AMOUNT OF MEDICAL WASTE COLLECTED BY METROPOLITAN UNICIPALITIES: DATA ON 2004 AND FIRST SIX MONTHS 2005; METHODS OF COLLECTING, AMASSING AND DISPOSAL MEDICAL WASTE IN 81 PROVINCES

Tehlikeli bulaşıcı hastalıkların artması, tek kullanımlık malzemelerin kullanımını artırmıştır. Dünya Sağlık Örgütü tarafından 2000 yılında kontamine şırıngalarla 21 milyon Hepatit B (tüm yeni enfeksiyonların %32'si), 2 milyon Hepatit C (tüm yeni enfeksiyonların %40'ı), en az 260.000 HIV enfeksiyonu (tüm yeni enfeksiyonların %5'i) oluştuğu tahmin edilmiştir. Amaç: Büyükşehir Belediyeleri tarafından toplanan 2003-2004 yılları ve 2005 yılı ilk altı ayı tıbbi atık miktarlarının bulunması, 81 ilin tıbbi atık toplama, biriktirme ve imha yöntemlerinin tespit edilmesi ile bu konuda yapılacak çalışmalara katkı sağlanması amaçlanmıştır. Yöntem: Büyükşehir belediyeleri ilgili dairelerinden 2003, 2004 yılları ve 2005 yılı ilk altı ayı tıbbi atık miktarları, Temel Sağlik Hizmetleri Genel Müdürlüğü (TSHGM) Çevre Sağlığı Açık Alan biriminden 81 ilin 2004 yılı toplama, biriktirme ve imha yöntemleri verileri alınmıştır. Bulgular: Yıllık tıbbi atık miktarı 82.803 ton tahmin edilmiştir. Çalışmada yer alan şehirlerde yatak başına tıbbi atık miktarı 0,36 ile 1,80 kg; kişi başına yıllık tıbbi atık miktarı 0,42 ile 1,86 kg arasında değişmektedir. Tıbbi atık toplama yöntemlerine bakıldığında 44 (% 54,3) ilde belediye çöp aracı ile (evsel atıklardan ayrı), 27 ilde (%33,3) özel tıbbi atık taşıma aracı ile toplanmaktadır. 33 il (%40,7) belediyesi çöp alanında, 32'si (%39,5) şehir dışındaki çöp alanında biriktirmekte, sadece 5'i (%6,2) özel tıbbi atık toplama alanında, 2'si (%2,5) özel şirket ve özel yakma tesisinde biriktirilmektedir. 40'ı (%49,4) gömme (12'si kireçlenerek), 22'si (%27,2) yakma methodu ile imha edilmektedir. Sonuç: Tıbbi atıkların imhası güç ve maliyetlidir. Üretim aşamasında azaltılması, üretim miktarlarının ölçülmesi önemlidir. Kesin değerlerin bilinebilmesi için sağlık kuruluşları ve belediyelerin tıbbi atıkları ayrı ayrı toplamaları gerekmektedir. Bu konuda yayınlanan yönetmelik ve genelgelerin ilgili kurumlar tarafından takiplerinin yapılması önem taşımaktadır. The increase in the prevalence of dangerous and communicable diseases gave rise to the use of disposable medical supplies all over the world. According to the estimations made by the WHO, 21 million cases of Hepatitis B (32 % of all infections) , 2 million cases of Hepatitis C (40 % of all infections), and minimum 260.000 cases of HIV infection (5 % of all new-borne infections) occurred due to syringes / injections. Objectives: To identify the amount of medical waste collected by the Metropolitan Municipalities in 2003-2004 term and the first half of 2005; to contribute to contribute to the future studies by identifying the medical waste collecting, storing and destroying methods used in 81 provinces across Turkey. Methods: Data on the amount of medical waste materials in 2003, 2004 and the first half of 2005 was received from the Metropolitan Municipalities and data on collecting, storing and destroying methods in 81 provinces was received from the Environmental Health Open Space Unit of Directorate General of Primary Health Care Services. Results: The estimated amount of medical waste materials per year was 82.803 tons. In the provinces subject to the above-mentioned study, the amount per hospital bed was 0.36 - 1.80 kg, the amount per person was 0.42 - 1.86 kg. As for the methods of collecting medical waste, in 44 provinces (54.3 %) medical was collected by the Municipality's dustcarts (apart from the household waste products) and in 27 provinces (33.3 %) with specially designed medical waste carts. In 33 of 81 provinces across Turkey (40.7 %) waste products were stored in the Municipality's dust field and in 32 (39.5 %) in a dust site far from the city center whereas just in 5 (6.2 %) of them it was kept in specially built medical waste collecting facilities and 2 (2.5 %) in private company-owned special burning centers. In 40 provinces medical waste materials (49.4 %) was preferably destroyed by burying (in provinces they are limed before burying) and in 22 (27.2 %) burning . Conclusion: Medical waste production should be reduced. Disposal is difficult and costly. Production amount should be known. Health care facilities and municipalities are supposed to collect medical waste materials separately in order to identify the exact amount. To this end, it is essential for relevant public agencies and authorities to follow-up and comply with the regulations and circulars issued

