0
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Association between multisite musculoskeletal pain and disability trajectories among community-dwelling older adults

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Pain is linked to disability, but how multisite musculoskeletal pain leads to disability over time is not well elaborated.

          Objective

          To examine the associations of multisite musculoskeletal pain with disability among a nationally representative cohort.

          Design

          We used data from the National Health and Aging Trends Study (NHATS) 2015-22. Disability was assessed by basic activities of daily living (ADL) and instrumental activities of daily living (IADL).

          Participants

          A total of 5557 individuals with multisite musculoskeletal pain dwelling in the community were included in this study.

          Methods

          Group-based trajectory models were applied to identify distinct profiles of disability in ADL and IADL. Design-based logistic regressions were used to examine associations among multisite musculoskeletal pain, disability, and dual trajectory group memberships, adjusted for sociodemographic, health status, behavioral, and mental characteristics.

          Results

          Persons who experienced multisite musculoskeletal pain were at higher risk of disability in ADL and IADL. We identified five heterogeneous disability trajectories and named them based on baseline levels and rates of increase over time. Approximately, 52.42% of older adults with multisite musculoskeletal pain were in trajectories with ADL and IADL declines, and 33.60% experienced a rapid decline. Multisite musculoskeletal pain was associated with elevated relative risk for the adverse disability trajectories, which generally increases with multisite musculoskeletal pain frequency and number of sites.

          Conclusions

          Persons with multisite musculoskeletal pain had a higher risk of disability. It is essential to adopt effective pain management strategies to maintain the independent living ability of older adults and to realize active aging.

          Supplementary Information

          The online version contains supplementary material available at 10.1007/s40520-024-02764-0.

          Key Points

          • Persons with multisite musculoskeletal pain were at higher risk of disability.

          • There is a dose-response correlation of disability with pain frequency and the number of sites.

          • We studied a nationally representative sample of 5557 individuals with multisite musculoskeletal pain dwelling in the community.

          Supplementary Information

          The online version contains supplementary material available at 10.1007/s40520-024-02764-0.

          Related collections

          Most cited references36

          • Record: found
          • Abstract: found
          • Article: not found

          The Patient Health Questionnaire-2: validity of a two-item depression screener.

          A number of self-administered questionnaires are available for assessing depression severity, including the 9-item Patient Health Questionnaire depression module (PHQ-9). Because even briefer measures might be desirable for use in busy clinical settings or as part of comprehensive health questionnaires, we evaluated a 2-item version of the PHQ depression module, the PHQ-2. The PHQ-2 inquires about the frequency of depressed mood and anhedonia over the past 2 weeks, scoring each as 0 ("not at all") to 3 ("nearly every day"). The PHQ-2 was completed by 6000 patients in 8 primary care clinics and 7 obstetrics-gynecology clinics. Construct validity was assessed using the 20-item Short-Form General Health Survey, self-reported sick days and clinic visits, and symptom-related difficulty. Criterion validity was assessed against an independent structured mental health professional (MHP) interview in a sample of 580 patients. As PHQ-2 depression severity increased from 0 to 6, there was a substantial decrease in functional status on all 6 SF-20 subscales. Also, symptom-related difficulty, sick days, and healthcare utilization increased. Using the MHP reinterview as the criterion standard, a PHQ-2 score > or =3 had a sensitivity of 83% and a specificity of 92% for major depression. Likelihood ratio and receiver operator characteristic analysis identified a PHQ-2 score of 3 as the optimal cutpoint for screening purposes. Results were similar in the primary care and obstetrics-gynecology samples. The construct and criterion validity of the PHQ-2 make it an attractive measure for depression screening.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            Prevalence of Chronic Pain and High-Impact Chronic Pain Among Adults — United States, 2016

