Introduction

There is a growing incidence of obesity around the world. Indo-Asian countries are now facing the unusual challenge of a rapid increase in obesity amid a chronic burden of undernutrition. Regardless of its close link to many metabolic disorders such as dyslipidaemia, diabetes mellitus, hypertension and cardiovascular injuries, obesity has been associated with many health hazards (Mukherjee & Mukhopadhyay, 2018).

Body mass index (BMI) or Quetelet's index is a value derived from the mass (weight) and height of a person. BMI is defined as the body mass divided by the square of body height and is uniformly expressed in kg m^-2 unit, resulting from kilogram mass and meter height. Clinicians and researchers use body mass often to determine the "normality" of one's body mass. BMI = mass (kg) / height (m²). A body mass index (BMI) of 30 kg / m2 is the generally accepted definition of obesity (Evans, Rowe, Racette, Ross, & McAuley, 2006).

Significant health issues are obesity and pain and related diseases (Hitt, McMillen, Thornton-Neaves, Koch, & Cosby, 2007). Chronic pain is much more severe and impacts work and quality of life. While obesity, as described by the Body Mass Index (BMI), was associated with pain prevalence, this association's mechanism remained unclear (Kushner & Foster, 2000).

Although the causal association between obesity and pain has not been thoroughly investigated, evidence indicates that obesity and pain adversely affect one another because they share mechanical, physiological, psychological and behavioural underlying mechanisms (Dong, Larsson, Fischer, & Gerdle, 2019).

Many recent studies have shown a close association between BMI and pain. Besides, pain levels increase across the continuum of BMI classifications, from Low-Normal BMI to Class III obesity (Wright et al., 2010).

An understanding of the relationship between obesity and pain is important to interject the process effectively. The causal link between the two is still unclear; whether obesity causes chronic pain, chronic pain causes obesity, or any other factor causes both at the same time is uncertain (McVinnie, 2013).

The World Health Organization (WHO) describes the quality of life as the perception of an individual's role in life, in the sense of the community and value systems in which they live and concerning their aspirations, values and concerns. This definition suggests quality of life as a subjective measurement and focuses on the quality of life experienced by respondents. Obesity and high BMI are associated with impaired functional capacity and reduced quality of life (QoL) in patients with chronic pain conditions (Arranz, 2017).

While the medical effects of obesity are of great concern to researchers and clinicians, obesity also has a significant negative impact on the functional ability and health-related quality of life of an individual (HRQL) (Heo, Allison, Faith, Zhu, & Fontaine, 2003).

Obesity is suspected of diminishing physical activity, hampering the ability of individuals to function effectively in their living environment, which affects their quality of life. There is a strong correlation between obesity and mental illness, which affects every aspect of an individual's quality of life. The relationship may begin early in the developmental cycle, and all the pathways connecting obesity and mental illness are not yet fully understood. What we know are the physical health factors that often occur secondary to obesity combined with social attitudes. These factors, coupled with psychological pharmacotherapy-related iatrogenic factors and several biological mediators, contribute to severe and increasingly widespread co-morbidity (Taylor, 2013).

MATERIAL AND METHODOLOGY

The participants in this study were from the community in Wardha. It is an observational cross-sectional study, which was conducted for one year. The sampling design was simple random sampling method with a sample size of 104.

Inclusion Criteria

• Both males and females

• Age group 18-75 years

• Population with high BMI

• Individuals with generalized body pain

Exclusion Criteria

• People below 18 years of age

• Pediatric population

• Bmi less than 30

Materials Used

• McGill Pain Questionnaire

• Short Form Health Survey-36.

Procedure

The institutional ethical committee clearance was obtained (IEC) DMIMS. The permission for the study was obtained from the principal of Ravi Nair Physiotherapy College, following which the work was started. The targeted population was selected from Wardha. The participants were selected as per the inclusion and exclusion criteria. The students were explained the whole procedure of the study (Figure 1).

In the present study, a total of 104 people from Wardha were selected who had generalized pain, and their age ranged between 18 and 22 years. Their BMI was calculated, and questionnaires (McGill Pain Questionnaire and Short Form Health Survey-36) were provided. They were then asked to fill the questionnaires with the answers best suited to them.

RESULT

Statistical analysis was done by using descriptive and inferential statistics using Pearson's correlation coefficient and software used in the analysis was SPSS 24.0 version, and the p-value less than 0.05 was considered as the level of significance.

BMI and pain intensity are directly related to each other, as the pain intensity increases with the increase in BMI (Figure 2). Obesity leads to increased pain intensity and impacts the quality of life of obese individuals.

A positive correlation was found between BMI and pain score (r=0.135, p=0.173), i.e. as BMI increases, the pain score also increases. A negative correlation was found between BMI and physical function (r= -0.137, p=0.164), i.e. as the BMI increases, the physical function decreases (Figure 3). A negative correlation was found between BMI and role limitation physical score (r= 0.118, p=0.23). As BMI increases, there is a decrease in physical role limitation (Figure 4).

