Combined effect of CO2and temperature on wheat powdery mildew development

The effect of simulated climate changes by applying different temperatures and CO₂ levels was investigated in the Blumeria graminis f. sp. tritici/wheat pathosystem. Healthy and inoculated plants were exposed in single phytotrons to six CO₂+temperature combinations: (1) 450 ppm CO₂/18–22°C (ambient CO₂ and low temperature), (2) 850 ppm CO₂/18–22°C (elevated CO₂ and low temperature), (3) 450 ppm CO₂/22–26°C (ambient CO₂ and medium temperature), (4) 850 ppm CO₂/22–26°C (elevated CO₂ and medium temperature), (5) 450 ppm CO₂/26–30°C (ambient CO₂ and high temperature), and (6) 850 ppm CO₂/26–30°C (elevated CO₂ and high temperature). Powdery mildew disease index, fungal DNA quantity, plant death incidence, plant expression of pathogenesis-related (PR) genes, plant growth parameters, carbohydrate and chlorophyll content were evaluated. Both CO₂ and temperature, and their interaction significantly influenced powdery mildew development. The most advantageous conditions for the progress of powdery mildew on wheat were low temperature and ambient CO₂. High temperatures inhibited pathogen growth independent of CO₂ conditions, and no typical powdery mildew symptoms were observed. Elevated CO₂ did not stimulate powdery mildew development, but was detrimental for plant vitality. Similar abundance of three PR transcripts was found, and the level of their expression was different between six phytotron conditions. Real time PCR quantification of Bgt was in line with the disease index results, but this technique succeeded to detect the pathogen also in asymptomatic plants. Overall, future global warming scenarios may limit the development of powdery mildew on wheat in Mediterranean area, unless the pathogen will adapt to higher temperatures

Thinness, overweight, and obesity in 6‐ to 9‐year‐old children from 36 countries: The World Health Organization European Childhood Obesity Surveillance Initiative - COSI 2015-2017

