Pain across the lifespan: global and regional reference curves from 6.1 million individuals in 118 countries

This study establishes the first global reference curves for pain across the lifespan using data from over 6 million individuals, revealing that pain prevalence is highest in women and unexpectedly peaks in late life among low Human Development Index countries, with significant regional variations in the impact of modifiable risk factors.

The Gist

Imagine trying to understand how "pain" works across the entire human population. For a long time, we've been trying to map this out using scattered puzzle pieces from different countries, different languages, and different ways of asking questions. It was like trying to build a single map of the world using only local sketches drawn by different artists with different rulers.

This paper is the result of a massive effort to gather all those scattered pieces and build one giant, unified map. The researchers took data from 6 million people in 118 countries—a true global crowd-sourcing project—to create the first-ever "reference guide" for how pain changes as we get older.

Here is the story of what they found, told in simple terms:

1. The "Pain Map" Project

Think of this study as building a global weather forecast for pain. Instead of predicting rain or sunshine, they predicted where and when people are likely to feel pain. They looked at 11 different "zones" of the body (like the back, knees, head, and stomach) and tracked how pain levels rise and fall from childhood (age 5) all the way to extreme old age (100+).

They didn't just look at people who went to the doctor; they asked regular people, "Do you have pain?" This is important because many people in the world never see a doctor for their aches, so previous maps missed them.

2. The Surprising "Inverted U" Shape

Most people assume pain is like a hill you climb and never come down from: the older you get, the more it hurts. The paper says this is mostly wrong.

Instead, for most types of pain (like headaches, stomach aches, and even neck pain), the pattern looks more like a rollercoaster hill:

• The Climb: Pain starts low in childhood and climbs steeply as we enter adulthood.
• The Peak: It hits a high point in mid-life (usually between ages 40 and 60).
• The Slide: Surprisingly, after that peak, the pain often starts to decrease as people get very old.

The Exception: The "weight-bearing" joints (back, hips, and knees) are different. They act more like a staircase, climbing steadily and staying high all the way into old age, likely because they carry the weight of our bodies for decades.

3. The Gender Gap

The map shows a clear difference between men and women. Women consistently report more pain than men across every single body part. It's like the "pain meter" is turned up higher for women, with the biggest gap seen in facial pain and headaches.

4. The "Development" Surprise

Here is the biggest twist in the story. Usually, we think that richer countries (with better hospitals and food) have more reported health problems because people are more aware of them. But for pain, the map shows the opposite.

• The Richer Countries: Pain levels rise in mid-life but then flatten out or drop in old age.
• The Poorer Countries: Pain levels start lower in youth but then skyrocket in old age.

By the time people in lower-income countries reach age 80, they are reporting nearly twice as much pain as those in wealthy nations. It's as if the "pain hill" in poorer countries keeps getting steeper and steeper as people age, while in wealthy countries, the hill levels off. The researchers admit they don't fully know why this happens yet, but it suggests that the usual suspects (like smoking or obesity) aren't the main drivers of pain in these regions.

5. The "Three Culprits" (and where they fail)

The researchers tried to blame three common lifestyle factors for the pain: smoking, obesity, and low income.

• In wealthy regions (like Eastern Europe and North America), these three factors explain about 27% of the pain burden. It's like they are the main villains in the story.
• However, in poorer regions (like Sub-Saharan Africa), these same three villains only explain about 12% of the pain.

This means that in the world's poorest areas, the "villains" causing pain are still a mystery. It's like trying to solve a crime with only half the suspects; the real causes (perhaps hard physical labor, lack of medical care, or infections) are hiding in the shadows.

6. The New Tool

Finally, the authors didn't just write a report; they built a digital dashboard (a "benchmarking tool"). Think of this as a "GPS for pain researchers." Now, if a doctor in a small town wants to know if their patients' pain levels are normal, high, or low compared to the rest of the world, they can plug their data into this tool and see exactly where they stand on the global map.

Summary

This paper tells us that pain isn't a simple "get older, get more pain" story. It's a complex journey that looks different depending on your body part, your gender, and where you live on the map. Most importantly, it reveals that the world's poorest elderly people are suffering the most, and we currently don't have the right map to understand why.

