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15. Role of Dentistry in Global Health: Challenges and Research Priorities.

Author

Hugo, F.N., Kassebaum, N.J., Marcenes, W., and Bernabé, E.

Subjects
WORLD health, DENTISTRY, POOR people, ORAL hygiene, POPULATION health
Abstract

Despite some improvements in the oral health of populations globally, major problems remain all over the planet, most notably among underprivileged communities of low- and middle-income countries but also in high-income countries. Furthermore, essential oral health care has been a privilege, instead of a right, for most individuals. The release of the Lancet issue on oral health in July 2019 built up some momentum and put oral conditions and dental services in the limelight. Yet, much work is still needed to bridge the gap between dental research and global health and get oral health recognized as a population health priority worldwide. Using the framework proposed by Shiffman, we argue that a global health network for oral health must be harnessed to influence global health policy and drive health system reform. We have identified challenges around 4 key areas (problem definition, positioning, coalition building, and governance) from our experience working in the global health arena and with collaborators in multidisciplinary teams. These challenges are outlined here to validate them externally but also to call the attention of interested players inside and outside dentistry. How well our profession addresses these challenges will shape our performance during the Sustainable Development Goals era and beyond. This analysis is followed by a discussion of fundamental gaps in knowledge, particularly in 3 areas of oral health action: 1) epidemiology and health information systems; 2) collection, harmonization, and rigorous assessment of evidence for prevention, equity, and treatment; and 3) optimal strategies for delivering essential quality care to all who need it without financial hardship. [ABSTRACT FROM AUTHOR]

Published
2021
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16. Global, regional, and national cancer incidence, mortality, years of life lost, years lived with disability, and disability-adjusted life-years for 32 cancer groups, 1990 to 2015: A Systematic Analysis for the Global Burden of Disease Study Global Burden of Disease Cancer Collaboration

Author

Fitzmaurice, C., Pourmalek, F., Lunevicius, R., Campos-Nonato, I., Khang, Y.-H., Jee, S.H., Rana, S.M., Sufiyan, M.B., Kedir, M.S., Khader, Y.S., Marcenes, W., Meles, K.G., Bensenor, I., Ding, E., Cowie, B., Leigh, J., Zaidi, Z., Melaku, Y.A., Sanabria, J.R., Oladimeji, K.E., James, S., Al-Raddadi, R., Kutz, M., Sartorius, B., Saleem, H.B., Global Burden of Disease Cancer Collaboration, Das Neves, J., Dicker, D.J., Husseini, A., Schwartz, S.M., Søreide, K., Ghiwot, T.T., Nagel, G., Nolte, S., Hailu, A., Pa, M., Wang, H., Kasaeian, A., Alabed, S., Zenebe, Z.M., Fernandes, J., Nand, D., Javanbakht, M., Weiderpass, E., Plass, D., Fleming, T., Oren, E., Sepanlou, S.G., Thakur, J.S., Linn, S., Yonemoto, N., Hay, R.J., Bedi, N., Ukwaja, K.N., Chimed-Orchir, O., Brenner, H., Sandar, L., Dhillon, P., Mohammadi, A., Shiue, I., Zeeb, H., Allen, C., Sykes, B.L., Tadese, F., Ahmed, M.B., Ali, R., Alem, G., Malta, D.C., Lan, Q., Westerman, R., Boneya, D., Wagner, J.A., Amoako, Y., Marquez, N., Larson, H.J., Khubchandani, J., Tessema, G.A., Alemayohu, M.A., Ekwueme, D., Chiang, P., Vollset, S.E., Asayesh, H., Fischer, F., Shore, H.R., Naghavi, M., Hancock, J., Catalá-López, F., Stroumpoulis, K., Barber, R.M., Satpathy, M., Zaki, M.E.S., Atnafu, N., Farvid, M., Shaikh, M.A., Zoeckler, L., Liang, X., Yebyo, H.G., Lim, S.S., Chudi Uzochukwu, B.S., Dharmaratne, S., Castañeda-Orjuela, C., Takahashi, K., Sawhney, M., Abd-Allah, F., Shackelford, K.A., Malekzadeh, R., Steiner, C., Driscoll, T., Hosgood, H.D., Dandona, R., Lopez, A.D., Shrime, M.G., Yu, C., Aldhahri, S.F., Sun, J., Qorbani, M., Vlassov, V.V., Chibueze, C., Huynh, C., Horino, M., Yimam, H.H., Stanaway, J., Ogbo, F.A., Dandona, L., El Razek, H.M.A., Huybrechts, I., Pereira, D.M., Younis, M.Z., Pinho, C., Damtew, S., Salomon, J.A., Bernabé, E., Berhane, A., Forouzanfar, M.H., Awasthi, A., Gopalani, S., Murray, C.J.L., Jakovljevic, M., She, J., Horita, N., MacIntyre, M.F., Stathopoulou, V., Barregard, L., Betsu, B., Dey, S., Bhutta, Z.A., Endries, A.Y., Shibuya, K., Tran, B.X., Mohammad, K.A., Barac, A., Miller, T.R., Radfar, A., Gebru, A., Islami, F., Chitheer, A., Kumar, G.A., Rahman, M., Markos, D., Park, E.-K., Moradi-Lakeh, M., Mohammed, S., Soneji, S., Mendoza, W., Amare, A., Tedla, B.A., Wubshet Terefe, M., Farzadfar, F., Vos, T., Artaman, A., So, S., Mengiste, D.T., Le Nguyen, Q., Choi, J.-Y., Binagwaho, A., Rafay, A., Mokdad, A.H., Kim, D., Marczak, L., Johnson, C.O., Alam, N.K., Meretoja, T.J., Inoue, M., Hunter-Merrill, R., Jonas, J.B., and Tabarés-Seisdedos, R.

Abstract

IMPORTANCE: Cancer is the second leading cause of death worldwide. Current estimates on the burden of cancer are needed for cancer control planning. OBJECTIVE: To estimate mortality, incidence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs) for 32 cancers in 195 countries and territories from 1990 to 2015. EVIDENCE REVIEW: Cancer mortality was estimated using vital registration system data, cancer registry incidence data (transformed to mortality estimates using separately estimated mortality to incidence [MI] ratios), and verbal autopsy data. Cancer incidence was calculated by dividing mortality estimates through the modeled MI ratios. To calculate cancer prevalence, MI ratios were used to model survival. To calculate YLDs, prevalence estimates were multiplied by disability weights. The YLLs were estimated by multiplying age-specific cancer deaths by the reference life expectancy. DALYs were estimated as the sum of YLDs and YLLs. A sociodemographic index (SDI) was created for each location based on income per capita, educational attainment, and fertility. Countries were categorized by SDI quintiles to summarize results. FINDINGS: In 2015, there were 17.5 million cancer cases worldwide and 8.7 million deaths. Between 2005 and 2015, cancer cases increased by 33%, with population aging contributing 16%, population growth 13%, and changes in age-specific rates contributing 4%. For men, the most common cancer globally was prostate cancer (1.6 million cases). Tracheal, bronchus, and lung cancer was the leading cause of cancer deaths and DALYs in men (1.2 million deaths and 25.9 million DALYs). For women, the most common cancer was breast cancer (2.4 million cases). Breast cancer was also the leading cause of cancer deaths and DALYs for women (523 000 deaths and 15.1 million DALYs). Overall, cancer caused 208.3 million DALYs worldwide in 2015 for both sexes combined. Between 2005 and 2015, age-standardized incidence rates for all cancers combined increased in 174 of 195 countries or territories. Age-standardized death rates (ASDRs) for all cancers combined decreased within that timeframe in 140 of 195 countries or territories. Countries with an increase in the ASDR due to all cancers were largely located on the African continent. Of all cancers, deaths between 2005 and 2015 decreased significantly for Hodgkin lymphoma (-6.1% [95% uncertainty interval (UI), -10.6% to -1.3%]). The number of deaths also decreased for esophageal cancer, stomach cancer, and chronic myeloid leukemia, although these results were not statistically significant. CONCLUSION AND RELEVANCE: As part of the epidemiological transition, cancer incidence is expected to increase in the future, further straining limited health care resources. Appropriate allocation of resources for cancer prevention, early diagnosis, and curative and palliative care requires detailed knowledge of the local burden of cancer. The GBD 2015 study results demonstrate that progress is possible in the war against cancer. However, the major findings also highlight an unmet need for cancer prevention efforts, including tobacco control, vaccination, and the promotion of physical activity and a healthy diet.

Published
2017
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17. Early Introduction of Sugar-Sweetened Beverages and Caries Trajectories from Age 12 to 48 Months.

Author

Bernabé, E., Ballantyne, H., Longbottom, C., and Pitts, N.B.

Subjects
SOFT drinks, DENTAL caries in children, PRESCHOOL children, CHILDHOOD obesity, SCOTS
Abstract

Early exposure to sweet tastes predicts similar food preferences and eating behavior in later life and is associated with childhood obesity. The aim of this study was to explore the associations of early (during the first year of life) and subsequent intake of sugar-sweetened beverages (SSBs) with 4-y caries trajectories among Scottish young children. We used data from 1,111 Scottish children who were followed annually from age 12 to 48 mo (4 sweeps in total). SSB intake was reported by parents in every sweep. SSB intake was broken down into 2 components, the initial SSB intake and the deviation over time from that initial value. Childhood dental caries was clinically determined (including noncavitated and cavitated lesions) every year. The association of SSB intake with baseline decayed, missing, and filled tooth surfaces (dmfs) (intercept) and rate of change in dmfs over time (slope) was examined in 2-level linear mixed-effects models, with repeated observations nested within children. Both the initial SSB intake and the deviation from the initial SSB intake were positively associated with steeper caries trajectories. By sweep 4, the predicted mean dmfs difference was 1.73 between children with low and high initial SSB intake (1 standard deviation below and above the mean) and 1.17 between children with low and high deviation from their initial SSB intake (1 SD below and above the mean). The findings of this prospective study among Scottish young children provide evidence that the introduction of SSBs during the first year of life can put children in a trajectory of high levels of dental caries. They support current recommendations to avoid sugars for very young children and interventions targeting early feeding practices for caries prevention. [ABSTRACT FROM AUTHOR]

Published
2020
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18. Comparing lifecourse models of social class and adult oral health using the 1958 national child development study

Author

Delgado-Angulo, E.K. and Bernabé, E.

Subjects
Adult, Male, Oral health, Adolescent, Health Status, purl.org/pe-repo/ocde/ford#3.02.14 [https], Social class, United Kingdom, Social Mobility, Cohort Studies, Young Adult, female, Socioeconomic Factors, classification, gingival diseases, Humans, Health Status Indicators, Longitudinal Studies, Lifecourse models, Mouth Diseases, Child, comparative study
Abstract

Objective: To identify the lifecourse model that best describes the association between social class and adult oral health. Methods: Data from 10,217 participants of the 1958 National Child Development Study were used. Social class at ages 7, 16 and 33 years were chosen to represent socioeconomic conditions during childhood, adolescence and adulthood, respectively. Two subjective oral health indicators (lifetime and past-year prevalence of persistent trouble with gums or mouth) were measured at age 33. The critical period, accumulation and social trajectories models were tested in logistic regression models and the most appropriate lifecourse model was identified using the structured modelling approach. Results: The critical period model showed that only adulthood social class was significantly associated with oral health. For the accumulation model, a monotonic gradient was found between the number of periods in manual social class and oral health; and four out of eight social trajectories were found to be distinctive. Finally, the social trajectories model was not significantly different from the saturated model indicating that it provided a good fit to the data. Conclusion: This study shows the social trajectories model was the most appropriate, in terms of model fit, to describe the association between social class and oral health.

Published
2015

19. Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990-2010 : a systematic analysis for the global burden of disease study 2010

Author

Vos, T., Flaxman, A.D., Naghavi, M., Lozano, R., Michaud, C., Ezzati, M., Shibuya, K., Salomon, J. A., Abdalla, S., Aboyans, V., Abraham, J., Ackerman, I., Aggarwal, R., Ahn, S., Ali, M.K., Alvarado, M., Ross Anderson, H., Anderson, L.M., Andrews, K.G., Atkinson, C., Baddour, L.M., Bahalim, A.N., Barker Collo, S., Barrero, L.H., Bartels, D.H., Basanez, M.G., Baxter, A., Bell, M.L., Benjamin, E.J., Bennett, D., Bernabé, E., Bhalla, K., Bhandari, B., Bikbov, B., Abulhak, A.B., Birbeck, G., Black, J.A., Blencowe, H., Blore, J.D., Blyth, F., Bolliger, I., Bonaventure, A., Boufous, S., Bourne, R., and Boussinesq, Michel

Subjects
SEXE, MALADIE, ENQUETE, GROUPE D'AGE, INVALIDITE, SANTE PUBLIQUE, MORBIDITE, REPARTITION GEOGRAPHIQUE, MODELISATION, VARIATION PLURIANNUELLE, PREVALENCE
Published
2012

21. Global, Regional, and National Prevalence, Incidence, and Disability-Adjusted Life Years for Oral Conditions for 195 Countries, 1990-2015: A Systematic Analysis for the Global Burden of Diseases, Injuries, and Risk Factors.

