On the Annual Fluctuations in the Number of Deaths from Various Diseases, Compared with Like Fluctuations in Crime, and in Other Events Within and Beyond the Control of the Human Will

Guy, William A.

doi:10.2307/2338211

Cited by 11 publications

(6 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…This pattern of mortality is reflective of the accepted patterns of mortality associated with “winter pressures”. Excess winter mortality has been described in studies dating back over a century, with an increase in all cause mortality, mortality related to cardiovascular disease, stroke, respiratory disease and Gram‐negative bacteraemia all being reported . In the majority of cases AKI does not represent intrinsic renal disease but occurs as a result of dysfunction of other organs leading to septic, ischaemic or toxic insults to the kidneys.…”

Section: Discussionmentioning

confidence: 99%

Seasonal pattern of incidence and outcome of Acute Kidney Injury: A national study of Welsh AKI electronic alerts

et al. 2017

View full text Add to dashboard Cite

SummaryObjectives: To identify any seasonal variation in the occurrence of, and outcome following Acute Kidney Injury. Methods:The study utilised the biochemistry based AKI electronic (e)-alert system established across the Welsh National Health Service to collect data on all AKI episodes to identify changes in incidence and outcome over one calendar year (1st October 2015 and the 30th September 2016).Results: There were total of 48 457 incident AKI alerts. The highest proportion of AKI episodes was seen in the quarter of January to March (26.2%), and the lowest in the quarter of October to December (23.3%, P < .001). The same trend was seen for both community-acquired and hospital-acquired AKI sub-sets. Overall 90 day mortality for all AKI was 27.3%. In contrast with the seasonal trend in AKI occurrence, 90 day mortality after the incident AKI alert was significantly higher in the quarters of January to March and October to December compared with the quarters of April to June and July to September (P < .001) consistent with excess winter mortality reported for likely underlying diseases which precipitate AKI. Conclusions:In summary we report for the first time in a large national cohort, a seasonal variation in the incidence and outcomes of AKI. The results demonstrate distinct trends in the incidence and outcome of AKI.

show abstract

Section: Discussionmentioning

confidence: 99%

Seasonal pattern of incidence and outcome of Acute Kidney Injury: A national study of Welsh AKI electronic alerts

et al. 2017

View full text Add to dashboard Cite

show abstract

“…xcess winter mortality has been reported in medical journals for about 150 years, 1 and most countries suffer from 5% to 30% excess winter mortality. 2 However, there still remains much debate with regard to why certain countries experience dramatically higher rates of seasonal mortality than others.…”

mentioning

confidence: 99%

Excess winter mortality in Europe: a cross country analysis identifying key risk factors

Healy

2003

Journal of Epidemiology & Community Health

529

389

View full text Add to dashboard Cite

Objective: Much debate remains regarding why certain countries experience dramatically higher winter mortality. Potential causative factors other than cold exposure have rarely been analysed. Comparatively less research exists on excess winter deaths in southern Europe. Multiple time series data on a variety of risk factors are analysed against seasonal-mortality patterns in 14 European countries to identify key relations Subjects and setting: Excess winter deaths (all causes), 1988-97, EU-14. Design: Coefficients of seasonal variation in mortality are calculated for EU-14 using monthly mortality data. Comparable, longitudinal datasets on risk factors pertaining to climate, macroeconomy, health care, lifestyle, socioeconomics, and housing were also obtained. Poisson regression identifies seasonality relations over time. Results: Portugal suffers from the highest rates of excess winter mortality (28%, CI = 25% to 31%) followed jointly by Spain (21%, CI = 19% to 23%), and Ireland (21%, CI = 18% to 24%). Cross country variations in mean winter environmental temperature (regression coefficient (b) = 0.27), mean winter relative humidity (b = 0.54), parity adjusted per capita national income (b = 1.08), per capita health expenditure (b = 21.19), rates of income poverty (b = 20.47), inequality (b = 0.97), deprivation (b = 0.11), and fuel poverty (b = 0.44), and several indicators of residential thermal standards are found to be significantly related to variations in relative excess winter mortality at the 5% level. The strong, positive relation with environmental temperature and strong negative relation with thermal efficiency indicate that housing standards in southern and western Europe play strong parts in such seasonality. Conclusions: High seasonal mortality in southern and western Europe could be reduced through improved protection from the cold indoors, increased public spending on health care, and improved socioeconomic circumstances resulting in more equitable income distribution.

show abstract

“…Although the existence of patterns between consecutive integer ages was quickly acknowledged and internalised by statistics and the actuarial literature, considering fractional age assumptions and/or continuous survival models (Hoem, 1984;Pascariu, 2018), the prevalence of seasonality patterns in death statistics has been almost forgotten (avoided) in this literature (Richards et al, 2020, is an exception), despite it being well-documented in the demographic, epidemiological and sociological literatures (e.g. Foster et al, 1998;Grant et al, 2017;Healy, 2003;Rau, 2007), as far back as the mid-19th century (Guy, 1858;Nature, 1874). The question is to what extend the death seasonality patterns impact on the sub-annual distributions of mortality risks after taking into account the seasonality of other demographic vital events (birth dates and migration flows) and ageing effects.…”

Section: Introductionmentioning

confidence: 99%

Estimation of the Combined Effects of Ageing and Seasonality on Mortality Risk: An Application to Spain

Pavía

Lledó

2022

Journal of the Royal Statistical Society Series A: Statistics in Society

View full text Add to dashboard Cite

Despite the overwhelming evidence that shows the persistence of intra-annual variations on demographic events (deaths, birth dates and migration flows), life tables are computed and provided on an annual basis. This paper develops a new estimator for estimating sub-annual death rates that, considering the exact moment of occurrence (exact age and day) of events, concurrently accounts for ageing and calendar fluctuations. This paper also shows how modelling the intra-annual variations of death rates, through specific seasonal-ageing indexes, can be used as a tool for constructing new sub-annual tables from annual tables. This new methodology is exemplified using a real database of Spain made up of 186 million demographic events (1.5 million of which are deaths), from which seasonal-ageing indexes are estimated and conclusions drawn. First, seasonal effects are, as a rule, stronger than ageing effects. For a given integer age, season has a higher impact on increasing or decreasing the average risk of death at that age than the actual age of the exposed-to-risk. Second, the intensity of the effects varies among seasons and age-quarters. Third, neither seasonal nor ageing effects are age-stationary.

show abstract

On the Annual Fluctuations in the Number of Deaths from Various Diseases, Compared with Like Fluctuations in Crime, and in Other Events Within and Beyond the Control of the Human Will

Cited by 11 publications

References 0 publications

Seasonal pattern of incidence and outcome of Acute Kidney Injury: A national study of Welsh AKI electronic alerts

Seasonal pattern of incidence and outcome of Acute Kidney Injury: A national study of Welsh AKI electronic alerts

Excess winter mortality in Europe: a cross country analysis identifying key risk factors

Estimation of the Combined Effects of Ageing and Seasonality on Mortality Risk: An Application to Spain

Contact Info

Product

Resources

About