|Year : 2020 | Volume
| Issue : 1 | Page : 21-27
Prevalence of obesity among type 2 diabetes mellitus patients in urban areas of Belagavi
Jambulingam Vasanthakumar1, Sanjay Kambar2
1 Department of Community Medicine, Panimalar Medical College Hospital and Research Institute, Chennai, Tamil Nadu, India
2 KLES Diabetes Centre, KLES Dr. Prabhakar Kore Hospital and Medical Research Centre; Department of Community Medicine, KLE University's J.N. Medical College, Belagavi, Karnataka, India
|Date of Submission||28-Sep-2018|
|Date of Acceptance||02-Dec-2019|
|Date of Web Publication||23-Jan-2020|
Dr. Jambulingam Vasanthakumar
Department of Community Medicine, Panimalar Medical College Hospital and Research Institute, Chennai, Tamil Nadu
Source of Support: None, Conflict of Interest: None
BACKGROUND: Diabetes is a major disease burden in India, and we are home to the second largest number of diabetes cases in the world with currently over 72 million cases of diabetes. The reported prevalence of obesity in type 2 diabetes mellitus (T2DM) was 60%–90%. Obesity and overweight pose a major risk for chronic diseases and are considered to be a strong risk factor for the development of T2DM.
AIMS: The aim of the study was to determine the prevalence of obesity among T2DM patients.
MATERIALS AND METHODS: This community-based cross-sectional study was conducted among T2DM patients residing in areas under Ashok Nagar and Rukmini Nagar Urban Health Centres, Belagavi. Three hundred and eighty T2DM patients were included in the study over a period of 1 year (January 1–December 31, 2017). Predesigned and pretested questionnaire was used to collect sociodemographic profile, and patient's height and weight were measured, and body mass index (BMI) was calculated and categorized based on Asian population.
STATISTICAL ANALYSIS USED: Statistical analysis was done using the Chi-square test for categorical variables. P < 0.05 was considered statistically significant.
RESULTS: The prevalence of generalized obesity (GO), abdominal obesity (AO), and combined obesity (CO) among T2DM patients were 58.68%, 81.84%, and 53.42%, respectively. Multiple logistic regression analysis showed that female gender and hypertension were significantly associated with GO, AO, and CO. Physical inactivity and hyperglycemic state were significantly associated with AO and CO but not with GO. The duration of T2DM was significantly associated with AO but not with GO and CO.
CONCLUSIONS: Our study concluded that obesity is a highly prevalent comorbidity in diabetic patients. AO appears to be a better indicator of diabetic risk than BMI. The combination of a low-calorie diet, increased physical activity, and behavioral therapy as the first-line intervention for weight loss should be stressed for the effective management of T2DM.
Keywords: Body mass index, obesity, prevalence, type 2 diabetes mellitus, waist–hip ratio
|How to cite this article:|
Vasanthakumar J, Kambar S. Prevalence of obesity among type 2 diabetes mellitus patients in urban areas of Belagavi. Indian J Health Sci Biomed Res 2020;13:21-7
|How to cite this URL:|
Vasanthakumar J, Kambar S. Prevalence of obesity among type 2 diabetes mellitus patients in urban areas of Belagavi. Indian J Health Sci Biomed Res [serial online] 2020 [cited 2022 Oct 4];13:21-7. Available from: https://www.ijournalhs.org/text.asp?2020/13/1/21/276421
| Introduction|| |
Diabetes is a major disease burden in India, and we are home to the second largest number of diabetes cases in the world. In 2017, there were over 72 million cases of diabetes in India. Obesity can be defined simply as the disease in which excess body fat has accumulated to such an extent that health may be adversely affected. World Health Organization (WHO) reported that obesity is one of the most common and also the most neglected, public health problems in both developed and developing countries. Obesity is strongly associated with other metabolic disorders, including diabetes, hypertension, dyslipidemia, cardiovascular disease, and even some cancers. It is a major contributor to the type 2 diabetes (T2DM) epidemic where nearly 88% of those with T2DM are considered overweight or obese. Despite the increased risk of poor clinical outcomes and negative impact on the quality of life, only one-half of individuals with diabetes and other chronic conditions receive counseling on diet and/or exercise by their primary care provider. Overweight and obesity have further been linked with poor control of blood pressure, cholesterol, and blood glucose levels among individuals with type 2 diabetes. Overweight and obesity are often determined by calculating the body mass index (BMI). BMI does not reflect body fat distribution, whereas the intraabdominal deposition of adipose tissue is a major contributor to the development of diabetes, hypertension, insulin resistance, and dyslipidemia. Thus, waist circumference (WC) and waist–hip ratio (WHR) have been used as a measure of abdominal fat or central obesity. WC is a convenient and simple measurement that is unrelated to height, correlates closely with BMI and WHR, and is an approximate index of intraabdominal fat mass and total body fat. Hence, in this study, WC is used as a measure of central obesity.
