wow-inequalities/02-data/intermediate/wos_sample/bdc65030329b3c4e34a089ccfed91919-foreman-kyle-j.-and/info.yaml

abstract: 'Background Understanding potential trajectories in health and drivers of

  health is crucial to guiding long -Lentil investments and policy

  itnpletnentation. Past work on forecasting has provided an incomplete

  landscape of future health scenarios, highlighting a need for a more

  robust modelling platform from which policy options and potential health

  trajectories can be assessed. This study provides a novel approach to

  modelling life expectancy, all -cause mortality and cause of death

  forecasts and alternative future scenarios for 250 causes of death from

  2016 to 2040 in 195 countries and territories.

  Methods We modelled 250 causes and cause groups organised by the Global

  Burden of Diseases, Injuries, and Risk Factors Study (GBD) hierarchical

  cause structure, using GBD 2016 estimates from 1990-2016, to generate

  predictions for 2017-40. Our modelling framework used data from the GBD

  2016 study to systematically account for the relationships between risk

  factors and health outcomes for 79 independent drivers of health. We

  developed a three-component model of cause-specific mortality: a

  component due to changes in risk factors and select interventions; the

  underlying mortality rate for each cause that is a function of income

  per capita, educational attainment, and total fertility rate under 25

  years and time; and an autoregressive integrated moving average model

  for unexplained changes correlated with time. We assessed the

  performance by fitting models with data from 1990-2006 and using these

  to forecast for 2007-16. Our final model used for generating forecasts

  and alternative scenarios was fitted to data from 1990-2016. We used

  this model for 195 countries and territories to generate a reference

  scenario or forecast through 2040 for each measure by location.

  Additionally, we generated better health and worse health scenarios

  based on the 85th and 15th percentiles, respectively, of annualised

  rates of change across location-years for all the GBD risk factors,

  income per person, educational attainment, select intervention coverage,

  and total fertility rate under 25 years in the past. We used the model

  to generate all-cause age-sex specific mortality, life expectancy, and

  years of life lost (YLLs) for 250 causes. Scenarios for fertility were

  also generated and used in a cohort component model to generate

  population scenarios. For each reference forecast, better health, and

  worse health scenarios, we generated estimates of mortality and YLLs

  attributable to each risk factor in the future.

  Findings Globally, most independent drivers of health were forecast to

  improve by 2040, but 36 were forecast to worsen. As shown by the better

  health scenarios, greater progress might be possible, yet for some

  drivers such as high body-mass index (BMI), their toll will rise in the

  absence of intervention. We forecasted global life expectancy to

  increase by 4.4 years (95\% UI 2.2 to 6.4) for men and 4.4 years (2.1 to

  6.4) for women by 2040, but based on better and worse health scenarios,

  trajectories could range from a gain of 7.8 years (5.9 to 9.8) to a

  non-significant loss of 0.4 years (-2.8 to 2.2) for men, and an increase

  of 7.2 years (5.3 to 9.1) to essentially no change (0.1 years {[}-2.7 to

  2. 5]) for women. In 2040, Japan, Singapore, Spain, and Switzerland had

  a forecasted life expectancy exceeding 85 years for both sexes, and 59

  countries including China were projected to surpass a life expectancy of

  80 years by 2040. At the same time, Central African Republic, Lesotho,

  Sotnalia, and Zimbabwe had projected life expectancies below 65 years in

  2040, indicating global disparities in survival are likely to persist if

  current trends hold. Forecasted YLLs showed a rising toll from several

  non-communicable diseases (NCDs), partly driven by population growth and

  ageing. Differences between the reference forecast and alternative

  scenarios were most striking for HIV/AIDS, for which a potential

  increase of 120-2\% (95\% UI 67.2-190.3) in YLLs (nearly 118 million)

  was projected globally from 2016-40 under the worse health scenario.

  Compared with 2016, NCDs were forecast to account for a greater

  proportion of YLLs in all GB D regions by 2040 (67.3\% of YLLs {[}95\%

  UI 61.9-72.3] globally); nonetheless, in many lower-income countries,

  communicable, maternal, neonatal, and nutritional (CMNN) diseases still

  accounted for a large share of YLLs in 2040 (eg, 53.5\% of YLLs {[}95\%

  UI 48.3-58.5] in Sub-Saharan Africa). There were large gaps for many

  health risks between the reference forecast and better health scenario

  for attributable YLLs. In most countries, metabolic risks amenable to

  health care (eg, high blood pressure and high plasma fasting glucose)

  and risks best targeted by population -level or intersectoral

  interventions (eg, tobacco, high BMI, and ambient particulate matter

  pollution) had some of the largest differences between reference and

  better health scenarios. The main exception was sub-Saharan Africa,

  where many risks associated with poverty and lower levels of development

  (eg, unsafe water and sanitation, household air pollution, and child

  malnutrition) were projected to still account for substantive

  disparities between reference and better health scenarios in 2040.

