The Relationship Between Multimorbidity and Types of Chronic Diseases and Self-Rated Memory

Abstract

This study explores the impact of multimorbidity and types of chronic diseases on self-rated memory in older adults in the United States. Data were drawn from the 2011 wave of the National Health and Aging Trends Study (NHATS, N = 6,481). Logistic regressions were used to examine the associations between multimorbidity and types of chronic diseases and fair/poor self-rated memory. Compared to respondents with no or one chronic disease, respondents with multimorbidity showed 35% higher odds of reporting fair/poor self-rated memory. Also, stroke, osteoporosis, and arthritis were identified as increasing the odds of reporting fair/poor self-rated memory by 41%, 20%, and 30%, respectively. Demonstrating the importance of both multimorbidity and types of chronic diseases in self-reporting of memory, our findings suggest the need to educate older adults with multimorbidity and certain types of diseases regarding negative self-rated memory and its consequences.

Keywords

multimorbidity self-rated memory chronic illness cognitive aging

Introduction

As the older adult population with dementia has increased, the attention on cognitive aging has increased as well. Approximately 6.2 million older adults are currently living with Alzheimer’s disease in the USA (Alzheimer’s Association, 2021). Although dementia prevalence and incidence are expected to decrease in high-income countries, the absolute number of older adults with the disease is projected to increase unless potentially modifiable risk factors are addressed (Larson et al., 2013; Norton et al., 2014). In line with this, individuals’ perceived memory status is considered one of the early indicators of cognitive decline and dementia onset.

Self-rated memory is often used in addition to objective cognitive status to assess cognitive health in clinical and research settings (Marino et al., 2009). Although single questions on self-rated memory lack psychometric properties, they are commonly used as a quick and easy measure of cognitive screening (Cutler, 2015; Jang et al., 2021). Self-rated memory is an individual’s assessment of their own memory status as opposed to receiving an objective diagnosis from a clinical evaluation, but subjective memory performance has been shown to be related to objective memory (Dubois et al., 2016; Steinberg et al., 2013). Thus, self-rated memory may help identify older adults who are at risk of cognitive impairment in the future when there is no diagnosis of cognitive impairment in the present (Mitchell et al., 2014). Furthermore, poor self-rated memory is quite common, with adults aged 65 and older being as high as 50% (Jonker et al., 2000; Mol et al., 2007). When it comes to demographic characteristics and self-reported information, research suggests that demographic characteristics (e.g., gender and education) are associated with self-rated health (Arezzo & Giudici, 2017; Bamia et al., 2017). For example, women tend to rate their self-rated health poorer than their male counterparts (Bamia et al., 2017). In line with this, we can postulate that respondents’ demographic characteristics would be associated with self-rated memory.

Along with cognition, chronic disease is another source of burden in later years of life. The risk of chronic disease increases with age and may be linked to the development of poor self-rated memory and cognitive impairment. It is well-documented that many risk factors for chronic diseases are modifiable and linked to lifestyle factors. For instance, cigarette smoking and obesity were observed to increase the risk of developing chronic diseases (Ng et al., 2020). Having chronic disease may limit older adults’ independence, decrease quality of life, and increase the cost of health care (Centers for Disease Control and Prevention [Cognitive, 2015). Approximately 60% of Americans aged 18 and older have at least one chronic disease, while 42% of adults have multiple chronic diseases (i.e., multimorbidity) (Buttorff et al., 2017). The prevalence of chronic disease and multimorbidity increases with age. Among adults aged 65 and older, it is common to have more than two chronic diseases. In fact, approximately 80% of older adults have at least two chronic diseases (National Council on Aging, 2018). To summarize, the prevalence of chronic diseases and negative self-rated memory is increasing, and it will inevitably have a negative impact on cognitive health in later life.

Literature Review

Chronic Diseases and Cognitive Impairment and Dementia

The close linkages between chronic diseases and negative self-rated memory have been identified in the aging population (Aarts et al., 2011; Yap et al., 2020). Given the high burden of chronic diseases at older ages and their potential to undermine self-rated memory, it is important to understand the relationship between chronic diseases and cognitive impairment and/or dementia. Having multimorbidity may be a risk factor for worsening cognitive status and dementia. Multimorbidity is an important factor for older adults since it is highly associated with quality of life and life expectancy (Chudasama et al., 2019; Williams & Egede, 2016). In addition, multimorbidity among older adults has been linked to higher costs and greater utilization of health care, as well as to age-related cognitive decline (Buttorff et al., 2017; Fabbri et al., 2015). In addition, care for multimorbidity is costly and challenging to manage for older adults (Navickas et al., 2016). The relationship between multimorbidity and mild cognitive impairment (MCI) and dementia was investigated in a study of older adults residing in Minnesota (Vassilaki et al., 2015). This study included 17 chronic conditions (e.g., hyperlipidemia, hypertension, depression, diabetes, asthma, coronary artery diseases, and substance abuse disorder). Although this study did not investigate which individual chronic condition is an important risk factor for developing MCI and dementia, the finding showed that risks of developing MCI and dementia were significantly higher for those who had multimorbidity than those with no multimorbidity.

