Estimated Life Expectancy Research Articles

Improving survival prediction of patients treated with external beam radiotherapy for dysphagia in esophageal cancer using prediction models.

358 Background: The recently published POLDER trial investigated the effects of external beam radiotherapy (EBRT) on dysphagia caused by incurable esophageal cancer. As the effects of EBRT were presumed not to be immediate, an estimated life expectancy of minimally three months was required for inclusion. However, nearly a third of the included patients died within three months. The aim of this study was to investigate if the use of prediction models could have improved the physician’s estimation of the patient’s survival, and thus the eligibility for EBRT treatment. Methods: Data from the POLDER trial (N = 110) were linked to the Netherlands Cancer Registry to retrieve additional patient, tumor and treatment characteristics. Two published prediction models (the SOURCE model and Steyerberg model) were used to predict overall survival for all patients included in the POLDER trial. Predicted survival probabilities were dichotomized (predicted deceased/alive at three months) and the positive predictive value, negative predictive value, sensitivity, specificity and the area under the curve (AUC) were used to evaluate the predictive performance. DeLong’s test was used to test the difference between the AUCs of the SOURCE and Steyerberg models for statistical significance. Results: In the POLDER trial, 35 patients were unjustly presumed to survive three months. Predicting survival at three months, the SOURCE and Steyerberg model had an AUC of 0.76 and 0.60 respectively. The difference between the AUCs of the models was significant (p =.017). Under optimal survival cut-off scores, SOURCE would have incorrectly predicted 16 patients to survive three months. For the Steyerberg model this was 22 patients. Furthermore, using SOURCE under these cut-off scores, seven patients were incorrectly predicted to not survive three months compared to 18 patients using the Steyerberg model. Conclusions: Results showed that the SOURCE and Steyerberg models could have improved survival predictions compared to clinical judgement alone. The SOURCE model was found to be a more useful decision aid than the Steyerberg model as it was more accurate. Accepting that a small proportion of patients are incorrectly predicted not to survive three months and are not considered for EBRT treatment, we recommend using the SOURCE model for patients that are considered for palliative treatment of dysphagia caused by esophageal cancer.

Life expectancy drop in 2020. Estimates based on Human Mortality Database.

In many countries of the world, COVID-19 pandemic has led to exceptional changes in mortality trends. Some studies have tried to quantify the effects of Covid-19 in terms of a reduction in life expectancy at birth in 2020. However, these estimates might need to be updated now that, in most countries, the mortality data for the whole year are available. We used data from the Human Mortality Database (HMD) Short-Term Mortality Fluctuations (STMF) data series to estimate life expectancy in 2020 for several countries. The changes estimated using these data and the appropriate methodology seem to be more pessimistic than those that have been proposed so far: life expectancy dropped in the Russia by 2.16 years, 1.85 in USA, and 1.27 in England and Wales. The differences among countries are substantial: many countries (e.g. Denmark, Island, Norway, New Zealand, South Korea) saw a rather limited drop in life expectancy or have even seen an increase in life expectancy.

Estimating life expectancy adjusted by self-rated health status in the United States: national health interview survey linked to the mortality

BackgroundLife expectancy is increasingly incorporated in evidence-based screening and treatment guidelines to facilitate patient-centered clinical decision-making. However, life expectancy estimates from standard life tables do not account for health status, an important prognostic factor for premature death. This study aims to address this research gap and develop life tables incorporating the health status of adults in the United States.MethodsData from the National Health Interview Survey (1986–2004) linked to mortality follow-up through to 2006 (age ≥ 40, n = 729,531) were used to develop life tables. The impact of self-rated health (excellent, very good, good, fair, poor) on survival was quantified in 5-year age groups, incorporating complex survey design and weights. Life expectancies were estimated by extrapolating the modeled survival probabilities.ResultsLife expectancies incorporating health status differed substantially from standard US life tables and by health status. Poor self-rated health more significantly affected the survival of younger compared to older individuals, resulting in substantial decreases in life expectancy. At age 40 years, hazards of dying for white men who reported poor vs. excellent health was 8.5 (95% CI: 7.0,10.3) times greater, resulting in a 23-year difference in life expectancy (poor vs. excellent: 22 vs. 45), while at age 80 years, the hazards ratio was 2.4 (95% CI: 2.1, 2.8) and life expectancy difference was 5 years (5 vs. 10). Relative to the US general population, life expectancies of adults (age < 65) with poor health were approximately 5–15 years shorter.ConclusionsConsiderable shortage in life expectancy due to poor self-rated health existed. The life table developed can be helpful by including a patient perspective on their health and be used in conjunction with other predictive models in clinical decision making, particularly for younger adults in poor health, for whom life tables including comorbid conditions are limited.

