389 results on '"Barquera, S"'
Search Results
52. Pitfalls of the self-regulation of advertisements directed at children on Mexican television.
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Théodore, F. L., Tolentino‐Mayo, L., Hernández‐Zenil, E., Bahena, L., Velasco, A., Popkin, B., Rivera, J. A., and Barquera, S.
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ADVERTISING ,FOOD habits ,MARKETING ,TELEVISION ,PROFESSIONAL standards - Abstract
Background There are no academic studies that characterize advertisements directed at children from the companies that signed the self-regulation. Objective The aim of this paper was to assess the extent and nature of food advertisements and the persuasive techniques used to market unhealthy food and beverages (UFB) to children, by signatory companies of self-regulation. Methods From December 2012 to April 2013, 600 h of programming were recorded on the four broadcast public television channels in Mexico with the highest rating nationwide. Marketing aimed at children directly (broadcast on children's programmes or advertisements with a specific appeal to children) or indirectly (aimed at other target audiences with messages or scenes that link children to the product) were considered. Results About 74.9% (2148) of the total food and beverage advertisements tried to influence children directly and indirectly. Companies, which had signed the self-regulation, focused 92.7% of their advertisements on UFB. Of the total number, 23.9% were aimed at children, 7.1% at adolescents, 12.5% at parents and 56.2% at the general public. Most of these advertisements were broadcast on movies (29.8%), cartoons (18%), soap operas (17.6%), entertainment shows (17.2%) and sports programs (6.4%). Conclusion Despite the self-regulation of television marketing, children were surrounded by UFB advertisements. Signatory companies influence children indirectly by targeting other audiences and by marketing during family television programs, which are also watched by children. [ABSTRACT FROM AUTHOR]
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- 2017
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53. Child overweight and obesity are associated with reduced executive cognitive performance and brain alterations: a magnetic resonance imaging study in Mexican children
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Bauer, C. C. C., primary, Moreno, B., additional, González-Santos, L., additional, Concha, L., additional, Barquera, S., additional, and Barrios, F. A., additional
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- 2014
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54. Reliability of the international physical activity questionnaire among Mexican adults
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Medina, C., primary, Barquera, S., additional, and Janssen, I., additional
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- 2012
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55. Recommendations for healthier hydration: addressing the public health issues of obesity and type 2 diabetes
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Armstrong, L. E., primary, Barquera, S., additional, Duhamel, J. ‐F., additional, Hardinsyah, R., additional, Haslam, D., additional, and Lafontan, M., additional
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- 2012
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56. Erratum: The overlap of overweight and anaemia among women in three countries undergoing the nutrition transition
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Eckhardt, C L, primary, Torheim, L E, additional, Monterrubio, E, additional, Barquera, S, additional, and Ruel, M T, additional
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- 2007
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57. The overlap of overweight and anaemia among women in three countries undergoing the nutrition transition
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Eckhardt, C L, primary, Torheim, L E, additional, Monterrubio, E, additional, Barquera, S, additional, and Ruel, M T, additional
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- 2007
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58. Diabetes Prevalence and Mortality Rates in Mexicans, Mexican-American and us Total Population
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Lazo, M, primary, Franco, M, additional, Durazo-Arvizu, R.A, additional, Barquera, S, additional, and Cooper, R, additional
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- 2006
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59. Cardiovascular disease surveillance in Mexicans and Mexican Americans: a tale of two countries.
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Durazo-Arvizu RA, Barquera S, Lazo-Elizondo M, Franco M, and Cooper RS
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- 2008
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60. Epidemiologic Panorama of Stomach Cancer Mortality in Mexico
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Tovar-Guzman, V., Hernandez-Giron, C., Barquera, S., Rodriguez-Salgado, N., and Lopez-Carrillo, L.
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- 2001
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61. Policy networks and competing interests in the development of the Mexican sugary sweetened beverages tax
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Carriedo, A, Cairney, P, Barquera, S, Hawkins, Benjamin, and Apollo - University of Cambridge Repository
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Introduction: Sugar taxes threaten the business models and profits of the food and beverage industry (F&BI), which has sought to avert, delay, or influence the content of health taxes globally. Mexico introduced a sugar-sweetened beverage (SSB) tax in 2014 and other regulatory measures to improve population diets. This paper examines how policy networks emerged within and affected the development and implementation of the Mexican SSB tax. Methods: This qualitative study analyses 31 interviews conducted with key stakeholders involved in the soda tax policy process and 145 documents, including grey literature and peer-reviewed literature. The policy network approach was used to map contacts, interconnections, relationships and links between the state, civil society and commercial actors involved in the SSB tax. These findings were used to examine the responsiveness, participation, and accountability of the soda tax policy formulation. Results: Complex interconnections were identified between state and non-state actors. These included advisory relationships, financial collaborations, and personal connections between those in high-level positions. Relationships between the government and the F&BI were not always disclosed. International organizations and academics were identified as key financial or technical supporters of the tax. Key governance principles of participation, responsiveness and accountability were undermined by some of these relationships, including the participation of non-state actors in policy development and the powerful role of the F&BI in evaluation and monitoring. Conclusion: This case study exemplifies the importance of links and networks between actors in health policymaking. The F&BI influence endangers the primary aim of the SSB tax to protect health. The identified links highlight the normalisation of connections among actors with competing aims and interests toward health, thereby jeopardising attempts to tackle obesity rates.
62. Prevention of cardiovascular disease based on lipid lowering treatment: A challenge for the Mexican health system | Prevención de la enfermedad cardiovascular basada en tratamiento hipolipemiante: Un reto para el sistema de salud de México
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Gómez-Pérez, F. J., Rojas, R., Salvador Villalpando, Barquera, S., Rull, J., and Aguilar-Salinas, C. A.
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hypercholesterolemia ,México ,lcsh:Public aspects of medicine ,cholesterol ,lcsh:RA1-1270 ,hipercolesterolemia ,colesterol ,triglicéridos ,LDL ,hypoalphalipoproteinemia ,colesterol HDL ,colesterol LDL ,cholesterol, HDL ,hipoalfalipoproteinemia ,triglycerides ,Mexico - Abstract
OBJECTIVE: To estimate the percentage of Mexican adults that may require lipid-lowering treatment according to National Cholesterol Education Program-III guidelines, using data from the National Health and Nutrition Survey 2006 (ENSANut 2006). MATERIAL AND METHODS: Information was obtained from 4 040 subjects aged 20 to 69 years, studied after a 9 to 12 hours fast. RESULTS: A cardiovascular risk equivalent was found in 13.8% and >2 risk factors were present in 31.5% of the population. LDL-C concentrations were above the treatment goal in 70% of the high-risk group and in 38.6% of subjects with >2 risk factors. Nearly 12 million Mexicans should be taught how to change their lifestyles and close to 8 million individuals require drug therapy to decrease their cardiovascular risk. CONCLUSIONS: Thirty percent of Mexican adults require some form of lipid-lowering treatment (lifestyle modifications in 36.25%, drug therapy in 24.19%).OBJETIVO: Calcular el porcentaje de adultos que requiere tratamiento hipolipemiante de acuerdo con las recomendaciones del Programa Nacional de Educación en Colesterol-III, usando los datos de la Encuesta Nacional de Salud y Nutrición 2006. MATERIAL Y MÉTODOS: Se incluyeron 4040 individuos con edad entre 20 y 69 años estudiados bajo un ayuno de 9 a 12 horas. RESULTADOS: Un equivalente de enfermedad cardiovascular fue identificado en 13.8% de los participantes. El 31.5% de la población tenía >2 factores de riesgo cardiovascular. La concentración de colesterol LDL estuvo arriba de la meta terapéutica en 70% de los casos con alto riesgo cardiovascular y en el 38.6% de los sujetos con >2 factores de riesgo. Cerca de 12 millones de mexicanos deben modificar su estilo de vida para reducir su concentración de colesterol LDL. Casi 8 millones califican para recibir tratamiento farmacológico. CONCLUSIONES: Una tercera parte de los adultos requiere alguna forma de tratamiento hipolipemiante (cambios en el estilo de vida: 36.25%, medicamentos: 24.19%).
63. Neural network for dispersion strengthened microalloyed steel sour corrosion from electrochemical impedance spectroscopy laboratory measurements
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Colorado, D., Serna-Barquera, S., Hernández, J. A., Barrera-Rojas, Y., Mónica Arely Lucio García, and Campillo, B.
64. Prevalence of obesity and metabolic syndrome components in Mexican adults without type 2 diabetes or hypertension
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Rosalba Rojas, Aguilar-Salinas, C. A., Jiménez-Corona, A., Gómez-Pérez, F. J., Barquera, S., and Lazcano-Ponce, E.
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Adult ,Male ,Metabolic Syndrome ,Salud ,waist circumference ,metabolic syndrome ,Young Adult ,Diabetes Mellitus, Type 2 ,Hypertension ,Prevalence ,Humans ,Female ,Obesity ,Mexico - Abstract
To describe the number of Mexican adults with undiagnosed diabetes and arterial hypertension and their association with obesity. Material and Methods. The study included a sub-sample of 6 613 subjects aged 20 years or more who participated in the 2006 National Health and Nutrition Survey (ENSANUT 2006). Subjects with a previous diagnosis of diabetes or hypertension (n=1 861) were excluded. Prevalences and standard errors were estimated, taking into account the complex sample design. Results. 6.4 million adults have obesity and undiagnosed impaired fasting glucose. Almost two million more have fasting glucose levels diagnostic for diabetes. As for arterial blood pressure, 5.4 million adults had prehypertension. Another 5.4 million adults had blood pressure levels suggestive of probable hypertension. A total of 21.4 million Mexican adults with obesity had at least one further component of the metabolic syndrome. Conclusions. A large proportion of adults with obesity-related metabolic comorbidities remains undiagnosed in Mexico.
65. Pharmacological treatment guidelines for the control of arterial hypertension 2009: Addendum to NOM 030,Guía de tratamiento farmacológico para el control de la hipertensión arterial 2009. Addendum a la NOM 030
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Villalobos, J. Á C., Ávila, M. H., Fernández, M. Á L., Moguel, J. O., Barreiro, L. A. D., Gilabert, C. R., López, M. F., Muñoz, E. G. C., Paris, J. V., Parra Carrillo, J. Z., Martínez, F. J. G., Barriguete-Meléndez, J. A., Guillermo Ceballos, Alva, J. C. N., Barquera, S., Aguilar Salinas, C. A., Chávez, A. G., Pliego, J. G., Lucas, C. H. Á, Esqueda, A. L., and García, H. R. H.
66. Manual of pharmacological treatment and systemic arterial hypertension control for the primary care level,Manual de tratamiento farmacológico y control de la hipertensión arterial sistémica para el primer nivel de atención
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Hernández Y Hernández, H., Meaney Mendiolea, E., Meaney Martínez, A., Hernández Ávila, M., Lezama Fernández, M. Á, Aguilar Salinas, C. A., Barriguete-Meléndez, J. A., Lara Esqueda, A., Barquera, S., González Chávez, A., Díaz Y Díaz, E., Díaz Barreiro, L. A., Navarro Robles, J., Guillermo Ceballos, Solache Ortiz, G., and Hernández Santamaría, I.
67. Prevalence of dyslipidemias in the Mexican National Health and Nutrition Survey 2006 | Prevalencia de las dislipidemias en la Encuesta Nacional de Salud y Nutrición 2006
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Aguilar-Salinas, C. A., Gómez-Pérez, F. J., Rull, J., Salvador Villalpando, Barquera, S., and Rojas, R.
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México ,lcsh:Public aspects of medicine ,cholesterol ,lcsh:RA1-1270 ,colesterol ,triglicéridos ,hypoalphalipoproteinemia ,colesterol HDL ,colesterol LDL ,cholesterol, LDL ,cholesterol, HDL ,hipoalfalipoproteinemia ,triglycerides ,Mexico - Abstract
OBJECTIVE: To describe the prevalence of lipid abnormalities found in the Mexican National Health and Nutrition Survey 2006 (ENSANut 2006). MATERIAL AND METHODS: Information was obtained from 4 040 subjects aged 20 to 69 years, studied after a 9- to 12-hour fast. RESULTS: Median lipid concentrations were: cholesterol 198.5 mg/dl, triglycerides 139.6 mg/dl, HDL-cholesterol 39.0 mg/dl, non-HDL-cholesterol 159.5 mg/dl and LDL-cholesterol 131.5 mg/dl. The most frequent abnormality was HDL-cholesterol below 40 mg/dl with a prevalence of 60.5% (95%CI 58.2-62.8%). Hypercholesterolemia (> 200 mg/dl) had a frequency of abnormality of 43.6% (95%CI 41.4-46.0%). Only 8.6% of the hypercholesterolemic subjects knew their diagnosis. Hypertriglyceridemia (> 150 mg/dl) was observed in 31.5% (IC 95% 29.3-33.9%) of the population. CONLUSIONS: The ENSANUT 2006 data confirm that the prevalence of hypoalphalipoproteinemia and other forms of dyslipidemia in Mexican adults is very high.OBJETIVO: Presentar la prevalencia de las dislipidemias observada en la Encuesta Nacional de Salud y Nutrición 2006 (ENSANUT 2006). MATERIAL Y MÉTODOS: Se incluyeron 4040 individuos con edad entre 20 y 69 años estudiados bajo un ayuno de 9 a 12 horas. RESULTADOS: Las concentraciones medias de los lípidos sanguíneos fueron colesterol 198.5 mg/dl, triglicéridos 139.6 mg/dl, colesterol HDL 39.0 mg/dl, colesterol noHDL 159.5 mg/dl y colesterol LDL 131.5 mg/dl. La anormalidad más común fue la hipoalfalipoproteinemia (colesterol HDL< 40 mg/dl); su prevalencia fue 60.5% (IC95% 58.2-62.8%). La hipercolesterolemia (colesterol > 200 mg/dl) fue la segunda anormalidad en frecuencia, con 43.6% (IC95% 41.4-46.0%). Sólo el 8.6% de los casos conocía su diagnóstico. La hipertrigliceridemia (> 150 mg/dl) fue observada en 31.5% (IC95% 29.3-33.9%) de la población en estudio. CONCLUSIONES: Los datos de la ENSANUT 2006 confirman que la prevalencia de hipoalfalipoproteinemia y otras formas de dislipidemia es muy alta en los adultos mexicanos.
68. Pharmacological treatment guidelines for the control of arterial hypertension 2009: Addendum to NOM 030 | Guía de tratamiento farmacológico para el control de la hipertensión arterial 2009. Addendum a la NOM 030
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Villalobos, J. Á C., Ávila, M. H., Fernández, M. Á L., Moguel, J. O., Barreiro, L. A. D., Gilabert, C. R., López, M. F., Muñoz, E. G. C., Paris, J. V., Parra Carrillo, J. Z., Martínez, F. J. G., Barriguete-Meléndez, J. A., Ceballos, G., Alva, J. C. N., Barquera, S., Aguilar Salinas, C. A., Chávez, A. G., Pliego, J. G., Lucas, C. H. Á, Esqueda, A. L., and García, H. R. H.
69. I. Integrated summary: The Mexican Official Standard NOM-030-SSA2-2009, for the prevention, detection, diagnosis, treatment and control of systemic arterial hypertension,I. Resumen integrado: Norma Oficial Mexicana NOM-030-SSA2-2009, para la prevención, detección, diagnóstico, tratamiento y control de la hipertensión arterial sistémica
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Hernández Y Hernández, H., Díaz Y Díaz, E., Meaney Mendiolea, E., Meaney Martínez, A., Hernández Ávila, M., Lezana Fernández, M. Á, Barriguete-Meléndez, J. A., Mancha Moctezuma, C., Ortiz Solís, G. R., León Farías, A. G., Lara Esqueda, A., Barquera, S., González Chávez, A., Díaz Barreiro, L. A., Guillermo Ceballos, Hernández García, H. R., Hernández Santamaría, I., Navarro Robles, J., Rodríguez Gilabert, C., Rubio Guerra, A. F., Solache Ortiz, G., and Verdejo París, J.
70. C-reactive protein concentrations in Mexican men and women: High prevalence of a cardiovascular risk factor,Concentraciones de proteína C reactiva en adultos mexicanos: Alta prevalencia de un factor de riesgo cardiovascular
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Mario Flores, Barquera, S., Carrión, C., Rojas, R., Villalpando, S., Olaiz-Fernández, G., and González-Villalpando, C.
71. Characterizing the epidemiological transition in Mexico: national and subnational burden of diseases, injuries, and risk factors.
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Stevens G, Dias RH, Thomas KJ, Rivera JA, Carvalho N, Barquera S, Hill K, Ezzati M, Stevens, Gretchen, Dias, Rodrigo H, Thomas, Kevin J A, Rivera, Juan A, Carvalho, Natalie, Barquera, Simón, Hill, Kenneth, and Ezzati, Majid
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Background: Rates of diseases and injuries and the effects of their risk factors can have substantial subnational heterogeneity, especially in middle-income countries like Mexico. Subnational analysis of the burden of diseases, injuries, and risk factors can improve characterization of the epidemiological transition and identify policy priorities.Methods and Findings: We estimated deaths and loss of healthy life years (measured in disability-adjusted life years [DALYs]) in 2004 from a comprehensive list of diseases and injuries, and 16 major risk factors, by sex and age for Mexico and its states. Data sources included the vital statistics, national censuses, health examination surveys, and published epidemiological studies. Mortality statistics were adjusted for underreporting, misreporting of age at death, and for misclassification and incomparability of cause-of-death assignment. Nationally, noncommunicable diseases caused 75% of total deaths and 68% of total DALYs, with another 14% of deaths and 18% of DALYs caused by undernutrition and communicable, maternal, and perinatal diseases. The leading causes of death were ischemic heart disease, diabetes mellitus, cerebrovascular disease, liver cirrhosis, and road traffic injuries. High body mass index, high blood glucose, and alcohol use were the leading risk factors for disease burden, causing 5.1%, 5.0%, and 7.3% of total burden of disease, respectively. Mexico City had the lowest mortality rates (4.2 per 1,000) and the Southern region the highest (5.0 per 1,000); under-five mortality in the Southern region was nearly twice that of Mexico City. In the Southern region undernutrition and communicable, maternal, and perinatal diseases caused 23% of DALYs; in Chiapas, they caused 29% of DALYs. At the same time, the absolute rates of noncommunicable disease and injury burdens were highest in the Southern region (105 DALYs per 1,000 population versus 97 nationally for noncommunicable diseases; 22 versus 19 for injuries).Conclusions: Mexico is at an advanced stage in the epidemiologic transition, with the majority of the disease and injury burden from noncommunicable diseases. A unique characteristic of the epidemiological transition in Mexico is that overweight and obesity, high blood glucose, and alcohol use are responsible for larger burden of disease than other noncommunicable disease risks such as tobacco smoking. The Southern region is least advanced in the epidemiological transition and suffers from the largest burden of ill health in all disease and injury groups. [ABSTRACT FROM AUTHOR]- Published
- 2008
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72. Nutrition transition in Mexico and in other Latin American countries.
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Rivera JA, Barquera S, González-Cossío T, Olaiz G, and Sepúlveda J
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- 2004
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73. Factors associated with physical activity among Mexican women of childbearing age.
