Discrimination and Hypertension among a Diverse Sample of Racial and Sexual Minority Men Living with HIV: Baseline Findings of a Longitudinal Cohort Study

Discrimination and Hypertension among a Diverse Sample of Racial and Sexual Minority Men Living with HIV: Baseline Findings of a Longitudinal Cohort Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Discrimination and Hypertension among a Diverse Sample of Racial and Sexual Minority Men Living with HIV: Baseline Findings of a Longitudinal Cohort Study Avrum Gillespie, Rui Song, John Barile, Lorie Okada, Shari Brown, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3838090/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 26 Jun, 2024 Read the published version in Journal of Human Hypertension → Version 1 posted 9 You are reading this latest preprint version Abstract Racial and sexual orientation discrimination may exacerbate the double epidemic of hypertension and HIV that affects men of color who have sex with men (MSM). This was a cross-sectional analysis of African American, Asian American, Native Hawaiian or Pacific Islander (NHPI) MSM living with HIV (PLWH) cohort in Honolulu and Philadelphia. Racial and sexual orientation discrimination, stress, anxiety, and depression was measured with computer assisted self-interview questionnaires (CASI). We examined the associations between racial and sexual orientation discrimination with hypertension measured both in the office and by 24-hour ambulatory blood pressure monitoring (ABPM) using multivariable logistic regression. Sixty participants (60% African American, 18% Asian, and 22% NHPI) completed CASIs and 24-hour ABPM. African American participants (80%) reported more daily racial discrimination than Asian American (36%) and NHPI participants (17%, p < 0.001). Many participants (51%) reported daily sexual orientation discrimination. Sixty-six percent of participants had hypertension by office measurement and 59% had hypertension by 24-hour ABPM measurement. Participants who experienced racial discrimination had greater odds of having office-measured hypertension than those who did not, even after adjustment ( Odds Ratio 5.1 (95% Confidence Interval [1.2–20.1], p = 0.01). This association was not seen with 24-hour ABPM. Hypertension was not associated with sexual orientation discrimination. In this cohort, MSM of color PLWH experience significant amounts of discrimination and hypertension. Those who experienced racial discrimination had higher in-office blood pressure. This difference was not observed in 24-hour APBM and future research is necessary to examine the long term cardiovascular effects. Health sciences/Diseases/Cardiovascular diseases/Hypertension Health sciences/Risk factors Health sciences/Health care/Diagnosis Health sciences/Medical research Hypertension Discrimination Asian Native Hawaiian Pacific Islander Black/ African American HIV/AIDS Men who have sex with men 24 ambulatory blood pressure monitor nocturnal dip Figures Figure 1 INTRODUCTION A double epidemic of hypertension (HTN) and HIV affects men of color who have sex with men (MSM). People living with HIV (PLWH) have greater rates of HTN than those without the disease.[ 1 ] The biological mechanisms of HTN in HIV include endothelial dysfunction and the adverse effects of anti-retroviral therapy.[ 2 ] Meanwhile, among PLWH of color in the United States (U.S.), the stress of racial discrimination may also increase blood pressure (BP).[ 4 , 5 ] Furthermore, racial minority MSM are often exposed to homophobia,[ 6 ] causing stress that could also increase BP. Currently, there is no systematic study addressing how these factors influence HTN among African American, Asian American, and Native Hawaiian or Pacific Islander (NHPI) MSM living with HIV – three racial groups which are disproportionally affected by the HIV epidemic in the U.S. For example, MSM composed 37% of new HIV diagnoses in African Americans,[ 7 ] 89% in Asian Americans,[ 8 ] and 84% in NHPIs, respectively.[ 9 ] The 24-hour ambulatory BP monitor (ABPM), often under-utilized in clinical practice, can more accurately predicts target organ damage and cardiac risk compared to office BP.[ 10 , 11 ] ABPM not only differentiates between sustained HTN, white-coat HTN, and masked HTN, but also detects the normal physiologic nocturnal BP dip (10% drop in average BP during the nighttime compared to daytime).[ 11 , 12 ] The nocturnal dip is a phenomenon associated with circadian sympathetic rhythm[ 13 ] and normotensive or hypertensive individuals with a blunted “dipping” response are at increased risk for target organ damage and cardiovascular mortality.[ 11 ] African Americans and Asian Americans have been shown to have higher rates of non-dipping compared to whites.[ 14 , 15 ] Several studies with African American participants have found that low or reverse nocturnal dip was associated with stress-inducing social factors including poverty,[ 16 ] being unmarried, low education status,[ 14 ] post-traumatic stress disorder,[ 16 ] low perceived social support,[ 14 , 15 ] and everyday discrimination.[ 17 ] The research linking social factors to the high non-dipping rate in Asian Americans and NHPIs is limited. There is also a lack of evidence on the association between HTN and racial and sexual orientation discrimination among MSM of color living with HIV. Given the higher rates of HTN and potential for psychosocial stress from discrimination among individuals, we report the baseline analysis of a longitudinal HIV and HTN cohort study examining the relationship of discrimination, psychosocial stress, and HTN on Asian American and NHPI MSM living with HIV in Hawai’i as well as African American MSM living with HIV in Philadelphia (see Fig. 1 ). Hawaiʽi was chosen because of its prevalent Asian (42.9%) and NHPI population (9.6%) who despite their plurality still experience systematic racism and discrimination.[ 18 , 19 ] Philadelphia was chosen for its prevalent African American population (41.4%) who also despite their plurality, experience systematic racism and discrimination. No white MSM were part of this study because the goal of the study was to look at intersection of race and sexual discrimination among racial minority groups.[ 20 ] We hypothesize that there is an additive effect of these stressors on hypertension and non-dipping. MATERIALS AND METHODS Study Design and Setting Data were derived from baseline assessments of an ongoing longitudinal HIV and HTN cohort study in Hawai‛i) and Philadelphia. Eligible participants were recruited at clinics affiliated with our respective universities and governmental and non-governmental organizations such as AIDS Service Organization who serve MSM. Data were collected between May 2019 and August 2020. This study was performed in line with the principles of the Declaration of Helsinki and approved by the University of Hawai`i institutional review board. Participants To be eligible for all activities, a participant must (1) have been age 18 or above (2) self-identify as African American, Asian, Native Hawaiian, or Other Pacific Islander, (3) self-identify as a biological male; (4) self-report having had sex with men in the last 12 months (oral, anal, or both); (5) a verifiable HIV-positive status; (6) have been able to give verbal and written consent; and (7) have been intending to stay in local study site area (Hawaiʽi or Philadelphia) for the next 36 months. Procedures After consent was obtained, each participant: (1) completed a computer-assisted self-interviewing (CASI) based psychosocial and behavioral assessment to minimize bias and (2) learned how to use the ABPM device. Participants were compensated $ 20 for completing the CASI-survey and use of the ABPM. Data Sources The data steward (JB) has access to information that could identify individual participants during and after data collection. Such sensitive personal data will be stored in a locked filing cabinet in a locked office, separately from survey or testing data (which will be stored in a separate locked filing cabinet) and used only for recruitment and retention purposes. Measurement The primary outcome measures were HTN measured in the office, HTN by 24-hour ABPM, and nocturnal dip. The primary exposures were sexual orientation discrimination and racial discrimination. Potential confounders included location, number of comorbidities. Socio-demographic Characteristics Socio-demographic variables included age, race/ethnicity, family characteristics, occupation, family income, education, marital status, and neighborhood characteristics. Psychosocial Measures The CASI-based assessment collected the following psychosocial measures to minimize bias: internalized homophobia scale,[ 6 ] experience of discrimination scale,[ 21 ] substance use/misuse, Center of Epidemiologic Studies Depression Scale,[ 22 ] Perceived Stress Scale,[ 23 ] Overall Depression Severity and Impairment Scale (OASIS),[ 24 ] and generalized anxiety disorder scale.[ 25 ] Health History The CASI-based assessment included participants’ history of hypertension, their history family history of hypertension, and Multiple Chronic Health Conditions Inventory.[ 26 ] The participants’ viral loads, heights, and weights were obtained from the electronic medical record. ABPM Assessment. Immediately after the completion of the CASI-based assessment, participants engaged in 24-hour ABPM monitoring using the Welch-Allyn or SpaceLabs® system. After placing the monitor with patient seated for 5 minutes per AHA standard guidelines,[ 27 ] 3 readings were recorded at 3-minute interval. Subsequently, the ABPM monitor obtained readings at 30-minute intervals. The ABPM was considered adequate and included for analysis if the monitor had been worn for a full 24 hours and if there were at least 10 acceptable daytime readings and 5 acceptable nighttime readings according to the International Database of Ambulatory BP in relation to Cardiovascular Outcome (IDACO) criteria.[ 28 ] Data from the monitor were downloaded locally, de-identified, and transmitted electronically for analysis. The definition of daytime and nighttime is based on the self-reported activity log, which is thought to be more reliable than fixed time intervals.[ 29 ] For intact BP data without available activity log, we used 9 AM − 9 PM as daytime and 1 AM − 6 AM as nighttime. The BP readings are further stratified into different phenotypes for comparison. Dipping status is calculated as 1 the ratio of the average systolic BP from nighttime divided by daytime. We defined individuals with nocturnal systolic BP dipping of less than 10% as “non-dipper.”[ 30 ] Hypertension was defined as having an office BP ≥ 130/80 mmHg, and/or average 24-hour ABPM readings ≥ 125/75mmHg.[ 30 ] Masked hypertension refers to a normal office BP with hypertension on ABPM reading and white-coat hypertension refers to hypertension in the office with normal ABPM readings. Analytic Strategies This study’s sample size was determined by a power analysis for detecting the endpoint of the longitudinal study that suggests that linear latent growth models with 400 participants across two groups (e.g., Philadelphia and Honolulu) with four assessment points can reach a power level of 0.80 for investigating differences in intercepts and slopes with a small-medium effect size. In addition, describing patterns of change within individual participants over time will allow us to identify trends within groups. This study is a baseline analysis of this cohort. Categorical and dichotomous variables are presented as frequency counts and percentages; continuous variables are summarized by their mean and standard deviation ( SD ) or median and interquartile range ( IQR ), as appropriate. Two-tailed bivariate analyses were used as appropriate. Missing data was case-wise deleted for the analyses. Missing data is reported in tables. Five multivariable logistic regression models were created with the main independent variables of interest were racial discrimination. Model 1 tests the univariate association of with the dependent variable of office-based hypertension. Models 2 adds study site and Model 3 adds number of comorbidities. For Model 4, the dependent variable was 24-hour SBP. For Model 5, the dependent variable was nocturnal dip. We inspected the model residual plots for normality and homoscedasticity. SPSS version 27[ 31 ] was used for the descriptive and bivariate and STATA 15[ 32 ] was used for multivariable analyses. Two sensitivity analyses were performed using bootstrap replication. The first sensitivity analysis was a bootstrap with 1000 replications performed on the association of daily racial discrimination and office measured hypertension. The second analyses were separating the data into each site (Hawaii and Philadelphia) and running a bootstrap univariate logistic regression with 1000 replications for each site. RESULTS Socio-demographic and Clinical Characteristics Seventy-five participants were enrolled, 60 (80%) completed their questionnaire and ABPM in accordance with the IDACO criteria and were included in the analysis. Table 1 presents key socio-demographic characteristics of the sample. Thirty-six participants were recruited and enrolled in Philadelphia, and 24 in Hawaiʽi with 23 from the island of Oʽahu and 1 from the island of Hawaiʽi. Enrollment was ended early as a result of the COVID-19 pandemic. Table 1 Sociodemographics and Self Reported Clinical Data by Race and Ethnicity Black N = 36 (59%) Asian N = 11 (19%) NHPI N = 13 (22%) Total N = 60 P Value Age Mean (SD) 48 (12) 48 (13) 52 (13) 49 (12) .67 Level of Education .73 Grade 12 or Less 10 (28%) 2 (18%) 3 (23%) 15 (25%) Some College 18 (50%) 4 (36%) 5 (39%) 27 (45%) Bachelor’s Degree or Higher 8 (22%) 5 (45%) 5 (39%) 18 (30%) Employment .06 Full-time 14 (39%) 4 (36%) 3 (23%) 21 (35%) Part-time 5 (14%) 1 (9%) 0 (0%) 6 (10%) Self-employed 2 (6%) 2 (18%) 0 (0%) 4 (7%) Retired 0 (0%) 2 (18%) 1 (8%) 3 (3%) On Disability 11 (31%) 1 (9%) 4 (31%) 16 (27%) Not employed 4 (11%) 1 (9%) 5 (39%) 10 (17%) Income < 40K 32 (89%) 6 (55%) 7 (54%) 45 (75%) .01 Married or Cohabiting 4 (11%) 5 (45%) 1 (8%) 10 (17%) .02 Substance Use 20 (57%) 5 (45%) 6 (46%) 31 (53%) .69 Family History of HTN 19 (54%) 7 (64%) 5 (45%) 31 (54%) .69 Self – HTN 17 (47%) 2 (18%) 3 (25%) 22 (37%) .13 Taking HTN medicines 13 (36%) 2 (18%) 3 (25%) 18 (31%) .47 Heart Disease 3 (9%) 1 (9%) 1 (9%) 5 (9%) .99 High Cholesterol 12 (33%) 4 (36%) 3 (23%) 19 (32%) .74 Chronic Pain 9 (25%) 1 (9%) 5 (39%) 15 (25%) .25 Diabetes 6 (17%) 2 (18%) 3 (23%) 11 (18%) .88 Depression 23 (64%) 6 (55%) 5 (39%) 34 (57%) .28 Anxiety 19 (53%) 3 (27%) 2 (15%) 24 (40%) .04 Sleep Disorder 11 (31%) 3 (27% 3 (25%) 17 (29%) .90 Hepatitis C 4 (12%) 0 (0%) 1 (8%) 4 (9%) .46 Height in. Mean (SD) 71 (3) 67 (2) 68 (3) 69 (3) .001 Weight lbs. Mean (SD) 182 (33) 151 (19) 179 (56) 175 (39) .08 BMI Mean (SD) a 26 (4) 24 (2) 27 (7) 26 (5) .13 Viral Load Median (IQR) b 0 (0–0) 12.5 (0–14,372) 0 (0–0) 0 (0–0) .09 CD4 Mean (SD) c 631 (288) 863 (422) 472 (379) 628 (317) .25 Table 1. shows sociodemographics and self reported clinical data by race and ethnicity. Native Hawaiian or Pacific Islander (NHPI), standard deviation (SD), $40,000 (40K), history (Hx), hypertension (HTN), Body Mass Index (BMI). a. BMI was Missing in 5 participants b. Viral load was missing in 22 participants c. CD4 was missing in 28 participants The mean age of the participants was 49 ± 12 years old (Table 1 ). Fifty-nine percent of the participants identified as Black or African American, 14% as Asian (Filipino, Chinese, Japanese, Korean, Okinawan), and 22% NHPI. Six participants identified as multiethnic and were recoded based on their ethnic minority status. All the participants from Philadelphia identified as Black or African American. Most participants (77%) reported at least one medical co-morbidity (Mean 5 ± 3, data not tabled). Thirty seven percent reported having HTN and 32% reported high cholesterol. As for psychiatric co-morbidities 56% of participants reported having Depression, 39% having anxiety, and 28% having a sleep disorder. BP Measurements and HTN Awareness by Race Table 2 presents BP measurements stratified by race. Asian participants had significantly lower in office diastolic BPs (DBP), 24 ABPM, and nocturnal DBP resulting in the lower rates of 24 ABPM hypertension when compared to African American and NHPI. African American participants had the highest in office DBP whereas NHPIs had the highest 24 ABPM DBP. NHPIs also had the highest rates of hypertension (85%) as measured by 24 ABPM. Overall, 59% of participants had HTN measured by 24-hour APBM and 54% were non-dippers. Table 2 Association between Self Reported Race and Ethnicity and Blood Pressure Measurements Variables Black N = 36 (60%) Asian N = 11 (18%) NHPI N = 13 (19%) Total N = 60 p Value HTN Measured In-office HTN 26 (72%) 4 (40%) 10 (77%) 40 (68%) .11 Office SBP mmHg 132 (13) 120 (14) 130 (17) 130 (14) .07 Office DBP mmHg 87 (11) 78 (10) 86 (9) 85 (11) .05 Aware of Office HTN (n = 45) 17 (61%) 2 (33%) 3 (27%) 22 (49%) .12 24H ABPM HTN 21 (58%) 4 (36%) 11 (85%) 36 (60%) .05 24H ABPM SBP 120 (9) 117 (12) 127 (15) 121 (12) .10 24H ABPM DBP 75 (6) 74 (9) 82 (11) 77 (9) .03 Total Wake Hours 15 (3) 13 (3) 16 (4) 15 (3) .25 Wake SBP 125 (10) 122 (12) 129 (18) 126 (12) .38 Wake DBP 80 (7) 78 (9) 84 (13) 81 (9) .25 Sleep SBP 113 (12) 108 (13) 119 (16) 113 (13) .10 Sleep DBP 68 (8) 68 (9) 77 (12) 70 (10) .02 Aware of 24 ABPM HTN 17 (68%) 2 (33%) 3 (30%) 22 (54%) .07 White Coat HTN 8 (22%) 1 (10%) 2 (17%) 11 (19%) .67 Masked HTN 3 (8%) 1 (10%) 3 (25%) 7 (12%) .30 Non-dipper 19 (53%) 5 (45%) 8 (62%) 32 (53%) .73 % Nocturnal Dip SBP 10 (7) 11 (7) 7 (10) 10 (8) .33 % Nocturnal Dip DBP 14 (9) 12 (8) 8 (10) 10 (8) .10 Table 2 shows the association between in self-reported race and in office blood pressure measurements, 24 hour ambulatory blood pressure measurements, nocturnal dip in blood pressure. All values are Mean and Standard deviation unless otherwise specified. Native Hawaiian or Pacific Islander (NHPI), systolic blood pressure (SBP), diastolic blood pressure (DBP), 24 hour ambulatory blood pressure monitoring (24H ABPM). Forty five percent of participants with elevated in-office systolic BP (SBP) and 39% with elevated 24h-ABPM SBP were not aware of their hypertension and thus not taking anti-hypertensive medication (Table 2 ). Rates of hypertension awareness were the lowest among NHPI. Seventy percent of the NHPI participants with elevated in office SBP were not receiving anti-hypertensive medication (data not in table). It should be noted that 8 participants, 12%, had masked HTN (Table 2 ). Discrimination and Psychosocial Measurements As shown in Table 3 , a greater percentage of Black participants reported daily racial discrimination compared to Asians and NHPIs and as a result more participants in Philadelphia experienced discrimination than in Hawaii. The most common racial discrimination was being discriminated against on the street or in a public place (79%), followed around in a store (74%), and discriminated against at school (56%). Fifty-one percent of participants reported daily sexual discrimination. The most common sexual orientation discrimination was being discriminated against on the street or in a public place (73%), discriminated against at school (57%), and getting poor service at a store or restaurant (50%, data not in tables). Race was not associated with sexual discrimination. Participants who experienced racial and sexual discrimination also had more co-morbidities (5.0 ± 3.7 vs. 2.5 ± 3.8, p = 0.002 and 5.0 ± 3.7 vs. 2.5 ± 2.6, p = 0.006; respectively). Participants who experienced racial discrimination scored higher on the Overall Anxiety Severity and Impairment Scale (OASIS) than those who did not (5.5 ± 4.8 vs. 3.0 ± 3.6, p = 0.02). This difference in the OASIS was not observed in participants who experienced sexual orientation discrimination. Racial and sexual orientation discrimination was not associated with a difference in the Center of Epidemiologic Studies (CES) depression scale, perceived stress, Generalized Anxiety Disorder (GAD) scale. Table 3 Racial and Sexual Orientation Discrimination by Demographics, Psychosocial Stress, and Hypertension. Experienced Daily Racial Discrimination a Experienced Sexual Orientation Discrimination Yes N = 35 (59%) No N = 24 (41%) p value Yes N = 31 (52%) No N = 29 (48%) p value Site < 0.001 0.07 Philadelphia 29 (83) 7 (29) 22 (71) 14 (48) Hawaii 6 (17) 17 (71) 9 (29) 15 (52) Race/Ethnicity < 0.001 0.15 Black 29 (83) 7 (29) 22 (71) 14 (48) Asian 4 (11) 7 (29) 5 (16) 6 (21) NHPI 2 (6) 10 (42) 4 (13) 9 (31) Number Comorbidities mean (SD) 5.0 (3.7) 2.5 (3.8) 0.002 5.0 (3.9) 2.7 (2.6) 0.006 Psychological Measurements CES-Depression Scale mean (SD) 9.7 (6.5) 7.6 (6.8) 0.22 9.0 (6.5) 8.7 (6.9) 0.90 Perceived Stress Scale mean (SD) 15.4 (8.0) 13.6 (7.8) 0.38 15.3 (7.2) 14.0 (8.6) 0.53 OASIS mean (SD) 5.5 (4.8) 3.0 (3.6) 0.02 4.4 (4.1) 4.5 (5.0) 0.99 Generalized Anxiety Disorder Scale mean (SD) 5.3 (4.5) 3.8 (4.1) 0.18 5.0 (4.5) 4.3 (4.3) 0.56 Hypertension Measurements b Office SBP mean (SD) 133 (12) 124 (16) 0.02 130 (11) 129 (16) 0.79 Office DBP mean (SD) 88 (10) 81 (11) 0.005 87 (11) 84 (12) 0.36 24-hour ABPM SBP mean (SD) 120 (10) 121 (12) 0.80 122 (11) 120 (12) 0.69 24-hour ABPM DBP mean (SD) 76 (8) 76 (8) 0.96 77 (7) 76 (10) 0.81 Nocturnal Dip SBP (%) mean (SD) 11 (7) 9 (9) 0.35 9 (8) 11 (8) 0.23 Nocturnal Dip DBP (%) mean (SD) 14 (9) 10 (9) 0.11 13 (10) 12 (9) 0.90 Office HTN 28 (80) 11 (48) 0.01 22 (71) 17 (63) 0.52 24 ABPM HTN 21 (60) 14 (58) 0.90 21 (68) 15 (52) 0.21 Non-Dipper 18 (51) 13 (54) 0.59 19 (61) 13 (45) 0.20 HTN Awareness (n = 45,46) c 18 (62) 5 (31) 0.05 14 (56) 9 (43) 0.37 Table 3. Shows the demographic, psychologic, and blood pressure difference in participants who experienced daily racial and daily sexual orientation discrimination. All categorical variables are represented as count and (percentage). Continuous variables are represented as mean and (standard deviation). Standard deviation (SD), Native Hawaiian or Pacific Islander (NHPI), systolic blood pressure (SBP), diastolic blood pressure (DBP), ambulatory blood pressure monitoring (ABPM), Overall Anxiety Severity and Impairment Scale (OASIS), Center of Epidemiologic Studies (CES). One participant did not answer the question about daily racial discrimination. One participant did not have his blood pressure measured in the office. This among participants who had a SBP > 130 in the office or a self-reported history of HTN. Discrimination and HTN Participants who experienced daily racial discrimination had higher office systolic and diastolic BP compared to those who did not experience daily racial discrimination (SBP 133 ± 12 vs. 124 ± 16, p = 0.02 and DBP 88 ± 10 vs. 81 ± 11, p = 0.005; respectively). Thus, more participants who had experienced racial discrimination met the criteria for HTN by in-office BP measurement. This association between racial discrimination and HTN was not seen on 24-hour ABPM SBP&DBP, and percent dip in nocturnal SBP. Daily sexual orientation was not associated with office-based and 24-hour ABPM SBP nor nocturnal SBP dip. Next, we created logistic regression models to examine the contribution of other variables to office hypertension including the survey site and the number of co-morbidities. Model 1 is the unadjusted model indicating that participants who experience daily racial discrimination had 4.4 greater odds (odds ratio OR 4.4 (95% confidence interval CI [1.4–14.0], p = 0.01, Table 4 , Model 1) of having hypertension than those who did not. Model 2 adjusts for the survey site and shows that office measured HTN remained significantly associated with racial discrimination ( OR 5.1 95%CI [1.2–20.1], p = 0.02; Model 2, Table 4 ) despite there being significantly more discrimination at the Philadelphia site than the Hawaii site. Next, we added the number of comorbidities, as this was significantly associated with discrimination and could explain hypertension. The number of comorbidities; however, was not associated with hypertension, and discrimination remained significantly associated with hypertension, but the model was no longer significant (Table 4 , Model 3). We also adjusted the model for age and BMI and racial discrimination remained significantly associated with hypertension (see Supplemental Table 3). Neither hypertension as measured by 24 hour ABPM (Table 4 , Model 4) or nocturnal dip (Table 4 , Model 5) were associated with discrimination after multivariable adjustment. Table 4 Linear associations of Discrimination, Race, Social Support with Office Systolic Blood Pressure, 24 Hour ABPM Systolic Blood Pressure, and Percent Dip in Systolic Blood Pressure Variables Model 1 Office HTN Discrimination Univariate N = 58 p = 0.03, R 2 = 0.15 Model 2 Office HTN Discrimination and Site N = 58, p = 0.04, R 2 = 0.15 Model 3 Office HTN Discrimination, Site, and Comorbidities N = 58, p = 0.07, R 2 = 0.16 Model 4 24H-ABPM HTN Discrimination, Site, and Comorbidities N = 59, p = 0.90, R 2 = 0.00 Model 5 Nocturnal Dip Discrimination, Site, and Comorbidities N = 59, p = 0.99, R 2 = 0.00 Daily Racial Discrimination 4.4 [1.4, 14.0], 0.01 5.1 [1.2–20.1], 0.02 5.9 [1.3–26.7], 0.02 1.1 [0.3–4.1], 0.90 0.8 [0.2 -3.0], 0.81 Hawaii (Site) 1.3 [0.3–5.5], 0.70 1.3 [0.3–5.5], 0.71 0.8 [0.2–2.9], 0.81 1.1 [0.3–3.9], 0.86 Number of Comorbidities 0.94 [0.8–1.1], 0.94 1.0 [0.9–1.2], 0.64 1.0 [0.9–1.2], 0.87 Table 4. shows the linear associations between discrimination, race, social support with in office systolic blood pressure (Model 1), 24 hour ambulatory blood pressure monitoring (Model 2) and percentage dip in nocturnal dip in systolic blood pressure (Model 3). A negative coefficient in Model 3 represents an increase in nocturnal systolic blood pressure. Systolic blood pressure (SBP). Native Hawaiian or Pacific Islander (NHPI). Ambulatory blood pressure monitor (ABPM). Sensitivity Analyses Racial discrimination remained associated with office measured hypertension after one thousand bootstrap replications (4.4 [1.3, 15.2], 0.02, Supplemental Table 2, Analysis 1). In analysis two, there was a similar positive association of racial discrimination and HTN when examined at Site 1, Hawaiʽi (5.0 [1.0–25.2], 0.05) and Site 2, Philadelphia (5.1 [0.8–32.2], 0.08); however, the associations were no longer significant after one thousand boot strap replications. DISCUSSION We set out to examine the baseline burden of racial discrimination, sexual orientation discrimination, and HTN among MSM of color living with HIV. We found that most participants experienced racial discrimination (59%) and sexual orientation discrimination (51%). African American participants experienced the most racial discrimination. Participants also had a high burden of HTN (including an absence of a nocturnal dip). Racial discrimination was associated with higher BP in the office but not on 24-hour APBM or nocturnal dip. There were no associations between sexual orientation discrimination and HTN. We were surprised that only the office and not 24-hour BP measurements were elevated in the context of exposure to racial discrimination. Previous studies have found a differential effect of racial discrimination on HTN, with lifetime discrimination increasing the incidence of HTN whereas daily reported discrimination did not,[ 5 , 6 ] suggesting that the long-term systemic effects of racism may be more impactful than the daily stressors. One explanation for the differences in office and 24-H ABPM measurement could be office measurement error; however, if so, the effects would differ by site. Another explanation for differences in office and 24 ABPM is white coat HTN. Thirty percent of those who had HTN in the office and experienced daily discrimination had white coat HTN. White coat hypertension has been associated with anxiety [ 33 ] and the racial discrimination participants experienced while coming to their clinical triggered their anxiety resulting in higher office BP measurements but the rest of the time, they avoided these daily triggers of racial discrimination and had normal BP measurements. Of note, white coat HTN although initially thought to be benign, has been associated with increased cardiovascular-related deaths [ 12 ]. Thus, we will continue to follow this cohort for the long-term effects of racial discrimination on hypertension and cardiovascular outcomes. Racial minorities are at an increased risk for both HIV and HTN resulting in a potential syndemic[ 34 ] and we examine the results of this cohort to previous studies. In our study, the prevalence of HTN among the study’s Asian cohort, 36%, was like the prevalence from a meta-analysis of 49 studies from the Americas, Europe, Africa, and Asia which estimated that 35% of HIV-positive patients receiving antiretroviral therapy have HTN.