C International Psychogeriatric Association 2014 International Psychogeriatrics (2014), 26:7, 1221–1229 doi:10.1017/S1041610214000611
Coexisting medical comorbidity and depression: Multiplicative effects on health outcomes in older adults ...........................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................
Cyrus SH Ho, Liang Feng, Johnson Fam, Rathi Mahendran, Ee Heok Kua and Tze Pin Ng Gerontology Research Programme and Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
ABSTRACT
Background: Depression in the elderly is often associated with coexisting medical illnesses. We investigated the individual and combined impacts of depression and medical illnesses on disability and quality of life among community-living older persons. Methods: Cross-sectional and longitudinal analyses of data from 1,844 participants aged 55 and above of the Singapore Longitudinal Aging Study (SLAS-1). Baseline depressive symptoms (Geriatric Depressive Scale, GDS5) and chronic medical comorbidity (2) from self-reports were related to baseline and 2-year follow up instrumental and basic activities of daily living (IADL-BADL), and quality of life (Medical Outcomes Study 12-item Short Form (SF-12) physical component summary (PCS) and mental component summary (MCS) scores. Results: The prevalence of depressive symptoms was 11.4%. In main effect analyses of cross-sectional and longitudinal relationships, depression and medical comorbidity were individually associated with higher risk of IADL-BADL disability and lower PCS and MCS scores of quality of life, and only medical comorbidity was associated with increased risk of hospitalization. Significant interactive effects of depression and medical comorbidity were observed in longitudinal relationships with IADL-BADL disability (p = 0.03), PCS (p < 0.01), and MCS (p < 0.01) scores at follow up. The associations of medical comorbidity with increased odds of IADL-BADL disability and decreased SF-12 PCS and MCS scores were at least threefolds stronger among depressed than nondepressed individuals. Conclusion: Medical comorbidities and depression exert additive and multiplicative effects on functional disability and quality of life. The adverse impact and potential treatment benefits of coexisting mental and physical conditions should be seriously considered in clinical practice. Keywords: Elderly, depression, medical comorbidity outcomes
Introduction It is estimated that 84% of people aged 65 and above have one or more chronic medical illness (Hoffman et al., 1996). The most common chronic medical illnesses associated with old age are cerebrovascular diseases, heart diseases, arthritis, and cataract, though considerable variability exist in the general population (Patten et al., 2005). Chronic physical diseases have high comorbidity (co-occurrence) with mental disorders (Ortega et al., 2006). Major
Correspondence should be addressed to: A/P Tze-Pin Ng, Gerontology Research Programme and Department of Psychological Medicine, National University of Singapore, NUHS Tower Block, 9th Floor, 1E Kent Ridge Road, Singapore 119228, Singapore. Phone: 65-67723478; Fax: 65-67772191. Email: [email protected]. Received 11 Feb 2014; revision requested 6 Mar 2014; revised version received 10 Mar 2014; accepted 11 Mar 2014. First published online 15 April 2014.
depression and depressive symptoms affect between 5% and 10% of the elderly in the outpatient setting (Harpole et al., 2005). It is well-known that chronic medical conditions result in impaired physical functioning and reduced quality of life. According to the Medical Outcomes Study, those with diabetes, myocardial infarction, congestive heart failure, chronic lung problems, arthritis, back problems, gastrointestinal disorders, and angina showed significantly worse physical, role and social functioning with poorer health perception compared to those without these conditions (Stewart et al., 1989). In particular, gastrointestinal conditions, cerebrovascular conditions, renal diseases, and musculoskeletal conditions contribute to poorer quality of life as compared to other conditions (Sprangers et al., 2000). Depression is a principal leading cause of disability-adjusted life years lost and is associated
