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How healthy are survey respondents compared with the general population? Using survey-linked death records to compare mortality outcomes

Keyes, Katherine M.; Rutherford, Caroline; Popham, Frank; Martins, Silvia S.; Gray, Linsay
doi: 10.1097/EDE.0000000000000775
Original Article: PDF Only

Background:

National surveys are used to capture US health trends and set clinical guidelines, yet the sampling frame often includes those in non-institutional households, potentially missing those most vulnerable for poor health. Declining response rates in national surveys also represent a challenge, and existing inputs to survey weights have limitations. We compared mortality rates between those who respond to surveys and the general population over time.

Methods:

Survey respondents from twenty waves of the National Health Interview Survey from 1990 through 2009 who have been linked to death records through 31 December 2011 were included. For each cohort in the survey, we estimated their mortality rates along with that cohort’s mortality rate in the census population using vital statistics records and differences were examined using Poisson models.

Results:

In all years, survey respondents had lower mortality rates compared with the general population, when data were both weighted and unweighted. Among men, survey respondents in the weighted sample had 0.86 (95% C.I. 0.853-0.868) times the mortality rate of the general population (among women, RR=0.887; 95% C.I. 0.879-0.895). Differences in mortality are evident along all points of the life course. Differences have remained relatively stable over time.

Conclusion:

Survey respondents have lower death rates than the general US population, suggesting that they are a systematically healthier source population. Incorporating non-household samples and revised weighting strategies to account for sample frame exclusion and non-response may allow for more rigorous estimation of the US population’s health.

This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Conflicts of interest: None

Acknowledgements: We would like to acknowledge the Columbia University Calderone Prize for Junior Faculty which provided funding for this project to Dr. Keyes. FP and LG are funded by the Medical Research Council, UK and Chief Scientist’s Office, Scottish Government (MC_UU_12017/13 and SPHSU13), as part of the core funding for the MRC/CSO Social & Public Health Sciences Unit, University of Glasgow, UK.

Data and code for replication: Full SAS and Stata code for these analyses are included as an online supplement, and data files are available by request to the corresponding author.

Corresponding author: Katherine M. Keyes, PhD, Associate Professor of Epidemiology, Columbia University Department of Epidemiology, Mailman School of Public Health, 722 West 168th Street, Suite 503, New York, NY 10032, Tel: (212) 304-5652, Email: kmk2104@columbia.edu

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