Journal of Preventive Medicine and Public Health最新文献

Objectives: Influenza vaccination is important for healthcare workers in order to prevent both the illness itself and transmission to patients. Previous studies in Saudi Arabia have revealed low influenza vaccine coverage among healthcare workers due to misconceptions. This study aimed to assess knowledge, attitudes, and practices regarding influenza vaccination among healthcare workers during 2021, addressing the current data gap.

Methods: A cross-sectional study was conducted, including 1273 healthcare workers from the Ministry of Health in Saudi Arabia. A self-administered questionnaire was distributed to participants via email.

Results: Most participants had an appropriate extent of knowledge, with 37.1% having a high level and 26.6% having a moderate level. Positive attitudes toward the influenza vaccine were observed in 41.2% of participants, and 80.2% demonstrated good vaccine practices. However, the vaccine coverage was 50.8% in the past 12 months. Factors associated with vaccine uptake included previous vaccination, workplace availability, awareness of guidelines, engagement in training programs, type of workplace settings, and having positive attitudes toward the vaccine. The most common reason for not getting vaccinated was the perception of being at low risk, making vaccination unnecessary.

Conclusions: Participants exhibited positive knowledge, attitudes, and practices regarding influenza vaccination. However, the observed vaccine uptake rate fell below the recommended coverage rate, indicating the presence of a knowledge-behavior gap. Targeted interventions are recommended to improve vaccination uptake among healthcare workers in Saudi Arabia.

Objectives: Prior research has not yet examined the relationship between post-term birth and neonatal mortality in Japan, along with factors associated with post-term birth. We investigated these associations utilizing nationwide birth data from Japan.

Methods: Birth and mortality data were obtained from the Vital Statistics of Japan for the years 2017 to 2022. The post-term birth rate was calculated by birth characteristics, and the neonatal mortality rates for post-term and term births were computed. Additionally, log-binomial regression analysis was employed to explore the associations between post-term birth and neonatal mortality, as well as between various characteristics and post-term birth. The characteristics considered included infant sex, maternal age group, parity, maternal nationality, maternal marital status, and household occupation.

Results: This study analyzed data from 4 698 905 singleton infants born at 37 weeks of gestational age or later. Regression analysis revealed that post-term birth was positively associated with neonatal mortality. The adjusted risk ratio for neonatal mortality in post-term compared to term births was 8.07 (95% confidence interval, 5.06 to 12.86). Factors positively associated with post-term birth included female infant sex, older maternal age, primiparity, non-Japanese maternal nationality, unmarried status, and various household occupations, including farmer, full-time worker at a smaller company, other type of worker, and unemployed. Younger maternal age was inversely associated with post-term birth.

Conclusions: In Japan, post-term birth represents a risk factor for neonatal mortality. Additionally, socio-demographic characteristics, such as maternal marital status, nationality, and parity were found to be predictors of post-term birth.

Objectives: In Korea, cardio-cerebrovascular disease (CCVD) is recognized as an occupational disease when sufficient evidence of a work-related burden exists. In 2021, approximately 26.8% of the payments from occupational disease insurance under the Industrial Accident Compensation Insurance Act were allocated to CCVDs. However, due to the specific nature of insurance policies for farmers, CCVD is not acknowledged as an occupational disease in their case.

Methods: We reviewed studies on the differences in the incidence, prevalence, and mortality rates of CCVDs between farmers and the general population or other occupations and described the exposure of farmers to risk factors for CCVDs.

Results: Several studies showed that farming is a high-risk occupation for CCVDs, with the following risk factors: long working hours, night work, lack of holidays, and strenuous physical labor; physical factors (noise, cold, heat, humidity, and vibration); exposure to hazardous gases (diesel exhaust, carbon monoxide, hydrogen sulfide, carbon disulfide, nitrogen oxides, and polycyclic aromatic hydrocarbons), pesticides, and dust (particulate matter, silica, and organic dust); exposure to a hypoxic environment; and job-related stress. Social isolation and lack of accessible medical facilities also function as additional risk factors by preventing farmers from receiving early interventions.

Conclusions: Farmers are exposed to various risk factors for CCVDs and are an occupation at risk for CCVDs. More studies are needed in the future to elucidate this relationship. This study lays the groundwork for future research to develop guidelines for approving CCVDs as occupational diseases among farmers.

Objectives: Transitional periods, such as patient discharge, are notably challenging. This study aimed to explore the perceptions of providers involved in hospital discharge support programs, identify the primary obstacles, and propose strategies for improvement.

