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Naghavi M, Ong KL, Aali A, Ababneh HS, Abate YH, Abbafati C, Abbasgholizadeh R, Abbasian M, Abbasi-Kangevari M, Abbastabar H, Abd ElHafeez S, Abdelmasseh M, Abd-Elsalam S, Abdelwahab A, Abdollahi M, Abdollahifar MA, Abdoun M, Abdulah DM, Abdullahi A, Abebe M, Abebe SS, Abedi A, Abegaz KH, Abhilash ES, Abidi H, Abiodun O, Aboagye RG, Abolhassani H, Abolmaali M, Abouzid M, Aboye GB, Abreu LG, Abrha WA, Abtahi D, Abu Rumeileh S, Abualruz H, Abubakar B, Abu-Gharbieh E, Abu-Rmeileh NME, Aburuz S, Abu-Zaid A, Accrombessi MMK, Adal TG, Adamu AA, Addo IY, Addolorato G, Adebiyi AO, Adekanmbi V, Adepoju AV, Adetunji CO, Adetunji JB, Adeyeoluwa TE, Adeyinka DA, Adeyomoye OI, Admass BAA, Adnani QES, Adra S, Afolabi AA, Afzal MS, Afzal S, Agampodi SB, Agasthi P, Aggarwal M, Aghamiri S, Agide FD, Agodi A, Agrawal A, Agyemang-Duah W, Ahinkorah BO, Ahmad A, Ahmad D, Ahmad F, Ahmad MM, Ahmad S, Ahmad S, Ahmad T, Ahmadi K, Ahmadzade AM, Ahmed A, Ahmed A, Ahmed H, Ahmed LA, Ahmed MS, Ahmed MS, Ahmed MB, 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K, Deng X, Denova-Gutiérrez E, Deravi N, Dereje N, Dervenis N, Dervišević E, Des Jarlais DC, Desai HD, Desai R, Devanbu VGC, Dewan SMR, Dhali A, Dhama K, Dhimal M, Dhingra S, Dhulipala VR, Dias da Silva D, Diaz D, Diaz MJ, Dima A, Ding DD, Ding H, Dinis-Oliveira RJ, Dirac MA, Djalalinia S, Do THP, do Prado CB, Doaei S, Dodangeh M, Dodangeh M, Dohare S, Dokova KG, Dolecek C, Dominguez RMV, Dong W, Dongarwar D, D'Oria M, Dorostkar F, Dorsey ER, dos Santos WM, Doshi R, Doshmangir L, Dowou RK, Driscoll TR, Dsouza HL, Dsouza V, Du M, Dube J, Duncan BB, Duraes AR, Duraisamy S, Durojaiye OC, Dwyer-Lindgren L, Dzianach PA, Dziedzic AM, E'mar AR, Eboreime E, Ebrahimi A, Echieh CP, Edinur HA, Edvardsson D, Edvardsson K, Efendi D, Efendi F, Effendi DE, Eikemo TA, Eini E, Ekholuenetale M, Ekundayo TC, El Sayed I, Elbarazi I, Elema TB, Elemam NM, Elgar FJ, Elgendy IY, ElGohary GMT, Elhabashy HR, Elhadi M, El-Huneidi W, Elilo LT, Elmeligy OAA, Elmonem MA, Elshaer M, Elsohaby I, Emeto TI, Engelbert 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Ghahramani S, Ghailan KY, Ghasemi MR, Ghasempour Dabaghi G, Ghasemzadeh A, Ghashghaee A, Ghassemi F, Ghazy RM, Ghimire A, Ghoba S, Gholamalizadeh M, Gholamian A, Gholamrezanezhad A, Gholizadeh N, Ghorbani M, Ghorbani Vajargah P, Ghoshal AG, Gill PS, Gill TK, Gillum RF, Ginindza TG, Girmay A, Glasbey JC, Gnedovskaya EV, Göbölös L, Godinho MA, Goel A, Golchin A, Goldust M, Golechha M, Goleij P, Gomes NGM, Gona PN, Gopalani SV, Gorini G, Goudarzi H, Goulart AC, Goulart BNG, Goyal A, Grada A, Graham SM, Grivna M, Grosso G, Guan SY, Guarducci G, Gubari MIM, Gudeta MD, Guha A, Guicciardi S, Guimarães RA, Gulati S, Gunawardane DA, Gunturu S, Guo C, Gupta AK, Gupta B, Gupta MK, Gupta M, Gupta RD, Gupta R, Gupta S, Gupta VB, Gupta VK, Gupta VK, Gurmessa L, Gutiérrez RA, Habibzadeh F, Habibzadeh P, Haddadi R, Hadei M, Hadi NR, Haep N, Hafezi-Nejad N, Hailu A, Haj-Mirzaian A, Halboub ES, Hall BJ, Haller S, Halwani R, Hamadeh RR, Hameed S, Hamidi S, Hamilton EB, Han C, Han Q, Hanif A, Hanifi N, 