Intersectional Differences in Health Care Outcomes among Patients with Musculoskeletal Disorders in Germany
1
Health Services Research, Faculty of Health, School of Medicine, Witten/Herdecke University, 58455 Witten, Germany
2
Department of Epidemiology and International Public Health, School of Public Health, Bielefeld University, 33615 Bielefeld, Germany
3
Department of Nursing and Health Services Research, School of Public Health, Bielefeld University, 33615 Bielefeld, Germany
*
Author to whom correspondence should be addressed.
Reports 2023, 6(2), 20; https://doi.org/10.3390/reports6020020
Submission received: 13 February 2023
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Revised: 11 April 2023
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Accepted: 23 April 2023
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Published: 29 April 2023
Abstract
:In all regions of the world, musculoskeletal disorders are a significant contributor to the burden of chronic illnesses. The effectiveness of treatments, such as rehabilitation, may vary intersectionally across demographic and other categories. The present study examines this intersectionality with respect to a lack of improvement in health conditions after rehabilitation of patients in Germany. Routine data from 298,617 patients aged 18–65 years residing in Germany who received rehabilitation because of arthropathies, dorsopathies, or soft tissue disorders during 2006–2016 were included in the analysis. Odds of the outcome were compared across demographic groups and across diagnostic sub-groups by means of multivariable logistic regression. Interaction terms were included to examine intersectional differences across these groups and over time. Women were more likely than men to have an impairment despite treatment (adjusted odds ratio [aOR] = 1.11; 95%-CI = 1.08, 1.13). In addition, patients in semi-skilled/unskilled employment were at higher odds of a poor outcome compared to patients in skilled positions (aOR = 1.13; 95%-CI = 1.10–1.17). Nationality also affected health care outcomes, with Turkish nationals and nationals from a Yugoslav successor state having higher odds of a poor outcome than Germans (aOR = 1.56; 95%-CI = 1.45–1.67 and aOR = 1.52; 95%-CI = 1.41–1.65, respectively). The findings highlight the importance of an intersectional perspective in health research and practice and can support the development of strategies and measures that aim to reduce disparities in health care.
1. Introduction
Musculoskeletal disorders are becoming a more prominent factor in the increasing burden of chronic illnesses in all parts of the world. They lead to significant direct and indirect costs, as a result of lost productivity, disability retirement, and higher healthcare expenses associated with continuous medical treatment and rehabilitation. These conditions, which affect the muscles, bones, and joints, can range from common conditions like osteoarthritis to more rare and complex conditions such as systemic lupus erythematosus [1]. They often result in chronic pain, reduced mobility, and decreased quality of life, and can significantly affect an individual’s ability to work and participate in daily activities [2].
In Germany, annually, there are approximately 1.8 million hospital cases recorded for musculoskeletal conditions, which account for over 10% of the total direct healthcare costs [3]. Rehabilitation and other tertiary preventive services may contribute to preventing disability and early retirement related to musculoskeletal conditions and to promoting return to work [4]. However, the effectiveness of these services may differ based on various demographic factors, including sex, socioeconomic status, and immigration status, resulting in disparities in health care outcomes [5,6]. In addition, it is important to investigate potential intersectional variations across these groups given that determinants can also interact with each other (intersectionality) [7].
To better meet the needs of an increasingly heterogeneous population, providers of health care strive to offer services that better address the specific requirements of diverse patients [8,9]. Diversity-sensitive care can help to take into account the diversity of needs and expectations of patients by providing necessary conditions at the personnel and organizational level. It offers advantages in everyday care for patients by improving care and increasing health care satisfaction as well as for staff by reducing the workload through systemization and optimization processes [10].
It remains unclear how effective these initiatives are, and it is not yet clear whether they help to reduce existing disparities in healthcare outcomes. Building on our own previous work [11], the aim of the present study was to offer empirical evidence from Germany and to investigate the effectiveness of rehabilitation in patients diagnosed with arthropathies, dorsopathies, and soft tissue disorders, specifically examining outcomes across diverse demographic and socioeconomic categories. The results of this research can inform clinical practice and guide further investigations, potentially contributing to the development of targeted strategies aimed at addressing existing disparities in health care. Additionally, the findings may suggest potential opportunities to reduce costs for health care systems across Europe and beyond.
2. Materials and Methods
2.1. Data
For the analysis, a 10% random sample of data on rehabilitation among patients of working age (18–65 years) residing in Germany who underwent rehabilitation because of arthropathies (M00-M25), dorsopathies (M40-M54), or soft tissue disorders (M60-M79) between 2006 and 2016, was used. The data was provided by the German Federal Pension Insurance (Deutsche Rentenversicherung), which is responsible for insurance coverage of all employees who are required to pay social insurance contributions. As far as rehabilitation is concerned, the agency covers treatment (usually in the form of inpatient programs at specialized hospitals) for patients of working age (and cancer patients, irrespective of age), which makes up about two-thirds of all rehabilitations provided in the country annually [12,13].
2.2. Variables
The outcome of the study was the improvement in health condition (yes, no) after rehabilitation which was based on an evaluation at the time of discharge [14]. The evaluation was conducted by physicians as part of a medical discharge summary for each patient who completes rehabilitation and is recorded as one item.
