The Relationship Between Low Back Pain and Sagittal Spinal Alignment and Back Muscle Mass in Korean Fishery Workers

Article information

Ann Rehabil Med. 2023;47(6):459-467
Publication date (electronic) : 2023 November 22
doi :
1Department of Physical Medicine and Rehabilitation, Inje University Busan Paik Hospital, Inje University College of Medicine, Busan, Korea
2Center for Fishermen’s Safety and Health, Inje University Busan Paik Hospital, Busan, Korea
Correspondence: Nami Han Department of Physical Medicine and Rehabilitation, Inje University Busan Paik Hospital, 75 Bokji-ro, Busanjin-gu, Busan 47392, Korea. Tel: +82-51-890-6295 Fax: +82-51-890-5997 E-mail:
Received 2023 June 19; Revised 2023 August 29; Accepted 2023 September 6.



To investigate the relationship between low back pain (LBP) and sagittal spino-pelvic parameters along with the relationship between LBP and back muscle mass in Korean male and female fishery workers.


This retrospective study included a total of 146 subjects who underwent Fishermen’s health survey conducted between June 2018 and August 2020. LBP was evaluated through visual analogue scale (VAS) and Oswestry Disability Index (ODI). Sagittal spino-pelvic parameters were measured from whole spine standing X-rays. Back muscle cross-sectional areas were identified through lumbar spine magnetic resonance imaging and body composition was analyzed through bioelectrical impedance analysis.


The study included 75 males and 71 females, with an average age of 58.33 years for males and 56.45 years for females. Female subjects exhibited higher VAS and ODI scores, larger pelvic tilt (PT) and trunk fat mass and smaller trunk muscle mass compared to males. In female, ODI positively correlated with sagittal vertical axis (SVA) and PT. No significant correlations were found between ODI scores and body composition in either sex. The high ODI group showed greater SVA, PT, and pelvic incidence-lumbar lordosis and higher trunk fat/muscle ratio. Psoas muscle mass, total and skeletal muscle mass and trunk muscle mass of that group were smaller than those of low ODI group.


Spino-pelvic parameters and back muscle mass were associated with ODI and there were differences between Korean male and female fishery workers.



Low back pain (LBP) is a very common musculoskeletal problem around the world and is known as a major health problem as it causes disability. In particular, Korea is a world’s leading aging country and the prevalence of LBP is on the rise with increasing personal and social costs, raising its importance [1].

Occupation is known as a factor that affects the prevalence of LBP [2]. Occupational groups with increased prevalence of LBP included construction and extraction workers, community and social service workers, health care practitioners, technician, farmer, fisher, and forestry [2]. Among all male workers’ occupations, health care practitioners had the highest risk for LBP, whereas among female and middle-aged (41–64 years) workers, farming, fishing, and forestry occupations had the highest risk [2]. It is reported motions causing LBP include lifting, pushing, pulling, standing, or walking for a long time [3,4].

Various clinical factors including sagittal spino-pelvic alignment and back muscle mass are known to be associated with LBP. A number of studies have been conducted on the association between LBP, sagittal spino-pelvic parameters. Previous studies found that parameters like sagittal vertical axis (SVA), lumbar lordosis (LL), sacral slope (SS), pelvic incidence (PI) and pelvic tilt (PT) were associated with prevalence of LBP [5,6].

There are studies that have investigated the relationship between the incidence of LBP and sagittal spino-pelvic parameters in certain occupational group. A study found that larger SVA and smaller LL were observed in Korean farmers compared to the general population, and there was a positive correlation between their working time and SVA [7]. Additionally, a study reported that sagittal spino-pelvic alignment was identified as a strong determinant of LBP and blue-collar occupation is associated with increased SVA and PT/PI ratio [8]. However, research on fishery workers is insufficient, although they are known to be vulnerable to LBP.

In addition to spino-pelvic alignment, recent studies have documented the relationship between LBP and back muscle strength, size and structures [9]. To evaluate back muscle mass, various tools were used such as dual-energy X-ray absorptiometry (DEXA), muscle cross-sectional area (CSA) and bioelectrical impedance analysis (BIA). Some studies found that erector spinae or multifidus CSA were smaller in LBP group, compared to normal group [10,11]. In contrast, there is a study which found no difference in average trunk muscle area according to LBP severity [12]. A study also reported the correlation between trunk muscle mass measured with BIA, Oswestry Disability Index (ODI) and EuroQol 5 Dimension (EQ5D) score [13].

