ABSTRACT
Background
The chronic low back pain (cLBP) literature rarely includes comprehensive characterization of demographic and biomedical factors in a large sample of individuals. The University of Pittsburgh Mechanistic Research Center, entitled, “Low Back Pain: Biological, Biomechanical, Behavioral Phenotypes (LB3P),” is part of the National Institutes of Health's Helping to End Addiction Long‐term Initiative. The LB3P conducted a prospective, observational cohort study to identify phenotypes of people with cLBP. Here, we report demographic and biomedical characteristics of a large cohort of individuals with cLBP, stratified by sex and age, collected at the in‐person enrollment visit.
Methods
The key eligibility criteria were adults with cLBP, English speakers, and identified in the electronic health record of our medical center. Recruitment strategies were through clinical partners who invited their patients to join the study and research registries. Participants completed demographic and biomedical surveys. Descriptive statistics were computed for the sample overall, and for the subgroups (male/female and age < 60/≥ 60).
Results
N = 1007 individuals (60% female) were enrolled, with an average age of 59 ± 17 years. Most participants were non‐Hispanic (90%), White (75%), and 53% attained college or higher education. 54% were married or had a partner, 43% were employed, 38% retired, 41% had an annual household income < $50 000, 20% had been off work for more than 30 days due to low back pain (LBP), 16% had applied for or received disability, and 6% were on worker's compensation. The majority were obese (average BMI of 31.5 kg/m2), 61% had back pain for > 5 years, and pain had been ongoing every or nearly every day in 76% of the sample. The participants reported a high prevalence of osteoarthritis (58%), anxiety (40%), depression (40%), vision impairment (35%), and balance problems/falls (31%). Among the chronic overlapping pain conditions, the most common were migraine or headache (29%), irritable bowel syndrome (16%), and temporomandibular joint dysfunction (12%). Previous low back surgery was reported by 25%. The most frequently reported LBP treatments during the previous month were exercise routine done on their own (58%), physical therapy, occupational therapy, or chiropractic care (33%), mindfulness, meditation, or relaxation (22%), and diet or nutrition counseling (21%). Medication intake during the last month was 43% for nonsteroidal anti‐inflammatory drugs, 18% for gabapentin, 13% for opioid, and 10% for antidepressants.
Conclusions
Describing comprehensive demographic and biomedical characteristics of individuals with cLBP stratified by sex and age will serve as a reference for clinicians and research planning, particularly with respect to comorbid conditions and utilization of treatment for cLBP. These data will be useful in future efforts to comprehensively phenotype cLBP.
Keywords: age, biomedical, characterization, chronic low back pain, demographics, sex
The University of Pittsburgh Mechanistic Research Center, entitled, “Low Back Pain: Biological, Biomechanical, Behavioral Phenotypes (LB3P),” is part of the National Institutes of Health's Helping to End Addiction Long‐term Initiative. The LB3P conducted a prospective, observational cohort study to identify phenotypes of people with cLBP. Here, we report demographic and biomedical characteristics of a large cohort of individuals with cLBP, stratified by sex and age, collected at the in‐person enrollment visit.
1. Introduction
Chronic low back pain (cLBP) is a leading cause of disability worldwide and places a heavy financial burden on societies [1]. Despite being highly prevalent and disabling, the pathology of cLBP is ill‐defined. Thus, fully understanding the contributors to cLBP is critical to improving its clinical management. Demographic and biomedical factors such as older age, female sex, obesity, smoking, co‐existing comorbidities, and lower socioeconomic status have all been associated with cLBP [2]. However, few clinical or population‐based studies have comprehensively characterized demographic and biomedical factors in cLBP. Amid the clinical studies, the majority have been of small size, narrow inclusiveness, and prone to underrepresenting the breadth of the cLBP population. The large clinical trials, although adequately sampled, have generally used justifiably stringent eligibility criteria to protect the safety of the individuals willing to undergo the experimental treatments, limiting the generalizability of the participants' characteristics [3, 4, 5]. The population‐based studies, while large and guarded from sampling bias, tend to characterize only selective demographic and biomedical factors, depending on the context of their investigation and available data [6, 7, 8, 9]. Thus, there is a compelling need for a comprehensive characterization of demographic and biomedical factors in representative individuals with cLBP to provide reference values to be used as the basis for phenotyping, research planning, or comparison in clinical practice.
Characterizing individuals with cLBP requires careful consideration of key biological factors such as sex and age. Although pain is ubiquitous to all individuals with cLBP, pain is not experienced by all individuals in the same way. Compared to males, females are more vulnerable to cLBP regardless of age [10, 11]. Older adults have a higher prevalence of cLBP compared to younger individuals, and associated factors such as retirement, knee osteoarthritis, and hypertension seem to be age‐related [2]. Additionally, the National Institute of Health (NIH) also requires that biological variables that affect a disease be factored into research design and that the research observations be reported stratified by these biological variables [12]. Providing information on cLBP based on sex and age will provide valuable data to the scientific community to help enhance the reproducibility of research in this population.
The University of Pittsburgh's Low Back Pain: Biological, Biomechanical, Behavioral Phenotypes (LB3P) Mechanistic Research Center is a member of the NIH Back Pain Consortium (BACPAC) Research Program—which is part of the Helping to End Addiction Long‐term (HEAL) Initiative. The LB3P is a study designed to collect an unbiased broad dataset on 1000 individuals with the purpose of facilitating understanding of multiple contributors to pain and phenotyping cLBP [13]. In this paper, we comprehensively describe the demographic and biomedical characteristics, stratified by sex and age, of individuals with cLBP enrolled in the LB3P study [13].
2. Materials and Methods
2.1. Design and Oversight
LB3P was a prospective longitudinal observational cohort study [13]. All participants signed an informed consent document approved by the University of Pittsburgh Institutional Review Board. Data collection took place at the University of Pittsburgh Physical Therapy—Clinical and Translational Research Center and remotely as applicable. The study was monitored by an independent observational study monitoring board and an advisory panel. This report follows the STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) reporting guidelines. The LB3P study protocol has been described elsewhere [13].
