Export 3 results:
Sort by: Author Title Type [ Year  (Desc)]
Vashishtha, D, Sieber W, Hailey B, Guirguis K, Gershunov A, Al-Delaimy WK.  2018.  Outpatient clinic visits during heat waves: findings from a large family medicine clinical database. Family Practice. 35:567-570.   10.1093/fampra/cmy013   AbstractWebsite

Introduction. The purpose of this study was to determine whether heat waves are associated with increased frequency of clinic visits for ICD-9 codes of illnesses traditionally associated with heat waves. Methods. During 4 years of family medicine clinic data between 2012 and 2016, we identified six heat wave events in San Diego County. For each heat wave event, we selected a control period in the same season that was twice as long. Scheduling a visit on a heat wave day (versus a non-heat wave day) was the primary predictor, and receiving a primary ICD-9 disease code related to heat waves was the outcome. Analyses were adjusted for age, gender, race/ethnicity and marital status. Results. Of the 5448 visits across the heat wave and control periods, 6.4% of visits (n = 346) were for heat wave-related diagnoses. Scheduling a visit on heat wave day was not associated with receiving a heat wave-related ICD code as compared with the control period (adjusted odds ratio: 1.35; 95% confidence interval: 0.86-1.36; P = 0.51). Discussion. We show that in a relatively large and demographically diverse population, patients who schedule appointments during heat waves are not being more frequently seen for diagnoses typically associated with heat waves in the acute setting. Given that heat waves are increasing in frequency due to climate change, there is an opportunity to increase utilization of primary care clinics during heat waves.

Sherbakov, T, Malig B, Guirguis K, Gershunov A, Basu R.  2018.  Ambient temperature and added heat wave effects on hospitalizations in California from 1999 to 2009. Environmental Research. 160:83-90.   10.1016/j.envres.2017.08.052   AbstractWebsite

Investigators have examined how heat waves or incremental changes in temperature affect health outcomes, but few have examined both simultaneously. We utilized distributed lag nonlinear models (DLNM) to explore temperature associations and evaluate possible added heat wave effects on hospitalizations in 16 climate zones throughout California from May through October 1999-2009. We define heat waves as a period when daily mean temperatures were above the zone- and month-specific 95th percentile for at least two consecutive days. DLNMs were used to estimate climate zone-specific non-linear temperature and heat wave effects, which were then combined using random effects meta-analysis to produce an overall estimate for each. With higher temperatures, admissions for acute renal failure, appendicitis, dehydration, ischemic stroke, mental health, noninfectious enteritis, and primary diabetes were significantly increased, with added effects from heat waves observed for acute renal failure and dehydration. Higher temperatures also predicted statistically significant decreases in hypertension admissions, respiratory admissions, and respiratory diseases with secondary diagnoses of diabetes, though heat waves independently predicted an added increase in risk for both respiratory types. Our findings provide evidence that both heat wave and temperature exposures can exert effects independently.

Semenza, JC, Caplan JS, Buescher G, Das T, Brinks MV, Gershunov A.  2012.  Climate change and microbiological water quality at California beaches. Ecohealth. 9:293-297.   10.1007/s10393-012-0779-1   AbstractWebsite

Daily microbiological water quality and precipitation data spanning 6 years were collected from monitoring stations at southern California beaches. Daily precipitation projected for the twenty-first century was derived from downscaled CNRM CM3 global climate model. A time series model of Enterococcus concentrations that was driven by precipitation, matched the general trend of empirical water quality data; there was a positive association between precipitation and microbiological water contamination (P < 0.001). Future projections of precipitation result in a decrease in predicted Enterococcus levels through the majority of the twenty-first century. Nevertheless, variability of storminess due to climate change calls for innovative adaptation and surveillance strategies.