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with increased healthcare utilization in the elderly (Golden et al., 2008; Penninx et al., 1999). In a longitudinal study, depressed older persons had increased risks of disability in activities of daily living (67%) and mobility (73%) at the end of 6 years, irrespective of their chronic medical conditions at baseline (Penninx et al., 1999). An increase in the number of depressive symptoms is also associated with increased mortality, suggesting a dose-response relationship (Whooley and Browner, 1998). The severity of depressive symptoms is inversely related to patients’ health-related quality of life even after controlling for age, gender, and medical comorbidities (Unützer et al., 2000; Pyne et al., 1997). Effective treatment of depression on the other hand improves functional outcomes (Coulehan et al., 1997). The nature of the combined impact of both physical and mental disorders on functional wellbeing and quality of life in an aging population is not well delineated, and may be described by additive and interactive models of comorbidity (Schettini Evans and Frank, 2004). An additive model suggests that the individual components of comorbid disorders have independent effects on functioning and the combined effect is approximately equal to the sum of the parts. On the other hand, an interactive model suggests that multiple comorbidities may be associated with significantly greater levels of functional outcomes than the summed effect of each individual disorder, as the presence of one disorder may alter the association of another disorder. Some studies have reported that the combined negative effects of mental disorders and chronic medical conditions on functioning are additive in nature (Buist-Bouwman et al., 2005; Wells et al., 1989), while others have found that the combined effects are interactive and nonadditive (Lim et al., 2012; Scott et al., 2009). These studies have mainly focused on the effects of individual chronic medical disorders with mental conditions not limited to solely depression. Furthermore, the populations surveyed in these studies were of relatively younger age at 20–59 years old (Lim et al., 2012) and had lesser Asian representation that comprised of people from only Japan and several parts of China out of a total of 17 countries surveyed (Scott et al., 2009). In this population-based prospective cohort study with 2-year follow up of older persons, we investigated whether the presence of depression and medical comorbidity was independently associated with poorer functional and/or quality of life outcomes, and whether their combined presence had a multiplicative (nonadditive) association with function and/or quality of life outcomes.
Method Study population This study was based on baseline and follow up data collected from the first wave cohort (SLAS1, N = 2805) of participants who were older adults aged 55 or above, who were recruited from door-to-door census in South East region of Singapore between 2003 and 2004, and followed up at 2 years after baseline interviews. Details of the SLAS study design, population sampling and measurements have been described in previous publications. (Niti et al., 2008) Residents who were physically or mentally incapacitated, such as those suffering from terminal illnesses, aphasia from stroke, and profound dementia were excluded. The study was approved by the National University of Singapore Institutional Review Board and all participants provided written informed consent. Trained interviewers conducted the interviews in the language or dialect that the respondents were most conversant in. Baseline data Socio-demographic characteristics included age, gender, ethnicity, education, marital status, living arrangement (as surrogate of socio-emotional support), and housing type and size (as surrogate of income and socio-economic status). Chronic medical illnesses. Baseline data on chronic medical illnesses within the past 1-year was based on questions asked by the trained interviewer: “Have you been told by the doctor that you had any of the following medical conditions?” The list of medical conditions included hypertension, diabetes, dyslipidaemia, ischemic heart diseases, heart failure, asthma, chronic obstructive pulmonary disease, stroke, gastric problems, thyroid problems, arthritis, and major eye problems (cataract and glaucoma). Chronic medical conditions reported were further corroborated with related reports of surgical operations or procedures, and physical identification of medications that they took for their illnesses. Comorbidity was defined as the cooccurrence of two or more medical disorders. Depressive symptoms. The presence of depressive symptoms in the past week was assessed using the locally validated English, Chinese, and Malay versions (Nyunt et al., 2009) of the 15-item Geriatric Depression Scale (GDS) (Yesavage, 1998). The total score was based on counting the responses that were in yes/no format and it ranged from 0 (no depressive symptoms) to 15 (severe depressive symptoms), with scores of 5 or more indicating the presence of depression. GDS is an appropriate scale to use in this study, as it
Depression and medical comorbidity outcomes
