[Body mass index, waist circumference and waist-to-height ratio associated with the incidence of type 2 diabetes mellitus: a cohort study]

[Construction of a Predictive Model for Diabetes Mellitus Type 2 in Middle-Aged and Elderly Populations Based on the Medical Checkup Data of National Basic Public Health Service]

Objective

To establish a universally applicable logistic risk prediction model for diabetes mellitus type 2 (T2DM) in the middle-aged and elderly populations based on the results of a Meta-analysis, and to validate and confirm the efficacy of the model using the follow-up data of medical check-ups of National Basic Public Health Service.

Methods

Cohort studies evaluating T2DM risks were identified in Chinese and English databases. The logistic model utilized Meta-combined effect values such as the odds ratio (OR) to derive β, the partial regression coefficient, of the logistic model. The Meta-combined incidence rate of T2DM was used to obtain the parameter α of the logistic model. Validation of the predictive performance of the model was conducted with the follow-up data of medical checkups of National Basic Public Health Service. The follow-up data came from a community health center in Chengdu and were collected between 2017 and 2022 from 7602 individuals who did not have T2DM at their baseline medical checkups done at the community health center. This community health center was located in an urban-rural fringe area with a large population of middle-aged and elderly people.

Results

A total of 40 cohort studies were included and 10 items covered in the medical checkups of National Basic Public Health Service were identified in the Meta-analysis as statistically significant risk factors for T2DM, including age, central obesity, smoking, physical inactivity, impaired fasting glucose, a reduced level of high-density lipoprotein cholesterol (HDL-C), hypertension, body mass index (BMI), triglyceride glucose (TYG) index, and a family history of diabetes, with the OR values and 95% confidence interval (CI) being 1.04 (1.03, 1.05), 1.55 (1.29, 1.88), 1.36 (1.11, 1.66), 1.26 (1.07, 1.49), 3.93 (2.94, 5.24), 1.14 (1.06, 1.23), 1.47 (1.34, 1.61), 1.11 (1.05, 1.18), 2.15 (1.75, 2.62), and 1.66 (1.55, 1.78), respectively, and the combined β values being 0.039, 0.438, 0.307, 0.231, 1.369, 0.131, 0.385, 0.104, 0.765, and 0.507, respectively. A total of 37 studies reported the incidence rate, with the combined incidence being 0.08 (0.07, 0.09) and the parameter α being -2.442 for the logistic model. The logistic risk prediction model constructed based on Meta-analysis was externally validated with the data of 7602 individuals who had medical checkups and were followed up for at least once. External validation results showed that the predictive model had an area under curve (AUC) of 0.794 (0.771, 0.816), accuracy of 74.5%, sensitivity of 71.0%, and specificity of 74.7% in the 7602 individuals.

Conclusion

The T2DM risk prediction model based on Meta-analysis has good predictive performance and can be used as a practical tool for T2DM risk prediction in middle-aged and elderly populations.

Independent and Joint Associations of BMI and Waist Circumference With the Onset of Type 2 Diabetes Mellitus in Chinese Adults: Prospective Data Linkage Study

BACKGROUND

General obesity and abdominal obesity, typically measured by BMI and waist circumference (WC), respectively, are associated with an increased risk of type 2 diabetes mellitus (T2DM). However, the magnitude of the association of these two obesity indicators and their joint association with the onset of T2DM remain controversial.

OBJECTIVE

The aim of this study was to investigate the associations between these two obesity indicators and T2DM among the Chinese population to contribute scientific evidence for appropriate T2DM interventions.

METHODS

A cohort of 3001 eligible participants was selected from the Ningbo Adult Chronic Disease Surveillance Project running since 2015. Based on BMI, individuals were categorized into groups of underweight or normal, overweight, and obesity. Based on WC, individuals were categorized in groups of normal, precentral obesity, and central obesity. Follow-up was performed by linking data of the baseline data set with the diabetes registry data set and the vital registry data set (both from the Ningbo Municipal Integrated Noncommunicable Disease Collaborative Management System), mainly using the participants' identity numbers. Follow-up was completed when a participant was diagnosed with T2DM. The associations were estimated with multivariate Cox proportional hazard regression.

