Journal of Child and Adolescent Health

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Research Article - Journal of Child and Adolescent Health (2018) Volume 2, Issue 1

The influence of high altitude on the anticipated childhood growth Taif city - Saudi Arabia 2018 :a cross sectional study

*Corresponding Author:
Dr. Mohammed Abdullah G. Alzhrani
College of Medicine Taif University Taif Saudi Arabia
Tel: +966 12 727 2020
E-mail: [email protected]

Accepted date: March 16, 2018

Citation: Alzhrani MA, Almarzoqi GSS, Alzahrani SAS, et al. The influence of high altitude on the anticipated childhood growth Taif city- Saudi Arabia 2018: A cross sectional study. J Child Adolesc Health. 2018;2(1):6-12.

Abstract

Optimal child growth is a crucial goal that should be pursued to guarantee a healthy life for the individuals in a population with a good quality of life. For this purpose, any risk factors that may disturb or affect the normal growth pattern should be recognized. Living at a high altitude is suggested to be one of these factors. In this study, we aimed to explore if there is a relationship between living in high altitude cities like "Taif' and children's growth. Our population was randomly selected from children whose ages range from 5 to 18 years old and who live in "Taif" city. A total of 277 children were included in this study. Information about their anthropometric measurements were collected and compared to the Saudi national growth standard. Results showed that both weight and height of boys were significantly higher than the Saudi national growth standard. And for girls, the weight was significantly higher while the height did not differ significantly from the Saudi national growth standard. These findings do not support the hypothesis that living in high altitude cities like "Taif" can affect child's growth negatively in terms of height and weight.

Keywords

Children, Growth, High altitude, Hypoxia, Weight, Height.

Background

Optimal child growth is a crucial goal that should be pursued to guarantee a healthy life for the individuals in a population with a good quality of life [1]. Many researchers have investigated the growth of children living at high altitude, but the magnitude of high altitudes hypoxia effect on child growth is still not clear [2,3].

Most investigators working in the Andes have found that growth in height and weight is delayed compared to low altitude. Growth at high altitude represents the response to a complex set of environmental conditions, and it is difficult to determine the extent to which any size difference between high and low altitude populations is due to the effect of hypoxia. However, not all morphological structures appear to be equally affected during growth at high altitude [4].

For example, Frisancho and Baker suggest that the growth of the chest dimensions may be accelerated while height and weight appear to be slowed [5].

It is also possible that different stages of the life cycle may be unequally affected during development at high altitude. Periods of rapid growth such as adolescence may be more severely modified than periods of more leisurely growth such as childhood. The extent to which these responses are conditioned by the reduced oxygen pressure of high altitude is unclear. Other factors such as the limited energy availability in the Andean high-altitude ecosystem, a distinct genetic potential, or a combination of these may be responsible [4].

On the other hand, some studies reported that children living in high altitude may have larger bodies (weight and height) compared to those living in low altitude cities [6].

Taif is a city in Mecca Province of Saudi Arabia at an elevation of 1,879 m (6,165 ft) on the slopes of Sarawat Mountains (Al- Sarawat Mountains). It has a population of 993,800 people [7].

Our aim was to find out if the high altitude at “Taif” city affects the growth of children in order to open the way for further researches to obtain the optimum health care and avoid any growth-related problems in Kingdom of Saudi Arabia.

Objectives

This study was conducted to find out if there is a relationship between living in high altitude cities like “Taif” and children’s growth at this city.

Subjects and Methods

A total of 277 children from Taif city were screened during July 2017. This included 133 males (48%) and 144 females (52%).

For those children, wet took the measurements of weight to the nearest 0.25 kg and height to the nearest 0.25 cm. Two body scales and 2-meter sticks were used for this purpose. We needed to measure the height of the parents to rule out the genetic predisposition for the short stature.

Data was collected using a questionnaire form during a face to face interview and was entered into the database using a computer.

Questions related to various diseases that may affect the growth and questions about the nutritional state, life style, parents’ education level, and maternal health during pregnancy were also included in the questionnaire.

Included subjects were children from the age of 5 to 18 years living in Taif, with good nutritional and good socio-economic status. Any child less than 5 years old or not living in “Taif” or has been diagnosed with any disease that may interfere with the normal growth was excluded.

All the data was analyzed by SPSS program and compared to the previous studies and to the Saudi and National standards.