In 2015-2017, the fourth round of the World Health Organization (WHO) European Childhood Obesity Surveillance Initiative (COSI) was conducted in 36 countries. National representative samples of children aged 6–9 (203,323) were measured by trained staff, with similar equipment and using a standardized protocol. This paper assesses the children's body weight status and compares the burden of childhood overweight, obesity, and thinness in Northern, Eastern, and Southern Europe and Central Asia. The results show great geographic variability in height, weight, and body mass index. On average, the children of Northern Europe were the tallest, those of Southern Europe the heaviest, and the children living in Central Asia the lightest and the shortest. Overall, 28.7% of boys and 26.5% of girls were overweight (including obesity) and 2.5% and 1.9%, respectively, were thin according to the WHO definitions. The prevalence of obesity varied from 1.8% of boys and 1.1% of girls in Tajikistan to 21.5% and 19.2%, respectively, in Cyprus, and tended to be higher for boys than for girls. Levels of thinness, stunting, and underweight were relatively low, except in Eastern Europe (for thinness) and in Central Asia. Despite the efforts to halt it, unhealthy weight status is still an important problem in the WHO European Region.The authors gratefully acknowledge support from a grant from the Russian Government in the context of the WHO European Office for the Prevention and Control of NCDs. Data collection in the countries was made possible through funding from the following: Albania: WHO through the Joint Programme on Children, Food Security and Nutrition “Reducing Malnutrition in Children,” funded by the Millennium Development Goals Achievement Fund, and the Institute of Public Health; Austria: Federal Ministry of Social Affairs, Health, Care and Consumer Protection, Republic of Austria; Bulgaria: Ministry of Health, National Center of Public Health and Analyses, WHO Regional Office for Europe; Croatia: Ministry of Health, Croatian Institute of Public Health and WHO Regional Office for Europe; Czechia: Ministry of Health of the Czech Republic, grants AZV MZČR 17-31670 A and MZČR – RVO EÚ 00023761; Cyprus: not available; Denmark: Danish Ministry of Health; Estonia: Ministry of Social Affairs, Ministry of Education and Research (IUT 42-2), WHO Country Office, and National Institute for Health Development; Finland: Finnish Institute for Health and Welfare; France: Santé publique France, the French Agency for Public Health; Georgia: WHO; Greece: International Hellenic University and Hellenic Medical Association for Obesity; Hungary: WHO Country Office for Hungary; Ireland: Health Service Executive; Italy: Ministry of Health and Italian National Institute of Health; Kazakhstan: Ministry of Health of the Republic of Kazakhstan and WHO Country Office; Kyrgyzstan: World Health Organization; Latvia: Ministry of Health, Centre for Disease Prevention and Control; Lithuania: Science Foundation of Lithuanian University of Health Sciences and Lithuanian Science Council and WHO; Malta: Ministry of Health; Montenegro: WHO and Institute of Public Health of Montenegro; North Macedonia: funded by the Government of North Macedonia through National Annual Program of Public Health and implemented by the Institute of Public Health and Centers of Public Health in the country. WHO country office provided support for training and data management; Norway: Ministry of Health and Norwegian Institute of Public Health; Poland: National Health Programme, Ministry of Health; Portugal: Ministry of Health Institutions, the National Institute of Health, Directorate General of Health, Regional Health Directorates and the kind technical support from the Center for Studies and Research on Social Dynamics and Health (CEIDSS); Romania: Ministry of Health; Russian Federation: WHO; San Marino: Health Ministry, Educational Ministry, Social Security Institute and Health Authority; Serbia: World Health Organization (Ref. File 2015-540940); Slovakia: Biennial Collaborative Agreement between WHO Regional Office for Europe and Ministry of Health SR; Slovenia: Ministry of Education, Science and Sport of the Republic of Slovenia within the SLOfit surveillance system; Spain: Spanish Agency for Food Safety and Nutrition (AESAN); Sweden: Public Health Agency of Sweden; Tajikistan: WHO Country Office in Tajikistan and Ministry of Health and Social Protection; Turkmenistan: WHO Country Office in Turkmenistan and Ministry of Health; Turkey: Turkish Ministry of Health and World Bank.info:eu-repo/semantics/publishedVersio

Methodology and implementation of the WHO European Childhood Obesity Surveillance Initiative (COSI)

