Abstract
Background:
Chronic pain is a significant public health concern in the United States. Obesity is associated with chronic pain. The body mass index may not accurately assess the health risks of obesity, and the body roundness index (BRI), a novel anthropometric indicator, may be more appropriate. However, the association between the BRI and chronic pain has not been validated. Therefore, this study examined the association between the BRI and chronic pain among adults in the United States.
Methods:
This cross-sectional study analyzed data from adult participants in the 1999–2004 National Health and Nutrition Examination Survey. Chronic pain was defined as self-reported pain lasting 3 months or more in the past year. The BRI was calculated using height and waist circumference. Multivariable logistic regression models and restricted cubic splines were used to assess the association between the BRI and chronic pain. Subgroup analyses were performed to explore confounder effects.
Results:
Of the 11,599 participants aged 20 years or older, 1690 (15.92%) had chronic pain. In fully adjusted models, the BRI was positively associated with chronic pain [odds ratio (OR) = 1.05, 95% confidence interval (CI) = 1.02–1.09]. Compared with participants in the lowest BRI quintile (Q1), those in the highest quintile (Q5) had an adjusted OR of 1.28 (95% CI = 1.07–1.54) for chronic pain. The multivariable restricted cubic spline showed a nonlinear association between the BRI and chronic pain. In two piecewise regression models, participants with BRI ≥ 4.63 had an adjusted OR of 1.07 (95% CI = 1.00–1.13) for chronic pain; however, no correlation was observed for participants with the BRI < 4.63. Further subgroup analyses revealed no significant interactions between these variables.
Conclusion:
Higher BRI was associated with an increased risk of chronic pain, indicating that the BRI was a significant risk factor. Therefore, regular monitoring and preventive measures are required to maintain optimal BRI levels and prevent chronic pain.
Keywords: body roundness index, chronic pain, cross-sectional study, NHANES, obesity
Introduction
Chronic pain is a significant global health issue affecting millions of people and challenging health care systems[1]. It impacts both physical and mental health and often leads to anxiety and depression[2,3]. In 2021, approximately 20.9% of adults in the United States experienced chronic pain, with 6.9% suffering from high-impact chronic pain[4,5]. In Brazil, the prevalence of chronic pain among adults ranges from 23.02% to 41.4%[6]. Consequently, the management of chronic pain continues to pose a significant challenge. A comprehensive understanding of the factors that influence chronic pain is essential to develop effective prevention and control strategies.
HIGHLIGHTS
Body roundness index (BRI) may assess the health risks of obesity better than body mass index.
A cross-sectional analysis of adults in the United States was conducted.
BRI was positively associated with chronic pain.
High BRI values are a significant risk factor of chronic pain.
Regular monitoring and preventive measures are required.
Obesity is another major public health problem closely associated with chronic pain[7]. It increases the risk of pain-related disabilities, exacerbates pain, reduces physical functioning, and negatively affects mental health[8]. Research indicates that a body mass index (BMI) of 30 or above is correlated with increased self-reported pain and a higher likelihood of chronic pain in the lower back, knees, and hips[9-12]. Previous studies have primarily used BMI as a measure of obesity; however, recent findings suggest that BMI cannot differentiate between central and peripheral fat and may not accurately assess the health risks associated with obesity[13]. Thomas et al suggested that the body roundness index (BRI) is a better predictor of visceral and body fat percentage[14], which has been demonstrated in a variety of populations. The BRI surpasses traditional anthropometric measures and demonstrates a strong correlation with visceral adipose tissue, as assessed using computed tomography imaging[15].
The BRI is associated with many diseases, including cardiovascular[16], metabolic[17,18], non-alcoholic fatty liver[19,20], and kidney stone diseases[21]. Previous studies have indicated that the BRI is a reliable predictor of cardiovascular disease[15,22], diabetes mellitus[23], metabolic syndrome[24], and various other diseases[25–27]. Zhang et al found a trend of increasing BRI in adults in the United States over a period of nearly 20 years. Furthermore, the BRI is correlated with all-cause mortality among adults in the United States, suggesting its significance in health evaluation and disease prognostication[28]. However, the association between the BRI and chronic pain has not yet been validated. Therefore, this study examined the relationship between the BRI and chronic pain among adults in the United States.
