Patient-clinician communication and cardiovascular outcomes: An analysis of the hispanic community health study/study of latinos (HCHS/SOL), 2008-2019 - PMC Skip to main content An official website of the United States government Here's how you know Here's how you know Official websites use .gov A .gov website belongs to an official government organization in the United States. Secure .gov websites use HTTPS A lock ( Lock Locked padlock icon ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites. Search Log in Dashboard Publications Account settings Log out Search… Search NCBI Primary site navigation Search Logged in as: Dashboard Publications Account settings Log in Search PMC Full-Text Archive Search in PMC Journal List User Guide PERMALINK Copy As a library, NLM provides access to scientific literature. 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Learn more: PMC Disclaimer | PMC Copyright Notice Am J Prev Cardiol . 2026 Feb 21;26:101493. doi: 10.1016/j.ajpc.2026.101493 Search in PMC Search in PubMed View in NLM Catalog Add to search Patient-clinician communication and cardiovascular outcomes: An analysis of the hispanic community health study/study of latinos (HCHS/SOL), 2008-2019 Samuel D Slavin Samuel D Slavin a Boston University Chobanian & Avedisian School of Medicine, USA Find articles by Samuel D Slavin a, ⁎ , Martha L Daviglus Martha L Daviglus b University of Illinois Chicago, USA Find articles by Martha L Daviglus b , Olga Garcia-Bedoya Olga Garcia-Bedoya b University of Illinois Chicago, USA Find articles by Olga Garcia-Bedoya b , Yasmin Mossavar-Rahmani Yasmin Mossavar-Rahmani c Albert Einstein College of Medicine, USA Find articles by Yasmin Mossavar-Rahmani c , Frank Penedo Frank Penedo d University of Miami, USA Find articles by Frank Penedo d , Krista Perreira Krista Perreira e University of North Carolina, USA Find articles by Krista Perreira e , Sylvia Wassertheil-Smoller Sylvia Wassertheil-Smoller c Albert Einstein College of Medicine, USA Find articles by Sylvia Wassertheil-Smoller c , Alberto Ramos Alberto Ramos d University of Miami, USA Find articles by Alberto Ramos d , Raymond Rigat Raymond Rigat a Boston University Chobanian & Avedisian School of Medicine, USA Find articles by Raymond Rigat a , Gregory Talavera Gregory Talavera f San Diego State University, USA Find articles by Gregory Talavera f , Andrew Telzak Andrew Telzak c Albert Einstein College of Medicine, USA Find articles by Andrew Telzak c , Murray A Mittleman Murray A Mittleman g Harvard T.H. Chan School of Public Health, USA Find articles by Murray A Mittleman g Author information Article notes Copyright and License information a Boston University Chobanian & Avedisian School of Medicine, USA b University of Illinois Chicago, USA c Albert Einstein College of Medicine, USA d University of Miami, USA e University of North Carolina, USA f San Diego State University, USA g Harvard T.H. Chan School of Public Health, USA ⁎ Corresponding author. [email protected] Received 2025 Aug 25; Revised 2026 Feb 13; Accepted 2026 Feb 19; Collection date 2026 Apr. © 2026 The Author(s) This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). PMC Copyright notice PMCID: PMC13084127 PMID: 42006439 Abstract Background Strong patient-clinician communication may improve health outcomes for Hispanic/Latino individuals. Objective We assessed the association between patient-clinician communication and cardiovascular (CV) events or death in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Methods HCHS/SOL is a longitudinal cohort study of individuals aged 18–74 who identified as Hispanic/Latino at 4 U.S. metropolitan areas. Participants' ratings of communication with clinicians during the year before enrollment were used to generate a 3-level communication score. The primary outcome was the composite of myocardial infarction (MI), heart failure events (HF), stroke, and all-cause mortality. The secondary outcomes included the components of the primary outcome. The association between the baseline communication score and outcomes of interest was assessed with Cox proportional hazards models adjusting for possible confounders. We also used multivariable linear regression to assess the cross-sectional association between communication and AHA Life’s Essential 8 (LE8), a measure of CV risk factors. All analyses