Relationship Between the Severity of Subjective Cognitive Decline and Health-Related Quality of Life in Community-Dwelling Older Adults: A Cross-Sectional Study Focusing on Sex Differences

Abstract

Background/Objectives: Sex differences in the relationship between subjective cognitive decline (SCD) and health-related quality of life (HRQOL), as well as psychological and physical factors affecting this relationship, have not been fully investigated. In this study, we aimed to examine the relationship between SCD severity and HRQOL in community-dwelling older adults in Japan and to clarify the psychological and physical factors affecting this relationship by sex. Methods: This cross-sectional study included 456 community-dwelling older adults and was conducted in September 2024. SCD severity was evaluated using the visual analog scale, and HRQOL was assessed using the EuroQol 5-Dimensions 5-Levels. Psychological factors (depression and insomnia) and physical factors (pain and frailty) were measured, and the relationship between SCD and HRQOL was analyzed by sex. Results: In women, HRQOL decreased as SCD severity increased and was associated with depression, insomnia, and physical pain. Conversely, in men, the association between SCD and HRQOL was not significant, and HRQOL was mainly associated with physical health factors, including pain and frailty. Conclusions: There were sex differences in the relationship between SCD and HRQOL, with women’s awareness of SCD associated with a decline in HRQOL, whereas physical health was the main determinant in men. Sex-specific interventions with psychological support being effective for women and support focusing on maintaining physical health for men are warranted.

1. Introduction

As Japan’s population ages, maintaining and improving the health-related quality of life (HRQOL) of older adults has become an important issue [1]. A decline in HRQOL is influenced by physical, cognitive, and psychological factors and can lead to reduced independence in daily life and social participation [2]. In particular, changes in cognitive function in older adults have a significant impact on HRQOL [3], and the subjective cognitive decline (SCD) associated with aging is related to a decline in HRQOL [4,5,6]. Semantic memory may become more densely structured owing to lifelong knowledge accumulation, whereas certain cognitive functions decline with age [7].

SCD refers to the subjective awareness of cognitive decline, including memory, attention, executive function, and language, at a stage before objective cognitive impairment is detected. Among various aspects of SCD, subjective memory complaints (SMCs) refer to self-perceived memory impairment. SCD has been identified as a potential risk factor for the development of mild cognitive impairment (MCI) and Alzheimer’s disease (AD), although not all individuals with SCD progress to dementia [8]. In addition to its potential role as an early indicator of cognitive decline, SCD is associated with psychological factors, such as depression and anxiety, which can lead to a decline in HRQOL [5]. Furthermore, hippocampal atrophy and a decline in brain network function have been reported in older adults with SCD [8,9], suggesting that it may be an early indicator of the degenerative process of the brain rather than just a subjective complaint.

Sex differences in SCD have been increasingly recognized, with prior studies indicating that women report SCD more frequently than men, possibly owing to differences in psychological distress, health perceptions, and cognitive reserve mechanisms [10]. Given these inconsistencies, further investigation into sex-specific factors influencing SCD is warranted. Sleep disturbances have also been associated with cognitive complaints in older adults [11,12]. However, the nature of this relationship remains unclear, as both sleep disorders and SCD may be influenced by shared underlying factors such as depression and anxiety [5,13]. This study aimed to explore these relationships further.

Additionally, SCD is not only a matter of subjective memory but is closely related to various factors and may comprehensively reduce the HRQOL of older adults [13,14,15]. Therefore, individual attributes and health conditions may affect the relationship between SCD and HRQOL. Particularly, the effects of sex have attracted attention [16]. However, how the relationship between SCD and HRQOL differs by sex and how the relationship between physical and psychological health and individual attributes works have not been fully investigated. Moreover, chronic pain has been linked to both cognitive complaints and reduced HRQOL [17,18]. Persistent pain may contribute to SCD by increasing psychological distress or altering attentional and memory processes [19]. Therefore, including body pain as a variable in this study provides a more comprehensive understanding of the factors affecting SCD and HRQOL.

