Association of Loneliness with Frailty and Functional Status
Kay Thwe Kyaw, DrPH, M.B., B.S, MPH 1
1: Founder of kaytharalotus LLC
Association of Loneliness with Frailty and Functional Status © 2006 by Kay Thwe Kyaw is licensed under CC BY 4.0. To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/
ABSTRACT
Introduction:Previous research findings showed that psychosocial factor, loneliness and social supports, are modifiable factors for. improving frailty, and maintain the functional ability. However, prior studies focused on association of loneliness with frailty and functional status were not generalizable to racially diverse population. Thus, we evaluated whether lower levels of loneliness were associated with decreased frailty and decreased impaired functional status using HAALSI (Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community in South Africa).
Method: We conducted a cross-sectional study using 347 participants from the HAALSI Dementia Cohort. Exposure was self-reported loneliness. Outcomes: frailty (measured by Fried’s frailty) and functional status (measured by ability to perform instrumental activities of daily living). Generalized estimating equation regression was carried out to find association of loneliness with frailty and functional status.
Results: This study did not find any association of loneliness with frailty and functional status. However, pre-frail individuals were more likely to associate with loneliness compared to frail at (β: 1.0110, 95 % CI: 0.0236, 1.9984) when adjusted for age, gender, education, and depression and (β: 1.0326 95 % CI: 0.0454, 2.0197) when adjusted for age, gender, education, depression, and vascular risk factors in Women. Men who reported at least 1 day of loneliness were less likely to have at least one declining IADL (β: -0.9239, 95 % CI: -1.8317, -0.0161).
Conclusions: Although this study did not find any association of loneliness with and frailty and declining IADLs in the HAALSI, gender seem to modify these association.
Keywords: Loneliness, frailty, functional status, older adults
INTRODUCTION
Healthy aging is essential to increasing life expectancy in Sub-Saharan Africa and decreasing the burden of age-related diseases in this community (HAALSI: Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community in South Africa, 2021). Given the rapidly increasing older population, healthy aging, defined by the WHO as “the process of developing and maintaining the functional ability that enables well-being in older age” is essential to increasing life expectancy in Sub-Saharan Africa and decreasing the burden of age-related diseases in this community (Organization, 2020). An individual’s functional ability can be measured by their capacity to perform basic activities of daily living (ADLs) and instrumental activities of daily living (IADLs) (Edemekong et al., 2022; Guo & Sapra, 2022; Hardy et al., 2004). One process that can directly impact an individual’s ability to participate in these ADLs and IADLs in the development of frailty, an age-related syndrome of physical and mental decline that predisposes individuals to adverse health outcomes, especially when exposed to stressors (Fried; Fried et al., 2021; Fried et al., 2001). Frailty is a complex clinical syndrome that develops in the setting of dysregulated metabolic and musculoskeletal systems that worsen with aging that contribute to frailty non-additively (Daly & Ruff, 2007; Fried et al., 2021; Whitson et al., 2016). Frailty and functional ability are both influenced by loneliness, in addition to other psychosocial, medical, and environmental factors (Hale et al., 2019; Organization, 2020). Loneliness has been defined as a subjective feeling of dissatisfaction with one’s available social supports or contacts; it is a psychosocial and emotional condition with many contributing factors, including social relationships, social isolation, and emotional isolation (Gale et al., 2018; Mullins, 2007). The prevalence of loneliness among older adults in individual countries varies globally by population, age, and measurement of loneliness (Davies et al., 2021). Although previous research identified an association of loneliness with frailty and functional status, there were insufficient findings on these associations, and the studies were not conducted in a diverse population (Davies et al., 2021; Gale et al., 2018; Herrera-Badilla et al., 2015; Hoogendijk et al., 2016; Payne et al., 2017; Sha et al., 2020; Shankar et al., 2017). Given the paucity of findings from previous studies, this study aimed to explore the association between loneliness and individuals’ frailty and functional status (Fried; Fried et al., 2021; Fried et al., 2001). We propose that lower levels of loneliness are associated with decreased frailty and increased functional status in a longitudinal cohort of rural South African older adults surveyed as part of the HAALSI Dementia Cohort (Bassil et al., 2021).