[ 35 ] We can also compare the prevalence of HTN in this study to studies of HIV uninfected individuals. For example, 57% of African American participants LWH had hypertension, which is similar to the Cardia study[ 5 ] which found that 50% of HIV uninfected African American participants have HTN by age 46 and 75% by age 55. In our study, NHPI participants living with HIV had the highest prevalence of HTN (85%). This is much higher than previous estimates of NHPI uninfected by HIV which were between 23% and 52%. [ 36 , 37 ] Further research is needed to confirm this high prevalence. In our study, the prevalence of non-dippers or reverse dippers was 68%. Similarly, a South African study of nocturnal dipping and HIV found the prevalence of non-dipping of 65%.[ 38 ] It should be noted that 91% of this sample in that study was female. A meta-analysis by Kent et al.[ 39 ] of 8 studies also found less nocturnal dipping in HIV-positive individuals than HIV-negative individuals. Previous studies have also linked systemic racism and the resulting post-traumatic stress disorder to non-dipping;[ 16 ] however, in our study, discrimination was not associated with loss of nocturnal dip. These results must be interpreted in the context of their limitations. First, the study was limited by the sample size because recruitment was terminated early because of the COVID-19 pandemic. This minimized the number of variables we could simultaneously analyze in our conceptual model. While these are two very different geographical sites, levels of racial discrimination and discrimination may vary in other locations. Our sample size was also limited by excluding 21% of participants because of incorrect usage of ABPM. Further, efforts should be made to increase hypertension awareness because only 45% of participants with a SBP greater than 130 mmHg,[ 27 ] and 33% with a SBP > 140 mmHg were aware of their diagnosis of hypertension.[ 40 ] Interventions should examine both patient level and provider level barriers to hypertension awareness. Lastly, this study is a cross-sectional baseline analysis and further research is underway to examine how discrimination and inflammation affect long term cardiovascular outcomes. In conclusion, this study provides insights and baseline information about the complex interplay of psychosocial factors and cardiovascular disease among MSM of color living with HIV. Further, many participants with elevated BP were either unaware or undiagnosed with HTN. This finding identifies opportunities for health interventions to improve HTN awareness and treatment in these high cardiovascular risk populations. Abbreviations HTN – hypertension PLWH - people living with HIV MSM - men who have sex with men U.S. – United States BP – blood pressure NHPI - Native Hawaiian or Pacific Islander ABPM - ambulatory BP monitor CASI - computer-assisted self-interviewing IDACO - International Database of Ambulatory BP in relation to Cardiovascular Outcome SD - standard deviation IQR - interquartile range DBP – diastolic blood pressure SBP – systolic blood pressure OASIS - Overall Anxiety Severity and Impairment Scale CES - Center of Epidemiologic Studies GAD - Generalized Anxiety Disorder OR – odds ratio CI – confidence interval BMI – body mass index Declarations Availability of data and material: Deidentified data and materials are available by request from Dr. Barile and approval of Principal investigator’s Drs. Ma and Wong as is permitted within the scope of the IRB protocol given the senstitive and protected nature of the data. Code availability: Code is available upon request. Acknowledgments : This research was funded by National Institue of Minority Health of the National Institutes of Health under the award grant (G.M. and F.W). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Author Contributions : Frank Wong, Grace Ma, Jack Barile, and Crystal Gadegbeku contributed to the study conception and design. Material preparation and data collection were performed by Lorie Okada, Shari Brown, Kerry Traub, Gina M. Simoncini, Yin Tan, and Julia Trout. Data analysis was performed by Avrum Gillespie, Rui Song, and Jack Barile. The first draft of the manuscript was written by Avrum Gillespie and Rui Song and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Ethics approval and consent to participate : This study was approved by the University of Hawai`i institutional review board. Written informed consent was obtained from all participants. The clinical and research activities being reported here are consistent with the adherence to the Declaration of Helsinki Conflicts of interest/competing interests: The authors have no relevant financial or non-financial interests to disclose. Funding source: This research was funded by National Institue of Minority Health of the National Institutes of Health under the award grant (G.M. and F.W). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. References Schouten J, Wit FW, Stolte IG, et al. Cross-sectional comparison of the prevalence of age-associated comorbidities and their risk factors between HIV-infected and uninfected individuals: the AGEhIV cohort study. Clin Infect Dis . 2014;59(12):1787-1797. Fahme SA, Bloomfield GS, Peck R. Hypertension in HIV-infected adults: novel pathophysiologic mechanisms. Hypertension . 2018;72(1):44-55. Sims M, Diez-Roux AV, Dudley A, et al. Perceived discrimination and hypertension among African Americans in the Jackson Heart Study. Am J Public Health . 2012;102(S2):S258-S265. Krieger N, Sidney S. Racial discrimination and BP: the CARDIA Study of young black and white adults. Am J Public Health . 1996;86(10):1370-1378. Forde AT, Lewis TT, Kershaw KN, Bellamy SL, Diez Roux AV. Perceived Discrimination and Hypertension Risk Among Participants in the Multi-Ethnic Study of Atherosclerosis. J Am Heart Assoc . 2021 Feb;10(5):e019541. doi: 10.1161/JAHA.120.019541. Igartua KJ, Gill K, Montoro R. Internalized homophobia: A factor in depression, anxiety, and suicide in the gay and lesbian population. Can J Commun Ment Health . 2009;22(2):15-30. CDC. HIV among African Americans. https://wwwcdcgov/hiv/group/racialethnic/africanamericans/indexhtml. Retrieved October 10, 2020. CDC. HIV among Asian Americans. https://wwwcdcgov/hiv/group/racialethnic/asians/indexhtml. Retrieved October 10, 2020. CDC. HIV among Native Hawaiians and Other Pacific Islanders in the United States. https://wwwcdcgov/hiv/group/racialethnic/asians/indexhtml. Retrieved October 10, 2020. Siu AL, USPSTF. Screening for high BP in adults: US Preventive Services Task Force recommendation statement. Ann Intern Med . 2015;163(10):778-786. Routledge FS, McFetridge-Durdle JA, Dean C. Night-time BP patterns and target organ damage: a review. Can J Cardiol . 2007;23(2):132-138. Cohen JB, Lotito MJ, Trivedi UK, Denker MG, Cohen DL, Townsend RR. Cardiovascular Events and Mortality in White Coat Hypertension: A Systematic Review and Meta-analysis. Ann Intern Med . 2019 Jun 18;170(12):853-862. doi: 10.7326/M19-0223. Sherwood A, Steffen PR, Blumenthal JA, Kuhn C, Hinderliter AL. Nighttime BP dipping: the role of the sympathetic nervous system. Am J Hypertens . 2002;15(2):111-118. Spruill TM, Gerin W, Ogedegbe G, Burg M, Schwartz JE, Pickering TG. Socioeconomic and psychosocial factors mediate race differences in nocturnal BP dipping. Am J Hypertens . 2009;22(6):637-642. Brown DE, James GD, Aki SL, Mills PS, Etrata MB. A comparison of awake–sleep BP variation between normotensive Japanese–American and Caucasian women in Hawaii. Journal Hypertens . 2003;21(11):2045-2051. Mellman TA, Brown TSH, Kobayashi I, et al. BP dipping and urban stressors in young adult African Americans . Ann Behav Med . 2015;49(4):622-627. Tomfohr L, Cooper DC, Mills PJ, Nelesen RA, Dimsdale JE. Everyday discrimination and nocturnal BP dipping in black and white Americans. Psychosom Med . 2010;72(3):266. https://www.census.gov/quickfacts/fact/table/philadelphiacitypennsylvania,honolulucountyhawaii/PST045221. Last accessed May 31 st , 2022. Kaholokula JKa, Iwane MK, Nacapoy AH. Effects of perceived racism and acculturation on hypertension in Native Hawaiians. Hawaii Med J. 2010;69(5 suppl 2):11. Choi K-H, Paul J, Ayala G, Boylan R, Gregorich SE. Experiences of discrimination and their impact on the mental health among African American, Asian and Pacific Islander, and Latino men who have sex with men. Am J Public Health . 2013;103(5):868-874. Krieger N, Smith K, Naishadham D, Hartman C, Barbeau EM. Experiences of discrimination: validity and reliability of a self-report measure for population health research on racism and health. Soc Sci Med . 2005;61(7):1576-1596. Radloff LS. The CES-D scale: A self-report depression scale for research in the general population. Appl Psychol Meas . 1977;1(3):385-401. Cohen S, Kamarck T, Mermelstein R. Perceived stress scale. Measuring stress: A guide for health and social scientists. 1994;10(2):1-2. Bentley KH, Gallagher MW, Carl JR, Barlow DH. Development and validation of the Overall Depression Severity and Impairment Scale. Psychol Assess . 2014;26(3):815. Spitzer RL, Kroenke K, Williams JB, Löwe B. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med . 2006 May 22;166(10):1092-7. doi: 10.1001/archinte.166.10.1092. PMID: 16717171. Barile JP, Mitchell SA, Thompson WW, et al. Peer Reviewed: Patterns of Chronic Conditions and Their Associations with Behaviors and Quality of Life, 2010. Prev Chronic Dis. 2015 ;12. Brook RD, Rajagopalan S. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA Guideline for the Prevention, Detection, Evaluation, and Management of High BP in Adults. A report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines . Circulation . 2018;12(3):238-238. Thijs L, Hansen TW, Kikuya M, et al. The International Database of Ambulatory BP in relation to Cardiovascular Outcome (IDACO): protocol and research perspectives. Blood Press Monit . 2007;12(4):255-262. BOOTH III JN, Muntner P, Abdalla M, et al. Differences in nighttime and daytime ambulatory BP when diurnal periods are defined by self-report, fixed-times and actigraphy: improving the detection of hypertension study. J Hypertens . 2016;34(2):235. O’Brien E, Parati G, Stergiou G. Ambulatory BP measurement: what is the international consensus? Hypertension . 2013;62(6):988-994. IBM SPSS Statistics for Windows, Version 27.0. Armonk, NY: IBM Corp. StataCorp. 2017. Stata Statistical Software: Release 15 . College Station, TX: StataCorp LLC Mancia G, Bombelli M, Seravalle G, Grassi G. Diagnosis and management of patients with white-coat and masked hypertension. Nat Rev Cardiol. 2011; 8 (12):686–693. Singer M. Introduction to syndemics: A critical systems approach to public and community health. John Wiley & Sons; 2009. Xu Y, Chen X, Wang K. Global prevalence of hypertension among people living with HIV: a systematic review and meta-analysis. J Am Soc Hypertens . 2017;11(8):530-540. Grandinetti A, Chen R, Kaholokula JKa, et al. Relationship of BP with degree of Hawaiian ancestry. Ethn Dis. 2002;12(2):221-228. Curb JD, Aluli NE, Huang BJ, et al. Hypertension in elderly Japanese Americans and adult native Hawaiians. Public Health Rep . 1996;111(Suppl 2):53. Borkum M, Heckmann J, Manning K, et al. High prevalence of “non-dipping” BP and vascular stiffness in HIV-infected South Africans on antiretrovirals. PloS one. 2017;12(9):e0185003. Kent ST, Bromfield SG, Burkholder GA, et al. Ambulatory BP monitoring in individuals with HIV: a systematic review and meta-analysis. PloS one. 2016;11(2):e0148920. De Socio GV, Ricci E, Maggi P, Parruti G, Pucci G, Di Biagio A, Calza L, Orofino G, Carenzi L, Cecchini E, Madeddu G, Quirino T, Schillaci G; CISAI Study Group. Prevalence, awareness, treatment, and control rate of hypertension in HIV-infected patients: the HIV-HY study. Am J Hypertens . 2014 Feb;27(2):222-8. doi: 10.1093/ajh/hpt182. PMID: 24077828. Additional Declarations There is NO conflict of interest to disclose. Supplementary Files SupplementalMaterialLog.docx Supplemental Material SummaryTableJHH.docx Cite Share Download PDF Status: Published Journal Publication published 26 Jun, 2024 Read the published version in Journal of Human Hypertension → Version 1 posted Editorial decision: revise 20 Feb, 2024 Review # 2 received at journal 19 Feb, 2024 Reviewer # 2 agreed at journal 31 Jan, 2024 Review # 1 received at journal 28 Jan, 2024 Reviewer # 1 agreed at journal 17 Jan, 2024 Reviewers invited by journal 15 Jan, 2024 Editor assigned by journal 14 Jan, 2024 Submission checks completed at journal 08 Jan, 2024 First submitted to journal 05 Jan, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3838090","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":267240661,"identity":"98bd912e-c261-4f03-9302-bbc65a05bc88","order_by":0,"name":"Avrum 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19:40:53","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3838090/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3838090/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41371-024-00919-0","type":"published","date":"2024-06-26T04:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":49762734,"identity":"fa841826-c44b-475f-b83a-7e0782379b60","added_by":"auto","created_at":"2024-01-17 16:14:24","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":536477,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eConceptual Framework of Socio-ecological Risk Factors, Clinical Risk Factors, Health Related Quality of Life, and Systolic Blood Pressure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFigure 1 shows the conceptual framework of the study in which we hypothesize that socio-ecological risk factors exacerbate clinical risk factors which can affect health-related quality of life and hypertension. We also hypothesize that social support and resilience can reduce the effects of these risk factors. Anti-retroviral therapy (ART).