the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 08 Dec 2023
Climatic impacts on mortality in pre-industrial Sweden
Abstract. Climate variability and change, as well as extreme weather events, have notable impacts on human health and mortality. In historical times, the effect of climate on health and mortality was presumably stronger than today, owing to that nutrition status was meditated through climatic impacts on food production along with factors such as poor housing and healthcare. Despite this, climatic impacts on mortality in the past remain poorly understood. This study aims to improve the understanding of historical climate effects on mortality, using annual mortality records and meteorological data from Sweden between 1749 and 1859. The analysis includes the entire population as well as subgroups based on sex and age. A statistically significant negative correlation was found between winter and spring temperatures and mortality (i.e., lower temperatures = higher mortality and vice versa). We demonstrate that colder winters and springs were linked to higher mortality levels, not only for the same year but also the following year. Conversely, no statistically significant associations were observed between summer or autumn temperatures and mortality, and only weak associations existed with precipitation. The impact of winter– spring temperature on mortality was most pronounced for the same year in southern Sweden and during the 19th century, but stronger for the following year in central Sweden and during the 18th century. These findings call for further research, especially investigating specific diseases and additional contributing factors to the observed increase in mortality following cold winter and spring conditions in Sweden during the late pre-industrial period.
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Status: open (until 21 Apr 2024)
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RC1: 'Comment on cp-2023-92', Anonymous Referee #1, 25 Dec 2023
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The comment was uploaded in the form of a supplement: https://cp.copernicus.org/preprints/cp-2023-92/cp-2023-92-RC1-supplement.pdf
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AC1: 'Reply on RC1', Fredrik Charpentier Ljungqvist, 23 Jan 2024
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Response to reviewer #1 of Chen et al.
Comment: It includes an excellent review of the literature. I suggest to add some information from the public health point of view, including a description of the annual cycle of mortality rate whose maximum should coincide with the coldest months of the year. I found an article that claims that for cohorts born in 1800 the risk of dying during the winter season was almost twice that of dying during summer (Ledberg, 2020).
Reply: Thank you for your positive evaluation of our review of the literature. You bring up two aspects, first how mortality varies over the calendar year, and next that this variation has declined with later-born cohorts, which is the conclusion of the suggested article by Ledberg (2020). This is very interesting and likely the result of many factors, for example, better housing, and better overall health especially concerning respiratory function (reduced smoking).
We have, as the reviewer suggests, now added some additional information about the annual cycle of mortality rate, relevant from a public health point of view, and also included a sentence in the revised manuscript summarising the main results of Ledberg (2020). Ledberg (2020) is interesting, although it should be pointed out that Ledberg (2020) only covers the period after 1860. Currently there are no monthly national series for Sweden for the 18th century, and there could be large regional differences. For example, if the impact of harvests were larger in earlier periods, deaths may have spread more during the whole year – as could also be the effect of epidemics and wars.
The annual cycle of mortality is, however, very complex. Not only does the effect vary by region, but also seems to vary for the occurrence of the disease and prognosis of the disease. For example, findings from Spain in The Lancet Regional Health – Europe (https://www.thelancet.com/journals/lanepe/article/PIIS2666-7762(23)00176-X/fulltext) shows a strong seasonal fluctuation in in-hospital mortality from respiratory diseases, and while hospital admissions were higher during the cold season, the maximum incidence of inpatient mortality was during the summer and was strongly related to high temperatures.
We also added the following text in the Introduction section to provide more information on the annual cycle of mortality:
“The total number of deaths follow an annual cycle, with higher mortality during the winter months in the extra-tropical Northern Hemisphere, a pattern also observed in contemporary Sweden. Many, but not all, causes of deaths display varying seasonal patterns. For example, data from the United States show that pneumonia, influenza, chronic obstructive pulmonary disease (COPD), and other respiratory diseases, peak during the winter months. A similar pattern, though less pronounced, is observed for cardiovascular diseases. Conversely, deaths from traffic accidents peak during summer months, while suicide and cancers show small or no seasonality. However, the differences vary by region and by baseline mortality level. In regions with warmer winters and cooler homes, a given rate of change in winter temperature will have a larger impact on death rates.”Comment: I suggest to indicate the sizes of the three age groups: 0–14 years, 15–64 years, over 65 years.
Reply: Thank you for pointing this out. Information of the sample size is now added for each of the three age groups in Table 3 of the revised manuscript.
