Phase angle reference values in healthy Chinese adults: A descriptive cross‐sectional study

Abstract

Background

Phase angle serves as a robust indicator of cellular integrity and overall health status. However, reference values for phase angle among healthy Chinese adults remain poorly defined.

Methods

We performed a multicenter descriptive cross‐sectional study in healthy Chinese adults from 2021 to 2024. Our primary outcome was phase angle, calculated from the relationship between resistance and reactance measured directly by bioelectrical impedance analysis. Standardized anthropometric and bioelectrical impedance analysis assessments were conducted. We examined associations of phase angle with age, sex, and body mass index using multivariable linear regression and generated sex‐, age‐, and body mass index–stratified percentiles.

Results

We analyzed 40,074 healthy adults (46.9% men; mean ± SD age 42.8 ± 12.9 years; mean ± SD body mass index 24.2 ± 3.5 kg/m²) who attended routine health examinations at three hospitals in Northern, Eastern, and Southwestern China. The mean ± SD phase angle was 5.52 ± 0.79°, with significantly higher values in men compared with women (5.95° vs 5.14°, P < 0.001). Phase angle positively correlated with body mass index (r = 0.35) and negatively with age (r = −0.20) (both P < 0.001). Peak phase angle values were observed in individuals aged 30–39 years and declined thereafter. Device type showed no significant effect on phase angle measurements.

Conclusion

We established the first large‐scale, sex‐, age‐, and bioelectrical impedance analysis–specific phase angle reference ranges for healthy Chinese adults. These normative values provide an essential foundation for clinical application of phase angle in health assessment, early disease screening, and individualized nutrition and medical interventions.

INTRODUCTION

Bioelectrical impedance analysis (BIA) is a noninvasive, rapid, and cost‐effective method for estimating body composition, demonstrating significant clinical value. ¹ , ² The phase angle, a key BIA‐derived parameter, is calculated from the relationship between resistance (R) and reactance (Xc) measured directly by BIA. ¹ , ³ , ⁴ It reflects the structural integrity of cell membranes and cellular functional status. ⁵ , ⁶ Studies indicate that higher phase angle values correlate with stronger cellular function, intact cell membranes, and better health, and lower phase angle may indicate cellular dysfunction or membrane damage, ⁵ , ⁷ , ⁸ commonly observed in pathological conditions such as cancer cachexia, chronic inflammation, and sarcopenia. ⁹ , ¹⁰ , ¹¹ However, reference values for phase angle among healthy Chinese adults remain poorly defined, with few studies available that provide a comprehensive, stratified reference range for phase angle. This gap limits the clinical utility of phase angle in assessing health status, particularly in Chinese populations, for whom body composition and metabolic profiles differ significantly from those in Western populations.

Existing evidence highlights the prognostic value of phase angle across diverse clinical scenarios. Previous studies associate low phase angle with malignancies, chronic diseases, malnutrition, and aging ¹² , ¹³ ; notably, in head‐and‐neck cancer under radiotherapy malnourished patients had 4.66° vs 5.71° in well‐nourished peers, and in poststroke rehabilitation sarcopenic patients had 4.8° vs 5.8° in those without sarcopenia. By contrast, athletes and metabolically healthy individuals typically exhibit higher phase angle values, ⁷ , ¹⁴ , ¹⁵ underscoring its potential as a positive health biomarker. Establishing population‐specific phase angle reference ranges is therefore critical for disease screening, health management, and personalized nutrition interventions.

