Relationship between weight-adjusted-waist index and all-cause and cardiovascular mortality in individuals with type 2 diabetes.

AIM: To investigate the relationship between the weight-adjusted-waist index (WWI) and all-cause mortality as well as cardiovascular mortality in individuals with type 2 diabetes. METHODS: We used data from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018 and the UK Biobank database. Restricted cubic spline curves and Cox proportional hazards models were employed to assess hazard ratios (HRs) and 95% confidence intervals (CIs) for all-cause mortality. RESULTS: In the UK Biobank database, compared with the lowest WWI quartile, the HR for all-cause and cardiovascular death in the highest quartile was 1.846 (95% CI 1.687-2.019) and 2.118 (95% CI 1.783-2.517), respectively, in the fully adjusted model. In the NHANES database, compared with the lowest WWI quartile, the highest quartile had an HR of 1.727 (95% CI 1.378-2.163) for all-cause death and 1.719 (95% CI 1.139-2.595) for cardiovascular death in the fully adjusted model. CONCLUSIONS: Our study indicates that WWI has a long-term synergistic negative impact on all-cause mortality and cardiovascular mortality in individuals with type 2 diabetes. The WWI is an independent predictor of mortality in individuals with type 2 diabetes.

Flavonoid intakes, chronic obstructive pulmonary disease, adult asthma, and lung function: a cohort study in the UK Biobank.

BACKGROUND: Given their antioxidative stress, anti-allergic, anti-inflammatory, and immune-modulating effects, flavonoids are hypothesized to play a role in preventing chronic obstructive pulmonary disease (COPD) and asthma. OBJECTIVES: This cohort study aimed to examine associations between flavonoid intake and COPD, asthma, and lung function. METHODS: Among 119,466 participants of the UK Biobank, median [interquartile range] age of 60 [53, 65] y, we estimated intakes of flavonoids, flavonoid-rich foods, and a flavodiet score from 24-h diet assessments. Prospective associations with both incident COPD and asthma and cross-sectional associations with measures of lung function [%predicted forced expiratory volume in 1s (FEV1); and FEV1/forced vital capacity (FVC)] were examined using multivariable-adjusted Cox proportional hazards and linear regression models, respectively. We investigated mediation by inflammation--represented by the INFLA score--and stratified analyses by smoking status. RESULTS: Compared with low intakes, moderate intakes of total flavonoids, flavonols, theaflavins + thearubigins, and flavanones, and moderate-to-high intakes of flavanol monomers, proanthocyanidins, anthocyanins, flavones, and the flavodiet score were associated with up to an 18% lower risk of incident COPD {e.g., [hazard ratio (95% confidence interval) for total flavonoids: 0.83 (0.75, 0.92)]} but not incident asthma. Furthermore, compared with low intakes, higher intakes of all flavonoid subclasses (except theaflavins + thearubigins), and the flavodiet score were associated with better percent predicted FEV1 baseline. Associations were most apparent in ever (current or former) smokers. Flavonoid intakes were inversely associated with the INFLA score, which appeared to mediate 11%-14% of the association between intakes of proanthocyanidins and flavones and incident COPD. CONCLUSIONS: Moderate-to-high flavonoid intakes were associated with a lower risk of COPD and better lung function, particularly among ever smokers. Promoting intakes of healthy flavonoid-rich foods, namely, tea, apples, and berries, may improve respiratory health and lower COPD risk, particularly in individuals with a smoking history.

Quantifying Triglyceride-Rich Lipoprotein Atherogenicity, Associations With Inflammation, and Implications for Risk Assessment Using Non-HDL Cholesterol.