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A, Lai DTC, Lal DK, Lalloo R, Lallukka T, Lam H, Lám J, Landrum KR, Lanfranchi F, Lang JJ, Langguth B, Lansingh VC, Laplante-Lévesque A, Larijani B, Larsson AO, Lasrado S, Lassi ZS, Latief K, Latifinaibin K, Lauriola P, Le NHH, Le TTT, Le TDT, Ledda C, Ledesma JR, Lee M, Lee PH, Lee SW, Lee SWH, Lee WC, Lee YH, LeGrand KE, Leigh J, Leong E, Lerango TL, Li MC, Li W, Li X, Li Y, Li Z, Ligade VS, Likaka ATM, Lim LL, Lim SS, Lindstrom M, Linehan C, Liu C, Liu G, Liu J, Liu R, Liu S, Liu X, Liu X, Llanaj E, Loftus MJ, López-Bueno R, Lopukhov PD, Loreche AM, Lorkowski S, Lotufo PA, Lozano R, Lubinda J, Lucchetti G, Lugo A, Lunevicius R, Ma ZF, Maass KL, Machairas N, Machoy M, Madadizadeh F, Madsen C, Madureira-Carvalho ÁM, Maghazachi AA, Maharaj SB, Mahjoub S, Mahmoud MA, Mahmoudi A, Mahmoudi E, Mahmoudi R, Majeed A, Makhdoom IF, Malakan Rad E, Maled V, Malekzadeh R, Malhotra AK, Malhotra K, Malik AA, Malik I, Malta DC, Mamun AA, Mansouri P, Mansournia MA, Mantovani LG, Maqsood S, Marasini 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Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet 2024:S0140-6736(24)00367-2. [PMID: 38582094 DOI: 10.1016/s0140-6736(24)00367-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 02/15/2024] [Accepted: 02/22/2024] [Indexed: 04/08/2024]
Abstract
BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation.
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N, Zakzuk J, Zamagni G, Zaman BA, Zaman SB, Zamora N, Zand R, Zandi M, Zandieh GGZ, Zanghì A, Zare I, Zastrozhin MS, Zeariya MGM, Zeng Y, Zhai C, Zhang C, Zhang H, Zhang H, Zhang Y, Zhang Z, Zhang Z, Zhao H, Zhao Y, Zhao Y, Zheng P, Zhong C, Zhou J, Zhu B, Zhu Z, Ziaeefar P, Zielińska M, Zou Z, Zumla A, Zweck E, Zyoud SH, Lim SS, Murray CJL. Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950-2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021. Lancet 2024:S0140-6736(24)00476-8. [PMID: 38484753 DOI: 10.1016/s0140-6736(24)00476-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 12/08/2023] [Accepted: 03/06/2024] [Indexed: 04/13/2024]
Abstract
BACKGROUND Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020-21 COVID-19 pandemic period. METHODS 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. FINDINGS Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5-65·1] decline), and increased during the COVID-19 pandemic period (2020-21; 5·1% [0·9-9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98-5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50-6·01) in 2019. An estimated 131 million (126-137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7-17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8-24·8), from 49·0 years (46·7-51·3) to 71·7 years (70·9-72·5). Global life expectancy at birth declined by 1·6 years (1·0-2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67-8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4-52·7]) and south Asia (26·3% [9·0-44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. INTERPRETATION Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic. FUNDING Bill & Melinda Gates Foundation.
