Relationship between potential inappropriate medications use and cognitive frailty among older adults in the community: mediating and moderating effects of depression

doi:10.21203/rs.3.rs-4809305/v1

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Research Article

Relationship between potential inappropriate medications use and cognitive frailty among older adults in the community: mediating and moderating effects of depression

https://doi.org/10.21203/rs.3.rs-4809305/v1

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Background

Both cognitive frailty and potentially inappropriate medications use are relatively highly prevalent among older adults in the community, and whether depression plays a mediating and regulating role in this process remains to be further explored.

Objective

To examine the association between PIMs and CF among older adults in the community and to explore the mediating and regulating roles of depression.

Methods

From March to July 2022, a multistage sampling method was used to sample older adults in Hefei, Anhui, China. The Montreal Basic Cognitive Assessment Scale, Comprehensive Frailty Assessment Instrument, 2017 Criteria for Potentially Inappropriate Medications for Older Adults in China and Geriatric Depression Scale were used to assess 237 older adults in the community.

Results

The average number of PIMs taken by these participants was 2.19. PIMs and depression are important factors of CF (P < 0.01), and depression had a significant moderating effect on this factor (β = 0.107, P < 0.01). Moreover, after controlling for confounding factors, depression could regulate the relationship between PIMs and CF. Simple slope analysis revealed that the effect of PIMs on CF in individuals with low-level depression (β = 0.631, P < 0.001) was significantly greater than that in those with high-level depression (β = 0.165, P > 0.01). Specifically, when depression scores were greater than 8.550, the association between PIMs and CF disappeared.

Conclusion

The prevalence of CF and PIMs was greater among older adults. Depression has a synergistic effect on the occurrence of PIMs and CF. To decrease the prevalence of CF and delay the progression of dementia in this population by reducing the prevalence of PIMs, community-based health efforts should be made to strengthen screening for CF, enhance the identification of CF related to medication use, pay attention to the depressive state of this group, and actively promote the review and management of community drugs.

Potentially inappropriate medication

Cognitive frailty

Moderating effect

Mediating effect

Depression

Frailty is a clinical syndrome characterized by reduced physiological reserves and multiple system disorders that limit an individual's ability to cope internally and externally and to maintain a stable internal environment^[1]. CF is a clinical syndrome characterized by both physical frailty and mild cognitive impairment (MCI), excluding Alzheimer's disease (AD) and other types of dementia, and is an independent dimension of frailty syndrome^[2]. Older adults with CF often experience reduced quality of life, increased drug dependence or hospitalization and are prone to negative emotions^[3]. Among them, depression, a common negative emotion in older adults, has been widely studied because of its controllable and reversible nature^[4].

Multiple studies have shown that PIMs is an important risk factor for frailty^[5–6]. PIMs are drugs whose effectiveness has not been established and/or where the risk of adverse drug events exceeds the expected clinical benefit and where there is a lack of safer alternatives^[7]. Studies have shown that the prevalence of PIMs use among older adults worldwide ranges from 18.8–59.4%^[8]. The elderly population is vulnerable to PIMs, which can accelerate cognitive decline, increase the risk of hospital admission and readmission, and reduce quality of life, and has been used as a key predictor of death^[9–10]. In view of the high prevalence and harm of PIMs, various countries have developed PIMs evaluation criteria, the most commonly used of which are the Beers criteria^[11] and the screening tool for older persons’ prescriptions/screening tool to alert them to the right treatment (STOPP/START)^[12]. On this basis, China has also compiled the criteria for potentially inappropriate medication for older adults in China^[13]. The criteria to be applied to adults 60 years old and older in all ambulatory, acute, and institutionalized settings of care, except hospice and end-of-life care settings. The more common PIMs are anticholinergics and sedatives^[14]. In particular, those drugs with potential effects on the central nervous system can increase the risk of cognitive impairment, and a review of PIMs use and the prescription of these drugs may be an effective way to improve cognitive function^[15].

