Household air pollution, adherence to a healthy lifestyle, and risk of cardiometabolic multimorbidity: Results from the China health and retirement longitudinal study

Insulin resistance assessed by estimated glucose disposal rate and risk of incident cardiovascular diseases among individuals without diabetes: findings from a nationwide, population based, prospective cohort study

BACKGROUND

Recent studies have suggested that insulin resistance (IR) contributes to the development of cardiovascular diseases (CVD), and the estimated glucose disposal rate (eGDR) is considered to be a reliable surrogate marker of IR. However, most existing evidence stems from studies involving diabetic patients, potentially overstating the effects of eGDR on CVD. Therefore, the primary objective of this study is to examine the relationship of eGDR with incidence of CVD in non-diabetic participants.

METHOD

The current analysis included individuals from the China Health and Retirement Longitudinal Study (CHARLS) who were free of CVD and diabetes mellitus but had complete data on eGDR at baseline. The formula for calculating eGDR was as follows: eGDR (mg/kg/min) = 21.158 - (0.09 × WC) - (3.407 × hypertension) - (0.551 × HbA1c) [WC (cm), hypertension (yes = 1/no = 0), and HbA1c (%)]. The individuals were categorized into four subgroups according to the quartiles (Q) of eGDR. Crude incidence rate and hazard ratios (HRs) with 95% confidence intervals (CIs) were computed to investigate the association between eGDR and incident CVD, with the lowest quartile of eGDR (indicating the highest grade of insulin resistance) serving as the reference. Additionally, the multivariate adjusted restricted cubic spine (RCS) was employed to examine the dose-response relationship.

RESULTS

We included 5512 participants in this study, with a mean age of 58.2 ± 8.8 years, and 54.1% were female. Over a median follow-up duration of 79.4 months, 1213 incident CVD cases, including 927 heart disease and 391 stroke, were recorded. The RCS curves demonstrated a significant and linear relationship between eGDR and all outcomes (all P for non-linearity > 0.05). After multivariate adjustment, the lower eGDR levels were founded to be significantly associated with a higher risk of CVD. Compared with participants with Q1 of eGDR, the HRs (95% CIs) for those with Q2 - 4 were 0.88 (0.76 - 1.02), 0.69 (0.58 - 0.82), and 0.66 (0.56 - 0.79). When assessed as a continuous variable, per 1.0-SD increase in eGDR was associated a 17% (HR: 0.83, 95% CI: 0.78 - 0.89) lower risk of CVD, with the subgroup analyses indicating that smoking status modified the association (P for interaction = 0.012). Moreover, the mediation analysis revealed that obesity partly mediated the association. Additionally, incorporating eGDR into the basic model considerably improve the predictive ability for CVD.

CONCLUSION

A lower level of eGDR was found to be associated with increased risk of incident CVD among non-diabetic participants. This suggests that eGDR may serve as a promising and preferable predictor and intervention target for CVD.

Impact of ambient air pollution on colorectal cancer risk and survival: insights from a prospective cohort and epigenetic Mendelian randomization study

BACKGROUND

This study investigates the associations between air pollution and colorectal cancer (CRC) risk and survival from an epigenomic perspective.

METHODS

Using a newly developed Air Pollutants Exposure Score (APES), we utilized a prospective cohort study (UK Biobank) to investigate the associations of individual and combined air pollution exposures with CRC incidence and survival, followed by an up-to-date systematic review with meta-analysis to verify the associations. In epigenetic two-sample Mendelian randomization analyses, we examine the associations between genetically predicted DNA methylation related to air pollution and CRC risk. Further genetic colocalization and gene-environment interaction analyses provided different insights to disentangle pathogenic effects of air pollution via epigenetic modification.

