www.healthmetricsandevaluation.org/

시애틀 소재 워싱턴대학교 부설 연구소. 2011년 건강영향측정평가연구소(IHME)에서 펴낸 보고서에서 “미국은 1인당 보건의료에 투자하는 비용이 어느 나라보다도 높지만 평균 예상 수명은 30위권 이하인 것”으로 나타났으며,  2008년 기준으로 미국의 보건의료 지출은 2조3000억달러 이상이며 1인당 7681달러를 쓴 것으로 조사된 바 있다.

* Disability-Adjusted Life Year (DALY) 장애보정수명
http://www.who.int/healthinfo/global_burden_disease/metrics_daly/en/

[참고] Life, Not Death, is Focus of New Health Metrics
http://discovermagazine.com/2013/julyaug/18-international-health-metric-measures-years-lost

Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990—2010: a systematic analysis for the Global Burden of Disease Study 2010

The Lancet, Volume 380, Issue 9859, Pages 2197 – 2223, 15 December 2012
http://www.thelancet.com/journals/lancet/article/PIIS0140-6736(12)61689-4/abstract

Prof Christopher J L Murray MD f †‡, Prof Theo Vos PhD b, Prof Rafael Lozano MD f, Mohsen Naghavi PhD f, Abraham D Flaxman PhD f, Catherine Michaud MD j, Prof Majid Ezzati PhD k, Prof Kenji Shibuya MD m, Prof Joshua A Salomon PhD p, Safa Abdalla MBBS v *, Prof Victor Aboyans MD w *, Jerry Abraham MPH x *, Ilana Ackerman PhD ac *, Prof Rakesh Aggarwal MD ad *, Stephanie Y Ahn MPH f *, Mohammed K Ali MBChB af *, Mohammad A AlMazroa MD ag *, Miriam Alvarado BA f *, Prof H Ross Anderson MD ah *, Laurie M Anderson PhD g *, Kathryn G Andrews MPH f *, Charles Atkinson BS f *, Prof Larry M Baddour MD ai *, Adil N Bahalim MEng aj *, Suzanne Barker-Collo PhD ak *, Lope H Barrero ScD al *, David H Bartels BA u *, Prof Maria-Gloria Basáñez PhD l *, Amanda Baxter MPH a *, Prof Michelle L Bell PhD an *, Prof Emelia J Benjamin MD ap *, Derrick Bennett PhD aq *, Eduardo Bernabé PhD as *, Kavi Bhalla PhD u *, Bishal Bhandari MSc aw *, Boris Bikbov MD ax *, Aref Bin Abdulhak MD ay *, Prof Gretchen Birbeck MD az *, James A Black MPhil ba *, Hannah Blencowe MBChB bb *, Jed D Blore PhD b *, Fiona Blyth PhD bg *, Ian Bolliger AB f *, Audrey Bonaventure MD bh *, Soufiane Boufous PhD bi *, Prof Rupert Bourne MD bl *, Michel Boussinesq MD bm *, Tasanee Braithwaite BMBCh bn *, Prof Carol Brayne MD bo *, Lisa Bridgett PhD bg *, Prof Simon Brooker DPhil bb *, Prof Peter Brooks MD ac *, Prof Traolach S Brugha MD bp *, Claire Bryan-Hancock BPsych bq *, Chiara Bucello BPsyc bk *, Prof Rachelle Buchbinder MBBS br *, Geoffrey Buckle MPH bu *, Christine M Budke PhD bw *, Michael Burch MD bx *, Prof Peter Burney MD l *, Roy Burstein BA f *, Bianca Calabria BPsych bj *, Benjamin Campbell BA f *, Prof Charles E Canter MD by *, Prof Hélène Carabin PhD bz *, Prof Jonathan Carapetis MBBS ca *, Loreto Carmona MD cc *, Claudia Cella PharmChemD cd *, Fiona Charlson MPH b *, Honglei Chen PhD ce *, Prof Andrew Tai-Ann Cheng MD cf *, David Chou BA f *, Prof Sumeet S Chugh MD ch *, Luc E Coffeng MD cj *, Prof Steven D Colan MD s *, Samantha Colquhoun MPH ck *, K Ellicott Colson BA f *, John Condon PhD ck *, Myles D Connor PhD cn cl cm *, Prof Leslie T Cooper MD co *, Matthew Corriere MD cp *, Monica Cortinovis BiotechD cd *, Karen Courville de Vaccaro MD cq *, Prof William Couser MD i *, Benjamin C Cowie MBBS cr *, Prof Michael H Criqui MD cs *, Marita Cross PhD bg *, Kaustubh C Dabhadkar MBBS af *, Manu Dahiya BDS av *, Nabila Dahodwala MD ct *, James Damsere-Derry MPH cu *, Goodarz Danaei MD p *, Prof Adrian Davis PhD cv *, Prof Diego De Leo DSc cy *, Prof Louisa Degenhardt PhD aa bj *, Robert Dellavalle MD cz *, Allyne Delossantos BS f *, Julie Denenberg MA cs *, Sarah Derrett PhD da *, Don C Des Jarlais PhD db *, Prof Samath D Dharmaratne MBBS f dc *, Mukesh Dherani PhD dd *, Cesar Diaz-Torne MD de *, Prof Helen Dolk DrPH df *, E Ray Dorsey MD bv *, Tim Driscoll PhD bf *, Herbert Duber MD i *, Beth Ebel MD i *, Karen Edmond PhD bb *, Alexis Elbaz MD bh *, Suad Eltahir Ali Mcs dg *, Holly Erskine BPsySc a *, Patricia J Erwin MLS ai *, Patricia Espindola MD dh *, Stalin E Ewoigbokhan MPH di *, Farshad Farzadfar MD dk *, Prof Valery Feigin MD dl *, Prof David T Felson MD ao *, Alize Ferrari BPsySc a *, Cleusa P Ferri PhD do *, Eric M Fèvre PhD cm *, Mariel M Finucane PhD o *, Seth Flaxman BA dp *, Louise Flood MBBS bq *, Kyle Foreman MPH l *, Mohammad H Forouzanfar MD f *, Prof Francis Gerry R Fowkes FRCPE cm *, Marlene Fransen PhD bd *, Michael K Freeman BA f *, Belinda J Gabbe PhD bs *, Prof Sherine E Gabriel MD ai *, Emmanuela Gakidou PhD f *, Hammad A Ganatra MBBS af *, Bianca Garcia MPH e *, Flavio Gaspari ChemD cd *, Prof Richard F Gillum MD dr *, Prof Gerhard Gmel PhD ds *, Diego Gonzalez-Medina BA f *, Prof Richard Gosselin MD du *, Rebecca Grainger PhD da *, Bridget Grant PhD ej *, Justina Groeger MPH dv *, Prof Francis Guillemin MD dy *, Prof David Gunnell DSc dz *, Ramyani Gupta MSc ah *, Juanita Haagsma PhD cj *, Prof Holly Hagan PhD ea *, Yara A Halasa DDS eb *, Prof Wayne Hall PhD e *, Diana Haring BS f *, Josep Maria Haro MD ec *, Prof James E Harrison MBBS bq *, Rasmus Havmoeller MD cg ed *, Prof Roderick J Hay DM at *, Hideki Higashi PhD b *, Catherine Hill MBBS ee *, Prof Bruno Hoen MD ef eg *, Howard Hoffman MA eh *, Prof Peter J Hotez MD ek *, Damian Hoy PhD bt *, John J Huang MD an *, Sydney E Ibeanusi MBBS el *, Kathryn H Jacobsen PhD em *, Spencer L James MPH f *, Deborah Jarvis FFPH l *, Rashmi Jasrasaria BA f *, Sudha Jayaraman MD t *, Nicole Johns BA f *, Prof Jost B Jonas MD en *, Ganesan Karthikeyan MD eo *, Nicholas Kassebaum MD h *, Prof Norito Kawakami MD n *, Prof Andre Keren MD ep *, Jon-Paul Khoo MBBS a *, Prof Charles H King MD eq *, Lisa Marie Knowlton MD r *, Olive Kobusingye MMed er es *, Adofo Koranteng MSc et *, Rita Krishnamurthi PhD dm *, Francine Laden ScD p *, Prof Ratilal Lalloo PhD cw cx *, Laura L Laslett MMedSci eu *, Tim Lathlean MA bq *, Janet L Leasher OD ev *, Yong Yi Lee MHEcon b *, James Leigh MBBS bf *, Daphna Levinson PhD ew *, Stephen S Lim PhD f *, Elizabeth Limb MSc ah *, John Kent Lin AB p *, Michael Lipnick MD du *, Prof Steven E Lipshultz MD ex *, Wei Liu MD q *, Maria Loane MSc df *, Summer Lockett Ohno BA f *, Prof Ronan Lyons MD ey *, Jacqueline Mabweijano MMed ez *, Michael F MacIntyre EdM f *, Prof Reza Malekzadeh MD dj *, Leslie Mallinger MPH f *, Sivabalan Manivannan ScM bu *, Prof Wagner Marcenes PhD aw *, Prof Lyn March MD be *, Prof David J Margolis MD ct *, Prof Guy B Marks PhD bg *, Prof Robin Marks MBBS ac *, Akira Matsumori MD fa *, Richard Matzopoulos MPhil fb fe *, Prof Bongani M Mayosi DPhil fe *, John H McAnulty MD ff *, Prof Mary M McDermott MD fg *, Neil McGill FRACP bg *, Prof John McGrath MD d *, Maria Elena Medina-Mora PhD fh *, Michele Meltzer MD fi *, Prof Ziad A Memish MD ag fj *, Prof George A Mensah MD fd *, Tony R Merriman PhD da *, Ana-Claire Meyer MD du *, Valeria Miglioli cd *, Matthew Miller MD p *, Ted R Miller PhD fk *, Prof Philip B Mitchell MD bk *, Prof Charles Mock MD i *, Prof Ana Olga Mocumbi MD fl fm *, Prof Terrie E Moffitt PhD fn *, Ali A Mokdad MD f *, Lorenzo Monasta DSc fo *, Marcella Montico Msc fo *, Maziar Moradi-Lakeh MD dk *, Andrew Moran MD fq *, Prof Lidia Morawska PhD fr *, Rintaro Mori MD fs *, Michele E Murdoch FRCP ft *, Michael K Mwaniki MBChB fu *, Prof Kovin Naidoo PhD fv *, M Nathan Nair MD f *, Luigi Naldi MD fw *, K M Venkat Narayan MD af *, Paul K Nelson MHSc bj *, Robert G Nelson MD ei *, Michael C Nevitt PhD dt *, Prof Charles R Newton MD ar *, Sandra Nolte PhD fx *, Prof Paul Norman MD cb *, Rosana Norman PhD b *, Martin O’Donnell PhD fy *, Simon O’Hanlon MSc l *, Casey Olives PhD i *, Saad B Omer MBBS ae *, Katrina Ortblad BA f *, Prof Richard Osborne PhD fz *, Doruk Ozgediz MD am *, Andrew Page PhD b *, Bishnu Pahari MD ga *, Jeyaraj Durai Pandian MD gb *, Andrea Panozo Rivero MD gc *, Prof Scott B Patten MD gd *, Prof Neil Pearce PhD bb *, Rogelio Perez Padilla MD ge *, Fernando Perez-Ruiz MD gf *, Norberto Perico MD cd *, Prof Konrad Pesudovs PhD bq *, David Phillips BS f *, Prof Michael R Phillips MD gg *, Kelsey Pierce BA f *, Sébastien Pion PhD bm *, Guilherme V Polanczyk MD dn *, Suzanne Polinder PhD ci *, Prof C Arden Pope PhD gi *, Svetlana Popova MD gj *, Esteban Porrini MD gk *, Farshad Pourmalek MD gl *, Prof Martin Prince MD au *, Rachel L Pullan PhD bb *, Kapa D Ramaiah PhD gm *, Dharani Ranganathan BS f *, Homie Razavi PhD gn *, Mathilda Regan MPH go *, Prof Jürgen T Rehm PhD gj *, David B Rein PhD gp *, Prof Guiseppe Remuzzi MD cd *, Kathryn Richardson MSc bo *, Prof Frederick P Rivara MD i *, Thomas Roberts BA f *, Carolyn Robinson BS du *, Felipe Rodriguez De Leòn MD gq *, Luca Ronfani PhD fo *, Prof Robin Room PhD ab gr *, Lisa C Rosenfeld MPH f *, Lesley Rushton PhD l *, Prof Ralph L Sacco MD ex *, Sukanta Saha PhD a *, Prof Uchechukwu Sampson MD gs *, Lidia Sanchez-Riera MD be *, Ella Sanman BS f *, Prof David C Schwebel PhD gt *, James Graham Scott PhD c *, Maria Segui-Gomez MD gu *, Saeid Shahraz MD eb *, Prof Donald S Shepard PhD eb *, Hwashin Shin PhD gv *, Rupak Shivakoti BA bv *, David Singh MD gw *, Gitanjali M Singh PhD p *, Jasvinder A Singh MBBS gt *, Jessica Singleton MIPH bj *, David A Sleet PhD dw *, Prof Karen Sliwa MD fc *, Emma Smith PhD bc *, Jennifer L Smith MSc bb *, Nicolas JC Stapelberg MBBS cy *, Andrew Steer MBBS y *, Prof Timothy Steiner PhD gy *, Wilma A Stolk PhD cj *, Prof Lars Jacob Stovner PhD gx *, Christopher Sudfeld ScM p *, Sana Syed MBBS gz *, Giorgio Tamburlini PhD fo *, Mohammad Tavakkoli MD p *, Prof Hugh R Taylor MD ac *, Jennifer A Taylor PhD ha *, William J Taylor PhD da *, Bernadette Thomas MD i *, Prof W Murray Thomson PhD da *, Prof George D Thurston ScD ea *, Imad M Tleyjeh MD ay *, Prof Marcello Tonelli MD hb *, Prof Jeffrey A Towbin MD hd *, Thomas Truelsen MD he *, Prof Miltiadis K Tsilimbaris MD hf *, Clotilde Ubeda MD hg *, Eduardo A Undurraga PhD eb *, Marieke J van der Werf PhD hh *, Prof Jim van Os PhD hi *, Prof Monica S Vavilala MD i *, N Venketasubramanian FRCP hj *, Mengru Wang MPH f *, Prof Wenzhi Wang MD hk *, Kerrianne Watt PhD dq *, David J Weatherall MD ar *, Prof Martin A Weinstock MD hl *, Robert Weintraub MBBS z hm *, Marc G Weisskopf PhD p *, Prof Myrna M Weissman PhD fp *, Richard A White MA p *, Prof Harvey Whiteford MBBS a *, Natasha Wiebe BMath hc *, Steven T Wiersma MD dx *, Prof James D Wilkinson MD ex *, Prof Hywel C Williams PhD hn *, Sean RM Williams MBBS ho *, Emma Witt MSc dm *, Frederick Wolfe MD hp *, Prof Anthony D Woolf MBBS hq *, Sarah Wulf MPH f *, Pon-Hsiu Yeh MS hr *, Anita KM Zaidi MBBS gz *, Prof Zhi-Jie Zheng gh *, David Zonies MD hs *, Prof Alan D Lopez PhD b †