Author

Kassebaum, N. J., Smith, A. G. C., Bernabé, E., Fleming, T. D., Reynolds, A. E., Vos, T., Murray, C. J. L., Marcenes, W., and GBD 2015 Oral Health Collaborators

Subjects
ORAL diseases, LIFE expectancy, HEALTH of people with disabilities, INTERNATIONAL cooperation on public health, PATIENTS, PREVENTION, AGE distribution, ECONOMIC aspects of diseases, WORLD health, DISEASE incidence, DISEASE prevalence, QUALITY-adjusted life years, STOMATOGNATHIC system diseases
Abstract

The Global Burden of Disease 2015 study aims to use all available data of sufficient quality to generate reliable and valid prevalence, incidence, and disability-adjusted life year (DALY) estimates of oral conditions for the period of 1990 to 2015. Since death as a direct result of oral diseases is rare, DALY estimates were based on years lived with disability, which are estimated only on those persons with unmet need for dental care. We used our data to assess progress toward the Federation Dental International, World Health Organization, and International Association for Dental Research's oral health goals of reducing the level of oral diseases and minimizing their impact by 2020. Oral health has not improved in the last 25 y, and oral conditions remained a major public health challenge all over the world in 2015. Due to demographic changes, including population growth and aging, the cumulative burden of oral conditions dramatically increased between 1990 and 2015. The number of people with untreated oral conditions rose from 2.5 billion in 1990 to 3.5 billion in 2015, with a 64% increase in DALYs due to oral conditions throughout the world. Clearly, oral diseases are highly prevalent in the globe, posing a very serious public health challenge to policy makers. Greater efforts and potentially different approaches are needed if the oral health goal of reducing the level of oral diseases and minimizing their impact is to be achieved by 2020. Despite some challenges with current measurement methodologies for oral diseases, measurable specific oral health goals should be developed to advance global public health. [ABSTRACT FROM AUTHOR]

Published
2017
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22. Birth Weight, Breastfeeding, Maternal Smoking and Caries Trajectories.

Author

Bernabé, E., MacRitchie, H., Longbottom, C., Pitts, N. B., and Sabbah, W.

Subjects
DENTAL caries in children, BIRTH weight, BREASTFEEDING, WOMEN'S tobacco use, CROSS-sectional method, LONGITUDINAL method, DECIDUOUS teeth, CHILDREN
Abstract

Evidence for the effects of low birth weight, breastfeeding and maternal smoking on childhood caries is mainly cross-sectional. We examined the association of these 3 putative early life factors with caries increment over a 4-y period among young children. We used data from a 4-y longitudinal caries-risk assessment study carried out among Scottish children. Early life factors were measured when children were aged 1 y (baseline). Caries assessment was repeated annually from ages 1 to 4, and the number of decayed, missing and filled primary tooth surfaces (dmfs) were used as a repeated outcome measure. The associations of low birth weight, breastfeeding and maternal smoking with dmfs at baseline and over time (trajectories) were assessed in linear mixed models. A total of 1,102 children were included in this analysis. Birth weight, breastfeeding and maternal smoking were not associated with dmfs at baseline. However, low birth weight and maternal smoking were associated with the rate of change in dmfs. By wave 4, the predicted mean difference in dmfs was 1.86 between children with low and normal birth weight, and 1.66 between children of smoking and non-smoking mothers. Children with low birth weight and smoking mothers had greater caries increments than those with normal weight and non-smoking mothers, respectively. There was no association between breastfeeding duration and childhood caries, either at baseline or over time. [ABSTRACT FROM AUTHOR]

Published
2017
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23. Are the lower incisors the best predictors for unerupted cuspid and bicuspids sums?:An analysis of a Peruvian sample

Author

Bernabé, E and Flores-Mir, C

Subjects
stomatognathic system
Abstract

The lower permanent incisor tooth width sum has been proposed as the best predictor for the tooth width sums of the unerupted canine and premolars (SPCP) for populations from different ethnic origins. Only two previous studies have refuted it. The purpose of the present study was to determine which sum or combination of sums of permanent tooth widths presented the best prediction capability for the SPCP in a Peruvian sample, to calculate a specific linear regression equation for this population, and to evaluate the clinical significance. A total of 150 children with complete permanent dentitions were selected. Fifty more children were used as a validation sample for the application of a multiple linear regression equation (MLRE). They did not present clinically visible dental caries or proximal restorations and no active or previous orthodontic treatment. Their dental casts were measured to 0.1 mm with a sliding caliper with a Vernier scale. Three-way analysis of variance, Pearson Correlation Test, Fisher Z values and a MLRE were used for the statistical analysis. The combination of the sums of permanent upper and lower central incisors and upper first molars was the best predictor for the SPCP in this sample. A MLRE was calculated including sex and arch as additional predictor variables. The MLRE determination coefficient was 60% with a standard error of 0.8 mm. This new MLRE underestimates (less than 1 mm discrepancy) the actual SPCP in only 7% of the cases on the basis of a validation sample. (Angle Orthod 2005;75: 202–207.)

Published
2005

24. Tooth width ratios in crowded and non-crowded dentitions

Author

Bernabé, E, Villanueva, KM, and Flores-Mir, C

Subjects
stomatognathic diseases, stomatognathic system
Abstract

Discrepancies in tooth width ratios could affect the excellence in the finishing of orthodontic cases. This study compares tooth width ratios in crowded and noncrowded dental arches. Tooth widths were measured from 143 dental casts (40 crowded and 33 spaced in male individuals and 43 crowded and 27 spaced in female individuals). Simultaneous crowded or spaced arches were selected. Tooth width measurements were made with a sliding caliper with a Vernier scale neared 0.1 mm. Inter- (0.990) and intraexaminer (0.993) reliability with mean differences of 0.03 mm (−0.03; 0.07) and 0.01 mm (−0.04; 0.05), respectively, were attained. Bolton analysis was applied to calculate the tooth width ratios (anterior and total). Descriptive statistics, Student's t-test, and analysis of variance were applied. There was no significant difference between the anterior and total tooth width ratios according to sex (P > .05). Both anterior and total ratios were significantly greater in subjects with crowding (P = .003 and P = .026, respectively), but no statistical difference by arch type in anterior and total tooth mass excess was found (P > .05). Differences among subjects with noncrowded and crowded dentitions were of 0.39 and 0.51 mm for the excess of anterior and total upper tooth mass, respectively, with respect to lower mass excess. Although the anterior and overall ratios and the differences between the upper and lower tooth width sums are greater in subjects with crowding, no clinically significant difference is observed (less than one mm).

Published
2004

25. The Shape of the Dose-Response Relationship between Sugars and Caries in Adults.

Author

Bernabé, E., Vehkalahti, M. M., Sheiham, A., Lundqvist, A., and Suominen, A. L.

Subjects
DOSE-response relationship in biochemistry, DENTAL caries, SUGAR, LONGITUDINAL method, DENTAL fluoride treatment, TOOTHPASTE, QUESTIONNAIRES, REPEATED measures design, PSYCHOLOGY, DENTIFRICES, CARIOSTATIC agents, DENTAL care, DOSE-effect relationship in pharmacology, CARBOHYDRATE content of food, FOOD habits, SOCIAL classes, TOOTH care & hygiene, EDUCATIONAL attainment, THERAPEUTICS
Abstract

Dental caries is considered a diet-mediated disease, as sugars are essential in the caries process. However, some gaps in knowledge about the sugars-caries relationship still need addressing. This longitudinal study aimed to explore 1) the shape of the dose-response association between sugars intake and caries in adults, 2) the relative contribution of frequency and amount of sugars intake to caries levels, and 3) whether the association between sugars intake and caries varies by exposure to fluoride toothpaste. We used data from 1,702 dentate adults who participated in at least 2 of 3 surveys in Finland (Health 2000, 2004/05 Follow-up Study of Adults' Oral Health, and Health 2011). Frequency and amount of sugars intake were measured with a validated food frequency questionnaire. The DMFT index was the repeated outcome measure. Data were analyzed with fractional polynomials and linear mixed effects models. None of the 43 fractional polynomials tested provided a better fit to the data than the simpler linear model. In a mutually adjusted linear mixed effects model, the amount of, but not the frequency of, sugars intake was significantly associated with DMFT throughout the follow-up period. Furthermore, the longitudinal association between amount of sugars intake and DMFT was weaker in adults who used fluoride toothpaste daily than in those using it less often than daily. The findings of this longitudinal study among Finnish adults suggest a linear dose-response relationship between sugars and caries, with amount of intake being more important than frequency of ingestion. Also, daily use of fluoride toothpaste reduced but did not eliminate the association between amount of sugars intake and dental caries. [ABSTRACT FROM AUTHOR]

Published
2016
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26. Ethnic Disparities in Oral Health Related Quality of Life among Adults in London, England.

Author

Abdelrahim, R., Delgado-Angulo, E. K., Gallagher, J. E., and Bernabé, E.

Abstract

Objective: To explore ethnic disparities in oral health related quality of life (OHQoL) among adults, and the role that socioeconomic factors play in that association. Research design: Data from 705 adults from a socially deprived, ethnically diverse metropolitan area of London (England) were analysed for this study. Ethnicity was self-assigned based on the 2001 UK Census categories. OHQoL was measured using the Oral Health Impact Profile (OHIP-14), which provides information on the prevalence, extent and intensity of oral impacts on quality of life in the previous 12 months. Ethnic disparities were assessed in logistic regression models for prevalence of oral impacts and negative binomial regression models for extent and intensity of oral impacts. Results: The prevalence of oral impacts was 12.7% (95% CI: 10.2-15.1) and the mean OHIP-14 extent and severity scores were 0.27 (95% CI: 0.20-0.34) and 4.19 (95% CI: 3.74-4.64), respectively. Black adults showed greater and Asian adults lower prevalence, extent and severity of oral impacts than White adults. However, significant differences were only found for the extent of oral impacts; Black adults reporting more and Asian adults fewer OHIP-14 items affected than their White counterparts. After adjustments for socioeconomic factors, Asian adults had significantly fewer OHIP-14 items affected than White adults (rate ratio: 0.28; 95%CI: 0.08-0.94). Conclusion: This study found disparities in OHQoL between the three main ethnic groups in South East London. Asian adults had better and Black adults had similar OHQoL than White adults after accounting for demographic and social factors. [ABSTRACT FROM AUTHOR]

Published
2017
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30. Global Burden of Untreated Caries: A Systematic Review and Metaregression.

Author

Kassebaum, N.J., Bernabé, E., Dahiya, M., Bhandari, B., Murray, C.J.L., and Marcenes, W.

Subjects
DENTAL caries, SYSTEMATIC reviews, TOOTH root diseases, DISEASE prevalence, TOOTH loss, EPIDEMIOLOGY
Abstract

We aimed to consolidate all epidemiologic data about untreated caries and subsequently generate internally consistent prevalence and incidence estimates for all countries, 20 age groups, and both sexes for 1990 and 2010. The systematic search of the literature yielded 18,311 unique citations. After screening titles and abstracts, we excluded 10,461 citations as clearly irrelevant to this systematic review, leaving 1,682 for full-text review. Furthermore, 1,373 publications were excluded following the validity assessment. Overall, 192 studies of 1,502,260 children aged 1 to 14 y in 74 countries and 186 studies of 3,265,546 individuals aged 5 y or older in 67 countries were included in separate metaregressions for untreated caries in deciduous and permanent teeth, respectively, using modeling resources from the Global Burden of Disease 2010 study. In 2010, untreated caries in permanent teeth was the most prevalent condition worldwide, affecting 2.4 billion people, and untreated caries in deciduous teeth was the 10th-most prevalent condition, affecting 621 million children worldwide. The global age-standardized prevalence and incidence of untreated caries remained static between 1990 and 2010. There is evidence that the burden of untreated caries is shifting from children to adults, with 3 peaks in prevalence at ages 6, 25, and 70 y. Also, there were considerable variations in prevalence and incidence between regions and countries. Policy makers need to be aware of a predictable increasing burden of untreated caries due to population growth and longevity and a significant decrease in the prevalence of total tooth loss throughout the world from 1990 to 2010. [ABSTRACT FROM PUBLISHER]

Published
2015
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31. Global Burden of Severe Periodontitis in 1990-2010: A Systematic Review and Meta-regression.

Author

Kassebaum, N.J., Bernabé, E., Dahiya, M., Bhandari, B., Murray, C.J.L., and Marcenes, W.

Subjects
PERIODONTITIS, PERIODONTAL disease, AGGRESSIVE periodontitis, INFLAMMATION, GINGIVAL diseases, TOOTH mobility, ORAL diseases
Abstract

We aimed to consolidate all epidemiologic data about severe periodontitis (SP) and, subsequently, to generate internally consistent prevalence and incidence estimates for all countries, 20 age groups, and both sexes for 1990 and 2010. The systematic search of the literature yielded 6,394 unique citations. After screening titles and abstracts, we excluded 5,881 citations as clearly not relevant to this systematic review, leaving 513 for full-text review. A further 441 publications were excluded following the validity assessment. A total of 72 studies, including 291,170 individuals aged 15 yr or older in 37 countries, were included in the metaregression based on modeling resources of the Global Burden of Disease 2010 Study. SP was the sixth-most prevalent condition in the world. Between 1990 and 2010, the global age-standardized prevalence of SP was static at 11.2% (95% uncertainty interval: 10.4%-11.9% in 1990 and 10.5%-12.0% in 2010). The age-standardized incidence of SP in 2010 was 701 cases per 100,000 person-years (95% uncertainty interval: 599-823), a nonsignificant increase from the 1990 incidence of SP. Prevalence increased gradually with age, showing a steep increase between the third and fourth decades of life that was driven by a peak in incidence at around 38 yr of age. There were considerable variations in prevalence and incidence between regions and countries. Policy makers need to be aware of a predictable increasing burden of SP due to the growing world population associated with an increasing life expectancy and a significant decrease in the prevalence of total tooth loss throughout the world from 1990 to 2010. [ABSTRACT FROM PUBLISHER]

Published
2014
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32. Influence of Scanner Precision and Analysis Software in Quantifying Three-Dimensional Intraoral Changes: Two-Factor Factorial Experimental Design

Author

O'Toole, Saoirse, Bartlett, David, Keeling, Andrew, McBride, John, Bernabe, Eduardo, Crins, Luuk, and Loomans, Bas

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Public aspects of medicine, RA1-1270
Abstract

BackgroundThree-dimensional scans are increasingly used to quantify biological topographical changes and clinical health outcomes. Traditionally, the use of 3D scans has been limited to specialized centers owing to the high cost of the scanning equipment and the necessity for complex analysis software. Technological advances have made cheaper, more accessible methods of data capture and analysis available in the field of dentistry, potentially facilitating a primary care system to quantify disease progression. However, this system has yet to be compared with previous high-precision methods in university hospital settings. ObjectiveThe aim of this study was to compare a dental primary care method of data capture (intraoral scanner) with a precision hospital-based method (laser profilometer) in addition to comparing open source and commercial software available for data analysis. MethodsLongitudinal dental wear data from 30 patients were analyzed using a two-factor factorial experimental design. Bimaxillary intraoral digital scans (TrueDefinition, 3M, UK) and conventional silicone impressions, poured in type-4 dental stone, were made at both baseline and follow-up appointments (mean 36 months, SD 10.9). Stone models were scanned using precision laser profilometry (Taicaan, Southampton, UK). Three-dimensional changes in both forms of digital scans of the first molars (n=76) were quantitatively analyzed using the engineering software Geomagic Control (3D Systems, Germany) and freeware WearCompare (Leeds Digital Dentistry, UK). Volume change (mm3) was the primary measurement outcome. The maximum point loss (μm) and the average profile loss (μm) were also recorded. Data were paired and skewed, and were therefore compared using Wilcoxon signed-rank tests with Bonferroni correction. ResultsThe median (IQR) volume change for Geomagic using profilometry and using the intraoral scan was –0.37 mm3 (–3.75-2.30) and +0.51 mm3 (–2.17-4.26), respectively (P

Published
2020
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33. Attitudes and practices regarding preventive dentistry among Libyan dentists.

