Original articleEstimating the association between metabolic risk factors and marijuana use in U.S. adults using data from the continuous National Health and Nutrition Examination Survey
Introduction
Marijuana use has become increasingly prevalent in the United States. In a 2010 survey from the Substance Abuse and Mental Health Services Administration, an estimated 7.3% of Americans aged 12 and older used marijuana in 2012, more than any other illicit substance. Of those who reported using marijuana, an estimated 18.9 million used in the past month and 7.6 million could be considered chronic users [1].
With the rapidly changing policy landscape surrounding the control of marijuana use and its application in healthcare, more research is needed on the short- and long-term health effects of marijuana. Evidence on the effect of marijuana on common disease processes, such as diabetes, would be useful in health care decision-making. Metabolic syndrome is a set of clinical criteria associated with increased risk of type II diabetes and cardiovascular disease [2]. Metabolic syndrome includes excess fat around the abdomen, low high-density lipoprotein cholesterol (HDL-C), high triglyceride levels, high blood pressure, high blood sugar level, and insulin resistance [3].
Previous examinations of the relationship between marijuana use and health outcomes have provided conflicting results. In a small controlled study of male research volunteers, periods of marijuana smoking increased daily caloric intake and body weight [4]. In another study that used data from National Health and Nutrition Examination Survey (NHANES) III, total caloric intake was higher in current users but body mass index (BMI) was lower in current users compared with nonusers [5]. One large-sample, retrospective analysis found an association between marijuana use and higher caloric and alcohol consumption but did not find an association between current use and BMI or cardiovascular risk factors [6]. In a case-control study matched for age, sex, ethnicity, and BMI, marijuana use was associated with higher abdominal visceral fat, lower HDL-C, and lower adipocyte insulin resistance; however, there were no differences in total body fat, hepatic steatosis, insulin insensitivity, measures of beta-cell function, or glucose intolerance [7]. A study that used two large U.S. data sets found no significant difference in the multivariate-adjusted odds of obesity in marijuana users compared with abstainers, with the exception of users who smoked marijuana more than three times a week [8]. Prevalence of overweight or obesity in young adults from the Mater-University of Queensland Study of Pregnancy and its Outcomes was significantly lower in marijuana users in multivariate-adjusted analyses [9]. In contrast, a study using the National Longitudinal Survey of Youth found that, compared to nonuse or low use in adolescence, consistent or increasing patterns of marijuana use in adolescence are associated with an increased risk of obesity [10]. In another study among youth in the United States, frequent marijuana use was associated with overweight status but not obesity in young girls [11]. In a recent study, Penner et al. [12] evaluated the association between self-reported marijuana use and components of metabolic syndrome using the National Health and Nutrition Survey from 2005 to 2010. Surprisingly, the results of ordinary least squares estimation (OLS) of the multivariate linear models suggested reduced fasting insulin, increased HDL-C levels, and a smaller waist circumference in “current users” of marijuana compared with “never users”.
Results from the analysis of survey data that indicate improved BMI and other factors of metabolic health contradict what is known about the role of cannabis compounds in the cannabinoid system in humans. It is well known that marijuana contains appetite-stimulating compounds known as cannabinoids, which attach to cannabinoid receptors in the brain and other parts of the body [13]. This physiological effect has motivated its use in the treatment of cachexia (wasting syndrome) in cancer and human immunodeficiency virus patients [14], [15]. To make sense of the conflicting and sometimes surprising results from the observational studies reviewed in the previous sections, the analytic methods used in these studies should be carefully considered.
The models used in prior observational research are based on OLS regression models that disregard the potential endogeneity of marijuana use in health outcome risk equations. When used as explanatory variables, endogenous variables lead to biased regression estimates because of the correlation with missing or unknown control variables [16]. For example, tobacco use is inversely related to obesity [17], [18], [19] and directly proportional to marijuana use [20]. If one were to exclude tobacco use inappropriately as a confounder in a model explaining the relationship between marijuana use and health outcomes, the estimated relationship would be potentially biased. Empirical studies have previously acknowledged the endogeneity of substance in the health economics literature [21]. Models that account for endogeneity should be considered, as well as different specifications and checks on model validity. This study aims to explore the relationship between marijuana use and the clinical factors of metabolic syndrome by critically evaluating OLS regression analysis of NHANES data from 2005 to 2012.
Section snippets
Sample
This study sample included participants from the continuous NHANES from 2005 to 2012, a cross-sectional survey which oversamples young children, older persons, and certain ethnic groups in two-year cycles and applies weights for a nationally representative sample. Participants underwent an in-home interview and laboratory tests, which included blood and urine samples. This investigation focused on the 6281 participants surveyed between 2005 and 2012 who responded to questionnaire items
Results
As summarized in Table 1, there were significant differences across marijuana use categories for demographic characteristics in the sample, including sex, race or ethnicity, age, education level, tobacco use, alcohol consumption, income, BMI category, and postmenopausal status (p < .0001). In unadjusted analyses of the association between marijuana use and cardiometabolic risk factors, significant differences were also observed in the means for fasting insulin, insulin resistance, BMI, and
Discussion
The results of multivariate linear regressions estimated using OLS were consistent with prior research [12]. Current marijuana users appeared to have lower fasting insulin, improved insulin resistance, lower BMI, and a smaller waist circumference than nonusers. The analysis that follows demonstrates the fallibility of OLS methods that have been used in studies that estimate the relationship between marijuana use and BMI and other factors of the metabolic profile [4], [5], [6], [7], [8], [9],
Conclusions
Previous observational research on the effect of marijuana use on metabolic syndrome has offered conflicting results. The reliability of the epidemiologic methods used and underlying data in these studies must be critically examined to makes sense of these conflicting results and, ultimately, to arrive at reliable estimates of the effect of marijuana use. This study demonstrates that OLS models for estimating this relationship are flawed. Given that alcohol use and carbohydrate consumption are
Acknowledgments
The authors thank Patricia St. Claire and Brian Tysinger for their assistance with the NHANES data and Jeff McCombs and Andrew Messali for their helpful advice in the interpretation of the results. They also thank Dr. Orison Woolcott for lending his expertise regarding the cannabinoid system and its relationship to metabolic processes. This work was not supported through any grants or financial support.
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