Abstract
This systematic review aimed to examine whether higher comorbidity burden, as assessed by comorbidity indices, was associated with a functional autonomy decline in individuals with cognitive impairment. The search was conducted in the following databases: PubMed/MEDLINE, ScienceDirect, Cochrane, and Embase. Both cross-sectional and longitudinal studies that examined the relationship between comorbidity indices and scales measuring activities of daily living (ADL) in individuals with cognitive impairment were included. The quality assessment tool for observational cohort and cross-sectional studies of the National Institutes of Health (NIH) was used. Overall, 12 studies were included, among which three were longitudinal. Significant association was frequently reported by cross-sectional designs (n=7 studies) and only one study reported a significant longitudinal association. This longitudinal study repeatedly assessed both comorbidity burden and functional autonomy, and considered comorbidity burden as a time-varying covariate. Considering comorbidity burden as a time varying covariate may deal with the dynamic nature of comorbidity burden over time, and conducting repeated assessments during the follow-up using both comorbidity index and ADL scales may increase their sensitivity to reliably measure comorbidity burden and functional autonomy decline over time. In conclusion, a higher comorbidity index was associated with a lower level of functional autonomy in people with cognitive impairment. This relationship seems to be dynamic over time and using comorbidity indices and ADL scales only once may not deal with the fluctuation of both comorbidity burden and functional autonomy decline. To cope with complexity of this relationship this review highlights some methodological approaches to be considered.
Key words: Comorbidity burden, comorbidity index, functional autonomy decline, dementia, cognition
Introduction
According to the World Health Organization (WHO), the global prevalence of dementia was approximately 55 million in 2019, and it is expected to triple by 2050 (1). Individuals with dementia and mild cognitive impairment (MCI) are more likely to experience a higher comorbidity burden compared to normal cognitive individuals (NCI), which could hasten cognitive decline (2, 3, 4, 5).
Studies have found that comorbidity burden in older NCI increases the risk of decline in function defined as an inability to perform autonomously activities of daily living (ADL) (6, 7, 8, 9). Nevertheless, this relationship in the population with dementia remains inconsistent (10, 11, 12). For instance, according to a one-year prospective cohort reported by Slaughter et al. higher comorbidity burden measured by the Charlson comorbidity index (CCI) was associated with two separate dimensions of functional autonomy (walking and eating disability) in patients with MCI (10). Nelis et al. also did so in a study where the number of medical conditions included for the calculation of the CCI was used to describe comorbidity burden and separate three dimensions of functional autonomy (poor mobility, self-care, and usual activities) (11). However, no significant association was found in a 6-month prospective cohort reported by Hiroyuki et al. who measured comorbidity burden by the total number of endorsed categories of the cumulative illness rating score for geriatrics (CIRS-G) and functional autonomy level was measured by the Physical Self-Maintenance Scale (PSMS) (12).
The heterogeneity in the results of such studies may be related to the heterogeneity in the assessment of comorbidity burden but also functional autonomy. The most accurate description of comorbidities is based on indices, such as the CCI, that consider both number and severity of comorbidities when assessing comorbidities (13, 14), and using ADL scales to assess functional autonomy allows the evaluation of the effect on overall function (15). To the best of our knowledge only one systematic review conducted in January 2016 that investigated the association between comorbidity burden and functional autonomy among late-onset Alzheimer's Disease (LOAD) (16). In this previous systematic review, seven studies were included (17, 18, 19, 20, 21, 22, 23), and among these one did not use a comorbidity index (23), and another used the Clinical Dementia Rating – sum of boxes that encompassed more than just ADL precluding conclusions as to the association between comorbidities and functional autonomy (20). Among the other studies one was a longitudinal study (did not find a significant association (22)) and four were cross-sectional (three of which found a significant association (18, 19, 21)), which did not allow to interpret causality link between higher comorbidity burden and functional autonomy decline.
We therefore conducted a systematic review to examine whether higher comorbidity burden, as assessed by comorbidity indices, was associated with a functional autonomy decline in individuals with cognitive impairment.
Methods
This systematic review is reported according to the Preferred Reporting Items for Systematic Review and Meta-Analyses (24).
Search strategy and study selection
We conducted the search in November, 2022 using key words and MeSH terms, in the following databases: PubMed/MEDLINE, ScienceDirect, Cochrane, and Embase. However, search equations were adapted to each database (supplementary appendix 1). Although we distinguish comorbidity and multimorbidity, the use of the term “multimorbidity” during the search process was unavoidable; prior to 2018, both terms were used interchangeably (25). To cope with limitation of our search strategy and to ensure the exhaustivity of the search, a snowballing strategy gathering articles through the reference list of included papers was used (26).
Eligibility criteria for selection of studies
Studies involved individuals with any stage of cognitive impairment, regardless of etiologic diagnosis. The comorbidity burden had to be measured by a comorbidity index, which could be validated in either the dementia population, geriatric population, or general population. In contrast, studies used disease count, the total number of endorsed disease categories or comorbidity index specific to one particular medical condition, such as the diabetes complications severity index, were excluded. Functional autonomy level had to be measured by ADL scales including basic (b) ADL, instrumental (i) ADL, or a combination of the both (b/iADL). Studies that separately examined few dimensions of functional autonomy, such as walking or eating, were excluded. The review included both cross-sectional and longitudinal studies that examined the relationship between comorbidity index and functional autonomy using quantitative measures. Studies had to be written in English or French language. The screening of titles and abstracts as well as full-text reviewing were ensured independently by a PhD student (MNT) and an epidemiologist (VD) based on eligibility criteria. Disagreements were resolved through discussion with the research team.
