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. 2024 Dec 13;103(50):e40949. doi: 10.1097/MD.0000000000040949

Relationship between pain severity and self-perceived health among United States adults: A cross-sectional, retrospective database study

David Rhys Axon a,*, Jonan Smith a
PMCID: PMC11651436  PMID: 39686452

Abstract

Self-perceived health is related to outcomes such as morbidity and mortality. However, little is known about the relationship between pain severity and self-perceived health, which could be useful to know to help improve health. This study assessed the association of pain severity and other contributing factors with self-perceived health among United States adults. This cross-sectional, retrospective database study used 2019 Medical Expenditure Panel Survey data and included United States adults aged ≥18 years who responded to the pain item in the survey. The independent variable was self-reported pain severity, and the dependent variable was self-perceived health. Various potentially confounding variables were controlled for in the analysis. Adjusted logistic regression models were used to identify statistical associations between each variable and self-perceived health. The complex survey design was maintained, while nationally representative estimates were obtained. Among the sample of 17,261 United States adults, 88.1% (95% confidence interval, 87.4%–88.8%) reported excellent, very good, or good self-perceived health, while 11.9% (95% confidence interval, 11.2%–12.6%) reported fair or poor self-perceived health. In adjusted analyses, there were significant associations between fair or poor self-perceived health and any level of pain severity versus no pain, age 40 to 64 versus 18 to 39 years, male versus female, Hispanic versus non-Hispanic, high school diploma or less versus more than high school, unemployed versus employed, poor, near poor, or low versus middle or high income, fair or poor versus excellent, very good, or good mental health, exercising <5 times versus ≥5 times per week, smoker versus nonsmoker, and ≥2 versus <2 comorbid conditions. This study found that greater levels of pain severity (and several other variables) were associated with greater odds of reporting fair or poor self-perceived health. These associations provide greater insight into the variables associated with self-perceived health, which may be useful targets to improve health.

Keywords: health status, pain intensity

1. Introduction

Pain is a subjective, prevalent condition described as “an unpleasant sensory and emotional experience associated with, or resembling that associated with, actual or potential tissue damage.”[1] In 2016, the National Health Survey determined ≈50 million (20%) United States (US) citizens reported having pain.[2] This has increased from 11.2% (25.3 million) in 2012.[3] Although multiple pharmacological and nonpharmacological products exist to control pain,[4,5] it is often not well managed with current treatment plans reportedly resulting in a reduction of pain by only 30%.[6] Therefore, although some patients benefit from their pain management approach, many are unable to adequately manage their pain. The number of individuals affected by pain has a considerable economic impact. For instance, health economists have reported pain costs $635 billion annually in 2010 US dollars.[7] Research has noted the high prevalence of pain and conditions related to pain as a major cause of disability and disease.[8] A systematic literature review from 2005 to 2013 found a correlation between the amount of pain individuals experience and their quality of life.[9] Pain is a primary pretext for seeking healthcare services and is often related to poorer health and increased mortality.[10–14]

Self-perceived health represents an individual’s subjective measure of their own health and is frequently used by large-scale surveys to estimate overall population well-being, physical health conditions, and functioning.[15–17] Self-perceived health is often presented as an indicator of health in wide-scale research and is associated with several characteristics such as age, ethnicity, body mass index, number of physician consultations, total household income, self-perceived work stress, hospitalizations, healthcare utilization, and mortality.[15,18–24] In the US, poor self-perceived health has increased in recent years. For example, 2014 Behavioral Risk Factor Surveillance System data showed 14.8% of adults reported poor/fair health,[25] while the same survey conducted in 2018 showed that 19.2% of US adults reported poor/fair health.[26]

Prior studies have found statistical relationships between pain and self-perceived health.[27–34] In particular, a recent study that evaluated 2018 Medical Expenditure Panel Survey (MEPS) data indicated that adults over the age of 50 years had increased odds of reporting good self-perceived health if they had little or moderate pain.[33] However, current literature is limited on the relationship (and extent of the relationship) between pain severity and the self-perceived health of US adults. Therefore, this study’s goal was to investigate this knowledge gap by assessing the relationship between pain severity and the self-perceived health of adults in the US.

