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BMC Public HealthBMC Public Health1471-2458BioMed Central London 1471-2458-5-131569399510.1186/1471-2458-5-13Research ArticleParental educational level and cardiovascular disease risk factors in schoolchildren in large urban areas of Turkey: Directions for public health policy Kocaoglu Bike 2kocaoglb@boun.edu.trMoschonis George 1gmoschi@hua.grDimitriou Maria 1ds20009@hua.grKolotourou Maria 1ds20019@hua.grKeskin Yasar 3keskinyasar@yahoo.comSur Haydar 3haydars@yahoo.comHayran Osman 3hayran@yahoo.comManios Yannis 1manios@hua.gr1 Department of Nutrition & Dietetics, Harokopio University of Athens, 70, E. Venizelou Ave,17671 Kallithea, Athens, Greece2 Department of Tourism Administration, School of Applied Disciplines, Bogazici University, Istanbul, Turkey3 Department of Health Education, University of Marmara School of Health Education, Kartal Devlet Hastanesi Yani, Cevizli, Kartal, Istanbul, Turkey2005 4 2 2005 5 13 13 10 6 2004 4 2 2005 Copyright © 2005 Kocaoglu et al; licensee BioMed Central Ltd.2005Kocaoglu et al; licensee BioMed Central Ltd.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Background
It is widely accepted that the development of atherosclerosis starts at an early age. However, there are very few studies evaluating the prevalence of the common clinical and behavioral cardiovascular disease (CVD) risk factors among children, especially in developing countries. The aim of the present cross-sectional survey was to evaluate the distribution of blood lipid profile and various behavioral (i.e. dietary habits, physical activity status) factors related to CVD risk and its relationships to paternal (PEL) and maternal educational level (MEL) among primary schoolchildren in Turkey.

Methods
In three major metropolises in Turkey (Istanbul, Ankara and Izmir), a random sample of 1044 children aged 12 and 13 years old was examined. ANOVA was applied to evaluate the tested hypothesis, after correcting for multiple comparisons (Tukey correction).

Results
After controlling for energy and fat intake, physical activity status and Body Mass Index (BMI), it was found that mostly PEL had a significant positive effect for most of the subgroups examined (Lower vs. Higher and Medium vs. Higher) on TC and HDL-cholesterol and a negative effect on TC/HDL ratio for both genders. Furthermore, both boys and girls with higher PEL and MEL were found to have higher energy intake derived from fat and protein than their counterparts with Medium and Lower PEL and MEL, while the opposite was observed for the percentage of energy derived from carbohydrates.

Conclusions
Our study provides indications for a possible association between an adverse lipid profile, certain dietary patterns and Higher PEL and MEL among schoolchildren in Turkey. These findings underline the possible role of social status, indicated by the degree of education of both parents, in developing certain health behaviors and health indices among Turkish children and provide some guidance for Public Health Policy.

Educational levelparentsadolescentscholesteroldeveloping countrydietphysical activity
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Background
Cardiovascular disease (CVD) is the primary cause of mortality in developed countries and generates a major burden of morbidity throughout life [1,2]. Additionally, CVD emergencies have become the leading cause of death in developing countries as well [3,4]. Prospective and retrospective studies have shown that CVD risk factors, namely obesity, the lipid profile, unhealthy diets and sedentary lifestyle, have their roots in childhood and tend to track into adulthood [5-8]. Therefore, early identification and understanding of behavioral and physiological variables related to CVD are essential, so that appropriate interventions can be targeted to children, minimizing the risk of developing the disease later in life.

The continuing modernization and technological advancement of the developing world has brought about rapid lifestyle changes (e.g. fast-food culture, caloric dense diets, sedentary lifestyle), which are known to have a major impact on the development of CVD and other chronic diseases [8,9]. Many investigators have pointed out social and economic status differences, indicated either by the type of school attended (i.e. public vs. private), by the region of residence (i.e. rural vs. urban), or by the level of parental education (primary school vs. University) as important determinants that appear to influence the prevalence of CVD risk factors in both developed and developing world [10-12]. Currently conducted cross-sectional studies have indicated that various socioeconomic factors are inversely associated with CVD morbidity and mortality in developed countries [11,13], while in developing countries, existing data on socioeconomic conditions and the prevalence of CVD are inconsistent [14-16]. The way in which parental educational level seems to exert its effect on health indices and health behaviors differentiates and therefore, should not be considered constant over time and geographic regions [17]. Together health behaviors with social and economic status indices are the outcome of a dynamic and interactive process among several parameters such as education, income, wealth, local culture, beliefs and practices and since none of those parameters stay constant over time and region so do these indices and the way they influence health [18,19]. This observation indicates the need for periodic assessment of these conditions in each population in order to have a clear picture of the social and economic variables and their effects over the populations' health which could effectively guide Public Health Policy in achieving "health for all" and social justice [18].