Author

Arheiam, A. and Bernabé, E.

Abstract

Purpose: To assess the attitudes towards and practices related to preventive dentistry among Libyan dentists. Methods: A cross-sectional, questionnaire-based survey was conducted among dentists working in Benghazi. All dentists registered with the Dental Association of Benghazi and with two or more years of practice were invited to participate. The questionnaire enquired about dentists' demographic (gender and age) and professional characteristics (practice sector and years of service), attitudes towards preventive dentistry using nine semantic differential scales and the frequency with which they performed eight preventive measures to patients. Non-parametric tests were used to compare attitudes towards and practices related to preventive dentistry by participants' demographic and professional characteristics. Results: Of the 175 dentists returning questionnaires (response rate 79%), 166 had complete information on all the variables needed for analysis (75%). Dentists felt preventive dentistry was useful and essential to the community as well as of scientific merit for dentists. As for practices, oral hygiene instruction and recommending fluoridated toothpaste were the most commonly reported preventive measures performed by dentists whereas the application of topical fluoride and fissure sealants were the least reported. Attitudes towards and practices related to preventive dentistry varied by professional but not demographic characteristics. Conclusion: Dentists showed a generally positive attitude towards preventive dentistry. However, certain preventive measures, particularly those that incur costs, were less frequently practised. [ABSTRACT FROM AUTHOR]

Published
2015
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34. Relationship between family characteristics and children's regular toothbrushing with fluoride toothpaste.

Author

Kino, S., Bernabé, E., Sabbah, W., and Aukett, J.

Abstract

Objective: To examine the association between toothbrushing habits of 8-9 year-olds and maternal behaviours and attitudes towards oral health in a sample of Japanese population. Methods: Cross-sectional data on mothers' behaviours and attitudes towards oral health and children's toothbrushing habits were collected from 378 mother-child pairs by self-administered questionnaires. Logistic regression examined the association of children's daily brushing with fluoride toothpaste with family characteristics, mother's behaviour (toothbrushing frequency, use of interdental aids and supervision of children's toothbrushing), and mother's attitudes towards oral health (priority for toothbrushing and dental fear). Results: Children's favourable brushing habits were positively associated with child's gender (female) (OR 1.29; 95%CI: 1.09,1.53), child's order of birth (first) (OR 1.53; 95%CI: 1.05,2.23), maternal brushing habits (OR 2.42; 95%CI: 1.73,3.40), and maternal dental fear (OR 1.45; 95%CI: 1.10,1.90). None of the other examined factors were significantly associated with child toothbrushing behaviour. Conclusions: Maternal oral hygiene practice and attitude towards dentists appear to be important predictors of children's toothbrushing habits in this Japanese community sample. [ABSTRACT FROM AUTHOR]

Published
2015
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35. Caries experience among Romanian schoolchildren: prevalence and trends 1992-2011.

Author

Baciu, D., Danila, I., Balcos, C., Gallagher, J. E., and Bernabé, E.

Abstract

Objectives: To assess the caries experience of 6-8- and 11-13-year-olds in Romania and to compare their caries levels with those from a previous study conducted in 1992. Methods: A cross-sectional pathfinder survey was conducted in five major cities of Romania (Iasi, Timisoara. Cluj-Napoca, Tirgu Mures and the capital, Bucharest) in 2011. Cities were purposively chosen for comparability with the 1992 study. Children were clinically examined by one trained dental examiner using the International Caries Detection and Assessment System (ICDAS II). Results: Among the 548 6-8-year-olds, 84.3% had caries experience (82.7% when carious lesions at stages 1-2 were excluded) with mean d1-6 and d3-6 of 4.76 (sd 3.46) and 4.43 (sd 3.35) respectively. Among the 592 11-13-year-olds, 83.1% had caries experience (76% when carious lesions at stages 1-2 were excluded) with mean D1-6 (MFT and D1-6 MFT of 4.52 (sd 4.01) and 3.39 (sd 3.35) respectively. Advanced carious lesions were the main contributors to children' s caries experience. There were significant differences by cities, with the lowest caries levels seen in Bucharest. High caries levels have persisted in Romania over the last decades in spite of a small but significant decrease in d1-6 mft and D3-6MFT values between 1992 and 2011. Variations in caries trends were found by city. Conclusion: These findings show that high caries levels still exist among schoolchildren in the five cities included in the study. Romania has not yet achieved the WHO target for 2000 of an average DMFT lower than 3 at 12 years of age. [ABSTRACT FROM AUTHOR]

Published
2015
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36. Comparing lifecourse models of social class and adult oral health using the 1958 National Child Development Study.

Author

Delgado-Angulo, E. K. and Bernabé, E.

Abstract

Objective: To identify the lifecourse model that best describes the association between social class and adult oral health. Methods: Data from 10,217 participants of the 1958 National Child Development Study were used. Social class at ages 7, 16 and 33 years were chosen to represent socioeconomic conditions during childhood, adolescence and adulthood, respectively. Two subjective oral health indicators (lifetime and past-year prevalence of persistent trouble with gums or mouth) were measured at age 33. The critical period, accumulation and social trajectories models were tested in logistic regression models and the most appropriate lifecourse model was identified using the structured modelling approach. Results: The critical period model showed that only adulthood social class was significantly associated with oral health. For the accumulation model, a monotonic gradient was found between the number of periods in manual social class and oral health; and four out of eight social trajectories were found to be distinctive. Finally, the social trajectories model was not significantly different from the saturated model indicating that it provided a good fit to the data. Conclusion: This study shows the social trajectories model was the most appropriate, in terms of model fit, to describe the association between social class and oral health. [ABSTRACT FROM AUTHOR]

Published
2015
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37. Global Burden of Oral Conditions in 1990-2010: A Systematic Analysis.

Author

Marcenes, W., Kassebaum, N.J., Bernabé, E., Flaxman, A., Naghavi, M., Lopez, A., and Murray, C.J.L.

Subjects
SYSTEMATIC reviews, DENTAL caries, PERIODONTAL disease, EDENTULOUS mouth, WORLD health, FUNCTIONAL assessment, PERMANENT dentition, PERIODONTITIS, TOOTH loss
Abstract

The Global Burden of Disease (GBD) 2010 Study produced comparable estimates of the burden of 291 diseases and injuries in 1990, 2005, and 2010. This article reports on the global burden of untreated caries, severe periodontitis, and severe tooth loss in 2010 and compares those figures with new estimates for 1990. We used disability-adjusted life-years (DALYs) and years lived with disability (YLDs) metrics to quantify burden. Oral conditions affected 3.9 billion people, and untreated caries in permanent teeth was the most prevalent condition evaluated for the entire GBD 2010 Study (global prevalence of 35% for all ages combined). Oral conditions combined accounted for 15 million DALYs globally (1.9% of all YLDs; 0.6% of all DALYs), implying an average health loss of 224 years per 100,000 population. DALYs due to oral conditions increased 20.8% between 1990 and 2010, mainly due to population growth and aging. While DALYs due to severe periodontitis and untreated caries increased, those due to severe tooth loss decreased. DALYs differed by age groups and regions, but not by genders. The findings highlight the challenge in responding to the diversity of urgent oral health needs worldwide, particularly in developing communities. [ABSTRACT FROM PUBLISHER]

Published
2013
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38. Income Inequality and Tooth Loss in the United States.

Author

Bernabé, E. and Marcenes, W.

Subjects
INCOME inequality, TOOTH loss, SOCIOECONOMIC factors, MULTILEVEL models, GINI coefficient, CONFIDENCE intervals, LOGITS
Abstract

This study explored the relationship between state income inequality and individual tooth loss among 386,629 adults in the United States who participated in the 2008 Behavioral and Risk Factor Surveillance System. Multilevel models were used to test the association of the state Gini coefficient with tooth loss after sequential adjustment for state- (median household income) and individual-level confounders (sex, age, race, education, and household income), as well as state- (percent receiving fluoridated water and dentist-to-population ratio) and individual-level mediators (marital status and last dental visit). The state Gini coefficient was significantly associated with tooth loss even after adjustment for state- and individual-level confounders and potential mediators (Odds Ratio, 1.17; 95% Confidence Interval, 1.05 to 1.30). This study provides support for the relationship between state income inequality and individual tooth loss in the United States. [ABSTRACT FROM PUBLISHER]

Published
2011
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40. Periodontal disease and quality of life in British adults.

Author

Bernabé E and Marcenes W

Abstract

Aim: To explore the association between periodontal disease and quality of life in British adults, independently of demographic factors, socioeconomic position and other common oral conditions. Materials and Methods: This is a cross-sectional study of 3122 dentate adults who participated in the 1998 Adult Dental Health Survey in the United Kingdom. The short-form oral health impact profile (OHIP-14) was used to assess oral health-related quality of life. Periodontal disease was defined as having at least two proximal sites with loss of attachment ⩾4mm and one proximal site with pocket depth ⩾4 mm, not necessarily on the same tooth. The association between periodontal disease and the OHIP-14 score was assessed in unadjusted, partially adjusted and fully adjusted models. Results: Periodontal disease was associated with the OHIP-14 score (rate ratio: 1.26, 95% CI: 1.16-1.38), even after adjustment for demographic factors (sex, age and English region or country), socioeconomic position (educational attainment and household income) and clinical conditions (number of teeth, partial denture use, dental caries, traumatic dental injuries and tooth wear). Conclusion: Periodontal disease was associated with quality of life, independent of socio-demographic characteristics and other conditions present in the mouth. [ABSTRACT FROM AUTHOR]

Published
2010
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41. Sense of coherence and oral health in dentate adults: findings from the Finnish Health 2000 survey Bernabé et al. Sense of coherence and oral health.

Author

Bernabé E, Watt RG, Sheiham A, Suominen-Taipale AL, Uutela A, Vehkalahti MM, Knuuttila M, Kivimäki M, and Tsakos G

Abstract

Aim: To assess the relationship between sense of coherence (SOC) and oral health, and the role of oral health-related behaviours in this relationship. Materials and Methods: This is a cross-sectional study of 5401 dentate adults who participated in the nationally representative Health 2000 Survey in Finland. The survey gathered information on SOC, demographic characteristics, education, income, preexisting diabetes, daily smoking, dental attendance, toothbrushing frequency and sugar intake frequency. Oral health was assessed through clinical outcomes, such as number of teeth, number of decayed teeth and extent of periodontal pockets and perceived oral health. Results: A strong SOC was related to having more teeth, fewer decayed teeth, lower extent of periodontal pockets and good perceived oral health after adjustment for confounders, such as demographic and socioeconomic factors (all p⩽0.003). These associations were attenuated but remained significant after further adjustment for potential mediators (oral health-related behaviours), except for the association of SOC with the extent of periodontal pockets, which was fully accounted for by pre-existing diabetes, oral health-related behaviours and dental plaque (p = 0.549). Conclusion: SOC is positively associated with various aspects of adult oral health, in part because of the better oral health-related behaviours among people with a strong SOC. [ABSTRACT FROM AUTHOR]

Published
2010
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42. A comprehensive evaluation of the validity of Child-OIDP: further evidence from Peru.

Author

Bernabé E, Sheiham A, and Tsakos G

Abstract

Objective: To comprehensively assess the psychometric properties of the child version of the Oral Impacts on Daily Performance (Child-OIDP), by reporting additional validation methodologies and highlighting underlying constructs. Methods: Four of seven public schools linked to the Mother-Child Health Centre from Puente Piedra (Lima, Peru) were randomly selected as clusters. All their 903 11- to 12-year-old children were invited to participate. The Child-OIDP was cross-culturally adapted to Spanish and its content, face, criterion and construct validity as well as internal and external reliability evaluated in successive pilot studies and a main study. Results: For criterion validity, Child-OIDP scores were associated to self-perceived oral health status, self-perceived dental treatment need and satisfaction with oral health status ( P < 0.001 in all cases). In relation to construct validity, an exploratory factor analysis provided three factors with eigenvalues greater than 1, which represented the physical, psychological and social health components. Cronbach's alpha varied between 0.62 and 0.65, whereas test-retest reliability was 0.85 (intra-class correlation coefficient). Conclusions: The Spanish(Peru) Child-OIDP is a valid and reliable interviewer-administered instrument to measure the impact of the oral conditions on quality of life. This study provides new evidence in support of the psychometric properties of the Child-OIDP. [ABSTRACT FROM AUTHOR]

Published
2008

44. Is Starch Intake Associated With Periodontal Status? An 11‐Year Longitudinal Analysis Among Finnish Adults.

Author

Jangda, F. H., Suominen, A. L., Lundqvist, A., Männistö, S., Golkari, A., and Bernabé, E.

