Education And Prevalence Of Overweight And Obesity Among .
Mengesha Kassie et al. BMC Public Health(2020) ESEARCH ARTICLEOpen AccessEducation and prevalence of overweightand obesity among reproductive age groupwomen in Ethiopia: analysis of the 2016Ethiopian demographic and health surveydataAyelign Mengesha Kassie* , Biruk Beletew Abate and Mesfin Wudu KassawAbstractBackground: Globally, the prevalence of overweight and obesity is escalating, particularly among women andwealthier people. In many developed countries, overweight and obesity are more prevalent in persons with lowersocioeconomic status. In contrast, studies in developing countries have reported a higher prevalence rate ofoverweight and obesity among women with higher educational status. Hence, this study aimed to assess theassociation between education and the prevalence of overweight and obesity among reproductive age groupwomen in Ethiopia.Methods: This cross-sectional study was done based on the 2016 Ethiopian demographic and health survey (EDHS)data. From the total 15,683 women participants of the 2016 EDHS, 2848 reproductive age group women aged15–49 years old who had a complete response to all variables of interest were selected and retained for analysis.Data were analyzed using SPSS version 20 software program. Both descriptive and logistic regression models wereused for analysis.Results: The prevalence of overweight and obesity among the study participants was 11.5 and 3.4% respectively.The combined prevalence of overweight and obesity was 14.9%. From the total participants who are overweightand, or obese, majority, 83.3% were urban dwellers and the remaining 16.7% were rural dwellers. Education waspositively associated with overweight and obesity among women. Besides, increased age, region, living in urbanareas, being in rich quintile, increased frequency of watching television, and frequency of using internet weresignificantly associated with the odds of being overweight and obese among reproductive age group women inEthiopia.Conclusions: The prevalence of overweight and obesity among reproductive age group women in Ethiopia isincreasing compared to previous studies. Education was found to be a risk factor for overweight and obesityamong women. Hence, context based interventions on the prevention and control methods of overweight andobesity are required.Keywords: Education, Ethiopia, Obesity, Overweight, Reproductive age group women* Correspondence: ayelignm@wldu.gov.et; ayelignmengesha59@gmail.comCollege of Health Sciences, Department of Nursing, Woldia University,Woldia, Ethiopia The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License,which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you giveappropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate ifchanges were made. The images or other third party material in this article are included in the article's Creative Commonslicence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commonslicence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtainpermission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.The Creative Commons Public Domain Dedication waiver ) applies to thedata made available in this article, unless otherwise stated in a credit line to the data.
Mengesha Kassie et al. BMC Public Health(2020) 20:1189BackgroundOver nutrition is becoming the major global publichealth problem. It includes, overweight, obesity and dietrelated non-communicable diseases (NCDs) [1]. Overweight and obesity refers an excessive fat accumulationin body tissues [2]. Obesity is an illness and necessitatesimmediate reversal to prevent early and untimely deathamong patients [2, 3].Globally, the prevalence of overweight and obesity isescalating, particularly among women and wealthierpeople [4]. Overweight and obesity in women increasesthe risk of diabetes, hypertension, caesarean delivery,postpartum hemorrhage, and high birth weight baby, infant overweight and obesity [1, 5].The disease burden related to high BMI has increased starting from 1990. Since 1980, the prevalenceof obesity has doubled in more than 70 countries andhas continuously increased in most other countries.In 2015 alone, more than 603 million adults wereobese worldwide [6].In 2013, the prevalence of overweight and obesityamong women was 37% worldwide which is slightlyhigher than the men (36%) [7]. According to a study ontrends in obesity among adults in the United States, theprevalence of obesity alone in 2013–2014 was 40.4%among women which is significantly higher than themen’s prevalence rate (35%) [8].Even though largely preventable, overweight and obesity are liked to more deaths than underweight [9]. In2015, high BMI had caused an estimated 4 milliondeaths globally, and nearly 40% of these deaths occurredin