Materials and methods
Data sources and study population
This cross-sectional study used data from the National Health and Nutrition Examination Survey (NHANES) conducted between 1999 and 2004. The NHANES assessed the health and nutritional status of non-institutionalized individuals in the United States using a stratified multistage probability sampling[29]. It was conducted by the National Center for Health Statistics (NCHS)[30]. Ethical approval for the NHANES was granted by the NCHS Ethics Review Committee, and all participants provided written informed consent prior to participation. The secondary analysis of these data did not require further ethical approval[31]. Information regarding the NHANES database can be obtained at https://www.cdc.gov/nchs/nhanes/index.htm. The present analysis included participants aged 20 years or older and excluded those with missing data on chronic pain, body measurements, or covariates. The work has been reported in line with the Strengthening The Reporting Of Cohort Studies In Surgery (STROCSS) criteria[32].
Chronic pain
The 11th edition of the International Classification of Diseases defines chronic pain as pain that lasts longer than 3 months and is either continuous or recurrent[33]. The McGill Pain Questionnaire (MPQ) was used to assess the qualitative and quantitative elements of pain, including sensory, affective, and evaluative dimensions[34]. The present study assessed chronic pain by comparing the values of two items: MPQ100 (Pain problem lasting more than 24 hours) and MPQ110 (How long have you experienced this pain?). MPQ100 denotes the existence of pain lasting more than 24 hours in the past month, whereas MPQ110 reflects the duration of the pain. Participants who had been in pain for 3 months or more (MPQ100 = 1, MPQ110 = 3 or 4) were classified as having chronic pain. Participants who reported no pain issues in the past month (MPQ100 = 2) and those with pain problems lasting less than 3 months (MPQ100 = 1, MPQ110 = 1 or 2) were considered to have chronic pain (control group).
BRI assessment
The BRI is designed to evaluate an individual’s body type by measuring height (in centimeters) and waist circumference (WC, in centimeters). Height and WC data were extracted from the participants’ examination records. To ensure precision in the measurements, trained health technicians collected anthropometric data at Mobile Examination Centers (MECs), with the assistance of a recorder who facilitated the process. The participants were required to remove their clothing and footwear prior to the measurement to ensure accuracy. Height was measured as the vertical distance from the floor to the top of the head while the participant was standing. WC was assessed in an upright standing position, representing the measurement taken at the midpoint between the lower rib and iliac crest. The BRI was calculated using the following formula:
BRI = 364.2 − 365.5 × (1 − [WC(m)/2π]2/[0.5 × height(m)]2)½
Covariates
Based on the existing literature, multiple potential covariates were assessed, including gender, age, race/ethnicity, marital status, education, poverty income ratio (PIR), physical activity, smoking status, hypertension, diabetes mellitus, history of cardiovascular disease, and stroke. Race/ethnicity was classified as non-Hispanic white, non-Hispanic black, Mexican American, or other. Marital status was categorized as married, living with a partner, or living alone. Educational level was classified into three categories: less than 9 years, 9–12 years, and ≥12 years. PIR was utilized to classify family income into three groups: low (PIR ≤ 1.3), medium (PIR > 1.3–3.5), and high (PIR > 3.5). Physical activity was categorized as sedentary, moderate (at least 10 minutes of exercise resulting in only light sweating or a mild to moderate increase in breathing or heart rate in the past 30 days), and vigorous (at least 10 minutes of activity, resulting in heavy sweating or an increase in breathing or heart rate in the past 30 days). Smoking status was divided into three categories: never smoked (<100 cigarettes), current smoker, and former smoker. Previous diseases (hypertension, diabetes, stroke, and coronary heart disease) were determined using a questionnaire asking whether the clinician had ever been notified of an illness. Considering the mathematical collinearity between the BRI and BMI, the BMI was excluded from the initial model to avoid estimation bias. As the depression questionnaire (CIQMDEP) was only administered to individuals aged 20–39 years, no adjustment was made for depression to avoid introducing a selection bias.
