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| Year : 2013
| Volume
: 15 | Issue : 65 | Page
: 253-260 |
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| Blood pressure of urban school children in relation to road-traffic noise, traffic density and presence of public transport |
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Katarina Paunovic, Goran Belojevic, Branko Jakovljevic
Institute for Hygiene and Medical Ecology, Faculty of Medicine, University of Belgrade, Serbia
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| Date of Web Publication | 15-Jun-2013 |
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The aim of the study was to investigate the relationship between noise levels, traffic density and the presence of public transport and children's blood pressure. Another aim was to assess the applicability of public transport as a proxy indicator of noise exposure. A cross-sectional study involved 1113 children aged 7-11 years from a central municipality in Belgrade. Equivalent noise levels were measured in front of all schools and in the middle of all streets. Traffic density was defined as number of light and heavy vehicles per hour. The number of public transport vehicles was calculated from official timetables. Children's addresses were matched with noise levels and transport maps. A physician measured blood pressure with the sphygmomanometer. Children attending schools with public transport running nearby had by 1.3 mmHg higher systolic pressure than did children from schools without public transport. This relationship was independent from children's age, gender, and body mass index, family history of hypertension, some dwelling characteristics, and lifestyle habits. The association between diastolic pressure and public transport was statistically insignificant. The study indicated a possible positive association between the presence of public transport in the vicinity of schools with systolic blood pressure in 7-11 year-old schoolchildren. The presence of public transport may serve as an auxiliary indicator of noise exposure in undeveloped countries with limited capacities for noise measurement or modeling. Keywords: Blood pressure, child, noise, public transport
How to cite this article:
Paunovic K, Belojevic G, Jakovljevic B. Blood pressure of urban school children in relation to road-traffic noise, traffic density and presence of public transport. Noise Health 2013;15:253-60 |
How to cite this URL:
Paunovic K, Belojevic G, Jakovljevic B. Blood pressure of urban school children in relation to road-traffic noise, traffic density and presence of public transport. Noise Health [serial online] 2013 [cited 2023 Jun 1];15:253-60. Available from: https://www.noiseandhealth.org/text.asp?2013/15/65/253/113521 |
| Introduction | |  |
Road-traffic noise is becoming a serious problem in Serbia. Public Health Institute in Belgrade has reported a steady increase of noise levels in Belgrade in the last 30 years. [1] Measured noise levels constantly exceed the values stipulated by the national regulations by 10-20 dBA (A-weighted decibel unit). [2] Nowadays, 1.5 million inhabitants of Belgrade use some means of transport approximately 3 million times/day, either by passenger cars or by riding in public transport. [3] Public transport in Belgrade comprises 1205 vehicles (buses, trams and trolleybuses), travelling on 139 lines throughout the city area, within a network almost 1.800 km long. [4] There is no subway system in Belgrade at the present.
Road-traffic noise is a possible risk factor for arterial hypertension among adults in Serbia. [5] Exposure to road-traffic noise increases blood pressure levels in Belgrade preschool children, [6] and school children. [7],[8] Some studies supported a positive correlation between children's blood pressure and road-traffic noise, [9],[10] whereas others found no association, [11] or a negative one. [12]
In previous epidemiological studies, noise exposure was assessed by matching the place of exposure with measured or modeled noise levels. [13] Nevertheless, researchers have rarely reported any other traffic characteristic, such as traffic density (number of vehicles), type of vehicles, or presence and type of public transport. We have decided to undertake this study using noise levels, traffic density and presence of public transport as exposure indicators and to explore their similarities, differences and applicability in future surveys.
The aim of this study was to investigate the relationship between children's blood pressure and noise exposure indicators, such as noise levels, traffic density, and presence of public transport. Another aim was to assess the applicability of public transport as a proxy indicator of noise exposure.
| Methods | | |
Study sample
A cross-sectional study was conducted in the municipality Stari grad, located in the centre of Belgrade. This municipality is an administrative and residential area with road traffic as a principal source of noise. In total, eight public primary schools are located in this municipality [Figure 1]. Investigators contacted children aged 7-11 years (1 st to 4 th grade) and their parents through school boards. Out of 2000 interviewed parents, 1150 (57.5%) returned the questionnaires with the signed approval for examination of their children. One week prior to the examination children received information sheets explaining the purpose of the study and the measurement protocol. In addition, physician explained the procedure in the classroom on the day of the examination. Children gave their written consent for participating in this study. Ethics Committee of the Faculty of Medicine in Belgrade approved the study.
