A Conceptual Framework for Healthy Eating Behavior in Ecuadorian Adolescents: A Qualitative Study

Objective: The objective of this study was to identify factors influencing eating behavior of Ecuadorian adolescents - from the perspective of parents, school staff and adolescents - to develop a conceptual framework for adolescents’ eating behavior. Study design: Twenty focus groups (N = 144 participants) were conducted separately with adolescents aged 11–15 y (n (focus groups) = 12, N (participants) = 80), parents (n = 4, N = 32) and school staff (n = 4, N = 32) in rural and urban Ecuador. A semi-structured questioning route was developed based on the ‘Attitude, Social influences and Self-efficacy’ model and the socio-ecological model to assess the relevance of behavioral and environmental factors in low- and middle-income countries. Two researchers independently analyzed verbatim transcripts for emerging themes, using deductive thematic content analysis. Data were analyzed using NVivo 8. Results: All groups recognized the importance of eating healthily and key individual factors in Ecuadorian adolescents’ food choices were: financial autonomy, food safety perceptions, lack of self-control, habit strength, taste preferences and perceived peer norms. Environmental factors included the poor nutritional quality of food and its easy access at school. In their home and family environment, time and convenience completed the picture as barriers to eating healthily. Participants acknowledged the impact of the changing socio-cultural environment on adolescents’ eating patterns. Availability of healthy food at home and financial constraints differed between settings and socio-economic groups. Conclusion: Our findings endorse the importance of investigating behavioral and environmental factors that influence and mediate healthy dietary behavior prior to intervention development. Several culture-specific factors emerged that were incorporated into a conceptual framework for developing health promotion interventions in Ecuador

Status and trends of physical activity surveillance, policy, and research in 164 countries: Findings from the Global Observatory for Physical Activity—GoPA! 2015 and 2020 Surveys

BACKGROUND: Physical activity (PA) surveillance, policy, and research efforts need to be periodically appraised to gain insight into national and global capacities for PA promotion. The aim of this paper was to assess the status and trends in PA surveillance, policy, and research in 164 countries. METHODS: We used data from the Global Observatory for Physical Activity (GoPA!) 2015 and 2020 surveys. Comprehensive searches were performed for each country to determine the level of development of their PA surveillance, policy, and research, and the findings were verified by the GoPA! Country Contacts. Trends were analyzed based on the data available for both survey years. RESULTS: The global 5-year progress in all 3 indicators was modest, with most countries either improving or staying at the same level. PA surveillance, policy, and research improved or remained at a high level in 48.1%, 40.6%, and 42.1% of the countries, respectively. PA surveillance, policy, and research scores decreased or remained at a low level in 8.3%, 15.8%, and 28.6% of the countries, respectively. The highest capacity for PA promotion was found in Europe, the lowest in Africa and low- and lower-middle-income countries. Although a large percentage of the world's population benefit from at least some PA policy, surveillance, and research efforts in their countries, 49.6 million people are without PA surveillance, 629.4 million people are without PA policy, and 108.7 million live in countries without any PA research output. A total of 6.3 billion people or 88.2% of the world's population live in countries where PA promotion capacity should be significantly improved. CONCLUSION: Despite PA is essential for health, there are large inequalities between countries and world regions in their capacity to promote PA. Coordinated efforts are needed to reduce the inequalities and improve the global capacity for PA promotion

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

Heterogeneous contributions of change in population distribution of body mass index to change in obesity and underweight NCD Risk Factor Collaboration (NCD-RisC)

From 1985 to 2016, the prevalence of underweight decreased, and that of obesity and severe obesity increased, in most regions, with significant variation in the magnitude of these changes across regions. We investigated how much change in mean body mass index (BMI) explains changes in the prevalence of underweight, obesity, and severe obesity in different regions using data from 2896 population-based studies with 187 million participants. Changes in the prevalence of underweight and total obesity, and to a lesser extent severe obesity, are largely driven by shifts in the distribution of BMI, with smaller contributions from changes in the shape of the distribution. In East and Southeast Asia and sub-Saharan Africa, the underweight tail of the BMI distribution was left behind as the distribution shifted. There is a need for policies that address all forms of malnutrition by making healthy foods accessible and affordable, while restricting unhealthy foods through fiscal and regulatory restrictions

