Prevalence Of Obesity In India Research Articles

Age-appropriate BMI cut-offs for malnutrition among older adults in India

With the increasing prevalence of obesity in India, body mass index (BMI) has garnered importance as a disease predictor. The current World Health Organization (WHO) body mass index (BMI) cut-offs may not accurately portray these health risks in older adults aged 60 years and above. This study aims to define age-appropriate cut-offs for older adults (60–74 years and 75 years and above) and compare the performance of these cut-offs with the WHO BMI cut-offs using cardio-metabolic conditions as outcomes. Using baseline data from the Longitudinal Ageing Study in India (LASI), classification and regression tree (CART) cross-sectional analysis was conducted to obtain age-appropriate BMI cut-offs based on cardio-metabolic conditions as outcomes. Logistic regression models were estimated to compare the association of the two sets of cut-offs with cardio-metabolic outcomes. The area under the receiver operating characteristic curve (AUC), sensitivity and specificity were estimated. Agreement with waist circumference, an alternate measure of adiposity, was conducted. For older adults aged 60–74 years and 75 years and above, the cut-off for underweight reduced from < 18.5 to < 17.4 and < 13.3 respectively. The thresholds for overweight and obese increased for older adults aged 60–74 years old from > = 25 to > 28.8 and > = 30 to > 33.7 respectively. For older adults aged 75 years and above, the thresholds decreased for both categories. The largest improvement in AUC was observed in older adults aged 75 years and above. The newly derived cut-offs also demonstrated higher sensitivity and specificity among all age-sex stratifications. There is a need to adopt greater rigidity in defining overweight/obesity among older adults aged 75 years and above, as opposed to older adults aged 60–74 years old among whom the thresholds need to be less conservative. Further stratification in the low risk category could also improve BMI classification among older adults. These age-specific thresholds may act as improved alternatives of the current WHO BMI thresholds and improve classification among older adults in India.

Obesity in India: Challenges and way forward

Obesity is a complex metabolic disorder characterized by excessive fat accumulation that can trigger many health issues in the long run. The global burden of obesity has tripled since the seventies. As of 2016, there were 1.9 billion overweight adults, of which 650 million were obese.1 In the same year, 135 million individuals were affected by obesity in India.2 It is projected that the prevalence of obesity in India will triple by 2040. Importantly, the prevalence of obesity in India by 2040 will be 9.5% in men and 13.9% in women.3Therefore, the obesity scourge can be considered to be a “ticking time bomb,” ready to explode at any moment and will impact large populations across all age groups in both rural and urban areas

Perception, risk factors, and health behaviours in adult obesity in Kolkata, India: a mixed methods approach

BackgroundWorld Health Organisation has described obesity as one of the most neglected public health issues. Initially, obesity was only a problem in high-income countries; however, at present, it is rising in middle and low-income countries as well, rapidly in India, especially in the urban areas. In the light of the increasing prevalence of obesity in India, it was worthwhile to study perception, risk factors and health behaviours in adult obesity holistically.MethodsThis study resorted to a concurrent mixed methods approach, collecting and combining quantitative survey (n = 120) and qualitative interview data (n = 18). Female and male aged 25–54 years with a waist circumference of 80 cm and 90 cm or higher, respectively, and a BMI of 25 or higher were selected from Kolkata, India. Kolkata was chosen as the study area since it ranked 7th out of 640 districts, the highest among the five major urban cities in India, with around 41% of the female and 43% of the male population aged 15–49 years with a BMI of 25 or higher.ResultsParticipants confirmed that lifestyle was one of the main reasons for obesity. They believed that family history, social relations, behavioural factors, urbanisation, and time-poor were significant risk factors of obesity. Interview participants expanded that technology, lack of health education and self-care, and digital marketing of food influenced the risk of obesity. Participants confirmed that they wanted to lose weight to feel healthier. Most respondents claimed that they engaged in lightly to moderate-intensity physical activity. However, a discrepancy in opinion was observed between survey responses and interview participants’ views on dietary behaviours. Participants confirmed that they rarely consulted health professionals and that the family had a minimal role in preventing obesity. Interview participants expanded that people should make better lifestyle choices at an individual level to prevent obesity.ConclusionsHealth education is fundamental. Making better lifestyle choices is crucial, which would help increase the lifespan and health span and decrease the risk of diseases. In addition, social support and better policies are required to prevent the disease and any related complications.

