Frontiers in epidemiology最新文献

Background: Solid waste collectors play an important role in maintaining health and hygiene in cities globally. The risk levels are very high in low-income countries since solid waste collectors have low socio-economic status and are exposed directly, unknowingly, and without adequate personal protection to municipal solid waste that contains hazardous materials. Solid waste collectors in Ethiopia are at high risk of occupational injuries due to the manual collection of hazardous solid waste by hand. In Jigjiga city, so far, there has been no study or published research showing the prevalence of occupational injuries and associated factors among municipal solid waste collectors.

Objective: To assess the prevalence of occupational injuries and associated factors among solid waste collectors in Jigjiga City, Somali Regional State, Ethiopia, 2023.

Methods: An institutional cross-sectional study was conducted in Jigjiga City, Somali Regional State, involving 247 solid waste collectors. Data was collected through an observational and structured questionnaire and analyzed using Epi Info and STATA software programs. The study used systematic random sampling techniques and bivariate and multivariable logistic regression analyses to determine the statistical association between the outcome variable and independent variables. The significance of the association was tested using the 95% confidence interval and p value (<0.05).

Results: The overall prevalence of occupational injuries was 54.7% (95% CI: 48.2%, 60.6%). Training on health and safety measures before employment [AOR: 0.43, 95% CI (0.24, 0.80)], sleeping problems [AOR: 3.28, 95% CI (1.86, 5.78)] and Temporary workers [AOR: 2.14, 95% CI (1.16, 3.95)] were significantly associated with occupational injuries.

Conclusion: The prevalence rate of occupational injuries among solid waste collectors in Jigjiga City was high. There should be preventive measures, like giving Training on Health and safety before employment, to safeguard the health and safety conditions of the workers.

During the COVID-19 pandemic, which spanned much of 2020-2023 and beyond, daily case and death counts were recorded globally. In this study, we examined available mortality counts and associated case counts, with a focus on the estimation missing information related to age distributions. In this paper, we explored a model-based paradigm for generating age distributions of mortality counts in a spatio-temporal context. We pursued this aim by employing Bayesian spatio-temporal lagged dependence models for weekly mortality at the county level. We compared three US states at the county level: South Carolina (SC), Ohio, and New Jersey (NJ). Models were developed for mortality counts using Bayesian spatio-temporal constructs, incorporating both dependence on current and cumulative case counts and lagged dependence on previous deaths. Age dependence was predicted based on total deaths in proportion to population estimates. This latent age field was generated as counterfactuals and then compared to observed deaths within age groups. The optimal retrospective space-time models for weekly mortality counts were those with lagged dependence and a function of caseload. Added random effects were found to vary across states: Ohio favored a spatially correlated model, while SC and NJ favored a simpler formulation. The generation of age-specific latent fields was performed for SC only and compared to a 15-month, 13-county data set of observed >65 age population. It is possible to model spatio-temporal variations in mortality at the county level with lagged dependencies, spatial effects, and case dependencies. In addition, it is also possible to generate latent age-specific fields based on estimates of death risk (using population proportions or more sophisticated modeling approaches). More detailed data will be needed to make more calibrated comparisons for future epidemic monitoring. The proposed discrepancy tool could serve as a useful resource for public health planners in tailoring interventions during epidemic situations.

Background: The health effects of alcohol consumption, particularly regarding potential protective benefits of light to moderate intake compared to abstinence, remain a subject of ongoing debate. However, epidemiological studies face limitations due to imprecise exposure measurements and the potential for bias through residual confounding and reverse causation. To address these limitations, we conducted a systematic review of Mendelian Randomization (MR) studies examining the causal relationship between alcohol consumption and cancers, cardiovascular, liver, and neurological diseases.

Methodology: We searched PubMed, ScienceDirect and Embase and Europe PMC up to 05/2024 for MR studies investigating the association of genetically predicted alcohol consumption with cancers, cardiovascular, liver and neurological diseases. We assessed methodological quality based on key elements of the MR design a genetic association studies tool.

Results: We included 70 MR studies that matched our inclusion criteria. Our review showed a significant association of alcohol consumption with multiple cancers such as oral and oropharyngeal, esophageal, colorectal cancers, hepatocellular carcinoma and cutaneous melanoma. While the available studies did not consistently confirm the adverse or protective effects of alcohol on other cancers, such as lung cancer, as suggested by observational studies. Additionally, MR studies confirmed a likely causal effect of alcohol on the risk of hypertension, atrial fibrillation, myocardial infraction and vessels disease. However, there was no evidence to support the protective effects of light to moderate alcohol consumption on cognitive function, Alzheimer's disease, and amyotrophic lateral sclerosis, as reported in observational studies while our review revealed an increased risk of epilepsy and multiple sclerosis. The available studies provided limited results on the link between alcohol consumption and liver disease.

