scholarly journals Beyond standardized mortality ratios; some uses of smoothed age-specific mortality rates on small areas studies

2020 ◽  
Vol 19 (1) ◽  
Author(s):  
Jordi Perez-Panades ◽  
Paloma Botella-Rocamora ◽  
Miguel Angel Martinez-Beneito
Keyword(s):  
Life Expectancy ◽  
Age Groups ◽  
Dependence Structure ◽  
Risk Indicator ◽  
Small Areas ◽  
Life Expectancy At Birth ◽  
First Case ◽  
Wide Range ◽  
Standardized Mortality Ratios

Abstract Background Most epidemiological risk indicators strongly depend on the age composition of populations, which makes the direct comparison of raw (unstandardized) indicators misleading because of the different age structures of the spatial units of study. Age-standardized rates (ASR) are a common solution for overcoming this confusing effect. The main drawback of ASRs is that they depend on age-specific rates which, when working with small areas, are often based on very few, or no, observed cases for most age groups. A similar effect occurs with life expectancy at birth and many more epidemiological indicators, which makes standardized mortality ratios (SMR) the omnipresent risk indicator for small areas epidemiologic studies. Methods To deal with this issue, a multivariate smoothing model, the M-model, is proposed in order to fit the age-specific probabilities of death (PoDs) for each spatial unit, which assumes dependence between closer age groups and spatial units. This age–space dependence structure enables information to be transferred between neighboring consecutive age groups and neighboring areas, at the same time, providing more reliable age-specific PoDs estimates. Results Three case studies are presented to illustrate the wide range of applications that smoothed age specific PoDs have in practice . The first case study shows the application of the model to a geographical study of lung cancer mortality in women. This study illustrates the convenience of considering age–space interactions in geographical studies and to explore the different spatial risk patterns shown by the different age groups. Second, the model is also applied to the study of ischaemic heart disease mortality in women in two cities at the census tract level. Smoothed age-standardized rates are derived and compared for the census tracts of both cities, illustrating some advantages of this mortality indicator over traditional SMRs. In the latest case study, the model is applied to estimate smoothed life expectancy (LE), which is the most widely used synthetic indicator for characterizing overall mortality differences when (not so small) spatial units are considered. Conclusion Our age–space model is an appropriate and flexible proposal that provides more reliable estimates of the probabilities of death, which allow the calculation of enhanced epidemiological indicators (smoothed ASR, smoothed LE), thus providing alternatives to traditional SMR-based studies of small areas.

scholarly journals Beyond standardized mortality ratios; some uses of smoothed age-specific mortality rates on small areas studies.

2020 ◽  
Author(s):  
Jordi Perez-Panades ◽  
Paloma Botella-Rocamora ◽  
Miguel Angel Martinez-Beneito
Keyword(s):  
Life Expectancy ◽  
Age Groups ◽  
Dependence Structure ◽  
Risk Indicator ◽  
Small Areas ◽  
Life Expectancy At Birth ◽  
First Case ◽  
Wide Range ◽  
Standardized Mortality Ratios

Abstract Background: Most epidemiological risk indicators strongly depend on the age composition of populations, which makes the direct comparison of raw (unstandardized) indicators misleading because of the different age structures of the spatial units of study. Age-standardized rates (ASR) are a common solution for overcoming this confusing effect. The main drawback of ASRs is that they depend on age-specific rates which, when working with small areas, are often based on very few, or no, observed cases for most age groups. A similar effect occurs with life expectancy at birth and many more epidemiological indicators, which makes standardized mortality ratios (SMR)the omnipresent risk indicator for small areas epidemiologic studies.Methods:To deal with this issue, a multivariate smoothing model, the M-model, is proposed in order to fit the age-specific probabilities of death (PoDs) for each spatial unit, which assumes dependence between closer age groups and spatial units. This age-space dependence structure enables information to be transferred between neighboring consecutive age groups and neighboring areas, at the same time, providing more reliable age-specific PoDs estimates.Results: Three case studies are presented to illustrate the wide range of applications that smoothed age specific PoDs have in practice . The first case study shows the application of the model to a geographical study of lung cancer mortality in women. This study illustrates the convenience of consideringage-space interactions in geographical studies and to explore the different spatial risk patterns shown by the different age groups. Second, the model is also applied to the study of ischaemic heart disease mortality in women in two cities at the census tract level. Smoothed age-standardized rates are derived and compared for the census tracts of both cities, illustrating some advantages of this mortality indicator over traditional SMRs. In the latest case study, the model is applied to estimate smoothed life expectancy (LE), which is the most widely used synthetic indicator for characterizing overall mortality differences when (not so small) spatial units are considered.Conclusion: Our age-space model is an appropriate and flexible proposal that provides more reliable estimates of the probabilities of death, which allow the calculation of enhanced epidemiological indicators (smoothed ASR, smoothed LE), thus providing alternatives to traditional SMR-based studies of small areas

