J Korean Med Sci.  2017 Jun;32(6):999-1008. 10.3346/jkms.2017.32.6.999.

Daily Mean Temperature and Urolithiasis Presentation in Six Cities in Korea: Time-Series Analysis

• Chi BH
• Chang IH
• Choi SY
• Suh DC
• Chang CW
• Choi YJ
• Lee SY

• KMID: 2377731
• DOI: http://doi.org/10.3346/jkms.2017.32.6.999

Abstract

Seasonal variation in urinary stone presentation is well described in the literature. However, previous studies have some limitations. To explore overall cumulative exposure-response and the heterogeneity in the relationships between daily meteorological factors and urolithiasis incidence in 6 major Korean cities, we analyzed data on 687,833 urolithiasis patients from 2009 to 2013 for 6 large cities in Korea: Seoul, Incheon, Daejeon, Gwangju, Daegu, and Busan. Using a time-series design and distributing lag nonlinear methods, we estimated the relative risk (RR) of mean daily urolithiasis incidence (MDUI) associated with mean daily meteorological factors, including the cumulative RR for a 20-day period. The estimated location-specific associations were then pooled using multivariate meta-regression models. A positive association was confirmed between MDUI and mean daily temperature (MDT), and a negative association was shown between MDUI and mean daily relative humidity (MDRH) in all cities. The lag effect was within 5 days. The multivariate Cochran Q test for heterogeneity at MDT was 12.35 (P = 0.136), and the related I2 statistic accounted for 35.2% of the variability. Additionally, the Cochran Q test for heterogeneity and I2 statistic at MDHR were 26.73 (P value = 0.148) and 24.7% of variability in the total group. Association was confirmed between daily temperature, relative humidity and urolithiasis incidence, and the differences in urolithiasis incidence might have been partially attributable to the different frequencies and the ranges in temperature and humidity between cities in Korea.

Keyword

Urolithiasis; Temperature; Humidity; Time-Series Analysis

MeSH Terms

Busan
Daegu
Gwangju
Humans
Humidity
Incheon
Incidence
Korea*
Meteorological Concepts
Population Characteristics
Seasons
Seoul
Urinary Calculi
Urolithiasis*

Figure

• 

  Fig. 1 Geographic distribution of the 6 Korean cities and the corresponding MDUI values. (A) Map of Korea corresponding to the cities included in the analysis. (B) The distribution of MDUI from 2009 to 2013. MDUI = mean daily urolithiasis incidence.

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  Fig. 2 The effects of temperature and humidity for daily urolithiasis incidence. (A) Temperature-urolithiasis incidence association in Daegu 2009–2013. Top-left: 3-D graph with black reference line at 13°C. Top-right: predictor-specific at 30°C (red line parallel to the reference in the 3-D graph). Bottom-left: lag-specific summary at lag 3 (red line perpendicular to the reference in the 3-D graph). Bottom-right: overall cumulative summary. The 95% CIs are reported as gray areas. (B) Relative humidity-urolithiasis incidence association in Seoul 2009–2013. Top-left: 3-D graph with black reference line at 60%. Top-right: predictor-specific at 90% (red line parallel to the reference in the 3-D graph). Bottom-left: lag-specific summary at lag 3 (red line perpendicular to the reference in the 3-D graph). Bottom-right: overall cumulative summary. The 95% CIs are reported as gray areas. CI = confidential interval.

• 

  Fig. 3 The cumulative effects of temperature and humidity for daily urolithiasis incidence. (A) Overall RR of urolithiasis cumulative over a 20-day lag period with MDT (°C) relative to 13°C in the 6 cities from 2009 to 2013. The estimated RRs of urolithiasis associated with MDT accumulated over a 20-day lag period using DLNMs are shown for each city. The solid red line is the point estimate at each temperature, and the surrounding gray area is the 95% CI. (B) Overall RR of urolithiasis cumulative over a 20-day lag period with mean relative humidity (%) relative to 60% in the 6 cities from 2009 to 2013. The estimated RRs of urolithiasis associated with mean relative humidity accumulated over a 20-day lag period using DLNMs are shown for each city. The solid red line is the point estimate at each temperature, and the surrounding gray area is the 95% CI. RR = relative risk, MDT = mean daily temperature, DLNMs = distributed lag nonlinear models, CI = confidential interval.

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  Fig. 4 Multivariate meta-regression model to estimate the exposure-response relationships in RR between temperature and relative humidity and the daily urolithiasis incidence in 6 Korean cities, 2009–2013. Residual heterogeneity was tested and then quantified by the multivariate extension of the Cochran Q test and I2 statistics at total (A), male (B), female (C), less than 40 years old (D), 40–60 years old (E), and more than 60 years old (F). The continuous bold red line represents the population-average curve, whereas the long-dashed grey lines are the study-specific estimates. Reference at 13°C (right), 60% (left). RR = relative risk, CI = confidential interval, AIC = Akaike information criterion, BIC = Bayesian information criterion.

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