Anthropometric measures and glucose levels in a large multi-ethnic cohort of individuals at risk of developing type 2 diabetes

Assessing body composition through anthropometry: Implications for diagnosing and managing polycystic ovary syndrome (PCOS)

Polycystic ovary syndrome (PCOS) is a multifaceted endocrine disorder with profound implications for the reproductive and metabolic health of women. The utilization of anthropometric measures in the diagnosis and management of PCOS has gained increasing attention due to their practicality and predictive capacity for associated conditions such as obesity and insulin resistance. This review rigorously explores the application of various anthropometric indices, including body mass index, waist-to-hip ratio, and advanced metrics such as the body shape index and body roundness index, wrist circumference, neck circumference. These indices offer critical insights into body fat distribution and its association with the metabolic and hormonal perturbations characteristic of PCOS. The review underscores the necessity of addressing obesity, a prevalent comorbidity in PCOS, through lifestyle modifications and personalized therapeutic approaches. By incorporating anthropometric evaluations into routine clinical practice, healthcare professionals can enhance diagnostic precision, optimize treatment strategies, and ultimately improve patient outcomes. This integrative approach not only facilitates the management of the metabolic challenges inherent in PCOS but also contributes to the development of more individualized therapeutic interventions, thereby enhancing the overall quality of life for women affected by PCOS.

The role of peripheral white blood cell counts in the association between central adiposity and glycemic status

AIMS

Although central adiposity is a well-known risk factor for diabetes, the underlying mechanism remains unclear. The aim of this study was to explore the potential mediation role of circulating WBC counts in the association between central adiposity and the risk of diabetes.

MATERIALS AND METHODS

A cross-sectional study was conducted using data from the Fuqing cohort study, which included 6,613 participants aged 35-75 years. Logistic regression analysis and Spearman's rank correlation analysis were used to examine the relationships between waist-to-hip ratio, WBC counts and glycemic status. Both simple and parallel multiple mediation models were used to explore the potential mediation effects of WBCs on the association of waist-to-hip ratio with diabetes.

RESULTS

The study revealed a positive relationship between waist-to-hip ratio and risk of prediabetes (OR = 1.53; 95% CI, 1.35 to 1.74) and diabetes (OR = 2.89; 95% CI, 2.45 to 3.40). Moreover, elevated peripheral WBC counts were associated with both central adiposity and worsening glycemic status (P < 0.05). The mediation analysis with single mediators demonstrated that there is a significant indirect effect of central adiposity on prediabetes risk through total WBC count, neutrophil count, lymphocyte count, and monocyte count; the proportions mediated were 9.92%, 6.98%, 6.07%, and 3.84%, respectively. Additionally, total WBC count, neutrophil count, lymphocyte count, monocyte count and basophil count mediated 11.79%, 11.51%, 6.29%, 4.78%, and 1.76%, respectively, of the association between central adiposity and diabetes. In the parallel multiple mediation model using all five types of WBC as mediators simultaneously, a significant indirect effect (OR = 1.09; 95% CI, 1.06 to 1.14) were observed, with a mediated proportion of 12.77%.

CONCLUSIONS

Central adiposity was independently associated with an elevated risk of diabetes in a Chinese adult population; levels of circulating WBC may contribute to its underlying mechanisms.

Identifying top ten predictors of type 2 diabetes through machine learning analysis of UK Biobank data

The study aimed to identify the most predictive factors for the development of type 2 diabetes. Using an XGboost classification model, we projected type 2 diabetes incidence over a 10-year horizon. We deliberately minimized the selection of baseline factors to fully exploit the rich dataset from the UK Biobank. The predictive value of features was assessed using shap values, with model performance evaluated via Receiver Operating Characteristic Area Under the Curve, sensitivity, and specificity. Data from the UK Biobank, encompassing a vast population with comprehensive demographic and health data, was employed. The study enrolled 450,000 participants aged 40-69, excluding those with pre-existing diabetes. Among 448,277 participants, 12,148 developed type 2 diabetes within a decade. HbA1c emerged as the foremost predictor, followed by BMI, waist circumference, blood glucose, family history of diabetes, gamma-glutamyl transferase, waist-hip ratio, HDL cholesterol, age, and urate. Our XGboost model achieved a Receiver Operating Characteristic Area Under the Curve of 0.9 for 10-year type 2 diabetes prediction, with a reduced 10-feature model achieving 0.88. Easily measurable biological factors surpassed traditional risk factors like diet, physical activity, and socioeconomic status in predicting type 2 diabetes. Furthermore, high prediction accuracy could be maintained using just the top 10 biological factors, with additional ones offering marginal improvements. These findings underscore the significance of biological markers in type 2 diabetes prediction.

