GLAUCYLARA REIS GEOVANINI
Projetos de Pesquisa
Unidades Organizacionais
Instituto Central, Hospital das Clínicas, Faculdade de Medicina
LIM/13 - Laboratório de Genética e Cardiologia Molecular, Hospital das Clínicas, Faculdade de Medicina
LIM/13 - Laboratório de Genética e Cardiologia Molecular, Hospital das Clínicas, Faculdade de Medicina
3 resultados
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- Poor sleep quality and lipid profile in a rural cohort (The Baependi Heart Study)(2019) GEOVANINI, Glaucylara Reis; LORENZI-FILHO, Geraldo; PAULA, Lilian K. de; OLIVEIRA, Camila Maciel; ALVIM, Rafael de Oliveira; BEIJAMINI, Felipe; NEGRAO, Andre Brooking; SCHANTZ, Malcolm von; KNUTSON, Kristen L.; KRIEGER, Jose Eduardo; PEREIRA, Alexandre CostaAim: To test the association between cardiometabolic risk factors and subjective sleep quality assessed by the Pittsburgh sleep quality index (PSQI), independent of obstructive sleep apnea (OSA) and sleep duration. Methods: A total of 573 participants from the Baependi Heart Study, a rural cohort from Brazil, completed sleep questionnaires and underwent polygraphy for OSA evaluation. Multivariable linear regression analysis tested the association between cardiovascular risk factors (outcome variables) and sleep quality measured by PSQI, adjusting for OSA and other potential confounders (age, sex, race, salary/wage, education, marital status, alcohol intake, obesity, smoking, hypertension, and sleep duration). Results: The sample mean age was 43 +/- 16 years, 66% were female, and mean body mass index (BMI) was 26 +/- 5 kg/m(2). Only 20% were classified as obese (BMI >= 30). Overall, 50% of participants reported poor sleep quality as defined by a PSQI score >= 5. A high PSQI score was significantly associated with higher very-low-density lipoprotein (VLDL) cholesterol levels (beta = 0.392, p = 0.012) and higher triglyceride levels (beta = 0.017, p = 0.006), even after adjustments, including the apneaehypopnea index. Further adjustments accounting for marital status, alcohol intake, and medication use did not change these findings. No significant association was observed between PSQI scores and glucose or blood pressure. According to PSQI components, sleep disturbances (beta = 1.976, p = 0.027), sleep medication use (beta = 1.121, p = 0.019), and daytime dysfunction (beta = 1.290, p = 0.024) were significantly associated with higher VLDL serum levels. Only the daytime dysfunction domain of the PSQI components was significantly associated with higher triglyceride levels (beta = 0.066, p = 0.004). Conclusion: Poorer lipid profile was independently associated with poor sleep quality, assessed by the PSQI questionnaire, regardless of a normal sleep duration and accounting for OSA and socio-economic status.
- Carotid intima-media thickness and metabolic syndrome in a rural population: Results from the Baependi Heart Study(2020) GEOVANINI, G.R.; SOUSA, I. Pinheiro de; TEIXEIRA, S.K.; FRANCISCO NETO, M.J.; GóMEZ, L.M. Gómez; GUERRA, G.C. Del; PEREIRA, A.C.; KRIEGER, J.E.Background and aims: Carotid intima-media thickness (cIMT) is a strong predictor of cardiovascular events and associated with metabolic syndrome (MetS). MetS is a cluster of cardiovascular risk factors, but the association structure between specific factors and disease development is not well-established in rural populations. We described the association structure between MetS factors and cIMT in a sample from rural Brazil. Methods: We studied 1937 participants from the Baependi Heart Study who underwent carotid ultrasound exam. We used ATP–III–2001 for MetS definition and linear mixed-effects models, adjusting by the family structure, to assess independent associations between the cardiovascular risk factors which define MetS and cIMT. Results: The sample's mean age was 46 ± 16y, 61% female, 73% white, mean body-mass-index 26±5 kg/m2, mean cIMT 0.53 ± 0.16 mm, with 35% of the sample classified with MetS. As expected, cIMT demonstrated a linear relationship with increasing age, and cIMT higher values were observed for MetS (0.58 ± 0.16 mm) compared to non-MetS (0.49 ± 0.14 mm). Considering models for cIMT with MetS and all of its factors, we found that blood pressure, glucose and obesity were independently associated with cIMT, but not HDL or triglycerides. Conclusions: cIMT showed a linear relationship with increasing age. Blood pressure, obesity, and glucose were independently associated with cIMT, but not HDL-cholesterol or triglycerides. In a rural population, hypertension, diabetes and obesity play a more important role than lipids in determining cIMT interindividual variability. © 2020 The Authors
- Age and Sex Differences in Heart Rate Variability and Vagal Specific Patterns - Baependi Heart Study(2020) GEOVANINI, Glaucylara Reis; VASQUES, Enio Rodrigues; ALVIM, Rafael de Oliveira; MILL, Jose Geraldo; ANDREAO, Rodrigo Varejao; VASQUES, Bruna Kim; PEREIRA, Alexandre Costa; KRIEGER, Jose EduardoBackground: Heart rate variability (HRV) is a noninvasive method for assessing autonomic function. Age, sex, and chronic conditions influence HRV. Objectives: Our aim was to evaluate HRV measures exploring differences by age, sex, and race in a sample from a rural area. Methods: Analytical sample (n = 1,287) included participants from the 2010 to 2016 evaluation period of the Baependi Heart Study, a family-based cohort in Brazil. Participants underwent 24-hour Holter-ECG (Holter) monitoring. To derive population reference values, we restricted our analysis to a 'healthy' subset (i.e. absence of medical comorbidities). A confirmatory analysis was conducted with a subgroup sample that also had HRV derived from a resting ECG 10'-protocol obtained during the same time period. Results: The 'healthy' subset included 543 participants. Mean age was 40 +/- 14y, 41% were male, 74% self-referred as white and mean body-mass-index was 24 +/- 3kg/m(2). Time domain HRV measures showed significant differences by age-decade and by sex. Higher values were observed for males across almost all age-groups. Parasympathetic associated variables (rMSSD and pNN50) showed a U-shaped distribution and reversal increase above 60y. Sympathetic-parasympathetic balance variables (SDNN, SDANN) decreased linearly by age. Race differences were no significant. We compared time domain variables with complete data (Holter and resting ECG) between 'healthy' versus 'unhealthy' groups. Higher HRV values were shown for the 'healthy' subset compared with the 'unhealthy' group. Conclusion: HRV measures vary across age and sex. A U-shaped pattern and a reversal increase in parasympathetic variables may reflect an age-related autonomic dysfunction even in healthy individuals that could be used as a predictor of disease development.