Moreover, previous studies have found that chronic diseases increase the risk of having cognitive impairment in the future (Kurella et al., 2005; Strachan et al., 2008). For example, Kurella et al. (2005) found that community-dwelling older adults with chronic kidney disease had an increased risk of developing cognitive impairment. Also, people with diabetes, particularly Type 2 diabetes, showed a significantly greater decline in cognition than those without diabetes (Strachan et al., 2008). Moreover, people with diabetes had greater odds of developing dementia. Thus, it can be hypothesized that having certain chronic diseases increases the risk of developing cognitive impairment and dementia.

Chronic Diseases and Self-Rated Memory

We were able to identify a few studies on the association between chronic diseases and self-rated memory with a single item (e.g., “Do you have problems with your memory?” or “Do you have memory problems?”). Research shows that respondents’ cognitive complaints commonly accompany chronic diseases and the complaints were elevated for those with multimorbidity (Taylor et al., 2020). Similar findings were documented in a study conducted on a Spanish population of older adults for whom negative subjective memory complaints increased with the number of chronic diseases (Pedro et al., 2016). In line with this, prior cross-sectional studies supported that there is a strong association between chronic diseases and subjective cognitive complaints (Aarts et al., 2011; Pedro et al., 2016; Yap et al., 2020). This relationship remains even after adjusting for potential factors including objective cognitive status, education level, and psychological stress (Aarts et al., 2011; Begum et al., 2012).

Similarly, a study conducted with respondents aged 45 and older showed that there was a positive relationship between subjective cognitive decline and chronic conditions (Taylor et al., 2020). This study included eight chronic conditions (asthma, heart attack/heart disease, stroke, cancer, chronic obstructive pulmonary disease [COPD], arthritis, kidney disease, and diabetes) and demonstrated that having chronic diseases was associated with greater odds of subjective cognitive decline. Particularly, respondents with stroke, heart disease, and COPD showed significantly higher odds of reporting subjective cognitive decline compared to those without these diseases. Nonetheless, one of the limitations of the study was that they included both middle-aged and older adults; the relationship between subjective cognitive decline and chronic diseases may differ for two age groups. For example, the prevalence of chronic diseases differs significantly between the two age groups; approximately 49.1% of middle-aged individuals have multimorbidity, while about 80.1% of individuals who are aged 65 and older have multimorbidity in the USA (Gerteis et al., 2014). Thus, it can be easily hypothesized that the burden from chronic diseases is higher among older adults than the middle-aged group, which may differently influence self-rated memory.

Although researchers recognize the importance of including objective memory status in the study of self-rated memory, there is limited literature which measures the impact of objective memory status on the association between chronic disease and self-rated memory. For example, the aforementioned studies (e.g., Jacob et al., 2019; Taylor et al., 2020) were not able to include objective assessment of memory due to the conditions of the survey design. Also, a national report demonstrated that chronic diseases impact subjective cognitive concerns (Centers for Disease Control and Prevention & National Center for Chronic Disease Prevention and Health Promotion, 2020). However, this report was not able to include objective memory status. Therefore, this study will advance the literature by examining the association of self-rated memory with multimorbidity and types of chronic diseases by including objective memory status, as well as using a nationally representative sample of older adults in the USA.

Purpose of This Study

Even if the importance of chronic diseases and self-rated memory is well-recognized, there has been a lack of research on the impact of multimorbidity and types of chronic diseases on self-rated memory in older adults. Although previous studies individually explored the relationship between either multimorbidity or types of chronic diseases and subjective cognitive concerns, there are few studies which have examined both the associations between multimorbidity and types of chronic diseases and self-rated memory in the USA. Hence, this study first examines the association between multimorbidity and self-rated memory using a nationally representative sample of older adults. We then explore which of eight individual chronic diseases are linked to reporting poor self-rated memory. We control for a set of socio-demographic characteristics (age, gender, race/ethnicity, marital status, annual household income, and education level), lifestyle factors (smoking status and body mass index [BMI]), mental health conditions (psychological well-being and depressive symptoms), prescribed medicine use, and objective memory status. The proposed research questions are: “Does multimorbidity increase the risk of reporting fair/poor self-rated memory?” and “Which chronic diseases are associated with increased risk of reporting fair/poor self-rated memory?” Based on the aforementioned literature, we hypothesize that older adults with multimorbidity would have a higher prevalence of fair/poor self-rated memory. Given that there is a high prevalence of both poor self-rated memory and chronic diseases among older adults, it is necessary to understand the association to provide information on cognitive impairment when there is yet to be an objective diagnosis of dementia.

