|Year : 2017 | Volume
| Issue : 4 | Page : 254-260
Effects of health education tool on select epidemiological factors associated with adult obese urban slum women
Deepika Pradeep Vora1, Pallavi S Shelke2
1 Resident Medical Officer, Department of Community Medicine, LTMMC and GH, Sion, Mumbai, Maharashtra, India
2 Associate Professor, Department of Community Medicine, LTMMC and GH, Sion, Mumbai, Maharashtra, India
|Date of Web Publication||6-Dec-2017|
Deepika Pradeep Vora
509, 5th Floor, Omkar CHS, T.J. Road, Grant Rd (w), Mumbai - 400 007, Maharashtra
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Background: National Family Health Survey-3 (2005–2006) India, found that 14.8% of Ever-Married Adults (age 15–49 years) had Body Mass Index (BMI) in the ranges of overweight and obese; compared to 10.6% in the National Family Health Survey-2. These figures highlighted the fact that India already faces a dual burden of chronic malnutrition, i.e., obesity, besides undernutrition. Higher BMI, especially, increased abdominal fat is an important determinant of the development of diabetes. Objective: This study aims to understand the effect of health education on obesity status of adult women above the age of 20 years in an urban slum area. Methods: Community-based, interventional study, to assess select epidemiological factors associated with obesity-including measurement of anthropometry and assessing random blood sugar level; followed by an intervention (health education to only obese women by means of flip-chart); followed by a follow-up 6 months later. Results: About 22.6% women were found to be obese. Almost, all dietary and physical activity parameters as well as weight improved for the better after the intervention, and the change was statistically significant. Conclusions: This community based interventional study was able to understand certain factors associated with pathophysiology of obesity in slum dwelling adult women, and effectively documented a reduction in weight along with a change in their obesogenic practices postintervention.
Keywords: Adult women, community based, health education, obesity
|How to cite this article:|
Vora DP, Shelke PS. Effects of health education tool on select epidemiological factors associated with adult obese urban slum women. Indian J Public Health 2017;61:254-60
|How to cite this URL:|
Vora DP, Shelke PS. Effects of health education tool on select epidemiological factors associated with adult obese urban slum women. Indian J Public Health [serial online] 2017 [cited 2020 May 30];61:254-60. Available from: http://www.ijph.in/text.asp?2017/61/4/254/220069
| Introduction|| |
For many years now India has been grappling under the pangs of undernutrition, poverty and maternal and child deaths. In an attempt to escape this vicious circle of poverty, undernutrition, poor quality of life and eventually death, a large number of people migrate from rural areas to more urbanized settlements where they usually settle down in slums and take up daily wage jobs. Several lifestyle alterations result from this transition: changes from their traditional eating habits; exposure to severe stress; decreased physical activity; and increase in smoking, tobacco chewing and alcohol intake. A significantly large part of India's population seems to be going through such a so-called “Nutrition Transition.” Hence, India with its substantial burden of undernutrition across age groups; sees a picture of “dual burdens”-one where obesity is now rapidly increasing across regions, and often coexisting in the same population (even same households) with chronic undernutrition.
National Family Health Survey (NFHS-3) (2005–2006) India, found that 33.0% of ever-married adults (age 15–49 years) had body mass index (BMI) below normal range whereas 14.8% in the same age group had BMI in the ranges of overweight and obese. This prevalence was 10.6% in NFHS-2. These figures highlighted the fact that besides undernutrition, India already faces a new form of chronic malnutrition-obesity.
The WHO defines obesity as a condition of abnormal or excessive fat accumulation in adipose tissue, to the extent that health may be impaired. The obesity epidemic moves through a population in a reasonably consistent pattern over time, and this is reflected in the different patterns in low- and high-income countries. In the transition phase, people with less education and lower socioeconomic status (SES) are more likely to be obese, and the gap is generally larger in women. In accordance with this fact, data from NFHS-3 show that in India, the trend of overweight and obesity is a rising one, especially among women.