RESULTS

In the cohort, 90 of 3001 participants developed T2DM (incidence density: 6.483/1000 person-years) with a median 4.72 years of follow-up. After controlling for age, sex, hypertension, dyslipidemia, smoking status, and family history of diabetes, the multivariate adjusted hazard ratios (HRs) across underweight/normal, overweight, and obesity BMI categories were 1.000, 1.653 (95% CI 1.030-2.654), and 2.375 (95% CI 1.261-4.473), respectively. The multivariate adjusted HRs across the normal, precentral obesity, and central obesity WC categories were 1.000, 1.215 (95% CI 0.689-2.142), and 1.663 (95% CI 1.016-2.723), respectively. Compared with the reference group (normal WC with an underweight/normal BMI), the multivariate adjusted HR for participants with both central obesity according to WC and obesity according to BMI was 2.489 (95% CI 1.284-4.825).

CONCLUSIONS

Both elevated BMI and WC at baseline increased the risk of T2DM. Compared with WC, BMI as an obesity indicator was more strongly associated with the onset of T2DM.

Association between central obesity and incident diabetes mellitus among Japanese: a retrospective cohort study using propensity score matching

Previous evidence revealed that central obesity played a vital role in the development of diabetes mellitus (DM). However, because of imbalanced confounding variables, some studies have not wholly established the association between central obesity and diabetes. Propensity score matching (PSM) analysis can minimize the impact of potential confounding variables. Therefore, the aim of the present study was to explore the relationship between central obesity and diabetes in the Japanese population by using PSM analysis. This retrospective cohort study included 15,453 Japanese adults who were free of diabetes at baseline between 2004 and 2015, which provided all medical records for individuals participating in the physical exam. Central obesity at baseline was an independent variable, and incident diabetes during follow-up was an outcome variable. Using a 1:1 PSM analysis, the present retrospective cohort study included 1639 adults with and without central obesity. Additionally, we employed a doubly robust estimation method to identify the association between central obesity and diabetes. Subjects with central obesity were 92% more likely to develop DM (HR = 1.65, 95%CI 1.12, 2.41). After adjusting for covariates, subjects with central obesity had a 72% increased risk of developing DM compared with subjects with non-central obesity in the PSM cohort (HR = 1.72, 95% CI 1.16, 2.56). Central obesity individuals had a 91% higher risk of DM than non-central obesity individuals, after adjustment for propensity score (HR = 1.91, 95% CI 1.29, 2.81). In sensitivity analysis, the central obesity group had a 44% (HR = 1.44, 95% CI 1.09, 1.90) and 59% (HR = 1.59, 95% CI1.35, 1.88) higher risk of DM than the non-central obesity group in the original and weighted cohorts after adjusting for confounding variables, respectively. Central obesity was independently associated with an increased risk of developing diabetes. After adjustment for confounding covariates, central obesity participants had a 72% higher risk of development of diabetes than non-central obesity individuals in the PSM cohort.

Normalized Hand Grip and Back Muscle Strength as Risk Factors for Incident Type 2 Diabetes Mellitus: 16 Years of Follow-Up in a Population-Based Cohort Study

PURPOSE

Muscle strength is associated with type 2 diabetes mellitus (T2DM). However, it is controversial whether muscle strength and normalized muscle strength is a risk factor for T2DM. Moreover, the relationship of back muscle strength (BMS) and incident T2DM has not been reported. In this study, we investigated the relationship between HGS, BMS, normalized HGS and BMS, and incident T2DM.

METHODS

A total of 2699 non-diabetes subjects aged 40-69 years (1313 women and 1386 men) in the Korean Genome and Epidemiology Study (KoGES) Ansan cohort were followed for 16 years. At the baseline and biennial follow-up visits, fasting glucose, postprandial 2-h glucose, clinical examinations, HGS, and BMS were measured by trained interviewers and examiners. HGS and BMS were measured at baseline. The relationships between incident T2DM, HGS, BMS, and normalized HGS and BMS were estimated using Cox proportional hazard regression models after adjusting for the confounding factors.

RESULTS

HGS and BMS were not associated with incident T2DM in multivariate analysis. However, the hazard ratio (HR) per one standard deviation (SD) increase in the body mass index (BMI), waist circumference (WC), waist-hip ratio (WHR)-normalized HGS, and BMS was associated with a lower risk for incident T2DM in both women and men after adjusting for the confounding factors (HR = 0.842-0.880-fold for women, p ≤ 0.015; HR = 0.887-0.903-fold for men, p ≤ 0.024). In the sub-analysis of menopause status, the HR per one SD increase in BMI, weight^2/3, WC, and WHR-normalized HGS was associated with a lower risk for incident T2DM in both pre- and post-menopausal women after adjusting for the confounding factors (HR = 0.860-0.820-fold for premenopausal, P ≤ 0.006; HR = 0.900-0.867-fold for postmenopausal, p ≤ 0.024). Additionally, we confirmed that the quartile group with higher muscle strength was associated with a lower risk for incident T2DM.

