Trends in educational inequalities in smoking-attributable mortality and their impact on changes in general mortality inequalities: evidence from England and Wales, Finland, and Italy (Turin).

BACKGROUND: Socioeconomic mortality inequalities are persistent in Europe but have been changing over time. Smoking is a known contributor to inequality levels, but knowledge about its impact on time trends in inequalities is sparse. METHODS: We studied trends in educational inequalities in smoking-attributable mortality (SAM) and assessed their impact on general mortality inequality trends in England and Wales (E&W), Finland, and Italy (Turin) from 1972 to 2017. We used yearly individually linked all-cause and lung cancer mortality data by educational level and sex for individuals aged 30 and older. SAM was indirectly estimated using the Preston-Glei-Wilmoth method. We calculated the slope index of inequality (SII) and performed segmented regression on SIIs for all-cause, smoking and non-SAM to identify phases in inequality trends. The impact of SAM on all-cause mortality inequality trends was estimated by comparing changes in SII for all-cause with non-SAM. RESULTS: Inequalities in SAM generally declined among males and increased among females, except in Italy. Among males in E&W and Finland, SAM contributed 93% and 76% to declining absolute all-cause mortality inequalities, but this contribution varied over time. Among males in Italy, SAM drove the 1976-1992 increase in all-cause mortality inequalities. Among females in Finland, increasing inequalities in SAM hampered larger declines in mortality inequalities. CONCLUSION: Our findings demonstrate that differing education-specific SAM trends by country and sex result in different inequality trends, and consequent contributions of SAM on educational mortality inequalities. The following decades of the smoking epidemic could increase educational mortality inequalities among Finnish and Italian women.

Impact of global smoking prevalence on mortality: a study across income groups.

BACKGROUND: Smoking significantly contributes to the mortality rates worldwide, particularly in non-communicable and preventable diseases such as cardiovascular ailments, respiratory conditions, stroke, and lung cancer. This study aims to analyse the impact of smoking on global deaths, and its association with mortality across the main income groups. METHODS: The comprehensive analysis spans 199 countries and territories from 1990 to 2019. The study categorises countries into four income groups: high income, upper middle income, lower middle income, and low income. RESULTS: The findings underscore the profound impact of global tobacco smoking on mortality. Notably, cardiovascular disease mortality is notably affected in both upper-middle-income and high-income groups. Chronic respiratory disease mortality rates show a significant impact across all income groups. Moreover, stroke-related mortality is observed in the lower-middle, upper-middle, and high-income groups. These results highlight the pervasive influence of smoking prevalence on global mortality, affecting individuals across various socioeconomic levels. CONCLUSION: The study underscores the critical implications of smoking on mortality rates, particularly in high-income countries. It emphasises the urgency of targeted interventions in these regions to address the specific challenges posed by tobacco smoking on public health. Policy recommendations include implementing prohibitive measures extending to indoor public areas such as workplaces and public transportation services. Furthermore, allocating funds for research on tobacco and health, is imperative to ensure policymakers are consistently informed about emerging facts and trends in this complex domain.

Lifestyle factors and their relative contributions to longitudinal progression of cardio-renal-metabolic multimorbidity: a prospective cohort study.

BACKGROUND: The role of lifestyle factors and their relative contributions to the development and mortality of cardio-renal-metabolic multimorbidity (CRMM) remains unclear. METHODS: A study was conducted with 357,554 UK Biobank participants. CRMM was defined as the coexistence of two or three cardio-renal-metabolic diseases (CRMDs), including cardiovascular disease (CVD), type 2 diabetes (T2D) and chronic kidney disease (CKD). The prospective study examined the associations of individual and combined lifestyle scores (diet, alcohol consumption, smoking, physical activity, sedentary behavior, sleep duration and social connection) with longitudinal progression from healthy to first cardio-renal-metabolic disease (FCRMD), then to CRMM, and ultimately to death, using a multistate model. Subsequently, quantile G-computation was employed to assess the relative contribution of each lifestyle factor. RESULTS: During a median follow-up of 13.62 years, lifestyle played crucial role in all transitions from healthy to FCRMD, then to CRMM, and ultimately to death. The hazard ratios (95% CIs) per score increase were 0.91 (0.90, 0.91) and 0.90 (0.89, 0.91) for healthy to FCRMD, and for FCRMD to CRMM, and 0.84 (0.83, 0.86), 0.87 (0.86, 0.89), and 0.90 (0.88, 0.93) for mortality risk from healthy, FCRMD, and CRMM, respectively. Among the seven factors, smoking status contributed to high proportions for the whole disease progression, accounting for 19.88-38.10%. High-risk diet contributed the largest proportion to the risk of transition from FCRMD to CRMM, with 22.53%. Less-frequent social connection contributed the largest proportion to the risk of transition from FCRMD to death, with 28.81%. When we further consider the disease-specific transitions, we find that lifestyle scores had slightly stronger associations with development to T2D than to CVD or CKD. CONCLUSIONS: Our study indicates that a healthy lifestyle may have a protective effect throughout the longitudinal progression of CRMM, informing more effective management and treatment. Smoking status, diet, and social connection played pivotal roles in specific disease transitions.

