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

Global burden of hypertensive heart disease and attributable risk factors, 1990-2021: insights from the global burden of disease study 2021

Hypertensive heart disease (HHD) significantly contributes to global morbidity and mortality, worsened by rising hypertension rates. This study aims to assess the burden of HHD from 1990 to 2021, analyzing prevalence, mortality, and disability-adjusted life years (DALYs) stratified by age, sex, and Sociodemographic Index (SDI). Utilizing data from the Global Burden of Disease 2021 project across 204 countries and 21 regions, the study calculated age-standardized rates and evaluated risk factors for prevention priorities. In 2021, there were 12.5 million HHD cases globally, resulting in 1.332 million deaths and 25.4622 million DALYs. Age-standardized rates were 148.3 for prevalence, 16.3 for deaths, and 301.6 for DALYs per 100,000 people, reflecting increases of 18.2% for prevalence but decreases for deaths (- 22%) and DALYs (- 25.8%) since 1990. Eastern Sub-Saharan Africa recorded the highest prevalence (291.8), while Bulgaria had the highest mortality (103.4) and DALY rates (1739.3). Age-specific trends showed that prevalence, deaths, and DALYs increased with age across genders, and at regional levels, DALYs decreased with higher SDI. Major contributing factors included high systolic blood pressure, metabolic risks, high body-mass index, unhealthy diet, alcohol use, and low fruit and vegetable intake. Despite advances in management, HHD remains a global health concern, especially in low-SDI areas. Efforts focused on modifiable risks, like hypertension control and dietary improvements, are essential to mitigate the burden of HHD.

Teaching Preclinical Medical Students Lifestyle Counseling Skills for Patients' Health Behavior Change

Introduction

Physicians face barriers to counseling patients regarding lifestyle, specifically, low perceived importance of and confidence in counseling, leading to underuse. There is a dearth in the literature evaluating educational interventions for counseling skills among preclinical medical students. Closing this gap is crucial to taking advantage of critical opportunities early in training.

Methods

We taught a session on evidence-based counseling for lifestyle changes to 124 preclinical medical students using case scenarios and role-plays. Our evaluation included (1) measures of perceived importance of and confidence in counseling and (2) measures of perceived gains related to learning objectives. We also undertook qualitative analysis of the session evaluation and thematic analysis of written assignments.

Results

There were statistically significant increases in perceived importance of and confidence in lifestyle counseling. Postintervention student responses demonstrated the highest gain for listing and addressing obstacles to physician counseling, followed by applying physician counseling interventions. Students applied models correctly; however, our thematic analysis of written assignments demonstrated room for continued improvement in application of motivational interviewing techniques.

Discussion

It is significant that our session impacted students' attitudes on the importance of lifestyle counseling. Based on the session evaluation, we are refining assignment instructions for clarity, providing more time for each role-play, and starting with a faculty role-play demonstration. Aggregate data over time will be more robust than our single cohort. Our evaluation was limited to self-reported attitudes and role-play transcript review, but future interventions could use thematic analysis of recorded role-plays or direct observation of patient simulations.

The clustering effects of current smoking status, overweight/obesity, and physical inactivity with all-cause and cause-specific mortality risks in U.S. adults

Objective

To estimate the associations of smoking, weight status and physical inactivity with all-cause and cause-specific deaths, and the advanced rate period (RAP) to determine how early death was advanced among United States (U.S.) adults aged 18 years or older.

Methods

We used data from the third National Health and Nutrition Examination Survey (NHANES III) and the 2019 Linked Mortality File (LMF) with a follow-up period of 21.6 years (n = 16,612, including 7,278 deaths). Smoking, weight status, and physical inactivity were obtained from NHANES III and mortality outcomes from the 2019 LMF. Cox regression was used to estimate hazard ratios, RAPs and their corresponding confidence intervals.

Results

For adults who currently smoke, were obese and physically inactive, the rate of dying from all-cause, CVD, and cancer was at least 231 % greater than for those who never smoked, were normal weight and physically active. The RAPs associated with the clustering of these risk factors for all cause, CVD- and cancer-specific cause of deaths were 13.0, 12.1 and 18.9 years older, respectively.

Conclusions

Our findings underscore the need to focus on modifiable risk factors for illness prevention and health promotion and call attention to the increasing clustering of unhealthy risk factors in the U.S. population.

Healthy lifestyle change and all-cause and cancer mortality in the European Prospective Investigation into Cancer and Nutrition cohort

BACKGROUND

Healthy lifestyles are inversely associated with the risk of noncommunicable diseases, which are leading causes of death. However, few studies have used longitudinal data to assess the impact of changing lifestyle behaviours on all-cause and cancer mortality.