The only exclusion criterion was the presence of chronic diseases affecting arterial blood pressure (diabetes mellitus, heart or kidney diseases). Apart from pupils with diabetes (n = 3) and those absent from school at the day of examination (n = 34), the final sample consisted of 1113 children (533 boys and 580 girls). | Figure 1: The location of schools in the investigated municipality Stari grad. 1 - School "Braća Baruh", no public transport, equivalent noise level = 57.0 dBA, 2 - School "Vuk Karadžić", public transport (bus plus tram), equivalent noise level = 70.1 dBA, 3 - School "Drinka Pavlović", no public transport, equivalent noise level = 64.5 dBA, 4 - School "Kralj Petar Prvi (first building)", no public transport, equivalent noise level = 65.0 dBA, 5 - School "Kralj Petar Prvi (second building)", no public transport, equivalent noise level = 68.1 dBA, 6 - School "Mihailo Petrović Alas", no public transport, equivalent noise level = 60.2 dBA, 7 - School "Skadarlija", public transport (bus), equivalent noise level = 72.3 dBA, 8 -School "Stari grad", no public transport, equivalent noise level = 58.3 dBA
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Noise measurements
Noise levels were measured in front of all eight schools and in all 115 streets of this municipality during September and October 2008. Hand-Held noise level analyzer type 2250 "Brüel and Kjær" was used, according to recommendations of International Standard Organization for the measurement of community noise (ISO, 1982). Noise levels around schools were measured on working days during lessons in two morning intervals (between 9 a.m. and 11 a.m., and between noon and 2 p.m.) and one afternoon interval (between 3 p.m. and 5 p.m.). Furthermore, noise levels were measured in the middle of all the streets where children lived, as close as possible to their homes. Noise was measured in two intervals during the day (between 10 a.m. and noon, and between 2 p.m. and 4 p.m.), in one evening interval (between 6 p.m. and 8 p.m.), and in two night intervals (between 10 p.m. and 12 p.m., and between midnight and 2 a.m.). The instrument was positioned on the pavement near the road; the time interval of each measurement was 15 min; the speed of sampling was 10/sec, with 9000 samples collected per measurement. Noise measurements were performed on several working days for each school; the measurements took place a few weeks after the examination of children in order to avoid researcher bias related to awareness of noise levels and traffic density.
A composite daytime equivalent noise level (L eq ) was calculated for each school; a composite daytime and night time L eq levels were calculated for each street from the obtained emission noise values. We were not able to measure noise levels in the streets of other municipalities in Belgrade; these values were missing for 288 children. Noise exposure was assessed for each child by linking their home and school addresses to the obtained composite L eq at homes and schools.
Traffic density and public transport
Traffic density was defined as the number of light vehicles (motorbikes, motors and cars) and heavy vehicles (vans, trucks, lorries, buses, trams, and trolleybuses) in front of every school and in all streets of this municipality. The number of vehicles was counted simultaneously with noise measurements, i.e., for 15 min/measurement per street. In total, three measurements were made for each school, and five measurements for each street. An average value per hour was calculated for schools and homes separately.
The official public transport maps in Belgrade show that 24 out of total 139 public transport lines run through the selected municipality, including 5 out of 12 tram lines, 7 out of 8 trolleybus lines and 12 out of 119 bus lines. [4] We assessed the presence of public transport by matching children's home and school addresses with these maps. Public transport included buses, trams, trolleybuses, and their combinations. We considered the routes of all daily lines, but not of the night lines. Data were missing for 24 children whose home addresses were unknown.
The number of public vehicles running in the investigated streets and near schools was calculated from original timetables of all transport lines. [4] First, for each transport line, we calculated the number of vehicles passing per hour. Second, we doubled this number, accounting that traffic runs in both directions. Finally, we added the number of vehicles of all lines passing by the investigated streets and schools.
Based on the presence of public transport in the vicinity of children's homes and schools, four groups were created: (1) No public transport near home and no public transport near school (n = 610, 287 boys and 323 girls); (2) Public transport near home and No public transport near school (n = 206, 102 boys and 104 girls); (3) No public transport near home and Public transport near school (n = 190, 92 boys and 98 girls); and (4) Public transport near home and Public transport near school (n = 83, 40 boys and 43 girls). The term "near" meant "passing along the street" where children's homes or schools were located.