Impact of Smoking and Chronic Obstructive Pulmonary Disease on All-Cause, Respiratory, and Cardio-Cerebrovascular Mortality.

Introduction: Mortality differences in chronic obstructive pulmonary disease (COPD) between nonsmokers and smokers remain unclear. We compared the risk of death associated with smoking and COPD on mortality. Methods: The study included participants aged ≥40 years who visited pulmonary clinics and were categorised into COPD or non-COPD and smoker or nonsmoker on the basis of spirometry results and cigarette consumption. Mortality rates were compared between groups using statistical analysis for all-cause mortality, respiratory disease-related mortality, and cardiocerebrovascular disease-related mortality. Results: Among 5811 participants, smokers with COPD had a higher risk of all-cause (adjusted hazard ratio (aHR), 1.69; 95% confidence interval (CI), 1.23-2.33) and respiratory disease-related mortality (aHR, 2.14; 95% CI, 1.20-3.79) than nonsmokers with COPD. Non-smokers with and without COPD had comparable risks of all-cause mortality (aHR, 1.39; 95% CI, 0.98-1.97) and respiratory disease-related mortality (aHR, 1.77; 95% CI, 0.85-3.68). However, nonsmokers with COPD had a higher risk of cardiocerebrovascular disease-related mortality than nonsmokers without COPD (aHR, 2.25; 95% CI, 1.15-4.40). Conclusion: The study found that smokers with COPD had higher risks of all-cause mortality and respiratory disease-related mortality compared to nonsmokers with and without COPD. Meanwhile, nonsmokers with COPD showed comparable risks of all-cause and respiratory mortality but had a higher risk of cardiocerebrovascular disease-related mortality compared to nonsmokers without COPD.

Association of cardiovascular health metrics with all-cause and cardiovascular disease mortality in chronic kidney disease: A cohort study.

BACKGROUND AND AIMS: Since the global burden of chronic kidney disease (CKD) is rising rapidly, the study aimed to assess the association of cardiovascular health (CVH) metrics with all-cause and cardiovascular disease (CVD) mortality among individuals with CKD. METHODS AND RESULTS: The cohort study included 5834 participants with CKD from the National Health and Nutrition Examination Survey 1999-2018. A composite CVH score was calculated based on smoking status, physical activity, body mass index, blood pressure, total cholesterol, diet quality, and glucose control. Primary outcomes were all-cause and CVD mortality as of December 31, 2019. Multivariable-adjusted Cox proportional hazards models were used to estimate the association between CVH metrics and deaths in CKD patients. During a median follow-up of 7.2 years, 2178 all-cause deaths and 779 CVD deaths were documented. Compared to participants with ideal CVH, individuals with intermediate CVH exhibited a 46.0% increase in all-cause mortality (hazard ratio, 1.46; 95% confidence interval: 1.17, 1.83), while those with poor CVH demonstrated a 101.0% increase (2.01; 1.54, 2.62). For CVD mortality, individuals with intermediate CVH experienced a 56.0% increase (1.56; 1.02, 2.39), and those with poor CVH demonstrated a 143.0% increase (2.43; 1.51, 3.91). Linear trends were noted for the associations of CVH with both all-cause mortality (P for trend <0.001) and CVD mortality (P for trend = 0.02). CONCLUSIONS: Lower CVH levels were associated with higher all-cause and CVD mortality in individuals with CKD, which highlights the importance of maintaining good CVH in CKD patients.

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.

Global burden of cardiovascular disease attributable to smoking, 1990-2019: an analysis of the 2019 Global Burden of Disease Study.

