Abstract
Chronic pain and obesity are prevalent conditions that substantially impair the quality of life and impose considerable socioeconomic burdens. We sought to investigate the relationship between the waist-to-height ratio (WHtR) and chronic pain in American adults. This cross-sectional analysis included adults who participated in the 1999 to 2004 National Health and Nutrition Examination Survey. Chronic pain referred to self-reported pain persisting for at least 3 months within the past year. The WHtR was derived by dividing the waist circumference in centimeters by the height in centimeters. Multivariable logistic regression and restricted cubic spline models were used to elucidate the relationship. Subgroup analyses were further used to assess the influence of potential confounding factors. A total of 11,591 adults were included, of whom 1690 (15.9%) had chronic pain. After full adjustment for potential confounders, a higher WHtR was significantly associated with an increased odd of chronic pain (OR = 3.16, 95% CI: 1.50–6.65, P = .004). Participants in the highest WHtR quintile (Q5) were more likely to experience chronic pain than those in the lowest quintile (Q1) (adjusted OR = 1.74, 95% CI: 1.47–2.08, P = .011). Restricted cubic spline analysis revealed a nonlinear association with an inflection point at approximately 0.53. No significant interactions were observed across the subgroups (all P for interaction > 0.05). WHtR, as a simple and reliable anthropometric measure of central obesity, was positively associated with the risk of chronic pain among U.S. adults. These findings highlight the importance of controlling central obesity in chronic pain prevention and public health interventions.
Keywords: central obesity, chronic pain, cross-sectional study, NHANES, waist-to-height ratio
1. Introduction
Chronic pain is typically defined as pain that remains after the usual healing period of an acute illness or injury, often persisting for more than 3 months. It represents a widespread and multifactorial di, profoundly affecting more than 20% of the world’s population and exerting an enormous economic burden worldwide.[1] It was estimated that approximately 51.6 million adults (20.9%) in the United States (U.S.) had chronic pain, with 17.1 million (6.9%) suffering from high-impact chronic pain in the year 2021.[2] Similarly, an epidemiological study estimated that the incidence of pain in China was over 30%.[3] Chronic pain is frequently linked to psychiatric and neurological comorbidities, including anxiety, depression, and dementia in adults,[4,5] and neuroinflammation is considered one of the crucial common pathophysiological mechanisms.[6] Multiple physical, psychological, and social determinants contribute to the onset and progression of chronic pain.[7] A better and comprehensive understanding of these factors is essential for the prediction and prevention of chronic pain.
Obesity is a preventable, multifactorial, chronic disease that significantly reduces life expectancy and quality of life.[8] Increasing evidence suggests the existence of an intricate and complex association between chronic pain and obesity. First, obese individuals tend to experience higher pain severity and intensity. A 2024 systematic review and meta-analysis showed that pain severity was significantly greater among obese individuals than that among those with normal weight.[9] Our previous cross-sectional study also demonstrated that a higher body roundness index was significantly and associated with an increased risk of chronic pain among U.S. adults.[10] Second, obesity increases the prevalence and severity of localized pain, particularly in the weight-bearing joints. A population-based study involving aging suggested that a high body mass index (BMI) correlates with a significantly elevated risk of knee, hip, and back pain.[11] Third, a potential mechanism is that obesity may contribute to pain through mechanical overload on joints and surrounding tissues, thereby intensifying nociceptive processes. Furthermore, obesity was considered to lead to a chronic, low-grade tissue inflammatory state that can sensitize pain receptors such as nociceptors, making individuals more sensitive to pain.[12] Nevertheless, the specific mechanisms underlying how obesity affects the incidence and severity of chronic pain are not completely explored and warrant further investigation, especially regarding different obesity phenotypes.
