Impact of secondhand smoke exposure in former smokers on their subsequent risk of coronary heart disease: evidence from the population-based cohort of the Tehran Lipid and Glucose Study

Advancements in Cardiovascular Disease Research Affected by Smoking

The harmful substances in tobacco are widely recognized to exert a significant detrimental impact on human health, constituting one of the most substantial global public health threats to date. Tobacco usage also ranks among the principal contributors to cardiovascular ailments, with tobacco being attributed to up to 30% of cardiovascular disease-related deaths in various countries. Cardiovascular disease is influenced by many kinds of pathogenic factors, among them, tobacco usage has led to an increased year by year incidence of cardiovascular disease. Exploring the influencing factors of harmful substances in tobacco and achieving early prevention are important means to reduce the incidence of cardiovascular diseases and maintain health. This article provides a comprehensive review of the effects of smoking on health and cardiovascular diseases.

Association of secondhand smoke exposure with all-cause mortality and cardiovascular death in patients with hypertension: Insights from NHANES

BACKGROUND AND AIM

The impact of environmental chemical exposure on blood pressure (BP) is well-established. However, the relationship between secondhand smoke exposure (SHSE) and mortality in hypertensive patients in the general population remains unclear.

METHODS AND RESULTS

This cohort study included US adults in the National Health and Nutrition Examination Survey from 2007 to 2018. All-cause mortality and cause-specific mortality outcomes were determined by associating them with the National Death Index records. Cox proportional risk models were used to estimate hazard ratios (HRs) for all-cause mortality and cardiovascular disease (CVD) mortality, and 95% confidence intervals (CIs) for SHSE. The cohort included 10,760 adult participants. The mean serum cotinine level was 0.024 ng/mL. During a mean follow-up period of 76.9 months, there were 1729 deaths, including 469 cardiovascular disease deaths recorded. After adjusting for lifestyle factors, BMI, hypertension duration, medication use, and chronic disease presence, the highest SHSE was significantly associated with higher all-cause and CVD mortality.

CONCLUSIONS

This study demonstrates that higher SHSE is significantly associated with higher all-cause mortality and CVD mortality. Further research is necessary to elucidate the underlying mechanisms.

Health effects associated with exposure to secondhand smoke: a Burden of Proof study

Despite a gradual decline in smoking rates over time, exposure to secondhand smoke (SHS) continues to cause harm to nonsmokers, who are disproportionately children and women living in low- and middle-income countries. We comprehensively reviewed the literature published by July 2022 concerning the adverse impacts of SHS exposure on nine health outcomes. Following, we quantified each exposure-response association accounting for various sources of uncertainty and evaluated the strength of the evidence supporting our analyses using the Burden of Proof Risk Function methodology. We found all nine health outcomes to be associated with SHS exposure. We conservatively estimated that SHS increases the risk of ischemic heart disease, stroke, type 2 diabetes and lung cancer by at least around 8%, 5%, 1% and 1%, respectively, with the evidence supporting these harmful associations rated as weak (two stars). The evidence supporting the harmful associations between SHS and otitis media, asthma, lower respiratory infections, breast cancer and chronic obstructive pulmonary disease was weaker (one star). Despite the weak underlying evidence for these associations, our results reinforce the harmful effects of SHS on health and the need to prioritize advancing efforts to reduce active and passive smoking through a combination of public health policies and education initiatives.

The predictive accuracy of coronary heart disease risk prediction models in rural Northwestern China

Cardiovascular risk models developed may have limitations when applied to rural Chinese. This study validated and compared the Framingham Risk Score (FRS) and Prediction for Atherosclerotic Cardiovascular Disease Risk in China (PAR) models in predicting 10-year risk of coronary heart disease (CHD) in a rural cohort in Ningxia, China from 2008 to 2019. The FRS and PAR models were validated by estimating predicted events, C index, calibration χ2 and plots. 1381 adults without CHD at baseline were followed up for 9.75 years on average. 168 CHD cases were observed. The FRS and PAR underestimated CHD events by 22 % and 46 % for the total population, while overestimated for males by 152 % and 78 %, respectively. The C index was slightly higher for PAR than FRS. Both models showed weak calibration with chi-square values above 20 (p < 0.001). Bland-Altman plots indicated FRS predicted higher CHD risk than PAR, lacking consistency. Overall, FRS and PAR demonstrated limited performance in predicting 10-year CHD risk in this rural population. PAR had slightly better discrimination than FRS, but require further improvement in calibration and individual risk estimation to suit the rural population in Northwest China.

