Assessment of critical exposure and outcome windows in time-to-event analysis with application to air pollution and preterm birth study

Biostatistics

Volumn 16, Issue 3, 2015, Pages 509-521

  Chang, Howard H ^a   Warren, Joshua L ^a   Darrow, Lnydsey A ^b   Reich, Brian J ^b   Waller, Lance A ^c  

^a EMORY UNIVERSITY   (United States)

^b YALE UNIVERSITY   (United States)

^c NORTH CAROLINA STATE UNIVERSITY   (United States)

Author keywords

Air pollution; Fine particulate matter; Joint effects; Preterm birth; Time dependent exposure; Time toevent model; Time varying effect

Indexed keywords

PARTICULATE MATTER;

ADVERSE EFFECTS; AIR POLLUTION; BAYES THEOREM; BIOSTATISTICS; COMPUTER SIMULATION; FEMALE; GEORGIA; HUMAN; NEWBORN; PARTICULATE MATTER; PREGNANCY; PREMATURE BIRTH; PRENATAL EXPOSURE; RISK FACTOR; STATISTICAL MODEL;

AIR POLLUTION; BAYES THEOREM; BIOSTATISTICS; COMPUTER SIMULATION; FEMALE; GEORGIA; HUMANS; INFANT, NEWBORN; MODELS, STATISTICAL; PARTICULATE MATTER; PREGNANCY; PREMATURE BIRTH; PRENATAL EXPOSURE DELAYED EFFECTS; RISK FACTORS;

EID: 84936767000     PISSN: 14654644     EISSN: 14684357     Source Type: Journal    
DOI: 10.1093/biostatistics/kxu060     Document Type: Article

References (26)

1. BELL, M. L. AND BELANGER, K. (2012). Review of research on residential mobility during pregnancy: consequences for assessment of prenatal environmental exposures. Journal of Exposure Science and Environmental Epidemiology 22, 429-438
2. BOSETTI, C., NIEUWENHUIJSEN, M. J., GALLUS, S., CIPRIANI, S., LA VECCHIA, C. AND PARAZZINI, F. (2010). Ambient particulate matter and preterm birth or birth weight: a review of the literature. Archives of Toxicology 348, 447-460
3. BUCHHOLZ, A. AND SAUERBREI, W. (2011). Comparison of procedures to assess non-linear and time-varying effects in multivariable models for survival data. Biometrical Journal 53, 308-331
4. CHANG, H. H., FUENTES M. AND FREY, H. C. (2012). Time series analysis of personal exposure to ambient PM2.5 and mortality using an exposure simulator. Journal of Exposure Science and Environmental Epidemiology 22, 483-488
5. CHANG, H. H., REICH, J. B. AND MIRANDA, M. L. (2012). Time-to-event analysis of fine particle air pollution and preterm birth: results from North Carolina, 2001-2005. American Journal of Epidemiology 175, 91-98
6. CHANG, H. H., REICH, J. B. AND MIRANDA, M. L. (2013). A spatial time-to-event approach for estimating associations between air pollution and preterm birth. Journal of the Royal Statistical Society Series C 62, 167-179
7. FAHRMEIR, L. AND KNORR-HELD, L. (1997). Dynamic discrete time duration models: estimation via Markov chain Monte Carlo. Sociological Methodology 27, 417-452
8. GENEREUX, M., AUGER, A., GONEAU, M. AND DAINIEL, M. (2008). Neighbourhood socioeconomic status, maternal education and adverse birth outcomes among mothers living near highways. Journal of Epidemiology&Community Health 62, 695-700
9. GOLDENBERG, R. L., CULHANE, J. F., IAMS, J. D. AND ROMERO, R. (2008). Epidemiology and causes of preterm birth. Lancet 9606, 75-94
10. HANEUSE, S. J., RUDSER, K. D. AND GILLEN, D. L. (2008). The separation of timescales in Bayesian survival modeling of the time-varying effect of a time-dependent exposure. Biostatistics 9, 400-410
11. HE, J., MCGEE, D. L. AND NIU, X. (2012). Application of the Bayesian dynamic survival model in medicine. Statistics in Medicine 29, 347-360
12. HEATON, M. J. AND PENG, R. D. (2012). Flexible distributed lag models using random functions with application to estimating mortality displacement from heat-related deaths. Journal of Agricultural, Biological, and Environmental Statistics 17, 313-331
13. MCKEAGUE, I. W. AND TIGHIOUART, M. (2000). Bayesian estimators for conditional hazard functions. Biometrics 56, 1007-1015
14. MOSTER, D., LIE, R. T. AND MARKESTAD, T. (2008). Long-term medical and social consequences of preterm birth. New England Journal of Medicine 359, 262-273
15. MUSTAFA, G. AND DAVID, R. (2001). Comparative accuracy of clinical estimate versus menstrual gestational age in computerized birth certificates. Public Health Report 116, 15-21
16. R CORE TEAM. (2014). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org
17. SAIGAL, S. AND DOYLE, L. W. (2008). An overview of mortality and sequelae of preterm birth from infancy to adulthood. Lancet 371, 261-269
18. SARNAT, S. E., SARNAT, J. A., MULHOLLAND, J., ISAKOV, V., OZKAYNAK, H., CHANG, H. H., KLEIN, M. AND TOLBERT, P. E. (2014). Application of alternative spatiotemporal metrics of ambient air pollution exposure in a time-series epidemiological study in Atlanta. Journal of Exposure Science and Environmental Epidemiology 23, 598-605
19. SCHWARTZ, J. (2000). The distributed lag between air pollution and daily deaths. Epidemiology 11, 320-326
20. SPIEGELHALTER, D. J., BEST, N. G., CARLIN, B. P. AND VAN DER LIND, A. (2002). Bayesian measures of model complexity and fit (with discussion). Journal of the Royal Statistical Society, Series B 64, 583-639
21. STRAND, L., BARNETT, A. AND TONG, S. (2011b).Methodological challengeswhen estimating the effects of season and seasonal exposures on birth outcomes. BMC Medical Research Methodology 11, doi:10.1186/1471-2288-11-49
22. SUH, Y. J., KIM, H., SEO, J. H., PARK, H., KIM, Y. J., HONG, Y. C. AND HA, E. H. Different effects of PM10 exposure on preterm birth by gestational period estimated from time-dependent survival analyses. International Archives of Occupational and Environmental Health 82, 613-621
23. U.S. EPA. Integrated Science Assessment for Particulate Matter (Final Report). U.S. Environmental Protection Agency, Washington, DC, EPA/600/R-08/139F
24. WARREN, J., FUENTES, M., HERRING, A. AND LANGLOIS, P. (2012). Spatial-temporal modeling of the association between air pollution exposure and preterm birth: identifying critical windows of exposure. Biometrics 68, 1157-1167
25. WELTY, L. J., PENG, R. D., ZEGER, S. L. AND DOMINICI, F. (2009). Bayesian distributed lag models: estimating effects of particulate matter air pollution on daily mortality. Biometrics 65, 282-291
26. ZANOBETTI, A., WAND, M. P., SCHWARTZ, J. AND RYAN, L. M. (2000). Generalized additive distributed lag models: quantifying mortality displacement. Biostatistics 1, 179-292