Trends in cardiometabolic risk factors in the Americas between 1980 and 2014: a pooled analysis of population-based surveys

Background: Describing the prevalence and trends of cardiometabolic risk factors that are associated with noncommunicable diseases (NCDs) is crucial for monitoring progress, planning prevention, and providing evidence to support policy efforts. We aimed to analyse the transition in body-mass index (BMI), obesity, blood pressure, raised blood pressure, and diabetes in the Americas, between 1980 and 2014. Methods: We did a pooled analysis of population-based studies with data on anthropometric measurements, biomarkers for diabetes, and blood pressure from adults aged 18 years or older. A Bayesian model was used to estimate trends in BMI, raised blood pressure (systolic blood pressure ≥140 mm Hg or diastolic blood pressure ≥90 mm Hg), and diabetes (fasting plasma glucose ≥7•0 mmol/L, history of diabetes, or diabetes treatment) from 1980 to 2014, in 37 countries and six subregions of the Americas. Findings: 389 population-based surveys from the Americas were available. Comparing prevalence estimates from 2014 with those of 1980, in the non-English speaking Caribbean subregion, the prevalence of obesity increased from 3•9% (95% CI 2•2–6•3) in 1980, to 18•6% (14•3–23•3) in 2014, in men; and from 12•2% (8•2–17•0) in 1980, to 30•5% (25•7–35•5) in 2014, in women. The English-speaking Caribbean subregion had the largest increase in the prevalence of diabetes, from 5•2% (2•1–10•4) in men and 6•4% (2•6–10•4) in women in 1980, to 11•1% (6•4–17•3) in men and 13•6% (8•2–21•0) in women in 2014). Conversely, the prevalence of raised blood pressure has decreased in all subregions; the largest decrease was found in North America from 27•6% (22•3–33•2) in men and 19•9% (15•8–24•4) in women in 1980, to 15•5% (11•1–20•9) in men and 10•7% (7•7–14•5) in women in 2014. Interpretation: Despite the generally high prevalence of cardiometabolic risk factors across the Americas, estimates also showed a high level of heterogeneity in the transition between countries. The increasing prevalence of obesity and diabetes observed over time requires appropriate measures to deal with these public health challenges. Our results support a diversification of health interventions across subregions and countries.Fil: Miranda, J. Jaime. Universidad Peruana Cayetano Heredia; PerúFil: Carrillo-Larco, Rodrigo M.. Imperial College London; Reino UnidoFil: Ferreccio, Catterina. Pontificia Universidad Católica de Chile; ChileFil: Hambleton, Ian R.. The University Of The West Indies; BarbadosFil: Lotufo, Paulo A.. Universidade de Sao Paulo; BrasilFil: Nieto-Martinez, Ramfis. Miami Veterans Affairs Healthcare System; Estados UnidosFil: Zhou, Bin. Imperial College London; Reino UnidoFil: Bentham, James. University Of Kent; Reino UnidoFil: Bixby, Honor. Imperial College London; Reino UnidoFil: Hajifathalian, Kaveh. Cleveland Clinic; Estados UnidosFil: Lu, Yuan. University of Yale; Estados UnidosFil: Taddei, Cristina. Imperial College London; Reino UnidoFil: Abarca-Gomez, Leandra. Caja Costarricense de Seguro Social; Costa RicaFil: Acosta-Cazares, Benjamin. Instituto Mexicano del Seguro Social; MéxicoFil: Aguilar-Salinas, Carlos A.. (Instituto Nacional de Ciencias Médicas y Nutrición; MéxicoFil: Andrade, Dolores S.. Universidad de Cuenca; EcuadorFil: Assunção, Maria Cecilia F.. Universidade Federal de Pelotas; BrasilFil: Barcelo, Alberto. Pan American Health Organization; Estados UnidosFil: Barros, Aluisio J.D.. Universidade Federal de Pelotas; BrasilFil: Barros, Mauro V.G.. Universidade de Pernambuco; BrasilFil: Bata, Iqbal. Dalhousie University Halifax; CanadáFil: Batista, Rosangela L.. Universidade Federal Do Maranhao; BrasilFil: Benet, Mikhail. Cafam University Foundation; ColombiaFil: Bernabe-Ortiz, Antonio. Universidad Peruana Cayetano Heredia; PerúFil: Bettiol, Heloisa. Universidade de Sao Paulo; BrasilFil: Boggia, Jose G.. Universidad de la Republica; UruguayFil: Boissonnet, Carlos P.. Centro de Educación Médica e Investigaciones Clínicas; ArgentinaFil: Brewster, Lizzy M.. University of Amsterdam; Países BajosFil: Cameron, Christine. Canadian