Central obesity, also known as abdominal obesity, is characterized by excessive visceral fat accumulation in the abdominal region and is often accompanied by metabolic disturbances, such as reduced adiponectin levels and systemic inflammation. Clinical evidence has also shown that central obesity is increasingly recognized as a major contributor to metabolic complications.[13] A retrospective study of patients with osteoarthritis demonstrated that individuals with osteoarthritis and central obesity experienced the onset of pain symptoms approximately 2 years earlier and had a greater number of affected joints than those without central obesity.[14] Similarly, a cross-sectional study of 310 postmenopausal women reported that the waist-to-height ratio (WHtR) assessment of central obesity was closely related to pain in the lower extremities and back.[15] Furthermore, a recent 2025 cross-sectional investigation identified a dose-dependent link between WHtR and severe headache/migraine in adults aged 20 to 60, highlighting WHtR’s superior predictive accuracy over 9 lipid-related metrics and visceral fat’s role in neuroinflammatory pain pathways.[16] Despite these findings, population-based evidence exploring the relationship between WHtR-defined central obesity and chronic pain among U.S. adults remains relatively limited. Therefore, our study was designed to evaluate the association between WHtR and the incidence of chronic pain among the American adult population using data from the National Health and Nutrition Examination Survey (NHANES), providing novel epidemiological insights to inform obesity-related pain prevention and management strategies.
2. Methods
2.1. Study population
This present study was carried out according to the STROBE reporting guidelines. Data were derived from the 1999 to 2004 NHANES cycles. In brief, the NHANES is an ongoing, nationally representative, cross-sectional study conducted by the National Center for Health Statistics (NCHS) that aims to comprehensively evaluate the health and nutritional status of a representative sample of the U.S. civilian, noninstitutionalized population.[17] Data collection for NHANES was approved and allowed by the NCHS Ethics Review Committee, and all study participants had given written informed consent before data collection and analysis. Because our study used a secondary analysis of anonymized public data, it was unnecessary to get additional ethical approval from the Institutional Review Board. Detailed information about NHANES is available at https://wwwn.cdc.gov/Nchs/Nhanes/. In our analysis, we included the American adults aged 20 years or older who had completed the household interview and medical examination. We excluded participants with missing chronic pain status, anthropometric measurements, or covariate information.
2.2. Chronic pain
Chronic pain, as defined by the International Classification of Diseases, 11th Revision (ICD-11), is a self-reported pain that persists or recurs for more than 3 months.[18] Pain conditions were assessed using the McGill Pain Questionnaire (MPQ), which has been extensively validated as a reliable measure of pain severity in clinical and epidemiological studies.[19] Chronic pain status in this study was defined using 2 items from the MPQ. Item MPQ100 assessed whether respondents had experienced pain lasting more than 24 hours during the previous month, whereas item MPQ110 evaluated the overall duration of pain. Participants who reported pain persisting for 3 months or longer (MPQ100 = 1 and MPQ110 = 3 or 4) were classified as having chronic pain. In contrast, those reporting no pain in the past month (MPQ100 = 2) or pain lasting less than 3 months (MPQ100 = 1 and MPQ110 = 1 or 2) were identified as non-chronic pain controls.
2.3. Assessment of the WHtR
The WHtR, computed by dividing participants’ waist circumference (in centimeters) by their height (in centimeters) measured in a standing position, is an anthropometric indicator used to assess body fat distribution in adults. Information on participants’ height and waist circumference was obtained from their physical examination records. All anthropometric assessments were obtained by certified health technicians using standardized protocols at the Mobile Examination Centers to ensure all data accuracy. The trained research assistants documented these values. Before the measurement procedure, participants were asked to remove their shoes and outer garments. Participants’ height was measured to the nearest 0.1 cm as the vertical distance from the floor to the highest point of the head using a stadiometer. Participants’ waist circumference was obtained at the midpoint between the lower margin of the last rib and the iliac crest using a flexible, nonelastic measuring tape.
2.4. Covariates
According to the prior literature,[20] we considered a broad range of covariates in our analyses, including such as demographic characteristics (sex, age, race/ethnicity, marital status, and education level), socioeconomic status (poverty income ratio [PIR]), lifestyle factors (physical activity and smoking status), and clinical conditions (hypertension, diabetes mellitus, cardiovascular disease, and stroke). According to the categories provided by the NCHS, participants were grouped by race/ethnicity as non-Hispanic White, non-Hispanic Black, Mexican American, or other racial/ethnic backgrounds. Marital status was categorized into 3 groups: married, cohabiting with a partner, and single/living alone. We categorized educational attainment into 3 levels: fewer than 9 years, 9 to 12 years, and more than 12 years. Household socioeconomic status was evaluated using the PIR, which was stratified into low (≤1.3), middle (>1.3–3.5), and high (>3.5) income levels. Physical activity was categorized into 3 levels: sedentary, moderate, and vigorous activity. Moderate activity referred to participation in exercise for at least 10 minutes during the past 30 days that caused light sweating or a mild-to-moderate increase in breathing or heart rate. Vigorous activity was defined as engaging in ≥10 minutes of exercise that resulted in heavy sweating or a marked elevation in respiration or heart rate. Smoking status was determined based on lifetime cigarette consumption and categorized as never (<100 cigarettes in total), former, or current smoker. Information on chronic conditions, including physician-diagnosed hypertension, diabetes, stroke, and coronary heart disease, was collected through self-reported medical history questionnaire.
