This is one of the first reports derived from a nationally representative U.S. dataset that describes the associations between a range of health behaviors/risk factors and the use of CAM. We found that someone who engages in LTPA, has consumed alcohol in his/her life but is not a current heavy drinker, is a former cigarette smoker, or is not obese is more likely to use CAM. These data begin to address a recommendation by the Institute of Medicine [4
] that the associations between CAM use and positive behavioral change be explored. However, it remains to be determined whether the use of CAM and the incorporation of positive health behaviors and/or the reduction of health risk factors occur simultaneously as a result of some life changing event [13
] resulting in adoption of a "wellness lifestyle" [14
] or whether one precedes, and perhaps elicits, the other. Also to be addressed is whether those who use CAM maintain positive health behaviors and/or curtail negative risk factors over time better than do other individuals.
In our study, leisure-time physical activity had the strongest direct association with CAM use among all the assessed health behaviors. To our knowledge, this observation has not been reported previously. Physical activity has been shown to exert a protective effect on health even in those with generally poor health behaviors [15
]. In addition, physical fitness has been associated with younger age, better education, higher income, greater internal (versus external) health locus of control, and higher sense of coherence [16
], which is also consistent with CAM use in this report.
Associations between CAM use and smoking status were not observed in earlier surveys of health fair participants [17
], individuals attending geriatric clinics [18
], and members of managed care and health maintenance organizations [19
]. Although participants in these surveys appeared to be healthier than our NHIS participants, in our analysis, adjusting for the number of health conditions and physician visits, and the use of pharmaceutical drugs had little effect on the odds ratios for the effect of smoking status on CAM use. Because we performed a cross-sectional analysis, the direction of causality, whether these individuals stopped smoking or used CAM first, cannot be directly assessed. However, several converging lines of evidence suggest the possibility of a time sequence. First, unpublished data from the NHIS suggest that a sizable number of CAM users do so for self-management of addictive behaviors [21
]. Second, in our data, CAM was more strongly associated with former smoking than with current smoking. This is consistent with smokers deciding to quit as part of a move to a healthier lifestyle that could involve CAM. If people first used CAM then quit smoking, we would expect more of an association between CAM and current smoking. Longitudinal analyses will be needed to answer this question definitively.
Previous reports have not agreed on whether, and to what extent, alcohol consumption is associated with CAM use, with some finding an inverse association [19
], some a positive association [2
], and some no significant relationship [17
]. After adjustment for potential confounds, we found CAM use to be highest among those who consumed light to moderate amounts of alcohol. Of note, some research has identified linkages between light to moderate alcohol consumption and a number of positive health behaviors, including regular physical activity, having a healthy weight, not smoking, and getting influenza vaccinations [22
]. Taken together, these findings suggest that people make clear lifestyle choices that encompass a range of health-related activities, including CAM use.
We identified a set of noteworthy associations between select measures of health status, healthcare access and utilization, and sociodemographic measures and the use of CAM independent of the relationships between respondents' health behaviors and CAM use. Similar to other reports [1
] we found a particularly strong association between use of CAM and a number of factors indicative of poorer health, such as the number of reported health conditions and the number of reported doctor visits. However, CAM use was also associated with improved health status and increased use of self-care indicators such as LTPA. The latter suggests that while CAM use is most likely among those with current chronic health problems, a subset of CAM users may be healthier (or more health-conscious) than those who do not use CAM. The association between CAM use and frequent physician visits could also be interpreted to reflect more active involvement in care. This is consistent with the concept that a significant portion of CAM use is for prevention, health promotion, and wellness, rather than solely treatment of illness [6
This study has several limitations. First, the variables being investigated were self-reported. The scientific literature suggests that most people tend to under-report negative health behaviors [24
]. Hence, the effects of alcohol consumption [25
], for example, may have been diminished in this study. Second, flu shots are very different than the other health behavior indicators we used in that flu shots require contact with a health care provider. As such, obtaining a flu shot is influenced by many factors other than an individual's motivation such as access to care or availability of vaccine, potential confounders we could not account for in our analyses. This might have resulted in our underestimating the association between CAM use and obtaining a flu shot seen by others [26
]. Third, these data reflect a cross-sectional set of associations. Longitudinal assessments might have identified cohort and secular trends in the associations between health behaviors and CAM use that were not evident in cross-sectional analysis. Fourth, it is possible that additional respondent health behaviors (as well as other unexplored factors) explain more of the observed relationships. However, the five measures employed are important modifiable factors contributing to fatal diseases and morbidity [27
], and can be seen as standard measures of a healthy lifestyle [28
]. Finally, because our primary focus was to identify factors associated with the use, versus nonuse, of CAM, a dichotomous dependent variable was utilized. By doing so, information on the number and type of CAM therapies used and frequency of their use was lost. It may be that substantial differences exist between heavy and light users of one or more CAM modalities [6
]. It has been found that the use of specific types of CAM therapies is associated with specific personality styles [29
]. These associations might confound our results if specific personality styles (e.g., "openness" or "control") are also related to adoption of positive health behaviors.