How accurate is Tanner’s formula in estimating target height?

Abstract

Background

Growth evaluation is one of the most common reasons for referral to pediatric endocrinologists. While many factors, including nutritional status, comorbidities, and hormonal imbalances, can affect growth, a child’s adult height (AH) is primarily influenced by parental stature. Target height (TH) calculation is a widely used tool to assess whether a child is growing within the expected familial range. Despite its popularity, Tanner’s formula, proposed in 1970, has faced criticism, and alternative formulas have been suggested.

Summary

Several factors, such as sex differences in stature, secular trends, height disparity between parents, assortative mating, and parent-child height correlations, may affect the accuracy of TH calculation. Additionally, the formula tends to underestimate AH in children from very short parents, leading to underestimation of growth potential and overestimation of the effect of growth-promoting therapies.

Key messages

Although TH calculation provides an estimate of AH, several factors can influence its accuracy. While alternative formulas exist, none have fully replaced Tanner’s formula. Therefore, clinicians should carefully assess its limitations on a case-by-case basis.

Introduction

In many societies, stature has a determinant role in developing a positive self-perception and can influence social interactions. While both tall and short stature can attract attention, short stature is more frequently perceived as a negative trait, sometimes triggering feelings of inadequacy or inferiority [1]. Therefore, individuals with short stature may experience social disadvantages and psychological stress, particularly in adolescence. Conversely, tall stature is generally regarded more positively and rarely prompts referrals to pediatric endocrinologists, except in cases of extreme height.

The evaluation of growth is probably the most common reason of referral to pediatric endocrinologists, and the main question for parents is how tall their child will be as an adult. The challenge for pediatric endocrinologists is to differentiate between those children with suboptimal growth due to an underlying endocrine (or systemic) condition, and those for whom short stature is a consequence of physiological variations among individuals and does not require medical treatment. Together with an extensive auxological evaluation, the calculation of “target height” (TH) is an essential and universally performed first step, as it is indispensable for guiding the diagnostic and therapeutic approach [1, 2]. The concept of TH relies on the evidence that the adult height (AH) of a child is highly correlated to the height of the parents [3, 4]. Indeed, genome-wide association studies have shown that height is determined for 60–70% by parental height, while other factors such as nutrition, physical activity, sleep and chronic illness influence the remaining 30–40%[5, 6]. However, height is inherited as a polygenic trait and, within a single family, siblings inherit a unique combination of genes from their parents, leading to differences in AH among them. The within-family height variance can account for around 50% or more of the total population height variance. This means that the genetic differences contributing to AH between siblings are a large component of the overall height variation observed in a population [7, 8].

Nevertheless, the fundamental purpose of calculating TH is to determine whether a child's stature deviates significantly from their genetic potential, thereby raising the suspicion of a possible underlying pathology. In 1970, Tanner and Goldstein proposed a formula to calculate TH, taking into account parental heights and the difference between average female and male adult stature [9]:

$$\mathrm{TH}\mathrm{boys}:\frac{\mathrm{father}\mathrm{height}\left(\mathrm{FH}\right)+\left[\mathrm{mother},,\mathrm{height},,\left(\mathrm{MH}\right),+,13\right]}{2}$$

$$\mathrm{TH}\mathrm{girls}:\frac{\left[\mathrm{father},,\mathrm{height},,\left(\mathrm{FH}\right),-,13\right]+\mathrm{mother}\mathrm{height}\left(\mathrm{MH}\right)}{2}$$

The so-calculated TH has a range of ± 8.5 cm, which reflects the within-family variance. However, a recent study showed that the probability that such a large difference occurs is only 3% [10].

Although there have been several attempts to increase the accuracy of this formula, to date Tanner’s formula is still routinely used in clinical practice. A first obvious objection to the accuracy of this prediction is that the difference in average adult stature between men and women varies across populations [11–13]; moreover, the formula does not account for the progressive increase in stature over the past century (i.e. secular trend), that is likely to reflect the improvement in nutritional, hygienic, health and socio-economical status registered for most populations. Also, this formula lacks accuracy in TH prediction in children born from shorts parents, underestimating growth potential and overestimating the beneficial effects of growth promoting therapies [14, 15].