Research Design

Sample

We used data from the 2011 National Health and Aging Trends Study (NHATS). The NHATS is nationally representative of Medicare beneficiaries aged 65 and older. The NHATS contains information on multiple domains including demographics, socioeconomic status, and health conditions of the respondents. The survey consisted of a two-hour in-person interview, with proxy respondents used if older adults were unable to complete the interview. In 2011, a total of 8245 respondents were interviewed. Our study excluded proxy respondents since they were not asked to rate the memory of the respondent (n = 583). In addition, we excluded respondents who were residing in nursing homes as they were also not asked the question on self-rated memory (n = 468). The final sample consisted of 6481 individuals after excluding respondents who were missing other covariates of interest (n = 713).

Measures

Self-rated memory

Participants were asked to rate their memory at present on a response of excellent, very good, good, fair, or poor. We coded the response into a binary variable of positive ratings (excellent/very good/good) and negative ratings (fair/poor). We have used this coding scheme to be in line with the existing literature on self-rated health. (DeSalvo et al., 2006), as well as how previous cognitive research classified the responses (Jang et al., 2021).

Chronic diseases

We included all eight chronic diseases (heart disease, heart attack, hypertension, diabetes, stroke, osteoporosis, arthritis, and lung disease) that respondents were asked about in the NHATS. For each chronic disease, the respondents were asked: Please tell me if a doctor ever told you that you had (chronic disease). Respondents with two or more chronic diseases were classified as having multimorbidity and those with no or one chronic disease as having no multimorbidity. Then each individual type of chronic disease was examined in the association.

Covariates

Control variables include demographic characteristics, socioeconomic status, lifestyle factors, mental health conditions, prescribed medicine use, and objective memory status. Demographic characteristics included age (65–69, 70–74, 75–79, 80–84, 85+), gender (male vs. female), race/ethnicity (non-Hispanic whites, non-Hispanic blacks, Hispanics, and other), and marital status (married/living with a partner, separated/divorced, widowed, and never married). Information on socioeconomic status consisted of education level (less than high school, high school graduate, some college, and college or more) and annual household income. We use the NHATS imputed household income variable (Montaquila et al., 2015). The income variable was log-transformed due to high skewness and kurtosis. Lifestyle factors included smoking status and BMI. Smoking status was classified as never smoker, former smoker, and current smoker. BMI was calculated using self-reported weight and height and defined using standard categories (Centers for Disease Control and Prevention, 2021): underweight (BMI<18.5 kg/m2), normal weight (18.5≤BMI<25 kg/m2), overweight (25≤BMI<30 kg/m2), or obese (BMI≥30 kg/m2). More than half of the overall sample was classified as overweight (38.4%) or obese (25.5%).

Research shows that individuals’ mood influences self-rated memory (Yates et al., 2017). To provide information on the respondents’ mood, we included depressive symptoms and psychological well-being. Depression was examined by using the total score of the Patient Health Questionnaire 2 (PHQ-2) (Kroenke et al., 2003). The questions were “Over the last month, how often have you had little interest or pleasure in doing things?”, as well as “Over the last month, how often have you felt down, depressed, or hopeless?” The answers were classified into 0 (not at all), 1 (several days), 2 (more than half the days), and 3 (nearly every day). The total scores from the two questions ranged from 0 to 6, with a higher score indicating more severe depressive symptoms. To capture the broad psychological well-being of the respondents, we used a psychological well-being scale. The answers were coded from 0 (agree a lot) to 2 (agree not at all) based on the five statements: I gave up trying to improve my life a long time ago; I like my living situation very much; I feel confident and good about myself; My life has meaning and purpose, and; I have an easy time adjusting to change. The total scores ranged from 0 to 10, with a higher score indicating better psychological well-being following previous research (Sol et al., 2020).

