Mortality among Guarani Indians in Southeastern and Southern Brazil

Worldwide, indigenous peoples display a high burden of disease, expressed by profound health inequalities in comparison to non-indigenous populations. This study describes mortality patterns among the Guarani in Southern and Southeastern Brazil, with a focus on health inequalities. The Guarani population structure is indicative of high birth and death rates, low median age and low life expectancy at birth. The crude mortality rate (crude MR = 5.0/1,000) was similar to the Brazilian national rate, but the under-five MR (44.5/1,000) and the infant mortality rate (29.6/1,000) were twice the corresponding MR in the South and Southeast of Brazil. The proportion of post-neonatal infant deaths was 83.3%, 2.4 times higher than general population. The proportions of ill-defined (15.8%) and preventable causes (51.6%) were high. The principal causes of death were respiratory (40.6%) and infectious and parasitic diseases (18.8%), suggesting precarious living conditions and deficient health services. There is a need for greater investment in primary care and interventions in social determinants of health in order to reduce the health inequalities.

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Delaware’s 1999-2017 Leading Causes of Death Information Illustrates Its Obesity and Obesity-Related Life-Limiting Disease Burdens

Research in Health Science ◽

10.22158/rhs.v4n4p327 ◽

2019 ◽

Vol 4 (4) ◽

pp. p327

Author(s):

Malcolm J. D’Souza ◽

Riza C. Li ◽

Derald E. Wentzien

Keyword(s):

African American ◽

Mortality Rate ◽

Death Rate ◽

Causes Of Death ◽

Death Certificate ◽

Rate Increase ◽

Crude Mortality Rate ◽

Crude Mortality ◽

American Black ◽

Underlying Cause Of Death

Using commercially available but powerful big data analytics, this non-clinical obesity and underlying causes of death observational study, analyzed the very large US Centers for Disease Control and Prevention’s (CDC) State of Obesity records, the CDC WONDER data, and the US census records. Compared to the 1999-to-2017 US obesity rate increase of 29.8%, an uncontrolled increase in Delaware’s obesity rate (81.7%) was observed. During the same time period, CDC WONDER death certificate archives disclosed that there was a 60.53% surge in crude Delawarean mortality rate when obesity was listed as a single underlying cause of death. When any mention of obesity was documented on the death certificate, Delaware’s 1999-2017 crude mortality rate advanced by 75.69% and its age-adjusted rate rose by 53.18%. Likewise, except for one year, Delaware’s African American/Black population experienced higher crude mortality rate averages but however, between the years of 1997 and 2017, its Caucasian/White inhabitants had an enormous 87.34% death rate increase. With additional available CDC mortality data, Delaware males saw substantially larger age-adjusted death rate increases (79.87%) than their female counterparts (28.92%).Diabetes, circulatory system diseases, and neoplasms (cancer), are three common obesity comorbidities. For these three conditions, Delaware’s 1999-2017 mortality rate figures mimic the falling national patterns of mortality rate averages, when each disease is listed as the single underlying cause of death, including observations where there are disproportionate numbers of cases that affect the African American/Black race.

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Trends and Characteristics of Mortality Associated with Congenital Anomalies in Korean Children under 5 Years of Age

Neonatal Medicine ◽

10.5385/nm.2021.28.3.99 ◽

2021 ◽

Vol 28 (3) ◽

pp. 99-107

Author(s):

Soo Bin Kim ◽

Min Jung Jang ◽

Young Hwa Song ◽

Seung Yeon Jung ◽

Jun Suk Oh ◽

...

