Advances in ISSN: 2378-3168AOWMC

Obesity, Weight Management & Control
Research Article
Volume 4 Issue 6 - 2016
Physical Activity a Determinant to Control Adolescent Obesity
Anjum Hashmi1*, Fayez Mamluh Alazmi2 and Jamil Ahmad Soomro3
1Infection Prevention & Control Director, Qurrayyat General Hospital, Saudi Arabia
2Hospital Director, Qurrayyat General Hospital, Saudi Arabia
3Community Medicine Department, Isra University Hyderabad, Pakistan
Received: December 14, 2015 | Published: July 21, 2016
*Corresponding author: Anjum Hashmi, MPH, Infection Prevention & Control, General Hospital, Al Qurayyat, Al Josf, Saudi Arabia, Email:
Citation: Hashmi A, Alazmi FM, Soomro JA (2016) Physical Activity a Determinant to Control Adolescent Obesity. Adv Obes Weight Manag Control 4(6): 00115. DOI: 10.15406/aowmc.2016.04.00115

Abstract

Objective: Lack of physical activity, unbalanced diet and unhealthy lifestyles have lead to lifelong obesity. Obesity in Pakistani children and adolescents has also becoming an important public health problem due to changes in life style and other factors. Our aim is to determine relationship between physical activity and obesity in urban youth.

Methods: A Cross-sectional study was conducted from 01 June 2013 to 30 December 2013 in Hyderabad Pakistan. A total of 504 male and female students of class six to ten were selected through simple random sampling. They were interviewed by trained data collectors through obesity and physical activity questionnaire. Anthropometric measurements were done with calibrated instruments using the age and sex specific BMI cut off points according to WHO growth reference.

Results: The prevalence of overweight (> 85th Percentile) and obesity (>95th percentile) was 23% and 15% among the boys respectively whereas in girls the prevalence of overweight and obesity was 16% and 8% respectively. A significant proportion of girls (86%) and boys (85%) had abnormal waist to hip ratios. Mean of moderate physical activity 6.2 hours SD 5.9 and mean of hard physical activity 5.3 hours SD 5.2.

Conclusion: Promoting physical activity has become a priority because of its role in preventing childhood obesity and chronic disease. The determinants of the obesity lie within the home and school environment and the overall socio-cultural phenomena. Children are spending an alarmingly large part of their daily time on sedentary activities and having minimal physical activity.

Keywords: Body Mass Index; Prevalence; Adolescent; Waist Circumference; Physical activity; Statistical Package for Social Sciences; Communicable diseases

Introduction

According to world health organization approximately 1.6 billion adults (age 15+) were overweight, and at least 400 million adults were obese in 2005, at least 20 million children under the age of 5 years were overweight globally in year 2005 [1-2]. During last three decades the prevalence of overweight and obesity in children and adolescents has been tripled. Physical inactivity, unbalanced diet, and unhealthy lifestyles may have caused this lifelong obesity [3].

According to the last census, 32.5% population of Pakistan was living in urban areas [4]. Lack development and jobs in rural areas lead to mass scale migration towards cities. Pakistan has only 22% physically active adult population [4-5] which is due to urbanization and modernization of society along with changes in life styles. Promoting physical activity among children can help to prevent childhood obesity and related conditions.

Studies have shown that children who are physically fit perform better in school and on tasks requiring concentration. Obesity driven burden of disease is induced by inappropriate diets and widespread physical inactivity which can be addressed by increasing Physical Activity (PA). A study done in Australia mentions decline in fitness level between childhood and adulthood was associated with increased obesity and insulin resistance. Programs aimed at maintaining high childhood physical activity levels into adulthood may have potential for reducing the burden of obesity and type II diabetes in adults [6]. Pakistan is among the countries which have high prevalence of obesity among boys and girls [7]. Pakistan is facing the double burden of diseasesand obesity which is a major risk factor for a number of Non communicable diseases [8].

