Adapting Andersen’s Behavioral Model of Health Service Use to Examine Risk Factors for Hypertension Among U.S. MSM

Abstract

Hypertension affects nearly a third of U.S. adult males and is a leading risk factor for cardiovascular disease, but there is a paucity of hypertension research among men who have sex with men (MSM). Andersen’s model of health service use was adapted to examine factors associated with hypertension among MSM. In 2008, 7,454 U.S. MSM completed an online survey. Overall, 16.5% of the sample reported a lifetime diagnosis of hypertension. In hierarchical logistic regression, Black MSM had increased odds of reporting hypertension (adjusted odds ratio [AOR] = 1.79, 95% confidence interval [CI] [1.24, 2.60]) compared with White MSM, as did men aged 30 years and older (age 30-39: AOR = 2.46, 95% CI [1.84, 3.29]; age 40-49: AOR = 3.76, 95% CI [2.85, 4.97]; age 50+: AOR = 6.40, 95% CI [4.78, 8.58]; Reference: 18-29 years). Health conditions associated with hypertension included diabetes (AOR = 3.62, 95% CI [2.81, 4.68]), heart disease (AOR = 5.19, 95% CI [3.99, 6.75]), depression (AOR = 1.38, 95% CI [1.17, 1.63]), anxiety (AOR = 1.30, 95% CI [1.09, 1.57]), and being overweight (AOR = 2.23, 95% CI [1.91, 2.59]). Having a primary care provider (AOR = 2.19, 95% CI [1.64, 2.93]) and residing in South Atlantic (AOR = 1.39, 95% CI [1.12, 1.74]) or South Central (AOR = 1.59, 95% CI [1.27, 2.00]) regions was also associated with reporting hypertension. Study findings are consistent with those in the literature for the general population. To address health care inequities, the Internet could serve as a potential access point for health screening and referral for care.

Health care needs of men who have sex with men (MSM) have, to a large extent, been overlooked in public health efforts. It is well documented that MSM experience extreme health disparities in some areas, such as HIV (Centers for Disease Control and Prevention [CDC], 2013a) and substance use (Stall et al., 2001). Health disparities that may exist in other areas have received less attention since most national surveys fail to include questions about sexual orientation (Mayer et al., 2008; Wolitski, Stall, & Valdiserri, 2008). According to the 2011 Institute of Medicine Report, assessing health care inequities in sexual minorities, including barriers to health care access, utilization rates, and the quality of care received, is a priority research area and may help reduce disparities in MSM populations (Institute of Medicine, 2011).

Hypertension affects nearly a third of adult males in the United States and is a leading risk factor for cardiovascular disease (CDC, 2011). Hypertension is more prevalent in Southern U.S. states (CDC, 2015). Risk factors for hypertension include comorbid health conditions such as HIV, psychological distress, heavy drinking, physical inactivity, and being overweight or obese (CDC, 2015; Meng, Chen, Yang, Zheng, & Hui, 2012; Nsagha et al., 2015). It has been documented that MSM may be at increased risk for hypertension compared with heterosexual men (Everett & Mollborn, 2013; Swartz, 2015), though it is unclear what factors may be contributing to this disparity. Furthermore, researchers have not assessed racial/ethnic differences in hypertension among MSM.

Andersen’s (1968, 1995) behavioral model of health service use was originally developed in the 1960s to describe factors that lead to the use of health services. Since then, the model has evolved (Andersen, 1995) and its components (i.e., predisposing factors, need factors, and enabling factors) have been used to guide the examination of predictors associated with various health outcomes, such as HIV medication use among individuals living with HIV (Andersen et al., 2000). Andersen’s (1995) model differentiates equitable from inequitable access to care; equitable access is driven by demographic characteristics and need, whereas inequitable access is a result of social structure and enabling resources.

The current study addressed gaps in the literature regarding risk and protective factors for hypertension among U.S. MSM, which may be explained by the four components of Andersen’s model: (a) predisposing vulnerable factors—traits that are theoretically antecedent to illness, such as education, race/ethnicity, and sexual orientation; (b) need factors—perceived need is how an individual views his own health; evaluated need is assessed by a health care provider; (c) other predisposing factors—such as age, gender, and relationship status; and (d) enabling factors—the logistical aspects of obtaining care, which include having a primary care provider, health insurance, geographic region, and community size. For this analysis, hypertension diagnosis is considered a proxy measure of health care utilization because it implies that the individual had an interaction with the health care system. Andersen’s model of health service use (Andersen et al., 2000) provided guidance and context for variable selection and interpretation of findings.

