Hostname: page-component-8448b6f56d-qsmjn Total loading time: 0 Render date: 2024-04-19T08:50:48.378Z Has data issue: false hasContentIssue false
  • English
  • Français

Birth weight, childhood and adolescent growth and diabetes risk factors in 21-year-old Asian Indians: the Pune Children’s Study

Published online by Cambridge University Press:  05 August 2020

Kalyanaraman Kumaran Open the ORCID record for Kalyanaraman Kumaran [Opens in a new window] ,
Himangi Lubree ,
Dattatray S. Bhat ,
Suyog Joshi ,
Charudatta Joglekar ,
Pallavi Yajnik ,
Sheila Bhave ,
Anand Pandit ,
Caroline H.D. Fall  and
Chittaranjan S Yajnik
Kalyanaraman Kumaran
Affiliation:
MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK Epidemiology Research Unit, Holdsworth Memorial Hospital, Mysore, India
Himangi Lubree
Affiliation:
Vadu Rural Health Program, KEM Hospital Research Centre, Pune, India
Dattatray S. Bhat
Affiliation:
Diabetes Unit, KEM Hospital Research Centre, Pune, India
Suyog Joshi
Affiliation:
Diabetes Unit, KEM Hospital Research Centre, Pune, India
Charudatta Joglekar
Affiliation:
Regional Centre for Adolescent Health and Nutrition, BKL Walawalkar Hospital and Rural Medical College, Dervan, India
Pallavi Yajnik
Affiliation:
Diabetes Unit, KEM Hospital Research Centre, Pune, India
Sheila Bhave
Affiliation:
Department of Pediatrics, KEM Hospital Research Centre, Pune, India
Anand Pandit
Affiliation:
Department of Pediatrics, KEM Hospital Research Centre, Pune, India
Caroline H.D. Fall
Affiliation:
MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
Chittaranjan S Yajnik*
Affiliation:
Diabetes Unit, KEM Hospital Research Centre, Pune, India
*
Address for correspondence: Chittaranjan S. Yajnik, Diabetes Unit, KEM Hospital Research Centre, Sardar Moodliar Road, Rasta Peth, Pune411011, India. Emails: diabetes@kemdiabetes.org; csyajnik@gmail.com
Get access Rights & Permissions [Opens in a new window]

Abstract

Our objective was to investigate associations of body size (birth weight and body mass index (BMI)) and growth in height, body fat (adiposity) and lean mass during childhood and adolescence, with risk markers for diabetes in young South Asian adults. We studied 357 men and women aged 21 years from the Pune Children’s Study birth cohort. Exposures were 1) birth weight, 21-year BMI, both of these mutually adjusted, and their interaction, and 2) uncorrelated conditional measures of growth in height and proxies for gain in adiposity and lean mass from birth to 8 years (childhood) and 8 to 21 years (adolescence) constructed from birth weight, and weight, height, and skinfolds at 8 and 21 years. Outcomes were plasma glucose and insulin concentrations during an oral glucose tolerance test and derived indices of insulin resistance and secretion. Higher 21-year BMI was associated with higher glucose and insulin concentrations and insulin resistance, and lower disposition index. After adjusting for 21-year BMI, higher birth weight was associated with lower 120-min glucose and insulin resistance, and higher disposition index. In the growth analysis, greater adiposity gain during childhood and adolescence was associated with higher glucose, insulin and insulin resistance, and lower disposition index, with stronger effects from adolescent gain. Greater childhood lean gain and adolescent height gain were associated with lower 120-min glucose and insulin. Consistent with other studies, lower birth weight and higher childhood weight gain increases diabetes risk. Disaggregation of weight gain showed that greater child/adolescent adiposity gain and lower lean and height gain may increase risk.

Keywords

Birth weightchild/adolescent body compositionglucose–insulin metabolismdiabetes riskIndia
Type
Original Article
Information
Journal of Developmental Origins of Health and Disease , Volume 12 , Issue 3 , June 2021 , pp. 474 - 483
Check for updates
Copyright
© Cambridge University Press and the International Society for Developmental Origins of Health and Disease 2020