We chose to conduct a cross sectional study during July 2017 on a sample of 277 children of both genders. That's been calculated through taking the numbers of all children from the age of 5 till 18 and we found that they represent around 23.32% of the total population of Saudi Arabia. Then, we applied this finding on the total population of Taif city. Finally, we took the numbers and calculated the sample size with a confidence level of 95%.

Data collected

The questionnaire was consisted of several parts to cover the following data items; weight, height, BMI, age, nationality, parental heights, current health status and diseases, number of family members, parents’ occupation and educational level, total family income, dietary and exercise habits, marriage of relatives, weight and physical changes for puberty, appetite, and tendency for infections. Questions about maternal and fetal health were included such as antenatal care visits, maternal infections and rashes, gestational diabetes occurrence, and radiation exposure during pregnancy.

Statistical analysis

Data were statistically described in terms of frequencies (number of cases) and valid percentages for categorical variables. Mean, standard deviations, minimum and maximum were used to describe numerical variables. Comparison of numerical variables between the subgroups was done using one-way ANOVA. One-sample t-test was used to compare the height and weight of study subjects to the age-relevant values in the Saudi standard growth curves. P values less than 0.05 were considered statistically significant. All statistical calculations were done using computer program IBM SPSS (Statistical Package for the Social Science; IBM Corp, Armonk, NY, USA) release 21 for Microsoft Windows.

Results

Participants’ characteristics

A total of 277 children were involved in this study. Of these children, 133 (48%) were males and 144 (52%) were females.

Their ages ranged from 5 to 18 years with a mean (± SD) value of 9.3 ± 3.48 years and a medial (IQR) value of 9(6) years. No significant difference (p=0.513) was found between the mean age of males (9.4 ± 3.57 years) and that of females (9.2 ± 3.41 years).

Physical characteristics were assessed through taking body measurements.

The participants’ heights ranged from 97 to 180 cm with a mean (± SD) value of 133.19 ± 18.09 cm. No significant difference (p=0.906) was found between the mean height of males (135.16 ± 18.21 cm) and that of females (131.38 ± 17.86 cm) (Figure 1).

child-adolescent-health-height

Figure 1: Participants’ height measurements.

As for body weight, the minimum value recorded was 12.7 kg while the maximum was 88 kg. The mean (± SD) value was 31.86 ± 14.84 Kg. The same as height, there was no significant difference (p=0.429) between the mean weight of males (33.33 ± 15.39 kg) and that of females (30.5 ± 14.23 kg) (Figure 2).

child-adolescent-health-weight

Figure 2: Participants’ weight measurements.

The BMI values were calculated and found to be ranging from 9.2 to 31.91 kg/m2 with a mean (± SD) value of 16.99 ± 3.9 kg/m2. The same as height and weight, BMI didn’t differ significantly (p=0.828) between males (17.29 ± 3.98 kg/m2) and females (16.72 ± 3.82 kg/m2).

Arm circumference was measured for all the subjects and the values were found to fall between 11.3 and 36 cm with a mean (± SD) value of 20.49 ± 3.99 cm with no significant difference between males and females (p=0.223).

Comparing height and weight to the standard measures of children and adolescents in Saudi Arabia

Regarding height, the average height of boys (135.16 ± 18.21 cm) was found to be significantly higher (p=0.047) than the agerelevant value extracted from the standard growth chart (132 cm) [8].

On the other hand, no significant difference (p=0.357) was found between the average height of the girls included in the study (131.38 ± 17.86 cm) compared to the age-relevant value extracted from the standard growth chart (130 cm).

While regarding the body weight, the average weight of boys in the study (31.86 ± 14.84 Kg) was significantly higher than the age-relevant value extracted from the standard growth chart (28 kg), p<0.001.

The same was reported in girls as the average body weight (30.5 ± 14.23 kg) was significantly higher than the age-relevant value extracted from the standard growth chart (27 kg), p=0.004.

Parental weight and height

Parental height was considered as important information to exclude genetic predisposition of short stature of children. Both mother’s and father’s height measurements were recorded where the mean (± SD) value for the fathers’ heights was 170.23 ± 8.05 cm while the mothers was 158.3 ± 6.87 cm. The maximum value recorded for father’s height was 189 cm while the minimum was 125 cm. The maximum value recorded for the mother’s height was 186 cm while the minimum was 109 cm.

