The influence of heat and cold waves on mortality in Russian subarctic cities with varying climates

Publications on ambient temperature-related mortality among Arctic or subarctic populations are extremely rare. While circumpolar areas cover large portions of several European countries, Canada, and the USA, the population of these territories is relatively small, and the data needed for statistical analysis of the health impacts of extreme temperature events are frequently insufficient. This study utilizes standard time series regression techniques to estimate relative increases in cause- and age-specific daily mortality rates during heat waves and cold spells in four Russian cities with a subarctic climate. The statistical significance of the obtained effect estimates tends to be greater in the continental climate than in the marine climate. A small meta-analysis was built around the obtained site-specific health effects. The effects were homogeneous and calculated for the selected weather-dependent health outcomes. The relative risks of mortality due to ischemic heart disease, all diseases of the circulatory system, and all non-accidental causes during cold spells in the age group ≥ 65 years were 1.20 (95% CI: 1.11-1.29), 1.14 (1.08-1.20), and 1.12 (1.07-1.17), respectively. Cold spells were more harmful to the health of the residents of Murmansk, Archangelsk, and Magadan than heat waves, and only in Yakutsk, heat waves were more dangerous. The results of this study can help the public health authorities develop specific measures for the prevention of excess deaths during cold spells and heat waves in the exposed subarctic populations.

On the association of ambient temperature and elderly mortality in a Mediterranean island - Crete

Extreme weather conditions affect human health. This study analyses the association of high and low temperature with cardiovascular and respiratory diseases on people over 65 years old for the years 2007 to 2015, in the region of Chania, Greece. The mortality is examined by time series analysis and further investigated by Poisson, and Negative Binomial regression, showing that one-lag in maximum temperature strongly affects the health of the elderly. Finally, cluster analysis is used from May to October, which is confirmed by discriminant analysis.

Mortality induced by PM2.5 exposure following the 1783 Laki eruption using reconstructed meteorological fields

The 1783–1784 Laki eruption provides a natural experiment to evaluate the performance of chemistry-transport models in predicting the health impact of air particulate pollution. There are few existing daily meteorological observations during the second part of the 18^th century. Hence, creating reasonable climatological conditions for such events constitutes a major challenge. We reconstructed meteorological fields for the period 1783–1784 based on a technique of analogues described in the Methods. Using these fields and including detailed chemistry we describe the concentrations of sulphur (SO₂/SO₄) that prevail over the North Atlantic, the adjoining seas and Western Europe during these 2 years. To evaluate the model, we analyse these results through the prism of two datasets contemporary to the Laki period: • The date of the first appearance of ‘dry fogs’ over Europe, • The excess mortality recorded in French parishes over the period June–September 1783. The sequence of appearances of the dry fogs is reproduced with a very-high degree of agreement to the first dataset. High concentrations of SO₂/SO₄ are simulated in June 1783 that coincide with a rapid rise of the number of deceased in French parishes records. We show that only a small part of the deceased of the summer of 1783 can be explained by the present-day relationships between PM2.5 and relative risk. The implication of this result is that other external factors such as the particularly warm summer of 1783, and the lack of health care at the time, must have contributed to the sharp increase in mortality over France recorded from June to September 1783.

Epidemic cycles and environmental pressure in colonial Quebec

OBJECTIVES

Research on historical populations in Europe finds that infectious disease epidemics appear to induce predictable cycles in age-specific mortality. We know little, however, about whether such cycles also occurred in less dense founder populations of North America. We used high-quality data on the Quebecois population from 1680 to 1798 to examine the extent to which age-specific mortality showed predictable epidemic cycles. We further examined whether environmental pressures-temperature, lack of precipitation, or crop failure-may have set the stage for the emergence of epidemics.

METHODS

We applied autoregressive, integrated, moving average time series methods to annual counts of period mortality for the following age groups: < 1 year, 1 to < 5 years, 5 to < 15 years, 15 to < 50 years, and 50 years and above. These methods controlled for other patterns (e.g., trend) before empirically identifying cycles.