Current phase angle reference standards predominantly focus on Western populations, ¹⁴ , ¹⁶ , ¹⁷ yet bioelectrical impedance parameters exhibit significant ethnic variations. ¹⁸ , ¹⁹ For instance, Asian populations demonstrate higher visceral fat ratios at lower body mass index (BMI) thresholds, ²⁰ and differences in body composition are known to influence the Xc/R ratio ¹ . Despite the rapid aging of the population of China, with 22.0% of the population aged >60 years in 2024, and rising adult obesity rate of 34.3%, ²¹ large‐scale phase angle reference studies for Chinese healthy adults remain scarce. Moreover, prior research often examines single factors (eg, age, sex, or BMI) independently, ¹⁶ , ²² neglecting their synergistic effects. Accordingly, we aimed to develop sex‐, age‐, and BMI‐stratified reference values for phase angle in healthy Chinese adults and to examine how these determinants jointly relate to phase angle. Our findings aim to provide precise phase angle reference values for diverse Chinese subpopulations, enhance the clinical utility of phase angle‐–based health assessments, and support the application of phase angle as a biomarker in health management.

PATIENTS AND METHODS

Study design

This multicenter cross‐sectional study aims to establish sex‐, age‐, and BMI‐stratified phase angle reference ranges for Chinese healthy adults and elucidate the interaction effects of key covariates. We performed a multicenter descriptive cross‐sectional study in healthy Chinese adults from 2021 to 2024. Data were collected from routine health examination records at three centers (Peking Union Medical College Hospital [North China], Nanjing Drum Tower Hospital Affiliated to Nanjing Medical University [East China], and Guizhou Provincial People's Hospital [Southwest China]). Our primary outcome was phase angle calculated from the relationship between R and Xc measured directly by BIA.

Participants

Participants were recruited from health examination cohorts at three regional medical centers covering major geographic regions of China. Written or verbal informed consent was obtained, and inclusion/exclusion criteria were strictly applied. We excluded participants with conditions that could interfere with BIA measurements or body composition, such as pregnancy, presence of metallic implants, severe comorbidities, or edema. Detailed inclusion and exclusion criteria are listed in the Supporting Information.

Data collection and measurements

All measurements were performed between 7:00 am and 12:00 am after overnight fasting (≥8 h) and bladder/bowel evacuation. Height was measured with a calibrated stadiometer to 0.1 cm (shoes removed, heels together, and Frankfurt plane horizontal). Weight was obtained to 0.1 kg from the integrated scale of the bioelectrical impedance analyzer (light clothing and no accessories). BMI was calculated as weight (kg)/height squared (m²). Waist and hip circumferences were obtained from the analyzer's impedance‐derived circumference module according to the manufacturer's protocol. ²³ Waist‐to‐hip ratio and waist‐to‐height ratio were computed from device‐reported circumferences and measured height. Across the three centers, a harmonized standard operating procedure was implemented with centralized training/certification, ²⁴ unified preassessment restrictions (≥8 h fast and avoidance of alcohol, caffeine, and vigorous exercise), morning measurements, daily device checks and periodic verification, standardized data entry, and routine outlier review.

BIA measurements were conducted in a standing position. At Peking Union Medical College Hospital, the Donghuayuan DBA‐610 device (50 kHz frequency) was used. Preassessment restrictions were standardized: no alcohol for 48 h, no vigorous exercise for 24 h, avoid caffeine and large meals for ≥8 h, overnight fast ≥8 h, and void the bladder within 30 min before testing; no intravenous fluids or strenuous activity before measurement. Segmental, multifrequency BIA was performed in a standing posture with eight‐point tactile electrodes following a harmonized standard operating procedure across the three centers. Participants were barefoot, soles and hands were cleaned and dried, metal accessories were removed, arms were slightly abducted (~15°) and legs shoulder‐width apart, and the room temperature was 22°C–26°C. Signal‐quality flags were reviewed and measurements were repeated if contact was unstable or impedance values were out of range. Across centers, technicians underwent centralized training and certification, devices underwent daily checks and periodic verification, data entry fields (age, sex, and measured height) were standardized, and outliers were routinely reviewed. Phase angle was calculated as:

Phase angle (°) = arctan(Xc/R) × (180/π)

where Xc = reactance and R = resistance. Additional BIA‐derived parameters included waist‐to‐hip ratio, waist‐to‐height ratio, fat‐free mass (FFM), body fat mass (BFM), percentage body fat (PBF), and skeletal muscle mass (SMM). All procedures followed standardized protocols by trained operators.