Data extraction
For each study, the following data were extracted: general characteristics, population characteristics and information about the studied association. However, general characteristics of studies were the first author, year of publication, setting of study, design and the quality of study. Data related to characteristics of population were the total number of sample, mean age with the standard deviation (SD), percentage of female, and the etiologic diagnosis and/or severity stages of cognitive impairment. Regarding the studied association, comorbidity indices, ADL scales, statistical methods used for analysis and a quantitative indicator of the relationship between comorbidity index and ADL scale (odds ratio [OR], regression coefficient, correlation coefficient, p-value, etc.), were extracted. Authors were contacted if there were any ambiguities. Data were summarized in one table (table 1), and results were considered statistically significant if the p-value was less than 0.05.
Table 1.
Summary of included studies (n = 12)
Authors | Study characteristics | Population characteristics | Studied association | |||||||
---|---|---|---|---|---|---|---|---|---|---|
Year/country | Design | Quality | Total number | Mean ± SD age, years | Proportion of female (%) | Distribution of etiologic disorder/severity stages (%) | Comorbidity indices | b/iADL scales | Statistical model and results | |
Lyketsos et al. (21) | 1999/USA | Cross-sectional | Fair | 619 | 76.56 ± NR | 68.6 | AD (55.6), VD (14.7), Unspecified (29.7) | GMHR | PGDRS-P | Findings of multiple linear regression were categorized by MMSE values: for mild dementia (MMSE ≥ 20), β = −1.8 (SE = 0.44), p = 0.001, for moderate dementia (MMSE = [10;19]), β = −4.1 (SE = 0.68), p = 0.001, and for advanced dementia (MMSE < 10), β = −5.3 (SE = 1.09), p = 0.001 |
Tekin et al. (17) | 2001/USA | Cross-sectional | Fair | 143 | 76.5 ± 7.78 | 67.8 | Possible AD (26.6), Probable AD (73.4) | CIRS-G | FAQ | Findings of bivariate Pearson correlation and standardized regression coefficients were: r = 0.101, β = 0.001, p = 0.99 |
Doraiswamy et al. (18) | 2002/USA | Cross-sectional | Fair | 679 | 82.1 ± NR | 67.2 | AD (100)/mild dementia (36.2), moderate (33.9), severe (29.9) | CIRS-G | Self-care HUI | Findings of general linear model were: R2 = 0.47, p < 0.0001 |
Mariani et al. (30) | 2008/Italy | Cross-sectional | Fair | 132 | 61.1±5.8 | 56.8 | MCI (100) | CIRS | IADL | Findings of multiple adjusted logistic regression were categorized across 4 quartiles of CIRS and the 1st quartile = [1;1.15] was the reference (OR = 1). The 2nd quartile = [1.16;1.30] and OR = 0.9 (95%CI [0.4;2.7]), p = NS (NR), the 3rd quartile = [1.31;1.53] and OR = 1.9 (95%CI [0.7;5.1]), p = NS (NR), the 4th quartile ≥ 1.54 and OR = 2.2 (95%CI [0.7;7]), p = NS (NR) |
Samus et al. (33) | 2009/USA | Cross-sectional | Fair | 155 | 85.4 ± 8.6 | 75.5 | Dementia (100) | GMHR | PGDRS-P | Findings of univariate linear regression were: B = −5.71 (SE = 0.95), p < 0.001, findings of multivariable linear regression were: B = −3.58 (SE = 0.85), p < 0.001 and findings of adjusted multivariable linear regression were: B = −3.54 (SE = 0.84), p < 0.001 |
Oosterveld et al. (19) | 2014/Netherlands | Cross-sectional | Fair | 213 | 75 ± 10 | 57.7 | Possible AD (9.4), Probable AD (90.6) | CIRS-G | DAD | Findings of Spearman correlation (r) were: r = −0.37, p < 0.001. |
King et al. (29) | 2014/USA | Cross-sectional | Fair | 76 | 63.9 ± 7.79 | NR | PD (100) | CIRS-G | PPT | Spearman correlation was applied for two measurements of CIRS-G. For total score: r = −0.36, p = 0.0041 and for the severity index: r = − 0.20, p = 0.121 |
Rossum et al. (31) | 2016/Netherlands | Cross-sectional | Fair | 474 | 78,1 ± 7.94 | 55.9 | MCI (NR), Dementia (NR) | CCI | DAD | Findings of univariate linear regression were: β = 0.12, p < 0.01, and findings for multivariable linear regression were: β = 0.03, p = 0.48 |
Boltz et al. (32) | 2021/USA | Cross-sectional | Fair | 299 | 81.6 ± 8.54 | 61.9 | Dementia (100) | CCI | BI | Findings of Pearson correlation were: r = −0.063, p = 0.283 |
Hiroyuki et al. (12) | 2019/Japan | Prospective Clinical Cohort | Fair | 131 | 87 ± 7 | 74.8 | AD (49.6), VD (33.6), LBD (2.3), Unspecified (14.5) | CCI | PSMS | For cross-sectional analysis, findings of Spearman correlation were: r = −0.163, p < 0.05, and findings of multiple regression (without precising if linear or no linear regression) were: β = −0.228 (95%CI [−0.94;−0.30]), p < 0.001. Association between baseline CCI and PSMS after 6 months was elaborated by multiple regression analysis and findings were: β = −0.16 (95%CI [−0.76;0.03]), p = 0.072 |
