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Bandyopadhyay S, Puttaswamy D, Gabriel MP, J J, Finkelstein JL, Selvam S, Kurpad AV, Kuriyan R. Estimation of Hydration and Density of Fat-Free Mass in Indian Children Using a 4-Compartment Model: Implications for the Estimation of Body Composition Using 2-Compartment Models. J Nutr 2023; 153:435-442. [PMID: 36894236 DOI: 10.1016/j.tjnut.2022.12.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Revised: 12/20/2022] [Accepted: 12/23/2022] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND Accurate methods are needed to measure body fat mass (FM), particularly in South Asian children who are thought to have greater adiposity for a given body size. The accuracy of simple 2-compartment (2C) models of measuring FM depends on the primary measurement of the fat free mass (FFM) and the validity of assumed constants for FFM hydration and density. These have not been measured in this particular ethnic group. OBJECTIVES To measure FFM hydration and density in South Indian children using a 4-compartment (4C) model and to compare FM estimates from this 4C-model with 2C-model-based estimates from hydrometry and densitometry, using literature-reported FFM hydration and density in children. METHODS This study included 299 children (45% boys), aged 6-16 y from Bengaluru, India. Total body water (TBW), bone mineral content (BMC), and body volume were measured using deuterium dilution, dual-energy X-ray absorptiometry, and air displacement plethysmography, respectively, to calculate the FFM hydration and density, and the FM using 4C and 2C models. The agreement between FM estimates from 2C and 4C models was also evaluated. RESULTS Mean FFM hydration and density were 74.2% ± 2.1% and 71.4% ± 2.0% and 1.095 ± 0.008 kg/L and 1.105 ± 0.008 kg/L in boys and girls respectively, which were significantly different from published values. Using the presently estimated constants, the mean hydrometry-based FM (as % body weight) estimates decreased by 3.5% but increased by 5.2% for densitometry-based 2C methods. When 2C-FM (using previously reported FFM hydration and density) were compared with 4C-FM estimates, the mean difference was -1.1 ± 0.9 kg for hydrometry and 1.6 ± 1.1 kg for densitometry. CONCLUSIONS Previously published constants of hydration and density of FFM may induce errors of -12% to +17% in FM (kg) when using different 2C models in comparison to the 4C models in Indian children. J Nutr 20xx;x:xx.
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Affiliation(s)
- Sulagna Bandyopadhyay
- Division of Nutrition, St. John's Research Institute, St. John's National Academy of Health Sciences, Bengaluru, Karnataka, India
| | - Deepa Puttaswamy
- Division of Nutrition, St. John's Research Institute, St. John's National Academy of Health Sciences, Bengaluru, Karnataka, India
| | - Mamatha Philip Gabriel
- Division of Nutrition, St. John's Research Institute, St. John's National Academy of Health Sciences, Bengaluru, Karnataka, India
| | - Jayakumar J
- Division of Nutrition, St. John's Research Institute, St. John's National Academy of Health Sciences, Bengaluru, Karnataka, India
| | - Julia L Finkelstein
- Division of Nutrition, St. John's Research Institute, St. John's National Academy of Health Sciences, Bengaluru, Karnataka, India; Division of Nutritional Sciences, Cornell University, Ithaca, NY, USA
| | - Sumithra Selvam
- Division of Epidemiology and Biostatistics, St. John's Research Institute, St. John's National Academy of Health Sciences, Bengaluru, Karnataka, India
| | - Anura V Kurpad
- Department of Physiology, St. John's Medical College, St. John's National Academy of Health Sciences, Bengaluru, Karnataka, India
| | - Rebecca Kuriyan
- Division of Nutrition, St. John's Research Institute, St. John's National Academy of Health Sciences, Bengaluru, Karnataka, India.
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Singh A, Wall C, Levine A, Midha V, Mahajan R, Sood A. Nutritional screening and assessment in inflammatory bowel disease. Indian J Gastroenterol 2022; 41:5-22. [PMID: 35031977 DOI: 10.1007/s12664-021-01223-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Accepted: 09/24/2021] [Indexed: 02/04/2023]
Abstract
Inflammatory bowel disease (IBD) is associated with increased risk of malnutrition and sarcopenia. Both malnutrition and sarcopenia negatively impact the clinical course, quality of life, response to therapy, and surgical outcomes in patients with IBD. This review article highlights the importance of nutritional assessment in patients with IBD and also discusses the different nutritional screening and assessment tools, and measures to detect sarcopenia in relation to IBD. Identification of malnutrition and sarcopenia will allow prioritization of the corrective actions, such as nutritional rehabilitation, to improve clinical outcomes. An approach to the evaluation of nutritional status in patients with IBD is also suggested.
