Association of longitudinal trajectories of fasting plasma glucose with all-cause and cardiovascular mortality among a Chinese older population: a retrospective cohort study.

The association between fasting plasma glucose (FPG), an important indicator of overall glycemic status, and the risk of cardiovascular mortality has been well investigated. The longitudinal study can repeatedly collect measured results for the variables to be studied and then consider the potential effects of intraindividual changes in measurement. This study aimed to identify long-term FPG trajectories and investigate the association between trajectory groups and cardiovascular and all-cause mortality. A latent class growth mixture modeling (LCGMM) was used to identify FPG trajectories. Cox proportional hazard models were used to estimate associations between FPG trajectories and the risk of all-cause and cardiovascular mortality. A U-shaped relationship between FPG and all-cause and cardiovascular mortality was observed in the restricted cubic spline regression models. Two FPG longitudinal trajectories of low-level (mean FPG = 5.12mmol/L) and high-level (mean FPG = 6.74mmol/L) were identified by LCGMM. After being adjusted for potential confounders, compared with the low-level category, the hazard ratios (HRs) for all-cause and cardiovascular mortality were 1.23(1.16-1.30) and 1.25(1.16-1.35), respectively, for the high-level group. Long-term FPG trajectories are significantly associated with and potentially impact the risk of all-cause and cardiovascular mortality.

Relationship between obesity indicators and hypertension-diabetes comorbidity in an elderly population: a retrospective cohort study.

BACKGROUND: The prevalence of obesity, hypertension and diabetes is increasing. Hypertension and diabetes are common complications. Additionally, obesity and hypertension-diabetes comorbidity (HDC) are both closely related to insulin resistance. The aim of this study was to determine the association of obesity indicators with HDC in elderly individuals. METHODS: This retrospective cohort study included 74,955 subjects aged ≥ 60 years living in Xinzheng, Henan Province, from January 2011 to December 2019. The data were collected from the annual health examination dataset. Cox proportional hazard regression models and competing-risk survival regression models were used to examine the relationships between the three indicators and HDC risk. RESULTS: After 346,504 person-years of follow-up, HDC developed in 9,647 subjects. After further adjustments for confounders and death competing risks, compared with a body mass index (BMI) of 18.5-23.9 kg/m2, the fully adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) of BMI < 18.5, 24-27.9 and ≥ 28 kg/m2 for HDC morbidity were 0.651(0.538,0.788),1.00,1.396(1.336,1.459) and 1.769(1.666,1.878), respectively. Moreover, participants with abdominal obesity measured via waist circumference (WC) or waist-to-height ratio (WtHR) had a higher risk of HDC (HR:1.513; 95% CI: 1.45,1.578 and HR:1.412;95% CI: 1.353,1.473), respectively, than participants with low WC or with low WtHR. In the joint analyses, the highest risk was observed in participants who were overweight and who had central obesity (HR: 1.721; 95% CI: 1.635, 1.811) compared with the nonoverweight and noncentral obesity groups. CONCLUSIONS: Increased BMI, WC and WtHR were associated with an increased risk of HDC. There was an additive interaction between general body adiposity (as measured via BMI) and central obesity (as measured via WC and WtHR) for HDC. Therefore, reasonable control of BMI, WC and WtHR may be an effective measure to prevent HDC among elderly individuals.

Association of body mass index and waist circumference with type 2 diabetes mellitus in older adults: a cross-sectional study.

BACKGROUND: The prevalence of obesity and diabetes is rising. The aim of this study was to determine the association of body mass index (BMI) and waist circumference (WC) with type 2 diabetes mellitus (T2DM) in the elderly and to compare the discriminatory abilities of BMI, WC and other anthropometric indicators, including waist-to-height ratio (WHtR), body adiposity estimator (BAE) and body roundness index (BRI) for T2DM. METHODS: This cross-sectional study included 69,388 subjects aged ≥ 60 years living in Xinzheng, Henan Province, from January to December 2020. The data came from the residents' electronic health records of the Xinzheng Hospital Information System. Logistic regression was used to examine the relationships. Fully adjusted models adjusted for age, sex, place of residence, alcohol consumption, smoking, physical exercise, SBP and RHR. The area under the receiver operating characteristic curve (AUC) was used to compare the discriminatory ability of different anthropometric indicators for T2DM under the influence of potential risk factors. RESULTS: After adjusting for multiple covariates, compared with the first BMI quintile, the odds ratios (ORs) and 95% confidence intervals (CIs) from the second to fifth quintile for T2DM were 1.416 (1.335-1.502), 1.664 (1.570-1.764), 1.879 (1.774-1.990) and 2.156 (2.037-2.283), respectively. Compared with the first WC quintile, the ORs and 95% CIs from the second to fifth quintiles for T2DM were 1.322 (1.244-1.404), 1.549 (1.459-1.643), 1.705 (1.609-1.807) and 2.169 (2.048-2.297), respectively. Among men, compared with other anthropometric indicators (BMI, WHtR, BAE and BRI), WC showed the highest AUC (AUC: 0.629; 95% CI: 0.622-0.636). Among women, the AUCs of BMI (AUC: 0.600; 95% CI: 0.594-0.606), WC (AUC: 0.600; 95% CI: 0.593-0.606) and BAE (AUC: 0.600; 95% CI: 0.594-0.607) were similar, and the AUCs of BMI, WC and BAE were higher than WHtR, BRI. CONCLUSIONS: All anthropometric indicators were positively associated with T2DM. In men, WC with the strongest positive association with T2DM was the best predictor of T2DM. In women, BMI was most strongly associated with T2DM, and the predictive powers of BMI, WC and BAE were similar. After adjusting the potential confounding factors including age, sex, place of residence, alcohol consumption, smoking, physical exercise, SBP and RHR, the effect of these factors was eliminated, the findings were independent of the covariates considered.