Statistical analyses
In accordance with NHANES recommendations and guidelines, an appropriate sampling weight was determined and incorporated to account for the complex multistage survey design strategies used in the study[35]. National estimates of household questionnaire data were obtained using the primary sample unit (sdmvpsu) and stratum (sdmvstra) variables. A 4-year MEC weight (WTMEC4YR) was used for the 1999–2002 NHANES data, whereas a 2-year MEC weight (WTMEC2YR) was applied for the 2003–2004 NHANES data. The sampling weights for the 1999–2004 data were computed as follows:
1999–2002 weights = 2/3 × WTMEC4YR; otherwise, 1/3 × WTMEC2YR.
Categorical variables were presented as unweighted numbers (weighted percentages), whereas continuous variables were described as means (standard errors). A one-way analysis of variance (for continuous variables) and chi-square tests (for categorical variables) were used to compare the characteristics among groups. Multivariate logistic regression models were used to calculate the odds ratio (OR) and 95% confidence interval (CI) for the relationship between BRI and chronic pain. Model 1 was a crude model without adjustment variables. Model 2 was adjusted for demographics and socioeconomic factors (age, gender, race/ethnicity, PIR, marital status, and educational level). Model 3 was adjusted for the factors included in Model 2, as well as health status and lifestyle factors (hypertension, diabetes mellitus, cardiovascular disease history, stroke, smoking status, and physical activity). The BRI was categorized into quintiles (Qs), with Q1 as the reference group. A multivariate logistic regression was used to analyze BRI as continuous and categorical variables, and a trend test was conducted. Furthermore, the restricted cubic spline approach was used to fit curves for the relationship between the BRI and chronic pain. A two-piece logistic regression model was created to evaluate the association between the BRI and chronic pain, adjusting for potential confounders in Model 3.
Additionally, to determine whether the relationship between the BRI and chronic pain was stable in the population, interaction and subgroup analyses were conducted according to gender, age (20–50 years vs. >50 years), hypertension, diabetes, coronary heart disease, and stroke. Logistic regression models and likelihood ratio tests were used to assess heterogeneity and interactions between subgroups, respectively.
All analyses were performed using R Statistical Software (Version 4.2.2, http://www.R-project.org, The R Foundation) and Free Statistics analysis platform (Version 2.0, Beijing, China). Two-sided P values <0.05 were considered statistically significant.
Results
Participant characteristics
This study included 11,599 participants. The inclusion and exclusion processes are presented in Fig. 1. Table 1 shows the participant characteristics according to the BRI quintiles. Among the participants, 1690 (15.92%) had chronic pain.
Figure 1.
Flow chart of the screening and enrollment of study participants.
Table 1.
Baseline characteristics of included individuals according to body roundness index (BRI)
| Variables | Total | Q1 (≤3.44) | Q2 (3.45-4.44) | Q3 (4.45-5.39) | Q4 (5.40-6.73) | Q5 (>6.73) | P-value |
|---|---|---|---|---|---|---|---|
