Statistical Studies of Heart Diseases: I. Heart Diseases and Allied Causes of Death in Relation to Age Changes in the Population

1948 ◽  
Vol 63 (17) ◽  
pp. 537 ◽  
Author(s):  
I. M. Moriyama ◽  
Mary Gover
Keyword(s):  
Causes Of Death ◽  
Heart Diseases ◽  
Age Changes ◽  
Statistical Studies

scholarly journals Redistribution of heart failure deaths using two methods: linkage of hospital records with death certificate data and multiple causes of death data

2019 ◽  
Vol 35 (5) ◽  
Author(s):  
Ana Luiza Bierrenbach ◽  
Gizelton Pereira Alencar ◽  
Cátia Martinez ◽  
Maria de Fátima Marinho de Souza ◽  
Gabriela Moreira Policena ◽  
...  
Keyword(s):  
Heart Failure ◽  
Causes Of Death ◽  
Kidney Diseases ◽  
Heart Diseases ◽  
National Study ◽  
Mortality Data ◽  
Multiple Causes Of Death ◽  
Underlying Causes ◽  
Garbage Code ◽  
Multiple Causes

Heart failure is considered a garbage code when assigned as the underlying cause of death. Reassigning garbage codes to plausible causes reduces bias and increases comparability of mortality data. Two redistribution methods were applied to Brazilian data, from 2008 to 2012, for decedents aged 55 years and older. In the multiple causes of death method, heart failure deaths were redistributed based on the proportion of underlying causes found in matched deaths that had heart failure listed as an intermediate cause. In the hospitalization data method, heart failure deaths were redistributed based on data from the decedents’ corresponding hospitalization record. There were 123,269 (3.7%) heart failure deaths. The method with multiple causes of death redistributed 25.3% to hypertensive heart and kidney diseases, 22.6% to coronary heart diseases and 9.6% to diabetes. The total of 41,324 heart failure deaths were linked to hospitalization records. Heart failure was listed as the principal diagnosis in 45.8% of the corresponding hospitalization records. For those, no redistribution occurred. For the remaining ones, the hospitalization data method redistributed 21.2% to a group with other (non-cardiac) diseases, 6.5% to lower respiratory infections and 9.3% to other garbage codes. Heart failure is a frequently used garbage code in Brazil. We used two redistribution methods, which were straightforwardly applied but led to different results. These methods need to be validated, which can be done in the wake of a recent national study that will investigate a big sample of hospital deaths with garbage codes listed as underlying causes.

scholarly journals Direct causes of death in Japanese patients with hypopituitarism as analyzed from a nation-wide autopsy database

2004 ◽  
pp. 149-152 ◽  
Author(s):  
H Kaji ◽  
K Chihara
Keyword(s):  
Relative Frequency ◽  
Causes Of Death ◽  
Matched Control ◽  
Heart Diseases ◽  
Japanese Patients ◽  
Control Population ◽  
Term Care ◽  
Age And Gender ◽  
And Gender ◽  
Matched Control Population

OBJECTIVES: The direct causes of death in Japanese patients with hypopituitarism remain unclear. In this study, the direct causes of death were investigated and compared between Japanese patients with hypopituitarism from a nation-wide autopsy database and an age- and gender-matched control population from national reports. SUBJECTS: Three hundred and ninety-one subjects with hypopituitarism who had died were selected from a nation-wide autopsy database (1984-1993). The ratios of each cause of death among the age- and gender-matched control population were derived from national reports. RESULTS: In subjects with hypopituitarism, an increased relative frequency of death from cerebrovascular diseases (male; 2.02 (95% confidence interval (CI) 1.45-2.82), female; 1.73 (95% CI 1.18-2.52)) was found. In particular, the relative frequency of death from cerebral hemorrhage was 4.60 (95% CI 2.95-7.17) in male and 4.80 (95% CI 2.90-7.94) in female subjects with hypopituitarism. Unexpectedly, a decreased relative frequency of death from all heart diseases (male; 0.439 (95% CI 0.277-0.696), female; 0.267 (95% CI 0.149-0.478)) was found in subjects with hypopituitarism, although there was no difference between subjects with hypopituitarism and controls in the frequency of death from ischemic heart disease. CONCLUSIONS: These results provide useful information for the long-term care of Japanese patients with hypopituitarism.

