Ajaere Tobechukwu Jones DIETARY HABITS AND RISK FACTORS OF OVERWEIGHT AND OBESITY IN SCHOOL AGED CHILDREN (11, 13 AND 15 YEARS OLD) IN LITHUANIA

LITHUANIAN UNIVERSITY OF HEALTH SCIENCES Medical Academy

Faculty of Public Health Department of Preventive Medicine

Ajaere Tobechukwu Jones

DIETARY HABITS AND RISK FACTORS OF OVERWEIGHT AND OBESITY

IN SCHOOL AGED CHILDREN (11, 13 AND 15 YEARS OLD) IN LITHUANIA

Master Thesis

(Public health)

Thesis supervisor Prof. Linas Šumskas

Thesis consultant Jūratė Tomkevičiūtė

SUMMARY

Master in Public Health

DIETARY HABITS AND RISK FACTORS OF OVERWEIGHT AND OBESITY IN SCHOOL AGED CHILDREN 11, 13 AND 15 YEARS OLD IN LITHUANIA

Ajaere Tobechukwu Jones

Supervisor Linas Šumskas, Prof. Dr. Consultant Jūratė Tomkevičiūtė

Lithuanian University of Health Sciences, Medical Academy, Faculty of Public Health, Department of Preventive Medicine. Kaunas; 2014. 85 p.

Aim of the study: To get better insights into the profile of body composition, the prevalence of overweight and obesity in school children aged 11, 13 and 15 years old and to analyze relationship of overweight and obesity with some behavioral and social health factors in Lithuania.

Objectives: To establish the prevalence of overweight and obesity in school-age children (11, 13 and 15 years old) in Lithuania. To describe the distribution of obesity and overweight by age, gender, nationality, family affluence, living place and household groups of school age children. To establish the statistical relationship of obesity and overweight with nutritional habits and physical activity and to analyze the relation of overweight and obesity with self-rated health and self body image.

Methods: In this master’s research work the selected primary source of existing research raw data from the HBSC questionnaire survey 2009/10 was used. The author of the master’s thesis has provided his own contribution by selecting the research topic, formulating the research questions, identifying the questionnaire items relevant to the topic and also conducting statistical analysis, interpretation of data. The analysis of the data (3338 questionnaires of 11, 13 and 15 year old school children were analyzed) was calculated in percentages, averages. IBM SPSS Statistics 20.0 and MS Excel 2007 were applied for calculations and visual presentation of the results. The significance level when p<0.05 was considered as statistically significant.

Results: 10.8% of 11, 13 and 15 years old school children were overweight and 1.6% were obese. Therefore, the percentage decreased with increased age. Prevalence of overweight and obesity was statistically higher (p<0.05) among boys (16.0%) than girls (8.7%). Higher prevalence (p<0.05) of overweight and obesity was observed in the merged group (all ages, both genders) of Polish students (19.4%) in comparison with Lithuanian students (11.9%). Percentage of respondents who reported they never ate fast food was (32.4%) was significantly higher than in normal or underweight (24.2%) group.

The results demonstrate statistically significantly larger percentage in overweight group, who played computer games (1 hour or more) in a day during weekdays (57.9%) and who played computer games (2 hours or more) in a day during weekends (48.6%) comparing to normal or underweight group (46.9% and 37.8% respectively). The proportion of school children who rated their health as poor were statistically significantly larger among obese (28.8%) than in merged normal-underweight group (14.2%). 64.8% of students from the normal-underweight group perceived their weight as about right in comparison with overweight group (36.5% self rated their weight as right) and obesity (11.5% rated their weight as right.

Conclusions: It was established that 12.4% of the Lithuanian school-aged children aged 11, 13 and 15 years were found to be overweight or obese. The prevalence of overweight and obesity in all three age groups was higher in boys than in girls. Higher prevalence of overweight and obesity was related with younger age. BMI distribution analysis did not establish a statistical differences in overweight and obesity by place of residence (urban vs. rural) and family well-off (low, medium and high affluence). Therefore, higher prevalence of overweight and obesity was established among Polish students in the merged group (all ages, both genders). Prevalence of overweight was higher in those living with single mother and the obesity was more prevalent in respondents living as orphans with no parents. Those who lived with grandfather, grandmother, stepfather and in foster home tend to be more obese except for those who lived with stepmother. The prevalence of overweight and obesity was significantly less prevalent in school children who had breakfast every day. The higher prevalence of obesity and overweight was established in school children who were involved in sedentary life style such as playing the computer games. It was established that obese group of children have evaluated their health as more poor in comparison with normal or underweight group of school students.

Keywords: school children, overweight and obesity, nutritional habits, physical activity, self-rated health, self-assessment of body image.

LIST OF ABBREVIATIONS

BMI – Body Mass Index

CDC – Center for Disease Control and Prevention COSI – Childhood Obesity Surveillance Initiative HBSC – Health Behavior in School age Children

OECD – Organization for Economic Co-operation and Development SES – Socio-economic Status

CONTENT

INTRODUCTION ... 5

1 AIM AND OBJECTIVES ... 8

2 LITERATURE REVIEW ... 9

2.1 Defining childhood overweight and obesity ... 9

2.2 Other measures of childhood obesity ... 13

2.3 Weight perception ... 14

2.4 Dietary habits among school age children ... 16

2.4.1 Nutrition in infancy and childhood and BMI ... 16

2.4.2 Nutrition behaviors in children ... 16

2.4.3 Dietary guidelines and assessments ... 18

2.4.4 The role of school in healthy nutrition ... 19

2.5 Socio-demographical factors of obesity and overweight in school age children ... 20

2.5.1 Gender and age ... 20

2.5.2 Socio-economic status, educational level and family structure ... 22

2.5.3 Other variables related to body composition ... 22

2.6 Body composition and physical activity ... 23

3 MATERIAL AND METHODS ... 25

3.1 Research design and sampling ... 25

3.2 Measurements and criteria ... 26

3.3 Statistical analysis ... 27

4 RESULTS ... 28

4.1 Prevalence of overweight and obesity for school age children in Lithuania ... 28

4.2 BMI and nutritional habits ... 42

4.3 BMI and physical activity ... 48

4.3.1 Physical activity ... 49

4.3.2 Physical inactivity ... 54

4.4 Self-rated health and self assessment of body image of school age children in Lithuania ... 59

4.4.1 Self-rated health ... 59

4.4.2 Self assessment of body image ... 64

CONCLUSIONS ... 71

PRACTICAL RECOMMENDATIONS ... 73

REFERENCES ... 74

INTRODUCTION

The World Health Organization (WHO) recognizes that childhood overweight and obesity as a health problem have reached epidemic proportions in many industrialized countries (WHO, 2009). During the last few decades many developing countries were passing through a period of epidemiological transition. This transition resulting in reduced incidence of infectious diseases, decrease of child mortality and also lower birth rates (Cutler & Mille, 2004). The recent changes show on higher prevalence of chronic diseases and increase in life expectancy at birth. In other words, this transition is related to movement from era of disease of poverty to the period of affluence disease (WHO, Uusitalo et al., 2002). Improved nutrition and everyday food availability has changed significantly the nutritional status of the entire populations and has resulted in increase of prevalence of overweight and obese persons (WHO, Swinburn et al., 2004).