accounted for the complex survey design. Results Our sample included 10,527 individuals without prior CV events and at least one medical encounter in the year before enrollment. The median age at enrollment was 41 years (IQR 29, 53), 59% were female, and 71% perceived high-quality communication with clinicians. The mean follow-up time was 9.4 years. High-quality communication was associated with the following results in our fully adjusted analyses: composite outcome (aHR 0.73; 95% CI 0.51, 1.03; p = 0.073), CV events (aHR 0.82, 95% CI 0.44, 1.51, p = 0.520), all-cause mortality (aHR 0.54; 95% CI 0.37, 0.80; p = 0.002). Conclusions High-quality patient-clinician communication was associated with a non-significant trend toward a lower rate of CV events and death, driven by a significant association with lower all-cause mortality. Keywords: Patient-clinician communication, Cardiovascular prevention, Hispanic/latino health, Cardiovascular epidemiology Graphical abstract Open in a new tab 1. Introduction Strong patient-clinician communication has the potential to improve chronic disease outcomes [ [1] , [2] , [3] , [4] , [5] , [6] ]. In cardiovascular (CV) medicine, however, the United States invests substantially in technologies while investing relatively little to study or to enhance patient-clinician communication [ [7] , [8] , [9] ]. The potential impact of communication quality may be particularly important for populations with barriers to care due to language, culture, or distrust [ 10 , 11 ]. Hispanic/Latino people living in the United States have relatively favorable CV outcomes, yet within this population disparities persist [ 12 , [13] , [43] ]. Disparities in CV outcomes result from prescribing patterns, cost, insurance coverage, implicit bias, and limitations to access [ 2 , 14 , [15] , [16] , [17] , [44] ]. Patient-side factors contribute as well, including immigration status, acculturation, income, health literacy, psychosocial stress, and trust/distrust of medical science [ 1 , 3 , [18] , [19] , [20] ]. Strong patient-clinician communication has the potential to mitigate many of these drivers of poor outcomes, yet prospective studies assessing the relationship with communication quality with hard CV outcomes are lacking. We therefore analyzed a large prospective cohort of self-identified Hispanic/Latino patients within the Hispanic Community Health Study/Study of Latinos (SOL). We aimed to evaluate the association of patient-clinician communication at baseline with cardiovascular risk factors, major cardiovascular events, and all-cause mortality. 2. Methods 2.1. Hispanic community health study/study of Latinos The Hispanic Community Health Study/Study of Latinos (HCHS/SOL) is an ongoing, population-based cohort study that includes 16,415 individuals aged 18 to 74 who self-identified as Hispanic/Latino. HCHS/SOL employed a stratified, multistage probability sampling design across four U.S. study sites (Bronx, NY; Chicago, IL; Miami, FL, and San Diego, CA). The first study visit took place between 2008 and 2011. Incident major adverse cardiovascular events and mortality have been recorded through 2019. Additional details of the HCHS/SOL study design have been published previously [ 21 , 22 ]. The study was approved by the institutional review board (IRB) at the coordinating center and each study site. Our sample included all HCHS/SOL participants without prior CV events who reported at least one visit with a healthcare professional within the year preceding their baseline enrollment and who provided responses to the patient-clinician communication questions. Recent medical encounters were assessed with the question, “During the past 12 months, how many times did you see a physician or health care provider for your health care?” Participants who responded “zero” were excluded because their patient-clinician communication was not assessed. (Supplemental Table 1 compares baseline demographic characteristics between participants in our sample and those without a recent medical encounter.) 2.2. Patient-Clinician communication Participants’ perception of communication with their clinicians was assessed at the baseline visit using survey questions derived from the Consumer Assessment of Healthcare Providers and Systems (CAHPS) survey developed by the Agency for Healthcare Research and Quality (AHRQ) [ 23 ]. The questions were phrased, “During the last 12 months, how often did doctors or other health care providers… (a) listen carefully to you? / (b) explain things in a way you could understand? / (c) show respect for what you had to say? / (d) spend enough time with you?”