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Wafa HA, Marshall I, Wolfe CD, Xie W, Johnson CO, Veltkamp R, Wang Y. Burden of intracerebral haemorrhage in Europe: forecasting incidence and mortality between 2019 and 2050. Lancet Reg Health Eur 2024; 38:100842. [PMID: 38362494 PMCID: PMC10867656 DOI: 10.1016/j.lanepe.2024.100842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 01/05/2024] [Accepted: 01/08/2024] [Indexed: 02/17/2024]
Abstract
Background Anticipating the burden of intracerebral haemorrhage is crucial for proactive management and building resilience against future health challenges. Prior forecasts are based on population demography and to a lesser extent epidemiological trends. This study aims to utilise selected modifiable risk factors and socio-demographic indicators to forecast the incidence and mortality of intracerebral haemorrhage in Europe between 2019 and 2050. Methods Three intracerebral haemorrhage risk factors identified in the Global Burden of Diseases, Injuries, and Risk Factors study (GBD 2019)-high systolic blood pressure, high fasting plasma glucose, and high body mass index-were utilised to predict the risk-attributable fractions between 2019 and 2050. Disease burden not attributable to these risk factors was then forecasted using time series models (autoregressive integrated moving average [ARIMA]), incorporating the Socio-demographic Index (SDI) as an external predictor. The optimal parameters of ARIMA models were selected for each age-sex-country group based on the Akaike Information Criterion (AIC). Different health scenarios were constructed by extending the past 85th and 15th percentiles of annualised rates of change in risk factors and SDI across all location-years, stratified by age and sex groups. A decomposition analysis was performed to assess the relative contributions of population size, age composition, and intracerebral haemorrhage risk on the projected changes. Findings Compared with observed figures in 2019, our analysis predicts an increase in the burden of intracerebral haemorrhage in Europe in 2050, with a marginal rise of 0.6% (95% uncertainty interval [UI], -7.4% to 9.6%) in incident cases and an 8.9% (-2.8% to 23.6%) increase in mortality, reaching 141.2 (120.6-166.5) thousand and 144.2 (122.9-172.2) thousand respectively. These projections may fluctuate depending on trajectories of the risk factors and SDI; worsened trends could result in increases of 16.7% (8.7%-25.3%) in incidence and 31.2% (17.7%-48%) in mortality, while better trajectories may lead to a 10% (16.4%-2.3%) decrease in intracerebral haemorrhage cases with stabilised mortality. Individuals aged ≥80 years are expected to contribute significantly to the burden, comprising 62.7% of the cases in 2050, up from 40% in 2019, and 72.5% of deaths, up from 50.5%. Country-wide variations were noted in the projected changes, with decreases in the standardised rates across all nations but varying crude rates. The largest relative reductions in counts for both incidence and mortality are expected in Latvia, Bulgaria, and Hungary-ranging from -38.2% to -32.4% and -37.3% to -30.2% respectively. In contrast, the greatest increases for both measures were forecasted in Ireland (45.7% and 74.4%), Luxembourg (45% and 70.7%), and Cyprus (44.5% and 74.2%). The modelled increase in the burden of intracerebral haemorrhage could largely be attributed to population ageing. Interpretation This study provides a comprehensive forecast of intracerebral haemorrhage in Europe until 2050, presenting different trajectories. The potential increase in the number of people experiencing and dying from intracerebral haemorrhage could have profound implications for both caregiving responsibilities and associated costs. However, forecasts were divergent between different scenarios and among EU countries, signalling the pivotal role of public health initiatives in steering the trajectories. Funding The European Union's Horizon 2020 Research and Innovation Programme under grant agreement No. 754517. The National Institute for Health and Care Research (NIHR) under its Programme Grants for Applied Research (NIHR202339).
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Affiliation(s)
- Hatem A. Wafa
- School of Life Course and Population Health Sciences, King’s College London, London, UK