It has been widely reported that cognitive decline in older adults is often accompanied by severe depressive symptoms^[16]. A meta-analysis of 15 studies revealed that cognitive frailty in older adults was associated with a greater risk of depression (OR = 2.06, 95% CI = 1.72–2.48, p = 0.001), and the overall prevalence of depression was 46% in cognitively frail patients^[17]. Depression can affect the lifestyle of older people, who often prefer to be alone at home and rarely participate in social activities and physical exercise. Long-term depression causes a series of declines in physical function, which can cause older adults to take a large number of drugs for treatment. According to statistics, antidepressants account for a larger proportion of PIMs taken by older adults^[18]. Therefore, depression is a mediating factor that may cause older adults to take more PIM and may lead to the development of CF. However, no research has examined the process by which PIMs exacerbates CF through depression.

In summary, we hypothesize that depressive symptoms may exacerbate the harmful effect of PIMs on CF. To improve our understanding of the interplay of depressive symptoms with CF and PIMs, we examined the mediating and moderating roles that different levels of depression play in the relationship between CF and PIMs among older adults.

Study design and sample

This study was designed as a cross-sectional study and was reported in accordance with strengthening the reporting of observational studies in epidemiology (STROBE).

This study was performed in Hefei, Anhui, China, from March 2021 to December 2021. The specific sampling methods were as follows: (1) taking Hefei city as the sampling pool, three streets were randomly selected from 12 streets by drawing lots; (2) with the street as the center and the residential community under its jurisdiction as the sampling range, one community was randomly selected from each street, and a total of three communities were selected; and (3) with the cooperation of the neighborhood committees and other departments, a convenient sampling method was adopted to set up investigation points in the activities organized by the community housing committees (community health records, health knowledge education lectures and related studies, etc.) and to go deep into the activity centers (community elderly life movement center, university for elderly individuals, social work activity center, free clinic activity, etc.). This study was approved by the institutional review board of the researchers’ hospital. All the participants provided written informed consent. A total of 237 older adults were included in our final sample.

Measures

Cognitive Frailty

The Comprehensive Frailty Assessment Instrument (CFAI) was used to assess frailty in older adults^[19]. The CFAI scale contains 23 items in 4 dimensions, which can be used to evaluate physical frailty, psychological frailty, social frailty and environmental frailty. The total CFAI score ranges from 20 to 97 points, the physical frailty score ranges from 4 to 12 points; a score ≤ 4 points indicates no physical frailty, and a higher score indicates greater severity. The Cronbach's alpha coefficient of the scale was 0.77 for the physical subscale, and the composite reliability coefficient was 0.70 for the total scale, indicating good reliability^[20].

The MoCA-B is a 30-point test that assesses nine cognitive domains (executive function, language, orientation, calculation, conceptual thinking, memory, visual perception, naming and attention)^[21]. According to the first validation study in China from Qihao Guo, the MOCA-B scale identified the MCI demarcation score according to the different education levels as illiterate and primary school (educational time ≤ 6 years) < 19 points, secondary school (duration of education is 7–12 years) < 22 points, and university (educational time > 12 years) < 24 points^[22]. To correct the deviation caused by education level, if the subject had less than 4 years of education, 1 point was added. If the subject is illiterate, regardless of the number of years of education, the total score will increase by 1 point, with a maximum score of 30 points. The Chinese version of the MoCA-B scale has been revised according to the cultural background and living habits of the Chinese population and has good reliability and validity; the Cronbach's alpha coefficient was 0.86, and the criterion validity was 0.86^[23].

We used the above two scales for assessment and classified the subjects with both physical frailty and MCI as having CF.

Potentially Inappropriate Medication

The 2017 criterion of potentially inappropriate medication for older adults in China was adopted for evaluation in combination with drug use records of the subjects^[13]. The criteria consisted of two parts: (1) PIMs criteria for older adults, including 72 types/classes of drugs in 13 categories; and (2) PIMs criteria for older adults under disease states, including 44 drugs/classes of 27 disease states. Data collection was carried out with the assistance of community staff. For the subjects who had been included in community chronic disease management, their individual drug use in the past 100 days was collected by consulting their health records, including their drug name, dosage and reason for administration. For subjects not included in community chronic disease management, the investigator spoke with the subject and/or the caregiver to collect the corresponding information and checked the subject's medicine bottles (boxes) for information verification.