Associations of BMI with all-cause mortality in normoglycemia, impaired fasting glucose and type 2 diabetes mellitus among an elderly Chinese population: a cohort study.

AIM: To explore the associations of body mass index (BMI) and mortality among people with normal fasting glucose (NFG), impaired fasting glucose (IFG), and type 2 diabetes mellitus (T2DM) in an elderly Chinese population.  METHODS: A retrospective cohort study was conducted that included 59,874 elderly people who were aged 60 and older at baseline. Data for the study came from a health check-up program in China between 2011 and 2019. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using multivariable Cox proportional hazard models of BMI categories by glycemic status. RESULTS: During the median of 5.96 years of follow-up, 7928 participants died (6457/49057 with NFG, 712/5898 with IFG and 759/4919 with T2DM). In adjusted Cox models, risk of mortality showed a decreasing trend with BMI < 18.5 kg/m2, 24 ≤ BMI < 28 kg/m2, and BMI ≥ 28 kg/m2 compared to 18.5 ≤ BMI < 24 kg/m2: HR (95% CI): 1.33 (1.18 to 1.49), 0.88 (0.83 to 0.93), and 0.90 (0.82 to 0.98), respectively, for NFG; 0.89 (0.55 to 1.46), 0.84 (0.71 to 0.99), and 0.88 (0.70 to 1.11), respectively, for IFG; and 1.42 (0.88 to 2.29), 0.75 (0.64 to 0.89), and 0.76 (0.62 to 0.93), respectively, for T2DM. There were curvilinear-shaped associations between BMI and mortality in the NFG and T2DM groups (P overall < 0.001 and P overall < 0.001, respectively; P nonlinearity < 0.001 and P nonlinearity = 0.027, respectively) and no significantly association between BMI and all-cause mortality was observed in the IFG group (P overall = 0.170). CONCLUSION: High BMI compared to normal BMI was associated with decreased mortality, especially in the old populations with NFG and T2DM. Future studies are needed to explain the obesity paradox in elderly patients with T2DM.

Hypertension modifies the associations of body mass index and waist circumference with all-cause mortality among older Chinese: a retrospective cohort study.

BACKGROUND: The effect of baseline hypertension status on the BMI-mortality association is still unclear. We aimed to explore the relationships of body mass index (BMI) and waist circumference (WC) with all-cause mortality among older hypertensive and normotensive Chinese individuals. METHODS: This retrospective cohort study was conducted in Xinzheng, Henan Province, Central China. The data came from the residents' electronic health records of the Xinzheng Hospital Information System. A total of 77,295 participants (41,357 hypertensive participants and 35,938 normotensive participants) aged ≥ 60 years were included from January 2011 to November 2019. Cox proportional hazard regression model was used to examine the relationships. RESULTS: During a mean follow-up of 5.3 years, 10,755 deaths were identified (6,377 in hypertensive participants and 4,378 in normotensive participants). In adjusted models, compared with a BMI of 18.5-24 kg/m2, the hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) of BMI < 18.5, 24-28 and ≥ 28 kg/m2 for mortality in hypertensive participants were 1.074 (0.927-1.244), 0.881 (0.834-0.931) and 0.856 (0.790-0.929), respectively, and 1.444 (1.267-1.646), 0.884 (0.822-0.949) and 0.912 (0.792-1.051), respectively, in normotensive participants. Compared with normal waist circumference, the adjusted HRs and 95% CIs of central obesity for mortality were 0.880 (0.832-0.931) in hypertensive participants and 0.918 (0.846-0.996) in normotensive participants. A sensitivity analysis showed similar associations for both hypertensive and normotensive participants. CONCLUSION: Low BMI and WC were associated with a higher risk of all-cause mortality regardless of hypertension status in older Chinese individuals. The lowest risk of death associated with BMI was in the overweight group in normotensive participants and in the obesity group in hypertensive participants.

