Next Article in Journal
Safety and Efficacy of a First-Line Chemotherapy Tailored by G8 Score in Elderly Metastatic or Locally Advanced Gastric and Gastro-Esophageal Cancer Patients: A Real-World Analysis
Previous Article in Journal
Key Factors and AI-Based Risk Prediction of Malnutrition in Hospitalized Older Women
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Geriatrics
Volume 7
Issue 5
10.3390/geriatrics7050106
geriatrics-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 thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Number of Chronic Medical Conditions and Quality of Life of Ethnic Minority Older Adults

by
Sharon Cobb
1,*,
Babak Najand
2,
Tara Gravidez
1,
Berlin Navarro
1,
Alondra Herreraramos
1 and
Mohsen Bazargan
2,3,4,5
1
Mervyn M. Dymally School of Nursing, Charles R Drew University of Medicine and Science, Los Angeles, CA 90059, USA
2
Marginalization-Related Diminished Returns (MDRs) Research Center, Los Angeles, CA 90059, USA
3
Department of Family Medicine, Charles R Drew University of Medicine and Science, Los Angeles, CA 90059, USA
4
Department of Urban Public Health, Charles R Drew University of Medicine and Science, Los Angeles, CA 90059, USA
5
Department of Family Medicine, University of California Los Angeles (UCLA), Los Angeles, CA 90095, USA
*
Author to whom correspondence should be addressed.
Geriatrics 2022, 7(5), 106; https://doi.org/10.3390/geriatrics7050106
Submission received: 18 August 2022 / Revised: 21 September 2022 / Accepted: 25 September 2022 / Published: 29 September 2022
(This article belongs to the Topic Mental Health Issues and Quality of Life in Older Individuals)
Versions Notes

Abstract

:
Background: The Blacks’ mental health paradox is defined as disproportionately better mental health among Black individuals compared to White individuals, despite their higher exposure to a wide range of adversities. However, the existing literature on this phenomenon is mainly limited to studies that have compared Black and White individuals. There has been little research on this phenomenon among ethnic groups other than Whites. Objectives: This study tested the Blacks’ mental health paradox with consideration of Latinx individuals as the control group. Methods: This cross-sectional study collected demographic data, socioeconomic status, chronic medical conditions, and mental and physical quality of life of 724 older Black and Latinx adults residing in low socioeconomic areas of south Los Angeles. Linear regressions were used for data analysis with mental and physical health-related quality of life (HRQoL) as dependent variables and the number of chronic medical conditions as the independent variable. Results: Overall, a higher number of chronic medical conditions was associated with lower mental and physical quality of life. A statistically significant interaction was found between race/ethnicity and the effect of the number of chronic medical conditions on mental HRQoL, which was indicative of Blacks’ mental health paradox. Conclusion: Older Black adults with a higher number of chronic medical conditions report better mental health compared to their Latinx peers with the same number of chronic medical conditions. Thus, Blacks’ mental health paradox can be seen when Black and Latinx populations are compared. Replication of such a paradox provides additional support for the relative mental health advantage of Black people compared to other ethnic groups.

1. Background

Poor physical health (e.g., multimorbidity) is associated with lower health-related quality of life (HRQoL) [1,2]. Individuals with specific types of chronic medical conditions, such as heart disease, cancer, asthma, and arthritis, are more likely to be depressed and report lower health-related quality of life (HRQoL) [3]. Several national and local studies in community [3] and clinical [4] settings in adults and older adults have shown that a high number of chronic medical conditions is a risk factor for poor mental health and well-being (e.g., HRQoL) [3].
The association between the number of chronic medical conditions and poorer mental well-being [5,6,7] may, however, vary by race/ethnicity [8,9,10,11,12,13,14,15]. This is in part because different populations utilize various coping mechanisms to deal with adversities, as some groups may have higher preparedness to face a new adversity or access to resources (e.g., healthcare) [16]. Some studies suggest that the link between chronic medical conditions and mental well-being may be weaker for Black individuals compared to White individuals [8,9,10,11,12,13,14,15]. However, most available comparative studies have exclusively compared Black and White individuals. Thus, we are unaware of any comparative studies of Black people that have included a non-White control group (e.g., Latinx).
The Blacks’ mental health paradox refers to the superior mental well-being of Black populations, despite their higher prevalence of adversities and chronic medical conditions. This phenomenon reflects the relative resilience of Black populations, and particularly of older adults. Various scholars have attributed this observation to growth and flourishing in the presence of adversity. However, it is unknown whether this paradox will hold true if we compare Black individuals with other ethnic groups (other than Whites). In a low-income community with majority Black and Latinx populations [17,18,19], the current study tested the Blacks’ mental health paradox with inclusion of Latinx individuals as the control group. Replication of the Blacks’ mental health paradox with Latinx individuals as a control group would suggest that Blacks’ mental health paradox is a stable and robust phenomenon which holds regardless of the control group (at least for Latinx individuals).