 The modern world makes it very easy to out-eat exercise, and nearly impossible to out-exercise excessive eating [9]. But simply advocating for more physical activity is unrealistic so substantial changes in urban planning and diet are needed to counter menus of obesity. Despite an appreciation that physical activity is essential for the normal growth and development of children and can prevents obesity and obesity-related health problems, too few children are physically active.

A concurrent problem is that today's young people spending more time in sedentary pursuits, including watching television and engaging in screen-based games. Active behavior has been displaced by these inactive recreational choices, which has contributed to reductions in activity-related energy expenditure [10]. Walking to school provides a convenient opportunity for children to be physically active [11].

This study was conducted in order to determine relationship between physical activity and obesity in urban high school students thus it can guide decision makers to formulate recommendations for preventing the growing epidemic of obesity in local setting.

Methods

A Cross-sectional study was conducted from 01 June 2013 to 30 December 2013 in urban city Hyderabad Pakistan. A total of 504 students, 255 male and 246 female students selected through simple random sampling. The sample size of 504 was divided among the government and private schools according to the probability proportional to size of students in private and government schools in the city. Finally the students were selected from the list of the students from the classes through Simple Random Sampling.

They were interviewed by trained data collectors through physical activity and diet questionnaires. Questionnaire was based on the variables on the socio-demographic factors, the variables on the physical activity and school and home environments conducive for physical activity. The physical activity questionnaire was further consolidated and adapted by using the questions from the Youth Physical Activity Survey questionnaire of “The School Health Action, Planning and Evaluation System-SHAPES” study of the University of the Waterloo Canada.

Anthropometric measurements were done with calibrated instruments using the age and sex specific BMI cut off points given by W.H.O. Obesity among the school children was the outcome/dependent variable. Cut off points given by the World Health Organization for the measurement of Obesity were used. In the new WHO growth reference for the school age children and adolescents, more than 85th percentile (BMI Kg/height2) is equivalent to overweight and more than 95th percentile (BMI Kg/height2) is equivalent to obesity [12,13].

Waist circumference (WC) is also an important measurement especially of truncal obesity. Although there is no consensus about how to define obesity among children using waist measurement, for clinical use the 98th percentiles is the suggested cut-off for obesity and the 91st percentile is the cut-off for overweight (NICE.UK) [14].

Six data collectors were hired and trained in workshop for preparation of the field work, to liaison with the school administration and gathering of the lists of the schools and children, signing up of assent forms by the parents, pretesting and final questionnaire administration and anthropometric measurements.

For the calculation of the sample size to keep the secondary objective in consideration we calculated sample size for two population proportions through using Epi info version 6. For associated factors 31% prevalence of mothers of the non obese school children with low education, 23.76% prevalence of non obese children in upper socioeconomic status and 17% prevalence of non obese children of working mothers (expected frequency of disease among non diseased) was considered [15].

The final sample size was given by the variable mother’s education because it gave the largest sample of all the independent variables. To see the association of mothers education with the obesity in children we took a confidence level of 95%, power of 80%, the ratio of exposed children (whose mothers are illiterate) to unexposed children (children whose mothers have at least five years of education) and the prevalence of obesity among children of educated mothers of 31% the sample size came to be 336 with 114 in unexposed arm and 228 among exposed arm. Using a design effect of 1.5 the final sample size came out to be 504 (336*1.5).

Data was analyzed in the Statistical Package for Social Sciences (SPSS) version 16.0 Descriptive analysis was conducted for calculating mean and standard deviations for continuous variables and proportions were calculated for categorical variables such as level of education of parents, gender and type of school. In inferential analysis, at a 5% level of significance (α), t-test was used. Multiple logistic regression analysis was used for adjusting the confounders. Any potential bias in the study was minimized through calibrated height and weight measurement tools.

