Article Text
PDF
Statistics from Altmetric.com
- Inequalities
- socio-economic
- public health
- social inequalities
- policy
- employment
- fertility
- sociology FQ
- epidemiology
- social epidemiology
- unemployment
The surveillance of social determinants of health
Social determinants of health are major factors responsible for a population's health and health inequalities.1 Public health surveillance was originally developed for the control of infectious diseases, but today its principles have also been applied to other public health problems such as chronic diseases and occupational and traffic injuries.2 Many countries already collect data on social determinants of health, dispersed across different information systems typically designed for other purposes. However, most social determinants of health remain outside surveillance systems and this area of public health remains limited or marginal within mainstream policy practice. Surveillance of social determinants of health is therefore a neglected but essential and challenging public health issue. The WHO Commission on Social Determinants of Health strongly recommended the creation of National Health Equity Surveillance Systems, with routine data collection on the social determinants of health and health equity, and investment in training of policy-makers and health practitioners in equity monitoring and health equity impact assessment.1 Such investment was given further priority by international organisations and member states through the adoption of a World Health Assembly Resolution on social determinants of health in May 2009, and further reaffirmed in the Rio Political Declaration on Social Determinants of Health in October 2011.3 Likewise, the former Spanish Minister of Health and Social Policy launched ‘Innovation in Public Health: Monitoring Social Determinants of Health and Reduction of Health Inequalities’ as a top priority for the Spanish presidency of the European Union in the first semester of 2010.4 In spite of these initiatives, however, today there is no comprehensive surveillance system capable of globally or nationally monitoring social determinants and their relationship with health inequalities. Employment and working conditions are key areas of social determinants of health research agenda.5 This paper describes the importance, gaps and challenges in developing employment-health-equity surveillance systems.
Monitoring employment conditions
Employment and working conditions are prominent determinants of health because work and employment relations play a major role in most people's lives.6 Because they are unequally distributed by social class, gender, ethnicity/race or migrant status, these conditions also make a substantial contribution to health inequalities.7 While working conditions have received considerable attention as social determinants of health and, to a lesser extent, of health inequalities,8 researchers have rarely focused on employment relations, that is, the power relations between employers and workers and the level of social protection that workers can count on. The employment conditions knowledge network of the Commission on Social Determinants of Health classified employment conditions into six main categories: unemployment, precarious employment, informal employment, child labour, slavery/bonded labour, and full-time permanent employment, and found that countries whose governments favour fair employment and decent work policies also tend to have better health indicators and lower health inequalities.7 However, knowledge on those employment-related health inequalities remains limited or is neglected, and their monitoring over time is limited to a few indicators of employment conditions and for economic—not public health—purposes.
Surveillance gaps: precarious employment, informal employment and migration as examples
Precarious employment encompasses unstable employment, individual-level bargaining over employment conditions (or not bargaining at all), low wages and economic deprivation, limited workplace rights and social protection, vulnerability and unbalanced workplace power relations, and powerlessness to exercise workplace rights.9 Today there is a lack of indicators for precarious employment surveillance beyond standard indicators, such as the percentage of temporary contracts,10 which can turn out to be highly misleading. In fact, during the current economic crisis the share of temporary employment in the Spanish labour market has fallen rapidly and is currently at its lowest in 20 years (26% by the end of 2011), reflecting a deep deterioration in labour market conditions rather than a decrease in the prevalence of precarious employment. The recent development of an Employment Precariousness Scale, a theory-based multidimensional questionnaire specifically devised for epidemiological studies11 is a promising tool for overcoming these limitations and measuring precariousness in different populations. For example, one study found that the overall prevalence of employment precariousness in Spain in 2005 reached 48%, being highest among women, immigrants, youth and manual workers. Based on the employment precariousness construct and taking advantage of the wealth of readily-available data,12 a set of proxy indicators could be created for precarious employment surveillance. A good example is the European Working Conditions Survey, applied every 5 years. Early efforts have been made to apply the concept of employment precariousness to the European Working Conditions Survey data.12 Although with limitations, this will allow showing its social distribution and health impact across countries, both cross-sectionally and over time.
Informal employment is a global phenomenon of growing importance, characterised by work that is performed outside of labour legislation, taxation, social protection or entitlement to employment benefits such as pensions. Although present in every country, this employment condition is especially present in low-income countries, where it currently represents over two-fifths of the gross domestic product. Currently, the International Labour Organization gathers data on informal employment, but this information is limited.13 First, countries can insert their questions on informal employment within one of multiple survey types, rendering data not necessarily comparable between countries. Second, countries can differ in their definitions of informal employment, geographical areas and branches of economic activity covered, informal enterprise cut-off size, registration criteria, criteria for inclusion or exclusion of secondary jobs in the informal sector, age limits, and whether or not to include professional or technical activities, among other criteria.14 So, while it is estimated that informal employment represents 41% of total employment, meaning nearly two billion people only in low income countries,15 there is a lack of reliable prevalence estimations concerning informal employment and its impact on health and health inequalities, especially in rural settings and poor countries. Efforts must be made to standardise an informal employment definition in low-income countries, capable of capturing informal jobs within and outside the informal economy. Indeed, the development of informal employment health-related inequalities surveillance systems will require extensive collaboration between national statistical offices, researchers and policy makers.13
Employment and working conditions faced by most migrant workers are dangerous to their health. With ‘globalisation’, investments, and labour has been increasingly mobile.6 International migrants were estimated at 214 million in 2010, of which about 90% are migrant workers and their families.16 In 2009, 40% of EU residents were born outside the European Union.17 The ‘pull’ of workers trying to access higher wage labour markets is compounded by the ‘push’ factor of corporations seeking less regulated labour markets.18 A major gap in international migration research is the lack of consistent, comparable data across countries. More global health surveillance and socio-epidemiologic analyses of migration are needed to render employment conditions prominent in migration policy.19 A key challenge concerns the need for high quality data and information systems, including reliable estimates of international migration flows, national-level data on the incidence and magnitude of migration, migrant workers' employment and working conditions and health status.14 Today most countries lack adequate national systems to monitor key occupational health problems among migrants and most official and unofficial statistics do not disaggregate migratory flows by age, gender, ethnicity or social class. Governments and health agencies should establish adequate information systems and research plans to gather data on migration processes and hard-to-reach or undocumented migrants. Oversampling of migrant workers and data-pooling are two approaches that can be used to address the statistical instability introduced by the small numbers of migrant workers in many studies. Overcoming these data problems will help to obtain better estimates of injuries, mortality and morbidity, and to properly monitor the evolution of immigrants, their health inequalities and health policy and prevention programmes.
