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. MethodsWe 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

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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/m 2 . 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, the...

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O objetivo do estudo foi analisar a autopercepção da imagem corporal (IC) e associar a IC com indicadores sociodemográficos, estado nutricional e nível de atividade física de universitários. Realizou-se um estudo transversal com 294 universitários (136 homens e 158 mulheres), mensurou-se a percepção da IC por meio da escala de silhueta, indicando a silhueta atual (SA), silhueta ideal (SI) e a silhueta ideal do sexo oposto (SIO). Ainda foram coletadas variáveis demográficas (sexo, idade, turno de estudo, ocupação), nível socioeconõmico, estado nutricional (índice de massa corporal) e o nível de atividade física (IPAQ - versão curta). Utilizou-se a análise descritiva e o teste de associação do qui-quadrado para análise dos dados. A prevalência de insatisfação com a IC foi de 61,2% (n = 180), sendo 61% nos homens e 61,4% nas mulheres. A silhueta 2 foi apontada por 57% das mulheres como a SI, entre os homens 38,2% e 39,7% apontaram a silhueta 3 e 4 como a SI. Foi identificada como SIO à silhueta 3 (63,2% masculino e 56,3% feminino). As mulheres demonstraram uma maior percepção (67,6%) em possuir uma silhueta menor que a atual. Já entre os homens houve a tendência (66,7%) a desejarem uma silhueta maior do que a atual. Além do sexo a percepção com a IC foi associada com o estado nutricional (p < 0,05), onde se observou que 78,7% dos indivíduos com excesso de peso desejam ter uma silhueta menor do que a atual. Concluísse que a autopercepção da IC esteve associada ao sexo e ao estado nutricional nos universitários

OBJECTIVE:To estimate the prevalence of physical activity in adolescents and to identify associated factors. METHODS:A cross-sectional study was conducted with a representative sample (n=1,518, 59.2% females) of students aged between 14 and 18 years, enrolled in the public school network of the city of Curitiba, Southern Brazil, in 2006. Physical activity practice was self-reported, according to the number of days per week when they perform moderate to vigorous physical activity lasting ≥ 60 minutes. This practice was analyzed in two distinct models. In the fi rst model, the variable was dichotomized into "0 day" and "≥ 1 day"; in the second, into "≤ 4 days" and "≥ 5 days". Independent variables were as follows: biological-demographic (sex, age, body mass index); socioeconomic (parents' level of education, number of cars); behavioral (number of hours spent watching television, number of hours spent using a computer); and sociocultural (social support from family and friends and the perception of barriers to the practice of activities), tested with Poisson regression. RESULTS:In the fi rst model of analysis, the prevalence of physical activity was 58.2% (75.1% in males; 46.5% in females; p<0.001), while, in the second, it was 14.5% (22.3% and 9.1%, respectively; p<0.001). In the fi rst model, the variables associated with physical activity were: male sex (PR=1.63, 95% CI: 1.48;1.78), social support from family (PR=1.14, 95% CI: 1.05;1.23), social support from friends (PR=1.52, 95% CI: 1.31;1.78) and high perception of barriers (PR=0.54, 95% CI: 0.46;0.62). In the second model, only male sex (PR=2.45, 95% CI: 1.73;3.46) and high perception of barriers (PR=0.24, 95% CI: 0.15;0.38) were associated with physical activity. CONCLUSIONS:More than half of adolescents practice physical activity at least one day of the week, although 14.5% achieved the current recommendations. The recommended levels are associated with a lower number of factors. Gender and perception of barriers were consistently associated with physical activity levels.

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