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Showing papers by "Luca Ronfani published in 2015"


Journal ArticleDOI
Mohsen Naghavi1, Haidong Wang1, Rafael Lozano1, Adrian Davis2  +728 moreInstitutions (294)
TL;DR: In the Global Burden of Disease Study 2013 (GBD 2013) as discussed by the authors, the authors used the GBD 2010 methods with some refinements to improve accuracy applied to an updated database of vital registration, survey, and census data.

5,792 citations


Journal ArticleDOI
TL;DR: The Global Burden of Disease, Injuries, and Risk Factor study 2013 (GBD 2013) as discussed by the authors provides a timely opportunity to update the comparative risk assessment with new data for exposure, relative risks, and evidence on the appropriate counterfactual risk distribution.

5,668 citations


Journal ArticleDOI
Theo Vos1, Ryan M Barber1, Brad Bell1, Amelia Bertozzi-Villa1  +686 moreInstitutions (287)
TL;DR: In the Global Burden of Disease Study 2013 (GBD 2013) as mentioned in this paper, the authors estimated the quantities for acute and chronic diseases and injuries for 188 countries between 1990 and 2013.

4,510 citations


Journal ArticleDOI
Christina Fitzmaurice1, Christina Fitzmaurice2, Daniel Dicker2, Daniel Dicker1, Amanda W Pain1, Hannah Hamavid1, Maziar Moradi-Lakeh1, Michael F. MacIntyre1, Michael F. MacIntyre3, Christine Allen1, Gillian M. Hansen1, Rachel Woodbrook1, Charles D.A. Wolfe1, Randah R. Hamadeh4, Ami R. Moore5, A. Werdecker6, Bradford D. Gessner, Braden Te Ao, Brian J. McMahon7, Chante Karimkhani8, Chuanhua Yu9, Graham S Cooke10, David C. Schwebel11, David O. Carpenter12, David M. Pereira13, Denis Nash, Dhruv S. Kazi14, Diego De Leo15, Dietrich Plass16, Kingsley N. Ukwaja17, George D. Thurston, Kim Yun Jin18, Edgar P. Simard19, Edward J Mills20, Eun-Kee Park21, Ferrán Catalá-López22, Gabrielle deVeber, Carolyn C. Gotay23, Gulfaraz Khan24, H. Dean Hosgood25, Itamar S. Santos26, Janet L Leasher27, Jasvinder A. Singh28, James Leigh12, Jost B. Jonas29, Juan R. Sanabria30, Justin Beardsley31, Justin Beardsley32, Kathryn H. Jacobsen33, Ken Takahashi34, Richard C. Franklin, Luca Ronfani35, Marcella Montico36, Luigi Naldi36, Marcello Tonelli, Johanna M. Geleijnse37, Max Petzold38, Mark G. Shrime39, Mark G. Shrime40, Mustafa Z. Younis41, Naohiro Yonemoto42, Nicholas J K Breitborde, Paul S. F. Yip43, Farshad Pourmalek44, Paulo A. Lotufo24, Alireza Esteghamati27, Graeme J. Hankey45, Raghib Ali46, Raimundas Lunevicius33, Reza Malekzadeh47, Robert P. Dellavalle45, Robert G. Weintraub48, Robert G. Weintraub49, Robyn M. Lucas50, Robyn M. Lucas51, Roderick J Hay52, David Rojas-Rueda, Ronny Westerman, Sadaf G. Sepanlou53, Sandra Nolte, Scott B. Patten54, Scott Weichenthal37, Semaw Ferede Abera55, Seyed-Mohammad Fereshtehnejad56, Ivy Shiue57, Tim Driscoll58, Tim Driscoll59, Tommi J. Vasankari29, Ubai Alsharif, Vafa Rahimi-Movaghar54, Vasiliy Victorovich Vlassov45, W. S. Marcenes60, Wubegzier Mekonnen61, Yohannes Adama Melaku62, Yuichiro Yano56, Al Artaman63, Ismael Campos, Jennifer H MacLachlan41, Ulrich O Mueller, Daniel Kim53, Matias Trillini64, Babak Eshrati65, Hywel C Williams66, Kenji Shibuya67, Rakhi Dandona68, Kinnari S. Murthy69, Benjamin C Cowie69, Azmeraw T. Amare, Carl Abelardo T. Antonio70, Carlos A Castañeda-Orjuela71, Coen H. Van Gool, Francesco Saverio Violante, In-Hwan Oh72, Kedede Deribe73, Kjetil Søreide74, Kjetil Søreide62, Luke D. Knibbs75, Luke D. Knibbs76, Maia Kereselidze77, Mark Green78, Rosario Cardenas79, Nobhojit Roy80, Taavi Tillmann57, Yongmei Li81, Hans Krueger82, Lorenzo Monasta24, Subhojit Dey36, Sara Sheikhbahaei, Nima Hafezi-Nejad45, G Anil Kumar45, Chandrashekhar T Sreeramareddy69, Lalit Dandona83, Haidong Wang69, Haidong Wang1, Stein Emil Vollset1, Ali Mokdad84, Ali Mokdad76, Joshua A. Salomon1, Rafael Lozano41, Theo Vos1, Mohammad H. Forouzanfar1, Alan D. Lopez1, Christopher J L Murray51, Mohsen Naghavi1 
Institute for Health Metrics and Evaluation1, University of Washington2, Iran University of Medical Sciences3, King's College London4, Arabian Gulf University5, University of North Texas6, Auckland University of Technology7, Alaska Native Tribal Health Consortium8, Columbia University9, Wuhan University10, Imperial College London11, University of Alabama at Birmingham12, University at Albany, SUNY13, City University of New York14, University of California, San Francisco15, Griffith University16, Environment Agency17, New York University18, Southern University College19, Emory University20, University of Ottawa21, Kosin University22, University of Toronto23, University of British Columbia24, United Arab Emirates University25, Albert Einstein College of Medicine26, University of São Paulo27, Nova Southeastern University28, University of Sydney29, Heidelberg University30, Case