Comparing the loss of life expectancy at birth during the 2020 and 1918 pandemics in six European countries

The COVID-19 pandemic that reached Europe in 2020 has often been compared to the Spanish flu pandemic of 1918. In this article, we compare the two pandemics in terms of their respective impacts on the loss of life expectancy at birth in six European countries (France, Italy, the Netherlands, Spain, Sweden, Switzerland) by estimating life expectancy in 2020 using Eurostat data. We found that the loss of life expectancy at birth was up to 20 times larger between 1917 and 1918 than between 2019 and 2020. A decomposition of these losses clearly shows that in all six countries, the main contributors were older age groups in 2020 and younger age groups in 1918. These observations are consistent with evidence indicating that most COVID-19 fatalities were among the elderly, while a majority of Spanish flu fatalities were among the young.

The impact of the COVID-19 pandemic on mortality: life expectancy reduction and geographical disparities in Argentina.

To assess the impact of the COVID-19 pandemic on mortality in Argentina, considering temporal trends in life expectancy at birth and premature mortality rate during 2010-2020. Based on demographic projections, this ecological time-series study compares a "normal" versus a "COVID-19" mortality scenario for 2020 over a set of 11 Argentine provinces. Annual life expectancy at birth and age-standardized rates of premature mortality were estimated from 2010 to 2020. Joinpoint regression and multilevel models were used. A potential reduction in life expectancy at birth (a gap between scenarios >1 year) was observed. A significant (negative) point of inflection in temporal trends was identified for the country and most of the provinces, under the COVID-19 mortality scenario. However, our findings reveal disparities between provinces in the estimated life expectancy reduction toward 2020 (values range from -0.63 to -1.85 year in females and up to -2.55 years in males). While men showed more accentuated declines in life expectancy at birth in 2020 (a national gap between scenarios of -1.47 year in men vs. -1.35 year in women), women experienced more unfavorable temporal trends of premature mortality. In the absence of COVID-19, an improvement in both indicators was estimated toward 2020 in both sexes, while a return to levels reported in the past was observed under the COVID-19 scenario. The COVID-19 pandemic might seriously affect the trends of mortality and exacerbate health disadvantages in Argentina. A temporal and contextual perspective of health inequities merits special attention in the COVID-19 research.

An Efficient Method for Computing Expected Value of Sample Information for Survival Data from an Ongoing Trial.

