Introduction:
Adolescence is a period of rapid physical growth and mental development. Out of 10 million deaths per year due to preventable and treatable conditions, 50% of deaths in this age group have been attributed to undernutrition. (1) Despite this many of the same population are now experiencing unprecedented rise in childhood obesity and overweight. This is ascribed to as “double burden of malnutrition”.
Inadequate nutrition in adolescents lead to several problems like decreased working capacity, impaired cognitive development, adverse reproductive outcomes and risk of metabolic diseases in adulthood. (2) Stunting in childhood is a risk factor for overweight and obesity in adulthood which in turn is a predictor of diabetes, hypertension and cardiovascular diseases. (3)
Due to rapid nutrition, economic and epidemiologic transition, India is facing a new challenge, the dual burden of stunting and overweight. (4) A glance at literature reveals that this dual burden of overweight and stunting has been documented in few countries. Dual burden can take several forms like stunting in child and overweight mothers, occurrence of stunted and overweight or obese individuals in same community, stunting in early childhood and overweight in later life, concurrent occurrence of undernutrition and overweight in same individual.(5) In various studies, the dual burden of underweight and overweight/obesity has been reported to range between 0% to 10%. (3-6) Prevalence of concurrent undernutrition and overweight has been described in countries such as Mexico, USA, south Africa, Indonesia in the form of small case studies. (6) Magnitude of this dual burden and the associated risk factors has not been explored much in India. Population level dual burden of malnutrition in adolescents is an important health issue due to varied and unique contextual factors and is a neglected area in public health. (5) Determining the magnitude of the double burden of malnutrition among adolescents and understanding the contextual factors will help in guiding them and also for policymakers to make the necessary changes to accomplish the Sustainable Development Goal of ending malnutrition in all its forms. (3-5)
Hence, present study is aimed to determine prevalence of dual burden of undernutrition, overweight and obesity at the using anthropometric parameters and haemoglobin levels and the associated risk factors among adolescents aged 10 to 17 years.
Material and Methods
This was an epidemiologic investigation with a cross sectional study design. The study participants were selected from private and Government schools which were located within the rural field practice area of Adichunchanagiri Institute of Medical Sciences, BG Nagara. Study duration was three months between1 1st July 2019 up to 31st October 2019. Study Population included school going adolescents aged 10 to 17 years from government and private schools which were located within the rural field practice area of the medical college. A cross sectional study was conducted in randomly selected three Government and three private schools which were located within the rural field practice area of the medical college in rural area of India. The students were selected by using stratified random sampling method. Ethical committee clearance was obtained and the letter number is 203/2019.
A prior permission for conducting the study was obtained from the block education officer, the institution administrators and parents. Assent was be obtained from the participants older than seven years of age. Written informed consent from the parents or guardians of the students was be obtained after briefing the research protocol to them in a meeting in presence of principal investigator
Based on the previous literature on prevalence of dual burden in adolescents in rural area, (5) a sample size of 860 was calculated by using below formula which was rounded up to 900. 10% relative precision and 95% confidence interval was followed.
Sample size= Z2pq/d2
Z = 1.96 (confidence interval of 95%), p=Prevalence of malnutrition (approximately 35%, as per the literature) (5,6) q=1-p, d =Relative precision
Inclusion criteria followed was apparently healthy school going adolescents aged between 10 and 17 years and who were willing to participate in the study. Students with overt signs of ill health like tuberculosis, hemolytic anemias, renal and cardiovascular disorders and with congenital diseases were excluded from the study.
Institution ethical committee clearance was obtained from the institutional human ethical committee. A predetermined and pretested semi structured questionnaire was administered to the students which was filled by parents at home. The questionnaire was administered by the undergraduate student in local language (kannada). The questionnaire was pre-tested in 5% (Combach’s alpha value 0.05%) of the students which included nonparticipants as well.
A complete history including age, sex, history of overt illness, history of congenital diseases, type of school as private and government, maternal education, paternal education, family size, government versus private school, socioeconomic status was included in the questionnaire.
The study was conducted in free or physical activity periods.
Data regarding age of the student was confirmed from school records.
Anthropometric measurements:
Height and weight were measured by standard technique.
Tools: Standard tools, i.e., electronic weighing machine and non-stretchable tape were used. These were prior validated.
Height was measured with holding head straight, body touching the wall and both feet together. Non-elastic tape was used which was attached to a vertical rod. Height was recorded in centimetres to the nearest of 0.5 cm.
