41 research outputs found

    Determination of the pKa value of phenolphthalein by means of absorbance measurements

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    We here report a laboratory protocol for the determination of the pKa value of an acid by means of determinations obtained with a spectrophotometer. Students determine the acidity constant (Ka) and the pKa associated with phenolphthalein from the absorbance values obtained from phenolphthalein solutions at different pHs. The present protocol for the determination of the pKa takes a very short time and is useful when teaching in conditions with limited equipment.Fil: Alonso, Manuel. Universidad de Buenos Aires. Facultad de Medicina. Departamento de Bioquímica Humana; ArgentinaFil: Chapela, Sebastián P.. Universidad de Buenos Aires. Facultad de Medicina. Departamento de Bioquímica Humana; ArgentinaFil: Cristaldo, María L.. Universidad de Buenos Aires. Facultad de Medicina. Departamento de Bioquímica Humana; ArgentinaFil: Nievas, Inés. Universidad de Buenos Aires. Facultad de Medicina. Departamento de Bioquímica Humana; ArgentinaFil: Burgos Oliver Gamondi, Hilda I.. Universidad de Buenos Aires. Facultad de Medicina. Departamento de Bioquímica Humana; ArgentinaFil: Stella, Carlos Alberto. Universidad de Buenos Aires. Facultad de Medicina. Departamento de Bioquímica Humana; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

    Future and potential spending on health 2015-40 : development assistance for health, and government, prepaid private, and out-of-pocket health spending in 184 countries

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    Background The amount of resources, particularly prepaid resources, available for health can affect access to health care and health outcomes. Although health spending tends to increase with economic development, tremendous variation exists among health financing systems. Estimates of future spending can be beneficial for policy makers and planners, and can identify financing gaps. In this study, we estimate future gross domestic product (GDP), all-sector government spending, and health spending disaggregated by source, and we compare expected future spending to potential future spending. Methods We extracted GDP, government spending in 184 countries from 1980-2015, and health spend data from 1995-2014. We used a series of ensemble models to estimate future GDP, all-sector government spending, development assistance for health, and government, out-of-pocket, and prepaid private health spending through 2040. We used frontier analyses to identify patterns exhibited by the countries that dedicate the most funding to health, and used these frontiers to estimate potential health spending for each low-income or middle-income country. All estimates are inflation and purchasing power adjusted. Findings We estimated that global spending on health will increase from US9.21trillionin2014to9.21 trillion in 2014 to 24.24 trillion (uncertainty interval [UI] 20.47-29.72) in 2040. We expect per capita health spending to increase fastest in upper-middle-income countries, at 5.3% (UI 4.1-6.8) per year. This growth is driven by continued growth in GDP, government spending, and government health spending. Lower-middle income countries are expected to grow at 4.2% (3.8-4.9). High-income countries are expected to grow at 2.1% (UI 1.8-2.4) and low-income countries are expected to grow at 1.8% (1.0-2.8). Despite this growth, health spending per capita in low-income countries is expected to remain low, at 154(UI133181)percapitain2030and154 (UI 133-181) per capita in 2030 and 195 (157-258) per capita in 2040. Increases in national health spending to reach the level of the countries who spend the most on health, relative to their level of economic development, would mean $321 (157-258) per capita was available for health in 2040 in low-income countries. Interpretation Health spending is associated with economic development but past trends and relationships suggest that spending will remain variable, and low in some low-resource settings. Policy change could lead to increased health spending, although for the poorest countries external support might remain essential.Peer reviewe

    First Latin American clinical practice guidelines for the treatment of systemic lupus erythematosus: Latin American Group for the Study of Lupus (GLADEL, Grupo Latino Americano de Estudio del Lupus)-Pan-American League of Associations of Rheumatology (PANLAR)

