Estimates of CAM use in this nationally representative sample were considerably lower than have been reported in previous surveys. Most CAM therapies are used by US adults in conjunction with conventional medical services.

BackgroundSurveys have generally found that individuals more likely to use complementary and alternative medicine are female, live in the western United States, are likely to have a health complaint, and have a higher socioeconomic status than do nonusers. What is not known is the extent to which those who use complementary and alternative medicine also engage in positive health behaviors, such as smoking cessation or increased physical activity and/or exhibit fewer health risk factors such as obesity. This has been identified as a key research question in a recent Institute of Medicine report. In the present study we sought to determine whether the use of complementary and alternative medicine is associated with health behaviors or risk factors known to impact on health status.MethodsThe current study is a cross-sectional regression analysis using data from the 2002 National Health Interview Survey. Data were collected in-person from 31,044 adults throughout the 50 states and the District of Columbia.ResultsAfter controlling for a range of other factors, we found that engaging in leisure-time physical activity, having consumed alcohol in one's life but not being a current heavy drinker, and being a former smoker are independently associated with the use of CAM. Obese individuals are slightly less likely to use CAM than individuals with a healthy body-mass index. No significant associations were observed between receipt of an influenza vaccine and CAM use.ConclusionThose engaging in positive health behaviors and exhibiting fewer health risk factors are more likely to use CAM than those who forgo positive health behaviors or exhibit more health risk factors. The fact that users of CAM tend to pursue generally healthy lifestyles suggests that they may be open to additional recommendations toward optimizing their health.

Results from the Joint Canada/United States Survey of Health (2002-2003) reveal that health status is relatively similar in the two countries, but income-related health disparities exist. Americans in the poorest income quintile are more likely to have poor health than their Canadian counterparts; there were no differences between the rich. In general, Canadians were more like insured Americans regarding access to services, and Canadians experienced fewer unmet needs overall. Despite higher U.S. levels of spending on health care, residents in the two countries have similar health status and access to care, although there are higher levels of inequality in the United States.

Calls for remedies for the persistent scarcity of accurate, reliable, national, disaggregated health statistics on hard-to-survey populations are common, but solutions are rare. Survey strategies used in community and clinical studies of hard-to-survey populations often cannot be, and generally are not, implemented at the national level. This essay presents a set of approaches, for use in combination with traditional survey methods in large-scale surveys of these populations, to overcome challenges in 2 domains: sampling and motivating respondents to participate. The first approach consists of using the American Community Survey as a frame, and the second consists of implementing a multifaceted community engagement effort. We offer lessons learned from implementing these strategies in a national survey, some of which are relevant to all survey planners. We then present evidence of the quality of the resulting data set. If these approaches were used more widely, hard-to-survey populations could become more visible and accurately represented to those responsible for setting national priorities for health research and services.

This study investigates whether the 6-item Strengths and Difficulties Questionnaire SDQ (5 symptoms and one impact item) included in the National Health Interview Survey can be used to construct models that accurately estimate the prevalence of any impairing mental disorder among children 4–17 years old as measured by a shortened Child/Adolescent or Preschool Age Psychiatric Assessment (CAPA or PAPA). A subsample of 217 NHIS respondents completed a follow-up CAPA or PAPA interview. Logistic regression models were developed to model presence of any child mental disorder with impairment (MDI) or with severe impairment (MDSI). Models containing only the SDQ impact item exhibited highly biased prevalence estimates. The best-performing model included information from both the five symptom SDQ items and the impact item, where absolute bias was reduced and sensitivity and concordance were increased. This study illustrates the importance of using all available information from the 6-item SDQ to accurately estimate the prevalence of any impairing childhood mental disorder from the NHIS.