Osong Public Health and Research Perspectives最新文献

Objectives: This study aimed to estimate the prevalence of loss to follow-up (LTFU) among tuberculosis (TB) patients in Indonesia and to identify associated factors.

Methods: This study analyzed data from the 2022 Tuberculosis Information System in Indonesia. A total of 71,665 drug-sensitive TB patients were included in the analysis. Age, sex, employment status, diagnosis type, human immunodeficiency virus (HIV) status, diabetes mellitus, TB type, mode of treatment, treatment standard, referral status, and type of residence. Categorical variables were analyzed using chi-square tests, followed by multivariable logistic regression to identify confounder-adjusted independent predictors of LTFU.

Results: The prevalence of LTFU was 18.4%. A higher likelihood of LTFU was observed among older adults aged ≥65 years (adjusted-prevalence-odds-ratio [aPOR], 1.862), men (aPOR, 1.187), unemployed individuals (aPOR, 1.136), non-referred patients (aPOR, 1.547), patients with HIV (aPOR, 3.712), and those obtaining TB drugs out of pocket (aPOR, 4.998). The strongest predictor was receipt of non-standard treatment, which was associated with a markedly increased likelihood of LTFU (aPOR, 26.912). In contrast, rural residence demonstrated a protective association (aPOR, 0.610). All associations were statistically significant (p<0.001).

Conclusion: This study highlights a substantial burden of LTFU among TB patients in Indonesia, with nearly one in five patients discontinuing treatment. Multiple sociodemographic and clinical factors-particularly non-standard treatment, non-referral status, and HIV co-infection-were strongly associated with LTFU, underscoring gaps in the TB care continuum. These findings emphasize the need for targeted, patient-centered interventions, strengthened referral pathways, improved communication, and enhanced care coordination to reduce LTFU in high-risk groups.

Objectives: This study aimed to determine the prevalence of severe dengue and examine the associations between pre-existing comorbidities and disease severity.

Methods: This retrospective study examined patients with dengue fever who received inpatient treatment at a hospital in northern Vietnam between January 1, 2022, and December 30, 2024. Patients were categorized into 2 groups-severe dengue and non-severe dengue-based on the 2009 World Health Organization criteria. Multivariable logistic regression was performed to assess factors associated with severe dengue.

Results: Among 3,692 patients, the prevalence of severe dengue was 1.5%. Patients with any pre-existing comorbidity had higher odds of severe dengue compared to those without comorbidities (adjusted odds ratio [aOR], 2.06; 95% confidence interval [CI], 1.20-3.53). Having 2 or more comorbidities was also associated with higher odds of severe dengue (aOR, 2.26; 95% CI, 1.18-4.33). Among individual conditions, hyperlipidemia was associated with severe dengue (aOR, 2.32; 95% CI, 1.17-4.81). Certain combinations of comorbidities, including hypertension with hyperlipidemia (aOR, 2.88; 95% CI, 1.39-5.97), hypertension with cardiac disease (aOR, 4.39; 95% CI, 1.30-14.79), and hyperlipidemia with cardiac disease (aOR, 4.02; 95% CI, 1.19-13.53), were also associated with higher odds of severe dengue.

Conclusion: Pre-existing comorbidities, particularly cardiometabolic conditions, were associated with higher odds of severe dengue. Considering comorbidity profiles at hospital admission may help identify patients who require closer clinical monitoring.

Objectives: The association between dietary fat intake and sleep quality remains unclear. This study investigated the impact of both dietary fat quality and quantity on sleep quality.

Methods: In this cross-sectional study, participants completed a food frequency questionnaire and Pittsburgh Sleep Quality Index to assess quantity and quality of fat intake and sleep quality.