Conclusions: Despite the valuable insights into the causal relationship between alcohol consumption and various health outcomes that MR studies provided, it is worth noting that the inconsistent ability of genetic instrumental variables to distinguish between abstainers, light and moderate drinkers makes it difficult to differentiate between U or J-shaped vs. linear relationships between exposure and outcome. Additional research is necessary to establish formal quality assessment tools for MR studies and to conduct more studies in diverse populations, including non-European ancestries.

Systematic review registration: www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021246154, Identifier: PROSPERO (CRD42021246154).

Background: Health-related quality of life (HRQoL) is crucial for understanding how health conditions impact overall well-being. The EuroQol-5 Dimension (EQ-5D) is a widely used tool for measuring HRQoL across diseases. In Ethiopia, this tool has been employed to assess HRQoL across various healthcare settings. This study aims to summarize EQ-5D-derived health outcomes in Ethiopian populations and identify key determinants influencing these outcomes.

Methods: A systematic search of PubMed, Embase, and Scopus was conducted through May 2024, with no publication date restrictions, focusing on HRQoL and EQ-5D instruments in Ethiopian populations. Grey literature searches were also performed using Google's Advanced Search. Cross-sectional studies across various diseases were included. Data were extracted by two independent reviewers, and pooled mean EQ-5D utility and EQ-5D visual analog scale (EQ-VAS) scores were calculated using a random-effects model in STATA software version 17. Study quality was evaluated using the Agency for Healthcare Research and Quality (AHRQ) checklist, and heterogeneity was assessed using the I² statistic.

Results: Fourteen cross-sectional studies involving 5,639 patients from 2019 to 2024 in Ethiopia were analyzed. Health utility values varied across diseases, with pain/discomfort and anxiety/depression being the most commonly affected dimensions. The pooled EQ-5D utility for HIV patients was 0.88, and the EQ-VAS score was 76.59. For diabetes mellitus (DM) patients, the pooled utility was 0.78, and the EQ-VAS score was 69.36. For COVID-19 patients, the pooled utility was 0.86, and the EQ-VAS score was 74.56. Cancer patients had a pooled EQ-VAS score of 67.87.

Conclusion: The EQ-5D is a reliable tool for measuring HRQoL in Ethiopian patients across various diseases. The study's pooled EQ-5D scores provide valuable insights for future economic evaluations in the Ethiopian healthcare system.

Systematic review registration: https://doi.org/10.1136/bmjopen-2024-085354, PROSPERO (CRD42024505028).

Background: A sharp increase in reported brucellosis incidence was observed in northwestern Tajikistan (from 1.0/100,000 people in January-May 2022 to 32.7/100,000 in January-May 2023). Most (82%) cases were from the same remote mountainous village (population = 10,712). The aim of this study was to identify risk factors for brucellosis infection and mitigate disease risk.

Methods: Using a case-control design, we conducted face-to-face interviews and collected blood samples during May-June 2023. Fifty-seven cases and 114 controls were recruited. Cases were the first person in a household diagnosed with brucellosis during February-June 2023 with positive serum agglutination test and antibody titers ≥1/160 from blood samples. Two controls were selected for each case (neighbors from different households matched by age and sex). Controls testing positive were excluded and replaced. We conducted conditional multivariable logistic regression to calculate adjusted odds ratio (AOR) and 95% confidence intervals (CI).

Results: Among the 87 brucellosis patients reported, 57 (66%) agreed to participate and didn't have secondary cases in the household. Of the 57 cases, 68% were 15-44 years old, and 44% were male. Cases peaked in May 2023. Common symptoms were joint pain (95%), fever (84%), weakness (72%), and night sweats (65%). Of selected controls, 13% tested positive and were excluded. All cases and 94% of controls owned livestock (mostly cattle, sheep, or goats); no animals had not been vaccinated in the past 5 years. Brucellosis was associated with consumption of both homemade kaymak (clotted cream) and home-raised meat compared with neither (AOR: 59 [95%CI: 4.3-798], p < 0.01), home-raised meat but not kaymak compared with neither (AOR: 54 [4.0-731], p < 0.01), and involvement in animal slaughter compared with no involvement (AOR: 36 [2.8-461], p < 0.01).