. Responses were recorded on a 4-point Likert scale of “never”, “sometimes”, “most of the time”, and “always”. Following CAHPS guidance, we collapsed responses of “never” and “sometimes”. Responses were coded as 1-never/sometimes, 2-most of the time, and 3-always. We calculated an overall communication score equal to the average of these items rounded to the nearest integer so that an overall score of 1, 2, or 3, corresponded to low-, mid-, or high-quality communication, in keeping with prior research [ 24 ]. Language-related challenges were assessed separately with the question, “During the last 12 months, how often did you have a hard time speaking with or understanding a doctor or other health providers because of language differences?” Responses were coded as 1-always/most of the time, 2-sometimes, and 3-never. 2.3. Endpoints Our prespecified primary composite endpoint was the time to first myocardial infarction (MI), heart failure (HF) encounter, stroke, or death from any cause. Information was extracted from medical records for hospitalizations and ED visits, analyzed by a computer-based algorithm, and reviewed by a panel of clinical specialists in accordance with HCHS/SOL classification criteria. Adjudicated cardiovascular endpoints included myocardial infarction (MI), a new diagnosis of heart failure (HF) or HF exacerbation, and stroke. Endpoint classification criteria have been published previously and protocols are also available on the HCHS/SOL website [ 21 , 25 ]. A secondary measure of interest was a composite of cardiovascular risk factors as measured by the American Heart Association Life’s Essential Eight (LE8) at the initial study visit. The LE8 is the average of scores from 0 (worst) to 100 (best) in each of the following domains: diet, physical activity, nicotine exposure, self-reported sleep duration, body mass index, blood lipids, blood glucose, and blood pressure [ 26 ]. 2.4. Covariates The following sociodemographic covariates were assessed at the baseline study visit: age, sex, educational attainment, income, marital status, employment, health insurance, nativity (with “U.S. born” defined as born in the 50 U.S. states or the District of Columbia), and years in the US for foreign/territory born participants, Hispanic/Latino background, preferred language (Spanish vs English), and study site. Baseline assessment also included smoking status, alcohol use, and the Charlson Comorbidity Index (CCI). While the CCI is likely to be lower in our sample due to excluding subjects with prior CV events, it still serves as an important measure for non-cardiovascular comorbidities. The Short Acculturation Scale for Hispanics (SASH) survey was also obtained at baseline but not included due to missingness. 2.5. Statistical analysis Baseline characteristics were reported for each group by high versus low relationship scores. Following HCHS/SOL guidelines [ 27 ], “all reported values were weighted to account for the disproportionate selection of the sample and to adjust for bias effects due to differential nonresponse at the household and person levels. The adjusted weights were also trimmed to limit precision losses due to the variability of the adjusted weights, and calibrated to the 2010 Census characteristics by age, sex, and Hispanic background in each field site’s target population. All analyses also account for cluster sampling and the use of stratification in sample selection.” Complete data on patient-clinician communication and the composite outcome were available for 10,515 of the 10,527 in our sample (<0.01 % missing). We performed a Cox proportional hazards model to estimate the association between high-quality patient-clinician communication at baseline and the composite outcome, with and without adjustment for the pre-specified covariates described above. Our first adjusted model included sociodemographic covariates (Model 1). Our fully adjusted model also included smoking, alcohol use, and the CCI (Model 2). Follow-up time was defined as the time to first event or end of