AIMS Public Health最新文献

Purpose: This study aimed to assess the association between nutrition behavior, food intake, being overweight, and obesity among school-aged children and adolescents aged 9 to 17 years. Additionally, it sought to examine how these factors influence being overweight and obese within this population.

Methods: A population-based cross-sectional study was conducted with a representative multistage cluster sample of 4200 Pakistani school-aged children and adolescents aged 9 to 17 years from 62 schools across seven random districts in Punjab province, Pakistan. Underweight (BMI < 5th percentile), overweight (85th ≤ BMI < 95th percentile), and obese (95th percentile ≤ BMI) were defined using the US Center for Disease Control (CDC) 2000 criteria, and a Chi-square test utilized for comparison. The Pearson correlation coefficient (r) assessed any correlations, while a linear regression analysis explored the predictive power of Nutrition Behavior/Food Intake factors (independent variables) on body-weight (dependent variable). A logistic regression analysis estimated the simultaneous influence of multiple factors on the dichotomous outcomes, and the 95% confidence intervals (CI) were calculated. The statistical significance level was set at p < 0.05.

Results: The study was comprised of 4108 Pakistani school children aged 9 to 17 years (mean age = 13.92 years, 59.3% boys) from 62 schools. Among them, the prevalence of being overweight and obese individuals was 19.4% and 10.7%, respectively. Factors such as skipping breakfast (OR 2.45, 95% CI 1.53-3.93, p < 0.001), consuming vegetables less than once a week (OR 4.12, 95% CI 3.06-5.55, p < 0.001), consuming soft drinks three or more times a week (OR 4.74, 95% CI 3.73-6.04, p < 0.001), and consuming fast food three or more times a week (OR 10.56, 95% CI 8.16-13.67, p < 0.001) were associated with a higher risk of obesity.

Conclusion: Being overweight and obese pose significant concerns among school-aged children and adolescents in Pakistan, showing a troubling upward trend. Poor nutrition behaviors, including frequenting fast-food restaurants and low consumption of fruits and vegetables, contribute to these issues. It is imperative to comprehend these risk factors to formulate impactful policies and dietary interventions that target childhood obesity in Pakistan. Identifying vulnerable populations and implementing tailored intervention strategies are essential for public health efforts. While further interventions may be needed to reduce the body mass index (BMI) and manage being overweight and obese, the findings of this study provide valuable insights into addressing these critical health challenges.

This study aimed to examine the relationship between changes in lifestyle habits and presenteeism change according to sex. This retrospective cohort study was conducted using data from health checkups, the World Health Organization Health and Work Performance Questionnaire (WHO-HPQ) short form, and health insurance claims for 9366 Japanese corporate employees in 2015 and 2016. Changes in 11 lifestyle habits of sleeping, eating, exercise, drinking, and smoking were classified into four patterns by combining lifestyle habits (good/poor): (a) no worsening, (b) worsening, (c) no improvement, and (d) improvement. A multiple regression analysis was conducted for each sex, with changes in the WHO-HPQ score as the objective variable, lifestyle habits change (worsening or improvement) as the explanatory variables, and age, job position, department, diseases, lifestyle habits, and WHO-HPQ score at baseline as adjustment variables. The results showed worsening of good lifestyle habits, such as sleeping, regular exercise, and frequency of drinking in men, while sleeping in women was associated with negative changes in the WHO-HPQ score. On the other hand, the improvement of poor lifestyle habit of sleeping was associated with positive changes in the WHO-HPQ score. These findings suggest that maintaining good lifestyle habits of sleeping for both sexes, and exercising and drinking for men, may be beneficial in maintaining work performance, while improving the poor lifestyle habit of sleeping for women may be beneficial in improving work performance.

Cancer represents a major global health burden, prompting continuous research for effective therapeutic strategies. Natural compounds derived from plants have emerged as potential strategies for preventing cancer and treatment because of their inherent pharmacological properties. This comprehensive review aimed to evaluate the therapeutic potential of five key natural compounds: apigenin, quercetin, piperine, curcumin, and resveratrol in cancer prevention and therapy. By examining their molecular mechanisms and preclinical evidence, this review seeks to elucidate their role as potential adjuvants or stand-alone therapies in cancer management. The exploration of natural compounds as cancer therapeutics offers several advantages, including low toxicity, wide availability, and compatibility with conventional chemotherapeutic agents. We highlighted the current understanding of their anticancer mechanisms and clinical applications for advancing personalized cancer care to improve patient outcomes. We discussed the empirical findings from in vitro, in vivo, and clinical studies reporting biological activity and therapeutic efficacy in antioxidant, immunomodulatory, anti-carcinogenic, and chemo-sensitizing modes. Innovative delivery systems and personalized treatment approaches may further enhance their bioavailability and therapeutic utility in a synergistic approach with chemo- and radiotherapeutic disease management. This review underscores the importance of natural compounds in cancer prevention and treatment, promoting a multidisciplinary approach to the development of innovative therapeutic strategies.

