| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
ORIGINAL RESEARCH COMMUNICATION |
1 From The Medical Research Council, Childhood Nutrition Research Centre, Institute of Child Health, University College London, London, United Kingdom (SC, JCKW, JEW, AL, and MSF), and the Discipline of Paediatrics and Child Health, Children's Nutrition Research Centre, University of Queensland, Royal Children's Hospital, Brisbane, Australia (PSWD)
2 Supported by the Medical Research Council (United Kingdom) and by the Anandamahidol Foundation and Chulalongkorn University Hospital (to SC). 3 Reprints not available. Address correspondence to S Chomtho, MRC Childhood Nutrition Research Centre, Institute of Child Health, 30 Guilford Street, London WC1N 1EH, United Kingdom. E-mail: s.chomtho{at}ich.ucl.ac.uk.
 |
ABSTRACT |
|---|
 TOP ABSTRACT INTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
|---|
Objective: We aimed to investigate associations between weight gain during different periods in infancy and later fat mass (FM) and fat-free mass (FFM).
Design: Body composition was assessed by using the 4-component model, dual-energy X-ray absorptiometry, and anthropometry in 234 healthy UK children and adolescents (105 boys; x ± SD age: 11.4 ± 3.8 y). Early growth measurements were prospective in 52 subjects and retrospective in 182. Relative weight gain was calculated as change in SD score (SDS) during different periods.
Results: Relative weight gain from 0 to 3 mo and from 3 to 6 mo showed positive relations with childhood FM, waist circumference, and trunk FM that were equivalent to increases in FMI (FM/height2) of 0.24 SDS (95% CI: 0.04, 0.44) and 0.50 SDS (0.25, 0.75) per 1-SDS increase in early weight and that were comparable to the effect of current obesity risk factors. Relative weight gain from 0 to 3 mo was also positively associated with later FFMI (FFM/height2). Relative weight gain from 6 to 12 mo was not associated with later body composition. Associations were independent of birth weight, sex, puberty, physical activity, socioeconomic class, ethnicity, and parental body mass index.
Conclusions: In this Western population, greater relative weight gain during early infancy was positively associated with later FM and central fat distribution and with FFM. Rapid weight gain in infancy may be a risk factor for later adiposity. Early infancy may provide an opportunity for interventions aimed at reducing later obesity risk.
|
INTRODUCTION |
|---|
|
TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
|---|
Most of the earlier publications investigating postnatal growth and later outcomes used body mass index (BMI; in kg/m2) or skinfold thickness (SFT) as a proxy for obesity. Stettler et al reported that rapid weight gain during the first 4 mo of life was associated with being overweight (defined by BMI > 95th centile) at age 7 y (9) and that it also predicted the likelihood of developing obesity (defined by BMI) in early adulthood (10). Ong et al (11) reported that infants who gained >0.67 SD in weight SD score (SDS) between birth and 2 y had greater BMI and SFT and larger waist circumference (WC) at 5 y. However, the component of BMI that is affected—fat-free mass (FFM), fat mass (FM), or fat distribution—is not yet known. More recently, a few publications that have attempted to measure FM and FFM separately have reported different associations between postnatal growth and these individual components. However, there has been no study using a reference method such as the 4-component (4C) model to explore associations between early growth and later body composition. Moreover, the critical windows for the effects of postnatal (infancy) weight gain on later obesity remain unclear. Greater weight gain in the first week of life was reported to be associated with a greater risk of overweight in adult life (12). Greater weight gain in the first 2 wk of life was also reported to be linked to insulin resistance and less arterial distensibility in adolescents born preterm (13, 14).
