European Journal of Epidemiology最新文献

Aging is a multifaceted and intricate physiological process characterized by a gradual decline in functional capacity, leading to increased susceptibility to diseases and mortality. While chronological age serves as a strong risk factor for age-related health conditions, considerable heterogeneity exists in the aging trajectories of individuals, suggesting that biological age may provide a more nuanced understanding of the aging process. However, the concept of biological age lacks a clear operationalization, leading to the development of various biological age predictors without a solid statistical foundation. This paper addresses these limitations by proposing a comprehensive operationalization of biological age, introducing the “AccelerAge” framework for predicting biological age, and introducing previously underutilized evaluation measures for assessing the performance of biological age predictors. The AccelerAge framework, based on Accelerated Failure Time (AFT) models, directly models the effect of candidate predictors of aging on an individual’s survival time, aligning with the prevalent metaphor of aging as a clock. We compare predictors based on the AccelerAge framework to a predictor based on the GrimAge predictor, which is considered one of the best-performing biological age predictors, using simulated data as well as data from the UK Biobank and the Leiden Longevity Study. Our approach seeks to establish a robust statistical foundation for biological age clocks, enabling a more accurate and interpretable assessment of an individual’s aging status.

Objectives: Shifting from animal-based to plant-based diets could reduce colorectal cancer (CRC) incidence. Currently, the impacts of these dietary shifts on CRC risk are ill-defined. Therefore, we examined partial substitutions of red or processed meat with whole grains, vegetables, fruits or a combination of these in relation to CRC risk in Finnish adults.

Methods: We pooled five Finnish cohorts, resulting in 43 788 participants aged ≥ 25 years (79% men). Diet was assessed by validated food frequency questionnaires at study enrolment. We modelled partial substitutions of red (100 g/week) or processed meat (50 g/week) with corresponding amounts of plant-based foods. Cohort-specific hazard ratios (HR) for CRC were calculated using Cox proportional hazards models and pooled together using random-effects models. Adjustments included age, sex, energy intake and other relevant confounders.

Results: During the median follow-up of 28.8 years, 1124 CRCs were diagnosed. We observed small risk reductions when red meat was substituted with vegetables (HR 0.97, 95% CI 0.95 - 0.99), fruits (0.97, 0.94 - 0.99), or whole grains, vegetables and fruits combined (0.97, 0.95 - 0.99). For processed meat, these substitutions yielded 1% risk reductions. Substituting red or processed meat with whole grains was associated with a decreased CRC risk only in participants with < median whole grain intake (0.92, 0.86 - 0.98; 0.96, 0.93 - 0.99, respectively; p_interaction=0.001).

Conclusions: Even small, easily implemented substitutions of red or processed meat with whole grains, vegetables or fruits could lower CRC risk in a population with high meat consumption. These findings broaden our insight into dietary modifications that could foster CRC primary prevention.

This meta-research study aims to evaluate the agreement of effect estimates between bodies of evidence (BoE) from RCTs and cohort studies included in the same nutrition evidence synthesis, to identify factors associated with disagreement, and to replicate the findings of a previous study. We searched Medline, Epistemonikos and the Cochrane Database of Systematic Reviews for nutrition systematic reviews that included both RCTs and cohort studies for the same patient-relevant outcome or intermediate-disease marker. We rated similarity of PI/ECO (population, intervention/exposure, comparison, outcome) between BoE from RCTs and cohort studies. Agreement of effect estimates across BoE was analysed by pooling ratio of risk ratios (RRR) for binary outcomes and difference of standardised mean differences (DSMD) for continuous outcomes. We performed subgroup and sensitivity analyses to explore determinants associated with disagreements. We included 82 BoE-pairs from 51 systematic reviews. For binary outcomes, the RRR was 1.04 (95% confidence interval (CI) 0.99 to 1.10, I² = 59%, τ² = 0.02, prediction interval (PI) 0.77 to 1.41). For continuous outcomes, the pooled DSMD was  - 0.09 (95% CI  - 0.26 to 0.09, PI  - 0.55 to 0.38). Subgroup analyses yielded that differences in type of intake/exposure were drivers towards disagreement. We replicated the findings of a previous study, where on average RCTs and cohort studies had similar effect estimates. Disagreement and wide prediction intervals were mainly driven by PI/ECO-dissimilarities. More research is needed to explore other potentially influencing factors (e.g. risk of bias) on the disagreement between effect estimates of both BoE.Trial registration: CRD42021278908.