Method

Participants

Eligibility criteria for the study were programmed into the online baseline survey. Participants had to identify as a man, be aged 18 years or older, report lifetime oral or anal sex with a man, reside in the United States, and have the ability to read and respond in English.

Procedure

In 2008, a sexual networking website popular among MSM sent an e-mail to its U.S. members (n = 609,960) that informed them of the opportunity to participate in an online health and behavioral study. Details of recruitment and eligibility have been described elsewhere (Hirshfield et al., 2012). After reading a study information page and consenting to participate, participants completed a 15-minute survey. No incentives were offered to study participants. The institutional review boards at Public Health Solutions and the CDC reviewed and approved all study procedures.

A total of 23,213 (3.8%) men clicked on the study recruitment e-mail hyperlink that took them to the study landing page; 9,539 (41%) left the landing page immediately and 13,674 (59%) consented to participate in the survey. Among men who consented, 12,109 (88%) completed most of the online survey. A more detailed description of the overall sample, exclusions, and nonresponse are described elsewhere (Hirshfield et al., 2012). The current analysis excluded 203 non-U.S., female, or transgender participants, 311 duplicate cases, and 28 cases with incongruous data. Of the remaining 11,567 participants, 4,113 dropped out of the survey or were missing data on key outcomes, resulting in an analytic sample of 7,454 men who reported lifetime oral or anal sex with a man.

Measures

A comparison of Andersen’s model for HIV-positive persons (Andersen et al., 2000) with the adapted version used in the current study is presented in Table 1. Lifetime health diagnoses, including the dependent variable hypertension, were assessed with a single question, “Have you ever been diagnosed with the following?” Participants were presented with a list of health conditions, from which they could check any that applied. The list of health conditions included anxiety, bipolar or other mood disorder, cancer, depression, diabetes, heart disease, hypertension, or schizophrenia.

Table 1.

Similarities and Differences Between Andersen’s Model of HIV-Positive Adults and Current Study.

Conceptual areas	Andersen et al.’s (2000) model for HIV-positive adults and highly active antiretroviral therapy adherence	Current study
Predisposing	Gender, education, ethnicity	Gender, education, race/ethnicity, sexual orientation
Need	Perceived: Tested for HIV because sick [Symptom Intensity Index]	Perceived: Currently overweight
	Evaluated: [Lowest CD4 count]	Evaluated: HIV status; lifetime diagnoses of: diabetes, heart disease, depression, or anxiety
Other predisposing	Demographic: Age	Demographic: Age
	Social structure: Living alone, how often sees relatives, how often sees friends, number of close friends	Social structure: Relationship status
	Beliefs: [How well informed about HIV] “My health is doctor’s top concern.”
Enabling	Individual/family: Usual source of care, perceived access scale, current income, [place of first HIV test], current health insurance, how long to appointment, travel time to usual source of care, wait time at usual source of care	Individual: Primary care provider, current income, current health insurance
	Community: Geographic region, metropolitan statistical area size	Community: Geographic region, residency (city size)

Note. Same or similar variables across models are in italics in the current study column. Variables from the Andersen et al.’s (2000) study that are not relevant to the current study are in brackets.

Predisposing vulnerable variables included education, race, ethnicity, and sexual orientation, which was assessed using the Kinsey scale (Kinsey, Pomeroy, & Martin, 1948). Need variables included self-reported HIV status and lifetime diagnoses of diabetes, heart disease, depression, and anxiety. Furthermore, a single item assessed participants’ perception of their current weight. Response options were measured on a 7-point scale ranging from very underweight to very overweight. Scores of 5 or higher were collapsed into overweight. Other predisposing variables included age and relationship status. Enabling variables included income, current health insurance (no; yes, through a job or someone else’s job; yes, paid for by the participant or another person; yes, Medicaid or Medicare) and having a primary care provider. Last, the survey assessed community size (rural, suburban, or urban) and geographic region (Northeast, South Atlantic, North Central, South Central, Mountain, Pacific).