Background: Silicosis is an occupational respiratory disease linked to silica dust inhalation. The main driver was traditional coal mining, but in recent decades, new sources of exposure have emerged. Our aim in this study was to assess the temporal and spatial distribution of mortality due to this disease over a 22-year period in Spain.

Methods: Silicosis records, as an Underlying Cause of Death, were extracted from the National Institute of Statistics from 1999 to 2020 using the International Classification of Diseases 10th revision (code J62.8). Age- and sex-adjusted mortality rates per 1,000,000 inhabitants were calculated for the territory and by province. A geographic analysis was performed, and clusters of deaths were identified at the municipal level, and then the outcomes were compared in two periods of 11 years.

Results: There were 2618 deaths due to silicosis in Spain. The mean age of death increased significantly by 0.66% annually from 1999 to 2013. The age-adjusted mortality rate decreased by 7.30% per year, falling from 3.00 to 0.65 per 1,000,000 inhabitants. The temporal pattern showed a significant decrease of mortality rate in 31% of the provinces (16 out of 52), while it increased in Pontevedra. Regarding the spatial analysis, 11 clusters were found in both periods, but some variations were observed in terms of their distribution in the Spanish territory, as well as in the affected municipalities.

Conclusions: The decrease in mortality due to Silicosis could be related to less exposure to silica dust over the years and an improvement in the survival of those affected. It is thus essential to analyze the role of preventive measures for this occupational disease.

As the COVID-19 global vaccination campaign was launched in December of 2020, vaccination became mandatory for many healthcare workers (HCWs) worldwide. Large minorities resisted the policy, and the responses of authorities to this resistance led to damaged professional reputations, job losses, and suspension or termination of practice licenses. The joint effect of dismissals, early retirements, career changes, and vaccine injuries disabling some compliant HCWs from adequate performance has exacerbated existing crises within health systems. Nevertheless, leading health authorities have maintained that the benefits of a fully vaccinated healthcare labor force-believed to be protecting health systems, vulnerable patient populations, and even HCWs themselves-achieved through mandates, if necessary, outweigh its potential harms. Informed by critical policy and discourse traditions, we examine the expert literature on vaccine mandates for HCWs. We find that this literature neglects evidence that contradicts official claims about the safety and effectiveness of COVID-19 vaccines, dismisses the science supporting the contextual nature of microbial virulence, miscalculates patient and system-level harms of vaccination policies, and ignores or legitimizes the coercive elements built into their design. We discuss the implications of our findings for the sustainability of health systems, for patient care, and for the well-being of HCWs, and suggest directions for ethical clinical and policy practice.

Objective: We employed machine learning algorithms to discriminate insulin resistance (IR) in middle-aged nondiabetic women.

Methods: The data was from the National Health and Nutrition Examination Survey (2007-2018). The study subjects were 2084 nondiabetic women aged 45-64. The analysis included 48 predictors. We randomly divided the data into training (n = 1667) and testing (n = 417) datasets. Four machine learning techniques were employed to discriminate IR: extreme gradient boosting (XGBoosting), random forest (RF), gradient boosting machine (GBM), and decision tree (DT). The area under the curve (AUC) of receiver operating characteristic (ROC), accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and F1 score were compared as performance metrics to select the optimal technique.

Results: The XGBoosting algorithm achieved a relatively high AUC of 0.93 in the training dataset and 0.86 in the testing dataset to discriminate IR using 48 predictors and was followed by the RF, GBM, and DT models. After selecting the top five predictors to build models, the XGBoost algorithm with the AUC of 0.90 (training dataset) and 0.86 (testing dataset) remained the optimal prediction model. The SHapley Additive exPlanations (SHAP) values revealed the associations between the five predictors and IR, namely BMI (strongly positive impact on IR), fasting glucose (strongly positive), HDL-C (medium negative), triglycerides (medium positive), and glycohemoglobin (medium positive). The threshold values for identifying IR were 29 kg/m², 100 mg/dL, 54.5 mg/dL, 89 mg/dL, and 5.6% for BMI, glucose, HDL-C, triglycerides, and glycohemoglobin, respectively.