is relatively free of measurement artifact due to overlapping somatic symptoms of physical illness and depression. The translated versions of GDS have been found to have good reliability (coefficient of 0.90), sensitivity (96.3%) and specificity (87.5%) for assessing late-life depression in communityliving older Asian adults (Lim et al., 2000; Nyunt et al., 2009). Cognitive functioning was measured using the modified Mini-Mental State Examination (MMSE) (Folstein et al., 1975), which has been validated in the local population with high sensitivity and specificity in identifying dementia (Ng et al., 2007) Respondents with MMSE score of 23 or less were classified as cognitively impaired. Outcome measures Functional disability, quality of life, and hospitalization were measured at baseline and at follow-up. Physical functioning This was assessed by the respondent’s level of dependency in performing basic activities of daily living (BADL) (Mahoney and Barthel, 1965) and instrumental activities of daily living (IADL) (Lawton and Brody, 1969). Functional disability was defined as needing at least some personal assistance in at least one task, and was divided into two categories (IAD-BADL disability versus none). Good construct validity for the basic and instrumental ADL scales were previously demonstrated (Ng et al., 2006; Niti et al., 2007). Quality of life This was measured using the Medical Outcomes Study 12-item Short Form (SF-12) (Ware et al., 1998), which comprised of two subscales: the Mental Component Summary (MCS) and the Physical Component Summary (PCS) measuring mental and physical health functioning, respectively. The scores were computed using the weighted summed scores from the 12 questions, and ranged in values from 0 to 100, with 0 score indicating the lowest level of functioning and 100 score indicating the highest possible level of functioning. The scores of SF12 were measured at baseline and at 1 year later. Hospitalization. Participants were asked whether they were hospitalized and the number of hospitalizations in the previous 1 year at baseline and follow-up interviews. From among 1,850 participants who were reinterviewed at 2-year follow-up visit, and after excluding 6 participants with missing data on depression, the present study included 1,844 participants with complete data for hospitalization and IADL-BADL outcomes. The analytical sample for PCS and MCS quality of life measures was
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based on 1,822 participants with complete data at baseline, and 1,788 participants with complete data at follow up. Compared to the participants in the study, those who were excluded were significantly (p < 0.05) more likely to be male, lived in lower end public housing apartments, and showed a higher rate of cognitive impairment and depressive symptoms. Statistical analysis The baseline covariates and outcome variables were compared between depressed and nondepressed participants by t test or Wilcoxon rank-sum tests for continuous variables or by Chi-square test for categorical variables. Hospitalization and functional disabilities at baseline and follow up were analysed as binary variables, and PCS and MCS measures of quality of life at baseline and follow up were analysed as continuous variables. Multiple logistic and linear regression analyses were performed to examine the main and interactive effects of medical comorbidities and depression on binary and continuous outcome variables. Adjustment covariates in the models included age, gender, education, ethnicity, marital status, housing type, living arrangement, cognitive impairment, and their corresponding baseline outcome measurements (in longitudinal analyses). Main effects (omitting interaction term from the model) in the whole sample for all the outcomes were reported as odds ratio (OR) and 95% confidence interval (CI) for binary outcomes, and regression coefficients and their standard errors (SE) for continuous outcomes. When there was a significant interaction effect of medical comorbidity and depression, OR and corresponding 95% CI of association of medical comorbidity and outcomes were estimated separately for strata of depressed and nondepressed participants, least square means for continuous outcomes based on depression and medical comorbidity subgroups. Bonferroni correction was used to control type I error due to multiple comparison. The family-wise error rate (overall significance level) was controlled at 0.05 for twosided test, and all analysis was performed with SAS 9.2 (SAS Institute, Inc., Cary, NC).
Results Among the total of 1,844 respondents in the survey, 11.4% had a GDS score of 5 or more, and they were classified as depressed. Subjects in both depressed and nondepressed groups had a mean age of greater than 65 and the majority was female. Significantly more individuals in the depressed group were unmarried and living in lower
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Table 1. Baseline characteristics of the study population by depressive status (n = 1,844) DEPRESSED N = 211(%)
NONDEPRESSED N = 1,633 (%)
P
.........................................................................................................................................................................................................................................................................................