BACKGROUND: Triglyceride-rich lipoproteins and remnants (TRL/remnants) have a causal, but not yet quantified, relationship with coronary heart disease (CHD): myocardial infarction plus revascularization. OBJECTIVES: The authors sought to estimate TRL/remnant per-particle atherogenicity, investigate causal relationships with inflammation, and determine whether differences in the atherogenicity of TRL/remnants and low-density lipoprotein (LDL) impact the causal association of non-high-density lipoprotein cholesterol (non-HDL-C) with CHD. METHODS: Single nucleotide polymorphisms (SNPs) (N = 1,357) identified by genome-wide association in the UK Biobank were ranked into 10 clusters according to the effect on TRL/remnant-C vs LDL-C. Mendelian randomization analysis was used to estimate for each SNP cluster CHD ORs per 10 mg/dL apolipoprotein B (apoB) and per 0.33 mmol/L non-HDL-cholesterol, and to evaluate association of TRL/remnants with biomarkers of systemic inflammation. RESULTS: SNPs in cluster 1 predominantly affected LDL-C, whereas SNPs in cluster 10 predominantly affected TRL/remnant-C. CHD risk per genetically predicted increase in apoB and in non-HDL-C rose across clusters. ORs per 10 mg/dL higher apoB was 1.15 (95% CI: 1.11-1.19) in cluster 1 vs 1.70 (95% CI: 1.52-1.90) in cluster 10. Comparing ORs between these TRL/remnant-predominant and LDL-predominant clusters, we estimated that TRL/remnants were at least 3.9 (95% CI: 2.8-5.4) times more atherogenic than LDL on a per-particle basis. For non-HDL-C, CHD ORs per 0.33 mmol/L rose from 1.15 (95% CI: 1.11-1.19) for cluster 1 to 1.40 (95% CI: 1.30-1.50) for cluster 10. TRL/remnants exhibited causal relationships with inflammation, but this did not explain their greater atherogenicity. CONCLUSIONS: TRL/remnants are about 4 times more atherogenic than LDL. Variation in the causal association of non-HDL-C with CHD indicates that adjustment for percentage TRL/remnant-C may be needed for accurate risk prediction.

Well-Being and Cardiovascular Health: Insights From the UK Biobank Study.

BACKGROUND: Cardiovascular diseases (CVDs) are a leading global health concern. Emerging evidence suggests a potential protective role of well-being in reducing CVD risk. METHODS AND RESULTS: We conducted a cohort analysis using the UK Biobank data set, encompassing 121 317 participants. We assessed the well-being of participants using a well-being index derived from baseline questionnaires. Well-being categories were derived by latent class analysis using general happiness and satisfaction with family, friendships, health, and finance situations. The relationship between well-being and 4 major CVDs was analyzed using Cox proportional hazards models and Mendelian randomization. The study also examined the impacts of well-being on lifestyle factors and inflammatory markers, and its mediating role in the well-being-CVD relationship. Higher well-being was associated with a significantly reduced risk of various CVDs. Latent class analysis identified 4 distinct well-being groups (low, variable, moderate-to-high, and high satisfaction), with higher satisfaction levels generally associated with lower risk of CVDs. Mendelian randomization suggested potential causal relationships between well-being and reduced risk of CVDs. Participants with greater well-being demonstrated healthier behaviors and lower levels of inflammatory markers. Mediation analysis indicated that lifestyle and inflammatory markers partially mediated the relationship between well-being and CVDs. CONCLUSIONS: This study demonstrates a robust inverse association between well-being and the risks of CVDs, suggesting that enhancing well-being may be a viable strategy for CVD prevention. The role of lifestyle factors and inflammation as a mediator provides insight into possible biological pathways linking psychological states and cardiovascular health.

How well can we measure chronic pain impact in existing longitudinal cohort studies? Lessons learned.