- National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care (CLAHRC) South London, London, UK
| | - Iain Marshall
- School of Life Course and Population Health Sciences, King’s College London, London, UK
- National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care (CLAHRC) South London, London, UK
| | - Charles D.A. Wolfe
- School of Life Course and Population Health Sciences, King’s College London, London, UK
- National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care (CLAHRC) South London, London, UK
| | - Wanqing Xie
- Department of Intelligent Medical Engineering, School of Biomedical Engineering, Anhui Medical University, Hefei, China
- Beth Israel Deaconess Medical Centre, Harvard Medical School, Harvard University, Boston, MA 02215, USA
| | - Catherine O. Johnson
- Institute of Health Metrics and Evaluation (IHME), University of Washington, Seattle, USA
| | - Roland Veltkamp
- Department of Neurology, Alfried Krupp Krankenhaus Essen, Alfried-Krupp-Straße 21, Essen 45131, Germany
- Department of Brain Sciences, Imperial College London, London, UK
| | - Yanzhong Wang
- School of Life Course and Population Health Sciences, King’s College London, London, UK
- National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care (CLAHRC) South London, London, UK
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Feigin VL, Stark BA, Johnson CO, Roth GA, Bisignano C, Abady GG, Abbasifard M, Abbasi-Kangevari M, Abd-Allah F, Abedi V, Abualhasan A, Abu-Rmeileh NME, Abushouk AI, Adebayo OM, Agarwal G, Agasthi P, Ahinkorah BO, Ahmad S, Ahmadi S, Ahmed Salih Y, Aji B, Akbarpour S, Akinyemi RO, Al Hamad H, Alahdab F, Alif SM, Alipour V, Aljunid SM, Almustanyir S, Al-Raddadi RM, Al-Shahi Salman R, Alvis-Guzman N, Ancuceanu R, Anderlini D, Anderson JA, Ansar A, Antonazzo IC, Arabloo J, Ärnlöv J, Artanti KD, Aryan Z, Asgari S, Ashraf T, Athar M, Atreya A, Ausloos M, Baig AA, Baltatu OC, Banach M, Barboza MA, Barker-Collo SL, Bärnighausen TW, Barone MTU, Basu S, Bazmandegan G, Beghi E, Beheshti M, Béjot Y, Bell AW, Bennett DA, Bensenor IM, Bezabhe WM, Bezabih YM, Bhagavathula AS, Bhardwaj P, Bhattacharyya K, Bijani A, Bikbov B, Birhanu MM, Boloor A, Bonny A, Brauer M, Brenner H, Bryazka D, Butt ZA, Caetano dos Santos FL, Campos-Nonato IR, Cantu-Brito C, Carrero JJ, Castañeda-Orjuela CA, Catapano AL, Chakraborty PA, Charan J, Choudhari SG, Chowdhury EK, Chu DT, Chung SC, Colozza D, Costa VM, Costanzo S, Criqui MH, Dadras O, Dagnew B, Dai X, Dalal K, Damasceno AAM, D'Amico E, Dandona L, Dandona R, Darega Gela J, Davletov K, De la Cruz-Góngora V, Desai R, Dhamnetiya D, Dharmaratne SD, Dhimal ML, Dhimal M, Diaz D, Dichgans M, Dokova K, Doshi R, Douiri A, Duncan BB, Eftekharzadeh S, Ekholuenetale M, El Nahas N, Elgendy IY, Elhadi M, El-Jaafary SI, Endres M, Endries AY, Erku DA, Faraon EJA, Farooque U, Farzadfar F, Feroze AH, Filip I, Fischer F, Flood D, Gad MM, Gaidhane S, Ghanei Gheshlagh R, Ghashghaee A, Ghith N, Ghozali G, Ghozy S, Gialluisi A, Giampaoli S, Gilani SA, Gill PS, Gnedovskaya EV, Golechha M, Goulart AC, Guo Y, Gupta R, Gupta VB, Gupta VK, Gyanwali P, Hafezi-Nejad N, Hamidi S, Hanif A, Hankey GJ, Hargono A, Hashi A, Hassan TS, Hassen HY, Havmoeller RJ, Hay SI, Hayat K, Hegazy MI, Herteliu C, Holla R, Hostiuc S, Househ M, Huang J, Humayun A, Hwang BF, Iacoviello L, Iavicoli I, Ibitoye SE, Ilesanmi OS, Ilic IM, Ilic MD, Iqbal U, Irvani SSN, Islam SMS, Ismail NE, Iso H, Isola G, Iwagami M, Jacob L, Jain V, Jang SI, Jayapal SK, Jayaram S, Jayawardena R, Jeemon P, Jha RP, Johnson WD, Jonas JB, Joseph N, Jozwiak JJ, Jürisson M, Kalani R, Kalhor R, Kalkonde Y, Kamath A, Kamiab Z, Kanchan T, Kandel H, Karch A, Katoto PDMC, Kayode GA, Keshavarz P, Khader YS, Khan EA, Khan IA, Khan M, Khan MAB, Khatib MN, Khubchandani J, Kim GR, Kim MS, Kim YJ, Kisa A, Kisa S, Kivimäki M, Kolte D, Koolivand A, Koulmane Laxminarayana SL, Koyanagi A, Krishan K, Krishnamoorthy V, Krishnamurthi RV, Kumar GA, Kusuma D, La Vecchia C, Lacey B, Lak HM, Lallukka T, Lasrado S, Lavados PM, Leonardi M, Li B, Li S, Lin H, Lin RT, Liu X, Lo WD, Lorkowski S, Lucchetti G, Lutzky Saute R, Magdy Abd El Razek H, Magnani FG, Mahajan PB, Majeed A, Makki A, Malekzadeh R, Malik AA, Manafi N, Mansournia MA, Mantovani LG, Martini S, Mazzaglia G, Mehndiratta MM, Menezes