In this study, we aimed to examine the relationship between SCD and HRQOL in older adults living in local communities in Japan and clarify the physical and psychological factors affecting this relationship by analyzing the relationship between SCD severity and HRQOL. Additionally, as the relationship between SCD and HRQOL may differ by sex, we examined the impact of SCD on HRQOL separately for men and women. The results of this study are expected to contribute to the development of intervention strategies to maintain and improve the QOL of older adults and to the development of support measures and intervention methods to reduce the impact of SCD as a risk factor for reduced QOL.

2. Materials and Methods

2.1. Research Design

This cross-sectional study included community-dwelling older adults who participated in health surveys conducted in two areas of Prefecture A and one area of Prefecture B in September 2024. Participants were recruited through comprehensive community support centers in each city. The participants were independent in their daily lives and arrived at the health survey venue on their own by public transportation, private car, bicycle, or on foot. Participants were given both oral and written explanations of the purpose and content of the study, the benefits and risks, the protection of privacy, and the possibility of withdrawing consent or declining participation, and their consent was obtained. This study was approved by the Kyoto Tachibana University Research Ethics Committee (approval numbers: 18–26) and was conducted in accordance with the Declaration of Helsinki.

2.2. Participants

The exclusion criteria for this study were as follows: (1) age < 65 years, (2) cognitive impairment, and (3) inability to complete all measurements. Cognitive impairment was defined as a Mini-Mental State Examination (MMSE) score of less than 24 points [20]. Finally, 456 older people were included in the analysis (Figure 1).

2.3. Measurement Items

In addition to basic attributes, the measurement items included HRQOL, the severity of SCD, the number of applicable items for the neuropsychological indicators MMSE and the five-item version of the Geriatric Depression Scale (GDS-5), the physical indicators from the Japanese version of the Athens Insomnia Scale (AIS-J), and the number of items that matched the Japanese version of the Cardiovascular Health Study (J-CHS) criteria.

(1)

Basic attributes

We obtained information on basic attributes, such as age, sex, number of health conditions, and the presence or absence of physical pain, by making the participants fill out a dedicated form with self-report questions. For the number of health conditions, we asked participants to choose the name of the disease that was the reason for their current visit to a medical institution from a list of options (hypertension, hyperlipidemia, diabetes, stroke, heart disease, cancer, depression, osteoporosis, or respiratory disease). For diseases not included in the list, respondents were asked to provide a free text response. The number of diseases was counted based on the results of the responses. As for the presence or absence of physical pain, respondents were asked to answer “Do you have any pain in your body at the moment?” with either “Yes” or “No”.

(2)

HRQOL

HRQOL was measured using the EuroQol 5-Dimensions 5-Levels (EQ-5D-5L) [21], a widely used tool for assessing health status. This instrument evaluates five core domains: mobility, self-care, daily activity engagement, physical pain or discomfort, and psychological well-being, including anxiety and depression. The EQ-5D-5L is designed as a self-report questionnaire in which participants rate their condition on a five-point Likert scale (1 = no issues, 2 = mild issues, 3 = moderate issues, 4 = severe issues, and 5 = extreme issues). The responses obtained were then converted into standardized utility values, referred to as HRQOL scores, using a validated algorithm. These values ranged from 0, representing the lowest possible health state (death), to 1, indicating optimal health.

(3)

Severity of SCD

To assess the severity of SCD, including SMCs, we used a visual analog scale (VAS) based on previous studies [22]. We drew a 10-cm horizontal line on an A3 sheet of paper with 11 vertical lines placed at equal intervals above it. This sheet was placed in front of the participant, who was asked the following question: “Do you think you have more forgetfulness than other people of the same age and sex?” The left end (0 points) was labeled “I think I have a lot of forgetfulness”, and the right end (10 points) was labeled “I think I have very little forgetfulness”. The participants were asked to mark the corresponding vertical lines. Lower VAS scores indicated more severe SCD.