Multiple large longitudinal cohorts provide opportunities to address questions about predictors of pain and pain trajectories, even when not anticipated in design of the historical databases. This focus article uses two empirical examples to illustrate the processes of assessing the measurement properties of data from large cohort studies to answer questions about pain. In both examples, data were screened to select candidate variables that captured the impact of chronic pain on self-care activities, productivity and social activities. We describe a series of steps to select candidate items and evaluate their psychometric characteristics in relation to the measurement of pain impact proposed. In UK Biobank, a general lack of internal consistency of variables selected prevented the identification of a satisfactory measurement model, with lessons for the measurement of chronic pain impact. In the English Longitudinal Study of Ageing, a measurement model for chronic pain impact was identified, albeit limited to capturing the impact of pain on self-care and productivity but lacking coverage related to social participation. In conjunction with its supplementary material, this focus article aims to encourage exploration of these valuable prospectively collected data; to support researchers to make explicit the relationships between items in the databases and constructs of interest in pain research; and to use empirical methods to estimate the possible biases in these variables. PERSPECTIVE: This focus article outlines a theory-driven approach for fitting new measurement models to data from large cohort studies, and evaluating their psychometric properties. This aims to help researchers develop an empirical understanding of the gains and limitations connected with the process of re-purposing the data stored in these datasets.

Genetic Variance in Heparan Sulfation Is Associated With Salt Sensitivity.

BACKGROUND: High heritability of salt sensitivity suggests an essential role for genetics in the relationship between sodium intake and blood pressure (BP). The role of glycosaminoglycan genes, which are crucial for salinity tolerance, remains to be elucidated. METHODS: Interactions between 54 126 variants in 130 glycosaminoglycan genes and daily sodium excretion on BP were explored in 20 420 EPIC-Norfolk (European Prospective Investigation Into Cancer in Norfolk) subjects. The UK Biobank (n=414 132) and the multiethnic HELIUS study (Healthy Life in an Urban Setting; n=2239) were used for validation. Afterward, the urinary glycosaminoglycan composition was studied in HELIUS participants (n=57) stratified by genotype and upon dietary sodium loading in a time-controlled crossover intervention study (n=12). RESULTS: rs2892799 in NDST3 (heparan sulfate N-deacetylase/N-sulfotransferase 3) showed the strongest interaction with sodium on mean arterial pressure (false discovery rate 0.03), with higher mean arterial pressure for the C allele in high sodium conditions. Also, rs9654628 in HS3ST5 (heparan sulfate-glucosamine 3-sulfotransferase 5) showed an interaction with sodium on systolic BP (false discovery rate 0.03). These interactions were multiethnically validated. Stratifying for the rs2892799 genotype showed higher urinary expression of N-sulfated heparan sulfate epitope D0S0 for the T allele. Conversely, upon dietary sodium loading, urinary D0S0 expression was higher in participants with stable BP after sodium loading, and sodium-induced effects on this epitope were opposite in individuals with and without BP response to sodium. CONCLUSIONS: The C allele of rs2892799 in NDST3 exhibits higher BP in high sodium conditions when compared with low sodium conditions, whereas no differences were detected for the T allele. Concomitantly, both alleles demonstrate distinct expressions of D0S0, which, in turn, correlates with sodium-mediated BP elevation. These findings underscore the potential significance of genetic glycosaminoglycan variation in human BP regulation.

Reclaiming mendelian randomization from the deluge of papers and misleading findings.

Mendelian randomization (MR) is a powerful epidemiological method for causal inference. However, its recent surge in popularity has brought two concerning trends. First, the public availability of summary results from genome-wide association studies has led to an explosion of low-quality two-sample mendelian randomization (2SMR) studies. These studies add minimal - if any - value and overwhelm reviewers and journals. Second, the availability of large datasets with individual-level genotype data, like UK Biobank, has spurred the development and use of novel MR methods. However, some methods are being applied without proper testing, leading to misleading results, as exemplified by recent spurious findings that are being retracted and/or corrected relating to vitamin D. What can editors and peer reviewers do to handle the deluge of 2SMR studies and the premature application of highly complex MR methods? We advise editors to simply reject papers that only report 2SMR findings, with no additional supporting evidence. For reviewers receiving such papers, we provide a template for rejection. In addition, reviewers should demand rigorous testing of novel methods, including through the use of positive and negative controls before they are applied. Rejecting non-contributory 2SMR papers and imposing intensive scrutiny to novel methods is crucial if the scientific community is to reclaim MR.

Night Shift Work Associates with All-Cause and Cause-Specific Mortality: A Large Prospective Cohort Study.

