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Eero Lahelma, Pekka Martikainen, Ossi Rahkonen, Eva Roos, Peppiina Saastamoinen, Occupational class inequalities across key domains of health: Results from the Helsinki Health Study, European Journal of Public Health, Volume 15, Issue 5, October 2005, Pages 504–510, https://doi.org/10.1093/eurpub/cki022
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Abstract
Background: Studies comparing socioeconomic inequalities in health using several health indicators are scarce. Therefore, this study aims to compare the shape and magnitude of occupational class inequalities across key domains of health, i.e. the subjective, functional and medical domains. Additionally, we examine whether physical or mental workload will affect these inequalities, and whether these effects are specific to particular health indicators. Methods: Cross-sectional survey data from the Helsinki Health Study in 2000 and 2001 were used. Each year employees of the City of Helsinki, reaching 40, 45, 50, 55 and 60 years received a mailed questionnaire. 6243 employees responded (80% women, response rate 68%). The socioeconomic indicator was occupational social class. Nine health indicators were included: self-rated health, pain or ache, GHQ-12 mental well-being, limiting long-standing illness, SF-36 physical and mental health functioning, Rose angina symptoms, circulatory diseases and mental problems. Prevalence percentages, odds ratios and inequality indices from logistic regression analysis were calculated. Results: Occupational class inequalities were found for self-rated health, pain or ache, limiting long-standing illness, physical health functioning, angina symptoms, and circulatory diseases. Physical or mental workload did not account for these inequalities. Inequalities were non-existent or slightly reversed for GHQ-12 mental well-being, SF-36 mental health functioning and mental problems. Conclusion: Expected occupational class inequalities in health among both women and men were found for global and physical health but not for mental health. The observed inequalities could not be attributed to physical or mental workload.
There is compelling evidence to show that socioeconomic inequalities in health are widespread and persistent in western countries.1–5 Health inequalities are found among men and women,2,4,6 and various age groups.7,8 The shape of health inequalities typically follows a hierarchical gradient: the lower the status, the poorer the health. Similar gradients are found in general populations2,9 and among employed people.10–14 However, inequalities in health among the employed tend to be smaller than in general populations because of early exit from work due to health reasons.9,13,15
Previous studies have examined a broad range of different health indicators. According to a conventional classification, the concept of health contains three key domains: firstly, the subjective domain following the illness model; secondly, the functional domain following the sickness model; and, thirdly, the medical domain following the disease model.16,17 Health inequalities have been found for subjective indicators, such as self-rated health.2,4,18 However, for subjective mental health indicators the findings have been mixed.14,18–20 Clear inequalities have also been found for functional indicators capturing the consequences of ill-health, such as SF-36 functioning21,22 and work ability.23 Also, several biomedical indicators and diseases confirmed by a doctor have shown socioeconomic inequalities.10,11,24
However, only rarely have studies compared inequalities across several indicators from all three key domains of health. When several health indicators have been used, socioeconomic inequalities have been found for most indicators among the general population25 as well as employees.10,11 However, since we lack studies comparing inequalities across various health indicators, we are unable judge for which domain or indicator inequalities might be particularly large or small, or possibly non-existent.
A number of studies confirm that working conditions contribute to socioeconomic inequalities in health.26–29 Thus, working conditions can be expected to be potential causes of health inequalities among employees. However, evidence on the contribution of both physical and mental workload to inequalities across different health indicators is needed.
Scope and purpose of the study
This study examines occupational class inequalities in health among middle-aged women and men from the Helsinki Health Study, an occupational cohort specifically designed for the investigation of work- and non-work-related determinants of health inequalities.30 The focus is justified since the occupational class position of middle-aged employees is crystallized, and health inequalities among them are likely to be larger than among their younger or older counterparts.7
The main aim is to compare the shape and magnitude of occupational class inequalities across nine health indicators covering the subjective, functional and medical domains. We expect to find linear inequalities across the studied health indicators. Additionally, we examine the bearing of physical and mental workload on these inequalities. More specifically we seek to answer the following research questions:
Can health inequalities by occupational class be found for all studied health indicators?
Does the magnitude of occupational class inequalities in health vary by indicator and domain of health?
Do health inequalities follow the expected hierarchical gradient? Can any deviations be observed?
Can occupational class inequalities in health be attributed to heavy physical and mental workload? Are these effects specific to certain health outcomes?
Data and methods
The Helsinki Health Study
This study is part of an ongoing Helsinki Health Study on women and men employed by the City of Helsinki, the capital of Finland. The City of Helsinki is the local government of the capital and the largest employer in the country (40 000 employees, 70% women). In 2000, the mean age of the staff was 44 years. Two-thirds had been employed by the City of Helsinki for at least 10 years and two-thirds were permanently employed.31 Seven per cent of men and 13% of women were employed part-time.32 These figures reflect a special feature of the Finnish labour market where both men and women are typically employed full-time. The main branches within the City of Helsinki include general local administration, health care, social welfare, education and culture, public transport, as well as technical and construction services. All employees are employed by the City of Helsinki and share the same central administration, personnel policies and registration, as well as occupational health care. The employees live within the Helsinki metropolitan area, and are not representative of the population or the labour force in general. Nevertheless, the overall level of health and its sociodemographic patterning corresponds to that among the Finnish population, with health being somewhat better among the studied employees due to the ‘healthy worker effect’.32
This sub-study uses data from the baseline surveys of the Helsinki Health Study from 2000 and 2001. Each spring those reaching 40, 45, 50, 55 and 60 years were mailed a questionnaire. The response rate for both years was 68%. Data from the two years were pooled to amount to a total of 6243 participants (80% women).
Occupational class classification
Information on occupational class was derived from the personnel register data of the City of Helsinki, linked to the questionnaire data for those who gave written permission for linkage (77%). For the rest, occupational data were completed from the questionnaires. For non-manual occupations, the City of Helsinki socioeconomic classification was followed, and the manual class was based on the Statistics Finland33 socioeconomic classification:
Managers have subordinates and do managerial/administrative work. They typically have a university degree.
Professionals, including other upper white collar employees, such as teachers and doctors, also have a university degree, but do professional work and typically do not have subordinates.
Semi-professionals include nurses, foremen and technicians, and other intermediate level white-collar employees.
Routine non-manual employees include non-professional clerical employees and other lower white-collar employees within the social and health services, such as child minders and assistant maids.
Manual workers work in transport and other technical occupations as well as in cleaning and canteens.
There were more men (16%) than women (8%) among the managers. Both the professional class and the semi-professional class accounted for between 17% and 26%, and these classes were relatively equal among men and women. However, the routine non-manual class was the largest one among women (43%), but only accounted for 11% of men. The manual class was the largest class among men (28%), but only accounted for 11% of women.