We compared the outcome between age (in years), sex (male, female), socioeconomic (SES) and nationality groups (Germany, Turkey, a Yugoslav successor state, Portugal/Spain/Italy/Greece, other) by means of multivariable logistic regression (since we were only able to take nationality into account, immigrants who have acquired German citizenship, in the present study, are included in the nationality group “Germany”). As proxies for SES, the type of employment (full-time, part-time, unemployed, not applicable), the type of occupation (manual [e.g., carpenters and mechanics], services, technical/professional, administrative, other) and occupational position (skilled labor, semi-skilled/unskilled labor, trainee/unemployed) were considered. All analyses were also adjusted for marital status, region of treatment and region of residence (both referring to the 16 Federal states in Germany). In addition, as a proxy for health status the time absent from work due to illness in the last 12 months was included.
2.3. Analysis
To examine the relationship of the aforementioned variables and the outcome of rehabilitation descriptively, we used chi-square tests for categorical variables and an independent t-test for age. Logistic regression was used to examine factors associated with improvement or no improvement in health condition after rehabilitation by means of multivariable analysis. Adjusted odds ratios (aOR) with 95% confidence intervals (95%-CI) were used as effects estimates. Temporal trends in disparities and trends across demographic/socioeconomic groups as well as across the three diagnostic sub-groups were examined by means of interaction terms included in the model. We used average marginal effects (AME) to examine multiplicative interaction effects, given that unobserved heterogeneity may bias the evaluation of interaction terms based on odds ratios [15]. Analyses were conducted by means of Stata 16.
3. Results
Data on 298,617 cases were available for those who received treatment between 2006 and 2016. Of these, 50.8% were male. The mean age was 50.3 years. About 15% of patients experienced no improvement of their underlying condition after rehabilitation (Table 1). Women had higher odds of having an impairment despite treatment (adjusted odds ratio [aOR] = 1.11; 95%-CI = 1.08–1.13). In addition, patients in semi-skilled/unskilled employment had higher odds of having a poor outcome compared to those in skilled positions (aOR = 1.13; 95%-CI = 1.10–1.17). Nationality was significantly associated with the outcome of treatment, with Turkish nationals and nationals of a Yugoslav successor state having higher odds for a poor outcome than Germans (aOR = 1.56; 95%-CI = 1.45–1.67 and aOR = 1.52; 95%-CI = 1.41–1.65, respectively) (Table 2). The year patients underwent rehabilitation was not associated with disparities in treatment outcomes.
However, differences between males and females were larger for soft tissue disorders than for arthropathies and dorsopathies and decreased with age (Figure 1, top). Similarly, differences in treatment outcomes between patients who worked as trainees or were unemployed, in part, decreased with age, while differences between non-Germans and Germans increased with age (Figure 1, bottom). Conversely, these age-related interaction effects also mean that the effect of age varies between men and women, among occupational position groups, as well as between non-Germans and Germans. An exploratory analysis of multiplicative three-way interactions also revealed that for males differences between German nationals on the one hand and nationals from Turkey and a Yugoslav successor state exist for all age groups and tend to increase with age. For females in both groups, differences also increase with age; however, they only become pronounced after the age of 45 (Figure 2).
4. Discussion
Given the significant burden of musculoskeletal conditions, it is essential that individuals have access to effective tertiary preventive and management strategies. Using data from Germany, the present study shows that approximately 15% of all patients who underwent rehabilitation because of arthropathies, dorsopathies, or soft tissue disorders between 2006 and 2016 did not experience improvement in their health conditions after treatment. Poor rehabilitation outcomes may contribute to substantial direct and indirect costs [1]. The present investigation shows that the outcomes of such treatments may vary by different diversity characteristics. It indicates that female sex, a lower occupational position, a Turkish nationality or a nationality related to one of the Yugoslav successor states, and age are factors contributing to a higher chance of impairment despite treatment. Furthermore, the study shows that demographic and socioeconomic factors interact with each other and affect the outcomes intersectionally.
We found that women have a higher chance for poorer treatment outcomes compared to men. Disparities in rehabilitation outcomes by sex and gender have also been reported in previous research. Several studies also show that significant sex disparities exist in rehabilitation referrals. A meta-analysis showed that women were 32% less likely to be referred for cardiovascular treatment than men, despite equal rehabilitation eligibility [16]. Existing data suggest that women have lower adherence and completion rates in rehabilitation and are more likely to withdraw from rehabilitation because of their personal financial or occupational constraints [17]. Previous research also emphasized that psychosocial factors, such as social support and anxiety, also play a greater role in rehabilitation for women than for men [18]. Additionally, the unique gender-related challenges faced by women, such as balancing work and home responsibilities, may contribute to less favorable treatment outcomes [19].
Health disparities related to migration status, ethnicity, or race may also be present in the rehabilitative care setting [20,21,22,23]. In our study, such differences in treatment outcomes could also be observed, with Turkish nationals and nationals from a Yugoslav successor state having higher odds for a poor outcome than Germans. Our findings, in conjunction with previous research [24,25,26], suggest that immigrants face various obstacles within the healthcare system that may impede the delivery of adequate care. These barriers could stem from challenges in communication between patients and healthcare providers, limited knowledge of rehabilitation services, poor health literacy, and inadequate proficiency in the German language [27]. These barriers can hinder health care professionals’ ability to instruct patients on therapies and exercises, and to obtain crucial medical information, potentially diminishing the efficacy of rehabilitation. Aside from these challenges, communication may also be impaired by cultural needs and healthcare expectations that are not adequately addressed by health care professionals, such as illness perceptions related to cultural or religious beliefs [24,28].