Depressive symptoms

The short-form Chinese Geriatric Depression Scale (GDS-15) was adopted to assess the depressive symptoms of the subjects. This scale consists of 15 items, each item scoring 1 or 0 points, with the total score ranging from 0 to 15^[24]. The cut-off value for the definition of depressive symptoms was 5 points or more, and a higher score indicated more severe depressive symptoms. According to a previous study, the reliability and validity of this scale were good, with a Cronbach's alpha coefficient of 0.790 and a retest reliability of 0.730^[25].

Control variables

We used a general data questionnaire to collect sociodemographic data from the participants.

ics, lifestyle indicators, and physical function status of the subjects.

The social demographic characteristics included sex, age, education level, residential status, economic status, and social network status^[26].

Lifestyle indicators, including smoking status and alcohol consumption.

Physical function status, including body mass index (BMI), nutritional status, activities of daily living (ADL), upper limb muscle strength function, lower limb muscle strength function, and physical disease. Nutritional status was assessed using the Short-form Mini-nutritional Assessment (MNA-SF), for which the full score was 14 points, a score ≥ 11 was classified as normal nutrition, and a score < 11 was classified as malnutrition^[27]. The Barthel Index (BI), developed by Barthel scholars in 1965, was used to assess the activities of daily living of the subjects^[28]. According to the method proposed by the American Association of Hand Therapists, upper limb muscle strength is evaluated by grip strength, the dominant hand grip strength of older adults is measured 3 times, and the average value is taken^[29]. The short physical performance battery (SPPB) was used to evaluate the muscle strength of the lower limbs. The SPPB included balance ability, walking speed, and chair sitting and standing. The score of each item ranged from 0–4 points, and the total score ranged from 0–12 points^[30]. The Charlson comorbidity index (CCI) was used to assess physical disease^[31].

Analysis

All analyses were performed with SPSS v 26.0 (SPSS Inc., Chicago, IL, USA), and P < 0.05 was considered to indicate statistical significance.

Count data are presented as frequencies and percentages. Normally distributed data were described statistically by means of means and standard deviations. Nonnormally distributed measurement data are presented as medians and quartiles. Multiple linear regression analysis was used to verify the influencing factors in older adults with CF. Model 4 of the PROCESS plug-in in SPSS software was used to analyse and test the mediating effect. The bootstrap method (repeated sampling 5,000 times) was used to estimate the 95% confidence intervals. If 0 was not included, it indicated that the mediation effect was significant. Model 1 of the PROCESS plug-in in SPSS software was used to analyse the moderating effect of depression. A simple slope analysis method was used to determine the level of the moderating effect by taking the mean of depression plus or minus one standard deviation to further verify the moderating effect of different levels of depression. We then used the Johnson‒Neyman technique to explore the boundary value of the conditional effect of depression and the range of depression that significantly interact with CF. All models were adjusted for potential covariates.

Participant characteristics (Table 1)

The participants had an average age of 75.46 years, and 119 were female (50.2%). They received an average of 4.55 years of schooling. A majority of older adults (62.4%) had a job and had high levels of monthly income (56.5%). Most of the older adults (94.8%) lived with their family, and most did not smoke (81.4%) or drink (84.0%).

The authors reported a median score of 6 for comorbidities, and 34.6% of the participants were malnourished. The median score was 6 for the SPPB and 17.33 for the grip. The participants reported a median score of 16 for social networks and for the MoCA-B and 85 for the BI. For the participants, the median score was 8 for physical frailty and 5 for depression. The average number of PIMs taken by these participants was 2.19. Finally, the results of this study also showed that the top three PIMs taken were clopidogrel (89 patients), EZ (76 patients), and spironolactone (45 patients), and a total of 27 study subjects took PIMs that should be taken cautiously or avoided under disease conditions, including aspirin (21 patients) and glucocorticoids (6 patients).