The aim of this study is to investigate the relationship between LBP and sagittal spino-pelvic parameters along with the relationship between LBP and back muscle mass in Korean male and female fishery workers. Furthermore, we aimed to find out how this correlation differs from general population or other occupational group.



This retrospective study enrolled 387 subjects who went through fisher’s low back musculoskeletal disorder health survey conducted from June 2018 to August 2020 in Inje University Busan Paik Hospital Center for Fishermen’s Safety and Health funded by Ministry of Oceans and Fisheries Affairs of the Republic of Korea. Institutional Review Board (IRB) of Inje University Busan Paik Hospital had reviewed and approved this study and informed consent requirement was waived based on the retrospective nature of this study (IRB No. 2022-11-048). Inclusion criteria for the study were as follows: (1) age between 40 to 64, (2) active fisherman, and (3) engagement in fishery for a minimum of 3 consecutive years at the point of examination. The exclusion criteria were as follows: (1) previous history of spinal accident or spine surgery, (2) presence of spinal tumor or fracture, and (3) insufficient data of exam such as questionnaire, whole spine standing X-ray, lumbar spine magnetic resonance imaging (MRI) and BIA (Fig. 1). Finally, a total of 146 subjects were included for statistical analysis.

Fig. 1.

Flow chart of study population selection. MRI, magnetic resonance imaging; BIA, bioelectrical impedance analysis.

Demographic characteristics

Data were collected from questionnaires and medical records. Variables included sex, age, work period in fishery, job classification, history of spinal surgery or accident. Job classification were as follows: fishing fishery (trap gill net, long line), aquaculture (shellfish, fish, and seaweeds), diving fishery such as Haenyeo (Korean female sea divers) and others like oyster shucker. Regarding spinal disorders, we retrospectively collected the data from prior MRI readings by a musculoskeletal specialized radiologist.


LBP severity were investigated through data collected from a face-to-face questionnaire. LBP severity was assessed using visual analogue scale (VAS) and ODI.

The ODI is considered as the gold standard of LBP functional outcome measure [14]. The ODI questionnaire consists of 10 items (pain intensity, difficulty in managing personal care, lifting, walking, sitting, standing, sleeping, sex life, social life, and traveling). Each item scores from 0 (no pain or disability) to 5 (worst pain or complete disability). The item associated with sex life is recommended to be conducted only if applicable. In this study, except for that one item, the scores for the nine items were added together. Final score was reported as percent using the following formula: ODI=sum of item scores (0–45)/maximum score (45)×100. The subjects were divided into two groups based on the ODI score, with a cutoff of 20%. Less than 20 was categorized as the low ODI group, while 21 or higher was classified as the high ODI group.

Sagittal spino-pelvic parameters

Whole spine standing lateral X-ray images were reviewed. The following parameters were measured by 2 examiners on the whole spine standing X-ray. The SVA is defined as the distance between C7 plumb line and superior-posterior corner of sacrum. LL is defined as the angle between upper margin of the first lumbar vertebra and upper margin of sacrum. SS is defined as the angle between upper margin of sacrum and the horizontal line. PI is defined as the angle between perpendicular bisector line of upper margin of sacrum and the line connecting the center of femoral head and the midpoint of upper margin of sacrum. PT is defined as the angle between the vertical line and the line connecting the center of femoral head and the midpoint of upper margin of sacrum (Fig. 2). Then the average value of two examiners’ measurements was used to reduce the measurement error.

Fig. 2.

Measurement of spino-pelvic parameters. LL, lumbar lordosis; SVA, sagittal vertical axis; SS, sacral slope; PI, pelvic incidence; PT, pelvic tilt.

Muscle mass measurement

Muscle mass was assessed using data from two methods: BIA and CSA measured on lumbar MRI. BIA had been conducted using InBody 370S (InBody). Whole body measurements had been taken with the subject in a standing barefoot on the rear sole electrodes of device with the arms abducted from the trunk. Subjects had been asked to hold the hand electrode so that the 4 fingers wrap the surface of the bottom hand electrode, and place the thumb on the oval electrode. All subjects had been required to be examined in the morning on an empty stomach. All tests had been performed by one examiner. Total fat mass, total muscle mass and skeletal muscle mass had been obtained. In addition, trunk fat/muscle ratio had been calculated by dividing trunk fat mass by trunk muscle mass.

Lumbar spinal MRI images taken in supine neutral position were reviewed by 2 examiners fot CSA parameters. Gross CSA of psoas muscle and paraspinal muscle (PSM) were measured at the lower edge of L4 vertebral level. PSM consist of erector spinae and multifidus muscle (Fig. 3). Each muscle’s CSA was obtained by adding both side measurements for each subject. Then, the final value was obtained calculating the average of two examiners’ measurements.

