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Sökning: WFRF:(Alfredsson Lars) > Jokela Markus

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1.
  • Fransson, Eleonor I, et al. (författare)
  • Job strain and the risk of stroke : an individual-participant data meta-analysis
  • 2015
  • Ingår i: Stroke. - 0039-2499 .- 1524-4628. ; 46:2, s. 557-559
  • Tidskriftsartikel (refereegranskat)abstract
    • 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.
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2.
  • Kivimäki, Mika, et al. (författare)
  • Body mass index and risk of dementia : Analysis of individual-level data from 1.3 million individuals
  • 2018
  • Ingår i: Alzheimer's & Dementia. - : Elsevier. - 1552-5260 .- 1552-5279. ; 14:5, s. 601-609
  • Tidskriftsartikel (refereegranskat)abstract
    • Introduction: Higher midlife body mass index (BMI) is suggested to increase the risk of dementia, but weight loss during the preclinical dementia phase may mask such effects. Methods: We examined this hypothesis in 1,349,857 dementia-free participants from 39 cohort studies. BMI was assessed at baseline. Dementia was ascertained at follow-up using linkage to electronic health records (N = 6894). We assumed BMI is little affected by preclinical dementia when assessed decades before dementia onset and much affected when assessed nearer diagnosis. Results: Hazard ratios per 5-kg/m(2) increase in BMI for dementia were 0.71 (95% confidence interval = 0.66-0.77), 0.94 (0.89-0.99), and 1.16 (1.05-1.27) when BMI was assessed 10 years, 10-20 years, and >20 years before dementia diagnosis. Conclusions: The association between BMI and dementia is likely to be attributable to two different processes: a harmful effect of higher BMI, which is observable in long follow-up, and a reverse-causation effect that makes a higher BMI to appear protective when the follow-up is short. (C) 2017 The Authors. Published by Elsevier Inc. on behalf of the Alzheimer's Association.
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3.
  • Kivimäki, Mika, et al. (författare)
  • Long working hours as a risk factor for atrial fibrillation : a multi-cohort study
  • 2017
  • Ingår i: European Heart Journal. - : Oxford University Press. - 0195-668X .- 1522-9645. ; 38:34, s. 2621-2628
  • Tidskriftsartikel (refereegranskat)abstract
    • Aims Studies suggest that people who work long hours are at increased risk of stroke, but the association of long working hours with atrial fibrillation, the most common cardiac arrhythmia and a risk factor for stroke, is unknown. We examined the risk of atrial fibrillation in individuals working long hours (>= 55 per week) and those working standard 35-40 h/week. Methods and results In this prospective multi-cohort study from the Individual-Participant-Data Meta-analysis in Working Populations (IPD-Work) Consortium, the study population was 85 494 working men and women (mean age 43.4 years) with no recorded atrial fibrillation. Working hours were assessed at study baseline (1991-2004). Mean follow-up for incident atrial fibrillation was 10 years and cases were defined using data on electrocardiograms, hospital records, drug reimbursement registers, and death certificates. We identified 1061 new cases of atrial fibrillation (10-year cumulative incidence 12.4 per 1000). After adjustment for age, sex and socioeconomic status, individuals working long hours had a 1.4-fold increased risk of atrial fibrillation compared with those working standard hours (hazard ratio = 1.42, 95% CI= 1.13-1.80, P= 0.003). There was no significant heterogeneity between the cohort-specific effect estimates (I-2= 0%, P = 0.66) and the finding remained after excluding participants with coronary heart disease or stroke at baseline or during the follow-up (N= 2006, hazard ratio= 1.36, 95% CI= 1.05-1.76, P = 0.0180). Adjustment for potential confounding factors, such as obesity, risky alcohol use and high blood pressure, had little impact on this association. Conclusion Individuals who worked long hours were more likely to develop atrial fibrillation than those working standard hours.
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4.
  • Kivimäki, Mika, et al. (författare)
  • Long working hours, socioeconomic status, and the risk of incident type 2 diabetes : a meta-analysis of published and unpublished data from 222 120 individuals.