Association of body mass index and waist circumference with high blood pressure in older adults.

BACKGROUND: The relationship between obesity and prevalent high blood pressure in older adults has predominantly been estimated using categorical measures of body mass index (BMI) and waist circumference (WC), masking the shape of the dose-response relationship. We aimed to examine the precise relationship of BMI, WC with high blood pressure and to assess the appropriate level of BMI and WC for high blood pressure. METHODS: We examined data for 126,123 individuals in Xinzheng city aged ≥60 years from a population based study from January to December 2019. Logistic regression and restricted cubic spline models were applied to assess the relationship and the appropriate level of BMI and WC for high blood pressure. An additive interaction analysis was used to test synergistic effects between a higher BMI and WC for high blood pressure. RESULTS: The full-adjusted odds ratios (ORs) with 95% confidence intervals (CIs) of an increase of 1 kg/m2 in BMI and 1 cm in WC for high blood pressure were 1.084 (1.080-1.087) and 1.026(1.024-1.027), respectively. Multivariable adjusted restricted cubic spline analyses showed the nonlinear relationships of BMI and WC with high blood pressure in both men and women (all P < 0.001). The risk of high blood pressure increased steeply with increasing BMI from ≥25 kg/m2 and WC ≥ 88 cm or 86 cm for males and females, respectively. And we observed a significant additive interaction between a higher BMI and WC such that the prevalence of high blood pressure was significantly enhanced. CONCLUSION: These findings suggest increased high blood pressure prevalence in the older adults with increased BMI and WC. BMI ≤ 25 kg/m2 and WC ≤ 88 cm or 86 cm for males and females may be the best suggestion with regard to primary prevention of high blood pressure in older adults.

Relationship between multimorbidity, disease cluster and all-cause mortality among older adults: a retrospective cohort analysis.

BACKGROUND: Previous studies have evaluated the association of multimorbidity with higher mortality, but epidemiologic data on the association between the disease clusters and all-cause mortality risk are rare. We aimed to examine the relationship between multimorbidity (number/ cluster) and all-cause mortality in Chinese older adults. METHODS: We conducted a population-based study of 50,100 Chinese participants. Multiple logistic regression analysis was used to estimate the impact of long-term conditions (LTCs) on all-cause mortality. RESULTS: The prevalence of multimorbidity was 31.35% and all-cause mortality was 8.01% (50,100 participants). In adjusted models, the odds ratios (ORs) and 95% confidence intervals (CIs) of all-cause mortality risk for those with 1, 2, and ≥ 3 LTCs compared with those with no LTCs was 1.45 (1.32-1.59), 1.72 (1.55-1.90), and 2.15 (1.85-2.50), respectively (Ptrend < 0.001). In the LTCs ≥2 category, the cluster of chronic diseases that included hypertension, diabetes, CHD, COPD, and stroke had the greatest impact on mortality. In the stratified model by age and sex, absolute all-cause mortality was higher among the ≥75 age group with an increasing number of LTCs. However, the relative effect size of the increasing number of LTCs on higher mortality risk was larger among those < 75 years. CONCLUSIONS: The risk of all-cause mortality is increased with the number of multimorbidity among Chinese older adults, particularly disease clusters.

Association of the CUN-BAE body adiposity estimator and other obesity indicators with cardiometabolic multimorbidity: a cross-sectional study.

Cardiometabolic multimorbidity (CM), defined as the coexistence of two or three cardiometabolic disorders, is one of the most common and deleterious multimorbidities. This study aimed to investigate the association of Clínica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE), body mass index (BMI), waist circumference (WC), and waist-to-height ratio (WHtR) with the prevalence of CM. The data were obtained from the 2021 health checkup database for residents of the Electronic Health Management Center in Xinzheng, Henan Province, China. 81,532 participants aged ≥ 60 years were included in this study. Logistic regression models were used to estimate the odd ratios (ORs) and 95% confidence intervals (CIs) for CUN-BAE, BMI, WC, and WHtR in CM. The area under the receiver operating characteristic curve (AUC) was used to compare the discriminatory ability of different anthropometric indicators for CM. The multivariable-adjusted ORs (95% CIs) (per 1 SD increase) of CM were 1.799 (1.710-1.893) for CUN-BAE, 1.329 (1.295-1.364) for BMI, 1.343 (1.308-1.378) for WC, and 1.314 (1.280-1.349) for WHtR, respectively. Compared with BMI, WC and WHtR, CUN-BAE had the highest AUC in both males and females (AUC: 0.642; 95% CI 0.630-0.653 for males, AUC: 0.614; 95% CI 0.630-0.653 for females). CUN-BAE may be a better measure of the adverse effect of adiposity on the prevalence of CM than BMI, WC, and WHtR.