scholarly journals Beyond standardized mortality ratios; some uses of smoothed age-specific mortality rates on small areas studies.

2020 ◽  
Author(s):  
Jordi Perez-Panades ◽  
Paloma Botella-Rocamora ◽  
Miguel Angel Martinez-Beneito
Keyword(s):  
Life Expectancy ◽  
Age Groups ◽  
Dependence Structure ◽  
Risk Indicator ◽  
Small Areas ◽  
Life Expectancy At Birth ◽  
First Case ◽  
Wide Range ◽  
Standardized Mortality Ratios

Abstract Background: Most epidemiological risk indicators strongly depend on the age composition of populations, which makes the direct comparison of raw(unstandardized) indicators misleading because of the dierent age structures of the spatial units of study. Age-standardized rates (ASR) are a common solution for overcoming this confusing effect. The main drawback of ASRs is that they depend on age-specific rates which, when working with small areas, are often based on very few, or no, observed cases for most age groups. A similar effect occurs with life expectancy at birth and many more epidemiological indicators, which makes standardized mortality ratios (SMR) the omnipresent risk indicator for small areas epidemiologic studies.Methods: To deal with this issue, a multivariate smoothing model, the M-model, is proposed in order to t the age-specic probabilities of death (PoDs)for each spatial unit, which assumes dependence between closer age groups and spatial units. This age-space dependence structure enables information to be transferred between neighboring consecutive age groups and neighboring areas, at the same time, providing more reliable age-specific PoDs estimates.Results: Three case studies are presented to illustrate the wide range of applications that smoothed age specific PoDs have in practice . The first case study shows the application of the model to a geographical study of lung cancer mortality in women. This study illustrates the convenience of considering age-space interactions in geographical studies and to explore the different spatial risk patterns shown by the different age groups. Second, the model is also applied to the study of ischaemic heart disease mortality in women in two cities at the census tract level. Smoothed age-standardized rates are derived and compared for the census tracts of both cities, illustrating some advantages of this mortality indicator over traditional SMRs. In the latest case study, the model is applied to estimate smoothed life expectancy (LE), which is the most widely used syntheticindicator for characterizing overall mortality differences when (not so small) spatial units are considered.Conclusion: Our age-space model is an appropriate and flexible proposal that provides more reliable estimates of the probabilities of death, which allow the calculation of enhanced epidemiological indicators (smoothed ASR, smoothed LE), thus providing alternatives to traditional SMR-based studies of small areas.

scholarly journals The decomposition of life expectancy for age and cause of death in Tuscany, Italy

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
N Nante ◽  
L Kundisova ◽  
F Gori ◽  
A Martini ◽  
F Battisti ◽  
...  
Keyword(s):  
Life Expectancy ◽  
Causes Of Death ◽  
National Level ◽  
Age Groups ◽  
Resistant Bacteria ◽  
Mortality Data ◽  
Life Expectancy At Birth ◽  
Icd 10 ◽  
Reduction Of Mortality ◽  
The Impact