  • 2015
  • Ingår i: The Lancet Diabetes and Endocrinology. - 2213-8587 .- 2213-8595. ; 3:1, s. 27-34
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUND: Working long hours might have adverse health effects, but whether this is true for all socioeconomic status groups is unclear. In this meta-analysis stratified by socioeconomic status, we investigated the role of long working hours as a risk factor for type 2 diabetes.METHODS: We identified four published studies through a systematic literature search of PubMed and Embase up to April 30, 2014. Study inclusion criteria were English-language publication; prospective design (cohort study); investigation of the effect of working hours or overtime work; incident diabetes as an outcome; and relative risks, odds ratios, or hazard ratios (HRs) with 95% CIs, or sufficient information to calculate these estimates. Additionally, we used unpublished individual-level data from 19 cohort studies from the Individual-Participant-Data Meta-analysis in Working-Populations Consortium and international open-access data archives. Effect estimates from published and unpublished data from 222 120 men and women from the USA, Europe, Japan, and Australia were pooled with random-effects meta-analysis.FINDINGS: During 1·7 million person-years at risk, 4963 individuals developed diabetes (incidence 29 per 10 000 person-years). The minimally adjusted summary risk ratio for long (≥55 h per week) compared with standard working hours (35-40 h) was 1·07 (95% CI 0·89-1·27, difference in incidence three cases per 10 000 person-years) with significant heterogeneity in study-specific estimates (I(2)=53%, p=0·0016). In an analysis stratified by socioeconomic status, the association between long working hours and diabetes was evident in the low socioeconomic status group (risk ratio 1·29, 95% CI 1·06-1·57, difference in incidence 13 per 10 000 person-years, I(2)=0%, p=0·4662), but was null in the high socioeconomic status group (1·00, 95% CI 0·80-1·25, incidence difference zero per 10 000 person-years, I(2)=15%, p=0·2464). The association in the low socioeconomic status group was robust to adjustment for age, sex, obesity, and physical activity, and remained after exclusion of shift workers.INTERPRETATION: In this meta-analysis, the link between longer working hours and type 2 diabetes was apparent only in individuals in the low socioeconomic status groups.FUNDING: Medical Research Council, European Union New and Emerging Risks in Occupational Safety and Health research programme, Finnish Work Environment Fund, Swedish Research Council for Working Life and Social Research, German Social Accident Insurance, Danish National Research Centre for the Working Environment, Academy of Finland, Ministry of Social Affairs and Employment (Netherlands), Economic and Social Research Council, US National Institutes of Health, and British Heart Foundation.
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5.
  • Kivimäki, Mika, et al. (författare)
  • Overweight, obesity, and risk of cardiometabolic multimorbidity : pooled analysis of individual-level data for 120 813 adults from 16 cohort studies from the USA and Europe
  • 2017
  • Ingår i: The Lancet Public Health. - : The Lancet Publishing Group. - 2468-2667. ; 2:6, s. e277-e285
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUND: Although overweight and obesity have been studied in relation to individual cardiometabolic diseases, their association with risk of cardiometabolic multimorbidity is poorly understood. Here we aimed to establish the risk of incident cardiometabolic multimorbidity (ie, at least two from: type 2 diabetes, coronary heart disease, and stroke) in adults who are overweight and obese compared with those who are a healthy weight.METHODS: ) to achieve sufficient case numbers for analysis. The main outcome was cardiometabolic multimorbidity (ie, developing at least two from: type 2 diabetes, coronary heart disease, and stroke). Incident cardiometabolic multimorbidity was ascertained via resurvey or linkage to electronic medical records (including hospital admissions and death). We analysed data from each cohort separately using logistic regression and then pooled cohort-specific estimates using random-effects meta-analysis.FINDINGS: Participants were 120  813 adults (mean age 51·4 years, range 35-103; 71 445 women) who did not have diabetes, coronary heart disease, or stroke at study baseline (1973-2012). During a mean follow-up of 10·7 years (1995-2014), we identified 1627 cases of multimorbidity. After adjustment for sociodemographic and lifestyle factors, compared with individuals with a healthy weight, the risk of developing cardiometabolic multimorbidity in overweight individuals was twice as high (odds ratio [OR] 2·0, 95% CI 1·7-2·4; p<0·0001), almost five times higher for individuals with class I obesity (4·5, 3·5-5·8; p<0·0001), and almost 15 times higher for individuals with classes II and III obesity combined (14·5, 10·1-21·0; p<0·0001). This association was noted in men and women, young and old, and white and non-white participants, and was not dependent on the method of exposure assessment or outcome ascertainment. In analyses of different combinations of cardiometabolic conditions, odds ratios associated with classes II and III obesity were 2·2 (95% CI 1·9-2·6) for vascular disease only (coronary heart disease or stroke), 12·0 (8·1-17·9) for vascular disease followed by diabetes, 18·6 (16·6-20·9) for diabetes only, and 29·8 (21·7-40·8) for diabetes followed by vascular disease.INTERPRETATION: The risk of cardiometabolic multimorbidity increases as BMI increases; from double in overweight people to more than ten times in severely obese people compared with individuals with a healthy BMI. Our findings highlight the need for clinicians to actively screen for diabetes in overweight and obese patients with vascular disease, and pay increased attention to prevention of vascular disease in obese individuals with diabetes.FUNDING: NordForsk, Medical Research Council, Cancer Research UK, Finnish Work Environment Fund, and Academy of Finland.
