title: Combining statistics from two national complex surveys to estimate injury rates per hour exposed and variance by activity in the USA.
abstract: A common issue in descriptive injury epidemiology is that in order to calculate injury rates that account for the time spent in an activity, both injury cases and exposure time of specific activities need to be collected. In reality, few national surveys have this capacity. To address this issue, we combined statistics from two different national complex surveys as inputs for the numerator and denominator to estimate injury rate, accounting for the time spent in specific activities and included a procedure to estimate variance using the combined surveys.
  
  
  
  The 2010 National Health Interview Survey (NHIS) was used to quantify injuries, and the 2010 American Time Use Survey (ATUS) was used to quantify time of exposure to specific activities. The injury rate was estimated by dividing the average number of injuries (from NHIS) by average exposure hours (from ATUS), both measured for specific activities. The variance was calculated using the 'delta method', a general method for variance estimation with complex surveys.
  
  
  
  Among the five types of injuries examined, 'sport and exercise' had the highest rate (12.64 injuries per 100 000 h), followed by 'working around house/yard' (6.14), driving/riding a motor vehicle (2.98), working (1.45) and sleeping/resting/eating/drinking (0.23). The results show a ranking of injury rate by activity quite different from estimates using population as the denominator.
  
  
  
  Our approach produces an estimate of injury risk which includes activity exposure time and may more reliably reflect the underlying injury risks, offering an alternative method for injury surveillance and research.
authors.affiliation: Center for Injury Epidemiology, Liberty Mutual Research Institute for Safety, Hopkinton, Massachusetts, USA.|Environmental and Occupational Medicine and Epidemiology Program, Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
authors.forename: Tin-Chi
authors.initials: TC
authors.lastname: Lin
authors.affiliation: Center for Injury Epidemiology, Liberty Mutual Research Institute for Safety, Hopkinton, Massachusetts, USA.
authors.forename: Helen R
authors.identifier: 0000-0002-4143-6340
authors.initials: HR
authors.lastname: Marucci-Wellman
authors.affiliation: Center for Injury Epidemiology, Liberty Mutual Research Institute for Safety, Hopkinton, Massachusetts, USA.
authors.forename: Joanna L
authors.initials: JL
authors.lastname: Willetts
authors.affiliation: Center for Injury Epidemiology, Liberty Mutual Research Institute for Safety, Hopkinton, Massachusetts, USA.
authors.forename: Melanye J
authors.initials: MJ
authors.lastname: Brennan
authors.affiliation: Center for Injury Epidemiology, Liberty Mutual Research Institute for Safety, Hopkinton, Massachusetts, USA.|Department of Family Medicine and Community Health, University of Massachusetts Medical School, Worcester, Massachusetts, USA.
authors.forename: Santosh K
authors.initials: SK
authors.lastname: Verma
mesh_terms: D000061:Accidents, Home / Q000517:prevention & control / Q000706:statistics & numerical data*; D000062:Accidents, Occupational / Q000517:prevention & control / Q000706:statistics & numerical data*; D000063:Accidents, Traffic / Q000517:prevention & control / Q000706:statistics & numerical data*; D000704:Analysis of Variance; D001265:Athletic Injuries / Q000453:epidemiology* / Q000517:prevention & control; D005260:Female; D006306:Health Surveys; D006801:Humans; D008297:Male; D008875:Middle Aged; D009309:National Center for Health Statistics, U.S.; D011634:Public Health; D012307:Risk Factors; D014481:United States / Q000453:epidemiology