Cardiovascular Disease Risk Factors and Myocardial Infarction in the Transgender Population
Circulation: Cardiovascular Quality and Outcomes
Abstract
Background:
As of 2016, ≈1.4 million people in the United States identify as transgender. Despite their growing number and increasing specific medical needs, there has been a lack of research on cardiovascular disease (CVD) and CVD risk factors in this population. Recent studies have reported that the transgender population had a significantly higher rate of CVD risk factors without a significant increase in overall CVD morbidity and mortality. These studies are limited by their small sample sizes and their predominant focus on younger transgender populations. With a larger sample size and inclusion of broader age range, our study aims to provide insight into the association between being transgender and cardiovascular risk factors, as well as myocardial infarction.
Methods and Results:
The Behavioral Risk Factor Surveillance System data from 2014 to 2017 were used to evaluate the cross-sectional association between being transgender and the reported history of myocardial infarction and CVD risk factors. A logistic regression model was constructed to study the association between being transgender and myocardial infarction after adjusting for CVD risk factors including age, diabetes mellitus, hypertension, hypercholesterolemia, chronic kidney disease, smoking, and exercise. Multivariable analysis revealed that transgender men had a >2-fold and 4-fold increase in the rate of myocardial infarction compared with cisgender men (odds ratio, 2.53; 95% CI, 1.14–5.63; P=0.02) and cisgender women (odds ratio, 4.90; 95% CI, 2.21–10.90; P<0.01), respectively. Conversely, transgender women had >2-fold increase in the rate of myocardial infarction compared with cisgender women (odds ratio, 2.56; 95% CI, 1.78–3.68; P<0.01) but did not have a significant increase in the rate of myocardial infarction compared with cisgender men.
Conclusions:
The transgender population had a higher reported history of myocardial infarction in comparison to the cisgender population, except for transgender women compared with cisgender men, even after adjusting for cardiovascular risk factors.
Introduction
See Editorial by Chan
Transgender is a term used to define individuals whose gender identity is different from their sex assigned at birth.1 Approximately 0.6% of the US population (1.4 million adults) identify themselves as transgender,2 and the number of transgender seeking gender-affirming hormone therapy is increasing.3 According to the National Transgender Discrimination Survey Report on Health and Health Care, at least 80% of transgender people have either utilized gender-affirming hormone therapy or plan to take it at some point.4 As sociocultural acceptance patterns evolve, clinicians will likely care for an increasing number of transgender people.5
Economic and healthcare disparities exist for transgender people, which may affect their health outcomes. Data from the 2015 US Transgender Survey, which includes nearly 28 000 transgender people, demonstrated higher poverty and unemployment rates in the transgender community when compared with the general population.6 Nearly one-third of transgender people self-reported not seeking health care due to financial constraints. In addition, 33% of transgender people experienced negative experiences related to their gender identity in the healthcare setting, and 23% cited fear of mistreatment due to gender identity as a reason for not seeking necessary medical care.7 In addition to these barriers faced by transgender people in seeking medical care, several known cardiovascular disease risk factors and behaviors are more prevalent in the transgender population.8–12 Large observational studies have shown higher rates of HIV infection, obesity, sedentary lifestyles, alcohol abuse, and smoking in transgender people compared with the general population. Psychiatric comorbidities occur with a much higher prevalence in the transgender population with higher rates of depression and suicide.7
To date, the majority of studies have not demonstrated a higher risk of myocardial infarction in the transgender population when compared with the cisgender population; however, these studies have been limited by small sample sizes and a young age of subjects.13 Using the Behavioral Risk Factor Surveillance System (BRFSS) data, we sought to conduct a large study with a broader age range to provide more insights into the association between myocardial infarction and being transgender after controlling for cardiovascular risk factors.
Methods
Study Population
BRFSS, a survey of adult US residents, is conducted monthly in a random sampling by the state health departments with assistance from the Centers for Disease Control and Prevention (CDC). CDC initiated this survey to collect prevalent data on risk behaviors and health practices that can affect health status.14 Combined data (n=1 842 439) from the 2014 (n=464 664), 2015 (n=441 456), 2016 (n=486 303), and 2017 (n=450 016) were used in this study.