Conclusion: Contact with unvaccinated livestock or consumption of their products was a key contributor to this outbreak in a remote village of Tajikistan. With 13% of controls testing positive, true incidence was likely greater than reported. Following our investigation, a brucellosis awareness education campaign and animal vaccination campaigns were carried out in the region and only one case was reported in September 2023.

Dementia is a leading cause of death and disability with over 60% of cases residing in low- and middle-income countries (LMICs). Therefore, new strategies to mitigate risk are urgently needed. However, despite the high burden of disease associated with dementia in LMICs, research into dementia risk profiling and risk prediction modelling is limited. Further, dementia risk prediction models developed in high income countries generally do not transport well to LMICs suggesting that context-specific models are instead needed. New prediction models have been developed, in China and Mexico only, with varying predictive accuracy. However, none has been externally validated or incorporated variables that may be important for predicting dementia risk in LMIC settings such as socio-economic status, literacy, healthcare access, nutrition, stress, pollutants, and occupational hazards. Since there is not yet any curative treatment for dementia, developing a context-specific dementia prediction model is urgently needed for planning early interventions for vulnerable groups, particularly for resource constrained LMIC settings.

Traditional methods for measuring chemical exposure have challenges in terms of obtaining sufficient data; therefore, improved methods for better assessing occupational exposure are needed. One possible approach to mitigate these challenges is to use self-monitoring methods such as sensors, diaries, or biomarkers. In the present study, a self-monitored method for measuring soot exposure, which included real-time air monitoring, a work diary, and the collection of urine samples, was evaluated. To validate the method, exposure measurements during the workday and diary entries were compared with velocities calculated from GPS tracking and the expected polycyclic aromatic hydrocarbon (PAH) metabolite patterns in urine. The method was applied with chimney sweeps, an occupational group at a high risk of many severe health outcomes and for whom effective control measures for reducing exposure are needed. In the study, 20 chimney sweeps followed a self-monitoring protocol for 8 consecutive workdays. Personal exposure to soot was measured as black carbon (BC) using micro-aethalometers. A diary was used to record the work tasks performed, and urine samples were collected and analysed for PAH metabolites. From the expected 160 full day measurements, 146 (91%) BC measurements and 149 (93%) diaries were collected. From the expected 320 urine samples, 304 (95%) were collected. The tasks noted in the diaries overlapped with information obtained from the GPS tracking of the chimney sweeps, which covered 96% of the measurement time. The PAH metabolites in urine increased during the work week. Factors believed to have positively influenced the sample collection and task documentation were the highly motivated participants and the continuous presence of trained occupational hygiene professionals during the planning of the study and throughout the measurement stage, during which they were available to inform, instruct, and address questions. In conclusion, the self-monitored protocol used in this study with chimney sweeps is a valuable and valid method that can be used to collect larger numbers of samples. This is especially valuable for occupations in which the employees are working independently and the exposure is difficult to monitor with traditional occupational hygiene methods.

The natural foci of Crimean-Congo haemorrhagic fever (CCHF) in Kazakhstan are geographically located in the southern regions of the country (Kyzylorda, Turkestan and Zhambyl regions), where the infection of ticks with the CCHF virus predominantly reside, tick species composition and the number of vectors are monitored annually. The objective of our research was to investigate the genetic variants of the CCHF virus in the southern endemic regions, as well as to monitor the spread of the CCHF virus in the western regions of the country (Aktobe, Atyrau and Mangystau regions). In total, 974 (216 pools) ticks from the western regions and 3527 (583 pools) ticks from the southern regions collected during 2021-2022 were investigated. The presence of CCHF virus was detected by real-time reverse transcription PCR (qRT- PCR) in 1 pool out of 799 pools (0.12%) with Hyalomma scupense ticks captured in the CCHF-endemic Kyzylorda region. In the western regions, CCHF virus was not detected in ticks. The sequencing of incomplete fragments of the S, M and L segments of the CCHF virus in the detected virus was identified as genotype Asia - I. Phylogenetic analysis showed that the isolate obtained in this study is grouped with the isolate from a patient with CCHF, which we reported in 2015 (KX129738 Genbank). Our findings highlight the importance of including sequencing in the annual monitoring system for better understanding the evolution of the CCHF virus in the study areas of our country.