Physical and mental workload
Physical workload was measured by a question on how heavy the respondent considered his/her work (ranging from ‘very light’ to ‘very heavy’). Responding ‘fairly heavy’ or ‘very heavy’ was classified as high physical workload (among women 41% and men 16%). Mental workload was measured by a corresponding question. Responding ‘very heavy’ or ‘fairly heavy’ was classified as high mental workload (among women 75% and men 76%).
Health indicators
We use population survey data, and therefore all our nine health indicators are based on self-reported data. Three key domains of health are covered, i.e. the subjective, functional and medical domains.16,17
Subjective health indicators
These indicators reflect the illness concept and are subjective since they are purely based on the respondents' own assessments:
Self-rated health was obtained by asking the respondents to assess whether their health in general was ‘excellent’, ‘very good’, ‘good’, ‘fair’ or ‘poor’. We analyse self-rated health as below good, i.e. combining categories ‘fair’ and ‘poor’. This indicator is a broad measure of health related well-being and ill-health,34 shows good reliability35 and predicts subsequent mortality.36,37
Pain or ache was based on a general question asking whether the respondent suffered from any current pain or ache. This is an indicator of health-related quality of life and predicts functional ability.38
Mental well-being was measured by the General Health Questionnaire (GHQ-12). Based on 12 symptoms on subjective mental health, such as depression, anxiety and self confidence, the GHQ-12 primarily indicates recent general mental well-being. In accordance with validation studies the cut-off point of three or more symptoms was used to indicate low mental well-being.39–41 The Cronbach alpha reliability coefficient was 0.91.
Functional health indicators
These indicators reflect the sickness concept and limitations of functioning in everyday life due to poor health:
Limiting long-standing illness was obtained by asking ‘Do you have any long-standing illness, disability or infirmity?’ If the response was ‘Yes’, a follow-up question asked ‘Does your illness/disability restrict your work or does it limit your daily activities (gainful employment, housework, schooling, studying)?’ A positive response implied limiting long-standing illness. This indicator measures consequences of ill-health and disease for everyday life.16,42
Physical health functioning was obtained from the physical component summary of the Short Form-36 (SF-36) questionnaire. Lower scores imply poorer functioning and a mean score of 50 is observed in the USA general population.43 The lowest quartile for each gender was classified as low physical functioning. A Finnish translation of the SF-36 was used.44
Mental health functioning was measured by the SF-36 mental component summary in a similar way to the physical component summary.
Medical health indicators
These indicators reflect the disease concept based on the medical model of health:
Rose angina symptoms were obtained from the Rose Questionnaire.45 The guidelines for the questionnaire were followed: those reporting pain with exertion which causes the person to stop or slow down and goes away in 10 min, and is located in the sternum, left chest and left arm, had symptoms of angina.
Circulatory diseases were obtained from a checklist of major medical conditions. Those reporting ever having been diagnosed with angina pectoris, myocardial infarction, cerebrovascular disorder or intermittent claudication were classified with a medically confirmed circulatory disease.
Mental problems were obtained from the same checklist. Those reporting ever having been diagnosed with depression, anxiety or any other mental disorder were classified with a medically confirmed mental problem.
Statistical analyses
Crude prevalence data are first given. Age adjusted odds ratios (OR) from logistic regression analyses were calculated to be able to compare the shape of the occupational class inequalities across the health indicators. Inequality indices and their 95% confidence intervals (CI) were estimated for each health indicator. These indices were obtained from logistic regression analysis by fitting occupational social class as a continuous variable. The inequality index is a total effect measure since it takes into account both the strength of the differences in ill-health between the classes and the distribution of the study population across these classes.46 The index has an intuitive interpretation as the average change in ill-health (in terms of the OR) for each step down the occupational class hierarchy. Age-adjusted inequality indices were estimated to be able to compare the magnitude of inequalities for all health indicators, and used in subsequent analyses where high physical and mental workload were adjusted for. The index also gives a stable estimate of health inequalities because data for all five occupational classes are used. The index imposes linearity on the association between occupational class and health, but departures from linearity can be assessed from table 2.
Results
Prevalence of ill-health
Among the subjective health indicators, the crude prevalence was highest for pain or ache (table 1), with women reporting 45% and men 37%. The prevalence of low GHQ-12 mental well-being and perceived health as below good varied from 24% to 29%, with negligible gender differences. Among the functional indicators the prevalence of limiting long-standing illness was also equal between women and men, i.e. 17/18%. Among the medical indicators, reporting symptoms of angina as well as ever having been diagnosed with a circulatory disease was <10% (table 1). Having ever been diagnosed with a mental problem was somewhat more common among women than men (18% and 13%, respectively).
. | Women . | Men . | ||
---|---|---|---|---|
. | (n = 4991) . | (n = 1252) . | ||
. | % . | % . | ||
Subjective health indicators | ||||
Self-rated health as below good | 27 | 29 | ||
GHQ-12 mental well-being | 26 | 24 | ||
Pain or ache | 45 | 37 | ||
Functional health indicators | ||||
Limiting long-standing illness | 18 | 17 | ||
SF-36 limited physical functioning | 25 | 25 | ||
SF-36 limited mental functioning | 25 | 25 | ||
Medical health indicators | ||||
Rose angina symptoms | 6 | 4 | ||
Medically confirmed circulatory diseases | 7 | 9 | ||
Medically confirmed mental problems | 18 | 13 |
. | Women . | Men . | ||
---|---|---|---|---|
. | (n = 4991) . | (n = 1252) . | ||
. | % . | % . | ||
Subjective health indicators | ||||
Self-rated health as below good | 27 | 29 | ||
GHQ-12 mental well-being | 26 | 24 | ||
Pain or ache | 45 | 37 | ||
Functional health indicators | ||||
Limiting long-standing illness | 18 | 17 | ||
SF-36 limited physical functioning | 25 | 25 | ||
SF-36 limited mental functioning | 25 | 25 | ||
Medical health indicators | ||||
Rose angina symptoms | 6 | 4 | ||
Medically confirmed circulatory diseases | 7 | 9 | ||
Medically confirmed mental problems | 18 | 13 |
. | Women . | Men . | ||
---|---|---|---|---|
. | (n = 4991) . | (n = 1252) . | ||
. | % . | % . | ||
Subjective health indicators | ||||
Self-rated health as below good | 27 | 29 | ||
GHQ-12 mental well-being | 26 | 24 | ||
Pain or ache | 45 | 37 | ||
Functional health indicators | ||||
Limiting long-standing illness | 18 | 17 | ||
SF-36 limited physical functioning | 25 | 25 | ||
SF-36 limited mental functioning | 25 | 25 | ||
Medical health indicators | ||||
Rose angina symptoms | 6 | 4 | ||
Medically confirmed circulatory diseases | 7 | 9 | ||
Medically confirmed mental problems | 18 | 13 |
. | Women . | Men . | ||
---|---|---|---|---|
. | (n = 4991) . | (n = 1252) . | ||
. | % . | % . | ||
Subjective health indicators | ||||
Self-rated health as below good | 27 | 29 | ||
GHQ-12 mental well-being | 26 | 24 | ||
Pain or ache | 45 | 37 | ||
Functional health indicators | ||||
Limiting long-standing illness | 18 | 17 | ||
SF-36 limited physical functioning | 25 | 25 | ||
SF-36 limited mental functioning | 25 | 25 | ||
Medical health indicators | ||||
Rose angina symptoms | 6 | 4 | ||
Medically confirmed circulatory diseases | 7 | 9 | ||
Medically confirmed mental problems | 18 | 13 |
Health inequalities
Occupational class inequalities in health were examined by age-adjusted OR (table 2). Of the subjective indicators among women, self-rated health showed a large and almost linear gradient between the occupational classes. However, managers' health was at a similar level with professionals. Inequalities for pain or ache were modest, whereas GHQ-12 mental well-being showed no inequalities. Self-rated health showed a slightly steeper gradient among men than women. Among men pain or ache showed clear inequalities, but GHQ-12 showed no inequalities.