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    Systemic lupus erythematosus (SLE), a complex and heterogeneous autoimmune disease, represents a significant challenge for both diagnosis and treatment. Patients with SLE in Latin America face special problems that should be considered when therapeutic guidelines are developed. The objective of the study is to develop clinical practice guidelines for Latin American patients with lupus. Two independent teams (rheumatologists with experience in lupus management and methodologists) had an initial meeting in Panama City, Panama, in April 2016. They selected a list of questions for the clinical problems most commonly seen in Latin American patients with SLE. These were addressed with the best available evidence and summarised in a standardised format following the Grading of Recommendations Assessment, Development and Evaluation approach. All preliminary findings were discussed in a second face-to-face meeting in Washington, DC, in November 2016. As a result, nine organ/system sections are presented with the main findings; an 'overarching' treatment approach was added. Special emphasis was made on regional implementation issues. Best pharmacologic options were examined for musculoskeletal, mucocutaneous, kidney, cardiac, pulmonary, neuropsychiatric, haematological manifestations and the antiphospholipid syndrome. The roles of main therapeutic options (ie, glucocorticoids, antimalarials, immunosuppressant agents, therapeutic plasma exchange, belimumab, rituximab, abatacept, low-dose aspirin and anticoagulants) were summarised in each section. In all cases, benefits and harms, certainty of the evidence, values and preferences, feasibility, acceptability and equity issues were considered to produce a recommendation with special focus on ethnic and socioeconomic aspects. Guidelines for Latin American patients with lupus have been developed and could be used in similar settings.Fil: Pons Estel, Bernardo A.. Centro Regional de Enfermedades Autoinmunes y Reumáticas; ArgentinaFil: Bonfa, Eloisa. Universidade de Sao Paulo; BrasilFil: Soriano, Enrique R.. Instituto Universitario Hospital Italiano de Buenos Aires. Rectorado.; ArgentinaFil: Cardiel, Mario H.. Centro de Investigación Clínica de Morelia; MéxicoFil: Izcovich, Ariel. Hospital Alemán; ArgentinaFil: Popoff, Federico. Hospital Aleman; ArgentinaFil: Criniti, Juan M.. Hospital Alemán; ArgentinaFil: Vásquez, Gloria. Universidad de Antioquia; ColombiaFil: Massardo, Loreto. Universidad San Sebastián; ChileFil: Duarte, Margarita. Hospital de Clínicas; ParaguayFil: Barile Fabris, Leonor A.. Hospital Angeles del Pedregal; MéxicoFil: García, Mercedes A.. Universidad de Buenos Aires. Facultad de Medicina. Hospital de Clínicas General San Martín; ArgentinaFil: Amigo, Mary Carmen. Centro Médico Abc; MéxicoFil: Espada, Graciela. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutiérrez"; ArgentinaFil: Catoggio, Luis J.. Hospital Italiano. Instituto Universitario. Escuela de Medicina; ArgentinaFil: Sato, Emilia Inoue. Universidade Federal de Sao Paulo; BrasilFil: Levy, Roger A.. Universidade do Estado de Rio do Janeiro; BrasilFil: Acevedo Vásquez, Eduardo M.. Universidad Nacional Mayor de San Marcos; PerúFil: Chacón Díaz, Rosa. Policlínica Méndez Gimón; VenezuelaFil: Galarza Maldonado, Claudio M.. Corporación Médica Monte Sinaí; EcuadorFil: Iglesias Gamarra, Antonio J.. Universidad Nacional de Colombia; ColombiaFil: Molina, José Fernando. Centro Integral de Reumatología; ColombiaFil: Neira, Oscar. Universidad de Chile; ChileFil: Silva, Clóvis A.. Universidade de Sao Paulo; BrasilFil: Vargas Peña, Andrea. Hospital Pasteur Montevideo; UruguayFil: Gómez Puerta, José A.. Hospital Clinic Barcelona; EspañaFil: Scolnik, Marina. Instituto Universitario Hospital Italiano de Buenos Aires. Rectorado.; ArgentinaFil: Pons Estel, Guillermo J.. Centro Regional de Enfermedades Autoinmunes y Reumáticas; Argentina. Hospital Provincial de Rosario; ArgentinaFil: Ugolini Lopes, Michelle R.. Universidade de Sao Paulo; BrasilFil: Savio, Verónica. Instituto Universitario Hospital Italiano de Buenos Aires. Rectorado.; ArgentinaFil: Drenkard, Cristina. University of Emory; Estados UnidosFil: Alvarellos, Alejandro J.. Hospital Privado Universitario de Córdoba; ArgentinaFil: Ugarte Gil, Manuel F.. Universidad Cientifica del Sur; Perú. Hospital Nacional Guillermo Almenara Irigoyen; PerúFil: Babini, Alejandra. Instituto Universitario Hospital Italiano de Buenos Aires. Rectorado.; ArgentinaFil: Cavalcanti, André. Universidade Federal de Pernambuco; BrasilFil: Cardoso Linhares, Fernanda Athayde. Hospital Pasteur Montevideo; UruguayFil: Haye Salinas, Maria Jezabel. Hospital Privado Universitario de Córdoba; ArgentinaFil: Fuentes Silva, Yurilis J.. Universidad de Oriente - Núcleo Bolívar; VenezuelaFil: Montandon