RG, Meretoja A, Mersha AG, Miao Jonasson J, Miazgowski B, Miazgowski T, Michalek IM, Mirrakhimov EM, Mohammad Y, Mohammadian-Hafshejani A, Mohammed S, Mokdad AH, Mokhayeri Y, Molokhia M, Moni MA, Montasir AA, Moradzadeh R, Morawska L, Morze J, Muruet W, Musa KI, Nagarajan AJ, Naghavi M, Narasimha Swamy S, Nascimento BR, Negoi RI, Neupane Kandel S, Nguyen TH, Norrving B, Noubiap JJ, Nwatah VE, Oancea B, Odukoya OO, Olagunju AT, Orru H, Owolabi MO, Padubidri JR, Pana A, Parekh T, Park EC, Pashazadeh Kan F, Pathak M, Peres MFP, Perianayagam A, Pham TM, Piradov MA, Podder V, Polinder S, Postma MJ, Pourshams A, Radfar A, Rafiei A, Raggi A, Rahim F, Rahimi-Movaghar V, Rahman M, Rahman MA, Rahmani AM, Rajai N, Ranasinghe P, Rao CR, Rao SJ, Rathi P, Rawaf DL, Rawaf S, Reitsma MB, Renjith V, Renzaho AMN, Rezapour A, Rodriguez JAB, Roever L, Romoli M, Rynkiewicz A, Sacco S, Sadeghi M, Saeedi Moghaddam S, Sahebkar A, Saif-Ur-Rahman KM, Salah R, Samaei M, Samy AM, Santos IS, Santric-Milicevic MM, Sarrafzadegan N, Sathian B, Sattin D, Schiavolin S, Schlaich MP, Schmidt MI, Schutte AE, Sepanlou SG, Seylani A, Sha F, Shahabi S, Shaikh MA, Shannawaz M, Shawon MSR, Sheikh A, Sheikhbahaei S, Shibuya K, Siabani S, Silva DAS, Singh JA, Singh JK, Skryabin VY, Skryabina AA, Sobaih BH, Stortecky S, Stranges S, Tadesse EG, Tarigan IU, Temsah MH, Teuschl Y, Thrift AG, Tonelli M, Tovani-Palone MR, Tran BX, Tripathi M, Tsegaye GW, Ullah A, Unim B, Unnikrishnan B, Vakilian A, Valadan Tahbaz S, Vasankari TJ, Venketasubramanian N, Vervoort D, Vo B, Volovici V, Vosoughi K, Vu GT, Vu LG, Wafa HA, Waheed Y, Wang Y, Wijeratne T, Winkler AS, Wolfe CDA, Woodward M, Wu JH, Wulf Hanson S, Xu X, Yadav L, Yadollahpour A, Yahyazadeh Jabbari SH, Yamagishi K, Yatsuya H, Yonemoto N, Yu C, Yunusa I, Zaman MS, Zaman SB, Zamanian M, Zand R, Zandifar A, Zastrozhin MS, Zastrozhina A, Zhang Y, Zhang ZJ, Zhong C, Zuniga YMH, Murray CJL. Global, regional, and national burden of stroke and its risk factors, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet Neurol 2021; 20:795-820. [PMID: 34487721 PMCID: PMC8443449 DOI: 10.1016/s1474-4422(21)00252-0] [Citation(s) in RCA: 1651] [Impact Index Per Article: 550.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 07/01/2021] [Accepted: 07/19/2021] [Indexed: 02/07/2023]
Abstract
BACKGROUND Regularly updated data on stroke and its pathological types, including data on their incidence, prevalence, mortality, disability, risk factors, and epidemiological trends, are important for evidence-based stroke care planning and resource allocation. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) aims to provide a standardised and comprehensive measurement of these metrics at global, regional, and national levels. METHODS We applied GBD 2019 analytical tools to calculate stroke incidence, prevalence, mortality, disability-adjusted life-years (DALYs), and the population attributable fraction (PAF) of DALYs (with corresponding 95% uncertainty intervals [UIs]) associated with 19 risk factors, for 204 countries and territories from 1990 to 2019. These estimates were provided for ischaemic stroke, intracerebral haemorrhage, subarachnoid haemorrhage, and all strokes combined, and stratified by sex, age group, and World Bank country income level. FINDINGS In 2019, there were 12·2 million (95% UI 11·0-13·6) incident cases of stroke, 101 million (93·2-111) prevalent cases of stroke, 143 million (133-153) DALYs due to stroke, and 6·55 million (6·00-7·02) deaths from stroke. Globally, stroke remained the second-leading cause of death (11·6% [10·8-12·2] of total deaths) and the third-leading cause of death and disability combined (5·7% [5·1-6·2] of total DALYs) in 2019. From 1990 to 2019, the absolute number of incident strokes increased by 70·0% (67·0-73·0), prevalent strokes increased by 85·0% (83·0-88·0), deaths from stroke increased by 43·0% (31·0-55·0), and DALYs due to stroke increased by 32·0% (22·0-42·0). During the same period, age-standardised rates of stroke incidence decreased by 17·0% (15·0-18·0), mortality decreased by 36·0% (31·0-42·0), prevalence decreased by 6·0% (5·0-7·0), and DALYs decreased by 36·0% (31·0-42·0). However, among people younger than 70 years, prevalence rates increased by 22·0% (21·0-24·0) and incidence rates increased by 15·0% (12·0-18·0). In 