Spinopelvic alignment in asymptomatic adults: a global meta-analysis quantifying heterogeneity and proposing a functional parameter hierarchy

Article information

Asian Spine J. 2026;.asj.2025.0532

Publication date (electronic) : 2026 April 23

doi : https://doi.org/10.31616/asj.2025.0532

Department of Human Anatomy and Histology, The First Moscow State Medical University (Sechenov University), Moscow, Russian Federation

Corresponding author: Yanis Shavlovskiy, Department of Human Anatomy and Histology, Sechenov University, Mokhovaya Street 11, Building 10, Moscow 125009, Russian Federation, Tel: +7-495-629-76-57, Fax: +8-495-629-76-57, E-mail: shavlovskiy_ya@staff.sechenov.ru

Received 2025 September 1; Revised 2025 October 21; Accepted 2025 December 4.

Abstract

Study Design

Meta-analysis.

Purpose

This PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses)-compliant meta-analysis aimed to quantify global variation in spinopelvic parameters among asymptomatic adults, distinguish population-invariant from adaptive components, and propose a clinically relevant parameter hierarchy.

Overview of Literature

High variability in sagittal spinal alignment is well established. However, a meta-analysis employing standardized methodology to quantify the heterogeneity and stratify findings by geographic region has not been conducted.

Methods

This systematic review identified 140 studies reporting 15 types of radiographic measurements in healthy 18–60-year-old individuals (n=1,229–15,251 subjects) from PubMed, Academia, and ResearchGate up to June 2025. The National Institutes of Health Quality Assessment Tool was used to assess the risk of bias. Parameters were regional spine curvatures, pelvic parameters, and global alignment measures. Random-effects models generated pooled estimates with 95% prediction intervals (95% pelvic incidence [PI]). Meta-regression was performed for geographic subgroup comparison.

Results

All parameters demonstrated substantial heterogeneity (I², 72%–98%), irreducible by demographic stratification. Pelvic tilt (PT) exhibited consistently low variability across populations (95% PI <5°). Bicoxofemoral axis-referenced angles—including T1 and T9 PT (T₁PT and T₉PT), and T1 pelvic angle (TPA)—demonstrated low variability in the available cohorts (95% PI <5°), indicating potential stability, but require further validation. The regional spine curvatures—including cervical lordosis, thoracic kyphosis, and lumbar lordosis—varied widely (95% PI >10°). PT was uniquely conserved across geographic subgroups (Δ<1°, p=0.58), with sacral slope (SS) and PI demonstrating population-specific adaptations. Major limitations include the high heterogeneity of data, measurement variability across the included studies, and the low number of included studies reporting T₁PT, T₉PT, and TPA.

Conclusions

We propose a functional hierarchy of spinopelvic parameters based on their observed heterogeneity—from stable “core” to variable “adaptive” components. Future research is warranted to validate the potential population-invariance of currently underreported bicoxofemoral axis-referenced parameters and to evaluate whether correction strategies focused on these stable elements improve surgical outcomes.

Keywords: Spinal curvatures; Postural balance; Pelvimetry; Population characteristics

Introduction

Over the past 30 years, the number of publications that address various aspects of spinal sagittal alignment has dramatically increased. Since the introduction of the “conus of balance” concept by Dubousset [1] and landmark studies by Duval-Beaupere et al. [2], Legaye et al. [3], and Jackson and McManus [4], significant efforts have been made to understand the logic behind the highly variable normative spinopelvic balance data, stratified based on sex, age, and ethnicity [5]. This interest is well justified, and clinicians depend on such data to define therapeutic goals for correcting spinal deformities, whereas researchers in fundamental science use them to develop realistic biomechanical models of the spine [6].

However, the outcomes of surgical interventions aimed at restoring spinopelvic balance remain mediocre, despite the substantial volume of collected data [7]. Further, the considerable variability in spinal configurations among healthy, asymptomatic individuals raises skepticism about establishing definitive “normative values” [8].

This study aims to analyze global normative data on sagittal alignment and rank parameters by their mechanistic contribution to vertical balance, thereby separating primary drivers (essential for equilibrium) from adaptive compensations (responsive to imbalance). This framework may refine surgical targets and reduce variability in outcomes.

Materials and Methods

Study design

The literature review adhered to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines [9]. A systematic search of PubMed was conducted on May 22, 2025. The search strategy used the following key terms: (“spinopelvic+balance” OR “sagittal+alignment” OR “sagittal+balance” OR “global+alignment”). The search was limited to studies published between 1995 and 2025 and supplemented by citation searches in Academia and ResearchGate up to June 1, 2025. Considering the high volume of initial search results, the generative artificial intelligence (AI) tools were employed to help remove duplicates and the preliminary screening of clearly irrelevant articles based on title and abstract (see PRISMA flow diagram, Fig. 1). To minimize potential bias, the AI role was limited to this initial, repetitive task. Human reviewers manually performed all subsequent steps. Reviewer 1 performed title and abstract screening. Two reviewers (1 and 2) independently conducted full-text screening, and conflicts were resolved through discussion in all cases. Reviewer 1 extracted selected data into a predefined spreadsheet, and reviewer 2 verified them for accuracy and completeness. Discrepancies were resolved by consensus. The analysis excluded any unclear or missing data. The National Institutes of Health Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies was employed to assess the risk of bias of individual studies. Two reviewers (1 and 2) independently performed assessments.