Fitness and Lifestyle Research Institute; CanadáFil: Cândido, Ana Paula C.. Universidade Federal de Juiz de Fora; BrasilFil: Cardoso, Viviane C.. Universidade de Sao Paulo; BrasilFil: Chan, Queenie. Imperial College London; Reino UnidoFil: Christofaro, Diego G.. Universidade Estadual Paulista; BrasilFil: Confortin, Susana C.. Universidade Federal de Santa Catarina; BrasilFil: Craig, Cora L.. Canadian Fitness and Lifestyle Research Institute; CanadáFil: d'Orsi, Eleonora. Universidade Federal de Santa Catarina; BrasilFil: Delisle, Hélène. University of Montreal; CanadáFil: De Oliveira, Paula Duarte. Universidade Federal de Pelotas; BrasilFil: Dias-da-Costa, Juvenal Soares. Universidade do Vale do Rio Dos Sinos; BrasilFil: Diaz, Alberto Alejandro. Universidad Nacional del Centro de la Provincia de Buenos Aires. Escuela Superior de Ciencias de la Salud. Instituto de Investigación en Ciencias de la Salud; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; Argentina. Provincia de Buenos Aires. Municipalidad de Tandil. Hospital Municipal Ramón Santamarina; ArgentinaFil: Donoso, Silvana P.. Universidad de Cuenca; EcuadorFil: Elliott, Paul. Imperial College London; Reino UnidoFil: Escobedo-de La Peña, Jorge. Instituto Mexicano del Seguro Social; MéxicoFil: Ferguson, Trevor S.. The University of The West Indies; JamaicaFil: Fernandes, Romulo A.. Universidade Estadual Paulista; BrasilFil: Ferrante, Daniel. Ministerio de Salud; ArgentinaFil: Flores, Eric Monterubio. Instituto Nacional de Salud Pública; MéxicoFil: Francis, Damian K.. The University of The West Indies; JamaicaFil: Do Carmo Franco, Maria. Universidade Federal de Sao Paulo; BrasilFil: Fuchs, Flavio D.. Hospital de Clinicas de Porto Alegre; BrasilFil: Fuchs, Sandra C.. Universidade Federal do Rio Grande do Sul; BrasilFil: Goltzman, David. Université McGill; CanadáFil: Gonçalves, Helen. Universidade Federal de Pelotas; BrasilFil: Gonzalez-Rivas, Juan P.. The Andes Clinic Of Cardio-Metabolic Studies; VenezuelaFil: Gorbea, Mariano Bonet. Instituto Nacional de Higiene, Epidemiología y Microbiología; CubaFil: Gregor, Ronald D.. Dalhousie University Halifax; CanadáFil: Guerrero, Ramiro. Universidad Icesi; ColombiaFil: Guimaraes, Andre L.. Universidade Estadual de Montes Claros; BrasilFil: Gulliford, Martin C.. King’s College London; Reino UnidoFil: Gutierrez, Laura. Instituto de Efectividad Clínica y Sanitaria; ArgentinaFil: Hernandez Cadena, Leticia. Instituto Nacional de Salud Pública; MéxicoFil: Herrera, Víctor M.. (Universidad Autónoma de Bucaramanga; ColombiaFil: Hopman, Wilma M.. Kingston General Hospital; CanadáFil: Horimoto, Andrea RVR. Instituto do Coração; BrasilFil: Hormiga, Claudia M.. Fundación Oftalmológica de Santander; ColombiaFil: Horta, Bernardo L.. Universidade Federal de Pelotas; BrasilFil: Howitt, Christina. The University of the West Indies; BarbadosFil: Irazola, Wilma E.. Instituto de Efectividad Clínica y Sanitaria; ArgentinaFil: Jiménez-Acosta, Santa Magaly. Instituto Nacional de Higiene, Epidemiología y Microbiología; CubaFil: Joffres, Michel. Simon Fraser University; CanadáFil: Kolsteren, Patricia. (Institute of Tropical Medicine; BélgicaFil: Landrove, Orlando. Ministerio de Salud Pública; CubaFil: Li, Yanping. Harvard TH Chan School of Public Health; Estados UnidosFil: Lilly, Christa L.. West Virginia University; Estados UnidosFil: Lima-Costa, M. Fernanda. Fundação Oswaldo Cruz; BrasilFil: Louzada Strufaldi, Maria Wany. Universidade Federal de Sao Paulo; BrasilFil: Machado-Coelho, George L. L.. Universidade Federal de Ouro Preto; BrasilFil: Makdisse, Marcia. Hospital Israelita Albert Einstein; BrasilFil: Margozzini, Paula. Pontificia Universidad Católica de Chile; ChileFil: Pruner Marques, Larissa. Universidade Federal de Santa Catarina; BrasilFil: Martorell, Reynaldo. Emory University; Estados UnidosFil: Mascarenhas, Luis. Universidade Federal do Paraná; BrasilFil: Matijasevich, Alicia. Universidade Federal de Sao Paulo; BrasilFil: Mc Donald Posso, Anselmo J.. Gorgas Memorial Institute of Health Studies; PanamáFil: McFarlane, Shelly R.. The University of the West Indies; JamaicaFil: McLean, Scott B.. (Statistics