Western Reserve University31, Cancer Treatment Centers of America32, University of Oxford33, George Mason University34, James Cook University35, University of Trieste36, University of Calgary37, Wageningen University and Research Centre38, University of Gothenburg39, University of the Witwatersrand40, Harvard University41, Jackson State University42, University of Arizona43, University of Hong Kong44, Tehran University of Medical Sciences45, University of Western Australia46, Aintree University Hospitals NHS Foundation Trust47, University of Colorado Denver48, Veterans Health Administration49, Royal Children's Hospital50, University of Melbourne51, Australian National University52, University of Marburg53, Charité54, Health Canada55, College of Health Sciences, Bahrain56, Karolinska Institutet57, Northumbria University58, University of Edinburgh59, National Research University – Higher School of Economics60, Queen Mary University of London61, Addis Ababa University62, Northwestern University63, Northeastern University64, Mario Negri Institute for Pharmacological Research65, Arak University of Medical Sciences66, University of Nottingham67, University of Tokyo68, Public Health Foundation of India69, University of Groningen70, University of the Philippines Manila71, University of Bologna72, Kyung Hee University73, Brighton and Sussex Medical School74, Stavanger University Hospital75, University of Bergen76, University of Queensland77, National Centre for Disease Control78, University of Sheffield79, Universidad Autónoma Metropolitana80, University College London81, Genentech82, Universiti Tunku Abdul Rahman83, Norwegian Institute of Public Health84
TL;DR: To estimate mortality, incidence, years lived with disability, years of life lost, and disability-adjusted life-years for 28 cancers in 188 countries by sex from 1990 to 2013, the general methodology of the Global Burden of Disease 2013 study was used.
Abstract: Importance Cancer is among the leading causes of death worldwide. Current estimates of cancer burden in individual countries and regions are necessary to inform local cancer control strategies. Objective To estimate mortality, incidence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs) for 28 cancers in 188 countries by sex from 1990 to 2013. Evidence Review The general methodology of the Global Burden of Disease (GBD) 2013 study was used. Cancer registries were the source for cancer incidence data as well as mortality incidence (MI) ratios. Sources for cause of death data include vital registration system data, verbal autopsy studies, and other sources. The MI ratios were used to transform incidence data to mortality estimates and cause of death estimates to incidence estimates. Cancer prevalence was estimated using MI ratios as surrogates for survival data; YLDs were calculated by multiplying prevalence estimates with disability weights, which were derived from population-based surveys; YLLs were computed by multiplying the number of estimated cancer deaths at each age with a reference life expectancy; and DALYs were calculated as the sum of YLDs and YLLs. Findings In 2013 there were 14.9 million incident cancer cases, 8.2 million deaths, and 196.3 million DALYs. Prostate cancer was the leading cause for cancer incidence (1.4 million) for men and breast cancer for women (1.8 million). Tracheal, bronchus, and lung (TBL) cancer was the leading cause for cancer death in men and women, with 1.6 million deaths. For men, TBL cancer was the leading cause of DALYs (24.9 million). For women, breast cancer was the leading cause of DALYs (13.1 million). Age-standardized incidence rates (ASIRs) per 100 000 and age-standardized death rates (ASDRs) per 100 000 for both sexes in 2013 were higher in developing vs developed countries for stomach cancer (ASIR, 17 vs 14; ASDR, 15 vs 11), liver cancer (ASIR, 15 vs 7; ASDR, 16 vs 7), esophageal cancer (ASIR, 9 vs 4; ASDR, 9 vs 4), cervical cancer (ASIR, 8 vs 5; ASDR, 4 vs 2), lip and oral cavity cancer (ASIR, 7 vs 6; ASDR, 2 vs 2), and nasopharyngeal cancer (ASIR, 1.5 vs 0.4; ASDR, 1.2 vs 0.3). Between 1990 and 2013, ASIRs for all cancers combined (except nonmelanoma skin cancer and Kaposi sarcoma) increased by more than 10% in 113 countries and decreased by more than 10% in 12 of 188 countries. Conclusions and Relevance Cancer poses a major threat to public health worldwide, and incidence rates have increased in most countries since 1990. The trend is a particular threat to developing nations with health systems that are ill-equipped to deal with complex and expensive cancer treatments. The annual update on the Global Burden of Cancer will provide all stakeholders with timely estimates to guide policy efforts in cancer prevention, screening, treatment, and palliation.