Summary

Background

Measuring disease and injury burden in populations requires a composite metric that captures both premature mortality and the prevalence and severity of ill-health. The 1990 Global Burden of Disease study proposed disability-adjusted life years (DALYs) to measure disease burden. No comprehensive update of disease burden worldwide incorporating a systematic reassessment of disease and injury-specific epidemiology has been done since the 1990 study. We aimed to calculate disease burden worldwide and for 21 regions for 1990, 2005, and 2010 with methods to enable meaningful comparisons over time.

Methods

We calculated DALYs as the sum of years of life lost (YLLs) and years lived with disability (YLDs). DALYs were calculated for 291 causes, 20 age groups, both sexes, and for 187 countries, and aggregated to regional and global estimates of disease burden for three points in time with strictly comparable definitions and methods. YLLs were calculated from age-sex-country-time-specific estimates of mortality by cause, with death by standardised lost life expectancy at each age. YLDs were calculated as prevalence of 1160 disabling sequelae, by age, sex, and cause, and weighted by new disability weights for each health state. Neither YLLs nor YLDs were age-weighted or discounted. Uncertainty around cause-specific DALYs was calculated incorporating uncertainty in levels of all-cause mortality, cause-specific mortality, prevalence, and disability weights.

Findings

Global DALYs remained stable from 1990 (2·503 billion) to 2010 (2·490 billion). Crude DALYs per 1000 decreased by 23% (472 per 1000 to 361 per 1000). An important shift has occurred in DALY composition with the contribution of deaths and disability among children (younger than 5 years of age) declining from 41% of global DALYs in 1990 to 25% in 2010. YLLs typically account for about half of disease burden in more developed regions (high-income Asia Pacific, western Europe, high-income North America, and Australasia), rising to over 80% of DALYs in sub-Saharan Africa. In 1990, 47% of DALYs worldwide were from communicable, maternal, neonatal, and nutritional disorders, 43% from non-communicable diseases, and 10% from injuries. By 2010, this had shifted to 35%, 54%, and 11%, respectively. Ischaemic heart disease was the leading cause of DALYs worldwide in 2010 (up from fourth rank in 1990, increasing by 29%), followed by lower respiratory infections (top rank in 1990; 44% decline in DALYs), stroke (fifth in 1990; 19% increase), diarrhoeal diseases (second in 1990; 51% decrease), and HIV/AIDS (33rd in 1990; 351% increase). Major depressive disorder increased from 15th to 11th rank (37% increase) and road injury from 12th to 10th rank (34% increase). Substantial heterogeneity exists in rankings of leading causes of disease burden among regions.

Interpretation

Global disease burden has continued to shift away from communicable to non-communicable diseases and from premature death to years lived with disability. In sub-Saharan Africa, however, many communicable, maternal, neonatal, and nutritional disorders remain the dominant causes of disease burden. The rising burden from mental and behavioural disorders, musculoskeletal disorders, and diabetes will impose new challenges on health systems. Regional heterogeneity highlights the importance of understanding local burden of disease and setting goals and targets for the post-2015 agenda taking such patterns into account. Because of improved definitions, methods, and data, these results for 1990 and 2010 supersede all previously published Global Burden of Disease results.

Funding

Bill & Melinda Gates Foundation.

==================================

술로 11개월, 담배로 9.4개월.. 건강壽命(수명) 축낸다

Population-wide weight loss and regain in relation to diabetes burden and cardiovascular mortality in Cuba 1980-2010: repeated cross sectional surveys and ecological comparison of secular trends

Manuel Franco, Usama Bilal, Pedro Orduñez, Mikhail Benet, Alain Morejón, Benjamín Caballero, Joan F Kennelly, Richard S Cooper

BMJ 2013;346:f1515 (Published 09 April 2013)

http://www.bmj.com/content/346/bmj.f1515

===============

경제봉쇄로 쿠바인 더 건강해져?

주영재 기자 jyj@kyunghyang.com

경향신문 입력 : 2013-04-10 13:53:29ㅣ수정 : 2013-04-10 13:53:29
http://news.khan.co.kr/kh_news/khan_art_view.html?artid=201304101353291&code=970100

쿠바인들이 1990년대 초반 미국의 경제봉쇄와 러시아 지원의 중단으로 석유와 식량 부족에 시달리며 힘든 시기를 겪으며 오히려 심장 질환과 당뇨의 발병률이 낮아졌다는 연구 결과가 나왔다.

쿠바인들은 1991~1995년까지 고난의 시기 동안 당나귀에 의존해 짐을 날랐고, 정부는 석유를 소비하는 차량 대신 중국에서 150만대의 자전거를 수입해야 했다.

가디언에 따르면 미국, 스페인, 쿠바의 대학 연구자들은 이 기간 식사량이 줄고, 자전거를 타거나 걷는 시간이 늘고, 육체 노동이 증가한 것이 건강에 어떤 영향을 미쳤는지를 확인하려고 했다.

쿠바는 무상 의료가 상당한 수준으로 진척된 국가로 “맨발의 의사”들이 광범위한 기초 진료를 행하고 있으며 국민 건강 상태에 대한 자료도 잘 구축되어 있다.

연구자들은 1980~2010년까지 쿠바인들의 몸무게와 심장질환, 뇌졸중, 당뇨로 인한 사망률의 변화를 관찰한 결과를 영국 메디컬저널에 발표했다.

스페인 마드리드의 알카라 대학의 마누엘 프랑코 교수가 이끈 연구진은 쿠바인의 몸무게가 경제봉쇄로 위기에 몰린 1991~1995년 동안 평균 5.5㎏ 감소했음을 알게됐다. 이는 건강에 직접적인 영향을 줘 당뇨로 인한 사망자를 절반까지 줄였으며 심근경색으로 인한 사망률은 3분의 1로 줄었다.

연구진은 “이런 추세는 소비에트 붕괴와 미국의 경제봉쇄로 쿠바 경제가 식량과 대중교통을 확보할 수 있는 능력이 줄어든 것과 관련이 있었다”며 “심각한 식량 및 에너지 부족은 열량 섭취를 줄이면서 동시에 (대중교통 대신 걷거나 자전거를 타면서) 열량 소비를 증가시켰다”고 말했다.

쿠바 경제 위기가 1996년 이후 끝나고 회복기에 들어서자 몸무게는 다시 증가하기 시작했고 신체활동 수준도 미미하지만 감소했다. 쿠바는 2000년부터 안정적인 성장을 지속했으며 2002년에 이르러서는 음식과 음료 소비량이 증가해 위기 이전 수준을 넘었다. 그 결과 2011년 쿠바 인구의 비만률은 1995년에 비해 거의 세배로 증가했다. 당뇨도 1995년부터 증가해 2002년부터 2010년까지 당뇨사망률은 위기 이전 수준의 증가세로 돌아갔다.

월터 윌렛 하버드 공공의료대학의 영양학과장은 이 연구가 “비만과 과체중 감소가 주는 커다란 이점을 보여주는 강력한 증거”라고 평가했다.

논문 저자들은 이같은 결과가 체중 감소가 실질적인 이득을 가져올 수 있다는 것을 보여준다고 주장하고 있다. 프랑코 교수는 “교통 정책이 근본적인 것으로 교통 수단으로 걷기와 자전거 타기를 장려할 필요성이 있다”고 밝혔다.

또한 육체 활동을 증진시키고 건강에 좋지 않은 음료와 음식을 어린이에게 공격적으로 홍보하는 것을 규제하거나 불량 식품에 더 많은 세금을 부과하는 것도 하나의 전략이라고 과학자들은 조언했다.

그럼에도 그는 쿠바의 경제 위기가 현재 경제위기를 겪는 유럽에 건강과 관련한 어떤 유사한 이득을 주지는 않을 것이라고 내다봤다. 인종과 사회적 환경이 유사한 쿠바와 달리 유럽은 훨씬 이질적이기 때문이다.

연구자들은 또한 과학 논문에 어울리지 않게 위기를 초래한 정치에 비난을, 쿠바인들의 대응 방식에 찬사를 보냈다.

이들은 논문에서 “우리는 고난의 기간 동안 극도로 어려운 사회 경제적 도전에 직면한 쿠바 국민들이 용기와 위엄을 잃지 않고 대응한 것에 존경과 찬사를 보낸다”며 “이 비극은 국제 정치에 의한 ‘인재’이며 다시는 어느 나라에서도 되풀이 되어선 안된다”고 썼다.

=======================

Research

Population-wide weight loss and regain in relation to diabetes burden and cardiovascular mortality in Cuba 1980-2010: repeated cross sectional surveys and ecological comparison of secular trends

BMJ 2013; 346 doi: http://dx.doi.org/10.1136/bmj.f1515 (Published 9 April 2013)

Cite this as: BMJ 2013;346:f1515
http://www.bmj.com/content/346/bmj.f1515

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1. Manuel Franco, associate professor1, adjunct associate professor2, visiting researcher3,
   
2. Usama Bilal, research assistant1, visiting researcher3,
   
3. Pedro Orduñez, regional adviser4, professor5,
   
4. Mikhail Benet, professor5,
   
5. Alain Morejón, assistant professor5,
   
6. Benjamín Caballero, professor6,
   
7. Joan F Kennelly, research assistant professor7,
   
8. Richard S Cooper, professor and chair8

Author Affiliations

1. 
   
   ¹Social and Cardiovascular Epidemiology Research Group, School of Medicine, University of Alcalá, Alcalá de Henares, Madrid, Spain
   
   
2. 
   
   ²Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
   
   
3. 
   
   ³Department of Epidemiology, Atherothrombosis and Cardiovascular Imaging, Centro Nacional de Investigaciones Cardiovasculares Madrid, Spain
   
   
4. 
   
   ⁴Project for Chronic Disease Prevention and Control, Pan American Health Organization, Washington, DC, USA
   
   
5. 
   
   ⁵Centro de Estudios sobre Enfermedades Crónicas, Universidad de Ciencias Médicas, Cienfuegos, Cuba
   
   
6. 
   
   ⁶Center for Human Nutrition, Department of International Health, Johns Hopkins Bloomberg School of Public Health, USA
   
   
7. 
   
   ⁷Division of Community Health Sciences, University of Illinois at Chicago School of Public Health, Chicago, IL, USA
   
   
8. 
   
   ⁸Department of Public Health Sciences, Loyola University Stritch School of Medicine, Maywood, IL, USA

1. Correspondence to: M Franco mfranco@uah.es

• Accepted 11 February 2013

Abstract

Objective To evaluate the associations between population-wide loss and gain in weight with diabetes prevalence, incidence, and mortality, as well as cardiovascular and cancer mortality trends, in Cuba over a 30 year interval.

Design Repeated cross sectional surveys and ecological comparison of secular trends.

Setting Cuba and the province of Cienfuegos, from 1980 to 2010.