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Affiliation(s)
- Arshdeep Singh
- Department of Gastroenterology, Dayanand Medical College and Hospital, Ludhiana, 141 001, India
| | - Catherine Wall
- Department of Medicine and Department of Human Nutrition, University of Otago, Christchurch, New Zealand
| | - Arie Levine
- Pediatric Gastroenterology and Nutrition Unit, Pediatric IBD Center, Wolfson Medical Center Holon, Tel Aviv University, Tel Aviv, Israel
| | - Vandana Midha
- Department of Internal Medicine, Dayanand Medical College, Ludhiana, 141 001, India
| | - Ramit Mahajan
- Department of Gastroenterology, Dayanand Medical College and Hospital, Ludhiana, 141 001, India
| | - Ajit Sood
- Department of Gastroenterology, Dayanand Medical College and Hospital, Ludhiana, 141 001, India.
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Amaral MA, Mundstock E, Scarpatto CH, Cañon-Montañez W, Mattiello R. Reference percentiles for bioimpedance body composition parameters of healthy individuals: A cross-sectional study. Clinics (Sao Paulo) 2022; 77:100078. [PMID: 36087566 PMCID: PMC9464854 DOI: 10.1016/j.clinsp.2022.100078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Revised: 05/30/2022] [Accepted: 06/21/2022] [Indexed: 11/29/2022] Open
Abstract
OBJECTIVES The aim of this study was to estimate the percentage distribution of body composition parameters for healthy people at different ages from the assessment of electrical bioimpedance. METHODS A cross-sectional study of healthy Brazilian aged 5 years and older. Were evaluated: total body fat; percent body fat; fat-free mass; percent lean mass; fat mass index; and fat-free mass index. RESULTS Of 1240 participants, with a median age of 27.0 years, 52.5% were female, and 73.7% were Caucasian. Most of the body composition variables were associated with age. The fat-free mass increased from youth to adult and decreased in the elderly in both sexes, with higher values in males than in females. In males, the percentage of lean mass has higher values in adolescence compared to childhood, and in adults compared to the elderly, when analyzed from the 50th percentile. In women, fat-free mass compared to adulthood, values were higher in childhood and lower in older ages. CONCLUSIONS The study is the first to describe the Brazilian reference values for most clinical parameters of bioimpedance in percentiles stratified by different life cycles and sex. These findings can be very useful in clinical practice for health promotion and monitoring the nutritional status of the individual.
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Affiliation(s)
- Marina Azambuja Amaral
- Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre, RS, Brazil; Centro Universitário Ritter dos Reis (UniRitter), Porto Alegre, RS, Brazil
| | - Eduardo Mundstock
- Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre, RS, Brazil; Secretaria da Educação, Esporte e Lazer de Canela, Canela, RS, Brazil
| | - Camila H Scarpatto
- Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | | | - Rita Mattiello
- Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre, RS, Brazil; Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil.