BackgroundDecisions about new health technologies are increasingly being made while trials are still in an early stage, which may result in substantial uncertainty around key decision drivers such as estimates of life expectancy and time to disease progression. Additional data collection can reduce uncertainty, and its value can be quantified by computing the expected value of sample information (EVSI), which has typically been described in the context of designing a future trial. In this article, we develop new methods for computing the EVSI of extending an existing trial’s follow-up, first for an assumed survival model and then extending to capture uncertainty about the true survival model.MethodsWe developed a nested Markov Chain Monte Carlo procedure and a nonparametric regression-based method. We compared the methods by computing single-model and model-averaged EVSI for collecting additional follow-up data in 2 synthetic case studies.ResultsThere was good agreement between the 2 methods. The regression-based method was fast and straightforward to implement, and scales easily to include any number of candidate survival models in the model uncertainty case. The nested Monte Carlo procedure, on the other hand, was extremely computationally demanding when we included model uncertainty.ConclusionsWe present a straightforward regression-based method for computing the EVSI of extending an existing trial’s follow-up, both where a single known survival model is assumed and where we are uncertain about the true survival model. EVSI for ongoing trials can help decision makers determine whether early patient access to a new technology can be justified on the basis of the current evidence or whether more mature evidence is needed.HighlightsDecisions about new health technologies are increasingly being made while trials are still in an early stage, which may result in substantial uncertainty around key decision drivers such as estimates of life-expectancy and time to disease progression. Additional data collection can reduce uncertainty, and its value can be quantified by computing the expected value of sample information (EVSI), which has typically been described in the context of designing a future trial.In this article, we have developed new methods for computing the EVSI of extending a trial’s follow-up, both where a single known survival model is assumed and where we are uncertain about the true survival model. We extend a previously described nonparametric regression-based method for computing EVSI, which we demonstrate in synthetic case studies is fast, straightforward to implement, and scales easily to include any number of candidate survival models in the EVSI calculations.The EVSI methods that we present in this article can quantify the need for collecting additional follow-up data before making an adoption decision given any decision-making context.

The impact of the SARS-CoV-2 epidemic on mortality in South Africa in 2020

Background. The impacts on mortality of both the SARS-CoV-2 epidemic and the interventions to manage it differ between countries. The Rapid Mortality Surveillance System set up by the South African Medical Research Council based on data from the National Population Register (NPR) provides a means of tracking this impact on mortality in South Africa. Objectives. To report on the change in key metrics of mortality (numbers of deaths, life expectancy at birth, life expectancy at age 60, and infant, under-5, older child and adolescent, young adult, and adult mortality) over the period 2015 - 2020. The key features of the impact are contrasted with those measured in other countries. Methods. The numbers of registered deaths by age and sex recorded on the NPR were increased to account for both registered deaths that are not captured by the NPR and an estimate of deaths not reported. The estimated numbers of deaths together with estimates of the numbers in the population in the middle of each of the years were used to produce life tables and calculate various indicators. Results. Between 2019 and 2020, the number of deaths increased by nearly 53 000 (65% female), and life expectancy at birth fell by 1 year for females and by only 2.5 months for males. Life expectancy at age 60 decreased by 1.6 years for females and 1.2 years for males. Infant mortality, under-5 mortality and mortality of children aged 5 - 14 decreased by 22%, 20% and 10%, respectively, while that for older children and adolescents decreased by 11% for males and 5% for females. Premature adult mortality, the probability of a 15-year-old dying before age 60, increased by 2% for males and 9% for females. Conclusions. COVID-19 and the interventions to manage it had differential impacts on mortality by age and sex. The impact of the epidemic on life expectancy in 2020 differs from that in most other, mainly developed, countries, both in the limited decline and also in the greater impact on females. These empirical estimates of life expectancy and mortality rates are not reflected by estimates from agencies, either because agency estimates have yet to be updated for the impact of the epidemic or because they have not allowed for the impact correctly. Trends in weekly excess deaths suggest that the drop in life expectancy in 2021 will be greater than that in 2020.

Slowdown in Life Expectancy Improvements for European Countries From 2000 to 2019