To ensure consistency across devices (DBA‐610 vs InBody 770), 30 participants underwent repeated measurements. Results showed excellent correlation (Pearson r = 0.993, P < 0.001) and Bland‐Altman agreement. Linear regression analysis yielded: y = −2.25 + 1.36x (Figure S1).

Statistical analysis

Phase angle data were stratified by sex (male/female), age (<18, 18–29, 30–39, 40–49, 50–59, and ≥60 years), and BMI (15–18.5, 18.5–28, and 28–35 kg/m²). Excess adiposity was defined as PBF > 25% (men) or >30% (women). ²⁵

Normality of phase angle distribution was assessed via histograms and P‐P plots. Continuous variables are presented as mean ± SD. Pearson correlation coefficients and heatmaps evaluated associations. Univariate and multivariate linear regression models assessed individual and combined effects of age, sex, and BMI on phase angle (R ² reported). Interaction effects between BMI and age were analyzed by centering variables and including interaction terms in regression models. Group comparisons used independent t tests and analysis of variance.

Sensitivity analyses employed analysis of covariance (ANCOVA) and multivariate regression to evaluate device effects after balancing sample sizes and adjusting for sex, age, and BMI. Analyses were performed using SPSS (version 27.0) and R (version 4.0.2). Significance testing was performed with the use of a two‐sided alpha level of 0.05.

Ethics and informed consent

This study was approved by the Ethics Committee of Peking Union Medical College Hospital (no. HS‐3068) and adhered to the Declaration of Helsinki. All participants provided written informed consent.

RESULTS

Baseline characteristics of participants

A total of 40,074 healthy adults (46.9% male) were included in this study. As shown in Table 1, men exhibited significantly higher FFM (51.71 ± 6.81 kg vs 38.55 ± 5.10 kg) and SMM (28.89 ± 4.12 kg vs 20.79 ± 3.05 kg) compared with women (P < 0.001). In contrast, BFM (19.65 ± 6.38 kg vs 19.17 ± 6.53 kg) and PBF (33.10 ± 6.16% vs 26.49 ± 6.13%) were significantly higher in women than in men (P < 0.001). Baseline anthropometric characteristics are also summarized by age group (18–29, 30–39, 40–49, 50–59, and ≥60 years) and presented separately for men and women (Tables S1–S2).

Table 1.

Baseline characteristics of participants.

Characteristics	Total (N = 40,074)	Male (n = 18,801)	Female (n = 21,273)	P value
Age, mean (SD), y	42.8 (12.9)	43.4 (13.1)	42.4 (12.7)	<0.001*
Age, median (IQR), y	42.0 (32.0–53.0)	43.0 (32.0–53.0)	42.0 (32.0–52.0)	<0.001†
Male, n (%)	18,801 (46.9)	–	–	–
Obesity, n (%)	6044 (15.1)	3466 (18.4)	2578 (12.1)	<0.001‡
Weight, mean (SD), kg	64.2 (12.4)	70.8 (11.4)	58.2 (10.0)	<0.001*
BMI, mean (SD), kg/m2	24.2 (3.5)	25.0 (3.4)	23.6 (3.6)	<0.001*
WHR, mean (SD)	0.89 (0.06)	0.91 (0.06)	0.88 (0.05)	<0.001*
WHtR, mean (SD)	0.52 (0.06)	0.53 (0.06)	0.52 (0.06)	<0.001*
PhA, mean (SD), °	5.5 (0.8)	6.0 (0.6)	5.1 (0.7)	<0.001*
FFM, mean (SD), kg	44.7 (8.9)	51.7 (6.8)	38.6 (5.1)	<0.001*
BFM, mean (SD), kg	19.4 (6.5)	19.2 (6.5)	19.7 (6.4)	<0.001*
PBF, mean (SD), %	30.0 (7.0)	26.5 (6.1)	33.1 (6.2)	<0.001*
SMM, mean (SD), kg	24.6 (5.4)	28.9 (4.1)	20.8 (3.1)	<0.001*

Abbreviations: BFM, body fat mass; BMI, body mass index; FFM, fat‐free mass; PBF, percentage body fat; PhA, phase angle; SMM, skeletal muscle mass; WHR, waist‐to‐hip ratio; WHtR, waist‐to‐height ratio.