In this review, we aim to critically examine the accuracy of the TH formula, addressing its limitations and suggesting possible solutions. Of note, the prediction of adult height (e.g. according to methods such as Bayley-Pinneau or based on previous height measurements, i.e. projected height calculation) is beyond the scope of this review [16]. In fact, although it offers insights into the likely AH, it does not directly address whether a child's height aligns with their inherited potential, which is instead estimated by TH calculation. Specifically, the value of TH is the same for all biological children of a given couple, whereas the prediction of AH is individualized and specific for each child.

Methods

We performed a systematic literature search, in February 2024, across two databases according to the following search strategies:

Pubmed:

(((target height[Title/Abstract]) OR (midparental height[Title/Abstract])) OR (mid parental height[Title/Abstract]) OR (mid-parental height[Title/Abstract])) AND ((((((method*[Title/Abstract]) OR (formula*[Title/Abstract])) OR (calculat*[Title/Abstract])) OR (estimat*[Title/Abstract])) OR (equation*[Title/Abstract])) OR (algorithm*[Title/Abstract])).

Embase:

Query('target':ti,ab,kw AND 'height':ti,ab,kw OR ('midparental' AND height:ti,ab,kw) OR ('mid parental' AND height:ti,ab,kw)) AND (method*:ti,ab,kw OR formula*:ti,ab,kw OR calculat*:ti,ab,kw OR estimat*:ti,ab,kw OR equation*:ti,ab,kw OR algorithm*:ti,ab,kw) AND 'human'/de AND ('article'/it OR 'chapter'/it OR 'editorial'/it OR 'erratum'/it OR 'review'/it OR 'short survey'/it) AND [english]/lim Mapped terms''human'' mapped to 'human', term is not exploded.

A total of 2.671 articles were initially identified across both databases. These articles were imported into Rayyan, a platform for systematic reviews, where 533 duplicates were removed. This left 2.138 unique articles for further screening based on title and abstract. The screening process was conducted independently by two reviewers. Of these, 21 articles had conflicts, which were resolved after discussion between the reviewers. As a result, 2.089 articles were excluded due to irrelevance or language barriers, which included one article in Polish and another in German.

Next, the full texts of the remaining 49 articles were screened, resulting in the inclusion of 21 articles. Additionally, three more articles were included after reference screening of the initially selected articles, bringing the total to 24 included studies. This selection aimed at identifying all studies proposing alternative equations to calculate TH. The selected articles guided the drafting of the manuscript, although additional relevant articles were included to address some supplemental aspects.

Does one formula fit all? The contribution of ethnicity to height prediction.

Growth charts for height are created from height measurements collected from a large number of healthy children to determine the physiological growth pattern in a specific population. The final measurement of height is typically reported between the age of 18 and 21, when the final stature is assumed to be reached. However, growth charts reporting AH at the age of 18 might underestimate it, considering that between the age of 18 and the age of 21 some growth might still occur, specifically for boys, as shown for example by Dutch and Flemish data (+ 1.4 cm and + 1.6 cm, respectively) [11, 17]. Growth charts for the UK population, dating from 1990 show a difference between average female and male AH of 13.2 cm (which is reflected by the correction factor of 13 included in the Tanner’s formula to calculate TH) [18].

However, when looking at different populations, this factor often assumes different values, e.g. 14.4 cm for the Flemish population [19], 13.9 cm for the Italian population[12], and 15.8 cm for the Indian population[13]. Interestingly, a difference between average female and male height close to 13 cm (specifically 13.3 cm) is calculated from the WHO growth charts. These charts for ages 0–5 years are based on data from the WHO Multicenter Growth Reference Study (MGRS), which involved children from five different countries (Brazil, California, Ghana, India, and Norway) and aimed to provide uniform growth standards regardless of ethnicity. For children aged 5–18 years, the WHO combined the MGRS data with the 1977 U.S. National Center for Health Statistics (NCHS) growth charts, which were derived from a cross-sectional study of American children. This combination sought to create a comprehensive growth reference, although it means the height differences noted may partly reflect the characteristics of the U.S. population used in the older NCHS data [20–22].

