Global Epidemiology最新文献

Causal assessments in epidemiology are a complex process due to the many methods involved. The general scientific method lords over the process joined by study designs and statistical methods. Other methods include those that evaluate quality and bias along with the research synthesis methods such as the systematic narrative review, meta-analysis, and the criteria-based methods. When different investigators apply these methods to the same evidence and come up with different causal assessments, as described in the review by Goodman et al. in this issue, a key question becomes, how can the differences be explained? A prime candidate involves different methodologic choices. A deeper question emerges from this same situation: are the methods used for causal assessments reliable? Reliability is a hallmark of scientific practice. The methods used to make claims about causality should be reliable. Given the complexity of the causal assessment process, an objective evaluation of reliability is challenging but clearly worth the effort. Fortunately, Hill's criterion of analogy, much maligned in epidemiology, provides a clue. This commentary explores the issue of the reliability of causal claims using the Goodman et al. systematic review as its foil along with the claims by EPA, IARC, and ATSDR about the relationship between perchloroethylene and non-Hodgkin lymphoma, the claims Goodman et al. believe are wrong.

Background

Studies on risk factors for severe COVID-19 in people of working age have generally not included non-working persons or established population attributable fractions (PAFs) for occupational and other factors.

Objectives

We describe the effect of job-related, sociodemographic, and other exposures on the incidence, relative risks and PAFs of severe COVID-19 in individuals aged 18–64.

Methods

We conducted a registry-based study in Swedish citizens aged 18–64 from 1 January 2020 to 1 February 2021 with respect to COVID-19-related hospitalizations and death.

Results

Of 6,205,459 persons, 272,043 (7.5%) were registered as infected, 3399 (0.05%) needed intensive care, and 620 (0.01%) died, with an estimated case fatality rate of 0.06% over the last 4-month period when testing was adequate. Non-Nordic origin was associated with a RR for need of intensive care of 3·13, 95%CI 2·91–3·36, and a PAF of 32·2% after adjustment for age, sex, work, region and comorbidities. In a second model with occupation as main exposure, and adjusted for age, sex, region, comorbidities and origin, essential workers had an RR of 1·51, 95%CI, 1·35–1·6, blue-collar workers 1·18, 95%CI 1·06–1·31, school staff 1·21, 95%CI 1·01–1·46, and health and social care workers 1·89, 95%CI 1·67–2·135) compared with people able to work from home, with altogether about 13% of the PAF associated with these occupations. Essential workers and blue-collar workers, but no other job categories had higher risk of death, adjusted RRs of 1·79, 95%CI 1·34–2·38 and 1·37, 95%CI 1·04–1·81, with adjusted PAFs of altogether 9%.

Conclusion

Among people of working age in Sweden, overall mortality and case fatality were low. Occupations that require physical presence at work were associated with elevated risk of needing intensive care for COVID-19, with 14% cases attributable to this factor, and 9% of deaths.

Background

Globally, work-related deaths (injuries and diseases) are a major social and public health problem. Register data on fatal occupational injuries in high-income countries may be considered to have high quality, especially when reporting is mandatory and regulated by law. We aimed to assess the accuracy of work-related injury death statistics in Norway, with reference to the Labour Inspection Authority and three other on-going registration systems (the cause-specific mortality register, the register for governmental compensations, and the register for insurance companies).

Methods

In this register-based study, we used the capture-recapture technique to adjust for undercounting. We investigated whether the capture-recapture method using two or three sources gave a valid estimate of fatal occupational injuries as compared with the number of cases identified in four registers administrated by the Norwegian Labour Inspection Authority, Statistics Norway, the Labour and Welfare Administration, and Finance Norway. The inclusion criteria were fatal unintentional injuries among residents of Norway between 2000 and 2003 that occurred while working for income in private and public land-based industries. We obtained ethical and legal approvals.

Results

In a period of four years (2000−2003), the Labour Inspection Authority registered 171 occupational injury deaths among residents employed in land-based industries. Two combinations of data sources gave capture-recapture estimates of 246 [95% CI 216; 279] and 265 [95% CI 234; 299] deaths. In total, 246 cases were identified in the four registration systems, which was 44% higher than the number of deaths registered by the Labour Inspection Authority. The Labour Inspection Authority had the most complete register out of the four registration systems.

Conclusions

The capture-recapture method used on two overlapping data sources gave highly valid estimates of the total deaths. We demonstrated the existence of significant weaknesses in the registration systems in a country considered to have high-quality register data.