persons who were not obese but high BMI. More thantwo thirds of deaths related to high BMI were due tocardiovascular diseases [6, 10].Latest WHO reports also show that overweight andobesity are becoming the leading causes of death worldwide [1, 9]. Overweight and obesity affects all age groupsof people both in developed and developing countriesregardless of their socioeconomic status [1, 11].According to a study on the global trends of overweight and obesity, 26.9% of adults in Africa are overweight and obese. It has also revealed that obesity wastwice more common among women than men [12].Over nutrition costs the world billions of dollars a yearin lost opportunities for economic growth and lost investments in human capital associated with increasedpreventable morbidity and mortality rates in both children and adults [1, 13].Ethiopia is not different. According to the 2016 EDHSreport 22% of reproductive age group women wereunderweight, an 8% drop from 30% in the 2000 EDHS.However, the proportion of overweight and obesityamong women has increased from 3% in 2000 to 8% in2016 [14].Page 2 of 11Overweight and obesity are associated with many factors including excessive consumption of alcohol,cigarette smoking and sedentary life style habits [15, 16].Overweight and obesity are also linked with lower socioeconomic status [17, 18].In many developed countries, women with a lowlevel of educational status are two to three timesmore likely to be overweight and obese than thosewith a higher level of education [19]. This might bedue to the failure of women to recognize the risksand the consequences of being overweight and obeseas fatness is considered a symbol of beauty and prosperity in many societies [20, 21].Therefore, education is the major tool to promotehealthy behaviors and solve these problems [22, 23].However, there are contrasting studies in developingcountries which have reported a higher prevalence rateof overweight and obesity among women with highereducational status than their counter parts [24, 25].Hence, this study aimed to assess the association between educational status and the prevalence of overweight and obesity among reproductive age groupwomen in Ethiopia.MethodsStudy design and populationThis cross-sectional study was done based on the 2016EDHS data. The survey included a nationally representative sample of women (aged 15–49 years) and men (aged15–59 years) from the nine regions and two administrative cities of the country [14]. However, the currentstudy involved non-pregnant reproductive age groupwomen only because, unlike men, overweight andobesity in women are more prevalent and are associatedwith multiple problems including increased risk of diabetes, hypertension, caesarean delivery, postpartumhemorrhage, high birth weight babies, and infant overweight and obesity [1]. Pregnant women were excluded,because, pregnancy nullifies the values of BMI and dataabout BMI was not collected among pregnant, and thosewomen who have had a birth in the 2 months before thesurvey in the 2016 EDHS [14].Sampling techniqueIn the 2016 EDHS, a two stage stratified sampling technique was employed to select representative samples forthe country as whole. The regions in the country werestratified into urban and rural areas. Then, samples ofenumeration areas (EAs) were selected in each stratumin two stages. In the first stage, 645 EAs were selectedwith probability proportional to the EA size. The EA sizeis the number of residential households in the EA as determined in the 2007 Ethiopian Population and HousingCensus. A household listing operation was implemented
Mengesha Kassie et al. BMC Public Health(2020) 20:1189in the selected EAs, and the resulting lists of householdsserved as the sampling frame for the selection of households in the second stage. In the second stage, a fixednumber of 28 households per cluster were selected withan equal probability systematic selection from the newlycreated household listing. All women aged 15–49 yearswho were usual members of the selected households orwho spent the night before the survey in the selectedhouseholds were eligible for the female survey [14]. Forthe purpose of this study, from the total, 15,683 womenparticipants of the 2016 EDHS, a sub-sample of 2848 reproductive age group women aged 15–49 years who hada complete response to all variables of interest were selected and retained for analysis after excluding womenwho were pregnant.Data collectionIn the 2016 EDHS, a standardized and validated questionnaire were adapted from the DHS Program’s standard Demographic and Health Survey questionnaires in away to reflect the population and health issues relevantto Ethiopia. The survey data were collected from January18 to June 27, 2016 by trained field workers [14]. For thepurpose of