Proteomic Profiles of Body Mass Index and Waist-to-Hip Ratio and Their Role in Incidence of Diabetes

CONTEXT

It is unclear to what extent the plasma proteome of abdominal fat distribution differs from that of body mass index, and whether the differences have clinical implications.

OBJECTIVE

To evaluate the difference between the plasma proteomic profiles of body mass index (BMI) and waist-to-hip ratio (WHR), and then examine the identified BMI- or WHR-specific proteins in relation to incidence of diabetes.

METHODS

Data were obtained from the Malmö Diet and Cancer-Cardiovascular Cohort study in the general community. Participants (n = 4203) with no previous diabetes (aged 57.2 ± 6.0 years, 37.8% men) were included. Plasma proteins (n = 136) were measured by the Proseek proximity extension method. BMI- and WHR-specific proteins were identified at baseline using a 2-step iterative resampling approach to optimize internal replicability followed by β coefficient comparisons. The identified proteins were considered internally replicated and were then studied in relation to incident diabetes by Cox proportional hazards regression analysis. The main outcome measure was incident diabetes over a mean follow-up of 20.3 ± 5.9 years.

RESULTS

After excluding 21 overlapping proteins and proteins that did not show significantly different associations with BMI vs WHR, 10 internally replicated proteins were found to be specific to BMI, and 22 were found to be specific to WHR (false discovery rate-adjusted P < .05). Of the WHR-specific proteins, 18 remained associated with diabetes risk after multivariate adjustments, whereas none of the BMI-specific proteins showed associations with diabetes risk.

CONCLUSION

Abdominal fat distribution was associated with some unique characteristics of the plasma proteome that potentially could be related to its additional risk of diabetes beyond general obesity.

New metabolic health definition might not be a reliable predictor for diabetes in the nonobese Chinese population

AIM

To investigate the predictive values of the new metabolic health (MH) definition for future diabetes in a nonobese Chinese population, compared with the MH definition from metabolic syndrome (MetS).

METHODS

The data were collected in 1992 and then again in 2007 from the same group of 653 participants. The risk assessment of the new MH definition and the MH definition from MetS for future diabetes was performed by Cox regression analysis with overlap weighting as the primary analysis.

RESULTS

During the follow-up, 62 participants were diagnosed with diabetes. In the primary analysis with overlap weighting, there was no significant association between new MH and diabetes (HR: 1.12; 95% CI: 0.45-2.78, p = 0.803); conversely, based on the MH definition from MetS, the participants with MH were less likely to have had diabetes than the participants with MUHs (HR: 0.41; 95% CI: 0.22-0.78, p = 0.007). Furthermore, other analysis methods also confirmed the reproducibility of abovementioned results. In addition, sensitivity analysis excluding participants with prediabetes also demonstrated similar results with the primary analysis.

CONCLUSION

In contrast to the previous MH definition from MetS, the new MH definition was not a reliable predictor for future diabetes in the nonobese Chinese population.

The waist-hip ratio: a flawed index

The waist-hip ratio, namely waist circumference (WC) divided by hip circumference (HC), has been referred to in thousands of articles, generally as a correlate and predictor either of health conditions such as cardiovascular disease and diabetes, or of amounts of visceral and subcutaneous abdominal fat. It has been argued that combining WC and HC as a ratio is inappropriate, and yet their individual roles can only be fully elucidated if considered jointly. Whereas WC is positively associated with cardiovascular disease, diabetes and premature mortality, the opposite is true of HC. With health-related measures taken as dependent variables, the present novel approach establishes that WC and HC are far better treated as separate independent variables in multiple regression equations than as their ratio. This necessarily produces closer fits to data. One should then allow for variations in height, or some other such measure of general body size, by including this in the regression equations. The widespread concern with the ratio seems to have distracted attention from HC, for this is discussed notably less often than WC. Given that other body parts, such as the thighs, may share relevant properties with the hips, measurements of these could perhaps replace HC.

Predictive Values of Anthropometric Measurements for Cardiometabolic Risk Factors and Cardiovascular Diseases Among 44 048 Chinese