Higher BMI and especially increased abdominal fat clearly is an important determinant of blood glucose levels, insulin resistance, and the development of diabetes. Asian populations appear to develop diabetes at a lower BMI than other populations.
Considering these facts, it was considered imperative to conduct a study on epidemiology of obesity in adult women dwelling in an urban slum area and attempt to alter for the better, modifiable factors. As the WHO has defined adolescents as age group from 10 to 19 years, adult women above the age of 20 years were decided on to be the study population.
This study aims to understand the effect of health education on modifiable factors associated with epidemiology of obesity among adult women above the age of 20 years in an urban slum area.
- To study the sociodemographic, dietary and physical activity factors associated with obesity in the selected population, for the development of community-specific health education tool (flip chart)
- To provide health education to the obese study population by means of the flip chart
- To assess the effect of the health education on them.
| Materials and Methods|| |
The present study has been conducted in the population served by one randomly selected health post of an urban slum area of a metropolitan city. Duration of the study was 2 years and 2 months.
The study was conducted in two phases. The first phase was a community based, cross-sectional study where baseline characters and necessary dietary-physical activity and anthropometric data were collected.
The second phase comprised of an intervention to obese respondents (from among the baseline) followed by a follow-up 6 months later. The intervention was health education by means of visual aid (Flip-chart).
Considering variations in population prevalence all over the country as well as in review of relevant literature, population prevalence of obesity in women above 20 years (P) was considered as 50% for the present study (as it gives maximum sample size). Considering an absolute precision level of 10% points the final sample size estimated was 500. The sampling unit was “a household with a woman above 20 years of age.”
The households were sampled by a circular systematic random sampling method. The sampling interval was calculated to be 33 (approx.). The slum area under the health post had a total population of 16,809 houses. No formal list of households comprising of women above 20 years was available. Hence, data available from the health post were referred to and the aid of community health volunteers was taken in identifying the households served by the health posts. Written informed consent was taken from all respondents before including them into the study.
- Inclusion criteria were any woman above 20 years of age giving consent to participate in the study
- Exclusion criteria included pregnant women or women up to 6 weeks' postpartum; Known case of any endocrine disorders all except diabetes mellitus; person known to have ascites or edema; person with known physical disability or psychiatric illness; person currently on any medications whose side-effects are known to be water-retention (edema) or weight gain, for example, oral contraceptive pills and Steroids.
The proposal of the study was submitted as per the protocol given by Institutional Scientific Review Committee and Ethics Committee. The approval and ethical clearance were obtained before the study.
The respondents were given information about the study using patient information sheet in their understandable language. If the respondent was illiterate, the sheet was read out to them.
Data were collected using a predesigned pretested semi-structured interview schedule along with clinical examination, anthropometric measurements by the use of electronic weighing scale and measuring tape, random blood sugar (RBS) level using an Accucheck glucometer and BP using a portable sphygmomanometer.
A single interviewer collected data by conducting personal face-to-face interview of the eligible women and completed the semi-structured interview schedule. A 7-day dietary recall was conducted to assess detailed dietary intake patterns. Furthermore, detailed physical activity assessment was done including daily chores and exercise if any. Clinical examination in the form of general and systemic health examination was conducted in the house of the respondent, and any abnormality was noted.
Anthropometric measurements of weight, height, waist, and hip circumference  were taken along with blood pressure. Furthermore, RBS level was assessed with an Accucheck Glucometer.
In case the woman disagreed to participate in the study, or the household was locked, no re-visit was made; the adjacent household was approached. If any woman was found not meeting the eligibility criteria, she was excluded from the study, and again the adjacent household was approached. If a household had more than one eligible respondent, then one was selected by lottery method to avoid any bias (as both women would have more or less similar dietary and other epidemiological exposures). The sampling frame was treated like a circle  and sampling was continued till the expected sample size (n = 500) was reached. General health education was orally given to all 500 respondents regarding obesity, its health-related implications, prevention and control.
BMI values were calculated for all 500 respondents interviewed using WHO Asian classification for BMI, and all those whose BMI was found to be ≥25 kg/m 2 were considered eligible for follow-up interview.