Fig. 1

PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagram of the search and selection process.

Inclusion criteria

Studies were selected based on the following criteria:

Imaging methodology

Lateral or biplane radiography (EOS; EOS imaging, Paris, France) is performed in a natural vertical standing position with horizontal gaze.

Study population

(1) Asymptomatic/healthy adults (aged 18–60 years) without significant spinal deformities, sacralization, lumbarization, or evident spinal pathology, hip or sacroiliac joint disorders, and spinal surgery history. (2) If age stratification was unavailable, ≥80% of the study population had to fall within the 18–60 range. (3) Body mass index of <30 kg/m² (where reported with stratification) to minimize the potential confounding effects of obesity on spinal alignment and posture. (4) Sample size of ≥20 subjects to ensure a minimum threshold for statistical reliability in parameter estimation.

Required radiographic parameters (measured using standardized methods)

(1) Cervical lordosis (CL): C₀–C₂ (MacGregor line to C₂ lower endplate) and C₂–C₇ (C₂ to C₇ lower endplate). (2) Thoracic kyphosis (TK): T₁–T₁₂ kyphosis (T₁ upper to T₁₂ lower endplate) and T₄–T₁₂ kyphosis (T₄ upper to T₁₂ lower endplate). (3) T₁ slope (T₁S). (4) Lumbar lordosis: L₁–S₁ (L₁ to S₁ upper endplate). (5) Sacral slope (SS), pelvic tilt (PT), and pelvic incidence (PI). (6) Sagittal vertical axis (SVA): SVA C₂–C₇ offset between the vertical line through the center of the odontoid process of C₂ and through the center of C₇. SVA C₇–S₁ offset between the vertical line through the center of C₇ and through the posterosuperior point of S1 upper endplate. (7) T₁ pelvic angle (TPA) (T₁ center, bicoxofemoral axis, and S₁ upper endplate center). (8) Spinosacral angle (SSA) (C₇ center, S1 upper endplate center, S₁ slope). (9) T₁ PT (T₁PT) (vertical tilt of line connecting T₁ center to bicoxofemoral axis). (10) T₉ PT (T₉PT) (vertical tilt of line connecting T₉ center to bicoxofemoral axis).

Exclusion criteria

Exclusion criteria are as follows: (1) Studies with overlapping participant cohorts (e.g., same authors reporting identical parameters across multiple papers) were identified systematically. Only the dataset with the largest sample size or most detailed methodology was included for such cases. Only non-repetitive values were analyzed when studies shared partial data (e.g., a subset of parameters). (2) Studies lack clear measurement methodology.

Ethnicity/geographic stratification

If ethnicity was not specified directly, geographic subregions were assigned based on study location or ethics committee affiliation (if applicable). Studies were categorized into three subgroups based on geographic region: (1) Group #1 (Western): Europe (France, Belgium, Netherlands, Hungary, and Germany), North America (Canada, United States, and Mexico), Brazil, and Australia. (2) Group #2 (Western/Southwestern Asia): Turkey, Lebanon, Iran, and India. (3) Group #3 (Eastern/Southeastern Asia): Japan, Korea, China, Singapore, and Malaysia. Subgroup comparisons were performed only if ≥4 studies were available per subgroup to ensure statistical robustness.

Statistical analysis and software

Numbers ver. 14.0 (Apple Inc., Cupertino, CA, USA) was used to manage and prepare data for synthesis. All statistical analyses were conducted in the R programming language using RStudio ver. 2024.12.1+563 (Posit Software; PBC, Boston, MA, USA) with the ‘metafor’ package. Adobe Illustrator ver. 29.2.1 (Adobe Inc., San Jose, CA, USA) was used for the graphical synthesis of forest plots. Generative AI (DeepSeek, Hangzhou, China) was used to assist in the preparation of R code and for grammar and style editing of the manuscript. A funnel plot was used to visually assess potential publication bias, and Egger’s linear regression test was used for statistical analysis.

All radiographic parameters were continuous; therefore, the effect measure was the mean value, and the synthesis aimed to estimate the overall pooled mean with 95% confidence intervals (95% CI) derived using random-effects meta-analysis. Mixed-effects meta-regression was applied with the Wald-type tests and adjusted for small-sample bias via the Knapp-Hartung modification for geographic subgroup comparisons [10]. I² and τ² statistics were used to quantify heterogeneity. The Higgins method was employed to derive 95% prediction intervals (95% PI) [11].

Registration and protocol

This systematic review was not registered. A post-hoc protocol detailing the study selection process, data extraction items, and planned statistical analyses has been made publicly available on the Open Science Framework platform along with all extracted data and analysis code: https://osf.io/cvhaz/?view_only=409d7d6206794082baa272a240bcebde.

