*Systematic Review* **Prevalence and Risk Factors of Musculoskeletal Disorders in Basketball Players: Systematic Review and Meta-Analysis**

**Silvia Cristina de Carvalho Borges <sup>1</sup> , Carolina Rodrigues Mendonça <sup>1</sup> , Regina Márcia Ferreira Silva 2,\*, Alberto De Vitta <sup>3</sup> and Matias Noll 1,2,\***


**Abstract:** Musculoskeletal disorders characteristically induce pain and limitations in mobility, ability, and overall functioning. In athletes, including basketball players, disorders such as back pain, postural changes, and spinal injuries are common. This systematic review aimed to evaluate the prevalence of back pain and musculoskeletal disorders in basketball players and ascertain the associated factors. Methods: The Embase, PubMed, and Scopus databases were searched for studies published in English without a time limit. Using STATA, meta-analyses were performed to estimate the prevalence of pain and musculoskeletal disorders of the back and spine. Results: Of the 4135 articles identified, 33 studies were included in this review, with 27 studies included in the meta-analysis. Of these, 21 were used for the meta-analysis of back pain, 6 articles were used for the meta-analysis of spinal injury, and 2 studies were used for the meta-analysis of postural changes. The overall prevalence of back pain was 43% [95% CI, −1% to 88%]; of these, the prevalence of neck pain was 36% [95% CI, 22–50%], the prevalence of back pain was 16% [95% CI, 4–28%], the prevalence of low back pain was 26% [95% CI, 16–37%], the prevalence of thoracic spine pain was 6% [95% CI, 3–9%]. The combined prevalence of spinal injury and spondylolysis was 10% [95% CI, 4–15%], with a prevalence of spondylolysis of 14% [95% CI, 0.1–27%]. The combined prevalence of hyperkyphosis and hyperlordosis was 30% [95% CI, 9–51%]. In conclusion, we found a high prevalence of neck pain, followed by low back pain and back pain, in basketball players. Thus, prevention programs are important to improve health and sports performance.

**Keywords:** back pain; athletes; sport

#### **1. Introduction**

Approximately 1.71 billion people worldwide suffer from musculoskeletal disorders that affect multiple areas or body systems, such as joints, bones, muscles, and spine; they are characterized by pain and limitations in mobility, ability, and overall level of functioning [1–3]; and necessitate rehabilitation [1]. Unlike that in the general population, musculoskeletal disorders can be exacerbated in athletes. Athletes frequently experience musculoskeletal disorders, with back pain being one of the most common symptoms [4–6]. Several sports are characterized by the need for specific movements, which may result in excessive spinal stress [7].

A study of elite German athletes from different sports reported that 77% of the athletes reported low back pain, followed by neck pain (63%) and thoracic spine pain (46%) [8]. Another study of 1114 elite German athletes from various sports reported an 89% prevalence of low back pain [9]. In another study of athletes from Finland, 46% of the basketball players who participated in the study had low back pain [10].

**Citation:** de Carvalho Borges, S.C.; Mendonça, C.R.; Ferreira Silva, R.M.; De Vitta, A.; Noll, M. Prevalence and Risk Factors of Musculoskeletal Disorders in Basketball Players: Systematic Review and Meta-Analysis. *Healthcare* **2023**, *11*, 1190. https://doi.org/10.3390/ healthcare11081190

Academic Editor: Felipe Aidar

Received: 7 March 2023 Revised: 11 April 2023 Accepted: 17 April 2023 Published: 21 April 2023

**Copyright:** © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

Basketball players frequently suffer from low back and neck pain [7–11], which confers a high risk for spinal injuries [7], and lumbar spine injuries are common in basketball players [12,13]. A study that longitudinally evaluated all injuries in the National Basketball Association (NBA) players over a 17-year period found that 10.2% of all injuries involved the lumbar spine and 0.9% of all injuries were due to lumbar disk degeneration [4].

Moreover, postural changes are common in players of various sports due to the repetitive and unilateral overload of the body during sports practice [14,15]. Furthermore, the trend of spinal curvature changes in basketball players, when compared to that in non-athletes, suggests an effect of regular basketball training on the degree of curvature of thoracic kyphosis and lumbar lordosis [16].

Basketball is an asymmetric sport that involves repetitive unilateral movements [15]. Therefore, the practice of this sport may promote pain and/or injury to the spine due to the number of throws and dribbles during a practice session or game [15]. Therefore, it is necessary to determine the prevalence of postural changes and back pain, as they may affect players' mobility and ability. Despite the importance of this topic, no systematic reviews of back pain and postural changes in basketball players have been published.

Therefore, this systematic review aimed to evaluate the prevalence of back pain whose causes remain uncertain and probably multifactorial and musculoskeletal disorders in basketball players. This research is intended to identify factors that are associated with musculoskeletal disorders and pain in basketball players to contribute to the implementation of spinal pain and injury prevention and treatment interventions and programs to improve the health, quality of life, and sports performance of basketball players.

#### **2. Materials and Methods**

#### *2.1. Protocol and Registration*

The protocol (PROSPERO CRD42020201653) of this systematic review was registered in the International Prospective Register of Systematic Reviews and was published as an article [17]. The systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses methodology [18]. Ethical approval was not required because this review involved an analysis of previously published data.

#### *2.2. Identification of Relevant Studies*

Studies published in English were searched without any restriction on the publication period. The search was performed in three databases (Embase, PubMed, and Scopus) on 6 March 2022. The main search terms were "back pain", "postural changes", "players", and "basketball". The general search strategy is described in Table 1 and was adapted for the different databases (Supplementary Material).