. | Managers (n = 578) . | Professionals (n = 1323) . | . | Semi-professionals (n = 1075) . | . | Routine non-manual employees (n = 2246) . | . | Manual workers (n = 881) . | . | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
. | OR . | OR . | CI . | OR . | CI . | OR . | CI . | OR . | CI . | |||||||||
Women | ||||||||||||||||||
Subjective health indicators | ||||||||||||||||||
Self-rated health | 1.00 | 0.95 | (0.71–1.28) | 1.09 | (0.81–1.48) | 1.52 | (1.17–1.99) | 2.14 | (1.57–2.91) | |||||||||
Pain or ache | 1.00 | 0.81 | (0.64–1.03) | 0.99 | (0.77–1.27) | 1.20 | (0.96–1.50) | 1.39 | (1.06–1.81) | |||||||||
GHQ-12 mental well-being | 1.00 | 1.30 | (0.86–1.48) | 1.09 | (0.82–1.44) | 0.91 | (0.71–1.17) | 0.93 | (0.69–1.27) | |||||||||
Functional health indicators | ||||||||||||||||||
Limiting long-standing illness | 1.00 | 0.76 | (0.55–1.05) | 1.02 | (0.73–1.41) | 1.24 | (0.93–1.65) | 1.31 | (0.93–1.84) | |||||||||
SF-36 physical functioning | 1.00 | 0.89 | (0.63–1.17) | 1.16 | (0.85–1.58) | 1.57 | (1.19–2.05) | 2.03 | (1.47–2.80) | |||||||||
SF-36 mental functioning | 1.00 | 1.29 | (0.98–1.70) | 1.08 | (0.81–1.44) | 0.85 | (0.66–1.10) | 0.85 | (0.62–1.15) | |||||||||
Medical health indicators | ||||||||||||||||||
Rose angina symptoms | 1.00 | 0.99 | (0.55–1.75) | 0.74 | (0.39–1.38) | 1.68 | (1.00–2.82) | 2.13 | (1.20–3.79) | |||||||||
Circulatory diseases | 1.00 | 0.68 | (0.41–1.15) | 0.58 | (0.33–1.01) | 1.37 | (0.87–2.15) | 1.92 | (1.16–3.17) | |||||||||
Mental problems | 1.00 | 1.34 | (0.98–1.83) | 1.25 | (0.90–1.72) | 1.07 | (0.80–1.44) | 0.83 | (0.58–1.20) | |||||||||
Men | ||||||||||||||||||
Subjective health indicators | ||||||||||||||||||
Self-rated health | 1.00 | 0.86 | (0.55–1.34) | 1.49 | (0.97–2.30) | 1.51 | (0.90–2.53) | 2.34 | (1.55–3.53) | |||||||||
Pain or ache | 1.00 | 1.46 | (0.98–2.20) | 1.78 | (1.17–2.69) | 1.62 | (0.99–2.64) | 2.54 | (1.71–3.77) | |||||||||
GHQ-12 mental well-being | 1.00 | 1.04 | (0.68–1.59) | 0.97 | (0.62–1.51) | 0.79 | (0.46–1.36) | 0.74 | (0.48–1.14) | |||||||||
Functional health indicators | ||||||||||||||||||
Limiting long-standing illness | 1.00 | 0.81 | (0.47–1.37) | 1.39 | (0.84–2.32) | 1.56 | (0.86–2.84) | 1.91 | (1.18–3.08) | |||||||||
SF-36 physical functioning | 1.00 | 1.26 | (0.79–2.02) | 1.80 | (1.13–2.88) | 1.67 | (0.94–2.94) | 2.61 | (1.67–4.08) | |||||||||
SF-36 mental functioning | 1.00 | 1.06 | (0.70–1.62) | 0.85 | (0.54–1.34) | 0.96 | (0.56–1.63) | 0.79 | (0.51–1.22) | |||||||||
Medical health indicators | ||||||||||||||||||
Rose angina symptoms | 1.00 | 0.83 | (0.29–2.35) | 1.77 | (0.72–4.37) | 1.24 | (0.36–4.31) | 1.81 | (0.73–4.47) | |||||||||
Circulatory diseases | 1.00 | 0.46 | (0.21–0.99) | 1.70 | (0.91–3.18) | 1.08 | (0.48–2.41) | 1.39 | (0.74–2.61) | |||||||||
Mental problems | 1.00 | 2.01 | (1.10–3.68) | 1.41 | (0.73–2.69) | 2.46 | (1.24–4.88) | 1.58 | (0.85–2.92) |
. | Managers (n = 578) . | Professionals (n = 1323) . | . | Semi-professionals (n = 1075) . | . | Routine non-manual employees (n = 2246) . | . | Manual workers (n = 881) . | . | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
. | OR . | OR . | CI . | OR . | CI . | OR . | CI . | OR . | CI . | |||||||||
Women | ||||||||||||||||||
Subjective health indicators | ||||||||||||||||||
Self-rated health | 1.00 | 0.95 | (0.71–1.28) | 1.09 | (0.81–1.48) | 1.52 | (1.17–1.99) | 2.14 | (1.57–2.91) | |||||||||
Pain or ache | 1.00 | 0.81 | (0.64–1.03) | 0.99 | (0.77–1.27) | 1.20 | (0.96–1.50) | 1.39 | (1.06–1.81) | |||||||||
GHQ-12 mental well-being | 1.00 | 1.30 | (0.86–1.48) | 1.09 | (0.82–1.44) | 0.91 | (0.71–1.17) | 0.93 | (0.69–1.27) | |||||||||
Functional health indicators | ||||||||||||||||||
Limiting long-standing illness | 1.00 | 0.76 | (0.55–1.05) | 1.02 | (0.73–1.41) | 1.24 | (0.93–1.65) | 1.31 | (0.93–1.84) | |||||||||
SF-36 physical functioning | 1.00 | 0.89 | (0.63–1.17) | 1.16 | (0.85–1.58) | 1.57 | (1.19–2.05) | 2.03 | (1.47–2.80) | |||||||||
SF-36 mental functioning | 1.00 | 1.29 | (0.98–1.70) | 1.08 | (0.81–1.44) | 0.85 | (0.66–1.10) | 0.85 | (0.62–1.15) | |||||||||
Medical health indicators | ||||||||||||||||||
Rose angina symptoms | 1.00 | 0.99 | (0.55–1.75) | 0.74 | (0.39–1.38) | 1.68 | (1.00–2.82) | 2.13 | (1.20–3.79) | |||||||||