Results

The final meta-analysis included 140 articles. Table 1 summarizes the key demographic characteristics and reported sagittal alignment parameters across all included studies [4,12–150]. The number of studies per radiographic parameter ranged from nine (for T₁PT) to 98 (for PI), with the number of included subjects ranging from 1,229 (T₉PT) to 15,251 (PI). Table 2 summarizes the random-effect model data for all investigated spinopelvic alignment parameters. The p-value for the test for heterogeneity (Q statistic) was <0.0001 for all evaluated parameters. The potential for publication bias was assessed for all parameters included in a meta-analysis. The results of Egger’s regression test for funnel plot asymmetry indicate potential bias for parameters of the cervical spine and cranio-cervical junction (C₀–C₂ lordosis, p<0.001; C₂–C₇ lordosis, p=0.04; SVA C₂–C₇, p=0.03, and T₁ slope, p<0.02). No significant statistical evidence of publication bias was detected for all other parameters (p>0.05). This includes parameters with fewer than 20 studies, including TPA, SSA, T₁PT, and T₉PT. Supplementary Files provide the corresponding funnel plots.

Table 1

Summary of demographic data and reported parameters

Table 2

Random-effect model data summary

Geographic subgroup comparisons (groups 1–3) were performed for several key parameters: CL (C₂–C₇), TK (both T₁–T₁₂ and T₄–T₁₂), LL (L₁–S₁), sagittal vertical axis (SVA C₇–S₁), and pelvic parameters, including SS, PT, PI, and T₁ slope. Most notably, PT was uniquely conserved across geographic subgroups, demonstrating a non-significant difference of <1° (p=0.58). For CL (C₀–C₂), SVA C₂–C₇, TPA, and SSA, only two-group comparisons (group #1 vs. group #3) were possible due to limited data availability in group #2. Meta-regression analysis was not conducted for T₁ and T₉ PT parameters as <4 studies per subgroup were available.

Figs. 2 –6 illustrate the forest plots with the meta-regression outcomes for all comparable parameters.

Fig. 2

Geographic variation in cervical lordosis (C₀–C₂, C₂–C₇) and thoracic kyphosis (T₁–T₁₂, T₄–T₁₂): forest plots and meta-regression analysis. CI, confidence interval.

Fig. 3

Geographic differences in sagittal vertical axis (SVA) (C₂–C₇, C₇–S₁), T₁ slope, and spino-sacral angle: forest plots and meta-regression results. CI, confidence interval.

Fig. 4

Forest plots and meta-regression results depicting geographic subgroup differences in lumbar lordosis and pelvic tilt. CI, confidence interval.

Fig. 5

Forest plots and meta-regression results depicting geographic subgroup differences in sacral slope and pelvic incidence. CI, confidence interval.

Fig. 6

Pooled estimates of T₁ pelvic angle, T₁ pelvic tilt, and T₉ pelvic tilt. CI, confidence interval.

Discussion

The most evident result of this meta-analysis is the profound heterogeneity observed across all sagittal alignment parameters. Even with stringent selection criteria—including specific age ranges and geographic subregions—this heterogeneity persists at a level that cannot be explained by measurement error alone. The variability likely originates from a range of methodological differences across studies, including technical factors (e.g., conventional radiography vs. biplanar EOS [151], tube-to-film distance, central beam placement [152]), patient positioning (e.g., mirror placement for gaze alignment, limb positioning [153,154]), and socio-cultural influences. Further, the inconsistencies are caused by recruitment biases (e.g., differences in sport activity vs. the general population [155]), radiographer experience [156], and the use of image stitching or automated measurement software [157,158].

Considering the impossibility of standardizing hundreds of studies retroactively, the meta-analytic approach itself—synthesizing a very large sample—becomes a methodological necessity. It operates on the principle that random errors and biases from individual studies will balance each other, enabling the central tendency of the underlying biological parameters to emerge [159]. Therefore, the pooled estimates from this large-scale synthesis may represent the closest available approximation of “true” global normative values, despite the irreducible heterogeneity. This result challenges the concept of universal norms derived from single populations and underscores the critical need for prospective, rigorously standardized imaging protocols in future research to finally identify true biological variation from methodological noise.

Notably, heterogeneity levels substantially varied between different alignment parameters. Our analysis revealed wide ranges in both traditional heterogeneity metrics (τ² and I²) and the more clinically meaningful 95% PIs—from ±1.2° for T₉ PT to ±15.0° for T₄–T₁₂ kyphosis (Fig. 7). We propose that this spectrum reflects fundamental differences in parameter function: those with narrow PIs (e.g., PT) likely represent core stability mechanisms conserved across populations, whereas highly variable parameters (e.g., regional kyphosis/lordosis) may reflect adaptive postural adjustments to individual anthropometrics.

