Gender inequalities in occupational health related to the unequal distribution of working and employment conditions: a systematic review

Introduction: Gender inequalities exist in work life, but little is known about their presence in relation to factors examined in occupation health settings. The aim of this study was to identify and summarize the working and employment conditions described as determinants of gender inequalities in occupational health in studies related to occupational health published between 1999 and 2010. Methods: A systematic literature review was undertaken of studies available in MEDLINE, EMBASE, Sociological Abstracts, LILACS, EconLit and CINAHL between 1999 and 2010. Epidemiologic studies were selected by applying a set of inclusion criteria to the title, abstract, and complete text. The quality of the studies was also assessed. Selected studies were qualitatively analysed, resulting in a compilation of all differences between women and men in the prevalence of exposure to working and employment conditions and work-related health problems as outcomes. Results: Most of the 30 studies included were conducted in Europe (n=19) and had a cross-sectional design (n=24). The most common topic analysed was related to the exposure to work-related psychosocial hazards (n=8). Employed women had more job insecurity, lower control, worse contractual working conditions and poorer self-perceived physical and mental health than men did. Conversely, employed men had a higher degree of physically demanding work, lower support, higher levels of effort-reward imbalance, higher job status, were more exposed to noise and worked longer hours than women did. Conclusions: This systematic review has identified a set of working and employment conditions as determinants of gender inequalities in occupational health from the occupational health literature. These results may be useful to policy makers seeking to reduce gender inequalities in occupational health, and to researchers wishing to analyse these determinants in greater depth.

Sexual health and socioeconomic-related factors in Spain

Purpose: The aim of the present study was to describe sexual health in Spain according to three important indicators of the World Health Organization definition and explore the influence of socioeconomic factors. Methods: We performed a population-based cross-sectional study of sexually active people aged 16-44 years residing in Spain in 2009 (2365 women and 2532 men). Three main aspects of sexual health were explored: sexual satisfaction, safe sex, and sexual abuse. The independent variables explored were age, age at first intercourse, reason for first intercourse, type of partner, level of education, country of origin, religiousness, parity, and social class. Bivariate and multivariate logistic regression models were fitted. Results: Both men and women were quite satisfied with their sexual life, their first sexual intercourse, and their sexual relationships during the previous year. Most participants had practiced safe sex both at first intercourse and during the previous year. Levels of sexual abuse were similar to those in other developed countries. People of disadvantaged socioeconomic position have less satisfying, more unsafe, and more abusive sexual relationships. Women experienced more sexual abuse and had less satisfaction at their first intercourse. Conclusions: The state of sexual health in Spain is relatively good. However, we observed inequalities according to gender and socioeconomic position.

Welfare state regimes and gender inequalities in the exposure to work-related psychosocial hazards

Background: Gender inequalities in the exposure to work-related psychosocial hazards are well established. However, little is known about how welfare state regimes influence these inequalities. Objectives: To examine the relationship between welfare state regimes and gender inequalities in the exposure to work-related psychosocial hazards in Europe, considering occupational social class. Methods: We used a sample of 27, 465 workers from 28 European countries. Dependent variables were high strain, iso-strain, and effort-reward imbalance, and the independent was gender. We calculated the prevalence and prevalence ratio separately for each welfare state regime and occupational social class, using multivariate logistic regression models. Results: More female than male managers/professionals were exposed to: high strain, iso-strain, and effort–reward imbalance in Scandinavian [adjusted prevalence ratio (aPR) = 2·26; 95% confidence interval (95% CI): 1·87–2·75; 2·12: 1·72–2·61; 1·41: 1·15–1·74; respectively] and Continental regimes (1·43: 1·23–1·54; 1·51: 1·23–1·84; 1·40: 1·17–1·67); and to high strain and iso-strain in Anglo-Saxon (1·92: 1·40–2·63; 1·85: 1·30–2·64; respectively), Southern (1·43: 1·14–1·79; 1·60: 1·18–2·18), and Eastern regimes (1·56: 1·35–1·81; 1·53: 1·28–1·83). Conclusion: Gender inequalities in the exposure to work-related psychosocial hazards were not lower in those welfare state regimes with higher levels of universal social protection policies.