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6.
  • Kivimäki, Mika, et al. (författare)
  • Physical inactivity, cardiometabolic disease, and risk of dementia : an individual-participant meta-analysis
  • 2019
  • Ingår i: The BMJ. - ENGLAND : BMJ Publishing Group Ltd. - 1756-1833 .- 0959-8138. ; 365
  • Tidskriftsartikel (refereegranskat)abstract
    • OBJECTIVE To examine whether physical inactivity is a risk factor for dementia, with attention to the role of cardiometabolic disease in this association and reverse causation bias that arises from changes in physical activity in the preclinical (prodromal) phase of dementia. DESIGN Meta-analysis of 19 prospective observational cohort studies. DATA SOURCES The Individual-Participant-Data Meta-analysis in Working Populations Consortium, the Inter-University Consortium for Political and Social Research, and the UK Data Service, including a total of 19 of a potential 9741 studies. REVIEW METHOD The search strategy was designed to retrieve individual-participant data from prospective cohort studies. Exposure was physical inactivity; primary outcomes were incident all-cause dementia and Alzheimer's disease; and the secondary outcome was incident cardiometabolic disease (that is, diabetes, coronary heart disease, and stroke). Summary estimates were obtained using random effects meta-analysis. RESULTS Study population included 404 840 people (mean age 45.5 years, 57.7% women) who were initially free of dementia, had a measurement of physical inactivity at study entry, and were linked to electronic health records. In 6.0 million person-years at risk, we recorded 2044 incident cases of all-cause dementia. In studies with data on dementia subtype, the number of incident cases of Alzheimer's disease was 1602 in 5.2 million person-years. When measured < 10 years before dementia diagnosis (that is, the preclinical stage of dementia), physical inactivity was associated with increased incidence of all-cause dementia (hazard ratio 1.40, 95% confidence interval 1.23 to 1.71) and Alzheimer's disease (1.36, 1.12 to 1.65). When reverse causation was minimised by assessing physical activity >= 10 years before dementia onset, no difference in dementia risk between physically active and inactive participants was observed (hazard ratios 1.01 (0.89 to 1.14) and 0.96 (0.85 to 1.08) for the two outcomes). Physical inactivity was consistently associated with increased risk of incident diabetes (hazard ratio 1.42, 1.25 to 1.61), coronary heart disease (1.24, 1.13 to 1.36), and stroke (1.16, 1.05 to 1.27). Among people in whom cardiometabolic disease preceded dementia, physical inactivity was non-significantly associated with dementia (hazard ratio for physical activity assessed > 10 before dementia onset 1.30, 0.79 to 2.14). CONCLUSIONS In analyses that addressed bias due to reverse causation, physical inactivity was not associated with all-cause dementia or Alzheimer's disease, although an indication of excess dementia risk was observed in a subgroup of physically inactive individuals who developed cardiometabolic disease.
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7.