Data Analysis

All statistical analyses were performed using IBM SPSS version 22 (IBM, Armonk, NY). To test Andersen’s theoretical model, bivariate associations significant at p < .10 were retained for inclusion in a multivariable model. Four blocks of predictors were sequentially entered into a hierarchical logistic regression model. This allowed for the testing of statistical significance with each block of predictors as well as the significance of individual predictors within blocks.

Following the structure of Andersen’s model (Andersen et al., 2000), independent variables were divided into four blocks: (a) the predisposing factors that distinguish traditionally vulnerable groups with respect to access to medical care; (b) need factors expected to have a substantial bearing on access to care; (c) other predisposing factors that represent demographic and social structure that might help explain limited access to care; and (d) enabling factors that might facilitate or impede access to care.

Results

Demographic and Health Characteristics

The main outcome, self-reported hypertension, was reported by 16.5% (n = 1,228), while 16% (n = 1,182) indicated they were HIV-positive, and 5% (n = 362) reported having diabetes and/or heart disease (n = 352; Table 2). The prevalence of hypertension varied by all demographic and behavioral characteristics except for sexual orientation. Approximately 79% (n = 969/1,228) of men with a hypertension diagnosis reported currently taking hypertension medication. The median age was 39 years (range: 18-81). Most men were White (83%, n = 6,189) and had a college degree or higher (56%, n = 4,177), though a substantial proportion had only some college or a technical degree (35%, n = 2,563). More than half reported being single and the largest proportion resided in the Northeast (24%, n = 1,764). About two-thirds had health insurance through an employer (67%, n = 4,894), with the remainder reporting no insurance (14%, n = 1,052), self-pay (13%, n = 927), or Medicaid/Medicare (6%, n = 444). More than half (51%, n = 3,533) reported an income of $50,000 or higher (range: under $10,000-$80,000 or more). Most men self-identified as gay or homosexual (85%, n = 6,284). The majority reported having a primary care provider (83%, n = 6,092), lifetime diagnosis of depression (33%, n = 2,414), anxiety (23%, n = 1,694), or bipolar disorder (6%, n = 429), and being overweight (52%, n = 3,803).

Table 2.

Demographic and Behavioral Characteristics by Lifetime Diagnosis of Hypertension.