Do socioeconomic gradients in women's health widen over time and with age

A population-based study was conducted to investigate changes over time in women's well-being and health service use by socio-cconomic status and whether these varied by age. Data from 12,328 mid-age women (aged 45-50 years in 1996) and 10,430 older women (aged 70-75 years) from the Australian Longitudinal Study on Women's Health were analysed. The main outcome measures were changes in the eight dimensions of the Short Form General Health Survey (SF-36) adjusted for baseline scores, lifestyle and behavioural factors; health care utilisation at Survey 2; and rate of deaths (older cohort only). Cross-sectional analyses showed clear socioeconomic differentials in well-being for both cohorts. Differential changes in health across tertiles of socioeconomic status (SES) were more evident in the mid-age cohort than in the older cohort. For the mid-aged women in the low SES tertile, declines in physical functioning (adjusted mean change of -2.4, standard error (SE) 1.1) and general health perceptions (-1.5, SE 1.1) were larger than the high SES group (physical functioning -0.8 SE 1.1, general health perceptions -0.8 SE 1.2). In the older cohort, changes in SF-36 scores over time were similar for all SES groups but women in the high SES group had lower death rates than women in the low SES group (relative risk: 0.79, 95% confidence interval 0.64-0.98). Findings suggest that SES differentials in physical health seem to widen during women's mid-adult years but narrow in older age. Nevertheless, SES remains an important predictor of health, health service use and mortality in older Australian women. (C) 2003 Elsevier Ltd. All rights reserved.

A comparison of the association between socioeconomic position and cardiovascular disease risk factors in three age cohorts of Australian women: findings from the Australian Longitudinal Study on Women's Health

Objectives To assess the associations between three measurements of socioeconomic position (SEP) - education, occupation and ability to cope on available income - and cardiovascular risk factors in three age cohorts of Australian women. Methods Cross-sectional analysis of three cohorts of Australian women aged 18-23, 45-50 and 70-75 years. Results In general, for all exposures and in all three cohorts, the odds of each adverse risk factor (smoking, obesity and physical inactivity) were lower in the most advantaged compared with the least advantaged. Within each of the three cohorts, the effects of each measurement of SEP on the outcomes were similar. There were, however, some notable between-cohort differences. The most marked differences were those with smoking. For women aged 70-75 (older), those with the highest educational attainment were more likely to have ever smoked than those with the lowest level of attainment. However, for the other two cohorts, this association was reversed, with a stronger association between low levels of education and ever smoking among those aged 18-23 (younger) than those aged 45-50 (mid-age). Similarly, for older women, those in the most skilled occupational classes were most likely to have ever smoked, with opposite findings for mid-age women. Education was also differently associated with physical inactivity across the three cohorts. Older women who were most educated were least likely to be physically inactive, whereas among the younger and mid-age cohorts there was little or no effect of education on physical inactivity. Conclusion These findings demonstrate the dynamic nature of the association between SEP and some health outcomes. Our findings do not appear to confirm previous suggestions that prestige-based measurements of SEP are more strongly associated with health-related behaviours than measurements that reflect material and psychosocial resources.

The Worsening of the employment and work conditions and its relationship to the self-perceived health in European working population. Relevance and effects of the latest socioeconomic crisis

The recent crisis of the capitalistic economic system has altered the working conditions and occupations in the European Union. The recession situation has accelerated trends and has brought transformations that have been observed before. Changes have not looked the same way in all the countries of the Union. The social occupation norms, labour relations models and the type of global welfare provision can help underline some of these inequalities. Poor working conditions can expose workers to situations of great risk. This is one of the basic assumptions of the theoretical models and analytical studies of the approach to the psychosocial work environment. Changes in working conditions of the population seems to be important to explain in the worst health states. To observe these features in the current period of economic recession it has made a comparative study of trend through the possibilities of the European Working Conditions Survey in the 2005 and 2010 editions. It has also set different multivariate logistic regression models to explore potential partnerships with the worst conditions of employment and work. It seems that the economic crisis has intensified changes in working conditions and highlighted the effects of those conditions on the poor health of the working population. This conclusion can’t be extended for all EU countries; some differences were observed in terms of global welfare models.

