The effects of health risk behaviors to excess mortality in the population with depression: A cohort study based on NHANES data.

BACKGROUND: The population with depression had a considerable excess mortality risk. This increased mortality may be attributed to the biological consequences of depression or the substantial prevalence of health risk behaviors (HRBs). This study aimed to quantify the combined effects of four major HRBs - smoking, excessive alcohol use, physical inactivity, and an unhealthy diet - on excess mortality among depressed individuals. METHODS: This study included 35,738 adults from the National Health and Nutrition Examination Survey 2005-06 to 2017-18, with mortality follow-up data censored through 2019. The standardized prevalence of HRBs was calculated for populations with and without depression. Poisson regression models were used to calculate the mortality rate ratio (MRR). Based on model adjusting for socio-demographic factors, the attenuation of MRR was determined after further adjustment for HRBs. RESULTS: A total of 3147 participants were identified as having depression. All HRBs showed a significantly higher prevalence among the population with depression. After adjusting for socio-demographic factors, depression was associated with 1.7 and 1.8 times higher all-cause and cardiovascular disease mortality rate, respectively. Further adjustment for all current HRBs resulted in a 21.9 % reduction in all-cause mortality rate and a 15.4 % decrease in cardiovascular disease mortality rate. LIMITATION: HRBs were reported at a single time point, and we are unable to demonstrate a causal effect. CONCLUSION: At least 1/5 of excess mortality for population with depression was attributable to HRBs. Efforts should be made to address HRBs among population with depression.

Association of national smoke-free policies with per-capita cigarette consumption and acute myocardial infarction mortality in Europe.

BACKGROUND: Evidence on the association between smoke-free policies and per-capita cigarette consumption and mortality due to acute myocardial infarction (AMI) in Europe is limited. Hence, we aimed to assess this association and to evaluate which factors influence it. METHODS: We performed an interrupted time series analysis, including 27 member states of the European Union and the UK, on per-capita cigarette consumption and AMI mortality.A multivariate meta-regression was used to assess the potential influence of other factors on the observed associations. RESULTS: Around half of the smoke-free policies introduced were associated with a level or slope change, or both, of per-capita cigarette consumption and AMI mortality (17 of 35). As for cigarette consumption, the strongest level reduction was observed for the smoking ban issued in 2010 in Poland (rate ratio (RR): 0.47; 95% CI: 0.41, 0.53). Instead, the largest level reduction of AMI mortality was observed for the intervention introduced in 2012 in Bulgaria (RR: 0.38; 95% CI: 0.34, 0.42).Policies issued more recently or by countries with a lower human development index were found to be associated with a larger decrease in per-capita cigarette consumption. In addition, smoking bans applying to bars had a stronger inverse association with both cigarette consumption and AMI mortality. CONCLUSIONS: The results of our study suggest that smoke-free policies are effective at reducing per-capita cigarette consumption and AMI mortality. It is extremely important to monitor and register data on tobacco, its prevalence and consumption to be able to tackle its health effects with concerted efforts.

New Estimates of Smoking-Attributable Mortality in the U.S. From 2020 Through 2035.

INTRODUCTION: The often-cited Centers for Disease Control and Prevention (CDC) estimate of 480,000 annual U.S. smoking-attributable deaths (SADs), including 439,000 first-hand smoke deaths, derives from 2005 to 2009 data. Since then, adult smoking prevalence has decreased by 40%, while the population has grown and the smoking population aged. An updated estimate is presented to determine whether the CDC figure remains accurate or has changed substantially. In addition, the likely annual smoking-related mortality toll is projected through 2035. METHODS: A well-established model of smoking prevalence and health effects is employed to estimate annual SADs among individuals exposed to first-hand smoke in the U.S. for two distinct periods: 2005-2009 and 2020-2035. The estimate for 2005-2009 serves as a benchmark to evaluate the reliability of the model's estimate in comparison to CDC's. The projections for 2020-2035 provide up-to-date figures for SADs, predicting how annual SADs are likely to change in the coming years. Data were collected between 2005 and 2020. The analysis was conducted in 2023. RESULTS: This study's estimate of 420,000 first-hand smoke deaths over 2005-2009 is 95.7% of CDC's estimate during the same period. The model projections indicate that SADs among individuals who currently smoke or formerly smoked have increased modestly since 2005-2009. Beginning in 2020, annual SADs will remain relatively stable at approximately 450,000 before starting to decline around 2030. CONCLUSIONS: These findings suggest that the CDC estimate of the annual mortality burden of smoking remains valid. Despite U.S. population growth and the aging of the smoking population, substantial reductions in smoking will finally produce a steady, if gradual, decline in SADs beginning around 2030.

