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Survey of county-level heat preparedness and response to the 2011 summer heat in 30 U.S. States.

White-Newsome JL, Ekwurzel B, Baer-Schultz M, Ebi KL, O'Neill MS, Anderson GB - Environ. Health Perspect. (2014)

Bottom Line: Previous research reveals that very few communities in the United States have programs to sufficiently prevent health problems during hot weather.County-level responses were pooled into national and regional-level summaries.Of 586 counties, 190 (32%) responded to the survey.

View Article: PubMed Central - PubMed

Affiliation: Union of Concerned Scientists, Washington, DC, USA.

ABSTRACT

Background: Adapting to extreme heat is becoming more critical as our climate changes. Previous research reveals that very few communities in the United States have programs to sufficiently prevent health problems during hot weather.

Objective: Our goal was to examine county-level local heat preparedness and response in 30 U.S. states following the unusually hot summer of 2011.

Methods: Using a multimodal survey approach, we invited local health and emergency response departments from 586 counties to participate in the largest survey to date of heat preparedness and response in the United States. County-level responses were pooled into national and regional-level summaries. Logistic regressions modeled associations between heat planning/response and county characteristics, including population, poverty rates, typical summer weather, and 2011 summer weather.

Results: Of 586 counties, 190 (32%) responded to the survey. Only 40% of these counties had existing heat plans. The most common heat responses were communication about heat, outreach, and collaborations with other organizations. Both heat preparedness and heat response were, on average, more extensive in counties with higher populations, lower poverty rates, and lower percentages of older people. Heat response was generally more extensive in counties with heat plans.

Conclusions: Most responding counties were underprepared for extreme heat in 2011 and lacked a formal response plan. Because counties with heat plans were more likely to act to prevent adverse heat impacts to residents, local health departments should consider adopting such plans, especially because increased extreme heat is anticipated with further climate change.

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County characteristics: distributions and associations with heat preparedness in 2011 (n = 185). (A) Distributions of county population, July climate (average of daily July maximum temperature values, 2001–2010), percent poverty, and percent of population ≥ 65 years. (B) Percent of counties with heat plans in 2011 in each quantile bin for county characteristics. All counties were divided into five bins based on the county characteristics, with breaks between bins at the 20th, 40th, 60th, and 80th percentiles of the characteristic; black vertical lines show divisions between bins as well as minimum and maximum values; points are positioned on the x-axis at the median characteristic value for the counties within the bin.
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f2: County characteristics: distributions and associations with heat preparedness in 2011 (n = 185). (A) Distributions of county population, July climate (average of daily July maximum temperature values, 2001–2010), percent poverty, and percent of population ≥ 65 years. (B) Percent of counties with heat plans in 2011 in each quantile bin for county characteristics. All counties were divided into five bins based on the county characteristics, with breaks between bins at the 20th, 40th, 60th, and 80th percentiles of the characteristic; black vertical lines show divisions between bins as well as minimum and maximum values; points are positioned on the x-axis at the median characteristic value for the counties within the bin.

Mentions: Heat plans were more likely in more populous counties (Table 2, Figure 2). Based on a logistic regression of heat plan status on county population (n = 185), 34% of counties with populations of 22,000 (25th percentile across all county populations) were expected to have heat plans, versus 48% of counties with populations of 161,000 (75th percentile across all county populations) (Table 2). The OR for having a heat plan for an IQR increase in county population was 1.83 (95% CI: 1.23, 2.72) (Table 2). However, analysis of OR and temperature quantiles suggests the relationship between heat plan status and average July temperature may be nonlinear and not statistically significant, as counties with hottest July temperatures did not have the highest prevalence of heat plans (Table 2, Figure 2). Heat plan status was inversely associated with the percentage of the population ≥ 65 years of age (OR for an IQR increase in percent of population ≥ 65 years of age: 0.76; 95% CI: 0.52, 1.12) and with county poverty rates (OR for an IQR increase in poverty status: 0.79; 95% CI: 0.55, 1.14), although again neither estimate was statistically significant (Table 2).


