Measuring Burden of Unhealthy Behaviours Using a Multivariable Predictive Approach: Life Expectancy Lost in Canada Attributable to Smoking, Alcohol, Physical Inactivity, and Diet

Trends in Cardiovascular Risk Factors in Canada: Variation by Migration and Temporal Factors, 2001-2018

Background

Cardiovascular disease is a leading cause of death in Canada, but how the major cardiovascular risk factors vary across ethnicity and immigration status has yet to be examined.

Methods

Using data from the Canadian Community Health Surveys, national trends in health conditions (hypertension, diabetes, high blood cholesterol level, and obesity) and health behaviours (smoking, activity levels, and alcohol consumption) were estimated for the period 2001-2018. In this cross-sectional study, the trends were then compared across sex, age, ethnicity, and immigration status.

Results

A total of 1,065,391 respondents were examined, for the period 2001-2018. During the study period, the prevalence of the following risk factors increased in Canada over time, as follows: diabetes by 54.5%; hypertension by 23.4%; and obesity by 32.3%. For health behaviours, smoking prevalence decreased overall, especially in racialized populations. Heavy drinking was most prevalent for nonracialized and non-Indigenous Canadian-born populations, and was of lowest prevalence among racialized immigrants. Physical inactivity was most prevalent for racialized immigrant populations. The prevalence of self-reported heart disease decreased by 21.0%, except for racialized established immigrants (≥ 10 years since immigration to Canada), who had a 4.2% increase.

Conclusions

During this study period, decreases occurred in the prevalences of smoking and physical inactivity, along with increases in obesity, diabetes, and hypertension prevalences. By migration-group status, established immigrants in Canada had a higher prevalence of cardiovascular disease risk factors compared to that among their Canadian-born counterparts. Migration gaps should be considered in future interventions targeted at reducing these cardiovascular risk factors in Canada.

Impact of Healthy Lifestyle Factors on Life Expectancy and Lifetime Health Care Expenditure: Nationwide Cohort Study

BACKGROUND

The association between lifestyle risk factors and the risk of mortality and chronic diseases has been established, while limited research has explored the impact of healthy lifestyle factors on lifetime health care expenditure using longitudinal individual data.

OBJECTIVE

We aimed to determine the individual and combined effects of 5 healthy lifestyle factors on life expectancy and lifetime health care expenditure in Taiwan.

METHODS

Using data from the National Health Interview Survey cohort, 5 healthy lifestyle behaviors were defined and analyzed: nonsmoking, avoiding excessive alcohol consumption, engaging in sufficient physical activity, ensuring sufficient fruit and vegetable intake, and maintaining a normal weight. We used a rolling extrapolation algorithm that incorporated inverse probability of treatment weighting to estimate the life expectancy and lifetime health care expenditure of the study populations with and without healthy lifestyle factors.

RESULTS

A total of 19,893 participants aged ≥30 (mean age 48.8, SD 13.4) years were included, with 3815 deaths recorded during a median follow-up period of 15.6 years. The life expectancy and per capita estimated lifetime health care expenditures for the overall study population were 35.32 years and US $58,560, respectively. Multivariable-adjusted hazard ratios for all-cause mortality in participants adhering to all 5 healthy lifestyle factors, compared with those adhering to none, were 0.37 (95% CI 0.27-0.49). We found significant increases in life expectancy for nonsmokers (2.31 years; 95% CI 0.04-5.13; P=.03), those with sufficient physical activity (1.85 years; 95% CI 0.25-4.34; P=.02), and those with adequate fruit and vegetable intake (3.25 years; 95% CI 1.29-6.81; P=.01). In addition, nonsmokers experienced a significant reduction in annual health care expenditure (-9.78%; 95% CI -46.53% to -1.45%; P=.03), as did individuals maintaining optimal body weight (-18.36%; 95% CI -29.66% to -8.57%; P=.01). Overall, participants adhering to all 5 healthy lifestyle behaviors exhibited a life gain of 7.13 years (95% CI 1.33-11.11; P=.02) compared with those adhering to one or none, with a life expectancy of 29.19 years (95% CI 25.45-33.62). Furthermore, individuals adopting all 5 healthy lifestyle factors experienced an average annual health care expenditure reduction of 28.12% (95% CI 4.43%-57.61%; P=.02) compared with those adopting one or none.

CONCLUSIONS

Adopting a healthy lifestyle is associated with a longer life expectancy and a reduction of health care expenditure in Taiwanese adults. This contributes to a more comprehensive understanding of the impact of healthy lifestyle factors on the overall health and economic burden.

Association of both depressive symptoms scores and specific depressive symptoms with all-cause and cardiovascular disease mortality

BACKGROUND

The presence of depression related to an increased risk of all-cause and cardiovascular disease (CVD) mortality has been reported. However, studies conducted on certain specific depressive symptoms are scarce. Our purpose was to assess the effect of both depressive symptoms scores and certain specific depressive symptoms on all-cause and CVD mortality.

METHODS

In the present cohort study, all participants, aged 18 years or older, were enrolled in the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2014. Depressive symptoms score was assessed using the validated 9-item Patient Health Questionnaire Depression Scale (PHQ-9), which ranges from 0 to 27, with a PHQ-9 score ≥ 10 diagnosed as depression. The outcome events were all-cause and CVD mortality, which were followed up from 2005 to 2014. The associations of both depressive symptoms score and certain specific depressive symptoms with all-cause and CVD mortality were examined by weighted multivariable proportional hazards models.

RESULTS

A total of 26,028 participants aged ≥ 18 years were included in the statistical analysis, including 12,813 (49.2%) males and 13,215 (50.8%) females, with a mean (SD) age of 47.34 (18.86) years. During the 9.32 (3.20) years of mean (SD) follow-up, 3261 deaths were recorded, of which 826 were cardiovascular deaths. All-cause mortality was 16.87/1000 person-years in subjects with depression. In terms of CVD mortality, these figures were 4.53/1000 person-years. In the full model (model 3), elevated depressive symptoms scores were independently associated with an increased risk of all-cause mortality (Highest depression symptom score group: adjusted hazard ratio, 1.63; 95% CI 1.44-1.85) and CVD mortality (Highest depression symptom score group: adjusted hazard ratio, 1.73; 95% CI 1.34-2.24). All 9 specific depressive symptoms that make up the PHQ-9 were related to an increased risk of all-cause mortality. However, only 3 symptoms, including trouble sleeping or sleeping too much, poor appetite or overeating, and suicidal ideation, were no significantly associated with an increased risk of CVD mortality.

CONCLUSIONS

The elevated depressive symptoms scores were strongly associated with an increased risk of all-cause and CVD mortality in US adults. Furthermore, all 9 specific depressive symptoms were associated with high all-cause mortality. However, trouble sleeping or sleeping too much, poor appetite or overeating, and suicidal ideation might not increase the risk of CVD mortality.

Health impacts of lifestyle and ambient air pollution patterns on all-cause mortality: a UK Biobank cohort study

BACKGROUND

Extensive evidence indicates that both lifestyle factors and air pollution are strongly associated with all-cause mortality. However, little studies in this field have integrated these two factors in order to examine their relationship with mortality and explore potential interactions.

METHODS

A cohort of 271,075 participants from the UK Biobank underwent analysis. Lifestyles in terms of five modifiable factors, namely smoking, alcohol consumption, physical activity, diet, and sleep quality, were classified as unhealthy (0-1 score), general (2-3 score), and healthy (4-5 score). Air pollution, including particle matter with a diameter ≤ 2.5 μm (PM2.5), particulate matter with a diameter ≤ 10 μm (PM10), particulate matter with a diameter 2.5-10 μm (PM2.5-10), nitrogen dioxide (NO2), and nitrogen oxides (NOx), was divided into three levels (high, moderate, and low) using Latent Profile Analysis (LPA). Cox proportional hazard regression analysis was performed to examine the links between lifestyle, air pollution, and all-cause mortality before and after adjustment for potential confounders. Restricted cubic spline curves featuring three knots were incorporated to determine nonlinear relationships. The robustness of the findings was assessed via subgroup and sensitivity analyses.

RESULTS

With unhealthy lifestyles have a significantly enhanced risk of death compared to people with general lifestyles (HR = 1.315, 95% CI, 1.277-1.355), while people with healthy lifestyles have a significantly lower risk of death (HR = 0.821, 95% CI, 0.785-0.858). Notably, the difference in risk between moderate air pollution and mortality risk remained insignificant (HR = 0.993, 95% CI, 0.945-1.044). High air pollution, on the other hand, was independently linked to increased mortality risk as compared to low air pollution (HR = 1.162, 95% CI, 1.124-1.201). The relationship between NOx, PM10, and PM2.5-10 and all-cause mortality was found to be nonlinear (p for nonlinearity < 0.05). Furthermore, no significant interaction was identified between lifestyle and air pollution with respect to all-cause mortality.

CONCLUSIONS

Exposure to ambient air pollution elevated the likelihood of mortality from any cause, which was impacted by individual lifestyles. To alleviate this hazard, it is crucial for authorities to escalate environmental interventions, while individuals should proactively embrace and sustain healthy lifestyles.

Adaptation and qualitative evaluation of the BETTER intervention for chronic disease prevention and screening by public health nurses in low income neighbourhoods: views of community residents

BACKGROUND

The BETTER intervention is an effective comprehensive evidence-based program for chronic disease prevention and screening (CDPS) delivered by trained prevention practitioners (PPs), a new role in primary care. An adapted program, BETTER HEALTH, delivered by public health nurses as PPs for community residents in low income neighbourhoods, was recently shown to be effective in improving CDPS actions. To obtain a nuanced understanding about the CDPS needs of community residents and how the BETTER HEALTH intervention was perceived by residents, we studied how the intervention was adapted to a public health setting then conducted a post-visit qualitative evaluation by community residents through focus groups and interviews.

METHODS

We first used the ADAPT-ITT model to adapt BETTER for a public health setting in Ontario, Canada. For the post-PP visit qualitative evaluation, we asked community residents who had received a PP visit, about steps they had taken to improve their physical and mental health and the BETTER HEALTH intervention. For both phases, we conducted focus groups and interviews; transcripts were analyzed using the constant comparative method.

RESULTS

Thirty-eight community residents participated in either adaptation (n = 14, 64% female; average age 54 y) or evaluation (n = 24, 83% female; average age 60 y) phases. In both adaptation and evaluation, residents described significant challenges including poverty, social isolation, and daily stress, making chronic disease prevention a lower priority. Adaptation results indicated that residents valued learning about CDPS and would attend a confidential visit with a public health nurse who was viewed as trustworthy. Despite challenges, many recipients of BETTER HEALTH perceived they had achieved at least one personal CDPS goal post PP visit. Residents described key relational aspects of the visit including feeling valued, listened to and being understood by the PP. The PPs also provided practical suggestions to overcome barriers to meeting prevention goals.