As far as Turkey is concerned, the available data on the possible effect of parental educational level on the clustering of CVD risk factors among children are limited. Turkey, which has experienced rapid urbanization and industrialization in the past few decades, is a middle-income country, located between Europe and Asia and bordering the Mediterranean, Aegean and Black Seas. The purpose of the present study was to examine the influence of PEL and MEL on CVD risk factors, namely the lipid profile and behavioral indices, among children of Turkey. Expanding our knowledge and understanding on the interrelationship of all these parameters could effectively guide Public Health Policy in early prevention of CVD risk factors in childhood.

Methods
Sampling
The first phase of this cross-sectional study took place during March-May 2001 and the second phase during January-May 2002. The study population consisted of primary schoolchildren aged 12 and 13 years old, living in three urban areas of Turkey, namely Istanbul, Ankara and Izmir. Out of totally 1320 6th grade primary school children registered in the selected schools, 1044 pupils (510 from Istanbul, 289 from Ankara, 245 from Izmir, 49.2% males, 50.8% females) were finally examined. Inclusion of subjects was on a voluntary basis; prior to acceptance, children's parents or guardians were fully informed about the objectives and methods of the study and were asked to sign a consent form.

The study population was selected from nine primary schools (three from each city) using the multi-stage sampling method. Schools were selected taking into consideration the available records of the Ministry of National Education and the National Statistical Center of Turkey, in an attempt to obtain a representative sample from the overall population. In the case of Ankara and Izmir data were collected from three public schools respectively, while in the case of Istanbul sample came from one private and two public schools. All children in the same class were invited to participate in the study to avoid ethical problems.

Approval to conduct this survey was granted by the Ethical Committee of Marmara University and the Turkish Ministry of Education.

Data collection
Baseline data was collected during face-to-face interviews with children by a team of trained personnel. The data collected from the children consisted of physiological indices, namely biochemical and behavioral indices, such as dietary habits, estimation of energy and nutrient intake and physical activity assessment. These data are presented in more detail below.

Demographic characteristics
A coded questionnaire was developed and administered to the study participants, in order to obtain information on socioeconomic conditions and their personal characteristics, such as family size, parental academic qualifications, occupation and car ownership. Both Paternal (PEL) and Maternal Educational Level (MEL) were classified into three categories. "Lower" PEL and MEL corresponded to illiterate, literate with no formal education and to primary school graduates. "Medium" PEL and MEL was attributed to those parents, who had completed junior high school or high school, whereas the category of "Higher" PEL and MEL included parents who possessed a college or a university diploma.

Biochemical indices
Early morning venous blood samples were obtained from each child for biochemical screening tests, following a 12-h overnight fast. Professional staff performed venipuncture, using vacutainers to obtain 10 ml of whole blood. Blood was centrifuged for plasma separation at the local University Hospital and 1.5 ml aliquots were pipetted into plastic Eppendorf tubes and stored at -80°C. When blood collection from each city was completed, all samples were sent to Marmara University, Faculty of Health Education, where the actual biochemical analysis took place.

Total cholesterol (TC) was determined using Allain's method [20], while Fossati's method was used for triglycerides (TG) determination [21]. High Density Lipoprotein-cholesterol (HDL-C) was measured by the heparin-manganese precipitation method. Low Density Lipoprotein-cholesterol (LDL-C) was calculated as follows:

LDL-C = TC - (HDL-C + TG/5) [22].

Anthropometrical measurements
Body weight was measured using a digital scale (Seca) with an accuracy of ± 100 g. Subjects were weighed without shoes, in the minimum clothing possible, i.e. underwear. Standing height was measured without shoes to the nearest 0.5 cm with the use of a commercial stadiometer, with the shoulders in relaxed position and arms hanging freely [23]. Body Mass Index (BMI) was calculated by dividing weight (kg) by height squared (m2).

Dietary assessment
Food consumption of children was assessed by the 24-hour recall technique on three consecutive days. Dietary data was collected from children during a face-to-face interview with a trained dietician. Dieticians were trained as a group to minimize inter-observer variation. During the interview, food models and photos of common Turkish dishes of various portions, as well as household cups and measures were used to define amounts, in order to obtain as accurate information as possible, regarding the type and amount of food and beverages consumed during the previous day. Macronutrient and micronutrient intake were calculated using the food database available in Marmara University, Faculty of Health Education. This database contains Turkish food composition tables for all food, including cooked Turkish dishes. Information on processed foods was obtained from food companies and national as well as international fast food chains.

Physical activity assessment
Physical activity during school hours and leisure time was assessed using a standardized physical activity diary completed by the children for two consecutive weekdays and one weekend day. A member of the research team crosschecked diary information during daily interviews. The diary was constructed for searching various physical activities ranging from mild to vigorous [24], while the time spent for each type of activity was recorded in hours.