	Overall, n (%)	Hypertension		Chi-square p
	N = 7,454	n (%)	n (%)
Education, n = 7,435		Yes	No
Up to high school degree	695 (9)	100 (8)	588 (10)
Some college/tech degree	2,563 (35)	393 (32)	2,124 (35)
College degree	2,375 (32)	381 (31)	1,976 (32)
Graduate or professional degree	1,802 (24)	352 (29)	1,435 (23)	.001
Race/ethnicity, n = 7,423
White	6,189 (83)	1,051 (86)	5,085 (83)
African American	272 (4)	51 (4)	221 (4)
Hispanic	596 (8)	75 (6)	512 (8)
Asian	110 (2)	6 (1)	102 (2)
Mixed/other race	256 (3)	40 (3)	213 (3)	.001
Sexual orientation, n = 7,424
Homosexual	6,284 (85)	1,033 (84)	5,197 (85)
Bisexual	1,080 (14)	180 (15)	887 (14)
Heterosexual	60 (1)	10 (1)	49 (1)	.971
Age (years), n = 7,454
18-29	1,986 (27)	89 (7)	1,872 (30)
30-39	1,756 (24)	222 (18)	1,517 (25)
40-49	2,325 (31)	450 (37)	1,855 (30)
50+	1,387 (18)	467 (38)	914 (15)	.000
Relationship statusa, n = 7,440
Single	4,577 (61)	665 (54)	3,868 (63)
In a relationship	2,508 (34)	457 (37)	2,031 (33)
Divorced, separated, or widowed	355 (5)	104 (9)	247 (4)	.000
HIV statusb, n = 7,417
HIV-positive	1,182 (16)	240 (20)	933 (15)
HIV-negative	5,545 (75)	881 (72)	4,623 (76)
Untested	690 (9)	103 (8)	572 (9)	.001
Lifetime diagnosesc, n = 7,384
Diabetes	362 (5)	200 (16)	162 (3)	.000
Heart disease	352 (5)	212 (17)	140 (2)	.000
Depression	2,414 (33)	537 (44)	1,877 (31)	.000
Anxiety	1,694 (23)	363 (30)	1,331 (22)	.000
Bipolar	429 (6)	83 (7)	346 (6)	.116
Currently overweightd, n = 7,338	3,803 (52)	867 (71)	2,933 (48)	.000
Income, n = 6,953
Up to $29,999	1,651 (24)	201 (17)	1,434 (25)
$30,000-$49,999	1,769 (25)	284 (25)	1,473 (26)
$50,000 or more	3,533 (51)	674 (58)	2,829 (49)	.000
Primary care provider, n = 7,336
Yes	6,092 (83)	1,151 (94)	4,939 (81)	.000
Health insurance, n = 7,317
Employer sponsored	4,894 (67)	849 (70)	4,043 (66)
Self-pay	927 (13)	115 (9)	811 (13)
Medicaid/Medicare	444 (6)	147 (12)	297 (5)
None	1,052 (14)	109 (9)	941 (16)	.000
Community size, n = 7,454
Rural	1,945 (26)	338 (27)	1,593 (26)
Suburban	1,551 (21)	277 (23)	1,259 (20)
Urban	3,958 (53)	613 (50)	3,306 (54)	.050
Geographic regione, n = 7,454
Northeast	1,764 (24)	267 (22)	1,479 (24)
South Atlantic	1,416 (19)	267 (22)	1,138 (18)
North Central	1,244 (17)	176 (14)	1,052 (17)
South Central	1,284 (17)	254 (21)	1,020 (17)
Mountain	674 (9)	106 (8)	562 (9)
Pacific	1,072 (14)	158 (13)	907 (15)	.000

Note. Significant findings in bold.

^aRelationship status: single (unmarried/no domestic partner) versus partnered (married/domestic male partner; married/domestic female partner) or divorced, separated, or widowed (from man or woman). ^bHIV status was self-reported. ^cParticipants checked boxes to signify which mental and physical health problems they had ever been diagnosed with. ^dOverweight: self-report of “a bit overweight” to “extremely overweight” versus “just the right weight” or less. ^eRegional definitions: Northeast (NY, NJ, CT, PA, MA, RI, NH, ME, VT); South Atlantic (DE, DC, MD, VA, WV, NC, SC, GA, FL); North Central (IN, MI, IA, WI, MN, SD, ND, IL, MO, KS, NE); South Central (AL, TN, MS, KY, OH, LA, AR, OK, TX); Mountain (MT, CO, WY, ID, UT, AZ, NM, NV); and Pacific (CA, HI, OR, WA, AK, GUAM).

Factors Associated With Hypertension

Column 1 of Table 3 presents unadjusted odds ratios for the predisposing vulnerable variables, need variables, other predisposing variables, and enabling variables for the outcome of reporting a lifetime diagnosis of hypertension. Men who did not have a professional or graduate degree were significantly less likely to report lifetime hypertension. Compared with White MSM, Hispanic, and Asian men were significantly less likely to have ever reported hypertension. Several variables were associated with increased odds of reporting hypertension. Lifetime diagnosis of hypertension significantly increased with age. Men in current relationships or those who were divorced, separated, or widowed (from men or women) were significantly more likely to ever report hypertension compared with single men. Compared with HIV-negative men, HIV-positive men were significantly more likely to report hypertension. Men reporting lifetime diagnoses of diabetes, heart disease, depression, or anxiety, or who were currently overweight were also more likely to report hypertension than men who did not report having a history of these factors. Having a primary care provider was a strong predictor of reporting a hypertension diagnosis. Likewise, compared with men with employer-sponsored health insurance, men with Medicaid or Medicare were significantly more likely to report hypertension, unlike self-paying or uninsured men who were less likely to report hypertension. Men living in suburban areas (compared with urban areas), the South Atlantic, or the South Central region of the United States (compared with the Northeast) were significantly more likely to report hypertension.

Table 3.

