Metrics of early childhood growth in recent epidemiological research: a scoping review

Metrics to quantify child growth vary across studies of the developmental origins of health and disease. We conducted a scoping review of child growth studies in which length/height, weight or body mass index (BMI) was measured at 2 time points. From a 10% random sample of eligible studies published between Jan 2010-Jun 2016, and all eligible studies from Oct 2015-June 2016, we classified growth metrics based on author-assigned labels (e.g., 'weight gain') and a 'content signature', a numeric code that summarized the metric's conceptual and statistical properties. Heterogeneity was assessed by the number of unique content signatures, and label-to-content concordance. In 122 studies, we found 40 unique metrics of childhood growth. The most common approach to quantifying growth in length, weight or BMI was the calculation of each child's change in z-score. Label-to-content discordance was common due to distinct content signatures carrying the same label, and because of instances in which the same content signature was assigned multiple different labels. In conclusion, the numerous distinct growth metrics and the lack of specificity in the application of metric labels challenge the integration of data and inferences from studies investigating the determinants or consequences of variations in childhood growth

Map of the study region, Kanungu District, Uganda.

<p>The study area is located northwest of Bwindi Impenetrable National Park, hemmed in by the border of the Democratic Republic of the Congo (DRC).</p

Table of variables used in regression analyses.

<p>Table of variables used in regression analyses.</p

Descriptive summary of birth outcome, meteorological and control variables in the dataset.

<p>Descriptive summary of birth outcome, meteorological and control variables in the dataset.</p

Trimester-specific associations between meteorological exposures and birth weight, stratified by ethnicity.

<p>Trimester-specific associations between meteorological exposures and birth weight, stratified by ethnicity.</p

Associations between study variables and birth weight (all models control for infant sex and gestational age).

<p>Associations between study variables and birth weight (all models control for infant sex and gestational age).</p

Sensitivity analyses of multivariable models for subsets of term births and ultrasound-dated births.

<p>Sensitivity analyses of multivariable models for subsets of term births and ultrasound-dated births.</p

Trimester-specific associations between meteorological exposures and birth weight, stratified by season of birth.

<p>Trimester-specific associations between meteorological exposures and birth weight, stratified by season of birth.</p

Decision tree for selection of metrics of growth in BMI (n = 49).

<p>Percentages represent the relative prevalence of the approach at each branching point. For example, the most common approach for expressing growth in BMI as an exposure with >2 data points was to first standardize BMI, then analyze it in relation to an outcome using latent class analysis.</p

Common content signatures and their associated author-specified labels for growth as an exposure, by anthropometric parameter^a.

<p>Common content signatures and their associated author-specified labels for growth as an exposure, by anthropometric parameter<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0194565#t002fn001" target="_blank">^a</a>.</p