Nutritional profile of the morbidly obese patients attending a bariatric clinic in a South Indian tertiary care centre

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Background: Obesity is sweeping across continents and is a major public health concern of the modern society.

Aims: The main objective of this study was to study the demographic, anthropometric and dietary patterns of the morbidly obese and study region wise variation in their nutrient intake.

Materials and Methods: The study was conducted on 101 morbidly obese individuals from different regions of India who attended the Bariatric clinic of a tertiary care hospital in India. Their socio-demographic details, anthropometric measurements were collected. The dietary assessment was done using a 24 hour dietary recall and a food frequency questionnaire. The study was approved by the Institutional review board and informed consent was obtained from them.

Results: More than 3/4th of the patients were females and 61 per cent had Type 2 diabetes mellitus. The mean age of the male and female population was 41.3 + 15.5 years and 36.7 + 11.9 years respectively. Their mean BMI was 41kg/m2. The mean daily intake of calories was more than 2200kcal/day with a gross deficit in the intake of micronutrients. Bonferroni Test showed that there was region wise variation in dietary intake, South Indian female population had the lowest intake of the micronutrients and those from East India had the highest intake. In the male population, there was a significant regional difference in intake of Proteins (p=0.039) and Energy (p=0.024). Independent Sample T test showed that South Indian had the highest intake of Energy and proteins. Anthropometric measures showed positive relation with various macronutrient intakes.

Conclusion: The obese patients require intense counselling by a dedicated team of an endocrinologist, psychiatrist, dietician, bariatric surgeon and a social worker to make achievable changes in the quality of life of the morbidly obese patients. Regional influences must be considered when counselling the patient.

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Оbesity is sweeping across continents and is a major public health concern of the modern society [1]. Morbid obesity is a medical term describing people who have a Body Mass Index (BMI) of more than 40 or of 35 to 40 with significant medical problems, caused by or made worse by their weight [2]. This is a serious health condition that negatively impacts the physical, mental and social well-being of an individual. The morbidly obese are at a higher risk for illnesses including diabetes, hypertension, obstructive sleep apnoea, gastro-oesophageal reflux and cancer [3].

The prevalence and incidence of Obesity is increasing rapidly in developed and developing countries [3]. The global burden of Obesity is 9.8% (7.7% in males and 11.9 % in females). By 2030, it is projected to afflict 1.12 billion individuals worldwide [4].

In the United States of America, there has been a rapid increase in the prevalence of obesity across different BMIs. There has been a 50% to 75% increase in those with BMI over 40 and 50 respectively between 2000 and 2005 [5].

Data from the Gulf countries showed that adult women in the 30-60 years age group had highest prevalence of obesity. Overweight and obesity was found amongst 70­85% in men and 75-88% in women in Kuwait, Qatar and Saudi Arabia [6].

In Asia, Thailand [7] has the highest rate of obesity (6.8%) followed by Singapore (6%) [8] and China (4%) [1].

Phase I of the Indian Council Of Medical Research study conducted in three States across the Indian continent indicated that generalised obesity classified according to WHO Asia Pacific guidelines [3], ranged between 11.8% to 31.3% and was significantly higher among the urban residents compared to rural areas [9].

The paradigm shift in eating habits, from coarse traditional diets to polished and fast foods has been the major reason for this burgeoning burden. The excess consumption of processed calorie dense foods combined with a declining physical activity has triggered a positive energy balance in the general population.

This is a cross-sectional study of morbidly obese patients being managed in the Bariatric clinic of the Department of Endocrinology, Diabetes & Metabolism of Christian Medical College, Vellore, Tamil Nadu, India. This hospital is a 2600 bedded tertiary care teaching hospital catering to the medical needs of patients from all over India and its neighbouring countries. The main objectives of this study were to look at the nutrient intake and regional differences in dietary pattern of morbidly obese patients.

Materials and methods

The study was conducted on 113 morbidly obese individuals who attended the Bariatric clinic over a 6 month period (June to Dec 2016). None of the patients had prior dietary counselling. All patients with a Body Mass Index greater than 35 kg/m2 were included in the study.

The demographic details of the patients were obtained by face to face interview using a pre-tested questionnaire. All the patients were examined by an endocrinologist. Anthropometric measurements including weight, height, waist and hip circumference, of the patients were measured using standard procedures (n=113). Their BMI was interpreted according to Asia-Pacific guidelines [3].

Nutritional data of the patients was recorded by 24 hour recall along with a frequency questionnaire, by a qualified dietician. The food frequency questionnaire elicited data related to intake of cereals, pulses, vegetables, fruits, nuts & oilseeds, milk & milk products, meats , eggs and poultry. Standardised vessels and pictorial representation of foods were used to achieve accuracy in the data.