Methods: In this qualitative cross-sectional study, we interviewed 49 healthcare professionals, comprising doctors, nurses, and social workers, who participated in two pilot programs. We organized focus group interviews with 3-6 participants per group, segmented by the type of discharge support program and profession. For data analysis, we employed phenomenological analysis, a qualitative method.

Results: Participants recognized the importance of the discharge support program and anticipated its benefits. The Rehabilitation Hospital Discharge Patient Support program saw more active involvement from doctors than the Establishment of a Public Health-Medical Collaboration System program. Both programs highlighted the critical need for more staff and better compensation, as identified by the doctors. Nurses and social workers cited the heavy documentation burden, uncooperative attitudes from patients and local governments, and other issues. They also anticipated that program improvements could be achieved through the standardization of regional welfare services and better coordination by local governments serving as welfare service regulators. All groups-doctors, nurses, and social workers-underscored the significance of promoting these programs.

Conclusions: Discharge support programs are crucial for patients with functional impairments and severe illnesses, particularly in ensuring continuity of care. Policy support is essential for the successful implementation of these programs in Korea.

Objectives: This study aimed to identify trends in avoidable mortality (AVM) in 16 provincial and metropolitan regions of Korea and determine the factors influencing AVM.

Methods: First, the avoidable mortality rate (AVMR) was calculated using the Statistics Korea cause-of-death and population data by age and region from 2013 to 2022. Second, a health determinants model was built, and we identified the factors influencing AVM using generalized estimating equations analysis.

Results: Although the AVMR per 100 000 people displayed a steadily decreasing trend from 2013 to 2020, it began to increase in 2021. Meanwhile, Jeonnam, Jeonbuk, Gyeongnam, Gyeongbuk, Chungnam, Chungbuk, and Gangwon Provinces showed a higher AVMR than the national average. The analysis revealed that each 1-unit increase in the older adult population, smoking, perceived stress, or non-local medical utilization was associated with an increase in the AVMR. Conversely, 1-unit increases in the male-to-female ratio, marriage rate, positive self-rated health, local medical utilization, doctor population, influenza vaccination rate, cancer screening rate, or financial independence were associated with decrease in the AVMR.

Conclusions: This study established that the AVMR, which had been continuously decreasing across the 16 regions, shifted to an increasing trend in 2021. We also identified several factors influencing AVM. Further studies are needed to confirm the reasons for this shift in the AVMR and explore the factors that influence AVM across Korea's 16 provincial and metropolitan regions.

Statistical testing in medicine is a controversial and commonly misunderstood topic. Despite decades of efforts by renowned associations and international experts, fallacies such as nullism, the magnitude fallacy, and dichotomania are still widespread within clinical and epidemiological research. This can lead to serious health errors (e.g., misidentification of adverse reactions). In this regard, our work sheds light on another common interpretive and cognitive error: the fallacy of high significance, understood as the mistaken tendency to prioritize findings that lead to low p-values. Indeed, there are target hypotheses (e.g., a hazard ratio of 0.10) for which a high p-value is an optimal and desirable outcome. Accordingly, we propose a novel method that goes beyond mere null hypothesis testing by assessing the statistical surprise of the experimental result compared to the prediction of several target assumptions. Additionally, we formalize the concept of interval hypotheses based on prior information about costs, risks, and benefits for the stakeholders (NORD-h protocol). The incompatibility graph (or surprisal graph) is adopted in this context. Finally, we discuss the epistemic necessity for a descriptive, (quasi) unconditional approach in statistics, which is essential to draw valid conclusions about the consistency of data with all relevant possibilities, including study limitations. Given these considerations, this new protocol has the potential to significantly impact the production of reliable evidence in public health.

The August 2024 floods in Bangladesh have precipitated a major public health crisis, significantly elevating the risk of waterborne and vector-borne diseases and exacerbating existing health vulnerabilities. This disaster has impacted over 5 million people, causing widespread environmental disruption, population displacement, and strained healthcare resources. The flooding of latrines, sewage systems, and agricultural land has led to the contamination of drinking water sources, increasing the risk of cholera, enterotoxigenic Escherichia coli diarrhoea, shigellosis, and hepatitis. Additionally, stagnant floodwaters have created breeding grounds for mosquitoes, thereby increasing the threat of malaria and dengue fever. The disruption of healthcare services has further compounded the crisis, delaying emergency responses and impeding access to care. The psychological impact on affected communities is profound, with mental health issues such as anxiety, depression, and post-traumatic stress disorder emerging as significant concerns. This perspective provides an analysis of these public health threats, supported by data on the impact of floods and a discussion of the underlying risk factors. This underscores the need for immediate and long-term public health interventions, including restoring clean water access, enhancing disease surveillance, repairing healthcare infrastructure, and addressing mental health needs. The response to this disaster must be rapid and comprehensive, with lessons learned to inform preparedness efforts to better manage similar events in the future.