Fig. 7

Spino-pelvic parameters ranked by heterogeneity (95% PI margin of error), illustrating core-to-adaptive hierarchy. PT, pelvic tilt; PA, pelvic angle; SS, sacral slope; PI, pelvic incidence; CL, cervical lordosis; SSA, spinosacral angle; TK, thoracic kyphosis; LL, lumbar lordosis.

This core-versus-adaptive paradigm finds strong support in our geographic subgroup analyses of the pelvic parameter triad (SS, PT, and PI). SS and PI demonstrated significant regional variation, whereas PT remained remarkably consistent generally (mean value 12.2° with 95% PI ±4.1°) and across all geographic subregions (mean differences, <1°; p=0.58) (Fig. 8). This finding strongly indicates that PT is the primary, conserved variable in this triad, whereas SS and PI function as adaptive components. Therefore, in a surgical context, the restoration of a population-invariant PT value could provide a stable foundation for reconstructing the pelvic component of alignment.

Fig. 8

Relationships between sacral slope (SS), pelvic tilt (PT) and pelvic incidence (PI) stratified by geographic group. The analysis demonstrates the invariant nature of PT and the adaptive relationship of SS with PI. p-value represents the test of moderators from a mixed-effects model.

The meta-regression justified stratification by geographic region for TK, LL, SS, and PI, demonstrating a high evidence level (p<0.0001 for moderators). T1S exhibited a marginal yet statistically significant difference between groups #1 and #3 (p=0.041). Notably, all thoracolumbar spine curvatures were less pronounced in Eastern/Southeastern Asian populations (group #3) compared with predominantly European-origin populations (group #1), whereas Western/Southwestern Asian populations (group #2) demonstrated similar curvature patterns to group #1 (p>0.05).

These findings introduce questions about the need to stratify normative spinal values by geographic regions—and potentially by countries or ethnic subgroups—to develop population-adjusted standards for surgical targets. However, such fine-grained stratification may prove unfeasible in the context of increasing globalization, where migration, ethnic diversity, and cultural integration blur traditional geographic and ethnic boundaries. The development of a universal predictive model for individualized spinal alignment, grounded in fundamental biomechanical principles common to all humans but calibrated to patient-specific factors (e.g., sex, age, weight, somatotype, gravity line projection), is a more viable alternative [160]. The existence of common principles would likely be reflected in the most stable spinal parameters—those with minimal heterogeneity.

A particularly intriguing finding was the low variability (95% PI <5°) of all angular parameters referencing the bicoxofemoral axis (T₁PT, T₉PT, and TPA), contrasting sharply with the greater variability of intervertebral measurements (CL, TK, and LL). This pattern reinforces our hypothesis of hierarchical parameter organization and indicates that the bicoxofemoral axis may serve as the primary reference point for sagittal balance. These results are consistent with and logically extend Roussouly’s principle of pelvic shape as the primary determinant of spinal configuration [161], thereby further emphasizing the foundational role of pelvic anatomy and orientation in global alignment of the spine [162]. The detected low variability of the bicoxofemoral axis-referenced parameters (TPA, T₁PT, and T₉PT), based on only 9–10 studies per parameter, is promising but must be considered preliminary and requires additional studies with larger, ethnically diverse cohorts. Other angular measurements subtended from the bicoxofemoral axis—to L₃, the odontoid process of C₂, and the center of the external acoustic meatus [17,67,108]—are underreported in the literature and were not analyzed. However, their potential relevance as core vertical alignment parameters warrants further investigation in future studies.

Surgical correction of spinal deformity depends on target values with significant heterogeneity, including LL, TK, and SVA [163–166]. However, this approach shows suboptimal treatment outcomes, failing to meet established spinopelvic alignment goals in >50% of cases [8,167]. The present study indicates that population-based alignment targets for spinal surgery may be inadequate for a large proportion of individuals, considering the substantial variability in adaptive spinal parameters (LL, CL, PI, TK, and SVA). The proposed hierarchy of spinopelvic parameters is based on relative heterogeneity rather than a mathematical imperative. The low variability of PT and other bicoxofemoral axis-referenced parameters indicates that they may be fundamental to balance, but this remains a statistical inference. Validation in surgical cohorts is warranted to investigate whether a surgical strategy that prioritizes the restoration of less variant “core” parameters (e.g., PT) provides a more robust foundation for achieving optimal alignment and improved patient outcomes.

This meta-analysis has several limitations that should be considered for result interpretation. One key limitation is that the promising findings regarding the bicoxofemoral axis-referenced parameters (T₁PT, T₉PT, and TPA) are based on a relatively small number of studies. Their low variability is highly suggestive, but these results remain preliminary and require validation in larger, ethnically diverse cohorts before firm conclusions are drawn regarding their population invariance.

Moreover, substantial methodological heterogeneity and measurement variability were observed across the included studies, as indicated by the high I² values. Random-effects models were employed to account for this variability, but it remains a source of uncertainty. Further, our assessment indicated potential funnel plot asymmetry for certain cervical parameters (C₀–C₂, C₂–C₇ lordosis, T₁ slope, and SVA C₂–C₇), which may indicate publication bias. However, noteworthily, Egger’s test is significant in the presence of high clinical heterogeneity [168], which was prevalent in our analysis.

