|Year : 2018 | Volume
| Issue : 5 | Page : 33-37
Noncommunicable diseases among school-going adolescents: A case study on prevalence of risk factors from Sabarkantha District of Gujarat, India
Tapasvi Puwar1, Deepak Saxena1, Sandul Yasobant2, Shital Savaliya1
1 Department of Epidemiology, Indian Institute of Public Health, Gandhinagar, Gujarat, India
2 Center for Development Research (ZEF), University of Bonn, Bonn, Germany
|Date of Submission||29-Apr-2018|
|Date of Acceptance||07-Aug-2018|
|Date of Web Publication||19-Dec-2018|
Dr. Deepak Saxena
Indian Institute of Public Health, Gandhinagar, Opp Air-Force Head Quarters, Near Lekawada Bus Stop, Gandhinagar-Chlioda Road, Lekawada, CRPF P.O, Gandhinagar - 382 042, Gujarat
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Background: The increasing burden of noncommunicable diseases (NCDs) and large proportion of adolescent population in India; crafts the dynamics of NCD risk factors. Most of the NCD risk factors are behaviorally acquired which are due to change in lifestyle during adolescent age groups. Objective: This study aims to determine the prevalence of risk factors among school-going adolescents in one of district of Gujarat state, India. Subjects and Methods: This is a cross-sectional study conducted among sampled schools of Sabarkantha district of Gujarat, India, during September–December 2016. A total of 484 school-going adolescents were screened for body weight, height, blood pressure, and some information of sociodemographic, lifestyle habits, and family history were collected through a structured questionnaire in vernacular language. Data were managed with SPSS version 20. Results: This study documents that not having fruits and not doing physical activities daily are the major risk factors of NCDs among school-going adolescents of Sabarkantha district, Gujarat. In addition to this, also it has been documented that there are differential standards for body mass index (BMI) available for adolescents and have been used extensively in various studies. This study provides an insight to these three major BMI standards and their differences in measurement for the school-going adolescents. Conclusions: This study recommends promoting healthier practices for prevention of NCD lifestyle risk factors among school-going adolescents and it also recommends standardizing the BMI measurements for adolescents for India.
Keywords: Adolescents, India, noncommunicable diseases, risk factors
|How to cite this article:|
Puwar T, Saxena D, Yasobant S, Savaliya S. Noncommunicable diseases among school-going adolescents: A case study on prevalence of risk factors from Sabarkantha District of Gujarat, India. Indian J Community Med 2018;43, Suppl S1:33-7
|How to cite this URL:|
Puwar T, Saxena D, Yasobant S, Savaliya S. Noncommunicable diseases among school-going adolescents: A case study on prevalence of risk factors from Sabarkantha District of Gujarat, India. Indian J Community Med [serial online] 2018 [cited 2020 Jun 1];43, Suppl S1:33-7. Available from: http://www.ijcm.org.in/text.asp?2018/43/5/33/247915
| Introduction|| |
Of 56.4 million global deaths in 2015, 39.5 million, or 70%, were due to noncommunicable diseases (NCDs). The leading risk factors responsible for NCDs are behavioral factors such as tobacco use, physical inactivity, and metabolic factors such as overweight/obesity, high blood pressure (BP), high cholesterol level, and high blood glucose level. Most of the risk factors are behaviorally acquired and are due to change in lifestyle during adolescent age group. According to the World Health Organization (WHO), adolescent is a person between 10 and 19 years of age period of life with rapid growth and development of body, mind, and social relationship with behavior changes such as sexual maturity and self-independence with more exposure to risk behavior such as unsafe sex, risky driving, and substance abuse. At this age, these risk factors are well tolerated and are barely perceived as harmful.