De Oliveira E Silva, Ana Carolina. Universidade Federal de Goiás; BrasilFil: Eraso Garnica, Ruth M.. Universidad de Antioquia; ColombiaFil: Herrera Uribe, Sebastián. Hospital General de Medellin Luz Castro de Gutiérrez; ColombiaFil: Gómez Martín, DIana. Instituto Nacional de la Nutrición Salvador Zubiran; MéxicoFil: Robaina Sevrini, Ricardo. Universidad de la República; UruguayFil: Quintana, Rosana M.. Hospital Provincial de Rosario; Argentina. Centro Regional de Enfermedades Autoinmunes y Reumáticas; ArgentinaFil: Gordon, Sergio. Hospital Interzonal General de Agudos Dr Oscar Alende. Unidad de Reumatología y Enfermedades Autoinmunes Sistémicas; ArgentinaFil: Fragoso Loyo, Hilda. Instituto Nacional de la Nutrición Salvador Zubiran; MéxicoFil: Rosario, Violeta. Hospital Docente Padre Billini; República DominicanaFil: Saurit, Verónica. Hospital Privado Universitario de Córdoba; ArgentinaFil: Appenzeller, Simone. Universidade Estadual de Campinas; BrasilFil: Dos Reis Neto, Edgard Torres. Universidade Federal de Sao Paulo; BrasilFil: Cieza, Jorge. Hospital Nacional Edgardo Rebagliati Martins; PerúFil: González Naranjo, Luis A.. Universidad de Antioquia; ColombiaFil: González Bello, Yelitza C.. Ceibac; MéxicoFil: Collado, María Victoria. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Médicas; ArgentinaFil: Sarano, Judith. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Médicas; ArgentinaFil: Retamozo, Maria Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Ciencias de la Salud. Universidad Nacional de Córdoba. Instituto de Investigaciones en Ciencias de la Salud; ArgentinaFil: Sattler, María E.. Provincia de Buenos Aires. Ministerio de Salud. Hospital Interzonal de Agudos "Eva Perón"; ArgentinaFil: Gamboa Cárdenas, Rocio V.. Hospital Nacional Guillermo Almenara Irigoyen; PerúFil: Cairoli, Ernesto. Universidad de la República; UruguayFil: Conti, Silvana M.. Hospital Provincial de Rosario; ArgentinaFil: Amezcua Guerra, Luis M.. Instituto Nacional de Cardiologia Ignacio Chavez; MéxicoFil: Silveira, Luis H.. Instituto Nacional de Cardiologia Ignacio Chavez; MéxicoFil: Borba, Eduardo F.. Universidade de Sao Paulo; BrasilFil: Pera, Mariana A.. Hospital Interzonal General de Agudos General San Martín; ArgentinaFil: Alba Moreyra, Paula B.. Universidad Nacional de Córdoba. Facultad de Medicina; ArgentinaFil: Arturi, Valeria. Hospital Interzonal General de Agudos General San Martín; ArgentinaFil: Berbotto, Guillermo A.. Provincia de Buenos Aires. Ministerio de Salud. Hospital Interzonal de Agudos "Eva Perón"; ArgentinaFil: Gerling, Cristian. Hospital Interzonal General de Agudos Dr Oscar Alende. Unidad de Reumatología y Enfermedades Autoinmunes Sistémicas; ArgentinaFil: Gobbi, Carla Andrea. Universidad Nacional de Córdoba. Facultad de Medicina; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Gervasoni, Viviana L.. Hospital Provincial de Rosario; ArgentinaFil: Scherbarth, Hugo R.. Hospital Interzonal General de Agudos Dr Oscar Alende. Unidad de Reumatología y Enfermedades Autoinmunes Sistémicas; ArgentinaFil: Brenol, João C. Tavares. Hospital de Clinicas de Porto Alegre; BrasilFil: Cavalcanti, Fernando. Universidade Federal de Pernambuco; BrasilFil: Costallat, Lilian T. Lavras. Universidade Estadual de Campinas; BrasilFil: Da Silva, Nilzio A.. Universidade Federal de Goiás; BrasilFil: Monticielo, Odirlei A.. Hospital de Clinicas de Porto Alegre; BrasilFil: Seguro, Luciana Parente Costa. Universidade de Sao Paulo; BrasilFil: Xavier, Ricardo M.. Hospital de Clinicas de Porto Alegre; BrasilFil: Llanos, Carolina. Universidad Católica de Chile; ChileFil: Montúfar Guardado, Rubén A.. Instituto Salvadoreño de la Seguridad Social; El SalvadorFil: Garcia De La Torre, Ignacio. Hospital General de Occidente; MéxicoFil: Pineda, Carlos. Instituto Nacional de Rehabilitación; MéxicoFil: Portela Hernández, Margarita. Umae Hospital de Especialidades Centro Medico Nacional Siglo Xxi; MéxicoFil: Danza, Alvaro. Hospital Pasteur Montevideo; UruguayFil: Guibert Toledano, Marlene. Medical-surgical Research Center; CubaFil: Reyes, Gil Llerena. Medical-surgical Research Center; CubaFil: Acosta Colman, Maria Isabel. Hospital de Clínicas; ParaguayFil: Aquino, Alicia M.. Hospital de Clínicas; ParaguayFil: Mora Trujillo, Claudia S.. Hospital Nacional Edgardo Rebagliati Martins; PerúFil: Muñoz Louis, Roberto. Hospital Docente Padre Billini; República DominicanaFil: García Valladares, Ignacio. Centro de Estudios de Investigación Básica y Clínica; MéxicoFil: Orozco, María Celeste. Instituto de Rehabilitación Psicofísica; ArgentinaFil: Burgos, Paula I.. Pontificia Universidad Católica de Chile; ChileFil: Betancur, Graciela V.. Instituto de Rehabilitación Psicofísica; ArgentinaFil: Alarcón, Graciela S.. Universidad Peruana Cayetano Heredia; Perú. University of Alabama at Birmingahm; Estados Unido

