Monitoring of alcohol and drugs under scrutiny: output and shortcomings.

A major focus of Dutch addiction policy is to improve the monitoring of substance use and addiction - which surveys and registrations are important for the monitoring of alcohol and drugs problems, and what information is generated or needs to be generated by these monitors? Three methods were used: an inventorisation of existing monitoring projects, a survey among experts in the field of alcohol and drugs to study the information needs, and a study on the output and shortcomings of the existing monitors. Sixty monitors and 13 'umbrella' monitors were found. Experts formulated the needs of 11 topics which were matched with the output of the monitors. Coverage of the nature and extent of use in general is good. Shortcomings apply to the use and accessibility of the monitors, as well as to their completeness, standardisation and content. Especially questions with respect to problem use, treatment demand/need of help and user careers cannot be answered sufficiently with the existing information.

Neighborhood socioeconomic status and all-cause mortality.

This study sought to determine the contribution of neighborhood socioeconomic status to all-cause mortality and to explore its correlates. As part of the longitudinal "Gezondheid en LevensOmstandigheden Bevolking en omstreken" (GLOBE) study in the Netherlands, 8,506 randomly selected men and women aged 15-74 years from 86 neighborhoods in the city of Eindhoven reported on their socioeconomic status in the 1991 baseline survey. During the 6-year follow-up, 487 persons died. Neighborhood socioeconomic status was derived from individual reports on socioeconomic status. Its effect on mortality was stringently controlled for four individual-level socioeconomic indicators. Persons living in a neighborhood with a high percentage of unemployed/disabled or poor persons had a higher mortality risk than did those living in a neighborhood with a low percentage of unemployed/disabled or poor persons. This was independent of individual socioeconomic characteristics, including individual unemployment/disability or reports of severe financial problems. Educational and occupational neighborhood indicators were similarly, but less strongly, related to mortality. The prevalence of poor housing conditions, social disintegration, and unhealthy psychologic profiles and behaviors was higher in neighborhoods with a low socioeconomic status. Contextual effects of socioeconomic status may thus be due to one or more of these specific circumstances. The findings indicate potential public health benefits of modifying socioeconomic characteristics of areas.

Socioeconomic differences in self-assessed health in a chronically ill population: the role of different health aspects.

We investigated the role that different health aspects play in the explanation of socioeconomic differences in self-assessed health. Socioeconomic differences in self-assessed health were investigated in relation to chronic disease, functional limitations, psychosomatic symptoms, and perceived discomfort/distress. In multiple logistic regression analyses, for three cutoff points of self-assessed health, significant socioeconomic differences in self-assessed health could be observed after adjusting for age and gender. After separate adjustment for each of the four health aspects, the analyses showed that for a health assessment as less-than-good and less-than-fair, psychosomatic symptoms were the most powerful explanatory factor. Perceived discomfort/distress proved to be the most powerful factor for a poor health assessment. We found that socioeconomic differences in self-assessed health could, to a large extent (72-80%), be explained through socioeconomic differences in the prevalence of the four types of health problems included in the study. For all cutoff points, objective health aspects accounted for a relatively small part of the socioeconomic variability in self-assessed health. More subjective aspects of health accounted for more of the variability.

Drinking patterns and health outcomes: occasional versus regular drinking.

AIMS: To compare the health of drinkers with different drinking patterns and particularly drinkers with comparable average intakes and different drinking frequency. SETTING: General population survey conduced in Eindhoven, the Netherlands (n = 18,973). MEASUREMENTS: Chronic conditions, perceived general health, and health complaints were the outcome measures. Drinking categories were constructed by taking into account the frequency and amount of alcohol consumption (up to six glasses per sitting). FINDINGS: Drinking 3-5 days per week/3-5 glasses per occasion and drinking 6-7 days/1-2 glasses were associated with lower likelihood for reporting health complaints and for perceiving one's health as less than good compared to those drinking 1-2 days/1-2 glasses (reference group). Drinking 1-2 days/6 glasses was associated with being more likely to report chronic conditions, compared to the reference group. Those drinking 1-2 days/6 glasses were significantly more likely to report > 3 health complaints than those drinking 6-7 days/1-2 glasses. Although no differences were observed for any of the other comparison groups, at high levels of consumption (18-35 units/week), occasional drinkers (3-5 days/6 glasses) seemed to have better health outcomes compared to their counterparts (6-7 days/3-5 glasses). CONCLUSION: In addition to average alcohol intake, drinking pattern is also related to health.

