Health Equity: 08/27/12

Monday, August 27, 2012

[EQ] What types of interventions generate inequalities?

What types of interventions generate inequalities?
Evidence from systematic reviews

Theo Lorenc 1, Mark Petticrew 1, Vivian Welch 2, Peter Tugwell 2

1 Department of Social & Environmental Health Research, London School of Hygiene & Tropical Medicine, London, UK

2 Centre for Global Health, University of Ottawa, Ottawa, Canada

J Epidemiol Community Health doi:10.1136/jech-2012-201257 - 8 August 2012

Background
Some effective public health interventions may increase inequalities by disproportionately benefiting less disadvantaged groups
(‘intervention-generated inequalities’ or IGIs). There is a need to understand which types of interventions are likely to produce IGIs, and which can reduce inequalities.

Methods We conducted a rapid overview of systematic reviews to identify evidence on ‘intervention-generated inequalities’ IGIs by socioeconomic status. We included any review of non-healthcare interventions in high-income countries presenting data on differential intervention effects on any health status or health behaviour outcome. Results were synthesised narratively.

Results The following intervention types show some evidence of increasing inequalities (IGIs) between socioeconomic status groups: media campaigns; and workplace smoking bans. However, for many intervention types, data on potential IGIs are lacking. By contrast, the following show some evidence of reducing health inequalities: structural workplace interventions; provision of resources; and fiscal interventions, such as tobacco pricing.

Conclusion Our findings are consistent with the idea that ‘downstream’ preventive interventions are more likely to increase health inequalities than ‘upstream’ interventions. More consistent reporting of differential intervention effectiveness is required to help build the evidence base on ‘intervention-generated inequalities’ IGIs. …”

KMC/2012/HSS
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[EQ] A new typology of policies to tackle health inequalities and scenarios of impact

A new typology of policies to tackle health inequalities and scenarios of impact
based on Rose’s population approach

Joan Benach,1,2 Davide Malmusi,2,3,4 Yutaka Yasui,5 Jose Miguel Martinez1,2,6

1 Health Inequalities Research Group, Employment Conditions Knowledge Network (GREDS-EMCONET), Department of Political and Social Sciences, Universitat Pompeu Fabra, Barcelona, Spain

2 CIBER Epidemiolog´ıa y Salud Pu´blica (CIBERESP), Barcelona, Spain

3 Age`ncia de Salut Pu´blica de Barcelona, IIB-Sant Pau, Barcelona, Spain

4 Unitat Docent de Medicina Preventiva i Salut Pu´blica PSMAR-UPF-ASPB, Barcelona, Spain

5 School of Public Health, University of Alberta, Canada
6 Occupational Health Research Center (CiSAL), Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain

J Epidemiol Community Health (2012). JECH August 17, 2012

Website: http://bit.ly/OED6YV

“………The last decade has witnessed a surge in interest for policies to tackle health inequalities. Adequate theoretical development of policy models is needed to understand how to design and evaluate equity-oriented health policies. In this paper we review Graham’s typology of policies (focused on the worst-off, on the gap, or on the gradient) and propose an adaptation (targeted, universal with additional targeting, redistributive, and proportionate universalism).

For each type, potential scenarios of impact on population health and health inequalities are depicted following the idea of Geoffrey Rose’s population curves and strategies, policy examples are given and a simulation with survey data is shown.

The proposed typology of scenarios of health inequality reduction can serve as an effective tool to interpret the differential impact of interventions and to reflect on how to adequately design or re-orient a policy and which measures to use to evaluate it…..”

KMC/2012/SDE
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* * *
This message from the Pan American Health Organization, PAHO/WHO, is part of an effort to disseminate
information Related to: Equity; Health inequality; Socioeconomic inequality in health; Socioeconomic
health differentials; Gender; Violence; Poverty; Health Economics; Health Legislation; Ethnicity; Ethics;
Information Technology - Virtual libraries; Research & Science issues. [DD/ KMC Area]
Washington DC USA

Thank you.