Weight was measured without shoes and in school uniform to the nearest of 0.5 kg. The reading was obtained twice and mean was considered as final. For female students a female attender was deputed. The same investigators took both the measurements. The investigators obtained prior training in taking measurements precisely with minimal error. The weighing machine was adjusted to zero each time.
A female attender was present while taking recordings in female participants. The measurement of Waist circumference was noted at the level of umbilicus.
The data on height, weight and BMI was compared to the age and sex matched reference standard of National centre for health statistics (NCHS/WHO), 1995 (4)
The criteria proposed by WHO, was be used for estimating the various outcome variables as follows: (7)
Underweight: < 5th percentile
Normal weight 5th to <85th percentile
Overweight: 85th to <95th percentile
Obese:> 95th percentile
Haemoglobin estimation:
2 ml of blood sample was collected in EDTA tubes under aseptic precautions by a trained pathology technician. Sample was processed on automated haematology analyser Sysmex KX 21, (model), Transasia (manufacturer), India, in central laboratory of pathology department.
Definition of variables:
Stunting was considered when height for age was equal to or below 2 standard deviation of National centre for health statistics (NCHS) reference values. (1)
Body mass index (BMI) was calculated by formula weight in (kg)/height (m2).
Categories based on age and sex specific cut offs of BMI by WHO was as follows:
Underweight: < -2 SD, Overweight: >+1 SD (=BMI 25kg/m2at 19 years), Obese: >+2 SD (=BMI 30kg/m2 at 19 years). (8)
All participants in whom stunting and or underweight was present were considered as undernourished.
Anaemia: Haemoglobin levels below normal for that particular age and sex was considered as anaemia.
All female participants and males <15 years who have haemoglobin concentration <12 g/dL were considered anaemic.
All males older than 15 years who have haemoglobin concentration<13 g/dL were considered as anaemic.
Various sociodemographic factors like gender, maternal and paternal education level, type of family, size of family, occupation of head of family were assessed.
Prevalence of underweight, stunting, overweight and obesity were determined. Association with various sociodemographic factors were assessed.
Statistical analysis:
Data analysis was performed using SPSS 22.0. Continuous data was expressed as mean and standard deviation. Categorical data were expressed as proportions. Association between nutritional parameters and various risk factors was be done by chi-square test or Fisher Exact test. Logistic regression analysis was done. p <0.05 was considered as statistically significant.
Results
In the present study 900 adolescents aged between 10 to 17 years were screened.
Sociodemographic profile of study participants:
Table 1 shows the sociodemographic profile of the study participants.
| Table 1: Sociodemographic profile of the study participants. |
Sociodemographic variables |
Number of participants |
Percentage |
Age in years |
10 to 13
14 to 17 |
312
588 |
34.6
65.3 |
Gender |
Male
Female |
534
366 |
59.3
40.6 |
Maternal education |
Illiterate |
24 |
2.6 |
Primary school |
136 |
15.1 |
Secondary school |
418 |
46.4 |
PU or Diploma |
246 |
27.3 |
Graduation |
62 |
6.8 |
Postgraduation |
8 |
0.8 |
Professional |
6 |
0.6 |
Paternal education |
Illiterate |
28 |
3.1 |
Primary school |
162 |
18 |
Secondary school |
330 |
36.6 |
PU or Diploma |
258 |
28.6 |
Graduation |
92 |
10.2 |
Postgraduation |
8 |
0.8 |
Professional |
22 |
2.4 |
Mother’s Occupation |
Labourer |
38 |
4.2 |
Agriculturist |
212 |
23.5 |
Service |
44 |
4.8 |
Business |
44 |
4.8 |
Housewives |
562 |
62.4 |
Father’s occupation |
Labourer |
54 |
6 |
Agriculturist |
408 |
45.3 |
Service |
44 |
4.8 |
Business |
184 |
20.4 |
No work |
210 |
23.3 |
Socioeconomic status [Ahmad S et al 8] |
Upper, upper middle, Middle
Lower middle / lower |
198
702 |
22
78 |
Family type |
Nuclear
Joint
3 Generation |
672
210
18 |
74.6
23.3
2 |
Family size |
01 to 04
05 to 10
>10 |
600
260
40 |
66.6
28.8
4.4 |
Anaemia |
Absent
Present |
340
560 |
37.7
62.2 |
The socioeconomic status was assessed based on the Modified B. G. Prasad socioeconomic scale 2017 as mentioned in the study by Ahmed et al. The merger amongst the strata was done as in the study by Ahmad S et al (8)
Out of total 900 adolescents, 534 (59.3%) were males and 366 (40.6%) were females. The mean age of the participants was 14.37±2.05 years. Maximum number of participants, i.e., 588 (62.4%) were in the age group of 14 to 17 years. Maternal education and paternal education were seen up to secondary level in most of the participants (46.4% and 36.6% respectively). The mothers of 62.4% of participants were housewives and fathers of 45.3% of participants were farmers by occupation. Total 78% of the participants belonged to lower middle or lower socioeconomic scale. The family type among most of the participants was of nuclear type 74.6%. 66.6% of adolescents had a family size of 1 to 4. Anaemia was present in 62.2% of the study participants.