            Chronic pain, one of the most common reasons adults seek medical care ( 1 ), has been linked to restrictions in mobility and daily activities ( 2 , 3 ), dependence on opioids ( 4 ), anxiety and depression ( 2 ), and poor perceived health or reduced quality of life ( 2 , 3 ). Population-based estimates of chronic pain among U.S. adults range from 11% to 40% ( 5 ), with considerable population subgroup variation. As a result, the 2016 National Pain Strategy called for more precise prevalence estimates of chronic pain and high-impact chronic pain (i.e., chronic pain that frequently limits life or work activities) to reliably establish the prevalence of chronic pain and aid in the development and implementation of population-wide pain interventions ( 5 ). National estimates of high-impact chronic pain can help differentiate persons with limitations in major life domains, including work, social, recreational, and self-care activities from those who maintain normal life activities despite chronic pain, providing a better understanding of the population in need of pain services. To estimate the prevalence of chronic pain and high-impact chronic pain in the United States, CDC analyzed 2016 National Health Interview Survey (NHIS) data. An estimated 20.4% (50.0 million) of U.S. adults had chronic pain and 8.0% of U.S. adults (19.6 million) had high-impact chronic pain, with higher prevalences of both chronic pain and high-impact chronic pain reported among women, older adults, previously but not currently employed adults, adults living in poverty, adults with public health insurance, and rural residents. These findings could be used to target pain management interventions. NHIS is a cross-sectional, in-person, household health survey of the civilian noninstitutionalized U.S. population, conducted by the National Center for Health Statistics (NCHS).* Data from the 2016 Sample Adult Core for adults aged ≥18 years (33,028; response rate = 54.3%) † were analyzed. Information about pain was collected through responses to the following questions: “In the past six months, how often did you have pain? Would you say never, some days, most days, or every day?” and “Over the past six months, how often did pain limit your life or work activities? Would you say never, some days, most days, or every day?” Chronic pain was defined as pain on most days or every day in the past 6 months, as recommended by the International Association for the Study of Pain, § modified to account for intermittent pain, and used in both the National Pain Strategy and National Institutes of Health Task Force on Chronic Back Pain ( 6 ). As suggested in the National Pain Strategy, high-impact chronic pain was defined as chronic pain that limited life or work activities on most days or every day during the past 6 months ( 5 ). The prevalence of chronic pain and high-impact chronic pain (both crude and age-adjusted, with 95% confidence intervals) were estimated for the U.S. adult population overall and by various sociodemographic characteristics. These characteristics, collected with the Family Core questionnaire, included age, sex, race/ethnicity, education level, current employment status, ¶ poverty status (calculated using NHIS imputed income files),** veteran status, health insurance coverage type (reported separately for adults aged <65 and ≥65 years), and urbanicity. All prevalence estimates met NCHS reliability standards. †† Because pain prevalence varies by age, age-adjusted estimates were used in comparisons of chronic pain and high-impact chronic pain between subgroups. Based on two-tailed Z-tests, all reported differences between subgroups are statistically significant (unless otherwise noted; p<0.05). Analyses were conducted using statistical software that accounts for the stratification and clustering of households in the NHIS sampling design. Estimates incorporated the final sample adult weights adjusted for nonresponse and calibrated to population control totals to enable generalization to the civilian noninstitutionalized population aged ≥18 years. In 2016, an estimated 20.4% of U.S. adults (50.0 million) had chronic pain and 8.0% of U.S. adults (19.6 