Employment grade differences in cause specific mortality. A 25 year follow up of civil servants from the first Whitehall study.

STUDY OBJECTIVE: To test the hypothesis that the association between socioeconomic status and mortality rates cuts across the major causes of death for middle aged and elderly men. DESIGN: 25 year follow up of mortality in relation to employment grade. SETTING: The first Whitehall study. PARTICIPANTS: 18,001 male civil servants aged 40-69 years who attended the initial screening between 1967 and 1970 and were followed up for at least 25 years. MAIN OUTCOME MEASURE: Specific causes of death. RESULTS: After more than 25 years of follow up of civil servants, aged 40-69 years at entry to the study, employment grade differences still exist in total mortality and for nearly all specific causes of death. Main risk factors (cholesterol, smoking, systolic blood pressure, glucose intolerance and diabetes) could only explain one third of this gradient. Comparing the older retired group with the younger pre-retirement group, the differentials in mortality remained but were less pronounced. The largest decline was seen for chronic bronchitis, gastrointestinal diseases and genitourinary diseases. CONCLUSIONS: Differentials in mortality persist at older ages for almost all causes of death.

The U-shaped curve: various health measures and alcohol drinking patterns.

OBJECTIVE: To determine whether the well-known U-shaped relationship between average alcohol intake and mortality also holds for other health measures and for aspects of drinking other than weekly average alcohol intake, such as frequency of heavy-drinking episodes. METHOD: This study was carried out within the framework of a general population survey conducted in Eindhoven, The Netherlands (N = 18,973). Apart from mortality, the following health measures were considered: self-assessed health (based on perceived general health and the Nottingham Health Profile questionnaire), a list of chronic conditions and a list of health complaints. Respondents were categorized as abstainers, light (1-14 units/week), moderate (15-28 units/week) and excessive drinkers (> or =29 units/week). Information on the frequency with which heavy-drinking episodes occurred was also available. RESULTS: Light or moderate drinkers had not only lower mortality but other health burdens were lower than for either abstainers or heavier drinkers. Frequent heavy-drinking episodes were observed to be directly related to increased mortality rates, although not significantly. A trend was observed for drinkers reporting seldom heavy-drinking episodes (once or twice in the previous 6 months) to report less health burdens and to have lower mortality rates than those reporting no heavy drinking episodes. CONCLUSIONS: A U-shaped pattern was observed for mortality as well as for several other health measures. Frequent heavy-drinking episodes were related to an increased likelihood of mortality (not significant but suggesting a J-shaped pattern) and were not related to other health measures.

Socioeconomic status and aortic atherosclerosis in Dutch elderly people: the Rotterdam Study.

An inverse association has been reported between socioeconomic status (SES) and cardiovascular morbidity and mortality. Studies on subclinical manifestations of atherosclerotic disease are limited and have not been carried out among elderly persons. The authors investigated the relation between SES and aortic atherosclerosis among elderly people. As part of the Rotterdam Study, data on SES and atherosclerosis were collected for 4,451 persons aged 55-94 years. Atherosclerosis was estimated by radiographic assessment of calcified deposits in the abdominal aorta. Aortic atherosclerosis was more common among women in the lower educational and occupational strata. The lowest educational group and the lowest occupational group had increased risks of aortic atherosclerosis compared with the highest groups (odds ratios were 1.3 (95% confidence interval (CI) 1.0-1.6) and 1.3 (95% CI 1.0-1.8), respectively). The odds ratios for severe atherosclerosis among women in the lowest socioeconomic stratum compared with those in the highest stratum were 1.6 (95% CI 1.0-2.7) for education, 2.8 (95% CI 1.1-7.5) for occupation, and 1.7 (95% CI 0.9-3.3) for income. After exclusion of persons with a history of cardiovascular disease, the same trends still emerged. No relations were observed among men. These findings show that SES is related to aortic atherosclerosis in women. This suggests that SES affects the incidence of cardiovascular disease before its clinical manifestation.

The influence of adult ill health on occupational class mobility and mobility out of and into employment in the The Netherlands.