Investigation of the association between more-detailed early growth data and later outcomes is therefore desirable. By using the most accurate body composition techniques currently available, we aimed to examine whether weight gain during different periods in infancy is differentially associated with body composition and fat distribution in a cohort of healthy British children and adolescents.
|
SUBJECTS AND METHODS |
|---|
|
TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
|---|
Birth weight and early growth data were collected from the parents' baby record books, which the families were asked to bring with them on the study day. A total of 234 children had early-growth records available from their records for 
1 time-point at 3, 6, and 12 wk and 6 and 12 mo. Time-points as close as possible to these ages were selected (not more than ±1 wk for the 3- and 6-wk time-points or ±2, ±4, and ±8 wk for the 12-wk and 6- and 12-mo time-points, respectively). These measurements were performed by health professionals, not by the parents. Of the 234 subjects, 52 were part of a cohort that has been followed up prospectively from birth, and their early-growth data at these ages were also recorded prospectively by the research team. Weight SDSs for gestation, sex, and exact age were calculated at different ages by using the British 1990 reference (15).
Written informed consent was obtained from the parents or from subjects >16 y old. Written assent was obtained from subjects 11–16 y old. Oral assent was obtained from all of the younger children. Ethical approval was obtained from the Research Ethics Committee of the Institute of Child Health and Great Ormond Street Hospital.
Measurement of body composition
The 4-component model
The 4C model divides the body into fat, water, protein, and mineral as described previously (16, 17). It minimizes the assumptions made in the 2-component model by directly evaluating several presumed constant relations [eg, hydration, density, and bone mineral content (BMC) of FFM] that are fundamental to the 2-component model. It has been accepted as the most robust technique by which to detect interindividual variability in the composition of FFM, and it also has shown consistent accuracy across a range of body fat (18). The various assumed densities of the 4 components were taken into account in calculating FM from the basic measurements, by using the following equation:
 | (1) |
FFM was then calculated as the difference between body weight and FM. To calculate the 4C model, measurements were obtained by using the following methods.
Air-displacement plethysmography
Whole body air-displacement plethysmography was performed by using the Bodpod body-composition system (Life Measurement Instruments, Concord, CA) while the subject was wearing a tight-fitting swimming costume and a swimming cap. The machine provides raw BV (L) for each subject from the difference between the volumes of air in this chamber, with and without the subject being present. Actual BV was obtained after correction for the thoracic gas volume and surface area artifact by using the appropriate equation to predict, from age, sex, weight, and height in children, as described previously (19). This method is more acceptable and has better precision in children than does hydrodensitometry (20).
Deuterium dilution
TBW was measured by using 2H-labeled water dilution with a dose equivalent to 0.05 g of 2H2O (99.9%) per kg body weight. Saliva samples were obtained before and 4 h after dose by using absorbent saliva-collection materials (salivettes; Sarstedt, Newton, NC) 30 min after the last ingestion of food or drink, stored frozen at –30°C, and then analyzed in duplicate by using the equilibration method (21) and isotope ratio–mass spectrometry (Delta plus XP; Thermofisher Scientific, Bremen, Germany). For calculating TBW, we assumed that the 2H2O dilution space overestimated TBS by a factor of 1.044 (22). Correction was made for dilution of the dose by water intake during the 4-h equilibration period.
Dual-energy X-ray absorptiometry
BMC, FM, and FFM were measured by using a GE Lunar Prodigy whole-body scanner (GE Medical Systems, Madison, WI) in conjunction with ENCORE 2002 software (version 6.80, Prodigy; Lunar Corp, Madison, WI). The instrument automatically alters scan depth depending on the thickness of the subject, as estimated from age, height, and weight. A whole-body scan was performed while the subject was wearing light indoor clothing and had no removable metal objects. The typical scan duration was 5–10 min, depending on subjects' height. The radiation exposure per whole-body scan was estimated to be 2.2 µSv, which is lower than the daily background radiation in the United Kingdom. All scans were performed and analyzed by one operator. The CVs for a Lunar DPX-L instrument (Lunar Corp), which is regarded by the manufacturers to be similar to the Lunar Prodigy, have been reported to be 1.10%, 2.0%, and 1.11% for total-body BMC, FM, and lean mass, respectively (23). Regional measurements (ie, arm, leg, and trunk) were marginally less precise than total-body measurements; the CVs were in the range of 1% to 3%.
Because of the limitations of DXA in measuring soft tissue composition (24, 25), only total-body BMC from DXA was used as a part of the 4C model. However, for regional body composition, DXA is still a practical tool when compared with gold standards such as magnetic resonance imaging and computerized tomography, which are more complicated and expensive, and, in the case of computerized tomography, which involves more radiation exposure. Therefore, DXA-derived trunk and limb composition measures were also used in some analyses.