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Hernández B, de Haene J, Barquera S, Monterrubio E, Rivera J, Shamah T, Sepúlveda J, Haas J, and Campirano F
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OBJECTIVE: To document the practice of light and heavy physical activities, especially sports and exercise, among women from 12 to 49 years old in Mexico, and to evaluate the association that that has with some sociodemographic characteristics. METHODS: A sample of 2 367 women 12 to 49 years old living in Mexico in 1999 was studied through secondary analysis of data from Mexico's 1999 National Nutrition Survey (Encuesta Nacional de Nutricion). The Survey used a clustered stratified multistage sampling scheme, with a final sample of 21 000 homes in the entire country. A questionnaire was used to evaluate the time that the women spent on various forms of physical activity, with the activity measured on a scoring scale in terms of metabolic equivalents (METs). The dependent variables in the study were the time spent on heavy physical activities (those that require an energy expenditure of at least 5 METs/hour) and the time devoted to light or sedentary activities (such as sitting while on the job or elsewhere; watching television, a video, a movie, or a theater presentation; or sleeping). The independent variables were age, schooling, parity, region of the country, area of residence (urban or rural), socioeconomic level (measured through an index prepared based on housing conditions and household possessions), and marital status. The association between the independent variables and practicing sports was evaluated, and gross odds ratios (ORs) were calculated, with 95% confidence intervals (CIs). In order to identify the association between practicing sports and the independent variables a logistic regression model was used, adjusted for the effects of possible confounding variables. Adjustments were also made in the probability of a woman's being selected for the sample, using a weighting factor. In addition, adjustments were made to control for the design effect produced by the grouping of the observations in the sample, using the 'svy' complex-samples routine of the Stata version 7.0 statistical analysis computer software. RESULTS: The 2 367 women whose information was analyzed spent an average of 0.08 hours per day practicing sports and 1.25 hours per day on heavy physical activities. Only 16% of the women reported that they regularly practiced some sport. After adjusting for all the independent variables, the women older than 30 years had a lower OR of practicing sports in comparison to women who were 20 years of age or less (OR = 0.53; 95% CI: 0.33 to 0.84), as was also true for women 21-30 years old (OR = 0.35; 95% CI: 0.23 to 0.54). Having the highest level of schooling and not having had children were both directly associated with practicing a sport. While the area of residence (urban or rural), marital status, and socioeconomic level showed differences among the groups, such differences were not significant after adjusting for the other study variables. In terms of physical activity measured in METs, the time spent on sports made up 10% of the total for heavy activity and 0.7% of the overall total. In terms of the possibility of being among the 10% of the women who expended the fewest METs per day, that was more likely for women under 21 years of age than it was for women 31 or older, and it was also more likely for women who had a primary level of schooling than for women with a secondary education. CONCLUSIONS: This study showed that practicing sports is not a frequent form of physical activity among women of childbearing age in Mexico, especially those who are over 20 years of age and those with a low level of schooling. This situation could contribute to increases in the prevalence of obesity and chronic diseases. [ABSTRACT FROM AUTHOR]
- Published
- 2003
74. Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980–2017: a systematic analysis for the Global Burden of Disease Study 2017
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Roth, Gregory A., Collaborotors, G. B. D.Causes Death, Abate, Degu, Abate, Kalkidan Hassen, Abay, Solomon M., Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Load, Abdela, Jemal, Abdelalim, Ahmed, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Haftom Temesgen, Abebe, Molla, Abebe, Zegeye, Abejie, Ayenew Negesse, Abera, Semaw F., Abil, Olifan Zewdie, Abraha, Haftom Niguse, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Adamu, Abdu A., Adebayo, Oladimeji, Adedoyin, Rufus Adesoji, Adekanmbi, Victor, Adookunboh, Olatunii, Adhena, Beyene Meressa, Adib, Mina G., Admasie, Aniha, Afshin, Ashkan, Agarwal, Gina, Agesa, Karelia M., Agrawal, Anurag, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Melidi, Ahmed, Muktar Beshir, Ahmed, Sayent, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Fddine, Akbari, Mohammad Esmaeil, Akinyeniti, Rufus Olusola, Akseer, Nadia, Al-Aly, Ziyad, Al-Eyadhy, Ayman, Al-Raddadi, Rajaa M., Alandab, Fares, Alam, Khurshid, Alam, Tahiya, Alebel, Animut, Alene, Kefyalew Addis, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, Francois, Allebeck, Peter, Alonso, Jordi, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T., Aminde, Leopold N., Amini, Erfan, Ammar, Walid, Amoako, Yaw Ampern, Anber, Nahla Hamed, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Ansari, Hossein, Aniha, Mustafa Geleto, Antonio, Carl Abelardo T., Anwari, Palwasha, Aremu, Olatunde, Arnlov, Johan, Arora, Amit, Arora, Monika, Artaman, Al, Aryal, Krishna K., Asayesh, Hamid, Asfaw, Ephremi Tsegay, Ataro, Zerihun, Atique, Suleman, Atre, Sachin R., Ausloos, Marcel, Avokpaho, Euripide F. G. A., Awasthi, Ashish, Quintattilla, Beatriz Paulina Ayala, Ayele, Yohanes, Ayer, Rakesh, Azzopardi, Peter S., Babazadeh, Arefeh, Bacha, Umar, Badali, Hamid, Badawi, Alaa, Bali, Ayele Geleto, Ballesteros, Katherine E., Banach, Maciej, Banerjee, Kajori, Bannick, Marlena S., Banoub, Joseph Adel Mattar, Barboza, Miguel A., Barker-Collo, Suzanne Lyu, Barnighausen, Till Winfried, Barquera, Simon, Barrero, Lope, Bassat, Quique, Base, Sanjay, Baune, Bernhard T., Baynes, Habtamu Wondifraw, Bazargan-Hejazi, Shahrzad, Beth, Neeraj, Beghi, Ettore, Behzadifar, Masoud, Behzadifar, Mcysam, Bejot, Yannick, Bekele, Bayu Begashaw, Belacliew, Abate Bekele, Belay, Ezra, Belay, Yihalem Abebe, Bell, Michelle L., Bello, Aminu K., Bennett, Derrick A., Bensenor, Isabela M., Berman, Adam F., Bernabe, Eduardo, Bernstein, Robert S., Bertolacci, Gregory J., Beuran, Mircea, Beyranvand, Tina, Bhalla, Ashish, Bhattarai, Suraj, Bhaumik, Sounayadeeep, Bhutta, Zulfiqar A., Biadgo, Belete, Biehl, Molly H., Bijani, Ali, Bikbov, Boris, Bilano, Ver, Bililign, Nigus, Bin Sayeed, Muhammad Shandaat, Bisanzio, Donal, Biswas, Tuhin, Blacker, Brigitte F., Basara, Berrak Bora, Borschmann, Rohan, Bosetti, Cristina, Bozorgmehr, Kayvan, Brady, Oliver J., Brant, Luisa C., Brayne, Carol, Brazinova, Alexandra, Breitborde, Nicholas J. K., Brenner, Hermann, Briant, Paul Svitil, Britton, Gabrielle, Brugha, Traolach, Busse, Reinhard, Butt, Zahid A., Callender, Charlton S. K. H., Campos-Nonato, Ismael R., Rincon, Julio Cesar Canapuzano, Cano, Jorge, Car, Mate, Cardenas, Rosario, Carreras, Giulia, Carrero, Juan J., Carter, Austin, Carvalho, Felix, Castaneda-Orjuela, Carlos A., Rivas, Jacqueline Castillo, Castle, Chris D., Castro, Clara, Castro, Franz, Catala-Lopez, Ferran, Cerin, Ester, Chaiah, Yazan, Chang, Jung -Chen, Chanson, Fiona J., Chaturvedi, Pankaj, Chiang, Peggy Pei-Chia, Chimed-Ochir, Odgerel, Chisumpa, Vesper Hichilombwe, Chitheet, Abdulaal, Chowdhury, Rajiv, Christensen, Hanne, Christopher, Devasahayam J., Chiang, Sheng-Chia, Cicuttini, Flavia M., Ciobanu, Liliana G., Cirillo, Massimo, Cohen, Aaron J., Cooper, Leslie Trumbull, Cortesi, Paolo Angelo, Cortinovis, Monica, Cousin, Ewerton, Cowie, Benjamin C., Criqui, Michael H., Cromwell, Elizabeth A., Crowe, Christopher Stephen, Crump, John A., Cunningham, Matthew, Daba, Alemneh Kabeta, Dadi, Abel Fekadu, Dandona, Lalit, Dandona, Rakhi, Dang, Anh Kim, Dargan, Paul I., Daryani, Ahmad, Das, Siddharth K., Das Gupta, Rajat, Das Neves, Jose, Dasa, Tamirat Tesfaye, Dash, Aditya Prasad, Davis, Adrian C., Weaver, Nicole Davis, Davitoiu, Dragos Virgil, Davletov, Kairat, De La Hoz, Fernando Pio, De Neve, Jan-Walter, Degefa, Meaza Girma, Degenhardt, Louisa, Degfie, Tizta T., Deiparine, Selina, Demoz, Gebre Teklemariam, Demtsu, Baleen Betsu, Denova-Gutierrez, Edgar, Deribe, Kebede, Dervenis, Nikolaos, Jarlais, Don C. 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Miller, Tr, Miller-Petrie, Mk, Mini, Gk, Mirrakhimov, Em, Misganaw, At, Mohammad, Ka, Mohammed, Ma, Mokdad, Ah, Moreno Velásquez, I, Morrison, Sd, Moschos, Mm, Mousavi, Sm, Muchie, Kf, Mueller, Uo, Mumford, Je, Musa, Ki, Nachega, Jb, Nansseu, Jr, Nascimento, Br, Negoi, Ri, Newton, Crj, Ngalesoni, Fn, Ngunjiri, Jw, Nguyen, Aq, Nguyen, Ht, Nguyen, Lh, Nguyen, Th, Ningrum, Dna, Nirayo, Yl, Nixon, Mr, Norheim, Of, Noubiap, Jj, Nouri, Hr, Nourollahpour Shiadeh, M, Nowroozi, Mr, Odell, Cm, Ogbo, Fa, Oh, Ih, Olagunju, At, Olivares, Pr, Olsen, He, Olusanya, Bo, Olusanya, Jo, Ong, Kl, Ong, Sk, Orpana, Hm, Ortiz, Jr, Øverland, S, Owolabi, Mo, Özdemir, R, P A, M, Pakhare, Ap, Pakpour, Ah, Pandian, Jd, Park, Ek, Parry, Cdh, Patton, Gc, Paturi, Vr, Paulson, Kr, Pereira, Dm, Phillips, Mr, Piel, Fb, Pigott, Dm, Pillay, Jd, Postma, Mj, Purcell, Ca, Quistberg, Da, Rade, Kw, Radfar, A, Rafay, A, Rafiei, A, Rahim, F, Rahman, Mhu, Rahman, Ma, Rai, Rk, Ranabhat, Cl, Rao, Pc, Rawaf, Dl, Razo-García, C, Reiner, Rc, Reitsma, Mb, Renzaho, Amn, Riahi, Sm, Ribeiro, Alp, Rios-Blancas, Mj, Roba, Kt, Roberts, Nl, Robinson, Sr, Sahraian, Ma, Saldanha, Rf, Sambala, Ez, Samy, Am, Sanchez-Niño, Md, Santomauro, Df, Santos, Jv, Milicevic, Mm, Sao Jose, Bp, Sarker, Ar, Sarmiento-Suárez, R, Sawant, Ar, Schmidt, Mi, Schneider, Ijc, Schöttker, B, Schutte, Ae, Schwebel, Dc, Scott, Jg, Sepanlou, Sg, Serván-Mori, E, Shackelford, Ka, Shaheen, Aa, Shaikh, Ma, Shrime, Mg, Siddiqi, Tj, Sigfusdottir, Id, Silberberg, Dh, Silva, Da, Silva, Jp, Silva, Ntd, Silveira, Dga, Singh, Ja, Singh, Np, Singh, Pk, Sinha, Dn, Sobaih, Bh, Sorensen, Rjd, Soriano, Jb, Soyiri, In, Sposato, La, Sreeramareddy, Ct, Stanaway, Jd, Starodubov, Vi, Stein, Dj, Stewart, Lg, Stokes, Ma, Subart, Ml, Sufiyan, Mb, Sur, Pj, Sykes, Bl, Sylaja, Pn, Sylte, Do, Szoeke, Cei, Tabarés-Seisdedos, R, Tadakamadla, Sk, Tassew, Sg, Tekalign, Tg, Tekle, Mg, Temsah, Mh, Teshale, My, Tessema, Ga, Thankappan, Kr, Thrift, Ag, Thurston, Gd, To, Qg, Torre, Ae, Tortajada-Girbés, M, Tovani-Palone, Mr, Tran, Bx, Tran, Kb, Troeger, Ce, Truelsen, Tc, Truong, Nt, Tsadik, Ag, Tuzcu, Em, Ukwaja, Kn, Undurraga, Ea, Updike, Rl, Uthman, Oa, Uzun, Sb, Valdez, Pr, Vasankari, Tj, Vladimirov, Sk, Vollset, Se, Wagner, Gr, Wallin, Mt, Walson, Jl, Wang, Yp, Wassie, Mm, Weintraub, Rg, Weldegwergs, Kg, Werkneh, Aa, West, Te, Whiteford, Ha, Wilner, Lb, Wolfe, Cda, Wu, Yc, Wyper, Gma, Yahyazadeh Jabbari, Sh, Yan, Ll, Yasin, Yj, Yentür, Gk, Yimer, Em, Yirsaw, Bd, Yoon, Sj, Younis, Mz, Zaman, Sb, Zeleke, Aj, Zenebe, Zm, Zhang, Al, Zuhlke, Lj, and Murray, Cjl.
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Adult ,Male ,Adolescent ,national age-sex-specific mortality ,UNITED-STATES ,Global Health ,Socioeconomic Factor ,Global Burden of Disease ,GBD, causes of death ,Young Adult ,Age Distribution ,Life Expectancy ,General & Internal Medicine ,Cause of Death ,PUBLIC-HEALTH PROBLEM ,mortality ,282 causes global burden of disease ,Sex Distribution ,Child ,Aged ,Aged, 80 and over ,BARRIERS ,DEMENTIA ,Medicine (all) ,Infant, Newborn ,Infant ,11 Medical And Health Sciences ,Middle Aged ,TRENDS ,PREVENTION ,PREVALENCE ,ALZHEIMERS-DISEASE ,INDIVIDUALS ,3121 General medicine, internal medicine and other clinical medicine ,Child, Preschool ,REGISTRATION ,Female ,Human medicine ,Human - Abstract
Background Global development goals increasingly rely on country-specific estimates for benchmarking a nation's progress. To meet this need, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 estimated global, regional, national, and, for selected locations, subnational cause-specific mortality beginning in the year 1980. Here we report an update to that study, making use of newly available data and improved methods. GBD 2017 provides a comprehensive assessment of cause-specific mortality for 282 causes in 195 countries and territories from 1980 to 2017. Methods The causes of death database is composed of vital registration (VR), verbal autopsy (VA), registry, survey, police, and surveillance data. GBD 2017 added ten VA studies, 127 country-years of VR data, 502 cancer-registry country-years, and an additional surveillance country-year. Expansions of the GBD cause of death hierarchy resulted in 18 additional causes estimated for GBD 2017. Newly available data led to subnational estimates for five additional countries Ethiopia, Iran, New Zealand, Norway, and Russia. Deaths assigned International Classification of Diseases (ICD) codes for non-specific, implausible, or intermediate causes of death were reassigned to underlying causes by redistribution algorithms that were incorporated into uncertainty estimation. We used statistical modelling tools developed for GBD, including the Cause of Death Ensemble model (CODErn), to generate cause fractions and cause specific death rates for each location, year, age, and sex. Instead of using UN estimates as in previous versions, GBD 2017 independently estimated population size and fertility rate for all locations. Years of life lost (YLLs) were then calculated as the sum of each death multiplied by the standard life expectancy at each age. All rates reported here are age-standardised. Findings At the broadest grouping of causes of death (Level 1), non-communicable diseases (NC Ds) comprised the greatest fraction of deaths, contributing to 73.4% (95% uncertainty interval [UI] 72.5-74.1) of total deaths in 2017, while communicable, maternal, neonatal, and nutritional (CMNN) causes accounted for 186% (17.9-19.6), and injuries 8.0% (7.7-8.2). Total numbers of deaths from NCD causes increased from 2007 to 2017 by 22.7% (21.5-23.9), representing an additional 7.61 million (7. 20-8.01) deaths estimated in 2017 versus 2007. The death rate from NCDs decreased globally by 7.9% (7.08.8). The number of deaths for CMNN causes decreased by 222% (20.0-24.0) and the death rate by 31.8% (30.1-33.3). Total deaths from injuries increased by 2.3% (0-5-4-0) between 2007 and 2017, and the death rate from injuries decreased by 13.7% (12.2-15.1) to 57.9 deaths (55.9-59.2) per 100 000 in 2017. Deaths from substance use disorders also increased, rising from 284 000 deaths (268 000-289 000) globally in 2007 to 352 000 (334 000-363 000) in 2017. Between 2007 and 2017, total deaths from conflict and terrorism increased by 118.0% (88.8-148.6). A greater reduction in total deaths and death rates was observed for some CMNN causes among children younger than 5 years than for older adults, such as a 36.4% (32.2-40.6) reduction in deaths from lower respiratory infections for children younger than 5 years compared with a 33.6% (31.2-36.1) increase in adults older than 70 years. Globally, the number of deaths was greater for men than for women at most ages in 2017, except at ages older than 85 years. Trends in global YLLs reflect an epidemiological transition, with decreases in total YLLs from enteric infections, respirator}, infections and tuberculosis, and maternal and neonatal disorders between 1990 and 2017; these were generally greater in magnitude at the lowest levels of the Socio-demographic Index (SDI). At the same time, there were large increases in YLLs from neoplasms and cardiovascular diseases. YLL rates decreased across the five leading Level 2 causes in all SDI quintiles. The leading causes of YLLs in 1990 neonatal disorders, lower respiratory infections, and diarrhoeal diseases were ranked second, fourth, and fifth, in 2017. Meanwhile, estimated YLLs increased for ischaemic heart disease (ranked first in 2017) and stroke (ranked third), even though YLL rates decreased. Population growth contributed to increased total deaths across the 20 leading Level 2 causes of mortality between 2007 and 2017. Decreases in the cause-specific mortality rate reduced the effect of population growth for all but three causes: substance use disorders, neurological disorders, and skin and subcutaneous diseases. Interpretation Improvements in global health have been unevenly distributed among populations. Deaths due to injuries, substance use disorders, armed conflict and terrorism, neoplasms, and cardiovascular disease are expanding threats to global health. For causes of death such as lower respiratory and enteric infections, more rapid progress occurred for children than for the oldest adults, and there is continuing disparity in mortality rates by sex across age groups. Reductions in the death rate of some common diseases are themselves slowing or have ceased, primarily for NCDs, and the death rate for selected causes has increased in the past decade. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd.
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75. 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
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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.
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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.
