Although growth monitoring is the single most important tool in health screening of infants and young children, the methods used in assessing the adequacy of growth are relatively crude and unreliable. Assessment of growth is a two-step process, consisting of anthropometric measurement followed by interpretation of the data with the use of appropriate references (1). The latter step is usually accomplished by plotting anthropometric data on reference growth charts. When serial data are available, growth is considered to be normal if the subject's growth trajectory approximately parallels the growth chart (tracking). It is evident that this method is not capable of detecting more subtle aberrations of growth, nor of detecting even large aberrations at an early stage (2). A more discerning method for growth assessment consists of the determination of the subject's growth rate (increment over time) and comparison with appropriate reference increments.
This report presents reference standards for increments in length, weight, head circumference, and mid-upper arm circumference (MUAC) for children between birth and 36 months of age. The reference data have been derived from the large and well-defined sample of children participating in the Euro-Growth Study (1,3). The references for increments were constructed in such a way that the calculation of selected percentile values for various age intervals between birth and 36 months was possible. The calculation of z-scores (4) was not possible. The new references were compared with published references for increments in length and weight (5,6). The effects of demographic variables such as sex, mid-parental height, and region (study site) were assessed as well.
MATERIALS AND METHODS
The Euro-Growth Study was a multicenter longitudinal, observational study using standardized methodology (1,3). Healthy term infants (gestational age between 37 and 44 weeks) who had no signs of intrauterine growth aberration and who met other inclusion criteria (3) were enrolled before 30 days of age and were monitored to 36 months of age. At enrollment the parents were interviewed to obtain demographic data, birth data for the infant (weight, length, and head circumference), and parents' heights.
The cohort consisted of 2245 subjects (1154 boys and 1091 girls) from 22 study sites in 12 European countries. The data from one center (n = 100) could not be used for the construction of references, leaving 2145 children for whom valid data were available (3). During the first 2 months of life, 54% of the infants were exclusively or fully breast-fed and an additional 20% received breast milk plus other feedings. At 5 to 6, 6 to 9, and 9 to 12 months of age, 31%, 25%, and 13%, respectively, of the infants were still receiving breast milk (7).
Anthropometric measurements were performed at the following 12 target ages: within 5 days of 30, 60, 91, 122, 153, and 183 days of age; within 7 days of 274 and 365 days of age; and within 14 days of 548, 730, 913, and 1096 days of age. The range of ages at which anthropometric measurements were actually performed, the anthropometric methodology, and the quality control measures have been described (1,3).
Construction of Age-and Sex-Specific Velocity References
The measurement scheme of the Euro-Growth Study allowed the calculation of increments for selected age intervals. An important decision in the construction of increment references concerns the selection of age intervals. From a practical point of view, intervals should be as short as possible. However, this demand must be weighed against the requirement for an acceptable ratio between measurement error and variation in growth velocity. Selection of appropriate intervals defined by midpoint and width was accomplished with the use of a parabolic growth model. The procedure is described in Appendix 1. The procedure was used to derive the tolerance limits around the selected interval midpoints and widths, taking into account the measurement schedule in the Euro-Growth Study. Thus, individual growth measurements were used for the construction of the references only if they met the inclusion criteria presented in Table 1.
Velocities were calculated for all individual intervals as the increment during the actual time elapsed and expressed as increment per unit of time. Two-, 3-, and 6-month intervals were used for length, weight, head circumference, and MUAC. In addition, 1-month intervals were used for weight between 0 and 6 months of age because the longitudinal reliabilities were found to be adequate (3).
Table 2 indicates the actual deviations from the target midpoint and target width and the number of observations per age interval. The percentage of observations that were accepted for calculation of increments according to the criteria listed in Table 1 ranged from 89.5% to 98.6%, depending on the age interval.
The distributions of the increments were often positively skewed (Appendix 2). High kurtosis indicated the presence of larger outliers in both (+ or -) directions. The combination of a low skewness and a high kurtosis is not favorable for a simple transformation to normality and the calculation of z-scores (4). The references, therefore, are presented as selected percentile (P) values (P3, P5, P10, P25, P50, P75, P90, P95, and P97) for boys and girls. The large number of subjects justified the inclusion of the 3rd and 97th percentiles.