Also the magnitude of the secular trend seems to be dependent on the population. For example, in Germany the height of conscripts became on average 6.5 cm taller, up to the reaching a plateau from 1956 to 2010 [23]. Italian conscripts born in 1980 were 12.2 cm taller than those born in 1854 (although regional differences were reported, with the greatest increase registered for people born in the Southern regions)[24]. For the Dutch population, an increase of about 21 cm was registered from 1858 to 1997, although at a slower rate in the more recent years [17, 25]. According to the last study assessing the growth in the Dutch population, this trend seems to have stopped [17]. In the Turkish population, in the last 30 years of the twentieth century, a secular trend of about 3.5 cm per generation was registered for both sexes [26]. In Australia, the secular trend has been estimated to be 0.4–2.1 cm/decade for males and 0.01–1.6 cm/decade for females, based on the comparison among a survey performed in 1992–1993 and two earlier independent surveys (in 1985 and in 1970) [27].

In contrast, the United States have encountered a negative secular trend, and from being one of the tallest nations in the world, they have progressively been surpassed by most North and Western European countries. The explanation of this trend as consequence of the increased prevalence of obesity in childhood has been proposed. Additionally, the possibility that American diets are sub-optimal compared to those in other regions could contribute to this trend. It has also been suggested that the universal health care systems and the robust social safety nets of European welfare states may offer a more favorable early-life health environment than the American health care system, potentially influencing growth outcomes. Furthermore, continuing immigration from Latin-American countries, where different genetic and nutritional factors are at play, may also contribute to variations in growth patterns. [28].

The secular trend has clearly not been measured or calculated uniformly across different populations. Moreover, if in some countries this trend seems to have stopped (e.g. in the Netherlands), in others, in particular in developing countries, the secular trend may still be ongoing. This variability makes it challenging to apply the secular trend uniformly across populations [29].

Historically, several authors have proposed alternative and population-specific formulas to calculate TH. In 1990, Ogata et al. proposed a modified version of Tanner’s formula, to take into account the secular trend of the Japanese population (2 cm) [30]. However, less than twenty years later, the same authors re-analyzed the height data of the Japanese population and, because the height difference between generations appeared negligible, they revised the formula once more, ultimately aligning it again with Tanner’s original formula [31].

In Taiwanese children, Tanner’s formula underestimated AH by 2.3 cm, thus Su et al. acquired the height data of parents (self-reported) and their adult offspring born in the 1970s (measured) in 1.229 healthy families. The increase in height between the two generations was 1.49–3.19 cm for boys and 2.03–2.61 cm for girls. Based on these data, they proposed the following population specific formulas: TH (boys) = 79.3 + 0.56*MPH, and TH (girls) = 35.2 + 0.76*MPH [32].

Also Atluri et al. noted an underestimation bias caused by Tanner’s formula in estimating AH in the Indian population. The underestimation was about 1.5 cm for girls and more than 2 cm for boys. Therefore, they proposed a modified TH formula [(FH + MH)/2 + 9 for boys and (FH + MH)/2 – 4 for girls] which is a simplified version of the equation that according to the study was the best model: 74.09 + 0.236 (FH) + 0.377 (MH) for boys, and 50.03 + 0.172 (FH) + 0.510 (MH) for girls [33].

An even greater underestimation bias was registered for a relatively small sample (n = 50) of children originating from rural area’s of South East Spain, namely 4.44 cm and 6.37 cm for boys and girls, respectively. However, no modified formula was suggested by this study [34].

A simple modified version of Tanner’s formula was proposed also for the Dutch population, to account for the secular trend: TH (boys) = (FH + MH + 13)/2 + 4.5 = MPH + 11 and TH (girls) = (FH + MH-13)/2 + 4.5 = MPH-2 [25]. This formula was later superseded by a subsequent study, as discussed at the end of next paragraph, and it is currently no longer recommended [35]. However, most of the proposed alternative formulas have never been widely used in clinical practice.