Activities were classified into two groups, namely Sedentary and Light Activities (< 4 METs) and Moderate to Vigorous Physical Activities (MVPA) (> 4 METs). Typical activities in the Sedentary and Light category were watching TV, board and computer games, studying and extra curricular classes (e.g. music, language), etc. The MVPA category included activities such as walking, bicycling, rhythmic-gymnastics, dancing, basketball, soccer, athletics, tennis, swimming, running up and down, jumping rope and general participation in active outdoors games. Given the age group, MVPA was defined as continuous vigorous activity causing sweating and heavy breathing for periods longer than 15 minutes, but with occasional breaks in intensity, rather than the strict aerobic definition of 20 continuous minutes appropriate for adults.

Statistical analysis
Descriptive statistics of continuous variables were expressed as the Mean ± standard deviation (s.d.), as well as median and 25th and 75th percentile for not normally distributed variables. The 2- sample Z test was used to compare proportions regarding values above normal range among the different categories of parental education for both genders. One- way analysis of variance (ANOVA) with a Tukey post- hoc analysis and multivariate analysis of variance (MANOVA) controlling for certain confounding factors, was conducted to determine whether differences derived from the comparison of continuous variables among the educational categories were statistically significant. For not normally distributed variables the non- parametric univariate Mann-Whitney test was used to verify the statistical significance of the existing differences among the three educational categories. All analyses were conducted using the SPSS 10.0 statistical software package for Windows. In all analyses a 5% significance level was used.

Results
Table 1 summarizes the mean serum lipid values determined for the study participants by gender and parental educational level, as well as the significant differences observed among the three educational level categories. According to these findings Higher PEL and MEL boys and girls were found to have significantly higher mean levels of TC and HDL-C, but lower mean TC to HDL-C ratio, compared to their Medium and Lower PEL and MEL peers. However, after adjusting for sex, energy intake, fat intake, BMI and MVPA some of the differences presented in Table 1 lost their significance (data not shown). More specifically, when PEL was used as a grouping variable HDL-C remained higher for Higher PEL boys and girls, compared to those of Medium PEL (p = 0.010 for boys and p < 0.001 for girls) as well as for Higher PEL girls compared to those of Lower PEL (p < 0.001). A similar observation applied for TC to HDL-C ratio, which remained lower for Lower PEL boys and girls, compared to Medium (p = 0.021 for boys and girls) and to Lower PEL ones (p = 0.022 for boys and p = 0.005 for girls). When mean serum lipid levels where compared on the basis of MEL categories, most of the differences observed in Table 1 lost their significance, since only HDL-C and LDL-C remained higher for Higher MEL boys, compared to Medium (p = 0.018) and to Lower MEL ones (p = 0.020) respectively.

Table 1 Biochemical indices by gender and parental educational level

Father's educational level (PEL)	BOYS		
			
Serum Lipids	Lower (n = 174)	Medium (n = 264)	Higher (n = 95)	p-value (ANOVA)	
TC (mg/dl)	159.7 ± 30.2	167.6 ± 31.6a	169.3 ± 30.9b	0.007	
HDL-C* (mg/dl)	53.8 ± 31.9	54.2 ± 14.7	60.3 ± 15.2b,c	<0.001	
LDL-C cholesterol (mg/dl)	90.3 ± 27.2	95.6 ± 30.0	96.2 ± 29.7	0.930	
Triglycerides* (mg/dl)]	90.6 ± 49.0	85.3 ± 38.0	85.4 ± 43.4	0.568	
TC/ HDL-C ratio	3.23 ± 0.85	3.28 ± 0.98	2.96 ± 0.86b,c	0.011	
	
Mother's educational level (MEL)					
Serum Lipids	Lower (n = 276)	Medium (n = 209)	Higher (n = 46)	p-value (ANOVA)	
	
TC (mg/dl)	162.3 ± 32.1	168.9 ± 29.4a	168.8 ± 34.0	0.036	
HDL-C* (mg/dl)	54.0 ± 15.9	53.7 ± 13.5	60.0 ± 18.0b,c	0.033	
LDL-C cholesterol (mg/dl)	90.9 ± 28.6	97.2 ± 29.1a	99.6 ± 31.8	0.017	
Triglycerides* (mg/dl)]	88.0 ± 45.2	87.2 ± 42.4	85.0 ± 39.1	0.851	
TC/ HDL-C ratio	3.16 ± 0.83	3.34 ± 1.01	3.02 ± 0.97	0.023	
	
Father's educational level (PEL)	GIRLS		
			
Serum Lipids	Lower (n = 164)	Medium (n = 281)	Higher (n = 66)	p-value (ANOVA)	
	
