October 2007
Sun Mon Tue Wed Thu Fri Sat
  1 2 3 4 5 6
7 8 9 10 11 12 13
14 15 16 17 18 19 20
21 22 23 24 25 26 27
28 29 30 31      

Authors' Committee


Matt Blackwell (Gov)


Martin Andersen (HealthPol)
Kevin Bartz (Stats)
Deirdre Bloome (Social Policy)
John Graves (HealthPol)
Rich Nielsen (Gov)
Maya Sen (Gov)
Gary King (Gov)

Weekly Research Workshop Sponsors

Alberto Abadie, Lee Fleming, Adam Glynn, Guido Imbens, Gary King, Arthur Spirling, Jamie Robins, Don Rubin, Chris Winship

Weekly Workshop Schedule

Recent Comments

Recent Entries



SMR Blog
Brad DeLong
Cognitive Daily
Complexity & Social Networks
Developing Intelligence
The Education Wonks
Empirical Legal Studies
Free Exchange
Health Care Economist
Junk Charts
Language Log
Law & Econ Prof Blog
Machine Learning (Theory)
Marginal Revolution
Mixing Memory
Mystery Pollster
New Economist
Political Arithmetik
Political Science Methods
Pure Pedantry
Science & Law Blog
Simon Jackman
Social Science++
Statistical modeling, causal inference, and social science



Powered by
Movable Type 4.24-en

« October 16, 2007 | Main | October 18, 2007 »

17 October 2007

How tall are you? No, really...

Continuing on the topic of self-reported health data, and how to correct for reporting (and other) biases, here an interesting paper on height and weight in the US. Those two measures have received a lot of interest in the past years, not least as components of the body-mass index BMI which is used to estimate the prevalence of obesity. BMI itself is not a great measure (more on that another day) but at least it’s relatively easy to collect via telephone and in-person interviews. Of course some people make mistakes while reporting their own vital measures, and some might do so systematically: a height of 6 foot sounds like a good height to have even to me, and I tend to think in the metric system!

Anyway, the paper by Ezzati et al examines the issue of systematic misreporting. They note that existing smaller-scale studies on this issue might in fact under-estimate the bias because of their design. People might limit their misreporting if they are measured before or after reporting their vitals, which is a challenge for validation studies. And participation might systematically differ with the interview modes of the analysis studies and a general health surveys (e.g. in-person versus telephone interviews) so that the studies are not directly comparable to population-level surveys.

The idea of the paper is to employ two nationally representative surveys to compare three different kinds of measurement for height and weight, by age group and gender. The first survey is the National Health and Nutrition Examination Survey NHANES which collects self-reported information through in-person interviews, and also through medical examination. The second survey is the Behavior and Risk Factor Surveillance Survey BRFFS, an annual cross-sectional telephone survey that is state-level representative and features widely in policy discussions.

The comparisons between the surveys might confirm your priors on misreporting. On average, women under-report their weight and men under 65 tend to over-report their height. The authors find that state-level obesity measures based on the BRFFS are too low – they re-calculate that a number of states in fact had obesity prevalences above 30% in 2000. Of course this is not a perfectly clean assessment, because the NHANES participants might have anticipated the clinical examination a few weeks after the in-person interview. But at the least this study is a good reminder that people do systematically misreport for some reason, and that analysts should treat self-reported BMI carefully.

Posted by Sebastian Bauhoff at 10:23 PM