Table 1

Characteristics of the Sample
Variables	n (%)	Variables	Mean ± sd or Median (quartile)
Gender		Age(years)	75.46 ± 7.75
Male	118 (49.8)	Years of schooling	4.55 ± 4.71
Female	119 (50.2)	PIMs	2.19 ± 1.36
Job		BMI	22.85 ± 3.40
Yes	148 (62.4)	CCI	6 (5, 8)
No	89 (37.6)	Grip	17.33 (13.30, 21.23)
Living condition		MoCA-B	16 (15, 19)
Live alone	17 (7.2)	BI	85 (70, 95)
Living with family	220 (92.8)	Physical Frailty	8 (6, 10)
Smoking		GDS	5 (2, 8)
Yes	44 (18.6)	Social network	16 (12, 20)
No	193 (81.4)	SPPB	6 (3, 8)
Drinking
Yes	38 (16.0)
No	199 (84.0)
Monthly income
Hight¹	134 (56.5)
Low²	103 (43.5)
Nutritional status
Normal	155 (65.4)
Malnutrition	82 (34.6)
1 = monthly income\(\:\ge\:\)5000; 2=monthly income<5000

Factors influencing CF

The multiple linear regression model takes CF as the dependent variable, and the tolerance of each variable is greater than 0.1, suggesting that there is no serious multiple collinearity between the variables. Model calibration yielded R² = 0.596, F = 17.846, and P < 0.01, indicating that the model fit was statistically significant. The results showed that the SPPB score, social network score, MoCA-B score, BI score, GDS score, and PIMs score are influencing factors of CF.

Table 2

Multiple linear regression model for old adults with CF
variables	B	SE	Beta	t	P
Constant	6.860	1.943		3.531	.001
Age	− .010	.015	− .037	− .643	.521
Gender	.433	.229	.106	1.885	.061
Years of schooling	− .014	.026	− .033	− .549	.583
Job	− .156	.275	− .037	− .565	.573
Living condition	.498	.355	.063	1.403	.162
Smoking	.537	.363	.103	1.480	.140
Drinking	− .003	.368	.000	− .007	.994
Monthly income	.023	.257	.006	.091	.928
Nutritional status	− .204	.247	− .048	− .825	.410
CCI	.047	.045	.064	1.048	.296
SPPB	− .087	.040	− .142	-2.171	.031
BMI	.051	.029	.086	1.768	.078
Grip	− .009	.020	− .024	− .464	.643
Social network	− .048	.021	− .123	-2.300	.022
MoCA-B	.066	.032	.092	2.032	.043
BI	− .029	.009	− .218	-3.189	.002
GDS	.119	.035	.213	3.394	.001
PIMs	.371	.090	.247	4.131	.000

Mediating effects of depression on PIMs and CF

Model 4 in PROCESS was adopted to conduct a bootstrap test on the mediating effect of depression between PIMs and CF. The results showed that after various control factors were included, the indirect effect of depression was 0.079, and the bootstrap 95% CI was 0.022 (0.161). The absence of 0 indicated that the total indirect effect was significant, and the mediation action path diagram is shown in Fig. 1. Since the direct effect of PIMs on CF was also significant, depression had an incomplete mediating effect on the relationship between PIMs and CF. The mediating effect accounts for 16.26% of the total indirect effect. The detailed results are shown in Table 3 and Table 4.

Table 3

Regression analysis of the relationships between variables in the mediation model
variables	Model 1			Model 2			Model 3
variables	β 非 χ2	t	P	β 非 c2	t	P	β 非 c2	t	P
PIMs 不服用	0.486	6.118	0.000	0.740	4.867	0.000	0.406	4.970	0.000
GDS 服用							0.107	3.184	0.002
R²	0.554			0.493			0.573
F	57.500			44.931			51.502

Model 1: the influence of the independent variable on the mediating variable; Model 2: the influence of the independent variable on the dependent variable; Model 3: the influence of the independent variable and mediating variable on the dependent variable.

