Mapping and Estimation of Nitrogen and Sulfur Atmospheric Deposition Fluxes in Central Region of the Mexican Bajio

The objective of this study was to assess the spatial and temporal distribution of nitrogen and sulfur deposition and its relationship with meteorological conditions in the metropolitan area of León in Guanajuato, México. N and S atmospheric deposition was collected using passive samplers (IER) in 10 sites in León City during three climatic seasons in 2018. Nitrate, ammonium, and sulfate concentrations and deposition fluxes of N and S were determined. From wind and air-mass trajectories analysis, mechanisms and possible sources contributing to N and S deposition in the study area were assessed. Atmospheric deposition fluxes were compared to critical load values reported for sensitive ecosystems in Europe. It was found that mean deposition flux for N (5.82 Kg N ha−1 year−1) was within the range of values reported for sensitive ecosystems in Nuevo México, Europe, and California. On the other hand, the mean deposition flux for S (13.77 S Kg ha−1 year−1) exceeded the critical load values proposed for Europe, suggesting that current S deposition could be a risk for ecosystems and water bodies in the region

Risk factors for unfavorable outcome and impact of early post-transplant infection in solid organ recipients with COVID-19: A prospective multicenter cohort study

The aim was to analyze the characteristics and predictors of unfavorable outcomes in solid organ transplant recipients (SOTRs) with COVID-19. We conducted a prospective observational cohort study of 210 consecutive SOTRs hospitalized with COVID-19 in 12 Spanish centers from 21 February to 6 May 2020. Data pertaining to demographics, chronic underlying diseases, transplantation features, clinical, therapeutics, and complications were collected. The primary endpoint was a composite of intensive care unit (ICU) admission and/or death. Logistic regression analyses were performed to identify the factors associated with these unfavorable outcomes. Males accounted for 148 (70.5%) patients, the median age was 63 years, and 189 (90.0%) patients had pneumonia. Common symptoms were fever, cough, gastrointestinal disturbances, and dyspnea. The most used antiviral or host-targeted therapies included hydroxychloroquine 193/200 (96.5%), lopinavir/ritonavir 91/200 (45.5%), and tocilizumab 49/200 (24.5%). Thirty-seven (17.6%) patients required ICU admission, 12 (5.7%) suffered graft dysfunction, and 45 (21.4%) died. A shorter interval between transplantation and COVID-19 diagnosis had a negative impact on clinical prognosis. Four baseline features were identified as independent predictors of intensive care need or death: advanced age, high respiratory rate, lymphopenia, and elevated level of lactate dehydrogenase. In summary, this study presents comprehensive information on characteristics and complications of COVID-19 in hospitalized SOTRs and provides indicators available upon hospital admission for the identification of SOTRs at risk of critical disease or death, underlining the need for stringent preventative measures in the early post-transplant period

Red Nacional de reconocedores de suelos.