2.2. Participants
The broad eligibility criteria promoted inclusion of a representative sample of individuals with cLBP. Inclusion criteria were: (1) cLBP defined as back pain (in the space between the lower posterior margin of the rib cage and the horizontal gluteal fold) that persisted at least 3 months and resulted in pain on at least half the days in the past 6 months—according to the definition from the NIH Task Force for Research Standards for cLBP [14]; (2) 18 years of age or older; (3) able to speak and understand English; and (4) willing to comply with all study procedures and sign the informed consent document. Exclusion criteria were: (1) no identification in the University of Pittsburgh Medical Center (UPMC) Electronic Health Record System; (2) participation in a masked intervention study for low back pain (LBP); and (3) medical condition that would place the participant at increased risk or preclude them from complying with study procedures.
2.3. Recruitment Sources
The LB3P study enrolled 1007 individuals over 40 months. Individuals with cLBP in Southwestern Pennsylvania were recruited from several sources. The primary source of recruitment was the identification of individuals with cLBP by screening the schedules of collaborating clinical partners and sending letters from the provider's office inviting their patients to enroll in the study. Collaboration with a team of clinical partners in general practice, physical medicine and rehabilitation, orthopedic surgery, physical therapy, and geriatrics resulted in robust and successful enrollment. Secondary sources of recruitment were registries, mainly Pitt+Me. Pitt+Me from the University of Pittsburgh's Clinical and Translational Science Institute (CTSI) is a database of more than 250,000 participants that engages the public and increases participation in research studies [15]. Additionally, media announcements were posted in local newspapers, newsletters to community groups, and the UPMC internal marketing system. Last, the CTSI Community PARTners Core assisted with recruitment by connecting our team with community members and organizations through partnerships designed to promote diversity and encourage participation in research studies [16].
2.4. Measures
All demographic and biomedical information reported in this study was collected during the in‐person enrollment visit and entered into a customized web‐based electronic data capture system. Except for the biomedical measures and the medical history survey that were administered by a certified clinician, all the other surveys were completed independently by the participants.
The study used the NIH HEAL Initiative Common Data Elements for collecting demographic information [17]. Additionally, we collected information on health insurance and the number of people in the household. Biomedical information included height and weight without shoes measured using a calibrated medical grade scale. Waist circumference was measured halfway between the lowest rib and the top of the hipbone in line with the umbilicus. This measurement was a recommendation of our advisory panel that was added after approximately two‐thirds of the study cohort had been enrolled. Blood pressure was obtained with the participant sitting quietly with the dominant arm supported at the level of the heart. The medical history was assessed using a form adapted from the NIH Minimum Data Set Taskforce by the BACPAC consortium, which queried the duration and frequency of back pain along with other LBP‐related questions [17]. The study adopted the comorbidity form harmonized by the BACPAC consortium MRCs that asked about past and current medical conditions diagnosed by a health professional. The Treatment Categories Questionnaire developed by the BACPAC Clinical Management Committee was used to assess the different treatments that patients had received for their LBP over the past month.
2.5. Statistical Analysis
Standard descriptive statistics were computed for the sample overall, and for the subgroups defined by biological sex and age (< 60, ≥ 60). Means and standard deviations (SDs) were used to describe continuous measures, whereas frequencies and percentages described categorical or ordinal variables. All analyses were performed using SAS version 9.4 (SAS Institute Inc. NC, USA). Due to the descriptive nature of these analyses and lack of hypothesis testing, we have elected to point out factors that were at least 5% different across sex and age subgroups as differences smaller than this are generally not considered clinically relevant.
3. Results
Enrollment took place from November 2020 to March 2024. In total, 1543 individuals were screened for the study and 1007 were eligible and enrolled (Figure 1). The most common reasons for exclusion were having LBP less frequently than half the days in the past 6 months (48%) and not being interested in the study (30%). Many participants (44%) were recruited from the clinical partners (Figure 2). From the enrolled participants, 17% were from orthopedic spine surgeons, 12% from primary care providers (PCPs), 12% from physical medicine and rehabilitation (PM&R) providers, and 3% from physical therapists (PTs). Research registries, referrals from other ongoing research studies in LBP, public announcement, and other (e.g., community outreach, word of mouth) contributed to 18%, 14%, 12%, and 12% of enrolled participants, respectively.
FIGURE 1.
Participant flow chart.
FIGURE 2.
The lighter blue tones represent the clinical partners: Orthopedic spine surgeons, primary care providers (PCPs), physical medicine and rehabilitation (PM&R) providers, and physical therapists (PTs).
3.1. All Participants
The average age was 59 years, and the sample was primarily female (60%), White (75%), and non‐Hispanic (90%). African Americans represented 18% of the sample. For education, 48% had less than a college degree, 27% completed college, and 26% had some postgraduate studies. Fifty‐four percent were married or had a partner, 43% were employed, 38% retired, 41% had an annual household income < $50 000, 26% from $50 000 to < $100 000, and 20% had income ≥ $100 000. Twenty percent of the sample had been off work for more than 30 days due to LBP, 16% had applied for or received disability compensation, and 6% were on worker's compensation (Table 1). Average BMI was 31.5 kg/m2 and 44% were current or past smokers. Low back was the body part with the most severe pain in 81% of participants, 61% had back pain for > 5 years, and 76% reported that pain was ongoing every or nearly every day. Previous low back surgery was reported by 25%, of which almost half (12%) had lumbar fusion. The sample reported a high prevalence of osteoarthritis (58%), joint replacement (44%), anxiety (40%), depression (40%), vision impairment (35%), and balance problems/falls (31%). Among the chronic overlapping pain conditions (COPCs), the most common were migraine or headache (29%), irritable bowel syndrome (16%), and temporomandibular joint dysfunction (12%) (Table 2). The most commonly reported non‐pharmacological LBP treatments during the last month were exercise routine done on their own (58%); PT, occupational therapy, or chiropractic care (33%); mindfulness, meditation, or relaxation (22%); and diet or nutrition counseling (21%) (Figure 3). For medications taken during the last month, nonsteroidal anti‐inflammatory drugs (NSAIDs) (43%) were the most frequent, followed by gabapentin (18%), opioid (13%) and selective serotonin reuptake inhibitor (SSRI) or serotonin‐norepinephrine reuptake inhibitor (SNRI) antidepressants (10%). Three percent of individuals reported having had a back surgery during the last month, from which 0.6% were lumbar fusion. Thirteen percent of the participants reported not receiving any treatment for back pain during the last month (Table 3).
