Metabolic screening · chronic pain

Metabolic Screening in Chronic Pain: Who to Test and What Changes

Screen chronic pain patients whose pain limits work, self-care or activity, or who hurt at multiple sites: that pain history predicts cardiometabolic death. Fasting insulin, the triglyceride-glucose index and body composition find the risk that glucose and CRP miss.

Pain that limits function and spreads across several sites carries mortality risk that survives adjustment. That turns the pain history into a screening trigger, not only a treatment problem.

The case for metabolic screening with chronic pain as the trigger rests on an epidemiologic finding most workups ignore: the pain history itself predicts cardiometabolic death, while the standard pain evaluation measures almost none of the cardiometabolic terrain. In most practices the back is managed in one silo and the glucose in another, and neither silo owns the patient.

The Cost of Pain Is Paid in Years, the Chapter 1 video of The Pained Brain by Dr. Gurpreet Singh Padda, MD, MBA, MHP, and Dr. KrisJay Fucanan, MD, makes that case for patients. For clinicians the translation is operational: which pain patients to screen, what the measurements add beyond glucose and CRP, what a finding changes, and how it is documented.

Does chronic pain raise the risk of early death?

In UK Biobank participants aged 40 to 69, chronic widespread pain was associated with all-cause mortality of 2.28 in men and 2.31 in women against no chronic pain, attenuating to 1.47 once body mass, activity, smoking, alcohol and diet entered the model. In an American cohort of 19,487 adults over 50 followed for two decades, activity-limiting pain carried a hazard of 1.64 unadjusted and 1.52 after sociodemographic adjustment. With cardiac, oncologic, pulmonary and diabetic disease plus BMI added, it still carried 1.33. Severe pain without functional limitation, by contrast, sat at 1.05, not significant. Interference, not intensity, is the variable worth charting.

Site count behaves like a dose. Across 384,367 UK adults, the mortality hazard rose from 1.09 with one chronic musculoskeletal pain site to 1.46 with four. Neck or shoulder pain alone carried 1.99 for death from endocrine, nutritional and metabolic disease, in a model adjusted for age, sex, ethnicity and deprivation but not for BMI or diabetes.

Read the attenuation carefully. When adjustment for weight, diabetes and heart disease shrinks the pain association, the absorbed variance sits in the metabolic disease. Arithmetic cannot say whether those variables confound or mediate. Clinically, the answer is the same either way: the risk lives where it can be measured.

A Danish interdisciplinary pain center linked 6,142 patients to the national death register and found a standardized mortality ratio of 6.2, with circulatory deaths at 5.7, adjusted only for age and sex.

Who needs metabolic screening for chronic pain?

A practical selection rule follows from those cohorts. Consider cardiometabolic measurement in chronic pain patients who have:

• pain that limits work, self-care or activity, regardless of the intensity score;
• pain at multiple sites, recorded as a count rather than as the worst site;
• central adiposity with a glucose and A1c that have been called normal;
• a normal BMI with East Asian or South Asian ancestry, where visceral and hepatic fat run ahead of weight;
• depression or anxiety alongside the pain, given that 39.3% of adults with chronic pain carry clinically significant depressive symptoms and 40.2% anxiety symptoms across pooled studies.

These criteria map onto existing selection criteria and can be written as a standing order for screening, so the pain history triggers the measurement without a separate decision at every visit.

Which blood tests find metabolic risk in chronic pain?

Glucose is a late signal. Hyperinsulinemia, defined as fasting insulin above 10 µU/mL, was present in 41.4% of nondiabetic NHANES adults in 2017-2018, and HOMA-IR insulin resistance in 38.4%. The HOMA-IR threshold of 2.6 behind those figures is a population percentile; no consensus diagnostic cutoff exists, so serial values within one laboratory are more informative than a single reading.

The triglyceride-glucose index is computable from labs already on file. In 3,546 Chinese adults with a mean BMI of 23.76 followed nine years, each one-unit rise predicted new severe chronic pain at 1.51, and baseline BMI did not differ between those who developed pain and those who did not, 24.06 against 23.75. In American survey data the index stayed associated with chronic pain after adjustment for BMI and diabetes status, at 1.25, and within the chronic pain group the top tertile carried 2.05 times the all-cause mortality of the bottom.

CRP is a weak screening anchor. A visceral-fat score predicted chronic pain in 5,905 NHANES adults, with CRP mediating 7.4% of the effect, and Mendelian randomization finds no causal effect of CRP on spinal pain. Prospectively, hs-CRP alone did not predict incident chronic musculoskeletal pain, yet hs-CRP at or above 3 mg/L combined with sleeplessness carried 2.47. The marker means more read against the sleep history than read alone. The underlying model is inflammation that fails to resolve, metaflammation, supported by gene-expression work in acute low back pain whose human arm remains observational.

What changes when a pain patient’s metabolic screen is abnormal?

A normoglycemic patient with hyperinsulinemia, a high triglyceride-glucose index or a visceral-predominant body composition is reclassified from a pain problem with normal labs to a pain problem inside metabolic disease. That changes the plan: lifestyle and behavioral work moves from discharge advice to the core of treatment, the interval for repeat measurement is set in advance, and procedures are framed as a bridge to terrain repair rather than the whole plan.