2. Methods

This cross-sectional study was conducted between the years 2015 to 2020 in areas of low socioeconomic status in South Los Angeles. Participants were recruited from low-income housing, churches, and other community venues within this communal environment. Participants were sampled in a non-randomized setting and all participants were individually interviewed with a healthcare provider in their location, which was convenient and maintained confidentiality. All participants resided in Service Planning Area 6 (SPA 6) of South Los Angeles, which is one of the most impoverished areas of Los Angeles, with most residents identifying as Black or Latinx [20]. In SPA6, 61% were Latino, 34% were Black, 3% were White and 2% were Asian/Other [19]. All participants had at least one chronic medical condition and were aged sixty-five or older. For more information on the methodology of this study, please see our previous publications [21,22,23,24,25]. The sample size included 724 individuals (116 Latinx and 608 Black).
This study collected data on demographic factors, including race/ethnicity, age, sex/gender, socioeconomic status (education, etc.), living condition, insurance status, physical health, and mental and physical HRQoL. A Latinx interviewer, who was MD MPH and bilingual, conducted the interviews. The 12-Item Short Form Survey (SF-12) assessed mental and physical HRQoL [26,27]. The SF-12 is one of the most widely used measures of quality of life. It has high validity and reliability with low burden to the patients and individuals, which reduces their fatigue [28]. Thus, the SF-12 generates mental and physical quality of life scores, with higher scores reflecting better well-being [29,30]. Chronic medical conditions (CMCs) included: (1) stomach or intestinal problems; (2) asthma or bronchitis; (3) arthritis; (4) hypertension/high blood pressure; (5) heart diseases; (6) diabetes; (7) chronic back pain; (8) cancer; (9) endocrine conditions and thyroid problems; (10) stroke; and (11) migraine/headache. The number of CMCs was measured by asking whether participants have been diagnosed with the conditions listed above [21,22,23,24,25].

3. Data Analysis

Data analysis was performed using the Statistical Package for Social Sciences (SPSS), version 22 (SPSS Inc., Chicago, IL, USA). In order, univariate, bivariate, and multivariable statistical methods were used for data analysis. For univariate analysis, we reported frequencies (percentages) for categorical variables and means and standard deviations for continuous measures. For bivariate analysis, chi-square tests and independent samples t-tests were employed in order to explore associations between race/ethnicity and study variables. Finally, we used linear regressions to test the overall association between our independent variable, namely, the number of chronic medical conditions, and our outcomes, namely, physical or mental quality of life. All confounders were controlled in our linear regression model. We used the “Enter” rather than the “Forward” or “Backward” method, meaning that independent and confounding variables remained in the model even if they were not statistically significant. As both independent and dependent variables were continuous, a beta was our measure of effect size, and a negative number was indicative of the effect of number of chronic medical conditions on physical or mental quality of life. In order to test racial/ethnic variation in this association, we included an interaction term, which was the multiplicative effect of ethnicity and the number of chronic medical conditions. Latinx was coded as one and non-Latinx as zero.

4. Results

This study included 724 individuals, with 116 identifying as Latinx and 608 as Black. Table 1 shows the results of univariate analysis overall and by ethnicity. This table also shows differences between ethnic groups in terms of demographic data, SES, number of chronic medical conditions, and physical and mental quality of life. Compared to Latinx participants, Black participants had higher ages and education levels, better HRQoL, and a higher number of chronic medical conditions. The groups did not differ in gender or insurance.
Table 2 shows the overall bivariate correlation. This table shows an inverse association between the number of chronic medical conditions and physical and mental HRQoL.
Table 3 and Table 4 show the linear regression results with physical or mental HRQoL as the outcome, demographic data and SES as covariates, and the number of chronic medical conditions as the independent variable. These models are employed overall in both the absence and presence of ethnicity by the interaction term, which was the number of chronic medical conditions. Overall, a higher number of chronic medical conditions was associated with lower mental and physical HRQoL of participants in the overall population. We documented a statistically significant interaction between race/ethnicity and the number of chronic medical conditions on mental, but not physical, HRQoL.