Subjects
*FOOD chemistry, *STARCH, *PERIODONTAL disease, *TUBERS, *REGRESSION analysis
Abstract

ABSTRACT Aim Methods Results Conclusion To evaluate the association between baseline starch intake (amount and sources) and changes in periodontal status over 11 years in adults.Adults aged 30–82 years, who participated in the Finnish Health 2000 survey and were re‐examined in 2004/2005 and/or 2011 were included in the study. The consumption of total starch and six relevant food groups (potatoes, fried potatoes, roots and tubers, pasta, wholegrains and legumes) over the past year was determined at baseline with a validated food frequency questionnaire. The number of teeth with periodontal pocketing ≥ 4 mm (NTPP) was recorded during clinical examinations in 2000, 2004/2005 and 2011. The association between baseline starch intake and the 11‐year change in the NTPP was tested in mixed‐effects negative binomial regression models, adjusting for covariates.A total of 1369 adults were included in the analysis. The mean NTPP was 4.1 ± 5.6, 6.3 ± 5.6, and 4.8 ± 5.9 in waves 1, 2 and 3, respectively. Baseline starch intake (in g/day or % energy intake) was not associated with changes in the NTPP after adjustment for covariates. In analysis by food groups, the baseline intake of wholegrains was negatively associated with the NTPP at baseline.This study found no evidence of an association between baseline starch intake and changes in periodontal status. Baseline intake of wholegrains was associated with better periodontal status at baseline. [ABSTRACT FROM AUTHOR]

Published
2024
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45. School bullying and traumatic dental injuries in East London adolescents.

Author

Agel, M., Marcenes, W., Stansfeld, S. A., and Bernabé, E.

Subjects
SCHOOL bullying, NUTRITION & oral health, TEETH injuries, VICTIMS of bullying
Abstract

Aim To explore the association between school bullying and traumatic dental injuries (TDI) among 15-16-year-old school children from East London.Design Data from phase III of the Research with East London Adolescents Community Health Survey (RELACHS), a school-based prospective study of a representative sample of adolescents, were analysed. Adolescents provided information on demographic characteristics, socioeconomic measures and frequency of bullying in school through self-administered questionnaires and were clinically examined for overjet, lip coverage and TDI. The association between school bullying and TDI was assessed using binary logistic regression models.Results The prevalence of TDI was 17%, while lifetime and current prevalence of bullying was 32% and 11%, respectively. The prevalence of TDI increased with a growing frequency of bullying; from 16% among adolescents who had never been bullied at school, to 21% among those who were bullied in the past but not this school term, to 22% for those who were bullied this school term. However, this association was not statistically significant either in crude or adjusted regression models.Conclusion There was no evidence of an association between frequency of school bullying and TDI in this sample of 15-16-year-old adolescents in East London. [ABSTRACT FROM AUTHOR]

Published
2014
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46. Global Burden of Severe Tooth Loss: A Systematic Review and Meta-analysis.

Author

Kassebaum, N.J., Bernabé, E., Dahiya, M., Bhandari, B., Murray, C.J.L., and Marcenes, W.

Subjects
DENTAL extraction, PUBLIC health research, TOOTH loss, GERIATRIC dentistry, EPIDEMIOLOGICAL research
Abstract

The goal of the Global Burden of Disease 2010 Study has been to systematically produce comparable estimates of the burden of 291 diseases and injuries and their associated 1,160 sequelae from 1990 to 2010. We aimed to report here internally consistent prevalence and incidence estimates of severe tooth loss for all countries, 20 age groups, and both sexes for 1990 and 2010. The systematic search of the literature yielded 5,618 unique citations. After titles and abstracts were screened, 5,285 citations were excluded as clearly not relevant to this systematic review, leaving 333 for full-text review; 265 publications were further excluded following the validity assessment. A total of 68 studies—including 285,746 individuals aged 12 yr or older in 26 countries—were included in the meta-analysis using modeling resources of the Global Burden of Disease 2010 Study. Between 1990 and 2010, the global age-standardized prevalence of edentate people decreased from 4.4% (95% uncertainty interval: 4.1%, 4.8%) to 2.4% (95% UI: 2.2%, 2.7%), and incidence rate decreased from 374 cases per 100,000 person-years (95% UI: 347, 406) to 205 cases (95% UI: 187, 226). No differences were found by sex in 2010. Prevalence increased gradually with age, showing a steep increase around the seventh decade of life that was associated with a peak in incidence at 65 years. Geographic differences in prevalence, incidence, and rate of improvement from 1990 to 2010 were stark. Our review of available quality literature on the epidemiology of tooth loss shows a significant decline in the prevalence and incidence of severe tooth loss between 1990 and 2010 at the global, regional, and country levels. [ABSTRACT FROM PUBLISHER]

Published
2014
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47. Impacts on Daily Performances Related to Wearing of Different Orthodontic Appliances--A Study on Brazilian Adolescents. Angle Orthodontist: Vol. 78, 482-486.

Author

Bernabé, E., Sheiham, A., and de Oliveira, C. M.

Subjects
LETTERS to the editor, ORTHODONTIC appliances
Abstract

A response by E. Bernabé, A. Sheiham and C. M. de Oliveira to a letter to the editor about their article "Impacts on Daily Performances Related to Wearing of Different Orthodontic Appliances--A Study on Brazilian Adolescents" in a 2008 issue is presented.

Published
2008

49. Measuring performance on the Healthcare Access and Quality Index for 195 countries and territories and selected subnational locations: a systematic analysis from the Global Burden of Disease Study 2016