Circulatory diseases | 1.00 | 0.68 | (0.41–1.15) | 0.58 | (0.33–1.01) | 1.37 | (0.87–2.15) | 1.92 | (1.16–3.17) | |||||||||
Mental problems | 1.00 | 1.34 | (0.98–1.83) | 1.25 | (0.90–1.72) | 1.07 | (0.80–1.44) | 0.83 | (0.58–1.20) | |||||||||
Men | ||||||||||||||||||
Subjective health indicators | ||||||||||||||||||
Self-rated health | 1.00 | 0.86 | (0.55–1.34) | 1.49 | (0.97–2.30) | 1.51 | (0.90–2.53) | 2.34 | (1.55–3.53) | |||||||||
Pain or ache | 1.00 | 1.46 | (0.98–2.20) | 1.78 | (1.17–2.69) | 1.62 | (0.99–2.64) | 2.54 | (1.71–3.77) | |||||||||
GHQ-12 mental well-being | 1.00 | 1.04 | (0.68–1.59) | 0.97 | (0.62–1.51) | 0.79 | (0.46–1.36) | 0.74 | (0.48–1.14) | |||||||||
Functional health indicators | ||||||||||||||||||
Limiting long-standing illness | 1.00 | 0.81 | (0.47–1.37) | 1.39 | (0.84–2.32) | 1.56 | (0.86–2.84) | 1.91 | (1.18–3.08) | |||||||||
SF-36 physical functioning | 1.00 | 1.26 | (0.79–2.02) | 1.80 | (1.13–2.88) | 1.67 | (0.94–2.94) | 2.61 | (1.67–4.08) | |||||||||
SF-36 mental functioning | 1.00 | 1.06 | (0.70–1.62) | 0.85 | (0.54–1.34) | 0.96 | (0.56–1.63) | 0.79 | (0.51–1.22) | |||||||||
Medical health indicators | ||||||||||||||||||
Rose angina symptoms | 1.00 | 0.83 | (0.29–2.35) | 1.77 | (0.72–4.37) | 1.24 | (0.36–4.31) | 1.81 | (0.73–4.47) | |||||||||
Circulatory diseases | 1.00 | 0.46 | (0.21–0.99) | 1.70 | (0.91–3.18) | 1.08 | (0.48–2.41) | 1.39 | (0.74–2.61) | |||||||||
Mental problems | 1.00 | 2.01 | (1.10–3.68) | 1.41 | (0.73–2.69) | 2.46 | (1.24–4.88) | 1.58 | (0.85–2.92) |
. | Managers (n = 578) . | Professionals (n = 1323) . | . | Semi-professionals (n = 1075) . | . | Routine non-manual employees (n = 2246) . | . | Manual workers (n = 881) . | . | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
. | OR . | OR . | CI . | OR . | CI . | OR . | CI . | OR . | CI . | |||||||||
Women | ||||||||||||||||||
Subjective health indicators | ||||||||||||||||||
Self-rated health | 1.00 | 0.95 | (0.71–1.28) | 1.09 | (0.81–1.48) | 1.52 | (1.17–1.99) | 2.14 | (1.57–2.91) | |||||||||
Pain or ache | 1.00 | 0.81 | (0.64–1.03) | 0.99 | (0.77–1.27) | 1.20 | (0.96–1.50) | 1.39 | (1.06–1.81) | |||||||||
GHQ-12 mental well-being | 1.00 | 1.30 | (0.86–1.48) | 1.09 | (0.82–1.44) | 0.91 | (0.71–1.17) | 0.93 | (0.69–1.27) | |||||||||
Functional health indicators | ||||||||||||||||||
Limiting long-standing illness | 1.00 | 0.76 | (0.55–1.05) | 1.02 | (0.73–1.41) | 1.24 | (0.93–1.65) | 1.31 | (0.93–1.84) | |||||||||
SF-36 physical functioning | 1.00 | 0.89 | (0.63–1.17) | 1.16 | (0.85–1.58) | 1.57 | (1.19–2.05) | 2.03 | (1.47–2.80) | |||||||||
SF-36 mental functioning | 1.00 | 1.29 | (0.98–1.70) | 1.08 | (0.81–1.44) | 0.85 | (0.66–1.10) | 0.85 | (0.62–1.15) | |||||||||
Medical health indicators | ||||||||||||||||||
Rose angina symptoms | 1.00 | 0.99 | (0.55–1.75) | 0.74 | (0.39–1.38) | 1.68 | (1.00–2.82) | 2.13 | (1.20–3.79) | |||||||||
Circulatory diseases | 1.00 | 0.68 | (0.41–1.15) | 0.58 | (0.33–1.01) | 1.37 | (0.87–2.15) | 1.92 | (1.16–3.17) | |||||||||
Mental problems | 1.00 | 1.34 | (0.98–1.83) | 1.25 | (0.90–1.72) | 1.07 | (0.80–1.44) | 0.83 | (0.58–1.20) | |||||||||
Men | ||||||||||||||||||
Subjective health indicators | ||||||||||||||||||
Self-rated health | 1.00 | 0.86 | (0.55–1.34) | 1.49 | (0.97–2.30) | 1.51 | (0.90–2.53) | 2.34 | (1.55–3.53) | |||||||||
Pain or ache | 1.00 | 1.46 | (0.98–2.20) | 1.78 | (1.17–2.69) | 1.62 | (0.99–2.64) | 2.54 | (1.71–3.77) | |||||||||
GHQ-12 mental well-being | 1.00 | 1.04 | (0.68–1.59) | 0.97 | (0.62–1.51) | 0.79 | (0.46–1.36) | 0.74 | (0.48–1.14) | |||||||||
Functional health indicators | ||||||||||||||||||
Limiting long-standing illness | 1.00 | 0.81 | (0.47–1.37) | 1.39 | (0.84–2.32) | 1.56 | (0.86–2.84) | 1.91 | (1.18–3.08) | |||||||||
SF-36 physical functioning | 1.00 | 1.26 | (0.79–2.02) | 1.80 | (1.13–2.88) | 1.67 | (0.94–2.94) | 2.61 | (1.67–4.08) | |||||||||
SF-36 mental functioning | 1.00 | 1.06 | (0.70–1.62) | 0.85 | (0.54–1.34) | 0.96 | (0.56–1.63) | 0.79 | (0.51–1.22) | |||||||||
Medical health indicators | ||||||||||||||||||
Rose angina symptoms | 1.00 | 0.83 | (0.29–2.35) | 1.77 | (0.72–4.37) | 1.24 | (0.36–4.31) | 1.81 | (0.73–4.47) | |||||||||
Circulatory diseases | 1.00 | 0.46 | (0.21–0.99) | 1.70 | (0.91–3.18) | 1.08 | (0.48–2.41) | 1.39 | (0.74–2.61) | |||||||||
Mental problems | 1.00 | 2.01 | (1.10–3.68) | 1.41 | (0.73–2.69) | 2.46 | (1.24–4.88) | 1.58 | (0.85–2.92) |