Prevalence of malnutrition among study participants:
Table 2 shows prevalence of malnutrition among study participants
| Table 2: Prevalence of malnutrition among study participants |
| BMI |
Number |
Percentage |
Stunting |
110 |
12.2% |
Underweight |
524 |
58.2% |
Overweight |
30 |
3.3% |
Obesity |
8 |
0.8% |
Dual burden |
562 |
62.3% |
The prevalence of stunting and underweight in the present study was 12.2% and 58.2% respectively. Prevalence of overweight and obesity in the present study was 3.3% and 0.8% respectively. Presence of dual burden (underweight, overweight and obesity) was 62.3%.
Gender wise distribution of prevalence of malnutrition among study participants:
Table 3 shows gender wise distribution of prevalence of malnutrition among study participants.
| Table 3: Gender wise distribution of prevalence of malnutrition among study participants |
| Variable |
Male N (%) |
Female N (%) |
Total N (%) |
Stunting |
74(67.2) |
36(32.7) |
110(12.2) |
Underweight |
344(65.6) |
180(34.3) |
524(58.2) |
Overweight |
14(46.6) |
16(53.3) |
30(3.3) |
Obesity |
6(75) |
2(25) |
8(0.8) |
Dual burden |
330(58.7) |
232(41.2) |
562(62.3) |
The proportion of stunting, underweight, obesity and dual burden was more in male adolescents i.e., 67.2%, 65.6%, 75% and 58.7% respectively. More female adolescents were overweight (46.6%) as compared to males (53.3%).
Dual Burden: The prevalence of dual burden (underweight, overweight and obesity) among the study participants was (n-562) 62.3% (Table 3).
Socio demographic profile of dual burden sample:
The association of dual burden with various sociodemographic variables is depicted in Table 4.
| Table 4: Association of dual burden with various sociodemographic variables |
|
Dual burden |
|
|
Yes |
No |
p value |
Age in years |
|
|
|
10 to 13
14 to 17 |
211
351 |
101
237 |
0.019* |
Gender |
|
|
|
Male
Female |
330
232 |
204
134 |
0.628 |
Maternal education |
|
|
|
Illiterate |
22 |
2 |
<0.001** |
Primary school |
128 |
8 |
Secondary school |
255 |
163 |
PU or Diploma |
142 |
104 |
Graduation |
11 |
51 |
Postgraduation |
1 |
7 |
Professional |
3 |
3 |
Paternal education |
|
|
0.437 |
Illiterate |
16 |
12 |
Primary school |
102 |
60 |
Secondary school |
216 |
114 |
PU or Diploma |
158 |
100 |
Graduation |
50 |
42 |
Postgraduation |
4 |
4 |
Professional |
16 |
6 |
Mother’s occupation |
|
|
|
Labourer |
26 |
12 |
0.372 |
Agriculturist |
124 |
88 |
Service |
26 |
18 |
Business |
32 |
12 |
Others |
354 |
208 |
Fathers occupation |
|
|
|
Labourer |
34 |
20 |
0.206 |
Agriculturist |
246 |
162 |
Service |
22 |
22 |
Business |
120 |
64 |
Others |
140 |
70 |
Socioeconomic status |
|
|
|
Upper, upper middle, Middle
Lower middle / lower |
200
362 |
99
234 |
≤0.001** |
Family type |
|
|
|
Nuclear
Joint
3 Generation |
430
124
8 |
242
86
10 |
0.122 |
Family size |
|
|
|
01 to 04
05 to 10
>10 |
368
168
26 |
232
92
14 |
0.622 |
Anaemia |
|
|
|
Absent
Present |
210
352 |
130
208 |
0.743 |
| Chi square test, p<0.05* statistically significant, p<0.001** statistically highly significant |
Mean age of patients presenting with dual burden was 14.35±2.227 years. Table 4 reveals that a statistically significant association was observed between dual burden and age, maternal education and socioeconomic status. Logistic regression analysis showed that late adolescents were 5 times more susceptible to dual burden (a OR -0.583, p-0.001) compared to early adolescents. The susceptibility of dual burden was 7 times and 11 times more if the mother was educated up to postgraduation and professional level as compared to when she was illiterate (a OR -7.832, p=0.026* & aOR11.189, p =0.78 respectively). The dual burden was 2 times and 3 times more if the fathers were educated up to postgraduation and professional level as compared to when they were illiterate (a OR 2.451, p=0.124 & aOR3.247, p =0.232 respectively).