follow-up. Given the low number of overall events, it is possible that survey weighting could distort our results toward a small number of events among heavily weighted individuals. Therefore, we performed a sensitivity analysis of primary outcome and components without survey weighting. We also calculated an E-value to assess the potential magnitude of unmeasured confounders. An E-value is defined as the minimal strength of association between an unmeasured confounder and the outcome that would account for the observed association [ 28 , 29 ]. Additionally, we performed unadjusted and adjusted multivariable linear regression to assess the cross-sectional association between patient-clinician communication and cardiovascular risk factors, as measured by LE8. The adjusted model included all the aforementioned covariates except smoking status, which is included in the LE8, and the CCI, due to overlap with LE8. Analyses were conducted using R statistical software version 4.3.2 [ 30 ]. We used the survey, survival , and gtsummary packages for analysis and visual presentation [ [31] , [32] , [33] , [34] ]. We considered a 2-sided p-value < 0.05 as statistically significant. 3. Results Our sample included 10,515 participants with at least one medical visit in the year before enrollment, complete communication survey data, and no prior CV events. Baseline characteristics of the study population are shown in Table 1 . The median age was 41 years (IQR 29, 53), 59 % were female, 49 % were married, 69 % had completed high school or equivalent, 59 % earned less than $30K/year, 24 % had lived fewer than 10 years in the United States. Most participants had a high patient-clinician communication score (71 %). Participants with high communication scores were older, more often married, more often born outside of the 50 US states, had lower educational attainment, preferred Spanish over English, had higher rates of diabetes and hypertension, and had lower use of alcohol ( Table 1 ). Table 1. Baseline characteristics by communication score. Communication Score Characteristic Low/Mid n = 3009, (29 %) 1 High n = 7518, (71 %) 1 p-value 2 Age 38 (26, 50) 42 (30, 55) <0.001 Female 1708 (59 %) 4196 (59 %) >0.9 Education <0.001 <HS 826 (28 %) 2331 (33 %) HS 820 (28 %) 1862 (26 %) >HS 299 (10 %) 907 (13 %) College+ 961 (33 %) 2036 (29 %) Annual Household Income 0.013 <$30K 1711 (59 %) 4254 (60 %) ≥$30K 1061 (36 %) 2406 (34 %) Missing 138 (4.7 %) 485 (6.8 %) Marital Status <0.001 Single 1132 (39 %) 2325 (33 %) Married 1309 (45 %) 3574 (50 %) Separated 463 (16 %) 1234 (17 %) Employment 0.002 Retired 203 (7.0 %) 760 (11 %) Unemployed 1259 (43 %) 2988 (42 %) Part-time 539 (19 %) 1162 (16 %) Full-time 900 (31 %) 2224 (31 %) Years in US <0.001 <10 603 (21 %) 1803 (25 %) 10+ 1327 (46 %) 3791 (53 %) US Born 968 (33 %) 1525 (21 %) Background <0.001 Dominican 291 (10 %) 837 (12 %) Central/South American 279 (9.6 %) 836 (12 %) Cuban 235 (8.1 %) 1480 (21 %) Mexican 1268 (44 %) 2574 (36 %) Puerto Rican 658 (23 %) 1170 (16 %) More than one/Other 164 (5.7 %) 239 (3.4 %) Preferred Language <0.001 Spanish 1806 (62 %) 5432 (76 %) English 1104 (38 %) 1714 (24 %) Charlson Comorbidity Index 0.13 0 934 (32 %) 2439 (34 %) 1–2 1655 (57 %) 3840 (54 %) 3+ 321 (11 %) 866 (12 %) Diabetes 385 (13 %) 1198 (17 %) <0.001 Hypertension 971 (33 %) 2887 (40 %) <0.001 Non-HDL Chol. > 130 1657 (57 %) 4287 (60 %) 0.10 Antihypertensive Drugs 443 (15 %) 1523 (21 %) <0.001 Lipid-lowering Drugs (including statins) 231 (8.1 %) 830 (12 %) <0.001 Antiplatelet Drugs (including aspirin) 509 (18 %) 1463 (20 %) 0.022 Alcohol Use Level 0.013 None 1345 (46 %) 3667 (51 %) Low 1393 (48 %) 3127 (44 %) High 170 (5.8 %) 347 (4.9 %) Tobacco Smoking 0.5 Never 1824 (63 %) 4571 (64 %) Former 489 (17 %) 1239 (17 %) Current 589 (20 %) 1326 (19 %) Study Site <0.001 Bronx 1021 (35 %) 2119 (30 %) Chicago 533 (18 %) 1086 (15 %) Miami 362 (12 %) 2100 (29 %) San Diego 993 (34 %) 1841 (26 %) Open in a new tab 1 Median (IQR); n ( %). 