METHODS

Within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, lifestyle profiles of 308,497 cancer-free adults (71% female) aged 35-70 years at recruitment across nine countries were assessed with baseline and follow-up questionnaires administered on average of 7 years apart. A healthy lifestyle index (HLI), assessed at two time points, combined information on smoking status, alcohol intake, body mass index, and physical activity, and ranged from 0 to 16 units. A change score was calculated as the difference between HLI at baseline and follow-up. Associations between HLI change and all-cause and cancer mortality were modelled with Cox regression, and the impact of changing HLI on accelerating mortality rate was estimated by rate advancement periods (RAP, in years).

RESULTS

After the follow-up questionnaire, participants were followed for an average of 9.9 years, with 21,696 deaths (8407 cancer deaths) documented. Compared to participants whose HLIs remained stable (within one unit), improving HLI by more than one unit was inversely associated with all-cause and cancer mortality (hazard ratio [HR]: 0.84; 95% confidence interval [CI]: 0.81, 0.88; and HR: 0.87; 95% CI: 0.82, 0.92; respectively), while worsening HLI by more than one unit was associated with an increase in mortality (all-cause mortality HR: 1.26; 95% CI: 1.20, 1.33; cancer mortality HR: 1.19; 95% CI: 1.09, 1.29). Participants who worsened HLI by more than one advanced their risk of death by 1.62 (1.44, 1.96) years, while participants who improved HLI by the same amount delayed their risk of death by 1.19 (0.65, 2.32) years, compared to those with stable HLI.

CONCLUSIONS

Making healthier lifestyle changes during adulthood was inversely associated with all-cause and cancer mortality and delayed risk of death. Conversely, making unhealthier lifestyle changes was positively associated with mortality and an accelerated risk of death.

Assessing Adherence to US LI-RADS Follow-up Recommendations in Vulnerable Patients Undergoing Hepatocellular Carcinoma Surveillance

Purpose To assess adherence to the US Liver Imaging Reporting and Data System (LI-RADS) recommendations for hepatocellular carcinoma (HCC) surveillance and associated patient-level factors in a vulnerable, diverse patient sample. Materials and Methods The radiology report database was queried retrospectively for patients who underwent US LI-RADS-based surveillance examinations at a single institution between June 1, 2020, and February 28, 2021. Initial US and follow-up liver imaging were included. Sociodemographic and clinical data were captured from electronic medical records. Adherence to radiologist recommendation was defined as imaging (US, CT, or MRI) follow-up in 5-7 months for US-1, imaging follow-up in 3-6 months for US-2, and CT or MRI follow-up in 2 months for US-3. Descriptive analysis and multivariable modeling that adjusted for age, sex, race, and time since COVID-19 pandemic onset were performed. Results Among 936 patients, the mean age was 59.1 years; 531 patients (56.7%) were male and 544 (58.1%) were Asian or Pacific Islander, 91 (9.7%) were Black, 129 (13.8%) were Hispanic, 147 (15.7%) were White, and 25 (2.7%) self-reported as other race. The overall adherence rate was 38.8% (95% CI: 35.7, 41.9). The most common liver disease etiology was hepatitis B (60.6% [657 of 936 patients]); 19.7% of patients (183 of 936) had current or past substance use disorder, and 44.8% (416 of 936) smoked. At adjusted multivariable analysis, older age (odds ratio [OR], 1.20; P = .02), male sex (OR, 1.62; P = .003), hepatology clinic attendance (OR, 3.81; P < .001), and recent prior US examination (OR, 2.44; P < .001) were associated with full adherence, while current smoking (OR, 0.39; P < .001) was negatively associated. Conclusion Adherence to HCC imaging surveillance was suboptimal, despite US LI-RADS implementation. Keywords: Liver, Ultrasound, Screening, Abdomen/GI, Cirrhosis, Metabolic Disorders, Socioeconomic Issues Supplemental material is available for this article. © RSNA, 2024.

The influence of socioeconomic status on the association between unhealthy lifestyle factors and adverse health outcomes: a systematic review

Background

Combinations of lifestyle factors (LFs) and socioeconomic status (SES) are independently associated with cardiovascular disease (CVD), cancer, and mortality. Less advantaged SES groups may be disproportionately vulnerable to unhealthy LFs but interactions between LFs and SES remain poorly understood. This review aimed to synthesise the available evidence for whether and how SES modifies associations between combinations of LFs and adverse health outcomes.

Methods

Systematic review of studies that examine associations between combinations of >3 LFs (eg.smoking/physical activity/diet) and health outcomes and report data on SES (eg.income/education/poverty-index) influences on associations. Databases (PubMed/EMBASE/CINAHL), references, forward citations, and grey-literature were searched from inception to December 2021. Eligibility criteria were analyses of prospective adult cohorts that examined all-cause mortality or CVD/cancer mortality/incidence.