TC (mg/dl)	168.9 ± 29.8	172.0 ± 34.2	175.5 ± 30.5	0.308	
HDL-C* (mg/dl)	51.1 ± 11.5	52.9 ± 12.5	61.5 ± 20.0b,c	<0.001	
LDL-C cholesterol (mg/dl)	103.2 ± 85.4	99.9 ± 32.8	95.5 ± 31.9	0.609	
Triglycerides* (mg/dl)]	95.3 ± 42.3	95.5 ± 49.6	98.1 ± 45.9	0.879	
TC/ HDL-C ratio	3.44 ± 0.84	3.40 ± 0.92	3.06 ± 0.89b,c	0.008	
	
Mother's educational level (MEL)					
Serum Lipids	Lower (n = 259)	Medium (n = 227)	Higher (n = 27)	p-value (ANOVA)	
	
TC (mg/dl)	168.4 ± 32.2	174.2 ± 32.7	179.7 ± 28.1b	0.046	
HDL-C* (mg/dl)	51.6 ± 13.9	54.9 ± 12.8a	56.2 ± 13.7b	0.002	
LDL-C cholesterol (mg/dl)	100.6 ± 72.0	99.8 ± 33.0	107.4 ± 26.3	0.799	
Triglycerides* (mg/dl)]	95.2 ± 42.1	97.4 ± 51.9	81.5 ± 35.1	0.194	
TC/ HDL-C ratio	3.41 ± 0.85	3.32 ± 0.93	3.38 ± 0.95	0.488	
a p < 0.05 Medium SES vs. Low SES

b p < 0.05 High SES vs. Low SES

c p < 0.05 High SES vs. Medium SES

* Parameter was log transformed.

Table 2 presents the proportions of children with serum lipid levels above the cut-off points, proposed by the NCEP [25]. According to these findings the prevalence of children found to be in "borderline or high risk" according to their TC and LDL-C serum levels, was significantly higher in Higher PEL and MEL boys and girls, compared to their Medium and Lower PEL and MEL peers, respectively. Furthermore, the prevalence of children with HDL-C levels below 35 mg/dl was found to be lower in Higher PEL boys, compared to those of Medium and Lower PEL.

Table 2 Percentage of children characterized as "borderline or high risk" by gender and parental educational level.

Father's educational level (PEL)	BOYS	GIRLS	
		
Borderline or High Risk	Lower % (n = 174)	Medium % (n = 264)	Higher % (n = 95)	Lower % (n = 164)	Medium % (n = 281)	Higher % (n = 66)	
TC ≥ 170	32.0	43.6a	49.5b	45.4	50.2	60.6b	
LDL-C ≥ 110	21.4	28.0	25.3	33.2	37.7	30.3	
HDL-C<35	7.8	5.7	0.0b,c	6.1	4.5	3.0	
TC/ HDL-C>4.5	9.7	9.1	5.3	10.7	10.9	9.1	
	
Mother's educational level (MEL)							
Borderline or High Risk	Lower % (n = 276)	Medium % (n = 209)	Higher % (n = 46)	Lower % (n = 259)	Medium % (n = 227)	Higher % (n = 27)	
	
TC ≥ 170	36.2	45.7a	50.0	45.1	54.8a	70.4b	
LDL-C ≥ 110	21.2	29.8a	32.6	32.5	38.0	40.7	
HDL-C<35	5.8	6.5	0.0	6.8	4.9	5.7	
TC/HDL-C>4.5	7.4	11.0	8.7	8.5	12.2	14.8	
* Lipids cut-off points in mg/ dl (according to NCEP)

a p < 0.05 Medium SES vs. Low SES

b p < 0.05 High SES vs. Low SES

c p < 0.05 High SES vs. Medium SES

Dietary and physical activity characteristics of the under study population are reported in Tables 3 and 4. Both boys and girls with Higher PEL were found to have higher intakes of energy derived from fat and protein than Lower and Medium PEL boys (p = 0.002 and p = 0.021) and girls (p = 0.007 and p = 0.010) respectively. Regarding boys of Higher MEL, they were found to have lower total energy intake (p = 0.005) but higher percentages of energy derived from fat (p = 0.002) and protein (p = 0.001), compared to boys of Lower and Medium MEL. The percentage of energy derived from fat was also found to be higher for Medium and Higher MEL girls, compared to those of Lower MEL (p = 0.001). On the other hand the contribution of carbohydrates to the total daily energy intake was found to be higher for Lower MEL boys (p = 0.025) and girls (p = 0.001), compared to Medium and Higher MEL children. With the exception of MVPA, which was found to be higher only for Medium MEL boys, compared to Lower MEL ones (P < 0.05), no other statistically significant differences were observed.

Table 3 Energy and macronutrient intakes by gender and parental educational level.