A gender specific risk assessment of coronary heart disease based on physical examination data

Large-scale screening for the risk of coronary heart disease (CHD) is crucial for its prevention and management. Physical examination data has the advantages of wide coverage, large capacity, and easy collection. Therefore, here we report a gender-specific cascading system for risk assessment of CHD based on physical examination data. The dataset consists of 39,538 CHD patients and 640,465 healthy individuals from the Luzhou Health Commission in Sichuan, China. Fifty physical examination characteristics were considered, and after feature screening, ten risk factors were identified. To facilitate large-scale CHD risk screening, a CHD risk model was developed using a fully connected network (FCN). For males, the model achieves AUCs of 0.8671 and 0.8659, respectively on the independent test set and the external validation set. For females, the AUCs of the model are 0.8991 and 0.9006, respectively on the independent test set and the external validation set. Furthermore, to enhance the convenience and flexibility of the model in clinical and real-life scenarios, we established a CHD risk scorecard base on logistic regression (LR). The results show that, for both males and females, the AUCs of the scorecard on the independent test set and the external verification set are only slightly lower (<0.05) than those of the corresponding prediction model, indicating that the scorecard construction does not result in a significant loss of information. To promote CHD personal lifestyle management, an online CHD risk assessment system has been established, which can be freely accessed at http://lin-group.cn/server/CHD/index.html .

Predictive Value of Cardiovascular Health Score for Health Outcomes in Patients with PCI: Comparison between Life's Simple 7 and Life's Essential 8

The American Heart Association recently published an updated algorithm for quantitative assessments of cardiovascular health (CVH) metrics, namely Life's Essential 8 (LE8). This study aimed to compare the predictive value between Life's Simple 7 (LS7) and LE8 and predict the likelihood of major adverse cardiac events (MACEs) in patients undergoing percutaneous coronary intervention (PCI) to determine the utility of the LE8 in predicting CVH outcomes. A total of 339 patients with acute coronary syndrome (ACS) who had undergone PCI were enrolled to assess the CVH scores using the LS7 and LE8. Multivariable Cox regression analysis was employed to evaluate the predictive value of the two different CVH scoring systems at 2 years for MACEs. Multivariable Cox regression analysis revealed that both the LS7 and LE8 scores were protective factors for MACEs (HR = 0.857, [95%CI: 0.78-0.94], HR = 0.964, [95%CI: 0.95-0.98]; p < 0.05, respectively). Receiver operator characteristic analysis indicated that the area under the curve (AUC) of LE8 was higher than that of LS7 (AUC: 0.662 vs. 0.615, p < 0.05). Lastly, in the LE8 score, diet, sleep health, serum glucose levels, nicotine exposure, and physical activity were found to be correlated with MACEs (HR = 0.985, 0.988, 0.993, 0.994, 0.994, respectively). Our study established that LE8 is a more reliable assessment system for CVH. This population-based prospective study reports that an unfavorable cardiovascular health profile is associated with MACEs. Future research is warranted to evaluate the effectiveness of optimizing diet, sleep health, serum glucose levels, nicotine exposure, and physical activity in reducing the risk of MACEs. In conclusion, our findings corroborated the predictive value of Life's Essential 8 and provided further evidence for the association between CVH and the risk of MACEs.

Association between tobacco smoking and heart disease in older adults: a cross-sectional study based on the Chinese Longitudinal Healthy Longevity Survey

Background

The association between the risk of heart disease and tobacco smoking has been studied in previous work, but there are arguments among various population. We aimed to investigate the association between heart disease incidence and smoking status among older adults.

Methods

A cross-sectional analysis was conducted with 10,891 older adults in the 2 most recent waves of the Chinese Longitudinal Healthy Longevity Survey (CLHLS), 2011-2014 and 2014-2018. The data included individual weighting variables to ensure they were nationally representative. The parameters consisted of age, sex, body mass index (BMI), smoking status, and disease history was collected. Smoking measures included current/former/never status, pack-years and the time to first cigarette. Heart disease included coronary artery disease, arrhythmias, heart failure, valve diseases and other heart conditions. Respondents with missed values were excluded. Multivariable logistic regression analyses were performed.

Results

Among the 10,006 respondents included in the analyses, 4,501 (44.9%) were men. The median age was 88 years old [interquartile range (IQR), 78-96]. A total of 6,713 respondents (67.1%) were nonsmokers, 1,695 respondents (16.9%) were former smokers, and 1,598 respondents (16.0%) were current smokers. The incidence of heart disease was significantly higher in smokers compared with nonsmokers (14.5% vs. 12.8%, P=0.018). Female smokers and those over 80 years old had higher morbidity than male smokers. After adjusting for sex, age, BMI, hypertension, diabetes, area of residency, alcohol status, and exercise status, smokers still had an increased risk of heart disease [odds ratio (OR) 1.29, 95% confidential interval (CI): 1.10-1.50, P=0.001]. The incidence of heart disease also increased with higher intensity of smoking for each additional pack-year (OR 1.01, 95% CI: 1.00-1.02, P=0.011).

Conclusions

For elderly adults, current or former smoking was largely associated with heart disease incidence, especially in females and those over 80 years old. These variables could be considered for inclusion in future heart disease risk prediction models.