2. Methods

2.1. Study design, data source, and eligibility criteria

This cross-sectional, retrospective database study used the latest available data from the 2019 MEPS full-year consolidated data file (HC-216), which collected demographic, health, and healthcare service data for 28,512 participants. The sampling framework for MEPS encompasses a subset of the households surveyed in the National Health Interview Survey, which is undertaken by the National Center for Health Statistics. The MEPS panel design features 5 rounds of interviewing over the course of 2 calendar years.[35–37] Eligibility criteria included MEPS participants who were alive in 2019, aged ≥18 years, and responded to the pain severity item when interviewed. MEPS participants provided informed consent before providing data.

2.2. Independent variable

The independent variable was self-reported pain severity, established by replies to the MEPS item: during the past 4 weeks, how much did pain interfere with your normal work (including both work outside the home and housework)? Response options included: not at all, a little bit, moderately, quite a bit, or extremely.[36,37]

2.3. Control variables

Control variables were identified based on their pertinence to perceived pain severity and self-perceived health and were classified into 1 of 3 categories for analysis using the Andersen Behavioral Model (predisposing, enabling, and need variables).[38] Predisposing variables comprised age, sex, race, and ethnicity. Enabling variables comprised education, employment, insurance, marital, and poverty status. Need variables comprised mental health, exercise, smoking, and comorbid conditions from the ensuing list: asthma, chronic bronchitis, emphysema, angina, coronary heart disease, hypercholesterolemia, hypertension, myocardial infarction, other heart diseases, stroke, diabetes, cancer, arthritis, and joint pain.[36,37]

2.4. Dependent variable

The dependent variable was self-perceived health, established by replies to the MEPS item: in general, compared with other people of your age, would you say that your health is excellent, very good, good, fair, or poor?[36,37] Responses were dichotomized such that fair or poor signified poor health and excellent, very good, or good signified good health.

2.5. Statistical analysis

Statistical analysis was conducted using SAS (SAS Institute, Inc, Cary, NC). The characteristics of individuals with fair or poor health and individuals with excellent, very good, or good health were compared using χ2 tests. Associations between pain severity and self-perceived health were tested using logistic regression. Model 1 was an unadjusted analysis that included the independent variable (pain severity) only and the dependent variable (fair or poor versus excellent, very good, or good self-perceived health). Models 2, 3, and 4 included the independent variable and were adjusted for predisposing variables (model 2), predisposing and enabling variables (model 3), and predisposing, enabling, and need variables (model 4). Alpha = 0.05 was selected a priori. Variables provided in the MEPS data file to maintain the cluster and strata of the data, as well as to obtain weighted population-based estimates, were used. A correlation matrix (≥0.8 suggested collinearity) and a variance inflation factor (≥10 suggested collinearity) were used to evaluate collinearity. No evidence of collinearity was detected. This study was approved by the University of Arizona Institutional Review Board (00001533; July 8, 2022).

3. Results

3.1. Number of individuals included in the study

Figure 1 shows the study eligibility criteria. Of the 28,512 individuals included in the 2019 data file, 17,261 were eligible for study inclusion. This represented a weighted sample of 242,169,897 US adults aged ≥18 years. Of these, 11.9% (95% confidence interval [CI], 11.2%–12.6%) reported fair or poor self-perceived health, while 88.1% (95% CI, 87.4%–88.8%) reported excellent, very good, or good self-perceived health.

Figure 1.

Figure 1.

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Study eligibility criteria.

3.2. Characteristics of individuals included in the study

Table 1 shows the characteristics of US adults aged ≥18 years grouped by self-perceived health in the 2019 MEPS data. Most individuals (63.5% [95% CI, 62.5–64.4]) reported not having pain. Among those who did report having pain, the most commonly reported pain severity was little pain (21.5% [95% CI, 20.7–22.2]). Among predisposing variables, the most common age category was 40 to 64 years. There were approximately equal proportions of males and females, and the majority were White and not Hispanic. Among enabling variables, the majority were educated beyond high school, were employed, were privately insured, were married, and had a middle or high income. Among need variables, the majority had excellent, very good, or good perceived mental health, were nonsmokers, and had <2 comorbid conditions. Just over half (51%) reported doing ≥30 minutes of exercise ≥5 times a week. Significant differences (P < .05) existed between self-perceived health groups for all variables except race (P = .6246) and ethnicity (P = .2457).

