Статті в журналах: "Life years lost"

1

Killock, David. "Life gained, years lost?" Nature Reviews Clinical Oncology 11, no. 6 (April 22, 2014): 303. http://dx.doi.org/10.1038/nrclinonc.2014.67.

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2

Tu, Jack V. "Life Expectancy and Years of Potential Life Lost." Journal of the American College of Cardiology 66, no. 6 (August 2015): 656–58. http://dx.doi.org/10.1016/j.jacc.2015.05.073.

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3

Kuller, L. H. "Obesity and Years of Life Lost." JAMA: The Journal of the American Medical Association 289, no. 14 (April 9, 2003): 1777—a—1777. http://dx.doi.org/10.1001/jama.289.14.1777-b.

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4

Aggarwal, Sanya. "Estimating Disability Adjusted Life Years using Survival Models in HIV/ AIDS Risk Groups." Journal of Communicable Diseases 53, no. 04 (December 31, 2021): 36–47. http://dx.doi.org/10.24321/0019.5138.202172.

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Introduction: Advances in human immunodeficiency virus (HIV) treatment have led to greater survival rates and have brought about a shift in the burden of disease from mortality to morbidity. The main purpose of this study is to estimate the Disability Adjusted Life Years (DALYs) of HIV infected patients associated with different modes of transmission. Methods: Non-parametric Kaplan-Meier estimate has been utilised to develop survival function, and the mean residual life model has been utilised to estimate the life expectancy of patients alive at the end of the study. The impact of factors such as age, sex, hepatitis B and syphilis on life expectancy has also been assessed by fitting a proportional mean residual life model. DALYs have been calculated based on the results of both models. Results: Retrospective time to event data of HIV patients undergoing Antiretroviral Therapy (ART) in Dr Ram Manohar Lohia Hospital, New Delhi, India has been utilised to illustrate the modelling technique. The study suggests that in total, 42300.15 DALYs were lost which includes 39765.10 years of life lost due to premature death and 2535.05 years of life lived with disability. When the covariates were taken into consideration, 47592.14 DALYs were found to have been lost with an average of 17.64 DALYs lost per patient. Conclusion: Our results suggest that the high-risk groups such as homosexuals and parent to child transmission are a major cause of concern, which are in accordance with the existing national policies. Also, we would suggest that gender-based and age-based policies should be incorporated to reduce the burden of disease.

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5

Andersen, Per Kragh, Vladimir Canudas-Romo, and Niels Keiding. "Cause-specific measures of life years lost." Demographic Research 29 (December 5, 2013): 1127–52. http://dx.doi.org/10.4054/demres.2013.29.41.

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6

Wendland, G., and K. Lauterbach. "PMI11 LIFE YEARS LOST DUE TO CHD." Value in Health 5, no. 3 (May 2002): 213. http://dx.doi.org/10.1016/s1098-3015(10)61036-4.

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7

McGoldrick, Kathryn E. "Years of Life Lost Due to Obesity." Survey of Anesthesiology 48, no. 1 (February 2004): 56–57. http://dx.doi.org/10.1097/01.sa.0000108478.38017.ad.

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8

Allison, D. B. "Obesity and Years of Life Lost--Reply." JAMA: The Journal of the American Medical Association 289, no. 14 (April 9, 2003): 1777—b—1778. http://dx.doi.org/10.1001/jama.289.14.1777-c.

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9

Fontaine, Kevin R., David T. Redden, Chenxi Wang, Andrew O. Westfall, and David B. Allison. "Years of Life Lost Due to Obesity." JAMA 289, no. 2 (January 8, 2003): 187. http://dx.doi.org/10.1001/jama.289.2.187.

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10

L, Tanya. "How the U.S. Lost Years of Life." Scientific American 328, no. 2 (February 2023): 76. http://dx.doi.org/10.1038/scientificamerican0223-76.

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11

Tönnies, Thaddäus, Annika Hoyer, and Ralph Brinks. "Productivity-adjusted life years lost due to type 2 diabetes in Germany in 2020 and 2040." Diabetologia 64, no. 6 (March 4, 2021): 1288–97. http://dx.doi.org/10.1007/s00125-021-05409-3.