Anthropometry
Body weight was measured with electronic scales to the nearest 0.01 kg, and height was measured to the nearest 0.1 cm with a wall-mounted stadiometer (Holtain, Dyfed, United Kingdom). BMI (in kg/m2) was calculated. WC was measured to the nearest 0.1 cm at the natural waist site (26) by using a nonstretchable fiberglass insertion tape. All measurements were undertaken by 1 of the 4 trained investigators.
Confounding variables
Factors that might confound the relation between early growth and body composition were assessed by using a structured questionnaire. Pubertal status was self-assessed with the use of pictures of the Tanner stages (27) for pubic hair and breast development (female) or genital development (male) and was coded as prepubertal (Tanner stage 1), early pubertal (Tanner stage 2 or 3), or late pubertal (Tanner stage 4 or 5). A simple parental assessment of subjects' physical activity level relative to their peers was made by using a 5-point scale ranging from "much less active," "less active," "same as peers," "more active," and "much more active." Socioeconomis class was assessed by using the Standard Occupational Classification (28) and classified as class 1 (high), 2, 3, or 4. Ethnicity was coded as white or nonwhite, because, in the present dataset, there were too few subjects for more detailed analyses of the nonwhite group. Reported parental height and weight were used to calculate parental BMI.
Statistical analysis
SDSs were derived for weight, height, and BMI by using the 1990 British reference (15, 29) and calculated by using the lMSGROWTH program (version 2.13; Medical Research Council, London, United Kingdom). WC was converted to SDS by using a nationally representative sample of UK children collected in 1988 (26) and was calculated by using the lMSGROWTH program. One sample t test was used to compare the SDS of the study population with reference data.
We adjusted body-composition variables by height squared to adjust for body size in a way comparable to that for BMI (30). Total and regional FM index (FMI; in FM/height2) and FFM index (FFMI; in FFM/height2) were then calculated. The body- composition variables were converted to age- and sex-specific SDSs by using our own reference database of 449 British subjects aged 4–23 y (204 boys) from an ongoing body-composition reference study (31). The SDSs were calculated by using the LMS method (32) and the lMSCHARTMAKER program (version 2.1; Medical Research Council, UK). This method also allows direct comparison of the effect size of the association between early growth and later FM or FFM because they both are in SDS, which avoids the problem of unequal variance between different body-composition variables.
Changes in weight SDS (
weight SDS) between 2 time-points were calculated by subtracting the earlier weight SDS from the later measurement. The association between early growth and later body composition was explored by using multiple regression models. Body-composition outcomes were regressed on weight SDS with adjustment for birth-weight SDS and other confounders. Alternatively, weight SDSs were divided into quartiles, and the adjusted mean of body-composition outcomes for each weight SDS quartile was analyzed by using general linear models. General linear models were also used to test the interactions between weight SDS and sex or birth-weight SDS in predicting later body composition. All analyses were performed by using SPSS software (version 13; SPSS Inc, Chicago, IL).
|
RESULTS |
|---|
|
TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
|---|
weight SDS did not differ between boys and girls during any period (data not shown).
As expected, weight SDSs for the different periods between birth and 12 mo were strongly correlated with each other, and the 2 nearest measurements showed the highest correlation (data not shown). Lower-birth-weight SDSs were correlated with later upward weight SDSs up to 6 mo of age (Table 1
). The weight SDS from birth to 3 wk was also negatively associated with weight SDS in subsequent periods until 6 mo except for the period of 3–6 wk.
|
weight SDS interaction in any period for predicting later body composition. There was also no significant birth-weight SDS x weight SDS over the 5 periods for predicting later body composition. Therefore, the analyses were performed without separating the sexes or birth-weight categories.