TABLE 1.
Demographic characteristics of participants.
| All | Male | Female | Age < 60 | Age ≥ 60 | |
|---|---|---|---|---|---|
| N = 1007 | N = 406 | N = 600 | N = 427 | N = 580 | |
| Age, mean ± SD, years | 58.9 ± 16.5 | 66.2 ± 15.6 | 56.7 ± 16.7 | 43.0 ± 11.5 | 70.6 ± 6.9 |
| Sex at birth, a N (%) | |||||
| Male | 406 (40) | 406 (100) | 0 (0) | 135 (32) | 271 (47) |
| Female | 600 (60) | 0 (0) | 600 (100) | 291 (68) | 309 (53) |
| Gender identity, N (%) | |||||
| Men | 408 (41) | 405 (100) | 3 (1) | 137 (32) | 271 (47) |
| Women | 594 (59) | 0 (0) | 593 (100) | 285 (67) | 309 (53) |
| Genderqueer/Nonconforming | 5 (0) | 1 (0) | 4 (1) | 5 (1) | 0 (0) |
| Race, N (%) | |||||
| White | 759 (75) | 320 (79) | 439 (73) | 290 (68) | 469 (81) |
| African American | 181 (18) | 58 (14) | 123 (21) | 88 (21) | 93 (16) |
| Asian | 19 (2) | 7 (2) | 12 (2) | 15 (4) | 4 (1) |
| Other b | 4 (0.4) | 2 (0.2) | 2 (0.2) | 3 (0.3) | 1 (0.1) |
| More than one race | 26 (3) | 9 (2) | 16 (3) | 18 (4) | 8 (1) |
| Missing | 18 (2) | 10 (2) | 8 (1) | 13 (3) | 5 (1) |
| Ethnicity, N (%) | |||||
| Hispanic or Latino | 26 (3) | 11 (3) | 15 (3) | 19 (4) | 7 (1) |
| Not Hispanic or Latino | 903 (90) | 350 (86) | 552 (92) | 379 (89) | 524 (90) |
| Missing | 78 (8) | 45 (11) | 33 (6) | 29 (7) | 49 (8) |
| Education, N (%) | |||||
| Less than secondary school | 62 (6) | 22 (5) | 39 (7) | 31 (7) | 31 (6) |
| Secondary school degree | 247 (25) | 92 (23) | 155 (26) | 109 (26) | 138 (24) |
| Associate's or technical degree | 168 (17) | 64 (16) | 104 (17) | 74 (17) | 94 (16) |
| College or baccalaureate degree | 270 (27) | 110 (27) | 160 (27) | 119 (28) | 151 (26) |
| Postgraduate | 259 (26) | 118 (29) | 141 (24) | 93 (22) | 166 (29) |
| Missing | 1 (0) | 0 (0) | 1 (0) | 0 (0) | 0 (0) |
| Relationship status, N (%) | |||||
| Married/have partner | 541 (54) | 267 (66) | 273 (46) | 194 (45) | 347 (60) |
| Divorced/have no partner | 465 (46) | 139 (34) | 326 (54) | 232 (54) | 233 (40) |
| Missing | 1 (0) | 0 (0) | 1 (0) | 1 (0) | 0 (0) |
| Employment status, N (%) | |||||
| Full‐time employment | 280 (28) | 100 (25) | 180 (30) | 200 (47) | 80 (14) |
| Part‐time employment | 152 (15) | 61 (15) | 91 (15) | 69 (16) | 83 (14) |
| Student | 15 (1) | 2 (0) | 13 (2) | 14 (3) | 1 (0) |
| Retired | 378 (38) | 182 (45) | 196 (33) | 18 (4) | 360 (62) |
| Choose not to work | 10 (1) | 6 (1) | 4 (1) | 7 (2) | 3 (1) |
| Not employed | 172 (17) | 55 (14) | 116 (19) | 119 (28) | 53 (9) |
| Health insurance, N (%) | |||||
| Private/Employer based | 285 (28) | 98 (24) | 187 (31) | 179 (42) | 106 (18) |
| Medicare | 279 (28) | 137 (34) | 142 (24) | 40 (9) | 239 (41) |
| Medicaid | 73 (7) | 26 (6) | 47 (8) | 57 (13) | 16 (3) |
| Tricare | 14 (1) | 10 (2) | 4 (1) | 8 (2) | 6 (1) |
| Self‐paid | 23 (2) | 7 (2) | 16 (3) | 15 (4) | 8 (1) |
| Other | 42 (4) | 21 (5) | 21 (4) | 24 (6) | 18 (3) |
| Multiple | 201 (20) | 79 (19) | 121 (20) | 46 (11) | 155 (27) |
| Missing | 90 (9) | 28 (7) | 62 (10) | 58 (14) | 32 (6) |
| Number of people in household, mean ± SD | 2.1 ± 1.1 | 2.1 ± 1.0 | 2.1 ± 1.2 | 2.5 ± 1.3 | 1.8 ± 0.8 |
| Annual household income, N (%) | |||||
| Less than $10 000 | 71 (7) | 23 (6) | 47 (8) | 51 (12) | 20 (3) |
| $10 000–$24 999 | 139 (14) | 55 (14) | 84 (14) | 66 (15) | 73 (13) |
| $25 000–$34 999 | 88 (9) | 24 (6) | 64 (11) | 35 (8) | 53 (9) |
| $35 000–$49 999 | 110 (11) | 41 (10) | 69 (12) | 44 (10) | 66 (11) |
| $50 000–$74 999 | 138 (14) | 46 (11) | 92 (15) | 52 (12) | 86 (15) |
| $75 000–$99 999 | 117 (12) | 58 (14) | 59 (10) | 46 (11) | 71 (12) |
| $100 000–$149 999 | 115 (11) | 57 (14) | 58 (10) | 40 (9) | 75 (13) |
| $150 000–$199 999 | 53 (5) | 24 (6) | 29 (5) | 30 (7) | 23 (4) |
| $200 000 or more | 36 (4) | 18 (4) | 18 (3) | 21 (5) | 15 (3) |
| Prefer not to answer | 140 (14) | 60 (15) | 80 (13) | 42 (10) | 98 (17) |
| Off work > 30 days due to LBP, N (%) | |||||
| Yes | 205 (20) | 90 (22) | 115 (19) | 111 (26) | 94 (16) |
| No | 623 (62) | 249 (61) | 374 (62) | 277 (65) | 346 (60) |
| Missing | 179 (18) | 68 (17) | 111 (19) | 39 (9) | 140 (24) |
| On worker's compensation due to LBP, N (%) | |||||
| Yes | 60 (6) | 33 (8) | 26 (4) | 24 (6) | 36 (6) |
| No | 794 (79) | 312 (77) | 482 (80) | 358 (84) | 436 (75) |
| Missing | 153 (15) | 61 (15) | 92 (15) | 45 (11) | 108 (19) |
| Lawsuit or legal claim for LBP, N (%) | |||||
| Yes | 17 (2) | 6 (1) | 11 (2) | 8 (2) | 9 (2) |
| No | 974 (97) | 396 (98) | 577 (96) | 413 (97) | 561 (97) |
| Missing | 16 (2) | 4 (1) | 12 (2) | 6 (1) | 10 (2) |
| Applied for or received disability insurance for LBP, N (%) | |||||
| Yes | 161 (16) | 66 (16) | 95 (16) | 79 (19) | 82 (14) |
| No | 846 (84) | 340 (84) | 505 (84) | 348 (81) | 498 (86) |
One participant reported sex at birth as intersex and was therefore not included in the descriptive statistics for male/female. Intersex was not reported separately due to identification potential.