Wubben et al. (28) | 2022/Netherlands | Prospective Clinical Cohort | Good | 331 | 74.9 ± 10.2 | 54.7 | AD (65.2), VD (21.4), Unspecified (13.3) | CIRS-G | DAD | Findings of conditional growth model were: B = −1.2 (SE = 0.29), p < 0.01 for cross-sectional analysis. Regarding longitudinal analysis two associations were reported: 1) B = −0.3 (SE = 0.12), p < 0.02, when using CIRS-G as time invariant baseline covariate. 2) B = −1.1 (SE = 0.23), p < 0.01, when using CIRS-G as time varying covariate |
Solomon et al. (22) | 2011/Romania | Prospective Clinical Cohort | Good | 102 | 75.4 ± 8.2 | 61.8 | AD (100) | CIRS-G | Katz bADL | Findings of ordinal logistic regression were: OR = 2.7 (95%CI [0.7;9.6]), p = NS (NR) |
Lawton iADL | Findings of ordinal logistic regression were: OR = 1.8 (95%CI [0.3;10.1]), p = NS (NR) | |||||||||
AD: Alzheimer's Disease; VD: Vascular Dementia; PD: Parkinson's Disease; MCI: Mild Cognitive Impairment; LBD: Lewy Body Dementia; CIRS-G: Cumulative Illness Rating Scale-Geriatric; CIRS: Cumulative Illness Rating Scale; CCI: Charlson Comorbidity Index; GMHR: General Medical Health Rating; DAD: Disability Assessment of Dementia; PGDRS-P: Psycho geriatric Dependency Rating Scale- Physical subscale; ADL: Activities of Daily Living; IADL: Instrumental Activities of Daily Living; BI: Barthel index; PSMS: Physical Self-Maintenance Scale; FAQ: Functional Activities Questionnaire; PPT: Physical Performance Test; HUI: Health Utilities Index; B: Unstandardized coefficient; β: Standardized coefficient; r: Correlation coefficient; OR: Odds Ratio; CI: Confidence Interval; MMSE: Mini-Mental State Examination; NR: Not Reported; NS: No significant; CI: Confident interval; SE: Standard error
Risk of bias in individual studies
The quality assessment tool for observational cohort and cross-sectional studies of the National Institutes of Health (NIH) was used (https://www.nhlbi.nih.gov/health-topics/study-quality-assessment-tools) (27). For each included study, the following criteria were evaluated: the clarity of objective, the definition of study population, the participation rate, the uniformity of subject selection, the sample size justification, whether assessment of exposure was prior to outcome, timing between exposure and outcome measurements, the analysis of exposure levels, the repeated assessment of exposure, validity and reliability of the assessment tool (exposure and outcome), blinding of outcome assessors, the loss to follow-up rate, and adjustment for potential confounding variables. This tool allowed us to determine whether the study was of poor (0–4), fair (5–10), or good (11–14) quality. Quality assessment and data extraction were conducted by MNT and verified by VD.
Results
Study selection
A total of 1092 records were identified, among which 83 were gathered by the snowballing strategy. After removing 316 duplicates, the titles and abstracts of 776 records were screened. All 267 reports were sought for retrieval were assessed for eligibility, and after full-text review 255 reports were excluded; 12 studies were included (figure 1).
Figure 1.
Flow Chart
Study and population characteristics
Included studies were published between 1999 and 2022, and were most frequently conducted in the USA (n = 6). We excluded from the description of participants the patients included in the study reported by Oosterveld et al. (19) (n = 213) since they were also included in the study reported by Wubben et al. as a subgroup (28). The total number of participants was 3141; the mean ± SD age was 76.6 ± 5.7 years, and 64% were female (King et al. did not provide information about gender (29)). The sample size of studies ranged from 76 to 697 patients, and 7/11 studies (n = 2081) described the etiologic diagnosis of cognitive impairment (table 1); the most frequent etiologic diagnosis was Alzheimer's disease (AD; n = 1567, 75.3%) and the least frequent was Parkinson's disease (PD; n = 76, 3.7%).
Description of the application of comorbidity indices
The CIRS-G was most frequently used (n = 6); three studies used the CCI, two studies used the General Medical Health Rating (GMHR), and one study used the CIRS (table 1).
Four studies used the CIRS-G as a physical comorbidity index by scoring 13/14 items, excluding the item “psychiatric illnesses” (17, 18, 19, 28). They excluded this item as dementia is included in the psychiatric item of CIRS-G. Solomon et al. chose to use all 14 items of the score without considering dementia diagnosis for the item “psychiatric illnesses” (22). To establish association between CIRS-G and functional autonomy scales, three studies used the CIRS-G total score (the sum of individual organ system scores) (17, 19, 28), two studies used the CIRS-G as a severity index (total score/total number of endorsed categories) (18, 22), and one study used the two summary measures (29). One study, reported by Mariani et al., did not use the geriatric version of CIRS (CIRS-G) but the CIRS published by Parmalee et al. (30). Regarding the CCI, two studies used the original version (12, 31) and one study used the Van Doorn version (32) (table 1; supplementary appendix 2).