Association of a healthy lifestyle with mortality in older people.

BACKGROUND: Unhealthy lifestyle behaviours such as smoking, high alcohol consumption, poor diet or low physical activity are associated with morbidity and mortality. Public health guidelines provide recommendations for adherence to these four factors, however, their relationship to the health of older people is less certain. METHODS: The study involved 11,340 Australian participants (median age 7.39 [Interquartile Range (IQR) 71.7, 77.3]) from the ASPirin in Reducing Events in the Elderly study, followed for a median of 6.8 years (IQR: 5.7, 7.9). We investigated whether a point-based lifestyle score based on adherence to guidelines for a healthy diet, physical activity, non-smoking and moderate alcohol consumption was associated with subsequent all-cause and cause-specific mortality. RESULTS: In multivariable adjusted models, compared to those in the unfavourable lifestyle group, individuals in the moderate lifestyle group (Hazard Ratio (HR) 0.73 [95% CI 0.61, 0.88]) and favourable lifestyle group (HR 0.68 [95% CI 0.56, 0.83]) had lower risk of all-cause mortality. A similar pattern was observed for cardiovascular related mortality and non-cancer/non-cardiovascular related mortality. There was no association of lifestyle with cancer-related mortality. CONCLUSIONS: In a large cohort of initially healthy older people, reported adherence to a healthy lifestyle is associated with reduced risk of all-cause and cause-specific mortality. Adherence to all four lifestyle factors resulted in the strongest protection.

Identifying best modelling practices for tobacco control policy simulations: a systematic review and a novel quality assessment framework.

BACKGROUND: Policy simulation models (PSMs) have been used extensively to shape health policies before real-world implementation and evaluate post-implementation impact. This systematic review aimed to examine best practices, identify common pitfalls in tobacco control PSMs and propose a modelling quality assessment framework. METHODS: We searched five databases to identify eligible publications from July 2013 to August 2019. We additionally included papers from Feirman et al for studies before July 2013. Tobacco control PSMs that project tobacco use and tobacco-related outcomes from smoking policies were included. We extracted model inputs, structure and outputs data for models used in two or more included papers. Using our proposed quality assessment framework, we scored these models on population representativeness, policy effectiveness evidence, simulated smoking histories, included smoking-related diseases, exposure-outcome lag time, transparency, sensitivity analysis, validation and equity. FINDINGS: We found 146 eligible papers and 25 distinct models. Most models used population data from public or administrative registries, and all performed sensitivity analysis. However, smoking behaviour was commonly modelled into crude categories of smoking status. Eight models only presented overall changes in mortality rather than explicitly considering smoking-related diseases. Only four models reported impacts on health inequalities, and none offered the source code. Overall, the higher scored models achieved higher citation rates. CONCLUSIONS: While fragments of good practices were widespread across the reviewed PSMs, only a few included a 'critical mass' of the good practices specified in our quality assessment framework. This framework might, therefore, potentially serve as a benchmark and support sharing of good modelling practices.

Combining machine learning and conventional statistical approaches for risk factor discovery in a large cohort study.