Questionnaire
Parents provided information about their children in a self-report questionnaire. It covered basic socio-demographics, such as child's age, gender (coded as: 0 - girl, 1 - boy); mother's education (coded as: 1 - primary school, 2 - secondary school, 3 - university); perceived family income (coded as: 1 - insufficient, 2 - sufficient, 3 - more than sufficient); cases of hypertension among parents (confirmed diagnosis or using medicines for hypertension); child's general health, and diseases related to arterial hypertension (diabetes, heart or kidney diseases). Dwelling characteristics included the orientation of child's room (coded as: 1 - facing the street vs. 0 - away from the street), and types of windows in child's room (coded as: 1 - single-glazed vs. 0 - double-glazed). Children gave information on their practicing physical activities outside the school (number of trainings/week), and the time they spent watching television (h/day). Children's eating habits included consumption of soft drinks (number of glasses/day of Coca-Cola, Fanta, Sprite etc.; a glass contains about 250 ml), and frequency of eating snacks (fast food, crisps etc.; coded as: 0 - rarely (1 to 3 times/month), and 1 - often (2-7 times/week).
In addition, researchers noted sound insulation in schools (coded as: 1 - single-glazed windows-defined as windows built with one glass panel vs. 0 - double-glazed windows-defined as windows built with two glass panels).
Anthropometrics
All measurements were performed in the morning in the school setting. The average temperature in the classroom during the examination was 20°C (range 19°C-24°C). Physicians measured children during classes, but not immediately after physical activity or play in the schoolyard. Children who had no breakfast and those apparently anxious/annoyed/distressed by examination were asked to return for measurement another day.
Body height was measured to the nearest 0.5 cm. Body weight was measured on a digital scale to the nearest 0.1 kg. Children were measured in light clothes and barefoot. Body mass index (BMI) was calculated from body weight in kilograms and squared body height in meters. Software available on the website of the Centers for Disease Control and Prevention was used to calculate BMI-for age-percentiles. [14]
Blood pressure measurement
A physician measured children's blood pressure with the mercury sphygmomanometer "Fazzini", Italy. This instrument complies with the Directive 93/42/EEC (European Economic Community) of the European Parliament and of the Council concerning medical devices. Cuff sizes of 7.5 cm × 19.5 cm or 11 cm × 27 cm were used according to arm measurement criteria. [15] All measurements were performed at the same time (between 8 a.m. and noon) in order to control for possible daytime variations of blood pressure. The measurements were performed after a 15-min rest, with the child sitting, their right arm at heart level. Two measurements were performed with a 5-min interval. If the difference between measurements exceeded 5 mmHg, a third measurement was performed; the average value of all readings was calculated. Researchers did not allow children to speak or walk around the room during the measurement session.
The obtained readings were re-categorized into percentiles for systolic blood pressure and diastolic blood pressure separately. These percentiles were obtained from the tables in relation to child's gender, age, and height. [16] Systolic and/or diastolic blood pressures equal or exceeding 95 th percentiles were defined as "high blood pressure."
Statistical analysis
Descriptive statistic was presented as mean values and standard deviation for numeric variables, or as percent's (relative numbers) for categorical variables. Systolic and diastolic pressures were tested by Kolmogorov-Smirnov test. Both observed distributions corresponded to the normal distribution. Multiple linear regressions were applied to assess the relationship between blood pressure values and public transport. For this purpose, public transport was represented by two variables, i.e., public transport near homes, and public transport near schools (both coded as: 0 - not present, 1 - present). To take into account that noise exposure was grouped within schools, mixed linear model procedure was performed. L eq at school were included as a fixed effect. Models included noise levels at schools at daytime, noise levels at home at nighttime, age, gender, BMI, heart rate, mother's education, family history of hypertension, eating snacks, watching television, orientation of child's room toward the street, windows glazing at home, and windows glazing at school. These variables were chosen because they modify blood pressure or noise exposure. As a result, an estimated change of systolic/diastolic pressure for a unit of outcome variables was estimated upon control of all independent variables in the models. Probability level of less than 0.05 was accepted as significant. The authors used SPSS 15.0 for Windows software (SPSS Inc. 1989-2006).