Clinical Measures
Subjects who answered “Yes” to the question “Has a doctor, nurse, or other health professional EVER told you that you had a heart attack also called a myocardial infarction?” were classified as having had a myocardial infarction. Subjects who answered “No” to this question were classified as not having had a myocardial infarction. Similarly, the diagnosis of hypertension, diabetes mellitus, hypercholesterolemia, and chronic kidney disease was collected from the questions “Have you EVER been told by a doctor, nurse, or other health professional that…?” for “you have high blood pressure,” “you have diabetes,” “your blood cholesterol is high,” and “you have kidney disease,” respectively. Subjects who responded “no,” “borderline,” and “only during pregnancy” were coded as “no.” Subjects who answered “Don’t know/Not sure” or “Refused” were coded as missing.
Demographic and Social Measures
Data of age and race/ethnicity were obtained by asking the subjects “What is your age?” and “Which one or more of the following would you say is your race/best represents your race?” Race/ethnicity was classified as “White-Non-Hispanic,” “Black-Non-Hispanic,” “Hispanic,” “Other race only-Non-Hispanic,” and “Multiracial-Non-Hispanic.” Subjects were classified as “Never smokers” if they answered “No” to the question “Have you smoked at least 100 cigarettes in your entire life?” Subjects were classified as “Former smokers” if they had smoked >100 cigarettes but answered “Not at all” to “Do you now smoke cigarettes every day, some days, or not at all?” The remaining subjects were classified as “Some days smokers” and “Daily smokers.” Subjects were classified as “Meet CDC Exercise Recommendations” if they participated in ≥150 minutes (or vigorous equivalent minutes) of physical activity per week and “Do Not Meet CDC Exercise Recommendations” if they participated in <150 minutes (or vigorous equivalent minutes) of physical activity per week.
Transgender Measure
Subjects who reported “Transgender, male-to-female” were classified as “Transgender women.” Subjects who reported “Transgender, female to male” were classified as “Transgender men.”
Subjects who reported “Transgender, gender nonconforming” and reported “male” to “Respondents Sex” were classified as “Transgender women.” Similarly, subjects who reported “Transgender, gender nonconforming” and reported “female” to “Respondents Sex” were classified as “Transgender men.”
Subjects who reported “No” to the question “Do you consider yourself to be transgender?” and reported “male” to “Respondents Sex” were classified as “cisgender men.” Similarly, subjects who reported “No” to the question “Do you consider yourself to be transgender?” and reported “female” to “Respondents Sex” were classified as “cisgender women.”
Statistical Analysis
Descriptive statistics analysis was conducted for the demographic and health characteristics based on gender status (transgender men, cisgender women, transgender women, and cisgender women). Rao-Scott χ2 tests were used to examine the differences in demographics and health characteristics between transgender women and transgender men compared with cisgender men and cisgender women in the combined data. Logistic regression analyses were used to estimate the adjusted odds of having had a myocardial infarction as a function of being a transgender man or transgender woman compared with a cisgender woman and a cisgender man after adjusting for other confounding factors. Confounding factors were age, diabetes mellitus, chronic kidney disease, hypertension, hypercholesterolemia, and exercise. This approach concurrently estimates the association between being a transgender person and myocardial infection while controlling for the other risk factors of myocardial infarction. Analyses were performed using SAS 9.4 accounting for the BRFSS complex survey design and following BRFSS procedures for combining datasets from 2014 to 2017. This study was not approved by the Institutional Review Board or the Research and Development Committee because this study was conducted based on a national deidentifiable data from the CDC. All data and materials are publicly available at the CDC website and can be accessed at https://www.cdc.gov/brfss/.
Results
Univariate Analysis
Demographic and health characteristics for transgender men and transgender women compared with cisgender women and cisgender men are shown in Tables 1 and 2. The analysis of combined data demonstrated that transgender men had significantly higher rate of myocardial infarction (7.2% vs. 3.1%; P<0.01) compared to cisgender women, but did not have significantly higher rate of myocardial infarction (7.2% vs. 5.6%; p-value = 0.30) compared to cisgender men. On the other hand, transgender women had significantly higher rate of myocardial infarction compared with cisgender women (7.8% versus 3.1%; P<0.01) and cisgender men (7.8% versus 5.6%; P<0.01). Transgender men and transgender women were more likely to smoke daily compared with cisgender women and cisgender men. Transgender men and transgender women were less likely to meet CDC exercise recommendation compared with cisgender women and cisgender men. Transgender men and transgender women were more likely to be young and from an ethnic minority group compared with cisgender men and cisgender women.