The nutrient composition of diet was computed from the book- Nutritive Value of Indian Foods [10]. Patients were provided individualized advice on diet modification for optimal nutrient intake and sustained weight loss.

The study protocol conformed to the ethical guidelines of the 1975 Declaration of Helsinki (and revised in 2000) and approval was obtained by the Institutional Review Board of Christian Medical College & Hospital, Vellore, India (IRB Min. No 1014 dated 22-06-2016).

Statistical analysis: The data was statistically analysed using SPSS version 18. Chi-square test and Pearson Correlation was used to study the association between nutrient data and demographic and anthropometric data. ANOVA analysis and post-hoc analysis (Bonferroni Test) were done to study regional difference in nutrient intake of the populations. P values <0.05 were considered statistically significant.


Table 1. Baseline characteristics of Bariatric patients




Age in years




>18 to 37






Mean Age in yearsa

4 1.4 (12.7)

38.8 (11.2)








Educational status <12th Class



>12th Class



Region of Origin South India



East India



Central India






Marital Status Married






Diabetes status Non-Diabetes









aReported in Mean and Standard deviation



Baseline details

A total of 113 morbidly obese patients were included in the study. Their baseline characteristics are presented in Table 1. The mean age of the subjects was 37.6 years (SD 12.6). This included eight adolescents in the age group of 13-17 years. More than 90 per cent of the patients were females. Half the population were educated beyond school. There were a large number of patients from East India (West Bengal). Eight of the patients (7.2%) hailed from the neighbouring countries of Bangladesh and the Gulf countries. Three-fourth of them was married. More than half the study population had Diabetes.

The above Table 2 highlights the anthropometric measurements of morbidly obese adults (BMI >34.9) who were managed at the Bariatric clinic. Only adults (age >18years) were included in this analysis. All the anthropometric measures were higher than the Asia Pacific standards [3]. The male subjects had a higher BMI than the female population. The mean waist circumference (124.7 cm) was larger than the mean hip circumference (119.9 cm) in the males, and in the female population it was the reverse (115.5cm; 121.5cm).


Energy and nutrient data

The nutrient data indicates that the male and female subjects were consuming more than 2200 calories per day. Fats constituted a major proportion of the total calories. There was a deficit in the intake of proteins.

Forty nine patients (females n=38; males n= 11) who underreported their dietary intake (total calories intake < 1800kcal/day) were excluded from this analysis to prevent data distortion.

The above figure illustrates the intake of nutrients and energy of morbidly obese male and female patients as percentages of their RDA. It is apparent that the intake of Fats and energy was grossly greater than the RDA in both the male and female subjects. However there was a deficit in the intake of micronutrient intake in this population.


Table 2. Anthropometric data of Morbidly Obese adult male (n=19) and female patients (n=85)


Male Mean (SD)

FemaleMean (SD)

Mean Weight kg

116.4 (27.0)

96.4 (14.6)

Mean Height cm

169.9 (9.0)

156.9 (6.0)

Mean Body Mass Index

42.5 (13.1)

39.3 (4.8)

Waist circumference

124.7 (22.2)

115.5 (13.9)

Hip circumference

119.9 (16.2)

121.5 (11.9)

Waist Hip Ratio

1.0 (0.1)

0.95 (0.1)

Waist Height Ratio


0.74 (0.1)


Gender and Region wise distribution of Nutrients & Energy

ANOVA was done to find if there were regional differences in the nutrient intake of patients from South India (Tamil Nadu, Karnataka, Kerala, Andhra Pradesh), East India (West Bengal, Chattisgharh, Jharkhand), Central parts of India (Madhya Pradesh, Maharashtra) and neighbouring countries (Bangladesh and the Gulf).

In the female population (n=54) there was a significant difference in the intake of fibre (p<0.001) carotene (p=0.025), niacin (p<0.001), Folic acid (p<0.019), Calcium (p<0.022) and Iron (p<0.001) between the different regions. Bonferroni Test showed that the South Indian female population had the lowest intake of these micronutrients and those from East India had the highest intake.

In the male population (n=10), there was a significant regional difference in intake of Proteins (p=0.039) and Energy (p=0.024). Independent Sample T test showed that South Indian had the highest intake of Energy and proteins.

