Healthy volunteer effect and cardiovascular risk.

REFERENCES 1. Murray CJ, Kulkarni SC, Michaud C, et al. Eight Americas: investigating mortality disparities across races, counties, and race-counties in the United States. PLoS Med. 2006;3:e260. 2. National Center for Health Statistics. Health, United States, 2012. 2013. Available at: http:// www.cdc.gov/nchs/hus.htm. Accessed 24 December 2013. 3. Gawande A. The hot spotters. New Yorker. 2011;86:41. 4. US Department of Health and Human Services. Healthy People 2020: General Health Status Topics and Objectives. Washington, DC: US Department of Health and Human Services; 2011. 5. Howard-Pitney B, Winkleby MA. Chewing tobacco: who uses and who quits? Findings from NHANES III, 1988–1994. Am J Public Health. 2002;92:250–256. 6. Lewis RJ. An introduction to classification and regression tree (CART) analysis. In: Annual Meeting of the Society for Academic Emergency Medicine. San Francisco, CA: Citeseer; 2000:1–14. 7. Breiman L. Random forests. Mach Learn. 2001;45:5–32. 8. Garge NR, Bobashev G, Eggleston B. Random forest methodology for model-based recursive partitioning: the mobForest package for R. BMC Bioinformatics. 2013;14:125. in such studies because relatively good health status is required for a person to agree to undergo the examinations. This implies that persons enrolled in a study requiring active participation are healthier than those who declined to participate. It is thus unclear whether the cardiovascular risk distributions among study participants adequately reflect the risk distribution of the source population. We aimed to quantify the consequences of this “healthy volunteer effect.” Within the Rotterdam Study,1 a prospective population-based cohort, we investigated the association between participation in the third examination (1997–1999), all-cause mortality,2 and coronary risk (Framingham point score; assessed at enrollment 1990–1993)3 (see eAppendix, http://links.lww.com/ EDE/A779 for details). Of 5423 eligible invitees (mean age 73.5 years; 39% men), 87% participated, of whom 76% visited the research center (eTable 1, http://links.lww.com/EDE/A779). Nonparticipants had lost interest (50%), had physical complaints (34%), or considered themselves too old to participate (12%; mean age 86.9 years). Persons who were elderly, women, less educated, and with higher levels of specific cardiovascular risk factors were less likely to participate (eTable 1). Nonparticipation was strongly associated with mortality (hazard ratio [HR] = 1.71 [95% confidence interval (CI) = 1.56–1.88]). This was most pronounced shortly after invitation (0–3 months, HR = 4.85 [2.43–9.71]), with a diminishing healthy volunteer effect during follow-up (test for trend, P < 0.001) (Table). Every percentagepoint increase in coronary risk yielded an approximately 3% lower probability of participating (eTable 2, http:// links.lww.com/EDE/A779). Those categorized as “high risk” were least likely to participate (odds ratio = 0.56 [95% CI = 0.45–0.71]; eTable 2). There was a slightly lower proportion of highrisk persons among the examined participants compared with all invitees