2019, the age-standardised stroke-related mortality rate was 3·6 (3·5-3·8) times higher in the World Bank low-income group than in the World Bank high-income group, and the age-standardised stroke-related DALY rate was 3·7 (3·5-3·9) times higher in the low-income group than the high-income group. Ischaemic stroke constituted 62·4% of all incident strokes in 2019 (7·63 million [6·57-8·96]), while intracerebral haemorrhage constituted 27·9% (3·41 million [2·97-3·91]) and subarachnoid haemorrhage constituted 9·7% (1·18 million [1·01-1·39]). In 2019, the five leading risk factors for stroke were high systolic blood pressure (contributing to 79·6 million [67·7-90·8] DALYs or 55·5% [48·2-62·0] of total stroke DALYs), high body-mass index (34·9 million [22·3-48·6] DALYs or 24·3% [15·7-33·2]), high fasting plasma glucose (28·9 million [19·8-41·5] DALYs or 20·2% [13·8-29·1]), ambient particulate matter pollution (28·7 million [23·4-33·4] DALYs or 20·1% [16·6-23·0]), and smoking (25·3 million [22·6-28·2] DALYs or 17·6% [16·4-19·0]). INTERPRETATION The annual number of strokes and deaths due to stroke increased substantially from 1990 to 2019, despite substantial reductions in age-standardised rates, particularly among people older than 70 years. The highest age-standardised stroke-related mortality and DALY rates were in the World Bank low-income group. The fastest-growing risk factor for stroke between 1990 and 2019 was high body-mass index. Without urgent implementation of effective primary prevention strategies, the stroke burden will probably continue to grow across the world, particularly in low-income countries. FUNDING Bill & Melinda Gates Foundation.
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Wafa HA, Wolfe CDA, Emmett E, Roth GA, Johnson CO, Wang Y. Burden of Stroke in Europe: Thirty-Year Projections of Incidence, Prevalence, Deaths, and Disability-Adjusted Life Years. Stroke 2020; 51:2418-2427. [PMID: 32646325 PMCID: PMC7382540 DOI: 10.1161/strokeaha.120.029606] [Citation(s) in RCA: 282] [Impact Index Per Article: 70.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND AND PURPOSE Prediction of stroke impact provides essential information for healthcare planning and priority setting. We aim to estimate 30-year projections of stroke epidemiology in the European Union using multiple modeling approaches. METHODS Data on stroke incidence, prevalence, deaths, and disability-adjusted life years in the European Union between 1990 and 2017 were obtained from the global burden of disease study. Their trends over time were modeled using 3 modeling strategies: linear, Poisson, and exponential regressions-adjusted for the gross domestic product per capita, which reflects the impact of economic development on health status. We used the Akaike information criterion for model selection. The 30-year projections up to 2047 were estimated using the best fitting models, with inputs on population projections from the United Nations and gross domestic product per capita prospects from the World Bank. The technique was applied separately by age-sex-country groups for each stroke measure. RESULTS In 2017, there were 1.12 million incident strokes in the European Union, 9.53 million stroke survivors, 0.46 million deaths, and 7.06 million disability-adjusted life years lost because of stroke. By 2047, we estimated an additional 40 000 incident strokes (+3%) and 2.58 million prevalent cases (+27%). Conversely, 80 000 fewer deaths (-17%) and 2.31 million fewer disability-adjusted life years lost (-33%) are projected. The largest increase in the age-adjusted incidence and prevalence rates are expected in Lithuania (average annual percentage change, 0.48% and 0.7% respectively), and the greatest reductions in Portugal (-1.57% and -1.3%). Average annual percentage change in mortality rates will range from -2.86% (Estonia) to -0.08% (Lithuania), and disability-adjusted life years' from -2.77% (Estonia) to -0.23% (Romania). CONCLUSIONS The number of people living with stroke is estimated to increase by 27% between 2017 and 2047 in the European Union, mainly because of population ageing and improved survival rates. Variations are expected to persist between countries showing opportunities for improvements in prevention and case management particularly in Eastern Europe.