Anthropometric measures showed positive relation with various nutrient intakes. In female subjects, Pearson correlation found that the BMI of the subjects were positively correlated with their intake of proteins (r=0.413, p=0.002), carbohydrates (r=0.280, p=0.040), fat and negatively correlated with the vitamin C (r= -0.319, p=0.019). The Hip circumference correlated with carbohydrates intake (r=.285, p=0.040).There was a strong positive correlation between the intake of fibre and micronutrients. A high fibre intake ensured a good intake of micronutrients like Iron (r=0.455, p= p<0.001), Riboflavin (r=0.567, p<0.001), Niacin (0.479, p<0.001), Folic acid (r=0.791, p<0.001) and Vitamin C (r=0.715, p<0.001).

In the case of the male subjects positive correlation was significant between waist circumference and energy intake (r=0.029, p=0.029), the hip circumference and fat and iron intake respectively (r=0.851, p=0.007; r=0.776, p=0.024).

Based on the BMI of the patients they were classified into 4 quartiles. Anova and post hoc Bonferroni test revealed that those with the largest BMI had the highest protein intake (p=0.017).


Diet Quality

The qualitative data was obtained from a sub-sample of the patients (n=52). Majority of the patients were non- vegetarians (84.7%) and consumed fish, meat and eggs. Nearly half the population skipped meals (42.3%). The most frequently missed meal was breakfast (86.4%). Three-fourths (73.3%) of them reported that dinner was their heaviest meal. Refined foods were consumed by 84.6% of them. All of them had fried snacks and bakery items three to four times a week. Carbonated drinks were also popular amongst this group. The mean fruit and vegetable consumption (n=52) was 207.14 + 117.7 gm/ day. The water consumption was 2.05 + 1.01 litres/day. The daily oil consumption in cooking was 31.6 + 14.9 gm/day.


Table 3. Mean (SD) Nutritional data of Morbidly Obese adult male and female patients per day

Males  Females






Energy kcal





Proteins gm





Fat gm





CHO gm





Fibre gm





Calcium mg





Phosphorous mg





Carotene mcg





Thiamine mg





Riboflavin mg





Niacin mg





Folic acid mg





vitamin mg





Iron mg





Percent of calories from CHO





Percent of calories from proteins





Percent of calories from fat







There is a paucity of research on the nutrient intake of morbidly obese patients from India. This study attempts to study the nutritional data of morbidly obese patients and detect any regional differences in their dietary habits.

Our study found an excess of 510 kcal per day in the female population and 100 kcal per day in the male population. Region-wise analysis found that South Indians consumed significantly more calories than those from other parts of India. We had to exclude data from forty nine patients since they underreported their diet intake. Under reporting is not uncommon in this group of subjects [11]. A US study found that 35-38% of the male and female subjects underreported their nutrient intake [12].These findings have significance in dietary surveillance and epidemiology studies.

The fat intake was higher than the RDA for Indians [10]. Added fats during food preparations were a significant contributor of calories. The mean quantity of cooking oil used for daily preparations was 31. 6+ 14.9 gm/day. This disproportionate calorie intake from fats over a period of time accrues as excess adipose tissues initiating obesity.

The diet of the study population was deficit in proteins. The male population in South India consumed significantly higher proteins than the overall population. It was interesting to find that there were no regional differences in the protein intake amongst the female population.

Similar findings have been reported by a Spanish study on the morbidly obese patients (BMI of 48.2 ± 7.8 kg/m2) who found that their mean energy intake was 2,584 ± 987 kcal/day in males and 2,094 ± 669 kcal/day in females (p < 0.05). The fats contributed 41.9% calories in males (CI 39.6 to 44.2) and 43.0% in females (CI 41.7 to 44.8) (13). The protein intake of this population was 19.1% of calories in males (CI 17.7 to 20.5) and 17.3% in females (CI 16.4 to 18.1) respectively.

It was not surprising to find that the intake of micronutrients was below the RDA. There was a deficit in the intake of micronutrients like carotene, riboflavin and Iron. This can be attributed to the poor intake of fibre rich foods like fruits and vegetables in the diet. The National Health service (UK) has recommended that an individual consume five servings of fruits and vegetables per day (fresh serving = 80gm) [14]. Our data indicated a low intake of fruits and vegetables (207.14+117.7gm/ day) which was far below the recommended intake resulting in a deficit in micronutrient intake. These patients should be encouraged to include fruits and vegetables at each meal. Thus the present obesogenic diet they are consuming should be replaced by a nutrigenic diet. A Spanish community out-reach program for the morbidly obese of BMI 45.5 kg/m2 showed positive changes in their body weight with a subsequent increase in the consumption of fruits & vegetables at the 3rd and 6th month follow-up visit [15]. Thus inculcating healthy eating habits and reinforcing them at frequent intervals shows promising results.

