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4. Utilization of Ayurveda, Yoga, Naturopathy, Unani, Siddha, and Homoeopathy (AYUSH) Practitioners’ Services Among Older Adults: Results From the Longitudinal Aging Study in India

Author

Mohanty, Parimala, primary, Kishore, Jugal, additional, Acharya, Geeta C, additional, Mohanty, Itishree, additional, Patnaik, Lipilekha, additional, Bhowmik, Bratati, additional, Sahoo, Monalisha, additional, Satpathy, Nancy, additional, Sahoo, Prasanta K, additional, and Jena, Pratap K, additional

Published
2024
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7. Dietary Patterns and Lifestyle Changes during COVID-19 Lockdown: A Cross-Sectional Online Survey among 674 Indian Older Adults.

Author

Mohanty, Parimala, Patnaik, Lipilekha, Srivastava, Shobhit, Muhammad, T., and Dutta, Ambarish

Subjects
*LIFESTYLES, *CROSS-sectional method, *DIETARY patterns, *BODY mass index, *LOGISTIC regression analysis, *SEX distribution, *DESCRIPTIVE statistics, *SCREEN time, *AGE distribution, *STAY-at-home orders, *ODDS ratio, *SLEEP, *HEALTH behavior, *CONFIDENCE intervals, *PUBLIC health, *HEALTH promotion, *HEALTH education, *COVID-19 pandemic, *PHYSICAL activity, *MIDDLE age, *OLD age
Abstract

The COVID-19 pandemic has had a significant impact on human health and has led to social isolation and health implications. In order to optimize public health, it is important to understand the role of social and behavioral sciences, including dietary patterns and lifestyle changes. This study aimed to identify the effect of lockdown on dietary patterns and its association with Body Mass Index (BMI) and lifestyle changes in the older Indian population (aged 60 and above).The study was conducted using an online web-based Google form and 674 participants took part over a one-month period. The k-means algorithm was used to identify non-overlapping dietary patterns and logistic regression was employed to determine the factors associated with changes in dietary patterns. Three dietary patterns were identified: pro-healthy, constant, and unhealthy.During the study, 33.1% of the participants decreased their physical activity while 61.6% increased their screen usage. 26.7% consumed a pro-healthy dietary pattern, while 61.9% consumed an unhealthy dietary pattern. Women reported lower consumption of the pro-healthy pattern (23.8%) and higher consumption of the unhealthy dietary pattern (64.5%) compared to men (30.6% and 58.3%, respectively). Adherence to the pro-healthy dietary pattern was positively associated with age. Participants with a lower BMI were less likely to consume a pro-healthy dietary pattern [AOR: 0.02; CI: 0.01, 0.2]. Those who increased their physical activity were more likely to follow the pro-healthy dietary pattern [AOR: 6.49; CI: 0.76, 55.76]. Those who had less sleep [AOR: 10.22; CI: 1.97, 52.92] and more screen time [AOR: 7.61; CI: 3.28, 17.62] had a higher risk of following an unhealthy dietary pattern.The lockdown had a significant impact on dietary patterns and was associated with unhealthy lifestyle outcomes among older Indian adults. From a public health perspective, promoting awareness of healthy dietary patterns and promoting healthy lifestyles through educational programs is a priority. [ABSTRACT FROM AUTHOR]

Published
2024
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8. Post COVID sequelae among COVID-19 survivors: insights from the Indian National Clinical Registry for COVID-19

Author

Kumar, Gunjan, primary, Bhalla, Ashish, additional, Mukherjee, Aparna, additional, Turuk, Alka, additional, Talukdar, Arunansu, additional, Mukherjee, Subhasis, additional, Bhardwaj, Pankaj, additional, Menon, Geetha R, additional, Sahu, Damodar, additional, Misra, Puspender, additional, Sharma, Lokesh Kumar, additional, Mohindra, Ritin, additional, S, Samita, additional, Suri, Vikas, additional, Das, Himadri, additional, Sarkar, Debasis, additional, Ghosh, Soumyadeep, additional, Ghosh, Priyanka, additional, Dutta, Moumita, additional, Chakraborty, Shreetama, additional, Kumar, Deepak, additional, Gupta, Manoj Kumar, additional, Goel, Akhil Dhanesh, additional, Baruah, Tridip Dutta, additional, Kannauje, Pankaj Kumar, additional, Shukla, Arvind Kumar, additional, Khambholja, Janakkumar R, additional, Patel, Amit, additional, Shah, Nitesh, additional, Bhuniya, Sourin, additional, Panigrahi, Manoj Kumar, additional, Mohapatra, Prasanta Raghab, additional, Pathak, Ashish, additional, Sharma, Ashish, additional, John, Mary, additional, Kaur, Kiranpreet, additional, Nongpiur, Vijay, additional, Pala, Star, additional, Shivnitwar, Sachin K, additional, Krishna, Bobba Rohil, additional, Dulhani, Naveen, additional, Gupta, Balkishan, additional, Gupta, Jigyasa, additional, Bhandari, Sudhir, additional, Agrawal, Abhishek, additional, Aggarwal, H K, additional, Jain, Deepak, additional, Shah, Arti D, additional, Naik, Parshwa, additional, Panchal, Manisha, additional, Anderpa, Mayank, additional, Kikon, Nyanthung, additional, Humtsoe, Christina Nzani, additional, Sharma, Nikita, additional, Vohra, Rajaat, additional, Patnaik, Lipilekha, additional, Sahoo, Jagdish Prasad, additional, Joshi, Rajnish, additional, Kokane, Arun, additional, Ray, Yogiraj, additional, Rajvansh, Kruti, additional, Purohit, Hemang M, additional, Shah, Nehal M, additional, Madharia, Arun, additional, Dube, Simmi, additional, Shrivastava, Neha, additional, Kataria, Sushila, additional, Shameem, Mohammad, additional, Fatima, Nazish, additional, Ghosh, Saumitra, additional, Hazra, Avijit, additional, D, Himanshu, additional, Salgar, Veeresh B, additional, Algur, Santosh, additional, M L, Kala Yadhav, additional, M, Pavan Kumar, additional, Panda, Samiran, additional, Vishnu Vardhana Rao, Mendu, additional, and Bhargava, Balram, additional