Life expectancy improvements have slowed across Europe since around 2010 for unknown reasons. We aimed to assess the contribution of specific conditions and risk factors to changes in life expectancy. We compared Global Burden of Disease (GBD) 2019 estimates for life expectancy at birth, years of life lost to premature mortality (YLLs) and population attributable fractions (PAFs) for risk factors, for 17 European Economic Area (EEA) countries from 2000 to 2010 and from 2010 to 2019. All 17 countries experienced a slowdown in life expectancy improvements after 2010, after decades of improvement. Denmark experienced the smallest drop in improvement from 2000 to 2010 compared to 2010 to 2019 (0.75 years drop), followed by Norway (0.79), Iceland (0.86), Finland and Sweden (both 0.89). The 5 countries with the largest drop in improvement were Spain (1.6 years drop), the Netherlands (1.88), Portugal (1.92), the United Kingdom (UK) (2.13), and Ireland (2.77). Ischaemic heart disease and stroke made the biggest contribution to the slowdown in life expectancy. Important risk factors for mortality varied by country and included tobacco, drug and alcohol use, and high fasting plasma glucose. The Nordic countries have maintained improvements in life expectancy substantially better than other European countries. The different patterns in different countries suggest multiple factors are contributing to the changes, including specific conditions, risks and behaviours, and broader societal determinants of health. Large scale, international, co-ordinated research is needed to better understand these changes and inform policy actions, particularly as the COVID-19 pandemic will increase international differences.

Life expectancy and cancer survival in Oncosalud: outcomes over a 15-year period in a Peruvian private institution.

BackgroundThere is a large gap in the data on cancer outcomes in Latin America, making it difficult to establish adequate cancer control policies in the region. The aim of our study was to describe the survival, life expectancy estimates and life expectancy changes over time for a large cohort of Peruvian patients insured with Oncosalud, a private healthcare system.Patients and methodsWe evaluated a retrospective cohort of patients diagnosed between 2000 and 2015 in Oncosalud (Lima-Peru). Cases included colon, rectum, stomach, bladder, breast, prostate and non-melanoma skin cancers. Survival was evaluated with the Kaplan–Meier methodology. The standard period life table was used to estimate the excess mortality risks of patients in our cohort compared to the population covered by the Peruvian Superintendence of Banks, Insurance Companies and Pension Funds (SBS). The years of life lost was estimated based on SBS population, matching patients by age and sex.ResultsA large cohort of 7,687 Peruvian cancer patients managed in a 15-year period was eligible. If patients survive 5 years after a cancer diagnosis, life expectancy tends to be close to that of a population without cancer. The number of years of life lost at diagnosis was higher at the youngest ages, steadily decreasing thereafter. During the first years after cancer diagnosis, young patients face a much higher loss in life expectancy than older ones. Patients suffering from colon, rectum, stomach and bladder cancer are the most affected by the years of life lost.ConclusionIn cancer patients surviving ≥ 5 years, life expectancy becomes similar to that observed in a population with similar socioeconomic characteristics. The estimated survival rate in our cohort is higher than that reported by public cancer registries in Peru. This could be explained by the different socio-economic background and access to specialised cancer care.

Life expectancy and its adjustment in cerebral palsy with severe impairment: Are we doing this right?

In children with very severe cerebral palsy, an adversarial legal process for medical negligence, when liability is admitted, requires an estimate of life expectancy. Medical experts using the same cohort data and the same clinical facts can produce quite different life expectancies, leading to arguments in legal conferences and courts. The issues that commonly arise include between-country comparisons, projected and therapy-induced advanced life expectancies, and the contribution of epilepsy, scoliosis, and especially cognition to life expectancy. In this review, these factors are discussed from an arithmetic, statistical, and medical viewpoint to initiate debate on the issue, including whether median survival should be advocated.

Life expectancy and potential years of life lost for schizophrenia in western China

Excess mortality in people with schizophrenia has been extensively reported. However, little is known about the life expectancy and potential years of life lost (PYLL) in western China. This study aimed to estimated life expectancy and PYLL for people with schizophrenia in western China. A total of 228,572 people with schizophrenia were included from National Information System for Psychosis in one province of western China. Life-expectancy was calculated by using Chiang's method. One-way ANOVA was used to compare the age-sex standardized PYLL for different causes of death among different demographic characteristics groups. Life expectancy for men and women with schizophrenia was 52.8 years and 59.0 years respectively. The overall PYLL of people with schizophrenia was 18.4 years, and suicide had the largest PYLL (31.2 years) among all causes of mortality. The PYLL due to suicide was significantly higher among men, high school and above, non-poverty, non-farmer and divorced people with schizophrenia. The PYLL due to diseases and medical conditions was higher among men, illiteracy, farmer and unmarried people with schizophrenia. Strategies to prevent causes of premature death in schizophrenia are urgently required in western China, particularly in the promotion of physical health and prevention of suicide.