Table 1.

Characteristics of United States adults aged ≥18 years stratified by self-perceived health in the 2019 Medical Expenditure Panel Survey.

Variable Excellent, very good, or good perceived health weighted N = 213,316,714, % (95% CI) Fair or poor perceived health weighted N = 28,853,183, % (95% CI) Total weighted N = 242,169,897, % (95% CI) P value
Pain severity <.0001
 Extreme 0.7 (0.5–0.8) 12.1 (10.5–13.6) 2.0 (1.8–2.3)
 Quite a bit 3.6 (3.2–3.9) 22.3 (20.2–24.4) 5.8 (5.4–6.2)
 Moderate 6.1 (5.6–6.5) 15.8 (14.0–17.7) 7.2 (6.7–7.7)
 Little 21.2 (20.3–22.0) 23.7 (21.7–25.6) 21.5 (20.7–22.2)
 No pain 68.5 (67.6–69.5) 26.1 (24.0–28.2) 63.5 (62.5–64.4)
Predisposing variables
Age, yr <.0001
 ≥65 19.7 (18.8–20.7) 31.6 (29.2–34.0) 21.1 (20.2–22.1)
 40–64 40.4 (39.4–41.5) 47.0 (44.7–49.3) 41.2 (40.2–42.2)
 18–39 39.8 (38.7–41.0) 21.4 (19.4–23.4) 37.6 (36.6–38.7)
Sex .0329
 Male 48.6 (47.9–49.3) 46.0 (43.9–48.2) 48.3 (47.7–48.9)
 Female 51.4 (50.7–52.1) 54.0 (51.8–56.1) 51.7 (51.1–52.3)
Race .6246
 White 78.0 (76.5–79.5) 77.4 (74.8–80.0) 77.9 (76.4–79.4)
 Other 22.0 (20.5–23.5) 22.6 (20.0–25.2) 22.1 (20.6–23.6)
Ethnicity .2457
 Hispanic 16.4 (14.7–18.1) 17.7 (14.8–20.6) 16.6 (14.9–18.3)
 Not Hispanic 83.6 (81.9–85.3) 82.3 (79.4–85.2) 83.4 (81.7. 85.1)
Enabling variables
 Education <.0001
  High school diploma or less 37.5 (36.0–39.0) 54.9 (52.2–57.6) 39.5 (38.0–41.1)
  More than high school 62.5 (61.0–64.0) 45.1 (42.4–47.8) 60.5 (58.9–62.0)
 Employment status <.0001
  Employed 71.5 (70.5–72.4) 42.8 (40.3–45.2) 68.0 (67.0–69.0)
  Unemployed 28.5 (27.6–29.5) 57.2 (54.8–59.7) 32.0 (31.0–33.0)
 Insurance status <.0001
  Any private 71.7 (70.3–73.1) 47.8 (45.3–50.2) 68.8 (67.4–70.3)
  Public only 20.6 (19.5–21.7) 45.8 (43.4–48.2) 23.6 (22.5–24.8)
  Uninsured 7.7 (6.9–8.5) 6.5 (5.0–7.9) 7.5 (6.7–8.3)
 Marital status <.0001
  Married 53.1 (51.9–54.3) 44.8 (42.2–47.5) 52.1 (50.9–53.3)
  Other 46.9 (45.7–48.1) 55.2 (52.5–57.8) 47.9 (46.7–49.1)
 Poverty status <.0001
  Poor, near poor, or low income 23.6 (22.4–24.8) 44.9 (42.0–47.8) 26.1 (24.9–27.4)
  Middle or high income 76.4 (75.2–77.6) 55.1 (52.2–58.0) 73.9 (72.6–75.1)
Need variables
 Mental health status <.0001
  Excellent, very good, or good 96.1 (95.7–96.5) 58.3 (55.8–60.8) 91.6 (91.1–92.2)
  Fair or poor 3.9 (3.5–4.3) 41.7 (39.2–44.2) 8.4 (7.8–8.9)
 Exercises ≥30 min, ≥5 times a week <.0001
  Yes 53.9 (52.7–55.1) 29.3 (26.9–31.7) 51.0 (49.8–52.2)
  No 46.1 (44.9–47.3) 70.7 (68.3–73.1) 49.0 (47.8–50.2)
 Smoker <.0001
  Yes 12.7 (11.9–13.5) 23.9 (21.5–26.3) 14.0 (13.2–14.9)
  No 87.3 (86.5–88.1) 76.1 (73.7–78.5) 86.0 (85.1–86.8)
 Comorbid conditions <.0001
  <2 62.5 (61.4–63.6) 24.7 (22.7–26.7) 58.0 (56.9–59.0)
  ≥2 37.5 (36.4–38.6) 75.3 (73.3–77.3) 42.0 (41.0–43.1)
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Analysis based on an unweighted sample n = 17,261 United States adults aged ≥18 years alive during the calendar year 2019. Statistically significant differences between groups based on χ2 tests.