. | Managers (n = 578) . | Professionals (n = 1323) . | . | Semi-professionals (n = 1075) . | . | Routine non-manual employees (n = 2246) . | . | Manual workers (n = 881) . | . | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
. | OR . | OR . | CI . | OR . | CI . | OR . | CI . | OR . | CI . | |||||||||
Women | ||||||||||||||||||
Subjective health indicators | ||||||||||||||||||
Self-rated health | 1.00 | 0.95 | (0.71–1.28) | 1.09 | (0.81–1.48) | 1.52 | (1.17–1.99) | 2.14 | (1.57–2.91) | |||||||||
Pain or ache | 1.00 | 0.81 | (0.64–1.03) | 0.99 | (0.77–1.27) | 1.20 | (0.96–1.50) | 1.39 | (1.06–1.81) | |||||||||
GHQ-12 mental well-being | 1.00 | 1.30 | (0.86–1.48) | 1.09 | (0.82–1.44) | 0.91 | (0.71–1.17) | 0.93 | (0.69–1.27) | |||||||||
Functional health indicators | ||||||||||||||||||
Limiting long-standing illness | 1.00 | 0.76 | (0.55–1.05) | 1.02 | (0.73–1.41) | 1.24 | (0.93–1.65) | 1.31 | (0.93–1.84) | |||||||||
SF-36 physical functioning | 1.00 | 0.89 | (0.63–1.17) | 1.16 | (0.85–1.58) | 1.57 | (1.19–2.05) | 2.03 | (1.47–2.80) | |||||||||
SF-36 mental functioning | 1.00 | 1.29 | (0.98–1.70) | 1.08 | (0.81–1.44) | 0.85 | (0.66–1.10) | 0.85 | (0.62–1.15) | |||||||||
Medical health indicators | ||||||||||||||||||
Rose angina symptoms | 1.00 | 0.99 | (0.55–1.75) | 0.74 | (0.39–1.38) | 1.68 | (1.00–2.82) | 2.13 | (1.20–3.79) | |||||||||
Circulatory diseases | 1.00 | 0.68 | (0.41–1.15) | 0.58 | (0.33–1.01) | 1.37 | (0.87–2.15) | 1.92 | (1.16–3.17) | |||||||||
Mental problems | 1.00 | 1.34 | (0.98–1.83) | 1.25 | (0.90–1.72) | 1.07 | (0.80–1.44) | 0.83 | (0.58–1.20) | |||||||||
Men | ||||||||||||||||||
Subjective health indicators | ||||||||||||||||||
Self-rated health | 1.00 | 0.86 | (0.55–1.34) | 1.49 | (0.97–2.30) | 1.51 | (0.90–2.53) | 2.34 | (1.55–3.53) | |||||||||
Pain or ache | 1.00 | 1.46 | (0.98–2.20) | 1.78 | (1.17–2.69) | 1.62 | (0.99–2.64) | 2.54 | (1.71–3.77) | |||||||||
GHQ-12 mental well-being | 1.00 | 1.04 | (0.68–1.59) | 0.97 | (0.62–1.51) | 0.79 | (0.46–1.36) | 0.74 | (0.48–1.14) | |||||||||
Functional health indicators | ||||||||||||||||||
Limiting long-standing illness | 1.00 | 0.81 | (0.47–1.37) | 1.39 | (0.84–2.32) | 1.56 | (0.86–2.84) | 1.91 | (1.18–3.08) | |||||||||
SF-36 physical functioning | 1.00 | 1.26 | (0.79–2.02) | 1.80 | (1.13–2.88) | 1.67 | (0.94–2.94) | 2.61 | (1.67–4.08) | |||||||||
SF-36 mental functioning | 1.00 | 1.06 | (0.70–1.62) | 0.85 | (0.54–1.34) | 0.96 | (0.56–1.63) | 0.79 | (0.51–1.22) | |||||||||
Medical health indicators | ||||||||||||||||||
Rose angina symptoms | 1.00 | 0.83 | (0.29–2.35) | 1.77 | (0.72–4.37) | 1.24 | (0.36–4.31) | 1.81 | (0.73–4.47) | |||||||||
Circulatory diseases | 1.00 | 0.46 | (0.21–0.99) | 1.70 | (0.91–3.18) | 1.08 | (0.48–2.41) | 1.39 | (0.74–2.61) | |||||||||
Mental problems | 1.00 | 2.01 | (1.10–3.68) | 1.41 | (0.73–2.69) | 2.46 | (1.24–4.88) | 1.58 | (0.85–2.92) |
Of the functional indicators among women, only SF-36 physical functioning showed similar inequalities as those for self-rated health (table 2). Among men, SF-36 physical functioning and limiting long-standing illness showed a clear gradient. For limiting long-standing illness among both genders and physical functioning among women there were slight but statistically non-significant suggestions of best health among professionals instead of managers. Of the medical indicators among women, the ORs for angina symptoms and circulatory diseases were highest in the two lowest occupational classes, but other differences were largely inconsistent. Among men there were no clear inequalities.
The magnitude of health inequalities
The magnitude of age-adjusted occupational class inequalities in health was examined by using inequality indices (table 3). Inequalities were largest among women for ever-diagnosed circulatory disease (1.33) and current angina symptoms (1.30). Inequalities were also found for SF-36 physical functioning and self-rated health. However, slightly reverse inequalities were found for GHQ-12 mental well-being, SF-36 mental functioning and diagnosed mental problems. Among men inequalities were largest for self-rated health (1.29) and SF-36 physical functioning (1.26). Among men the mental health indicators showed negligible inequalities.
