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. 2025 Nov 15;70(1):97–104. doi: 10.1111/jir.70060

Measuring Muscle Mass in Adults With Intellectual Disabilities: The Reliability and Construct Validity of Calf Circumference

Kirsten I de Oude 1,✉, Rosalie J E Bonnet 1, Roy G Elbers 1, Dederieke A M Maes‐Festen 1, Alyt Oppewal 1
PMCID: PMC12703055  PMID: 41239952

ABSTRACT

Background

The amount of muscle mass is an important criterion to diagnose sarcopenia. Two feasible methods for measuring muscle mass in adults with intellectual disabilities (ID) are bioelectrical impedance analysis (BIA) and calf circumference (CC). CC measurements are more accessible, cheaper and easier to use than BIA in adults with ID. This study aimed to investigate the construct validity and intrarater reliability of CC to estimate muscle mass compared to BIA in adults with mild and moderate ID and cardiovascular risk factors (CVRF).

Methods

This study was part of the PRET study (NTR, NL8382), which examined the effect of Progressive Resistance Exercise Training on cardiovascular risk factors in 36 adults with ID (55.58 years, SD: 12.89). Construct validity was analysed with Pearson's correlations between CC and BIA measurements (skeletal muscle mass [SMM], segmental muscle mass [SegMM] and skeletal muscle index [SMI]). The intrarater reliability was analysed with the intraclass correlation coefficient (ICC).

Results

The correlation between CC and SMM was 0.19 (95% CI [−0.16, 0.49]), 0.60 (95% CI [0.33, 0.78]) between CC and SegMM and 0.69 (95% CI [0.47, 0.83]) between CC and SMI. The ICC was 0.94 (95% CI [0.89, 0.97]).

Conclusions

The excellent intrarater reliability of CC indicates that CC measurements are reliable within the same assessor for adults with ID and CVRF. However, the use of CC to estimate muscle mass compared to BIA remains questionable.

Keywords: bioelectrical impedance analysis, calf circumference, intellectual disabilities, muscle mass

1. Introduction

The European Working Group on Sarcopenia in Older People 2 (EWGSOP2) defined the condition sarcopenia as a progressive and generalised skeletal muscle disorder characterised by a decline of muscle strength and muscle mass. The condition is severe if physical performance is also affected (Cruz‐Jentoft et al. 2019). Sarcopenia can cause problems in daily life (Malmstrom et al. 2016) and is associated with risks, such as falling and mortality in the general elderly population (Yeung et al. 2019; Sepúlveda‐Loyola et al. 2020).

A study about sarcopenia from the Academic Collaborative Research Center Healthy Ageing and Intellectual Disabilities (HA‐ID) showed that 12.7% of older adults ID aged between 50 and 64 years had sarcopenia (Bastiaanse et al. 2012). An ID is a neurodevelopmental disorder and defined as a deficit in intellectual and adaptive functioning, both with onset in the developmental period before the age of 22 (American Psychiatric Association. 2013). In the general population the prevalence of sarcopenia ranges between 5% and 10% in elderly of 60 years and older, following the EWGSOP2 definition (Yuan and Larsson 2023). A recent study from HA‐ID found that sarcopenia and severe sarcopenia are associated with early mortality in older adults with ID (Valentin et al. 2023). Thus, a timely diagnosis of sarcopenia is necessary in adults with ID.

Muscle mass is a crucial element in the diagnosis of sarcopenia (Cruz‐Jentoft et al. 2019). There are multiple methods that can determine muscle mass (Beaudart et al. 2016), but their applicability for adults with ID can be questioned. In the general population, the recommended method for measuring muscle mass is a dual X‐ray absorptiometry (DXA) scan. CT and MRI scans can also identify muscle mass (Beaudart et al. 2016). However, DXA, CT and MRI scans require qualified personnel and are expensive and time consuming. Moreover, these devices are not suitable for transport which restricts the use in a remote setting. Especially for adults with ID, this can be a limitation because transferring to a research location, such as a hospital, can cause distress and limits the feasibility.

