Association between Body Mass Index and Stroke Risk Among Patients with Type 2 Diabetes

Association of novel lipid indicators with the risk of stroke among participants in Central China: a population-based prospective study

Background

Several easily and inexpensively measured indicators of visceral adiposity dysfunction are currently available, but it remains unclear whether they are correlated with stroke risk in the community-dwelling population. We aimed to examine the longitudinal association of the triglyceridemic-waist phenotypes, the triglyceride glucose (TyG) index, as well as TyG-related indicators with stroke risk.

Methods

In this study, we conducted a prospective cohort study in Hunan, a region located in Central China, where the prevalence of stroke is relatively high. We included a total of 20185 subjects aged ≥40 years between November 2017 and December 2018. Triglyceride glucose-body mass index (TyG-BMI) and triglyceride glucose-waist circumference (TyG-WC) were calculated as multiplying TyG index by BMI and WC, respectively. Triglyceride waist phenotypes were categorized into four phenotypes: HTGW (elevated triglyceride and enlarged WC), NTNW (normal triglyceride and normal WC); HTNW (high triglyceride and normal WC), and NTGW (normal triglyceride and enlarged WC). We constructed a multivariable Cox regression model to assess the association between these novel lipid indicators and the risk of stroke. Subgroup analysis was conducted to test the robustness of our research findings. ROC curve was used for assessing the predictive ability of different stroke risk indices.

Results

After 2 years of follow- up, 135 participants experienced new stroke events. After adjusting for potential confounders, we found that participants with HTGW had higher likelihood of stroke (HR: 1.96, 95% CI: 1.21 to 3.16). However, we did not find significant associations for HTNW (HR: 1.42, 95% CI: 0.91 to 2.21) and NTGW (HR: 1.09, 95% CI 0.67 to 1.78). when compared to participants in the first TyG quartile, those in the fourth TyG quartile were associated with a 2.06-fold (95% CI: 1.22, 3.50) risk of stroke. Each 1-SD increase in TyG, TyG-BMI, and TyG-WC was associated with a higher risk of stroke, with adjusted HRs of 1.34 (95% CI: 1.11 to 1.61), 1.35 (95% CI: 1.14 to 1.59), and 1.23 (95% CI: 1.04 to 1.46), respectively. In subgroup analyses, those positive relationships appeared to be stronger among male participants with lower levels of physical activity and smoking.

Conclusion

HTGW, along with higher levels of TyG and TyG-related indicators, were found to be associated with an elevated risk of stroke. HTGW and these novel lipid indicators might be reliable indicators to identify populations at elevated risk of stroke.

Non-linear dose-response relationship between body mass index and stroke risk in middle-aged and elderly Chinese men: a nationwide Longitudinal Cohort Study from CHARLS

Objective

Body mass index (BMI) and stroke risk have been linked, but these findings are still debated. This study investigated the relationship between BMI and stroke risk in a middle-aged and elderly Chinese population.

Methods

This study used four waves of CHARLS data (2011, 2013, 2015, and 2018), including 12,161 participants. The CHARLS sample was obtained by multi-stage probability sampling and all participants were assessed by one-to-one interviews using a standardized questionnaire. We used a Cox proportional-hazards regression model to examine the relationship between BMI and stroke risk. We used Cox proportional hazards regression with cubic spline functions and smooth curve fitting to identify the non-linear relationship between them. A series of sensitivity analyses were also conducted.

Results

The multivariate Cox proportional hazards regression model identified a positive association between BMI and stroke risk (HR=1.025, 95% CI: 1.010-1.040). We also found a non-linear relationship between BMI and stroke incidence, with an inflection point at 26.63 kg/m2 for BMI. Each 1 kg/m2 increase in BMI to the left of the inflection point was related to a 4.4% increase in stroke risk (HR=1.044, 95% CI: 1.019-1.069). We stratified individuals by gender to further investigate their association and found a particular non-linear relationship and saturation effect between BMI and stroke risk in men, with the inflection point at 25.94 kg/m2. Each 1 kg/m2 increase in BMI to the left of the inflection point was related to a 7.6% increase in stroke risk (HR=1.076, 95% CI 1.034-1.119). The association was linear in women, with each 1 kg/m2 increase in BMI associated with a 2.1% increase in stroke risk (HR=1.021, 95% CI 1.002, 1.040).

