Socioeconomic disadvantage is a risk factor for many diseases. We characterised cascades of these conditions by using a data-driven approach to examine the association between socioeconomic status ...and temporal sequences in the development of 56 common diseases and health conditions.
In this multi-cohort study, we used data from two Finnish prospective cohort studies: the Health and Social Support study and the Finnish Public Sector study. Our pooled prospective primary analysis data comprised 109 246 Finnish adults aged 17–77 years at study entry. We captured socioeconomic status using area deprivation and education at baseline (1998–2013). Participants were followed up for health conditions diagnosed according to the WHO International Classification of Diseases until 2016 using linkage to national health records. We tested the generalisability of our findings with an independent UK cohort study—the Whitehall II study (9838 people, baseline in 1997, follow-up to 2017)—using a further socioeconomic status indicator, occupational position.
During 1 110 831 person-years at risk, we recorded 245 573 hospitalisations in the Finnish cohorts; the corresponding numbers in the UK study were 60 946 hospitalisations in 186 572 person-years. Across the three socioeconomic position indicators and after adjustment for lifestyle factors, compared with more advantaged groups, low socioeconomic status was associated with increased risk for 18 (32·1%) of the 56 conditions. 16 diseases formed a cascade of inter-related health conditions with a hazard ratio greater than 5. This sequence began with psychiatric disorders, substance abuse, and self-harm, which were associated with later liver and renal diseases, ischaemic heart disease, cerebral infarction, chronic obstructive bronchitis, lung cancer, and dementia.
Our findings highlight the importance of mental health and behavioural problems in setting in motion the development of a range of socioeconomically patterned physical illnesses. Policy and health-care practice addressing psychological health issues in social context and early in the life course could be effective strategies for reducing health inequalities.
UK Medical Research Council, US National Institute on Aging, NordForsk, British Heart Foundation, Academy of Finland, and Helsinki Institute of Life Science.
Physical activity and physical functioning have been reported to change over retirement transition, but the results have been inconsistent, and the two constructs have not been studied concurrently. ...The objective of this study was to examine concurrent changes in physical activity and physical functioning during transition to retirement among public sector employees, and to examine if occupation, sex, marital status, body mass index (BMI), alcohol consumption and smoking status are associated with observed different multi-trajectory paths. 3,550 participants of the Finnish Retirement and Aging study responded to an annual survey on physical activity and physical functioning (SF-36) before and after retirement. Group-based multi-trajectory analysis was used to identify clusters with dissimilar concurrent changes in physical activity and physical functioning. Multinomial regression analysis was used to describe the associations between covariates and the probability of being classified to a certain cluster. Low physical activity below the level usually recommended was associated with lower physical functioning during retirement transition. These findings could be useful when planning interventions for retirees to maintain their physical functioning level.
Physical activity and body mass index (BMI) have been reported to change around retirement. The objective was to examine the concurrent changes in physical activity and BMI around retirement, which ...have not been studied before. In addition, the associations of different demographic characteristics with these changes were examined.
The prospective cohort study consisted of 3,351 participants in the ongoing Finnish Retirement and Ageing Study (FIREA). Repeated postal survey, including questions on physical activity and body weight and height, was conducted once a year up to five times before and after the retirement transition, the mean follow-up time being 3.6 years (SD 0.7). Group-based multi-trajectory modeling was used to identify several clusters with dissimilar concurrent changes in physical activity and BMI within the studied cohort.
Of the participants, 83% were women. The mean age at the last wave before retirement was 63.3 (SD 1.4) years. Four clusters with different trajectories of physical activity and BMI were identified. BMI remained stable around retirement transition in all four clusters, varying from normal weight to class II obesity. The association of BMI trajectories with physical activity levels were inverse, however, each activity trajectory showed a temporary increase during the retirement transition.
Retirement seems to have more effect on physical activity than BMI, showing a temporary increase in physical activity at the time of retirement.
Background Physical activity and body mass index (BMI) have been reported to change around retirement. The objective was to examine the concurrent changes in physical activity and BMI around ...retirement, which have not been studied before. In addition, the associations of different demographic characteristics with these changes were examined. Methods The prospective cohort study consisted of 3,351 participants in the ongoing Finnish Retirement and Ageing Study (FIREA). Repeated postal survey, including questions on physical activity and body weight and height, was conducted once a year up to five times before and after the retirement transition, the mean follow-up time being 3.6 years (SD 0.7). Group-based multi-trajectory modeling was used to identify several clusters with dissimilar concurrent changes in physical activity and BMI within the studied cohort. Results Of the participants, 83% were women. The mean age at the last wave before retirement was 63.3 (SD 1.4) years. Four clusters with different trajectories of physical activity and BMI were identified. BMI remained stable around retirement transition in all four clusters, varying from normal weight to class II obesity. The association of BMI trajectories with physical activity levels were inverse, however, each activity trajectory showed a temporary increase during the retirement transition. Conclusions Retirement seems to have more effect on physical activity than BMI, showing a temporary increase in physical activity at the time of retirement.