Other limitations include the absence of prospective protocol registration and the potential bias introduced by the use of generative AI tools during preliminary screening. Further, formal sensitivity analyses to assess the effect of excluding studies with a high risk of bias or to investigate alternative synthesis methods were not conducted, as the large number of parameters synthesized made this impractical. Thus, the pooled estimates provide useful insights, whereas they should be interpreted with appropriate caution in light of these limitations.

Conclusions

Our findings support two key advancements in spinal care. First, they underscore the need to standardize clinical measurement protocols to incorporate bicoxofemoral axis-based assessments, capitalizing on their high reliability. Second, they highlight the importance to validate the potentially stable nature of the proposed “core” parameters and to identify whether prioritizing the restoration of these fundamental alignment values during surgical correction leads to superior patient outcomes. Our results challenge the conventional use of rigid, population-based alignment targets. Instead, they support for a patient-specific paradigm in which stable core parameters (e.g., PT) serve as the foundation for defining individualized correction goals.

Key Points

Reveals a heterogeneity gradient: Parameters exist along a continuous spectrum of heterogeneity, with bicoxofemoral axis-referenced angles forming a stable “core” end and intervertebral curvatures at the adaptive end.
Identifies a reliable anatomical reference: This analysis revealed that measurements based on the bicoxofemoral axis demonstrated low variability, warranting further research into their potential role as a reliable clinical benchmark.
Challenges universal alignment targets: The substantial and irreducible heterogeneity in spinal curvatures across a global cohort challenges the validity of one-size-fits-all surgical targets for sagittal alignment.
Reveals geographic conservation of pelvic tilt: Pelvic tilt was uniquely conserved across geographic sub-groups, whereas sacral slope and pelvic incidence demonstrated region-specific adaptations.
Advocates for a personalized surgical paradigm: The findings advocate for surgical planning that prioritizes restoring stable “core” parameters rather than aiming for population-based averages of adaptive angles.

Notes

Conflict of Interest

No potential conflict of interest relevant to this article was reported.

Acknowledgments

Figs. 7 and 8 were created using illustrations provided by the Anatomy Standard project [169].

Author Contributions

Conceptualization: YS. Methodology: YS. Formal analysis: YS, VN. Software: YS. Validation: VN. Writing–original draft preparation: YS. Writing–review and editing: VN. Supervision: VN. Final approval of the manuscript: all authors.