Keyword(s):

Mortality Rate ◽

Congenital Anomalies ◽

Linked Data ◽

Causes Of Death ◽

Infant Mortality Rate ◽

Careful Monitoring ◽

Korean Children ◽

Infant Deaths ◽

Child Deaths ◽

Children Under 5

Purpose: Studies have been conducted on the prevalence and infant mortality rate of congenital anomalies; however, studies on child mortality are rare. Therefore, we evaluated the characteristics of deaths associated with congenital anomalies among children born in Korea who died within 5 years of age.Methods: Birth-to-death cohort linked data of children under the age of 5 years from 2010 to 2013, and statistical data on the cause of death by age from 1999 to 2019, both provided by the Korea National Statistical Office's Microdata Integrated Service, were retrospectively investigated. We investigated the trends and characteristics of mortality associated with congenital anomalies.Results: Among 1,858,945 children, 6,510 children who died were under 5 years of age, and among them, 1,229 deaths were associated with congenital anomalies, while 5,281 deaths were due to other causes. Deaths associated with congenital anomalies accounted for 18.9% of all deaths. When comparing congenital anomalies by systems, anomalies of the cardiovascular system (52.6%) were the most common. The mortality rate associated with congenital anomalies and those of other causes showed similar declining trends in 21 years.Conclusion: The mortality rate of congenital anomalies during the first 5 years of life did not increase differently from the prevalence of congenital anomalies but rather decreased. Deaths associated with congenital anomalies accounted for 20.5% of all infant deaths and 12.1% of child deaths, since the major causes of death in infants and children are slightly different, continuous and careful monitoring is required.

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Deaths from unintentional injuries in rural areas of the Islamic Republic of Iran

Eastern Mediterranean Health Journal ◽

10.26719/1999.5.1.55 ◽

1999 ◽

Vol 5 (1) ◽

pp. 55-60 ◽

Cited By ~ 3

Author(s):

H. Soori ◽

M. Naghavi

Keyword(s):

Mortality Rate ◽

Rural Areas ◽

Traffic Accidents ◽

Causes Of Death ◽

Islamic Republic ◽

Accidental Injury ◽

Unintentional Injuries ◽

Crude Mortality Rate ◽

Crude Mortality ◽

Islamic Republic Of Iran

Deathsfrom accidental injury in the rural areas of 13 provinces in the Islamic Republic of Iran from 1993 to 1994 were investigated. The crude mortality rate was 4.33 per 1000 and the number of deaths from unintentional injuries was 5213 [10.7% of all deaths]. There were more deaths among males than females [65.7 per 100, 000 versus 26.1 per 100, 000]. After the age of 1 year, over 65-year-olds had the highest average of deaths resulting from injuries [111.9 per 100, 000]. The leading causes of death were traffic accidents [55.0%], drowning [10.1%], falls [9.5%]and burns and scalding [9.5%]. Since most injuries are preventable, their reduction should be considered a priority

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Using Satellite Images and Deep Learning to Identify Associations Between County-Level Mortality and Residential Neighborhood Features Proximal to Schools: A Cross-Sectional Study

Frontiers in Public Health ◽

10.3389/fpubh.2021.766707 ◽

2021 ◽

Vol 9 ◽

Author(s):

Joshua J. Levy ◽

Rebecca M. Lebeaux ◽

Anne G. Hoen ◽

Brock C. Christensen ◽

Louis J. Vaickus ◽

...

Keyword(s):