Other: American Indian or Alaskan Native and Hawaiian or Pacific Islander races were combined due to small cell numbers and identification potential.
TABLE 2.
Biometrics and medical history characteristics of participants.
| All | Male a | Female a | Age < 60 | Age ≥ 60 | |
|---|---|---|---|---|---|
| N = 1007 | N = 406 | N = 600 | N = 427 | N = 580 | |
| Height (m), mean ± SD b | 1.68 ± 0.1 | 1.76 ± 0.1 | 1.63 ± 0.1 | 1.69 ± 0.1 | 1.68 ± 0.1 |
| Weight (kg), mean ± SD b | 89.1 ± 23.6 | 95.9 ± 22.0 | 84.5 ± 23.6 | 92.4 ± 26.6 | 86.7 ± 20.8 |
| BMI (kg/m2), mean ± SD b | 31.5 ± 7.6 | 31.0 ± 6.5 | 31.8 ± 8.2 | 32.5 ± 8.9 | 30.8 ± 6.4 |
| Waist circumference (cm), mean ± SD c | 107.0 ± 17.3 | 111.4 ± 16.1 | 103.3 ± 17.5 | 105.3 ± 18.4 | 108.0 ± 16.6 |
| Blood pressure d | |||||
| Systolic (mmHg), mean ± SD | 126 ± 18 | 128 ± 18 | 124 ± 18 | 120 ± 17 | 130 ± 18 |
| Diastolic (mmHg), mean ± SD | 74 ± 11 | 75 ± 10 | 74 ± 11 | 76 ± 11 | 73 ± 10 |
| How long is back pain ongoing, mean ± SD | |||||
| 3–6 months | 22 (2) | 8 (2) | 14 (2) | 9 (2) | 13 (2) |
| 6 months–1 year | 69 (7) | 29 (7) | 40 (7) | 31 (7) | 38 (7) |
| 1–5 years | 305 (30) | 115 (28) | 190 (32) | 140 (33) | 165 (28) |
| > 5 years | 611 (61) | 254 (63) | 356 (59) | 247 (58) | 364 (63) |
| How often has LBP been ongoing over past 6 months, N (%) | |||||
| At least half of the days | 244 (24) | 82 (20) | 162 (27) | 121 (28) | 123 (21) |
| Every day or nearly every day | 763 (76) | 324 (80) | 438 (73) | 306 (72) | 457 (79) |
| Low back is the body's most severe pain, N (%) | |||||
| Yes | 818 (81) | 325 (80) | 492 (82) | 353 (83) | 465 (80) |
| No | 82 (8) | 45 (11) | 37 (6) | 32 (7) | 50 (9) |
| Not sure | 107 (11) | 36 (9) | 71 (12) | 42 (10) | 65 (11) |
| Previous low back surgery, N (%) | |||||
| Yes | 247 (25) | 110 (27) | 137 (23) | 79 (19) | 168 (29) |
| No | 760 (75) | 296 (73) | 463 (77) | 348 (81) | 412 (71) |
| Previous lumbar fusion, N (%) | |||||
| Yes | 123 (12) | 56 (14) | 67 (11) | 40 (9) | 83 (14) |
| No | 124 (12) | 54 (13) | 70 (12) | 39 (9) | 85 (15) |
| Smoked before, N (%) | |||||
| Never | 529 (53) | 211 (52) | 317 (53) | 243 (57) | 286 (49) |
| Currently | 101 (10) | 46 (11) | 55 (9) | 61 (14) | 40 (7) |
| Quit | 347 (34) | 140 (34) | 207 (35) | 102 (24) | 245 (42) |
| Missing | 30 (3) | 9 (2) | 21 (4) | 21 (5) | 9 (2) |
| Comorbidities, N (%) | |||||
| Osteoarthritis in any joint | 581 (58) | 235 (58) | 346 (58) | 162 (38) | 419 (72) |
| Osteoarthritis in hip | 187 (19) | 76 (19) | 111 (10) | 37 (9) | 150 (26) |
| Osteoarthritis in knee | 329 (33) | 122 (30) | 207 (35) | 71 (17) | 258 (44) |
| Osteoarthritis in hand | 216 (21) | 82 (20) | 134 (22) | 42 (10) | 174 (30) |
| Joint replacement | 440 (44) | 177 (44) | 263 (44) | 127 (30) | 313 (54) |
| Anxiety | 407 (40) | 110 (27) | 297 (50) | 244 (57) | 163 (28) |
| Depression | 402 (40) | 109 (27) | 292 (49) | 218 (51) | 184 (32) |
| Vision impairment or loss | 354 (35) | 165 (41) | 189 (32) | 108 (25) | 246 (42) |
| Herniated disk | 336 (33) | 152 (38) | 184 (31) | 138 (32) | 198 (34) |
| Balance problems/falls | 310 (31) | 119 (29) | 191 (32) | 105 (25) | 205 (35) |
| Scoliosis | 225 (23) | 69 (17) | 156 (26) | 74 (17) | 151 (26) |
| Vertebral fracture | 88 (9) | 39 (10) | 48 (8) | 31 (7) | 57 (10) |
| Hearing impairment or loss | 213 (21) | 127 (31) | 86 (14) | 43 (10) | 170 (29) |
| Cancer | 203 (20) | 91 (22) | 112 (19) | 32 (7) | 171 (29) |
| Thyroid disease | 184 (18) | 38 (10) | 145 (24) | 48 (11) | 136 (23) |
| Diabetes | 159 (16) | 73 (18) | 85 (14) | 43 (10) | 116 (20) |
| Osteoporosis | 117 (12) | 24 (6) | 93 (16) | 23 (5) | 94 (16) |
| Spinal cord injury | 35 (3) | 17 (4) | 18 (3) | 17 (4) | 18 (3) |
| Multiple sclerosis | 14 (1) | 3 (1) | 11 (1) | 5 (1) | 9 (1) |
| Chronic overlapping pain conditions | |||||
| Migraine or chronic headache | 293 (29) | 79 (19) | 214 (36) | 165 (39) | 128 (22) |
| Irritable bowel syndrome | 161 (16) | 40 (10) | 121 (20) | 61 (14) | 100 (17) |