CONCLUSIONS

Residents living in low income neighbourhoods faced daily stress that reduced their capacity to make preventive lifestyle changes. Key adapted features of BETTER HEALTH such as public health nurses as PPs were highly supported by residents. The intervention was perceived valuable for the community by providing access to disease prevention.

TRIAL REGISTRATION

#NCT03052959, 10/02/2017.

Healthy lifestyle, statin, and mortality in people with high CVD risk: A nationwide population-based cohort study

Objective

To examine the joint association of healthy lifestyles and statin use with all-cause and cardiovascular mortality in high-risk individuals, and evaluate the survival benefits by life expectancy.

Methods

During 2015-2021, participants aged 35-75 years were recruited by the China Health Evaluation And risk Reduction through nationwide Teamwork. Based on number of healthy lifestyles related to smoking, alcohol drinking, physical activity, and diet, we categorized them into: very healthy (3-4), healthy (2), and unhealthy (0-1). Statin use was determined by self-report taking statin in last two weeks.

Results

Among the 265,209 included participants at high risk, 6979 deaths were observed, including 3236 CVD deaths during a median 3.6 years of follow-up. Individuals taking statin and with a very healthy lifestyle had the lowest risk of all-cause (HR: 0.70; 95 %CI: 0.57-0.87) and cardiovascular mortality (0.56; 0.40-0.79), compared with statin non-users with an unhealthy lifestyle. High-risk participants taking statin and with a very healthy lifestyle had the highest years of life gained (5.90 years at 35-year-old [4.14-7.67; P < 0.001]) compared with statin non-users with an unhealthy lifestyle among high-risk people. And their life expectancy was comparable with those without high risk but with a very healthy lifestyle (4.49 vs. 4.68 years).

Conclusion

The combination of preventive medication and multiple healthy lifestyles was associated with lower risk of all-cause and cardiovascular mortality and largest survival benefits. Integrated strategy to improve long-term health for high-risk people was urgently needed.

Risk of premature mortality due to smoking, alcohol use, obesity and physical activity varies by income: A population-based cohort study

Background

Premature deaths are a strong population health indicator. There is a persistent and widening pattern of income inequities for premature mortality. We sought to understand the combined effect of health behaviours and income on premature mortality in a large population-based cohort.

Methods

We analyzed a cohort of 121,197 adults in the 2005-2014 Canadian Community Health Surveys, linked to vital statistics data to ascertain deaths for up to 5 years following baseline. Information on household income quintile and mortality-relevant risk factors (smoking status, alcohol use, body mass index (BMI), and physical activity) was captured from the survey. Hazard ratios (HR) for combined income-risk factor groups were estimated using Cox proportional hazards models. Stratified Cox models were used to identify quintile-specific HR for each risk factor.

Results

For each risk factor, HR of premature mortality was highest in the lowest-income, highest-risk group. Additionally, an income gradient was seen for premature mortality HR for every exposure level of each risk factor. In the stratified models, risk factor HRs did not vary meaningfully between income groups. All findings were consistent in the unadjusted and adjusted models.

Conclusion

These findings highlight the need for targeted strategies to reduce health inequities and more careful attention to how policies and interventions are distributed at the population level. This includes targeting and tailoring resources to those in lower income groups who disproportionately experience premature mortality risk to prevent further widening health inequities.

A drink equals how many cigarettes? Equating mortality risks from alcohol and tobacco use in Canada

Objective

To quantify and communicate risk equivalencies for alcohol-and tobacco-attributable mortality by comparing per standard drinks consumed to per number of cigarettes smoked in Canada.

Methods

Alcohol-and tobacco-attributable premature deaths (≤75 years of age) and years of life lost (YLL) were estimated using a lifetime risk modeling approach. Alcohol-attributable death statistics were obtained from the 2023 Canadian Guidance on Alcohol and Health data source. Tobacco-attributable death statistics were derived from the Mortality Population Risk Tool (MPoRT) model.

Results

The risk of alcohol use on premature death and YLL increased non-linearly with the number of drinks consumed, while the risk for tobacco use on these two measures increased linearly with the number of cigarettes smoked. Males who consumed 5 drinks/day-a standard drink contains 13.45 grams of alcohol in Canada-had an equivalent risk as smoking 4.9 cigarettes/day (when modeling for premature death) and 5.1 cigarettes/day (when modeling for YLL). Females who consumed 5 drinks/day experienced an equivalent risk as smoking 4.2 cigarettes/day for premature deaths and YLL. At all levels of alcohol consumption females and males who consumed <5 drinks/day have less risks from consuming a standard drink than from smoking a cigarette. For males who consumed 5 drinks/day, the increased risks of death from per drink consumed and per cigarette smoked were equal.

Conclusion

Risk equivalencies comparing alcohol use to tobacco use could help people who drink improve their knowledge and understanding of the mortality risks associated with increased number of drinks consumed per day.

A study protocol for a predictive model to assess population-based avoidable hospitalization risk: Avoidable Hospitalization Population Risk Prediction Tool (AvHPoRT)

INTRODUCTION

Avoidable hospitalizations are considered preventable given effective and timely primary care management and are an important indicator of health system performance. The ability to predict avoidable hospitalizations at the population level represents a significant advantage for health system decision-makers that could facilitate proactive intervention for ambulatory care-sensitive conditions (ACSCs). The aim of this study is to develop and validate the Avoidable Hospitalization Population Risk Tool (AvHPoRT) that will predict the 5-year risk of first avoidable hospitalization for seven ACSCs using self-reported, routinely collected population health survey data.

METHODS AND ANALYSIS

The derivation cohort will consist of respondents to the first 3 cycles (2000/01, 2003/04, 2005/06) of the Canadian Community Health Survey (CCHS) who are 18-74 years of age at survey administration and a hold-out data set will be used for external validation. Outcome information on avoidable hospitalizations for 5 years following the CCHS interview will be assessed through data linkage to the Discharge Abstract Database (1999/2000-2017/2018) for an estimated sample size of 394,600. Candidate predictor variables will include demographic characteristics, socioeconomic status, self-perceived health measures, health behaviors, chronic conditions, and area-based measures. Sex-specific algorithms will be developed using Weibull accelerated failure time survival models. The model will be validated both using split set cross-validation and external temporal validation split using cycles 2000-2006 compared to 2007-2012. We will assess measures of overall predictive performance (Nagelkerke R2), calibration (calibration plots), and discrimination (Harrell's concordance statistic). Development of the model will be informed by the Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) statement.

ETHICS AND DISSEMINATION

This study was approved by the University of Toronto Research Ethics Board. The predictive algorithm and findings from this work will be disseminated at scientific meetings and in peer-reviewed publications.

Age and its impact on crisis management performance and learning after simulation-based education by acute care physicians: a multicentre prospective cohort study

BACKGROUND

Physiological changes associated with ageing could negatively impact the crisis resource management skills of acute care physicians. This study was designed to determine whether physician age impacts crisis resource management skills, and crisis resource management skills learning and retention using full-body manikin simulation training in acute care physicians.

METHODS

Acute care physicians at two Canadian universities participated in three 8-min simulated crisis (pulseless electrical activity) scenarios. An initial crisis scenario (pre-test) was followed by debriefing with a trained facilitator and a second crisis scenario (immediate post-test). Participants returned for a third crisis scenario 3-6 months later (retention post-test).

RESULTS

For the 48 participants included in the final analysis, age negatively correlated with baseline Global Rating Scale (GRS; r=-0.30, P<0.05) and technical checklist scores (r=-0.44, P<0.01). However, only years in practice and prior simulation experience, but not age, were significant in a subsequent stepwise regression analysis. Learning from simulation-based education was shown with a mean difference in scores from pre-test to immediate post-test of 2.28 for GRS score (P<0.001) and 1.69 for technical checklist correct score (P<0.001); learning was retained for 3-6 months. Only prior simulation experience was significantly correlated with a decreased change in learning (r=-0.30, P<0.05).

CONCLUSIONS

A reduced amount of prior simulation training and increased years in practice, but not age on its own, were significant predictors of low baseline crisis resource management performance. Simulation-based education leads to crisis resource management learning that is well retained for 3-6 months, regardless of age or years in practice.

Impact of 8 lifestyle factors on mortality and life expectancy among United States veterans: The Million Veteran Program

BACKGROUND

Lifestyle medicine has been proposed as a way to address the root causes of chronic disease and their associated health care costs.

OBJECTIVE

This study aimed to estimate mortality risk and longevity associated with individual lifestyle factors and comprehensive lifestyle therapy.

METHODS

Age- and sex-specific mortality rates were calculated on the basis of 719,147 veterans aged 40-99 y enrolled in the Veteran Affairs Million Veteran Program (2011-2019). Hazard ratios and estimated increase in life expectancy were examined among a subgroup of 276,132 veterans with complete data on 8 lifestyle factors at baseline. The 8 lifestyle factors included never smoking, physical activity, no excessive alcohol consumption, restorative sleep, nutrition, stress management, social connections, and no opioid use disorder.

RESULTS

On the basis of 1.12 million person-years of follow-up, 34,247 deaths were recorded. Among veterans who adopted 1, 2, 3, 4, 5, 6, 7, and 8 lifestyle factors, the adjusted hazard ratios for mortality were 0.74 (0.60-0.90), 0.60 (95% CI: 0.49, 0.73), 0.50 (95% CI: 0.41, 0.61), 0.43 (95% CI: 0.35, 0.52), 0.35 (95% CI: 0.29, 0.43), 0.27 (95% CI: 0.22, 0.33), 0.21 (95% CI: 0.17, 0.26), and 0.13 (95% CI: 0.10, 0.16), respectively, as compared with veterans with no adopted lifestyle factors. The estimated life expectancy at age 40 y was 23.0, 26.5, 28.8, 30.8, 32.7, 35.1, 38.3, 41.3, and 47.0 y among males and 27.0, 28.8, 33.1, 38.0, 39.2, 41.4, 43.8, 46.3, and 47.5 y for females who adopted 0, 1, 2, 3, 4, 5, 6, 7, and 8 lifestyle factors, respectively. The difference in life expectancy at age 40 y was 24.0 y for male veterans and 20.5 y for female veterans when comparing adoption of 8-9 lifestyle factors.

CONCLUSIONS

A combination of 8 lifestyle factors is associated with a significantly lower risk of premature mortality and an estimated prolonged life expectancy.