The association of undernutrition and overweight/obesity with various sociodemographic variables is shown in Table 5.
| Table 5: Association of undernutrition and overweight/Obesity with various sociodemographic variables |
|
|
Underweight |
Overweight/
Obesity |
|
|
|
|
N |
Adjusted odd’s ratio |
p value |
N |
Adjusted odd’s ratio |
p value |
Age in years |
10 to 13 |
208 |
|
≤0.001* |
6 |
|
|
14 to 17 |
316 |
0.481 |
32 |
15.371 |
<.001* |
Gender |
Male |
307 |
|
0.847 |
20 |
|
0.405 |
Female |
217 |
0.969 |
18 |
1.496 |
Maternal education |
Illiterate |
6 |
|
|
1 |
|
|
Primary school |
80 |
0.000 |
0.999 |
1 |
2.456 |
0.553 |
Secondary school |
256 |
0.000 |
0.999 |
4 |
3.25 |
0.999 |
PU or Diploma |
146 |
0.000 |
0.999 |
16 |
74.911 |
.<001** |
Graduation |
32 |
0.000 |
0.999 |
10 |
40.2 |
0.995 |
Postgraduation |
2 |
0.000 |
0.999 |
4 |
37.49 |
.006* |
Professional |
2 |
1.165 |
1.000 |
2 |
132.737 |
.006* |
Paternal education |
Illiterate |
12 |
|
|
2 |
|
|
Primary school |
94 |
2.462 |
0.235 |
6 |
8.319 |
.164 |
Secondary school |
208 |
1.397 |
0.574 |
2 |
2.637 |
0.443 |
PU or Diploma |
146 |
1.42 |
0.542 |
4 |
4.207 |
0.252 |
Graduation |
46 |
1.563 |
0.439 |
5 |
6.665 |
0.124 |
Postgraduation |
4 |
2.064 |
0.232 |
6 |
7.589 |
0.133 |
Professional |
14 |
2.476 |
0.367 |
11 |
43.6 |
0.999 |
Mother’s occupation |
Labourer |
18 |
|
|
16 |
|
|
Agriculturist |
122 |
1.069 |
0.887 |
12 |
0.125 |
.033* |
Service |
24 |
1.094 |
0.662 |
4 |
3.64 |
.019* |
Business |
28 |
1.476 |
0.315 |
2 |
2.331 |
0.15 |
Others |
332 |
0.663 |
0.328 |
2 |
0.325 |
0.424 |
Father’s occupation |
Labourer |
30 |
|
|
4 |
|
|
Agriculturist |
236 |
1.506 |
0.287 |
10 |
1.921 |
0.569 |
Service |
20 |
1.33 |
0.201 |
2 |
3.222 |
0.056 |
Business |
108 |
2.404 |
.029* |
12 |
0.652 |
0.703 |
Others |
130 |
1.214 |
0.441 |
10 |
1.157 |
0.823 |
Socioeconomic status |
Upper, upper middle, Middle |
185 |
|
≤0.001** |
30 |
3.121 |
≤0.001** |
Lower middle / lower |
339 |
2.938 |
8 |
|
Family type |
Nuclear |
398 |
|
|
32 |
|
|
Joint |
120 |
0.41 |
0.134 |
4 |
1.197 |
0.896 |
3 Generation |
6 |
0.584 |
0.384 |
2 |
4.078 |
0.381 |
Family size |
01 to 04 |
336 |
|
0.136 |
32 |
|
|
05 to 10 |
164 |
1.823 |
0.191 |
4 |
1.19 |
0.879 |
>10 |
24 |
1.222 |
0.645 |
2 |
2.648 |
0.419 |
Anaemia |
Absent |
194 |
|
|
16 |
|
|
Present |
330 |
0.871 |
0.127 |
22 |
1.001 |
0.061 |
| Logistic regression analysis. At p <0.05* statistically significant. |
Underweight:
The odds of being underweight was more in the age group of 14 to 17 years (a OR-0.481, p -≤0.001**) as compared to when they were in their early adolescents.