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Intraindividual double-burden of anthropometric undernutrition and "metabolic obesity" in Indian children: a paradox that needs action. Eur J Clin Nutr 2021; 75:1205-1217. [PMID: 33893450 PMCID: PMC7612996 DOI: 10.1038/s41430-021-00916-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2020] [Revised: 03/04/2021] [Accepted: 03/29/2021] [Indexed: 12/16/2022]
Abstract
Background Intraindividual coexistence of anthropometrically defined undernutrition and “metabolic obesity”, characterised by presence of at least one abnormal cardiometabolic risk factor, is rarely investigated in young children and adolescents, particularly in Low-and-Middle-Income-Countries undergoing rapid nutrition transition. Methods Prevalence of biomarkers of metabolic obesity was related to anthropometric and socio-demographic characteristics in 5-19 years old participants from the population-based Comprehensive National Nutrition Survey in India (2016-2018). The biomarkers, serum lipid-profile (total cholesterol (TC), low density lipoprotein (LDL), high density lipoprotein (HDL) and triglycerides), fasting glucose, and glycosylated hemoglobin (HbA1C), and all jointly were analysed in 22567, 23192, 25962 and 19143 participants, respectively. Results Overall (entire dataset), the prevalence of abnormalities was low (4.3-4.5%) for LDL and TC, intermediate for dysglycemia (10.9-16.1%), and high for HDL and triglycerides (21.725.8%). Proportions with ≥1 abnormal metabolic obesity biomarker(s) were 56.2% overall, 54.2% in thin (BMI-for-age <-2SD) and 59.3% in stunted (height-for-age <-2SD) participants. Comparable prevalence was evident in mild undernutrition (-1 to -2 SD). Clustering of two borderline abnormalities occurred in one-third, warranting active life-style interventions. Metabolic obesity prevalence increased with BMI-for-age. Among those with metabolic obesity, only 9% were overweight/obese (>1SD BMI-for-age). Among poor participants, triglyceride, glucose and HDL abnormalities were higher. Conclusions A paradoxical, counter-intuitive prevalence of metabolic obesity biomarker(s) exists in over half of anthropometrically undernourished and normal-weight Indian children and adolescents. There is a crucial need for commensurate investments to address overnutrition along with undernutrition. Nutritional status should be characterized through additional reliable biomarkers, instead of anthropometry alone.
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Sharma E, Jacob P, Murthy P, Jain S, Varghese M, Jayarajan D, Kumar K, Benegal V, Vaidya N, Zhang Y, Desrivieres S, Schumann G, Iyengar U, Holla B, Purushottam M, Chakrabarti A, Fernandes GS, Heron J, Hickman M, Kartik K, Kalyanram K, Rangaswamy M, Bharath RD, Barker G, Orfanos DP, Ahuja C, Thennarasu K, Basu D, Subodh BN, Kuriyan R, Kurpad SS, Kumaran K, Krishnaveni G, Krishna M, Singh RL, Singh LR, Toledano M. Consortium on Vulnerability to Externalizing Disorders and Addictions (cVEDA): A developmental cohort study protocol. BMC Psychiatry 2020; 20:2. [PMID: 31898525 PMCID: PMC6941284 DOI: 10.1186/s12888-019-2373-3] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Accepted: 11/26/2019] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Low and middle-income countries like India with a large youth population experience a different environment from that of high-income countries. The Consortium on Vulnerability to Externalizing Disorders and Addictions (cVEDA), based in India, aims to examine environmental influences on genomic variations, neurodevelopmental trajectories and vulnerability to psychopathology, with a focus on externalizing disorders. METHODS cVEDA is a longitudinal cohort study, with planned missingness design for yearly follow-up. Participants have been recruited from multi-site tertiary care mental health settings, local communities, schools and colleges. 10,000 individuals between 6 and 23 years of age, of all genders, representing five geographically, ethnically, and socio-culturally distinct regions in India, and exposures to variations in early life adversity (psychosocial, nutritional, toxic exposures, slum-habitats, socio-political conflicts, urban/rural living, mental illness in the family) have been assessed using age-appropriate instruments to capture socio-demographic information, temperament, environmental exposures, parenting, psychiatric morbidity, and neuropsychological functioning. Blood/saliva and urine samples have been collected for genetic, epigenetic and toxicological (heavy metals, volatile organic compounds) studies. Structural (T1, T2, DTI) and functional (resting state fMRI) MRI brain scans have been performed on approximately 15% of the individuals. All data and biological samples are maintained in a databank and biobank, respectively. DISCUSSION The cVEDA has established the largest neurodevelopmental database in India, comparable to global datasets, with detailed environmental characterization. This should permit identification of environmental and genetic vulnerabilities to psychopathology within a developmental framework. Neuroimaging and neuropsychological data from this study are already yielding insights on brain growth and maturation patterns.