RESULTS

Results indicate a strong seven-year cycle in mortality among infants and children under seven years of age. Warm temperatures (across Quebec overall) and relatively dry years (in Eastern Quebec) also predicted an increased risk of mortality in infancy and childhood, although these environmental variables appear to act independently of the epidemic cycle pattern.

DISCUSSION

Findings indicate a strong seven-year epidemic cycle in historical Quebec which afflicted naïve birth cohorts not previously exposed to the prior epidemic. We contend that smallpox epidemics likely contributed to this cycle. The seven-year cycle occurred only in the latter half of the test period (post 1740) with increasing size of the colony and population concentration in urban areas.

Temperature extremes and infant mortality in Bangladesh: Hotter months, lower mortality

Background

Our study aims to obtain estimates of the size effects of temperature extremes on infant mortality in Bangladesh using monthly time series data.

Methods

Data on temperature, child and infant mortality were obtained for Matlab district of rural Bangladesh for January 1982 to December 2008 encompassing 49,426 infant deaths. To investigate the relationship between mortality and temperature, we adopted a regression with Autoregressive Integrated Moving Average (ARIMA) errors model of seasonally adjusted temperature and mortality data. The relationship between monthly mean and maximum temperature on infant mortality was tested at 0 and 1 month lags respectively. Furthermore, our analysis was stratified to determine if the results differed by gender (boys versus girls) and by age (neonates (≤ 30 days) versus post neonates (>30days and <153days)). Dickey Fuller tests were performed to test for stationarity, and since the time series were non-stationary, we conducted the regression analysis based on the first differences of mortality and temperature.

Results

Hotter months were associated with lower infant mortality in Bangladesh. Each degree Celsius increase in mean monthly temperature reduced monthly mortality by 3.672 (SE 1.544, p<0.05) points. A one degree increase in mean monthly temperature one month prior reduced mortality by 0.767 (SE 0.439, p<0.1) for boys and by -0.0764 (SE 0.366, NS) for girls. Beneficial effects of maximum monthly temperature were on the order of 0.623 to -0.712 and statistically significant for girls and boys respectively. Effect sizes of mean monthly temperature were larger for neonates at 1.126 (SE 0.499, p<0.05) than for post-neonates at 0.880 (SE 0.310, p<0.05) reductions in mortality per degree.

Conclusion

There is no evidence that infant survival is adversely affected by monthly temperature extremes in Bangladesh. This may reflect a more heightened sensitivity of infants to hypothermia than hyperthermia in this environment.

Climate and marriage in the Netherlands, 1871-1937

Environmental factors such as climate variability can place significant constraints on demographic behavior in a range of settings. However, few studies investigate the relationships between demography and climate in historical contexts. Using longitudinal individual-level demographic data from the Historical Sample of the Netherlands (HSN) and climate and economic data from 1871-1937, we examine the effects of climate variability on marriage. This analysis reveals that marriage increases with negative environmental conditions such as cold temperatures, riverine flooding, and high rye prices. These findings are not consistent with a Malthusian narrative of marriage behavior, or with the expectation that environmental constraints were stronger in the historical past.

Climate Variability and Human Migration in the Netherlands, 1865-1937

Human migration is frequently cited as a potential social outcome of climate change and variability, and these effects are often assumed to be stronger in the past when economies were less developed and markets more localized. Yet, few studies have used historical data to test the relationship between climate and migration directly. In addition, the results of recent studies that link demographic and climate data are not consistent with conventional narratives of displacement responses. Using longitudinal individual-level demographic data from the Historical Sample of the Netherlands (HSN) and climate data that cover the same period, we examine the effects of climate variability on migration using event history models. Only internal moves in the later period and for certain social groups are associated with negative climate conditions, and the strength and direction of the observed effects change over time. International moves decrease with extreme rainfall, suggesting that the complex relationships between climate and migration that have been observed for contemporary populations extend into the nineteenth century.