Prevalence of Cardiovascular Health by Occupation: A Cross-Sectional Analysis Among U.S. Workers Aged ≥45 Years

MacDonald, Leslie A.; Bertke, Stephen; Hein, Misty J.; Judd, Suzanne E.; Baron, Sherry; Merritt, Robert; Howard, Virginia J.

doi:10.1016/j.amepre.2017.02.022

Cited by 26 publications

(36 citation statements)

References 45 publications

(43 reference statements)

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“…This concept has been used in a limited number of studies involving US working populations. These studies confirmed the relationship between occupation and cardiovascular health (MacDonald et al 2017;Shockey et al 2016). However, there are limited data on CVD risk factors in European working populations.…”

Section: Introductionsupporting

confidence: 58%

“…Shiftwork, passive smoking, and job strain, among others, are well documented in this respect (Kristensen 1989a, b;Nyberg 2013;Olsen and Kristensen 1991). Therefore, it is not surprising that the prevalence of CVD and cardiovascular risk factors differs between professions and economic sectors (Kelsall et al 2018;MacDonald et al 2017;Shockey et al 2016;Zimmermann Verdejo et al 2010). An economic sector includes a particular range of occupations, which may involve a higher risk for CVD or for some cardiovascular risk factors because of the associated working conditions or the socio-economic background of the workers which they attract.…”

Section: Introductionmentioning

confidence: 98%

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Prevalence of high cardiovascular risk by economic sector

Vandersmissen

Schouteden

Verbeek

et al. 2019

Int Arch Occup Environ Health

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Purpose The aim of this study was to assess the prevalence of high cardiovascular risk and the trend of cardiovascular risk factors in a large sample of Belgian workers. Methods A cross-sectional study was performed on the data of workers under medical surveillance by the non-profit occupational health service IDEWE in 2018. The prevalence of poor health for smoking, physical activity, body mass index (BMI), and blood pressure according to the American Heart Association (AHA) definition was investigated. The presence of three or more poor cardiovascular health metrics was considered high cardiovascular risk. A log-binomial regression model was used to compare the prevalence of high cardiovascular risk between economic sectors taking into account age and gender and to calculate predicted probabilities of high cardiovascular risk. Results Data about 212,792 workers were available. In 2018, overall, 7% of workers had high cardiovascular risk. Transport and construction had the highest prevalence of high cardiovascular risk, 14% and 12%, respectively. The lowest prevalence, 3%, was observed in education. Differences between sectors remained statistically significant after adjustment for age and gender. In men, workers in transport and storage and in construction had the highest predicted probability of high cardiovascular risk that increased with age. In women, highest predicted probability was observed in transport and storage. Conclusions When implementing health promotion initiatives, priority should be given to sectors and professions where risk factors are most prevalent or are increasing rapidly. Measures should be tailored to the special needs of the occupational groups at high risk.

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Section: Introductionsupporting

confidence: 58%

Section: Introductionmentioning

confidence: 98%

Prevalence of high cardiovascular risk by economic sector

Vandersmissen

Schouteden

Verbeek

et al. 2019

Int Arch Occup Environ Health

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“…It is also possible that a dietary difference exists between this study’s cohort and an urban population and this could affect metabolic parameters. However, the American and European heart associations do not accept rural residence as a conventional cardiovascular risk factor 55 , 56 . Although this cross-sectional study did demonstrate a significant association between diabetes and posterosuperior rotator cuff tears and between hypo-HDLemia and posterosuperior rotator cuff tears, we could not evaluate the cumulative effects of serum lipid abnormalities on posterosuperior rotator cuff tears and any association between the duration or severity of diabetes and posterosuperior rotator cuff tears.…”