Our study also shows that health care outcomes are associated with socioeconomic factors such as employment. This is in line with preceding studies [29,30] and may be explained by numerous challenges to health care and rehabilitation encountered by individuals with low socioeconomic status, such as poor health literacy [29,30,31].
When considering the broader context, our overall findings can be explained by the diversity of health care needs and preferences, thus illustrating the necessity for an intersectional perspective in health care [7]. An important finding from this analysis is that health care disparities are not caused by a single factor, but that many determinants are involved, which in part interact with each other. To address disparities in health care, therefore, the attention of health care facilities and professionals must be focused on multiple aspects. Consequently, only taking into account selected diversity characteristics such as migration status is not sufficient to provide adequate rehabilitative care to all population groups. In order to effectively address the needs of populations, including minorities, it is essential to consider their heterogeneity and to approach them at an individual and intersectional level—both in health research and health care practice [7,32]. What the present study and existing literature illustrate is the complexity of categories and diversity characteristics of patients, which is often insufficiently addressed. In particular, the mutually reinforcing effects of inequalities have not yet been sufficiently acknowledged, and the social determinants of health and characteristics of individual heterogeneous groups have not been adequately included—in either health research or health care practice. First, much of the existing literature, particularly in the field of health promotion and cultural competence, essentializes, for example, nationality or culture at the expense of other factors and barriers. Second, it simplifies different variables and their effects, often due to a lack of representative data that capture the complexity of experiences in minority groups or individuals in general [33].
By taking an intersectionality approach, stakeholders can better understand and address the needs and experiences of health care users, leading to more effective and equitable health care outcomes. In this way, a higher degree of patient centeredness in health care can be attained. Studies show that hospitals and rehabilitation facilities are well aware of the need for diversity-sensitive care. Yet, adequate strategies promoting diversity-sensitive care are rarely used [34,35]. This is largely due to a lack of practical hands-on overviews of suitable instruments that can be consulted for that purpose. A recent project addressed that limitation for rehabilitative care in Germany by developing a manual (‘DiversityKAT’) with tools and recommendations that can assist rehabilitation facilities in the implementation of diversity-sensitive health care approaches [36].
Designing diversity-sensitive health care strategies depends on the unique characteristics, structures, and objectives of health care facilities. These should be identified as part of a thorough needs assessment. Tools and techniques geared towards a diversity-sensitive approach often originate in the corporate world, but many can be adapted for use in the health care sector as well. Fundamental tools include mission statements that are sensitive to diversity, ethical guidelines, and policies that condemn discrimination and disadvantage for any particular population groups and that recognize diversity as a valuable opportunity for the organization. Concrete measures contributing towards diversity-sensitive care, for example, are adequate diversity trainings provided for health care staff. They aim to increase the awareness of staff about the diversity of their colleagues and patients by fostering respective values and attitudes, by promoting self-reflection, and by imparting appropriate skills, for example with respect to cross-cultural communication [10]. Similarly, mentoring programs can be implemented, where new employees are guided by experienced employees to help ease their transitions into the facility [37,38]. Furthermore, increasing diversity awareness in health care facilities can be accomplished through a personnel policy that is sensitive towards diversity, thereby avoiding diversity-related disadvantages in the hiring process and promoting diversity among staff, which again can have benefits in regard to catering to diverse patients. If employees are deployed according to their abilities, interests and available resources, they can better respond to needs and expectations of health care users, thus contributing to the optimization of health care processes. In designing adequate approaches, it is imperative to involve all relevant stakeholders, which do not only comprise health care facilities and insurance companies/health care providers, but also patients and their representing bodies.
The strengths of this study lie in the utilization of reliable and representative routine data, enabling both control for several confounding variables and analysis of trends over a period of ten years. However, it is essential to consider that as the only proxy variable for health status, only information on time of sickness-related absence from work in the year preceding rehabilitation was available. Consequently, residual confounding may exist due to variations in health status before rehabilitation, which could impact disparities in health outcomes among different population groups. Additional information related to rehabilitation, e.g., patients’ initial health status, their attitudes towards treatment, as well as information about the treatment itself (type and number of therapies, etc.), could provide further insights into intersectional differences in health outcomes. Unfortunately, this information was not available in the present study. Another limitation concerns information on migration status. At present, the only feasible way to identify immigrants in routine data from the German Federal Pension Insurance is by their nationality. As a result, immigrants who have acquired German citizenship and who make up more than half of the immigrant population in Germany [39], in the present study were included in the nationality group “Germany”.
5. Conclusions
Musculoskeletal conditions are becoming a larger contributor to the global burden of chronic diseases, causing significant financial impacts in both direct and indirect ways, including lost productivity, early retirement due to disability, and increased healthcare expenses from ongoing care. Effective rehabilitation services make a significant contribution to enhancing patients’ mobility, quality of life, and ability to work, and empowering them in their health maintenance. Outcomes of health care, including rehabilitation, may vary intersectionally across demographic and socioeconomic groups. Previous research suggests that, for example, immigrants face various obstacles within the healthcare system that may impede the delivery of adequate care. The present investigation delivers empirical evidence from Germany and examines outcomes of rehabilitation of arthropathies, dorsopathies, and soft tissue disorders in patients across these categories. By means of nationwide and representative data, it identified several disparities between demographic/socioeconomic groups in health care outcomes over time, some of which also intersectionally overlap with each other. Although some limitations need to be considered, the study shows that differences in health care outcomes do not vary over time, indicating that current approaches implemented by health care providers are not successful in reducing disparities. Formulating effective methods to eliminate disparities in healthcare can also lower expenses for the healthcare system. Future efforts, therefore, must rely on approaches which are not only holistic, systematic, and sensitive to the diversity of health care users, but for which appropriate evaluation studies have been conducted. For this purpose, it is necessary to facilitate the translation of research findings into practice.