Mobilizing governments and society to combat obesity: Reflections on how data from the WHO European Childhood Obesity Surveillance Initiative are helping to drive policy progress

To meet the need for regular and reliable data on the prevalence of overweight andobesity among children in Europe, the World Health Organization (WHO) EuropeanChildhood Obesity Surveillance Initiative (COSI) was established in 2007. Theresulting robust surveillance system has improved understanding of the public healthchallenge of childhood overweight and obesity in the WHO European Region. For the past decade, data from COSI have helped to inform and drive policy action onnutrition and physical activity in the region. This paper describes illustrative examplesof how COSI data have fed into national and international policy, but the real scopeof COSI's impact is likely to be much broader. In some countries, there are signs thatpolicy responses to COSI data have helped halt the rise in childhood obesity. As thecountries of the WHO European Region commit to pursuing United Action for BetterHealth in Europe in WHO's new European Programme of Work, COSI provides anexcellent example of such united action in practice. Further collaborative action willbe key to tackling this major public health challenge which affects children through-out the regionThe 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 the countries featured in this paper was made possible through funding from: 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; Georgia: WHO; Ireland: Health Service Executive; Italy: Ministry of Health and Italian National Institute of Health; Latvia: Centre for Disease Prevention and Control, Ministry of Health, Latvia; Malta: Ministry of Health; 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. WHO country office provides support for training and data management; 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); Turkey: Turkish Ministry of Health and World Bank.info:eu-repo/semantics/publishedVersio

Parental Perceptions of Children’s Weight Status in 22 Countries: The WHO European Childhood Obesity Surveillance Initiative: COSI 2015/2017

