Underestimating the true impact of obesity Reply

Non peer reviewe

Job strain as a risk factor for leisure-time physical inactivity: an individual-participant meta-analysis of up to 170,000 men and women: the IPD-Work Consortium

Unfavorable work characteristics, such as low job control and too high or too low job demands, have been suggested to increase the likelihood of physical inactivity during leisure time, but this has not been verified in large-scale studies. The authors combined individual-level data from 14 European cohort studies (baseline years from 1985–1988 to 2006–2008) to examine the association between unfavorable work characteristics and leisure-time physical inactivity in a total of 170,162 employees (50% women; mean age, 43.5 years). Of these employees, 56,735 were reexamined after 2–9 years. In cross-sectional analyses, the odds for physical inactivity were 26% higher (odds ratio = 1.26, 95% confidence interval: 1.15, 1.38) for employees with high-strain jobs (low control/high demands) and 21% higher (odds ratio = 1.21, 95% confidence interval: 1.11, 1.31) for those with passive jobs (low control/low demands) compared with employees in low-strain jobs (high control/low demands). In prospective analyses restricted to physically active participants, the odds of becoming physically inactive during follow-up were 21% and 20% higher for those with high-strain (odds ratio = 1.21, 95% confidence interval: 1.11, 1.32) and passive (odds ratio = 1.20, 95% confidence interval: 1.11, 1.30) jobs at baseline. These data suggest that unfavorable work characteristics may have a spillover effect on leisure-time physical activity

Job strain and the risk of stroke: an individual-participant data meta-analysis

Background and Purpose—Psychosocial stress at work has been proposed to be a risk factor for cardiovascular disease. However, its role as a risk factor for stroke is uncertain. Methods—We conducted an individual-participant-data meta-analysis of 196 380 males and females from 14 European cohort studies to investigate the association between job strain, a measure of work-related stress, and incident stroke. Results—In 1.8 million person-years at risk (mean follow-up 9.2 years), 2023 first-time stroke events were recorded. The age- and sex-adjusted hazard ratio for job strain relative to no job strain was 1.24 (95% confidence interval, 1.05;1.47) for ischemic stroke, 1.01 (95% confidence interval, 0.75;1.36) for hemorrhagic stroke, and 1.09 (95% confidence interval, 0.94;1.26) for overall stroke. The association with ischemic stroke was robust to further adjustment for socioeconomic status. Conclusion—Job strain may be associated with an increased risk of ischemic stroke, but further research is needed to determine whether interventions targeting job strain would reduce stroke risk beyond existing preventive strategies

Emotional demands at work and risk of long-term sickness absence in 1·5 million employees in Denmark : a prospective cohort study on effect modifiers

Publisher Copyright: © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under CC BY-NC-ND 4.0 licenseBackground: High emotional demands at work can affect employees’ health and there is a need to understand whether such an association might be modified by other working conditions. We aimed to examine emotional demands at work as a risk factor for long-term sickness absence and analyse whether influence, possibilities for development, role conflicts, and physical demands at work might modify this risk. Methods: We did a nationwide, population-based, prospective cohort study in Denmark and included employed individuals who were residing in Denmark in 2000, aged 30–59 years, who had complete data on age, sex, and migration background, with information on emotional demands and possible effect modifiers from job exposure matrices, and covariates and outcome (sickness absence) from population registers. Individuals with long-term sickness absence (≥6 weeks of consecutive sickness absence) between Jan 1, 1998, and Dec 31, 2000, and self-employed individuals were excluded. We assessed long-term sickness absence during a 10-year period from Jan 1, 2001, to Dec 31, 2010. Using Cox regression, we estimated hazard ratios (HRs) and 95% CIs and tested interaction as departure from additivity, estimating relative excess risk due to interaction (RERI). Multivariable adjusted models included sex, age, cohabitation, migration background, and income. Findings: 1 521 352 employed individuals were included and contributed data between Jan 1, 2000, and Dec 31, 2010. During 11 919 021 person-years (mean follow-up 7·8 years), we identified 480 685 new cases of long-term sickness absence. High emotional demands were associated with increased risk of long-term sickness absence compared with low emotional demands, after adjusting for age, sex, cohabitation, migration background, income, and the four possible effect modifiers (adjusted HR 1·55 [95% CI 1·53–1·56]). The association between high emotional demands and risk of long-term sickness absence was stronger in a synergistic way when individuals were also exposed to low possibilities for development (RERI 0·35 [95% CI 0·22–0·47]; 28·9 additional cases per 1000 person-years) and high role conflicts (0·13 [0·11–0·15]; 22·0 additional cases per 1000 person-years). No synergy was observed for influence and physical demands at work. Interpretation: People in occupations with high emotional demands were at increased risk of long-term sickness absence. Our findings on synergistic interactions suggest that, in emotionally demanding occupations, increasing possibilities for development and reducing work-related role conflicts might reduce long-term sickness absence. Further interventional studies are needed to confirm or refute this hypothesis. Funding: Danish Work Environment Research Fund, NordForsk.Peer reviewe