A method that appears more suitable in a remote setting is bioelectrical impedance analysis (BIA). BIA is often used to assess body composition in the general population and athletes. BIA is a portable, relatively noninvasive and quick method. In elderly, the use of BIA to assess body composition has been found reliable (intraclass correlation coefficient [ICC]), ranging between 0.91 (Anusitviwat et al. 2023) and 0.99 (Ling et al. 2011) as well as valid showing a good correlation to DXA r 2 = 0.76 (Kim and Kim 2013). BIA uses the electrical conductive properties of the body to estimate muscle mass (Cruz‐Jentoft et al. 2019; Sergi et al. 2017). Overall, BIA devices are recommended to be used for assessment of muscle mass with clinical considerations such as age, ethnicity and hydration status of the participant (Cruz‐Jentoft et al. 2019). Even though BIA is commonly used in the general population, the cost of a BIA device fit for professional use and the requirement of staying still without assistance can be challenging for adults with ID. Second, the validity and reliability of BIA measurements are sensitive to changes in the environment (temperature and humidity) and person (fasting time and hydration). Repeated measurements should therefore be performed in the same environment and at the same time whenever possible (Campa et al. 2021).

The most noninvasive, low cost and low effort method to measure muscle mass is by measuring CC (Beaudart et al. 2016; WHO 1995). The use of CC is recommended for older adults if no other diagnostic methods are available (Cruz‐Jentoft et al. 2019). CC is less sensitive than BIA to changes in the environment and person, which makes the repeatability more reliable. In the general population, the intrarater reliability has been found excellent (Sharkey et al. 2018; Tunc et al. 2007). Previous studies have compared CC and BIA in the general elderly population as a way of measuring muscle mass. These studies have shown moderate and strong positive correlations between CC and BIA (Bohannon et al. 2016; González‐Correa et al. 2020; Ishii et al. 2014). However, the applicability of these studies to adults with ID is uncertain. Some genetic syndromes are characterised by an altered growth (Cole and Hughes 1994; Edmondson and Kalish 2015) or a different stature (Tüysüz et al. 2012) compared to the general population, which could alter the interpretation of muscle mass. Additionally, obesity is highly prevalent in adults with ID (de Winter et al. 2012), and in the general population, it was found that people with a higher BMI often have a bigger CC without it representing a higher muscle mass (Gonzalez et al. 2021). Lastly, adults with ID often have gait characteristics that differ from the general population (Oppewal et al. 2018), which might affect the use and development of muscles and could lead to atypical CC measurements that are not representative of overall muscle mass. Therefore, the correlation between CC and BIA could be lower in adults with ID, because of the aforementioned physical differences.

The primary aim of this study was to assess the construct validity of CC measurement for assessing muscle mass compared to BIA in adults with ID. Second, we assessed the intrarater reliability of CC measurements. We expected a good intrarater reliability for CC measurements, because the measurements are not dependent on the participant's ability to follow instructions.

2. Material and Methods

2.1. Study Design

This study was part of the Progressive Resistance Exercise Training (PRET) study (NTR, NL8382) (Elbers et al. 2022), which was performed within the Academic Collaborative Research Center Healthy Ageing and Intellectual Disabilities (HA‐ID). We obtained ethical approval from the Medical Ethics Review Committee of the Erasmus MC, University Medical Center Rotterdam in the Netherlands (MEC‐2019‐0544). This study is registered in the Netherlands Trail Register (NTR, NL‐8382) and ClinicalTrials.gov (NCT‐06579898). The PRET study uses a repeated time series design to examine the effect of PRET on cardiovascular risk factors in adults with ID. As a secondary outcome of the PRET study, muscle mass was measured using CC and BIA. Details of the PRET study are reported in the protocol paper (Elbers et al. 2022).

For this study, baseline measurements of the PRET study were used. Baseline measurements were performed at three different time points (T0, T1 and T2) with an interval of 6 weeks. The PRET study was still ongoing during the completion of this study. Data for this study were collected between December 2021 and November 2023.

2.2. Study Population and Inclusion

The participants of the PRET study (n = 36) were adults (≥ 18 years) with moderate (IQ = 35–49) or mild (IQ = 50–69) ID who received support or care from one of the involved care organisations (Amarant, Abrona or Ipse de Bruggen) in the Netherlands. Because of the primary objective of the PRET study, only people with a minimum of two cardiovascular risk factors (diabetes mellitus type II, hypertension, obesity or hypercholesterolemia) or metabolic syndrome were included. Furthermore, the participants could not have any physical limitations interfering with participating in PRET. More specific information about the inclusion criteria is reported in the protocol article (Elbers et al. 2022). For this study, participants from the PRET study were included if they had two completed baseline measurements conducted by the same researcher.