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Abstract Aims/hypothesis Type 2 diabetes can lead to reduced productivity during working age. We aimed to estimate productive life years lost associated with type 2 diabetes on the individual and population level in Germany in 2020 and 2040, while accounting for future trends in mortality. Methods Based on a mathematical projection model, we estimated age- and sex-specific productivity losses associated with type 2 diabetes during working age (20–69 years) in Germany in 2020 and 2040. Productivity losses in terms of excess mortality (years of life lost, YLL) and reductions in labour force participation, presenteeism and absenteeism (years of productivity lost, YPL) were summed to calculate productivity-adjusted life years (PALY) lost. Input data for the projection were based on meta-analyses, representative population-based studies and population projections to account for future trends in mortality. Results Compared with a person without type 2 diabetes, mean PALY lost per person with type 2 diabetes in 2020 was 2.6 years (95% CI 2.3, 3.0). Of these 2.6 years, 0.4 (95% CI 0.3, 0.4) years were lost due to YLL and 2.3 (95% CI 1.9, 2.6) years were lost due to YPL. Age- and sex-specific results show that younger age groups and women are expected to lose more productive life years than older age groups and men. Population-wide estimates suggest that 4.60 (95% CI 4.58, 4.63) million people with prevalent type 2 diabetes in 2020 are expected to lose 12.06 (95% CI 10.42, 13.76) million PALY (1.62 million years due to YLL and 10.44 million years due to YPL). In 2040, individual-level PALY lost are projected to slightly decrease due to reductions in YLL. In contrast, population-wide PALY lost are projected to increase to 15.39 (95% CI 13.19, 17.64) million due to an increase in the number of people with type 2 diabetes to 5.45 (95% CI 5.41, 5.50) million. Conclusions/interpretation On the population level, a substantial increase in productivity burden associated with type 2 diabetes was projected for Germany between 2020 and 2040. Efforts to reduce the incidence rate of type 2 diabetes and diabetes-related complications may attenuate this increase. Graphical abstract

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12

Raicevic, Jagos, Milan Merkle, Joachim Enrhard, and Marko Ninkovic. "Years of life lost due to external radiation exposure." Nuclear Technology and Radiation Protection 19, no. 2 (2004): 40–46. http://dx.doi.org/10.2298/ntrp0402040r.

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In this paper a new approach for calculation of the years of life lost per excess death due to stochastic health effects is applied to external exposure pathways. The short-term external exposures are due to the passage of radioactive cloud and due to the skin and clothes contamination. The long-term external exposure is the one from the radioactive material deposited on the ground (groundshine). Three nuclides, 131I, 137Cs, and 239Pu, and with the extremely wide range of half-life are considered in order to examine their possible influence on the calculated values of years of life lost. For each of these nuclides, the number of years of life lost has been found as a decreasing function of the age at the expo sure and presented graphically in this paper. For protracted exposures, the fully averaged number of years of life lost is negative correlated with the nuclide?s half-life. On the other hand, the short-term external exposures do not depend on the nuclide?s half-life. In addition, a weak years of life lost dependence of the dose has been commented.

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13

Wrigley-Field, Elizabeth. "Life Years Lost to Police Encounters in the United States." Socius: Sociological Research for a Dynamic World 6 (January 2020): 237802312094871. http://dx.doi.org/10.1177/2378023120948718.

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How much life in the United States is lost to encounters with the police? The author builds on a demographic life table model by Edwards, Lee, and Esposito to estimate, for race- and gender-specific populations, how many years of life are lost in two categories of police encounters: (1) encounters involving officer use of force and (2) all deaths involving police encounters. Average life years lost by individuals who are killed ranges from 39 years (white men) to 52 years (Native women). The loss of years per 100,000 people over their collective lifetimes is largest for Black men, with 5,696 years of life lost to all encounters with police, of which 3,772 years are lost to police use of force. This implies a loss of roughly 16,000 years of life for recent cohorts of Black men. These results provide context for current debates surrounding the cost and necessity of protests.

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14

Stevens, A. J., E. S. Searle, and G. P. Winyard. "AIDS and life years lost: one district's challenge." BMJ 294, no. 6571 (February 28, 1987): 572–73. http://dx.doi.org/10.1136/bmj.294.6571.572-a.

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15

Benjamin, Bernard. "Years of life lost and other mortality indices." Journal of the Institute of Actuaries 115, no. 4 (December 1988): 709–19. http://dx.doi.org/10.1017/s002026810004292x.

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In 1953 together with a colleague (Benjamin and Logan) the author called attention to a paper by Haenzel (1950) describing a new index of mortality years of life lost.The argument was that many people were living for more than the three score and ten years and that every earlier death represented a loss of potential further years of life; that adding up the total years of life lost might be a significant measure of the toll of largely preventable disease; that changes in this total year by year would maximize the improvement gained by curative and especially preventative medicine.

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16

Pikala, Małgorzata, Monika Burzyńska, and Irena Maniecka-Bryła. "Years of Life Lost Due to Cervical Cancer in Poland in 2000 to 2015." International Journal of Environmental Research and Public Health 16, no. 9 (May 1, 2019): 1545. http://dx.doi.org/10.3390/ijerph16091545.

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The aim of the study was an analysis of years of life lost due to cervical cancer in Poland in the period 2000 to 2015 with consideration given to differences related to education and place of residence. The study material was 28,274 death certificates of all female inhabitants of Poland, who died in 2000 to 2015 due to cervical cancer. In order to calculate years of life lost, the authors used indices: SEYLLp (Standard Expected Years of Life Lost per living person), SEYLLd (per deaths) and AAPC (Average Annual Percentage Change). The SEYLLp index (per 100,000) due to cervical cancer in Poland decreased from 394.3 in 2000 to 220.9 years of life in 2015 (AAPC = −3.6%). Women with university education lost the smallest number of years of life (SEYLLp = 139.0 in 2000 and 53.7 in 2015; AAPC = −5.4%), whereas those with elementary education had the greatest number of years of life lost (524.2 and 312.8; AAPC = −3.4%). Women living in rural areas lost on average 329.5 years in 2000 and 177.0 in 2015 (AAPC = −3.8%). In city areas, the values were 428.6 and 247.1 (AAPC = −3.4%). Many of the years of life lost could have been avoided by including more women, particularly those with elementary education, in screening examinations.