The food frequency assessment revealed that cereals constituted the major portions at each meal (56% to 60% of the total calories). The South Indian population had the lowest intake of fibre and this can be attributed to polished rice, which was the staple food. This refined cereal is devoid of nutrient rich fibre and B-complex vitamins and is available at a subsidised cost in the public distribution system (PDS). Millets (small high fibre grains) which was the primary food of the earlier generations, has a lower glycaemic index due to its high fibre content and higher satiety index. These nutri- cereals need to be introduced into the public distribution system so that it can be available at a subsidized cost. Amongst those from East and Central India, wheat was the staple food.


Fig. 1. Consumption of energy and nutrients by the participants in the study (male and female), as a percentage of the recommended daily rate.


Majority of them consumed fish, meat and poultry less than thrice a week. Milk, pulses and refined cereals were the major contributor of proteins. There was a distinct difference in the style of food preparations. The fish preparations were always fried prior cooking amongst those from East India. Mustard oil was popular in those from East India and refined vegetable oils were used by others.

A review paper on the global snacking pattern of the obese/overweight, revealed that the frequency of consumption, quality of food choices and context/ environment of eating snacks contribute to excess energy from fats with little nutrition. The author goes on to say that in this vulnerable population of obese/ overweight individuals, snacking often happens in the absence of hunger, in an irregular fashion and due to non-physiological cues. This snacking pattern is a major cause of obesity. Thus interventions aimed at decreasing snacking should address food choices and behavioural components [16].

Substituting with fresh fruits and vegetables will not only reduce the calorie intake but fill the micronutrient gap in this group of patients.

A study of French adults found that sweets, cereal bars, biscuits, and sodas were mostly consumed as snacks [17]. Brazilian study found that snacking was more prevalent during the afternoon and evening hours. Sweetened coffee and tea, sweets and desserts, fruit, sugar-sweetened beverages, and high-calorie salgados (fried/baked dough with meat/cheese/ vegetable) were the top five most commonly consumed snacks [18].

Our study population snacked on traditional fried snacks, bakery snacks and Indian sweets which are rich in added sugars and solid fats. Carbonated drinks and Western fast foods (burgers, pizzas) were more popular with the younger generation. Majority of them attributed to eating snacks even in the absence of hunger.

Meal pattern showed that nearly half of them skipped their meal, mostly breakfast. They indulged in a calorie dense snack at mid-morning and late afternoon/evening. Dinner was the heaviest meal for 84.6% of the study population. Emerging evidence suggests that eating irregularity and eating later in the day may be detrimental for weight control. Ensuring regular regime in eating is pivotal in weight management [19].

Recent epidemiological studies from France points out that, increased feeding frequency reduces the total secretion of insulin, insulin resistance, improves blood glucose control and blood lipid profile. The authors recommend to split the total energy intake into as many meals as our social pattern allows without exceeding our daily requirements, keeping a good balance of macronutrients and micronutrients [20]. The major problem in our population was the “uncontrolled grazing through the day” pattern which was the major root for intake of excess calorie intake.

Anthropometric measures like BMI, waist and hip circumference of our subjects positively correlated with the proteins, carbohydrates and fat intake. Thus reiterating that in these groups of patients, a daily reduction in the intake of these macronutrients is the key to weight reduction.

To our knowledge, this is the first study from Southern India that looked at the dietary pattern of morbidly obese patients. The limitation of the study was that the dietary data was obtained by the 24 hour recall method and self-reported food frequency, the accuracy of which is questionable. This output tends to over or underestimate the actual intakes. Moreover nearly one-third of them under reported their dietary intake and it was not possible to extrapolate their actual food intake. Studies with more objective measures of dietary intake will give a more vivid picture.


The Obese patients are a vulnerable group who require intense and frequent counselling by a dedicated team of an endocrinologist, psychiatrist, dietician, bariatric surgeon and a social worker to make sustained diet alterations and achieve desirable body weight within a feasible period of time.

About the authors

Mini Joseph

Christian Medical College & Hospital

Author for correspondence.