Participants Measurements in Cienfuegos included a representative sample of 1657, 1351, 1667, and 1492 adults in 1991, 1995, 2001, and 2010, respectively. National surveys included a representative sample of 14 304, 22 851, and 8031 participants in 1995, 2001, and 2010, respectively.

Main outcome measures Changes in smoking, daily energy intake, physical activity, and body weight were tracked from 1980 to 2010 using national and regional surveys. Data for diabetes prevalence and incidence were obtained from national population based registries. Mortality trends were modelled using national vital statistics.

Results Rapid declines in diabetes and heart disease accompanied an average population-wide loss of 5.5 kg in weight, driven by an economic crisis in the mid-1990s. A rebound in population weight followed in 1995 (33.5% prevalence of overweight and obesity) and exceeded pre-crisis levels by 2010 (52.9% prevalence). The population-wide increase in weight was immediately followed by a 116% increase in diabetes prevalence and 140% increase in diabetes incidence. Six years into the weight rebound phase, diabetes mortality increased by 49% (from 9.3 deaths per 10 000 people in 2002 to 13.9 deaths per 10 000 people in 2010). A deceleration in the rate of decline in mortality from coronary heart disease was also observed.

Conclusions In relation to the Cuban experience in 1980-2010, there is an association at the population level between weight reduction and death from diabetes and cardiovascular disease; the opposite effect on the diabetes and cardiovascular burden was seen on population-wide weight gain.

Introduction

It was recognised early in the course of the global epidemic of type 2 diabetes that variation in the prevalence of the disease among populations could be explained largely by relative weight.1 This observation is supported by survey research from virtually every country in the World Health Organization database.2 Despite predictions on the effect of the obesity and diabetes epidemics on life expectancy,3 it is unclear to what extent they can alter the downward trend of cardiovascular diseases prevalence observed in many countries.4 Furthermore, lack of adequate data for public health precludes the empirical assessment of comparable trends across the developing world. Most cohort studies have suggested a “U” shaped association between body mass index and mortality, with the lowest point in the index range of 24 to 29.5 6 Therefore, key unknown factors are the net health impact of a given downward shift in the distribution of body mass index in a population, and the time lag between changes in body mass index and in the prevalence of non-communicable disease.7

Video abstract

Marked and rapid reductions in mortality from diabetes and coronary heart disease were observed in Cuba after the profound economic crisis of the early 1990s.8 These trends were associated with the declining capacity of the Cuban economy to assure food and mass transportation in the aftermath of the dissolution of the former Soviet Union and the tightening of the US embargo. Severe shortages of food and gas resulted in a widespread decline in dietary energy intake and increase in energy expenditure (mainly through walking and cycling as alternatives to mechanised transportation).

The largest effect of this economic crisis occurred over a period of about five years (1991-95, the so called “special period”), resulting in an average weight loss of 4-5 kg across the adult population.8 This economic crisis was not a full disruption of previous routines of daily life, but was actually characterised by its slow process of economic decline. During these years, the whole population continued to meet responsibilities in relation to work, school, and other social aspects, and the Ministry of Public Health maintained its regular surveillance system activities.9 10

Since then, the Cuban economy has shown a modest but constant recovery, especially after the year 2000.11 12 In fact, surveys have shown that the prevalence of obesity has now exceeded pre-crisis levels.13 The table⇓ shows basic sociodemographic and economic information on Cuba before, during, and after the economic crisis.

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Basic sociodemographic and economic information on Cuba at various stages of economic crisis¹²

To advance the prevention of non-communicable diseases, population-wide data remain crucial. Comparing disease rates over time, in relation to changes in risk factor levels in the population, indicates the extent to which disease can be prevented and what the most important risk factors are at the population level.14 The population preventive approach articulated by Geoffrey Rose in his seminal paper,15 is of importance when preventing and controlling non-communicable diseases, particularly cardiovascular diseases. The current study exemplifies a unique situation where population-wide body weight changed considerably, as a result of the combined and sustained effect of reduced energy intake and elevated physical activity. This scenario allowed us to assess its effect on diabetes and cardiovascular disease.16

Our objective was to examine the effect of population-wide changes in body weight—over a full cycle of weight loss and regain—on diabetes incidence, prevalence, and mortality in Cuba, from 1980 to 2010. We also assessed the effects of this weight change cycle on rates of death from cardiovascular disease, cancer, all causes.

Methods

To study the population-wide changes in body weight over time, we used four cross sectional surveys in the city of Cienfuegos, on the southern coast of Cuba. These surveys are part of the Project of Cienfuegos, an initiative designed to study the risk factors for non-communicable diseases in Cuba.

To obtain all available data from government and published sources on mortality, physical activity, energy intake, and smoking in Cuba between 1980 and 2011, we did a systematic search. We used the following databases: Medline, Spanish Bibliographic Index in Health Sciences (IBECS), and the Scientific Library Online (BVS-SciELO Cuba), which includes most Cuban journals. Web appendix 1 details the 12 references included.

Height, weight or overweight, and obesity

The four cross sectional surveys measured height and weight, on the basis of stratified probability samples from the urban population aged 15-74 years. The surveys included 1657, 1351, 1667, and 1492 adults for the years 1991, 1995, 2001, and 2011, respectively. The age distribution of the population in Cienfuegos is similar to the general Cuban population (web appendix 2). We used the following categories for body mass index: underweight (<18.5), normal weight (18.5-<25), overweight (25-<30), and obesity (≥30). All participants in the four surveys signed the informed consent. The ethics committee of the University of Medical Sciences, Cienfuegos, approved protocols.

Physical activity

Measures of self reported physical activity were available from representative samples of the population in Havana in 1987, 1988, and 1994 and from the national surveys on risk factors and chronic diseases (conducted nationally in 1995, 2001, and 2010, respectively). In these surveys, participants were designated as physically active if they engaged in regular physical activity, defined as 30 minutes of moderate or intense activity on at least five days per week.

Energy intake

The Food and Agriculture Organization of the United Nations provides disappearance data on energy intake per capita, by dividing total calories available for human consumption by the total population consuming the food supply during the reference period.

Smoking

National use of cigarettes per capita was calculated as the total number of cigarettes sold per year divided by the population aged 15 years and over. The prevalence of smoking was obtained from the national surveys on risk factors and chronic diseases conducted in 1995, 2001, and 2010, and other national studies previously conducted. We defined smoking as self reported current use of cigarettes or cigars (or both).17

Diabetes prevalence and incidence

In the Cuban national health system, the primary care doctor-nurse team is responsible for collecting health data for all residents in the neighbourhood of their catchment area (about 1500 individuals per team). One of the team activities organised by the health system is continuous assessment and risk evaluation (CARE, or Dispensarización in Spanish).18 19 All households are visited at least once a year for a comprehensive health evaluation of the family, while patients with chronic diseases receive a visit at least once every three to six months. These health examinations covered 61.2% (n=595 1088) of the population in 1979,20 75.9% (n=7 918 647) in 1989,20 and 98.2% (n=11 038 820) in 2009.21 We obtained data for diabetes prevalence and incidence from the CARE registries, spanning the time period of 1980-2009.20 21 These registries allow the monitoring of chronic disease trends, such as diabetes incidence or prevalence.

Mortality

We obtained annual, age adjusted rates of mortality per 100 000 people from the Cuban Ministry of Public Health. ICD-10 (international classification of diseases, 10th revision) codes were used for death from type 2 diabetes (E10-E14), coronary heart disease (I20-I25), stroke (I60-I69), cancer (C00-C97), and all causes for the period of 1980-2010. We used data from 1980 to examine possible trends unrelated to the economic crisis during the special period in 1991-95. The 1981 Cuban population census was used for age adjustment. Vital records in Cuba are essentially complete. Postmortem examinations in some hospitals include up to 85% of people coded as dying from cardiovascular disease, which provided considerable confidence in an accurate designation of the cause of death.22

Statistical analysis

To illustrate the distributions of body mass index in the four surveys from Cienfuegos (in 1991, 1995, 2001, and 2011), we used Stata SE version 12.1 to generate density plots through the Gaussian kernel function. To analyse changes in prevalence and mortality, joinpoint regression analysis was conducted using software developed by the Surveillance Research Program of the United States National Cancer Institute.23 This regression model allows identification of significant changes in linear trend slopes. The estimated annual change (%) was then computed for each mortality trend by fitting a regression line to the natural logarithm of the rates within each period or phase.

We did not use this procedure to analyse diabetes incidence, owing to missing data from the years during the crisis. Because incidence estimates are inherently unstable, we enhanced visual presentation by constructing moving averages for each year with available data, using the incidence data from the previous, current, and following year.

Results

Risk factor trends

From its lowest point in the mid-1990s, average daily intake of energy per capita increased monotonically, reaching pre-crisis levels in 2002 and levelling off in 2005 (fig 1⇓). On the other hand, physical activity had a slight downward trend after the mid-1990s, remaining stable from 2001, with more than half of the population being physically active. Although 80% of the population was classified as active in surveys conducted during the special period in 1991-95, this proportion fell steadily in the last decade, and is currently at 55% (fig 1). These population-wide changes in energy intake and physical activity were accompanied by large changes in body weight over this entire interval (figs 2⇓ and 3⇓).

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Fig 1 Physical activity, dietary energy intake, and smoking in Cuba, 1980-2010. Red shaded area=period of economic crisis; blue shaded area=period of economic recovery. Physical activity data recorded in 1987, 1988, and 1994 obtained from Havana surveys; data recorded in 1995, 2001, and 2010 come from national surveys. *1 kcal=0.00418 MJ

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Fig 2 Distributions of body mass index as recorded by national surveys conducted in Cienfuegos in 1991, 1995, 2001, and 2010

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Fig 3 Prevalence of obesity and diabetes, incidence, and mortality in Cuba, 1980-2010. Red shaded area=period of economic crisis; blue shaded area=period of economic recovery. Diabetes prevalence increased by 2.93% per year from 1980 to 1997, and 6.27% per year from 1997 to 2010. Diabetes mortality increased by 5.85% per year from 1980 to 1989, but fell by 0.68% per year from 1989 to 1996 and 13.95% per year from 1996 to 2002, before increasing by 3.31% per year from 2002 to 2010

Smoking prevalence (fig 1) slowly decreased during the 1980s and 1990s (42% in 1984, 37% in 1995), before declining more rapidly in the 2000s (32% in 2001, 24% in 2010). The number of cigarettes consumed per capita decreased during and shortly after the crisis. In 1990, 1934 cigarettes per capita were consumed (fig 1). This number changed to 1572, 1196, and 1449 cigarettes per capita in 1993, 1997, and 1999, respectively. Cigarette consumption has since remained stable.

Figure 2 depicts the distribution of body mass index from the Cienfuegos surveys of 1991, 1995, 2001, and 2010 with kernel density plots of each year’s measurements. During the special period of 1991-95, there was a weight loss of 5.5 kg across the entire range of body mass index (that is, not only among obese people), with a mean reduction in body mass index of 1.5 units. After a period of economic recovery and stability, an increase in body mass index of 2.6 units was observed from 1995 to 2010; weight regain also occurred across the entire population, irrespective of body mass index. These distribution shifts in body mass index were consistent across surveys. The proportion of the population in the normal weight category decreased from 56.4% at the end of the special period in 1995 to 42.1% in 2010. At the same time, proportions in the overweight and obesity categories increased by 19.4%, from 33.5% in 1995 to 52.9% in 2010 (web appendix 3).

Diabetes trends

Diabetes prevalence and incidence

Joinpoint regression analyses showed two different phases of diabetes prevalence (fig 3). The first phase had a slow and stable increase from 1980 (1.5 per 100 people) to 1997 (1.9 per 100 people), a total increase of 26.6% (2.9% per year). In the second phase, diabetes prevalence increased from 1.9 per 100 people in 1997 to 4.1 per 100 people in 2009 and 2010, a total increase of 115.8% (6.3% per year).

Incidence of diabetes fluctuated widely (fig 3). For the decade before the crisis, incidence was stable, between 1980 (1.5 per 1000 people) and 1989 (1.8 per 1000 people). The only data point in the middle of the economic crisis showed a decrease in diabetes incidence, falling to 1.2 per 1000 people in 1992. For the years immediately after the crisis, incidence was lower than pre-crisis levels (1 per 1000 people in 1996 and 1997 v 1.4 per 1000 people in 1999). Sharp increases were observed from 2000 onwards, peaking in 2002 (2.2 per 1000 people) and 2009 (2.4 per 1000 people). Thus, overall diabetes incidence decreased by 53% from its peak in the pre-crisis years (1986) to its lowest point after the crisis (1996 and 1997). Subsequently, incidence rose by 140% from 1996 to 2009.

Diabetes mortality

Joinpoint regression analysis of diabetes mortality showed four different phases (fig 3). The first phase, from 1980 to 1989 (pre-crisis years), was characterised by an increase of 60% (5.9% per year). The second phase from 1990 to 1996 overlapped with the special period in 1991-95, during which diabetes mortality stabilised (0.7% decrease per year). However, from 1996 to 2002, we recorded a decrease in diabetes mortality of 50% (13.95% per year). Finally, from 2002 onwards, mortality rose by 49% (3.31% per year; from 9.3 deaths per 10 000 people in 2002 to 13.9 deaths per 10 000 people in 2010), returning to pre-crisis rates.