    Trends in future health financing and coverage: future health spending and universal health coverage in 188 countries, 2016–40

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    Background: Achieving universal health coverage (UHC) requires health financing systems that provide prepaid pooled resources for key health services without placing undue financial stress on households. Understanding current and future trajectories of health financing is vital for progress towards UHC. We used historical health financing data for 188 countries from 1995 to 2015 to estimate future scenarios of health spending and pooled health spending through to 2040. Methods: We extracted historical data on gross domestic product (GDP) and health spending for 188 countries from 1995 to 2015, and projected annual GDP, development assistance for health, and government, out-of-pocket, and prepaid private health spending from 2015 through to 2040 as a reference scenario. These estimates were generated using an ensemble of models that varied key demographic and socioeconomic determinants. We generated better and worse alternative future scenarios based on the global distribution of historic health spending growth rates. Last, we used stochastic frontier analysis to investigate the association between pooled health resources and UHC index, a measure of a country's UHC service coverage. Finally, we estimated future UHC performance and the number of people covered under the three future scenarios. Findings: In the reference scenario, global health spending was projected to increase from US10trillion(9510 trillion (95% uncertainty interval 10 trillion to 10 trillion) in 2015 to 20 trillion (18 trillion to 22 trillion) in 2040. Per capita health spending was projected to increase fastest in upper-middle-income countries, at 4·2% (3·4–5·1) per year, followed by lower-middle-income countries (4·0%, 3·6–4·5) and low-income countries (2·2%, 1·7–2·8). Despite global growth, per capita health spending was projected to range from only 40(2465)to40 (24–65) to 413 (263–668) in 2040 in low-income countries, and from 140(90200)to140 (90–200) to 1699 (711–3423) in lower-middle-income countries. Globally, the share of health spending covered by pooled resources would range widely, from 19·8% (10·3–38·6) in Nigeria to 97·9% (96·4–98·5) in Seychelles. Historical performance on the UHC index was significantly associated with pooled resources per capita. Across the alternative scenarios, we estimate UHC reaching between 5·1 billion (4·9 billion to 5·3 billion) and 5·6 billion (5·3 billion to 5·8 billion) lives in 2030. Interpretation: We chart future scenarios for health spending and its relationship with UHC. Ensuring that all countries have sustainable pooled health resources is crucial to the achievement of UHC. Funding: The Bill & Melinda Gates Foundation

