The Quality of Modern Cross-Sectional Ecologic Studies: A Bibliometric Review

被引:56
作者
Dufault, Brenden [1 ]
Klar, Neil [2 ]
机构
[1] Univ Manitoba, Fac Med, Dept Community Hlth Sci, Winnipeg, MB R3E 0W3, Canada
[2] Univ Western Ontario, Dept Epidemiol & Biostat, Schulich Sch Med & Dent, London, ON, Canada
关键词
cross-sectional studies; ecological models; epidemiologic methods; research design; review; EPIDEMIOLOGY; REGRESSION; TRIALS;
D O I
10.1093/aje/kwr241
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
The ecologic study design is routinely used by epidemiologists in spite of its limitations. It is presently unknown how well the challenges of the design are dealt with in epidemiologic research. The purpose of this bibliometric review was to critically evaluate the characteristics, statistical methods, and reporting of results of modern cross-sectional ecologic papers. A search through 6 major epidemiology journals identified all cross-sectional ecologic studies published since January 1, 2000. A total of 125 articles met the inclusion requirements and were assessed via common evaluative criteria. It was found that a considerable number of cross-sectional ecologic studies use unreliable methods or contain statistical oversights; most investigators who adjusted their outcomes for age or sex did so improperly (64%), statistical validity was a potential issue for 20% of regression models, and simple linear regression was the most common analytic approach (31%). Many authors omitted important information when discussing the ecologic nature of their study (31%), the choice of study design (58%), and the susceptibility of their research to the ecological fallacy (49%). These results suggest that there is a need for an international set of guidelines that standardizes reporting on ecologic studies. Additionally, greater attention should be given to the relevant biostatistical literature.
引用
收藏
页码:1101 / 1107
页数:7
相关论文
共 22 条
[1]  
Anselin L., 2002, Political Analysis, V10, P276, DOI [10.1093/pan/10.3.276, DOI 10.1093/PAN/10.3.276]
[2]   What you see may not be what you get: A brief, nontechnical introduction to overfitting in regression-type models [J].
Babyak, MA .
PSYCHOSOMATIC MEDICINE, 2004, 66 (03) :411-421
[3]   Improving the quality of reporting of randomized controlled trials - The CONSORT statement [J].
Begg, C ;
Cho, M ;
Eastwood, S ;
Horton, R ;
Moher, D ;
Olkin, I ;
Pitkin, R ;
Rennie, D ;
Schulz, KF ;
Simel, D ;
Stroup, DF .
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 1996, 276 (08) :637-639
[4]   SPATIAL CORRELATION IN ECOLOGICAL ANALYSIS [J].
CLAYTON, DG ;
BERNARDINELLI, L ;
MONTOMOLI, C .
INTERNATIONAL JOURNAL OF EPIDEMIOLOGY, 1993, 22 (06) :1193-1202
[5]  
Duncan OtisDudley., 1961, STAT GEOGRAPHY PROBL
[6]   ECOLOGICAL BIAS, CONFOUNDING, AND EFFECT MODIFICATION [J].
GREENLAND, S ;
MORGENSTERN, H .
INTERNATIONAL JOURNAL OF EPIDEMIOLOGY, 1989, 18 (01) :269-274
[7]   ECOLOGIC STUDIES - BIASES, MISCONCEPTIONS, AND COUNTEREXAMPLES [J].
GREENLAND, S ;
ROBINS, J .
AMERICAN JOURNAL OF EPIDEMIOLOGY, 1994, 139 (08) :747-760
[8]  
Haneuse S., 2004, Ecological inference: new methodological strategies, P266
[9]   The quality of reports of randomised trials in 2000 and 2006: comparative study of articles indexed in PubMed [J].
Hopewell, Sally ;
Dutton, Susan ;
Yu, Ly-Mee ;
Chan, An-Wen ;
Altman, Douglas G. .
BMJ-BRITISH MEDICAL JOURNAL, 2010, 340 :c723
[10]   Homicide on the job: Workplace and community determinants [J].
Loomis, D ;
Wolf, SH ;
Runyan, CW ;
Marshall, SW ;
Butts, JD .
AMERICAN JOURNAL OF EPIDEMIOLOGY, 2001, 154 (05) :410-417