  Interpretation With the present study, we provide a robust, flexible

  forecasting platform from which reference forecasts and alternative

  health scenarios can be explored in relation to a wide range of

  independent drivers of health. Our reference forecast points to overall

  improvements through 2040 in most countries, yet the range found across

  better and worse health scenarios renders a precarious vision of the

  future a world with accelerating progress from technical innovation but

  with the potential for worsening health outcomes in the absence of

  deliberate policy action. For some causes of YLLs, large differences

  between the reference forecast and alternative scenarios reflect the

  opportunity to accelerate gains if countries move their trajectories

  toward better health scenarios or alarming challenges if countries fall

  behind their reference forecasts. Generally, decision makers should plan

  for the likely continued shift toward NCDs and target resources toward

  the modifiable risks that drive substantial premature mortality. If such

  modifiable risks are prioritised today, there is opportunity to reduce

  avoidable mortality in the future. However, CMNN causes and related

  risks will remain the predominant health priority among lower -income

  countries. Based on our 2040 worse health scenario, there is a real risk

  of HIV mortality rebounding if countries lose momentum against the HIV

  epidemic, jeopardising decades of progress against the disease.

  Continued technical innovation and increased health spending, including

  development assistance for health targeted to the world''s poorest

  people, are likely to remain vital components to charting a future where

  all populations can live full, healthy lives. Copyright 2018 The

  Author(s). Published by Elsevier Ltd. This is an Open Access article

  under the CC BY 4.0 license.'
affiliation: 'Murray, CJL (Corresponding Author), Univ Washington, Inst Hlth Metr
  \& Evaluat, Seattle, WA 98121 USA.

  Foreman, Kyle J.; Dolgert, Andrew; Fukutaki, Kai; Fullman, Nancy; McGaughey, Madeline;
  Pletcher, Martin A.; Smith, Amanda E.; Tang, Kendrick; Yuan, Chun-Wei; Brown, Jonathan
  C.; Patel, Disha J.; Carter, Austin; Cercy, Kelly; Douwes-Schultz, Dirk; Frank,
  Tahvi; Goettsch, Falko; Nandakumar, Vishnu; Reitsma, Marissa B.; Sadat, Nafis; Sorensen,
  Reed J. D.; Srinivasan, Vinay; Updike, Rachel L.; Lim, Stephen S.; Mokdad, Ali H.;
  Vollset, Stein Emil; Murray, Christoper J. L., Univ Washington, Inst Hlth Metr \&
  Evaluat, Seattle, WA 98121 USA.

  Marquez, Neal, Univ Washington, Dept Sociol, Seattle, WA 98195 USA.

  Friedman, Joseph, Univ Calif Los Angeles, Sch Publ Hlth, Los Angeles, CA 90024 USA.

  Liu, Patrick Y., Univ Calif Los Angeles, Sch Med, Los Angeles, CA USA.

  He, Jiawei, Baidu, Beijing, Peoples R China.

  Heuton, Kyle P., OM1, Boston, MA USA.

  Holmberg, Mollie, Univ British Columbia, Dept Geog, Vancouver, BC, Canada.

  Reidy, Patrick, Wellframe, Boston, MA USA.

  Reuter, Vince, Mem Sloan Kettering Canc Ctr, 1275 York Ave, New York, NY 10021 USA.

  Lopez, Alan D., Univ Melbourne, Sch Populat \& Global Hlth, Melbourne, Vic, Australia.

