Respiratory and skin health among glass microfiber production workers: a cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Only a few studies have investigated non-malignant respiratory effects of glass microfibers and these have provided inconsistent results. Our objective was to assess the effects of exposure to glass microfibers on respiratory and skin symptoms, asthma and lung function.</p> <p>Methods</p> <p>A cross-sectional study of 102 workers from a microfiber factory (response rate 100%) and 76 office workers (73%) from four factories in Thailand was conducted. They answered a questionnaire on respiratory health, occupational exposures, and lifestyle factors, and performed spirometry. Measurements of respirable dust were available from 2004 and 2005.</p> <p>Results</p> <p>Workers exposed to glass microfibers experienced increased risk of cough (adjusted OR 2.04), wheezing (adjOR 2.20), breathlessness (adjOR 4.46), nasal (adjOR 2.13) and skin symptoms (adjOR 3.89) and ever asthma (adjOR 3.51), the risks of breathlessness (95%CI 1.68–11.86) and skin symptoms (1.70–8.90) remaining statistically significant after adjustment for confounders. There was an exposure-response relation between the risk of breathlessness and skin symptoms and increasing level of microfiber exposure. Workers exposed to sensitizing chemicals, including phenol-formaldehyde resin, experienced increased risk of cough (3.43, 1.20–9.87) and nasal symptoms (3.07, 1.05–9.00).</p> <p>Conclusion</p> <p>This study provides evidence that exposure to glass microfibers increases the risk of respiratory and skin symptoms, and has an exposure-response relation with breathlessness and skin symptoms. Exposure to sensitizing chemicals increased the risk of cough and nasal symptoms. The results suggest that occupational exposure to glass microfibers is related to non-malignant adverse health effects, and that implementing exposure control measures in these industries could protect the health of employees.</p

Short sleep and obesity in a large national cohort of Thai adults

Objective: To investigate the relationship between short sleep and obesity among Thai adults

Oral Health-Related Quality of Life among a large national cohort of 87,134 Thai adults

Background Oral health has been of interest in many low and middle income countries due to its impact on general health and quality of life. But there are very few population-based reports of adult Oral Health Related Quality of Life (OHRQoL) in developing countries. To address this knowledge gap for Thailand, we report oral health findings from a national cohort of 87,134 Thai adults aged between 15 and 87 years and residing all over the country. Methods In 2005, a comprehensive health questionnaire was returned by distance learning cohort members recruited through Sukhothai Thammathirat Open University. OHRQoL dimensions included were discomfort speaking, swallowing, chewing, social interaction and pain. We calculated multivariate (adjusted) associations between OHRQoL outcomes, and sociodemographic, health behaviour and dental status. Results Overall, discomfort chewing (15.8%), social interaction (12.5%), and pain (10.6%) were the most commonly reported problems. Females were worse off for chewing, social interaction and pain. Smokers had worse OHRQoL in all dimensions with Odds Ratios (OR) ranging from 1.32 to 1.51. Having less than 20 teeth was strongly associated with difficulty speaking (OR = 6.43), difficulty swallowing (OR = 6.27), and difficulty chewing (OR = 3.26). Conclusions Self-reported adverse oral health correlates with individual function and quality of life. Outcomes are generally worse among females, the poor, smokers, drinkers and those who have less than 20 teeth. Further longitudinal study of the cohort analysed here will permit assessment of causal determinants of poor oral health and the efficacy of preventive programs in Thailand

Predictors of Mortality among Inter-Hospital Transferred Patients in a Middle-Income Country: a Retrospective Cohort Study