Risk Factors for Hypertension Among Men Who Have Sex With Men Recruited Online: Adapting Andersen’s Behavioral Model of Health Service Use With Hierarchical Logistic Regressions.

Variable (referent category)	Bivariate odds ratio (OR)	Multivariable AORs
		Predisposing vulnerable variables	Plus need variables	Plus other predisposing variables	Plus enabling variables
	1	2	3	4	5
Block Statistics		χ2 = 35.14	χ2 = 740.90	χ2 = 282.16	χ2 = 88.53
	OR [90% CI]	AOR [95% CI]	AOR [95% CI]	AOR [95% CI]	AOR [95% CI]
Predisposing Vulnerable
Education (ref. graduate degree)
Up to high school degree	0.69 [0.57, 0.85]	0.68 [0.53, 0.87]	0.65 [0.50, 0.85]	0.93 [0.70, 1.22]	0.96 [0.71, 1.31]
Some college/tech degree	0.75 [0.66, 0.85]	0.73 [0.62, 0.85]	0.67 [0.56, 0.79]	0.92 [0.77, 1.11]	0.96 [0.79, 1.17]
College degree	0.79 [0.69, 0.89]	0.78 [0.66, 0.92]	0.79 [0.67, 0.94]	0.97 [0.81, 1.16]	1.00 [0.83, 1.21]
Race/Ethnicity (ref. White)
African American	1.12 [0.86, 1.45]	1.16 [0.85, 1.59]	1.32 [0.94, 1.85]	1.76 [1.24, 2.50]	1.79 [1.24, 2.60]
Hispanic	0.71 [0.57, 0.88]	0.73 [0.56, 0.93]	0.79 [0.61, 1.04]	1.01 [0.76, 1.33]	1.09 [0.82, 1.45]
Asian	0.29 [0.14, 0.57]	0.27 [0.12, 0.61]	0.43 [0.19, 1.00]	0.70 [0.30, 1.64]	0.69 [0.27, 1.75]
Mixed/other race	0.91 [0.68, 1.21]	0.93 [0.66, 1.31]	0.90 [0.62, 1.31]	1.12 [0.76, 1.64]	1.11 [0.74, 1.67]
Sexual Orientation (ref. Homosexual)
Bisexual	1.02 [0.88, 1.18]	1.06 [0.89, 1.26]	1.15 [0.95, 1.39]	0.99 [0.80, 1.21]	0.89 [0.72, 1.12]
Heterosexual	1.03 [0.58, 1.82]	1.01 [0.51, 2.00]	0.99 [0.46, 2.15]	0.97 [0.44, 2.15]	1.01 [0.44, 2.33]
Other Predisposing
Age (years; ref. 18-29)
30-39	3.08 [2.49, 3.81]			2.78 [2.12, 3.63]	2.46 [1.84, 3.29]
40-49	5.10 [4.19, 6.22]			4.12 [3.19, 5.31]	3.76 [2.85, 4.97]
50+	10.75 [8.79, 13.15]			7.36 [5.63, 9.61]	6.40 [4.78, 8.58]
Relationship Statusa (ref. single)
Partnered	1.31 [1.17, 1.46]			1.13 [0.98, 1.31]	1.10 [0.94, 1.29]
Divorced, separated, or widowed	2.45 [1.99, 3.00]			1.35 [1.02, 1.79]	1.22 [0.91, 1.65]
Need
HIV Statusb (ref. HIV-Negative)
HIV-positive	1.35 [1.18, 1.54]		1.37 [1.15, 1.64]	1.06 [0.88, 1.27]	0.98 [0.80, 1.19]
Untested	0.95 [0.78, 1.14]		1.05 [0.82, 1.33]	1.38 [1.07, 1.78]	1.44 [1.09, 1.89]
Lifetime Diabetesc (ref. No)
Yes	7.22 [6.01, 8.66]		5.05 [3.98, 6.41]	3.99 [3.13, 5.09]	3.62 [2.81, 4.68]
Lifetime Heart Diseasec (ref. No)
Yes	8.99 [7.45, 10.84]		6.75 [5.31, 8.58]	5.14 [4.00, 6.59]	5.19 [3.99, 6.75]
Lifetime Depressionc (ref. No)
Yes	1.78 [1.60, 1.98]		1.44 [1.23, 1.68]	1.39 [1.19, 1.64]	1.38 [1.17, 1.63]
Lifetime Anxietyc (ref. No)
Yes	1.53 [1.36, 1.71]		1.21 [1.02, 1.44]	1.32 [1.10, 1.57]	1.30 [1.09, 1.57]
Currently Overweightd (ref. No)
Yes	2.65 [2.37, 2.96]		2.49 [2.15, 2.87]	2.28 [1.97, 2.65]	2.23 [1.91, 2.59]
Enabling
Income (ref. $50,000 or more)
Up to $29,999	0.59 [0.51, 0.68]				0.94 [0.74, 1.19]
$30,000-$49,999	0.81 [0.71, 0.92]				0.97 [0.81, 1.16]
Primary Care Provider (ref. No)
Yes	3.84 [3.12, 4.73]				2.19 [1.64, 2.93]
Health Insurance (ref. Employer)
Self-pay	0.68 [0.57, 0.81]				0.72 [0.56, 0.92]
Medicaid/Medicare	2.36 [1.97, 2.81]				1.39 [1.04, 1.86]
None	0.55 [0.46, 0.66]				0.76 [0.58, 0.99]
Community Size (ref. Urban)
Rural	1.14 [1.01, 1.29]				1.12 [0.93, 1.35]
Suburban	1.19 [1.04, 1.35]				1.21 [1.01, 1.46]
U.S. Regione (ref. Northeast)
South Atlantic	1.30 [1.11, 1.52]				1.39 [1.12, 1.74]
North Central	0.93 [0.78, 1.10]				1.11 [0.87, 1.41]
South Central	1.38 [1.18, 1.62]				1.59 [1.27, 2.00]
Mountain	1.05 [0.85, 1.28]				1.22 [0.90, 1.63]
Pacific	0.97 [0.81, 1.15]				1.04 [0.81, 1.33]
Change in R2		.01	.18	.24	.26