\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3838090/v1/192e556d8dc103ee13b47ad1.jpeg"},{"id":59165926,"identity":"b97e2a56-e3b0-45d1-a780-91aabe7a53d8","added_by":"auto","created_at":"2024-06-27 07:09:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1734067,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3838090/v1/f299b9e5-0942-4e3f-9426-9e1cb0bb0711.pdf"},{"id":49762094,"identity":"b45b4f66-681a-41ed-8b4e-81ac0f3a2ba6","added_by":"auto","created_at":"2024-01-17 16:06:24","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":23188,"visible":true,"origin":"","legend":"\u003cp\u003eSupplemental Material\u003c/p\u003e","description":"","filename":"SupplementalMaterialLog.docx","url":"https://assets-eu.researchsquare.com/files/rs-3838090/v1/2f0ac09c3737069f54d6be56.docx"},{"id":49762095,"identity":"0e2488e3-09c3-4fb7-8bca-31ea6fcec07d","added_by":"auto","created_at":"2024-01-17 16:06:24","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":15280,"visible":true,"origin":"","legend":"","description":"","filename":"SummaryTableJHH.docx","url":"https://assets-eu.researchsquare.com/files/rs-3838090/v1/f9ee4051a864d785d073d6c6.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose.","formattedTitle":"Discrimination and Hypertension among a Diverse Sample of \r\nRacial and Sexual Minority Men Living with HIV: \r\nBaseline Findings of a Longitudinal Cohort Study","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eA double epidemic of hypertension (HTN) and HIV affects men of color who have sex with men (MSM). People living with HIV (PLWH) have greater rates of HTN than those without the disease.[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] The biological mechanisms of HTN in HIV include endothelial dysfunction and the adverse effects of anti-retroviral therapy.[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] Meanwhile, among PLWH of color in the United States (U.S.), the stress of racial discrimination may also increase blood pressure (BP).[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] Furthermore, racial minority MSM are often exposed to homophobia,[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] causing stress that could also increase BP.\u003c/p\u003e \u003cp\u003eCurrently, there is no systematic study addressing how these factors influence HTN among African American, Asian American, and Native Hawaiian or Pacific Islander (NHPI) MSM living with HIV \u0026ndash; three racial groups which are disproportionally affected by the HIV epidemic in the U.S. For example, MSM composed 37% of new HIV diagnoses in African Americans,[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] 89% in Asian Americans,[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] and 84% in NHPIs, respectively.[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eThe 24-hour ambulatory BP monitor (ABPM), often under-utilized in clinical practice, can more accurately predicts target organ damage and cardiac risk compared to office BP.[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] ABPM not only differentiates between sustained HTN, white-coat HTN, and masked HTN, but also detects the normal physiologic nocturnal BP dip (10% drop in average BP during the nighttime compared to daytime).[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] The nocturnal dip is a phenomenon associated with circadian sympathetic rhythm[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] and normotensive or hypertensive individuals with a blunted \u0026ldquo;dipping\u0026rdquo; response are at increased risk for target organ damage and cardiovascular mortality.[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eAfrican Americans and Asian Americans have been shown to have higher rates of non-dipping compared to whites.[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] Several studies with African American participants have found that low or reverse nocturnal dip was associated with stress-inducing social factors including poverty,[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] being unmarried, low education status,[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] post-traumatic stress disorder,[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] low perceived social support,[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] and everyday discrimination.[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] The research linking social factors to the high non-dipping rate in Asian Americans and NHPIs is limited. There is also a lack of evidence on the association between HTN and racial and sexual orientation discrimination among MSM of color living with HIV.\u003c/p\u003e \u003cp\u003eGiven the higher rates of HTN and potential for psychosocial stress from discrimination among individuals, we report the baseline analysis of a longitudinal HIV and HTN cohort study examining the relationship of discrimination, psychosocial stress, and HTN on Asian American and NHPI MSM living with HIV in Hawai\u0026rsquo;i as well as African American MSM living with HIV in Philadelphia (see Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Hawaiʽi was chosen because of its prevalent Asian (42.9%) and NHPI population (9.6%) who despite their plurality still experience systematic racism and discrimination.[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] Philadelphia was chosen for its prevalent African American population (41.4%) who also despite their plurality, experience systematic racism and discrimination. No white MSM were part of this study because the goal of the study was to look at intersection of race and sexual discrimination among racial minority groups.[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] We hypothesize that there is an additive effect of these stressors on hypertension and non-dipping.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Setting\u003c/h2\u003e \u003cp\u003eData were derived from baseline assessments of an ongoing longitudinal HIV and HTN cohort study in Hawai‛i) and Philadelphia. Eligible participants were recruited at clinics affiliated with our respective universities and governmental and non-governmental organizations such as AIDS Service Organization who serve MSM. Data were collected between May 2019 and August 2020. This study was performed in line with the principles of the Declaration of Helsinki and approved by the University of Hawai`i institutional review board.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eTo be eligible for all activities, a participant must (1) have been age 18 or above (2) self-identify as African American, Asian, Native Hawaiian, or Other Pacific Islander, (3) self-identify as a biological male; (4) self-report having had sex with men in the last 12 months (oral, anal, or both); (5) a verifiable HIV-positive status; (6) have been able to give verbal and written consent; and (7) have been intending to stay in local study site area (Hawaiʽi or Philadelphia) for the next 36 months.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eProcedures\u003c/h2\u003e \u003cp\u003e After consent was obtained, each participant: (1) completed a computer-assisted self-interviewing (CASI) based psychosocial and behavioral assessment to minimize bias and (2) learned how to use the ABPM device. Participants were compensated \u003cspan\u003e$\u003c/span\u003e20 for completing the CASI-survey and use of the ABPM.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eData Sources\u003c/strong\u003e \u003cp\u003eThe data steward (JB) has access to information that could identify individual participants during and after data collection. Such sensitive personal data will be stored in a locked filing cabinet in a locked office, separately from survey or testing data (which will be stored in a separate locked filing cabinet) and used only for recruitment and retention purposes.\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eMeasurement\u003c/h2\u003e \u003cp\u003eThe primary outcome measures were HTN measured in the office, HTN by 24-hour ABPM, and nocturnal dip. The primary exposures were sexual orientation discrimination and racial discrimination. Potential confounders included location, number of comorbidities.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003eSocio-demographic Characteristics\u003c/h2\u003e \u003cp\u003eSocio-demographic variables included age, race/ethnicity, family characteristics, occupation, family income, education, marital status, and neighborhood characteristics.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003ePsychosocial Measures\u003c/h2\u003e \u003cp\u003eThe CASI-based assessment collected the following psychosocial measures to minimize bias: internalized homophobia scale,[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] experience of discrimination scale,[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] substance use/misuse, Center of Epidemiologic Studies Depression Scale,[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] Perceived Stress Scale,[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] Overall Depression Severity and Impairment Scale (OASIS),[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] and generalized anxiety disorder scale.[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003eHealth History\u003c/h2\u003e \u003cp\u003eThe CASI-based assessment included participants\u0026rsquo; history of hypertension, their history family history of hypertension, and Multiple Chronic Health Conditions Inventory.[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] The participants\u0026rsquo; viral loads, heights, and weights were obtained from the electronic medical record.\u003c/p\u003e \u003cp\u003e\u003cb\u003eABPM Assessment.\u003c/b\u003e Immediately after the completion of the CASI-based assessment, participants engaged in 24-hour ABPM monitoring using the Welch-Allyn or SpaceLabs\u0026reg; system. After placing the monitor with patient seated for 5 minutes per AHA standard guidelines,[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] 3 readings were recorded at 3-minute interval. Subsequently, the ABPM monitor obtained readings at 30-minute intervals. The ABPM was considered adequate and included for analysis if the monitor had been worn for a full 24 hours and if there were at least 10 acceptable daytime readings and 5 acceptable nighttime readings according to the International Database of Ambulatory BP in relation to Cardiovascular Outcome (IDACO) criteria.[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] Data from the monitor were downloaded locally, de-identified, and transmitted electronically for analysis. The definition of daytime and nighttime is based on the self-reported activity log, which is thought to be more reliable than fixed time intervals.[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] For intact BP data without available activity log, we used 9 AM \u0026minus;\u0026thinsp;9 PM as daytime and 1 AM \u0026minus;\u0026thinsp;6 AM as nighttime. The BP readings are further stratified into different phenotypes for comparison. Dipping status is calculated as 1 the ratio of the average systolic BP from nighttime divided by daytime. We defined individuals with nocturnal systolic BP dipping of less than 10% as \u0026ldquo;non-dipper.\u0026rdquo;[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] Hypertension was defined as having an office BP\u0026thinsp;\u0026ge;\u0026thinsp;130/80 mmHg, and/or average 24-hour ABPM readings\u0026thinsp;\u0026ge;\u0026thinsp;125/75mmHg.[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] Masked hypertension refers to a normal office BP with hypertension on ABPM reading and white-coat hypertension refers to hypertension in the office with normal ABPM readings.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003eAnalytic Strategies\u003c/h2\u003e \u003cp\u003e This study\u0026rsquo;s sample size was determined by a power analysis for detecting the endpoint of the longitudinal study that suggests that linear latent growth models with 400 participants across two groups (e.g., Philadelphia and Honolulu) with four assessment points can reach a power level of 0.80 for investigating differences in intercepts and slopes with a small-medium effect size. In addition, describing patterns of change within individual participants over time will allow us to identify trends within groups. This study is a baseline analysis of this cohort.\u003c/p\u003e \u003cp\u003eCategorical and dichotomous variables are presented as frequency counts and percentages; continuous variables are summarized by their mean and standard deviation (\u003cem\u003eSD\u003c/em\u003e) or median and interquartile range (\u003cem\u003eIQR\u003c/em\u003e), as appropriate. Two-tailed bivariate analyses were used as appropriate. Missing data was case-wise deleted for the analyses. Missing data is reported in tables.\u003c/p\u003e \u003cp\u003eFive multivariable logistic regression models were created with the main independent variables of interest were racial discrimination. Model 1 tests the univariate association of with the dependent variable of office-based hypertension. Models 2 adds study site and Model 3 adds number of comorbidities. For Model 4, the dependent variable was 24-hour SBP. For Model 5, the dependent variable was nocturnal dip. We inspected the model residual plots for normality and homoscedasticity. SPSS version 27[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] was used for the descriptive and bivariate and STATA 15[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] was used for multivariable analyses.