Background Early life exposures have been associated with the risk of frailty in old age. We investigated whether early life exposures predict the level and rate of change in a frailty index (FI) from midlife into old age. Methods A linear mixed model analysis was performed using data from three measurement occasions over 17 years in participants from the Helsinki Birth Cohort Study (n=2000) aged 57-84 years. A 41-item FI was calculated on each occasion. Information on birth size, maternal body mass index (BMI), growth in infancy and childhood, childhood socioeconomic status (SES), and early life stress (wartime separation from both parents), was obtained from registers and healthcare records. Results At age 57 years the mean FI level was 0.186 and the FI levels increased by 0.34 percent/year from midlife into old age. Larger body size at birth associated with a slower increase in FI levels from midlife into old age. Per 1kg greater birth weight the increase in FI levels per year was -0.087 percentage points slower (95% CI=-0.163, -0.011; p=0.026). Higher maternal BMI was associated with a higher offspring FI level in midlife and a slower increase in FI levels into old age. Larger size, faster growth from infancy to childhood, and low SES in childhood were all associated with a lower FI level in midlife but not with its rate of change. Conclusions Early life factors seem to contribute to disparities in frailty from midlife into old age. Early life factors may identify groups that could benefit from frailty prevention, optimally initiated early in life.

Young children’s digital media use and physical activity have gained attention in recent research. Parental co-participation has a major impact on children’s health consequences. This study addressed a gap in the research by investigating daily parental co-participation in children’s digital media use and physical play, using the family ecological model theoretical framework. The participants in this nationally representative cross-sectional study were 2512 Finnish parents with two- to six-year-old children. Parents completed a questionnaire. Sociodemographic correlates of co-participation and of the awareness of guidelines regarding co-participation and correlation between co-participation in digital media use and physical play were analysed. Parental co-participation in physical play and digital media use correlated positively. Lower parental age, male parental gender, Finnish and Swedish languages, a fewer number of children, and a male child gender were associated with more co-participation in one or both activities, and parental female gender and low family income were associated with more awareness. The awareness of guidelines was not associated with co-participation in digital media use. There were sociodemographic differences in parental co-participation. From a health counselling perspective, parents may benefit from national recommendations on digital media use and physical activity, but adherence to guidelines depends on the family context.

Background Body mass index (BMI) may not be an optimal predictor of frailty as its constituents, lean and fat mass, may have opposite associations with frailty. Methods A linear mixed model analysis was performed in the Helsinki Birth Cohort Study (n=2000) spanning from 57 to 84 years. A 39-item frailty index (FI) was calculated on three occasions over 17 years. Body composition in late midlife included BMI, percent body fat (%BF), waist-to-hip ratio (WHR), lean mass index (LMI), and fat mass index (FMI). Results Mean FI levels increased by 0.28%/year among men and by 0.34%/year among women. Among women, per each kg/m 2 higher BMI and each unit higher %BF the increases in FI levels per year were 0.013 percentage points (PP) steeper (95% CI=0.004, 0.023) and 0.009 PP steeper (95% CI=0.002, 0.016) from late midlife into old age. Among men, per each 0.1-unit greater WHR the increase in FI levels was 0.074 PP steeper per year (95% CI=-0.0004, 0.148). Cross-sectionally, greater FMI and LMI in late midlife were associated with higher FI levels but the direction of the association regarding LMI changed after adjustment for FMI. The categories ‘high FMI & high LMI’ and ‘high FMI & low LMI’ showed the highest FI levels relative to the category ‘low FMI & low LMI’. Conclusions In late midlife, greater adiposity (%BF) among women and abdominal obesity (WHR) among men may predispose to higher levels of frailty from late midlife into old age. Greater lean mass alone may be protective of frailty, but not in the presence of high fat mass.

Objective. Heart rate (HR) monitoring provides a convenient and inexpensive way to predict energy expenditure (EE) during physical activity. However, there is a lot of variation among individuals in the EE-HR relationship, which should be taken into account in predictions. The objective is to develop a model that allows the prediction of EE based on HR as accurately as possible and allows an improvement of the prediction using calibration measurements from the target individual. Approach. We propose a nonlinear (logistic) mixed model for EE and HR measurements and an approach to calibrate the model for a new person who does not belong to the dataset used to estimate the model. The calibration utilizes the estimated model parameters and calibration measurements of HR and EE from the person in question. We compare the results of the logistic mixed model with a simpler linear mixed model for which the calibration is easier to perform. Main results. We show that the calibration is beneficial already with only one pair of measurements on HR and EE. This is an important benefit over an individual-level model fitting, which requires a larger number of measurements. Moreover, we present an algorithm for calculating the confidence and prediction intervals of the calibrated predictions. The analysis was based on up to 11 pairs of EE and HR measurements from each of 54 individuals of a heterogeneous group of people, who performed a maximal treadmill test. Significance. The proposed method allows accurate energy expenditure predictions based on only a few calibration measurements from a new individual without access to the original dataset, thus making the approach viable for example on wearable computers.

This study set out to evaluate the association between job demands at baseline and physical performance over a six-year period across three cohorts of older Dutch workers examined 10 years apart. Data were drawn from three cohorts (1992–1999, 2002–2009 and 2012–2019) of the Longitudinal Aging Study Amsterdam. Individuals aged 55–65 years from each cohort who worked for pay were included (n = 274, n = 416, n = 618, respectively). Physical performance was measured using gait speed and chair stand performance. A population-based job exposure matrix was used to indicate levels of exposure probability of physical (use of force and repetitive movements) and psychosocial (cognitive demands and time pressure) job demands. We found that psychosocial job demands increased and physical demands decreased across the three cohorts. No between cohort differences were found for how job demands affected changes in physical performance over follow-up. For men, faster decline in gait speed was observed when comparing higher and lower use of force at baseline (β −0.012, 95% CI −0.021, −0.004). Greater use of force and repetitive movements were associated with faster decline in chair stand performance (β −0.012, 95% CI −0.020, −0.004 and β −0.009, 95% CI −0.017, −0.001, respectively). In women, no association of job demands on change in physical performance was observed. The study concluded that higher physical job demands were associated with stronger decline in physical performance across six years for men in all cohorts, while no associations were found among women.