**Table 1.** General search strategy for the identification of published articles.


The review followed the PECO structure (population, exposure, comparators, and outcomes) [19]. In this article, "P" represents players, "E" represents basketball sport, "C" represents spine regions (lumbar spine, cervical spine, thoracic spine), and "O" represents the prevalence of back pain and musculoskeletal disorders (postural changes and spinal injuries) in basketball players and associated factors.

Musculoskeletal disorders include fractures, acute soft tissue injuries (i.e., bruises, sprains, or strains); non-articular and non-rheumatic soft tissue disorders, tissue disorders including local myofascial pain syndrome and systemic fibromyalgia, arthritis, neurological disorders, amputations, and problems of postoperative rehabilitation following interventional orthopedic procedures [20]. Functional disorders that were evaluated in this review included traumatic injuries of the spine and injuries of the spinal cord, nerve roots, bone structure, and disk ligaments of the spine [21]. Postural changes considered included scoliosis, kyphosis, and lordosis. Back pain was defined as pain in the cervical, thoracic, and/or lumbar spine [22–24].

Inclusion criteria were: (a) basketball players of both sexes; (b) age up to 50 years (articles with other age groups were included, provided the data were presented separately); (c) observational studies (longitudinal, cross-sectional, cohort, and case-control); (d) assessment of musculoskeletal disorders or back pain in basketball players (articles with other injuries were included, provided the data are presented separately); (e) publications in English; and (f) studies with players from communities of different nationalities. Both specific and non-specific back pain were included.

Articles based on the following criteria were excluded: (a) studies with basketball players that pertained to injuries in other body regions (knee, shoulder, hip, ankle) unless back and spine data were presented separately or could be calculated; (b) paralympic athletes and/or players with physical or mental disabilities; (c) mixed sports samples, unless basketball player data were presented separately or could be calculated; (d) experimental studies; and (e) studies with incomplete data.

This search included full articles published without the restriction of the search period, and excluded books, book chapters, case reports, commentaries, letters, editorials, and systematic reviews. Articles for which the full text could not be retrieved from online databases were requested by email from the authors of the papers.

#### *2.3. Study Selection*

Articles found in the databases were imported into Mendeley [25] software, where we excluded duplicate studies. Subsequently, the Rayyan software [26] was used to read the titles and abstracts of the studies, and articles that did not meet the previously established eligibility criteria were excluded. Next, the full texts of the selected studies were read to confirm their eligibility. All steps were performed by two reviewers (SCCB and MSVF), and disagreements, if any, were resolved by a third reviewer (MN). The flowchart of the study selection is shown in Figure 1.

#### *2.4. Data Extraction*

*2.5. Examiner Training* 

*2.4. Data Extraction*  The following data were extracted from the selected studies: author and year of publication, type of study, country of origin, population, sex, age group, type of change, tool, prevalence of postural change and injuries, location, and prevalence of back pain. The following data were extracted from the selected studies: author and year of publication, type of study, country of origin, population, sex, age group, type of change, tool, prevalence of postural change and injuries, location, and prevalence of back pain. The full description of the extracted data is included in Tables 2–5.

The full description of the extracted data is included in Tables 2–5. We performed a meta-analysis with the data that were extracted to ascertain the prevalence of back pain, postural changes, and spinal injuries. However, these data were We performed a meta-analysis with the data that were extracted to ascertain the prevalence of back pain, postural changes, and spinal injuries. However, these data were insufficient to perform a meta-analysis of the associated factors.

Authors participating in the eligibility assessments were trained in the inclusion/exclusion criteria for studies and assessed the eligibility of 50 sample abstracts be-

insufficient to perform a meta-analysis of the associated factors.

#### *2.5. Examiner Training*

Authors participating in the eligibility assessments were trained in the inclusion/ exclusion criteria for studies and assessed the eligibility of 50 sample abstracts before they began reviewing the articles [27]. Besides performing standardized analyses using Mendeley and Rayyan software [25,26], the authors were trained to use risk-of-bias analysis tools through the examination of five non-included articles.

#### *2.6. Methodological Quality and Risk of Bias*

The included articles were assessed for methodological quality and risk of bias by using the Grading of Recommendations, Assessment, Development, and Evaluations-GRADE [28] or the Downs and Black checklist [29]. GRADE is a method that serves transparency and simplicity by enabling the classification of the quality of evidence into four categories: very low quality, low quality, moderate quality, and high quality. GRADE has been adopted worldwide because of its rigorous methodological classification and ease of use [28].

An adapted version of the Downs and Black checklist that was proposed by Noll was used [30], wherein each item indicates: (A) clearly stated objective; (B) clearly described main outcomes; (C) clearly defined sample characteristics; (D) clearly described distribution of main confounders; (E) clearly defined main findings; (F) random variability in estimates provided; (G) loss to follow-up described; (H) probability values provided; (I) representative target sample of the population; (J) representative sample recruitment of the population; (K) analyses adjusted for different follow-up times; (L) properly used statistical tests; (M) valid/reliable primary outcomes; (N) sample recruited from the same population; (O) adequate adjustment for confounders; and P) sample loss to follow-up considered (corresponding to items 1–3, 5–7, 9–12, 17, 18, 20, 21, 25, and 26). Items G and P were applied only to longitudinal studies, whereas items K and N were applied only to the case-control and longitudinal studies. Scores reach 100% at 12, 14, and 16 points for cross-sectional, case-control, and longitudinal studies, respectively. Scores above 70% were used to define a low risk of bias [29]. The Downs and Black checklist was identified as one of the two tools that were most frequently used in systematic reviews, which were registered in PROSPERO from 2011 to 2018 [31].