The susceptibility of being underweight was 2 times more when the fathers of the adolescents were businessmen by occupation (a OR-2.404, p-.029*). this difference was statistically significant.
The susceptibility of adolescents of being underweight was higher by 2.4, 2.0- & 2.4-times when their fathers were primary education, postgraduates or had acquired professional degrees respectively as compared to when the fathers were illiterate. But this was not statistically significant (p - 0.235, 0.232,0.367 respectively)
The adolescents were 1.8 times more susceptible for being underweight when they lived in a joint family as compared to when they stayed in nuclear family, but this difference was not statistically significant. (a OR-1.8, p-0.191).
Overweight and Obesity:
The odds of being overweight/obese was more in the age group of 14 to 17 years (a OR-15.37, p ≤0.001**) as compared to those in early adolescents. This difference was statistically significant.
The adolescents were more susceptible for being overweight/obese when their had received PU or diploma degree, postgraduation and professional education with odds ratio and p value being a OR – 74.9, p≤0.001, aOR-37.4, p-0.006*, aOR-132.7, p-0.006* respectively.
There was 7.5 times and 43 .6 times increased susceptibility of being overweight/obese when the fathers of the participants had received postgraduation and professional education respectively (p-0.133 &0.999 respectively). But this difference was not statistically significant.
Living in joint type of family had a higher chance of being overweight/obese (a OR -4.07, p-0.381) than living in a nuclear family. However, this difference was not statistically significant.
The susceptibility of being overweight/obese was 2.6 times more when the adolescent was in a family size consisting of more than 10 members as compared to those who belonged to a family size of less than 4. However, this difference was not statistically significant.
Discussion
Adolescent age group is a key component of any population consisting of individuals between 10 to 19 years of age. Accounting for one fifth of the world population, about 87% of the adolescents reside in developing countries. [8,9] Stunting in childhood is a risk factor for overweight and obesity in adulthood which in turn is a predictor of diabetes, hypertension and cardiovascular diseases. (3)
Dual burden exists in three forms. First form of dual burden is at the individual level i.e; the presence of undernutrition and overweight/obesity in same individual. Second form of dual burden at the household level is characterized by the presence of overweight or obesity in mother and undernutrition in the child. Third category of dual burden is at the population level wherein individuals with undernutrition co exists amongst individuals with overweight and obesity. (10) In present study an attempt was made to determine the prevalence of dual burden at the population level.
This dual burden was initially described to occur in adults is now being noticed in childhood as well as in adolescents. (6) A review by Rishi et al revealed that the dual burden is common in low- and middle-income countries. (6) Magnitude of this dual burden and the associated risk factors in not known in South India.
In the present study, the prevalence of dual burden was 62.3% which included 58.2% of adolescents with undernutrition and 4.1 % overweight/obese individuals. Similar findings were reported by Ahmad et al who observed dual burden among 55.6% in adolescent females. (8) In their study the prevalence of undernutrition was 47% which was slightly lower than that of the present study (58.2%). The overweight/ obesity prevalence in their study was higher (8.6%) than that observed in the present study (4.1%). A slightly lower prevalence of 47% of dual burden was reported by Gupta et al. (11) In a study by Jeemon P et al, who analysed 3750 adolescents across 10 industrial sites in India, observed that the prevalence of dual burden was 35.6% which was lower than that reported in the present study. (12) The authors noted that the prevalence of underweight and overweight among the study population was 27.1% and 8.5% respectively. Similarly, low prevalence of 33.1% dual burden was noted by Singh et al in a study conducted among the adolescents in an urban area of Manipur. (13)
Studies from other parts of the world revealed a lower proportion of dual burden of underweight and overweight across the population. (5,6,8-12) The substantial variation of dual burden across the countries as well as within India could be due to the variations in the methods, tools and criteria used for measuring and defining the variables. Likewise, the variances in the baseline characteristics of the study population would vary across the countries and also within India, which may play a role in the variations observed. (5,6, 8)