FINDINGS

During a median 12.97-year follow-up, 5767 incident CRC cases among 428,632 participants free of baseline CRC and 533 deaths in 2401 patients with CRC were documented in the UK Biobank. A higher APES score was associated with an increased CRC risk (HR, 1.03, 95% CI = 1.01-1.06; P = 0.016) and poorer survival (HR, 1.13, 95% CI = 1.03-1.23; P = 0.010), particularly among participants with insufficient physical activity and ever smokers (Pinteraction > 0.05). A subsequent meta-analysis of seven observational studies, including UK Biobank data, corroborated the association between PM2.5 exposure (per 10 μg/m3 increment) and elevated CRC risk (RR,1.42, 95% CI = 1.12-1.79; P = 0.004; I2 = 90.8%). Genetically predicted methylation at PM2.5-related CpG site cg13835894 near TMBIM1/PNKD and cg16235962 near CXCR5, and NO2-related cg16947394 near TMEM110 were associated with an increased CRC risk. Gene-environment interaction analysis confirmed the epigenetic modification of aforementioned CpG sites with CRC risk and survival.

INTERPRETATION

Our study suggests the association between air pollution and CRC incidence and survival, underscoring the possible modifying roles of epigenomic factors. Methylation may partly mediate pathogenic effects of air pollution on CRC, with annotation to epigenetic alterations in protein-coding genes TMBIM1/PNKD, CXCR5 and TMEM110.

FUNDING

Xue Li is supported by the Natural Science Fund for Distinguished Young Scholars of Zhejiang Province (LR22H260001), the National Nature Science Foundation of China (No. 82204019) and Healthy Zhejiang One Million People Cohort (K-20230085). ET is supported by a Cancer Research UK Career Development Fellowship (C31250/A22804). MGD is supported by the MRC Human Genetics Unit Centre Grant (U127527198).

The role of lifestyle in the association between long-term ambient air pollution exposure and cardiovascular disease: a national cohort study in China

BACKGROUND

Cardiovascular disease (CVD) caused by air pollution poses a considerable burden on public health. We aim to examine whether lifestyle factors mediate the associations of air pollutant exposure with the risk of CVD and the extent of the interaction between lifestyles and air pollutant exposure regarding CVD outcomes.

METHODS

We included 7000 participants in 2011-2012 and followed up until 2018. The lifestyle evaluation consists of six factors as proxies, including blood pressure, blood glucose, blood lipids, body mass index, tobacco exposure, and physical activity, and the participants were categorized into three lifestyle groups according to the number of ideal factors (unfavorable, 0-1; intermediate, 2-4; and favorable, 5-6). Satellite-based spatiotemporal models were used to estimate exposure to ambient air pollutants (including particles with diameters ≤ 1.0 μm [PM1], ≤ 2.5 μm [PM2.5], ≤ 10 μm [PM10], nitrogen dioxide [NO2], and ozone [O3]). Cox regression models were used to examine the associations between air pollutant exposure, lifestyles and the risk of CVD. The mediation and modification effects of lifestyle categories on the association between air pollutant exposure and CVD were analyzed.

RESULTS

After adjusting for covariates, per 10 μg/m3 increase in exposure to PM1 (HR: 1.09, 95% CI: 1.05-1.14), PM2.5 (HR: 1.04, 95% CI: 1.00-1.08), PM10 (HR: 1.05, 95% CI: 1.03-1.08), and NO2 (HR: 1.11, 95% CI: 1.05-1.18) was associated with an increased risk of CVD. Adherence to a healthy lifestyle was associated with a reduced risk of CVD compared to an unfavorable lifestyle (HR: 0.65, 95% CI: 0.56-0.76 for intermediate lifestyle and HR: 0.41, 95% CI: 0.32-0.53 for favorable lifestyle). Lifestyle played a significant partial mediating role in the contribution of air pollutant exposure to CVD, with the mediation proportion ranging from 7.4% for PM10 to 14.3% for PM2.5. Compared to an unfavorable lifestyle, the relative excess risk due to interaction for a healthier lifestyle to reduce the effect on CVD risk was - 0.98 (- 1.52 to - 0.44) for PM1, - 0.60 (- 1.05 to - 0.14) for PM2.5, - 1.84 (- 2.59 to - 1.09) for PM10, - 1.44 (- 2.10 to - 0.79) for NO2, and - 0.60 (- 1.08, - 0.12) for O3.

CONCLUSIONS

Lifestyle partially mediated the association of air pollution with CVD, and adherence to a healthy lifestyle could protect middle-aged and elderly people from the adverse effects of air pollution regarding CVD.