United States ◽

Deep Learning ◽

Mortality Rate ◽

Satellite Images ◽

The United States ◽

Mortality Rates ◽

Image Features ◽

County Level ◽

Crude Mortality Rate ◽

Crude Mortality

What is the relationship between mortality and satellite images as elucidated through the use of Convolutional Neural Networks?Background: Following a century of increase, life expectancy in the United States has stagnated and begun to decline in recent decades. Using satellite images and street view images, prior work has demonstrated associations of the built environment with income, education, access to care, and health factors such as obesity. However, assessment of learned image feature relationships with variation in crude mortality rate across the United States has been lacking.Objective: We sought to investigate if county-level mortality rates in the U.S. could be predicted from satellite images.Methods: Satellite images of neighborhoods surrounding schools were extracted with the Google Static Maps application programming interface for 430 counties representing ~68.9% of the US population. A convolutional neural network was trained using crude mortality rates for each county in 2015 to predict mortality. Learned image features were interpreted using Shapley Additive Feature Explanations, clustered, and compared to mortality and its associated covariate predictors.Results: Predicted mortality from satellite images in a held-out test set of counties was strongly correlated to the true crude mortality rate (Pearson r = 0.72). Direct prediction of mortality using a deep learning model across a cross-section of 430 U.S. counties identified key features in the environment (e.g., sidewalks, driveways, and hiking trails) associated with lower mortality. Learned image features were clustered, and we identified 10 clusters that were associated with education, income, geographical region, race, and age.Conclusions: The application of deep learning techniques to remotely-sensed features of the built environment can serve as a useful predictor of mortality in the United States. Although we identified features that were largely associated with demographic information, future modeling approaches that directly identify image features associated with health-related outcomes have the potential to inform targeted public health interventions.

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Analysis of death causes of residents in poverty-stricken Areas in 2020: take Liangshan Yi Autonomous Prefecture in China as an example

BMC Public Health ◽

10.1186/s12889-022-12504-6 ◽

2022 ◽

Vol 22 (1) ◽

Author(s):

Rujun Liao ◽

Lin Hu ◽

Qiang Liao ◽

Tianyu Zhu ◽

Haiqun Yang ◽

...

Keyword(s):

Mortality Rate ◽

Life Expectancy ◽

Malignant Tumors ◽

Heart Diseases ◽

Health Policies ◽

Years Of Life Lost ◽

Crude Mortality Rate ◽

Crude Mortality ◽

Standardized Mortality Rate ◽

Death Causes

Abstract Background Continuous surveillance of death can measure health status of the population, reflect social development of a region, thus promote health service development in the region and improve the health level of local residents. Liangshan Yi Autonomous Prefecture was a poverty-stricken region in Sichuan province, China. While at the end of 2020, as the announcement of its last seven former severely impoverished counties had shaken off poverty, Liangshan declared victory against poverty. Since it is well known that the mortality and cause of death structure will undergo some undesirable changes as the economy develops, this study aimed to reveal the distribution of deaths, as well as analyze the latest mortality and death causes distribution characteristics in Liangshan in 2020, so as to provide references for the decision-making on health policies and the distribution of health resources in global poverty-stricken areas. Methods Liangshan carried out the investigation on underreporting deaths among population in its 11 counties in 2018, and combined with the partially available data from underreporting deaths investigation data in 2020 and the field experience, we have estimated the underreporting rates of death in 2020 using capture-recapture (CRC) method. The crude mortality rate, age-standardized mortality rate, proportion and rank of the death causes, potential years of life lost (PYLL), average years of life lost (AYLL), potential years of life lost rate (PYLLR), standardized potential years of life lost (SPYLL), premature mortality from non-communicable diseases (premature NCD mortality), life expectancy and cause-eliminated life expectancy were estimated and corrected. Results In 2020, Liangshan reported a total of 16,850 deaths, with a crude mortality rate of 608.75/100,000 and an age-standardized mortality rate of 633.50/100,000. Male mortality was higher than female mortality, while 0-year-old mortality of men was lower than women’s. The former severely impoverished counties’ age-standardized mortality and 0-year-old mortality were higher than those of the non-impoverished counties. The main cause of death spectrum was noncommunicable diseases (NCDs), and the premature NCD mortality of four major NCDs were 14.26% for the overall population, 19.16% for men and 9.27% for women. In the overall population, the top five death causes were heart diseases (112.07/100,000), respiratory diseases (105.85/100,000), cerebrovascular diseases (87.03/100,000), malignant tumors (73.92/100,000) and injury (43.89/100,000). Injury (64,216.78 person years), malignant tumors (41,478.33 person years) and heart diseases (29,647.83 person years) had the greatest burden on residents in Liangshan, and at the same time, the burden of most death causes on men were greater than those on women. The life expectancy was 76.25 years for overall population, 72.92 years for men and 80.17 years for women, respectively, all higher than the global level (73.3, 70.8 and 75.9 years). Conclusions Taking Liangshan in China as an example, this study analyzed the latest death situation in poverty-stricken areas, and proposed suggestions on the formulation of health policies in other poverty-stricken areas both at home and abroad.