Variable | Transgender Status | |||||
---|---|---|---|---|---|---|
Transgender Men, % | Cisgender Women, % | P Value | Transgender Women, % | Cisgender Men, % | P Value | |
Total, n (%); Population size | 1267 (0.40%); 231 590 | 410 828 (99.60%); 57 504 789 | 1788 (0.64%); 340 365 | 306 046 (99.36%); 53 215 945 | ||
Myocardial infarction | 7.2 | 3.1 | <0.01 | 7.8 | 5.6 | 0.01 |
Cigarette smoking | ||||||
Never | 65.2 | 64.0 | <0.01 | 55.8 | 53.0 | 0.17 |
Former | 15.5 | 21.6 | 24.0 | 28.3 | ||
Some days | 5.0 | 4.2 | 7.00 | 6.1 | ||
Daily | 14.3 | 10.2 | 13.2 | 12.5 | ||
Health status | ||||||
Hypertension | 26.0 | 31.3 | 0.12 | 34.8 | 35.0 | 0.96 |
Diabetes mellitus | 12.0 | 10.7 | 0.38 | 13.2 | 11.4 | 0.17 |
High cholesterol | 34.5 | 33.6 | 0.83 | 37.0 | 35.7 | 0.68 |
Kidney disease | 3.7 | 3.2 | 0.59 | 3.5 | 2.7 | 0.12 |
Demographics | ||||||
Age (±SD), y | 51.4 (±18.9) | 56.9 (±16.6) | <0.01 | 53.1 (±17.6) | 54.3 (±16.9) | <0.01 |
Race/ethnicity | ||||||
White | 55.2 | 65.0 | 0.02 | 55.6 | 65.2 | <0.01 |
Black | 15.2 | 12.1 | 13.8 | 10.7 | ||
Hispanic | 19.8 | 15.1 | 20.0 | 15.8 | ||
Other races | 8.0 | 6.4 | 8.1 | 6.8 | ||
Multiracial | 1.8 | 1.4 | 2.4 | 1.5 | ||
Met CDC exercise recommendations | 41.7 | 48.8 | 0.09 | 41.7 | 51.4 | <0.01 |
BRFSS indicates Behavioral Risk Factor Surveillance System; and CDC, Centers for Disease Control and Prevention.
Variable | Transgender Status | |||||
---|---|---|---|---|---|---|
Transgender Men, % | Cisgender Men, % | P Value | Transgender Women, % | Cisgender Women, % | P Value | |
Total, n (%); Population size | 1267 (0.43%); 231 590 | 306,046 (99.57%); 53 215 945 | 1788 (0.59%); 340 365 | 410,828 (99.41%); 57 504 789 | ||
Myocardial infarction | 7.2 | 5.6 | 0.30 | 7.8 | 3.1 | <0.01 |
Cigarette smoking | ||||||
Never | 65.2 | 53.0 | <0.01 | 55.8 | 64.0 | <0.01 |
Former | 15.5 | 28.3 | 24.0 | 21.6 | ||
Some days | 5.0 | 6.1 | 7.00 | 4.2 | ||
Daily | 14.3 | 12.5 | 13.2 | 10.2 | ||
Health status | ||||||
Hypertension | 26.0 | 35.0 | 0.01 | 34.8 | 31.3 | 0.17 |
Diabetes mellitus | 12.0 | 11.4 | 0.71 | 13.2 | 10.7 | 0.04 |
High cholesterol | 34.5 | 35.7 | 0.74 | 37.0 | 33.6 | 0.25 |
Kidney disease | 3.7 | 2.7 | 0.27 | 3.5 | 3.2 | 0.58 |
Demographics | ||||||
Age (±SD), y | 51.4 (±18.9) | 54.3 (±16.9) | <0.01 | 53.1 (±17.6) | 56.9 (±16.6) | <0.01 |
Race/ethnicity | ||||||
White | 55.2 | 65.2 | 0.01 | 55.6 | 65.0 | <0.01 |
Black | 15.2 | 10.7 | 13.8 | 12.1 | ||
Hispanic | 19.8 | 15.8 | 20.0 | 15.1 | ||
Other races | 8.0 | 6.8 | 8.1 | 6.4 | ||
Multiracial | 1.8 | 1.5 | 2.4 | 1.4 | ||
Met CDC exercise recommendations | 41.7 | 51.4 | 0.02 | 41.7 | 48.8 | 0.01 |
BRFSS indicates Behavioral Risk Factor Surveillance System; and CDC, Centers for Disease Control and Prevention.
