BACKGROUND: Tobacco smoking poses a significant risk for various diseases, including cardiovascular diseases, chronic respiratory diseases, and cancers. In Kenya, tobacco-related deaths contribute substantially to non-communicable disease mortality. This study aims to quantify the mortality attributed to tobacco smoking in Kenya from 2012 to 2021.
METHODS: Employing a prevalence-based analysis model, the study utilized population attributable fraction (PAF) to estimate age-specific smoke attributable mortality (SAM) rates for individuals aged ≥35 years. Causes of death associated with tobacco use, including cancers, cardiovascular diseases, respiratory diseases, tuberculosis, and diabetes, were analyzed based on age, sex, and death records between 2012 and 2021.
RESULTS: Over the study period, 60228 deaths were attributed to tobacco-related diseases, with an annual increase observed until 2016 and subsequent fluctuations. Respiratory diseases, diabetes mellitus, malignant cancers, tuberculosis, and cardiovascular diseases collectively accounted for 16.5% of deaths among individuals aged ≥35 years. Notable contributors were pneumonia and influenza (respiratory diseases), esophageal cancer (cancers), and cerebrovascular diseases (cardiovascular diseases). Of the observed deaths, 16.5% were attributed to smoking, with respiratory diseases (40.5%), malignant cancers (31.4%), tuberculosis (13%), cardiovascular diseases (8.9%), and diabetes mellitus (6.1%) contributing. Pneumonia and influenza, esophageal cancer, chronic airway obstruction, and tuberculosis were primary causes, comprising 70% of all SAM.
CONCLUSIONS: Tobacco-related mortality is a significant public health concern in Kenya. Efforts should focus on preventing tobacco use and managing associated disease burdens. Smoking cessation initiatives and comprehensive tobacco control measures are imperative to mitigate the impact on population health.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is a growing health crisis in the general population of the United States (U.S.), but the relationship between systemic immune-inflammation (SII) index and NAFLD is not known.
METHODS: We collected data from the National Health and Nutrition Examination Survey 2017-2018. Next, propensity score matching (PSM), collinearity analysis, restricted cubic spline (RCS) plot, logistic regression, quantile regression analysis, subgroup analysis, mediation analysis, and population attributable fraction were used to explore the association of the SII with risk of NAFLD.
RESULTS: A total of 665 participants including the 532 Non-NAFLD and 133 NAFLD were enrolled for further analysis after PSM analysis. The RCS results indicated that there was a linear relationship between the SII and controlled attenuation parameter (p for nonlinear = 0.468), the relationship also existed after adjustment for covariates (p for nonlinear = 0.769). The logistic regression results indicated that a high SII level was an independent risk factor for NAFLD (OR = 3.505, 95% CI: 1.092-11.249, P < 0.05). The quantile regression indicated that at higher quantiles (0.90, and 0.95) the SII was significantly associated with NAFLD (p < 0.05). Mediation analysis indicated that alanine aminotransferase (ALT), triglycerides, and blood urea nitrogen (BUN) were partially contribute to the relationship between SII and NAFLD. The population attributable fractions indicated that 23.19% (95% CI: 8.22%, 38.17%) of NAFLD cases could be attributed to SII corresponding to 133 NAFLD cases.
CONCLUSIONS: There was a positive linear relationship between the SII and the risk of NAFLD. The ALT, triglycerides, and BUN had a partial mediating effect on the relationship between the SII and NAFLD.