  • Kivimäki, Mika, et al. (författare)
  • Work stress and risk of death in men and women with and without cardiometabolic disease : a multicohort study
  • 2018
  • Ingår i: The Lancet Diabetes and Endocrinology. - : Elsevier. - 2213-8587 .- 2213-8595. ; 6:9, s. 705-713
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUND: Although some cardiovascular disease prevention guidelines suggest a need to manage work stress in patients with established cardiometabolic disease, the evidence base for this recommendation is weak. We sought to clarify the status of stress as a risk factor in cardiometabolic disease by investigating the associations between work stress and mortality in men and women with and without pre-existing cardiometabolic disease.METHODS: In this multicohort study, we used data from seven cohort studies in the IPD-Work consortium, initiated between 1985 and 2002 in Finland, France, Sweden, and the UK, to examine the association between work stress and mortality. Work stress was denoted as job strain or effort-reward imbalance at work. We extracted individual-level data on prevalent cardiometabolic diseases (coronary heart disease, stroke, or diabetes [without differentiation by diabetes type]) at baseline. Work stressors, socioeconomic status, and conventional and lifestyle risk factors (systolic and diastolic blood pressure, total cholesterol, smoking status, BMI, physical activity, and alcohol consumption) were also assessed at baseline. Mortality data, including date and cause of death, were obtained from national death registries. We used Cox proportional hazards regression to study the associations of work stressors with mortality in men and women with and without cardiometabolic disease.RESULTS: We identified 102 633 individuals with 1 423 753 person-years at risk (mean follow-up 13·9 years [SD 3·9]), of whom 3441 had prevalent cardiometabolic disease at baseline and 3841 died during follow-up. In men with cardiometabolic disease, age-standardised mortality rates were substantially higher in people with job strain (149·8 per 10 000 person-years) than in those without (97·7 per 10 000 person-years; mortality difference 52·1 per 10 000 person-years; multivariable-adjusted hazard ratio [HR] 1·68, 95% CI 1·19-2·35). This mortality difference for job strain was almost as great as that for current smoking versus former smoking (78·1 per 10 000 person-years) and greater than those due to hypertension, high total cholesterol concentration, obesity, physical inactivity, and high alcohol consumption relative to the corresponding lower risk groups (mortality difference 5·9-44·0 per 10 000 person-years). Excess mortality associated with job strain was also noted in men with cardiometabolic disease who had achieved treatment targets, including groups with a healthy lifestyle (HR 2·01, 95% CI 1·18-3·43) and those with normal blood pressure and no dyslipidaemia (6·17, 1·74-21·9). In all women and in men without cardiometabolic disease, relative risk estimates for the work stress-mortality association were not significant, apart from effort-reward imbalance in men without cardiometabolic disease (mortality difference 6·6 per 10 000 person-years; multivariable-adjusted HR 1·22, 1·06-1·41).INTERPRETATION: In men with cardiometabolic disease, the contribution of job strain to risk of death was clinically significant and independent of conventional risk factors and their treatment, and measured lifestyle factors. Standard care targeting conventional risk factors is therefore unlikely to mitigate the mortality risk associated with job strain in this population.FUNDING: NordForsk, UK Medical Research Council, and Academy of Finland.
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8.
  • Nyberg, Solja T., et al. (författare)
  • Association of alcohol use with years lived without major chronic diseases : A multicohort study from the IPD-Work consortium and UK Biobank
  • 2022
  • Ingår i: The Lancet Regional Health - Europe. - : Elsevier. - 2666-7762. ; 19
  • Tidskriftsartikel (refereegranskat)abstract
    • Background Heavy alcohol consumption increases the risk of several chronic diseases. In this multicohort study, we estimated the number of life-years without major chronic diseases according to different characteristics of alcohol use.Methods In primary analysis, we pooled individual-level data from up to 129,942 adults across 12 cohort studies with baseline data collection on alcohol consumption, drinking patterns, and history between 1986 and 2005 (the IPD-Work Consortium). Self-reported alcohol consumption was categorised according to UK guidelines - non-drinking (never or former drinkers); moderate consumption (1-14 units); heavy consumption (>14 units per week). We further subdivided moderate and heavy drinkers by binge drinking pattern (alcohol-induced loss of consciousness). In addition, we assessed problem drinking using linked data on hospitalisations due to alcohol abuse or poisoning. Follow-up for chronic diseases for all participants included incident type 2 diabetes, coronary heart disease, stroke, cancer, and respiratory disease (asthma and chronic obstructive pulmonary disease) as ascertained via linkage to national morbidity and mortality registries, repeated medical examinations, and/or self-report. We estimated years lived without any of these diseases between 40 and 75 years of age according to sex and