We also included prescribed medicine use since it can be assumed that individuals with chronic disease may take prescription medicines to manage their health conditions. When chronic diseases are untreated or undertreated, older adults may experience subjective cognitive decline (Taylor et al., 2020). At the same time, when older adults take medication to manage chronic disease, it could also have a side effect which involves memory problems. Thus, we included information on prescribed medicine use and objective memory status. The use of prescribed medicine was asked by: In the last month, did you take any medicines prescribed by a doctor? The responses were 1 (yes) and 0 (no).

Objective memory status was based on immediate and delayed word recall tests. For both tests, a list of 10 nouns was read to respondents and they were asked to recall as many nouns as possible. There were approximately 5 minutes between when the immediate and delayed tests were administered. The measure ranged from 0 to 20 points, with higher scores indicating better objective memory status.

Analytical Strategy

We performed descriptive analyses for respondents with and without multimorbidity. Group differences in study variables were examined by using t-tests for continuous variables and chi-squared tests for categorical variables. In the main analyses, we ran logistic regression models predicting fair/poor self-rated memory. In the first model, the key independent variable of interest was multimorbidity. In the second model, the key independent variables of interest were the eight individual chronic diseases. Both models adjusted for the full set of covariates, including socio-demographic characteristics (race/ethnicity, age, gender, marital status, education level, and annual household income), lifestyle factors (smoking status and BMI), mental health conditions (psychological well-being and depressive symptoms), prescribed medicine use (yes or no), and objective memory status (based on immediate and delayed recall). All analyses were performed using STATA 14.2 (Stata Corp, College Station, TX) and were weighted to account for complex survey design.

Results

Descriptive characteristics of the sample

Table 1 shows weighted descriptive characteristics of the overall sample. More than half of respondents reported having multimorbidity (N = 4380; weighted percentage = 64.2%). Most (82.7%) respondents were non-Hispanic white, 7.9% were non-Hispanic black, 6.4% were Hispanic, and 2.8% were from other racial/ethnic groups. Approximately half of the respondents were married or living with a partner (58.7%), and roughly a quarter were widowed. In the overall sample, 46.9% were never smokers, 44.2% were former smokers, and only 8.85% were current smokers. The most common chronic conditions were hypertension (63.6%) and arthritis (53.2%), followed by diabetes (23.4%) and osteoporosis (20.5%) in the overall sample. The chronic condition with the lowest prevalence was stroke (9.0%). For the overall sample, having two chronic conditions was the modal category and having five or more chronic conditions was the least common (7.0%). Figure 1 shows the distribution of chronic disease for people who report excellent/very good/good self-rated memory and for those who report fair/poor self-rated memory. Among those who report fair/poor self-rated memory, 54.1% have three or more chronic diseases. In contrast, this figure is 36.4% among those reporting excellent/very good/good self-rated memory.

Table 1.

Descriptive Statistics by multimorbidity, NHATS 2011

	Overall Sample (N=6481)% or Mean (SE)	No multimorbidity^f (N=2101)% or Mean (SE)	Multimorbidity^g (N=4380)% or Mean (SE)	X²/t
Self-rated memory (fair/poor)	16.80	24.81	75.19	58.84***
Race/ethnicity				8.21**
Non-Hispanic whites	82.71	36.61	63.39
Non-Hispanic blacks	7.99	26.67	73.33
Hispanics	6.48	34.11	65.89
Other	2.82	39.02	60.98
Age				31.51***
65–69	29.35	45.19	54.81
70–74	25.97	35.65	64.35
75–79	19.32	30.74	69.26
80–84	14.36	27.98	72.02
85+	11.00	29.47	70.53
Gender
Female	55.87	30.30	69.70	73.34***
Marital status				22.79***
Married/living with a partner	58.72	40.09	59.91
Separated/divorced	12.34	33.33	66.67
Widowed	25.72	26.40	73.60
Never-married	3.22	39.57	60.43
Education level				20.79***
Less than high school	19.78	27.15	72.85
High school graduate	27.47	34.26	65.74
Some college	27.25	35.31	64.69
College or more	25.50	44.38	55.62
Annual household income ^a	10.33 (0.02)	10.50 (0.04)	10.24 (0.02)	28.87***
Smoking Status				1.65
Never Smoker	46.95	37.12	62.88
Former Smoker	44.21	34.19	65.81
Current Smoker	8.85	35.92	64.08
BMI				35.92***
Underweight	1.79	44.43	55.57
Normal	31.25	41.01	58.99
Overweight	38.40	39.15	60.85
Obese	28.56	24.77	75.23
Psychological well-being^b	5.23 (0.01)	5.33 (0.02)	5.18 (0.01)	25.61***
Depressive symptoms^c	0.89 (0.02)	0.57 (0.02)	1.06 (0.02)	207.72***
Prescribed medicine use ^d	90.71	30.80	69.20	447.05***
Objective memory status ^e	8.43 (0.06)	8.89 (0.08)	8.17 (0.06)	79.25***
Types of chronic diseases		__	__	__
Heart disease	16.96
Heart attack	13.76
Hypertension	63.69
Diabetes	23.45
Stroke	9.06
Osteoporosis	20.51
Arthritis	53.23
Lung disease	15.58
Number of chronic diseases		__	__	__
0 or 1	35.72
2	27.33
3	19.76
4	10.13
5 or more	7.06

