Seasonal variation of Pacific Northern Fulmar bycatch: Implications for age and sex‐specific mortality

2020 ◽  
Author(s):  
Jessie Beck ◽  
Pamela E. Michael ◽  
Michelle Hester ◽  
Hannahrose M. Nevins ◽  
Erica Donnelly‐Greenan ◽  
...  
Rheumatology ◽  
2020 ◽  
Vol 60 (1) ◽  
pp. 207-216
Author(s):  
Irene E M Bultink ◽  
Frank de Vries ◽  
Ronald F van Vollenhoven ◽  
Arief Lalmohamed

Abstract Objectives We wanted to estimate the magnitude of the risk from all-cause, cause-specific and sex-specific mortality in patients with SLE and relative risks compared with matched controls and to evaluate the influence of exposure to medication on risk of mortality in SLE. Methods We conducted a population-based cohort study using the Clinical Practice Research Datalink, Hospital Episode Statistics and national death certificates (from 1987 to 2012). Each SLE patient (n = 4343) was matched with up to six controls (n = 21 780) by age and sex. Cox proportional hazards models were used to estimate overall and cause-specific mortality rate ratios. Results Patients with SLE had a 1.8-fold increased mortality rate for all-cause mortality compared with age- and sex-matched subjects [adjusted hazard ratio (HR) = 1.80, 95% CI: 1.57, 2.08]. The HR was highest in patients aged 18–39 years (adjusted HR = 4.87, 95% CI: 1.93, 12.3). Mortality rates were not significantly different between male and female patients. Cumulative glucocorticoid use raised the mortality rate, whereas the HR was reduced by 45% with cumulative low-dose HCQ use. Patients with SLE had increased cause-specific mortality rates for cardiovascular disease, infections, non-infectious respiratory disease and for death attributable to accidents or suicide, whereas the mortality rate for cancer was reduced in comparison to controls. Conclusion British patients with SLE had a 1.8-fold increased mortality rate compared with the general population. Glucocorticoid use and being diagnosed at a younger age were associated with an increased risk of mortality. HCQ use significantly reduced the mortality rate, but this association was found only in the lowest cumulative dosage exposure group.


2020 ◽  
Vol 117 (18) ◽  
pp. 9696-9698 ◽  
Author(s):  
Jennifer Beam Dowd ◽  
Liliana Andriano ◽  
David M. Brazel ◽  
Valentina Rotondi ◽  
Per Block ◽  
...  

Governments around the world must rapidly mobilize and make difficult policy decisions to mitigate the coronavirus disease 2019 (COVID-19) pandemic. Because deaths have been concentrated at older ages, we highlight the important role of demography, particularly, how the age structure of a population may help explain differences in fatality rates across countries and how transmission unfolds. We examine the role of age structure in deaths thus far in Italy and South Korea and illustrate how the pandemic could unfold in populations with similar population sizes but different age structures, showing a dramatically higher burden of mortality in countries with older versus younger populations. This powerful interaction of demography and current age-specific mortality for COVID-19 suggests that social distancing and other policies to slow transmission should consider the age composition of local and national contexts as well as intergenerational interactions. We also call for countries to provide case and fatality data disaggregated by age and sex to improve real-time targeted forecasting of hospitalization and critical care needs.


Author(s):  
Karin Modig ◽  
Anders Ahlbom ◽  
Marcus Ebeling

Abstract Background Sweden has one of the highest numbers of COVID-19 deaths per inhabitant globally. However, absolute death counts can be misleading. Estimating age- and sex-specific mortality rates is necessary in order to account for the underlying population structure. Furthermore, given the difficulty of assigning causes of death, excess all-cause mortality should be estimated to assess the overall burden of the pandemic. Methods By estimating weekly age- and sex-specific death rates during 2020 and during the preceding five years, our aim is to get more accurate estimates of the excess mortality attributed to COVID-19 in Sweden, and in the most affected region Stockholm. Results Eight weeks after Sweden’s first confirmed case, the death rates at all ages above 60 were higher than for previous years. Persons above age 80 were disproportionally more affected, and men suffered greater excess mortality than women in ages up to 75 years. At older ages, the excess mortality was similar for men and women, with up to 1.5 times higher death rates for Sweden and up to 3 times higher for Stockholm. Life expectancy at age 50 declined by less than 1 year for Sweden and 1.5 years for Stockholm compared to 2019. Conclusions The excess mortality has been high in older ages during the pandemic, but it remains to be answered if this is because of age itself being a prognostic factor or a proxy for comorbidity. Only monitoring deaths at a national level may hide the effect of the pandemic on the regional level.