METHODS
We conducted a cross sectional study using participants from the Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community in South Africa (HAALSI) Dementia Cohort (Bassil et al., 2021). The study sample was selected from this cohort (n = 635) using stepwise selection, with the final analysis including 347 participants. Inclusion criteria consisted of diagnosis of dementia; age 49 years and above during the study period (2019–2020); and the availability of information on loneliness, weight, height, and body mass index (BMI). Participants with a history of stroke (n = 33); a history of traumatic brain injury (n = 44); missing information on loneliness (n = 4); missing information on weight, height, and BMI (n = 202); age <49 years (n = 4); and other missing information (n = 1) were excluded (Figure 1). Participants’ who had history of traumatic brain injury and stroke were excluded from the sample selection to avoid bias (Pinkston et al., 2009; Shively et al., 2012). Collaboration institution approved for this research. As this study utilized secondary data and de-identifying information, submission to Institutional Review Board was not required.
Exposure
Loneliness was assessed using participants’ responses to one of the items on the CES-D scale (Radloff, 1977): “The Past Week Felt Lonely.” Four responses were possible: “Rarely or None of the Time (Less than 1 Day)”; “Some or Little of the Time (1–2 Days)”; “Occasionally or a Moderate Amount of Time (3–4 Days)”; and “Most or All of the Time (5–7 Days)” (Radloff, 1977). A three-level ordinal variable of loneliness was constructed as follows: “low” for the response Rarely or None of the Time (Less than 1 Day) and “medium” for the responses Some or Little of the Time (1–2 Days) and Occasionally or a Moderate Amount of Time (3–4 Days), and “high” for the response Most or All of the Time (5–7 Days). A binary variable of loneliness was constructed by assigning 0 for the response Rarely or None of the Time (Less than 1 Day) and 1 for the responses Some or Little of the Time (1–2 Days), Occasionally or a Moderate Amount of Time (3–4 Days), and Most or All of the Time (5–7 Days).
Outcomes
Five components of frailty were assessed: weight loss, exhaustion, physical activity, walk time, and grip strength (Fried et al., 2001).
Weight loss: Bodyweight in the current year (kg) was subtracted from body weight in the previous year, and the result was divided by body weight in the previous year to calculate the weight loss criterion K (Richardson et al., 1994). K ≥ 0.05 indicates frailty by this criterion.
Exhaustion: Participants’responses to two items from Center for Epidemiology Studies Depression (CES-D) scales were used to assess exhaustion. Responding “A Moderate Amount of Time (3–4 Days)” to the item “I Could Not Get Going” or “Most of the Time” to the item “Felt that Everything I Did Was an Effort” indicate frailty in this criterion (Fried et al., 2001).
Physical activity: This criterion was evaluated using a modified version that includes the total number of hours spent engaged in sedentary behaviours, such as watching television, reading, and napping.). The number of sedentary hours in a week (reverse scoring) was converted to kcal with the formula kcal = weight (kg)/hours*7. We designated kcal values >383 in men and >270 in women as indicative of frailty in this criterion (Richardson et al., 1994).
Walk time: The amount of time required by each participant (in seconds s) to walk 5 meters (16 feet) was measured and compared against thresholds assigned by gender and height. Men with height >173 cm and walk time ≥6 s or with height ≤173 cm and walk time ≥7 s were considered frail. Women with height >159 cm and walk time ≥6 s or with height ≤159cm and walk time ≥7 s were considered frail (Fried et al., 2001).
Grip strength: Grip strength was measured by a handheld device Dynamometer and compared against thresholds assignedby gender and BMI. Men with BMI ≤28 and grip strength ≤30 kg or with BMI >28 and grip strength ≤32 kg was considered frail. Women with BMI ≤29 and grip strength ≤30 kg or with BMI >29 and grip strength ≤21 were considered frail (Fried et al., 2001).
From the five frailty criteria (weight loss, exhaustion, physical activity, walk time, and grip strength), a multinomial/ordinal variable for frailty was constructed as follows: frail (meeting ≥3 frailty criteria), prefrail (meeting <3 frailty criteria), and not frail (no frailty criteria). In addition, a binary variable for frailty was constructed in which “frail” meant meeting ≥1 frailty criterion and “not frail” meant meeting no frailty criteria according to Fried’s frailty criteria (Fried et al., 2001).
Functional status was obtained by self-reported answer to survey question of ability to participate in IADLs: preparing meals, managing money, driving or using public transportation, shopping, using the telephone, and managing medication (Marshall et al., 2011). A binary variable for total IALDs was created by assigning 1 for at least one declining IADL or 0 for no declining IADLs.
