DOI: https://doi.org/10.21203/rs.2.22230/v2
Background: The surge of methamphetamine use has been a complicating factor compounding the steeply increasing number of drug overdose deaths in the U.S. Infection from blood-borne viruses (BBVs) including hepatitis B virus (HBV), hepatitis C virus (HCV) and HIV, related to methamphetamine use continue to grow. This study aimed to examine the risk factors associated with HBV, HCV and HIV among people who used methamphetamine.
Methods: People who ever used methamphetamine were identified from five National Health and Nutrition Examination Survey (NHANES) cohorts, 2007 to 2016. The outcome was either tested positive or negative for blood-borne viruses as identified from laboratory tests. Weighted statistics for the combined ten years of data were calculated by multiplying the sample weight WTMEC2YR by 0.2. We examined the association of sexual activities (sexual partners, sexual identity), drug use behaviors (poly-drug use, injection drug use, frequency of drug use, age started using methamphetamine), demographics, and socio-economic status with BBV using bivariate and multivariable logistic regression models.
Results: There were 943 participants representing approximately 10,149,002 persons who ever used methamphetamine in the U.S. Blood-borne viruses’ positive rate was 13.3 per 100,000. Multivariable logistic regression analyses showed significant associations of blood-borne infections with age 50-59 years (vs. age 20-29 years, adjusted odds ratio 6.61, 95% CI 1.37 - 31.90), living within poverty index 1-1.9 (vs. poverty index >=2, 2.89; 1.33 – 6.31), living below the poverty threshold (vs. poverty index >=2, 2.64; 1.21 – 5.77), having lower than high school education (vs. equal or higher than high school education, 3.38; 1.65 – 6.91), sexual identity as other than heterosexual (vs. heterosexual, 7.81; 2.54 – 24.03), using methamphetamine and heroin and cocaine (vs. using methamphetamine alone, 4.98; 1.20 – 20.68), injection drug use (vs. no injection drug use, 3.57; 1.81 – 7.03), and started using methamphetamine at age above 25 (vs. started using methamphetamine at age between 10-17, 2.26; 1.03 – 4.97).
Conclusions: Among people who use methamphetamine, those who use polysubstance, or who inject substance, are in urgent need for vaccination and interventions to avoid further harm from blood borne infections.
Methamphetamine-related overdose has been increasing across the United States (U.S.) for the past several years [1]. According to the Centers for Disease Control and Prevention (CDC) data, the overdose death rates of psychostimulants with abuse potential which primarily include methamphetamine and other drugs such as amphetamine and methylphenidate, had tripled between 2016 and 2017 [2]. Provisional data from CDC indicates that deaths involving psychostimulants continued to increase in 2018, despite a drop in overall overdose deaths observed at the same time [3]. People who use methamphetamine also have elevated risk of nonfatal harms, including mental health disorders [4], violent and aggressive behavior [4], risky sexual behavior [4], sexually transmitted infection [5], harm to the fetus, and infection of blood-borne viruses (BBVs) [4, 6]. The pathogens of primary concern for blood-borne infectious diseases are the human immunodeficiency virus (HIV), hepatitis B virus (HBV), and hepatitis C virus (HCV) [7].
Methamphetamine use has been strongly associated with many outbreaks of blood-borne infections. Of the HBV patients identified in the 2003 HBV outbreak in Natrona County, Wyoming, eighty-eight percent reported injecting methamphetamine [8]. Methamphetamine use is prevalent among people living with HIV and AIDS, particularly among men who have sex with men in the U.S. [9]. In the 2014 HIV outbreak in Scott County, Indiana, 22% of the patients reported injecting methamphetamine [10]. A study characterizing methamphetamine use and HIV serological status in San Diego found that 54% of the people who use methamphetamine were HIV positive [11]. Another study examined risk factors associated with HBV infections among people who used methamphetamine [12]. A prospective cohort study conducted in Canada determined that injecting methamphetamine independently predicted HCV infection among young, street-involved persons with injection drug use (IDU) [13].
Other than injection, methamphetamine use through smoking, swallowing, or snorting also increases risk of blood-borne infections by negatively affecting judgment and triggering risky behaviors (e.g., unprotected sex) [14]. In addition to that, it is suggested that long-time methamphetamine use is associated with bleeding gums [15] and increasing risk of blood-borne infections through oral sex among sexually active population.