Author

Nancy, Fullman, Jamal, Yearwood, Solomon, M, Abay, Cristiana, Abbafati, Foad, Abd-Allah, Jemal, Abdela, Ahmed, Abdelalim, Zegeye, Abebe, Teshome, Abuka, Abebo, Victor, Aboyans, Haftom, Niguse, Abraha, Daisy, M, X, Abreu, Laith, Abu-Raddad, J, Akilew, Awoke, Adane, Rufus, Adesoji, Adedoyin, Olatunji, Adetokunboh, Tara, Ballav, Adhikari, Mohsen, Afarideh, Ashkan, Afshin, Gina, Agarwal, Dominic, Agius, Anurag, Agrawal, Sutapa, Agrawal, Aliasghar, Ahmad, Kiadaliri, Miloud, Taki, Eddine, Aichour, Mohammed, Akibu, Rufus, Olusola, Akinyemi, Tomi, Akinyemiju, F, Nadia, Akseer, Faris, Hasan, Lami, Al, Fares, Alahdab, Ziyad, Al-Aly, Khurshid, Alam, Tahiya, Alam, Deena, Alasfoor, Mohammed, I, Albittar, Kefyalew, Addis, Alene, Ayman, Al-Eyadhy, Syed, Danish, Ali, Mehran, Alijanzadeh, Syed, M, Aljunid, Ala’A, Alkerwi, François, Alla, Peter, Allebeck, Christine, Allen, Mahmoud, A, Alomari, Rajaa, Al-Raddadi, Ubai, Alsharif, Khalid, A, Altirkawi, Nelson, Alvis-Guzman, Azmeraw, T, Amare, Kebede, Amenu, Walid, Ammar, Yaw, Ampem, Amoako, Nahla, Anber, Catalina, Liliana, Andrei, Sofia, Androudi, Carl, Abelardo, Antonio, T, Valdelaine, E, Araújo, M, Olatunde, Aremu, Johan, Ärnlöv, Artaman, Al, Krishna, Kumar, Aryal, Hamid, Asayesh, Ephrem, Tsegay, Asfaw, Solomon, Weldegebreal, Asgedom, Rana, Jawad, Asghar, Mengistu, Mitiku, Ashebir, Netsanet, Abera, Asseffa, Tesfay, Mehari, Atey, Sachin, R, Atre, Madhu, Atteraya, S, Leticia, Avila-Burgos, Euripide, Frinel, Arthur, G, Avokpaho, Ashish, Awasthi, Beatriz, Paulina, Ayala, Quintanilla, Animut, Alebel, Ayalew, Henok, Tadesse, Ayele, Rakesh, Ayer, Tambe, Betrand, Ayuk, Peter, Azzopardi, Natasha, Azzopardi-Muscat, Tesleem, Kayode, Babalola, Hamid, Badali, Alaa, Badawi, Maciej, Banach, Amitava, Banerjee, Amrit, Banstola, Ryan, M, Barber, Miguel, Barboza, A, Suzanne, L, Barker-Collo, Till, Bärnighausen, Simon, Barquera, Lope, H, Barrero, Quique, Bassat, Sanjay, Basu, Bernhard, T, Baune, Shahrzad, Bazargan-Hejazi, Neeraj, Bedi, Ettore, Beghi, Masoud, Behzadifar, Meysam, Behzadifar, Bayu, Begashaw, Bekele, Abate, Bekele, Belachew, Saba, Abraham, Belay, Yihalem, Abebe, Belay, Michelle, L, Bell, Aminu, Bello, K, Derrick, A, Bennett, James, Bennett, R, Isabela, M, Bensenor, Derbew, Fikadu, Berhe, Eduardo, Bernabé, Robert, Steven, Bernstein, Mircea, Beuran, Ashish, Bhalla, Paurvi, Bhatt, Soumyadeep, Bhaumik, Zulfiqar, A, Bhutta, Belete, Biadgo, Ali, Bijani, Boris, Bikbov, Charles, Birungi, Stan, Biryukov, Hailemichael, Bizuneh, Ian, W, Bolliger, Kaylin, Bolt, Ibrahim, R, Bou-Orm, Kayvan, Bozorgmehr, Oliver, Jerome, Brady, Alexandra, Brazinova, Nicholas, J, Breitborde, K, Hermann, Brenner, Gabrielle, Britton, Traolach, S, Brugha, Zahid, Butt, A, Lucero, Cahuana-Hurtado, Ismael, Ricardo, Campos-Nonato, Julio, Cesar, Campuzano, Josip, Car, Mate, Car, Rosario, Cárdenas, Juan, Jesus, Carrero, Felix, Carvalho, Carlos, A, Castañeda-Orjuela, Jacqueline, Castillo, Rivas, Ferrán, Catalá-López, Kelly, Cercy, Julian, Chalek, Hsing-Yi, Chang, Jung-Chen, Chang, Aparajita, Chattopadhyay, Pankaj, Chaturvedi, Peggy, Pei-Chia, Chiang, Vesper, Hichilombwe, Chisumpa, Jee-Young, J, Choi, Hanne, Christensen, Devasahayam, Jesudas, Christopher, Sheng-Chia, Chung, Liliana, G, Ciobanu, Cirillo, Massimo, Danny, Colombara, Sara, Conti, Cyrus, Cooper, Leslie, Cornaby, Paolo, Angelo, Cortesi, Monica, Cortinovis, Alexandre, Costa, Pereira, Ewerton, Cousin, Michael, H, Criqui, Elizabeth, Cromwell, A, Christopher, Stephen, Crowe, John, Crump, A, Alemneh, Kabeta, Daba, Berihun, Assefa, Dachew, Abel, Fekadu, Dadi, Lalit, Dandona, Rakhi, Dandona, Paul, I, Dargan, Ahmad, Daryani, Maryam, Daryani, Jai, Das, Siddharth, Kumar, Das, José, Das, Neves, Nicole, Davis, Weaver, Kairat, Davletov, Barbora, De, Courten, Diego, Leo, De, Jan-Walter, De, Neve, Robert, Dellavalle, P, Gebre, Demoz, Kebede, Deribe, Don, C, Des, Jarlais, Subhojit, Dey, Samath, D, Dharmaratne, Meghnath, Dhimal, Shirin, Djalalinia, David, Teye, Doku, Kate, Dolan, Ray, E, Dorsey, Kadine, Priscila, Bender, Dos, Santos, Kerrie, E, Doyle, Tim, Driscoll, R, Manisha, Dubey, Eleonora, Dubljanin, Bruce, Bartholow, Duncan, Michelle, Echko, Dumessa, Edessa, David, Edvardsson, Joshua, R, Ehrlich, Erika, Eldrenkamp, Ziad, El-Khatib, Matthias, Endres, Aman, Yesuf, Endries, Babak, Eshrati, Sharareh, Eskandarieh, Alireza, Esteghamati, Mahdi, Fakhar, Tamer, Farag, Mahbobeh, Faramarzi, Emerito, Jose, Aquino, Faraon, André, Faro, Farshad, Farzadfar, Adesegun, Fatusi, Mir, Sohail, Fazeli, Valery, Feigin, L, Andrea, B, Feigl, Netsanet, Fentahun, Seyed-Mohammad, Fereshtehnejad, Eduarda, Fernandes, João, C, Fernandes, Daniel, Obadare, Fijabi, Irina, Filip, Florian, Fischer, Christina, Fitzmaurice, Abraham, D, Flaxman, Luisa, Sorio, Flor, Nataliya, Foigt, Kyle, J, Foreman, Joseph, Frostad, J, Thomas, Fürst, Neal, D, Futran, Emmanuela, Gakidou, Silvano, Gallus, Ketevan, Gambashidze, Amiran, Gamkrelidze, Morsaleh, Ganji, Abadi, Kahsu, Gebre, Tsegaye, Tewelde, Gebrehiwot, Amanuel, Tesfay, Gebremedhin, Yalemzewod, Assefa, Gelaw, Johanna, M, Geleijnse, Demeke, Geremew, Peter, W, Gething, Reza, Ghadimi, Khalil, Ghasemi, Falavarjani, Maryam, Ghasemi-Kasman, Paramjit, Singh, Gill, Ababi, Zergaw, Giref, Maurice, Giroud, Melkamu, Dedefo, Gishu, Giorgia, Giussani, William, W, Godwin, Srinivas, Goli, Hector, Gomez-Dantes, Philimon, N, Gona, Amador, Goodridge, Sameer, Vali, Gopalani, Yevgeniy, Goryakin, Alessandra, Carvalho, Goulart, Ayman, Grada, Max, Griswold, Giuseppe, Grosso, Harish, Chander, Gugnani, Yuming, Guo, Rahul, Gupta, Rajeev, Gupta, Tanush, Gupta, Tarun, Gupta, Vipin, Gupta, Juanita, A, Haagsma, Vladimir, Hachinski, Nima, Hafezi-Nejad, Gessessew, Bugssa, Hailu, Randah, Ribhi, Hamadeh, Samer, Hamidi, Graeme, J, Hankey, Hilda, Harb, L, Heather, C, Harewood, Sivadasanpillai, Harikrishnan, Josep, Maria, Haro, Hamid, Yimam, Hassen, Rasmus, Havmoeller, Caitlin, Hawley, Simon, I, Hay, Jiawei, He, Stephen, J, Hearps, C, Mohamed, I, Hegazy, Behzad, Heibati, Mohsen, Heidari, Delia, Hendrie, Nathaniel, J, Henry, Victor, Hugo, Herrera, Ballesteros, Claudiu, Herteliu, Desalegn, Tsegaw, Hibstu, Molla, Kahssay, Hiluf, Hans, W, Hoek, Enayatollah, Homaie, Rad, Nobuyuki, Horita, Dean, H, Hosgood, Mostafa, Hosseini, Seyed, Reza, Hosseini, Mihaela, Hostiuc, Sorin, Hostiuc, Damian, G, Hoy, Mohamed, Hsairi, Aung, Soe, Htet, Guoqing, Hu, John, J, Huang, Kim, Moesgaard, Iburg, Fachmi, Idris, Ehimario, Uche, Igumbor, Chad, Ikeda, Bogdan, Vasile, Ileanu, Olayinka, Ilesanmi, S, Kaire, Innos, Seyed, Sina, Naghibi, Irvani, Caleb, M, Irvine, S, Farhad, Islami, Troy, A, Jacobs, Kathryn, Jacobsen, H, Nader, Jahanmehr, Rajesh, Jain, Sudhir, Kumar, Jain, Mihajlo, Jakovljevic, M, Moti, Tolera, Jalu, Amr, Jamal, A, Mehdi, Javanbakht, Achala, Upendra, Jayatilleke, Panniyammakal, Jeemon, Ravi, Prakash, Jha, Vivekanand, Jha, Jacek, Józwiak, Oommen, John, Sarah, Charlotte, Johnson, Jost, Jonas, B, Vasna, Joshua, Mikk, Jürisson, Zubair, Kabir, Rajendra, Kadel, Amaha, Kahsay, Rizwan, Kalani, Chittaranjan, Kar, Marina, Karanikolos, André, Karch, Corine, Kakizi, Karema, Seyed, Karimi, M, Amir, Kasaeian, Dessalegn, Haile, Kassa, Getachew, Mullu, Kassa, Tesfaye, Dessale, Kassa, Nicholas, Kassebaum, J, Srinivasa, Vittal, Katikireddi, Anil, Kaul, Norito, Kawakami, Konstantin, Kazanjan, Seifu, Kebede, Peter, Njenga, Keiyoro, Grant, Rodgers, Kemp, Andre, Pascal, Kengne, Maia, Kereselidze, Ezra, Belay, Ketema, Yousef, Saleh, Khader, Morteza, Abdullatif, Khafaie, Alireza, Khajavi, Ibrahim, A, Khalil, Ejaz, Ahmad, Khan, Gulfaraz, Khan, Nuruzzaman, Md, Khan, Muhammad, Ali, Khan, Mukti, Nath, Khanal, Young-Ho, Khang, Mona, M, Khater, Abdullah, Tawfih, Abdullah, Khoja, Ardeshir, Khosravi, Jagdish, Khubchandani, Getiye, Dejenu, Kibret, Daniel, Ngari, Kiirithio, Daniel, Kim, Yun, Jin, Kim, Ruth, Kimokoti, W, Yohannes, Kinfu, Sanjay, Kinra, Adnan, Kisa, Niranjan, Kissoon, Sonali, Kochhar, Yoshihiro, Kokubo, Jacek, A, Kopec, Soewarta, Kosen, Parvaiz, A, Koul, 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Agrawal, Anurag, Agrawal, Sutapa, Ahmad Kiadaliri, Aliasghar, Aichour, Miloud Taki Eddine, Akibu, Mohammed, Akinyemi, Rufus Olusola, Akinyemiju, Tomi F., Akseer, Nadia, Al Lami, Faris Hasan, Alahdab, Fare, Al-Aly, Ziyad, Alam, Khurshid, Alam, Tahiya, Alasfoor, Deena, Albittar, Mohammed I., Alene, Kefyalew Addi, Al-Eyadhy, Ayman, Ali, Syed Danish, Alijanzadeh, Mehran, Aljunid, Syed M., Alkerwi, Ala'a, Alla, Françoi, Allebeck, Peter, Allen, Christine, Alomari, Mahmoud A., Al-Raddadi, Rajaa, Alsharif, Ubai, Altirkawi, Khalid A., Alvis-Guzman, Nelson, Amare, Azmeraw T., Amenu, Kebede, Ammar, Walid, Amoako, Yaw Ampem, Anber, Nahla, Andrei, Catalina Liliana, Androudi, Sofia, Antonio, Carl Abelardo T., Araújo, Valdelaine E.M., Aremu, Olatunde, Ärnlöv, Johan, Artaman, Al, Aryal, Krishna Kumar, Asayesh, Hamid, Asfaw, Ephrem Tsegay, Asgedom, Solomon Weldegebreal, Asghar, Rana Jawad, Ashebir, Mengistu Mitiku, Asseffa, Netsanet Abera, Atey, Tesfay Mehari, Atre, Sachin R., Atteraya, Madhu S., 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Dean, Hosseini, Mostafa, Hosseini, Seyed Reza, Hostiuc, Mihaela, Hostiuc, Sorin, Hoy, Damian G., Hsairi, Mohamed, Htet, Aung Soe, Hu, Guoqing, Huang, John J., Iburg, Kim Moesgaard, Idris, Fachmi, Igumbor, Ehimario Uche, Ikeda, Chad, Ileanu, Bogdan Vasile, Ilesanmi, Olayinka S., Innos, Kaire, Irvani, Seyed Sina Naghibi, Irvine, Caleb M.S., Islami, Farhad, Jacobs, Troy A., Jacobsen, Kathryn H., Jahanmehr, Nader, Jain, Rajesh, Jain, Sudhir Kumar, Jakovljevic, Mihajlo M., Jalu, Moti Tolera, Jamal, Amr A., Javanbakht, Mehdi, Jayatilleke, Achala Upendra, Jeemon, Panniyammakal, Jha, Ravi Prakash, Jha, Vivekanand, Józwiak, Jacek, John, Oommen, Johnson, Sarah Charlotte, Jonas, Jost B., Joshua, Vasna, Jürisson, Mikk, Kabir, Zubair, Kadel, Rajendra, Kahsay, Amaha, Kalani, Rizwan, Kar, Chittaranjan, Karanikolos, Marina, Karch, André, Karema, Corine Kakizi, Karimi, Seyed M., Kasaeian, Amir, Kassa, Dessalegn Haile, Kassa, Getachew Mullu, Kassa, Tesfaye Dessale, Kassebaum, Nicholas J., Katikireddi, Srinivasa Vittal, Kaul, Anil, Kawakami, Norito, Kazanjan, Konstantin, Kebede, Seifu, Keiyoro, Peter Njenga, Kemp, Grant Rodger, Kengne, Andre Pascal, Kereselidze, Maia, Ketema, Ezra Belay, Khader, Yousef Saleh, Khafaie, Morteza Abdullatif, Khajavi, Alireza, Khalil, Ibrahim A., Khan, Ejaz Ahmad, Khan, Gulfaraz, Khan, Md Nuruzzaman, Khan, Muhammad Ali, Khanal, Mukti Nath, Khang, Young-Ho, Khater, Mona M., Khoja, Abdullah Tawfih Abdullah, Khosravi, Ardeshir, Khubchandani, Jagdish, Kibret, Getiye Dejenu, Kiirithio, Daniel Ngari, Kim, Daniel, Kim, Yun Jin, Kimokoti, Ruth W., Kinfu, Yohanne, Kinra, Sanjay, Kisa, Adnan, Kissoon, Niranjan, Kochhar, Sonali, Kokubo, Yoshihiro, Kopec, Jacek A., Kosen, Soewarta, Koul, Parvaiz A., Koyanagi, Ai, Kravchenko, Michael, Krishan, Kewal, Krohn, Kristopher J., Kuate Defo, Barthelemy, Kumar, G. Anil, Kumar, Pushpendra, Kutz, Michael, Kuzin, Igor, Kyu, Hmwe H., Lad, Deepesh Pravinkumar, Lafranconi, Alessandra, Lal, Dharmesh Kumar, Lalloo, Ratilal, Lam, Hilton, Lan, Qing, Lang, Justin J., Lansingh, Van C., Lansky, Sonia, Larsson, Ander, Latifi, Arman, Lazarus, Jeffrey Victor, Leasher, Janet L., Lee, Paul H., Legesse, Yirga, Leigh, Jame, Leshargie, Cheru Tesema, Leta, Samson, Leung, Janni, Leung, Ricky, Levi, Miriam, Li, Yongmei, Liang, Juan, Liben, Misgan Legesse, Lim, Lee-Ling, Lim, Stephen S., Lind, Margaret, Linn, Shai, Listl, Stefan, Liu, Patrick Y., Liu, Shiwei, Lodha, Rakesh, Lopez, Alan D., Lorch, Scott A., Lorkowski, Stefan, Lotufo, Paulo A., Lucas, Timothy C.D., Lunevicius, Raimunda, Lurton, Grégoire, Lyons, Ronan A., Maalouf, Fadi, Macarayan, Erlyn Rachelle King, Mackay, Mark T., Maddison, Emilie R., Madotto, Fabiana, Magdy Abd El Razek, Hassan, Magdy Abd El Razek, Mohammed, Majdan, Marek, Majdzadeh, Reza, Majeed, Azeem, Malekzadeh, Reza, Malhotra, Rajesh, Malta, Deborah Carvalho, Mamun, Abdullah A., Manguerra, Helena, Manhertz, Treh, Mansournia, Mohammad Ali, Mantovani, Lorenzo G., Manyazewal, Tsegahun, Mapoma, Chabila C., Margono, Christopher, Martinez-Raga, Jose, Martins, Sheila Cristina Ourique, Martins-Melo, Francisco Rogerlândio, Martopullo, Ira, März, Winfried, Massenburg, Benjamin Ballard, Mathur, Manu Raj, Maulik, Pallab K., Mazidi, Mohsen, McAlinden, Colm, McGrath, John J., McKee, Martin, Mehata, Suresh, Mehrotra, Ravi, Mehta, Kala M., Mehta, Varshil, Meier, Toni, Mejia-Rodriguez, Fabiola, Meles, Kidanu Gebremariam, Melku, Mulugeta, Memiah, Peter, Memish, Ziad A., Mendoza, Walter, Mengiste, Degu Abate, Mengistu, Desalegn Tadese, Menota, Bereket Gebremichael, Mensah, George A., Meretoja, Atte, Meretoja, Tuomo J., Mezgebe, Haftay Berhane, Miazgowski, Tomasz, Micha, Renata, Milam, Robert, Millear, Anoushka, Miller, Ted R., Mini, G.K., Minnig, Shawn, Mirica, Andreea, Mirrakhimov, Erkin M., Misganaw, Awoke, Mitchell, Philip B., Mlashu, Fitsum Weldegebreal, Moazen, Babak, Mohammad, Karzan Abdulmuhsin, Mohammadibakhsh, Roghayeh, Mohammed, Ebrahim, Mohammed, Mohammed A., Mohammed, Shafiu, Mokdad, Ali H., Mola, Glen Liddell D., Molokhia, Mariam, Momeniha, Fatemeh, Monasta, Lorenzo, Montañez Hernandez, Julio Cesar, Moosazadeh, Mahmood, Moradi-Lakeh, Maziar, Moraga, Paula, Morawska, Lidia, Moreno Velasquez, Ilai, Mori, Rintaro, Morrison, Shane D., Moses, Mark, Mousavi, Seyyed Meysam, Mueller, Ulrich O., Murhekar, Manoj, Murthy, Gudlavalleti Venkata Satyanarayana, Murthy, Sriniva, Musa, Jonah, Musa, Kamarul Imran, Mustafa, Ghulam, Muthupandian, Saravanan, Nagata, Chie, Nagel, Gabriele, Naghavi, Mohsen, Naheed, Aliya, Naik, Gurudatta A., Naik, Nitish, Najafi, Farid, Naldi, Luigi, Nangia, Vinay, Nansseu, Jobert Richie Njingang, Narayan, K.M. 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Moares Pedroso, Marcel, Pedroza, Sandra P., Pereira, David M., Perico, Norberto, Peterson, Hannah, Petzold, Max, Peykari, Niloofar, Phillips, Michael Robert, Piel, Frédéric B., Pigott, David M., Pillay, Julian David, Piradov, Michael A., Polinder, Suzanne, Pond, Constance D., Postma, Maarten J., Pourmalek, Farshad, Prakash, Swayam, Prakash, V., Prasad, Narayan, Prasad, Noela Marie, Purcell, Caroline, Qorbani, Mostafa, Quintana, Hedley Knewjen, Radfar, Amir, Rafay, Anwar, Rafiei, Alireza, Rahimi, Kazem, Rahimi-Movaghar, Afarin, Rahimi-Movaghar, Vafa, Rahman, Mahfuzar, Rahman, Muhammad Aziz, Rahman, Sajjad Ur, Rai, Rajesh Kumar, Raju, Sree Bhushan, Ram, Usha, Rana, Saleem M., Rankin, Zane, Rasella, Davide, Rawaf, David Laith, Rawaf, Salman, Ray, Sarah E., Razo-García, Christian Aspacia, Reddy, Priscilla, Reiner, Robert C., Reis, Cesar, Reitsma, Marissa B., Remuzzi, Giuseppe, Renzaho, Andre M.N., Resnikoff, Serge, Rezaei, Satar, Rezai, Mohammad Sadegh, Ribeiro, Antonio L., Rios Blancas, Maria Jesu, Rivera, Juan A., Roever, Leonardo, Ronfani, Luca, Roshandel, Gholamreza, Rostami, Ali, Roth, Gregory A., Rothenbacher, Dietrich, Roy, Ambuj, Roy, Nobhojit, Ruhago, George Mugambage, Sabde, Yogesh Damodar, Sachdev, Perminder S., Sadat, Nafi, Safdarian, Mahdi, Safiri, Saeid, Sagar, Rajesh, Sahebkar, Amirhossein, Sahraian, Mohammad Ali, Sajadi, Haniye Sadat, Salama, Joseph, Salamati, Payman, De Freitas Saldanha, Raphael, Salimzadeh, Hamideh, Salomon, Joshua A., Samy, Abdallah M., Sanabria, Juan Ramon, Sancheti, Parag K., Sanchez-Niño, Maria Dolore, Santomauro, Damian, Santos, Itamar S., Santric Milicevic, Milena M., Sarker, Abdur Razzaque, Sarrafzadegan, Nizal, Sartorius, Benn, Satpathy, Maheswar, Savic, Miloje, Sawhney, Monika, Saxena, Sonia, Saylan, Mete I., Schaeffner, Elke, Schmidhuber, Josef, Schmidt, Maria Inê, Schneider, Ione J.C., Schumacher, Austin E., Schutte, Aletta E., Schwebel, David C., Schwendicke, Falk, Sekerija, Mario, Sepanlou, Sadaf G., Servan-Mori, Edson E., Shafieesabet, Azadeh, Shaikh, Masood Ali, Shakh-Nazarova, Marina, Shams-Beyranvand, Mehran, Sharafi, Heidar, Sharif-Alhoseini, Mahdi, Shariful Islam, Sheikh Mohammed, Sharma, Meenakshi, Sharma, Rajesh, She, Jun, Sheikh, Aziz, Shfare, Mebrahtu Teweldemedhin, Shi, Peilin, Shields, Chloe, Shigematsu, Mika, Shinohara, Yukito, Shiri, Rahman, Shirkoohi, Reza, Shiue, Ivy, Shrime, Mark G., Shukla, Sharvari Rahul, Siabani, Soraya, Sigfusdottir, Inga Dora, Silberberg, Donald H., Silva, Diego Augusto Santo, Silva, João Pedro, Silveira, Dayane Gabriele Alve, Singh, Jasvinder A., Singh, Lavanya, Singh, Narinder Pal, Singh, Virendra, Sinha, Dhirendra Narain, Sinke, Abiy Hiruye, Sisay, Mekonnen, Skirbekk, Vegard, Sliwa, Karen, Smith, Alison, Soares Filho, Adauto Martin, Sobaih, Badr H.A., Somai, Melek, Soneji, Samir, Soofi, Moslem, Sorensen, Reed J.D., Soriano, Joan B., Soyiri, Ireneous N., Sposato, Luciano A., Sreeramareddy, Chandrashekhar T., Srinivasan, Vinay, Stanaway, Jeffrey D., Stathopoulou, Vasiliki, Steel, Nichola, Stein, Dan J., Stokes, Mark Andrew, Sturua, Lela, Sufiyan, Muawiyyah Babale, Suliankatchi, Rizwan Abdulkader, Sunguya, Bruno F., Sur, Patrick J., Sykes, Bryan L., Sylaja, P.N., Szoeke, Cassandra E.I., Tabarés-Seisdedos, Rafael, Tadakamadla, Santosh Kumar, Tadesse, Andualem Henok, Taffere, Getachew Redae, Tandon, Nikhil, Tariku, Amare Tariku, Taveira, Nuno, Tehrani-Banihashemi, Arash, Temam Shifa, Girma, Temsah, Mohamad-Hani, Terkawi, Abdullah Sulieman, Tesema, Azeb Gebresilassie, Tesfaye, Dawit Jember, Tessema, Belay, Thakur, J.S., Thomas, Nihal, Thompson, Matthew J., Tillmann, Taavi, To, Quyen G., Tobe-Gai, Ruoyan, Tonelli, Marcello, Topor-Madry, Roman, Topouzis, Foti, Torre, Anna, Tortajada, Miguel, Tran, Bach Xuan, Tran, Khanh Bao, Tripathi, Avnish, Tripathy, Srikanth Prasad, Troeger, Christopher, Truelsen, Thoma, Tsoi, Derrick, Tudor Car, Lorainne, Tuem, Kald Beshir, Tyrovolas, Stefano, Uchendu, Uche S., Ukwaja, Kingsley Nnanna, Ullah, Irfan, Updike, Rachel, Uthman, Olalekan A., Uzochukwu, Benjamin S. Chudi, Valdez, Pascual Rubén, Van Boven, Job F.M., Varughese, Santosh, Vasankari, Tommi, Venketasubramanian, Narayanaswamy, Violante, Francesco S., Vladimirov, Sergey K., Vlassov, Vasiliy Victorovich, Vollset, Stein Emil, Vos, Theo, Wagnew, Fasil, Waheed, Yasir, Wallin, Mitchell T., Walson, Judd L., Wang, Yafeng, Wang, Yuan-Pang, Wassie, Molla Mesele, Weaver, Marcia R., Weiderpass, Elisabete, Weintraub, Robert G., Weiss, Jordan, Weldegwergs, Kidu Gidey, Werdecker, Andrea, West, T. Eoin, Westerman, Ronny, White, Richard G., Whiteford, Harvey A., Widecka, Justyna, Winkler, Andrea Sylvia, Wiysonge, Charles Shey, Wolfe, Charles D.A., Wondimkun, Yohanes Ayele, Workicho, Abdulhalik, Wyper, Grant M.A., Xavier, Deni, Xu, Gelin, Yan, Lijing L., Yano, Yuichiro, Yaseri, Mehdi, Yimer, Nigus Bililign, Yin, Peng, Yip, Paul, Yirsaw, Biruck Desalegn, Yonemoto, Naohiro, Yonga, Gerald, Yoon, Seok-Jun, Yotebieng, Marcel, Younis, Mustafa Z., Yu, Chuanhua, Zadnik, Vesna, Zaidi, Zoubida, El Sayed Zaki, Maysaa, Zaman, Sojib Bin, Zamani, Mohammad, Zenebe, Zerihun Menlkalew, Zhou, Maigeng, Zhu, Jun, Zimsen, Stephanie R.M., Zipkin, Ben, Zodpey, Sanjay, Zuhlke, Liesl Joanna, Murray, Christopher J.L., Lozano, Rafael, Viðskiptadeild (HR), School of Business (RU), Háskólinn í Reykjavík, Reykjavik University, Abay, Sm, Abebo, Ta, Abraha, Hn, Abreu, Dmx, Abu-Raddad, Lj, Adane, Aa, Adedoyin, Ra, Adhikari, Tb, Aichour, Mte, Akinyemi, Ro, Akinyemiju, Tf, Al Lami, Fh, Albittar, Mi, Alene, Ka, Ali, Sd, Aljunid, Sm, Alomari, Ma, Altirkawi, Ka, Amare, At, Amoako, Ya, Andrei, Cl, Antonio, Cat, Araújo, Vem, Aryal, Kk, Asfaw, Et, Asgedom, Sw, Asghar, Rj, Ashebir, Mm, Asseffa, Na, Atey, Tm, Atre, Sr, Avokpaho, Efga, Ayala Quintanilla, Bp, Ayalew, Aa, Ayele, Ht, Ayuk, Tb, Babalola, Tk, Barber, Rm, Barboza, Ma, Barker-Collo, Sl, Barrero, Lh, Baune, Bt, Bekele, Bb, Belachew, Ab, Belay, Sa, Belay, Ya, Bell, Ml, Bello, Ak, Bennett, Da, Bennett, Jr, Bensenor, Im, Berhe, Df, Bhutta, Za, Bolliger, Iw, Bou-Orm, Ir, Brady, Oj, Breitborde, Njk, Butt, Za, Campos-Nonato, Ir, Campuzano, Jc, Carrero, Jj, Castañeda-Orjuela, Ca, Chang, Hy, Chang, Jc, Chiang, Pp, Chisumpa, Vh, Choi, Jj, Christopher, Dj, Chung, Sc, Ciobanu, Lg, Cortesi, Pa, Criqui, Mh, Cromwell, Ea, Crump, Ja, Daba, Ak, Dachew, Ba, Dadi, Af, Dargan, Pi, Das, Sk, De Neve, Jw, Dellavalle, Rp, Des Jarlais, Dc, Dharmaratne, Sd, Doku, Dt, Dorsey, Er, Dos Santos, Kpb, Doyle, Ke, Driscoll, Tr, Duncan, Bb, Ehrlich, Jr, El-Khatib, Zz, Endries, Ay, Faraon, Eja, Feigin, Vl, Feigl, Ab, Fereshtehnejad, Sm, Fernandes, Jc, Fijabi, Do, Flaxman, Ad, Foreman, Kj, Frostad, Jj, Futran, Nd, Gebre, Ak, Gebrehiwot, Tt, Gebremedhin, At, Gelaw, Ya, Geleijnse, Jm, Gething, Pw, Giref, Az, Gishu, Md, Godwin, Ww, Gona, Pn, Gopalani, Sv, Goulart, Ac, Gugnani, Hc, Haagsma, Ja, Hailu, Gb, Hamadeh, Rr, Hankey, Gj, Harb, Hl, Harewood, Hc, Haro, Jm, Hassen, Hy, Hay, Si, Hearps, Sjc, Hegazy, Mi, Henry, Nj, Herrera Ballesteros, Vh, Hibstu, Dt, Hiluf, Mk, Hoek, Hw, Hosgood, Hd, Hosseini, Sr, Hoy, Dg, Huang, Jj, Iburg, Km, Igumbor, Eu, Ileanu, Bv, Irvani, Ssn, Irvine, Cm, Jacobs, Ta, Jacobsen, Kh, Jain, Sk, Jakovljevic, Mb, Jalu, Mt, Jamal, Aa, Jayatilleke, Au, Jha, Rp, Johnson, Sc, Jonas, Jb, Karema, Ck, Karimi, Sm, Kassa, Dh, Kassa, Gm, Kassa, Td, Kassebaum, Nj, Katikireddi, Sv, Keiyoro, Pn, Kemp, Gr, Kengne, Ap, Ketema, Eb, Khafaie, Ma, Khalil, Ia, Khan, Ea, Khan, Mn, Khan, Ma, Khanal, Mn, Khang, Yh, Khater, Mm, Khoja, Ata, Kibret, Gd, Kiirithio, Dn, Kim, Yj, Kimokoti, Rw, Kopec, Ja, Koul, Pa, Krohn, Kj, Kumar, Ga, Kyu, Hh, Lad, Dp, Lal, Dk, Lang, Jj, Lansingh, Vc, Lazarus, Jv, Leasher, Jl, Lee, Ph, Leshargie, Ct, Liben, Ml, Lim, Ll, Lopez, Ad, Lorch, Sa, Lotufo, Pa, Lucas, Tcd, Lyons, Ra, Macarayan, Erk, Mackay, Mt, Maddison, Er, Malta, Dc, Mamun, Aa, Mansournia, Ma, Mantovani, Lg, Mapoma, Cc, Martins, Sco, Martins-Melo, Fr, Massenburg, Bb, Mathur, Mr, Maulik, Pk, Mcgrath, Jj, Mehta, Km, Meles, Kg, Memish, Za, Mengiste, Da, Mengistu, Dt, Menota, Bg, Mensah, Ga, Meretoja, Tj, Mezgebe, Hb, Miller, Tr, Mini, Gk, Mirrakhimov, Em, Mitchell, Pb, Mlashu, Fw, Mohammad, Ka, Mohammed, Ma, Mokdad, Ah, Mola, Gl, Montañez Hernandez, Jc, Morrison, Sd, Mousavi, Sm, Mueller, Uo, Murthy, Gv, Musa, Ki, Naik, Ga, Nansseu, Jrn, Narayan, Kv, Nascimento, Br, Negoi, Ri, Newton, Cr, Ngunjiri, Jw, Nguyen, Th, Ningrum, Dna, Nong, Vm, Norheim, Of, Noubiap, Jjn, Obermeyer, Cm, Ogbo, Fa, Oh, Ih, Olagunju, At, Olagunju, To, Olivares, Pr, Oliveira, Ppv, Olsen, He, Olusanya, Bo, Olusanya, Jo, Opio, Jn, Ortega-Altamirano, Dv, Pain, Aw, Palone, Mrt, Pandian, Jd, Park, Ek, Patil, St, Patton, Gc, Paturi, Vr, Pedroso, Mm, Pedroza, Sp, Pereira, Dm, Phillips, Mr, Piel, Fb, Pigott, Dm, Pillay, Jd, Piradov, Ma, Pond, Cd, Postma, Mj, Prasad, Nm, Quintana, Hk, Rahman, Ma, Rahman, Su, Rai, Rk, Raju, Sb, Rana, Sm, Rawaf, Dl, Ray, Se, Razo-García, Ca, Reiner, Rc, Reitsma, Mb, Renzaho, Amn, Ribeiro, Al, Rios Blancas, Mj, Rivera, Ja, Roth, Ga, Ruhago, Gm, Sabde, Yd, Sahraian, Ma, Saldanha, Rf, Salomon, Ja, Samy, Am, Sanabria, Jr, Sancheti, Pk, Sanchez-Niño, Md, Santric Milicevic, Mm, Sarker, Ar, Saylan, Mi, Schmidt, Mi, Schneider, Ijc, Schumacher, Ae, Schutte, Ae, Schwebel, Dc, Sepanlou, Sg, Servan-Mori, Ee, Shaikh, Ma, Shariful Islam, Sm, Shfare, Mt, Shrime, Mg, Shukla, Sr, Sigfusdottir, Id, Silberberg, Dh, Silva, Da, Silva, Jp, Silveira, Dga, Singh, Ja, Singh, Np, Sinha, Dn, Sinke, Ah, Soares Filho, Am, Sobaih, Bha, Sorensen, Rjd, Soriano, Jb, Soyiri, In, Sposato, La, Sreeramareddy, Ct, Stanaway, Jd, Stein, Dj, Stokes, Ma, Sufiyan, Mb, Suliankatchi, Ra, Sunguya, Bf, Sur, Pj, Sykes, Bl, Sylaja, Pn, Tadakamadla, Sk, Tadesse, Ah, Taffere, Gr, Tariku, At, Temsah, Mh, Tesema, Ag, Tesfaye, Dj, Thompson, Mj, To, Qg, Tran, Bx, Tran, Kb, Tripathy, Sp, Tuem, Kb, Ukwaja, Kn, Uthman, Oa, Uzochukwu, Bsc, Valdez, Pr, van Boven, Jfm, Vladimirov, Sk, Vlassov, Vv, Vollset, Se, Wallin, Mt, Walson, Jl, Wang, Yp, Wassie, Mm, Weaver, Mr, Weintraub, Rg, Weldegwergs, Kg, West, Te, White, Rg, Whiteford, Ha, Wolfe, Cd, Wondimkun, Ya, Wyper, Gma, Yan, Ll, Yimer, Nb, Yirsaw, Bd, Yoon, Sj, Younis, Mz, Zaki, Me, Zaman, Sb, Zenebe, Zm, Zimsen, Srm, Zuhlke, Lj, Murray, Cjl, and Lozano, R.