Los relevamientos sistemáticos de suelos en Argentina comenzaron en la década de 1960, en el marco del Plan Mapa de Suelos. Dicho plan, desarrollado y liderado por el INTA, dio impulso a la formación de especialistas y a la producción de cartografía de suelos a diferentes escalas. Sin embargo, a partir del año 2000 las actividades se redujeron notablemente y gran parte de los equipos provinciales formados hasta ese momento se desarticularon. Desde entonces los relevamientos continuaron de manera aislada sólo en aquellas provincias donde se mantuvieron los grupos de trabajo. Este hecho condujo a que actualmente diferentes regiones del país no cuenten con información acerca de las propiedades y distribución de suelos a una escala adecuada para la toma de decisiones. En este contexto, en el 2018 se crea la Red Nacional de Reconocedores de Suelos (RNRS) que organiza las capacidades técnicas y operativas a nivel nacional para dar pronta respuesta a la creciente demanda de cartografía. Se trata de un equipo interinstitucional e interdisciplinario de especialistas distribuidos por todo el país, que realiza tareas de relevamiento, produce y difunde cartografía básica y utilitaria de suelos, ofrece capacitación y genera espacios de discusión y actualización metodológica. A la fecha, la RNRS ha relevado aproximadamente 760.000 ha en el sur de Córdoba, estimando completar durante el presente año el relevamiento del departamento Río Cuarto. Esta estrategia organizacional permitirá avanzar en el mapeo semidetallado de suelos en nuestro país, estableciendo vinculaciones sinérgicas entre profesionales de diferentes instituciones a fin de fortalecer y potenciar los equipos de trabajo en cada región. El motivo de esta contribución es presentar la RNRS, sus objetivos, avances a la fecha y desafíos a futuro, haciendo una breve revisión del estado actual de los relevamientos a escala semidetallada en nuestro país.Fil: Moretti, Lucas M. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Cerro Azul; ArgentinaFil: Rodriguez, Darío M. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; ArgentinaFil: Schulz, Guillermo A. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; ArgentinaFil: Kurtz, Ditmar Bernardo. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Corrientes; ArgentinaFil: Altamirano D. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi; ArgentinaFil: Amin, S. Universidad Nacional de Río Cuarto; ArgentinaFil: Angelini, Marcos Esteban. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; Argentina. Wageningen University. Soil Geography and Landscape group; Holanda. International Soil Reference and Information Centre. World Soil Information; HolandaFil: Babelis, German Claudio. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria San Juan; ArgentinaFil: Becerra, Alejandra Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Bedendo, Dante Julian. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Paraná; ArgentinaFil: Boldrini, C. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Marcos Juárez. Agencia de Extensión Rural Río Cuarto; AgentinaFil: Bongiovanni, C. Universidad Nacional de Río Cuarto; ArgentinaFil: Bozzer, S. Universidad Nacional de Río Cuarto; ArgentinaFil: Cabrera, A. Universidad Nacional de Río Cuarto; ArgentinaFil: Canale, A. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Marcos Juárez. Agencia de Extensión Rural Río Cuarto; AgentinaFil: Chilano, Y. Universidad Nacional de Río Cuarto; ArgentinaFil: Cholaky, Carmen. Universidad Nacional de Río Cuarto. Facultad de Agronomía y Veterinaria; ArgentinaFil: Cisneros; José Manuel. Universidad Nacional de Río Cuarto. Cátedra de Uso y Manejo de Suelos; ArgentinaFil: Colazo, Juan Cruz. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria San Luis; ArgentinaFil: Corigliano, J. Universidad Nacional de Río Cuarto; ArgentinaFil: Degioanni, Américo José. Universidad Nacional Río Cuarto. Facultad de Agronomía y Veterinaria. Departamento de Ecología Agraria; ArgentinaFil: de la Fuente, Juan Carlos Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; ArgentinaFil: Escobar, Dardo. Ministerio de Agricultura, Ganadería y Pesca; ArgentinaFil: Faule, L. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi. Córdoba. ArgentinaFil: Galarza, Carlos Martin. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Marcos Juárez; ArgentinaFil: González, J. Universidad Nacional de Río Cuarto; ArgentinaFil: Holzmann, R. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Alto Valle; ArgentinaFil: Irigoin, Julieta. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; Argentina. Universidad Nacional de Luján. Departamento Tecnología; ArgentinaFil: Lanfranco, M. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi; ArgentinaFil: León Giacosa, C. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Rafaela; ArgentinaFil: Matteio, J.P. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; ArgentinaFil: Márquez, C. Gobierno de Córdoba. Ministerio de Agricultura y Ganadería; ArgentinaFil: Marzari, R. Universidad Nacional de Río Cuarto; ArgentinaFil: Mattalia, M.L. Universidad Nacional de Río Cuarto; ArgentinaFil: Morales Poclava, P.C. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Salta; ArgentinaFil: Muñoz, S. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Marcos Juárez; ArgentinaFil: Paladino, Ileana Ruth. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; Argentina. Universidad Nacional de Lomas de Zamora. Facultad de Ciencias Agrarias; ArgentinaFil: Parra, B. Universidad Nacional de Río Cuarto; ArgentinaFil: Pérez, M. Gobierno de Córdoba. Ministerio de Agricultura y Ganadería; ArgentinaFil: Pezzola, A. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Hilario Ascasubi; ArgentinaFil: Perucca, S. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Marcos Juárez. Agencia de Extensión Rural Río Cuarto; ArgentinaFil: Porcel de Peralta, R. Gobierno de Córdoba. Ministerio de Agricultura y Ganadería; ArgentinaFil: Renaudeau, S. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Corrientes; ArgentinaFil: Salustio, M. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Marcos Juárez. Agencia de Extensión Rural Río Cuarto; ArgentinaFil: Sapino, V. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Rafaela; ArgentinaFil: Tenti Vuegen, L.M. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos. ArgentinaFil: Tosolini, R. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Rafaela; ArgentinaFil: Vicondo, M.E. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi; Argentina. Universidad Nacional de Córdoba. ArgentinaFil: Vizgarra, L.A. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Quimili; ArgentinaFil: Ybarra, D.D. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Corrientes; ArgentinaFil: Winschel, C. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Hilario Ascasubi; ArgentinaFil: Zamora, E. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Corrientes; Argentin

