Occupational inequality in health expectancy in Denmark

2019 ◽  
Vol 48 (3) ◽  
pp. 338-345 ◽  
Author(s):  
Henrik Brønnum-Hansen ◽  
Else Foverskov ◽  
Ingelise Andersen
Keyword(s):  
Life Expectancy ◽  
White Collar ◽  
Blue Collar ◽  
Health Expectancy ◽  
Pension Scheme ◽  
Activity Limitations ◽  
Occupational Groups ◽  
Men And Women ◽  
Pension Age

Background: The pension age in Denmark is adjusted in line with projected increasing life expectancy without taking health differentials between occupational groups into account. The purpose was to study occupational disparities in partial life expectancy and health expectancy between the ages of 50 and 75. Methods: Register data on occupation and mortality were combined with data from the Danish part of Survey of Health, Ageing and Retirement in Europe in 2010–2014 ( N=3179). Expected lifetime without and with activity limitations and without and with long-term illness was estimated by Sullivan’s method and comparisons made between four occupational groups. Results: We found clear differences between occupational groups. Expected lifetime without activity limitations between the ages of 50 and 75 was about 4.5 years longer for men and women in high skilled white-collar occupations than for men and women in low skilled blue-collar occupations. Men in high skilled blue-collar and low skilled white-collar occupations could expect 2.3 and 3.8 years shorter lifetimes without activity limitations, respectively, than men in high skilled white-collar occupations. For women in low skilled white-collar occupations, lifetime without activity limitations was 2.6 years shorter than for women in high skilled white-collar occupations. Due to few observations, no results were obtained for women in the high skilled blue-collar group. The social gradient was also significant when health was measured by years without long-term illness. Conclusions: The results support implementation of a flexible pension scheme to take into account the health differentials between occupational groups.

scholarly journals Perceived Stress among Different Occupational Groups and the Interaction with Sedentary Behaviour

2019 ◽  
Vol 16 (23) ◽  
pp. 4595 ◽  
Author(s):  
Dėdelė ◽  
Miškinytė ◽  
Andrušaitytė ◽  
Bartkutė
Keyword(s):  
Physical Activity ◽  
Sedentary Behaviour ◽  
Perceived Stress ◽  
White Collar ◽  
Individual Characteristics ◽  
Blue Collar ◽  
Full Time ◽  
Occupational Groups ◽  
Blue Collar Workers ◽  
The Impact

Sedentary lifestyle and low physical activity are associated with health issues, including both physical and mental health, non-communicable diseases, overweight, obesity and reduced quality of life. This study investigated differences in physical activity and other individual factors among different occupational groups, highlighting the impact of sedentary behaviour on perceived stress by occupation. Cross-sectional study included 571 full-time workers of Kaunas city, Lithuania. The outcome of this study was assessment of perceived stress. Time spent sedentary per day, occupation and other individual characteristics were self-reported using questionnaires. Two main occupational groups were analysed: white-collar and blue-collar workers. Multivariate logistic regression was used to assess the impact of sedentary behaviour on perceived stress among different occupational groups. The prevalence of high sedentary behaviour was 21.7 and 16.8 % among white-collar and blue-collar workers, respectively. Blue-collar workers had a higher risk of high perceived stress (OR 1.55, 95% CI 1.05–2.29) compared to white-collar workers; however, sedentary time did not have any impact on high perceived stress level. Meanwhile, white-collar male (OR 4.34, 95% CI 1.46–12.95) and white-collar female (OR 3.26, 95% CI 1.23–8.65) workers who spend more than three hours per day sedentary had a greater risk of high levels of perceived stress. These findings indicate sedentary behaviour effect on perceived stress among two occupational groups—white-collar and blue-collar workers—and other important factors associated with perceived stress.

Persistent social inequality in life expectancy and disability-free life expectancy: Outlook for a differential pension age in Denmark?