Subjects
Peformance, Coverage, Dánartíðni, Lífslíkur, Life expectancy, GBD, Background A key component of achieving universal health coverage is ensuring that all populations have access to quality health care. Examining where gains have occurred or progress has faltered across and within countries is crucial to guiding decisions and strategies for future improvement. We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) to assess personal health-care access and quality with the Healthcare Access and Quality (HAQ) Index for 195 countries and territories, as well as subnational locations in seven countries, from 1990 to 2016. Methods Drawing from established methods and updated estimates from GBD 2016, we used 32 causes from which death should not occur in the presence of effective care to approximate personal health-care access and quality by location and over time. To better isolate potential effects of personal health-care access and quality from underlying risk factor patterns, we risk-standardised cause-specific deaths due to non-cancers by location-year, replacing the local joint exposure of environmental and behavioural risks with the global level of exposure. Supported by the expansion of cancer registry data in GBD 2016, we used mortality-to-incidence ratios for cancers instead of risk-standardised death rates to provide a stronger signal of the effects of personal health care and access on cancer survival. We transformed each cause to a scale of 0–100, with 0 as the first percentile (worst) observed between 1990 and 2016, and 100 as the 99th percentile (best), universal health coverage, Article, access quality health care, health care access and quality index, Nations, Healthcare Acce, Cause-specific mortality, Psychology, Healthcare Access and Quality Index, Mælitæki, States, Medicine (all), Health care, Þjóðir, Public Health, Global Health, Social Medicine and Epidemiology, Quality, Heilbrigðisþjónusta, Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi, Sálfræði, Indicator, Amenable mortality, Transition, we set these thresholds at the country level, and then applied them to subnational locations. We applied a principal components analysis to construct the HAQ Index using all scaled cause values, providing an overall score of 0–100 of personal health-care access and quality by location over time. We then compared HAQ Index levels and trends by quintiles on the Socio-demographic Index (SDI), a summary measure of overall development. As derived from the broader GBD study and other data sources, we examined relationships between national HAQ Index scores and potential correlates of performance, such as total health spending per capita. Findings In 2016, HAQ Index performance spanned from a high of 97·1 (95% UI 95·8–98·1) in Iceland, followed by 96·6 (94·9–97·9) in Norway and 96·1 (94·5–97·3) in the Netherlands, to values as low as 18·6 (13·1–24·4) in the Central African Republic, 19·0 (14·3–23·7) in Somalia, and 23·4 (20·2–26·8) in Guinea-Bissau. The pace of progress achieved between 1990 and 2016 varied, with markedly faster improvements occurring between 2000 and 2016 for many countries in sub-Saharan Africa and southeast Asia, whereas several countries in Latin America and elsewhere saw progress stagnate after experiencing considerable advances in the HAQ Index between 1990 and 2000. Striking subnational disparities emerged in personal health-care access and quality, with China and India having particularly large gaps between locations with the highest and lowest scores in 2016. In China, performance ranged from 91·5 (89·1–93·6) in Beijing to 48·0 (43·4–53·2) in Tibet (a 43·5-point difference), while India saw a 30·8-point disparity, from 64·8 (59·6–68·8) in Goa to 34·0 (30·3–38·1) in Assam. Japan recorded the smallest range in subnational HAQ performance in 2016 (a 4·8-point difference), whereas differences between subnational locations with the highest and lowest HAQ Index values were more than two times as high for the USA and three times as high for England. State-level gaps in the HAQ Index in Mexico somewhat narrowed from 1990 to 2016 (from a 20·9-point to 17·0-point difference), whereas in Brazil, disparities slightly increased across states during this time (a 17·2-point to 20·4-point difference). Performance on the HAQ Index showed strong linkages to overall development, with high and high-middle SDI countries generally having higher scores and faster gains for non-communicable diseases. Nonetheless, countries across the development spectrum saw substantial gains in some key health service areas from 2000 to 2016, most notably vaccine-preventable diseases. Overall, national performance on the HAQ Index was positively associated with higher levels of total health spending per capita, as well as health systems inputs, but these relationships were quite heterogeneous, particularly among low-to-middle SDI countries. Interpretation GBD 2016 provides a more detailed understanding of past success and current challenges in improving personal health-care access and quality worldwide. Despite substantial gains since 2000, many low-SDI and middle-SDI countries face considerable challenges unless heightened policy action and investments focus on advancing access to and quality of health care across key health services, especially non-communicable diseases. Stagnating or minimal improvements experienced by several low-middle to high-middle SDI countries could reflect the complexities of re-orienting both primary and secondary health-care services beyond the more limited foci of the Millennium Development Goals. Alongside initiatives to strengthen public health programmes, the pursuit of universal health coverage hinges upon improving both access and quality worldwide, and thus requires adopting a more comprehensive view—and subsequent provision—of quality health care for all populations, Trends, Inequalities
Abstract