The prevalence of undernutrition in present study was 58.2%. Whilst Ahmad et al 47% and Gupta et al reported a slightly lower prevalence of undernutrition as 47% and 33% respectively, Warraich HJ et al reported a prevalence of 52% which was in accordance with that of our study. (8,11,14) In the present study, among the various socioeconomic variables examined for undernutrition, a significant association was observed with age, socioeconomic status and father’s occupation. In present study prevalence of undernutrition was more in late adolescents. Similar findings were observed by Venkaiah et al, who reported an increase in prevalence of undernutrition with increasing age. (15) A significantly high prevalence of undernutrition was noted in low-income group which was similar to that reported in other studies in the literature. (2,15,16) Fathers of adolescents who were businessmen by occupation had a higher prevalence of undernutrition in present study. Similar findings were reported by Venkaiah et al. (15) In the present study, stunting was observed in 12.2 % of adolescents. A similar finding of 17. 4% adolescents with stunting was observed by Senbanjo et al (2) However a higher stunting prevalence of 39% and 27.8% was recorded by Venkaiah et al and Bisai et al respectively. (15,18)
| Table 6: Comparison of prevalence of underweight, stunting, overweight & obesity and dual burden among various studies and present study. |
| Variables |
Ahmad et al [8] |
Gupta et al [11] ] |
Jeemon Pet al[12] |
Singh et al[13] |
Warraich et al [14] |
Venkaiah et al [15] |
Ramachandran et al [17] |
Bisai et al[18] |
Present study |
Underweight |
47.0% |
33.0% |
27.1% |
|
52% |
18.6% |
- |
28.3% |
58.2% |
Stunting |
- |
- |
|
|
|
39% |
- |
27.8% |
12.2% |
Overweight |
5.9% |
7.1% |
8.5% |
|
8% |
|
Boys
17.8% |
Girls-
15.8% |
- |
3.3% |
Obesity |
2.7% |
1.3% |
|
6% |
|
3.6% |
2.7% |
- |
0.8% |
Dual burden |
55.6% |
41.3% |
35.6% |
33.1% |
|
- |
- |
- |
62.3% |
The prevalence of overweight and obesity in the present study was 4.1%. However various other studies from India recorded a slightly higher prevalence of overweight and obesity i.e., 8.4 to 14%. Overweight or obesity was seen more frequently among the late adolescents. Pubertal growth spurt compounded with their willingness and freedom to choose their own foods would have attracted them towards the more readily available fast foods in market leading to access weight. (8) In the present study among the various socioeconomic variables examined for overweight and obesity, statistically significant association was noted with maternal education and occupation. Adolescents whose mothers received PU or diploma degree, post-graduation and professional education were at significant risk of being overweight or obese, which was similar to that reported by Ahmad et al and Ramachandran et al. (8,17) The adolescents whose fathers were educated up to postgraduation or professional course were 7 times and 43 times more susceptible for being overweight or obese. In spite of the parents being educated, the parental attention towards eating habits of their children is lacking. Similar higher education consequently leads to increased family income which in turn provide easy availability to fast processed food. Studies have well established an association between overweight obesity and high economic status. (5,6,810,11) Our findings also demonstrate the concept of increase in obesity with increased income.
In the present study, stunting was observed in 12.2 % of adolescents. A similar finding of 17. 4% adolescents with stunting was observed by Senbanjo et al. (2) However a higher stunting prevalence of 39% and 27.8% was recorded by Venkaiah et al and Bisai et al respectively. (15,18) The findings of the present study adds to the data on the nutrition status of adolescents from a rural area in South India. The major component of dual burden in the present study was because of undernutrition than obesity. This is explained by the observation that 78% of the participants belonged to the low socioeconomic status. This calls for an imperious need to take preventive and corrective measures to curb undernutrition.
Limitation
The limitation of the study was it was school based study and hence the results may not be applicable at the community level. However large sample size provided conclusive results.
Conclusion
The prevalence of dual burden was high among adolescents. The major part of this dual burden was due to undernutrition rather than overweight or obesity. Hence, there is a need for policy makers to take measures to combat this dual burden with more emphasis on undernutrition to reduce the morbidity and mortality associated with this. This data on dual burden is important for formulating new policies or modulating the existing one’s for tackling the dual burden.
Recommendations for Future Research
Further studies to create data base of nutritional status of adolescents from different parts of the country is needed in order to strengthen the existing policies on adolescent health for their wellbeing.
Acknowledgement
Authors acknowledge Rajiv Gandhi University of Health Sciences, Bengaluru, Karnataka for providing the financial assistance for conducting the study. Authors also thank, Dr MG Shivaramu, Principal, Adichunchanagiri Institute of Medical Sciences, Dean (Health Sciences), Adichunchanagiri University, and Dr Vijay Shankar S, Professor & HOD, Department of Pathology, for the support provided.
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