| Number of participants | 11,599 | 2320 | 2320 | 2319 | 2320 | 2320 | |
| Gender, n (%) | <0.001 | ||||||
| Male | 5513 (47.94) | 1150 (44.89) | 1204 (52.76) | 1269 (56.24) | 1099 (48.69) | 791 (36.18) | |
| Female | 6086 (52.06) | 1170 (55.11) | 1116 (47.24) | 1050 (43.76) | 1221 (51.31) | 1529 (63.82) | |
| Age (years) | 45.63 (16.50) | 38.18 (14.21) | 44.20 (15.93) | 48.05 (16.11) | 50.97 (16.61) | 50.03 (16.45) | <0.001 |
| Race/ethnicity, n (%) | <0.001 | ||||||
| Non-Hispanic White | 5957 (72.67) | 1314 (75.11) | 1214 (72.38) | 1177 (72.19) | 1192 (73.67) | 1060 (68.94) | |
| Non-Hispanic Black | 2194 (10.46) | 526 (11.03) | 417 (9.63) | 374 (8.81) | 371 (9.39) | 506 (13.66) | |
| Mexican American | 2547 (7.03) | 292 (4.52) | 486 (7.15) | 577 (8.38) | 595 (8.12) | 597 (7.89) | |
| Others | 901 (9.84) | 188 (9.33) | 203 (10.85) | 191 (10.62) | 162 (8.82) | 157 (9.51) | |
| Education level (year), n (%) | <0.001 | ||||||
| <9 | 1658 (6.31) | 155 (3.39) | 278 (5.23) | 366 (6.77) | 439 (9.30) | 420 (8.29) | |
| 9–12 | 4656 (38.91) | 845 (33.09) | 907 (37.10) | 940 (40.36) | 945 (41.94) | 1019 (44.92) | |
| >12 | 5285 (54.78) | 1320 (63.52) | 1135 (57.68) | 1013 (52.86) | 936 (48.76) | 881 (46.79) | |
| Marital status, n (%) | <0.001 | ||||||
| Married or living with a partner | 7292 (65.07) | 1262 (57.58) | 1524 (68.40) | 1567 (69.43) | 1564 (69.70) | 1375 (62.07) | |
| Living alone | 4307 (34.93) | 1058 (42.42) | 796 (31.60) | 752 (30.57) | 756 (30.30) | 945 (37.93) | |
| Family income, n (%) | <0.001 | ||||||
| Low | 3278 (21.28) | 595 (20.31) | 589 (19.26) | 600 (17.81) | 693 (22.20) | 801 (28.21) | |
| Medium | 4478 (35.90) | 824 (32.62) | 876 (34.33) | 936 (38.21) | 920 (37.86) | 922 (38.01) | |
| High | 3843 (42.82) | 901 (47.07) | 855 (46.40) | 783 (43.98) | 707 (39.94) | 597 (33.78) | |
| Hypertension, n (%) | 2983 (22.07) | 228 (7.77) | 411 (14.93) | 606 (21.97) | 781 (32.61) | 957 (41.13) | <0.001 |
| Diabetes, n (%) | 1102 (6.57) | 42 (1.32) | 129 (3.40) | 191 (5.30) | 297 (9.86) | 443 (16.26) | <0.001 |
| Coronary heart disease, n (%) | 509 (3.54) | 40 (1.06) | 78 (2.64) | 131 (4.78) | 128 (5.23) | 132 (5.17) | <0.001 |
| Stroke, n (%) | 347 (2.19) | 28 (0.85) | 50 (1.52) | 78 (2.54) | 94 (3.22) | 97 (3.53) | <0.001 |
| Physical activity, n (%) | <0.001 | ||||||
| Sedentary | 4978 (35.56) | 727 (25.85) | 876 (31.30) | 1000 (36.08) | 1128 (41.98) | 1247 (47.85) | |
| Moderate | 3343 (29.86) | 583 (25.88) | 647 (27.96) | 715 (32.08) | 710 (33.38) | 688 (31.93) | |
| Vigorous | 3278 (34.58) | 1010 (48.27) | 797 (40.74) | 604 (31.84) | 482 (24.65) | 385 (20.23) | |
| Smoking status, n (%) | <0.001 | ||||||
| Never | 5954 (49.93) | 1203 (51.79) | 1194 (49.86) | 1183 (49.55) | 1144 (47.46) | 1230 (50.27) | |
| Former | 3089 (25.13) | 407 (17.68) | 560 (23.82) | 683 (27.34) | 754 (31.54) | 685 (28.52) | |
| Current | 2556 (24.95) | 710 (30.54) | 566 (26.32) | 453 (23.11) | 422 (21.00) | 405 (21.21) | |
| Chronic pain, n (%) | 1690 (15.91) | 286 (12.82) | 285 (14.24) | 324 (15.53) | 372 (18.34) | 423 (20.44) | <0.001 |
%, Weighted proportion; Q1–Q5: Quintile according to body roundness index.
Data presented as unweighted numbers (weighted percentage) for categorical variables and mean (standard error) for continuous variables.
