Context matters: a global bibliometric review of regional innovation systems

[EN] The concept of the regional innovation system (RIS) has received substantial attention from the scientific community, public administrations, and international organisations. This paper presents a systematic quantitative review of RIS research using bibliometric techniques and the Web of Science Core Collection database up to and including the year 2017. Four periods were examined to track the evolution of the RIS concept. The results show that RIS research has grown considerably since 2010, becoming a central research theme in countries focused on a systemic approach toward innovation and in decentralised countries, especially in Western Europe. 'Innovation', 'Europe', 'technology', 'networks', and 'firms' have been the core themes of RIS research since the concept arose in 1992. 'Entrepreneurship' was the major emerging research theme in the 2010s. Since 2010, other emerging topics have appeared, namely 'collaboration', 'organisation', 'triple helix', 'China', 'perspective', 'knowledge bases', and 'governance'. 'Smart specialisation' and 'creation' have been major themes since 2015.This research benefitted from: i GV063/19 funded by Generalitat Valenciana ii RTI2018-093791-B-C22 funded by Ministerio de Ciencia, Innovación y Universidades and FEDER.López-Rubio, P.; Roig-Tierno, N.; Mas Verdú, F. (2022). Context matters: a global bibliometric review of regional innovation systems. International Journal of Technology, Policy and Management (IJTPM). 22(3):247-270. https://doi.org/10.1504/IJTPM.2022.12525724727022

Regional innovation system research trends: toward knowledge management and entrepreneurial ecosystems

