A quantile regression analysis of ambulance response time.

BACKGROUND: Shorter ambulance response time (ART) contributes to improved clinical outcomes. Various methods have been used to analyze ART. OBJECTIVES: We aimed to compare the use of quantile regression with the standard ordinary least squares (OLS) model for identifying factors associated with ART in Singapore. A secondary aim was to determine the relative importance of patient-level (e.g., gender and ethnicity) versus system-level (e.g., call volumes within the last one hour) factors contributing to longer ART. METHODS: We conducted a retrospective review of data electronically captured from ambulance dispatch records and patient case notes of emergency calls to the national ambulance service from January to May 2006 (n = 30,687). The primary outcome was ART, defined as the time taken for an ambulance to arrive at the scene upon receiving an emergency call, and modeled as a function of patient- and system-level factors. We used a quantile regression model to account for potential heterogeneous effects of explanatory variables on ART across different quantiles of the ART distribution, and compared estimates derived with the corresponding OLS estimates. RESULTS: Quantile regression estimates suggested that the call volume in the previous one hour predicted increased ART, with the effect being more pronounced in higher ART quantiles. At the 90th and 50th percentiles of ART, each additional call in the last one hour was predicted to increase ART to the next call from the same area by 93 and 57 seconds, respectively. The corresponding OLS estimate was 58 seconds. Patient factors had little effect on ART. CONCLUSION: The quantile regression model is more useful than the OLS model for estimating ART, revealing that in Singapore, ART is influenced heterogeneously by the volume of emergency calls in the past one hour.

The associations between self-reported sleep duration and adolescent health outcomes: what is the role of time spent on Internet use?

OBJECTIVE: This study aimed to examine the associations of self-reported sleep duration with adolescent health outcomes, taking into account time spent on Internet use. METHODS: We used data from the 2008-2009 Korea Youth Behavioral Risk Factor Survey, a cross-sectional online survey of middle and high school students aged 13-18years in South Korea (N=136,589) to examine the associations of self-reported sleep duration with four mental and physical health measures, e.g. self-report of depressive symptoms, suicidal ideation, weight status, and self-rated health. The binary logit and generalized ordered logit models controlled for time spent on Internet use for non-study purposes and other factors. RESULTS: Shorter self-reported sleep duration was associated with a higher likelihood of reporting depressive symptoms, suicidal ideation, and overweight or obese status, and a lower likelihood of reporting better self-rated health, even after accounting for time spent on Internet use. Excessive Internet use was found to be an independent risk factor for these outcomes. CONCLUSIONS: Among in-school adolescents in South Korea, shorter sleep duration and excessive Internet use are independently and additively associated with multiple indicators of adverse health status. Excessive Internet use may have not only direct adverse health consequences, but also have indirect negative effects through sleep deprivation.