Identifying health inequalities in individuals with major mental illness (MMI) using routine data

Abstract and Summary of Thesis: Background: Individuals with Major Mental Illness (such as schizophrenia and bipolar disorder) experience increased rates of physical health comorbidity compared to the general population. They also experience inequalities in access to certain aspects of healthcare. This ultimately leads to premature mortality. Studies detailing patterns of physical health comorbidity are limited by their definitions of comorbidity, single disease approach to comorbidity and by the study of heterogeneous groups. To date the investigation of possible sources of healthcare inequalities experienced by individuals with Major Mental Illness (MMI) is relatively limited. Moreover studies detailing the extent of premature mortality experienced by individuals with MMI vary both in terms of the measure of premature mortality reported and age of the cohort investigated, limiting their generalisability to the wider population. Therefore local and national data can be used to describe patterns of physical health comorbidity, investigate possible reasons for health inequalities and describe mortality rates. These findings will extend existing work in this area. Aims and Objectives: To review the relevant literature regarding: patterns of physical health comorbidity, evidence for inequalities in physical healthcare and evidence for premature mortality for individuals with MMI. To examine the rates of physical health comorbidity in a large primary care database and to assess for evidence for inequalities in access to healthcare using both routine primary care prescribing data and incentivised national Quality and Outcome Framework (QOF) data. Finally to examine the rates of premature mortality in a local context with a particular focus on cause of death across the lifespan and effect of International Classification of Disease Version 10 (ICD 10) diagnosis and socioeconomic status on rates and cause of death. Methods: A narrative review of the literature surrounding patterns of physical health comorbidity, the evidence for inequalities in physical healthcare and premature mortality in MMI was undertaken. Rates of physical health comorbidity and multimorbidity in schizophrenia and bipolar disorder were examined using a large primary care dataset (Scottish Programme for Improving Clinical Effectiveness in Primary Care (SPICE)). Possible inequalities in access to healthcare were investigated by comparing patterns of prescribing in individuals with MMI and comorbid physical health conditions with prescribing rates in individuals with physical health conditions without MMI using SPICE data. Potential inequalities in access to health promotion advice (in the form of smoking cessation) and prescribing of Nicotine Replacement Therapy (NRT) were also investigated using SPICE data. Possible inequalities in access to incentivised primary healthcare were investigated using National Quality and Outcome Framework (QOF) data. Finally a pre-existing case register (Glasgow Psychosis Clinical Information System (PsyCIS)) was linked to Scottish Mortality data (available from the Scottish Government Website) to investigate rates and primary cause of death in individuals with MMI. Rate and primary cause of death were compared to the local population and impact of age, socioeconomic status and ICD 10 diagnosis (schizophrenia vs. bipolar disorder) were investigated. Results: Analysis of the SPICE data found that sixteen out of the thirty two common physical comorbidities assessed, occurred significantly more frequently in individuals with schizophrenia. In individuals with bipolar disorder fourteen occurred more frequently. The most prevalent chronic physical health conditions in individuals with schizophrenia and bipolar disorder were: viral hepatitis (Odds Ratios (OR) 3.99 95% Confidence Interval (CI) 2.82-5.64 and OR 5.90 95% CI 3.16-11.03 respectively), constipation (OR 3.24 95% CI 3.01-3.49 and OR 2.84 95% CI 2.47-3.26 respectively) and Parkinson’s disease (OR 3.07 95% CI 2.43-3.89 and OR 2.52 95% CI 1.60-3.97 respectively). Both groups had significantly increased rates of multimorbidity compared to controls: in the schizophrenia group OR for two comorbidities was 1.37 95% CI 1.29-1.45 and in the bipolar disorder group OR was 1.34 95% CI 1.20-1.49. In the studies investigating inequalities in access to healthcare there was evidence of: under-recording of cardiovascular-related conditions for example in individuals with schizophrenia: OR for Atrial Fibrillation (AF) was 0.62 95% CI 0.52 - 0.73, for hypertension 0.71 95% CI 0.67 - 0.76, for Coronary Heart Disease (CHD) 0.76 95% CI 0.69 - 0.83 and for peripheral vascular disease (PVD) 0.83 95% CI 0.72 - 0.97. Similarly in individuals with bipolar disorder OR for AF was 0.56 95% CI 0.41-0.78, for hypertension 0.69 95% CI 0.62 - 0.77 and for CHD 0.77 95% CI 0.66 - 0.91. There was also evidence of less intensive prescribing for individuals with schizophrenia and bipolar disorder who had comorbid hypertension and CHD compared to individuals with hypertension and CHD who did not have schizophrenia or bipolar disorder. Rate of prescribing of statins for individuals with schizophrenia and CHD occurred significantly less frequently than in individuals with CHD without MMI (OR 0.67 95% CI 0.56-0.80). Rates of prescribing of 2 or more anti-hypertensives were lower in individuals with CHD and schizophrenia and CHD and bipolar disorder compared to individuals with CHD without MMI (OR 0.66 95% CI 0.56-0.78 and OR 0.55 95% CI 0.46-0.67, respectively). Smoking was more common in individuals with MMI compared to individuals without MMI (OR 2.53 95% CI 2.44-2.63) and was particularly increased in men (OR 2.83 95% CI 2.68-2.98). Rates of ex-smoking and non-smoking were lower in individuals with MMI (OR 0.79 95% CI 0.75-0.83 and OR 0.50 95% CI 0.48-0.52 respectively). However recorded rates of smoking cessation