Previous Article in Journal
Who Seeks Help? A Sociodemographic Analysis of Cannabis Use Disorder Treatment in New York
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Psychoactives
Volume 4
Issue 2
10.3390/psychoactives4020018
psychoactives-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Chronic Pain Conditions and Over-the-Counter Analgesic Purchases in U.S. Households: An Analysis of Nielsen-Kilts Ailment and Consumer Panel Data (2023)

by
Chesmi Kumbalatara
,
Dollia Cortez
and
Wasantha Jayawardene
*
School of Human Sciences, College of Health and Human Sciences, Southern Illinois University, Carbondale, IL 62901, USA
*
Author to whom correspondence should be addressed.
Psychoactives 2025, 4(2), 18; https://doi.org/10.3390/psychoactives4020018
Submission received: 1 May 2025 / Revised: 11 June 2025 / Accepted: 16 June 2025 / Published: 19 June 2025
Review Reports Versions Notes

Abstract

:
Chronic pain is a prevalent public health concern in the United States, frequently managed with over-the-counter (OTC) painkillers without professional medical supervision. This study investigates household-level patterns of over-the-counter painkiller use utilizing a nationally representative dataset from NielsenIQ, focusing on how reported health conditions, whether self-identified or professionally diagnosed, affect purchasing behaviors. By linking consumer purchase data with self-reported ailment information, this study analyzed painkiller expenditures across different ailment types and demographic groups. Results show that over-the-counter painkiller purchases were highly symptom-driven, particularly for headache-related products, which were the most frequently purchased category across all household types. Nearly one-third of single-member households purchased over-the-counter painkillers for headaches, regardless of diagnosis type, indicating a strong role of perceived need in driving behavior. Females and older individuals more frequently reported ailments, with consistently higher proportions across both pain-related and other conditions. Nonetheless, a notable share of households reported over-the-counter painkiller use without any reported ailments. The findings suggest that diagnostic status plays a limited role in determining over-the-counter painkiller usage, emphasizing the need for improved public health messaging around safe self-medication. These insights can inform targeted education, labeling regulations, and policy interventions to support safer and more equitable pain management practices at the population level.

1. Introduction

Chronic pain, defined as persistent discomfort lasting for three months or more and affecting quality of life, is a major health issue that significantly disrupts everyday life and work for millions of adults in the U.S. While over-the-counter (OTC) painkillers offer convenient relief for many, their widespread availability and use raise concerns about potential misuse, overuse, and the delayed diagnosis of underlying conditions [1]. This includes professionally diagnosed conditions such as arthritis, migraines, and chronic back pain, as well as self-identified chronic pain, where individuals perceive their symptoms as chronic despite lacking formal medical diagnosis. In 2016, approximately 50 million adults in the U.S. suffered from chronic pain conditions, which led to considerable healthcare expenditures and productivity losses. By 2021, this number further increased to 51.6 million (20.9% of adults) reporting chronic pain, with one-third of them experiencing severe forms that heavily restricted daily activities [2]. Pain conditions are also linked to mental health challenges such as depression [3], cognitive decline [4], increased risk of suicide [5], and substance use and misuse [6]. Given the widespread impact of chronic pain, improving care and quality of life for those affected has become a public health priority.
Professionally diagnosed chronic pain often involves regular monitoring, structured treatment plans, and multidisciplinary care, whereas self-identified chronic pain is often self-managed, symptomatically, without any professional advice. Psychological and behavioral factors, including health perceptions, coping mechanisms, and social influences, play a crucial role in determining whether pain is clinically addressed or self-managed. The subjective nature of pain also complicates its categorization, as individuals may downplay or overstate symptoms based on personal thresholds or cultural attitudes toward healthcare [7].
OTC painkillers, such as acetaminophen, ibuprofen, and aspirin, are widely accessible and serve as essential tools in managing pain for millions of individuals. The ability to obtain them without a prescription offers consumers the convenience of addressing pain conditions promptly, contributing to rising trends in sales and consumption patterns. The affordability and ease of acquisition make OTC painkillers an accessible solution for individuals across diverse socioeconomic backgrounds [8]. The medications have become integral to daily routines, often used to address minor aches and pains without requiring medical consultation. However, the overall widespread use of OTC painkillers raises questions about their long-term safety and the potential for misuse, particularly in cases of chronic pain management [1] and a gateway drug for other substances, especially for adolescents [9].
The use of OTC painkillers often stems from the desire for pain relief without the need for medical consultation. Accessibility, affordability, and perceived severity of symptoms are primary motivators for self-medication. Many individuals see OTC painkillers as a convenient way to regain productivity or normalcy, especially in the context of work or family obligations that make visiting a healthcare provider challenging. Marketing and branding further influence consumer decisions, with certain products being perceived as more effective or safer due to their reputation or active ingredients. However, the long-term use of OTC medications without professional guidance poses risks, including medication overuse, the delayed diagnosis of underlying conditions, and potential adverse health outcomes. Over time, the habitual use of OTC painkillers may also mask symptoms of more serious conditions, which can create additional barriers to seeking appropriate medical care [10].
Existing data on the incidence of chronic pain in the U.S. is confined to particular communities, healthcare professionals, age groups, pain types, or conditions, as well as claims data or medical records [11]. Despite the widespread use of OTC painkillers, existing research lacks a comprehensive comparison of consumption patterns between individuals with self-identified and medically diagnosed chronic pain conditions. Understanding this distinction is critical for tailoring public health interventions to address the specific needs and behaviors of different consumer groups. Studies that explore these patterns often overlook the influence of psychosocial and economic factors, which are critical for understanding the diverse behaviors of consumers. Additionally, there is limited evidence on how differences in pain perception and health literacy impact the choice of OTC medications [12]. Understanding the gaps in knowledge is critical for addressing disparities in healthcare access and improving consumer safety. Greater insights into these factors could be used to inform targeted interventions and educate the public on safe medication use and reduce the risks associated with self-medication.
Several previous studies had utilized NielsenIQ data, including both purchasing and ailment information, for a range of research purposes. For instance, one study examined disparities in ultra-processed food purchases among U.S. households using nationally representative data from the NielsenIQ Homescan Consumer Panel [13]. In addition, the “Annual Ailments, Health, and Wellness Survey” had been integrated into the NielsenIQ Consumer Panel data, capturing information on respondents’ ailments, diagnoses, and the ways in which these factors influenced shopping preferences [14]. Other research had employed the Nielsen Consumer Panel and Retail Scanner Data to investigate the effects of sugar-sweetened beverage taxes on purchasing behaviors [15].
Although the painkiller purchasing behavior had not been analyzed with ailments, this study investigated household-level patterns of OTC painkiller usage using a large, nationally representative dataset, with particular attention to how reported health conditions—whether self-identified or professionally diagnosed—influence medication purchasing behavior. The analysis explored differences in OTC painkiller expenditures among households with pain-related ailments, other ailments, or no reported ailments, and highlighted demographic influences such as gender, age, and household composition. These insights are intended to inform public health communication, guide responsible OTC usage, and support efforts to promote more equitable and evidence-based approaches to pain management at the household level.
By exploring these differences, this study aims to understand behavioral and systemic factors that contribute to variations in pain management strategies. The findings are intended to provide actionable insights for policymakers, healthcare providers, and public health campaigns to promote the safer and more effective use of OTC medications.