2 Wilcoxon rank-sum test for complex survey samples; chi-squared test with Rao & Scott's second-order correction. During the study period from 2008 to 2019 at least one of the composite outcome events occurred in 515 participants (4.7 %), a first adjudicated CV event occurred in 239 (2.2 %) and death occurred in 313 (3.0 %). The mean follow-up time was 9.4 years, and 183 subjects withdrew from the study (1.9 %). The composite outcome of first CV event or death from any cause was numerically lower in the those with high communication scores (HR 0.92; 95 % CI 0.63, 1.35; p = 0.66) and this association strengthened in our fully adjusted model but did not meet nominal statistical significance (aHR 0.73; 95 % CI 0.51, 1.03; p = 0.073). Death from any cause was numerically lower in the group with high communication scores (HR 0.72; 95 % CI 0.44, 1.17; p = 0.18) and this association strengthened in the adjusted model, reaching nominal statistical significance (aHR 0.54; 95 % CI 0.37, 0.80; p = 0.002). There was no appreciable difference in first CV events (HR 0.99; 95 % CI 0.48, 2.03; p = 0.98), while the rate was numerically lower in the adjusted model (aHR 0.82, 95 % CI 0.44, 1.51, p = 0.520) but not statistically significant. Full results of the unadjusted, sociodemographic-adjusted and fully adjusted analyses are presented in Table 2 . Table 2. Patient-clinician communication and hazard of first CV event or death, HCHS/SOL, 2008–2019. Unadjusted Adjusted (model 1) 1 Adjusted (model 2) 2 HR 95 % CI p-value HR 95 % CI p-value HR 95 % CI p-value Communication score: high vs. low-to-mid First CV event or death from any cause 0.92 0.63, 1.35 0.66 0.71 0.49, 1.01 0.057 0.73 0.51, 1.03 0.073 Death from any cause 0.72 0.44, 1.17 0.18 0.53 0.35, 0.80 0.003 0.54 0.37, 0.80 0.002 First CV Event 0.99 0.48, 2.03 0.98 0.78 0.41, 1.48 0.46 0.82 0.44, 1.51 0.52 Language difficulties: none vs. any First CV event or death from any cause 1.24 0.88, 1.73 0.22 1.15 0.84, 1.56 0.39 1.15 0.84, 1.57 0.38 Death from any cause 1.75 1.18, 2.59 0.005 1.57 1.05, 2.36 0.028 1.59 1.05, 2.39 0.028 First CV Event 1.01 0.59, 1.74 0.98 0.89 0.57, 1.39 0.60 0.90 0.57, 1.41 0.64 Open in a new tab HR = hazard ratio, CI = confidence interval; All analyses account for survey weights. 1 Adjusted for age, sex, educational attainment, income, marital status, employment, health insurance, nativity/years in the US, study site, national origin, and preferred language;. 2 Adjusted for smoking, alcohol use, and Charlson Comorbidity Index in addition to the Model 1 covariates above;. In the group that reported never having language-related communication challenges, the composite outcome of first CV event or death from any cause was numerically higher (HR 1.24; 95 % CI 0.88, 1.73; p = 0.22) and this association attenuated slightly in our fully adjusted model (aHR 1.15; 95 % CI 0.84, 1.57; p = 0.38). Death from any cause was higher in the group without language-related challenges (HR 1.75; 95 % CI 1.18, 2.29; p = 0.005) and this association attenuated in the adjusted model but remained statistically significant (aHR 1.59; 95 % CI 1.05, 2.39; p = 0.028). There was no appreciable difference in first CV events (HR 1.01; 95 % CI 0.59, 1.74; p = 0.98) with similar results in the adjusted model (aHR 0.90; 95 % CI 0.57, 1.41; p = 0.64). In our sensitivity analysis without survey weighting, the association between a high communication score the composite outcome was similar to the primary analysis (aHR 0.83, 95 % CI 0.68, 1.01; p = 0.065). The association between a high communication score and death from any cause was also similar (aHR 0.73; 95 % CI 0.57, 0.94; p = 0.013). The association between never having language difficulty and death from any cause was not statistically significant in the unweighted sensitive analysis. Full results of the unweighted sensitivity analysis are presented in Supplemental Table 2A. E-value for the association between communication quality and all-cause mortality was 3.11. In other words, if an unmeasured confounder explained this result, it would need to be associated with a hazard ratio of 3.11 for all-cause death and simultaneously associated to the same degree with high-quality communication. A high communication score was associated with a lower baseline LE8 (LE8 difference -1.50; 95 % CI -2.50, -0.60; p = 0.001), but there was no difference in the adjusted model (LE8 difference -0.15; 95 % CI -1.0, 0.70; p = 0.720). All values are presented in Table 3 . Table 3. LE8 difference by communication characteristics. LE 8 Difference 95 % CI 1 p-value Communication Score: high vs low-mid Crude -1.4 -2.4, -0.49 0.003 Adjusted 2 -0.15 -1.0, 0.70 0.72 Language Difficulties: none vs any Crude 0.23 -0.76, 1.2 0.65 Adjusted 0.46 -0.41, 1.3 0.30 Open in a new tab 1 CI = Confidence Interval. 