To explore to which extent neurodegeneration and cerebral small vessel disease (SVD) could mediate the association between type-2 diabetes and higher dementia risk. The analytical sample consisted in 2228 participants, out of the Three-City study, aged 65 and older, free of dementia at baseline who underwent brain MRI. Diabetes was defined by medication intake or fasting or non-fasting elevated glucose levels. Dementia status was assessed every 2 to 3 years, during up to 12 years of follow-up. Brain parenchymal fraction (BPF) and white matter hyperintensities volume (WMHV) were selected as markers of neurodegeneration and cerebral SVD respectively. We performed a mediation analysis of the effect of baseline BPF and WMHV (mediators) on the association between diabetes and dementia risk using linear and Cox models adjusted for age, sex, education level, hypertension, hypercholesterolemia, BMI, smoking and alcohol drinking status, APOE-ε4 status, and study site. At baseline, 8.8% of the participants had diabetes. Diabetes (yes vs. no) was associated with higher WMHV (β_diab = 0.193, 95% CI 0.040; 0.346) and lower BPF (β_diab = -0.342, 95% CI -0.474; -0.210), as well as with an increased risk of dementia over 12 years of follow-up (HR_diab = 1.65, 95% CI 1.04; 2.60). The association between diabetes status and dementia risk was statistically mediated by higher WMHV (HRdiab=1.05, 95% CI 1.01; 1.11, mediated part = 10.8%) and lower BPF (HR_diab = 1.12, 95% CI 1.05; 1.20, mediated part = 22.9%). This study showed that both neurodegeneration and cerebral SVD statistically explained almost 30% of the association between diabetes and dementia.

Prospective benchmarking of an observational analysis against a randomized trial increases confidence in the benchmarking process as it relies exclusively on aligning the protocol of the trial and the observational analysis, while the trials findings are unavailable. The Randomized Evaluation of Decreased Usage of Betablockers After Myocardial Infarction (REDUCE-AMI, ClinicalTrials.gov ID: NCT03278509) trial started recruitment in September 2017 and results are expected in 2024. REDUCE-AMI aimed to estimate the effect of long-term use of beta blockers on the risk of death and myocardial following a myocardial infarction with preserved left ventricular systolic ejection fraction. We specified the protocol of a target trial as similar as possible to that of REDUCE-AMI, then emulated the target trial using observational data from Swedish healthcare registries. Had everyone followed the treatment strategy as specified in the target trial protocol, the observational analysis estimated a reduction in the 5-year risk of death or myocardial infarction of 0.8 percentage points for beta blockers compared with no beta blockers; effects ranging from an absolute reduction of 4.5 percentage points to an increase of 2.8 percentage points in the risk of death or myocardial infarction were compatible with our data under conventional statistical criteria. Once results of REDUCE-AMI are published, we will compare the results of our observational analysis against those from the trial. If this prospective benchmarking is successful, it supports the credibility of additional analyses using these observational data, which can rapidly deliver answers to questions that could not be answered by the initial trial. If benchmarking proves unsuccessful, we will conduct a "postmortem" analysis to identify the reasons for the discrepancy. Prospective benchmarking shifts the investigator focus away from an endeavour to use observational data to obtain similar results as a completed randomized trial, to a systematic attempt to align the design and analysis of the trial and the observational analysis.