Covariates
Covariates included age, gender, education, depression, and vascular risk factors. Educational attainment was assessed as a four-level variable (no education, preschool to grade 7, grade 8 to grade 11, and at least partial tertiary education). Depression was assessed with the CES-D scale, with the exclusion of items on loneliness and exhaustion to avoid measurement bias when assessing depression (Lee et al., 2020). Participants were considered to have vascular risk factors if they reported a previous diagnosis of hypertension or diabetes mellitus.
Statistical Analysis
Based on findings from previous research studies, a priori power calculation was carried out and showed that at least 10 participants were required for effect sizes of 2.6 for higher loneliness and frailty, 1.57 for medium loneliness and frailty, and 1.71 for loneliness and IADLs. Missing information of variables was imputed using Hot Deck imputation (Fritsch et al., 2005). Primary statistical analyses were carried out with generalized estimating equations models; a binomial model was used for frail vs. not frail outcome, and multinomial models were used for presence vs. absence of frailty, and prefrail status vs. absence of frailty outcomes. Next, any effect modifications or interactions were assessed among the following demographic factors: age (<70 years and ≥70 years), gender and educational level (no education and at least some education). Statistical significance for interaction was determined using an exploratory p < 0.10. All other analyses used a significance level of p < 0.05. All analyses were carried out in Statistical Analysis Software (SAS), version 9.4.
RESULTS
Among 347 participants, the mean age was 69.06 ± 10.6 years; women (64.27 %); The mean depression score was 9.55 ± 8, 51.1 % reported having education, and had vascular risk factors (60.1%). In our sample, 59.9% of study participants reported being lonely Rarely or None of the Time (Less than 1 Day) and having higher proportion of participants were prefrail (70.6%) (Table 1). The majority (59.9%) of study participants reported being lonely Rarely or None of the Time (Less than 1 Day); 40.1% were lonely at least 1 day in the previous week. Most participants were prefrail (70.6%); 15.9% were frail, and 13.5% were not frail (Table 1). After adjusting for age, gender, and education (model 1), we did not observe an association between loneliness and frailty in our sample. This persisted after subsequent adjustments for depression (model 2) and depression and vascular risk factors (model 3). Similarly, there was no association between loneliness and declining IADLs in all adjusted models (Tables 2 and 3).
We did find that gender significantly modified several outcome variables, and thus we conducted multiple robust regression analyses stratified by gender. In subsequent analyses stratified by sex, females who reported being lonely for at least 1 day were more likely to be prefrail than not frail with adjustment for age, gender, education, and depression (β = 1.0110, 95% confidence interval (CI) 0.0236, 1.9984) and with adjustment for age, gender, education, depression, and vascular risk factors (β = 1.0326, 95% CI: 0.0454, 2.0197). Men who reported at least 1 day of loneliness were less likely to have at least one declining IADL (β = -0.9239, 95% CI:-1.8317, -0.0161) (Tables 4 and 5).
DISCUSSION
Previous observational studies have observed a relationship between loneliness and frailty. For example, two longitudinal studies examining these relationships in the UK used the UCLA Three-Item Loneliness Scale to assess loneliness and a frailty index to assess frailty. One of these studies (2004–2017) found that medium and higher levels of loneliness increased the risk of frailty (Davies et al., 2021), and the other found that higher levels of loneliness were associated with an increased risk of being frail and prefrail (Gale et al., 2018). Other observational studies such as the Coyoacán Cohort study, a 3-6 year Chinese longitudinal study, and a longitudinal study using an urban Amsterdam cohort demonstrated similar findings that individuals with a high level of loneliness were at an increased risk for frailty (Herrera-Badilla et al., 2015; Sha et al., 2020).
However, the present study did not find an association between loneliness and frailty or functional status. One explanation for this, is that unlike the aforementioned studies, the HAALSI cohort recruited participants from a predominantly rural. Prior studies have demonstrated that rural older adults were more likely to be in poor physical and cognitive health compared to their urban counterparts (Cohen et al., 2018). This is likely multifactorial, but limited access to healthcare resources, reduced physical activity, and limited health food options may be contributing factors (Xu et al., 2021). In view of cross sectional, we do not know the baseline health status of study participants and physical activity in HAALSI Cohort, a conclusion that is supported by the high proportion of pre-frail and frail individuals in the cohort; it may have been more difficult to recognize the impact that loneliness had on further impairment on physical health and functional status. Furthermore, adjustment for vascular risk factors was likely not sufficient to capture the impact of comorbid medical conditions, and future studies should examine the impact of baseline health on the association between loneliness and frailty in rural populations with greater granularity.