Burden of current and past smoking across 28 European countries in 2017: A cross-sectional analysis

INTRODUCTION

Most studies use the prevalence of current smoking as an indicator to quantify the burden of smoking. However, length and intensity of smoking, as well as time since cessation for former smokers are also known to impact smoking-related health risks. The aim of this study was to quantify and compare the burden of smoking across the European Union (EU) using a range of smoking burden indicators.

METHODS

We conducted a cross-sectional analysis using data from the March 2017 Eurobarometer 87.1 (n=27901, people aged ≥15 years) in 28 European Union Member States (EU MS) and the Tobacco Control Scale. We defined five indicators of smoking burden including the prevalence of current and ever smoking, length of smoking, pack-years, and discounted pack-years, and ranked EU MS by each indicator. Two-level linear and logistic regressions were performed to assess the association between these indicators and sociodemographic and tobacco policy factors.

RESULTS

Wide variations across the EU countries were observed in all smoking burden indicators. While some MS ranked consistently high (e.g. Greece, France) or consistently low (e.g. Ireland, United Kingdom) in all indicators, we found substantial discrepancies in ranking depending on the indicator used for MS such as Malta, Denmark, Finland and the Netherlands. All indicators of smoking burden were lower among women and respondents without financial difficulties; however, the magnitude of those inequalities varied two-fold among the different indicators.

CONCLUSIONS

Using a range of smoking burden indicators can be more informative than relying on prevalence alone. Our analysis highlights the limitations of relying solely on prevalence of current smoking to estimate the burden of smoking and the potential value of more nuanced indicators. We recommend that multiple and more nuanced indicators that consider former smokers, intensity and duration of smoking should be utilized to monitor tobacco use and evaluate tobacco control policies.

Risk factors for incident cardiovascular events among adults in low- and middle-income countries: A systematic review and meta-analysis of prospective cohort studies

The relative contributions of risk factors for cardiovascular events at a population level has received little attention in low- and middle-income countries (LMICs). We estimated the population attributable fraction (PAF) of risk factors associated with incident cardiovascular events in LMICs. We searched six databases for relevant articles, supplemented with a manual search of reference lists. Articles included in the meta-analyses were those based on prospective community-based cohorts and incorporating adjusted hazard ratios (HR) or relative risks with 95% confidence intervals (95% CI) for associations between risk factors and a composite cardiovascular and/or stroke endpoint. Pooled HRs and 95% CI were calculated using the random effects model. We assessed heterogeneity using the I² test and study quality using the Newcastle-Ottawa Scale. We calculated the PAF of each associated risk factor. The protocol was registered in PROSPERO (CRD42019122741). We identified 18 cohorts from LMICs with 1,125,846 participants, 77,045 composite cardiovascular events and 42,216 strokes. Substantial proportions of incident cardiovascular events were attributable to hypertension (HR [95% CI], 2.23 [2.01-2.48], PAF = 28%); current smoking (1.44 [1.31-1.58], PAF = 10%); and diabetes mellitus (1.93 [1.67-2.23], PAF = 8%). Other risk factors identified included number of children, depression, bone mineral density, and air pollution. A substantial proportion of incident cardiovascular events were linked to traditional metabolic and behavioural modifiable risk factors. However, other novel risk factors also appear to contribute. Targeting of these established and novel risk factors has the potential to reduce the burden of CVD in LMICs.

Role of Air Pollution and rs10830963 Polymorphism on the Incidence of Type 2 Diabetes: Tehran Cardiometabolic Genetic Study

Diabetes mellitus (DM) is considered one of the leading health issues that are egregiously threatening human life throughout the world. Several epidemiological studies have examined the relationship of a particular matter < 10 μm (PM10) exposure and with type 2 diabetes mellitus (T2DM) prevalence and incidence. Accordingly, the current study is a study investigating the independent influence of air pollution (AP) and rs10830963 on the incidence of T2DM. A total number of 2428 adults over 20 years of age participated in a prospective cohort (TCGS) during a 9-year follow-up phase. The concentration of AP was measured, and the obtained values were considered the mean level in three previous years since the exposure concentration took the people living in that location. The COX regression model was employed to determine the influence of AP and rs10830963 on the incidence of T2DM in adjustment with covariate factors. Among the 392 T2DM, 230 cases (58.7%) were female diabetics, and 162 (41.3%) were male diabetics. According to the multivariable-adjusted model, exposure to PM10 (per 10 μm/m3), associated with the risk of T2DM, although just a borderline (p = 0.07) was found in the multivariable model (HR; 1.50, 95% CI; 1-2.32). The rs10830963 was directly associated with the incidence of diabetes, and the GG genotype increased the T2DM rate by 113% (more than two times) (HR; 2.134, 95% CI; 1.42-3.21, p ≤ 0.001) and GC increased it by 65% (HR; 1.65, 95% CI; 1.24-2.21, p ≤ 0.001). Long-term exposure to PM10 was associated with an increased risk of diabetes. Thus, it is suggested that the individuals with variant rs10830963 genotypes fall within a group susceptible to an increased risk of T2DM arising from AP.