the current study, the women’s data from the2016 EDHS was utilized.Variables and operational definitionsIn addition to education, several important covariateslike, respondent’s age, and wealth index were analyzeddepending on their availability in the 2016 EDHSdata (Fig 1). Educational level of participants was categorized as; no education, primary, secondary, and highereducation. Additional details of independent variablesare available somewhere else [28]. The dependent variables of interest were overweight and obesity amongnon-pregnant women aged 15–49 years. These outcomevariables of interest were categorized as follows based onthe WHO Classification of body mass index; overweightif the BMI is 25.0–29.9 kg/m2 and obese if it is 30 kg/m2[2]. The combined prevalence of overweight and obesitywas determined by merging the two outcomes together.Page 3 of 11presented in relation to different socio-demographiccharacteristics. Binary logistic regression analysis wascarried out to see the association between overweightand obesity and each predictor variable separately topresent a crude or unadjusted analysis. Then, a multivariable logistic regression analysis was done to examinethe association between educational status of women,other covariates and overweight and, or obesity. Ap-value of less than 0.05 was used to declare a statistically significant association between the independentand the outcome variables.ResultBaseline characteristics of respondentsIn this study 2848 participants of the 2016 EDHS wereincluded. More than half, 53.2% of the participants wereOrthodox Christianity followers, 23.7% Muslims, 21.9%Protestants, 0.7% Catholics and the remaining 0.5% weretraditional and other religion followers. Regarding toeducational status of the study participants, 43.2% hadno education and the remaining 56.8% had completedup to higher levels of education. Majority, 63% of theparticipants were rural dwellers. Furthermore, 59.6% ofthe participants were in the first (rich) wealth indexquintile, 15.9% were in the second (middle) quintile and24.5% were in the third (poor) quintile (Table 1).The prevalence of overweight and obesity among reproductive age group women was 11.5 and 3.4% respectively and, the combined prevalence of overweight andobesity was 14.9% (Table 2).The prevalence of overweight and obesity was higher,37, 26.7 and 16.2% respectively among women with ahigher, secondary and primary level of education compared to 5.8% among women with no education. Besides,the prevalence of overweight and obesity was 19.8 and16.2% among women with age group of 35 years and25–34 years respectively compared to 6.6% in womenwith age group of 15–24 years. Similarly, the prevalenceof overweight and obesity was also higher, 23.7% inwomen with rich wealth quintile compared to 1.4% inwomen with poor wealth quintile (Table 3).Statistical analysisData analysis started with a summary of the sociodemographic characteristics, and other important factorswere included in assessment of overweight and obesityamong women using frequency distribution analysis.Weighting was applied during preparation of analyticalsample and in all percentage calculations so that tomake the results representative for reproductive agegroup women in Ethiopia. Data were analyzed usingSPSS version 20 software program. Bivariate analysisusing Pearson’s chi-squared test was used to assess thefrequency distribution of the main outcomes and isRegression analysis of associated factors with overweightand obesityIn this study bivariate logistic regression analysis wasperformed and, variables which have a p-value of lessthan 0.25 were fitted into the multivariable logistic regression analysis model. In the multivariable logistic regression analysis, educational status was significantlyassociated the odds of being overweight and obeseamong women. The odds of being overweight and obesewas around 2 times higher among those who had higher(AOR 2.11, 95% CI, 1.18, 3.76), secondary (AOR 1.90,
Mengesha Kassie et al. BMC Public Health(2020) 20:1189Page 4 of 11Table 1 Sociodemographic characteristics of reproductive age group women in Ethiopia, EDHS 2016, (N 2848)CharacteristicsResponseFrequencyEducational status of respondentsNo education123143.2Primary99034.8Respondents ageReligionRegion of respondentsArea of residenceEmployment statusHusband/partners educational statusRespondents wealth indexPercentageSecondary36512.8Higher2629.215–24 years old72825.625-34 years old130645.9 35 years 2077.3SNNPR48016.9Gambella1926.7Harari1465.1Addis Ababa35412.4Dire Dawa1585.5Urban105437.0Rural179463.0Not employed124343.6Employed160556.4No her39513.9Poor69824.5Medium45315.9Rich169759.695% CI, 1.16, 3.12) and primary education (AOR 1.91,95% CI, 1.30, 2.79) than those who had no education.Besides, respondent’s