We utilized compositional data analysis (CoDA) to study changes in the composition of the 24-h movement behaviors during an activity tracker based physical activity intervention. A total of 231 ...recently retired Finnish retirees were randomized into intervention and control groups. The intervention participants were requested to use a commercial activity tracker bracelet with daily activity goal and inactivity alerts for 12 months. The controls received no intervention. The 24-h movement behaviors, i.e., sleep, sedentary time (SED), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) were estimated from wrist-worn ActiGraph data using the GGIR R-package. Three balance coordinates describing the composition of movement behaviors were applied: ratio of active vs. passive behaviors, LPA vs. MVPA, and sleep vs. SED. A linear mixed model was used to study changes between the baseline and 6-month time point. Overall, the changes in the 24-h movement behaviors were small and did not differ between the groups. Only the ratio of LPA to MVPA tended to change differently between the groups (group*time interaction p = 0.08) as the intervention group increased LPA similarly to controls but decreased their MVPA. In conclusion, the use of a commercial activity tracker may not be enough to induce changes in the 24-h movement behaviors among retirees.
The Short Physical Performance Battery (SPPB) is a well-established tool to assess lower extremity physical performance status. Its predictive ability for all-cause mortality has been sparsely ...reported, but with conflicting results in different subsets of participants. The aim of this study was to perform a meta-analysis investigating the relationship between SPPB score and all-cause mortality.
Articles were searched in MEDLINE, the Cochrane Library, Google Scholar, and BioMed Central between July and September 2015 and updated in January 2016. Inclusion criteria were observational studies; >50 participants; stratification of population according to SPPB value; data on all-cause mortality; English language publications. Twenty-four articles were selected from available evidence. Data of interest (i.e., clinical characteristics, information after stratification of the sample into four SPPB groups 0-3, 4-6, 7-9, 10-12) were retrieved from the articles and/or obtained by the study authors. The odds ratio (OR) and/or hazard ratio (HR) was obtained for all-cause mortality according to SPPB category (with SPPB scores 10-12 considered as reference) with adjustment for age, sex, and body mass index.
Standardized data were obtained for 17 studies (n = 16,534, mean age 76 ± 3 years). As compared to SPPB scores 10-12, values of 0-3 (OR 3.25, 95%CI 2.86-3.79), 4-6 (OR 2.14, 95%CI 1.92-2.39), and 7-9 (OR 1.50, 95%CI 1.32-1.71) were each associated with an increased risk of all-cause mortality. The association between poor performance on SPPB and all-cause mortality remained highly consistent independent of follow-up length, subsets of participants, geographic area, and age of the population. Random effects meta-regression showed that OR for all-cause mortality with SPPB values 7-9 was higher in the younger population, diabetics, and men.
An SPPB score lower than 10 is predictive of all-cause mortality. The systematic implementation of the SPPB in clinical practice settings may provide useful prognostic information about the risk of all-cause mortality. Moreover, the SPPB could be used as a surrogate endpoint of all-cause mortality in trials needing to quantify benefit and health improvements of specific treatments or rehabilitation programs. The study protocol was published on PROSPERO (CRD42015024916).
Abstract
Objectives
Mental health is determined by social, biological, and cultural factors and is sensitive to life transitions. We examine how psychosocial working conditions, social living ...environment, and cumulative risk factors are associated with mental health changes during the retirement transition.
Method
We use data from the Finnish Retirement and Aging study on public sector employees (n = 3,338) retiring between 2014 and 2019 in Finland. Psychological distress was measured with the General Health Questionnaire annually before and after retirement and psychosocial working conditions, social living environment, and accumulation of risk factors at the study wave prior to retirement.
Results
Psychological distress decreased during the retirement transition, but the magnitude of the change was dependent on the contexts individuals retire from. Psychological distress was higher among those from poorer psychosocial working conditions (high job demands, low decision authority, job strain), poorer social living environment (low neighborhood social cohesion, small social network), and more cumulative risk factors (work/social/both). During the retirement transition, greatest reductions in psychological distress were observed among those with poorer conditions (work: absolute and relative changes, p Group × Time interactions < .05; social living environment and cumulative risk factors: absolute changes, p Group × Time interactions < .05).
Discussion
Psychosocial work-related stressors lead to quick recovery during the retirement transition but the social and cumulative stressors have longer-term prevailing effects on psychological distress. More studies are urged incorporating exposures across multiple levels or contexts to clarify the determinants of mental health during the retirement transition and more generally at older ages.