Mortality trends

Coronary disease mortality

Mortality from coronary heart disease evolved in three phases (fig 4⇓). From 1980 to 1996, mortality fell consistently (reduction of 8.8%, 0.5% per year). After the crisis in 1996-2002, mortality decreased sharply by 34.4% (6.5% per year). After 2002, the rate of decline slowed to 7.4% (1.4% per year), similar to pre-crisis rates.

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Fig 4 Obesity prevalence and coronary heart disease, cancer and stroke mortality in Cuba (1980-2010). Red shaded area=period of economic crisis; blue shaded area=period of economic recovery; CHD=coronary heart disease. CHD mortality decreased by 0.50% per year from 1980 to 1996, 6.48% per year from 1996 to 2002, and 1.42% per year from 2002 to 2010. Cancer mortality decreased by 0.12% per year from 1980 to 1996, but increased by 0.47% per year from 1996 to 2010. Stroke mortality fell by 0.39% per year from 1980 to 2000, 5.03% per year from 2000 to 2004, and 0.01% per year from 2004 to 2010

Stroke mortality

Mortality from stroke mirrored the pattern of mortality from coronary heart disease, with a modest decrease of 6.9% lasting from 1980 to 2000 (0.4% per year) and a sharp fall between 2000 and 2004 of 13.6% (5.3% per year). From 2004 to 2010, mortality fell by 1.3% (0.01% per year, similar to pre-crisis rates).

Cancer mortality

Cancer mortality followed a distinctly different pattern to that observed in coronary heart disease, stroke, and diabetes, with two distinct phases (fig 4). From 1980 to 1996, a slight decrease of 2.4% in cancer mortality was observed (0.1% per year), which reverted to a slight increase of 5.4% in 1996-2010 (0.5% per year).

All cause mortality

Mortality from all causes, as expected, was highly influenced by trends in coronary heart disease and stroke, showing three different phases (data not shown). A prolonged decrease in mortality of 1.7% from 1980 to 1996 (0.1% per year) was followed a sharp decline of 10.5% from 1996 to 2002 (2.9% per year). From 2002 to 2010, there has been a modest decrease of 2% (0.7% per year).

Discussion

During the deepest period of the economic crisis in Cuba, lasting from 1991 to 1995, food was scarce and access to gas was greatly reduced, virtually eliminating motorised transport and causing the industrial and agricultural sectors to shift to manual intensive labour. This combination of food shortages and unavoidable increases in physical activity put the entire population in a negative energy balance, resulting in a population-wide weight loss of 4-5 kg.8 The decline in food availability was associated with a neuropathy outbreak in the adult population in 1993.24 25 The Cuban economy started recovering in 1996 with a sustained growth phase from 2000 onwards. Since 1996, physical activity has slightly declined. By 2002, energy intake had increased above pre-crisis levels.

As a result of the above trends, by 2011, the Cuban population has regained enough weight to almost triple the obesity rates of 1995. This U shaped, population-wide pattern in body weight is historically unique because of several factors: the initial weight loss occurred in a population that had been well nourished previously, lasted for five years, and affected people at all initial levels of body mass index.

Diabetes trends could have been substantially influenced by these population-wide changes in body weight. Diabetes prevalence surged from 1997 onwards, as weight started to rebound. Diabetes incidence decreased during the crisis, reaching its lowest point in 1996. The largest economic recovery saw diabetes incidence peaking in 2004 and 2009.

Five years after the start of the economic crisis in 1996, an abrupt downward trend was observed in mortality from diabetes, coronary heart disease, stroke, and all causes. This period lasted an additional six years, during which energy intake status gradually recovered and physical activity levels were progressively reduced; in 2002, mortality rates returned to the pre-crisis pattern. A particularly dramatic shift in diabetes mortality was observed: from 2002 to 2010, the annual increase in diabetes mortality was similar to that before the crisis. Moreover, declining rates of coronary heart disease and stroke slowed to annual decreasing rates similar to those before the crisis.

Comparison with other studies

The effect of high risk, preventive approaches on diabetes or cardiovascular mortality has been extensively studied and has reported conflicting and non-conclusive results. For example, the Look AHEAD clinical trial,26 aimed at reducing cardiovascular risk associated with diabetes through weight reduction and exercise, has been prematurely terminated for lack of an effect on cardiovascular mortality. Other high risk approaches, such as the prevention and control of diabetes through massive screenings, has recently shown no improvements in diabetes, cardiovascular, or all cause mortality.27 Overall, it seems that high risk preventive approaches have either not produced a beneficial effect on cardiovascular mortality or diabetes control and mortality, or have been unsuccessful in reducing risk to a sufficient degree to warrant a conclusion.

The complementary pathway to disease prevention, the population approach, has received scant attention in the literature. To our knowledge, the effect of population-wide weight regain on diabetes and cardiovascular mortality has not been previously studied. Research on population-wide interventions has so far only studied modelling studies28 or small scale interventions.14

Research on weight cycling, described in obese individuals undergoing repeated attempts at weight loss followed by weight regain, has reported conflicting results: either an increase29 30 31 32 or no association with general mortality.33 Specifically, no association between weight cycling and diabetes incidence has been recorded.34 35 Since individual weight cycling usually refers to multiple weight changes over an extended period, those results might have limited relevance for the population experience of a single cycle of weight gain, loss, and regain that we report here.

As shown in our results, smoking levels were affected by the crisis. The number of cigarettes smoked per capita in Cuba decreased in the crisis years, only to slightly recover afterwards and remain stable thereafter. Smoking prevalence has continuously decreased during the past 15 years in Cuba. The role of tobacco in the development and control of diabetes has been recently studied; both active and passive smoking are associated with increased incidence.36 This association is dose dependent37; therefore, the decrease in smoking in Cuba during the crisis may have contributed to the decline in diabetes incidence in those years. The effects of decreasing smoking rates should drive down the rates of diabetes incidence and mortality in the long term. In this case, the observed decline in smoking rates during and after the crisis should cause a decrease in diabetes mortality in the last decade of our study. The increase in diabetes mortality from year 2002 seems to rule out smoking as a major confounding factor in the observed trends, although it could be masking the true size of the effect of changes in dietary and physical activity on diabetes mortality. This consideration is analogous for coronary heart disease and stroke, which should fall as smoking prevalence declines.

Strengths and limitations of study

Our study presents the first observation of a population-wide event of this magnitude and its subsequent effects on public health. Population-wide shifts in other risk factors, such as cholesterol and blood pressure, have been described in large scale prevention interventions, for example, the North Karelia and FINRISK studies.38 In the Cuban experience, the changes in population-wide body weight were adaptive responses to dietary energy availability and energy expenditure; therefore, it is not possible to separate these two effects on mortality patterns.

Other unique effects of this experience should also be considered. Problems with food production in Cuba led to the creation and expansion of urban agriculture, allowing citizens to buy fresh produce directly from farmers. Large public health campaigns in schools and communities are currently in place using community gardening as an effort to improve nutrition education and diet quality.39 During the crisis, the Cuban government acquired and distributed more than one million bicycles, which contributed to the population-wide increase in physical activity.39 These unique features of the Cuban experience make it to that degree non-comparable with other examples of economic crises. For example, previous research on the health consequences of the Great Depression in the US showed that banking suspensions (as a proxy for large scale economic decline) was not followed by a decrease in mortality.40

As noted previously, controversy persists over the net benefit of generalised weight loss in modern populations.41 As articulated by Geoffrey Rose,15 a key element of a prevention strategy for diseases in populations with near universal exposure to the causal risk factor is a downward shift in the overall mean. The data presented here confirm this theory. The Cuban experience shows that within a relatively short period, modest weight loss in the whole population can have a profound effect on the overall burden of diabetes. In Cuba, weight loss also had a major effect on trends in cardiovascular diseases and all cause mortality. Although obesity is an important risk factor for cancer,42 only modest changes in cancer mortality were observed.

Our study has some important limitations. We had no data on diabetes incidence for most crisis years, and rates in the subsequent years showed wide fluctuations. Data for diabetes mortality were available for the whole study period, but might not have adequately represented the health burden of diabetes. Death certificates are subject to misclassification bias, although the parallel trends in cardiovascular and all cause mortality rule out substantial shifts away from diabetes to major illnesses that occurred at the same time—the most common of which would have been vascular in cause. The cyclic pattern of the observed trends makes a bias less likely, owing to widespread changes in coding of death certificates. Estimating dietary intake from food disappearance data has known limitations, but data from available dietary surveys for the years before, during, and after the special period were consistent with food disappearance data from the Food and Agriculture Organization.8

Conclusions and policy implications

We found that a population-wide loss of 4-5 kg in weight in a relatively healthy population was accompanied by diabetes mortality falling by half and mortality from coronary heart disease falling by a third. Furthermore, a rebound in body weight was associated with an increased diabetes incidence and mortality, and a deceleration of the decline in mortality from coronary heart disease. So far, no country or regional population has successfully reduced the distribution of body mass index or reduced the prevalence of obesity through public health campaigns or targeted treatment programmes.16 The latest reports in the US have documented a plateau in the epidemic curve of obesity in adults,43 children, and adolescents,44 but the public health effects of these changes have not yet been reported. It is therefore not possible to compare the Cuba findings with other populations. Therefore, the generalisability of our findings is uncertain. Nonetheless, these data are a notable illustration of the potential health benefits of reversing the global obesity epidemic.

What is already known on this topic

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  The health effects of population-wide changes in body weight on a well nourished population with a functioning universal health system is unknown

  
  
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  Large reductions in diabetes and cardiovascular mortality were noted after the population-wide weight loss in Cuba, during the economic crisis of the early 1990s

What this study adds

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  Body weight regain in the Cuban population was associated with an increase in diabetes prevalence, incidence, and mortality, as well as a deceleration in the previously declining rates of cardiovascular death

  
  
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  Small losses in body weight and prevention of body weight gain across the population could be a critical strategy in the prevention of non-communicable diseases

Notes

Cite this as: BMJ 2013;346:f1515

Footnotes

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  We would like to acknowledge our great respect and admiration for the Cuban people who faced extremely difficult social and economic challenges during the special period—and by making common cause against this tragedy held up with courage and dignity. This tragedy was “man made” by international politics and should never happen again to any population.

  
  
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  Contributors: MF and RC contributed to the original design. PO, MB, and AM organised and conducted data collection. UB conducted the statistical analyses. MF, UB, and RC carried on the systematic literature research. MF, UB, PO, BC, JFK, and RC were active in the interpretation of results. The manuscript was drafted by MF, UB, JFK, and RC, and reviewed by all authors. All authors have approved the final report. All authors had full access to the data in the study and take responsibility for its integrity and the accuracy of the data analysis. MF is the guarantor for this study.

  
  
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  Funding: No funding sources had any role in the decision to submit this manuscript or in its writing.

  
  
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  Competing interests: All authors have completed the Unified Competing Interest form at www.icmje.org/coi_disclosure.pdf (available on request from the corresponding author) and declare: no support from any organisation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous 3 years; no other relationships or activities that could appear to have influenced the submitted work.

  
  
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  Ethical approval: The ethics committee of the University of Medical Sciences, Cienfuegos, approved protocols.

  
  
• 
  

  Data sharing: No additional data available.

This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 3.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/3.0/.

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==================

Economic Hard Times in Cuba Reduces Rates Of Heart Disease And Diabetes

Medical News Today Article Date: 10 Apr 2013 – 11:00 PDT
http://www.medicalnewstoday.com/articles/258930.php

During the 1990s in Cuba, food was sparse and gasoline was nearly unavailable because of the US embargo and loss of Russian support; one of the positive consequences of that situation was a reduction in rates of diabetes and heart disease.

The “special period” (as it became known) was between 1991 and 1995 and consisted of people using donkeys to move loads, as well as the government importing 1.5 million bicycles from China for modes of transportation. The current study, published in BMJ, aimed to determine whether eating less, cycling, walking, and manual labor contributed to the health of the nation as a whole. In other words, might a change in whole nation’s dietary intake plus increased physical activity caused by transportation policies impact on the incidence of type 2 diabetes and cardiovascular disease?

The shortage of food and fuel in Cuba produced a reduction in dietary energy intake and a large increase in physical activity. These changes produced a population-wide weight loss of 4-5kg (8-11 lbs.) Significant decreases in death rates from coronary heart disease and diabetes were seen shortly after.

A team of investigators from Cuba, Spain, and the U.S. analyzed..:

• ..link between diabetes prevalence and population-wide body changes
  
• ..incidence and death rates from type 2 diabetes and cardiovascular disease
  
• ..cancer and all-causes

Cuba is a nation with a long history of public health and cardiovascular research, which provided the data needed from primary chronic disease registries, cardiovascular studies, and national health surveys. The Cuban population has seen economic and social changes directly associated with physical activity and food intake from 1980 to 2010.