In the debate about the explanation of socio-economic health inequalities one of the important issues is the relative importance of health selection. The aim of this study was to investigate to what extent occupational class mobility and mobility out of and into employment are health-related, and in addition, to estimate the contribution of health-related social mobility to socio-economic health differences in the working population. Data were taken from the Longitudinal Study on Socio-Economic Health Differences in the Netherlands, which started in 1991; follow-up data were collected in 1995. The analysis is based on 2533 persons aged 15-59 at baseline. The influence of health problems in 1991 (perceived general health, health complaints and chronic conditions) on changes in occupational class between 1991 and 1995 was negligible. Neither upward nor downward mobility was affected by health problems. However, health problems in 1991 were significantly associated with a higher risk of mobility out of employment and a lower risk of mobility into employment in 1995. For example, for mobility out of employment among persons that reported at least one chronic condition in 1991, the odds ratio was 1.46. Health-related mobility out of employment substantially influences the estimate of socio-economic health inequalities in the working population (measured by current occupation). For manual workers, as compared to non-manual workers, the odds ratio for a less-than-good perceived general health was underestimated by 34% in 1995. Selective mobility into employment overestimates socio-economic inequalities in health in the working population by 9%. Respondents that moved into and out of employment were healthier than those that remained economically inactive, but their health was worse than of those that remained employed (both manual and non-manual). Implications for health policy are that the prospects for people with health problems to stay in paid employment should be improved.

Explaining educational differences in mortality: the role of behavioral and material factors.

OBJECTIVES: This study examined the role of behavioral and material factors in explaining educational differences in all-cause mortality, taking into account the overlap between both types of factors. METHODS: Prospective data were used on 15,451 participants in a Dutch longitudinal study. Relative hazards of all-cause mortality by educational level were calculated before and after adjustment for behavioral factors (alcohol intake, smoking, body mass index, physical activity, dietary habits) and material factors (financial problems, neighborhood conditions, housing conditions, crowding, employment status, a proxy of income). RESULTS: Mortality was higher in lower educational groups. Four behavioral factors (alcohol, smoking, body mass index, physical activity) and 3 material factors (financial problems, employment status, income proxy) explained part of the educational differences in mortality. With the overlap between both types of factors accounted for, material factors were more important than behavioral factors in explaining mortality differences by educational level. CONCLUSIONS: The association between educational level and mortality can be largely explained by material factors. Thus, improving the material situation of people might substantially reduce educational differences in mortality.

Socioeconomic differences in stroke among Dutch elderly women: the Rotterdam Study.

BACKGROUND AND PURPOSE: We sought to assess the association between socioeconomic status and the risk of stroke among elderly women. Methods--The association between socioeconomic status and stroke emerged in cross-sectional and longitudinal data on 4274 female participants of the Rotterdam Study, a prospective, population-based, follow-up study in the Netherlands among older subjects. RESULTS: A history of stroke was more common among women in lower socioeconomic strata. The same trend was observed for the relationship between the lowest socioeconomic groups and the incidence of stroke. Risk factors for stroke were not related to socioeconomic status in a consistent manner. Smoking, history of cardiovascular diseases, and overweight were more common in lower socioeconomic groups. However, socioeconomic differences in hypertension, antihypertensive drug use, prevalence of atrial fibrillation, and prevalence of left ventricular hypertrophy were not observed. The complex of established risk factors could only partly explain the association between socioeconomic status and stroke. CONCLUSIONS: There is a strong association among elderly women between socioeconomic status and stroke. The association could only partly be explained by known risk factors. Our findings indicate that not only the actual risk profile but also risk factors earlier in life may be of importance.

Social class in childhood and general health in adulthood: questionnaire study of contribution of psychological attributes.

OBJECTIVE: To determine the contribution of psychological attributes (personality characteristics and coping styles) to the association between social class in childhood and adult health among men and women. DESIGN: Partly retrospective, partly cross sectional study conducted in the framework of the Dutch GLOBE study. SUBJECTS: Sample of general population from south east Netherlands consisting of 2174 men and women aged 25-74 years. Baseline self reported data from 1991 provided information on childhood and adult social class, psychological attributes, and general health. MAIN OUTCOME MEASURE: Self rated poor health. RESULTS: Independent of adult social class, low childhood social class was related to self rated poor health (odds ratio 1.67 (95% confidence interval 1.02 to 2.75) for subjects whose fathers were unskilled manual workers versus subjects whose fathers were higher grade professionals). Subjects whose fathers were manual workers generally had more unfavourable personality profiles and more negative coping styles. External locus of control, neuroticism, and the absence of active problem focused coping explained about half of the association between childhood social class and self rated poor health. The findings were independent of adult social class and height. CONCLUSIONS: A higher prevalence of negative personality profiles and adverse coping styles in subjects who grew up in lower social classes explains part of the association between social class in childhood and adult health. This finding underlines the importance of psychological mechanisms in the examination of the negative effects of adverse socioeconomic conditions in childhood.