The prevalence of childhood overweight has increased worldwide during the last decades. Studies suggest that over 155 million children are overweight or obese; 42 million of these children are under the age of 5. This trend is increasing rapidly in industrial including the most European countries (Jackson-Leach & Lobstein, 2006). Studies show that it ranging from 3.5% among Lithuanian girls to 31.7% in boys from Malta. In Eastern European countries (Due et al., 2012) its prevalence rates up to 30% (Wang & Lobstein, 2006; Lobstein & Frelut, 2003), but current survey have suggested that this development is fading off (Bergstrom & Blomquist, 2009; Lioret et al., 2009). Estimates of overweight and obesity prevalence in Norwegian children are similar to those reported in many Northern and Western European countries, but lower than those reported in the United Kingdom, southern European countries and the USA (Juliusson et al., 2007).

Researchers have worked on establishment of origins of obesity and overweight and have come to a conclusion that it is a result of energy imbalance. When the amount of energy taken in from food or drink and the energy being used by the body support became excess the body accumulates the fat. It was proved that the main determinants of fat accumulation in the body are: lifestyle, dietary habits, genetically predisposition, and social factors, economical and other determinants. These issues mostly that of nutrition became one of the major health challenges globally due to gradual improvement of nutritional status of population also in many former underdeveloped countries (Waters et al., 2010; Lobstein et al. 2010).

Overweight was rare and malnutrition was more common years ago in the first part of 20th century in European children (Juliusson, 2010). These were times of high pediatric morbidity and

mortality with stunting in growth. In European countries, a secular trend in longitudinal growth has been documented with gradual increase in final height of 0.3-3 cm per decade (Hauspie et al., 1997). This improvement in growth appeared together with improvements in nutritional status and changing of disease profile.

Recently epidemiological surveys showed that close to one in four schoolchildren in the 25 European Union (EU) Member States is overweight, with the number increasing by more than 400 000 new cases every year (HBSC, 2006). But as overweight prevalence rises, the risk documenting health consequences of pediatric obesity grows. Obese young people are at greater risk of health problems such as poor glucose tolerance, hyperinsulinemia, type 2 diabetes, hypertension and asthma (Haug et al., 2006). However, their association with morbidity and increased risk of premature mortality from coronary heart disease, arteriosclerosis and certain types of cancer still remains a huge concern.

In economically developed regions the prevalence of overweight is dramatically higher, but its significance is rising in most parts of the world. Therefore, in the last two decades in industrialized countries this trend has continued with a higher prevalence of obesity and its consequences, presenting in adults from higher socio-economic classes. Since the early 90’s several authors have noted the obesity epidemic affecting developing countries as this change in nutritional status is occurring much faster than in developed countries. In Eastern European countries dietary habits and physical activity tend to deteriorate during adolescence, due to the influence of social and economic transitions (Lien et al., 2010) leading to an increased risk for developing chronic disease with other significant likelihood having some multiple risk factors for type 2 diabetes. Like previously said obesity is a risk factor for many diseases such as certain cancers, hypertension, type II diabetes mellitus, dyslipidemia, metabolic syndrome and coronary heart disease and a variety of other co-morbidities before or during early adulthood.

Growth evaluation and monitoring is method which is universally used to assess nutritional status, health and development of individual children (Srivastava et al., 2012). The nutritional status of children is a good indicator of the health status of a community and the school-going children, the most important segment of our society, present a general health status of a community and the nation as a whole (Vashisht et al., 2005). Anthropometric examination is an almost mandatory tool in any research to assess health and nutritional condition in childhood. According to WHO various indices can be use based on anthropometry to evaluate the nutritional status of children. Body mass index (BMI) is an inexpensive and non-invasive measure that has been extensively utilized to assess the nutritional status of adults and thinness in adolescents (WHO, 1995).

Today the new evidences regarding overweight prevalence in children from low-income families are important to direct and implement public policies and improve public health in general. Therefore, to improve the prevalence estimates of weight status, the conducting of health interventions is recommended (Ellert et al., 2014). Evaluation strategies approach is required to promote health improvement, social, justice and sustainable economic development by linking interventions in food, physical activity and healthy environments across all stages of the lifecycle (Robertson et al., 2007). In order to establish the factors behinds obesity and the insight of full body composition, health monitoring of trends in obesity across diverse population represents the key areas of research. Such aims can also be utilized by both planning “high risk strategies” and “all population targeting strategies” for obesity prevention (Waters et al., 2010).

1

AIM AND OBJECTIVES

Aim:

To get better insights into the profile of body composition, the prevalence of overweight and obesity in school children aged 11, 13 and 15 years old and to analyze relationship of overweight and obesity with some behavioral and social health factors in Lithuania.

Objectives:

1. To establish the prevalence of overweight and obesity in school-age children (11, 13 and 15 years old) in Lithuania.

2. To describe the distribution features of obesity and overweight by age, gender, nationality, family affluence, living place and household groups of school age children.

3. To establish the statistical relationship of obesity and overweight with nutritional habits and physical activity.

4. To analyze the relation of overweight and obesity with self-rated health and self body image in school age children.

2

LITERATURE REVIEW

2.1

Defining childhood overweight and obesity

WHO defined obesity and overweight as abnormal or excessive fat accumulation that presents a risk to health which affects all age group as a global epidemic with huge outcome for public health, Global changes in nutrition and dietary habits and lack of excessive physical activity is a huge reason for the concern (WHO, 2007). Defining obesity (excess body fat) in children is challenging not only because the fat in children is more difficult than in adults as normal body fat not only differ between the sexes, but also varies with age and the maturity of the child. There remains no universally accepted definition for obesity in children that differentiates those with normal or healthy fat from those in whom fatness is unhealthy.

In definition of child obesity and overweight epidemiological studies, obesity research, and clinical care play a major role and they are all very important. For instance in epidemiological point of view obesity and overweight is defined as the necessity to determine the prevalence and to follow trend over time. While in clinical research the definition is mostly about health symptoms and outcomes of health risk. Therefore, in obesity research the definition deals both with prevalence and also etiology, considerable clinical thresholds could be defined for when to alert the parents or when to initiate evaluation or intervention.