Abstract
Background
Frailty is an important geriatric syndrome, but little is known about its development in the years preceding onset of the syndrome. The aim of this study was to examine the ...progression of frailty and compare the trajectories of each frailty component prior to frailty onset.
Methods
Repeat data were from two cohort studies: the Longitudinal Aging Study Amsterdam (n = 1440) with a 15-year follow-up and the InCHIANTI Study (n = 998) with a 9-year follow-up. Participants were classified as frail if they had >3 frailty components (exhaustion, slowness, physical inactivity, weakness, and weight loss). Transitions between frailty components were examined with multistate modeling. Trajectories of frailty components were compared among persons who subsequently developed frailty to matched nonfrail persons by using mixed effects models.
Results
The probabilities were 0.43, 0.40, and 0.36 for transitioning from 0 to 1 frailty component, from 1 component to 2 components, and from 2 components to 3–5 components (the frail state). The transition probability from frail to death was 0.13. Exhaustion separated frail and nonfrail groups already 9 years prior to onset of frailty (pooled risk ratio RR = 1.53, 95% confidence interval CI 1.04–2.24). Slowness (RR = 1.94, 95% CI 1.44–2.61), low activity (RR = 1.59, 95% CI 1.19–2.13), and weakness (RR = 1.39, 95% CI 1.10–1.76) separated frail and nonfrail groups 6 years prior to onset of frailty. The fifth frailty component, weight loss, separated frail and nonfrail groups only at the onset of frailty (RR = 3.36, 95% CI 2.76–4.08).
Conclusions
Evidence from two cohort studies suggests that feelings of exhaustion tend to emerge early and weight loss near the onset of frailty syndrome.
Poor diet quality has been linked to increased risk of many chronic diseases and premature mortality. Less research has considered dietary habits in relation to disease-free life expectancy.
Our ...objective was to investigate the association of diet quality with cardiometabolic disease–free life expectancy between ages 50 and 85 y.
Diet quality of 8041 participants of the Whitehall II cohort study was assessed with the Alternative Healthy Eating Index 2010 (AHEI-2010) in 1991–1994, 1997–1999, and 2002–2004. The measurement of diet quality closest to age 50 for each participant was used. We utilized repeat measures of cardiometabolic disease (coronary heart disease, stroke, and type 2 diabetes) from the first observation when participants were aged ≥50 y. Multistate life table models with covariates age, gender, occupational position, smoking, physical activity, and alcohol consumption were used to estimate total and sex-specific cardiometabolic disease–free life expectancy from age 50 to 85 y for each AHEI-2010 quintile, where the lowest quintile represents unhealthiest dietary habits and the highest quintile the healthiest habits.
The number of cardiometabolic disease–free life-years after age 50 was 23.9 y (95% CI: 23.0, 24.9 y) for participants with the healthiest diet, that is, a higher score on the AHEI-2010, and 21.4 y (95% CI: 20.6, 22.3 y) for participants with the unhealthiest diet. The association between diet quality and cardiometabolic disease–free life expectancy followed a dose–response pattern and was observed in subgroups of participants of different occupational position, BMI, physical activity level, and smoking habit, as well as when participants without cardiometabolic disease at baseline were excluded from analyses.
Healthier dietary habits are associated with cardiometabolic disease–free life expectancy between ages 50 and 85.
OBJECTIVES: To determine optimal hand‐grip strength cut points for likelihood of mobility limitation in older people and to study whether these cut points differ according to body mass index (BMI).
...DESIGN: Cross‐sectional analysis of data.
SETTING: Data collected in the Finnish population‐based Health 2000 Survey.
PARTICIPANTS: One thousand eighty‐four men and 1,562 women aged 55 and older with complete data on anthropometry, hand‐grip strength and self‐reported mobility.
MEASUREMENTS: Mobility limitation was defined as difficulty walking 0.5 km or climbing stairs. Receiver operating characteristic analysis was used to estimate hand‐grip strength cut points for likelihood of mobility limitation.
RESULTS: The overall hand‐grip strength cut points for likelihood of mobility limitation were 37 kg (sensitivity 62%; specificity 76%) for men and 21 kg (sensitivity 67%; specificity 73%) for women. The effect of the interaction between hand‐grip strength and BMI on mobility limitation was significant in men (P=.02), but no such interaction was observed in women (P=.16). In men, the most‐optimal cutoff points were 33 kg (sensitivity 73%; specificity 79%) for normal‐weight men, 39 kg (sensitivity 67%; specificity 71%) for overweight men, and 40 kg (sensitivity 57%; specificity 68%) for obese men. In women, BMI‐specific hand‐grip strength cutoff values was not markedly more accurate than the overall cutoff value.
CONCLUSION: The hand‐grip strength test is a useful tool to identify persons at risk of mobility limitation. In men, hand‐grip strength cut points for mobility increased with BMI, whereas in women, only one hand‐grip strength threshold was identified.
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