Functional disability with systematic trends and uncertainty: a comparison between China and the US

AbstractChina and the US are two contrasting countries in terms of functional disability and long-term care. China is experiencing declining family support for long-term care and developing private long-term care insurance. The US has a more developed public aged care system and private long-term care insurance market than China. Changes in the demand for long-term care are driven by the levels, trends and uncertainty in mortality and functional disability. To understand the future potential demand for long-term care, we compare mortality and functional disability experiences in China and the US, using a multi-state latent factor intensity model with time trends and systematic uncertainty in transition rates. We estimate the model with the Chinese Longitudinal Healthy Longevity Survey (CLHLS) and the US Health and Retirement Study (HRS) data. The estimation results show that if trends continue, both countries will experience longevity improvement with morbidity compression and a declining proportion of the older population with functional disability. Although the elderly Chinese have a shorter estimated life expectancy, they are expected to spend a smaller proportion of their future lifetime functionally disabled than the elderly Americans. Systematic uncertainty is shown to be significant in future trends in disability rates and our model estimates higher uncertainty in trends for the Chinese elderly, especially for urban residents.

The frequency of demand and options for surgical treatment of breast cancer metastases in long and flat bones, depending on the histological subtype of the tumor

Introduction. Bone metastases increase the risk of developing a pathological fracture, spinal cord compression, pain syndrome and require palliative, radiation therapy and oncoortopedic operations. The appearance of these metastases and the above complications is associated with an unfavorable prognosis and negatively affects the quality of life of patients.Objective – to analyze the outcomes of surgical treatment in patients with breast cancer metastases to long and flat bones and to identify an optimal surgical tactics depending on the morphological subtype of the tumor.Materials and methods. Between April 2015 and April 2021, a total of 731 patients with breast cancer and bone metastases were consulted in the departments of the Russian Research Center of Radiology, Ministry of Health of Russia. Two hundred and thirty patients (31.5 %) had indications for orthopedic surgery. This study included 78 patients with breast cancer metastases to long or flat bones. Of them, 50 individuals had metastases to bones only, whereas 28 participants additionally had metastases to other organs. Luminal A and B breast cancer was diagnosed in 27 patients (34.6 %) and 40 patients (51.2 %), respectively. Ten participants (12.8 %) were found to have HER2-positive tumors, whereas one patient (1.3 %) had triplenegative cancer.Results. Eighteen patients with metastatic lesions in long bones have undergone bone grafting; 17 patients had intramedullary internal fixation with osteoplasty; and 1 patient had extramedullary internal fixation with osteoplasty. Forty two patients with metastatic lesions in the flat bones have undergone 39 osteoplasty surgeries of the iliac bone, while 3 patients had osteoplasty surgeries of the sternum. The survival rates of patients with luminal A, luminal B, HER2- positive, and triple-negative breast cancer were as follows: 1-year survival – 95, 84, 87 and 100 %, respectively; 3-year survival – 83, 64, 23 and 0 %, respectively; 5-year survival – 66, 32, 23 and 0 %, respectively. Thirty-one patients were lost to follow-up between month 0 and month 46. Eighteen patients died between month 1 and month 58.Conclusion. Patients with luminal A and B breast cancer and threatened pathologic fracture should undergo intramedullary/extramedullary internal fixation, while for patients who already developed pathologic fracture and their estimated life expectancy does not exceed 1 months, it is recommended to perform bone grafting regardless of the tumor immunohistochemical type. Patients with threatened pathologic fractures demonstrated a more favorable prognosis, better functional status, and higher survival rates than patients with pathologic fractures: 1-year survival was 90 and 87 %, respectively; 3-year survival was 67 and 58 %, respectively, and 5-year survival was 54 and 0 %, respectively. Radiation therapy increases the risk of pathological fractures, but is not a contraindication for orthopedic surgery.