AIMS: This study aims to investigate the trends in the global cardiovascular disease (CVD) burden attributable to smoking from 1990 to 2019. METHODS AND RESULTS: Global Burden of Disease Study 2019 was used to analyse the burden of CVD attributable to smoking (i.e. ischaemic heart disease, peripheral artery disease, stroke, atrial fibrillation and flutter, and aortic aneurysm). Age-standardized mortality rates (ASMRs) per 100 000 and age-standardized disability-adjusted life year rates (ASDRs) per 100 000, as well as an estimated annual percentage change (EAPC) in ASMR and ASDR, were determined by age, sex, year, socio-demographic index (SDI), regions, and countries or territories. The global ASMR of smoking-attributed CVD decreased from 57.16/100 000 [95% uncertainty interval (UI) 54.46-59.97] in 1990 to 33.03/100 000 (95% UI 30.43-35.51) in 2019 [EAPC -0.42 (95% UI -0.47 to -0.38)]. Similarly, the ASDR of smoking-attributed CVD decreased between 1990 and 2019. All CVD subcategories showed a decline in death burden between 1990 and 2019. The burden of smoking-attributed CVD was higher in men than in women. Significant geographic and regional variations existed such that Eastern Europe had the highest ASMR and Andean Latin America had the lowest ASMR in 2019. In 2019, the ASMR of smoking-attributed CVD was lowest in high SDI regions. CONCLUSION: Smoking-attributed CVD morbidity and mortality are declining globally, but significant variation persists, indicating a need for targeted interventions to reduce smoking-related CVD burden.

The burden of cardiovascular disease (CVD) attributed to smoking declined worldwide between 1990 and 2019. The burden of smoking-attributed CVD was higher in men than in women in 2019. There were significant variations between different countries and regions such that Eastern Europe had the highest death rate and Andean Latin America had the lowest death rate in 2019. Also, countries with high socio-economic status had lower death rates from smoking-attributed CVD. This highlights the need for targeted interventions to reduce the burden of smoking-attributed CVD.The overall age-adjusted deaths from CVD attributed to smoking declined from 57.16/100 000 in 1990 to 33.03/100 000 in 2019.In 2019, ischaemic heart disease was the leading cause of smoking-attributed CVD deaths.

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.

Changes in global mortality from aortic aneurysm.

OBJECTIVE: Globally, there has been a marked increase in aortic aneurysm-related deaths between 1990 and 2019. We sought to understand the underlying etiologies for this mortality trend by examining secular changes in both demographics and the prevalence of risk factors, and how these changes may vary across sociodemographic index (SDI) regions. METHODS: We queried the Global Burden of Disease Study (GBD) for aortic aneurysm deaths from 1990 to 2019 overall and by age group. We identified the percentage of aortic aneurysm deaths attributable to each risk factor identified by GBD modeling (smoking, hypertension, lead exposure, and high sodium diet) and their respective changes over time. We then analyzed aneurysm mortality by SDI region. RESULTS: The number of aortic aneurysm-related deaths have increased from 94,968 in 1990 to 172,427 in 2019, signifying an 81.6% increase, which greatly exceeds the 18.2% increase in all-cause mortality observed over the same time interval. Examination of age-specific mortality demonstrated that the number of aortic aneurysm deaths markedly correlated with advancing age. However, when considering rate of death rather than mortality count, overall age-standardized death rates decreased 18% from 2.72 per 100,000 in 1990 to 2.21 per 100,000 in 2019. Analysis of the specific risk factors associated with aneurysm death revealed that the percentage of deaths attributable to smoking decreased from 45.6% in 1990 to 34.6% in 2019, and deaths attributable to hypertension decreased from 38.7% to 34.7%. Globally, hypertension surpassed smoking as the leading risk factor. The reported rate of death was consistently greater as SDI increased, and this effect was most pronounced among low-middle and middle SDI regions (173.2% and 170.4%, respectively). CONCLUSIONS: Despite an overall increase in the number of aneurysm deaths, there was a decrease in the age-standardized death rate, demonstrating that the observed increased number of aortic aneurysm deaths between 1990 and 2019 was primarily driven by an overall increase in the age of the global population. Fortunately, it appears that the increase in overall aneurysm-related deaths has been modulated by improved risk factor modification, in particular smoking. Given the rise in aneurysm-related deaths, global expansion of vascular specialty capabilities is warranted and will serve to amplify improvements in population-based aneurysm health achieved with risk factor control.

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.

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.

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.