\u003c/p\u003e \u003cp\u003eTwo sensitivity analyses were performed using bootstrap replication. The first sensitivity analysis was a bootstrap with 1000 replications performed on the association of daily racial discrimination and office measured hypertension. The second analyses were separating the data into each site (Hawaii and Philadelphia) and running a bootstrap univariate logistic regression with 1000 replications for each site.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n\u003ch2\u003eSocio-demographic and Clinical Characteristics\u003c/h2\u003e\n\u003cp\u003eSeventy-five participants were enrolled, 60 (80%) completed their questionnaire and ABPM in accordance with the IDACO criteria and were included in the analysis. Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e presents key socio-demographic characteristics of the sample. Thirty-six participants were recruited and enrolled in Philadelphia, and 24 in Hawaiʽi with 23 from the island of Oʽahu and 1 from the island of Hawaiʽi. Enrollment was ended early as a result of the COVID-19 pandemic.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eSociodemographics and Self Reported Clinical Data by Race and Ethnicity\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eBlack\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"Underline\"\u003eN\u003c/span\u003e\u0026thinsp;=\u0026thinsp;36 (59%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eAsian\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"Underline\"\u003eN\u003c/span\u003e\u0026thinsp;=\u0026thinsp;11 (19%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eNHPI\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"Underline\"\u003eN\u003c/span\u003e\u0026thinsp;=\u0026thinsp;13 (22%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eTotal\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"Underline\"\u003eN\u003c/span\u003e\u0026thinsp;=\u0026thinsp;60\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eP\u003c/em\u003e Value\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAge Mean (SD)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e48 (12)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e48 (13)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e52 (13)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e49 (12)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.67\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLevel of Education\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.73\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eGrade 12 or Less\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10 (28%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2 (18%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3 (23%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15 (25%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eSome College\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18 (50%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4 (36%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5 (39%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27 (45%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eBachelor\u0026rsquo;s Degree or\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eHigher\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8 (22%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5 (45%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5 (39%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18 (30%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEmployment\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e.06\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eFull-time\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14 (39%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4 (36%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3 (23%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21 (35%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ePart-time\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5 (14%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1 (9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0 (0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6 (10%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eSelf-employed\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2 (6%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2 (18%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0 (0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4 (7%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eRetired\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0 (0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2 (18%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1 (8%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3 (3%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eOn Disability\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11 (31%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1 (9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4 (31%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e16 (27%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eNot employed\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4 (11%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1 (9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5 (39%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10 (17%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIncome\u0026thinsp;\u0026lt;\u0026thinsp;40K\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e32 (89%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6 (55%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7 (54%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e45 (75%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e.01\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMarried or Cohabiting\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4 (11%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5 (45%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1 (8%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10 (17%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e.02\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSubstance Use\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20 (57%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5 (45%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6 (46%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e31 (53%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.69\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFamily History of HTN\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19 (54%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7 (64%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5 (45%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e31 (54%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.69\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSelf \u0026ndash; HTN\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17 (47%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2 (18%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3 (25%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22 (37%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.13\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTaking HTN medicines\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13 (36%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2 (18%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3 (25%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18 (31%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.47\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHeart Disease\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3 (9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1 (9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1 (9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5 (9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.99\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHigh Cholesterol\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12 (33%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4 (36%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3 (23%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19 (32%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.74\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eChronic Pain\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9 (25%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1 (9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5 (39%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15 (25%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.25\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDiabetes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6 (17%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2 (18%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3 (23%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11 (18%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.88\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDepression\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23 (64%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6 (55%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5 (39%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e34 (57%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.28\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAnxiety\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19 (53%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3 (27%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2 (15%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e24 (40%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e.04\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSleep Disorder\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11 (31%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3 (27%\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3 (25%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17 (29%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.90\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHepatitis C\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4 (12%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0 (0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1 (8%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4 (9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.46\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHeight in. Mean (SD)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e71 (3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e67 (2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e68 (3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e69 (3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eWeight lbs. Mean (SD)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e182 (33)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e151 (19)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e179 (56)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e175 (39)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e.08\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBMI Mean (SD)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26 (4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e24 (2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27 (7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26 (5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.13\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eViral Load Median (IQR)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12.5 (0\u0026ndash;14,372)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e.09\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCD4 Mean (SD)\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e631 (288)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e863 (422)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e472 (379)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e628 (317)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.25\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"6\"\u003eTable 1. shows sociodemographics and self reported clinical data by race and ethnicity. Native Hawaiian or Pacific Islander (NHPI), standard deviation (SD), $40,000 (40K), history (Hx), hypertension (HTN), Body Mass Index (BMI).\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"6\"\u003ea. BMI was Missing in 5 participants\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"6\"\u003eb. Viral load was missing in 22 participants\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"6\"\u003ec. CD4 was missing in 28 participants\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe mean age of the participants was 49\u0026thinsp;\u0026plusmn;\u0026thinsp;12 years old (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Fifty-nine percent of the participants identified as Black or African American, 14% as Asian (Filipino, Chinese, Japanese, Korean, Okinawan), and 22% NHPI. Six participants identified as multiethnic and were recoded based on their ethnic minority status. All the participants from Philadelphia identified as Black or African American.\u003c/p\u003e\n\u003cp\u003eMost participants (77%) reported at least one medical co-morbidity (Mean 5\u0026thinsp;\u0026plusmn;\u0026thinsp;3, data not tabled). Thirty seven percent reported having HTN and 32% reported high cholesterol. As for psychiatric co-morbidities 56% of participants reported having Depression, 39% having anxiety, and 28% having a sleep disorder.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n\u003ch2\u003eBP Measurements and HTN Awareness by Race\u003c/h2\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e presents BP measurements stratified by race. Asian participants had significantly lower in office diastolic BPs (DBP), 24 ABPM, and nocturnal DBP resulting in the lower rates of 24 ABPM hypertension when compared to African American and NHPI. African American participants had the highest in office DBP whereas NHPIs had the highest 24 ABPM DBP. NHPIs also had the highest rates of hypertension (85%) as measured by 24 ABPM. Overall, 59% of participants had HTN measured by 24-hour APBM and 54% were non-dippers.