Community based cross-sectional study on prevalence of overweight and obesity among adult population of Jabalpur City, Madhya Pradesh, India

Introduction: The WHO had estimated that in 2016, more than 1.9 billion adults worldwide (39%) were overweight, and over 650 million (13%) were obese. Approximately 2.8 million deaths were reported as a result of being overweight or obese. The prevalence of overweight and obesity in India is increasing faster than the world average. A study reported that prevalence of obesity in India is 40.3%.This fast-paced growth has been accompanied by notable increases in the burden of non-communicable diseases. Objectives: to estimate the prevalence of overweight and obesity among adults in Jabalpur City and to study the association between socio-demographic factors and overweight in adults. Methodology: Multistage sampling method was used for the study. In this method, the sampling procedure was carried out at several stages, each stage involves a different sampling procedure. House to house survey was conducted after explaining the purpose and procedure of the study and obtaining informed written consent from study participants. Interview of eligible study participants regarding socio-demographic, behavioral parameters along with measurement of physical/ anthropometric parameters was carried out using a predesigned and pretested Questionnaire.

The Quality of Indian Obesity-Related mHealth Apps: PRECEDE-PROCEED Model-Based Content Analysis.

BackgroundThe prevalence of obesity in India is increasing at an alarming rate. Obesity-related mHealth apps have proffered an exciting opportunity to remotely deliver obesity-related information. This opportunity raises the question of whether such apps are truly effective.ObjectiveThe aim of this study was to identify existing obesity-related mHealth apps in India and evaluate the potential of the apps’ contents to promote health behavior change. This study also aimed to discover the general quality of obesity-related mHealth apps.MethodsA systematic search for obesity-related mHealth apps was conducted in both the Google Play Store and the Apple App Store. The features and quality of the sample apps were assessed using the Mobile Application Rating Scale (MARS) and the potential of the sample apps’ contents to promote health behavior change was assessed using the PRECEDE-PROCEED Model (PPM).ResultsA total of 13 apps (11 from the Google Play Store and 2 from the Apple App Store) were considered eligible for the study. The general quality of the 13 apps assessed using MARS resulted in mean scores ranging from 1.8 to 3.7. The bivariate Pearson correlation between the MARS rating and app user rating failed to establish statistically significant results. The multivariate regression analysis result indicated that the PPM factors are significant determinants of health behavior change (F3,9=63.186; P<.001) and 95.5% of the variance (R2=0.955; P<.001) in the dependent variable (health behavior change) can be explained by the independent variables (PPM factors).ConclusionsIn general, mHealth apps are found to be more effective when they are based on theory. The presence of PPM factors in an mHealth app can greatly influence the likelihood of health behavior change among users. So, we suggest mHealth app developers consider this to develop efficient apps. Also, mHealth app developers should consider providing health information from credible sources and indicating the sources of the information, which will increase the perceived credibility of the apps among the users. We strongly recommend health professionals and health organizations be involved in the development of mHealth apps. Future research should include mHealth app users to understand better the apps’ effectiveness in bringing about health behavior change.

