**3. Results**

#### *3.1. Descriptive Data*

The prevalence of LBP in the cohort is summarized in Table 2.


**Table 2.** Prevalence of low back pain.

#### *3.2. Outcome Data*

A total of 53 (12.9%) participants (23 (11.4%) male and 30 (14.3%) female) were found to have LBP among subjects randomly selected from the basic resident registry of a suburb town. There were no cases of acute LBP at the time of data acquisition. The prevalence of LBP for the 50's, 60's, 70's, and 80's age groups was 6.1%, 5.7%, 14.5%, and 20.0% in men and 17.0%, 6.6%, 14.8%, and 20.8% in women, respectively. The prevalence of LBP tended to increase with age, with the exception of 50's women. Similar results were observed between genders.

#### *3.3. Main Result*

In univariate analysis, the subject-specific factors of SVA, PI-LL mismatch, and aging had significant associations with LBP, while those of sex, BMI, BMD, SMI, and smoking did not. PI-LL mismatch was the only significant independent factor according to multivariate analysis, with an odds ratio of 1.91 (Table 3).


**Table 3.** Effects of subject-specific factors on low back pain.

BMI: body mass index, SMI: skeletal muscle mass index, BMD: bone mineral density, SVA: sagittal vertical axis, PI: pelvic incidence, LL: lumbar lordosis.

#### **4. Discussion**

#### *4.1. Key Result*

This study evaluated the prevalence and related factors of LBP by random sampling from the basic resident registry of a suburb town for subject selection with age and gender clustering on a general population basis. LBP prevalence tended to increase comparably with age for both genders apart from 50's women, for which social activities and stress were possible reasons for the higher incidence. Multivariate analysis considering various confounders, such as age, gender, and BMI, revealed PI-LL mismatch as an independent factor associated with LBP. These findings may help in the early detection and treatment of LBP in subclinical or asymptomatic community-dwelling members.

Although numerous factors have been linked to LBP, their authenticity remains under debate [8,9]. Several reports have described an association between obesity and LBP [21,22]. In one population-based study, BMI was significantly associated with higher chronic LBP prevalence in women [22]. Hirano et al. also showed BMI to be strongly associated with lumbar spinal canal stenosis in community-living people [23]. On the other hand, Dario et al. witnessed that BMI did not increase the risk of chronic LBP in a population of Spanish adult twin [24]. In another study, although obesity was not associated with overall chronic LBP, its impact was more pronounced for severe chronic LBP [25]. In the present investigation, BMI did not significantly associate with LBP. Social factors and lifestyle have also been cited in relation to LBP, with reports implicating smoking with LBP [26,27]. In contrast, smoking and alcohol were not significantly linked to LBP in a cross-sectional

prospective study of young twins [28], with conflicting associations for smoking [29,30]. We observed no remarkable associations for smoking with LBP.

Several reports have described a relationship between BMD and LBP [31–33]. A small-sample study argued that lower BMD of the lumbar spine was more frequent among LBP patients and that LBP could increase the risk of osteopenia [31]. On the other hand, another report found that participants with LBP had significantly higher lumbar BMD than did those without LBP, concluding that the presence of rotational asymmetry and associated motion restriction increased BMD in affected vertebrae [32]. A population-based cross-sectional study also showed an association for lumbar BMD with LBP [33]. In this investigation, however, BMD was not significantly related to LBP.

Regarding the influence of muscle mass, paraspinal muscle volume has been linked to sagittal spinal alignment [34–36]. Hori et al. described that trunk muscle mass was significantly associated with VAS scores in LBP patients visiting spinal outpatient clinics [37]. A systematic review showed that the cross-sectional area of the multifidus muscle was negatively related to LBP, with conflicting evidence for associations between the erector spinae, psoas, and quadratus lumborum cross-sectional area and LBP [38]. Our study found no significant impact for SMI on LBP.

In recent years, corrective surgeries for sagittal spinal deformity have been widely performed in older adults since such disorders were associated with impaired walking and mobility, respiratory and digestive symptoms, and LBP [39,40]. Multiple studies have stated that reduced lumbar lordosis is closely related to chronic LBP in adulthood [39,41]. Kitagawa et al. found that subjects with LBP showed significantly larger SVA and smaller LL as compared with the values of subjects without LBP in a study of total knee arthroplasty patients [42]. In our cohort, SVA > 50 mm, PI-LL mismatch, and aging were significantly associated with LBP in univariate analysis, although PI-LL mismatch alone remained associated with LBP in multivariate analysis (odds ratio: 1.91). A PI-LL mismatch is caused by a compensatory failure of the pelvis in spinal sagittal alignment. In a multicenter study of adult spinal deformity patients, a linear regression model demonstrated the threshold radiographical parameter for the Oswestry Disability Index of >40 to be PI-LL of 11◦ or more [43]. The results of our study sugges<sup>t</sup> that individuals with LBP may more frequently suffer from pelvic compensatory insufficiency in postural abnormalities.