million) had high-impact chronic pain (Table), with higher prevalence associated with advancing age. Age-adjusted prevalences of both chronic pain and high-impact chronic pain were significantly higher among women, adults who had worked previously but were not currently employed, adults living in or near poverty, and rural residents. In addition, the age-adjusted prevalences of chronic pain and high-impact chronic pain were significantly lower among adults with at least a bachelor’s degree compared with all other education levels. TABLE Prevalence of chronic pain* and high impact chronic pain † among U.S. adults aged ≥18 years, by sociodemographic characteristics—National Health Interview Survey, 2016 Characteristic Chronic pain* High-impact chronic pain† Estimated no.§ Crude
% (95% CI) Age-adjusted¶
% (95% CI) Estimated no.§ Crude
% (95% CI) Age-adjusted¶
% (95% CI) Total 50,009,000 20.4 (19.7–21.0) 19.4 (18.7–20.0) 19,611,000 8.0 (7.6–8.4) 7.5 (7.1–7.9) Age group (yrs) 18–24 2,082,000 7.0 (5.8–8.5) —** 446,000 1.5 (0.9–2.3) —** 25–44 11,042,000 13.2 (12.3–14.1) —** 3,681,000 4.4 (3.9–5.0) —** 45–64 23,269,000 27.8 (26.6–29.0) —** 10,044,000 12.0 (11.2–12.9) —** 65–84 11,808,000 27.6 (26.4–29.0) —** 4,578,000 10.7 (9.9–11.6) —** ≥85 1,766,000 33.6 (30.1–37.3) —** 830,000 15.8 (13.2–18.9) —** Sex Male 21,989,000 18.6 (17.7–19.5) 17.8 (17.0–18.7) 8,276,000 7.0 (6.5–7.6) 6.7 (6.2–7.3) Female 28,049,000 22.1 (21.2–23.0) 20.8 (19.9–21.6) 11,296,000 8.9 (8.4–9.4) 8.2 (7.7–8.7) Race/Ethnicity Hispanic 5,856,000 15.1 (13.6–16.7) 16.7 (15.2–18.4) 2,754,000 7.1 (6.0–8.3) 7.9 (6.9–9.2) White, non-Hispanic 36,226,000 23.0 (22.2–23.8) 21.0 (20.3–21.8) 13,230,000 8.4 (7.9–8.9) 7.4 (7.0–7.9) Black, non-Hispanic 5,148,000 17.9 (16.4–19.6) 17.8 (16.3–19.4) 2,387,000 8.3 (7.2–9.4) 8.1 (7.1–9.2) Other, non-Hispanic†† 2,774,000 13.8 (12.1–15.7) 14.4 (12.7–16.3) 1,326,000 6.6 (5.3–8.1) 7.0 (5.7–8.5) Education Less than high school 7,809,000 26.1 (24.2–28.2) 23.7 (21.7–25.7) 4,069,000 13.6 (12.3–15.2) 12.1 (10.7–13.7) High school/GED 14,441,000 23.7 (22.5–25.0) 22.6 (21.2–23.9) 5,910,000 9.7 (9.0–10.6) 9.1 (8.4–10.0) Some college 17,129,000 22.6 (21.5–23.8) 22.9 (21.8–24.0) 6,518,000 8.6 (7.9–9.4) 8.7 (8.0–9.5) Bachelor's degree or higher 10,383,000 13.4 (12.6–14.3) 12.4 (11.7–13.3) 2,944,000 3.8 (3.4–4.3) 3.5 (3.1–4.0) Employment status Employed 22,085,000 14.7 (14.1–15.5) 14.5 (13.8–15.2) 5,108,000 3.4 (3.1–3.8) 3.2 (2.9–3.6) Not employed; worked previously 25,737,000 31.5 (30.3–32.7) 29.2 (27.8–30.6) 13,318,000 16.3 (15.4–17.2) 16.1 (15.0–17.3) Not employed; never worked 2,083,000 15.9 (13.8–18.2) 18.7 (16.1–21.6) 1,192,000 9.1 (7.6–10.9) 11.1 (9.1–13.4) Poverty status <100% FPL 8,017,000 25.8 (24.2–27.6) 29.6 (27.9–31.3) 4,630,000 14.9 (13.6–16.4) 17.5 (16.1–19.0) 100% ≤FPL<200% 11,357,000 26.2 (24.5–27.9) 25.9 (24.2–27.7) 5,375,000 12.4 (11.3–13.6) 12.3 (11.2–13.5) 200% ≤FPL<400% 14,181,000 20.3 (19.2–21.4) 19.3 (18.3–20.4) 5,100,000 7.3 (6.7–8.1) 6.9 (6.2–7.6) ≥400% FPL 16,441,000 16.3 (15.4–17.2) 14.6 (13.8–15.5) 4,438,000 4.4 (4.0–4.9) 3.9 (3.5–4.4) Veteran Yes 6,379,000 29.1 (27.1–31.2) 26.0 (23.5–28.7) 2,258,000 10.3 (9.1–11.8) 9.2 (7.7–11.1) No 43,519,000 19.5 (18.9–20.2) 19.0 (18.4–19.7) 17,407,000 7.8 (7.4–8.2) 7.5 (7.1–7.9) Health insurance coverage§§ Age <65 yrs Private 20,539,000 15.1 (14.3–15.8) 14.0 (13.3–14.8) 5,713,000 4.2 (3.8–4.7) 3.8 (3.4–4.2) Medicaid and other public coverage 8,215,000 29.3 (27.3–31.5) 30.0 (28.0–32.2) 4,822,000 17.2 (15.6–19.0) 17.8 (16.2–19.6) Other 3,860,000 43.5 (40.0–47.2) 34.8 (31.2–38.7) 2,263,000 25.5 (22.5–28.8) 19.3 (16.4–22.5) Uninsured 3,683,000 16.2 (14.4–18.2) 17.0 (15.2–19.0) 1,319,000 5.8 (4.7–7.2) 6.2 (5.0–7.6) Age ≥65 yrs Private 5,606,000 28.0 (26.3–29.9) 28.1 (26.3–30.0) 1,842,000 9.2 (8.1–10.5) 9.3 (8.2–10.6) Medicare and Medicaid 1,428,000 42.5 (37.6–47.5) 42.5 (37.6–47.5) 816,000 24.3 (20.4–28.6) 24.3 (20.4–28.6) Medicare Advantage 3,094,000 25.5 (23.1–28.1) 25.8 (23.4–28.4) 1,226,000 10.1 (8.5–11.8) 10.3 (8.7–12.1) Medicare only, excluding Medicare Advantage 2,115,000 25.9 (23.1–28.9) 25.9 (23.1–28.9) 939,000 11.5 (9.5–13.7) 11.5 (9.5–13.7) Other 1,229,000 31.6 (27.2–36.3) 31.8 (27.4–36.5) 