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Affiliation(s)
- Eesha Sharma
- Department of Child and Adolescent Psychiatry, National Institute of Mental Health and Neuro-Sciences (NIMHANS), Bangalore, Karnataka India
| | - Preeti Jacob
- Department of Child and Adolescent Psychiatry, National Institute of Mental Health and Neuro-Sciences (NIMHANS), Bangalore, Karnataka India
| | - Pratima Murthy
- Department of Psychiatry, National Institute of Mental Health and Neuro-Sciences (NIMHANS), Bangalore, Karnataka India
| | - Sanjeev Jain
- Department of Psychiatry, National Institute of Mental Health and Neuro-Sciences (NIMHANS), Bangalore, Karnataka India
| | - Mathew Varghese
- Department of Psychiatry, National Institute of Mental Health and Neuro-Sciences (NIMHANS), Bangalore, Karnataka India
| | - Deepak Jayarajan
- Department of Psychiatry, National Institute of Mental Health and Neuro-Sciences (NIMHANS), Bangalore, Karnataka India
| | - Keshav Kumar
- Department of Child and Adolescent Psychiatry, National Institute of Mental Health and Neuro-Sciences (NIMHANS), Bangalore, Karnataka India
| | - Vivek Benegal
- Department of Psychiatry, National Institute of Mental Health and Neuro-Sciences (NIMHANS), Bangalore, Karnataka India
| | - Nilakshi Vaidya
- Centre for Population Neuroscience and Precision Medicine, Institute of Psychology, Psychiatry & Neuroscience, MRC SGDP Centre, King’s College London, London, UK
| | - Yuning Zhang
- Centre for Population Neuroscience and Precision Medicine, Institute of Psychology, Psychiatry & Neuroscience, MRC SGDP Centre, King’s College London, London, UK
| | - Sylvane Desrivieres
- Centre for Population Neuroscience and Precision Medicine, Institute of Psychology, Psychiatry & Neuroscience, MRC SGDP Centre, King’s College London, London, UK
| | - Gunter Schumann
- Centre for Population Neuroscience and Precision Medicine, Institute of Psychology, Psychiatry & Neuroscience, MRC SGDP Centre, King’s College London, London, UK
| | - Udita Iyengar
- Department of Child & Adolescent Psychiatry, Institute of Psychology, Psychiatry & Neuroscience, King’s College London, London, UK
| | - Bharath Holla
- Department of Psychiatry, National Institute of Mental Health and Neuro-Sciences (NIMHANS), Bangalore, Karnataka India
| | - Meera Purushottam
- Molecular Genetics Laboratory, National Institute of Mental Health and Neuro-Sciences (NIMHANS), Bangalore, Karnataka India
| | - Amit Chakrabarti
- Regional Occupational Health Centre (ROHC), Eastern, ICMR-National Institute of Occupational Health (NIOH), Kolkata, West Bengal India
| | - Gwen Sascha Fernandes
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Jon Heron
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Matthew Hickman
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Kamakshi Kartik
- Rishi Valley Rural Health Centre, Madanapalle, Chittoor, Andhra Pradesh India
| | - Kartik Kalyanram
- Rishi Valley Rural Health Centre, Madanapalle, Chittoor, Andhra Pradesh India
| | | | - Rose Dawn Bharath
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neuro-Sciences (NIMHANS), Bangalore, Karnataka India
| | - Gareth Barker
- Department of Neuroimaging, Institute of Psychology, Psychiatry & Neuroscience, King’s College London, London, UK
| | | | - Chirag Ahuja
- Department of Radiodiagnosis and Imaging, Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh, India
| | - Kandavel Thennarasu
- Department of Biostatistics, National Institute of Mental Health and Neuro-Sciences (NIMHANS), Bangalore, Karnataka India
| | - Debashish Basu
- Department of Psychiatry, Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh, India
| | - B. N. Subodh
- Department of Psychiatry, Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh, India
| | - Rebecca Kuriyan
- Division of Nutrition, St John’s Research Institute, Bengaluru, India
| | - Sunita Simon Kurpad
- Department of Psychiatry and Department of Medical Ethics, St. John’s Medical College and Hospital, Bengaluru, India
| | | | - Ghattu Krishnaveni
- Epidemiology Research Unit, CSI Holdsworth Memorial Hospital, Mysore, India
| | - Murali Krishna
- Foundation for Research and Advocacy in Mental Health, Mysore, India
| | - Rajkumar Lenin Singh
- Department of Psychiatry, Regional Institute of Medical Sciences (RIMS), Imphal, Manipur India
| | - L. Roshan Singh
- Department of Clinical Psychology, Regional Institute of Medical Sciences (RIMS), Imphal, Manipur India
| | - Mireille Toledano
- Faculty of Medicine, School of Public Health, Imperial College, London, UK
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