The data used for the analysis included participants between the ages of 15 and 74 years and information on:

• height
  
• weight
  
• energy intake
  
• smoking
  
• physical activity

Dramatic Drop in Rates Seen Just From This Instance

Changes in physical activity and energy intake went hand-in-hand with changes in body weight. For example, between 1991 and 1995 there was a 5kg reduction on average, while between 1195 and 2010 a weight rebound was seen of 9kg.

The incidence of smoking fell during the 1980s and 1990s and decreased even more quickly in the 2000s.

The prevalence of diabetes continued to rise from 1997 as the population started to gain weight. It then decreased during the weight loss period, followed by another increase until it peaked in the weight regain years.

A sudden downward cycle in deaths from diabetes was seen five years after the beginning of the weight loss period, in 1996. This went on for about six years during which energy consumption status slowly recovered and physical activity levels decreased. In 2002, death rates went back to pre-crisis figures and a significant increase in diabetes deaths was seen.

Stroke and coronary heart disease death rates slowly dropped from 1980 to 1996 with a bigger decrease occurring after the weight-loss phase. During the weight regain phase, these declines stopped.

The investigators concluded that the “Cuban experienced in 1980-2010″ showed that within a short period, noteworthy weight loss in the whole population can greatly affect the overall burden of deaths from diabetes and cardiovascular disease.

They point out that findings show that a 5kg population-wide weight loss “would reduce diabetes mortality by half and CHD mortality by a third”, however, these findings are an unusual circumstance from this one experience. On the other hand, they do provide a “notable illustration of the potential health benefits of reversing the global obesity epidemic”.

Previous research has shown that there is a link between diabetes and heart disease. Diabetics are more likely to develop hardened arteries than non-diabetics.

A separate study demonstrated the association between sitting for long periods and developing heart disease and diabetes. Even for people who are physically active, sitting for long periods could raise the risk for both conditions.

Written by Kelly Fitzgerald

.

World Health Statistics 2012

http://www.who.int/healthinfo/EN_WHS2012_Full.pdf

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■ 모성 사망률 : 20년 동안 모성사망자 수는 1990년 54만명에서 2010년 29만명 이하로 약 47%   감소하였다. 이러한 모성사망의 1/3은 주로 두 국가에서 발생하고 있는데 인도는 숫자의 20%, 나이지리아는 14%를 차지한다.
■ 아동사망 원인의 10년 추이 : 2000년에서 2010년의 자료를 보면 지난 10년간 공중보건의 발전이 아동의 생명을 구하는데 도움이 되고 있음을 보여준다. 2000년 5세 이하 어린이 사망자 수가 약 1천만명에서 2010년 연간 사망자수 7백 6십만명으로 감소하는 큰 발전을 이루었다. 특히 설사관련 질환과 홍역으로 인한 사망자수의 감소가 특히 눈에 띈다.
■ 사망 등록: 전 세계 34개국(전체 인구의 15%)에서 질 높은 사망원인 자료를 생산하고 있으며, 저소득 국가에서는 전체 사망의 10% 이하만 등록되고 있다.

어린이 비만, 다른 심혈관계 위험 요인, 그리고 조숙 사망

1945년~1985년에 태어난 당뇨병이 없는 American Indian 어린이  4857명의 cohort  연구결과가 NEJM 최신호에 발표되었습니다.

체질량지수(BMI), 당 불내성(glucose tolerance), 혈압, 콜레스테롤 수치에 따른 내부적인 원인에 의한 조숙사망을 예측하였습니다.

그 결과 체질량지수(BMI), 당 불내성(glucose tolerance), 혈압과 내부적인 원인에 의한 조숙사망률은 아주 강한 연관관계가 있다는 사실이 밝혀졌습니다.

반면 어린이의 고지혈증(hypercholesterolemia)은 내부적인 원인에 의한 조숙사망률과 상관관계가 없는 것으로 밝혀졌습니다.

논문의 전문은 아래 내용과 첨부파일을 참조하시기 바랍니다.

한편 호주 멜버른 모나시 대학의 폴 오브라이언 박사팀이 최근 미국의사협회저널에 실은 보고서에서 “비만인 경우 위밴드수술을 받는 것이 체중 감량에 더욱 크고 지속적인 효과를 나타내는 것으로 나타났다”고 주장했다는 뉴스를 맨 아래에 첨부합니다.

======================================

ABSTRACT

Background The effect of childhood risk factors for cardiovascular disease on adult mortality is poorly understood.

Methods In a cohort of 4857 American Indian children without diabetes (mean age, 11.3 years; 12,659 examinations) who were born between 1945 and 1984, we assessed whether body-mass index (BMI), glucose tolerance, and blood pressure and cholesterol levels predicted premature death. Risk factors were standardized according to sex and age. Proportional-hazards models were used to assess whether each risk factor was associated with time to death occurring before 55 years of age. Models were adjusted for baseline age, sex, birth cohort, and Pima or Tohono O’odham Indian heritage.

Results There were 166 deaths from endogenous causes (3.4% of the cohort) during a median follow-up period of 23.9 years. Rates of death from endogenous causes among children in the highest quartile of BMI were more than double those among children in the lowest BMI quartile (incidence-rate ratio, 2.30; 95% confidence interval [CI], 1.46 to 3.62). Rates of death from endogenous causes among children in the highest quartile of glucose intolerance were 73% higher than those among children in the lowest quartile (incidence-rate ratio, 1.73; 95% CI, 1.09 to 2.74). No significant associations were seen between rates of death from endogenous or external causes and childhood cholesterol levels or systolic or diastolic blood-pressure levels on a continuous scale, although childhood hypertension was significantly associated with premature death from endogenous causes (incidence-rate ratio, 1.57; 95% CI, 1.10 to 2.24).

Conclusions Obesity, glucose intolerance, and hypertension in childhood were strongly associated with increased rates of premature death from endogenous causes in this population. In contrast, childhood hypercholesterolemia was not a major predictor of premature death from endogenous causes.

Despite recent increases in life expectancy, the rising global prevalence of obesity may reverse this trend.¹ The rising rates and increasingly early onset of other chronic diseases such as type 2 diabetes may also affect mortality rates.²

Cardiovascular risk factors are common in children.^3,4 Although early-onset diabetes has been shown to raise mortality rates,² and the relation between cardiovascular risk factors during adulthood and early death is well defined,^5,6,7 little is known about the way in which cardiovascular risk factors that are present during childhood affect life span. Defining such relationships may help predict the long-term human and economic costs of cardiovascular risk factors in childhood and might justify interventions that are intended to improve health and reduce the rates of premature death.

In this study, we assessed the extent to which obesity, glucose intolerance, hypertension, and hypercholesterolemia in children without diabetes predicted premature death (defined as death before 55 years of age) in American Indians from Arizona.

Methods

Study Population

We invited residents in a well-defined geographic area of the Gila River Indian Community in Arizona, most of whom were Pima or Tohono O’odham Indians,^8,9 to participate in a longitudinal study of diabetes and related disorders. Pima or Tohono O’odham Indian heritage was defined by the heritage of each of the child’s parents, grandparents, and great-grandparents, as reported by the parents of the participating children. Included in the study were 4857 children and adolescents (5 to <20 years of age) who had at least 4/8 Pima or Tohono O’odham Indian heritage, did not have diabetes, and underwent one or more research examinations between February 1966 and December 2003. Participants were born between 1945 and 1984 and resided on the reservation during the study. Participants who were 18 years of age or older gave written informed consent; those younger than 18 years of age gave written assent and a parent or guardian gave written informed consent. The institutional review board of the National Institute of Diabetes and Digestive and Kidney Diseases approved the study.

Study Examinations

We assessed the extent to which childhood body-mass index (BMI), 2-hour plasma glucose level during a 75-g oral glucose-tolerance test, and blood pressure and total cholesterol levels predicted premature death. The baseline examination was the first examination at which all these variables were measured. The analyses included data from the date of the baseline examination until the person’s death, the person’s 55th birthday, or the end of 2003, whichever came first. Vital status was ascertained as of December 31, 2003. Death records for community residents were maintained throughout the study period. Copies of death certificates were obtained. The underlying cause of death was classified as endogenous or external. We defined deaths due to endogenous causes as those in which the proximate cause was disease or self-inflicted injury, such as acute alcohol intoxication or drug use, and deaths due to external causes as those that resulted from such causes as accidents or homicide. These definitions are consistent with those used in previous mortality studies undertaken in this cohort.¹⁰ The cause of death was determined from a review of available clinical autopsy records and death certificates. (For a list of the specific causes of death and the corresponding International Classification of Diseases, 9th Revision [ICD-9] codes, see the Supplementary Appendix, available with the full text of this article at NEJM.org.)

All participants underwent a 75-g oral glucose-tolerance test; results were interpreted according to World Health Organization diagnostic criteria.¹¹ We considered diabetes to be present if the fasting plasma glucose concentration was more than 7.0 mmol per liter (126 mg per deciliter), if the 2-hour plasma glucose concentration was 11.1 mmol per liter (200 mg per deciliter) or more, or if a previous clinical diagnosis was documented. Blood pressure was measured and standard anthropometric data were obtained while participants were wearing lightweight clothing and no shoes; the data were collected by trained study personnel.^8,9,12 No measures of puberty were available. Blood assays were performed as described previously.^8,9,12 Alcohol dependence in adulthood (for which data were available from 2672 of the participants) was estimated with the use of the CAGE questionnaire.¹³

Statistical Analysis

Analyses were performed with the use of SAS software, version 9.1 (SAS Institute). The characteristics of the participants are presented as arithmetic means (±SD) or, in the case of characteristics with skewed distributions, as medians and ranges. The z scores, which were standardized within sex and 1-year age strata, were computed for use in regression analyses. Age-standardized and sex-standardized incidence was calculated by the direct method with the use of the total study population as the reference group. Incidence-rate ratios were calculated from the incidence data with the use of Poisson regression controlled for age, sex, and Pima or Tohono O’odham Indian heritage. For incidence analyses, follow-up was truncated at 55 years of age, since there were few person-years beyond that point. Cox proportional-hazards models were used to test for associations between the baseline childhood risk factors and time to death, with adjustment for baseline age, sex, Pima or Tohono O’odham Indian heritage, and birth year, since birth year was correlated with many variables of interest (e.g., r=0.36 for the correlation between BMI and birth year). We tested the validity of the proportionality assumption for each variable by including a time-dependent interaction term in the baseline models.¹⁴ When this assumption was violated, stratified proportional-hazards models were fitted and a summarized incidence-rate ratio was calculated across strata; no material differences in death rates were observed across sex and baseline-age strata (data not shown).

Results

Premature Death among Study Participants

Table 1 shows the baseline characteristics of the participants. During the follow-up period, 559 of the 4857 participants (11.5%) died before they reached 55 years of age. A total of 166 deaths were from endogenous causes: 59 were attributed to alcoholic liver disease, 22 to cardiovascular disease, 21 to infections, 12 to cancer, 10 to diabetes or diabetic nephropathy, 9 to acute alcoholic poisoning or drug overdose, and 33 to other causes (see the Supplementary Appendix for a list of ICD-9 codes). Table 2 shows the rates of premature death by 10-year age strata.

View this table: [in this window] [in a new window]   Table 1. Baseline Characteristics of the Participants and Prevalence of Death before 55 Years of Age.

 

View this table: [in this window] [in a new window]   Table 2. Premature Death among Study Participants, According to Age at Study Entry.

 
Childhood Obesity and Premature Death

BMI was positively associated with the risk of premature death from endogenous causes (incidence-rate ratio per 1 unit of BMI z score, 1.40; 95% confidence interval [CI], 1.20 to 1.63). BMI was positively, but not significantly, associated with death from external causes (incidence-rate ratio per 1 SD of standardized BMI, 1.19; 95% CI, 1.00 to 1.42).

Children in the highest quartile of age-standardized and sex-standardized BMI had significantly higher rates of death than did children in the lowest quartile (Figure 1 and Table 3). The rates of death from endogenous causes among children in the highest quartile of BMI were more than double those among children in the lowest quartile (incidence-rate ratio, 2.30; 95% CI, 1.46 to 3.62) (Table 3). This finding could not be explained just by the presence of extremely obese children in the highest quartile, however, since none of the 51 extremely obese children (BMI z score >3) died during the follow-up period, possibly because these participants were younger and from more recent birth cohorts (median follow-up, 21.4 years) than participants who were less obese. The association between BMI and premature death from endogenous causes was attenuated but remained significant after adjustment for baseline glucose level, cholesterol level, and blood pressure (incidence-rate ratio for the highest BMI quartile vs. the lowest quartile, 1.41; 95% CI, 1.19 to 1.67) (Table 3).

View larger version (36K): [in this window] [in a new window]   Figure 1. Kaplan–Meier Curves for Premature Death. The graphs show the rates of premature death from all causes, external causes, and endogenous causes according to quartiles of age-standardized and sex-standardized body-mass index at different baseline ages during childhood and adolescence. Plots were computed with the use of baseline data. Age at baseline for each age group was taken as the midpoint of the age range.