Functional outcomes
Nine functional autonomy scales were used by the included studies (table 1). The majority of scales (5/9) measured the bADL: Psychogeriatric Dependency Rating Scale- Physical subscale (PGDRS-P) (19, 28, 31), Katz bADL (22), self-care Health Utilities Index (HUI) (18), Physical Performance Test (PPT) (29), and Barthel index (BI) (32). Two scales measured the iADL: Lawton iADL (22, 30), and Functional Activities Questionnaire (FAQ) (17). Two scales measured both b/iADL: Disability Assessment of Dementia (DAD) (19) and PSMS (12).
Risk of bias
Two longitudinal studies were rated as having good quality according to the NIH assessment tool (22, 28), while the remaining studies were graded as fair. Only two studies used comorbidity indices as categorical variables (30, 31). Only one study performed multiple assessments of comorbidity indices over time (4 times) (28). Given the majority of the studies were cross-sectional (9/12), it was not possible to determine the proportion of participants lost to follow-up, and thus it was considered as not applicable for the NIH. However, one longitudinal study initially intended to span a duration of 12 months had to be prematurely stopped at 6 months due to a significant dropout rate, with more than 20% of participants who were lost to follow-up after at this point (12). Only two studies performed more than one assessment of functional autonomy: two time points in the study reported by Hiroyuki et al. (12), and four time points in the study reported by Wubben et al. (28).
Association between comorbidity indices and functional autonomy
Overall, cross-sectional associations were reported by 11 studies and longitudinal associations were reported by three studies. Nine studies used only cross-sectional association, one study used only longitudinal association and two studies used both. Seven studies reported a significant association between higher comorbidity indices and a lower functional autonomy level (table 1).
Studies used only cross-sectional association (n = 9 studies)
Four studies used CIRS-G score to evaluate comorbidity burden and three of them reported a significant association (18, 19, 29), a lower functional autonomy level was significantly associated with higher CIRS-G total score (19, 29) and CIRS-G considered as a severity index (18). One study reported by Mariani et al. did not report a significant association between CIRS and IADL (30).
Two studies used CCI to evaluate comorbidity burden and only one reported a significant association with a lower functional autonomy level (31). This significant association was found in the univariate linear regression model but it did not remain significant in the multivariable linear regression model.
Two studies used GMHR to evaluate comorbidity burden, and both reported a significant association between higher comorbidity burden (lower GMHR) and a lower functional autonomy level (21, 33). Specifically, one study examined this relationship across different stages of cognitive impairment, as measured by the Mini-Mental State Examination (MMSE), and found a significant association in all three stages: MMSE ≥20, MMSE 10–19, and MMSE <10 (21).
Studies used both cross-sectional and longitudinal association (n = 2 studies)
Two studies used both cross-sectional and longitudinal analysis (12, 28). In the study reported by Hiroyuki et al. a significant association was found only at cross-sectional level between lower functional autonomy and higher comorbidity burden measured by the CCI. Regarding the longitudinal analysis, a trend towards a significant association between CCI and subsequent decline in functional autonomy was reported after 6 months of follow-up with a β of −0.16 (95%CI [−0.76;0.03]) and p-value = 0.072.
In the study reported by Wubben et al. the CIRS-G total score was used to measure comorbidity burden (28). At a cross-sectional level, a significant association was found between lower functional autonomy and higher comorbidity burden. Regarding the longitudinal analysis, two associations were reported. When considering CIRS-G as a time invariant baseline covariate, it was significantly associated with functional autonomy decline over time with a B of −0.3 (SE = 0.12). Also, when considering CIRS-G as a time varying covariables, it was significantly associated with functional autonomy decline over time with B of −1.1 (SE = 0.23). However, the association was weaker when CIRS-G was considered as time invariant baseline covariate compared to when it was considered as time varying covariate.
Studies used only longitudinal association (n = 1 study)
The study reported by Solomon et al. examined the association between CIRS-G severity score and the relative annual rate of change in functional autonomy measured by both Katz bADL and Lawton iADL, and a trend towards a significant association was reported with respective OR of 2.7 (95%CI [0.7;9.6]) and 1.8 (95%CI [0.3;10.1]; p-value was not reported) (22).
Discussion
Overall, 12 studies reporting association between comorbidity index and functional autonomy were included in the systematic review, among which three were longitudinal. The majority of studies provide evidence that higher comorbidity index is associated with lower functional autonomy level in people with cognitive impairment.
Significant association was frequently reported by cross-sectional designs (12, 18, 19, 21, 28, 29, 33). When examining the studied relationship using longitudinal designs (12, 22, 28), findings varied. Associations that involved comorbidity burden as invariant over time to predict functional autonomy decline were either significant but weak (28) or found only a trend towards a significant effect (12, 22); in contrast, a longitudinal study reported by Wubben et al., in which both comorbidity burden and functional autonomy were repeatedly assessed and comorbidity burden was considered as a time-varying covariate, found a significant association (28). These findings suggest that the impact of comorbidity burden on functional autonomy may diminish over time, and therefore considering comorbidity burden as time-varying may provide a better explanation of its impact on functional autonomy decline over time. This is further supported by Leoutsakos et al. who investigated another outcome in AD, and who found in a longitudinal study that comorbidity burden when considered as time-varying may better explain cognitive decline than when it is considered as invariant (20).