2.5. Statistical analyses
All statistical analyses were performed in accordance with the NHANES analytic protocol, applying appropriate fasting subsample weights to account for the survey’s complex, multistage probability sampling design.[21] Nationally representative estimates were derived using the primary sampling unit (SDMVPSU) and stratum (SDMVSTRA) variables. For participants from the 1999 to 2002 survey cycles, 4-year MEC weights (WTMEC4YR) were applied, whereas 2-year MEC weights (WTMEC2YR) were used for the 2003 to 2004 cycle. To generate a single weight covering the 1999 to 2004 dataset, a composite weight was calculated as (2/3 × WTMEC4YR) + (1/3 × WTMEC2YR).
Descriptive statistics were expressed as unweighted counts with weighted percentages for categorical variables and as weighted means with standard errors for continuous variables. Group comparisons were performed using one-way ANOVA and chi-square tests as appropriate. Adjusted odds ratios and 95% confidence intervals for the association between WHtR and chronic pain were estimated using multivariable logistic regression analyses. Model 1: unadjusted; Model 2: adjusted for demographic and socioeconomic factors (age, sex, race/ethnicity, poverty–income ratio, marital status, and education level); Model 3: further adjusted for health and lifestyle covariates, including hypertension, diabetes mellitus, cardiovascular disease, stroke, smoking status, and physical activity. WHtR was evaluated both as a continuous variable and by quintiles, using the lowest quintile (Q1) as the reference group. A test for linear trends across WHtR quintiles was performed, and restricted cubic spline models were employed to assess potential nonlinear associations between WHtR and chronic pain.
Subgroup and interaction analyses were conducted to evaluate the consistency of the association across different population strata, including sex, age (20–50 years and >50 years), hypertension, diabetes, coronary heart disease, and stroke status. Logistic regression models combined with likelihood ratio tests were applied to explore potential effect modifications and heterogeneity among these subgroups.
All statistical procedures in this study were conducted using R software (version 4.2.2; R Foundation for Statistical Computing, Vienna, Austria) and the Free Statistics analysis platform (version 2.0; Beijing, China). A 2-sided P-value of <.05 was considered to be statistically significant.
3. Results
3.1. Baseline characteristics
After applying the inclusion and exclusion criteria, a total of 11,591 adult participants from the NHANES 1999 to 2004 cycles were included in our analysis finally. An overview of participant enrollment and the corresponding exclusion procedures is shown in Figure 1. The baseline characteristics of the study population, stratified by WHtR quintiles, are summarized in Table 1.
Figure 1.
Flowchart summarizing the selection process of the present study.
Table 1.
Baseline characteristics of included individuals according to the WHtR.