- The objective was to determine the prevalence of obesity among type 2 diabetes mellitus (T2DM) patients and its associated risk factors.
| Materials and Methods|| |
- Study population: T2DM patients residing in areas belonging to Ashok Nagar Urban Health Centre and Rukmini Nagar Urban Health Centre in Belagavi, Karnataka.
- Study design: This was a community-based cross-sectional study.
- Study period: The study was conducted from January 2017 to December 2017.
- Sample size: Sample size was calculated as 380 assuming that the prevalence of obesity is 28.1%, and that the true prevalence is expected to fall within ± 5% with a confidence level of 95% and with the dropout rate of 15%, using the formula n = 4pq/d2.
- Sampling method: Simple random sampling.
Method of collection of data
- T2DM patients residing in the study area.
- Type 1 diabetes mellitus
- Pregnant and lactating women
- Patients on medications such as steroid treatment for any cause, decongestants, appetite suppressants, cyclosporine, tricyclic antidepressants, erythropoietin, nonsteroidal anti-inflammatory agents, and cocaine.
The study was approved by the Institutional Ethics Committee for Human Subject's Research, Jawaharlal Nehru Medical College, K. L. E University, Belagavi, with the reference number MDC/DOME/25 dated October 17, 2016.
Periodic noncommunicable disease camps were conducted within the study areas to identify the known case of T2DM patients. From the identified T2DM patients, the study participants were selected based on the selection criteria. The selected patients were given appointment for reporting at the nearest urban health center which was convenient to the participants. Since fasting samples were to be collected, the participants were advised in writing about the instructions regarding overnight fasting and the time in early morning to assemble at the centers. Data were collected using a predesigned and pretested questionnaire by personal interview method from the participants. Blood samples were collected for the estimation of fasting plasma glucose and postprandial plasma glucose. Informed consent was obtained before data collection.
The questionnaire was designed according to the needs of the present study. It includes questions regarding sociodemographic profile, duration of diabetes, current antidiabetic medications, and other risk factors.
Information regarding per capita income (in Rupees/month) was collected, and socioeconomic status was classified using Modified BG Prasad's classification for the study period of 2017 [Table 1].
A modification was done with the aid of correction factor (CF), which was obtained as below:
As the study period was from January 1, to December 31, 2017, the mean consumer price index for the period was considered.
The average consumer price index for the year 2017 was 274.
Modified BG Prasad's = Per capita family monthly income of 1961 (BG Prasad) × CF
- Height: The participant was asked to stand straight without footwear, with heels, buttocks and back straight, and arms hanging by side. The height was measured from head to heel. The coinciding reading was measured to the nearest 0.1 cm using a metallic measuring tape
- Weight: The body weight was measured without any footwear and with minimal clothing to the nearest 0.1 kg using a standard portable adult weighing machine, which was standardized periodically during the study. The scale was adjusted to zero before each session and weight was recorded in kilograms
- Calculation of BMI (in Kg/m2): Calculation of BMI (in Kg/m2): Weight in Kg/(Height in m)2 × 100 BMI calculated was categorized as per the WHO criteria for Asian population
- WC: The measurement was made at the approximate midpoint between the lower margin of the last palpable rib and the top of the iliac crest and the participant stands with arms at the sides, feet positioned close together, and weight evenly distributed across the feet. WC ≥80 cm for females and ≥90 cm for males was considered to have abdominal obesity (AO)
- Hip circumference (HC): It is the maximum circumference in the horizontal plane measured over the buttocks at the level of greater tubercle.