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

†

KK and HL joint first authors

‡

CHDF and CSY joint senior authors

References

Gaziano, TA, Bitton, A, Anand, S, Abrahams-Gessel, S, Murphy, A. Growing epidemic of coronary heart disease in low- and middle-income countries. Curr Probl Cardiol. 2010; 35, 72–115.CrossRefGoogle ScholarPubMed
GBD 2015 Mortality and Causes of Death Collaborators. Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980-2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2016; 388, 1459–1544.CrossRefGoogle Scholar
International Diabetes Federation. IDF Diabetes Atlas, 7th edn., 2015. International Diabetes Federation, Brussels, Belgium. http://www.idf.org/diabetesatlas.Google Scholar
Wild, S, Roglic, G, Green, A, Sicre, R, King, H. Global prevalence of diabetes. Estimates for the year 2000 and projections for 2030. Diabetes Care. 2004; 27, 1047–1053.CrossRefGoogle ScholarPubMed
Hales, CN, Barker, DJP. Type 2 (non-insulin-dependant) diabetes mellitus: the thrifty phenotype hypothesis. Diabetologia. 1992; 35, 595–601.CrossRefGoogle Scholar
Yajnik, CS. Early life origins of insulin resistance and type 2 diabetes in India and other Asian countries. J Nutr. 2004; 134, 205–210.10.1093/jn/134.1.205CrossRefGoogle ScholarPubMed
Bavdekar, A, Yajnik, CS, Fall, CHD, et al. Insulin resistance syndrome in 8-year-old Indian children: small at birth, big at 8 years, or both? Diabetes. 1999; 48, 2422–2429.CrossRefGoogle Scholar
Phillips, DIW, Barker, DJP, Hales, CN, Hirst, S, Osmond, C. Thinness at birth and insulin resistance in adult life. Diabetologia. 1994; 37, 150–154.CrossRefGoogle ScholarPubMed
Whincup, PF, Cook, DG, Adshead, F, et al. Childhood size is more strongly related than size at birth to glucose and insulin levels in 10–11 year-old children. Diabetologia. 1997; 40, 319–326.10.1007/s001250050681CrossRefGoogle ScholarPubMed
Ong, KK, Petry, CJ, Emmett, PM, et al.; ALSPAC study team. Insulin sensitivity and secretion in normal children related to size at birth, postnatal growth, and plasma insulin-like growth factor-I levels. Diabetologia. 2004; 47, 1064–1070.CrossRefGoogle ScholarPubMed
Bhargava, SK, Sachdev, HPS, Fall, CHD, et al. Relation of serial changes in childhood body mass index to impaired glucose tolerance in young adulthood. New England J Med. 2004; 350, 865–875.CrossRefGoogle ScholarPubMed
Eriksson, JG, Forsen, T, Tuomilheto, J, Jaddoe, VWV, Osmond, C, Barker, DJP. Effect of size at birth and childhood growth on the insulin resistance syndrome in elderly individuals. Diabetologia. 2002; 45, 342–348.CrossRefGoogle Scholar
Definition, Diagnosis and Classification of Diabetes Mellitus and its Complications Report of a WHO Consultation. Part 1: Diagnosis and Classification of Diabetes Mellitus, 1999. World Health Organization, Geneva.Google Scholar
International Institute for Population Sciences and Macro International. National Family Health Survey (NFHS-3), India 2005-06, 2007. IIPS, Mumbai.Google Scholar
The Oxford Centre for Diabetes, Endocrinology and Metabolism, Diabetes Trials Unit. HOMA calculator. Available from http://www.dtu.ox.ac.uk, accessed 15 July 2015.Google Scholar
Wareham, NJ, Phillips, DI, Byrne, CD, Hales, CN. The 30 minute insulin incremental response in an oral glucose tolerance test as a measure of insulin secretion. Diabet Med. 1995; 12, 931.CrossRefGoogle Scholar
DeFronzo, RA, Matsuda, M. Reduced time points to calculate the composite index. Diabetes Care. 2010; 33, e93.CrossRefGoogle ScholarPubMed
Bergman, RN, Phillips, LS, Cobelli, C. Physiologic evaluation of factors controlling glucose tolerance in man. Measurement of insulin sensitivity and β-cell glucose sensitivity from the response to intravenous glucose. J Clin Invest. 1981; 68, 1456–1467.CrossRefGoogle ScholarPubMed
BMI classification. World Health Organization. Global database on body mass index. Available from http://www.who.int/bmi, accessed 01 August 2015.Google Scholar
World Health Organization. Physical status: the use and interpretation of anthropometry. Report of a WHO Expert Committee. World Health Organ Tech Rep Ser. 1995; 854, 1–452.Google Scholar
American Diabetes Association. Standards of medical care in diabetes—2014. Diabetes Care. 2014; 37, S14–S80.CrossRefGoogle Scholar
Lucas, A, Fewtrell, MS, Cole, TJ. Fetal origins of adult disease-the hypothesis revisited. BMJ. 1999; 319, 245–249.CrossRefGoogle ScholarPubMed
Adair, LS, Fall, CHD, Osmond, C, et al. Associations of linear growth and relative weight gain during early life with adult health and human capital in countries of low and middle income: findings from five birth cohort studies. Lancet. 2013; 382, 525–534.CrossRefGoogle ScholarPubMed
Osmond, C, Fall, CHD. Conditional Growth Models: An Exposition and Some Extensions. In Handbook of Statistics 37; Disease modelling and public health, Part B. (eds. Srinivasa Rao, ASR, Pyne, S, Rao, CR), 2017; Chapter 11, pp. 275–300. North Holland/Elsevier, Amsterdam, Netherlands.CrossRefGoogle Scholar
Krishnaveni, GV, Veena, SR, Srinivasan, K, Osmond, C, Fall, CHD. Linear growth and fat and lean tissue gain in childhood: associations with cardiometabolic and cognitive outcomes in adolescent Indian children. PLoS One. 2015; 10, e0143231.CrossRefGoogle ScholarPubMed
Eriksson, JG. Early growth, and coronary heart disease and type 2 diabetes: experiences from the Helsinki Birth Cohort Studies. Int J Obes. 2006; 30, S18–S22.CrossRefGoogle ScholarPubMed
Norris, SA, Osmond, C, Gigante, D, et al. Size at birth, weight gain in infancy and childhood, and adult diabetes risk in five low- or middle-income country birth cohorts. Diabetes Care. 2012; 35, 72–79.CrossRefGoogle ScholarPubMed
Warner, MJ, Ozanne, SE. Mechanisms involved in the developmental programming of adult diseae. Biochemistry J. 2010; 427, 333–347.CrossRefGoogle Scholar
Yajnik, CS, Fall, CHD, Coyaji, KJ, et al. Neonatal anthropometry: the thin-fat Indian baby; the Pune Maternal Nutrition Study. Int J Obesity. 2003; 27, 173–180.CrossRefGoogle ScholarPubMed
Wells, JC. The thrifty phenotype: an adaptation in growth or metabolism? Am J Hum Biol. 2011; 23, 65–75.CrossRefGoogle ScholarPubMed
Wells, JC, Pomeroy, E, Walimbe, SR, Popkin, BM, Yajnik, CS. The elevated susceptibility to diabetes in India: an evolutionary perspective. Front Public Health. 2016; 4, 145.CrossRefGoogle Scholar