Mid-life alcohol consumption and survival to age 90 in men: The Tromsø Study 1979-1980 with follow-up to 2019

AIMS

The Tromsø Study 1979-1980 collected information on alcohol (beer, wine and spirits) consumption frequency and inebriation frequency, and the oldest male participants (aged 50-54 years) were followed for all-cause mortality. This study aimed to identify the impact of habitual alcohol consumption in mid-life on reaching up to 90 years of age.

RESULTS

Among the study sample of 778, a total of 120 (15.4%) men reached the age of 90. The most common reported alcohol consumption frequency was 'never or a few times a year', and 18.9% of those in this group reached 90 compared with 11.9% of those who reported a more frequent beer consumption. Fifty per cent survival in these groups was 80.5 and 76.9 years, respectively. The pattern was similar for spirits consumption and for inebriation but not for wine consumption. Number of deaths increased gradually with increasing beer and spirits consumption frequency and with inebriation frequency. We observed no J-shape or pattern that revealed a beneficial influence of light alcohol consumption. Daily smoking, physical inactivity, marital status, blood pressure and total cholesterol reduced the contribution of alcohol consumption to a small degree.

CONCLUSIONS

This study shows that all beer and spirits consumption frequencies in mid-life affect later life and total lifespan. Refraining from alcohol consumption or drinking only a few times a year increases one's chances of living longer, and the chance of reaching 90 years of age is 1.6-fold higher than in those with more frequent alcohol consumption.

Assessing the Efficacy of a 28-Day Comprehensive Online Prostate Cancer Patient Empowerment Program (PC-PEP) in Facilitating Engagement of Prostate Cancer Patients in Their Survivorship Care: A Qualitative Study

A 28-day Prostate Cancer-Patient Empowerment Program (PC-PEP) developed through patient engagement was successful at promoting mental and physical health. Thirty prostate cancer patients from Halifax, Canada participated in the 28-day PC-PEP intervention in early 2019. PC-PEP encompassed daily patient education and empowerment videos, prescribed physical activities (including pelvic floor exercises), a mostly plant-based diet, stress reduction techniques, intimacy education, social connection, and support. Quantitative exit surveys and semi-structured interviews (conducted in focus groups of ten) were used to assess perceived factors that facilitated or impeded adherence to the program. The program received high praise from the patients and was deemed extremely useful by the participating men, who rated it 9 out of 10. Patients expressed that the multifaceted, online, home-based nature of the program helped them adhere to it better than they would have had to a single or less comprehensive intervention. Feedback from the participants indicated that the program, when viewed as a whole, was perceived as greater than the sum of its individual parts. Furthermore, the program addressed various issues, including emotional vulnerability and distress, physical fitness, urinary incontinence, challenges in expressing emotions, perceived lack of control over healthcare decisions, emotional fragility, and hesitancy to discuss prostate cancer-related matters in social settings. Patients highly (9.6/10) endorsed integrating the program into the standard care regimen from the very beginning of diagnosis. However, challenges such as work commitments were noted. Patients' high endorsement of PC-PEP suggests that its implementation into the standard of care from day one of diagnosis may be warranted.

Associations between Liver Enzymes, Lifestyle Risk Factors and Pre-Existing Medical Conditions in a Population-Based Cross-Sectional Sample

While alanine aminotransferase (ALT) and gamma-glutamyltransferase (GGT) enzymes are commonly used indicators of liver dysfunction recent studies have suggested that these may also serve as predictive biomarkers in the assessment of extrahepatic morbidity. In order to shed further light on the interactions between serum liver enzyme abnormalities, factors of lifestyle and health status we examined ALT and GGT activities in a population-based sample of 8743 adult individuals (4048 men, 4695 women from the National FINRISK 2002 Study, mean age 48.1 ± 13.1 years) with different levels of alcohol drinking, smoking, physical activity, body weight and the presence or absence of various pre-existing medical conditions. The assessments also included laboratory tests for inflammation, lipid status and fatty liver index (FLI), a proxy for fatty liver. The prevalence of ALT and GGT abnormalities were significantly influenced by alcohol use (ALT: p < 0.0005 for men; GGT: p <0.0005 for both genders), smoking (GGT: p <0.0005 for men, p =0.002 for women), adiposity (p < 0.0005 for all comparisons), physical inactivity (GGT: p <0.0005; ALT: p <0.0005 for men, p <0.05 for women) and coffee consumption (p <0.0005 for GGT in both genders; p <0.001 for ALT in men). The total sum of lifestyle risk factor scores (LRFS) influenced the occurrence of liver enzyme abnormalities in a rather linear manner. Significantly higher LRFS were observed in the subgroups of individuals with pre-existing medical conditions when compared with those having no morbidities (p <0.0005). In logistic regression analyses adjusted for the lifestyle factors, both ALT and GGT associated significantly with fatty liver, diabetes and hypertension. GGT levels also associated with coronary heart disease, angina pectoris, cardiac insufficiency, cerebrovascular disease, asthma and depression. Combinations of abnormal ALT and GGT activities significantly increased the odds for hypertension coinciding with abnormalities in biomarkers of inflammation, lipid status and FLI. The data indicates that ALT and GGT activities readily respond to unfavorable factors of lifestyle associating also with a wide array of pre-existing medical conditions. The data supports close links between both hepatic and extrahepatic morbidities and lifestyle risk factors and may open new insights on a more comprehensive use of liver enzymes in predictive algorithms for assessing mechanistically anchored disease conditions.

Predictive risk markers in alcoholism

The medical disorders of alcoholism rank among the leading public health problems worldwide and the need for predictive and prognostic risk markers for assessing alcohol use disorders (AUD) has been widely acknowledged. Early-phase detection of problem drinking and associated tissue toxicity are important prerequisites for timely initiations of appropriate treatments and improving patient's committing to the objective of reducing drinking. Recent advances in clinical chemistry have provided novel approaches for a specific detection of heavy drinking through assays of unique ethanol metabolites, phosphatidylethanol (PEth) or ethyl glucuronide (EtG). Carbohydrate-deficient transferrin (CDT) measurements can be used to indicate severe alcohol problems. Hazardous drinking frequently manifests as heavy episodic drinking or in combinations with other unfavorable lifestyle factors, such as smoking, physical inactivity, poor diet or adiposity, which aggravate the metabolic consequences of alcohol intake in a supra-additive manner. Such interactions are also reflected in multiple disease outcomes and distinct abnormalities in biomarkers of liver function, inflammation and oxidative stress. Use of predictive biomarkers either alone or as part of specifically designed biological algorithms helps to predict both hepatic and extrahepatic morbidity in individuals with such risk factors. Novel approaches for assessing progression of fibrosis, a major determinant of prognosis in AUD, have also been made available. Predictive algorithms based on the combined use of biomarkers and clinical observations may prove to have a major impact on clinical decisions to detect AUD in early pre-symptomatic stages, stratify patients according to their substantially different disease risks and predict individual responses to treatment.

Ideal cardiovascular health metrics and life expectancy free of cardiovascular diseases: a prospective cohort study

Objectives

Whether cardiovascular health (CVH) metrics impact longevity with and without cardiovascular diseases (CVDs) has not been well established. This study aimed to investigate the association between CVH metrics and life expectancy in participants free of CVD events. We hypothesized that ideal CVH status was associated with increased life expectancy and assessed the effect of CVH status as a prevention target of longevity in the framework of predictive, preventive, and personalized medicine (PPPM/3PM).

Methods

A total of 92,795 participants in the Kailuan study were examined and thereafter followed up until 2020. We considered three transitions (from non-CVD events to incident CVD events, from non-CVD events to mortality, and from CVD events to mortality). The multistate lifetable method was applied to estimate the life expectancy.

Results

During a median follow-up of 13 years, 12,541 (13.51%) deaths occurred. Compared with poor CVH, ideal CVH attenuated the risk of incident CVD events and mortality without CVD events by approximately 58% and 27%, respectively. Women with ideal CVH at age 35 had a 5.00 (3.23-6.77) year longer life expectancy free of CVD events than did women with poor CVH metrics. Among men, ideal CVH was associated with a 6.74 (5.55-7.93) year longer life expectancy free of CVD events.

Conclusion

An ideal CVH status is associated with a lower risk of premature mortality and a longer life expectancy, either in the general population or in CVD patients, which are cost-effective ways for personalized medicine of potential CVD patients. Our findings suggest that the promotion of a higher CVH score or ideal CVH status would result in reduced burdens of CVD events and extended disease-free life expectancy, which offered an accurate prediction for primary care following the concept of PPPM/3PM.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-023-00322-8.

Associations Between Gender Gaps in Life Expectancy, Air Pollution, and Urbanization: A Global Assessment With Bayesian Spatiotemporal Modeling

Objectives: It's evident that women have a longer life expectancy than men. This study investigates the spatiotemporal trends of gender gaps in life expectancy (GGLE). It demonstrates the spatiotemporal difference of the influence factors of population-weighted air pollution (pwPM_2.5) and urbanization on GGLE. Methods: Panel data on GGLE and influencing factors from 134 countries from 1960 to 2018 are collected. The Bayesian spatiotemporal model is performed. Results: The results show an obvious spatial heterogeneity worldwide with a continuously increasing trend of GGLE. Bayesian spatiotemporal regression reveals a significant positive relationship between pwPM_2.5, urbanization, and GGLE with the spatial random effects. Further, the regression coefficients present obvious geographic disparities across space worldwide. Conclusion: In sum, social-economic development and air quality improvement should be considered comprehensively in global policy to make a fair chance for both genders to maximize their health gains.

Mortality and Life Expectancy Lost in Canada Attributable to Dietary Patterns: Evidence From Canadian National Nutrition Survey Linked to Routinely Collected Health Administrative Databases

Using 5 diet quality indexes, we estimated the mortality and life expectancy lost, at the national level, attributable to poor dietary patterns, which had previously been largely unknown. We used the Canadian Community Health Survey 2004, linked to vital statistics (n = 16,212 adults; representing n = 22,898,880). After a median follow-up of 7.5 years, 1,722 deaths were recorded. Population attributable fractions were calculated to estimate the mortality burden of poor dietary patterns (Dietary Guidelines for Americans Adherence Index 2015, Dietary Approaches to Stop Hypertension, Healthy Eating Index, Alternative Healthy Eating Index, and Mediterranean Style Dietary Pattern Score). Better diet quality was associated with a 32%-51% and 21%-43% reduction in all-cause mortality among adults aged 45-80 years and ≥20 years, respectively. Projected life expectancy at 45 years was longer for Canadians adhering to a healthy dietary pattern (average of 5.2-8.0 years (men) and 1.6-4.1 (women)). At the population level, 26.5%-38.9% (men) and 8.9%-22.9% (women) of deaths were attributable to poor dietary patterns. Survival benefit was greater for individuals with higher scores on all diet indexes, even with relatively small intake differences. The large attributable burden was likely from assessing overall dietary patterns instead of a limited range of foods and nutrients.

