Online Program

326578
Development and Validation of Household Asset-Based Socio-Economic Index — Results from SAGE4Health Study in Rural Malawi


Monday, November 2, 2015

Alice Yan, M.D., PhD, Joseph J. Zilber School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, WI
Emmanuel Ngui, DrPH, MSc, Joseph J. Zilber School of Public Health,, University of Wisconsin-Milwaukee, Milwaukee, WI
Patricia E. Stevens, RN, PhD, FAAN, College of Nursing, University of Wisconsin-Milwaukee, Milwaukee, WI
Loren W. Galvao, MD, MPH, Center for Global Health Equity, College of Nursing, University of Wisconsin-Milwaukee, Milwaukee, WI
Katarina Grande, MPH, Joseph J. Zilber School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, WI
Lindsay Emer, PhD(c), Joseph J. Zilber School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, WI
Thokozani Mwenyekonde, CARE, CARE International in Malawi, Lilongwe, Malawi
Lance S. Weinhardt, PhD, Joseph J. Zilber School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, WI
Background

Understanding social drivers of HIV risk and vulnerability is essential in highly impacted countries such as Malawi (11% HIV rate). Effects of Socioeconomic status (SES) on HIV/AIDS have not been well studied in developing countries, leaving gaps in how to define, validate, and measure SES.  Rather than income/expenditure, literature suggests using asset-based variables as a more reliable measure to develop SES indices in low-income settings.

Methods

We conducted Principal Components Analyses (N=899) to generate a Social Economic Index from an array of household assets variables. We used baseline data from a non-equivalent control group effectiveness study (SAGE4Health) that examined pathways linking distal ecosocial factors to HIV vulnerability in rural Malawi. The index’s criterion-related validity was examined. Finally, we classified households into quintiles to represent SES gradient.

Results

The factor analysis revealed eight principal factors explaining 60% of the variance. The first component, explaining the largest variance proportion (20%), related to ownership and quality of housing stock, such as roof and floor types, and bed number. The second and third components included ownership and quality of livestock (i.e., improved dairy cows or work oxen) and radio and farming equipment (i.e., axes, sickles) ownership, respectively. The index demonstrated good criterion-related validity and was significantly associated with HIV vulnerability (e.g., food security).

Conclusions

The PCA generated robust asset-based proxy SES indices to differentiate SES status. Findings support the validity of our Malawi study index and suggest the utility of using the index for research on HIV vulnerability in rural sub-Saharan countries.

Learning Areas:

Biostatistics, economics
Public health or related research
Social and behavioral sciences

Learning Objectives:
Describe the process of developing and validating an economic index, based on household assets in rural Malawi Discuss the use of the economic index in differentiating socioeconomic status of participants in a large community intervention project. Discuss the relationship of the index with HIV vulnerability in Malawi.

Keyword(s): Economic Analysis, Methodology

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I wrote the abstract and conducted the major analyses for the abstract. I also have a Ph.D. in Public Health and have been conducting research for the past five years.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.

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