2. Materials and Methods

This study utilized two datasets provided by NielsenIQ: the Consumer Panel Data and the Ailment Dataset. Data for the 2023 calendar year were accessed from both datasets [14].

2.1. Consumer Panel Data

The Consumer Panel Data is a longitudinal, household-level dataset that captures detailed information on consumer purchasing behaviors across the United States. For this study, OTC painkiller purchases were analyzed. The data included every purchase recorded by panelist households using in-home scanners provided by NielsenIQ. Panelists scanned each item purchased during any retail visit, thereby enabling objective, item-level tracking of consumer behavior throughout the year.
The panel covered all major retail channels, including grocery, drug, mass merchandise, convenience, and superstores. Painkillers were identified across eight OTC product categories available in the data: analgesics, alkalizers, arthritis treatments, back/leg pain relievers, pediatric liquids, headache remedies, menstrual pain medications, and UTI treatments.
Sampling for the panel was conducted by NielsenIQ using stratified, proportionate methods to ensure demographic representation across 61 geographic markets. Panel retention was maintained at approximately 80% through incentive programs, including gift points and e-gift cards. Data quality was ensured through quarterly comparisons with point-of-sale (POS) data and by filtering out poor reporters. When POS data were not available, panelists manually reported prices, which were then verified through internal consistency checks and external data sources.

2.2. Ailment Data

The Ailment Dataset contained self-reported health information for up to five members per household. For each reported ailment, gender, age, and diagnosis source (self-diagnosed or professionally diagnosed) were recorded. The dataset included 48 ailments in total, of which seven were pain-related conditions. Arthritis, cancer, tension headaches, migraines, joint/neck/back pain, menopause, and musculoskeletal issues were the primary focus of this study. All remaining ailments were grouped together under the category of “other ailments” to provide a broad comparison with pain-related conditions and to focus the analysis on the primary research interest.
A total of 38,600 households were included in the original ailment dataset. Among 55,733 household members in the consumer panel, 28,608 households had matching entries in the ailment dataset. For the purposes of this analysis, only these overlapping households were considered, as they provided the data for health conditions as well as purchasing behaviors relevant to the research questions.
To align the temporal resolution of purchase data with the ailment data, daily OTC painkiller purchases were aggregated to the annual level. Furthermore, because purchases were recorded at the household level and were not linked to specific individuals, only households with a single reporting member were retained for ailment-related analyses, investigating the association between ailment status and OTC painkiller consumption. Households with multiple members were excluded from this portion of the analysis due to the inability to attribute purchases to individual users within households.