In the past 2 decades the prevalence of overweight and obesity became higher in developing countries by more than 65% as well as in the developed countries (increase by 48%). Therefore, nowadays the trend in developed countries (11.7%) has since double that of developing countries (6.1%). Three elements appear to contribute to the development of the obesogenic environment prevalent in the Western world but also rising fast in developing countries: food availability, urbanization and sedentary lifestyle. Linking prevalence of overweight and obesity to many serious health diseases leading to death in the world especially in children, using the National Center for Health Statistics (NCHS) in 2002 and WHO growth standard in 2006 and 2010, WHO describe the rapid increase worldwide (De Onis et al., 2010; Kotanidou et al., 2013). Marked differences were observed across regions. In Africa for instance, the prevalence of childhood overweight and obesity in 2010 is 8.5%, and it is expected to increase to 12.7% in 2020. In Asia, the estimated prevalence is lower than in Africa (4.9% in 2010, increasing to 6.8% in 2020). Whereas another studies have examined childhood overweight and obesity prevalence in European countries. The highest prevalence

levels are observed in southern European countries. In 1991, 21% of school age children in Greece were overweight or obese, but a decade later, in 2000, 26% of boys and 19% of girls in Northern Greece were overweight or obese, while data from Crete in 2002 show 44% of boys aged 15years to be overweight or obese. In Spain, 35% of boys and 32% of girls aged 13-14 years were overweight in a survey in 2000. Northern European countries tend to have lower prevalence values. In Sweden in 2000-2001, the prevalence was 18% for children aged 10 years. In the Netherlands the figures are particularly low, with only 10% of children aged 5-17 overweight, including only 2% obese, in a 1997 survey. In France, the figures are a bit higher, at 15% overweight and 3% obese in a Northern French survey in 2000, and these figures appear to have remained stable, according to recent preliminary results of surveys in 2007. 16% in England, prevalence rates have climbed to 29% overweight, including 10% obese, in a 2004 survey, in eastern Europe the trend of obesity and overweight decrease when economic suffers but increase when economic recovers for instance in Poland, East Germany, Croatia, Lithuania and Latvia from 1930 until 1994 indicated that the lowest values for both traits were found immediately post-war (1948-49), increasing to the end of the 1970s, and falling again during the recession of the 1980s.

In southern European countries 15% of adolescents (Greece, Italy, Portugal and Spain), as well as in Croatia, Iceland, Luxembourg and Slovenia, report being overweight or obese. Fewer than 10% of children in Latvia and Lithuania, as well as in Denmark, France and the Netherlands, report overweight or obesity. But with an increasing number of people abandoning traditional dietary habits and adopting more sedentary lifestyles the trend of obesity and overweight seems to be spreading so fast in children especially in Lithuania and other eastern European countries. Recent survey data in Lithuania shows that the prevalence in obesity and overweight is higher in adults above 20 years old (more than 16%) especially in adult men than in children below 15 years old (De Onis et al., 2010; Grabauskas et al., 2003; Olds et al., 2009; Lobstein et al., 2010; OECD, 2012).

There are other several methods available for assessing overweight and obesity in children (CDC, 2011a). Using some sample set, non-invasive and inexpensive methods of anthropometrical methods to measure body size and composition of human body is the most suitable approach, not just because it’s the most realistic alternative for screening (Power et al., 1997). Height and weight are considered to be the most useful anthropometric measures for monitoring nutritional status, such as underweight, overweight and obesity (James & WHO, 2004). Even though the precision is poor and the cost seems low. In that respect, weight for height is considered a most useful index for assessing preschool children (De Onis et al., 2004). The anthropometric indices derived from these measures need to be specified by age and gender and are often considered more useful than the measures alone).

The body mass index (BMI), calculated as weight (kg) divided by height squared (m2), is a simple index of weight for height commonly used to classify underweight, overweight and obesity in adults (James, 2004). Since it does not distinguish between weight associated with muscle and weight associated with fat, BMI provides only a crude measure of body fatness (WHO, 2000). To estimate the proportion of the population considered overweight and obese, cut-off points need to be applied. For children and adolescents, overweight and obesity are defined differently and use different approaches (WHO, 2000; Lobstein, 2004).

The use of the weight-for height index was recommended for the classification of overweight in preschool children, before the launch of the new WHO Child Growth Standards in April 2006 (WHO, 2006), this index was defined as a weight-for-height greater than +2 standard deviations (SDs) of the United States National Center for Health Statistics (NCHS)/WHO international reference median (De Onis, 2004). Aside from the weight-for-height index which is been cut off at age of 10 y for girls and 11.5 y for boys, the WHO 2006 Standards provide BMI-for-age values that can be used for the early detection of a growth pattern leading to increased obesity risk.

Also, WHO is reviewing the development of a new reference for school-age children and adolescents WHO (1995) recommends the use of age- and gender-specific BMI for- age percentiles for children in the United States, where overweight is defined as a BMI ≥ 85th percentile and obesity as a BMI ≥ 95th percentile (Must, 1991). In 2000, Cole et al. published international age- and gender-specific cut-off points for young people aged 2–18 years (Cole, 2000). The International Obesity Taskforce (IOTF) have implemented these cut off points so as it has been used by other researchers and investigators. They are based on the adult cut-off points, and project BMI in childhood to BMI in adulthood by using an international reference population. Some of the studies identified used both WHO and IOTF recommended cut-off points to report the prevalence of overweight and obesity.

IOTF defines in adults excess body weight as having a BMI of ≥ 25 kg/m2; obesity, as having a BMI of ≥ 30 kg/m2; and pre-obesity, as having a BMI of 25.0–29.9 kg/m2. Adults are overweight if they have a BMI of ≥ 25 kg/m2, although some authors use the term solely for those with a BMI of 25.0–29.9 kg/m2 (WHO, 2000; James, 2004). James et al. (James, 2004) suggested that the most useful information for analyzing the burden of disease from overweight is the population distribution of BMI values per gender and age group, rather than the more commonly used quantification of percentage of the population classified as overweight and obese.

Defining excess body weight in children and adolescence on the other hand is of particular interest because of possible long-term associations with adult disease, but evidence on long-term relationships is fragmentary and an overview is needed that clarifies how they might occur (Power et

al., 1997), even though BMI was not ideal as a measure of adiposity, it had been validated against other, more direct measures of body fatness and may therefore be used to define overweight and obesity in children and adolescents (Lobstein et al., 2004), because the criteria of a suitable measurement of overweight according to Power et al. (1997) is an ideal measure of body fat which should be accurate, precise with small measurement error; accessible, simplicised, ease of use; acceptable and well-documented (Power et al., 1997).

Using a centile cut off point which could in theory be identified as the point on the distribution of body mass index where the health risk of obesity starts to rise steeply, but unfortunately such a point cannot be identified with any precision stating that children have less disease related to obesity than adults, and the association between child obesity and adult health risk may be mediated through adult obesity, which is associated both with child obesity and adult disease. However International Obesity Task Force proposed that these adult cut off points be linked to body mass index centiles for children to provide child cut off points describing development of age and sex specific cut off points for body mass index for overweight and obesity in children (Cole et al., 2000),on the average IOTF defines excess fat of body weight in child and adolescence from age 2 to 18 years as having a BMI of >18.41-25 kg/m2 for male, and 18.02-25 kg/m2 for female, obesity 20.09-30 kg/m2 for male and 19.81-30kg/m2 for female. In this study the range are 11, 13 and 15 respectively, which gives an accurate cut off point for each age group and gender since every age has specific centile cut off point, for instance the table below indicate International cut-off points for body mass index for overweight and obesity by gender from 11, 13 and 15 years (Table 1).