Fig. 3.

Axial view of lumbar spine magnetic resonance imaging. The cross-sectional areaof psoas major (PM), erector spinae (ES), and multifidus (MF) muscles were obtained on axial T2 weighted image at the lower edge of L4 spinal level.

Statistical analysis

To compare the difference of variables between male and female, independent t-test was performed. Independent student t-test was used for the comparison of sagittal spinal alignment, back muscle CSA, body composition between low ODI group, and high ODI group.

Correlation between ODI, spinal parameters and body composition mass were analyzed using Pearson’s correlation test. A p-value less than 0.05 was considered statistically significant. All statistics were analyzed using IBM SPSS version 23.0 (IBM Corp.).


Table 1 shows subject demographic characteristics and variables. Among all subjects, 75 (51.4%) were male and 71 (48.6%) were female. The average age was 58.33±4.98 years in male and 56.45±5.17 in female. Statistically significantly higher VAS, ODI score and greater PT, total fat mass, trunk fat mass, and trunk fat/muscle ratio were found in female compared to male. Male showed significantly higher age and larger PSM and psoas muscle mass, total muscle mass, skeletal muscle mass, and trunk muscle mass than female. There was a difference in the proportion of fishery type that female and male engaged in.

Demographic characteristics and variables of subjects

The prevalences of other spinal disorders are presented in Supplementary Table S1. The prevalence of at least one level of herniated intervertebral disc (HIVD) was found to be 19.18%, and the prevalence of advanced disc degeneration was 63.01%. In the case of facet joint degeneration (FJD), moderate degenerative disease was observed in 27.40% and severe degenerative disease was observed in 15.75% of subjects. When evaluating spondylolisthesis, 19.9% had mild spondylolisthesis.

Table 2 presents correlation between ODI, spino-pelvic parameters and body composition in male and female group. In female, positive correlation with ODI was found SVA (r=0.422, p<0.001) and PT (r=0.335, p=0.004). No statistically significant correlation was found in male. In both groups, no parameter measured by BIA showed statistically significant correlation with ODI. The ODI score did not correlate with any of muscle mass calculated by CSA on spine MRI.

Pearson’s correlation coefficients (r) for sagittal spino-pelvic alignment and body composition with the Oswestry Disability Index score

The high ODI group revealed greater SVA, PT and PI-LL (Table 3). They showed greater trunk fat/muscle ratio and smaller psoas muscle mass, psoas muscle mass divided by weight, total muscle mass, skeletal muscle mass, and trunk muscle mass (Table 4).

Comparison of sagittal spino-pelvic alignment between low ODI group and high ODI group

Comparison of back muscle CSA and body composition between low ODI group and high ODI group


Studies have been conducted on the relationship between spinal alignment, back muscle and LBP. In addition, sex differences have been noticed widely in the field of research about LBP and spine pathology. However, research on the relationship between LBP and spinal alignment has not been done for fishermen, although they are known to be highly exposed to working environment inducing LBP. This study is the first presented research that focused on a specific occupational group of Korean fishery workers. In this study, spino-pelvic parameters that showed differences among the ODI groups were SVA, PT, and PI-LL. Significant differences were observed in body composition parameters, including trunk fat/muscle ratio, psoas muscle mass, psoas muscle mass divided by weight, total muscle mass, skeletal muscle mass, and trunk muscle mass. We also found that ODI positively correlated with SVA and PT only in female.

According to previous studies, it is known that greater SVA, PI-LL, smaller LL, SS are associated with LBP [5,6]. The SVA is the most widely used measure of global sagittal balance and higher SVA value correlates with increased disability [6]. Regarding the relationship between LBP and PT, controversial results have been reported in previous studies [5,15]. Several studies were conducted on spinopelvic alignment of specific occupation like farmer [8,16]. Especially, a study recruiting Korean farmers revealed that LL was significantly smaller in subjects with LBP than in those without [17].

In our study subjected to Korean fishery workers, several parameters reflecting spino-pelvic alignment were observed to be related with ODI. Especially in female, there was a positive correlation between ODI score and SVA and PT, while no correlation was found in male. Based on an ODI score of 20, subjects were divided into low ODI group and high ODI group. The latter group showed greater SVA, PT, and PI-LL. It has been reported that SVA≥14.8 mm, PT≥17.9°, PI-LL≥2.7° are radiographic thresholds that predict moderate disability (ODI>20%) [15]. Consistent with previous research findings, larger SVA and PI were associated with more severe disability, and the previously controversial PT value also demonstrated such associations. Unlike the study of Korean farmers, there was no statistically significant LL difference between the low ODI group and the high ODI group in this study [17].