Note: All estimates are weighted to account for complex survey design.

Abbreviation: NHATS = National Health and Aging Trends Study; SE = standard error.

*p<0.05; **p<0.01; ***p<0.001.

^aAnnual household income was log-transformed.

^bPsychological well-being values ranged from 0 to 10, with a higher score corresponding to greater psychological well-being.

^cDepressive symptoms was evaluated by the Patient Health Questionnaire-2 and values ranged from 0 to 6, with a higher score indicating more severe depressive symptoms.

^dThe use of prescribed medicine was asked by: In the last month, did you take any medicines prescribed by a doctor? The responses were 1 (yes) and 0 (no).

^eObjective memory status was based on immediate and delayed recall. Values ranged from 0 to 20, with a higher score indicating better memory status.

^fNo multimorbidity means the individual has 0 or 1 chronic condition.

^gMultimorbidity means that the individual has 2+ chronic conditions.

Figure 1.

Distribution of Chronic Disease Stratified by Those Who Report Excellent/Very good/Good Self-Rated Memory and Those Who Report Fair/Poor Self-Rated Memory.

Approximately 69.7% of female respondents had multimorbidity, while 30.3% of female respondents had no multimorbidity in our sample. Approximately 72.8% of respondents with multimorbidity had a less than high school education level compared to 27.15% of respondents without multimorbidity. In addition, those with multimorbidity were more likely to be classified as obese (75.2%) than those without multimorbidity (24.7%). In addition, respondents with multimorbidity scored lower on psychological well-being (5.1% vs. 5.3%) and higher on depressive symptoms (1.0% vs. 0.5%). The prevalence of prescribed medicine use was substantially higher among respondents with multimorbidity (69.2%) than respondents without multimorbidity (30.8%). A higher percentage of those with multimorbidity reported having fair/poor self-rated memory than respondents without multimorbidity (75.19% vs. 24.81%). Consistent with the differences in self-rated memory, the objective memory status score was lower among those with multimorbidity compared to those without multimorbidity. In summary, respondents with multimorbidity were more likely to be non-Hispanic black or Hispanic, older, female, widowed, and less educated. In addition, they were more likely to have worse psychological well-being, more depressive symptoms, and worse objective memory status. Nearly all of them were on prescription medication.

Further information on the prevalence of combinations of chronic diseases in the overall sample is provided in Appendix 1. Appendix 1 shows what the most common combinations of chronic diseases are for the overall sample. For example, among respondents with heart disease, 6.6% had a heart attack, 12.9% had hypertension, 6% had diabetes, 2.6% had stroke, 3.9% had osteoporosis, 10.6% had arthritis, and 4.4% had lung disease. Having both hypertension and arthritis was the most common condition (37.0%), followed by hypertension and diabetes (18.4%). The least common combinations were stroke and lung disease (2.1%) and stroke and osteoporosis (2.4%). In addition, Appendix 2 describes the bivariate association between each type of chronic disease and fair/poor self-rated memory. The result showed that there are differences in each type of chronic disease and fair/poor self-rated memory in the study.

Association between multimorbidity and types of chronic diseases and fair/poor self-rated memory

The first set of results examines the association between having any multimorbidity and fair/poor self-rated memory. Table 2 presents the results from logistic regression models predicting fair/poor self-rated memory status. In Model 1, our main predictor was multimorbidity and the findings showed that having two or more chronic diseases was a significant predictor of fair/poor self-rated memory compared to those with none or one chronic disease, controlling for the full set of covariates (95% confidence interval [CI] = 1.11–1.65). Being non-Hispanic black or Hispanic was associated with 1.35 (95% CI = 1.12–1.63) and 2.21 (1.70–2.88) times higher odds of reporting fair/poor self-rated memory compared to non-Hispanic whites, respectively. In addition, none of the lifestyle variables (smoking status and BMI) were significant predictors of fair/poor self-rated memory. Among mental health conditions, having a higher score on depressive symptoms was associated with 1.41 (95% CI = 1.35–1.47) times higher odds of reporting fair/poor self-rated memory, controlling for other variables. In addition, scoring lower on objective memory status was a significant contributor to fair/poor self-rated memory (95% CI = 0.85–0.90).