(4)

MMSE

The Mini-Mental State Examination (MMSE) [23] was used to evaluate global cognitive function. This brief assessment tool has been widely used worldwide for cognitive screening. It assesses 11 domains, including tasks ranging from writing text to replicating drawings. Prior research has demonstrated strong validity [24] and reliability [20]. Participants’ cognitive performance was quantified based on their total MMSE score, which reflected all assessed cognitive domains.

(5)

GDS-5

The GDS-5, a shortened form of the Geriatric Depression Scale (GDS) [25], was used to assess depressive symptoms. This self-report questionnaire was specifically designed to capture key depressive characteristics in older adults. Its validity and reliability have been well established [26]. The GDS-5 comprises five yes/no questions, with each affirmative response indicating depressive symptoms assigned one point. The total score, calculated by summing all the responses, reflects the overall severity of depressive symptoms.

(6)

AIS-J

The AIS-J [27] was used to assess the severity of insomnia symptoms. This tool consists of eight items that evaluate sleep disturbances over the past month, specifically (1) sleep initiation, (2) nighttime awakenings, (3) early morning awakenings, (4) total sleep duration, (5) overall sleep quality, (6) problems with sense of well-being, (7) overall functioning, and (8) daytime sleepiness. Each item is scored on a four-point scale: 0 = no problems, 1 = some problems, 2 = significant problems, and 3 = very significant problems. The total score ranges from 0 to 24, with higher scores indicating more severe insomnia. Based on this score, insomnia severity is categorized into three levels: pathological insomnia (6–24), nocturnal insomnia (4–5), and no insomnia (0–3). The AIS-J has been validated as a reliable measure of sleep disturbances in clinical and research settings [27,28].

(7)

Number of items matching the J-CHS criteria

Frailty was evaluated using the J-CHS criteria [29], which define five key characteristics associated with reduced physiological reserve and increased vulnerability. These include unintentional weight loss of 2 kg or more within 6 months, self-reported fatigue, low activity levels assessed through interviews, muscle weakness (grip strength below 28 kg for men and 18 kg for women), and slow walking speed (gait speed below 1.0 m/s). Each criterion was assigned one point, with the total scores ranging from 0 to 5, where higher scores indicate greater frailty severity [30]. This assessment tool has been validated for reliability [31]. Grip strength was measured in kilograms using a Smedley-type handheld dynamometer (GRIP-D; Takei Ltd., Niigata, Japan). During the measurements, participants were seated with their wrists in a neutral position and elbows bent at 90°. Each hand was tested twice, and the highest recorded value was used for analysis. Walking speed was measured using the WalkWay MW-1000 system (Anima Co., Tokyo, Japan), which captures temporal and spatial gait characteristics based on foot pressure distribution. Participants completed a 6.4 m walking test, which included a 2 m acceleration phase, a 2.4 m measurement zone, and a 2 m deceleration phase. Walking speed was calculated from the measurement section, and each test was performed twice at the participant’s fastest speed.

2.4. Statistical Analysis

Statistical analyses were conducted to evaluate group differences and relationships among the variables. The normality of the data was assessed for each participant group and measurement item using the Shapiro–Wilk test. The Mann–Whitney U test was used for continuous variables to compare differences between sexes, whereas categorical variables were analyzed using the χ² test. Spearman’s rank correlation coefficients were computed to examine associations between HRQOL scores, SCD severity, and relevant psychological and physical factors. Sample weighting was applied based on population demographics (males: 43.4%, females: 56.6%) to address the unequal distribution of male and female participants [32]. Weighted analyses were conducted to verify whether the observed sex differences remained consistent. To determine the factors influencing HRQOL, a multiple regression analysis using the forced entry method was performed with HRQOL as the dependent variable. Independent variables included SCD severity (VAS), the number of health conditions, the presence of physical pain, MMSE score, GDS-5 score, AIS-J score, and the number of criteria met in the J-CHS assessment. Additionally, the multiple regression analysis was repeated using the weighted dataset to assess the robustness of our findings. To statistically test sex differences in the relationship between SCD severity and HRQOL, an interaction term (SCD severity × sex) was included in an additional regression model. Before creating the interaction term, the continuous variable (SCD severity) was mean-centered to minimize multicollinearity. The significance of the interaction term was evaluated to determine whether sex moderates the effect of SCD severity on HRQOL. Multicollinearity among independent variables was evaluated using the variance inflation factor (VIF). All statistical analyses were conducted using SPSS Statistics software (version 26; IBM, Armonk, NY, USA), with the statistical significance set at p < 0.05.