Associations of types of grains and lifestyle with all-cause mortality among Chinese adults aged 65 years or older: a prospective cohort study

BACKGROUND

Little is known on the association of types of grains with mortality and the moderating effect of lifestyle on this association. This study aims to evaluate the single or joint associations of types of grains and lifestyle with all-cause mortality among Chinese older adults.

METHODS

Data were derived from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) from 1998 to 2018. Subjects aged ≥ 65 years were eligible. The types of grains included wheat, total rice, and coarse cereals. Lifestyle was derived using smoking, alcohol consumption, physical activity, and dietary pattern. All-cause mortality was the primary outcome.

RESULTS

This study included 30275 participants with a mean age 87 ± 11 years and documented 19261 deaths during a mean follow-up of 4.8 years. Compared to wheat, in those with healthy and intermediate lifestyle, total rice was associated with a 13% (HR: 0.87, 95% CI 0.80, 0.93) and 6% (HR: 0.94, 95% CI 0.90, 1.00) lower risk of mortality, respectively, and coarse cereals were associated with a 14% (HR: 0.86, 95% CI 0.74, 1.00) and 12% (HR: 0.88, 95% CI 0.79, 0.97) lower risk of mortality, respectively. Meanwhile, an increase per SD in intakes of wheat and coarse cereals was associated with a 10% (HR: 1.10, 95% CI 1.03, 1.18) and 25% (HR: 1.25, 95% CI 1.08, 1.44) higher mortality rate in those with healthy lifestyle, and a 13% (HR: 1.13, 95% CI 1.08, 1.19) and 29% (HR: 1.29, 95% CI 1.17, 1.44) higher mortality in females but not males. In addition, a U-shaped association of intake of total grains with all- cause mortality was observed (P for non-linearity = 0.002), and a J-shaped association of intake of total rice with all- cause mortality was observed (P for non-linearity = 0.003).

CONCLUSIONS

Specific types of grains and lifestyle were separately or jointly associated with all-cause mortality. Compared to wheat, total rice and coarse cereals were advanced grains for participants with a relatively healthy lifestyle. Intake of total rice was related to all-cause mortality in a dose-response manner. Therefore, a combination of intermediate intake of total rice and healthy lifestyle should be encouraged in older adults.

Primary care-based smoking cessation treatment and subsequent healthcare service utilisation: a matched cohort study of smokers using linked administrative healthcare data

BACKGROUND

No research has assessed the individual-level impact of smoking cessation treatment delivered within a general primary care patient population on multiple forms of subsequent healthcare service use.

OBJECTIVE

We aimed to compare the rate of outpatient visits, emergency department (ED) visits and hospitalisations during a 5-year follow-up period among smokers who had and had not accessed a smoking cessation treatment programme.

METHODS

The study was a retrospective matched cohort study using linked demographic and administrative healthcare databases in Ontario, Canada. 9951 patients who accessed smoking cessation services between July 2011 and December 2012 were matched to a smoker who did not access services, obtained from the Canadian Community Health Survey, using a combination of hard matching and propensity score matching. Outcomes were rates of healthcare service use from index date (programme enrolment or survey response) to March 2017.

RESULTS

After controlling for potential confounders, patients in the overall treatment cohort had modestly greater rates of the outcomes: outpatient visits (rate ratio (RR) 1.10, 95% CI: 1.06 to 1.14), ED visits (RR 1.08, 95% CI: 1.03 to 1.13) and hospitalisations (RR 1.09, 95% CI: 1.02 to 1.18). Effect modification of the association between smoking cessation treatment and healthcare service use by prevalent comorbidity was found for outpatient visits (p=0.006), and hospitalisations (p=0.050), but not ED visits.

CONCLUSIONS

Patients who enrolled in smoking cessation treatment offered through primary care clinics in Ontario displayed a modest but significantly greater rate of outpatient visits, ED visits and hospitalisations over a 5-year follow-up period.

Healthy lifestyle and life expectancy at age 30 years in the Chinese population: an observational study

BACKGROUND

The improvement of life expectancy is one of the aims of the Healthy China 2030 blueprint. We aimed to investigate the extent to which healthy lifestyles are associated with life expectancy in Chinese adults.

METHODS

We used the prospective China Kadoorie Biobank (CKB) study to examine the relative risk of mortality associated with individual and combined lifestyle factors (never smoking or quitting not for illness, no excessive alcohol use, being physically active, healthy eating habits, and healthy body shape). Participants with coronary heart disease, stroke, cancer, or missing values for body-mass index were excluded. For analysis of chronic respiratory diseases, participants with chronic obstructive pulmonary disease or asthma were excluded. We estimated the national prevalence of lifestyle factors using data from the China Nutrition and Health Surveillance (CNHS; 2015) and derived mortality rates from the Global Burden of Diseases, Injuries, and Risk Factors Study (2015). All three data sources were combined to estimate the life expectancy of individuals at age 30 years following different levels of lifestyle factors by using the life table method. The cause-specific decomposition of the life expectancy differences was analysed using Arriaga's method.

FINDINGS

After the exclusion of CKB participants with coronary heart disease, stroke, cancer, or missing BMI data at baseline, 487 209 were included in the primary analysis. Participants with COPD or asthma at baseline were additionally excluded for chronic respiratory disease-related analysis, leaving 451 233 participants with data available for analysis. Data from 171 127 adults aged 30-84 years from the CNHS 2015 were used to estimate the sex-specific and age-specific prevalence of lifestyle-related factors. There were 42 496 deaths documented over a median follow-up of 11·1 years (IQR 10·2-12·1) in CKB. The adjusted hazard ratios (aHRs) of participants adopting five versus 0-1 low-risk factors was 0·38 (95% CI 0·34-0·43) for all-cause mortality, aHR 0·37 (0·30-0·46) for cardiovascular disease mortality, aHR 0·47 (0·39-0·56) for cancer mortality, and aHR 0·30 (0·14-0·64) for chronic respiratory disease mortality. The life expectancy at age 30 years for individuals with 0-1 low-risk factors was on average 41·7 years (95% CI 41·5-42·0) for men and 47·3 years (46·6-48·0) for women. For individuals with all five low-risk factors, the life expectancy at age 30 was 50·5 years (95% CI 48·5-52·4) for men and 55·4 years (53·5-57·4) for women; meaning a difference of 8·8 years (95% CI 6·8-10·7) for men and 8·1 years (6·5-9·9) for women. The estimated extended life expectancy for men and women was mainly attributable to reduced death from cardiovascular disease (2·4 years [27% of the total extended life expectancy] for men and 3·7 years [46%] for women), cancer (2·6 years [30%] for men and 0·9 years [11%] for women), and chronic respiratory disease (0·6 years [7%] for men and 1·2 years [15%] for women).

INTERPRETATION

Our findings suggest that increasing the adoption of these five healthy lifestyle factors through public health interventions could be associated with substantial gains in life expectancy in the Chinese population.

FUNDING

National Natural Science Foundation of China, National Key Research and Development Program of China, Kadoorie Charitable Foundation, UK Wellcome Trust.

Evaluation of the PREDIGT score’s performance in identifying newly diagnosed Parkinson’s patients without motor examination

Several recent publications described algorithms to identify subjects with Parkinson’s disease (PD). In creating the “PREDIGT Score”, we previously developed a hypothesis-driven, simple-to-use formula to potentially calculate the incidence of PD. Here, we tested its performance in the ‘De Novo Parkinson Study’ (DeNoPa) and ‘Parkinson’s Progression Marker Initiative’ (PPMI); the latter included participants from the ‘FOllow Up persons with Neurologic Disease’ (FOUND) cohort. Baseline data from 563 newly diagnosed PD patients and 306 healthy control subjects were evaluated. Based on 13 variables, the original PREDIGT Score identified recently diagnosed PD patients in the DeNoPa, PPMI + FOUND and the pooled cohorts with area-under-the-curve (AUC) values of 0.88 (95% CI 0.83–0.92), 0.79 (95% CI 0.72–0.85), and 0.84 (95% CI 0.8–0.88), respectively. A simplified version (8 variables) generated AUC values of 0.92 (95% CI 0.89–0.95), 0.84 (95% CI 0.81–0.87), and 0.87 (0.84–0.89) in the DeNoPa, PPMI, and the pooled cohorts, respectively. In a two-step, screening-type approach, self-reported answers to a questionnaire (step 1) distinguished PD patients from controls with an AUC of 0.81 (95% CI 0.75–0.86). Adding a single, objective test (Step 2) further improved classification. Among seven biological markers explored, hyposmia was the most informative. The composite AUC value measured 0.9 (95% CI 0.88–0.91) in DeNoPa and 0.89 (95% CI 0.84–0.94) in PPMI. These results reveal a robust performance of the original PREDIGT Score to distinguish newly diagnosed PD patients from controls in two established cohorts. We also demonstrate the formula’s potential applicability to enriching for PD subjects in a population screening-type approach.

Impact of Physical Activity on the Characteristics and Metabolic Consequences of Alcohol Consumption: A Cross-Sectional Population-Based Study

Sedentary lifestyle and excessive alcohol drinking are major modifiable risk factors of health. In order to shed further light on the relationships between physical activity and health consequences of alcohol intake, we measured biomarkers of liver function, inflammation, lipid status and fatty liver index tests in a large population-based sample of individuals with different levels of physical activity, alcohol drinking and other lifestyle risk factors. The study included 21,050 adult participants (9940 men, 11,110 women) (mean age 48.2 ± 13.3 years) of the National FINRISK Study. Data on physical activity, alcohol drinking, smoking and body weight were recorded. The participants were classified to subgroups according to gender, levels of physical activity (sedentary, low, moderate, vigorous, extreme), alcohol drinking levels (abstainers, moderate drinkers, heavy drinkers) and patterns (regular or binge, types of beverages preferred in consumption). Serum liver enzymes (GGT, ALT), C-reactive protein (CRP) and lipid profiles were measured using standard laboratory techniques. Physical activity was linearly and inversely related with the amount of alcohol consumption, with the lowest alcohol drinking levels being observed in those with vigorous or extreme activity (p < 0.0005). Physically active individuals were less frequently binge-type drinkers, cigarette smokers or heavy coffee drinkers than those with sedentary activity (p < 0.0005 for linear trend in all comparisons). In the General Linear Model to assess the main and interaction effects of physical activity and alcohol consumption on biomarker status, as adjusted for anthropometric measures, smoking and coffee consumption, increasing levels of physical activity were found to be associated with more favorable findings on serum GGT (p < 0.0005), ALT (p < 0.0005 for men), cholesterol (p = 0.025 for men; p < 0.0005 for women), HDL-cholesterol (p < 0.0005 for men, p = 0.001 for women), LDL-cholesterol (p < 0.03 for men), triglycerides (p < 0.0005 for men, p < 0.03 for women), CRP (p < 0.0005 for men, p = 0.006 for women) and fatty liver index (p < 0.0005). The data support the view that regular moderate to vigorous physical activity may counteract adverse metabolic consequences of alcohol consumption on liver function, inflammation and lipid status. The role of physical activity should be further emphasized in interventions aimed at reducing health problems related to unfavorable risk factors of lifestyle.