The scores were used to determine the methodological quality of the studies while considering five aspects: presentation, external validity, internal validity-bias, internal validity-confounders, and statistical power for inferences [29]. The risk of bias was assessed independently by two examiners. The prevalence of data identified in the studies was used for the data synthesis strategy.

#### *2.7. Statistical Analysis*

Meta-analyses were performed to estimate the prevalence of back pain, spinal injuries, and postural changes. Data were presented graphically in Forest plots to estimate the prevalence rates with 95% confidence intervals (CI). Statistical I<sup>2</sup> values were calculated to quantify the degree of heterogeneity between studies, with values of 25–50% representing moderate heterogeneity and values > 50% representing large heterogeneity among the studies [32]. Publication bias was assessed using Egger's test. All analyses were performed using STATA (version 16.0; StataCorp, College Station, TX, USA).

#### **3. Results**

The stages of study selection are presented in Figure 1. According to the eligibility criteria, 6443 studies were identified, of which 1852 duplicate records were excluded. After screening the title and abstract, 4591 articles were selected; among these, 4506 did not meet the eligibility criteria, and 85 articles were included for a full-text review.

In this stage, 52 studies were excluded because they assessed other sports (n = 19), had different outcomes (n = 30), or were missing data (n = 3). Finally, 33 studies were included in this systematic review [6–8,10,11,16,33–59] (Table 2). Moderate interrater agreement (98%) was found between the two examiners.

#### *3.1. Risk of Bias and Evaluation of the Quality of Studies*

Of the articles included, 69.7% of the studies obtained ethical approval (n = 23) [6,7,10,11,16,34–36,38–40,44–48,50,51,53–56,59] and 51.5% clearly reported that there were no conflicts of interest (n = 17) [6,7,10,11,16,33,34,36–38,45,46,50,51,53,56,58].

The quality of evidence was low quality in 57.6% (n = 19) [6,10,11,16,37–51] and very low quality in 42.4% (n = 14) [7,8,33–36,52–59] of studies, respectively (Table 3). A total of 78.8% of the articles had a low risk of bias (n = 26) [6–8,10,11,16,33,34,36–47,49–51,54,57,58].

#### *3.2. Main Characteristics of the Studies*

In total, 72.7% (n = 24) of the articles were published between 2011 and 2022 [6–8,10,11,16,33,34,36,38–42,45–47,49–52,56–58]; 45.4% of the studies were conducted on the European continent (n = 15) (Table 4) [7,8,10,16,33,34,37,39,42,46–50,57]. With regard to the type of pain, back pain was addressed in 60.6% of the articles (n = 20) [6–8,11,34,35,37,38,42,43,46,47,49,50,54–56,58,59]; 48.5% of the articles investigated spine injuries (n = 16) [35,36,39–41,43–46,48,51–55,57].

The majority of the studies, 69.7% (n = 23), included participants from both sexes [6,8,10, 33,34,37,38,40–50,52–55,58]. The average age of the participants ranged from 11.47 ± 2.10 [33] to 24.4 ± 4.7 years [36]. The sample size varied widely across studies, with a minimum of 10 [16] and a maximum of 5,566,124 players [41]. Furthermore, 63.6% (n = 21) of the articles were cross-sectional [6–8,11,34,37,38,40–42,44,45,47,48,52–55,57–59] (Table 4).

The vast majority of studies, a total of 14, did not present the period in which low back pain was assessed [6,38–41,43–46,48,52,55,57]. A total of 8 studies assessed low back pain in the last 3 to 6 months [33,35–37,42,51,56,59], 5 studies assessed it over a period of one year [10,16,34,47,50], 4 studies assessed it over a lifetime [7,8,11,54], and finally, 2 studies assessed it within the last 3 to 5 five years [49,53]. The detailed characteristics of the studies included in the systematic review are shown in Table 4.


63.46%

**Table 2.** Characteristics of the studies included in the systematic review and their outcome variables.








52







\* Information missing in the article; ±, Standard deviation; BP, Back pain; F, Female; M, Male.



**Study (Year)** 

Cross-sectional

Yabe et al.

**Study (Year)** 

**Study (Year)** 

Cross-sectional

Yabe et al. [6]

**Study (Year)** 

Cross-sectional

Yabe et al. [6]

**Study (Year)** 

24-week follow-up New Zealand

Cross-sectional

Cross-sectional

24-week follow-up New Zealand

Yabe et al. [6]

Yabe et al. [6]

**Conflicts of Interest** 

Japan 592 (56.1%) 12–14 years

**Conflicts of Interest** 

Japan 592 (56.1%) 12–14 years

**Ethical Approval** 

> **Conflicts of Interest**

Japan 592 (56.1%) 12–14 years

Japan 592 (56.1%) 12–14 years

**Conflicts of Interest** 

**Ethical Approval** 

**Table 3.** Assessment of methodological quality and strength of evidence.

\* Information missing in the article; ±, Standard deviation; BP, Back pain; F, Female; M, Male.

**Ethical Approval** 

> **Conflicts of Interest**

Japan 592 (56.1%) 12–14 years

**Ethical** 

**Table 3.** Assessment of methodological quality and strength of evidence.

**Table 3.** Assessment of methodological quality and strength of evidence.

Training per day during the week: 2 h on average

\* Information missing in the article; ±, Standard deviation; BP, Back pain; F, Female; M, Male.

\* Information missing in the article; ±, Standard deviation; BP, Back pain; F, Female; M, Male.