CI = confidence interval.

3.3. Associations between pain severity and self-perceived health

Table 2 reports the associations between pain severity and fair or poor (versus excellent, very good, or good) self-perceived health among US adults in the 2019 MEPS data. In the unadjusted analysis, those who reported increased levels of pain severity had increased odds of reporting fair or poor self-perceived health than those with no pain. This pattern remained the same in adjusted analyses although the odds ratios became progressively lower as additional variables were controlled for. For instance, in the fully adjusted analysis, those who reported having extreme pain (versus no pain) had ≈13 times greater odds of reporting fair or poor self-perceived health, whereas those reporting little pain (versus no pain) had ≈2 times greater odds of reporting fair or poor self-perceived health. In fully adjusted analyses, predisposing variables associated with greater odds of reporting fair or poor perceived health were aged 40 to 64 (versus 18–39) years, males (versus females), and Hispanic (versus not Hispanic) ethnicity. Enabling variables associated with greater odds of reporting fair or poor perceived health were having a high school diploma or less (versus more than high school), being unemployed (versus employed), and having poor, near poor, or low income (versus middle or high income). Need variables associated with increased odds of reporting fair or poor perceived health were reporting fair or poor perceived mental health (versus excellent, very good, or good), not exercising ≥30 minutes for ≥5 times per week (versus exercising ≥30 minutes for ≥5 times per week), being a smoker (versus not a smoker), and having ≥2 comorbid conditions (versus <2). The c-statistic = 0.873 and the Wald statistic = <0.0001 in the fully adjusted model.

Table 2.

Associations between pain severity and fair or poor (versus excellent or very good or good) self-perceived health among United States adults aged ≥18 years in the 2019 Medical Expenditure Panel Survey

Variable Model 1: pain severity (unadjusted), OR (95% CI) Model 2: pain severity and predisposing variables, OR (95% CI) Model 3: pain severity, predisposing, and enabling variables, OR (95% CI) Model 4: pain severity, predisposing. enabling, and need variables, OR (95% CI)
Pain severity
 Extreme versus no pain 46.1 (36.2–58.6)* 43.9 (34.6–55.8)* 27.6 (21.3–35.9)* 12.7 (9.3–17.3)*
 Quite a bit versus no pain 16.5 (13.9–19.4)* 15.9 (13.4–19.0)* 12.0 (10.0–14.4)* 6.5 (5.3–7.9)*
 Moderate versus no pain 6.9 (5.8–8.1)* 6.7 (5.6–8.1)* 5.5 (4.6–6.6)* 3.4 (2.8–4.1)*
 Little versus no pain 2.9 (2.6–3.4)* 2.9 (2.6–3.4)* 2.8 (2.4–3.2)* 1.9 (1.7–2.3)*
Predisposing variables
 Age ≥65 versus 18–39 yr 1.4 (1.2–1.6)* 1.1 (0.9–1.3) 0.9 (0.7–1.1)
 Age 40–64 versus 18–39 yr 1.4 (1.2–1.6)* 1.5 (1.3–1.8)* 1.2 (1.0–1.5)*
 Male versus female 1.1 (1.0–1.2) 1.1 (1.0–1.3)* 1.2 (1.1–1.4)*
 White versus other 0.8 (0.7–0.9)* 1.0 (0.8–1.1) 0.9 (0.7–1.0)
 Hispanic versus non-Hispanic 1.7 (1.4–2.0)* 1.4 (1.1–1.6)* 1.6 (1.3–1.9)*
Enabling variables
 High school diploma or less versus more than high school 1.3 (1.2–1.5)* 1.3 (1.1–1.5)*
 Employed versus unemployed 0.6 (0.5–0.7)* 0.8 (0.7–0.9)*
 Any private versus uninsured 0.9 (0.7–1.2) 0.8 (0.6–1.1)
 Public only versus uninsured 1.3 (1.0–1.8)* 1.0 (0.7–1.3)
 Married versus other 0.8 (0.7–0.9)* 1.0 (0.8–1.1)
 Poor, near poor, or low versus middle or high income 1.5 (1.3–1.7)* 1.3 (1.1–1.5)*
Need variables
 Excellent, very good, or good versus fair or poor mental health 0.1 (0.1–0.1)*
 Exercises ≥30 min, ≥5 times a week yes versus no 0.5 (0.4–0.6)*
 Smoker yes versus no 1.5 (1.3–1.8)*
 Comorbid conditions <2 versus ≥2 0.3 (0.3–0.4)*
Open in a new tab