In models stratified by sex, loneliness was associated with pre-frail status (versus absence of frailty) only among women after adjusting for depression and vascular risk factors. Thus, there may be gender specific differences in participants that are related to depression and vascular risk factors that play a more influential role in determining whether loneliness relates to early levels of frailty. For example, older women are likely to have begun or completed the menopausal transition, a biological state that is associated with increased risk for hypertension and depressive mood, likely due to declining oestrogen levels (Prabakaran et al., 2021), as well as osteoporosis and higher rates of frailty (Freeman et al., 2004; Ruan et al., 2020). Although older men may be more likely to experience frailty as they age, they do not have a related biological state that predisposes them to similar risk factors. Additionally, previous research has found gender differences in loneliness (Hutten et al., 2021; Pagan, 2020); specifically that women were more likely to report higher loneliness scores than men (Borys & Perlman, 1985; Pagan, 2020), although there is limited evidence to suggest that there is a clear biological sex-based difference for these findings.
One strength of this study is that we maximized internal validity by minimizing selection bias through stepwise selection and strict inclusion/exclusion criteria, such as the exclusion of participants with missing information on weight, height, BMI, and grip assessment were excluded to avoid measurement bias. In addition, although our findings are mainly generalizable to the HAALSI population, this cohort represents a more racially and socioeconomically diverse population than those examined in previous cohort studies. Given the cross-sectional nature of this study, temporal or causal associations between loneliness and frailty or IADLs could not be analyzed, and the possibility of reverse causality (e.g., the poor functional status may have prevented individuals from engaging with peers, resulting in increased loneliness) could not be addressed. Additionally, because loneliness information and IADLs information were obtained from a survey questionnaire, we could not avoid respondent bias or recall bias, which may have impacted the internal validity of the findings. Finally, this study did not account for the possibility that home individuals with declining functional status may enlist the help of home care support, which may affect both their functional status and perception of loneliness.
CONCLUSION:
This cohort study did not find any association of loneliness with frailty or functional status in the HAALSI sample of older adults in Sub-Saharan Africa. However, associations between loneliness and frailty were identified among women, as well as associations between loneliness and poorer functional status in men. These findings further support the need to account for sociocultural and sex-based differences in diverse communities in the investigation of these pathways and in understanding the generalizability of prior studies. The findings of this study may guide future longitudinal studies into the association of loneliness with frailty and functional status.
Table 1. Characteristics of Study Participants in HAALSI Dementia Cohort (2019-2020)
| n=347 | n (%) |
| Age (Years) | |
| Mean ± SD | 69.06 ± 10.6 |
| Gender | |
| Women | 223 (64.3) |
| Men | 124 (35.7) |
| Education | |
| None | 170 (48.9) |
| Preschool to Grade 7 | 131 (37.8) |
| Grades 8 to 11 | 26 (7.5) |
| At least partial Tertiary | 20 (5.8) |
| Depression (CES-D) | |
| (mean ± SD) | 9.55 ± 8.0 |
| Vascular Risk (check again) | |
| Present | 211 (60.8) |
| Absent | 136 (39.2) |
| Frailty Criteria | |
| Weight Loss Frailty Criteria (Yes) | 93 (26.8) |
| (No) | 254 (73.2) |
| Exhaustion Frailty Criteria (Yes) | 224 (64.5) |
| (No) | 123 (35.5) |
| Physical activity Frailty Criteria (Yes) | 45 (13.0) |
| (No) | 302 (87.0) |
| Walk-time frailty criteria (Yes) | 107 (30.8) |
| (No) | 240 (69.2) |
| Grip strength frailty criteria (Yes) | 41 (11.8) |
| (No) | 306 (88.2) |
| Frailty | |
| Frail | 300 (86.5) |
| No Frail | 47 (13.5) |
| Level of Frailty | |
| Frail | 55 (15.9) |
| Pre-frail | 245 (70.6) |
| No Frail | 47 (13.5) |
| Functional Status | |
| IADLs scores | 0.75 ± 1.3 |
| Loneliness | |
| Rare or < 1 day 2 | 208 (59.9) |
| At least 1 day | 139 (40.1) |
| Level of Loneliness | |
| Rare or < 1 Day | 208 (59.9) |
| Some of the time | 105 (30.3) |
| Moderate to most of the time | 34 (9.8) |
Vascular Risk: having diabetes and hypertension; Some: Loneliness having < day 1 to some or little of the Time (1-2 Days); Moderate to most of the time; Loneliness having occasionally or a Moderate Amount of Time (3-4 Days) and Most or All of the Time (5-7 Days). IADLs: Instrumental activities of daily living.