The average age of the study participants was 45.62 (16.50) years, and 6082 (52.06%) participants were female. With increasing BRI quintiles, participants were more likely to be female; be non-Hispanic white; have a higher educational level; be married or living with a partner; have a medium family income; and have a higher incidence of hypertension, diabetes, coronary heart disease, and stroke.
Association between the BRI and chronic pain
After adjusting for age, gender, race/ethnicity, PIR, marital status, education level, hypertension, diabetes mellitus, cardiovascular disease history, stroke, smoking status, and physical activity, the BRI was positively associated with chronic pain (OR = 1.05, 95% CI = 1.02–1.09, P = 0.004). This association was maintained when the BRI was transformed into a categorical variable using quintiles. Compared with participants (in Q1) (≤3.44), those in Q5 (>6.73) had an adjusted OR of 1.28 for chronic pain (95% CI = 1.07–1.54, P = 0.011; Table 2).
Table 2.
The association between body roundness index (BRI) and chronic pain
| Variables | Model 1 | Model 2 | Model 3 | |||
|---|---|---|---|---|---|---|
| OR (95% CI) | P-value | OR (95% CI) | P-value | OR (95% CI) | P-value | |
| Continuous | ||||||
| BRI | 1.11 (1.08–1.13) | <0.001 | 1.08 (1.05–1.11) | <0.001 | 1.05 (1.02–1.09) | 0.004 |
| Categorized | ||||||
| Q1 (≤3.44) | Reference | Reference | Reference | |||
| Q2 (3.45–4.44) | 1.13 (0.90–1.41) | 0.283 | 1.09 (0.87–1.36) | 0.442 | 1.07 (0.86–1.34) | 0.506 |
| Q3 (4.45–5.39) | 1.25 (1.00–1.56) | 0.048 | 1.19 (0.96–1.46) | 0.102 | 1.14 (0.93–1.39) | 0.199 |
| Q4 (5.40–6.73) | 1.53 (1.22 ~ 1.90) | <0.001 | 1.35 (1.06 ~ 1.73) | 0.016 | 1.23 (0.95–1.60) | 0.113 |
| Q5 (>6.73) | 1.75 (1.47–2.08) | <0.001 | 1.52 (1.28–1.80) | <0.001 | 1.28 (1.07–1.54) | 0.010 |
| P for trend | <0.001 | <0.001 | 0.015 | |||
BRI: body roundness index; CI, confidence interval; OR, odds ratio; Q1–Q5: Quintile according to BRI.
Crude model: Unadjusted. Model 1 was the crude model without adjustment for covariates. Model 2 was adjusted for age, gender, race/ethnicity, poverty income ratio, marital status, and education level. Model 3 was adjusted as for Model 2, additionally adjusted for hypertension, diabetes mellitus, cardiovascular disease history, stroke, smoking status, physical activity.
After multivariate adjustments (Model 3), a nonlinear relationship was observed between the BRI and chronic pain (P = 0.004), (Fig. 2). In two piecewise regression models, participants with BRI values ≥4.63 had an adjusted OR of 1.07 for chronic pain (95% CI = 1.00–1.13, P = 0.04), whereas no association was observed between the BRI and chronic pain in participants with BRI values <4.63(Table 3).
Figure 2.
Association between BRI and chronic pain. Solid and dashed lines indicate the predicted value and 95% CI. The restricted cubic spline model was adjusted for age, gender, race, poverty income ratio, marital status, education level, hypertension, diabetes mellitus, cardiovascular disease history, stroke, smoking status, and physical activity. BRI, body roundness index.
Table 3.
Association between BRI and chronic pain using two-piecewise regression models
| Crude model | Adjusted modela | |||
|---|---|---|---|---|
| BRI | OR (95% CI) | P-value | OR (95% CI) | P-value |
| <4.63 | 1.13(0.98-1.29) | 0.090 | 1.08(0.94, 1.24) | 0.290 |
| ≥4.63 | 1.11(1.06-1.17) | <0.001 | 1.07(1.00, 1.13) | 0.040 |
BRI: body roundness index; CI, confidence interval; OR, odds ratio.