Abstract Introduction Changing of life expectancy at birth (LE) over time reflects variations of mortality rates of a certain population. Italy is amongst the countries with the highest LE, Tuscany ranks fifth at the national level. The aim of the present work was to evaluate the impact of various causes of death in different age groups on the change in LE in the Tuscany region (Italy) during period 1987-2015. Material and methods Mortality data relative to residents that died during the period between 1987/1989 and 2013/2015 were provided by the Tuscan Regional Mortality Registry. The causes of death taken into consideration were cardiovascular (CVS), respiratory (RESP) and infective (INF) diseases and cancer (TUM). The decomposition of LE gain was realized with software Epidat, using the Pollard’s method. Results The overall LE gain during the period between two three-years periods was 6.7 years for males, with a major gain between 65-89, and 4.5 years for females, mainly improved between 75-89, <1 year for both sexes. The major gain (2.6 years) was attributable to the reduction of mortality for CVS, followed by TUM (1.76 in males and 0.83 in females) and RESP (0.4 in males; 0.1 in females). The major loss of years of LE was attributable to INF (-0.15 in females; -0.07 in males) and lung cancer in females (-0.13), for which the opposite result was observed for males (gain of 0.62 years of LE). Conclusions During the study period (1987-2015) the gain in LE was major for males. To the reduction of mortality for CVS have contributed to the tempestuous treatment of acute CVS events and secondary CVS prevention. For TUM the result is attributable to the adherence of population to oncologic screening programmes. The excess of mortality for INF that lead to the loss of LE can be attributed to the passage from ICD-9 to ICD-10 in 2003 (higher sensibility of ICD-10) and to the diffusion of multi-drug resistant bacteria, which lead to elevated mortality in these years. Key messages The gain in LE during the period the 1987-2015 was higher in males. The major contribution to gain in LE was due to a reduction of mortality for CVS diseases.

scholarly journals The global burden of premature mortality due to the Middle East respiratory syndrome (MERS) using standard expected years of life lost, 2012 to 2019

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Maryam Salamatbakhsh ◽  
Kazhal Mobaraki ◽  
Sara Sadeghimohammadi ◽  
Jamal Ahmadzadeh
Keyword(s):  
Middle East ◽  
Age Groups ◽  
International Study ◽  
Premature Mortality ◽  
Middle East Respiratory Syndrome ◽  
Global Burden ◽  
Years Of Life Lost ◽  
Life Expectancy At Birth ◽  
First Case ◽  
Disease Study

Abstract Background It has been 8 years since the first case of Middle East respiratory syndrome coronavirus (MERS-CoV) was reported in Saudi Arabia and the disease is still being reported in 27 countries; however, there is no international study to estimate the overall burden related of this emerging infectious disease. The present study was conducted to assess the burden of premature mortality due to Middle East respiratory syndrome (MERS) worldwide. Methods In this retrospective analysis, we have utilized publicly available data from the WHO website related to 1789 MERS patients reported between September 23, 2012 and May 17, 2019. To calculate the standard expected years of life lost (SEYLL), life expectancy at birth was set according to the 2000 global burden of disease study on levels 25 and 26 of West model life tables from Coale-Demeny at 82.5 and 80 years for females and males, respectively. Results Overall, the total SEYLL in males and females was 10,702 and 3817.5 years, respectively. The MERS patients within the age range of 30–59 year-olds had the highest SEYLL (8305.5 years) in comparison to the patients within the age groups 0–29 (SEYLL = 3744.5 years) and ≥ 60 years (SEYLL = 2466.5 years). The total SEYLL in all age groups in 2012, 2013, 2014, 2015, 2016, 2017, 2018, and 2019 were 71.5, 2006.5, 3162, 4425.5, 1809.5, 878, 1257.5 and 909 years, respectively. The most SEYLL related to MERS-CoV infection was in the early four years of the onset of the pandemic (2012 to 2015) and in the last four years of the MERS-CoV pandemic (216 to 2019), a significant reduction was observed in the SEYLL related to MERS-CoV infection in the MERS patients. Conclusion We believe that the findings of this study will shed light about the burden of premature mortality due to MERS infection in the world and the results may provide necessary information for policy-makers to prevent, control, and make a quick response to the outbreak of MERS-CoV disease.