Diet Composition, Anthropometrics, and Mortality Risk

While overeating is considered a cause of the obesity epidemic as quantified by body mass index (BMI), the association of diet with a body shape index (ABSI) and hip index (HI), which are transformations of waist and hip circumference that are independent of BMI and which predict mortality risk, is poorly known. We used data from the Atherosclerosis Risk in Communities (ARIC) study of about 15,000 middle-aged adults to investigate associations between macronutrient intake (energy, carbohydrate, protein, and fat, the latter two divided into plant and animal sources, all based on self-reported food frequency) with anthropometric indices (BMI, ABSI, and HI). We also analyzed the association of diet and anthropometrics with death rate during approximately 30 years of follow-up. High intake of energy and animal fat and protein was generally associated with higher ABSI and lower HI at baseline, as well as greater mortality hazard. BMI was also positively linked with animal fat and protein intake. In contrast, higher intake of carbohydrates and plant fat and protein was associated with lower ABSI and BMI, higher HI, and lower mortality hazard. For example, after adjustment for potential confounders, each standard deviation of additional plant fat intake (as a fraction of total energy) was associated with a 5% decrease in mortality rate, while animal fat intake was associated with a 5% mortality increase per standard deviation. The directions of the associations between diet and anthropometrics are consistent with those found between anthropometrics and mortality without reference to diet.

Association between healthy lifestyle and the occurrence of cardiometabolic multimorbidity in hypertensive patients: a prospective cohort study of UK Biobank

BACKGROUND

Cardiometabolic multimorbidity (CMM) is becoming increasingly common in patients with hypertension, and it is well established that healthy lifestyle plays a key role in the prevention of hypertension. However, the association between combined lifestyle factors and CMM in patients with hypertension is uncertain.

METHODS

This prospective analysis included the data (obtained from the UK biobank) of participants with hypertension who did not have coronary heart disease (CHD), stroke, or diabetes. The outcome was the occurrence of CMM, defined as ≥ 1 disease of CHD, stroke, and diabetes that occurred in participants with hypertension. Four lifestyle factors (smoking, alcohol consumption, diet, and physical activity) were assessed using a weighted healthy lifestyle score, and participants were divided into four groups: the very unhealthy, unhealthy, healthy, and very healthy groups. The flexible parameter Royston-Parmar proportional hazard model was used to estimate hazard ratios (HRs) between lifestyles and CMM, as well as the difference in CMM-free life expectancy.

RESULTS

During a median follow-up of 12.2 years, 9812 (18.4%) of the 53,397 hypertensive patients occurred CMM. Compared with the very unhealthy group, the very healthy group had a 41% reduction in the risk for CMM in hypertensive patients and a 32-50% reduction in the risk for specific cardiometabolic diseases such as CHD, stroke, and diabetes. For each lifestyle factor, non-smoking had the greatest protective effect against CMM (HR: 0.64, 95% confidence interval (CI) 0.60-0.68). A lifestyle combining multiple healthy factors extended CMM-free life expectancy (e.g., six years longer at age 45 years for participants in the very healthy group).

CONCLUSIONS

Combined healthy lifestyle factors were associated with a lower risk for CMM in hypertensive patients. This suggests that combined healthy lifestyle should be supported to decrease disease burden.

The Impact of Education and Lifestyle Factors on Disability-Free Life Expectancy From Mid-Life to Older Age: A Multi-Cohort Study

Objectives: Low education and unhealthy lifestyle factors such as obesity, smoking, and no exercise are modifiable risk factors for disability and premature mortality. We aimed to estimate the individual and joint impact of these factors on disability-free life expectancy (DFLE) and total life expectancy (TLE).

Methods: Data (n = 22,304) were from two birth cohorts (1921–26 and 1946–51) of the Australian Longitudinal Study on Women’s Health and linked National Death Index between 1996 and 2016. Discrete-time multi-state Markov models were used to assess the impact on DFLE and TLE.

Results: Compared to the most favourable combination of education and lifestyle factors, the least favourable combination (low education, obesity, current/past smoker, and no exercise) was associated with a loss of 5.0 years TLE, 95% confidence interval (95%CI): 3.2–6.8 and 6.4 years DFLE (95%CI: 4.8–7.8) at age 70 in the 1921–26 cohort. Corresponding losses in the 1946–51 cohort almost doubled (TLE: 11.0 years and DFLE: 13.0 years).

Conclusion: Individual or co-ocurrance of lifestyle risk factors were associated with a significant loss of DFLE, with a greater loss in low-educated women and those in the 1946–51 cohort.

Associations between sleep patterns, smoking, and alcohol use among older adults in Canada: Insights from the Canadian Longitudinal Study on Aging (CLSA)

Poor sleep is associated with chronic health conditions among older adults. As substance use rates increase in this population, age-related physiological and cognitive declines may exacerbate its detrimental consequences, including sleep problems. We analyzed cross-sectional associations between sleep patterns, smoking, and alcohol use using baseline data from 30,097 community-dwelling Canadian adults aged 45-85 years from the Canadian Longitudinal Study on Aging. Insomnia symptoms (difficulties falling/staying asleep), sleep duration (short:<6h; long:>8h), and sleep satisfaction(dissatisfied/neutral/satisfied) were measured. Smoking and alcohol-use frequency (past 12 months), average daily amount (past 30 days), and binge drinking (past 12 months) were self-reported, and associations were examined using modified Poisson regression. Approximately 23% of participants had insomnia symptoms, and 26% reported sleep dissatisfaction. 91% of participants were current non-smokers, whereas 7% reported smoking daily. Over 50% drank ≤ 2 drinks daily, and 3% reported binge drinking. There was a higher adjusted prevalence of insomnia among daily smokers (PR = 1.10, 95% CI = 1.00-1.21) and binge drinkers (PR = 1.21, 95% CI = 1.02-1.43). Odds of short sleep duration were lower among regular drinkers (COR = 0.71, 95% CI = 0.56-0.90) and higher among daily smokers (COR = 1.19, 95% CI = 1.01-1.40). Heavy and frequent smoking and alcohol use are associated with both insomnia symptoms and sleep dissatisfaction, but not consistently with sleep duration. Further longitudinal investigation of this relationship in aging populations is needed in clinical and public health settings to infer the extent of causality and design effective public health interventions in this vulnerable population.

Association between the visceral adiposity index and risks of all-cause and cause-specific mortalities in a large cohort: Findings from the UK biobank

BACKGROUND AND AIMS

The visceral adiposity index (VAI) has been recently established as a measure of visceral fat distribution and is shown to be associated with a wide range of adverse health events. However, the precise associations between the VAI score and all-cause and cause-specific mortalities in the general population remain undetermined.

METHODS AND RESULTS

In this large-scale prospective epidemiological study, 357,457 participants (aged 38-73 years) were selected from the UK Biobank. We used Cox competing risk regression models to estimate the association between the VAI score and all-cause, cardiovascular disease (CVD), cancer, and other mortalities. The VAI score was significantly correlated with an increased risk of all-cause mortality (hazard ratio [HR], 1.200; 95% confidence interval [CI], 1.148-1.255; P < 0.0001), cancer mortality (HR, 1.224; 95% CI, 1.150-1.303; P < 0.0001), CVD mortality (HR, 1.459; 95% CI, 1.148-1.255; P < 0.0001), and other mortalities (HR, 1.200; 95% CI, 1.148-1.255; P < 0.0001) after adjusting for a series of confounders. In addition, the subgroup analyses showed that HRs were significantly higher in participants who were male, aged below 65 years, and body mass index less than 25.

CONCLUSION

In summary, VAI was positively associated with an increased risk of all-cause and cause-specific mortalities in a nationwide, well-characterised population identified in a UK Biobank. The VAI score might be a complementary traditional predictive indicator for evaluating the risk of adverse health events in the population of Western adults aged 38 years and older.

The Impact of 51 Risk Factors on Life Expectancy in Canada: Findings from a New Risk Prediction Model Based on Data from the Global Burden of Disease Study

The aims of this study were (1) to develop a comprehensive risk-of-death and life expectancy (LE) model and (2) to provide data on the effects of multiple risk factors on LE. We used data for Canada from the Global Burden of Disease (GBD) Study. To create period life tables for males and females, we obtained age/sex-specific deaths rates for 270 diseases, population distributions for 51 risk factors, and relative risk functions for all disease-exposure pairs. We computed LE gains from eliminating each factor, LE values for different levels of exposure to each factor, and LE gains from simultaneous reductions in multiple risk factors at various ages. If all risk factors were eliminated, LE in Canada would increase by 6.26 years for males and 5.05 for females. The greatest benefit would come from eliminating smoking in males (2.45 years) and high blood pressure in females (1.42 years). For most risk factors, their dose-response relationships with LE were non-linear and depended on the presence of other factors. In individuals with high levels of risk, eliminating or reducing exposure to multiple factors could improve LE by several years, even at a relatively advanced age.

Non-linear relations between life expectancy, socio-economic, and air pollution factors: a global assessment with spatial disparities

Influential factors of socio-economic and air pollution on life expectancy (LE) show complexity. The investigations of non-linear functions of LE, socio-economic, and air pollution factors have not been largely conducted, and spatial and temporal differences of the linear or non-linear relations between LE and the influential factors have been obscured across countries in the world. In this study, the non-linear relations between LE and factors of per capita gross national income (GNI_pc), urban population rate (UPR), and fine-particulate (PM_2.5) were estimated from 2000 to 2015 by using a generalized additive model (GAM). The collected data included the 219 countries and regions with sufficient data and covers the period 2000-2015. The results demonstrate that at the global level, the GNI_pc plays a stable and significant non-linear role in LE, while the non-linear relationships between UPR, PM_2.5, and LE are not significant. The temporal variation was further investigated that the non-linear effect of PM_2.5 on LE is gradually strengthened, and the non-linear effect of UPR on LE shows a weakened trend. However, GNI_pc always plays a significantly non-linear role in the LE level. Furthermore, the spatial difference in the non-linear relations among different continents is detected. In sum, it cannot be ignored the non-linear effects of socio-economic and air pollution factors on LE at a global scale and across different continents.