In order to explore the association between meat consumption and gastrointestinal/colorectal cancer (CRC) risk and to estimate the Israeli population attributable fraction (PAF), we conducted a collaborative historical cohort study using the individual participant data of seven nutritional studies from the past 6 decades. We included healthy adult men and women who underwent a nutritional interview. Dietary assessment data, using food-frequency or 24-h recall questionnaires, were harmonized. The study file was linked to the National Cancer and death registries. Among 27,754 participants, 1216 (4.4%) were diagnosed with gastrointestinal cancers and 839 (3.0%) with CRC by the end of 2016. Using meta-analysis methods applied to Cox proportional hazard models (adjusted for daily energy intake, sex, age, ethnic origin, education and smoking),100 g/day increments in beef, red meat and poultry consumption, and 50 g/day increment in processed meat consumption were associated with hazard ratios (HRs) and 95% confidence intervals of 1.46 (1.06-2.02), 1.15 (0.87-1.52), 1.06 (0.89-1.26), and 0.93 (0.76-1.12), respectively, for CRC. Similar results were obtained for gastrointestinal cancer, although red meat consumption reached statistical significance (HR = 1.27; 95%CI: 1.02-1.58). The PAFs associated with a reduction to a maximum of 50 g/day in the consumption of red meat were 2.7% (95%CI: -1.9 to 12.0) and 5.2% (0.3-13.9) for CRC and gastrointestinal cancers, respectively. Reduction of beef consumption to a maximum of 50 g/day will result in a CRC PAF reduction of 7.5% (0.7%-24.3%). While beef consumption was associated with gastrointestinal/CRC excess risk, poultry consumption was not. A substantial part of processed meat consumption in Israel is processed poultry, perhaps explaining the lack of association with CRC.

OBJECTIVE: The contribution of suboptimal diets to gastrointestinal (GI) cancer incidence globally remains unquantified, and we aimed to evaluate it.
METHODS: Comprehensive meta-analyses and rigorous evidence-grading assessment identified the associations between suboptimal diets and 6 GI cancers and their subtypes. A comparative risk assessment model was used to estimate the proportional attributable burden and attributable rate of GI cancers to suboptimal diets by using the corroborative association estimates. In addition, correlation assessments with the Sociodemographic Index were carried out.
RESULTS: In 2018, 21.5% (95% uncertainty interval, 19.1%-24.5%) of incident GI cancer cases globally were attributable to suboptimal diets, maintaining a relatively stable proportion since 1990 (22.4%; 19.7%-25.6%), whereas the absolute diet-attributable cases doubled from 581,000 (511,000-664,000) in 1990 to 1,040,000 (923,000-1,187,000) in 2018. Excessive processed meat consumption (5.9%; 4.2%-7.9%), insufficient fruit intake (4.8%; 3.8%-5.9%), and insufficient whole grain intake (3.6%; 2.8%-5.1%) were the most significant dietary risk factors in 2018, a shift from 1990 when the third major concern was insufficient nonstarchy vegetable intake. In addition, Central and Eastern Europe and Central Asia experienced the highest attributable burden across regions in both 1990 (31.6%; 27.0%-37.4%) and 2018 (31.6%; 27.3%-36.5%), and a positive correlation (P < .01) between the Sociodemographic Index and the attributable GI cancer incidence was observed.
CONCLUSIONS: Although the proportional attributable GI incidence remains relatively stable, the doubling of absolute cases from 1990 to 2018, along with the discrepancies among urbanicity and countries/regions, informs dietary priorities and more targeted preventive measures.

In 2018, the authors reported estimates of the number and proportion of cancers attributable to potentially modifiable risk factors in 2014 in the United States. These data are useful for advocating for and informing cancer prevention and control. Herein, based on up-to-date relative risk and cancer occurrence data, the authors estimated the proportion and number of invasive cancer cases (excluding nonmelanoma skin cancers) and deaths, overall and for 30 cancer types among adults who were aged 30 years and older in 2019 in the United States, that were attributable to potentially modifiable risk factors. These included cigarette smoking; second-hand smoke; excess body weight; alcohol consumption; consumption of red and processed meat; low consumption of fruits and vegetables, dietary fiber, and dietary calcium; physical inactivity; ultraviolet radiation; and seven carcinogenic infections. Numbers of cancer cases and deaths were obtained from data sources with complete national coverage, risk factor prevalence estimates from nationally representative surveys, and associated relative risks of cancer from published large-scale pooled or meta-analyses. In 2019, an estimated 40.0% (713,340 of 1,781,649) of all incident cancers (excluding nonmelanoma skin cancers) and 44.0% (262,120 of 595,737) of all cancer deaths in adults aged 30 years and older in the United States were attributable to the evaluated risk factors. Cigarette smoking was the leading risk factor contributing to cancer cases and deaths overall (19.3% and 28.5%, respectively), followed by excess body weight (7.6% and 7.3%, respectively), and alcohol consumption (5.4% and 4.1%, respectively). For 19 of 30 evaluated cancer types, more than one half of the cancer cases and deaths were attributable to the potentially modifiable risk factors considered in this study. Lung cancer had the highest number of cancer cases (201,660) and deaths (122,740) attributable to evaluated risk factors, followed by female breast cancer (83,840 cases), skin melanoma (82,710), and colorectal cancer (78,440) for attributable cases and by colorectal (25,800 deaths), liver (14,720), and esophageal (13,600) cancer for attributable deaths. Large numbers of cancer cases and deaths in the United States are attributable to potentially modifiable risk factors, underscoring the potential to substantially reduce the cancer burden through broad and equitable implementation of preventive initiatives.

