 1.92]; HRT1vsT3 1.62 [95% CI 1.06, 2.48]; ptrend = 0.02). These findings seem to be supported by predicted AMH trajectories, which suggested that plasma AMH levels were lower at younger ages in women who developed type 2 diabetes compared with women who did not. The trajectories also suggested that AMH levels declined at a slower rate in women who developed type 2 diabetes, although differences in trajectories were not statistically significant. CONCLUSIONS/INTERPRETATION: We observed that lower age-specific AMH levels were associated with a higher risk of type 2 diabetes in women. Longitudinal analyses did not show clear evidence of differing AMH trajectories between women who developed type 2 diabetes compared with women who did not, possibly because these analyses were underpowered. Further research is needed to investigate whether AMH is part of the biological mechanism explaining the association between reproductive ageing and type 2 diabetes. Graphical abstract.

The sex difference in gait speed among older adults: how do sociodemographic, lifestyle, social and health determinants contribute?

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.

The mediating role of unhealthy behavior in the relationship between shift work and perceived health.

BACKGROUND: Little is known about the relationship between shift work and perceived health, including potential underlying mechanisms such as unhealthy behaviors. The aim of this study was to investigate whether unhealthy behaviors mediate the relationship between shift work and perceived mental and physical health, taking into account potential differences by level of education. METHODS: Data from 1633 workers participating in the Doetinchem Cohort Study during 1995-2016 were used. Being engaged in shift work was determined at 1 year preceding the assessment of health behaviors. Mental and physical health were assessed after 5 years of follow-up by the 5-item Mental Health Inventory and the physical functioning scale of the 36-item Short Form Health Survey. Smoking, physical inactivity, alcohol consumption, and overweight were considered as potential mediators and education was treated as moderator. Moderated mediation analyses using generalized estimated equations were performed. RESULTS: Shift work was not statistically significantly related to either mental or physical health. Despite this, statistically significant mediation effects of smoking (Beta - 0.09; 95% Confidence Interval - 0.20 - -0.01, respectively B -0.09; 95%CI -0.21 - -0.01) and physical inactivity (B 0.11; 95%CI 0.03-0.23, respectively B 0.08; 95%CI 0.01-0.18) were found in the relationship between shift work and mental or physical health. Direct and indirect effects outweighed each other in the relationship between shift work and mental health, since the direction of these effects was opposite. The relationship between shift work, unhealthy behavior, and health was not different by educational level. CONCLUSION: Shift workers did not report lower mental or physical health than non-shift workers. Though mediation effects of unhealthy behavior were observed in the relationship between shift work and perceived health, these small effects had minor public health relevance.

Lifestyle factors and risk of multimorbidity of cancer and cardiometabolic diseases: a multinational cohort study.

BACKGROUND: Although lifestyle factors have been studied in relation to individual non-communicable diseases (NCDs), their association with development of a subsequent NCD, defined as multimorbidity, has been scarcely investigated. The aim of this study was to investigate associations between five lifestyle factors and incident multimorbidity of cancer and cardiometabolic diseases. METHODS: In this prospective cohort study, 291,778 participants (64% women) from seven European countries, mostly aged 43 to 58 years and free of cancer, cardiovascular disease (CVD), and type 2 diabetes (T2D) at recruitment, were included. Incident multimorbidity of cancer and cardiometabolic diseases was defined as developing subsequently two diseases including first cancer at any site, CVD, and T2D in an individual. Multi-state modelling based on Cox regression was used to compute hazard ratios (HR) and 95% confidence intervals (95% CI) of developing cancer, CVD, or T2D, and subsequent transitions to multimorbidity, in relation to body mass index (BMI), smoking status, alcohol intake, physical activity, adherence to the Mediterranean diet, and their combination as a healthy lifestyle index (HLI) score. Cumulative incidence functions (CIFs) were estimated to compute 10-year absolute risks for transitions from healthy to cancer at any site, CVD (both fatal and non-fatal), or T2D, and to subsequent multimorbidity after each of the three NCDs. RESULTS: During a median follow-up of 11 years, 1910 men and 1334 women developed multimorbidity of cancer and cardiometabolic diseases. A higher HLI, reflecting healthy lifestyles, was strongly inversely associated with multimorbidity, with hazard ratios per 3-unit increment of 0.75 (95% CI, 0.71 to 0.81), 0.84 (0.79 to 0.90), and 0.82 (0.77 to 0.88) after cancer, CVD, and T2D, respectively. After T2D, the 10-year absolute risks of multimorbidity were 40% and 25% for men and women, respectively, with unhealthy lifestyle, and 30% and 18% for men and women with healthy lifestyles. CONCLUSION: Pre-diagnostic healthy lifestyle behaviours were strongly inversely associated with the risk of cancer and cardiometabolic diseases, and with the prognosis of these diseases by reducing risk of multimorbidity.

Measurement and genetic architecture of lifetime depression in the Netherlands as assessed by LIDAS (Lifetime Depression Assessment Self-report).