2.3. Measurements

The primary parameters of this study were muscle mass measured with BIA and CC, both measured by a trained researcher during baseline at T0, T1 and T2. Before conducting the measurements, a researcher received training in the proper application of both measurement techniques. The training involved practising the procedures according to predefined protocols.

2.3.1. Calf Circumference

Calf circumference of each leg was measured twice at the widest point of the calf with a measuring tape (Seca 200, Germany), to the nearest half centimetre. The participant was measured in seated position with the feet flat on the ground. When a participant wore compression stockings, these were not removed. If the difference between the two measurements exceeded 1 cm, the procedure was repeated (Elbers et al. 2022). The result of the leg with the highest CC was used in the analysis, based on the expectation that this limb would have greater muscle mass. This selection was considered more appropriate for comparison with muscle mass measurements derived from BIA measurement.

2.3.2. Bioelectrical Impedance Analysis

After measuring the CC, BIA measurements were taken with the Tanita Body Composition Analyzer MC‐780MA S (Tanita, Tokyo, Japan) was used. In young healthy adults, the device has been found to correlate strongly with DXA in assessing fat free mass (Velazquez‐Alva et al. 2014; Verney et al. 2015). One study found a moderate sensitivity and specificity of the Tanita MC‐780MA for recognising low muscle mass in elderly compared to a DXA scan (van den Helder et al. 2022).

The Tanita MC‐780MA S is an eight‐electrode and multifrequency device that is intended for professional use. It uses electrical conductivity to estimate body composition through the hands and feet of the participant (Cruz‐Jentoft et al. 2019; Sergi et al. 2017). Additionally, the device requires height, sex and age to estimate muscle mass. Measurements were conducted according to the manufacturer's guidelines, and standard quality control procedures were followed to ensure reliability. No calibration statistics are available for the device used in this study. The participant stands barefoot on the BIA device without external support for the measurement to be successful. Measurements were done in the same room, at the same day of the week and at the same time for each participant. For this study, we used the following outcomes from BIA: skeletal muscle mass (SMM, kg), segmental muscle mass of each leg (SegMM, kg) and skeletal muscle index (SMI, kg/m2). The SMI is equivalent to the appendicular SMM (the SMM of only the arms and legs) divided by height squared and is reported as kg/m2. Considering CC strictly involves the lower extremities, SegMM of the leg is expected to show a higher correlation with CC.

2.3.3. Participant Characteristics

Age, sex and level of ID were collected from medical records. During baseline measurements weight, height and BMI were also measured. Weight and BMI were measured with BIA and height with a measuring tape (Elbers et al. 2022).

2.4. Statistical Analysis

We used percentages or means with standard deviations to describe the participant characteristics (age, sex, level of ID, weight, height and BMI).

To assess the construct validity of CC, we determined the correlation between CC and BIA (SMM, SegMM and SMI) measurements at T0. If T0 was missing, we used the measurement from T1, and if T1 was missing, we used the measurement from T2. We used the SegMM of the same leg as the highest CC. If both legs had the same CC, the SegMM of the left leg was used. The Pearson's correlation coefficient was used to assess the correlation between CC, and SMM, SegMM and SMI. The correlation coefficients were classified as minor (0.0–0.1), weak (0.1–0.39), moderate (0.4–0.69), strong (0.7–0.89) or excellent (0.9–1.0) (Schober et al. 2018).

For the intrarater reliability, we used two measurements of CC at T0, T1 or T2, done by the same trained researcher. The intrarater reliability of the CC was analysed using the intraclass correlation coefficient (ICC, single rater, absolute agreement and two‐way mixed‐effects model). A confidence interval of 95% was applied. The ICC was categorised as poor (< 0.5), moderate (0.5–0.75), good (0.75–0.9) or excellent (> 0.9) (Koo and Li 2016). Additionally, a Bland–Altman plot was used to illustrate the agreement between the repeated CC measurements. The difference between the repeated CC measurements was plotted against the mean of both CC measurements. The systematic bias was calculated as the mean of the differences with a one‐sample T test, and the limits of agreement were set at two standard deviations above and below this mean. IBM SPSS statistics Version 28.0.1.0 (142) was used for all statistical analysis.