Household polluting cooking fuels and intrinsic capacity among older population: A harmonized nationwide analysis in India and China

BACKGROUNDS

Household polluting cooking fuels, as an important changeable behavior, are related to various detrimental health effects among the elderly. There is limited research on the association between polluting cooking fuel use and intrinsic capacity (IC) as an indicator of healthy aging. This study aimed to evaluate the above-mentioned association in India and China, where polluting cooking fuel use is common.

METHODS

We enrolled 33,803 participants aged ≥60 years from two nationally representative studies: the Longitudinal Aging Study in India and the China Health and Retirement Longitudinal Study. Polluting cooking fuel use was defined as a self-report of using wood, coal, kerosene, crop residue, or dung. IC was measured by five aspects, including locomotion, cognition, vitality, sensory, and psychological capacity. The random-effects mixed linear regression and logistic regression with population weighting were performed. Multivariable-adjusted model and propensity score were used to adjust for potential confounders.

RESULTS

A total of 47.54 % and 59.32 % of elderly adults reported primary cooking using polluting fuels in India and China, respectively. Using polluting cooking fuels was consistently associated with IC decline; particularly, cognitive capacity was the most susceptible domain. In India, participants using polluting fuels had a 1.062 (95 % confidence interval [CI]: 1.047-1.078) times risk for IC deficits, whereas more prominent results were observed in China (odds ratio [OR]: 2.040, 95 % CI: 1.642-2.533). Such harmful effects might be alleviated by transferring from polluting to clean fuels. Additionally, the duration of polluting fuel use was also positively associated with IC deficits.

CONCLUSION

This study provided substantial public implications on healthy aging for the elderly population at a global scale, strengthening the importance of health education and policy efforts to accelerate the transition from polluting to clean fuels.

Assessment of six surrogate insulin resistance indexes for predicting cardiometabolic multimorbidity incidence in Chinese middle-aged and older populations: Insights from the China health and retirement longitudinal study

AIMS

Insulin resistance (IR) is associated with cardiometabolic multimorbidity (CMM). We aimed to explore the predictive value of six surrogate IR indexes-Chinese visceral adiposity index (CVAI), lipid accumulation product (LAP), triglyceride-glucose (TyG), atherogenic index of plasma (AIP), TyG-body mass index (TyGBMI), and TyG-waist circumference (TyGwaist)-to establish the CMM incidence in Chinese middle-aged and older populations.

MATERIAL AND METHODS

To estimate the odds ratio (OR) with a 95% confidence interval (95% CI) for incident CMM using six surrogates, we analysed data from the China Health and Retirement Longitudinal Study using multivariate logistic regression models. The nonlinear dose-response correlation was evaluated using restricted cubic spline analysis; predictive performance was assessed using receiver operator characteristic curves.

RESULTS

Among 6451 eligible participants, 268 (4.2%) developed CMM during the 4-year follow-up period. The ORs (95% CI) for incident CMM increased with increasing CVAI quartiles (Q) [Q2: 1.71, 1.03-2.90; Q3: 2.72, 1.70-4.52; Q4: 5.16, 3.29-8.45; all p < 0.05] after full adjustment, with Q1 as the reference. Other indexes yielded similar results. These associations remained significant in individuals with a normal body mass index. Notably, CVAI, AIP, and TyG exhibited a linear dose-response relationship with CMM (Pnonlinear ≥0.05), whereas LAP, TyGBMI, and TyGwaist displayed significant nonlinear correlations (Pnonlinear <0.05). The area under the curve for the CVAI (0.691) was significantly superior to that of other indexes (all p < 0.05).

CONCLUSIONS

The six IR surrogates were independently associated with CMM incidence. CVAI may be the most appropriate indicator for predicting CMM in middle-aged and older Chinese populations.

Lifestyle and clinical factors as predictive indicators of cardiometabolic multimorbidity in Chinese adults: Baseline findings of the Beijing Health Management Cohort (BHMC) study

BACKGROUND

Cardiometabolic multimorbidity (CMM) is increasing globally as a result of lifestyle changes and the aging population. Even though previous studies have examined risk factors associated with CMM, there is a shortage of prediction models that can accurately identify high-risk individuals for early prevention.