CONCLUSION

The present study suggested that normalized HGS and BMS were associated with a lower risk for the future development of T2DM. Moreover, weak muscle strength in premenopausal women may be the cause of T2DM. Further research is needed to determine whether efforts to improve muscle strength, such as exercise can reduce the risk of T2DM.

Body Composition and the Components of Metabolic Syndrome in Type 2 Diabetes: The Roles of Disease Duration and Glycemic Control

PURPOSE

Data about body compositional changes throughout the course of type 2 diabetes (T2D) are limited and inconsistent. We investigated the roles of the disease duration and glycemic control in T2D-associated changes of body composition and the components of metabolic syndrome (MetS).

PATIENTS AND METHODS

A total of 25 non-diabetic controls and 92 individuals aged 20-60 years with T2D were included in a case-control study conducted at King Faisal Specialist Hospital, Saudi Arabia. Based on disease duration (newly diagnosed: within the first year and long duration: ≥5 years) and glycemic control (glycated hemoglobin [HbA1C] level ≤7%), the patients were divided into the following groups: newly diagnosed and controlled (N&C, n=25), newly diagnosed and uncontrolled (N&U, n=17), old and controlled (O&C, n=25), and old and uncontrolled (O&U, n=25). Blood samples were collected to assess fasting blood glucose level, HbA1C level, and lipid profile. Anthropometric data were evaluated, and body composition was assessed using a bio-impedancemetry analyzer. Nonparametric tests and multivariable logistic regression analyses were performed.

RESULTS

Compared to the control group, the fat mass (FM) was significantly higher in all groups; furthermore, the fat mass/fat-free mass (FM/FFM) ratio was significantly higher in the N&C. The N&U and O&U groups showed significantly higher percentages of all components of MetS. Among all selected independent factors, only age increased the likelihood of MetS diagnosis by 7% (OR: 1.07; 95% CI: 1.004-1.149; P<0.05). Besides, age, gender, adherence to diet regimen, and T2D duration showed lower odds of increased FM/FFM ratio.

CONCLUSION

This study provided evidence about the impact of T2D on body composition and the other components of MetS. Thus, further characterization of T2D contributes to defining the etiology of the disease to detect and treat poor cardiometabolic health.

Obesity- and Lipid-Related Parameters in the Identification of Older Adults with a High Risk of Prediabetes According to the American Diabetes Association: An Analysis of the 2015 Health, Well-Being, and Aging Study

This study evaluated the predictive ability of 11 obesity- and lipid-related parameters, including body mass index (BMI), waist circumference (WC), waist-to-height ratio (WtHR), body roundness index (BRI), "A" body-shape index (ABSI), conicity index (CI), visceral adiposity index (VAI), triglyceride-to-glucose fasting index (TyG), triglyceride-to-glucose fasting related to BMI (TyG-BMI), triglyceride-to-glucose fasting related to WC (TyG-WC), and triglyceride-to-glucose fasting related to WtHR (TyG-WtHR), to identify patients from an elderly Colombian population with a high risk of prediabetes according to the 2016 American Diabetes Association criteria. The data were obtained from the 2015 Colombian Health and Wellbeing and Aging Survey. A total of 3307 elderly Colombian individuals (aged over 60 years) were included. Anthropometric data, fasting plasma glucose, blood lipid profiles, family history, and health-related behaviors were assessed, and prediabetes was defined as a fasting plasma glucose of 100 to 125 mg/dL. The areas under the receiver operating characteristic (ROC) curves (AUCs) were calculated for each anthropometric indicator, using the prediabetes classification to identify their sensitivity and specificity, and these indicated that the prevalence of prediabetes was 25.3% in this population. After adjusting for potential confounding factors, the TyG index was strongly associated with the odds of having prediabetes in both sexes, and multivariate logistic regression analysis showed that the ORs for prediabetes increased across quartiles (p < 0.001). The TyG index was best able to identify prediabetes in either sex (AUC and optimal cut-off = 0.700 and 8.72, and 0.695 and 8.92 for men and women, respectively), suggesting that compared to the other parameters, the TyG index has the best discriminative power to predict prediabetes in the whole population. Thus, we propose the TyG index be used as a complementary marker for assessing prediabetes in older adults.