3. Results

3.1. Participant Characteristics

A total of 36 participants were included in the PRET study. Of all participants, two out of three baseline measurements, performed by the same researcher, were available and therefore eligible for this study. The participant characteristics are presented in Table 1. The participants had a mean age of 55.58 years (SD 12.89), 19 (52.8%) were men and 21 (58.3%) had a mild ID. One participant had severe ID, which we found out after the participant completed the intervention. The inclusion criterion for level of ID was based on the anticipation that PRET would not be feasible for adults with severe and profound ID. Because this participant successfully participated in PRET, we decided to include this participant in the analysis.

TABLE 1.

Participant characteristics.

N = 36 Mean ± SD
Age Years 55.58 ± 12.89
Sex Male, n (%) 19 (52.8%)
Female, n (%) 17 (47.2%)
Level of ID Mild, n (%) 21 (58.3%)
Moderate, n (%) 14 (38.9%)
Severe, n (%) 1 (2.8%)
Cause of ID Congenital 5 (13.9%)
Perinatal 3 (8.3%)
Unknown 28 (77.8)
Syndrome Down syndrome 1 (2.8%)
Velocardiofacial 1 (2.8%)
Williams 1 (2.8%)
Other 3 (8.3%)
Unknown 30 (83.3%)
Height cm 169.61 ± 10.32
Weight kg 86.10 ± 21.52
BMI kg/m2 30.12 ± 8.42
Obese N = 35
CC at T0 cm 39.33 ± 6.49
CC at T1 or T2 cm 39.25 ± 7.29
SMM kg 29.90 ± 6.73 a
SMI kg 8.30 ± 1.54 a
SegMM kg 9.02 ± 2.08 a
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Abbreviations: BMI, body mass index; CC, calf circumference; ID, intellectual disability; SD, standard deviation; SegMM, segmental muscle mass; SMI, skeletal muscle mass index; SMM, skeletal muscle mass.

a

N = 35.

3.2. Construct Validity of the Calf Circumference

For the analysis to assess the construct validity of calf circumference, 35 participants were included. One participant was excluded from these analyses because the BIA measurement could not be completed due to ataxia. The means of the SMM, SegMM and SMI are shown in Table 2.

TABLE 2.

Reliability statistics.

Outcome Value SD 95% CI p value
Intraclass correlation (ICC) 0.94 0.89–0.97 < 0.001
Mean (bias) 0.08 2.43 −4.68‐4.84 0.419
β (difference ~ mean) −0.12 0.06 0.05
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There was a statistically weak nonsignificant Pearson's correlation between CC and SMM (r = 0.19, 95% CI [−0.16‐0.49]), a moderate significant correlation between CC and SegMM (r = 0.60, 95% CI [0.33–0.78]) and a moderate significant correlation between CC and SMI (r = 0.69, 95% CI [0.47–0.83]).

3.3. Intrarater Reliability of the Calf Circumference

The analysis to assess the intrarater reliability of the CC measurement included all 36 participants. Intrarater reliability was excellent with an ICC of 0.94 (95% CI [0.89–0.97], p ≤ 0.001).

The Bland Altman plot (Figure 1) showed that on average the second CC measurement is 0.08 cm (95% CI [−0.74‐0.91]) higher than the first CC measurement. This indicates that there is relatively small systematic bias between measurements. The relatively wide range in the limits of agreement (−4.68‐4.84) suggests that there was considerable variability in the differences.

FIGURE 1.

FIGURE 1

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Bland Altman plot for the calf circumference measurements.

4. Discussion

The aim of this study was to assess the construct validity of CC measurement for assessing muscle mass compared to BIA and the intrarater reliability of CC measurements in adults with ID and CVRF. We found a statistically significant moderate correlation between CC and SegMM and CC and SMI but a statistically nonsignificant weak correlation between CC and SMM. An excellent intrarater reliability was found.

The correlation between CC and SMM was weak and nonsignificant. However, for both SegMM and SMI, we found a moderate and significant correlation with CC. SMM represents the whole‐body muscle mass, whereas SegMM and SMI both do not include the muscle mass of the trunk. This could explain the better correlation between CC and SegMM and SMI. Another explanation could be that truncal muscle mass is not accurately estimated by BIA. It is known that DXA has a low accuracy for estimating truncal muscle mass due to the inability to separate intra‐abdominal organs, which could result in an overestimation or underestimation of whole‐body muscle mass (Tagliafico et al. 2022). Therefore, it is recommended by the EWGSOP2 guidelines to use SMI as a value for muscle mass when using DXA. This is probably the same for BIA measurements, which could explain why SegMM and SMI have a stronger correlation with CC.