Conclusion

In men, there was a specific non-linear association and saturation effect of BMI with stroke (inflection point of 25.94 kg/m2), while in women, there was none. When males had a BMI below 25.94 kg/m2, the risk of stroke was significantly and positively associated with BMI. By controlling BMI below 25.94 kg/m2 in men, a further decrease in BMI may promote a significant reduction in stroke risk.

Trends in obesity prevalence and cardiometabolic risk factor control in US adults with diabetes, 1999-2020

OBJECTIVE

Trends in obesity prevalence and trends in control of cardiometabolic risk factors among National Health and Nutrition Examination Survey participants with diabetes from 1999 through 2020 were analyzed.

METHODS

Adults who were 20 years or older and who reported having received a diagnosis of diabetes from a physician were included.

RESULTS

The prevalence of overall obesity, obesity class II, and obesity class III increased from 46.9%, 14.1%, and 10.3% in 1999 to 2002 to 58.1%, 16.6%, and 14.8% in 2015 to 2020, respectively. The prevalence of participants who achieved glycemic control (HbA1c <7%) increased from 42.5% in 1999 to 2002 to 51.8% in 2007 to 2010, then decreased to 48.0% in 2015 to 2020. The prevalence of participants who achieved blood pressure control (<140/90 mmHg) or achieved non-high-density lipoprotein cholesterol control (<130 mg/dL) increased throughout the study periods. The prevalence of participants who met all three risk factor goals increased from 8.3% in 1999 to 2002 to 21.2% in 2011 to 2014 and then decreased to 18.5 in 2015 to 2020. Participants with obesity showed worsening glycemic control and lipid control than participants with normal weight.

CONCLUSIONS

There were increasing trends in prevalence of obesity, blood pressure control, and lipid control from 1999 to 2002 to 2015 to 2020. Participants with obesity showed worsening glycemic control and lipid control than normal-weight participants.

Effects of a Lifestyle Intervention in Young Women with GDM and Subsequent Diabetes

The purpose of this study was to examine whether a 9-month intensive lifestyle intervention could lead to weight loss and improve cardiovascular risk factors among young women with both gestational diabetes mellitus (GDM) and newly diagnosed diabetes. A total of 83 young women, who had GDM and were subsequently diagnosed as type 2 diabetes at an average of 2.6 years after delivery, participated in a 9-month intensive lifestyle intervention and a follow-up survey at 6-9 years postintervention. After the 9-month intervention, these women had a weight loss of 2.90 kg (-4.02% of initial weight), decreased waist circumference (-3.12 cm), body fat (-1.75%), diastolic blood pressure (-3.49 mmHg), fasting glucose (-0.98 mmol/L) and HbA1c (-0.72%). During the 6-9 years postintervention period, they still had lower weight (-3.71 kg; -4.62% of initial weight), decreased waist circumference (-4.56 cm) and body fat (-2.10%), but showed a slight increase in HbA1c (0.22%). The prevalence of using glucose-lowering agents increased from 2.4% at baseline to 34.6% after the 9-month lifestyle intervention, and to 48.4% at 6-9 years postintervention. A 9-month intensive lifestyle intervention can produce beneficial effects on body weight, HbA1c and other cardiovascular risk factors among young women with previous GDM who subsequently developed new diabetes.

Association between abdominal obesity indices and risk of cardiovascular events in Chinese populations with type 2 diabetes: a prospective cohort study

BACKGROUND

Waist circumference (WC), visceral adiposity index (VAI), lipid accumulation product (LAP), and Chinese visceral adiposity index (CVAI) are considered surrogate indicators of abdominal fat deposition, but the longitudinal association of these indices with cardiovascular (CV) events in adults with type 2 diabetes (T2D) remains unclear. Our study aimed to examine the associations between abdominal obesity indices and incident CV events among people with T2D and to compare their predictive performance in risk assessment.