2,375 citations


Journal ArticleDOI
TL;DR: The Global Burden of Disease, Injuries, and Risk Factor study 2013 (GBD 2013) as mentioned in this paper provides a timely opportunity to update the comparative risk assessment with new data for exposure, relative risks, and evidence on the appropriate counterfactual risk distribution.

1,656 citations


Journal ArticleDOI
TL;DR: Patterns of the epidemiological transition with a composite indicator of sociodemographic status, which was constructed from income per person, average years of schooling after age 15 years, and the total fertility rate and mean age of the population, were quantified.

1,609 citations


Journal ArticleDOI
21 May 2015-PLOS ONE
TL;DR: The results show that home environment was the variable with greater influence on neurodevelopment at 18 months, and the observation of how parents and children interact in the home context is crucial to adequately evaluate early child development.
Abstract: BACKGROUND: The relative role of socioeconomic status (SES), home environment and maternal intelligence, as factors affecting child cognitive development in early childhood is still unclear. The aim of this study is to analyze the association of SES, home environment and maternal IQ with child neurodevelopment at 18 months. METHODS: The data were collected prospectively in the PHIME study, a newborn cohort study carried out in Italy between 2007 and 2010. Maternal nonverbal abilities (IQ) were evaluated using the Standard Progressive Matrices, a version of the Raven's Progressive Matrices; a direct evaluation of the home environment was carried out with the AIRE instrument, designed using the HOME (Home Observation for Measurement of the Environment) model; the socioeconomic characteristics were evaluated using the SES index which takes into account parents occupation, type of employment, educational level, homeownership. The study outcome was child neurodevelopment evaluated at 18 months, with the Bayley Scales of Infant and Toddler Development Third Edition (BSID III). Linear regression analyses and mediation analyses were carried out to evaluate the association between the three exposures, and the scaled scores of the three main scales of BSID III (cognitive, language and motor scale), with adjustment for a wide range of potential explanatory variables. RESULTS: Data from 502 mother-child pairs were analyzed. Mediation analysis showed a relationship between SES and maternal IQ, with a complete mediation effect of home environment in affecting cognitive and language domains. A direct significant effect of maternal IQ on the BSID III motor development scale and the mediation effect of home environment were found. CONCLUSIONS: Our results show that home environment was the variable with greater influence on neurodevelopment at 18 months. The observation of how parents and children interact in the home context is crucial to adequately evaluate early child development. Language: en