Dental Health and Mortality in People With End-Stage Kidney Disease Treated With Hemodialysis: A Multinational Cohort Study

Background Dental disease is more extensive in adults with chronic kidney disease, but whether dental health and behaviors are associated with survival in the setting of hemodialysis is unknown. Study Design Prospective multinational cohort. Setting & Participants 4,205 adults treated with long-term hemodialysis, 2010 to 2012 (Oral Diseases in Hemodialysis [ORAL-D] Study). Predictors Dental health as assessed by a standardized dental examination using World Health Organization guidelines and personal oral care, including edentulousness; decayed, missing, and filled teeth index; teeth brushing and flossing; and dental health consultation. Outcomes All-cause and cardiovascular mortality at 12 months after dental assessment. Measurements Multivariable-adjusted Cox proportional hazards regression models fitted with shared frailty to account for clustering of mortality risk within countries. Results During a mean follow-up of 22.1 months, 942 deaths occurred, including 477 cardiovascular deaths. Edentulousness (adjusted HR, 1.29; 95% CI, 1.10-1.51) and decayed, missing, or filled teeth score ≥ 14 (adjusted HR, 1.70; 95% CI, 1.33-2.17) were associated with early all-cause mortality, while dental flossing, using mouthwash, brushing teeth daily, spending at least 2 minutes on oral hygiene daily, changing a toothbrush at least every 3 months, and visiting a dentist within the past 6 months (adjusted HRs of 0.52 [95% CI, 0.32-0.85], 0.79 [95% CI, 0.64-0.97], 0.76 [95% CI, 0.58-0.99], 0.84 [95% CI, 0.71-0.99], 0.79 [95% CI, 0.65-0.95], and 0.79 [95% CI, 0.65-0.96], respectively) were associated with better survival. Results for cardiovascular mortality were similar. Limitations Convenience sample of clinics. Conclusions In adults treated with hemodialysis, poorer dental health was associated with early death, whereas preventive dental health practices were associated with longer survival

Repositioning of the global epicentre of non-optimal cholesterol

High blood cholesterol is typically considered a feature of wealthy western countries(1,2). However, dietary and behavioural determinants of blood cholesterol are changing rapidly throughout the world(3) and countries are using lipid-lowering medications at varying rates. These changes can have distinct effects on the levels of high-density lipoprotein (HDL) cholesterol and non-HDL cholesterol, which have different effects on human health(4,5). However, the trends of HDL and non-HDL cholesterol levels over time have not been previously reported in a global analysis. Here we pooled 1,127 population-based studies that measured blood lipids in 102.6 million individuals aged 18 years and older to estimate trends from 1980 to 2018 in mean total, non-HDL and HDL cholesterol levels for 200 countries. Globally, there was little change in total or non-HDL cholesterol from 1980 to 2018. This was a net effect of increases in low- and middle-income countries, especially in east and southeast Asia, and decreases in high-income western countries, especially those in northwestern Europe, and in central and eastern Europe. As a result, countries with the highest level of non-HDL cholesterol-which is a marker of cardiovascular riskchanged from those in western Europe such as Belgium, Finland, Greenland, Iceland, Norway, Sweden, Switzerland and Malta in 1980 to those in Asia and the Pacific, such as Tokelau, Malaysia, The Philippines and Thailand. In 2017, high non-HDL cholesterol was responsible for an estimated 3.9 million (95% credible interval 3.7 million-4.2 million) worldwide deaths, half of which occurred in east, southeast and south Asia. The global repositioning of lipid-related risk, with non-optimal cholesterol shifting from a distinct feature of high-income countries in northwestern Europe, north America and Australasia to one that affects countries in east and southeast Asia and Oceania should motivate the use of population-based policies and personal interventions to improve nutrition and enhance access to treatment throughout the world.Peer reviewe