2.3. Data Preparation and Analysis

The Ailment and Consumer Panel datasets were linked using the household primary key, as previously conducted in related data integration efforts [16]. After identifying the overlapping households, product types and purchase data were extracted using multiple tables from the Consumer Panel dataset, including panelist, trip, purchase, and productdesc (product description). Corresponding ailment and demographic information for these households were obtained from the self-reported Ailment dataset.
Data preparation was conducted primarily using the dplyr (1.1.4) package [17] in R [18], with the vroom (1.6.5) package [19] employed to efficiently handle the large datasets in Consumer Panel dataset. Households with reported OTC painkiller purchases totaling USD 0 were excluded from the analysis (7 households out of 20,348) due to missing or unverifiable pricing information where NielsenIQ had no historical prices to adjust them.
Descriptive statistics were computed initially, followed by comparisons of OTC painkiller purchases across ailment categories: pain-related, other ailments, and no reported ailments. Normality assumptions for ANOVA were tested using the Kolmogorov–Smirnov test [20] and Agostino’s test [21] for skewness, both of which indicated non-normal distributions and skewed data. Consequently, the median was used to represent annual OTC expenditures. The Kruskal–Wallis test [22] was used to assess group differences in median expenditures, and Dunn’s post hoc test [23] with Bonferroni adjustment [24] was applied for pairwise comparisons. The crosstabs were tested for significance using the chi-square test [25]. A significance level of 5% was used for all statistical tests.

3. Results

Among 28,608 households, the average household size was 2.16 (SD = 1.18). Approximately 42.95% of households had two members, while 30.92% were single-member households. Only 0.11% of households included nine members, the highest number recorded in the study survey. Most household members were female (54.72%) (Table 1). The mean age was slightly higher among females compared to males. Ailment status varied by gender: while a similar proportion of male (31.33%) and female (30.26%) household members reported no ailments (61.87% of all members), pain-related ailments were reported substantially more often by female members (18.28%) than males (8.44%). Additionally, other ailments were also reported more frequently among females (11.89%) compared to males (7.53%).
As shown in Table 2, pain-related ailments were reported among various households and household members. Arthritis was the most frequently reported pain-related ailment at the household level (14.42%) and affected 8.22% of household members, with a majority being female (66.34%) and a mean age of 67.55 years (SD = 10.24). The next most reported pain-related ailment was joint, neck, or back pain, which was prevalent in 12.91% of households and 7.54% of household members. Menopause-related issues, although reported by only 7.60% of households, were found to be nearly exclusively prevalent among females (99.42%), as expected. Migraines and tension headaches were reported more frequently among females as well (79.75% and 73.35%, respectively), with average ages in their early 50s. Musculoskeletal pain was reported by 8.14% of households and affected 4.64% of household members, predominantly female (69.35%). Cancer and arthritis affected older populations, with average ages above 66 years.
Notably, 39.25% of households and 61.87% of household members did not report any pain-related conditions. It was also observed that the proportion of females among those who did not report any ailments (48.91%) was notably lower than that among individuals reporting any type of ailment, which was consistently greater than about 55%. Additionally, 33.12% of households reported experiencing “other ailments,” and a substantial 73.83% of household members also reported such conditions.
The overall median annual expense for OTC painkillers was USD 21.58 (IQR = 34.68) among 20,331 households that reported any purchases of them (Table 3). Annual household spending on OTC painkillers differed significantly by ailment category. Households with pain-related ailments (USD 23.66; IQR = 37.69) and those with any other ailments (USD 22.58; IQR = 38.69) reported significantly higher median expenditures compared to households with no reported ailments (USD 18.72; IQR = 29.57), as indicated by the Kruskal–Wallis test (p < 0.001) and confirmed by post hoc analysis. However, no significant differences were found between the pain-related ailment group and the other ailment reported groups.
Among the specific OTC painkiller categories, the highest median annual expenditures were observed for products “for headache” (USD 15.93; IQR = 23.84) and the third highest were observed for products “for analgesics” (USD 13.99; IQR = 18.76), based on households that reported any OTC painkiller purchases. These two categories also represented the most frequently purchased OTC painkillers, with 85.90% of households purchasing products for headaches and 41.32% purchasing analgesics. Both categories showed significant differences in spending across ailment groups (p < 0.001). For headache-related OTC painkiller products, significantly higher median expenditures were observed among households with pain-related ailments (USD 17.17; IQR = 26.04) and any other ailments (USD 15.99; IQR = 24.40) compared to those with no reported ailments (USD 14.36; IQR = 20.85), as indicated by the Kruskal–Wallis test and confirmed by post hoc analysis. However, no significant difference was found between the pain-related and any other ailment groups.
For other categories of painkillers—including those for arthritis, back and leg pain, pediatric liquids, menstrual relief, alkalizers, and products related to UTIs—no statistically significant differences were observed among the three groups, and fewer than 10% of households had purchased them for any category.
Among households with only one household member reporting a single pain-related ailment or other condition, the highest proportions of reported OTC painkiller purchases were in the categories “For headache” (45.83–61.67%) and “For analgesics” (17.39–33.33%), based on 1962 individuals (Table 4). In contrast, lower percentages of individuals reported using OTC painkillers for conditions such as cancer, migraine, and urinary tract infections. Notably, a substantial number of non-purchasers were observed across all ailment categories, suggesting that not all individuals with these conditions rely on OTC painkillers. For example, 43.33% of households reported having cancer, and 42.48% of those who reported having migraines did not purchase OTC painkillers. Nearly half (48.89%) of household members who did not report any ailments purchased OTC painkillers for headaches, while 21.68% purchased analgesics.
Out of the households with a single household member considered in Table 4, the data were filtered to include only households that either purchased OTC painkillers for headaches or did not purchase any OTC painkillers, resulting in a total of 5231 households. Among these, 3470 households reported no ailment; of these, 58.80% purchased OTC painkillers for headaches (Table 5). In contrast, approximately 63% of households with a single household member reported either pain-related (any pain-related ailment; N = 1116) or other ailments (any other ailment; N = 65) and purchased OTC painkillers for headaches. This difference was statistically significant (χ2 = 43.65, p < 0.001), indicating a clear association between the reported ailment and the likelihood of purchasing OTC painkillers for headaches.
Purchases of OTC painkillers did not vary significantly based on whether the pain was self-identified or diagnosed by a healthcare professional. Regardless of the method of pain identification or the type of ailment (pain-related or otherwise), a substantial proportion—nearly one-third—of households reported purchasing OTC painkillers for headaches.

