Death after Widow(er)hood: An Analysis of Mortality Rates up to 13 Years after Bereavement

1995 ◽  
Vol 31 (1) ◽  
pp. 35-49 ◽  
Author(s):  
Ann Bowling ◽  
Joy Windsor
Keyword(s):  
Survival Time ◽  
Excess Mortality ◽  
Mortality Rates ◽  
Proportional Hazard ◽  
Significant Excess ◽  
Risk Of Mortality ◽  
Best Fitting ◽  
Males And Females ◽  
Male Sex ◽  
Fitting Model

The mortality rates of a national random sample of 503 elderly people who were widowed in 1979 were analyzed. Over the thirteen and a quarter year period analyzed, 62 percent of the sample had died. Although earlier analyses had indicated excess mortality in the first six months of bereavement for men aged 75+, there were no further significant excess mortality rates over the thirteen and a quarter year period analyzed. The data were analyzed by fitting Cox's proportional hazard regression model to the widowed's survival time for factors predicting survival time. The best fitting model for males and females indicated that risk of mortality at each period was associated with older age, male sex, and poorer functional ability (measured in 1979). Frequency of telephone contacts as a risk factor for survival period was only significant for the younger widowed.

Long-term mortality rates and associated risk factors following primary and revision knee arthroplasty

2022 ◽  
Vol 104-B (1) ◽  
pp. 45-52
Author(s):  
Liam Zen Yapp ◽  
Nick D. Clement ◽  
Matthew Moran ◽  
Jon V. Clarke ◽  
A. Hamish R. W. Simpson ◽  
...  
Keyword(s):  
General Population ◽  
Knee Arthroplasty ◽  
Mortality Rates ◽  
Factors Associated ◽  
Revision Knee Arthroplasty ◽  
Risk Of Mortality ◽  
Increased Risk ◽  
Male Sex ◽  
Long Term Mortality

Aims The aim of this study was to determine the long-term mortality rate, and to identify factors associated with this, following primary and revision knee arthroplasty (KA). Methods Data from the Scottish Arthroplasty Project (1998 to 2019) were retrospectively analyzed. Patient mortality data were linked from the National Records of Scotland. Analyses were performed separately for the primary and revised KA cohorts. The standardized mortality ratio (SMR) with 95% confidence intervals (CIs) was calculated for the population at risk. Multivariable Cox proportional hazards were used to identify predictors and estimate relative mortality risks. Results At a median 7.4 years (interquartile range (IQR) 4.0 to 11.6) follow-up, 27.8% of primary (n = 27,474/98,778) and 31.3% of revision (n = 2,611/8,343) KA patients had died. Both primary and revision cohorts had lower mortality rates than the general population (SMR 0.74 (95% CI 0.73 to 0.74); p < 0.001; SMR 0.83 (95% CI 0.80 to 0.86); p < 0.001, respectively), which persisted for 12 and eighteight years after surgery, respectively. Factors associated with increased risk of mortality after primary KA included male sex (hazard ratio (HR) 1.40 (95% CI 1.36 to 1.45)), increasing socioeconomic deprivation (HR 1.43 (95% CI 1.36 to 1.50)), inflammatory polyarthropathy (HR 1.79 (95% CI 1.68 to 1.90)), greater number of comorbidities (HR 1.59 (95% CI 1.51 to 1.68)), and periprosthetic joint infection (PJI) requiring revision (HR 1.92 (95% CI 1.57 to 2.36)) when adjusting for age. Similarly, male sex (HR 1.36 (95% CI 1.24 to 1.49)), increasing socioeconomic deprivation (HR 1.31 (95% CI 1.12 to 1.52)), inflammatory polyarthropathy (HR 1.24 (95% CI 1.12 to 1.37)), greater number of comorbidities (HR 1.64 (95% CI 1.33 to 2.01)), and revision for PJI (HR 1.35 (95% 1.18 to 1.55)) were independently associated with an increased risk of mortality following revision KA when adjusting for age. Conclusion The SMR of patients undergoing primary and revision KA was lower than that of the general population and remained so for several years post-surgery. However, approximately one in four patients undergoing primary and one in three patients undergoing revision KA died within tenten years of surgery. Several patient and surgical factors, including PJI, were associated with the risk of mortality within ten years of primary and revision surgery. Cite this article: Bone Joint J 2022;104-B(1):45–52.

scholarly journals Gender features of age-related risk of mortality associated with nervous diseases

2014 ◽  
Vol 95 (5) ◽  
pp. 703-705
Author(s):  
A K Mamedbeyli
Keyword(s):  
Mortality Rate ◽  
Age Groups ◽  
Mortality Rates ◽  
Situational Factors ◽  
Age Related ◽  
Risk Of Mortality ◽  
Related Risk ◽  
Males And Females ◽  
Gender Features ◽  
Overall Mortality