Worldwide trends in underweight and obesity from 1990 to 2022: a pooled analysis of 3663 population-representative studies with 222 million children, adolescents, and adults

Background Underweight and obesity are associated with adverse health outcomes throughout the life course. We estimated the individual and combined prevalence of underweight or thinness and obesity, and their changes, from 1990 to 2022 for adults and school-aged children and adolescents in 200 countries and territories. Methods We used data from 3663 population-based studies with 222 million participants that measured height and weight in representative samples of the general population. We used a Bayesian hierarchical model to estimate trends in the prevalence of different BMI categories, separately for adults (age ≥20 years) and school-aged children and adolescents (age 5–19 years), from 1990 to 2022 for 200 countries and territories. For adults, we report the individual and combined prevalence of underweight (BMI <18·5 kg/m2) and obesity (BMI ≥30 kg/m2). For schoolaged children and adolescents, we report thinness (BMI <2 SD below the median of the WHO growth reference) and obesity (BMI >2 SD above the median). Findings From 1990 to 2022, the combined prevalence of underweight and obesity in adults decreased in 11 countries (6%) for women and 17 (9%) for men with a posterior probability of at least 0·80 that the observed changes were true decreases. The combined prevalence increased in 162 countries (81%) for women and 140 countries (70%) for men with a posterior probability of at least 0·80. In 2022, the combined prevalence of underweight and obesity was highest in island nations in the Caribbean and Polynesia and Micronesia, and countries in the Middle East and north Africa. Obesity prevalence was higher than underweight with posterior probability of at least 0·80 in 177 countries (89%) for women and 145 (73%) for men in 2022, whereas the converse was true in 16 countries (8%) for women, and 39 (20%) for men. From 1990 to 2022, the combined prevalence of thinness and obesity decreased among girls in five countries (3%) and among boys in 15 countries (8%) with a posterior probability of at least 0·80, and increased among girls in 140 countries (70%) and boys in 137 countries (69%) with a posterior probability of at least 0·80. The countries with highest combined prevalence of thinness and obesity in school-aged children and adolescents in 2022 were in Polynesia and Micronesia and the Caribbean for both sexes, and Chile and Qatar for boys. Combined prevalence was also high in some countries in south Asia, such as India and Pakistan, where thinness remained prevalent despite having declined. In 2022, obesity in school-aged children and adolescents was more prevalent than thinness with a posterior probability of at least 0·80 among girls in 133 countries (67%) and boys in 125 countries (63%), whereas the converse was true in 35 countries (18%) and 42 countries (21%), respectively. In almost all countries for both adults and school-aged children and adolescents, the increases in double burden were driven by increases in obesity, and decreases in double burden by declining underweight or thinness. Interpretation The combined burden of underweight and obesity has increased in most countries, driven by an increase in obesity, while underweight and thinness remain prevalent in south Asia and parts of Africa. A healthy nutrition transition that enhances access to nutritious foods is needed to address the remaining burden of underweight while curbing and reversing the increase in obesit

Height and body-mass index trajectories of school-aged children and adolescents from 1985 to 2019 in 200 countries and territories: a pooled analysis of 2181 population-based studies with 65 million participants