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- 2018
76. Global, regional, and national age-sex-specific mortality and life expectancy, 1950–2017: a systematic analysis for the Global Burden of Disease Study 2017
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Samuel, Ogbo, Felix Akpojene, Oh, In-Hwan, Okoro, Anselm, Oladimeji, Olanrewaju, Olagunju, Andrew T, Olagunju, Tinuke O, Olivares, Pedro R, Olusanya, Bolajoko Olubukunola, Olusanya, Jacob Olusegun, Ong, Sok King, Opio, John Nelson, Oren, Eyal, Ortiz, Justin R, Ortiz, Alberto, Ota, Erika, Otstavnov, Stanislav S, Øverland, Simon, Owolabi, Mayowa Ojo, Oyekale, Abayomi Samuel, P A, Mahesh, Pacella, Rosana, Pakhale, Smita, Pakhare, Abhijit P, Pana, Adrian, Panda, Basant Kumar, Panda-Jonas, Songhomitra, Pandey, Achyut Raj, Pandian, Jeyaraj Durai, Parisi, Andrea, Park, Eun-Kee, Parry, Charles D H, Parsian, Hadi, Patel, Shanti, Patle, Ajay, Patten, Scott B, Patton, George C, Paudel, Deepak, Pearce, Neil, Peprah, Emmanuel K, Pereira, Alexandre, Pereira, David M, Perez, Krystle M, Perico, Norberto, Pervaiz, Aslam, Pesudovs, Konrad, Petri, William A, Petzold, Max, Phillips, Michael R, Pigott, David M, Pillay, Julian David, Pirsaheb, Meghdad, Pishgar, Farhad, Plass, Dietrich, Polinder, Suzanne, 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Narayanaswamy, Vidavalur, Ramesh, Villafaina, Santo, Violante, Francesco S, Vladimirov, Sergey Konstantinovitch, Vlassov, Vasily, Vollset, Stein Emil, Vos, Theo, Vosoughi, Kia, Vujcic, Isidora S, Wagner, Gregory R, Wagnew, Fasil Wagnew Shiferaw, Waheed, Yasir, Wang, Yanping, Wang, Yuan-Pang, Wassie, Molla Mesele, Weiderpass, Elisabete, Weintraub, Robert G, Weiss, Daniel J, Weiss, Jordan, Weldegebreal, Fitsum, Weldegwergs, Kidu Gidey, Werdecker, Andrea, Westerman, Ronny, Whiteford, Harvey A, Widecka, Justyna, Widecka, Katarzyna, Wijeratne, Tissa, Winkler, Andrea Sylvia, Wiysonge, Charles Shey, Wolfe, Charles D A, Wondemagegn, Sintayehu Ambachew, Wu, Shouling, Wyper, Grant M A, Xu, Gelin, Yadav, Rajaram, Yakob, Bereket, Yamada, Tomohide, Yan, Lijing L, Yano, Yuichiro, Yaseri, Mehdi, Yasin, Yasin Jemal, Ye, Pengpeng, Yearwood, Jamal A, Yentür, Gökalp Kadri, Yeshaneh, Alex, Yimer, Ebrahim M, Yip, Paul, Yisma, Engida, Yonemoto, Naohiro, Yoon, Seok-Jun, York, Hunter W, Yotebieng, Marcel, 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Child mortality ,Alnæmi ,Dánartíðni ,Heilsufar ,GBD ,Börn ,Dauði ,Almennar lyflækningar ,Fullorðnir ,General & Internal Medicine ,parasitic diseases ,Psychology ,age-specific mortality ,Estimating adult mortality ,Medicine (all) ,HIV ,11 Medical And Health Sciences ,General Medicine ,All-cause mortality ,humanities ,Countries ,Death ,mortality, national ,Sálfræði ,Health ,GBD, mortality ,Human medicine ,Trends - Abstract
The content is solely the responsibility of the authors and does not necessarily represent the official views of the funders. Data for this research was provided by MEASURE Evaluation, funded by the United States Agency for International Development (USAID). Views expressed do not necessarily reflect those of USAID, the US Government, or MEASURE Evaluation. The Palestinian Central Bureau of Statistics granted the researchers access to relevant data in accordance with licence no. SLN2014-3-170, after subjecting data to processing aiming to preserve the confidentiality of individual data in accordance with the General Statistics Law-2000. The researchers are solely responsible for the conclusions and inferences drawn upon available data., Background Assessments of age-specific mortality and life expectancy have been done by the UN Population Division, Department of Economics and Social Affairs (UNPOP), the United States Census Bureau, WHO, and as part of previous iterations of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD). Previous iterations of the GBD used population estimates from UNPOP, which were not derived in a way that was internally consistent with the estimates of the numbers of deaths in the GBD. The present iteration of the GBD, GBD 2017, improves on previous assessments and provides timely estimates of the mortality experience of populations globally. Methods The GBD uses all available data to produce estimates of mortality rates between 1950 and 2017 for 23 age groups, both sexes, and 918 locations, including 195 countries and territories and subnational locations for 16 countries. Data used include vital registration systems, sample registration systems, household surveys (complete birth histories, summary birth histories, sibling histories), censuses (summary birth histories, household deaths), and Demographic Surveillance Sites. In total, this analysis used 8259 data sources. Estimates of the probability of death between birth and the age of 5 years and between ages 15 and 60 years are generated and then input into a model life table system to produce complete life tables for all locations and years. Fatal discontinuities and mortality due to HIV/AIDS are analysed separately and then incorporated into the estimation. We analyse the relationship between age-specific mortality and development status using the Socio-demographic Index, a composite measure based on fertility under the age of 25 years, education, and income. There are four main methodological improvements in GBD 2017 compared with GBD 2016: 622 additional data sources have been incorporated; new estimates of population, generated by the GBD study, are used; statistical methods used in different components of the analysis have been further standardised and improved; and the analysis has been extended backwards in time by two decades to start in 1950. Findings Globally, 18·7% (95% uncertainty interval 18·4–19·0) of deaths were registered in 1950 and that proportion has been steadily increasing since, with 58·8% (58·2–59·3) of all deaths being registered in 2015. At the global level, between 1950 and 2017, life expectancy increased from 48·1 years (46·5–49·6) to 70·5 years (70·1–70·8) for men and from 52·9 years (51·7–54·0) to 75·6 years (75·3–75·9) for women. Despite this overall progress, there remains substantial variation in life expectancy at birth in 2017, which ranges from 49·1 years (46·5–51·7) for men in the Central African Republic to 87·6 years (86·9–88·1) among women in Singapore. The greatest progress across age groups was for children younger than 5 years; under-5 mortality dropped from 216·0 deaths (196·3–238·1) per 1000 livebirths in 1950 to 38·9 deaths (35·6–42·83) per 1000 livebirths in 2017, with huge reductions across countries. Nevertheless, there were still 5·4 million (5·2–5·6) deaths among children younger than 5 years in the world in 2017. Progress has been less pronounced and more variable for adults, especially for adult males, who had stagnant or increasing mortality rates in several countries. The gap between male and female life expectancy between 1950 and 2017, while relatively stable at the global level, shows distinctive patterns across super-regions and has consistently been the largest in central Europe, eastern Europe, and central Asia, and smallest in south Asia. Performance was also variable across countries and time in observed mortality rates compared with those expected on the basis of development. Interpretation This analysis of age-sex-specific mortality shows that there are remarkably complex patterns in population mortality across countries. The findings of this study highlight global successes, such as the large decline in under-5 mortality, which reflects significant local, national, and global commitment and investment over several decades. However, they also bring attention to mortality patterns that are a cause for concern, particularly among adult men and, to a lesser extent, women, whose mortality rates have stagnated in many countries over the time period of this study, and in some cases are increasing., Research reported in this publication was supported by the Bill & Melinda Gates Foundation, the University of Melbourne, Public Health England, the Norwegian Institute of Public Health, St. Jude Children's Research Hospital, the National Institute on Aging of the National Institutes of Health (award P30AG047845), and the National Institute of Mental Health of the National Institutes of Health (award R01MH110163).
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- 2018
77. 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
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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, Farzadfar, Farshad, Fazeli, Mir Sohail, Feigin, Valery L, Feigl, Andrea B, Fereshtehnejad, Seyed-Mohammad, Fernandes, João C, Ferrari, Alize J, Feyissa, Tesfaye Regassa, Filip, Irina, Fischer, Florian, Fitzmaurice, Christina, Flaxman, Abraham D, Foigt, Nataliya, Foreman, Kyle J, Franklin, Richard C, Frostad, Joseph J, Fullman, Nancy, Fürst, Thomas, Furtado, Joao M, Futran, Neal D, Gakidou, Emmanuela, Garcia-Basteiro, Alberto L, Gebre, Teshome, Gebregergs, Gebremedhin Berhe, Gebrehiwot, Tsegaye Tewelde, Geleijnse, Johanna M, Geleto, Ayele, Gemechu, Bikila Lencha, Gesesew, Hailay Abrha, Gething, Peter W, Ghajar, Alireza, Gibney, Katherine B, Gillum, Richard F, Ginawi, Ibrahim Abdelmageem Mohamed, Gishu, Melkamu Dedefo, Giussani, Giorgia, Godwin, William W, Goel, Kashish, Goenka, Shifalika, Goldberg, Ellen M, Gona, Philimon N, Goodridge, Amador, Gopalani, Sameer Vali, Gosselin, Richard A, Gotay, Carolyn C, Goto, Atsushi, Goulart, Alessandra Carvalho, Graetz, Nicholas, Gugnani, Harish Chander, Gupta, Prakash C, Gupta, Rajeev, Gupta, Tanush, Gupta, Vipin, Gupta, Rahul, Gutiérrez, Reyna A, Hachinski, Vladimir, Hafezi-Nejad, Nima, Hailu, Alemayehu Desalegne, Hailu, Gessessew Bugssa, Hamadeh, Randah Ribhi, Hamidi, Samer, Hammami, Mouhanad, Handal, Alexis J, Hankey, Graeme J, Hao, Yuantao, Harb, Hilda L, Hareri, Habtamu Abera, Haro, Josep Maria, Harun, Kimani M, Harvey, James, Hassanvand, Mohammad Sadegh, Havmoeller, Rasmus, Hay, Simon I, Hay, Roderick J, Hedayati, Mohammad T, Hendrie, Delia, Henry, Nathaniel J, Heredia-Pi, Ileana Beatriz, Heydarpour, Pouria, Hoek, Hans W, Hoffman, Howard J, Horino, Masako, Horita, Nobuyuki, Hosgood, H Dean, Hostiuc, Sorin, Hotez, Peter J, Hoy, Damian G, Htet, Aung Soe, Hu, Guoqing, Huang, John J, Huynh, Chantal, Iburg, Kim Moesgaard, Igumbor, Ehimario Uche, Ikeda, Chad, Irvine, Caleb Mackay Salpeter, Islam, Sheikh Mohammed Shariful, Jacobsen, Kathryn H, Jahanmehr, Nader, Jakovljevic, Mihajlo B, James, Peter, Jassal, Simerjot K, Javanbakht, Mehdi, Jayaraman, Sudha P, Jeemon, Panniyammakal, Jensen, Paul N, Jha, Vivekanand, Jiang, Guohong, John, Denny, Johnson, Catherine O, Johnson, Sarah Charlotte, Jonas, Jost B, Jürisson, Mikk, Kabir, Zubair, Kadel, Rajendra, Kahsay, Amaha, Kamal, Ritul, Kar, Chittaranjan, Karam, Nadim E, Karch, André, Karema, Corine Kakizi, Karimi, Seyed M, Karimkhani, Chante, Kasaeian, Amir, Kassa, Getachew Mullu, Kassaw, Nigussie Assefa, Kassebaum, Nicholas J, Kastor, Anshul, Katikireddi, Srinivasa Vittal, Kaul, Anil, Kawakami, Norito, Keiyoro, Peter Njenga, Kemmer, Laura, Kengne, Andre Pascal, Keren, Andre, Kesavachandran, Chandrasekharan Nair, Khader, Yousef Saleh, Khalil, Ibrahim A, Khan, Ejaz Ahmad, Khang, Young-Ho, Khoja, Abdullah T, Khosravi, Ardeshir, Khubchandani, Jagdish, Kiadaliri, Aliasghar Ahmad, Kieling, Christian, Kim, Yun Jin, Kim, Daniel, Kimokoti, Ruth W, Kinfu, Yohannes, Kisa, Adnan, Kissimova-Skarbek, Katarzyna A, Kissoon, Niranjan, Kivimaki, Mika, Knudsen, Ann Kristin, Kokubo, Yoshihiro, Kolte, Dhaval, Kopec, Jacek A, Kosen, Soewarta, Kotsakis, Georgios A, Koul, Parvaiz A, Koyanagi, Ai, Kravchenko, Michael, Krohn, Kristopher J, Kumar, G Anil, Kumar, Pushpendra, Kyu, Hmwe H, Lager, Anton Carl Jonas, Lal, Dharmesh Kumar, Lalloo, Ratilal, Lallukka, Tea, Lambert, Nkurunziza, Lan, Qing, Lansingh, Van C, Larsson, Anders, Leasher, Janet L, Lee, Paul H, Leigh, James, Leshargie, Cheru Tesema, Leung, Janni, Leung, Ricky, Levi, Miriam, Li, Yichong, Li, Yongmei, Liang, Xiaofeng, Liben, Misgan Legesse, Lim, Stephen S, Linn, Shai, Liu, Patrick Y, Liu, Angela, Liu, Shiwei, Liu, Yang, Lodha, Rakesh, Logroscino, Giancarlo, Looker, Katharine J, Lopez, Alan D, Lorkowski, Stefan, Lotufo, Paulo A, Lozano, Rafael, Lucas, Timothy C D, Lunevicius, Raimundas, Lyons, Ronan A, Macarayan, Erlyn Rachelle King, Maddison, Emilie R, Magdy Abd El Razek, Hassan Magdy Abd, Magdy Abd El Razek, Mohammed, Magis-Rodriguez, Carlos, Mahdavi, Mahdi, Majdan, Marek, Majdzadeh, Reza, Majeed, Azeem, Malekzadeh, Reza, Malhotra, Rajesh, Malta, Deborah Carvalho, Mamun, Abdullah A, Manguerra, Helena, Manhertz, Treh, Mantovani, Lorenzo G, Mapoma, Chabila C, March, Lyn M, Marczak, Laurie B, Martinez-Raga, Jose, Martins, Paulo Henrique Viegas, Martins-Melo, Francisco Rogerlândio, Martopullo, Ira, März, Winfried, Mathur, Manu Raj, Mazidi, Mohsen, McAlinden, Colm, McGaughey, Madeline, McGrath, John J, McKee, Martin, Mehata, Suresh, Meier, Toni, Meles, Kidanu Gebremariam, Memiah, Peter, Memish, Ziad A, Mendoza, Walter, Mengesha, Melkamu Merid, Mengistie, Mubarek Abera, Mengistu, Desalegn Tadese, Mensah, George A, Meretoja, Tuomo J, Meretoja, Atte, Mezgebe, Haftay Berhane, Micha, Renata, Millear, Anoushka, Miller, Ted R, Minnig, Shawn, Mirarefin, Mojde, Mirrakhimov, Erkin M, Misganaw, Awoke, Mishra, Shiva Raj, Mitchell, Philip B, Mohammad, Karzan Abdulmuhsin, Mohammadi, Alireza, Mohammed, Muktar Sano Kedir, Mohammed, Kedir Endris, Mohammed, Shafiu, Mohan, Murali B V, Mokdad, Ali H, Mollenkopf, Sarah K, Monasta, Lorenzo, Montañez Hernandez, Julio Cesar, Montico, Marcella, Moradi-Lakeh, Maziar, Moraga, Paula, Morawska, Lidia, Mori, Rintaro, Morrison, Shane D, Moses, Mark, Mountjoy-Venning, Cliff, Mruts, Kalayu Birhane, Mueller, Ulrich O, Muller, Kate, Murdoch, Michele E, Murray, Christopher J L, Murthy, Gudlavalleti Venkata Satyanarayana, Murthy, Srinivas, Musa, Kamarul Imran, Nachega, Jean B, Nagel, Gabriele, Naghavi, Mohsen, Naheed, Aliya, Naidoo, Kovin S, Nangia, Vinay, Nasher, Jamal T, Natarajan, Gopalakrishnan, Negasa, Dumessa Edessa, Negoi, Ruxandra