An evaluation of micronutrient status in severe obesity and follow-up assessment after bariatric surgery: A retrospective single-center study

Background: Micronutrient deficiency is common in obesity despite surplus weight and high caloric intake. Further exacerbation is often seen after bariatric surgery due to the resultant dietary restrictions, and physiological and anatomical alterations. Owing to the rising prevalence of obesity in India with a simultaneous surge in bariatric surgeries, an account of micronutrient status is required. This will help in identifying susceptible individuals and setting up priorities for prevention and intervention. Subjects and Methods: A retrospective study was designed to analyze the data collected before and until 1 year (3, 6, and 12 months) after bariatric surgery in individuals with severe obesity (body mass index ≥35 kg/m2, n = 150). We included the assessment of nutritional parameters, namely, serum iron, ferritin, total iron-binding capacity, Vitamin B12, folic acid, homocysteine, calcium, phosphorus, Vitamin D, and parathormone along with anthropometric and routine biochemical investigations. Results: Deficiency of Vitamin D was most prevalent (52%) at baseline, followed by anemia (21%). Ferritin deficiency was 9.3%, followed by iron (8.0%), Vitamin B12(7.3%), and folate deficiency (4.7%) at baseline. There was a remarkable improvement in Vitamin D deficiency (26%), whereas the percent prevalence of other micronutrients has shown deterioration in 12 months after bariatric surgery. No significant difference existed in the prevalence of micronutrient deficiency between laparoscopic sleeve gastrectomy (n = 75) and laparoscopic Roux-en-Y gastric bypass surgery (n = 75) over the 12-month follow-up period. Conclusion: Micronutrient deficiencies persisted after bariatric surgery underlining the need for fine adjustment of supplementations and monitoring compliance to ensure the best patient outcomes.

Population estimates, consequences, and risk factors of obesity among pregnant and postpartum women in India: Results from a national survey and policy recommendations.

ObjectiveTo examine prevalence, risk factors, and consequences of maternal obesity; and provide evidence on current policies and programs to manage maternal obesity in India.MethodsThis is a mixed‐methods study. We analyzed the National Family Health Survey (NFHS)‐4 data (2015–16) to estimate the prevalence and risk factors of obesity, followed by a desk review of literature and stakeholder mapping with interviews to develop policy guidance.ResultsNational prevalence of obesity (defined by WHO as body mass index ≥25) was comparable among pregnant (12%) and postpartum women (13%) ≥20 years of age. A high prevalence of obesity (>40%) was observed in over 30 districts in multiple states. Older maternal age, urban residence, increasing wealth quintile, and secondary education were associated with increased odds of obesity among pregnant and postpartum women; higher education increased odds among postpartum women only (OR 1.90; 95% CI, 1.44–2.52). Dietary variables were not associated with obesity. Several implementation challenges across healthcare system blocks were observed at policy level.ConclusionOverall prevalence of obesity in India during and after pregnancy is high, with huge variation across districts. Policy and programs must be state‐specific focusing on prevention, screening, and management of obesity among pregnant and postpartum women.

Relative contribution of diet and physical activity to increased adiposity among rural to urban migrants in India: A cross-sectional study.

In common with many other low- and middle-income countries (LMICs), rural to urban migrants in India are at increased risk of obesity, but it is unclear whether this is due to increased energy intake, reduced energy expenditure, or both. Knowing this and the relative contribution of specific dietary and physical activity behaviours to greater adiposity among urban migrants could inform policies for control of the obesity epidemic in India and other urbanising LMICs. In the Indian Migration Study, we previously found that urban migrants had greater prevalence of obesity and diabetes compared with their nonmigrant rural-dwelling siblings. In this study, we investigated the relative contribution of energy intake and expenditure and specific diet and activity behaviours to greater adiposity among urban migrants in India. The Indian Migration Study was conducted between 2005 and 2007. Factory workers and their spouses from four cities in north, central, and south of India, together with their rural-dwelling siblings, were surveyed. Self-reported data on diet and physical activity was collected using validated questionnaires, and adiposity was estimated from thickness of skinfolds. The association of differences in dietary intake, physical activity, and adiposity between siblings was examined using multivariable linear regression. Data on 2,464 participants (median age 43 years) comprised of 1,232 sibling pairs (urban migrant and their rural-dwelling sibling) of the same sex (31% female) were analysed. Compared with the rural siblings, urban migrants had 18% greater adiposity, 12% (360 calories/day) more energy intake, and 18% (11 kilojoules/kg/day) less energy expenditure (P < 0.001 for all). Energy intake and expenditure were independently associated with increased adiposity of urban siblings, accounting for 4% and 6.5% of adiposity difference between siblings, respectively. Difference in dietary fat/oil (10 g/day), time spent engaged in moderate or vigorous activity (69 minutes/day), and watching television (30 minutes/day) were associated with difference in adiposity between siblings, but no clear association was observed for intake of fruits and vegetables, sugary foods and sweets, cereals, animal and dairy products, and sedentary time. The limitations of this study include a cross-sectional design, systematic differences in premigration characteristics of migrants and nonmigrants, low response rate, and measurement error in estimating diet and activity from questionnaires. We found that increased energy intake and reduced energy expenditure contributed equally to greater adiposity among urban migrants in India. Policies aimed at controlling the rising prevalence of obesity in India and potentially other urbanising LMICs need to be multicomponent, target both energy intake and expenditure, and focus particularly on behaviours such as dietary fat/oil intake, time spent on watching television, and time spent engaged in moderate or vigorous intensity physical activity.

