{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T18:42:40Z","timestamp":1769193760136,"version":"3.49.0"},"reference-count":32,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2013,12,10]],"date-time":"2013-12-10T00:00:00Z","timestamp":1386633600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Biometrics"],"published-print":{"date-parts":[[2014,3]]},"abstract":"<jats:title>Summary<\/jats:title><jats:sec><jats:label\/><jats:p>Traditional studies of short\u2010term air pollution health effects use time series data, while cohort studies generally focus on long\u2010term effects. There is increasing interest in exploiting individual level cohort data to assess short\u2010term health effects in order to understand the mechanisms and time scales of action. We extend semiparametric regression methods used to adjust for unmeasured confounding in time series studies to the cohort setting. Time series methods are not directly applicable since cohort data are typically collected over a prespecified time period and include exposure measurements on days without health observations. Therefore, long\u2010time asymptotics are not appropriate, and it is possible to improve efficiency by exploiting the additional exposure data. We show that flexibility of the semiparametric adjustment model should match the complexity of the trend in the health outcome, in contrast to the time series setting where it suffices to match temporal structure in the exposure. We also demonstrate that pre\u2010adjusting exposures concurrent with the health endpoints using trends in the complete exposure time series results in unbiased health effect estimation and can improve efficiency without additional confounding adjustment. A recently published article found evidence of an association between short\u2010term exposure to ambient fine particulate matter (PM<jats:sub>2.5<\/jats:sub>) and retinal arteriolar diameter as measured by retinal photography in the Multi\u2010Ethnic Study of Atherosclerosis (MESA). We reanalyze the data from this article in order to compare the methods described here, and we evaluate our methods in a simulation study based on the MESA data.<\/jats:p><\/jats:sec>","DOI":"10.1111\/biom.12125","type":"journal-article","created":{"date-parts":[[2013,12,10]],"date-time":"2013-12-10T14:26:40Z","timestamp":1386685600000},"page":"164-174","source":"Crossref","is-referenced-by-count":13,"title":["Estimating acute air pollution health effects from cohort study data"],"prefix":"10.1093","volume":"70","author":[{"given":"Adam A.","family":"Szpiro","sequence":"first","affiliation":[{"name":"Department of Biostatistics University of Washington Seattle, Washington U.S.A."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lianne","family":"Sheppard","sequence":"additional","affiliation":[{"name":"Departments of Biostatistics and Environmental and Occupational Health Sciences University of Washington Seattle, Washington U.S.A."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sara D.","family":"Adar","sequence":"additional","affiliation":[{"name":"Department of Epidemiology University of Michigan Ann Arbor, Michigan U.S.A."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joel D.","family":"Kaufman","sequence":"additional","affiliation":[{"name":"Department of Environmental and Occupational Health Sciences University of Washington Seattle, Washington U.S.A."}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2013,12,10]]},"reference":[{"key":"e_1_2_11_2_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pmed.1000372"},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.1093\/aje\/kwf113"},{"key":"e_1_2_11_4_1","doi-asserted-by":"publisher","DOI":"10.1161\/CIR.0b013e3181dbece1"},{"key":"e_1_2_11_5_1","doi-asserted-by":"crossref","DOI":"10.1093\/oso\/9780198524847.001.0001","author":"Diggle P.","year":"2002","journal-title":"Analysis of Longitudinal Data"},{"key":"e_1_2_11_6_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJM199312093292401"},{"key":"e_1_2_11_7_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1751-5823.2003.tb00195.x"},{"key":"e_1_2_11_8_1","doi-asserted-by":"publisher","DOI":"10.1198\/016214504000000656"},{"key":"e_1_2_11_9_1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.295.10.1127"},{"key":"e_1_2_11_10_1","unstructured":"National Ambient Air Quality Standards 2006 Environmental Protection Agency"},{"key":"e_1_2_11_11_1","doi-asserted-by":"publisher","DOI":"10.1093\/ije\/dyg246"},{"key":"e_1_2_11_12_1","doi-asserted-by":"publisher","DOI":"10.1214\/009053604000001048"},{"key":"e_1_2_11_13_1","doi-asserted-by":"publisher","DOI":"10.1198\/tast.2010.10052"},{"key":"e_1_2_11_14_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-92407-6"},{"key":"e_1_2_11_15_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.1889"},{"key":"e_1_2_11_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.annepidem.2008.06.004"},{"key":"e_1_2_11_17_1","doi-asserted-by":"publisher","DOI":"10.1093\/aje\/kws169"},{"key":"e_1_2_11_18_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/73.1.13"},{"key":"e_1_2_11_19_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa054409"},{"key":"e_1_2_11_20_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-985X.2006.00410.x"},{"key":"e_1_2_11_21_1","first-page":"1","article-title":"the R\u00a0Development Core Team","author":"Pinheiro J.","year":"2010","journal-title":"nlme: Linear and Nonlinear Mixed Effects Models"},{"key":"e_1_2_11_22_1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.287.9.1132"},{"key":"e_1_2_11_23_1","unstructured":"R: A Language and Environment for Statistical Computing 2010 R Development Core Team"},{"key":"e_1_2_11_24_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJM200012143432401"},{"key":"e_1_2_11_25_1","doi-asserted-by":"publisher","DOI":"10.2307\/3315405"},{"key":"e_1_2_11_26_1","doi-asserted-by":"publisher","DOI":"10.1097\/00001648-200005000-00016"},{"key":"e_1_2_11_27_1","first-page":"198","article-title":"Comment on: Model choice in time series studies of air pollution and mortality","volume":"169","author":"Schwartz J.","year":"2006","journal-title":"Journal of the Royal Statistical Society, Series A"},{"key":"e_1_2_11_28_1","doi-asserted-by":"publisher","DOI":"10.1097\/00001648-199901000-00006"},{"key":"e_1_2_11_29_1","doi-asserted-by":"publisher","DOI":"10.1002\/env.1014"},{"key":"e_1_2_11_30_1","article-title":"Measurement error in two\u2010stage analyses, with application to air pollution epidemiology","author":"Szpiro A. 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