19 research outputs found

    Two years of school-based intervention program could improve the physical fitness among Ecuadorian adolescents at health risk : subgroups analysis from a cluster-randomized trial

    Get PDF
    Background: Adolescents with overweight and poor physical fitness have an increased likelihood of developing cardiovascular diseases during adulthood. In Ecuador, a health promotion program improved the muscular strength and speed-agility, and reduced the decline of the moderate-to-vigorous physical activity of adolescents after 28 months. We performed a sub-group analysis to assess the differential effect of this intervention in overweight and low-fit adolescents. Methods: We performed a cluster-randomized pair matched trial in schools located in Cuenca–Ecuador. In total 20 schools (clusters) were pair matched, and 1440 adolescents of grade 8 and 9 (mean age of 12.3 and 13.3 years respectively) participated in the trial. For the purposes of the subgroup analysis, the adolescents were classified into groups according to their weight status (body mass index) and aerobic capacity (scores in the 20 m shuttle run and FITNESSGRAM standards) at baseline. Primary outcomes included physical fitness (vertical jump, speed shuttle run) and physical activity (proportion of students achieving over 60 min of moderate–to-vigorous physical activity/day). For these primary outcomes, we stratified analysis by weight (underweight, normal BMI and overweight/ obese) and fitness (fit and low fitness) groups. Mixed linear regression models were used to assess the intervention effect. Results: The prevalence of overweight/obesity, underweight and poor physical fitness was 20.3 %, 5.8 % and 84.8 % respectively. A higher intervention effect was observed for speed shuttle run in overweight (β = −1.85 s, P = 0.04) adolescents compared to underweight (β = −1.66 s, P = 0.5) or normal weight (β = −0.35 s, P = 0.6) peers. The intervention effect on vertical jump was higher in adolescents with poor physical fitness (β = 3.71 cm, P = 0.005) compared to their fit peers (β = 1.28 cm, P = 0.4). The proportion of students achieving over 60 min of moderate-to-vigorous physical activity/ day was not significantly different according to weight or fitness status. Conclusion: Comprehensive school-based interventions that aim to improve diet and physical activity could improve speed and strength aspects of physical fitness in low-fit and overweight/obese adolescents

    Repositioning of the global epicentre of non-optimal cholesterol

    Get PDF
    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, Finland, Greenland, Iceland, Norway, Sweden, Switzerland and Malta in 1980 to those in Asia and the Pacific, such as Tokelau, Malaysia, The Philippines and Thailand. In 2017, high non-HDL cholesterol was responsible for an estimated 3.9 million (95% credible interval 3.7 million-4.2 million) worldwide deaths, half of which occurred in east, southeast and south Asia. The global repositioning of lipid-related risk, with non-optimal cholesterol shifting from a distinct feature of high-income countries in northwestern Europe, north America and Australasia to one that affects countries in east and southeast Asia and Oceania should motivate the use of population-based policies and personal interventions to improve nutrition and enhance access to treatment throughout the world.Peer reviewe

    Height and body-mass index trajectories of school-aged children and adolescents from 1985 to 2019 in 200 countries and territories: a pooled analysis of 2181 population-based studies with 65 million participants

    Get PDF
    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/m2. 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, they had a much larger gain in height than they did in BMI. The unhealthiest changes—gaining too little height, too much weight for their height compared with children in other countries, or both—occurred in many countries in sub-Saharan Africa, New Zealand, and the USA for boys and girls; in Malaysia and some Pacific island nations for boys; and in Mexico for girls. Interpretation The height and BMI trajectories over age and time of school-aged children and adolescents are highly variable across countries, which indicates heterogeneous nutritional quality and lifelong health advantages and risks

    Rising rural body-mass index is the main driver of the global obesity epidemic in adults

