Health Equity: 05/29/08

Thursday, May 29, 2008

[EQ] Low socio-economiceconomic position is associated with poor social networks and social

Low socio-economiceconomic position is associated with poor social networks and social

support: results from the Heinz Nixdorf Recall Study

Simone Weyers1§, Nico Dragano1, Susanne Möbus 2, Eva-Maria Beck 2 , Andreas

Stang 4, Stephan Möhlenkamp3 , Karl Heinz Jöckel 2 , Raimund Erbel3, Johannes Siegrist1

1 Department of Medical Sociology, University Duesseldorf, Heinrich-Heine-Universität Duesseldorf, Universitätsstrasse 1, Duesseldorf, Germany

2 Institute for Medical Informatics, Biometry and Epidemiology, University Hospital,University of Duisburg-Essen, Essen, Germany

3 West German Heart Center Essen, University Hospital, University of Duisburg-Essen, Essen, Germany

4 Institute of Medical Epidemiology, Biometry and Informatics, Medical Faculty,Martin-Luther-University of Halle-Wittenberg, Halle, Germany

International Journal for Equity in Health – May 2008, 7:13

http://www.equityhealthj.com/content/pdf/1475-9276-7-13.pdf

Background Social networks and social support are supposed to contribute to the development of unequal health within populations. However, little is known about their socio-economic distribution. In this study, we explore this distribution.

Methods This study analyses the association of two indicators of socio-economic position, education and income, with different measures of social networks and support. Cross-sectional data have been derived from the baseline examination of an epidemiological cohort study of 4.814 middle aged urban inhabitants in Germany (Heinz Nixdorf Recall Study). Bivariate and multivariate logistic regression analysis were carried out to estimate the risk of having poor social networks and support across socio-economic groups.

Results Socially disadvantaged persons more often report poor social networks and social support. In multivariate analyses, based on education, odds ratios range from 1.0 (highest education) to 4.9 (lowest education) in a graded way. Findings based on income show similar effects, ranging from 1.0 to 2.5. There is one exception: no association of SEP with close ties living nearby and regularly seen was observed.

Conclusion Poor social networks and low social support are more frequent among socio-economically disadvantaged people. To some extent, this finding varies according to the indicator chosen to measure these social constructs.

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information Related to: Equity; Health inequality; Socioeconomic inequality in health; Socioeconomic
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[EQ] The Economics of Early Childhood Policy

The Economics of Early Childhood Policy

What the Dismal Science Has to Say About Investing in Children

M. Rebecca Kilburn, Lynn A. Karoly

RAND Corporation, Sponsored by Casey Family Programs, 2008

Website: http://rand.org/pubs/occasional_papers/OP227/

“……Scientific discoveries over the past two decades have transformed the way in which researchers, policymakers, and the public think about early childhood. For example, recent research in brain science has provided a biological basis for prevailing theories about early child development, and cost-benefit analysis has reoriented some of the discussion about early childhood toward prevention programs. Several recent reports have been particularly helpful in translating research findings into practical information that improves policy.

This paper summarizes the contributions from the field of economics, which has played an increasingly prominent role in recent discussions about early childhood policy. The insights from economics also have broader implications for social programs focused on prevention, especially during childhood, rather than later-in-life remediation. This research will be of value to individuals who are interested in early childhood policy, including decision makers in the public and private sectors, service providers, and the public more generally. …”

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[EQ] Canada - Health Indicators 2008

Canada - Health Indicators 2008

The Canadian Institute for Health Information (CIHI and Statistics Canada, May 2008

Website: http://secure.cihi.ca/cihiweb/dispPage.jsp?cw_page=PG_1350_E&cw_topic=1350&cw_rel=AR_152_E

PDF file [96p.] at: http://secure.cihi.ca/cihiweb/dispPage.jsp?cw_page=download_form_e&cw_sku=HI08ENPDF&cw_ctt=1&cw_dform=N

“….Hospitalization rates vary across the country for seven chronic conditions that could potentially be managed or treated in the community, known as ambulatory care sensitive conditions (ACSC).This report measures ambulatory care sensitive conditions ACSC admission rates in health regions across Canada and explores the factors that contribute to higher or lower rates. Ambulatory care sensitive conditions ACSC such as asthma, diabetes and hypertension.

This year’s report includes results for more health regions with a population greater than 50,000 (encompassing about 98% of Canada’s population) and for provinces and territories. This enhancement increases the number of regions included in this report from 71 up to 80. Following the Health Indicator Framework, each indicator is grouped into one of the following four dimensions:

• Health status—provides insight on the health of Canadians, including well-being, human function and selected health conditions.

• Non-medical determinants of health—reflect factors outside of the health system that affect health.

• Health system performance—provides insight on the quality of health services, including accessibility, appropriateness, effectiveness and patient safety.

• Community and health system characteristics—provide useful contextual information, rather than direct measures of health status or quality of care.

Health Indicators 2008 also provides an in-depth analysis of one indicator—hospital admissions for ambulatory care sensitive conditions (ACSC). This indicator includes seven chronic conditions that can potentially be effectively managed in the community but may result in hospitalization in an acute care facility. They are:

• angina;

• asthma;

• chronic obstructive pulmonary disease (COPD);

• diabetes;

• grand mal status and other epileptic convulsions;

• heart failure and pulmonary edema; and
• hypertension

Content:

Executive Summary

Health Indicator Framework

In Focus: Hospitalization Rates for Ambulatory Care Sensitive Conditions

What the Numbers Tell Us

Regional Variations

Factors Affecting ACSC Hospitalizations

Variations by Age

Variations by Sex

Rural and Urban Variations

Variations by Income

What Is Being Done

Information Gaps

References
Health Indicators—Region by Region
Health Region Profile

Health Status

Non-Medical Determinants of Health

Health System Performance

Community and Health System Characteristics

General Notes

Indicator Index
Regional Map

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