BACKGROUND: Health problems associated with shift work and night shift work are gaining increasing public attention. OBJECTIVE: To investigate the association between night shift work and the hazard of mortality. DESIGN: Prospective cohort study. PARTICIPANTS: A total of 283,579 individuals with paid employment or self-employment aged 37-73 years were included from the UK Biobank with a median follow-up period of 14.0 years. MAIN MEASURES: Participants were divided into day workers and shift workers, including the frequency of night shifts, to evaluate the association between baseline work schedules and all-cause and cause-specific mortality using the Cox proportional hazards model. Additionally, 75,760 participants with work histories were assessed for the association between average frequency and cumulative years of exposure to night shift work and all-cause and cause-specific mortality. KEY RESULTS: Compared with that of day workers, the adjusted hazard of all-cause mortality was increased by 12.0% (hazard ratio [HR], 1.12; 95% confidence interval [CI], 1.07-1.18) in shift workers, particularly in those with no or rare night shifts (approximately 16.1%; HR, 1.16; 95% CI, 1.08-1.25) and those with irregular night shifts (approximately 9.2%; HR, 1.09; 95% CI, 1.00-1.19). Moreover, a non-linear relationship was identified between cumulative night shift years and all-cause and cause-specific mortality. Only individuals who worked night shifts for 20-30 years exhibited a substantially increased hazard of all-cause (HR, 1.52; 95% CI, 1.15-2.00) and cardiovascular disease (CVD; HR, 2.08; 95% CI, 1.16-3.71) mortality. CONCLUSIONS: Shift workers, particularly those with rare or irregular night shifts, exhibited an increased hazard of mortality. Additionally, participants who worked night shifts for 20-30 years exhibited a substantially increased hazard of all-cause and CVD mortality.

Habitual Coffee, Tea, and Caffeine Consumption, Circulating Metabolites, and the Risk of Cardiometabolic Multimorbidity.

CONTEXT: Cardiometabolic multimorbidity (CM) is an increasing public health concern. Previous observational studies have suggested inverse associations between coffee, tea, and caffeine intake and risks of individual cardiometabolic diseases; however, their associations with CM and related biological markers are unknown. METHODS: This prospective study involved 172 315 (for caffeine analysis) and 188 091 (tea and coffee analysis) participants free of any cardiometabolic diseases at baseline from the UK Biobank; 168 metabolites were measured among 88 204 and 96 393 participants. CM was defined as the coexistence of at least 2 of the following conditions: type 2 diabetes, coronary heart disease, and stroke. RESULTS: Nonlinear inverse associations of coffee, tea, and caffeine intake with the risk of new-onset CM were observed. Compared with nonconsumers or consumers of less than 100 mg caffeine per day, consumers of moderate amount of coffee (3 drinks/d) or caffeine (200-300 mg/d) had the lowest risk for new-onset CM, with respective hazard ratios (95% CIs) of 0.519 (0.417-0.647) and 0.593 (0.499-0.704). Multistate models revealed that moderate coffee or caffeine intake was inversely associated with risks of almost all developmental stages of CM, including transitions from a disease-free state to single cardiometabolic diseases and subsequently to CM. A total of 80 to 97 metabolites, such as lipid components within very low-density lipoprotein, histidine, and glycoprotein acetyls, were identified to be associated with both coffee, tea, or caffeine intake and incident CM. CONCLUSION: Habitual coffee or caffeine intake, especially at a moderate level, was associated with a lower risk of new-onset CM and could play important roles in almost all transition phases of CM development. Future studies are warranted to validate the implicated metabolic biomarkers underlying the relation between coffee, tea, and caffeine intake and CM.

Smoking Cessation and Incident Atrial Fibrillation in a Longitudinal Cohort.