Analysis based on an unweighted sample n = 17,261 United States adults aged ≥18 years alive during the calendar year 2019. The reference group in the binomial logistic regression models was excellent or very good or good perceived health.

CI = confidence interval, OR = odds ratio.

*

The characteristic has a significant association with self-perceived physical health (P < .05). Model c-statistics: model 1 = 0.769, model 2 = 0.785, model 3 = 0.810, and model 4 = 0.873. The Wald value was P < .0001 in all 4 models.

4. Discussion

4.1. Discussion of key independent variable

The first key finding was that US adults had increased odds of reporting fair or poor self-perceived health as pain severity increased. In agreement with this finding, a previous study that evaluated 2018 MEPS data showed that adults aged at least 50 years with little or moderate pain had increased odds of reporting good perceived health than adults with quite a bit or extreme pain in the US.[33] Other studies have found that pain is associated with greater odds of reporting poorer health in Canada and Brazil.[39,40] Furthermore, a study of Swedish men aged 65 to 73 years from 2010 to 2019 showed that pain was a key factor in determining self-perceived health.[41] The present study’s findings are, therefore, consistent with previously published papers that found, perhaps unsurprisingly, that the severity of pain can influence an individual’s perception of their health. This study adds to what is already known by offering contemporary evidence of the extent of this association among US adults.

The second key finding was the identification of statistically significant associations between predisposing, enabling, and need variables with self-perceived health.

4.2. Discussion of predisposing variables

Our study showed 40- to 64-year-olds had increased odds of having fair or poor self-perceived health than 18- to 39-year-olds. This is a logical finding given that older age is typically associated with poorer physiological functioning and overall health.[42–44] However, in contrast to this notion, our study also showed that adults aged ≥65 years did not have higher odds of reporting fair or poor self-perceived health than adults aged 18 to 39 years. This finding contrasts with the theory of a linear relationship between poor health and age.[45] The relationship between age and self-perceived health among adults in the US is, therefore, unclear and requires further investigation. Possible reasons to explain our findings are whether the question asked about general health status versus age-related health or that those aged ≥65 years are less likely to be working and less physically active and, therefore, experience less work-related fatigue compared with working-age adults.[46,47] Another reason could be that US adults wait until they are aged ≥65 years to obtain healthcare services through Medicare.[48] A further reason could be that older adults have become accustomed to living with pain and poorer health or expect to have pain and poorer health as they get older; thus, they have a lower likelihood of reporting poor self-perceived health.[49]

Our study showed that males had increased odds of recording fair or poor self-perceived health compared with females. This is contrary to the findings in existing literature, which have found no difference in health status between sexes among older adults in Spain and adults in Brazil.[50,51] One possible reason to explain our result is that men have more chronic conditions than women, which is related to health status.[52] Our study also showed that Hispanics had increased odds of reporting fair or poor self-perceived health compared with non-Hispanics. This finding parallels existing literature[53,54] and is thought to be because Hispanics do not always have continuous health insurance coverage, have poorer quality healthcare, use the healthcare system less, and have poorer English language skills.[55–57]