The correlations between SMM and SMI with CC found in this study are mostly in accordance with the results that have been found previously. In elderly of the general population, previous studies found various correlations, ranging from 0.52 to 0.81 (Bohannon et al. 2016; Champaiboon et al. 2023; Ishii et al. 2014; Kawakami et al. 2020). Of these studies, only Kawakami et al. (2020) also used a Tanita device (MC‐980A). They found a strong correlation of 0.81 for men and 0.73 for woman in Japanese middle aged and elderly. Bohannon et al. (2016) conducted their study amongst European elderly and found similar correlations to ours. However, they used a different BIA.

It is known that BIA devices use different equations for different ethnicities. According to the EWGSOP2, for European elderly, the Sergi equation should be used for valid measurements with BIA (Cruz‐Jentoft et al. 2019). Because we do not know which equations the Tanita MC‐780 uses, it is not clear if the BIA results are valid for our sample, and these can be used as a reference for CC. Before using a BIA device, it is important to know which equations are used to estimate muscle mass for a good interpretation of the results.

The intrarater reliability of CC measurements found in this study is in agreement with other studies. Tunc et al. (2007) and Sharkey et al. (2018) both also found an excellent intrarater reliability. Tunc et al. (2007) found an agreement between CC measurements of 88% and Sharkey et al. (2018) found an excellent consistency of 0.94 for experts and an acceptable consistency of 0.72 for students. The difference between experts and students could indicate that knowledge and experience are important for a reliable CC measurement. These results show that there is no indication that there is a difference in intrarater reliability between adults with ID and the general population. Our Bland Altman plot showed a mean difference of 0.08 cm which is in accordance with the found ICC that there is excellent agreement between measurements. We did find considerable variability; however, this can be explained by the outliers in the data. Due to our small sample, these outliers are of great influence on the limits of agreement.

4.1. Limitations

This study gives insight in the correlations between CC measurements and muscle mass measured with BIA for adults with mild and moderate ID and CVRF. However, a few limitations can be identified in this study.

First, we used BIA as the reference for the CC measurement. Even though EWGSOP2 recognises BIA as a method for estimating muscle mass (Cruz‐Jentoft et al. 2019), a DXA scan remains the most recommended method. For future studies, a DXA scan as a gold standard reference measurement would give more valid results for the correlation with CC measurements. Additionally, we aimed to standardise the BIA measurement conditions as much as possible by conducting the measurements on the same day of the week, at the same location and at the same time. However, we did not report room temperature or hydration status, which may have been of influence on the BIA measurement.

Second, participant characteristics like age are used by the BIA for the estimation of body composition. The equations used by the BIA devices are based on the general population. Because BIA devices are susceptible to different ethnicities and body types, it is possible that a specific equation for adults with ID is needed for valid BIA measurements. Despite our efforts, the exact equations used in TANITA MC‐780 are unknown.

Third, our study sample consisted of 36 participants, allowing outliers to be more influential on results and reducing the potential for subgroup analyses. A guideline to ensure sufficient statistical power in validation studies is at least 100 participants (Prinsen et al. 2016). Because this study was part of a larger study examining the effects of progressive resistance training on cardiovascular risk factors, the sample size was not determined based on a power analysis specific to the aims of this study. Although our sample equally represents level of ID and sex, our specific inclusion criteria for ID, CVRF and physical abilities limit generalisability to the entire population of adults with ID. There is a lot of diversity within the ID population. There is a great variation in the severity and aetiology of ID (American Psychiatric Association 2013) and mobility (Evenhuis et al. 2012). Therefore, in an additional study a larger, more diverse group of adults with ID should be included.

Another limitation is the prevalence of obesity in our sample. Because our sample consists of adults with ID and CVRF, most participants were obese. From previous studies, we know that this could influence CC and BIA measurements. BIA devices can underestimate sarcopenia in people with obesity (van den Helder et al. 2022; Velazquez‐Alva et al. 2014), and CC could overestimate muscle mass in people with obesity due to fat distribution (Cruz‐Jentoft et al. 2019).