Irina, Negoi, Ionut, Newton, Charles R, Ngunjiri, Josephine Wanjiku, Nguyen, Cuong Tat, Nguyen, Quyen Le, Nguyen, Trang Huyen, Nguyen, Grant, Nguyen, Minh, Nichols, Emma, Ningrum, Dina Nur Anggraini, Nong, Vuong Minh, Norheim, Ole F, Norrving, Bo, Noubiap, Jean Jacques N, Nyandwi, Alypio, Obermeyer, Carla Makhlouf, O'Donnell, Martin J, Ogbo, Felix Akpojene, Oh, In-Hwan, Okoro, Anselm, Oladimeji, Olanrewaju, Olagunju, Andrew Toyin, Olagunju, Tinuke Oluwasefunmi, Olsen, Helen E, Olusanya, Bolajoko Olubukunola, Olusanya, Jacob Olusegun, Ong, Kanyin, Opio, John Nelson, Oren, Eyal, Ortiz, Alberto, Osborne, Richard H, Osgood-Zimmerman, Aaron, Osman, Majdi, Ota, Erika, Owolabi, Mayowa O, PA, Mahesh, Pacella, Rosana E, Panda, Basant Kumar, Pandian, Jeyaraj Durai, Papachristou, Christina, Park, Eun-Kee, Parry, Charles D, Parsaeian, Mahboubeh, Patil, Snehal T, Patten, Scott B, Patton, George C, Paudel, Deepak, Paulson, Katherine, Pearce, Neil, Pereira, David M, Perez, Krystle Marie, Perico, Norberto, Pesudovs, Konrad, Peterson, Carrie Beth, Petri, William Arthur, Petzold, Max, Phillips, Michael Robert, Phipps, Geoffrey, Pigott, David M, Pillay, Julian David, Pinho, Christine, Piradov, Michael A, Plass, Dietrich, Pletcher, Martin A, Popova, Svetlana, Poulton, Richie G, Pourmalek, Farshad, Prabhakaran, Dorairaj, Prasad, Narayan, Purcell, Carrie, Purwar, Manorama, Qorbani, Mostafa, Quintanilla, Beatriz Paulina Ayala, Rabiee, Rynaz H S, Radfar, Amir, Rafay, Anwar, Rahimi, Kazem, Rahimi-Movaghar, Afarin, Rahimi-Movaghar, Vafa, Rahman, Mohammad Hifz Ur, Rahman, Muhammad Aziz, Rahman, Mahfuzar, Rai, Rajesh Kumar, Rajsic, Sasa, Ram, Usha, Ranabhat, Chhabi Lal, Rangaswamy, Thara, Rankin, Zane, Rao, Paturi Vishnupriya, Rao, Puja C, Rawaf, Salman, Ray, Sarah E, Reiner, Robert C, Reinig, Nikolas, Reitsma, Marissa, Remuzzi, Giuseppe, Renzaho, Andre M N, Resnikoff, Serge, Rezaei, Satar, Ribeiro, Antonio L, Rivas, Jacqueline Castillo, Roba, Hirbo Shore, Robinson, Stephen R, Rojas-Rueda, David, Rokni, Mohammad Bagher, Ronfani, Luca, Roshandel, Gholamreza, Roth, Gregory A, Rothenbacher, Dietrich, Roy, Ambuj, Rubagotti, Enrico, Ruhago, George Mugambage, Saadat, Soheil, Safdarian, Mahdi, Safiri, Saeid, Sagar, Rajesh, Sahathevan, Ramesh, Sahraian, Mohammad Ali, Salama, Joseph, Saleh, Muhammad Muhammad, Salomon, Joshua A, Salvi, Sundeep Santosh, Samy, Abdallah M, Sanabria, Juan Ramon, Sanchez-Niño, Maria Dolores, Santomauro, Damian, Santos, João Vasco, Santos, Itamar S, Santric Milicevic, Milena M, Sartorius, Benn, Satpathy, Maheswar, Sawhney, Monika, Saxena, Sonia, Schelonka, Kathryn, Schmidt, Maria Inês, Schneider, Ione J C, Schöttker, Ben, Schutte, Aletta E, Schwebel, David C, Schwendicke, Falk, Seedat, Soraya, Sepanlou, Sadaf G, Servan-Mori, Edson E, Shaheen, Amira, Shaikh, Masood Ali, Shamsipour, Mansour, Sharma, Rajesh, Sharma, Jayendra, She, Jun, Shi, Peilin, Shibuya, Kenji, Shields, Chloe, Shifa, Girma Temam, Shiferaw, Mekonnen Sisay, Shigematsu, Mika, Shiri, Rahman, Shirkoohi, Reza, Shirude, Shreya, Shishani, Kawkab, Shoman, Haitham, Siabani, Soraya, Sibai, Abla Mehio, Sigfusdottir, Inga Dora, Silberberg, Donald H, Silva, Diego Augusto Santos, Silva, João Pedro, Silveira, Dayane Gabriele Alves, Singh, Jasvinder A, Singh, Om Prakash, Singh, Narinder Pal, Singh, Virendra, Sinha, Dhirendra Narain, Skiadaresi, Eirini, Slepak, Erica Leigh, Smith, David L, Smith, Mari, Sobaih, Badr H A, Sobngwi, Eugene, Soljak, Michael, Sorensen, Reed J D, Sousa, Tatiane Cristina Moraes, Sposato, Luciano A, Sreeramareddy, Chandrashekhar T, Srinivasan, Vinay, Stanaway, Jeffrey D, Stathopoulou, Vasiliki, Steel, Nicholas, Stein, Dan J, Steiner, Caitlyn, Steinke, Sabine, Stokes, Mark Andrew, Stovner, Lars Jacob, Strub, Bryan, Subart, Michelle, Sufiyan, Muawiyyah Babale, Sunguya, Bruno F, Sur, Patrick J, Swaminathan, Soumya, Sykes, Bryan L, Sylte, Dillon, Szoeke, Cassandra E I, Tabarés-Seisdedos, Rafael, Tadakamadla, Santosh Kumar, Taffere, Getachew Redae, Takala, Jukka S, Tandon, Nikhil, Tanne, David, Tarekegn, Yihunie L, Tavakkoli, Mohammad, Taveira, Nuno, Taylor, Hugh R, Tegegne, Teketo Kassaw, Tehrani-Banihashemi, Arash, Tekelab, Tesfalidet, Terkawi, Abdullah Sulieman, Tesfaye, Dawit Jember, Tesssema, Belay, Thakur, JS, Thamsuwan, Ornwipa, Theadom, Alice M, Theis, Andrew M, Thomas, Katie E, Thomas, Nihal, Thompson, Robert, Thrift, Amanda G, Tobe-Gai, Ruoyan, Tobollik, Myriam, Tonelli, Marcello, Topor-Madry, Roman, Tortajada, Miguel, Touvier, Mathilde, Traebert, Jefferson, Tran, Bach Xuan, Troeger, Christopher, Truelsen, Thomas, Tsoi, Derrick, Tuzcu, Emin Murat, Tymeson, Hayley, Tyrovolas, Stefanos, Ukwaja, Kingsley Nnanna, Undurraga, Eduardo A, Uneke, Chigozie Jesse, Updike, Rachel, Uthman, Olalekan A, Uzochukwu, Benjamin S Chudi, van Boven, Job F M, Varughese, Santosh, Vasankari, Tommi, Veerman, Lennert J, Venkatesh, S, Venketasubramanian, Narayanaswamy, Vidavalur, Ramesh, Vijayakumar, Lakshmi, Violante, Francesco S, Vishnu, Abhishek, Vladimirov, Sergey K, Vlassov, Vasiliy Victorovich, Vollset, Stein Emil, Vos, Theo, Wadilo, Fiseha, Wakayo, Tolassa, Wallin, Mitchell T, Wang, Yuan-Pang, Weichenthal, Scott, Weiderpass, Elisabete, Weintraub, Robert G, Weiss, Daniel J, Werdecker, Andrea, Westerman, Ronny, Whiteford, Harvey A, Wijeratne, Tissa, Williams, Hywel C, Wiysonge, Charles Shey, Woldeyes, Belete Getahun, Wolfe, Charles D A, Woodbrook, Rachel, Woolf, Anthony D, Workicho, Abdulhalik, Xavier, Denis, Xu, Gelin, Yadgir, Simon, Yaghoubi, Mohsen, Yakob, Bereket, Yan, Lijing L, Yano, Yuichiro, Ye, Pengpeng, Yihdego, Mahari Gidey, Yimam, Hassen Hamid, Yip, Paul, Yonemoto, Naohiro, Yoon, Seok-Jun, Yotebieng, Marcel, Younis, Mustafa Z, Yu, Chuanhua, Zaidi, Zoubida, Zaki, Maysaa El Sayed, Zegeye, Elias Asfaw, Zenebe, Zerihun Menlkalew, Zhang, Xueying, Zheng, Yingfeng, Zhou, Maigeng, Zipkin, Ben, Zodpey, Sanjay, Zoeckler, Leo, Zuhlke, Liesl Joanna, Viðskiptadeild (HR), School of Business (RU), Háskólinn í Reykjavík, Reykjavik University, Cell biology, Hematology, Neurology, Simon, I, Hay, Amanuel, Alemu, Abajobir, Kalkidan, Hassen, Abate, Cristiana, Abbafati, Kaja, M, Abbas, Foad, Abd Allah, Abdishakur, M, Abdulle, Teshome, Abuka, Abebo, Semaw, Ferede, Abera, Victor, Aboyan, Laith, J, Abu, Raddad, Ilana, N, Ackerman, Isaac, A, Adedeji, Olatunji, Adetokunboh, Ashkan, Afshin, Rakesh, Aggarwal, Sutapa, Agrawal, Anurag, Agrawal, Aliasghar, Ahmad, Kiadaliri, Muktar, Beshir, Ahmed, Amani, Nidhal, Aichour, Ibtihel, Aichour, Miloud, Taki, Eddine, Aichour, Sneha, Aiyar, Tomi, F, Akinyemiju, Nadia, Akseer, Faris, Hasan, Al, Lami, Fares, Alahdab, Ziyad, Al Aly, Khurshid, Alam, Noore, Alam, Tahiya, Alam, Deena, Alasfoor, Kefyalew, Addi, Alene, Raghib, Ali, Reza, Alizadeh Navaei, Juma, M, Alkaabi, Ala’A, Alkerwi, François, Alla, Peter, Allebeck, Christine, Allen, Fatma, Al Maskari, Mohammad, Abdulaziz, Almazroa, Rajaa, Al Raddadi, Ubai, Alsharif, Shirina, Alsowaidi, Benjamin, M, Althouse, Khalid, A, Altirkawi, Nelson, Alvis Guzman, Azmeraw, T, Amare, Erfan, Amini, Walid, Ammar, Yaw, Ampem, Amoako, Mustafa, Geleto, Ansha, Carl, Abelardo, T, Antonio, Palwasha, Anwari, Johan, Ärnlöv, Megha, Arora, Al, Artaman, Krishna, Kumar, Aryal, Solomon, W, Asgedom, Tesfay, Mehari, Atey, Niguse, Tadele, Atnafu, Leticia, Avila Burgo, Euripide, Frinel, G, Arthur, Avokpaho, Ashish, Awasthi, Shally, Awasthi, Beatriz, Paulina, Ayala, Quintanilla, Mahmoud, Reza, Azarpazhooh, Peter, Azzopardi, Tesleem, Kayode, Babalola, Umar, Bacha, Alaa, Badawi, Kalpana, Balakrishnan, Marlena, S, Bannick, Aleksandra, Barac, Suzanne, L, Barker, Collo, Till, Bärnighausen, Simon, Barquera, Lope, H, Barrero, Sanjay, Basu, Robert, Battista, Katherine, E, Battle, Bernhard, T, Baune, Shahrzad, Bazargan Hejazi, Justin, Beardsley, Neeraj, Bedi, Yannick, Béjot, Bayu, Begashaw, Bekele, Michelle, L, Bell, Derrick, A, Bennett, Jame, R, Bennett, Isabela, M, Bensenor, Jennifer, Benson, Adugnaw, Berhane, Derbew, Fikadu, Berhe, Eduardo, Bernabé, Balem, Demtsu, Betsu, Mircea, Beuran, Addisu, Shunu, Beyene, Anil, Bhansali, Samir, Bhatt, Zulfiqar, A, Bhutta, Sibhatu, Biadgilign, Kelly, Bienhoff, Boris, Bikbov, Charles, Birungi, Stan, Biryukov, Donal, Bisanzio, Habtamu, Mellie, Bizuayehu, Fiona, M, Blyth, Dube, Jara, Boneya, Dipan, Bose, Ibrahim, R, Bou, Orm, Rupert, R, A, Bourne, Michael, Brainin, Carol, E, G, Brayne, Alexandra, Brazinova, Nicholas, J, 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Rahimi, K, Rahimi-Movaghar, A, Rahimi-Movaghar, V, Rahman, M, Rai, R, Rajsic, S, Ram, U, Ranabhat, C, Rangaswamy, T, Rankin, Z, Rao, P, Rawaf, S, Ray, S, Reiner, R, Reinig, N, Reitsma, M, Remuzzi, G, Renzaho, A, Resnikoff, S, Rezaei, S, Ribeiro, A, Rivas, J, Roba, H, Robinson, S, Rojas-Rueda, D, Rokni, M, Ronfani, L, Roshandel, G, Roth, G, Rothenbacher, D, Roy, A, Rubagotti, E, Ruhago, G, Saadat, S, Safdarian, M, Safiri, S, Sagar, R, Sahathevan, R, Sahraian, M, Salama, J, Saleh, M, Salomon, J, Salvi, S, Samy, A, Sanabria, J, Sanchez-Niño, M, Santomauro, D, Santos, J, Santos, I, Santric Milicevic, M, Sartorius, B, Satpathy, M, Sawhney, M, Saxena, S, Schelonka, K, Schmidt, M, Schneider, I, Schöttker, B, Schutte, A, Schwebel, D, Schwendicke, F, Seedat, S, Sepanlou, S, Servan-Mori, E, Shaheen, A, Shaikh, M, Shamsipour, M, Sharma, R, Sharma, J, She, J, Shi, P, Shibuya, K, Shields, C, Shifa, G, Shiferaw, M, Shigematsu, M, Shiri, R, Shirkoohi, R, Shirude, S, Shishani, K, Shoman, H, Siabani, S, Sibai, A, Sigfusdottir, I, Silberberg, D, Silva, D, Silva, J, Silveira, D, Singh, J, Singh, O, Singh, N, Singh, V, Sinha, D, Skiadaresi, E, Slepak, E, Smith, D, Smith, M, Sobaih, B, Sobngwi, E, Soljak, M, Sorensen, R, Sousa, T, Sposato, L, Sreeramareddy, C, Srinivasan, V, Stanaway, J, Stathopoulou, V, Steel, N, Stein, D, Steiner, C, Steinke, S, Stokes, M, Stovner, L, Strub, B, Subart, M, Sufiyan, M, Sunguya, B, Sur, P, Swaminathan, S, Sykes, B, Sylte, D, Szoeke, C, Tabarés-Seisdedos, R, Tadakamadla, S, Taffere, G, Takala, J, Tandon, N, Tanne, D, Tarekegn, Y, Tavakkoli, M, Taveira, N, Taylor, H, Tegegne, T, Tehrani-Banihashemi, A, Tekelab, T, Terkawi, A, Tesfaye, D, Tesssema, B, Thakur, J, Thamsuwan, O, Theadom, A, Theis, A, Thomas, K, Thomas, N, Thompson, R, Thrift, A, Tobe-Gai, R, Tobollik, M, Tonelli, M, Topor-Madry, R, Tortajada, M, Touvier, M, Traebert, J, Tran, B, Troeger, C, Truelsen, T, Tsoi, D, Tuzcu, E, Tymeson, H, Tyrovolas, S, Ukwaja, K, Undurraga, E, Uneke, C, Updike, R, Uthman, O, Uzochukwu, B, van Boven, J, Varughese, S, Vasankari, T, Veerman, L, Venkatesh, S, Venketasubramanian, N, Vidavalur, R, Vijayakumar, L, Violante, F, Vishnu, A, Vladimirov, S, Vlassov, V, Vollset, S, Vos, T, Wadilo, F, Wakayo, T, Wallin, M, Wang, Y, Weichenthal, S, Weiderpass, E, Weintraub, R, Weiss, D, Werdecker, A, Westerman, R, Whiteford, H, Wijeratne, T, Williams, H, Wiysonge, C, Woldeyes, B, Wolfe, C, Woodbrook, R, Woolf, A, Workicho, A, Xavier, D, Xu, G, Yadgir, S, Yaghoubi, M, Yakob, B, Yan, L, Yano, Y, Ye, P, Yihdego, M, Yimam, H, Yip, P, Yonemoto, N, Yoon, S, Yotebieng, M, Younis, M, Yu, C, Zaidi, Z, Zaki, M, Zegeye, E, Zenebe, Z, Zhang, X, Zheng, Y, Zhou, M, Zipkin, B, Zodpey, S, Zoeckler, L, Zuhlke, L, Brayne, Carol [0000-0001-5307-663X], Chowdhury, Rajiv [0000-0003-4881-5690], and Apollo - University of Cambridge Repository
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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
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78. Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016
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K., Johnson, Catherine O., Jonas, Jost B., Jurisson, Mikk, Kabir, Zubair, Kadel, Rajendra, Kahsay, Amaha, Kamal, Ritul, Karch, Andre, Karema, Corine Kakizi, Kasaeian, Amir, Kassebaum, Nicholas J., Kastor, Anshul, Katikireddi, Srinivasa Vittal, Kawakami, Norito, Keiyoro, Peter Njenga, Kelbore, Sefonias Getachew, Kemmer, Laura, Kengne, Andre Pascal, Kesavachandran, Chandrasekharan Nair, Khader, Yousef Saleh, Khalil, Ibrahim A., Khan, Ejaz Ahmad, Khang, Young-Ho, Khosravi, Ardeshir, Khubchandani, Jagdish, Kieling, Christian, Kim, Daniel, Kim, Jun Y., Kim, Yun Jin, Kimokoti, Ruth W., Kinfu, Yohannes, Kisa, Adnan, Kissimova-Skarbek, Katarzyna A., Kivimaki, Mika, Knibbs, Luke D., Knudsen, Ann Kristin, Kopec, Jacek A., Kosen, Soewarta, Koul, Parvaiz A., Koyanagi, Ai, Kravchenko, Michael, Krohn, Kristopher J., Kromhout, Hans, Defo, Barthelemy Kuate, Bicer, Burcu Kucuk, Kumar, G. 