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Space-Time Covariation of Mortality with Temperature: A Systematic Study of Deaths in France, 1968-2009.

Todd N, Valleron AJ - Environ. Health Perspect. (2015)

Bottom Line: The temperature-mortality relationship has repeatedly been found, mostly in large cities, to be U/J-shaped, with higher minimum mortality temperature (MMT) at low latitudes being interpreted as indicating human adaptation to climate.The RM25/18 ratio of mortality at 25°C versus that at 18°C declined significantly (p = 5 × 10-5) as warming increased: 18% for P1, 16% for P2, and 15% for P3.Results of this spatiotemporal analysis indicated some human adaptation to climate change, even in rural areas.

View Article: PubMed Central - PubMed

Affiliation: U1169, INSERM (Institut national de la santé et de la recherche médicale), Le Kremlin-Bicêtre, France.

ABSTRACT

Background: The temperature-mortality relationship has repeatedly been found, mostly in large cities, to be U/J-shaped, with higher minimum mortality temperature (MMT) at low latitudes being interpreted as indicating human adaptation to climate.

Objectives: Our aim was to partition space with a high-resolution grid to assess the temperature-mortality relationship in a territory with wide climate diversity, over a period with notable climate warming.

Methods: The 16,487,668 death certificates of persons > 65 years of age who died of natural causes in continental France (1968-2009) were analyzed. A 30-km × 30-km grid was placed over the map of France. Generalized additive model regression was used to assess the temperature-mortality relationship for each grid square, and extract the MMT and the RM25 and RM25/18 (respectively, the ratios of mortality at 25°C/MMT and 25°C/18°C). Three periods were considered: 1968-1981 (P1), 1982-1995 (P2), and 1996-2009 (P3).

Results: All temperature-mortality curves computed over the 42-year period were U/J-shaped. MMT and mean summer temperature were strongly correlated. Mean MMT increased from 17.5°C for P1 to 17.8°C for P2 and to 18.2°C for P3 and paralleled the summer temperature increase observed between P1 and P3. The temporal MMT rise was below that expected from the geographic analysis. The RM25/18 ratio of mortality at 25°C versus that at 18°C declined significantly (p = 5 × 10-5) as warming increased: 18% for P1, 16% for P2, and 15% for P3.

Conclusions: Results of this spatiotemporal analysis indicated some human adaptation to climate change, even in rural areas.

No MeSH data available.


Related in: MedlinePlus

(A) Grid placed over continental France to obtain the squares used in the analysis. The pixel color indicates the population density in 2008 (red: highest; pale yellow: lowest). The temperature–mortality analysis (shown in (B) for a particular square in the western part of France) was done for each of the squares with > 1.5 deaths/day during each of the studied periods, corresponding to 22,500 deaths in the total analysis (228 squares), and to 7,500 deaths/period for the by-period analyses (224 squares). For each grid square, a GAM was used to model the temperature–mortality relationship and extract the corresponding curve and three parameters: the minimum mortality temperature (MMT) and the relative risk of mortality expressed as the ratios of mortality observed at 25°C to that observed at MMT (RM25) or that observed at 18°C (RM25/18). This map is interactive at http://www.isis-diab.org/isispub/ehp/interactive_map_wp.htm. (B) Clicking on any square of the map shows vital information on the square (top), the smooth function of time [s(t) (defined in Equation 1) bottom right], and the variation with temperature of the relative risk of total mortality for individuals > 65 years old [the reference risk was the mortality observed at the MMT of each square: here (bottom left) is thus plotted s1(T)/s1(MMT)]. One example is shown here: The detailed information pertaining to the 1968–2009 period for all squares of the grid is obtained on the interactive map where the temperature–mortality curves can be viewed for the all the study periods [Pall (1968-2009), P1 (1968–1981), P2 (1982–1995), and P3 (1996–2009)].
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f1: (A) Grid placed over continental France to obtain the squares used in the analysis. The pixel color indicates the population density in 2008 (red: highest; pale yellow: lowest). The temperature–mortality analysis (shown in (B) for a particular square in the western part of France) was done for each of the squares with > 1.5 deaths/day during each of the studied periods, corresponding to 22,500 deaths in the total analysis (228 squares), and to 7,500 deaths/period for the by-period analyses (224 squares). For each grid square, a GAM was used to model the temperature–mortality relationship and extract the corresponding curve and three parameters: the minimum mortality temperature (MMT) and the relative risk of mortality expressed as the ratios of mortality observed at 25°C to that observed at MMT (RM25) or that observed at 18°C (RM25/18). This map is interactive at http://www.isis-diab.org/isispub/ehp/interactive_map_wp.htm. (B) Clicking on any square of the map shows vital information on the square (top), the smooth function of time [s(t) (defined in Equation 1) bottom right], and the variation with temperature of the relative risk of total mortality for individuals > 65 years old [the reference risk was the mortality observed at the MMT of each square: here (bottom left) is thus plotted s1(T)/s1(MMT)]. One example is shown here: The detailed information pertaining to the 1968–2009 period for all squares of the grid is obtained on the interactive map where the temperature–mortality curves can be viewed for the all the study periods [Pall (1968-2009), P1 (1968–1981), P2 (1982–1995), and P3 (1996–2009)].