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Smoke-free legislation and neonatal and infant mortality in Brazil: longitudinal quasi-experimental study

Tobacco Control ◽

10.1136/tobaccocontrol-2019-054923 ◽

2019 ◽

pp. tobaccocontrol-2019-054923 ◽

Cited By ~ 1

Author(s):

Thomas Hone ◽

Andre Salem Szklo ◽

Filippos T Filippidis ◽

Anthony A Laverty ◽

Isabela Sattamini ◽

...

Keyword(s):

Experimental Study ◽

Mortality Rate ◽

Infant Mortality ◽

Neonatal Mortality ◽

Fixed Effects ◽

Infant Health ◽

Infant Mortality Rate ◽

Infant Deaths ◽

Quasi Experimental ◽

Fixed Effects Regression

ObjectiveTo examine the associations of partial and comprehensive smoke-free legislation with neonatal and infant mortality in Brazil using a quasi-experimental study design.DesignMonthly longitudinal (panel) ecological study from January 2000 to December 2016.SettingAll Brazilian municipalities (n=5565).ParticipantsInfant populations.InterventionSmoke-free legislation in effect in each municipality and month. Legislation was encoded as basic (allowing smoking areas), partial (segregated smoking rooms) or comprehensive (no smoking in public buildings). Associations were quantified by immediate step and longer term slope/trend changes in outcomes.Statistical analysesMunicipal-level linear fixed-effects regression models.Main outcomes measuresInfant and neonatal mortality.ResultsImplementation of partial smoke-free legislation was associated with a −3.3 % (95% CI −6.2% to −0.4%) step reduction in the municipal infant mortality rate, but no step change in neonatal mortality. Comprehensive smoke-free legislation implementation was associated with −5.2 % (95% CI −8.3% to −2.1%) and −3.4 % (95% CI −6.7% to −0.1%) step reductions in infant and neonatal mortality, respectively, and a −0.36 (95% CI −0.66 to−0.06) annual decline in the infant mortality rate. We estimated that had all smoke-free legislation introduced since 2004 been comprehensive, an additional 10 091 infant deaths (95% CI 1196 to 21 761) could have been averted.ConclusionsStrengthening smoke-free legislation in Brazil is associated with improvements in infant health outcomes—particularly under comprehensive legislation. Governments should accelerate implementation of comprehensive smoke-free legislation to protect infant health and achieve the United Nation’s Sustainable Development Goal three.

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Mortality in 787,666 school pupils with and without autism: A cohort study

Autism ◽

10.1177/1362361320944037 ◽

2020 ◽

pp. 136236132094403

Author(s):

Gillian S Smith ◽

Michael Fleming ◽

Deborah Kinnear ◽

Angela Henderson ◽

Jill P Pell ◽

...

Keyword(s):