Multivariable Analysis
Logistic regression models, in Table 3, demonstrated that transgender women had a 2-fold increase in odds of having a myocardial infarction (odds ratio [OR], 2.56; 95% CI, 1.78–3.68; P<0.01) when compared with cisgender women. However, there was no significant difference between transgender women and cisgender men after adjusting for age, diabetes mellitus, chronic kidney disease, smoking, hypertension, hypercholesterolemia, and exercise. In Table 3, logistic regression models also showed that transgender men had >4-fold (OR, 4.90; 95% CI, 2.21–10.90; P<0.01) and 2-fold (OR, 2.53; 95% CI, 1.14–5.63; P=0.02) increase in the odds of having a myocardial infarction compared with cisgender women and cisgender men, respectively, after adjusting for age, diabetes mellitus, chronic kidney disease, smoking, hypertension, hypercholesterolemia, and exercise. All models revealed that age, hypertension, diabetes mellitus, hypercholesterolemia, chronic kidney disease, and exercise were significantly associated with myocardial infarction.
Model | Adjusted Model | |
---|---|---|
Characteristics | OR (95% CI) | P Value |
Transgender status | ||
Reference group | Cisgender men | |
Transgender women | 1.32 (0.92–1.90) | 0.13 |
Transgender men | 2.53 (1.14–5.63) | 0.02 |
Cisgender women | 0.52 (0.48–0.55) | <0.01 |
Reference group | Cisgender women | |
Transgender women | 2.56 (1.78–3.68) | <0.01 |
Transgender men | 4.90 (2.21–10.90) | <0.01 |
Cisgender men | 1.94 (1.81–2.07) | <0.01 |
Age (per year) | 1.05 (1.05–1.05) | <0.01 |
Hypertension | 2.14 (1.97–2.33) | <0.01 |
Diabetes mellitus | 1.75 (1.62–1.89) | <0.01 |
High cholesterol | 1.95 (1.81–2.10) | <0.01 |
Kidney disease | 1.99 (1.78–2.23) | <0.01 |
CDC exercise recommendations | 0.81 (0.76–0.87) | <0.01 |
Cigarette smoking | ||
Never | Reference | |
Former | 1.61 (1.50–1.73) | <0.01 |
Some days | 2.72 (2.31–3.20) | <0.01 |
Daily | 2.78 (2.49–3.12) | <0.01 |
n | 314 264 | |
Population size | 50 187 749 |
BRFSS indicates Behavioral Risk Factor Surveillance System; CDC, Centers for Disease Control and Prevention; and OR, odds ratio.
The individual analyses of 2014, 2015, 2016, and 2017 data were included separately in Table 4. Interestingly, the rate of myocardial infarction has increased significantly for transgender men in 2017. Figure 1 depicts the OR of myocardial infarction in transgender men and women compared with cisgender women and men in the 4 models. Figure 2 depicts the trend in the prevalence rate of myocardial infarction from 2014 to 2017.
Years | Transgender Status | |||
---|---|---|---|---|
Transgender Men, % | Cisgender Women, % | Transgender Women, % | Cisgender Men, % | |
BRFSS 2014 | 7.3 | 3.1 | 7.3 | 5.9 |
BRFSS 2015 | 3.8 | 3.1 | 6.0 | 5.9 |
BRFSS 2016 | 3.4 | 3.1 | 9.7 | 5.5 |
BRFSS 2017 | 11.3 | 3.2 | 7.8 | 5.4 |
BRFSS indicates Behavioral Risk Factor Surveillance System.
Discussion
To the best of our knowledge, this is the first cross-sectional study that demonstrates an association between being transgender and reported history of myocardial infarction after adjusting for myocardial infarction risk factors. The current investigation demonstrated, after adjusting for myocardial infarction risk factors, that transgender men have a >4-fold and 2-fold increased odds of having a myocardial infarction when compared with cisgender women and cisgender men, respectively. Transgender women had an increase in the odds of having myocardial infarction compared with cisgender women but were not significantly different from cisgender men when we adjusted for age, diabetes mellitus, chronic kidney disease, smoking status, hypertension, hypercholesterolemia, and exercise.