Socioeconomic factors affecting the longevity of the Japanese population: a study for 1980 and 1985

1992 ◽  
Vol 24 (4) ◽  
pp. 497-504 ◽  
Author(s):  
Eiichi Uchida ◽  
Shunichi Araki ◽  
Katsuyuki Murata
Keyword(s):  
Life Expectancy ◽  
Socioeconomic Factors ◽  
Low Income ◽  
Japanese Population ◽  
Age Groups ◽  
High Income ◽  
Factors Affecting ◽  
Life Expectancy At Birth ◽  
Males And Females

SummaryThe effects of urbanisation, low income and rejuvenation of the population on life expectancy at birth and at 20, 40 and 65 years of age for males and females in Japan were examined twice, in 1980 and 1985. For males, urbanisation was the major factor determining life expectancy at birth and at age 20 years, and low income was the key determinant of decreased life expectancy except at 65 years of age. For females high income was the factor significantly decreasing life expectancy at 65 years of age in 1980, and rejuvenation of the population inversely influenced life expectancy except at birth in 1985. Life expectancy for all age groups in 1985 was significantly longer than in 1980 for both males and females.

scholarly journals Regional health inequalities explained: empirical evidence from Czechia

Geografie ◽  
2019 ◽  
Vol 124 (4) ◽  
pp. 365-383
Author(s):  
Aleš Bělohradský ◽  
Daniela Glocker
Keyword(s):  
Alcohol Consumption ◽  
Life Expectancy ◽  
Economic Situation ◽  
Geographic Scale ◽  
Explanatory Variables ◽  
Life Expectancy At Birth ◽  
Wide Range ◽  
Main Driver ◽  
Environmental Causes ◽  
The Impact

Health outcomes in Central and Eastern Europe have been generally improving over the last two decades. However, in Czechia, similar to other countries, the outcomes vary significantly across the regional dimension. In 2016, life expectancy at birth ranged from between 75.5 to 80 years – across 77 districts. This article empirically analyses the determinants of these differences using a wide range of explanatory variables that are available on a district level. Applying factor analysis, our findings indicate that the socio-economic situation within a district is the main driver – explaining a difference of up to four years in life expectancy at birth. Further, controlling for gender specific variables, the results suggest that for men alcohol consumption significantly reduces life expectancy. Both factors capturing the socio-economic situation and alcohol consumption exceed the impact of health care accessibility or environmental causes on life expectancy. The results remain robust when using more disaggregated information on 206 administrative districts – per geographic scale.

scholarly journals Gender gap in life expectancy in India and role of age groups: A comparison between before and after male – female life expectancy at birth crossover

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0260657
Author(s):  
Girimallika Borah
Keyword(s):  
Life Expectancy ◽  
Gender Gap ◽  
Age Groups ◽  
Absolute Number ◽  
Reproductive Age ◽  
Sample Survey ◽  
Mortality Data ◽  
Female Life Expectancy ◽  
Life Expectancy At Birth ◽  
Before And After

To assess the gender gap in life expectancy at birth in India and its major states as well as the timing of male-female life expectancy at birth crossover. To analyze the age-specific contributions to the changing gender differences before and after the crossover at the national and sub-national levels. We have used sample-survey-based age-specific mortality data available for the periods 1970–2018 to construct abridged life tables. The contribution of different age groups to the gender gap is estimated by using Arriaga’s method of decomposition. During 1981–85 female life expectancy at birth caught up with male life expectancy at birth for India and by 2005 all major states completed the crossover. The male-female crossover in life expectancy at the national level in the early 80s is remarkable in the face of continued female disadvantage from birth till adolescence, even for some richer states. We provide evidence that gender difference in longevity in favour of females is largely a function of adult age groups and younger age groups contribute negatively to the gender gap in life expectancy at birth in most states. Juxtaposing the results from contribution in an absolute number of years and their relative contribution change before and after the crossover, it is established that although the adult and old age groups contribute the highest in the absolute number of years before and after the crossover, the contribution of the reproductive age groups and childhood years in the recent time is most relevant in relative terms.

scholarly journals Applications of Virtual Data in Subsea Inspections

2020 ◽  
Vol 8 (5) ◽  
pp. 328 ◽  
Author(s):  
Michael O’Byrne ◽  
Bidisha Ghosh ◽  
Franck Schoefs ◽  
Vikram Pakrashi
Keyword(s):  
Virtual Environments ◽  
Real World ◽  
Detection Methods ◽  
Current State ◽  
First Case ◽  
Wide Range ◽  
Inspection Process ◽  
State Of Research ◽  
Virtual Data