Recently, sarcopenia has attracted attention as one of the major causes of LBP. A number of papers have been published on the relationship between LBP and back muscle mass. Measuring CSA on MRI or computed tomography (CT) is widely used as accurate method of measuring the lumbar muscle mass. Studies found CSAs of back muscles such as multifidus, psoas and erector spinae were smaller in LBP patients [10,18]. A study also revealed that CSA of erector spinae was significantly smaller in chronic LBP group than that of the improved LBP group, suggesting the possibility of CSA of erector spinae as a prognostic factor [19]. However, it is still controversial which muscle is responsible among them.

DEXA, MRI, and CT require a lot of time, dedicated space for exam, are expensive, and there is also a limitation that DEXA and CT have the risk of radiation exposure. Therefore, interest in usefulness of BIA, which is easy, safe and cost-effective, is increasing. Several studies showed the amount of trunk muscle measured through BIA is proportional to the CSA of the actual back muscle and is also associated with the back muscle strength [20,21]. Additionally, a study demonstrated significant correlation between trunk muscle mass measured with BIA, ODI and EQ5D, and suggested the potential of BIA as an evaluation tool in patients with LBP [13].

In a paper on Korean farmers, ODI was found to have positive correlation with trunk fat/muscle ratio, total fat and visceral fat muscle mass in female farmers [22]. Back muscle mass and psoas muscle mass had no statistically significant correlation with the ODI score [22]. In this study of Korean fishery workers, no parameters measured by BIA or muscle mass calculated by CSA on spine MRI showed statistically significant correlation with ODI score in both male and female. Divided by ODI score, high ODI group had a larger trunk fat/muscle ratio and smaller total muscle mass, skeletal muscle mass, and trunk muscle mass. Similarly, it was found that psoas muscle CSA and psoas muscle CSA divided by weight are significantly smaller in high ODI group. As we did not reflect the muscle density, it can be thought that the psoas muscle, which is known to be less affected by fat infiltration than multifidus and erector spinae, showed significant difference [23].

The prevalence of LBP had been reported to be higher in female than in male, showing 1.28-fold higher among female in the 50-years or older age group [24]. In this study, VAS and ODI score of female were higher with statistical significance than those of male. Among spino-pelvic parameters, only PT angle presented statistically significant differernce between sexes, in contrast to a previous study on healthy population which reported that PI and PT were larger in female [25]. These sex differences can be affected by the subtypes of fishery work that they mainly engage in. 21.1% of female engaged in diving fishery while none of male did.

Workload and working posture also can contribute to the sex difference of LBP prevalence. A study found high workload is significantly associated with increased incidence of LBP in Danish fishermen [26]. A research showed that female were more likely to report back pain if they were “skilled agricultural, forestry, and fishery workers,” while LBP was found to be common in male engaging in “elementary occupation” [27] and contributed to our finding that specific pattern and posture of work, female generally assigned in, can provoke LBP. Regardless of the type of fishery, such as fishing fishery or aquaculture, male and female tend to have different division of roles. Females tend to work in squatting position doing manual jobs such as shucking oysters and trimming seafood or equipment. Working in sitting position with trunk flexion was suggested to be responsible for LBP in a research, which reported that the prevalence of lower back musculoskeletal disorders were 1.24 times higher in female shellfish gatherers [28]. Workload analysis for each fishery type is complicated because the environment and individual ways of work are not standardized and needed for further exploration of pathology of LBP.

For the sex differences in the correlation between LBP and spino-pelvic parameters, two other potential explanations are relevent based on our data. First, when comparing male and female in this study, female had higher ODI scores, which implies that a clear correlation with spino-pelvic alignment may only be observed when there’s a certain degree of disability. Second, based on the results of body composition analysis, female had smaller trunk muscle mass and greater trunk fat mass and fat/muscle ratio than those of male. The clinical importance of trunk muscle mass in association with disabilities arising from LBP was clarified in previous studies [29,30]. A study also found that the deterioration quality of life started with trunk muscle mass approximately <23 kg [31]. In this study, the average of trunk muscle mass was smaller in female as 19.70 kg, contributing to higher ODI score in female. Trunk muscle mass of male fishery workers was maintained larger (25.60 kg) and other parameters reflecting body composion such as total fat mass and skeletal muscle mass remained to be in better condition than those of female. For this reason, it can be assumed that the lack of trunk muscle mass in female did not exert an appropriate compensation mechanism for back pain caused by abnormal spinal alignment.

