Dataset Information

Global, regional, and national disability-adjusted life years (DALYs) for 306 diseases and injuries and healthy life expectancy (HALE) for 188 countries, 1990-2013: quantifying the epidemiological transition.

ABSTRACT:

SUBMITTER: GBD 2013 DALYs and HALE Collaborators

PROVIDER: S-EPMC4673910 | biostudies-literature | 2015 Nov

REPOSITORIES: biostudies-literature

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Global, regional, and national disability-adjusted life years (DALYs) for 306 diseases and injuries and healthy life expectancy (HALE) for 188 countries, 1990-2013: quantifying the epidemiological transition.

Murray Christopher J L CJ Barber Ryan M RM Foreman Kyle J KJ Abbasoglu Ozgoren Ayse A Abd-Allah Foad F Abera Semaw F SF Aboyans Victor V Abraham Jerry P JP Abubakar Ibrahim I Abu-Raddad Laith J LJ Abu-Rmeileh Niveen M NM Achoki Tom T Ackerman Ilana N IN Ademi Zanfina Z Adou Arsène K AK Adsuar José C JC Afshin Ashkan A Agardh Emilie E EE Alam Sayed Saidul SS Alasfoor Deena D Albittar Mohammed I MI Alegretti Miguel A MA Alemu Zewdie A ZA Alfonso-Cristancho Rafael R Alhabib Samia S Ali Raghib R Alla François F Allebeck Peter P Almazroa Mohammad A MA Alsharif Ubai U Alvarez Elena E Alvis-Guzman Nelson N Amare Azmeraw T AT Ameh Emmanuel A EA Amini Heresh H Ammar Walid W Anderson H Ross HR Anderson Benjamin O BO Antonio Carl Abelardo T CA Anwari Palwasha P Arnlöv Johan J Arsic Arsenijevic Valentina S VS Artaman Al A Asghar Rana J RJ Assadi Reza R Atkins Lydia S LS Avila Marco A MA Awuah Baffour B Bachman Victoria F VF Badawi Alaa A Bahit Maria C MC Balakrishnan Kalpana K Banerjee Amitava A Barker-Collo Suzanne L SL Barquera Simon S Barregard Lars L Barrero Lope H LH Basu Arindam A Basu Sanjay S Basulaiman Mohammed O MO Beardsley Justin J Bedi Neeraj N Beghi Ettore E Bekele Tolesa T Bell Michelle L ML Benjet Corina C Bennett Derrick A DA Bensenor Isabela M IM Benzian Habib H Bernabé Eduardo E Bertozzi-Villa Amelia A Beyene Tariku J TJ Bhala Neeraj N Bhalla Ashish A Bhutta Zulfiqar A ZA Bienhoff Kelly K Bikbov Boris B Biryukov Stan S Blore Jed D JD Blosser Christopher D CD Blyth Fiona M FM Bohensky Megan A MA Bolliger Ian W IW Bora Başara Berrak B Bornstein Natan M NM Bose Dipan D Boufous Soufiane S Bourne Rupert R A RR Boyers Lindsay N LN Brainin Michael M Brayne Carol E CE Brazinova Alexandra A Breitborde Nicholas J K NJ Brenner Hermann H Briggs Adam D AD Brooks Peter M PM Brown Jonathan C JC Brugha Traolach S TS Buchbinder Rachelle R Buckle Geoffrey C GC Budke Christine M CM Bulchis Anne A Bulloch Andrew G AG Campos-Nonato Ismael R IR Carabin Hélène H Carapetis Jonathan R JR Cárdenas Rosario R Carpenter David O DO Caso Valeria V Castañeda-Orjuela Carlos A CA Castro Ruben E RE Catalá-López Ferrán F Cavalleri Fiorella F Çavlin Alanur A Chadha Vineet K VK Chang Jung-Chen JC Charlson Fiona J FJ Chen Honglei H Chen Wanqing W Chiang Peggy P PP Chimed-Ochir Odgerel O Chowdhury Rajiv R Christensen