Table 2.

Odds Ratios from Logistic Regression Models for the Association Between Multimorbidity and Types of Chronic Diseases and Fair/Poor Self-rated Memory.

Variables	Model 1 OR (95% CI)	Model 2 OR (95% CI)
Multimorbidity (Ref: None or one)
Two or more	1.35 (1.11–1.65)**
Types of chronic diseases
Heart disease		1.13 (9.12–1.40)
Heart attack		1.01 (0.80–1.25)
Hypertension		0.97 (0.81–1.17)
Diabetes		1.04 (0.88–1.24)
Stroke		1.41 (1.12–1.76)**
Osteoporosis		1.20 (1.00–1.44)*
Arthritis		1.30 (1.19–1.60)***
Lung disease		1.18 (0.96–1.45)
Race/ethnicity (Ref: Non-Hispanic whites)
Non-Hispanic blacks	1.35 (1.12–1.63)**	1.42 (1.16–1.72)**
Hispanics	2.21 (1.70–2.88)***	2.29 (1.74–3.02)***
Other	1.19 (0.73–1.92)	1.20 (0.76–1.90)
Age (Ref: 65–69)
70–74	1.15 (0.86–1.53)	1.15 (0.86–1.54)
75–79	1.10 (0.83–1.46)	1.09 (0.82–1.45)
80–84	1.32 (1.01–1.73)*	1.30 (0.99–1.72)
85+	1.47 (1.08–2.01)*	1.45 (1.06–1.97)*
Gender (Ref: male)
Female	0.79 (0.67–0.93)**	0.69 (1.57–1.83)***
Marital status (Ref: married/living with a partner)
Separated/divorced	0.96 (0.75–1.23)	0.94 (0.74–1.21)
Widowed	0.88 (0.72–1.07)	0.86 (0.71–1.05)
Never-married	0.79 (0.48–1.30)	0.79 (0.49–1.29)
Education level (Ref: less than high school)
High school graduate	1.79 (1.39–2.30)***	1.74 (1.35–2.25)***
Some college	1.28 (0.99–1.67)	1.29 (0.99–1.68)
College or more	1.15 (0.88–1.50)	1.14 (0.87–1.50)
Annual household income^a	0.91 (0.86–0.97)**	0.92 (0.87–0.97)**
Smoking status (Ref: never smoker)
Former smoker	0.91 (0.78–1.06)	0.89 (0.76–1.04)
Current smoker	0.80 (0.60–1.07)	0.77 (0.58–1.04)
BMI (Ref: normal)
Underweight	1.19 (0.83–1.69)	1.19 (0.83–1.70)
Overweight	0.87 (0.72–1.06)	0.86 (0.71–1.06)
Obese	0.97 (0.80–1.17)	0.96 (0.79–1.17)
Psychological well-being^b	0.94 (0.86–1.02)	0.94 (0.86–1.02)
Depressive symptoms^c	1.41 (1.35–1.47)***	1.38 (1.32–1.44)***
Prescribed medicine use	1.08 (0.75–1.57)	1.10 (0.75–1.60)
Objective memory status^d	0.88 (0.85–0.90)***	0.88 (0.85–0.90)***
N	6481	6481

Note: All estimates are weighted to account for complex survey design.

Abbreviation: OR = odds ratio; CI = confidence interval.

*p<0.05; **p<0.01; ***p<0.001.

^aAnnual household income was log-transformed.

^bPsychological well-being values ranged from 0 to 10, with a higher score corresponding to greater psychological well-being.

^cDepressive symptoms was evaluated by the Patient Health Questionnaire-2 and values ranged from 0 to 6, with a higher score indicating more severe depressive symptoms.

^dThe use of prescribed medicine was asked by: In the last month, did you take any medicines prescribed by a doctor? The responses were 1 (yes) and 0 (no).

^eObjective memory status was based on immediate and delayed recall. Values ranged from 0 to 20, with a higher score indicating better memory status.