age, region, residence, wealthindex, frequency of watching television, and frequency ofusing internet were positively associated with the oddsof overweight and obesity among women. The odds ofoverweight and obesity among respondents aged 25–34years and 35 years was more than 3 (AOR 3.03, 95%CI, 2.06, 4.48) and 6.5 (AOR 6.51, 95% CI, 4.08, 10.37)times higher respectively than those aged 15–24 yearsold. The odds of being overweight and obese amongrespondents living in Oromia, Somali, Benishangul, Harari, Addis Ababa, and Dire Dawa was higher than thosewho live in Tigray region.Similarly, the odds of those who live in urban areaswas more than 3 folds higher (AOR 3.11, 95% CI, 2.02,4.80) than those who live in rural areas. Wealth indexwas also significantly associated with overweight andobesity. The odds of being overweight and obese amongrespondents of rich wealth quintile class was around 5times higher (AOR 4.82, 95% CI, 2.40, 9.71) than thosewho are from poor wealth quintile class. Frequency of
Mengesha Kassie et al. BMC Public Health(2020) 20:1189Page 5 of 11Fig. 1 Conceptual framework for the prevalence of overweight and obesity and its associated factors among reproductive age group women inEthiopia, adapted from different sources by the principal investigator after reviewing different literatures [8, 14, 26, 27]media use was also significantly associated with overweight and obesity. The odds of being overweight andobese was higher among those watch television at leastonce a week (AOR 1.91, 95% CI, 1.26, 2.90) and useinternet at least once a week (AOR 1.89, 95% CI, 1.06,3.36) compared to those who did not use it at all(Table 4).DiscussionThe prevalence of overweight and obesity among thestudy participants was 11.5 and 3.4% respectively. Thecombined prevalence of overweight and obesity was14.9%. This finding is higher than previous studies conducted in Ethiopia [29, 30]. However, it is lower than astudy in Malawi that the prevalence of overweight andobesity among adult women was 16.8 and 6.3%, respectively [26]. This variation in the prevalence rates mightbe due to the differences in the age group of studyparticipants.Unlike the current study, the Malawi study was conducted among adults aged from 18 years to 49 years old.The current study was conducted among reproductiveage group women aged from 15 to 49 years old whichTable 2 Prevalence of overweight and obesity amongreproductive age group women in Ethiopia (N es32711.5No252188.5ObeseOverweight and obeseYes983.4No275096.6Yes42514.9No242385.1can potentially lower the prevalence of overweight andobesity among women. Because, age of participants wasone determinant which was significantly associated withthe prevalence of overweight and obesity among thestudy participants. The prevalence of overweight andobesity among the age group of participants containingadolescents was lower than the other groups in thisstudy. Adolescence is a stage of rapid growth and development and there is an increase in nutrition demand atthis time [31]. Thus, the inclusion of adolescents maypotentially hider the overall prevalence of overweightand obesity among the study participants in this study.It is also lower than a study in India which had shownthat the prevalence of overweight and obesity among reproductive age group women was 22.6 and 10.7% respectively [27]. This variation may emanate fromdifferences in developmental level of the two countries,because, majority of the associated factors with overweight and obesity are the result of demogtaphic and socioeconomic transitions across countries [32]. The highprevalence of overweight and, or obesity in womenmight be also due to their physiology as they tend to deposit more fat than lean mass [33–35].Besides, from the total participants who are overweightand obese, majority, 83.3% were urban dwellers and theremaining 16.7% were rural dwellers. This finding is inline with the Malawi and Indian studies that theprevalence of overweight and obesity was higher amongwomen living in urban areas as compared to theircounter parts [26, 27]. Consistent finding has been alsoreported in other low and middle-income countries[36–38]. This could be attributed to the life style ofurban dwellers. Unlike rural residents who are usuallymore actively involved in a less sedentary lifestyle and