Background A key component of achieving universal health coverage is ensuring that all populations have access to quality health care. Examining where gains have occurred or progress has faltered across and within countries is crucial to guiding decisions and strategies for future improvement. We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) to assess personal health-care access and quality with the Healthcare Access and Quality (HAQ) Index for 195 countries and territories, as well as subnational locations in seven countries, from 1990 to 2016. Methods Drawing from established methods and updated estimates from GBD 2016, we used 32 causes from which death should not occur in the presence of effective care to approximate personal health-care access and quality by location and over time. To better isolate potential effects of personal health-care access and quality from underlying risk factor patterns, we risk-standardised cause-specific deaths due to non-cancers by location-year, replacing the local joint exposure of environmental and behavioural risks with the global level of exposure. Supported by the expansion of cancer registry data in GBD 2016, we used mortality-to-incidence ratios for cancers instead of risk-standardised death rates to provide a stronger signal of the effects of personal health care and access on cancer survival. We transformed each cause to a scale of 0-100, with 0 as the first percentile (worst) observed between 1990 and 2016, and 100 as the 99th percentile (best); we set these thresholds at the country level, and then applied them to subnational locations. We applied a principal components analysis to construct the HAQ Index using all scaled cause values, providing an overall score of 0-100 of personal health-care access and quality by location over time. We then compared HAQ Index levels and trends by quintiles on the Socio-demographic Index (SDI), a summary measure of overall development. As derived from the broader GBD study and other data sources, we examined relationships between national HAQ Index scores and potential correlates of performance, such as total health spending per capita. Findings In 2016, HAQ Index performance spanned from a high of 97.1 (95% UI 95.8-98.1) in Iceland, followed by 96.6 (94.9-97.9) in Norway and 96.1 (94.5-97.3) in the Netherlands, to values as low as 18.6 (13.1-24.4) in the Central African Republic, 19.0 (14.3-23.7) in Somalia, and 23.4 (20.2-26.8) in Guinea-Bissau. The pace of progress achieved between 1990 and 2016 varied, with markedly faster improvements occurring between 2000 and 2016 for many countries in sub-Saharan Africa and southeast Asia, whereas several countries in Latin America and elsewhere saw progress stagnate after experiencing considerable advances in the HAQ Index between 1990 and 2000. Striking subnational disparities emerged in personal health-care access and quality, with China and India having particularly large gaps between locations with the highest and lowest scores in 2016. In China, performance ranged from 91.5 (89.1-936) in Beijing to 48.0 (43.4-53.2) in Tibet (a 43.5-point difference), while India saw a 30.8-point disparity, from 64.8 (59.6-68.8) in Goa to 34.0 (30.3-38.1) in Assam. Japan recorded the smallest range in subnational HAQ performance in 2016 (a 4.8-point difference), whereas differences between subnational locations with the highest and lowest HAQ Index values were more than two times as high for the USA and three times as high for England. State-level gaps in the HAQ Index in Mexico somewhat narrowed from 1990 to 2016 (from a 20.9-point to 17.0-point difference), whereas in Brazil, disparities slightly increased across states during this time (a 17.2-point to 20.4-point difference). Performance on the HAQ Index showed strong linkages to overall development, with high and high-middle SDI countries generally having higher scores and faster gains for non-communicable diseases. Nonetheless, countries across the development spectrum saw substantial gains in some key health service areas from 2000 to 2016, most notably vaccine-preventable diseases. Overall, national performance on the HAQ Index was positively associated with higher levels of total health spending per capita, as well as health systems inputs, but these relationships were quite heterogeneous, particularly among low-to-middle SDI countries. Interpretation GBD 2016 provides a more detailed understanding of past success and current challenges in improving personal health-care access and quality worldwide. Despite substantial gains since 2000, many low-SDI and middle-SDI countries face considerable challenges unless heightened policy action and investments focus on advancing access to and quality of health care across key health services, especially non-communicable diseases. Stagnating or minimal improvements experienced by several low-middle to high-middle SDI countries could reflect the complexities of re-orienting both primary and secondary health-care services beyond the more limited foci of the Millennium Development Goals. Alongside initiatives to strengthen public health programmes, the pursuit of universal health coverage upon improving both access and quality worldwide, and thus requires adopting a more comprehensive view and subsequent provision of quality health care for all populations., Bill & Melinda Gates Foundation. Barbora de Courten is supported by a National Heart Foundation Future Leader Fellowship (100864). Ai Koyanagi’s work is supported by the Miguel Servet contract financed by the CP13/00150 and PI15/00862 projects, integrated into the National R + D + I and funded by the ISCIII —General Branch Evaluation and Promotion of Health Research—and the European Regional Development Fund (ERDF-FEDER). Alberto Ortiz was supported by Spanish Government (Instituto de Salud Carlos III RETIC REDINREN RD16/0019 FEDER funds). Ashish Awasthi acknowledges funding support from Department of Science and Technology, Government of India through INSPIRE Faculty scheme Boris Bikbov has received funding from the European Union’s Horizon 2020 research and innovation programme under Marie Sklodowska-Curie grant agreement No. 703226. Boris Bikbov acknowledges that work related to this paper has been done on the behalf of the GBD Genitourinary Disease Expert Group. Panniyammakal Jeemon acknowledges support from the clinical and public health intermediate fellowship from the Wellcome Trust and Department of Biotechnology, India Alliance (2015–20). Job F M van Boven was supported by the Department of Clinical Pharmacy & Pharmacology of the University Medical Center Groningen, University of Groningen, Netherlands. Olanrewaju Oladimeji is an African Research Fellow hosted by Human Sciences Research Council (HSRC), South Africa and he also has honorary affiliations with Walter Sisulu University (WSU), Eastern Cape, South Africa and School of Public Health, University of Namibia (UNAM), Namibia. He is indeed grateful for support from HSRC, WSU and UNAM. EUI is supported in part by the South African National Research Foundation (NRF UID: 86003). Ulrich Mueller acknowledges funding by the German National Cohort Study grant No 01ER1511/D, Gabrielle B Britton is supported by Secretaría Nacional de Ciencia, Tecnología e Innovación and Sistema Nacional de Investigación de Panamá. Giuseppe Remuzzi acknowledges that the work related to this paper has been done on behalf of the GBD Genitourinary Disease Expert Group. Behzad Heibati would like to acknowledge Air pollution Research Center, Iran University of Medical Sciences (IUMS), Tehran, Iran. Syed Aljunid acknowledges the National University of Malaysia for providing the approval to participate in this GBD Project. Azeem Majeed and Imperial College London are grateful for support from the Northwest London National Insititute of Health Research (NIHR) Collaboration for Leadership in Applied Health Research & Care. Tambe Ayuk acknowledges the Institute of Medical Research and Medicinal Plant Studies for office space provided. José das Neves was supported in his contribution to this work by a Fellowship from Fundação para a Ciência e a Tecnologia, Portugal (SFRH/BPD/92934/2013). João Fernandes gratefully acknowledges funding from FCT–Fundação para a Ciência e a Tecnologia (grant number UID/Multi/50016/2013). Jan-Walter De Neve was supported by the Alexander von Humboldt Foundation. Kebede Deribe is funded by a Wellcome Trust Intermediate Fellowship in Public Health and Tropical Medicine (201900). Kazem Rahimi was supported by grants from the Oxford Martin School, the NIHR Oxford BRC and the RCUK Global Challenges Research Fund. Laith J Abu-Raddad acknowledges the support of Qatar National Research Fund (NPRP 9-040-3-008) who provided the main funding for generating the data provided to the GBD-IHME effort. Liesl Zuhlke is funded by the national research foundation of South Africa and the Medical Research Council of South Africa. Monica Cortinovis acknowledges that work related to this paper has been done on the behalf of the GBD Genitourinary Disease Expert Group. Chuanhua Yu acknowleges support from the National Natural Science Foundation of China (grant number 81773552 and grant number 81273179) Norberto Perico acknowledges that work related to this paper has been done on behalf of the GBD Genitourinary Disease Expert Group. Charles Shey Wiysonge’s work is supported by the South African Medical Research Council and the National Research Foundation of South Africa (grant numbers 106035 and 108571). John J McGrath is supported by grant APP1056929 from the John Cade Fellowship from the National Health and Medical Research Council and the Danish National Research Foundation (Niels Bohr Professorship). Quique Bassat is an ICREA (Catalan Institution for Research and Advanced Studies) research professor at ISGlobal. Richard G White is funded by the UK MRC and the UK Department for International Development (DFID) under the MRC/DFID Concordat agreement that is also part of the EDCTP2 programme supported by the European Union (MR/P002404/1), the Bill & Melinda Gates Foundation (TB Modelling and Analysis Consortium: OPP1084276/OPP1135288, CORTIS: OPP1137034/OPP1151915, Vaccines: OPP1160830), and UNITAID (4214-LSHTM-Sept15; PO 8477-0-600). Rafael Tabarés-Seisdedos was supported in part by grant number PROMETEOII/2015/021 from Generalitat Valenciana and the national grant PI17/00719 from ISCIII-FEDER. Mihajlo Jakovljevic acknowleges contribution from the Serbian Ministry of Education Science and Technological Development of the Republic of Serbia (grant OI 175 014). Shariful Islam is funded by a Senior Fellowship from Institute for Physical Activity and Nutrition, Deakin University and received career transition grants from High Blood Pressure Research Council of Australia. Sonia Saxena is funded by various grants from the NIHR. Stefanos Tyrovolas was supported by the Foundation for Education and European Culture, the Sara Borrell postdoctoral program (reference number CD15/00019 from the Instituto de Salud Carlos III (ISCIII–Spain) and the Fondos Europeo de Desarrollo Regional. Stefanos was awarded with a 6 months visiting fellowship funding at IHME from M-AES (reference no. MV16/00035 from the Instituto de Salud Carlos III). S Vittal Katikreddi was funded by a NHS Research Scotland Senior Clinical Fellowship (SCAF/15/02), the MRC (MC_UU_12017/13 & MC_ UU_12017/15) and the Scottish Government Chief Scientist Office (SPHSU13 & SPHSU15). Traolach S Brugha has received funding from NHS Digital UK to collect data used in this study. The work of Hamid Badali was financially supported by Mazandaran University of Medical Sciences, Sari, Iran. The work of Stefan Lorkowski is funded by the German Federal Ministry of Education and Research (nutriCARD, Grant agreement number 01EA1411A). Mariam Molokhia’s research was supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. We also thank the countless individuals who have contributed to GBD 2016 in various capacities.