Table 2. Generalized Estimated Equation Models for Association between Loneliness§ and Frailty§§
| n=347 | Frail vs. No Frail§§ | Nominal Frailty | ||||
| Frail vs. No Frail§§ | Prefrail vs. No Frail§§ | |||||
| β | 95 % CI | β | 95 % CI | β | 95 % CI | |
| Lonely vs. Rare Lonely | ||||||
| Model 1 | ||||||
| Lonely | -0.2860 | -0.9422, 0.3701 | 0.2190 | -0.6267, 1.0647 | 0.2867 | -0.3747, 0.9480 |
| Model 2 | ||||||
| Lonely | -0.3870 | -1.1253, 0.3513 | 0.3795 | -0.5739, 1.3330 | 0.3844 | -0.3603, 1.1291 |
| Model 3 | ||||||
| Lonely | -0.3743 | -1.1127, 0.3641 | 0.3651 | -0.5849, 1.3152 | 0.3708 | -0.3748, 1.1164 |
| Level of Loneliness Ref: Rare Lonely | ||||||
| Model 1 | ||||||
| Most Lonely | -0.2636 | -1.3327, 0.8055 | -0.5684 | -2.0231, 0.8862 | -0.2053 | -1.2848, 0.8743 |
| Some Lonely | -0.2936 | -0.9971, 0.4099 | -0.1347 | -1.0331 0.7636 | -0.3132 | -1.0235, 0.3970 |
| Model 2 | ||||||
| Most Lonely | -0.4156 | -1.6763, 0.8450 | -0.8784 | -2.5470, 0.790 | -0.3407 | -1.6129, 0.9315 |
| Some Lonely | -0.3809 | -1.1274, 0.3656 – | -0.3011 | -1.2596, 0.6573 | -0.3930 | -1.1480, 0.3620 |
| Model 3 | ||||||
| Most Lonely | -0.3842 | -1.6483, 0.8800 | -0.8446 | -2.5174, 0.8282 | -0.3059 | -1.5815, 0.9696 |
| Some Lonely | -0.3722 | -1.1179, 0.3735 | -0.2905 | -1.2443, 0.6633 | -0.3839 | -1.1388, 0.3710 |
| Scores of loneliness | ||||||
| Model 1 | -0.1885 | -0.6083, 0.2313 | -0.2690 | -0.8062, 0.2683 | -0.1779 | -0.6044, 0.2486 |
| Model 2 | -0.2634 | -0.7656, 0.2387 | -0.4122 | -1.0695, 0.2452 | -0.2324 | -0.7351, 0.2704 |
| Model 3 | -0.2497 | -0.7532, 0.2538 | -0.4017 | -1.0589, 0.2555 | -0.2200 | -0.7242, 0.2842 |
Model 1. Adjusted for demographic factors. Model 2: Adjusted for depression. Model 3: Adjusted for vascular risk. *: <0.05, **<0.01, *** <0.001. §: Independent Factor; §§: Dependent factor.
Table 3. Generalized Estimate Equation model for Association between Loneliness §and Functional status §§ (IADLs)
| IADLs§§ | ||
| β | 95 % CI | |
| Loneliness | ||
| Model 1 | ||
| Lonely vs Rare Lonely | -0.1933 | -0.6658 ,0.2792 |
| Model 2 | ||
| Lonely vs Rare Lonely with depression | -0.0553 | -0.5957, 0.4852 |
| Model 3 | ||
| Lonely vs Rare Lonely with vascular risk | -0.0575 | -0.5988 ,0.4837 |
| Level of Loneliness | ||
| Model 1 (Ref: Rare Lonely) | ||
| Most Lonely | -0.3662 | -1.1729,0.4404 |
| Some Lonely | -0.1396 | -0.6492,0.3700 |
| Model 2 (Ref: Rare Lonely) | ||
| Most Lonely | -0.1728 | -1.0576 0.7119 |
| Some Lonely | -0.0313 | -0.5930 0.5304 |
| Model 3 (Ref: Rare Lonely) | ||
| Most Lonely | -0.1805 | -1.0648, 0.7038 |
| Some Lonely | -0.0322 | -0.5944, 0.5299 |
| Loneliness scores | ||
| Model 1 | -0.1885 | -0.6083, 0.2313 |
| Model 2 | -0.2634 | -0.7656, 0.238 |
| Model 3 | -0.2497 | -0.7532, 0.2538 |
Model 1. Adjusted for age, gender, and education. Model 2: Adjusted for age, gender, education, and depression. Model 3: Adjusted for age, gender, education, depression, and vascular risk. *: <0.05, **<0.01, *** <0.001. §: Independent Factor; §§: Dependent factor.