The association between being transgender and having a myocardial infarction is likely multifactorial due to the increase in social stressors, health disparity, poor socioeconomic status, and substance abuse among this population.8,15,16 Increased stress levels related to neglect, abuse, and mistreatment have been hypothesized to contribute to increased inflammation, which may, in turn, predispose to cardiovascular disease. One study of transgender men on hormone therapy demonstrated that transgender patients who reported higher levels of stress on hormone therapy had increased high-sensitivity c-reactive protein levels.17 Hormonal replacement therapy may have some impact on the rate of myocardial infarction in the transgender population.8–10 Hormonal replacement therapy is also associated with an increase in inflammatory markers,18 hemoglobin/hematocrit, thromboxane, and low HDL (high-density lipoprotein) cholesterol,19 which are known to promote clotting and vasoconstriction and may lead to cardiovascular disease. We speculate that this association is modified by age and the presence of vascular injury and atherosclerosis.10
A recent meta-analysis of 26 studies, included a total of 4731 transgender patients, demonstrated that the rate of myocardial infarction is low in transgender patients who are on hormonal replacement therapy. This finding is not surprising as the mean age of transgender patients in these studies was only between 20 and 40 years old.13 In contrast, our study included a wider age range. Meyer et al11 reported, using the 2014 data, the OR for myocardial infarction among the transgender population was almost 2-fold compared with the cisgender population; however, their study did not evaluate the association based on the gender status. More recently, using data of BRFSS from 2014 to 2016, Downing and Przedworski12 demonstrated that transgender men have higher odds of having a myocardial infarction compared with cisgender women. However, this study did not adjust for myocardial infarction risk factors. Wierckx et al9 revealed in a small study that the rate of myocardial infarction in transgender women and transgender men was not significantly different when compared with cisgender men and cisgender women, respectively.
Getahun et al20 recently conducted a retrospective cohort study based on the electronic medical records of Kaiser Health system. This study showed that the adjusted hazard ratio of myocardial infarction was significantly high in Transfeminine cohort compared with cisgender women, but not significantly different compared with cisgender men. These findings are similar to the results of our study. However, Getahun et al20 reported that there was no significant difference in the rate of myocardial infarction between Transmasculine cohort and cisgender cohort, which is different than what we found in our analysis. We contribute the differences in the results to the following factors. First, we defined transgender status based on what subjects reported, but Getahun et al20 defined transgender status based on keywords from electronic medical records. Second, in our study, the mean age of transgender men was 51 years (±19); in contrast, only 5.7% of the subjects who were in the Transmasculine cohort were above 55 years. Finally, our subjects were randomly sampled and representative to the US population; in contrast, Getahun et al20 included subjects from electronic medical record of Kaiser system, which is not representative due to the increase in the rate of uninsured subjects among transgender community.11,12
The increased odds of myocardial infarction associated with other risk factors including smoking,21,22 hypercholesterolemia,23 diabetes mellitus,24,25 and hypertension26,27 found in this study are consistent with previous studies, which increases our confidence in the findings on the association between the transgender population and myocardial infarction. However, this study has several limitations. BRFSS is a cross-sectional study; thus, it only permits identifying associations. BRFSS relies on self-report; thus, there is a possibility of recall bias. However, the way the question was asked in this survey “Has a doctor, nurse, or other health professionals EVER told you that you had a heart attack also called a myocardial infarction?” has been validated in previous studies with 81% to 98% agreement to medical records.28,29 In BRFSS, few subjects identified themselves as “Transgender, gender nonconforming.” Those subjects were assigned based on another variable “sex of respondent” into transgender men and transgender women. Those group might introduce bias to our analysis. Thus, cisgender men and cisgender women were used as referenced groups to all data. Other limitations include the fact that there is no information on hormonal replacement therapy or detailed information about cardiovascular medications. As with any study, there is always the possibility of unknown confounding from variables not included in the final logistic regression model. However, the majority of these limitations would likely bias the OR estimates toward the null and underestimate the actual risks associated with being transgender.
Conclusions
The transgender population had a higher reported history of myocardial infarction in comparison to the cisgender population, except for transgender women compared with cisgender men, even after adjusting for cardiovascular risk factors. Future studies are required to address how to reduce the rate of myocardial infarction in this population and achieve health equality.
Acknowledgments
This research would not have been possible without the support of the Centers for Disease Control and Prevention (CDC) and the State Health Departments that conduct Behavioral Risk Factor Surveillance System (BRFSS) survey every year. This article was prepared using BRFSS data obtained from the CDC, but this article does not necessarily reflect their opinions or views about this topic.
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© 2019 American Heart Association, Inc.
History
Received: 11 February 2019
Accepted: 14 March 2019
Published in print: April 2019
Published online: 5 April 2019
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