METHODS

In the baseline survey of the Beijing Health Management Cohort, a total of 77,752 adults aged 18 years or older were recruited from 2020 to 2021. Data on lifestyle factors, clinical profiles, and diagnoses of diabetes, coronary heart disease, and stroke were collected. Logistic regression models were used to identify risk factors for CMM. Nomograms were developed to estimate an individual's probability of CMM based on the identified risk factors. The performance of the model was evaluated using the area under the receiver operating characteristic curve (AUC).

RESULTS

In men, the top three risk factors for CMM were hypertension (OR: 3.52, 95 % CI: 2.97-4.18), eating very fast (3.43, 2.27-5.16), and dyslipidemia (2.59, 2.20-3.06). In women, hypertension showed the strongest association with CMM (3.62, 2.90-4.52), followed by night sleep duration less than 5 h per day (2.41, 1.67-3.50) and dyslipidemia (1.91, 1.58-2.32). The ORs for holding passive and depressed psychological traits were 1.49 (95%CI: 1.08-2.06) in men and 1.58 (1.03-2.43) in women. Prediction models incorporating these factors demonstrated good discrimination in the test set, with AUC 0.84 (0.83-0.86) for men and 0.90 (0.89-0.91) for women. The sex-specific nomograms were established based on selected predictors.

CONCLUSIONS

Modifiable lifestyle factors, metabolic health and psychological trait are associated with the risk of CMM. The developed prediction models and nomograms could facilitate early identification of individuals at high-risk of CMM.

Long-term influence of air pollutants on morbidity and all-cause mortality of cardiometabolic multi-morbidity: A cohort analysis of the UK Biobank participants

BACKGROUND

The effects of air pollutants on cardiometabolic diseases (CMDs) have been widely explored, whereas their influences on cardiometabolic multi-morbidity (CMM) were not clear.

METHODS

We employed the UK Biobank cohort (N = 317,160) to study the association between six air pollutants (PM2.5, PM10, PM2.5-10, PM2.5abs, NO2, and NOx) and four CMDs including type II diabetes (T2D), coronary artery disease (CAD), stroke and hypertension. CMM was defined as occurrence of two or more of the four diseases. Multi-state Cox models were performed to estimate hazard ratio (HR) and its 95% confidence interval (95%CI).

RESULTS

During a median follow-up of 12.8 years, 52,211 participants developed only one CMD, 15,446 further developed CMM, and 16,861 ultimately died. It was demonstrated that per interquartile range increase (IQR) increases in PM2.5, PM10, PM2.5-10, PM2.5abs, NO2, and NOx would increase 12% (9%-15%), 4% (1%-7%), 3% (1%-6%), 7% (4%-10%), 11% (8%-15%) and 10% (7%-13%) higher risk of developing one CMD from health baseline; 7% (2%-12%), 8% (3%-13%), 6% (2%-11%), 10% (5%-15%), 13% (7%-18%) and 10% (5%-15%) greater risk of occurring CMM from one CMD baseline; and 11% (-2%∼26%), 22% (7%-38%), 17% (3%-32%), 31% (16%-49%), 33% (17%-51%) and 32% (17%-50%) larger risk of causing death from CMM baseline, respectively.

CONCLUSIONS

We revealed that people living in areas with high air pollution suffered from higher hazard of CMD, CMM and all-cause mortality; our findings implied keeping clean air was an effective approach to prevent or mitigate initiation, progression, and death from healthy to CMDs and from CMDs to CMM.

Relationship of triglyceride-glucose index with cardiometabolic multi-morbidity in China: evidence from a national survey

BACKGROUND

Cardiometabolic multi-morbidity (CMM) is emerging as a global healthcare challenge and a pressing public health concern worldwide. Previous studies have principally focused on identifying risk factors for individual cardiometabolic diseases, but reliable predictors of CMM have not been identified. In the present study, we aimed to characterize the relationship of triglyceride-glucose (TyG) index with the incidence of CMM.