We present a simple and efficient hypothesis-free machine learning pipeline for risk factor discovery that accounts for non-linearity and interaction in large biomedical databases with minimal variable pre-processing. In this study, mortality models were built using gradient boosting decision trees (GBDT) and important predictors were identified using a Shapley values-based feature attribution method, SHAP values. Cox models controlled for false discovery rate were used for confounder adjustment, interpretability, and further validation. The pipeline was tested using information from 502,506 UK Biobank participants, aged 37-73 years at recruitment and followed over seven years for mortality registrations. From the 11,639 predictors included in GBDT, 193 potential risk factors had SHAP values ≥ 0.05, passed the correlation test, and were selected for further modelling. Of the total variable importance summed up, 60% was directly health related, and baseline characteristics, sociodemographics, and lifestyle factors each contributed about 10%. Cox models adjusted for baseline characteristics, showed evidence for an association with mortality for 166 out of the 193 predictors. These included mostly well-known risk factors (e.g., age, sex, ethnicity, education, material deprivation, smoking, physical activity, self-rated health, BMI, and many disease outcomes). For 19 predictors we saw evidence for an association in the unadjusted but not adjusted analyses, suggesting bias by confounding. Our GBDT-SHAP pipeline was able to identify relevant predictors 'hidden' within thousands of variables, providing an efficient and pragmatic solution for the first stage of hypothesis free risk factor identification.

Association between low density lipoprotein cholesterol and all-cause mortality: results from the NHANES 1999-2014.

The association between low density lipoprotein cholesterol (LDL-C) and all-cause mortality has been examined in many studies. However, inconsistent results and limitations still exist. We used the 1999-2014 National Health and Nutrition Examination Survey (NHANES) data with 19,034 people to assess the association between LDL-C level and all-cause mortality. All participants were followed up until 2015 except those younger than 18 years old, after excluding those who died within three years of follow-up, a total of 1619 deaths among 19,034 people were included in the analysis. In the age-adjusted model (model 1), it was found that the lowest LDL-C group had a higher risk of all-cause mortality (HR 1.708 [1.432-2.037]) than LDL-C 100-129 mg/dL as a reference group. The crude-adjusted model (model 2) suggests that people with the lowest level of LDL-C had 1.600 (95% CI [1.325-1.932]) times the odds compared with the reference group, after adjusting for age, sex, race, marital status, education level, smoking status, body mass index (BMI). In the fully-adjusted model (model 3), people with the lowest level of LDL-C had 1.373 (95% CI [1.130-1.668]) times the odds compared with the reference group, after additionally adjusting for hypertension, diabetes, cardiovascular disease, cancer based on model 2. The results from restricted cubic spine (RCS) curve showed that when the LDL-C concentration (130 mg/dL) was used as the reference, there is a U-shaped relationship between LDL-C level and all-cause mortality. In conclusion, we found that low level of LDL-C is associated with higher risk of all-cause mortality. The observed association persisted after adjusting for potential confounders. Further studies are warranted to determine the causal relationship between LDL-C level and all-cause mortality.

Understanding longevity in Hong Kong: a comparative study with long-living, high-income countries.

BACKGROUND: Since 2013, Hong Kong has sustained the world's highest life expectancy at birth-a key indicator of population health. The reasons behind this achievement remain poorly understood but are of great relevance to both rapidly developing and high-income regions. Here, we aim to compare factors behind Hong Kong's survival advantage over long-living, high-income countries. METHODS: Life expectancy data from 1960-2020 were obtained for 18 high-income countries in the Organisation for Economic Co-operation and Development from the Human Mortality Database and for Hong Kong from Hong Kong's Census and Statistics Department. Causes of death data from 1950-2016 were obtained from WHO's Mortality Database. We used truncated cross-sectional average length of life (TCAL) to identify the contributions to survival differences based on 263 million deaths overall. As smoking is the leading cause of premature death, we also compared smoking-attributable mortality between Hong Kong and the high-income countries. FINDINGS: From 1979-2016, Hong Kong accumulated a substantial survival advantage over high-income countries, with a difference of 1·86 years (95% CI 1·83-1·89) for males and 2·50 years (2·47-2·53) for females. As mortality from infectious diseases declined, the main contributors to Hong Kong's survival advantage were lower mortality from cardiovascular diseases for both males (TCAL difference 1·22 years, 95% CI 1·21-1·23) and females (1·19 years, 1·18-1·21), cancer for females (0·47 years, 0·45-0·48), and transport accidents for males (0·27 years, 0·27-0·28). Among high-income populations, Hong Kong recorded the lowest cardiovascular mortality and one of the lowest cancer mortalities in women. These findings were underpinned by the lowest absolute smoking-attributable mortality in high-income regions (39·7 per 100 000 in 2016, 95% CI 34·4-45·0). Reduced smoking-attributable mortality contributed to 50·5% (0·94 years, 0·93-0·95) of Hong Kong's survival advantage over males in high-income countries and 34·8% (0·87 years, 0·87-0·88) of it in females. INTERPRETATION: Hong Kong's leading longevity is the result of fewer diseases of poverty while suppressing the diseases of affluence. A unique combination of economic prosperity and low levels of smoking with development contributed to this achievement. As such, it offers a framework that could be replicated through deliberate policies in developing and developed populations globally. FUNDING: Early Career Scheme (RGC ECS Grant #27602415), Research Grants Council, University Grants Committee of Hong Kong.

