Does More Accurate Exposure Prediction Necessarily Improve Health Effect Estimates?

被引：88

作者：

Szpiro, Adam A. ^{[1
]}

Paciorek, Christopher J. ^{[2
,3
]}

Sheppard, Lianne ^{[1
,4
]}

机构：

[1] Univ Washington, Dept Biostat, Seattle, WA 98195 USA

[2] Harvard Univ, Sch Publ Hlth, Dept Biostat, Boston, MA 02115 USA

[3] Univ Calif Berkeley, Dept Stat, Berkeley, CA 94720 USA

[4] Univ Washington, Dept Environm & Occupat Hlth Sci, Seattle, WA 98195 USA

来源：

EPIDEMIOLOGY | 2011年 / 22卷 / 05期

基金：

美国国家环境保护局;

关键词：

AIR-POLLUTION; LONG;

D O I：

10.1097/EDE.0b013e3182254cc6

中图分类号：

R1 [预防医学、卫生学];

学科分类号：

1004 ; 120402 ;

摘要：

A unique challenge in air pollution cohort studies and similar applications in environmental epidemiology is that exposure is not measured directly at subjects' locations. Instead, pollution data from monitoring stations at some distance from the study subjects are used to predict exposures, and these predicted exposures are used to estimate the health effect parameter of interest. It is usually assumed that minimizing the error in predicting the true exposure will improve health effect estimation. We show in a simulation study that this is not always the case. We interpret our results in light of recently developed statistical theory for measurement error, and we discuss implications for the design and analysis of epidemiologic research. (Epidemiology 2011; 22: 680-685)

引用

页码：680 / 685

页数：6

共 19 条

[1]

Brauer Michael, 2010, Proc Am Thorac Soc, V7, P111, DOI 10.1513/pats.200908-093RM

[2]

Carroll R. J., 2006, MEASUREMENT ERROR NO

[3] Modelling spatio-temporal variation in exposure to particulate matter: a two-stage approach [J].

Fanshawe, T. R. ;

Diggle, P. J. ;

Rushton, S. ;

Sanderson, R. ;

Lurz, P. W. W. ;

Glinianaia, S. V. ;

Pearce, M. S. ;

Parker, L. ;

Charlton, M. ;

Pless-Mulloli, T. .

ENVIRONMETRICS, 2008, 19 (06) :549-566

[4]

Friedman J., 2001, The Elements of Statistical Learning: Data Mining, Inference, and Prediction, V1

[5] Measurement error caused by spatial misalignment in environmental epidemiology [J].

Gryparis, Alexandros ;

Paciorek, Christopher J. ;

Zeka, Ariana ;

Schwartz, Joel ;

Coull, Brent A. .

BIOSTATISTICS, 2009, 10 (02) :258-274

[6] A review of land-use regression models to assess spatial variation of outdoor air pollution [J].

Hoek, Gerard ;

Beelen, Rob ;

de Hoogh, Kees ;

Vienneau, Danielle ;

Gulliver, John ;

Fischer, Paul ;

Briggs, David .

ATMOSPHERIC ENVIRONMENT, 2008, 42 (33) :7561-7578

[7] Spatial analysis of air pollution and mortality in Los Angeles [J].

Jerrett, M ;

Burnett, RT ;

Ma, RJ ;

Pope, CA ;

Krewski, D ;

Newbold, KB ;

Thurston, G ;

Shi, YL ;

Finkelstein, N ;

Calle, EE ;

Thun, MJ .

EPIDEMIOLOGY, 2005, 16 (06) :727-736

[8] A review and evaluation of intraurban air pollution exposure models [J].

Jerrett, M ;

Arain, A ;

Kanaroglou, P ;

Beckerman, B ;

Potoglou, D ;

Sahsuvaroglu, T ;

Morrison, J ;

Giovis, C .

JOURNAL OF EXPOSURE ANALYSIS AND ENVIRONMENTAL EPIDEMIOLOGY, 2005, 15 (02) :185-204

[9] Establishing an air pollution monitoring network for intra-urban population exposure assessment: A location-allocation approach [J].

Kanaroglou, PS ;

Jerrett, M ;

Morrison, J ;

Beckerman, B ;

Arain, MA ;

Gilbert, NL ;

Brook, JR .

ATMOSPHERIC ENVIRONMENT, 2005, 39 (13) :2399-2409

[10] Health Effects of Long-term Air Pollution Influence of Exposure Prediction Methods [J].

Kim, Sun-Young ;

Sheppard, Lianne ;

Kim, Ho .

EPIDEMIOLOGY, 2009, 20 (03) :442-450

← 1 2 →