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Arthur, Awasthi, Ashish, Azzopardi, Peter, Bacha, Umar, Badawi, Alaa, Balakrishnan, Kalpana, Ballew, Shoshana H., Barac, Aleksandra, Barber, Ryan M., Barker-Collo, Suzanne L., Bärnighausen, Till, Barquera, Simon, Barregard, Lar, Barrero, Lope H., Batis, Carolina, Battle, Katherine E., Baune, Bernhard T., Beardsley, Justin, Bedi, Neeraj, Beghi, Ettore, Bell, Michelle L., Bennett, Derrick A., Bennett, James R., Bensenor, Isabela M., Berhane, Adugnaw, Berhe, Derbew Fikadu, Bernabé, Eduardo, Betsu, Balem Demtsu, Beuran, Mircea, Beyene, Addisu Shunu, Bhansali, Anil, Bhutta, Zulfqar A., Bikbov, Bori, Birungi, Charle, Biryukov, Stan, Blosser, Christopher D., Boneya, Dube Jara, Bou-Orm, Ibrahim R., Brauer, Michael, Breitborde, Nicholas J.K., Brenner, Hermann, Brugha, Traolach S., Bulto, Lemma Negesa Bulto, Baumgarner, Blair R., Butt, Zahid A., Cahuana-Hurtado, Lucero, Cárdenas, Rosario, Carrero, Juan Jesu, Castañeda-Orjuela, Carlos A., Catalá-López, Ferrán, Cercy, Kelly, Chang, Hsing-Yi, Charlson, Fiona J., Chimed-Ochir, Odgerel, Chisumpa, Vesper Hichilombwe, Chitheer, Abdulaal A., Christensen, Hanne, Christopher, Devasahayam Jesuda, Cirillo, Massimo, Cohen, Aaron J., Comfort, Haley, Cooper, Cyru, Coresh, Josef, Cornaby, Leslie, Cortesi, Paolo Angelo, Criqui, Michael H., Crump, John A., Dandona, Lalit, Dandona, Rakhi, Das Neves, José, Davey, Gail, Davitoiu, Dragos V., Davletov, Kairat, De Courten, Barbora, Degenhardt, Louisa, Deiparine, Selina, Dellavalle, Robert P., Deribe, Kebede, Deshpande, Aniruddha, Dharmaratne, Samath D., Ding, Eric L., Djalalinia, Shirin, Do, Huyen Phuc, Dokova, Klara, Doku, David Teye, Dorsey, E. Ray, Driscoll, Tim R., Dubey, Manisha, Duncan, Bruce Bartholow, Duncan, Sarah, Ebert, Natalie, Ebrahimi, Hedyeh, El-Khatib, Ziad Ziad, Enayati, Ahmadali, Endries, Aman Yesuf, Ermakov, Sergey Petrovich, Erskine, Holly E., Eshrati, Babak, Eskandarieh, Sharareh, Esteghamati, Alireza, Estep, Kara, Faraon, Emerito Jose Aquino, Farinha, Carla Sofia E. Sa, Faro, André, Farzadfar, Farshad, Fay, Kairsten, Feigin, Valery L., Fereshtehnejad, Seyed-Mohammad, Fernandes, João C., Ferrari, Alize J., Feyissa, Tesfaye Regassa, Filip, Irina, Fischer, Florian, Fitzmaurice, Christina, Flaxman, Abraham D., Foigt, Nataliya, Foreman, Kyle J., Frostad, Joseph J., Fullman, Nancy, Fürst, Thoma, Furtado, Joao M., Ganji, Morsaleh, Garcia-Basteiro, Alberto L., Gebrehiwot, Tsegaye Tewelde, Geleijnse, Johanna M., Geleto, Ayele, Gemechu, Bikila Lencha, Gesesew, Hailay Abrha, Gething, Peter W., Ghajar, Alireza, Gibney, Katherine B., Gill, Paramjit Singh, Gillum, Richard F., Giref, Ababi Zergaw, Gishu, Melkamu Dedefo, Giussani, Giorgia, Godwin, William W., Gona, Philimon N., Goodridge, Amador, Gopalani, Sameer Vali, Goryakin, Yevgeniy, Goulart, Alessandra Carvalho, Graetz, Nichola, Gugnani, Harish Chander, Guo, Jingwen, Gupta, Rajeev, Gupta, Tanush, Gupta, Vipin, Gutiérrez, Reyna A., Hachinski, Vladimir, Hafezi-Nejad, Nima, Hailu, Gessessew Bugssa, Hamadeh, Randah Ribhi, Hamidi, Samer, Hammami, Mouhanad, Handal, Alexis J., Hankey, Graeme J., Harb, Hilda L., Hareri, Habtamu Abera, Hassanvand, Mohammad Sadegh, Havmoeller, Rasmu, Hawley, Caitlin, Hay, Simon I., Hedayati, Mohammad T., Hendrie, Delia, Heredia-Pi, Ileana Beatriz, Hoek, Hans W., Horita, Nobuyuki, Hosgood, H. Dean, Hostiuc, Sorin, Hoy, Damian G., Hsairi, Mohamed, Hu, Guoqing, Huang, Hsiang, Huang, John J., Iburg, Kim Moesgaard, Ikeda, Chad, Inoue, Manami, Irvine, Caleb Mackay Salpeter, Jackson, Maria Delore, Jacobsen, Kathryn H., Jahanmehr, Nader, Jakovljevic, Mihajlo B., Jauregui, Alejandra, Javanbakht, Mehdi, Jeemon, Panniyammakal, Johansson, Lars R.K., Johnson, Catherine O., Jonas, Jost B., Jürisson, Mikk, Kabir, Zubair, Kadel, Rajendra, Kahsay, Amaha, Kamal, Ritul, Karch, André, Karema, Corine Kakizi, Kasaeian, Amir, Kassebaum, Nicholas J., Kastor, Anshul, Katikireddi, Srinivasa Vittal, Kawakami, Norito, Keiyoro, Peter Njenga, Kelbore, Sefonias Getachew, Kemmer, Laura, Kengne, Andre Pascal, Kesavachandran, Chandrasekharan Nair, Khader, Yousef Saleh, Khalil, Ibrahim A., Khan, Ejaz Ahmad, Khang, Young-Ho, Khosravi, Ardeshir, Khubchandani, Jagdish, Kieling, Christian, Kim, Daniel, Kim, Jun Y., Kim, Yun Jin, Kimokoti, Ruth W., Kinfu, Yohanne, Kisa, Adnan, Kissimova-Skarbek, Katarzyna A., Kivimaki, Mika, Knibbs, Luke D., Knudsen, Ann Kristin, Kopec, Jacek A., Kosen, Soewarta, Koul, Parvaiz A., Koyanagi, Ai, Kravchenko, Michael, Krohn, Kristopher J., Kromhout, Han, Kuate Defo, Barthelemy, Kucuk Bicer, Burcu, Kumar, G. Anil, Kutz, Michael, Kyu, Hmwe H., Lal, Dharmesh Kumar, Lalloo, Ratilal, Lallukka, Tea, Lan, Qing, Lansingh, Van C., Larsson, Ander, Lee, Alexander, Lee, Paul H., Leigh, Jame, Leung, Janni, Levi, Miriam, Li, Yichong, Li, Yongmei, Liang, Xiaofeng, Liben, Misgan Legesse, Linn, Shai, Liu, Patrick, Lodha, Rakesh, Logroscino, Giancarlo, Looker, Katherine J., Lopez, Alan D., Lorkowski, Stefan, Lotufo, Paulo A., Lozano, Rafael, Lunevicius, Raimunda, Macarayan, Erlyn Rachelle King, 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, Mantovani, Lorenzo G., Mapoma, Chabila C., Martin, Randall V., Martinez-Raga, Jose, Martins-Melo, Francisco Rogerlândio, Mathur, Manu Raj, Matsushita, Kunihiro, Matzopoulos, Richard, Mazidi, Mohsen, McAlinden, Colm, McGrath, John J., Mehata, Suresh, Mehndiratta, Man Mohan, Meier, Toni, Melaku, Yohannes Adama, Memiah, Peter, Memish, Ziad A., Mendoza, Walter, Mengesha, Melkamu Merid, Mensah, George A., Mensink, Gert B.M., Mereta, Seid Tiku, Meretoja, Atte, Meretoja, Tuomo J., Mezgebe, Haftay Berhane, Micha, Renata, Millear, Anoushka, Miller, Ted R., Minnig, Shawn, Mirarefin, Mojde, Mirrakhimov, Erkin M., Misganaw, Awoke, Mishra, Shiva Raj, Mohammad, Karzan Abdulmuhsin, Mohammed, Kedir Endri, Mohammed, Shafiu, Mohamed Ibrahim, Norlinah, Mohan, Murali B.V., Mokdad, Ali H., Monasta, Lorenzo, Montañez Hernandez, Julio Cesar, Montico, Marcella, Moradi-Lakeh, Maziar, Moraga, Paula, Morawska, Lidia, Morrison, Shane D., Mountjoy-Venning, Cliff, Mueller, Ulrich O., Mullany, Erin C., Muller, Kate, Murthy, Gudlavalleti Venkata Satyanarayana, Musa, Kamarul Imran, Naghavi, Mohsen, Naheed, Aliya, Nangia, Vinay, Natarajan, Gopalakrishnan, Negoi, Ionut, Negoi, Ruxandra Irina, Nguyen, Cuong Tat, Nguyen, Grant, Nguyen, Minh, Nguyen, Quyen Le, Nguyen, Trang Huyen, Nichols, Emma, Ningrum, Dina Nur Anggraini, Nomura, Marika, Nong, Vuong Minh, Norheim, Ole F., Norrving, Bo, Noubiap, Jean Jacques N., Obermeyer, Carla Makhlouf, Ogbo, Felix Akpojene, Oh, In-Hwan, Oladimeji, Olanrewaju, Olagunju, Andrew Toyin, Olagunju, Tinuke Oluwasefunmi, Olivares, Pedro R., Olsen, Helen E., Olusanya, Bolajoko Olubukunola, Olusanya, Jacob Olusegun, Opio, John Nelson, Oren, Eyal, Ortiz, Alberto, Ota, Erika, Owolabi, Mayowa O., Pa, Mahesh, Pacella, Rosana E., Pana, Adrian, Panda, Basant Kumar, Panda-Jonas, Songhomitra, Pandian, Jeyaraj D., Papachristou, Christina, Park, Eun-Kee, Parry, Charles D., Patten, Scott B., Patton, George C., Pereira, David M., Perico, Norberto, Pesudovs, Konrad, Petzold, Max, Phillips, Michael Robert, Pillay, Julian David, Piradov, Michael A., Pishgar, Farhad, Plass, Dietrich, Pletcher, Martin A., Polinder, Suzanne, Popova, Svetlana, Poulton, Richie G., Pourmalek, Farshad, Prasad, Narayan, Purcell, Carrie, Qorbani, Mostafa, Radfar, Amir, Rafay, Anwar, Rahimi-Movaghar, Afarin, Rahimi-Movaghar, Vafa, Rahman, Mahfuzar, Rahman, Mohammad Hifz Ur, Rahman, Muhammad Aziz, Rai, Rajesh Kumar, Rajsic, Sasa, Ram, Usha, Rawaf, Salman, Rehm, Colin D., Rehm, Jürgen, Reiner, Robert C., Reitsma, Marissa B., Reynales-Shigematsu, Luz Myriam, Remuzzi, Giuseppe, Renzaho, Andre M.N., Resnikoff, Serge, Rezaei, Satar, Ribeiro, Antonio L., Rivera, Juan A., Roba, Kedir Teji, Rojas-Rueda, David, Roman, Yesenia, Room, Robin, Roshandel, Gholamreza, Roth, Gregory A., Rothenbacher, Dietrich, Rubagotti, Enrico, Rushton, Lesley, Sadat, Nafi, Safdarian, Mahdi, Safi, Sare, Safiri, Saeid, Sahathevan, Ramesh, Salama, Joseph, Salomon, Joshua A., Samy, Abdallah M., Sanabria, Juan Ramon, Sanchez-Niño, Maria Dolore, Sánchez-Pimienta, Tania G., Santomauro, Damian, Santos, Itamar S., Santric Milicevic, Milena M., Sartorius, Benn, Satpathy, Maheswar, Sawhney, Monika, Saxena, Sonia, Schaeffner, Elke, Schmidt, Maria Inê, Schneider, Ione J.C., Schutte, Aletta E., Schwebel, David C., Schwendicke, Falk, Seedat, Soraya, Sepanlou, Sadaf G., Serdar, Berrin, Servan-Mori, Edson E., Shaddick, Gavin, Shaheen, Amira, Shahraz, Saeid, Shaikh, Masood Ali, Shamah Levy, Teresa, Shamsipour, Mansour, Shamsizadeh, Morteza, Shariful Islam, Sheikh Mohammed, Sharma, Jayendra, Sharma, Rajesh, She, Jun, Shen, Jiabin, Shi, Peilin, Shibuya, Kenji, Shields, Chloe, Shiferaw, Mekonnen Sisay, Shigematsu, Mika, Shin, Min-Jeong, Shiri, Rahman, Shirkoohi, Reza, Shishani, Kawkab, Shoman, Haitham, Shrime, Mark G., Sigfusdottir, Inga Dora, Silva, Diego Augusto Santo, Silva, João Pedro, Silveira, Dayane Gabriele Alve, Singh, Jasvinder A., Singh, Virendra, Sinha, Dhirendra Narain, Skiadaresi, Eirini, Slepak, Erica Leigh, Smith, David L., Smith, Mari, Sobaih, Badr H.A., Sobngwi, Eugene, Soneji, Samir, Sorensen, Reed J.D., Sposato, Luciano A., Sreeramareddy, Chandrashekhar T., Srinivasan, Vinay, Steel, Nichola, Stein, Dan J., Steiner, Caitlyn, Steinke, Sabine, Stokes, Mark Andrew, Strub, Bryan, Subart, Michelle, Sufiyan, Muawiyyah Babale, Suliankatchi, Rizwan Abdulkader, Sur, Patrick J., Swaminathan, Soumya, Sykes, Bryan L., Szoeke, Cassandra E.I., Tabarés-Seisdedos, Rafael, Tadakamadla, Santosh Kumar, Takahashi, Ken, Takala, Jukka S., Tandon, Nikhil, Tanner, Marcel, Tarekegn, Yihunie L., Tavakkoli, Mohammad, Tegegne, Teketo Kassaw, Tehrani-Banihashemi, Arash, Terkawi, Abdullah Sulieman, Tesssema, Belay, Thakur, J.S., Thamsuwan, Ornwipa, Thankappan, Kavumpurathu Raman, Theis, Andrew M., Thomas, Matthew Lloyd, Thomson, Alan J., Thrift, Amanda G., Tillmann, Taavi, Tobe-Gai, Ruoyan, Tobollik, Myriam, Tollanes, Mette C., Tonelli, Marcello, Topor-Madry, Roman, Torre, Anna, Tortajada, Miguel, Touvier, Mathilde, Tran, Bach Xuan, Truelsen, Thoma, Tuem, Kald Beshir, Tuzcu, Emin Murat, Tyrovolas, Stefano, Ukwaja, Kingsley Nnanna, Uneke, Chigozie Jesse, Updike, Rachel, Uthman, Olalekan A., Van Boven, Job F.M., Van Donkelaar, Aaron, Varughese, Santosh, Vasankari, Tommi, Veerman, Lennert J., Venkateswaran, Vidhya, Venketasubramanian, Narayanaswamy, Violante, Francesco S., Vladimirov, Sergey K., Vlassov, Vasiliy Victorovich, Vollset, Stein Emil, Vos, Theo, Wadilo, Fiseha, Wakayo, Tolassa, Wallin, Mitchell T., Wang, Yuan-Pang, Weichenthal, Scott, Weiderpass, Elisabete, Weintraub, Robert G., Weiss, Daniel J., Werdecker, Andrea, Westerman, Ronny, Whiteford, Harvey A., Wiysonge, Charles Shey, Woldeyes, Belete Getahun, Wolfe, Charles D.A., Woodbrook, Rachel, Workicho, Abdulhalik, Wulf Hanson, Sarah, Xavier, Deni, Xu, Gelin, Yadgir, Simon, Yakob, Bereket, Yan, Lijing L., Yaseri, Mehdi, Yimam, Hassen Hamid, Yip, Paul, Yonemoto, Naohiro, Yoon, Seok-Jun, Yotebieng, Marcel, Younis, Mustafa Z., Zaidi, Zoubida, El Sayed Zaki, Maysaa, Zavala-Arciniega, Lui, Zhang, Xueying, Zimsen, Stephanie Raman M., Zipkin, Ben, Zodpey, Sanjay, Lim, Stephen S., and Murray, Christopher J.L.
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Líkamsþyngdarstuðull ,Dánarmein ,Heilsufar ,Dánartíðni ,Birthweight ,Fæðingarþyngd ,Börn ,HEALTH-RISKS ,Pregnancy ,EPIDEMIOLOGY ,Psychology ,Meðganga ,Children ,Konur ,Body mass index ,PRECAUTIONARY PRINCIPLE ,Public health ,Global burden of disease/statistics and numerical data ,Medicine (all) ,Smoking ,COST ,Men ,11 Medical And Health Sciences ,Health policy ,Háþrýstingur ,Sálfræði ,World health ,Hypertension ,Lýðheilsa ,Reykingar ,Life Sciences & Biomedicine ,COUNTRIES ,Quality of life ,DEATHS ,Lífsgæði ,Health risk assessment ,Medicine, General & Internal ,Heilbrigðisvísindi ,General & Internal Medicine ,Heilbrigðisstefna ,Women ,Mortality ,Áhættugreining ,CHINESE POPULATION ,OBESITY PREVENTION ,Science & Technology ,HYPERTENSION ,MORTALITY ,Malnutrition ,Næringarskortur ,Karlar ,Cause of death/trends ,RA - Abstract
Correction in: LANCET Volume: 390 Issue: 10104 Pages: 1736-1736 Published: OCT 14 2017 ; LANCET Volume: 390 Issue: 10106 Pages: E38-E38 Published: OCT 28 2017., Background The Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of risk factor exposure and attributable burden of disease. By providing estimates over a long time series, this study can monitor risk exposure trends critical to health surveillance and inform policy debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2016. This study included 481 risk-outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk (RR) and exposure estimates from 22 717 randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources, according to the GBD 2016 source counting methods. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. Finally, we explored four drivers of trends in attributable burden: population growth, population ageing, trends in risk exposure, and all other factors combined. Findings Since 1990, exposure increased significantly for 30 risks, did not change significantly for four risks, and decreased significantly for 31 risks. Among risks that are leading causes of burden of disease, child growth failure and household air pollution showed the most significant declines, while metabolic risks, such as body-mass index and high fasting plasma glucose, showed significant increases. In 2016, at Level 3 of the hierarchy, the three leading risk factors in terms of attributable DALYs at the global level for men were smoking (124.1 million DALYs [95% UI 111.2 million to 137.0 million]), high systolic blood pressure (122.2 million DALYs [110.3 million to 133.3 million], and low birthweight and short gestation (83.0 million DALYs [78.3 million to 87.7 million]), and for women, were high systolic blood pressure (89.9 million DALYs [80.9 million to 98.2 million]), high body-mass index (64.8 million DALYs [44.4 million to 87.6 million]), and high fasting plasma glucose (63.8 million DALYs [53.2 million to 76.3 million]). In 2016 in 113 countries, the leading risk factor in terms of attributable DALYs was a metabolic risk factor. Smoking remained among the leading five risk factors for DALYs for 109 countries, while low birthweight and short gestation was the leading risk factor for DALYs in 38 countries, particularly in sub-Saharan Africa and South Asia. In terms of important drivers of change in trends of burden attributable to risk factors, between 2006 and 2016 exposure to risks explains an 9.3% (6.9-11.6) decline in deaths and a 10.8% (8.3-13.1) decrease in DALYs at the global level, while population ageing accounts for 14.9% (12.7-17.5) of deaths and 6.2% (3.9-8.7) of DALYs, and population growth for 12.4% (10.1-14.9) of deaths and 12.4% (10.1-14.9) of DALYs. The largest contribution of trends in risk exposure to disease burden is seen between ages 1 year and 4 years, where a decline of 27.3% (24.9-29.7) of the change in DALYs between 2006 and 2016 can be attributed to declines in exposure to risks. Interpretation Increasingly detailed understanding of the trends in risk exposure and the RRs for each risk-outcome pair provide insights into both the magnitude of health loss attributable to risks and how modification of risk exposure has contributed to health trends. Metabolic risks warrant particular policy attention, due to their large contribution to global disease burden, increasing trends, and variable patterns across countries at the same level of development. GBD 2016 findings show that, while it has huge potential to improve health, risk modification has played a relatively small part in the past decade., The Bill & Melinda Gates Foundation, Bloomberg Philanthropies.