2 Adjusted for age, sex, educational attainment, income, marital status, employment, health insurance, nativity/years in the US, preferred language, study center, Hispanic/Latino background, alcohol use, smoking tobacco, and Charlson Comorbidity Index. 4. Discussion In this prospective study of 10,527 Hispanic/Latino adults in four American cities, we found that high-quality patient-clinician communication was associated with a non-significant trend toward a lower rate of CV events or death from any cause, driven by a lower rate of all-cause death that was statistically significant. The absence of language barriers was associated with a non-significant trend toward higher rates of the composite endpoint and higher rates of all-cause death, although this association did not persistent in our unweighted sensitivity analysis. Our study builds upon prior literature investigating patient-clinician communication, and, to our knowledge, this is the first study to assess the association between patient-clinician communication and long-term cardiovascular and mortality outcomes. Small randomized trials enhancing patient-clinician communication have shown benefits in surrogate measures, such as blood pressure, smoking cessation, anxiety/depression, and weight loss [ 5 ]. In one randomized trial of stroke patients, motivational interviewing approaches by health care practitioners resulted in reduced mortality at one year [ 35 ]. Our study offers a novel prospective assessment focused on both cardiovascular events and death over more than 10 years of follow-up. Our study is also the largest study to date specifically investigating patient-clinician communication among self-identified Hispanic/Latino adults living in the United States, a population that is often marginalized by the healthcare system. Our findings are notable for a 46 % lower rate of all-cause mortality associated with high-quality patient-clinician communication. Possible explanations are either that high-quality communication reduces mortality or that high-quality communication is closely associated with strong unmeasured confounders. The E-value for this finding was high, at 3.11, which supports a causal relationship between baseline communication quality and all-cause mortality. If the relationship is not causal, then these results demonstrate an equally notable finding: unmeasured communication-associated variables—variables such as empathy, trust, a longitudinal relationship, patient-clinician concordance, and cultural sensitivity—have a strong mortality benefit. High-quality communication may improve cardiovascular outcomes and mortality through a direct effect on health-promoting behaviors, such as improved adherence to lifestyle advice or medications [ 36 ]. It is also possible that high-quality communication improves future health-seeking behavior, such as attending follow-up appointments, routine screening, and early presentation for concerning symptoms. Moreover, patient-perceived high-quality communication may represent a deeper sense of connection and understanding between patient and clinician, which can have physiologic benefits mediated by psychological mechanisms [ 37 , 38 ]. When the strong association between communication and all-cause mortality is considered in light of the modest non-significant association with CV events, the benefits of high-quality communication appear to be driven less by modification of CV risk factors and are more by enhanced healthcare engagement and the psychosocial benefits of connectedness. The association between the absent language difficulties and higher mortality is unlikely to be directly causal as there is no apparent mechanism. Some of this association may be explained by acculturation, which is associated with poorer health outcomes for Hispanic/Latino populations in the U.S and may not be captured by the measured sociocultural covariates [ 39 ]. Notably, this association was not statistically significant in our sensitivity analysis without survey weighting, which suggests in may have be driven by a small number of events in heavily weighted individuals. High-quality patient-clinician communication qualities were not associated with higher baseline LE8 