Individual and Combined Effects of Job Strain Components on Subsequent Morbidity and Mortality

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Predicting work disability among people with chronic conditions: a prospective cohort study

Few risk prediction scores are available to identify people at increased risk of work disability, particularly for those with an existing morbidity. We examined the predictive performance of disability risk scores for employees with chronic disease. We used prospective data from 88,521 employed participants (mean age 43.1) in the Finnish Public Sector Study including people with chronic disorders: musculoskeletal disorder, depression, migraine, respiratory disease, hypertension, cancer, coronary heart disease, diabetes, comorbid depression and cardiometabolic disease. A total of 105 predictors were assessed at baseline. During a mean follow-up of 8.6 years, 6836 (7.7%) participants were granted a disability pension. C-statistics for the 8-item Finnish Institute of Occupational Health (FIOH) risk score, comprising age, self-rated health, number of sickness absences, socioeconomic position, number of chronic illnesses, sleep problems, BMI, and smoking at baseline, exceeded 0.72 for all disease groups and was 0.80 (95% CI 0.80-0.81) for participants with musculoskeletal disorders, 0.83 (0.82-0.84) for those with migraine, and 0.82 (0.81-0.83) for individuals with respiratory disease. Predictive performance was not significantly improved in models with re-estimated coefficients or a new set of predictors. These findings suggest that the 8-item FIOH work disability risk score may serve as a scalable screening tool in identifying individuals with increased risk for work disability

Long‐term risk of dementia following hospitalization due to physical diseases: A multicohort study

Introduction Conventional risk factors targeted by prevention (e.g., low education, smoking, and obesity) are associated with a 1.2‐ to 2‐fold increased risk of dementia. It is unclear whether having a physical disease is an equally important risk factor for dementia. Methods In this exploratory multicohort study of 283,414 community‐dwelling participants, we examined 22 common hospital‐treated physical diseases as risk factors for dementia. Results During a median follow‐up of 19 years, a total of 3416 participants developed dementia. Those who had erysipelas (hazard ratio = 1.82; 95% confidence interval = 1.53 to 2.17), hypothyroidism (1.94; 1.59 to 2.38), myocardial infarction (1.41; 1.20 to 1.64), ischemic heart disease (1.32; 1.18 to 1.49), cerebral infarction (2.44; 2.14 to 2.77), duodenal ulcers (1.88; 1.42 to 2.49), gastritis and duodenitis (1.82; 1.46 to 2.27), or osteoporosis (2.38; 1.75 to 3.23) were at a significantly increased risk of dementia. These associations were not explained by conventional risk factors or reverse causation. Discussion In addition to conventional risk factors, several physical diseases may increase the long‐term risk of dementia.Peer reviewe

Body-mass index and risk of obesity-related complex multimorbidity : an observational multicohort study

Background The accumulation of disparate diseases in complex multimorbidity makes prevention difficult if each disease is targeted separately. We aimed to examine obesity as a shared risk factor for common diseases, determine associations between obesity-related diseases, and examine the role of obesity in the development of complex multimorbidity (four or more comorbid diseases). Methods We did an observational study and used pooled prospective data from two Finnish cohort studies (the Health and Social Support Study and the Finnish Public Sector Study) comprising 114 657 adults aged 16-78 years at study entry (1998-2013). A cohort of 499 357 adults (aged 38-73 years at study entry; 2006-10) from the UK Biobank provided replication in an independent population. BMI and clinical characteristics were assessed at baseline. BMIs were categorised as obesity (Peer reviewe