5. Discussion

This study revealed an inverse association between a higher number of chronic medical conditions and worse physical and mental HRQoL. While the association between the number of chronic medical conditions and physical HRQoL was similar in Black and Latinx individuals, we found an interaction which was suggestive of Blacks’ mental health paradox, which is defined as better mental well-being among the Black population despite their overall higher number of chronic medical conditions [8,9,10,11,12,13,14,15].
The finding that a higher number of chronic medical conditions is associated with worse physical and mental HRQoL is well-documented, as mental and physical aspects of health tend to covary [5,6,7]. Moreover, being diagnosed with a chronic condition lowers physical and mental HRQoL, regardless of the type of condition [5,6,7]. This association is reported for many chronic diseases, including but not limited to cardiovascular [31], renal [14], gastrointestinal [32], and respiratory conditions [33]. These chronic conditions impose limitations on activities of daily living [34], and may cause depression [35] and disability [36]. Additionally, chronic conditions may cause fatigue [37], pain [38], and other disabling symptoms [39]. Fear of death may impact well-being of individuals with medical conditions [40]. Other aspects of well-being, such as sleep, sexuality, mobility, and socialization, which all have inverse effects on individuals’ HRQoL, may also be limited [41]. As a result, the number of chronic medical conditions an individual has, regardless of their type or severity, is a risk factor for low HRQoL. Across various chronic conditions, however, chronic renal disease may have the highest impact on depression, and cardiovascular conditions may have the highest impact on anxiety [2].
As shown in this study, the Blacks’ mental health paradox holds even when we compare Black and Latinx individuals. This study is unique because it extends what we know from Black–White differences to more diverse ethnic groups. This is an interesting finding, as the Blacks’ mental health paradox has been validated frequently, but only for comparison of Black and White controls [42,43,44]. As all of these studies have only recruited Black and White individuals [8,9,10,11,12,13,14,15], less is known about any similar differences between Black and Latinx individuals. Despite chronic medical conditions being risk factors for poor mental well-being, Black individuals with chronic conditions report better mental HRQoL. This means that chronic medical conditions do not similarly result in the same degree of poor mental well-being for Black, White, and Latinx individuals [8,9,10,11,12,13,14,15]. As the impact of the number of chronic medical conditions on mental quality of life is greater for Latinx individuals, Black individuals with multiple chronic medical conditions maintain good mental well-being. The same, however, cannot be said for physical quality of life.
As mentioned before, this phenomenon has already been shown for Black–White comparisons [8,9,10,11,12,13,14,15]. In cross-sectional and longitudinal studies, associations between the number of chronic medical conditions and poor mental health are shown to be stronger for White individuals than Black individuals [8,9,10,11,12,13,14,15]. In one study that followed participants for 25 years, bidirectional effects of depression and chronic disease and disability were mainly present for White but absent for Black individuals [45]. In another study that also followed participants for 25 years, emergence of the Black–White mental and physical health paradox was observed over time [17]. As these comparative studies have only recruited Black and White individuals, we were not aware of any comparative study of Black and other non-White control group. This is why this study makes a unique and major contribution to the literature.
We propose three explanations for our observed racial/ethnic variation. First, this phenomenon can be interpreted as a relative resilience of Black populations, particularly older Black adults, compared to other groups. Keyes and colleagues [18] have argued that this phenomenon may reflect preparedness of Black people in facing adversity. Mezuk, Jackson, and colleagues [16] argue that Black individuals are more prepared than other groups to negate some effects of depression by lowering their stress through behavioral risks such as consuming an unhealthy diet [46]. Jackson and Mezuk [16] have proposed than Black people may use some unhealthy behaviors to maintain their mental health; however, some contrasting results are also shown [47]. It may be inferred that Black individuals, who have faced long histories of institutionalized and structural racism and discrimination, have learned to cope with adversity and access to fewer resources [48,49]. The second explanation for this phenomenon is that the mental wellness of Black individuals may imply a smaller effect of chronic diseases, due to the larger impact of of sociodemographic factors and other adversities [50]. This aligns with the theory of minorities’ diminished returns, suggesting that similar resources may not result in similar outcomes for marginalized and privileged groups, because marginalized people face more discrimination, stress, and racism in their lives [51,52,53]. In other words, racism, discrimination, stress, and low SES may be detrimental for Black people, regardless of their chronic disease status [51,52,53]. The third explanation is that due to racism and discrimination, presence or absence of resources and assets may have lost some of their protective effects. For example, due to other adverse conditions, lack of physical health conditions may not be enough to enhance the sense of wellbeing of Black individuals [54,55,56,57]. The fourth explanation suggests that Black individuals may better utilize religion, spirituality, and social support than other groups [58,59]. For example, some research has shown stronger protection of religion and social support among Black people [60,61,62,63,64,65,66]. Some other studies by Mouzon and colleagues, however, have failed to show a full explanation of the mechanisms for such a paradox [67,68]. Religion and spirituality are shown to be very beneficial for Black people.
The results have clinical implications. At any level of mental HRQoL, ethnic groups have different physical health statuses. This information is relevant to the provision of integration of physical and mental health care for ethnic minorities. In addition, clinicians need to monitor for chronic disease in Black patients regardless of their well-being. For Latinx patients, however, there is an increasing need for monitoring and screening of chronic diseases when HRQoL is low.
Study limitations include non-randomized sample size, low sample size of Latinx group, self-reported data on chronic medical conditions, lack of analysis of each type of chronic disease, and omission of variables that may confound our association of interest. Given the small sample size and non-random sampling, the results are not able to be generalized to apply to older American adults or even our SPA6 population. This was a preliminary and local study with convenient sampling, and there is a need for future research with a random, large U.S. sample. Black and Latinx sample sizes were also unequal, so the results may be biased due to a higher number of Black than Latinx individuals. Factors such as year of diagnosis, medications used, and adherence to medications may have confounded our association of interest. Thus, our study had unmeasured confounders. Finally, although self-reported data are commonly used to collect information on chronic diseases, the validity of the results would be increased if we could confirm those conditions through medical records. Given these limitations, the results should be interpreted with caution. Thus, there is a need for future quantitative and qualitative research on this topic. Qualitative methods may provide very relevant information on Black individuals’ resilience and mental health advantages.

