The effect of climate warming on the seasonal variation of mortality in European countries

Prevezanos, Michail; Benos, Alexios; Zoumakis, Nikolaos; Papadakis, Nikolaos

doi:10.1007/s11600-022-00809-4

Artykuł - szczegóły

Tytuł artykułu

The effect of climate warming on the seasonal variation of mortality in European countries

Autorzy

Prevezanos Michail , Benos Alexios , Zoumakis Nikolaos , Papadakis Nikolaos

Wybrane pełne teksty z tego czasopisma

https://www.springer.com/journal/11600

Identyfikatory

DOI

10.1007/s11600-022-00809-4

Warianty tytułu

Języki publikacji

Abstrakty

Although several studies have concluded that excess winter deaths are not a suitable indicator of cold-related health impacts, the investigation of temporal fluctuation in mortality across many European countries could provide an insight into the seasonal variation of deaths at different climatic conditions. We investigated the evolution over time of the Excess Winter Deaths Index (EWDI) and the Summer-to-Winter Deaths ratio (S/W) for the period 1960–2018 and the temporal fluctuation of the Heating and Cooling Degree Days indices for the period 1979–2020. We found a clear spatial pattern of EWDI with statistically significant decreasing trends in Mediterranean countries and increasing trends in Nordic countries. On the other hand, S/W index shown increasing trends in Mediterranean region and decreasing trends in Nordic countries. Statistical analysis of Heating Degree Days index showed significant decreasing trends for all European countries, probably due to the appearance of milder winters. Also, the values of Cooling Degree Days index exhibited a statistically significant upward trend for Mediterranean countries, mainly due to increased frequency of warmer summers, as a result of climate change. This study shows that the differences in seasonal variation of mortality between European countries are likely to disappear, as the climate gets warmer. A possible explanation for our findings is that climate change already brings milder winters and hotter summers to the Mediterranean countries, while in the Nordic countries global warming causes less severe winters and more pleasant summers as shown from Heating and Cooling Degree Days analysis. In addition to providing a basis to investigate potential effects of global warming on human mortality, the findings of this study are likely to be crucial for climate change policy and developing relevant adaptation strategies in Europe.

Słowa kluczowe

human mortality heating degree days climate change global warming

śmiertelność ludzi stopniodni ogrzewania zmiana klimatu globalne ocieplenie

Wydawca

Instytut Geofizyki PAN
Springer

Czasopismo

Acta Geophysica

Rocznik

2022

Tom

Vol. 70, no 4

Strony

1947--1956

Opis fizyczny

Bibliogr. 56 poz.

Twórcy

autor

Prevezanos Michail

pmichail@auth.gr

Laboratory of Hygiene, Social and Preventive Medicine and Medical Statistics, Faculty of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece

autor

Benos Alexios

Laboratory of Primary Health Care, General Medicine and Health Research Services, Faculty of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece

autor

Zoumakis Nikolaos

Laboratory of Hygiene, Social and Preventive Medicine and Medical Statistics, Faculty of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece

autor

Papadakis Nikolaos

Laboratory of Hygiene, Social and Preventive Medicine and Medical Statistics, Faculty of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece

Bibliografia

1. Addinsoft (2014) XLSTAT Statistical and data analysis solution for Microsoft Excel. Long Island, NY
2. Agri4Cast Resource Portal (2021) ‘Monthly heating and cooling degree days’.
3. Anderson TW, Darling DA (1954) A Test of goodness of fit. J Am Stat Assoc 49(268):765–769. https://doi.org/10.2307/2281537
4. Aström DO et al (2016) Evolution of minimum mortality temperature in Stockholm, Sweden, 1901–2009. Environ Health Perspect 124(6):740–744. https://doi.org/10.1289/ehp.1509692
5. Bartels R (1982) The rank version of von Neumann’s ratio test for randomness. J Am Stat Assoc 77(377):40–46. https://doi.org/10.1080/01621459.1982.10477764
6. Box G, Jenkins G, Reinsel G (2008) Time series analysis: forecasting and control. John Wiley, Hoboken, NJ
7. Breusch T, Pagan A (1979) A simple test for heteroscedasticity and random coefficient variation. Econometrica 47:1287–1294. https://doi.org/10.2307/1911963
8. Clinch JP, Healy JD (2000) Housing standards and excess winter mortality. J Epidemiol Commun Health. https://doi.org/10.1136/jech.54.9.719
9. Cromwell J, Labys W, Terraza M (1994) Univariate tests for time series models. Sage Publications, Thousand Oaks, CA
10. Durbin J (1969) Tests for serial correlation in regression analysis based on the periodogram of least-squares residuals. Biometrika 56(1):1–15. https://doi.org/10.2307/2334686
11. Engle RF (1982) Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica 50(4):987–1007. https://doi.org/10.2307/1912773
12. Eurostat (2021a) ‘Browse statistics by theme’. Available at: https://ec.europa.eu/eurostat/en/web/main/data/statistics-by-theme. Accessed 20 Dec 2021a
13. Eurostat (2021b) ‘Energy statistics-cooling and heating degree days’
14. Forzieri G et al (2017) Increasing risk over time of weather-related hazards to the European population: a data-driven prognostic study. Lancet Planet Health 1(5):e200–e208. https://doi.org/10.1016/S2542-5196(17)30082-7
15. Fowler T et al (2015) Excess winter deaths in Europe: a multi-country descriptive analysis. Eur J Pub Health 25(2):339–345. https://doi.org/10.1093/eurpub/cku073
16. Gasparrini A et al (2015a) Mortality risk attributable to high and low ambient temperature: a multicountry observational study. Lancet 386(9991):369–375. https://doi.org/10.1016/S0140-6736(14)62114-0
17. Gasparrini A et al (2015b) Temporal variation in heat-mortality associations: a multicountry study. Environ Health Perspect 123(11):1200–1207. https://doi.org/10.1289/ehp.1409070
18. Gasparrini A et al (2016) Changes in susceptibility to heat during the summer: a multicountry analysis. Am J Epidemiol 183(11):1027–1036. https://doi.org/10.1093/aje/kwv260
19. Gasparrini A et al (2017) Projections of temperature-related excess mortality under climate change scenarios. Lancet Planet Health 1(9):e360–e367. https://doi.org/10.1016/S2542-5196(17)30156-0
20. Godfrey LG (1978a) Testing against general autoregressive and moving average error models when the regressors include lagged dependent variables. Econometrica 46(6):1293–1301. https://doi.org/10.2307/1913829
21. Godfrey LG (1978b) Testing for higher order serial correlation in regression equations when the regressors include lagged dependent variables. Econometrica 46(6):1303–1310. https://doi.org/10.2307/1913830
22. Hajat S, Gasparrini A (2016) The excess winter deaths measure: why its use is misleading for public health understanding of cold-related health impacts. Epidemiology 27(4):486–491. https://doi.org/10.1097/EDE.0000000000000479
23. Hamed K, Rao R (1998) A modified Mann-Kendall trend test for autocorrelated data. J Hydrol 204:182–196
24. Hamilton JD (1994) Time series analysis. Princeton University Press, NJ
25. Healy JD (2003) ‘Excess winter mortality in Europe: a cross country analysis identifying key risk factors. J Epidemiol Commun Health. https://doi.org/10.1136/jech.57.10.784
26. Hobijn B et al (2004) Generalizations of the KPSS-test for stationarity. Stat Neerl 58(4):483–502. https://doi.org/10.1111/J.1467-9574.2004.00272.X
27. IPCC (2014) Climate change 2014: synthesis report. Contribution of working groups I, II and III to the fifth assessment report of the intergovernmental panel on climate change. [Core writing team, Pachauri RK, Meyer (eds.)]. Geneva: IPCC, pp. 151
28. Jarque CM, Bera AK (1980) Efficient tests for normality, homoscedasticity and serial independence of regression residuals. Econ Lett 6(3):255–259. https://doi.org/10.1016/0165-1765(80)90024-5
29. Jarque CM, Bera AK (1987) A test for normality of observations and regression residuals. Int Stat Rev 55(2):163–172. https://doi.org/10.2307/1403192