scores. Communication quality within the prior year may take time to affect the LE8 and therefore would not be apparent in a cross-sectional analysis. Ongoing visits with a variety of health care practitioners and not just one visit with a clinician are likely needed to provide counseling related to the multiple behaviors associated with LE8 scores. It is also possible that patient-clinician communication may affect health through non-traditional risk factors, including mitigation of psychological stressors which are strongly associated with CV outcomes but not included in the LE8 [ 40 ]. Of course, it is also possible that the signal of benefit associated with strong relationships may be lost due to unmeasured confounding from baseline health conditions that lead people to build relationships with clinicians. The present findings have far-reaching implications for future research and innovation. There is a need for studies in populations with higher event rates to confirm or refute the trends seen in our data. These findings also demonstrate the need for randomized trials of interventions aimed at improving communication parameters with a particular emphasis on the inclusion of Hispanic/Latino participants who are generally underrepresented in clinical studies [ 41 ]. 4.1. Limitations and strengths This study has important limitations. First, residual confounding is inherent to the observational design and limits the ability to make causal conclusions. While rich baseline survey data, including both detailed medical and psychosocial domains, made it possible to adjust for many potential confounders, some important confounders were not assessed. For instance, there was no measure of personal or organizational health literacy [ 42 ]. Second, the cohort was relatively young with a low overall event rate, which limited the power to detect a statistically significant difference in event rates for the composite outcome. Moreover, we limited our analysis to adjudicated CV events, increasing our specificity, but at the cost of sensitivity. Third, our external validity may be limited as 71 % of the population reported high-quality communication, twice that reported in another nationally representative cohort using the same survey instrument [ 24 ], reflecting the fact that those who enroll in a study like HCHS/SOL may be more engaged with their health than the larger population. However, this issue is partially mitigated by using sampling weights. Fourth, high quality communication may affect outcomes through the use of preventive therapies, but medication use patterns were not assessed longitudinally. Fifth, patient-clinician communication involves two or more individuals, but we only had patient-perspective data without input from their clinicians or third-party observers, and the setting of the clinical encounters (continuity visits vs acute care) was unknown. Finally, we demonstrated an association between communication quality and all-cause mortality, but the specific causes of death in this cohort have yet to be fully adjudicated. Strengths of this study include the large cohort representing a diverse population of self-identified Hispanic/Latino adults in geographically diverse settings across the United States, prospective assessment of multiple dimensions of the patient-clinician communication, rich baseline survey data on social and economic covariates, prospective adjudication of cardiovascular events, and minimal loss to follow-up. 5. Conclusion In a diverse cohort of Hispanic/Latino participants living in the U.S, high-quality patient-clinician communication was associated with a non-significant trend toward lower rates of CV events and significantly lower all-cause mortality. These findings demonstrate the potential for research and innovation focused on patient-clinician communication to improve health outcomes, including for medically marginalized populations. Disclosure Drs. Mittleman and Slavin had full access to the study data and take responsibility for the integrity of the data and accuracy of analyses. All authors have reviewed and approved the final manuscript. None of the authors had any financial or other conflicts of interest. Ethical review statement The study was approved by the institutional review board (IRB) at the University of North Carolina coordinating center and