Young People ◽

Causes Of Death ◽

Quality Care ◽

Current Generation ◽

Children And Young People ◽

The Past ◽

Crude Mortality Rate ◽

Crude Mortality ◽

Common Causes ◽

External Causes

Studies on children and adults combined suggest higher mortality rates for autistic than other people, but few report mortality rates for autistic children. In addition, past studies may not be representative of the current generation of children diagnosed with autism. We examined mortality in children using data from Scotland’s annual pupil census, linked to National Records of Scotland deaths register, between 2008 and 2015. In total, 9754 (1.2%) of 787,666 pupils had autism. They were more likely to live in neighbourhoods of greater deprivation and receive free school meals. Six autistic pupils died; crude mortality rate 15.8/100,000 person-years (95% CI = 7.1–35.1), compared with 458 other pupils; crude mortality rate 12.5/100,000 person-years (95% CI = 11.4–13.7). The indirectly standardised mortality ratio was 1.1 (95% CI = 0.5–2.5). In the autistic pupils, the most common causes of death were nervous system diseases, for example, epilepsy. Avoidable causes were common. In the comparison group, external causes and cancers were the most common causes of death. We cautiously conclude that mortality in the current generation of autistic children is no higher than for other children, perhaps due to recent widening of criteria for autism spectrum diagnosis, but some deaths could have been avoided by better care. Lay abstract There are few studies on the deaths of children and young people with autism; some studies on children and adults combined suggest that those with autism may have higher death rates than other people. More children are diagnosed with autism than in the past, suggesting that there are now more children with milder autism who have the diagnosis than in the past, so studies in the past might not apply to the current generation of children and young people diagnosed with autism. We examined the rates of death in children and young people in Scotland using recorded information in Scotland’s annual pupil census, linked to the National Records of Scotland deaths register, between 2008 and 2015. In total, 9754 (1.2%) out of 787,666 pupils had autism. Six pupils with autism died in the study period, compared with 458 other pupils. This was equivalent to 16 per 100,000 for pupils with autism and 13 per 100,000 pupils without autism; hence, the rate of death was very similar. In the pupils with autism, the most common causes of death were diseases of the nervous system, whereas they were from external causes in the comparison pupils. The autism group had some deaths due to epilepsy which might have been prevented by good quality care. We cautiously conclude that the death rate in the current generation of children and young adults with autism is no higher than for other children, but that even in this high-income country, some deaths could be prevented by high quality care.

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The descriptive epidemiology of suicide in Tuscany, 1988-2002

Epidemiologia e Psichiatria Sociale ◽

10.1017/s1121189x00004450 ◽

2006 ◽

Vol 15 (3) ◽

pp. 202-210 ◽

Cited By ~ 9

Author(s):

Michele Arcangelo Martiello ◽

Francesco Cipriani ◽

Fabio Voller ◽

Eva Buiatti ◽

Mariano Giacchi

Keyword(s):

Spatial Analysis ◽

Rural Communities ◽

Mortality Rate ◽

Empirical Bayes ◽

Mining District ◽

Mine Closure ◽

Descriptive Epidemiology ◽

Bayes Estimates ◽

Crude Mortality Rate ◽

Crude Mortality

SUMMARYAims – To describe the epidemiology of Suicide in Tuscany according to the triad of time, place and person. Methods – The 4, 764 cases of suicide, defined according to categories E950-E959 of ICD-9 in Tuscany over the period 1988–2002, were obtained from the Tuscan Mortality Register. Mortality indicators were calculated and analyzed. The spatial analysis was carried out by deriving Empirical Bayes Estimates for the 287 municipalities. Results – The crude mortality rate in the 2000–2002 is 7.8 per 100000 population (male: 12.4; female: 3.5). The age-standardized rate in the 2000–2002 is 5.8 per 100, 000 population (male: 9.6; female: 2.6). The highest risk for suicide, especially in the case of males, are concentrated in the southern hinterland Tuscany, in a cluster of rural municipalities that represent the old mining district of Tuscany. The SMRs according to residential municipality (population per square kilometre), confirm a greater risk of suicide for males residing in rural communities. Conclusions – The cluster of excessive mortality from suicide in Southern Tuscany could be the consequence of social determinants, related to the urban and social crisis following agriculture decline and mine closure.Declaration of Interest: none.

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Using Satellite Images and Deep Learning to Identify Associations Between County-Level Mortality and Neighborhood Features

10.1101/2020.10.12.20211755 ◽

2020 ◽

Author(s):

Joshua J. Levy ◽

Rebecca M. Lebeaux ◽

Anne G. Hoen ◽

Brock C. Christensen ◽

Louis J. Vaickus ◽

...

