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Sökning: hsv:(SAMHÄLLSVETENSKAP) > Mittuniversitetet > Högskolan i Skövde > Tidskriftsartikel > Singh Manoux Archana

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1.
  • Heikkilä, Katriina, et al. (författare)
  • Job Strain as a Risk Factor for Peripheral Artery Disease : A Multi-Cohort Study
  • 2020
  • Ingår i: Journal of the American Heart Association. - : Wiley-Blackwell. - 2047-9980 .- 2047-9980. ; 9:9
  • Tidskriftsartikel (refereegranskat)abstract
    • Background Job strain is implicated in many atherosclerotic diseases, but its role in peripheral artery disease (PAD) is unclear. We investigated the association of job strain with hospital records of PAD, using individual-level data from 11 prospective cohort studies from Finland, Sweden, Denmark, and the United Kingdom. Methods and Results Job strain (high demands and low control at work) was self-reported at baseline (1985-2008). PAD records were ascertained from national hospitalization data. We used Cox regression to examine the associations of job strain with PAD in each study, and combined the study-specific estimates in random effects meta-analyses. We used τ2, I2, and subgroup analyses to examine heterogeneity. Of the 139 132 participants with no previous hospitalization with PAD, 32 489 (23.4%) reported job strain at baseline. During 1 718 132 person-years at risk (mean follow-up 12.8 years), 667 individuals had a hospital record of PAD (3.88 per 10 000 person-years). Job strain was associated with a 1.41-fold (95% CI, 1.11-1.80) increased average risk of hospitalization with PAD. The study-specific estimates were moderately heterogeneous (τ2=0.0427, I2: 26.9%). Despite variation in their magnitude, the estimates were consistent in both sexes, across the socioeconomic hierarchy and by baseline smoking status. Additional adjustment for baseline diabetes mellitus did not change the direction or magnitude of the observed associations. Conclusions Job strain was associated with small but consistent increase in the risk of hospitalization with PAD, with the relative risks on par with those for coronary heart disease and ischemic stroke.
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2.
  • 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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3.
  • Virtanen, Marianna, et al. (författare)
  • Long working hours and change in body weight : analysis of individual-participant data from 19 cohort studies
  • 2020
  • Ingår i: International Journal of Obesity. - : Nature Publishing Group. - 0307-0565 .- 1476-5497. ; 44:6, s. 1368-1375
  • Tidskriftsartikel (refereegranskat)abstract
    • Objective: To examine the relation between long working hours and change in body mass index (BMI). Methods: We performed random effects meta-analyses using individual-participant data from 19 cohort studies from Europe, US and Australia (n = 122,078), with a mean of 4.4-year follow-up. Working hours were measured at baseline and categorised as part time (<35 h/week), standard weekly hours (35–40 h, reference), 41–48 h, 49–54 h and ≥55 h/week (long working hours). There were four outcomes at follow-up: (1) overweight/obesity (BMI ≥ 25 kg/m2) or (2) overweight (BMI 25–29.9 kg/m2) among participants without overweight/obesity at baseline; (3) obesity (BMI ≥ 30 kg/m2) among participants with overweight at baseline, and (4) weight loss among participants with obesity at baseline. Results: Of the 61,143 participants without overweight/obesity at baseline, 20.2% had overweight/obesity at follow-up. Compared with standard weekly working hours, the age-, sex- and socioeconomic status-adjusted relative risk (RR) of overweight/obesity was 0.95 (95% CI 0.90–1.00) for part-time work, 1.07 (1.02–1.12) for 41–48 weekly working hours, 1.09 (1.03–1.16) for 49–54 h and 1.17 (1.08–1.27) for long working hours (P for trend <0.0001). The findings were similar after multivariable adjustment and in subgroup analyses. Long working hours were associated with an excess risk of shift from normal weight to overweight rather than from overweight to obesity. Long working hours were not associated with weight loss among participants with obesity. Conclusions: This analysis of large individual-participant data suggests a small excess risk of overweight among the healthy-weight people who work long hours. 
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