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Affiliation(s)
- Hatem A Wafa
- School of Population Health and Environmental Sciences, King's College London, United Kingdom (H.A.W., C.D.A.W., E.E., Y.W.).,National Institute for Health Research (NIHR) Biomedical Research Centre, Guy's and St Thomas' NHS Foundation Trust and King's College London, United Kingdom (H.A.W., C.D.A.W., Y.W.).,National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care (CLAHRC) South London, United Kingdom (H.A.W., C.D.A.W., Y.W.)
| | - Charles D A Wolfe
- School of Population Health and Environmental Sciences, King's College London, United Kingdom (H.A.W., C.D.A.W., E.E., Y.W.).,National Institute for Health Research (NIHR) Biomedical Research Centre, Guy's and St Thomas' NHS Foundation Trust and King's College London, United Kingdom (H.A.W., C.D.A.W., Y.W.).,National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care (CLAHRC) South London, United Kingdom (H.A.W., C.D.A.W., Y.W.)
| | - Eva Emmett
- School of Population Health and Environmental Sciences, King's College London, United Kingdom (H.A.W., C.D.A.W., E.E., Y.W.)
| | - Gregory A Roth
- Department of Medicine, University of Washington, Seattle (G.A.R.).,Institute of Health Metrics and Evaluation (IHME), University of Washington, Seattle (G.A.R., C.O.J.)
| | - Catherine O Johnson
- Institute of Health Metrics and Evaluation (IHME), University of Washington, Seattle (G.A.R., C.O.J.)
| | - Yanzhong Wang
- School of Population Health and Environmental Sciences, King's College London, United Kingdom (H.A.W., C.D.A.W., E.E., Y.W.).,National Institute for Health Research (NIHR) Biomedical Research Centre, Guy's and St Thomas' NHS Foundation Trust and King's College London, United Kingdom (H.A.W., C.D.A.W., Y.W.).,National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care (CLAHRC) South London, United Kingdom (H.A.W., C.D.A.W., Y.W.)
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Wafa HA, Wolfe CDA, Bhalla A, Wang Y. Long-term trends in death and dependence after ischaemic strokes: A retrospective cohort study using the South London Stroke Register (SLSR). PLoS Med 2020; 17:e1003048. [PMID: 32163411 PMCID: PMC7067375 DOI: 10.1371/journal.pmed.1003048] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Accepted: 02/10/2020] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND There have been reductions in stroke mortality over recent decades, but estimates by aetiological subtypes are limited. This study estimates time trends in mortality and functional dependence by ischaemic stroke (IS) aetiological subtype over a 16-year period. METHODS AND FINDINGS The study population was 357,308 in 2011; 50.4% were males, 56% were white, and 25% were of black ethnic backgrounds. Population-based case ascertainment of stroke was conducted, and all participants who had their first-ever IS between 2000 and 2015 were identified. Further classification was concluded according to the underlying mechanism into large-artery atherosclerosis (LAA), cardio-embolism (CE), small-vessel occlusion (SVO), other determined aetiologies (OTH), and undetermined aetiologies (UND). Temporal trends in survival rates were examined using proportional-hazards survival modelling, adjusted for demography, prestroke risk factors, case mix variables, and processes of care. We carried out additional regression analyses to explore patterns in case-fatality rates (CFRs) at 30 days and 1 year and to explore whether these trends occurred at the expense of greater functional dependence (Barthel Index [BI] < 15) among survivors. A total of 3,128 patients with first-ever ISs were registered. The median age was 70.7 years; 50.9% were males; and 66.2% were white, 25.5% were black, and 8.3% were of other ethnic groups. Between 2000-2003 and 2012-2015, the adjusted overall mortality decreased by 24% (hazard ratio [HR] per year 0.976; 95% confidence interval [CI] 0.959-0.993). Mortality reductions were equally noted in both sexes and in the white and black populations but were only significant in CE strokes (HR per year 0.972; 95% CI 0.945‒0.998) and in patients aged ≥55 years (HR per year 0.975; 95% CI 0.959‒0.992). CFRs within 30 days and 1 year after an IS declined by 38% (rate ratio [RR] per year 0.962; 95% CI 0.941‒0.984) and 37% (RR per year 0.963; 95% CI 0.949‒0.976), respectively. Recent IS was independently associated with a 23% reduced risk of functional dependence at 3 months after onset (RR per year 0.983; 95% CI 0.968-0.998; p = 0.002 for trend). The study is limited by small number of events in certain subgroups (e.g., LAA), which could have led to insufficient power to detect significant trends. CONCLUSIONS Both mortality and 3-month functional dependence after IS decreased by an annual average of around 2.4% and 1.7%, respectively, during 2000‒2015. Such reductions were particularly evident in strokes of CE origins and in those aged ≥55 years.
