0000000000204262
AUTHOR
Lauri Kortelainen
Changes in physical performance according to job demands across three cohorts of older workers in the Longitudinal Aging Study Amsterdam
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 tim…
Sociodemographic Correlates of Parental Co-Participation in Digital Media Use and Physical Play of Preschool-Age Children
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…
Early-Life Factors as Predictors of Age-Associated Deficit Accumulation Across 17 Years From Midlife Into Old Age
Abstract 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 3 measurement occasions over 17 years in participants from the Helsinki Birth Cohort Study (n = 2 000) 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 health ca…
Body Composition in Late Midlife as a Predictor of Accelerated Age-associated Deficit-accumulation From Late Midlife into Old Age: A Longitudinal Birth Cohort Study
Abstract 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 = 2 000) 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/m2 higher BMI and each unit higher %BF the increases in FI leve…
A nonlinear mixed model approach to predict energy expenditure from heart rate.
Abstract 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 …