Does childhood socioeconomic status influence adult health through behavioural factors?

BACKGROUND: The purpose of this study is to assess to what extent the effect of childhood socioeconomic status on adult health could be explained by a higher prevalence of unhealthy behaviour among those with lower childhood socioeconomic status. METHODS: Data were obtained from the baseline of a prospective cohort study in the Netherlands (13 854 respondents, aged between 25 and 74). Childhood socioeconomic group was indicated by occupation of the father, and adult health was indicated by perceived general health, health complaints and mortality. Adult socioeconomic status was measured by current occupation. Behavioural factors were smoking, alcohol consumption, Body Mass Index and physical activity. Relations were analysed using logistic regression models. RESULTS: A clear association between childhood socioeconomic circumstances and adult health was shown, as well as an association between childhood socioeconomic circumstances and health-related behaviour, even after adjustment for current socioeconomic status. Physical activity shows the strongest relation with childhood socioeconomic circumstances. Behavioural factors explain the relation between childhood socioeconomic status and adult health for approximately 10%. CONCLUSIONS: Childhood socioeconomic circumstances have an independent effect on adult health and health-related behaviour: the risk of health problems and health damaging behaviour is higher in lower childhood socioeconomic groups. The independent effect of childhood circumstances on adult health operates for a small part through unhealthy behaviour.

Role of childhood health in the explanation of socioeconomic inequalities in early adult health.

STUDY OBJECTIVE: To examine the contribution of childhood health to the explanation of socioeconomic inequalities in health in early adult life. DESIGN: Retrospective data were used, which were obtained from a postal survey in the baseline of a prospective cohort study (the Longitudinal Study on Socio-Economic Health Differences in the Netherlands). Adult socioeconomic status was indicated by educational level, while health was indicated by perceived general health. Childhood health was measured by self reported periods of severe disease in childhood. Relations were analysed using logistic regression models. The reduction in odds ratios of "less than good" perceived general health for different educational groups after adjustment for childhood health was used to estimate the contribution of childhood health. SETTING: The population of the city of Eindhoven and surroundings in the south east of the Netherlands in 1991. PARTICIPANTS: 2511 respondents, aged 25-34 years, men and women, of Dutch nationality, were included in the analysis. MAIN RESULTS: There was a clear association between childhood health and adult health, as well as an association between childhood health and adult socioeconomic status. Approximately 5% to 10% of the increased risk of the lower socioeconomic groups of having a "less than good" perceived general health can be explained by childhood health. CONCLUSIONS: Childhood health contributes to the explanation of socioeconomic inequalities in early adult health. Although this contribution is not very large, it cannot be ignored and has to be interpreted largely in terms of selection on health.

The importance of psychosocial stressors for socio-economic inequalities in perceived health.

The uneven distribution of psychosocial stressors as well as their differential health impact have been suggested as a possible explanation for socio-economic inequalities in health. We assessed the importance of both explanations, using data from the baseline of a Dutch longitudinal study. The outcome measure was the prevalence of perceived health problems. Educational level was used as an indicator of socio-economic status, whilst both life-events and long-term difficulties were included as stressors. We controlled for educational differences in neuroticism in order to eliminate any bias which might arise from the fact that people in lower educational groups are more inclined to report both stressors and health problems. The higher exposure to stressors was found to contribute to the increased risk of perceived health problems, even after differences in neuroticism were taken into account. Long-term difficulties, especially those related to material conditions, account for most of the effect. The impact of stress on health was hardly found to be moderated by educational level. The implications for future research are discussed.

A higher prevalence of health problems in low income groups: does it reflect relative deprivation?