Introduction: Parents can act as important agents of change and support for healthy childhood growth and development. Studies have found that parents may not be able to accurately perceive their child’s weight status. The purpose of this study was to measure parental perceptions of their child’s weight status and to identify predictors of potential parental misperceptions. Methods: We used data from the World Health Organization (WHO) European Childhood Obesity Surveillance Initiative and 22 countries. Parents were asked to identify their perceptions of their children’s weight status as “underweight,” “normal weight,” “a little overweight,” or “extremely overweight.” We categorized children’s (6–9 years; n = 124,296) body mass index (BMI) as BMI-for-age Z-scores based on the 2007 WHO-recommended growth references. For each country included in the analysis and pooled estimates (country level), we calculated the distribution of children according to the WHO weight status classification, distribution by parental perception of child’s weight status, percentages of accurate, overestimating, or underestimating perceptions, misclassification levels, and predictors of parental misperceptions using a multilevel logistic regression analysis that included only children with overweight (including obesity). Statistical analyses were performed using Stata version 15 1. Results: Overall, 64.1% of parents categorized their child’s weight status accurately relative to the WHO growth charts. However, parents were more likely to underestimate their child’s weight if the child had overweight (82.3%) or obesity (93.8%). Parents were more likely to underestimate their child’s weight if the child was male (adjusted OR [adjOR]: 1.41; 95% confidence intervals [CI]: 1.28–1.55); the parent had a lower educational level (adjOR: 1.41; 95% CI: 1.26–1.57); the father was asked rather than the mother (adjOR: 1.14; 95% CI: 0.98–1.33); and the family lived in a rural area (adjOR: 1.10; 95% CI: 0.99–1.24). Overall, parents’ BMI was not strongly associated with the underestimation of children’s weight status, but there was a stronger association in some countries. Discussion/Conclusion: Our study supplements the current literature on factors that influence parental perceptions of their child’s weight status. Public health interventions aimed at promoting healthy childhood growth and development should consider parents’ knowledge and perceptions, as well as the sociocultural contexts in which children and families live.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 by: Albania: World Health Organization 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; Bulgaria: Ministry of Health, National Center of Public Health and Analyses, World Health Organization Regional Office for Europe; Croatia: Ministry of Health, Croatian Institute of Public Health and World Health Organization Regional Office for Europe; Czechia: Grants AZV MZČR 17-31670 A and MZČR – RVO EÚ 00023761; Denmark: Danish Ministry of Health; France: French Public Health Agency; Georgia: World Health Organization; Ireland: Health Service Executive; Italy: Ministry of Health; Istituto Superiore di sanità (National Institute of Health); Kazakhstan: Ministry of Health of the Republic of Kazakhstan and World Health Organization Country Office; Latvia: n/a; Lithuania: Science Foundation of Lithuanian University of Health Sciences and Lithuanian Science Council and World Health Organization; Malta: Ministry of Health; Montenegro: World Health Organization and Institute of Public Health of Montenegro; 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 of Center for Studies and Research on Social Dynamics and Health (CEIDSS); Romania: Ministry of Health; Russia (Moscow): n/a; San Marino: Health Ministry; Educational Ministry; Social Security Institute; the Health Authority; Spain: Spanish Agency for Food Safety and Nutrition (AESAN); Tajikistan: World Health Organization Country Office in Tajikistan and Ministry of Health and Social Protection; and Turkmenistan: World Health Organization Country Office in Turkmenistan and Ministry of Health. The authors alone are responsible for the views expressed in this article and they do not necessarily represent the views, decisions, or policies of the institutions with which they are affiliated.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

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

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

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

Contrasting cardiovascular mortality trends in Eastern Mediterranean populations: contributions from risk factor changes and treatments

Background Middle income countries are facing an epidemic of non-communicable diseases, especially coronary heart disease (CHD). We used a validated CHD mortality model (IMPACT) to explain recent trends in Tunisia, Syria, the occupied Palestinian territory (oPt) and Turkey. Methods Data on populations, mortality, patient numbers, treatments and risk factor trends from national and local surveys in each country were collated over two time points (1995–97; 2006–09); integrated and analysed using the IMPACT model. Results Risk factor trends: Smoking prevalence was high in men, persisting in Syria but decreasing in Tunisia, oPt and Turkey. BMI rose by 1–2 kg/m2 and diabetes prevalence increased by 40%–50%. Mean systolic blood pressure and cholesterol levels increased in Tunisia and Syria. Mortality trends: Age-standardised CHD mortality rates rose by 20% in Tunisia and 62% in Syria. Much of this increase (79% and 72% respectively) was attributed to adverse trends in major risk factors, occurring despite some improvements in treatment uptake. CHD mortality rates fell by 17% in oPt and by 25% in Turkey, with risk factor changes accounting for around 46% and 30% of this reduction respectively. Increased uptake of community treatments (drug treatments for chronic angina, heart failure, hypertension and secondary prevention after a cardiac event) accounted for most of the remainder. Discussion CHD death rates are rising in Tunisia and Syria, whilst oPt and Turkey demonstrate clear falls, reflecting improvements in major risk factors with contributions from medical treatments. However, smoking prevalence remains very high in men; obesity and diabetes levels are rising dramatically

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