Father's educational level (PEL)	BOYS		
			
Dietary Indices	Lower (n = 171)	Medium (n = 266)	Higher (n = 99)	p-value (ANOVA)	
Energy Intake* (Kcal/ day)	2031.4 ± 556.1	2017.7 ± 603.5	1952.3 ± 642.9	0.373	
Fat Intake (%)	29.7 ± 7.2	30.2 ± 6.3	32.4 ± 5.5b,c	0.002	
Protein Intake (%)	13.3 ± 2.3	13.3 ± 2.6	14.1 ± 2.5b,c	0.021	
CHO Intake (%)	40.0 ± 10.9	39.3 ± 10.5	39.9 ± 9.3	0.739	
	
Mother's educational level (MEL)					
Dietary Indices	Lower (n = 274)	Medium (n = 213)	Higher (n = 46)	p-value (ANOVA)	
	
Energy Intake* (Kcal/ day)	2000.7 ± 546.9	2059.6 ± 650.8	1754.8 ± 557.5b,c	0.005	
Fat Intake (%)	29.7 ± 6.6	30.6 ± 6.4	33.2 ± 6.9b,c	0.002	
Protein Intake (%)	13.3 ± 2.4	13.4 ± 2.6	14.8 ± 2.8b,c	0.001	
CHO Intake (%)	41.1 ± 8.6	40.6 ± 10.7	38.4 ± 10.2b	0.025	
	
Father's educational level (PEL)	GIRLS		
			
Dietary Indices	Lower (n = 157)	Medium (n = 278)	Higher (n = 73)	p-value (ANOVA)	
	
Energy Intake* (Kcal/ day)	1913.3 ± 562.9	1926.8 ± 585.8	1796,0 ± 413,0	0.414	
Fat Intake (%)	30.5 ± 6.7	31.0 ± 6.3	33,2 ± 6,4b,c	0.007	
Protein Intake (%)	12.9 ± 2.6	12.9 ± 2.5	13,8 ± 2,2b,c	0.010	
CHO Intake (%)	38.4 ± 11.5	36.7 ± 10.4	36,6 ± 7,9	0.189	
	
Mother's educational level (MEL)					
Dietary Indices	Lower (n = 260)	Medium (n = 220)	Higher (n = 31)	p-value (ANOVA)	
	
Energy Intake* (Kcal/ day)	1889,3 ± 554,7	1915.5 ± 533.4	1780.2 ± 609.5	0.404	
Fat Intake (%)	30,2 ± 6,5	31.9 ± 6.5a	33.4 ± 6.5b	0.001	
Protein Intake (%)	12,8 ± 2,4	13.0 ± 2.6	13.6 ± 2.3	0.260	
CHO Intake (%)	38,8 ± 11,2	35.7 ± 9.6a	35.4 ± 10.0	0.001	
a p < 0.05 Medium SES vs. Low SES,

b p < 0.05 High SES vs. Low SES,

c p < 0.05 High SES vs. Medium SES

* Parameter was log transformed

Table 4 Physical activity by gender and parental educational level.

Father's educational level (PEL)	BOYS	GIRLS	
			
Physical Activity	Lower (n = 174)	Medium (n = 267)	Higher (n = 94)	Lower (n = 157)	Medium (n = 281)	Higher (n = 71)	
MVPA (hours/week)	Median (25th – 75th percentile)	6.7 (2.3–11.1)	7.0 (3.5–11.6)	7.0 (3.2–11.6)	2.3 (0.0–7.0)	3.5 (0.0–7.0)	1.2 (0.0–7.0)	
	Mean ± SD	7.3 ± 6.4	7.9 ± 6.1	7.6 ± 6.4	4.1 ± 4.4	4.2 ± 4.5	4.0 ± 5.3	
	
Mother's educational level (MEL)							
Physical Activity	Lower (n = 273)	Medium (n = 214)	Higher (n = 45)	Lower (n = 260)	Medium (n = 222)	Higher (n = 30)	
	
MVPA (hours/week)	Median (25th – 75th percentile)	5.8 (2.3–10.5)	8.1a (3.5–11.6)	5.8 (2.3–8.1)	2.3 (0.0–7.0)	3.5 (0.0–7.0)	0.6 (0.0–5.2)	
	Mean ± SD	7.2 ± 6.4	8.2 ± 6.1a	6.7 ± 5.8	3.8 ± 4.3	4.4 ± 4.8	3.5 ± 5.0	
a p < 0.05 Medium SES vs. Low SES (Mann Whitney test).

Discussion
Despite the traditional notions of CVD as a Western disease of "affluence", more than three quarters of global CVD mortality now occurs in middle- and lower- income nations (WHO, 2001) [26]. Furthermore, progression of CVD as well as the risk factors and health behaviors leading to this medical condition seem to be related with various social and economic indices for both adults and children [11,27]. However, prevention seems to be the most effective way to treat CVD and since the roots of the disease are located in childhood, early detection and management of the related risk factors should begin at that age [27,28].