Establishment of the WHO European Childhood Obesity Surveillance Initiative (COSI)has resulted in a surveillance system which provides regular, reliable, timely, andaccurate data on children's weight status—through standardized measurement ofbodyweight and height—in the WHO European Region. Additional data on dietaryintake, physical activity, sedentary behavior, family background, and schoolenvironments are collected in several countries. In total, 45 countries in the EuropeanRegion have participated in COSI. The first five data collection rounds, between 2007and 2021, yielded measured anthropometric data on over 1.3 million children. In COSI,data are collected according to a common protocol, using standardized instrumentsand procedures. The systematic collection and analysis of these data enables inter-country comparisons and reveals differences in the prevalence of childhood thinness,overweight, normal weight, and obesity between and within populations. Furthermore,it facilitates investigation of the relationship between overweight, obesity, and poten-tial risk or protective factors and improves the understanding of the development ofoverweight and obesity in European primary-school children in order to supportappropriate and effective policy responses.The authors gratefully acknowledge support through a grant from the Russian Government in the context of the WHO European Office for the Prevention and Control of NCDs. The ministries of health of Austria, Croatia, Greece, Italy, Malta, Norway, and the Russian Federation provided financial support for the meetings at which the protocol, data collection procedures, and analyses were discussed. Data collection in countries was made possible through funding from the following: Albania: WHO through the Joint Programme on Children, Food Security and Nutrition “Reducing Malnutrition in Children,” funded by the Millennium Development Goals Achievement Fund, and the Institute of Public Health. Austria: Federal Ministry of Labor, Social Affairs, Health and Consumer Protection of Austria. Bulgaria: Ministry of Health, National Center of Public Health and Analyses, and WHO Regional Office for Europe. Bosnia and Herzegovina: WHO country office support for training and data management. Croatia: Ministry of Health, Croatian Institute of Public Health, and WHO Regional Office for Europe. Czechia: Ministry of Health of the Czech Republic, grant number 17-31670A and MZCR—RVO EU 00023761. Denmark: Danish Ministry of Health. Estonia: Ministry of Social Affairs, Ministry of Education and Research (IUT 42-2), WHO Country Office, and National Institute for Health Development. Finland: Finnish Institute for Health and Welfare. France: Santé publique France (the French Agency for Public Health). Georgia: WHO. Greece: International Hellenic University and Hellenic Medical Association for Obesity. Hungary: WHO Country Office for Hungary. Ireland: Health Service Executive. Italy: Ministry of Health. Kazakhstan: Ministry of Health of the Republic of Kazakhstan, WHO, and UNICEF. Kyrgyzstan: World Health Organization. Latvia: Ministry of Health and Centre for Disease Prevention and Control. Lithuania: Science Foundation of Lithuanian University of Health Sciences and Lithuanian Science Council and WHO. Malta: Ministry of Health. Montenegro: WHO and Institute of Public Health of Montenegro. North Macedonia: Government of North Macedonia through National Annual Program of Public Health and implemented by the Institute of Public Health and Centers of Public Health; WHO country office provides support for training and data management. Norway: the Norwegian Ministry of Health and Care Services, the Norwegian Directorate of Health, and the Norwegian Institute of Public Health. Poland: National Health Programme, Ministry of Health. Portugal: Ministry of Health Institutions, the National Institute of Health, Directorate General of Health, Regional Health Directorates, and the kind technical support from the Center for Studies and Research on Social Dynamics and Health (CEIDSS). Romania: Ministry of Health. Russian Federation: WHO. San Marino: Health Ministry, Educational Ministry, and Social Security Institute and Health Authority. Serbia: WHO and the WHO Country Office (2015-540940 and 2018/873491-0). Slovakia: Biennial Collaborative Agreement between WHO Regional Office for Europe and Ministry of Health SR. Slovenia: Ministry of Education, Science and Sport of the Republic of Slovenia within the SLOfit surveillance system. Spain: Spanish Agency for Food Safety and Nutrition. Sweden: Public Health Agency of Sweden. Tajikistan: WHO Country Office in Tajikistan and Ministry of Health and Social Protection. Turkmenistan: WHO Country Office in Turkmenistan and Ministry of Health. Turkey: Turkish Ministry of Health and World Bank.info:eu-repo/semantics/publishedVersio

Physical activity, screen time, and sleep duration of children aged 6-9 years in 25 countries:An analysis within the WHO european childhood obesity surveillance initiative (COSI) 2015-2017

BACKGROUND: Children are becoming less physically active as opportunities for safe active play, recreational activities, and active transport decrease. At the same time, sedentary screen-based activities both during school and leisure time are increasing. OBJECTIVES: This study aimed to evaluate physical activity (PA), screen time, and sleep duration of girls and boys aged 6-9 years in Europe using data from the WHO European Childhood Obesity Surveillance Initiative (COSI). METHOD: The fourth COSI data collection round was conducted in 2015-2017, using a standardized protocol that included a family form completed by parents with specific questions about their children's PA, screen time, and sleep duration. RESULTS: Nationally representative data from 25 countries was included and information on the PA behaviour, screen time, and sleep duration of 150,651 children was analysed. Pooled analysis showed that: 79.4% were actively playing for >1 h each day, 53.9% were not members of a sport or dancing club, 50.0% walked or cycled to school each day, 60.2% engaged in screen time for 1 h/day, 8.2-85.6% were not members of a sport or dancing club, 17.7-94.0% walked or cycled to school each day, 32.3-80.0% engaged in screen time for <2 h/day, and 50.0-95.8% slept for 9-11 h/night. CONCLUSIONS: The prevalence of engagement in PA and the achievement of healthy screen time and sleep duration are heterogenous across the region. Policymakers and other stakeholders, including school administrators and parents, should increase opportunities for young people to participate in daily PA as well as explore solutions to address excessive screen time and short sleep duration to improve the overall physical and mental health and well-being of children