4. Discussion

This study investigated household-level patterns of OTC painkiller usage using a nationally representative consumer/retailer dataset, focusing on differences by ailment type, gender, age, and method of diagnosis (self-reported vs. professionally diagnosed). The findings reveal that OTC painkiller use is widespread and symptom-driven, with headache-related medications the most commonly purchased category. Among households that reported any OTC painkiller use, the median annual expenditure was highest for headache medications (USD 15.93), followed by analgesics (USD 13.99). Approximately one-third of all households with a single household member reported purchasing OTC painkillers for headaches, regardless of whether the ailment was self-identified or medically diagnosed. Notably, among all households that had purchased any OTC painkillers, 85.90% had purchased medications specifically for headaches. This consistency across diagnostic types suggests that the perception of symptoms, rather than diagnostic classification, largely drove OTC medication behavior, particularly for headaches [26]. This underscores the influence of self-assessment in managing this common ailment [10].
Significant gender and age differences emerged in ailment reporting, with females more frequently reporting both pain-related and other ailments. The average age among individuals not reporting any ailments (45.47 years) was younger than among those with reported conditions, suggesting that older populations are more susceptible to chronic or recurring ailments (as expected) that might require pain management. Notably, households with no reported ailments still exhibited considerable amounts of painkiller purchases, particularly for headaches, indicating a strong reliance on OTC-based solutions even in the absence of reported chronic pain conditions [27].
While headaches accounted for the majority of OTC painkiller purchases, other conditions also contributed meaningfully to usage patterns. Musculoskeletal pain, arthritis, and menopausal symptoms—though less frequently reported—were associated with regular use of OTC painkillers. For example, arthritis was reported in 14.42% of households and affected 8.22% of individuals, with notable representation among older females. Similarly, menopause-related issues and musculoskeletal conditions were predominantly reported by women. While these conditions did not drive usage to the same extent as headaches, they suggest a wider range of health concerns influencing OTC painkiller consumption and point to potential associations with demographic characteristics such as age and gender.
The findings highlight that headaches play a major role in motivating OTC painkiller purchases. Even in households with no reported ailments and just one member, more than half reported buying OTC painkillers, especially for headaches. This aligns with the literature suggesting that headaches, especially tension-type headaches and migraines, are among the most common reasons for self-medication with OTC analgesics [28]. The lack of statistically significant differences in painkiller purchases between self-identified and provider-diagnosed conditions suggests that individuals trust their own judgment in managing pain symptoms, particularly headaches, an observation supported by past research on self-medication practices [29,30,31].
Furthermore, the notable association between health status and OTC purchases for headaches (χ2 = 43.65, p < 0.001) indicates that, although OTC medication behavior is affected by reported health issues, a significant portion of its use may still be for preventive reasons or based on occasional, non-chronic symptoms. The higher prevalence of pain-related conditions among females, particularly conditions like arthritis, migraines, and menopause-related issues, could partially explain the greater overall purchase frequency and expenditure observed in households with predominantly female members. This aligns with longstanding findings on the gender gap in chronic pain prevalence and analgesic use [32].
These results have important implications for public health and pain management interventions and policies. First, the widespread purchase of OTC painkillers for headaches across all household types, irrespective of reported ailments or diagnostic clarity, indicates a critical need for better public education on the safe use of these medications. Given the potential risks of overuse, such as medication-overuse headaches, liver toxicity from acetaminophen, or gastrointestinal bleeding from NSAIDs, educational campaigns should target common misconceptions about the safety of frequent OTC painkiller use [33].
Second, the data suggest that OTC medication use is less about diagnostic certainty and more about recognizing symptoms and starting self-care. This supports initiatives focused on providing consumers with clear labeling, pharmacist guidance, and tools for making informed decisions about self-medication [34]. Policies encouraging pharmacist–patient interactions at the point of purchase could improve outcomes without restricting access.
Finally, the gender and age disparities in ailment reporting and purchasing behavior indicate the value of tailoring educational and clinical interventions to older adults and women, who appear more vulnerable to chronic ailments requiring ongoing pain management. Community-based health initiatives could benefit from focusing on these subgroups to address both the risks of long-term OTC analgesic use and the need for more comprehensive pain assessment strategies [35].
Future studies should explore longitudinal designs to trace the temporal dynamics of OTC painkiller usage and examine if patterns shift with public health campaigns, regulatory adjustments, or disease progression. Gaining more detailed individual-level data regarding dosage, frequency, and the concurrent use of prescription medications could further improve the understanding of usage trends and associated risks. Research that investigates the decision-making process for OTC painkiller usage—especially the impact of media, interactions with pharmacists, and online information—can support the development of more targeted interventions.
Additionally, the relationship between mental health conditions and painkiller usage is worth exploring, as stress-related disorders are often linked to headache prevalence [36] and may drive excessive or inappropriate medication use. There is also a need for research focusing on underserved or rural populations where access to professional healthcare is limited, potentially leading to greater reliance on OTC medications.