Objectives: This study aimed to identify factors associated with life satisfaction by developing machine learning (ML) models to predict life satisfaction in older adults living alone.

Methods: Data were extracted from 3,112 older adults participating in the 2020 Korea Senior Survey. We employed 5 ML models to classify the life satisfaction of older adults living alone: logistic Lasso regression, decision tree-based classification and regression tree (CART), C5.0, random forest, and extreme gradient boost (XGBoost). The variables used as predictors included demographics, health status, functional abilities, environmental factors, and activity participation. The performance of these ML models was evaluated based on accuracy, precision, recall, F1-score, and area under the curve (AUC). Additionally, we assessed the significance of variable importance as indicated by the final classification models.

Results: Out of the 1,411 older adults living alone, 45.34% expressed satisfaction with their lives. The XGBoost model surpassed the performance of other models, achieving an F1-score of .72 and an AUC of .75. According to the XGBoost model, the five most important variables influencing life satisfaction were overall community satisfaction, self-rated health, opportunities to interact with neighbors, proximity to a child, and satisfaction with residence.

Conclusions: Overall satisfaction with the community environment emerged as the most significant predictor of life satisfaction among older adults living alone. These findings indicate that enhancing the supportiveness of the community environment could improve life satisfaction for this demographic.

Objectives: This study aimed to compare the Delta, Greenland, and Monte Carlo methods for estimating 95% confidence intervals (CIs) of the population-attributable fraction (PAF). The objectives were to identify the optimal method and to determine the influence of primary parameters on PAF calculations.

Methods: A dataset was simulated using hypothetical values for primary parameters (population, relative risk [RR], prevalence, and variance of the beta estimator ) involved in PAF calculations. Three methods (Delta, Greenland, and Monte Carlo) were used to estimate the 95% CIs of the PAFs. Perturbation analysis was performed to assess the sensitivity of the PAF to changes in these parameters. An R Shiny application, the "GDM-PAF CI Explorer," was developed to facilitate the analysis and visualization of these computations.

Results: No significant differences were observed among the 3 methods when both the RR and p-value were low. The Delta method performed well under conditions of low prevalence or minimal RR, while Greenland's method was effective in scenarios with high prevalence. Meanwhile, the Monte Carlo method calculated 95% CIs of PAFs that were stable overall, though it required intensive computational resources. In a novel approach that utilized perturbation for sensitivity analysis, was identified as the most influential parameter in the estimation of CIs.

Conclusions: This study emphasizes the necessity of a careful approach for comparing 95% CI estimation methods for PAFs and selecting the method that best suits the context. It provides practical guidelines to researchers to increase the reliability and accuracy of epidemiological studies.

Objectives: This study aimed to map the incidence of acute respiratory infections (ARIs) among under-5 children in Indonesia, address the triple burden of malnutrition, and analyze the impact of malnutrition on ARIs, taking into account the environmental and wealth disparities in Indonesia.

Methods: This study utilized an ecological design, analyzing aggregate data from the Indonesia Nutrition Survey, 2022. It encompassed 33 provinces and 486 districts/cities, involving a total of 334 878 children under 5 years of age. Partial least squares structural equation modeling was employed to investigate the relationships among wealth, environment, malnutrition (stunting, wasting, and underweight), and ARIs.

Results: The proportion of ARI cases in Indonesia was generally concentrated in central Sumatra, the western and eastern parts of Java, and eastern Papua. In contrast, the northern part of Sumatra, central Kalimantan, central Sulawesi, and central Papua had a higher proportion of malnutrition cases compared to other regions. Negative associations were found between malnutrition and ARIs (path coefficient =-0.072; p<0.01) and between wealth and environment (path coefficient =-0.633; p<0.001), malnutrition (path coefficient=-0.399; p<0.001), and ARIs (path coefficient=-0.918; p<0.001).

Conclusions: An increasing wealth index is expected to contribute to reducing ARIs, malnutrition and environmental burdens in the future. This study emphasizes the necessity for focused strategies that address both immediate health challenges and the underlying socioeconomic determinants to improve child health outcomes in the Indonesian context.