Self-reported

*Healthcare* **2023**, *11*, x FOR PEER REVIEW 15 of 33

Training per day during the week: 2 h on average

**Table 3.** Assessment of methodological quality and strength of evidence.

**Downs and Black Checklist** 

**A B C D E F G H I J K L M N O P Total** 

*Healthcare* **2023**, *11*, x FOR PEER REVIEW 15 of 33

**A B C D E F G H I J K L M N O P Total** 

years questionnaire 15.4%

**Downs and Black Checklist** 

Self-reported

Self-reported

**A B C D E F G H I J K L M N O P Total** 

**A B C D E F G H I J K L M N O P Total** 

**Downs and Black Checklist** 

Self-reported

*Healthcare* **2023**, *11*, x FOR PEER REVIEW 15 of 33

*Healthcare* **2023***11*, x FOR PEER REVIEW 15 of 33

**A B C D E F G H I J K L M N O P Total** 

years questionnaire 15.4%

**GRADE** 

10 0%

**Sc or e#**

questionnaire \* \* \* Low back pain: 12.8%

**GRADE** 

**GRADE** 

questionnaire \* \* \* Low back pain: 12.8%

**Sc or e#**

questionnaire \* \* \* Low back pain: 12.8%

**Sc or e#**

questionnaire \* \* \* Low back pain: 12.8%

questionnaire \* \* \* Low back pain: 12.8%

**GRADE** 

**Sc or e#**

**GRADE** 

Farahbakhsh et al. [7] No Yes 1 1 1 0 1 1 - 1 0 0 - 1 1 - 1 - 9/12

Farahbakhsh et al. [7] No Yes 1 1 1 0 1 1 - 1 0 0 - 1 1 - 1 - 9/12

2 Farahbakhsh et al. [7] No Yes 1 1 1 0 1 1 - 1 0 0 - 1 1 - 1 - 9/12

75 %

10 0%

75 %

75 %

75 %

3

3

3

*Healthcare* **2023**, *11*, x FOR PEER REVIEW 15 of 33

Self-reported

years questionnaire 15.4%

Self-reported

*Healthcare* **2023**, *11*, x FOR PEER REVIEW 15 of 33

Training per day during the week: 2 h on average

Training per day during the week: 2 h on average

years questionnaire 15.4%

*Healthcare* **2023**, *11*, x FOR PEER REVIEW 15 of 33

years questionnaire 15.4%

years questionnaire 15.4%

*Healthcare* **2023**, *11*, x FOR PEER REVIEW 15 of 33

*Healthcare* **2023**, *11*, x FOR PEER REVIEW 15 of 33

*Healthcare* **2023**, *11*, x FOR PEER REVIEW 15 of 33

years questionnaire 15.4%

Self-reported

*Healthcare* **2023**, *11*, x FOR PEER REVIEW 15 of 33

*Healthcare* **2023**, *11*, x FOR PEER REVIEW 15 of 33

years questionnaire 15.4%

Self-reported

*Healthcare* **2023**, *11*, x FOR PEER REVIEW 15 of 33

Training per day during the week: 2 h on average

\* Information missing in the article; ±, Standard deviation; BP, Back pain; F, Female; M, Male.

24-week follow-up New Zealand

Japan 592 (56.1%) 12–14 years

Cross-sectional

Cross-sectional

Japan 592 (56.1%) 12–14 years

Japan 592 (56.1%) 12–14 years

Yabe et al. [6]

Yabe et al. [6]

Cross-sectional

24-week follow-up New Zealand

24-week follow-up New Zealand

Cross-sectional

24-week follow-up New Zealand

Japan 592 (56.1%) 12–14 years

Yabe et al. [6]

Yabe et al. [6]

24-week follow-up New Zealand

24-week follow-up New Zealand

> Yabe et al. [6]

Cross-sectional

24-week follow-up New Zealand

24-week follow-up New Zealand

24-week follow-up New Zealand

Cross-sectional

Yabe et al. [6]

Japan 592 (56.1%) 12–14 years

Training per day during the week: 2 h on average

**Table 3.** Assessment of methodological quality and strength of evidence.

**Table 3.** Assessment of methodological quality and strength of evidence.

\* Information missing in the article; ±, Standard deviation; BP, Back pain; F, Female; M, Male.

Training per day during the week: 2 h on average

\* Information missing in the article; ±, Standard deviation; BP, Back pain; F, Female; M, Male.

\* Information missing in the article; ±, Standard deviation; BP, Back pain; F, Female; M, Male.

Training per day during the week: 2 h on average

**Table 3.** Assessment of methodological quality and strength of evidence.

Training per day during the week: 2 h on average

**Table 3.** Assessment of methodological quality and strength of evidence.

\* Information missing in the article; ±, Standard deviation; BP, Back pain; F, Female; M, Male.

**Table 3.** Assessment of methodological quality and strength of evidence.

Training per day during the week: 2 h on average

Training per day during the week: 2 h on average

\* Information missing in the article; ±, Standard deviation; BP, Back pain; F, Female; M, Male.