6. Conclusions

Despite the inverse association that exists between number of chronic medical conditions and poor physical and mental HRQoL, the link between the number of chronic medical conditions and poor mental HRQoL is weaker for Black than Latinx individuals. This is similar to and supports the Blacks’ mental health paradox, in which Black individuals report better mental health despite higher prevalence of adversities and chronic medical conditions. This pattern is not merely limited to the comparison of Black and White people, as evidenced supported by the study, it may hold for comparison of Black individuals with other similarly under-resourced minority groups such as Latinx population.

Author Contributions

Conceptualization, T.G., B.N. (Babak Najand), B.N. (Berlin Navarro) and A.H.; methodology, M.B.; software, M.B.; validation, M.B.; formal analysis, T.G., B.N. (Babak Najand), B.N. (Berlin Navarro) and A.H.; investigation, M.B.; resources, M.B.; data curation, M.B.; writing—original draft preparation, S.C.; writing—review and editing, T.G., B.N. (Babak Najand), B.N. (Berlin Navarro), A.H., M.B., S.C.; supervision, M.B. and S.C.; project administration, M.B.; funding acquisition, M.B. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by the Center for Medicare and Medicaid Services (CMS) Grant 1H0CMS331621 to Charles R. Drew University of Medicine and Science (Principal Investigator: M. Bazargan).

Institutional Review Board Statement

Charles R. Drew University of Medicine and Science IRB approved the study protocol (14-12-2450-05).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Data are available upon request.

Conflicts of Interest

The authors have no conflict of interest.