scholarly journals Mortality Cause in Goldsmith Workers of Bangladesh: Findings From Verbal Autopsy

2021 ◽  
Author(s):  
Fahmida Afroz Khan ◽  
Md. Khalequzzaman ◽  
Mohammad Tanvir Islam ◽  
Ataur Rahman ◽  
Shahrin Emdad Rayna ◽  
...  
Keyword(s):  
Life Expectancy ◽  
Cause Of Death ◽  
Verbal Autopsy ◽  
Causes Of Death ◽  
Heart Diseases ◽  
Control Program ◽  
Ischemic Heart ◽  
World Health ◽  
Average Life Expectancy ◽  
Health Organization

Abstract Background: Information on the mortality causes of goldsmith workers in Bangladesh is very limited. This study was conducted to find out the causes of death in this group of population.Methods: The study subject was deceased goldsmith workers where face-to-face interviews were conducted with the family members who were present during the deceased's illness preceding death. A World Health Organization recommended questionnaire was adapted to conduct 20 deceased goldsmith workers' verbal autopsy. Causes of death were determined by reviewing the outcomes of the interviews by the expert physicians.Results: The mean age of the goldsmith workers at death was 59.2 ± 9.3 years. Among the deceased goldsmith workers, 70.0% were smokers, and 50.0% of them were alcohol consumers. Cardiovascular diseases (CVD) were the most common immediate and underlying cause of death (55.0% and 45.0%, respectively). Acute ischemic heart disease was the single most common (30.0%) immediate cause of death among the deceased goldsmith workers, whereas, for underlying causes of death, it was both acute and chronic ischemic heart diseases (35.0%).Conclusions: The life expectancy of goldsmith workers was much lower than the average life expectancy of Bangladesh, where CVD was the common cause of death. Smoking and alcohol consumption were prevalent among the majority of the deceased goldsmith workers. Awareness of healthy lifestyles should be prioritized for a successful CVD control program for this population. Trial registration: Not applicable.

scholarly journals Hypertension and the Risk of All-Cause and Cause-Specific Mortality: An Outcome-Wide Association Study of 67 Causes of Death in the National Health Interview Survey

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Dagfinn Aune ◽  
Wentao Huang ◽  
Jing Nie ◽  
Yafeng Wang
Keyword(s):  
Heart Disease ◽  
Causes Of Death ◽  
Motor Vehicle ◽  
Heart Diseases ◽  
Uterine Cancer ◽  
Ischemic Heart ◽  
Circulatory Disease ◽  
Increased Risk ◽  
Circulatory System Diseases ◽  
All Cause Mortality