Background The predictive value of adiposity indices and the newly developed index for cardiometabolic risk factors and cardiovascular diseases (CVDs) remains unclear in the Chinese population. This study aimed to compare the predictive value of A Body Shape Index with other 5 conventional obesity-related anthropometric indices (body mass index, waist circumference, hip circumference, waist-to-hip ratio, waist-to-height ratio) in Chinese population. Methods and Results A total of 44 048 participants in the study were derived from the baseline data of the PURE-China (Prospective Urban and Rural Epidemiology) study in China. All participants' anthropometric parameters, CVDs, and risk factors (dyslipidemia, abnormal blood pressure, and hyperglycemia) were collected by standard procedures. Multivariable logistic regression models and receiver operator characteristic curve analysis were used to evaluate the predictive values of obesity-related anthropometric indices to the cardiometabolic risk factors and CVDs. A positive association was observed between each anthropometric index and cardiometabolic risk factors and CVDs in all models (P<0.001). Compared with other anthropometric indices (body mass index, waist circumference, hip circumference, waist-to-hip ratio, and A Body Shape Index), waist-to-height ratio had significantly higher areas under the curve (AUCs) for predicting dyslipidemia (AUCs: 0.646, sensitivity: 65%, specificity: 44%), hyperglycemia (AUCs: 0.595, sensitivity: 60%, specificity: 45%), and CVDs (AUCs: 0.619, sensitivity: 59%, specificity: 41%). Waist circumference showed the best prediction for abnormal blood pressure (AUCs: 0.671, sensitivity: 66%, specificity: 40%) compared with other anthropometric indices. However, the new body shape index did not show a better prediction to either cardiometabolic risk factors or CVDs than that of any other traditional obesity-related indices. Conclusions Waist-to-height ratio appeared to be the best indicator for dyslipidemia, hyperglycemia, and CVDs, while waist circumference had a better prediction for abnormal blood pressure.

Comparison of the association of predicted fat mass, body mass index, and other obesity indicators with type 2 diabetes risk: two large prospective studies in US men and women

Obesity, defined by body mass index (BMI), is a well-established risk factor of type 2 diabetes, but BMI has been criticized for its inability to discriminate fat mass and lean body mass. We examined the association between predicted fat mass and type 2 diabetes risk in two large US prospective cohorts, and compared the magnitude of the association with BMI and other obesity indicators. Validated anthropometric prediction equations previously developed from the National Health and Nutrition Examination Survey were used to estimate predicted fat mass and percent fat for 97,111 participants from the Health Professionals Follow-up Study (1987-2012) and the Nurses' Health Study (1986-2012) who were followed up for type 2 diabetes. Multivariable-adjusted hazard ratios for type 2 diabetes across quintiles of predicted fat mass were 1.00, 1.96, 2.96, 3.90, and 8.38 for men and 1.00, 2.20, 3.50, 5.73, and 12.1 for women; of BMI were 1.00, 1.69, 2.45, 3.54, and 6.94 for men and 1.00, 1.76, 2.86, 4.88, and 9.88 for women. Predicted FM showed the strongest association with type 2 diabetes in men followed by waist circumference (WC), waist-to-height ratio (WHtR), predicted percent fat, BMI, Waist-to-hip ratio (WHR), and a body shape index (ABSI). For women, the strongest association was shown for WHtR, followed by WC, predicted percent fat, predicted fat mass, BMI, ABSI, and WHR. Compared to BMI, predicted fat mass demonstrated consistently stronger association with type 2 diabetes risk. However, there was inconclusive evidence to suggest that predicted fat mass is substantially superior to other obesity indicators.

Diabetes and Impaired Fasting Glucose Prediction Using Anthropometric Indices in Adults from Maracaibo City, Venezuela

To determine the predictive power of various anthropometric indices for the identification of dysglycemic states in Maracaibo, Venezuela. A cross-sectional study with randomized, multi-staged sampling was realized in 2230 adult subjects of both genders who had their body mass index (BMI), waist circumference (WC) and waist-height ratio (WHR) determined. Diagnoses of type 2 diabetes mellitus (DM2) and impaired fasting glucose (IFG) were made following ADA 2015 criteria. ROC curves were used to evaluate the predictive power of each anthropometric parameter. Area under the curve (AUC) values were compared through Delong's test. Of the total 2230 individuals (52.6 % females), 8.4 % were found to have DM2, and 19.5 % had IFG. Anthropometric parameters displayed greater predictive power regarding newly diagnosed diabetics, where WHR was the most important predictor in both females (AUC = 0.808; CI 95 % 0.715-0.900. Sensitivity: 82.8 %; specificity: 76.2 %) and males (AUC = 0.809; CI 95 % 0.736-0.882. Sensitivity: 78.6 %; specificity: 68.1 %), although all three parameters appeared to have comparable predictive power in this subset. In previously diagnosed diabetic subjects, WHR was superior to both WC and BMI in females, and WHR and WC were both superior to BMI in males. Lower predictive values were found for IFG in both genders. Accumulation of various altered anthropometric measurements was associated with increased odds ratios for both newly and previously diagnosed DM2. The predictive power of anthropometric measurements was greater for DM2 than IFG. We suggest assessment of as many available parameters as possible in the clinical setting.