**Ethical Approval** 

**Downs and Black Checklist** 

years questionnaire 15.4%

Self-reported

years questionnaire 15.4%

questionnaire \* \* \* Low back pain: 12.8%

**Downs and Black Checklist** 

*Healthcare* **2023**, *11*, x FOR PEER REVIEW 15 of 33

years questionnaire 15.4%

years questionnaire 15.4%

**Downs and Black Checklist** 

*Healthcare* **2023**, *11*, x FOR PEER REVIEW 15 of 33

Self-reported

Self-reported

questionnaire \* \* \* Low back pain: 12.8%

questionnaire \* \* \* Low back pain: 12.8%

questionnaire \* \* \* Low back pain: 12.8%

questionnaire \* \* \* Low back pain: 12.8%



*Healthcare* **2023**, *11*, x FOR PEER REVIEW 15 of 33

years questionnaire 15.4%

years questionnaire 15.4%

questionnaire \* \* \* Low back pain: 12.8%

Self-reported

years questionnaire 15.4%

*Healthcare* **2023**, *11*, x FOR PEER REVIEW 15 of 33

Training per day during the week: 2 h on average

*Healthcare* **2023**, *11*, x FOR PEER REVIEW 15 of 33

years questionnaire 15.4%

*Healthcare* **2023**, *11*, x FOR PEER REVIEW 15 of 33

*Healthcare* **2023**, *11*, x FOR PEER REVIEW 15 of 33

years questionnaire 15.4%

questionnaire \* \* \* Low back pain: 12.8%

questionnaire \* \* \* Low back pain: 12.8%

questionnaire \* \* \* Low back pain: 12.8%

*Healthcare* **2023**, *11*, x FOR PEER REVIEW 15 of 33

Self-reported

Self-reported

\* Information missing in the article; ±, Standard deviation; BP, Back pain; F, Female; M, Male.

Training per day during the week: 2 h on average

**Table 3.** Assessment of methodological quality and strength of evidence.

Training per day during the week: 2 h on average

\* Information missing in the article; ±, Standard deviation; BP, Back pain; F, Female; M, Male.

Self-reported

Training per day during the week: 2 h on average

24-week follow-up New Zealand

Cross-sectional

Japan 592 (56.1%) 12–14 years

Japan 592 (56.1%) 12–14 years

Cross-sectional

24-week follow-up New Zealand

> Yabe et al. [6]

Yabe et al. [6]

Yabe et al. [6]

Yabe et al. [6]

Cross-sectional

24-week follow-up New Zealand

24-week follow-up New Zealand

Japan 592 (56.1%) 12–14 years

24-week follow-up New Zealand

> Yabe et al. [6]

Cross-sectional

24-week follow-up New Zealand

Japan 592 (56.1%) 12–14 years

Cross-sectional

**Study (Year)** 

Cross-sectional

**Study (Year)** 

24-week follow-up New Zealand

**Study (Year)** 

**Study (Year)** 

Cross-sectional

Yabe et al. [6]

Japan 592 (56.1%) 12–14 years

**Conflicts of Interest** 

**Conflicts of Interest** 

**Conflicts of Interest** 

**Ethical Approval** 

Yabe et al. [6]

Japan 592 (56.1%) 12–14 years

**Conflicts of Interest** 

**Ethical Approval** 

**Table 3.** Assessment of methodological quality and strength of evidence.

\* Information missing in the article; ±, Standard deviation; BP, Back pain; F, Female; M, Male.

Training per day during the week: 2 h on average

\* Information missing in the article; ±, Standard deviation; BP, Back pain; F, Female; M, Male.

**Table 3.** Assessment of methodological quality and strength of evidence.

\* Information missing in the article; ±, Standard deviation; BP, Back pain; F, Female; M, Male.

Self-reported

**Downs and Black Checklist** 

Training per day during the week: 2 h on average

**Table 3.** Assessment of methodological quality and strength of evidence.

**Table 3.** Assessment of methodological quality and strength of evidence.

**Ethical Approval** 

\* Information missing in the article; ±, Standard deviation; BP, Back pain; F, Female; M, Male.

**A B C D E F G H I J K L M N O P Total** 

years questionnaire 15.4%

**Downs and Black Checklist** 

**Downs and Black Checklist** 

Self-reported

*Healthcare* **2023**, *11*, x FOR PEER REVIEW 15 of 33

**Downs and Black Checklist** 

years questionnaire 15.4%

questionnaire \* \* \* Low back pain: 12.8%

**GRADE** 

**Sc or e#**

**GRADE** 

**Sc or e#**

**GRADE** 

questionnaire \* \* \* Low back pain: 12.8%

**Table 3.** *Cont.*

**Study (Year)** 

**Conflicts of Interest** 

Japan 592 (56.1%) 12–14 years

**Ethical Approval** 

Abdollahi et al. [51] No \* 1 1 1 1 1 1 - 1 1 1 - 1 1 - 1 - 12/12

\* Information missing in the article; ±, Standard deviation; BP, Back pain; F, Female; M, Male.

**Table 3.** Assessment of methodological quality and strength of evidence.

Training per day during the week: 2 h on average

**Ethical Approval** 

**Downs and Black Checklist** 

**A B C D E F G H I J K L M N O P Total** 

**A B C D E F G H I J K L M N O P Total** 

Self-reported

**Downs and Black Checklist** 

**A B C D E F G H I J K L M N O P Total** 

**GRADE** 

1

10 0%

**Sc or e#**

questionnaire \* \* \* Low back pain: 12.8%

**GRADE** 

**Sc or e#**

**Sc**

10

1

2

3

2

1

2

2

1

1

1

2

3

3

3

1

3

2

0%

75 %

3

Auvinen et al. [37] No Yes 1 1 1 1 1 1 - 1 1 1 - 1 1 - 1 - 12/12

primary outcomes; (N) sample recruited from the same population; (O) adequate adjustment for confounders; and (P) sample loss to follow-up considered (corresponding to items 1–3, 5–7, 9–12, 17,18, 20, 21, 25, 26). \*, not informed, -, not applied. Items G and P were applied to only longitudinal studies. Items K and N were applied to only case-control and longitudinal studies. # Scores reach 100% at 12, 14, and 16 points for cross-sectional, case-control, and longitudinal studies, respectively. GRADE, Grading of Recommendations, Assessment, Development, and Evaluations; were one filled circle, very low quality; two filled circles, low quality; three filled circles, moderate quality; and four filled circles, high quality.