BACKGROUND: This study determined whether tooth loss was associated with the development of functional disability and estimated the population attributable fraction (PAF) of functional disability due to tooth loss, along with risk factors for functional disability such as physical function and cognitive impairment.
METHODS: The participants were 838 community-dwelling older adults aged ≥70 years living in the Tsurugaya district in Japan in 2003. The exposure variable was the number of remaining teeth (counted by trained dentists). Other variables were age, sex, depressive symptoms, cognitive impairment, educational attainment, physical function and social support. The Cox proportional hazards model was applied to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) of the incidence of functional disability for each risk factor, such as tooth loss. The functional disability PAF due to tooth loss was estimated, and risk factors for functional disability were identified.
RESULTS: In total, 619 (73.9%) participants developed functional disability during follow-up. A multivariable model showed that those with <20 teeth (HR, 1.28; 95% CI, 1.08-1.53) were more likely to develop functional disability than those with 20 teeth or more. PAF estimation for functional disability was shown to have decreasing values in the following order: age, female sex, tooth loss and reduced physical function.
CONCLUSIONS: Tooth loss was associated with the development of functional disability in community-dwelling older Japanese adults. While retaining teeth may be a potential strategy for avoiding functional disability, clinical studies on the effect of dental treatment on preventing functional disability are warranted.

Here we introduce graphPAF, a comprehensive R package designed for estimation, inference and display of population attributable fractions (PAF) and impact fractions. In addition to allowing inference for standard population attributable fractions and impact fractions, graphPAF facilitates display of attributable fractions over multiple risk factors using fan-plots and nomograms, calculations of attributable fractions for continuous exposures, inference for attributable fractions appropriate for specific risk factor → mediator → outcome pathways (pathway-specific attributable fractions) and Bayesian network-based calculations and inference for joint, sequential and average population attributable fractions in multi-risk factor scenarios. This article can be used as both a guide to the theory of attributable fraction estimation and a tutorial regarding how to use graphPAF in practical examples.

Long-term exposure to ambient PM2.5 is known associated with cardiovascular and respiratory health effects. However, the heterogeneous concentrationresponse function (CRF) between PM2.5 exposure across different concentration range and cardiopulmonary disease and diabetes mellitus (DM) incidence, and their implications on attributable years lived with disability (YLD) and regulation policy has not been well-studied. In this retrospective longitudinal cohort study, disease-free participants (approximately 170,000 individuals, aged ≥ 30 years) from the MJ Health Database were followed up (2007-2017) regarding incidents of coronary heart disease (CHD), ischemic stroke, chronic obstructive pulmonary disease (COPD), lower respiratory tract infections (LRIs), and DM. We used a time-dependent nonlinear weight-transformation Cox regression model for the CRF with an address-matched 3-year mean PM2.5 exposure estimate. Town/district-specific PM2.5-attributable YLD were calculated by multiplying the disease incidence rate, population attributable fraction, disability weight, and sex-age group specific subpopulation for each disease separately. The estimated CRFs for cardiopulmonary diseases were heterogeneously with the hazard ratios (HRs) increased rapidly for CHD and ischemic stroke at PM2.5 concentration lower than 10 μg/m3, whereas the HRs for DM (LRIs) increased with PM2.5 higher than 15 (20) μg/m3. Women had higher HRs for ischemic stroke and DM but not CHD. Relative to the lowest observed PM2.5 concentration of 6 μg/m3 of the study population, the PM2.5 level with an extra risk of 0.1 % (comparable to the disease incidence) for CHD, ischemic stroke, DM, and LRIs were 8.59, 11.85, 22.09, and 24.23 μg/m3, respectively. The associated attributable YLD decreased by 51.4 % with LRIs reduced most (83.6 %), followed by DM (63.7 %) as a result of PM2.5 concentration reduction from 26.10 to 16.82 μg/m3 during 2011-2019 in Taiwan. The proportion of YLD due to CHD and ischemic stroke remained dominant (56.4 %-69.9 %). The cost-benefit analysis for the tradeoff between avoidable YLD and mitigation cost suggested an optimal PM2.5 exposure level at 12 μg/m3. CRFs for cardiopulmonary diseases, attributable YLD, and regulation level, may vary depending on the national/regional background and spatial distribution of PM2.5 concentrations, as well as demographic characteristics.