Recent progress in genetics, epigenetics and metagenomics unveils the pathophysiology of human obesity

In high-, middle- and low-income countries, the rising prevalence of obesity is the underlying cause of numerous health complications and increased mortality. Being a complex and heritable disorder, obesity results from the interplay between genetic susceptibility, epigenetics, metagenomics and the environment. Attempts at understanding the genetic basis of obesity have identified numerous genes associated with syndromic monogenic, non-syndromic monogenic, oligogenic and polygenic obesity. The genetics of leanness are also considered relevant as it mirrors some of obesity's aetiologies. In this report, we summarize ten genetically elucidated obesity syndromes, some of which are involved in ciliary functioning. We comprehensively review 11 monogenic obesity genes identified to date and their role in energy maintenance as part of the leptin-melanocortin pathway. With the emergence of genome-wide association studies over the last decade, 227 genetic variants involved in different biological pathways (central nervous system, food sensing and digestion, adipocyte differentiation, insulin signalling, lipid metabolism, muscle and liver biology, gut microbiota) have been associated with polygenic obesity. Advances in obligatory and facilitated epigenetic variation, and gene-environment interaction studies have partly accounted for the missing heritability of obesity and provided additional insight into its aetiology. The role of gut microbiota in obesity pathophysiology, as well as the 12 genes associated with lipodystrophies is discussed. Furthermore, in an attempt to improve future studies and merge the gap between research and clinical practice, we provide suggestions on how high-throughput '-omic' data can be integrated in order to get closer to the new age of personalized medicine.

The most important questions in cancer research and clinical oncology-Question 2-5. Obesity-related cancers: more questions than answers

Obesity is recognized as the second highest risk factor for cancer. The pathogenic mechanisms underlying tobacco-related cancers are well characterized and effective programs have led to a decline in smoking and related cancers, but there is a global epidemic of obesity without a clear understanding of how obesity causes cancer. Obesity is heterogeneous, and approximately 25% of obese individuals remain healthy (metabolically healthy obese, MHO), so which fat deposition (subcutaneous versus visceral, adipose versus ectopic) is "malignant"? What is the mechanism of carcinogenesis? Is it by metabolic dysregulation or chronic inflammation? Through which chemokines/genes/signaling pathways does adipose tissue influence carcinogenesis? Can selective inhibition of these pathways uncouple obesity from cancers? Do all obesity related cancers (ORCs) share a molecular signature? Are there common (over-lapping) genetic loci that make individuals susceptible to obesity, metabolic syndrome, and cancers? Can we identify precursor lesions of ORCs and will early intervention of high risk individuals alter the natural history? It appears unlikely that the obesity epidemic will be controlled anytime soon; answers to these questions will help to reduce the adverse effect of obesity on human condition.

The relationship between adipokines and the onset of type 2 diabetes in middle-aged men: The PRIME study

AIMS

Epidemiological evidence suggests that adipokines may be associated with the onset of type 2 diabetes, but the evidence to date is limited and inconclusive. This study examined the association between adiponectin and leptin and the subsequent diagnosis of type 2 diabetes in a UK population based cohort of non-diabetic middle-aged men.

METHODS

Baseline serum levels of leptin and adiponectin were measured in 1839 non-diabetic men aged 50-60years who were participating in the prospective population-based PRIME study. Over a mean follow-up of 14.7years, new cases of type 2 diabetes were determined from self-reported clinical information with subsequent validation by general practitioners.

RESULTS

151 Participants developed type 2 diabetes during follow-up. In Cox regression models adjusted for age, men in the top third of the leptin distribution were at increased risk (hazard ratio (HR) 4.27, 95% CI 2.67-6.83) and men in the top third of the adiponectin distribution at reduced risk (HR 0.24, 95% CI 0.14-0.42) relative to men in the bottom third. However, significance was lost for leptin after additional adjustment for BMI, waist to hip ratio, lifestyle factors and biological risk factors, including C-reactive protein (CRP). Further adjustment for HOMA-IR also resulted in loss of significance for adiponectin.

CONCLUSIONS

This study provides evidence that adipokines are associated with men's future type 2 diabetes risk but not independently of other risk factors.

Association of waist and hip circumference and waist-hip ratio with type 2 diabetes risk in first-degree relatives

AIMS

To evaluate the association of type 2 diabetes risk in first-degree relatives of diabetics with waist and hip circumference (WC and HC) and waist-hip ratio (WHR).

METHODS

We retrieved the data of 1319 subjects who had at least two visits during 2003-2010 and had been examined for diabetes status, WC and HC. Joint survival-longitudinal analysis and Cox regression were performed and the results were compared.

RESULTS

There was a significant direct relationship between diabetes risk and WC and WHR. The risk increased by 23% (95% CI: 5%-38%) and by 28% (95% CI: 9%-58%) respectively, for every 10cm increase in WC and 10% increase in WHR. Post-hoc subgroup analysis showed that these findings were present in females, but not in males. No significant association was seen for HC. Simple Cox regression showed direct association with WC and HC and no association with WHR.