| Results | | |
Noise parameters in the vicinity of schools and children's homes are presented in [Table 1] and [Table 2]. Mean L eq near schools were 8-10 dBA higher than noise levels near schools where there was no public transport [Table 1]. Maximal and minimal noise levels near schools were 5-8 dBA higher than noise levels near schools where there was no public transport. Traffic density was great close to schools where public transport was running. The highest equivalent and maximal noise levels and the highest number of heavy vehicles were reported near schools with buses passing by. The highest number of light vehicles per hour was reported near schools with transport that included both buses and tramlines. "Bus" and "bus plus tram" categories were united for further analysis. The number of public transport vehicles calculated from official timetables accounted for 70-80% of the number of heavy vehicles running near schools [Table 1]. | Table 1: Noise parameters near investigated schools in relation to the presence of public transport
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 | Table 2: Noise parameters near children's homes in relation to the presence of public transport
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L eq near homes with public transport passing nearby were by 5-12 dBA higher than noise levels measured near homes without public transport, at daytime and nighttime [Table 2]. Traffic density was higher in the vicinity of homes with public transport running nearby, particularly buses only. The lowest L eq and the lowest traffic density were recorded in the vicinity of homes where trams passed. All types of public transport were pooled into one category for further analysis due to a small number of children. The number of public transport vehicles obtained from official timetables was similar to the number of heavy vehicles running in the investigated streets [Table 2].
General characteristic of children from four groups were shown on [Table 3]. Children were similar by age, gender, BMI, and some family characteristics. Parental acceptance or refusal to take part in the study was not related to any school, children's grade or class. Systolic blood pressure and heart rate were higher among children attending schools with public transport passing nearby. Diastolic blood pressure and prevalence of high blood pressure were similar among four investigated groups of children. | Table 3: General characteristics of the investigated children in relation to the presence of public transport near homes and schools
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[Table 4] represents the association between blood pressure and noise exposure indicators when adjusted for other variables. Significant predictors of systolic pressure were male gender, BMI, and heart rate (data not shown). Road-traffic noise exposure and presence of public transport were related to an increase in systolic pressure in both models. In Model 1, a statistically insignificant increase of 0.14 mmHg of systolic blood pressure was estimated for an increase of L eq near schools by 1.0 dBA. In Model 2, slight increases of systolic pressure of 1.3 mmHg and 0.7 mmHg were estimated when public transport was running in the vicinity of schools and homes, respectively. Concurrent presence of public transport in both locations corresponded to an increase of systolic pressure by 2 mmHg. The association between systolic blood pressure and public transport near schools was independent of children's age, gender, BMI, family history of hypertension, some dwelling characteristics, and lifestyle habits. | Table 4: The association between blood pressure levels, equivalent noise levels and the presence of public transport
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Significant predictors of diastolic pressure were age, BMI, heart rate, and daily time spent watching television (data not shown). Noise exposure and public transport were related to a decrease in diastolic pressure, but the association was statistically insignificant [Table 4]. In Model 1, a decrease of 0.17 mmHg per 1 dBA L eq measured near schools was estimated. In Model 2, decreases of diastolic pressure of 1.3 mmHg and 0.7 mmHg were estimated when public transport was running in the vicinity of schools and homes, respectively.
| Discussion | | |
The presence of public transport near schools corresponded to a slight increase in children's systolic pressure (by 1.3 mmHg), independent of children's age, gender, BMI, family history of hypertension, physical activity, and eating habits. The association between L eq outside schools and children's systolic pressure was statistically insignificant.
Other studies on the effects of road traffic noise on children's blood pressure reported a variety of contradictory results. The highest difference in systolic blood pressure (by 4-5 mmHg) was observed between children attending noisy and quiet kindergartens in Slovakia and Serbia, [6],[10] and a 2 mmHg difference was reported between children in noisy and quiet schools in a previous pilot study in Belgrade. [8] However, the association between noise exposure at schools and systolic blood pressure was negative in a large RANCH study (Road Traffic and Aircraft Noise Exposure and Children's Cognition and Health). [12]
The presented study did not indicate an exact association between noise levels at children's homes and their blood pressure, contrary to our previous findings. [7] We demonstrated that public transport in the vicinity of children's homes may account for a small increase in systolic pressure (by 0.7 mmHg), in addition to other relevant factors. An approximate 2 mmHg difference in systolic blood pressure was observed between children living in busy-traffic streets and those living in low-traffic streets in Germany. [9] Children exposed to higher levels of noise at homes had up to 2 mmHg higher systolic pressure in an Austrian study; however, the difference was not significant. [17] On the contrary, the RANCH study, [12] and another Austrian study [11] proved negative association between noise exposure in dwellings and children's systolic blood pressure.