Limitations

Several limitations must be acknowledged. First, the ailment data relies on self-report, which can be subject to recall bias and social desirability bias, particularly in reporting sensitive health information. Second, the dataset reflects household-level rather than individual-level expenditures, which limits the granularity of behavioral analysis at the individual level. Third, the dataset did not include information on the quantity of medication consumed or dosing frequency, limiting the ability to assess risks of overuse or chronic exposure to OTC medications.

5. Conclusions

This study highlights the widespread, symptom-driven use of OTC painkillers in U.S. households, particularly for headaches. Nearly one-third of households purchased headache medications, often without a formal diagnosis, highlighting the role of perceived need in self-medication. Notable patterns by age and gender, especially among older adults and women, were observed in both ailment reporting and purchasing behavior. These findings point to the need for targeted public health strategies that support safe and informed OTC painkiller use, combining education, provider guidance, and policy measures to promote equitable and effective pain management.

Author Contributions

Conceptualization, C.K. and W.J.; methodology, C.K. and W.J.; software, C.K.; validation, C.K., W.J., and D.C.; formal analysis, C.K.; investigation, W.J.; resources, C.K.; data curation, C.K. and W.J.; writing—original draft preparation, C.K.; writing—review and editing, D.C. and W.J.; visualization, C.K. and W.J.; supervision, W.J.; project administration, C.K.; funding acquisition, W.J. All authors have read and agreed to the published version of the manuscript.

Funding

This secondary data analysis was funded by the Illinois Department of Public Health (IDPH) under Grant# 33281072K.

Institutional Review Board Statement

Ethical review and approval were waived for this study as it involves secondary analysis of de-identified data.

Informed Consent Statement

Not applicable.

Data Availability Statement

Access to NielsenIQ data is subject to confidentiality agreements and may require a license or subscription. Researcher(s)’ own analyses calculated (or derived) based in part on data from Nielsen Consumer LLC and marketing databases provided through the NielsenIQ Datasets at the Kilts Center for Marketing Data Center at The University of Chicago Booth School of Business. The conclusions drawn from the NielsenIQ data are those of the researcher(s) and do not reflect the views of NielsenIQ. NielsenIQ is not responsible for, had no role in, and was not involved in analyzing and preparing the results reported herein.

Acknowledgments

We extend our heartfelt thanks to Kyndra Minchew, Angie Bailey, and Kelli Corner at Southern Illinois Healthcare (SIH) for their invaluable support and guidance throughout the course of this research. We are also grateful to the staff and faculty of Southern Illinois University Carbondale for their essential administrative and logistical assistance.

Conflicts of Interest

The authors declare no conflict of interest.