2016 ◽  
Vol 45 (4) ◽  
pp. 459-462 ◽  
Author(s):  
Henrik Brønnum-Hansen ◽  
Mette Lindholm Eriksen ◽  
Karen Andersen-Ranberg ◽  
Bernard Jeune
Keyword(s):  
Life Expectancy ◽  
Social Inequality ◽  
Educational Level ◽  
Average Life Expectancy ◽  
Men And Women ◽  
Level Of Education ◽  
Disability Free Life Expectancy ◽  
Low Levels ◽  
Pension Age ◽  
Old Men

Aims: The state old-age pension in Denmark increases to keep pace with the projected increase in average life expectancy (LE) without any regard to the social gap in LE and expected lifetime in good health. The purpose of this study was to compare changes in LE and disability-free life expectancy (DFLE) between groups of Danes with high, medium and low levels of education. Methods: Nationwide register data on education and mortality were combined with data from the Surveys of Health, Ageing and Retirement in Europe (SHARE) surveys in 2006–2007, 2010–2011 and 2013–2014 and the DFLE by educational level was estimated by Sullivan’s method for each of these three time points. Results: Between 2006–2007 and 2013–2014, LE among 65-year-old men and women with a low educational level increased by 1.3 and 1.0 years, respectively, and by 1.4 and 1.3 years for highly educated men and women. The gap in LE between people with high and low levels of education remained more than 2 years. In 2006–2007, 65-year-old men with a high level of education could expect 3.2 more years without disability than men of the same age with a low level of education. In 2013–2014, the difference was 2.9 years. For women, the results were 3.7 and 3.4 years, respectively. Conclusions: With the persistent social inequality in LE of more than 2 years and the continuous gap between high and low educational groups in DFLE of about 3 years, a differential pension age is recommended.

Is Age Becoming Irrelevant? An Exploratory Study of Perceived Age Norms

1987 ◽  
Vol 24 (4) ◽  
pp. 241-256 ◽  
Author(s):  
Harold Zepelin ◽  
Randy A. Sills ◽  
Michael W. Heath
Keyword(s):  
Exploratory Study ◽  
White Collar ◽  
The United States ◽  
Blue Collar ◽  
Men And Women ◽  
Age Norms ◽  
Role Transitions ◽  
Age Related ◽  
Perceived Age ◽  
Representative Samples

To check on impressionistic assertions that the United States is becoming an “age-irrelevant society,” a quota sample of white-collar and blue-collar men and women (ages eighteen to seventy; N = 462) was studied with a questionnaire that asked for designation of the most suitable ages for various role transitions and age-related attributes. The findings converged with pertinent recent reports from more representative samples. Comparisons with findings in the 1950s indicated loosening of the norms, but with continuing adherence to a prescriptive timetable and with persistent socio-economic differences. These results challenge the notion of age-irrelevance.

scholarly journals Psychosocial work demands and physical workload decrease with ageing in blue-collar and white-collar workers: a prospective study based on the SLOSH cohort

BMJ Open ◽  
2019 ◽  
Vol 9 (9) ◽  
pp. e030918 ◽  
Author(s):  
Torbjörn Åkerstedt ◽  
Andrea Discacciati ◽  
Henrike Häbel ◽  
Hugo Westerlund
Keyword(s):  
Working Life ◽  
White Collar ◽  
Self Report ◽  
Blue Collar ◽  
Physical Workload ◽  
Work Demands ◽  
Psychosocial Work ◽  
Occupational Groups ◽  
Gradual Improvement ◽  
Psychosocial Work Demands

ObjectivesPsychosocial work demands and physical workload are important causes of ill health. The dramatic demographic changes in society make it important to understand if such factors change with ageing, but this is presently not known. The purpose of the present study was to investigate whether psychosocial work demands and physical workload change across 8 years of ageing, whether occupational groups show different trajectories of change and if such trajectories are reflected in sleep or fatigue.MethodsA cohort of 5377 participants (mean age: 47.6±11.6 (SD) years, 43.2% males, 40.2% blue-collar workers) was measured through self-report in five biannual waves across 8 years. Mixed model regression analyses was used to investigate change across ageing.ResultsPsychosocial work demands decreased significantly across 8 years (Coeff: −0.016±0.001), with the strongest decrease in the high white-collar group (Coeff=−0.031±0.003) and the oldest group. Physical workload also decreased significantly (Coeff=−0.032±0.002), particularly in the blue-collar group (Coeff=−0.050±0.004) and in the oldest group. Fatigue decreased, and sleep problems increased with ageing, but with similar slopes in the occupational groups. All effect sizes were small, but extrapolation suggests substantial decreases across a working life career.ConclusionsThe decrease in psychosocial work demands and physical workload suggests that the burden of work becomes somewhat lighter over 8 years. The mechanism could be ‘pure’ ageing and/or increased experience or related factors. The gradual improvement in the work situation should be considered in the discussion of the place of older individuals in the labour market, and of a suitable age for retirement. The results also mean that prospective studies of work and health need to consider the improvement in working life with ageing.