An analysis of the distribution of health behaviors among adolescents from >100 countries found that approximately 80% of them performed daily physical activities (for at least 60 min), 32% used the computer for >2 h per day, 6% smoked cigarettes daily, 7.6% consumed beer weekly, and 25% had an unhealthy diet. Each of these risk factors for NCDs has a different impact on health. Adolescents with low levels of physical activity have a higher risk of hypertension. Sedentary adolescents have a higher risk of obesity. Physical inactivity and sedentary behavior are different constructs and represent different causes and consequences that affect health. Another risk factor for NCDs that have a negative impact on the health of adolescents is unhealthy diet, either through the low consumption of fruits and vegetables or the high intake of foods rich in sugars that cause diabetes mellitus type II. In addition, excessive alcohol use causes changes in the central nervous system that may be a cause of depression among adolescents.
Lifestyle-associated risk factors among adolescent are rampantly increasing throughout the world., In framing of cost-effective strategies for prevention and treatment, identification of the risk factors and their quantification is of great importance. India with >243 million adolescents and being the capital of NCDs; this study aims to determine the prevalence of risk factors among school-going adolescents in one of the district of Gujarat state, India.
| Subjects and Methods|| |
This is a cross-sectional study conducted during September–December 2016 in Sabarkantha district of Gujarat, India.
The reported prevalence of different NCD among adolescents in India was retrieved from a systematic review published in 2014. The overall prevalence of NCDs was 10%–20%, half of adolescents were underweight, 15%–20% adolescents were using tobacco, 3%–15% adolescents were consuming alcohol, and 5%–10% adolescents were hypertensive. At the same time, few studies showed that 3%–5% of adolescents were suffering from type 1 and type 2 diabetes mellitus, and 5%–7% suffered from asthma.
At 95% confidence level (CI) and 15% average prevalence with design effect of 2, and response rate of 80%, the sample size of 484 adolescents was calculated. Considering average class size of 30, 14 schools were randomly selected from the list of schools obtained from the district education office. All the primary schools were selected from rural area as secondary/higher secondary schools were situated in urban area. All selected schools were government or government-aided schools.
The stepwise approach of the WHO on NCD risk factors was adapted to collect the data.
Questionnaire: Information on sociodemographic variables, family history, and behavioral risk factors such as tobacco use, alcohol use, physical activity level, and dietary habits were obtained using a STEPS survey format of the WHO, which was translated in vernacular language and administered by trained researchers.
Measurements: Height, weight, and BP of each adolescent were measured in the study. After removing belts and shoes, all children were weighed using a standardized spring balance scale nearest to 500 g and a maximum capacity of 125 kg. The machine was regularly checked using test weights. Each child was made to stand still and upright with weight evenly distributed between 2 feet. Zero was readjusted after each reading on the scale. A standard measure tape was used to make calibrations on a wall nearest to 1 cm. All adolescents were made to stand against wall after removing shoes and their heels touching wall. Height was measured using flat scale while adolescent was looking straight. Based on the weight and height, the body mass index (BMI) was calculated as per the formula BMI = Weight (kg)/Height (m2). Adolescents were classified based on their BMI using, The WHO BMI classification for Asian adults (Indians), WHO reference for adolescents and Indian Academy of Pediatrics (IAP) standards.
Team of four supervisors and eight volunteered trained by a doctor for measuring BP using digital sphygmomanometer screened adolescents for hypertension. BP was determined in the right arm in sitting position after a sufficient rest, by standardized method using standard digital sphygmomanometers with a set of different sized cuffs. The cuff bladder was wide enough to cover at least two-third of the arm and long enough to encircle arm completely. Height percentile of each adolescent was determined using IAP growth charts. IAP reference for BP using height percentile was used to define hypertension. The BP level <90th percentile was considered normal. Prehypertension was defined as systolic or diastolic BP or both between 90th and 95th percentile for height for age and sex. The BP level >95th percentile is hypertension. Stage 1 hypertension is the designation for BP levels that range from the 95th percentile to 5 mmHg above the 99th percentile. Stage 2 hypertension is the designation for BP levels that are 5 mmHg above the 99th percentile. Students found to have hypertension or prehypertension on the first visit were contacted to undergo a second set of BP measurement after 10 min. Adolescents diagnosed having hypertension were referred to nearest government hospital for further evaluation and management.