    Get PDF
    Body-mass index (BMI) has increased steadily in most countries in parallel with a rise in the proportion of the population who live in cities(.)(1,2) This has led to a widely reported view that urbanization is one of the most important drivers of the global rise in obesity(3-6). Here we use 2,009 population-based studies, with measurements of height and weight in more than 112 million adults, to report national, regional and global trends in mean BMI segregated by place of residence (a rural or urban area) from 1985 to 2017. We show that, contrary to the dominant paradigm, more than 55% of the global rise in mean BMI from 1985 to 2017-and more than 80% in some low- and middle-income regions-was due to increases in BMI in rural areas. This large contribution stems from the fact that, with the exception of women in sub-Saharan Africa, BMI is increasing at the same rate or faster in rural areas than in cities in low- and middle-income regions. These trends have in turn resulted in a closing-and in some countries reversal-of the gap in BMI between urban and rural areas in low- and middle-income countries, especially for women. In high-income and industrialized countries, we noted a persistently higher rural BMI, especially for women. There is an urgent need for an integrated approach to rural nutrition that enhances financial and physical access to healthy foods, to avoid replacing the rural undernutrition disadvantage in poor countries with a more general malnutrition disadvantage that entails excessive consumption of low-quality calories.Peer reviewe

    Heterogeneous contributions of change in population distribution of body mass index to change in obesity and underweight NCD Risk Factor Collaboration (NCD-RisC)

    Get PDF
    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

    Factors affecting physical activity in ecuadorian adolescents: a focus group study

    No full text
    Background: Physical inactivity levels are increasingly prevalent among Ecuadorian adolescents. School-based interventions can be potentially effective in promoting physical activity but must be informed by cultural-specific factors. Methods: Twelve focus groups were carried out with adolescents (n = 80) in rural and urban Ecuador to identify factors influencing physical activity. In addition, 4 focus group discussions with parents (n = 32) and 4 with school staff (n = 32) were conducted. Individual and environmental factors were questioned using the ‘Attitude, Social influences and Self-efficacy’ model and the socioecological model as theoretical frameworks. Results: Factors influencing physical activity varied between groups. In the rural area farming and norms for girls impeded leisure-time physical activity, whereas urban groups emphasized traffic and crime concerns. Groups from a low socioeconomic status more frequently mentioned a fear of injuries and financial constraints. Several factors were common for all groups including preferences for sedentary activities, poor knowledge, time constraints and laziness, as well as a lack of opportunities at home and school, unsupportive parental rules and lack of role models. Conclusion: A conceptual framework including the identified factors emerged to inform the design of a cultural-sensitive school-based intervention to improve physical activity among Ecuadorian adolescents. Future interventions should be tailored to each setting

    Intervención escolar sobre salud comportamiento de los adolescentes ecuatorianos: efecto de un grupo controlado aleatorizado prueba en tiempo de pantalla