Fatal and nonfatal harms caused by rapidly increasing methamphetamine use are further compounded by existing opioid crisis, described by some scholars as “twin epidemics” [16]. Polysubstance use, such as co-occurring use of prescription opioids, synthetic opioids other than methadone, heroin, cocaine, or methamphetamine is now commonplace [1, 17, 18]. Specifically, in 2017, opioids were involved in over half of the 10,333 psychostimulant-related deaths [1]. Deaths involving opioids and methamphetamine increased significantly by 14% between July 2017 and June 2018 [18]. People prefer to use multiple substances for various reasons: (a) to experience the synergistic effect; (b) to enhance the benefits of each substance; (c) to overcome dysphoria and manage withdrawal symptoms; (d) to experiment; (e) to avail cheaper substances; (f) to balance the stimulation from methamphetamine with sedation from opioid/heroin [19, 20]. However, since heroin, fentanyl, and methamphetamine are all short-acting substances, persons with IDU tend to inject more frequently to stay “high”. The combined injection of methamphetamine and opioids, or sequential use of methamphetamine after opioids is associated with increased number of injections and increased probability of the reuse of syringes, thus, leading to elevated risk of BBVs [21-23].
Under this landscape of increasing polysubstance use, it is not clear how methamphetamine use affects the overall likelihood of blood-borne infections. A dynamic model investigating the excess risk of HIV and HCV infections among people who inject stimulants estimated that a median of 5–10% of new HIV and 3–7% of new HCV infections in the following year could each be attributed to 10% increase in the prevalence of stimulant injection use [4]. Another recent study found that women, poverty, IDU, and HCV infection were associated with increased risk of HBV infection among people who use methamphetamine [12]. CDC and a few state health departments have developed vulnerability assessment tools to identify counties at high risk of HIV and HCV; however, these tools do not include HBV [21, 24]. To date, no studies have used national data to examine factors associated with overall likelihood of positive BBV test results among people who use methamphetamine.
This study aims to examine risk factors associated with positive BBV test results among people who use methamphetamine in the National Health and Nutrition Examination Survey (NHANES). Findings from this study will identify vulnerable sub-population groups that are susceptible to infections from these BBVs.
Study data
The study population was identified from five NHANES cohorts from 2007 to 2016. Conducted by the National Center for Health Statistics (NCHS), NHANES is a continuous cross-sectional survey with data released biannually and is effective in determining the prevalence of major diseases and associated risk factors among adults and children in the U.S. [25, 26]. The NHANES data are rich and unique in two ways. Firstly, it combines information collected from both interviews and physical examinations that are necessary to answer the research questions. The interviews include demographics, socio-economic status, drug use information, and health-related questions; and the physical examinations include medical measurements and results of laboratory tests. Secondly, each survey cycle examines a nationally representative sample, and findings from the study are generalizable to the U.S. Further details are described elsewhere [26].
Study population and sampling procedure
The study population comprised people who reported methamphetamine use in lifetime. The flow chart in Figure 1 illustrates the process of case selection. The study included anyone who completed testing for any of the three sets of tests including HBV, HCV and HIV, and also answered “yes” to both questions “ever used cocaine/heroin/methamphetamine” and “ever used methamphetamine”. The study excluded anyone whose age was not between 20 and 59 years (as they were not eligible to answer drug use question) and anyone who obtained HBV immunity and was not infected by HBV.
Data sources
The primary outcome measure was positive/ negative detection of any of the three BBVs (HBV, HCV, and HIV) which were determined according to the results of a set of serological tests. Three HBV serological markers were tested in the NHANES study: antibody to hepatitis B core antigen (anti-HBc), indicative of previous or ongoing HBV infection; hepatitis B surface antigen (HBsAg), indicative of chronic infection; and antibody to hepatitis B surface antigen (HBsAb), serological evidence of vaccine-induced immunity [27]. Positive HBV detection was defined as a positive result of anti-HBc; while negative HBV detection was defined as negative for all HBV serological markers including anti-HBc, HBsAg and HBsAb. Indeterminate serological test results were coded as negative since we used a conservative definition to determine positive detection. The HBsAg is tested only when the anti-HBc test is positive. Participants who were HBsAb positive but anti-HBc negative and HBsAg negative were excluded from analyses, since they had acquired immunity through vaccination and were not considered as population at risk of HBV infection.
Two HCV serological markers were tested: hepatitis C antibody and hepatitis C RNA [28]. The hepatitis C RNA is tested only when the hepatitis C antibody test is positive. Current HCV infection was indicated by both hepatitis C antibody and RNA positive, and chronic HCV infection was defined as hepatitis C RNA positive 6 months after an acute infection. Positive HCV detection was defined as a positive result for both hepatitis C antibody and hepatitis C RNA; while negative HCV detection was defined as negative for hepatitis C antibody. Similarly, indeterminate serological test results were coded as negative.
