|Year : 2022 | Volume
| Issue : 4 | Page : 565-571
Influence of socio-economic status on lifestyle preferences contributing to childhood obesity: A cross-sectional study
Poonam Ashish Gupte, Shital Ashok Giramkar, Supriya Sudhakar Bhalerao
Obesity-Diabetes Lab, Interactive Research School for Health Affairs, Bharati Vidyapeeth Deemed (to be) University, Pune, Maharashtra, India
|Date of Submission||29-Apr-2021|
|Date of Decision||11-Jun-2021|
|Date of Acceptance||11-Jun-2021|
|Date of Web Publication||01-Sep-2021|
Supriya Sudhakar Bhalerao
Obesity- Diabetes Lab, Interactive Research School for Health Affairs, Bharati Vidyapeeth Deemed (to be) University, Pune, Maharashtra
Source of Support: None, Conflict of Interest: None
Background: Socioeconomic status (SES) is the major determinant for lifestyle preferences in individuals, contributing to development of metabolic diseases like obesity. Aims: This study was undertaken to study the influence of SES on lifestyle preferences, namely dietary habits, food beliefs, physical activity, and their contribution to childhood obesity in school children of Pune city. Settings and Design: School-based, cross-sectional, observational study. Materials and Methods: Following approval from the Institutional Ethics Committee, the study was conducted in schools representing high, medium, and low SES in Pune. Children of either sex, aged 9–14 years were recruited after obtaining parental consent and verbal assent of children. Anthropometry and body composition along with dietary choices, food beliefs, and physical activity was recorded using predesigned questionnaires. Statistical Analysis: Parametric data are expressed as mean ± standard deviation, whereas nonparametric data are expressed as median (range). Distribution of children into different weight categories and data regarding unhealthy food consumption frequency and food beliefs is expressed in percentages. Results: Of 424 total recruited children, obesity prevalence was the highest in high SES school children (10.49%) while overweight prevalence was high in middle SES school children (18.11%). Middle SES school had maximum children with high waist circumference and body fat percentage along with high frequency of unhealthy food consumption. Surprisingly, activity profile from middle SES school was significantly better as compared to other schools. Conclusion: Children from middle SES school with maximum prevalence of overweight displayed poor dietary choices, average food beliefs, and habits pressing the need for aggressive strategies for obesity prevention.
Keywords: Childhood obesity, food beliefs, physical activity, socioeconomic status
|How to cite this article:|
Gupte PA, Giramkar SA, Bhalerao SS. Influence of socio-economic status on lifestyle preferences contributing to childhood obesity: A cross-sectional study. Med J DY Patil Vidyapeeth 2022;15:565-71
|How to cite this URL:|
Gupte PA, Giramkar SA, Bhalerao SS. Influence of socio-economic status on lifestyle preferences contributing to childhood obesity: A cross-sectional study. Med J DY Patil Vidyapeeth [serial online] 2022 [cited 2022 Jul 3];15:565-71. Available from: https://www.mjdrdypv.org/text.asp?2022/15/4/565/325413
| Introduction|| |
Obesity in childhood is a significant risk factor for various non-communicable diseases occurring in adult life,,, which is growing rapidly worldwide., Increasing sedentary lifestyles and changing dietary habits play a major role in the development of obesity in childhood and adolescence.,, Considering its public health importance, trends in obesity in childhood need to be closely monitored.
India, although a developing country, is in a state of epidemiological transition due to growing urbanization and socioeconomic development. Lately, a huge increase is noted in the population with overweight and obesity. The prevalence of obesity in childhood is reported to be varying pertaining to geographical, social, and cultural norms in the different parts of the country with no reports on nationally representative studies. A study documenting the prevalence data from 16 Indian states revealed a higher percentage of obesity occurring in childhood and adolescence in Northern India compared to South zone. A combined prevalence rate of 19.3% of overweight and obesity in childhood was reported as compared to earlier prevalence of 16.3%.
There are various factors contributing to the rise of obesity in childhood, of which socio-economic status (SES) is a major determinant. The role of dietary habits such as preference to packaged and fast foods along with lack of physical activity is acknowledged as an important causative factor for obesity. Further, the influence of SES on eating and activity patterns of an individual ultimately affecting weight gain has also been explored in few studies. Unhealthy eating and physical inactivity among people from low socioeconomic groups have been reported responsible for obesity in adolescence as per a study, while another study documented higher SES as a driver for obesity in similar age group.