As this study aimed to explore the relationship between sagittal spine alignment, body composition, and LBP, we recognized the potential influence of structural anomalies of spine, such as HIVD, degenerative disc disease (DDD), FJD and spondylolisthesis. Consequently, we undertook a comprehensive review of the spinal disorders based on MRI findings (Supplementary Table S1). In this study, HIVD was observed in 19.18% and advanced disc degeneration was observed in 63.04% of the total participants. This rates appeared similar to the results of a previous study on asymptomatic individuals, where HIVD was identified in approximately 22% of individuals aged 40 to 59, and DDD was observed in 59% [32]. The prevalence of FJD also appeared to be consistent with prior research involving community-based populations [33]. Regarding the prevalence of spondylolisthesis, 80.14% were classified as normal and 19.86% exhibited grade 1 corresponding to less than 25% slippage. Similar finding had been identified with an earlier study targeting middle-aged individuals from the Beijing community which reported a prevalence of lumbar spondylolisthesis at 17.26% [34]. Based on these similar rates, it is assumed that these abnormal findings observed in the MRI of our study subjects can be considered not to exert a major impact on the outcomes of our research.

Several limitations should be considered in this study. First, it has targeted subjects who visited for medical check-up. Most of the subjects were able to walk independently and had almost no disability. Therefore, relatively good condition of participants made it hard to correlate variables with substantial degree of LBP that actually causes disability, as in patients visiting the spinal clinic. Second, this study was designed as a cross-sectional study. The results showed the relationships between LBP, spinal alignment and trunk muscle mass, but it could not be clearly determined which one is the cause or result of another. A longitudinal follow up and expanding to a cohort study is desirable. Third, we used gross CSA measurements within the borders of lumbar muscles not considering bias of muscle density. As we could not use Hounsfield units to reflect fat infiltration in muscle, we tried to increase the reliability of measurement by using the average value of the two examiners’ measurements. Finally, the differences in fishery working experience, daily working time, specific posture and working environment were not fully understood and reflected to our analysis.

In conclusion, this study suggests the relationship between LBP, sagittal spinal alignment and body composition in Korean male and female fishery workers. Multi-dimensional approach using spinal alignment and muscle mass can be considered for LBP evaluation especially when routine radiologic interpretation can not fully explain patient’s disability.



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


This work was supported by Ministry of Oceans and Fisheries Affairs of the Republic of Korea in 2018.


Conceptualization: Han N. Kim H. Methodology: Han N, Kim H, Nam H. Formal analysis: Kook M, Kim I, Seo J. Funding acquisition: Kim H, Han N. Project administration: Han N, Kook M. Visualization: Kook M, Kim I, Seo J. Writing – original draft: Kook M, Kim I. Writing – review and editing: Han N, Kook M, Nam H. Approval of final manuscript: all authors.


The authors thank the Ministry of Oceans and Fisheries Affairs of the Republic of Korea.


Supplementary materials can be found via

Supplementary Table S1.