Table 1. The international centile cut off points for body mass index for overweight and obesity by gender in 11, 13 and 15 years old children

Age Body mass index 25 kg/m

2

Body mass index 30 kg/m2

Boys Girls Boys Girls

11 years old 20.55 20.74 25.10 25.42

13 years old 21.91 22.58 26.84 27.76

15 years old 23.29 23.94 28.30 29.11

Although the use of anthropometry measure is cheaper and easily accessible to assess the size, shape and composition of the human body. It reflects both health and nutrition status and predicts performance, risk factors and survival. Even though it is the most widely use measurements to predict fatness are weight and height, skinfolds and circumferences (Cole & Cachera, 2006) yet the precision still remains poor (De Onis, 2004).

2.2

Other measures of childhood obesity

Apart from height, weight, age and gender, there are other epidemiological measures which are use both in children and in adult like, skin fold thickness and bioelectrical impedance analysis. All these are indirect body fat and they are not based on weight.

Waist circumference, usually measured midway between the rib cage and the iliac crest, is an indirect measure of central obesity, and so has an advantage over BMI in that it gives an Indication of the distribution of body fat. Both subcutaneous abdominal fat and intra abdominal fat contribute to central obesity and in children waist circumference correlates highly with both types of fat when measured by computed tomography (CT) (r=0.93 and 0.84 for subcutaneous abdominal and intra abdominal fat respectively) (Goran et al., 1998).

Central obesity is well known to be a risk factor for cardiovascular disease in adults (Rexrodeet al., 1998), and waist circumference is associated with cardiovascular risk factors in children and adolescents, such as adverse lipid profiles and increased blood pressure (Freedman et al., 1999; Savva et al., 2000) Percentile curves for waist circumference were developed in 2001 from data obtained from a 1988 sample of 8000 British children age 5-17 (McCarthy et al., 2001) but there are some basic issues when considering using waist circumference as a measure of obesity. Appropriate cut offs to define overweight and obesity have not been agreed, and the relative proportions of intra abdominal and subcutaneous fat vary with ethnicity (Goran & Gower, 1999), so that waist circumference measurements will have different implications for morbidity in different ethnic groups.

Waist-hip ratio is another measure of central obesity that has been widely used in adults and has been shown to predict both all cause and cardiovascular mortality (Welborn & Dhaliwal, 2007), but it is of less use in children because it is strongly age dependent and has been shown to be less accurate than waist circumference in measuring abdominal adiposity (Taylor et al., 2000).

Skinfold thickness measurements involve measuring the layer of subcutaneous fat at different sites in the body. Commonly measured sites are triceps, biceps, sub scapular and suprailiac skin folds.

Triceps skinfold thickness measures in adolescents and sum of skin fold measures at 4 different sites in children have been shown to be a better screening tool for obesity than BMI (Bedogni et al., 2003; Sardinha et al., 1999). Sub scapular, abdominal and suprailiac skinfold measures have been shown to correlate reasonably well with intra abdominal fat in children, although their correlation with subcutaneous fat is higher (Goran & Gower, 1999). In adolescents the sum of skin fold measures at 4 sites is better than BMI in predicting body fat in adulthood (Nooyens et al., 2007). For a given BMI value, skinfold thickness has been shown to vary by sex and ethnicity and so may be a useful addition to BMI in assessing disease risk in different ethnic groups (Sisson et al., 2009). Published equations are frequently used to derive a value for percentage body fat from skinfold measures, but an issue with this is that the equations are population specific and often inaccurate (Wells, 2001) A major problem with skinfold thickness measures is the poor intra and inter-observer reliability (Ulijaszek & Kerr, 1999), and this limits their use in epidemiological studies.

Bioelectrical impedance analysis (BIA) is based on the principle that the electrical conductivity of fat free mass is greater than that of fat mass due to its higher water content (Sung et al, 2001), so equations can be used to derive an estimate of percentage body fat from a measure of electrical impedance through the body (Wabitsch, 2000). Body fat estimates from BIA in children have shown good agreement with reference standard measures (dual energy x-ray absorptiometry, DXA) (Sung et al., 2001), and have been shown to be more strongly associated with blood pressure and lipid profiles than BMI and triceps skin fold thickness (Vizcaino et al., 2007). BIA measures are an attractive option for epidemiological studies as they are technically straightforward to perform and reliable, and population reference curves for body fat derived from BIA have been developed in recent years (McCarthy et al., 2006). These reference curves are of limited use, however, because the equations to derive percentage body fat are specific to the models of bio-impedance monitor used, and so cannot be compared to body fat measures from other bio-impedance monitors.

Despite the shortcomings of BMI as a measure of obesity in children, and the advantages of some of the alternatives, it remains the most widely used epidemiological measure of childhood obesity.

2.3

Weight perception

If individuals who are overweight, obese or underweight do not recognize their original weight status, it becomes clear that they are unaware of the health risk and do not take any measure to lead a healthy life. Similar may be the case when healthy people perceive themselves as obese or overweight

and engage in physical activity or weight control behaviour which is not needed or unhealthy (Binkley et al., 2009). Biased perception of overweight could be related to depressed mood, lower self health esteem and somatic complains in some ethnic and gender groups (Whetstone et al., 2007). It has been found that the perception of weight status is very much different in the males and the females and it also shows drastic variation across gender. Girls in most of the cases perceive themselves to be overweight to report more body dissatisfaction and to be concerned about their weight than boys (Pillai, 2011).

Based on the latest estimates, overweight affects 30-70% and obesity affects 10-30% of adults in EU countries. The Health Behavior in School-aged Children (HBSC) survey conducted in 2005-2006 gathered self-reported data on weight and height in 11-, 13- and 15-year-olds in 26 EU Member States and used the Cole et al cut-offs for the definition of excess body weight. It indicated that among 11-year-olds, up to 30% of boys and 25% of girls were overweight; among 15-year-olds, the corresponding figures were 28% and 32%, respectively. Up to 31% of both year-old boys and 13-year-old girls were overweight.