Behavioral Health Risk Factors and Motivation to Change among Cardiovascular General Hospital Patients Aged 50 to 79 Years

Little is known about the (co-)occurrence of smoking, alcohol at-risk drinking, physical inactivity and overweight, and the motivation to change these behavioral health risk factors (HRFs) in older general hospital patients with cardiovascular disease. Between October and December 2016, all consecutively admitted patients aged 50 to 79 years were proactively recruited on 3 cardiology wards and asked to participate in a survey on HRFs and behavior change motivation. Of the eligible patients, 80.4% participated in the survey (n = 328). The mean age was 66.5 years (standard deviation 9.0), and 65.5% were male. At least 1 HRF was present in 91.8% (n = 280), at least 2 HRFs in 54.4% (n = 166), and 3 or 4 HRFs in 12.1% (n = 37) of participants. The proportion of older adults who contemplated or were changing or planning to change their behavior to meet health behavior recommendations ranged between 66.0% (smoking) and 93.2% (alcohol consumption). The results indicate a notable co-occurrence of behavioral HRFs in older patients with cardiovascular disease. The majority of older adults were at least considering changing the respective behavior. To prevent and treat diseases efficiently, hospitalization may be a suitable moment for systematic multiple HRF screening and intervention.

Impact of modifiable healthy lifestyle adoption on lifetime gain from middle to older age

OBJECTIVE

this study explored whether the modification of selected lifestyles is likely to increase life expectancy from middle age onwards, regardless of the presence of major comorbidities.

METHODS

we examined a prospective cohort of 20,373 men and 26,247 women aged 40-80 years. Eight modifiable lifestyle factors were assessed: consumption of fruit, fish and milk, walking and/or sports participation, body-mass index, smoking status, alcohol consumption and sleep duration. Modifiable healthy lifestyle factors scored one point each, for a maximum of eight points. The impact of modifiable healthy lifestyle adoption on lifetime gain during the ages of 40-102 years was analysed.

FINDINGS

during the median 21 years of follow-up, 8,966 individuals (3,683 men and 5,283 women) died. Life expectancy at 40 years (95% confidence intervals) for 7-8 health lifestyle points was 46.8 (45.6-48.1) and 51.3 (50.0-52.6) years for men and women, respectively. The potential impact of modifiable healthy lifestyle adoption on lifetime gain persisted over the age of 80 years or more, in individuals with ≥5 factors (P < 0.001), particularly older men. The benefits were more pronounced among patients with major comorbidities, such as cardiovascular disease, cancer, hypertension, diabetes, kidney disease and those with multimorbidity throughout all age categories.

CONCLUSION

adopting modifiable healthy lifestyles was associated with lifetime gain, even in individuals aged 80 years or more, regardless of the presence of any major comorbidities in each life stage since middle age. The findings imply the importance of improving the one's lifestyle for an increased lifespan, even among older patients and/or those with multimorbidity.

Is Religiousness Associated with Better Lifestyle and Health Among Danes? Findings from SHARE

Evidence of a possible association between religion and health in secular societies is sparse. We therefore conducted a nationwide study using data from 1596 Danes aged 50 + who participated in the Survey of Health, Ageing and Retirement in Europe (SHARE) wave 1 (2004-2005) and were followed up between 2006 and 2015, to investigate the association between religiousness and health including a lifestyle index. Results from the longitudinal models adjusted for age and gender showed that being religiously educated by parents, taking part in a religious organization, and praying were factors associated with fewer risk factors of unhealthy lifestyle. Furthermore, being religiously educated was associated with lower odds of self-rated poor health and depressive symptoms. Results were overall consistent across the cross-sectional and longitudinal models and persisted after further adjustment for education and marital status. These findings provide support for a positive relationship between religiousness and health among Danes, particularly for those being religiously educated by their parents.

Association Between Living Risk and Healthy Life Years Lost Due to Multimorbidity: Observations From the China Health and Retirement Longitudinal Study

Background

Multimorbidity has an effect on life expectancy, while its effect on healthy life years is unclear. This study aims to investigate the associations between healthy life years lost due to multimorbidity and living risk.

Methods

The participants of The China Health and Retirement Longitudinal Study (CHARLS) were assessed at four visits between 2011 (baseline) and 2018. At baseline, 13,949 individuals were administered surveys. A combined score based on seven health-related factors was calculated, and the participants were classified into 3 groups based on living risk. We used the adjusted Cox regression methods to examine the associations between living risk groups and multimorbidity. We estimated the healthy life years lost due to multimorbidity using the Sullivan method.

Results

A total of 9,091 adults aged 45 years or older (mean age of 59.55 ± 9.50 years with one disease, 52.60% women) were analyzed in the CHARLS. The probability of no multimorbidity over 7 years decreased from 0.9947 to 0.9697 in the low-risk group, whereas the probability of multimorbidity in low living risk was lower than that of high living risk, ranging from HR 1.253 (95% CI.992–1.581; P = 0.058) to 1.431 (1.05–1.949; P = 0.023) in sex, and ranging from HR 1.340 (95% CI 1.106–1.623; P = 0.003) to 2.002 (1.058–3.787; P = 0.033) in area. At 45 years, the healthy life years lost in men was <0.27 years compared to women in the low-risk group. Hypertension increased the risk of multimorbidity with an HR of 1.5 (95% CI 1.21–1.91; P < 0.001) in men. In urban areas, participants with diabetes had 3.2 times (95% CI 1.75–5.94, P < 0.001) higher risk of multimorbidity than participants without diabetes.

Conclusions

These findings indicate that a low-risk lifestyle could decrease the loss of healthy life years under multimorbidity. The probability of multimorbidity in women and in urban areas was high. Hypertension was correlated with the hazard risk of multimorbidity.

Impact of a Clinical Decision Support System for Addressing Physical Activity and/or Healthy Eating during Smoking Cessation Treatment: Hybrid Type I Randomized Controlled Trial (Preprint)

Background

People who smoke have other risk factors for chronic diseases, such as low levels of physical activity and poor diet. Clinical decision support systems (CDSSs) might help health care practitioners integrate interventions for diet and physical activity into their smoking cessation programming but could worsen quit rates.

Objective

The aims of this study are to assess the effects of the addition of a CDSS for physical activity and diet on smoking cessation outcomes and to assess the implementation of the study.

Methods

We conducted a pragmatic hybrid type I effectiveness-implementation trial with 232 team-based primary care practices in Ontario, Canada, from November 2019 to May 2021. We used a 2-arm randomized controlled trial comparing a CDSS addressing physical activity and diet to treatment as usual and used the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework to measure implementation outcomes. The primary outcome was self-reported 7-day tobacco abstinence at 6 months.

Results

We enrolled 5331 participants in the study. Of these, 2732 (51.2%) were randomized to the intervention group and 2599 (48.8%) to the control group. At the 6-month follow-up, 29.7% (634/2137) of respondents in the intervention arm and 27.3% (552/2020) in the control arm reported abstinence from tobacco. After multiple imputation, the absolute group difference was 2.1% (95% CI −0.5 to 4.6; F_1,1000.42=2.43; P=.12). Mean exercise minutes changed from 32 (SD 44.7) to 110 (SD 196.1) in the intervention arm and from 32 (SD 45.1) to 113 (SD 195.1) in the control arm (group effect: B=−3.7 minutes; 95% CI −17.8 to 10.4; P=.61). Servings of fruit and vegetables changed from 2.64 servings to 2.42 servings in the intervention group and from 2.52 servings to 2.45 servings in the control group (incidence rate ratio for intervention group=0.98; 95% CI 0.93-1.02; P=.35).

Conclusions

A CDSS for physical activity and diet may be added to a smoking cessation program without affecting the outcomes. Further research is needed to improve the impact of integrated health promotion interventions in primary care smoking cessation programs.

Trial Registration

ClinicalTrials.gov NCT04223336 https://www.clinicaltrials.gov/ct2/show/NCT04223336

International Registered Report Identifier (IRRID)

RR2-10.2196/19157

Temporal and Spatial Trends From Counterfactual Scenarios of Physical Activity on Mortality, Years of Life Lost, and Life Expectancy Due to Noncommunicable Diseases in Argentina

BACKGROUND

This study estimates the spatial distribution and trends in preventable deaths, years of life lost (YLL), and life expectancy (LE), associated with noncommunicable diseases under alternative distributions of physical activity in Argentina.

METHODS

Potential impact fractions were used to calculate the preventable deaths and YLL attributable to various scenarios of physical activity. Cause-eliminated life tables were used to estimate LE gains, and Monte Carlo simulations were performed for uncertainty analysis.

RESULTS

From 2005 to 2018, physical activity could have prevented up to 7544 to 8220 potential deaths (≈4.27% of major noncommunicable diseases and ≈2.66% of all causes) and about 221 to 219 YLL per 100,000 inhabitants; between 0.67 and 0.71 years of LE could have been gained. If the World Health Organization recommendations (at least 600 metabolic equivalent tasks minutes per week) had been achieved, between 2813 and 3111 potential deaths could have been prevented, about 80 fewer years of life (per 100,000 inhabitants) would have been lost, and 0.23 years of LE could have been gained. A 15% reduction in insufficient physical activity has shown a small impact on outcomes.

CONCLUSION

Public health initiatives aimed at increasing population-wide physical activity could reduce noncommunicable disease deaths in Argentina.

Describing the linkage between administrative social assistance and health care databases in Ontario, Canada

Background

The linkage of records across administrative databases has become a powerful tool to increase information available to undertake research and analytics in a privacy protective manner.

Objective

The objective of this paper was to describe the data integration strategy used to link the Ontario Ministry of Children, Community and Social Services (MCCSS)-Social Assistance (SA) database with administrative health care data.

Methods

Deterministic and probabilistic linkage methods were used to link the MCCSS-SA database (2003-2016) to the Registered Persons Database, a population registry containing data on all individuals issued a health card number in Ontario, Canada. Linkage rates were estimated, and the degree of record linkage and representativeness of the dataset were evaluated by comparing socio-demographic characteristics of linked and unlinked records.

Results

There were a total of 2,736,353 unique member IDs in the MCCSS-SA database from the 1^st January 2003 to 31^st December 2016; 331,238 (12.1%) were unlinked (linkage rate = 87.9%). Despite 16 passes, most record linkages were obtained after 2 deterministic (76.2%) and 14 probabilistic passes (11.7%). Linked and unlinked samples were similar for most socio-demographic characteristics (i.e., sex, age, rural dwelling), except migrant status (non-migrant versus migrant) (standardized difference of 0.52). Linked and unlinked records were also different for SA program-specific characteristics, such as social assistance program, Ontario Works and Ontario Disability Support Program (standardized difference of 0.20 for each), data entry system, Service Delivery Model Technology only and both Service Delivery Model Technology and Social Assistance Management System (standardized difference of 0.53 and 0.52, respectively), and months on social assistance (standardized difference of 0.43).