Adjusted for age, gender, race/ethnicity, poverty income ratio, marital status, and education level, hypertension, diabetes mellitus, cardiovascular disease history, stroke, smoking status, and physical activity.
Subgroup analyses
A stratified analysis was performed for several subgroups to assess the effects of modifications on the relationship between the BRI and chronic pain. No significant interactions were observed in any subgroup after stratification by gender (male vs. female), age (20–50 vs. >50 years), hypertension (yes vs. no), diabetes mellitus (yes vs. no), cardiovascular disease history (yes vs. no), or stroke (yes vs. no). These analyses supported the robustness of the results for different populations (all P-values for interaction >0.05; Fig. 3).
Figure 3.
Association between body roundness index (BRI) and chronic pain according to the general characteristics. Except for the stratification factor itself, the stratifications were adjusted for all variables (age, gender, race, poverty income ratio, marital status, education level, hypertension, diabetes mellitus, cardiovascular disease history, stroke, smoking status, and physical activity). BRI, body roundness index.
Discussion
This study revealed a positive association between the BRI and chronic pain. A one-unit increase in the BRI corresponded to a 5% increase in the risk of chronic pain. Individuals in the highest BRI quintile had a 28% higher risk of chronic pain than those in the lowest quintile. This association remained robust after adjusting for all covariates and persisted in the subgroup analyses. Furthermore, a nonlinear relationship was observed between the BRI and chronic pain, with an inflection point of 4.63. A BRI exceeding 4.63 reflects a pathophysiological threshold in the body, similar to a visceral fat area above 100 cm2, triggering macrophage infiltration, which releases Interleukin-6/C-Reactive Protein (IL-6/CRP) and leads to central sensitization. A BRI exceeding 4.63 corresponds to the WC risk threshold (94 cm for men and 80 cm for women) established by the World Health Organization[36]. In primary care, a BRI exceeding 4.63 can be used to screen for risk of pain, thereby avoiding costly imaging studies.
The nonlinear relationship between the BRI and chronic pain can be attributed to multiple interrelated physiological mechanisms. The BRI reflects the distribution of body fat. The metabolic and inflammatory properties of fat fluctuate with changes in fat distribution. At lower BRI levels, subcutaneous fat, which is primarily metabolically inert, is predominant. However, at higher BRI levels, a shift occurs toward visceral adipose tissue, which has pro-inflammatory properties. The accumulation of visceral adipose tissue, particularly when the BRI exceeds 4.63, is closely associated with NOD-like receptor family pyrin domain containing 3 (NLRP3)-mediated neuroinflammation and pain sensitization. Additionally, adipose tissue secretes various hormones and metabolic factors, such as leptin, adiponectin, and insulin, which play roles in inflammation, insulin resistance, and pain perception. Critical BRI thresholds, such as a leptin-adiponectin imbalance (BRI > 4.5), may disrupt endocrine homeostasis and amplify the IL-6/CRP cascade, whereas insulin resistance may exacerbate neurosensitization. Furthermore, the cubic relationship between the BRI and abdominal volume causes mechanical stress on joints and muscles to increase exponentially. When BRI exceeds 5.2, the mechanical load on the spine and knees surpasses the body’s adaptive capacity, accelerating structural damage and leading to chronic pain[37].
The results of this study align with the findings of previous studies, which have shown that obesity is significantly associated with an increased likelihood of experiencing chronic pain among adults in the United States[38]. The relationship between the BRI and chronic pain can be explained by inflammatory and biomechanical stress mechanisms. The BRI reflects body fat distribution, particularly visceral adiposity, which is more metabolically active and pro-inflammatory than subcutaneous fat. Visceral fat releases inflammatory cytokines, such as IL-6 and TNF-α, which contribute to systemic inflammation and nociceptor sensitization, thereby amplifying pain signals[39]. In terms of biomechanics, a higher BRI indicates a central fat distribution, which alters the center of mass and increases mechanical stress on the musculoskeletal system. This can lead to spinal and joint strain, accelerate joint degeneration, and increase the risk of musculoskeletal injuries and chronic pain. For instance, excess abdominal fat may cause an anterior pelvic tilt, which strains spinal structures and contributes to low back pain, whereas obesity increases the load on weight-bearing joints and exacerbates osteoarthritis[40]. Additionally, the BRI is more effective than other anthropometric indicators in predicting the risk of various clinical outcomes, such as depression, cardiometabolic disease, kidney disease, and cancer[16,21,35,41]. These conditions are often comorbid with chronic pain, suggesting that a higher BRI may indicate a higher risk of chronic pain due to the associated health complications. Therefore, elevated BRI may serve as a valuable predictor of chronic pain.