The first data collection round of the WHO European Childhood Obesity Surveillance Initiative (COSI) took place during the school year 2007-2008 and preliminary results, based on measured weight and height and using the 2007 WHO child growth reference, indicate that both overweight and obesity are more prevalent among boys than among girls. On average 24% of the children aged 6-9 years old were overweight or obese. Besides the HBSC and COSI, other trend data in children and adolescents based on measured or self-reported data are available in a few countries only, such as in Belgium, Bulgaria, France, the Netherlands, Slovenia, Sweden and the United Kingdom) (European Commission, 2010). Weight perception is a very important driving force in determination of behavioral pattern of eating, weight management among adolescents (Eaton et al., 2005). Perceived body weight and weight gain concern have a direct influence on desire to change weight and in turn influence physical activity (Plotnikoff et al., 2007). Perceived health status also drives the estimation of caloric intake and it has been shown that overweight adolescents and adults tent to underestimate their caloric intake as compared to right weight individuals (Gilbert, 1995). For example as one of the literature mentioned behavioral attitude of fast food consumption was significantly and positively associated with perceived barrier of healthy eating, but there is not enough research done whether the perceived barrier varies by weight status (French et al., 2001). Negative perception also has detrimental effects on the health of the adolescents. Negative weight perception is related to extreme weight control behaviors like dieting, use of laxatives, diet pills and binge eating among over weight adolescents (Boutelle et al., 2002).

2.4

Dietary habits among school age children

2.4.1 Nutrition in infancy and childhood and BMI

Greater consumption of protein in earlier life has been suggested to predispose people to later adiposity. In France, for 151 children followed from 1 month to 16 years of age, adiposity increased during the first year and then decreased with a renewed increase at a later age, called the age of adiposity rebound. The rebound age related to final adiposity, with an earlier rebound being associated with greater later adiposity (Cachera et al., 1984). When the growth of 112 French children was followed from 2 to 8 years, protein intake at the age of 2 was positively correlated with BMI and subscapular skinfold thickness at age 8. Rolland et al. concluded that a high protein intake increased body fatness at 8 years of age, which was mediated through an earlier adiposity rebound (Hoppe, 2004).

A study in Iceland followed 90 healthy newborn babies up to 6 years of age. More rapid growth during infancy was associated with increased BMI at age 6 years, and, in boys, those with the highest protein intake had the highest BMI (Gunnarsdottir & Thorsdottir, 2003). A cohort study of 889 English children from birth to age 5 found no relationship between dietary protein (or any other aspect of the diet) and age of adiposity rebound. Parental obesity, however, was associated with an earlier rebound (Branca et al., 2007). In 142 Danish children, although protein intake at 9 months of age was associated with greater growth in length and weight, there was no relationship with adiposity or with the percentage of body fat at age 10 (Hornell et al., 2013).

Metges (2001) concluded that there is only weak epidemiological evidence that dietary protein in early postnatal life influences the development of adiposity in later life. The European early childhood obesity programme, in a randomized double-blind intervention trial in 1150 infants in five centres, is testing the hypothesis that high early protein intake enhances the risk of later obesity (Koletzko et al., 2005).

2.4.2 Nutrition behaviors in children

Nutrition is considered as a major modifiable determinant of overweight and obesity and other chronic diseases. The scientific evidence increasingly supporting the view that alterations in diet could

have strong effects, both positive or negative on the health throughout the life span. Adequate energy balance is needed to maintain healthy nutritional behavior, the energy requirement of an individual or group of persons is the amount of dietary energy needed to maintain health, growth, and an appropriate level of physical activity (Torun, 2005). Dietary adjustments may not only influence present health status, but may determine whether or not an individual will develop such diseases as cancer, cardiovascular diseases and diabetes much later in life (WHO, 2003), also preference for energy dense foods may serve as a risk factor in the development of overweight if consumption of these foods leads to excessive fat and energy intake. Fisher & Birch (1999) and Ricketts (1997) found that children with greater triceps skin fold thickness displayed a higher preference for fat and children’s preference for high fat foods was positively associated with fat intake, that is, frequency exposure to fat may exert a stronger influence on hedonic (pleasant) rating of food containing fat than total fat intake (Ricketts, 1997).

Cross sectional and longitudinal research provides more convincing evidence of a relationship between children’s percent fat intake and weight status. Higher percent fat intake among children has been concurrently associated with higher percentage body fat, fat mass, and skin fold thickness. Moreover, higher percent fat intake has been prospectively associated with greater increase in children’s skin fold thickness across a period of a year and greater increase in BMI over 2 years. Another explanation might be related to alterations in dietary intake due to gastrointestinal abnormalities (Campos et al., 2014).

Conversely, a preference for fruits and vegetables may serve as a protective factor for the development of overweight. Similarly, Resnicow (1997) and co-workers found that children’s consumption of fruits and vegetables was positively associated with their preference for fruits and vegetables (Davison & Birch, 2001).

For instance, a dietary pattern study in Indian school children suggested that majority of school children had regular healthy meal including regular breakfast but girls in rural region who had basic and cereal-based meal, had inadequate intake of healthy diet like milk and milk products, pulses, green leafy vegetables, other vegetables, and fruits. Therefore, the intake of boys in these healthy dietary patterns was adequate and rich, even though most of the obese children knew that they were obese, but they still ate excessively monotonous meal. This indicates that either they do not have enough knowledge on this matter, or their knowledge has not transformed into their practices (Alavi Naini et al., 2006; Kotecha et al., 2013).

Inadequacy of the complementary diet likely contributes substantially to the high rates of micronutrient deficiencies, morbidity, and growth stunting often observed among complementary-fed

children in low-income country settings (WHO/UNICEF, 1998). According to the UNICEF data regarding children malnutrition in Peru, show 30% of stunting in children aged less than 5 (using as the referral standards the WHO growth curves), which shows malnutrition is qualitatively and not only quantitatively different from normal nutrition (Andrissi et al., 2013).Nutrition behavior does not only leads to overweight and obesity, it also leads to other factors like underweight, malnutrition stunted growth, for instance children’s dietary patterns are central in the development of overweight as excess caloric intake, relative to energy expenditure, therefore will result in the storage of energy as fat, eventually leading to excessive levels of fat in the body.

Another study, in Brazil shows that school age boys were significantly more stunted than girls of the same age while a second study stunting was also found to increase with age where younger school children were reported to have a prevalence of just 2% compared to 16% among older school children in Bangladesh, both indices of nutritional status worsened as the study population got older, particularly for boys (Mwaniki & Makokha, 2013).

In addition to problems noted in measuring dietary intake among adults (e.g. the inability to remember and accurately report all foods consumed, the restricted list of foods provided, and self-report biases), self-reports of children’s dietary intake are also limited by the fact that they are generally based upon reports from a third person, usually a parent. Inconsistencies in research to date may also be explained by the fact that research has rarely considered child characteristics that moderate the relationship between dietary patterns and weight status, the contexts in which children’s eating patterns emerge, and the processes by which such patterns emerge (Davison & Birch, 2001). Finally, increases in children’s percent fat intake have been associated with greater increases in their BMI. Only one study among those identified failed to identify an association between children’s percent fat intake and weight status. Relatively few studies have assessed the relationship between food preferences, food intake, and weight status among children.