Canada; CanadáFil: Menezes, Ana Maria B.. Universidade Federal de Pelotas; BrasilFil: Miquel, Juan Francisco. Pontificia Universidad Católica de Chile; ChileFil: Mohanna, Salim. Universidad Peruana Cayetano Heredia; PerúFil: Monterrubio, Eric A.. Instituto Nacional de Salud Pública; MéxicoFil: Moreira, Leila B.. Universidade Federal do Rio Grande do Sul; BrasilFil: Morejon, Alain. Universidad de Ciencias Médicas; CubaFil: Motta, Jorge. Gorgas Memorial Institute of Public Health; PanamáFil: Neal, William A.. West Virginia University; Estados UnidosFil: Nervi, Flavio. Pontificia Universidad Católica de Chile; ChileFil: Noboa, Oscar A.. Universidad de la República; UruguayFil: Ochoa-Avilés, Angélica M.. Universidad de Cuenca; EcuadorFil: Olinto, Maria Teresa Anselmo. Universidad de Vale do Rio dos Sinos; BrasilFil: Oliveira, Isabel O.. Universidade Federal de Pelotas; BrasilFil: Ono, Lariane M.. Universidade Federal de Santa Catarina; BrasilFil: Ordunez, Pedro. Pan American Health Organization; Estados UnidosFil: Ortiz, Ana P.. Universidad de Puerto Rico; Puerto RicoFil: Otero, Johanna A.. Fundación Oftalmológica de Santander; ColombiaFil: Palloni, Alberto. University of Wisconsin-Madison; Estados UnidosFil: Viana Peixoto, Sergio. Fundação Oswaldo Cruz; BrasilFil: Pereira, Alexandre C.. Instituto do Coração; BrasilFil: Pérez, Cynthia M.. Universidad de Puerto Rico; Puerto RicoFil: Rangel Reina, Daniel A.. Gorgas Memorial Institute of Health Studies; PanamáFil: Ribeiro, Robespierre. Secretaria de Estado de Saúde de Minas Gerais; BrasilFil: Ritti-Dias, Raphael M.. Universidade Nove de Julho; BrasilFil: Rivera, Juan A.. Instituto Nacional de Salud Pública; MéxicoFil: Robitaille, Cynthia. Public Health Agency of Canada; CanadáFil: Rodríguez-Villamizar, Laura A.. Universidad Industrial de Santander; ColombiaFil: Rojas-Martinez, Rosalba. Instituto Nacional de Salud Pública; MéxicoFil: Roy, Joel G. R.. Statistics Canada; CanadáFil: Rubinstein, Adolfo Luis. Instituto de Efectividad Clínica y Sanitaria; ArgentinaFil: Ruiz-Betancourt, Blanca Sandra. Instituto Mexicano del Seguro Social; MéxicoFil: Salazar Martinez, Eduardo. Instituto Nacional de Salud Pública; MéxicoFil: Sánchez-Abanto, José. Instituto Nacional de Salud; PerúFil: Santos , Ina S.. Universidade Federal de Pelotas; BrasilFil: dos Santos, Renata Nunes. Universidade Federal de Sao Paulo; BrasilFil: Scazufca, Marcia. Universidade Federal de Sao Paulo; BrasilFil: Schargrodsky, Herman. Hospital Italiano; ArgentinaFil: Silva, Antonio M.. Universidade Federal do Maranhao; BrasilFil: Santos Silva, Diego Augusto. Universidade Federal de Santa Catarina; BrasilFil: Stein, Aryeh D.. Emory University; Estados UnidosFil: Suárez-Medina, Ramón. Instituto Nacional de Higiene, Epidemiología y Microbiología; CubaFil: Tarqui-Mamani, Carolina B.. Instituto Nacional de Salud; PerúFil: Tulloch-Reid, Marshall K.. The University of the West Indies; JamaicaFil: Ueda, Peter. Harvard TH Chan School of Public Health; Estados UnidosFil: Ugel, Eunice E.. Universidad Centro-Occidental Lisandro Alvarado; VenezuelaFil: Valdivia, Gonzalo. Pontificia Universidad Católica de Chile; ChileFil: Varona, Patricia. Instituto Nacional de Higiene, Epidemiología y Microbiología; CubaFil: Velasquez-Melendez, Gustavo. Universidade Federal de Minas Gerais; BrasilFil: Verstraeten, Roosmarijn. Institute of Tropical Medicine; BélgicaFil: Victora, Cesar G.. Universidade Federal de Pelotas; BrasilFil: Wanderley Jr, Rildo S.. Universidade Federal de Pernambuco; BrasilFil: Wang, Ming-Dong. Public Health Agency of Canada; CanadáFil: Wilks, Rainford J.. The University of the West Indies; JamaicaFil: Wong-McClure, Roy A.. Caja Costarricense de Seguro Social; Costa RicaFil: Younger-Coleman, Novie O.. The University of the West Indies; JamaicaFil: Zuñiga Cisneros, Julio. Gorgas Memorial Institute of Public Health; PanamáFil: Danaei, Goodarz. Harvard TH Chan School of Public Health; Estados UnidosFil: Stevens, Gretchen A.. World Health Organization; SuizaFil: Riley, Leanne M.. World Health Organization; SuizaFil: Ezzati, Majid. (Imperial College London; Reino UnidoFil: Di Cesare, Mariachiara. Middlesex University; Reino Unid