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17

Lin, Charles C., and Norman J. Johnson. "Decomposition of life expectancy and expected life-years lost by disease." Statistics in Medicine 25, no. 11 (2006): 1922–36. http://dx.doi.org/10.1002/sim.2381.

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18

Mazurek, Jacek M., John Wood, David J. Blackley, and David N. Weissman. "Coal Workers’ Pneumoconiosis–Attributable Years of Potential Life Lost to Life Expectancy and Potential Life Lost Before Age 65 Years — United States, 1999–2016." MMWR. Morbidity and Mortality Weekly Report 67, no. 30 (August 3, 2018): 819–24. http://dx.doi.org/10.15585/mmwr.mm6730a3.

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19

Cervantes, Claudio Alberto Dávila, and Marcela Agudelo Botero. "Average years of life lost due to breast and cervical cancer and the association with the marginalization index in Mexico in 2000 and 2010." Cadernos de Saúde Pública 30, no. 5 (May 2014): 1093–102. http://dx.doi.org/10.1590/0102-311x00113813.

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The objective of this study was to calculate average years of life lost due to breast and cervical cancer in Mexico in 2000 and 2010. Data on mortality in women aged between 20 and 84 years was obtained from the National Institute for Statistics and Geography. Age-specific mortality rates and average years of life lost, which is an estimate of the number of years that a person would have lived if he or she had not died prematurely, were estimated for both diseases. Data was disaggregated into five-year age groups and socioeconomic status based on the 2010 marginalization index obtained from the National Population Council. A decrease in average years of life lost due to cervical cancer (37.4%) and an increase in average years of life lost due breast cancer (8.9%) was observed during the period studied. Average years of life lost due to cervical cancer was greater among women living in areas with a high marginalization index, while average years of life lost due to breast cancer was greater in women from areas with a low marginalization index.

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20

Pyankova, Anastasiya I., Timur A. Fattakhov, and Mikhail B. Denisenko. "Years of Life Lost due to Premature Mortality in Russia, 1990-2021." Population and Economics 8, no. 4 (December 31, 2024): 92–122. https://doi.org/10.3897/popecon.8.e112749.

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According to the Global Burden of Disease, in Russia in 2019, the standardised rate of years of life lost from premature mortality reached its lowest value since the early 1990s. Still, it was 1.5 and 1.3 times higher than the similar rates for men and women in the WHO European Region. The authors sought to trace the evolution of the structural characteristics of years of life lost in Russia from 1990 to 2021 and identify the factors that led to such a significant gap in the level of losses from premature mortality. Estimates of the absolute number of years of life lost (YLL), age-specific (AYLL) and age-standardised rates (ES1976) of years of life lost (SYLL) for each sex were made based on Rosstat data for 1990-2021 on the distribution of deaths by sex, by five-year age groups (0, 1-4, 5-9...85+), and causes of death (statistical form C-51). A table for life expectancy at birth at 92.6 years was used as a standard life table. Redistribution of garbage codes of causes of death and correction for polymorbidity were not performed. Estimates of years of life lost are comparable to WHO estimates for Russia in absolute values by sex and age, while only partially so by causes of death. From 1990-2019, SYLL declined in both sexes, by a quarter. In 2019, SYLL for men was 374 per 1,000, 2.3 higher than that for women. Increased losses during the COVID-19 pandemic levelled up these gains. The maximum inequality in years of life lost for both sexes was characteristic of external causes of death (ECD) and respiratory diseases (RD), while the minimum, of neoplasms (NP). From 1990 to 2021, SYLL declined in both sexes from CD, NP, ECD, and RD. In the pre-pandemic period, there was an increase in losses from digestive diseases (DD), infectious diseases (ID) and a group of all other classes of causes of death. The approach we used enabled us to focus more on causes of death with a low standardised death rate (SDR), such as HIV, liver disease, and pancreatic conditions. While these causes contribute less to the SDR, deaths from them typically occur at a younger age, thus raising the total number of years of life lost. The analysis allowed us to reevaluate the impact of COVID-19, accountable for 1/7 and 1/5 of all years of life lost for men and women in 2021, respectively. Therefore, if women’s life expectancy decline was more significant than men’s, the SYLL for men during both years of the pandemic was higher than that for women.

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21

Kříž, Jaroslav. "Lost Years of Healthy Life in the Czech Republic." Hygiena 61, no. 2 (June 1, 2016): 88–90. http://dx.doi.org/10.21101/hygiena.a1451.

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22

Hankey, B. F. "Stat Bite: Average Years of Life Lost per Person." JNCI Journal of the National Cancer Institute 84, no. 17 (September 2, 1992): 1311. http://dx.doi.org/10.1093/jnci/84.17.1311.