Estimating Dementia Risk Using Multifactorial Prediction Models

IMPORTANCE: The clinical value of current multifactorial algorithms for individualized assessment of dementia risk remains unclear. OBJECTIVE: To evaluate the clinical value associated with 4 widely used dementia risk scores in estimating 10-year dementia risk. DESIGN, SETTING, AND PARTICIPANTS: This prospective population-based UK Biobank cohort study assessed 4 dementia risk scores at baseline (2006-2010) and ascertained incident dementia during the following 10 years. Replication with a 20-year follow-up was based on the British Whitehall II study. For both analyses, participants who had no dementia at baseline, had complete data on at least 1 dementia risk score, and were linked to electronic health records from hospitalizations or mortality were included. Data analysis was conducted from July 5, 2022, to April 20, 2023. EXPOSURES: Four existing dementia risk scores: the Cardiovascular Risk Factors, Aging and Dementia (CAIDE)-Clinical score, the CAIDE-APOE-supplemented score, the Brief Dementia Screening Indicator (BDSI), and the Australian National University Alzheimer Disease Risk Index (ANU-ADRI). MAIN OUTCOMES AND MEASURES: Dementia was ascertained from linked electronic health records. To evaluate how well each score predicted the 10-year risk of dementia, concordance (C) statistics, detection rate, false-positive rate, and the ratio of true to false positives were calculated for each risk score and for a model including age alone. RESULTS: Of 465 929 UK Biobank participants without dementia at baseline (mean [SD] age, 56.5 [8.1] years; range, 38-73 years; 252 778 [54.3%] female participants), 3421 were diagnosed with dementia at follow-up (7.5 per 10 000 person-years). If the threshold for a positive test result was calibrated to achieve a 5% false-positive rate, all 4 risk scores detected 9% to 16% of incident dementia and therefore missed 84% to 91% (failure rate). The corresponding failure rate was 84% for a model that included age only. For a positive test result calibrated to detect at least half of future incident dementia, the ratio of true to false positives ranged between 1 to 66 (for CAIDE-APOE-supplemented) and 1 to 116 (for ANU-ADRI). For age alone, the ratio was 1 to 43. The C statistic was 0.66 (95% CI, 0.65-0.67) for the CAIDE clinical version, 0.73 (95% CI, 0.72-0.73) for the CAIDE-APOE-supplemented, 0.68 (95% CI, 0.67-0.69) for BDSI, 0.59 (95% CI, 0.58-0.60) for ANU-ADRI, and 0.79 (95% CI, 0.79-0.80) for age alone. Similar C statistics were seen for 20-year dementia risk in the Whitehall II study cohort, which included 4865 participants (mean [SD] age, 54.9 [5.9] years; 1342 [27.6%] female participants). In a subgroup analysis of same-aged participants aged 65 (±1) years, discriminatory capacity of risk scores was low (C statistics between 0.52 and 0.60). CONCLUSIONS AND RELEVANCE: In these cohort studies, individualized assessments of dementia risk using existing risk prediction scores had high error rates. These findings suggest that the scores were of limited value in targeting people for dementia prevention. Further research is needed to develop more accurate algorithms for estimation of dementia risk

Body-mass index and risk of obesity-related complex multimorbidity: an observational multicohort study

BACKGROUND: The accumulation of disparate diseases in complex multimorbidity makes prevention difficult if each disease is targeted separately. We aimed to examine obesity as a shared risk factor for common diseases, determine associations between obesity-related diseases, and examine the role of obesity in the development of complex multimorbidity (four or more comorbid diseases). METHODS: We did an observational study and used pooled prospective data from two Finnish cohort studies (the Health and Social Support Study and the Finnish Public Sector Study) comprising 114 657 adults aged 16-78 years at study entry (1998-2013). A cohort of 499 357 adults (aged 38-73 years at study entry; 2006-10) from the UK Biobank provided replication in an independent population. BMI and clinical characteristics were assessed at baseline. BMIs were categorised as obesity (≥30·0 kg/m2), overweight (25·0-29·9 kg/m2), healthy weight (18·5-24·9 kg/m2), and underweight (<18·5 kg/m2). Via linkage to national health records, participants were followed-up for death and diseases diagnosed according to the International Classification of Diseases 10th Revision (ICD-10). Hazard ratios (HRs) with 95% CIs and population attributable fractions (PAFs) for associations between BMI and multimorbidity were calculated. FINDINGS: Mean follow-up duration was 12·1 years (SD 3·8) in the Finnish cohorts and 11·8 years (1·7) in the UK Biobank cohort. Obesity was associated with 21 non-overlapping cardiometabolic, digestive, respiratory, neurological, musculoskeletal, and infectious diseases after Bonferroni multiple testing adjustment and ignoring HRs of less than 1·50. Compared with healthy weight, the confounder-adjusted HR for obesity was 2·83 (95% CI 2·74-2·93; PAF 19·9% [95% CI 19·3-20·5]) for developing at least one obesity-related disease, 5·17 (4·84-5·53; 34·4% [33·2-35·5]) for two diseases, and 12·39 (9·26-16·58; 55·2% [50·9-57·5]) for complex multimorbidity. The proportion of participants of healthy weight with complex multimorbidity by age 75 years was observed by age 55 years in participants with obesity, and degree of obesity was associated with complex multimorbidity in a dose-response relationship. Compared with obesity, the association between overweight and complex multimorbidity was more modest (HR 2·67, 95% CI 1·94-3·68; PAF 13·3% [95% CI 9·6-16·3]). The same pattern of results was observed in the UK Biobank cohort. INTERPRETATION: Obesity is associated with diverse, increasing disease burdens, and might represent an important target for multimorbidity prevention that avoids the complexities of multitarget preventive regimens. FUNDING: Wellcome Trust, Medical Research Council, National Institute on Aging