Author Contributions
Conceptualization, P.B.; Data curation, P.B.; Formal analysis, P.B.; Investigation, P.B. and K.A.; Methodology, P.B.; Project administration, P.B.; Resources, P.B. and K.A.; Software, P.B.; Supervision, P.B. and Y.Y.-A.; Validation, P.B., K.A. and Y.Y.-A.; Visualization, P.B.; Writing—original draft, P.B. and K.A.; Writing—review & editing, P.B., K.A. and Y.Y.-A. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
The current study utilizes administrative/routine data which fully complies with Germany’s Federal data protection act and adheres to the requirements outlined in the German Social Code. This data is completely anonymous and did not involve any experiments, therefore no further ethical approval was required in accordance with national standards for secondary data analyses in Germany.
Informed Consent Statement
Not applicable, because administrative/routine data is used.
Data Availability Statement
Researchers who meet the eligibility requirements for access to confidential data may obtain the data supporting the findings of this study free of charge from the German Federal Pension Insurance. More information can be found at https://www.eservice-drv.de/FdzPortalWeb/dispcontent.do?id=main_fdz_english (accessed on 26 April 2023).
Conflicts of Interest
The authors declare no conflict of interest.
References
- Hoy, D.G.; Smith, E.; Cross, M.; Sanchez-Riera, L.; Blyth, F.M.; Buchbinder, R.; Woolf, A.D.; Driscoll, T.; Brooks, P.; March, L.M. Reflecting on the global burden of musculoskeletal conditions: Lessons learnt from the global burden of disease 2010 study and the next steps forward. Ann. Rheum. Dis. 2015, 74, 4–7. [Google Scholar] [CrossRef]
- Palazzo, C.; Ravaud, J.F.; Papelard, A.; Ravaud, P.; Poiraudeau, S. The burden of musculoskeletal conditions. PLoS ONE 2014, 9, e90633. [Google Scholar] [CrossRef] [PubMed]
- Federal Statistical Office. Hospital Statistics—Diagnostic Data of the Hospital Patients (Fachserie 12 Reihe 6.2.1); Federal Statistical Office/Statistisches Bundesamt: Wiesbaden, Germany, 2019. [Google Scholar]
- Hammond, A. Rehabilitation in musculoskeletal diseases. Best Pract. Res. Clin. Rheumatol. 2008, 22, 435–449. [Google Scholar] [CrossRef] [PubMed]
- Goodman, S.M.; Parks, M.L.; McHugh, K.; Fields, K.; Smethurst, R.; Figgie, M.P.; Bass, A.R. Disparities in outcomes for African Americans and whites undergoing total knee arthroplasty: A systematic literature review. J. Rheumatol. 2016, 43, 765–770. [Google Scholar] [CrossRef]
- Brzoska, P.; Voigtländer, S.; Spallek, J.; Razum, O. Utilization and effectiveness of medical rehabilitation in foreign nationals residing in Germany. Eur. J. Epidemiol. 2010, 25, 651–660. [Google Scholar] [CrossRef] [PubMed]
- Kelly, U.A. Integrating intersectionality and biomedicine in health disparities research. Adv. Nurs. Sci. 2009, 32, E42–E56. [Google Scholar] [CrossRef] [PubMed]
- Pfannstiel, M.A. State of the Art von Maßnahmen und Instrumenten zum Management der Patienten- und Mitarbeiterdiversität im Krankenhaus. In Dienstleistungsmanagement im Krankenhaus II. Prozesse, Produktivität, Diversität; Bounken, R.B., Pfannstiel, M.A., Reutschl, A.J., Eds.; Springer Gabler: Wiesbaden, Germany, 2014; pp. 381–427. [Google Scholar]
- Truong, M.; Paradies, Y.; Priest, N. Interventions to improve cultural competency in healthcare: A systematic review of reviews. BMC Health Serv. Res. 2014, 14, 99. [Google Scholar] [CrossRef] [PubMed]
- Saha, S.; Beach, M.C.; Cooper, L.A. Patient centeredness, cultural competence and healthcare quality. J. Natl. Med. Assoc. 2008, 100, 1275–1285. [Google Scholar] [CrossRef]
- Brzoska, P.; Yilmaz-Aslan, Y. Trends in health care outcomes among patients with musculoskeletal disorders in Germany undergoing rehabilitation. An intersectionality perspective. In Proceedings of the 14th World Congress of the International Society of Physical and Rehabilitation Medicine, Orlando, FL, USA, 4–9 March 2020. [Google Scholar]
- Bengel, J.; Koch, U. Grundlagen der Rehabilitationswissenschaften: Themen, Strategien und Methoden der Rehabilitationsforschung; Springer: Berlin, Germany, 2000. [Google Scholar]
- Gerdes, N.; Zwingmann, C.; Jäckel, W.H. The system of rehabilitation Germany. In Research in Rehabilitation; Jäckel, W.H., Bengel, J., Herdt, J., Eds.; Schattauer: Stuttgart, Germany, 2006; pp. 3–19. [Google Scholar]