Two HIV serological markers were tested: HIV-1 and HIV-2 antibody [29]. Specimens are initially tested by a combo set of HIV-1/2 Enzyme Immunoassay (EIA), and then repeated reactive specimens are tested with HIV-1/2 supplemental assay. Positive HIV detection was defined as positive result from the two rounds of tests. If EIA is positive but following supplemental tests are not positive (e.g., negative, indeterminate), a confirmatory test is performed for a final rule: HIV detection is positive with a positive confirmatory test result, and HIV detection is negative with a negative confirmatory test result.
According to previous literature [4, 5, 12, 30, 31], demographic characteristics (age, gender, race/ethnicity), socio-economic status (poverty index, health insurance, healthcare access, education), sexual activity (number of sexual partners in the past year, sexual identity), and drug use behaviors (number of drug use, IDU, number of times used methamphetamine in lifetime use, age started using methamphetamine) were known factors associated with infection of BBV. Therefore, these variables were included as potential confounders in the analyses.
Demographics including age, gender and race, health insurance and hospital utilization and access to care information were collected through Sample Person Questionnaire. Socio-economic status (poverty index, education) was obtained through Family Questionnaire. Drug use information (e.g., number of drug use, IDU, number of times used methamphetamine in lifetime use, and age started using methamphetamine, etc.) was obtained through Audio Computer Assisted Personal Self Interview (ACASI) Questionnaire. Sexual behaviors (number of sexual partners, sexual identity) were collected through both ACASI and computer assisted personal interview (CAPI) questionnaires during participants’ visit to the examination center. All three BBVs related measures were obtained from corresponding laboratory tests. The specific laboratory methods can be found elsewhere [25]. Responses to questions including education, drug use, and sexual activity were limited to participants aged 20 to 59 years.
Statistical analysis
Descriptive analyses include both raw and weighted frequency and percent of all covariates mentioned above. Weighted frequencies and percentage for the combined ten years of data were calculated by multiplying the sample weight WTMEC2YR by 0.2. The Rao Scott Chi-squared statistic was calculated to assess the association between each covariate and outcome measure. Bivariate logistic regression and three multivariable logistic regression models were developed to examine the risk factors associated with BBV positive results among people who used methamphetamine. The outcome was tested positive for BBV or negative to BBV as identified from laboratory tests. The main risk factors of interest were drug use behaviors (number of drug use, IDU, number of times used methamphetamine in lifetime use, and age started using methamphetamine).
Model I, which only includes demographics, evaluated the effect of demographic characteristics on the BBV positive result. Model II further added a set of socio-economic characteristics and sexual behavior information into the modelling to evaluate their effect on the BBV positive result, controlling for demographics. Although health insurance, healthcare access, and number of sexual partners were not statistical significant in our model, they are, in general, confirmed risk factors for BBV infection according to previous literatures, so included them in the model to adjust for their effects. Model III further explored how drug use affects the BBV positive result while taking into consideration all previous variables, which is our key research interest. The rationale to include them are two-fold: i), they are statistically significantly associated (p<0.05) with the BBV positive result in the unadjusted analyses; ii), they are suggested to have influence on the likelihood of being tested BBV positive.
Unadjusted odds ratios (uORs) and their 95% confidence intervals (CIs) were reported from bivariate logistic regression models, and adjusted odds ratios (aORs) and their 95% CIs were reported from the three multivariable logistic regression models. Missing data was not included in the analyses. For all ORs reported, statistical significance was considered as CI not crossing 1 and corresponding p-value being less than 0.05.
R programming (RStudio, version 3.6) was used for all analyses. Library “tidyverse” was used to clean data and generate appropriate subset for statistical analyses. Library “survey” and “srvyr” were used to analyze weighted NHANES data. Survey functions “svytotal”, “svymean”, “svychisq” and “svyCreateTableOne” were used to perform descriptive analyses; “svyglm” was used to perform logistic regression modeling, and “jtools” was used to draw figure 2.