Mengesha Kassie et al. BMC Public Health(2020) 20:1189Page 6 of 11Table 3 Cross-tabulation of baseline characteristics, andoverweight and obesity among reproductive age group womenin Ethiopia (N 2848)Table 3 Cross-tabulation of baseline characteristics, andoverweight and obesity among reproductive age group womenin Ethiopia (N 2848) (Continued)Respondents baselineCharacteristicsRespondents baselineCharacteristicsOverweight and ObeseYes, n (%)P-ValueNo, n (%)Educational status of respondentsOverweight and ObeseYes, n (%)No, n (%)Not 84.4)Employment statusNo )Secondary96(26.7)269(73.3)Higher97(37.0)165(63.0) 0.00148(6.6)680(93.4)25-34 years old216(16.5)1090(83.5) 35 years old161(19.8)653(80.2) rs1(7.1)13(92.9)No 347(13.6)2199(86.4)Yes78(25.8)224(74.2)Respondents wealth indexReligionOrthodox0.223Husband/partners educational statusRespondents age15–24 years oldP-Value 0.001 0.001 0.001Respondent drinks alcoholNumber of children0.311Respondent smokes cigaretteNone24(10)215(90)1–3299(18.3)1335(81.7) 4102(10.5)873(89.5) 0.001Respondent chews chatType of current contraceptive 85.5) 0.001258(15.5)1408(84.5) 6 month167(14.1)1015(85.9) 0.001Frequency of reading newspaper or magazineDuration of current contraceptive use 6 month0.7140.316Region of respondentsNot at all267(11.3)2095(88.7)Less than once a week111(30.9)248(69.1)At least once a week47(37.0)80(63.0) 0.001Frequency of listening to ara23(4.3)509(95.7)Oromia33(9.1)330(90.9) 0.001Not at all185(10.9)1514(89.1)Less than once a week95(17.1)459(82.9)At least once a week145(24.4)450(75.6)Frequency of watching televisionSomali5(31.2)11(68.8)Not at ss than once a week53(14.0)325(86.0)At least once a a22(11.5)170(88.5)Harari51(34.9)95(65.1)Not at all351(13.1)2326(86.9)Addis Ababa147(41.5)207(58.5)Less than once a week16(42.1)22(57.9)Dire Dawa50(31.6)108(68.4)At least once a week32(44.4)40(55.6)Almost every 723(96.0) 0.001Frequency of using internetResidenceUrban 0.001 0.001 0.001
Mengesha Kassie et al. BMC Public Health(2020) 20:1189Page 7 of 11Table 4 Regression analysis of overweight and obesity among reproductive age group women with their educational status andother covariates in Ethiopia, (N 2848)RespondentCharacteristicsOverweight and ObeseBivariate logistic regressionMultivariable logistic regressionYes, n (%)No, n (%)COR (95%CI)AOR (95%CI)No 76)0.01215–24 years old48(6.6)680(93.4)1125-34 years 8) 0.001 35 years 7) 0.001P-ValueEducational statusRespondents 3, 35(81.7)2.01(1.29,3.12)1.46(0.86,2.49)0.167 0.2290.3350.353Number of childrenType of current contraceptive 6(12.6)181(87.4)2.01(1.11,3.65)4.05(2.04,8.07) 34,13.03)3.10(1.62,5.92)0.001Addis .39)0.001Dire 1(2.02,4.80) 0.001Rural71(4.0)1723(96.0)11Not 8,1.15)Employed251(15.6%)1354(84.4)11Respondents regionResidenceEmployment status0.361
Mengesha Kassie et al. BMC Public Health(2020) 20:1189Page 8 of 11Table 4 Regression analysis of overweight and obesity among reproductive age group women with their educational status andother covariates in Ethiopia, (N 2848) (Continued)RespondentCharacteristicsOverweight and ObeseBivariate logistic regressionMultivariable logistic regressionYes, n (%)No, n (%)COR (95%CI)AOR (95%CI)842(93.7)11P-ValueHusband/partners educational statusNo 1.36(11.33,40.27)4.82(2.40,9.71) (1.67,2.92)1.42(0.98,2.07)Wealth indexRespondent chews Chat0.063Frequency of reading newspaper or magazineNot at all267(11.3)2095(88.7)11Less than once a 6)0.853At least once a .760Not at all185(10.9)1514(89.1)11Less than once a )0.008At least once a 7)0.320Frequency of listening to radioFrequency of watching televisionNot at all85(5.1)1572(94.9)11Less than once a )0.246At least once a .90)0.002Not at all351(13.1)2326(86.9)11Less than once a 0.461At least once a 0.031Almost every .449Frequency of using internetmore laborious activities, the occupation of urbandwellers may result in sedentary type life stylesamong women [39–41].In the multivariable logistic regression analysis model,educational status of women was positively associatedwith the odds of being overweight and obese. The oddsof being overweight and obese was around 2 timeshigher among those who had higher, secondary and primary educational status than those who had no education. This is not expected because people who areeducated are expected to get more information on theeffect and methods of overweight and obesity from different sources than those who are not educated. Nevertheless, consistent findings have been reported in otherlow and middle-income countries [24, 25]. The possibleexplanation could be people with a higher level of educational status usually live in urban areas where theprevalence of overweight and obesity is higher thanthose who are not educated [42].Besides, women with higher educational level are morelikely to have a higher wealth status one of the significant factor for overweight and obesity than lesseducated women [43]. The other reason could be aspeople with better educational status usually live inurban areas, the nature of their occupation might lead toincreased body weight than the rural residents [42, 44].This can be justified by the results of the current studythat from the total participants who are overweight andobese, majority, 83.3% were urban dwellers and only16.7% were rural dwellers.