| Temporomandibular joint dysfunction | 117 (12) | 29 (7) | 88 (15) | 57 (13) | 60 (10) |
| Interstitial cystitis/Irritable bladder | 100 (10) | 44 (11) | 56 (9) | 24 (6) | 76 (13) |
| Fibromyalgia | 99 (10) | 10 (2) | 89 (15) | 45 (11) | 54 (9) |
| Chronic fatigue | 43 (4) | 12 (3) | 31 (5) | 23 (5) | 20 (3) |
| For women only | |||||
| Endometriosis | — | — | 81 (14) | 36 (12) | 45 (15) |
| Vulvodynia | — | — | 12 (2) | 6 (2) | 6 (2) |
| Previous pregnancy, N (%) | — | — | 426 (71) | 188 (65) | 238 (77) |
| History of COVID‐19 infection, N (%) e | 323 (32) | 133 (33) | 190 (32) | 147 (35) | 176 (30) |
One participant reported sex at birth as intersex and was therefore not included in the descriptive statistics for male/female.
The denominators for height, weight and BMI are N = 1006 for all participants, N = 405 for male, N = 600 for female, N = 426 for age < 60, and N = 580 for age ≥ 60.
The denominators for waist circumference are N = 385 for all participants, N = 175 for male, N = 210 for female, N = 150 for age < 60, and N = 235 for age > 60 because this assessment was started 2/3 into the study.
The denominators for blood pressure are N = 1002 for all participants, N = 403 for male, N = 599 for female, N = 423 for age < 60, and N = 579 for age > 60.
The denominators for COVID‐19 infection are N = 1005 for all participants, N = 406 for males, N = 599 for females, N = 426 for age < 60, and N = 579 for age > 60.
FIGURE 3.
Dark blue bars represent main categories whereas light blue bars represent sub‐categories. Treatments are presented in categories from most to least frequent.
TABLE 3.
Treatments received for low back pain during the past month.
| All | Male a | Female a | Age < 60 | Age ≥ 60 | |
|---|---|---|---|---|---|
| N = 1007 | N = 406 | N = 600 | N = 427 | N = 580 | |
| Spine surgery, N (%) b | 27 (3) | 15 (4) | 12 (2) | 12 (3) | 15 (3) |
| If spinal surgery, number of spinal fusions | 6 (0.6) | 4 (1) | 2 (0.2) | 3 (0.7) | 3 (0.5) |
| Spine injection, N (%) b | 73 (7) | 30 (7) | 43 (7) | 25 (6) | 48 (8) |
| Medication, N (%) b | |||||
| No | 443 (44) | 191 (47) | 252 (42) | 196 (46) | 247 (43) |
| Yes, type of medication: | 558 (56) | 214 (53) | 344 (58) | 226 (54) | 350 (57) |
| Nonsteroidal anti‐inflammatory | 431 (43) | 162 (40) | 269 (45) | 182 (43) | 249 (43) |
| Gabapentin | 180 (18) | 65 (16) | 115 (19) | 79 (19) | 101 (17) |
| Opioid | 131 (13) | 49 (12) | 82 (14) | 58 (14) | 73 (13) |
| SSRI/SNRI antidepressant | 97 (10) | 20 (5) | 77 (13) | 55 (13) | 42 (7) |
| Tricyclic antidepressant | 29 (3) | 7 (2) | 22 (4) | 13 (3) | 16 (3) |
| Other | 37 (4) | 18 (4) | 19 (3) | 12 (3) | 25 (4) |
| Physical/Occupational therapy or chiropractic, N (%) | |||||
| No | 675 (67) | 266 (66) | 408 (68) | 284 (67) | 391 (67) |
| Yes, type of treatment: | 332 (33) | 140 (34) | 192 (32) | 143 (33) | 189 (33) |
| Active (e.g., supervised exercise) | 191 (19) | 86 (21) | 105 (18) | 81 (19) | 110 (19) |
| Adjustment/Manipulation | 130 (13) | 51 (13) | 79 (13) | 63 (15) | 67 (12) |
| Passive (e.g., ultrasound, massage) | 83 (8) | 31 (8) | 52 (9) | 39 (9) | 44 (8) |
| Other | 34 (3) | 11 (3) | 23 (4) | 9 (2) | 25 (4) |
| Exercise routine done on their own, N (%) | 581 (58) | 252 (62) | 329 (55) | 226 (53) | 355 (61) |
| Mindfulness, meditation, or relaxation, N (%) | 223 (22) | 71 (17) | 152 (25) | 118 (28) | 105 (18) |
| Diet or nutrition counseling, N (%) | 209 (21) | 67 (17) | 141 (24) | 89 (21) | 120 (21) |
| Group supervised exercise, N (%) | 127 (13) | 37 (9) | 90 (15) | 49 (11) | 78 (13) |
| None reported, N (%) | 135 (13) | 52 (13) | 83 (14) | 64 (15) | 71 (12) |
| Mind/body (e.g., yoga, Tai‐chi), N (%) | 112 (12) | 36 (9) | 86 (14) | 65 (15) | 57 (10) |
| Mental health therapy or counseling, N (%) | 44 (4) | 12 (3) | 32 (5) | 31 (7) | 13 (2) |
| Acupuncture, N (%) | 22 (2) | 9 (2) | 13 (2) | 9 (2) | 13 (2) |
One participant reported sex at birth as intersex and was therefore not included in the descriptive statistics for male/female.
