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Indian Journal of Community Medicine

Calorie and Protein Intake and its Determinants Among Adolescent School Girls in Delhi

Author(s): A. K. Sharma, D. Shukla, A.T. Kannan

Vol. 30, No. 1 (2005-03 - 2005-03)

Abstract

Research Question

  • Is protein and calorie intake of adolescent school girls adequate?
  • What determines the dietary intake of adolescent school girls?

Objectives : This study examines the calorie and protein intake and its determinants among adolescent school girls in Delhi.

Study Design. : Cross sectional.

Setting : A government and a private school in Delhi.

Participants : 336 adolescent girls studying in class VIII to XII.

Statistical Analysis : t-test, ANOVA, linear regression.

Results: The calorie intake was analysed for 153 and 148 respondents from government school and 153 private school students. The average calorie intake among government and private school students was 827.9 ± 191.2 and 1491.3 ± 541.0 respectively (p<0.001). Corresponding figures for protein intake were 29.95 ± 6.7 gm and 57.49 ± 20.9 gm respectively (p < 0.001). Family size, number of siblings and income of family emerged as significant predictor variables for low calorie and protein intake. Conclusion : The daily protein and calorie intake was found to be lower than the recommended dietary allowance. The deficit was more profound in respondents of government school, and lower socio economic group. Nutrition intervention in terms of education and awareness is required in order to improve dietary intake.

Key Words : Calorie, Protein, Adolescents, Recommended Dietary Allowances, Dietary Intake

Introduction

Adolescence is a crucial period in a woman's life. Health and nutritional status during this phase is critical for the physical maturity, which in turn influences the health of the offspring. It is seen that the rate of low birth weight, prematurity and neonatal and infant mortality is high among children born to malnourished adolescent girls1. Adolescents constitute 21.2% of the total population of India2. In India, malnutrition is an important public health problem among children and adolescents. Adequacy of dietary intake in terms of calorie and protein are important in order to improve the chances of child survival and safe motherhood. In this regard, it is pertinent to examine the factors that determine the calorie and protein consumption pattern of adolescent girls, in order to plan suitable intervention measures to correct the deficits in dietary intake. Therefore this study was conducted to assess the calorie and protein consumption and identify the factors influencing their consumption patterns among adolescent girls of Delhi.

Methodology

Dietary intake may be assessed by various method, as for example diet recall interview, food frequency questionnaire (FFQ), diet records etc.3. A food frequency questionnaire was designed, based on Willet's FFQ5. A pilot survey was carried out among adolescents to identify the food items commonly eaten by them. The dietetics department of GTB Hospital was also consulted in this regard. Calorie and protein content of common Indian food items was calculated using tables on nutritive value of Indian foods6. The FFQ was pilot tested on 20 adolescent girls and compared with 24 Hr. recall method. It showed an underreporting of calorie consumption by less than 3% and protein consumption by less than 1%, hence it was accepted as standard tool for data collection. A cross sectional study design was selected. In order to determine the factors influencing calorie and protein intake, it was decided to recruit adolescent girls from a government sponsored school. Such schools because of subsidized education are usually attended by adolescent girls from lower socio economic strata. Another privately owned school was selected for recruitement of students belonging to higher socio economic strata.

The sample size was calculated in order to find a difference in protein intake of 10% among the two group of adolescent girls at a significance level of 5%. The estimated sample size was 168 in each group. All students enrolled in VII to XII standard were offered to participate in the study, expected to be in the age range of 13 to 17 years. All students were explained the objectives of the study by one of the authors. An informed consent in writing was obtained from all those students who agreed to participate in the study. One hundred sixty students from the government school and one hundred sixty two students from the private school finally participated. The FFQs were analyzed to estimate the average calorie and protein consumption per day. The students with estimated calorie intake of less than 500 calories per day and more than 3000 calories per day were considered incorrect and excluded from the study. Similarly, students with estimated protein intake of less than 20 grams and more than 120 grams were also excluded. Thus calorie intake was analyzed for 153 government school and 148 private school students. Similarly protein intake was analyzed for 145 government school and 153 private school students.

Univariate analysis was performed using unpaired t-test and ANOVA. Multivariate analysis was performed using linear regression.

The socio economic and demographic profile of all the 329 students is given in table I. Seventy girls from government school and four girls from private school could not recollect their date of birth correctly, hence age could not be calculated.

Results

Table I : Socio-economic and Demographic Profile of Respondents.