Smoking Behavior and Prognosis After Colorectal Cancer Diagnosis: A Pooled Analysis of 11 Studies.

Background: Smoking has been associated with colorectal cancer (CRC) incidence and mortality in previous studies, but current evidence on smoking in association with survival after CRC diagnosis is limited. Methods: We pooled data from 12 345 patients with stage I-IV CRC from 11 epidemiologic studies in the International Survival Analysis in Colorectal Cancer Consortium. Cox proportional hazards regression models were used to evaluate the associations of prediagnostic smoking behavior with overall, CRC-specific, and non-CRC-specific survival. Results: Among 12 345 patients with CRC, 4379 (35.5%) died (2515 from CRC) over a median follow-up time of 7.5 years. Smoking was strongly associated with worse survival in stage I-III patients, whereas no association was observed among stage IV patients. Among stage I-III patients, clear dose-response relationships with all survival outcomes were seen for current smokers. For example, current smokers with 40 or more pack-years had statistically significantly worse overall, CRC-specific, and non-CRC-specific survival compared with never smokers (hazard ratio [HR] =1.94, 95% confidence interval [CI] =1.68 to 2.25; HR = 1.41, 95% CI = 1.12 to 1.78; and HR = 2.67, 95% CI = 2.19 to 3.26, respectively). Similar associations with all survival outcomes were observed for former smokers who had quit for less than 10 years, but only a weak association with non-CRC-specific survival was seen among former smokers who had quit for more than 10 years. Conclusions: This large consortium of CRC patient studies provides compelling evidence that smoking is strongly associated with worse survival of stage I-III CRC patients in a clear dose-response manner. The detrimental effect of smoking was primarily related to noncolorectal cancer events, but current heavy smoking also showed an association with CRC-specific survival.

Lipid-Lowering Drug Use and Cancer Incidence and Mortality in the ARIC Study.

Background: Lipid-lowering drugs, particularly statins, are associated with reduced incidence of certain cancers in some studies. Associations with cancer mortality are not well studied, and whether associations are similar across race is unknown. Methods: We conducted a prospective analysis of 12 997 cancer-free participants in the Atherosclerosis Risk in Communities Study who were never users at visit 1 (1987-1989). Ever use, duration of use, and age at first use were modeled as time-dependent variables using Cox regression to estimate associations with total, obesity- and smoking-associated, bladder, breast, colorectal, lung, and prostate cancer incidence and mortality. Results: We ascertained 3869 cancer cases and 1661 cancer deaths in 237 999 or more person-years. At 6 years of follow-up, 70.8% of lipid-lowering drug use was a statin. Compared with never use, ever use was associated with lower total, obesity- and smoking-associated cancer mortality and with colorectal cancer mortality (hazard ratio [HR] = 0.50, 95% confidence interval [CI] = 0.32 to 0.79) and incidence (HR = 0.69, 95% CI = 0.53 to 0.92). Inverse associations were consistent by sex and race. Shorter-term use was associated with bladder cancer incidence in men (<10 years: HR = 1.67, 95% CI = 1.02 to 2.73). First use at age 60 years or older was inversely associated with: total mortality, obesity- and smoking-associated mortality, and colorectal cancer mortality; and total incidence, obesity- and smoking-associated incidence, and breast, colorectal, and prostate cancer incidence. Conclusions: This study provides additional evidence for inverse associations between lipid-lowering drug use and cancer incidence and mortality but a positive association with bladder cancer incidence in men. Evaluation of the impact of chemoprevention strategies that include lipid-lowering drugs on population-level cancer burden is needed.