Status and Trends of Physical Activity Surveillance, Policy, and Research in 164 Countries: Findings From the Global Observatory for Physical Activity—GoPA! 2015 and 2020 Surveys

Background: Physical activity (PA) surveillance, policy, and research efforts need to be periodically appraised to gain insight into national and global capacities for PA promotion. The aim of this paper was to assess the status and trends in PA surveillance, policy, and research in 164 countries. Methods: We used data from the Global Observatory for Physical Activity (GoPA!) 2015 and 2020 surveys. Comprehensive searches were performed for each country to determine the level of development of their PA surveillance, policy, and research, and the findings were verified by the GoPA! Country Contacts. Trends were analyzed based on the data available for both survey years. Results: The global 5-year progress in all 3 indicators was modest, with most countries either improving or staying at the same level. PA surveillance, policy, and research improved or remained at a high level in 48.1%, 40.6%, and 42.1% of the countries, respectively. PA surveillance, policy, and research scores decreased or remained at a low level in 8.3%, 15.8%, and 28.6% of the countries, respectively. The highest capacity for PA promotion was found in Europe, the lowest in Africa and low- and lower-middle-income countries. Although a large percentage of the world’s population benefit from at least some PA policy, surveillance, and research efforts in their countries, 49.6 million people are without PA surveillance, 629.4 million people are without PA policy, and 108.7 million live in countries without any PA research output. A total of 6.3 billion people or 88.2% of the world’s population live in countries where PA promotion capacity should be significantly improved. Conclusion: Despite PA is essential for health, there are large inequalities between countries and world regions in their capacity to promote PA. Coordinated efforts are needed to reduce the inequalities and improve the global capacity for PA promotion.</jats:p

Effects of diabetes definition on global surveillance of diabetes prevalence and diagnosis: A pooled analysis of 96 population-based studies with 331 288 participants

