|Year : 2020 | Volume
| Issue : 3 | Page : 1578-1582
Double burden of malnutrition among women residing in tenements in a resettlement area, Kancheepuram district
M Buvnesh Kumar1, TK Raja1, M Jasmine2, Fasna Liaquathali2, V Pragadeesh Raja2, NV Manju3
1 Department of Community Medicine, Chettinad Hospital and Research Institute, Chettinad Academy of Research and Education [CARE], Kelambakkam, Tamil Nadu, India
2 Department of Community Medicine, Shri Sathya Sai Medical College and Research Institute, Sri Balaji Vidyapeeth (SBV)- Deemed to be University, Kancheepuram, Tamil Nadu, India
3 Department of Community Medicine, Saveetha Medical College and Hospital, Saveetha University, Saveetha Nagar, Chennai, Tamil Nadu, India
|Date of Submission||21-Nov-2019|
|Date of Decision||10-Feb-2020|
|Date of Acceptance||13-Feb-2020|
|Date of Web Publication||26-Mar-2020|
Dr. M Jasmine
Assistant Professor, Department of Community Medicine, Shri Sathya Sai Medical College and Research Institute, Sri Balaji Vidyapeeth (SBV)- Deemed to be University, Tiruporur- Gudvancherry Main Road, Ammapettai, Nellikuppam, Chengalpet Taluk, Kancheepuram District, Tamil Nadu - 603 108
Source of Support: None, Conflict of Interest: None
Introduction: The double burden of malnutrition is the co-existence of undernutrition along with overweight/obesity. The underweight can cause cognitive impairment, increase mortality, and over nutrition increases the chance of noncommunicable diseases like type 2 diabetes and hypertension. Women are vulnerable for early marriages, early conception, and so forth, which have an impact on their nutritional status. Objective: To estimate the prevalence of double burden of malnutrition among women residing in tenements in a resettlement area, Kancheepuram district. Materials and Methods: This is a cross-sectional study conducted among women aged above 18 years residing in a tenement in a resettlement area, Kancheepuram district using a semi-structured questionnaire. The sample size was 211. Results: The median age of the participants was 44. 78; 2% were married; 30.8% belong to class III. Based on BMI 1.4% were underweight, 17.1% had normal BMI, 48.8% were pre-obese, and 19.9% were under obese stage 1. Based on the waist circumference, 23.7% were under high risk and according to the waist–hip ratio, 69.7% were under high risk. The prevalence of diabetes among the high-risk category for waist–hip ratio was higher (80.3%) with statistical significance. Conclusion: The national programs are concentrating more on the undernutrition. The importance of obesity as a risk factor for many noncommunicable diseases should be stressed in the nutritional programs thereby providing proper interventions to prevent them, which could be done by interlinking with NPCDCS.
Keywords: Double burden of malnutrition, obesity, over nutrition, undernutrition, women
|How to cite this article:|
Kumar M B, Raja T K, Jasmine M, Liaquathali F, Raja V P, Manju N V. Double burden of malnutrition among women residing in tenements in a resettlement area, Kancheepuram district. J Family Med Prim Care 2020;9:1578-82
|How to cite this URL:|
Kumar M B, Raja T K, Jasmine M, Liaquathali F, Raja V P, Manju N V. Double burden of malnutrition among women residing in tenements in a resettlement area, Kancheepuram district. J Family Med Prim Care [serial online] 2020 [cited 2020 Mar 29];9:1578-82. Available from: http://www.jfmpc.com/text.asp?2020/9/3/1578/281154
| Introduction|| |
The malnutrition is the major public health problem in many low- and middle-income countries. The double burden of malnutrition is the co-existence of undernutrition along with overweight/obesity. The changes in the dietary intake patterns and leisure time activities associated with industrialization, urbanization is known to increase obesity. The underweight can cause cognitive impairment, increase mortality, and over nutrition increases the chance of noncommunicable diseases like type 2 diabetes and hypertension. Malnutrition is prevalent among all segments of the population, poor nutrition among women begins at infancy and continues throughout their lifetime. Women are vulnerable for early marriages, early conception, domestic violence, and so on, which has an impact on their nutritional status. The dimension of malnutrition problem in India is presented with reference to its implications on birth outcome and undernutrition in children.
According to WHO, in 2014, more than 1.9 billion adults worldwide were overweight and around 462 million people were underweight. More than 600 million were obese. According to NFHS-4 data, women with Body Mass Index (BMI) <18.5 indicating underweight/chronic energy deficiency were 22.9% for India  and 14.6% for Tamilnadu. Similarly, women with BMI of more than or equal to 25 indicating overweight/obese for India and Tamil Nadu were 20.7% and 30.9% respectively. The NFHS 4 data highlights about the double burden of malnutrition among women especially in Tamil Nadu.
The burden of overweight is steadily increasing among the women surpassing the rates of underweight in accordance with the NFHS-4 data. This shift could be attributed to development in economics, urbanization, changes in lifestyle. Studies have shown that the obesity and the underweight are one of the top ten risk factors for the worldwide burden of diseases. The recent World Health Organization data has also shown that the underweight is responsible for 6 percent of the global disability-adjusted life years.