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79. Global, regional, and national under-5 mortality, adult mortality, age-specific mortality, and life expectancy, 1970–2016: a systematic analysis for the Global Burden of Disease Study 2016
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Abajobir, Amanuel Alemu, Abate, Kalkidan Hassen, Abbafati, Cristiana, Abbas, Kaja M., Abd-Allah, Foad, Abera, Semaw Ferede, Abraha, Haftom Niguse, Abu-Raddad, Laith J., Abu-Rmeileh, Niveen M. E., Adedeji, Isaac Akinkunmi, Adedoyin, Rufus Adesoji, Adetifa, Ifedayo Morayo O., Adetokunboh, Olatunji, Afshin, Ashkan, Aggarwal, Rakesh, Agrawal, Anurag, Agrawal, Sutapa, Ahmad Kiadaliri, Aliasghar, Ahmed, Muktar Beshir, Aichour, Miloud Taki Eddine, Aichour, Amani Nidhal, Aichour, Ibthiel, Aiyar, Sneha, Akanda, Ali Shafqat, Akinyemiju, Tomi F., Akseer, Nadia, Al Lami, Faris Hasan, Alabed, Samer, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alam, Noore, Alasfoor, Deena, Aldridge, Robert William, Alene, Kefyalew Addis, Al-Eyadhy, Ayman, Alhabib, Samia, Ali, Raghib, Alizadeh-Navaei, Reza, Aljunid, Syed M., Alkaabi, Juma M., Alkerwi, Ala'a, Alla, François, Allam, Shalini D., Allebeck, Peter, Al-Raddadi, Rajaa, Alsharif, Ubai, Altirkawi, Khalid A., Alvis-Guzman, Nelson, Amare, Azmeraw T., Ameh, Emmanuel A., Amini, Erfan, Ammar, Walid, Amoako, Yaw Ampem, Anber, Nahla, Andrei, Catalina Liliana, Androudi, Sofia, Ansari, Hossein, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T., Anwari, Palwasha, Ärnlöv, Johan, Arora, Megha, Artaman, Al, Aryal, Krishna Kumar, Asayesh, Hamid, Asgedom, Solomon Weldegebreal, Asghar, Rana Jawad, Assadi, Reza, Assaye, Ashagre Molla, Atey, Tesfay Mehari, Atre, Sachin R., Avila-Burgos, Leticia, Avokpaho, Euripide Frinel G. Arthur, Awasthi, Ashish, Babalola, Tesleem Kayode, Bacha, Umar, Badawi, Alaa, Balakrishnan, Kalpana, Balalla, Shivanthi, Barac, Aleksandra, Barber, Ryan M., Barboza, Miguel A., Barker-Collo, Suzanne L., Bärnighausen, Till, Barquera, Simon, Barregard, Lars, Barrero, Lope H., Baune, Bernhard T., Bazargan-Hejazi, Shahrzad, Bedi, Neeraj, Beghi, Ettore, Béjot, Yannick, Bekele, Bayu Begashaw, Bell, Michelle L., Bello, Aminu K., Bennett, Derrick A., Bennett, James R., Bensenor, Isabela M., Benson, Jennifer, Berhane, Adugnaw, Berhe, Derbew Fikadu, Bernabé, Eduardo, Beuran, Mircea, Beyene, Addisu Shunu, Bhala, Neeraj, Bhansali, Anil, Bhaumik, Soumyadeep, Bhutta, Zulfiqar A., Bicer, Burcu Kucuk, Bidgoli, Hassan Haghparast, Bikbov, Boris, Birungi, Charles, Biryukov, Stan, Bisanzio, Donal, Bizuayehu, Habtamu Mellie, Bjerregaard, Peter, Blosser, Christopher D., Boneya, Dube Jara, Boufous, Soufiane, Bourne, Rupert R. A., Brazinova, Alexandra, Breitborde, Nicholas J. 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Ayala Quintanilla, B, Babalola, T, Bacha, U, Badawi, A, Balakrishnan, K, Balalla, S, Barac, A, Barber, R, Barboza, M, Barker-Collo, S, Bärnighausen, T, Barquera, S, Barregard, L, Barrero, L, Baune, B, Bazargan-Hejazi, S, Bedi, N, Beghi, E, Béjot, Y, Bekele, B, Bell, M, Bello, A, Bennett, D, Bennett, J, Bensenor, I, Benson, J, Berhane, A, Berhe, D, Bernabé, E, Beuran, M, Beyene, A, Bhala, N, Bhansali, A, Bhaumik, S, Bhutta, Z, Bikbov, B, Birungi, C, Biryukov, S, Bisanzio, D, Bizuayehu, H, Bjerregaard, P, Blosser, C, Boneya, D, Boufous, S, Bourne, R, Brazinova, A, Breitborde, N, Brenner, H, Brugha, T, Bukhman, G, Bulto, L, Bumgarner, B, Burch, M, Butt, Z, Cahill, L, Cahuana-Hurtado, L, Campos-Nonato, I, Car, J, Car, M, Cárdenas, R, Carpenter, D, Carrero, J, Carter, A, Castañeda-Orjuela, C, Castillo Rivas, J, Castro, F, Castro, R, Catalá-López, F, Chen, H, Chiang, P, Chibalabala, M, Chisumpa, V, Chitheer, A, Choi, J, Christensen, H, Christopher, D, Ciobanu, L, Cirillo, M, Cohen, A, Colquhoun, S, Coresh, J, Criqui, M, Cromwell, E, Crump, J, Dandona, L, Dandona, R, Dargan, P, Das Neves, J, Davey, G, Davitoiu, D, Davletov, K, De Courten, B, De Leo, D, Degenhardt, L, Deiparine, S, Dellavalle, R, Deribe, K, Deribew, A, Des Jarlais, D, Dey, S, Dharmaratne, S, Dherani, M, Diaz-Torné, C, Ding, E, Dixit, P, Djalalinia, S, Do, H, Doku, D, Donnelly, C, Dos Santos, K, Douwes-Schultz, D, Driscoll, T, Duan, L, Dubey, M, Duncan, B, Dwivedi, L, Ebrahimi, H, El Bcheraoui, C, Ellingsen, C, Enayati, A, Endries, A, Ermakov, S, Eshetie, S, Eshrati, B, Eskandarieh, S, Esteghamati, A, Estep, K, Fanuel, F, Faro, A, Farvid, M, Farzadfar, F, Feigin, V, Fereshtehnejad, S, Fernandes, J, Feyissa, T, Filip, I, Fischer, F, Foigt, N, Foreman, K, Frank, T, Franklin, R, Fraser, M, Friedman, J, Frostad, J, Fullman, N, Fürst, T, Furtado, J, Futran, N, Gakidou, E, Gambashidze, K, Gamkrelidze, A, Gankpé, F, Garcia-Basteiro, A, Gebregergs, G, Gebrehiwot, T, Gebrekidan, K, Gebremichael, M, Gelaye, A, Geleijnse, J, Gemechu, B, Gemechu, K, Genova-Maleras, R, Gesesew, H, Gething, P, Gibney, K, Gill, P, Gillum, R, Giref, A, Girma, B, Giussani, G, Goenka, S, Gomez, B, Gona, P, Gopalani, S, Goulart, A, Graetz, N, Gugnani, H, Gupta, P, Gupta, R, Gupta, T, Gupta, V, Haagsma, J, Hafezi-Nejad, N, Haghparast Bidgoli, H, Hakuzimana, A, Halasa, Y, Hamadeh, R, Hambisa, M, Hamidi, S, Hammami, M, Hancock, J, Handal, A, Hankey, G, Hao, Y, Harb, H, Hareri, H, Harikrishnan, S, Haro, J, Hassanvand, M, Havmoeller, R, Hay, R, Hay, S, He, F, Heredia-Pi, I, Herteliu, C, Hilawe, E, Hoek, H, Horita, N, Hosgood, H, Hostiuc, S, Hotez, P, Hoy, D, Hsairi, M, Htet, A, Hu, G, Huang, H, Huang, J, Iburg, K, Igumbor, E, Ileanu, B, Inoue, M, Irenso, A, Irvine, C, Islam, N, Jacobsen, K, Jaenisch, T, Jahanmehr, N, Jakovljevic, M, Javanbakht, M, Jayatilleke, A, Jeemon, P, Jensen, P, Jha, V, Jin, Y, John, D, John, O, Johnson, S, Jonas, J, Jürisson, M, Kabir, Z, Kadel, R, Kahsay, A, Kalkonde, Y, Kamal, R, Kan, H, Karch, A, Karema, C, Karimi, S, Karthikeyan, G, Kasaeian, A, Kassaw, N, Kassebaum, N, Kastor, A, Katikireddi, S, Kaul, A, Kawakami, N, Kazanjan, K, Keiyoro, P, Kelbore, S, Kemp, A, Kengne, A, Keren, A, Kereselidze, M, Kesavachandran, C, Ketema, E, Khader, Y, Khalil, I, Khan, E, Khan, G, Khang, Y, Khera, S, Khoja, A, Khosravi, M, Kibret, G, Kieling, C, Kim, C, Kim, D, Kim, P, Kim, S, Kim, Y, Kimokoti, R, Kinfu, Y, Kishawi, S, Kissimova-Skarbek, K, Kissoon, N, Kivimaki, M, Knudsen, A, Kokubo, Y, Kopec, J, Kosen, S, Koul, P, Koyanagi, A, Kravchenko, M, Krohn, K, Kuate Defo, B, Kucuk Bicer, B, Kuipers, E, Kulikoff, X, Kulkarni, V, Kumar, G, Kumar, P, Kumsa, F, Kutz, M, Lachat, C, Lagat, A, Lager, A, Lal, D, Lalloo, R, Lambert, N, Lan, Q, Van Lansingh, C, Larson, H, Larsson, A, Laryea, D, Lavados, P, Laxmaiah, A, Lee, P, Leigh, J, Leung, J, Leung, R, Levi, M, Li, Y, Liao, Y, Liben, M, Lim, S, Linn, S, Lipshultz, S, Liu, S, Lodha, R, Logroscino, G, Lorch, S, Lorkowski, S, Lotufo, P, Lozano, R, Lunevicius, R, Lyons, R, Ma, S, Macarayan, E, Machado, I, Mackay, M, Magdy Abd El Razek, M, Magis-Rodriguez, C, Mahdavi, M, Majdan, M, Majdzadeh, R, Majeed, A, Malekzadeh, R, Malhotra, R, Malta, D, Mantovani, L, Manyazewal, T, Mapoma, C, Marczak, L, Marks, G, Martinez-Raga, J, Martins-Melo, F, Massano, J, Maulik, P, Mayosi, B, Mazidi, M, Mcalinden, C, Mcgarvey, S, Mcgrath, J, Mckee, M, Mehata, S, Mehndiratta, M, Mehta, K, Meier, T, Mekonnen, T, Meles, K, Memiah, P, Memish, Z, Mendoza, W, Mengesha, M, Mengistie, M, Mengistu, D, Menon, G, Menota, B, Mensah, G, Meretoja, A, Meretoja, T, Mezgebe, H, Micha, R, Mikesell, J, Miller, T, Mills, E, Minnig, S, Mirarefin, M, Mirrakhimov, E, Misganaw, A, Mishra, S, Mohammad, K, Mohammadi, A, Mohammed, K, Mohammed, S, Mohan, M, Mohanty, S, Mokdad, A, Molla Assaye, A, Mollenkopf, S, Molokhia, M, Monasta, L, Montañez Hernandez, J, Montico, M, Mooney, M, Moore, A, Moradi-Lakeh, M, Moraga, P, Morawska, L, Moreno Velasquez, I, Mori, R, Morrison, S, Mruts, K, Mueller, U, Mullany, E, Muller, K, Murthy, G, Murthy, S, Musa, K, Nachega, J, Nagata, C, Nagel, G, Naghavi, M, Naidoo, K, Nanda, L, Nangia, V, Nascimento, B, Natarajan, G, Negoi, I, Nguyen, C, Nguyen, G, Nguyen, Q, Nguyen, T, Ningrum, D, Nisar, M, Nomura, M, Nong, V, Norheim, O, Norrving, B, Noubiap, J, Nyakarahuka, L, Obermeyer, C, O'Donnell, M, Ogbo, F, Oh, I, Okoro, A, Oladimeji, O, Olagunju, A, Olusanya, B, Olusanya, J, Oren, E, Ortiz, A, Osgood-Zimmerman, A, Ota, E, Owolabi, M, Oyekale, A, Mahesh, P, Pacella, R, Pakhale, S, Pana, A, Panda, B, Panda-Jonas, S, Park, E, Parsaeian, M, Patel, T, Patten, S, Patton, G, Paudel, D, Pereira, D, Perez-Padilla, R, Perez-Ruiz, F, Perico, N, Pervaiz, A, Pesudovs, K, Peterson, C, Petri, W, Petzold, M, Phillips, M, Piel, F, Pigott, D, Pishgar, F, Plass, D, Polinder, S, Popova, S, Postma, M, Poulton, R, Pourmalek, F, Prasad, N, Purwar, M, Qorbani, M, Rabiee, R, Radfar, A, Rafay, A, Rahimi-Movaghar, A, Rahimi-Movaghar, V, Rahman, M, Rahman, S, Rai, R, Rajsic, S, Ram, U, Rana, S, Ranabhat, C, Rao, P, Rawaf, S, Ray, S, Rego, M, Rehm, J, Reiner, R, Remuzzi, G, Renzaho, A, Resnikoff, S, Rezaei, S, Rezai, M, Ribeiro, A, Rokni, M, Ronfani, L, Roshandel, G, Roth, G, Rothenbacher, D, Roy, A, Rubagotti, E, Ruhago, G, Saadat, S, Sabde, Y, Sachdev, P, Sadat, N, Safdarian, M, Safi, S, Safiri, S, Sagar, R, Sahathevan, R, Sahebkar, A, Sahraian, M, Salama, J, Salamati, P, Salomon, J, Salvi, S, Samy, A, Sanabria, J, Sanchez-Niño, M, Santos, I, Santric Milicevic, M, Sarmiento-Suarez, R, Sartorius, B, Satpathy, M, Sawhney, M, Saxena, S, Saylan, M, Schmidt, M, Schneider, I, Schutte, A, Schwebel, D, Schwendicke, F, Seedat, S, Seid, A, Sepanlou, S, Servan-Mori, E, Shackelford, K, Shaheen, A, Shahraz, S, Shaikh, M, Shamsipour, M, Shamsizadeh, M, Islam, S, Sharma, J, Sharma, R, She, J, Shen, J, Shetty, B, Shi, P, Shibuya, K, Shigematsu, M, Shiri, R, Shiue, I, Shrime, M, Sigfusdottir, I, Silberberg, D, Silpakit, N, Silva, D, Silva, J, Silveira, D, Sindi, S, Singh, A, Singh, J, Singh, P, Singh, V, Sinha, D, Skiadaresi, E, Sligar, A, Smith, D, Sobaih, B, Sobngwi, E, Soneji, S, Soriano, J, Sreeramareddy, C, Srinivasan, V, Stathopoulou, V, Steel, N, Stein, D, Steiner, C, Stöckl, H, Stokes, M, Strong, M, Sufiyan, M, Suliankatchi, R, Sunguya, B, Sur, P, Swaminathan, S, Sykes, B, Szoeke, C, Tabarés-Seisdedos, R, Tadakamadla, S, Tadese, F, Tandon, N, Tanne, D, Tarajia, M, Tavakkoli, M, Taveira, N, Tehrani-Banihashemi, A, Tekelab, T, Tekle, D, Temam Shifa, G, Temsah, M, Terkawi, A, Tesema, C, Tesssema, B, Theis, A, Thomas, N, Thompson, A, Thomson, A, Thrift, A, Tiruye, T, Tobe-Gai, R, Tonelli, M, Topor-Madry, R, Topouzis, F, Tortajada, M, Tran, B, Truelsen, T, Trujillo, U, Tsilimparis, N, Tuem, K, Tuzcu, E, Tyrovolas, S, Ukwaja, K, Undurraga, E, Uthman, O, Uzochukwu, B, Van Boven, J, Varakin, Y, Varughese, S, Vasankari, T, Vasconcelos, A, Venketasubramanian, N, Vidavalur, R, Violante, F, Vishnu, A, Vladimirov, S, Vlassov, V, Vollset, S, Vos, T, Waid, J, Wakayo, T, Wang, Y, Weichenthal, S, Weiderpass, E, Weintraub, R, Werdecker, A, Wesana, J, Wijeratne, T, Wilkinson, J, Wiysonge, C, Woldeyes, B, Wolfe, C, Workicho, A, Workie, S, Xavier, D, Xu, G, Yaghoubi, M, Yakob, B, Yalew, A, Yan, L, Yano, Y, Yaseri, M, Ye, P, Yimam, H, Yip, P, Yirsaw, B, Yonemoto, N, Yoon, S, Yotebieng, M, Younis, M, Zaidi, Z, El Sayed Zaki, M, Zeeb, H, Zenebe, Z, Zerfu, T, Zhang, A, Zhang, X, Zodpey, S, Zuhlke, L, Lopez, A, Murray, C, Erasmus MC other, Emergency Medicine, Rehabilitation Medicine, Gastroenterology & Hepatology, Public Health, and Neurology
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Dánarmein ,Heilsufar ,Dánartíðni ,Lífslíkur ,Epidemiology ,Aldurshópar ,ALCOHOL ,Börn ,Medicine and Health Sciences ,Psychology ,DEVELOPING-COUNTRIES ,Children ,Konur ,Ungbörn ,Tölfræði ,Educational status ,Aldraðir ,Medicine (all) ,Global burden of disease/statistics and numerical data ,DEATH ,Men ,Þjóðir ,Staðtölur ,Stillbirth ,Sálfræði ,World health ,SURVIVAL ,Income ,CHILD-MORTALITY ,HEALTH ,Burðarmálsdauði ,Infants ,Age distribution ,HIV infections ,Child mortality ,Alnæmi ,Menntun ,GBD ,Fæðingartíðni ,RUSSIAN MORTALITY ,Birth rate ,Life Expectancy ,SDG 3 - Good Health and Well-being ,Women ,Mortality ,METAANALYSIS ,Faraldsfræði ,HIV ,Frjósemi ,Fertility ,Socioeconomic Factors ,Karlar ,Barnadauði ,Félagshagfræði ,Tekjur ,Older people ,Cause of death/trends ,RA - Abstract
Correction in: Group Author(s): GBD 2016 Mortality Collaborators LANCET Volume: 390 Issue: 10106 Pages: E38-E38 Published: OCT 28 2017, Background Detailed assessments of mortality patterns, particularly age-specific mortality, represent a crucial input that enables health systems to target interventions to specific populations. Understanding how all-cause mortality has changed with respect to development status can identify exemplars for best practice. To accomplish this, the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) estimated age-specific and sex-specific all-cause mortality between 1970 and 2016 for 195 countries and territories and at the subnational level for the five countries with a population greater than 200 million in 2016. Methods We have evaluated how well civil registration systems captured deaths using a set of demographic methods called death distribution methods for adults and from consideration of survey and census data for children younger than 5 years. We generated an overall assessment of completeness of registration of deaths by dividing registered deaths in each location-year by our estimate of all-age deaths generated from our overall estimation process. For 163 locations, including subnational units in countries with a population greater than 200 million with complete vital registration (VR) systems, our estimates were largely driven by the observed data, with corrections for small fluctuations in numbers and estimation for recent years where there were lags in data reporting (lags were variable by location, generally between 1 year and 6 years). For other locations, we took advantage of different data sources available to measure under-5 mortality rates (U5MR) using complete birth histories, summary birth histories, and incomplete VR with adjustments; we measured adult mortality rate (the probability of death in individuals aged 15-60 years) using adjusted incomplete VR, sibling histories, and household death recall. We used the U5MR and adult mortality rate, together with crude death rate due to HIV in the GBD model life table system, to estimate age-specific and sex-specific death rates for each location-year. Using various international databases, we identified fatal discontinuities, which we defined as increases in the death rate of more than one death per million, resulting from conflict and terrorism, natural disasters, major transport or technological accidents, and a subset of epidemic infectious diseases; these were added to estimates in the relevant years. In 47 countries with an identified peak adult prevalence for HIV/AIDS of more than 0.5% and where VR systems were less than 65% complete, we informed our estimates of age-sex-specific mortality using the Estimation and Projection Package (EPP)-Spectrum model fitted to national HIV/AIDS prevalence surveys and antenatal clinic serosurveillance systems. We estimated stillbirths, early neonatal, late neonatal, and childhood mortality using both survey and VR data in spatiotemporal Gaussian process regression models. We estimated abridged life tables for all location-years using age-specific death rates. We grouped locations into development quintiles based on the Sociodemographic Index (SDI) and analysed mortality trends by quintile. Using spline regression, we estimated the expected mortality rate for each age-sex group as a function of SDI. We identified countries with higher life expectancy than expected by comparing observed life expectancy to anticipated life expectancy on the basis of development status alone. Findings Completeness in the registration of deaths increased from 28% in 1970 to a peak of 45% in 2013; completeness was lower after 2013 because of lags in reporting. Total deaths in children younger than 5 years decreased from 1970 to 2016, and slower decreases occurred at ages 5-24 years. By contrast, numbers of adult deaths increased in each 5-year age bracket above the age of 25 years. The distribution of annualised rates of change in age-specific mortality rate differed over the period 2000 to 2016 compared with earlier decades: increasing annualised rates of change were less frequent, although rising annualised rates of change still occurred in some locations, particularly for adolescent and younger adult age groups. Rates of stillbirths and under-5 mortality both decreased globally from 1970. Evidence for global convergence of death rates was mixed; although the absolute difference between age-standardised death rates narrowed between countries at the lowest and highest levels of SDI, the ratio of these death rates-a measure of relative inequality-increased slightly. There was a strong shift between 1970 and 2016 toward higher life expectancy, most noticeably at higher levels of SDI. Among countries with populations greater than 1 million in 2016, life expectancy at birth was highest for women in Japan, at 86.9 years (95% UI 86.7-87.2), and for men in Singapore, at 81.3 years (78.8-83.7) in 2016. Male life expectancy was generally lower than female life expectancy between 1970 and 2016, and the gap between male and female life expectancy increased with progression to higher levels of SDI. Some countries with exceptional health performance in 1990 in terms of the difference in observed to expected life expectancy at birth had slower progress on the same measure in 2016. Interpretation Globally, mortality rates have decreased across all age groups over the past five decades, with the largest improvements occurring among children younger than 5 years. However, at the national level, considerable heterogeneity remains in terms of both level and rate of changes in age-specific mortality; increases in mortality for certain age groups occurred in some locations. We found evidence that the absolute gap between countries in age-specific death rates has declined, although the relative gap for some age-sex groups increased. Countries that now lead in terms of having higher observed life expectancy than that expected on the basis of development alone, or locations that have either increased this advantage or rapidly decreased the deficit from expected levels, could provide insight into the means to accelerate progress in nations where progress has stalled., Bill & Melinda Gates Foundation, and the National Institute on Aging and the National Institute of Mental Health of the National Institutes of Health.