    Get PDF
    Antecedentes: las intervenciones efectivas sobre los comportamientos frente a la pantalla (televisión, videojuegos y tiempo en la computadora) son necesarias para prevenir las enfermedades no transmisibles en los países de ingresos bajos y medianos. El presente manuscrito investiga el efecto de una intervención de promoción de la salud basada en la escuela sobre el comportamiento frente a la pantalla entre adolescentes de 15 años. Informamos el efecto de la prueba en el tiempo de pantalla después de dos etapas de implementación. Métodos: Realizamos un ensayo emparejado con asignación al azar por grupos en escuelas urbanas de Cuenca-Ecuador. Participantes: adolescentes de octavo y noveno grado (edad media 12,8 ± 0,8 años, n = 1370, grupo de control n = 684) de 20 escuelas (grupo de control n = 10). La intervención incluyó un componente individual y ambiental adaptado a las necesidades locales, contexto y recursos. La primera etapa de intervención se centró en la dieta, la actividad física y el comportamiento frente a la pantalla, mientras la segunda etapa se centró únicamente en la dieta y la actividad física. Se evaluaron los comportamientos frente a la pantalla, resultado primario al inicio del estudio, después de la primera (18 meses) y la segunda etapa (28 meses). Se utilizaron modelos lineales mixtos para analizar la datos. Resultados: Después de la primera etapa (datos de n = 1224 adolescentes; grupo control n = 608), el grupo de intervención tuvo una menor aumento del tiempo de televisión en un día de la semana (β = −15,7 min; P = 0,003) y un día de fin de semana (β = −18,9 min; P = 0,005), en total tiempo frente a la pantalla en un día laborable (β = −25,9 min; P = 0,03) y en la proporción de adolescentes que no cumplieron con la recomendación de tiempo de pantalla (β = -4 puntos porcentuales; P = 0,01), en comparación con el grupo de control. Después de la segunda etapa (datos de n = 1078 adolescentes; grupo de control n = 531), el tiempo de televisión en un día laborable (β = 13,1 min; P = 0,02), y el tiempo total frente a la pantalla en un día de la semana (β = 21,4 min; P = 0,03) aumentó más en los adolescentes del grupo de intervención. No se informaron efectos adversos. Discusión y Conclusión: Una intervención escolar de componentes múltiples solo pudo mitigar el aumento de el tiempo de televisión de los adolescentes y el tiempo total frente a la pantalla después de la primera etapa de la intervención o, en otras palabras, cuando la intervención incluyó componentes o actividades específicas que se enfocaron en reducir el tiempo frente a la pantalla. Después de la segunda etapa de la intervención, que solo incluyó componentes y actividades relacionados con la mejora de la alimentación saludable y la actividad física y para no disminuir el tiempo frente a la pantalla, los adolescentes volvieron a aumentar su tiempo frente a la pantalla. Nuestros hallazgos podrían implicar que la reducción del tiempo frente a la pantalla solo es posible cuando la intervención se centra específicamente en reducir el tiempo frente a la pantalla.Background: Effective interventions on screen-time behaviours (television, video games and computer time) are needed to prevent non-communicable diseases in low- and middle-income countries. The present manuscript investigates the effect of a school-based health promotion intervention on screen-time behaviour among 12- to 15-year-old adolescents. We report the effect of the trial on screen-time after two stages of implementation. Methods: We performed a cluster-randomised pair matched trial in urban schools in Cuenca-Ecuador. Participants were adolescents of grade eight and nine (mean age 12.8 ± 0.8 years, n = 1370, control group n = 684) from 20 schools (control group n = 10). The intervention included an individual and environmental component tailored to the local context and resources. The first intervention stage focused on diet, physical activity and screen-time behaviour, while the second stage focused only on diet and physical activity. Screen-time behaviours, primary outcome, were assessed at baseline, after the first (18 months) and second stage (28 months). Mixed linear models were used to analyse the data. Results: After the first stage (data from n = 1224 adolescents; control group n = 608), the intervention group had a lower increase in TV-time on a week day (β = −15.7 min; P = 0.003) and weekend day (β = −18.9 min; P = 0.005), in total screen-time on a weekday (β = −25.9 min; P = 0.03) and in the proportion of adolescents that did not meet the screen-time recommendation (β = −4 percentage point; P = 0.01), compared to the control group. After the second stage (data from n = 1078 adolescents; control group n = 531), the TV-time on a weekday (β = 13.1 min; P = 0.02), and total screen-time on a weekday (β = 21.4 min; P = 0.03) increased more in adolescents from the intervention group. No adverse effects were reported. Discussion and Conclusion: A multicomponent school-based intervention was only able to mitigate the increase in adolescents’ television time and total screen-time after the first stage of the intervention or in other words, when the intervention included specific components or activities that focused on reducing screen-time. After the second stage of the intervention, which only included components and activities related to improve healthy diet and physical activity and not to decrease the screen-time, the adolescents increased their screen-time again. Our findings might imply that reducing screen-time is only possible when the intervention focuses specifically on reducing screen-time

    A school-based intervention improves physical fitness in Ecuadorian adolescents: a cluster-randomized controlled trial