Conclusion: The XGBoosting algorithm demonstrated superior performance metrics for discriminating IR in middle-aged nondiabetic women, with BMI, glucose, HDL-C, glycohemoglobin, and triglycerides as the top five predictors.

Gender-based violence (GBV) poses a significant concern in the construction and natural resources industries, where women, due to lower social status and integration, are at heightened risk. This systematic review aimed to identify the prevalence and experience of GBV in the construction and natural resources industries. A systematic search across databases including PubMed, OVID, Scopus, Web of Science, and CINAHL was conducted. The Risk of Bias Instrument for Cross-sectional Surveys of Attitudes and Practices by McMaster University and the Critical Appraisal of Qualitative Studies by the Center for Evidence Based Medicine at the University of Oxford were used to assess the studies included in the review. Six articles were included after full-text analysis. GBV was reported in the construction, mining, urban forestry, and arboriculture sectors. Workplace GBV was measured differently across the studies, and all studies examined more than one form of GBV. The main forms of GBV discussed in these studies were discrimination, sexual harassment, and sexism. The studies provided some insight for demographic factors that may or may not be associated with GBV, such as age, region of work, and number of years working in the industry. The review also suggests that workplace GBV has a negative impact on mental health and well-being outcomes, such as higher levels of stress and lower job satisfaction. The current research has not established the effectiveness of interventions, tools, or policies in these workplaces. Thus, additional research should include intervention studies that aim to minimize or prevent GBV in male-dominated workplaces. The current study can bring awareness and acknowledgement towards GBV in the workplace and highlight the importance of addressing it as this review outlines the negative consequences of GBV on mental health and well-being in these male-dominated industries.

Measles, a highly contagious viral disease, spreads primarily through respiratory droplets and can result in severe complications, often proving fatal, especially in children. In this article, we propose an algorithm to solve a system of fractional nonlinear equations that model the measles disease. We employ a fractional approach by using the Caputo operator and validate the model's by applying the Schauder and Banach fixed-point theory. The fractional derivatives, which constitute an essential part of the model can be treated precisely by using the Broyden and Haar wavelet collocation methods (HWCM). Furthermore, we evaluate the system's stability by implementing the Ulam-Hyers approach. The model takes into account multiple factors that influence virus transmission, and the HWCM offers an effective and precise solution for understanding insights into transmission dynamics through the use of fractional derivatives. We present the graphical results, which offer a comprehensive and invaluable perspective on how various parameters and fractional orders influence the behaviours of these compartments within the model. The study emphasizes the importance of modern techniques in understanding measles outbreaks, suggesting the methodology's applicability to various mathematical models. Simulations conducted by using MATLAB R2022a software demonstrate practical implementation, with the potential for extension to higher degrees with minor modifications. The simulation's findings clearly show the efficiency of the proposed approach and its application to further extend the field of mathematical modelling for infectious illnesses.

Introduction: The prevalence of workplace bullying, job burnout, and turnover intention among nursing staff increased during the COVID-19 pandemic. However, to the best of our knowledge, there are no studies that have measured the relationships among variables of interest after the pandemic.

Objective: Our intention is to investigate the effect of workplace bullying on job burnout and turnover intention in nursing staff.

Methods: We conducted a cross-sectional study during January-February 2024 in Greece. We obtained a convenience sample of 450 nurses. We used the 22-item Negative Acts Questionnaire-Revised to assess workplace bullying. We measured job burnout with the single-item burnout measure. We measured nurses' turnover intention with a valid 6-point Likert scale.

Results: The study sample included 450 nurses with the mean age of 39.1 years (standard deviation [SD] = 10.2). The mean workplace bullying score was 7.7 (SD = 2.0), while the mean job burnout score was 7.7 (SD = 2.0). Among our nurses, 57.3% showed a high level of turnover intention. After eliminating confounders, we found that increased workplace bullying (adjusted beta = 0.031, 95% confidence interval [CI] = 0.023 to 0.039, p < 0.001) was associated with increased job burnout. Moreover, multivariable logistic regression analysis showed that increased turnover intention was more common among nurses who experienced higher levels of workplace bullying (adjusted odds ratio = 1.057, 95% CI = 1.043 to 1.071, p < 0.001).

Conclusion: We found a positive relationship between workplace bullying, job burnout, and turnover intention. Nurse managers, organizations, and policy-makers ought to consider such findings to intervene and decrease workplace bullying by improving working conditions.