Prognostic value of the Tokuhashi scale when choosing a method of surgical treatment of metastatic lesions of the spine

Introduction. Metastatic spinal lesion remains one of the most difficult problems of modern medicine. The purpose of treatment of patients with metastatic spinal lesion is to reduce pain, improve the quality of life, restore stability in the affected segment, prevent or reduce neurological deficits. In order to build the right treatment tactics, it is necessary to evaluate the prognosis of the life of a patient with spinal metastases before treatment.The study objective is to evaluate the prognostic significance of the Tokuhashi scale in patients with metastatic spinal lesion.Materials and methods. The study included 124 patients with metastatic spinal lesion operated in the spinal department in the period from March 2013 to July 2019 (64 (52 %) men and 60 (48%) women). The average age was 59 years and ranged from 18 to 78 years. The catamnesis ranged from 1 month to 6 years. 6 (5 %) spinal tumors were radically removed, palliative removal was performed in 77 (62 %) cases. In the remaining cases, 41 (33 %) underwent vertebroplasty. The mandatory diagnostic protocol of the preoperative examination included oncological status, clinical and neurological examination. The functional status of the patient was assessed on the Karnofski scale, life expectancy – on the Tokuhashi scale. In terms of preoperative examination, patients underwent computed tomography examination with intravenous contrast of three zones: the thoracic, abdominal cavities and pelvic region to determine the degree of dissemination of the process and, in some cases, to identify the primary focus. Currently, positron emission tomography is the optimal method of investigation at the preoperative stage. However, this method is not yet available in all clinics, so performing computed tomography scans of three zones is currently the optimal “gold standard” for examining this category of patients..Results. The life expectancy estimate was calculated for each patient according to the Tokuhashi scale (2005). Survival analysis was performed using Kaplan-Meier curves within the Tokuhashi prognostic groups. The median survival within the Tokuhashi groups was more than 3 years for the group of 12–15 points (life expectancy over a year), 14 months for the group of 9–11 points (life expectancy 6 to 12 months) and 7 months for the group of 1–8 points (life expectancy less than 6 months). The Cox model was used to identify factors related to survival.Conclusion. Determining the tactics of surgical treatment of a patient with a metastatic lesion of the spine is a complex and multicomponent question to which there is no unambiguous answer. A multidisciplinary consultation is currently the most adequate and reliable way to determine the treatment strategy for this category of patients. The use of the Tokuhashi prognostic scale is an additional effective tool for determining the life expectancy of patients with spinal metastases, and thus, in some cases, serve as the tool with which it is possible to determine the tactics of surgical treatment of patients.

Estimating patient health in prostate cancer treatment counseling.

We assessed the concordance among urologists' judgment of health quartiles for patients with localized prostate cancer, and compared the life expectancy (LE) and ensuing treatment recommendations when following National Comprehensive Cancer Network (NCCN) guidelines based on actuarial life tables versus the Kent model, a validated LE prediction model. NCCN suggests using actuarial life tables and relying on surgeon assessment of patient health to increase (for the best quartile) or decrease (for the worst quartile) LE by 50%. Eleven urologic surgeons allocated quartile of health and recommended treatments for ten patient vignettes. The 10-year survival probability was calculated using the Kent model and compared to the life-table estimate based on health quartile by surgeon consensus. Surgeon assessment agreed with the presumed true quartile of health based on a validated model in 41% of cases. For no case did three-quarters of surgeons assign health quartile correctly; in half of cases, <50% of surgeons assigned the correct quartile. The NCCN comorbidity-adjusted LE estimates underestimated risk of death in the best health quartile and overestimated risk of death in the worst health quartile, compared to the Kent model. Patients with LE > 10 years on NCCN estimation were recommended more frequently for surgery (81%) and those with ≤10 years estimated LE were more commonly recommended for radiation (57%) or observation (29%). A method based on physician-assessed health quartiles for LE estimation, as suggested by the NCCN guidelines, appears too crude to be used in the treatment counseling of men with localized prostate cancer, as compared to a validated prediction model, such as the Kent model.