Results: A total of 1,904 participants (55% female) were included in the study. Participants in the highest tertile of polyunsaturated fatty acids (PUFA) intake, compared with those in the lowest tertile, had significantly higher total sleep quality scores (odds ratio [OR], 1.27; 95% confidence interval [CI], 1.01-1.62) and longer sleep onset latency (OR, 1.40; 95% CI, 1.08-1.83). Participants with higher animal fat intake exhibited higher total sleep quality scores (OR, 1.44; 95% CI, 1.09-1.89) and increased sleep disturbances (OR, 1.37; 95% CI, 1.02-1.83). Among women, those in the highest tertile compared with the lowest tertile showed increased odds of higher total sleep quality scores with total fat (OR, 1.37; 95% CI, 1.04-1.82), PUFA (OR, 1.41; 95% CI, 1.07-1.87), monounsaturated fatty acids (OR, 1.44; 95% CI, 1.09-1.90), saturated fatty acid (OR, 1.33; 95% CI, 1.01-1.77), and animal fat (OR, 1.58; 95% CI, 1.18-2.11).

Conclusion: These findings suggest that higher intakes of PUFA and animal fat are associated with higher total sleep quality scores. When stratified by sex, higher intake of total fat and unsaturated fats was associated with higher total sleep quality scores in women only.

Background: This study aimed to examine the temporal dynamics of dengue cases in Malaysia from 2022 to 2024 using seasonal-trend decomposition and time-series modeling.

Methods: Weekly dengue case counts from the national registry were analyzed across all states using seasonal-trend decomposition using LOESS (STL) to separate trend, seasonal, and irregular components. Autoregressive integrated moving average (ARIMA) and seasonal ARIMA (SARIMA) models were fitted to validate temporal structures, with model selection based on the Akaike information criterion (AIC), corrected AIC, and Bayesian information criterion. Diagnostic checks, including residual analysis and Ljung-Box testing, were performed to ensure model adequacy.

Results: Dengue incidence showed marked heterogeneity across states. STL decomposition indicated that long-term trends contributed more strongly to case dynamics than seasonality in most states, although seasonal influences were significant in the states of Kedah and Kelantan. Seasonal peak timing varied between states, highlighting differences in epidemic cycles. ARIMA and SARIMA modeling confirmed that no single temporal structure could adequately represent all states; while some series were well fitted by simple ARIMA models, others required seasonal adjustments. Residual diagnostics demonstrated that the selected models were statistically adequate.

Conclusion: Dengue dynamics in Malaysia are shaped by both trend and seasonal components, with considerable variation across states. Combining STL decomposition with ARIMA/SARIMA modeling strengthens the evidence base for state-specific forecasting and proactive vector control. Tailoring surveillance systems and interventions to local temporal patterns.

Background: Non-communicable disease (NCD) risk among adolescents represents a growing concern due to modifiable, lifestyle-related behavioral risk factors. Early identification and control of these factors are essential for prevention. This study assessed the correlates and cooccurrence of NCD-related lifestyle risk factors among school-going adolescents in Karnataka, India, aiming to inform intervention development.

Methods: Screening was conducted among 1,100 school adolescents aged 13-16 years from 8 randomly selected urban and rural schools in Karnataka. Data were collected using a validated self-administered questionnaire covering sociodemographic characteristics and social cognitive theory predictors of lifestyle practices. Descriptive statistics, chi-square tests, and logistic regression were employed.

Results: Of the 1,100 adolescents surveyed, 552 and 548 were from urban and rural areas, respectively. Both groups reported high rates of insufficient fruit and vegetable (FV) intake (96.7% and 67.7%, respectively), inadequate physical activity (96.7% and 68.6%), tobacco use (5.6% and 11.5%), and alcohol consumption (5.6% and 10.8%). On logistic regression, urban adolescents were significantly more likely than rural peers to exhibit multiple behavioral risk factors, with 19-fold higher odds of having ≥1 factor (adjusted odds ratio [AOR], 19.04; p< 0.001) and 4-fold higher odds of having ≥2 (AOR, 4.06; p < 0.001). Parental (particularly maternal) education was associated with NCD risk (AOR, 1.82; p= 0.001). Physical inactivity significantly co-occurred with low FV intake (71.7%) and junk food consumption (72.8%).