Assistant Professor Department of Endocrinology, Diabetes and Metabolism


Nitin Kapoor

Christian Medical College & Hospital



Associate professor

Shobana Ramasamy

Weill Cornell Medicine


United States

medical student

Stephen Amarjeet Jiwanmall

Christian Medical College & Hospital



Associate professor

Dheeraj Kattula

Christian Medical College & Hospital



Associate professor

Vijay Abraham

Christian Medical College & Hospital




Inian Samarasam

Christian Medical College & Hospital




Thomas Paul

Christian Medical College & Hospital




Nihal Thomas

Christian Medical College & Hospital





  1. Ramachandran A, Snehalatha C. Rising Burden of Obesity in Asia. J Obes [Internet]. 2010 [cited 2016 Aug 16];2010. Available from:
  2. WHO :: Global Database on Body Mass Index [Internet]. [cited 2016 Aug 16]. Available from:
  3. The Asia-Pacific perspective: Redefining obesity and its treatment. Melb Int Diabetes Inst. 2000;11–2. – Google Search [Internet]. [cited 2016 Aug 16]. Available from:
  4. Kelly T, Yang W, Chen C, et al. Global burden of obesity in 2005 and projections to 2030. International journal of obesity. 2008;32(9):1431.
  5. Sturm R. Increases in morbid obesity in the USA: 2000–2005. Public Health. 2007;121(7):492-496. doi: 10.1016/j.puhe.2007.01.006.
  6. Ng SW, Zaghloul S, Ali HI, et al. The prevalence and trends of overweight, obesity and nutrition-related non-communicable diseases in the Arabian Gulf States. Obesity Reviews. 2011;12(1):1-13. doi: 10.1111/j.1467-789X.2010.00750.x.
  7. Wichai Aekplakorn M, Bruce Neal M, Suwat Chariyalertsak M, et al. Prevalence and determinants of overweight and obesity in Thai adults: results of the Second National Health Examination Survey. J Med Assoc Thai. 2004;87(6):685-693.
  8. Deurenberg-Yap M, Chew SK, Lin VFP, et al. Relationships between indices of obesity and its co-morbidities in multi-ethnic Singapore. International Journal of Obesity. 2001;25(10):1554-1562. doi: 10.1038/sj.ijo.0801739.
  9. Mohan V, Pradeepa R, Anjana R, et al. Prevalence of generalized & abdominal obesity in urban & rural India – the ICMR – INDIAB Study (Phase-I) [ICMR - INDIAB-3]. Indian Journal of Medical Research. 2015;142(2):139. doi: 10.4103/0971-5916.164234.
  10. Gopalan C, Rama Sastri BV, Balasubramanian SC, others. Nutritive value of Indian foods. 1971 [cited 2016 Jan 5]; Available from:
  11. Bandini LG, Schoeller DA, Cyr HN, Dietz WH. Validity of reported energy intake in obese and nonobese adolescents. The American journal of clinical nutrition. 1990;52(3):421-425.
  12. Subar AF. Using Intake Biomarkers to Evaluate the Extent of Dietary Misreporting in a Large Sample of Adults: The OPEN Study. American Journal of Epidemiology. 2003;158(1):1-13. doi: 10.1093/aje/kwg092.
  13. Moizé V, Deulofeu R, Torres F, et al. Nutritional Intake and Prevalence of Nutritional Deficiencies Prior to Surgery in a Spanish Morbidly Obese Population. Obesity Surgery. 2011;21(9):1382-1388. doi: 10.1007/s11695-011-0360-y.
  14. Choices NHS. 5 A DAY portion sizes - Live Well - NHS Choices [Internet]. 2016 [cited 2016 Aug 26]. Available from:
  15. Nield L, Kelly S. Outcomes of a community-based weight management programme for morbidly obese populations. Journal of Human Nutrition and Dietetics. 2016;29(6):669-676. doi: 10.1111/jhn.12392.
  16. Bellisle F. Meals and snacking, diet quality and energy balance. Physiology & Behavior. 2014;134:38-43. doi: 10.1016/j.physbeh.2014.03.010.
  17. Bellisle F, Dalix AM, Mennen L, et al. Contribution of snacks and meals in the diet of French adults: a diet-diary study. Physiology & Behavior. 2003;79(2):183-189. doi: 10.1016/s0031-9384(03)00088-x.
  18. Duffey KJ, Pereira RA, Popkin BM. Prevalence and energy intake from snacking in Brazil: analysis of the first nationwide individual survey. European Journal of Clinical Nutrition. 2013;67(8):868-874. doi: 10.1038/ejcn.2013.60.
  19. McCrory MA, Shaw AC, Lee JA. Energy and Nutrient Timing for Weight Control. Endocrinology and Metabolism Clinics of North America. 2016;45(3):689-718. doi: 10.1016/j.ecl.2016.04.017.
  20. Louis-Sylvestre J, Lluch A, Neant F, Blundell JE. Highlighting the positive impact of increasing feeding frequency on metabolism and weight management. Forum Nutr. 2003;56:126-128.

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