Section: Discussionmentioning

confidence: 99%

Factors Associated with Atraumatic Posterosuperior Rotator Cuff Tears

Park

Gwark

et al. 2018

The Journal of Bone and Joint Surgery

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Background:Certain metabolic factors have been proposed as risk factors for a posterosuperior rotator cuff tear. Although metabolic syndrome is of increasing concern in industrialized societies, little information exists regarding its association with posterosuperior rotator cuff tears. The purpose of this study was to determine the risk factors for an atraumatic posterosuperior rotator cuff tear, including metabolic factors and metabolic syndrome.Methods:This study involved 634 subjects (634 shoulders) drawn from a cohort of rural residents. Posterosuperior rotator cuff tear diagnoses were based on magnetic resonance imaging (MRI) findings. Logistic regression analysis was used to determine the odds ratios (ORs) and 95% confidence intervals (CIs) for various demographic, physical, and social factors, including age, sex, dominant-side involvement, body mass index (BMI), and participation in manual labor; the comorbidities of diabetes, hypertension, dyslipidemia, thyroid dysfunction, ipsilateral carpal tunnel syndrome, and metabolic syndrome; and the serum metabolic parameters of serum lipid profile, glycosylated hemoglobin A1c, and level of thyroid hormone. Two multivariable analyses were performed: the first excluded metabolic syndrome while including diabetes, hypertension, BMI, and hypo-high-density lipoproteinemia (hypo-HDLemia), and the second included metabolic syndrome while excluding the formerly included variables.Results:Age, BMI, waist circumference, dominant-side involvement, manual labor, diabetes, hypertension, metabolic syndrome, ipsilateral carpel tunnel syndrome, HDL (high-density lipoprotein), and hypo-HDLemia were significantly associated with posterosuperior rotator cuff tears in univariate analyses (p ≤ 0.035). In the first multivariable analysis, age (OR. 1.86 [95% CI, 1.47 to 2.35]), BMI (OR, 1.09 [95% CI, 1.02 to 1.18]), dominant-side involvement (OR, 2.04 [95% CI, 1.38 to 3.01]), manual labor (OR, 9.48 [95% CI, 5.13 to 17.51]), diabetes (OR, 3.38 [95% CI, 1.98 to 5.77]), and hypo-HDLemia (OR, 2.07 [95% CI, 1.30 to 3.29]) were significantly associated with posterosuperior rotator cuff tears (p ≤ 0.019). In the second multivariable analysis, age (OR, 1.85 [95% CI, 1.48 to 2.31]), dominant-side involvement (OR, 1.83 [95% CI, 1.26 to 2.67]), manual labor (OR, 7.71 [95% CI, 4.33 to 13.73]), and metabolic syndrome (OR, 1.98 [95% CI, 1.35 to 2.91]) were significantly associated with posterosuperior rotator cuff tears (p ≤ 0.002).Conclusions:The metabolic factors of diabetes, BMI, hypo-HDLemia, and metabolic syndrome were significant independent factors associated with the development of posterosuperior rotator cuff tears.Level of Evidence:Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

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“…In a previous study on 6,282 employed Americans, prevalence of optimal composite clinical and behavioural cardiovascular health scores were in general low, with large variation between major occupational groups. Sales and low status o ce workers had a low prevalence of optimal total cardiovascular health score, and especially computer and healthcare support workers had a low prevalence of optimal behavioural health (32). Accumulation of multiple healthy or unhealthy lifestyle indicators is shown to strongly associate with multi-morbidity, disability-adjusted life-years gained and years lived without a chronic disease (33)(34)(35).…”

Section: Clustering Of Risk Indicators In Occupational Groupsmentioning

confidence: 99%

Lifestyle-associated health risk indicators across a wide range of occupational groups: a cross-sectional analysis in 72 855 workers

Väisänen

Kallings

Andersson

et al. 2020

Preprint

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ObjectivesIdentify and compare health risk indicators for common chronic diseases between different occupational groups. Methods A total of 72,855 participants (41% women) participating in an occupational health servicescreening in 2014–2019 were included. Occupation was defined by the Swedish Standard Classification of Occupation, and divided into nine major and additionally eight sub-major groups. These were analysed separately, as white- and blue-collar occupations and as low- and high-skilled occupations. Seven health risk indicators were self-reported: exercise, physical work situation, sitting at work and leisure, smoking, diet, and perceived health, whereas cardiorespiratory fitness, BMI and blood pressure were measured. These were further dichotomized (yes/no) and as clustering of risk indicators (≥3 vs. <3).ResultsThe greatest variation in OR across sub-major and major occupational groups were seen for daily smoking (OR=0.68 to OR=5.12), physically demanding work (OR=0.55 to OR=45.74) and high sitting at work (OR=0.04 to OR=1.86). For clustering of health risk indicators, blue-collar workers had significantly higher clustering of health risks (OR: 1.80; 95% CI 1.71-1.90) compared to white-collar workers (reference). Compared to high-skilled white-collar workers, low-skilled white-collar workers had similar OR (2.00; 1.88-2.13) as high-skilled blue-collar workers (1.98; 1.86-2.12), with low-skilled blue-collar workers having the highest clustered risk (2.32; 2.17-2.48).ConclusionThere were large differences in health risk indicators across occupational groups, mainly between high-skilled white-collar occupations and the other occupations, with important variations also between major and sub-major occupational groups. Future health interventions should target the occupational groups identified with the highest risk for effective disease prevention.

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Prevalence of Cardiovascular Health by Occupation: A Cross-Sectional Analysis Among U.S. Workers Aged ≥45 Years

Cited by 26 publications

References 45 publications

Prevalence of high cardiovascular risk by economic sector

Prevalence of high cardiovascular risk by economic sector

Factors Associated with Atraumatic Posterosuperior Rotator Cuff Tears

Lifestyle-associated health risk indicators across a wide range of occupational groups: a cross-sectional analysis in 72 855 workers

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