Abdominal obesity also known as central obesity is the excessive accumulation of fat around the stomach. These can be measured by anthropometric measures like waist circumference and waist–hip ratio. Central obesity is linked to multimorbidity like type 2 diabetes, stroke, and cardiovascular diseases.
Both the obesity and underweight are easily preventable by simple lifestyle modification. Many evidences have shown that simple primary care practices such as eating healthy diet, practicing physical activity, and avoiding sedentary practices can have a spectacular effect on maintaining a healthy body weight. On screening for double burden of malnutrition in a community, it helps to take an integrated action on all forms of malnutrition.
| Objectives|| |
- To estimate the prevalence of double burden of malnutrition among women residing in tenements in a resettlement area, Kancheepuram district
- To assess the association of waist–hip ratio as a risk factor for noncommunicable diseases.
| Material and Methods|| |
The study was a cross-sectional study conducted in tenements in a resettlement area.
The duration of the study was 6 months.
Sample size determination
Taking prevalence as 14.6 (underweight prevalence) and allowable error of 5%, the estimated sample size was 192. To account for the non-response, 10% of subjects are being added to the sample size. Thus, total of 211 subjects were included in the study.
Sampling and study population
The sampling method used to derive the sample was Simple Random Sampling.
Women aged above 18 years residing in the study area for more than 1 year.
Pregnant women and mentally challenged women.
A standardized pretested semi-structured questionnaire was used as the study instrument. The questionnaire had 2 sections. Section 1 consists of sociodemographic profile of the participants and section 2 had anthropometric measurements.
Asian criteria cut off for Body mass Index
According to the Asian Body Mass Index classification, BMI of less than 18.5 is considered to be underweight. BMI between 18.5 and 22.9 is considered as normal nutritional status. Overweight is considered as BMI between 23 and 24.9. Preobese is when BMI is between 25 and 29.9. BMI of more than or equal to 30 is considered as obesity, in which BMI of 30 to 40 is type 1 obesity, 40 to 50 is type 2 obesity, and more than 50 is considered as type 3 obesity.
Waist circumference of more than 88 cm in females is considered as higher risk for morbidity.
Waist–hip ratio is calculated by dividing waist circumference with the hip circumference. Normal waist–hip ratio for females is less than 0.80.
Data collection procedure
After obtaining written informed consent, the participants were interviewed using pretested, prevalidated semi-structured questionnaire.
Data was entered in Microsoft Excel spread sheet and after checking the normality of the study it was analyzed in Statistical Package for Social Sciences (SPSS-IBM) software version 21. Frequency for each variable, BMI and WHR will be calculated. Bivariate analysis is done by the application of Pearson chi square test and the P value of less than 0.05 was considered significant.
Ethical consideration and confidentiality
All participants were informed regarding the purpose of study, benefits, procedure, and confidentiality of the research study in local language. The study was undertaken after getting informed consent from the participants using the pretested, prevalidated semi-structured questionnaire.
| Results|| |
The median age of the participants was 44 years. 55.9% of the total participants belong to nuclear family. Only 18% were illiterates [Table 1]. The study also showed that 68.2% of the study participants were financially dependent either totally or partially. 4.7% belonged to the upper class and 18.5% belonged to the lower class and maximum of the study participants (30.8%) belong to the middle class according to modified BG Prasad classification.
|Table 1: Distribution of study participants according to the sociodemographic profile (n=211)|
Click here to view
Out of the 211 study participants, only 17.1% had normal BMI. Around 48.8% are preobese [Table 2]. The prevalence of overweight and preobesity in the present study was 12.8% and 48.8% respectively and the prevalence of obesity I was 19.9%. (According to WHO Asian BMI classification ).
|Table 2: Distribution of the study participants according to the BMI classification (n=211)|
Click here to view
Though only 23.7% are under the high risk based on the waist circumference [Table 3], nearly 69.7% are under high risk according to the waist–hip ratio. (According to WHO classification of Waist Hip ratio ).
|Table 3: Distribution of the study participants according to waist circumference and waist-hip ratio (n=211)|
Click here to view
Among those who had diabetes, 80.3% had higher waist–hip ratio (statistically significant) [Table 4]. The present study showed a higher prevalence of cardiovascular disease (69.2%) among the higher WHR than those with lower WHR.
|Table 4: Distribution of study participant's prevalence of non-communicable disease according to Waist-hip ratio|
Click here to view
| Discussion|| |
The present study was conducted among the women residing in the tenements in a resettlement area of Kancheepuram district, Tamil Nadu. The study has shown that the median age of the study participants was 44. Similarly, in a study done by Palo SK et al., it was shown that the mean age of the study participants was 45.7%, almost similar to the present study.
The present study has shown that the prevalence of overweight and preobesity was 12.8% and 48.8% respectively. In a study conducted by Anuradha et al., the results stated that the prevalence of overweight and obesity was 27.7% and 19.8% respectively. Similarly, in a study done by Sidhu S et al., the prevalence was 20% and 25.3% respectively. Likewise, in a study done by Rao BB et al. the results showed that the prevalence of overweight among women was 28.2%. The prevalence of obese I in the present study was 19.9% and this data almost corresponds with the National Family Health survey (NFHS-4) data.