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23

Luz, P. M., B. Grinsztejn, and A. P. Galvani. "Disability adjusted life years lost to dengue in Brazil." Tropical Medicine & International Health 14, no. 2 (February 2009): 237–46. http://dx.doi.org/10.1111/j.1365-3156.2008.02203.x.

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24

HAYBITTLE, JOHN L. "Should Years Lost Always be Equated with Life Expectancy?" International Journal of Epidemiology 23, no. 3 (1994): 592–94. http://dx.doi.org/10.1093/ije/23.3.592.

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25

Marlow, A. K. "Potential years of life lost: what is the denominator?" Journal of Epidemiology & Community Health 49, no. 3 (June 1, 1995): 320–22. http://dx.doi.org/10.1136/jech.49.3.320.

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26

Andersen, Per Kragh. "Life years lost among patients with a given disease." Statistics in Medicine 36, no. 22 (June 5, 2017): 3573–82. http://dx.doi.org/10.1002/sim.7357.

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27

Baudisch, Annette, and Jose Manuel Aburto. "How lifespan and life years lost equate to unity." Demographic Research 50 (April 4, 2024): 643–66. http://dx.doi.org/10.4054/demres.2024.50.24.

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28

Espinosa-Yépez, Kevin Ricardo. "Years of life lost due to cancer in Ecuador." Cancer Epidemiology 94 (February 2025): 102717. http://dx.doi.org/10.1016/j.canep.2024.102717.

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29

Grover, Steven A., Mohammed Kaouache, Philip Rempel, Lawrence Joseph, Martin Dawes, David C. W. Lau, and Ilka Lowensteyn. "Years of life lost and healthy life-years lost from diabetes and cardiovascular disease in overweight and obese people: a modelling study." Lancet Diabetes & Endocrinology 3, no. 2 (February 2015): 114–22. http://dx.doi.org/10.1016/s2213-8587(14)70229-3.

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30

Smyth, Breda, Valerie Hoffman, Jing Fan, and Yih-Ing Hser. "Years of potential life lost among heroin addicts 33 years after treatment." Preventive Medicine 44, no. 4 (April 2007): 369–74. http://dx.doi.org/10.1016/j.ypmed.2006.10.003.

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31

Kondrova, Nina S., Elmira R. Shaykhlislamova, Tatiana K. Larionova, Evgeniy G. Stepanov, Marina V. Frants, and Nadezhda I. Simonova. "Disability-adjusted life years due to occupational diseases in agriculture workers." Hygiene and sanitation 101, no. 1 (February 9, 2022): 53–61. http://dx.doi.org/10.47470/0016-9900-2022-101-1-53-61.

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Introduction. Currently, many agro-industrial countries are experiencing a rapid intensification of agricultural and livestock production, which can critically affect the health of workers employed in agriculture, one of the five leading sectors of the economy with an increased risk of occupational diseases. Materials and methods. In order to assess the lost years of healthy life due to occupational diseases among agricultural workers of the Republic of Bashkortostan, 1,199 cases of chronic occupational morbidity of workers over 57 years (1960-2017) were analyzed; the number of years of life not lived or lived insufficiently due to this disease was calculated (the DALY index). Results. During the analyzed period, 41 occupational diseases was diagnosed as a result of exposure to four groups of the main harmful production factors of the working environment and the labour process: physical (43.6%), physical overload (38.9%), harmful chemicals (14.0%) and biological factors (3.5%). It was found that agricultural workers lost 2,256.1 years of healthy life due to occupational diseases, 73.2% accounted for dorsopathies, occupational diseases from vibration exposure and soft tissue diseases. The frequency of detection of occupational diseases and their clinical characteristics are reflected in the total number of years of healthy life lost. More than 75% of a total load of occupational diseases was caused by physical factors together with physical overload. A five-year delay in forming occupational diseases reduces the total lost years of healthy life by 17.0% and a ten-year delay by 33.5%. Limitations. One thousand one hundred ninety-nine cases were assessed over 57 years of observation when studying occupational morbidity, which is a sufficient reference sample. Conclusion. Quantitative analysis of the DALY index due to occupational disease allows to assess the likely medical and social damage by the number of years of healthy life lost for patients and justify priority measures aimed at reducing this damage.

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Andarwatolanrain, Ana Nurjanah, Bambang Riyanto, and Hari Kusnanto. "Years of potential life lost due to HIV-AIDS infection and associated factors in Yogyakarta." Berita Kedokteran Masyarakat 32, no. 1 (January 1, 2016): 1. http://dx.doi.org/10.22146/bkm.7881.