Results

Six studies (n=42,467-399,537; 46.5-56.8 years old; 54.6-59.3% women) of five cohorts were included. All examined all-cause mortality; three assessed CVD/cancer outcomes. Four studies observed multiplicative interactions between LFs and SES, but in opposing directions. Two studies tested for additive interactions; interactions were observed in one cohort (UK Biobank) and not in another (National Health and Nutrition Examination Survey (NHANES)). All-cause mortality HRs (95% confidence intervals) for unhealthy LFs (versus healthy LFs) from the most advantaged SES groups ranged from 0.68 (0.32-1.45) to 4.17 (2.27-7.69). Equivalent estimates from the least advantaged ranged from 1.30 (1.13-1.50) to 4.00 (2.22-7.14). In 19 analyses (including sensitivity analyses) of joint associations between LFs, SES, and all-cause mortality, highest all-cause mortality was observed in the unhealthiest LF-least advantaged suggesting an additive effect.

Conclusions

Limited and heterogenous literature suggests that the influence of SES on associations between combinations of unhealthy LFs and adverse health could be additive but remains unclear. Additional prospective analyses would help clarify whether SES modifies associations between combinations of unhealthy LFs and health outcomes.

Registration

Protocol is registered with PROSPERO (CRD42020172588;25 June 2020).

Body mass index and risk of all-cause mortality among elderly Chinese: An empirical cohort study based on CLHLS data

The aim of our study was to evaluate the relationship between body mass index (BMI) and all-cause mortality among elderly Chinese. The subjects of our study were a cohort of 13 319 elderly Chinese enrolled between 2008 and 2018. Participants were classified in three groups: underweight (<18.5 kg/m²), normal weight (18.5-24.9 kg/m²), overweight and obese (≥25 kg/m²) according to different BMI levels. Cox proportional-hazards regression model was used to analyze the association between BMI grouping and the risk of mortality among the three groups and each corresponding subgroup. The restricted cubic spline regression was performed to investigate the variation tendency of BMI and mortality in different groups and subgroups. We found that the hazard ratios (HRs) of mortality in the underweight and the normal-weight groups were 1.213 and 1.104, respectively, compared with those in the overweight and obesity groups. HR for mortality decreased as BMI increased, although this phenomenon was not observed as not a linear relationship in all participants. Nonetheless, this nonlinear relationship was significant in type 2 diabetes patients. Among subjects with non-type 2 diabetes, the shape of the negative curve, reflecting the HR for BMI and mortality, decreased when BMI increased. Our findings suggest that an obesity paradox exists in non-type 2 diabetes patients, in which BMI has a nonlinear negative relationship with mortality. Conversely, in type 2 diabetes patients there is a U-shaped association. Obesity may thus be protective for all-cause mortality among non-diabetic older populations.

The influence of socioeconomic status on the association between unhealthy lifestyle factors and adverse health outcomes: a systematic review

Background: Combinations of lifestyle factors (LFs) and socioeconomic status (SES) are independently associated with cardiovascular disease (CVD), cancer, and mortality. Less advantaged SES groups may be disproportionately vulnerable to unhealthy LFs but interactions between LFs and SES remain poorly understood. This review aimed to synthesise the available evidence for whether and how SES modifies associations between combinations of LFs and adverse health outcomes. Methods: Systematic review of studies that examine associations between combinations of >3 LFs and health outcomes and report data on SES influences on associations. Databases (PubMed/EMBASE/CINAHL), references, forward citations, and grey-literature were searched from inception to December 2021. Eligibility criteria were analyses of prospective adult cohorts that examined all-cause mortality or CVD or cancer mortality/incidence. Results: Six studies (n=42,467–399,537; 46.5–56.8 years old; 54.6–59.3% women) of five cohorts were included. All examined all-cause mortality; three assessed CVD/cancer outcomes. Four studies observed multiplicative interactions between LFs and SES, but in opposing directions. Two studies tested for additive interactions; interactions were observed in one cohort (UK Biobank) and not in another (NHANES). All-cause mortality HRs (95% CIs) for unhealthy LFs (versus healthy LFs) from the most advantaged SES groups ranged from 0.68 (0.32–1.45) to 4.17 (2.27–7.69). Equivalent estimates from the least advantaged ranged from 1.30 (1.13–1.50) to 4.00 (2.22–7.14). In 19 analyses (including sensitivity analyses) of joint associations between LFs, SES, and all-cause mortality, highest all-cause mortality was observed in the unhealthiest LF-least advantaged suggesting an additive effect. Conclusions: Limited and heterogenous literature suggests that the influence of SES on associations between combinations of unhealthy LFs and adverse health could be additive but remains unclear. Additional prospective analyses would help clarify whether SES modifies associations between combinations of unhealthy LFs and health outcomes. Registration: Protocol is registered with PROSPERO (CRD42020172588; 25 June 2020).