Abbreviations

The following abbreviations are used in this manuscript:
OTCOver-the-counter

References

  1. Abbott, F.V.; Fraser, M.I. Use and abuse of over-the-counter analgesic agents. J. Psychiatry Neurosci. 1998, 23, 13. [Google Scholar] [PubMed]
  2. Rikard, S.M.; Strahan, A.E.; Schmit, K.M.; Guy, G.P., Jr. Chronic Pain Among Adults—United States, 2019–2021. MMWR Morb. Mortal. Wkly. Rep. 2023, 72, 379–385. [Google Scholar] [CrossRef] [PubMed]
  3. Zis, P.; Daskalaki, A.; Bountouni, I.; Sykioti, P.; Varrassi, G.; Paladini, A. Depression and chronic pain in the elderly: Links and management challenges. Clin. Interv. Aging 2017, 12, 709–720. [Google Scholar] [CrossRef] [PubMed]
  4. Khalid, S.; Sambamoorthi, U.; Umer, A.; Lilly, C.L.; Gross, D.K.; Innes, K.E. Increased odds of incident Alzheimer’s disease and related dementias in presence of common non-cancer chronic pain conditions in Appalachian older adults. J. Aging Health 2022, 34, 158–172. [Google Scholar] [CrossRef] [PubMed]
  5. NIH. Interagency Pain Research Coordinating Committee. Available online: https://www.iprcc.nih.gov/about/nih-iprcc (accessed on 5 April 2025).
  6. Ditre, J.W.; Zale, E.L.; LaRowe, L.R. A reciprocal model of pain and substance use: Transdiagnostic considerations, clinical implications, and future directions. Annu. Rev. Clin. Psychol. 2019, 15, 503–528. [Google Scholar] [CrossRef]
  7. Hooten, W.M. Chronic Pain and Mental Health Disorders: Shared Neural Mechanisms, Epidemiology, and Treatment. Mayo Clin. Proc. 2016, 91, 955–970. [Google Scholar] [CrossRef] [PubMed]
  8. Coherent market Insights. Over-the-Counter (OTC) Analgesics Market to Reach US$ 39.74 Billion by 2030, Says Coherent Market. Available online: https://www.globenewswire.com/news-release/2023/06/23/2693711/0/en/Over-the-Counter-OTC-Analgesics-Market-to-Reach-US-39-74-Billion-by-2030-Says-Coherent-Market-Insights.html (accessed on 5 April 2025).
  9. Agley, J.; Gassman, R.; YoussefAgha, A.; Jun, M.; Torabi, M.; Jayawardene, W. Examining sequences of adolescent substance use initiation involving over-the-counter (OTC) drug abuse. J. Child. Adolesc. Subst. Abus. 2015, 24, 212–219. [Google Scholar] [CrossRef]
  10. Perrot, S.; Cittée, J.; Louis, P.; Quentin, B.; Robert, C.; Milon, J.Y.; Bismut, H.; Baumelou, A. Self-medication in pain management: The state of the art of pharmacists’ role for optimal Over-The-Counter analgesic use. Eur. J. Pain. 2019, 23, 1747–1762. [Google Scholar] [CrossRef]
  11. Nahin, R.; Feinberg, T.; Kapos, F.; Terman, G. Estimated rates of incident and persistent chronic pain among US adults, 2019–2020. JAMA Netw. Open 2023, 6, e2313563. [Google Scholar] [CrossRef]
  12. Devraj, R.; Herndon, C.M.; Griffin, J. Pain awareness and medication knowledge: A health literacy evaluation. J. Pain. Palliat. Care Pharmacother. 2013, 27, 19–27. [Google Scholar] [CrossRef]
  13. Dunford, E.K.; Miles, D.R.; Popkin, B.M. Exploring disparities in the proportion of ultra-processed foods and beverages purchased in grocery stores by US households in 2020. Public Health Nutr. 2025, 28, e85. [Google Scholar] [CrossRef] [PubMed]
  14. Kilts Center for Marketing. NielsenIQ Research Data. Available online: https://www.chicagobooth.edu/research/kilts/research-data/nielseniq (accessed on 5 April 2025).
  15. Barker, A.R.; Mazzucca, S.; An, R. The Impact of Sugar-Sweetened Beverage Taxes by Household Income: A Multi-City Comparison of Nielsen Purchasing Data. Nutrients 2022, 14, 922. [Google Scholar] [CrossRef] [PubMed]
  16. Kumbalatara, C.; Jayawardene, W. Relationship between dieting and fasting practices and alcohol expenses in U.S. households: An analysis of nielsen-kilts consumer panel and ailment data. In Proceedings of the APHA 2024 Annual Meeting and Expo, Minneapolis, MN, USA, 27–30 October 2024. [Google Scholar]
  17. Wickham, H.; Fronois, F.R.; Henry, L.; Müller, K.; Vaughan, D. dplyr: A Grammar of Data Manipulation, R package version 1.1.4. 2023. Available online: https://cran.r-project.org/web/packages/dplyr/index.html (accessed on 5 April 2025).
  18. R Core Team. R: A Language and Environment for Statistical Computing. Available online: https://www.R-project.org/ (accessed on 13 January 2025).
  19. Hester, J.; Wickham, H.; Bryan, J. Vroom: Read and Write Rectangular Text Data Quickly, R. package version 1.6.5. 2021; Volume 1. [CrossRef]
  20. Massey, F.J., Jr. The Kolmogorov-Smirnov test for goodness of fit. J. Am. Stat. Assoc. 1951, 46, 68–78. [Google Scholar] [CrossRef]
  21. D’agostino, R.; Pearson, E.S. Tests for departure from normality. Empirical results for the distributions of b 2 and√ b. Biometrika 1973, 60, 613–622. [Google Scholar] [CrossRef]
  22. Kruskal, W.H.; Wallis, W.A. Use of ranks in one-criterion variance analysis. J. Am. Stat. Assoc. 1952, 47, 583–621. [Google Scholar] [CrossRef]
  23. Dunn, O.J. Multiple comparisons using rank sums. Technometrics 1964, 6, 241–252. [Google Scholar] [CrossRef]
  24. Holm, S. A simple sequentially rejective multiple test procedure. Scand. J. Stat. 1979, 6, 65–70. [Google Scholar]