Aim. To explore the hypothesis of equal age-related risk of mortality associated with nervous diseases in females and males. Methods. Descriptive statistics, qualitative analysis were performed. 13 580 medical certificates of cause of death, all related to nervous diseases (all classes of ICD-10) were analyzed. Results. The mortality rate increased with age. Age-specific mortality rates had gender differences. In most ages (20-24, 30-34, 45-49, 50-54, 55-59, 65-69), mortality rate was higher in males, at the age of 5-9, 15-19, 60-64, 70 and over - in females. Death relative risk in males of different age groups (compared to the similar rates in females) varied between 0.39 (in the age group of 5-9 years) to 5.93 (in patients aged 20-24 years). Overall, the level of mortality associated with nervous diseases was 130.02±1.69 per 100 000 in males and 163.41±1.86 per 100 000 in females, so, overall mortality rate was 1.25 times higher in females. After adjustment for age differences was performed, no significant differences were found between the groups (146.74 and 144.16 per 100 000 respectively for males and females). Conclusion. Gender features of age-related risk of mortality associated with nervous diseases were characterized by multidirectional alterations of mortality rates and share of nervous diseases among all reasons of mortality. These features were mainly caused by situational factors (different age structure and overall mortality level for males and females), and vanished after adjustment.

scholarly journals Excess mortality during the COVID-19 pandemic in Israel, March–November 2020: when, where, and for whom?

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Ziona Haklai ◽  
Miriam Aburbeh ◽  
Nehama Goldberger ◽  
Ethel-Sherry Gordon
Keyword(s):  
Excess Mortality ◽  
Average Rate ◽  
Total Mortality ◽  
Mortality Rates ◽  
Significant Excess ◽  
Arab Population ◽  
Susceptible Population ◽  
Demographic Groups ◽  
Arab Sector ◽  
Official Data

Abstract Background Excess all-cause mortality has been used in many countries as an estimate of mortality effects from COVID-19. What was the excess mortality in Israel in 2020 and when, where and for whom was this excess? Methods Mortality rates between March to November 2020 for various demographic groups, cities, month and week were compared with the average rate during 2017–2019 for the same groups or periods. Results Total mortality rates for March–November were significantly higher by 6% in 2020, than the average of 2017–2019, 14% higher among the Arab population and 5% among Jews and Others. Significantly higher monthly mortality rates were found in August, September and October by 11%, 13% and 19%, respectively, among Jews and Others, and by 19%, 64% and 40% in the Arab population. Excess mortality was significant only at older ages, 7% higher rates at ages 65–74 and 75–84 and 8% at ages 85 and above, and greater for males than females in all ages and population groups. Interestingly, mortality rates decreased significantly among the younger population aged under 25. The cities with most significant excess mortality were Ramla (25% higher), Bene Beraq (24%), Bat Yam (15%) and Jerusalem (8%). Conclusion Israel has seen significant excess mortality in August–October 2020, particularly in the Arab sector. The excess mortality in March–November was statistically significant only at older ages, over 65. It is very important to protect this susceptible population from exposure and prioritize them for inoculations. Lockdowns were successful in lowering the excess mortality. The excess mortality is similar to official data on COVID-19 deaths.

165 Effects of Digestible Lysine Level on Growth Performance and Economics of Grow-finish Pigs

2021 ◽  
Vol 99 (Supplement_1) ◽  
pp. 58-59
Author(s):  
Larissa L Becker ◽  
Emily E Scholtz ◽  
Joel M DeRouchey ◽  
Mike D Tokach ◽  
Jason C Woodworth ◽  
...  
Keyword(s):  
Phase 1 ◽  
Information Criterion ◽  
Response Curves ◽  
Phase 3 ◽  
Ileal Digestibility ◽  
Distillers Dried Grains ◽  
Feed Cost ◽  
Best Fitting ◽  
Dietary Treatments ◽  
Fitting Model

