Past research in the MRC LEU has shown strong associations between patterns of post-natal growth and the risk of developing cardiovascular disease, hypertension and type 2 diabetes in later life. In India, we have studied this mainly in the New Delhi Birth Cohort (add link to New Delhi Birth Cohort) and Vellore Birth Cohort (add link to Vellore Birth Cohort). Both of these prospective cohorts have weight and height data collected longitudinally from birth to adolescence/adulthood.

In both cohorts, type 2 diabetes in adult life was associated with low weight or body mass index at birth and during infancy but with rapid BMI gain in mid-childhood and adolescence (Figure).

This pattern of small size at birth and/or infancy, followed by rapid weight or BMI gain, is consistently associated with higher cardiometabolic risk in many cohorts around the world. We do not know the reason, but it may be that early life under-nutrition (in fetal life and infancy) impairs the development of key metabolic tissues (such as skeletal muscle, the liver, and pancreas) which leaves an individual unable to maintain metabolic homeostasis in later life when metabolic systems are stressed by excess adiposity (body fat).

The men and women in the New Delhi and Vellore cohorts are now aged 45-50 years, and are currently taking part in a study of early life growth as a predictor of mid-life cardiac structure and function (INDECHO study). It aims to answer the following questions:

  • How do left ventricular (LV) mass and LV function relate to current and earlier cardiometabolic risk markers, lifestyle and socio-economic circumstances?
  • Are lower birth weight-for-gestational age, lower infant weight and greater BMI gain during childhood/adolescence associated with higher LV mass and poorer LV function?
  • Does growth in early life modify the associations of adult cardio-metabolic risk factors and lifestyle with LV structure and function?

Left ventricular dimensions and systolic and diastolic function are being assessed using transthoracic echocardiography. M-mode and 2-D echocardiography in parasternal long axis, mid-papillary short axis and apical 2- and 4-chamber views are used to measure/derive inter-ventricular septal thickness, posterior wall thickness, LV internal dimensions in systole and diastole, relative wall thickness, LV mass, atrial and ventricular volumes, ejection fraction, fractional shortening and regional wall motion. Pulsed-wave and tissue Doppler are used to measure mitral inflow parameters and septal and lateral mitral annular velocities in early and late diastole, and pulmonary venous flow. We are also measuring carotid intima media thickness (cIMT) and assessing ECG and clinical evidence of coronary heart disease.

Conditional growth modelling

In recent studies, we have used conditional growth variables to examine associations between growth during particular age windows in early life and later health outcomes. Within an individual, different body measurements at a given age, and the same body measurement at different ages, are strongly correlated. This makes it difficult to assess the relationship of the growth of specific tissues during specific age periods to later outcomes. Conditional growth analysis, in which standardised residuals are derived from regressing current size on all prior size measurements, is one way of overcoming this. It has been most commonly applied to single body measurements such as Z-standardised weight or height (Figure (a)).

Figure legend: Each pyramid shows the calculation of a set of conditional variables, based on body size data at birth (0), 1 year, 2 years, 5 years, 11 years and 20 years; a) shows the use of a single measurement eg weight or height; b) shows two measurements combined (weight and height); and c) shows three measurements combined (height, skinfolds and weight). Within each pyramid, each row shows the calculation of one conditional variable, from length at birth at the top to (at the base) 20 year conditional weight or height (a), conditional relative weight (b) or conditional lean gain (c). These variables are measures of the residuals from regression models in which the measure to the left of the vertical bar is the outcome, and measures to the right of the vertical bar are the predictors. (a): In the first method, current weight or height is conditioned respectively on all previous measurements of the same type. (b): In the second method ‘linear growth’ is current height conditioned on all previous height and weight measurements; ‘relative weight gain’ is current weight conditioned on current height and all previous weight and height measures. (c): In the three variable version, ‘linear growth’ is current height conditioned on all previous height, skinfold and weight measurements; ‘fat gain’ is current skinfold thickness conditioned on current height and all previous height, skinfold and weight measures; ‘lean tissue gain’ is current weight conditioned on current height and skinfolds, and all previous height, skinfold and weight measures. H: height/length; SS: sum of skinfold thickness; W: weight

The conditional variables measure the difference between the size attained and that expected from the child’s earlier size measurements and selected current measurements, using data from the whole population or cohort being studied. A positive value indicates greater (or faster) than expected growth, and a negative value indicates less (or slower) growth than expected. An advantage of this method is that, by construction, the conditional variables at all ages for any individual are uncorrelated with each other, and can be included together in a regression model. A disadvantage is that conditional variables can only be used for those who have valid measurements at every age chosen.