Mentions: Discretization of space. The temperature–mortality relationship was studied within each 0.50°-latitude × 0.50°-longitude “square” (approximately 30 km × 30 km) of a grid placed over the map of continental France. This grid was built by aggregating four 0.25°-latitude × 0.25°-longitude squares of the E-OBS data set, starting at 40.625° latitude and –5.625° longitude and ending at 10.625° latitude and 51.875° longitude, yielding 295 squares (Figure 1), for which the daily mean temperatures, precipitations, and average sea-level pressures were obtained by averaging the four 0.25°-latitude × 0.25°-longitude E-OBS database source values.


Space-Time Covariation of Mortality with Temperature: A Systematic Study of Deaths in France, 1968-2009.

Todd N, Valleron AJ - Environ. Health Perspect. (2015)

(A) Grid placed over continental France to obtain the squares used in the analysis. The pixel color indicates the population density in 2008 (red: highest; pale yellow: lowest). The temperature–mortality analysis (shown in (B) for a particular square in the western part of France) was done for each of the squares with > 1.5 deaths/day during each of the studied periods, corresponding to 22,500 deaths in the total analysis (228 squares), and to 7,500 deaths/period for the by-period analyses (224 squares). For each grid square, a GAM was used to model the temperature–mortality relationship and extract the corresponding curve and three parameters: the minimum mortality temperature (MMT) and the relative risk of mortality expressed as the ratios of mortality observed at 25°C to that observed at MMT (RM25) or that observed at 18°C (RM25/18). This map is interactive at http://www.isis-diab.org/isispub/ehp/interactive_map_wp.htm. (B) Clicking on any square of the map shows vital information on the square (top), the smooth function of time [s(t) (defined in Equation 1) bottom right], and the variation with temperature of the relative risk of total mortality for individuals > 65 years old [the reference risk was the mortality observed at the MMT of each square: here (bottom left) is thus plotted s1(T)/s1(MMT)]. One example is shown here: The detailed information pertaining to the 1968–2009 period for all squares of the grid is obtained on the interactive map where the temperature–mortality curves can be viewed for the all the study periods [Pall (1968-2009), P1 (1968–1981), P2 (1982–1995), and P3 (1996–2009)].
© Copyright Policy - public-domain
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4492259&req=5