Factors associated with mortality in rheumatoid arthritis-associated interstitial lung disease: a systematic review and meta-analysis.

BACKGROUND: Interstitial lung disease (ILD) is a common and potentially life-threatening complication for rheumatoid arthritis (RA) patients. However, there is a lack of clear prognostic factors in rheumatoid arthritis-associated interstitial lung disease (RA-ILD) patients. The purpose of this study was to complete a systematic review and meta-analysis of the factors associated with mortality in RA-ILD patients. METHODS: Medline, EMBASE and the Cochrane Library were searched up to September 1, 2020. The Newcastle-Ottawa Scale (NOS) was applied to assess the methodological quality of the eligible studies. Study characteristics and magnitude of effect sizes were extracted. Then, pooled hazard ratios (HRs) with the corresponding 95% confidence intervals (CIs) and pooled risk ratios (RRs) with 95% CIs were calculated to assess the factors associated with mortality in RA-ILD. RESULTS: Twenty-three of 3463 articles were eligible, and ten factors associated with mortality for RA-ILD were evaluated in the meta-analysis. Older age (HRs = 1.04, 95% CI 1.03-1.05), male sex (HRs = 1.44, 95% CI 1.21-1.73), having a smoking history (HRs = 1.42, 95% CI 1.03-1.96), lower diffusing capacity of the lung for carbon monoxide (DLCO)% predicted (HRs = 0.98, 95% CI 0.97-1.00), forced vital capacity (FVC)% predicted (HRs = 0.99, 95% CI 0.98-1.00), composite physiological index (CPI) (HRs = 1.04, 95% CI 1.02-1.06), usual interstitial pneumonia (UIP) pattern on HRCT (HRs = 1.88, 95% CI 1.14-3.10 and RRs = 1.90, 95% CI 1.50-2.39), emphysema presence (HRs = 2.31, 95% CI 1.58-3.39), and acute exacerbation of ILD (HRs = 2.70, 95% CI 1.67-4.36) were associated with increased mortality in RA-ILD, whereas rheumatoid factor (RF) positive status was not associated. CONCLUSIONS: Through this systematic review and meta-analysis, we found that older age, male sex, smoking history, higher CPI, lower DLCO% predicted, lower FVC% predicted, UIP pattern on HRCT, emphysema presence and acute exacerbation of ILD were associated with an increased risk of mortality in RA-ILD.

Variations in disease burden of laryngeal cancer attributable to alcohol use and smoking in 204 countries or territories, 1990-2019.

BACKGROUND: Alcohol consumption and smoking are the leading risk factors for laryngeal cancer (LC). Understanding the variations in disease burden of LC attributable to alcohol use and smoking is critical for LC prevention. METHODS: Disease burden data of LC were retrieved from the Global Burden of Disease Study 2019. We used estimated average percentage change (EAPC) to measure the temporal trends of the age-standardized mortality rate (ASMR) of LC. RESULTS: Globally, while the ASMR of LC decreased by 1.49% (95% CI, 1.41-1.57%) per year between 1990 and 2019, the number of deaths from LC has increased 41.0% to 123.4 thousand in 2019. In 2019, 19.4 and 63.5% of total LC-related deaths were attributable to alcohol use and smoking worldwide, respectively. The ASMR of alcohol- and smoking-related LC decreased by 1.78 and 1.93% per year, whereas the corresponding death number has increased 29.2 and 25.1% during this period, respectively. The decreasing trend was more pronounced in developed countries. In some developing countries, such as Guinea and Mongolia, the LC mortality has shown an unfavorable trend. CONCLUSION: The ubiquitous decrease in LC mortality was largely attributed to the smoking control and highlighted the importance of smoking control policies. However, the disease burden of LC remained in increase and more effective strategies are needed to combat the global increase of alcohol consumption.