advice in smokers with MMI were significantly lower than the recorded rates of smoking cessation advice in smokers with diabetes (88.7% vs. 98.0%, p<0.001), smokers with CHD (88.9% vs. 98.7%, p<0.001) and smokers with hypertension (88.3% vs. 98.5%, p<0.001) without MMI. The odds ratio of NRT prescription was also significantly lower in smokers with MMI without diabetes compared to smokers with diabetes without MMI (OR 0.75 95% CI 0.69-0.81). Similar findings were found for smokers with MMI without CHD compared to smokers with CHD without MMI (OR 0.34 95% CI 0.31-0.38) and smokers with MMI without hypertension compared to smokers with hypertension without MMI (OR 0.71 95% CI 0.66-0.76). At a national level, payment and population achievement rates for the recording of body mass index (BMI) in MMI was significantly lower than the payment and population achievement rates for BMI recording in diabetes throughout the whole of the UK combined: payment rate 92.7% (Inter Quartile Range (IQR) 89.3-95.8 vs. 95.5% IQR 93.3-97.2, p<0.001 and population achievement rate 84.0% IQR 76.3-90.0 vs. 92.5% IQR 89.7-94.9, p<0.001 and for each country individually: for example in Scotland payment rate was 94.0% IQR 91.4-97.2 vs. 96.3% IQR 94.3-97.8, p<0.001. Exception rate was significantly higher for the recording of BMI in MMI than the exception rate for BMI recording in diabetes for the UK combined: 7.4% IQR 3.3-15.9 vs. 2.3% IQR 0.9-4.7, p<0.001 and for each country individually. For example in Scotland exception rate in MMI was 11.8% IQR 5.4-19.3 compared to 3.5% IQR 1.9-6.1 in diabetes. Similar findings were found for Blood Pressure (BP) recording: across the whole of the UK payment and population achievement rates for BP recording in MMI were also significantly reduced compared to payment and population achievement rates for the recording of BP in chronic kidney disease (CKD): payment rate: 94.1% IQR 90.9-97.1 vs.97.8% IQR 96.3-98.9 and p<0.001 and population achievement rate 87.0% IQR 81.3-91.7 vs. 97.1% IQR 95.5-98.4, p<0.001. Exception rates again were significantly higher for the recording of BP in MMI compared to CKD (6.4% IQR 3.0-13.1 vs. 0.3% IQR 0.0-1.0, p<0.001). There was also evidence of differences in rates of recording of BMI and BP in MMI across the UK. BMI and BP recording in MMI were significantly lower in Scotland compared to England (BMI:-1.5% 99% CI -2.7 to -0.3%, p<0.001 and BP: -1.8% 99% CI -2.7 to -0.9%, p<0.001). While rates of BMI and BP recording in diabetes and CKD were similar in Scotland compared to England (BMI: -0.5 99% CI -1.0 to 0.05, p=0.004 and BP: 0.02 99% CI -0.2 to 0.3, p=0.797). Data from the PsyCIS cohort showed an increase in Standardised Mortality Ratios (SMR) across the lifespan for individuals with MMI compared to the local Glasgow and wider Scottish populations (Glasgow SMR 1.8 95% CI 1.6-2.0 and Scotland SMR 2.7 95% CI 2.4-3.1). Increasing socioeconomic deprivation was associated with an increased overall rate of death in MMI (350.3 deaths/10,000 population/5 years in the least deprived quintile compared to 794.6 deaths/10,000 population/5 years in the most deprived quintile). No significant difference in rate of death for individuals with schizophrenia compared with bipolar disorder was reported (6.3% vs. 4.9%, p=0.086), but primary cause of death varied: with higher rates of suicide in individuals with bipolar disorder (22.4% vs. 11.7%, p=0.04). Discussion: Local and national datasets can be used for epidemiological study to inform local practice and complement existing national and international studies. While the strengths of this thesis include the large data sets used and therefore their likely representativeness to the wider population, some limitations largely associated with using secondary data sources are acknowledged. While this thesis has confirmed evidence of increased physical health comorbidity and multimorbidity in individuals with MMI, it is likely that these findings represent a significant under reporting and likely under recognition of physical health comorbidity in this population. This is likely due to a combination of patient, health professional and healthcare system factors and requires further investigation. Moreover, evidence of inequality in access to healthcare in terms of: physical health promotion (namely smoking cessation advice), recording of physical health indices (BMI and BP), prescribing of medications for the treatment of physical illness and prescribing of NRT has been found at a national level. While significant premature mortality in individuals with MMI within a Scottish setting has been confirmed, more work is required to further detail and investigate the impact of socioeconomic deprivation on cause and rate of death in this population. It is clear that further education and training is required for all healthcare staff to improve the recognition, diagnosis and treatment of physical health problems in this population with the aim of addressing the significant premature mortality that is seen. Conclusions: Future work lies in the challenge of designing strategies to reduce health inequalities and narrow the gap in premature mortality reported in individuals with MMI. Models of care that allow a much more integrated approach to diagnosing, monitoring and treating both the physical and mental health of individuals with MMI, particularly in areas of social and economic deprivation may be helpful. Strategies to engage this “hard to reach” population also need to be developed. While greater integration of psychiatric services with primary care and with specialist medical services is clearly vital the evidence on how best to achieve this is limited. While the National Health Service (NHS) is currently undergoing major reform, attention needs to be paid to designing better ways to improve the current disconnect between primary and secondary care. This should then help to improve physical, psychological and social outcomes for individuals with MMI.