METHODS

The present study included 2328 individuals with T2D from the Xinjiang Multi-Ethnic Cohort. Multivariable Cox regression analyses were applied to assess the associations between abdominal obesity indices and CV events. Harrell's concordance statistic (C-statistic), net reclassification improvement (NRI) index, and integrated discrimination improvement (IDI) index were utilized to evaluate the predictive performance of each abdominal obesity index.

RESULTS

At a median follow-up period of 59 months, 289 participants experienced CV events. After multivariable adjustment, each 1-SD increase in WC, VAI, LAP, and CVAI was associated with a higher risk of CV events in people with T2D, with adjusted hazard ratios (HRs) being 1.57 [95% CI (confidence interval): 1.39-1.78], 1.11 (95% CI 1.06-1.16), 1.46 (95% CI 1.36-1.57), and 1.78 (95% CI 1.57-2.01), respectively. In subgroup analyses, these positive associations appeared to be stronger among participants with body mass index (BMI) < 25 kg/m² compared to overweight/obese participants. As for the predictive performance, CVAI had the largest C-statistic (0.700, 95% CI 0.672-0.728) compared to VAI, LAP, WC, and BMI (C-statistic: 0.535 to 0.670, all P for comparison < 0.05). When the abdominal obesity index was added to the basic risk model, the CVAI index also showed the greatest incremental risk stratification (C-statistic: 0.751 vs. 0.701, P < 0.001; IDI: 4.3%, P < 0.001; NRI: 26.6%, P < 0.001).

CONCLUSIONS

This study provided additional evidence that all abdominal obesity indices were associated with the risk of CV events and highlighted that CVAI might be a valuable abdominal obesity indicator for identifying the high risk of CV events in Chinese populations with T2D. These results suggest that proactive assessment of abdominal obesity could be helpful for the effective clinical management of the diabetic population.

Body mass index and stroke risk among patients with diabetes mellitus in Korea

Background

Obesity and diabetes mellitus (DM) are both associated with cardiovascular disease. This study aimed to evaluate the association between body mass index (BMI) and stroke risk among patients with DM in Korea since relatively few studies have analyzed this area in detail.

Methods

We analyzed a total of 56,051 DM patients aged >30 years from the Korean National Health Insurance Service Cohort who had undergone at least one national health examination between 2002 and 2012. BMI scores were divided into six categories, while hazard ratios for stroke were calculated using Cox proportional hazard models.

Results

Overall stroke risk was positively associated with BMI for both men and women. For ischemic stroke, the risk was positively associated with BMI in women. However, for me, only patients with the highest BMI were at increased risk compared with patients with a BMI of 20–22.4 kg/m². For hemorrhagic stroke, the risk was significantly associated with BMI with a U-shaped association in men. In women, only patients with the lowest BMI had an increased risk of hemorrhagic stroke compared with patients that have a BMI of 20–22.4 kg/m².

Conclusion

BMI was positively associated with the overall risk of stroke among DM patients in Korea. The risk of ischemic stroke was higher in obese patients compared to overweight or normal-weight patients. However, the risk of hemorrhagic stroke was higher in slimmer patients compared with overweight or obese patients.

Combined consideration of body mass index and waist circumference identifies obesity patterns associated with risk of stroke in a Chinese prospective cohort study

Background

In China, few studies have examined the relationship between the combination of body mass index and waist circumference and the risk of stroke. Moreover, the relationship may also be different in different genders. Thus, we investigated the association between the combination of body mass index and waist circumference and the risk of stroke in Chinese.

Methods

This prospective cohort study included 36 632 participants aged 18 to 90 years. Participants were recruited from 60 surveillance sites (25 urban sites and 35 rural sites) across China in 2010 China Chronic Disease Risk Factor Surveillance, and followed up in 2016-2017. Incident cases of stroke were identified through questionnaires (including the basis of clinical diagnosis, imaging tests, time of diagnosis, diagnosis unit) and Cardiovascular Event Report System. Risk factors for stroke were collected at baseline using questionnaire, physical measurements and laboratory tests. Cox proportional hazards regression models were used to generate adjusted hazard ratios and 95%CI. All analyses were duplicated by gender stratification.