Gender-related differences in increments were evaluated using t- tests. The influences of sex, region (study site) and mid-parental height on increments were studied by using analysis of covariance. Selected percentile values (5th, 50th, and 95th) of the Euro-Growth references were compared with those reported by Roche et al. (5) and Guo et al. (6), which are based on growth velocities of infants in the United States. Both references include data underlying the National Center for Health Statistics (NCHS) growth references (9). In addition, Guo et al. included infants who were studied by Fomon et al. (2).
Sex-specific reference values (mean, standard deviation [SD], and percentiles) are presented for increments in length in Table 3, weight in Table 4, head circumference in Table 5, and MUAC in Table 6. As the data show, all increments decreased rapidly with increasing age during the first 4 to 6 months of life and continued to decrease thereafter at a progressively less rapid rate. The SD of increments tended to be smaller for longer than for shorter age intervals (at similar ages), presumably because the influence of the measurement error on the calculated increment diminished with increasing length of the observation period. All increments were larger for boys than for girls during the early months of life. The difference was significant for length until 5 months, for weight until 7.5 months, for head circumference until 3.5 months, and for MUAC until 2.5 months (Appendix 3). At older ages sex-related differences were mostly small and not statistically significant. Length increments were actually significantly larger for girls than for boys during a number of intervals beginning at 6 to 9 months.
Comparison of the Euro-Growth weight increments (0–6 months) with those of Roche et al. (5) showed (Table 7) that the 50th percentile was similar between 2 and 6 months of age. The 10th and the 90th percentile values were markedly different at essentially all ages. For example, the Roche 10th percentile value for weight gain of boys between 1 and 2 months of age was 250 g higher than the corresponding Euro-Growth percentile. The broader range of weight increments (10th–90th percentiles) in the Euro-Growth references are explained by the fact that we did not use mathematical models for fitting serial weight data. Comparison of the Euro-Growth length and weight increments with those of Guo et al. (6) also shows that the 50th percentiles are similar, but the ranges of the Euro-Growth references are broader (Appendix 4).
The overall effect of sex on increments was modest. Only 3%, 7%, 2%, and 1% of the variances of increments in length, weight, head circumference, and MUAC, respectively, were explained by sex. Table 8 indicates the individual and combined effects of mid-parental height, sex, and study site (region) on increments. Each of the three demographic variables had a significant influence on length and weight increments at most age intervals. Head circumference and MUAC increments, however, were essentially influenced only by study site. The combined predictive power of the three demographic variables did not explain more than 13%, 13%, 14%, and 8% of the variance in length, weight, head circumference, and MUAC increments, respectively.
For a number of reasons, the present new references for increments in anthropometric parameters represent an improvement over existing references. The new references are based on a more extensive database than previous references. Furthermore, the Euro-Growth Study (1,3) drew on children from a wide range of European regions with a diversity of socioeconomic characteristics. Study subjects were approximately representative of the background population surrounding the 21 study sites. The incidence and duration of breast-feeding in the study cohort corresponded to that of the European background population in that 74% of the infants were breast-fed (7). In contrast, only 32% of the infants forming the references of Guo et al. (6) were breast-fed. In contrast to smaller databases, the extensive Euro-Growth database enabled establishment of outlying percentiles (e.g., 3rd, 97th) with the necessary degree of confidence.
Some of the shortcomings of other references were avoided in constructing the new references. Thus, the construction of the present references did not involve the fitting of data to mathematical models. In several previous studies, fitting mathematical models to serial data for individual subjects (5,6,10,11) derived reference data for increments. The data of each child were summarized in a few derived parameters that were then used to estimate growth velocities during selected age intervals. The parameters in the model were estimated with the Marquardt method (12).
The Gompertz or logistic function (13), fractional polynomials (5), or piece-wise connected functions (14) also described individual increments in healthy children. These functions are fitted to the individual measurements using (nonlinear) least-squares methods to obtain a certain degree of smoothing. Growth velocities at prechosen target ages are estimated by taking the mathematical age derivative of the fitted function and do not necessitate a uniform measurement scheme in time. The variation in the estimated growth increments in these biological models are generally low (15), with the exception of the beginning and the end of the age range under observation, where the standard errors are larger (5). This is due to the absence of surrounding measurements.