Challenges with extremes: tall or short parents, parental height disparity and assortative mating

A child’s AH is correlated to his current height and this correlation increases from birth to puberty (from 0.3 to 0.9). Parental heights are better correlated with their child’s AH (0.4–0.5) than with the child’s current height (which can be influenced by the maturation rate). Lastly, the correlation between mother’s and father’s height is variable (from 0.1 to 0.4), as a consequence of assortative mating, which indicates the tendency of people to choose a partner with similar phenotypic characteristics (as shown in Fig. 1) [36, 37].

Fig. 1.

Correlations between child’s adult height, current height and parental heights. a A child’s adult height is highly correlated to his current height and this correlation increases from birth to puberty (from 0.3 to 0.9). b Parental heights are better correlated with their child’s adult height (0.4–0.5) c than with child’s current height (which can be influenced by the maturation rate). d The correlation between mother’s and father’s height is variable (0.1–0.4)

However, according to a phenomenon known in biology and in statistics as regression to the mean, children born from very short or very tall parents usually will reach less short or less tall AH. It is particularly relevant to keep this concept in mind when examining children referred for short stature, and for whom the diagnosis of familial short stature is likely. In fact, in these cases, TH risks to underestimate the growth potential of the child, which is likely to be above the calculated value, and this should be discussed appropriately with the child and their caregivers. An adjustment for extreme parental heights was proposed a long time ago by Tanner and Buckler, who suggested to calculate mid-parental height (MPH) and then add or subtract 1 cm for every 5 cm that this deviates from the population mean [38].

As an alternative, Cole et al. proposed to evaluate the growth impairment of short children born from short parents using a formula including both the child’s height SDS and MPH SDS to calculate what they defined “conditional height SDS” (i.e. the expected child’s height SDS based on MPH SDS):

$$\mathrm{Conditional}\mathrm{height}\mathrm{SDS}=\left({\mathrm{child}}^{\prime },\mathrm{s},,\mathrm{height},,-,,{\mathrm{r}}^{*},,\mathrm{MPH},,\mathrm{SDS}\right)/\surd \left(1,-,{\mathrm{r}}^2\right).$$

In this formula r represents the correlation between the child’s height SDS and the MPH SDS, which between the age of 2 and 9 years is close to 0.5. MPH. SDS was calculated as: (MH SDS + FH SDS)/1.6. The value 1.6 results from √(2 + (1*r(M,F)), where r(M,F) is the correlation between parental heights, assumed to be 0.3 as consequence of assortative mating [39].

Of note, the distribution of AH (and thus also AH SDS) is about 10% greater in men than in women. Taking into account this aspect, already in the nineteenth century, Galton proposed to calculate MPH SDS upweighting the FH SDS by 8–11% [40]. However, it was later demonstrated that MPH SDS obtained by averaging the height SDSs of the two parents is a valid alternative [41]. Taking into account MPH SDS, Wright et al. proposed to calculate the expected child’s height SDS as MPH SDS * 0.5 (a simplified version of the initially proposed model where TH-SDS = MPH SDS * 0.51 + 0.015). Ninety per cent of children included in the study had values within 1.4 SDS of their expected SDS [42].

However, the use of MPH SDS rather than the value expressed in cm does not solve another issue that in some cases needs to be taken into consideration. In fact, assortative mating does not apply to every parental couple, and the difference between mother’s and father’s height can be far from the sex correction factor of 13 cm in case of evident parental height disparity. In addition, a study conducted on a large sample of Taiwanese families showed that FH contributes most to the height of the tallest son, while MH contributes most to the height of the shortest daughter [32], making the parental contribution to a child’s AH not always balanced.

One of the best known studies to assess the accuracy of Tanner’s formula was performed on a large sample of 2402 healthy Swedish children by Luo et al. in 1998 [14], who proposed the following equations to calculate TH:

TH (boys) = 45.99 + 0.78 * MPH, and TH (girls) = 37.85 + 0.75 * MPH, with a 95% predicted interval of about ± 10 cm. This prediction model was similar in SDS, and was not affected by assortative mating or a difference in parental heights. Although it may underestimate TH by about 2 cm for children with a MPH below −2 SDS (or 163 cm), this model is an improvement of the Tanner method, for which the underestimation bias is of about 6 cm.