  25. Pearson, K.X. On the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling. Lond. Edinb. Dublin Philos. Mag. J. Sci. 1900, 50, 157–175. [Google Scholar] [CrossRef]
  26. Robinson, R.G. Pain relief for headaches. Is self-medication a problem? Can. Fam. Physician 1993, 39, 867–868, 871–872. [Google Scholar]
  27. Ahmed, F. Headache disorders: Differentiating and managing the common subtypes. Br. J. Pain. 2012, 6, 124–132. [Google Scholar] [CrossRef]
  28. Smitherman, T.A.; Burch, R.; Sheikh, H.; Loder, E. The Prevalence, Impact, and Treatment of Migraine and Severe Headaches in the U nited S tates: A Review of Statistics From National Surveillance Studies. Headache J. Head. Face Pain. 2013, 53, 427–436. [Google Scholar] [CrossRef] [PubMed]
  29. Figueiras, A.; Caamano, F.; Gestal-Otero, J.J. Sociodemographic factors related to self-medication in Spain. Eur. J. Epidemiol. 2000, 16, 19–26. [Google Scholar] [CrossRef]
  30. Hughes, C.M.; McElnay, J.C.; Fleming, G.F. Benefits and risks of self medication. Drug Saf. 2001, 24, 1027–1037. [Google Scholar] [CrossRef] [PubMed]
  31. Tesfaye, Z.T.; Ergena, A.E.; Yimer, B.T. Self-medication among medical and nonmedical students at the University of Gondar, Northwest Ethiopia: A cross-sectional study. Scientifica 2020, 2020, 4021586. [Google Scholar] [CrossRef] [PubMed]
  32. Unruh, A.M. Gender variations in clinical pain experience. Pain 1996, 65, 123–167. [Google Scholar] [CrossRef]
  33. Amatya, E.; Fois, R.; Williams, K.A.; Pont, L.G. Potential for detection of Safety signals for Over-the-counter Medicines using National ADR spontaneous Reporting Data: The Example of OTC NSAID-Associated gastrointestinal bleeding. Pharmacy 2020, 8, 174. [Google Scholar] [CrossRef] [PubMed]
  34. Nazaryan, L.; Barseghyan, A.; Rayisyan, M.; Beglaryan, M.; Simonyan, M. Evaluating consumer self-medication practices, pharmaceutical care services, and pharmacy selection: A quantitative study. BMC Health Serv. Res. 2024, 24, 10. [Google Scholar] [CrossRef] [PubMed]
  35. Carrillo, M.; Yingst, J.; Tuan, W.J.; Giampetro, D.; Nyland, J.E.; Zgierska, A.E. Problems accessing pain care, and the adverse outcomes among adults with chronic pain: A cross-sectional survey study. Pain. Manag. 2025, 15, 81–91. [Google Scholar] [CrossRef]
  36. Rains, J.C.; Penzien, D.B.; McCrory, D.C.; Gray, R.N. Behavioral headache treatment: History, review of the empirical literature, and methodological critique. Headache J. Head. Face Pain. 2005, 45, S92–S109. [Google Scholar] [CrossRef]
Table 1. Demographics and health characteristics of household members by gender.
Table 1. Demographics and health characteristics of household members by gender.
CharacteristicMale
N (%) or
Mean (SD)		Female
N (%)
Mean (SD)
Household members (count)27,568 (44.92%)33,584 (54.72%)
Age in years for a household member *49.39 (22.76)52.14 (21.10)
Household members reported no ailments19,226 (31.33%)18,574 (30.26%)
Household members reported any other ailment4623 (7.53%)7296 (11.89%)
Household members reported any pain-related ailment5180 (8.44%)11,222 (18.28%)
The values represented are counts (N) and percentages (%) within parentheses. The gender is not specified as male or female for 0.36% of household members, and it is not mentioned for any characteristics due to the smaller percentage. * The values represented are the mean and standard deviation within parentheses.
Table 2. Household members and household statistics by reported pain conditions.
Table 2. Household members and household statistics by reported pain conditions.
AilmentPercentage of Households
(N = 28,608)		Percentage of Household Members
(N = 61,375)		Percentage of Female (%)Age of a Household Member
Mean (SD)
Arthritis14.428.2266.3467.55 (10.24)
Cancer3.781.8454.7766.59 (11.00)
Tension headache7.634.2473.3552.76 (15.08)
Migraine7.573.9879.7551.12 (15.16)
Joint/neck/back12.917.5458.1660.40 (13.94)
Menopause7.603.6299.4256.52 (8.08)
Musculoskeletal8.144.6469.3560.50 (13.42)
Other ailments33.1273.8161.2359.20 (15.24)
Not reported39.2561.8748.9145.47 (23.76)
Total--54.7250.82 (21.94)
A household can have more than one household member; therefore, a given household can have more than one ailment, resulting in total percentages not summing to 100%. A household member can report more than one ailment; therefore, the total percentages does not equal 100%.
Table 3. Household annual expenditures on OTC painkillers by pain condition category.
Table 3. Household annual expenditures on OTC painkillers by pain condition category.
Painkiller
Category		All (N = 20,331)
M (IQR) [HH%]		No Ailment
(N = 7341)
M (IQR) [HH%]		Pain-Related Ailment
(N = 9796)
M (IQR) [HH%]		Any Other Ailment
(N = 3194)
M (IQR)
[HH%]		p-ValuePost Hoc
For analgesics13.52 (19.85) [41.32%]12.50 (17.32) [38.77%]14.27 (21.46) [43.06%]13.98 (21.16)
[41.86%]		<0.001No ailment < pain ailment, any other ailment
For alkalizers5.99 (5.92) [2.33%]5.78 (7.55) [2.18%]5.78 (6.04) [2.34%]8.02 (5.48)
[2.66%]		0.0767-
For arthritis13.99 (18.76) [9.69%]13.79 (17.96) [7.53%]14.82 (19.41) [11.05%]13.88 (17.91)
[10.49%]		0.119-
For back/leg11.97 (17.72) [3.47%]11.97 (18.66) [2.98%]11.96 (16.40) [3.65%]12.52 (17.50)
[4.04%]		0.517-
