Background
Methods
-
Impacts measured as reduction in excess heat stroke incidence, hospitalization for heat-related illness, and cases of cardiovascular, respiratory and all-cause mortality in extreme heat periods as compared to previous heat periods.
-
Effectiveness measured
Search strategy
Selection criteria
Inclusion
Exclusion
Study quality assessment
Study synthesis
Results
Study characteristics
Heat adaptation
Reference
|
Type of evaluation
|
Results
|
---|---|---|
Rogot et al. 1992 [65] | Comparing mortality during heat in people with air conditioned homes to those with no air conditioning | Central air condition compared to no air condition: OR below 1 for all groups, significant (p = 0.03 Mantel-Haenszel). Room air condition compared to no air condition: OR 0.96 for total group, p = 0.71). RR for central air condition vs. no air condition 0.58 for total group, RR for room air condition to no air condition 0.41 for total group |
Smoyer 1998 [67] | Comparing mortality rates of 1980 and 1995 | The average elderly mortality rate on heat wave days went down from 2.36 (SD 1.20) to 1.65 (SD 0.52), the average elderly mortality rate on non- heat days went down from 1.56 (SD 0.45) to 1.46 (SD 0.55) |
Palecki et al. 2001 [64] | Comparing excess deaths in 1995 and 1999 |
Mortality rates in Chicago and St Louis both 1.4 per 100.000 in 1999, if not using core cities but counties. In 1995, 700 died in Chicago and 27 in St Louis |
Weisskopf et al. 2002 [68] | Changes in population vulnerability | Model 1: predicted mortality rate of 1.80 per heat-index degree above 80 °F. 42.3 expected deaths, actual deaths in 1999 were 10. Model 2: RR for heat-related death in 1999: 0.17-0.24, RR for emergency medical services in 1999 0.32-0.46
|
Davis et al. 2003 [60] | Comparing temperature mortality relationship from 1964 to 1998 | The threshold for 1960s-1970s is no longer connected to an increased mortality in the 1980s in Northeastern cities, and in the 1990s 10 show no elevated mortality above threshold and of the remaining 18 cities 12 show a decline in mortality rate. Six cities remain with an increased mortality rate above the threshold: Atlanta, Buffalo, Dallas, Denver, Seattle, San Francisco |
Delaroziere and Sanmarco 2004 [52] | Comparing mortality before and after implementation of warning system | Mean index of daily excess mortality has dropped from 3.27 in the years 1986 to 1982, down to 1.32 in the years 1984–1997, p = 0.008) |
Marinacci et al. 2009 [57] | Comparing no. of hospitalizations and deaths in summer 2004, RCT | Males: in intervention group Odds to be emergency hospitalized: OR 0.33, 95% CI: 0.11; 0.96. Females: in intervention group odds to be hospitalized overall: OR 0.96, 95% CI: 0.93; 0.98
|
Tan et al. 2007 [70] | Comparing daily excess mortality in 1998 and 2003. |
Correlation coefficient between daily deaths and weather and air pollution parameters: death and time of heat wave: 0.34 in 1998 and 0.41 in 2003, Tmax in 1998 0.51 to 0.62 in 2003. Heat related deaths in 1998: 358 (absolutes), 253 in 2003 (absolutes) |
De’Donato et al. 2008 [51] | Daily excess mortality before (reference period) and after implementation of heat warning system | J-shape temperature-mortality curve in all cities. In Milan and Rome in 2007 there was a weaker association between high temps and mortality. In Bari and Catania there was a greater impact of high temp on mortality in 2007 (all compared to 2003). In 2007 excess mortality occurred during three heat waves, with impacts on mortality of +10-41% in the center and 11-56% in the South
|
Fouillet et al. 2008 [53] | Comparing excess daily mortality in 2003 to 2006 | During summers 2004 and 2005, observed no. of deaths was 2-8% lower than predicted no. of deaths. In 2006 2065 excess deaths occurred, predicted for that temperature were 6452 excess deaths, 4400 fewer deaths than predicted
|
Kysely and Kriz 2008 [55] | Comparing excess mortality in the 1990s and 2003 | Excess daily mortality in 1990s: 98 deaths in 1992, 113 deaths in 1994; 50 deaths in 2003. Aggregated: 1992 718 excess deaths, in 1994 919 excess deaths, in 2003 236 excess deaths
|
Bargagli et al. 2009 [49] | Mortality rate among patients with active surveillance and those without = comparison of mortality rate with and without intervention |