Current body-composition outcomes
Descriptive statistics of the 234 subjects (age range: 4.2–20.4 y) are summarized in Table 2. As has been seen in other contemporary populations, both the boys and girls in the present dataset were heavier and taller and had higher BMIs than did the British 1990 reference children. They also had significantly higher WC (in the form of SDS) than did the reference group.
|
Early growth and later body size and composition
The main analysis was conducted in relation to 3 periods of change in weight SDS in the first year of life (ie, 0–3 mo, 3–6 mo, and 6–12 mo). Regression analyses of later body size and composition on weight SDS during different periods of infancy are shown in Table 3. In the first model (Table 3), after adjustment for birth-weight SDS and sex, weight SDS during the first 6 mo showed a positive association with height SDS in childhood and adolescence. A 1-SDS increase in weight during these respective periods was associated with an increase of 
0.32 to 0.44 SDS in later height. The association remained significant in the same direction after adjustment for confounders (Table 3). There was no significant association between weight SDS in the second half of infancy and later body size.
|
weight SDS at 0–3, 3–6, and 6–12 wk) to investigate whether we could identify smaller "critical periods" for the long-term outcomes (Table 4). The weight SDS in the very early postnatal period (ie, the first 6 wk) showed a stronger association with later height than did that in later periods.
|
weight SDSs at 0–3 mo and 3–6 mo showed a positive relation with childhood FMI SDS. A 1-SDS increase in early weight was associated with increases of 0.24 SDS (95% CI: 0.04, 0.44) and 0.50 SDS (95% CI: 0.25, 0.75) in later FMI for those time periods, respectively. The association remained significant, but the magnitude was less after adjustment for potential confounders (Table 3
). The association between weight SDS during these 2 periods with respect to later FMI SDS was of a magnitude similar to or greater than that of birth-weight SDS and physical activity, for both the regression coefficients (β) and the proportion of variance explained (partial r2) (data not shown). For example, 1-SDS increases in weight from 0 to 3 mo and birth weight were associated with increases of 0.34 SDS (95% CI: 0.14, 0.54) and 0.17 SDS (95% CI: –0.001, 0.34), respectively, in later FMI, and they explained 6.8% and 2.4% of the variance in later FMI, respectively. In the same multiple regression model, physical activity rating and maternal BMI explained a further 5.7% and 6.6% of the variability in later FMI, respectively.
The positive association between greater weight SDS during the first 3 mo and later FFMI SDS had an effect size similar to that of FMI SDS; a 1-SDS increase in weight from birth to 3 mo was associated with increases of 0.26 SDS (95% CI: 0.6, 0.46) and 0.24 SDS (95% CI: 0.04, 0.44) in later whole-body FFMI and limb FFMI, respectively. These associations remained of similar magnitude after adjustment for potential confounders (Table 3). However, when the period from birth to 3 mo was split, there was generally no significant association between weight SDS over any of the 3 smaller windows and later FFMI except a weak positive relation with limb FFMI in the period from birth to 3 wk (Table 4). The main findings did not change when birth-weight SDS was removed from the models (data not shown).
Early growth and fat distribution
Greater weight SDS over various periods in the first 6 mo was associated with a tendency toward central fat distribution assessed by WC and trunk FMI; the effect size was increases of 0.36–0.39 SDS in WC and 0.26–0.52 SDS in trunk FMI per 1-SDS increase in early weight (Table 3). Because WC SDS was not available for subjects >17 y old, analyses using WC adjusted for height were also performed; the association was similar to that using WC SDS (data not shown). After adjustment for potential confounders (Table 3), this association remained. The additional analysis of the shorter periods of weight gain in the first 3 mo showed similar results without any period predominantly affecting later fat distribution (Table 4).
To separate the associations between early growth and the tendency to store fat centrally from associations with total fatness, further adjustments for limb FMI SDS (for trunk FMI) and 4C FMI SDS (for WC) were performed. The positive association between weight SDS and trunk FMI was no longer significant after adjustment for limb FMI, whereas the relation with WC was substantially decreased, but a positive trend still remained for weight SDS in the first 3 mo of life. It is interesting that, in the additional analysis (Table 4), only weight SDS for 0–3 wk showed a positive correlation with later WC after adjustment for total FMI; this is equivalent to an increase of 0.22 (95% CI: 0.04, 0.40) SDS in later WC per each 1-SDS increase in early weight. This finding suggests that the association between weight SDS and trunk FMI was not greater than that between weight SDS and total fatness, whereas the association of weight SDS and WC may be somewhat greater.