Demographic variables Government School Private School Total
Standard number % number % number %
VIII 35 52.2 32 47.8 67 20.4
IX 34 50.0 34 50.0 68 20.6
X 26 42.6 35 57.4 61 18.5
XI 34 50.0 34 50.0 68 20.6
XII 33 50.7 32 49.3 65 19.9
Family Income Per Month
≤ 3,000 58 35.8 00 0 58 17.6
3,001 - 7,000 71 43.8 00 0 71 21.6
7,001 - 12,000 07 43.8 29 17.4 36 10.9
12,001 - 20,000 01 0.6 75 33.9 76 23.1
>20,000 0 0 53 31.7 53 16.1
Not Known 25 15.4 10 6.0 35 10.7
Family Size
≤ 5 71 43.8 123 73.7 194 59.0
6 - 9 64 39.5 40 23.9 104 31.6
> 10 25 15.5 02 01.2 27 08.2
No response 02 01.2 02 01.2 04 01.2
Mean ± S.D. 6.75 ± 3.07   4.92 ± 2.53   5.82 ± 2.53  
Birth Order
1 41 25.3 61 36.5 102 31.0
2 78 48.1 76 45.5 154 46.7
3 26 16.1 18 10.8 44 13.4
> 4 16 09.9 09 05.4 25 07.6
No response 01 00.6 03 01.8 04 01.3
Mean ± S.D. 2.16 ± 1.12   1.88 ± 0.94   2.02 ± 1.04  
Number of total Siblings
0 0 0 6 03.6 6 01.8
1 10 6.2 52 31.1 62 18.9
2 55 33.9 53 31.8 108 32.9
3 38 23.5 30 17.9 68 20.6
> 4 59 36.4 26 15.6 85 25.8
Mean ± S.D. 3.36 ± 1.74   2.16 ± 1.29   2.76 ± 1.64  

Therefore the standard in which a student was studying was taken as a proxy measure for age. The protein and calorie intake among the two groups is given in Table II. The mean protein and calorie intake among girls from private school were 1.91 and 1.80 times higher than that among the governement school girls respectively. An inverse linear association was observed between monthly income of the family, family size and number of total siblings with respect to protein and calorie intake. About two thirds of the government school students did not know about their father's education and occupation, hence these variables were not included in the analysis.

Table II : Comparison of Protein and Calorie Intake Among Different Groups.

Parameters Protein intake Calorie intake
n Mean ± S.D. p n Mean ± S.D. p
Type of school
Government School 145 29.95 ± 6.7 - 153 827.9 ± 191.2 -
Private School 153 57.49 ± 20.9 + 148 1491.3 ± 541.0 +
B.Family income per month
< Rs. 3000 52 29.1 ± 6.3   55 775.7 ± 143.3  
Rs. 3001-7000 62 29.9 ± 6.6   66 849.0 ± 201.9  
Rs. 7001-12000 33 52.2 ± 19.3   31 1325.4 ± 412.8  
Rs.12001-20000 68 57.8 ± 20.7   68 1483.9 ± 550.6  
> Rs. 20001 50 58.0 ± 21.7   49 1514.0 ± 586.9 +
C. Family Size
< 5 176 48.1 ± 22.2   178 1244.1 ± 559.1  
6-9 94 39.6 ± 17.2   98 1042.8 ± 431.5  
> 10 25 32.8 ± 9.3 * 26 925.2 ± 303.0 +
D. Order of birth
1 92 46.3 ± 21.8   93 1160.9 ± 500.8  
2 136 45.7 ± 22.3   138 1194.1 ± 561.2  
3 43 38.8 ± 15.3   43 1075.5 ± 410.3  
> 4 23 35.9 ± 3.7 * 23 986.7 ± 433.8 NS
E. Number of siblings
0 5 54.4 ± 21.3   5 1442.9 ± 548.9  
1 55 53.3 ± 24.2   54 1338.7 ± 576.5  
2 97 45.1 ± 21.2   98 1174.9 ± 524.9  
3 61 40.5. ± 19.3   64 1054.3 ± 517.2  
> 4 78 37.8 ± 18.0 + 78 1025.8 ± 382.3 $
NS = Not significant * P<0.05 P<0.001, P<0.01

Discussion

Of the 329 adolescent girls, who filled up the FFQ, the demographic profile suggest that there is fair representation of different socio-economic group. It was observed that majority of students from the government school were from lower socio-economic group because the education is almost free. The average family size of a private school student was significantly less than that of a government school student. A government school student was 3 times more likely to have three or more siblings compared to a private school student (OR = 2.96; 95% Cl = 1.84 - 4.76, p > 0.000). However no significant difference was observed with respect to gender of the siblings.