Survey of county-level heat preparedness and response to the 2011 summer heat in 30 U.S. States.

White-Newsome JL, Ekwurzel B, Baer-Schultz M, Ebi KL, O'Neill MS, Anderson GB - Environ. Health Perspect. (2014)

County characteristics: distributions and associations with heat preparedness in 2011 (n = 185). (A) Distributions of county population, July climate (average of daily July maximum temperature values, 2001–2010), percent poverty, and percent of population ≥ 65 years. (B) Percent of counties with heat plans in 2011 in each quantile bin for county characteristics. All counties were divided into five bins based on the county characteristics, with breaks between bins at the 20th, 40th, 60th, and 80th percentiles of the characteristic; black vertical lines show divisions between bins as well as minimum and maximum values; points are positioned on the x-axis at the median characteristic value for the counties within the bin.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4048256&req=5

f2: County characteristics: distributions and associations with heat preparedness in 2011 (n = 185). (A) Distributions of county population, July climate (average of daily July maximum temperature values, 2001–2010), percent poverty, and percent of population ≥ 65 years. (B) Percent of counties with heat plans in 2011 in each quantile bin for county characteristics. All counties were divided into five bins based on the county characteristics, with breaks between bins at the 20th, 40th, 60th, and 80th percentiles of the characteristic; black vertical lines show divisions between bins as well as minimum and maximum values; points are positioned on the x-axis at the median characteristic value for the counties within the bin.
Mentions: Heat plans were more likely in more populous counties (Table 2, Figure 2). Based on a logistic regression of heat plan status on county population (n = 185), 34% of counties with populations of 22,000 (25th percentile across all county populations) were expected to have heat plans, versus 48% of counties with populations of 161,000 (75th percentile across all county populations) (Table 2). The OR for having a heat plan for an IQR increase in county population was 1.83 (95% CI: 1.23, 2.72) (Table 2). However, analysis of OR and temperature quantiles suggests the relationship between heat plan status and average July temperature may be nonlinear and not statistically significant, as counties with hottest July temperatures did not have the highest prevalence of heat plans (Table 2, Figure 2). Heat plan status was inversely associated with the percentage of the population ≥ 65 years of age (OR for an IQR increase in percent of population ≥ 65 years of age: 0.76; 95% CI: 0.52, 1.12) and with county poverty rates (OR for an IQR increase in poverty status: 0.79; 95% CI: 0.55, 1.14), although again neither estimate was statistically significant (Table 2).

Bottom Line: Previous research reveals that very few communities in the United States have programs to sufficiently prevent health problems during hot weather.County-level responses were pooled into national and regional-level summaries.Of 586 counties, 190 (32%) responded to the survey.

View Article: PubMed Central - PubMed

Affiliation: Union of Concerned Scientists, Washington, DC, USA.

ABSTRACT

Background: Adapting to extreme heat is becoming more critical as our climate changes. Previous research reveals that very few communities in the United States have programs to sufficiently prevent health problems during hot weather.

Objective: Our goal was to examine county-level local heat preparedness and response in 30 U.S. states following the unusually hot summer of 2011.

Methods: Using a multimodal survey approach, we invited local health and emergency response departments from 586 counties to participate in the largest survey to date of heat preparedness and response in the United States. County-level responses were pooled into national and regional-level summaries. Logistic regressions modeled associations between heat planning/response and county characteristics, including population, poverty rates, typical summer weather, and 2011 summer weather.

Results: Of 586 counties, 190 (32%) responded to the survey. Only 40% of these counties had existing heat plans. The most common heat responses were communication about heat, outreach, and collaborations with other organizations. Both heat preparedness and heat response were, on average, more extensive in counties with higher populations, lower poverty rates, and lower percentages of older people. Heat response was generally more extensive in counties with heat plans.

Conclusions: Most responding counties were underprepared for extreme heat in 2011 and lacked a formal response plan. Because counties with heat plans were more likely to act to prevent adverse heat impacts to residents, local health departments should consider adopting such plans, especially because increased extreme heat is anticipated with further climate change.

Show MeSH
Related in: MedlinePlus