Prevalence of spinal disorders based on magnetic resonance imaging findings



1. Hartvigsen J, Hancock MJ, Kongsted A, Louw Q, Ferreira ML, Genevay S, et al. What low back pain is and why we need to pay attention. Lancet 2018;391:2356–67.
2. Yang H, Haldeman S, Lu ML, Baker D. Low back pain prevalence and related workplace psychosocial risk factors: a study using data from the 2010 National Health Interview Survey. J Manipulative Physiol Ther 2016;39:459–72.
3. Macfarlane GJ, Thomas E, Papageorgiou AC, Croft PR, Jayson MI, Silman AJ. Employment and physical work activities as predictors of future low back pain. Spine (Phila Pa 1976) 1997;22:1143–9.
4. Keawduangdee P, Puntumetakul R, Chatchawan U, Kaber D, Siritaratiwat W. Prevalence and associated risk factors of low-back pain in textile fishing net manufacturing. Hum Factors Ergon Manuf Serv Ind 2012;22:562–70.
5. Chaléat-Valayer E, Mac-Thiong JM, Paquet J, Berthonnaud E, Siani F, Roussouly P. Sagittal spino-pelvic alignment in chronic low back pain. Eur Spine J 2011;20(Suppl 5):634–40.
6. Iyer S, Sheha E, Fu MC, Varghese J, Cunningham ME, Albert TJ, et al. Sagittal spinal alignment in adult spinal deformity: an overview of current concepts and a critical analysis review. JBJS Rev 2018;6e2.
7. Hong JH, Han MS, Lee SK, Lee JK, Moon BJ. Is the agricultural work a risk factor for Koreans elderly spinal sagittal imbalance? J Korean Neurosurg Soc 2020;63:623–30.
8. Araújo F, Lucas R, Alegrete N, Azevedo A, Barros H. Individual and contextual characteristics as determinants of sagittal standing posture: a population-based study of adults. Spine J 2014;14:2373–83.
9. Masaki M, Aoyama T, Murakami T, Yanase K, Ji X, Tateuchi H, et al. Association of low back pain with muscle stiffness and muscle mass of the lumbar back muscles, and sagittal spinal alignment in young and middle-aged medical workers. Clin Biomech (Bristol, Avon) 2017;49:128–33.
10. Danneels LA, Vanderstraeten GG, Cambier DC, Witvrouw EE, De Cuyper HJ. CT imaging of trunk muscles in chronic low back pain patients and healthy control subjects. Eur Spine J 2000;9:266–72.
11. Sions JM, Elliott JM, Pohlig RT, Hicks GE. Trunk muscle characteristics of the multifidi, erector spinae, psoas, and quadratus lumborum in older adults with and without chronic low back pain. J Orthop Sports Phys Ther 2017;47:173–9.
12. Hicks GE, Simonsick EM, Harris TB, Newman AB, Weiner DK, Nevitt MA, et al. Cross-sectional associations between trunk muscle composition, back pain, and physical function in the health, aging and body composition study. J Gerontol A Biol Sci Med Sci 2005;60:882–7.
13. Hori Y, Hoshino M, Inage K, Miyagi M, Takahashi S, Ohyama S, et al. Gender-specific analysis for the association between trunk muscle mass and spinal pathologies. Sci Rep 2021;11:7816.
14. Deyo RA, Battie M, Beurskens AJ, Bombardier C, Croft P, Koes B, et al. Outcome measures for low back pain research. A proposal for standardized use. Spine (Phila Pa 1976) 1998;23:2003-13. Spine (Phila Pa 1976) 1998;23:2003. :13. Erratum in: Spine 1999;24:418.
15. Schwab FJ, Blondel B, Bess S, Hostin R, Shaffrey CI, Smith JS, et al. Radiographical spinopelvic parameters and disability in the setting of adult spinal deformity: a prospective multicenter analysis. Spine (Phila Pa 1976) 2013;38:E803–12.
16. Zhang X, Yang W, Zheng Z, Wang J, Huang B, Fan S, et al. The influence of long-term shoulder loading on sagittal spino-pelvic morphology: a population-based retrospective study of Chinese farmers from radiology. J Orthop Surg Res 2020;15:196.
17. Park KH, Baek S, Kang EK, Park HW, Kim G, Kim SH. The association between sagittal plane alignment and disc space narrowing of lumbar spine in farmers. Ann Rehabil Med 2021;45:294–303.
18. Demoulin C, Crielaard JM, Vanderthommen M. Spinal muscle evaluation in healthy individuals and low-back-pain patients: a literature review. Joint Bone Spine 2007;74:9–13.
19. Lee HI, Song J, Lee HS, Kang JY, Kim M, Ryu JS. Association between cross-sectional areas of lumbar muscles on magnetic resonance imaging and chronicity of low back pain. Ann Rehabil Med 2011;35:852–9.
20. Salimi H, Ohyama S, Terai H, Hori Y, Takahashi S, Hoshino M, et al. Trunk muscle mass measured by bioelectrical impedance analysis reflecting the cross-sectional area of the paravertebral muscles and back muscle strength: a cross-sectional analysis of a prospective cohort study of elderly population. J Clin Med 2021;10:1187.
21. Fujimoto K, Inage K, Eguchi Y, Orita S, Toyoguchi T, Yamauchi K, et al. Dual-energy X-ray absorptiometry and bioelectrical impedance analysis are beneficial tools for measuring the trunk muscle mass of patients with low back pain. Spine Surg Relat Res 2019;3:335–41.
22. Baek S, Park HW, Kim G. Associations between trunk muscle/fat composition, narrowing lumbar disc space, and low back pain in middle-aged farmers: a cross-sectional study. Ann Rehabil Med 2022;46:122–32.
23. Crawford RJ, Elliott JM, Volken T. Change in fatty infiltration of lumbar multifidus, erector spinae, and psoas muscles in asymptomatic adults of Asian or Caucasian ethnicities. Eur Spine J 2017;26:3059–67.
24. Wáng YX, Wáng JQ, Káplár Z. Increased low back pain prevalence in females than in males after menopause age: evidences based on synthetic literature review. Quant Imaging Med Surg 2016;6:199–206.
25. Yukawa Y, Kato F, Suda K, Yamagata M, Ueta T, Yoshida M. Normative data for parameters of sagittal spinal alignment in healthy subjects: an analysis of sex specific differences and changes with aging in 626 asymptomatic individuals. Eur Spine J 2018;27:426–32.
26. Berg-Beckhoff G, Østergaard H, Jepsen JR. Prevalence and predictors of musculoskeletal pain among Danish fishermen - results from a cross-sectional survey. J Occup Med Toxicol 2016;11:51.
27. Park J, Han BY, Kim Y. sex differences in occupations and complaints of musculoskeletal symptoms: representative sample of South Korean workers. Am J Ind Med 2017;60:342–9.
28. Barreto Moreira Couto MC, Rocha Falcão I, Dos Santos Müller J, Batista Alves I, da Silva Viana W, Maria Cadena Lima V, et al. Prevalence and work-related factors associated with lower back musculoskeletal disorders in female shellfish gatherers in Saubara, Bahia-Brazil. Int J Environ Res Public Health 2019;16:857.
29. Parkkola R, Rytökoski U, Kormano M. Magnetic resonance imaging of the discs and trunk muscles in patients with chronic low back pain and healthy control subjects. Spine (Phila Pa 1976) 1993;18:830–6.
30. Goubert D, Oosterwijck JV, Meeus M, Danneels L. Structural changes of lumbar muscles in non-specific low back pain: a systematic review. Pain Physician 2016;19:E985–1000.
31. GBD 2017 Disease and Injury Incidence and Prevalence Collaborators. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet 2018;392:1789–858. Erratum in: Lancet 2019;393:e44.
32. Boden SD, McCowin PR, Davis DO, Dina TS, Mark AS, Wiesel S. Abnormal magnetic-resonance scans of the cervical spine in asymptomatic subjects. A prospective investigation. J Bone Joint Surg Am 1990;72:1178–84.
33. Kalichman L, Li L, Kim DH, Guermazi A, Berkin V, O'Donnell CJ, et al. Facet joint osteoarthritis and low back pain in the community-based population. Spine (Phila Pa 1976) 2008;33:2560–5.
34. He D, Li ZC, Zhang TY, Cheng XG, Tian W. Prevalence of lumbar spondylolisthesis in middle-aged people in Beijing community. Orthop Surg 2021;13:202–6.

