Table 1
Socio-demographic data of the population
Demographic Categories | Percentages |
Age (in years) | 19–20 | 100 |
Education qualification | GNM | 63 |
| B.sc Nursing | 37 |
Family income | Less than 15K | 37 |
Less than 25K | 28 |
Less than 35K | 9 |
| Less than 40K | 8 |
| 40K and above | 18 |
Family type | Nuclear | 70 |
| Joint | 30 |
Table 1 shows socio-demographic characteristics of the population. All the students were between 18–19 years girls studying B.sc nursing. Family income was categorised into five classification. Most of the students i.e. 37% belong to low income category. Majority of students 70% belong from nuclear family and 30% belong from joint family.
Table 2
Response in EDE-questionnaire (n = 100)
EDE-Q score | n(%) | Mean \(\pm\) SD |
More than equal to 4 | 11 | 4.22 \(\pm\) 0.21 |
Less than 4 | 89 | 0.77 \(\pm\) 0.66 |
The table shows prevalence of eating disorder among the population. Total 100 students were approached for the study and all participants responded in the EDE questionnaire. Out of 100 students, 11 were found to have eating disorder. They scored above the cut-off marks i.e., 4 in the questionnaire. So, 11% population had eating disorder with a mean of 4.22. The prevalence of eating disorder of our study is consistent with the study by Thangaraju et al. [12] where eating disorder prevalence was found 13.6% by the same questionnaire.
Table 3
Weight category of the population with and without eating disorder (n = 100)
BMI | EDE score > 4 | EDE score < 4 | Total |
Underweight (< 18.5) | 1 | 27 | 28 |
Normal (18.5–24.9) | 1 | 44 | 50 |
Overweight (≥ 25- 29.9) | 4 | 17 | 21 |
Obesity (≥ 30.0) | 5 | 1 | 6 |
Total | 11 | 89 | 100 |
The table shows 4% students are overweight and 5% are obese who also have eating disorder. Among rest of the population most of them i.e., 44% are in normal body weight and 27% are underweight. This value is comparable with the study of Balhara et. al in 2012 where underweight value was 31.1% among medical and nursing undergraduate students [20]. Only a little percentage shows overweight and this may be due to genetic pattern or abnormal hormonal response. 5% obesity has been found among eating disorder people which is similar to the study done by Shashank et. al [14] who found 3% overweight & obesity among eating disorder females assessed by SCOFF questionnaire and 2% obesity by EAT-26 questionnaire.
Almost same percentage (17.4%) of overweight among entire population was found by Ramaiah in 2015 among female medical students living in hostel though prevalence of ED was slightly higher in that study.[15] Difference is prevalence rate among various places may be due to usage of different questionnaire.
Table 4
Amount of nutrients provided to the students from hostel canteen
Nutrients | Amount |
Energy | 1833.24 kcal |
Carbohydrate | 266.71 g |
Protein | 51.72 g |
Fat | 46.1 g |
The table shows that the food provided to the students contains less calorie & protein, more carbohydrate and fat compared to RDA of 2010. All the participants reported that they took only hostel foods. This low-calorie food may be a cause of underweight of total 28% population.
The cases of overweight and obesity were high among eating disorder participants. Incident of secret eating may be a cause of overweight. Another cause is avoidance of food for prolonged time to reduce weight. Most of the students skip breakfast due to study pressure or rush for classes. Some students prefer breakfast or dinner skipping for weight reduction. But the body functions differently in response of insulin after a long-time meal gap. Food consumption after a meal skipping increases hunger and causes insulin resistance that reduces carbohydrate utilization and storage of it as fat which triggers weight gain [21]. Further, for some persons increase food intake increases insulin secretion which stimulates lipogenesis by triggering expression of lipogenic enzymes and suppresses lipolysis by inhibiting hormone-sensitive lipase [22].