Waist-Stature Ratio And Its Relationship With Autonomic Recovery From Aerobic Exercise In Healthy Men

Autonomic modulation and cardiorespiratory variables are influenced by numerous factors, including anthropometric variables. We investigated autonomic recovery following aerobic exercise in healthy men with different waist-stature ratio (WSR) values. The study was conducted with 52 healthy men aged 18 to 30 years, divided into groups according to the WSR: G1 – between 0.40 and 0.449 (N = 19), G2 – between 0.45 and 0.50 (N = 28) and G3 – between 0.5 and 0.56 (N = 5). The subjects endured 15 minutes seated and at rest followed by an aerobic exercise and then remained seated for 60 minutes and at rest during recovery from exercise. Heart rate (HR) variability (HRV) (rMSSD, SD1, HF [ms²]) and cardiorespiratory variables were analyzed before and after exercise. Recovery of respiratory rate, diastolic blood pressure, SD1 and HF indices were delayed in G2. G3 presented delayed recovery after the maximal effort test while no difference with G2 was noted in the moderate intensity. Correlation and linear regression analysis indicated association of WSR, body mass index and waist circumference with HRV indices in the recovery from aerobic exercise (45 to 60 minutes after exercise) in G2. In conclusion, healthy men with higher WSR accomplished delayed autonomic recovery following maximal effort exercise.

Associations of General and Central Adiposity With Incident Diabetes in Chinese Men and Women

OBJECTIVE

We assess associations of general and central adiposity in middle age and of young adulthood adiposity with incident diabetes in adult Chinese and estimate the associated population burden of diabetes.

RESEARCH DESIGN AND METHODS

The prospective China Kadoorie Biobank enrolled 512,891 adults 30-79 years of age from 10 localities across China during 2004-2008. During 9.2 years of follow-up, 13,416 cases of diabetes were recorded among 482,589 participants without diabetes at baseline. Cox regression yielded adjusted hazard ratios (HRs) for incident diabetes associated with measures of general (e.g., BMI and BMI at 25 years) and central (e.g., waist circumference [WC]) adiposity.

RESULTS

The mean (SD) BMI was 23.6 kg/m² (3.4 kg/m²), and 3.8% had a BMI ≥30 kg/m². Throughout the range examined (19-32 kg/m²), BMI showed a positive log-linear relationship with diabetes, with adjusted HRs per SD higher usual BMI greater in men (1.98; 95% CI 1.93-2.04) than in women (1.77; 1.73-1.81) (P for heterogeneity <0.001). For WC, HRs per SD were 2.13 (95% CI 2.07-2.19) in men and 1.91 (1.87-1.95) in women (P for heterogeneity <0.001). Mutual adjustment attenuated these associations, especially those of BMI. BMI at age 25 years was weakly positively associated with diabetes (men HR 1.09 [95% CI 1.05-1.12]; women 1.04 [1.02-1.07] per SD), which was reversed after adjustment for baseline BMI. In China, the increase in adiposity accounted for ∼50% of the increase in diabetes burden since 1980.

CONCLUSIONS

Among relatively lean Chinese adults, higher adiposity-general and central-was strongly positively associated with the risk of incident diabetes. The predicted continuing increase in adiposity in China foreshadows escalating rates of diabetes.

Elevated incidence rates of diabetes in Peru: report from PERUDIAB, a national urban population-based longitudinal study

OBJECTIVE

A recent report from a non-nationally representative, geographically diverse sample in four separate communities in Peru suggests an unusually high diabetes incidence. We aimed to estimate the national diabetes incidence rate using PERUDIAB, a probabilistic, national urban population-based longitudinal study.

RESEARCH DESIGN AND METHODS

662 subjects without diabetes, selected by multistage, cluster, random sampling of households, representing the 24 administrative and the 3 (coast, highlands and jungle) natural regions across the country, from both sexes, aged 25+ years at baseline, enrolled in 2010-2012, were followed for 3.8 years. New diabetes cases were defined as fasting blood glucose ≥126 mg/dL or on medical diabetes treatment.

RESULTS

There were 49 cases of diabetes in 2408 person-years follow-up. The weighted cumulative incidence of diabetes was 7.2% while the weighted incidence rate was estimated at 19.5 (95% CI 13.9 to 28.3) new cases per 1000 person-years. Older age, obesity and technical or higher education were statistically associated with the incidence of diabetes.

CONCLUSION

Our results confirm that the incidence of diabetes in Peru is among the highest reported globally. The fast economic growth in the last 20 years, high overweight and obesity rates may have triggered this phenomenon.