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Table 1

Summary of demographic data and reported parameters

Report	No.	Sex (M/F)	Average age±SD (range), yr	Region	CL C₀–C₂	CL C₂–C₇	SVA C₂–C₇	T₁S	TK T₁–T₁₂	TK T₄–T₁₂	LL L₁–S₁	SS	PT	PI	SVA C₇–S₁	TPA	SSA	T₁PT	T₉PT
Abrisham et al. [12] (2020)	403	189/214	(20–60)	2					X
Acharya et al. [13] (2022)	171	92/78	30±7.76 (20–40)	3		X	X	X
Ahn et al. [14] (2010)	166	166/0	21.8±1.3 (19–26)	3								X		X	X
Aksekili et al. [15] (2021)	170	137/33	24.1±4.9 (17–39)	2						X	X	X	X	X	X			X
Aktan et al. [16] (2025)	400	198/202	40.2±14.7	2						X	X	X	X	X
Amabile et al. [17] (2016)	69	32/37	26.3±4.7 (18–40)	1					X	X	X	X	X	X	X	X		X	X
Ao et al. [18] (2019)	190	NA	(<54)	3		X	X
Araujo et al. [19] (2014)	57	NA	(18–40)	1							X	X	X	X	X
Arima et al. [20] (2018) (Asian)	312	NA	37.2±11.7 (18–69)	3							X	X	X	X
Asai et al. [21] (2017)	426	131/295	(<59)	3							X		X	X	X
Attali et al. [22] (2019)	50	28/22	34 (26–48)	1					X	X	X	X	X	X
Bakouny et al. [23] (2017)	90	46/44	21.6±2.2 (18–28)	2					X	X	X	X	X	X
Bakouny et al. [24] (2018)	92	48/44	21.5±2.2 (18–28)	2		X	X	X	X	X	X	X	X	X	X			X
Bayraktar [25] (2019)	126	54/62	27.4±6.9 (20–40)	2						X	X		X	X	X
B_erthonnaoud et al. [26] (2005)	160	70/90	25.7±5.5 (20–70)	1						X	X	X	X	X
Bhat et al. [27] (2019)	200	27/128	34.6±8.1 (18–50)	2							X	X	X	X	X
Bhosale et al. [28] (2020)	130	65/65	34.49±8.53 (18–50)	2								X	X	X
Boulay et al. [29] (2006)	149	78/71	30.8±6 (19–51)	1						X		X	X	X					X
Chen et al. [30] (2017)	90	NA	(21–60)	3		X	X	X
Chevillotte et al. [31] (2024)	373	178/195	27	1								X	X	X
Cho [32] (2017)	252	151/101	33.2±8.2 (20–50)	3						X	X	X	X	X	X		X
Cruz et al. [33] (2023)	104	104/0	(20–30)	1							X	X	X	X	X
Daffin et al. [34] (2024)	150	61/89	22.5±3.6 (18–30)	1	X
El Rayes et al. [35] (2017)	95	54/41	(21–30)	2								X	X	X
Endo et al. [36] (2012)	50	NA	31.5±7.4	3							X	X	X	X
Endo et al. [37] (2014)	86	48/38	35.9±11.1 (23–59)	3						X	X	X	X	X	X
Ganesan et al. [38] (2014)	120	NA	30 (18–45)	2								X	X	X
Gerlimez et al. [39] (2021)	75	NA	(18–50)	2	X
Gharbi et al. [40] (2024)	78	NA	(20–50)	1	X	X		X	X		X	X	X	X	X	X	X	X	X
Guigui et al. [41] (2003)	250	NA	(18–60)	1							X		X	X					X
Guo et al. [42] (2011)	414	213/201	(<65)	3	X	X
Haas et al. [43] (2024)	220	81/139	43±12.5	1			X
Hardacker et al. [44] (1997)	50	25/25	38.4±9.4 (23–65)	1			X		X						X
Harrison et al. [45] (2002)	20	15/5	28.0±6.6	1					X			X
Harrison et al. [46] (2004)	72	36/36	40.6±10.4	1		X
Hasegawa et al. [47] (2016)	126	30/96	39.4±11.3 (20–70)	3		D			X	X	X	X	X	X	X
Hasegawa et al. [48] (2017)	136	40/96	39.7±22.4 (20–69)	3		X			D		D	D	D	D	D
H_asegawa et al. [49] (2022) (Arabo-Bèrbère)	80	30/50	45.5±14.3 (18–80)	2								X	X	X
H_asegawa et al. [49] (2022) (Asian)	185	69/116	36.7±15.0 (18–80)	3								X	X	X
H_asegawa et al. [49] (2022) (Caucasian)	176	73/103	42.0±14.6 (18–80)	1									X	X
Heo et al. [50] (2022)	92	27/65	21.5 (20–30)	3					X			X	X	X	X
Hey et al. [51] (2017)	26	22/4	24 (19–38)	3		X		X
Hey et al. [52] (2019)	60	48/12	21±0 (21–21)	3							X	X	X	X
Hey et al. [53] (2021)	100	49/51	45±15.9	3				X						X	X
Hu et al. [54] (2016)	272	161/111	23.2±4.4 (18–45)	3							X	X	X	X	X		X
Hu et al. [55] (2022)	238	106/129	(20–50)	3							X				X	X
Iorio et al. [56] (2018)	65	NA	(<35–54)	1	X	X	X	X		X	X	X	X	X	X
İplikçioğlu et al. [57] (2023)	78	42/36	30.6±10.7 (16–50)	2	X	X	X	X
İplikçioğlu et al. [58] (2023)	50	28/22	31.57±8.33 (18–60)	2										X
Iyer et al. [59] (2016)	71	17/54	(21–60)	1					X		X	X	X	X	X	X
Iyer et al. [60] (2016)	71	18/53	(21–60)	1			X	X
Jackson et al. [4] (1994)	100	50/50	38.9±9.4 (20–63)	1					X		X				X
Janssen et al. [61] (2009)	60	30/30	26.5 (20–49)	1						X	X	X	X	X					X
Jin et al. [62] (2024)	318	183/135	(20–59)	3		X	X	X
Jouibari et al. [63] (2019)	25	7/18	(20–60)	1		X	X	X
Yüceli et al. [64] (2019)	347	119/228	44.1±16.0 (18–60)	2		X	D
Kalidindi et al. [65] (2022)	100	69/31	29.1±7.9 (18–60)	2								X	X	X
Kaur et al. [66] (2023)	80	44/36	25.6±8.7 (18–55)	2							X	X	X	X
Khalife et al. [67] (2024)	605	301/304	(20–59)	1					X			X	X	D	X	X	X	X
Khalife et al. [68] (2024)	484	NA	29.5 (18–50)	1							X			X
Khalil et al. [69] (2018)	144	73/71	29±22.0 (18–59)	2			X	X	X		X	X	X	X	X		X	X	X
Kim et al. [70] (2024)	136	42/94	38±11 (23–64)	3							X	X	X	X
Korovessis et al. [71] (1998)	67	NA	(20–59)	1						X
Kouyoumdjian et al. [72] (2024)	120	74/56	25.6 (22–27)	1								X		X
Laouissat et al. [73] (2018)	296	126/170	27 (18–48)	1							X	X	X	X
Le Huec et al. [74] (2015)	106	59/47	38.0 (18–76)	1	X	X			X		X	X	X	X