. | Inequality indices (95% confidence intervals) . | . | . | . | ||||
---|---|---|---|---|---|---|---|---|
. | 1. Age adjusted . | 2. 1 + physical workload . | 3. 1 + mental workload . | 4. Fully adjusted . | ||||
Women | ||||||||
Subjective health indicators | ||||||||
Self-rated health | 1.25 (1.17–1.32) | 1.14 (1.07–1.22) | 1.31 (1.23–1.40) | 1.21 (1.13–1.30) | ||||
Pain or ache | 1.14 (1.09–1.20) | 1.05 (0.99–1.11) | 1.20 (1.14–1.26) | 1.10 (1.04–1.16) | ||||
GHQ-12 mental well-being | 0.94 (0.89–1.00) | 0.91 (0.86–0.97) | 1.02 (0.96–1.08) | 1.01 (0.94–1.07) | ||||
Functional health indicators | ||||||||
Limiting long-standing illness | 1.15 (1.08–1.23) | 1.06 (0.98–1.14) | 1.20 (1.12–1.28) | 1.10 (1.02–1.18) | ||||
SF-36 physical functioning | 1.27 (1.19–1.35) | 1.12 (1.04–1.19) | 1.34 (1.25–1.43) | 1.18 (1.09–1.26) | ||||
SF-36 mental functioning | 0.89 (0.84–0.94) | 0.88 (0.82–0.93) | 0.96 (0.91–1.02) | 0.97 (0.91–1.04) | ||||
Medical health indicators | ||||||||
Rose angina symptoms | 1.30 (1.16–1.45) | 1.26 (1.11–1.43) | 1.35 (1.20–1.52) | 1.33 (1.17–1.51) | ||||
Circulatory diseases | 1.33 (1.20–1.49) | 1.32 (1.18–1.49) | 1.33 (1.19–1.49) | 1.31 (1.16–1.49) | ||||
Mental problems | 0.93 (0.87–0.99) | 0.93 (0.87–1.00) | 0.97 (0.91–1.04) | 0.99 (0.92–1.06) | ||||
Men | ||||||||
Subjective health indicators | ||||||||
Self-rated health | 1.29 (1.18–1.41) | 1.25 (1.13–1.37) | 1.32 (1.20–1.44) | 1.28 (1.16–1.41) | ||||
Pain or ache | 1.22 (1.12–1.33) | 1.19 (1.09–1.30) | 1.27 (1.16–1.38) | 1.23 (1.13–1.35) | ||||
GHQ-12 mental well-being | 0.91 (0.83–1.00) | 0.87 (0.79–0.96) | 0.95 (0.86–1.05) | 0.91 (0.82–1.01) | ||||
Functional health indicators | ||||||||
Limiting long-standing illness | 1.23 (1.11–1.37) | 1.18 (1.05–1.32) | 1.28 (1.15–1.43) | 1.23 (1.10–1.38) | ||||
SF-36 physical functioning | 1.26 (1.14–1.39) | 1.17 (1.06–1.30) | 1.30 (1.18–1.44) | 1.22 (1.09–1.35) | ||||
SF-36 mental functioning | 0.93 (0.85–1.03) | 0.92 (0.83–1.02) | 0.98 (0.89–1.08) | 0.97 (0.87–1.07) | ||||
Medical health indicators | ||||||||
Rose angina symptoms | 1.19 (0.97–1.46) | 1.20 (0.97–1.48) | 1.19 (0.97–1.47) | 1.20 (0.97–1.49) | ||||
Circulatory diseases | 1.17 (1.02–1.35) | 1.16 (1.00–1.34) | 1.17 (1.02–1.35) | 1.16 (0.99–1.35) | ||||
Mental problems | 1.05 (0.93–1.18) | 0.99 (0.87–1.13) | 1.07 (0.95–1.20) | 1.01 (0.89–1.15) |
. | Inequality indices (95% confidence intervals) . | . | . | . | ||||
---|---|---|---|---|---|---|---|---|
. | 1. Age adjusted . | 2. 1 + physical workload . | 3. 1 + mental workload . | 4. Fully adjusted . | ||||
Women | ||||||||
Subjective health indicators | ||||||||
Self-rated health | 1.25 (1.17–1.32) | 1.14 (1.07–1.22) | 1.31 (1.23–1.40) | 1.21 (1.13–1.30) | ||||
Pain or ache | 1.14 (1.09–1.20) | 1.05 (0.99–1.11) | 1.20 (1.14–1.26) | 1.10 (1.04–1.16) | ||||
GHQ-12 mental well-being | 0.94 (0.89–1.00) | 0.91 (0.86–0.97) | 1.02 (0.96–1.08) | 1.01 (0.94–1.07) | ||||
Functional health indicators | ||||||||
Limiting long-standing illness | 1.15 (1.08–1.23) | 1.06 (0.98–1.14) | 1.20 (1.12–1.28) | 1.10 (1.02–1.18) | ||||
SF-36 physical functioning | 1.27 (1.19–1.35) | 1.12 (1.04–1.19) | 1.34 (1.25–1.43) | 1.18 (1.09–1.26) | ||||
SF-36 mental functioning | 0.89 (0.84–0.94) | 0.88 (0.82–0.93) | 0.96 (0.91–1.02) | 0.97 (0.91–1.04) | ||||
Medical health indicators | ||||||||
Rose angina symptoms | 1.30 (1.16–1.45) | 1.26 (1.11–1.43) | 1.35 (1.20–1.52) | 1.33 (1.17–1.51) | ||||
Circulatory diseases | 1.33 (1.20–1.49) | 1.32 (1.18–1.49) | 1.33 (1.19–1.49) | 1.31 (1.16–1.49) | ||||
Mental problems | 0.93 (0.87–0.99) | 0.93 (0.87–1.00) | 0.97 (0.91–1.04) | 0.99 (0.92–1.06) | ||||
Men | ||||||||
Subjective health indicators | ||||||||
Self-rated health | 1.29 (1.18–1.41) | 1.25 (1.13–1.37) | 1.32 (1.20–1.44) | 1.28 (1.16–1.41) | ||||
Pain or ache | 1.22 (1.12–1.33) | 1.19 (1.09–1.30) | 1.27 (1.16–1.38) | 1.23 (1.13–1.35) | ||||
GHQ-12 mental well-being | 0.91 (0.83–1.00) | 0.87 (0.79–0.96) | 0.95 (0.86–1.05) | 0.91 (0.82–1.01) | ||||
Functional health indicators | ||||||||
Limiting long-standing illness | 1.23 (1.11–1.37) | 1.18 (1.05–1.32) | 1.28 (1.15–1.43) | 1.23 (1.10–1.38) | ||||
SF-36 physical functioning | 1.26 (1.14–1.39) | 1.17 (1.06–1.30) | 1.30 (1.18–1.44) | 1.22 (1.09–1.35) | ||||
SF-36 mental functioning | 0.93 (0.85–1.03) | 0.92 (0.83–1.02) | 0.98 (0.89–1.08) | 0.97 (0.87–1.07) | ||||
Medical health indicators | ||||||||
Rose angina symptoms | 1.19 (0.97–1.46) | 1.20 (0.97–1.48) | 1.19 (0.97–1.47) | 1.20 (0.97–1.49) | ||||
Circulatory diseases | 1.17 (1.02–1.35) | 1.16 (1.00–1.34) | 1.17 (1.02–1.35) | 1.16 (0.99–1.35) | ||||
Mental problems | 1.05 (0.93–1.18) | 0.99 (0.87–1.13) | 1.07 (0.95–1.20) | 1.01 (0.89–1.15) |
. | Inequality indices (95% confidence intervals) . | . | . | . | ||||
---|---|---|---|---|---|---|---|---|
. | 1. Age adjusted . | 2. 1 + physical workload . | 3. 1 + mental workload . | 4. Fully adjusted . | ||||