The denominator for surgery, injection, and medication is N = 1001 for all participants, N = 404 for male, N = 596 for female, N = 422 for age < 60, and N = 579 for age ≥ 60.
3.2. Biological Sex
The average ages were 66 years for males and 57 years for females. African Americans represented 14% of males and 21% of females. Males reported 20% more frequently than females being married/having a partner and 5% more frequently having some postgraduate education. Five percent more females were either employed full‐time or not employed, and 12% fewer females were retired or on Medicare compared to males (Table 1). As anticipated, the males were taller, heavier, and had larger waist circumference. Presence of daily/nearly daily back pain was reported 7% more frequently in males. A larger number of females reported anxiety (23%), depression (22%), and thyroid disease (14%), and fewer had hearing problems (17%) than males. The COPCs such as migraine or headache, irritable bowel syndrome, and fibromyalgia were reported in higher numbers in females (Table 2). Compared to males, females reported 8% more frequent use of SSRI or SNRI antidepressants, 5% more frequent use of NSAIDs, and ≥ 5% more frequent engagement in group supervised exercises, mindfulness, mind/body activities, and diet/nutritional counseling for back pain. On the other hand, females reported exercising on their own 7% less frequently than males (Table 3).
3.3. Age
Forty‐two percent of the sample was < 60 years old and 58% ≥ 60 years old. African Americans represented 21% of the younger and 15% of the older group. Compared to the younger group, the older group reported more frequently having postgraduate education (7%), being married/having a partner (15%), being retired (59%), and being enrolled in Medicare (32%). On the other hand, younger adults reported more frequently not being employed or having private health insurance (19% and 24%, respectively). The frequency of individuals on worker's compensation was higher in the younger compared to the older group (Table 1). The older group had 5% more reports of back pain ongoing for > 5 years, 7% more reports of experiencing back pain daily/nearly daily, and 10% more lumbar surgery—including 5% more lumbar fusion. A larger proportion of the younger group never smoked. The older group had a higher proportion of individuals with age‐related conditions such as osteoarthritis, joint replacements, cancer, osteoporosis, thyroid issues, diabetes, vertebral fractures, and balance, hearing, or vision problems. In contrast, fewer older adults had depression, anxiety, and migraine (Table 2). The younger group reported taking SSRI or SNRI antidepressants about twice as often as the older group. The older group reported doing exercise on their own or engaging in group supervised exercise more frequently than the younger group; whereas more younger individuals reported engaging in mindfulness and mind/body activities (Table 3).
4. Discussion
We believe this study provides one of the most comprehensive characterizations of demographic and biomedical factors stratified by sex and age in a large cohort of 1007 people with cLBP. This cohort greatly contributes to LBP research by providing reference values for clinical use and enhancing research planning, in addition to future phenotyping. Our recruitment efforts resulted in a diverse sample of individuals with cLBP. To put it in perspective, the race and ethnicity distribution of our sample in comparison to the U.S. Census demonstrated higher representation of African Americans (18% in our study compared to 14% in the U.S. Census) and similar representation for White and more than one race (75% and 3%, respectively in the U.S. Census and our study) [18]. Despite our outreach efforts to Hispanic and Asian local communities, the study's representation was low (3% and 2%, respectively) and smaller than the U.S. Census (19% Hispanic and 6% Asian). This low representation is likely a reflection of enrolling from Southwestern Pennsylvania, an area with approximately 2% Hispanic and 3.5% Asian residents [18].
The demographic characteristics of our sample were compared to the most recent large epidemiologic study characterizing cLBP in the U.S. from Schmagel et al. [9] The Schmagel study used the National Health and Nutrition Examination Survey (NHANES) 2009–2010 and surveyed 700 adults with cLBP. While the data collected in the current study and that of the Schmagel study were slightly different, we observed similarities in the distributions for household income, relationship status, obesity, smoking history, and co‐existing comorbidities. This comparison also revealed a similar higher representation of female (56% in Schmagel and 60% in our study), corroborating evidence of a higher prevalence of LBP for women than men [19, 20]. On the other hand, our sample had a higher representation of Medicare beneficiaries and highly educated individuals. The higher representation of individuals on Medicare (28% in our study and 13% in Schmagel study) is likely due to the older age range in our study, from 18 to 95 years old. For context, the administration of NHANES surveys in the Schmagel study was limited to individuals from 20 to 69 years old. For education level, our sample included 48% of individuals with less than a college degree compared to 80% in the Schmagel study. This difference may be related to most of our recruitment taking place in an academic medical center and a geographic area with several higher education institutions, in contrast to the NHANES study that used a probability sampling process based on census information.
Several of the sex and age differences seem to be due to males in our sample being on average 9 years older than the females. For example, the females and younger group were more frequently employed and less frequently retired and Medicare beneficiaries. Additionally, differences related to age, such as the older group reporting longer LBP and more lumbar surgery, may be a result of this subgroup living with LBP for extended periods of time. For the other sex and age‐related factors, such as females and the younger group reporting less education and lower frequency of being unemployed, married/having a partner, and experiencing daily/nearly daily back pain compared to males, it is challenging to contextualize our observations as the prior literature lacks a comprehensive characterization of these factors by sex and age. Further studies are needed to assess the implications of these sex‐ and age‐related findings in pain and disability experienced in cLBP.
