@ARTICLE{Singh, author = {Singh, Chetna and Jain, Neha and Saini, Vandana and Jain, Monika and Tyagi, Gargi and }, title = {Dietary Habits and a Need Assessment Survey of Obese Working Adults in Delhi, India}, volume = {11}, number = {3}, abstract ={Background: Lifestyle changes in working adults have caused a high prevalence of obesity and various interrelated comorbidities, including hypertension, type 2 diabetes, and cardiovascular diseases. Healthy dietary modifications can help tackle these problems, but easy accessibility to healthier options is an issue. This study aims to investigate the dietary habits of obese adults and identify their unmet food-related needs. Materials and Methods: In this cross-sectional study, subjects were of 30-59 (n = 400) years. The subjects worked in offices in Delhi and were diagnosed with obesity based on their body mass index (BMI) being ≥ 25 kg/m2. A self-administered questionnaire was used to record dietary information and perform a need assessment survey. Additionally, mean, standard deviation, Z-test, and odds ratio were used for statistical analysis. Results: The mean BMI of males and females was 28.02 ± 2.25 kg/m2 and 28.04 ± 2.00 kg/m2. Waist circumference was higher than 90 cm in 98.0% of males and 80 cm in 97.7% of females. Besides, over half of the subjects (56.75%) reported comorbidities, most commonly diabetes, hypertension, and dyslipidemia. Unhealthy foods including fast foods, sweets, ice cream, burgers, fries, chips, and other high-fat snacks like samosas were frequently consumed by over two-thirds of subjects. The highest unmet need among the subjects was nutraceutical-rich healthy food. Conclusions: High waist circumference was prevalent among the subjects causing a high risk of NCDs. The urgent need among subjects was for non-ultra-processed nutraceuticals rich and high-fiber foods. }, URL = {http://johe.rums.ac.ir/article-1-578-en.html}, eprint = {http://johe.rums.ac.ir/article-1-578-en.pdf}, journal = {Journal of Occupational Health and Epidemiology}, doi = {10.61186/johe.11.3.238}, year = {2022} }