Additional analyses
To illustrate the associations between early weight gain and later body composition in a more easily understandable form, we analyzed the weight SDS during infancy as a categorical variable (ie, dividing weight SDS into quartiles). The main findings of the association between weight SDS quartiles and later body composition were similar to those obtained by using weight gain as a continuous variable (Figure 1).
|
|
DISCUSSION |
|---|
|
TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
|---|
Several publications have reported positive associations between infant growth and height, weight, and BMI in childhood and early adulthood (9–11, 34–36). Most studies present infant growth over a 6- or 12-mo period, because more-detailed infant growth records are rarely available. Our findings agree with these studies but provide more information about the possible "critical" period of infant growth. Thus, an increase in weight SDS during the first 6 wk of life had a stronger association with later height than does an increase in later periods, whereas the period from 0–3 mo was most influential for later BMI.
Few studies have examined associations between infant growth and specific components of later body composition. Using bioelectrical impedance, Wells et al (34) reported that weight SDS from birth to 6 mo was associated with later height, BMI, and FFM (but not FM) in 9-y-old Brazilian boys. An exclusive association between postnatal growth (length gain from birth to 2 y) and FFM in adults was also found by Li et al (37) in a Guatemalan population. Sachdev et al (38) reported a positive association between change in BMI SDS from 0 to 6 mo and later lean body mass (calculated from SFT equations) in young Indian adults, with a weak positive association between growth in the same period and the later sum of SFTs. In contrast, results from industrialized populations suggest stronger associations between early growth and later FM. Euser et al (35) reported that weight SDSs at 0–3 mo and 3–12 mo were associated with FM, FFM (calculated from an SFT equation), and WC, independent of birth weight in a preterm-born Dutch cohort in early adult life. The proportions of variance explained by weight SDS in both periods were larger for adult FM than for FFM. Ekelund et al (36) showed, using air-displacement plethysmography, that an increase in weight SDS from 0 to 6 mo was positively associated with FM, FFM, and WC at age 17 y in a Swedish cohort. Even more recently, Demerath et al (33) reported that persons with the greatest weight gain between birth and 2 y had significantly greater stature, fat mass, and percentage body fat measured by DXA at a mean age of 46.8 y. Our findings are in general agreement with those from 3 Western countries that showed a predominant positive correlation between early weight gain and later FM, whereas data from non-Western populations suggest a predominant association with later FFM. One potential explanation for the apparent population differences could be that, in non-Western populations in whom the intrauterine development of muscle fibers might be less optimal, there is greater potential for growth in the early postnatal period to influence later FFM. The findings of Yajnik et al (39) that Indian infants are more "adipose," despite being smaller at birth, than are UK infants supports this concept. Another explanation could be differences in the postnatal environment including infant feeding practices between non-Western and Western countries, with the latter more likely than the former to experience "excess" nutrition, which would lead to greater FM.
Determinants of postnatal weight gain and practical implications
Although the associations shown in our study cannot provide information on causation, a consideration of the factors driving postnatal growth is relevant in identifying potential practical interventions aimed at preventing adverse consequences of early growth patterns. Infant growth is clearly determined by both genetic and environmental factors. Demerath et al (33) estimated that additive genetic effects explained a high proportion of the variance in both infant weight status (heritability estimate: 0.61–0.95) and infant weight gain (heritability estimate: 0.56–0.82). The role of specific genes in determining normal variations in birth weight and infant growth remains poorly understood. Nevertheless, Freathy et al (40) recently showed the first association between a type 2 diabetes susceptibility gene and birth weight; using genome-wide association data, Weedon et al (41) reported that a common variation in the HMGA2 gene is associated with height in multiple studies. The effect on growth was apparent as early as age 7 y, but it is not clear whether this gene is implicated in infant growth. Recent studies also highlighted genetic influences on eating behavior and concentrations of appetite-related hormones during childhood (42), although the significance of this finding for infant appetite and food intake is currently unknown.