Keyword(s):

United States ◽

Deep Learning ◽

Mortality Rate ◽

Satellite Images ◽

The United States ◽

Mortality Rates ◽

Image Features ◽

County Level ◽

Crude Mortality Rate ◽

Crude Mortality

AbstractWhat is the relationship between mortality and satellite images as elucidated through the use of Convolutional Neural Networks?BackgroundFollowing a century of increase, life expectancy in the United States has stagnated and begun to decline in recent decades. Using satellite images and street view images, prior work has demonstrated associations of the built environment with income, education, access to care and health factors such as obesity. However, assessment of learned image feature relationships with variation in crude mortality rate across the United States has been lacking. We sought to investigate if county-level mortality rates in the U.S. could be predicted from satellite images.MethodsSatellite images were extracted with the Google Static Maps application programming interface for 430 counties representing approximately 68.9% of the US population. A convolutional neural network was trained using crude mortality rates for each county in 2015 to predict mortality. Learned image features were interpreted using Shapley Additive Feature Explanations, clustered, and compared to mortality and its associated covariate predictors.ResultsPredicted mortality from satellite images in a held-out test set of counties was strongly correlated to the true crude mortality rate (Pearson r=0.72). Learned image features were clustered, and we identified 10 clusters that were associated with education, income, geographical region, race and age. Direct prediction of mortality using a deep learning model across a cross-section of 430 U.S. counties identified key features in the environment (e.g. sidewalks, driveways and hiking trails) associated with lower mortality.ConclusionsThe application of deep learning techniques to remotely-sensed features of the built environment can serve as a useful predictor of mortality in the United States. Although we identified features that were largely associated with demographic information, future modeling approaches that directly identify image features associated with health-related outcomes have the potential to inform targeted public health interventions.

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الزيادة الطبيعية لسكان محافظة دهوك للفترة (2007 – 2017) وتباينه مكانياً

10.31219/osf.io/592ct ◽

2021 ◽

Author(s):

Chinar Muhsin Hasan

Keyword(s):

Mortality Rate ◽

Birth Rate ◽

Crude Birth Rate ◽

Natural Increase ◽

Noticeable Increase ◽

Crude Mortality Rate ◽

Crude Mortality ◽

Increase Rate ◽

The Difference

الملخص: تهدف الدراسة المعنونة بـ ((الزيادة الطبيعية لسكان محافظة دهوك للفترة (2007 – 2017) وتباينه مكانياً)) إلى بيان معدلات الزيادة الطبيعية أي الفرق بين الولادات والوفيات في محافظة دهوك حسب الأقضية بعد أن شهدت المحافظة زيادة ملحوظة خلال السنوات الأخيرة مما استدعت إلى الوقوف عليها، وقد تكوّنَ البحث من ثلاث مباحث: المبحث الأول تطرق إلى استخراج معدل الولادات الخام، والمبحث الثاني درس معدل الوفيات الخام، والمبحث الثالث درس معدل الزيادة الطبيعية (الحيوية) خلال الفترة حسب الوحدات الإدراية، وقد توصلت الدراسة إلى أنَّ معدل الزيادة الطبيعية في محافظة دهوك انخفضت من نسبة (3.3%) في عام 2007 إلى(2.1%) في عام 2017. Abstract:The objective of the study is to increase the natural increase in the population of Duhok governorate in the period (2007 - 2017) to indicate the rates of natural increase, i.e. the difference between births and deaths in Duhok governorate by district after the governorate witnessed a noticeable increase in recent years. The research may consist of three subjects: first, crude birth rate, second crude mortality rate, and third natural increase rate during the period according to administrative units.The study found that the rate of natural increase in Duhok Governorate decreased from 3.3% in 2007 to 2.1% in 2017.

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