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Affiliation(s)
- Hatem A. Wafa
- School of Population Health and Environmental Sciences, King’s College London, London, United Kingdom
- National Institute for Health Research (NIHR) Biomedical Research Centre, Guy’s and St Thomas’ NHS Foundation Trust and King’s College London, London, United Kingdom
- National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care (CLAHRC) South London, London, United Kingdom
- * E-mail:
| | - Charles D. A. Wolfe
- School of Population Health and Environmental Sciences, King’s College London, London, United Kingdom
- National Institute for Health Research (NIHR) Biomedical Research Centre, Guy’s and St Thomas’ NHS Foundation Trust and King’s College London, London, United Kingdom
- National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care (CLAHRC) South London, London, United Kingdom
| | - Ajay Bhalla
- School of Population Health and Environmental Sciences, King’s College London, London, United Kingdom
- Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
| | - Yanzhong Wang
- School of Population Health and Environmental Sciences, King’s College London, London, United Kingdom
- National Institute for Health Research (NIHR) Biomedical Research Centre, Guy’s and St Thomas’ NHS Foundation Trust and King’s College London, London, United Kingdom
- National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care (CLAHRC) South London, London, United Kingdom
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Wafa HA, Wolfe CDA, Rudd A, Wang Y. Long-term trends in incidence and risk factors for ischaemic stroke subtypes: Prospective population study of the South London Stroke Register. PLoS Med 2018; 15:e1002669. [PMID: 30289919 PMCID: PMC6173399 DOI: 10.1371/journal.pmed.1002669] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2018] [Accepted: 09/07/2018] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND As the average life expectancy increases, more people are predicted to have strokes. Recent studies have shown an increasing incidence in certain types of cerebral infarction. We aimed to estimate time trends in incidence, prior risk factors, and use of preventive treatments for ischaemic stroke (IS) aetiological subtypes and to ascertain any demographic disparities. METHODS AND FINDINGS Population-based data from the South London Stroke Register (SLSR) between 2000 and 2015 were studied. IS was classified, based on the underlying mechanism, into large-artery atherosclerosis (LAA), cardio-embolism (CE), small-vessel occlusion (SVO), other determined aetiologies (OTH), and undetermined aetiologies (UND). After calculation of age-, sex-, and ethnicity-specific incidence rates by subtype for the 16-year period, we analysed trends using Cochran-Armitage tests, Poisson regression models, and locally estimated scatterplot smoothers (loess). A total of 3,088 patients with first IS were registered. Between 2000-2003 and 2012-2015, the age-adjusted incidence of IS decreased by 43% from 137.3 to 78.4/100,000/year (incidence rate ratio [IRR] 0.57, 95% CI 0.5-0.64). Significant declines were observed in all subtypes, particularly in SVO (37.4-18; p < 0.0001) and less in CE (39.3-25; p < 0.0001). Reductions were recorded in males and females, younger (<55 years old) and older (≥55 years old) individuals, and white and black ethnic groups, though not significantly in the latter (144.6-116.2; p = 0.31 for IS). A 4-fold increase in prior-to-stroke use of statins was found (adjusted odds ratio [OR] 4.39, 95% CI 3.29-5.86), and despite the increasing prevalence of hypertension (OR 1.54, 95% CI 1.21-1.96) and atrial fibrillation (OR 1.7, 95% CI 1.22-2.36), preventive use of antihypertensive and antiplatelet drugs was declining. A smaller number of participants in certain subgroup-specific analyses (e.g., black ethnicity and LAA subtype) could have limited the power to identify significant trends. CONCLUSIONS The incidence of ISs has been declining since 2000 in all age groups but to a lesser extent in the black population. The reported changes in medication use are unlikely to fully explain the reduction in stroke incidence; however, innovative prevention strategies and better management of risk factors may contribute further reduction.
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Affiliation(s)
- Hatem A. Wafa
- School of Population Health and Environmental Sciences, King’s College London, London, United Kingdom
- * E-mail:
| | - Charles D. A. Wolfe
- School of Population Health and Environmental Sciences, King’s College London, London, United Kingdom
- National Institute for Health Research (NIHR) Biomedical Research Centre, Guy’s and St Thomas’ NHS Foundation Trust and King’s College London, London, United Kingdom
- National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care (CLAHRC) South London, London, United Kingdom
| | - Anthony Rudd
- School of Population Health and Environmental Sciences, King’s College London, London, United Kingdom
- National Institute for Health Research (NIHR) Biomedical Research Centre, Guy’s and St Thomas’ NHS Foundation Trust and King’s College London, London, United Kingdom
| | - Yanzhong Wang
- School of Population Health and Environmental Sciences, King’s College London, London, United Kingdom
- National Institute for Health Research (NIHR) Biomedical Research Centre, Guy’s and St Thomas’ NHS Foundation Trust and King’s College London, London, United Kingdom
- National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care (CLAHRC) South London, London, United Kingdom
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