Because low-birth-weight infants are more likely than are normal-birth-weight infants to show rapid infant growth, it could be argued that reducing the incidence of low birth weight may reduce the risk of later fatness or obesity by removing the stimulus for catch-up during the postnatal period. However, as highlighted in a systematic review (43), nutritional interventions during pregnancy aiming to prevent low birth weight have had only limited success. Moreover, we showed that the magnitude of the association between early weight gain and later FM was greater than that of birth weight and later FM and similar to that of other important risk factors for later obesity, such as physical activity or maternal BMI. In practical terms, environmental factors such as infant nutrition have been shown in randomized trials to affect postnatal growth. For example, infants born small-for-gestational-age at term show more rapid infant growth when randomly assigned to a nutrient-enriched formula than to a standard term formula (44). Therefore, we propose that manipulating infant nutrition and hence growth in the first 6 mo of life may be a practical strategy for reducing later obesity.
Critical windows for programming of body composition
The investigation of potential "critical windows" raises methodologic issues related to the selection of growth periods for analyses; short periods may introduce more "noise" from measurement error at both ends, whereas longer periods may be too insensitive. In addition to presenting data for longer periods of growth in our main analysis, we also provided data on weight SDS for shorter periods of growth. We found that, whereas rapid weight gain from age 0 to 3 wk was not correlated with later BMI or FMI, it was associated with greater WC, even after adjustment for FMI. This finding lends some support to the concept that rapid weight gain during the first few weeks of life may have a long-term influence on development of the metabolic syndrome (13, 14). However, this possibiliy requires further investigation in cohorts with precise, prospective measurements of infant growth.
Study limitations
Most of our infant weight data were obtained from the parents' baby record books, and the data generally were not recorded at the precise times specified for the prospective study. This limitation was addressed by presenting all early-growth data as weight SDSs. Body-composition outcomes were measured over a wide range of ages and stages of pubertal maturation. However, we expressed body-composition variables as age- and sex-specific SDSs, and results did not change after adjustment for pubertal maturation. The subjects in the present study were taller and heavier and had bigger waist circumference than average, as compared with 1990 UK reference data (secular trends in the United Kingdom are similar); 43 subjects (18.4%) were overweight and 6 (2.6%) were obese according to the International Obesity Task Force cutoff for BMI (45). However, infant growth patterns in the present cohort were generally representative of the reference population, which suggests that our findings should be generalizable to similar populations.
In conclusion, our data suggest that, in a Western population, growth in the first 6 mo of life is associated more strongly with FM than with FFM during childhood and adolescence, and the magnitude of the association is comparable to that of other recognized obesity risk factors. The practical relevance of these findings requires further investigation in terms of the relative importance of FM and FFM for health outcomes such as cardiovascular risk factors.
|
ACKNOWLEDGMENTS |
|---|
The authors' responsibilities were as follows—SC and MSF: designed the study and analyzed the data; JEW and SC: measured the subjects and modeled the body-composition data; SC: wrote the first draft of the manuscript; JCKW: provided critical input on the body-composition protocol and data analyses; AL and PSWD: set up the original prospective cohort; and all authors: participated in the interpretation of the results and contributed to revision of the manuscript. None of the authors had a personal or financial conflict of interest.
|
REFERENCES |
|---|
|
TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
|---|
This article has been cited by other articles:
|
|
 |
|
  R. W. J. Leunissen, G. F. Kerkhof, T. Stijnen, and A. Hokken-Koelega Timing and Tempo of First-Year Rapid Growth in Relation to Cardiovascular and Metabolic Risk Profile in Early Adulthood JAMA, June 3, 2009; 301(21): 2234 - 2242. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 B. Koletzko, R. von Kries, R. C. Monasterolo, J. E. Subias, S. Scaglioni, M. Giovannini, J. Beyer, H. Demmelmair, B. Anton, D. Gruszfeld, et al. Can infant feeding choices modulate later obesity risk? Am. J. Clinical Nutrition, May 1, 2009; 89(5): 1502S - 1508S. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