Based on the observations made in the first phase cross-sectional study regarding family history, dietary intake pattern and physical activity practices, a health education tool, i.e., flip chart was developed in this study. The tool was developed in the local language, i.e., Hindi and then validated. Only those respondents who were found to be obese were visited again and given detailed health education by administering the flip chart.
The contents of the flip chart included the definition of overweight and obesity, its causes and ill-effects, basics of prevention, healthy diet-need, and techniques-especially keeping in mind the dietary patterns of the population observed during first phase and finally the role of physical activity in obesity prevention-incorporating factors practical and feasible to the population.
The duration between the health education session and follow-up interview was 6 months. The same single interviewer conducted the health education session and the follow-up interview for each eligible respondent. The average duration of the health education session was 20 min and was conducted in the house of the eligible respondent. In the follow-up interview, changes in the dietary pattern, physical activity levels, and weight were assessed. The total study duration was 2 years.
Data were collected and compiled using Microsoft Excel 2010 and then analyzed using SPSS 20.0 version (IBM's., Armonk, New York, USA) and Open Epi Software Version 2.3 (Atlanta, Georgia) by calculating frequencies and percentages of various parameters. Paired t-test was applied to test the significance of association wherever necessary. The WHO Asian classification was used for defining BMI categories. Hence, BMI values of respondents were divided into two broad categories for analysis of data – those who were found to be obese (BMI ≥25.00) and those who were not obese (BMI <25.00). The nonobese category includes those who were underweight, in normal range as well as those who classified as overweight according to their BMI.
| Results|| |
The prevalence of obesity was estimated using BMI for Asian population classification and was found to be 22.6% (113 respondents out of 500).
[Table 1] shows association between various epidemiological factors observed in the present study and the BMI categories the respondents belonged to. The present study found that being obese was significantly associated with increasing age and higher parity (P< 0.05). No other sociodemographic factor showed statistically significant association.
[Table 2] depicts findings of dietary factors and physical activity patterns observed in the study. Calorie content was calculated using standard values of the National Institute of Nutrition. Using RDA values according to their occupation, the total Calorie intake was classified as Adequate, excess, or deficient for each respondent. CDC has recommended 7–8 h of sleep as adequate sleep duration for adults. Besides sleeping, time spent in other activities where the respondent remained sedentary such as watching TV, sitting in a place while doing kitchen chores and social gatherings was estimated separately as per the WHO guidelines. Only frequency of consumption of green leafy vegetables (GLVs), frequency of consumption fried foods at home, amount of oil consumed per day and total duration of time spent sleeping was found to be statistically significantly associated with obesity status of the respondent.
|Table 2: Association of dietary and physical activity patterns with obesity status|
Click here to view
[Table 3] and [Table 4] display the change in dietary habits, physical activity pattern reported by the respondents of the study and anthropometric parameters of the respondents 6 months after the health intervention. All the factors had changed for the better after the health intervention.
|Table 4: Comparison of physical activity and anthropometric parameters pre and post intervention|
Click here to view
| Discussion|| |
No comparative study was found while reviewing various literature that included all the epidemiological factors investigated in the present study. Vadera et al., found the prevalence of obesity increased with the rise in age till 50 years, after which it declined (P< 0.001); similar to the present study. Gupta and Kapoor  also found significant positive correlations between parity number and various obesity markers in their study. Comparable to the findings of the present study, Anuradha et al. found no statistical association between religion, occupation, type of family, and marital status with obesity. However, unlike in the present study where no statistical association was found, Anuradha et al. found highly significant association between education as well SES and obesity (P< 0.001).
Jayamani et al. found that the odds of women who took higher calorie diet (whether urban or rural) being overweight or obese was five times more than women who had low-calorie diet. Anuradha et al. found no association between frequency of GLV consumption, fruit consumption and obesity. Basagoudar and Chandrashekhar. found statistically significant higher occurrence of overweight or obesity among women who had the habit of eating junk foods or snacks in between the meals regularly. Some findings of the present study were comparable to other study findings such as no statistical association between type of diet and obesity; significant association between frequency of eating fried foods at home and obesity; significant association between amount of oil used per person per day; and no statistically significantly differences for meat and occurrence of obesity.