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

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

Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: A systematic analysis for the Global Burden of Disease Study 2017

Background: The Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017) includes a comprehensive assessment of incidence, prevalence, and years lived with disability (YLDs) for 354 causes in 195 countries and territories from 1990 to 2017. Previous GBD studies have shown how the decline of mortality rates from 1990 to 2016 has led to an increase in life expectancy, an ageing global population, and an expansion of the non-fatal burden of disease and injury. These studies have also shown how a substantial portion of the world's population experiences non-fatal health loss with considerable heterogeneity among different causes, locations, ages, and sexes. Ongoing objectives of the GBD study include increasing the level of estimation detail, improving analytical strategies, and increasing the amount of high-quality data. Methods: We estimated incidence and prevalence for 354 diseases and injuries and 3484 sequelae. We used an updated and extensive body of literature studies, survey data, surveillance data, inpatient admission records, outpatient visit records, and health insurance claims, and additionally used results from cause of death models to inform estimates using a total of 68 781 data sources. Newly available clinical data from India, Iran, Japan, Jordan, Nepal, China, Brazil, Norway, and Italy were incorporated, as well as updated claims data from the USA and new claims data from Taiwan (province of China) and Singapore. We used DisMod-MR 2.1, a Bayesian meta-regression tool, as the main method of estimation, ensuring consistency between rates of incidence, prevalence, remission, and cause of death for each condition. YLDs were estimated as the product of a prevalence estimate and a disability weight for health states of each mutually exclusive sequela, adjusted for comorbidity. We updated the Socio-demographic Index (SDI), a summary development indicator of income per capita, years of schooling, and total fertility rate. Additionally, we calculated differences between male and female YLDs to identify divergent trends across sexes. GBD 2017 complies with the Guidelines for Accurate and Transparent Health Estimates Reporting. Findings: Globally, for females, the causes with the greatest age-standardised prevalence were oral disorders, headache disorders, and haemoglobinopathies and haemolytic anaemias in both 1990 and 2017. For males, the causes with the greatest age-standardised prevalence were oral disorders, headache disorders, and tuberculosis including latent tuberculosis infection in both 1990 and 2017. In terms of YLDs, low back pain, headache disorders, and dietary iron deficiency were the leading Level 3 causes of YLD counts in 1990, whereas low back pain, headache disorders, and depressive disorders were the leading causes in 2017 for both sexes combined. All-cause age-standardised YLD rates decreased by 3·9% (95% uncertainty interval [UI] 3·1-4·6) from 1990 to 2017; however, the all-age YLD rate increased by 7·2% (6·0-8·4) while the total sum of global YLDs increased from 562 million (421-723) to 853 million (642-1100). The increases for males and females were similar, with increases in all-age YLD rates of 7·9% (6·6-9·2) for males and 6·5% (5·4-7·7) for females. We found significant differences between males and females in terms of age-standardised prevalence estimates for multiple causes. The causes with the greatest relative differences between sexes in 2017 included substance use disorders (3018 cases [95% UI 2782-3252] per 100 000 in males vs 1400 [1279-1524] per 100 000 in females), transport injuries (3322 [3082-3583] vs 2336 [2154-2535]), and self-harm and interpersonal violence (3265 [2943-3630] vs 5643 [5057-6302]). Interpretation: Global all-cause age-standardised YLD rates have improved only slightly over a period spanning nearly three decades. However, the magnitude of the non-fatal disease burden has expanded globally, with increasing numbers of people who have a wide spectrum of conditions. A subset of conditions has remained globally pervasive since 1990, whereas other conditions have displayed more dynamic trends, with different ages, sexes, and geographies across the globe experiencing varying burdens and trends of health loss. This study emphasises how global improvements in premature mortality for select conditions have led to older populations with complex and potentially expensive diseases, yet also highlights global achievements in certain domains of disease and injury

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

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