A spatiotemporal analysis of inequalities in life expectancy and 20 causes of mortality in sub-neighbourhoods of Metro Vancouver, British Columbia, Canada, 1990-2016.

Spatially varying baseline data can help identify and prioritise actions directed to determinants of intra-urban health inequalities. Twenty-seven years (1990-2016) of cause-specific mortality data in British Columbia, Canada were linked to three demographic data sources. Bayesian small area estimation models were used to estimate life expectancy (LE) at birth and 20 cause-specific mortality rates by sex and year. The gaps in LE for males and females ranged from 6.9 years to 9.5 years with widening inequality in more recent years. Inequality ratios increased for almost all causes, especially for HIV/AIDS and sexually transmitted infections, maternal and neonatal disorders, and neoplasms.

Mortality transition over a quarter century in rural South Africa: findings from population surveillance in Agincourt 1993-2018

ABSTRACT Background Mortality burden in South Africa since the mid-1990s has been characterized by a quadruple disease burden: HIV/AIDS and tuberculosis (TB); other communicable diseases (excluding HIV/AIDS and TB), maternal causes, perinatal conditions and nutritional deficiencies; non-communicable diseases (NCDs); and injuries. Causes from these broad groupings have persistently constituted the top 10 causes of death. However, proportions and rankings have varied over time, alongside overall mortality levels. Objective To provide evidence on the contributions of age and cause-of-death to changes in mortality levels in a rural South African population over a quarter century (1993–2018). Methods Using mortality and cause-of-death data from the Agincourt Health and Socio-Demographic Surveillance System (HDSS), we derive estimates of the distribution of deaths by cause, and hazards of death by age, sex, and time period, 1993–2018. We derive estimates of life expectancies at birth and years of life expectancy gained at age 15 if most common causes of death were deleted. We compare mortality indicators and cause-of-death trends from the Agincourt HDSS with South African national indicators generated from publicly available datasets. Results Mortality and cause-of-death transition reveals that overall mortality levels have returned to pre-HIV epidemic levels. In recent years, the concentration of mortality has shifted towards older ages, and the mortality burden from cardiovascular diseases and other chronic NCDs are more prominent as people living with HIV/AIDS access ART and live longer. Changes in life expectancy at birth, distribution of deaths by age, and major cause-of-death categories in the Agincourt population follow a similar pattern to the South African population. Conclusion The Agincourt HDSS provides critical information about general mortality, cause-of-death, and age patterns in rural South Africa. Realigning and strengthening the South African public health and healthcare systems is needed to concurrently cater for the prevention, control, and treatment of multiple disease conditions.

Fracture toughness as an alternative approach to quantify the ageing of insulation paper in oil

Oil-immersed transformers use paper and oil as insulation system which degrades slowly during the operation of these machines. Cellulose materials are used generally as insulation solid in power transformers. The degree of polymerization (DP), defined as number of repeating β-glucose residues in the cellulose molecule, is a critical property of cellulosic insulation material used in transformers, since it provides information about paper ageing and its mechanical strength. The fast-developing electric power industry demanding superior performance of electrical insulation materials has led to the development of new materials, as well as different drying techniques performed during transformer manufacturing and service when required. Both developments have caused some practical difficulties in the DP measurement. Moreover, the increasing interest in synthetic dielectric materials replacing cellulose materials requires measuring alternative properties to the DP to quantify the degradation of insulation solids over time. In this sense, this paper proposes the possibility of analyzing paper degradation through fracture toughness. This approach is different from the study of mechanical properties such as tensile strength or strain because it provides a tool for solving most practical problems in engineering mechanics, such as safety and life expectancy estimation of cracked structures and components which cannot to be considered through the traditional assessment of the mechanical resistance of the material. An accelerated thermal ageing of Kraft paper in mineral oil was carried out at 130 °C during different periods of time, to obtain information on the kinetics of the ageing degradation of the paper. Double-edged notched specimens were tested in tension to study their fracture toughness. The evolution of the load–displacement curves obtained for different ageing times at the ageing temperature of 130 °C was utilized to the determination of the stress intensity factor. Furthermore, different kinetic models based on this stress intensity factor were applied to relate its evolution over time as a function of the temperature. Finally, the correlation between the DP and stress intensity factor, which depends on the fiber angle, was also defined.Graphic abstract