^* t Test.

^† Mann‐Whitney U test.

^‡ Chi‐square test.

Phase angle correlation analysis

The correlations between phase angle and other parameters are illustrated in Figure 1. The mean phase angle was 5.52 ± 0.79°, with significantly higher values in men compared with women (5.95 ± 0.64° vs 5.14 ± 0.71°; P < 0.001). Phase angle showed a significant positive correlation with BMI (r = 0.35, P < 0.01) and a significant negative correlation with age (r = –0.20, P < 0.01). Additionally, phase angle was strongly positively correlated with FFM and SMM, whereas a negative correlation was observed with PBF.

Figure 1.

Heatmap of correlation analysis between phase angle and related variables. All correlations between variables were statistically significant (P < 0.01). Sex: men = 1 and women = 0. BFM, body fat mass; BMI, body mass index; FFM, fat‐free mass; PBF, percentage body fat; SMM, skeletal muscle mass; WHR, waist‐to‐hip ratio; WHtR, waist‐to‐height ratio.

Univariate regression analysis revealed that for each 1‐year increase in age, phase angle decreased by 0.01° (β = −0.01, P < 0.001), whereas each 1 kg/m² increase in BMI was associated with a 0.08° increase in phase angle (β = 0.08, P < 0.001). Men exhibited significantly higher phase angle than women (β = 0.81, P < 0.001).

In the multivariate regression model, age (β = −0.273, P < 0.001), sex (β = 0.52, P < 0.001), and BMI (β = 0.312, P < 0.001) were all independent predictors of phase angle. The model explained 47.6% of the variance in phase angle (R² = 0.476), indicating that nearly half of the variability in phase angle could be predicted by age, sex, and BMI. However, a multivariate model incorporating only age and sex explained only 38.3% of the variance.

Interaction effects

After introducing interaction terms, significant interactions were observed between age and sex (P < 0.05) and between age and BMI (P < 0.05). The model's explanatory power (R ²) increased marginally from 0.476 to 0.484 and 0.477, respectively, suggesting modest moderating roles of sex and BMI in the relationship between age and phase angle. In contrast, interactions involving BMI and sex, as well as the three‐way interaction among age, sex, and BMI, were nonsignificant (P > 0.05). Thus, phase angle variation was predominantly driven by the independent effects of age, sex, and BMI, with minimal contribution from interaction effects.

Reference ranges of phase angle in healthy adults

Mean phase angle stratified by sex, age, and BMI

As shown in Table 2, men exhibited consistently higher phase angle values than women across all age and BMI subgroups. Within each BMI stratum, mean phase angle increased progressively with higher BMI in both sexes and all age groups. In the 15 ≤ BMI < 18.5 kg/m² group, phase angle declined gradually with advancing age among men. Conversely, in women within the same BMI range and other BMI categories (18.5 ≤ BMI < 28 kg/m² and 28 ≤ BMI < 35 kg/m²), phase angle peaked in the 30–39 age group and subsequently decreased with age. Notably, obese older adults demonstrated lower phase angle values compared with younger lean individuals. For example, men aged ≥60 years with BMI ≥ 35 kg/m² had a mean phase angle of 5.56 ± 0.61°, whereas young adult men (18–29 years) with 15 ≤ BMI < 18.5 kg/m² showed a maximum mean phase angle of only 5.46 ± 0.58°. Similar trends were observed in women.