The present study showed that nearly 69.7% are under higher risk for waist–hip ratio. The present study also showed higher prevalence of waist–hip ratio (central obesity) than the general obesity. Similar result is shown in a study done by Ramachandran A et al., which showed higher prevalence of waist–hip ratio (50.3%) than general obesity (30.8%) similar to the present study. Similarly, in a study done by Palo SK et al., it was shown that around 51.9% had higher waist–hip ratio, which is higher than the general obesity.
Among those who had diabetes, 80.3% had higher waist–hip ratio (statistically significant). In a study done by Mohan V et al., the prevalence of diabetes among those who had higher (62.6%) waist–hip ratio was higher than those with lower WHR, which supports the present study. Likewise, in a study done by Joshi B et al. the results stated that there is higher prevalence of diabetes among those who had higher waist–hip ratio. Similar report was shown in a study done by Fallahzadeh H et al. and Sun Y et al. Both the studies report that higher waist–hip ratio (central obesity) is associated with morbidities like diabetes.
In a study done by Patel SA et al., the results showed that the waist–hip ratio was significantly associated with unhealthy cardiovascular profile, in a similar way, the present study showed a higher prevalence of cardiovascular disease (69.2%) among the higher waist–hip ratio than those with lower waist–hip ratio. Similar report was shown by the study done by Sun Y et al. It was reported that the central obesity, which means higher abdominal fat distribution is associated with higher mortality risk independent of BMI.
| Conclusion|| |
The rates of overweight are steadily increasing among the women surpassing the rates of underweight. In the context of nutrition, the national programs are concentrating more on the undernutrition. The importance of obesity as a risk factor for many noncommunicable diseases should be stressed in the nutritional programs, thereby providing proper interventions to prevent them, which could be done by interlinking with National Program for Prevention and Control of Cancer, Diabetes, Cardiovascular diseases and Stroke.
Declaration of patient consent
The authors certify that they have obtained all appropriate patient consent forms. In the form the patient(s) has/have given his/her/their consent for his/her/their images and other clinical information to be reported in the journal. The patients understand that their names and initials will not be published and due efforts will be made to conceal their identity, but anonymity cannot be guaranteed.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Shrimpton R, Rokx C. The Double Burden of Malnutrition in Indonesia. Jakarta, Indonesia: World Bank Jakarta; 2013.
Di Cesare M, Bhatti Z, Soofi SB, Fortunato L, Ezzati M, Bhutta ZA. Geographical and socioeconomic inequalities in women and children's nutritional status in Pakistan in 2011: An analysis of data from a nationally representative survey. Lancet Glob Health 2015;3:e229-39.
Guilbert JJ. The world health report 2002–reducing risks, promoting healthy life. Educ Health 2003;16:230.
Who EC. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet (London, England) 2004;363:157.
Palo SK, Swain S, Priyadarshini S, Behera B, Pati S. Epidemiology of obesity and its related morbidities among rural population attending a primary health centre of Odisha, India. J Fam Med Prim Care 2019;8:203.
Anuradha R, Ravivarman G, Jain T. The prevalence of overweight and obesity among women in an urban slum of Chennai. J Clin Diagn Res 2011;5:957-60.
Sidhu S, Tatla HK. Prevalence of overweight and obesity among adult urban females of Punjab: A cross-sectional study. Anthropologist 2002;4:101-3.
Rao BB, Junapudi SS. A comparative study of prevalence of overweight and obesity among urban, and rural population of South India. Int J Commun Med Public Health 2019;6:1091-5.
Ramachandran A, Snehalatha C, Kapur A, Vijay V, Mohan V, Das AK, et al
. High prevalence of diabetes and impaired glucose tolerance in India: National Urban Diabetes Survey. Diabetologia 2001;44:1094-101.
Mohan V, Shanthirani CS, Deepa R. Glucose intolerance (diabetes and IGT) in a selected South Indian population with special reference to family history, obesity and lifestyle factors--The Chennai Urban Population Study (CUPS 14). J Assoc Physicians India 2003;51:771-7.
Joshi B, Shrestha L, Bhattarai K, Manandhar N, Mahotra NB. Comparison of central obesity with overall obesity in predicting the risk of type 2 diabetes mellitus. J Universal College Med Sci 2019;7:17-21.
Fallahzadeh H, Ostovarfar M, Lotfi MH. Population attributable risk of risk factors for type 2 diabetes; Bayesian methods. Diabetes Metab Syndr 2019;13:1365-8.
Sun Y, Liu B, Snetselaar LG, Wallace RB, Caan BJ, Rohan TE, et al
. Association of normal-weight central obesity with all-cause and cause-specific mortality among postmenopausal women. JAMA Network Open 2019;2:e197337.
Patel SA, Deepa M, Shivashankar R, Ali MK, Kapoor D, Gupta R, et al
. Comparison of multiple obesity indices for cardiovascular disease risk classification in South Asian adults: The CARRS Study. PLoS One 2017;12:e0174251.
[Table 1], [Table 2], [Table 3], [Table 4]