title: High temperature effects on out-patient visits and hospital admissions in Chiang Mai, Thailand.
abstract: OBJECTIVE
  This study investigated the short-term effects of temperature on out-patient visits and hospital admissions in Chiang Mai, Thailand. While mortality outcomes in the literature have been reported, there is less evidence of morbidity effects with very few studies conducted in developing countries with subtropical or tropical climate.
  
  
  METHODS
  Time-series regression analysis was employed using generalized negative binomial regression to model the short-term relationships between temperature and morbidity after controlling for seasonal patterns and other potential confounders. Lag effects up to 13 days and effect modification by age (0-14 years, 15-64 years, ≥65 years) were examined.
  
  
  RESULTS
  Temperature effects with wide confidence intervals were found, with an increase in diabetic visits of 26.3% (95% CI: 7.1%-49.0%), and circulatory visits of 19.2% (95% CI: 7.0%-32.8%) per 1 °C increase in temperature above an identified threshold of 29 °C. Additionally, there was a rise of both visits (3.7% increase, 95% CI: 1.5%-5.9%) and admissions (5.8% increase, 95% CI: 2.3%-9.3%) due to intestinal infectious disease in association with each 1 °C increase across the whole temperature range. The effects of temperature were stronger in the elderly though not statistically significant.
  
  
  CONCLUSIONS
  Daily morbidity in Chiang Mai was positively associated with temperature with a lag effect of up to 2 weeks, which was longer than lag effects previously reported. Public health preparedness and interventions should be considered to minimise possible increased hospital visits and admissions during hot weather.
authors.affiliation: Sirindhorn College of Public Health Chonburi, 29 Vachiraprakarn Road, Muang District, Chonburi Province, 20000 Thailand. nareerutp@yahoo.com
authors.forename: Nareerut
authors.initials: N
authors.lastname: Pudpong
authors.forename: Shakoor
authors.initials: S
authors.lastname: Hajat
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000553:Ambulatory Care / Q000706:statistics & numerical data*; D016010:Binomial Distribution; D002318:Cardiovascular Diseases / Q000453:epidemiology; D002648:Child; D002947:Cities; D016001:Confidence Intervals; D003906:Developing Countries; D003920:Diabetes Mellitus / Q000453:epidemiology; D006358:Hot Temperature / Q000009:adverse effects*; D006801:Humans; D007411:Intestinal Diseases, Parasitic / Q000453:epidemiology; D008875:Middle Aged; D009017:Morbidity; D010343:Patient Admission / Q000706:statistics & numerical data*; D012044:Regression Analysis; D012140:Respiratory Tract Diseases / Q000453:epidemiology; D012621:Seasons; D013785:Thailand / Q000453:epidemiology; D013997:Time Factors; D014505:Urban Population / Q000706:statistics & numerical data; D055815:Young Adult