The other well-known model is the one proposed by Hermanussen and Cole in 2002, who aimed to correct Tanner’s formula taking into account assortative mating and parent–offspring correlation. Based on the study of Luo et al., the parent-parent correlation was assumed to be 0.27, and the parent–offspring correlation 0.57. The final simplified equation to calculate the corrected TH SDS was:

$$\mathrm{TH}\mathrm{SDS}={\left[\left(\mathrm{FH},,\mathrm{SDS},+,\mathrm{MH},,\mathrm{SDS}\right),/,2\right]}^{*}0.72,\mathrm{with}95\%\mathrm{C}.\mathrm{I}.\pm 1.6\mathrm{SDS}.$$

This formula is not sex-specific, and it is also not influenced by the secular trend if parental height SDS is obtained from growth charts dating back one generation [43].

However, because the correlation coefficients can vary over time and among populations, it could be needed to calculate the simplified formula reported above for each population [44].

For example, for the Dutch population the following formula has been proposed to take into account the assortative mating and the parent–offspring correlation, and has been adjusted to calculate TH in cm [35]:

$$\mathrm{TH}\left(\mathrm{boys}\right)=44.5+0.{376}^{*}\mathrm{FH}\left(\mathrm{cm}\right)+0.{411}^{*}\mathrm{MH}\left(\mathrm{cm}\right).$$

$$\mathrm{TH}\left(\mathrm{girls}\right)=47.1+0.{334}^{*}\mathrm{FH}\left(\mathrm{cm}\right)+0.{364}^{*}\mathrm{MH}\left(\mathrm{cm}\right).$$

Similarly, based on the method of Hermanussen and Cole, modified equations expressing TH in cm rather than SDS were proposed for the Australian population [45]:

$$\mathrm{TH}\left(\mathrm{boys}\right)=176.9+2.{57}^{*}\left[\left(\mathrm{FH},-,176.9\right),/,7.1,+,\left(\mathrm{MH},-,163.3\right),/,6.5\right];95\%\mathrm{CI}\pm 11.7\mathrm{cm}.$$

$$\mathrm{TH}\left(\mathrm{girls}\right)=163.3+2.{33}^{*}\left[\left(\mathrm{FH},-,176.9\right),/,7.1,+,\left(\mathrm{MH},-,163.3\right),/,6.5\right];95\%\mathrm{CI}\pm 10.6\mathrm{cm}.$$

The comparison of Tanner’s formula with three alternatives formulas was performed in a sample of 85 children with idiopathic short stature (ISS) who had reached AH, and for whom TH was calculated a) according to Tanner’s formula [9], b) MPH SDS calculated as (MH SDS + FH SDS)/2 [41], and c) as (MH SDS + FH SDS)/1.6 [39], and d) TH SDS calculated according to Hermanussen and Cole [43]. If the child’s current height was within the familial range, ISS was classified as familial short stature (FSS), otherwise ISS was classified as non-familial short stature (NFSS). The allocation of a child in the FSS or in the NFSS group depended on the method chosen to calculate TH. Although according to the concept of regression to the mean we would expect that children with FSS would reach an AH above their TH, in this study all children with FSS reached (as a group) a mean AH below the TH, with the exception of children classified as having FSS according to method 3 [39]. Using this formula, the study population reached a mean AH SDS close to the TH SDS. As expected, children with NFSS did not attain their TH independently of the method used to calculate TH [46].

Recently, a new algorithm has been developed using data from 23 large families mainly of Ashkenazi Jewish ancestry (the mean number of children per family was 11). The algorithm derived by the authors takes into account the correction for sex of the child, the correction of parental height for age and the regression to the mean. However, its complexity may represent a disadvantage for routinely use in clinical practice [10].

An overview of the above mentioned formulas is shown in Table 1.

Table 1.