121 citations


01 Jan 2015
TL;DR: The Global Burden of Disease Study 2013 (GBD 2013) aims to bring together all available epidemiological data using a coherent measurement framework, standardised estimation methods, and transparent data sources to enable comparisons of health loss over time and across causes, age-sex groups, and countries as discussed by the authors.
Abstract: Background The Global Burden of Disease Study 2013 (GBD 2013) aims to bring together all available epidemiological data using a coherent measurement framework, standardised estimation methods, and transparent data sources to enable comparisons of health loss over time and across causes, age–sex groups, and countries. The GBD can be used to generate summary measures such as disability-adjusted life-years (DALYs) and healthy life expectancy (HALE) that make possible comparative assessments of broad epidemiological patterns across countries and time. These summary measures can also be used to quantify the component of variation in epidemiology that is related to sociodemographic development. Methods We used the published GBD 2013 data for age-specific mortality, years of life lost due to premature mortality (YLLs), and years lived with disability (YLDs) to calculate DALYs and HALE for 1990, 1995, 2000, 2005, 2010, and 2013 for 188 countries. We calculated HALE using the Sullivan method; 95% uncertainty intervals (UIs) represent uncertainty in age-specific death rates and YLDs per person for each country, age, sex, and year. We estimated DALYs for 306 causes for each country as the sum of YLLs and YLDs; 95% UIs represent uncertainty in YLL and YLD rates. We quantified patterns of the epidemiological transition with a composite indicator of sociodemographic status, which we constructed from income per person, average years of schooling after age 15 years, and the total fertility rate and mean age of the population. We applied hierarchical regression to DALY rates by cause across countries to decompose variance related to the sociodemographic status variable, country, and time. Findings Worldwide, from 1990 to 2013, life expectancy at birth rose by 6·2 years (95% UI 5·6–6·6), from 65·3 years (65·0–65·6) in 1990 to 71·5 years (71·0–71·9) in 2013, HALE at birth rose by 5·4 years (4·9–5·8), from 56·9 years (54·5–59·1) to 62·3 years (59·7–64·8), total DALYs fell by 3·6% (0·3–7·4), and age-standardised DALY rates per 100 000 people fell by 26·7% (24·6–29·1). For communicable, maternal, neonatal, and nutritional disorders, global DALY numbers, crude rates, and age-standardised rates have all declined between 1990 and 2013, whereas for non–communicable diseases, global DALYs have been increasing, DALY rates have remained nearly constant, and age-standardised DALY rates declined during the same period. From 2005 to 2013, the number of DALYs increased for most specific non-communicable diseases, including cardiovascular diseases and neoplasms, in addition to dengue, food-borne trematodes, and leishmaniasis; DALYs decreased for nearly all other causes. By 2013, the five leading causes of DALYs were ischaemic heart disease, lower respiratory infections, cerebrovascular disease, low back and neck pain, and road injuries. Sociodemographic status explained more than 50% of the variance between countries and over time for diarrhoea, lower respiratory infections, and other common infectious diseases; maternal disorders; neonatal disorders; nutritional deficiencies; other communicable, maternal, neonatal, and nutritional diseases; musculoskeletal disorders; and other non-communicable diseases. However, sociodemographic status explained less than 10% of the variance in DALY rates for cardiovascular diseases; chronic respiratory diseases; cirrhosis; diabetes, urogenital, blood, and endocrine diseases; unintentional injuries; and self-harm and interpersonal violence. Predictably, increased sociodemographic status was associated with a shift in burden from YLLs to YLDs, driven by declines in YLLs and increases in YLDs from musculoskeletal disorders, neurological disorders, and mental and substance use disorders. In most country-specific estimates, the increase in life expectancy was greater than that in HALE. Leading causes of DALYs are highly variable across countries. Interpretation Global health is improving. Population growth and ageing have driven up numbers of DALYs, but crude rates have remained relatively constant, showing that progress in health does not mean fewer demands on health systems. The notion of an epidemiological transition—in which increasing sociodemographic status brings structured change in disease burden—is useful, but there is tremendous variation in burden of disease that is not associated with sociodemographic status. This further underscores the need for country-specific assessments of DALYs and HALE to appropriately inform health policy decisions and attendant actions.

