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1.
Br J Nutr ; 128(4): 762-769, 2022 08 28.
Artigo em Inglês | MEDLINE | ID: mdl-34511145

RESUMO

The present study aimed to explore the association between dietary patterns in abdominal obesity obtained by reduced-rank regression (RRR) with visceral fat index (VFI) as a dependent variable and dyslipidemia in rural adults in Henan, China. A total of 29538 people aged 18-79 were selected from the Henan Rural Cohort Study. RRR analysis was used to identify dietary patterns; logistic regression analysis and restricted cubic spline regression models were applied to analyze the association between dietary patterns in abdominal obesity and dyslipidemia. VFI was used as a mediator to estimate the mediation effect. The dietary pattern in abdominal obesity was characterized by high carbohydrate and red meat intake and low consumption of fresh fruits, vegetables, milk, etc. After full adjustment, the highest quartile of dietary pattern scores was significantly associated with an increased risk of dyslipidemia (OR: 1·33, 95 % CI 1·23-1·44, Ptrend < 0·001), there was a non-linear dose-response relationship between them (Poverall-association < 0·001, Pnon-lin-association = 0·022). The result was similar in dose-response between the dietary pattern scores and VFI. The indirect effect partially mediated by VFI was significant (OR: 1·07, 95 % CI 1·06-1·08). VIF explained approximately 53·3 % of odds of dyslipidemia related to the dietary pattern. Abdominal obesity dietary pattern scores positively affected VFI and dyslipidemia; there was a dose-response in both relationships. Dyslipidemia progression increased with higher abdominal obesity dietary pattern scores. In addition, VFI played a partial mediating role in relationship between abdominal obesity dietary pattern and dyslipidemia.


Assuntos
Dislipidemias , Obesidade Abdominal , Adulto , Humanos , Estudos de Coortes , Gordura Intra-Abdominal , Dieta/efeitos adversos , Obesidade , China , Fatores de Risco
2.
Biomed Environ Sci ; 34(12): 952-962, 2021 Dec 20.
Artigo em Inglês | MEDLINE | ID: mdl-34981718

RESUMO

OBJECTIVE: To our knowledge, no definitive conclusion has been reached regarding the relationship between glucocorticoids and hypertension. Here, we aimed to explore the characteristics of glucocorticoids in participants with dysglycemia and hypertension, and to analyze their association with blood pressure indicators. METHODS: The participants of this study were from the Henan Rural Cohort study. A total of 1,688 patients 18-79 years of age were included in the matched case control study after application of the inclusion and exclusion criteria. Statistical methods were used to analyze the association between glucocorticoids and various indices of blood pressure, through approaches such as logistic regression analysis, trend tests, linear regression, and restricted cubic regression. RESULTS: The study population consisted of 552 patients with dysglycemia and hypertension (32.7%). The patients with co-morbidities had higher levels of serum cortisol ( P = 0.009) and deoxycortisol ( P < 0.001). The adjusted odds ratios (and 95% confidence intervals) for dysglycemia with hypertension were 1.55 (1.18, 2.04) for the highest tertile of Ln-cortisol compared with the lowest tertile. Additionally, the highest Ln-deoxycortisol levels were associated with increased prevalence of dysglycemia with hypertension by 159% (95% confidence interval: 122%, 207%). CONCLUSIONS: Serum deoxycortisol was positively correlated with systolic blood pressure, pulse pressure, mean arterial pressure, mean blood pressure, and mean proportional arterial pressure. Glucocorticoids (deoxycortisol and cortisol) increase the risk of hypertension in people with dysglycemia, particularly in those with T2DM.


Assuntos
Pressão Sanguínea , Glucocorticoides/sangue , Carga Glicêmica , Hidrocortisona/sangue , Hipertensão/epidemiologia , Adulto , Idoso , Idoso de 80 Anos ou mais , Estudos de Casos e Controles , China/epidemiologia , Estudos de Coortes , Feminino , Humanos , Hipertensão/etiologia , Masculino , Pessoa de Meia-Idade , Prevalência , Fatores de Risco , População Rural , Adulto Jovem
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