Comorbidity burden and functional autonomy decline are both variable over time for various reasons (28, 34, 35). Interaction between diseases (36, 37) and the effect of treatments on the stability of each disease (38, 39, 40, 41) (whether individuals are treated or not, and whether they receive an appropriate treatment or not) are among factors that may increase fluctuation of comorbidity burden over time. Specifically, in people with cognitive impairment some factors may contribute to the variability over time of comorbidity burden as the poor level of treatment adherence and the lower access to health services (42). In addition to the progressive functional decline related to cognitive impairment, functional decline may be further accentuated by the dynamic nature of comorbidity burden in two ways (8, 16, 34, 43, 44): on the one hand some comorbidities have been directly associated with lower functional autonomy level independently from the cognitive state (8, 43, 44), and, on the other hand, comorbidity burden can further reduce indirectly functional autonomy level by exacerbating the current cognitive decline (16, 45). However, the methodology used by Wubben et al. seems to take into account the complexity of this relationship by two aspects (28): considering comorbidity burden as a time varying covariate may deal with the dynamic nature of comorbidity burden over time, and conducting repeated assessments during the follow-up using both comorbidity index and ADL scales may increase their sensitivity to reliably measure comorbidity burden and functional autonomy decline over time and better explain their relationship.
Another important point reported by this review is that significant association was frequently found when measuring comorbidity burden by either CIRS-G (18, 19, 28, 29) or GMHR (21, 33) compared to one study reported significant association using the CCI (12). Both CIRS-G and GMHR can consider medication use, the stability of diseases and some geriatric syndromes (depression, urinary incontinence and medication number) (46) to determine the severity level of comorbidity burden. In contrast, the CCI considers only weight related to each condition to determine severity level of comorbidity burden. There is no consensus in the literature regarding the best comorbidity index to measure comorbidity burden, but we believe that considering medication, the stability of diseases and geriatric syndromes may reliably measure the comorbidity burden. However, the limited number of included studies did not allow us to suggest which comorbidity index may better explain functional autonomy decline.
The most important limitation of the present study was the heterogeneity between studies (population, comorbidity indices, b/iADL scales, and design) that did not encourage us to perform a meta-analysis, but this systematic review suggests that an appropriate assessment of comorbidity burden and functional autonomy can elucidate the negative impact of comorbidity burden on functional autonomy decline. Another limitation was that the report of the comorbidity may not be exhaustive in individuals with cognitive impairment, which may affect the use of comorbidity indices in some included studies. To cope with this limitation, future studies may ameliorate the assessment of comorbidity burden by using different sources of information to gather medical conditions (prescriptions, caregivers/families and health care providers) as the case of GMHR.
In conclusion, a higher comorbidity index was associated with a lower level of functional autonomy in people with cognitive impairment. This relationship seems to be dynamic over time and using comorbidity indices and ADL scales only once may not deal with the fluctuation of both comorbidity burden and functional autonomy decline. To cope with complexity of this relationship this review highlights some methodological approaches to be considered. Functional autonomy decline detrimentally impacts life quality and heightens mortality risk in individual with cognitive impairment. In contrast, comorbidity burden represents a potentially modifiable factor, and effective management of comorbidities may mitigate the severity stages of functional autonomy decline.
Acknowledgments
Mohamed Nour Temedda (PhD student) is supported by “France Médéric d'Alzheimer” (Research scholarship). We thank the Dr Philip Robinson (Hospices Civils de Lyon) for help in manuscript preparation.
Electronic Supplementary Material
Supplementary material is available in the online version of this article at https://doi.org/10.14283/jpad.2024.51.
Supplementary material, approximately 15.2 KB.
Authors' contributions: Mohamed Nour Temedda: Conceptualization, Methodology, Data analysis, Writing - Original Draft. Antoine Garnier-Crussard: Writing - Review & Editing. Christelle Mouchoux: Conceptualization, Methodology, Analysis, Writing - Original Draft, Supervision. Virginie Dauphinot: Conceptualization, Methodology, Data analysis, Writing - Original Draft, Supervision.
Funding: None.
Conflict of Interest: The authors declare no competing interests; this manuscript has not been published or submitted elsewhere. All authors have contributed significantly, and all authors are in agreement with the content of the manuscript.
Ethical standards: Not applicable.