    Measuring progress and projecting attainment on the basis of past trends of the health-related Sustainable Development Goals in 188 countries: an analysis from the Global Burden of Disease Study 2016

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    The UN’s Sustainable Development Goals (SDGs) are grounded in the global ambition of “leaving no one behind”. Understanding today’s gains and gaps for the health-related SDGs is essential for decision makers as they aim to improve the health of populations. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016), we measured 37 of the 50 health-related SDG indicators over the period 1990–2016 for 188 countries, and then on the basis of these past trends, we projected indicators to 2030

    Alcohol use and burden for 195 countries and territories, 1990-2016 : a systematic analysis for the Global Burden of Disease Study 2016

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    Background Alcohol use is a leading risk factor for death and disability, but its overall association with health remains complex given the possible protective effects of moderate alcohol consumption on some conditions. With our comprehensive approach to health accounting within the Global Burden of Diseases, Injuries, and Risk Factors Study 2016, we generated improved estimates of alcohol use and alcohol-attributable deaths and disability-adjusted life-years (DALYs) for 195 locations from 1990 to 2016, for both sexes and for 5-year age groups between the ages of 15 years and 95 years and older. Methods Using 694 data sources of individual and population-level alcohol consumption, along with 592 prospective and retrospective studies on the risk of alcohol use, we produced estimates of the prevalence of current drinking, abstention, the distribution of alcohol consumption among current drinkers in standard drinks daily (defined as 10 g of pure ethyl alcohol), and alcohol-attributable deaths and DALYs. We made several methodological improvements compared with previous estimates: first, we adjusted alcohol sales estimates to take into account tourist and unrecorded consumption; second, we did a new meta-analysis of relative risks for 23 health outcomes associated with alcohol use; and third, we developed a new method to quantify the level of alcohol consumption that minimises the overall risk to individual health. Findings Globally, alcohol use was the seventh leading risk factor for both deaths and DALYs in 2016, accounting for 2.2% (95% uncertainty interval [UI] 1.5-3.0) of age-standardised female deaths and 6.8% (5.8-8.0) of age-standardised male deaths. Among the population aged 15-49 years, alcohol use was the leading risk factor globally in 2016, with 3.8% (95% UI 3.2-4-3) of female deaths and 12.2% (10.8-13-6) of male deaths attributable to alcohol use. For the population aged 15-49 years, female attributable DALYs were 2.3% (95% UI 2.0-2.6) and male attributable DALYs were 8.9% (7.8-9.9). The three leading causes of attributable deaths in this age group were tuberculosis (1.4% [95% UI 1. 0-1. 7] of total deaths), road injuries (1.2% [0.7-1.9]), and self-harm (1.1% [0.6-1.5]). For populations aged 50 years and older, cancers accounted for a large proportion of total alcohol-attributable deaths in 2016, constituting 27.1% (95% UI 21.2-33.3) of total alcohol-attributable female deaths and 18.9% (15.3-22.6) of male deaths. The level of alcohol consumption that minimised harm across health outcomes was zero (95% UI 0.0-0.8) standard drinks per week. Interpretation Alcohol use is a leading risk factor for global disease burden and causes substantial health loss. We found that the risk of all-cause mortality, and of cancers specifically, rises with increasing levels of consumption, and the level of consumption that minimises health loss is zero. These results suggest that alcohol control policies might need to be revised worldwide, refocusing on efforts to lower overall population-level consumption.Peer reviewe

    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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    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\ub71 (95% UI 95\ub78-98\ub71) in Iceland, followed by 96\ub76 (94\ub79-97\ub79) in Norway and 96\ub71 (94\ub75-97\ub73) in the Netherlands, to values as low as 18\ub76 (13\ub71-24\ub74) in the Central African Republic, 19\ub70 (14\ub73-23\ub77) in Somalia, and 23\ub74 (20\ub72-26\ub78) 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\ub75 (89\ub71-93\ub76) in Beijing to 48\ub70 (43\ub74-53\ub72) in Tibet (a 43\ub75-point difference), while India saw a 30\ub78-point disparity, from 64\ub78 (59\ub76-68\ub78) in Goa to 34\ub70 (30\ub73-38\ub71) in Assam. Japan recorded the smallest range in subnational HAQ performance in 2016 (a 4\ub78-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\ub79-point to 17\ub70-point difference), whereas in Brazil, disparities slightly increased across states during this time (a 17\ub72-point to 20\ub74-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

    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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    Copyright © 2018 The Author(s). Published by Elsevier Ltd. 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 (89·1-93·6) 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

    Global, regional, and national disability-adjusted life-years (DALYs) for 359 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017.