Technical Summary

Technical Summary: Pain across the lifespan: global and regional reference curves from 6.1 million individuals in 118 countries

Problem Statement
Pain is the leading cause of disability globally, yet it lacks an objective biomarker, relying entirely on self-report. Current global surveillance frameworks, such as the Global Burden of Disease (GBD) study, rely on clinically defined conditions and modelled estimates derived from heterogeneous data sources. These approaches often fail to capture pain that does not enter diagnostic pathways, particularly in settings with limited access to care. Furthermore, existing self-reported pain data are fragmented across diverse instruments, recall periods, and study designs, preventing systematic harmonization at a global scale. Reported prevalence varies widely (8% to 64%), and fundamental questions regarding the emergence of pain across the lifespan, its variation by phenotype and sex, and its distribution across world regions remain unresolved due to the absence of a consistent reference framework.

Methodology
The study conducted a pooled analysis of individual-level data from 6,075,021 participants across 894 population-based data sources in 118 countries and territories, spanning the years 1990 to 2025.

• Data Harmonization: The authors mapped study-specific wording and body-map coding schemes to standardized categories for 11 major anatomical sites (head, face, neck/shoulder, foot/ankle, hand/wrist, elbow, chest, back, stomach/abdomen, hip, and knee). A composite "any bodily pain" outcome was derived where data permitted. Secondary outcomes included high-intensity pain (NRS ≥7) and generalized pain (pain in ≥4 of 5 body regions per 2016 fibromyalgia criteria).
• Statistical Modeling: Age-specific trajectories (ages 5 to 100+) were estimated using generalized linear mixed-effects models (GLMM) with a logit link. Natural cubic splines (3 degrees of freedom) were employed to flexibly capture nonlinear age trajectories.
• Adjustments and Controls: Models incorporated random effects to account for hierarchical data structures (individuals nested within cohorts and world regions). Fixed effects adjusted for key methodological features, specifically recall period (standardized to a past-month recall) and case definition (general vs. chronic-explicit).
• Risk Factor Analysis: The study evaluated associations with three modifiable risk factors: smoking status, body mass index (BMI), and household income (harmonized into study-specific quintiles). Population attributable fractions (PAFs) were calculated to quantify the burden attributable to these exposures across regions.
• Regional and Developmental Analysis: Trajectories were analyzed as a function of world regions (UN SDG classification) and the Human Development Index (HDI) to assess how national development levels influence pain accumulation.

Key Results

• Lifespan Trajectories: Pain prevalence varied significantly by anatomical site, ranging from 2.5% for facial pain to 45.0% for back pain. Contrary to the assumption that pain accumulates monotonically with age, 7 of 11 anatomical sites exhibited an inverted U-shaped trajectory, peaking in mid-to-late adulthood (e.g., headache peaking at age 34, abdominal pain at 22, and neck/shoulder pain at 58–62) before declining. Musculoskeletal pain in weight-bearing sites (back, hip, knee) showed progressive increases, often continuing into late life.
• Sex Differences: Women consistently reported higher prevalence than men across all 11 sites (Risk Ratio range: 1.09 to 1.83), with the largest disparities observed for facial, headache, and stomach/abdominal pain.
• Regional and HDI Disparities: While early-life pain prevalence was similar across regions, significant divergence occurred after age 65. Individuals in the lowest HDI countries experienced nearly twice the late-life prevalence of any bodily pain compared to those in the highest HDI countries (Risk Difference: 31.8 percentage points). Eastern Europe showed the greatest late-life excess, while Western Europe remained below the global reference in late adulthood.
• Risk Factors: Globally, 18.3% of pain burden was attributable to smoking, obesity, and low income. However, this varied drastically by region: 27.1% in Eastern Europe versus 12.6% in Sub-Saharan Africa. In low-HDI settings, these three factors accounted for a small fraction of the burden, suggesting that the drivers of pain in these regions remain poorly characterized and distinct from those in high-income settings.
• Intensity and Generalization: High-intensity and generalized pain followed inverted U trajectories, peaking in midlife (around age 50–70) before declining, whereas the likelihood of experiencing any pain rose steadily with age.

Significance and Claims
The paper claims to provide the first harmonized global reference framework for self-reported pain, constructed from raw individual-level data rather than aggregated statistics or clinical diagnoses. By establishing these reference trajectories, the study offers a common ground for comparing cohorts, clinical populations, and countries, particularly those underrepresented in global estimates.

The authors assert that their findings challenge prevailing assumptions that pain burden is uniformly higher in high-income regions or that it increases linearly with age. Instead, the data suggest that the majority of pain burden accumulates before midlife (age 55) and that the drivers of pain in lower-HDI settings are fundamentally different from those in high-income settings. The study concludes that these reference curves and the accompanying open-access benchmarking platform provide a foundation for more equitable global pain monitoring, highlighting the need for improved surveillance in lower-HDI regions to better understand the distinct determinants of pain burden in these populations.