2.4.3 Dietary guidelines and assessments

According to WHO Global Strategy on Diet, physical activity and health in 2004 proclaimed that food advertising affects food choices and influences dietary habits. Food and beverage advertisements should not exploit children’s inexperience or credulity. Messages that encourage unhealthy dietary practices or physical inactivity should be discouraged, and positive, healthy messages encouraged (WHO, 2004). In the Canadian Food Guide (CFG) it is recommends that, every day, children aged 2 to 5 consume at least a minimum (depending on age) of two to four servings of milk

and alternatives, one to two servings of meat and alternatives, four to six servings of fruit and vegetables, and three to six servings of grain products. Rather than the number of servings, the ACS asked the parent/guardian how frequently the child consumed various types of food (Langlois et al., 2013). Examination of the food habits among school children in Maine indicates that many of the diets tend to be low in citrus fruits and juices, raw vegetables, green leafy vegetables, and milk and milk products. White bread and other white flour products, cereals, potatoes, dried beans, meats, fish, and eggs are used very frequently. Fried foods and desserts are very popular, and between meals eating is very common. In respective of where they are from or their ethnic or religious believe studies have shown that the dietary habits of most children, particularly those living in rural areas, may be influenced not only by the accessibility and availability of foods such as fruit and vegetables but also the influence of friends and lack of parental guidance they prefer to feed on junks claiming it makes them feel healthy. In Europe several studies have made to understand the dietary pattern among school age children but national and locally. For instance, a survey in 2004 shows that Vitamin D intake is greatest in Northern European countries and low in some Western European countries due to high availability of milk while Vitamin E intake is highest in some Central and Eastern European countries which may have reflected the higher consumption of Polyunsaturated Fatty Acids (PUFA) (WHO, 2003). Eating pattern has not only been associated with body size but also with behavior. Spurrier and colleagues recently found that parental restriction of access by children to less healthy foods was associated with better dietary patterns while coercive behaviors were associated with poorer ones (Hoerr et al., 2009), for instance in China it is said that health awareness, positive health attitude and healthy behaviors among school teachers are associated with healthy eating behaviors among their students, and negatively associated with their unhealthy eating behaviors.

2.4.4 The role of school in healthy nutrition

The main aim of school is education and they reach almost 100% of children of school age in the high- and medium-income countries in the WHO European Region. In addition, most primary and secondary schools serve at least one meal every school day, according to the country’s law and tradition. Schools therefore represent an ideal setting to provide healthy nutrition and implement nutrition education program.

A survey in 26 European countries showed a great variety of school food services that can influence children’s and adolescents’ food habits and choices and that could be one of the environmental factors leading to the differences in obesity rates among European countries (WHO,

2003). School meals, from nursery school to secondary school, are often nutritionally imbalanced (Grajeta, 2003; Belderson, 2003). In a study in kindergartens in Poland, the energy and nutrient content of meals exceeded requirements (Grajeta, 2003). In a survey in two secondary schools in southern England and one junior school in northern England (Belderson, 2003), the standard breakfast provided was too high in salt, fat, saturated fat and percentage of energy. In conclusion, the available studies suggest, with moderate evidence, that nutritionally imbalanced school meals can promote unhealthy eating habits that favor the development of obesity among students.

2.5

Socio-demographical factors of obesity and overweight in school age children

Overweight and obesity is a result of many components since energy intake in excess of expenditure over a period of time is the simplest explanation for weight gain. We can say this multi-component is influenced and operating by individual, family, society and environmental levels and affecting the theory of energy balance. Complex and multilevel interactions between genetic, energy intake, energy expenditure, neuron-psychology, metabolic, environmental and socio-cultural factors make the understanding of “web-of causation” of childhood obesity difficult (Kiranmala et al., 2012). Even though sometimes these multi factor contradict each other like for instance in Ghana which documented an association between maternal employment and childhood overweight among advantaged households but on the other hand in India a study reported maternal unemployment to be a risk factor for childhood overweight (Muhihi et al., 2013). The fact still remains both cases are caused by socioeconomically factor.

2.5.1 Gender and age

According to survey by WHO, health behavior in school age children in the UK it is said that socioeconomic inequalities are understood to be of key importance to the patterning of health and health behaviours in the adult population and among children (Currie, 1997). It was established that excess body weight is inversely related to childhood socio-economical status (SES) and the disparity increases with age (Baum & Ruhm 2009). Although there seems to more focus on children and adolescence contributing to the influence of the inequalities, because Benzeval et al. (2009), during an investigation in a range indicators of health, both objective and subjective amongst 15 years and 18 years cohort group shows that social inequalities in health emerge in early adulthood, while another finding shows that women are more likely to report health problems and to seek medical help than men.

In the 2001-2002 HBSC study, the findings of overweight and obese boys and girls among 35 various countries and region was studied (Mulvihill et al. in Currie et al., 2004). Also findings were observed in overweight between 13 and 15 years old school children. According to HBSC study data, Mulvihill (Currie et al., 2004) indicates that boys tend to be overweight and obese more often than girls in mostly all countries they have studied except for Ireland, Scotland and Canada. Comparing 13 years and 15 years old school children data also shows that 13 years old have bigger proportion of overweight and obesity than 15 years old. For instance, prevalence of overweight and obesity in Lithuania for 13 and 15 years boys and girls in 2001-2002 is presented in Table 2.

Table 2. Prevalence of overweight and obesity in Lithuanian school age children in 2001-2002 13 years old, % 15 years old, %

Boys Girls Boys Girls

Overweight 5.3 3.6 4.4 3.0

Obesity 0.4 0.1 0.6 0.3

It is important to evaluate overweight and obesity of child and adolescent by age and gender because excess weight during childhood and particularly late adolescence is a strong predictor of adult obesity (Baum & Ruhm, 2009). Although there is still a major question on how a balance can be maintained to ensure young people maintain a healthy body weight irrespective of the age and gender differences.

2.5.2 Socio-economic status, educational level and family structure

In Europe and in the United States, overweight and obesity are more frequent among people with lower socio-economic status (Parsons, 1999). In countries with economies in transition, obesity is more frequent in affluent families (Wang, 2000). Food choices and intake can differ among families with different educational levels. In the United Kingdom, a survey conducted among the parents of 564 children aged 2-6 years who attended 22 nursery schools in London showed that the child’s vegetable intake was positively associated with the mother’s education level (Cooke, 2004). A cross-sectional study of a cohort of 404 11-year-olds in Finland showed that high family socio-economic status was associated with healthier food choices by children (Haapalahti, 2003).

A prospective cohort study in the United States among 2931 children aged 0-8 years found that those who lived with single mothers were significantly more likely to become obese by the six-year follow-up, as were children who were African American, had parents who were not employed or had mothers who did not complete secondary school.

A 1973 survey in the United States of 113 mothers of children aged 1-4 demonstrated that a mother’s negative attitude towards being a mother and a homemaker can negatively influence the quality of the child’s diet (Branca, 2007). This indicated that a mother who does not like motherhood or a specific child could hide her feelings behind the overprotective behavior of over feeding the child and thus induce obesity (Bruch, 1957).