Important indications of the burden of cLBP in our population include the majority reporting that pain was ongoing every day or nearly every day (76%), having had pain for more than 5 years (61%), and 20% reporting having been out of work for 30 days or more due to back pain. The results also revealed that many individuals with cLBP had co‐existing conditions such as osteoarthritis, anxiety, depression, balance problems, and COPCs. This observation emphasizes the relevance of properly addressing these co‐existing conditions in the management of cLBP. Furthermore, our study shows consistency with the distribution of comorbidities across sex and age as previously reported for the general population regardless of LBP status [21, 22, 23, 24, 25, 26]. For example, the older adults had a higher frequency of age‐related conditions such as osteoarthritis, cancer, osteoporosis, diabetes, and hearing, vision, and balance problems, but a lower frequency of depression, anxiety, and migraine [21, 22, 23]; and females had a higher frequency of COPCs, anxiety, depression, and thyroid disease [24, 25, 26]. The findings of female and younger groups being more frequently depressed also aligned with these subgroups taking more SSRI/SNRI antidepressants.
There is limited literature to compare our findings for LBP‐related treatments. For medications used in the last month, our results were compared to a U.S. representative community‐based data from the 2009–2010 cycle of the NHANES [27]. The use of opioids in our study was 13% and 19% in the NHANES study, NSAID use was 43% in our study and 10% in NHANES, SSRI or SNRI antidepressant use was 10% and 15% respectively, gabapentin or pregabalin use was 18% and 7%, and tricyclic antidepressant use was 3% in our study and 2% in the NHANES study. The comparatively lower use of opioids and higher use of NSAIDs and gabapentin/pregabalin in our cohort could be due to the older age of our sample or the approximately 10‐year lapse in data collection from NHANES and our study, reflecting a potential positive impact of last decade's opioid reducing campaigns.
For sex‐related findings, females reported taking NSAIDs more frequently than males, which could reflect females' lower efficiency in pain coping or hormonal‐related higher susceptibility to musculoskeletal pain [28, 29]. Additionally, females and younger groups reported engaging in mindfulness and mind/body activities more frequently and exercising on their own less frequently, whereas females and older adults reported engaging in group supervised exercise more frequently. Overall, the sex and age differences highlighted in this study substantiate the importance of factoring these variables into research designs, analysis, and reporting in clinical studies in cLBP. While the NIH Policy on Sex as a Biological Variable has been enacted since 2014 [12], age also appears to be a critical biological variable to be consistently considered in cLBP research.
While this paper provides a description of a large sample of individuals with cLBP that successfully met the eligibility criteria, we acknowledge this is not a description of the general population with cLBP. This study is limited by enrolling participants from a single site and with more education than community‐based epidemiologic studies, and the fact that less than half (43%) of the sample was employed. The latter was likely due to the lengthy (4–5 h) study assessment visit [13] that could limit participation of individuals in hourly jobs or those without available personal time off. Strengths of our study included attracting more retired, Medicare beneficiaries, and older individuals compared to previous epidemiologic studies. Including a representative sample of older adults is crucial as the prevalence of LBP increases with age [30]. It is our belief that despite some limitations, our research brings attention to novel information on comprehensive demographic and biomedical characteristics stratified by sex and age, their frequencies, and the use of treatments for LBP in a large sample of individuals suffering from cLBP. Future work of our group will include assessment of the interplay of these comprehensive factors and pain and disability in cLBP, as well as their potential contribution in phenotyping and characterizing the experience of cLBP.
5. Conclusions
Describing comprehensive demographic and biomedical characteristics of individuals with cLBP, stratified by sex and age, collected by the unprecedented dataset of the LB3P study will allow clinicians and researchers to gain a deeper understanding of cLBP and serve as a reference to inform future research and clinical practice.
Conflicts of Interest
The authors declare no conflicts of interest.
Supporting information
Data S1 Supporting information.
Acknowledgments
The Back Pain Consortium Research Program is administered by the National Institute of Arthritis and Musculoskeletal and Skin Diseases. This research was supported by the National Institutes of Health through the NIH HEAL Initiative under award number U19AR076725. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or its NIH HEAL Initiative. The authors would like to thank Selena Crawford, LB3P's project manager, and the members of our advisory board—Dino Samartzis, James Iatridis, Kevin Luster, Nicole Kelly, and Ronald Glick.
Piva S. R., Smith C., Anderst W., et al., “Demographic and Biomedical Characteristics of an Observational Cohort With Chronic Low Back Pain: A Descriptive Analysis,” JOR Spine 8, no. 3 (2025): e70094, 10.1002/jsp2.70094.
Funding: This work was supported by National Institute of Arthritis and Musculoskeletal and Skin Diseases, U19AR076725.