Published
2023
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22. Analysis of predictors and outcomes of COVID-19 patients requiring ICU admission from COVID 19

Author

Kajal, Kamal, primary, Singla, Karan, additional, Puri, Goverdhan Dutt, additional, Bhalla, Ashish, additional, Mukherjee, Aparna, additional, Kumar, Gunjan, additional, Turuk, Alka, additional, Premkumar, Madhumita, additional, Mahajan, Varun, additional, Bingi, Thrilok Chander, additional, Bhardwaj, Pankaj, additional, John, Mary, additional, Menon, Geetha R, additional, Sahu, Damodar, additional, Panda, Samiran, additional, Rao, Vishnu Vardhan, additional, Mesipogu, Rajarao, additional, Mohiuddin, Mohammed Ayaz, additional, Aedula, Vinaya Sekhar, additional, Gupta, Manoj K, additional, Goel, Akhil D, additional, Loomba, Vikas, additional, Thomas, Maria, additional, Ojha, U K, additional, Jha, R R, additional, Salgar, Veeresh, additional, Algur, Santosh, additional, Pathak, Ashish, additional, Sharma, Ashish, additional, Purohit, Manju, additional, Dandu, Himanshu, additional, Gupta, Amit, additional, Kumar, Vivek, additional, Sarangi, Lisa, additional, Rath, Mahesh, additional, Baruah, Tridip Dutta, additional, Kannauje, Pankaj Kumar, additional, Kumar, Ajit, additional, Joshi, Rajnish, additional, Saigal, Saurabh, additional, Goel, Abhishek, additional, Khambholja, Janakkumar R, additional, Patel, Amit, additional, Madan, Surabhi, additional, Shah, Nitesh, additional, Katyal, V K, additional, Singh, Deepinder, additional, Goyal, Sandeep, additional, Shah, Arti, additional, Chauhan, Amit, additional, Patel, Bhavesh, additional, L, Kala Yadhav M, additional, P, Dayananda V, additional, S, Chetana G, additional, Desai, Anita, additional, Panchal, Manisha, additional, Anderpa, Mayank, additional, Tadavi, Payal, additional, Bhuniya, Sourin, additional, Panigrahi, Manoj Kumar, additional, Bal, Shakti Kumar, additional, Shivnitwar, Sachin K, additional, Lokhande, Prajakta, additional, Tripathy, Srikanth, additional, Nongpiur, Vijay, additional, Pala, Star, additional, Jamil, Md, additional, Gupta, Bal Kishan, additional, Gupta, Jigyasa, additional, Upadhyay, Rashmi, additional, Srivast, Saurabh, additional, Dube, Simmi, additional, Dwivedi, Preksha, additional, Saxena, Rita, additional, Shameem, Mohammed, additional, Fatima, Nazish, additional, Ahmed, Shariq, additional, Shah, Nehal M., additional, Ghosh, Soumitra, additional, Ray, Yogiraj, additional, Hazra, Avijit, additional, Talukdar, Arunansu, additional, Dulhani, Naveen, additional, Kikon, Nyanthung, additional, Mukherjee, Subhasis, additional, Mallick, Susenjit, additional, Patnaik, Lipilekha, additional, Bhandari, Sudhir, additional, Agrawal, Abhishek, additional, Vohra, Rajaat, additional, Sharma, Nikita, additional, Bandaru, Rajiv Kumar, additional, Mirza, Mehdi Ali, additional, Chakravarty, Jaya, additional, Kataria, Sushila, additional, Choudhury, Ratnamala, additional, Chatterji, Soumyadip, additional, and Kumar, M.Pavan, additional

Published
2022
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30. End-of-life care and social security issues among geriatric people attending a tertiary care hospital of Eastern India

Author

Pany, Subraham, Patnaik, Lipilekha, Rao, E., Pattanaik, Sumitra, and Sahu, Trilochan

Subjects
Terminal care -- Methods, Elderly patients -- Care and treatment -- Social aspects, Social security -- Health aspects, Health
Abstract

Byline: Subraham. Pany, Lipilekha. Patnaik, E. Rao, Sumitra. Pattanaik, Trilochan. Sahu Context: The care of sick members is the hallmark of a civilized society. End-of-life care and social security for [...]