- (WHR): The ratio of WC to the hip circumference <0.85 in females and <0.90 in males was considered normal.
- Body fat percentage: Calculated using the formula.
- Body fat % for men = ([0. 567 × WC in cm] + [0. 101 × age in years])-31. 8
- Body fat % for women = ([0. 438 × WC in cm] + [0. 221 × age in years])-9. 4
- PBF ≥25% (male) or ≥30% (Female) was considered as obese according to the U.S. National Institutes of Health criterion standards for body fat percent.
The glycemic status was assessed by their fasting blood sugar (FBS) and postprandial blood sugar (PPBS) levels using the hexokinase method.
The glycemic control was graded as:
- Euglycemic if FBS ≤126 mg/dl and PPBS is ≥200 mg/dl
- Hyperglycemic if FBS is >126 mg/dl or PPBS is >200 mg/dl.
- Hypertension: Defined as systolic blood pressure (SBP) ≥140 or diastolic blood pressure (DBP) ≥90 or known case of hypertension
- Generalized obesity (GO): Defined as a BMI ≥25 Kg/m2 for both genders (based on the WHO Asia Pacific Guidelines) with or without AO [Table 2]
- AO: Defined as a WC ≥90 cm for men and ≥80 cm for women
- Combined obesity (CO): Defined as individuals with GO and AO.
|Table 2: Obesity Classification according to WHO Asia-Pacific guidelines|
Click here to view
Data were entered in Excel sheet after coding. The analysis of the numerical variable outcomes was summarized by computing the mean and standard deviations (SDs). Categorical data were summarized using rates (percentages). Chi-square test was done for categorical variables. The significance level was kept at 0.05 level of probability. Multiple logistic regression was done for all the variables with P < 0.05 in the univariate analysis. The IBM Statistical Package for the Social Sciences (SPSS) for windows version 20.0, Armonk, New York: IBM Corp. and Microsoft data Excel sheet were used to analyze the data.
| Results|| |
[Table 3] shows the sociodemographic characteristics of the study participants. Out of 380 study participants, 29.73% were in the age group of 61–70 years and 25.52% were in the age group of 51–60 years forming the majority of the participants. The average age of the study participant was 56.25 ± 11.24 (mean ± SD.) with a range of 32–80 years of age. About 60.26% were female forming the major portion and 39.74% were male. Majority of the study participants were homemakers (55.79%) and self-employed (20.26%). Thirty percent of the participants did not have any kind of formal education; 23.42% of them studied up to secondary and 22.63% primary school; majority of the study participants belonged to socioeconomic status (SES) class IV (32.37%); 65.53% of participants were Hindus. The study participants' duration of diabetes varied. Most of them (49.21%) had diabetes from 1 to 5 years. The prevalence of tobacco consumption and alcohol consumption was 16.05% and 16.84%, respectively.
|Table 3: Distribution of the study participants according to sociodemographic characteristics (n=380)|
Click here to view
[Table 4] presents the prevalence of hypertension and the glycemic status of the study participants. The prevalence of hypertension was 66.84%. The mean SBP was 132.72 ± 17.89, and the mean DBP was 81.6 ± 8.99. The number of study participants with a known case of hypertension was 163 (42.89%). Two hundred and seventy-three (71.84%) were hyperglycemic and 28.16% were euglycemic. The mean serum FBS was 153.3 ± 46.25 and the mean serum PPBS was 229.18 ± 75.34
|Table 4: Distribution of the participants according to hypertension and glycemic status (n=380)|
Click here to view
[Table 5] shows the prevalence of GO, AO, CO, and body fat percentage. Based on BMI, the prevalence of overweight was 18.95%, and the prevalence of GO was 58.68%. The mean BMI of the study participants was 25.89 ± 3.86 Kg/m2. The prevalence of AO based on WC criteria was 81.84%. The mean WC was 93.64 ± 13.13. The mean WHR was 0.98 ± 0.075. The overall prevalence of CO (GO and AO) was 53.42%. The prevalence of obesity based on body fat percentage was 85.5% [Figure 1]. The mean body fat percentage among men was 26.80 ± 7.89 and the mean body fat percentage among women was 43.87 ± 5.98.