Hanne H Christophi Costas A CA Cirillo Massimo M Coates Matthew M MM Coffeng Luc E LE Coggeshall Megan S MS Colistro Valentina V Colquhoun Samantha M SM Cooke Graham S GS Cooper Cyrus C Cooper Leslie T LT Coppola Luis M LM Cortinovis Monica M Criqui Michael H MH Crump John A JA Cuevas-Nasu Lucia L Danawi Hadi H Dandona Lalit L Dandona Rakhi R Dansereau Emily E Dargan Paul I PI Davey Gail G Davis Adrian A Davitoiu Dragos V DV Dayama Anand A De Leo Diego D Degenhardt Louisa L Del Pozo-Cruz Borja B Dellavalle Robert P RP Deribe Kebede K Derrett Sarah S Des Jarlais Don C DC Dessalegn Muluken M Dharmaratne Samath D SD Dherani Mukesh K MK Diaz-Torné Cesar C Dicker Daniel D Ding Eric L EL Dokova Klara K Dorsey E Ray ER Driscoll Tim R TR Duan Leilei L Duber Herbert C HC Ebel Beth E BE Edmond Karen M KM Elshrek Yousef M YM Endres Matthias M Ermakov Sergey P SP Erskine Holly E HE Eshrati Babak B Esteghamati Alireza A Estep Kara K Faraon Emerito Jose A EJ Farzadfar Farshad F Fay Derek F DF Feigin Valery L VL Felson David T DT Fereshtehnejad Seyed-Mohammad SM Fernandes Jefferson G JG Ferrari Alize J AJ Fitzmaurice Christina C Flaxman Abraham D AD Fleming Thomas D TD Foigt Nataliya N Forouzanfar Mohammad H MH Fowkes F Gerry R FG Paleo Urbano Fra UF Franklin Richard C RC Fürst Thomas T Gabbe Belinda B Gaffikin Lynne L Gankpé Fortuné G FG Geleijnse Johanna M JM Gessner Bradford D BD Gething Peter P Gibney Katherine B KB Giroud Maurice M Giussani Giorgia G Gomez Dantes Hector H Gona Philimon P González-Medina Diego D Gosselin Richard A RA Gotay Carolyn C CC Goto Atsushi A Gouda Hebe N HN Graetz Nicholas N Gugnani Harish C HC Gupta Rahul R Gupta Rajeev R Gutiérrez Reyna A RA Haagsma Juanita J Hafezi-Nejad Nima N Hagan Holly H Halasa Yara A YA Hamadeh Randah R RR Hamavid Hannah H Hammami Mouhanad M Hancock Jamie J Hankey Graeme J GJ Hansen Gillian M GM Hao Yuantao Y Harb Hilda L HL Haro Josep Maria JM Havmoeller Rasmus R Hay Simon I SI Hay Roderick J RJ Heredia-Pi Ileana B IB Heuton Kyle R KR Heydarpour Pouria P Higashi Hideki H Hijar Martha M Hoek Hans W HW Hoffman Howard J HJ Hosgood H Dean HD Hossain Mazeda M Hotez Peter J PJ Hoy Damian G DG Hsairi Mohamed M Hu Guoqing G Huang Cheng C Huang John J JJ Husseini Abdullatif A Huynh Chantal C Iannarone Marissa L ML Iburg Kim M KM Innos Kaire K Inoue Manami M Islami Farhad F Jacobsen Kathryn H KH Jarvis Deborah L DL Jassal Simerjot K SK Jee Sun Ha SH Jeemon Panniyammakal P Jensen Paul N PN Jha Vivekanand V Jiang Guohong G Jiang Ying Y Jonas Jost B JB Juel Knud K Kan Haidong H Karch André A Karema Corine K CK Karimkhani Chante C Karthikeyan Ganesan G Kassebaum Nicholas J NJ Kaul Anil A Kawakami Norito N Kazanjan Konstantin K Kemp Andrew H AH Kengne Andre P AP Keren Andre A Khader Yousef S YS Khalifa Shams Eldin A SE Khan Ejaz A EA Khan Gulfaraz G Khang Young-Ho YH Kieling Christian C Kim Daniel D Kim Sungroul S Kim Yunjin Y Kinfu Yohannes Y Kinge Jonas M JM Kivipelto Miia M Knibbs Luke D LD Knudsen