CONCLUSIONS

In addition to dependence on measurement time, results from Cox model were inconclusive. The joint model showed a direct effect of WC and WHR albeit weaker than those in the general population, suggesting the possibility that factors other than the obesity indices are playing a stronger role in the elevated risk in this population. Multivariate models are needed for shedding light on the association.

From Genome-Wide Association Study to Phenome-Wide Association Study: New Paradigms in Obesity Research

Obesity is a condition in which excess body fat has accumulated over an extent that increases the risk of many chronic diseases. The current clinical classification of obesity is based on measurement of body mass index (BMI), waist-hip ratio, and body fat percentage. However, these measurements do not account for the wide individual variations in fat distribution, degree of fatness or health risks, and genetic variants identified in the genome-wide association studies (GWAS). In this review, we will address this important issue with the introduction of phenome, phenomics, and phenome-wide association study (PheWAS). We will discuss the new paradigm shift from GWAS to PheWAS in obesity research. In the era of precision medicine, phenomics and PheWAS provide the required approaches to better definition and classification of obesity according to the association of obese phenome with their unique molecular makeup, lifestyle, and environmental impact.

Physical activity, body composition and metabolic syndrome in young adults

OBJECTIVE

Low physical activity (PA) is a major risk factor for cardiovascular and metabolic disorders in all age groups. We measured intensity and volume of PA and examined the associations between PA and the metabolic syndrome (MS), its components and body composition among young Finnish adults.

RESEARCH DESIGN AND METHODS

The study comprises 991 men and women born 1985-86, who participated in a clinical study during the years 2009-11 which included assessments of metabolism, body composition and PA. Objectively measured (SenseWear Armband) five-day PA data was available from 737 participants and was expressed in metabolic equivalents of task (MET).

RESULTS

The prevalence of MS ranged between 8-10%. Higher total mean volume (MET-hours) or intensity (MET) were negatively associated with the risk of MS and separate components of MS, while the time spent at sedentary level of PA was positively associated with MS.

CONCLUSIONS

MS was prevalent in approximately every tenth of the young adults at the age of 24 years. Higher total mean intensity and volume rates as well as longer duration spent at moderate and vigorous PA level had a beneficial impact on the risk of MS. Longer time spent at the sedentary level of PA increased the risk of MS.

Multiple anthropometric measures in relation to incidence of diabetes: a Swedish population-based cohort study

BACKGROUND

Obesity is the major modifiable risk factor for diabetes. This study investigated the incidence of diabetes in relation to multiple anthropometric measures.

METHODS

Body mass index (BMI), waist circumference (WC), waist-height ratio (WHtR), waist-hip ratio (WHR) and body fat percentage (BF %) were measured among 26,604 subjects (aged 45-73 years) without history of diabetes from the Malmö Diet and Cancer cohort.

RESULTS

During 14 years of follow-up, 2935 subjects (1519 men, 1416 women) were diagnosed with diabetes. In men, incidence of diabetes was 24.1 and 4.0 per 1000 person-years comparing the fourth vs. first quartile of WHtR. The multivariate adjusted hazard ratios (HR; fourth vs first quartile) were 6.00 [95% confidence interval (CI): 5.02-7.16) for WHtR, 5.95 (CI: 4.96-7.14) for WC, 5.19 (CI: 4.38-6.15) for BMI, 4.71 (CI: 3.96-5.60) for WHR and 3.21 (CI: 2.75-3.76] for BF%. For women, incidence of diabetes was 15.1 and 1.4 per 1000 person-years for fourth vs first quartile of WHtR (HR: 10.19, CI: 8.10-12.82). HR was 9.16 (CI: 7.40-11.33) for WC, 6.42 (CI: 5.27-7.81) for BMI, 6.75 (CI: 5.52-8.25) for WHR and 5.39 (CI: 4.42-6.57) for BF%. Model discrimination was marginally increased when WC, WHtR or WHR was used in combination with BMI.

CONCLUSION

All measures of obesity were associated with substantially increased incidence of diabetes. Abdominal obesity was associated with higher incidence rates in men than in women, but in terms of relative risks the relationships were stronger in women. The combination of BMI and abdominal obesity measures had stronger association with diabetes than BMI alone.