Farahbakhsh et al. [7] No Yes 1 1 1 0 1 1 - 1 0 0 - 1 1 - 1 - 9/12

2

3


56


**Table 4.** Characteristics of the studies included in the systematic review.

#### **Table 5.** Associated Factors.





**Table 5.** *Cont.*

CI, confidence interval; OR, odds ratio; RR, Relative Risk; Cramér's V, V is a measure of association between two nominal variables; χ2, chi-square. SLVDJ: single leg drops vertical jump.

#### *3.3. Assessment of the Prevalence of Spinal Injuries and Postural Changes*

Of the tools used to assess spinal injuries, 31.3% were radiographs (n = 5) [39,40,43, 48,55], 31.3% were questionnaires (n = 5) [36,46,51,53,57], and 18.8% comprised medical records (n = 3) [35,44,59]. The other studies used different tools to assess the prevalence of spine injuries, with 18.8% using magnetic resonance imaging (n = 3) (Table 3) [39,43,54]. Plurimeters (inclinometers) (n = 2) [16,52] were used in 66.7% of cases, and the Checkup-Adams' forward bend test and scoliometer measurement (n = 1) [33] were used in 33.3% of cases to assess postural changes.

The most common diagnoses were spondylolysis in 31.3% of the studies (n = 5) [40, 43,48,55,59], lumbar spine injuries in 25% (n = 4) [35,36,51,53], and cervical spine injuries in 18.8% (n = 3) [35,41,57]. Of these studies, 43.8% (n = 7) examined more than one postural change [35,43,44,46,51,57,59]. Among the postural changes, the most common abnormalities were hyperlordosis, hypolordosis, and hyperkyphosis in 66.7% of the studies (n = 2) [16,52].

For spinal injuries, the prevalence of low back injuries was 48.5% (n = 204) [51], whereas that of disk degeneration, spondylolysis, back injuries (lumbar, dorsal, and cervical), overuse injuries, and trunk displacement/separation in players was 42.9% (n = 63) [54], 33% (n = 194) [40], 33.3% (n = 66) [35], 15.4% (n = 13) [36], and 12.9% (n = 19,991), respectively [45]. With regard to postural changes, the prevalence of hyperkyphosis was 70% (n = 10) [16], and hypolordosis was 42.3% (n = 52) [52].

#### *3.4. Assessment of the Prevalence of Back Pain*

To assess the prevalence of back pain, self-reported questionnaires were used in 80% of the studies (n = 16) [6–8,10,11,34,37,38,42,46,47,49,50,54,56,58] and medical records in 10% (n = 2) [35,59]. In 80% (n = 16) of the studies, low back pain was identified [6–8,10,11,37,38, 43,46,47,49,50,54–56,59]; in 25% (n = 5) of the studies reported back pain [8,34,42,49,58]. In 25% (n = 5) of the studies, more than one outcome was reported for the location of back pain [7,8,37,42,49].

The prevalence of low back pain and back pain was 91% in 21 players [8], the prevalence of low back pain was 81% in 63 players [54], and of back pain was 70.9% in 182 participants [42]. The prevalence of neck pain ranged from 44.5% in a sample of 4314 players [37] to 26.5% in a sample of 182 players [42].

#### *3.5. Associated Factors*

Studies reported sex and age as factors that were associated with musculoskeletal disorders. Female basketball players had a higher injury rate than male players (IRR, 1.11 [CI: 0.44–2.71]; RR, 2.02 [CI: 1.01–4.03]) [46,51]. Furthermore, higher age was associated with low back pain (OR, 1.22 [CI: 1.05–1.41], *p* < 0.008) [7] and were more likely to suffer consecutive injuries (*p* = 0.010) [40]. Data on the associated factors found in the articles are presented in Table 5 but were insufficient to perform a meta-analysis.

#### **4. Meta-Analysis**

The overall prevalence of back pain was 43% [confidence interval (CI) of 95%: −1% to 88%] (Figure 2). Statistical heterogeneity between studies was high (I2 = 91.76%, *p* < 0.001). Thus, we performed a meta-regression analysis (tau2 = 0, I2 = 0.00). The analysis showed that heterogeneity had no influence on the result of the analysis. Using Egger's regression test, we found no evidence of publication bias in the meta-analysis of the overall prevalence of pain (*p* = 0.081). *Healthcare* **2023**, *11*, x FOR PEER REVIEW 21 of 29

#### **Figure 2.** Meta-analysis of overall prevalence of back pain [7,10,37,55,59].

**Figure 2.** Meta-analysis of overall prevalence of back pain. [7,10,37,55,59]. The prevalence of neck pain was 36% [95% CI, 22–50%], back pain was 16% [95% CI, 4–28%] (Figure 3), of low back pain was 26% [95% CI, 16–37%], and of thoracic spine pain was 6% [95% CI, 3–9%]. The combined prevalence of pain was 26% [95% CI, 17–34%]. There was high statistical heterogeneity for both back pain (I2 = 97.04%, *p* = 0.001) and low back pain (I2 = 99.37%, *p* = 0.001). Similarly, we performed a meta-regression analysis The prevalence of neck pain was 36% [95% CI, 22–50%], back pain was 16% [95% CI, 4–28%] (Figure 3), of low back pain was 26% [95% CI, 16–37%], and of thoracic spine pain was 6% [95% CI, 3–9%]. The combined prevalence of pain was 26% [95% CI, 17–34%]. There was high statistical heterogeneity for both back pain (I2 = 97.04%, *p* = 0.001) and low back pain (I2 = 99.37%, *p* = 0.001). Similarly, we performed a meta-regression analysis (Tau2 = 20.82, I2 = 0.001). The analysis showed that heterogeneity had no influence on the outcome of the analysis. Using the Egger regression test, we found evidence of publication bias in the meta-analysis of pooled prevalence (*p* = 0.001).

tion bias in the meta-analysis of pooled prevalence (*p* = 0.001).

