Vulnerable and susceptible groups

From Testiwiki
Jump to: navigation, search
The text on this page is taken from an equivalent page of the IEHIAS-project.

The populations studied as part of integrated environmental health impact assessments are never wholly uniform. How the environment impacts on the people concerned is therefore likely to vary, depending on their personal characteristics and situations. Ignoring these variations can be dangerous, both because it can lead to errors in the assessment and, more specifically, can mean that the differences in impact that occur across the population (including, in some cases, contrasts between benefits and losses) are not recognised.

Three terms are often used, sometimes interchangeably, to describe the personal and contextual factors that contribute to these variations: sensitivity, susceptibility and vulnerability. To avoid the ambiguity that thus arises, it is helpful to use only the first two terms - vulnerability and susceptibility - and to define these carefully.


Vulnerability refers to the variations in exposure between individuals or groups - and thus to the potential for health effects. To a large extent, this is likely to be due to variations in the hazards themselves. However, exposure is also a function of where people live, how (and where) they spend their time, and their more general lifestyle. In the case of air pollution, for example, living near busy roads or spending long hours in transport environments tends to increase vulnerability. In the case of pesticides, living close to areas where crops are sprayed or eating foodstuffs that have been heavily treated during production, storage or processing likewise acts to increase exposure, and thus vulnerability.


In contrast, susceptibility refers to the degree to which individuals or groups may respond to a given exposure to a hazard. This can be subdivided into innate and acquired susceptibility. Innate susceptibility is to a large extent due to genetic predisposition or to incomplete development of normal (adult) physiological functions. For example, a young child may be susceptible to a given pollutant because detoxification processes are not yet fully developed. Such susceptibility is transient and disappears with age and growth. Acquired susceptibility may be due to disease, age or socioeconomic status (though It should be noted that 'socioeconomic status' is not a precise identification of a causal factor). A number of mechanisms are known to play a part (see the detailed report on Susceptible Groups, under See also).

Dealing with vulnerability and susceptibility in health impact assessments

The importance of vulnerability and susceptibility in determining the health effects of exposures to environmental hazards, such as polluants, means that they need to be taken into account in all impact assessments. This has various implications for the way in which the assessment is designed. In particular:

  • study population should be segregated into appropriate sub-population groups, which can be separately analysed (e.g. on the basis of age, gender or socio-economic status);
  • relevant information on factors affecting vulnerability should be available and incorporated into the assessment (e.g. by taking account of behaviour and time-activity patterns);
  • relevant information on the factors affecting susceptibility should likewise be available, and incorporated (e.g. by using exposure-response functions specific to each sub-population group);
  • outcomes of the assessment should be reported for the different sub-population groups, as well as for the study population as a whole, so that inequalities in impacts can be identified.

Socio-economic status

Demographic and socio-economic factors are important determinants of health. In general, people who are economically more disadvantaged also face the double jeopardy of being:

  • subject to higher exposures to environmental pollutants and other hazards (the so-called problem of environmental injustice or inequity), because of being involved in more hazardous occupations and because of where they live;
  • to have less healthy lifestyles, due to poor diet, poor housing and lack of educational opportunities or access to social care and health services.

These factors in turn contribute to noticeable gradients in mortality and morbidity by socio-economic status.

Indicators of socio-economic status

For these reasons, socio-eonomic status (SES) is often seen as an indicator of both vulnerability and susceptibility to environmental effects on health, and efforts are often made to take account of SES both in epidemiological studies and in environmental health impact assessment. The indicators used vary, in part because of cultural differences between different countries, but in part also because of differences in data availability. Common measures include indicators of income or wealth, education and occupation, or some aggregation of these and other variables in the form of an index of deprivation. Some countries now have relatively well established indexes of this sort, usually based on census data or other routine statistics. Examples include the (somewhat different) indices used across the United Kingdom. Care is of course needed in using measures of SES in environmental health impact studies for two crucial reasons:

  1. SES in itself is not a direct cause of differences in health, but rather an indirect determinant, which operates through factors such as diet and lifestyle;
  2. SES tends to be associated both both levels of exposure (vulnerability) and degree of susceptibility, so confounding may occur in relationships between SES and health; it is important neither to dilute or remove the influence of the environment, by controlling for SES, nor to inflate possible health impacts by double-counting the joint effects of socio-economic status and environmental factors.