545,000 14.0 (11.3–17.3) 14.3 (11.5–17.7) Uninsured 106,000 —¶¶ —¶¶ 59,000 —¶¶ —¶¶ Urbanicity*** Urban 38,401,000 19.0 (18.3–19.7) 18.4 (17.7–19.0) 14,754,000 7.3 (6.9–7.8) 7.0 (6.6–7.4) Rural 11,575,000 26.9 (25.4–28.5) 24.0 (22.5–25.6) 4,776,000 11.1 (10.2–12.2) 9.8 (8.8–10.9) Abbreviations: CI = confidence interval; FPL = federal poverty level; GED = General Educational Development certification. * Pain on most days or every day in the past 6 months. † Chronic pain limiting life or work activities on most days or every day in the past 6 months. § The estimated numbers, rounded to 1,000s, were annualized based on the 2016 data. Counts for adults of unknown status (responses coded as “refused,” “don’t know,” or “not ascertained”) with respect to chronic pain and high-impact chronic pain are not shown separately in the table, nor are they included in the calculation of percentages (as part of either the denominator or the numerator), to provide a more straightforward presentation of the data. ¶ Estimates are age-adjusted using the projected 2000 U.S. population as the standard population and five age groups: 18–29, 30–39, 40–49, 50–59, and ≥60 years. ** Not applicable. †† Non-Hispanic other includes non-Hispanic American Indian and Alaska Native only, non-Hispanic Asian only, non-Hispanic Native Hawaiian and Pacific Islander only, and non-Hispanic multiple race. §§ Based on a hierarchy of mutually exclusive categories. Adults reporting both private and Medicare Advantage coverage were assigned to the Medicare Advantage category. “Uninsured” includes adults who had no coverage as well as those who had only Indian Health Service coverage or had only a private plan that paid for one type of service such as accidents or dental care. “Other” comprises military health care including TRICARE, VA, and CHAMP-VA, and certain types of local and state governmental coverage, not including the Children’s Health Insurance Program. ¶¶ Estimates are considered unreliable according to the National Center for Health Statistics’ standards of reliability. *** Based on U.S. Census Bureau definitions of urban and rural areas (https://www2.census.gov/geo/pdfs/reference/ua/Defining_Rural.pdf). Whereas non-Hispanic white adults had a significantly higher age-adjusted prevalence of chronic pain than did all other racial and ethnic subgroups, no significant differences in high-impact chronic pain prevalence by race/ethnicity were observed. Similarly, the age-adjusted prevalence of chronic pain was significantly higher among veterans than among nonveterans, but no significant difference was observed in the prevalence of high-impact chronic pain. Among adults aged <65 years, the age-adjusted prevalences of chronic pain and high-impact chronic pain were higher among those with Medicaid and other public health care coverage or other insurance (e.g., Veteran’s Administration, certain local and state government) than among adults with private insurance or those who were uninsured. Among adults aged ≥65 years, those with both Medicare and Medicaid had higher age-adjusted prevalences of chronic pain and high-impact chronic pain than did adults with all other types of coverage. Discussion Pain is a component of many chronic conditions, and chronic pain is emerging as a health concern on its own, with negative consequences to individual persons, their families, and society as a whole ( 4 , 5 ). Healthy People 2020 (https://www.healthypeople.gov/), the nation’s science-based health objectives, has a developmental objective to “decrease the prevalence of adults having high-impact chronic pain.” This analysis extends previous national studies of chronic pain prevalence by identifying adults with high-impact chronic pain. In 2016, approximately 20% of U.S. adults had chronic pain (approximately 50 million), and 8% of U.S. adults (approximately 20 million) had high-impact chronic pain. This estimate of high-impact chronic pain is similar to or slightly lower than estimates reported in the few studies that have looked at pain using a similar construct. For example, a recent study that used a measure of high-impact chronic pain similar to the one used in this study reported an