30. Kinney PL et al (2015) Winter season mortality: Will climate warming bring benefits? Environ Res Lett 10(6):064016. https://doi.org/10.1088/1748-9326/10/6/064016
31. Kwiatkowski D et al (1992) Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we that economic time series have a unit root? J Econom 54:159–178. https://doi.org/10.1016/0304-4076(92)90104-Y
32. Laake K, Sverre JM (1996) Winter excess mortality: a comparison between Norway and England plus wales. Age Ageing 25(5):343–348. https://doi.org/10.1093/ageing/25.5.343
33. Lee JHH, King ML (1993) A locally most mean powerful based score test for ARCH and GARCH regression disturbances. J Bus Econ Stat 11(1):17–27. https://doi.org/10.1080/07350015.1993.10509930
34. Liddell C et al (2015) Excess winter deaths in 30 European countries 1980–2013: a critical review of methods. J Public Health. https://doi.org/10.1093/pubmed/fdv184
35. Mann HB (1945) Nonparametric tests against trend. Econometrica 13(3):245. https://doi.org/10.2307/1907187
36. McCleary R et al (1980) Applied time series analysis for the social sciences. Sage, Beverly Hills, CA
37. McKee CM (1989) Deaths in winter: Can Britain learn from Europe? Eur J Epidemiol 5(2):178–182. https://doi.org/10.1007/bf00156826
38. McLeod AI, Li WK (1983) Diagnostic checking ARIMA time series models using squared-residual autocorrelations. J Time Ser Anal 4(4):269–273. https://doi.org/10.1111/j.1467-9892.1983.tb00373.x
39. Mora C et al (2017) Global risk of deadly heat. Nat Clim Chang 7(7):501–506. https://doi.org/10.1038/nclimate3322
40. Newey WK, West KD (1994) Automatic lag selection in covariance matrix estimation. Rev Econ Stud 61:631–653. https://doi.org/10.2307/2297912
41. Oudin Åström D et al (2018) Investigating changes in mortality attributable to heat and cold in Stockholm, Sweden. Int J Biometeorol 62(9):1777–1780. https://doi.org/10.1007/s00484-018-1556-9
42. Ramsey J (1969) Tests for specification errors in classical linear least squares regression analysis. J R Stat Soc. https://doi.org/10.1111/j.2517-6161.1969.tb00796.x
43. Royston P (1992) Approximating the Shapiro-Wilk W-test for non-normality. Stat Comput 2(3):117–119. https://doi.org/10.1007/BF01891203
44. SAS Institute Inc. (2017) ETS 14.3 User’s guide. The AUTOREG procedure. Cary, NC
45. Sen PK (1968) Estimates of the regression coefficient based on Kendall’s Tau. J Am Stat Assoc 63(324):1379. https://doi.org/10.2307/2285891
46. Shapiro SS, Wilk MB (1965) An analysis of variance test for normality (complete samples). Biometrika 52(3/4):591–611. https://doi.org/10.2307/2333709
47. The Eurowinter Group (1997) Cold exposure and winter mortality from ischaemic heart disease, cerebrovascular disease, respiratory disease, and all causes in warm and cold regions of Europe. Lancet 349(9062):1341–1346. https://doi.org/10.1016/S0140-6736(96)12338-2
48. Twardosz R, Kossowska-Cezak U (2015) Exceptionally hot and cold summers in Europe (1951–2010). Acta Geophys 63(1):275–300. https://doi.org/10.2478/S11600-014-0261-2
49. Twardosz R, Kossowska-Cezak U, Pelech S (2016) Extremely cold winter months in Europe (1951–2010). Acta Geophys 64(6):2609–2629. https://doi.org/10.1515/ACGEO-2016-0083
50. Vardoulakis S et al (2015) Comparative assessment of the effects of climate change on heat- and cold-related mortality in the United Kingdom and Australia. Environ Health Perspect 122(12):1285–1292. https://doi.org/10.1289/ehp.1307524
51. Wald A, Wolfowitz J (1940) On a test whether two samples are from the same population. Ann Math Statist 11(2):147–162. https://doi.org/10.1214/aoms/1177731909
52. White H (1980) A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica 48:817–838. https://doi.org/10.2307/1912934
53. White KJ (1992) The Durbin-Watson test for autocorrelation in nonlinear models. Rev Econ Stat 74(2):370–373. https://doi.org/10.2307/2109675
54. Wong H, Li WK (2011) Portmanteau test for conditional heteroscedasticity using ranks of squared residuals. J Appl Stat 22(1):121–134. https://doi.org/10.1080/757584402
55. Wooldridge J (2013) Introductory econometrics: a modern approach. Joe Sabatino (ed), 5th edn. Mason, OH, Thomson/South-Western, pp 268–334
56. Zoumakis M, Zoumakis N, Prevezanos M (2017) The urban built environment and temperature-related mortality risk in a warming climate. Lancet Planet Health 1(8):e313. https://doi.org/10.1016/S2542-5196(17)30137-7

Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).

Typ dokumentu

Bibliografia

Identyfikator YADDA

bwmeta1.element.baztech-cbaee6be-33c7-4993-852f-82ad75a9291d