Excess mortality on heat days vs. non-heat days in controls: RR 1.20, 95% CI: 1.14-1.27; excess mortality on heat days vs. non-heat days in intervention patients: RR 0.95, 95% CI: 0.65-1.34
|
Chau et al. 2009 [69] | Comparing associations between hot weather warning and mortality rates from ischemic heart disease and stroke from 1997 to 2005. | Absence of warning system was associated with an increase of 1.23 deaths from IHD (95% CI 0.32; 2.14), an increase of 0.97 deaths from stroke (95% CI: 0.02; 1.92) per day |
Ostro et al. 2010 [63] | Comparing hospitalization among those with air conditioning to those without | Reduction in excess risk of hospitalization with 10% increase in A/C ownership: respiratory disease: relative reduction 19.9% (95% CI 0.7;39.), CVD relative reduction: 49.1% (95% CI 19.9;78.3), heat stroke relative reduction 4.0% (95% CI 1.9;6.0)
|
Kysely and Plavcova 2012 [78] | Comparing temperature mortality relationship from 1986 to 2009 | Significant trends in deviation of mortality on lag days from 1986 to 2009: all ages D + 1 -0.61, D + 2 -0.55; 70- years: D + 1 -0.66; 70+ years: D + 2 -0.66. Relative deviations of mortality declined by 0.4% to 0.5% in all age groups until 2009. Overall decline of mortality by 10% for all groups
|
Morabito et al. 2012 [58] | Comparing mortality before and after implementation of warning system | Odds Ratios for mortality by age group pre- and post-2003: only significant in 75 years+, OR for average apparent temperature before 2003 1.18 (CI 1.10-1.26), 2004 to 2005: 1.24 (CI 1.14-1.35), 2006–2007: 1.20 (CI 1.09-1.31). Also significant for maximum temperature |
Schifano et al. 2012 [59] | Comparing daily mortality in 1998–2002 (before) and from 2006 to 2010 (after) implementation of prevention program |
Weaker relationships between heat and mortality in all 16 cities post-intervention. Percentage change in mortality per 3°C increase in max apparent temperature MAT (pooled results): for 0 to 3% increase of 3°C increase: 1998–2002: 5.65%, for 2006 to 2010: 5.65%; 3 to 6% MAT increase: in 1998–2002 6.72% change, in 2006 to 2010: 7.79% change. Largest results: 12 to 15% MAT increase, 41.76% change from 1998–2002; 5.65% change from 2006 to 2010
|
Reference
|
Type of evaluation
|
Methods
|
Results
|
---|---|---|---|
Mattern et al. 2000 [62] | Case-only survey | Standardized questionnaire | 34 respondents. At pretest 67% of respondents knew whom to contact during heat for assistance, post-intervention 94% knew whom to contact. 6% knew about the City of Philadelphia hotline at pretest, 29% at post-test. 76% monitored temperature daily, 21% monitored temperature during hot days |
Ebi et al. 2004 [61] | Economic cost-effectiveness evaluation | Multiple linear regression, estimation of lives saved, estimation of benefits |
2.6 lives saved on average for each warning day plus three day lag (not significant). Estimated value of $6.12mill. per life = $468 mill. saved with 117 lives saved over 3 years. Costs for system $210.000 |
Kishonti et al. 2006 [54] | State of knowledge on heat, the warning system, protective behavior | Quantitative telephone survey | Sample size 2500. Awareness of heat: persons between 30 and 59 years of age mentioned at least two health impacts of heat. 27% of respondents saw hypertension as risk, 11% heat stroke, 22% CVD. 25% of interviewees had seen the communication campaign, of whom 78% saw it on TV, 57% in the newspaper and 41% on the street. 59% of respondents had heard of heat alarm
|
Bouchama et al. 2007 [74] | Systematic review and meta-analysis on risk and protective factors for heat-related deaths | Systematic review and meta-analysis | Protective factors: home air condition (OR 0.23 95% CI 0.1-0.6), visiting cool environments (OR 0.34 95% CI 0.2-0.5), increased social contact (OR 0.40 95% CI 0.2-0.8), taking extra showers (OR 0.32, 95% CI 01.-1.1), use of fans (OR 0.60 95% CI 0.4-1.1)
|
Kalkstein and Sheridan 2007 [34] | State of knowledge on heat, the warning system, protective behavior | Quantitative survey | 201 respondents, 14 of age 65+. 90.2% of females knew about the heat warning system, 75.3% of males knew about the system. 25% felt heat was dangerous. Of those aware of heat warnings, 49.7% altered behavior, 47.3% did not |