2019 ◽  
Vol 18 (1) ◽  
Author(s):  
Ali Kiadaliri ◽  
Margarita Moreno-Betancur ◽  
Aleksandra Turkiewicz ◽  
Martin Englund

Abstract Background Gout is the most common inflammatory arthritis with a rising prevalence around the globe. While educational inequalities in incidence and prevalence of gout have been reported, no previous study investigated educational inequality in mortality among people with gout. The aim of this study was to assess absolute and relative educational inequalities in all-cause and cause-specific mortality among people with gout in comparison with an age- and sex-matched cohort free of gout in southern Sweden. Methods We identified all residents aged ≥30 years of Skåne region with doctor-diagnosed gout (ICD-10 code M10, n = 24,877) during 1998–2013 and up to 4 randomly selected age- and sex-matched comparators free of gout (reference cohort, n = 99,504). These were followed until death, emigration, or end of 2014. We used additive hazards models and Cox regression adjusted for age, sex, marital status, and country of birth to estimate slope and relative indices of inequality (SII/RII). Three cause-of-death attribution approaches were considered for RII estimation: “underlying cause”, “any mention”, and “weighted multiple-cause”. Results Gout patients with the lowest education had 1547 (95% CI: 1001, 2092) more deaths per 100,000 person-years compared with those with the highest education. These absolute inequalities were larger than in the reference population (1255, 95% CI: 1038, 1472). While the contribution of cardiovascular (cancer) mortality to these absolute inequalities was greater (smaller) in men with gout than those without, the opposite was seen among women. Relative inequality in all-cause mortality was smaller in gout (RII 1.29 [1.18, 1.41]) than in the reference population (1.46 [1.38, 1.53]). The weighted multiple-cause approach generally led to larger RIIs than the underlying cause approach. Conclusions Our register-based matched cohort study showed that low level of education was associated with increased mortality among gout patients. Although the magnitude of relative inequality was smaller in people with gout compared with those without, the absolute inequalities were greater reflecting a major mortality burden among those with lower education.


2000 ◽  
Vol 16 (1) ◽  
pp. 201-219 ◽  
Author(s):  
James L. Bodkin ◽  
Alexander M. Burdin ◽  
Dmitry A. Ryazanov

2020 ◽  
Vol 132 (21-22) ◽  
pp. 685-689 ◽  
Author(s):  
Martin Posch ◽  
Peter Bauer ◽  
Alexander Posch ◽  
Franz König

SummaryWe analyze the age and sex distribution of the reported COVID-19 deaths in Austria. In accordance with international studies, the Austrian data also suggests that the risk of death increases substantially with age. The observed age dependency of the proportions of registered COVID-19 deaths in relation to the population sizes in the age groups is approximately exponential, similar to the age dependency of the general age specific mortality rate. Furthermore, we compare the general age specific mortality rate in Austria with the estimates of the SARS-CoV‑2 infection fatality rate by Ferguson et al. (2020). The parallels to the general age specific mortality rates do not imply that COVID-19 does not pose an additional risk. On the contrary, it follows from the structure and magnitude of the infection fatality rate that it is substantial, especially for higher age groups. However, since in many cases persons with severe pre-existing conditions are affected, it is not yet possible to estimate what effects COVID-19 will have on life expectancy.


Platelets ◽  
2017 ◽  
Vol 29 (3) ◽  
pp. 312-315 ◽  
Author(s):  
Marialaura Bonaccio ◽  
Augusto Di Castelnuovo ◽  
Simona Costanzo ◽  
Amalia De Curtis ◽  
Maria Benedetta Donati ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Valentina Gallo ◽  
Paolo Chiodini ◽  
Dario Bruzzese ◽  
Elias Kondilis ◽  
Dan Howdon ◽  
...  