Association of Metabolically Healthy Obesity and Risk of Cardiovascular Disease Among Adults in China: A Retrospective Cohort Study.

Purpose: Previous studies have shown that metabolically healthy obesity (MHO) and changes in its status are connected to an increased incidence of cardiovascular disease (CVD). Yet, fewer studies have been conducted in China, especially for the middle-aged and elderly population, a high-risk group. The purpose of the study was to investigate the association between metabolic health status and CVD events. Patients and Methods: A total of 46,055 participants were categorized into 6 subgroups with different metabolic states according to the existence of metabolic syndrome and body mass index (BMI). The changes in obesity and metabolic health status were defined from baseline to follow-up outcomes with a combination of overweight and obesity. Cox proportional hazards models estimated the association of CVD events and each BMI-metabolic groups. Results: MHO and metabolic abnormality normal weight (MANW) subjects had a higher HR of CVD, 1.62 (95% CI, 1.36-1.92) and 1.24 (95% CI, 1.07-1.44), respectively, than their metabolically healthy normal weight (MHNW) counterparts. Then, more than 50% and 30% of the metabolically healthy overweight or obesity (MHOO) populations maintained their status and converted to a metabolically unhealthy state, respectively. Stable MANW, MHOO and metabolically abnormal obesity (MAO) were associated with a higher risk for CVD, 1.68 (95% CI, 1.37-2.05),1.26 (95% CI, 1.08-1.47) and 1.65 (95% CI, 1.45-1.88), respectively, than stable MHNW. Conclusion: Despite being of normal weight, MANW status is in fact a risk factor for CVD, as well as MHO, especially for the Chinese middle-aged and elderly population. Furthermore, metabolic health is a transient state for partial middle-aged and elderly Chinese individuals, and MAO has the highest risk of CVD, including coronary heart disease (CHD) and stroke.

Association of body roundness index and its trajectories with all-cause and cardiovascular mortality among a Chinese middle-aged and older population: A retrospective cohort study.

Objectives: The body roundness index (BRI) is a novel anthropometric index that is a better indicator for predicting fat distribution than the body mass index (BMI). The longitudinal study can repeatedly collect measured results for the variables to be studied and then consider the potential effects of intraindividual changes in measurement. However, few population-based, longitudinal studies of BRI have been conducted, especially among the Chinese population. The study aimed to investigate the association of BRI and its longitudinal trajectories with all-cause and cardiovascular mortality. Methods: A total of 71,166 participants with four times BRI measurements between January 2010 and December 2019 were included in this longitudinal study, with a median follow-up was 7.93 years, and 11,538 deaths were recorded, of which 5,892 deaths were due to cardiovascular disease (CVD). A latent class growth mixture modeling (LCGMM) was used to identify BRI trajectories. Cox proportional hazard models were used to estimate associations between BRI trajectories and the risk of all-cause and cardiovascular mortality. Results: In the restricted cubic spline regression models, a U-shaped relationship between BRI and all-cause and cardiovascular mortality was observed. Three BRI longitudinal trajectories of low-stable (mean BRI = 2.59), moderate-stable (mean BRI = 3.30), and high-stable (mean BRI = 3.65) were identified by LCGMM. After being adjusted for potential confounders, the HRs for all-cause mortality were 1.18 (1.13-1.24) for the moderate-stable group and 1.74 (1.66-1.82) for the high-stable group compared to the low-stable group. The HRs for cardiovascular mortality were 1.12 (1.05-1.18) for the moderate-stable group and 1.64 (1.53-1.75) for the high-stable group compared to the low-stable group. Conclusion: A nonlinear association of BRI with all-cause and cardiovascular mortality was observed, and participants in the higher BRI longitudinal trajectory group were significantly associated with an increased risk of all-cause and cardiovascular mortality.

Association of the Clínica Universidad de Navarra-Body Adiposity Estimator With Type 2 Diabetes: A Retrospective Cohort Study.