BACKGROUND: Although smoking heightens the risk of AF, it remains unknown if that risk is amenable to modification after smoking cessation. OBJECTIVES: This study sought to evaluate the association between smoking cessation and atrial fibrillation (AF) risk in a large longitudinal cohort. METHODS: After excluding those with prevalent AF and no history of smoking at baseline, we evaluated 146,772 UK Biobank participants with serial smoking assessments. We compared AF risk between former smokers at baseline and those who quit smoking during the study to current smokers. Incident AF was ascertained from outpatient and inpatient encounters and identified using International Classification of Diseases codes. Cox models were used to compare the risk of incident AF among current and former smokers as well as those who quit smoking during the study while controlling for age, sex, race, body mass index, education, cardiovascular comorbidities, alcohol use, and pack-years. RESULTS: Among the 146,772 participants (48.3% female; age: 57.3 ± 7.9 years), 37,377 (25.5%) currently smoked; 105,429 (72.0%) were former smokers; and 3,966 (2.7%) quit smoking during the study. Over a mean 12.7 ± 2.0 years of follow-up, 11,214 (7.6%) participants developed AF. Compared to current smokers, the adjusted risk of AF was 13% lower in former smokers (HR: 0.87; 95% CI: 0.83-0.91) and 18% lower in those who quit smoking during the study (HR: 0.82; 95% CI: 0.70-0.95). CONCLUSIONS: Compared to those who continue to smoke, smoking cessation was associated with a lower risk of AF.

The Relationship Between Physical Activity and Non-Modifiable Risk Factors on Alzheimer's Disease and Brain Health Markers: A UK Biobank Study.

Background: Modifiable (physical activity) and non-modifiable (sex and genotype) risk factors interact to affect Alzheimer's disease (AD) risk. Further investigation is necessary to understand if these factors influence brain volume and cognition. Objective: The study aimed to assess the effect of physical activity, APOE genotype, and sex on AD risk, brain volume, and cognition. Methods: UK Biobank data from 2006 to 2023 was accessed. Physical activity was measured by accelerometers, and International Physical Activity Questionnaire. Outcomes were AD incidence; brain volume (ventricular cerebrospinal fluid and total brain); and cognition (executive function, memory, visuospatial ability, processing speed, and reaction time). Logistic and linear regression models were conducted. Results: 69,060 participants met inclusion criteria (mean age: 62.28 years, SD: 7.84; 54.64% female). Higher self-reported (OR = 0.63, 95% CI [0.40, 1.00], p = 0.047) and accelerometer-assessed (OR = 0.96 [0.93, 0.98], p = 0.002) physical activity was associated with lower disease incidence. Smaller ventricular cerebrospinal fluid volume (ß= - 65.43 [- 109.68, - 17.40], p = 0.007), and larger total brain volume (ß= 4398.46 [165.11, 8631.82], p <  0.001) was associated with increased accelerometer-assessed and self-reported physical activity respectively. Both brain volume analyses were moderated by sex. Increased accelerometer-assessed physical activity levels were associated with faster reaction time (ß= - 0.43 [- 0.68, - 0.18], p = 0.001); though poorer visuospatial ability (ß= - 0.06 [- 0.09, - 0.03], p <  0.001), and executive function (ß= 0.49 [0.31, 0.66], p <  0.001; ß= 0.27 [0.10, 0.45], p = 0.002) was related to self-reported physical activity levels. Conclusions: Higher levels of physical activity reduce AD risk independently of non-modifiable risk factors. Moderation of sex on brain volume highlighted the importance of incorporating non-modifiable risk factors in analysis.

Integrating external summary information in the presence of prior probability shift: an application to assessing essential hypertension.

Recent years have witnessed a rise in the popularity of information integration without sharing of raw data. By leveraging and incorporating summary information from external sources, internal studies can achieve enhanced estimation efficiency and prediction accuracy. However, a noteworthy challenge in utilizing summary-level information is accommodating the inherent heterogeneity across diverse data sources. In this study, we delve into the issue of prior probability shift between two cohorts, wherein the difference of two data distributions depends on the outcome. We introduce a novel semi-parametric constrained optimization-based approach to integrate information within this framework, which has not been extensively explored in existing literature. Our proposed method tackles the prior probability shift by introducing the outcome-dependent selection function and effectively addresses the estimation uncertainty associated with summary information from the external source. Our approach facilitates valid inference even in the absence of a known variance-covariance estimate from the external source. Through extensive simulation studies, we observe the superiority of our method over existing ones, showcasing minimal estimation bias and reduced variance for both binary and continuous outcomes. We further demonstrate the utility of our method through its application in investigating risk factors related to essential hypertension, where the reduced estimation variability is observed after integrating summary information from an external data.