Tackling health inequalities in primary care: an exploration of GPs’ experience at the frontline

In Scotland, life expectancy and health outcomes are strongly tied to socioeconomic status. Specifically, socioeconomically deprived areas suffer disproportionately from high levels of premature multimorbidity and mortality. To tackle these inequalities in health, challenges in the most deprived areas must be addressed. One avenue that merits attention is the potential role of general medical practitioners (GPs) in helping to address health inequalities, particularly due to their long-term presence in deprived communities, their role in improving patient and population health, and their potential advocacy role on behalf of their patients. GPs can be seen as what Lipsky calls ‘street-level bureaucrats’ due to their considerable autonomy in the decisions they make surrounding individual patient needs, yet practising under the bureaucratic structure of the NHS. While previous research has examined the applicability of Lipsky’s framework to the role of GPs, there has been very little research exploring how GPs negotiate between the multiple identities in their work, how GPs ‘socially construct’ their patients, how GPs view their potential role as ‘advocate’, and what this means in terms of the contribution of GPs to addressing existing inequalities in health. Using semi-structured interviews, this study explored the experience and views of 24 GPs working in some of Scotland’s most deprived practices to understand how they might combat this growing health divide via the mitigation (and potential prevention) of existing health inequalities. Participants were selected based on several criteria including practice deprivation level and their individual involvement in the Deep End project, which is an informal network comprising the 100 most deprived general practices in Scotland. The research focused on understanding GPs’ perceptions of their work including its broader implications, within their practice, the communities within which they practise, and the health system as a whole. The concept of street-level bureaucracy proved to be useful in understanding GPs’ frontline work and how they negotiate dilemmas. However, this research demonstrated the need to look beyond Lipsky’s framework in order to understand how GPs reconcile their multiple identities, including advocate and manager. As a result, the term ‘street-level professional’ is offered to capture more fully the multiple identities which GPs inhabit and to explain how GPs’ elite status positions them to engage in political and policy advocacy. This study also provides evidence that GPs’ social constructions of patients are linked not only to how GPs conceptualise the causes of health inequalities, but also to how they view their role in tackling them. In line with this, the interviews established that many GPs felt they could make a difference through advocacy efforts at individual, community and policy/political levels. Furthermore, the study draws attention to the importance of practitioner-led groups—such as the Deep End project—in supporting GPs’ efforts and providing a platform for their advocacy. Within this study, a range of GPs’ views have been explored based on the sample. While it is unclear how common these views are amongst GPs in general, the study revealed that there is considerable scope for ‘political GPs’ who choose to exercise discretion in their communities and beyond. Consequently, GPs working in deprived areas should be encouraged to use their professional status and political clout not only to strengthen local communities, but also to advocate for policy change that might potentially affect the degree of disadvantage of their patients, and levels of social and health inequalities more generally.