Ann Kristin AK Kokubo Yoshihiro Y Kosen Soewarta S Krishnaswami Sanjay S Kuate Defo Barthelemy B Kucuk Bicer Burcu B Kuipers Ernst J EJ Kulkarni Chanda C Kulkarni Veena S VS Kumar G Anil GA Kyu Hmwe H HH Lai Taavi T Lalloo Ratilal R Lallukka Tea T Lam Hilton H Lan Qing Q Lansingh Van C VC Larsson Anders A Lawrynowicz Alicia E B AE Leasher Janet L JL Leigh James J Leung Ricky R Levitz Carly E CE Li Bin B Li Yichong Y Li Yongmei Y Lim Stephen S SS Lind Maggie M Lipshultz Steven E SE Liu Shiwei S Liu Yang Y Lloyd Belinda K BK Lofgren Katherine T KT Logroscino Giancarlo G Looker Katharine J KJ Lortet-Tieulent Joannie J Lotufo Paulo A PA Lozano Rafael R Lucas Robyn M RM Lunevicius Raimundas R Lyons Ronan A RA Ma Stefan S Macintyre Michael F MF Mackay Mark T MT Majdan Marek M Malekzadeh Reza R Marcenes Wagner W Margolis David J DJ Margono Christopher C Marzan Melvin B MB Masci Joseph R JR Mashal Mohammad T MT Matzopoulos Richard R Mayosi Bongani M BM Mazorodze Tasara T TT Mcgill Neil W NW Mcgrath John J JJ Mckee Martin M Mclain Abigail A Meaney Peter A PA Medina Catalina C Mehndiratta Man Mohan MM Mekonnen Wubegzier W Melaku Yohannes A YA Meltzer Michele M Memish Ziad A ZA Mensah George A GA Meretoja Atte A Mhimbira Francis A FA Micha Renata R Miller Ted R TR Mills Edward J EJ Mitchell Philip B PB Mock Charles N CN Mohamed Ibrahim Norlinah N Mohammad Karzan A KA Mokdad Ali H AH Mola Glen L D GL Monasta Lorenzo L Montañez Hernandez Julio C JC Montico Marcella M Montine Thomas J TJ Mooney Meghan D MD Moore Ami R AR Moradi-Lakeh Maziar M Moran Andrew E AE Mori Rintaro R Moschandreas Joanna J Moturi Wilkister N WN Moyer Madeline L ML Mozaffarian Dariush D Msemburi William T WT Mueller Ulrich O UO Mukaigawara Mitsuru M Mullany Erin C EC Murdoch Michele E ME Murray Joseph J Murthy Kinnari S KS Naghavi Mohsen M Naheed Aliya A Naidoo Kovin S KS Naldi Luigi L Nand Devina D Nangia Vinay V Narayan K M Venkat KM Nejjari Chakib C Neupane Sudan P SP Newton Charles R CR Ng Marie M Ngalesoni Frida N FN Nguyen Grant G Nisar Muhammad I MI Nolte Sandra S Norheim Ole F OF Norman Rosana E RE Norrving Bo B Nyakarahuka Luke L Oh In-Hwan IH Ohkubo Takayoshi T Ohno Summer L SL Olusanya Bolajoko O BO Opio John Nelson JN Ortblad Katrina K Ortiz Alberto A Pain Amanda W AW Pandian Jeyaraj D JD Panelo Carlo Irwin A CI Papachristou Christina C Park Eun-Kee EK Park Jae-Hyun JH Patten Scott B SB Patton George C GC Paul Vinod K VK Pavlin Boris I BI Pearce Neil N Pereira David M DM Perez-Padilla Rogelio R Perez-Ruiz Fernando F Perico Norberto N Pervaiz Aslam A Pesudovs Konrad K Peterson Carrie B CB Petzold Max M Phillips Michael R MR Phillips Bryan K BK Phillips David E DE Piel Frédéric B FB Plass Dietrich D Poenaru Dan D Polinder Suzanne S Pope Daniel D Popova Svetlana S Poulton Richie G RG Pourmalek Farshad F Prabhakaran Dorairaj D Prasad Noela M NM Pullan Rachel L RL Qato Dima M DM Quistberg D Alex DA Rafay Anwar A Rahimi Kazem K Rahman Sajjad U SU Raju Murugesan