Note. AOR = adjusted odds ratio; CI = confidence interval. χ² = Model chi-square for each block of variables, all significant at p < .001. Nagelkerke R². Significant findings in bold.

^aRelationship status: single (unmarried/no domestic partner) versus partnered (married/domestic male partner; married/domestic female partner) or divorced, separated, or widowed (from man or woman). ^bHIV status was self-reported. ^cParticipants checked boxes to signify which mental and physical health problems they had ever been diagnosed with. ^dOverweight: self-report of “a bit overweight” to “extremely overweight” versus “just the right weight” or less. ^eRegional definitions: Northeast (NY, NJ, CT, PA, MA, RI, NH, ME, VT); South Atlantic (DE, DC, MD, VA, WV, NC, SC, GA, FL); North Central (IN, MI, IA, WI, MN, SD, ND, IL, MO, KS, NE); South Central (AL, TN, MS, KY, OH, LA, AR, OK, TX); Mountain (MT, CO, WY, ID, UT, AZ, NM, NV); and Pacific (CA, HI, OR, WA, AK, GUAM).

In multivariable analysis, the addition of each block of theoretical predictors demonstrated an increasingly complex picture of individual-level and structural-level variables associated with reporting a hypertension diagnosis. Predisposing vulnerable variables (column 2) identified that the more vulnerable groups (i.e., those with lower education; Hispanic and Asian men) were less likely to report hypertension. The adjusted odds ratios for need variables (column 3) were significant but lower than in bivariate analysis. The addition of the need variable block resulted in a reduction in the likelihood of Asian MSM (and a loss of significance among Hispanic MSM) reporting hypertension. With the addition of other predisposing variables (column 4), several notable changes occurred. Education, Asian race, being in a relationship, and reporting an HIV-positive status were no longer associated with having a hypertension diagnosis. However, being Black (vs. White) and having never tested for HIV (vs. HIV-negative) emerged as being significantly associated with hypertension. In the final model that included enabling variables (column 5), Black MSM were significantly more likely than White MSM to report lifetime hypertension. Increased likelihood of a hypertension diagnosis by age remained highly significant, as did being untested for HIV, currently being overweight, and reporting lifetime diagnoses of diabetes, heart disease, depression, and anxiety, though relationship status was no longer associated with hypertension. In addition, men who reported having a primary care provider, living in a suburban area, and residing in the South Atlantic or South Central U.S. regions had increased odds of a lifetime hypertension diagnosis. Men who self-paid for health insurance or did not have health insurance were significantly less likely to report having hypertension compared with those with employer-sponsored insurance. Those with Medicaid or Medicare were significantly more likely than those with employer-sponsored insurance to have a hypertension diagnosis.