This paper investigates the role that virtual environments can play in assisting engineers and divers when performing subsea inspections. We outline the current state of research and technology that is relevant to the development of effective virtual environments. Three case studies are presented demonstrating how the inspection process can be enhanced through the use of virtual data. The first case study looks at how immersive virtual underwater scenes can be created to help divers and inspectors plan and implement real-world inspections. The second case study shows an example where deep learning-based computer vision methods are trained on datasets comprised of instances of virtual damage, specifically instances of barnacle fouling on the surface of a ship hull. The trained deep models are then applied to detect real-world instances of biofouling with promising results. The final case study shows how image-based damage detection methods can be calibrated using virtual images of damage captured under various simulated levels of underwater visibility. The work emphasizes the value of virtual data in creating a more efficient, safe and informed underwater inspection campaign for a wide range of built infrastructure, potentially leading to better monitoring, inspection and lifetime performance of such underwater structures.

scholarly journals Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis

2021 ◽  
pp. jech-2020-215505
Author(s):  
Jose Manuel Aburto ◽  
Ridhi Kashyap ◽  
Jonas Schöley ◽  
Colin Angus ◽  
John Ermisch ◽  
...  
Keyword(s):  
Life Expectancy ◽  
Excess Mortality ◽  
Prediction Interval ◽  
Age Groups ◽  
Population Level ◽  
England And Wales ◽  
Life Expectancy At Birth ◽  
Using Data ◽  
The Impact ◽  
Excess Deaths

BackgroundDeaths directly linked to COVID-19 infection may be misclassified, and the pandemic may have indirectly affected other causes of death. To overcome these measurement challenges, we estimate the impact of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality from week 10 of 2020, when the first COVID-19 death was registered, to week 47 ending 20 November 2020 in England and Wales through an analysis of excess mortality.MethodsWe estimated age and sex-specific excess mortality risk and deaths above a baseline adjusted for seasonality with a systematic comparison of four different models using data from the Office for National Statistics. We additionally provide estimates of life expectancy at birth and lifespan inequality defined as the SD in age at death.ResultsThere have been 57 419 (95% prediction interval: 54 197, 60 752) excess deaths in the first 47 weeks of 2020, 55% of which occurred in men. Excess deaths increased sharply with age and men experienced elevated risks of death in all age groups. Life expectancy at birth dropped 0.9 and 1.2 years for women and men relative to the 2019 levels, respectively. Lifespan inequality also fell over the same period by 5 months for both sexes.ConclusionQuantifying excess deaths and their impact on life expectancy at birth provide a more comprehensive picture of the burden of COVID-19 on mortality. Whether mortality will return to—or even fall below—the baseline level remains to be seen as the pandemic continues to unfold and diverse interventions are put in place.

scholarly journals What can lifespan variation reveal that life expectancy hides? Comparison of five high-income countries

2021 ◽  
pp. 014107682110117
Author(s):  
Lucinda Hiam ◽  
Jon Minton ◽  
Martin McKee
Keyword(s):  
Life Expectancy ◽  
Age Groups ◽  
Population Data ◽  
High Income ◽  
Life Expectancy At Birth ◽  
Specific Mortality ◽  
The Usa ◽  
Lifespan Variation ◽  
The Uk ◽  
Aggregate Population

Objectives In most countries, life expectancy at birth (e0) has improved for many decades. Recently, however, progress has stalled in the UK and Canada, and reversed in the USA. Lifespan variation, a complementary measure of mortality, increased a few years before the reversal in the USA. To assess whether this measure offers additional meaningful insights, we examine what happened in four other high-income countries with differing life expectancy trends. Design We calculated life disparity (a specific measure of lifespan variation) in five countries -- USA, UK, France, Japan and Canada -- using sex- and age specific mortality rates from the Human Mortality Database from 1975 to 2017 for ages 0--100 years. We then examined trends in age-specific mortality to identify the age groups contributing to these changes. Setting USA, UK, France, Japan and Canada Participants aggregate population data of the above nations. Main Outcome Measures Life expectancy at birth, life disparity and age-specific mortality. Results The stalls and falls in life expectancy, for both males and females, seen in the UK, USA and Canada coincided with rising life disparity. These changes may be driven by worsening mortality in middle-age (such as at age 40). France and Japan, in contrast, continue on previous trajectories. Conclusions Life disparity is an additional summary measure of population health providing information beyond that signalled by life expectancy at birth alone.

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