Table 5
Association between anemia and eating disorder
| Anemia | Total | Test for significance |
Present | Absent | χ2 | p (2- tailed) |
Eating disorder Yes No | 5 19 | 6 70 | 11 89 | 3.119a | 0.077 |
Total | 24 | 76 | 100 | | |
24% population has been detected with mild anemia among them 5 persons have eating disorder. The difference is not statistically significant (p > 0.05). This means eating disorder is not always associated with anemia. Incidence of anemia is also low among the whole population. The hostel diet is inadequate in iron content that may be the reason of mild early stage of anemia among some students. The symptoms of anemia were clinically tested
The study contradicts with study of Nivedita et al. where anemia case was lower among ED population but high among rest of the study population [23].
Table 6
Association between menstruation frequency and eating disorder
| Menstruation | Total | Test for significance |
Regular | Irregular | Chi-square value | p (2- tailed) |
Eating disorder Yes No | 8 85 | 3 4 | 11 89 | 7.803a | 0.005 |
Total | 93 | 7 | 100 | | |
Irregular menstruation has been observed among 7% population. 3% students have both eating disorder and irregular menstruation. The difference is statistically significant (p < 0.05). Thus, eating disorder is associated with irregular menstruation or loss of menstruation. Though 24% population has been detected with mild anemia, it does not affect menstruation frequency but puts them at risk of developing severe form of anemia or irregular menstruation in future.
Table 7
Correlation between Eating disorder global score, body fat percentage and BMI
| Global scoring | Body fat percentage | BMI |
Global scoring | | 0.427* | 0.441* |
Body fat percentage | 0.427* | | 0.813* |
BMI | 0.441* | 0.813* | |
*Correlation is significant at the 0.05 level (2-tailed).
From the table it was seen that there is statistically significant and positive correlation between mean eating disorder global score, body fat percentage and BMI. That means body fat and BMI increase with increase in eating disorder. With eating disorder, body fat percentage and BMI have moderately significant correlation. Increase body fat and weight were seen among students who were detected to have eating disorder according to questionnaire suggesting eating disorder is associated with high BMI. The high BMI may be an indicator of binge eating. But here all the students reported to have only hostel foods where portion control or meal skipping episodes were prevalent especially breakfast. Breakfast has important role in our nutrition. Skipping breakfast is associated with weight gain as it lowers satiety and increases hunger throughout the day, sometimes makes craving to the next meal or to some foods. This results in weight gain and high BMI [24].
Stress or hormonal imbalance are also responsible for increased body weight.
Body fat percentage and BMI has strongly significant positive correlation. Thus, high BMI indicates presence of more body fat. So, BMI and body fat percentage are determined as risk factors of ED.
Table 8
Correlation between subscales
| Restraint scale | Eating scale | Weight scale | Shape scale |
Restraint scale | | 0.648* | 0.687* | 0.733* |
Eating scale | 0.648* | | 0.709* | 0.750* |
Weight scale | 0.687* | 0.709* | | 0.920* |
Shape scale | 0.733* | 0.750* | 0.920* | |
*Correlation is significant at the 0.01 level (2-tailed).
There is significant positive correlationship between the subscales of EDE-Q. Among them, strongly high relationship exists between weight and shape concern. Strongly high relationship is seen between weight and shape concern subscales. This indicates people who follow weight control behaviours are definitely very much conscious about their body shape. This is applicable for non-eating disorder people also who had detected only with these two concerns but responses in other subscale concerns were low in the questionnaire.
Though family type plays a role on emotional behavior of adolescents and development of ED [25], here role of family was nil as all the participants live in hostel.
Our study has some strengths and limitations.
Advantages:-
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All the data were collected by investigator itself so chance of biasness is less.
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The current height, weight were taken from which BMI was calculated.
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Instead of a single day dietary history, 3 days history was taken. The nutrient consumption level varies with type of food. So, 3 days recall helps to better understand the dietary pattern of the population.
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Determination of menstruation pattern also helps to understand nutritional status.
Limitations:-
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The study was done in a nursing college of Birbhum district so the result cannot be generalized for all female adolescents of the district.
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The response may vary according to other questionnaires.
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The response in EDE questionnaire was marked as per participants’ reply so, some point of biasness may be present.
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3 days dietary history was taken due to time constraint. A 7 days recall will give a better understanding.
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Hemoglobin test can be done to the students found anemic by clinical symptoms.