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...

Objective: To investigate the effectiveness of active video games (AVGs) on obesity-related outcomes and physical activity levels in children and adolescents. Design: Systematic review with meta-analysis. Methods:Literature search was performed in five electronic databases and the main clinical trials registries. Randomized controlled trials investigating the effect of AVGs compared with no/minimal intervention on obesity-related outcomes (body mass index [BMI], body weight, body fat, and waist circumference) and physical activity levels of children and adolescents were eligible. Two independent reviewers extracted the data of each included study. PEDro scale was used to assess risk of bias and GRADE approach to evaluate overall quality of evidence. Pooled estimates were obtained using random effect models. Results: Twelve studies were considered eligible for this review. Included studies mostly reported outcome data at short-term (less or equal than three months) and intermediate-term follow-up (more than 3 months, but <12 months). AVGs were more effective than no/minimal intervention in reducing BMI/zBMI at short-term (SMD = −0.34; 95% CI: −0.62 to −0.05) and intermediate-term follow-up (SMD = −0.36; 95% CI: −0.01 to −0.71). In addition, AVGs were more effective in reducing body weight compared with no/minimal intervention at intermediate-term follow-up (SMD = −0.25; 95% CI: −0.46 to −0.04). Regarding physical activity levels, AVGs were not more effective compared with minimal intervention at short-term and intermediate-term follow-up. Conclusions: Our review identified that AVGs were better than minimal intervention in reducing BMI and body weight, but not for increasing physical activity in young people.

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. Funding Wellcome Trust.

Background: Elevated screen time has been associated with addictive behaviors, such as alcohol and sugar intake and smoking. Considering the substantial increase in screen time caused by social isolation policies, this study aimed to analyze the association of increased screen time in different devices during the COVID-19 pandemic with consumption and increased desire of alcohol, smoking, and sweetened foods in adults.Methods: A sample of 1,897 adults with a mean age of 37.9 (13.3) years was assessed by an online survey, being composed by 58% of women. Participants were asked whether screen time in television, cell phone, and computer increased during the pandemic, as well as how much time is spent in each device. Closed questions assessed the frequency of alcohol and sweetened food consumption, smoking, and an increased desire to drink and smoke during the pandemic. Educational level, age, sex, feeling of stress, anxiety, depression, and use of a screen device for physical activity were covariates. Binary logistic regression models considered adjustment for covariates and for mutual habits.Results: Increased television time was associated with increased desire to drink (OR = 1.46, 95% CI: 1.12; 1.89) and increased sweetened food consumption (OR = 1.53, 95% CI: 1.18; 1.99), while an increase in computer use was negatively associated with consumption of alcohol (OR = 0.68, 95% CI: 0.53; 0.86) and sweetened foods (OR = 0.78, 95% CI: 0.62; 0.98). Increased cell phone time was associated with increased sweetened food consumption during the pandemic (OR = 1.78, 95% CI: 1.18; 2.67). Participants with increased time in the three devices were less likely to consume sweetened foods for ≥5 days per week (OR = 0.63, 95% CI: 0.39; 0.99) but were twice as likely to have sweetened food consumption increased during pandemic (OR = 2.04, 95% CI: 1.07; 3.88).Conclusion: Increased screen time was differently associated with consumption and desire for alcohol and sweets according to screen devices. Increased time in television and cell phones need to be considered for further investigations of behavioral impairments caused by the pandemic.

BackgroundThe outbreak of novel coronavirus disease 2019 (COVID-19) has caused a global panic and public concern due to its mortality ratio and lack of treatments/vaccines. Reduced levels of physical activity have been reported during the outbreak, affecting the normal daily pattern.ObjectiveTo investigate (i) the relationship of physical activity level with sleep quality and (ii) the effects of reduction physical activity levels on sleep quality.MethodsA Google form was used to address personal information, COVID-19 personal care, physical activity, and mental health of 1,907 adult volunteers. Binary logistic regression was used to verify the association of physical activity parameters and sleep quality.ResultsInsufficient physical activity levels were a risk factor to have disturbed sleep pattern [OR: 1.28, 95% CI (1.01–1.62)]; however, when the BMI was added to the analysis, there was no more statistical difference [OR: 1.23, 95% CI (0.96–1.57)]. On the other hand, we found that the reduction of physical activity levels was associated with negative changes in sleep quality [OR: 1.73, 95% CI (1.37–2.18)], regardless all the confounders [OR: 1.30, 95% CI (1.01–1.68)], unless when feeling of depression was added in Model 6 [OR: 1.28, 95% CI (0.99–1.66)].ConclusionDisruption in daily physical activity routine, rather than physical activity level, negatively influences sleep quality during the COVID-19 quarantine.

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.

ObjectiveTo analyse the association between different domains of physical activity (PA) and health-related domains of health-related quality of life (HRQoL) in older adults, independent of confounding variables.DesignCross-sectional study.ParticipantsIn total, 400 individuals 60 years or above were randomly selected to participate in the study.Primary and secondary outcome measuresPA was assessed by a questionnaire in three different domains (work/occupational, sports/gym and leisure time) and total PA. The 36-Item Short Form Health Survey was used to evaluate HRQoL. The variables socioeconomic condition, marital status and presence of health professional-diagnosed comorbidities were self-reported.ResultsThe mean age of the sample was 71.5 (±8.4) years, of whom 58% (n=232) were female. Male older adults showed higher scores of PA in sports, leisure time and in total PA than female adults. Older adults who were more physically active in the work/occupational domain were associated with better scores in functional capacity (OR=1.73, 95% CI 1.02 to 2.93) and general health perception (OR=1.61, 95% CI 1.02 to 2.56). Those who presented a higher score in the sports/gym domain had better scores in functional capacity, even after adjustment for comorbidities (OR=1.72, 95% CI 1.01 to 2.96). Individuals with higher activity in leisure time were more likely to have better scores in functional capacity (OR=1.75, 95% CI 1.03 to 2.98), body pain (OR=1.74, 95% CI 1.09 to 2.78) and mental health (OR=1.67, 95% CI 1.03 to 2.69). Older adults who were more active in total PA were 77% more likely to have better scores in functional capacity (OR=1.77, 95% CI 1.04 to 3.02).ConclusionPhysically active older adults in the different domains of PA presented better HRQoL parameters, reinforcing the importance of studies analysing PA in different contexts and in countries with low and medium socioeconomic conditions.