Larisa G Tereshchenko, Kazi T Haq, Stacey J Howell, Evan C Mitchell, Jesús Martínez, Jessica Hyde, Genesis Briceno, Jose Pena, Edvinas Pocius, Akram Khan, Elsayed Z Soliman, João A C Lima, Samir R Kapadia, Anita D Misra-Hebert, Michael W Kattan, Mayank M Kansal, Martha L Daviglus, Robert Kaplan
{"title":"Latent profiles of global electrical heterogeneity: the Hispanic Community Health Study/Study of Latinos.","authors":"Larisa G Tereshchenko, Kazi T Haq, Stacey J Howell, Evan C Mitchell, Jesús Martínez, Jessica Hyde, Genesis Briceno, Jose Pena, Edvinas Pocius, Akram Khan, Elsayed Z Soliman, João A C Lima, Samir R Kapadia, Anita D Misra-Hebert, Michael W Kattan, Mayank M Kansal, Martha L Daviglus, Robert Kaplan","doi":"10.1093/ehjdh/ztae048","DOIUrl":null,"url":null,"abstract":"<p><strong>Aims: </strong>Despite the highest prevalence of stroke, obesity, and diabetes across races/ethnicities, paradoxically, Hispanic/Latino populations have the lowest prevalence of atrial fibrillation and major Minnesota code-defined ECG abnormalities. We aimed to use Latent Profile Analysis in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) population to obtain insight into epidemiological discrepancies.</p><p><strong>Methods and results: </strong>We conducted a cross-sectional analysis of baseline HCHS/SOL visit. Global electrical heterogeneity (GEH) was measured as spatial QRS-T angle (QRSTa), spatial ventricular gradient azimuth (SVGaz), elevation (SVGel), magnitude (SVGmag), and sum absolute QRST integral (SAIQRST). Statistical analysis accounted for the stratified two-stage area probability sample design. We fitted a multivariate latent profile generalized structural equation model adjusted for age, sex, ethnic background, education, hypertension, diabetes, smoking, dyslipidaemia, obesity, chronic kidney disease, physical activity, diet quality, average RR' interval, median beat type, and cardiovascular disease (CVD) to gain insight into the GEH profiles. Among 15 684 participants (age 41 years; 53% females; 6% known CVD), 17% had an increased probability of likely abnormal GEH profile (QRSTa 80 ± 27°, SVGaz -4 ± 21°, SVGel 72 ± 12°, SVGmag 45 ± 12 mVms, and SAIQRST 120 ± 23 mVms). There was a 23% probability for a participant of being in Class 1 with a narrow QRSTa (40.0 ± 10.2°) and large SVG (SVGmag 108.3 ± 22.6 mVms; SAIQRST 203.4 ± 39.1 mVms) and a 60% probability of being in intermediate Class 2.</p><p><strong>Conclusion: </strong>A substantial proportion (17%) in the Hispanic/Latino population had an increased probability of altered, likely abnormal GEH profile, whereas 83% of the population was resilient to harmful risk factors exposures.</p>","PeriodicalId":72965,"journal":{"name":"European heart journal. Digital health","volume":"5 5","pages":"611-621"},"PeriodicalIF":3.9000,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11417492/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"European heart journal. Digital health","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/ehjdh/ztae048","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/9/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Aims: Despite the highest prevalence of stroke, obesity, and diabetes across races/ethnicities, paradoxically, Hispanic/Latino populations have the lowest prevalence of atrial fibrillation and major Minnesota code-defined ECG abnormalities. We aimed to use Latent Profile Analysis in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) population to obtain insight into epidemiological discrepancies.
Methods and results: We conducted a cross-sectional analysis of baseline HCHS/SOL visit. Global electrical heterogeneity (GEH) was measured as spatial QRS-T angle (QRSTa), spatial ventricular gradient azimuth (SVGaz), elevation (SVGel), magnitude (SVGmag), and sum absolute QRST integral (SAIQRST). Statistical analysis accounted for the stratified two-stage area probability sample design. We fitted a multivariate latent profile generalized structural equation model adjusted for age, sex, ethnic background, education, hypertension, diabetes, smoking, dyslipidaemia, obesity, chronic kidney disease, physical activity, diet quality, average RR' interval, median beat type, and cardiovascular disease (CVD) to gain insight into the GEH profiles. Among 15 684 participants (age 41 years; 53% females; 6% known CVD), 17% had an increased probability of likely abnormal GEH profile (QRSTa 80 ± 27°, SVGaz -4 ± 21°, SVGel 72 ± 12°, SVGmag 45 ± 12 mVms, and SAIQRST 120 ± 23 mVms). There was a 23% probability for a participant of being in Class 1 with a narrow QRSTa (40.0 ± 10.2°) and large SVG (SVGmag 108.3 ± 22.6 mVms; SAIQRST 203.4 ± 39.1 mVms) and a 60% probability of being in intermediate Class 2.
Conclusion: A substantial proportion (17%) in the Hispanic/Latino population had an increased probability of altered, likely abnormal GEH profile, whereas 83% of the population was resilient to harmful risk factors exposures.