European Journal of Epidemiology最新文献

Evidence on the recent temporal trend in the incidence and mortality of early-onset cancer, i.e., cancer diagnosed at ages of < 50 years, in Germany is scarce. To estimate the temporal trend in the incidence and mortality of early-onset cancer in Germany between 1999 and 2019. Input data were obtained from the Centre for Cancer Registry Data (Zentrum für Krebsregisterdaten, ZfKD). The analysis comprised all ages until 50 years and all types of cancer classified by the International Classification of Diseases (ICD-10)-codes C00-C97 (excl. C44). Temporal trends were estimated using negative binomial regression, differentiated by sex and cancer type. Between 1999 and 2019 in Germany, we observed stable or slightly increasing trends (0% and 1%) in the incidence of all early-onset cancers combined (C00-C97) for men and women, respectively, and strict declines in the mortality for both, men and women (-2% and - 3%). However, the trends differ largely with respect to sex and the individual cancer types. Early-onset cancer should be closely monitored to see whether stable and decreasing trends in the incidence and mortality continue. Knowing that despite decreasing incidence, the prevalence of a disease can rise due to their interplay with mortality, we recommend to maintain precise surveillance, efforts in prevention and early detection, as well as appropriate investments into healthcare resources, research and development.

Neurofilament light chain (NfL) is a neuron-specific structural protein released into the extracellular space, including body fluids, upon neuroaxonal damage. Despite evidence of a link in neurological disorders, few studies have examined the association of serum NfL with mortality in population-based studies. Data from the National Health and Nutrition Survey were utilized including 2,071 Non-Hispanic White, Non-Hispanic Black and Hispanic adult participants and adult participants of other ethnic groups (20-85 years) with serum NfL measurements who were followed for ≤ 6 years till 2019. We tested the association of serum NfL with mortality in the overall population and stratified by sex with the addition of potential interactive and mediating effects of cardio-metabolic risk factors and nutritional biomarkers. Elevated serum NfL levels (above median group) were associated with mortality risk compared to the below median NfL group in the overall sample (P = 0.010), with trends observed within each sex group (P < 0.10). When examining Log_e NfL as a continuum, one standard deviation of Log_e NfL was associated with an increased mortality risk (HR = 1.88, 95% CI 1.60-2.20, P < 0.001) in the reduced model adjusted for age, sex, race, and poverty income ratio; a finding only slightly attenuated with the adjustment of lifestyle and health-related factors. Four-way decomposition indicated that there was, among others, mediated interaction between NfL and HbA1c and a pure inconsistent mediation with 25(OH)D3 in predicting all-cause mortality, in models adjusted for all other covariates. Furthermore, urinary albumin-to-creatinine ratio interacted synergistically with NfL in relation to mortality risk both on the additive and multiplicative scales. These data indicate that elevated serum NfL levels were associated with all-cause mortality in a nationally representative sample of US adults.

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 $\to$ mediator $\to$ 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.

Introduction: The PRIME-NL study prospectively evaluates a new integrated and personalized care model for people with parkinsonism, including Parkinson's disease, in a selected region (PRIME) in the Netherlands. We address the generalizability and sources of selection and confounding bias of the PRIME-NL study by examining baseline and 1-year compliance data.

Methods: First, we assessed regional baseline differences between the PRIME and the usual care (UC) region using healthcare claims data of almost all people with Parkinson's disease in the Netherlands (the source population). Second, we compared our questionnaire sample to the source population to determine generalizability. Third, we investigated sources of bias by comparing the PRIME and UC questionnaire sample on baseline characteristics and 1-year compliance.

Results: Baseline characteristics were similar in the PRIME (n = 1430) and UC (n = 26,250) source populations. The combined questionnaire sample (n = 920) was somewhat younger and had a slightly longer disease duration than the combined source population. Compared to the questionnaire sample in the PRIME region, the UC questionnaire sample was slightly younger, had better cognition, had a longer disease duration, had a higher educational attainment and consumed more alcohol. 1-year compliance of the questionnaire sample was higher in the UC region (96%) than in the PRIME region (92%).

Conclusion: The generalizability of the PRIME-NL study seems to be good, yet we found evidence of some selection bias. This selection bias necessitates the use of advanced statistical methods for the final evaluation of PRIME-NL, such as inverse probability weighting or propensity score matching. The PRIME-NL study provides a unique window into the validity of a large-scale care evaluation for people with a chronic disease, in this case parkinsonism.

As China faces demographic shifts and socioeconomic changes, the burden of Alzheimer's disease (AD) and associated cognitive impairments is increasing dramatically, with significant implications for public health and the economy. This systematic review and meta-analysis aims to provide a comprehensive assessment of the prevalence and incidence of AD across China. Drawing from an extensive search of international and Chinese databases up to August 27, 2023, including PubMed, Embase, and the Cochrane Library, we synthesized data from 105 studies. Our analysis reveals a combined prevalence of AD of 3.48% within a sample of 626,276 elderly individuals and an incidence rate of 7.90 per 1000 person-years. Subgroup and meta-regression analyses highlight age and gender as pivotal factors influencing these epidemiological patterns. Notably, significant heterogeneity exists due to variations in diagnostic criteria and study quality, impacting the comparability of findings. This meta-analysis underscores the need for continued research into demographic and modifiable risk factors influencing AD, while emphasizing standardized reporting practices to address these limitations and improve the understanding of AD's challenge in China.