This study was ethically cleared from Institutional Ethics Committee of Indian Institute of Public Health, Gandhinagar, India. Written consent was obtained from each adolescent before data collection and measurements. List of adolescents, who were suffering from or having high risk of NCDs, was shared with school management for further referral and appropriate prevention, however, kept confidential to the other stakeholders.
Data were entered and analyzed through SPSS version 20. Descriptive statistics and univariate analysis was conducted to understand the difference between the genders and expressed in the form of P value at the level of 95% of CI.
| Results|| |
Among 484 studied sample, 56% were boys and 44% were girls while 58% of them were from 10 to 14 years of age and 42% were of 15–19 years of age. Mean age of the boys was 13.9 ± 1.9 years while the mean age of girls was 14.3 ± 1.9 years. Overall, the mean age of the population was 14.1 ± 1.9 years. Majority of the study population belonged to other backward caste category followed by scheduled caste.
For this study, we defined Junk food, salty food, fast food, and food with high-fat content as per their local availability and use by the community. Various diet-related healthy behaviors, as reported by adolescents, are described in [Table 1].
No diet survey was conducted and results are presented as reported by adolescents. Only 11.6% of the study population consumed fruits daily. About 60% of them consume one or two fruits per serving. The difference between boys and girls for consumption of fruits daily was statistically significant. More than 70% of the study population consumed vegetables daily in their diet. Almost 80% of them consumed one or two katori of vegetables per serving.
Almost 69% of boys and 59% of girls consumed milk daily. The difference was statistically significant. Over 60% of boys and girls took one glass of milk per day. Occasional eating was defined as eating that food once in 2 weeks or once in a month or never. More than 40% of the study population consumed junk foods occasionally. Similarly, >60% consumed carbonated drinks occasionally. Only 27% and 14% adolescents consumed high-salt and high-fat diet occasionally. Finally, about 77% of adolescents reported that advantages of eating vegetables and fruits explained to them in the school.
Physical activity-related factors
More than 88% adolescent reported that advantages of physical activities explained to them in the school. Moreover, 87% of boys and 60% of girls reported doing some or other physical activity daily as shown in [Table 2]. This difference was statistically significant (P = 0.000). Types of physical activities among boys and girls are shown in [Table 2]. Most common physical activity among boys and girls was cycling and walking, respectively. Average duration of cycling among boys is 30 min and 26 min per day among girls. Average duration of physical activities like various sports was 40 min among boys and 55 min among girls.
About 2.2% (6) boys and 1 girl reported to having addiction of chewing tobacco. No adolescent reported having smoking or alcohol addiction. However, 83% of them reported exposure to passive smoking in the last 1 week out of which 21% reported exposure to passive smoking every day in the last 1 week.
About 60% boys and 35% girls reported that someone in the family (mainly father) was addicted to tobacco and/or alcohol. 13.3% boys and 1.9% girls reported addiction among peers mainly of chewing tobacco. Almost all adolescent (97%) reported that they would not taste tobacco or alcohol under the pressure from friends.
More than 80% of adolescents reported that ill effects of tobacco were explained to them in the school. 80% of adolescent knew that tobacco could cause disease while 51% knew that alcohol addiction could cause disease. However, correct knowledge about which diseases caused by tobacco and alcohol was very low.
Body mass index
BMI of the adolescents was classified using the WHO-BMI standards for Asians adults, WHO adolescent reference for BMI, and IAP BMI standards as shown in [Table 3].
|Table 3: Differential body mass index scores of the study population as per three different body mass index standards|
Click here to view
As per the WHO-BMI standards for Asian adults (Indians); majority of adolescents were undernourished. Only 1.2% adolescents were overweight while 1.4% were obese according to the WHO adult standards for Asians. These standards are used to define obesity or undernutrition in Rashtriya Kishor Swasthya Karyakram.
As per the WHO-BMI standards for adolescent; majority of adolescents as per this reference were normal. While 3.7% were overweight and 1.7% adolescents were obese. However, the WHO recommends country-specific standards for BMI. In India, IAP has published standards for various growth parameters of children and adolescents including BMI.