4.3. Discussion of enabling variables

Among enabling variables, our study showed that having a high school diploma or less, being unemployed, and having poor/near poor/low income were associated with higher odds of reporting fair or poor self-perceived health than having more than a high school education. This finding is supported by existing literature that investigated education status, health status, and employment status with health status.[58–60] Various theories exist to explain these findings, with one being that less healthy individuals have less time for education.[58] A cross-sectional study of 2004 to 2010 MEPS data found that employed individuals had a greater likelihood to delay or forgo treatment and theorized that as an individual’s health gets worse, they become less able to work.[61] Income has one of the strongest relationships with health in the US.[62,63] A 2018 systematic review showed that a broad range of social health determinants, including education status and occupational factors, was linked to chronic lower back pain,[59] which supports an association between many of the variables controlled for in our study and reporting pain.

4.4. Discussion of need variables

Among need variables, mental health status, not exercising for 30 minutes or ≥5 times per week, being a smoker, and having ≥2 comorbid conditions were associated with self-perceived health. These findings are perhaps unsurprising given their known relationship with health but are worthwhile documenting as they provide contemporary evidence of their association with self-perceived health. Poor self-reported mental health is associated with poor self-perceived health in other studies.[64,65] Likewise, the association between exercise frequency and smoking status on health status has been well studied.[12,66–68] Finally, having multiple significant health conditions can result in poorer health outcomes and poorer self-perceived health.[69,70]

4.5. Limitations

Study limitations included self-reported secondary data collected by other researchers for purposes other than this study. Thus, we had to make use of the available variables as they were collected and defined, which may limit this study’s comparability with other studies that may have used different definitions for variables such as pain and health status. Other variables that may be relevant to the topic, such as sleep quality, were not available in the dataset and, thus, not included in the analysis. The self-reported data can result in reporting errors and recall bias, which may also affect the reliability and validity of the results. Importantly, this study had a cross-sectional, retrospective database design. Thus, only a statistical association can be made rather than a cause-and-effect relationship. Further research with different study designs is warranted to establish causality. Furthermore, it is possible that self-perceived pain severity and self-perceived health were not synchronized in this study and may change over time. The relatively large sample size included in this analysis may warrant a more conservative statistical threshold, for example, 0.001 rather than 0.05. Depending on the statistical threshold used, the interpretation of statistical significance may vary for some results. Regardless of these limitations, MEPS provides a large sample and number of variables that can produce nationally representative estimates with good external validity, which are strengths of this study.

5. Conclusion

In conclusion, this cross-sectional, retrospective database study demonstrated a significant statistical relationship between increasing pain severity levels and fair or poor self-perceived health. Our study also showed a statistical relationship between various predisposing, enabling, and need variables with self-perceived health. These findings can be used by policymakers and healthcare professionals to better understand the association between various characteristics and pain severity with self-perceived health among adults in the US.

Author contributions

Conceptualization: David Rhys Axon

Data curation: David Rhys Axon

Formal analysis: David Rhys Axon

Funding acquisition: David Rhys Axon

Investigation: David Rhys Axon, Jonan Smith

Methodology: David Rhys Axon, Jonan Smith

Project administration: David Rhys Axon

Resources: David Rhys Axon, Jonan Smith

Software: David Rhys Axon

Supervision: David Rhys Axon

Validation: David Rhys Axon, Jonan Smith

Visualization: David Rhys Axon, Jonan Smith

Writing – original draft: David Rhys Axon, Jonan Smith

Writing – review & editing: David Rhys Axon, Jonan Smith

Abbreviations:

CI
confidence interval
MEPS
Medical Expenditure Panel Survey
US
United States

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

DRA reports grant funding from the American Association of Colleges of Pharmacy, Arizona Department of Health, Merck & Co., National Council for Prescription Drug Programs, Pharmacy Quality Alliance, and Tabula Rasa HealthCare Group, outside of this study. JS has 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: Axon DR, Smith J. Relationship between pain severity and self-perceived health among United States adults: A cross-sectional, retrospective database study. Medicine 2024;103:50(e40949).

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