at each study site. Funding The Hispanic Community Health Study/Study of Latinos was carried out as a collaborative study supported by contracts from the National Heart, Lung, and Blood Institute (NHLBI) to the University of North Carolina (N01-HC65233), University of Miami (N01-HC65234), Albert Einstein College of Medicine (N01-HC65235), Northwestern University (N01-HC65236), and San Diego State University (N01-HC65237). The following Institutes/Centers/Offices contribute to the HCHS/SOL through a transfer of funds to the NHLBI: National Center on Minority Health and Health Disparities, the National Institute of Deafness and Other Communications Disorders, the National Institute of Dental and Craniofacial Research, the National Institute of Diabetes and Digestive and Kidney Diseases, the National Institute of Neurological Disorders and Stroke, and the Office of Dietary Supplements. Dr. Slavin was supported by a training grant from the National Institutes of Health (T32HL007604). CRediT authorship contribution statement Samuel D. Slavin: Conceptualization, Methodology, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization, Project administration. Martha L. Daviglus: Investigation, Methodology, Resources, Writing – review & editing. Olga Garcia-Bedoya: Investigation, Methodology, Resources, Writing – review & editing. Yasmin Mossavar-Rahmani: Investigation, Methodology, Resources, Writing – review & editing. Frank Penedo: Investigation, Methodology, Resources, Writing – review & editing. Krista Perreira: Investigation, Methodology, Resources, Writing – review & editing. Sylvia Wassertheil-Smoller: Investigation, Methodology, Resources, Writing – review & editing. Alberto Ramos: Investigation, Methodology, Resources, Writing – review & editing, Project administration. Raymond Rigat: Investigation, Visualization. Gregory Talavera: Investigation, Methodology, Resources, Writing – review & editing. Andrew Telzak: Investigation, Methodology, Resources, Writing – review & editing. Murray A. Mittleman: Conceptualization, Methodology, Formal analysis, Investigation, Resources, Writing – review & editing, Supervision, Project administration. Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Samuel D. Slavin reports financial support was provided by National Institutes of Health. The Hispanic Community Health Study/Study of Latinos was carried out as a collaborative study supported by contracts from the National Heart, Lung, and Blood Institute (NHLBI) to the University of North Carolina (N01-HC65233), University of Miami (N01-HC65234), Albert Einstein College of Medicine (N01-HC65235), Northwestern University (N01-HC65236), and San Diego State University (N01-HC65237). The following Institutes/Centers/Offices contribute to the HCHS/SOL through a transfer of funds to the NHLBI: National Center on Minority Health and Health Disparities, the National Institute of Deafness and Other Communications Disorders, the National Institute of Dental and Craniofacial Research, the National Institute of Diabetes and Digestive and Kidney Diseases, the National Institute of Neurological Disorders and Stroke, and the Office of Dietary Supplements. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgment The authors thank the staff and participants of HCHS/SOL for their important contributions. A complete list of staff and investigators has been published previously and is also available on the study website. Footnotes Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.ajpc.2026.101493 . Contributor Information Samuel D. Slavin, Email: [email protected]. Martha L. Daviglus, Email: [email protected]. Olga Garcia-Bedoya, Email: [email protected]. Yasmin Mossavar-Rahmani, Email: [email protected]. Frank Penedo, Email: [email protected]. Krista Perreira, Email: [email protected]. Sylvia Wassertheil-Smoller, Email: [email protected]. Alberto Ramos, Email: [email protected]. Raymond Rigat, Email: [email protected]. Gregory Talavera, Email: [email protected]. Andrew Telzak, Email: [email protected]. Murray A. Mittleman, Email: [email protected]. Appendix. Supplementary materials mmc1.docx (14.4KB, docx) mmc2.docx (22.9KB, docx) mmc3.docx (17.2KB, docx) mmc4.docx (19.1KB, docx) mmc5.docx (24.5KB, docx) References 1. Piette J.D., Heisler M., Krein S., Kerr EA. 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