 

View this table: [in this window] [in a new window]   Table 3. Incidence-Rate Ratios for Premature Death, According to Quartile of Variables.

 
A total of 1394 of the children (28.7%) were obese, which was defined as a BMI in the 95th percentile or higher on the Centers for Disease Control and Prevention (CDC) growth charts.¹⁵ Among the obese children as compared with the nonobese children, the incidence-rate ratios were 1.31 (95% CI, 1.10 to 1.57) for premature death from all causes, 1.90 (95% CI, 1.37 to 2.65) for death from endogenous causes, and 1.14 (95% CI, 0.92 to 1.41) for death from external causes.

Childhood Glucose, Cholesterol, and Blood-Pressure Levels and Premature Death

The 2-hour plasma glucose level during a 75-g oral glucose-tolerance test, expressed in age-standardized and sex-standardized units, was not associated with premature death from either endogenous or external causes. However, children in the highest quartile of glucose level had a 73% higher risk of premature death from endogenous causes than children in the lowest quartile (Table 3). Adjustment for childhood BMI reduced the magnitude of the association (incidence-rate ratio, 1.24; 95% CI, 0.79 to 1.96).

In models of impaired glucose tolerance (i.e., 2-hour glucose level of 7.8 to 11.0 mmol per liter [140 to 199 mg per deciliter])¹⁸ as compared with normal glucose tolerance as the predictor variable, the incidence-rate ratios were 0.90 (95% CI, 0.63 to 1.30) for all-cause premature death, 0.81 (95% CI, 0.39 to 1.65) for death from endogenous causes, and 0.94 (95% CI, 0.62 to 1.43) for death from external causes. Children with impaired glucose tolerance accounted for 15% of the children in the highest quartile of plasma glucose levels and were all in the top decile of the standardized 2-hour glucose distribution.

No significant associations were observed between death rates and childhood cholesterol levels or blood pressure (Table 3). In models in which hypercholesterolemia, as defined by the American Heart Association cutoff point (total cholesterol level, 5.18 mmol per liter [200 mg per deciliter]), was used as the predictor variable,¹⁷ the incidence-rate ratios were 1.33 (95% CI, 0.95 to 1.88) for all-cause premature death, 1.70 (95% CI, 0.96 to 3.01) for death from endogenous causes, and 1.18 (95% CI, 0.77 to 1.80) for death from external causes.

With hypertension defined according to the criteria of the National High Blood Pressure Education Program¹⁶ in the case of children and as 140/90 mm Hg or higher in the case of participants 18 years of age or older, there was no significant association with rates of death from all causes (incidence-rate ratio, 1.15; 95% CI, 0.93 to 1.43) or from external causes (incidence-rate ratio, 0.98; 95% CI, 0.75 to 1.29). However, childhood hypertension was strongly associated with the rate of death from endogenous causes (incidence-rate ratio, 1.57; 95% CI, 1.10 to 2.24).

Potential Mediators of the Association between Obesity and Death

Most deaths occurred in study participants who were not known to have diabetes. Of the 559 participants in whom diabetes developed, 79 died: 40 from endogenous causes and 39 from external causes. Adjusting the BMI prediction models for incident diabetes did not significantly alter the risk estimates (incidence-rate ratio for the highest BMI quartile vs. the lowest quartile, 2.70; 95% CI, 1.70 to 4.31). In contrast, inclusion of diabetes in the 2-hour glucose model reduced the risk estimate for the highest quartile of 2-hour glucose levels, and the association between the highest and lowest quartiles was not significant (incidence-rate ratio, 1.10; 95% CI, 0.72 to 1.68). In Cox proportional-hazards models that included 2672 participants, there were no significant associations between childhood BMI and alcohol dependency in adulthood (incidence-rate ratio per unit of BMI z score, 1.01; 95% CI, 0.96 to 1.07).

Discussion

It is well known that obesity, glucose intolerance, hypertension, and hypercholesterolemia in adulthood increase mortality rates. We conducted the present study to determine whether the presence of these risk factors in childhood predicts premature death. The rate of death from endogenous causes in the highest quartile of childhood BMI was more than double that in the lowest quartile, and the rate in the highest quartile of childhood two-hour plasma glucose levels during a 75-g oral glucose-tolerance test was 73% higher than that in the lowest quartile. Although neither blood pressure nor cholesterol level in childhood, when included as a continuous variable, significantly predicted premature death, childhood hypertension increased the risk of premature death from endogenous causes by 57%.

The absence of an association between premature death and cholesterol levels may be due partly to the low proportion of deaths due to cardiovascular disease in this cohort (13.3%). Treatment for any of the predictor traits during childhood or during adulthood did not appear to explain the pattern of association (data not shown). No childhood risk factor that was examined significantly predicted rates of premature death from external causes.

Childhood obesity predicted premature death from endogenous, but not external, causes. The study was not powered to analyze effects on more specific categories of cause of death. Including only liver-related causes of death in the analysis reduced the magnitude of the association of premature death with childhood BMI and with the 2-hour glucose level, but the direction and pattern of associations were similar to those observed when all endogenous causes of death were included.

We considered whether the relationship between childhood BMI and premature death reflects associations with adiposity or some other component of body mass. Our study began before the availability of modern adiposity measures such as dual-energy x-ray absorptiometry. However, we previously reported relationships between BMI and adipose mass and between adipose mass and the cardiovascular risk factors in this population¹⁹; in that study, BMI and adiposity were strongly correlated (r>0.96), varying little with age and sex, and BMI and adipose mass were similarly correlated with the cardiovascular risk factors. Thus, the observations for childhood BMI reported here are likely to reflect a positive association between adiposity and rates of premature death.

In a study involving 508 U.S. adolescents (13 to 18 years of age) who were born between 1922 and 1935, overweight (>75th percentile of the sample distribution) was associated with increased rates of death due to coronary heart disease.²⁰ Two studies have assessed the relationship between body weight and mortality in European birth cohorts from the early 20th century.^21,22 In a study of 2299 Welsh children born between 1937 and 1939, there was no association between childhood BMI and death from cardiovascular causes.²¹ However, there was an association between childhood BMI and death from all causes; the lowest rate of death was seen in the next-to-lowest BMI quartile and the highest rate of death in the highest quartile, suggesting that, as in the case of adult Pima Indians,²³ a U-shaped relationship exists between obesity and mortality. In the second European study, involving 504 overweight children and adolescents admitted to hospitals in Stockholm between 1921 and 1947, weight gain between puberty and young adulthood was associated with cardiovascular disease, diabetes, and death from all causes.²² A limitation of these studies is that obesity was uncommon during the study period. For example, of the 2299 children in the Welsh study,²¹ only 92 (4.0%) had a BMI above the 90th percentile for the age-specific and sex-specific distributions of the 1990 British population, and British children in 1990 were leaner than their contemporary counterparts.²⁴

In the Arizona Pima Indians, unlike most other ethnic groups, childhood obesity has been common for decades.²⁵ It has been estimated that at the turn of the 21st century, approximately 15% of U.S. children between the ages of 6 and 19 years (11 million children) were overweight or obese,²⁶ a prevalence that is unlikely to decline in the near future²⁷ and that is triple the prevalence among children of the same age in the 1960s.^28,29 In the present study, 1394 children (28.7%) were obese (BMI, 95th percentile on the 2000 CDC growth charts). This prevalence is similar to that observed in contemporary Hispanic and African-American children.²⁷ Thus, although we studied a population with high rates of obesity and diabetes, our findings may reflect the future burden of premature death among contemporary children from other ethnic groups and may be more generalizable than the findings in previous studies.

In this study, we compared mortality rates with several clinical risk factors as variables. Adjusting the obesity models for the development of diabetes in adulthood did not significantly alter the risk estimates, whereas adjusting the glucose models for subsequent diabetes did attenuate the association between childhood glucose levels and premature death. Hence, dysregulated glucose metabolism in childhood may be a mediator of the effects of childhood obesity on mortality rates, but it does not appear to be the sole or dominant factor; however, the association between childhood glucose intolerance and premature death does appear to be mediated by the development of subsequent diabetes.

The pattern of the relationships between the risk factors and observed mortality supports the view that childhood obesity is an early metabolic derangement, whereas most of the other risk factors evolve later. In fact, the predictive power of a risk score for type 2 diabetes (including measures of obesity and insulin, blood-pressure, glucose, and lipid levels) in children is almost entirely dependent on abdominal obesity, whereas in adolescents, the risk profile has evolved to include obesity, hyperglycemia, and dyslipidemia.³⁰ Our findings complement those in our previous study, which showed that type 2 diabetes, when it occurs during adolescence in this population, strongly predicts subsequent renal failure and death.²

Although there was no significant association between childhood hypercholesterolemia and death before 55 years of age in this young cohort, an elevated cholesterol level in childhood may emerge as a significant risk factor and other causes of death may predominate if the cohort is followed to older ages. Cholesterol levels, however, are lower in American Indians than they are in most other ethnic groups,³¹ a finding that may partially explain the absence of association for this trait. The relationship between BMI and high-density lipoprotein (HDL) cholesterol is relatively strong in Pima children (r=–0.3 to –0.6), but the relationship between BMI and total cholesterol is weaker (r=0.1).¹⁹ The effect of BMI on premature death might be attributable in part to low HDL-cholesterol concentrations, which were not measured in most of the study participants. Nevertheless, we speculate that low HDL-cholesterol levels are likely to mediate rather than confound this relationship.

It is possible that the relationship between childhood BMI and mortality is confounded by unmeasured lifestyle factors. Nevertheless, obesity can be both the cause and the consequence of adverse lifestyle factors such as physical inactivity, excessive caloric intake, and specific nutrient preferences. Thus, such factors may be important components of the causal pathway between obesity and death. It is also possible that genetic factors have pleiotropic effects on BMI and mortality.

Childhood obesity is predictive of excess mortality in several divergent settings,^20,21,22 indicating that obesity itself is causally related to either death or other commonly related factors. Even if preventing childhood obesity does not affect the risk of death, increased physical activity and modification of diet are likely to have long-term benefits. The lack of specific data on such factors is a limitation of this study.

In summary, obesity in children who do not have diabetes is associated with an increased rate of death from endogenous causes during early adulthood, an association that may be partially mediated by the development of glucose intolerance and hypertension in childhood. In contrast, the cholesterol level in childhood is not a major determinant of premature death in this population. Childhood obesity is becoming increasingly prevalent around the globe. Our observations, combined with those of other investigators, suggest that failure to reverse this trend may have wide-reaching consequences for the quality of life and longevity. Such evidence underscores the importance of preventing obesity starting in the early years of life.

Supported by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) intramural research program. Dr. Franks was supported in part by grants from the Swedish Diabetes Association, the Swedish Heart Lung Foundation, the Swedish Research Council, Umeå University (Career Development Award), and the Västerbotten regional health authority (Strategic Appointment 2006-09).

No potential conflict of interest relevant to this article was reported.

We thank members of the Gila River Indian Community for participating in this study and for the profound commitment this community has made over the past half century to studies that seek to further our understanding of human health and disease; the staff of the Diabetes Epidemiology and Clinical Research Section of the NIDDK for conducting the examinations; and Joy C. Bunt, M.D., Ph.D., for comments on the manuscript.

Source Information

From the Diabetes Epidemiology and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ (P.W.F., R.L.H., W.C.K., M.L.S., P.H.B., H.C.L.); the Genetic Epidemiology and Clinical Research Group, Department of Public Health and Clinical Medicine, Section for Medicine, Umeå University Hospital, Umeå, Sweden (P.W.F.); the Medical Research Council Epidemiology Unit, Institute of Metabolic Sciences, University of Cambridge, Cambridge, United Kingdom (P.W.F.); and Mount Sinai School of Medicine, New York (H.C.L.).

Address reprint requests to Dr. Franks at the Genetic Epidemiology and Clinical Research Group, Department of Public Health and Clinical Medicine, Section for Medicine, Umeå University Hospital, Umeå 901 87, Sweden, or at paul.franks@medicin.umu.se

.

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10대 비만, 식이요법·운동보다 수술이 효과적”

출처 : 뉴시스 | 이진례 | 입력 2010.02.10 15:20

【시카고=로이터/뉴시스】이진례 기자 = 식욕을 억제하기 위해 위밴드수술을 받은 10대 과체중자들이 식이요법과 운동을 병행하는 10대 과체중자들보다 더욱 건강한 생활을 한다는 연구 결과가 나와 주목되고 있다.

호주 멜버른 모나시 대학의 폴 오브라이언 박사와 그의 동료들은 9일(현지시각) 미국의사협회저널에 실은 보고서에서 “연구 결과, 비만인 경우 위밴드수술을 받는 것이 체중 감량에 더욱 크고 지속적인 효과를 나타내는 것으로 나타났다”며 이와 같이 주장했다.