Background

This study assesses the effect of blood lipid indices and lipid ratios on cardiovascular diseases (CVDs) using inverse probability-of-exposure weighted estimation of marginal structural models (MSMs).

Methods

A pooled dataset of two US representative cohort studies, including 16736 participants aged 42–84 years with complete information at baseline, was used. The effect of each lipid index, including low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglyceride (TG), ratios of TC/HDL-C, LDL-C/HDL-C, and TG/HDL-C on coronary heart disease (CHD) and stroke were estimated using weighted Cox regression.

Results

There were 1638 cases of CHD and 1017 cases of stroke during a median follow-up of 17.1 years (interquartile range: 8.5 to 25.7). Compared to optimal levels, the risk of CVD outcomes increased substantially in high levels of TC, LDL-C, TC/HDL-C, and LDL-C/HDL-C. If everyone had always had high levels of TC (≥240 mg/dL), risk of CHD would have been 2.15 times higher, and risk of stroke 1.35 times higher than if they had always had optimal levels (<200 mg/dL). Moreover, if all participants had been kept at very high (≥190 mg/dL) levels of LDL-C, risk of CHD would have been 2.62 times higher and risk of stroke would have been 1.92 times higher than if all participants had been kept at optimal levels, respectively. Our results suggest that high levels of HDL-C may be protective for CHD, but not for stroke. There was also no evidence of an adverse effect of high triglyceride levels on stroke.

Conclusions

Using MSM, this study highlights the effect of TC and LDL-C on CVD, with a stronger effect on CHD than on stroke. There was no evidence for a protective effect of high levels of HDL-C on stroke. Besides, triglyceride was not found to affect stroke.

Competing events are events that preclude the occurrence of the primary outcome. Much has been written on mainly the statistics behind competing events analyses. However, many of these publications and tutorials have a strong statistical tone and might fall short in providing a practical guide to clinician researchers as to when to use a competing event analysis and more importantly which method to use and why.

Here we discuss the different target effects in the Fine-Gray and cause-specific methods using simple causal diagrams and provide strengths and limitations of both approaches for addressing etiologic questions. We argue why the Fine-Gray method might not be the best approach for handling competing events in etiological time-to-event studies.

Background

SARS-CoV-2 continues to spread despite fast vaccine rollout, which could be attributed to waning immunity or to a reduced protection against some variants. A thorough characterization of vaccine protection and its duration in time is needed to inform vaccination policies and enhance public trust.

Methods

We linked three national databases with exhaustive information on screening, vaccination and hospitalizations in France from January 1st to December 12, 2021. We performed a two-step analysis to estimate vaccine effectiveness against severe outcomes of Covid-19 (requiring hospitalization) in people aged 50 years or over, combining: (i) a test-negative case–control design to assess vaccine effectiveness against symptomatic infections; and (ii) a survival analysis to assess the additional protection against severe outcomes (hospitalizations, ICU admissions and inpatient deaths) in infected individuals.

Findings

We found a high vaccine effectiveness in people aged 50 years or more, reaching 82% against symptomatic infections and 94% against hospitalizations, after a full vaccination scheme with the Covid-19 vaccines used in France.

Vaccine effectiveness against symptomatic infections decreased over time, dropping to 53% after six months, but remained high against severe outcomes (90% after six months). The booster dose allowed restoring protection levels above 90% against symptomatic infections. Vaccine protection and its evolution in time, showed little difference against the variants that circulated prior to December 2021 in France, including the Delta variant.

Interpretation

Though vaccine immunity decreases over time, vaccination remains crucial to provide individual protection against severe outcomes requiring hospitalization. This decline can be reversed by the receipt of a booster dose.

Aims

Stroke is a leading cause of death and disability for Americans, and growing evidence suggests that air pollution may play an important role. To facilitate pollution control efforts, the National Academy of Sciences and the World Health Organization have prioritized determining which air pollutants are most toxic. However, evidence is limited for the simultaneous effects of multiple air pollutants on stroke.