| Variables | Total | Q1 (≤0.50) | Q2 (0.51–0.55) | Q3 (0.56–0.60) | Q4 (0.61–0.65) | Q5 (>0.65) | P-value |
|---|---|---|---|---|---|---|---|
| Number of participants | 11,591 | 2318 | 2318 | 2318 | 2318 | 2319 | – |
| Gender, n (%) | |||||||
| Male | 5509 (47.94) | 1149 (44.89) | 1203 (52.76) | 1267 (56.19) | 1099 (48.68) | 791 (36.26) | <.001 |
| Female | 6082 (52.06) | 1169 (55.11) | 1115 (47.24) | 1051 (43.81) | 1219 (51.32) | 1528 (63.74) | |
| Age (year) | 48.97 (16.50) | 39.75 (14.20) | 47.12 (15.93) | 51.37 (16.10) | 54.19 (16.61) | 52.40 (16.45) | <.001 |
| Race/ethnicity, n (%) | |||||||
| Non-Hispanic White | 5950 (72.65) | 1312 (75.10) | 1213 (72.39) | 1176 (72.18) | 1189 (73.62) | 1060 (68.94) | <.001 |
| Non-Hispanic black | 2194 (10.47) | 526 (11.04) | 417 (9.63) | 374 (8.82) | 371 (9.40) | 506 (13.66) | |
| Mexican American | 2546 (7.03) | 292 (4.53) | 485 (7.12) | 577 (8.39) | 596 (8.15) | 596 (7.89) | |
| Others | 901 (9.85) | 188 (9.34) | 203 (10.85) | 191 (10.62) | 162 (8.83) | 157 (9.51) | |
| Education level (year), n (%) | |||||||
| < 9 | 1657 (6.31) | 155 (3.39) | 277 (5.22) | 366 (6.78) | 439 (9.28) | 421 (8.32) | <.001 |
| 9–12 | 4652 (38.91) | 844 (33.08) | 906 (37.09) | 940 (40.36) | 944 (41.97) | 1018 (44.87) | |
| >12 | 5282 (54.79) | 1319 (63.52) | 1135 (57.70) | 1012 (52.86) | 936 (48.75) | 880 (46.81) | |
| Marital status, n (%) | |||||||
| Married or living with a partner | 7288 (65.07) | 1261 (57.59) | 1522 (68.39) | 1566 (69.41) | 1563 (69.70) | 1376 (62.11) | <.001 |
| Living alone | 4303 (34.93) | 1057 (42.41) | 796 (31.61) | 752 (30.59) | 755 (30.30) | 943 (37.89) | |
| Family income, n (%) | |||||||
| Low | 3273 (21.27) | 594 (20.29) | 588 (19.26) | 600 (17.82) | 691 (22.19) | 800 (28.17) | <.001 |
| Medium | 4476 (35.90) | 824 (32.64) | 875 (34.32) | 936 (38.21) | 920 (37.90) | 921 (37.95) | |
| High | 3842 (42.83) | 900 (47.07) | 855 (46.42) | 782 (43.97) | 707 (39.91) | 598 (33.88) | |
| Hypertension, n (%) | 2980 (22.06) | 226 (7.72) | 411 (14.93) | 606 (21.98) | 780 (32.62) | 957 (41.10) | <.001 |
| Diabetes, n (%) | 1099 (6.55) | 42 (1.32) | 129 (3.40) | 191 (5.30) | 297 (9.87) | 440 (16.13) | <.001 |
| Coronary heart disease, n (%) | 507 (3.54) | 39 (1.03) | 77 (2.63) | 131 (4.78) | 128 (5.23) | 132 (5.17) | <.001 |
| Stroke, n (%) | 346 (2.19) | 28 (0.85) | 49 (1.51) | 78 (2.54) | 94 (3.22) | 97 (3.53) | <.001 |
| Physical activity, n (%) | |||||||
| Sedentary | 4973 (35.55) | 726 (25.83) | 876 (31.31) | 1000 (36.10) | 1126 (41.98) | 1245 (47.75) | <.001 |
| Moderate | 3340 (29.86) | 582 (25.87) | 645 (27.93) | 715 (32.07) | 710 (33.41) | 688 (31.93) | |
| Vigorous | 3278 (34.60) | 1010 (48.30) | 797 (40.76) | 603 (31.83) | 482 (24.60) | 386 (20.23) | |
| Smoking status, n (%) | |||||||
| Never | 5952 (49.93) | 1203 (51.82) | 1193 (49.86) | 1182 (49.53) | 1143 (47.41) | 1231 (50.34) | <.001 |
| Former | 3086 (25.12) | 406 (17.66) | 559 (23.81) | 683 (27.35) | 753 (31.56) | 685 (28.46) | |
| Current | 2553 (24.95) | 709 (30.52) | 566 (26.33) | 453 (23.12) | 422 (21.03) | 403 (21.19) | |
| Chronic pain, n (%) | 1690 (15.92) | 286 (12.83) | 285 (14.24) | 323 (15.52) | 373 (18.38) | 423 (20.44) | <.001 |
Data are presented as unweighted numbers (weighted percentage) for categorical variables and mean (standard error) for continuous variables.
%, weighted proportion; Q1–Q5, Quintile according to the waist-to-height ratio.
WHtR = waist-to-height ratio.