Life expectancy with and without dementia in persons with mild cognitive impairment in the community

BackgroundVarious clinical studies have provided estimates of life expectancy of patients with mild cognitive impairment (MCI) from outpatient clinics, but whether these apply to community‐dwelling individuals at home or in primary care is uncertain.MethodsWithin the population‐based Rotterdam Study, we studied life expectancy with and without dementia in 648 community‐dwelling persons with MCI and 6410 without MCI. Participants aged 60 years and older were assessed for MCI at baseline (2002–2014) and subsequently followed for the onset of dementia and death. We used multistate life tables to determine age‐specific life expectancy with and without dementia by sex, educational attainment, and MCI subtype.ResultsTotal life expectancy for MCI ranged from 21.4 years (95% CI: 19.0–23.6) at age 60 to 2.6 years (1.6–3.6) at age 95. With advancing age, an increasing proportion of these years was lived with dementia (2.9 years [1.8–4.0] at age 60; 1.2 [0.2–2.2] at age 95). Women and higher educated individuals lived longer and lived more years with dementia. No differences in total life expectancy were observed by MCI subtype, although individuals with amnestic MCI lived a larger proportion of those years with dementia.ConclusionsPrognosis of MCI, in terms of life years lived with and without dementia, is more favorable in the general population than described in prior clinical observations, due likely to a substantial proportion of individuals with MCI in the clinic not seeking medical attention in an earlier stage.

Center-peripheral differences in life expectancy in Russia: a regional analysis

Elevated mortality (compared with the West) and significant spatial differences in life expectancy are serious challenges facing Russia. The goals of improving Russians' health and increasing their life expectancy by reducing inequality in mortality between regions and settlements are closely intertwined with the goals of spatial development of Russia, aimed at reducing interregional differences in the quality of life.&#x0D; This paper presents an assessment of the scope and dynamics of changes in mortality differences between the ‘center’ and the ‘periphery’ in 67 regions of Russia, which are home to three-quarters of the country's population. The selected research period - 2003-2018 - is characterized by a steady increase in life expectancy at birth (LE) in Russia. Using unpublished data from Rosstat for cities, we estimated life expectancy at birth in 67 regional centers and in the rest of the regions (‘periphery’). Depending on the magnitude of the differences in LE and the dynamics, we identified 6 types of regions. For those regions with a LE gap between center and periphery larger than the average, the decomposition method was applied, which made it possible to determine the key age groups and causes of death responsible for such high differences.&#x0D; In 36 regions of Russia classified as types I-III, the center-peripheral gap exceeded the average Russian level, while only in six regions in 2003-18 was there a tendency towards a reduction in the size of this gap. The decomposition results showed that elevated mortality of males in the periphery is due to a higher mortality rate at working age from external causes of death, especially from traffic accidents, homicides and suicides, as well as from ‘alcoholic’ causes of death; females in the periphery suffer from higher mortality rate at older ages from chronic non-communicable diseases.&#x0D; Despite the seemingly ‘objective’ nature of the mortality differences between the center and the periphery (the advantage of the former being due to the socio-demographic characteristics of its residents and the educational structure of the population, as well as to selective migration), the positive experience of other countries shows that effective public health policies can substantially reduce the degree of spatial inequality in mortality even if significant heterogeneity in the level of socio-economic development remains.