Summary Background Comparable global data on health and nutrition of school-aged children and adolescents are scarce. We aimed to estimate age trajectories and time trends in mean height and mean body-mass index (BMI), which measures weight gain beyond what is expected from height gain, for school-aged children and adolescents. Methods For this pooled analysis, we used a database of cardiometabolic risk factors collated by the Non-Communicable Disease Risk Factor Collaboration. We applied a Bayesian hierarchical model to estimate trends from 1985 to 2019 in mean height and mean BMI in 1-year age groups for ages 5–19 years. The model allowed for non-linear changes over time in mean height and mean BMI and for non-linear changes with age of children and adolescents, including periods of rapid growth during adolescence. Findings We pooled data from 2181 population-based studies, with measurements of height and weight in 65 million participants in 200 countries and territories. In 2019, we estimated a difference of 20 cm or higher in mean height of 19-year-old adolescents between countries with the tallest populations (the Netherlands, Montenegro, Estonia, and Bosnia and Herzegovina for boys; and the Netherlands, Montenegro, Denmark, and Iceland for girls) and those with the shortest populations (Timor-Leste, Laos, Solomon Islands, and Papua New Guinea for boys; and Guatemala, Bangladesh, Nepal, and Timor-Leste for girls). In the same year, the difference between the highest mean BMI (in Pacific island countries, Kuwait, Bahrain, The Bahamas, Chile, the USA, and New Zealand for both boys and girls and in South Africa for girls) and lowest mean BMI (in India, Bangladesh, Timor-Leste, Ethiopia, and Chad for boys and girls; and in Japan and Romania for girls) was approximately 9–10 kg/m2. In some countries, children aged 5 years started with healthier height or BMI than the global median and, in some cases, as healthy as the best performing countries, but they became progressively less healthy compared with their comparators as they grew older by not growing as tall (eg, boys in Austria and Barbados, and girls in Belgium and Puerto Rico) or gaining too much weight for their height (eg, girls and boys in Kuwait, Bahrain, Fiji, Jamaica, and Mexico; and girls in South Africa and New Zealand). In other countries, growing children overtook the height of their comparators (eg, Latvia, Czech Republic, Morocco, and Iran) or curbed their weight gain (eg, Italy, France, and Croatia) in late childhood and adolescence. When changes in both height and BMI were considered, girls in South Korea, Vietnam, Saudi Arabia, Turkey, and some central Asian countries (eg, Armenia and Azerbaijan), and boys in central and western Europe (eg, Portugal, Denmark, Poland, and Montenegro) had the healthiest changes in anthropometric status over the past 3·5 decades because, compared with children and adolescents in other countries, they had a much larger gain in height than they did in BMI. The unhealthiest changes—gaining too little height, too much weight for their height compared with children in other countries, or both—occurred in many countries in sub-Saharan Africa, New Zealand, and the USA for boys and girls; in Malaysia and some Pacific island nations for boys; and in Mexico for girls. Interpretation The height and BMI trajectories over age and time of school-aged children and adolescents are highly variable across countries, which indicates heterogeneous nutritional quality and lifelong health advantages and risks

Global variation in diabetes diagnosis and prevalence based on fasting glucose and hemoglobin A1c

Fasting plasma glucose (FPG) and hemoglobin A1c (HbA1c) are both used to diagnose diabetes, but these measurements can identify different people as having diabetes. We used data from 117 population-based studies and quantified, in different world regions, the prevalence of diagnosed diabetes, and whether those who were previously undiagnosed and detected as having diabetes in survey screening, had elevated FPG, HbA1c or both. We developed prediction equations for estimating the probability that a person without previously diagnosed diabetes, and at a specific level of FPG, had elevated HbA1c, and vice versa. The age-standardized proportion of diabetes that was previously undiagnosed and detected in survey screening ranged from 30% in the high-income western region to 66% in south Asia. Among those with screen-detected diabetes with either test, the age-standardized proportion who had elevated levels of both FPG and HbA1c was 29-39% across regions; the remainder had discordant elevation of FPG or HbA1c. In most low- and middle-income regions, isolated elevated HbA1c was more common than isolated elevated FPG. In these regions, the use of FPG alone may delay diabetes diagnosis and underestimate diabetes prevalence. Our prediction equations help allocate finite resources for measuring HbA1c to reduce the global shortfall in diabetes diagnosis and surveillance

Rising rural body-mass index is the main driver of the global obesity epidemic in adults

