Interaction Between Obesity and Hypertension on Arteriosclerosis in Chinese Urban Adults: A Population-Based Cross-Sectional Study

Li, Xiaohan; Yu, Junwu; Bai, Jianjuan; Huang, Huiming; Ying, Shanshan; Wang, Aiwen; Wang, Ping

doi:10.1177/10547738221120733

Cited by 3 publications

(2 citation statements)

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“…Obesity and hypertension, two major risk factors for CVD, contribute to global health and economic burdens (1,2,5,6,41). Given the dramatic increase in hypertension with the significant rise in obesity, early detection of hypertension using ORI screening could effectively prevent future hypertension and CVD risk.…”

Section: Discussionmentioning

confidence: 99%

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Comparison of 10 obesity-related indices for predicting hypertension based on ROC analysis in Chinese adults

Lee

Gao

Zhang

et al. 2022

Front. Public Health

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ObjectiveTo compare the predictive performance of the percentage body fat (PBF), body mass index (BMI), waist circumference (WC), hip circumference (HC), waist–hip ratio (WHR), waist–height ratio (WHtR), a body shape index (ABSI), body roundness index (BRI), abdominal volume index (AVI), and conicity index (CI) for identifying hypertension.MethodsA cross-sectional study was conducted among 2,801 adults (1,499 men and 1,302 women) aged 18 to 81 in Ningbo, China. The receiver operator characteristic (ROC) analysis and multiple non-parametric Z tests were used to compare the areas under the curve (AUC). The maximum Youden's indices were used to determine the optimal cut-off points of 10 obesity-related indices (ORI) for hypertension risk.ResultsThe AUC of all the indices were statistically significant (P < 0.05). The AUC of all the indices in men and women were 0.67–0.73 and 0.72–0.79, respectively. Further non-parametric Z tests showed that WHR had the highest AUC values in both men [0.73 (95% CI: 0.70, 0.76)] and women (0.79 (95% CI: 0.75, 0.83)], and several central ORI (men: WHR, WC, BRI, AVI, and CI, 0.71–0.73; women: WC, WHR, and AVI, 0.77–0.79) were higher than general ORI (PBF and BMI, 0.68 in men; 0.72–0.75 in women), with adjusted P < 0.05. The optimal cut-off points for identifying hypertension in men and women were as follows: PBF (23.55%, 32.55%), BMI (25.72 kg/m2, 23.46 kg/m2), HC (97.59 cm, 94.82 cm), WC (90.26 cm, 82.78 cm), WHR (0.91, 0.88), WHtR (0.51, 0.55), ABSI (0.08 m7/6/kg2/3, 0.08 m7/6/kg2/3), BRI (4.05, 4.32), AVI (16.31 cm2, 13.83 cm2), and CI (1.23 m2/3/kg1/2, 1.27 m2/3/kg1/2). Multivariate logistic regression models showed that all indices were statistically significant (P < 0.05) with the adjusted ORs (per 1-SD increase) at 1.39–2.06 and ORs (over the optimal cut-off points) at 1.80–2.64.ConclusionsAll 10 ORI (PBF, BMI, HC, WC, WHR, WHtR, ABSI, BRI, AVI, and CI) can effectively predict hypertension, among which WHR should be recommended as the best predictor. Central ORI (WHR, WC, and AVI) had a better predictive performance than general ORIs (PBF and BMI) when predicting the risk of hypertension.

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Section: Discussionmentioning

confidence: 99%

“…In regular clinical and epidemiological settings, baPWV is the most widely used measure of arteriosclerosis. Arteriosclerosis was defined by a baPWV ≥1400 cm/s (41). The smoking status was defined as smoking at least one cigarette per day continuously or cumulatively for 6 months (42).…”

Section: Indices Formula Referencementioning

confidence: 99%

Comparison of 10 obesity-related indices for predicting hypertension based on ROC analysis in Chinese adults

Lee

Gao

Zhang

et al. 2022

Front. Public Health

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Application of machine learning algorithms in predicting carotid artery plaques using routine health assessments

Wei,

Tao,

Geng

et al. 2024

Front. Cardiovasc. Med.

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BackgroundCardiovascular diseases (CVD) constitute a grave global health challenge, engendering significant socio-economic repercussions. Carotid artery plaques (CAP) are critical determinants of CVD risk, and proactive screening can substantially mitigate the frequency of cardiovascular incidents. However, the unequal distribution of medical resources precludes many patients from accessing carotid ultrasound diagnostics. Machine learning (ML) offers an effective screening alternative, delivering accurate predictions without the need for advanced diagnostic equipment. This study aimed to construct ML models that utilize routine health assessments and blood biomarkers to forecast the onset of CAP.MethodsIn this study, seven ML models, including LightGBM, LR, multi-layer perceptron (MLP), NBM, RF, SVM, and XGBoost, were used to construct the prediction model, and their performance in predicting the risk of CAP was compared. Data on health checkups and biochemical indicators were collected from 19,751 participants at the Beijing MJ Health Screening Center for model training and validation. Of these, 6,381 were diagnosed with CAP using carotid ultrasonography. In this study, 21 indicators were selected. The performance of the models was evaluated using the accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), F1 score, and area under the curve (AUC) value.ResultsAmong the seven ML models, the light gradient boosting machine (LightGBM) had the highest AUC value (85.4%). Moreover, age, systolic blood pressure (SBP), gender, low-density lipoprotein cholesterol (LDL-C), and total cholesterol (CHOL) were the top five predictors of carotid plaque formation.ConclusionsThis study demonstrated the feasibility of predicting carotid plaque risk using ML algorithms. ML offers effective tools for improving public health monitoring and risk assessment, with the potential to improve primary care and community health by identifying high-risk individuals and enabling proactive healthcare measures and resource optimization.

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Advances in the Synthesis and Physiological Metabolic Regulation of Nicotinamide Mononucleotide

Zheng,

Li,

et al. 2024

Nutrients

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Nicotinamide mononucleotide (NMN), the direct precursor of nicotinamide adenine dinucleotide (NAD+), is involved in the regulation of many physiological and metabolic reactions in the body. NMN can indirectly affect cellular metabolic pathways, DNA repair, and senescence, while also being essential for maintaining tissues and dynamic metabolic equilibria, promoting healthy aging. Therefore, NMN has found many applications in the food, pharmaceutical, and cosmetics industries. At present, NMN synthesis strategies mainly include chemical synthesis and biosynthesis. Despite its potential benefits, the commercial production of NMN by organic chemistry approaches faces environmental and safety problems. With the rapid development of synthetic biology, it has become possible to construct microbial cell factories to produce NMN in a cost-effective way. In this review, we summarize the chemical and biosynthetic strategies of NMN, offering an overview of the recent research progress on host selection, chassis cell optimization, mining of key enzymes, metabolic engineering, and adaptive fermentation strategies. In addition, we also review the advances in the role of NMN in aging, metabolic diseases, and neural function. This review provides comprehensive technical guidance for the efficient biosynthesis of NMN as well as a theoretical basis for its application in the fields of food, medicine, and cosmetics.

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Interaction Between Obesity and Hypertension on Arteriosclerosis in Chinese Urban Adults: A Population-Based Cross-Sectional Study

Cited by 3 publications

References 36 publications

Comparison of 10 obesity-related indices for predicting hypertension based on ROC analysis in Chinese adults

Comparison of 10 obesity-related indices for predicting hypertension based on ROC analysis in Chinese adults

Application of machine learning algorithms in predicting carotid artery plaques using routine health assessments

Advances in the Synthesis and Physiological Metabolic Regulation of Nicotinamide Mononucleotide

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