According to the findings of the current study there was a higher prevalence of "borderline or high risk", with respect to TC levels, for children with Medium and Higher parental educational level (Table 2). Several other investigators, who have conducted analogous epidemiological surveys in other developing nations, such as in Philippines, Costa Rica and Iran [29-31], have confirmed these alarmingly high prevalence rates among children living under the supervision and care of better educated parents. Furthermore, in contrast with Western populations where TC levels are often inversely associated with income and education [32,33], but in consistency with several other studies conducted in recent years in Turkey the findings of the current one indicated a positive effect of parental education on serum TC levels [34,35]. The same trend applied for HDL-C levels since, in consistency to the findings of Mahley et al. (2001) [34] for upper socioeconomic status prepubescent subjects, the present study showed that children with Medium and Higher PEL and MEL were found to have higher serum levels of this lipoprotein than those with Lower PEL and MEL.

The effect of diet on serum lipids and lipoproteins has been extensively studied in various clinical trials and epidemiological studies, and although dietary content is clearly an important determinant, several environmental and metabolic factors intervene to modulate the dietary effect (36). Previously conducted surveys in urban regions of Turkey have provided strong evidence that children coming from more affluent and/or well-educated families consumed diets higher in animal protein and fat, while the typical diet of less privileged children was rich in carbohydrates, including cereal grains and sugar (37). These findings, regarding the macronutrient content of the consumed diet, are in consistency with the current study, since children from Medium and Higher PEL and MEL were found to consume higher percentage of energy derived from fat and protein, while the opposite was observed for carbohydrate intake (Table 3). Based on the existing literature (38) we could safely speculate that higher intake of fat, especially saturated, and of protein, originating mostly from animal products, could explain the more unfavorable lipidemic profile, with respect to TC and LDL-C serum levels, among children with Higher PEL and MEL. Additionally the lower HDL-C levels and the higher TC to HDL-C ratio reported for children of Lower PEL and MEL could probably be attributed to the higher ratio of carbohydrates constituting their diet. Indeed the percentage of energy derived from carbohydrates has been inversely associated with HDL-C levels according to the results from several other studies [39,34].

Regarding physical activity, it is well established that higher levels of physical activity are associated with higher HDL-C and lower TC to HDL-C ratio values in both children and adolescents [40-42]. However the current study, in agreement to similar findings of Mahley et al (2001) [34], has not revealed any significant differences with respect to MVPA among children of different PEL and MEL. Still, of great interest are the differences observed in physical activity levels between genders. The present study in consistency with many other studies conducted in the developed world [43-45] revealed that boys were found to devote more time on MVPA than girls. This gender differentiation in physical activity levels should not be attributed to physiological differences between the two sexes but to social and cultural beliefs of parents and teachers as to the types of activities appropriate for boys and girls. Family and society have been shown to influence the level and type of physical activity, girls are engaged in and therefore may determine the lifetime habits with respect to habitual physical activity [45].

The findings of the current study are in agreement with previous surveys conducted in Turkey indicating that parental education, either as a single estimate of social status or combined with other social and/or economic indices, is a "reliable index" of socioeconomic status [34,46]. Both indices (PEL and MEL) utilized in the present study provided similar findings regarding the differences on children's serum lipid levels. These could probably be attributed to dietary differences, since no significant differences were reported for physical activity. Furthermore, higher percentage of energy derived from fat and protein recorded for Higher PEL and MEL children, compared to those with Lower PEL and MEL, in conjunction with the opposite finding regarding carbohydrates, is in agreement with previous studies indicating "limited" access to food by children of lower socioeconomic status [46]. These findings may provide some indication that less privileged children are not only under a greater risk of undernourishment but furthermore, by having a higher ratio of TC to HDL-C, that they combine, at the same time, a high prevalence of a health risk index of affluence. However, due to its cross sectional design the present study could not establish causal-effect relationships, but only generate hypothesis about the possible role of parental education on certain CVD risk factors. Another limitation that has to be considered is the fact that the study's focus was on certain biochemical and behavioral indices, since it has not included other important CVD risk factors such as fasting glucose, insulin, blood pressure and smoking habits.

The underlying influence of socio-economic status on health status is far more complex than diet and physical activity alone, since many other factors interact in producing the differences observed for serum lipids or other health indices. Based on the data provided by the current study it could be concluded that the differences regarding the lipidemic profile of children with different parental educational level could possibly be attributed to the differences observed on their dietary and macronutrient intake. Any attempt for the development and implementation of a health and education programme should consider these findings and set priorities accordingly. However further research is needed in order to develop an effective index for assessing socioeconomic level, as well as in better understanding its multidimensional role on public health. All these will help the public health authorities to develop effective strategies, which will efficiently tackle these health issues early in life.