- Deutsche Rentenversicherung Bund. Der Ärztliche Reha-Entlassungsbericht. Leitfaden zum Einheitlichen Entlassungsbericht in der medizinischen Rehabilitation der Gesetzlichen Rentenversicherung 2007; Deutsche Rentenversicherung Bund: Berlin, Germany, 2007. [Google Scholar]
- Tabachnick, B.G.; Fidell, L.S. Using Multivariate Statistics; Pearson: Boston, MA, USA, 2012. [Google Scholar]
- Colella, T.J.; Gravely, S.; Marzolini, S.; Grace, S.L.; Francis, J.A.; Oh, P.; Scott, L.B. Sex bias in referral of women to outpatient cardiac rehabilitation? A meta-analysis. Eur. J. Prev. Cardiol. 2015, 22, 423–441. [Google Scholar] [CrossRef]
- Colbert, J.D.; Martin, B.J.; Haykowsky, M.J.; Hauer, T.L.; Austford, L.D.; Arena, R.A.; Knudtson, M.L.; Meldrum, D.A.; Aggarwal, S.G.; Stone, J.A. Cardiac rehabilitation referral, attendance and mortality in women. Eur. J. Prev. Cardiol. 2015, 22, 979–986. [Google Scholar] [CrossRef]
- Cossette, S.; Maheu-Cadotte, M.A.; Mailhot, T.; Fontaine, G.; Cournoyer, A.; Cournoyer, C.; Guertin, M.C.; Juneau, M. Sex-and gender-related factors associated with cardiac rehabilitation enrollment: A secondary analysis among systematically referred patients. J. Cardiopulm. Rehabil. Prev. 2019, 39, 259–265. [Google Scholar] [CrossRef]
- Supervía, M.; Medina-Inojosa, J.R.; Yeung, C.; Lopez-Jimenez, F.; Squires, R.W.; Pérez-Terzic, C.M.; Brewer, L.C.; Leth, S.E.; Thomas, R.J. Cardiac rehabilitation for women: A systematic review of barriers and solutions. Mayo Clin. Proc. 2017, 92, 565–577. [Google Scholar] [CrossRef]
- Gary, K.W.; Arango-Lasprilla, J.C.; Stevens, L.F. Do racial/ethnic differences exist in post-injury outcomes after TBI? A comprehensive review of the literature. Brain Inj. 2009, 23, 775–789. [Google Scholar] [CrossRef] [PubMed]
- Flores, L.E.; Verduzco-Gutierrez, M.; Molinares, D.; Silver, J.K. Disparities in health care for Hispanic patients in physical medicine and rehabilitation in the United States: A narrative review. Am. J. Phys. Med. Rehabil. 2020, 99, 338–347. [Google Scholar] [CrossRef]
- Castellanos, L.R.; Viramontes, O.; Bains, N.K.; Zepeda, I.A. Disparities in cardiac rehabilitation among individuals from racial and ethnic groups and rural communities—A systematic review. J. Racial Ethn. Health Disparities 2019, 6, 1–11. [Google Scholar] [CrossRef] [PubMed]
- Resurrección, D.M.; Moreno-Peral, P.; Gomez-Herranz, M.; Rubio-Valera, M.; Pastor, L.; Caldas de Almeida, J.M.; Motrico, E. Factors associated with non-participation in and dropout from cardiac rehabilitation programmes: A systematic review of prospective cohort studies. Eur. J. Cardiovasc. Nurs. 2019, 18, 38–47. [Google Scholar] [CrossRef] [PubMed]
- Brzoska, P.; Sauzet, O.; Yilmaz-Aslan, Y.; Widera, T.; Razum, O. Satisfaction with rehabilitative health care services among German and non-German nationals residing in Germany: A cross-sectional study. BMJ Open 2017, 7, e015520. [Google Scholar] [CrossRef] [PubMed]
- Brzoska, P. Disparities in health care outcomes between immigrants and the majority population in Germany: A trend analysis, 2006–2014. PLoS ONE 2018, 13, e0191732. [Google Scholar] [CrossRef]
- Handtke, O.; Schilgen, B.; Mösko, M. Culturally competent healthcare—A scoping review of strategies implemented in healthcare organizations and a model of culturally competent healthcare provision. PLoS ONE 2019, 14, e0219971. [Google Scholar] [CrossRef] [PubMed]
- Berens, E.M.; Vogt, D.; Messer, M.; Hurrelmann, K.; Schaeffer, D. Health literacy among different age groups in Germany: Results of a cross-sectional survey. BMC Public Health 2016, 16, 1151. [Google Scholar] [CrossRef]
- Yilmaz-Aslan, Y.; Brzoska, P.; Bluhm, M.; Aslan, A.; Razum, O. Illness perceptions in Turkish migrants with diabetes: A qualitative study. Chronic Illn. 2014, 10, 107–121. [Google Scholar] [CrossRef]
- Schultz, W.M.; Kelli, H.M.; Lisko, J.C.; Varghese, T.; Shen, J.; Sandesara, P.; Quyyumi, A.A.; Taylor, H.A.; Gulati, M.; Harold, J.G.; et al. Socioeconomic status and cardiovascular outcomes: Challenges and interventions. Circulation 2018, 137, 2166–2178. [Google Scholar] [CrossRef] [PubMed]
- Kangovi, S.; Barg, F.K.; Carter, T.; Levy, K.; Sellman, J.; Long, J.A.; Grande, D. Challenges faced by patients with low socioeconomic status during the post-hospital transition. J. Gen. Intern. Med. 2014, 29, 283–289. [Google Scholar] [CrossRef] [PubMed]
- de Melo Ghisi, G.L.; da Silva Chaves, G.S.L.; Britto, R.R.; Oh, P. Health literacy and coronary artery disease: A systematic review. Patient Educ. Couns. 2018, 101, 177–184. [Google Scholar] [CrossRef]