Methods and results

We constructed a nationwide population-based cohort study, using the Medicare Chronic Conditions Warehouse (2000–2017) and high-resolution air pollution data, to investigate the impact of long-term exposure to ambient PM_2.5, NO₂, and ground-level O₃ on incident stroke. Hazard ratios (HR) for stroke incidence were estimated using single-, bi-, and tri-pollutant Cox proportional hazards models. We identified ~2.2 million incident stroke cases among 17,443,900 fee-for-service Medicare beneficiaries. Per interquartile range (IQR) increase in the annual average PM_2.5 (3.7 μg/m³), NO₂ (12.4 ppb), and warm-season O₃ (6.5 ppb) one-year prior to diagnosis, the HRs were 1.022 (95% CI: 1.017–1.028), 1.060 (95% CI: 1.054–1.065), and 1.021 (95% CI: 1.017–1.024), respectively, from the tri-pollutant model. There was strong evidence of linearity in concentration-response relationships for all three air pollutants in single-pollutant models. This linear relationship remained robust for NO₂ and O₃ in tri-pollutant models while the effect of PM_2.5 attenuated at the lower end of concentrations.

Conclusion

Using a large nationwide cohort, our study suggests that long-term exposure to PM_2.5, NO₂, and O₃ may independently increase the risk of stroke among the US elderly, among which traffic-related air pollution plays a particularly crucial role.

Background

Breast cancer (BC) is the most frequently diagnosed cancer and a major cause of cancer mortality in Sudan. However, there is lack of data related to BC relapse. Therefore, this study was undertaken to estimate the 5-year relapse free survival (RFS) rate and factors related to BC relapse in Sudanese women with non-metastatic BC.

Methods

Data of BC women with BC diagnosed and treated at the National Cancer Institute-University of Gezira during 2012 were retrieved from medical records. The cases were followed-up through hospital records and telephone contact. Survival functions were calculated using Kaplan-Meier method and compared by log-rank test. The prognostic factors were tested using univariate and multivariable Cox regression analyses.

Results

We included 168 women with median age of 45 years (range, 22–83 years). 53.5%of women had stage III at time of diagnosis, whereas 4.2% and 42.3% of women presented with stage I and stage II, respectively. At the end of 5 years follow-up, with median follow-up period of 64 months, 94 (56.0%) women were alive in remission, 11 (6.5%) were alive with BC relapse, 49 (29.2%) were dead, and survival status was unknown in 14 (8.3%) women. Most of the occurred relapses were distant relapses. The 5-year RFS was 59%. The independent predictors of relapse were: larger primary tumor size (HR:1.84, 95% CI: 1.54-5.48, p=0.018); involved axillary lymph nodes with tumour (HR:  2.91, 95% CI:  1.53–7.91, p=0.001); not receiving adjuvant radiotherapy (HR: 2.2, 95% CI: 1.22–3.95, p=0.009); and not receiving hormone therapy (HR: 1.67, 95% CI: 1.01–2.76, p= 0.046).

Conclusion

We found a high risk of BC relapse in our resource-constrained settings. Advanced stages, not receiving adjuvant radiotherapy, and not receiving adjuvant hormone therapy were independent predictors associated with worse 5-year RFS. Therefore, enhancing the early diagnosis of BC and improving timely access to appropriate treatments represent key approaches to achieving better treatment outcomes.

Environmental epidemiology has proven critical to study various associations between environmental exposures and adverse human health effects. However, there is a perception that it often does not sufficiently inform quantitative risk assessment. To help address this concern, in 2017, the Health and Environmental Sciences Institute initiated a project engaging the epidemiology, exposure science, and risk assessment communities with tripartite representation from government agencies, industry, and academia, in a dialogue on the use of environmental epidemiology for quantitative risk assessment and public health decision making. As part of this project, four meetings attended by experts in epidemiology, exposure science, toxicology, statistics, and risk assessment, as well as one additional meeting engaging funding agencies, were organized to explore incentives and barriers to realizing the full potential of epidemiological data in quantitative risk assessment. A set of questions was shared with workshop participants prior to the meetings, and two case studies were used to support the discussion.

Five key ideas emerged from these meetings as areas of desired improvement to ensure that human data can more consistently become an integral part of quantitative risk assessment: 1) reducing confirmation and publication bias, 2) increasing communication with funding agencies to raise awareness of research needs, 3) developing alternative funding channels targeted to support quantitative risk assessment, 4) making data available for reuse and analysis, and 5) developing cross-disciplinary and cross-sectoral interactions, collaborations, and training.

We explored and integrated these themes into a roadmap illustrating the need for a multi-stakeholder effort to ensure that epidemiological data can fully contribute to the quantitative evaluation of human health risks, and to build confidence in a reliable decision-making process that leverages the totality of scientific evidence.