The participant’s current health status was also important to be taken into consideration. They were asked if they suffer from any diseases and the following was found; 2 (0.7%) had sickle cell disease, 12 (4.3%) had asthma, 4 (1.4%) had anemia, 2 (0.7%) had food intolerance, 1 (0.4%) had diabetes, 1 (0.4%) had kidney disease, and 48 (17.3%) had other diseases.

No significant differences were found between the heights (p=0.067), weights (p=0.078) or BMI (p=0.359) of children who have any diseases and those who are diseases-free.

Regarding nationality, 244 (88.1%) of participants were Saudi while 33 (11.9%) were of other nationalities. The participants were also asked about their place of residence and it was found that those who were living in Taif were 257 (92.8%), those who were living in other high-altitude cities were 19 (6.9%) while only one participant (0.4%) was not living in a high-altitude city. The duration of residence ranged from 1 to 18 years with a mean (± SD) value of 13.94 ± 6.07 years.

The number of family members was collected. The most prevalent was families with 5 members (74 participants, 26.7%). This was closely followed by 19.5% having 4 family members. More details are shown in the Table 1.

Number of family members Frequency Percent
2.00 1 0.4
3.00 13 4.7
4.00 54 19.5
5.00 74 26.7
6.00 50 18.1
7.00 34 12.3
8.00 20 7.2
9.00 15 5.4
10.00 6 2.2
11.00 5 1.8
12.00 1 0.4
13.00 3 1.1
14.00 1 0.4
Total 277 100.0

Table 1: Showing the number of family members in each participant.

Occupation and educational level of parents

Regarding the father’s occupation, 40.1% were military members, 23.8% were teachers, 7.2% were engineers, 4% were physicians, 2.9% were involved in free works and 22% occupy other positions. Regarding the father’s education, 51.3% hold a bachelor’s degree, 44.4% were high school graduates, while 4.3% held a Masters or PhD degree.

Regarding the mother’s occupation, 67.5% were homemakers, 0.7% were engineers, 8.7% were physicians, 20.6% were involved in free works and 2.5% occupy other positions. Regarding the mother’s education, 56.7% held a bachelor’s degree, 39% were high school graduates, while 4.3% held a Masters or PhD degree.

Socioeconomic status

As for the total family income, the number of participants who had average income ranging from 5000 to 15000 SR was 168 (60.6%). Those who had high total family income (more than 15000) were 89 (32.1%) participants, while those who had low total family income (less than 5000) were 20 (7.2%) participants.

The economic status of families (expressed as total income) showed no significant effect on children’s height (p=0.071), weight (p=0.055) or BMI (p=0.079).

A total of 150 participants (54.2%) live in a house owned by the family while 127 (45.8%) lived in a house that was rented. Regarding the number of rooms in the house, 14 (5.1%) lived in a house that had 2 rooms or less. 189 (68.2%) lived in a house that had 3 - 5 rooms, while 74 (26.7%) lived in a house that had more than 5 rooms.

Eating, drinking and exercise habits

Information about the participants’ eating habits was also collected by asking them about their favorite foods and how many times per day the participant consumed them. These were the largest group of findings for each category. Cereals were consumed with more than 3 meals per day by 38.6% of the participants. Fruits and vegetables were consumed with more than 3 meals per day by 29.6%of the participants. 35.4% of the participants consumed fast foods once per day. Packed food was not preferred with the largest group making up around 29.2% of the participants don’t eat it. 48% of the participants consumed meat with more than 3 meals per day. As for the sweets, these were consumed once daily by 23.8% of the participants. More details are found in the Table 2.

Food Type Number of meals in a Day Frequency Percent
Cereals One meal 57 20.6
2 meals 49 17.7
3 meals 43 15.5
More than 3 meals 107 38.6
Don't eat 21 7.6
Total 277 100.0
Vegetables and fruits One meal 29 10.5
2 meals 64 23.1
3 meals 47 17.0
More than 3 meals 82 29.6
Don't eat 55 19.9
Total 277 100.0
Fast food One meal 98 35.4
2 meals 73 26.4
3 meals 26 9.4
More than 3 meals 17 6.1
Don't eat 63 22.7
Total 277 100.0
Packed Food One meal 65 23.5
2 meals 32 11.6
3 meals 29 10.5
More than 3 meals 70 25.3
Don't eat 81 29.2
Total 277 100.0
Meats One meal 58 20.9
2 meals 26 9.4
3 meals 35 12.6
More than 3 meals 133 48.0
Don't eat 25 9.0
Total 277 100.0
Sweets One meal 66 23.8
2 meals 36 13.0
3 meals 42 15.2
More than 3 meals 95 34.3
Don't eat 38 13.7
Total 277 100.0

Table 2: Showing the frequency and the percent of the daily consumption of each food type regarding the participant.