We have developed the method further by combining two measurements (weight and height, Figure (b)) in order to derive measures that represent weight independent of height (conditional relative weight) and height independent of weight (linear growth). In this case, conditional height is current height accounting for all prior height and weight measures but not current weight, and weight gain independent of linear growth is current weight accounting for current height and all prior weight and height measures. We have also combined three measurements (eg. height, sum of skinfold thickness and weight) in order to create variables that represent fat gain, skeletal or linear gain and lean gain (Figure (c)). Conditional length/height (representing ‘linear growth’) is current length/height accounting for all prior length/height, skinfold and weight measurements but not current skinfolds and weight; conditional fat (representing ‘fat gain’) is current skinfold thickness accounting for all prior length/height, skinfolds and weight, and current height but not current weight; and conditional lean (representing ‘lean tissue gain’) is current weight accounting for all prior length/height, skinfolds and weight and current height and skinfolds.

Selected recent publications related to growth:

  • Osmond C, Fall CHD. Conditional Growth Models: An Exposition and Some Extensions. Chapter 11 p275-300 in Handbook of Statistics 37; Disease modelling and public health, Part B. Eds.: Srinivasa Rao ASR, Pyne S, Rao CR. North Holland/Elsevier, Amsterdam, Netherlands, 2017.
  • Adair LS, Fall CHD, Osmond C, Stein AD, Martorell R, Ramirez-Zea M, Sachdev HPS, Dahly DL, Bas I, Norris S, Micklesfield L, Hallal P, Victora C and the COHORTS group. 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: 525-34. PMID: 23541370
  • Krishnaveni GV, Veena SR, Srinivasan K, Osmond C, Fall CHD. Linear growth and fat and lean tissue gain during childhood: associations with cardiometabolic and cognitive outcomes in adolescent Indian children. PLoS One 2015; 10: e0143231. PMID: 26575994.
  • De Beer M, Vrijkotte GM, Fall CHD, van Eijsden M, Osmond C, Gemke RJBJ. Associations of Infant Feeding and Timing of Weight Gain and Linear Growth During Early Life with Childhood Blood Pressure: Findings from a Prospective Population Based Cohort Study. PLoS One 2016 11; e0166281. PMID: 27832113.
  • Vasan SK, Roy A, Samuel VT, Antonisamy B, Bhargava SK, Alex AG, Singh B, Osmond C, Geethanjali FS, Karpe F, Sachdev HPS, Agrawal K, Ramakrishnan L, Tandon N, Thomas NJ, Premkumar PS, Asaithambi P, Princy SFX, Sinha S, Paul TV, Prabhakaran D, Fall CHD. IndEcho study: Cohort study investigating birth size, childhood growth and young adult cardiovascular risk factors as predictors of mid-life myocardial structure and function in South Asians. BMJ Open 2018:8:e019675. doi:10.1136/bmjopen-2017-019675. PMID: 29643156
  • Antonisamy B, Vasan SK, Geethanjali FS, Gowri S, Hepsy FS, Richard J, Raghupathy P, Karpe F, Osmond C, Fall CHD. Weight gain and height growth during infancy, childhood, and adolescence as predictors of adult cardiovascular risk. J Pediatr 2017; 180: 53-61. PMID: 27823768.
  • Fall CHD, Victora C, Eriksson JG, Osmond C. Disentangling the contributions of childhood and adult weight to cardiovascular disease risk. Commentary on a historical reprint for IJE on: Abraham S, Collins G, Nordsieck M. Relationship of childhood weight status to morbidity in adults. HSMHA Health Reports 1971; 86: 273-84. Int J Epidemiol 2016; 45: 1031-6. PMID: 27498298