86 citations


01 Dec 2015
TL;DR: The Global Burden of Disease, Injuries, and Risk Factor study 2013 (GBD 2013) as mentioned in this paper provides a timely opportunity to update the comparative risk assessment with new data for exposure, relative risks, and evidence on the appropriate counterfactual risk distribution.
Abstract: Background The Global Burden of Disease, Injuries, and Risk Factor study 2013 (GBD 2013) is the first of a series of annual updates of the GBD. Risk factor quantification, particularly of modifiable risk factors, can help to identify emerging threats to population health and opportunities for prevention. The GBD 2013 provides a timely opportunity to update the comparative risk assessment with new data for exposure, relative risks, and evidence on the appropriate counterfactual risk distribution. Methods Attributable deaths, years of life lost, years lived with disability, and disability-adjusted life-years (DALYs) have been estimated for 79 risks or clusters of risks using the GBD 2010 methods. Risk–outcome pairs meeting explicit evidence criteria were assessed for 188 countries for the period 1990–2013 by age and sex using three inputs: risk exposure, relative risks, and the theoretical minimum risk exposure level (TMREL). Risks are organised into a hierarchy with blocks of behavioural, environmental and occupational, and metabolic risks at the first level of the hierarchy. The next level in the hierarchy includes nine clusters of related risks and two individual risks, with more detail provided at levels 3 and 4 of the hierarchy. Compared with GBD 2010, six new risk factors have been added: handwashing practices, occupational exposure to trichloroethylene, childhood wasting, childhood stunting, unsafe sex, and low glomerular filtration rate. For most risks, data for exposure were synthesised with a Bayesian meta-regression method, DisMod-MR 2.0, or spatial-temporal Gaussian process regression. Relative risks were based on meta-regressions of published cohort and intervention studies. Attributable burden for clusters of risks and all risks combined took into account evidence on the mediation of some risks such as high body-mass index (BMI) through other risks such as high systolic blood pressure and high cholesterol. Findings All risks combined account for 57·2% (95% uncertainty interval [UI] 55·8–58·5) of deaths and 41·6% (40·1–43·0) of DALYs. Risks quantified account for 87·9% (86·5–89·3) of cardiovascular disease DALYs, ranging to a low of 0% for neonatal disorders and neglected tropical diseases and malaria. In terms of global DALYs in 2013, six risks or clusters of risks each caused more than 5% of DALYs: dietary risks accounting for 11·3 million deaths and 241·4 million DALYs, high systolic blood pressure for 10·4 million deaths and 208·1 million DALYs, child and maternal malnutrition for 1·7 million deaths and 176·9 million DALYs, tobacco smoke for 6·1 million deaths and 143·5 million DALYs, air pollution for 5·5 million deaths and 141·5 million DALYs, and high BMI for 4·4 million deaths and 134·0 million DALYs. Risk factor patterns vary across regions and countries and with time. In sub-Saharan Africa, the leading risk factors are child and maternal malnutrition, unsafe sex, and unsafe water, sanitation, and handwashing. In women, in nearly all countries in the Americas, north Africa, and the Middle East, and in many other high-income countries, high BMI is the leading risk factor, with high systolic blood pressure as the leading risk in most of Central and Eastern Europe and south and east Asia. For men, high systolic blood pressure or tobacco use are the leading risks in nearly all high-income countries, in north Africa and the Middle East, Europe, and Asia. For men and women, unsafe sex is the leading risk in a corridor from Kenya to South Africa. Interpretation Behavioural, environmental and occupational, and metabolic risks can explain half of global mortality and more than one-third of global DALYs providing many opportunities for prevention. Of the larger risks, the attributable burden of high BMI has increased in the past 23 years. In view of the prominence of behavioural risk factors, behavioural and social science research on interventions for these risks should be strengthened. Many prevention and primary care policy options are available now to act on key risks.

