Lisa Grentz, MS, RDN, CD, LDN, FAND
Parents hear about their child’s growth at every well-child appointment, but parents who are raising children with feeding tubes, might hear more about their child’s growth than they ever thought possible. Sometimes, the pressure of wondering if your child is growing adequately is compounded when medical professionals use different metrics for assessing that growth, and it’s important for parents to understand the difference between a growth percentile and a z-score.
Obtaining and interpreting growth measurements is a key component of assessing a child’s nutritional status. Measurements of weight, length/height, head circumference, weight for length, and/or body mass index (BMI) are obtained routinely from infancy through adolescence, and these data points are plotted on gender and age-appropriate growth charts (percentile curves that show the distribution of measurements for comparison to population data). What this essentially means is that percentiles show you the standing of your child within the population, and it allows you to see how your child ranks or fits in. On a growth chart, the 50th percentile represents the median. So, if a 3-year-old girl’s weight plots at the 25th percentile, that means that 25% of the reference population (other 3-year-old girls) will weigh less and 75% will weigh more.
However, growth charts not only show how a child is growing compared to other sex and age matched children. They also track the pattern of growth over time. What we see in children who are measured frequently is that the curve is a bit of misnomer because growth occurs in spurts rather than in a consistent linear fashion. This is one reason why percentiles are intended to be stated as intervals, such as “between the 10th and 25th percentile.” They do not reveal the actual degree of deviation from population norms. Because of this limitation, z-scores are now the recommended indicator for assessing nutritional status.
A z-score is a statistical measure (discrete number) that tells you how far away from the mean the single data point is when compared to the population data. Think of z-scores like a bell-shaped curve where a z-score of 0 is the mean. Positive z-scores represent the standard deviations above the mean and negative z-score represent the standard deviations below the mean. So, if a 3-year-old girl has a BMI z-score for age of -2.36, she is 2.36 standard deviations below the mean. Tracking z-scores (deviations from the mean) over time, helps the clinician identify if growth trends are improving, stabilizing, or worsening. One distinction between growth charts and z-scores is that growth charts are used as a tool for assessment but are not diagnostic; whereas, z-scores can be used for diagnosing underweight, overweight, and obesity.
That said, while monitoring percentiles and z-scores are both important, clinicians should also take into account other factors that might be influencing growth rates like premature birth, genetics, ethnicity, onset of puberty, illness, etc. We also know that healthy children come in all shapes and sizes and metrics are just once piece of the whole child. When assessing the child’s overall well-being, we want to look at their development and ability to meet milestones, mental health and emotional development, learning ability, social behavior and relationships, mood, and demeanor – and not just weight and length.