Abstract

Bladder cancer, a common neoplasm, is primarily caused by tobacco smoking. Epigenetic alterations including DNA methylation have the potential to be used as prospective markers of increased risk, particularly in at-risk populations such as smokers. We aimed to investigate the potential of smoking-related white blood cell (WBC) methylation markers to contribute to an increase in bladder cancer risk prediction over classical questionnaire-based smoking metrics (i.e., duration, intensity, packyears) in a nested case–control study within the prospective prostate, lung, colorectal, and ovarian (PLCO) Cancer Screening Trial and the alpha-tocopherol, beta-carotene cancer (ATBC) Prevention Study (789 cases; 849 controls). We identified 200 differentially methylated sites associated with smoking status and 28 significantly associated (after correction for multiple testing) with bladder cancer risk among 2670 previously reported smoking-related cytosine–phosphate–guanines sites (CpGs). Similar patterns were observed across cohorts. Receiver operating characteristic (ROC) analyses indicated that cg05575921 (AHHR), the strongest smoking-related association we identified for bladder cancer risk, alone yielded similar predictive performance (AUC: 0.60) than classical smoking metrics (AUC: 0.59–0.62). Best prediction was achieved by including the first principal component (PC1) from the 200 smoking-related CpGs alongside smoking metrics (AUC: 0.63–0.65). Further, PC1 remained significantly associated with elevated bladder cancer risk after adjusting for smoking metrics. These findings suggest DNA methylation profiles reflect aspects of tobacco smoke exposure in addition to those captured by smoking duration, intensity and packyears, and/or individual susceptibility relevant to bladder cancer etiology, warranting further investigation.

Abstract

A hypothesized benefit of social participation is that it encourages people to be more physically active. However, limited evidence exists on the association between social participation over the life-course and physical activity in midlife. We sought to apply a life-course framework to examine the association of social participation and device measured physical activity in midlife in the UK. We used the 1970 British Birth Cohort Study (BCS70), which includes all people born in Britain during a single week in 1970. Social participation was assessed at ages 16, 30, 34 and 42. Physical activity was measured by accelerometery at age 46, as mean daily step count and time spent in moderate to vigorous physical activity (MVPA). The associations of social participation and physical activity were tested using two different life-course models: the sensitive period model and the accumulation model. Individuals with medium and high participation compared to no social participation over their life-course had higher mean daily step count and MVPA in midlife, supporting the accumulation model. In the sensitive period model, only those that actively participated at age 42 had higher mean daily steps and MVPA compared to those who did not participate. Our study provides empirical evidence on the importance of sustaining social participation at all ages over the life-course rather than at a particular timepoint of someone’s life. If our findings reflect causal effects, interventions to promote social participation throughout the life-course could be an avenue to promote physical activity in middle life.

Meta-analyses have shown modest positive associations between diabetes mellitus (DM) and bladder cancer risk, but results are heterogeneous. This might be due to lack of distinction between bladder cancer subtypes, between sexes, and possibly between Type 2 and Type 1 DM (T2DM and T1DM). The relationship of T2DM (and secondarily T1DM) characteristics with risk of bladder cancer subtypes (invasive versus noninvasive) was investigated in the Netherlands Cohort Study. In 1986, 120,852 men and women aged 55–69 years provided information on DM and lifestyle data. After 20.3 years of follow-up, multivariable case-cohort analyses were based on 1020 invasive and 1088 noninvasive bladder cancer cases, and 4267 subcohort members with complete data on DM and confounders. While T2DM was not associated with noninvasive bladder cancer, it was statistically significantly associated with invasive bladder cancer risk: the multivariable-adjusted was HR = 1.57 (95% CI 1.04–2.37), comparing participants with T2DM versus without DM. The association was only significant in women, and women showed a stronger association [HR = 2.19 (95% CI 1.10–4.34)] between T2DM and invasive bladder cancer than men [HR = 1.42 (95% CI 0.88–2.30)]; interaction by sex was nonsignificant. Associations were stronger positive in those whose age at diagnosis of T2DM was 55+ years, and in those diagnosed with T2DM less than five years before baseline. T2DM participants using antidiabetic medication had higher invasive bladder cancer risk than those without DM. Exploratory age-sex-adjusted analyses suggested a positive association between T1DM and invasive bladder cancer, but this was based on few cases. These findings suggest that T2DM and possibly T1DM are positively associated with invasive bladder cancer risk.