Women | ||||||||
Subjective health indicators | ||||||||
Self-rated health | 1.25 (1.17–1.32) | 1.14 (1.07–1.22) | 1.31 (1.23–1.40) | 1.21 (1.13–1.30) | ||||
Pain or ache | 1.14 (1.09–1.20) | 1.05 (0.99–1.11) | 1.20 (1.14–1.26) | 1.10 (1.04–1.16) | ||||
GHQ-12 mental well-being | 0.94 (0.89–1.00) | 0.91 (0.86–0.97) | 1.02 (0.96–1.08) | 1.01 (0.94–1.07) | ||||
Functional health indicators | ||||||||
Limiting long-standing illness | 1.15 (1.08–1.23) | 1.06 (0.98–1.14) | 1.20 (1.12–1.28) | 1.10 (1.02–1.18) | ||||
SF-36 physical functioning | 1.27 (1.19–1.35) | 1.12 (1.04–1.19) | 1.34 (1.25–1.43) | 1.18 (1.09–1.26) | ||||
SF-36 mental functioning | 0.89 (0.84–0.94) | 0.88 (0.82–0.93) | 0.96 (0.91–1.02) | 0.97 (0.91–1.04) | ||||
Medical health indicators | ||||||||
Rose angina symptoms | 1.30 (1.16–1.45) | 1.26 (1.11–1.43) | 1.35 (1.20–1.52) | 1.33 (1.17–1.51) | ||||
Circulatory diseases | 1.33 (1.20–1.49) | 1.32 (1.18–1.49) | 1.33 (1.19–1.49) | 1.31 (1.16–1.49) | ||||
Mental problems | 0.93 (0.87–0.99) | 0.93 (0.87–1.00) | 0.97 (0.91–1.04) | 0.99 (0.92–1.06) | ||||
Men | ||||||||
Subjective health indicators | ||||||||
Self-rated health | 1.29 (1.18–1.41) | 1.25 (1.13–1.37) | 1.32 (1.20–1.44) | 1.28 (1.16–1.41) | ||||
Pain or ache | 1.22 (1.12–1.33) | 1.19 (1.09–1.30) | 1.27 (1.16–1.38) | 1.23 (1.13–1.35) | ||||
GHQ-12 mental well-being | 0.91 (0.83–1.00) | 0.87 (0.79–0.96) | 0.95 (0.86–1.05) | 0.91 (0.82–1.01) | ||||
Functional health indicators | ||||||||
Limiting long-standing illness | 1.23 (1.11–1.37) | 1.18 (1.05–1.32) | 1.28 (1.15–1.43) | 1.23 (1.10–1.38) | ||||
SF-36 physical functioning | 1.26 (1.14–1.39) | 1.17 (1.06–1.30) | 1.30 (1.18–1.44) | 1.22 (1.09–1.35) | ||||
SF-36 mental functioning | 0.93 (0.85–1.03) | 0.92 (0.83–1.02) | 0.98 (0.89–1.08) | 0.97 (0.87–1.07) | ||||
Medical health indicators | ||||||||
Rose angina symptoms | 1.19 (0.97–1.46) | 1.20 (0.97–1.48) | 1.19 (0.97–1.47) | 1.20 (0.97–1.49) | ||||
Circulatory diseases | 1.17 (1.02–1.35) | 1.16 (1.00–1.34) | 1.17 (1.02–1.35) | 1.16 (0.99–1.35) | ||||
Mental problems | 1.05 (0.93–1.18) | 0.99 (0.87–1.13) | 1.07 (0.95–1.20) | 1.01 (0.89–1.15) |
. | Inequality indices (95% confidence intervals) . | . | . | . | ||||
---|---|---|---|---|---|---|---|---|
. | 1. Age adjusted . | 2. 1 + physical workload . | 3. 1 + mental workload . | 4. Fully adjusted . | ||||
Women | ||||||||
Subjective health indicators | ||||||||
Self-rated health | 1.25 (1.17–1.32) | 1.14 (1.07–1.22) | 1.31 (1.23–1.40) | 1.21 (1.13–1.30) | ||||
Pain or ache | 1.14 (1.09–1.20) | 1.05 (0.99–1.11) | 1.20 (1.14–1.26) | 1.10 (1.04–1.16) | ||||
GHQ-12 mental well-being | 0.94 (0.89–1.00) | 0.91 (0.86–0.97) | 1.02 (0.96–1.08) | 1.01 (0.94–1.07) | ||||
Functional health indicators | ||||||||
Limiting long-standing illness | 1.15 (1.08–1.23) | 1.06 (0.98–1.14) | 1.20 (1.12–1.28) | 1.10 (1.02–1.18) | ||||
SF-36 physical functioning | 1.27 (1.19–1.35) | 1.12 (1.04–1.19) | 1.34 (1.25–1.43) | 1.18 (1.09–1.26) | ||||
SF-36 mental functioning | 0.89 (0.84–0.94) | 0.88 (0.82–0.93) | 0.96 (0.91–1.02) | 0.97 (0.91–1.04) | ||||
Medical health indicators | ||||||||
Rose angina symptoms | 1.30 (1.16–1.45) | 1.26 (1.11–1.43) | 1.35 (1.20–1.52) | 1.33 (1.17–1.51) | ||||
Circulatory diseases | 1.33 (1.20–1.49) | 1.32 (1.18–1.49) | 1.33 (1.19–1.49) | 1.31 (1.16–1.49) | ||||
Mental problems | 0.93 (0.87–0.99) | 0.93 (0.87–1.00) | 0.97 (0.91–1.04) | 0.99 (0.92–1.06) | ||||
Men | ||||||||
Subjective health indicators | ||||||||
Self-rated health | 1.29 (1.18–1.41) | 1.25 (1.13–1.37) | 1.32 (1.20–1.44) | 1.28 (1.16–1.41) | ||||
Pain or ache | 1.22 (1.12–1.33) | 1.19 (1.09–1.30) | 1.27 (1.16–1.38) | 1.23 (1.13–1.35) | ||||
GHQ-12 mental well-being | 0.91 (0.83–1.00) | 0.87 (0.79–0.96) | 0.95 (0.86–1.05) | 0.91 (0.82–1.01) | ||||
Functional health indicators | ||||||||
Limiting long-standing illness | 1.23 (1.11–1.37) | 1.18 (1.05–1.32) | 1.28 (1.15–1.43) | 1.23 (1.10–1.38) | ||||
SF-36 physical functioning | 1.26 (1.14–1.39) | 1.17 (1.06–1.30) | 1.30 (1.18–1.44) | 1.22 (1.09–1.35) | ||||
SF-36 mental functioning | 0.93 (0.85–1.03) | 0.92 (0.83–1.02) | 0.98 (0.89–1.08) | 0.97 (0.87–1.07) | ||||
Medical health indicators | ||||||||
Rose angina symptoms | 1.19 (0.97–1.46) | 1.20 (0.97–1.48) | 1.19 (0.97–1.47) | 1.20 (0.97–1.49) | ||||
Circulatory diseases | 1.17 (1.02–1.35) | 1.16 (1.00–1.34) | 1.17 (1.02–1.35) | 1.16 (0.99–1.35) | ||||
Mental problems | 1.05 (0.93–1.18) | 0.99 (0.87–1.13) | 1.07 (0.95–1.20) | 1.01 (0.89–1.15) |
Adjusting for high physical workload slightly reduced the inequalities for some health indicators, among both genders (table 3). The largest reduction was for women's physical functioning. Adjusting for high mental workload, in contrast, tended to slightly increase the inequalities for most indicators. Simultaneous adjustment for both high physical and mental workload had negligible effects on inequalities in health.