- Weber, L.; Zambrana, R.E.; Fore, M.E.; Parra-Medina, D. Racial and ethnic health inequities: An intersectional approach. In Handbook of the Sociology of Racial and Ethnic Relations; Springer: Berlin/Heidelberg, Germany, 2018; pp. 133–160. [Google Scholar]
- Koehn, S.; Neysmith, S.; Kobayashi, K.; Khamisa, H. Revealing the shape of knowledge using an intersectionality lens: Results of a scoping review on the health and health care of ethnocultural minority older adults. Ageing Soc. 2013, 33, 437–464. [Google Scholar] [CrossRef]
- Erdsiek, F.; Aksakal, T.; Mader, M.; Idris, M.; Yılmaz-Aslan, Y.; Razum, O.; Brzoska, P. Diversity-sensitive measures in German hospitals—Attitudes, implementation, and barriers according to administration managers. BMC Health Serv. Res. 2022, 22, 689. [Google Scholar] [CrossRef]
- Aksakal, T.; Erdsiek, F.; Yılmaz-Aslan, Y.; Mader, M.; Padberg, D.; Razum, O.; Brzoska, P. Umsetzungsstrategien einer diversitätssensiblen Gesundheitsversorgung und Unternehmensführung—Eine bundesweite postalische Befragung von Rehabilitationseinrichtungen. Die Rehabil. 2022, 62, 40–47. [Google Scholar] [CrossRef] [PubMed]
- Aksakal, T.; Mader, M.; Annac, K.; Erdsiek, F.; Korn, M.; Padberg, D.; Idris, M.; Yilmaz-Aslan, Y.; Razum, O.; Brzoska, P. Entwicklung eines Instrumentenkatalogs und Handlungsleitfadens für Rehabilitationseinrichtungen und Rehabilitationsträger zur Umsetzung einer diversitätssensiblen Versorgung (DiversityKAT). Abschlussbericht. Universität Witten/Herdecke sowie Universität Bielefeld. 2021. Available online: https://www.deutsche-rentenversicherung.de/SharedDocs/Downloads/DE/Experten/reha_forschung/forschungsprojekte/abschlussbericht_diversitykat.pdf (accessed on 26 April 2023).
- Latham, C.L.; Hogan, M.; Ringl, K. Nurses supporting nurses: Creating a mentoring program for staff nurses to improve the workforce environment. Nurs. Adm. Q. 2008, 32, 27–39. [Google Scholar] [CrossRef] [PubMed]
- Hayward, L.M.; Canali, A.; Hill, A. Interdisciplinary peer mentoring: A model for developing culturally competent health care professionals. J. Phys. Ther. Educ. 2005, 19, 28–40. [Google Scholar] [CrossRef]
- Statistisches Bundesamt. Bevölkerung und Erwerbstätigkeit. Bevölkerung mit Migrationshintergrund. Ergebnisse des Mikrozensus 2021 (Fachserie 1 Reihe 2.2); Statistisches Bundesamt: Wiesbaden, Germany, 2022. [Google Scholar]
Figure 1.
Predicted probability of a lack of improvement in health condition after rehabilitation by different interacting categories. Multivariable logistic regression model with two-way interaction terms (10% random sample of all individuals residing in Germany who underwent rehabilitation because of arthropathies, dorsopathies or soft tissue disorders during 2006–2016, n = 298,617). Note: For purposes of visualization, a small offset between the groups is used in the graphs to better illustrate overlapping confidence intervals.
Figure 1.
Predicted probability of a lack of improvement in health condition after rehabilitation by different interacting categories. Multivariable logistic regression model with two-way interaction terms (10% random sample of all individuals residing in Germany who underwent rehabilitation because of arthropathies, dorsopathies or soft tissue disorders during 2006–2016, n = 298,617). Note: For purposes of visualization, a small offset between the groups is used in the graphs to better illustrate overlapping confidence intervals.
Figure 2.
Predicted probability of a lack of improvement in health condition after rehabilitation by age, nationality and sex. Multivariable logistic regression model with a three-way interaction term (10% random sample of all individuals residing in Germany who underwent rehabilitation because of arthropathies, dorsopathies, or soft tissue disorders during 2006–2016, n = 298,617). Note: For purposes of visualization, a small offset between the groups is used in the graphs to better illustrate overlapping confidence intervals.
Figure 2.
Predicted probability of a lack of improvement in health condition after rehabilitation by age, nationality and sex. Multivariable logistic regression model with a three-way interaction term (10% random sample of all individuals residing in Germany who underwent rehabilitation because of arthropathies, dorsopathies, or soft tissue disorders during 2006–2016, n = 298,617). Note: For purposes of visualization, a small offset between the groups is used in the graphs to better illustrate overlapping confidence intervals.
Table 1.