Table 2.

Mean phase angle stratified by sex, age, and BMI groups.

BMI group, kg/m2	Age group, y	Men		Women		P value*
		n	Mean (SD)	n	Mean (SD)
15.0 to <18.5	18–29	193	5.5 (0.6)	533	4.7 (0.5)	<0.001
	30–39	114	5.4 (0.5)	271	4.8 (0.5)	<0.001
	40–49	49	5.2 (0.5)	68	4.7 (0.6)	<0.001
	50–59	55	5.1 (0.6)	77	4.6 (0.6)	<0.001
	≥60	59	4.6 (0.7)	51	4.3 (0.5)	0.02
18.5 to <28.0	18–29	2319	6.1 (0.6)	3014	5.1 (0.5)	<0.001
	30–39	3906	6.1 (0.5)	4773	5.2 (0.5)	<0.001
	40–49	3223	6.0 (0.5)	4087	5.2 (0.5)	<0.001
	50–59	3475	5.8 (0.6)	4165	5.0 (0.5)	<0.001
	≥60	1942	5.3 (0.6)	1656	4.8 (0.5)	<0.001
28.0 to <35.0	18–29	589	6.4 (0.6)	435	5.5 (0.5)	<0.001
	30–39	1079	6.4 (0.5)	707	5.7 (2.6)	<0.001
	40–49	827	6.2 (0.5)	576	5.5 (0.5)	<0.001
	50–59	718	6.0 (0.6)	613	5.4 (0.5)	<0.001
	≥60	253	5.6 (0.6)	247	4.9 (0.6)	<0.001

Abbreviation: BMI, body mass index.

^* P values compare men and women within each stratum using t tests.

Phase angle percentile plots stratified by sex, age, and BMI groups

Figure 2 displays the percentile plots of phase angle across sex‐, age‐, and BMI‐specific subgroups. In all subgroups except men aged >60 years with BMI < 18.5 kg/m² (phase angle: 3.4° vs 3.5° in women), men exhibited higher phase angle values at every percentile compared with women. Within the same BMI group, phase angle declined with advancing age. However, in some BMI strata (eg, 18.5 ≤ BMI < 28 kg/m²), phase angle peaked in the 30–39 age group. In women, the median phase angle peaked in the 30–40 age group and increased progressively with higher BMI (4.8° vs 5.2° vs 5.6°), followed by a gradual decline. In men, for BMI < 18.5 kg/m² and 18.5 ≤ BMI < 28 kg/m², the median phase angle peaked in the 18–29 age group. For BMI ≥ 28 kg/m², the median phase angle peaked in the 30–39 age group, after which it declined with age.

Figure 2.

Phase angle percentile plots stratified by sex, age, and BMI groups. BMI, body mass index.

Phase angle distribution stratified by PBF

Table 3 presents phase angle values grouped by the presence of excess adiposity (defined as PBF > 25% in men or >30% in women) within the same BMI categories. Across all subgroups, individuals with excess adiposity exhibited significantly lower phase angle values compared with those with normal adiposity (P < 0.05). Findings were similar in men and women (Tables S3–S4).

Table 3.

Mean phase angle stratified by BMI and presence of excess adiposity.

BMI, kg/m2	Excess adiposity group, mean (SD)	Normal adiposity group, mean (SD)	P value*
15 ≤ BMI < 18.5	4.2 (0.5)	4.9 (0.6)	<0.01
	n = 42	n = 1428
18.5 ≤ BMI < 28	5.4 (0.7)	5.6 (0.7)	<0.01
	n = 20,569	n = 11,991
28 ≤ BMI < 35	5.9 (1.1)	6.5 (1.0)	<0.01
	n = 5953	n = 91

Note: Excess adiposity was defined sex‐specifically as percentage body fat > 25% for men and >30% for women.

Abbreviation: BMI, body mass index.