Effect of Different Shoe Lacing Pattern on Different Types of Foot in Recreational Runners

Background: There has been an increase in the overall prevalence of obesity in India. There has been a&#x0D; 26% rise in the obesity among the young adults of India. At the same time, an awareness about fitness and&#x0D; health has also been on a rise in our country.Jogging and running have been on a rise in popularity among&#x0D; the youth of India. Heel-to-toe drop, styles of running, brand, fit and shoe lacing are some other factors that&#x0D; affect running. Out of these shoe lacing is one of the simplest factors to modify. It can be done by anybody&#x0D; and is an extremely cost effective measure.&#x0D; Methodology: An experimental study is being conducted with a sample size of 33 subject in karad. The&#x0D; population under study is Recreational runners age group of 20-40 years both male and female subjects. VAS&#x0D; and Foot Posture Index were the outcome measures used.&#x0D; Result: There was a significant effect of modifying shoe lacing patterns on FFI scores. (p=&lt;0.001) There was&#x0D; also a significant effect on FPS (p &lt;0.001) and FDS (p &lt;0.001) subscales whereas there was no significant&#x0D; effect on ALS subscale (p &gt;0.05). A significant decrease in pain was also noted. (p &lt;0.05)&#x0D; Conclusion On the basis of the results of the study, it was concluded that there was a significant effect of&#x0D; modifying shoe lacing patterns on amateur runners.

Prevalence of Obesity in India and Its Neurological Implications: A Multifactor Analysis of a Nationwide Cross-Sectional Study.

Background:India is undergoing a rapid epidemiological transition, from underweight to overweight/obese population. Obesity is a major risk factor in type 2 diabetes and cardiovascular diseases, and is also implicated as a factor in neurological diseases such as Alzheimer’s disease. A robust, pan-Indian estimate of obesity is not yet available.Purpose:This study estimates the pan-Indian prevalence of obesity, stratified across nonmodifiable (age and gender) and modifiable (education and physical activity levels) factors, and across zones and urban/rural.Methodology:Data for 1,00,531 adults from a nationwide randomized cluster sample survey (Niyantrita Madhumeha Bharata 2017, phase 1) were analyzed. Obesity was determined using body mass index, and cross-tabulations were calculated across zones, age, gender, education, physical activity, and area. To determine statistical significance, t-tests were used. The odds of obesity within each category of the various factors were calculated using binary logistic regression.Results:Prevalence of obesity in India is 40.3%. Zonal variations were seen as follows: south highest at 46.51% and east lowest at 32.96%. Obesity was higher among women than men (41.88% vs. 38.67%), urban than rural (44.17% vs. 36.08%), and over 40 than under 40 (45.81% vs. 34.58%). More education implied a higher obesity (44.6% college vs. 38% uneducated), as did lowered physical activity (43.71% inactive vs. 32.56% vigorously active). The odds ratio for physical activity was 3.83, stronger than age (1.58), education (1.4), urban (1.3), and gender (1.2).Conclusion:Obesity levels in India are very high, across all zones. The odds of being obese increases with age, and is higher among women and among urban dwellers. Obesity is the highest among aging urban men and women who are college educated and are sedentary. Physical activity and aging are the strongest determinants of obesity. Given the high cost of obesity in terms of type 2 diabetes, cardiovascular diseases, and Alzheimer’s disease, urgent public health measures are necessary to reduce its impact.