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80. Intake of sugar sweetened beverages among children and adolescents in 185 countries between 1990 and 2018: population based study.
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Lara-Castor L, Micha R, Cudhea F, Miller V, Shi P, Zhang J, Sharib JR, Erndt-Marino J, Cash SB, Barquera S, and Mozaffarian D
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- Humans, Adolescent, Child, Female, Male, Child, Preschool, Young Adult, Global Health, Rural Population statistics & numerical data, Sugar-Sweetened Beverages statistics & numerical data, Sugar-Sweetened Beverages adverse effects
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Objective: To quantify global intakes of sugar sweetened beverages (SSBs) and trends over time among children and adolescents., Design: Population based study., Setting: Global Dietary Database., Population: Children and adolescents aged 3-19 years in 185 countries between 1990 and 2018, jointly stratified at subnational level by age, sex, parental education, and rural or urban residence., Results: In 2018, mean global SSB intake was 3.6 (standardized serving=248 g (8 oz)) servings/week (1.3 (95% uncertainly interval 1.0 to 1.9) in south Asia to 9.1 (8.3 to 10.1) in Latin America and the Caribbean). SSB intakes were higher in older versus younger children and adolescents, those resident in urban versus rural areas, and those of parents with higher versus lower education. Between 1990 and 2018, mean global SSB intakes increased by 0.68 servings/week (22.9%), with the largest increases in sub-Saharan Africa (2.17 servings/week; 106%). Of 185 countries included in the analysis, 56 (30.3%) had a mean SSB intake of ≥7 servings/week, representing 238 million children and adolescents, or 10.4% of the global population of young people., Conclusion: This study found that intakes of SSBs among children and adolescents aged 3-19 years in 185 countries increased by 23% from 1990 to 2018, parallel to the rise in prevalence of obesity among this population globally. SSB intakes showed large heterogeneity among children and adolescents worldwide and by age, parental level of education, and urbanicity. This research should help to inform policies to reduce SSB intake among young people, particularly those with larger intakes across all education levels in urban and rural areas in Latin America and the Caribbean, and the growing problem of SSBs for public health in sub-Saharan Africa., Competing Interests: Competing interests: All authors have completed the ICMJE uniform disclosure form at https://www.icmje.org/disclosure-of-interest/ and declare the following: support from the Bill & Melinda Gates Foundation, American Heart Association, and Consejo Nacional de Ciencia y Tecnología in Mexico. LLC reports research funding from the Bill & Melinda Gates Foundation, the American Heart Association, and Consejo Nacional de Ciencia y Tecnología in Mexico (CONACyT), outside of the submitted work. RM reports research funding from the Bill & Melinda Gates Foundation; and (ended) the US National Institutes of Health, Danone, and Nestle. She also reports consulting from Development Initiatives and as IEG chair for the Global Nutrition Report, outside of the submitted work. FC, JZ, and PS report research funding from the Bill & Melinda Gates Foundation, as well as the National Institutes of Health, outside of the submitted work. VM reports research funding the Canadian Institutes of Health Research and from the American Heart Association, outside the submitted work. JRS reports research funding from the Bill & Melinda Gates Foundation, as well as the National Institutes of Health, Nestlé, Rockefeller Foundation, and Kaiser Permanent Fund at East Bay Community Foundation, outside of the submitted work. SBC reports research funding from the US. National Institutes of Health, US. Department of Agriculture, the Rockefeller Foundation, US. Agency for International Development, and the Kaiser Permanente Fund at East Bay Community Foundation, outside the submitted work. SB reports funding from Bloomberg Philanthropies, CONACyT, United Nations International Children’s Emergency Fund (Unicef), and Fundación Rio Arronte, outside the submitted work. DM reports research funding from the US National Institutes of Health, the Bill & Melinda Gates Foundation, the Rockefeller Foundation, Vail Innovative Global Research, and the Kaiser Permanente Fund at East Bay Community Foundation; personal fees from Acasti Pharma, Barilla, Danone, and Motif FoodWorks; is on the scientific advisory board for Beren Therapeutics, Brightseed, Calibrate, Elysium Health, Filtricine, HumanCo, Instacart, January, Perfect Day, Tiny Organics, and (ended) Day Two, Discern Dx, and Season Health; has stock ownership in Calibrate and HumanCo; and receives chapter royalties from UpToDate, outside the submitted work. The investigators did not receive funding from a pharmaceutical company or other agency to write this report, and declare no other relationships or activities that could appear to have influenced the submitted work., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY. No commercial re-use. See rights and permissions. Published by BMJ.)
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81. Let's end corporate sponsorship of sporting events.
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Buse K, Barquera S, and Wetzel M
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- Humans, Sports ethics, Sports economics
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Competing Interests: Competing interests: KB is a board member of the World Obesity Federation and chairs its Policy and Prevention Committee. SB is President of the World Obesity Federation.
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- 2024
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82. Sodium and potassium excretion and its association with cardiovascular disorders in Mexican adults.
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Campos Nonato I, Mendoza K, Vargas Meza J, Flores Aldana M, and Barquera S
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Worldwide, as well as in Mexico, the leading cause of death is cardiovascular disease (CVD). Hypertension is the main risk factor for CVD; about 50% of the adult population suffers from this condition. High sodium (Na) intake combined with low potassium (K) intake can trigger cardiovascular disorders such as high blood pressure (BP). The aim of this study was to estimate the mean excretion of Na and K in Mexican adults using a spot urine sample, and its association with cardiovascular disorders. Information on 2,778 adults, 20-59 years of age, who participated in ENSANUT-2016 was analyzed. Na and K were estimated using Tanaka formulae. Biomarkers such as glucose, total cholesterol, triglycerides, HDL cholesterol and LDL cholesterol, and anthropometry were measured. Mean Na was 3,354 mg/day (95%CI: 3,278, 3,429), 1,440 mg/day of K (95%CI: 1,412, 1,469), and the Na-K ratio was 2.4. The excretion of Na was greater in adults with high BP (3,542 mg/day) compared to those with normal BP (3,296 mg/day). In adults with hypertension, excretion of K was 10% greater (1,534 mg/day) than in adults with normal BP (1,357 mg/day). In adults with moderate reduction of renal function, Na excretion was 22% less (2,772 mg/day) than in adults with normal kidney function (3,382 mg/day). The results of this study show that the cardiovascular health of Mexican adults is at risk, as they showed high Na excretion and low K excretion., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Campos Nonato, Mendoza, Vargas Meza, Flores Aldana and Barquera.)
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83. Self-reported decreases in the purchases of selected unhealthy foods resulting from the implementation of warning labels in Mexican youth and adult population.
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Contreras-Manzano A, White CM, Nieto C, Quevedo KL, Vargas-Meza J, Hammond D, Thrasher JF, Barquera S, and Jáuregui A
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- Humans, Adolescent, Male, Female, Mexico, Adult, Cross-Sectional Studies, Young Adult, Choice Behavior, Nutrition Policy, Middle Aged, Diet, Healthy statistics & numerical data, Food Labeling, Self Report, Consumer Behavior, Food Preferences, Sugar-Sweetened Beverages
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Background: Front-of-package nutritional warning labels (WLs) are designed to facilitate identification and selection of healthier food choices. We assessed self-reported changes in purchasing different types of unhealthy foods due to WLs in Mexico and the association between the self-reported reductions in purchases of sugary beverages and intake of water and sugar-sweetened beverages., Methods: Data came from 14 to 17 year old youth (n = 1,696) and adults ≥ 18 (n = 7,775) who participated in the Mexican arm of the 2020-2021 International Food Policy Study, an annual repeat cross-sectional online survey. Participants self-reported whether the WLs had influenced them to purchase less of each of nine unhealthy food categories due to WLs. Among adults, a 23-item Beverage Frequency Questionnaire was used derive past 7-day intake of water and sugary beverages analyzed to determine the relationship between self-reported reductions in purchasing sugary drinks due to the WLs. Multilevel mixed-effects logistic regression models were fitted to estimate the percentage of participants who self-reported reducing purchases within each food group, and overall. Sociodemographic characteristics associated with this reduction were investigated as well., Results: Overall, 44.8% of adults and 38.7% of youth reported buying less of unhealthy food categories due to the implementation of WL, with the largest proportion reporting decreased purchases of cola, regular and diet soda. A greater impact of WLs on the reported purchase of unhealthy foods was observed among the following socio-demographic characteristics: females, individuals who self-identified as indigenous, those who were overweight, individuals with lower educational levels, those with higher nutrition knowledge, households with children, and those with a significant role in household food purchases. In addition, adults who reported higher water intake and lower consumption of sugary beverages were more likely to report reduced purchases of sugary drinks due to the WLs. Adults who reported greater water intake and lower sugary beverages intake were significantly more likely to report buying fewer sugary drinks due to the WLs., Conclusion: Our findings suggest that implementation of WLs has reduced perceived purchases of unhealthy foods in Mexico. These results underscore the potential positive impact of the labeling policy particularly in subpopulations with lower levels of education and among indigenous adults., (© 2024. The Author(s).)
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84. Pre-Gestational Obesity and Gestational Weight Gain as Predictors of Childhood Obesity.
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Hernández-Barrera L, Trejo-Valdivia B, Téllez-Rojo MM, Baccarelli A, Wright R, Cantoral A, and Barquera S
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- Humans, Female, Pregnancy, Adult, Child, Child, Preschool, Mexico epidemiology, Male, Risk Factors, Overweight epidemiology, Overweight physiopathology, Obesity epidemiology, Obesity physiopathology, Gestational Weight Gain, Pediatric Obesity epidemiology, Pediatric Obesity physiopathology, Body Mass Index
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Objective: To evaluate the associations of pre-gestational body mass index (BMI) and gestational weight gain (GWG) with the risks of overweight, obesity, and adiposity in the first seven years of life in the offspring of a cohort of pregnant women., Methods: Analysis of 751 mothers and their children participating in the PROGRESS cohort. These women were recruited in Mexico City between 2007 and 2010. Pre-gestational BMI was classified as normal, overweight, and obesity according to the WHO. GWG was calculated as the difference between the last reported pre-pregnancy weight and the pre-gestational weight and categorized as inadequate, adequate, or excessive, according to US IOM recommendations. Children's anthropometry was evaluated at 4-5 and 6-7 years of age. Adiposity was classified into three groups: normal (BMI z-score and waist circumference), overweight (BMI z-score>1), and overweight plus abdominal obesity (OW+AO). A generalized structural equation model (GSEM) was constructed to account for the temporal relationship between variables and to assess direct and indirect effects., Results: A total of 49.3% of the women had excessive (13.8 ± 4.2 kg) and 19.8% inadequate (3.15 ± 3.4 kg) GWG. Women with pre-gestational overweight or obesity were more likely to have excessive GWG (OR 1.9 [95% CI: 1.32, 2.74] and 3.50 [95% CI: 1.83, 6.69], respectively). In the GSEM, excessive GWG was directly associated with OW+AO at 4-5 years. At 6-7 years, pre-gestational obesity was associated with OW+AO., Conclusion: Pre-gestational obesity and excessive GWG were independent predictors of childhood obesity., Competing Interests: Disclosure The authors declare that they have no actual or potential competing financial interests. Completed disclosure of interest forms are available to view online as supporting information., (Copyright © 2024. Published by Elsevier Inc.)
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- 2024
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85. A high density of ultra-processed food, alcohol & tobacco retail stores, and social inequalities are associated with higher mortality rates of non-communicable diseases in Mexican adults: 2005 to 2021.
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Garduño-Alanis A, Contreras-Manzano A, Salgado JC, Lamadrid-Figueroa H, Curi-Quinto K, and Barquera S
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- Adult, Humans, Food, Processed, Mexico epidemiology, Socioeconomic Factors, Poverty, Noncommunicable Diseases epidemiology
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Background: Non-communicable diseases (NCDs) are the leading causes of mortality in Mexico. Factors contributing to NCDs-related deaths may vary across small geographic areas such as municipalities. We aimed to predict municipal-level factors associated with NCD mortality in Mexican adults from 2005 to 2021 using the small-area analysis (SSA) approach., Methods: We gathered data on population sociodemographic, access to healthcare services, and mortality records at the municipal-level from census and public institutions from 2005 to 2021. We identified municipal predictors of NCDs mortality rates (MR) using negative binomial regression models., Results: A total of 584,052 observations of Mexican adults were analyzed. The national expected NCDs MR per 100,000 inhabitants was 210.7 (95%CI: 196.1-226.7) in 2005 and increased to 322.4 (95%CI: 300.3-346.4) by 2021. Predictors of NCDs mortality (quintile 5 vs. quintile 1) included; indigeneity (IRR = 1.15, 95%CI: 1.12-1.19), poverty (IRR = 1.14, 95%CI: 1.13-1.15), affiliation with Mexican Social Security Institute (IRR = 1.11, 95%CI: 1.09-1.14), households with television (IRR = 1.14, 95%CI: 1.11-1.17), and high density of ultra-processed food, alcohol & tobacco retail stores (IRR = 1.15, 95%CI: 1.13-1.17). The greatest increases in MR were observed in municipalities from Oaxaca (>200% increments)., Conclusion: There was an overall increase in NCDs MR from 2005 to 2021, with a significant geographic variation among Mexican municipalities. The results of this study highlight the importance of identifying priority areas in the country that urgently require public policies focused on local factors associated with deaths from NCDs, such as the regulation of the ultra-processed food, alcohol & tobacco retail stores, and efforts to reduce social inequalities., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Garduño-Alanis et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
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- 2024
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86. Sociodemographic differences in nutrition labels effect on Chilean and Mexican youth.
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Quevedo KL, Jáuregui A, Nieto C, Contreras-Manzano A, White CM, Vanderlee L, Barquera S, Corvalán C, and Hammond D
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Objective: To examine sociodemographic differences in the awareness, understanding, use and effect of nutrition labels among Mexican and Chilean youth., Methods: Online surveys among youth (10-17 years) were obtained in 2019 (n=2631). Participants reported their awareness, understanding, and use of their country-specific nutrition facts tables (NFT) and front-of-pack labels (FOPL) (Chile: warning labels [WLs]; Mexico: guideline daily amounts [GDA]). Additionally, participants reported their perceived healthfulness of a sweetened fruit drink after viewing one of six versions of it with different FOPL (no-label control, Health Star Rating, WLs, GDAs, Traffic Light, or Nutri-Score) during an experimental task., Results: Higher self-reported nutrition knowledge was associated with higher NFT and FOPL awareness, understanding, and use, except for WL use. WLs were the most effective FOPL in decreasing the perceived healthfulness of the sweetened fruit drink compared to a no-label condition and other FOP labels. In Chile, the effect of GDA differed by income adequacy, while in Mexico Nutri-Score differed by age., Conclusions: Results suggest that nutrition label awareness, use, understanding, and impact differ across demographics, favoring higher income and nutrition knowledge. Despite this, WLs are likely to have a positive impact on nutrition-related knowledge and behaviors among Mexican and Chilean youth, independently of their socio-demographic groups.
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- 2024
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87. Development of a crowdsourcing- and gamification-based mobile application to collect epidemiological information and promote healthy lifestyles in Mexico.
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Mendoza K, Villalobos-Daniel VE, Jáuregui A, Valero-Morales I, Hernández-Alcaraz C, Zacarías-Alejandro N, Alarcon-Guevara RO, and Barquera S
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- Adult, Humans, Gamification, Healthy Lifestyle, Mexico, Review Literature as Topic, Pilot Projects, Crowdsourcing, Mobile Applications, Noncommunicable Diseases
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We developed a mobile application to promote healthy lifestyles and collect non-communicable disease (NCD) data in Mexico. Its theoretical foundations are supported by a framework-guided literature review. With design sprints, Scrum, Model-View-Controller, and Representational State Transfer architecture, we operationalized evidence-based nutrition/physical activity information into a crowdsourcing- and gamification-based application. The application was piloted for three months to monitor the response of 520 adults. Potential improvements were characterized, considering benchmarking, expert guidance, and standards. Salud Activa (English: Active Health) has two crowdsourcing modules: Nutritional scanner, scanning products' bar codes, providing nutritional data, and allowing new product registry feeding our databases; Surveys, comprising gradually-released NCD questions. Three intervention modules were generated: Drinks diary, a beverage assessment component to receive hydration recommendations; Step counter, monitoring users' steps via Google Fit/Health-iOS; Metabolic Avatar, interconnecting modules and changing as a function of beverage and step records. The 3-month median of Salud Activa use was seven days (IQR = 3-12), up to 35% of participants completed a Survey section, and 157 food products were registered through Nutritional scanner. Better customization might benefit usability and user engagement. Quantitative and qualitative data will enhance Salud Activa's design, user uptake, and efficacy in interventions delivered through this platform., (© 2024. The Author(s).)
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- 2024
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88. Let's talk differently about obesity.
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Buse K, Ralston J, and Barquera S
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- Humans, Obesity prevention & control
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Competing Interests: Competing interests: The authors declare their association with the World Obesity Federation. KB is Chair of its Policy and Prevention Committee. SB is President-Elect. JR is CEO.
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- 2024
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89. Perspective: Mexico's Experience in Building a Toolkit for Obesity and Noncommunicable Diseases Prevention.
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Rivera JA, Colchero MA, Pérez-Ferrer C, and Barquera S
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- Humans, Mexico epidemiology, Obesity prevention & control, Obesity epidemiology, Diet, Public Health, Noncommunicable Diseases epidemiology, Noncommunicable Diseases prevention & control
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Noncommunicable diseases (NCDs) are a leading cause of death and disability worldwide, with a higher risk of death in low- and middle-income countries. Diet and excess weight are risk factors for NCDs. In Mexico, the prevalence of overweight and obesity increased dramatically in the last 30 y and is among the highest in the world. To address this public health problem, governments and public health professionals have several policy instruments available. In this study, we present the policy instruments currently approved in Mexico, which include fiscal, informational, and authoritative tools that aim to improve the food environment and promote healthy behaviors (taxes, school food guidelines, front-of-pack labeling, marketing regulations, and dietary guidelines). These types of interventions are important in regions like Latin America, where social inequities and poor access to information are common, and individual healthy choices are often limited. These interventions target the environments in which individuals live, study, work, and seek entertainment, while limiting access to unhealthy choices and offering information to promote healthy alternatives. The Mexican experience in design, implementation, and evaluation of policies to improve the food environment can be useful for other low- and middle-income countries facing similar challenges., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)
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- 2024
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90. Análisis de los argumentos recibidos en la consulta pública para el etiquetado frontal de advertencia mexicano.
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Tolentino-Mayo L, Durán R, Espinosa F, Ferré I, Munguía A, and Barquera S
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Objetivo: Analizar los diferentes elementos en los argumentos recibidos durante la consulta pública del Proyecto de Modificación a la Norma Oficial Mexicana-051 (NOM-051), con énfasis en la protección de niñas, niños y adolescentes (NNA). Material y métodos. Se analizó la información de 1 095 argumentos, se identificó a los actores clave y se realizó un análisis de contenido para conocer la postura, a favor o en contra de los numerales relacionados con la protección a NNA. El análisis se hizo en el programa NVivo., Resultados: Se identificaron 781 actores clave. Durante la consulta pública se identificaron cuatro tácticas del sector privado para interferir en el proceso de la NOM-051: a) grupos fachada que enviaron comentarios en contra de la NOM-051; b) cuestionar la evidencia científica sobre la relación del consumo de edulcorantes y el desarrollo de obesidad en escolares; c) cuestionar la efectividad del uso del etiquetado de advertencia para edulcorantes; d) responsabilizar a los individuos de su enfermedad. Conclusión. La interferencia del sector privado en el proceso de implementación de la NOM-051 fue evidente en los argumentos enviados durante la consulta pública.