As per the IAP-BMI standards, majority of adolescents had normal BMI. Only 0.8% adolescents were obese and 4.5% were overweight. More than quarters of adolescents knew that obesity can cause any disease.
As suggested in STEPS methodology of the WHO, we also measured BP of all the study participants. IAP has also published standards for interpreting the levels of BP among adolescents. The mean SBP for boys 110 and for girls 111 and overall is 110.3 mmHg; whereas, mean DBP for boys 69.7 and for girls 69.9 and overall is 69.7 mmHg.
| Discussion|| |
This study estimated the most prevalent risk factors for NCDs among adolescents are as not eating fruits daily (P = 0.001), not doing exercise daily (P = 0.000), and having high BP (P = 0.005).
A review of few selected studies during 2001–2012 showed a prevalence of overweight among children aged 10–19 year to be 9.9–19.9%; high in both boys (3%–15.1%) and girls (5.3%–13.3%) indicating early onset of obesity,, affecting more of urban school adolescents (3.4%–6.5%),,, as compared to 0.6% among the rural adolescents with significant gender variations. In another STEPS survey from Northern India reported the higher obesity among the girls; however, in this study, overweight found to be more among boys.
Another lifestyle-related factor is dietary pattern. In previous studies among adolescents, it has been reported that inadequate amount of fruits and vegetables intake and high consumption of fast food in their dietary habits,, which is also similarly reported by this study.
Lack of physical activity among adolescent found to be a major risk factor for NCDs, however, the range of physically inactive is huge from 10% to 90% reported in various studies,, with gender variations. In this study also, lack of exercise, especially the duration of activity found to be an important factor.
| Conclusions|| |
There are two major risk factors documented in this study, that is, not having daily fruits in the diet and not doing physical activity daily among school-going adolescents. Although this study identified higher BMI as one of the major contributing risk factor, it could not able to justify the same. Because high BMI as per one standard does not mean as high for other standards, therefore the availability of three different BMI standards resulted into a challenge for classifying these adolescents. This study provides an insight to these three major BMI standards and their differences in measurement for the school-going adolescents. On the one hand, this study recommends promoting healthier practices for prevention of NCD lifestyle risk factors among school-going adolescents, and on the other hand, it recommends standardizing the BMI measurements for adolescents for India.
This study conducted on school-going adolescents only so cannot be generalized for all adolescents of the block or district of Gujarat, India.
Financial support and sponsorship
This study was funded by John D. and Catherine T. MacArthur Foundation. Funders have no role in study designing and findings from this research.
Conflicts of interest
There are no conflicts of interest.
| References|| |
Esmailnasab N, Moradi G, Delaveri A. Risk factors of non-communicable diseases and metabolic syndrome. Iran J Public Health 2012;41:77-85.
Currie C, Gabhainn SN, Godeau E, Roberts C, Smith R, Currie D, et al
. Inequalites in young people's health: Health behavior in school-aged children international report from 2005–2006. Copenhagen: World Health Organization; 2008.
Taylor RM, Gibson F, Franck LS. The experience of living with a chronic illness during adolescence: A critical review of the literature. J Clin Nurs 2008;17:3083-91.
da Silva KS, Nahas MV, Peres KG, Lopes Ada S. Factors associated with physical activity, sedentary behavior, and participation in physical education among high school students in Santa Catarina state, Brazil. Cad Saude Publica 2009;25:2187-200.
Pronk NP, Anderson LH, Crain AL, Martinson BC, O'Connor PJ, Sherwood NE, et al.
Meeting recommendations for multiple healthy lifestyle factors. Prevalence, clustering, and predictors among adolescent, adult, and senior health plan members. Am J Prev Med 2004;27:25-33.
Singh AP, Misra G. Adolescent lifestyle in India: Prevalence of risk and promotive factors of health. psychology and developing societies. Psychology and Developing Societies 2012;24:145-60.