Results

During 6.42 ± 0.50 years of follow-up, 1 333 (597 males, 736 females) stroke events were observed among the 27 112 participants who did not have cardiovascular diseases at baseline. Compared with the general population who have normal weight or underweight with normal WC, those who have normal weight or underweight with abdominal obesity (adjusted hazard ratios 1.45, 95%CI 1.07-1.97 in males; 0.98, 95%CI 0.78-1.24 in females), overweight with abdominal obesity (1.41, 95%CI 1.14-1.75 in males; 1.33, 95%CI 1.10-1.61 in females), obesity with abdominal obesity (1.46, 95%CI 1.11-1.91 in males; 1.46, 95%CI 1.17-1.81 in females). Overweight with normal WC was found to be not statistically significant for both males and females (all P>0.05). Subgroup analysis found a multiplicative interaction between age and anthropometric group in females (P for interaction <0.05). Sensitivity analysis results did not change. In the subjects with CVD risk factors, we found a similar relationship as in the general population .

Conclusions

Combined assessment of body mass index and waist circumference identifies obesity patterns associated with stroke risk.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-12756-2.

Factors associated with stroke among patients with type 2 diabetes mellitus in China: a propensity score matched study

OBJECTIVE

This study aimed to examine the prevalence of stroke and associated factors of stroke in patients with type 2 diabetes(T2DM) in China.

METHODS

Participants were 18,013 T2DM patients recruited with stratified random cluster sampling method from December 2013 to January 2014 in China. Propensity score matching was used to eliminate confounding effects between groups and logistic regression analysis was used to examine factors associated with stroke among T2DM patients.

RESULTS

Overall, the prevalence of stroke in the subjects with T2DM was 9.5%. After nearest neighbor matching, smoking (OR = 1.60, 95%CI: 1.26-2.03), hypertension (OR = 2.96, 95%CI: 2.55-3.43), dyslipidemia (OR = 2.00, 95%CI: 1.71-2.33), family history of stroke (OR = 2.02, 95%CI: 1.61-2.54), obesity (OR = 1.21, 95%CI: 1.01-1.45) and sleep duration < 6 h/day (OR = 1.44, 95%CI: 1.20-1.73) or > 8 h/day (OR = 1.22, 95%CI: 1.05-1.42) were positively associated with stroke, whereas drinking 1-3 days/week (OR = 0.64, 95%CI: 0.45-0.90) or daily (OR = 0.45, 95%CI: 0.33-0.60), effective exercise (OR = 0.65, 95%CI: 0.57-0.73) and underweight (OR = 0.30, 95%CI: 0.13-0.71) were negatively related to stroke. Besides, the risk of stroke increased substantially with accumulation of above seven modified risk factors. The odds ratio values of stroke in patients having ≥ 5 of the above seven risk factors was 14.39 (95% CI: 8.87-23.26).

CONCLUSIONS

The prevalence of stroke was high among T2DM in China. It is of great significance to strengthen comprehensive management of health-related behaviors including smoking cessation, moderate alcohol consumption, effective exercise, 6-8 h of sleep duration, keeping normal weight and the prevention of hypertension and dyslipidemia to have sustained beneficial effects on improvements of stroke risk factors.

Association Between a Body Shape Index and Subclinical Carotid Atherosclerosis in Population Free of Cardiovascular and Cerebrovascular Diseases

AIM

We used a dataset from a cross-sectional survey conducted in China to determine which of the anthropometric indices of obesity are important in terms of carotid atherosclerosis free of cardiovascular and cerebrovascular diseases.

METHODS

A total of 5,245 participants who were volunteering for carotid ultrasound unit in this cross-sectional survey were included in the present analysis. All subjects were free of angina, myocardial infarction, heart failure and stroke, and cancer. A low-risk subgroup was defined as people free of hypertension, diabetes, and hyperlipidemia. All analyses based on logistic regression were gender-specific.