Sample description by treatment outcome (10% random sample of all individuals residing in Germany who underwent rehabilitation because of arthropathies [ICD-10 M00-M25], dorsopathies [ICD-10 M40-M54], or soft tissue disorders [ICD-10 M60-M79] during 2006–2016, n = 298,617).
Table 1.
Sample description by treatment outcome (10% random sample of all individuals residing in Germany who underwent rehabilitation because of arthropathies [ICD-10 M00-M25], dorsopathies [ICD-10 M40-M54], or soft tissue disorders [ICD-10 M60-M79] during 2006–2016, n = 298,617).
| Improvement in Health Condition after Rehabilitation (n, %) | Total | p-Value | ||
|---|---|---|---|---|
| Yes | No | |||
| Sex (n, %) | <0.01 | |||
| Male | 129,345 (51.0%) | 22,392 (49.7%) | 151,737 (50.8%) | |
| Female | 124,213 (49.0%) | 22,667 (50.3%) | 146,880 (49.2%) | |
| Age (mean, sd) | 50.3 (8.8) | 50.2 (8.8) | 50.3 (8.8) | <0.01 |
| Nationality (n, %) | <0.01 | |||
| Germany | 238,324 (94.0%) | 41,348 (91.8%) | 279,672 (93.7%) | |
| Portugal/Spain/Italy/Greece | 2931 (1.2%) | 649 (1.4%) | 3580 (1.2%) | |
| Yugoslav successor state | 3022 (1.2%) | 826 (1.8%) | 3848 (1.3%) | |
| Turkey | 3369 (1.3%) | 1080 (2.4%) | 4449 (1.5%) | |
| Other | 5912 (2.3%) | 1156 (2.6%) | 7068 (2.4%) | |
| Occupational position (n, %) | <0.01 | |||
| Skilled labor | 191,032 (75.3%) | 32,128 (71.3%) | 223,160 (74.7%) | |
| Semi-skilled/unskilled labor | 46,228 (18.2%) | 10,179 (22.6%) | 56,407 (18.9%) | |
| Trainee/unemployed | 16,298 (6.4%) | 2752 (6.1%) | 19,050 (6.4%) | |
| Type of employment (n, %) | <0.01 | |||
| Fulltime | 174,270 (68.7%) | 29,691 (65.9%) | 203,961 (68.3%) | |
| Part-time | 43,267 (17.1%) | 7883 (17.5%) | 51,150 (17.1%) | |
| Unemployed | 16,046 (6.3%) | 4201 (9.3%) | 20,247 (6.8%) | |
| Other | 19,975 (7.9%) | 3284 (7.3%) | 23,259 (7.8%) | |
| Occupation (n, %) | <0.01 | |||
| Manual | 76,993 (30.4%) | 14,299 (31.7%) | 91,292 (30.6%) | |
| Services | 59,649 (23.5%) | 11,437 (25.4%) | 71,086 (23.8%) | |
| Technical/professional | 38,746 (15.3%) | 6495 (14.4%) | 45,241 (15.2%) | |
| Administrative | 40,963 (16.2%) | 6922 (15.4%) | 47,885 (16.0%) | |
| Other | 37,207 (14.7%) | 5906 (13.1%) | 43,113 (14.4%) | |
| Diagnosis (n, %) | <0.01 | |||
| Arthropathies | 62,033 (24.5%) | 9823 (21.8%) | 71,856 (24.1%) | |
| Dorsopathies | 173,488 (68.4%) | 31,354 (69.6%) | 204,842 (68.6%) | |
| Soft tissue disorders | 18,037 (7.1%) | 3882 (8.6%) | 21,919 (7.3%) | |
| Marital status (n, %) | <0.01 | |||
| Not married | 74,411 (29.3%) | 14,157 (31.4%) | 88,568 (29.7%) | |
| Married | 175,055 (69.0%) | 30,183 (67.0%) | 205,238 (68.7%) | |
| Other | 4092 (1.6%) | 719 (1.6%) | 4811 (1.6%) | |
| Time absent from work in the last 12 months (n, %) | <0.01 | |||
| None | 37,724 (14.9%) | 5675 (12.6%) | 43,399 (14.5%) | |
| <3 months | 141,324 (55.7%) | 17,990 (39.9%) | 159,314 (53.4%) | |
| 3–6 months | 37,581 (14.8%) | 8704 (19.3%) | 46,285 (15.5%) | |
| 6+ months | 28,893 (11.4%) | 11,460 (25.4%) | 40,353 (13.5%) | |
| Not employed | 8036 (3.2%) | 1230 (2.7%) | 9266 (3.1%) | |
Note. sd: standard deviation.
Table 2.
Results of the multivariable logistic regression models with no improvement in health condition after rehabilitation as the dependent variable. Adjusted odds ratios (aOR), adjusted average marginal effects (aAMR), and their respective 95% confidence intervals [95%-CI] (10% random sample of all individuals residing in Germany who underwent rehabilitation because of arthropathies [ICD-10 M00-M25], dorsopathies [ICD-10 M40-M54] or soft tissue disorders [ICD-10 M60-M79] during 2006–2016, n = 298,617).
Table 2.
