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| ORIGINAL ARTICLE |
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| Year : 2014 | Volume
: 2
| Issue : 2 | Page : 63-67 |
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Prevalence and predictors of the dual burden of malnutrition among adolescents in North India
Anmol Gupta1, Deepak Sharma2, Durgesh Thakur1, Anita Thakur1, Salig Ram Mazta1
1 Department of Community Medicine, Indira Gandhi Medical College, Shimla, Himachal Pradesh, India
2 Department of Community Medicine, Post Graduate Institute of Medical Education and Research, Chandigarh, India
| Date of Web Publication | 18-Dec-2014 |
Correspondence Address:
Anmol Gupta
Department of Community Medicine, Indira Gandhi Medical College, Shimla, Himachal Pradesh
India
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/2347-2618.147345
Background: Dual burden of malnutrition comprising of both under nutrition and over nutrition constitutes an important public health problem among Indian adolescents. Objective: The objective of this study is to determine the prevalence of dual burden of malnutrition (underweight and overweight/obesity) among adolescents and to understand the role of dietary habits and physical activity in this regard. Methodology: A cross-sectional survey was conducted in Shimla district of North India. A total of 720 adolescents aged 14-19 years were selected to participate in the study. Data were collected on sociodemographic status, physical activity, dietary intake, and anthropometry. Statistical analysis was done using Epi info software for windows (version 6.0, Centre for Disease Control, Atlanta, USA). Results: A total of 298 (41.3%) of the adolescents were suffering from dual burden of malnutrition. The binary logistic regression revealed a statistically significant positive association of overweight/obesity with frequent fast food consumption (odds ratio [OR] = 4.45, confidence interval [CI] = 2.42-8.18). Individuals consuming less salt in the diet had lower odds of being overweight/obese (OR = 0.47, CI = 0.25-0.87). Similarly, individuals frequently consuming fruits in the diet had lesser odds of being underweight (OR = 0.61, CI = 0.42-0.86). Conclusion: The high prevalence of the dual burden of malnutrition in this study stresses the need for policy makers in India to adapt the current adolescent program so as to focus on both ends of the nutrition spectrum. Keywords: Adolescent, dual burden of malnutrition, underweight, overweight, obesity
How to cite this article:
Gupta A, Sharma D, Thakur D, Thakur A, Mazta SR. Prevalence and predictors of the dual burden of malnutrition among adolescents in North India. Saudi J Obesity 2014;2:63-7 |
How to cite this URL:
Gupta A, Sharma D, Thakur D, Thakur A, Mazta SR. Prevalence and predictors of the dual burden of malnutrition among adolescents in North India. Saudi J Obesity [serial online] 2014 [cited 2023 Jun 2];2:63-7. Available from: https://www.saudijobesity.com/text.asp?2014/2/2/63/147345 |
| Introduction | |  |
Adolescence is a time of rapid developmental changes. Adequate nutrition during this period is a fundamental cornerstone of an individual's health. Dual burden of the adolescent malnutrition refers to the double burden of under and over nutrition occurring simultaneously within a population. Both of these extremes of the nutrition spectrum are linked with a range of adverse health conditions. [1],[2]
Undernourished adolescents are more likely to face short stature and lower resistance to infections that in turn leads to higher risk of morbidity and mortality throughout their lives. [3],[4],[5] Overweight and obese adolescents are at risk factors of developing noncommunicable diseases and also suffer from psychological problems such as stigmatization and poor self-esteem. [6],[7]
Studies on dual burden of the adolescent malnutrition and its predictors are currently limited in India. In view of generating data on this public health problem, the present study was conducted to determine the prevalence of dual burden of malnutrition comprising of underweight and overweight/obesity among school going adolescents and to understand the dietary and physical activity practices in this regard.
| Methodology | | |
This cross-sectional study was carried out among adolescent schoolchildren of both sexes, aged 14-19 years in urban field practice area of Indira Gandhi Medical College, Shimla, Himachal Pradesh, North India. The study area (Boileuganj Ward No. 7 of Shimla Municipal Corporation) is located nearly 10 km from the medical college and has 10 high and senior secondary schools. The study was carried over a period of 14 months (September 2012 to November 2013).
Sample size was estimated based on the formula n = 4pq/L2 . Since no previous study was available from the study area, the value of "p" (prevalence of behavioral, physical, and emotional risk factor among adolescents) was selected as 50%, absolute error 5%, design effect 2, and a nonresponse rate 20%. The sample size worked out 720 school adolescents. Stratified cluster sampling was used to draw this representative sample of students from classes 9 th to 12 th in 10 randomly selected schools in the study area. Study population was divided into four strata from grade 9 th to 12 th . In all, there were 38 clusters (classes) from which 21 clusters (primary sampling unit) were selected through probability proportionate to size sampling. Finally, 36 students were selected from each class using a lottery method of randomization.
Information was obtained on relevant sociodemographic characteristics such as age, sex, physical activity, and dietary practices with the aid of an interviewer administered semi-structured questionnaire. Weight was recorded by a trained field investigator using a single electronic weighing machine (Omron Health Care India Private Ltd.). Study subjects were made to stand still and upright with weight evenly distributed between two feet. Measurement was taken to the nearest 0.1 kg. For the measuring height, each study subject was made to stand against a calibrated vertical bar with a horizontal headboard. Height was recorded to the nearest 0.5 cm. Body mass index (BMI) was calculated as per the formula BMI = weight (kg)/height (m 2 ). Age and sex-specific BMI percentiles were computed based on the Centre for Disease Control (CDC)/National Centre for Health Statistics growth curves. Study subjects were classified as underweight (<5 th percentile), normal weight (≥5 th percentile and <85 th percentile), overweight (≥85 th and <95 th percentile), and obese (≥95 th percentile).
