Browsing by Author "Liu, Chunyu"

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    A meta-analysis of gene expression signatures of blood pressure and hypertension
    (2015) Huan, Tianxiao; Esko, Tõnu; Peters, Marjolein J.; Pilling, Luke C.; Schramm, Katharina; Schurmann, Claudia; Chen, Brian H.; Liu, Chunyu; Joehanes, Roby; Eyheramendy Duerr, Susana
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    Body mass index is superior to other body adiposity indexes in predicting incident hypertension in a highly admixed sample after 10-year follow-up: The Baependi Heart Study
    (2022) Maciel de Oliveira, Camila; Franca da Rosa, Francielle; de Oliveira Alvim, Rafael; Mourao Junior, Carlos Alberto; Bacells, Mercedes; Liu, Chunyu; Pavani, Jessica; Capasso, Robson; Lavezzo Dias, Fernando Augusto; Eduardo Krieger, Jose; Costa Pereira, Alexandre
    Hypertension is the leading cause of overall mortality in low- and middle-income countries. In Brazil, there is paucity of data on the determinants of incident hypertension and related risk factors. We aimed to determine the incidence of hypertension in a sample from the Brazilian population and investigate possible relationships with body adiposity indexes. We assessed risk factors associated with cardiovascular disease, including adiposity body indexes and biochemical analysis, in a sample from the Baependi Heart Study before and after a 10-year follow-up. Hypertension was defined by the presence of systolic blood pressure (SBP) >= 140 mmHg and/or diastolic blood pressure >= 90 mmHg or the use of antihypertensive drugs. From an initial sample of 1693 participants, 498 (56% women; mean age 38 +/- 13 years) were eligible to be included. The overall hypertension incidence was 24.3% (22.3% in men and 25.6% in women). Persons who developed hypertension had higher prevalence of obesity, higher levels for blood pressure, higher frequency of dyslipidemia, and higher body adiposity indexes at baseline. The best prediction model for incident hypertension includes age, sex, HDL-c, SBP, and Body Mass Index (BMI) [AUC = 0.823, OR = 1.58 (95% CI 1.23-2.04)]. BMI was superior in its predictive capacity when compared to Body Adiposity Index (BAI), Body Roundness Index (BRI), and Visceral Adiposity Index (VAI). Incident hypertension in a sample from the Brazilian population was 24.3% after 10-year follow-up and BMI, albeit the simpler index to be calculated, is the best anthropometric index to predict incident hypertension.
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    Comparing different metabolic indexes to predict type 2 diabetes mellitus in a five years follow-up cohort: The Baependi Heart Study
    (2022) de Oliveira, Camila Maciel; Pavani, Jessica Leticia; Liu, Chunyu; Balcells, Mercedes; Capasso, Robson; Alvim, Rafael de Oliveira; Mourao-Junior, Carlos Alberto; Krieger, Jose Eduardo; Pereira, Alexandre Costa
    This study evaluates the association of anthropometric indexes and the incidence of type 2 diabetes mellitus (T2DM) after a 5-year follow-up. This analysis included 1091 middle-aged participants (57% women, mean age 47 +/- 15 years) who were free of T2DM at baseline and attended two health examinations cycles [cycle 1 (2005-2006) and cycle 2 (2010-2013)]. As expected, the participants who developed T2DM after five years (3.8%) had the worst metabolic profile with higher hypertension, dyslipidemia, and obesity rates. Besides, using mixed-effects logistic regression and adjustment for sex, age, and glucose, we found that one unit increase in body adiposity index (BAI) was associated with an 8% increase in their risk of developing T2DM (odds ratio [OR] = 1.08 [95% CI, 1.02-1.14]) and visceral adiposity index (VAI) was associated with a risk increase of 11% (OR = 1.11 [95% CI, 1.00-1.22]). Moreover, a one-unit increase in the triglycerides-glucose index (TyG) was associated with more than four times the risk of developing T2DM (OR = 4.27 [95% CI, 1.01-17.97]). The interquartile range odds ratio for the continuous predictors showed that TyG had the best discriminating performance. However, when any of them were additionally adjusted for waist circumference (WC) or even body mass index (BMI), all adiposity indexes lost the effect in predicting T2DM. In conclusion, TyG had the most substantial predictive power among all three indexes. However, neither BAI, VAI, nor TyG were superior to WC or BMI for predicting the risk of developing T2DM in a middle-aged normoglycemic sample in this rural Brazilian population.
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    Relationship between marital status and incidence of type 2 diabetes mellitus in a Brazilian rural population: The Baependi Heart Study
    (2020) de Oliveira, Camila Maciel; Viater Tureck, Luciane; Alvares, Danilo; Liu, Chunyu; Horimoto, Andrea Roseli Vancan Russo; Balcells, Mercedes; de Oliveira Alvim, Rafael; Krieger, Jose Eduardo; Pereira, Alexandre Costa
    Many factors influence the incidence of type 2 diabetes mellitus (T2DM). Here, we investigated the associations between socio-demographic characteristics and familial history with the 5-year incidence of T2DM in a family-based study conducted in Brazil. T2DM was defined as baseline fasting blood glucose >= 126 mg/dL or the use of any hypoglycaemic drug. We excluded individuals with T2DM at baseline or if they did not attend two examination cycles. After exclusions, we evaluated a sample of 1,125 participants, part of the Baependi Heart Study (BHS). Mixed-effects logistic regression models were used to assess T2DM incident given different characteristics. At the 5-year follow-up, the incidence of T2DM was 6.7% (7.2% men and 6.3% women). After adjusting for age, sex, and education status, the model that combined marital and occupation status, skin color, and familial history of T2DM provided the best prediction for T2DM incidence. Only marital status was independently associated with T2DM incidence. Individuals that remained married, despite having significantly increased their weight, were significantly less likely to develop diabetes than their divorced counterparts.
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    Vulnerability of blue foods to human-induced environmental change
    (2023) Cao, Ling; Halpern, Benjamin S.; Troell, Max; Short, Rebecca; Zeng, Cong; Jiang, Ziyu; Liu, Yue; Zou, Chengxuan; Liu, Chunyu; Liu, Shurong; Liu, Xiangwei; Cheung, William W. L.; Cottrell, Richard S.; DeClerck, Fabrice; Gelcich, Stefan; Gephart, Jessica A.; Godo-Solo, Dakoury; Kaull, Jessie Ihilani; Micheli, Fiorenza; Naylor, Rosamond L.; Payne, Hanna J.; Selig, Elizabeth R.; Sumaila, U. Rashid; Tigchelaar, Michelle
    Global aquatic foods are a key source of nutrition, but how their production is influenced by anthropogenic environmental changes is not well known. The vulnerability of global blue food systems to main environmental stressors and the related spatial impacts across blue food nations are now quantified.