Assessing socioeconomic effects on different sized populations: to weight or not to weight?


Related Publications

Smolina K, Weymann D, Morgan S, Ross C, Carleton B. Association between regulatory advisories and codeine prescribing to postpartum women. Journal of the American Medical Association. 2015;313(18):1861-2.
Suter E, Misfeldt R, Mallinson S, Wilhelm A, Boakye O, Marchildon G, et al. Comparative Review of the Policy Landscape of Team-based Primary Health Care Service Delivery in Western Canada. Alberta Health Services; 2014.
Laberge M, Pang J, Walker K, Wong ST, Hogg W, Wodchis WP. QUALICOPC (Quality and Costs of Primary Care) Canada: A focus on the aspects of primary care most highly rated by current patients of primary care practices. Ottawa, ON: Canadian Foundation for Healthcare Improvement; 2014.
McGregor MJ, Abu-Laban RB, Ronald L, McGrail KM, Andrusiek D, Baumbusch J, et al. Nursing Home Characteristics Associated with Resident Transfers to Emergency Department. Canadian Journal on Aging. 2012;33(1):38-48.

Publication Topics

Assessing socioeconomic effects on different sized populations: to weight or not to weight?

Publication TypeJournal Article
Year of Publication2001
AuthorsFrohlich N, Carriere KC, Potvin L, Black CD
JournalJournal of epidemiology and community healthJ.Epidemiol.Community Health
Pages913 - 920
Date Published2001
KeywordsAge Factors, Bias (Epidemiology), Ecology, Female, Health Services Needs and Demand/statistics & numerical data, Humans, Male, Manitoba, Population Density, Primary Health Care/utilization, Regression Analysis, Sex Factors, Socioeconomic Factors
AbstractOBJECTIVE: Researchers in health care often use ecological data from population aggregates of different sizes. This paper deals with a fundamental methodological issue relating to the use of such data. This study investigates the question of whether, in doing analyses involving different areas, the estimating equations should be weighted by the populations of those areas. It is argued that the correct answer to that question turns on some deep epistemological issues that have been little considered in the public health literature. DESIGN: To illustrate the issue, an example is presented that estimates entitlements to primary physician visits in Manitoba, Canada based on age/gender and socioeconomic status using both population weighted and unweighted regression analyses. SETTING AND SUBJECTS: The entire population of the province furnish the data. Primary care visits to physicians based on administrative data, demographics and a measure of socioeconomic status (SERI), based on census data, constitute the measures. RESULTS: Significant differences between weighted and unweighted analyses are shown to emerge, with the weighted analyses biasing entitlements towards the more populous and advantaged population. CONCLUSIONS: The authors endorse the position that, in certain problems, data analyses involving population aggregates unweighted by population size are more appropriate and normatively justifiable than are analyses weighted by population. In particular, when the aggregated units make sense, theoretically, as units, it is more appropriate to carry out the analyses without weighting by the size of the units. Unweighted analyses yield more valid estimations.
Citation Key354