Contribution of common non-synonymous variants in PCSK1 to body mass index variation and risk of obesity: a systematic review and meta-analysis with evidence from up to 331 175 individuals

Polymorphisms rs6232 and rs6234/rs6235 in PCSK1 have been associated with extreme obesity [e.g. body mass index (BMI) ≥ 40 kg/m(2)], but their contribution to common obesity (BMI ≥ 30 kg/m(2)) and BMI variation in a multi-ethnic context is unclear. To fill this gap, we collected phenotypic and genetic data in up to 331 175 individuals from diverse ethnic groups. This process involved a systematic review of the literature in PubMed, Web of Science, Embase and the NIH GWAS catalog complemented by data extraction from pre-existing GWAS or custom-arrays in consortia and single studies. We employed recently developed global meta-analytic random-effects methods to calculate summary odds ratios (OR) and 95% confidence intervals (CIs) or beta estimates and standard errors (SE) for the obesity status and BMI analyses, respectively. Significant associations were found with binary obesity status for rs6232 (OR = 1.15, 95% CI 1.06-1.24, P = 6.08 × 10(-6)) and rs6234/rs6235 (OR = 1.07, 95% CI 1.04-1.10, P = 3.00 × 10(-7)). Similarly, significant associations were found with continuous BMI for rs6232 (β = 0.03, 95% CI 0.00-0.07; P = 0.047) and rs6234/rs6235 (β = 0.02, 95% CI 0.00-0.03; P = 5.57 × 10(-4)). Ethnicity, age and study ascertainment significantly modulated the association of PCSK1 polymorphisms with obesity. In summary, we demonstrate evidence that common gene variation in PCSK1 contributes to BMI variation and susceptibility to common obesity in the largest known meta-analysis published to date in genetic epidemiology.

Blood pressure in relation to general and central adiposity among 500 000 adult Chinese men and women

Background: Greater adiposity is associated with higher blood pressure. Substantial uncertainty remains, however, about which measures of adiposity most strongly predict blood pressure and whether these associations differ materially between populations.

Methods: We examined cross-sectional data on 500 000 adults recruited from 10 diverse localities across China during 2004–08. Multiple linear regression was used to estimate the effects on systolic blood pressure (SBP) of general adiposity [e.g. body mass index (BMI), body fat percentage, height-adjusted weight] vs central adiposity [e.g. waist circumference (WC), hip circumference (HC), waist-hip ratio (WHR)], before and after adjustment for each other. The main analyses excluded those reported taking any antihypertensive medication, and were adjusted for age, region and education.

Results: The overall mean [standard deviation (SD)] BMI was 23.6 (3.3) kg/m² and mean WC was 80.0 (9.5) cm. The differences in SBP (men/women, mmHg) per 1SD higher general adiposity (height-adjusted weight: 6.6/5.6; BMI: 5.5/4.9; body fat percentage: 5.5/5.0) were greater than for central adiposity (WC: 5.0/4.3; HC: 4.8/4.1; WHR: 3.7/3.2), with a 10 kg/m² greater BMI being associated on average with 16 (men/women: 17/14) mmHg higher SBP. The associations of blood pressure with measures of general adiposity were not materially altered by adjusting for WC and HC, but those for central adiposity were significantly attenuated after adjusting for BMI (WC: 1.1/0.7; HC: 0.3/−0.2; WHR: 0.6/0.6).

Conclusion: In adult Chinese, blood pressure is more strongly associated with general adiposity than with central adiposity, and the associations with BMI were about 50% stronger than those observed in Western populations.

Identification of Type 2 Diabetes Risk Factors Using Phenotypes Consisting of Anthropometry and Triglycerides based on Machine Learning

The hypertriglyceridemic waist (HW) phenotype is strongly associated with type 2 diabetes; however, to date, no study has assessed the predictive power of phenotypes based on individual anthropometric measurements and triglyceride (TG) levels. The aims of the present study were to assess the association between the HW phenotype and type 2 diabetes in Korean adults and to evaluate the predictive power of various phenotypes consisting of combinations of individual anthropometric measurements and TG levels. Between November 2006 and August 2013, 11,937 subjects participated in this retrospective cross-sectional study. We measured fasting plasma glucose and TG levels and performed anthropometric measurements. We employed binary logistic regression (LR) to examine statistically significant differences between normal subjects and those with type 2 diabetes using HW and individual anthropometric measurements. For more reliable prediction results, two machine learning algorithms, naive Bayes (NB) and LR, were used to evaluate the predictive power of various phenotypes. All prediction experiments were performed using a tenfold cross validation method. Among all of the variables, the presence of HW was most strongly associated with type 2 diabetes (p < 0.001, adjusted odds ratio (OR) = 2.07 [95% CI, 1.72-2.49] in men; p < 0.001, adjusted OR = 2.09 [1.79-2.45] in women). When comparing waist circumference (WC) and TG levels as components of the HW phenotype, the association between WC and type 2 diabetes was greater than the association between TG and type 2 diabetes. The phenotypes tended to have higher predictive power in women than in men. Among the phenotypes, the best predictors of type 2 diabetes were waist-to-hip ratio + TG in men (AUC by NB = 0.653, AUC by LR = 0.661) and rib-to-hip ratio + TG in women (AUC by NB = 0.73, AUC by LR = 0.735). Although the presence of HW demonstrated the strongest association with type 2 diabetes, the predictive power of the combined measurements of the actual WC and TG values may not be the best manner of predicting type 2 diabetes. Our findings may provide clinical information concerning the development of clinical decision support systems for the initial screening of type 2 diabetes.