Improving prediction models of amyotrophic lateral sclerosis (ALS) using polygenic, pre-existing conditions, and survey-based risk scores in the UK Biobank.

BACKGROUND AND OBJECTIVES: Amyotrophic lateral sclerosis (ALS) causes profound impairments in neurological function, and a cure for this devastating disease remains elusive. This study aimed to identify pre-disposing genetic, phenotypic, and exposure-related factors for amyotrophic lateral sclerosis using multi-modal data and assess their joint predictive potential. METHODS: Utilizing data from the UK (United Kingdom) Biobank, we analyzed an unrelated set of 292 ALS cases and 408,831 controls of European descent. Two polygenic risk scores (PRS) are constructed: "GWAS Hits PRS" and "PRS-CS," reflecting oligogenic and polygenic ALS risk profiles, respectively. Time-restricted phenome-wide association studies (PheWAS) were performed to identify pre-existing conditions increasing ALS risk, integrated into phenotypic risk scores (PheRS). A poly-exposure score ("PXS") captures the influence of environmental exposures measured through survey questionnaires. We evaluate the performance of these scores for predicting ALS incidence and stratifying risk, adjusting for baseline demographic covariates. RESULTS: Both PRSs modestly predicted ALS diagnosis but with increased predictive power when combined (covariate-adjusted receiver operating characteristic [AAUC] = 0.584 [0.525, 0.639]). PheRS incorporated diagnoses 1 year before ALS onset (PheRS1) modestly discriminated cases from controls (AAUC = 0.515 [0.472, 0.564]). The "PXS" did not significantly predict ALS. However, a model incorporating PRSs and PheRS1 improved the prediction of ALS (AAUC = 0.604 [0.547, 0.667]), outperforming a model combining all risk scores. This combined risk score identified the top 10% of risk score distribution with a fourfold higher ALS risk (95% CI [2.04, 7.73]) versus those in the 40%-60% range. DISCUSSION: By leveraging UK Biobank data, our study uncovers pre-disposing ALS factors, highlighting the improved effectiveness of multi-factorial prediction models to identify individuals at highest risk for ALS.

Life's Essential 8, genetic susceptibility, and risk of incident pancreatic cancer: A prospective cohort study.

The association between the American Heart Association (AHA) Life's Essential 8 (LE8) and the risk of pancreatic cancer (PC) remains unclear. Our goal was to assess the relationships between LE8, genetic susceptibility, and PC risk. This cohort consisted of 234,102 participants from the UK Biobank. The components of LE8 include diet, nicotine exposure, sleep, physical activity, blood glucose, body mass index, blood lipids, and blood pressure. LE8 is classified into three categories: low cardiovascular health (CVH), moderate CVH, and high CVH. Measurements were made using Cox proportional risk models to estimate impact of associations between LE8, genetic susceptibility, and incidence of PC in participants. Compared to participants with low LE8 scores, those with moderate and high LE8 scores had a 53% (HR, 0.47; 95% CI, 0.39-0.57) and 70% (HR, 0.30; 95% CI, 0.22-0.41) lower risk of developing PC, respectively. Interestingly, among individuals with high genetic risk, high LE8 scores were associated with greater benefits (HR, 0.24; 95% CI, 0.15-0.40), whereas the protective effect was weaker among those with low genetic risk (HR, 0.40; 95% CI, 0.21-0.75). Participants with a high LE8 score and a low polygenic risk score (PRS) had the lowest risk of PC (HR, 0.19; 95% CI: 0.11-0.33). Furthermore, we observed a significant additive interaction between LE8 and PRS. A higher LE8 score is associated with a lower risk of PC, especially for participants with a high PRS. These findings have important implications for participants most genetically predisposed to PC and for targeted strategies for PC prevention.