Overall, 50,588 people participated in NHANES surveys from 2007 to 2016, of whom 1,878 participants who failed to complete medical exams. Further, 29,894 participants who were younger than 20 or over 59 years of age were excluded. There were 18,816 participants eligible to answer the question “ever using cocaine, heroin, or methamphetamine” of whom 2,491 (13.2%) participants did not respond to this question. Participants with missing values were more likely to be female (59% vs. 50%, p < 0.001) and belonging to races identified other than white or black (48% vs. 39%, p < 0.001). There were 1,132 participants who reported ever using methamphetamine, and among them 213 had HBV vaccine-induced immunity. After further excluding those with HBV vaccine-induced immunity or missing results of HBV immunity (n = 189), 943 participants were eligible (Figure 1) with 125 (13.3%) BBV positive and 818 (86.7%) BBV negative. The number of participants infected by HBV, HCV and HIV were 71 (57%), 78 (62%), and 11 (9%), respectively. Among the 125 persons with BBV positive, 35 of them were infected by two viruses: 6 were infected by both HIV and HBV, 29 were infected by both HBV and HCV, and no one was infected by both HCV and HIV. Table 1 summarizes the frequencies and weighted numbers and percentages of the characteristics of people who used methamphetamine. Based on the weighted estimates, the 943 participants represented approximately 10,149,002 persons who used methamphetamine in the U.S. population with the overall BBV positive rate at 13.3 per 100,000. Specifically, the positive rate of HBV, HCV and HIV were 6.4, 8.1 and 1.3 per 100,000, respectively.
In the study sample, a third of the participants were female, about two thirds (65%) were non-Hispanic white, 29% of the participants were 50 to 59 years old and they accounted for 51% of BBV positive. Approximately, a quarter (24%) of the participants were living below the poverty threshold and they accounted for 40% of BBV positive cases; another 29% were living between 1 to 1.9 times poverty index and they accounted for 31% of BBV positive cases. Over a third of the participants did not have any health insurance, and a quarter did not have routine healthcare access. Nearly a quarter of the participants with BBV positive had less than high school education. The 6% of participants whose sexual identity was identified other than heterosexual were accounted for 14% of BBV positive cases. While only 18% of people who used methamphetamine also reported ever using the other two drugs (heroin and cocaine), they accounted for almost a half (49%) of BBV positive cases. The majority of people who used methamphetamine did not inject any drugs (78%); however, almost two thirds (65%) of BBV positive were among the 22% persons with IDU. Half of participants first started using methamphetamine at age 18 to 25, a quarter between 10 and 17 years, and another quarter older than 25 years.
Table 2 summarizes the estimated model effects (uOR and aOR with 95% CIs) of factors associated with the outcome variable. The three multivariable logistic regression models adjusted for the covariates in a stepwise manner. The effect size of all aORs with 95% CIs are illustrated in Figure 2. In model 1, only being older than 50 (vs. age 20 – 29, 3.66; 1.02 – 13.18) and being non-Hispanic black (vs. non-Hispanic white, 1.98; 1.01 - 3.89) were significantly associated with BBV positive cases. After adding socio-economic status and sexual activities into model 2, there were significant associations of BBV positive with age 50-59 years old (vs. age 20 – 29, 9.37; 2.13 – 41.27), living around poverty index 1 to 1.9 (vs. living 2 times above poverty index, 2.95; 1.43 – 6.08), living below the poverty threshold (vs. living 2 times above poverty index, 3.88; 1.63 – 9.22), having lower than high school education (vs. equal to or higher than high school education, 3.03; 1.51 – 6.10), and sex identity other than heterosexual (vs. heterosexual, 4.86; 1.88 – 12.54). In the model 3, after adding drug use behaviors, associations of the same risk factors with BBV positive persisted: age 50-59 years old (vs. age 20 – 29, 6.61; 1.37 – 31.90), living around poverty index 1 to 1.9 (vs. living 2 times above poverty index, 2.89; 1.33 – 6.31), living below the poverty threshold (vs. living 2 times above poverty index, 2.64; 1.21 – 5.77), having lower than high school education (vs. equal to or higher than high school education, 3.38; 1.65 – 6.91), and sexual identity other than heterosexual (vs. heterosexual, 7.81; 2.54 – 24.03). In addition, in this model, ever used heroin and cocaine (vs. never used heroin or cocaine, 4.98; 1.20 – 20.68), IDU (vs. no IDU, 3.57; 1.81 – 7.03), and started using methamphetamine at age over 25 (vs. started using methamphetamine between age 10 to 17, 2.26; 1.03 – 4.97) were also significantly associated with BBV positive.
Findings from our study using 10 consecutive years of NHANES data suggest that polysubstance use and IDU were strongly associated with increased risk of being BBV positive among people who used methamphetamine. Compared with people who were tested BBV negative, those tested BBV positive were largely older, living two times below poverty index, having less than high school education, sexual identity other than heterosexual, having ever used all three illicit drugs including methamphetamine, heroin, and cocaine, having ever injected drugs, and having started using methamphetamine at age over 25. Previous literature has shown that people who use methamphetamine have an elevated risk of infection of BBVs through sexual risk (MSM) and injecting risk [9, 32, 33]. Our study found that injection drug use and sexual identity other than heterosexual are significant risk factors associated with elevated risk of BBV infection among this population.