Furthermore, this study showed a slight decrease in diastolic pressure in relation to noise exposure and the presence of public transport near schools, but this association was insignificant after adjustment for other parameters. A negative relationship between road-traffic noise and diastolic blood pressure was established in the RANCH study, [12] and no correlation was reported in other studies. [6],[17] However, children in Slovakia attending noisy kindergartens had up to 4-5 mmHg higher diastolic pressure than did children from quiet kindergartens. [10] Pilot studies in Belgrade reported a 2 mmHg difference in diastolic pressure among children from noisy schools and noisy dwellings, in comparison to those living at quiet locations. [7],[8] In Germany, children living in streets with busy traffic had by 1.0 mmHg higher diastolic pressure than did children living in streets with little traffic. The difference, however, was not significant. [9]
Several factors may explain a positive impact of noise exposure on systolic pressure and a negative one on diastolic pressure. First, noise-related changes of blood pressure may be masked by children's age, gender and body weight. Second, blood pressure changes are small and may arise from measurement error. Third, systolic and diastolic pressures have different regulation pathways, and respond to environmental stimuli in a different way. The main physiological role of systolic pressure is to force blood through the arteries during a heartbeat, affected by sympathetic nervous system, and stress stimuli. [18] The role of diastolic blood pressure is to provide perfusion of peripheral tissues during heart relaxation. [19] Finally, the observed changes in blood pressure are probably not clinically significant during childhood. However, they may indicate an increased physiological reactivity to physical or mental stress, which leads to elevated blood pressure later in life. [20],[21]
The novelty of this study is the introduction of public transport as a noise indicator. We hypothesized that public transport passing by near schools and noise levels outside schools shared similar effects on children's blood pressure. To authors' knowledge, this is a first study where public transport near schools and homes was assessed by transport maps. In the German Environmental Survey for children, parents of the examined children assessed the streets as low-traffic, moderate-traffic, heavy-traffic side-streets or busy main roads. [9] Contrary to this subjective measure, we believe that public transport can be an objective, easily accessible, and relatively stable estimate of noise exposure in small urban areas.
Several traffic characteristics are applied in noise mapping. Traffic density, defined as the number of vehicles passing per hour, was an independent noise indicator in some studies. [22],[23] The number of vehicles recorded in this study was much smaller than the number in other countries, i.e., Pakistan. [24] On the contrary, average noise levels measured in the vicinity of the investigated schools were higher than were levels in other countries. Average noise levels measured outside primary schools ranged from 48 dBA to 53 dBA (in London, Amsterdam and Madrid), [25] to 57 dBA (in another study in London), [26] up to 70 dBA (in Spain). [27]
An increase of overall traffic (light and heavy vehicles) was reported in the streets where public transport was passing; this was expected because these streets represent the main roads in the city center. We did not examine the effects of light and heavy vehicles separately, keeping in mind the total sound energy principle. However, we were able to obtain the number of public transport vehicles for all investigated streets using official timetables. The number of public transport vehicles predicted from timetables accounted for the majority of heavy vehicles counted in the streets. Other heavy vehicles permitted in the city centre include delivery vehicles weighing less than 3.5 tones. In authors' opinion, public transport vehicles produce the highest proportion of sound energy among all vehicles, which justifies the use of public transport as a proxy for traffic density.
Another, a bit unexpected outcome of the study was the lack of association between noise levels, traffic density and public transport near children's homes with children's blood pressure. We propose several explanations for this finding. Children spend more time at home than they do at school, engaged in leisure-time activities, where their exposure to noise remains unknown. Noise levels in clubs, sport centers or on rock concerts may reach up to 110 dBA (15-60 min L eq ). [28] Home appliances (vacuum cleaners, toys, audio equipment) may emit noise levels up to 110 dB. [29] Noise from other sources (aircraft, neighbourhood or industrial facilities) may additionally affect children's health at home. [12],[25],[30] Exposure to road-traffic noise at home may increase if a child's room faces the street or if the windows have single glazing; this study, however, did not explore this hypothesis. Dwelling characteristics may reflect the socio-economic status of the family. Children from low-income families in the USA lived in noisier homes; [31] a higher proportion of children of lower socio-economic status attended noisy schools in Britain. [32] The presented results differ from these two studies because of an opposite relationship between family income and noise exposure. Families who resided in areas where public transport was not running, more often described their income as insufficient for their needs. Perceived family income is an insufficient indicator of socio-economic status. We used it, however, because we could not obtain objective data, and because it correlated significantly to parental education level, which is a well-established determinant of socio-economic status. [33] Finally, researchers measured blood pressure at schools, not at home. This implies that the survey missed assessing blood pressure variations in different activities. Further investigations and continuous blood pressure readings should examine children's blood pressure related to noise exposure during the whole day.