The impact of solid fuel use on major depression and the buffering effect of outdoor time in the UK adults: A 12-year cohort study.

BACKGROUND: This study aims to investigate age- and gender-specific effects of household solid fuels for heating on major depression and buffering effects of outdoor time in a high-income country. METHODS: Data were obtained from the UK Biobank. Participants with complete information on our studied variables and no prior diagnosis of major depression at baseline were included. Cox proportional hazards regression models were used to examine the effects of household solid fuels for heating on major depression. Subgroup analyses were conducted to investigate the buffering effects of outdoor time in summer and winter. Sensitivity analyses were performed to test the robustness of the main findings. RESULTS: Of 255,505 participants (50.2 % women), the 12-year cumulative incidence of major depression was 4.4 %. Household solid fuels for heating increased the risk of major depression only in women aged <45 years (HR (95%CI) = 1.30 (1.04, 1.63)). In this group, the solid fuel effect was moderated by outdoor time spending both in summer (HR (95%CI), ≤2 h/day: 1.61 (1.13, 2.28); >2 h/day: 1.13 (0.84, 1.52)) and winter (≤1 h/day: 1.35 (1.01, 1.08); >1 h/day: 1.24 (0.86, 1.77)). LIMITATIONS: Self-reported measures might lead to recall bias and some potential confounders, such as ventilation efficiency, were not measured and controlled in data analyses. CONCLUSIONS: Younger women are more vulnerable to the impact of domestic air pollution on major depression. Promoting outdoor activities is a cost-effective and efficient approach to mitigating the risk of major depression caused by household solid fuels.

Association between plant and animal protein and biological aging: findings from the UK Biobank.

PURPOSE: This study aimed to evaluate the relationship between plant protein, animal protein and biological aging through different dimensions of biological aging indices. Then explore the effects of substitution of plant protein, animal protein, and their food sources on biological aging. METHODS: The data came from 79,294 participants in the UK Biobank who completed at least two 24-h dietary assessments. Higher Klemera-Doubal Method Biological Age (HKDM-BA), higher PhenoAge (HPA), higher allostatic load (HAL), and longer telomere length (LTL) were estimated to assess biological aging. Logistic regression was used to estimate protein-biological aging associations. Substitution model was performed to assess the effect of dietary protein substitutions. RESULTS: Plant protein intake was inversely associated with HKDM-BA, HPA, HAL, and positively associated with LTL (odds ratios after fully adjusting and comparing the highest to the lowest quartile: 0.83 (0.79-0.88) for HKDM-BA, 0.86 (0.72-0.94) for HPA, 0.90 (0.85-0.95) for HAL, 1.06 (1.01-1.12) for LTL), while animal protein was not correlated with the four indices. Substituting 5% of energy intake from animal protein with plant protein, replacing red meat or poultry with whole grains, and replacing red or processed meat with nuts, were negatively associated with HKDM-BA, HPA, HAL and positively associated with LTL. However, an inverse association was found when legumes were substituted for yogurt. Gamma glutamyltransferase, alanine aminotransferase, and aspartate aminotransferase mediated the relationship between plant protein and HKDM-BA, HPA, HAL, and LTL (mediation proportion 11.5-24.5%; 1.9-6.7%; 2.8-4.5%, respectively). CONCLUSION: Higher plant protein intake is inversely associated with biological aging. Although there is no association with animal protein, food with animal proteins displayed a varied correlation.

Time from waking to the first cigarette and mortality and incident cardiovascular disease.