Studies examining polysubstance use and their associations with harmful health effects are usually conducted at a smaller scale and among high-risk populations because of the challenges in capturing such information [19]. Using latent class analysis, studies have illustrated greater occurrence of sexual risk behaviors and increased diagnoses of blood-borne infections [34]. Findings from our study using nationally representative sample with large sample size corroborate results from previous smaller studies that individuals with polysubstance use (i.e., co-ingestion or sequential use of methamphetamine with heroin, fentanyl or cocaine) have a higher likelihood of being tested BBV positive.
Our study results suggest that persons who started using methamphetamine at age over 25 were more likely to be tested BBV positive, compared to those who started using methamphetamine at an early age. In a study assessing the effect of age and HIV status on methamphetamine use, the authors concluded that older persons without HIV were using methamphetamine at higher levels and were, therefore, at an increased risk of HIV [11]. More informed knowledge about risky behaviors among vulnerable age-groups can provide guidance to tailor treatment among this subgroup of population.
A recent study concluded that women using methamphetamine were four times as likely to be infected by HBV as males [12]. While our study did not find sex statistically significantly associated with BBV positive result, the odds ratio did indicate that women are more likely to be exposed to HBV compared to men. Similarly, the number of past year sexual partners is also likely associated with elevated risk of being tested BBV positive, although not statistically significant.
There are potential limitations associated with this study. Firstly, NHANES participants do not include incarcerated or homeless individuals, who have a higher rate of methamphetamine use than usual population. This may affect the generalizability of conclusion to the entire US adult population. Secondly, for sexual identity, we coded any heterosexual as “heterosexual”, and leaving all the others as “other”, including men who had sex with men and men (MSM), female homosexual, and other sexual identities. Although previous literature has identified MSM as a known risk factor for BBV infection, due to the small sample size of this group (n = 26, less than 3%), we combined MSM with other than heterosexual. This recoding method may be different from others and affect the generalizability of our results. Thirdly, questions about illicit drug use and sexual behavior are sensitive in nature, thus, people might refuse to respond or be unwilling to respond honestly to those questions, leading to incorrect estimates. Fourthly, some subgroups have very small sample sizes and therefore, very large confidence intervals. The small sample size potentially limited the power of our study. We had carefully categorized risk factors associated with BBV infection and reduced the effect of small sample size. Fifthly, the response to the question of lifetime use of methamphetamine (yes/no) might not be associated with BBV infection temporally. For one reason, the methamphetamine use could have been many years before any risk for blood-borne infection; for another reason, the use of methamphetamine could have commenced after the BBV infection.
In conclusion, as methamphetamine use, especially polysubstance use including methamphetamine, continues to increase, it is of great public health importance to identify those vulnerable populations who are prone to be infected by BBVs. The results of the study are expected to provide evidence to inform timely harm reduction efforts to identify this population and target vaccination and interventions to prevent transmission. Prevention and intervention efforts targeted toward these specific subgroups can help alleviate fatal and nonfatal harms caused by methamphetamine use. In addition, an evolving polysubstance use landscape indicates a need for a rapid, multifaceted approach to incorporate more comprehensive surveillance efforts to inform effective prevention and response strategies to prevent blood-borne infection outbreak.
Availability of data and materials
The datasets generated and/or analysed during the current study are available from R package "nhanesA", which can be downloaded from: https://cran.r-project.org/web/packages/nhanesA/index.html. The names of the five datasets from 2007 to 2016 are SXQ_I, SXQ_H, SXQ_G, SXQ_F, SXQ_E.
Ethics approval and consent to participate
Not applicable
Consent for publication
Not applicable
Competing interests
No conflict declared.
Funding
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Authors' contributions
YC and ZD formulated the research question and designed the study. YC conducted all statistical analyses and SW provided statistical expertise. YC drafted the methods and results sections, ZD drafted the introduction and part of the discussion section, and RB completed the discussion section. RB also provided critical comments and valuable suggestions to the study. All authors had full access to all of the data and approved the final manuscript.
Acknowledgements
The authors would like to thank Dr. Casey Jelsema for his help on R codes.
AIDS: Acquired Immunodeficiency Syndrome; aOR: Adjusted odds ratio; CDC: Centers for Disease Control and Prevention; CI: Confidence interval; HBsAb: Hepatitis B surface antibody; HBsAg: Hepatitis B surface antigen; HBV: Hepatitis B virus; HCV: Hepatitis C virus; HIV: Human immunodeficiency virus; IDU: Injection drug use; NCHS: National Center for Health Statistics; NHANES: National Health and Nutrition Examination Survey; MSM: Men who had sex with men; uOR: Unadjusted odds ratio.