A total of 1690 participants (15.92%) reported chronic pain. The mean age of the total sample was 48.97 ± 16.50 years, and women accounted for 52.06% of the sample (n = 6082). Individuals in the upper WHtR quintiles were more frequently female, non-Hispanic White, and had higher educational attainment. Compared with those in the lower quintiles, participants in the higher categories were more likely to be in a marital or cohabiting relationship and had increased occurrences of hypertension, diabetes mellitus, and cardiovascular disease.
3.2. Association between WHtR and chronic pain
In the multivariable logistic regression model adjusted for demographic (age, sex, race/ethnicity), socioeconomic (PRI, marital status, education), comorbidity (hypertension, diabetes, cardiovascular disease, stroke), and lifestyle factors (smoking status, physical activity), WHtR showed a significant positive association with chronic pain (OR = 3.16, 95% CI: 1.50–6.55; P = .004).
A clear dose–response trend was observed when WHtR was analyzed in quintiles. Compared with participants in the lowest quintile (Q1, WHtR ≤0.50), those in the highest quintile (Q5, WHtR >0.65) had an adjusted OR of 1.74 (95% CI: 1.47–2.08; P = .011) for chronic pain (Table 2).
Table 2.
The association between WHtR and chronic pain.
| Variable | Model 1 | Model 2 | Model 3 | |||
|---|---|---|---|---|---|---|
| OR (95% CI) | P-value | OR (95% CI) | P-value | OR (95% CI) | P-value | |
| Continuous | ||||||
| WHtR | 10.26 (5.51–19.11) | <.001 | 6.04 (3.14–11.59) | <.001 | 3.16 (1.50–6.65) | .004 |
| Categorized | ||||||
| Q1(≤0.50) | Reference | – | Reference | – | Reference | – |
| Q2(0.51–0.55) | 1.13 (0.90–1.41) | .284 | 1.09 (0.87–1.36) | .446 | 1.07 (0.86–1.34) | .516 |
| Q3(0.56–0.60) | 1.25 (1.00–1.56) | .051 | 1.18 (0.96–1.45) | .109 | 1.13 (0.93–1.38) | .214 |
| Q4(0.61–0.65) | 1.53 (1.23–1.90) | <.001 | 1.36 (1.07–1.73) | .015 | 1.23 (0.95–1.59) | .112 |
| Q5(>0.65) | 1.74 (1.47–2.08) | <.001 | 1.52 (1.28–1.80) | <.001 | 1.28 (1.07–1.54) | .011 |
| P for trend | – | <.001 | – | <.001 | – | .015 |
Q1-Q5: Quintile according to the waist-to-height ratio; Crude model: Unadjusted; Model 1 is the crude model without adjustment for covariates. Model 2 was adjusted for age, sex, race/ethnicity, poverty income ratio, marital status, and education level. Model 3 was adjusted as for model 2 and, additionally adjusted for hypertension, diabetes mellitus, cardiovascular disease history, stroke, smoking status, and physical activity.
CI = confidence interval, OR = odds ratio, WHtR = waist-to-height ratio.
As shown in Figure 2, the RCS model identified a significant nonlinear correlation between WHtR and the likelihood of chronic pain (P for nonlinearity <.001). The inflection point was identified at a WHtR of 0.53. In the piecewise regression model, participants with WHtR ≥0.53 had a higher likelihood of experiencing chronic pain (adjusted OR = 3.43, 95% CI: 1.12–10.49; P = .03), whereas no significant relationship was found among those with WHtR <0.53 (Table 3).
Figure 2.
Restricted cubic spline model depicting the nonlinear association between the WHtR and the prevalence of chronic pain among adults in the United States. WHtR = waist-to-height ratio.
Table 3.
Association between WHtR and chronic pain using 2-piecewise regression models.
| Crude model | Adjusted model | |||
|---|---|---|---|---|
| WHtR | OR (95% CI) | P-value | OR (95% CI) | P-value |
| <0.53 | 1.70 (0.04–79.00) | .78 | 0.81 (0.02–36.81) | .91 |
| ≥0.53 | 12.52 (4.84–32.42) | .001 | 3.43 (1.12–10.49) | .03 |
WHtR = waist-to-height ratio.
3.3. Subgroup analyses
Subgroup analyses were implemented to explore whether the relationship persisted across different levels of potential effect modifiers. No significant interactions were detected in the analyses stratified by sex (male vs female), age group (20–50 vs >50 years), hypertension, diabetes, cardiovascular disease, or stroke status (all P for interaction >.05; Fig. 3).
