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

BackgroundLittle is known about the epidemiology and health related quality of life (HRQoL) of the new DSM-5 diagnoses, Binge Eating Disorder (BED) and Avoidant/Restrictive Food Intake Disorder (ARFID) in the Australian population. We aimed to investigate the prevalance and burden of these disorders.MethodsWe conducted two sequential population-based surveys including individuals aged over 15 years who were interviewed in 2014 (n = 2732) and 2015 (n =3005). Demographic information and diagnostic features of DSM-5 eating disorders were asked including the occurrence of regular (at least weekly over the past 3 months) objective binge eating with levels of distress, extreme dietary restriction/fasting for weight/shape control, purging behaviors, overvaluation of shape and/or weight, and the presence of an avoidant/restrictive food intake without overvaluation of shape and/or weight. In 2014 functional impact or role performance was measured with the ‘days out of role’ question and in 2015, Health Related Quality of Life (HRQoL) was assessed with the Short Form −12 item questionnaire (SF-12v1).ResultsThe 2014 and 2015 3-month prevalence of eating disorders were: anorexia nervosa-broad 0.4% (95% CI 0.2–0.7) and 0.5% (0.3–0.9); bulimia nervosa 1.1% (0.7–1.5) and 1.2% (0.9–1.7); ARFID 0.3% (0.1–0.5) and 0.3% (0.2–0.6). The 2015 3-month prevalence rates were: BED-broad 1.5% (1.1–2.0); Other Specified Feeding or Eating Disorder (OSFED) 3.2 (2.6–3.9); and Unspecified Feeding or Eating Disorder (UFED) 10.4% (0.9–11.5). Most people with OSFED had atypical anorexia nervosa and majority with UFED were characterised by having recurrent binge eating without marked distress. Eating disorders were represented throughout sociodemographic groups and those with bulimia nervosa and BED-broad had mean weight (BMI, kg/m2) in the obese range. Mental HRQoL was poor in all eating disorder groups but particularly poor for those with BED-broad and ARFID. Individuals with bulimia nervosa, BED-broad and OSFED-Purging Disorder also had poor physical HRQoL. ARFID and bulimia nervosa groups had lower role performance than those without an eating disorder.ConclusionsWhilst full spectrum eating disorders, including ARFID, were less common than OSFED or UFED, they were associated with poor mental HRQoL and significant functional impairment. The present study supports the movement of eating disorders in to broader socio demographic groups including men, socio-economic disadvantaged groups and those with obesity.

BackgroundIn this paper, the basic elements related to the selection of participants for a health research are discussed. Sample representativeness, sample frame, types of sampling, as well as the impact that non-respondents may have on results of a study are described. The whole discussion is supported by practical examples to facilitate the reader's understanding.ObjectiveTo introduce readers to issues related to sampling.

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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The importance of estimating sample sizes is rarely understood by researchers, when planning a study. This paper aims to highlight the centrality of sample size estimations in health research. Examples that help in understanding the basic concepts involved in their calculation are presented. The scenarios covered are based more on the epidemiological reasoning and less on mathematical formulae. Proper calculation of the number of participants in a study diminishes the likelihood of errors, which are often associated with adverse consequences in terms of economic, ethical and health aspects.

Resumo A integração entre a agricultura familiar e a alimentação escolar têm o potencial de melhorar a variedade dos cardápios escolares aproximando produção e consumo de alimentos. Este estudo caracterizou os municípios brasileiros quanto à compra de alimentos da agricultura familiar pelo Programa Nacional de Alimentação Escolar. Trata-se de estudo transversal realizado por meio de questionário eletrônico enviado aos 5.565 municípios do país. Participaram da pesquisa 93,2% dos municípios (n = 5.184). Destes, 78,5% adquiriram alimentos da agricultura familiar, destacando-se a região Sul, com a maior frequência de municípios realizando a compra (95,5%), e a região Centro-Oeste com a menor (67,9%). Os municípios de grande porte, com gestão da alimentação escolar do tipo mista, descentralizada ou terceirizada e sem nutricionista como responsável técnico, apresentaram menor frequência de compra de alimentos da agricultura familiar. Conclui-se que, apesar da ampla efetivação da aquisição de alimentos da agricultura familiar pelo programa em todo país, 50% dos municípios não investiram o mínimo exigido em lei, demandando ações educativas e de assistência técnica direcionadas para o cumprimento da legislação, em especial nos estados e regiões que apresentaram maiores dificuldades.

Repositioning of the global epicentre of non-optimal cholesterol NCD Risk Factor Collaboration (NCD-RisC)* 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,