Table 4

Bootstrap tests for mediating effects of depression
	Bootstrapped distribution
		Effect	SE	LLCI	ULCI	Ratios of total effect
		Effect	SE	(Bias-corrected 95% CI)		Ratios of total effect
total effect	0.486	0.079	0.330	0.642
direct effect	0.406	0.082	0.245	0.567
Indirect effect	0.079	0.036	0.022	0.161	16.26%

Moderating effects of depression on PIMs and CF

Model 1 in PROCESS was used to conduct a bootstrap test on the moderating effect of depression on PIMs and CF. The results showed that after various control factors were included, the coefficient of the interaction term depression ×PIMs was significant (β=-0.064, P < 0.05). Simple slope analysis revealed that the effect of PIMs on CF was significantly greater in individuals with low depression (β = 0.631, P < 0.001) than in those with high depression (β = 0.165, P > 0.05), as shown in Fig. 2.

The Johnson–Neyman plot showed that the correlation between PIMs and CF gradually decreased with increasing depression score, suggesting that the adverse effects of PIMs on CF gradually decreased with increasing depression score. Specifically, when depression scores were greater than 8.550, the association between PIMs and CF disappeared, as shown in Fig. 3.

In this study, CF was regarded as an adverse health outcome of older adults in the community, and the relationship between PIMs and CF in older adults in the community was explored. In addition, by controlling for confounding factors, the contribution of depression factors to the effect of PIMs on CF was explored.

A cross-sectional retrospective study of 1,853 older adults who regularly visited the ambulatory care setting for PIMs screening showed that almost one out of two individuals used PIMs^[32]. Our study is similar to previous studies, and the results show that PIMs is a significant factor causing CF, and the average number of PIMs is 2 or more. Our study also revealed that the three most common PIMs were clopidogrel (89 patients), EZ (76 patients), and spironolactone (45 patients). Because of poor physical function, older adults with CF often suffer from a variety of chronic diseases and receive a variety of drugs. Most older adults with cardiovascular and cerebrovascular diseases and sleep disorders often use these two drugs or a combination of drugs for treatment, but these drugs also increase the occurrence of muscle loss, falls, depression and other adverse drug reactions, further aggravating cognitive frailty. At the same time, there are different degrees of cognitive function decline, which makes it more common for patients to mistake, miss, or overdose drugs. In addition, in the primary medical care environment, medical staff do not pay enough attention to PIMs or take effective management measures.

Due to decreases in the plasma levels of transforming growth factor and brain-derived neurotrophic factor and hippocampal atrophy, the cognitive function of people with depression is significantly decreased^[33]. In addition, an increase in depression will seriously change the lifestyle habits of elderly people, resulting in a decrease in social activities and a corresponding lack of physical exercise, aggravating physical weakness. The results of this study are similar to those of previous studies^[34], and depression can significantly aggravate CF. The mediation model test revealed that depression played an incomplete mediating role between PIMs and CF. Due to the long-term increase in depression in this population, a series of symptoms or diseases may develop, increasing medical behaviour and drug use, and the hospital lacks effective drug supervision, thereby increasing PIMs exposure and CF. Therefore, community health care workers should pay attention to the emotional changes of older adults with CF and strengthen health education for their families so that they can develop correct disease cognition and identify signs of depression to help older adults improve negative emotions, increase medical cooperation, promote social participation, and delay the progression of CF.

After controlling for SPPB, social network, MoCA-B, and BI scores, the predictive effect of PIMs on CF was moderated by depressive status. As the level of depression in older adults increased, the degree of influence of PIM on CFs gradually decreased. This may be because when older adults initially have cognitive or physical function decline, they tend to participate less in social activities and are reluctant to socialize and lack corresponding physical exercise. These factors can easily cause older adults to be relatively lonely, accompanied by various negative emotions, such as silence, indifference, and depression. Therefore, as the severity of depression continues to increase, older adults exhibit reduced activity, decreased ability to live daily, and decreased cognitive function, which leads to the development of corresponding diseases and increased PIMs use. In addition, this study revealed that when depression scores were above 8, that is, when older adults had moderate or severe depression, the effect of PIMs on CF disappeared. The more depressed an older adult is, the worse his or her cognitive and physical function will be. Older adults at this stage may not be exposed to PIM because of depression but because of a range of clinical syndromes caused by various disease factors. Therefore, it is necessary to increase the sample size in the future to continue to explore the moderating effect of different levels of depression on the role of PIMs in CF.