M Rana Saleem M SM Razavi Homie H Reddy K Srinath KS Refaat Amany A Remuzzi Giuseppe G Resnikoff Serge S Ribeiro Antonio L AL Richardson Lee L Richardus Jan Hendrik JH Roberts D Allen DA Rojas-Rueda David D Ronfani Luca L Roth Gregory A GA Rothenbacher Dietrich D Rothstein David H DH Rowley Jane T JT Roy Nobhojit N Ruhago George M GM Saeedi Mohammad Y MY Saha Sukanta S Sahraian Mohammad Ali MA Sampson Uchechukwu K A UK Sanabria Juan R JR Sandar Logan L Santos Itamar S IS Satpathy Maheswar M Sawhney Monika M Scarborough Peter P Schneider Ione J IJ Schöttker Ben B Schumacher Austin E AE Schwebel David C DC Scott James G JG Seedat Soraya S Sepanlou Sadaf G SG Serina Peter T PT Servan-Mori Edson E EE Shackelford Katya A KA Shaheen Amira A Shahraz Saeid S Shamah Levy Teresa T Shangguan Siyi S She Jun J Sheikhbahaei Sara S Shi Peilin P Shibuya Kenji K Shinohara Yukito Y Shiri Rahman R Shishani Kawkab K Shiue Ivy I Shrime Mark G MG Sigfusdottir Inga D ID Silberberg Donald H DH Simard Edgar P EP Sindi Shireen S Singh Abhishek A Singh Jasvinder A JA Singh Lavanya L Skirbekk Vegard V Slepak Erica Leigh EL Sliwa Karen K Soneji Samir S Søreide Kjetil K Soshnikov Sergey S Sposato Luciano A LA Sreeramareddy Chandrashekhar T CT Stanaway Jeffrey D JD Stathopoulou Vasiliki V Stein Dan J DJ Stein Murray B MB Steiner Caitlyn C Steiner Timothy J TJ Stevens Antony A Stewart Andrea A Stovner Lars J LJ Stroumpoulis Konstantinos K Sunguya Bruno F BF Swaminathan Soumya S Swaroop Mamta M Sykes Bryan L BL Tabb Karen M KM Takahashi Ken K Tandon Nikhil N Tanne David D Tanner Marcel M Tavakkoli Mohammad M Taylor Hugh R HR Te Ao Braden J BJ Tediosi Fabrizio F Temesgen Awoke M AM Templin Tara T Ten Have Margreet M Tenkorang Eric Y EY Terkawi Abdullah S AS Thomson Blake B Thorne-Lyman Andrew L AL Thrift Amanda G AG Thurston George D GD Tillmann Taavi T Tonelli Marcello M Topouzis Fotis F Toyoshima Hideaki H Traebert Jefferson J Tran Bach X BX Trillini Matias M Truelsen Thomas T Tsilimbaris Miltiadis M Tuzcu Emin M EM Uchendu Uche S US Ukwaja Kingsley N KN Undurraga Eduardo A EA Uzun Selen B SB Van Brakel Wim H WH Van De Vijver Steven S van Gool Coen H CH Van Os Jim J Vasankari Tommi J TJ Venketasubramanian N N Violante Francesco S FS Vlassov Vasiliy V VV Vlassov Vasiliy V VV Vollset Stein Emil SE Wagner Gregory R GR Wagner Joseph J Waller Stephen G SG Wan Xia X Wang Haidong H Wang Jianli J Wang Linhong L Warouw Tati S TS Weichenthal Scott S Weiderpass Elisabete E Weintraub Robert G RG Wenzhi Wang W Werdecker Andrea A Westerman Ronny R Whiteford Harvey A HA Wilkinson James D JD Williams Thomas N TN Wolfe Charles D CD Wolock Timothy M TM Woolf Anthony D AD Wulf Sarah S Wurtz Brittany B Xu Gelin G Yan Lijing L LL Yano Yuichiro Y Ye Pengpeng P Yentür Gökalp K GK Yip Paul P Yonemoto Naohiro N Yoon Seok-Jun SJ Younis Mustafa Z MZ Yu Chuanhua C Zaki Maysaa E ME Zhao Yong Y Zheng Yingfeng Y Zonies David D Zou Xiaonong X Salomon Joshua A JA Lopez Alan D AD Vos Theo T