[EN] The regional innovation system (RIS) is a popular way of explaining a region¿s development and competitiveness based on innovation activities and processes. In this paper, bibliometric techniques are used to analyze all RIS studies indexed in the Web of Science Core Collection (WoS CC) database as of December 2017. The goal of the analysis is to identify the main trends in RIS research. The evolution of the total number of publications and citations per year indicates that this research field has garnered considerable attention from the scientific community, public administrations, and international organizations. Analysis of the most common keywords and their co-occurrence sheds light on the conceptual framework of RIS research, where knowledge, innovation, clusters, policy, networks, systems, R&D, firms, and industry are key concepts. The 17 most influential RIS articles indexed in WoS CC are identified according to the total number of citations and the ratio of number of citations per year. Reviewing these 17 articles reveals 3 groups of underlying research trends: (1) research on innovation systems, which was mainly conducted in the 1990s, (2) research on knowledge management since the beginning of the 2000s, and (3) research on entrepreneurial ecosystems in recent years. Finally, analysis of citations to these 17 most influential RIS articles reveals strong interconnections according to the number of times they are cited together.Norat Roig-Tierno wish to thank Project GV/2019/063, funded by the Generalitat Valenciana, for supporting this research.López-Rubio, P.; Roig-Tierno, N.; Mas-Tur, A. (2020). Regional innovation system research trends: toward knowledge management and entrepreneurial ecosystems. International Journal of Quality Innovation. 6:1-16. https://doi.org/10.1186/s40887-020-00038-xS1166Freeman C (1987) Technology policy and economic performance: lessons from Japan. Pinter PublishersLundvall BA (1992) National systems of innovation: towards a theory of innovation and interactive learning. Pinter, LondonNelson RR (1993) In: Nelson RR (ed) National innovation systems. a comparative analysisIsard W (1975) Introduction to regional science. Prentice Hall, New YorkCooke P, Uranga MG, Etxebarria G (1998) Regional systems of innovation: an evolutionary perspective. Environ Plan A 30:1563–1584. https://doi.org/10.1068/a301563Forrest JE (1991) Models of the process of technological innovation. Tech Anal Strat Manag 4(3):439–452. https://doi.org/10.1080/09537329108524070Cooke P, Uranga MG, Etxebarria G (1997) Regional innovation systems: institutional and organisational dimensions. Res Policy 26(4–5):475–491. https://doi.org/10.1016/S0048-7333(97)00025-5Cooke P (1992) Regional innovation systems: competitive regulation in the new Europe. Geoforum 23(3):365–382. https://doi.org/10.1016/0016-7185(92)90048-9Asheim BT, Smith HL, Oughton C (2011) Regional innovation systems: theory, empirics and policy. Reg Stud 45(7):875–891. https://doi.org/10.1080/00343404.2011.596701Doloreux, D., & Parto, S. (2004). Regional innovation systems: a critical synthesis. United Nations University, Institute for New Technologies, Discussion Paper Series #2004-17.Asheim BT, Coenen L (2005) Knowledge bases and regional innovation systems: comparing Nordic clusters. Res Policy 34(8):1173–1190. https://doi.org/10.1016/j.respol.2005.03.013Borrás S, Jordana J (2016) When regional innovation policies meet policy rationales and evidence: a plea for policy analysis. Eur Plan Stud 24(12):2133–2153. https://doi.org/10.1080/09654313.2016.1236074Buesa M, Heijs J, Pellitero MM, Baumert T (2006) Regional systems of innovation and the knowledge production function: the Spanish case. Technovation 26(4):463–472. https://doi.org/10.1016/j.technovation.2004.11.007Isaksen A, Normann RH, Spilling OR (2017) Do general innovation policy tools fit all? Analysis of the regional impact of the Norwegian Skattefunn scheme. J Innov Entrep 6(1):6. https://doi.org/10.1186/s13731-017-0068-xMytelka LK (2000) Local systems of innovation in a globalized world economy. Ind Innov 7(1):15–32. https://doi.org/10.1080/713670244Freeman C (1995) The national system of innovation in historical perspective. Camb J Econ 19:5–24. https://doi.org/10.1093/oxfordjournals.cje.a035309Edler J, Fagerberg J (2017) Innovation policy: what, why, and how. Oxf Rev Econ Policy 33(1):2–23. https://doi.org/10.1093/oxrep/grx001European Commission (2014). The European Union explained: research and innovation. Luxembourg, Publications Office of the European Union, 2014. doi:https://doi.org/10.2775/74012.OECD (2015) The innovation imperative: contributing to productivity, growth and well-being. OECD Publishing, Paris. https://doi.org/10.1787/9789264239814-enLundvall BA, Johnson B, Andersen ES, Dalum B (2002) National systems of production, innovation and competence-building. Res Policy 31(2):213–231. https://doi.org/10.1016/S0048-7333(01)00137-8Sharif N (2006) Emergence and development of the national innovation systems concept. Res Policy 35(5):745–766. https://doi.org/10.1016/j.respol.2006.04.001Etzkowitz H, Leydesdorff L (2000) The dynamics of innovation: from national systems and “Mode 2” to a triple helix of university-industry-government relations. Res Policy 29:109–123. https://doi.org/10.1016/S0048-7333(99)00055-4Chesbrough H (2003) Open innovation: the new imperative for creating and profiting from technology. Harvard Business School PressTodtling F, Trippl M (2005) One size fits all? Towards a differentiated regional innovation policy approach. Res Policy 34(8):1203–1219. https://doi.org/10.1016/j.respol.2005.01.018Uyarra E (2010) What is evolutionary about ‘regional systems of innovation’? Implications for regional policy. J Evol Econ 20:115–137. https://doi.org/10.1007/s00191-009-0135-yMetcalfe JS (1995) Technology systems and technology policy in an evolutionary framework. Camb J Econ 19:25–46. https://doi.org/10.1093/oxfordjournals.cje.a035307Nelson R, Winter S (1982) An evolutionary theory of economic change. Belknap, CambridgeDosi G (1988) The nature of the innovative process. In: Dosi G et al (eds) Technical change and economic theory. Pinter, LondonKline S, Rosenberg N (1986) An overview of innovation. Reprinted. In: Edquist C, McKelvey M (eds) Systems of