Community health workers should also focus on elderly people who live alone, are widowed, have low income status, have low participation in social activities, and have poor physical functioning. This population should be encouraged to actively participate in physical exercise, such as aerobic exercise and progressive resistance training^[35], and carry out various forms of social activities, such as playing traditional music, musical instruments, singing nostalgic songs and dancing^[36], to increase the social participation of older adults and reduce the incidence of depression and other negative emotions. For older adults with severe depression, community medical workers should improve the management of health records, strengthen disease monitoring, and use relaxation therapy^[37], mindfulness-based stress reduction^[38] and other means to reduce depression. Finally, due to the high rate of PIMs use among elderly people with CF and its significant harmfulness, community health care workers should undergo drug screening as the key component of CF management and regular follow-up to detect adverse drug reactions. At the same time, we should perform good chronic disease archive management and choose nondrug intervention methods for chronic diseases that can be prevented and controlled.

Limitations

The limitations of this study include that the survey was only conducted in a city in China, which limits the representativeness of the sample and the generalizability of our findings. This was a cross-sectional design that limited the understanding of directional relationships; thus, future longitudinal prospective research is needed. In addition, the 15-item Geriatric Depression Scale (GDS-15) was used to screen for depressive symptoms, not to diagnose depression. Finally, this may be due to the limited sample size. Our study concluded that there was no moderating effect when depression levels were high.

This study suggested that depression may act as an important mediator of the relationship between PIMs and CF and may act as an external resource that older adults can rely on to cope with PIM and its impact on CF. This study can strengthen the early recognition of depression in the elderly population by community medical workers, increase awareness of drug supervision, and provide guidance for the construction of feasible cognitive frailty management strategies.

Ethical statements

This study was approved by the Ethics Committee of PLA Joint Logistic Support Force No.901 Hospital (approval number: 901YYLL2021019), Patients were consented by an informed consent process that was reviewed by the Ethics Committee of PLA Joint Logistic Support Force No.901 Hospital and certify that the study was performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki.

Funding

This work is supported by National Natural Science Foundation of China (Grant No. 72274136).

Author Contribution

SW, QX and YS conceived and designed the study. SW, QX, LW drafted and edited the manuscript. All authors aided in revising this manuscript for intellectual content and approved the final version to be published. All authors read and approved the final manuscript.

Acknowledgements

Not applicable.

Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol Biol Sci Med Sci. 2001;56(3):M146–56.
Sugimoto T, Arai H, Sakurai T. An update on cognitive frailty: Its definition, impact, associated factors and underlying mechanisms, and interventions. Geriatr Gerontol Int. 2022;22(2):99–109.
Qiu Y, Li G, Zheng L, Liu W, Li X, Wang X, et al. Relationship Between Cognitive Frailty and Mortality in Older Adults: A Systematic Review and Meta-Analysis. J Am Med Dir Assoc. 2023;24(11):1637–44.
Gómez-Gómez I, Motrico E, Moreno-Peral P, Casajuana-Closas M, López-Jiménez T, Zabaleta-Del-Olmo E, et al. A multiple health behaviour change intervention to prevent depression: A randomized controlled trial. Gen Hosp Psychiatry. 2023;82:86–94.
Ma W, Wang H, Wen Z, Liu L, Zhang X. Potentially inappropriate medication and frailty in older adults: A systematic review and meta-analysis. Arch Gerontol Geriatr. 202;114:105087.
Porter B, Arthur A, Savva GM. How do potentially inappropriate medications and polypharmacy affect mortality in frail and nonfrail cognitively impaired older adults? A cohort study. BMJ Open. 2019;14(5):e026171.
Gobbens RJ, van Assen MA, Luijkx KG, Wijnen-Sponselee MT, Schols JM. The Tilburg Frailty Indicator: psychometric properties. J Am Med Dir Assoc. 2010;11(5):344–55.
Tian F, Chen Z, Zeng Y, Feng Q, Chen X. Prevalence of Use of Potentially Inappropriate Medications Among Older Adults Worldwide: A Systematic Review and Meta-Analysis. JAMA Netw Open. 2023;6(8):e2326910.
Harasani K, Xhafaj D, Begolli A, Olvera-Porcel MC. Prevalence of potentially inappropriate prescriptions in primary care and correlates with mild cognitive impairment. Pharm Pract (Granada). 2020;18(3):2017.
Bayliss EA, Shetterly SM, Drace ML, Norton J, Green AR, Reeve E, et al. The OPTIMIZE patient- and family-centered, primary care-based deprescribing intervention for older adults with dementia or mild cognitive impairment and multiple chronic conditions: study protocol for a pragmatic cluster randomized controlled trial. Trials. 2020;21(1):542.
The 2023 American Geriatrics Society Beers Criteria® Update Expert Panel. American Geriatrics Society 2023 updated AGS Beers Criteria® for potentially inappropriate medication use in older adults. J Am Geriatr Soc. 2023;71(7):2052–81.
O'Mahony D, O'Sullivan D, Byrne S, O'Connor MN, Ryan C, Gallagher P. STOPP/START criteria for potentially inappropriate prescribing in older people: version 2. Age Ageing. 2015;44(2):213–8.
Chinese Society of Geriatric Health Medicine, senile Rational Drug Use Branch. Criteria of potentially inappropriate medications for older adults in China. Adverse Drug React J. 2018;20(1):2–8.
Hasan SS, Burud IAS, Kow CS, Rasheed MK, Chan KSC, Tay PK, et al. Use of potentially inappropriate medications among older outpatients and inpatients in a tertiary care hospital in Malaysia. Int J Clin Pract. 2021;75(3):e13714.
Dos Santos ANM, Farias-Itao DS, Benseñor IM, Goulart AC, Brunoni AR, Viana MC, et al. Potentially inappropriate medications and cognitive performance: cross-sectional results from the ELSA-Brasil study. Eur J Clin Pharmacol. 2023;79(7):927–34.
Zhou L, Ma X, Wang W. Relationship between Cognitive Performance and Depressive Symptoms in Chinese Older Adults: The China Health and Retirement Longitudinal Study (CHARLS). J Affect Disord. 2021;281:454–8.
Zou C, Yu Q, Wang C, Ding M, Chen L. Association of depression with cognitive frailty: A systematic review and meta-analysis. J Affect Disord. 2023;320:133–9.
Wolff J, Reißner P, Hefner G, Normann C, Kaier K, Binder H, et al. Pharmacotherapy, drug–drug interactions and potentially inappropriate medication in depressive disorders. PLoS ONE. 2021;16(7):e0255192.
De Witte N, Gobbens R, De Donder L, Dury S, Buffel T, Schols J, et al. The comprehensive frailty assessment instrument: development, validity and reliability. Geriatr Nurs. 2013;34(4):274–81.
Qiao X, Wang C, Tian X, Dong L, Liu N, Jin Y, et al. Cross-cultural adaptation and validation of the Comprehensive Frailty Assessment Instrument in Chinese community-dwelling older adults. Geriatr Gerontol Int. 2018;18(2):301–7.