(Tau2 = 20.82, I2 = 0.001). The analysis showed that heterogeneity had no influence on the outcome of the analysis. Using the Egger regression test, we found evidence of publica-

**Figure 3.** Meta-analysis of prevalence of neck pain, back pain, and low back pain [6– 10,11,34,35,37,38,42,43,46,47,49–51,53,54,56,58]. 42,43,46,47,49–51,53,54,56,58].

The pooled prevalence of spine injury and spondylolysis was 10% [95% CI, 4–15%] (Figure 4). The prevalence of spine injury was 3% [95% CI, 1–5%], and spondylolysis was 14% [95% CI, 0.1–27%]. There was high statistical heterogeneity for spondylolysis (I2 = 96.85%, *p* = 0.001). Therefore, we performed a meta-regression (tau2 = 0, I2 = 0.001). The Egger's regression test showed no evidence of publication bias (*p* <sup>=</sup> 0.187). **Figure 3.** Meta-analysis of prevalence of neck pain, back pain, and low back pain [6–11,34,35,37,38, The pooled prevalence of spine injury and spondylolysis was 10% [95% CI, 4–15%] (Figure 4). The prevalence of spine injury was 3% [95% CI, 1–5%], and spondylolysis was 14% [95% CI, 0.1–27%]. There was high statistical heterogeneity for spondylolysis (I2 = 96.85%, *p* = 0.001). Therefore, we performed a meta-regression (tau2 = 0, I2 = 0.001). The analysis showed that heterogeneity had no influence on the outcome of the analysis. Egger's regression test showed no evidence of publication bias (*p* = 0.187).

analysis showed that heterogeneity had no influence on the outcome of the analysis.

**Figure 4.** Meta-analysis of pooled prevalence of spinal injury and spondylolysis. [39,40,43,44,48,55]. **Figure 4.** Meta-analysis of pooled prevalence of spinal injury and spondylolysis. [39,40,43,44,48,55].

The pooled prevalence of hyperkyphosis and hyperlordosis was 30% [95% CI, 9– 51%] (Figure 5). The prevalence of hyperkyphosis was 28%, and of hyperlordosis was 13%. There was no evidence of statistical heterogeneity (I2 = 0.001). The pooled prevalence of hyperkyphosis and hyperlordosis was 30% [95% CI, 9–51%] (Figure 5). The prevalence of hyperkyphosis was 28%, and of hyperlordosis was 13%. There was no evidence of statistical heterogeneity (I2 = 0.001). *Healthcare* **2023**, *11*, x FOR PEER REVIEW 24 of 29

This is the first systematic review to examine the prevalence of back pain and musculoskeletal disorders in basketball players and to ascertain the associated factors. Our findings suggest a high overall prevalence of back pain, with neck pain and low back pain being the most prevalent. Among musculoskeletal disorders, spondylolysis was most prevalent among spinal injuries. The prevalence of hyperkyphosis was highest

This review found an overall prevalence of back pain of 43% in basketball players. These results corroborate the findings of Pasanen et al. [47], who showed that one in six young elite basketball players reported back pain as the predominant pain [47]. Our data indicate a prevalence of neck pain of 36% in basketball, which is consistent with Safiri et al. [60], which showed that the number of cases of neck pain in women was 166.0 million

Similarly, there were 568.4 million (95% IU: 505.0–640.6 million) cases of low back pain worldwide in 2019 [60], and our study showed a prevalence of 25% of low back pain in basketball players. According to Kim et al. [61], who studied college basketball players, the prevalence of low back pain was 69.8% in the last year of training and 84.1% throughout life [61]. In 2022, low back pain remained the largest contributor to the total number of cases of musculoskeletal disorders. There are 570 million cases worldwide,

Our study found a prevalence of spinal injuries of 3%. In addition to the direct effects of back injury on general health, the indirect effects of this injury could lead to the irreversible loss of future young athletes [1–3]. Furthermore, our study found a pooled prevalence of spine injuries and spondylolysis of 10% and a prevalence of spondylolysis

which account for 7.4% of years lived with disability [62].

(118.7–224.8), whereas in men it was 122.7 million (87.1–167.5) [59].

**5. Discussion** 

#### **5. Discussion**

This is the first systematic review to examine the prevalence of back pain and musculoskeletal disorders in basketball players and to ascertain the associated factors. Our findings suggest a high overall prevalence of back pain, with neck pain and low back pain being the most prevalent. Among musculoskeletal disorders, spondylolysis was most prevalent among spinal injuries. The prevalence of hyperkyphosis was highest among postural changes. Sex and age were associated with musculoskeletal disorders in this review, but the data were insufficient to perform a meta-analysis.