3. Results

Table 1. Comparison of fundamental information and measurements between sexes.

Variable	Total (n = 456)	Male (n = 109)	Female (n = 347)	p-Value (Before Weighting)	p-Value (After Weighting)
Age (year)	75.81 ± 5.96	77.61 ± 6.26	75.24 ± 5.76	<0.01	<0.01
Number of health conditions (n)	1.21 ± 0.93	1.10 ± 0.94	1.25 ± 0.93	0.11	0.04
Presence of physical pain [Yes/No] (n [%]) *	280 (61.4)/176 (38.6)	60 (55.0)/49 (45.0)	220 (69.6)/127 (40.2)	0.14	0.07
HRQOL score (score)	0.83 ± 0.13	0.84 ± 0.15	0.83 ± 0.13	0.67	0.59
VAS for SCD severity (score)	5.98 ± 2.16	5.91 ± 2.14	6.00 ± 2.18	0.73	0.67
MMSE (score)	28.27 ± 1.82	28.10 ± 1.90	28.33 ± 1.79	0.18	0.09
GDS-5 (score)	0.64 ± 1.00	0.63 ± 0.93	0.65 ± 1.02	0.79	0.74
AIS-J (score)	3.98 ± 3.02	3.83 ± 2.86	4.03 ± 3.07	0.51	0.08
Number of items that match the J-CHS judgment criteria (n)	0.63 ± 0.81	0.72 ± 0.92	0.60 ± 0.77	0.30	0.19

Data are presented as the mean ± standard deviation. Presence of physical pain: number [%]. Mann–Whitney U test, *: χ² test. HRQOL: health-related quality of life, VAS: visual analog scale, SCD: subjective cognitive decline, MMSE: Mini-Mental State Examination, GDS-5: five-item version of the Geriatric Depression Scale, AIS-j: Japanese version of the Athens Insomnia Scale, and J-CHS: Japanese version of the Cardiovascular Health Study.

shows the basic information of the participants and the results of the comparison of the measurement values by sex. The ages of the males were significantly older than that of the females (p < 0.01), and this difference remained significant after applying sample weighting. No significant sex differences were observed in the other indices before weighting (p ≥ 0.05). However, after weighting, females had significantly more health conditions than males (p = 0.04).

Table 2. Correlation analysis among HRQOL, SCD severity, and each indicator.

	HRQOL Score (Score)				VAS for SCD Severity (Score)
	Male (n = 109)		Female (n = 347)		Male (n = 109)		Female (n = 347)
	ρ	p-Value	ρ	p-Value	ρ	p-Value	ρ	p-Value
Age (year)	−0.023	0.813	0.011	0.833	0.115	0.232	0.075	0.166
Number of health conditions (n)	−0.345	p < 0.001	−0.111	0.040	0.060	0.534	−0.050	0.354
HRQOL score (score)					−0.087	0.371	0.292	<0.001
VAS for SCD severity (score)	−0.087	0.371	0.292	<0.001
MMSE (score)	0.090	0.351	0.002	0.974	0.002	0.987	0.049	0.362
GDS-5 (score)	−0.298	0.002	−0.328	<0.001	−0.107	0.268	−0.245	<0.001
AIS-J (score)	−0.330	p < 0.001	−0.395	<0.001	−0.175	0.068	−0.159	0.003
Number of items that match the J-CHS judgment criteria (n)	−0.337	p < 0.001	−0.356	<0.001	0.119	0.218	−0.188	<0.001