BACKGROUND: This study aimed to investigate the associations of time from waking to the first cigarette (TWFC) with all-cause mortality, cardiovascular disease (CVD) mortality and incident CVD among people smoking. METHODS: Data were from the UK Biobank, including 32 519 people smoking aged 40-70 years. TWFC was investigated using a touch-screen questionnaire. Outcomes included all-cause mortality and mortality from and incidence of CVD, ischemic heart disease (IHD) and stroke. RESULTS: Compared with participants reporting TWFC >120 min, those reporting TWFC between 61 and 120 min (HR, 1.30; 95% CI, 1.10-1.53), TWFC between 5 and 60 min (1.48, 1.30-1.70) and TWFC <5 min (1.65, 1.42-1.93) had a higher risk of all-cause mortality. Compared with participants reporting TWFC >120 min, those reporting TWFC between 5 and 60 min and TWFC <5 min had higher risks of CVD and IHD mortality and incident CVD and IHD, but those reporting TWFC between 61 and 120 min did not. The associations of TWFC with stroke mortality and incident stroke were not observed. CONCLUSION: In this cohort study, a shorter TWFC was associated with higher risks of all-cause mortality, mortality from CVD and IHD, as well as incident CVD and IHD.

Sex disparity in the association between metabolic-anthropometric phenotypes and risk of obesity-related cancer: a prospective cohort study.

BACKGROUND: Sex disparity between metabolic-obesity (defined by body mass index, BMI) phenotypes and obesity-related cancer (ORC) remains unknown. Considering BMI reflecting overall obesity but not fat distribution, we aimed to systematically assess the association of our newly proposed metabolic-anthropometric phenotypes with risk of overall and site-specific ORC by sex. METHODS: A total of 141,579 men (mean age: 56.37 years, mean follow-up time: 12.04 years) and 131,047 women (mean age: 56.22 years, mean follow up time: 11.82 years) from the UK Biobank was included, and designated as metabolic-anthropometric phenotypes based on metabolic status (metabolically healthy/unhealthy), BMI (non-obesity/obesity) and body shape (pear/slim/apple/wide). The sex-specific association of different phenotypes with overall and site-specific ORC was assessed by hazard ratios (HRs) and 95% confidence intervals (CIs) using Cox proportional hazards regression models. RESULTS: We found metabolically unhealthy and/or obesity phenotypes conveyed a higher risk in men than in women for overall ORC and colorectal cancer compared with metabolically healthy non-obesity phenotype (Pinteraction < 0.05). Of note, metabolically healthy obesity phenotype contributed to increased risks of most ORC in men (HRs: 1.58 ~ 2.91), but only correlated with higher risks of endometrial (HR = 1.89, 95% CI: 1.54-2.32) and postmenopausal breast cancers (HR = 1.17, 95% CI: 1.05-1.31) in women. Similarly, even under metabolically healthy, men carrying apple and wide shapes phenotypes (metabolically healthy apple/wide and metabolically healthy non-obesity apple/wide) suffered an increased risk of ORC (mainly colorectal, liver, gastric cardia, and renal cancers, HRs: 1.20 ~ 3.81) in comparison with pear shape or non-obesity pear shape. CONCLUSIONS: There was a significant sex disparity between metabolic-anthropometric phenotypes and ORC risk. We advised future ORC prevention and control worth taking body shape and sex disparity into account.

Estimating trans-ancestry genetic correlation with unbalanced data resources.

The aim of this paper is to propose a novel method for estimating trans-ancestry genetic correlations in genome-wide association studies (GWAS) using genetically-predicted observations. These correlations describe how genetic architecture of complex traits varies among populations. Our new estimator corrects for biases arising from prediction errors in high-dimensional weak GWAS signals, while addressing the ethnic diversity inherent in GWAS data, such as linkage disequilibrium (LD) differences. A distinguishing feature of our approach is its flexibility regarding sample sizes: it necessitates a large GWAS sample only from one population, while the secondary population may have a much smaller cohort, even in the hundreds. This design directly addresses the existing imbalance in GWAS data resources, where datasets for European populations typically outnumber those of non-European ancestries. Through extensive simulations and real data analysis from the UK Biobank study encompassing 26 complex traits, we validate the reliability of our method. Our results illuminate the broader implications of transferring genetic findings across diverse populations.