Lifestyle factors and metabolomic aging biomarkers: Meta-analysis of cross-sectional and longitudinal associations in three prospective cohorts.

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.

Willingness to get vaccinated against influenza, pneumococcal disease, pertussis, and herpes zoster - A pre-COVID-19 exploration among the older adult population.

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.

The Association between BMI and Different Frailty Domains: A U-Shaped Curve?

OBJECTIVES: Previous studies showed a U-shaped association between BMI and (physical) frailty. We studied the association between BMI and physical, cognitive, psychological, and social frailty. Furthermore, the overlap between and prevalence of these frailty domains was examined. DESIGN: Cross-sectional study. SETTING: The Doetinchem Cohort Study is a longitudinal population-based study starting in 1987-1991 examining men and women aged 20-59 with follow-up examinations every 5 yrs. PARTICIPANTS: For the current analyses, we used data from round 5 (2008-2012) with 4019 participants aged 41-81 yrs. MEASUREMENTS: Physical frailty was defined as having ≥ 2 of 4 frailty criteria from the Frailty Phenotype (unintentional weight loss, exhaustion, physical activity, handgrip strength). Cognitive frailty was defined as the < 10th percentile on global cognitive functioning (based on memory, speed, flexibility). Psychological frailty was defined as having 2 out of 2 criteria (depression, mental health). Social frailty was defined as having ≥ 2 of 3 criteria (loneliness, social support, social participation). BMI was divided into four classes. Analyses were adjusted for sex, age, level of education, and smoking. RESULTS: A U-shaped association was observed between BMI and physical frailty, a small linear association for BMI and cognitive frailty and no association between BMI and psychological and social frailty. The four frailty domains showed only a small proportion of overlap. The prevalence of physical, cognitive and social frailty increased with age, whereas psychological frailty did not. CONCLUSION: We confirm that not only underweight but also obesity is associated with physical frailty. Obesity also seems to be associated with cognitive frailty. Further, frailty prevention should focus on multiple domains and target individuals at a younger age (<65yrs).