Spearman’s rank correlation coefficient. HRQOL: health-related quality of life, VAS: visual analog scale, SCD: subjective cognitive decline, MMSE: Mini-Mental State Examination, GDS-5: five-item version of the Geriatric Depression Scale, AIS-J: Japanese version of the Athens Insomnia Scale, and J-CHS: Japanese version of the Cardiovascular Health Study.

shows the results of the correlation analysis between the HRQOL score, the severity of SCD, and each indicator by sex. Regarding the HRQOL score, in both groups, the lower the number of health conditions, GDS-5, AIS-J, and J-CHS criteria applicable, the higher the HRQOL score (p < 0.05). Additionally, in women, the higher the VAS score for subjective cognitive decline (i.e., the milder the symptoms), the higher the HRQOL score (p < 0.01). Regarding the severity VAS for subjective cognitive decline, in women, the lower the number of GDS-5 and JCHS criteria applicable, the higher the severity VAS for subjective cognitive decline (p < 0.01). In men, no indicator showed a significant correlation with the severity of VAS for subjective cognitive decline (p ≥ 0.05). Furthermore, no substantial changes were observed in the correlation coefficients or p-values before and after applying sample weighting. Therefore, only the pre-weighting values are presented in Table 2.

Table 3. Comparison of HRQOL and SCD severity by the presence or absence of body pain.

	HRQOL Score (Score)				VAS for SCD Severity (Score)
	Presence of Body Pain	Absence of Body Pain	p-Value (Before Weighting)	p-Value (After Weighting)	Presence of Body Pain	Absence of Body Pain	p-Value (Before Weighting)	p-Value (After Weighting)
Male (n = 109)	0.77 ± 0.12	0.92 ± 0.12	<0.01	<0.01	5.85 ± 1.67	5.99 ± 2.61	0.71	0.60
Female (n = 347)	0.78 ± 0.11	0.93 ± 0.11	<0.01	<0.01	5.75 ± 2.14	6.43 ± 2.19	<0.01	<0.01

Data are presented as the mean ± standard deviation. Mann–Whitney U test. HRQOL: health-related quality of life, VAS: visual analog scale, and SCD: subjective cognitive decline.

shows the results of the comparison of the HRQOL score and the severity of subjective cognitive decline (VAS) by sex, with and without physical pain. The HRQOL score of those with pain was significantly lower than those without pain in both groups (p < 0.05). Regarding the severity VAS of subjective cognitive decline, the score for those with pain was significantly lower (indicating more severe symptoms) than that for those without pain in women (p < 0.05). These trends remained consistent after applying sample weighting, with no substantial changes in statistical significance. While the p-value for the VAS score in men showed a slight decrease (from 0.71 to 0.60), it remained non-significant, indicating that the weighting adjustment did not notably affect the overall findings.

Table 4. Results of the multiple regression analysis with the HRQOL score as the dependent variable.