|Table 5: Distribution of the study participants according to the types of obesity (n=380)|
Click here to view
|Figure 1: The prevalence of types of obesity among the genders of the study population|
Click here to view
[Table 6] describes various risk factors associated with the types of obesity in the study population. In the present study, it was observed that the proportion of GO and CO was significantly higher among the age group of 41–50 years. The proportion of AO was significantly more among those with the duration of diabetes more than 10 years. GO and CO showed no significant association with the duration of diabetes. AO and CO are significantly associated with the glycemic status of the participants. All three types of obesity showed statistically significant association with the female gender, no physical activity, and hypertension. No significant association was seen with education, SES, type of diet, mode of treatment, tobacco, and alcohol consumption.
|Table 6: Association of types of obesity with various factors in the study population (n=380)|
Click here to view
[Table 7] shows multiple logistic regression analysis using GO, AO, and CO as the dependent variables and various risk factors as independent variables. It included all variables with P < 0.05 in the univariate analysis. Female gender and hypertension were significantly associated with GO, AO, and CO. Physical inactivity and hyperglycemic state were significantly associated with AO and CO. The duration of T2DM was significantly associated with AO.
| Discussion|| |
The present study aimed to determine the prevalence of obesity among T2DM patients among the urban areas of Belagavi. The distribution of the study participants was such that most of them were between the age group of 41 and 60 years which shows that T2DM was more prevalent among the age group of 41–60 years. This observation was similar to the WHO report which predicts that in India and other developing countries, the highest increase would occur in the age group of 41–60 years. Female-to-male ratio was 1.52:1 in this study. This observation was similar to a study conducted by Bilal Wani et al. who reported that prevalence of diabetes among women was higher than in men with the ratio of 1.41:1. The prevalence of GO based on BMI was 58.68%. The mean BMI of the study participants was 25.89 Kg/m2. Study conducted in Warangal reported 59.2% of overweight and obese which is in par with our study. Another study conducted in Bangalore reported 73% obesity with the mean BMI 26 Kg/m2. Similar observation to our study was made in a study conducted by Shyaminda Kahandawa et al. reported the mean BMI of 26.4 Kg/m2. The prevalence of abdominal/central obesity assessed by WC was 81.84% in our study. “Asian Indian phenotype” is characterized by less of GO (measured by BMI) and greater central body obesity as shown by greater WC. Our study supports this hypothesis. In a study done in a rural area of Mangalore district of Karnataka showed higher central obesity prevalence (90.63%) when compared to BMI. The prevalence of CO (GO and AO) in our study was 53.42%. Undavalli et al. reported that the prevalence of GO, AO, and CO was 56%, 71.2%, and 51.3%, respectively, which was similar to our observations. The prevalence of obesity due to body fat percentage in our study was 85.5%, and the mean body fat percentage among males and females was 26.8 ± 7.89 and 43.87 ± 5.98, respectively. The findings of our study were on par with the study conducted by Ahmad Shirafkan et al. which reported body fat percentage among males and females as 31.55 ± 6.00 and 43.21 ± 5.31, respectively. In our study, we had observed a significant gender difference in the prevalence of all types of obesity (GO, AO, and CO). A high prevalence of obesity was noted in females than in males. These results are in accord with those reported from both in general population and among patients with T2DM conducted in India,,, Iran,, Tanzania, and Saudi Arabia. The present showed that the prevalence of GO, AO, and CO was high among those with hypertension. This observation is in line with the findings of the study conducted by Pradeepa et al.