Analysis of the results is presented in descriptive variables, univariate logistic regression analysis and multivariate logistic regression analysis. Each of these groups are again subdivided and ordered into most understandable categories namely overweight and obesity descriptive variables, variables on the school environment for physical activity of the students and finally the parental/home factors promoting obesity among children.

Results

Results were available for 501 subjects out of the 504 subjects. Three forms were not eligible for the analysis due to the incompleteness of the data. The prevalence of overweight (>85th Percentile) and obesity (>95th percentile) was 23% and 15% among the boys respectively whereas in girls the prevalence of overweight and obesity was 16% and 8% respectively. The Waist to Hip Ratios (WHR) is another measure of central obesity along with BMI. A significant proportion of girls (86%) and boys (85%) had abnormal WHR. Use of transport by students was the most common mode (60%) to reach school will likely to be obese than those who reach school by physical activity i.e. walking and cycling. Mean time to reach school by physical activity is 9.66 hours SD 6.7. Mean of moderate physical activity 6.2 hours SD 5.9 and mean of hard physical activity hours 5.3 SD 5.2. Obese children in our sample were attempting or trying to lose weight explaining that they were conscious of their weight status and the consequences.

Time to reach school by activity (by foot or by cycle) P value= 0.339, OR 1.2 (CI 95- 0.98-1.08)
Moderate Physical activity (hrs per week) P value= 0.320, OR 1.02(CI 95- 0.98-1.06) and Hard Physical activity (hrs per week) OR .97 (CI 95-0.92-1.01). Parental support in physical activity OR 1 and unsupportive parents for physical activity P value= 0.988. OR 1.00 CI for OR 0.61-0.62.

Multivariate analysis contained other independent variables including; school gives awards in non-competitive sports (p value=0.123). Males showed a higher risk of obesity as compared to females. Specifically the females were 67% less likely to be obese than males, (OR.0.33). This gender relationship with the outcome improved from 35% in the univariate to 65% in the multivariate analysis. Those who rated themselves poor in athletic ability were OR 5.50 (P value=0.001) more likely to be obese Table(1-5).

Variables

Boy’s

Girl’s

Overweight

N

%

N

%

Yes (>85th Percentile)

59

23%

39

16%

No (<85th Percentile )

196

77%

207

84%

Obesity

 

 

 

 

Yes (>95th Percentile)

38 (15%)

 

20 (8%)

 

No (<95th Percentile)

217(85%)

 

226 (92%)

 

Waist to Hip Ratio (WHR)

 

 

 

 

WHR Less than 0.8

NA

 

35

14%

WHR More than 0.8

NA

 

211

86%

WHR Less than 0.9

177

69%

NA

 

WHR More than 0.9

78

11%

NA

 

Waist Circumference

 

 

Mean

75.50

72.23

SD

10.46

8.52

Hip Circumference

 

 

Mean

86.03

85.24

SD

10.09

8.95

Table 1: Description of overweight and obesity by sex in students.

Variables

Frequency*

Percent

Mode of Travel to School (n=501)

 

 

Actively (walk, cycle)

197

39.3

Inactively (car, bus etc)

304

60.7

Typical Week of Moderate Exercise

Yes

374

75

No, less active in last 7 days

127

25

Typical Week of Hard Exercise

Yes

338

67

No, I was less active in last 7 days

163

33

Anything Prevented Exercise Last Week? (n=500)

Yes

150

30

No

350

70

Exercise for the Flexibility of Muscles? (n=501)

less than 4 days in a week

423

84

More than 4 Days a week

76

15

Exercise for the Strength of the Muscles? (n=500)

less than 4 days in a week

436

87

More than 4 Days a week

64

13

3-4 Days in a week

61

12.2

More than 5 Days a week

64

12.8

Individual Exercises after School (n=501)

Yes

310

62

No

191

38

What are you Trying for your Weight (n=501)

Lose Weight

190

38

Gain Weight

78

16

Stay with the same Weight

147

29

Not doing anything about Weight

86

17

Participate in Games Outside School (e.g. in neighborhoods) (n=501)

Yes

296

59

No

204

41

 

Mean**

SD

Time to reach school by activity (hours)

9.66

6.7

Time spent on Media (hrs per week)

20

12.9

Mean hrs of moderate physical activity

6.2

5.9

Mean hrs of hard physical activity

5.3

5.2

Table 2: Descriptive characteristics related to Physical Activity.