This review found an overall prevalence of back pain of 43% in basketball players. These results corroborate the findings of Pasanen et al. [47], who showed that one in six young elite basketball players reported back pain as the predominant pain [47]. Our data indicate a prevalence of neck pain of 36% in basketball, which is consistent with Safiri et al. [60], which showed that the number of cases of neck pain in women was 166.0 million (118.7–224.8), whereas in men it was 122.7 million (87.1–167.5) [59].

Similarly, there were 568.4 million (95% IU: 505.0–640.6 million) cases of low back pain worldwide in 2019 [60], and our study showed a prevalence of 25% of low back pain in basketball players. According to Kim et al. [61], who studied college basketball players, the prevalence of low back pain was 69.8% in the last year of training and 84.1% throughout life [61]. In 2022, low back pain remained the largest contributor to the total number of cases of musculoskeletal disorders. There are 570 million cases worldwide, which account for 7.4% of years lived with disability [62].

Our study found a prevalence of spinal injuries of 3%. In addition to the direct effects of back injury on general health, the indirect effects of this injury could lead to the irreversible loss of future young athletes [1–3]. Furthermore, our study found a pooled prevalence of spine injuries and spondylolysis of 10% and a prevalence of spondylolysis of 14%. Spondylolysis is an anatomic defect or fracture of the pars interarticularis (part of the neural arch located between the superior and inferior articular facets) of the vertebral arch, which occurs in the fifth lumbar vertebra (L5) in 85% to 95% of cases [63]. The higher percentage of spondylolysis can be explained by the risk factors for the development of this injury, which includes repetitive hyperextension and rotation of the lumbar spine that may occur in sports such as basketball [64].

Given the strong association between low back pain and sports activities that involve hyperextension with rotation of the lumbar spine, spondylolysis is a major concern in adolescent athletes [65]. This suggests that more frequent basketball training may have a negative effect on spinal positioning in basketball players [66]. Our study showed a pooled prevalence of hyperkyphosis and hyperlordosis of 30%, with a prevalence of hyperkyphosis of 28% and of hyperlordosis of 13%, in the sample.

In the study of basketball players conducted by Nam et al. [67], the sample had curvature values in the range of 37–42◦ , which represents a difference of approximately 10◦ as compared with the normal range [68]. In addition, Kaplan [69], when comparing basketball players and a control group to determine posture, found that the basketball group had a lateral spinal curvature, head positioned in the right sagittal plane, pelvic tilt, and thoracic kyphosis [70].

The first limitation of this study is the limitation may be different periods of back pain; example, we have studies that did not mention the period in which the prevalence was verified [6,38–41,43–46,48,52,55,57], and we also have studies that verified the prevalence in the last three months [33,42] up to the last five years [53]. Second, lack of definition of back pain in many studies, and the fact that different tools were used in the assessment of back pain [69], spinal injuries, and postural changes in the included studies, which makes it difficult to compare the results. Third, some studies could not be fully retrieved. Fourth, most studies had a cross-sectional design, which does not allow an inference of cause and effect. The strengths of this study include the performance of a meta-analysis that provided a general estimate of the prevalence of back pain, spinal injuries, and postural changes in basketball players. To our knowledge, this is the first systematic review to summarize the

evidence of the association between these musculoskeletal disorders in basketball players, which allows us to clarify some gaps in the literature and make recommendations for future research.

In this sense, future studies should consider the severity and duration of back pain, spine injuries, and postural changes to prevent players from withdrawing from sports for a long time [71]. The relationship between back pain, spine injuries, and postural changes should be further investigated, and the associated factors need to be analyzed. The results of our study indicate that clarifying the relationship between back pain, injuries, and postural changes is important for developing actions and programs to prevent and treat musculoskeletal disorders, thus contributing to the health and sports performance of basketball players. It is important for health professionals to be aware of the origin of back pain, spinal injuries, and postural changes, as well as the protective mechanisms that can be adopted for more effective interventions.

#### **6. Conclusions**

We found a significant overall prevalence of back pain in basketball players. On comparing the prevalence of this pain in the general population, the value found was lower, suggesting that basketball players have a lower prevalence of back pain than the general population. The most prevalent types of back pain were neck pain and low back pain, the most prevalent musculoskeletal disorder was spondylolysis, and the most prevalent postural change was hyperkyphosis.

**Supplementary Materials:** The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/healthcare11081190/s1, Table S1: Database search strategy.

**Author Contributions:** Conceptualization, S.C.d.C.B., C.R.M., R.M.F.S. and M.N.; methodology, S.C.d.C.B., C.R.M., R.M.F.S. and M.N.; software, S.C.d.C.B., C.R.M., R.M.F.S. and M.N.; validation, S.C.d.C.B., C.R.M., R.M.F.S. and M.N.; formal analysis, S.C.d.C.B., C.R.M., R.M.F.S. and M.N.; investigation, S.C.d.C.B., C.R.M., R.M.F.S. and M.N.; resources, S.C.d.C.B., C.R.M., R.M.F.S. and M.N.; data curation, S.C.d.C.B., C.R.M., R.M.F.S. and M.N.; writing—original draft preparation, S.C.d.C.B., C.R.M., R.M.F.S. and M.N.; writing—review and editing, S.C.d.C.B., C.R.M., R.M.F.S., A.D.V. and M.N.; visualization, S.C.d.C.B., C.R.M., R.M.F.S., A.D.V. and M.N.; supervision, A.D.V. and M.N.; project administration, A.D.V. and M.N. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Additional data can be obtained from the authors.

**Acknowledgments:** The authors would like to show their gratitude to Instituto Federal Goiano, Universidade Federal de Goiás and the Research Group on Child and Adolescent Health (www. gpsaca.com.br (accessed on 4 April 2023)) for the support.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


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