AbstractComparison of COVID-19 trends in space and over time is essential to monitor the pandemic and to indirectly evaluate non-pharmacological policies aimed at reducing the burden of disease. Given the specific age- and sex- distribution of COVID-19 mortality, the underlying sex- and age-distribution of populations need to be accounted for. The aim of this paper is to present a method for monitoring trends of COVID-19 using adjusted mortality trend ratios (AMTRs). Age- and sex-mortality distribution of a reference European population (N = 14,086) was used to calculate age- and sex-specific mortality rates. These were applied to each country to calculate the expected deaths. Adjusted Mortality Trend Ratios (AMTRs) with 95% confidence intervals (C.I.) were calculated for selected European countries on a daily basis from 17th March 2020 to 29th April 2021 by dividing observed cumulative mortality, by expected mortality, times the crude mortality of the reference population. These estimated the sex- and age-adjusted mortality for COVID-19 per million population in each country. United Kingdom experienced the highest number of COVID-19 related death in Europe. Crude mortality rates were highest Hungary, Czech Republic, and Luxembourg. Accounting for the age-and sex-distribution of the underlying populations with AMTRs for each European country, four different patterns were identified: countries which experienced a two-wave pandemic, countries with almost undetectable first wave, but with either a fast or a slow increase of mortality during the second wave; countries with consistently low rates throughout the period. AMTRs were highest in Eastern European countries (Hungary, Czech Republic, Slovakia, and Poland). Our methods allow a fair comparison of mortality in space and over time. These might be of use to indirectly estimating the efficacy of non-pharmacological health policies. The authors urge the World Health Organisation, given the absence of age and sex-specific mortality data for direct standardisation, to adopt this method to estimate the comparative mortality from COVID-19 pandemic worldwide.


2020 ◽  
Author(s):  
Valentina Gallo ◽  
Paolo Chiodini ◽  
Dario Bruzzese ◽  
Elias Kondilis ◽  
Daniel Howdon ◽  
...  

Background Since COVID19 was declared a pandemic, attempts have been made to monitor trends over time and to compare countries and regions. Insufficient testing for COVID19 underestimates the incidence and inflates the case/fatality proportion. Given the age and sex distribution of morbidity and mortality from COVID19, the underlying sex and age distribution of a population needs to be accounted for. The aim of this paper is to present a method for monitoring trends of COVID19 using adjusted mortality trend ratios (AMTR). Methods Age and sex mortality distribution of a reference population composed of the first 14,086 fatalities which occurred before the end of March and were reported in Europe by some countries were used to calculate age and sex specific mortality rates per 1,000,000 population. These were applied to each country population to calculate the expected deaths. Adjusted Mortality Trend Ratios (AMTRs) with 95% confidence intervals (C.I.) were calculated for selected European countries from 17/03/2020 to 22/06/2020 by dividing observed cumulative mortality, by expected mortality times the crude mortality of the reference population. These estimated the sex and age adjusted mortality for COVID19 per million population in each country. Results The cumulative mortality from COVID19, the crude mortality rates, and the AMTRs were calculated for each country and compared. United Kingdom, Italy, France and Spain registered the highest mortality in Europe. On 22/06/2020 in Europe the total mortality rate from COVID-19 was 352 per 1,000,000 inhabitants; and it was highest in Belgium (850 per 1,000,000 inhabitants) followed by Spain, UK, Italy, Sweden and France. When accounting for the underlying age and sex structure of each country, Belgium remained the single country experiencing the highest AMTR of 929 per million inhabitants on 22/06/2020; however Ireland (which had a CMR in line with the total European population) emerged as having experienced a much more important impact of COVID19 mortality with an AMTR of 550/million on 22/06/2020, higher than Sweden and Italy. Conclusions In understanding and managing the pandemic of COVID19, comparable international data is a priority. Our methods allow a fair comparison of mortality in space and over time. The authors urge the WHO, given the absence of age and sex-specific mortality data for direct standardisation, to adopt this method to estimate the comparative mortality from COVID19 pandemic worldwide.


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