*Frequency and percentage is given for the categorical variable.
**Mean and standard deviation is given for the continuous variables.

Variable

P value

OR

95 % CI

Time Spent on Media Per Week

 

 

 

Weekly

0.528

1.01

(0.99-1.02)

Mode of Travel to School

 

 

 

Actively (walk, cycle)

 

1.00

 

Inactively (car, bus etc)

0.348

1.25

(0.79-1.97)

Time to Reach School by Activity (by Foot or by Cycle)

 

 

 

Hour per week

0.339

1.02

(0.98-1.08)

Moderate Physical Activity

 

 

 

Hours per week

0.320

1.02

(0.98-1.06)

Typical Week of Moderate Exercise

 

 

 

Yes

 

1.00

 

No, less active

0.076

1.54

(0.96-2.49)

Hard Physical Activity

 

 

 

Hours per week

 

0.97

(0.92-1.01)

Typical Week of Hard Exercise

 

 

 

Yes

 

1.00

 

No, less active

0.167

1.38

(0.87-2.18)

Exercise for the Flexibility of Muscles?

 

 

 

Less than 4 days a week

0.981

1.01

(0.55-1.86)

More than 4 days a week

 

1.00

 

Exercise for the Strength of the Muscles?

 

 

 

Less than 4 days a week

0.656

0.86

(0.46-1.64)

More than 4 days a week

 

1.00

 

Physically Active Students do Better in School

 

 

 

Agree

 

1.00

 

Disagree

0.691

1.11

(0.66-1.88)

Participate in Games Outside School (e.g. in neighborhoods)

 

 

 

Yes

 

1.00

 

No

0.552

1.14

(0.73-1.79)

Table 3: Univariate analysis: Factors related to physical activity of students.

Variables

 P value

 OR

CI for OR

School Emphasis on Participation Competitive Sports

None

0.135

1.00

 

A Little

 

2.02

(1.06-3.86)

Some

 

1.17

(0.62-2.21)

A Lot

 

1.18

(0.59-2.32)

School Emphasis on Participation Non-competitive Sports

None

0.920

 

 

A Little

 

1.04

(0.57-1.89)

Some

 

0.93

(0.53-1.63)

A Lot

 

0.82

(0.42-1.61)

School Emphasis on Developing Positive Attitudes about Physical Activity

None

0.332

 

 

A Little

 

0.48

(0.21-1.10)

Some

 

1.09

(0.63-1.91)

A Lot

 

0.59

(0.31-1.10)

School Emphasis on Informing Opportunities to Stay Physically Active

None

0.317

1.00

 

A Little

 

0.90

(0.46-1.78)

Some

 

1.10

(0.64-1.90)

A Lot

 

0.63

(0.33-1.19)

Involving students in Planning of Sports Events

None

0.156

1.00

 

A Little

 

0.93

(0.49-1.75)

Some

 

1.24

(0.73-2.11)

A Lot

 

0.54

(0.26-1.11)

School Emphasis on School Staff Physically Active in School

None

0.258

1.00

 

A Little

 

1.77

(0.91-3.43)

Some

 

0.83

(0.42-1.62)

A Lot

 

0.71

(0.27-1.91)

Table 4: Univariate analysis: Factors related to “school physical activity environment” of students.

Variables

Crude OR (95% CI)

Adjusted OR (95% C.I.)