References
- 1. GBD 2021 Low Back Pain Collaborators , “Global, Regional, and National Burden of Low Back Pain, 1990‐2020, Its Attributable Risk Factors, and Projections to 2050: A Systematic Analysis of the Global Burden of Disease Study 2021,” Lancet Rheumatology 5 (2023): e316–e329. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. Wong C. K., Mak R. Y., Kwok T. S., et al., “Prevalence, Incidence, and Factors Associated With Non‐Specific Chronic Low Back Pain in Community‐Dwelling Older Adults Aged 60 Years and Older: A Systematic Review and Meta‐Analysis,” Journal of Pain 23 (2022): 509–534. [DOI] [PubMed] [Google Scholar]
- 3. Hayden J. A., Ellis J., Ogilvie R., et al., “Some Types of Exercise Are More Effective Than Others in People With Chronic Low Back Pain: A Network Meta‐Analysis,” Journal of Physiotherapy 67 (2021): 252–262. [DOI] [PubMed] [Google Scholar]
- 4. Ho E. K., Chen L., Simic M., et al., “Psychological Interventions for Chronic, Non‐Specific Low Back Pain: Systematic Review With Network Meta‐Analysis,” BMJ (Clinical Research Ed.) 376 (2022): e067718. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Baroncini A., Maffulli N., Schafer L., et al., “Physiotherapeutic and Non‐Conventional Approaches in Patients With Chronic Low‐Back Pain: A Level I Bayesian Network Meta‐Analysis,” Scientific Reports 14 (2024): 11546. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Ferguson S. A., Merryweather A., Thiese M. S., et al., “Prevalence of Low Back Pain, Seeking Medical Care, and Lost Time due to Low Back Pain Among Manual Material Handling Workers in the United States,” BMC Musculoskeletal Disorders 20 (2019): 243. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Freburger J. K., Holmes G. M., Agans R. P., et al., “The Rising Prevalence of Chronic Low Back Pain,” Archives of Internal Medicine 169 (2009): 251–258. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Feldman D. E. and Nahin R. L., “Disability Among Persons With Chronic Severe Back Pain: Results From a Nationally Representative Population‐Based Sample,” Journal of Pain 23 (2022): 2144–2154. [DOI] [PubMed] [Google Scholar]
- 9. Shmagel A., Foley R., and Ibrahim H., “Epidemiology of Chronic Low Back Pain in US Adults: Data From the 2009‐2010 National Health and Nutrition Examination Survey,” Arthritis Care & Research (Hoboken) 68 (2016): 1688–1694. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Wang Y. X., Wang J. Q., and Kaplar Z., “Increased Low Back Pain Prevalence in Females Than in Males After Menopause Age: Evidences Based on Synthetic Literature Review,” Quantitative Imaging in Medicine and Surgery 6 (2016): 199–206. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Hestbaek L., Iachine I. A., Leboeuf‐Yde C., Kyvik K. O., and Manniche C., “Heredity of Low Back Pain in a Young Population: A Classical Twin Study,” Twin Research 7 (2004): 16–26. [DOI] [PubMed] [Google Scholar]
- 12. National Institutes of Health , “Consideration of Sex as a Biological Variable in NIH‐Funded Research. NOT‐OD‐15‐102,” 2015. (2015), NIH Office of Extramural Research.
- 13. Vo N. V., Piva S. R., Patterson C. G., et al., “Toward the Identification of Distinct Phenotypes: Research Protocol for the Low Back Pain Biological, Biomechanical, and Behavioral (LB3P) Cohort Study and the BACPAC Mechanistic Research Center at the University of Pittsburgh,” Pain Medicine 24 (2023): S36–S47. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Deyo R. A., Dworkin S. F., Amtmann D., et al., “Report of the NIH Task Force on Research Standards for Chronic Low Back Pain,” Journal of Pain 15 (2014): 569–585. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Clinical and Translational Science Institute , “Pitt+Me,” (2018), Clinical and Translational Science Institute, University of Pittsburgh.
- 16. Clinical and Translational Science Institute , “Community PARTners,” (2019), Clinical and Translational Science Institute, University of Pittsburgh.
- 17. Wandner L. D., Domenichiello A. F., Beierlein J., et al., “NIH'S Helping to End Addiction Long‐Term(SM) Initiative (NIH HEAL Initiative) Clinical Pain Management Common Data Element Program,” Journal of Pain 23 (2022): 370–378. [DOI] [PubMed] [Google Scholar]
- 18. United States Census Bureau, U.S. Department of Commerce , “QuickFacts United States,” 2023. V2023 ed.
- 19. Meucci R. D., Fassa A. G., and Faria N. M., “Prevalence of Chronic Low Back Pain: Systematic Review,” Revista de Saúde Pública 49, no. 1 (2015): 1–10. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.“QuickStats: Percentage* of Adults Aged ≥18 Years Who Had Lower Back Pain in the Past 3 Months,† by Sex and Age Group ‐ National Health Interview Survey,§ United States, 2018,” MMWR. Morbidity and Mortality Weekly Report 68 (2020): 1196. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Hasin D. S., Goodwin R. D., Stinson F. S., and Grant B. F., “Epidemiology of Major Depressive Disorder: Results From the National Epidemiologic Survey on Alcoholism and Related Conditions,” Archives of General Psychiatry 62 (2005): 1097–1106. [DOI] [PubMed] [Google Scholar]
- 22. Seibert T., Schroeder M. W., Perkins A. J., et al., “The Impact of the COVID‐19 Pandemic on the Mental Health of Older Primary Care Patients and Their Family Members,” Journal of Aging Research 2022 (2022): 6909413. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Wijeratne T., Tang H. M., Crewther D., and Crewther S., “Prevalence of Migraine in the Elderly: A Narrated Review,” Neuroepidemiology 52 (2019): 104–110. [DOI] [PubMed] [Google Scholar]
- 24. Maixner W., Fillingim R. B., Williams D. A., Smith S. B., and Slade G. D., “Overlapping Chronic Pain Conditions: Implications for Diagnosis and Classification,” Journal of Pain 17 (2016): T93–T107. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25. Shawon M. S. R., Hossain F. B., Hasan M., and Rahman M. R., “Gender Differences in the Prevalence of Anxiety and Depression and Care Seeking for Mental Health Problems in Nepal: Analysis of Nationally Representative Survey Data,” Global Mental Health (Cambridge) 11 (2024): e46. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26. Vanderpump M. P. J., Tunbrldge W. M. G., French J. M., et al., “The Incidence of Thyroid Disorders in the Community: A Twenty‐Year Follow‐Up of the Whickham Survey,” Clinical Endocrinology 43 (1995): 55–68. [DOI] [PubMed] [Google Scholar]
- 27. Shmagel A., Ngo L., Ensrud K., and Foley R., “Prescription Medication Use Among Community‐Based U.S. Adults With Chronic Low Back Pain: A Cross‐Sectional Population Based Study,” Journal of Pain 19 (2018): 1104–1112. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28. Staud R., Robinson M. E., C. J. Vierck, Jr. , and Price D. D., “Diffuse Noxious Inhibitory Controls (DNIC) Attenuate Temporal Summation of Second Pain in Normal Males but Not in Normal Females or Fibromyalgia Patients,” Pain 101 (2003): 167–174. [DOI] [PubMed] [Google Scholar]
- 29. Wong A. Y. L., “Musculoskeletal Pain in Postmenopausal Women—Implications for Future Research,” Hong Kong Physiotherapy Journal 34 (2016): A1–A2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30. Back, Lower Limb, and Upper Limb Pain Among U.S. Adults, 2019 (National Center for Health Statistics, 2021), 10.15620/cdc:107894. [DOI] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data S1 Supporting information.