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To assess the knowledge, attitude and practices of people regarding overweight and obesity: a cross-sectional study

India is gaining weight. Traditionally known for malnutrition, Indians now report more and more frequently with overweight, obesity, and their consequences. Indians exhibit unique features of obesity: Excess body fat, abdominal adiposity, increased subcutaneous and intra-abdominal fat, and deposition of fat in ectopic sites (such as liver, muscle, and others). Data regarding the nutritional status of adults, as determined by body mass index (BMI), indicate that 50% of Indian adults suffer from different types of chronic energy deficiency, in that they have a BMI. 2


INTRODUCTION
Obesity is becoming a major public health problem all over the world due to its link with diabetes, hypertension and other disorders related to metabolic syndrome. Developing countries are also increasingly vulnerable to the worldwide epidemic of obesity, which affects all segments of the population and appear to be at greater risk of the diseases associated with overweight and obesity. 1 India is gaining weight. Traditionally known for malnutrition, Indians now report more and more frequently with overweight, obesity, and their consequences. Indians exhibit unique features of obesity: Excess body fat, abdominal adiposity, increased subcutaneous and intra-abdominal fat, and deposition of fat in ectopic sites (such as liver, muscle, and others). Data regarding the nutritional status of adults, as determined by body mass index (BMI), indicate that 50% of Indian adults suffer from different types of chronic energy deficiency, in that they have a BMI. 2 As per NFHS 4 (2015-2016), Women who are overweight or obese (BMI≥25.0 kg/m 2 ) are 20.7% as compared to 12.6% in NFHS 3 (2005NFHS 3 ( -2006 likewise Men who are overweight or obese (BMI≥25.0 kg/m 2 ) are 18.6% as compared to 14.3% in NFHS 3 (2005NFHS 3 ( -2006. 3 the present study assessed the knowledge, attitude and practices of the people of urban slum regarding obesity.

Objective
The objective of the study was to assess the knowledge, attitude and practises of people regarding overweight and obesity.

Study area
The present study was carried out in Shivaji Nagar (Govandi) urban slum area of Mumbai city.

Study population
The study population was selected from all adults above 18 years of age; the population consists of people who have migrated from different parts of India.

Study design and study period
It was an epidemiological community-based crosssectional study conducted during the period from August 2014 to July 2015.

Sample size calculation
Sample size calculation is already been described in another study. 4 Sample size was calculated by considering the prevalence of obesity and overweight in adult population. According to NFHS-3 data (2007) the prevalence of obesity and overweight in adult population in India was 34%, [138] and the sample size has been calculated by formula n=4pq/l 2 . Where n= sample size, p=prevalence of obesity (34%) q= 100-p (66%), l= admissible error (15% of p) So the sample size will be 350.
In the given urban slum there were 50 plots, each plot contains 180 houses. The plots were chosen by selecting every alternate plot i.e. 25 plots. So for the sample size of 350, 14 houses per plot were included in the study (350/25) and thus every 13 th house with a random start was selected for enrolling the subjects. In case there was no eligible subject available in the selected house, the next consecutive house was surveyed for eligible subject. However, the next house was surveyed as per the prescheduled number. When there were more than one adult in the house, the youngest one was selected.

Study method
Systematic Sampling with a random start

Inclusion criteria
Inclusion criteria were adults living in the study area; those residing in the study-area for more than 1 year; adults consenting to be a part of the study.

Exclusion criteria
An exclusion criterion was adults not present at the selected household at the time of visit for at least three visits.

Plan of analysis
Data collected and analysed by using appropriate statistical method. Chi square test was used to test association.      Table 3, association between how subjects rate themself and BMI. As per one study, Perceived body weight remained significantly associated with actual BMI. Generally, participants' perceptions about their weight corresponded with actual BMI status. 5 but in present study, out of 51 people who thought they were overweight, 45 (88.2%) had their BMI 25 and out of 299 subjects who perceive that they are slim and fit, 98 (32.8%) of them still had their BMI 25 and above. This association was found to be significant. This is of serious concern as subjects who do not think that they are overweight but they are actually overweight according to their BMI, may not take necessary action to prevent or control obesity and its consequences.

As per
As per Table 4, showed association between views on presence/absence of health consequences of being obese and BMI. It is possible that health risk knowledge motivates people to start the weight loss process, but, does not predict success with weight loss and knowledge of health consequences of obesity and being obese was significant. 6 In present study it was seen that, 22 (73.3%) obese subjects, 79 (69.9%) overweight subjects and 147 (71%) non overweight subjects mentioned that there are health consequences of being obese but of 42 subjects who had their BMI 25 and above don't think that there are any health consequences of being obese. This association was not significant. This may be due to lack of awareness in the community, lack of IEC about obesity and its consequences and this may cause people to take less effort to prevent or control obesity as they do not know about its consequences.

Limitations
There were some limitations encountered as its being a cross-sectional study; the results we got here cannot be applied to the entire general population. The age / sex composition of different population is different like-wise education status and socio-economic status is also different for different slum population so these results cannot be applied to all other slum population.