Published
2018

50. Global, regional, and national disability-adjusted life-years (DALYs) for 333 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

Author

Abajobir, Amanuel Alemu, Abate, Kalkidan Hassen, Abbafati, Cristiana, Abbas, Kaja M, Abd-Allah, Foad, Abdulkader, Rizwan Suliankatchi, Abdulle, Abdishakur M, Abebo, Teshome Abuka, Abera, Semaw Ferede, Aboyans, Victor, Abu-Raddad, Laith J, Ackerman, Ilana N, Adedeji, Isaac A, Adetokunboh, Olatunji, Afshin, Ashkan, Aggarwal, Rakesh, Agrawal, Sutapa, Agrawal, Anurag, Ahmed, Muktar Beshir, Aichour, Miloud Taki Eddine, Aichour, Amani Nidhal, Aichour, Ibtihel, Aiyar, Sneha, Akinyemiju, Tomi F, Akseer, Nadia, Al Lami, Faris Hasan, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alam, Noore, Alam, Tahiya, Alasfoor, Deena, Alene, Kefyalew Addis, Ali, Raghib, Alizadeh-Navaei, Reza, Alkaabi, Juma M, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Allen, Christine, Al-Maskari, Fatma, AlMazroa, Mohammad AbdulAziz, Al-Raddadi, Rajaa, Alsharif, Ubai, Alsowaidi, Shirina, Althouse, Benjamin M, Altirkawi, Khalid A, Alvis-Guzman, Nelson, Amare, Azmeraw T, Amini, Erfan, Ammar, Walid, Amoako, Yaw Ampem, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Anwari, Palwasha, Ärnlöv, Johan, Arora, Megha, Artaman, Al, Aryal, Krishna Kumar, Asgedom, Solomon W, Atey, Tesfay Mehari, Atnafu, Niguse Tadele, Avila-Burgos, Leticia, Avokpaho, Euripide Frinel G Arthur, Awasthi, Ashish, Awasthi, Shally, Azarpazhooh, Mahmoud Reza, Azzopardi, Peter, Babalola, Tesleem Kayode, Bacha, Umar, Badawi, Alaa, Balakrishnan, Kalpana, Bannick, Marlena S, Barac, Aleksandra, Barker-Collo, Suzanne L, Bärnighausen, Till, Barquera, Simon, Barrero, Lope H, Basu, Sanjay, Battista, Robert, Battle, Katherine E, Baune, Bernhard T, Bazargan-Hejazi, Shahrzad, Beardsley, Justin, Bedi, Neeraj, Béjot, Yannick, Bekele, Bayu Begashaw, Bell, Michelle L, Bennett, Derrick A, Bennett, James R, Bensenor, Isabela M, Benson, Jennifer, Berhane, Adugnaw, Berhe, Derbew Fikadu, Bernabé, Eduardo, Betsu, Balem Demtsu, Beuran, Mircea, Beyene, Addisu Shunu, Bhansali, Anil, Bhatt, Samir, Bhutta, Zulfiqar A, Biadgilign, Sibhatu, Bicer, Burcu Kucuk, Bienhoff, Kelly, Bikbov, Boris, Birungi, Charles, Biryukov, Stan, Bisanzio, Donal, Bizuayehu, Habtamu Mellie, Blyth, Fiona M, Boneya, Dube Jara, Bose, Dipan, Bou-Orm, Ibrahim R, Bourne, Rupert R A, Brainin, Michael, Brayne, Carol, Brazinova, Alexandra, Breitborde, Nicholas J K, Briant, Paul S, Britton, Gabrielle, Brugha, Traolach S, Buchbinder, Rachelle, Bulto, Lemma Negesa Bulto, Bumgarner, Blair R, Butt, Zahid A, Cahuana-Hurtado, Lucero, Cameron, Ewan, Campos-Nonato, Ismael Ricardo, Carabin, Hélène, Cárdenas, Rosario, Carpenter, David O, Carrero, Juan Jesus, Carter, Austin, Carvalho, Felix, Casey, Daniel, Castañeda-Orjuela, Carlos A, Castle, Chris D, Catalá-López, Ferrán, Chang, Jung-Chen, Charlson, Fiona J, Chaturvedi, Pankaj, Chen, Honglei, Chibalabala, Mirriam, Chibueze, Chioma Ezinne, Chisumpa, Vesper Hichilombwe, Chitheer, Abdulaal A, Chowdhury, Rajiv, Christopher, Devasahayam Jesudas, Ciobanu, Liliana G, Cirillo, Massimo, Colombara, Danny, Cooper, Leslie Trumbull, Cooper, Cyrus, Cortesi, Paolo Angelo, Cortinovis, Monica, Criqui, Michael H, Cromwell, Elizabeth A, Cross, Marita, Crump, John A, Dadi, Abel Fekadu, Dalal, Koustuv, Damasceno, Albertino, Dandona, Lalit, Dandona, Rakhi, das Neves, José, Davitoiu, Dragos V, Davletov, Kairat, de Courten, Barbora, De Leo, Diego, De Steur, Hans, Defo, Barthelemy Kuate, Degenhardt, Louisa, Deiparine, Selina, Dellavalle, Robert P, Deribe, Kebede, Deribew, Amare, Des Jarlais, Don C, Dey, Subhojit, Dharmaratne, Samath D, Dhillon, Preet K, Dicker, Daniel, Djalainia, Shirin, Do, Huyen Phuc, Dokova, Klara, Doku, David Teye, Dorsey, E Ray, dos Santos, Kadine Priscila Bender, Driscoll, Tim R, Dubey, Manisha, Duncan, Bruce Bartholow, Ebel, Beth E, Echko, Michelle, El-Khatib, Ziad Ziad, Enayati, Ahmadali, Endries, Aman Yesuf, Ermakov, Sergey Petrovich, Erskine, Holly E, Eshetie, Setegn, Eshrati, Babak, Esteghamati, Alireza, Estep, Kara, Fanuel, Fanuel Belayneh Bekele, Farag, Tamer, Farinha, Carla Sofia e Sa, Faro, André, 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Subjects
Male, Dánarmein, AUSTRALIA, GBD, disability-adjusted life-years (DALYs), Heilsufar, Lífslíkur, Epidemiology, Life expectancy, Diseases, Global Health, THERAPY, Global Burden of Disease, Residence Characteristics, Fullorðnir, Cause of Death, Medicine and Health Sciences, Psychology, Konur, Aged, 80 and over, Tölfræði, PLASMODIUM-FALCIPARUM, Aldraðir, Sjúkdómar, Medicine (all), Fatlaðir, Men, Þjóðir, 11 Medical And Health Sciences, ASSOCIATION, Middle Aged, Health policy, PREVALENCE, Sálfræði, disability-adjusted life-years (DALYs), Female, Lýðheilsa, Quality-Adjusted Life Years, Life Sciences & Biomedicine, Global Health Metrics, Adult, AFRICA, Quality of life, People with disabilities, GBD, WEIGHTS, Social ecology, Lífsgæði, Communicable Diseases, World health/statistics, Age Distribution, Life Expectancy, Medicine, General & Internal, SDG 3 - Good Health and Well-being, General & Internal Medicine, Heilbrigðisstefna, Humans, Adults, Disabled Persons, Women, Sex Distribution, Mortality, Noncommunicable Diseases, Aged, Science & Technology, Faraldsfræði, MORTALITY, Wounds and injuries, EPIDEMIOLOGIC TRANSITION, HIV, Áverkar, Karlar, Wounds and Injuries, Félagshagfræði, Older people
Abstract

Correction in: LANCET Volume: 390 Issue: 10106 Pages: E38-E38 Published: OCT 28 2017, Background Measurement of changes in health across locations is useful to compare and contrast changing epidemiological patterns against health system performance and identify specific needs for resource allocation in research, policy development, and programme decision making. Using the Global Burden of Diseases, Injuries, and Risk Factors Study 2016, we drew from two widely used summary measures to monitor such changes in population health: disability-adjusted life-years (DALYs) and healthy life expectancy (HALE). We used these measures to track trends and benchmark progress compared with expected trends on the basis of the Socio-demographic Index (SDI). Methods We used results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 for all-cause mortality, cause-specific mortality, and non-fatal disease burden to derive HALE and DALYs by sex for 195 countries and territories from 1990 to 2016. We calculated DALYs by summing years of life lost and years of life lived with disability for each location, age group, sex, and year. We estimated HALE using age-specific death rates and years of life lived with disability per capita. We explored how DALYs and HALE differed from expected trends when compared with the SDI: the geometric mean of income per person, educational attainment in the population older than age 15 years, and total fertility rate. Findings The highest globally observed HALE at birth for both women and men was in Singapore, at 75.2 years (95% uncertainty interval 71.9-78.6) for females and 72.0 years (68.8-75.1) for males. The lowest for females was in the Central African Republic (45.6 years [42.0-49.5]) and for males was in Lesotho (41.5 years [39.0-44.0]). From 1990 to 2016, global HALE increased by an average of 6.24 years (5.97-6.48) for both sexes combined. Global HALE increased by 6.04 years (5.74-6.27) for males and 6.49 years (6.08-6.77) for females, whereas HALE at age 65 years increased by 1.78 years (1.61-1.93) for males and 1.96 years (1.69-2.13) for females. Total global DALYs remained largely unchanged from 1990 to 2016 (-2.3% [-5.9 to 0.9]), with decreases in communicable, maternal, neonatal, and nutritional (CMNN) disease DALYs offset by increased DALYs due to non-communicable diseases (NCDs). The exemplars, calculated as the five lowest ratios of observed to expected age-standardised DALY rates in 2016, were Nicaragua, Costa Rica, the Maldives, Peru, and Israel. The leading three causes of DALYs globally were ischaemic heart disease, cerebrovascular disease, and lower respiratory infections, comprising 16.1% of all DALYs. Total DALYs and age-standardised DALY rates due to most CMNN causes decreased from 1990 to 2016. Conversely, the total DALY burden rose for most NCDs; however, age-standardised DALY rates due to NCDs declined globally. Interpretation At a global level, DALYs and HALE continue to show improvements. At the same time, we observe that many populations are facing growing functional health loss. Rising SDI was associated with increases in cumulative years of life lived with disability and decreases in CMNN DALYs offset by increased NCD DALYs. Relative compression of morbidity highlights the importance of continued health interventions, which has changed in most locations in pace with the gross domestic product per person, education, and family planning. The analysis of DALYs and HALE and their relationship to SDI represents a robust framework with which to benchmark location-specific health performance. Country-specific drivers of disease burden, particularly for causes with higher-than-expected DALYs, should inform health policies, health system improvement initiatives, targeted prevention efforts, and development assistance for health, including financial and research investments for all countries, regardless of their level of sociodemographic development. The presence of countries that substantially outperform others suggests the need for increased scrutiny for proven examples of best practices, which can help to extend gains, whereas the presence of underperforming countries suggests the need for devotion of extra attention to health systems that need more robust support., Bill & Melinda Gates Foundation

Published
2017

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