Pre-publication history
The pre-publication history for this paper can be accessed here:



Acknowledgements
This study was supported with a research grant from Kellogg Europe and Bogazici University Research Fund.
==== Refs
Diet, nutrition and the prevention of chronic diseases Journal 2003 916 1 149 backcover 
Labarthe DR  Epidemiology and prevention of cardiovascular diseases: a global challenge 1998 Gaitherburg, MD: Aspen Publishers 
Bhatnagar D  The metabolic basis of increased coronary risk attributed to people from the Indian sub- continent Curr Sci 1998 74 1087 1094 
Minh HV Byass P Wall S  Mortality from cardiovascular diseases in Bavi District, Vietnam. Scand Scand J Public Health 2003 26 31 14649634 10.1080/14034950310015077 
Guo SS Huang C Demerath E Towne B Chumlea WC Siervogel RM  Body mass index during childhood, adolescence and young adulthood in relation to adult overweight and adiposity: the Fels Longitudinal Study Int J Obes Relat Metab Disord 2000 24 1628 1635 11126216 10.1038/sj.ijo.0801461 
Eriksson JG Forsen T Tuomilehto J Osmond C Barker DJ  Early growth and coronary heart disease in later life: longitudinal study BMJ 2001 322 949 953 11312225 10.1136/bmj.322.7292.949 
Kelder SH Peryy CL Klepp KI Lytle LL  Longitudinal tracking of adolescent smocking, physical activity and food choice behaviors Am J Public Health 1994 84 1121 1126 8017536 
Beaglehole R  Cardiovascular diseases in developing countries, an epidemic that can be prevented BMJ 1992 305 1170 1171 1467714 
Callabero B  Symposium: Obesity in Developing Countries: Biological and Ecological Factors J Nutr 2001 866 870 11238776 
Winkleby MA Cubbin C Ahn DK Kraemer HC  Pathways by which SES and ethnicity influence cardiovascular disease risk factors Ann N Y Acad Sci 1999 896 191 209 10681898 
Kaplan GA Keil JE  Socioeconomic factors and cardiovascular disease: a review of the literature Circulation 1993 88 1973 1998 8403348 
Bunker CH Ukoli FA Okoro FI Olomu AB Kriska AM Huston SL Markovic N Kuller LH  Correlates of serum lipids in a lean black population Atherosclerosis 1996 123 215 225 8782852 10.1016/0021-9150(96)05810-8 
Winkleby MA Jatulis DE Frank E Fortmann SP  Socio-economic status and health: how education, income and occupation contribute to risk factors for cardiovascular disease Am J Public Health 1992 82 816 820 1585961 
Gupta R Gupta VP Ahluwalia NS  Educational status, coronary heart disease, and coronary risk factor prevalence in a rural population of India BMJ 1994 309 1332 1336 7866081 
Sorlie PD Garcia-Palmieri MR  Educational status and coronary heart disease in Puerto Rico: The Puerto Rico Heart Health program Int J Epidemiol 1990 19 59 65 2351525 
Zhijie Yu Aulikki Nissinen Erkki Vartiainen Gang Hu Huiguang Tian Zeyu Guo  Socio-economic status and serum lipids: A cross sectional study in a Chinese urban population J Clin Epidemiol 2002 55 143 149 11809352 10.1016/S0895-4356(01)00451-6 
Lynch J Davey Smith G Harper S Hillemeier M  Is income inequality a determinant of population health? Part 2. US National and regional trends in income inequality and age-and cause- specific mortality The Milbank Quarterly 2004 82 355 400 15225332 10.1111/j.0887-378X.2004.00312.x 
Adler NE Ostrove JM  Socioeconomic status and health: what we know and what we don't Ann N Y Acad Sci 1999 896 3 15 10681884 
Freeman HP  Poverty, culture, and social injustice: determinants of cancer disparities CA Cancer J Clin 2004 54 72 7 15061597 
Allain CC Poon LS Chan CS Richmond W Fu PC  Enzymatic determination of total serum cholesterol Clin Chem 1974 20 470 475 4818200 
Fossati P Prencipe L  Serum triglycerides determined colorimetrically with an enzyme that produces hydrogen peroxide Clin Chem 1982 28 2077 2080 6812986 
Friedewald WT Levy RI Fredrickson DS  Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge Clin Chem 1972 18 499 502 4337382 
Lohman TG Roche AF Mastorell R  Anthropometric standardization reference manual: 1991 Champaign, IL: Human Kinetics Publishers 
Pereira MA FitzerGerald SJ Gregg EW Joswiak ML Ryan WJ Suminski RR Utter AC Zmunda JM  A collection of Physical Activity Questionnaires for health-related research Med Sci Sports Exerc 1997 29 1 205 9243481 
National Cholesterol Education Program (NCEP)  highlights of the report of the Expert Panel on Blood Cholesterol Levels in Children and Adolescents Pediatrics 1992 89 495 501 1741227 