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    How long one lives, how many years of life are spent in good and poor health, and how the population's state of health and leading causes of disability change over time all have implications for policy, planning, and provision of services. We comparatively assessed the patterns and trends of healthy life expectancy (HALE), which quantifies the number of years of life expected to be lived in good health, and the complementary measure of disability-adjusted life-years (DALYs), a composite measure of disease burden capturing both premature mortality and prevalence and severity of ill health, for 359 diseases and injuries for 195 countries and territories over the past 28 years. Methods We used data for age-specific mortality rates, years of life lost (YLLs) due to premature mortality, and years lived with disability (YLDs) from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 to calculate HALE and DALYs from 1990 to 2017. We calculated HALE using age-specific mortality rates and YLDs per capita for each location, age, sex, and year. We calculated DALYs for 359 causes as the sum of YLLs and YLDs. We assessed how observed HALE and DALYs differed by country and sex from expected trends based on Socio-demographic Index (SDI). We also analysed HALE by decomposing years of life gained into years spent in good health and in poor health, between 1990 and 2017, and extra years lived by females compared with males. Findings Globally, from 1990 to 2017, life expectancy at birth increased by 7·4 years (95% uncertainty interval 7·1-7·8), from 65·6 years (65·3-65·8) in 1990 to 73·0 years (72·7-73·3) in 2017. The increase in years of life varied from 5·1 years (5·0-5·3) in high SDI countries to 12·0 years (11·3-12·8) in low SDI countries. Of the additional years of life expected at birth, 26·3% (20·1-33·1) were expected to be spent in poor health in high SDI countries compared with 11·7% (8·8-15·1) in low-middle SDI countries. HALE at birth increased by 6·3 years (5·9-6·7), from 57·0 years (54·6-59·1) in 1990 to 63·3 years (60·5-65·7) in 2017. The increase varied from 3·8 years (3·4-4·1) in high SDI countries to 10·5 years (9·8-11·2) in low SDI countries. Even larger variations in HALE than these were observed between countries, ranging from 1·0 year (0·4-1·7) in Saint Vincent and the Grenadines (62·4 years [59·9-64·7] in 1990 to 63·5 years [60·9-65·8] in 2017) to 23·7 years (21·9-25·6) in Eritrea (30·7 years [28·9-32·2] in 1990 to 54·4 years [51·5-57·1] in 2017). In most countries, the increase in HALE was smaller than the increase in overall life expectancy, indicating more years lived in poor health. In 180 of 195 countries and territories, females were expected to live longer than males in 2017, with extra years lived varying from 1·4 years (0·6-2·3) in Algeria to 11·9 years (10·9-12·9) in Ukraine. Of the extra years gained, the proportion spent in poor health varied largely across countries, with less than 20% of additional years spent in poor health in Bosnia and Herzegovina, Burundi, and Slovakia, whereas in Bahrain all the extra years were spent in poor health. In 2017, the highest estimate of HALE at birth was in Singapore for both females (75·8 years [72·4-78·7]) and males (72·6 years [69·8-75·0]) and the lowest estimates were in Central African Republic (47·0 years [43·7-50·2] for females and 42·8 years [40·1-45·6] for males). Globally, in 2017, the five leading causes of DALYs were neonatal disorders, ischaemic heart disease, stroke, lower respiratory infections, and chronic obstructive pulmonary disease. Between 1990 and 2017, age-standardised DALY rates decreased by 41·3% (38·8-43·5) for communicable diseases and by 49·8% (47·9-51·6) for neonatal disorders. For non-communicable diseases, global DALYs increased by 40·1% (36·8-43·0), although age-standardised DALY rates decreased by 18·1% (16·0-20·2)

    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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    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 Socio-demographic 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, an
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