Figure 3.
Forest plot presenting subgroup analyses of the relationship between the WHtR and chronic pain across demographic and clinical characteristics. WHtR = waist-to-height ratio.
These consistent findings across subgroups support the robustness and stability of the association between WHtR and chronic pain.
4. Discussion
In recent years, accumulating evidence has highlighted a potential link between central obesity and chronic pain. However, the underlying relationship remains poorly understood. To bridge this gap, we conducted a cross-sectional study using data from the NHANES data. Our findings revealed a significant nonlinear association between the WHtR and chronic pain among U.S. adults, independent of demographic, lifestyle, and comorbid factors. The consistency of this positive association across diverse subpopulations was further supported by the subgroup analyses. These results suggest that maintaining a lower WHtR may help reduce the risk of and development of chronic pain.
Previous studies have primarily examined the relationship between BMI and pain; however, this relationship remains controversial and is subject to debate. In young adults with patellofemoral pain, a higher BMI has been linked to reduced functional capacity and weaker knee flexion strength.[22] A longitudinal study also identified a bidirectional relationship between BMI and joint pain among middle-aged adults, suggesting a mutual influence over time.[23] However, several studies have argued against this. A retrospective single-center cohort study involving pediatric patients demonstrated that BMI was not associated with postoperative pain following general, orthopedic, or neurospinal surgeries.[24] Another clinical study also showed that there was no significant association between BMI and temporomandibular disorder-related pain.[25] Collectively, these findings suggest that while BMI is the most widely used formula to evaluate obesity and being overweight, it may not adequately capture the distribution of body fat or its role in pain development, emphasizing the need to assess other indicators such as WHtR.
WHtR is a practical and reliable measure of central obesity, offering distinct advantages over BMI by accurately reflecting the abdominal fat distribution. It is simple to obtain and has demonstrated superior predictive ability for metabolic syndrome and cardiometabolic risk in diverse populations. A large meta-analysis involving over 300,000 adults showed that WHtR outperformed BMI and waist circumference in identifying cardiometabolic abnormalities.[26] Similarly, a previous cross-sectional study identified that WHtR was more closely correlated with diabetes than BMI and waist-to-hip ratio, particularly among women aged ≥40 years.[27] In addition, central obesity, characterized by a high WHtR, may have detrimental effects on cognitive function in the elderly.[20] A recent cross-sectional study from the NHANES 2009 to 2010 revealed that various anthropometric measures, including WHtR, were significantly and positively associated with the risk of chronic low back pain development.[28] However, research investigating the relationship between WHtR and chronic pain remains limited.
The current analysis identified a positive link between WHtR and chronic pain among American adults, consistent with previous epidemiological investigations. For instance, research in Brazil demonstrated that central obesity was associated with chronic pain incidence, and an interventional trial revealed that excess abdominal fat adversely affected pain processing and autonomic regulation.[29] A crossover randomized controlled trial demonstrated that central obesity significantly affected pain processing and autonomic function, particularly by intensifying the impact of acute hyperglycemia on pain sensitivity and inhibition.[30] In addition, central obesity has been linked to a higher prevalence of multisite pain in older adults.[31] Central obesity measured using the WHtR was associated with the onset of joint pain in women with osteoarthritis and may also play a role in the prediction of cardiovascular disease.[14] These results collectively support the role of central adiposity in the pathophysiology of pain.
Interestingly, a J-shaped association was observed between WHtR and chronic pain, with an inflection point identified at 0.53. The prevalence of chronic pain remained low when the WHtR was ≤0.53 but increased sharply beyond this threshold. A previous study found that the WHtR may serve as a more effective global clinical screening tool than waist circumference for predicting cardiovascular disease and diabetes, with a recognized threshold value of 0.5.[32] Findings from a sample of 1709 older adults in the United States showed that the WHtR–cognitive function association among women exhibited an inverted U-shaped curve, reaching a peak at 0.68.[20] Together, this evidence reinforces the utility of WHtR as a simple and informative marker for assessing the risk of chronic pain.