RESULTS

The present study consisted of 2,501 males and 2,744 females, with 776 (31.03%) diagnosed as carotid artery plaque in males and 550 (20.04%) in females. Univariable analyses in unadjusted logistic model showed significant associations between disease presence and all central obesity indices. After adjusting for more variables, only a body shape index (ABSI) was associated with the presence of disease in both males and females. Moreover, stepwise regression approaches revealed that ABSI was always an independent determinant of the presence of subclinical carotid plaque. Multiple regression shows a linear and significant increase in the prevalence of atherosclerosis in males and females as ABSI decile levels increased. Similar results were obtained when the association between ABSI and carotid plaque was studied in this low-risk subgroup.

CONCLUSIONS

ABSI, as a novel anthropometric indicator compared with traditional indices, was found to have a closer relationship with subclinical carotid atherosclerosis, even in populations free of hypertension, diabetes, and hyperlipidemia.

Prevalence of and factors associated with stroke in hypertensive patients in Thailand from 2014 to 2018: A nationwide cross-sectional study

Stroke is a significant cause of death and disability. In Thailand, it imposes a major health burden, and the prevalence of stroke is increasing, particularly in patients with hypertension (HT), diabetes mellitus (DM), and dyslipidemia (DLP). We aimed to determine the trends in the prevalence of stroke and the associated factors among Thai patients with HT. Nationwide cross-sectional studies were conducted annually in 2014, 2015 and 2018 based on data obtained from the Thailand DM/HT study. Nationally, representative patients with HT in Thailand were sampled with stratified one-stage cluster sampling. A total of 104,028 participants were included in this study. The prevalence of stroke remained constant, with prevalence rates of 4.0%, 3.8%, and 3.9% in 2014, 2015 and 2018, respectively (p for trend = 0.221). Our findings suggested that the management of stroke patients who are covered by the universal coverage scheme should be evaluated. Effective interventions, including promoting smoking cessation, attenuating cholesterol levels, and controlling blood pressure should be provided to hypertensive patients to prevent ischemic stroke. Young adults with HT should be more concerned about the possibility of stroke. The use of prophylactic low-dose aspirin should be carefully monitored to prevent hemorrhagic stroke.

Association of BMI with cardiovascular disease incidence and mortality in patients with type 2 diabetes mellitus: A systematic review and dose-response meta-analysis of cohort studies

AIMS

The relation of body mass index (BMI) with cardiovascular disease (CVD) and mortality has been extensively investigated in the general population but is less clear in individuals with type 2 diabetes mellitus (T2DM). We performed a meta-analysis of cohort studies to quantitatively evaluate the association of BMI with CVD incidence and mortality in patients with T2DM.

DATA SYNTHESIS

PubMed and Embase databases were searched for relevant cohort articles published up to June 8, 2020. Restricted cubic splines were used to evaluate the potential linear or non-linear dose-response associations. We identified 17 articles (21 studies) with 1,349,075 participants and 57,725 cases (49,354 CVD incidence and 8371 CVD mortality) in the meta-analysis. We found a linear association between BMI and risk of CVD incidence (P_{non-linearity} = 0.182); the pooled RR for CVD incidence was 1.12 (95% CI, 1.04-1.20) with a 5-unit increase in BMI. We found an overall nonlinear relationship between BMI and CVD mortality (P_{non-linearity} < 0.001). The lowest risk was at BMI about 28.4 kg/m², with increased mortality risk for higher BMI values; the RR with a 5-unit increase in BMI was 0.87 (95% CI, 0.79-0.96) and 1.11 (95% CI, 1.04-1.18) for BMI ≤28.4 kg/m² and BMI >28.4 kg/m², respectively.

CONCLUSIONS

In individuals with T2DM, BMI may have a positive linear association with risk of CVD incidence but a nonlinear association with CVD mortality. Our results can provide evidence for weight control and lifestyle intervention for preventing and managing cardiovascular disease in T2DM.