Lee et al. [75] (2011)	86	54/32	28.19 (20–39)	3						X	X	X	X	X
Lee et al. [76] (2012)	77	NA	(21–50)	3	X			X
Legaye et al. [77] (1998)	49	28/21	24±5.8 (19–50)	1					X			D	D	D
Legaye et al. [78] (2005)	49	28/21	24 (19–30)	1								X	X	X					X
Legaye [79] (2007)	143	72/73	40.7±18.7 (15–76)	1								X	X	X
Legaye et al. [80] (2008)	42	23/19	24.4±6.3	1								D	D	D				X	D
Li et al. [81] (2021)	87	54/33	37.3±7.2 (18–45)	3							X	X	X	X
Liu et al. [82] (2019)	120	60/60	(21–60)	3		X		X
Mac-Thiong et al. [83] (2010)	709	354/355	36.8±14.31 (16–76)	1							X						X
Mac-Thiong et al. [84] (2011)	709	354/355	36.8±14.31 (16–76)	1								X	X	X
Machino et al. [85] (2016)	819	413/406	(20–59)	3		X
Maekawa et al. [86] (2019)	105	NA	33.3±8.4 (20–49)	3							X	X	X
Marty et al. [87] (2002)	44	23/21	(19–28)	1								X	X	X
Mekhael et al. [88] (2021)	68	17/51	39±13	2							X		X	X	X
Menezes-Reis et al. [89] (2018)	93	43/50	27.1±5.3 (20–40)	1						X	X	X	X	X	X		X
Nojiri et al. [90] (2003)	264	123/141	45 (20–77)	3	X
Oe et al. [91] (2015)	36	NA	(50–59)	3		X	X	X			X	X	X	X	X
Oh et al. [92] (2013)	80	80/0	21.2±2.12	3								X	X	X
Ohashi et al. [93] (2023)	140	57/83	40.2±10.9 (20–76)	3								X	X	X
Otayek et al. [94] (2020)	134	68/66	29±11 (18–59)	2					X		X		X	X	X	X
Ouchida et al. [95] (2023) (Asians)	68	NA	41.1±13.5	3		X
Ouchida et al. [95] (2023) (Caucasians)	68	NA	42.3±16.2	1		X
Park et al. [96] (2014)	104	30/74	39.1 (20–59)	3	X	X	X
Park et al. [97] (2020)	99	NA	(20–59)	3								X		X
Pratali et al. [98] (2018)	88	NA	(18–59)	1				X			X	X	X	X	X	X
Prost et al. [99] (2022)	648	NA	34.25±4.37 (20–49)	1									X	X	X
Quintana et al. [100] (2024)	80	34/46	25±4.1 (20–35)	1								X	X	X
Rajnics et al. [101] (2001)	30	15/15	34.3±3.06 (30–39)	1						X	X	X	X	X					X
Rezaee et al. [102] (2020)	100	41/59	47.4±11.7	2								X	X	X
R_omero-Vargas et al. [103] (2013)	51	NA	29	1							X	X	X	X
Rossanez et al. [104] (2023)	70	NA	(18–59)	1	X	X	X	X
Roussouly et al. [105] (2006)	153	73/80	27 (18–48)	1						X	X	X	X	X	X		X
Ru et al. [106] (2021)	239	135/104	32.5±9.5 (18–45)	3							X	X	X	X
Ru et al. [107] (2023)	142	NA	31.0±9.7 (18–45)	3						X	X	X	X	X	X
Saad et al. [108] (2022)	31	13/18	45±15 (21–76)	2		X			X		X		X	X	X
Sangondimath et al. [109] (2022)	100	59/41	(20–60	2					X	X	X	X	X	X	X				X
Schwab et al. [110] (2006)	49	31/19	38.6 (21–60)	1						X	X	X	X	X	X
Shao et al. [111] (2019)	216	NA	40.5±12.9	3		X	X	X			X	X			X
Sherekar et al. [112] (2006)	346	180/176	(20–59)	2	X
Shimizu et al. [113] (2020)	58	0/58	47.4±6.2	3							X	X	X	X	X
Siddiqui et al. [114] (2015)	84	55/29	(20–60)	2								X	X	X
Singh et al. [115] (2018)	50	29/21	31.1±9.6	2							X	X	X	X
Sudhir et al. [116] (2016)	52	26/26	32.2±10.4 (18–48)	2							X	X	X	X
Sun et al. [117] (2020)	507	256/251	43.4±13.9 (18–76)	3			X	X
Sun et al. [118] (2022)	143	49/94	23.0±2.3 (19–29)	3						X	X	X	X	X	X	X
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Takahashi et al. [121] (2021)	100	25/75	38.9±11.0 (20–70)	3							X	X	X	X
Tang et al. [122] (2022)	126	67/59	(18–30)	3	X	X	X	X		X	X	X	X	X	X
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Verhaegen et al. [127] (2022)	49	NA	(20–40)	1							X	X	X	X
Vialle et al. [128] (2005)	300	190/110	35.4±12 (20–70)	1						X	X	X	X	X				X	X
Wang et al. [129] (2017)	103	33/70	37.4±12.3	3	X	X	X	X
Wang et al. [130] (2022)	385	203/182	38.3±11.9 (20–73)	3					X		X	X		X
Xing et al. [131] (2018)	50	25/25	32.1±9.2 (20–50)	3		X	X	X
Xu et al. [132] (2023)	129	NA	(20–49)	3	X	X
Xue et al. [133] (2020)	50	25/25	(21–30)	3		X			X						X
Yan et al. [134] (2022)	346	133/213	42.6±13.2	3		X	X	X	X			X	X	X	X
Yang et al. [135] (2016)	119	61/58	34.7±13.8 (11–58)	3				D				D	D	D	D	D		X
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Yin et al. [139] (2013)	111	55/56	(18–60)	3							X	X	X	X	X		X
Yonezawa et al. [140] (2024)	62	43/19	39.3±10.4 (23–64)	3		X		X	X		X	X	X	X		X
Yukawa et al. [141] (2018)	417	207/210	(20–59)	3					X			X	X	X	X
Z_árate-Kalfópulos et al. [142] (2012) (Caucasians)	160	74/86	27	1									X	X	X
Zeng et al. [143] (2018)	85	39/46	46±14.1 (21–65)	3		X				X	X	X	X	X	X		X
Zhao et al. [144] (2022)	145	51/94	23.1±2.3 (19–29)	3						X	X	X	X	X	X	X
Zhou et al. [145] (2020)	140	NA	23.2±2.6	3						X	X	X	X	X	X	X
Zhou et al. [146] (2022)	435	188/247	(18–59)	3						X	X	X	X	X	X	X
Zhu et al. [147] (2014)	260	NA	34.3±11.2	3						X	X	X	X	X
Zhu et al. [148] (2018)	119	NA	(18–60)	3		X		X
Zhu et al. [149] (2020)	46	NA	28.0±8.09	3		X	X	X		X	X	X	X	X	X
Zhu et al. [150] (2020)	307	144/163	24.5±3.1 (18–30)	3		X	X	X