이들이 14세 이상~18세 이하 청소년 50명을 대상으로 실시한 결과, 위밴드수술을 받은 과체중 청소년 25명 가운데 21명은 자신의 초과 체중의 절반 이상을 뺐으나 식이요법과 운동, 행동수정프로그램을 실시한 또 다른 25명 가운데서는 단 3명만이 초과 체중의 절반 이상을 감소하는 데 성공했다.

또한 위밴드수술을 받은 지 2년이 지난 청소년들의 경우 총 신체 체중의 28.3%가 감소한 것으로 나타났는데, 이는 초과 체중의 78.8%에 해당하는 수준이다.

그러나 식이요법과 운동을 병행한 청소년의 경우 총 신체 체중의 3%만이 감소한 것으로 나타났는데, 이는 초과 체중의 13.2%에 해당하는 것이다.

아울러 위밴드수술은 비만과 더불어 신진대사증후군과 고혈압, 콜레스테롤 및 혈당 조절에 도움을 주는 것으로 나타났다.

이 연구팀이 연구를 시작할 당시 위밴드수술을 받은 청소년들 가운데 36%, 식이요법과 운동을 병행한 청소년의 40%가 신진대사증후군을 겪고 있었는데, 2년 후 위밴드수술을 받은 청소년 가운데서 신진대사증후군을 앓는 이는 한 명도 없었다. 그러나 위밴드수술을 받지 않은 청소년 가운데 22%는 여전히 신진대사증후군을 앓고 있었다.

텍사스 사우스웨스턴 의료대학의 교수이자 미국의사협회저널의 편집자인 에드워드 리빙스톤 박사는 논평을 통해 “이번 연구결과는 젊은이들을 위한 비만을 치료하는데 비만 치료 수술을 이용하는 것과 관련한 구체적인 증거를 제공해 준다”고 밝혔다.

이어 그는 “비만을 치료하기 위해 수술을 받는 것에 대한 논쟁으로, 비만 치료 수술을 지지하는 증거의 질이 조악한 상태”라며 “미국의 많은 보험사들이 비만 치료 수술을 위해서는 보험금을 지급하지 않을 것이고, 이러한 결정은 이들 지지자들의 설득력이 부족하고 일반적으로 받아들여질 수 있는 증거에 기인한 것이다”고 밝혔다.

현재 미국 어린이의 약 3분의 1이 비만을 겪고 있는 가운데, 버락 오바마 미국 대통령은 현 세대에서 해결해야할 최우선 과제 가운데 하나로 어린이 비만을 꼽고 있다.

그 동안 성인 비만과 관련된 비만 수술에 대한 안정성 및 효과에 대한 연구는 많았으나, 어린이와 10대 비만을 위한 체중감량 수술의 안전성 및 효과에 대한 연구는 부족했다.

eeka232@newsis.com

이대택(국민대 체육대) 교수가 최근 [비만 히스테릭](지성사)이라는
책을 펴냈는데… “비만이란 질병은 존재하지 않는다. 우리가 지금 알고 있는 비만의 위험성이나 다이어트의 건강에 대한 유용성은 모두 존재하지 않는다. 오히려 왜곡되어 있다.”는 주장에 기반하여 “비만과 건강의 관계는 과대 포장됐다”면서 체중이 높을수록 사망률이나 질병 발병률이 높다는 기존 연구 결과들의 ‘오류’를 꼬집는 내용이라고 합니다. 

이대택 교수는 비만과 과체중, 정상 체중을 가르는 척도로 흔히 쓰이는 신체질량지수(BMI)에 의문을 제기하고 있습니다. 키와 몸무게만 계산하고 체구성을 상관하지 않으므로 건강상의 위험성을 가려낼 수 없는데다, 서양인에게 쓰이는 기준을 그대로 동양인에게 쓰는 것도 적합하지 않다는 것입니다. 

그는 “과체중이면, 그리고 25세 이후에 체중이 늘면 심혈관 질환의 유발 위험이 커진다”는 연구 결과에 대해 운동과 체력, 다이어트 습관, 스트레스 등의 변인을 고려하지 않는 오류를 저질렀다고 지적했습니다.

그는 건강의 척도를 ‘체중’이나 ‘체격’이 아니라 ‘체력’에서 찾아야 한다고 주장하고 있습니다.
 
이대택 교수가 그 주장의 근거로 삼고 있는 내용은 폴 캄포스(Paul Campos)의 [비만 신화(The Diet Myth 2005),The Obesity Myth 2004)]인 것 같습니다.

사람들은 왜 비만을 ‘과하게’ 걱정하게 된 것일까요? 이대택 교수는 비만을 둘러싼 산업이 가장 발달한 미국에서 그 답을 찾고 있습니다.

이대택 교수는 폴 캄포스가 주장한 ”의료 산업과 제약 산업의 이윤을 극대화하는 입장에서 이상적인 질병은, 그 질병에 시달리게 하면서도 죽지 않게 하고, 효과적으로 치료도 안 되며, 그러면서도 의사나 환자가 치료를 위해 달려드는 그런 것”이라는 [비만 신화]의 내용을 소개하고 있습니다.

한편 미국 내 전국 레스토랑 연합체인 소비자자유센터(The Center for Consumer Freedom)는 폴 캄포스가 주장하는 내용과 거의 유사한 내용을 기반으로  비만과 질병과의 인과관계를 부인하고 있습니다.

소비자자유센터(The Center for Consumer Freedom)라는 NGO를 가장한 레스토랑 연합체는 담배소송과 유사한 ‘햄버거 소송’을 모면하기 위해 ‘비만’이 신화라고 주장하고 있으며… 육식을 권장하고 있습니다.

소비자자유센터(The Center for Consumer Freedom) 홈페이지에 파일 전문을 공개된 [An Epidemic of Obesity Myths](The Center for Consumer Freedom)의 목차는 아래와 같고… 원문 PDF파일은 첨부파일을 참조하시기 바랍니다.

콜라, 햄버거, 피자, 아스파탐 등 정크푸드, 패스트푸드를 통해 막대한 이윤을 창출하는 식품산업과 다이어트 식품, 살빼는 약, 수술 등을 통해 막대한 이윤을 창출하는 제약, 의료 산업을 비판하는 작업과 비만이 건강에 거의(또는 전혀) 영향을 끼치지 않으며 현대인이 만들어낸 신화에 불과하다는 과격한(?) 주장이 과연 서로 합치될 수 있을지 의문입니다.

또한 이과 별개로 체중, 체격, 체력, 체질량지수(BMI) 등과 건강과 질병에 대한 정의에 대해서도 철학적이고 근본적인 고민을 해봐야 할 것 같습니다.

=============================

An Epidemic of Obesity Myths

(원문 파일 : http://www.obesitymyths.com/downloads/obesityMyths.pdf)

The Myths
Introduction ……………………………………………………………………… 1
65 Percent of Americans Are Overweight or Obese …………….. 4
“Overweight” and “obese” celebrities and sports stars …………….. 5
Who was behind the redefi nition of “overweight”? ………………… 9
Experts criticize the body mass index (BMI) …………………………. 12
BMI report cards …………………………………………………………….. 13
Consequences of using the BMI …………………………………………. 15
Obesity Kills 400,000 Americans Annually ………………………….. 19
CDC study dramatically lowers death estimate ……………………… 20
Timeline of the debunked 400,000-deaths study …………………… 20
The CDC’s excuses …………………………………………………………. 34
Why the 26,000-deaths study is scientifi cally superior …………….. 37
Who was behind the 400,000-deaths statistic? ………………………. 51
Harvard’s straw man ………………………………………………………… 54
Experts questioning the obesity-mortality link………………………. 60
Obesity Will Shorten Life Expectancy ………………………………….. 67
Improving medical technology …………………………………………… 70
From science to activism …………………………………………………… 72
You Can’t Be Overweight and Healthy …………………………………. 77
Fitness vs. fatness …………………………………………………………….. 77
The cost of physical inactivity ……………………………………………. 82
Overeating Is the Primary Cause of Obesity …………………………. 85
A nation of couch potatoes ……………………………………………….. 85
The state of physical activity ………………………………………………. 92
Other causes of obesity …………………………………………………….. 94
Smoking cessation and weight gain …………………………………….. 96
Does food marketing cause obesity? …………………………………….. 96
Will nutrition information on restaurant menus help? …………….. 97
Fast food and obesity ……………………………………………………….. 100
Are healthy foods too expensive? ………………………………………… 101
Soda Causes Childhood Obesity ………………………………………….. 103
Obesity Costs Americans $117 Billion Annually …………………… 109
Obesity Has Made Diabetes Epidemic …………………………………. 113
Syndrome X …………………………………………………………………… 121
Childhood type-2 diabetes ………………………………………………… 123
The Myth Makers
Overview …………………………………………………………………………… 127
The Weight-loss Gold Rush ………………………………………………… 131
Professional Organizations Supported
by the Weight-loss Industry ……………………………………………….. 133
Influential Obesity Researchers and Their Industry Ties ……….. 145
Defending Fen-phen …………………………………………………………… 149

===========================

The Myths

65 Percent of Americans Are Overweight or Obese

Obesity Kills 400,000 Americans Annually

Obesity Will Shorten Life Expectancy

You Can’t Be Overweight and Healthy

Overeating Is the Primary Cause of Obesity

Soda Causes Childhood Obesity

Obesity Costs Americans $117 Billion Annually

Obesity Has Made Diabetes Epidemic

==========================

The Diet Myth: Why America’s Obsessions with Weight is Hazardous to Your Health

Paul Campos (Author)

Paperback: 336 pages
Publisher: Gotham (May 9, 2005)
Language: English

====================================
The Obesity Myth: Why America’s Obsession with Weight is Hazardous to Your Health

 Paul Campos (Author)
Hardcover: 288 pages
Language: English

[메디컬 피트니스] 신체 활동과 운동

출처 : 프레시안 기사입력 2010-02-04 오전 9:24:16

미국스포츠의학회(American College of Sports Medicine·www.acsm.org)의 조사에 따르면, 의사들 중 40퍼센트만이 신체 활동의 필요성을 환자들에게 이야기합니다. 의사들이 환자들에게 적절한 운동이 질병 예방과 치료에 중요하다는 사실을 수시로 주지시키지는 않는 것입니다.

그 결과 병원을 찾은 환자들 중 불과 25퍼센트만이 의사로부터 운동에 대한 권고를 받는 걸로 나타났습니다. 같은 조사에서 운동이 필요한 환자들에게 객관적인 충분한 정보들이 다양한 수준에서 제공된다면, 약 65퍼센트의 환자들이 보다 큰 관심을 갖고 삶의 질 향상을 위해 운동을 실천에 옮길 수 있을 것으로 전망하고 있습니다.

이처럼 신체 활동의 증가와 운동 요법이 질병의 예방과 치료에 표준화된 일부로 정착하는 일은 매우 필요한 일입니다. 한국에서도 의학적 패러다임을 전환시키는 중요한 이슈가 될 것이라 전망됩니다.

높은 사망률을 보이는 낮은 심폐적성

심폐적성이란 개인의 운동 능력을 나타내는 주요 지표로 신체 활동이나 운동에 따른 산소소모율로 평가됩니다. 남자 40만842명과 여자 1만2943명을 대상으로 한 대규모 역학조사에서 낮은 심폐적성이 높은 사망률을 설명하는 가장 주요한 인자임이 최근 보고에 의해 밝혀졌습니다(아래 그림 참조).

여러 건강 관련 위험인자들이나 만성질병보다도 신체 활동 저하로 인한 낮은 심폐적성이 사망률에 미치는 영향이 매우 커서 21세기에 가장 큰 개인의 건강 관련 문제일 것이라는 연구결과는 우리에게도 시사하는 바가 매우 크다 할 것입니다.

ⓒ프레시안

올바른 강도의 적절한 신체 활동의 유익성

비록 낮은 수준의 운동이라 하더라도 셀 수 없을 만큼 많은 장점을 가지고 있습니다. 올바른 강도의 적절한 신체 활동은 다음과 같은 구체적이고 객관적인 유익한 점들이 있습니다.

① 심장 질환을 40퍼센트 낮춥니다.
② 뇌졸중의 위험도를 27퍼센트 줄입니다.
③ 당뇨 발생을 거의 50퍼센트 줄입니다.
④ 고혈압의 발생을 50퍼센트까지 감소시킵니다.
⑤ 유방암의 사망률과 재발 위험을 50퍼센트 줄여줄 수 있습니다.
⑥ 대장암 발생을 60퍼센트 이상 감소시킬 수 있습니다.
⑦ 알츠하이머병(알츠하이머성 치매) 발병을 3분의 1로 줄여줄 수 있습니다.
⑧ 항우울제 복용이나 행동 치료만큼이나 우울증을 감소시킬 수 있습니다.

자신의 평소 신체 활동량 알기

아래 설문은 세계보건기구(World Health Organization·www.who.int)에서 마련한 신체 활동에 대한 단축형 설문입니다. 이 설문은 지난 7일간 독자께서 신체 활동에 얼마나 많은 시간을 소모했는지를 알아보는 것입니다.