It is also informative to investigate the relationship between the types of chronic diseases and self-rated memory status in the logistic regression model with the full set of covariates. In Model 2, we investigated the associations between types of chronic diseases and fair/poor self-rated memory separately in the logistic regression model—three out of eight chronic diseases were significant predictors of fair/poor self-rated memory (i.e., stroke, osteoporosis, and arthritis). For example, respondents with stroke had 1.41 times (95% CI = 1.12–1.76) higher odds of reporting fair/poor self-rated memory. Respondents with osteoporosis or arthritis had 20% (95% CI = 1.00–1.44) and 30% (95% CI = 1.19–1.60) higher odds of reporting fair/poor self-rated memory, respectively. The findings for other predictors were very similar to those described in Model 1. Based on both models, our findings suggested that being non-Hispanic black, Hispanic, older age, female, having less than a high school education level, having low annual household income, having higher levels of depressive symptoms, and having low objective memory score were linked to significantly greater odds of reporting fair/poor self-rated memory.

Discussion

As the prevalence and incidence of chronic diseases and cognitive impairment in aging societies are projected to increase, the burden on public health with regards to medical costs and disease management will inevitably increase. For example, the prevalence of poor self-rated memory ranges from 25% to 50% among older adults and tends to increase with age (Jonker et al., 2000). In addition, it is common for older adults aged 65 and older to have multimorbidity (National Council on Aging, 2018). Thus, self-rated memory and chronic diseases are important factors, both of which undermine older adults’ independence, mental health, and quality of life. Moreover, having chronic diseases as well as poor self-rated memory may be a particularly adverse combination. For example, having multimorbidity may require individuals to take multiple medications for chronic disease management. Having poor self-rated memory may make it more difficult to manage a complicated medication regimen. Also, older adults with poor self-rated memory may be more likely to develop dementia in the future compared to older adults without poor self-rated memory (Mitchell et al., 2014), which may worsen older adults’ quality of life and independence. Although the importance of both chronic diseases and self-rated memory is well-documented, there are few studies on the association between chronic diseases and self-rated memory. Thus, this study expanded the scope of the literature by investigating the association between fair/poor self-rated memory and two important dimensions of chronic disease: multimorbidity and types of diseases.

First, we found that respondents with multimorbidity had higher odds of reporting fair/poor self-rated memory compared to those without multimorbidity, controlling for the full set of covariates (demographic characteristics, socioeconomic status, lifestyle factors, mental health conditions, prescribed medicine use, and objective memory status). This result is consistent with a prior study conducted on the population aged 16 and older, which suggested that there is a positive association between multimorbidity and subjective memory concerns (Jacob et al., 2019). Our study contributes to the literature by using a nationally representative sample and focusing on older adults. Being non-Hispanic black, Hispanic, older, and female was associated with significantly higher probabilities of reporting fair/poor self-rated memory. Individuals with less than high school education, low annual household income, more depressive symptoms, and low objective memory status were significantly more likely to report fair/poor self-rated memory.

In addition, we further performed logistic regression analysis on the association between types of chronic diseases and fair/poor self-rated memory, adjusted for our covariates. Among the eight chronic diseases, three chronic diseases remained significant (i.e., stroke, osteoporosis, and arthritis). Stroke was the chronic condition associated with the greatest elevation in the odds of reporting fair/poor self-rated memory. Consistent with previous findings (Jacob et al., 2019; Taylor et al., 2020), we were able to identify that specific chronic diseases are more likely to be associated with fair/poor self-rated memory than those without that chronic disease. Our findings also demonstrated that older adults with stroke, osteoporosis, or arthritis had a greater prevalence of fair/poor self-rated memory than those without these chronic diseases. There are several potential mechanisms through which specific diseases can influence cognitive impairment. For example, stroke may cause neuroanatomical lesions in areas of the brain including the hippocampus and the white matter lesions, as well as cerebral microbleeds (Al-Qazzaz et al., 2014; Sun et al., 2014). These in turn may contribute to the development of cognitive impairment following a stroke. Low bone mineral density, which has been found to be highly associated with cognitive impairment, may explain the relationship between osteoporosis or arthritis and cognitive impairment (Kang et al., 2018). It is possible that bone mass loss increases inflammatory markers (e.g., interleukin-6), which in turn increase the risk of developing Alzheimer’s disease (Ershler, 1993; Lui et al., 2003).