2.5.3 Other variables related to body composition

Other socio-demographic factors associated with increased risk for paediatric overweight are: single parent families, small family size and rural setting. The Norwegian studies addressing socio-demographic risk factors and adiposity have been restricted to self-reported weight and height and have mainly been limited to adolescents (Lien et al., 2007, Groholt et al., 2008). A study comparing the effect of poverty on the obesity prevalence in Canada, Norway and the US, showed that children

defined as being not poor were less obese in all countries, although non-poor children in Norway were less obese than non-poor children in US and Canada (Phipps et al., 2006).

The influence of the home environment is critical to the development of eating habits. Unhealthy habits become an important factor in the development of childhood obesity (Branca, 2007; Fisher & Birch, 1995; Strauss & Knight, 1999; Birch & Davison, 2001). As parents provide environments for their children’s experiences with food and eating, they significantly influence their children’s dietary practices (Golan & Crow, 2004; Nicklas, 2001). Dietary practices that can favour the development of obesity can act directly through the type of food available and provided to the child and indirectly through other environmental factors that comprise the basis for food choices, such as family structure, family and parents’ socio-economic status and level of education, and parents’ personal weight, attitudes and food preferences (Birch & Davison, 2001; Golan & Crow, 2004; Nicklas, 2001).

2.6

Body composition and physical activity

WHO has stated that physical activity is a key determinant of energy expenditure, and thus is fundamental to energy balance and weight control (WHO, 2010),it‘s impact has been a great deal not only for teenagers and adolescent but also for adults in all age group and genders. Although several studies have shown it decreases of physical activity in many countries around the world mostly in older school children especially in boys. The study in United States revealed that preschool boys were found to be more physically active than preschool girls, also similar gender differences in over weight prevalence have been observed in older children and adults (Ogden et al., 1997). During another study in Australia it was stated that as children get older, sleep time, physical activity, and TV watching time decline. However, other kinds of sedentary behaviors fill the time void left by these declines. Non-screen sedentary behaviors (less active school classes, talking with friends, “hanging out,” reading) rise from about 2 hours per day at age 12 to over 9 hours per day at age 17 (WHO, 2010; Olds et al., 2010). There are evidence that shows physical activities increase during weekdays and decrease during weekends but the question as to whether the changes in physical activity compensate for the increases observed in weekend energy intake or does a change in activity patterns contribute further a positive energy balance is yet unknown (McCarthy, 2013) but then some assumptions were made by some researchers that these increase in inactivity are mainly characterized by an increase in TV viewing. This increase in TV viewing on weekends is also associated with poorer dietary quality in children on weekends during increased TV viewing time, whereas other studies have concentrated on the

relationship between diet and inactivity (usually measured by television viewing), with few looking at the relationship with physical activity. More “unhealthy” diets have been found to be associated with greater time spent watching television even though there’s there was little association between dietary patterns and overweight and obesity with a significant relationships which were in boys of aged 5-11 years, with the lowest intake of “snacks” and the highest intake of “fish and sauce” in obese school children (Craig et al., 2010).

In the WHO global recommendation on physical activity, play, games, sports, transportation, recreation, physical education, or planned exercise, in the context of family, school and community activities are the types of physical activities necessary for children under age 5-17 years old which is within the age range of our study. Also the following recommendations are advice and to be met duly in order to improve cardio respiratory and muscular fitness, bone health, cardiovascular and metabolic health biomarkers and reduce symptoms of anxiety and depression.

3

MATERIAL AND METHODS

3.1

Research design and sampling

In this master’s research work the selected primary source of existing research raw data from the HBSC study 2009/10 was used. The author of the master’s thesis has provided his own contribution by selecting the research topic, formulating the research questions, identifying the questionnaire items relevant to the topic and also conducting statistical analysis, interpretation of data. The Lithuanian HBSC national team at Lithuania University of Health Sciences has authorized the use of these national data.

HBSC cross-sectional surveys are carried out at four year intervals since 1983/84. Their findings are used to inform and influence health promotion and health education policy with the general aim of increasing the understanding of young people’s health, well-being, health behavior and social context. Lithuania has participated in the HBSC survey since 1993/94. The national survey was coordinated by Lithuanian University of Health Sciences (principal investigator in Lithuania is prof. Apolinaras Zaborskis). The 2009/10 survey was conducted in ten districts of Lithuania in randomly selected schools among 4194 respondents aged 11, 13 and 15 year old. The schools were selected from the list of all schools of Lithuania presented by Lithuanian Ministry of Education and Science. The school and the students’ classes were considered as units of observation. The 2009/10 HBSC international mandatory question has not change from the 2005/2006 version, apart from one addition on order to improve the capacity of HBSC to provide accurate cross national comparison of risk behavior (HBSC protocol, 2009/10).

Data were collected through self-completion questionnaire administered in the classroom, and later compiled into an international data file. The survey was a cross-sectional representative survey conducted every fourth year and constituting the Lithuanian contribution to the HBSC survey. The questionnaire covered a range of health indicators, health and related-behavior of young people. In this master’s research work we used 18 questions relevant to the topic for the final analysis.

3.2

Measurements and criteria

The survey questionnaire was developed and approved by the international experts involved in the HBSC study. The questionnaire covered self-reported height and weight (BMI), which was analyzed later by age and gender groups and other demographical factors such as social context, self-rated health, health behavior and risk in healthy lifestyle. The obtained data were calculated in percentages (%) as such, prevalence of BMI in all selected participants i.e. in age group (11, 13 and 15 years old) and gender (boys and girls) of Lithuania school children. Prevalence of BMI among school children was analyzed separately according to each age group and in gender group. Prevalence of BMI was also used to distinguish boys and girls in different age group. Information on nationality among school children in Lithuania and was categorized into 4 groups (Lithuanian, Polish, Russians and others) and was presented as such distribution of BMI between Lithuanians and other nationalities, prevalence of BMI between Lithuanians and other nationality age different age groups, i.e. 11 years,13 years and 15 years old.

Questions on the social context (e.g. family well-off, living place, household group). Family’s well-off as indicator of socio-economical status was divided into 3 groups: high affluence, medium affluence, low affluence. Distribution of BMI (normal or underweight, overweight and obesity) was analyzed according to “Family well-off in school children”, prevalence of BMI for groups of family well-off in 11, 13 and 15 years old. Questions on “living place (rural and urban)” was described as BMI distribution by “living place in school children”, BMI groups by living place in “different age group” was analyzed.

Households were categorized by family structure as nuclear families (both parents and children), single parent families (only father or mother with children), no parents families, and extended families (plus step mother, step father, grandmother, grandfather, foster or child home). Data was analyzed as BMI distribution by family type and gender, age group.