54 citations


Journal ArticleDOI
TL;DR: A flushing procedure with one flush per day allows maintenance of catheter patency without an increase in catheter-related complications and is proposed to reduce costs, labour and unnecessary manipulation of the catheters which can cause distress in younger children and their parents.
Abstract: Objective Recent evidence supports the use of normal saline flushes in place of heparin to maintain the patency of peripheral intravenous locks (IVLs); however, there are no data regarding the recommended flush frequency. Study design This was an open, non-inferiority, randomised controlled trial. Children with IVLs, aged 1–17 years, were randomly assigned to receive saline flushing every 12 h (group A) or every 24 h (group B). The main outcome was the maintenance of catheter patency. Results Four hundred patients were randomised; 198 subjects were analysed in the 12 h group and 199 in the 24 h group (three patients were lost at follow-up). Occlusion occurred in 15 children (7.6%) in group A versus 9 (4.5%) in group B (p=0.21). The difference in catheter patency was +3.1% in favour of the 24 h group (95% CI −1.6% to 7.7%), showing the non-inferiority of the 24 h procedure (the non-inferiority margin was set at −4%). Catheter-related complications were not different between the two groups (12.1% in group A vs 9.5% in group B; p=0.42). Conclusions A flushing procedure with one flush per day allows maintenance of catheter patency without an increase in catheter-related complications. We propose a simplification of the flushing procedure with only one flush per day, thereby reducing costs (materials use and nursing time), labour and unnecessary manipulation of the catheters which can cause distress in younger children and their parents. Trial registration number The study is registered in the international database ClinicalTrial.gov under registration number NCT02221024.

16 citations


Journal ArticleDOI
TL;DR: Both higher and lower-than-expected rates of CD and “above” AVD rates are significantly associated with increased risk of complications, whereas the “below” status for AVD showed a “protective” effect on maternal and neonatal outcomes.
Abstract: Although the evaluation of caesarean delivery rates has been suggested as one of the most important indicators of quality in obstetrics, it has been criticized because of its controversial ability to capture maternal and neonatal outcomes. In an “ideal” process of labor and delivery auditing, both caesarean (CD) and assisted vaginal delivery (AVD) rates should be considered because both of them may be associated with an increased risk of complications. The aim of our study was to evaluate maternal and neonatal outcomes according to the outlier status for case-mix adjusted CD and AVD rates in the same obstetric population. Standardized data on 15,189 deliveries from 11 centers were prospectively collected. Multiple logistic regression was used to estimate the risk-adjusted probability of a woman in each center having an AVD or a CD. Centers were classified as “above”, “below”, or “within” the expected rates by considering the observed-to-expected rates and the 95% confidence interval around the ratio. Adjusted maternal and neonatal outcomes were compared among the three groupings. Centers classified as “above” or “below” the expected CD rates had, in both cases, higher adjusted incidence of composite maternal (2.97%, 4.69%, 3.90% for “within”, “above” and “below”, respectively; p = 0.000) and neonatal complications (3.85%, 9.66%, 6.29% for “within”, “above” and “below”, respectively; p = 0.000) than centers “within” CD expected rates. Centers with AVD rates above and below the expected showed poorer and better composite maternal (3.96%, 4.61%, 2.97% for “within”, “above” and “below”, respectively; p = 0.000) and neonatal (6.52%, 9.77%, 3.52% for “within”, “above” and “below”, respectively; p = 0.000) outcomes respectively than centers with “within” AVD rates. Both risk-adjusted CD and AVD delivery rates should be considered to assess the level of obstetric care. In this context, both higher and lower-than-expected rates of CD and “above” AVD rates are significantly associated with increased risk of complications, whereas the “below” status for AVD showed a “protective” effect on maternal and neonatal outcomes.