The mean protein intake of 298 students was 44.09 ± 20.9 grams. The protein intake on an average is 30% less than what is recommended by Indian Council of Medical Research (ICMR)7. The deficit was more pronounced in case of government school students (50%) then the private school students (5%). This could be attributed to poor economic status of the children studying in government schools. In fact, table II shows that the average intake of younger students of private school was almost normal. Predictably, the protein intakes showed a linear trend with respect to age of the students. However gross difference was observed regarding protein intake between government and private school students. Chugh et al in their study of dietary habits of affluent adolescent girls reported that protein and calorie intake was deficient in affluent girls of Delhi9. In the study conducted by Nagi et al, there was no difference in calorie and protein intake in different income groups9. Chaturvedi et al reported 23% to 32% less protein intake among adolescent girls in rural area of Rajasthan10. To understand the influence of various factors on protein intake, a multivariate analysis was performed using linear regression. The two predictors for protein intake were income status and family size.

In order to further understand the protein intake pattern, the mean intake was calculated between government and privates school students after adjusting for other socio economic variables, viz. income, family size, birth order and number of siblings, the difference persisted throughout between the students of two schools. Thus suggesting that it is an important marker for protein intake among adolescent school girls. Regarding calorie intake, it was observed that overall calorie intake was quiet poor compared to the recommended values. The mean calorie intake for 301 adolescent school girls was 1155.9 ± 522.7 which is only 56% of recommended daily calorie intake7. For the government and private schools, the values were 827.4 ± 191.2 and 1491.3 ± 541.0 respectively. In each weight and age category, the calorie intake was less compared to the recommendations of ICMR. Same are the observations of other researchers8-10. The deficit in calorie intake in our study is 20% to 35% in various age groups of private school respondents and 55% to 64% in case of government school respondents. Inadequate calorie consumption among girls is also reported by Qamra et al among both higher and lower socio economic groups in Chandigarh11. They found that 64% girls were consuming less than adequate calories. This difference was highly significant. In contrast. Mehta reported a higher calorie intake among 16 and 17 year old girls from a school of Delhi, which caters to higher socio-economic group. However, the method used in her study was 24 Hour recall method12. In the National Health and Nutrition Examination survey of the United states, the calorie intake among 16 to 19 year old girls was found to be 1965.61 calories13. Similar findings are reported by Lluch et al14. It makes us conclude that among the affluent class and in developed countries, the calorie intake is remarkably higher. However, the methodology used for assessment of calorie intake in these studies is different from that of ours.

The socio-economic factors that significantly influenced calorie intake were income, number of siblings and weight of the students. This difference became more prominent, after adjusting for type of school i.e. government or private. However regression analysis showed that the only predictor variable was income of the family. Regression after adjusting for school type, showed that in case of government school, it was number of the siblings and for the private school, it was none.

Conclusion

The calorie and protein intake of the adolescent girls is much lower among the lower socio economic group adolescent girls. Even in the comparatively better economic status girls, the intake fell short of requirement. In our study, income and number of siblings emerged as predictor variables. It may be used to identify underfed adolescent girls and suitable interventions in the form of nutrition education and emphasis on improvement of food intake may be made in order to reduce the deficits.

Acknowledgement

The author acknowledge the financial assistance provided by the Indian Council of Medical reasearch, New Delhi for conducting the study.

References

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  2. Census of India 1991. Table c-6, Part-IV, Social and cultural tabls. Registar General of India. Census data online.
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  10. Chaturvedi S, Kapil U, Gnanasekaran N, Sachdev HP, Pandey RM, Bhanti T, Nutrient intake amongs adolescent girls belonging to poor socioeconomic group of rural area of Rajasthan. Indian Pediatr 1996; 33(3): 197-201.
  11. Qamra SR, Mehta S, Deodhar SD. Physical growth in school girls: relationship to socio-economic status and dietary intake-II. Indian Pediatr 1990;27 (10): 1051-65.
  12. Mehta M. Prevalence of obesity amongst affluent senior secondary school girls of 16 and 17 years age group in Delhi. Thesis submitted to University of Delhi for MD (Community Medicine). 2003.
  13. Toriano RP, Briefel RR, Coarroll MD, Bialostosky K. Energy and fat intakes of children and adolescents in the United states: data from the National Health and Nutrition Examination Surveys. Am J Clin Nutrition 2000; 72 (supple): 13438-535.
  14. Lluch A, Herbeth B, Mejean L, Siest G. Dietary intakes, eating styles and overweight in the Stanislas Family Study. Int J Obes Relate Metab Disord 2000; 24 (11): 1493-99.

Deptt. of Community Medicine,
University College of Medical Sciences Delhi-110 095
E-mail : [email protected]

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