Objectives: Clínica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE) is considered to be a more accurate indicator of body fat estimation. We aimed to investigate the association of CUN-BAE with the risk of type 2 diabetes mellitus (T2DM) and to compare the strength of the association between CUN-BAE, body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR) and T2DM. Methods: The data were obtained from the annual health checkup database of residents in Xinzheng, China. From January 2011 to December 2021, 80,555 subjects aged ≥45 years met the inclusion criteria. Cox proportional hazard regression models were used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) for CUN-BAE, BMI, WC, and WHtR in T2DM. Results: During a mean follow-up of 6.26 years, T2DM occurred in 12,967 subjects. The multivariable-adjusted HRs (95% CIs) of T2DM (highest vs. reference group) were 1.994 (1.811-2.196) for CUN-BAE, 1.751 (1.665-1.842) for WC, 1.715 (1.631-1.804) for WHtR, and 1.510 (1.436-1.588) for BMI, respectively. In addition, the risk of T2DM increased with baseline CUN-BAE (HR: 1.374; 95% CI: 1.328, 1.421), WC (HR: 1.236; 95% CI: 1.215, 1.256), WHtR (HR: 1.228; 95% CI: 1.208, 1.248), and BMI (HR: 1.175; 95% CI: 1.156, 1.195). Conclusion: Compared to BMI, WC or WHtR, CUN-BAE may more adequately reflect the adverse effects of adiposity on the risk of T2DM.

Relationship Between Six Insulin Resistance Surrogates and Nonalcoholic Fatty Liver Disease Among Older Adults: A Cross-Sectional Study.

Background: Non-alcoholic fatty liver disease (NAFLD) represents a large and growing public health problem. Insulin resistance (IR) plays a crucial role in the pathogenesis of NAFLD. The aim of this study was to determine the association of triglyceride-glucose (TyG) index, TyG index with body mass index (TyG-BMI), lipid accumulation product (LAP), visceral adiposity index (VAI), triglycerides/high-density lipoprotein cholesterol ratio (TG/HDL-c) and metabolic score for IR (METS-IR) with NAFLD in older adults and to compare the discriminatory abilities of these six IR surrogates for NAFLD. Methods: This cross-sectional study included 72,225 subjects aged ≥60 years living in Xinzheng, Henan Province, from January 2021 to December 2021. The data were collected from the annual health examination dataset. Logistic regression models were used to examine the relationships between the six indicators and NAFLD risk. The area under the receiver operating characteristic curve (AUC) was used to compare the discriminatory ability of different IR surrogates for NAFLD under the influence of potential risk factors. Results: After adjusting for multiple covariates, compared with the first quintile, the odds ratios (ORs) and 95% confidence intervals (CIs) of the highest quintiles of TyG-BMI were the most obvious (OR:43.02, 95% CI:38.89-47.72), followed by the METS-IR (OR:34.49, 95% CI:31.41-37.95). Restricted cubic spline analysis reported that there were non-linear positive association and dose-response relationship between 6 IR surrogates and NAFLD risk. Compared with other IR-related indicators (LAP, TyG, TG/HDL-c and VAI), TyG-BMI showed the highest AUC (AUC:0.8059;95% CI:0.8025-0.8094). Additionally, METS-IR also had a high predictive performance for NAFLD, and the AUC was greater than 0.75 (AUC:0.7959;95% CI:0.7923-0.7994). Conclusion: TyG-BMI and METS-IR had pronounced discrimination ability to NAFLD, which are recommended as complementary markers for the assessment of NAFLD risk both in clinic and in future epidemiological studies.

Association of anthropometric indices with the development of multimorbidity in middle-aged and older adults: A retrospective cohort study.

BACKGROUND: Previous studies have explored the relationship between body mass index (BMI) and multimorbidity. However, the relationship between other obesity indicators and their dynamic changes and multimorbidity has not been systematically estimated. Therefore, we aimed to investigate the association of BMI and other obesity indicators, including waist circumference (WC), waist-to-height ratio (WHtR), waist divided by height0.5 (WHT.5R), and body roundness index (BRI) and their changes and the risk of multimorbidity in middle-aged and older adults through a retrospective cohort study. METHODS: Data collected from annual health examination dataset in the Jinshui during 2017 and 2021. Cox regression models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) to evaluate the effect of baseline and dynamic changes in the anthropometric indices on the risk of multimorbidity. RESULTS: A total of 75,028 individuals were included in the study, and 5,886 participants developed multimorbidity during the follow-up. Multivariate Cox regression analysis revealed a progressive increase in the risk of multimorbidity with increasing anthropometric indicators (BMI, WC, WHtR, WHT.5R, and BRI) (all P<0.001). Regardless of general obesity status at baseline, increased WC was associated with a high risk of multimorbidity. Compared to the subjects with baseline BMI<24 kg/m2 and WC<90 (men)/80 (women), the HRs (95% CI) of the baseline BMI<24 kg/m2 and WC≥90 (men)/80 (women) group and BMI≥24 kg/m2 and WC≥90 (men)/80 (women) group were 1.31 (1.08, 1.61) and 1.82 (1.68, 1.97), respectively. In addition, the dynamics of WC could reflect the risk of multimorbidity. When subjects with baseline WC<90 (men)/80 (women) progressed to WC≥90 (men)/80 (women) during follow-up, the risk of multimorbidity significantly increased (HR = 1.78; 95% CI, 1.64, 1.95), while the risk of multimorbidity tended to decrease when people with abnormal WC at baseline reversed to normal at follow-up (HR = 1.40; 95% CI, 1.26, 1.54) compared to those who still exhibited abnormal WC at follow-up (HR = 2.00; 95% CI, 1.82, 2.18). CONCLUSIONS: Central obesity is an independent and alterable risk factor for the occurrence of multimorbidity in middle-aged and elderly populations. In addition to the clinical measurement of BMI, the measurement of the central obesity index WC may provide additional benefits for the identification of multimorbidity in the Chinese middle-aged and elderly populations.