References
- 1.The Lancet Public Health Reinvigorating the public health response to dementia. Lancet Public Health. 2021;6(10):e696. doi: 10.1016/S2468-2667(21)00215-2. 10.1016/S2468-2667(21)00215-2 PubMed PMID: 34563278; PMCID 8516159. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Chen TB, Yiao SY, Sun Y, et al. Comorbidity and dementia: A nationwide survey in Taiwan. PLOS ONE. 2017;12(4) doi: 10.1371/journal.pone.0175475. 10.1371/journal.pone.0175475 PubMed PMID: 28403222; PMCID 5389824. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Poblador-Plou B, Calderón-Larrañaga A, Marta-Moreno J, et al. Comorbidity of dementia: a cross-sectional study of primary care older patients. BMC Psychiatry. 2014;14:84. doi: 10.1186/1471-244X-14-84. 10.1186/1471-244X-14-84 PubMed PMID: 24645776; PMCID 3994526. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Kao SL, Wang JH, Chen SC, Li YY, Yang YL, Lo RY. Impact of Comorbidity Burden on Cognitive Decline: A Prospective Cohort Study of Older Adults with Dementia. Dement Geriatr Cogn Disord. 2021;50(1):43–50. doi: 10.1159/000514651. 10.1159/000514651 PubMed PMID: 33789290. [DOI] [PubMed] [Google Scholar]
- 5.Vance D, Larsen KI, Eagerton G, Wright MA. Comorbidities and cognitive functioning: implications for nursing research and practice. J Neurosci Nurs. 2011;43(4):215–224. doi: 10.1097/JNN.0b013e3182212a04. 10.1097/JNN.0b013e3182212a04 PubMed PMID: 21796044. [DOI] [PubMed] [Google Scholar]
- 6.Stuck AE, Walthert JM, Nikolaus T, Büla CJ, Hohmann C, Beck JC. Risk factors for functional status decline in community-living elderly people: a systematic literature review. Social Science & Medicine. 1999;48(4):445–469. doi: 10.1016/s0277-9536(98)00370-0. 10.1016/S0277-9536(98)00370-0 [DOI] [PubMed] [Google Scholar]
- 7.Falvey JR, Gustavson AM, Price L, Papazian L, Stevens-Lapsley JE. Dementia, Comorbidity, and Physical Function in the Program of All-Inclusive Care for the Elderly. J Geriatr Phys Ther. 2019;42(2):E1–E6. doi: 10.1519/JPT.0000000000000131. 10.1519/JPT.0000000000000131 PubMed PMID: 28437317; PMCID 5650947. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Aubert CE, Kabeto M, Kumar N, Wei MY. Multimorbidity and long-term disability and physical functioning decline in middle-aged and older Americans: an observational study. BMC Geriatrics. 2022;22(1):910. doi: 10.1186/s12877-022-03548-9. 10.1186/s12877-022-03548-9 PubMed PMID: 36443663; PMCID 9703785. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Buckinx F, Peyrusqué E, Kergoat MJ, Aubertin-Leheudre M. Reference Standard for the Measurement of Loss of Autonomy and Functional Capacities in Long-Term Care Facilities. J Frailty Aging. 2023;12(3):236–243. doi: 10.14283/jfa.2023.4. PubMed PMID: 37493385. [DOI] [PubMed] [Google Scholar]
- 10.Slaughter SE, Hayduk LA. Contributions of environment, comorbidity, and stage of dementia to the onset of walking and eating disability in long-term care residents. J Am Geriatr Soc. 2012;60(9):1624–1631. doi: 10.1111/j.1532-5415.2012.04116.x. 10.1111/j.1532-5415.2012.04116.x PubMed PMID: 22985138. [DOI] [PubMed] [Google Scholar]
- 11.Nelis SM, Wu YT, Matthews FE, et al. The impact of co-morbidity on the quality of life of people with dementia: findings from the IDEAL study. Age Ageing. 2019;48(3):361–367. doi: 10.1093/ageing/afy155. 10.1093/ageing/afy155 PubMed PMID: 30403771. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Tanaka H, Nagata Y, Ishimaru D, Ogawa Y, Fukuhara K, Nishikawa T. Clinical factors associated with activities of daily living and their decline in patients with severe dementia. Psychogeriatrics. 2020;20(3):327–336. doi: 10.1111/psyg.12502. 10.1111/psyg.12502 PubMed PMID: 31883310. [DOI] [PubMed] [Google Scholar]
- 13.Rozzini R, Frisoni GB, Ferrucci L, et al. Geriatric Index of Comorbidity: validation and comparison with other measures of comorbidity. Age Ageing. 2002;31(4):277–285. doi: 10.1093/ageing/31.4.277. 10.1093/ageing/31.4.277 PubMed PMID: 12147566. [DOI] [PubMed] [Google Scholar]
- 14.Aslam F, Khan NA. Tools for the Assessment of Comorbidity Burden in Rheumatoid Arthritis. Front Med (Lausanne) 2018;5:39. doi: 10.3389/fmed.2018.00039. 10.3389/fmed.2018.00039 PubMed PMID: 29503820. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Marshall GA, Amariglio RE, Sperling RA, Rentz DM. Activities of daily living: where do they fit in the diagnosis of Alzheimer's disease? Neurodegener Dis Manag. 2012;2(5):483–491. doi: 10.2217/nmt.12.55. 10.2217/nmt.12.55 PubMed PMID: 23585777. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Haaksma ML, Vilela LR, Marengoni A, et al. Comorbidity and progression of late onset Alzheimer's disease: A systematic review. PLOS ONE. 2017;12(5) doi: 10.1371/journal.pone.0177044. 10.1371/journal.pone.0177044 PubMed PMID: 28472200; PMCID 5417646. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Tekin S, Fairbanks LA, O'Connor S, Rosenberg S, Cummings JL. Activities of daily living in Alzheimer's disease: neuropsychiatric, cognitive, and medical illness influences. Am J Geriatr Psychiatry. 2001;9(1):81–86. 10.1097/00019442-200102000-00013 PubMed PMID: 11156757. [PubMed] [Google Scholar]