Abstract A total of 2,124 barrows and gilts (PIC 1050′DNA 600, initially 48.9 kg) were used in a 32-d study to determine the optimal dietary standardized ileal digestibility (SID) Lys level in a commercial setting. Pigs were randomly allotted to 1 of 5 dietary treatments with 24 to 27 pigs/pen and 16 replications/treatment. Similar number of barrows and gilts were placed in each pen. Diets were fed over 3 phases (48.9 to 58.6, 58.6 to 70.9, and 70.9 to 80.8 kg respectively). Dietary treatments were corn-soybean meal-based and contained 10 (phase 1 and 2) or 5% (phase 3) distillers dried grains with solubles. Diets were formulated to 85, 95, 103, 110, or 120% of the current Pig Improvement Company (PIC, Hendersonville, TN) SID Lys gilt recommendations with phase 1 SID Lys levels of 0.90, 1.01, 1.09, 1.17 and 1.27%, phase 2 levels of 0.79, 0.87, 0.94, 1.03, and 1.10%, and phase 3 levels of 0.71, 0.78, 0.85, 0.92, and 0.99%, respectively. Dose response curves were evaluated using linear (LM), quadratic polynomial (QP), broken-line linear (BLL), and broken-line quadratic (BLQ) models. For each response variable, the best-fitting model was selected using the Bayesian information criterion. Overall (d 0 to 32), increasing SID Lys increased (linear, P&lt; 0.001) BW, ADG, G:F, Lys intake/d, and Lys intake/kg of gain. Modeling margin over feed cost (MOFC), BLL and QP estimated the requirement at 105.8% and 113.7% respectively. In summary, while growth increased linearly up to 120% of the PIC current feeding level, the optimal MOFC was 106% to 114% depending on the model used.

Genetic and Environmental Influences of Dietary Indices in a UK Female Twin Cohort

2020 ◽  
Vol 23 (6) ◽  
pp. 330-337
Author(s):  
Olatz Mompeo ◽  
Rachel Gibson ◽  
Paraskevi Christofidou ◽  
Tim D. Spector ◽  
Cristina Menni ◽  
...  
Keyword(s):  
Healthy Eating ◽  
Menopausal Status ◽  
Healthy Eating Index ◽  
Healthy Diet ◽  
Nutritional Epidemiology ◽  
Best Fitting ◽  
Heritability Estimates ◽  
Fitting Model ◽  
Dietary Indices ◽  
Health Parameters

AbstractA healthy diet is associated with the improvement or maintenance of health parameters, and several indices have been proposed to assess diet quality comprehensively. Twin studies have found that some specific foods, nutrients and food patterns have a heritable component; however, the heritability of overall dietary intake has not yet been estimated. Here, we compute heritability estimates of the nine most common dietary indices utilized in nutritional epidemiology. We analyzed 2590 female twins from TwinsUK (653 monozygotic [MZ] and 642 dizygotic [DZ] pairs) who completed a 131-item food frequency questionnaire (FFQ). Heritability estimates were computed using structural equation models (SEM) adjusting for body mass index (BMI), smoking status, Index of Multiple Deprivation (IMD), physical activity, menopausal status, energy and alcohol intake. The AE model was the best-fitting model for most of the analyzed dietary scores (seven out of nine), with heritability estimates ranging from 10.1% (95% CI [.02, .18]) for the Dietary Reference Values (DRV) to 42.7% (95% CI [.36, .49]) for the Alternative Healthy Eating Index (A-HEI). The ACE model was the best-fitting model for the Healthy Diet Indicator (HDI) and Healthy Eating Index 2010 (HEI-2010) with heritability estimates of 5.4% (95% CI [−.17, .28]) and 25.4% (95% CI [.05, .46]), respectively. Here, we find that all analyzed dietary indices have a heritable component, suggesting that there is a genetic predisposition regulating what you eat. Future studies should explore genes underlying dietary indices to further understand the genetic disposition toward diet-related health parameters.

scholarly journals Healthcare-related impact of gout in hospitalized patients in Spain

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Diego Benavent ◽  
Diana Peiteado ◽  
María Ángeles Martinez-Huedo ◽  
María Hernandez-Hurtado ◽  
Alejandro Balsa ◽  
...  
Keyword(s):  
Heart Failure ◽  
Kidney Disease ◽  
Mortality Rates ◽  
Progressive Increase ◽  
Cerebrovascular Diseases ◽  
Hospitalized Patients ◽  
Data Set ◽  
Private Hospitals ◽  
Risk Of Mortality ◽  
General Mortality

AbstractTo analyze the epidemiology, clinical features and costs of hospitalized patients with gout during the last decade in Spain. Retrospective observational study based on data from the Minimum Basic Data Set (MBDS) from the Spanish National Health Service database. Patients ≥ 18 years with any gout diagnosis at discharge who had been admitted to public or private hospitals between 2005 and 2015 were included. Patients were divided in two periods: p1 (2005–2010) and p2 (2011–2015) to compare the number of hospitalizations, mean costs and mortality rates. Data from 192,037 patients with gout was analyzed. There was an increase in the number of hospitalized patients with gout (p < 0.001). The more frequent comorbidities were diabetes (27.6% of patients), kidney disease (26.6%) and heart failure (19.3%). Liver disease (OR 2.61), dementia (OR 2.13), cerebrovascular diseases (OR 1.57), heart failure (OR 1.41), and kidney disease (OR 1.34) were associated with a higher mortality risk. Women had a lower risk of mortality than men (OR 0.85). General mortality rates in these hospitalized patients progressively increased over the years (p < 0.001). In addition, costs gradually rose, presenting a significant increase in p2 even after adjusting for inflation (p = 0.001). A progressive increase in hospitalizations, mortality rates and cost in hospitalized patients with gout was observed. This harmful trend in a preventable illness highlights the need for change and the search for new healthcare strategies.