		Before Weighting						After Weighting
				95% CI for β						95% CI for β
Group	Independent Variable	β	std-β	Lower	Upper	p-Value	VIF	β	std-β	Lower	Upper	p-Value	VIF
Male (n = 109)	Age (year)	−0.001	−0.032	−0.004	0.003	0.668	1.077	−0.001	−0.032	−0.003	0.002	0.556	1.077
	Number of medical histories (n)	−0.015	−0.100	−0.040	0.009	0.221	1.305	−0.015	−0.100	−0.033	0.003	0.092	1.305
	Presence of physical pain [1: Yes/0: No]	−0.136	−0.471	−0.180	−0.092	<0.001	1.189	−0.136	−0.471	−0.168	−0.104	<0.001	1.189
	VAS for SCD severity (score)	−0.007	−0.102	−0.017	0.003	0.180	1.136	−0.007	−0.102	−0.014	0.000	0.065	1.136
	MMSE (score)	0.007	0.093	−0.004	0.018	0.201	1.043	0.007	0.093	−0.001	0.015	0.078	1.043
	GDS-5 (score)	−0.018	−0.115	−0.043	0.007	0.158	1.299	−0.018	−0.115	−0.036	0.000	0.052	1.299
	AIS-J (score)	−0.011	−0.229	−0.019	−0.004	0.004	1.163	−0.011	−0.229	−0.017	−0.006	<0.001	1.163
	Number of items that match the J-CHS judgment criteria (n)	−0.038	−0.241	−0.063	−0.013	0.004	1.301	−0.038	−0.241	−0.056	−0.020	<0.001	1.301
	Adjusted R2 (p-value)	0.462 (p < 0.001)						0.481 (p < 0.001)
Female (n = 316)	Age (year)	0.000	−0.008	−0.002	0.002	0.860	1.119	0.000	−0.008	−0.002	0.002	0.879	1.119
	Number of medical histories (n)	−0.009	−0.063	−0.020	0.002	0.124	1.028	−0.009	−0.063	−0.022	0.004	0.187	1.028
	Presence of physical pain [1: Yes/0: No]	−0.125	−0.461	−0.147	−0.103	<0.001	1.081	−0.125	−0.461	−0.151	−0.099	0.000	1.081
	VAS for SCD severity (score)	0.007	0.123	0.002	0.012	0.004	1.113	0.007	0.123	0.002	0.013	0.014	1.113
	MMSE (score)	0.002	0.028	−0.004	0.008	0.493	1.050	0.002	0.028	−0.005	0.009	0.556	1.050
	GDS-5 (score)	−0.019	−0.151	−0.031	−0.007	0.001	1.376	−0.019	−0.151	−0.033	−0.006	0.006	1.376
	AIS-J (score)	−0.007	−0.169	−0.011	−0.004	<0.001	1.200	−0.007	−0.169	−0.012	−0.003	0.001	1.200
	Number of items that match the J-CHS judgment criteria (n)	−0.025	−0.149	−0.041	−0.010	0.001	1.304	−0.025	−0.149	−0.043	−0.007	0.006	1.304
	Adjusted R2 (p-value)	0.447 (p < 0.001)						0.442 (p < 0.001)

Multiple regression analysis (forced entry method), independent variable: HRQOL score β: unstandardized regression coefficients, std-β: standardized regression coefficient, 95% CI: 95% confidence interval, VIF: variance inflation factor, HRQOL: health-related quality of life, VAS: visual analog scale, SCD: subjective cognitive decline, MMSE: Mini-Mental State Examination, GDS-5: five-item version of the Geriatric Depression Scale, AIS-J: Japanese version of the Athens Insomnia Scale, and J-CHS: Japanese version of the Cardiovascular Health Study.

shows the results of the multiple regression analysis (forced entry method) with the HRQOL score as the dependent variable categorized by sex. In men, even after excluding the effects of all explanatory variables, the absence of physical pain, the Athens Insomnia Scale score, and a low number of J-CHS criteria applicable were significantly associated with high HRQOL scores (p < 0.01). In women, the absence of physical pain; a high VAS score for the severity of subjective cognitive decline (mild symptoms); and a low score on the GDS-5, Athens Insomnia Scale, and J-CHS criteria for Judgment were significantly associated with a high HRQOL score (p < 0.01). After applying sample weighting, slight variations in the p-values were observed; however, the overall pattern of significant associations remained unchanged.

Table 5. Results of the multiple regression analysis examining the interaction between sex and SCD severity on HRQOL.

