Introduction

A proper body weight is most conducive to good health. The problem of excess body weight is confronting more and more people in the prosperous communities. Because of this, obesity can be seen as the first wave of a defined cluster of non communicable diseases called “New World Syndrome” creating an enormous socioeconomic and public health burden in poorer countries (WHO,2000) . The World Health Organization has described obesity as one of today’s most neglected public health problems. Following the increase in adult obesity, the proportion of children and adolescents who are overweight and obese have also been increasing (Wong et al.,2005).

Obesity is the result of an incorrect energy balance leading to an increased store of energy mainly as fat and excess calorie in the diet and can be deadly if not cured. It is rightly said “you are shortening your life at your own dining table”.

In developing countries, the incidence of obesity is increasing because of excessive consumption of low cost starchy food, as they are cheaper than lower calorie fruits and vegetables. Statistics shows that obesity is closely associated with cardiovascular problem, diabetes, and degenerative arthritis, gout and gall bladder diseases. It also produces psychological setbacks. Few studies have been performed to study the relationship between socio economic status and obesity. So the present study is an attempt to clarify the contributions of different socio economic and dietary factors that act as precipitating factor in causing obesity .

Material And Methods

Selection of subjects

Socio-economic information

Anthropometric Measurements

The anthropometrical measurement of height and weight were taken in the morning before breakfast. To determine whether an adult’s weight is appropriate for weight, Body mass Index (B.M.I.) was computed from these. The height and weight of the subjects were measured by the method of Jeliffe (1966) and BMI was calculated by the given by Garrow (1986).

Height: The measurement of height (in cm) was taken with the help of measuring tape to the nearest 0.5 cm. and the height was measured in centimeters.

Weight: The body weight is the simplest measurement of growth and nutritional status. The subjects were weighed on a simple weighing machine (bathroom sale). The reading was taken to the nearest 0.5 Kg.

Body Mass Index: BMI is expressed as a ratio of weight in kilogram to square of height in meters.

BMI = Weight (Kg)/Height²(m)

Figure 1

Table 1.1 : Classification of subjects according to B.M.I.

The classification on the basis of B.M.I. is based on the criteria given by Garrow (1986) and Naidu et al (1991).

Waist Hip Ratio (W.H.R.): For calculating abdominal obesity, waist and hip circumferences were measured. Waist to hip ratio was calculated.

W.H.R. = Waist (cm)/Hip (cm)

Figure 2

Table 1.2: Classification of subjects according to W.H.R.

Dietary Survey Method

Statistical Analysis of Data

Results And Discussion

Perusal of table 1.3 indicated that the obesity was found more prevalent in women (62.5%) than men (37.5%) and urban (56.82%) compared to rural dwellers (43.18%). Despite the urbanization and gender, loneliness and divorced or widowed status were also the strong predictors of obesity among obese subjects rather than non-obese subjects. The reason might be that the peoples try to compensate their feeling of loneliness by over eating. Furthermore, nuclear family pattern (65.90 %) was one of the reasons for obesity as the availability of food increases.

Figure 3

Table 1.3: Relationship between socio-economic condition and obesity

In comparison to non-obese subjects, among obese subjects, the level of education was low. Amid obese subjects, the maximum affected peoples were who (39.77%) remain at home. No manual worker was found obese as their energy output remains high.

Table 1.4 revealed that mean height for the obese was a little more i.e. 1.68m as compared with the non-obese (1.67m) but the mean body weight of the obese (78.31 kg) was much higher than the non-obese (64.97 kg). The obese subjects had 20.77 per cent extra body weight than the standard weight for their height (64.84 kg.)

The value of B.M.I. for obese subjects was 28.22 as compared to standard value i.e. 22.97. Though, the B.M.I. of the non-obese subjects was slightly more (23.20) than the ideal (23.18) but that was in the normal range (18-25 kg/m²). This may be due to that it has long been recognized that in adult life with advancing years, body weights tend to rise slightly. This could be due to reduced energy requirements, hormonal change and sedentary life styles. According to waist hip ratio, all the non-obese subjects fell within the normal range i.e. (.85~. 90).

Figure 4

Table 1.4: Anthropometric measurement of non-obese vs obese subjects

Dietary data (table 1.5b) revealed that the diets of the obese were highly imbalanced. They were consuming excess of energy (118.66%), protein (126.79%), fat (195.56%), ascorbic acid (353.25%), vitamin A (112.75%), thiamine (116%), riboflavin (105.5%) and calcium (309.46%) of their R.D.A.'s. On the other hand carbohydrate, fiber and iron were being consumed in deficient amounts. The carbohydrate intake was 99.37 and of iron was 94.96 per cent of the R.D.A. The differences in R.D.A.’s were found to be statistically significant (p≤ 0.05) except for carbohydrate, iron, vitamin A and riboflavin .

Table 1.4(a) cleared that non-obese were consuming energy, protein, carbohydrate, fats , iron, vitamin C and vitamin A by 99.14, 122.71, 104.32 and 106.03, 61.78, 249.9 and 106.78 per cent, respectively of their recommended allowances. Thus except for energy, carbohydrate and fats intake which was almost balanced fiber and iron were in deficient amount and remaining nutrients were being consumed in higher amounts. The differences between worked out R.D.A. 's and mean intake of the non-obese subject were statistically significant for protein, iron, Vitamin C, thiamine and calcium and not significant for other nutrients. Thus, the non-obese were consuming diets that were better balanced in terms of all nutrients in comparison to obese subjects of present study.

Figure 5

Table 1.5 (a): Student’t’ test applied to dietary data of non-obese subjects

Figure 6

Table 1.5(b): student 't' test applied to dietary data of obese subjects

Further, it was found out that most of the subjects in both the groups did not do heavy work. Their work schedule revealed that they virtually spent their whole day on very light activities. All the subjects were almost leading sedentary lives except the manual workers and all of them were non-obese.

Conclusion

Decline in activity coupled with high calorie intake were the leading causes of obesity. The obesity was found more prevalent in women than men and urban compared to rural dwellers. Urbanization, gender, loneliness and divorced or widowed status were the strong predictors of obesity. The present dietary data indicated that obese peoples were consuming highly imbalanced diets containing more protein, fat and calcium and less amounts of fiber, iron than the Recommended Dietary Allowances. Coupled to this , the problem of sedentary life style and virtual lack of physical exercise, which are the precipitating factors for the so called diseases of urban life style i.e. obesity. A community based approach using multiple strategies including appropriate education will be required to address the problem

Acknowledgement