Table 4. Generalized Estimate Equation Model for Association between Loneliness §and Frailty §§by Gender
| n=347 | Frail vs. No Frail§§ | Nominal Frailty | ||||
| Frail vs. No Frail§§ | Prefrail vs. No Frail§§ | |||||
| β | 95 % CI | β | 95 % CI | β | 95 % CI | |
| Model1 | ||||||
| Men | 0.1073 | -0.7744, 0.9890 | -0.1656 | -1.7992, 1.4679 | -0.1008 | -0.9906, 0.7889 |
| Women | -0.7398 | -1.7055, 0.2258 | 0.7113 | -0.3973, 1.8199 | 0.7446 | -0.2311, 1.7204 |
| Model2 | ||||||
| Men | 0.0502 | -0.9946, 1.0950 | -0.0586 | -1.1057, 0.9884 | -0.0586 | -1.1057, 0.9884 |
| Women | -1.0077 * | -1.9756, -0.0397 | 0.9902 | -0.1343, 2.1147 | 1.0110 * | 0.0236, 1.9984 |
| Model3 | ||||||
| Men | 0.0577 | -0.9815, 1.0970 | 0.0332 | -2.0571, 2.1236 0.03 | -0.0671 | -1.1098, 0.9756 |
| Women | -1.0290 * | -1.9987, -0.0594 | 1.0133 | -0.1230, 2.1496 | 1.0326 * | 0.0454, 2.0197 |
Model 1. Adjusted for age, gender, and education. Model 2: Adjusted for age, gender, education, and depression. Model 3: Adjusted for age, gender, education, depression, and vascular risk. *: <0.05, **<0.01, *** <0.001. §: Independent Factor; §§: Dependent factor.
Table 5. Generalized Estimate Equation model for Association between Loneliness §and Functional Status §§(IADLs) by Gender
| IADLs§§ | ||
| β | 95 % CI | |
| Lonely vs Rare Lonely | ||
| Model 1 | ||
| Men | -0.9239 * | -1.8317, -0.0161 |
| Women | 0.1562 | -0.4109, 0.7234 |
| Model 2 | ||
| Men | -0.6006 | -1.5933, 0.3921 |
| Women | 0.2297 | -0.4340, 0.8934 |
| Model 3 | ||
| Men | -0.6083 | -1.6189, 0.4024 |
| Women | 0.2269 | -0.4475, 0.9013 |
Model 1. Adjusted for age, gender, and education. Model 2: Adjusted for age, gender, education, and depression. Model 3: Adjusted for age, gender, education, depression, and vascular risk. *: <0.05, **<0.01, *** <0.001. §: Independent Factor; §§: Dependent factor.
No known conflict of interest to disclose.
This research was conducted by Kay Thwe Kyaw while affaliated with Neurology Department of NYU in 2021-2022.
REFERENCES:
Bassil, D. T., Farrell, M. T., Wagner, R. G., Brickman, A. M., Glymour, M. M., Langa, K. M., Manly, J. J., Salinas, J., Tipping, B., Tollman, S., & Berkman, L. F. (2021). Cohort Profile Update: Cognition and dementia in the Health and Aging in Africa Longitudinal Study of an INDEPTH community in South Africa (HAALSI dementia). International journal of epidemiology. https://doi.org/10.1093/ije/dyab250
Borys, S., & Perlman, D. (1985). Gender Differences in Loneliness. Personality and Social Psychology Bulletin, 11(1), 63-74. https://doi.org/10.1177/0146167285111006
Cohen, S. A., Greaney, M. L., & Sabik, N. J. (2018). Assessment of dietary patterns, physical activity and obesity from a national survey: Rural-urban health disparities in older adults. PloS one, 13(12), e0208268. https://doi.org/10.1371/journal.pone.0208268
Daly, J. J., & Ruff, R. L. (2007). Construction of efficacious gait and upper limb functional interventions based on brain plasticity evidence and model-based measures for stroke patients. ScientificWorldJournal, 7, 2031-2045. https://doi.org/10.1100/tsw.2007.299
Davies, K., Maharani, A., Chandola, T., Todd, C., & Pendleton, N. (2021). The longitudinal relationship between loneliness, social isolation, and frailty in older adults in England: a prospective analysis. The Lancet Healthy Longevity, 2(2), e70-e77. https://doi.org/10.1016/S2666-7568(20)30038-6
Edemekong, P. F., Bomgaars, D. L., Sukumaran, S., & Levy, S. B. (2022). Activities of Daily Living. In StatPearls. StatPearls Publishing. Copyright © 2022, StatPearls Publishing LLC.