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- 2023
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91. The relationship between parent's self-reported exposure to food marketing and child and parental purchasing and consumption outcomes in five countries: findings from the International Food Policy Study.
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Soares Guimarães J, Pauzé E, Potvin Kent M, Barquera S, Jáuregui A, Sacks G, Vanderlee L, and Hammond D
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- Child, Humans, United States, Self Report, Beverages, Parents, Food, Marketing
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Food and beverage marketing influences children's food preferences and dietary intake. Children's diets are also heavily influenced by their family environment. The aim of this study was to assess the relationship between parent's self-reported exposure to unhealthy food marketing and a range of outcomes related to children's desire for and intake of unhealthy foods and beverages. The study also sought to examine whether these outcomes varied across different countries. The analysed data are from the International Food Policy Study and were collected in 2018 using an online survey. The sample included 5764 parents of children under 18, living in Australia, Canada, Mexico, the United Kingdom, or the United States. Binary logistic regressions assessed the link between the number of parental exposure locations and children's requests for and parental purchases of unhealthy foods. Generalized ordinal regression gauged the relationship between the number of exposure locations and children's consumption of such items. Interaction terms tested if these associations varied by country. Parental exposure to unhealthy food marketing was positively associated with parents reporting child purchase requests and purchase outcomes; and differed by country. Increased parental exposure to unhealthy food marketing was associated with slightly lower odds of children's weekly consumption of unhealthy foods, and this association varied by country. In conclusion, parental report of a greater range of food marketing exposure was associated with a range of outcomes that would increase children's exposure to unhealthy food products or their marketing. Governments should consider developing more comprehensive restrictions on the marketing of unhealthy foods., (© The Author(s) 2023.)
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- 2023
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92. The state of food systems worldwide in the countdown to 2030.
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Schneider KR, Fanzo J, Haddad L, Herrero M, Moncayo JR, Herforth A, Remans R, Guarin A, Resnick D, Covic N, Béné C, Cattaneo A, Aburto N, Ambikapathi R, Aytekin D, Barquera S, Battersby J, Beal T, Molina PB, Cafiero C, Campeau C, Caron P, Conforti P, Damerau K, Di Girolamo M, DeClerck F, Dewi D, Elouafi I, Fabi C, Foley P, Frazier TJ, Gephart J, Golden C, Fischer CG, Hendriks S, Honorati M, Huang J, Kennedy G, Laar A, Lal R, Lidder P, Loken B, Marshall Q, Masuda YJ, McLaren R, Miachon L, Muñoz H, Nordhagen S, Qayyum N, Saisana M, Suhardiman D, Sumaila UR, Cullen MT, Tubiello FN, Vivero-Pol JL, Webb P, and Wiebe K
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- Food Supply
- Abstract
This Analysis presents a recently developed food system indicator framework and holistic monitoring architecture to track food system transformation towards global development, health and sustainability goals. Five themes are considered: (1) diets, nutrition and health; (2) environment, natural resources and production; (3) livelihoods, poverty and equity; (4) governance; and (5) resilience. Each theme is divided into three to five indicator domains, and indicators were selected to reflect each domain through a consultative process. In total, 50 indicators were selected, with at least one indicator available for every domain. Harmonized data of these 50 indicators provide a baseline assessment of the world's food systems. We show that every country can claim positive outcomes in some parts of food systems, but none are among the highest ranked across all domains. Furthermore, some indicators are independent of national income, and each highlights a specific aspiration for healthy, sustainable and just food systems. The Food Systems Countdown Initiative will track food systems annually to 2030, amending the framework as new indicators or better data emerge., (© 2023. The Author(s).)
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- 2023
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93. Effects of front-of-package caffeine and sweetener disclaimers in Mexico: cross-sectional results from the 2020 International Food Policy Study.
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Arellano-Gómez LP, Jáuregui A, Nieto C, Contreras-Manzano A, Quevedo KL, White CM, Thrasher JF, Davis RE, Hammond D, and Barquera S
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- Child, Adolescent, Humans, Male, Aged, Mexico, Cross-Sectional Studies, Nutrition Policy, Food Labeling, Consumer Behavior, Sweetening Agents, Caffeine
- Abstract
Objective: Front-of-package warning labels introduced in Mexico in 2020 included disclaimers that caution against allowing children to consume products with non-sugary sweeteners and caffeine. We examined the awareness and use of the disclaimers among Mexican adults and youth 1 month after the regulation was implemented. We also investigated their impact on the perceived healthfulness of industrialised beverages designed for children., Design: Data on the awareness and use of the disclaimers were analysed. Two between-subjects experiments examined the effect of a sweetener disclaimer (Experiment 1, youth and adults) or a caffeine disclaimer (Experiment 2, only adults) on the perceived healthfulness of industrialised beverages. Interactions between experimental conditions and demographic characteristics were tested., Setting: Online survey in 2020., Participants: Mexican adults (≥18 years, n 2108) and youth (10-17 years, n 1790)., Results: Most participants (>80 %) had seen the disclaimers at least rarely, and over 60 % used them sometimes or frequently. The sweetener disclaimer led to a lower perceived healthfulness of a fruit drink (adults: 2·74 ± 1·44; youth: 2·04 ± 0·96) compared with the no-disclaimer condition (adults: 3·17 ± 1·54; youth: 2·32 ± 0·96) ( t 's: >4·0, P values: <0·001). This effect was larger among older adults and male youth. The caffeine disclaimer did not affect adult's perceived healthfulness of a caffeinated drink ( t = 0·861, P value = 0·3894)., Conclusions: There were high awareness and use of the sweeteners and caffeine disclaimers shortly after the warning labels were implemented. The sweetener disclaimer appears to be helping consumers modify their perceptions regarding industrialised beverages for children. Findings may help decision-makers improve the regulation and better target communication strategies.
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- 2023
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94. Self-reported decreases in the purchases of selected unhealthy foods resulting from the implementation of warning labels in Mexican youth and adult population.
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Contreras-Manzano A, White CM, Nieto C, Quevedo KL, Vargas-Meza J, Hammond D, Thrasher JF, Barquera S, and Jáuregui A
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Background: Front-of-package nutritional warning labels (WLs) are designed to facilitate identification and selection of healthier food choices. We assessed self-reported changes in purchasing different types of unhealthy foods due to WLs in Mexico and the association between the self-reported reductions in purchases of sugary beverages and intake of water and sugar-sweetened beverages., Methods: Data came from 14-17 year old youth (n=1,696) and adults ≥18 (n=7,775) who participated in the Mexican arm of the 2020-2021 International Food Policy Study, an annual repeat cross-sectional online survey. Participants self-reported whether the WLs had influenced them to purchase less of each of ten unhealthy food categories due to WLs. Among adults, a 23-item Beverage Frequency Questionnaire was used derive past 7-day intake of water and sugary beverages analyzed to determine the relationship between self-reported reductions in purchasing sugary drinks due to the WLs. Multilevel mixed-effects logistic regression models were fitted to estimate the percentage of participants who self-reported reducing purchases within each food group, and overall. Sociodemographic characteristics associated with this reduction were investigated as well., Results: Overall, 44.8% of adults and 38.7% of youth reported buying less of unhealthy food categories due to the implementation of WL, with the largest proportion reporting decreased purchases of cola, regular and diet soda. A greater impact of WLs on the reported purchase of unhealthy foods was observed among the following socio-demographic characteristics: females, individuals who self-identified as indigenous, those who were overweight, individuals with lower educational levels, those with higher nutrition knowledge, households with children, and those with a significant role in household food purchases. In addition, adults who reported higher water intake and lower consumption of sugary beverages were more likely to report reduced purchases of sugary drinks due to the WLs. Adults who reported greater water intake and lower sugary beverages intake were significantly more likely to report buying fewer sugary drinks due to the WLs., Conclusion: Our findings suggest that implementation of WLs has reduced purchases of unhealthy foods in Mexico. These results underscore the positive impact of the labeling policy particularly in subpopulations with lower levels of education and among indigenous adults.
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- 2023
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95. Factores asociados con el cumplimiento de los comportamientos del movimiento en adultos mexicanos: Ensanut 2022.
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Medina C, Jáuregui A, Hernández C, González C, Blas N, Campos I, and Barquera S
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Objetivo: Examinar las características sociodemográficas e indicadores de salud asociados con el cumplimiento de las recomendaciones de los comportamientos del movimiento en adultos mexicanos. Material y métodos. Estudio transversal que utilizó datos de la Encuesta Nacional de Salud y Nutrición (Ensanut) 2022. Se obtuvo información de actividad física (AF), sedentarismo y sueño, características sociodemográficas e indicadores de salud en adultos de 20-78 años. Para el análisis se utilizaron regresiones logísticas y lineales ajustadas y no por covariables., Resultados: Los adultos que viven en áreas urbanas tuvieron mayor posibilidad de no cumplir las recomendaciones de actividad física, sedentarismo, sueño y los comportamientos del movimiento (CM) en conjunto. No cumplir las recomendaciones de los tres CM se asoció con mayores niveles de glucosa, colesterol y tensión arterial elevada. Conclusión. La asociación de los CM con indicadores de salud muestra la importancia de identificar estrategias para promover estos comportamientos en la población mexicana.
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- 2023
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96. Hypothetical impact of the Mexican front-of-pack labeling on intake of critical nutrients and energy.
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Villaverde P, Tolentino-Mayo L, Cruz-Casarrubias C, Salgado JC, Aburto TC, and Barquera S
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- Humans, Mexico epidemiology, Nutrients, Sugars, Sodium, Food Labeling methods, Energy Intake
- Abstract
Background: Since 2020 in Mexico, front-of-pack warning labels (FOPWL) have been implemented in processed products. Evidence supports warning labels allow consumers to identify unhealthy products. We aimed to evaluate the hypothetical impact of the FOPWL regulation on the Mexican population's intake of critical nutrients and energy, based on the replacement of food and beverages using 4 hypothetical scenarios which represented the phases of the regulation., Methods: Dietary data were collected using a standardized 24-h dietary recall from the 2016 Mexican National Health and Nutrition Survey (n = 4184). To evaluate the hypothetical impact of FOPWL, the nutritional content of critical nutrients in processed products was evaluated according to the Mexican Official Standard 051 (NOM-051). Then, we replaced products with several warning labels (WL) with those with a fewer number of them or with non-processed food. For the replacement, 4 hypothetical scenarios were established: scenario 1: the current consumption of the Mexican Population, scenario 2: the replacement during the first phase of the norm, scenario 3: the replacement in the second phase and scenario 4: the replacement in the last phase. We estimated the means, confidence intervals (CI 95%), and the mean percentage change of energy, saturated fat, trans-fat, added sugars, and sodium intake during the second, third, and the fourth scenarios., Results: According to the norm, in the second scenario, the majority of the products presented a label for energy (52.6%) whereas in the third (56.4%) and fourth (61.2%) scenarios were for sodium. In contrast, trans-fat was the least labeled nutrient in all the scenarios (from 2.1 to 4.1%). In the fourth scenario, we observed a reduction of the intake of energy intake to 15.4% as well as saturated fat (- 20%, CI 95% - 18.4; - 21.6), trans-fat (- 8.2%, CI 95% - 6.4; - 10.1) and sodium (- 12.7%, CI 95% - 11.3; - 14.1). The most important reduction was observed for added sugars intake (until - 54.1%, CI 95% - 51; - 57.1)., Conclusions: FOPWL could be an effective strategy to decrease energy consumption and nutrients of concern. If consumers use the FOPWL, it would be an important change in critical nutrients intake. These results support that FOPWL might help the Mexican population to choose healthier nutrition alternatives., (© 2023. The Author(s).)
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- 2023
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97. Latin America and the Caribbean Code Against Cancer 1st edition: Tobacco and nicotine-related products, secondhand smoke, and alcohol and cancer.
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Reynales-Shigematsu LM, Barnoya J, Cavalcante T, Aburto TC, Romieu I, Stern MC, Barquera S, Corvalán C, Hallal PC, Canelo-Aybar C, Alvarado-Villacorta R, Espina C, Feliu A, and Rivera JA
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- Child, Adolescent, Humans, Nicotine, Latin America epidemiology, Ethanol, Caribbean Region epidemiology, Tobacco Smoke Pollution adverse effects, Tobacco Smoke Pollution prevention & control, Electronic Nicotine Delivery Systems, Neoplasms epidemiology, Neoplasms etiology, Neoplasms prevention & control
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Tobacco, secondhand smoke (SHS), and alcohol, all carcinogens, are leading preventable cancer risk factors in Latin America and the Caribbean (LAC). Since 2000, smoking and SHS exposure have significantly decreased in the region. Yet alcohol consumption remains high. The entry of nicotine-related products such as electronic cigarettes (e-cigs) threatens achievements made in tobacco control and chronic diseases prevention, including cancer. E-cigs use is likely associated with smoking initiation among adolescents who had never smoked and dual use with combustible tobacco products. Therefore, the LAC Code Against Cancer recommends to the public actions they can take to reduce their risk of cancer: 1. Don't smoke or use any type of tobacco. If you do, quitting is possible, with professional help if needed. Don't use e-cigarettes either, as they lead to tobacco use. 2. Make your home a smoke-free place. Respect and promote laws that ensure smoke-free spaces to protect our health. and 3. Avoid drinking alcoholic beverages. This helps prevent several types of cancer. The Code recommends to policymakers a package of cost-effective policies based on the MPOWER and SAFER to prevent cancer at the population level. It also recommends that primary care health professionals: 1. Ask all their patients and their families whether they smoke or vape, inform them about the harms of smoking and vaping, and promote tobacco and nicotine related products cessation strategies among users. 2. Inform about the harms of exposure to SHS, especially among children, and promote smoke-free environments, and 3. Prevent alcohol use by their patients and their families, use tools to assess use, intensity, and frequency, and apply brief counseling intervention to support alcohol abstinence in primary care., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)
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- 2023
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98. Public support for food policies in Mexican adults: Findings from the International Food Policy Study, 2017-2021.
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Quevedo KL, Jáuregui A, Nieto C, Ortiz-Panozo E, Contreras-Manzano A, Barquera S, Vanderlee L, White CM, and Hammond D
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Deaths attributable to unhealthful eating underscore the need to improve dietary patterns through upstream, policy-led solutions. The approval and successful implementation of food policies is partly determined by their public acceptance. Little is known about public support for food policies in Mexico. We aimed to investigate the level of public support for 30 food policies, grouped into 5 domains, and their associated characteristics among Mexican adults. Data are from the 2017-2021 International Food Policy Study (IFPS), a cross-sectional web-based survey of adults. Differences in public support across years were estimated using linear regression models. The association between demographic characteristics and policy support was analyzed using multivariate logistic regression models. The highest mean support was for the subsidies and benefits domain, followed by the labelling and reformulation domain. The level of support varied across years and policy domains. Support was higher in 2019 compared to 2017 and 2018, and subsequently lower in 2020 and 2021 compared to previous years. Older age was associated with greater support across all domains (OR ranged from 0.002 to 0.004, p < 0.01). Female participants and those selfidentifying as indigenous showed greater support for certain policy domains, whereas higher income adequacy was associated with lower support for other policy domains. In Mexico, support for food policies varies across subpopulations. Our findings may serve as a guide to the development and promotion of food policies in Mexico, as well as to improve their feasibility and success., Competing Interests: Declaration of Competing Interest David Hammond has provided paid expert testimony on behalf of public health authorities in response to legal claims from the food and beverage industry. All remaining authors declare no conflicts of interest., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)
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- 2023
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99. Latin American and the Caribbean Code Against Cancer 1st edition: Weight, physical activity, diet, breastfeeding, and cancer.
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Aburto TC, Romieu I, Stern MC, Barquera S, Corvalán C, Hallal PC, Reynales-Shigematsu LM, Barnoya J, Cavalcante TM, Canelo-Aybar C, Santero M, Feliu A, Espina C, and Rivera JA
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- Female, Humans, Breast Neoplasms, Caribbean Region epidemiology, Colorectal Neoplasms epidemiology, Colorectal Neoplasms etiology, Colorectal Neoplasms prevention & control, Latin America epidemiology, Weight Gain, Breast Feeding, Diet, Exercise, Neoplasms prevention & control
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In Latin America and the Caribbean a considerable proportion of the population have excess body weight, do not meet the recommendations of physical activity and healthy diet, and have suboptimal rates of breastfeeding. Excess body weight is associated with at least 15 cancer sites, physical activity protects against three cancers, with some evidence suggesting a protective effect for eight more cancer sites, and sedentary behavior probably increases the risk of five cancer sites. Fiber and wholegrains protect against colorectal cancer, high intake of fruits and vegetables could reduce the risk of aerodigestive cancers; processed and red meat increase the risk of colorectal cancer; and very hot beverages are associated with esophageal cancer. Moreover, sugar-sweetened beverages and ultra-processed foods are a convincing cause for excess body weight, increasing cancer risk through this pathway, with some emerging evidence suggesting also direct pathways. Breastfeeding protects against breast cancer, and could protect against ovarian cancer. Taking this evidence into account, the Latin America and the Caribbean Code Against Cancer recommends the general public to maintain a healthy body weight, be physically active and limit sedentary behavior, eat a healthy diet (eat plenty of vegetables, fruits, wholegrains and legumes; avoid sugar-sweetened beverages and processed meat; and limit ultra-processed foods, red meat and very hot beverages), and breastfeed. Moreover, the Latin America and the Caribbean Code Against Cancer also includes a set of public policy recommendations for cancer prevention to inform policy makers and civil society about the need of policies to shape healthy environments and create opportunities to facilitate the adoption of the recommendations directed to the public., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)
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- 2023
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100. Policy networks and competing interests in the development of the Mexican sugar-sweetened beverages tax.
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Carriedo A, Cairney P, Barquera S, and Hawkins B
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- Humans, Carbonated Beverages, Mexico epidemiology, Policy, Taxes, Sugar-Sweetened Beverages
- Abstract
Introduction: Sugar taxes threaten the business models and profits of the food and beverage industry (F&BI), which has sought to avert, delay or influence the content of health taxes globally. Mexico introduced a sugar-sweetened beverage (SSB) tax in 2014 and other regulatory measures to improve population diets. This paper examines how policy networks emerged within and affected the development and implementation of the Mexican SSB tax., Methods: This qualitative study analyses 31 interviews conducted with key stakeholders involved in the soda tax policy process and 145 documents, including grey literature and peer-reviewed literature. The policy network approach was used to map contacts, interconnections, relationships and links between the state, civil society and commercial actors involved in the SSB tax. These findings were used to examine the responsiveness, participation and accountability of the soda tax policy formulation., Results: Complex interconnections were identified between state and non-state actors. These included advisory relationships, financial collaborations and personal connections between those in high-level positions. Relationships between the government and the F&BI were not always disclosed. International organisations and academics were identified as key financial or technical supporters of the tax. Key governance principles of participation, responsiveness and accountability were undermined by some of these relationships, including the participation of non-state actors in policy development and the powerful role of the F&BI in evaluation and monitoring., Conclusion: This case study exemplifies the importance of links and networks between actors in health policymaking. The F&BI influence endangers the primary aim of the SSB tax to protect health. The identified links highlight the normalisation of connections among actors with competing aims and interests toward health, thereby jeopardising attempts to tackle obesity rates., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ.)
- Published
- 2023
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