Pune, which was traditionally a cultural hub of the country is witnessing rapid growth in terms of commerce, infrastructure as well as education and is turning as a major metropolitan hub today. The changing economy of the city has resulted into change in food culture as evident by increase in the number of restaurants and fast food joints. There is a plethora of food choices, which are easily available and affordable with growing incomes. The next generation could be a viable target of this changing scenario.
With this background, the present study was planned for assessing influence of SES on above-mentioned lifestyle factors in school children from Pune.
| Materials and Methods|| |
Study design and setting
After obtaining approval from the ethics committee (BVDU/MC/51E), a cross-sectional study was carried out over a period from February 2015 to October 2016 among children from 3 schools. The schools were selected using convenient/purposive sampling method.
The annual income of parent was documented in case of each participating student. The socioeconomic class of each student was determined using Kuppuswamy scale. The upper class was considered as High SES, the upper and lower middle categories were clubbed as Middle SES while the upper lower and lower categories were grouped under low SES. The frequency of low, middle, and high SES students per school was calculated. If more than 60% students belong to a particular SES, the school status is termed as that particular SES category.
Sampling method and sample size
Of the different divisions per grade, one division from each grade was selected by simple random sampling. As children belonging to schools from three different SES were to be studied, a sample size of minimum 100 children from each of the schools was considered adequate.
Children of either sex aged 9–14 years from 5th to 9thgrades were included in the study following verbal assent and informed consent from their parents/guardians. Children with known history of any endocrinological disorders, sustained physical/mechanical injury (e.g., limb injury/fracture) inhibiting data collection (body composition analysis) and unable to provide assent/consent were excluded.
Once recruited, demographic information pertaining to name, age, grade, and division was collected from every child. This was followed by anthropometric measurements, which included body weight, height, body mass index (calculated as weight [kg]/height [m]2) and waist circumference along with body composition analysis using bio-impedance method. Height was measured with a wall mounted stadiometer. The children were instructed to stand without shoes and socks in an upright position, in contact with the wall for recording height. For measurement of weight, they were directed to stand straight on a digital scale with error of ± 0.1 kg. Waist circumference was measured at the upper level of umbilicus. Karada scan (Omron HBF 701) was used to estimate the body composition which included parameters such as total body fat and skeletal muscle mass.
Subsequently, depending on the medium of instruction, questionnaire in either English or Marathi language was administered to the children and information regarding their dietary patterns and food beliefs was collected. Diet details such as consumption frequency of junk food viz. fast food items such as pizzas, burgers, chips, aerated, nonaerated drinks, during a week, was documented. Aerated drinks meant carbonated soft drinks while nonaerated included fresh as well as packaged fruit juices/squashes. Frequency of eating/drinking while watching television and doing sedentary activities such as reading and playing indoor games were also recorded. The information about food beliefs included knowledge about food pyramid, opinions regarding food choices, parental role, etc. A semi-structured questionnaire was used to note details about time spent in physical activities; both indoor and outdoor, at school as well as at home.
The data collection was done during free periods to avoid wasting time of the children.
The nutritional status of children was determined using percentile growth charts recommended by Indian Institute of Pediatrics (IAP). The distribution of children into different categories of weight and data regarding unhealthy food consumption frequency and food beliefs is expressed in percentages. Parametric data are expressed as mean ± standard deviation while nonparametric data has been expressed as median (range).
| Results|| |
A total of 424 children were recruited in the study; of which 175 were girls and 249 were boys. There were 124 children from low, 138 from middle and 162 from schools with high SES. The sex wise distribution of the children was not statistically significant [Table 1].
Prevalence of overweight and obesity
Overall, overweight was found in 14.38% children while obesity was seen in 5.89% children [Figure 1]. When the data were analyzed with respect to SES, it was observed that the school with high SES had maximum prevalence of children with obesity while school with middle SES had maximum percentage of children with overweight. None of the children in school with low SES had obesity [Table 2]. The difference among the weight categories across the schools was statistically significant (P = 0.0019).
|Table 2: Number (percentage) of children in different weight groups as per socioeconomic status|
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Anthropometry and Body composition
The children from school with middle SES had bigger waist circumference as compared to children from school with high SES (P < 0.01) along with higher body fat percentage compared to children from both schools with high and low SES. The skeletal muscle mass in children from school with middle SES was significantly lower compared to that of children from school with high SES and significantly higher compared to that of children from school with low SES. Further, the difference in body fat percentage and skeletal muscle mass between children from schools with high and low SES was also statistically significant [Table 3].