WHO  Cardiovascular diseases. Prevention and control 2001 Geneva: World Health Organization 
Tyroler HA  The influence of socioeconomic factors on cardiovascular disease risk factor development Prev Med 1999 29 S36 40 10641816 10.1006/pmed.1998.0441 
Labarthe DR  Prevention of cardiovascular risk factors in the first place Prev Med 1999 29 S72 8 10641821 10.1006/pmed.1999.0539 
Kuzawa CW Adair LS Avila JL Cadungog JH Le NA  Atherogenic lipid profiles in Filipino adolescents with low body mass index and low dietary fat intake Am J Human Biol 2003 15 688 696 12953181 10.1002/ajhb.10200 
Monge-Rojas R  Serum lipids and lipoprotein levels in Costa Rican 13–18 year-old teenagers Arch Latinoam Nutr 2001 51 236 243 11791476 
Azizi F Rahmani M Madjid M Allahverdian S Ghanbili J Ghanbarian A Hajipour R  Serum lipid levels in an Iranian population of children and adolescents: Tehran lipid and glucose study Eur J Epidemiol 2001 17 281 288 11680549 10.1023/A:1017932212350 
Liu K Cedres LB Stamler J Dyer A Stamler R Nanas S Berkson DM Paul O Lepper M Lindberg HA Marquardt J Stevens E Schoenberger JA Shekelle RB Collette P Shekelle S Garside D  Relationship of education to major risk factors and death from coronary heart disease, cardiovascular diseases and all causes, Findings of three Chicago epidemiologic studies Circulation 1982 66 1308 14 6814786 
Winkleby MA Jatulis DE Frank E Fortmann SP  Socioeconomic status and health: how education, income, and occupation contribute to risk factors for cardiovascular disease Am J Public Health 1992 82 816 20 1585961 
Mahley RW Arslan P Pekcan G Pepin GM Agacdiken A Karaagoglu N Rakicioglu N Nursal B Dayanikli P Palaoglu KE Bersot TP  Plasma lipids in Turkish children: impact of puberty, socioeconomic status, and nutrition on plasma cholesterol and HDL Journal of Lipid Research 2001 42 1996 2006 11734572 
Mahley RW Palaoglu KE Atak Z Dawson-Pepin J Langlois AM Cheung V Onat H Fulks P Mahley LL Vakar F  Turkish Heart Study: lipids, lipoproteins, and apolipoproteins J Lipid Res 1995 36 839 59 7616127 
Kaplan GA Keil JE  Socioeconomic factors and cardiovascular disease: a review of the literature Circulation 1993 88 1973 98 8403348 
Kocaoglu BA  Effects of Socioeconomic conditions on Growth, Developmentand Obesity among Adolescents in Turkey PhD Dissertation 1996  Institute of health Science, Nutrition and Dietetics Programme, Hacettepe University, Ankara, Turkey 
Mensink RP Katan MB  Effect of dietary fatty acids on serum lipids and lipoproteins. A meta-analysis of 27 trials Arterioscler Thromb 1992 12 911 9 1386252 
Knuiman JT West CE Katan MB Hautvast JG  Total cholesterol and high density lipoprotein cholesterol levels in populations differing in fat and carbohydrate intake Arteriosclerosis 1987 7 612 9 3318781 
Raitakari OT Taimela S Porkka KV Telama R Valimaki J Akerblom HK Viikari JS  Association between physical activity and risk factors for coronary heart disease: the Cardiovascular Risk in Young Finns Study Med Sci Sports 1997 29 1055 1061 
Tolfley K Campell IG Batterham AM  Exercise training induced alterations in prepubertal childrens' lipid-lipoprotein profile Med Sci Sports Exerc 1998 30 1684 1692 9861600 10.1097/00005768-199812000-00005 
Tolfley K Jones AM Campell IG  The effect of aerobic exercise training on the lipid- lipoprorein profile of children and adolescent Sports Med 2000 29 99 112 10701713 
Manios Y Yiannakouris N Papoutsakis C Moschonis G Magkos F Skenderi K Zampelas A  Behavioral and physiological indices related to BMI in a cohort of primary schoolchildren in Greece Am J Hum Biol 2004 16 639 47 15495234 10.1002/ajhb.20075 
Guillaume M Lapidus L Bjorntorp P Lambert A  Physical activity, obesity and cardiovascular risk factors in children: the Belgium Luxembourg Child Study II Obes Res 1997 5 549 556 9449139 
Manios Y Kafatos A Codrington C  Gender differences in physical activity and physical fitness in young children in Crete J Sports Med Phys Fitness 1999 39 24 30 10230165 
Keskin Y Moschonis G Dimitriou M Sur H Kocaoglu B Hayran O Manios Y  Prevalence of iron deficiency among schoolchildren of different socio-economic status in urban Turkey Eur J Clin Nutr 2005 59 64 71 15280908 10.1038/sj.ejcn.1602035

