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

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...

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.

ObjectiveThe aim of this study was to examine the associations between sedentary behavior and different intensities of physical activity with cardiometabolic risk, and to analyze the simultaneous effect of excess sedentary behavior and recommended levels of physical activity on cardiometabolic risk markers in older adults.MethodsWe conducted a population-based cross-sectional study on a sample of older adults (60+) living in Florianopolis, Brazil. The objectively measured predictors were sedentary time, light physical activity and moderate to vigorous physical activity, and the outcomes were markers of cardiometabolic risk. Data were considered valid when the participant had used the accelerometer for at least four days per week.ResultsThe sample included 425 older adults (59.8% women), with a mean age of 73.9 years (95%CI: 73.5–74.4). Sedentary behavior was associated with lower systolic blood pressure levels (β = -0.03; 95%CI: -0.05; -0.01) and lower HDL cholesterol (β = -0.02; 95%CI: -0.02; -0.01). Light physical activity was not associated with any cardiovascular risk markers after adjustment. Each minute spent in moderate to vigorous physical activity was associated with lower waist circumference (β = -0.15; 95%CI: -0.24; -0.05), systolic blood pressure (β = -0.18; 95%CI: -0.32; -0.04) and plasma glucose (β = -0.18; 95%CI: -0.33;-0.02), and with higher HDL cholesterol (β = 0.10; 95%CI: 0.01; 0.18). Moreover, physically inactive and sedentary individuals had a greater mean waist circumference and lower HDL cholesterol than physically active and non-sedentary subjects.ConclusionThe results suggest that moderate to vigorous physical activity have a positive impact on cardiometabolic risk markers in older adults. Light physical activity does not appear to have a beneficial effect on the cardiometabolic markers, and despite the benefits provided by the different intensities of physical activity, the simultaneous presence of sedentary behavior and low physical activity level was associated with poor cardiometabolic risk markers.

RESUMO: Objetivo: Investigar a prevalência da simultaneidade de fatores de risco cardiovasculares e sua associação com características sociodemográficas em idosos no sul do Brasil. Metodologia: Estudo transversal com 1.553 idosos participantes do Estudo Epidemiológico das Condições de Saúde dos Idosos de Florianópolis (EpiFloripa Idoso), Santa Catarina. Os fatores de risco foram: insuficiência no consumo de frutas, legumes e vegetais (FLV), insuficiência de atividade física no lazer, consumo abusivo de álcool e tabagismo. Construiu-se a variável desfecho através da combinação de todos os fatores, categorizada em nenhum, um, dois, três e quatro fatores de risco. Foram realizadas análises bivariadas e multivariadas empregando-se a regressão de Poisson. Resultados: Constatou-se que 57,6% dos idosos convivem com a simultaneidade de fatores de risco para doenças cardiovasculares. A maior prevalência observada tanto nas mulheres quanto nos homens foi da insuficiência de atividade física com a insuficiência no consumo de FLV, sendo de 46,4 e 28,1%, respectivamente. A prevalência observada dos quatro fatores simultâneos foi maior entre os homens (2,5%) em comparação às mulheres (0,3%). O sexo masculino apresentou 11,0% mais probabilidade de acumular fatores de risco comparado ao sexo feminino. E cada ano a mais de escolaridade representa 4,0% a menos de probabilidade de acumular fatores de risco cardiovasculares. Conclusões: As diferenças entre a simultaneidade de fatores de risco e aspectos sociodemográficos devem ser consideradas na abordagem do idoso tanto em nível individual quanto na construção de políticas públicas.