4.2. Clinical Implications and Recommendations

Considering the limitations of our study, we cannot conclude with certainty that CC is a valid measurement for muscle mass in adults with ID. The use of BIA as a reference measurement for CC measurements remains questionable because of the uncertainty of equations used and the applicability of existing equations for adults with ID. Therefore, the validity of both BIA and CC should be further investigated using a DXA scan as a gold standard reference measurement.

When the validity of CC as a measurement for muscle mass in adults with ID is established, it is a more suitable measurement for clinical practice in remote settings. To use a BIA device in clinical practice, the assessor should be well trained in using the device and have knowledge about how the device estimates body composition. This is necessary for a good interpretation of the outcomes. Furthermore, the results of different BIA devices are not interchangeable. Lastly, BIA measurements are susceptible to changes in the environment and person (Campa et al. 2021). Therefore, to get reliable repeated measurements, each measurement should be performed at the same day, time and nutritional status. A CC measurement is easy to perform, quick and cheap and does not need extensive instructions and preconditions.

Despite the limitations of our study, we still found a moderate correlation between CC measurement and SegMM and SMI. Therefore, CC measurement could still be used when diagnosing sarcopenia. Second, besides muscle mass, muscle strength is a criterion for diagnosing sarcopenia, and physical performance is an additional criterion for diagnosing severe sarcopenia (Cruz‐Jentoft et al. 2019). In a recent study in older adults with ID, Valentin et al. (2023) investigated the association between sarcopenia and 5‐year mortality. For diagnosing sarcopenia, they also used CC as a measurement for muscle mass (Valentin et al. 2023). They found a similar association as in the general population, which could indicate that using CC for diagnosing sarcopenia contributes to a valid diagnosis when used together with scores for muscle strength and physical performance.

In clinical practice, CC measurements provide a fast, practical and easily implementable tool. We do not recommend CC as a sole indicator of muscle mass because it can overestimate muscle mass when used in adults with obesity. When combined with other diagnostic criteria for sarcopenia, such as muscle strength and physical performance, these measurements are valuable for early detection and allow for timely interventions.

5. Conclusion

The excellent intrarater reliability of CC indicates that CC measurements are reliable within the same assessor for adults with ID and CVRF. However, the use of CC to estimate muscle mass compared to BIA remains questionable. We found no correlation between CC and SMM measured with BIA. The moderate correlations with BIA for SegMM and SMI, combined with the excellent intrarater reliability, suggest that CC could potentially be used as an indicator of SegMM and SMI in adults with ID if other methods are unavailable. A DXA scan remains the preferred method. These results cannot be generalised to all adults with ID, because the participants in this study were selected based on strict inclusion criteria. Further research is necessary, with a more heterogenetic sample of adults with ID and a CT or DXA scan as reference method.

Ethics Statement

The PRET study adheres to the principles of the Declaration of Helsinki, and the Medical Ethics Committee of the Erasmus MC, University Medical Center Rotterdam, the Netherlands (MEC‐2019‐0544), approved the PRET study. The person with the intellectual disability or their legal representative consented to the participation in the PRET study (Elbers et al. 2022).

Conflicts of Interest

The authors declare no conflicts of interest.

Acknowledgements

The authors would like to thank the participants that participated in the PRET study. They are also thankful for the contribution of Ipse de Bruggen, Abrona and Amarant, the three involved care providers, for the collaboration in the PRET study.

de Oude, Kirsten I. , Bonnet, Rosalie J.  E. , Elbers, Roy G. , Maes‐Festen, Dederieke A.  M. , and Oppewal, A. (2026) Measuring Muscle Mass in Adults With Intellectual Disabilities: The Reliability and Construct Validity of Calf Circumference. Journal of Intellectual Disability Research, 70: 97–104. 10.1111/jir.70060.

Funding: This study was supported by the HA‐ID Consortium (Chair of Intellectual Disability Medicine of the Erasmus Medical Center, Ipse de Bruggen, Abrona and Amarant).

Data Availability Statement

The data underlying this study are available upon request. Researchers may contact the corresponding author for access to the data used in this article.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The data underlying this study are available upon request. Researchers may contact the corresponding author for access to the data used in this article.

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