Multiple Trigger Points for Quantifying Heat-health Impacts: New Evidence From a Hot Climate

Diana B. Petitti; David M. Hondula; Shuo Yang; Sharon L. Harlan; Gerardo Chowell

Disclosures

Environ Health Perspect. 2016;124(2):176-183. 

In This Article

Results

During the time period for which both mortality and morbidity data were available, the number of morbidity events greatly exceeded the number of mortality events (Table 1). The average number of heat-related deaths per year for the months in the analysis from 2008 to 2011 (n = 35) was 10.1% of the average number of heat-related hospitalizations (n = 346), which in turn was 25.4% of the average number of heat-related ED visits (n = 1,361). For reference, in Maricopa County during the period 2008–2011, approximately 460,000 hospitalizations and 1.1 million ED visits (not admitted to the hospital) per year were recorded [Agency for Healthcare Research and Quality (AHRQ) 2014].

Across all temperature metrics, the relative risk of all-cause mortality at the highest recorded temperatures exceeded 1.05, with 95% confidence intervals that excluded 1.0 (Figure 1). All three trigger points (MRT, IRT, and ERT) were identified for all six temperature metrics. Regardless of the temperature metric examined, the ERT estimate for all-cause mortality was 2–3°C higher than the IRT, and the IRT estimate was 3–5°C higher than the MRT.

Figure 1.

The modeled relationship between the relative risk of all-cause mortality and six different same-day temperature metrics during the warm season for Maricopa County, Arizona, 2000–2011. The solid blue line shows the relative risk of mortality, and the shaded blue region shows the 95% confidence interval. Specific points labeled on the curve identify the minimum risk temperature (MRT, black), the increasing risk temperature (IRT, blue), and the excess risk temperature (ERT, red), representing different conceptualizations of trigger points for intervention activities as discussed in "Methods."

CVD mortality increased with temperature with a 1-day lag (Figure 2). Relative risks exceeded 1.05 with 95% confidence intervals that excluded 1.0 for some temperature metrics at the highest temperatures. CVD trigger points were less consistent than those for all-cause mortality: an ERT estimate could not be identified for Tmax, HImax, and HImin, and there was a large difference in IRT and MRT using Tmax (22 and 36°C, respectively). Where trigger points could be identified, the ERT was 2–3°C higher than the IRT, and, with the exception of Tmax, the IRT was 3–6°C higher than the MRT. The number of CVD deaths (n = 30,531) was substantially smaller than the number of deaths from all causes (n = 112,853), and the lack of consistency may be a consequence of random error due to the smaller sample size.

Figure 2.

The modeled relationship between the relative risk of cardiovascular mortality and six different temperature metrics with a 1-day lag, as in Figure 1. Fewer than three points are indicated on the curve if some of the trigger points could not be identified.

No clear pattern of increased risk with higher temperature (1-day lag) emerged for CVD hospitalization or ED visits with CVD listed as the first discharge diagnosis (see Supplemental Material, Figures S2 and S3 http://ehp.niehs.nih.gov/wp-content/uploads/124/2/ehp.1409119.s001.acco.pdf). Consequently, trigger points could not be identified for these health events for any temperature metric.

For the category of conditions called "consequences of heat and dehydration," the relationship with temperature was consistently positive for mortality, hospitalization, and ED visits (Figure 3; see also Supplemental Material, Figures S4 and S5 http://ehp.niehs.nih.gov/wp-content/uploads/124/2/ehp.1409119.s001.acco.pdf), but the confidence intervals were wide. The slope of the relationship was shallow. The MRTs and IRTs were much lower for this category of conditions than for all-cause mortality, CVD mortality, and heat-related conditions. For example, considering Tmax, the MRT and IRT were 25°C and 31°C, respectively, for mortality due to conditions considered consequences of heat and dehydration, whereas the MRT and IRT were 35°C and 39°C, respectively, for all-cause mortality.

Figure 3.

The modeled relationship between the relative risk of mortality from consequences of heat and dehydration and six different temperature metrics with a 1-day lag, as in Figure 1. Fewer than three points are indicated on the curve if some of the trigger points could not be identified.

We found strong and statistically significant associations between same-day temperature and the three directly heat-related health events (Figures 4 and 5). The relationship exhibited an exponential pattern across all temperature metrics and types of events. MRTs, IRTs, and ERTs were identified for all six temperature metrics for all types of heat-related events. Notably, for all of the temperature metrics, both the MRT and the IRT were consistently 2–7°C lower for heat-related hospitalization and heat-related ED visits than for heat-related mortality. For example, considering Tmax, the corresponding MRT was 26°C for mortality, but 22°C for hospitalization and 22°C for ED visits; similarly, the IRT was 33°C for mortality, but 27°C for hospitalization and 29°C for ED visits. For all of the temperature metrics, however, the ERT was almost the same (± 1–2°C) for each type of heat-related event. For example, considering HImax, the ERT was 39°C for heat-related death and 38°C for both hospitalization and ED visits.

Figure 4.

The modeled relationship between the relative risk of heat-related mortality (top panels), heat-related hospitalization (middle panels), and heat-related emergency department visits (lower panels), and three same-day temperature metrics (Tmax, Tmean, Tmin) during the warm season for Maricopa County, Arizona, 2000–2011 (2008–2012 for morbidity), as in Figure 1. For heat-related events, MRT is the temperature at which the fewest events were observed. Note that the vertical axis scale varies between panels.

Figure 5.

The modeled relationship between the relative risk of heat-related mortality (top panels), heat-related hospitalization (middle panels), and heat-related emergency department visits (lower panels), and three same-day heat index metrics (HImax, HImean, HImin), as in Figure 1. MRT is the temperature at which the fewest events were observed. Note that the vertical axis scale varies between panels.

The conceptualization of trigger point and choice of health event and diagnosis led to large contrasts in the temperatures at which estimated heat risk increased. Table 2 lists the MRT, IRT, and ERT for 8 of the 10 health events considered in order to facilitate comparisons across categories, event types, temperature metrics, and risk levels; comparisons for Tmax for select events are also illustrated in Figure 6. Cardiovascular morbidity events are excluded from these tables and figures because of the lack of a consistent association with any temperature metric. Spanning the entire range of risk temperatures, health events, and categories of mortality and morbidity, we observed that trigger points varied by as much as 22°C, holding the temperature metric constant. For example, the ERT for all-cause mortality (considering Tmax) was 42°C, but the MRT for heat-related mortality was 26°C. When examining contrasts across metrics within each type of health event, the MRT, IRT, and ERT were often within 2°C for the air temperature and HI forms of the metric. When the trigger points differed, in most cases, the HI trigger point was 1–2°C lower than the air temperature trigger point.

Figure 6.

Minimum, increasing, and excess risk temperatures (MRT, IRT, ERT) based on daily maximum temperature (Tmax) for four health events examined in this study. Values on the right-hand side of the figure denote climatological averages at regularly spaced intervals during the warm season in Maricopa County.

Sensitivity analyses revealed that the overall scale and pattern of the differences between trigger points based on different conceptualizations of thresholds was consistent regardless of the specific time period examined, although the specific values of the MRT, IRT, and ERT were not identical for all examined time periods (see Supplemental Material, Tables S4 and S5 http://ehp.niehs.nih.gov/wp-content/uploads/124/2/ehp.1409119.s001.acco.pdf).

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