Conclusions

Additional techniques to account for sub-optimal linkage rates may be required to address potential biases resulting from this data linkage. Nonetheless, the linkage between administrative social assistance and health care data will provide important findings on the social determinants of health.

Cardiovascular health and healthy longevity in people with and without cardiometabolic disease: A prospective cohort study

BACKGROUND

Existing evidence suggest an association of cardiovascular health (CVH) level with cardiometabolic disease (CMD) and mortality, but the effect of CVH on life expectancy, particularly survival years in CMD patients, has not been well-established. This study aimed to investigate the association of CVH defined using the 7-item tool from the American Heart Association (AHA) with life expectancy in people with and without CMD.

METHODS

Between 2006 and 2010, a total of 341,331 participants (age 37-73 years) in the UK Biobank were examined and thereafter followed up to 2020. The CVH raised by the AHA included 4 behavioral (smoking, diet, physical activity, body mass index) and 3 biological (fasting glucose, blood cholesterol, blood pressure) metrics, coded on a three-point scale (0, 1, 2). The CVH score was the sum of 7 metrics (score range 0-14) and was then categorized into poor (scores 0-6), intermediate (7-11), and ideal (12-14) CVH. The flexible parametric survival models were applied to estimate life expectancy.

FINDINGS

During a median follow-up of 11.4 years, 18,420 (5.4%) deaths occurred. The multivariable-adjusted hazard ratio (HRs) of all-cause mortality were 2.21 (95% CI: 1.77 to 2.75) for male and 2.63 (95% CI: 2.22 to 3.12) for female with prevalent CMD and a poor CVH compared with CMD-free and ideal CVH group, an ideal CVH attenuated the CMD-related risk of mortality by approximately 62% for male and 53% for female. In CMD patients, an ideal CVH compared to poor CVH was associated with additional life years gain of 5.50 (95% CI: 3.94-7.05) for male 4.20 (95% CI: 2.77-5.62) for female at the age of 45 years. Corresponding estimates in those without CMD were 4.55 (95% CI: 3.62-5.48) and 4.89 (95% CI: 3.99-5.79), respectively. Ideal smoking status, fasting glucose and physical activity for male and ideal smoking status, cholesterol level and physical activity for female contributed to the greatest survival benefit.

INTERPRETATION

An ideal CVH is associated with a lower risk of premature mortality and longer life expectancy whether in general population or CMD patients. Our study highlights the benefits of maintaining better CVH across the life course and calls attention to the need for comprehensive strategies (healthy behavioral lifestyle and biological phenotypes) to preserve and restore a higher CVH level.

FUNDING

Scientific Research Foundation for Scholars of HZNU (Grant No. 4265C50221204119).

Serum markers of biological ageing provide long-term prediction of life expectancy-a longitudinal analysis in middle-aged and older German adults

BACKGROUND

lifestyle behaviours and chronic co-morbidities are leading risk factors for premature mortality and collectively predict wide variability in individual life expectancy (LE). We investigated whether a pre-selected panel of five serum markers of biological ageing could improve predicting the long-term mortality risk and LE in middle-aged and older women and men.

METHODS

we conducted a case-cohort study (n = 5,789 among which there were 2,571 deaths) within the European Prospective Investigation into Cancer-Heidelberg cohort, a population cohort of middle-aged and older individuals, followed over a median duration of 18 years. Gompertz models were used to compute multi-adjusted associations of growth differentiation factor-15, N-terminal pro-brain natriuretic peptide, glycated haemoglobin A1c, C-reactive protein and cystatin-C with mortality risk. Areas under estimated Gompertz survival curves were used to estimate the LE of individuals using a model with lifestyle-related risk factors only (smoking history, body mass index, waist circumference, alcohol, physical inactivity, diabetes and hypertension), or with lifestyle factors plus the ageing-related markers.

RESULTS

a model including only lifestyle-related factors predicted a LE difference of 16.8 [95% confidence interval: 15.9; 19.1] years in men and 9.87 [9.20; 13.1] years in women aged ≥60 years by comparing individuals in the highest versus the lowest quintiles of estimated mortality risk. Including the ageing-related biomarkers in the model increased these differences up to 22.7 [22.3; 26.9] years in men and 14.00 [12.9; 18.2] years in women.

CONCLUSIONS

serum markers of ageing are potentially strong predictors for long-term mortality risk in a general population sample of older and middle-aged individuals and may help to identify individuals at higher risk of premature death, who could benefit from interventions to prevent further ageing-related health declines.

The Impact of Smoking and Multiple Health Behaviors on All-Cause Mortality

Four common health risk behaviors have the greatest impact on all-cause mortality risk, but studies are needed with larger samples and the appropriate age range for cigarette smokers. We examined the impact of smoking in the context of multiple health behaviors on all-cause mortality using a nationally representative sample of adults aged 30 and older in the United States. National Health Interview Survey data from 1997 to 2005 were linked to the National Death Index with a follow-up to December 2015. The primary dependent variable was all-cause mortality, and the primary predictors were smoking, heavy drinking, physical inactivity, and unhealthy weight (underweight or obesity). The sample contained 189,087 individuals (≥ age 30; population estimate = 140.7 million). Our primary statistical analysis tool involved fitting Cox proportional hazards models. Our findings demonstrated that smoking led to the highest mortality risk among the four risk behaviors examined, but more than half of smokers engaged in at least one additional health risk behavior. Smokers who engaged in multiple health behaviors experienced higher increased mortality risks: smoking combined with one other health risk behavior increased mortality risk by 32% and by 82% when combined with two behaviors. Engaging in all four risk behaviors more than doubled the mortality risk of smokers. Smoking cessation interventions that address multiple risk behaviors-physical inactivity, heavy drinking, and unhealthy weight-will likely prevent premature death better than interventions that address only smoking.

Examining if changes in gender-specific and co-ed intramural programs affect youth physical activity over time: a natural experiment evaluation using school- and student-level data from the COMPASS study

BACKGROUND

Despite the benefits of physical activity (PA), the majority of Canadian youth are falling short of the recommended 60 min of moderate-to-vigorous physical activity (MVPA) per day. School-based physical activity programs such as intramurals, are important opportunities for youth to be physically active. There is limited evidence available on the impact of gender-specific (e.g., female-only, male-only) and co-ed intramurals on youth PA over time, however, evidence suggests female-only intramurals may be important for female MVPA. This research aims to capitalize on a natural experiment to generate practice-based evidence on the impact of changes in gender-specific and co-ed intramurals on youth MVPA over time.

METHODS

This study used linked longitudinal school- and student-level data from Ontario secondary schools in year 5 (Y5:2016-2017), year 6 (Y6: 2017-2018) and year 7 (Y7: 2018-2019) of the COMPASS study. Data on intramurals from 55 schools were used to determine the changes to gender-specific and co-ed intramurals that occurred from Y5 to Y6. Baseline demographic characteristics were measured and data on PA and sport participation were collected in Y5, Y6 and Y7 on a sample of 4417 students. Hierarchical linear mixed regression models were used to estimate how changes in gender-specific and co-ed intramurals were associated with youth MVPA over time.

RESULTS

Participation in intramural, varsity and community sport were all positively and significantly associated with youth MVPA. Changes in gender-specific and co-ed intramurals were not significantly associated with youth MVPA in Y6 or Y7. However, the positive association between maintaining the addition of gender-specific intramurals on female MVPA in Y7 was on par with the significance level of α = 0.05, suggesting that adding gender-specific intramurals may be important for female MVPA.

CONCLUSIONS

Adding gender-specific and co-ed intramurals may not be sufficient strategies to increase PA among youth. Further research should explore the effect of gender-specific intramurals on youth PA, as this study may have been underpowered at the school-level. Gender-specific intramurals may promote a supportive PA environment that promotes MVPA, especially among females. These intramurals may be an important component of more comprehensive strategies to increase youth MVPA.

Protecting vulnerable groups from tobacco-related harm during and following the COVID-19 pandemic

Marginalized populations are being disproportionally affected by the current pandemic. Direct effects include higher infection rates with greater morbidity and mortality; indirect effects stem from the societal response to limit the spread of the virus. These same groups also have smoking rates that are significantly higher than the general population. In this commentary, we discuss how the pandemic has been acting to further increase the harm from tobacco endured by these groups by applying the syndemic framework. Using this approach, we elaborate on the factors that promote clustering of harms from tobacco with harms from COVID-19. These include the worsening of psychological distress, a potential increase in smoking behaviour, greater exposure to second-hand smoke and less access to smoking cessation services. Then, we offer mitigation strategies to protect disadvantaged groups from tobacco-related harm during and following the COVID-19 pandemic. These strategies include affordable smoking cessation services, a proactive approach for smoking treatment using information technology, opportunistic screening and treatment of tobacco dependence among individuals presenting for COVID-19 vaccination, policy interventions for universal coverage of cessation pharmacotherapy, comprehensive smoke-free policies and regulation of tobacco retail density. Now more than ever, coordinated action between clinicians, health care systems, public health organizations and health policy makers is needed to protect vulnerable groups from the harm of tobacco.

The impact of multimorbidity level and functional limitations on the accuracy of using self-reported survey data compared to administrative data to measure general practitioner and specialist visits in community-living adults

Background

Researchers often use survey data to study the effect of health and social variables on physician use, but how self-reported physician use compares to administrative data, the gold standard, in particular within the context of multimorbidity and functional limitations remains unclear. We examine whether multimorbidity and functional limitations are related to agreement between self-reported and administrative data for physician use.

Methods

Cross-sectional data from 52,854 Ontario participants of the Canadian Community Health Survey linked to administrative data were used to assess agreement on physician use. The number of general practitioner (GP) and specialist visits in the previous year was assessed using both data sources; multimorbidity and functional limitation were from self-report.

Results

Fewer participants self-reported GP visits (84.8%) compared to administrative data (89.1%), but more self-reported specialist visits (69.2% vs. 64.9%). Sensitivity was higher for GP visits (≥90% for all multimorbidity levels) compared to specialist visits (approximately 75% for 0 to 90% for 4+ chronic conditions). Specificity started higher for GP than specialist visits but decreased more swiftly with multimorbidity level; in both cases, specificity levels fell below 50%. Functional limitations, age and sex did not impact the patterns of sensitivity and specificity seen across level of multimorbidity.