UNASSIGNED: Increased particulate matter <2.5 μm (PM2.5) air pollution is associated with adverse cardiovascular outcomes. However, its impact on patients with prior coronary artery bypass grafting (CABG) is unknown.
UNASSIGNED: The purpose of this study was to evaluate the association between major adverse cardiovascular events (MACE) (defined as myocardial infarction, stroke, or cardiovascular death) and air pollution after CABG.
UNASSIGNED: We linked 26,403 U.S. veterans who underwent CABG (2010-2019) nationally with average annual ambient PM2.5 estimates using residential address. Over a 5-year median follow-up period, we identified MACE and fit a multivariable Cox proportional hazard model to determine the risk of MACE as per PM2.5 exposure. We also estimated the absolute potential reduction in PM2.5 attributable MACE simulating a hypothetical PM2.5 lowered to the revised World Health Organization standard of 5 μg/m3.
UNASSIGNED: The observed median PM2.5 exposure was 7.9 μg/m3 (IQR: 7.0-8.9 μg/m3; 95% of patients were exposed to PM2.5 above 5 μg/m3). Increased PM2.5 exposure was associated with a higher 10-year MACE rate (first tertile 38% vs third tertile 45%; P < 0.001). Adjusting for demographic, racial, and clinical characteristics, a 10 μg/m3 increase in PM2.5 resulted in 27% relative risk for MACE (HR: 1.27, 95% CI: 1.10-1.46; P < 0.001). Currently, 10% of total MACE is attributable to PM2.5 exposure. Reducing maximum PM2.5 to 5 μg/m3 could result in a 7% absolute reduction in 10-year MACE rates.
UNASSIGNED: In this large nationwide CABG cohort, ambient PM2.5 air pollution was strongly associated with adverse 10-year cardiovascular outcomes. Reducing levels to World Health Organization-recommended standards would result in a substantial risk reduction at the population level.

Stroke is a leading cause of death in the United States across all race/ethnicity and sex groups, though disparities exist. We investigated the potential for primary prevention of total first stroke for Americans aged 20 and older, stratified by sex and race/ethnicity. Specifically, we calculated population attributable fractions (PAF) of first stroke for 7 potentially modifiable risk factors: smoking, physical inactivity, poor diet, obesity, hypertension, diabetes, and atrial fibrillation. PAFs are a function of (1) the relative risk of first stroke for people with the exposure and (2) the prevalence of the risk factor in the population. Relative risks came from recent meta-analyses and sex-race/ethnicity-specific prevalence estimates came from the 2015-2018 NHANES or Multi-Ethnic Study of Atherosclerosis (for atrial fibrillation only). Approximately 1/3 (35.7% [CI: 21.6%-49.0%]) for women, 32.7% [CI: 19.2%-45.1%] for men) of strokes were attributable to the 7 risk factors we considered. A 20% proportional reduction in stroke risk factors would result in approximately 37,000 fewer strokes annually in the United States. The estimated PAF was highest for non-Hispanic Black women (39.3% [CI: 24.8%-52.3%]) and lowest for non-Hispanic Asian men (25.5% [CI: 14.6%-36.2%]). For most groups, obesity and hypertension were the largest contributors to stroke rates.