    No full text
    Background: Effective lifestyle interventions are needed to prevent noncommunicable diseases in low- and middle-income countries. We analyzed the effects of a school-based health promotion intervention on physical fitness after 28 months and explored if the effect varied with important school characteristics. We also assessed effects on screen time, physical activity and BMI. Methods and results: We performed a cluster-randomized pair matched trial in schools in urban Ecuador. The intervention included an individual and environmental component tailored to the local context and resources. Primary outcomes were physical fitness (EUROFIT battery), screen time (questionnaires) and physical activity (accelerometers). Change in BMI was a secondary outcome. A total of 1440 grade 8 and 9 adolescents (intervention: n = 700, 48.6%) and 20 schools (intervention: n = 10, 50%) participated. Data of 1083 adolescents (intervention: n = 550, 50.8%) from 20 schools were analyzed. The intervention increased vertical jump (mean effect 2.5 cm; 95% CI 0.8-4.2; P = 0.01). Marginally insignificant, adolescents from the intervention group needed less time for speed shuttle run (intervention effect = −0.8 s, 95% CI −1.58-0.07; P = 0.05). The proportion of students achieving over 60 minutes of moderate-to-vigorous physical activity/day decreased over time with the change in proportion significantly less in the intervention schools (6 vs. 18 percentage points, P < 0.01). The intervention effect on speed shuttle run was significant in larger schools while the effect on vertical jump was larger in mixed gender school compared to small and female schools. The proportion of schools that met the recommendations for physical activity increased with 37% in intervention schools with half-day schedule compared to the controls in the pair. No significant effects were found on screen time and BMI. Measurement of physical activity in a subsample was a limitation. No adverse effects were reported. Conclusions: A school-based intervention with an individual and environment component can improve physical fitness and can minimize the decline in physical activity levels from childhood into adolescence in urban Ecuador

    A school-based intervention improved dietary intake outcomes and reduced waist circumference in adolescents: a cluster randomized controlled trial

    Get PDF
    Abstract Background In Ecuador, adolescents’ food intake does not comply with guidelines for a healthy diet. Together with abdominal obesity adolescent’s inadequate diets are risk factors for non-communicable diseases. We report the effectiveness of a school-based intervention on the dietary intake and waist circumference among Ecuadorian adolescents. Methods A pair-matched cluster randomized controlled trial including 1430 adolescents (12–14 years old) was conducted. The program aimed at improving the nutritional value of dietary intake, physical activity (primary outcomes), body mass index, waist circumference and blood pressure (secondary outcomes). This paper reports: (i) the effect on fruit and vegetable intake, added sugar intake, unhealthy snacking (consumption of unhealthy food items that are not in line with the dietary guidelines eaten during snack time; i.e. table sugar, sweets, salty snacks, fast food, soft drinks and packaged food), breakfast intake and waist circumference; and, (ii) dose and reach of the intervention. Dietary outcomes were estimated by means of two 24-h recall at baseline, after the first 17-months (stage one) and after the last 11-months (stage two) of implementation. Dose and reach were evaluated using field notes and attendance forms. Educational toolkits and healthy eating workshops with parents and food kiosks staff in the schools were implemented in two different stages. The overall effect was assessed using linear mixed models and regression spline mixed effect models were applied to evaluate the effect after each stage. Results Data from 1046 adolescents in 20 schools were analyzed. Participants from the intervention group consumed lower quantities of unhealthy snacks (−23.32 g; 95% CI: −45.25,-1.37) and less added sugar (−5.66 g; 95% CI: −9.63,-1.65) at the end of the trial. Daily fruit and vegetable intake decreased in both the intervention and control groups compared to baseline, albeit this decrease was 23.88 g (95% CI: 7.36, 40.40) lower in the intervention group. Waist circumference (−0.84 cm; 95% CI: −1.68, 0.28) was lower in the intervention group at the end of the program; the effect was mainly observed at stage one. Dose and reach were also higher at stage one. Conclusions The trial had positive effects on risk factors for non-communicable diseases, i.e. decreased consumption of unhealthy snacks. The program strategies must be implemented at the national level through collaboration between the academia and policy makers to assure impact at larger scale. Trial registration ClinicalTrial.gov-NCT01004367
    corecore