- 18.Doraiswamy PM, Leon J, Cummings JL, Marin D, Neumann PJ. Prevalence and impact of medical comorbidity in Alzheimer's disease. J Gerontol A Biol Sci Med Sci. 2002;57(3):M173–M177. doi: 10.1093/gerona/57.3.m173. 10.1093/gerona/57.3.M173 PubMed PMID: 11867654. [DOI] [PubMed] [Google Scholar]
- 19.Oosterveld SM, Kessels RPC, Hamel R, et al. The influence of co-morbidity and frailty on the clinical manifestation of patients with Alzheimer's disease. J Alzheimers Dis. 2014;42(2):501–509. doi: 10.3233/JAD-140138. 10.3233/JAD-140138 PubMed PMID: 24898646. [DOI] [PubMed] [Google Scholar]
- 20.Leoutsakos JMS, Han D, Mielke MM, et al. Effects of general medical health on Alzheimer's progression: the Cache County Dementia Progression Study. Int Psychogeriatr. 2012;24(10):1561–1570. doi: 10.1017/S104161021200049X. 10.1017/S104161021200049X PubMed PMID: 22687143; PMCID 3573852. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Lyketsos CG, Galik E, Steele C, et al. The General Medical Health Rating: a bedside global rating of medical comorbidity in patients with dementia. J Am Geriatr Soc. 1999;47(4):487–491. doi: 10.1111/j.1532-5415.1999.tb07245.x. 10.1111/j.1532-5415.1999.tb07245.x PubMed PMID: 10203127. [DOI] [PubMed] [Google Scholar]
- 22.Solomon A, Dobranici L, Kåreholt I, Tudose C, Lăzărescu M. Comorbidity and the rate of cognitive decline in patients with Alzheimer dementia. Int J Geriatr Psychiatry. 2011;26(12):1244–1251. doi: 10.1002/gps.2670. 10.1002/gps.2670 PubMed PMID: 21500282. [DOI] [PubMed] [Google Scholar]
- 23.Melis RJF, Marengoni A, Rizzuto D, et al. The influence of multimorbidity on clinical progression of dementia in a population-based cohort. PLoS One. 2013;8(12) doi: 10.1371/journal.pone.0084014. 10.1371/journal.pone.0084014 PubMed PMID: 24386324; PMCID 3875493. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.PRISMA_update_protocol_20180214.pdf. Published online February 14, 2018. Accessed July 27, 2023.https://osf.io/https://osf.io/2v7mk
- 25.Nicholson K, Makovski TT, Griffith LE, Raina P, Stranges S, van den Akker M. Multimorbidity and comorbidity revisited: refining the concepts for international health research. J Clin Epidemiol. 2019;105:142–146. doi: 10.1016/j.jclinepi.2018.09.008. 10.1016/j.jclinepi.2018.09.008 PubMed PMID: 30253215. [DOI] [PubMed] [Google Scholar]
- 26.Falagas ME, Pitsouni EI, Malietzis GA, Pappas G. Comparison of PubMed, Scopus, Web of Science, and Google Scholar: strengths and weaknesses. FASEB J. 2008;22(2):338–342. doi: 10.1096/fj.07-9492LSF. 10.1096/fj.07-9492LSF PubMed PMID: 17884971. [DOI] [PubMed] [Google Scholar]
- 27.Ma LL, Wang YY, Yang ZH, Huang D, Weng H, Zeng XT. Methodological quality (risk of bias) assessment tools for primary and secondary medical studies: what are they and which is better? Military Medical Research. 2020;7(1):7. doi: 10.1186/s40779-020-00238-8. 10.1186/s40779-020-00238-8 PubMed PMID: 32111253; PMCID 7049186. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Wubben N, Haaksma M, Ramakers IHGB, et al. A comparison of two approaches for modeling dementia progression in a changing patient context. Int J Geriatr Psychiatry. 2022;37(5) doi: 10.1002/gps.5706. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.King LA, Priest KC, Nutt J, et al. Comorbidity and functional mobility in persons with Parkinson disease. Arch Phys Med Rehabil. 2014;95(11):2152–2157. doi: 10.1016/j.apmr.2014.07.396. 10.1016/j.apmr.2014.07.396 PubMed PMID: 25102383; PMCID 4322903. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Mariani E, Monastero R, Ercolani S, et al. Influence of comorbidity and cognitive status on instrumental activities of daily living in amnestic mild cognitive impairment: results from the ReGAl project. Int J Geriatr Psychiatry. 2008;23(5):523–530. doi: 10.1002/gps.1932. 10.1002/gps.1932 PubMed PMID: 18058828. [DOI] [PubMed] [Google Scholar]
- 31.van Rossum ME, Koek HL. Predictors of functional disability in mild cognitive impairment and dementia. Maturitas. 2016;90:31–36. doi: 10.1016/j.maturitas.2016.05.007. 10.1016/j.maturitas.2016.05.007 PubMed PMID: 27282791. [DOI] [PubMed] [Google Scholar]