Our study reported that GO is significantly associated with female gender and those with hypertension, whereas AO and CO were associated with female gender, hypertension, physical inactivity, and glycemic status (hyperglycemia). Our study supports the arguments, WC as a better indicator of health risk than BMI. WC has been suggested as more practical measure of intraabdominal fat mass and total body fat. The Framingham study suggested that the WC predicted mortality better than other anthropometric measures. Another study showed that the change in waist was a better predictor of the change in visceral adipose tissue. WC captures information on general as well as abdominal obesities including both abdominal subcutaneous fat and visceral adipose.
| Conclusions|| |
In the present study, it can be concluded that the prevalence of GO, AO, and CO among T2DM patients were 58.68%, 81.84%, and 53.42%, respectively. Furthermore, all three types of obesity were more prevalent among females and among those with hypertension. AO and CO were significantly associated with physical inactivity and glycemic status. Thus, AO appears to be a better indicator of diabetic risk than BMI. Combination of a low-calorie diet, increased physical activity, and behavioral therapy as the first-line intervention for weight loss should be stressed in the management of diabetes mellitus. Weight reduction using lifestyle modification with or without pharmacotherapy is important in reducing the risk of developing diabetes and improving metabolic control in obese patients with type 2 diabetes.
Financial support and sponsorship
Conflicts of interest
| References|| |
International Diabetes Foundation. International Diabetes Foundation 2017.
World Health Organization (WHO). Obesity: preventing and managing the global epidemic. Report of a WHO consultation. (1-253). World Health Organ Tech Rep Ser. 2000;894:i–xii.
Pradeepa R, Anjana RM, Joshi SR, et al
. Prevalence of generalized & abdominal obesity in urban & rural India--the ICMR-INDIAB Study (Phase-I) [ICMR- NDIAB-3]. Indian J Med Res. 2015;142:139–150. doi:10.4103/0971-5916.164234.
American Association of Diabetes Educators, Chicago, IL, August 2018.
Damian J. Damian, Kelvin Kimaro, Godwin Mselle, Rose Kaaya and Isaac Lyaruu. Prevalence of overweight and obesity among type 2 diabetic patients attending diabetes clinics in northern Tanzania. BMC research notes 2017;10:515.
Ahmad Shirafkan and Abdoljalal Marjani. Prevalence of Obesity Among Type 2 Diabetes Mellitus In Gorgan (South East of Caspian Sea), Iran. World Applied Sciences Journal 2011;14:1389-96.
Rao C, Kamath V, Shetty A, Kamath A. A study on the prevalence of type 2 diabetes in coastal Karnataka. Int J Diabetes Dev Ctries 2010;30:80.
Singh T, Sharma S, Nagesh S. Socio-economic status scales updated for 2017. Int J Res Med Sci 2017;5:3264.
World Health Organization. The WHO STEPwise approach to noncommunicable disease risk factor surveillance. World Heal Organ 2017;36:1-474.
International Diabetes Institute/ Western Pacific World Health Organization/ International, Force A for the study of OIOT. The Asia-Pacific perspective: redefining obesity and its treatment. Geneva, Switz. World Health Organisation 2000;56.
Lean MEJ, Han TS, Deurenberg P. Predicting body composition by densitometry from simple anthropometric measurements. Am. J. Clin. Nutr 1996;63:4-14.
US Department of Health and Human Services, National Institutes of Health. WIN Weight Control Network. Understanding Adult Obesity. NIH Publication No. 01-3680.
WHO. Definition and Diagnosis of Diabetes Mellitus and Intermediate Hyperglycemia. Who2 2006;50.
Verdecchia P, Angeli F, Mancia G, Fagard R, Narkiewicz K, Redon J, et al
. How can we use the results of ambulatory blood pressure monitoring in clinical practice? Hypertension 2016;11:102–7.
Sreelatha M, Kumar VS, Shekar GC, Shekar VC. Study of Thyroid Profile in Patients with Type 2 Diabetes Mellitus. 2017;5:211–20.
Khan MA, Hafiz N, Kohli S. Research Article Prevalence Of Thyroid Dysfunction In Patients Of Type 2 Diabetes Mellitus: Resident Department of General Medicine Hamdard Institute of Medical Sciences and Research t of Obsteterics and Gynecology, ESIC Hospital Okhla, New Delhi 4 Hea. 2018;4–7.
Nagendra A, Chekri P, Swarupa K. A Study on Prevalence of Abdominal Obesity among Diabetics. Indian J Nutri. 2017;4: 175.
Kahandawa S, Somasundaram NP, Ediriweera DS, Kusumsiri DP, Ellawala S, Chandrika GHTNK, et al
. Prevalence of thyroid dysfunction among type 2 diabetic patients attending the Diabetes Clinic, National Hospital of Sri Lanka. Sri Lanka J 2014;4:43–8.