Conclusions

Countries around the world collect health surveys to inform health policy and planning, but the extent to which these are linked with administrative, or similar, data are limited. Our study illustrates the potential for misclassification of physician use in self-report data and the need for sensitivity analyses or other corrections.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-07160-2.

Risk stratification for COVID-19 hospitalization: a multivariable model based on gradient-boosting decision trees

BACKGROUND

The COVID-19 pandemic has led to an increased demand for health care resources and, in some cases, shortage of medical equipment and staff. Our objective was to develop and validate a multivariable model to predict risk of hospitalization for patients infected with SARS-CoV-2.

METHODS

We used routinely collected health records in a patient cohort to develop and validate our prediction model. This cohort included adult patients (age ≥ 18 yr) from Ontario, Canada, who tested positive for SARS-CoV-2 ribonucleic acid by polymerase chain reaction between Feb. 2 and Oct. 5, 2020, and were followed up through Nov. 5, 2020. Patients living in long-term care facilities were excluded, as they were all assumed to be at high risk of hospitalization for COVID-19. Risk of hospitalization within 30 days of diagnosis of SARS-CoV-2 infection was estimated via gradient-boosting decision trees, and variable importance examined via Shapley values. We built a gradient-boosting model using the Extreme Gradient Boosting (XGBoost) algorithm and compared its performance against 4 empirical rules commonly used for risk stratifications based on age and number of comorbidities.

RESULTS

The cohort included 36 323 patients with 2583 hospitalizations (7.1%). Hospitalized patients had a higher median age (64 yr v. 43 yr), were more likely to be male (56.3% v. 47.3%) and had a higher median number of comorbidities (3, interquartile range [IQR] 2-6 v. 1, IQR 0-3) than nonhospitalized patients. Patients were split into development (n = 29 058, 80.0%) and held-out validation (n = 7265, 20.0%) cohorts. The gradient-boosting model achieved high discrimination (development cohort: area under the receiver operating characteristic curve across the 5 folds of 0.852; validation cohort: 0.8475) and strong calibration (slope = 1.01, intercept = -0.01). The patients who scored at the top 10% captured 47.4% of hospitalizations, and those who scored at the top 30% captured 80.6%.

INTERPRETATION

We developed and validated an accurate risk stratification model using routinely collected health administrative data. We envision that modelling such risk stratification based on routinely collected health data could support management of COVID-19 on a population health level.

Diet and exercise in NAFLD/NASH: Beyond the obvious

Lifestyle represents the most relevant factor for non-alcoholic fatty liver disease (NAFLD) as the hepatic manifestation of the metabolic syndrome. Although a tremendous body of clinical and preclinical data on the effectiveness of dietary and lifestyle interventions exist, the complexity of this topic makes firm and evidence-based clinical recommendations for nutrition and exercise in NAFLD difficult. The aim of this review is to guide readers through the labyrinth of recent scientific findings on diet and exercise in NAFLD and non-alcoholic steatohepatitis (NASH), summarizing "obvious" findings in a holistic manner and simultaneously highlighting stimulating aspects of clinical and translational research "beyond the obvious". Specifically, the importance of calorie restriction regardless of dietary composition and evidence from low-carbohydrate diets to target the incidence and severity of NAFLD are discussed. The aspect of ketogenesis-potentially achieved via intermittent calorie restriction-seems to be a central aspect of these diets warranting further investigation. Interactions of diet and exercise with the gut microbiota and the individual genetic background need to be comprehensively understood in order to develop personalized dietary concepts and exercise strategies for patients with NAFLD/NASH.

Association of healthy lifestyle score with all-cause mortality and life expectancy: a city-wide prospective cohort study of cancer survivors

BACKGROUND

Adherence to a healthy lifestyle could reduce the cancer mortality in the western population. We conducted a city-wide prospective study in China investigating the association of a healthy lifestyle score with all-cause mortality and the life expectancy in cancer survivors.

METHODS

This prospective cohort study included 46,120 surviving patients who were firstly diagnosed with cancer in Guangzhou. Five low-risk lifestyle factors including never smoking, never alcohol use, regular physical activity (≥ 2 h/week), sufficient sleep (≥ 6 h/day), and normal or high BMI (≥ 18.5 kg/m²) were assessed and a lifestyle score (0-5, a higher score indicates healthier lifestyle) was generated. Hazard ratios (HRs) of all-cause mortality and the life expectancy by levels of the lifestyle scores were estimated.

RESULTS

Of 46,120 cancer survivors registered from 2010 to 2017, during an average follow-up of 4.3 years (200,285 person-years), 15,209 deaths were recorded. Adjusted HRs for mortality in cancer survivors with lifestyle score of 0-2, versus 5, were 2.59 (95% confidence interval (CI): 2.03-3.30) in women, 1.91 (95%CI 1.77-2.05) in men, 2.28 (95%CI 2.03-2.55) in those aged <65 years, and 1.90 (95%CI 1.75, 2.05) in those aged ≥ 65 years. Life expectancy at age 55 for those with a score of 0-2 and 5 was 53.4 and 57.1 months, respectively. We also found that cancer survivors with healthy lifestyle scores of 5 showed 59.9 months of life expectancy on average, which was longer than those with a score of 0-2.

CONCLUSION

Adopting a healthy lifestyle was associated with a substantially lower risk of all-cause mortality and longer life expectancy in cancer survivors. Our findings should be useful for health education and health promotion in primary care and clinical practice.

Development and validation of a predictive algorithm for risk of dementia in the community setting

Background

Most dementia algorithms are unsuitable for population-level assessment and planning as they are designed for use in the clinical setting. A predictive risk algorithm to estimate 5-year dementia risk in the community setting was developed.

Methods

The Dementia Population Risk Tool (DemPoRT) was derived using Ontario respondents to the Canadian Community Health Survey (survey years 2001 to 2012). Five-year incidence of physician-diagnosed dementia was ascertained by individual linkage to administrative healthcare databases and using a validated case ascertainment definition with follow-up to March 2017. Sex-specific proportional hazards regression models considering competing risk of death were developed using self-reported risk factors including information on socio-demographic characteristics, general and chronic health conditions, health behaviours and physical function.

Results

Among 75 460 respondents included in the combined derivation and validation cohorts, there were 8448 cases of incident dementia in 348 677 person-years of follow-up (5-year cumulative incidence, men: 0.044, 95% CI: 0.042 to 0.047; women: 0.057, 95% CI: 0.055 to 0.060). The final full models each include 90 df (65 main effects and 25 interactions) and 28 predictors (8 continuous). The DemPoRT algorithm is discriminating (C-statistic in validation data: men 0.83 (95% CI: 0.81 to 0.85); women 0.83 (95% CI: 0.81 to 0.85)) and well-calibrated in a wide range of subgroups including behavioural risk exposure categories, socio-demographic groups and by diabetes and hypertension status.

Conclusions

This algorithm will support the development and evaluation of population-level dementia prevention strategies, support decision-making for population health and can be used by individuals or their clinicians for individual risk assessment.

cchsflow: an open science approach to transform and combine population health surveys

Setting

The Canadian Community Health Survey (CCHS) is one of the world’s largest ongoing cross-sectional population health surveys, with over 130,000 respondents every two years or over 1.1 million respondents since its inception in 2001. While the survey remains relatively consistent over the years, there are differences between cycles that pose a challenge to analyze the survey over time.

Intervention

A program package called cchsflow was developed to transform and harmonize CCHS variables to consistent formats across multiple survey cycles. An open science approach was used to maintain transparency, reproducibility and collaboration.

Outcomes

The cchsflow R package uses CCHS survey data between 2001 and 2014. Worksheets were created that identify variables, their names in previous cycles, their category structure, and their final variable names. These worksheets were then used to recode variables in each CCHS cycle into consistently named and labelled variables. Following, survey cycles can be combined. The package was then added as a GitHub repository to encourage collaboration with other researchers.

Implication

The cchsflow package has been added to the Comprehensive R Archive Network (CRAN) and contains support for over 160 CCHS variables, generating a combined data set of over 1 million respondents. By implementing open science practices, cchsflow aims to minimize the amount of time needed to clean and prepare data for the many CCHS users across Canada.

A School-Level Examination of the Association between Programs and Policies and Physical Activity Outcomes among Females from the COMPASS Study

(1) The majority of Canadian youth are not meeting physical activity guidelines, and more female than male youth are falling short of these recommendations. School programs and policies are a viable strategy to improve youth physical activity. However, they may differentially affect female and male activity. This study aimed to examine school-level differences in physical activity outcomes among male and female students and to explore how school programs and policies associate with school-level physical activity outcomes among females. (2) This study used data from 136 schools participating in year 7 (Y7 2018–2019) of the COMPASS study. Data on school programs and policies and on student physical activity were collected. School-level means and percentages for outcomes were calculated and compared between males and females and the impact of physical activity programs and policies on female physical activity outcomes were examined. (3) More males met the guidelines, achieved more strength training days and physical activity minutes compared to females. The number of female varsity sports, community partnerships and fitness ambassadors were all positively and significantly associated with female physical activity. (4) Supportive physical activity environments fostered by offering varsity sports, establishing community partnerships and positive role models may promote physical activity among female youth.

Co-designing Behavior Change Resources With Treatment-Seeking Smokers: Engagement Events' Findings

Background: Primary care organizations are well-suited to help patients change their unhealthy behaviors. Evidence shows that risk communication and self-monitoring of behavior are is an effective strategy practitioners can use to promote health behavior change with their patients. In order for this evidence to be actionable, it is important to understand how patients would like this information to be communicated and to operationalize the self-monitoring resources. The objective of this study was to co-create resources that encourage behavior change based on the scientific evidence and from patients with lived experiences.

Materials and Methods: Twenty-seven individuals who participated in a smoking cessation program and engaged in at least one other unhealthy behavior joined one of two engagement events. Each event was 3 h in duration and consisted of two exercises that provided support to participants in reaching a consensus about the types of messages they would like to receive from their practitioner as well as self-monitoring resources they would prefer to use. The first exercise followed an adapted version of the Consensus Methodology developed by the Institute of Cultural Affairs Canada, while the second exercise was in accordance to the Nominal Group Technique.

Results: Participants' preference was to have practitioners convey messages to promote health behavior change that include positive affirmation and to monitor all their health behaviors using a single self-reported tracking sheet.

Conclusions: This paper features the use of engagement events to reflect upon and identify potential resources that treatment seeking smokers prefer to receive while attempting to modify unhealthy behaviors. These resources can be used by health care providers in primary care settings to support health promotion interventions and assist their patients to increase their likelihood of adopting positive changes to risk behaviors.