Stronger Associations of Body Mass Index and Waist Circumference with Diabetes than Waist-Height Ratio and Triglyceride Glucose Index in the Middle-Aged and Elderly Population: A Retrospective Cohort Study.

Background: It remains controversial whether body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), or triglyceride glucose (TyG) index has a stronger association with diabetes. The aims of the study were to compare the magnitude of associations of four indicators with diabetes risk. Methods: Data collected from annual health examination dataset in the Xinzheng during 2011 and 2019. A total of 41,242 participants aged ≥ 45 years were included in this study. Cox proportional hazard regression models were used to examine associations between the four indicators and diabetes risk. Results: After 205,770 person-years of follow up, diabetes developed in 2,472 subjects. Multivariable-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) of diabetes (highest vs reference group) were 1.92 (1.71-2.16) for BMI, 1.99 (1.78-2.23) for WC, 1.65 (1.47-1.86) for WHtR, and 1.66 (1.47-1.87) for TyG, respectively. In addition, the risk of diabetes increased with baseline BMI (HR: 1.30; 95% CI: 1.25, 1.35) and TyG (HR: 1.25; 95% CI: 1.20, 1.30), but the lowest HR was 0.78 (95% CI 0.65-0.92) when WC was approximately 72 cm, and 0.85 (95% CI 0.72-0.99) when WHtR was approximately 0.47 in women. In joint analyses, the highest risk was observed in participants with a high BMI combined with a high WC (HR: 2.26; 95% CI: 1.98, 2.58). Conclusions: In middle-aged and elderly Chinese population, BMI and WC were more strongly associated with diabetes than WHtR or TyG, especially the combined effect of BMI and WC.

Distribution of risk factors differs from coronary heart disease and stroke in China: a national population survey.

OBJECTIVES: This study aimed to explore the distribution differences of common risk factors between coronary heart disease (CHD) and stroke in China. SETTING: The China National Stroke Screening Survey is a cluster sampling survey based on a nationwide general community population, adopting multistage stratified sampling method and covering all 31 provinces in China mainland. PARTICIPANTS: A total number of 725 707 people aged 40 years and above were included in the study. PRIMARY AND SECONDARY OUTCOME MEASURES: The basic demographic information, lifestyle behaviour, physical examination, traditional risk factors, family history of cardiovascular disease (CVD) and CVD events were collected. Risk factors of CHD and stroke were explored and analysed in the whole investigated population to identify the common risk factors. Multivariate logistic regression analysis was used to analyse the distribution difference of risk factors between CHD and stroke. RESULTS: There were 13 variables associated with CHD and stroke, in which 11 variables revealed differences in the distribution between CHD and stroke. Family history of stroke (OR: 2.30; 95% CI 2.15 to 2.45), men (OR: 1.92; 95% CI 1.80 to 2.05), rural areas (OR: 1.70; 95% CI 1.60 to 1.80), transient ischaemic attack (OR: 1.41; 95% CI 1.30 to 1.54) and hypertension (OR: 1.28; 95% CI 1.19 to 1.38) indicated significantly stronger association with stroke, while family history of CHD (OR: 0.25; 95% CI 0.23 to 0.27), atrial fibrillation (OR: 0.60; 95% CI 0.51 to 0.71), diabetes (OR: 0.76; 95% CI 0.71 to 0.81), dyslipidaemia (OR: 0.76; 95% CI 0.72 to 0.81), smoking (OR: 0.79; 95% CI 0.73 to 0.85) and overweight/obesity (OR: 0.90; 95% CI 0.86 to 0.93) had closer relationship with CHD. CONCLUSIONS: The distribution of risk factors for CHD and stroke were substantial differences. More specific prevention and control measures should be formulated according to the distribution differences of risk factors related to CVD.

