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The evolution of comorbidities in chronic diseases among Chinese middle-aged and elderly people: Evidence from the CHARLS (2015-2020)
Background The comorbidity of chronic diseases among middle-aged and elderly people is a global public health concern that has attracted great attention in recent years. It is crucial to explore the evolutionary pattern of chronic disease comorbidity in Chinese middle-aged and elderly people and to reveal the developmental trajectory of chronic diseases in this population. Methods Data from the China Health and Retirement Longitudinal Study (CHARLS 2015–2020) were utilized for the fixed cohort analysis. Based on the prevalence information of 14 chronic diseases (including hypertension, dyslipidemia, diabetes, cancer, chronic lung diseases, liver disease, heart disease, stroke, kidney disease, stomach diseases, emotional problems, memory-related diseases, arthritis, and asthma) among 10,089 participants aged ≥45 years, association rules and cluster analysis were used to identify trends and trajectories of comorbidities in the middle-aged and elderly populations in China. Results The analysis revealed that the comorbidity rate of the 14 chronic diseases showed a consistent annual increase from 2015–2020. By 2020, over 85% of patients diagnosed with a single chronic condition exhibited concurrent multimorbidity. This epidemiological progression was paralleled by a progressive increase in detected disease associations: binary comorbidities rose from three significant associations in 2015–10 in 2020, whereas higher-order combinations expanded from one ternary association in 2015–35 ternary and 18 quaternary associations by 2020. Notably, hypertension maintained a central position across all identified comorbidity clusters. The comorbidity patterns identified in 2015 included respiratory, liver and kidney, and cardio-cerebral comorbidity patterns and cancer and emotional problems. The comorbidity patterns identified in 2018 included respiratory, liver and kidney, cerebrovascular, and cardiovascular metabolic comorbidity patterns. The comorbidity pattern in 2020 was the same as that in 2018. Conclusion The issues of comorbidities in chronic diseases among Chinese middle-aged and elderly people is significant, with observed variations in the comorbidity patterns across different time periods. The development of clinical assessment and management guidelines for chronic diseases comorbid with key conditions, such as hypertension and dyslipidemia, is recommended. These guidelines aim to facilitate the co-management, co-treatment, and co-reduction of multiple diseases among middle-aged and elderly people.
Expression of concern: Water, sanitation, and hygiene conditions and prevalence of intestinal parasitosis among primary school children in Dessie City, Ethiopia
Healthcare utilization associated with antimicrobial resistance at a tertiary hospital in Vietnam: A retrospective observational study from 2016 to 2021
Background Despite the increasing burden of antimicrobial resistance (AMR), specifically on priority ESKAPE pathogens, studies examining the economic impact of AMR in low- and lower-middle-income countries have been scarce and require further investigation to optimize the post-COVID resource allocation. Objectives To quantify the incremental hospital costs and length of stay (LOS) associated with antimicrobial-resistant versus -susceptible among priority ESKAPE pathogens from the healthcare sector perspective. Methods We conducted a retrospective observational study of patients hospitalized at the Hospital for Tropical Diseases from 2016−2021 with non-duplicate isolates of any ESKAPE pathogens from clinical specimens. The patients were then stratified into resistant- and susceptible- groups by the WHO classification. Multivariate generalized linear regression and negative binomial regression with linear spline at COVID-19 occurrence were employed to evaluate the incremental hospital costs and LOS due to AMR, respectively. These regressions were adjusted for sociodemographic and clinical characteristics. We applied difference-in-difference (DiD) to estimate the differential cost between resistant and susceptible groups regarding COVID-19 change. Results During the six-year period, 4,197 out of 6,670 patients (62.92%) were isolated with priority pathogens, with the highest prevalence of priority pathogens observed in 3GCREC and MRSA (accounting for 45.63% and 25.33%, respectively). After covariate adjustments, the incremental hospital costs per resistant patient were significantly higher across most pathogens except for patients tested with MRSA results (average CRAB $3,980; CRPA $1,000; 3GCREC $444; 3GCRKP $1,942; MRSA -$326), while incremental LOS ranged from 1.40 days for 3GCREC (95%CI: 0.69–2.10 ) to 12.54 days for CRPA (95%CI: 11.12–13.97). COVID-19 significantly enlarged the hospital cost gaps between patients with antibiotic-resistant and antibiotic-susceptible profiles, with A.baumannii (CRAB vs. CSAB) showing the highest DiD at $9,116 (95%CI: $6,019-$12,213). Conclusion The incremental hospital costs of AMR were significant, with the highest one observed in CRAB patients, and the difference between resistant and susceptible cases widened during the COVID-19 pandemic.
Correction: Impact of prolonged social crisis on resilience and coping indicators
Prevalence, associated risk factors and satellite imagery analysis in predicting soil-transmitted helminth infection in Nakhon Si Thammarat Province, Thailand
Abstract Soil-transmitted helminth (STH) infections remain a significant public health concern in rural areas, often leading to nutritional and physical impairment, particularly in children. This study aimed to assess the prevalence and associated factors of STH infections among schoolchildren in Thasala District, Nakhon Si Thammarat Province, Thailand, and to develop a predictive model for identifying high-risk areas using satellite imagery data. A cross-sectional study was conducted with 319 primary schoolchildren from six sub-districts in Thasala District. Stool samples were analyzed for STH infections using the formalin ethyl acetate concentration technique (FECT) and agar plate culture (APC), while behavioral data were collected through questionnaires to identify key risk factors. We developed an innovative predictive model by integrating convolutional neural networks (CNNs) for land-use classification of satellite imagery with artificial neural networks (ANNs) following dimensionality reduction through principal component analysis (PCA). The STH infections were detected in 31 samples (9.72%), with higher prevalence in males (11.38%) than females (8.67%). Mono-infections predominated, with Trichuris trichiura (5.02%) and hookworm (3.49%) being the most frequent. Mixed infections accounted for 1.25%, primarily co-infections of hookworm with T. trichiura (0.94%) or Strongyloides stercoralis (0.31%). Not cutting nails was identified as a significant behavioral factor associated with STH infections (p = 0.047), while other behavioral factors showed no statistical significance. From the satellite imagery analysis, specific environmental features, particularly higher proportions of agricultural land and closer proximity to water bodies, were positively associated with elevated STH prevalence. The modelling approach generated spatial risk maps for STH infections, providing a cost-effective tool for identifying high-risk transmission zones. These findings highlight that STH infections persist among rural Thai schoolchildren, with poor hygiene practices as a contributing factor. Strengthening hygiene education, improving sanitation, and implementing targeted environmental interventions are essential for effective control.