STUDY OBJECTIVE: Although it has frequently been suggested that income affects health, there is hardly any research in which this issue has been explored directly. The aim of this study was, firstly, to examine whether income is independently associated with health, secondly, to assess the extent to which this association reflects high levels of deprivation in low income groups, and thirdly, to examine which specific components of deprivation contribute most to the link between income and health. Health indicators used were the prevalence of chronic conditions, health complaints and less than "good" perceived general health. SETTING: Region in the south east of the Netherlands. PARTICIPANTS: A population of 2567 men and women who participated in an oral interview, aged 15-74. DESIGN: Data were obtained from the baseline of a prospective cohort study aimed at the explanation of socioeconomic inequalities in health. RESULTS: Large inequalities in health by (equivalent) income after differences in other socioeconomic indicators had been controlled for were observed. For example, among those in the lowest income group the risk of bad perceived health was three times as high as among people in the highest income group. The prevalence of deprivation (basic, housing, social) increased with decreasing income to approximately 50-60% in the lowest income group. A substantial part of the increased health risks of the lowest income groups could statistically be accounted for by the higher prevalence of deprivation in these groups. The components that are likely to influence health indirectly, through a psychological or behavioural mechanism, accounted for most of the effect. CONCLUSIONS: These analyses provide evidence to suggest that a low income has detrimental health effects through relative deprivation. Moreover, the results indicate an indirect link between deprivation and health problems involving psychological or behavioural factors.

Socioeconomic inequalities in health in the working population: the contribution of working conditions.

BACKGROUND: The aim was to study the impact of different categories of working conditions on the association between occupational class and self-reported health in the working population. METHODS: Data were collected through a postal survey conducted in 1991 among inhabitants of 18 municipalities in the southeastern Netherlands. Data concerned 4521 working men and 2411 working women and included current occupational class (seven classes), working conditions (physical working conditions, job control, job demands, social support at work), perceived general health (very good or good versus less than good) and demographic confounders. Data were analysed with logistic regression techniques. RESULTS: For both men and women we observed a higher odds ratio for a less than good perceived general health in the lower occupational classes (adjusted for confounders). The odds of a less than good perceived general health was larger among people reporting more hazardous physical working conditions, lower job control, lower social support at work and among those in the highest category of job demands. Results were similar for men and women. Men and women in the lower occupational classes reported more hazardous physical working conditions and lower job control as compared to those in higher occupational classes. High job demands were more often reported in the higher occupational classes, while social support at work was not clearly related to occupational class. When physical working conditions and job control were added simultaneously to a model with occupational class and confounders, the odds ratios for occupational classes were reduced substantially. For men, the per cent change in the odds ratios for the occupational classes ranged between 35% and 83%, and for women between 35% and 46%. CONCLUSIONS: A substantial part of the association between occupational class and a less than good perceived general health in the working population could be attributed to a differential distribution of hazardous physical working conditions and a low job control across occupational classes. This suggests that interventions aimed at improving these working conditions might result in a reduction of socioeconomic inequalities in health in the working population.

Educational differences in leisure-time physical inactivity: a descriptive and explanatory study.

In this study we aim to explain educational differences in leisure-time physical inactivity in terms of psychosocial and material factors. Cross-sectional data were obtained from the baseline of the Dutch GLOBE study in 1991, including 2598 men and women, aged 15-74 years. Physical inactivity during leisure time was defined as not participating in any activity, such as sports, gardening, walking or cycling. Psychosocial factors included in the study were coping resources, personality, and stressors. Material factors were financial situation, employment status, and living conditions. Logistic regression models were used to calculate educational differences in physical inactivity. Physical inactivity was more prevalent in lower educational groups. Psychosocial factors related to physical inactivity were locus of control, parochialism, neuroticism, emotional social support, active problem focussing, optimistic and palliative coping styles. Material factors associated with physical inactivity were income, employment status and financial problems. All correlates of physical inactivity were unequally distributed over educational groups, except optimistic and palliative coping. Personality and coping style were the main contributors to the observed educational differences in physical inactivity. That is to say, parochialism, locus of control, neuroticism and active problem focussing explained about half of elevated odds ratios of physical inactivity in the lower educational groups. The material factors, equivalent income and employment status explained about 40% of the elevated odds ratios. Psychosocial and material correlates together reduced the odds ratios of lower educational groups by on average 75%. These results have practical consequences for the design of more effective interventions to promote physical activity. In particular, personality and coping style of risk groups, such as lower educational groups, should be taken into consideration at the future development of these interventions, as well as inequalities in material restrictions related to engaging in physical activity. Supplementary interventions focussing on childhood conditions which, partly, influence both personality and physical inactivity may also contribute to a reduction of socio-economic differences in physical inactivity.