Article information Continued

Fig. 1.

Flow chart of study population selection. MRI, magnetic resonance imaging; BIA, bioelectrical impedance analysis.

Fig. 2.

Measurement of spino-pelvic parameters. LL, lumbar lordosis; SVA, sagittal vertical axis; SS, sacral slope; PI, pelvic incidence; PT, pelvic tilt.

Fig. 3.

Axial view of lumbar spine magnetic resonance imaging. The cross-sectional areaof psoas major (PM), erector spinae (ES), and multifidus (MF) muscles were obtained on axial T2 weighted image at the lower edge of L4 spinal level.

Table 1.

Demographic characteristics and variables of subjects

Characteristics Male (n=75) Female (n=71) p-value
Age (yr) 58.33±4.98 56.45±5.17 0.03*
Visual analogue scale 2.45±2.89 3.49±2.86 0.03*
Oswestry Disability Index (%) 6.13±9.61 13.86±14.58 <0.001**
Body mass index (kg/m2) 25.21±3.14 25.67±3.44 0.40
Spino-pelvic parameter
 LL angle (°) 43.46±9.19 44.24±8.25 0.59
 SVA (mm) 5.51±23.55 4.29±25.35 0.76
 PI angle (°) 49.10±8.97 51.05±8.77 0.19
 SS angle (°) 35.08±6.66 35.11±8.02 0.98
 PT angle (°) 14.02±6.65 17.17±9.10 0.02*
 PI-LL (°) 5.56±10.78 7.01±10.38 0.44
Cross-sectional area
 Paraspinal muscle mass (cm2) 24.69±6.14 20.59±5.30 <0.001**
 Psoas muscle mass (cm2) 12.69±3.39 7.83±2.04 <0.001**
 Total fat mass-BIA (kg) 17.57±5.41 22.54±5.87 <0.001**
 Total muscle mass-BIA (kg) 51.66±5.88 39.37±5.60 <0.001**
 Skeletal muscle mass-BIA (kg) 30.54±3.73 22.67±3.52 <0.001**
 Trunk fat mass-BIA (kg) 9.39±3.17 11.72±3.26 <0.001**
 Trunk muscle mass-BIA (kg) 25.60±2.84 19.70±2.72 <0.001**
 Trunk fat/muscle ratio-BIA 0.37±0.10 0.60±0.14 <0.001**
Fishery types
 Fishing fishery 68 (90.7) 46 (64.8)
 Aquaculture 6 (8.0) 9 (12.7)
 Diving fishery 0 (0) 15 (21.1)
 Other 1 (1.3) 1 (1.4)

Values are presented as mean±standard deviation or number (%).