Background Diabetes has been defined on the basis of different biomarkers, including fasting plasma glucose (FPG), 2-h plasma glucose in an oral glucose tolerance test (2hOGTT), and HbA(1c). We assessed the effect of different diagnostic definitions on both the population prevalence of diabetes and the classification of previously undiagnosed individuals as having diabetes versus not having diabetes in a pooled analysis of data from population-based health examination surveys in different regions. Methods We used data from 96 population-based health examination surveys that had measured at least two of the biomarkers used for defining diabetes. Diabetes was defined using HbA(1c) (HbA(1c) &gt;= 6 . 5% or history of diabetes diagnosis or using insulin or oral hypoglycaemic drugs) compared with either FPG only or FPG-or-2hOGTT definitions (FPG &gt;= 7 . 0 mmol/L or 2hOGTT &gt;= 11 . 1 mmol/L or history of diabetes or using insulin or oral hypoglycaemic drugs). We calculated diabetes prevalence, taking into account complex survey design and survey sample weights. We compared the prevalences of diabetes using different definitions graphically and by regression analyses. We calculated sensitivity and specificity of diabetes diagnosis based on HbA1c compared with diagnosis based on glucose among previously undiagnosed individuals (ie, excluding those with history of diabetes or using insulin or oral hypoglycaemic drugs). We calculated sensitivity and specificity in each survey, and then pooled results using a random-effects model. We assessed the sources of heterogeneity of sensitivity by meta-regressions for study characteristics selected a priori. Findings Population prevalence of diabetes based on FPG- or-2hOGTT was correlated with prevalence based on FPG alone (r= 0 . 98), but was higher by 2-6 percentage points at different prevalence levels. Prevalence based on HbA(1c) was lower than prevalence based on FPG in 42 . 8% of age-sex-survey groups and higher in another 41 . 6%; in the other 15 . 6%, the two definitions provided similar prevalence estimates. The variation across studies in the relation between glucose-based and HbA(1c)-based prevalences was partly related to participants' age, followed by natural logarithm of per person gross domestic product, the year of survey, mean BMI, and whether the survey population was national, subnational, or from specific communities. Diabetes defined as HbA(1c) 6 . 5% or more had a pooled sensitivity of 52 . 8% (95% CI 51 . 3-54 . 3%) and a pooled specificity of 99 . 74% (99 . 71-99 . 78%) compared with FPG 7 . 0 mmol/L or more for diagnosing previously undiagnosed participants; sensitivity compared with diabetes defined based on FPG-or-2hOGTT was 30 . 5% (28 . 7-32 . 3%). None of the preselected study-level characteristics explained the heterogeneity in the sensitivity of HbA(1c) versus FPG. Interpretation Different biomarkers and definitions for diabetes can provide different estimates of population prevalence of diabetes, and differentially identify people without previous diagnosis as having diabetes. Using an HbA(1c)-based definition alone in health surveys will not identify a substantial proportion of previously undiagnosed people who would be considered as having diabetes using a glucose-based test

Diminishing benefits of urban living for children and adolescents’ growth and development

Optimal growth and development in childhood and adolescence is crucial for lifelong health and well-being1–6. Here we used data from 2,325 population-based studies, with measurements of height and weight from 71 million participants, to report the height and body-mass index (BMI) of children and adolescents aged 5–19 years on the basis of rural and urban place of residence in 200 countries and territories from 1990 to 2020. In 1990, children and adolescents residing in cities were taller than their rural counterparts in all but a few high-income countries. By 2020, the urban height advantage became smaller in most countries, and in many high-income western countries it reversed into a small urban-based disadvantage. The exception was for boys in most countries in sub-Saharan Africa and in some countries in Oceania, south Asia and the region of central Asia, Middle East and north Africa. In these countries, successive cohorts of boys from rural places either did not gain height or possibly became shorter, and hence fell further behind their urban peers. The difference between the age-standardized mean BMI of children in urban and rural areas was <1.1 kg m–2 in the vast majority of countries. Within this small range, BMI increased slightly more in cities than in rural areas, except in south Asia, sub-Saharan Africa and some countries in central and eastern Europe. Our results show that in much of the world, the growth and developmental advantages of living in cities have diminished in the twenty-first century, whereas in much of sub-Saharan Africa they have amplified