References

  1. Noohi, S.; Khaghani-Zadeh, M.; Javadipour, M.; Assari, S.; Najafi, M.; Ebrahiminia, M.; Pourfarziani, V. Anxiety and depression are correlated with higher morbidity after kidney transplantation. Transpl. Proc. 2007, 39, 1074–1078. [Google Scholar] [CrossRef] [PubMed]
  2. Bayat, N.; Alishiri, G.H.; Salimzadeh, A.; Izadi, M.; Saleh, D.K.; Lankarani, M.M.; Assari, S. Symptoms of anxiety and depression: A comparison among patients with different chronic conditions. J. Res. Med. Sci. 2011, 16, 1441–1447. [Google Scholar] [PubMed]
  3. Megari, K. Quality of life in chronic disease patients. Health Psychol. Res. 2013, 1, e27. [Google Scholar] [CrossRef] [PubMed]
  4. Dworkin, R.H.; Gitlin, M.J. Clinical aspects of depression in chronic pain patients. Clin. J. Pain 1991, 7, 79–94. [Google Scholar] [CrossRef] [PubMed]
  5. Katon, W.; Lin, E.H.; Kroenke, K. The association of depression and anxiety with medical symptom burden in patients with chronic medical illness. Gen. Hosp. Psychiatry 2007, 29, 147–155. [Google Scholar] [CrossRef] [PubMed]
  6. Katon, W.J. Epidemiology and treatment of depression in patients with chronic medical illness. Dialogues Clin. Neurosci. 2022, 13, 7–23. [Google Scholar] [CrossRef]
  7. Egede, L.E. Major Depression in individuals with chronic medical disorders: Prevalence, correlates and association with health resource utilization, lost productivity and functional disability. Gen. Hosp. Psychiatry 2007, 29, 409–416. [Google Scholar] [CrossRef]
  8. Coman, E.N.; Wu, H.Z.; Assari, S. Exploring causes of depression and anxiety health disparities (Hd) by examining differences between 1:1 matched individuals. Brain Sci. 2018, 8, 207. [Google Scholar] [CrossRef]
  9. Assari, S. Black-White Differences in social, psychological, and medical correlates of depression in the United States. Int. J. Epidemiol. Res. 2018, 5, 40–42. [Google Scholar] [CrossRef]
  10. Assari, S. Race and ethnic differences in additive and multiplicative effects of depression and anxiety on cardiovascular risk. Int. J. Prev. Med. 2016, 7, 22. [Google Scholar] [CrossRef]
  11. Lankarani, M.M.; Assari, S. Association between number of comorbid medical conditions and depression among individuals with diabetes; race and ethnic variations. J. Diabetes Metab. Disord. 2015, 14, 56. [Google Scholar] [CrossRef] [PubMed]
  12. Assari, S.; Caldwell, C.H. Gender and ethnic differences in the association between obesity and depression among black adolescents. J Racial Ethn. Health Disparities 2015, 2, 481–493. [Google Scholar] [CrossRef] [PubMed]
  13. Assari, S.; Lankarani, M.M. Race and ethnic differences in the associations between cardiovascular diseases, anxiety, and depression in the United States. Int. J. Travel Med. Glob. Health 2014, 2, 107–113. [Google Scholar] [PubMed]
  14. Assari, S. Chronic kidney disease, anxiety and depression among american blacks; does ethnicity matter? Int. J. Travel Med. Glob. Health 2014, 2, 133–139. [Google Scholar]
  15. Assari, S. Additive effects of anxiety and depression on body mass index among blacks: Role of ethnicity and gender. Int. Cardiovasc. Res. J. 2014, 8, 44–51. [Google Scholar]
  16. Mezuk, B.; Abdou, C.M.; Hudson, D.; Kershaw, K.N.; Rafferty, J.A.; Lee, H.; Jackson, J.S. “White Box” epidemiology and the social neuroscience of health behaviors: The environmental affordances model. Soc. Ment. Health 2013, 3, 79–95. [Google Scholar] [CrossRef]
  17. Assari, S.; Burgard, S.; Zivin, K. Long-term reciprocal associations between depressive symptoms and number of chronic medical conditions: Longitudinal support for black-white health paradox. J. Racial Ethn. Health Disparities 2015, 2, 589–597. [Google Scholar] [CrossRef]
  18. Keyes, C.L. The black-white paradox in health: Flourishing in the face of social inequality and discrimination. J. Pers. 2009, 77, 1677–1706. [Google Scholar] [CrossRef]
  19. Mcandrew, B.M.; Gil, N.; Lee, D.P.; Teklehaimanot, S.; Schrode, K.M.; Bailey, S.; Jordan, W.; Spencer, L.Y.; Rothman, E.; Harawa, N.T.; et al. An exploratory study to characterize the hiv testing-to-care continuum to improve outcomes for black and latinx residents of south Los Angeles. PLoS ONE 2022, 17, E0268374. [Google Scholar] [CrossRef]
  20. Los Angeles County Department Of Public Health; Office of Health Assessment and Epidemiology. Key Indicators of Health by Service Planning Area; Los Angeles County Department Of Public Health: Los Angeles, CA, USA, 2013.
  21. Cobb, S.; Bazargan, M.; Sandoval, J.C.; Wisseh, C.; Evans, M.C.; Assari, S. Depression treatment status of economically disadvantaged african american older adults. Brain Sci. 2020, 10, 154. [Google Scholar] [CrossRef]
  22. Evans, M.C.; Cobb, S.; Smith, J.; Bazargan, M.; Assari, S. Depressive symptoms among economically disadvantaged african american older adults in south Los Angeles. Brain Sci. 2019, 9, 246. [Google Scholar] [CrossRef] [PubMed]