Body-mass index (BMI) has increased steadily in most countries in parallel with a rise in the proportion of the population who live in cities . This has led to a widely reported view that urbanization is one of the most important drivers of the global rise in obesity . Here we use 2,009\ua0population-based studies, with measurements of height and weight in more than 112\ua0million adults, to report national, regional and global trends in mean\ua0BMI segregated by place of residence (a rural or urban area) from 1985 to 2017. We show that, contrary to the dominant paradigm, more than 55% of the global rise in mean BMI from 1985 to 2017—and more than 80% in\ua0some low- and middle-income regions—was due to increases in BMI in rural areas. This large contribution stems from the fact that, with the exception of women in sub-Saharan Africa, BMI is increasing at the same rate or faster in rural areas than in cities\ua0in low- and middle-income regions. These trends have in turn resulted in a closing—and in some countries reversal—of the gap in BMI between urban and rural areas in low- and middle-income countries, especially for women. In high-income and industrialized countries, we noted a persistently higher rural BMI, especially for women. There is an urgent need for an integrated approach to rural nutrition that enhances financial and physical access to healthy foods, to avoid replacing the rural undernutrition disadvantage in poor countries with a more general malnutrition disadvantage that entails excessive consumption of low-quality calories

Worldwide trends in hypertension prevalence and progress in treatment and control from 1990 to 2019: a pooled analysis of 1201 population-representative studies with 104 million participants.

BACKGROUND: Hypertension can be detected at the primary health-care level and low-cost treatments can effectively control hypertension. We aimed to measure the prevalence of hypertension and progress in its detection, treatment, and control from 1990 to 2019 for 200 countries and territories. METHODS: We used data from 1990 to 2019 on people aged 30-79 years from population-representative studies with measurement of blood pressure and data on blood pressure treatment. We defined hypertension as having systolic blood pressure 140 mm Hg or greater, diastolic blood pressure 90 mm Hg or greater, or taking medication for hypertension. We applied a Bayesian hierarchical model to estimate the prevalence of hypertension and the proportion of people with hypertension who had a previous diagnosis (detection), who were taking medication for hypertension (treatment), and whose hypertension was controlled to below 140/90 mm Hg (control). The model allowed for trends over time to be non-linear and to vary by age. FINDINGS: The number of people aged 30-79 years with hypertension doubled from 1990 to 2019, from 331 (95% credible interval 306-359) million women and 317 (292-344) million men in 1990 to 626 (584-668) million women and 652 (604-698) million men in 2019, despite stable global age-standardised prevalence. In 2019, age-standardised hypertension prevalence was lowest in Canada and Peru for both men and women; in Taiwan, South Korea, Japan, and some countries in western Europe including Switzerland, Spain, and the UK for women; and in several low-income and middle-income countries such as Eritrea, Bangladesh, Ethiopia, and Solomon Islands for men. Hypertension prevalence surpassed 50% for women in two countries and men in nine countries, in central and eastern Europe, central Asia, Oceania, and Latin America. Globally, 59% (55-62) of women and 49% (46-52) of men with hypertension reported a previous diagnosis of hypertension in 2019, and 47% (43-51) of women and 38% (35-41) of men were treated. Control rates among people with hypertension in 2019 were 23% (20-27) for women and 18% (16-21) for men. In 2019, treatment and control rates were highest in South Korea, Canada, and Iceland (treatment >70%; control >50%), followed by the USA, Costa Rica, Germany, Portugal, and Taiwan. Treatment rates were less than 25% for women and less than 20% for men in Nepal, Indonesia, and some countries in sub-Saharan Africa and Oceania. Control rates were below 10% for women and men in these countries and for men in some countries in north Africa, central and south Asia, and eastern Europe. Treatment and control rates have improved in most countries since 1990, but we found little change in most countries in sub-Saharan Africa and Oceania. Improvements were largest in high-income countries, central Europe, and some upper-middle-income and recently high-income countries including Costa Rica, Taiwan, Kazakhstan, South Africa, Brazil, Chile, Turkey, and Iran. INTERPRETATION: Improvements in the detection, treatment, and control of hypertension have varied substantially across countries, with some middle-income countries now outperforming most high-income nations. The dual approach of reducing hypertension prevalence through primary prevention and enhancing its treatment and control is achievable not only in high-income countries but also in low-income and middle-income settings. FUNDING: WHO