- 32.Boltz M, Resnick B, Kuzmik A, et al. Pain Incidence, Treatment, and Associated Symptoms in Hospitalized Persons with Dementia. Pain Manag Nurs. 2021;22(2):158–163. doi: 10.1016/j.pmn.2020.08.002. 10.1016/j.pmn.2020.08.002 PubMed PMID: 32921569. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Samus QM, Mayer L, Onyike CU, et al. Correlates of functional dependence among recently admitted assisted living residents with and without dementia. J Am Med Dir Assoc. 2009;10(5):323–329. doi: 10.1016/j.jamda.2009.01.004. 10.1016/j.jamda.2009.01.004 PubMed PMID: 19497544; PMCID 2746023. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Meghani SH, Buck HG, Dickson VV, et al. The Conceptualization and Measurement of Comorbidity: A Review of the Interprofessional Discourse. Nurs Res Pract. 2013;2013 doi: 10.1155/2013/192782. PubMed PMID: 24187618; PMCID 3800641. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Wadley VG, Crowe M, Marsiske M, et al. Changes in everyday function among individuals with psychometrically defined Mild Cognitive Impairment in the ACTIVE Study. J Am Geriatr Soc. 2007;55(8):1192–1198. doi: 10.1111/j.1532-5415.2007.01245.x. 10.1111/j.1532-5415.2007.01245.x PubMed PMID: 17661957; PMCID 2153444. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Quiñones AR, Markwardt S, Thielke S, Rostant O, Vásquez E, Botoseneanu A. Prospective Disability in Different Combinations of Somatic and Mental Multimorbidity. J Gerontol A Biol Sci Med Sci. 2018;73(2):204–210. doi: 10.1093/gerona/glx100. 10.1093/gerona/glx100 PubMed PMID: 28541396. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Jiang X, Wang L, Morgenstern LB, Cigolle CT, Claflin ES, Lisabeth LD. New Index for Multiple Chronic Conditions Predicts Functional Outcome in Ischemic Stroke. Neurology. 2021;96(1):e42–e53. doi: 10.1212/WNL.0000000000010992. 10.1212/WNL.0000000000010992 PubMed PMID: 33024024; PMCID 7884978. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Zhuang S, Wang HF, Li J, Wang HY, Wang X, Xing CM. Renin-angiotensin system blockade use and risks of cognitive decline and dementia: A meta-analysis. Neurosci Lett. 2016;624:53–61. doi: 10.1016/j.neulet.2016.05.003. 10.1016/j.neulet.2016.05.003 PubMed PMID: 27163195. [DOI] [PubMed] [Google Scholar]
- 39.Tully PJ, Hanon O, Cosh S, Tzourio C. Diuretic antihypertensive drugs and incident dementia risk: a systematic review, meta-analysis and meta-regression of prospective studies. J Hypertens. 2016;34(6):1027–1035. doi: 10.1097/HJH.0000000000000868. 10.1097/HJH.0000000000000868 PubMed PMID: 26886565. [DOI] [PubMed] [Google Scholar]
- 40.Fox C, Smith T, Maidment I, et al. Effect of medications with anti-cholinergic properties on cognitive function, delirium, physical function and mortality: a systematic review. Age Ageing. 2014;43(5):604–615. doi: 10.1093/ageing/afu096. 10.1093/ageing/afu096 PubMed PMID: 25038833. [DOI] [PubMed] [Google Scholar]
- 41.Liu L, Jia L, Jian P, et al. The Effects of Benzodiazepine Use and Abuse on Cognition in the Elders: A Systematic Review and Meta-Analysis of Comparative Studies. Front Psychiatry. 2020;11 doi: 10.3389/fpsyt.2020.00755. 10.3389/fpsyt.2020.00755 PubMed PMID: 33093832; PMCID 7527532. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Bunn F, Burn AM, Goodman C, et al. Comorbidity and dementia: a scoping review of the literature. BMC Medicine. 2014;12(1):192. doi: 10.1186/s12916-014-0192-4. 10.1186/s12916-014-0192-4 PubMed PMID: 25358236; PMCID 4229610. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Castellanos-Perilla N, Borda MG, Fernández-Quilez Á, Aarsland V, Soennesyn H, Cano-Gutiérrez CA. Factors associated with functional loss among community-dwelling Mexican older adults. Biomedica. 2020;40(3):546–556. doi: 10.7705/biomedica.5380. 10.7705/biomedica.5380 PubMed PMID: 33030833; PMCID 7666859. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Gardener EA, Huppert FA, Guralnik JM, Melzer D. Middle-aged and mobility-limited: prevalence of disability and symptom attributions in a national survey. J Gen Intern Med. 2006;21(10):1091–1096. doi: 10.1111/j.1525-1497.2006.00564.x. 10.1111/j.1525-1497.2006.00564.x PubMed PMID: 16970558; PMCID 1831629. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Valletta M, Vetrano DL, Calderón-Larrañaga A, et al. Association of mild and complex multimorbidity with structural brain changes in older adults: A population-based study. Alzheimers Dement. Published online January 3, 2024. [DOI] [PMC free article] [PubMed]
- 46.Canaslan K, Ates Bulut E, Kocyigit SE, Aydin AE, Isik AT. Predictivity of the comorbidity indices for geriatric syndromes. BMC Geriatr. 2022;22(1):440. doi: 10.1186/s12877-022-03066-8. 10.1186/s12877-022-03066-8 PubMed PMID: 35590276; PMCID 9118684. [DOI] [PMC free article] [PubMed] [Google Scholar]
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