Sheridan 2007 [66] | State of knowledge on heat, protective behavior, available cooling systems in the house | Quantitative telephone survey | 908 respondents across all cities. In the four cities, most people learned about heat warnings on television (Dayton: 89%, Philadelphia: 84%, Phoenix: 92%, Toronto: 64%). 46% of respondents altered their behavior during heat, varying significantly across cities (p = 0.003). Use of air conditioning self-restricted due to concerns about costs |
Abrahamson et al. 2009 [35] | State of knowledge on heat-related health risks and protective behavior | Semi-structured interviews with topic guide, 1 data collection wave summer of 2007 | 73 respondents, mean age 81 years (range 72–90) in London; mean age 80 (range 75 to 94) in Norwich. Themes identified: perception of vulnerability to heat; behavior change during heat; knowledge of protection measures; perception of usefulness of heat wave plan. No consensus on usefulness of heat wave plan components. Most respondents adjust their behavior during heat. Few respondents perceived of themselves at risk |
Kosatsky et al. 2009 [71] | State of knowledge on heat, protective behavior | Quantitative, questionnaire based face-to-face interviews | 238 respondents. 86% know about risks of high night time temperature, 94% know about health risks for lung and heart disease patients. 80% listen to weather forecasts, mid-summer 93% had heard a heat advisory. 71% use a fan, 87% do less strenuous activities in heat. 73% have air condition at home, those with air condition reported more additional behavior changes than those without |
Bassil and Cole 2010 [73] | Systematic review of all study types | Systematic review and expert elicitation | Narrative results: most studies evaluate heat warning systems, awareness and perception. If effects measured then often as regression analysis. Methodological challenges |
Oakman et al. 2010 [72] | State of knowledge on heat, heat warnings, protective behavior | Quantitative telephone survey | 328 interviews, 63% knew of health warnings: of these 74% saw it on TV, 42% on radio, 15% in newspapers. 96.1% of respondents used air condition in hot weather, 94% drank water, 90% stayed indoors |
Bittner and Stößel 2012 [50] | State of knowledge on heat, protective behavior, heat warnings | Questionnaire-based interviews, qualitative analysis with framework approach | 20 respondents. Themes: vulnerability, changes in daily routine, sources of information, content of advice received, activity level and health status. Individual vulnerability not always perceived. Controversial role of the GP. 19 respondents stated they changed behavior |
Gupta et al. 2012 [75] | Systematic review of RCTs, and experimental designs with controls | Systematic review according to Cochrane guidelines |
No studies with rigorous experimental designs found
|
Toloo et al. 2013 [44] | Systematic review of any heat warning evaluation | Systematic review of databases | Six articles asserted that post-intervention expected deaths were reduced. High study heterogeneity. One economic assessment. Eight studies assessed awareness, including one qualitative study |
Quality appraisal
Subgroup analysis: articles comparing mortality and morbidity
Subgroup analysis: perception and behavior change studies
Discussion
-
Differing heat wave impacts due to unstable intensity and frequency [76].
-
Role of confounders such as socio-economic variables and long-term healthcare improvements [76].
-
Short time frame between implementation of heat prevention and evaluation [73].
-
Location-specific acclimatization [73].
-
Simultaneous implementation of sub-interventions in a heat prevention plan [73].
-
Data availability [76].
-
Although older persons are generally included as a vulnerable group, age ranges differ and impede comparability.
-
Lack of pre-tests in awareness studies. Participants’ knowledge of heat warning systems or healthy behaviors cannot clearly be attributed to the adaptation.
-
Most of the observational studies did not examine alternative hypotheses for changes. Often authors mentioned a variety of reasons for changes, all of them with equal or unknown likeliness.