Pediatric liquids9.49 (9.35) [6.31%]9.39 (10.48) [7.59%]9.49 (8.66) [4.96%]9.74 (9.29)
[7.48%]		0.549-
For headache15.93 (23.84) [85.90%]14.36 (20.85) [84.66%]17.17 (26.04) [86.78%]15.99 (24.40)
[86.07%]		<0.001No ailment < pain ailment, any other ailment
For menstruation5.98 (5.63) [1.46%]5.98 (5.32) [1.21%]5.98 (6.42) [1.61%]5.86 (6.37)
[1.57%]		0.659-
For UTI8.99 (8.69) [3.33%]9.39 (10.08) [2.63%]8.73 (6.30) [3.50%]8.99 (8.81)
[4.41%]		0.315-
Total21.58 (34.68)
-		18.72 (29.57)
-		23.66 (37.69)
-		22.58 (38.69)
-		<0.001No ailment < pain ailment, any other ailment
M: median; IQR: interquartile range; HH: household; and N: number of households in the group. The median and interquartile range represent the annual expenses per household for OTC painkillers, expressed in USD. The p-values are associated with the Kruskal–Wallis test conducted to compare the medians among groups with no ailment, pain-related ailments, and other ailments (Households who reported both pain-related and non-pain-related ailments were excluded). Dunn’s test is employed as a post hoc analysis to identify group differences using a Bonferroni adjustment at a significance level of 5%. A household could purchase more than one OTC painkiller; therefore, the total percentages do not equal 100% for all households by OTC painkiller category.
Table 4. OTC painkiller purchases for households with only one household member who reports a single pain-related ailment or any other one ailment (N = 1962) and no ailment (N = 3819).
Table 4. OTC painkiller purchases for households with only one household member who reports a single pain-related ailment or any other one ailment (N = 1962) and no ailment (N = 3819).
OTC Painkiller
Category		ArthritisCancerTension HeadacheMigraineJoint/Neck/
Back		MenopauseMusculoskeletalOther AilmentsNo Ailment
For analgesics30.87%23.33%21.97%21.24%30.77%21.48%33.33%17.39%21.68%
For alkalizers0.78%2.50%0.00%2.65%0.45%0.00%0.00%1.45%1.26%
For arthritis13.49%4.17%8.33%5.31%5.88%5.93%10.56%5.80%4.32%
For back/leg2.08%3.33%0.76%0.88%0.90%1.48%2.78%1.45%1.75%
Pediatric liquids1.04%0.83%3.79%0.00%0.68%2.22%1.67%1.45%1.23%
For headache57.07%45.83%57.58%49.56%58.14%59.26%61.67%59.42%48.89%
For menstruation0.13%0.00%0.76%1.77%0.45%0.74%1.67%0.00%0.42%
For UTI1.56%2.50%1.52%1.77%2.26%3.70%1.67%1.45%1.47%
* No purchases30.61%43.33%34.09%42.48%33.48%30.37%28.33%34.78%41.97%
Total771120132113442135180693819
The cell values represent the percentage of households (equivalent to the number of household members, as only single-member households are considered) that purchase each specific OTC painkiller, calculated relative to the total number of households reporting the corresponding pain-related ailment. A household can purchase more than one OTC painkiller; therefore, the total percentages do not equal 100% for all households by OTC painkiller category. The total row represents the number of households without duplication for each ailment and no ailment categories. * A separate row for households that do not purchase any OTC painkillers is included for comparison.
Table 5. OTC painkiller for headache purchases for households with only one household member who reported a single pain-related ailment or any other ailment by pain diagnosis.
Table 5. OTC painkiller for headache purchases for households with only one household member who reported a single pain-related ailment or any other ailment by pain diagnosis.
Pain Diagnosis/
Painkiller Purchase		No AilmentPain-Related AilmentAny Other Ailmentp-Value
Self-identified
No purchases 435 (36.99%)15 (36.59%)
For headache 741 (63.01%)26 (63.41%)1.000
Identified by a healthcare professional
No purchases 186 (35.77%)9 (37.50%)
For headache 334 (64.23%)15 (62.50%)0.832
All
No purchases1603 (46.20%)621 (36.62%)24 (36.92%)
For headache1867 (53.80%)1075 (63.38%)41 (63.08%)<0.001
The Chi-squared test was used for comparisons in each category.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Kumbalatara, C.; Cortez, D.; Jayawardene, W. Chronic Pain Conditions and Over-the-Counter Analgesic Purchases in U.S. Households: An Analysis of Nielsen-Kilts Ailment and Consumer Panel Data (2023). Psychoactives 2025, 4, 18. https://doi.org/10.3390/psychoactives4020018

AMA Style

Kumbalatara C, Cortez D, Jayawardene W. Chronic Pain Conditions and Over-the-Counter Analgesic Purchases in U.S. Households: An Analysis of Nielsen-Kilts Ailment and Consumer Panel Data (2023). Psychoactives. 2025; 4(2):18. https://doi.org/10.3390/psychoactives4020018

Chicago/Turabian Style

Kumbalatara, Chesmi, Dollia Cortez, and Wasantha Jayawardene. 2025. "Chronic Pain Conditions and Over-the-Counter Analgesic Purchases in U.S. Households: An Analysis of Nielsen-Kilts Ailment and Consumer Panel Data (2023)" Psychoactives 4, no. 2: 18. https://doi.org/10.3390/psychoactives4020018

APA Style

Kumbalatara, C., Cortez, D., & Jayawardene, W. (2025). Chronic Pain Conditions and Over-the-Counter Analgesic Purchases in U.S. Households: An Analysis of Nielsen-Kilts Ailment and Consumer Panel Data (2023). Psychoactives, 4(2), 18. https://doi.org/10.3390/psychoactives4020018

Article Metrics

Back to TopTop