Combined use of waist and hip circumference to identify abdominally obese HIV-infected patients at increased health risk

OBJECTIVES

To determine whether for a given waist circumference (WC), a larger hip circumference (HC) was associated with a reduced risk of insulin resistance, type 2 diabetes (T2D), hypertension and cardiovascular disease (CVD) in HIV-infected patients. A second objective was to determine whether, for a given WC, the addition of HC improved upon estimates of abdominal adiposity, in particular visceral adipose tissue (VAT), compared to those obtained by WC alone.

METHODS

HIV-infected men (N = 1481) and women (N = 841) were recruited between 2005 and 2009. WC and HC were obtained using standard techniques and abdominal adiposity was measured using computed tomography.

RESULTS

After control for WC and covariates, HC was negatively associated with risk of insulin resistance (p<0.05) and T2D [Men: OR = 0.91 (95% CI: 0.86-0.96); Women: OR = 0.91 (95% CI: 0.84-0.98)]. For a given WC, HC was also negatively associated with a lower risk of hypertension (p<0.05) and CVD [OR = 0.94 (95% CI: 0.88-0.99)] in men, but not women. Although HC was negatively associated with VAT in men and women after control for WC (p<0.05), the addition of HC did not substantially improve upon the prediction of VAT compared to WC alone.

CONCLUSIONS

The identification of HIV-infected individuals at increased health risk by WC alone is substantially improved by the addition of HC. Estimates of visceral adipose tissue by WC are not substantially improved by the addition of HC and thus variation in visceral adiposity may not be the conduit by which HC identifies increased health risk.

A systematic review of the impact of including both waist and hip circumference in risk models for cardiovascular diseases, diabetes and mortality

Both a larger waist and narrow hips are associated with heightened risk of diabetes, cardiovascular diseases and premature mortality. We review the risk of these outcomes for levels of waist and hip circumferences when terms for both anthropometric measures were included in regression models. MEDLINE and EMBASE were searched (last updated July 2012) for studies reporting the association with the outcomes mentioned earlier for both waist and hip circumferences (unadjusted and with both terms included in the model). Ten studies reported the association between hip circumference and death and/or disease outcomes both unadjusted and adjusted for waist circumference. Five studies reported the risk associated with waist circumference both unadjusted and adjusted for hip circumference. With the exception of one study of venous thromboembolism, the full strength of the association between either waist circumference or hip circumference with morbidity and/or mortality was only apparent when terms for both anthropometric measures were included in regression models. Without accounting for the protective effect of hip circumference, the effect of obesity on risk of death and disease may be seriously underestimated. Considered together (but not as a ratio measure), waist and hip circumference may improve risk prediction models for cardiovascular disease and other outcomes.

Comparisons of the strength of associations with future type 2 diabetes risk among anthropometric obesity indicators, including waist-to-height ratio: a meta-analysis

The aim of this meta-analysis was to compare the association of waist-to-height ratio (WHtR) with risk of incident diabetes with the associations of 3 other conventional obesity indicators (body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR)) with risk of incident diabetes. Literature searches in MEDLINE (January 1950 to April 27, 2011) and EMBASE (January 1974 to April 27, 2011) were conducted for prospective studies that made it possible to estimate the relative risk of diabetes per 1-standard deviation increase in WHtR, in addition to the RR of BMI, WC, or WHR. Strength of the estimated pooled relative risk for a 1-standard deviation increase of each indicator (expressed as RR(WHtR), RR(BMI), RR(WC), and RR(WHR)) was compared with a bivariate random-effects model. Pooled relative risks of the 15 eligible studies with 6,472 diabetes cases were 1.62 (95% CI: 1.48, 1.78) for RR(WHtR), 1.55 (95% CI: 1.43, 1.69) for RR(BMI), 1.63 (95% CI: 1.49, 1.79) for RR(WC), and 1.52 (95% CI: 1.40, 1.66) for RR(WHR). WHtR had an association stronger than that of BMI (P<0.001) or WHR (P<0.001). The present meta-analysis showed that WHtR has a modestly but statistically greater importance than BMI and WHR in prediction of diabetes. Nevertheless, measuring height in addition to WC appeared to have no additional benefit.

BMI is strongly associated with hypertension, and waist circumference is strongly associated with type 2 diabetes and dyslipidemia, in northern Chinese adults

Background

Obesity is closely associated with chronic diseases such as hypertension, type 2 diabetes mellitus (T2DM), and dyslipidemia. We analyzed the optimal obesity index cut-off values for metabolic syndrome (MetS), and identified the obesity index that is more closely associated with these chronic diseases, in a population of northern Chinese.