				95% CI for β
	Independent Variable	β	std-β	Lower	Upper	p-Value	VIF
Before weighting	VAS for SCD severity (score)	−0.005	−0.076	−0.016	0.007	0.420	4.309
	Sex (0: Male, 1: Female)	−0.003	−0.009	−0.031	0.025	0.841	1.000
	VAS for SCD severity × Sex	0.022	0.310	0.009	0.035	0.001	4.308
	Adjusted R2 (p-value)	0.054 (p < 0.001)
After weighting	VAS for SCD severity (score)	−0.005	−0.075	−0.014	0.004	0.291	2.357
	Sex (0: Male, 1: Female)	−0.003	−0.010	−0.028	0.022	0.821	1.000
	VAS for SCD severity × Sex	0.022	0.262	0.010	0.034	<0.001	2.356
	Adjusted R2 (p-value)	0.038 (p < 0.001)

Multiple regression analysis (forced entry method), independent variable: HRQOL score β: unstandardized regression coefficients, std-β: standardized regression coefficient, 95% CI: 95% confidence interval, VIF: variance inflation factor, HRQOL: health-related quality of life, VAS: visual analog scale, and SCD: subjective cognitive decline.

shows the results of the multiple regression analysis examining the interaction between sex and SCD severity on HRQOL. Before weighting, the interaction term between VAS for SCD severity and sex was significant (p = 0.001), whereas the main effects of SCD severity and sex were not significant (p = 0.420 and p = 0.841, respectively). The adjusted R² was 0.054. After weighting, the interaction term remained significant (p < 0.001), whereas the main effects of SCD severity and sex remained non-significant (p = 0.291 and p = 0.821, respectively). The adjusted R² was 0.038. These results indicate that sex modifies the relationship between SCD severity and HRQOL.

4. Discussion

In this study, we examined the relationship between HRQOL and the severity of subjective cognitive decline in older adults by sex. The results showed that, as the severity of subjective cognitive decline increased, HRQOL scores decreased in women. However, this relationship was not statistically significant in men. Additionally, the presence or absence of physical pain affected HRQOL scores in both sexes, and physical pain in women was also associated with the severity of subjective cognitive decline. These results suggest that there may be sex differences in the relationship between the severity of subjective cognitive decline and HRQOL.

Interestingly, neither HRQOL nor SCD severity showed a significant correlation with age. This finding contrasts with previous studies that reported a decline in HRQOL [5] and an increase in SCD [4] with aging. One possible explanation is that our study participants were relatively healthy older adults, as they were able to attend the survey venue independently. This may have led to a narrower range of health conditions, thereby reducing the influence of age on HRQOL and SCD. Additionally, SCD is influenced not only by age but also by psychological factors, such as depression and anxiety [5], which may have had a stronger effect in our sample. Further studies with a more diverse sample, including individuals with varying levels of health and frailty, are needed to clarify the role of age in these relationships.

HRQOL tended to decline among women as they became more aware of subjective cognitive decline. This indicates that women are more sensitive to changes in their cognitive function and that this awareness may directly impact their quality of life. Previous research [5] has reported that subjective cognitive decline is associated with depressive symptoms and anxiety and that these contribute to a decline in HRQOL. Women tend to have high expectations in terms of their social roles and interpersonal relationships [33] and a strong sense of anxiety about cognitive decline [34]. These psychological factors may mediate the subjective awareness of memory loss and decline in HRQOL.

One of the novel aspects of this study is that it did not look at SCD from the perspective of its presence but rather as a severity scale using the VAS. In previous studies [5], the mainstream approach was to analyze the impact of SCD on HRQOL; however, in this study, we were able to conduct a more detailed analysis by quantitatively evaluating the strength of the impact of SCD severity on HRQOL. In particular, the finding that the degree of SCD awareness is related to HRQOL in women is an advancement of previous findings, and it has been clarified that the severity of subjective cognitive decline is a significant risk factor for a decline in HRQOL.

No significant association was observed between subjective cognitive decline severity and HRQOL scores in men. This suggests that men’s tendency to underestimate changes in their cognitive function [35] may indicate that their awareness of subjective cognitive decline does not directly impact their HRQOL. Additionally, it has been reported that men tend to see their physical health as the main indicator of HRQOL and are more sensitive to physical discomfort than to changes in cognitive function [36]. Therefore, the impact of awareness of subjective cognitive decline on HRQOL may be smaller in women than in men.