  23. Bazargan, M.; Smith, J.L.; Robinson, P.; Uyanne, J.; Abdulrahoof, R.; Chuku, C.; Assari, S. Chronic respiratory disease and health-related quality of life of african american older adults in an economically disadvantaged area of los angeles. Int. J. Environ. Res. Public Health 2019, 16, 1756. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Assari, S.; Smith, J.L.; Zimmerman, M.A.; Bazargan, M. Cigarette smoking among economically disadvantaged african-american older adults in south los angeles: Gender differences. Int. J. Environ. Res. Public Health 2019, 16, 1208. [Google Scholar] [CrossRef] [PubMed]
  25. Assari, S.; Smith, J.; Bazargan, M. Health-related quality of life of economically disadvantaged african american older adults: Age and gender differences. Int. J. Environ. Res. Public Health 2019, 16, 1522. [Google Scholar] [CrossRef] [PubMed]
  26. Cheak-Zamora, N.C.; Wyrwich, K.W.; Mcbride, T.D. Reliability and Validity of the Sf-12v2 in the Medical Expenditure Panel Survey. Qual. Life Res. 2009, 18, 727–735. [Google Scholar] [CrossRef] [PubMed]
  27. Fleishman, J.A.; Selim, A.J.; Kazis, L.E. Deriving Sf-12v2 physical and mental health summary scores: A comparison of different scoring algorithms. Qual. Life Res. 2010, 19, 231–241. [Google Scholar] [CrossRef]
  28. Larson, C.O.; Schlundt, D.; Patel, K.; Hargreaves, M.; Beard, K. Validity of the Sf-12 for Use in A Low-Income African American Community-Based Research Initiative (Reach 2010). Prev. Chronic Dis. 2008, 5, A44. [Google Scholar]
  29. Luo, X.; George, M.L.; Kakouras, I.; Edwards, C.L.; Pietrobon, R.; Richardson, W.; Hey, L. Reliability, Validity, And Responsiveness of the Short Form 12-Item Survey (Sf-12) in Patients with Back Pain. Spine 2003, 28, 1739–1745. [Google Scholar] [CrossRef]
  30. Gandhi, S.K.; Salmon, J.W.; Zhao, S.Z.; Lambert, B.L.; Gore, P.R.; Conrad, K. Psychometric Evaluation Of The 12-Item Short-Form Health Survey (Sf-12) in Osteoarthritis and Rheumatoid Arthritis Clinical Trials. Clin. Ther. 2001, 23, 1080–1098. [Google Scholar] [CrossRef]
  31. Moraska, A.R.; Chamberlain, A.M.; Shah, N.D.; Vickers, K.S.; Rummans, T.A.; Dunlay, S.M.; Spertus, J.A.; Weston, S.A.; Mcnallan, S.M.; Redfield, M.M.; et al. Depression, Healthcare Utilization, and Death in Heart Failure: A Community Study. Circ. Heart Fail 2013, 6, 387–394. [Google Scholar] [CrossRef]
  32. Huang, M.H.; Wang, Y.P.; Wu, P.S.; Chan, Y.E.; Cheng, C.M.; Yang, C.H.; Tsai, S.J.; Lu, C.L.; Tsai, C.F. Association between Gastrointestinal Symptoms and Depression among Older Adults in Taiwan: A Cross-Sectional Study. J. Chin. Med. Assoc. 2021, 84, 331–335. [Google Scholar] [CrossRef] [PubMed]
  33. Bąk, B.; Witusik, A.; Kamecki, K.; Pietras, T. Is Asthma with Hypersenitivity to Non-Steroidal Anti-Inflammatory Drugs is a Risk Factor for Depression? Pol. Merkur. Lekarski. 2022, 50, 99–101. [Google Scholar] [PubMed]
  34. Machicado, J.D.; Amann, S.T.; Anderson, M.A.; Abberbock, J.; Sherman, S.; Conwell, D.L.; Cote, G.A.; Singh, V.K.; Lewis, M.D.; Alkaade, S.; et al. Quality of Life in Chronic Pancreatitis Is Determined by Constant Pain, Disability/Unemployment, Current Smoking, and Associated Co-Morbidities. Am. J. Gastroenterol. 2017, 112, 633–642. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  35. Reinlieb, M.E.; Persaud, A.; Singh, D.; Garcon, E.; Rutherford, B.R.; Pelton, G.H.; Devanand, D.P.; Roose, S.P.; Sneed, J.R. Vascular Depression: Overrepresented among African Americans? Int. J. Geriatr. Psychiatry 2014, 29, 470–477. [Google Scholar] [CrossRef]
  36. Gulley, S.P.; Rasch, E.K.; Bethell, C.D.; Carle, A.C.; Druss, B.G.; Houtrow, A.J.; Reichard, A.; Chan, L. At The intersection of chronic disease, disability and health services research: A scoping literature review. Disabil. Health J. 2018, 11, 192–203. [Google Scholar] [CrossRef]
  37. Menting, J.; Tack, C.J.; Bleijenberg, G.; Donders, R.; Droogleever Fortuyn, H.A.; Fransen, J.; Goedendorp, M.M.; Kalkman, J.S.; Strik-Albers, R.; Van Alfen, N. Is fatigue a disease-specific or generic symptom in chronic medical conditions? Health Psychol. 2018, 37, 530. [Google Scholar] [CrossRef]
  38. Pagé, M.G.; Lacasse, A.; Dassieu, L.; Hudspith, M.; Moor, G.; Sutton, K.; Thompson, J.M.; Dorais, M.; Montcalm, A.J.; Sourial, N. A Cross-Sectional study of pain status and psychological distress among individuals living with chronic pain: The chronic pain & COVID-19 pan-canadian study. Chronic Dis. Inj. Can. 2021, 41, 141–152. [Google Scholar]
  39. Ballering, A.V.; Bonvanie, I.J.; Hartman, T.C.O.; Monden, R.; Rosmalen, J.G. Gender and sex independently associate with common somatic symptoms and lifetime prevalence of chronic disease. Soc. Sci. Med. 2020, 253, 112968. [Google Scholar] [CrossRef]
  40. Assari, S.; Moghani Lankarani, M. Race and gender differences in correlates of death anxiety among elderly in the United States. Iran. J. Psychiatry Behav. Sci. 2016, 10, E2024. [Google Scholar] [CrossRef]
  41. Kazemi-Saleh, D.; Pishgoo, B.; Farrokhi, F.; Fotros, A.; Assari, S. Sexual function and psychological status among males and females with ischemic heart disease. J. Sex. Med. 2008, 5, 2330–2337. [Google Scholar] [CrossRef]