Methods

We surveyed 8940 adults (age, 20–74 years) living in northern China for chronic diseases. Receiver operating characteristics (ROC) analysis, relative risk, and multivariate regression were used to develop an appropriate index and optimal cut-off values for MetS and obesity-related chronic diseases.

Results

Waist circumference (WC) and body mass index (BMI) were good markers for MetS, WC was a good marker for T2DM and dyslipidemia, and BMI was a good marker for hypertension. The optimal BMI cut-off value of MetS was 24 kg/m², and the optimal WC cut-offs were 86 cm and 78 cm in men and women, respectively. Relative risk regression models showed that BMI was associated with hypertension, T2DM, and hypertriglyceridemia and a higher prevalence ratio (PR) for hypertension: 2.35 (95% CI, 2.18–2.50). WC was associated with T2DM, hypertension, and hypertriglyceridemia, with PRs of 2.05 (1.63–2.55) for T2DM and 2.47 (2.04–2.85) for hypertriglyceridemia. In multivariate regression models, the standardized regression coefficients (SRCs) of BMI were greater for SBP and DBP, and the SRC of WC was greater for fasting blood glucose, 2-hour postload blood glucose, triglyceride, and total cholesterol.

Conclusions

Our analysis of a population of northern Chinese indicates that the optimal cut-off values for MetS are WCs of 86 cm in men and 78 cm in women and a BMI of 24 kg/m² in both sexes. BMI was strongly associated with hypertension, while WC was strongly associated with T2DM and dyslipidemia.

The influence of hip circumference on the relationship between abdominal obesity and mortality

BACKGROUND

Higher waist circumference and lower hip circumference are both associated with increased cardiovascular disease (CVD) risk, despite being directly correlated. The real effects of visceral obesity may therefore be underestimated when hip circumference is not fully taken into account. We hypothesized that adding waist and hip circumference to traditional risk factors would significantly improve CVD risk prediction.

METHODS

In a population-based survey among South Asian and African Mauritians (n = 7978), 1241 deaths occurred during 15 years of follow-up. In a model that included variables used in previous CVD risk calculations (a Framingham-type model), the association between waist circumference and mortality was examined before and after adjustment for hip circumference. The percentage with an increase in estimated 10-year cumulative mortality of >25% and a decrease of >20% after waist and hip circumference were added to the model was calculated.

RESULTS

Waist circumference was strongly related to mortality only after adjustment for hip circumference and vice versa. Adding waist and hip circumference to a Framingham-type model increased estimated 10-year cumulative CVD mortality by >25% for 23.7% of those who died and 15.7% of those censored. Cumulative mortality decreased by >20% for 4.5% of those who died and 14.8% of those censored.

CONCLUSIONS

The effect of central obesity on mortality risk is seriously underestimated without adjustment for hip circumference. Adding waist and hip circumference to a Framingham-type model for CVD mortality substantially increased predictive power. Both may be important inclusions in CVD risk prediction models.

Adiponectin in relation to insulin sensitivity and insulin secretion in the development of type 2 diabetes: a prospective study in 64-year-old women

OBJECTIVES

To examine how serum adiponectin levels predict the incidence of type 2 diabetes, from different prediabetic states, in relation to insulin sensitivity and β-cell function during 5.5 years of follow-up.

METHODS

In a population-based cohort of 64-year-old Caucasian women, we assessed glucose tolerance, insulin sensitivity as homeostasis model assessment, insulin secretion as acute insulin response, lifestyle factors and serum concentrations of adiponectin and high-sensitivity C-reactive protein. After 5.5 years of follow-up, 167 women with normal glucose tolerance (NGT) and 174 with impaired glucose tolerance (IGT) at baseline were re-examined and incidence of diabetes was assessed.

RESULTS

A total of 69 new cases of diabetes were detected during follow-up. Diabetes incidence was independently predicted by low levels of serum adiponectin, insulin resistance and insulin secretion, cigarette smoking, impaired fasting glucose (IFG) and IGT at baseline. Serum adiponectin below 11.54 g L(-1) was associated with an odds ratio of 3.6 (95% confidence interval 1.4-8.6) for future type 2 diabetes. At baseline, a high serum adiponectin concentration correlated positively with high levels of insulin sensitivity and insulin secretion. Women with incident diabetes had lower serum adiponectin levels in the NGT, IFG and IGT groups at baseline compared to those who did not develop diabetes during follow-up.

CONCLUSIONS

Low adiponectin concentrations were associated with future diabetes independently of insulin secretion and sensitivity, as well as IGT, IFG, smoking and abdominal obesity.