Obesity, Lipid Profile and Inflammation: A Study of Adult Women of Low socioeconomic Background from Mumbai City

Obesity associated inflammation is an important mediator for obesity-associated non-communicable diseases (NCDs). The increasing prevalence of obesity in India, therefore is of concern. The present study aimed to examine the prevalence of obesity in apparently healthy women (n=1500) and examine the relationship between anthropometric indices, lipid profile and inflammatory markers. The prevalence of obesity was 43.6% by body mass index, 59.5% using percent body fat, 36.5% by waist circumference and 40.6% by waist hip ratio respectively. Mean serum triglyceride and high sensitivity C-reactive protein (hs-CRP) were significantly high in obese women. In obese women, hs-CRP significantly correlated with body mass index, waist circumference and percent body fat; whereas Interleukin-6 correlated with waist circumference and waist hip ratio. Therefore, with rising obesity, it is important to intervene in order to reduce the risks associated with obesity.

Prevalence of Obesity among 6 to 12 Year Old School Children in Kolenchery, Kerala

Childhood obesity is one of the major public health threats both nationally and internationally. The prevalence of childhood obesity in India has been increasing at an alarming pace owing its credit to fast food culture, changing habits of children as well as the parents. An imbalance between calorie intake and calories utilized by the growing child's body is what primarily leads to malnutrition. One or more factors (genetic, behavioural, and environmental) cause obesity in children. Obese children and their families suffer physical, psychological, and social problems. Hence, effective intervention strategies are needed to prevent and control obesity in children. The purpose of this study was to assess the prevalence of childhood obesity among 6 to 12 year old school going children at Kolenchery, Kerala, address various factors influencing childhood obesity, so that a variety of interventions and governmental actions to address this challenge can be developed.

Obesity among adult population of a rural coastal area in South India

&lt;p class="abstract"&gt;&lt;strong&gt;Background:&lt;/strong&gt; Obesity is associated with cardiovascular diseases and has become the main public health issue in India. However, the prevalence of obesity in India varies widely. The aim of this study was to assess the prevalence of overweight and obesity among rural adults in a coastal area of South India.&lt;strong&gt;&lt;/strong&gt;&lt;/p&gt;&lt;p class="abstract"&gt;&lt;strong&gt;Methods:&lt;/strong&gt; The prevalence of overweight and obesity was assessed among individuals of 15 years and above living in a rural coastal area of Tamil Nadu in India.&lt;/p&gt;&lt;p class="abstract"&gt;&lt;strong&gt;Results:&lt;/strong&gt; Among 207 adult participants, 69.1% were female. About one-fourth (23.7%) of the participants were in age group of 15-24 years and 67.2% participants were literate. About one-third (30%) of the adults were overweight. Obesity was present in 14% of the study participants (26% by using the Asian cut-offs). Using waist circumference and waist-hip ratio cut-offs, abdominal obesity was observed among 55% and 57% of the participants. Among females the central obesity was more common than males. &lt;strong&gt;&lt;/strong&gt;&lt;/p&gt;&lt;strong&gt;Conclusions:&lt;/strong&gt; The prevalence of obesity in rural areas was high. There is need to implement community based programs to tackle the increasing obesity.

Diabetes epidemic in the South Asian Diaspora: action before desperation

Diabetes epidemic in the South Asian Diaspora: action before desperation

Diabetes epidemic in the South Asian Diaspora: Action before desperation

Diabetes epidemic in the South Asian Diaspora: Action before desperation