Lancet (London, England) 20150828 10009

<h4>Background</h4>The Global Burden of Disease Study 2013 (GBD 2013) aims to bring together all available epidemiological data using a coherent measurement framework, standardised estimation methods, and transparent data sources to enable comparisons of health loss over time and across causes, age-sex groups, and countries. The GBD can be used to generate summary measures such as disability-adjusted life-years (DALYs) and healthy life expectancy (HALE) that make possible comparative assessments ...[more]

PMID: 26321261

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Project description:ObjectiveTo quantify and compare the contribution of 306 diseases and injuries to the changes in health adjusted life expectancy at birth (HALE0) between 1990 and 2013.DesignRetrospective demographic analysis based on aggregated data and using life table technique, Sullivan method, and decomposition method for differences in health expectancy.SettingThe globe, 21 regions, and 187 countries, covered in the Global Burden of Disease Study (GBD) 2013.Main outcome measuresCause specific contribution to changes in HALE0 between 1990 and 2013 in terms of mortality effect, disability effect, and total effect.ResultsBetween 1990 and 2013, global HALE0 increased by 5.31 years for males and 5.73 years for females. The cross national Gini coefficient of HALE0 for both sexes combined decreased by 15.22% from 0.0736 to 0.0624. HALE0 declined in 11 countries during the period, predominantly owing to HIV/AIDS except in Belize, Belarus, and Paraguay. Controlling communicable, maternal, neonatal, and nutritional diseases accounted for 56.47% (3.10 years) of changes in HALE0 for both sexes combined, followed by non-communicable diseases (30.05%; 1.65 years) and injuries (13.67%; 0.75 years). Globally, HIV/AIDS caused the biggest reduction in HALE0 (-0.28 years) and mainly afflicted residents in southern (-7.86 years), western (-1.53 years), and eastern (-1.38 years) sub-Saharan Africa. Diabetes had the second biggest negative total effect on changes in HALE0 (-0.12 years), which was quite widespread across regions. Despite their positive total effect in high income regions, such non-communicable diseases as ischaemic heart disease, cerebrovascular disease, and hypertensive heart disease had a negative total effect in many low and middle income regions. Mortality reduction was the predominant driver (93.62%; 5.14 years) for improvement in HALE0, accompanied by an increase of 0.80 years in life expectancy lived with disability at birth. Only 44 (27%) of 163 causes at level 3 in the GBD cause hierarchy influenced changes in HALE0, mainly or only through disability.ConclusionsBetween 1990 and 2013, the globe made achievements in not only promoting population health as a whole but reducing health inequality between countries. This study pinpoints the priority diseases and injuries for altering the declining health trend in 11 countries, for curbing the epidemic of non-communicable diseases in low and middle income countries, and for promoting compression of morbidity worldwide. The detailed country specific decomposition results of effects of diseases and injuries on change in population health will further facilitate the development of national health policies.

Project description:BackgroundHALE is now a regular strategic planning indicator for all levels of the Chinese government. However, HALE measurements necessitate comprehensive data collection and intricate technology. Therefore, effectively converting numerous diseases into the years lived with disability (YLD) rate is a significant challenge for HALE measurements. Our study aimed to construct a simple YLD rate measurement model with high applicability based on the current situation of actual data resources within China to address challenges in measuring HALE target values during planning.MethodsFirst, based on the Chinese YLD rate in the Global Burden of Disease (GBD) 2019, Pearson correlation analysis, the global optimum method, etc., was utilized to screen the best predictor variables from the current Chinese data resources. Missing data for predictor variables were filled in via spline interpolation. Then, multiple linear regression models were fitted to construct the YLD rate measurement model. The Sullivan method was used to measure HALE. The Monte Carlo method was employed to generate 95% uncertainty intervals. Finally, model performances were assessed using the mean absolute error (MAE) and mean absolute percentage error (MAPE).ResultsA three-input-parameter model was constructed to measure the age-specific YLD rates by sex in China, directly using the incidence of infectious diseases, the incidence of chronic diseases among persons aged 15 and older, and the addition of an under-five mortality rate covariate. The total MAE and MAPE for the combined YLD rate were 0.0007 and 0.5949%, respectively. The MAE and MAPE of the combined HALE in the 0-year-old group were 0.0341 and 0.0526%, respectively. There were slightly fewer males (0.0197, 0.0311%) than females (0.0501, 0.0755%).ConclusionWe constructed a high-accuracy model to measure the YLD rate in China by using three monitoring indicators from the Chinese national routine as predictor variables. The model provides a realistic and feasible solution for measuring HALE at the national and especially regional levels, considering limited data.