The results of the interaction analysis (Table 5) further support this sex difference. The interaction term between SCD severity and sex was statistically significant, both before and after applying sample weighting. This finding suggests that the effect of SCD severity on HRQOL differs by sex. Specifically, this relationship was not observed in men, whereas an increase in SCD severity was associated with lower HRQOL in women. The stability of this result, even after weighting adjustment, highlights that the observed sex difference is unlikely to be influenced by sampling bias. This aligns with previous research indicating that women are more likely than men to perceive and report cognitive decline and that their subjective perception of cognitive function is closely tied to psychological well-being [5,33]. The findings suggest that interventions targeting HRQOL in older adults should consider not only the presence of subjective cognitive decline but also its differential impact by sex.

This study showed that older adults with physical pain had a lower HRQOL than those without pain. Previous studies on older adults living in the community have also reported that the intensity [2], number [37], and severity of central sensitization [2] of pain can cause a decline in HRQOL. The results of this study support those of previous studies. Furthermore, physical pain was associated with a severe decline in subjective cognitive function in women. Previous research [5] has also reported that the presence of pain can affect the occurrence of subjective cognitive decline. Chronic pain can cause depression [38] and anxiety [39], and these psychological factors can affect self-assessments of cognitive function [5]. In particular, women are sensitive to pain [40], and psychological stress caused by pain can intensify the subjective awareness of forgetfulness [41].

Sample weighting was applied based on population demographics to address potential biases caused by the unequal distribution of male and female participants. After applying weighting, the statistical significance of the sex difference in the number of health conditions changed (p = 0.04), whereas the other results remained stable. These findings suggest that the influence of physical health factors, such as comorbidities, should be carefully considered when analyzing sex differences in HRQOL and SCD.

The results of this study provide important suggestions for interventions to maintain and improve the quality of life of older adults. In particular, psychological support for changes in cognitive function is necessary for women, because the severity of subjective cognitive decline is associated with a decline in HRQOL [42]. Specifically, interventions, such as cognitive behavioral therapy [43] and supportive counseling [44], may be effective. However, for men, maintaining and improving physical health is likely to contribute to improving HRQOL. It is important to address the physical aspects of the problem, such as pain management [45], promoting physical activity [46], and improving sleep quality [47].

This study had some limitations. First, this study used a cross-sectional design; therefore, it was not possible to clarify the causal relationships between the indicators. In the future, it will be necessary to conduct a longitudinal study to clarify the causal relationships by tracking changes over time. Second, while sample weighting was applied to adjust for sex imbalances, residual confounding factors may still exist. Future studies should consider refining weighting techniques or using propensity score matching to enhance the robustness of the findings. Third, while we applied certain exclusion criteria, we did not account for medication use or underlying conditions that could influence cognitive status. Future studies should incorporate these factors to enhance the reliability of the findings. Fourth, although anxiety is known to influence subjective cognitive decline, we did not assess it in this study. Including measures of anxiety in future research would provide a more comprehensive understanding of its impact on cognitive perception and health-related quality of life. Finally, the assessment of the severity of subjective cognitive decline relies on self-reports and does not distinguish between the effects of different cognitive domains, such as memory and attention. Future research should use standardized functional tests for each cognitive domain, in combination with self-reports, to examine the relationship between the severity of subjective cognitive decline and objective cognitive function in detail.

5. Conclusions

In conclusion, the severity of subjective cognitive decline appeared to be associated with a decline in HRQOL in older Japanese women, whereas physical health was the main determinant of HRQOL in men. However, given the cross-sectional nature of this study and its methodological limitations, these findings should be interpreted with caution. Further longitudinal research is needed to confirm these associations. Nevertheless, our results suggest that healthcare professionals in geriatrics consider psychological interventions for women that combine psychoeducation and cognitive–behavioral therapy, as well as interventions that emphasize maintaining physical health for men, such as promoting physical activity and pain management. Providing appropriate sex-specific support may help improve the HRQOL of older people.