The data regarding dietary profile involving junk food items such as pizzas and burgers revealed that almost equal number of children from both schools with low and middle SES consumed them per week at least once or twice. This percentage was very low in school with high SES. Consumption of aerated drinks was higher in children from school with low SES followed by children from school with middle SES. School children from school with high SES rarely consumed aerated drinks rather they preferred nonaerated drinks more. Majority of children from school with middle SES consumed nonaerated drinks too with almost 25% of them taking these drinks daily. Eating/drinking habits while indulging in other activities were prominent in children from school with low SES closely followed by children from school with middle SES while children from school with high SES did so less frequently. There was statistically significant difference among all the dietary habits across the schools (P < 0.001) [Table 4].
|Table 4: Number (percentage) of children based on dietary habits as per socioeconomic status|
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It was observed that the knowledge of food pyramid was increasing as the SES increased. The habits such as eating outside (restaurant) food at least once a week, belief that all healthy vegetables have bad taste, erratic timings for meals at home, parental pressures regarding food, etc., were more common among children from school with low SES. In spite of accepting that healthy foods don't taste bad, the percentage of children from school with high SES consuming vegetables was least. On the contrary, the children from school with low SES believed that healthy vegetables were bad in taste, but the consumption frequency of vegetables was found highest in them. There was more number of children from school with middle SES who preferred eating outside once a week and made food choices as per parental beliefs compared to children from school with high SES. The frequency of eating due to depressed mood (that can be correlated with binge eating) was documented more by children from school with high SES [Table 5].
|Table 5: Number (percentage) of children having rational food beliefs as per socioeconomic status|
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The activity profile was observed to be best in children from middle SES school, followed by high SES school. The sedentary hours were significantly more in low SES school children compared to other two schools [Figure 2].
| Discussion|| |
Our study documented overall ~20% prevalence of children with overweight and obesity irrespective of SES. This finding was in line with the study conducted in 16 states in India which has reported 19.3% prevalence. When the data were analyzed with respect to SES, a greater prevalence of obesity was observed in children from school with high SES (10.49%) which is in line with the observations by Thakor et al. where it was 12.13% for the school going children of private schools in Pune city. Surprisingly, children from school with middle SES showed maximum prevalence of overweight (18.11%). None of the children from school with low SES school had obesity, these results show consistency with results from other Indian studies., The most worrisome observation of our study was ~9% prevalence of children with overweight in school with low SES. There were a small percentage of children who were underweight in all schools including school with high SES with no statistically significant difference as per SES. This points out to the changing health scenario in the society.
Although the school with high SES had maximum number of children with obesity, waist circumference, and body fat percentage were found higher in children from school with middle SES. The skeletal muscle mass was the highest in school with high SES closely followed by school with middle SES. Both waist circumference and body fat percentage have been independently associated with the risk of cardiovascular disease., Besides, higher skeletal muscle mass with low fat mass too has been correlated with lower cardiovascular mortality. Thus, the findings denote a warning situation for children from school with middle SES who stand at a higher threshold of risk due to greater waist circumference, body fat percentage, and low muscle mass.
Dietary details of the children revealed many interesting facts. The frequency of consumption of processed and junk food was higher in children from school with middle SES almost equivalently followed by children from school with low SES. The children from school with high SES comparatively consumed these foods to a minimal extent. It has been reported that social status influences the diet preferences and dietary intake in people. Lower the SES, preference to low quality but energy dense food could be more. This observation was resonant with our finding in this study wherein children from both schools with middle and low SES displayed a liking for consumption of junk food compared to high class.
The frequency of consumption of aerated drinks was higher in children from school with low SES closely followed by children from school with middle SES. The children from school with middle SES consumed nonaerated sugary drinks also to a sizeable extent. The children from school with high SES consumed nonaerated sugary drinks more and aerated drinks minimally. Thus, consumption of sugary drinks was a major part of dietary profile of most of children. This is an important finding considering the direct association between sugar sweetened beverages and obesity and recommendations of the American Heart Association regarding the same. The preference to nonaerated drinks over aerated ones among the middle and high SES class can be attributed to the assumption of nonaerated drinks being healthier.