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eAssociation between Self Reported Race and Ethnicity and Blood Pressure Measurements\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eVariables\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eBlack\u003c/p\u003e\n\u003cp\u003eN\u0026thinsp;=\u0026thinsp;36 (60%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eAsian\u003c/p\u003e\n\u003cp\u003eN\u0026thinsp;=\u0026thinsp;11 (18%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eNHPI\u003c/p\u003e\n\u003cp\u003eN\u0026thinsp;=\u0026thinsp;13 (19%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eTotal\u003c/p\u003e\n\u003cp\u003eN\u0026thinsp;=\u0026thinsp;60\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep Value\u003c/em\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHTN Measured\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIn-office HTN\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26 (72%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4 (40%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10 (77%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e40 (68%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.11\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOffice SBP mmHg\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e132 (13)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e120 (14)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e130 (17)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e130 (14)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.07\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOffice DBP mmHg\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e87 (11)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e78 (10)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e86 (9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e85 (11)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e.05\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAware of Office HTN (n\u0026thinsp;=\u0026thinsp;45)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17 (61%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2 (33%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3 (27%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22 (49%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.12\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e24H ABPM HTN\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21 (58%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4 (36%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11 (85%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e36 (60%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e.05\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e24H ABPM SBP\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e120 (9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e117 (12)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e127 (15)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e121 (12)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.10\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e24H ABPM DBP\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e75 (6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e74 (9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e82 (11)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e77 (9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e.03\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTotal Wake Hours\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15 (3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13 (3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e16 (4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15 (3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.25\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eWake SBP\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e125 (10)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e122 (12)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e129 (18)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e126 (12)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.38\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eWake DBP\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e80 (7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e78 (9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e84 (13)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e81 (9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.25\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSleep SBP\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e113 (12)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e108 (13)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e119 (16)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e113 (13)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.10\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSleep DBP\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e68 (8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e68 (9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e77 (12)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e70 (10)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e.02\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAware of 24 ABPM HTN\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17 (68%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2 (33%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3 (30%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22 (54%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.07\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eWhite Coat HTN\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8 (22%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1 (10%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2 (17%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11 (19%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.67\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMasked HTN\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3 (8%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1 (10%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3 (25%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7 (12%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.30\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNon-dipper\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19 (53%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5 (45%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8 (62%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e32 (53%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.73\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e% Nocturnal Dip SBP\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10 (7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11 (7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7 (10)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10 (8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.33\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e% Nocturnal Dip DBP\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14 (9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12 (8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8 (10)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10 (8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.10\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 2 shows the association between in self-reported race and in office blood pressure measurements, 24 hour ambulatory blood pressure measurements, nocturnal dip in blood pressure. All values are Mean and Standard deviation unless otherwise specified. Native Hawaiian or Pacific Islander (NHPI), systolic blood pressure (SBP), diastolic blood pressure (DBP), 24 hour ambulatory blood pressure monitoring (24H ABPM).\u003c/p\u003e\n\u003c/div\u003e\n\u003cp\u003eForty five percent of participants with elevated in-office systolic BP (SBP) and 39% with elevated 24h-ABPM SBP were not aware of their hypertension and thus not taking anti-hypertensive medication (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Rates of hypertension awareness were the lowest among NHPI. Seventy percent of the NHPI participants with elevated in office SBP were not receiving anti-hypertensive medication (data not in table). It should be noted that 8 participants, 12%, had masked HTN (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003ch2\u003eDiscrimination and Psychosocial Measurements\u003c/h2\u003e\n\u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, a greater percentage of Black participants reported daily racial discrimination compared to Asians and NHPIs and as a result more participants in Philadelphia experienced discrimination than in Hawaii. The most common racial discrimination was being discriminated against on the street or in a public place (79%), followed around in a store (74%), and discriminated against at school (56%). Fifty-one percent of participants reported daily sexual discrimination. The most common sexual orientation discrimination was being discriminated against on the street or in a public place (73%), discriminated against at school (57%), and getting poor service at a store or restaurant (50%, data not in tables). Race was not associated with sexual discrimination. Participants who experienced racial and sexual discrimination also had more co-morbidities (5.0\u0026thinsp;\u0026plusmn;\u0026thinsp;3.7 vs. 2.5\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002 and 5.0\u0026thinsp;\u0026plusmn;\u0026thinsp;3.7 vs. 2.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006; respectively). Participants who experienced racial discrimination scored higher on the Overall Anxiety Severity and Impairment Scale (OASIS) than those who did not (5.5\u0026thinsp;\u0026plusmn;\u0026thinsp;4.8 vs. 3.0\u0026thinsp;\u0026plusmn;\u0026thinsp;3.6, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02). This difference in the OASIS was not observed in participants who experienced sexual orientation discrimination. Racial and sexual orientation discrimination was not associated with a difference in the Center of Epidemiologic Studies (CES) depression scale, perceived stress, Generalized Anxiety Disorder (GAD) scale.\u003c/p\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eRacial and Sexual Orientation Discrimination by Demographics, Psychosocial Stress, and Hypertension.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eExperienced Daily Racial Discrimination\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eExperienced Sexual Orientation Discrimination\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003cp\u003eN\u0026thinsp;=\u0026thinsp;35 (59%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003cp\u003eN\u0026thinsp;=\u0026thinsp;24 (41%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003cp\u003eN\u0026thinsp;=\u0026thinsp;31 (52%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003cp\u003eN\u0026thinsp;=\u0026thinsp;29 (48%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eSite\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.07\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ePhiladelphia\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e29 (83)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7 (29)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22 (71)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14 (48)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eHawaii\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6 (17)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17 (71)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9 (29)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15 (52)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eRace/Ethnicity\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.15\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBlack\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e29 (83)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7 (29)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22 (71)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14 (48)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eAsian\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4 (11)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7 (29)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5 (16)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6 (21)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eNHPI\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2 (6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10 (42)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4 (13)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9 (31)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eNumber Comorbidities mean (SD)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.0 (3.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.5 (3.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.002\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.0 (3.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.7 (2.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.006\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ePsychological Measurements\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eCES-Depression Scale\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003emean (SD)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9.7 (6.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.6 (6.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9.0 (6.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.7 (6.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.90\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ePerceived Stress Scale mean (SD)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15.4 (8.