A key strength of this study is the use of a nationally representative sample of older adults that included information on self-rated memory status as well as objective memory status. Moreover, our study included all chronic diseases that were asked about by the survey, which are common among the older population. Nonetheless, there are limitations to this study. First, whether a respondent had a chronic disease was ascertained through self-reports. In addition, respondents were asked only whether they had a chronic disease, lacking information on time since diagnosis, which is associated with severity. The severity of the chronic disease may be linked to self-rated memory since greater severity has been found to be associated with a lower quality of life and worse physical and mental health (Pizzi et al., 2006). In addition, individuals’ mood is highly associated with self-rated memory among older adults (Yates et al., 2017). Although the survey did not ask about mood specifically, we did include measures of psychological well-being and depressive symptoms, which have been found to be highly associated with individuals’ mood in prior studies (Polak et al., 2015). Moreover, self-rated memory was not asked about to older adults who were institutionalized; therefore, our findings are restricted to older adults who are living in community settings. Lastly, it is unclear whether the presence of certain chronic diseases may invalidate how respondents rate their memory even if we included objective memory status in the analysis.

Despite these limitations, this study contributes to the literature by considering the associations between two measures of chronic disease and self-rated memory through the use of a nationally representative sample of older adults. The study’s findings highlight the importance of the prevention of chronic diseases and how multimorbidity negatively impacts respondents’ self-rated memory, which may be linked to cognitive impairment in the long term. Considering projections for both the absolute number of older adults with cognitive impairment and with chronic disease are increasing, it is important that health professionals recognize that poor self-rated memory is highly prevalent among older adults with multimorbidity. Not only health professionals but also patients need to understand the impact of multimorbidity on self-rated memory and factor the relationship into disease management and treatment. Our results highlight the importance of monitoring self-rated memory among older adults with stroke, osteoporosis, and arthritis in clinical settings. A prior study has found that older adults are less likely to initiate discussions about memory problems with their health care providers even when they believe their memory is fair/poor (Waldorff et al., 2008). Our findings demonstrate that older adults with stroke, osteoporosis, and arthritis are more likely to report fair/poor self-rated memory than those without these diseases. Thus, clinicians who treat patients with these chronic conditions should pay close attention to patients’ self-rated memory status.

There are mixed trends in lifestyle factors in the USA. First, the increasing prevalence of obesity may lead to increased risk of developing chronic diseases among older adults in the future. This has an important implication, since this may lead to elevated prevalence of fair/poor self-rated memory and lead to cognitive decline among older adults. At the same time, smoking trends are declining, which may potentially lead to reduced prevalence of chronic diseases. It will be interesting to witness how future trends in multimorbidity will play out among older adults and how they might affect the individuals’ self-rated memory based on these mixed trends in lifestyle factors.

Considering this study was not able to include severity of chronic disease, future work is needed on how this factor influences self-rated memory. Does more severe chronic disease worsen self-rated memory among older adults? Given the complexity of chronic disease management and treatments, more studies are needed to explore whether disease severity influences self-rated memory.

Supplemental Material

sj-pdf-1-roa-10.1177_01640275221087612 - Supplemental Material for The Relationship Between Multimorbidity and Types of Chronic Diseases and Self-Rated Memory

Supplemental Material for sj-pdf-1-roa-10.1177_01640275221087612 The Relationship Between Multimorbidity and Types of Chronic Diseases and Self-Rated Memory by Yujin Franco, Yuri Jang, Joseph L. Saenz, and Jessica Y. Ho in Research on Aging.

Footnotes

Author Contribution

Y. Franco planned the study, performed statistical analyses, and wrote the paper. Y. Jang helped with statical analyses and contributed to writing the paper. J. L. Saenz and J. Y. Ho helped to plan the study and contributed to writing the paper.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Institutes of Health/National Institute on Aging (R00AG058799, PI: Joseph L. Saenz, PhD).

ORCID iDs

Yujin Franco

Yuri Jang

Jessica Y. Ho

Supplemental Material

Supplemental material for this article is available online.

Author Biographies

Yujin Franco, M.A. is a Ph.D. candidate in Gerontology program at the University of Southern California. Her research interests include cognition, social determinants of health, socioeconomic differences in health, and health disparities.

Yuri Jang, Ph.D. is a Professor at the University of Southern California (USC) Suzanne Dworak-Peck School of Social Work. Dr. Jang’s areas of interest include health disparities and minority health and service use. She also works on cultural adaptation of evidence-based interventions for older immigrants with limited English proficiency.

Joseph Saenz is an assistant professor at the Leonard Davis School of Gerontology at the University of Southern California. He focuses his research on socioeconomic disparities in cognitive aging.

Jessica Y. Ho, PhD, is an Assistant Professor of Gerontology, Sociology, and Spatial Sciences in the Leonard Davis School of Gerontology at the University of Southern California. Her research focuses on identifying causes of America’s lagging life expectancy and examining drivers of inequalities in health and mortality.

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