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Years of potential life lost due to HIV-AIDS infection and associated factors in YogyakartaPurposeThis study aimed to determine the years of potential life lost and associated factors among people living with HIV in Yogyakarta special region, Indonesia.MethodsThis research was an observational study with a retrospective cohort design. Data included socio-demographic factors, behaviour and clinical conditions at time of diagnosis that were collected from medical records in Dr. Sardjito hospital. The cut-off age for years of potential life lost calculations was 65 years. ResultsThere were 193 people living with HIV who died during 2010-2015: 71% male, 47% married, 27% being infected by heterosexual, 73% did not receive antiretroviral therapy, and 37% experienced moderate anemia. The total of years of potential life lost was 6,003.7 years (average 31.12 years). The regression model indicated that among deceased people living with HIV, female, unmarried status and severe anemia were associated with additional 5.6 (p=0.002), 17 (p=0.000) and 5.9 (p=0.02) average years of potential life lost, respectively.ConclusionHIV screening should be performed intensively by Yogyakarta health office and hospitals. There should be a comprehensive education for both risk groups and general population, to increase awareness in following antiretroviral therapy before experiencing a severe clinical condition that could lead to premature mortality.

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Chan, Eunice Y. S., Davy Cheng, and Janet Martin. "Impact of COVID-19 on excess mortality, life expectancy, and years of life lost in the United States." PLOS ONE 16, no. 9 (September 1, 2021): e0256835. http://dx.doi.org/10.1371/journal.pone.0256835.

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This paper quantifies the net impact (direct and indirect effects) of the pandemic on the United States population in 2020 using three metrics: excess deaths, life expectancy, and total years of life lost. The findings indicate there were 375,235 excess deaths, with 83% attributable to direct, and 17% attributable to indirect effects of COVID-19. The decrease in life expectancy was 1.67 years, translating to a reversion of 14 years in historical life expectancy gains. Total years of life lost in 2020 was 7,362,555 across the USA (73% directly attributable, 27% indirectly attributable to COVID-19), with considerable heterogeneity at the individual state level.

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Perea, Lillia Magali Estrada, Alexandra Crispim Boing, Marco Aurélio Peres, and Antonio Fernando Boing. "Potential years of life lost due to oropharyngeal cancer in Brazil: 1979 to 2013." Revista de Saúde Pública 53 (February 7, 2019): 67. http://dx.doi.org/10.11606/s1518-8787.2019053001054.

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OBJECTIVE: To estimate the years of life lost by the Brazilian population due to mouth and pharynx cancer from 1979 to 2013, and analyze the temporal trends in the studied period, according to the country’s region, sex and anatomical site. METHODS: The death records were obtained from the Mortality Information System and the data referring to the population, from the censuses of the Brazilian Institute of Geography and Statistics of 1980, 1991, 2000, 2010, and from intercensal estimates for the other years. The rates of potential years of life lost were calculated by applying the method suggested by Romeder and McWhinnie, and their trends were calculated using the Prais-Winsten method with firstorder autocorrelation. The historical series were smoothed with the centered moving average technique of third order for white noise reduction. RESULTS: In the period from 1979 to 2013 in Brazil, there were a total of 107,506 premature deaths due to mouth and pharynx cancer, which generated a total of 1,589,501 potential years of life lost, the equivalent to a rate of 3.6 per 10,000 inhabitants. Males, whose rate was six times higher than for females, contributed with 85% of the years lost. The trends in the rates of years of life lost showed an annual 0.72% increase for men, 1.13% for women and 1.05% for pharynx cancer. CONCLUSIONS: The rate of potential years of life lost due to mouth and pharynx cancer in the country showed an upward trend within the studied period for both sexes, as well as for pharynx cancer and for the North, Northeast and Midwest regions.

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Moga, Ana-Maria. "Fictionalising Shakespeare’s ‘Lost Years’: Will’s Rise to Fame." Linguaculture 14, no. 1 (June 30, 2023): 101–20. http://dx.doi.org/10.47743/lincu-2023-1-0332.

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While the lack of information on Shakespeare’s life poses a great challenge to biographers in their pursuit of compiling the poet’s definitive Life, it is the early years of his career–the so-called ‘Lost Years’–which represent perhaps the biggest mystery to historians. Consequently, biographies fill in this gap by relying mostly on speculation and theories rather than hard facts. For this reason, this period seems to be a favourite for fictional representations of William Shakespeare’s life, offering the most space for creativity for the authors. Craig Pearce’s TV series Will (2017) specifically brings to the public a version of Shakespeare’s ‘Lost Years.’ Thus, the gaps in the poet’s life are filled in by setting his story in a rather dystopian England and by incorporating anachronistic elements in the historical narrative. For instance, Will’s arrival in London and his struggles are juxtaposed with a soundtrack that is comprised of modern rock songs, while the characters’ costumes, make-up, colourful hair and tattoos are reminiscent of popular culture films such as The Hunger Games or Star Wars, as well as of the punk rock culture of the 1970s. This way, the young man’s journey to fame is associated with the modern-day equivalent of a rock star’s ascension.

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Owen, Alice J., Salsabil B. Maulida, Ella Zomer, and Danny Liew. "Productivity burden of smoking in Australia: a life table modelling study." Tobacco Control 28, no. 3 (July 16, 2018): 297–304. http://dx.doi.org/10.1136/tobaccocontrol-2018-054263.