Drinks consumption included in the diet was also considered. The following was found to be the most prevalent percentages. Pasteurized milk was consumed to travel purposes by 32.9% followed by 29.6% who consumed it more than 3 times daily. Fresh milk was consumed to travel purposes by 47.3%. Soft drinks were consumed to travel by 46.6%. Natural juices were consumed once per day by 27.8% while tea and coffee were consumed to travel by 54.2%. More details are shown in the Table 3.

Type of Drink Number of drinks in a Day Frequency Percent
Pasteurized milk Once 67 24.2
Twice 18 6.5
Three times 18 6.5
More than 3 times 82 29.6
To travel 91 32.9
0 1 0.4
Total 277 100.0
Soft drinks Once 64 23.1
Twice 32 11.6
Three times 28 10.1
More than 3 times 23 8.3
To travel 129 46.6
0 1 0.4
Total 277 100.0
Fresh milk Once 61 22.0
Twice 19 6.9
Three times 19 6.9
More than 3 times 45 16.2
To travel 131 47.3
0 2 0.7
Total 277 100.0
Natural juices Once 77 27.8
Twice 35 12.6
Three times 51 18.4
More than 3 times 55 19.9
To travel 59 21.3
Total 277 100.0
Tea/ coffee Once 53 19.1
Twice 21 7.6
Three times 19 6.9
More than 3 times 33 11.9
To travel 150 54.2
0 1 0.4
Total 277 100.0

Table 3: Showing the frequency and the percent of the daily consumption of different kind of drinks.

Exercise habits were also tracked. The participants were asked about different exercise forms and the number of times per week the participants would engage in them. The participants going for a walk were divided as follows according to the frequency; 14.8% went for a walk once per week, 2.2% twice per week, and 14.1% three times per week while 24.5% never went for walks. 44.4% of the participants claimed to go for walks daily. Participants were also asked about playing football to which they claimed that 7.6% played once per week, 1.4% twice per week, 20.9% three times per week, 18.4% daily while 51.6% never played football on regular basis. The last form of exercise was swimming. 10.5% of the participants claimed to swim once per week, 2.9% swam twice per week, 13.79% three times per week, 27.1% daily while 45.5% never went for a swim. More details are shown in the Table 4.

Type of Exercise Number of times doing exercise in a week Frequency Percent
A walk to exercise Once per week 41 14.8
Twice per week 6 2.2
Three times per week 39 14.1
Daily 123 44.4
Never 68 24.5
Total 277 100.0
Play football Once per week 21 7.6
Twice per week 4 1.4
Three times per week 58 20.9
Daily 51 18.4
Never 143 51.6
Total 277 100.0
Swim Once per week 14 5.1
Twice per week 6 2.2
Three times per week 48 17.3
Daily 12 4.3
Never 197 71.1
Total 277 100.0
Ride a bike Once per week 29 10.5
Twice per week 8 2.9
Three times per week 38 13.7
Daily 76 27.4
Never 126 45.5
Total 277 100.0

Table 4: Showing the type and the frequency of each exercise that had been done by the participants weekly.

Relatives marriage

There participants were asked if the family includes relative’s marriage. 34.7% answered yes while 65.3% answered no. More details are shown in the Table 5.

Relatives Marriage Frequency Percent Valid Percent
Valid No 181 65.3 65.3
Yes 96 34.7 34.7
Total 277 100.0 100.0

Table 5: Showing the prevalence of consanguinity among all participants.

Weight changes

The participants were asked if they experienced weight changes recently and 74.7% claimed that they did not, while 25.3% said that they did experience weight changes. More details are shown in the Table 6.

Weight changes Frequency Percent Valid Percent
Valid No 207 74.7 74.7
Yes 70 25.3 25.3
Total 277 100.0 100.0

Table 6: Showing how many participants noticed change in weight.

Frequent chronic infections

The participants were asked if they suffered from frequent chronic infections, to which 21.7% answered yes and 78.3% said no.

The participants’ appetite was also questioned. It was found that 9% had above average appetite, 63.9% had average appetite, and 27.1% had below average appetite. More details are shown in the Table 7.

