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What Can Ecological Studies Tell Us About Death? Yehuda Neumark

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What Can Ecological Studies Tell Us About Death? Yehuda Neumark Neumark Israel Journal of Health Policy Research (2017) 6:52 DOI 10.1186/s13584-017-0176-x COMMENTARY Open Access What can ecological studies tell us about death? Yehuda Neumark Abstract: Using an ecological study design, Gordon et al. (Isr J Health Policy Res 6:39, 2017) demonstrate variations in mortality patterns across districts and sub-districts of Israel during 2008–2013. Unlike other epidemiological study designs, the units of analysis in ecological studies are groups of people, often defined geographically, and the exposures and outcomes are aggregated, and often known only at the population-level. The ecologic study has several appealing characteristics (suchasrelianceonpublic-domain anonymous data) alongside a number of important potential limitations including the often mentioned ‘ecological fallacy’.Advantagesand disadvantages of the ecological design are described briefly below. Keywords: Ecological fallacy, Ecological studies, Epidemiology, Mortality, Study design Main text In this journal, Gordon et al. [4] employ an ecological "The aim of epidemiology is to decipher nature with re- design to demonstrate variations in mortality patterns spect to human health and disease, and no one should across districts and sub-districts of Israel during the underestimate the complexities of epidemiological research" five-year period of 2008–2013. Standardized mortality [1]. To achieve this lofty and complex goal, the epide- ratios (SMRs) reveal a 25% excess of kidney disease re- miologic investigative toolbox contains various study lated deaths in the Haifa district, for example, while the methodologies including individual-based experimental risk of death from influenza/pneumonia is 25% lower designs (e.g., randomized controlled trial), individual- there than the national average. Some attenuation of re- based observational designs (e.g., prospective cohort gional differences is noted upon adjusting for “ethnicity” study, retrospective case-control study) and group-based, (Arabs; Jews by continent of birth) leading the authors or ecological studies. As articulated by Susser [2], the aim to conclude that "factors associated with ethnicity may of ecological analysis is "to study health in an environmen- affect mortality more than regional factors". The authors tal context… to understand how context affects the health also correlate SMRs with selected district-level socio- of persons and groups through selection, distribution, economic characteristics, and demonstrate significant in- interaction adaptation, and other responses". verse correlations (−0.63–0.71) between (sub)district-average In an ecological study, the units of analysis and com- years of education and all-cause mortality in males and parison are groups of people often defined geographically females, cancer-related death and diabetes-related (such as an administrative region or an entire country), death. Significant negative correlations (−0.52–0.57) are and the exposures and outcomes are aggregated and also found with the percent of district residents who known at the population-level only. Morgenstern [3] cate- purchased supplementary health insurance and cancer, gorized ecologic studies into ‘exploratory’ studies that heart and diabetes related mortality. The (sub)district- compare rates of disease or other outcomes across groups level prevalence of smoking correlates positively with in a descriptive fashion and do not attempt to correlate SMRs for diabetes-related mortality and all-cause mor- these rates with exposure data, and ‘multiple-group com- tality in males (0.59) and females (0.63). parison’ studies that explore associations between average The ecologic study has several appealing characteris- exposure levels and rates of the outcome across groups.1 tics, primary of which is the reliance on anonymous (often public domain) data that cover large geographical areas, even nationwide. This is particularly pertinent Correspondence: [email protected] when individual-level data is lacking or not readily avail- Braun School of Public Health and Community Medicine, Hebrew University of Jerusalem, P.O. Box 1227, 99112102 Jerusalem, Israel able, and even when such data can be collected, the use © The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Neumark Israel Journal of Health Policy Research (2017) 6:52 Page 2 of 5 of secondary data sources has an obvious advantage in The major, and most often mentioned limitation in- terms of cost and time.2 herent in testing etiologic hypotheses through ecologic Another advantage of using aggregated data is the analyses is the potential of making a “mistaken assump- avoidance of measurement error of individual-level ex- tion that a statistical association observed between two posures. Valid information about personal consumption group-level variables is equal to the association between of alcoholic beverages, for example, may be difficult to the corresponding variables at the individual level” obtain, whereas aggregated data (e.g., from alcohol tax (Gail & Benichou, 2001). This potential bias is known revenue records) may provide more accurate information. as ‘ecological fallacy’ (sometimes referred to as ‘aggrega- This is certainly the case with air pollution exposures that tion bias’ or ‘cross-level bias’. are difficult to ascertain accurately at the individual The discordance, or at least lack of necessary concord- level, and are more feasibly measured via ambient air ance, between individual-level and ecological-level corre- monitoring. lations, was first described mathematically by Robinson Ecological studies have been employed extensively to [9] in his seminal paper on ecological correlations. Rob- assess and explain regional variations in mortality, such inson used a classic 2*2 table approach to elegantly illus- as Lavados et al. [5] who found significant differences in trate that a given set of marginal frequencies (i.e., the age-adjusted stroke-related mortality across 13 adminis- disease/death rate and the prevalence of exposure) can trative regions in Chile. Merging data from the national be generated by a large set of internal frequencies (number death registry with individual-level data aggregated at the or rate of exposed and unexposed cases, for example). In a regional level, they concluded that socio-economic charac- group-based or ecological study design, the marginal fre- teristics, primarily poverty, explained 34% of the stroke- quencies are known, while the joint distribution of expos- related mortality variance across regions, and cardiovascu- ure and outcome variables remains unknown, leading lar risk factors (i.e., diabetes, sedentarism and overweight) Robinson to conclude "the only reasonable assumption is explained an additional 26% of the variability. that an ecological correlation is almost certainly not equal Ecological analyses have also been undertaken to exam- to its corresponding individual correlation" [9]. ine mortality patterns in Israel. Examining sub-district Despite Gordon et al.’s cautionary mention of ecological mortality variations using data from 1987 to 1994, fallacy, a presumption of a “causal” association between Ginsberg et al. [6] found elevated standardized mortal- education and mortality is implicit in their recommenda- ity ratios (SMR) adjusted for age, sex and ethnicity in tion to "increase the education level of all sectors of the the Haifa district for all cardiovascular diseases, liver population". Their concluding recommendations of "rais- disease, motor vehicle accidents and lung cancer. The ing the education level, reducing smoking, control of authors concluded that the observed regional mortality hypertension, encouraging healthy lifestyles and screening differences "may be due to socioeconomic, nutritional, for cancer", assume that because mortality is higher in dis- environmental, occupational, or health care factors". In tricts with larger exposure prevalence, it is those individ- 2008, responding to public concern about exposure to uals with fewer years of education, smokers, and/or those industrial park emissions in the south of Israel, Karakis who did not undergo screening, who died, or were at et al. [7] used an ecological approach to demonstrate a higher risk of death during the study period. This assump- correlation between mortality rates (1995–2001) and tion attributes to members of the group the characteristic residential proximity to the industrial park among the of the group [10]. While these are not unreasonable as- Bedouin population. More recently, in this journal, sumptions, they cannot be tested or supported using Goldberger & Haklai [8] demonstrated steady national aggregated data. declines in age-adjusted rates of “amenable deaths” (i.e., Part of the challenge in making cross-level inferences deaths that could be prevented by effective health care), relates to different underlying constructs being measured although regional variations persist. For example, for the by the “same” variable
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