METHODS

We enrolled 7,970 participants from the China Health and Retirement Longitudinal Study (CHARLS) and placed them into groups according to quartile of TyG index. The endpoint of interest was CMM, defined as the presence of at least two of the following: stroke, heart disease, and diabetes mellitus. Cox regression models and multivariable-adjusted restricted cubic spline (RCS) curves were used to evaluate the relationship between TyG index and CMM.

RESULTS

In total, 638 (8.01%) incident cases of CMM were recorded among the participants who did not have CMM at baseline (2011) during a median follow-up of 84 months (interquartile range, 20‒87 months). The incidences of CMM for the participants in quartiles (Q) 1-4 of TyG index were 4.22%, 6.12%, 8.78%, and 12.60%, respectively. A fully adjusted Cox model showed that TyG index was closely associated with the incidence of CMM: the hazard ratio (HR) [95% confidence interval (CI)] for each 1.0-unit increment in TyG index for CMM was 1.54 (1.29-1.84); and the HRs (95% CIs) for Q3 and Q4 (Q1 as reference) of the TyG index for CMM were 1.41 (1.05-1.90) and 1.61 (1.18-2.20), respectively. The association of TyG index with the incidence of CMM was present in almost all the subgroups, and persisted in the sensitivity analyses and additional analyses. Multivariable-adjusted RCS analysis revealed a significant dose-response relationship of TyG index with the risk of CMM (overall P < 0.001; non-linear P = 0.129).

CONCLUSIONS

We found that a high TyG index is associated with a higher risk of incident CMM. This finding may have significance for clinical practice and facilitate the creation of a personalized prevention strategy that involves monitoring the TyG index.

Associations of healthy lifestyle and three latent socioeconomic status patterns with physical multimorbidity among middle-aged and older adults in China

BACKGROUND

Multimorbidity is an emerging global public health concern. However, complex associations of healthy lifestyle and socioeconomic status (SES) with multimorbidity have not been identified.

METHODS

This population-based prospective cohort study used data from four waves of the China Health and Retirement Longitudinal Study (CHARLS) to explore these relationships. Physical multimorbidity was measured using 12 non-communicable diseases. Latent class analysis (LCA) was conducted to determine the optimal SES patterns based on annual per-capita household expenditure, occupation, education level, and health insurance. The healthy lifestyle score (0-5) was constructed comprising information on smoking, drinking, physical activity, sleep, and body shape.

RESULTS

Of 17,708 participants in the CHARLS, 7776 were eligible for inclusion in our analysis (13.3% with high SES, 26.1% with medium SES, and 60.6% with low SES). Compared with high SES participants, those with low SES had higher risks of incident physical multimorbidity (OR 1.22, 95% CI 1.05, 1.42), which was competitively mediated by lifestyle (mediation proportion, -10.17%, 95% CI -19.12%, -1.23%). Significant interactions were observed between lifestyle factors and SES in patients with incident diabetes. Participants with low SES and no or one healthy lifestyle factor had a higher risk of incident physical multimorbidity than those with high SES and four to five healthy lifestyle factors (OR 2.19, 95% CI 1.57, 3.04).

CONCLUSION

Healthy lifestyles competitively mediate a fractional proportion of socioeconomic inequity in incident physical multimorbidity. Furthermore, healthy lifestyles were associated with lower multimorbidity risk in the SES subgroups, supporting the important role of lifestyle in reducing physical multimorbidity burden.

Traffic-related air pollution, adherence to healthy lifestyles, and risk of cognitive impairment: A nationwide population-based study

BACKGROUND

Traffic-related air pollution (TRAP) is a risk factor for cognitive function, whereas healthy lifestyles are associated with better cognition. We aimed to examine their joint effects on cognition among the Chinese elderly.