Discussion

Andersen’s model was adapted to identify factors associated with reporting a lifetime hypertension diagnosis by including sets of variables according to hypothesized dimensions that could affect health status. The model helped uncover factors that may be driving disparities in hypertension among MSM. In addition to need factors (i.e., comorbid physical and mental health conditions), several enabling factors were associated with the most inequities regarding hypertension. Having a primary care provider and residing in South Atlantic and South Central regions of the United States were associated with higher odds for a hypertension diagnosis, while self-pay or no insurance was associated with lower odds. Similar findings have been reported for hypertension and other chronic health conditions, suggesting that individuals with public insurance may perceive themselves as having a need for medical care compared with uninsured individuals (Decker, Kostova, Kenney, & Long, 2013; Smolen, Thorpe, Bowie, Gaskin, & LaVeist, 2014). Alternatively, uninsured adults may differ from adults with private and public insurance, in terms of exercise, diet, attitudes toward health and health care, and mandated health screenings (Cogan, 2011; Sommers, 2014). Each of these factors is especially relevant given the introduction of the Affordable Care Act (ACA). The ACA may increase the proportion of U.S. adults who have private insurance and who access medical care, which may result in earlier detection of hypertension. However, the proportion of U.S. adults who take advantage of ACA insurance mandates varies geographically (Nardin, Zallman, McCormick, Woolhandler, & Himmelstein, 2013). Therefore, MSM with hypertension who reside in lower uptake states or regions may be at greater risk for not accessing critical medical care. As these data were collected prior to the introduction of the ACA, continued monitoring of health care access among MSM to identify regional disparities is warranted.

Findings from this study add to a growing body of literature on chronic health disparities among sexual minority men. This is one of the first studies to assess factors for self-reported hypertension among a large convenience sample of MSM. Prior studies (Everett & Mollborn, 2013; Swartz, 2015) have reported increased risk for hypertension among MSM. However, a lower percentage of MSM in this online sample (16.5%) reported hypertension than both prior studies (~25% to 39%; Everett & Mollborn, 2013; Swartz, 2015). Direct comparisons with these studies are not possible, as they employed different methods of recruitment and data collection. Nevertheless, there is still relatively little information available concerning risk and protective factors for hypertension in this population. The results of the current study are consistent with those in the literature for the general population in that MSM who are Black, older, have comorbid mental and physical health conditions, and reside in Southern U.S. regions had greater odds of self-reporting hypertension. In addition, men who had never been tested for HIV were at increased risk for hypertension.

In applying Andersen’s behavioral model of health service use to MSM, this study observed findings consistent with those of prior research that have reported particular demographic and health conditions associated with hypertension. First, Black men in this sample were at increased risk for hypertension with the inclusion of predisposing and enabling variables from Andersen’s model. Swartz (2015) reported that Black men have two times higher risk for hypertension than White men, which is similar to findings from the current study. Not surprisingly, increased age, having a lifetime diagnosis of diabetes or heart disease, and being overweight were all significantly associated with greater odds for hypertension in all models. Although substantial research has indicated that heterosexual men are more likely to have a higher body mass index than gay or bisexual men (Austin et al., 2009; Conron, Mimiaga, & Landers, 2010; Deputy & Boehmer, 2010; Everett & Mollborn, 2013), a recent prospective cohort study indicated a high prevalence of sexual minority men reporting that they were overweight or obese (>50%; Guadamuz et al., 2012). Also consistent with other studies (Everett & Mollborn, 2013; Swartz, 2015; Wallace, Cochran, Durazo, & Ford, 2011), these findings are a reminder that hypertension is often accompanied by comorbid health conditions that may interact and complicate health management.