In the present study, total duration of sleep taken in the day (which included night sleep as well as any time spent sleeping in the day) was compared with obesity status and the difference was found to be statistically significant (Chi-square value = 7.89, P = 0.019) which is comparable to Anuradha et al. (P = 0.006). Only 22 respondents (4.4%) were found to be exercising regularly according to the WHO guideline of regular exercise. Out of these 22 respondents, 13 (59.1%) were found to be obese and the rest 9 (40.9%) were not obese. However, whether they had started exercising after they realized they were gaining weight or as a regular habit was not assessed in the current study. Hence, no association was assessed between obesity and exercising habits.
A total of 113 respondents were found to fall within the BMI range ≥ 25.00. Hence, the prevalence of obesity was found to be 22.6% in the present study. All these women were given health education regarding obesity, its epidemiology, prevention and control by means of flip-chart. They were then visited again after 6 months to evaluate any change in their dietary habits, physical activity pattern and weight. The results of the findings of these parameters before and after intervention are enumerate below.
All dietary habits reviewed in the study showed statistically significant change after the intervention (P< 0.05). These findings are similar to the findings of studies conducted by Sharaf (2010) (frequency of consumption of fresh vegetables and frequency of junk food consumption) and O'Brien et al. (frequency of meat consumption and frequency of fruit consumption).
The respondents reported fewer hours spent sedentary overall after the intervention. Although the respondents who had reported that they over or underslept earlier, mentioned better-sleeping patterns after the intervention, the change was not found to be statistically significant. Sharaf (2010) also found no significant improvement in any physical activity patterns of their respondents after intervention in the study. Twenty-two, more respondents, reported exercising regularly postintervention in the present study. Hardcastle et al. found that there was a significant increase in walking between baseline and follow-up in the intervention group indicating a sustained change for this variable over the follow-up period in their study. They found a significant impact of health education in their study which is comparable to the findings of the present study.
The present study reports a statistically significant change in both parameters in the follow-up period of intervention. This finding is comparable to the study conducted by Hardcastle et al. who also found that BMI in obese patients significantly decreased between baseline and 6-month observations in those who were given health intervention.
| Conclusions|| |
The present cross-sectional study was conducted on women >20 years. After health education intervention by means of flip-chart given to all the obese respondents, it was observed that there was a significant change in dietary and physical activity patterns of the respondents like increased GLV consumption, increased frequency of fruit consumption in a week (Respondents reported that a serving of fruit replaced an unhealthy dietary habit instead of it being an added serving to other dietary calories), decreased frequency of fried food items, junk foods and oil consumption. The study also noted reporting of decrease in duration of time spent sleeping and other sedentary activities. Weight and BMI of the obese respondents also decreased over the period of follow-up and more respondents reported exercising regularly.
Results of the study strongly suggest that obesity is associated with numerous factors and their interplay in various combinations rather than a single cause. This predisposes adult women residing in adverse environmental conditions of slums to harmful weight gain. Obesity needs to be curbed at its roots. Measures should be deployed at its various trigger points at the individual and community level to help contain this fast-growing epidemic. This cannot be achieved without intersectoral coordination and active participation of both health professionals and community members. Very few community-based interventions have been attempted in India, even few so in slums.
This study is also not devoid of limitations. No information about childhood factors of the respondents such as birth weight, exclusive breastfeeding in their childhood, and history of childhood obesity were obtained in the study. Details of her antenatal history or other factors like whether she had exclusive breastfed her child/children was not obtained. Psychological factors like body image perception, depression, etc., associated with obesity were not considered in the present study. In addition, the study being a cross-sectional study design, the association may not be causal and better-designed studies are recommended to prove the hypothesis. More detailed community-based studies are required and recommended to understand the role of these factors in the epidemiology of obesity.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Park K. Park's Textbook of Preventive and Social Medicine. 23rd
ed. Jabalpur: Banarsidas Banot Publishers; 2013. p. 523-7.
