Conicity-index predicts all-cause mortality in Chinese older people: a 10-year community follow-up

Zhang, Anhang; Li, Yingnan; Ma, Shouyuan; Bao, Qiligeer; Sun, Jin; Cai, Shuang; Li, Man; Su, Yue; Cheng, Bokai; Dong, Jing; Zhang, Yan; Wang, Shuxia; Zhu, Ping

doi:10.1186/s12877-022-03664-6

Cited by 12 publications

(3 citation statements)

References 41 publications

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“…C‐index was calculated with the following formula 22 :

C - index = {0.109}^{- 1} WC (m) {([], \frac{weight (kg)}{height (normalm)})}^{- 1 / 2}

…”

Section: Methodsmentioning

confidence: 99%

Association between two novel anthropometric measures and type 2 diabetes in a Chinese population

Wang,

Chen,

et al. 2024

Diabetes Obesity Metabolism

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AimsTo investigate the associations of conicity index (C‐index) and relative fat mass (RFM) with incident type 2 diabetes mellitus (T2DM) among adults in China.Materials and MethodsA total of 10 813 participants aged over 18 years in Shenzhen Longhua district were enrolled in a follow‐up study conducted from 2018 to 2022. The participants were categorized based on quartiles (Q) of C‐index and RFM. The Cox proportional hazards model was performed to examine the relationships between C‐index, RFM and the risk of T2DM.ResultsAfter adjusting for potential confounding factors, including age, sex, occupation, marital status, education level, smoking status, alcohol consumption, physical exercise, hypertension status, fasting blood glucose (FBG) and total cholesterol (TC), both C‐index and RFM showed positive and independent associations with risk of T2DM. The multivariable‐adjusted hazard ratios (95% confidence intervals) for T2DM risk in participants in C‐index Q3 and Q4 compared with those in C‐index Q1 were 1.50 (1.12, 2.02) and 1.73 (1.29, 2.30), and 1.94 (1.44, 2.63), 3.18 (1.79, 5.64), 4.91 (2.68, 9.00) for participants in RFM Q2, Q3 and Q4 compared with RFM Q1. These differences were statistically significant (all p < 0.05).ConclusionC‐index and RFM are strongly associated with new‐onset T2DM and could be used to identify the risk of diabetes in large‐scale epidemiological studies.

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“…C‐index was calculated with the following formula 22 :

C - index = {0.109}^{- 1} WC (m) {([], \frac{weight (kg)}{height (normalm)})}^{- 1 / 2}

…”

Section: Methodsmentioning

confidence: 99%

Association between two novel anthropometric measures and type 2 diabetes in a Chinese population

Wang,

Chen,

et al. 2024

Diabetes Obesity Metabolism

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“…Guided by previous studies [ 26 , 27 , 28 , 29 ], we used the following formula for calculating the results of the various indices (AVI, BFP, BMI, CI, PI, RFM, WC, WHR, WHtR) to diagnose obesity and set cutoff values. The calculation formulas are listed in Table 1 .…”

Section: Methodsmentioning

confidence: 99%

The Efficacy of Anthropometric Indicators in Predicting Non-Alcoholic Fatty Liver Disease Using FibroScan® CAP Values among the Taiwanese Population

Lee,

Felipe-Dimog,

Yang

et al. 2023

Biomedicines

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The controlled attenuation parameter (CAP) measurement obtained from FibroScan® is a low-risk method of assessing fatty liver. This study investigated the association between the FibroScan® CAP values and nine anthropometric indicators, including the abdominal volume index (AVI), body fat percentage (BFP), body mass index (BMI), conicity index (CI), ponderal index (PI), relative fat mass (RFM), waist circumference (WC), waist–hip ratio (WHR), and waist-to-height ratio (WHtR), and risk of non-alcoholic fatty liver disease (fatty liver). We analyzed the medical records of adult patients who had FibroScan® CAP results. CAP values <238 dB/m were coded as 0 (non- fatty liver) and ≥238 dB/m as 1 (fatty liver). An individual is considered to have class 1 obesity when their body mass index (BMI) ranges from 30 kg/m2 to 34.9 kg/m2. Class 2 obesity is defined by a BMI ranging from 35 kg/m2 to 39.9 kg/m2, while class 3 obesity is designated by a BMI of 40 kg/m2 or higher. Out of 1763 subjects, 908 (51.5%) had fatty liver. The BMI, WHtR, and PI were found to be more strongly correlated with the CAP by the cluster dendrogram with correlation coefficients of 0.58, 0.54, and 0.54, respectively (all p < 0.0001). We found that 28.3% of the individuals without obesity had fatty liver, and 28.2% of the individuals with obesity did not have fatty liver. The BMI, CI, and PI were significant predictors of fatty liver. The BMI, PI, and WHtR demonstrated better predictive ability, indicated by AUC values of 0.72, 0.68, and 0.68, respectively, a finding that was echoed in our cluster group analysis that showed interconnected clustering with the CAP. Therefore, of the nine anthropometric indicators we studied, the BMI, CI, PI, and WHtR were found to be more effective in predicting the CAP score, i.e., fatty liver.

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“…It can be an indicator of early mortality. Nearly one-third of the world's population is now classified as overweight or obese (Zhang et al 2022).…”

Section: Introductionmentioning

confidence: 99%

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2023

T-ANTH

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Overweight and obesity is a medical condition in which abnormal or excess body fat has accumulated to an extreme that may harm health and reduce life expectancy. It may increase the risk of hypertension, diabetes mellitus, cardiovascular disease and musculoskeletal disorder.The investigation has been conducted to assess overweight and obesity and understand its relation with the morbidity pattern in traffic police personnel.The present investigation has been conducted in the Nagpur division among 277 traffic police personnel, including both male and female police personnel. Information has been collected through an interview schedule.The study shows that more than 50 percent of traffic police personnel are overweight, and 17 percent are obese. Between male and female traffic police personnel, there is a significant difference in BMI (ᵪ 2 =14.069, df=3, p=0.003). Forty percent of traffic police personnel suffer from musculoskeletal disorders, cardiovascular disease, and diabetes in 11 percent of traffic police personnel.

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Conicity-index predicts all-cause mortality in Chinese older people: a 10-year community follow-up

Cited by 12 publications

References 41 publications

Association between two novel anthropometric measures and type 2 diabetes in a Chinese population

Association between two novel anthropometric measures and type 2 diabetes in a Chinese population

The Efficacy of Anthropometric Indicators in Predicting Non-Alcoholic Fatty Liver Disease Using FibroScan® CAP Values among the Taiwanese Population

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