Recent Reforms of the Russian Pension System: pro et contra

2003 ◽  
pp. 56-67
Author(s):  
O. Khmyz
Keyword(s):  
Life Expectancy ◽  
Pension System ◽  
General System ◽  
Population Ageing ◽  
Private Pension ◽  
Pension Scheme ◽  
Management Company

Recent reforms of the general pension regime have gone a long way to ensuring a fair, equitable and transparent pension scheme, available to all workers younger than 45 years old. An adjustable formula relates pensions to the duration and level of contributions, and life-expectancy. It introduces some welcome flexibility to the system, as benefits are automatically adjusted for the effects of population ageing. Today the workers must choose a state or a private pension fund's management company. However, it is not clear whether recent reforms will be sufficient to ensure the long-term actuarial and financil balance of the general system.

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

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Daniel Väisänen ◽  
Lena V. Kallings ◽  
Gunnar Andersson ◽  
Peter Wallin ◽  
Erik Hemmingsson ◽  
...  
Keyword(s):  
Health Risk ◽  
White Collar ◽  
Blue Collar ◽  
Risk Indicators ◽  
Physical Work ◽  
Future Health ◽  
Occupational Groups ◽  
Blue Collar Workers ◽  
Wide Range ◽  
White Collar Workers

Abstract Background Identify 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 service screening 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). Results The 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). Conclusion There 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.

scholarly journals O6C.2 Differences in cardiovascular risk factor profiles across occupational groups

2019 ◽  
Vol 76 (Suppl 1) ◽  
pp. A56.1-A56
Author(s):  
Lucy A Barnes ◽  
Marine Corbin ◽  
Hayley J Denison ◽  
Amanda Eng ◽  
Andrea ‘t Mannetje ◽  
...  
Keyword(s):  
Risk Factors ◽  
New Zealand ◽  
General Population ◽  
White Collar ◽  
Blue Collar ◽  
High Cholesterol ◽  
Cvd Risk Factors ◽  
Cvd Risk ◽  
Occupational Groups ◽  
White Collar Workers

BackgroundDifferences in cardiovascular disease (CVD) risk between occupations have been observed, but what specific risk factors underlie these patterns remains unclear. This study assessed how established CVD risk factors differ across occupational groups in New Zealand, and whether patterns differ by gender and ethnicity.MethodsTwo probability-based sample surveys of the general New Zealand adult population (2004–2006; n=3003) and of the indigenous peoples of New Zealand (M&_x0101;ori; 2009–2010; n=2107), for which occupational histories and lifestyle factors were collected, were linked with routinely collected health data. For males and females in each cohort, smoking, body mass index, diabetes, hypertension and high cholesterol were dichotomised and compared between occupational groups using age-adjusted logistic regression. In addition, two way tables and chi-squared tests were used to compare the distribution of risk factors between white and blue-collar workers.ResultsThe prevalence of ever smoking was greater in blue-collar compared to white-collar workers of both cohorts, i.e. general population male (56%; 47%), general population female (62%; 47%), M&_x0101;ori male (68%; 55%) and M&_x0101;ori female (84%; 64%). For diabetes and high cholesterol, differences were statistically significant only for general population females (11%; 6% and 26%; 16% respectively). Hypertension prevalence was higher in blue versus white-collar workers for general population females (36%; 29%), M&_x0101;ori males (43%; 36%) and M&_x0101;ori females (44%; 37%), but not for general population males (35%; 34%). Results by occupational group revealed the same patterns with some noteworthy exceptions. In both cohorts, clerks had an increased risk of hypertension, particularly among males. Male agricultural workers in the general population cohort had a reduced risk of hypertension, diabetes and high cholesterol, but this pattern was not observed for females or among M&_x0101;ori.ConclusionThis study showed differences in profiles of known CVD risk factors across occupations, with some notable ethnic and gender differences.

scholarly journals Identification of occupations susceptible to high exposure and risk associated with multiple toxicants in an observational study: National Health and Nutrition Examination Survey 1999-2014