Background. Few studies have assessed the association between hypertension and risk of detailed causes of death. We investigated the association between hypertension and all-cause mortality and 67 causes of death in a large cohort. Methods. Multivariable Cox regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs) for self-reported hypertension vs. no hypertension and mortality. Adults aged ≥18 years ( n = 213798 ) were recruited in 1997-2004 and followed through December 31, 2006. Results. During 5.81 years of follow-up, 11254 deaths occurred. Self-reported hypertension vs. no hypertension was associated with increased risk of all-cause mortality ( HR = 1.25 , 95% CI: 1.19-1.31) and mortality from septicemia (HR =1.66, 1.06-2.59), other infectious parasitic diseases ( HR = 2.67 , 1.09-6.51), diabetes mellitus ( HR = 1.97 , 1.45-2.67), circulatory disease ( HR = 1.49 , 1.37-1.61), hypertensive heart disease ( HR = 3.23 , 2.00-5.20), ischemic heart disease ( HR = 1.35 , 1.23-1.49), acute myocardial infarction ( HR = 1.50 , 1.27-1.77), other chronic ischemic heart diseases ( HR = 1.35 , 1.17-1.56), all other forms of heart disease ( HR = 1.51 , 1.21-1.89), primary hypertension and renal disease ( HR = 3.11 , 1.82-5.30), cerebrovascular disease ( HR = 1.64 , 1.37-1.97), other circulatory system diseases ( HR = 1.71 , 1.09-2.69), other chronic lower respiratory diseases ( HR = 1.39 , 1.12-1.73), other chronic liver disease ( HR = 1.89 , 1.06-3.37), renal failure ( HR = 1.91 , 1.33-2.74), motor vehicle accidents ( HR = 1.60 , 1.07-2.37), and all other diseases (HR =1.30, 1.10-1.54), but with lower risk of uterine cancer ( HR = 0.37 , 95% CI: 0.15-0.90) and Alzheimer’s disease ( HR = 0.65 , 95% CI: 0.47-0.92). Conclusion. Hypertension was associated with increased risk of all-cause mortality and 17 out of 67 causes of death, with most of these being circulatory disease outcomes, however, some of the remaining associations are unlikely to be causal. Further studies are needed to clarify associations with less common causes of death and potential causality across outcomes.

scholarly journals Changes and Variations in Death Due to Senility in Japan

Healthcare ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 443
Author(s):  
Masaki Bando ◽  
Nobuyuki Miyatake ◽  
Hiroaki Kataoka ◽  
Hiroshi Kinoshita ◽  
Naoko Tanaka ◽  
...  
Keyword(s):  
Ecological Study ◽  
Causes Of Death ◽  
Heart Diseases ◽  
Malignant Neoplasm ◽  
Cerebrovascular Diseases ◽  
Elderly Individuals ◽  
Study Results ◽  
Definition Of ◽  
Medical Bills ◽  
Observation Period

Objective: The proportion of elderly individuals (≥65 years old) in Japan has markedly increased. However, the definition of senility in Japan is controversial. The aim of the present study was to investigate changes and variations in the number of deaths due to senility in Japan. Methods: Information on the number of deaths due to senility between 1995 and 2018 as well as other major causes of death was obtained from the Statistics Bureau of Japan official website. Changes and variations in the number of deaths due to senility were compared with other major causes of death in Japan. The relationships between the number of deaths due to senility and socioeconomic factors were also examined in an ecological study. Results: The number of deaths due to senility was 35.7 ± 23.2/one hundred thousand people/year during the observation period and has continued to increase. A change point was identified in 2004 by a Jointpoint regression analysis. Variations in the number of deaths due to senility, which were evaluated by a coefficient of variation, were significantly greater than those due to other major causes of death, i.e., malignant neoplasm, heart diseases, cerebrovascular diseases, and pneumonia. The number of elderly individuals (≥65 years old) (%) and medical bills per elderly subject (≥75 years old) correlated with the number of deaths due to senility. Conclusion: The number of deaths due to senility has been increasing, particularly since 2004. However, variations in the number of deaths due to senility were observed among all prefectures in Japan.

scholarly journals Short-term mortality risks among patients with non-metastatic bladder cancer

BMC Cancer ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Menghe Zhai ◽  
Chenye Tang ◽  
Ming Li ◽  
Xin Chen ◽  
Yigang Jin ◽  
...  
Keyword(s):  
Risk Factors ◽  
Bladder Cancer ◽  
Causes Of Death ◽  
Heart Diseases ◽  
Chronic Obstructive ◽  
Second Malignancies ◽  
Short Term ◽  
Obstructive Pulmonary Disease ◽  
The Us