Overview of the formulas proposed over the time to calculate target height

Authors, year	Studied Population	Formula	Adjustment(s)
Tanner et al., 1970 [8]	England	[(FH + MH) ± 13]/2; range ± 8.5 cm	-
Ogata et al., 1990* [29]	Japan	[(FH + MH) ± 13]/2 + 2 range boys ± 9 cm, girls ± 8 cm	Secular trend
Su et al., 2007 [31]	Taiwan	TH (boys) = 79.3 + 0.56*MPH TH (girls) = 35.2 + 0.76*MPH	Secular trend
Atluri et al., 2018 [32]	India	TH (boys) = (FH + MH)/2 + 9 TH (girls) = (FH + MH)/2 – 4	Secular trend and sex correction factor
Cole 1996 [38]	England	MPH SDS = (MH SDS + FH SDS)/1.6	Extreme parental heights
Cole 2000 [40]	England	MPH SDS = (MH SDS + FH SDS)/2	Extreme parental heights
Wright et al., 1999 [41]	England	TH-SDS = MPH SDS * 0.51 + 0.015	Extreme parental heights
Luo et al., 1998 [13]	Sweden	TH (boys) = 45.99 + 0.78 * MPH TH (girls) = 37.85 + 0.75 * MPH range: ± 10 cm	Not affected by assortative mating or the absence of it
Hermanussen & Cole, 2002[42]	Germany	TH SDS =  [(FH SDS + MH SDS)/2]*0.72 range: ± 1.6 SDS	Assortative mating and parent–offspring correlation
Van Dommelen et al., 2012 [34]	Netherlands	TH (boys) = 44.5 + 0.376 * FH (cm) + 0.411 * MH (cm) TH (girls) = 47.1 + 0.334 * FH (cm) + 0.364 * MH (cm)	Assortative mating and parent–offspring correlation
Hughes & Davies, 2008 [44]	Australia	TH (boys) = 176.9 + 2.57 * [(FH-176.9)/7.1 + (MH-163.3)/6.5] range: ± 11.7 cm TH (girls) = 163.3 + 2.33 *[(FH-176.9)/7.1 + (MH-163.3)/6.5] range = ± 10.6 cm	Assortative mating and parent–offspring correlation

FH father height, MH mother height, MPH mid-parental height, SDS standard deviation score, TH target height

^*In 2007 the same authors re-updated the formula, aligning it with Tanner’s formula

Can target height range calculation help in evaluating the growth of children with physiological variations of pubertal timing?

Pathological alteration of pubertal timing (i.e. precocious or delayed puberty) can impair the attainment of AH, which can be below the TH range [47–50]. Nevertheless, results from different studies are not homogeneous and in other cohorts, AH has been reported to be in line with TH [51–53].

Interestingly, non-pathological variations of pubertal timing seem to be associated with altered growth patterns. In fact, in the absence of pathological conditions, an association between age at pubertal onset and AH percentile exists. This means that children growing at a faster pace are likely to enter puberty earlier than their peers, while children growing at a slower pace (thus on a percentile below their target) will likely enter puberty a bit later than expected. For example, in case of advanced bone age (i.e. bone age > = 2 SDS for chronological age) without signs suggestive of endocrinopathy, AH is usually within TH range although it might be reached earlier than expected, and at the moment of the assessment, the child might be growing above his target [54]. Similarly, in girls with early-normal puberty (puberty onset and progression between the age of 8 and 9 years), AH is usually in line with TH, although reached earlier than in peers [53].

Regardless of bone age advancement or retardation, a child may temporarily grow on a percentile different from its target. The “height gap” (i.e. the difference between the child’s height percentile and the target height percentile) will usually be filled by the modulation of pubertal timing, allowing the attainment of AH within the target range. BMI can play a role in this modulation. A study conducted in 170 Israelian and 335 Polish children, showed that when the BMI remained constant, an increase of 1 SDS in the height gap was associated with advanced puberty onset, specifically of 0.9 years (Israelian girls), 1.07 years (Israelian boys), 0.25 years (Polish girls), and 0.34 years (Polish boys). Similarly, a decrease of 1 SDS in the height gap was associated with a similar delayed puberty onset [55].

Therefore, it is important to take into account the pubertal stage in children who are growing above or below their target range, in absence of hormonal alterations.

Self-reported parental height: accuracy and impact on prediction.