innovation: growth, competitiveness and employment. Edward Elgar, CheltenhamEdquist C, Johnson B (1997) Institutions and organisations in systems of innovation. In: Edquist C (ed) , pp 41–63Edquist C (ed) (1997) Systems of innovation: technologies, institutions and organisations. Pinter, LondonBoschma R (2004) Competitiveness of regions from an evolutionary perspective. Reg Stud 38(9):1001–1014. https://doi.org/10.1080/0034340042000292601Iammarino S (2005) An evolutionary integrated view of regional systems of innovation: concepts, measures and historical perspectives. Eur Plan Stud 13(4):497–519. https://doi.org/10.1080/09654310500107084Asheim B, Coenen L, Moodysson J, Vang J (2007) Constructing knowledge-based regional advantage: implications for regional innovation policy. Int J Entrep Innov Manag 7(2-5):140–155. https://doi.org/10.1504/IJEIM.2007.012879Asheim B, Moodysson J (2017). Innovation policy for economic resilience: the case of Sweden (No. 2017/5). Lund University, CIRCLE-Center for Innovation, Research and Competences in the Learning Economy.Pritchard A (1969) Statistical bibliographic or bibliometrics? J Doc 25(4):348–349Lawani S (1981) Bibliometrics: its theoretical foundations, methods and applications. Libri 31(4):294–315. https://doi.org/10.1515/libr.1981.31.1.294Thelwall M (2008) Bibliometrics to webometrics. J Inf Sci 34(4):605–621. https://doi.org/10.1177/0165551507087238Hirsch JE (2005) An index to quantify an individual’s scientific research output. Proc Natl Acad Sci U S A 102:16569–16572. https://doi.org/10.1073/pnas.0507655102Small H (1999) Visualizing science by citation mapping. J Am Soc Inf Sci 50(9):799–813 https://doi.org/10.1002/(SICI)1097-4571(1999)50:93.0.CO;2-GNoyons ECM, Moed HF, Van Raan AFJ (1999) Integrating research performance analysis and science mapping. Scientometrics 46(3):591–604. https://doi.org/10.1007/BF02459614Callon M, Courtial P, Turner WA, Bauin S (1983) From translations to problematic networks: an introduction to co-word analysis. Soc Sci Inf 22(2):191–235. https://doi.org/10.1177/053901883022002003Kessler MM (1963) Bibliographic coupling between scientific papers. Am Doc 14:10–25. https://doi.org/10.1002/asi.5090140103Small H (1973) Co-citation in the scientific literature: a new measure of relationship between two documents. J Am Soc Inf Sci 24:265–269. https://doi.org/10.1002/asi.4630240406White HD, Griffith BC (1981) Author co-citation: a literature measure of intellectual structure. J Am Soc Inf Sci 21:163–172. https://doi.org/10.1002/asi.4630320302Van Eck NJ, Waltman L (2010) Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 84(2):523–538. https://doi.org/10.1007/s11192-009-0146-3Cobo MJ, López-Herrera AG, Herrera-Viedma E, Herrera F (2011) Science mapping software tools: review, analysis, and cooperative study among tools. J Am Soc Inf Sci Technol 62(7):1382–1402. https://doi.org/10.1002/asi.21525Merigó JM, Yang JB (2016) A bibliometric analysis of operations research and management science. Omega 73:37–48. https://doi.org/10.1016/j.omega.2016.12.004Acs ZJ, Anselin L, Varga A (2002) Patents and innovation counts as measures of regional production of new knowledge. Res Policy 31(7):1069–1085. https://doi.org/10.1016/S0048-7333(01)00184-6Muller E, Zenker A (2001) Business services as actors of knowledge transformation: the role of KIBS in regional and national innovation systems. Res Policy 30(9):1501–1516. https://doi.org/10.1016/S0048-7333(01)00164-0Rodriguez-Pose A, Crescenzi R (2008) Research and development, spillovers, innovation systems, and the genesis of regional growth in Europe. Reg Stud 42(1):51–67. https://doi.org/10.1080/00343400701654186Ter Wal ALJ, Boschma RA (2009) Applying social network analysis in economic geography: framing some key analytic issues. Ann Reg Sci 43(3):739–756. https://doi.org/10.1007/s00168-008-0258-3Cooke P (2005) Regionally asymmetric knowledge capabilities and open innovation. Exploring ‘Globalisation 2’ – a new model of industry organization. Res Policy 34(8):1128–1149. https://doi.org/10.1016/j.respol.2004.12.005Fritsch M, Franke G (2004) Innovation, regional knowledge spillovers and R&D cooperation. Res Policy 33(2):245–255. https://doi.org/10.1016/S0048-7333(03)00123-9Hansen HK, Niedomysl T (2009) Migration of the creative class: evidence from Sweden. J Econ Geogr 9(2):191–206. https://doi.org/10.1093/jeg/lbn046Yam RCM, Lo W, Tang EPY, Lau AKW (2011) Analysis of sources of innovation, technological innovation capabilities, and performance: an empirical study of Hong Kong manufacturing industries. Res Policy 40(3):391–402. https://doi.org/10.1016/j.respol.2010.10.013Spigel B (2017) The relational organization of entrepreneurial ecosystems. Entrep Theory Pract 41(1):49–72. https://doi.org/10.1111/etap.12167Oh DS, Phillips F, Park S, Lee E (2016) Innovation ecosystems: a critical examination. Technovation 54:1–6. https://doi.org/10.1016/j.technovation.2016.02.004Audretsch DB, Belitski M (2017) Entrepreneurial ecosystems in cities: establishing the framework conditions. J Technol Transfer 42(5):1030–1051. https://doi.org/10.1007/s10961-016-9473-8Gaviria-Marin M, Merigó JM, Baier-Fuentes H (2019) Knowledge management: a global examination based on bibliometric analysis. Technol Forecast Soc Chang 140:194–220. https://doi.org/10.1016/j.techfore.2018.07.006Huber F (2011) Do clusters really matter for innovation practices in Information Technology? Questioning the significance of technological knowledge spillovers. J Econ Geogr 12(1):107–126. https://doi.org/10.1093/jeg/lbq058Miles I, Kastrinos N, Bilderbeek R, Hertog PD, Flanagan K, Huntink W, Bouman M (1995) Knowledge-intensive business services: users, carriers and sources of information. European Innovation Monitoring System (EIMS) Reports, European Commission, BrusselsNonaka I (1994) A dynamic theory of organizational knowledge creation. Organ Sci 5(1):14–37. https://doi.org/10.1287/orsc.5.1.14Acs ZJ, Autio E, Szerb L (2014) National systems of entrepreneurship: measurement issues and policy implications. Res Policy 43(3):476–494. https://doi.org/10.1016/j.respol.2013.08.016Autio E, Kenney M, Mustar P, Siegel D, Wright M (2014) Entrepreneurial innovation: the importance of context. Res Policy 43(7):1097–1108. https://doi.org/10.1016/j.respol.2014.01.01