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ObjectivesThis study aimed to examine the impact of smoking on productivity in Australia, in terms of years of life lost, quality-adjusted life years (QALYs) lost and the novel measure of productivity-adjusted life years (PALYs) lost.MethodsLife table modelling using contemporary Australian data simulated follow-up of current smokers aged 20–69 years until age 70 years. Excess mortality, health-related quality of life decrements and relative reduction in productivity attributable to smoking were sourced from published data. The gross domestic product (GDP) per equivalent full-time (EFT) worker in Australia in 2016 was used to estimate the cost of productivity loss attributable to smoking at a population level.ResultsAt present, approximately 2.5 million Australians (17.4%) aged between 20 and 69 years are smokers. Assuming follow-up of this population until the age of 70 years, more than 3.1 million years of life would be lost to smoking, as well as 6.0 million QALYs and 2.5 million PALYs. This equates to 4.2% of years of life, 9.4% QALYs and 6.0% PALYs lost among Australian working-age smokers. At an individual level, this is equivalent to 1.2 years of life, 2.4 QALYs and 1.0 PALY lost per smoker. Assuming (conservatively) that each PALY in Australia is equivalent to $A157 000 (GDP per EFT worker in 2016), the economic impact of lost productivity would amount to $A388 billion.ConclusionsThis study highlights the potential health and productivity gains that may be achieved from further tobacco control measures in Australia via application of PALYs, which are a novel, and readily estimable, measure of the impact of health and health risk factors on work productivity.

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Liu, Xiang, Dan Wang, Ruoxin Fan, Rongke Wang, Hu Xiang, Xianmei Yang, and Yuanyuan Liu. "Life expectancy and potential years of life lost for schizophrenia in western China." Psychiatry Research 308 (February 2022): 114330. http://dx.doi.org/10.1016/j.psychres.2021.114330.

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Andersen, Lykke E., and Alejandra Gonzáles Rocabado. "Life and Death During the First Year of the COVID-19 Pandemic: An analysis of cross-country differences in changes in quantity and quality of life." Revista Latinoamericana de Desarrollo Económico, no. 35 (May 7, 2021): 9–57. http://dx.doi.org/10.35319/lajed.202135438.

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This study carries out a cross-country analysis of changes in quantity and quality of life during the first year of the COVID-19 pandemic for 124 countries. Changes in the quantity of life are measured as life years lost to COVID-19, including excess deaths not officially reported as COVID-19 deaths. Changes in quality of life are proxied by the average change in daily mobility, compared to a pre-COVID baseline. We find a significant negative correlation between the two, meaning that the countries with the biggest reductions in mobility are also the countries with the biggest losses of life years. We calculate that about 48 million life years were lost during the first year of the pandemic, corresponding to 0.018% of all expected life years. For comparison, at least double the amount of life years are lost every year due to children dying of diarrhea. About 28 million life years are created every day from babies being born, so the first year of the pandemic set us back less than two days in terms of quantity of life. The setbacks in terms of quality of life are several orders of magnitude larger. Some countries have suffered close to a 50% reduction in mobility sustained over 12 months, with devastating effects on many aspects of quality of life. We estimate that 1.2 billion quality life years were lost due to mobility reductions, which is 25 times as many as life years lost due to COVID-19 related deaths during the first year of the pandemic.

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Gebeyehu, Daniel Teshome, Leah East, Stuart Wark, and Md Shahidul Islam. "Disability-adjusted life years (DALYs) based COVID-19 health impact assessment: A systematic review protocol." PLOS ONE 17, no. 9 (September 12, 2022): e0274468. http://dx.doi.org/10.1371/journal.pone.0274468.

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Background COVID-19 is a highly contagious infectious disease that emerged in 2019. This disease is causing devastating health, socio-economic, and economic crises. More specifically COVID-19 is affecting both the quality and length of human life. The overall health impact of this disease is measured by the disability-adjusted life years which is the sum of the life years lost due to disability (the effect on the health quality) and the years life lost due to premature death (effect on the length of life). The purpose of this review is to summarise DALYs-based health impact publications and produce compiled and informative literature that can aid the health regulators to make evidence-based decisions on mitigating COVID-19. Methods The review will be conducted using the PRISMA 2020 guidelines. The DALYs-based original observational and cross-sectional studies will be collected for assessing the health impact of COVID-19. Both the life quality and length impacts of COVID-19 will be reviewed. The life quality impact of COVID-19 will be measured using the life years lost due to disability (pre-recovery illness, pre-death illness, and post-acute consequences), and its impact on the length of life will be measured with years of life lost due to premature death (shortening of life expectancy). The combined health impact of COVID-19 on the quality and length of life will be measured in disability-adjusted life years. Discussion The impacts of COVID-19 on the two health outcomes (quality and length of life) will indicate the level of COVID-19 health burden. The increase or decrease of COVID-19 health impact might be due to the sample size differences of different studies and the omission of years lost due to post-acute consequences in some studies. After having a summarized systematic review health decision-makers will apply an impact-based response to COVID-19. Trail registration Systematic review registration: This protocol is pre-registered in PROSPERO with the registration number CRD42022324931.