Regarding food beliefs, the children from school with middle SES were well aware of the food pyramid and fared slightly better in terms of food beliefs than children from school with low SES. The children from school with high SES had rational food habits, better than children from both groups with middle and low SES. Eating outside at least once every week was seen as a common belief in children from school with middle SES almost equal to the number of children from school with low SES.
Availability of multiple food choices, consumption of energy dense, calorie rich food due to better SES and excess sugar consumption in the form of drinks, despite optimal caloric intake could be a few reasons for excess burdening of calories on the body in children from both schools with middle and high SES.
The activity profile of children from school with middle SES was surprisingly better followed by children from school with high SES. Both these schools engaged the children in varied physical activities. The children from school with high SES had long school hours (~8 h) followed by school with middle SES (~6.5 h) and low SES (~5.5 h). The more active hours in school with high SES may be due to longer school timings. As per a study conducted in South Africa, the children with high SES were heavier but physically more active, watched less television compared to children belonging to low SES. Better educational qualifications of parents with high SES and emotional stability at home was considered the reason for the same. Cross national comparison of childhood obesity reported that different SES groups are at different risks, and the relationship between obesity and SES varies across countries.
Our study has few limitations. We have not calculated sample size using scientific approach/statistical formula, and hence, the power of our study is limited. We have not recorded family history of obesity in these children, due to which we could not assess the impact of heredity on weight percentiles. The school with high SES had lunch service available in the school; however, no details for the same were taken, which could have thrown more light on the effect of dietary habits. The data regarding consumption of meat were also not recorded despite its known association with obesity. We used the convenient/purposive sampling method while selecting schools, based on permission from school authorities that could hamper generalization of the observed findings. The physical activity questionnaire was a semi structured one. Hence, data regarding actual duration of rigorous physical activity, their enlistment, duration of sleep hours, and television time were missing.
| Conclusions|| |
The children from school with middle SES showed highest prevalence of overweight with elevated anthropometric measurements and body composition parameters. They displayed poor dietary choices along with average food beliefs. However, the good activity profile observed in these children could have proved as limiting factor for further weight gain in them. Overall, it can be concluded from our study that the middle socioeconomic class needs to be focused and followed for futuristic obesity implications than other socioeconomic groups.
We would like to acknowledge Dr. Sneha Kulkarni, Ms. Jyotibala Banjare and Ms. Megha Salunke for assisting us in data acquisition. We extend our thanks to Dr. Kaehalee Ghorpade, for helping us in assessment of food beliefs in low SES school. We would also like to thank the school authorities and parents of participating children in the study. A special mention to Dr. Sahebrao Mahadik for his valuable inputs regarding the study.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Freedman DS, Mei Z, Srinivasan SR, Berenson GS, Dietz WH. Cardiovascular risk factors and excess adiposity among overweight children and adolescents: The Bogalusa Heart Study. J Pediatr 2007;150:12-7.e2.
Arya SN, Kumar R. Obesity. Indian Acad Clin Med 2004;5:166-81.
Després JP, Lemieux I, Prud'homme D. Treatment of obesity: Need to focus on high risk abdominally obese patients. BMJ 2001;322:716-20.
Micic D. Obesity in children and adolescent – A new epidemic? Consequences in adult life. Pediatr Endocrinol Metab 2001;14:1345-52.
Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of childhood and adult obesity in the United States, 2011-2012. JAMA 2014;311:806-14.
Pandher AK, Sangha J, Chawla P. Childhood obesity among Punjabi children in relation to physical activity and their blood profile. J Hum Ecol 2004;15:179-82.
Giammattei J, Blix G, Marshak HH, Wollitzer AO, Pettitt DJ. Television watching and soft drink consumption: Associations with obesity in 11 to 13 year old school children. Arch Pediatr Adolesc Med 2003;157:882-6.
Smith EM, Olivier MM. Using SNPs to unravel the genetic basis of obesity. Clin Lab Int 2006:1-2/ Available at http://wrap.warwick.ac.uk/36504/
. [Last accessed on 2021Aug 25].
Unnikrishnan AG, Kalra S, Garg MK. Preventing obesity in India: Weighing the options. Indian J Endocrinol Metab 2012;16:4-6.