Living with a Smoker and Physical Inactivity across Eight Years in High-Risk Medical Patients

Recent research has demonstrated a link between living with a smoker and physical inactivity. However, no research has examined this issue in the context of recovery in medical patients. The present study broadens research on living with a smoker by applying it to physical inactivity in a group of high-risk medical patients with histories of cancer or cardiovascular disease compared to a control group without histories of these conditions. In addition, this study extends the time frame of research on living with a smoker in predicting physical inactivity to eight years. Participants were 76,758 women between 49 and 81 years of age from the Women's Health Initiative Observational Study. Data on living with a smoker were collected at baseline; data on physical activity were collected at baseline and annually from 3 to 8 years. Analyses utilized latent growth modeling. Patient status, compared to control status, was associated with more physical inactivity at baseline. Independent of patient status, living with a smoker predicted a significant increase in the odds of no moderate or strenuous exercise and a significant increase in the odds of no walking at baseline. The effect of living with a smoker on physical inactivity was stronger than that of patient status. Moreover, the living with a smoker effect on physical inactivity remained stable across eight years. These findings highlight an overlooked impediment to compliance with recommendations for lifestyle change among high-risk medical patients.

Health-Risk Behaviors and Dietary Patterns Among Jordanian College Students: A Pilot Study

Background/Aims: Health promotion and the incorporation of health-protective behaviors in people's lifestyles have a great role in enhancing individuals' overall health and well-being. College students are at increased risk of developing unhealthy dietary and lifestyle behaviors. A cross-sectional pilot study was conducted to assess the health-risk behaviors among undergraduate college students at Jordan University of Science and Technology. Methods: The final sample included 136 students, with a mean age of 21.1 ± 2.37 years, mostly females (69%). A self-reported questionnaire was used for data collection about dietary and lifestyle behaviors among college students. The questionnaire consisted of four parts: sociodemographic characteristics, body weight classifications, lifestyle behaviors, and dietary patterns and intake, and eating behaviors. Results: Most of the students did not meet the daily recommendations for fruit (76%) and vegetable (82%) intake. Males were significantly consuming fast food more frequently (p = 0.019), and smoked cigarettes (p < 0.001) or hookah (p = 0.015) more frequently than did females. Further, the majority met the recommendations for physical activity (81%), but exceeded recommendations for sedentary behavior. Females were more likely to have normal weight or be underweight (OR = 4.865), to have a fear of weight gain (OR = 3.387), and to have the recommended sleeping hours (OR = 7.685) than were males. Conclusion: The results indicate the health-risk behaviors and the gender-related differences among college students.

Comparative efficacy and safety of pharmacological interventions for smoking cessation in healthy adults: A network meta-analysis

Smoking is the leading cause of morbidity and mortality in different non-communicable diseases, and cessation leads to immense health benefits. The present network meta-analysis has been conducted to evaluate and compare the effects of available pharmacological interventions for smoking cessation in adults. A standard meta-analysis protocol was developed and after performing a comprehensive literature search on MEDLINE/PubMed, Cochrane databases, and International Clinical Trials Registry Platform, reviewers extracted data from 97 randomized controlled trials. PRISMA guidelines were followed in data extraction, analysis and reporting of findings. Random effects Bayesian network meta-analysis was done to pool the effects across the interventions. Network graph was built, and for closed triangles in the network graph, node splitting analysis was performed. The primary outcome measure was self-reported biochemically verified smoking abstinence at six months. The number of participants achieving continuous abstinence was reported. Data for the number of participants reporting at least one adverse event was also extracted, if available. Combination of nicotine receptor agonist and nicotine replacement therapy had a significant odd of 4.4 (95%CrI:2.2-8.7), bupropion and nicotine receptor agonist 4.0 (95%CrI:2.1-7.7), bupropion and nicotine replacement therapy 3.8 (95%CrI:2.3-6.2), combination nicotine replacement therapy has an odd of 2.6 (95%CrI:1.8-3.8), and nicotine receptor agonist had a significant odd of 2.7 (95%CrI:2.3-3.2) when compared to placebo (moderate quality of evidence) for continuous abstinence at 6 months. When compared with behavioural therapy, the odds ratio of interventions was not statistically significant. Combination of nicotine receptor agonist and nicotine replacement therapy has the highest probability of being the best treatment for abstinence from smoking.