Results of the multivariable logistic regression models with no improvement in health condition after rehabilitation as the dependent variable. Adjusted odds ratios (aOR), adjusted average marginal effects (aAMR), and their respective 95% confidence intervals [95%-CI] (10% random sample of all individuals residing in Germany who underwent rehabilitation because of arthropathies [ICD-10 M00-M25], dorsopathies [ICD-10 M40-M54] or soft tissue disorders [ICD-10 M60-M79] during 2006–2016, n = 298,617).
| Independent Variable 1 | aOR 2 | 95%-CI | aAME 2 | 95%-CI | ||
|---|---|---|---|---|---|---|
| Sex (Ref.: Male) | ||||||
| Female | 1.11 | 1.08 | 1.13 | 0.012 | 0.009 | 0.016 |
| Age (in years) | 1.002 | 1.001 | 1.003 | 0.0003 | 0.0001 | 0.0004 |
| Nationality (Ref.: Germany) | ||||||
| Portugal/Spain/Italy/Greece | 1.22 | 1.12 | 1.33 | 0.026 | 0.014 | 0.038 |
| Yugoslav successor state | 1.53 | 1.41 | 1.65 | 0.059 | 0.046 | 0.072 |
| Turkey | 1.56 | 1.45 | 1.68 | 0.062 | 0.051 | 0.074 |
| Other | 1.07 | 1.00 | 1.14 | 0.008 | 0.000 | 0.017 |
| Occupational position (Ref: Skilled labor) | ||||||
| Semi-skilled/unskilled labor | 1.13 | 1.10 | 1.17 | 0.016 | 0.013 | 0.020 |
| Trainee/unemployed | 1.03 | 0.96 | 1.10 | 0.003 | −0.005 | 0.012 |
| Type of employment (Ref.: Full time) | ||||||
| Part-time | 1.04 | 1.01 | 1.08 | 0.005 | 0.001 | 0.009 |
| Unemployed | 1.30 | 1.25 | 1.35 | 0.034 | 0.029 | 0.040 |
| Other | 1.01 | 0.95 | 1.07 | 0.001 | −0.006 | 0.008 |
| Occupation (Ref.: Manufacturing) | ||||||
| Services | 1.00 | 0.97 | 1.03 | 0.000 | −0.004 | 0.003 |
| Technical/professional | 0.96 | 0.93 | 1.00 | −0.004 | −0.009 | 0.000 |
| Administrative | 0.96 | 0.93 | 1.00 | −0.005 | −0.009 | 0.000 |
| Other | 0.92 | 0.89 | 0.96 | −0.010 | −0.014 | −0.006 |
| Diagnosis (Ref: Skeletal system) | ||||||
| Dorsopathies | 1.17 | 1.14 | 1.20 | 0.019 | 0.016 | 0.022 |
| Soft tissue disorders | 1.20 | 1.15 | 1.25 | 0.022 | 0.017 | 0.027 |
| Significant interaction effects (p < 0.05) | ||||||
| Sex by diagnostic group | ||||||
| Arthropathies, female vs. male | 0.0000 | −0.0042 | 0.0061 | |||
| Dorsopathies, female vs. male | 0.0110 | 0.0084 | 0.0155 | |||
| Soft tissue, female vs. male | 0.0530 | 0.0438 | 0.0623 | |||
| Age by sex | ||||||
| Male, age | 0.0010 | 0.0005 | 0.0008 | |||
| Female, age | −0.0002 | −0.0004 | 0.00003 | |||
| Age by occupational group | ||||||
| Skilled labor, age | 0.0005 | 0.0003 | 0.0006 | |||
| Semi-skilled/unskilled labor, age | 0.0004 | 0.0001 | 0.0008 | |||
| Trainee/unemployed, age | −0.0014 | −0.0019 | −0.0010 | |||
| Age by nationality | ||||||
| Germany, age | 0.0002 | 0.0001 | 0.0004 | |||
| Portugal/Spain/Italy/Greece, age | 0.0008 | −0.0006 | 0.0022 | |||
| Yugoslav successor state, age | 0.0017 | 0.0004 | 0.0030 | |||
| Turkey, age | 0.0020 | 0.0006 | 0.0033 | |||
| Other, age | −0.0001 | −0.0010 | 0.0008 | |||
Note. 1 Main effects have been calculated based on a main effects model with no interaction effects included. Interaction effects have been calculated based on a main effects model with interaction effects. 2 Odds ratio (aOR) and average marginal effects (aAME) are adjusted for the variables displayed in the tables as well as for marital status, region of residence, region of treatment and the time absent from work due to illness in the last 12 months.
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Brzoska, P.; Annac, K.; Yilmaz-Aslan, Y. Intersectional Differences in Health Care Outcomes among Patients with Musculoskeletal Disorders in Germany. Reports 2023, 6, 20. https://doi.org/10.3390/reports6020020
AMA Style
Brzoska P, Annac K, Yilmaz-Aslan Y. Intersectional Differences in Health Care Outcomes among Patients with Musculoskeletal Disorders in Germany. Reports. 2023; 6(2):20. https://doi.org/10.3390/reports6020020
Chicago/Turabian StyleBrzoska, Patrick, Kübra Annac, and Yüce Yilmaz-Aslan. 2023. "Intersectional Differences in Health Care Outcomes among Patients with Musculoskeletal Disorders in Germany" Reports 6, no. 2: 20. https://doi.org/10.3390/reports6020020
APA StyleBrzoska, P., Annac, K., & Yilmaz-Aslan, Y. (2023). Intersectional Differences in Health Care Outcomes among Patients with Musculoskeletal Disorders in Germany. Reports, 6(2), 20. https://doi.org/10.3390/reports6020020