X: reported parameters of the sagittal alignment; D: repetitive values reported elsewhere excluded from the analysis.

M, male; F, female; SD, standard deviation; CL, cervical lordosis; SVA, sagittal vertical axis; T1S, T1 slope; TK, thoracic kyphosis; LL, lumbar lordosis; SS, sacral slope; PT, pelvic tilt; PI, pelvic incidence; TPA, T1 pelvic angle; SSA, spinosacral angle; NA, not available.

Parameters	Studies	Subjects included	Pooled mean (95% CI)	τ²±SE	I² (%)	95% PI (±)	t-value (Egger’s test)	p-value (Egger’s test)	Subgroup comparison
Lordosis C₀–C₂ (°)	15	2,185	17.6 (16.0–19.2)	9.7±3.9	96	6.9	4.51	<0.001	0.066^a)
Lordosis C₂–C₇ (°)	38	5,566	10.1 (8.1–12.2)	40.6±9.8	98	13.1	−2.18	0.04	0.50
SVA C₂–C₇ (mm)	26	3,828	18.9 (17.0–20.8)	18.2±5.5	97	9.0	2.33	0.03	0.21^a)
T₁ slope (°)	30	3,915	23.9 (22.5–25.2)	14.1±3.9	97	7.8	2.51	0.02	0.041^a)
Kyphosis T₁–T₁₂ (°)	25	3,819	44.7 (42.7–46.7)	25.1±7.6	98	10.6	0.71	0.48	<0.0001
Kyphosis T₄–T₁₂ (°)	31	4,243	32.8 (30.3 – 35.4)	51.6±13.6	99	15.0	−1.37	0.18	<0.0001
Lordosis L₁–S₁ (°)	69	10,520	52.6 (51.0–54.2)	46.6±8.2	99	13.8	0.16	0.87	<0.0001
Sacral slope (°)	91	13,264	37.6 (37.0–38.2)	8.4±1.36	96	5.8	0.06	0.95	<0.0001
Pelvic tilt (°)	94	14,630	12.2 (11.8–12.7)	4.22±0.69	94	4.1	0.45	0.66	0.58
Pelvic incidence (°)	98	15,251	49.7 (49.1–50.4)	9.36±1.49	94	6.1	0.16	0.87	<0.0001
SVA C₇–S₁ (mm)	51	8,600	14.0 (10.8–17.1)	126.3±26.7	98	22.8	−0.28	0.78	0.31
T₁ pelvic angle (°)	13	2,438	6.7 (5.8–7.7)	2.66±1.21	93	3.7	0.82	0.43	0.88^a)
Spino-sacral angle (°)	10	2,502	129.9 (127.6–132.2)	13.3±6.5	98	8.9	−1.08	0.31	0.14^a)
T₁ pelvic tilt (°)	9	1,619	4.7 (3.6–5.7)	2.47±1.29	98	3.9	−0.43	0.68	NA
T₉ pelvic tilt (°)	10	1,229	10.9 (10.5–11.2)	0.23±0.16	75	1.2	0.63	0.54	NA