Mengesha Kassie et al. BMC Public Health(2020) 20:1189In addition, respondent’s age, region, residence, wealthindex, frequency of listening to radio, frequency ofwatching television, and frequency of using internet weresignificantly associated with overweight and obesityamong women. The odds of being overweight and obeseamong respondents aged 25–34 years old and 35 yearsold were more than 3 and 6.5 times higher respectivelythan those aged 15–24 years old. This is in agreementwith studies conducted in both developed and developing countries which have indicated that overweightand obesity in women tend to increase with age [45–47].It might be also due to family transitions as somestudies shown that starting at the age of 30 years womentend to shift various household roles to their childrenmaking themselves less active in routine household activities. As women grew old, some tend to express lesswillingness to reduce their body weight irrespective oftheir health status [47]. The link between age and bodyweight might be due to the fact that increasing age is aknown risk factor of overweight, obesity and other noncommunicable diseases [48]. Furthermore, advancingage is linked with number of parity which is an important risk factor for overweight and obesity [49]. Bodyweight usually increases during pregnancy which can becontinued for a lifetime if weight loss did not occur inthe post-partum period [50, 51].The odds of being overweight and obese among respondents living in Oromia, Somali, Benishangul, Harari,Addis Ababa, and Dire Dawa was higher than those wholive in Tigray region. This difference might be due todifferences in sociodemographic and socioeconomic status of the people in these regions. For example, unlikeTigray region which contains both urban and rural residents, Addis Ababa and Dire Dawa are urban and peopleliving in urban areas are at increased risk of being overweight and obese as evidenced in this and other previousstudies [26, 27, 52, 53].In this study the odds of being overweight and obesewas more than 3 folds higher among women living inurban areas than those who live in rural areas. This finding is in line with the Malawi and Indian studies [26,27]. This could be due to the fact that urban dwellersare usually from middle and high income groups ofpeople and, households with a high income tend to purchase food in bulk
weight and obesity refers an excessive fat accumulation in body tissues [2]. Obesity is an illness and necessitates immediate reversal to prevent early and untimely death among patients [2, 3]. Globally, the prevalence of overweight and obesity is escalating, particularly among women and wealthier people
NBF Fundamental Sector Rotation - May 2022 Name (Sector/Industry) Recommendation S&P/TSX weight Energy Overweight 18.0% Energy Equipment & Services Overweight 0.0% Oil, Gas & Consumable Fuels Overweight 17.9% Materials Overweight 13.0% Chemicals Market Weight 2.5% Containers & Packaging Overweight 0.5% Metals & Mining * Overweight 2.7% Gold Overweight 6.7% Paper & Forest Products Market Weight .
Prevalence¶ of Self-Reported Obesity Among U.S. Adults by State and Territory, BRFSS, 2016 Summary q No state had a prevalence of obesity less than 20%. q 3 states and the District of Columbia had a prevalence of obesity between 20% and 25%. q 22 states and Guam had a prevalence of obesity between 25% and 30%. q 20 states, Puerto Rico, and Virgin Islands had a prevalence
Notes: Prevalence of Overweight & Obesity by Education in Urban Areas In this graph, overweight refers to BMI 25– 30, and obesity as BMI 30 kg/m2 Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m²,
Prevalence of Excess Weight Among Children in England National Child Measurement Programme 2013/14 3 Patterns and trends in child obesity Child overweight (including obesity)/ excess weight: BMI 85th centile of the UK90 growth reference One in five children in Reception is overweight or obese (boys 23.4%, girls 21.6%) One in three children in Year 6 is overweight or obese (boys 35.2%, girls
Overweight or obesity prevalence in this report refers to the proportion of public school students found to be overweight or obese during the school year. Overweight/obese was defined as BMI greater than or equal to the 85th percentile for children of the
National and Arkansas Childhood Obesity Trends NHANES data sources: Ogden et al. Prevalence and Trends in Overweight Among US Children and Adolescents, 1999-2000.JAMA 2002;288(14):1728-1732. Ogden et al. Prevalence of Overweight and Obesity in the United States, 1999-2004.
The prevalence of obesity has doubled in the last 25 years (PHAC, 2011) One in three children is overweight or obese (PHAC, 2011) Between 1978 and 2004, the combined prevalence of overweight and obesity amongst children two to 17 years doubled from 15% to 26% (PHAC, 2011) 6
BIOGRAPHIES Opening session Walter Radermacher Mr Walter Radermacher was appointed Director General of Eurostat as of 1 August 2008. Walter Radermacher, previously the Head of the German Statistical Office (Destatis), has held a wide variety of posts during his thirty-year career there, notably in the fields of environmental and economic statistics. He has been President since December 2006 .