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Carson, Daniel S., Navya Gunaje, Sarah K. Holt, Nana Frimpong, Jenney R. Lee, Liz Sage, Erika M. Wolff, and Yaw A. Nyame. "Abstract C139: Cancer related excess death and potential life years lost among Black Americans." Cancer Epidemiology, Biomarkers & Prevention 33, no. 9_Supplement (September 21, 2024): C139. http://dx.doi.org/10.1158/1538-7755.disp24-c139.

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Abstract Introduction: Cancer represents the second leading cause of death in the United States and disproportionately affects Black Americans. In recent years, cancer-related mortality rates have declined for both Black and White Americans. However, mortality rates and rate ratios alone are insufficient for characterizing the burden of cancer disparities between racial groups. Among the most prevalent cancers in the US, we evaluated trends in excess mortality and years of potential life lost between Black and White Americans. Methods: This was a serial cross-sectional study using US national level data from CDC Wonder between the years 1999-2020. We included White and non-Hispanic Black Americans with a cause of death from breast, prostate, lung, colon, bladder, or uterine cancer. We measured age-adjusted excess death as well as excess years of potential life lost for each cancer site among Black and White Americans, stratified by sex when applicable. Annual mortality rates for each cancer site were sourced from the CDC Cancer Statistic Data Visualization tool. Results: The age adjusted mortality rate for all cancers declined between 1999-2020 for Black (257.2 to 166.8 per 100,000) and White Americans (200.9 to 149.3 per 100,000). Site specific cancer mortality rates declined in Black and White Americans for breast, prostate, lung, colon, and bladder cancer, but increased for uterine cancer. Among the most prevalent cancer sites, there were a total of 115,43 excess deaths with 2,093,327 excess years potential life lost for Black men and 59,134 excess deaths with 1,508,052 excess years potential life lost for Black women over a 22-year period. The trend of annual excess death and years potential life lost has slowly increased for Black men with colon cancer as well as Black women with breast and uterine cancer. Annual excess death and years potential life lost in Black men with prostate cancer decreased until 2013 after which it has slowly increased. Conclusion: Despite declining mortality rates in most cancers in the United States, Black Americans still experience a staggering number of excess deaths and years potential life lost due to cancer. Furthermore, the discordance between declining mortality rates and increasing excess death or years potential life lost in breast, prostate, colon, and uterine cancer highlight that racial disparities in cancer care and outcomes are likely worsening among Black Americans. Action is needed to support interventions and organizations committed to addressing cancer health inequities among Black Americans. Citation Format: Daniel S. Carson, Navya Gunaje, Sarah K. Holt, Nana Frimpong, Jenney R. Lee, Liz Sage, Erika M Wolff, Yaw A. Nyame. Cancer related excess death and potential life years lost among Black Americans [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr C139.

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Mahendran, C. S., S. M. Kumar, and P. Katara. "Life expectancy decline in people with treated tuberculosis and the possible benefits of prophylaxis." CARDIOMETRY, no. 25 (February 14, 2023): 1444–49. http://dx.doi.org/10.18137/cardiometry.2022.25.14441449.

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Background: Evidence of significant, measurable, and preventable loads of mortality risk even after anti-tuberculosis therapy and cure would be a convincing, tangible, and meaningful indicator of the efficacy of prevention. Aims & Objectives: To study of a life expectancy decline in people with treated tuberculosis and the possible benefits of prophylaxis Methods & Materials: We examined the years of potential life lost between 918 people with latent tuberculous infection and a cohort of 386 cured tuberculosis (TB) patients. To estimate the anticipated years of potential life lost for each cohort and for demographic groupings, we built a regression model. Results: When compared to a group without active TB, decedents with a history of thoroughly treated TB are anticipated to lose an additional 3.6 years of life on average. White and Hispanic people were expected to see greater longevity losses than their Black and Asian counterparts. Conclusion: The expected lifetime of treated TB survivors was significantly different from that of a comparable group without active TB, according to our research. With a total of 1485 lifeyears lost, or the equivalent of more than 180 75-year lifespans, these excess losses are considerable. These results highlight an important lost opportunity cost for each TB case that could have been prevented: an average of 3.6 years of life. We come to the conclusion that despite adequate anti-tuberculosis treatment, there is still a significant burden of preventable mortality, which is a strong argument in favour of more widespread and organised use of prevention.

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Yaghoobi, Halimeh, Hassan Ahmadinia, Ziba Shabani, Reza Vazirinejad, Reza Safari, Roozbeh Shahizadeh, Fatemeh Zolfizadeh, and Mohsen Rezaeian. "Life expectancy and years of life lost in HIV patients under the care of BandarAbbas Behavioral Disorders Counseling Center." Nepal Journal of Epidemiology 7, no. 4 (August 10, 2018): 702–12. http://dx.doi.org/10.3126/nje.v7i4.20627.