Published
2018

37. Effectiveness of Mobile Application for Promotion of Physical Activity Among Newly Diagnosed Patients of Type II Diabetes - A Randomized Controlled Trial.

Author

Patnaik, Lipilekha, Panigrahi, Sandeep Kumar, Sahoo, Abhay Kumar, Mishra, Debahuti, Muduli, Anil Kumar, and Beura, Saswatika

Subjects
*TYPE 2 diabetes, *PHYSICAL activity, *RANDOMIZED controlled trials, *MOBILE apps, *METABOLIC equivalent
Abstract

Background: Mobile health intervention shows the positive effects on the management of chronic diseases. Therefore, the study was planned to study the effectiveness of a mobile-based application promotion of physical activity among newly diagnosed patients with type II diabetes. Methods: The present study was a parallel-design randomized controlled trial conducted over 2 years. The participants were type II diabetes patients between 18 and 60 years within 3 months of diagnosis who attended the endocrinology outpatient department having knowledge of using smart phone. The sample size was calculated to be 66 and 33 for each arm. The block random design method was adopted for allocation into different arms. A pretested interview schedule was used for the collection of data. Outcomes included body mass index, waist circumference, body fat percentage, and changes in the physical activity was obtained by global physical activity questionnaire (GPAQ). The information thus collected were processed and analyzed using SPSS v 20. Results: The study included 66 patients aged between 18 and 60 years, out of which 33 were enrolled into control and 33 into intervention group. The mean age of the participants was 42.29 ± 9.5 years ranged from 25 years to 59 years, 65.2% were males and 34.8% were females. It was observed that a higher proportion of intervention participants met WHO recommendations of physical activity level. Total metabolic equivalent of task (MET) value per minute (Mean ± SD) was 1347.27 ± 1028.5 in the control group and 1223.03 ± 584.87 in intervention group at baseline and was not different (P = 0.538). The total MET value per minute was found to be higher among the intervention group in all follow-ups. There was a significant decrease in weight, BMI, waist circumference, hip circumference, body fat percentage, and systolic blood pressure (SBP) in the intervention group. Conclusions: Cost-effective, simple mobile applications may help in routine clinical practice to encourage the patients for the promotion of physical activity. [ABSTRACT FROM AUTHOR]

Published
2022
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45. Out-of-pocket expenditure and its predictors for illness of under-five children: A cross-sectional study in urban slums of Eastern India.

Author

Mohanty, Parimala, Satpathy, Sudhir, Patnaik, Sibabratta, and Patnaik, Lipilekha

Subjects
SLUMS, CROSS-sectional method, URBAN studies, MEDICAL fees, GENDER, MEDICAL care costs
Abstract

Introduction: Out-of-pocket (OOP) expenditure influences the access to the healthcare of the marginalized and vulnerable population including under-five children (U5C). The aim of the study is to estimate the OOP expenditure and its predictors in Bhubaneswar, a region of eastern India. Methods: A cross-sectional study was conducted using a semi-structured interview schedule in 20 urban slums of Bhubaneswar. The survey was carried out by using the National Sample Survey Office (NSSO) health consumption schedule 25.0 in which mothers of U5C with illness (n = 530) were interviewed. For data analysis, the nonparametric Wilcoxon rank-sum test and Kruskal–Wallis test were used as tests of significance. Results: The study revealed that the mean OOP expenditure for outpatient department (OPD) care was ₹375.9 (₹219.48). The mean approximated expenditure was ₹1669.8 (₹1131.9) for inpatient department (IPD) care. In OPD care, doctors' fee and medicine cost constituted 65.01% and 50.46% of OOP expenditure, respectively. In IPD care, medicine cost and doctors' fee contributed to 36.62% and 30.54% of OOP expenditure, respectively. The major significant predictors that contributed to increased OOP were gender and delay in approaching the source of treatment in OPD, whereas in IPD no such predictors were observed. Conclusions: This study prominently sheds light on the issue of accessibility and affordability of health services without a comprehensive health insurance scheme for U5C illness among the vulnerable urban slum dwellers to achieve universal health coverage. [ABSTRACT FROM AUTHOR]

Published
2021
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46. Awareness of the warning symptoms and risk factors of stroke among adults seeking health care from a rural hospital of India

Author

Patnaik, Lipilekha, Sahoo, Himanshu, and Sahu, Trilochan

Subjects
Precision medicine -- Research, Medical research, Stroke -- Care and treatment, Health promotion -- Methods, Public health administration -- Methods, Health
Abstract

Byline: Lipilekha. Patnaik, Himanshu. Sahoo, Trilochan. Sahu Sir, Stroke is a major disabling health problem in developing countries like India. Stroke burden in India has been rising in the last [...]

Published
2015

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