LL, lumbar lordosis; SVA, sagittal vertical axis; PI, pelvic incidence; SS, sacral slope; PT, pelvic tilt; BIA, bioelectrical impedance analysis.

p-values from mean comparisons are also reported *p<0.05 and **p<0.01.

Table 2.

Pearson’s correlation coefficients (r) for sagittal spino-pelvic alignment and body composition with the Oswestry Disability Index score

Male (n=75)
Female (n=71)
r p-value r p-value
Spino-pelvic alignment
 LL angle (°) -0.057 0.629 -0.127 0.293
 SVA (mm) 0.202 0.082 0.422** <0.001**
 PI angle (°) 0.076 0.515 0.090 0.456
 SS angle (°) 0.004 0.971 0.020 0.866
 PT angle (°) 0.099 0.399 0.335** 0.004**
 PI-LL (°) 0.112 0.339 0.214 0.073
Body mass index (kg/m2) -0.115 0.325 -0.099 0.412
Bioelectrical impedance analysis
 Total fat mass (kg) -0.141 0.226 -0.052 0.664
 Skeletal muscle mass (kg) -0.008 0.946 -0.058 0.631
 Trunk fat mass (kg) -0.139 0.233 -0.050 0.679
 Trunk muscle mass (kg) 0.010 0.930 -0.051 0.671
 Trunk fat/muscle ratio -0.117 0.317 -0.030 0.805
Cross-sectional area
 PSM mass (cm2) 0.133 0.257 0.141 0.240
 Psoas muscle mass (cm2) -0.20 0.085 -0.160 0.184
 PSM mass/weight (cm2/kg) 0.133 0.257 0.141 0.240
 Psoas muscle mass/weight (cm2/kg) -0.200 0.085 -0.160 0.184

LL, lumbar lordosis; SVA, sagittal vertical axis; PI, pelvic incidence; SS, sacral slope; PT, pelvic tilt; PSM, paraspinal muscle.

*p<0.05 and **p<0.01.

Table 3.

Comparison of sagittal spino-pelvic alignment between low ODI group and high ODI group

Low ODI (n=118) High ODI (n=28) p-value
LL angle (°) 44.13±8.99 42.61±7.51 0.408
SVA (mm) 1.97±23.05 17.31±26.24 0.002**
PI angle (°) 49.56±8.62 52.10±9.88 0.175
SS angle (°) 35.00±6.39 35.50±10.55 0.748
PT angle (°) 14.56±6.68 19.73±11.56 0.002**
PI-LL (°) 5.43±10.36 10.00±10.84 0.04*

Values are presented as mean±standard deviation.

ODI, Oswestry Disability Index; LL, lumbar lordosis; SVA, sagittal vertical axis; PI, pelvic incidence; SS, sacral slope; PT, pelvic tilt.

*p<0.05 and **p<0.01.

Table 4.

Comparison of back muscle CSA and body composition between low ODI group and high ODI group

Low ODI (n=118) High ODI (n=28) p-value
Body mass index (kg/m2) 25.47±3.23 25.30±3.59 0.816
 PSM mass (cm2) 22.85±6.37 21.97±4.77 0.494
 Psoas muscle mass (cm2) 10.90±3.78 7.91±2.18 <0.001**
 PSM mass/weight (cm2/kg) 0.33±0.08 0.34±0.07 0.46
 Psoas muscle mass/weight (cm2/kg) 0.16±0.05 0.12±0.03 <0.001**
 Total fat mass (kg) 19.63±6.07 21.48±6.34 0.154
 Total muscle mass (kg) 46.85±8.38 40.74±6.62 <0.001**
 Skeletal muscle mass (kg) 27.46±5.33 23.59±4.28 <0.001**
 Trunk fat mass (kg) 10.38±3.42 11.12±3.36 0.303
 Trunk muscle mass (kg) 23.29±4.02 20.39±3.39 0.001**
 Trunk fat/muscle ratio 0.46±0.16 0.56±0.16 0.004**

Values are presented as mean±standard deviation.

CSA, cross-sectional area; ODI, Oswestry Disability Index; PSM, paraspinal muscle; BIA, bioelectrical impedance analysis.

*p<0.05 and **p<0.01.