Discussion
Overview of results and discussion
Based on the vast amount of previous research, we examined occupational class inequalities across nine health indicators among employees. Four main results are summarized below.
Firstly, occupational class gradients were found for most, although not all, studied health indicators among both women and men. Rather than following the distinction between the subjective, functional and medical domains of health, the dividing line was that between mental health versus global and physical health. Poorer health was found in the lower classes for all global and physical health indicators, but inequalities were non-existent, or even slightly reversed, for all mental health indicators. Also, previous studies suggest that inequalities for mental health might contrast physical health. The picture, however, is mixed since some studies have found inequalities for mental health,25,47 while others have found weak, non-existent or reverse inequalities.10,11,18,19,21 As suggested, underreporting among lower classes might hide underlying inequalities in mental health,19 but over-reporting in higher classes is equally possible. Additionally, top occupational positions may be mentally particularly demanding for women. Health inequalities are also likely to vary by various socioeconomic indicators.48,49
Secondly, for global and physical indicators health was gradually poorer towards the lower classes. Among the uppermost white-collar employees a distinction was made between managers and professionals, but our results suggest that health differences between these classes are small. Some indicators suggested slightly better health among professionals than managers, but none of these differences reached statistical significance. However, similar slight departures from linearity have been observed in previous studies.10–12 If such departures factually exist they can nevertheless signal stresses and strains in managerial jobs, or selection into these jobs.
Thirdly, we assessed the magnitude of health inequalities by using inequality indices. These impose linearity and if deviations are found this may affect the inequality index values. The indices suggest some variation in the magnitude of inequalities across the studied nine health indicators. Among women, inequalities by the two cardiovascular indicators were largest. Among men, inequalities for self-rated health and SF-36 physical functioning were largest. However, the magnitude of health inequalities did not follow our distinction between the three key domains of health, but instead confirmed no class gradients for mental health. Additionally, our findings suggest that women did not have smaller health inequalities than men as found in some previous studies.6,50,51 If anything, women's health inequalities tended to be slightly larger.
Fourthly, the found inequalities for global and physical health could not be attributed to mental and physical working conditions. If the two key workload factors had any impact, they were contrasting: physical workload slightly narrowing but mental workload slightly widening the inequalities. The latter finding reflects higher mental workload among the top occupational positions. Previous studies have found that physical, mental and psychosocial working conditions contribute to inequalities in cardiovascular diseases,11 global health26,28,29 and work ability.23 The weak impacts of the two workload factors in our study may be partly due to the single-item indicators. Nevertheless, both physical and mental workload factors are strongly associated with health in these data (data not shown). The weakly contrasting impacts of the two workload factors may suggest complex interrelationships between socioeconomic status and various domains of workload and health. Caution is thus needed in simultaneous adjustment for mental and physical working conditions since this may hide potential mechanisms behind socioeconomic inequalities in health. At the same time, focusing on just one workload factor may provide a misleading assessment of the effects of working conditions on health inequalities.
Methodological considerations
We studied nine reliable and validated health indicators.22,39,43,45 However, all indicators were based on the respondents' self-reports and are subjective in this sense. Availability of clinical tests and medically confirmed diagnoses would further broaden the measurement of health. An advantage of our occupational classification is that it derives from reliable personnel register data, and that it distinguishes between four non-manual classes and manual workers. Further socioeconomic indicators, such as education or income, may produce partly different results.48,49 As our data included employees from one single employer, although large, generalizations on the work force or general population should be made with caution. Analysing employed people tends to underestimate health inequalities.9,13,15
The overall survey response rate was 68% (women 70%; men 64%). Non-response analyses showed that older men participated more often (76%) than their younger counterparts; female upper white-collar employees also participated slightly more often (73%); and long sickness absence spells contributed to the non-response (women 64%; men 62%).52 The possible bias due to non-response is likely to underestimate the found health inequalities.
Conclusion
Although health inequalities are widespread among employed and non-employed populations, inequalities are nevertheless unlikely to be universally similar. In our study the shape and magnitude of health inequalities depended on gender and the specific health indicator used. While inequalities could not be understood in terms of the conventional subjective, functional and medical domains of health, another kind of health divide emerged: occupational class inequalities were found for global and physical health but not for mental health.
The shape of health inequalities typically follows a hierarchical gradient. This was confirmed and the lower occupational classes reported gradually poorer health. However, a slight departure from the expected pattern was found since health among managers was not necessarily better than among professionals. To further confirm our findings, future studies should also include medically confirmed data. This would additionally allow analyses of inequalities by self-reported health, adjusting for medical conditions.
In summary, this study showed clear occupational class inequalities in health for several global and physical health indicators but not for any mental health indicator. The inequalities were broadly independent of physical and mental workload within this large municipal workplace. Further areas of working conditions, such as job demands and control,53 and effort–reward imbalance,54 should be included in future studies to assess whether these would affect the shape and magnitude of health inequalities across self-reported as well as medically confirmed health indicators.
This study examined occupational class inequalities across nine different health indicators.
A health divide emerged suggesting that inequalities exist for global and physical health, but not for mental health.
The found inequalities could not be attributed to mental or physical work load.
Reducing health inequalities should focus particularly on problems of physical health.
The Helsinki Health Study is supported by the Academy of Finland (#48118 and #53245), and the Finnish Work Environment Fund (#99090). P.M. is supported by the Academy of Finland (#70631 and #48600) and O.R. is supported by the Academy of Finland (#45664). We thank the City of Helsinki, all participating employees, and members of the Helsinki Health Study group.
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