Challenges
A general goal, and the most challenging one, is the development of global employment-related health inequalities surveillance systems, with an emphasis on middle- and low-income countries. Such systems must aim at overcoming the difficulties inherent to cross-country comparisons that arise from the diversity of forms of employment and working conditions, the ensuing barriers to reaching universally standardised definitions and the lack of available data.
Unlike existing data systems, which often only present country-level health averages, a key feature of such monitoring systems should be to present the data stratified by social groups. Researchers and policy makers would therefore be able to know whether the country's health averages are concealing large health differences between groups, and be able to formulate policies and interventions that are more equitable.6 Moreover, researchers would be able to study the differential exposure to socially patterned risks and differential vulnerability-effect modification to these factors across groups. Both, differential exposure and effect modification are the main hypotheses to explain health inequalities.20 Second, and when possible, interactions between social strata as determined by social class, gender, ethnicity, age and migration status could be analysed, as intersectional approaches provide an excellent insight on health inequalities.21 ,22 Specifically, for analysing gender inequalities due to employment conditions, family characteristics and household chores should be taken into account, as health inequalities cannot be understood without a work-family interaction insight.6 ,23 Third, surveillance should be inclusive and cover all the population connected to employment: from standard employees to persons exclusively dedicated to reproductive labour and disabled persons. Fourth, some attention should be paid to choosing the most appropriate measures for health inequalities.24 Finally, the most appropriate definitions and indicators for employment conditions such as precarious and informal employment have to be formulated, based on a theoretical conceptualisation for health purposes, and not exclusively for economic purposes.
Today knowledge of what constitutes the most appropriate indicators for monitoring employment conditions in different social contexts, and the methods to choose them, remain limited to traditional labour market outcomes such as unemployment25 but are very scarce for other employment conditions. To date, only a few countries have introduced data on employment conditions—mainly unemployment—in their public health surveillance systems, Sweden and the UK, being two good examples.25 In spite of these limitations, ongoing employment and working conditions-related surveys are promising tools to monitor employment-related health inequalities. However, to be useful, these surveys must be representative of the population and large enough to analyse inequalities by gender, socioeconomic position and immigration status, they must be repeated over time (eg, every other year) in order to evaluate time trends and include health indicators to analyse the impact of employment conditions. However, the greatest challenge regarding ongoing surveys is being able to apply valid and conceptually sound measures, as exemplified above with the employment precariousness concept.11 ,12
Concluding remarks
The surveillance of health-related employment conditions is necessary to determine their magnitude, evolution over time and most affected populations. The monitoring of employment health-related inequalities is important for two main reasons: to identify potential policy entry-points, and to assess the impact of policies and interventions. The measurement of gains in health equity should be based on indicators that are relevant to the contexts in which they are placed, and take into account the varying levels of information available in different countries and regions. Governments and health agencies should establish adequate surveillance information systems to gather public health data associated with fundamental employment conditions such as precarious employment, informal employment and other extreme forms of hazardous employment such as slavery (at least 12 million people worldwide) or child labour (about 250 million), paying special attention to the social mechanisms of inequality.6 In addition, special efforts should be made to develop new sensitive indicators more able to capture the whole impact of the economic recession in high-income countries on the population's health. These systems can become key tools to support evidence-based policy-making, effective interventions and advocacy. Surveillance systems can be used to determine entry-points for intervention, evaluate the impact of policies, and prioritise the use of public resources. These systems should be comprehensible, user friendly and accessible to researchers such as epidemiologists, health professionals, policy-makers, experts and the general public.
References
Footnotes
-
Funding This work was supported by GEHES project and SOPHIE project, grant number CSO2009-12536 (for GEHES), 278173 (for SOPHIE). This study was partially supported by the Spanish Ministry of Science and Innovation (Ref. CSO2009-12536) and PLAN E. (Financiado por MICINN (Ref. CSO2009-12536) y Plan E). The research leading to these results has also received funding from the European Community's Seventh Framework Programme (FP7/2007-2013) under grant agreement number 278173 (SOPHIE project).
-
Competing interests None.
-
Provenance and peer review Commissioned; externally peer reviewed.