The evidence base for pain treatment rarely describes this patient. Half of 168 randomized trials in nonspecific low back pain excluded prior or scheduled surgery, while among 500,295 UK adults, 69.1% of those with chronic pain had at least one long-term condition and 36.2% had two or more. Guideline-derived care was built on somebody else, which is the argument for measuring the person in front of you. It takes some humility for pain medicine, Dr. Padda’s own specialty, to admit that of the twelve chronic pain modalities the American Society of Anesthesiologists lists, none addresses systemic inflammation.

The drivers are not only biological. At age 52, pain was reported by 40% of Americans born in 1965 without a bachelor’s degree against 32% of the 1955 cohort, rising 0.6 percentage points per birth year without a degree and 0.2 with one; body mass explained about a quarter. Pain prevalence reaches 31.4% in nonmetropolitan counties. Screening that follows only symptoms will miss the populations where the gradient is steepest.

Where Measura fits in the workflow

Measura [Cardiometabolic and Autonomic Health Analysis] is a testing service under physician medical direction. It performs and reports measurements; diagnosis and management stay with the ordering physician. For this indication the relevant tests are laboratory panels that add fasting insulin and the lipid pattern to glucose and A1c, bioimpedance body composition to separate fat and lean compartments that BMI conflates, and arterial stiffness and endothelial function for the vascular consequence of sustained hyperinsulinemia.

Documentation should carry the variables the cohorts validated: pain site count, whether pain limits activity, waist circumference in centimeters, fasting insulin with glucose and lipids, and a mood screen. Structured fields make those values reportable and trendable, and getting results into the record keeps them in front of the next clinician. For context, under 12.2% of US adults met full metabolic-health criteria on NHANES 2009–2016 and under 7% on the tighter post-2021 criteria; in Dr. Padda’s practice, under 1% of chronic pain patients do, practice-reported figures from our own population, not trial outcomes, with individual results that vary. The study-level detail is in the Chapter 1 supplement, and the diagnostic framework that follows is in the physician article on screening the terrain before escalating care.

Frequently asked questions

References

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• Chen, L., Ferreira, M. L., Nassar, N., Preen, D. B., Hopper, J. L., Li, S., Bui, M., Beckenkamp, P. R., Shi, B., Arden, N. K., & Ferreira, P. H. (2021). Association of chronic musculoskeletal pain with mortality among UK adults: A population-based cohort study with mediation analysis. EClinicalMedicine, 42, 101202. https://doi.org/10.1016/j.eclinm.2021.101202
• Macfarlane, G. J., Beasley, M., & Jones, G. T. (2023). Chronic pain and premature mortality in men and women, using data from UK Biobank. The Journal of Clinical Investigation, 133(5), e166949. https://doi.org/10.1172/JCI166949
• Vaegter, H. B., Støten, M., Silseth, S. L., Erlangsen, A., Handberg, G., Sondergaard, S., & Stenager, E. (2019). Cause-specific mortality of patients with severe chronic pain referred to a multidisciplinary pain clinic: a cohort register-linkage study. Scandinavian Journal of Pain, 19(1), 93–99. https://doi.org/10.1515/sjpain-2018-0094
• Zhou, D., Jin, F., Zhang, L., Chen, J., Tian, L., & Li, J. (2026). The Mediating Role of WBC in the Relationship Between Triglyceride-Glucose Index and Chronic Pain: Evidence From NHANES 2001-2004 Data. Pain Research & Management, 2026(1), e3793191. https://doi.org/10.1155/prm/3793191
• Skarpsno, E. S., Mork, P. J., Nilsen, T. I. L., Steingrímsdóttir, Ó. A., Zwart, J. A., & Nilsen, K. B. (2019). The interplay between sleeplessness and high-sensitivity C-reactive protein on risk of chronic musculoskeletal pain: longitudinal data from the Tromsø Study. Sleep, 42(9), zsz127. https://doi.org/10.1093/sleep/zsz127
• McQueenie, R., Jani, B. D., Siebert, S., McLoone, P., McCowan, C., Macdonald, S., Mair, F. S., & Nicholl, B. I. (2021). Prevalence of chronic pain in LTCs and multimorbidity: A cross-sectional study using UK Biobank. Journal of Multimorbidity and Comorbidity, 11, Article 26335565211005870. https://doi.org/10.1177/26335565211005870
• McMasters, M., & Mora, J. (2025). Addressing Meta-Inflammation in the Comprehensive Management of Chronic Pain. Cureus, 17(10), e94863. https://doi.org/10.7759/cureus.94863
• Aaron, R. V., Ravyts, S. G., Carnahan, N. D., Bhattiprolu, K., Harte, N., McCaulley, C. C., Vitalicia, L., Rogers, A. B., Wegener, S. T., & Dudeney, J. (2025). Prevalence of Depression and Anxiety Among Adults With Chronic Pain: A Systematic Review and Meta-Analysis. JAMA Network Open, 8(3), Article e250268. https://doi.org/10.1001/jamanetworkopen.2025.0268
• Case, A., Deaton, A., & Stone, A. A. (2020). Decoding the mystery of American pain reveals a warning for the future. Proceedings of the National Academy of Sciences of the United States of America, 117(40), 24785-24789. https://doi.org/10.1073/pnas.2012350117

Related reading

• Preoperative Diabetes Screening Before Pain Procedures and Surgery
• Laboratory Panels

Medically reviewed by Dr. Gurpreet Singh Padda, MD, MBA, MHP, medical director of Measura. Last reviewed September 12, 2026.