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Open access

Jarmmaree Sornboot, Wichai Aekplakorn, Pongrama Ramasoota, Surat Bualert, Somying Tumwasorn and Wiroj Jiamjarasrangsi



Long-term surveillance of airborne bioaerosols in health care facilities is required to protect the health of patients and health care workers. Feasible methods to measure airborne bioaerosol concentrations and determine associated environmental factors may help to avoid nosocomial tuberculosis (TB).


To describe the concentrations and size of airborne bioaerosols and to identify the potential contributors to indoor airborne bioaerosols in TB high-risk areas in health care facilities.


We conducted a cross-sectional study in 7 large health care facilities located in Bangkok and nearby in central Thailand using a 6-stage Andersen cascade impactor to collect viable airborne bioaerosols that were quantified using culture techniques. Environmental parameters were determined using a tracer gas technique with an indoor air quality meter. Other potential factors were assessed using a questionnaire.


The mean indoor airborne bacterial and fungal concentrations were 596.1 and 521.2 colony-forming units (cfu)/m3, respectively, and the mean outdoor airborne bacterial and fungal concentrations were 496.5 and 650.1 cfu/m3, respectively. The majority of airborne bioaerosols were in respirable sizes. The indoor-to-outdoor ratios were 1.2 for bacteria and 0.8 for fungi. Air change rate was inversely correlated with indoor airborne bioaerosol concentrations, whereas emergency department central-type air conditioners and relative humidity were positively correlated with the indoor airborne bioaerosol concentrations (P < 0.05).


High indoor bioaerosol concentrations found in the health care facilities suggest that it is imperative to improve the indoor air quality. Improved air change rate and avoiding use of central-type air-conditioning systems may reduce bioaerosol concentrations.

Open access

Andrew J. Hillman, Vitool Lohsoonthorn, Orrawadee Hanvivatvong and Wiroj Jiamjarasrangsi


Background: Limited information is available regarding associations of metabolic syndrome with C-reactive protein (CRP) concentrations among Asian populations. Objective: Investigate the association of high sensitivity CRP (hsCRP) concentrations and metabolic syndrome among Thai adults. Methods: This cross-sectional study was comprised of 467 Thai participants (209 men and 258 women) receiving annual health check-up. Spearman’s rank correlation coefficients were used to assess the associations between metabolic parameters (age, waist circumference, blood pressure, triglycerides, HDL-C, fasting plasma glucose, fasting insulin and uric acid) with hsCRP concentrations for men and women, respectively. Multivariable logistic regression procedures were used to estimate the risk (odds ratios (OR), and 95% confidence intervals (CI) of metabolic syndrome according to low, moderate, and high hsCRP concentrations (<1.0, 1.0-3.0, and >3.0 mg/L, respectively). Results: Measures of adiposity and fasting insulin were positively and significantly correlated with hsCRP concentrations among women with and without metabolic syndrome. Similar associations were observed among men without metabolic syndrome. After controlling for confounders, moderately elevated hsCRP concentrations were associated with a 2.38-fold increased risk of metabolic syndrome (OR=2.38, 95%CI=1.20-4.72) among men. Men with high hsCRP concentrations had a 5.45-fold increased risk of metabolic syndrome (OR=5.45, 95%CI=2.24- 13.27) when compared with those who had low hsCRP concentrations. The corresponding OR for women with moderately elevated and high hsCRP concentrations were 4.92 (OR=4.92, 95%CI=2.34-10.35) and 11.93 (OR=11.93, 95%CI=5.54-25.72), respectively. Conclusions: These findings are consistent with the literature suggesting a role of hsCRP as a biomarker for metabolic syndrome.

Open access

Wiroj Jiamjarasrangsi, Suwapiccha Attavorrarat, Rungrawee Navicharern, Wichai Aekplakorn and Prasit Keesukphan


Background: Sparse information exists regarding the progress of the chronic care model (CCM) implementation for type 2 diabetes, at system-wide level for developing countries including Thailand.

Objective: We assessed the extent to which type 2 diabetes patients in Bangkok, Thailand report having received CCM-based services by using the Patient Assessment of Chronic Illness Care (PACIC).

Methods: One thousand type 2 diabetes patients from 64 healthcare facilities throughout Bangkok were randomly selected, data about the extent they have received CCM-based services, their dietary, physical activity, medication-taking behaviors, body mass index (BMI), and blood sugar control status were collected by a set of structured questionnaires and medical record abstraction.

Results: PACIC and self-management scores for patients receiving care from public hospitals and health centers were significantly higher than those from private hospitals. Being the primary care unit (PCU)-where the CCM implementation has been enforced since 2008 was significantly associated with higher PACIC scores for public hospitals. This was not the case for private hospitals. PCU status was significantly associated with better selfmanagement scores for patients in both public and private hospitals. However, variations in PACIC and selfmanagement scores did not reflect to BMI or glycemic control outcomes of the patients.

Conclusion: There is encouraging evidence of progress of CCM implementation for type 2 diabetes patients in Bangkok, Thailand. This had also resulted in improved self-management, but not physiological or metabolic outcomes.