Nutritional habits (e.g. eating and diet). For measuring eating and diet the questions were classified by “Healthy diet and Unhealthy diet.” Frequency was calculated in such that children who had “breakfast every day”, “fruits once a day or more often” and “vegetable once a day or more often” were said to have healthy diet, while those who had sweets, soft drinks, cake, chips and fast foods were said to have unhealthy diet or junks and questions were asked in different categories: for distribution of school children who had regular health diet (breakfast every day, fruits once a day or more often and vegetable once a day or more often) and children who had unhealthy diet (sweets, soft drinks, cake,

chips and fast foods), prevalence was determined by percentages. There were also category of “Healthy and unhealthy diet” in age and gender groups.

Data survey for physical activity was determined by the same demographical characteristics like eating habits but in physical activity participants were grouped as follows. Those who were physically active in exercises „for more than 2-3 times a week”, “more than 1 hour a day” and both “more than 2-3 times a week and 1 hour a day” in age group 11, 13 and 15 years old for boys and girls. Also in our study we categorically indicated those who were involved in sedentary, less active lifestyle: spend more time on TV, video games and computer use, were physically less active than those who were more active in exercise.

Self-rated health was classified into two groups: “Excellent or good” and “fair or poor”. Data was calculated as such, prevalence of rated health by “gender and age group”. Distribution of self-rated health by BMI was calculated as well as self-self-rated health by BMI in “gender and age group” was analyzed.

Self assessment of body image was grouped into “a bit too fat, much too fat”, “a bit too thin, much too thin”, and “about right”. The data was evaluated as follow “frequency of perceived health among school children”. “Prevalence of self body image in both gender group and age group” was calculated. Distribution of self body image for “boys and girls in each age group” was measured. Percentage of self assessment of body image according to BMI groups, age and gender groups was analyzed respectively.

3.3

Statistical analysis

Statistical data analysis was performed using IBM SPSS Statistics, version 20.0. The χ2 (Chi-square) and z (with Bonferroni adjustment) tests were applied for the evaluation of statistical hypotheses on difference in the distribution of nominal variables between respondents’ groups. For quantitative variable (BMI) the hypothesis concerning normal distribution was checked using Kolmogorov-Smirnov test. The normality was denied, so three independent samples (i.e. distributions of BMI, as primary quantitative data, for 11, 13 and 15 years old school children) were compared using Kruskal-Wallis test. The statistically significant difference was established at p<0.05. Graphical data presentation was performed using MS Excel 2007.

4

RESULTS

Sample data selected to determine overweight and obesity in school children in the study were analyzed according to their age, gender, nationality, family well-off and living place. Distribution of each social demographical factor is displayed in Table 3.

Table 3. Sample characteristics of 11, 13 and 15 years old school children

Characteristics n (%) Age 11 years old 998 (29.9) 13 years old 1079 (32.3) 15 years old 1261 (37.8) Total 3338 (100) Gender Boys 1657 (49.6) Girls 1681 (50.4) Total 3338 (100) Nationality Lithuanian 2941 (88.2) Russian 174 (5.2) Polish 180 (5.4) Other 38 (1.1) Total 3333 (100) Family well-off Very good 92 (2.8) Quite good 931 (28.1) Moderate 1671 (50.4)

Not very good 547 (16.5)

Not good at all 76 (2.3)

Total 3317 (100)

Living place

Urban 1699 (51.0)

Rural 1634 (49.0)

Total 3333 (100)

4.1

Prevalence of overweight and obesity for school age children in Lithuania

BMI status was calculated for each participant in this study. For children and adolescents, overweight and obesity are defined differently as abnormal or excessive fat according to WHO, also

different approaches are used (WHO, 2000; Lobstein, 2004). Main statistical characteristics for 11, 13 and 15 years boys and girls are displayed in Table 4.

Table 4. Mean and standard deviation of BMI in gender and age groups of school children

Age n

BMI

Mean Standard deviation

Boys 11 years old* 495 18.5 2.95 13 years old* 533 19.4 2.63 15 years old* 629 21.0 2.67 Total 1657 19.7 2.93 Girls 11 years old* 503 17.6 2.98 13 years old* 546 19.0 2.75 15 years old* 632 20.0 2.54 Total 1681 19.0 2.92

*p<0.001 compared to each age group

Using the point of distribution which is the centile cut off point according to IOTF that defines excess fat of body weight in child and adolescence from age 2 to 18 years as having a BMI of >18.41-25 kg/m2 for male, and 18.02-25 kg/m2 for female, obesity 20.09-30 kg/m2 for male and 19.81-30 kg/m2 for female. Therefore, in our analysis we also applied Cole TJ approach for defining body composition categories (Cole et al, 2000). The age range was 11, 13 and 15 respectively, which gives an accurate cut off point for each age group and gender since every age has specific centile cut off point, for instance, age 11 overweight have a BMI of 20.55 kg/m2 for boys, 20.74 kg/m2 for girls, obesity 25.10 kg/m2 for boys and 25.42 kg/m2 for girls, age 13 overweight have a BMI of 21.91 kg/m2 for boys and 22.58 kg/m2 for girls and obesity 26.84 kg/m2 for males and 27.76 kg/m2 for females, and age 15 overweight have BMI of 23.29 kg/m2 for males and 23.94 kg/m2 for females, obesity 28.30 kg/m2 for males and 29.11 kg/m2 for females respectively (Cole et al, 2000).

Figure 1 shows the BMI status distribution for 11, 13 and 15 years school children in Lithuania according to HBSC data and by the IOTF criteria: 87.7% of all age groups were normal or underweight, while 10.8% were overweight and 1.6% were obese. The report estimate of normal was higher in both boys and girls, also in all age group but low in overweight and obesity in school children.

Figure 1. Prevalence of overweight and obesity in school age (11, 13 and 15 years old) children

According to the research data distribution of BMI differed significantly in school age children according to their age (p=0.003) (Figure 2).

*p<0.05 compared to 11 y

Figure 2. BMI distribution by age in school age children (11, 13 and 15 years old) overweight 10,8% 85,2% 0,0% 10,0% 20,0% 30,0% 40,0% 50,0% 60,0% 70,0% 80,0% 90,0% 100,0% Normal or underweight

Prevalence of overweight and obesity in school age (11, 13 and 15 years old) children

According to the research data distribution of BMI differed significantly in school age children according to their age (p=0.003) (Figure 2).

*p<0.05 compared to 11 years old; **p<0.05 compared to 15 years old

Figure 2. BMI distribution by age in school age children (11, 13 and 15 years old) overweight

10,8%

obesity 1,6%

BMI distribution of school age children

85,2% 12,6%** 87,3% 11,7%** 90,0%* 8,5%

Normal or underweight Overweight BMI ditribution by age

11 years old 13 years old 15 years old

Prevalence of overweight and obesity in school age (11, 13 and 15 years old) children

According to the research data distribution of BMI differed significantly in school age

ears old; **p<0.05 compared to 15 years old

Figure 2. BMI distribution by age in school age children (11, 13 and 15 years old) normal or

underweight 87,7% BMI distribution of school age children

2,2%

1,0% 1,5% Obesity 15 years old