estimate of 13.7% among a sample of U.S. adult health plan enrollees ( 7 ). Similarly, a 2001 study of adults from a region in Scotland found that 14.1% of survey participants reported significant chronic pain, and 6.3% reported severe chronic pain, and a 2001 study of Australian adults reported that 11.0% of men and 13.5% of women reported chronic pain that interfered, to some degree, with daily life activities ( 3 , 8 ). The results of subgroup analyses in the current study were consistent with findings in these studies ( 3 , 8 ) insofar as the prevalence of high-impact chronic pain was higher among women, adults who had achieved lower levels of education, and those who were not employed at the time of the survey, and was lower among adults with private health insurance compared with public and other types of coverage. In addition, high-impact chronic pain was also found to be higher among adults living in poverty and among rural residents. Socioeconomic status appears to be a common factor in many of the subgroup differences in high-impact chronic pain prevalence reported here. Indicators of socioeconomic status such as education, poverty, and health insurance coverage have been determined to be associated with both general health status and the presence of specific health conditions ( 9 ) as well as with patients’ success in navigating the health care system ( 9 ). Identifying populations at risk is necessary to inform efforts for developing and targeting quality pain services. The findings in this report are subject to at least five limitations. First, data are self-reported and subject to recall bias. Second, data are cross-sectional, precluding drawing causal inferences. This might be particularly relevant for socioeconomic status, which can be both a risk factor for and a consequence of chronic pain or high-impact chronic pain, or both. Third, no information is available on treatment for chronic pain to assess the prevalence of chronic pain and high-impact chronic pain among those with and without treatment. Fourth, NHIS excludes important populations, such as active duty military and residents of long-term care facilities or prisons. And finally, NHIS does not collect data on chronic pain or high-impact chronic pain in children. Despite these limitations, three strengths of this study are that it used a large, nationally representative data source to produce estimates of chronic pain and high-impact chronic pain across many demographic subgroups, it used standard broad definitions of pain that were not limited to one or more specific health conditions (e.g., headache or arthritis), and it used the standard case definition for high-impact chronic pain proposed by the National Pain Strategy. Chronic pain contributes to an estimated $560 billion each year in direct medical costs, lost productivity, and disability programs ( 4 ). The National Pain Strategy, which is the first national effort to transform how the population burden of pain is perceived, assessed, and treated, recognizes the need for better data to inform action and calls for estimates of chronic pain and high-impact chronic pain in the general population ( 5 ). This report helps fulfill this objective and provides data to inform policymakers, clinicians, and researchers focused on pain care and prevention. Summary What is already known about this topic? Chronic pain has been linked to numerous physical and mental conditions and contributes to high health care costs and lost productivity. A limited number of studies estimate that the prevalence of chronic pain ranges from 11% to 40%. What is added by this report? In 2016, an estimated 20.4% of U.S. adults had chronic pain and 8.0% of U.S. adults had high-impact chronic pain. Both were more prevalent among adults living in poverty, adults with less than a high school education, and adults with public health insurance. What are the implications for public health practice? This report helps fulfill a National Pain Strategy objective of producing more precise estimates of chronic pain and high-impact chronic pain.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Group-based trajectory modeling in clinical research.