Abstract Background Population-based analysis for the short-term non-bladder cancer related mortality among patients with non-metastatic bladder cancer is currently lacking. The objective of the current study was to assess and quantify cause of death after bladder cancer diagnosis. Methods The custom Surveillance, Epidemiology, and End Results (SEER) dataset for standardized mortality ratios (SMRs) was utilized to identify 24,074 patients who were diagnosed with nonmetastatic (M0) bladder cancer from 2014 to 2015. SMRs for causes of death were calculated. Risk factors for bladder cancer-specific mortality, competing mortality, second-cancer mortality, and noncancer mortality were determined using either multivariable Cox or competing risk regression models. Results Among all the 4179 (17.4%) deaths occurred during the follow-up period, almost half of them (44.2%) were attributed to non-bladder cancer cause, including second non-bladder cancer (10%) and other non-cancer causes (34.2%). The most common noncancer causes of death were heart diseases followed by chronic obstructive pulmonary disease. Patients had a higher risk of death from second malignancies (SMR, 1.59; 95% CI, 1.47–1.74) compared with death from first malignancies in the US general population, and also had higher risks of death from heart diseases (SMR, 1.29; 95% CI, 1.18–1.40) and chronic obstructive pulmonary disease (SMR, 1.52; 95% CI, 1.29–1.79) compared with the US general population. Additionally, some risk factors for competing second malignancies or noncancer mortality were determined, such as age, gender, marital status and treatment modalities. Conclusions Death from non-bladder cancer cause contributed to almost half of all deaths in bladder cancer survivors during the short-term follow-up period. These findings can inform medical management and assist clinicians in counseling those survivors regarding their short-term health risks.

Estimating transition coefficients for reconstructing coherent series of mortality by cause of Death

2019 ◽  
Vol 19 (3) ◽  
pp. 299-322
Author(s):  
Carlo G Camarda
Keyword(s):  
Cause Of Death ◽  
Causes Of Death ◽  
Heart Diseases ◽  
Age Groups ◽  
Medical Knowledge ◽  
Malignant Neoplasms ◽  
Classification Of Diseases ◽  
German Data

Regular revisions of the classification of diseases and the consequent disruptions of mortality series are well-known issues in long-term cause-of-death analysis. Given basic assumptions and medical knowledge about possible exchanges across causes of death in the revision years, redistribution of counts of causes of death into a new classification can be viewed as a constrained optimization problem. Penalized likelihood within a quadratic programming framework allows estimation of exchanges that vary smoothly over age groups. The approach is illustrated using both German data on malignant neoplasms and French data on heart diseases.

scholarly journals Analysis of lifetime death probability for major causes of death among residents in China

2020 ◽  
Author(s):  
Ping Yuan ◽  
Jianjun Xiang ◽  
Matthew Borg ◽  
Tiehui CHEN ◽  
Xiuquan Lin ◽  
...  
Keyword(s):  
Heart Disease ◽  
Respiratory Disease ◽  
Disease Surveillance ◽  
Regional Differences ◽  
Causes Of Death ◽  
Heart Diseases ◽  
Eastern Region ◽  
Cumulative Mortality ◽  
Death Probability ◽  
The Impact

Abstract Background: Cumulative mortality rate and cumulative mortality risk are the two commonly used indicators to measure the impact and severity of diseases. However, they are calculated during a defined life span and assume the subject does not die from other causes. This study aims to use a new indicator, lifetime death probability (LDP), to estimate the lifetime death probabilities for the top five leading causes of death in China and explore the regional differences and trends over time. Methods: LDPs were calculated using a probability additive formula and abridged life tables. Results: In 2014, LDPs for heart disease, cerebrovascular disease, malignancy, respiratory disease, and injury and poisoning were 24.4%, 23.7%, 19.2%, 15.5%, and 5.3%, respectively. The LDPs for heart disease and malignancy increased by 7.3% and 0.5%, respectively, compared to those from 2004 to 2005. In contrast, the LDPs for cerebrovascular and respiratory disease decreased by 1.0% and 3.9%, respectively, compared to those in 2004-2005. Across the eastern, central and western regions, malignancy had the highest LDP in the eastern region, cerebrovascular and heart diseases in the central region, and respiratory diseases, and injury and poisoning in the western region. Conclusions: LDP is an effective indicator for comparing health outcomes and can be applied for future disease surveillance. Heart disease and malignancy were the two most common causes of death in China, but with regional differences. There is a need to implement targeted measures to prevent diseases in different regions.

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