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Background: HIV epidemic is mostly targeted adults and has numerous negative health, social, economic, cultural and political consequences. In this study Life Expectancy (LE) and Average Years of Life Lost (AYLL) in HIV/AIDS patients are estimated.Materials and Methods: In this descriptive study all the patients at the age of 18 and more under the care of BandarAbbas Behavioral Disorders Counseling Center (BBDCC) during 2005-2015 are included. The town of BandarAbbas is center of Hormozgan Province in southern Iran. LE and AYLL have been estimated based on Life Table.Results: One hundred thirty four of the 426 eligible patients died during the study period. Compared to the general population LE for HIV/AIDS patients at age 20 is 46 years less in comparison with the general population of BandarAbbas. Moreover, a total of 8839 years of life lost during 2005-2015.Conclusion: LE in HIV/AIDS patients is less than LE among BandarAbbas general population and AYLL among them is more than general population. Most of the years of life lost are preventable if the health care system seriously will implement programs to control HIV/AIDS.Nepal J Epidemiol. 2017;7(4); 702-712.

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Gardner, John W., and Jill S. Sanborn. "Years of Potential Life Lost (YPLL)—What Does it Measure?" Epidemiology 1, no. 4 (July 1990): 322–29. http://dx.doi.org/10.1097/00001648-199007000-00012.

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Gefeller, Olaf. "Years of Potential Life Lost (YPLL)—What Does It Measure?" Epidemiology 2, no. 2 (March 1991): 160. http://dx.doi.org/10.1097/00001648-199103000-00016.

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Yip, Paul S. F., Ka Y. Liu, and C. K. Law. "Years of Life Lost from Suicide in China, 1990–2000." Crisis 29, no. 3 (May 2008): 131–36. http://dx.doi.org/10.1027/0227-5910.29.3.131.

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Suicide is an important public health problem in China: It is the fifth leading cause of death in China, and suicide in China accounts for over 30% of the worlds overall suicide deaths. The substantial burden due to suicide has not been well recognized. This study aims to provide an estimate of the socioeconomic burden of the suicide problem in China in terms of years of life lost (YLL) and to discuss its implications. Suicide rates and the related YLL by age, gender, and region (urban/rural) from 1990 to 2000 were estimated using the most recent data from the Ministry of Health of China. The suicide rate in rural China was three times higher than that in urban areas. Suicide completers in rural areas shared 90% of total YLL. Rural women aged 25–39 years contributed the largest share of YLL. Our results show that some population subgroups contributed a disproportionate share to the disease burden of suicide. National strategies for suicide prevention should include targeted programs in catering the need of these specified subgroups in China.

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Larson, Bruce A. "Calculating disability-adjusted-life-years lost (DALYs) in discrete-time." Cost Effectiveness and Resource Allocation 11, no. 1 (2013): 18. http://dx.doi.org/10.1186/1478-7547-11-18.

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Laires, PA, M. Gouveia, H. Canhão, A. Rodrigues, N. Gouveia, M. Eusébio, and JC Branco. "Years of Working Life Lost Caused By Osteoarthritis In Portugal." Value in Health 18, no. 7 (November 2015): A642. http://dx.doi.org/10.1016/j.jval.2015.09.2294.

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Mariotti, Sergio, Paola D'Errigo, Simona Mastroeni, and Karen Freeman. "Years of life lost due to premature mortality in Italy." European Journal of Epidemiology 18, no. 6 (June 2002): 513–21. http://dx.doi.org/10.1023/a:1024635401206.

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O'shea, E. "Social gradients in years of potential life lost in Ireland." European Journal of Public Health 13, no. 4 (December 1, 2003): 327–33. http://dx.doi.org/10.1093/eurpub/13.4.327.

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Manjunath, Lakshman, Jiaqi Hu, Latha Palaniappan, and Fatima Rodriguez. "Years of Potential Life Lost from Cardiovascular Disease Among Hispanics." Ethnicity & Disease 29, no. 3 (July 18, 2019): 477–84. http://dx.doi.org/10.18865/ed.29.3.477.

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Objective: To quantify the impact of cardiovascular disease and its subtypes on the premature mortality of Hispanics in the United States.Methods: We used national death records to identify deaths for the three largest Hispanic subgroups (Mexicans, Puerto Ricans, and Cubans) in the United States from 2003 to 2012 (N = 832,550). We identified all deaths from cardiovascular disease and by subtype (ie, ischemic, cerebrovascular, hypertensive and heart failure) using the underlying cause of death via ICD-10 codes. Years of potential life lost (YPLL) was calculated by age categories standardizing with the 2000 US Census population. Population estimates were calculated using linear interpolation from 2000 and 2010 US Census data.Results: After standardization, Puerto Ricans experienced the highest YPLL for all types of cardiovascular disease compared with Mexicans and Cubans (1,139 years per 100,000 compared with 868 and 841, respectively), a disparity that remained consistent over the course of a decade. Among different subcategories of cardiovascular disease, Puerto Ricans had the highest YPLL for ischemic and hypertensive heart disease, while Mexicans had the highest YPLL from cerebrovascular disease.Conclusions: In conclusion, disaggregation of Hispanic subgroups revealed marked heterogeneity in premature cardiovascular mortality. These findings suggest that measures to improve the cardiovascular health of Hispanics should incorporate subgroup status as a key part of public health strategy.Ethn Dis. 2019;29(3):477-484; doi:10.18865/ed.29.3.477

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