Low density lipoprotein cholesterol and all-cause mortality rate: findings from a study on Japanese community-dwelling persons.

BACKGROUND: Low-density lipoprotein cholesterol (LDL-C) independently impacts aging-related health outcomes and plays a critical role in cardiovascular diseases (CVDs). However, there are limited predictive data on all-cause mortality, especially for the Japanese community population. In this study, it was examined whether LDL-C is related to survival prognosis based on 7 or 10 years of follow-up. METHODS: Participants included 1610 men (63 ± 14 years old) and 2074 women (65 ± 12 years old) who participated in the Nomura cohort study conducted in 2002 (first cohort) and 2014 (second cohort) and who continued throughout the follow-up periods (follow-up rates: 94.8 and 98.0%). Adjusted relative risk estimates were obtained for all-cause mortality using a basic resident register. The data were analyzed by a Cox regression with the time variable defined as the length between the age at the time of recruitment and that at the end of the study (the age of death or censoring), and risk factors including gender, age, body mass index (BMI), presence of diabetes, lipid levels, renal function, serum uric acid levels, blood pressure, and history of smoking, drinking, and CVD. RESULTS: Of the 3684 participants, 326 (8.8%) were confirmed to be deceased. Of these, 180 were men (11.2% of all men) and 146 were women (7.0% of all women). Lower LDL-C levels, gender (male), older age, BMI under 18.5 kg/m2, and the presence of diabetes were significant predictors for all-cause mortality. Compared with individuals with LDL-C levels of 144 mg/dL or higher, the multivariable-adjusted Hazard ratio (and 95% confidence interval) for all-cause mortality was 2.54 (1.58-4.07) for those with LDL-C levels below 70 mg/dL, 1.71 (1.15-2.54) for those with LDL-C levels between 70 mg/dL and 92 mg/dL, and 1.21 (0.87-1.68) for those with LDL-C levels between 93 mg/dL and 143 mg/dL. This association was particularly significant among participants who were male (P for interaction = 0.039) and had CKD (P for interaction = 0.015). CONCLUSIONS: There is an inverse relationship between LDL-C levels and the risk of all-cause mortality, and this association is statistically significant.

Future life expectancy in Europe taking into account the impact of smoking, obesity, and alcohol.

Introduction: In Europe, women can expect to live on average 82 years and men 75 years. Forecasting how life expectancy will develop in the future is essential for society. Most forecasts rely on a mechanical extrapolation of past mortality trends, which leads to unreliable outcomes because of temporal fluctuations in the past trends due to lifestyle 'epidemics'. Methods: We project life expectancy for 18 European countries by taking into account the impact of smoking, obesity, and alcohol on mortality, and the mortality experiences of forerunner populations. Results: We project that life expectancy in these 18 countries will increase from, on average, 83.4 years for women and 78.3 years for men in 2014 to 92.8 years for women and 90.5 years for men in 2065. Compared to others (Lee-Carter, Eurostat, United Nations), we project higher future life expectancy values and more realistic differences between countries and sexes. Conclusions: Our results imply longer individual lifespans, and more elderly in society. Funding: Netherlands Organisation for Scientific Research (NWO) (grant no. 452-13-001).