Freeman, E. W., Sammel, M. D., Liu, L., Gracia, C. R., Nelson, D. B., & Hollander, L. (2004). Hormones and menopausal status as predictors of depression in women in transition to menopause. Arch Gen Psychiatry, 61(1), 62-70. https://doi.org/10.1001/archpsyc.61.1.62
Fried, L. Frailty and Resilience in Aging. History-development-lessons-learned-frailty-concept. World Health Organization. https://www.who.int/ageing/health-systems/4_History-development-lessons-learned-frailty-concept.pdf
Fried, L. P., Cohen, A. A., Xue, Q.-L., Walston, J., Bandeen-Roche, K., & Varadhan, R. (2021). The physical frailty syndrome as a transition from homeostatic symphony to cacophony. Nature Aging, 1(1), 36-46. https://doi.org/10.1038/s43587-020-00017-z
Fried, L. P., Tangen, C. M., Walston, J., Newman, A. B., Hirsch, C., Gottdiener, J., Seeman, T., Tracy, R., Kop, W. J., Burke, G., & McBurnie, M. A. (2001). Frailty in Older Adults: Evidence for a Phenotype. The Journals of Gerontology: Series A, 56(3), M146-M157. https://doi.org/10.1093/gerona/56.3.M146
Fritsch, T., Smyth, K. A., Debanne, S. M., Petot, G. J., & Friedland, R. P. (2005). Participation in Novelty-Seeking Leisure Activities and Alzheimer’s Disease. Journal of Geriatric Psychiatry and Neurology, 18(3), 134-141. https://doi.org/10.1177/0891988705277537
Gale, C. R., Westbury, L., & Cooper, C. (2018). Social isolation and loneliness as risk factors for the progression of frailty: the English Longitudinal Study of Ageing. Age Ageing, 47(3), 392-397. https://doi.org/10.1093/ageing/afx188
Guo, H. J., & Sapra, A. (2022). Instrumental Activity of Daily Living. In StatPearls. StatPearls Publishing. Copyright © 2022, StatPearls Publishing LLC.
HAALSI: Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community in South Africa. (2021). Harvard University. https://haalsi.org/about
Hale, M., Shah, S., & Clegg, A. (2019). Frailty, inequality and resilience. Clinical medicine (London, England), 19(3), 219-223. https://doi.org/10.7861/clinmedicine.19-3-219
Hardy, S. E., Concato, J., & Gill, T. M. (2004). Resilience of Community-Dwelling Older Persons [https://doi.org/10.1111/j.1532-5415.2004.52065.x]. Journal of the American Geriatrics Society, 52(2), 257-262. https://doi.org/https://doi.org/10.1111/j.1532-5415.2004.52065.x
Herrera-Badilla, A., Navarrete-Reyes, A. P., Amieva, H., & Avila-Funes, J. A. (2015). Loneliness Is Associated with Frailty in Community-Dwelling Elderly Adults [https://doi.org/10.1111/jgs.13308]. Journal of the American Geriatrics Society, 63(3), 607-609. https://doi.org/https://doi.org/10.1111/jgs.13308
Hoogendijk, E. O., Suanet, B., Dent, E., Deeg, D. J., & Aartsen, M. J. (2016). Adverse effects of frailty on social functioning in older adults: Results from the Longitudinal Aging Study Amsterdam. Maturitas, 83, 45-50. https://doi.org/10.1016/j.maturitas.2015.09.002
Hutten, E., Jongen, E. M. M., Hajema, K., Ruiter, R. A. C., Hamers, F., & Bos, A. E. R. (2021). Risk factors of loneliness across the life span. Journal of Social and Personal Relationships, 02654075211059193. https://doi.org/10.1177/02654075211059193
Lee, S., Pearce, E., Ajnakina, O., Johnson, S., Lewis, G., Mann, F., Pitman, A., Solmi, F., Sommerlad, A., Steptoe, A., Tymoszuk, U., & Lewis, G. (2020). The association between loneliness and depressive symptoms among adults aged 50 years and older: a 12-year population-based cohort study. The Lancet Psychiatry, 8. https://doi.org/10.1016/S2215-0366(20)30383-7
Marshall, G. A., Rentz, D. M., Frey, M. T., Locascio, J. J., Johnson, K. A., Sperling, R. A., & Alzheimer’s Disease Neuroimaging, I. (2011). Executive function and instrumental activities of daily living in mild cognitive impairment and Alzheimer’s disease. Alzheimer’s & dementia : the journal of the Alzheimer’s Association, 7(3), 300-308. https://doi.org/10.1016/j.jalz.2010.04.005