Circulating C-reactive protein and breast cancer risk – systematic literature review and meta-analysis of prospective cohort studies

We conducted a systematic literature review to explore the association between circulating C-reactive protein (CRP), a low-grade inflammation biomarker, and breast cancer risk. Relevant prospective studies in women were identified in PubMed and Web of Science until February 2015. Random-effects dose-response metaanalysis was conducted, overall and in post-menopausal women. Twelve out of 15 studies identified were included in the meta-analysis on any breast cancers (3,522 cases, 69,610 women) and nine on postmenopausal breast cancer (2,516 cases, 36,847 women). For each doubling of CRP concentration, a 7% (95% CI: 2%–12%) and 6% (95% CI: 1%–11%) increased risk was observed (I2=47% and 32%; P heterogeneity=0.04 and 0.17), respectively. The association was linear over most of the range of CRP concentrations. Positive associations remained in the studies that examined the exclusion of early years of follow-up. Associations were attenuated in studies adjusted for lifestyle factors, which partly explained the significant heterogeneity between studies in the overall analysis. On average, the associations in studies adjusted or not adjusted for body mass index were similar. Low-grade inflammation may have a role in breast cancer development. Additional prospective studies are needed to better understand confounding and effect modification from lifestyle factors

Preclinical Models of Middle Cerebral Artery Occlusion: New Imaging Approaches to a Classic Technique