^*Mean (SD) phase angle values were compared between the excess and normal adiposity groups using t tests.

Sensitivity analysis

The ANCOVA results indicated that machine type had no significant effect on phase angle measurements (P > 0.05). Multivariate regression analysis further confirmed the nonsignificance of the machine type variable in the model (P > 0.05), indicating that the machine type did not significantly influence phase angle measurements. The robustness of the study findings was thus validated.

DISCUSSION

This multicenter cross‐sectional study, involving 40,074 healthy Chinese adults from diverse regions, established the first sex‐, age‐, and BMI‐stratified reference values for phase angle. The results demonstrated that men exhibited significantly higher phase angle than women (mean: 5.95° vs 5.14°). Phase angle peaked in the 30–39 age group for most subgroups, except for underweight men (BMI < 18.5 kg/m²), whose phase angle peaked in the 18–29 age group before declining with age. Phase angle increased with higher BMI, and multivariate regression analysis identified age, sex, and BMI as independent predictors of phase angle, collectively explaining nearly half of its variability (R² = 0.476). These reference values provide critical scientific evidence for health assessments and personalized health management in the Chinese population.

Low phase angle has been consistently linked to health risks such as malnutrition and chronic diseases, ²⁶ , ²⁷ , ²⁸ with numerous studies highlighting its prognostic value in predicting mortality across conditions like renal disease, cancer, and infections. ²⁹ , ³⁰ , ³¹ , ³² Establishing population‐specific phase angle reference ranges holds significant clinical and public health relevance, ²⁹ , ³³ enabling precise health evaluations, optimized disease screening, and tailored nutrition interventions. Our multidimensional stratification (age, sex, and BMI) further supports individualized health strategies.

The observed sex difference in phase angle aligns with prior studies. ¹⁴ , ¹⁹ , ³⁴ , ³⁵ , ³⁶ The observed sex differences in phase angle may be attributed to distinct body composition profiles between men and women. ³⁷ Men typically exhibit higher muscle mass and lower PBF, ⁸ , ³⁶ and phase angle is strongly associated with muscle mass. ⁸ , ⁹ , ³⁸ In this study, a robust positive correlation was observed between phase angle and SMM (r = 0.57). For example, Italian studies reported higher phase angle values in male and female athletes aged 20–30 years (7.7° and 6.8°, respectively), ¹⁴ compared with the general population of the same age group (7.3° and 6.2°). ³⁹ This discrepancy likely stems from athletes’ greater muscle mass.

Regarding the relationship between phase angle and age, this study revealed a declining trend in phase angle with advancing age, consistent with findings from prior studies. ¹⁸ , ⁴⁰ With aging, the integrity of cellular membranes and cellular function gradually decline. ⁴¹ Additionally, advancing age is generally accompanied by a decrease in muscle mass and an increase in adiposity. ⁴¹ , ⁴² Consequently, studies have suggested that phase angle may serve as a biomarker of cellular health and aging. ³⁵ , ⁴³

Regarding the relationship between phase angle and BMI, this study identified a significant positive correlation between phase angle and BMI. Existing literature reports conflicting conclusions about the phase angle–BMI relationship. ¹⁸ , ³⁴ , ⁴⁴ , ⁴⁵ Some studies suggest that individuals with higher BMI may exhibit greater cell volume and muscle mass, leading to higher phase angle values. ⁴⁶ Additionally, phase angle is directly associated with the quantity and functional status of cell membranes, represented by reactance (Xc). Because individuals with higher BMI may have a greater number of cells, this theoretically supports higher phase angle values. ⁴⁷ However, other studies argue that excessively high BMI may reflect excess adiposity, and thus the increase in phase angle might only occur within specific BMI ranges. ⁴⁴ , ⁴⁵ Previous research observed declines in phase angle among individuals with BMI > 35 kg/m² or >40 kg/m², ⁴⁴ , ⁴⁵ but our study did not include such populations, potentially explaining the absence of phase angle reduction in obese individuals. Some studies also reported no significant difference in phase angle between obese and general populations, ³⁴ although age‐related effects were not accounted for. Although further comprehensive and large‐scale studies are needed to clarify the phase angle–BMI relationship, our findings confirm that phase angle is unequivocally influenced by BMI within the general BMI range (15–35 kg/m²) in healthy individuals.