Lifetime diagnoses of depression and anxiety were likewise associated with increased risk for hypertension, which is consistent with studies reporting that adults with hypertension also have more depression (Meng et al., 2012). MSM tend to report higher levels of depression and anxiety than heterosexual men (Bostwick, Boyd, Hughes, & McCabe, 2010), and therefore may be particularly vulnerable to the development of cardiovascular-related conditions. Population-level data reveal that sexual minority men experience higher rates of psychological distress than heterosexual men (Cochran & Mays, 2007; Conron et al., 2010; Wallace et al., 2011). MSM are disproportionately at risk for HIV and other sexually transmitted infections (CDC, 2013a, 2013b). Recent literature indicates that both HIV infection and some medications to treat HIV are associated with increased risk for cardiovascular health problems, including hypertension (Vu et al., 2013). Given this and the increased stress of living with a chronic health condition, it is surprising that the multivariable findings did not detect associations between having an HIV-positive status and hypertension; alternately, this finding also suggests that HIV-positive men who are in care may maintain better health to avoid becoming hypertensive. Rather, men in this sample who had never been tested for HIV were identified to be at increased risk for hypertension compared with HIV-negative men. This finding suggests that, while MSM may be screened for hypertension, they may not be routinely screened for HIV. Current guidelines recommend that all MSM be screened at least annually for HIV, while those who report high-risk behaviors (e.g., condomless sex and drug use) should be screened more often (Workowski, Berman, & CDC, 2010). There appear to be missed opportunities for health care providers to assess sexual history and screen for HIV or sexually transmitted infections during routine medical appointments.

Limitations

As this was a cross-sectional survey, these results should be considered in the context of several important limitations. Based on a national estimation of MSM by race/ethnicity (Lieb et al., 2011), the current study underrepresented minorities; specifically, White men were overrepresented by 12%, and Black and Hispanic men were underrepresented by 5% and 8%, respectively. Moreover, the sample was recruited from a sexual networking website for MSM and thus may not represent a general MSM population. In addition, all known risk factors associated with hypertension were not assessed. Specifically, the current study did not assess perceived barriers to care, such as health insurance costs, other reasons for not having health insurance, and access to culturally competent providers. Lifetime substance use disorders and current or lifetime tobacco use were not assessed as part of the study, preventing observations about the role of substance use in both health care utilization and hypertension. The survey also did not assess self-ratings of health, in general or specific to any condition. Subjective ratings of health may have contributed to the need factor in the model. Finally, the main outcome (i.e., hypertension diagnosis) is based on self-report. Men were not screened in person for hypertension and medical records were not used to extract hypertension history. As such, the current study was not able to detect cases of undiagnosed hypertension. A national study reported that 39.4% of U.S. adults were unaware of their hypertension (CDC, 2012). Although a medical examination would most conclusively establish whether someone was hypertensive, some MSM may not be out to their medical provider about their sexual orientation. Studies using various methods to assess hypertension among MSM are needed to triangulate information about hypertension among MSM.

Conclusions

Despite these limitations, using Andersen’s health service use model provided a framework in which to better understand risk and protective factors associated with hypertension. The results of this study have implications for future research regarding hypertension, as well as the overall provision of health care for MSM. Although many aspects of chronic disease self-management may be similar between heterosexual and sexual minority men, optimizing such programs may be difficult in health care settings that are not culturally competent to serve sexual minorities (Cahill & Makadon, 2014; Sánchez, Sánchez, Lunn, Yehia, & Callahan, 2014). Addressing health care inequities should continue to be a critical priority for improving the health of sexual minorities. To that end, future research that inquires about motivations for going to a health care provider (e.g., perceived or actual need of medical services, having health insurance, getting a regular checkup, work requirement) may indicate avenues for increasing health care utilization for MSM. Second, continued efforts to promote HIV testing during routine medical exams are needed. The adoption of a holistic approach to addressing MSM health, including routine screening for multiple physical and mental health conditions, is needed, but not yet realized in the United States. Furthermore, the Internet could serve as a potential access point for health screening and referral for care. Finally, to advance research in this area, national health surveys that include items to assess physical and mental health, as well as sexual identity, orientation, and behavior, are urgently needed to fully understand physical health disparities in sexual minorities (Sánchez et al., 2014).