A Robust Seven-Gene Signature Associated With Tumor Microenvironment to Predict Survival Outcomes of Patients With Stage III-IV Lung Adenocarcinoma.

BACKGROUND: Due to the relatively insidious early symptoms of lung adenocarcinoma (LUAD), most LUAD patients are at an advanced stage at the time of diagnosis and lose the best chance of surgical resection. Mounting evidence suggested that the tumor microenvironment (TME) was highly correlated with tumor occurrence, progress, and prognosis. However, TME in advanced LUAD remained to be studied and reliable prognostic signatures based on TME in advanced LUAD also had not been well-established. This study aimed to understand the cell composition and function of TME and construct a gene signature associated with TME in advanced LUAD. METHODS: The immune, stromal, and ESTIMATE scores of each sample from The Cancer Genome Atlas (TCGA) database were, respectively, calculated using an ESTIMATE algorithm. The LASSO and Cox regression model were applied to select prognostic genes and to construct a gene signature associated with TME. Two independent datasets from the Gene Expression Omnibus (GEO) were used for external validation. Twenty-two subsets of tumor-infiltrating immune cells (Tiics) were analyzed using the CIBERSORT algorithm. RESULTS: Favorable overall survival (OS) and progression-free survival (PFS) were found in patients with high immune score (p = 0.048 and p = 0.028; respectively) and stromal score (p = 0.024 and p = 0.025; respectively). Based on the immune and stromal scores, 453 differentially expressed genes (DEGs) were identified. Using the LASSO and Cox regression model, a seven-gene signature containing AFAP1L2, CAMK1D, LOXL2, PIK3CG, PLEKHG1, RARRES2, and SPP1 was identified to construct a risk stratification model. The OS and PFS of the high-risk group were significantly worse than that of the low-risk group (p < 0.001 and p < 0.001; respectively). The receiver operating characteristic (ROC) curve analysis confirmed the good potency of the seven-gene signature. Similar findings were validated in two independent cohorts. In addition, the proportion of macrophages M2 and Tregs was higher in high-risk patients (p = 0.041 and p = 0.022, respectively). CONCLUSION: Our study established and validated a seven-gene signature associated with TME, which might serve as a prognosis stratification tool to predict survival outcomes of advanced LUAD patients. In addition, macrophages M2 polarization may lead to worse prognosis in patients with advanced LUAD.

Identification of a Prognostic Signature Model with Tumor Microenvironment for predicting Disease-free Survival after Radical Prostatectomy.

Background: The tumor microenvironment (TME) and immune checkpoint inhibitors have been shown to promote active immune responses through different mechanisms. We attempted to identify the important prognostic genes and prognostic characteristics related to TME in prostate cancer (PCa). Methods: The gene transcriptome profiles and clinical information of PCa patients were obtained from The Cancer Genome Atlas (TCGA) database, and the immune and stromal scores were calculated by the ESTIMATE algorithm. We evaluated the prognostic value of the risk score (RS) model based on univariate Cox analysis and least absolute shrinkage and selection operation (LASSO) Cox regression analysis and established a nomogram to predict disease-free survival (DFS) in PCa patients. The GSE70768 dataset was utilized for external validation. Twenty-two subsets of tumor-infiltrating immune cells were analyzed using the CIBERSORT algorithm. Results: In this study, the patients with higher immune/stromal scores were associated with a worse DFS, higher Gleason score, and higher pathological T stage. Based on the immune and stromal scores, 515 differentially expressed genes (DEGs) were identified. The univariate Cox and LASSO Cox regression models were employed to select 18 DEGs from 515 DEGs and construct an RS model. The DFS of the high-RS group was significantly lower than that of the low-RS group (P<0.001). The AUCs for the 1-year, 3-year and 5-year DFS rates in the RS model were 0.890, 0.877 and 0.841, respectively. A nomogram of DFS was established based on the RS and Gleason score, and the AUCs for the 1-year, 3-year and 5-year DFS rates in the nomogram were 0.907, 0.893, and 0.872, respectively. These results were further validated in the GSE70768 dataset. In addition, the proportion of Tregs was determined to be higher in high-RS patients (P<0.05), and the expression levels of five immune checkpoints (CTLA-4, PD-1, LAG-3, TIM-3 and TIGIT) were observed to be higher in high-RS patients (P<0.05). Conclusions: Our study established and validated an 18-gene prognostic signature model associated with TME, which might serve as a prognosis stratification tool to predict DFS in PCa patients after radical prostatectomy.

Association of changes in waist circumference with cardiovascular disease and all-cause mortality among the elderly Chinese population: a retrospective cohort study.