f1: (A) Grid placed over continental France to obtain the squares used in the analysis. The pixel color indicates the population density in 2008 (red: highest; pale yellow: lowest). The temperature–mortality analysis (shown in (B) for a particular square in the western part of France) was done for each of the squares with > 1.5 deaths/day during each of the studied periods, corresponding to 22,500 deaths in the total analysis (228 squares), and to 7,500 deaths/period for the by-period analyses (224 squares). For each grid square, a GAM was used to model the temperature–mortality relationship and extract the corresponding curve and three parameters: the minimum mortality temperature (MMT) and the relative risk of mortality expressed as the ratios of mortality observed at 25°C to that observed at MMT (RM25) or that observed at 18°C (RM25/18). This map is interactive at http://www.isis-diab.org/isispub/ehp/interactive_map_wp.htm. (B) Clicking on any square of the map shows vital information on the square (top), the smooth function of time [s(t) (defined in Equation 1) bottom right], and the variation with temperature of the relative risk of total mortality for individuals > 65 years old [the reference risk was the mortality observed at the MMT of each square: here (bottom left) is thus plotted s1(T)/s1(MMT)]. One example is shown here: The detailed information pertaining to the 1968–2009 period for all squares of the grid is obtained on the interactive map where the temperature–mortality curves can be viewed for the all the study periods [Pall (1968-2009), P1 (1968–1981), P2 (1982–1995), and P3 (1996–2009)].
Mentions: Discretization of space. The temperature–mortality relationship was studied within each 0.50°-latitude × 0.50°-longitude “square” (approximately 30 km × 30 km) of a grid placed over the map of continental France. This grid was built by aggregating four 0.25°-latitude × 0.25°-longitude squares of the E-OBS data set, starting at 40.625° latitude and –5.625° longitude and ending at 10.625° latitude and 51.875° longitude, yielding 295 squares (Figure 1), for which the daily mean temperatures, precipitations, and average sea-level pressures were obtained by averaging the four 0.25°-latitude × 0.25°-longitude E-OBS database source values.

Bottom Line: The temperature-mortality relationship has repeatedly been found, mostly in large cities, to be U/J-shaped, with higher minimum mortality temperature (MMT) at low latitudes being interpreted as indicating human adaptation to climate.The RM25/18 ratio of mortality at 25°C versus that at 18°C declined significantly (p = 5 × 10-5) as warming increased: 18% for P1, 16% for P2, and 15% for P3.Results of this spatiotemporal analysis indicated some human adaptation to climate change, even in rural areas.

View Article: PubMed Central - PubMed

Affiliation: U1169, INSERM (Institut national de la santé et de la recherche médicale), Le Kremlin-Bicêtre, France.

ABSTRACT

Background: The temperature-mortality relationship has repeatedly been found, mostly in large cities, to be U/J-shaped, with higher minimum mortality temperature (MMT) at low latitudes being interpreted as indicating human adaptation to climate.

Objectives: Our aim was to partition space with a high-resolution grid to assess the temperature-mortality relationship in a territory with wide climate diversity, over a period with notable climate warming.

Methods: The 16,487,668 death certificates of persons > 65 years of age who died of natural causes in continental France (1968-2009) were analyzed. A 30-km × 30-km grid was placed over the map of France. Generalized additive model regression was used to assess the temperature-mortality relationship for each grid square, and extract the MMT and the RM25 and RM25/18 (respectively, the ratios of mortality at 25°C/MMT and 25°C/18°C). Three periods were considered: 1968-1981 (P1), 1982-1995 (P2), and 1996-2009 (P3).

Results: All temperature-mortality curves computed over the 42-year period were U/J-shaped. MMT and mean summer temperature were strongly correlated. Mean MMT increased from 17.5°C for P1 to 17.8°C for P2 and to 18.2°C for P3 and paralleled the summer temperature increase observed between P1 and P3. The temporal MMT rise was below that expected from the geographic analysis. The RM25/18 ratio of mortality at 25°C versus that at 18°C declined significantly (p = 5 × 10-5) as warming increased: 18% for P1, 16% for P2, and 15% for P3.

Conclusions: Results of this spatiotemporal analysis indicated some human adaptation to climate change, even in rural areas.

No MeSH data available.


Related in: MedlinePlus