Mullins, L. C. (2007). Loneliness. In J. E. Birren (Ed.), Encyclopedia of Gerontology (Second Edition) (pp. 93-98). Elsevier. https://doi.org/https://doi.org/10.1016/B0-12-370870-2/00115-3
Organization, W. H. (2020). Healthy ageing and functional ability. World Health Organization. . World Health Organization. https://www.who.int/news-room/questions-and-answers/item/healthy-ageing-and-functional-ability
Pagan, R. (2020). Gender and Age Differences in Loneliness: Evidence for People without and with Disabilities. International journal of environmental research and public health, 17(24). https://doi.org/10.3390/ijerph17249176
Payne, C. F., Wade, A., Kabudula, C. W., Davies, J. I., Chang, A. Y., Gomez-Olive, F. X., Kahn, K., Berkman, L. F., Tollman, S. M., Salomon, J. A., & Witham, M. D. (2017). Prevalence and correlates of frailty in an older rural African population: findings from the HAALSI cohort study. BMC geriatrics, 17(1), 293-293. https://doi.org/10.1186/s12877-017-0694-y
Pinkston, J. B., Alekseeva, N., & González Toledo, E. (2009). Stroke and dementia. Neurological Research, 31(8), 824-831. https://doi.org/10.1179/016164109X12445505689643
Prabakaran, S., Schwartz, A., & Lundberg, G. (2021). Cardiovascular risk in menopausal women and our evolving understanding of menopausal hormone therapy: risks, benefits, and current guidelines for use. Ther Adv Endocrinol Metab, 12, 20420188211013917. https://doi.org/10.1177/20420188211013917
Radloff, L. S. (1977). The CES-D Scale: A Self-Report Depression Scale for Research in the General Population. Applied Psychological Measurement, 1(3), 385-401. https://doi.org/10.1177/014662167700100306
Richardson, M. T., Leon, A. S., Jacobs, D. R., Ainsworth, B. E., & Serfass, R. (1994). Comprehensive evaluation of the Minnesota leisure time physical activity questionnaire. Journal of Clinical Epidemiology, 47(3), 271-281. https://doi.org/https://doi.org/10.1016/0895-4356(94)90008-6
Ruan, H., Hu, J., Zhao, J., Tao, H., Chi, J., Niu, X., Zhang, J., & Wang, Y. (2020). Menopause and frailty: a scoping review. Menopause, 27(10), 1185-1195. https://doi.org/10.1097/gme.0000000000001612
Sha, S., Xu, Y., & Chen, L. (2020). Loneliness as a risk factor for frailty transition among older Chinese people. BMC geriatrics, 20(1), 300. https://doi.org/10.1186/s12877-020-01714-5
Shankar, A., McMunn, A., Demakakos, P., Hamer, M., & Steptoe, A. (2017). Social isolation and loneliness: Prospective associations with functional status in older adults. Health Psychol, 36(2), 179-187. https://doi.org/10.1037/hea0000437
Shively, S., Scher, A. I., Perl, D. P., & Diaz-Arrastia, R. (2012). Dementia Resulting From Traumatic Brain Injury: What Is the Pathology? Archives of Neurology, 69(10), 1245-1251. https://doi.org/10.1001/archneurol.2011.3747
Whitson, H. E., Duan-Porter, W., Schmader, K. E., Morey, M. C., Cohen, H. J., & Colón-Emeric, C. S. (2016). Physical Resilience in Older Adults: Systematic Review and Development of an Emerging Construct. The journals of gerontology. Series A, Biological sciences and medical sciences, 71(4), 489-495. https://doi.org/10.1093/gerona/glv202
Xu, R., Li, Q., Guo, F., Zhao, M., & Zhang, L. (2021). Prevalence and risk factors of frailty among people in rural areas: a systematic review and meta-analysis. BMJ open, 11(4), e043494. https://doi.org/10.1136/bmjopen-2020-043494
Suggested Citation:
Kyaw, Kay Thwe. “Association of Loneliness with Frailty and Functional Status.” Kaytharalotus, 2026, https://kaytharalotus.com/loneliness-and-frailty/.