Nevertheless, this study had several limitations. First, due to the cross-sectional nature of this study, a causal association between the BRI and chronic pain could not be established. Second, despite extensive adjustments for possible confounders, the possibility of reverse causation and residual confounding factors could not be completely eliminated. Certain factors may contain novel signs that were not addressed in this study. Third, although the use of MPQ100 and MPQ110 as proxies for chronic pain is practical for large-scale surveys such as the NHANES, it may not fully capture the nuanced dimensions of pain assessed by the complete MPQ. Future studies should incorporate more comprehensive pain assessment tools and clinical evaluations to validate the present findings. Finally, although this study used a large sample size, the study population was limited to adults in the United States. Further research is required to evaluate whether the current findings can be generalized to other groups.
Conclusion
This study suggests that the BRI is positively associated with chronic pain in adults in the United States. The BRI can be used as a simple anthropometric indicator to predict chronic pain. Therefore, regular monitoring and preventive measures are required to maintain optimal BRI and prevent chronic pain. Further research is required to explore the potential mechanisms underlying the BRI and explore the benefits for patients with chronic pain.
Footnotes
Sponsorships or competing interests that may be relevant to content are disclosed at the end of this article.
Contributor Information
Weiai Jia, Email: jiaweiai-546@126.com.
Hemei Wang, Email: wanghemei93@126.com.
Fangfang Yong, Email: yff2017@hebmu.edu.cn.
Wei Liu, Email: liuvice@163.com.
Jingpu Shi, Email: shijingpu1007@163.com.
Huiqun Jia, Email: jysyjiahuiqun@163.com.
Ethical approval
Ethical approval for the NHANES was granted by the NCHS Ethics Review Committee, and all participants provided written informed consent prior to their involvement. The secondary analysis of this data did not necessitate further approval from an Institutional Review Board (https://wwwn.cdc.gov/nchs/nhanes/default. aspx).
Consent
All participants provided written informed consent prior to participation, and the study was approved by the NCHS Research Ethics Review Board (https://wwwn.cdc.gov/nchs/nhanes/default. aspx). The authors have no ethical, legal, and financial conflicts related to the article. All authors read and approved the manuscript for publication.
Sources of funding
Not applicable.
Author contributions
W.J. and H.J.: Writing – review & editing, conceptualization, supervision, and project administration. W.J. and H.W.: Writing – review & editing, conceptualization, and methodology. W.J. and F.Y.: Writing – original draft and Formal analysis. W.J. and W.L.: Writing – original draft and data curation. W.J. and J.S.: Writing – review & editing and software.
Conflicts of interest disclosure
The authors declare no competing interests.
Research registration unique identifying number (UIN)
N/A.
Guarantor
Huiqun Jia.
Provenance and peer review
This manuscript has not been published or presented elsewhere in part or in entirety and is not under consideration by another journal.
Data availability statement
The National Health and Nutrition Examination Survey data are publicly available at https://wwwn.cdc.gov/nchs/nhanes/, which is publicly available. The data underlying this article will be shared on reasonable request with the corresponding author.
Acknowledgments
This work was supported by the Medical Science Research Project of Hebei (20241643).
Declarations
The authors have no ethical, legal, and financial conflicts related to the article. All authors read and approved the manuscript for publication.
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Associated Data
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Data Availability Statement
The National Health and Nutrition Examination Survey data are publicly available at https://wwwn.cdc.gov/nchs/nhanes/, which is publicly available. The data underlying this article will be shared on reasonable request with the corresponding author.