Cultural, material, and psychosocial correlates of the socioeconomic gradient in smoking behavior among adults.

BACKGROUND: The aim was to identify the correlates of educational differences in smoking among adults. METHODS: We used data from the baseline of a Dutch longitudinal study, relating to a population of 2,462 respondents, ages 25-74. Logistic regression was used to assess the educational gradient in smoking. Current smokers were compared with former and never smokers, respectively. RESULTS: The risk of being a current smoker compared with being a former/never smoker was higher among lower educational groups. For example, the odds of being a current smoker compared with never smoker among persons in the lowest level was more than five times as high as that for persons in the highest level. A substantial part (20-40%) of the increased risk of being a smoker among lower groups appeared to be associated with adverse material conditions. The financial situation especially accounted for that effect. One of the cultural factors, i.e., locus of control, was found to account for approximately 30% of the educational gradient in the case in which smokers were compared with former smokers. Psychosocial factors, i.e., neuroticism and coping styles, accounted for less of the gradient in smoking than cultural and material factors. CONCLUSIONS: On the basis of the results, we hypothesize that both cultural and material factors contribute to the higher smoking rates among lower socioeconomic groups. Psychosocial factors seem to be less important. If our results are confirmed in more powerful studies, this would indicate, first, that possibilities for a reduction of smoking differences may be found in tailoring smoking cessation programs to the more externally oriented locus of control and the coping styles that are common among lower educational groups, and second, that a reduction of smoking differences may follow from an improvement of the material living conditions of lower socioeconomic groups.

The interrelationship between income, health and employment status.

BACKGROUND: The aim of the study was to test the hypothesis that the relatively strong association between income and health compared to that between education/occupation and health, can partly be interpreted in terms of an association between employment status and health. METHODS: Health indicators used were the prevalence of one or more chronic conditions, and perceived general health. Data were generated from a postal survey, part of the baseline data collection of a Dutch prospective cohort study on socioeconomic inequalities in health. RESULTS: After controlling for differences in other socioeconomic indicators, the association between income and health was found to be stronger than that between occupation or education and health. Most of the difference in strength was found to be due to employment status, especially among men. Controlling for employment status, and controlling for the distribution of those with a long-term work disability in particular, reduced the risks of lower income groups, whereas the risks of lower educational and occupational groups hardly changed. CONCLUSIONS: These results suggest that the relatively strong association between income and health can for a large part be interpreted in terms of an interrelationship between employment status, income and health. More specifically, it is largely due to the concentration of the long-term disabled in lower income groups. This indicates the importance of the selection mechanism, as these groups are excluded from paid employment because of their health status, leading to a lowering of income. However, income was still found to be related to perceived general health after controlling for employment status especially among women. This suggests that an explanation in terms of an effect of material factors on health may also be important.

Smaller socioeconomic inequalities in health among women: the role of employment status.

BACKGROUND: Socioeconomic inequalities in health are smaller among women than among men. In this paper, it is hypothesized that this is due to a gender difference in employment status. METHODS: We used data from the baseline of a Dutch longitudinal study. The socioeconomic indicators were educational level of the respondent and occupational level of the main breadwinner. Logistic regression was used to assess the size of socioeconomic inequalities in the prevalence of chronic conditions and less than 'good' perceived general health. RESULTS: The smaller socioeconomic inequalities in health among women were partly due to a less pronounced concentration among women than among men of relatively unhealthy employment status categories (unemployed, long-term work-disabled) in lower socioeconomic groups. The smaller inequalities in perceived general health among women could also partly be explained by the smaller overall size of the group of unemployed/long-term disabled/early retired among women than among men, a group which is characterized by relatively large inequalities in health. CONCLUSION: These findings suggest that in the Netherlands the low proportion of women in paid employment, and thereby the low proportion of the unemployed/long-term disabled/early retired, explains part of the smaller socioeconomic inequalities in health among women. The more pronounced concentration of those with a long-term work disability in lower socioeconomic groups among men, also points at the importance of working conditions for the gender difference in the size of socioeconomic inequalities in health.