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13.6 (7.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.38\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15.3 (7.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14.0 (8.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.53\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eOASIS mean (SD)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.5 (4.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.0 (3.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.02\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.4 (4.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.5 (5.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.99\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eGeneralized Anxiety Disorder Scale mean (SD)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.3 (4.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.8 (4.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.0 (4.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.3 (4.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.56\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eHypertension Measurements\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003eb\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eOffice SBP mean (SD)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e133 (12)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e124 (16)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.02\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e130 (11)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e129 (16)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.79\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eOffice DBP mean (SD)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e88 (10)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e81 (11)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.005\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e87 (11)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e84 (12)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.36\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e24-hour ABPM SBP\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003emean (SD)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e120 (10)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e121 (12)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.80\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e122 (11)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e120 (12)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.69\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e24-hour ABPM DBP\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003emean (SD)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e76 (8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e76 (8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.96\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e77 (7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e76 (10)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.81\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eNocturnal Dip SBP (%)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003emean (SD)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11 (7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9 (9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9 (8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11 (8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.23\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eNocturnal Dip DBP (%)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003emean (SD)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14 (9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10 (9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13 (10)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12 (9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.90\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eOffice HTN\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e28 (80)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11 (48)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.01\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22 (71)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17 (63)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.52\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e24 ABPM HTN\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21 (60)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14 (58)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.90\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21 (68)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15 (52)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.21\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eNon-Dipper\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18 (51)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13 (54)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.59\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19 (61)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13 (45)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.20\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eHTN Awareness (n\u0026thinsp;=\u0026thinsp;45,46)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ec\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18 (62)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5 (31)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14 (56)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9 (43)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.37\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 3. Shows the demographic, psychologic, and blood pressure difference in participants who experienced daily racial and daily sexual orientation discrimination. All categorical variables are represented as count and (percentage). Continuous variables are represented as mean and (standard deviation). Standard deviation (SD), Native Hawaiian or Pacific Islander (NHPI), systolic blood pressure (SBP), diastolic blood pressure (DBP),\u0026nbsp; ambulatory blood pressure monitoring (ABPM), Overall Anxiety Severity and Impairment Scale (OASIS), Center of Epidemiologic Studies (CES).\u003c/p\u003e\n\u003col style=\"list-style-type: lower-alpha;\"\u003e\n\u003cli\u003e\n\u003cp\u003eOne participant did not answer the question about daily racial discrimination.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eOne participant did not have his blood pressure measured in the office.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eThis among participants who had a SBP \u0026gt; 130 in the office or a self-reported history of HTN.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ol\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n\u003ch2\u003eDiscrimination and HTN\u003c/h2\u003e\n\u003cp\u003eParticipants who experienced daily racial discrimination had higher office systolic and diastolic BP compared to those who did not experience daily racial discrimination (SBP 133\u0026thinsp;\u0026plusmn;\u0026thinsp;12 vs. 124\u0026thinsp;\u0026plusmn;\u0026thinsp;16, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02 and DBP 88\u0026thinsp;\u0026plusmn;\u0026thinsp;10 vs. 81\u0026thinsp;\u0026plusmn;\u0026thinsp;11, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.005; respectively). Thus, more participants who had experienced racial discrimination met the criteria for HTN by in-office BP measurement. This association between racial discrimination and HTN was not seen on 24-hour ABPM SBP\u0026amp;DBP, and percent dip in nocturnal SBP. Daily sexual orientation was not associated with office-based and 24-hour ABPM SBP nor nocturnal SBP dip.\u003c/p\u003e\n\u003cp\u003eNext, we created logistic regression models to examine the contribution of other variables to office hypertension including the survey site and the number of co-morbidities. Model 1 is the unadjusted model indicating that participants who experience daily racial discrimination had 4.4 greater odds (odds ratio \u003cem\u003eOR\u003c/em\u003e 4.4 (95% confidence interval \u003cem\u003eCI\u003c/em\u003e [1.4\u0026ndash;14.0], \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01, Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e, Model 1) of having hypertension than those who did not. Model 2 adjusts for the survey site and shows that office measured HTN remained significantly associated with racial discrimination (\u003cem\u003eOR\u003c/em\u003e 5.1 95%CI [1.2\u0026ndash;20.1], \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02; Model 2, Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e) despite there being significantly more discrimination at the Philadelphia site than the Hawaii site. Next, we added the number of comorbidities, as this was significantly associated with discrimination and could explain hypertension. The number of comorbidities; however, was not associated with hypertension, and discrimination remained significantly associated with hypertension, but the model was no longer significant (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e, Model 3). We also adjusted the model for age and BMI and racial discrimination remained significantly associated with hypertension (see Supplemental Table\u0026nbsp;3). Neither hypertension as measured by 24 hour ABPM (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e, Model 4) or nocturnal dip (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e, Model 5) were associated with discrimination after multivariable adjustment.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab4\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eLinear associations of Discrimination, Race, Social Support with Office Systolic Blood Pressure, 24 Hour ABPM Systolic Blood Pressure, and Percent Dip in Systolic Blood Pressure\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eVariables\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eModel 1 Office HTN Discrimination Univariate\u003c/p\u003e\n\u003cp\u003eN\u0026thinsp;=\u0026thinsp;58 \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.03, R\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.15\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eModel 2 Office HTN\u003c/p\u003e\n\u003cp\u003eDiscrimination and Site\u003c/p\u003e\n\u003cp\u003eN\u0026thinsp;=\u0026thinsp;58, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.04, R\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.15\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eModel 3 Office HTN\u003c/p\u003e\n\u003cp\u003eDiscrimination, Site, and Comorbidities\u003c/p\u003e\n\u003cp\u003eN\u0026thinsp;=\u0026thinsp;58, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.07, R\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.16\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eModel 4 24H-ABPM HTN\u003c/p\u003e\n\u003cp\u003eDiscrimination, Site, and Comorbidities\u003c/p\u003e\n\u003cp\u003eN\u0026thinsp;=\u0026thinsp;59, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.90, R\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.00\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eModel 5 Nocturnal Dip\u003c/p\u003e\n\u003cp\u003eDiscrimination, Site, and Comorbidities\u003c/p\u003e\n\u003cp\u003eN\u0026thinsp;=\u0026thinsp;59, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.99, R\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.00\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eDaily Racial Discrimination\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e4.4 [1.4, 14.0], 0.01\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.1 [1.2\u0026ndash;20.1], 0.02\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.9 [1.3\u0026ndash;26.7], 0.02\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.1 [0.3\u0026ndash;4.1], 0.90\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.8 [0.2 -3.0], 0.81\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eHawaii (Site)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.3 [0.3\u0026ndash;5.5], 0.70\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.3 [0.3\u0026ndash;5.5], 0.71\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.8 [0.2\u0026ndash;2.9], 0.81\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.1 [0.3\u0026ndash;3.9], 0.86\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNumber of Comorbidities\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.94 [0.8\u0026ndash;1.1], 0.94\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.0 [0.9\u0026ndash;1.2], 0.64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.0 [0.9\u0026ndash;1.2], 0.87\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 4. shows the linear associations between discrimination, race, social support with in office systolic blood pressure (Model 1), 24 hour ambulatory blood pressure monitoring (Model 2) and percentage dip in nocturnal dip in systolic blood pressure (Model 3). A negative coefficient in Model 3 represents an increase in nocturnal systolic blood pressure. Systolic blood pressure (SBP). Native Hawaiian or Pacific Islander (NHPI). Ambulatory blood pressure monitor (ABPM).\u003c/p\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n\u003ch2\u003eSensitivity Analyses\u003c/h2\u003e\n\u003cp\u003eRacial discrimination remained associated with office measured hypertension after one thousand bootstrap replications (4.4 [1.3, 15.2], 0.02, Supplemental Table\u0026nbsp;2, Analysis 1). In analysis two, there was a similar positive association of racial discrimination and HTN when examined at Site 1, Hawaiʽi (5.0 [1.0\u0026ndash;25.2], 0.05) and Site 2, Philadelphia (5.1 [0.8\u0026ndash;32.2], 0.08); however, the associations were no longer significant after one thousand boot strap replications.