BACKGROUND: Major depressive disorder (MDD) is a common mood disorder, with a heritability of around 34%. Molecular genetic studies made significant progress and identified genetic markers associated with the risk of MDD; however, progress is slowed down by substantial heterogeneity as MDD is assessed differently across international cohorts. Here, we used a standardized online approach to measure MDD in multiple cohorts in the Netherlands and evaluated whether this approach can be used in epidemiological and genetic association studies of depression. METHODS: Within the Biobank Netherlands Internet Collaboration (BIONIC) project, we collected MDD data in eight cohorts involving 31 936 participants, using the online Lifetime Depression Assessment Self-report (LIDAS), and estimated the prevalence of current and lifetime MDD in 22 623 unrelated individuals. In a large Netherlands Twin Register (NTR) twin-family dataset (n ≈ 18 000), we estimated the heritability of MDD, and the prediction of MDD in a subset (n = 4782) through Polygenic Risk Score (PRS). RESULTS: Estimates of current and lifetime MDD prevalence were 6.7% and 18.1%, respectively, in line with population estimates based on validated psychiatric interviews. In the NTR heritability estimates were 0.34/0.30 (s.e. = 0.02/0.02) for current/lifetime MDD, respectively, showing that the LIDAS gives similar heritability rates for MDD as reported in the literature. The PRS predicted risk of MDD (OR 1.23, 95% CI 1.15-1.32, R2 = 1.47%). CONCLUSIONS: By assessing MDD status in the Netherlands using the LIDAS instrument, we were able to confirm previously reported MDD prevalence and heritability estimates, which suggests that this instrument can be used in epidemiological and genetic association studies of depression.

The Healthy Aging Index analyzed over 15 years in the general population: The Doetinchem Cohort Study.

The Healthy Aging Index (HAI), an index of physiological aging, has been demonstrated to predicts mortality, morbidity and disability. We studied the longitudinal development of the HAI to identify aging trajectories and evaluated the role of baseline sociodemographic characteristics and lifestyle factors of the trajectories. Four measurements with intervals of 5 years were included from the Doetinchem Cohort Study. The HAI reflects levels of systolic blood pressure, non-fasting plasma glucose levels, global cognitive functioning, plasma creatinine levels and lung functioning. The HAI score ranges from 0 to 10: higher scores indicate a better health profile. Latent class mixture modelling was used to model within-person change and to identify aging trajectories. Area under the curve was calculated per trajectory to estimate total healthy years. In total, 2324 women and 2013 men were included. One HAI trajectory was identified for women, and two trajectories for men, labelled 'gradual' aging (76%) and 'early' aging (24%). Men who were medium/high educated, below 36 years at baseline, complied with guidelines on physical activity and were not obese in any round were associated with increased odds to 'gradual' aging of 1.46 (CI: 1.18-1.81), 1.93 (CI: 1.42-2.62), 1.26 (1.02-1.57) and 1.76 (1.32-2.35), respectively. Between 30 and 70 years of age, men in the 'early' aging trajectory had the least healthy years (29.6 years), followed by women (30.1 years), and 'gradual' aging men (34.7 years). This study emphasizes that 'physiological aging' is not only an issue of older ages. Between 30 and 70 years of age, 'early' aging men and women had approximately five healthy years less compared to 'gradual' aging men. Lifestyle factors (e.g. nutrition and physical activity) seem to play an important role in optimal aging.

Shift work, chronotype and the risk of cardiometabolic risk factors.

Background: The relation between shift work and a large variety of cardiometabolic risk factors is unclear. Also, the role of chronotype is understudied. We examined relations between shift work and cardiometabolic risk factors, and explored these relations in different chronotypes. Methods: Cardiometabolic risk factors (anthropometry, blood pressure, lipids, diabetes, γ-glutamyltransferase, C-reactive protein, uric acid and estimated glomerular filtration rate) were assessed among 1334 adults in 1987-91, with repeated measurements every 5 years. Using shift work history data collected in 2013-15, we identified shift work status 1 year prior to all six waves. Linear mixed models and logistic generalized estimating equations were used to estimate the longitudinal relations between shift work and risk factors 1 year later. Results: Shift work was not significantly related with cardiometabolic risk factors (P ≥ 0.05), except for overweight/body mass index. Shift workers had more often overweight (OR: 1.44, 95% CI 1.06-1.95) and a higher body mass index (BMI) (ß: 0.56 kg m-2, 95% CI 0.10-1.03) than day workers. A significant difference in BMI between day and shift workers was observed among evening chronotypes (ß: 0.97 kg m-2, 95% CI 0.21-1.73), but not among morning chronotypes (ß: 0.04 kg m-2, 95% CI -0.85 to 0.93). No differences by frequency of night shifts and duration of shift work were observed. Conclusion: Shift workers did not have an increased risk of cardiometabolic risk factors compared with day workers, but, in particular shift working evening chronotypes, had an increased risk of overweight. More research is needed to verify our results, and establish whether tailored interventions by chronotype are wanted.

Health literacy among older adults is associated with their 10-years' cognitive functioning and decline - the Doetinchem Cohort Study.

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.

A four-domain approach of frailty explored in the Doetinchem Cohort Study.

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.