Manual occupations with high all-cause mortality: The contribution of socioeconomic and occupational characteristics

2020 ◽  
pp. 140349482096065
Author(s):  
Hanna Rinne ◽  
Mikko Laaksonen
Keyword(s):  
High Mortality ◽  
Excess Mortality ◽  
Proportional Hazard ◽  
Individual Level ◽  
Cox Proportional Hazard ◽  
Occupational Characteristics ◽  
Study Population ◽  
Cox Proportional Hazard Regression ◽  
Year 2000

Aims: Most high mortality-risk occupations are manual occupations. We examined to what extent high mortality of such occupations could be explained by education, income, unemployment or industry and whether there were differences in these effects among different manual occupations. Methods: We used longitudinal individual-level register-based data, the study population consisting of employees aged 30–64 at the end of the year 2000 with the follow-up period 2001–2015. We used Cox proportional hazard regression models in 31 male and 11 female occupations with high mortality. Results: There were considerable differences between manual occupations in how much adjusting for education, income, unemployment and industry explained the excess mortality. The variation was especially large among men: controlling for these variables explained over 50% of the excess mortality in 23 occupations. However, in some occupations the excess mortality even increased in relation to unadjusted mortality. Among women, these variables explained a varying proportion of the excess mortality in every occupation. After adjustment of all variables, mortality was no more statistically significantly higher than average in 14 occupations among men and 2 occupations among women. Conclusions: The high mortality in manual occupations was mainly explained by education, income, unemployment and industry. However, the degree of explanation varied widely between occupations, and considerable variation in mortality existed between manual occupations after controlling for these variables. More research is needed on other determinants of mortality in specific high-risk occupations.

scholarly journals Incidence, Characteristics, and Outcome of COVID-19 in Adults on Kidney Replacement Therapy: A Regionwide Registry Study

2020 ◽  
pp. ASN.2020060875
Author(s):  
Johan De Meester ◽  
Dirk De Bacquer ◽  
Maarten Naesens ◽  
Bjorn Meijers ◽  
Marie M. Couttenye ◽  
...  
Keyword(s):  
General Population ◽  
Excess Mortality ◽  
Mortality Rates ◽  
Incidence Rates ◽  
Registry Study ◽  
Additional Risk ◽  
Mortality Burden ◽  
Kidney Replacement Therapy ◽  
Expected Mortality ◽  
Chronic Comorbidities

BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection disproportionally affects frail, elderly patients and those with multiple chronic comorbidities. Whether patients on RRT have an additional risk because of their specific exposure and complex immune dysregulation is controversial.MethodsTo describe the incidence, characteristics, and outcomes of SARS-CoV-2 infection, we conducted a prospective, multicenter, region-wide registry study in adult patients on RRT versus the general population from March 2 to May 25, 2020. This study comprised all patients undergoing RRT in the Flanders region of Belgium, a country that has been severely affected by coronavirus disease 2019 (COVID-19).Results At the end of the epidemic wave, crude and age-standardized cumulative incidence rates of SARS-CoV-2 infection were 5.3% versus 2.5%, respectively, among 4297 patients on hemodialysis, and 1.4% versus 1.6%, respectively, among 3293 patients with kidney transplants (compared with 0.6% in the general population). Crude and age-standardized cumulative mortality rates were 29.6% versus 19.9%, respectively, among patients on hemodialysis, and 14.0% versus 23.0%, respectively, among patients with transplants (compared with 15.3% in the general population). We found no excess mortality in the hemodialysis population when compared with mean mortality rates during the same 12-week period in 2015–2019 because COVID-19 mortality was balanced by lower than expected mortality among uninfected patients. Only 0.18% of the kidney transplant population died of SARS-CoV-2 infection.ConclusionsMortality associated with SARS-CoV-2 infection is high in patients on RRT. Nevertheless, the epidemic’s overall effect on the RRT population remained remarkably limited in Flanders. Calculation of excess mortality and age standardization provide a more reliable picture of the mortality burden of COVID-19 among patients on RRT.

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