Objective: To identify predictors for hospital mortality among inter-hospital transferred patients in low-resource settings of rural hospitals in Thailand. Methods: We conducted a retrospective cohort study of patients transferred from emergency room(ER) of a community hospital to its designated tertiary care hospital in a western province of Thailand. During March 2018 and February 2019, medical records of 412 patients were reviewed and extracted for potential predictor variables and outcomes. We defined deaths within 72 hrs after a transfer as primary outcome and overall hospital mortality as secondary outcome. Multivariate logistic regression analysis was performed to identify predictors of the outcomes adjusted for potential confounders. Results: Out of 412 patients, a total of 37 patients (9.0%) died during the stay in receiving hospital and 18 (4.4%) of them died within 72 hrs after transfer. Top ten primary diagnostic categories included road traffic injuries (19.7%), acute appendicitis (9.7%), and acute myocardial infarction (5.1%). Univariate analysis revealed early mortality (<72 hrs) was associated with NEWS2, Emergency Severity Index (ESI), cardiac arrest prior to transfer, use of vasoactive agents, endotracheal intubation and admitting service. Using multiple logistic regression model  adjusted for  the predictors identified by univariate analysis, we found early mortality was independently associated with NEWS2 ≥ 9 (compared to NEWS2 0-6) with OR= 17.51(95%CI 3.16-97.00)  and vasoactive medication use (OR= 5.46, 95%CI 1.39-21.46). Similarly, overall mortality was also independently associated with NEWS2 ≥ 9(OR= 4.76, 95%CI 1.31–17.36)  and  vasoactive medication use (OR= 7.51,95%CI  2.76–20.45). Conclusion: This study identified predictors of early (<72 hrs) hospital mortality and overall hospital mortality among ER patients transferred from a rural community hospital to its designated tertiary care hospital in Thailand, a middle-income country with universal healthcare coverage. The findings might be helpful to inform decision-making dealing with the inter-hospital transfer of ER patients in resource-poor rural settings with similar case-mix

æCLIMATE-HEAT The

association between overall health, psychological distress, and occupational heat stress among a large national cohort of 40,913 Thai worker

The magnitude of obesity and metabolic syndrome among diabetic chronic kidney disease population: A nationwide study

<div><p>Background</p><p>Although the prevalence of obesity and metabolic syndrome (MetS) among dialysis patients has been exceeding than general population, little is known regarding obesity and MetS in non-dialysis chronic kidney disease (CKD). We aimed to find the magnitude of obesity and MetS and their associations with impaired renal function among type 2 diabetes mellitus (T2DM) patients.</p><p>Methods</p><p>A national survey of T2DM patients was collected in the Thai National Health Security Office database during 2014–5. The sampling frame was designated as distinct geographic regions throughout the country. A stratified two-stage cluster sampling was used to select the study population. Anthropometry and 12-hour fasting blood samples were obtained by trained personnel. BMI of ≥25 kg/m² was classified as obesity. MetS was defined as having elevated waist circumference (>90 and >80 cm in men and women, respectively) plus any two of the followings: triglyceride ≥150 mg/dL, HDL-C <40 in men or <50 mg/dL in women, blood pressure ≥130/85 mmHg, and fasting blood sugar ≥100 mg/dL. CKD was defined as an impaired renal function (eGFR <60 mL/min/1.73m² according to the CKD-EPI equation). Logistic regression analysis was performed to examine the relationship between obesity and MetS with the presence of CKD.</p><p>Results</p><p>A total of 32,616 diabetic patients were finally recruited from 997 hospitals. The mean age was 61.5±10.9 years with 67.5% women. Of the participants, 35.4% were CKD patients. The prevalence of obesity was 46.5% in CKD and 54.1% in non-CKD patients with T2DM (<i>p</i><0.001). In contrast, the prevalence of MetS in CKD patients was higher than their non-CKD counterparts (71.3 <i>vs</i> 68.8%, <i>p</i><0.001). Moreover, there was an association between the prevalence of MetS with CKD stage from 3a to 5 (70.1, 72.3, 73.4, and 72.7%, respectively, <i>p trend</i> = 0.02). MetS, but not obesity, had a significant association with CKD in T2DM patients after adjusting for age, sex, and comorbidities [OR 1.14; 95% CI 1.06–1.22, <i>p</i><0.001]. When stratified by each component of MetS, only high serum triglyceride and low HDL-C levels were increased in patients with CKD stage 4 and 5 compared with CKD stage 3 (<i>p</i><0.001) and had a significant relationship with impaired renal function.</p><p>Conclusion</p><p>There were relatively high prevalences of both obesity and MetS in T2DM patients. A higher prevalence of MetS, but lower prevalence of obesity, was observed among diabetic CKD group compared with their non-CKD counterparts. MetS, as a surrogate of insulin resistance, appeared to be more important than obesity in the development of impaired renal function in diabetic population.</p></div

Unadjusted and adjusted odd ratio (OR) and 95% confidence interval (CI) for the relationship between different subclasses of obesity and metabolic syndrome with the presence of CKD.

<p>Unadjusted and adjusted odd ratio (OR) and 95% confidence interval (CI) for the relationship between different subclasses of obesity and metabolic syndrome with the presence of CKD.</p