Hazreen MA, Su TT, Jalaludin MY, Dahlui M, Chinna K, Ismail M, et al.
An exploratory study on risk factors for chronic non-communicable diseases among adolescents in Malaysia: Overview of the Malaysian health and adolescents longitudinal research team study (The myHeART study). BMC Public Health 2014;14 Suppl 3:S6.
Sunitha S, Gururaj G. Health behaviours & problems among young people in India: Cause for concern & call for action. Indian J Med Res 2014;140:185-208.
] [Full text]
Misra A, Chowbey P, Makkar BM, Vikram NK, Wasir JS, Chadha D, et al.
Consensus statement for diagnosis of obesity, abdominal obesity and the metabolic syndrome for Asian Indians and recommendations for physical activity, medical and surgical management. J Assoc Physicians India 2009;57:163-70.
Rashtriya Kishor Swasthya Karyakram. Operational Frameworks and Strategy Guidelines. Adolescent Health Division Ministry of Health and Family Welfare Government of India; January, 2014.
Indian Academy of Pediatrics Growth Charts Committee, Khadilkar V, Yadav S, Agrawal KK, Tamboli S, Banerjee M, et al.
Revised IAP growth charts for height, weight and body mass index for 5- to 18-year-old Indian children. Indian Pediatr 2015;52:47-55.
Goyal JP, Kumar N, Parmar I, Shah VB, Patel B. Determinants of overweight and obesity in affluent adolescent in Surat city, South Gujarat region, India. Indian J Community Med 2011;36:296-300.
] [Full text]
Kotian MS, S GK, Kotian SS. Prevalence and determinants of overweight and obesity among adolescent school children of South Karnataka, India. Indian J Community Med 2010;35:176-8.
] [Full text]
Aggarwal T, Bhatia RC, Singh D, Sobti PC. Prevalence of obesity and overweight in affluent adolescents from Ludhiana, Punjab. Indian Pediatr 2008;45:500-2.
Laxmaiah A, Nagalla B, Vijayaraghavan K, Nair M. Factors affecting prevalence of overweight among 12- to 17-year-old urban adolescents in Hyderabad, India. Obesity (Silver Spring) 2007;15:1384-90.
Mehta M, Bhasin SK, Agrawal K, Dwivedi S. Obesity amongst affluent adolescent girls. Indian J Pediatr 2007;74:619-22.
Khadilkar VV, Khadilkar AV. Prevalence of obesity in affluent school boys in Pune. Indian Pediatr 2004;41:857-8.
Kumar S, Mahabalaraju DK, Anuroopa MS. Prevalence of obesity and its influencing factor among affluent school children of Davangere city. Indian J Community Med 2007;32:15-7. [Full text]
Thakur JS, Jeet G, Pal A, Singh S, Singh A, Deepti SS, et al.
Profile of risk factors for non-communicable diseases in Punjab, Northern India: Results of a state-wide STEPS survey. PLoS One 2016;11:e0157705.
Jain A, Dhanawat J, Kotian MS, Angeline R. Assessment of risk factors of non-communicable diseases among high school students in Mangalore, India. Int J Health Allied Sci 2012;1:249-54. [Full text]
Kumar S, Ray S, Roy D, Ganguly K, Dutta S, Mahapatra T, et al.
Exercise and eating habits among urban adolescents: A cross-sectional study in Kolkata, India. BMC Public Health 2017;17:468.
Mahmood SE, Khan KM, Agrawal AK. Study of lifestyle disease risk factors among school going adolescents of urban Bareilly, Uttar Pradesh, India. Int J Community Med Public Health 2017;4:516-21.
Parsekar SS, Ashok L, Monteiro AD, Singh MM, Bhumika TV. Modifiable life style associated risk factors for non communicable diseases among students of pre-university college of Udupi Taluk. GJMEDPH 2015;4:1-7.
Singh AK, Maheshwari A, Sharma N, Anand K. Lifestyle associated risk factors in adolescents. Indian J Pediatr 2006;73:901-6.
[Table 1], [Table 2], [Table 3]