  42. Thomas Tobin, C.S.; Erving, C.L.; Hargrove, T.W.; Satcher, L.A. Is the black-white mental health paradox consistent across age, gender, and psychiatric disorders? Aging Ment. Health 2022, 26, 196–204. [Google Scholar] [CrossRef] [PubMed]
  43. Brown, L. The black-white mental health paradox among older adults: Evidence from the health and retirement study. Innov. Aging 2020, 4, 581. [Google Scholar] [CrossRef]
  44. Tobin, C.S.T.; Moody, M.D. Does early-life racial discrimination explain a mental health paradox among black adults? Innov. Aging 2019, 3, S192. [Google Scholar]
  45. Assari, S. Bidirectional Associations between chronic medical conditions, disability, and depressive symptoms over 25 years: Black-white differences. Int. J. Epidemiol. Res. 2016, 3, 302–317. [Google Scholar]
  46. Assari, S.; Lankarani, M.M. Association between stressful life events and depression; intersection of race and gender. J. Racial Ethn. Health Disparities 2016, 3, 349–356. [Google Scholar] [CrossRef] [PubMed]
  47. Pamplin, J.R.; Kezios, K.L.; Hayes-Larson, E.; Keyes, K.M.; Susser, E.S.; Factor-Litvak, P.; Link, B.G.; Bates, L.M. Explaining the black-white depression paradox: Interrogating the environmental affordances model. Soc. Sci. Med. 2021, 277, 113869. [Google Scholar] [CrossRef] [PubMed]
  48. Bassett, M.T.; Graves, J.D. Uprooting institutionalized racism as public health practice. Am. J. Public Health 2018, 108, 457. [Google Scholar]
  49. Cobbinah, S.S.; Lewis, J. Racism & health: A public health perspective on racial discrimination. J. Eval. Clin. Pract. 2018, 24, 995–998. [Google Scholar]
  50. Alang, S.M. Mental health care among blacks in America: Confronting racism and constructing solutions. Health Serv. Res. 2019, 54, 346–355. [Google Scholar]
  51. Assari, S. Blacks’ Diminished return of education attainment on subjective health; mediating effect of income. Brain Sci. 2018, 8, 176. [Google Scholar] [CrossRef]
  52. Assari, S. Diminished economic return of socioeconomic status for black families. Soc. Sci. 2018, 7, 74. [Google Scholar] [CrossRef] [PubMed]
  53. Assari, S. Socioeconomic determinants of systolic blood pressure; minorities’ diminished returns. J. Health Econ. Dev. 2019, 1, 1–11. [Google Scholar] [PubMed]
  54. Cobb, S.; Javanbakht, A.; Khalifeh Soltani, E.; Bazargan, M.; Assari, S. Racial difference in the relationship between health and happiness in the United States. Psychol. Res. Behav. Manag. 2020, 13, 481–490. [Google Scholar] [CrossRef] [PubMed]
  55. Maharlouei, N.; Cobb, S.; Bazargan, M.; Assari, S. Subjective health and happiness in the United States: Gender differences in the effects of socioeconomic status indicators. J. Ment. Health Clin. Psychol. 2020, 4, 8–17. [Google Scholar] [CrossRef] [PubMed]
  56. Assari, S. Race, sense of control over life, and short-term risk of mortality among older adults in the United States. Arch. Med. Sci. 2017, 13, 1233–1240. [Google Scholar] [CrossRef] [PubMed]
  57. Assari, S.; Lankarani, M.M.; Burgard, S. Black-white difference in long-term predictive power of self-rated health on all-cause mortality in United States. Ann. Epidemiol. 2016, 26, 106–114. [Google Scholar] [CrossRef]
  58. Assari, S. Race And Ethnicity, Religion Involvement, Church-Based Social Support And Subjective Health In United States: A Case Of Moderated Mediation. Int. J. Prev. Med. 2013, 4, 208–217. [Google Scholar]
  59. Assari, S.; Moghani lankarani, M. secular and religious social support better protect blacks than whites against depressive symptoms. Behav. Sci. 2018, 8, 46. [Google Scholar] [CrossRef]
  60. Krause, N.; Van Tran, T. Stress and religious involvement among older blacks. J. Gerontol. 1989, 44, S4–S13. [Google Scholar] [CrossRef]
  61. Shaw, B.A.; Krause, N. Exploring race variations in aging and personal control. J. Gerontol. B Psychol. Sci. Soc. Sci. 2001, 56, S119–S124. [Google Scholar] [CrossRef] [Green Version]
  62. Krause, N. Race, religion, and abstinence from alcohol in late life. J. Aging Health 2003, 15, 508–533. [Google Scholar] [CrossRef] [PubMed]
  63. Krause, N. Common facets of religion, unique facets of religion, and life satisfaction among older african americans. J. Gerontol. B Psychol. Sci. Soc. Sci. 2004, 59, S109–S117. [Google Scholar] [CrossRef] [PubMed]
  64. Krause, N.; Hayward, R.D. Awareness of the historical role of the church and change in self-esteem among older african americans. Appl. Psychol. Health Well Being 2012, 4, 240–260. [Google Scholar] [CrossRef] [PubMed]
  65. Krause, N. Assessing supportive social exchanges inside and outside religious institutions: Exploring variations among whites, hispanics, and blacks. Soc. Indic. Res. 2016, 128, 131–146. [Google Scholar]
  66. Mcintosh, R.; Ironson, G.; Krause, N. Keeping hope alive: Racial-ethnic disparities in distress tolerance are mitigated by religious/spiritual hope among black americans. J. Psychosom. Res. 2021, 144, 110403. [Google Scholar] [CrossRef]