METHODS

The data from the Chinese Longitudinal Healthy Longevity Survey was used. Participants' cognitive performance was assessed by the Chinese version of the mini-mental state examination. Residential proximity to major roadways was obtained through self-report and categorized into five categories: > 300 m, 201-300 m, 101-200 m, 50-100 m, and < 50 m, serving as a surrogate for TRAP. Six lifestyle behaviors (smoking, drinking, exercise, body mass index, sleep duration, and dietary diversity) were taken into account to calculate healthy lifestyle scores. The scores ranged from zero to six and were then divided into three groups: healthy (5-6), intermediate (2-4), and unhealthy (0-1). Logistic regression models were applied to investigate the joint effects of TRAP and healthy lifestyle scores on cognition.

RESULTS

Compared to participants living < 50 m from major roadways and adopting an unhealthy lifestyle, those living > 300 m from major roadways and adopting a healthy lifestyle had a significantly decreased risk of cognitive impairment. Stratified analysis indicated that the associations between TRAP and cognitive impairment were more pronounced among participants adopting an unhealthy lifestyle compared to the participants adopting a healthy lifestyle.

CONCLUSIONS

TRAP may impair cognitive function, and its detrimental impacts may be lessened by healthy lifestyles.

Association between non-insulin-based insulin resistance indices and cardiovascular events in patients undergoing percutaneous coronary intervention: a retrospective study

BACKGROUND

Insulin resistance (IR) has been confirmed that getting involved in the pathophysiological process of cardiovascular diseases (CVD). Recently, increasing evidence suggests metabolic score for insulin resistance (METS-IR), triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio, triglyceride and glucose (TyG) index, triglyceride glucose-body mass (TyG-BMI) index are simple and reliable surrogates for IR. However, their abilities in predicting cardiovascular outcomes in patients undergoing percutaneous coronary intervention (PCI) are not well explored. Therefore, this study aimed to investigate the association and evaluate the predictive performance of each index.

METHODS

A total of 2533 consecutive participants undergoing PCI were included in this study, and the data from 1461 patients were used to determine the correlation of these non-insulin-based IR indices with major adverse cardiac and cerebrovascular events (MACCEs) via performing the multivariate logistic models and restricted cubic splines (RCS).

RESULTS

During a median of 29.8 months follow-up, 195 cases of 1461 patients experienced incident MACCEs. In the overall population, both univariate and multivariate logistic regression analyses indicated no statistically significant connection between these IR indices and MACCEs. Subgroup analyses revealed significant interactions between age subgroups and TyG-BMI index, as well as METS-IR, and between sex subgroups and TyG index. In elderly patients, per 1.0-SD increment in TyG-BMI index and METS-IR had a significant association with MACCEs, with odds ratios (ORs) [95% confidence interval (CI)] of 1.24 (1.02-1.50) and 1.27 (1.04-1.56), respectively (both P < 0.05). Moreover, in female patients, all the IR indices showed significant associations with MACCEs. Multivariable-adjusted RCS curves demonstrated a linear relationship between METS-IR and MACCEs in elderly and female patients, respectively. However, all the IR indices failed to enhance the predictive performance of the basic risk model for MACCEs.

CONCLUSION

All the four IR indices showed a significant association with MACCEs in female individuals, whereas only TyG-BMI index and METS-IR showed associations in elderly patients. Although the inclusion of these IR indices did not improve the predictive power of basic risk model in either female or elderly patients, METS-IR appears to be the most promising index for secondary prevention of MACCEs and risk stratification in patients undergoing PCI.

Solid Fuel Use and the Progression of Multimorbidity in Middle-Aged Chinese Participants: A Prospective Cohort Study

Objectives: This study aimed to examine the association of solid fuel use for cooking and heating with the progression of multimorbidity. Methods: A total of 5,437 participants from the China Health and Retirement Longitudinal Study were included. Multivariate logistic regression models were used to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) for the associations of the independent and joint effects of solid fuel use for cooking and heating with the progression of multimorbidity. Results: The proportion of participants reporting solid fuel use for both cooking and heating was 59.0% at baseline. Solid fuel use for both cooking and heating was associated with the progression of multimorbidity (adjusted OR: 1.42, 95% CI: 1.19-1.70), compared with clean fuel use for both. Conclusion: Solid fuel use for cooking and heating play an important role in the progression of multimorbidity. Therefore, solid fuel reduction should be considered in developing multimorbidity control and prevention programmes.