For assessing physical activity two questions were asked: (a) "Are you currently doing moderate to vigorous intensity physical activity (which increases heart rate and breathing) at least 60 min/day for at least 3 days per week? [8] (b) Do you daily walk to school (at least 10 min of daily activity)? A "frequent vegetable intake" was defined as an individual taking vegetables at least one serving five or more days per week. A "frequent fruit intake" was defined as taking fruits at least one serving five or more days per week. A "frequent fast food intake" was defined as taking fast food (samosa, burger chips or any other packed and oily snack) >3 days per week. Extra salt intake was defined as "an individual adding salt in curd or sprinkling over salad."
The computer program used for analysis was"Epi Info software version 7 for windows (version 6.0, Centre for Disease Control, Atlanta, USA)". Binary logistic regression analysis was carried out to determine the predictors of normal weight, underweight and overweight/obese individuals. The study was approved by the Ethics Committee of Indira Gandhi Medical College, Shimla, Himachal Pradesh, India.
| Results | | |
A total of 720 students participated in this study. Their mean age was 15.4 years. About 41% were suffering from dual burden of malnutrition; out of which 33.0% were undernourished, 7.1% were overweight while 1.3% were obese.
Descriptive analysis revealed that there was no gender difference in dual burden of malnutrition (males 41.90%, females 41.7%). The age group break up showed that more adolescents in the age group 14-16 years suffered from double burden of malnutrition (43%) as compared to those in the older age group 17-19 years (35%). Studying the association between dual malnutrition and dietary habits revealed that those with a dual burden of malnutrition less frequently consumed vegetables (44.7%) and fruits (45.7%). Furthermore, 47.8% consumed fast food, and 50% added extra salt in their diet. Study subjects are watching television >3 h a day were more malnourished (44%) as compared with those watching <3 h a day (40%). Adolescents walking daily >10 min to school were less malnourished (39.5%) when compared with those walking <10 min daily (44.8%) [Table 1]. | Table 1: Sociodemographic and lifestyle correlates of dual burden of malnutrition among adolescents
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The binary logistic regression revealed a statistically significant positive association of overweight/obesity with frequent fast food consumption (odds ratio [OR] = 4.45, [CI] = 2.42-8.18). Study subjects consuming less salt intake in diet had lower odds of being overweight/obese (OR = 0.47, CI = 0.25-0.87). Similarly, individuals frequently consuming fruits in diet had lesser odds of being underweight (OR = 0.61, CI = 0.42-0.86). For normal weight individuals, the significant positive predictor was frequent fruit intake (OR = 1.60, CI = 1.13-2.25) and negative predictor was fast food consumption (OR = 0.67, CI = 0.48-0.94) [Table 2]. | Table 2: Logistic regression model for predictors of dual burden of malnutrition among adolescents
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| Discussion | | |
The present study revealed that 41.3% adolescents were suffering from dual burden of malnutrition (33.0% undernourished, 7.1% overweight, and 1.3% obese). Similar findings have been reported in various studies done in India and abroad. In a study among Northeast Indian adolescents the dual burden reported was 33.4% (underweight 28.3% and overweight 5.1%). [9] In another multicenter study in 10 different sites across India, 35.6% of adolescents were found having dual burden of malnutrition (underweight 27.1% and overweight 8.5%). [10] Internationally, a study among South African adolescents reported 43.1% adolescents suffering from dual burden of malnutrition (27.1% underweight, 11.2% overweight, and 4.8% obese). [11]
However, in contrast to our finding a lower proportion of adolescents (27.8%) were found suffering from dual burden of malnutrition in a national survey in Korea (9.1% underweight and 18.7% overweight). [12] Similarly, in another study among Nigerian adolescents in an urban area the proportion of the dual burden was 24.7% (9.9% underweight, 10.7% overweight, and 4.1% obese [13] ). The differences between studies may be attributed to the difference in study area and the different study tool used to classify nutritional status like body mass index cutoff, International obesity task force cutoff or World Health Organization Z scores cutoff. In our study, we used the CDC criteria for classifying the nutritional status.
Good nutrition plays a crucial role in maintaining the adolescent health. Our study identified a significant association between frequent fast food consumption and dual burden of malnutrition. Furthermore, frequent consumption of fruits was negatively associated this this outcome. This may be due to the reason that fruits have protective action. They are an important source of dietary fibers which prevents overweight and obesity. Furthermore, since they are important source of micronutrients they have a protective effect on under nutrition. Studies carried out by researchers around the world have recorded this association. [14],[15]
| Conclusion | | |
Dual burden of malnutrition (both underweight and overweight/obesity) are prevalent and co-existing among the adolescent school children of Shimla district in North India. This appears to be the result of their incorrect life style practices. The need of the hour is to educate adolescents to practice health lifestyle practices and promote behavior change communication so as to tide over this important public health problem.
| Acknowledgment | | |
We thank the National Rural Health Mission, Himachal Pradesh, India for funding this research work.
| References | | |
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[Table 1], [Table 2]
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