              Group-based trajectory models are increasingly being applied in clinical research to map the developmental course of symptoms and assess heterogeneity in response to clinical interventions. In this review, we provide a nontechnical overview of group-based trajectory and growth mixture modeling alongside a sampling of how these models have been applied in clinical research. We discuss the challenges associated with the application of both types of group-based models and propose a set of preliminary guidelines for applied researchers to follow when reporting model results. Future directions in group-based modeling applications are discussed, including the use of trajectory models to facilitate causal inference when random assignment to treatment condition is not possible.
                Bookmark

                Author and article information

                Contributors
                xiaomei.cong@yale.edu
                shangshaomei@126.com
                Journal
                Aging Clin Exp Res
                Aging Clin Exp Res
                Aging Clinical and Experimental Research
                Springer International Publishing (Cham )
                1594-0667
                1720-8319
                23 May 2024
                23 May 2024
                2024
                : 36
                : 1
                : 115
                Affiliations
                [1 ]School of Nursing, Peking University, ( https://ror.org/02v51f717) 38 Xueyuan Road, Haidian District, Beijing, 100191 China
                [2 ]Nursing Department, Peking University Third Hospital, ( https://ror.org/04wwqze12) 49 North Garden Road, Haidian District, Beijing, 100191 China
                [3 ]School of Nursing, Yale University, ( https://ror.org/03v76x132) 400 West Campus Drive, Orange, Connecticut 06477 USA
                Article
                2764
                10.1007/s40520-024-02764-0
                11116213
                38780859
                c68c6614-72da-49d1-af0f-19fe6d9cfcab
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 8 January 2024
                : 22 April 2024
                Funding
                Funded by: National Natural Science Foundation of China
                Award ID: 82102661 and 81972158
                Award ID: 82102661 and 81972158
                Funded by: Peking University Third Hospital Key Project
                Award ID: BYSYRCYJ2024003
                Categories
                Original Article
                Custom metadata
                © Springer Nature Switzerland AG 2024

                multisite musculoskeletal pain,disability,activities of daily living,group-based trajectory models,older adults

                Comments

                Comment on this article