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eWe set out to examine the baseline burden of racial discrimination, sexual orientation discrimination, and HTN among MSM of color living with HIV. We found that most participants experienced racial discrimination (59%) and sexual orientation discrimination (51%). African American participants experienced the most racial discrimination. Participants also had a high burden of HTN (including an absence of a nocturnal dip). Racial discrimination was associated with higher BP in the office but not on 24-hour APBM or nocturnal dip. There were no associations between sexual orientation discrimination and HTN.\u003c/p\u003e \u003cp\u003eWe were surprised that only the office and not 24-hour BP measurements were elevated in the context of exposure to racial discrimination. Previous studies have found a differential effect of racial discrimination on HTN, with lifetime discrimination increasing the incidence of HTN whereas daily reported discrimination did not,[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] suggesting that the long-term systemic effects of racism may be more impactful than the daily stressors. One explanation for the differences in office and 24-H ABPM measurement could be office measurement error; however, if so, the effects would differ by site. Another explanation for differences in office and 24 ABPM is white coat HTN. Thirty percent of those who had HTN in the office and experienced daily discrimination had white coat HTN. White coat hypertension has been associated with anxiety [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] and the racial discrimination participants experienced while coming to their clinical triggered their anxiety resulting in higher office BP measurements but the rest of the time, they avoided these daily triggers of racial discrimination and had normal BP measurements. Of note, white coat HTN although initially thought to be benign, has been associated with increased cardiovascular-related deaths [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Thus, we will continue to follow this cohort for the long-term effects of racial discrimination on hypertension and cardiovascular outcomes.\u003c/p\u003e \u003cp\u003eRacial minorities are at an increased risk for both HIV and HTN resulting in a potential syndemic[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] and we examine the results of this cohort to previous studies. In our study, the prevalence of HTN among the study\u0026rsquo;s Asian cohort, 36%, was like the prevalence from a meta-analysis of 49 studies from the Americas, Europe, Africa, and Asia which estimated that 35% of HIV-positive patients receiving antiretroviral therapy have HTN.[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] We can also compare the prevalence of HTN in this study to studies of HIV uninfected individuals. For example, 57% of African American participants LWH had hypertension, which is similar to the Cardia study[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] which found that 50% of HIV uninfected African American participants have HTN by age 46 and 75% by age 55. In our study, NHPI participants living with HIV had the highest prevalence of HTN (85%). This is much higher than previous estimates of NHPI uninfected by HIV which were between 23% and 52%. [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] Further research is needed to confirm this high prevalence.\u003c/p\u003e \u003cp\u003eIn our study, the prevalence of non-dippers or reverse dippers was 68%. Similarly, a South African study of nocturnal dipping and HIV found the prevalence of non-dipping of 65%.[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] It should be noted that 91% of this sample in that study was female. A meta-analysis by Kent et al.[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] of 8 studies also found less nocturnal dipping in HIV-positive individuals than HIV-negative individuals. Previous studies have also linked systemic racism and the resulting post-traumatic stress disorder to non-dipping;[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] however, in our study, discrimination was not associated with loss of nocturnal dip.\u003c/p\u003e \u003cp\u003eThese results must be interpreted in the context of their limitations. First, the study was limited by the sample size because recruitment was terminated early because of the COVID-19 pandemic. This minimized the number of variables we could simultaneously analyze in our conceptual model. While these are two very different geographical sites, levels of racial discrimination and discrimination may vary in other locations. Our sample size was also limited by excluding 21% of participants because of incorrect usage of ABPM. Further, efforts should be made to increase hypertension awareness because only 45% of participants with a SBP greater than 130 mmHg,[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] and 33% with a SBP\u0026thinsp;\u0026gt;\u0026thinsp;140 mmHg were aware of their diagnosis of hypertension.[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] Interventions should examine both patient level and provider level barriers to hypertension awareness. Lastly, this study is a cross-sectional baseline analysis and further research is underway to examine how discrimination and inflammation affect long term cardiovascular outcomes.\u003c/p\u003e \u003cp\u003eIn conclusion, this study provides insights and baseline information about the complex interplay of psychosocial factors and cardiovascular disease among MSM of color living with HIV. Further, many participants with elevated BP were either unaware or undiagnosed with HTN. This finding identifies opportunities for health interventions to improve HTN awareness and treatment in these high cardiovascular risk populations.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eHTN \u0026ndash; hypertension\u003c/p\u003e\n\u003cp\u003ePLWH - people living with HIV\u003c/p\u003e\n\u003cp\u003eMSM - men who have sex with men\u003c/p\u003e\n\u003cp\u003eU.S. \u0026ndash; United States\u003c/p\u003e\n\u003cp\u003eBP \u0026ndash; blood pressure\u003c/p\u003e\n\u003cp\u003eNHPI - Native Hawaiian or Pacific Islander\u003c/p\u003e\n\u003cp\u003eABPM - ambulatory BP monitor\u003c/p\u003e\n\u003cp\u003eCASI - computer-assisted self-interviewing\u003c/p\u003e\n\u003cp\u003eIDACO - International Database of Ambulatory BP in relation to Cardiovascular Outcome\u003c/p\u003e\n\u003cp\u003eSD - standard deviation\u003c/p\u003e\n\u003cp\u003eIQR - interquartile range\u003c/p\u003e\n\u003cp\u003eDBP \u0026ndash; diastolic blood pressure\u003c/p\u003e\n\u003cp\u003eSBP \u0026ndash; systolic blood pressure\u003c/p\u003e\n\u003cp\u003eOASIS - Overall Anxiety Severity and Impairment Scale\u003c/p\u003e\n\u003cp\u003eCES - Center of Epidemiologic Studies\u003c/p\u003e\n\u003cp\u003eGAD - Generalized Anxiety Disorder\u003c/p\u003e\n\u003cp\u003eOR \u0026ndash; odds ratio\u003c/p\u003e\n\u003cp\u003eCI \u0026ndash; confidence interval\u003c/p\u003e\n\u003cp\u003eBMI \u0026ndash; body mass index\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAvailability of data and material:\u0026nbsp;\u003c/strong\u003eDeidentified data and materials are available by request from Dr. Barile and approval of Principal investigator\u0026rsquo;s Drs. Ma and Wong as is permitted within the scope of the IRB protocol given the senstitive and protected nature of the data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability:\u0026nbsp;\u003c/strong\u003eCode is available upon request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e This research was funded by National Institue of Minority Health of the National Institutes of Health under the award grant (G.M. and F.W). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e: Frank Wong, Grace Ma, Jack Barile, and Crystal Gadegbeku contributed to the study conception and design. Material preparation and data collection were performed by Lorie Okada, Shari Brown, Kerry Traub, Gina M. Simoncini, Yin Tan, and Julia Trout. Data analysis was performed by Avrum Gillespie, Rui Song, and Jack Barile. The first draft of the manuscript was written by Avrum Gillespie and Rui Song and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e: This study was approved by the University of Hawai`i institutional review board. Written informed consent was obtained from all participants. The clinical and research activities being reported here are consistent with the adherence to the Declaration of Helsinki\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest/competing interests:\u003c/strong\u003e The authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding source:\u003c/strong\u003e This research was funded by National Institue of Minority Health of the National Institutes of Health under the award grant (G.M. and F.W). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eSchouten J, Wit FW, Stolte IG, et al. 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PMID: 24077828.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-human-hypertension","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"jhh","sideBox":"Learn more about [Journal of Human Hypertension](http://www.nature.com/jhh/)","snPcode":"41371","submissionUrl":"https://mts-jhh.nature.com/cgi-bin/main.plex","title":"Journal of Human Hypertension","twitterHandle":"@jhhypertension","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Hypertension, Discrimination, Asian, Native Hawaiian, Pacific Islander, Black/ African American, HIV/AIDS, Men who have sex with men, 24 ambulatory blood pressure monitor, nocturnal dip","lastPublishedDoi":"10.21203/rs.3.rs-3838090/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3838090/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eRacial and sexual orientation discrimination may exacerbate the double epidemic of hypertension and HIV that affects men of color who have sex with men (MSM). This was a cross-sectional analysis of African American, Asian American, Native Hawaiian or Pacific Islander (NHPI) MSM living with HIV (PLWH) cohort in Honolulu and Philadelphia. Racial and sexual orientation discrimination, stress, anxiety, and depression was measured with computer assisted self-interview questionnaires (CASI). We examined the associations between racial and sexual orientation discrimination with hypertension measured both in the office and by 24-hour ambulatory blood pressure monitoring (ABPM) using multivariable logistic regression. Sixty participants (60% African American, 18% Asian, and 22% NHPI) completed CASIs and 24-hour ABPM. African American participants (80%) reported more daily racial discrimination than Asian American (36%) and NHPI participants (17%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Many participants (51%) reported daily sexual orientation discrimination. Sixty-six percent of participants had hypertension by office measurement and 59% had hypertension by 24-hour ABPM measurement. Participants who experienced racial discrimination had greater odds of having office-measured hypertension than those who did not, even after adjustment (\u003cem\u003eOdds Ratio\u003c/em\u003e 5.1 (95% Confidence Interval [1.2\u0026ndash;20.1], \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01). This association was not seen with 24-hour ABPM. Hypertension was not associated with sexual orientation discrimination. In this cohort, MSM of color PLWH experience significant amounts of discrimination and hypertension. Those who experienced racial discrimination had higher in-office blood pressure. This difference was not observed in 24-hour APBM and future research is necessary to examine the long term cardiovascular effects.\u003c/p\u003e","manuscriptTitle":"Discrimination and Hypertension among a Diverse Sample of \nRacial and Sexual Minority Men Living with HIV: \nBaseline Findings of a Longitudinal Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-17 16:06:19","doi":"10.21203/rs.3.rs-3838090/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2024-02-20T16:54:05+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2024-02-19T16:53:19+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2024-01-31T16:03:54+00:00","index":2,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2024-01-29T04:59:56+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2024-01-17T18:27:27+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2024-01-15T17:53:27+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-01-15T02:31:22+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-01-08T14:12:30+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Human Hypertension","date":"2024-01-05T19:39:16+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-human-hypertension","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"jhh","sideBox":"Learn more about [Journal of Human Hypertension](http://www.nature.com/jhh/)","snPcode":"41371","submissionUrl":"https://mts-jhh.nature.com/cgi-bin/main.plex","title":"Journal of Human Hypertension","twitterHandle":"@jhhypertension","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"d7427e45-b1e3-4c7f-a151-18b55f6564aa","owner":[],"postedDate":"January 17th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":28153879,"name":"Health sciences/Diseases/Cardiovascular diseases/Hypertension"},{"id":28153880,"name":"Health sciences/Risk factors"},{"id":28153881,"name":"Health sciences/Health care/Diagnosis"},{"id":28153882,"name":"Health sciences/Medical research"}],"tags":[],"updatedAt":"2024-06-27T07:09:28+00:00","versionOfRecord":{"articleIdentity":"rs-3838090","link":"https://doi.org/10.1038/s41371-024-00919-0","journal":{"identity":"journal-of-human-hypertension","isVorOnly":false,"title":"Journal of Human Hypertension"},"publishedOn":"2024-06-26 04:00:00","publishedOnDateReadable":"June 26th, 2024"},"versionCreatedAt":"2024-01-17 16:06:19","video":"","vorDoi":"10.1038/s41371-024-00919-0","vorDoiUrl":"https://doi.org/10.1038/s41371-024-00919-0","workflowStages":[]},"version":"v1","identity":"rs-3838090","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3838090","identity":"rs-3838090","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}