characteristics of alcohol use. We repeated the main analyses using data from 427,621 participants in the UK Biobank cohort study.Findings During 1.73 million person-years at risk, 22,676 participants in IPD-Work cohorts developed at least one chronic condition. From age 40 to 75 years, never-drinkers [men: 29.3 (95%CI 27.9-30.8) years, women 29.8 (29.2 - 30.4) years)] and moderate drinkers with no binge drinking habit [men 28.7 (28.4-29.0) years, women 29.6 (29.4-29.7) years] had the longest disease-free life span. A much shorter disease-free life span was apparent in participants who experienced alcohol poisoning [men 23.4 (20.9-26.0) years, women 24.0 (21.4-26.5) years] and those with self-reported heavy overall consumption and binge drinking [men: 26.0 (25.3-26.8), women 27.5 (26.4 - 28.5) years]. The pattern of results for alcohol poisoning and self-reported alcohol consumption was similar in UK Biobank. In IPD-Work and UK Biobank, differences in disease-free years between self-reported moderate drinkers and heavy drinkers were 1.5 years or less.Interpretation Individuals with alcohol poisonings or heavy self-reported overall consumption combined with a binge drinking habit have a marked 3- to 6-year loss in healthy longevity. Differences in disease-free life between categories of self-reported weekly alcohol consumption were smaller.
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9.
  • Nyberg, Solja T., et al. (författare)
  • Association of Healthy Lifestyle With Years Lived Without Major Chronic Diseases
  • 2020
  • Ingår i: JAMA Internal Medicine. - : American Medical Association (AMA). - 2168-6106 .- 2168-6114. ; 180:5, s. 760-768
  • Tidskriftsartikel (refereegranskat)abstract
    • This cohort study examines disease-free life-years in participants with varying combinations of lifestyle risk factors.Question: Are different combinations of lifestyle factors associated with years lived without chronic diseases?Findings: In a multicohort study of 116 & x202f;043 participants, a statistically significant association between overall healthy lifestyle score and an increased number of disease-free life-years was noted. Of 16 different lifestyle profiles studied, the 4 that were associated with the greatest disease-free life years included body mass index lower than 25 and at least 2 of 3 factors: never smoking, physical activity, and moderate alcohol consumption.Meaning: Various healthy lifestyle profiles appear to be associated with extended gains in life lived without type 2 diabetes, cardiovascular and respiratory diseases, and cancer.Importance: It is well established that selected lifestyle factors are individually associated with lower risk of chronic diseases, but how combinations of these factors are associated with disease-free life-years is unknown.Objective: To estimate the association between healthy lifestyle and the number of disease-free life-years.Design, Setting, and Participants: A prospective multicohort study, including 12 European studies as part of the Individual-Participant-Data Meta-analysis in Working Populations Consortium, was performed. Participants included 116 & x202f;043 people free of major noncommunicable disease at baseline from August 7, 1991, to May 31, 2006. Data analysis was conducted from May 22, 2018, to January 21, 2020.Exposures: Four baseline lifestyle factors (smoking, body mass index, physical activity, and alcohol consumption) were each allocated a score based on risk status: optimal (2 points), intermediate (1 point), or poor (0 points) resulting in an aggregated lifestyle score ranging from 0 (worst) to 8 (best). Sixteen lifestyle profiles were constructed from combinations of these risk factors.Main Outcomes and Measures: The number of years between ages 40 and 75 years without chronic disease, including type 2 diabetes, coronary heart disease, stroke, cancer, asthma, and chronic obstructive pulmonary disease.Results: Of the 116 & x202f;043 people included in the analysis, the mean (SD) age was 43.7 (10.1) years and 70 & x202f;911 were women (61.1%). During 1.45 million person-years at risk (mean follow-up, 12.5 years; range, 4.9-18.6 years), 17 & x202f;383 participants developed at least 1 chronic disease. There was a linear association between overall healthy lifestyle score and the number of disease-free years, such that a 1-point improvement in the score was associated with an increase of 0.96 (95% CI, 0.83-1.08) disease-free years in men and 0.89 (95% CI, 0.75-1.02) years in women. Comparing the best lifestyle score with the worst lifestyle score was associated with 9.9 (95% CI 6.7-13.1) additional years without chronic diseases in men and 9.4 (95% CI 5.4-13.3) additional years in women (P < .001 for dose-response). All of the 4 lifestyle profiles that were associated with the highest number of disease-free years included a body-mass index less than 25 (calculated as weight in kilograms divided by height in meters squared) and at least 2 of the following factors: never smoking, physical activity, and moderate alcohol consumption. Participants with 1 of these lifestyle profiles reached age 70.3 (95% CI, 69.9-70.8) to 71.4 (95% CI, 70.9-72.0) years disease free depending on the profile and sex.Conclusions and Relevance: In this multicohort analysis, various healthy lifestyle profiles appeared to be associated with gains in life-years without major chronic diseases.