Comment: It is not clear the purpose of including Fig. 1 showing the seasonal histograms of the Uppsala temperature record. As this information is not used later on in the analysis, I suggest to eliminate it.
Reply: We respectfully disagree on this point. We think that the seasonal temperature distribution and their temporal changesare of significant interest to provide readers with valuable insight to understand the climate of (central) Sweden. We motivate the inclusion of Uppsala temperature record in the following way: “The Uppsala temperature record is presented because it is the longest available record in present-day Sweden covering the studied period.” However, if the editor deems it necessary, we are open to the possibility of excluding Fig. 1, the Uppsala temperature record, from the article.
Comment: In line 145 the study period is defined as 1750–1859. However in other parts of the text is mentioned as 1749–1859 (lines 6, 95, 111, 135, 138, 158, figure caption of Fig. 1).
Reply: We agree with the need for clarification, and will incorporate this into the revision. Information from 1749 is only included to calculate excess mortality for 1750.
Comment: It is a general consensus that in temperate climates mortality rate is highest during winter, let say from November to March. Then, as the data for mortality rate is only available on an annual basis, the causes for an anomalously high value of mortality for a certain year can be attributed to anomalously cold weather either at the beginning of the year (January–February), at the end of the year (November–December) or both at the beginning or at the end of the year. This difficulty for the interpretation of the results is not mentioned when presenting the available data.
Reply: Thank you for bringing this issue up. In the original manuscript, we only included this difficulty for the interpretation in the Discussion section. We have now, as the reviewer suggests, also added a short commentary on this in the presentation of the data: “Annual mortality data may not capture the seasonal nuances of mortality rates in temperate climates, where peak mortality typically occurs during the winter months, roughly from November to March. This limitation makes it challenging to attribute anomalously high mortality rates during a specific year solely to the effects of exceptionally cold conditions during certain months (e.g., January–February or November–December). Despite this limitation, our study provides valuable insights into the potential connection between climate and mortality. If adverse climatic conditions have an immediate effect on mortality, we would expect correlations without time lags in our annual data. However, even in annual data, correlations with time lags may emerge if there is a delayed effect between climate conditions and mortality. Future research using more granular monthly mortality data could offer a more detailed understanding of these dynamics.”
Comment: The correlation technique is generally used to test an hypothesis for a relationship between two variables. What it would be the hypothesis for a relationship between the mean regional temperature for a single month and the annual rate of mortality that are behind the correlations presented in Tables 1, 2, 3, 4, A1 and A2? Is it plausible to consider that mean temperature during a single month will have an impact on the annual rate of mortality? This question if particularly valid for months at the end of the year, considering that to a large extent the mortality rate is determined by the deaths that occurred during the previous months.
I suggest to use a more precise language when extracting conclusions from correlations relatively low in magnitude, although statistically significant. For example, from correlations presented in Table 1 it is mentioned in line 190 “Colder winters and springs were associated with higher mortality and vice versa”. In fact, the correlations of the order of –0.3 explain only 9% of the mortality variance. A scatter diagram (which is not presented) would illustrate the weakness of the link among the two variables. Later on in the text it is shown that the relatively low magnitude of the correlations derives from the fact that the relationship between temperature and mortality rate during winter and spring does not persist during the entire study period, due to geographical changes in its intensity (see Fig. 7).Reply: We appreciate this suggestion and will strive to use more precise and careful language when formulating our conclusions in the revised manuscript. Although we acknowledge the relatively low magnitude of correlations, we consider fluctuations of ~10% in mortality attributed to climate as rather noteworthy. The effect of spring temperature on excess death is demonstrated in the scatter diagram (below).
Comment: I suggest to eliminate the discussion about the relationship between the rate of mortality and the PDSI index. Correlations presented in Table A2 are mostly not statistically significant and explain at most 4% of the variance of mortality. Furthermore, it is mentioned in line 151–152 that precipitation measurements can be considered unreliable prior to the late 19th century in Sweden. Regarding this, in the discussion section there is another example of a statement that overrates the results that were obtained. Line 307: “While our findings demonstrate the influence of a wet autumn on mortality in both western and eastern Sweden…”. This statement is not supported by the results presented in Table A2, showing very low and mostly not statistically significant correlations between mortality and PDSI data for March, April and May. As in the case of temperature, it is possible that the positive correlations are stronger for certain periods, but this analysis was not performed.