Practical use of electronic health records among patients with diabetes in scientific research

Electronic health (medical) records, which are also considered as patients’ information that are routinely collected, provide a great chance for researchers to develop an epidemiological understanding of disease. Electronic health records systems cannot develop without the advance of computer industries. While conducting clinical trials that are always costly, feasible and reasonable analysis of routine patients’ information is more cost-effective and reflective of clinical practice, which is also called real world study. Real world studies can be well supported by big data in healthcare industry. Real world studies become more and more focused and important with the development of evidence-based medicine. These big data will definitely help in making decisions, making policies and guidelines, monitoring of effectiveness and safety on new drugs or technologies. Extracting, cleaning, and analyzing such big data will be a great challenge for clinical researchers. Successful applications and developments of electronic health record in western countries (eg, disease registries, health insurance claims, etc) have provided a clear direction for Chinese researchers. However, it is still at primary stages in China. This review tries to provide a full perspective on how to translate the electronic health records into scientific achievements, for example, among patients with diabetes. As a summary in the end, resource sharing and collaborations are highly recommended among hospitals and healthcare groups.

Different Indicators of Adiposity and Fat Distribution and Cardiometabolic Risk Factors in Patients with Type 2 Diabetes

OBJECTIVE

This study aimed to evaluate the effect of adiposity and fat distribution on the odds of elevated cardiovascular risk factors among adults with type 2 diabetes mellitus.

METHODS

The present cross-sectional study included 2,427 adults with type 2 diabetes mellitus. Body fat was assessed by dual-energy x-ray absorptiometry. Multivariate-adjusted logistic regression was used to estimate effects of adiposity parameters on elevated hemoglobin A_1c (HbA_1c , ≥7.0%), hypertension (blood pressure ≥140/90 mmHg), and elevated low-density lipoprotein (LDL) cholesterol (≥2.6 mmol/L).

RESULTS

The multivariable-adjusted odds ratio (OR) for elevated HbA_1c was 0.82 (95% CI: 0.70-0.96) for each SD increase in leg fat mass. The multivariable-adjusted OR for hypertension was 1.15 (95% CI: 1.00-1.32) for each SD increase in android fat mass. Multivariable-adjusted ORs for elevated LDL cholesterol ranged from 1.16 (95% CI: 1.00-1.35) to 1.27 (95% CI: 1.06-1.51) for each SD increase in arm and android fat mass and percentage of total, truncal, arm, and android fat. Each SD increase in BMI, truncal-to-leg fat ratio, and android-to-gynoid fat ratio was significantly associated with increased risks of elevated HbA_1c , hypertension, and elevated LDL cholesterol.

CONCLUSIONS

Subcutaneous fat in the lower body was associated with a more favorable glycemic profile, but not blood pressure or lipid profile, whereas central adiposity was associated with poor control of cardiovascular risk factors among patients with type 2 diabetes mellitus.

Estimating the effects of body mass index and central obesity on stroke in diabetics and non-diabetics using targeted maximum likelihood estimation: Atherosclerosis Risk in Communities study

OBJECTIVES

The association of body mass index (BMI) with the risk of cardiovascular disease among diabetic patients is controversial. This study compared the effects of BMI and central obesity on stroke in diabetics and non-diabetics using targeted maximum likelihood estimation.

MATERIALS AND METHODS

This analysis included 12 725 adults aged 45-75 years, after excluding prevalence cases and participants with missing data, from the Atherosclerosis Risk in Communities study. Obesity was defined with BMI, waist circumference, waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), body shape index (BSI) and body roundness index (BRI), which categorized all participants as obese and non-obese. Generalized linear models and TMLE (with the tmle package) were used to estimate risk ratio (RR).

RESULTS

During 27 years of follow-up, 1078 (8.47%) cases of stroke occurred. After adjustment for demographic, behavioural, biologic and central obesity variables, the effect of BMI decreased in both diabetics and non-diabetics. The effect of BMI in diabetics was more attenuated, in full model, (RR: 1.04 [0.90, 1.20]) rather than non-diabetics (RR: 1.11 [1.00, 1.24]). This attenuation was more related to biologic variables in non-diabetics and central obesity in diabetics. With respect to central obesity, BSI (RR [95% CI]: 1.15 [0.96, 1.38]) and WHR (RR [95% CI]: 1.15 [0.87, 1.52]) had strongest and marginally significant effects for diabetics and BSI (RR [95% CI]: 1.10 [1.02, 1.20]) for non-diabetics.

CONCLUSIONS

Among diabetics, BSI and WHR indices were associated with a higher incidence of stroke. Future studies should consider how central obesity affects higher incidence of stroke among diabetics stratified by sex and age groups.