Project description:IntroductionNo information is available in Belgium on life expectancy adjusted for health-related quality of life (HRQoL). Quality-adjusted life expectancy (QALE) captures the multidimensionality of health by accounting for losses in mortality and HRQoL linked to physical, mental, and social impairments. The objective of this study is to estimate for Belgium QALE, the changes in QALE between 2013 and 2018 and the contribution of mortality, HRQoL and its dimensions to this trend.MethodsThe Belgian Health Interview Survey (BHIS), a representative sample of the general population, included the EQ-5D-5L instrument in 2013 and 2018. The tool assesses HRQoL comprising five dimensions (mobility, self-care, usual activities, pain/discomfort, anxiety/depression) using a 5-level severity scoring to define a large variety of health states. The Sullivan method was used to compute at different ages QALE by gender using mortality data from the Belgian statistical office and average EQ-5D scores from the BHIS. QALE was calculated for 2013 and 2018, and changes in QALE over time were decomposed into mortality and ill-health effect.ResultsIn 2018, QALE at age 15 years (QALE15) was 56.3 years for women and 55.8 years for men, a decrease from 2013 by 0.7 year for women and a stagnation for men. In men, the decrease in mortality counterbalanced the decline in HRQoL. The decline in QALE in women is driven by a decrease in mortality rates that is too small to compensate for the substantial decline in HRQoL before the age of 50 years. In women at older ages, improvements in HRQoL are observed. In women, QALE15 is decreasing due to an increase in pain/discomfort, anxiety/depression and problems in usual activities. In men at age 15, the pain/discomfort and anxiety/depression domains contributed to the stagnation. QALE65 increased somewhat, due to an improvement in self-care and mobility for both genders, and usual activities and anxiety/depression in men only.ConclusionThe strength of QALE as member of the family of composite indicators, the health expectancies, is the multidimensional structure of the underlying health component, including both ill-health with different health domains as levels of severity. The ability to decompose differences in the health expectancy not only into a mortality and health component but also into the different health dimensions allows to better inform on general population health trends. Next, compared to other health expectancy indicators, QALE is more sensitive to changes at younger ages.

Project description:BackgroundHealth impact assessment (HIA) studies are increasingly predicting the health effects of mode shifts in traffic. The challenge for such studies is to combine the health effects, caused by injuries, with the disease driven health effects, and to express the change in the health with a common health indicator. Disability-adjusted life year (DALY) combines years lived disabled or injured (YLD) and years of life lost (YLL) providing practical indicator to combine injuries with diseases. In this study, we estimate the average YLDs for one person injured in a transport crash to allow easy to use methods to predict health effects of transport injuries.MethodsWe calculated YLDs and YLLs for transport fatalities and injuries based on the data from the Swedish Traffic Accident Data Acquisition (STRADA). In STRADA, all the fatalities and most of the injuries in Sweden for 2007-2011 were recorded. The type of injury was recorded with the Abbreviated Injury Scale (AIS) codes. In this study these AIS codes were aggregated to injury types, and YLDs were calculated for each victim by multiplying the type of injury with the disability weight and the average duration of that injury. YLLs were calculated by multiplying the age of the victim with life expectancy of that age and gender. YLDs and YLLs were estimated separately for different gender, mode of transport and location of the crash.ResultsThe average YLDs for injured person was 14.7 for lifelong injuries and 0.012 for temporal injuries. The average YLDs per injured person for lifelong injuries for pedestrians, cyclists and car occupants were 9.4, 12.8 and 18.4, YLDs, respectively. Lifelong injuries sustained in rural areas were on average 31% more serious than injuries in urban areas.ConclusionsThe results show that shifting modes of transport will not only change the likelihood of injuries but also the severity of injuries sustained, if injured. The results of this study can be used to predict DALY changes in HIA studies that take into account mode shifts between different transport modes, and in other studies predicting the health effects of traffic injuries.

Dataset Information

Global, regional, and national disability-adjusted life years (DALYs) for 306 diseases and injuries and healthy life expectancy (HALE) for 188 countries, 1990-2013: quantifying the epidemiological transition.

Publications

Global, regional, and national disability-adjusted life years (DALYs) for 306 diseases and injuries and healthy life expectancy (HALE) for 188 countries, 1990-2013: quantifying the epidemiological transition.

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