Another potentially valuable finding was that double-glazing correlated positively to systolic pressure and negatively to diastolic pressure. On one hand, double-glazing may underestimate the effect of noise. On the other, double-glazing was not equally distributed among schools, and the association was no longer significant after statistical control for confounding. Baring in mind that all schools where public transport was running had double-glazed windows, we assumed that these schools had replaced windows previously, in order to reduce noise exposure.
The limitations of the study include a relatively low response rate of 57.5% of eligible children, although school boards, parents and children were informed in detail about the study. However, we were able to cover all primary schools from the selected municipality. Second, we did not take into account other possible sources of noise outdoors (street works or neighborhood noise), or indoors (electrical facilities or human activities). This municipality was chosen because of its central position, stable demographic structure (low immigration ratio due to high property values), relatively high socio-economic level (considered to be the location for the privileged), and absence of aircraft or rail-transport noise. Third, we did not measure noise levels indoors. Fourth, we were not able to control for the location of classrooms, because children change classrooms when taking part in specific activities (art and music, foreign languages, computer skills). We did not take into consideration window opening in classrooms, which may affect noise exposure, but depends on season, weather, and time of day. However, we were able to check the distance from the schools to the streets, since all schools in this metropolitan area are built near the road. Fifth, we did not examine children's hearing. Sixth, we did not control for children's race/ethnicity, because Serbian children are White Caucasian. Seventh, we failed to assess consumption of energy drinks and addition of salt to food, which may affect blood pressure. Nevertheless, such practices may be rare among children under 11 years. On the other hand, this study accomplished to use many relevant parameters, especially children's body composition, physical activity and lifestyle habits. Some of these habits, such as the time spent watching television [34] and the consumption of soft drinks, [35] proved a positive relationship with children's blood pressure at this age. Finally, we are aware that the presented results cannot be easily generalized for use in developed countries guided by noise maps. We propose public transport as a simple, auxiliary noise indicator in small urban areas lacking capacities for noise measurements and modeling. We admit that its application may be limited to public health authorities in undeveloped regions.
The Master Plan of Belgrade by 2021 proposed several goals for development of traffic system network in Belgrade. They include general reduction of traffic, increase of the proportion of public transport in relation to passenger cars, and promotion of walking and cycling. [3] The presented results suggest that public-health policies and noise abatement strategies should directly affect public transport, particularly in school areas. Apart from redirecting public transport away from schools, reducing the number of vehicles and transport lines, old vehicles should be replaced with modern and silent buses, trams or trolleybuses. This may reduce noise in Belgrade and possibly improve health of the whole population.
| Conclusion | | |
This cross-sectional study indicated a possible positive association between the presence of public transport near schools and systolic blood pressure in 7-11 year-old schoolchildren. The presence of public transport may serve as an auxiliary indicator of noise exposure for health risk assessment in undeveloped countries with limited capacities for noise measurement or modeling.
| Acknowledgment | | |
The authors are grateful to Dr. Jelena Iliæ Živojinoviæ, Dr. Milica Apostoloviæ, and Dr. Vesna Stojanov who helped in collecting data for this project. The authors are grateful to Dr. Goran Trajkoviæ who assisted in performing mixed linear model procedure. This research was financially supported by the Ministry of Science of Serbia, Project No. 175078.
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Correspondence Address:
Katarina Paunovic
Institute for Hygiene and Medical Ecology, Faculty of Medicine, University of Belgrade, Dr. Subotica 8, 11000 Belgrade
Serbia
 Source of Support: This research was financially supported by the Ministry of Education, Science and Technological Development of the Republic of Serbia, Project No. 175078, Conflict of Interest: None  | Check |
DOI: 10.4103/1463-1741.113521
[Figure 1]
[Table 1], [Table 2], [Table 3], [Table 4] |
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