Reply: We will reconsider, after receiving the second review and hearing the editor’s decision, whether we should include or exclude hydroclimate (PDSI) from the study.
Comment: There are several references to results showing the impact of winter and spring temperature on mortality (i.e. lines 255, 270, 282, 293). However, surprisingly, most of the correlations shown in Tables 1–4, A1 and A2 for December, January and February are not statistically significant. It is more correct to indicate that the results reveal some impact of low temperature on mortality during late winter and spring. Same objection is valid for statements in the Abstract and in the Conclusions.
Reply: We will in the revised manuscript make changes, as suggested by the reviewer, emphasising the effect of temperature on late winter and spring rather than winter and spring.
Comment: Lines 367–369: “… we found that the southern-most regions experienced the greatest impact of temperature on mortality during the same year. Conversely, central Sweden exhibited the strongest temperature effect on mortality in the following year”
Comment: In my opinion this conclusion does not summarize in an adequate way the results presented in Fig. 7. This figure shows significant geographical changes of these impacts during the study period. Thus, in the eastern – central part of the country anomalously low temperature during FMA tended to be associated with above average mortality rate in the period 1805–1859, but not in the period before. Do the author have and hypothesis for this?. On the other hand, while during the period 1750–1804 relatively large mortality rate tended to prevail in the whole region the year following an anomalously cold FMA, this relationship was restricted to the centraleastern portion of the country afterward. Do the authors consider that improved food and nutrition security did not reach that part of the country during that period (1804–1859)?Reply: We will add the following clarification in the Conclusion section of the revised manuscript: “This suggests that in central and northern Sweden, the influence of temperature on mortality was primarily attributed to the adverse effects of cold weather on agricultural harvests, while this was not the case in southern Sweden. To establish causation definitively, future studies should incorporate data on regional harvest and monthly mortality.”
Comment: Lines 371–372: “Among adults, colder conditions in April had the most adverse effect on mortality both for the same year and the following year”. I question this statement referring to the impact of temperature during a single month, considering that Table 3 shows correlations similar in magnitude to that in April for the periods February–April, March–April and March April and May.
Reply: We agree with the reviewer, and we have hence now removed this sentence.
Citation: https://doi.org/10.5194/cp-2023-92-AC1
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AC1: 'Reply on RC1', Fredrik Charpentier Ljungqvist, 23 Jan 2024
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CC1: 'Comment on cp-2023-92', Bertil Forsberg, 20 Mar 2024
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Climate impacts on mortality in pre-industrial Sweden
T.T. Chen, R- Edvinsson, K. Modig, H.W. Linderholm, F. C Ljungqvist
Recommendation: To be published after some changes.
1.1 Climate-mortality relationships: past and present
It would be useful here with a clear separation between observed seasonal and annual relationships and the known effects of hot and cold days and short episodes of extreme temperatures on the daily mortality, including the different lag structure as a result of different mechanisms. There are a few studies covering quite long periods e.g. Åström DO, Forsberg B, Edvinsson S, Rocklöv J. Acute fatal effects of short-lasting extreme temperatures in Stockholm, Sweden: evidence across a century of change. Epidemiology. 2013 Nov;24(6):820-9. doi: 10.1097/01.ede.0000434530.62353.0b. PMID: 24051892.I lack a discussion about harvesting effects, how high mortality among vulnerable (elderly) could be followed by lower mortality and weaker effects of exposure. This effect can be visible also with moderate increases in deaths, see Rocklöv J, Forsberg B, Meister K. Winter mortality modifies the heat-mortality association the following summer. Eur Respir J. 2009 Feb;33(2):245-51. doi: 10.1183/09031936.00037808. Epub 2008 Sep 17. Erratum in: Eur Respir J. 2009 Apr;33(4):947. PMID: 18799511.
In the last paragraphs discussing the attenuated effects of cold, one could also expect vaccination of elderly and lower air pollution levels to modify the relationships.
2.3 Statistical methods
It would be interesting to know if the expected number of deaths in the oldest group (65+) would differ much (due to harvesting) if you use a baseline/trend without the last year and mortality from last year as a separate variable, or if annual numbers are too crude.4.1 Discussion
The lack of an effect the following year in the oldest group could be a harvesting effect (see above!).
Could cold winter-spring months also have resulted in a lack of wood fuel to heat homes?
Citation: https://doi.org/10.5194/cp-2023-92-CC1
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