Misra A, Pandey RM, Devi JR, Sharma R, Vikram NK, Khanna N. A high prevalence of diabetes, obesity and dyslipidaemia in an urban slum population in Northern India. Int J Obesity Relat Metab Disord 2001;25:1722-9.
International Institute for Population Sciences (IIPS) and Macro International. National Family Health Survey (NFHS-3), 2005-06. India, Mumbai: IIPS, Key Findings; 2007.
World Health Organization (WHO). International Association for the Study of Obesity (IASO), and International Obesity Task Force (IOTF). The Asia-Pacific Perspective: Redefining Obesity and Its Treatment. Geneva: World Health Organization; 2000. p. 378-420.
Basu K, Maertens A. The pattern and causes of economic growth in India. Oxford Rev Econ Policy 2007;23:143-67.
Reddy M, Kumar K, Jamil K. New World Syndrome (Obesity) in South India. Open Access Sci Rep 2012;1:567.
Lwanga SK, Lemeshow S. Sample Size Determination in Health Studies: A Practical Manual. Geneva: WHO; 1991.
World Health Organisation. WHO STEPS Surveillance. Part 3 Training and Practical Guides, Section 4: Guide to Physical Measurements (Step 2). Geneva: WHO; 2008. p. 1-15.
Roche Manufacturers. Accu Chek Active Glucometer Manual. Germany: Roche Manufacturers; 2008. p. 31-9.
National Institute of Nutrition. Dietary Guidelines for Indians – A Manual. 2nd
ed. Hyderabad: Indian Council of Medical Research; 2011.
Park K. Park's Textbook of Preventive and Social Medicine. 23rd
ed. Jabalpur: Banarsidas Banot Publishers; 2013. p. 636.
Vadera BN, Yadav SB, Yadav BS, Parmar DV, Unadkat SV. Study on obesity and influence of dietary factors on the weight status of an adult population in Jamnagar city of Gujarat: A cross-sectional analytical study. Indian J Community Med 2010;35:482-6.
] [Full text]
Gupta S, Kapoor S. Independent and combined association of parity and short pregnancy with obesity and weight change among Indian women. Health 2012;4:271-6.
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.
Jayamani V, Gopichandran V, Lee P, Alexander G, Christopher S, Prasad JH. Diet and physical activity among women in urban and rural areas in South India: A community based comparative survey. J Fam Med Prim Care 2013;2:334-8.
Basagoudar S, Chandrashekhar R. Study of obesity and its risk factors among women of reproductive age group. Int J Curr Res Rev 2013;5:23-38.
Tiwari R, Srivastava D, Gour N. A cross-sectional study to determine prevalence of obesity in high income group colonies of Gwalior city. Indian J Community Med 2009;34:218-22.
] [Full text]
Andreou E, Hajigeorgiou P, Kyriakou K, Avraam T, Chappa G, Kallis P, et al.
Risk factors of obesity in a cohort of 1001 Cypriot adults: An epidemiological study. Hippokratia 2012;16:256-60.
Sharaf F. Impact of health education on compliance among patients of chronic diseases in Al Qassim, Saudi Arabia. Int J Health Sci (Qassim) 2010;4:139-48.
O'Brien KM, Hutchesson MJ, Jensen M, Morgan P, Callister R, Collins CE, et al.
Participants in an online weight loss program can improve diet quality during weight loss: A randomized controlled trial. Nutr J 2014;13:82.
Hardcastle SJ, Taylor AH, Bailey MP, Harley RA, Hagger MS. Effectiveness of a motivational interviewing intervention on weight loss, physical activity and cardiovascular disease risk factors: A randomised controlled trial with a 12-month post-intervention follow-up. Int J Behav Nutr Phys Act 2013;10:40.
[Table 1], [Table 2], [Table 3], [Table 4]