Julayanont P, Tangwongchai S, Hemrungrojn S, Tunvirachaisakul C, Phanthumchinda K, Hongsawat J, et al. The Montreal Cognitive Assessment-Basic: A Screening Tool for Mild Cognitive Impairment in Illiterate and Low-Educated Elderly Adults. J Am Geriatr Soc. 2015;63(12):2550–4.
Chen KL, Xu Y, Chu AQ, Ding D, Liang XN, Nasreddine ZS, et al. Validation of the Chinese Version of Montreal Cognitive Assessment Basic for Screening Mild Cognitive Impairment. J Am Geriatr Soc. 2016;64(12):e285–90.
Dandan Wang. The diagnostic value of the Chinese version of MoCA-B scale in mild cognitive impairment in people over 50 years old in Jiaxing City. Bengbu: Bengbu Medical College; 2018.
Sheikh JI, Yesavage JA. Geriatric depression scale (GDS): recent evidence and development of a shorter version. Clin Gerontologist. 1986;5(1):165–73.
Tang Dan. Application of Short Form Geriatric Depression Scale (GDS-15) In Chinese Elderly. Chin J Clin Psychol. 2013;21(03):402–5.
Lubben J, Blozik E, Gillmann G, Iliffe S, von Renteln Kruse W, Beck JC, et al. Performance of an abbreviated version of the Lubben Social Network Scale among three European community-dwelling older adult populations. Gerontologist. 2006;46(4):503–13.
Rubenstein LZ, Harker JO, Salvà A, Guigoz Y, Vellas B. Screening for undernutrition in geriatric practice: developing the short-form mini-nutritional assessment (MNA-SF). J Gerontol Biol Sci Med Sci. 2001;56(6):M366–72.
Mahoney FI, Barthel DW. Functional evaluation: the barthel index. Md State Med J. 1965;14:61–5.
Fesseec S. Clinical assessment recommendations. 2nd ed. Chicago: American Society of Hand Therapists; 1992. pp. 41–5.
Guralnik JM, Simonsick EM, Ferrucci L, Glynn RJ, Berkman LF, Blazer DG, et al. A short physical performance battery assessing lower extremity function: association with self-reported disability and prediction of mortality and nursing home admission. J Gerontol. 1994;49(2):M85–94.
Charlson M, Szatrowski TP, Peterson J, Gold J. Validation of a combined comorbidity index. J Clin Epidemiol. 1994;47(11):1245–51. e.
Alwhaibi M. Potentially Inappropriate Medications Use among Older Adults with Comorbid Diabetes and Hypertension in an Ambulatory Care Setting. J Diabetes Res. 2022;2022:1591511.
Price RB, Duman R. Neuroplasticity in cognitive and psychological mechanisms of depression: an integrative model. Mol Psychiatry. 2020;25(3):530–43.
Zou C, Yu Q, Wang C, Ding M, Chen L. Association of depression with cognitive frailty: A systematic review and meta-analysis. J Affect Disord. 2023;320:133–9.
Rodrigues F, Domingos C, Monteiro D, Morouço P. A Review on Aging, Sarcopenia, Falls, and Resistance Training in Community-Dwelling Older Adults. Int J Environ Res Public Health. 2022;19(2):874.
Saredakis D, Keage HAD, Corlis M, Loetscher T. Virtual reality intervention to improve apathy in residential aged care: protocol for a multisite non-randomised controlled trial. BMJ Open. 2021;11(2):e046030.
McPhillips MV, Li J, Petrovsky DV, Brewster GS, Ward EJ 3rd, Hodgson N, et al. Assisted Relaxation Therapy for Insomnia in Older Adults With Mild Cognitive Impairment: A Pilot Study. Int J Aging Hum Dev. 2023;97(1):65–80.
Yildirim D, Çiriş Yildiz C, Ozdemir FA, Harman Özdoğan M, Can G. Effects of a Mindfulness-Based Stress Reduction Program on Stress, Depression, and Psychological Well-being in Patients With Cancer: A Single-Blinded Randomized Controlled Trial. Cancer Nurs. 2024;47(2):E84–92.

No competing interests reported.

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Relationship between potential inappropriate medications use and cognitive frailty among older adults in the community: mediating and moderating effects of depression

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Abstract

Figures

Introduction

Methods

Study design and sample

Measures

Cognitive Frailty

Potentially Inappropriate Medication

Depressive symptoms

Control variables

Analysis

Results

Participant characteristics (Table 1)

Factors influencing CF

Mediating effects of depression on PIMs and CF

Moderating effects of depression on PIMs and CF

Discussion

Limitations

Conclusions and implications

Declarations

Ethical statements

Funding

Author Contribution

Acknowledgements

References

Additional Declarations

Supplementary Files

Status:

Version 1