Appetite Frequency Percent Valid Percent
Above average 25 9.0 9.0
Average 177 63.9 63.9
Low 75 27.1 27.1
Total 277 100.0 100.0

Table 7: Assessing the appetite of each participant in which 9% have above the average appetite and 27.1% have a low appetite.

The participants were asked about their prenatal health. This was evaluated by asking about the antenatal care visits and maternal health during pregnancy. It was found that 209 (75.5%) of the participants’ mothers had been to antenatal care visits. Regarding maternal infections, 209 (75.5%) claimed that there was none. Regarding maternal skin rashes, 262 (94.6%) claimed that there was none.

Regarding gestational diabetes, 191 (39.7%) had a history of gestational diabetes, 24 (8.7%) were controlled. Regarding gestational hypertension, 101 (36.5%) had a history of gestational diabetes, 16 (5.8%) were controlled. As for radiation exposure during pregnancy, 22 (7.9%) claimed that they were exposed to radiation while they were pregnant while 255 (92.1%) were not exposed to radiation. More details are shown in the Table 8.

Antenatal risk factors Frequency Percent
Antenatal care visits No 68 24.5
Yes 209 75.5
Total 277 100.0
Maternal infection No 209 75.5
Yes 68 24.5
Total 277 100.0
Maternal skin rash No 262 94.6
Yes 15 5.4
Total 277 100.0
History of gestational diabetes yes controlled 24 8.7
yes not controlled 86 31.0
no 167 60.3
Total 277 100.0
History of gestational hypertension yes controlled 16 5.8
yes not controlled 85 30.7
no 176 63.5
Total 277 100.0
Radiation exposure during pregnancy yes 22 7.9
no 255 92.1
Total 277 100.0

Table 8: Showing different antenatal risk factors that developed during the pregnancy of each participant in which 24.5% of the mother participant were not followed up regularly and 24.5% had infection during pregnancy.

The duration of pregnancy was also recorded. A total of 206 (74.4%) children were delivered as full-term babies, 50 (18.1%) were delivered post-term while 21 (7.6%) were delivered preterm. More details are shown in the Table 9.

Duration of pregnancy Frequency Percent
Full term 206 74.4
Post term 50 18.1
Pre-term 21 7.6
Total 277 100.0

Table 9: Showing 7.6% of participants were preterm and 18.1% were post term.

The weight at delivery was also recorded where 50 (18.1%) participants were less than 2500 g at delivery, 171 (61.7%) weighed between 2500 and 3000 g at delivery, 49(17.7%) weighed between 3000 and 4000 g at delivery, while 7 (2.5%) weighed more than 4000 g at delivery. More details are shown in the Table 10.

Weight at delivery Frequency Percent
2500 to 3000 g 171 61.7
3000 to 4000 g 49 17.7
Less than 2500 g 50 18.1
More than 4000 g 7 2.5
Total 277 100.0

Table 10: Showing the weight of each participant after delivery 18.1% were less than 2500 g and 2.5% were more than 4000 g.

Data about how the participants were fed after birth was also collected and it was found that 55 (19.9%) of the participants depended on bottle feeding, 33(11.9%) were breast fed, while 189 (68.2%) depended on mixed feeding. More details are shown in the Table 11.

Feeding types Frequency Percent
Bottle Feeding 55 19.9
Breast feeding 33 11.9
Mixed feeding 189 68.2
Total 277 100.0

Table 11: Showing the type of feeding of each participant in which only 11.9% were exclusively breast feeding while 19.9% were only on bottle feeding.

The family’s stature was also evaluated, and it was found that 95 (34.3%) had short stature while 182 (65.7%) had normal stature. More details are shown in the Table 12.

Family short stature Frequency Percent
No 182 65.7
Yes 95 34.3
Total 277 100.0

Table 12: Showing the family history of short stature.

After applying the weight, height and body mass index of each child on the Saudi standard growth charts, the correct percentile was determined, and the results shown:

Regarding weight, more than half of the children (51.3%) are in the mid-area of the curve (26th to 75th percentiles) with the largest proportion (29.6%) in the third quartile (51st to 75th percentile).

The same was reported for height, as 40.8% of the children are in the mid-area of the curve (26th to 75th percentiles) with the largest proportion (23.1%) in the third quartile (51st to 75th percentile).