Stroke remains a major burden on patients, families, and healthcare professionals, despite major advances in prevention, acute treatment, and rehabilitation. Preclinical basic research can help to better define mechanisms contributing to stroke pathology, and identify therapeutic interventions that can decrease ischemic injury and improve outcomes. Animal models play an essential role in this process, and mouse models are particularly well-suited due to their genetic accessibility and relatively low cost. Here, we review the focal cerebral ischemia models with an emphasis on the middle cerebral artery occlusion technique, a gold standard in surgical ischemic stroke models. Also, we highlight several histologic, genetic, and in vivo imaging approaches, including mouse stroke MRI techniques, that have the potential to enhance the rigor of preclinical stroke evaluation. Together, these efforts will pave the way for clinical interventions that can mitigate the negative impact of this devastating disease

Preclinical models of middle cerebral artery occlusion: new imaging approaches to a classic technique

Stroke remains a major burden on patients, families, and healthcare professionals, despite major advances in prevention, acute treatment, and rehabilitation. Preclinical basic research can help to better define mechanisms contributing to stroke pathology, and identify therapeutic interventions that can decrease ischemic injury and improve outcomes. Animal models play an essential role in this process, and mouse models are particularly well-suited due to their genetic accessibility and relatively low cost. Here, we review the focal cerebral ischemia models with an emphasis on the middle cerebral artery occlusion technique, a “gold standard” in surgical ischemic stroke models. Also, we highlight several histologic, genetic, and in vivo imaging approaches, including mouse stroke MRI techniques, that have the potential to enhance the rigor of preclinical stroke evaluation. Together, these efforts will pave the way for clinical interventions that can mitigate the negative impact of this devastating disease

Contributions of mean and shape of blood pressure distribution to worldwide trends and variations in raised blood pressure: A pooled analysis of 1018 population-based measurement studies with 88.6 million participants

© The Author(s) 2018. Background: Change in the prevalence of raised blood pressure could be due to both shifts in the entire distribution of blood pressure (representing the combined effects of public health interventions and secular trends) and changes in its high-blood-pressure tail (representing successful clinical interventions to control blood pressure in the hypertensive population). Our aim was to quantify the contributions of these two phenomena to the worldwide trends in the prevalence of raised blood pressure. Methods: We pooled 1018 population-based studies with blood pressure measurements on 88.6 million participants from 1985 to 2016. We first calculated mean systolic blood pressure (SBP), mean diastolic blood pressure (DBP) and prevalence of raised blood pressure by sex and 10-year age group from 20-29 years to 70-79 years in each study, taking into account complex survey design and survey sample weights, where relevant. We used a linear mixed effect model to quantify the association between (probittransformed) prevalence of raised blood pressure and age-group- and sex-specific mean blood pressure. We calculated the contributions of change in mean SBP and DBP, and of change in the prevalence-mean association, to the change in prevalence of raised blood pressure. Results: In 2005-16, at the same level of population mean SBP and DBP, men and women in South Asia and in Central Asia, the Middle East and North Africa would have the highest prevalence of raised blood pressure, and men and women in the highincome Asia Pacific and high-income Western regions would have the lowest. In most region-sex-age groups where the prevalence of raised blood pressure declined, one half or more of the decline was due to the decline in mean blood pressure. Where prevalence of raised blood pressure has increased, the change was entirely driven by increasing mean blood pressure, offset partly by the change in the prevalence-mean association. Conclusions: Change in mean blood pressure is the main driver of the worldwide change in the prevalence of raised blood pressure, but change in the high-blood-pressure tail of the distribution has also contributed to the change in prevalence, especially in older age groups

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(.)(1,2) This has led to a widely reported view that urbanization is one of the most important drivers of the global rise in obesity(3-6). Here we use 2,009 population-based studies, with measurements of height and weight in more than 112 million adults, to report national, regional and global trends in mean BMI 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 some 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 in 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.Peer reviewe

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

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. Copyright (C) 2021 World Health Organization; licensee Elsevier