Sources of data on socio-economic status

A common European index of deprivation has not been developed. Information on socio-economic characteristics is available, however, from Eurostat - the statistical office of the European Union, which is tasked with providing statistics at European level that enable comparisons between countries and regions. Eurostat’s main role is to collect statistics supplied by Member States, and consolidate these using a harmonised methodology. This is facilitated by the NUTS (Nationales Unites Territoriales Statistiques) system, a standard hierarchy of administrative regions established in Europe. Member States are subdivided into three levels with 1 to 3 representing country, province/state and county/department areas, respectively. It is statistics for these top levels that are available through Eurostat, many of which are crucial for informing decisions and evaluation at European level.

Eurostat provides statistics on a wide range of socio-economic themes. Amongst these, those most of relevance for the derivation of measures of SES relate to health, education, labour, income, living conditions, social protection, crime and culture, all available via the Eurostat Population and social conditions theme. For the most part, these data are available at NUTS 2 or NUTs 3 level.

National statistical offices also serve a vital role in providing socio-economic statistics and indicators. Many of these are available for relatively small administrative areas (e.g. communes or census tracts), enabling them to be used for sub-national, city or small area assessments. If available, statistics for LAUs can usually be obtained from the National statistics offices; links to these websites can be found via the Eurostat portal.


See also

Integrated Environmental Health Impact Assessment System
IEHIAS is a website developed by two large EU-funded projects Intarese and Heimtsa. The content from the original website was moved to Opasnet.
Topic Pages

Boundaries · Population: age+sex 100m LAU2 Totals Age and gender · ExpoPlatform · Agriculture emissions · Climate · Soil: Degredation · Atlases: Geochemical Urban · SoDa · PVGIS · CORINE 2000 · Biomarkers: AP As BPA BFRs Cd Dioxins DBPs Fluorinated surfactants Pb Organochlorine insecticides OPs Parabens Phthalates PAHs PCBs · Health: Effects Statistics · CARE · IRTAD · Functions: Impact Exposure-response · Monetary values · Morbidity · Mortality: Database

Examples and case studies Defining question: Agriculture Waste Water · Defining stakeholders: Agriculture Waste Water · Engaging stakeholders: Water · Scenarios: Agriculture Crop CAP Crop allocation Energy crop · Scenario examples: Transport Waste SRES-population UVR and Cancer
Models and methods Ind. select · Mindmap · Diagr. tools · Scen. constr. · Focal sum · Land use · Visual. toolbox · SIENA: Simulator Data Description · Mass balance · Matrix · Princ. comp. · ADMS · CAR · CHIMERE · EcoSenseWeb · H2O Quality · EMF loss · Geomorf · UVR models · INDEX · RISK IAQ · CalTOX · PANGEA · dynamiCROP · IndusChemFate · Transport · PBPK Cd · PBTK dioxin · Exp. Response · Impact calc. · Aguila · Protocol elic. · Info value · DST metadata · E & H: Monitoring Frameworks · Integrated monitoring: Concepts Framework Methods Needs
Listings Health impacts of agricultural land use change · Health impacts of regulative policies on use of DBP in consumer products
Guidance System
The concept
Issue framing Formulating scenarios · Scenarios: Prescriptive Descriptive Predictive Probabilistic · Scoping · Building a conceptual model · Causal chain · Other frameworks · Selecting indicators
Design Learning · Accuracy · Complex exposures · Matching exposure and health · Info needs · Vulnerable groups · Values · Variation · Location · Resolution · Zone design · Timeframes · Justice · Screening · Estimation · Elicitation · Delphi · Extrapolation · Transferring results · Temporal extrapolation · Spatial extrapolation · Triangulation · Rapid modelling · Intake fraction · iF reading · Piloting · Example · Piloting data · Protocol development
Execution Causal chain · Contaminant sources · Disaggregation · Contaminant release · Transport and fate · Source attribution · Multimedia models · Exposure · Exposure modelling · Intake fraction · Exposure-to-intake · Internal dose · Exposure-response · Impact analysis · Monetisation · Monetary values · Uncertainty