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
Research policy observers are increasingly concerned about the potential impact of current academic working conditions on mental health, particularly in PhD students. The aim of the current study is threefold. First, we assess the prevalence of mental health problems in a representative sample of PhD students in Flanders, Belgium (N=3659). Second, we compare PhD students to three other samples: (1) highly educated in the general population (N=769); (2) highly educated employees (N=592); and (3) higher education students (N=333). Third, we assess those organizational factors relating to the role of PhD students that predict mental health status. Results based on 12 mental health symptoms (GHQ-12) showed that 32% of PhD students are at risk of having or developing a common psychiatric disorder, especially depression. This estimate was significantly higher than those obtained in the comparison groups. Organizational policies were significantly associated with the prevalence of mental health problems. Especially work-family interface, job demands and job control, the supervisor’s leadership style, team decision-making culture, and perception of a career outside academia are linked to mental health problems.
BackgroundThe Belgian Health Interview Survey (BHIS) is organised every 4 to 5 years and collects health information from around 10,000 individuals in a face-to-face setting. This manuscript describes the methodological choices made in the sampling design, the outcomes of the previous surveys in terms of participation rates and achieved targets and the factors to be accounted for in data-analysis.MethodsThe BHIS targets all persons residing in Belgium with no restrictions on age or nationality. Trimestral copies of the National Population Registry are used as the sampling frame. To select the respondents, a multistage sampling design is applied involving a geographical stratification, a selection of clusters, a selection of households within each cluster and a selection of respondents within each household. Using matched substitution of non-participating households assures the realisation of the predefined net-sample.ResultsFor each BHIS the required number of participants is achieved, including the years when an oversampling of provinces and of the elderly occurred. The sampling design guarantees that the survey is implemented in large cities as well as in small municipalities. A growing problem is related to the sampling frame: it is increasingly subject of deterioration, especially in the Brussels-Capital Region.ConclusionsThe methodological approach developed for the first BHIS proves to be accurate and was kept nearly unchanged throughout the following surveys. Fieldwork substitution contributes to a considerable extent to the success of the fieldwork but yields in higher percentages of non-participation. The sampling design requires special attention when analysing the data: the unequal selection probability, e.g. due to the non-proportional stratification at the regional level, necessitates the use of weights. The BHIS is progressively embedded in the European Health Survey, a process that doesn’t jeopardise the comparability of the Belgian results throughout time.
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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