  67. Mouzon, D.M. Relationships of choice: Can friendships or fictive kinships explain the race paradox in mental health? Soc. Sci. Res. 2014, 44, 32–43. [Google Scholar] [CrossRef]
  68. Taylor, R.J.; Mouzon, D.M.; Nguyen, A.W.; Chatters, L.M. Reciprocal family, friendship and church support networks of african americans: Findings from the national survey of american life. Race Soc. Probl. 2016, 8, 326–339. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Table
Table 1. Descriptive data overall and by race/ethnicity.
Table 1. Descriptive data overall and by race/ethnicity.
All
n = 724		Latinx
n = 116		Black
n = 608
n%n%n%
Gender
Male25234.84034.521234.9NS
Female47265.27665.539665.1
Marital Status
Not Married58580.87463.851184.0*
Married13919.24236.29716.0
Medicare Insurance
No19827.33126.716727.5NS
Yes52672.78573.344172.5
MeanSDMeanSDMeanSD
Age73.866.89473.326.44373.966.977*
Years of Education11.913.2757.744.26312.702.320*
Number of Chronic Conditions4.08702.024583.95692.148384.11182.00099*
Mental HRQoL SF1253.037510.6579950.664614.5761353.49029.68333*
Physical HRQoL—SF1240.906711.9745739.629711.5554441.150312.04674*
* p < 0.05 for comparison of Latinx and Black, HRQoL: Health-Related Quality of Life, NS: Non-significant.
Table
Table 2. Correlation between study variables overall.
Table 2. Correlation between study variables overall.
12345678910
1 Age1−0.139 **0.0340.044−0.079 *0.112 **0.018−0.0040.0440.065
2 Years of Education 10.556 **0.089 *−0.0430.078 *−0.077 *−0.0460.136 **0.047
3 Black 1−0.003−0.189 **0.188 **−0.0060.0280.097 **0.047
4 Gender 1−0.152 **0.074 *−0.0320.123 **0.046−0.152 **
5 Married 1−0.442 **0.000−0.0490.0160.089 *
6 Living Arrangement 1−0.0220.107 **−0.068−0.135 **
7 Medicare 10.0340.004−0.033
8 Chronic Diseases (n) 1−0.232 **−0.464 **
9 Mental HRQoL—SF12 1−0.025
10 Physical HRQoL—SF12 1
HRQoL: Health-Related Quality of Life,* p < 0.05, ** p < 0.01.
Table
Table 3. Linear regression on mental health-related quality of life as the outcome.
Table 3. Linear regression on mental health-related quality of life as the outcome.
Model 1Model 2
Unstand bSEBeta95% CI pUnstand bSEBeta95% CI p
Black1.7211.3010.059−0.8334.2750.186−3.3392.351−0.115−7.9541.2750.156
Age0.0940.0570.061−0.0180.2050.1000.0890.0570.058−0.0220.2000.117
Gender1.5600.8250.070−0.0593.1790.0591.6060.8220.072−0.0073.2190.051
Years of Education0.3330.1450.1020.0480.6190.0220.3360.1450.1030.0510.6200.021
Married0.1061.1010.004−2.0562.2680.9240.0361.0970.001−2.1192.1900.974
Living Arrangement−1.5400.869−0.072−3.2470.1660.077−1.5490.866−0.072−3.2490.1510.074
Medicare Coverage0.4700.8600.020−1.2182.1570.5850.4450.8560.019−1.2362.1260.604
Chronic with no depression−1.2110.192−0.230−1.587−0.8340.000−2.2500.446−0.427−3.125−1.3750.000
Chronic with no depression × race/ethnicity 1.2650.4900.2820.3022.2270.010
Model 1: main effects, Model 2: main effects and interaction.
Table
Table 4. Linear regression with physical quality of life as the outcome.
Table 4. Linear regression with physical quality of life as the outcome.
Model 1Model 2
Unstand bSEBeta95% CI pUnstand bSEBeta95% CI p
Black2.3541.3280.072−0.2534.9610.0774.9562.4080.1520.2289.6830.040
Age (Years)0.1380.0580.0800.0250.2520.0170.1410.0580.0810.0270.2550.015
Gender−2.2940.842−0.091−3.947−0.6410.007−2.3170.842−0.092−3.970−0.6650.006
Years of Education0.0460.1480.012−0.2460.3370.7590.0440.1480.012−0.2470.3350.766
Married1.0341.1240.034−1.1733.2420.3581.0701.1240.035−1.1363.2770.341
Living Arrangement−2.1560.887−0.089−3.898−0.4140.015−2.1520.887−0.089−3.893−0.4100.016
Medicare Coverage−0.6180.877−0.023−2.3411.1040.481−0.6060.877−0.023−2.3281.1160.490
Chronic Medical Conditions (n)−2.6130.196−0.442−2.997−2.2280.000−2.0780.457−0.351−2.975−1.1820.000
Chronic Medical Conditions (n) × race/ethnicity −0.6500.502−0.129−1.6360.3350.196
Model 1: main effects, Model 2: main effects and interaction.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Cobb, S.; Najand, B.; Gravidez, T.; Navarro, B.; Herreraramos, A.; Bazargan, M. Number of Chronic Medical Conditions and Quality of Life of Ethnic Minority Older Adults. Geriatrics 2022, 7, 106. https://doi.org/10.3390/geriatrics7050106

AMA Style

Cobb S, Najand B, Gravidez T, Navarro B, Herreraramos A, Bazargan M. Number of Chronic Medical Conditions and Quality of Life of Ethnic Minority Older Adults. Geriatrics. 2022; 7(5):106. https://doi.org/10.3390/geriatrics7050106

Chicago/Turabian Style

Cobb, Sharon, Babak Najand, Tara Gravidez, Berlin Navarro, Alondra Herreraramos, and Mohsen Bazargan. 2022. "Number of Chronic Medical Conditions and Quality of Life of Ethnic Minority Older Adults" Geriatrics 7, no. 5: 106. https://doi.org/10.3390/geriatrics7050106

APA Style

Cobb, S., Najand, B., Gravidez, T., Navarro, B., Herreraramos, A., & Bazargan, M. (2022). Number of Chronic Medical Conditions and Quality of Life of Ethnic Minority Older Adults. Geriatrics, 7(5), 106. https://doi.org/10.3390/geriatrics7050106

Article Metrics

Back to TopTop