A negative correlation was found between BMI and energy/vitality (r= -0.096, p= 0.332). With an increase in BMI, the energy/vitality also decreased (Figure 5). A negative correlation was found between BMI and health perception (r= -0.088, p= 0.376). With an increase in BMI, health perception also decreased (Figure 6).

DISCUSSION

More the BMI, i.e. more obese a person is, more will be his pain score thereby, affecting all the domains of quality of life. There is a direct relationship between obesity and pain intensity since the BMI increased; the pain intensity of the individual was also more. The sample had 104 obese individuals with higher BMI. The measurement of BMI with pain intensity, and with all the domains of quality of life was done, the higher the BMI, the more the pain score and more impaired the quality of life functional scores.

These cross-sectional data support a direct correlation between BMI and HRQoL impairments. The findings showed that more obese an individual is, more impaired is the functional score.

The result showed that as the BMI increases, the physical function score decreases, i.e. the physical function is hampered in obese individuals. A negative correlation was found between BMI and physical function (r= -0.137, p=0.164). The role limitation physical score also decreases with an increase in the BMI, and there is a limitation in physical activities of these individuals. A negative correlation was found between BMI and role limitation physical score (r= 0.118, p=0.23). As BMI increases, there is a decrease in physical role limitation. The health perception gets impaired as well, as a result, showed that the health perception score also decreases with an increase in BMI.

The pain score increases with an increase in BMI, which means the pain intensity experienced by the obese individual increases with an increase in weight. The energy or vitality score also decreases with an increase in BMI. A positive correlation was found between BMI and pain score (r=0.135, p=0.173), i.e. as BMI increases, the pain score also increases.

The more obese a person is, his energy or vitality is compromised. A negative correlation was found between BMI and energy/vitality (r= -0.096, p= 0.332). With an increase in BMI, the energy/vitality also decreased. A significant decrease was found in the individual's energy level. The study of SF-36 found that in people with extra weight, physical activity, general health and the description of physical components were inferior. Prevention of high BMI is therefore very significant because it is also highly likely to avoid harmful effects on HRQL from the mediator variables.

Research has shown that perceived health output of obese individuals is deteriorating as BMI rises. Individuals with obesity view their general wellbeing universally as worse than those with healthier weights (Kushner et al., 2000).

The aetiology and treatment of pain and obesity also included behavioural factors. In this context, inactivity and a sedentary lifestyle can lead to obesity which helps turn acute pain into chronic pain. Pain can reduce physical activity and contribute to weight gain (Wright et al., 2010).

In many studies, obesity and pain management have become topics of the interest — obesity because it has become an epidemic and social strata, and pain because the nuances of pain and pain control are increasingly understood, not to mention increased media concern around the abuse of pain medication products (Hitt et al., 2007).

The very concept of pain, which is both subjective and complex, contributes to limitations. It is difficult to quantify pain through survey techniques reliably. The estimation of pain frequency and severity is also complex. Above results were derived from an observational sample, which may be due to residual confounding or confounding from unmeasured variables that the correlations observed between BMI pain score indices of HRQL. The cross-sectional design did not allow us to test causal inferences about the association over time between BMI, pain severity and HRQL, or their relationship.

Obesity is characterized by using body mass index (BMI) cut-points. BMI does not explicitly quantify body fat, and the relationship between BMI and body fat varies according to sex, age, race and Hispanic origin. Risk of morbidity and mortality at the same BMI can vary between different racial and Hispanic groups of origin. Some studies indicate that health and mortality risks among some Asian subgroups may start at a lower BMI compared to other racial and Hispanic groups (Ogden & Flegal, 2015).

Despite the awareness we currently have, it's essential to consider how obesity is linked to chronic pain and vice versa. It is also important to be aware of the degree to which both conditions affect patient functioning and QoL and how this can be improved. The effects of chronic pain amplify the risk of obesity and hinder an obese person's development, while obesity has adverse effects on chronic pain. Therefore, to avoid this vicious loop in which global health, QoL and functionality worsen, leading to more pain and obesity, it is important to assess our patients. We must also take into consideration all the possible factors aggravating this cycle. Losing weight, lowering high cholesterol rates, decreasing abdominal fat, increasing the calorie and nutrient quality of the diet, maintaining optimum sleep time and having an individualized physical activity schedule are the examples of important approaches to accomplish and enhance the survival of obese people in time (Arranz, 2017).

Conclusion

Obesity has a complicated relationship between pain and with quality of life of an individual and is directly co-related to each other. BMI and pain intensity are directly related to each other, as the BMI increases the pain intensity also increases. Obesity leads to increased pain intensity and also affects the quality of life of obese individuals. BMI is an important factor that affects the pain intensity and quality of life.

Funding support

The authors declare that they have no funding support for this study.

Conflict of interest

The authors declare that there is no conflict of interest for this study.