스스로 활동적이지 않다고 생각되시더라도 각 질문에 응답해 보시기 바랍니다. 직장과 집에서 하는 활동, 교통수단을 이용할 때 하는 활동, 여가 시간에 시행하는 활동, 운동 또는 스포츠 모두를 포함하여 생각해 주시기 바랍니다.

귀하가 지난 7일간 하신 모든 격렬한 활동을 생각해보십시오. 격렬한 신체 활동이란 힘들게 움직이는 활동으로서 평소보다 숨이 훨씬 더 차게 만드는 활동입니다. 한 번에 적어도 10분 이상 지속한 활동만을 생각하여 응답해주시기 바랍니다. 1. 지난 7일간 무거운 물건 나르기, 달리기, 에어로빅, 빠른 속도로 자전거타기 등과 같은 격렬한 신체 활동을 며칠간 하였습니까? 일주일에 ( ) 일 ◇ 격렬한 신체 활동 없었음 ➣ 3번으로 가세요. 2. 그런 날 중 하루에 격렬한 신체 활동을 하면서 보낸 시간이 보통 얼마나 됩니까? 하루에 ( )시간 ( )분 ◇ 모르겠다. / 확실하지 않다. 지난 7일간 중간 정도의 신체 활동(평소보다 숨이 조금 더 차게 만드는 활동)을 한 번에 적어도 10분 이상 지속한 활동만을 생각하여 응답하여 주시기 바랍니다. 3. 지난 7일간 가벼운 물건 나르기, 보통 속도로 자전거 타기, 복식 테니스 등과 같은 중간 정도의 신체 활동을 며칠간 하였습니까? (걷기는 포함시키지 마세요) 일주일에 ( )일 ◇ 중간 정도의 신체 활동이 없었음. ➣ 5번으로 가세요. 4. 그런 날 중 하루에 중간 정도의 신체 활동을 하면서 보낸 시간이 보통 얼마나 됩니까? 하루에 ( )시간 ( )분 ◇ 모르겠다. / 확실하지 않다. 지난 7일간 걸은 시간을 생각해 보세요. 직장이나 집에서 혹은 오락 활동, 스포츠, 운동, 여가시간에 걸은 것도 포함됩니다. 5. 지난 7일간 한 번에 적어도 10분 이상 걸은 날은 며칠입니까? 일주일에 ( )일 ◇ 걷지 않았음. ➣ 7번으로 가세요. 6.그런 날 중 하루에 걸으면서 보낸 시간은 보통 어마나 됩니까? 하루에 ( )시간 ( )분 ◇ 모르겠다. / 확실하지 않다. 지난 7일간 앉아서 보낸 시간에 관한 것입니다. 책상에 앉아 있거나 친구를 만나거나, 독서를 할 때 앉거나, TV를 앉아서 또는 누워서 시청한 시간이 포함됩니다. 7. 지난 7일간 주중에 앉아서 보낸 시간이 보통 얼마나 됩니까? 하루에 ( )시간 ( )분 ◇ 모르겠다. / 확실하지 않다.

개인별 신체 활동량 판정

개인별 신체 활동량을 판정하기 위해서는 신체 활동에 따른 METs(metabolic equivalents)의 총합을 구해야 합니다. METs란 운동 강도를 표현하는 단위로 안정시 산소이용률(3.5ml/kg/min)을 1METs로 할 때 상대적인 크기로 나타낸 값입니다. METs의 값을 계산하여 아래와 같이 신체 활동을 평가할 수 있습니다.

격렬한 활동(A) : 분당 8.0METs
중등도의 신체활동(B) : 분당 4.0METs
걷는 것으로 대표되는 가벼운 신체 활동(C) : 분당 3.3METs

이와 같이 얻은 활동 정도를 이용하여 신체 활동 수준을 아래와 같이 판정합니다.

1) 높은 수준의 신체 활동 : 다음 둘 중의 하나에 해당될 때.
- 격렬한 신체 활동(A)을 최소한 일주일에 3일 이상 1500MET-minutes를 한 경우
- 어떤 수준의 운동의 조합이건 매일 운동을 하여 주 3000MET-minutes 이상 한 경우

2) 중간 수준의 신체 활동 : 다음 셋 중 하나에 해당될 때.
- 격렬한 신체 활동(A)을 최소한 일주일에 3일 이상 하루에 20분 이상 한 경우
- 중간 정도의 신체 활동(B)을 최소한 일주일에 5일 이상 하루에 30분 이상 한 경우
- 어떤 수준의 운동의 조합이건 5일 이상 운동을 하여 주 600MET-minutes 이상 한 경우

3) 낮은 수준의 신체 활동 : 위의 높은 수준이나 중간 수준에 해당되지 않는 신체 활동임.

신체 활동의 수준이 낮다는 것은 심폐적성이 낮음을 의미하며, 심폐적성이 낮다는 것은 위의 그림에서 볼 수 있는 바와 같이 비만, 흡연, 고혈압, 고지혈증, 당뇨 등 익히 알려져 있는 질병이나 질병 위험인자보다 더 높은 사망률을 보여 주는 중요한 인자입니다.

그러므로 독자 여러분들께서는 적어도 중간 수준의 신체 활동을 유지할 수 있을 만큼 운동을 생활화하셔서 심폐적성이 낮은 수준에 머물지 않도록 하시는 것이 건강유지의 지름길입니다.

/공인덕 연세대학교 운동의학센터 교수,예병일 연세대학교 운동의학센터 교수

Obesity and overweight

What are overweight and obesity?

Related links :: WHO Global Infobase :: WHO Global Database on Body Mass Index (BMI) :: WHO Global Strategy on Diet, Physical Activity and Health :: WHO Child Growth Standards :: WHO Department of Chronic Diseases and Health Promotion :: WHO Department of Nutrition for Health and Development

Overweight and obesity are defined as abnormal or excessive fat accumulation that may impair health.

Body mass index (BMI) is a simple index of weight-for-height that is commonly used in classifying overweight and obesity in adult populations and individuals. It is defined as the weight in kilograms divided by the square of the height in meters (kg/m2).

BMI provides the most useful population-level measure of overweight and obesity as it is the same for both sexes and for all ages of adults. However, it should be considered as a rough guide because it may not correspond to the same degree of fatness in different individuals.

The World Health Organization (WHO) defines “overweight” as a BMI equal to or more than 25, and “obesity” as a BMI equal to or more than 30. These cut-off points provide a benchmark for individual assessment, but there is evidence that risk of chronic disease in populations increases progressively from a BMI of 21.

The new WHO Child Growth Standards, launched in April 2006, include BMI charts for infants and young children up to age 5. However, measuring overweight and obesity in children aged 5 to 14 years is challenging because there is not a standard definition of childhood obesity applied worldwide. WHO is currently developing an international growth reference for school-age children and adolescents.

Facts about overweight and obesity

WHO’s latest projections indicate that globally in 2005:

• approximately 1.6 billion adults (age 15+) were overweight;
  
• at least 400 million adults were obese.

WHO further projects that by 2015, approximately 2.3 billion adults will be overweight and more than 700 million will be obese.

At least 20 million children under the age of 5 years are overweight globally in 2005.

Once considered a problem only in high-income countries, overweight and obesity are now dramatically on the rise in low- and middle-income countries, particularly in urban settings.

What causes obesity and overweight?

The fundamental cause of obesity and overweight is an energy imbalance between calories consumed on one hand, and calories expended on the other hand. Global increases in overweight and obesity are attributable to a number of factors including:

• a global shift in diet towards increased intake of energy-dense foods that are high in fat and sugars but low in vitamins, minerals and other micronutrients; and
  
• a trend towards decreased physical activity due to the increasingly sedentary nature of many forms of work, changing modes of transportation, and increasing urbanization.

What are common health consequences of overweight and obesity?

Overweight and obesity lead to serious health consequences. Risk increases progressively as BMI increases. Raised body mass index is a major risk factor for chronic diseases such as:

• Cardiovascular disease (mainly heart disease and stroke) – already the world’s number one cause of death, killing 17 million people each year.
  
• Diabetes – which has rapidly become a global epidemic. WHO projects that diabetes deaths will increase by more than 50% worldwide in the next 10 years.
  
• Musculoskeletal disorders – especially osteoarthritis.
  
• Some cancers (endometrial, breast, and colon).

Childhood obesity is associated with a higher chance of premature death and disability in adulthood.

Many low- and middle-income countries are now facing a “double burden” of disease:

• While they continue to deal with the problems of infectious disease and under-nutrition, at the same time they are experiencing a rapid upsurge in chronic disease risk factors such as obesity and overweight, particularly in urban settings.
  
• It is not uncommon to find under-nutrition and obesity existing side-by-side within the same country, the same community and even within the same household.
  
• This double burden is caused by inadequate pre-natal, infant and young child nutrition followed by exposure to high-fat, energy-dense, micronutrient-poor foods and lack of physical activity.

How can the burden of overweight and obesity be reduced?

Overweight and obesity, as well as their related chronic diseases, are largely preventable.

At the individual level, people can:

• achieve energy balance and a healthy weight;
  
• limit energy intake from total fats and shift fat consumption away from saturated fats to unsaturated fats;
  
• increase consumption of fruit and vegetables, as well as legumes, whole grains and nuts;
  
• limit the intake of sugars; and
  
• increase physical activity – at least 30 minutes of regular, moderate-intensity activity on most days. More activity may be required for weight control.

The implementation of these recommendations requires sustained political commitment and the collaboration of many stakeholders, public and private. Governments, international partners, civil society and nongovernmental organizations and the private sector have vital roles to play in shaping healthy environments and making healthier diet options affordable and easily accessible. This is especially important for the most vulnerable in society – the poor and children – who have limited choices about the food they eat and the environments in which they live.

Initiatives by the food industry to reduce the fat, sugar and salt content of processed foods and portion sizes, to increase introduction of innovative, healthy, and nutritious choices, and to review current marketing practices could accelerate health gains worldwide.

WHO’s strategy for preventing overweight and obesity

Adopted by the World Health Assembly in 2004, the WHO Global Strategy on Diet, Physical Activity and Health describes the actions needed to support the adoption of healthy diets and regular physical activity. The Strategy calls upon all stakeholders to take action at global, regional and local levels and aims to lead to a significant reduction in the prevalence of chronic diseases and their common risk factors, primarily unhealthy diet and physical inactivity.

WHO’s work on diet and physical activity is part of the overall WHO chronic disease prevention and control framework of the Department of Chronic Diseases and Health Promotion. The strategic objectives of the department are to: advocate for health promotion and chronic disease prevention and control; promote health, especially for poor and disadvantaged populations; slow and reverse the adverse trends in the common chronic disease risk factors; and prevent premature deaths and avoidable disability due to major chronic diseases.

This work is complemented by that of the Department of Nutrition for Health and Development. The strategic objectives of the department are to promote healthy diets and improve the nutritional status of the population throughout the life course, particularly among the vulnerable. This is achieved by providing support to countries in developing and implementing national intersectoral Food and Nutrition Policies and Programmes to address double-burden of nutrition-related ill-health, and to contribute to the achievement of the Millennium Development Goals (MDGs).

For more information contact:

WHO Media centre
Telephone: +41 22 791 2222
E-mail: mediainquiries@who.int

김빛내리 교수 등 ‘성장조절 마이크로RNA’ 발견
한겨레 | 입력 2009.12.11 08:20

 
[한겨레] 김빛내리(사진) 서울대 생명과학부 교수와 현서강·이정현 박사 등 연구팀이 인슐린 신호 전달을 조절해 신체 성장에 영향을 끼치는 마이크로 아르엔에이(RNA)와 관련 유전자를 발굴해 국제 과학저널 < 셀 > 11일치에 발표한다.

마이크로 아르엔에이는 20개가량의 염기로 이뤄진 아주 작은 아르엔에이를 말하는데, 아르엔에이는 오랜 동안 유전정보를 전달하는 수동적인 물질로 이해됐으나 최근엔 유전자와 단백질의 기능에 개입하는 마이크로 아르엔에이들이 잇따라 발견돼 크게 주목받고 있다.

이 분야에서 국제적 명성을 얻고 있는 김 교수 연구팀은 이번 연구에서 초파리에 있는 마이크로 아르엔에이의 하나인 ‘미르(miR)-8′(사람에선 ‘미르-200′)이 없어지면 초파리의 몸집이 작게 성장한다는 것을 확인했으며 이 아르엔에이가 지방세포에서 인슐린 신호 전달을 촉진해 어린 초파리의 신체 성장을 조절한다는 사실을 발견했다.

또 이 아르엔에이가 제어하는 유전자를 찾아냄으로써 기존에 알려지지 않은 새로운 방식으로 인슐린 신호 전달이 조절되며, 이런 작용이 사람 세포에도 그대로 적용될 수 있음을 확인했다. 연구팀은 “인슐린 신호 전달이 암·당뇨·노화와 관련이 있어, 이번 연구는 마이크로 아르엔에이와 질병의 연관성을 연구하는 데 중요한 단서가 될 것”으로 기대했다.

오철우 기자 cheolwoo@hani.co.kr