And for BMI, almost half of the children (47.3%) were in the mid-area of the curve (26th to 75th percentiles) while the largest proportion (24.2%) was in the second quartile (26th to 75th percentile). More details are shown in the Tables 13.

Weight percentile Frequency Percent Valid Percent Cumulative Percent
Valid below 3 percentile 7 2.5 2.5 2.5
from 3 to 5 5 1.8 1.8 4.3
from 6 to 10 11 4.0 4.0 8.3
from 11 to 25 19 6.9 6.9 15.2
from 26 to 50 60 21.7 21.7 36.8
from 51 to 75 82 29.6 29.6 66.4
from 76 to 90 42 15.2 15.2 81.6
from 91 to 95 24 8.7 8.7 90.3
from 96 to 97 6 2.2 2.2 92.4
above 97 21 7.6 7.6 100.0
Total 277 100.0 100.0  
Height percentile Frequency Percent Valid Percent Cumulative Percent
Valid below 3 percentile 9 3.2 3.2 3.2
from 3 to 5 5 1.8 1.8 5.1
from 6 to 10 6 2.2 2.2 7.2
from 11 to 25 17 6.1 6.1 13.4
from 26 to 50 49 17.7 17.7 31.0
from 51 to 75 64 23.1 23.1 54.2
from 76 to 90 48 17.3 17.3 71.5
from 91 to 95 36 13.0 13.0 84.5
from 96 to 97 10 3.6 3.6 88.1
above 97 33 11.9 11.9 100.0
Total 277 100.0 100.0  
BMI percentile Frequency Percent Valid Percent Cumulative Percent
Valid below 3 percentile 5 1.8 1.8 1.8
from 3 to 5 3 1.1 1.1 2.9
from 6 to 10 18 6.5 6.5 9.4
from 11 to 25 49 17.7 17.7 27.1
from 26 to 50 67 24.2 24.2 51.3
from 51 to 75 64 23.1 23.1 74.4
from 76 to 90 48 17.3 17.3 91.7
from 91 to 95 11 4.0 4.0 95.7
from 96 to 97 3 1.1 1.1 96.8
above 97 9 3.2 3.2 100.0
Total 277 100.0 100.0  

Table 13: Show the exact weight and height and BMI in which percentile after applying it on growth chart.

Discussion

It is still questionable if living in high altitude can negatively affect children’s growth in terms of height and weight especially during the early childhood when the growth rate is at its maximum [9].

And accordingly, this cross-sectional study was conducted on children living in “Taif” city as an example of a high-altitude city in order to examine the effect of high altitude on children growth. A face to face questionnaire was filled-in for 277 children. In addition, body measurements including height, weight, and BMI and arm circumference were taken for these children. The research question was answered by comparing the mean values of body measurements of those children (mainly weight and height) to the standard growth curves of Saudi children developed by El-Mouzan et al. [8].

Results of the current study showed that the body weights of boys and girls were significantly higher that the age-relevant values in the standard growth curves (p<0.001 and p=0.004 respectively).

The same as body weight, height of boys was significantly higher than the Saudi national growth standard (p=0.047). On the other hand, no significant difference (p=0.357) was found between the average height of girls compared to the age-relevant value extracted from the standard growth chart.

Results of our study can be supported by a previous study that has been conducted in Bolivia, 1982 on school age children to find that, the effect of high altitude on children growth is small if compared to that of other environmental and genetic factors [10].

However, our findings are against the results of several previous studies which revealed that living in high altitude cities can affect child’s growth negatively in terms of height and weight.

This includes a study conducted on Tibet population which showed that living in high altitude might result in delay in the growth especially in height regardless of socioeconomic, nutrition and disease, and the effect on weight could be limited but they only covered children from the birth till the age of 3-year-old [11].

This is also against the findings reported in a study has been done in Abha, Saudi Arabia 1995 among children varying from the age of 6 to 14 and they found that children who lives in Abha has lower weight, height and weight for height ratio in comparison to NCHS growth standard. But they did not assess the relation of these results to the socioeconomic state or the genetic predisposition or nutritional state of the child [12].

Conclusion

Results of the current study showed that living in “Taif” as an example of high altitude city did not affect children growth negatively in terms of height and weight. And accordingly, additional research in other high-altitude cities in is required in order to further affirm or deny this hypothesis and identify any other factors that might affect the optimum growth rate of children in Saudi Arabia.

References