Ranjani H, Mehreen TS, Pradeepa R, Anjana RM, Garg R, Anand K, et al.
Epidemiology of childhood overweight and obesity in India: A systematic review. Indian J Med Res 2016;143:160-74.
] [Full text]
Sobal J, Stunkard AJ. Socioeconomic status and obesity: A review of the literature. Psychol Bull 1989;105:260-75.
Mukherjee R, Chaturvedi S. A study of the dietary habits of school children in Pune city, Maharashtra, India. Int J Community Med Public Health 2017;4:593-7.
Hills AP, Andersen LB, Byrne NM. Physical activity and obesity in children. Br J Sports Med 2011;45:866-70.
Janssen I, Boyce WF, Simpson K, Pickett W. Influence of individual- and area-level measures of socioeconomic status on obesity, unhealthy eating, and physical inactivity in Canadian adolescents. Am J Clin Nutr 2006;83:139-45.
Bhargava M, Kandpal SD, Aggarwal P, Sati HC. Overweight and obesity in school children of a Hill State in North India: Is the dichotomy urban-rural or socio-economic? Results from a cross-sectional survey. PLoS One 2016;11:e0156283.
Butsch C, Kumar S, Wagner PD, Kroll M, Kantakumar LN, Bharucha E, et al.
Growing 'Smart'? Urbanization processes in the Pune Urban agglomeration. Sustainability 2017;9:1-21.
Kishore J, Kohli C, Kumar N. Kuppuswamy's Socioeconomic Scale-Update for July 2015. Int J Preven Curat Comm Med 2015;1:26-8.
Khadilkar VV, Khadilkar AV. Revised Indian Academy of Pediatrics 2015 growth charts for height, weight and body mass index for 5–18-year-old Indian children. Indian J Endocr Metab 2015;19:470-6.
] [Full text]
Ghonge S, Adhav PS, Landge J, Thakor N. Prevalence of obesity and overweight among school children of Pune city, Maharashtra, India: A cross sectional study. Int J Res Med Sci 2015;3:3599-603.
Tharkar S, Viswanathan V. Impact of socioeconomic status on prevalence of overweight and obesity among children and adolescents in Urban India. Open Obesity J 2009;1:9-14.
Marwaha RK, Tandon N, Singh Y, Aggarwal R, Grewal K, Mani K. A study of growth parameters and prevalence of overweight and obesity in school children from Delhi. Indian Pediatr 2006;43:943-52.
Zeng Q, Dong SY, Sun XN, Xie J, Cui Y. Percent body fat is a better predictor of cardiovascular risk factors than body mass index. Braz J Med Biol Res 2012;45:591-600.
Savva SC, Tornaritis M, Savva ME, Kourides Y, Panagi A, Silikiotou N, et al
. Waist circumference and waist-to-height ratio are better predictors of cardiovascular disease risk factors in children than body mass index. Int J Obesity 2000;24:1453-8.
Srikanthan P, Horwich TB, Tseng CH. Relation of muscle mass and fat mass to cardiovascular disease mortality. Am J Cardiol 2016;117:1355-60.
Dhurandhar EJ. The food-insecurity obesity paradox: A resource scarcity hypothesis. Physiol Behav 2016;162:88-92.
Keller A, Bucher Della Torre S. Sugar-sweetened beverages and obesity among children and adolescents: A review of systematic literature reviews. Child Obes 2015;11:338-46.
Katzmarzyk PT, Broyles ST, Champagne CM, Chaput JP, Fogelholm M, Hu G, Kuriyan R, et.al., Relationship between Soft Drink Consumption and Obesity in 9-11 Years Old Children in a Multi-National Study. Nutrients. 2016.30;8(12):770-782.
Bailey RL, Fulgoni VL, Cowan AE, Gaine PC. Sources of Added Sugars in Young Children, Adolescents, and Adults with Low and High Intakes of Added Sugars. Nutrients. 2018;10(1):102-113.
Mcveigh JA, Norris SA, Wet T. The relationship between socio-economic status and physical activity patterns in South African children. Acta Paediatrica 2004;93:982-8.
Wang Y. Cross-national comparison of childhood obesity: The epidemic and the relationship between obesity and socioeconomic status. Int J Epidemiol 2001;30:1129-36.
[Figure 1], [Figure 2], [Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]