A last aspect to consider in TH calculation is that reported parental heights are often unreliable. Parents tend to overestimate their height, and fathers do that to a greater extent than mothers. The estimation of the partner’s height by one of the parents is equally unreliable. Although usually this bias does not influence TH calculation significantly, it is not rare that parents overestimate their height by 4–6 cm or more and this occurs particularly in parents with short stature [56, 57].

Consequently, TH calculation should be made after measuring the stature of the mother and the father during the consultation, and rely on reported measurements only when the presence of both parents at the clinic is not possible.

Conclusion

The calculation of TH is extensively used in clinical practice to evaluate the growth of children with or without an underlying pathological condition. While tall stature is only rarely a cause of concern, children with short stature are more likely to undergo extensive diagnostic work-up and start growth-promoting therapies when indicated. In the context of familial short stature, TH calculation according to Tanner might underestimate AH significantly, and as such overestimate the effect of growth-promoting therapies. Moreover, other factors such as the correlation between both parental heights, the timing of puberty, and the ongoing secular trend might affect TH calculation accuracy. Although several alternative formulas to calculate (or correct) TH have been proposed over time, they are not (yet) routinely used. Nevertheless, the formula proposed by Hermanussen and Cole [43] has been used to estimate TH in the studies conducted on the KIGS (Pfizer International Growth Database) [58, 59] and its use has been advised also in the Consensus Statement for the diagnosis and treatment of ISS [1]. As shown in Table 2, this formula overcomes several pitfalls of Tanner’s formula. Therefore, we advise to introduce the use of this formula in clinical practice. As a suggestion for future research, a comprehensive analysis comparing various TH formulas using real-world data would be valuable. This would involve selecting a large dataset, including both biological parents' heights along with the adult height of the offspring. This would offer insights into the precision and reliability of different prediction models, particularly in cases involving atypical parental height distributions, such as those with one parent significantly shorter than the other. That said, TH is and will remain an estimation, far from ever becoming an exact calculation, as clearly deductible by the height discrepancy often present among healthy siblings.

Table 2.

Main pitfalls in target height calculation

Pitfalls	Suggestions
Sex correction factor can be population-specific	Derive the sex correction factor from population-specific growth charts OR Use population-specific formula’s if available
Height disparity between parents can be greater than average	Use the models proposed by Luo et al., Hermanussen & Cole AND Take into account that father height is more likely to influence sons’ height and mother’s height daughters’ height
Secular trend and its differences among populations	Obtain information about secular trend for the specific population OR Use population-specific formulas accounting for secular trend if available OR Use the model proposed by Hermanussen & Cole if parental height SDS is obtained from growth charts dating back one generation
TH can underestimate growth potential in children born from very short parents	Calculate TH-SDS rather than TH expressed in cm OR add 1 cm for every 5 cm that mid-parental height deviates from the population mean
TH can overestimate growth potential in children born from very tall parents	Calculate TH-SDS rather than TH expressed in cm OR subtract 1 cm for every 5 cm that mid-parental height deviates from the population mean
Need for taking into account assortative mating and parent–offspring correlation	Use the model proposed by Hermanussen & Cole

The model proposed by Luo et. al resulted in a formula calculated on data specific for the Swedish population. A recalculation of the formula for data specific for other populations might be needed to increase accuracy. Similarly, the model proposed by Hermanussen & Cole is based on parent-parent and parent–offspring correlation coefficients calculated by Luo et al. for the Swedish population. This correlation coefficients might differ for other populations, however they are accepted for European populations

Abbreviations

AH

Adult height

FH

Father’s height

MH

Mother’s height

MPH

Mid-parental height

TH

Target height

Authors’ contributions

Study concept: SC. Article selection: SC, PRC. Drafting of the manuscript: SC. Critical revision of the manuscript: MC. All authors approved the final version of the manuscript.

Funding

SC is supported by a project grant from the Research Foundation—Flanders (FWO; G065819N). MC is supported by a Ghent University Fund for Innovation and Clinical Research (FIKO IV) grant. The funders had no role in the design, data collection, data analysis, and reporting of this study.

Data availability

No datasets were generated or analysed during the current study.

Declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.