On average, in Europe, men can currently expect to live till the age of 75 and women until they are 82. But what will their lifespans be in the next decades? Reliable answers to this question are essential to help governments plan for future health care and social security costs. While medical improvements are likely to further extend lifespans, lifestyle factors can result in temporal distortions of this trend. Yet, most estimates of future life expectancy fail to consider changing lifestyles, as they only use past mortality trends in their calculations. This can make these projections unreliable: for example, increases in smoking rates among Northern and Western European men led to stagnating male life expectancies in the 1950s and 1960s, but these picked up again after smoking declined. The same pattern is showing for women, except it is lagging as they took up smoking later than men. Based simply on the extrapolation of past mortality trends, current projection models fail to consider the past and predicted modifications of life expectancy trends prompted by changing rates of health behaviours ­ such as increases followed by (anticipated) declines in alcohol consumption and obesity rates, similar to what was observed with smoking. To produce a more reliable forecast, Janssen et al. incorporated trends in smoking, obesity, and alcohol use into life expectancy projections for 18 European countries. The predictions suggest that life expectancy for women in these countries will increase from 83.4 years in 2014 to 92.8 years in 2065. For men, it will also go up, from 78.3 to 90.5 years. In the future, this integrative approach may help to track the effects of health-behaviour related prevention policies on life expectancy, and allow scientists to account for changes caused by the COVID-19 pandemic. In the meantime, these estimates are higher than those obtained using more traditional methods; they suggest that communities should start to adjust to the possibility of longer individual lifespans, and of larger numbers of elderly people in society.

Smoking habit as a risk amplifier in chronic kidney disease patients.

Several studies showed the association between non-traditional risk factors [proteinuria and estimated Glomerular Filtration Rate (eGFR)] and cardiovascular (CV) and renal outcomes. Nevertheless, the etiologic role of traditional CV risk factors in referred CKD patients is less defined. Herein, we examined the association between smoking habit and CV events, mortality and CKD progression. We undertook an observational analysis of 1306 stage III-V CKD patients. Smoking habit was modeled as a categorical (never, current or former smokers) and continuous (number of cigarettes/day) variable. Mean eGFR was 35.8 ± 12.5 mL/min/1.73 m2. Never, current and former smokers were 61.1%, 10.8% and 28.1%. During a median follow-up of 2.87 years, current and former smokers were at significant risk for CV events (HRs of 1.93 [95% CI, 1.18-3.16] and 1.44 [95% CI, 1.01-2.05]) versus never smokers. Current smokers were at increased mortality risk (HR 2.13 [95% CI, 1.10-4.11]). Interactions were found between former smokers and proteinuria (p = 0.007) and diabetes (p = 0.041) for renal risk, and between current smokers and male gender (p = 0.044) and CKD stage V (p = 0.039) for renal and mortality risk. In referred CKD patients, smoking habit is independently associated with CV events and mortality. It acts as a risk "amplifier" for the association between other risk factors and renal outcomes.

Rates, Predictors, and Impact of Smoking Cessation after Stroke or Transient Ischemic Attack: A Systematic Review and Meta-Analysis.

BACKGROUND: Smoking cessation after a first cardiovascular event reduces the risk of recurrent vascular events and mortality. This systematic review and meta-analysis aimed to summarize data on the rates, predictors, and the impact of smoking cessation in patients after a stroke or transient ischemic attack (TIA). METHODS: MEDLINE, EMBASE and Web of Science were searched to identify all published studies providing relevant data through May 20, 2021. Random-effects meta-analysis method was used to pool proportions. Some findings were summarized narratively. RESULTS: Twenty-five studies were included. The pooled smoking cessation rates were 51.0% (8 studies, n = 1738) at 3 months, 44.4% (7 studies, n = 1920) at 6 months, 43.7% (12 studies, n = 1604) at 12 months, and 49.8% (8 studies, n = 2549) at 24 months or more of follow-up. Increased disability and intensive smoking cessation support programs were associated with a higher likelihood of smoking cessation, whereas alcohol consumption and depression had an inverse effect. Two studies showed that patients who quit smoking after a stroke or a TIA had substantially lower risk of recurrent stroke, death, and a composite of stroke, myocardial infarction, and death. CONCLUSION: Smoking cessation in stroke survivors is associated with reduced recurrent vascular events and death. About half of smokers who experience a stroke or a TIA stop smoking afterwards. Those with low post-stroke disability, who consume alcohol, or have depression are less likely to quit. Intensive support programs can increase the likelihood of smoking cessation.