Several plausible mechanisms could help elucidate how central obesity contributes to chronic pain development. There is literature supporting that systemic inflammation, mechanical overload, and autonomic dysfunction may contribute to increased risk of chronic pain caused by obesity.[33] First, an excessive systemic inflammatory response seems to play a vital role in the development of chronic pain. Adipose tissue dysfunction in central obesity contributes to a chronic low-grade inflammatory state with high amounts of pro-inflammatory cytokines and adipokines, promoting local and systemic pain sensitization.[34] Second, mechanical overload from excess body weight places additional strain on weight-bearing joints such as the knees and lower back, exacerbating musculoskeletal pain. Evidence from clinical trials indicates that lifestyle interventions combining diet and exercise can modestly alleviate knee pain in individuals with obesity.[35] Third, central obesity-related metabolic disturbances, including insulin resistance and dysregulated lipid metabolism, may contribute to altered nociceptive processing in patients with obesity. An observational cross-sectional study showed that insulin resistance was closely associated with central pain in patients with fibromyalgia.[36] Alterations in lipid metabolism also affect joint pain, inflammation, and cartilage degradation in patients with osteoarthritis.[36] In addition, central obesity was found to be significantly associated with mental disorder, overall multimorbidity, and combined physical-mental multimorbidity,[37] which can further exacerbate the experience of pain.[38,39]
The present study provides novel and valuable insights into the relationship between the WHtR and chronic pain. Its primary strengths lie in the use of a large, nationally representative sample of the U.S. adult population, the inclusion of extensive covariate adjustments, and the application of advanced statistical techniques to explore potential nonlinear associations through smoothed curve fitting and threshold effect analysis. Despite these advantages, several limitations must be acknowledged. First, the cross-sectional design precluded causal inference between WHtR and chronic pain. Second, the reliance on self-reported data may introduce recall or social desirability bias. Third, as our analysis was restricted to U.S. adults, the generalizability of these findings to younger individuals or populations from other countries remains uncertain. Future longitudinal and interventional studies are warranted to confirm these findings and to clarify the biological mechanisms linking central obesity, as measured by WHtR, to chronic pain.
5. Conclusions
Our study revealed a strong positive relationship between a higher WHtR and the prevalence of chronic pain among U.S. adults (Fig. 4). WHtR may serve as a simple, practical, and effective screening indicator for identifying high-risk groups for chronic pain. Future prospective and mechanistic studies are needed to confirm causality and further clarify the biological pathways linking central obesity and chronic pain.
Figure 4.
Graphical abstract summarizing the study design, analytical approach, and main findings of the association between WHtR and chronic pain. WHtR = waist-to-height ratio.
Acknowledgments
The authors would like to thank Editage for the English language editing. Figure 4 was created with created using FigDraw.
Author contributions
Conceptualization: Weiai Jia.
Data curation: Jingpu Shi.
Formal analysis: Jingpu Shi.
Funding acquisition: Weiai Jia.
Methodology: Kangsheng Zhu, Fangfang Yong.
Project administration: Kangsheng Zhu, Fangfang Yong.
Resources: Kangsheng Zhu, Fangfang Yong.
Software: Kangsheng Zhu, Fangfang Yong.
Supervision: Jingpu Shi.
Validation: Jingpu Shi, Weiai Jia.
Visualization: Jingpu Shi, Weiai Jia.
Writing – original draft: Jingpu Shi, Weiai Jia.
Writing – review & editing: Weiai Jia.
Abbreviations:
- BMI
- body mass index
- CI
- confidence intervals
- MEC
- mobile examination center
- MPQ
- McGill pain questionnaire
- NCHS
- National Center for Health Statistics
- NHANES
- National Health and Nutrition Examination Survey
- OR
- odds ratio
- PIR
- poverty income ratio
- Q
- quintile
- WHtR
- waist-to-height ratio
This work was supported by the Medical Science Research Project of Hebei Province (20241643), China.
The NHANES is conducted by the NCHS and is approved by the NCHS Research Ethics Review Committee. All participants provided written informed consent prior to the study’s commencement.
The authors have no conflicts of interest to disclose.
The datasets generated during and/or analyzed during the current study are publicly available.
How to cite this article: Shi J, Zhu K, Yong F, Jia W. Association between waist-to-height ratio and chronic pain among American adults: A cross-sectional study of the National Health and Nutrition Examination Survey. Medicine 2026;105:10(e47958).
Contributor Information
Jingpu Shi, Email: shijingpu1007@163.com.
Kangsheng Zhu, Email: jysyzhukangsheng@126.com.
Fangfang Yong, Email: 806442593@qq.com.
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