Padmanabha UR, Nalam U, Badiger S, Nagarajaiah P, Rani U. Prevalence and Risk Factors of Type 2 Diabetes Mellitus in the Rural Population of Mangalore, South India. Natl J Community Natl J Community Med 2017;8:456–61.
Undavalli VK, Ponnaganti SC, Narni H. Prevalence of generalized and abdominal obesity: India's big problem. International Journal of Community Medicine Public Health 2018;5:1311-6.
Anari R, Amani R, Veissi M. Obesity and poor glycemic control in patients with type 2 diabetes. International Journal of Research in Medical Sciences | February 2016 | Vol 4 | Issue 2.
B. A. Bakhotmah. Prevalence of Obesity among Type 2 Diabetic Patients: Non-Smokers Housewives Are the Most Affected in Jeddah, Saudi Arabia. Journal of Endocrine and Metabolic Diseases, 2013, 3, 25-30.
Dey, D.K., E. Rothenberg, V. Sundh, I. Bosaeus and B. Steen, 2002. Waist circumference, body mass index and risk for stroke in older people: a 15 year longitudinal population study of 70- year-olds. J. Am. Geriatr Soc., 50: 1510-8.
Vadstrup, E.S., L. Petersen, T.I. Sorensen and M. Gronbaek, 2003. Waist circumference in relation to history of amount and type of alcohol: results from the Copenhagen City Heart Study. International. Journal Obesity Related Metabolic disorders 27: 238-46.
Despres, J.P., S. Lemieux, B. Lamarche, D. Prud'homme, S. Moorjani, L.D. Brun, C. Gagne and P.J. Lupien, 1995. The insulin resistance-dyslipidemic syndrome: contribution of visceral obesity and therapeutic implications. International. Journal Obesity Related Metabolic disorders Supplement. 1: S76-86.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7]
|This article has been cited by|
||Socio-anthropometric features and lifestyle in ketosis-prone diabetes vs controls
| ||Kwadjo Anicet Luc Dere, Agnon Prisca Djoupo, Coulibaly Djenebou, Fofana Seguenan, Gnomblesson Georges Tiahou |
| ||International Journal of Clinical Biochemistry and Research. 2022; 9(2): 141 |
|[Pubmed] | [DOI]|
||Association of telomere length and serum vitamin D levels with type 2 diabetes mellitus and its related complications: A possible future perspective
| ||C Akash, Madhav Prabhu, Arif Maldar, Poornima Akash, Sanjay Mishra, TK Madhura, Santosh Kumar, RekhaS Patil, Shobhit Piplani, KS Smitha |
| ||Genome Integrity. 2021; 12(1): 1 |
|[Pubmed] | [DOI]|
||Prevalence of obesity and overweight among type 2 diabetic patients in Bisha, Saudi Arabia
| ||MohammadS AlShahrani |
| ||Journal of Family Medicine and Primary Care. 2021; 10(1): 143 |
|[Pubmed] | [DOI]|
||Prevalence of Diabetes and Its Relationship With Body Mass Index Among Elderly People in a Rural Area of Northeastern State of India
| ||Gajendra K Medhi,Gitashree Dutta,Prasanta Borah,Markordor Lyngdoh,Amitav Sarma |
| ||Cureus. 2021; |
|[Pubmed] | [DOI]|
||Fibroblast Growth Factor 21 and Its Association With Oxidative Stress and Lipid Profile in Type 2 Diabetes Mellitus
| ||Mudassar Aleem,Hamza Maqsood,Shifa Younus,Ahmed F Zafar,Abdul Subhan Talpur,Hassan Shakeel |
| ||Cureus. 2021; |
|[Pubmed] | [DOI]|
||Differential risk factors and morbidity/mortality pattern in type 2 diabetes: A study among two Mendelian populations with different ancestry (India)
| ||Imnameren Longkumer,Naorem Kiranmala Devi,Benrithung Murry,Kallur Nava Saraswathy |
| ||Diabetes & Metabolic Syndrome: Clinical Research & Reviews. 2020; 14(6): 1769 |
|[Pubmed] | [DOI]|