2021 ◽  
Author(s):  
Vy Kim Nguyen ◽  
Justin Colacino ◽  
Chirag J Patel ◽  
Maureen Sartor ◽  
Olivier Jolliet
Keyword(s):  
White Collar ◽  
Chemical Exposure ◽  
Occupational Group ◽  
Blue Collar ◽  
Nutrition Examination Survey ◽  
Occupational Groups ◽  
Chemical Exposures ◽  
Blue Collar Workers ◽  
Health And Nutrition ◽  
Similar Chemical

Background: According to the World Health Organization, occupational exposures to hazardous chemicals are estimated to cause over 370,000 premature annual deaths. The risks due to multiple workplace chemical exposures, and those occupations most susceptible to the resulting health effects, remain poorly characterized. Objectives: The aim of this study is to identify occupations with elevated toxicant biomarker concentrations and increased health risk associated with toxicant exposures in a working US population from diverse categories of occupation. More specifically, we aim to 1) define differences in chemical exposures based on occupation description, 2) identify occupational groups with similar chemical exposure profiles, and 3) identify occupational groups with chemical biomarker levels exceeding acceptable health-based biomarker levels. Methods: For this observational study of 51,008 participants, we used data from the 1999-2014 National Health and Nutrition Examination Survey. We characterized differences in chemical exposures by occupational group for 129 chemicals by applying a series of generalized linear models with the outcome as biomarker concentrations and the main predictor as the occupational groups, adjusting for age, sex, race/ethnicity, poverty income ratio, study period, and biomarker of tobacco use. We identified groups of occupations with similar chemical exposure profiles via hierarchical clustering. For each occupational group, we calculated percentages of participants with chemical biomarker levels exceeding acceptable health-based guidelines. Results: Blue collar workers from "Construction", "Professional, Scientific, Technical Services", "Real Estate, Rental, Leasing", "Manufacturing", and "Wholesale Trade" have higher biomarker levels of toxic chemicals such as several heavy metals, acrylamide, glycideamide, and several volatile organic compounds compared to their white-collar counterparts. For these toxicants, 1-58% of blue-collar workers from these industries have toxicant concentrations exceeding acceptable levels. Discussion: Blue collar workers have toxicant levels higher relative to their white-collar counterparts, often exceeding acceptable levels associated with noncancer effects. Our findings identify multiple occupations to prioritize for targeted interventions and health policies to monitor and reduce high toxicant exposures.

scholarly journals Occupational Differences in Metabolic Syndrome Incidence Among Older Workers

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 52-52
Author(s):  
Katharina Runge ◽  
Sander K R van Zon ◽  
Ute Bültmann ◽  
Kène Henkens
Keyword(s):  
Metabolic Syndrome ◽  
Health Behaviors ◽  
Older Workers ◽  
White Collar ◽  
Occupational Group ◽  
Blue Collar ◽  
Occupational Groups ◽  
Blue Collar Workers ◽  
Physical Measurements ◽  
Occupational Differences

Abstract This study investigates whether the incidence of metabolic syndrome (MetS), and its components, differs by occupational group among older workers (45-65 years) and whether health behaviors (smoking, leisure-time physical activity, diet quality) can explain these differences. We analyzed data from older workers (N=23 051) from two comprehensive measurement waves of the Lifelines Cohort Study and Biobank. MetS components were determined by physical measurements, blood markers, medication use, and self-reports. Occupational group and health behaviors were assessed by questionnaires. The association between occupational groups and MetS incidence was examined using Cox regression analysis. Health behaviors were subsequently added to the model to examine whether they can explain differences in MetS incidence between occupational groups. Low skilled white-collar (HR: 1.25, 95% CI: 1.13, 1.39) and low skilled blue-collar (HR: 1.45, 95% CI: 1.25, 1.69) workers had a significantly higher MetS incidence risk during 3.65 years follow-up than high skilled white-collar workers. Health behaviors reduced the strength of the association between occupational group and MetS incidence most among low skilled blue-collar workers (i.e. 10.3% reduction) as unhealthy behaviors were more prevalent in this occupational group. Similar occupational differences were observed on MetS component level. To conclude, MetS incidence in older workers differs between occupational groups and health behaviors only explain a small part of these differences. Health promotion tailored to occupational groups may be beneficial specifically among older low skilled blue-collar workers. Research into other factors that contribute to occupational differences is needed, as well as studies spanning the entire working life course.

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