P-value
(MVA)

Gender

 

 

 

Males

1.00

1.00

 

Females

0.65 (0.41-1.01)

0.33 (0.16-68)

0.002

Athletic Ability

 

 

 

Excellent

1.00

1.00

0.001

Good

1.14 (0.64-2.03)

1.20 (0.53-2.70)

 

Fair

0.62 (0.29-1.31)

0.48 (0.16-1.44)

 

Poor

4.61 (2.21-9.61)

5.50 (1.81-16.68)

 

Socioeconomic Status

 

 

 

Lower tertile

1.00

1.00

0.004

Middle tertile

2.22 (1.14-4.33)

3.43 (1.49-7.93)

 

Upper tertile

1.62 (0.81-3.22)

0.12 (0.01-1.00)

 

Table 5: Multivariate Logistic Regression Analysis Obesity and Overweight vs Normal Weight with Physical Activity of students (n=501).

Discussion

A high prevalence of overweight and obesity among the sampled population was the main finding of our study. A cross-sectional study showed varieties of factors are potential determinants of physical activity behaviors in children and adolescents. Physiologic, environmental, and psychosocial /socio demographic factors play a role in influencing physical activity behaviors for children and adolescents. In all likelihood, these factors interact in various forms to potentially “cause” a physical activity behavior in children and adolescents [16] which endorse our study.

Our finding is the middle socioeconomic tertile were 3.43 times more likely to be obese than those in the lower tertile. Physical activity opportunity during school hours is one of the major determinants of childhood obesity. Our study showed that almost half of the schools were not meeting the children’s needs of the physical activity. The youth who participated in games outside schools were also found to be protected against obesity (P value=0.552). A study showed large proportion of the children in urban Nigeria who participate in physical activity the prevalence of overweight and obesity is low [17] which are consistent with our findings.

A study done in USA showed that the lack of physical inactivity, poor diet, and excessive television produce obese children. Lack of regular physical exercise contributes to a child's likelihood to be obese, while a program of exercise can reverse an unhealthy lifestyle. Weight loss and/or gain can be simply represented by the laws of thermodynamics and serve as the basis for understanding the role of physical activity and exercise interventions [18] which supports our finding.

In our study use of transport was the most common mode (60%) to reach school these students are likely to be obese than those who reach school by physical activity i.e. walking and cycling. Mean time to reach school by physical activity is 9.66 hours SD 6.7. A study showed walking to and from school is considered an additional time spent on moderate to vigorous physical activity and the studies conclude that this in fact helps children maintain an optimum weight and remain physically active [19-20]. Another study, in particular, showed that active way of commuting to and from school was associated with about extra 24 minutes of physical activity among children [21] both of these studies endorse our study.
Apart from genetic risk factors for obesity that are transferred to a child from his parents evidence is in favor that other parental factors also play a major role in the obesity among children [19,21,23]. Our study also showed that parental factors were also important determinants for the childhood obesity.

Results of our study endorse Australian and American studies concluding that a decline in fitness from childhood to adulthood due to decline in physical activity is associated with obesity [24] and vigorous physical activity may reduce the risk of obesity or overweight among male adolescents [25].

A longitudinal study adds strong support for the hypothesis that higher levels of physical activity during childhood lead to the acquisition of less body fat by the time of early adolescence [26]. Results of our study also showed similar trends, for instance; children who rated themselves as poor athletes were 5.5 times more likely to be obese than those who rated themselves excellent athletes.

Conclusion

There is increasingly high burden of overweight and obesity among the urban adolescent. Prevalence of obesity is highest in the middle income families. The determinants of the obesity lie within the home and school environment and the overall socio-cultural phenomena. Children are spending a considerable part of their daily routine on sedentary activities and having minimal physical activity opportunities both at school and home and easier access to energy rich fast foods were found to be the major determinants of obesity in our study.

For physical activity to contribute to reversing the trend in childhood obesity, a multi-factorial and multi-agency solution will be required that involves schools, the home, the neighborhoods and considered local planning and provision [27].

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