Regarding ethnic and regional differences, the phase angle reference values established in this study for the Chinese healthy population demonstrate marked discrepancies compared with other populations. An Italian study reported mean phase angle values of 6.9° in men and 6.1° in women. ³⁹ A Brazilian study analyzing racial and ethnic differences in phase angle identified significant variations (P < 0.001): 6.55 ± 1.10° (Asian), 6.82 ± 1.13° (White), 7.00 ± 1.01° (mixed race), 7.21 ± 1.19° (Black), 7.33 ± 1.13° (Hispanic), and 7.45 ± 0.98° (other ethnicities). ⁴⁸ Our findings indicate that Chinese individuals exhibit lower phase angle values than these populations. These ethnic disparities in phase angle may be attributed to genetic differences, dietary patterns, lifestyles, and body composition characteristics. ⁴⁹ , ⁵⁰ Such differences underscore the necessity of incorporating ethnicity‐specific considerations when establishing phase angle reference values to enhance their clinical applicability and precision.

The key strengths of this study include the large sample size (N = 40,074) recruited from three major medical centers in North, East, and Southwest China, enhancing generalizability. By providing sex‐, age‐, and BMI‐stratified subgroups, this study establishes precise reference values and highlights the importance of BMI stratification. Furthermore, sensitivity analyses confirmed measurement consistency across BIA devices, and multivariate regression with interaction analysis comprehensively evaluated phase angle determinants. However, several limitations should be acknowledged. Despite the large sample, sourcing data from only three hospitals may introduce regional biases. The descriptive cross‐sectional design precludes causal inferences or dynamic tracking of phase angle changes over time. Additionally, lifestyle and dietary confounders were not fully controlled, and minor interdevice variations might affect precision despite validation. The lack of smoking/comorbidity data may limit external comparability; however, given that reference values are derived from apparently healthy examinees, the cohort is expected to have low prevalence of chronic disease, and our sex‐, age‐, and BMI‐stratified reference ranges remain informative for clinical interpretation. Future longitudinal studies with multiethnic cohorts are needed to further elucidate phase angle dynamics.

CONCLUSION

Based on multicenter large‐sample data from China, this study established the first sex‐, age‐, and BMI‐stratified reference ranges for phase angle in healthy adults. The results demonstrate that phase angle is significantly influenced by sex (higher in men), BMI (positive correlation), and age (negative correlation). These findings provide essential baseline data for health assessments and disease screening while offering scientific evidence for the application of phase angle in personalized nutrition interventions and disease management. The reference values derived from this study can be widely applied in clinical practice to accurately evaluate individual health status, optimize health management strategies, and lay the groundwork for future research on phase angle across diverse ethnic groups, regions, and specific disease populations.

AUTHOR CONTRIBUTIONS

Na Yang contributed to the review and editing, original draft, software, resources, methodology, investigation, formal analysis, and conceptualization. Wanyang Li contributed to the review and editing, methodology, and data curation. Mingyao Sun contributed to the review and editing, visualization, methodology, and investigation. Xiaodong Shi contributed to the methodology and formal analysis. Rongrong Li contributed to the review and editing and validation. Wei Chen contributed to the review and editing, original draft, supervision, project administration, methodology, formal analysis, and conceptualization.

CONFLICT OF INTEREST STATEMENT

None declared.

Supporting information

supplement.

Supplement Figure 1.

DATA AVAILABILITY STATEMENT

The datasets generated and/or analyzed during the current study are not publicly available because of confidentiality agreements with participants.