Conclusion: Unhealthy lifestyle behaviors among adolescents displayed significant cooccurrence, underscoring the critical need for comprehensive, theory-based school interventions to address multiple interconnected risk factors and mitigate the burden of NCDs.

Background: In May 2025, clusters of salmonellosis were identified in 7 cities in the Republic of Korea, all associated with consumption of identical bakery products. This investigation aimed to characterize the outbreak, identify potential contributing factors, and inform strategies for preventing similar multi-facility foodborne outbreaks.

Methods: A case series study was conducted among individuals who consumed Manufacturer H's Product I and Product II on May 15-16, 2025 at 7 facilities (n= 1,235). Clinical specimens from symptomatic individuals, retained food samples, and environmental samples were collected and tested. Food-exposure histories were assessed, and active case finding was implemented across all supplied facilities. Traceback investigations were conducted at the manufacturer, distributor, and egg farms. Human and food isolates underwent pulsed-field gel electrophoresis (PFGE) and whole-genome sequencing (WGS).

Results: A total of 323 cases met the outbreak case definition (attack rate, 26.2%), of which 48 were laboratory-confirmed. Salmonella Enteritidis was isolated from both clinical specimens and retained bakery products. PFGE patterns were indistinguishable between human and food isolates, and WGS demonstrated high genetic relatedness. These findings confirmed a common-source outbreak linked to the implicated bakery products.

Conclusion: This outbreak underscores the value of integrating epidemiological investigation, active case finding, and molecular typing to identify common food vehicles in outbreaks involving widely distributed manufactured foods. Coordinated collaboration between public health and food safety authorities is essential for the effective detection, response, and prevention of multi-facility foodborne outbreaks.

The coronavirus disease 2019 (COVID-19) pandemic had an unprecedented global impact, resulting in both positive and negative consequences. The virus not only affected millions of lives worldwide but also caused long-term harm to multiple organ systems in many survivors, thereby substantially impairing quality of life. This persistent condition is now referred to as long COVID (LC). The aim of this study is to raise awareness of LC-related organ system impacts and to highlight the key role of artificial intelligence (AI) in mitigating these effects. The present research conducts a narrative review focusing on LC-related impacts. In this context, unstructured searches were conducted to identify a total of 69 relevant studies indexed in Embase, PubMed, Web of Science, or Scopus, each of which was reviewed by at least 2 experts with sufficient domain knowledge in health sciences. Based on the authors' perspectives and insights, the review narratively examines damage to human organ systems attributable to LC and explores the role of AI in addressing LC-related challenges. Significant ethical, practical, and societal concerns arising from the extensive use of AI, particularly major issues such as data privacy and algorithmic bias, are also discussed. LC has caused lasting impacts on human organ systems, while AI is offering substantial potential for LC-related care.

Background: Smartphone overdependence (SOD) and anxiety are major concerns in adolescent mental health; however, few studies have examined their bidirectional relationship. This study aimed to examine reciprocal associations between SOD and anxiety among adolescents.

Methods: A secondary analysis was conducted with data from 50,975 adolescents in the 19th Korea Youth Risk Behavior Survey. SOD was measured using the SOD scale, and anxiety was assessed using the generalized anxiety disorder 7-item scale. Multivariable logistic regression analyses were conducted to examine reciprocal associations, adjusting for sociodemographic factors, perceived stress, loneliness, and depressive symptoms.

Results: Moderate to severe anxiety was found in 12.6% of participants, and 3.3% were classified as being at high risk for SOD. In adjusted models, the model with anxiety as the outcome demonstrated higher predictive performance (concordance rate, 86.5%) than the model with SOD as the outcome (77.3%). Adolescents at high risk for SOD had higher odds of reporting anxiety, and those with severe anxiety had higher odds of being classified as at high risk for SOD. Stress, loneliness, and smartphone use time were also identified as significant predictors.

Conclusion: SOD and anxiety were strongly associated with each other among adolescents. Integrated approaches addressing both digital behavior and mental health may help inform strategies to reduce psychological distress. Public health strategies may benefit from considering both aspects when screening for problematic smartphone use and anxiety.