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10.
  • Theorell, Töres, et al. (författare)
  • Obesity and loss of disease-free years owing to major non-communicable diseases : a multicohort study
  • 2018
  • Ingår i: The Lancet Public Health. - : Elsevier Ltd. - 2468-2667. ; 3:10, s. e490-e497
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Obesity increases the risk of several chronic diseases, but the extent to which the obesity-related loss of disease-free years varies by lifestyle category and across socioeconomic groups is unclear. We estimated the number of years free from major non-communicable diseases in adults who are overweight and obese, compared with those who are normal weight. Methods: We pooled individual-level data on body-mass index (BMI) and non-communicable diseases from men and women with no initial evidence of these diseases in European cohort studies from the Individual-Participant-Data Meta-Analysis in Working Populations consortium. BMI was assessed at baseline (1991–2008) and non-communicable diseases (incident type 2 diabetes, coronary heart disease, stroke, cancer, asthma, and chronic obstructive pulmonary disease) were ascertained via linkage to records from national health registries, repeated medical examinations, or self-report. Disease-free years from age 40 years to 75 years associated with underweight (BMI <18·5 kg/m2), overweight (≥25 kg/m2 to <30 kg/m2), and obesity (class I [mild] ≥30 kg/m2 to <35 kg/m2; class II–III [severe] ≥35 kg/m2) compared with normal weight (≥18·5 kg/m2 to <25 kg/m2) were estimated. Findings: Of 137 503 participants from ten studies, we excluded 6973 owing to missing data and 10 349 with prevalent disease at baseline, resulting in an analytic sample of 120 181 participants. Of 47 127 men, 211 (0·4%) were underweight, 21 468 (45·6%) normal weight, 20 738 (44·0%) overweight, 3982 (8·4%) class I obese, and 728 (1·5%) class II–III obese. The corresponding numbers among the 73 054 women were 1493 (2·0%), 44 760 (61·3%), 19 553 (26·8%), 5670 (7·8%), and 1578 (2·2%), respectively. During 1 328 873 person-years at risk (mean follow-up 11·5 years [range 6·3–18·6]), 8159 men and 8100 women developed at least one non-communicable disease. Between 40 years and 75 years, the estimated number of disease-free years was 29·3 (95% CI 28·8–29·8) in normal-weight men and 29·4 (28·7–30·0) in normal-weight women. Compared with normal weight, the loss of disease-free years in men was 1·8 (95% CI −1·3 to 4·9) for underweight, 1·1 (0·7 to 1·5) for overweight, 3·9 (2·9 to 4·9) for class I obese, and 8·5 (7·1 to 9·8) for class II–III obese. The corresponding estimates for women were 0·0 (−1·4 to 1·4) for underweight, 1·1 (0·6 to 1·5) for overweight, 2·7 (1·5 to 3·9) for class I obese, and 7·3 (6·1 to 8·6) for class II–III obese. The loss of disease-free years associated with class II–III obesity varied between 7·1 and 10·0 years in subgroups of participants of different socioeconomic level, physical activity level, and smoking habit. Interpretation: Mild obesity was associated with the loss of one in ten, and severe obesity the loss of one in four potential disease-free years during middle and later adulthood. This increasing loss of disease-free years as obesity becomes more severe occurred in both sexes, among smokers and non-smokers, the physically active and inactive, and across the socioeconomic hierarchy. Funding: NordForsk, UK Medical Research Council, US National Institute on Aging, Academy of Finland, Helsinki Institute of Life Science, and Cancer Research UK. 
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