BACKGROUND: To examine the association of baseline waist circumference (WC) and changes in WC with cardiovascular disease (CVD) and all-cause mortality among elderly people. METHODS: A total of 30,041 eligible participants were included from a retrospective cohort in China. The same questionnaire, anthropometric and laboratory measurements were performed at baseline (2010) and the first follow-up (2013). The percent change in WC between baseline and the first follow-up was calculated to evaluate three years change of WC. We collected the occurrence of CVD and all-cause death from the first follow-up to December 31, 2018. Restricted cubic splines and Cox proportional-hazards regression models were used to evaluate the relationship between baseline WC/ changes in WC and mortality. RESULTS: The dose-response relationships between baseline WC and CVD mortality were U- or J-shaped. In low WC group, compared with stable group, the fully adjusted hazard ratio (aHR) for CVD mortality was 1.60 (95% CI: 1.24-2.06) in WC gain group among men. In normal WC group, the CVD mortality risk increased with WC gain (men: aHR = 1.86, 95% CI: 1.36-2.56; women: aHR = 1.83, 95% CI: 1.29-2.58). In moderate-high WC group, the CVD mortality risk increased with WC gain (men: aHR = 1.76, 95% CI: 1.08-2.88; women: aHR = 1.46, 95% CI: 1.04-2.05) and risk decreased with WC loss (men: aHR = 0.54, 95% CI: 0.30-0.98; women: aHR = 0.59, 95% CI: 0.37-0.96). CONCLUSIONS: For the elderly population, WC gain may increase CVD mortality risk regardless of baseline WC, whereas WC reduction could decrease the risk only in the moderate-high WC group.

Trajectories of body mass index (BMI) and hypertension risk among middle-aged and elderly Chinese people.

This study aimed to identify heterogeneity in BMI trajectories and evaluate the impact of BMI trajectories on the risk of hypertension in middle-aged and elderly Chinese people. After data screening, 28, 706 residents' e-health records from 2010 to 2018, including basic personal information, lifestyle and health, were finally included in this population-based longitudinal study. By latent class growth modeling, we identified 12 BMI trajectories: "underweight-increase I (A1)" and "underweight-increase II (A2)"; "normal weight-stable (B1)", "normal weight-decrease (B2)", "normal weight-increase I (B3)" and "normal weight-increase II (B4)"; "overweight-stable (C1)", "overweight-decrease (C2)" and "overweight-increase (C3)"; and "obese-stable I (D1)", "obese-decrease (D2)" and "obese-stable II (D3)". By Cox proportional hazards models, we found that the risk of hypertension in the BMI stable group was lower than that in the BMI increasing trajectory group and higher than that in the BMI decreasing group. For the underweight and normal weight groups, the risk of hypertension was related not only to the magnitude of BMI growth, but also to the rate of growth. For overweight and obesity groups, the risk of hypertension was higher in the high-level stable BMI group than in the low-level stable BMI group. Therefore, for underweight and normal weight people, weight growth and growth rate should be controlled; for overweight and obese people, health education or targeted weight loss exercise should be taken to reduce weight as much as possible to prevent hypertension.

Socioeconomic and Demographic Factors for Spousal Resemblance in Obesity Status in China.

INTRODUCTION: The purposes of this study were to explore the resemblance in the weight status within couples with different family contextual factors and analyze the influence of the level of overweight or obesity of a spouse on that of the other spouse. METHODS: The data were from the sixth National Health Service Survey of Henan Province in 2018. After screening, 7432 eligible couples were finally included. Socioeconomic and demographic factors were compared by the χ2 test or nonparametric test. The difference in the body mass index (BMI) of spouses was assessed by a t-test. The Pearson correlation coefficient and kappa value were used as indicators of consistency in weight status. A logistic regression analysis was used to further explore the effect of a spouse's level of overweight/obesity on that of the other spouse. RESULTS: The results show that the prevalence of overweight/obesity in couples aged 20 or older is 33.76%. The Pearson correlation coefficient of the BMI within couples was 0.102 (95% CI: 0.076-0.120). The kappa coefficients suggested a low resemblance in the weight status within couples (k = 0.049, 95% CI: 0.031-0.069). Besides, the influence of the overweight/obesity status of the wives on that of the husbands (odds ratio (OR) = 1.411, 95% CI: 1.309-1.521) was slightly higher than that of the husbands on that of the wives (OR = 1.404, 95% CI: 1.302-1.514). CONCLUSIONS: We found that there was a moderate but significant resemblance in the body weight status between spouses, especially elderly couples with a low education level in rural areas. Health education activities for couple interventions can have a good effect of intervention.