We decided not to fit mathematical models to serial data for individual subjects, being aware that the SD of increments would be larger than with a model-fitting approach. The major disadvantage of the modeling approach is that measurement errors (2) as well as the possible true short-term variations in growth rate are neglected (“oversmoothing”) (16). It is well documented that growth in length during infancy occurs in discontinuous, aperiodic saltatory spurts (17). Infants can display saltatory length increments of 0.5 to 2.5 cm, separated by intervals of 3 to 60 days' duration with no measurable growth (17). References obtained by model-fitting thus provide artificially diminished SDs. In practical terms, the consequence can be clinical misinterpretation of data obtained in health monitoring.
As expected, velocities for length, weight, and head circumference decreased rapidly with age, especially during the early months of life, confirming earlier reports (5,6,10,11,18–20). The observed tendency for boys to have larger increments for length and weight during the early months agrees with previous studies. (5,6,10,11, 18–20). Also in agreement with previous observations (5,6), we observed that the values for the 3rd and 5th percentiles for weight were initially higher and decreased more markedly in boys than in girls. In contrast, gender-related differences in length and head circumference increments were less marked. Deceleration in increments for MUAC was modest. The MUAC is a composite estimate of skin, adipose tissue, muscle, and bone. Body fatness (percentage of weight) increases during the first 6 months of life (21), and this may explain the slow deceleration in increments of MUAC.
Demographic variables such as gender, mid-parental height, and study site had only modest effects on increments in length and weight. Furthermore, the data clearly showed that the influence of gender was independent of the influences of mid-parental height and study site. Size at birth was not included in this model, because its predictive power on growth between 1 and 36 months of age rapidly decreases with increasing age (1).
Length of the age intervals to which increment references apply has important implications. On the one hand, to be clinically useful, intervals should be as short as possible; on the other hand, the shorter the age interval, the larger the influence of the measurement error. For example, the difference between the 5th and the 50th percentiles for length between 4 and 5 months of age is similar in magnitude to the measurement error (5). Data on length increments for age intervals as short as 1 month are therefore not useful. Similarly, in young infants within-day variation in weight (e.g., the difference in weight before and after a feeding) as well as day-to-day variation are large relative to the difference between percentiles. Intervals shorter than 1 month are therefore not useful for weight increments. The intervals chosen for presentation in the new Euro-Growth references strike a reasonable compromise between the demands of clinical usefulness and theoretical considerations.
The use of increment references in growth monitoring is inherently more complex and demanding than the use of simple growth charts. Meaningful use of increment references requires that measurements be obtained over approximately the same age intervals for which references are available. It further requires that increments per unit of time be calculated from the measurements. The use of increment references should therefore be reserved for select situations that most benefit from such use. For example, in situations in which attained values decline below the 5th or above the 95th percentiles, the question of adequacy of growth can be resolved with the use of age-and gender-specific increment references. Similarly, increment references are useful in the evaluation of children whose serial anthropometric data show a change in relative position on the growth charts.
The new Euro-Growth references for increments are suitable for practical use. They are representative of children in Europe in general. They are also representative of the predominant mode of feeding (breast-feeding) in the European population.
EURO-GROWTH STUDY GROUP
Austria (A): C. Male, A. Golser; C. Huemer, B. Pietschnig
Croatia (HR): I. Svel, G. Armano
France (F): J. Schmitz, J. L. Muns, J. Beley, B. Digeon, J. Panis, G. Degy
Germany (D): F. Manz, E. Jekov, M. Radke,
Greece (G): T. Zachou, S. Egglezou, J. Sofatzis
Hungary (H): E. Barko
Italy (I): M. Salerno
Ireland (IRL): V. Freeman, H. Hoey, M. Gibney
Portugal (P): N. Teixeira Santos, A. Guerra, C. Rego, D. Silva
Spain (E): M. Hernandes, J. Molina, C. Ruiz, R. Tojo, E. Sanches, I. Rica, J. Argmeni, J. Rivera, C. Garcia-Caballero, M. Monleon, M. Manrique
Sweden (S): L. Persson, M. Lundstrom
United Kingdom (GB): J. Durnin, J. Reilly, S. Savage
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