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| 2. |
- Fransson, Eleonor, 1971-, et al.
(författare)
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Job strain as a risk factor for leisure-time physical inactivity : an individual-participant meta-analysis of up to 170,000 men and women
- 2012
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Ingår i: American Journal of Epidemiology. - Cary : Oxford University Press. - 0002-9262 .- 1476-6256. ; 176:12, s. 1078-1089
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Forskningsöversikt (refereegranskat)abstract
- 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 19851988 to 20062008) 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 29 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.
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| 3. |
- Heikkila, Katriina, et al.
(författare)
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Job Strain and Alcohol Intake : A Collaborative Meta-Analysis of Individual-Participant Data from 140 000 Men and Women
- 2012
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 7:7, s. Art. no. e40101-
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Tidskriftsartikel (refereegranskat)abstract
- Background: The relationship between work-related stress and alcohol intake is uncertain. In order to add to the thus far inconsistent evidence from relatively small studies, we conducted individual-participant meta-analyses of the association between work-related stress (operationalised as self-reported job strain) and alcohol intake. Methodology and Principal Findings: We analysed cross-sectional data from 12 European studies (n = 142 140) and longitudinal data from four studies (n = 48 646). Job strain and alcohol intake were self-reported. Job strain was analysed as a binary variable (strain vs. no strain). Alcohol intake was harmonised into the following categories: none, moderate (women: 1-14, men: 1-21 drinks/week), intermediate (women: 15-20, men: 22-27 drinks/week) and heavy (women: > 20, men: > 27 drinks/week). Cross-sectional associations were modelled using logistic regression and the results pooled in random effects meta-analyses. Longitudinal associations were examined using mixed effects logistic and modified Poisson regression. Compared to moderate drinkers, non-drinkers and (random effects odds ratio (OR): 1.10, 95% CI: 1.05, 1.14) and heavy drinkers (OR: 1.12, 95% CI: 1.00, 1.26) had higher odds of job strain. Intermediate drinkers, on the other hand, had lower odds of job strain (OR: 0.92, 95% CI: 0.86, 0.99). We found no clear evidence for longitudinal associations between job strain and alcohol intake. Conclusions: Our findings suggest that compared to moderate drinkers, non-drinkers and heavy drinkers are more likely and intermediate drinkers less likely to report work-related stress.
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| 4. |
- Heikkilä, Katriina, et al.
(författare)
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Work stress and risk of cancer: meta-analysis of 5700 incident cancer events in 116 000 European men and women
- 2013
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Ingår i: The BMJ. - : BMJ. - 1756-1833. ; 345:f165
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Tidskriftsartikel (refereegranskat)abstract
- Objective To investigate whether work related stress, measured and defined as job strain, is associated with the overall risk of cancer and the risk of colorectal, lung, breast, or prostate cancers.Design Meta-analysis of pooled prospective individual participant data from 12 European cohort studies including 116 056 men and women aged 17-70 who were free from cancer at study baseline and were followed-up for a median of 12 years. Work stress was measured and defined as job strain, which was self reported at baseline. Incident cancers (all n=5765, colorectal cancer n=522, lung cancer n=374, breast cancer n=1010, prostate cancer n=865) were ascertained from cancer, hospital admission, and death registers. Data were analysed in each study with Cox regression and the study specific estimates pooled in meta-analyses. Models were adjusted for age, sex, socioeconomic position, body mass index (BMI), smoking, and alcohol intakeResults A harmonised measure of work stress, high job strain, was not associated with overall risk of cancer (hazard ratio 0.97, 95% confidence interval 0.90 to 1.04) in the multivariable adjusted analyses. Similarly, no association was observed between job strain and the risk of colorectal (1.16, 0.90 to 1.48), lung (1.17, 0.88 to 1.54), breast (0.97, 0.82 to 1.14), or prostate (0.86, 0.68 to 1.09) cancers. There was no clear evidence for an association between the categories of job strain and the risk of cancer.Conclusions These findings suggest that work related stress, measured and defined as job strain, at baseline is unlikely to be an important risk factor for colorectal, lung, breast, or prostate cancers.
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| 5. |
- Kivimäki, Mika, et al.
(författare)
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Associations of job strain and lifestyle risk factors with risk of coronary artery disease : a meta-analysis of individual participant data
- 2013
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Ingår i: CMJA. Canadian Medical Association Journal. Onlineutg. Med tittel. - : CMA Joule Inc.. - 0820-3946 .- 1488-2329. ; 185:9, s. 763-769
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Tidskriftsartikel (refereegranskat)abstract
- Background: It is unclear whether a healthy lifestyle mitigates the adverse effects of job strain on coronary artery disease. We examined the associations of job strain and lifestyle risk factors with the risk of coronary artery disease.Methods: We pooled individual-level data from 7 cohort studies comprising 102 128 men and women who were free of existing coronary artery disease at baseline (1985–2000). Questionnaires were used to measure job strain (yes v. no) and 4 lifestyle risk factors: current smoking, physical inactivity, heavy drinking and obesity. We grouped participants into 3 lifestyle categories: healthy (no lifestyle risk factors), moderately unhealthy (1 risk factor) and unhealthy (2–4 risk factors). The primary outcome was incident coronary artery disease (defined as first nonfatal myocardial infarction or cardiac-related death).Results: There were 1086 incident events in 743 948 person-years at risk during a mean follow-up of 7.3 years. The risk of coronary artery disease among people who had an unhealthy lifestyle compared with those who had a healthy lifestyle (hazard ratio [HR] 2.55, 95% confidence interval [CI] 2.18–2.98; population attributable risk 26.4%) was higher than the risk among participants who had job strain compared with those who had no job strain (HR 1.25, 95% CI 1.06–1.47; population attributable risk 3.8%). The 10-year incidence of coronary artery disease among participants with job strain and a healthy lifestyle (14.7 per 1000) was 53% lower than the incidence among those with job strain and an unhealthy lifestyle (31.2 per 1000).Interpretation: The risk of coronary artery disease was highest among participants who reported job strain and an unhealthy lifestyle; those with job strain and a healthy lifestyle had half the rate of disease. A healthy lifestyle may substantially reduce disease risk among people with job strain.
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| 6. |
- Kivimäki, Mika, et al.
(författare)
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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
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Ingår i: The Lancet Public Health. - : The Lancet Publishing Group. - 2468-2667. ; 2:6, s. e277-e285
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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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| 7. |
- Nyberg, Solja T., et al.
(författare)
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Association of Healthy Lifestyle With Years Lived Without Major Chronic Diseases
- 2020
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Ingår i: JAMA Internal Medicine. - : American Medical Association (AMA). - 2168-6106 .- 2168-6114. ; 180:5, s. 760-768
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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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| 8. |
- Theorell, Töres, et al.
(författare)
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Obesity and loss of disease-free years owing to major non-communicable diseases : a multicohort study
- 2018
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Ingår i: The Lancet Public Health. - : Elsevier Ltd. - 2468-2667. ; 3:10, s. e490-e497
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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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