While its etiology is not fully elucidated, preterm birth represents a major public health concern as it is the leading cause of child mortality and morbidity. Stress is one of the most common perinatal conditions and may increase the risk of preterm birth. In this paper we aimed to investigate the association of maternal perceived stress and anxiety with length of gestation. We used harmonized data from five birth cohorts from Canada, France, and Norway. A total of 5297 pregnancies of singletons were included in the analysis of perceived stress and gestational duration, and 55,775 pregnancies for anxiety. Federated analyses were performed through the DataSHIELD platform using Cox regression models within intervals of gestational age. The models were fit for each cohort separately, and the cohort-specific results were combined using random effects study-level meta-analysis. Moderate and high levels of perceived stress during pregnancy were associated with a shorter length of gestation in the very/moderately preterm interval [moderate: hazard ratio (HR) 1.92 (95%CI 0.83, 4.48); high: 2.04 (95%CI 0.77, 5.37)], albeit not statistically significant. No association was found for the other intervals. Anxiety was associated with gestational duration in the very/moderately preterm interval [1.66 (95%CI 1.32, 2.08)], and in the early term interval [1.15 (95%CI 1.08, 1.23)]. Our findings suggest that perceived stress and anxiety are associated with an increased risk of earlier birth, but only in the earliest gestational ages. We also found an association in the early term period for anxiety, but the result was only driven by the largest cohort, which collected information the latest in pregnancy. This raised a potential issue of reverse causality as anxiety later in pregnancy could be due to concerns about early signs of a possible preterm birth.

Emerging evidence has shown the association between female reproductive histories (e.g., menarche age, parity, premature and early menopause) and the risk of dementia. However, little attention has been given to infertility and pregnancy loss. To examine the associations of infertility, recurrent miscarriages, and stillbirth with the risk of dementia, this study used data from four cohorts in the International Collaboration for a Life Course Approach to Reproductive Health and Chronic Disease Events. Women with data on at least one of the reproductive exposures of interest, dementia, and all covariates were included. Histories of infertility, miscarriage, and stillbirth were self-reported. Dementia (including Alzheimer’s disease) was identified through surveys, aged care, pharmaceutical, hospital, and death registry data. Cause-specific Cox regression models were used to estimate the hazard ratios of dementia, accounting for well-established risk factors of dementia, study variability, and within-study correlation. Overall, 291,055 women were included at a median (interquartile range) age of 55.0 (47.0–62.0) at baseline. During the median (interquartile range) follow-up period of 13.0 (12.0–14.0) years, 3334 (1.2%) women developed dementia. Compared to women without stillbirth, a history of recurrent stillbirths (≥ 2) was associated with 64% higher risk of dementia (adjusted hazard ratio = 1.64, 95% confidence interval: 1.46–1.85). Compared to women without miscarriage, women with recurrent miscarriages (≥ 3) were at 22% higher risk of dementia (adjusted hazard ratio = 1.22, 95% confidence interval: 1.19–1.25). These findings suggest that recurrent stillbirths is a risk factor for dementia and may need to be considered in risk assessment of dementia in women.

Background: Smokers are at increased risk of type 2 diabetes (T2D), but the underlying mechanisms are unclear. We investigated if the smoking-T2D association is mediated by alterations in the metabolome and assessed potential interaction with genetic susceptibility to diabetes or insulin resistance.

Methods: In UK Biobank (n = 93,722), cross-sectional analyses identified 208 metabolites associated with smoking, of which 131 were confirmed in Mendelian Randomization analyses, including glycoprotein acetyls, fatty acids, and lipids. Elastic net regression was applied to create a smoking-related metabolic signature. We estimated hazard ratios (HR) of incident T2D in relation to baseline smoking/metabolic signature and calculated the proportion of the smoking-T2D association mediated by the signature. Additive interaction between the signature and genetic risk scores for T2D (GRS-T2D) and insulin resistance (GRS-IR) on incidence of T2D was assessed as relative excess risk due to interaction (RERI).

Findings: The HR of T2D was 1·73 (95% confidence interval (CI) 1·54 - 1·94) for current versus never smoking, and 38·3% of the excess risk was mediated by the metabolic signature. The metabolic signature and its mediation role were replicated in TwinGene. The metabolic signature was associated with T2D (HR: 1·61, CI 1·46 - 1·77 for values above vs. below median), with evidence of interaction with GRS-T2D (RERI: 0·81, CI: 0·23 - 1·38) and GRS-IR (RERI 0·47, CI: 0·02 - 0·92).

Interpretation: The increased risk of T2D in smokers may be mediated through effects on the metabolome, and the influence of such metabolic alterations on diabetes risk may be amplified in individuals with genetic susceptibility to T2D or insulin resistance.