  Lozano, Rafael, Natl Inst Publ Hlth, Cuernavaca, Morelos, Mexico.'
author: Foreman, Kyle J. and Marquez, Neal and Dolgert, Andrew and Fukutaki, Kai and
  Fullman, Nancy and McGaughey, Madeline and Pletcher, Martin A. and Smith, Amanda
  E. and Tang, Kendrick and Yuan, Chun-Wei and Brown, Jonathan C. and Friedman, Joseph
  and He, Jiawei and Heuton, Kyle P. and Holmberg, Mollie and Patel, Disha J. and
  Reidy, Patrick and Carter, Austin and Cercy, Kelly and Capin, Abigail and Douwes-Schultz,
  Dirk and Frank, Tahvi and Goettsch, Falko and Liu, Patrick Y. and Nandakumar, Vishnu
  and Reitsma, Marissa B. and Reuter, Vince and Sadat, Nafis and Sorensen, Reed J.
  D. and Srinivasan, Vinay and Updike, Rachel L. and York, Hunter and Lopez, Alan
  D. and Lozano, Rafael and Lim, Stephen S. and Mokdad, Ali H. and Vollset, Stein
  Emil and Murray, Christoper J. L.
author-email: cjlm@uw.edu
author_list:
- family: Foreman
  given: Kyle J.
- family: Marquez
  given: Neal
- family: Dolgert
  given: Andrew
- family: Fukutaki
  given: Kai
- family: Fullman
  given: Nancy
- family: McGaughey
  given: Madeline
- family: Pletcher
  given: Martin A.
- family: Smith
  given: Amanda E.
- family: Tang
  given: Kendrick
- family: Yuan
  given: Chun-Wei
- family: Brown
  given: Jonathan C.
- family: Friedman
  given: Joseph
- family: He
  given: Jiawei
- family: Heuton
  given: Kyle P.
- family: Holmberg
  given: Mollie
- family: Patel
  given: Disha J.
- family: Reidy
  given: Patrick
- family: Carter
  given: Austin
- family: Cercy
  given: Kelly
- family: Capin
  given: Abigail
- family: Douwes-Schultz
  given: Dirk
- family: Frank
  given: Tahvi
- family: Goettsch
  given: Falko
- family: Liu
  given: Patrick Y.
- family: Nandakumar
  given: Vishnu
- family: Reitsma
  given: Marissa B.
- family: Reuter
  given: Vince
- family: Sadat
  given: Nafis
- family: Sorensen
  given: Reed J. D.
- family: Srinivasan
  given: Vinay
- family: Updike
  given: Rachel L.
- family: York
  given: Hunter
- family: Lopez
  given: Alan D.
- family: Lozano
  given: Rafael
- family: Lim
  given: Stephen S.
- family: Mokdad
  given: Ali H.
- family: Vollset
  given: Stein Emil
- family: Murray
  given: Christoper J. L.
da: '2023-09-28'
doi: 10.1016/S0140-6736(18)31694-5
eissn: 1474-547X
esi-highly-cited-paper: Y
esi-hot-paper: N
files: []
issn: 0140-6736
journal: LANCET
keywords-plus: 'GLOBAL BURDEN; UNITED-STATES; PROJECTIONS; HEALTH; TRENDS; DISABILITY;

  EDUCATION; SMOKING; DISEASE; OBESITY'
language: English
month: NOV 10
number: '10159'
number-of-cited-references: '52'
orcid-numbers: 'Mokdad, Ali H./0000-0002-4994-3339

  Lozano, Rafael/0000-0002-7356-8823

  Lopez, Alan D/0000-0001-5818-6512

  Friedman, Joseph/0000-0002-5225-3267

  Srinivasan, Vinay/0000-0001-5779-5068

  York, Hunter/0000-0001-5084-5966

  Frank, Tahvi/0000-0002-1972-782X

  Douwes-Schultz, Dirk/0000-0002-6186-2275

  Carter, Austin/0000-0002-3588-6142'
pages: 2052-2090
papis_id: 2ce95d5e53a9725326d3a3996d77dd94
ref: Foreman2018forecastinglife
researcherid-numbers: 'Lopez, Alan/AAA-2734-2022

  Reitsma, Marissa/AAE-7719-2020

  Sorensen, Reed/HSH-0549-2023

  Mokdad, Ali H./AAD-1232-2022

  Lozano, Rafael/T-5352-2018

  Lopez, Alan D/F-1487-2010

  Friedman, Joseph/ABA-5864-2020

  '
times-cited: '923'
title: 'Forecasting life expectancy, years of life lost, and all-cause and cause-specific
  mortality for 250 causes of death: reference and alternative scenarios for 2016-40
  for 195 countries and territories'
type: article
unique-id: WOS:000449710900009
usage-count-last-180-days: '23'
usage-count-since-2013: '248'
volume: '392'
web-of-science-categories: Medicine, General \& Internal
year: '2018'