Age, mean (SD) Gender (male) Education: Primary and below Secondary/ITE Pre-u/above Ethnicities: Chinese Malay Indian Married (vs. others) Housing type: 12 rooms 3 rooms 45 rooms/private Live alone (vs. others) GDS score, mean (SD) MMSE total score, mean (SD) Normal (26) Mild (2125) Moderate (1120) Severe (110) Cognitive impairment C-morbidities, mean (SD), median Comorbidities: 0 or 1 2 or above Any hospitalization in past year At baseline First follow up IADL-BADL disability At baseline First follow up MCS, mean (SD) At baseline First follow up PCS, mean (SD) At baseline First follow up
66.4 (8.23) 72 (34.1) 121 (57.4) 70 (33.2) 20 (9.5) 202 (95.7) 5 (2.4) 4 (1.9) 135(64.0) 31 (14.7) 63 (29.9) 117 (55.5) 17 (8.1) 7.8 (2.60) 26.0 (4.45) 144 (68.3) 45 (21.3) 19 (9.0) 3 (1.4) 42 (19.9) 1.7 (1.37), 1.0 106 (50.2) 105 (49.8)
65.9 (7.27) 567 (34.7) 820 (50.2) 542 (33.2) 271 (16.6) 1530 (93.7) 54 (3.3) 49 (3.0) 1223 (74.9) 92 (5.6) 371 (22.7) 1170 (71.7) 109 (6.7) 0.98 (1.17) 27.3 (2.96) 1319 (80.8) 250 (15.3) 60 (3.7) 4 (0.2) 160 (9.8) 1.5 (1.20), 1.0 908 (55.6) 725 (44.4)
0.47 0.86 0.02
0.50
Coexisting medical comorbidity and depression: Multiplicative effects on health outcomes in older adults ...........................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................
Cyrus SH Ho, Liang Feng, Johnson Fam, Rathi Mahendran, Ee Heok Kua and Tze Pin Ng Gerontology Research Programme and Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
ABSTRACT
Background: Depression in the elderly is often associated with coexisting medical illnesses. We investigated the individual and combined impacts of depression and medical illnesses on disability and quality of life among community-living older persons. Methods: Cross-sectional and longitudinal analyses of data from 1,844 participants aged 55 and above of the Singapore Longitudinal Aging Study (SLAS-1). Baseline depressive symptoms (Geriatric Depressive Scale, GDS5) and chronic medical comorbidity (2) from self-reports were related to baseline and 2-year follow up instrumental and basic activities of daily living (IADL-BADL), and quality of life (Medical Outcomes Study 12-item Short Form (SF-12) physical component summary (PCS) and mental component summary (MCS) scores. Results: The prevalence of depressive symptoms was 11.4%. In main effect analyses of cross-sectional and longitudinal relationships, depression and medical comorbidity were individually associated with higher risk of IADL-BADL disability and lower PCS and MCS scores of quality of life, and only medical comorbidity was associated with increased risk of hospitalization. Significant interactive effects of depression and medical comorbidity were observed in longitudinal relationships with IADL-BADL disability (p = 0.03), PCS (p < 0.01), and MCS (p < 0.01) scores at follow up. The associations of medical comorbidity with increased odds of IADL-BADL disability and decreased SF-12 PCS and MCS scores were at least threefolds stronger among depressed than nondepressed individuals. Conclusion: Medical comorbidities and depression exert additive and multiplicative effects on functional disability and quality of life. The adverse impact and potential treatment benefits of coexisting mental and physical conditions should be seriously considered in clinical practice. Keywords: Elderly, depression, medical comorbidity outcomes
Introduction It is estimated that 84% of people aged 65 and above have one or more chronic medical illness (Hoffman et al., 1996). The most common chronic medical illnesses associated with old age are cerebrovascular diseases, heart diseases, arthritis, and cataract, though considerable variability exist in the general population (Patten et al., 2005). Chronic physical diseases have high comorbidity (co-occurrence) with mental disorders (Ortega et al., 2006). Major
Correspondence should be addressed to: A/P Tze-Pin Ng, Gerontology Research Programme and Department of Psychological Medicine, National University of Singapore, NUHS Tower Block, 9th Floor, 1E Kent Ridge Road, Singapore 119228, Singapore. Phone: 65-67723478; Fax: 65-67772191. Email: [email protected]. Received 11 Feb 2014; revision requested 6 Mar 2014; revised version received 10 Mar 2014; accepted 11 Mar 2014. First published online 15 April 2014.
depression and depressive symptoms affect between 5% and 10% of the elderly in the outpatient setting (Harpole et al., 2005). It is well-known that chronic medical conditions result in impaired physical functioning and reduced quality of life. According to the Medical Outcomes Study, those with diabetes, myocardial infarction, congestive heart failure, chronic lung problems, arthritis, back problems, gastrointestinal disorders, and angina showed significantly worse physical, role and social functioning with poorer health perception compared to those without these conditions (Stewart et al., 1989). In particular, gastrointestinal conditions, cerebrovascular conditions, renal diseases, and musculoskeletal conditions contribute to poorer quality of life as compared to other conditions (Sprangers et al., 2000). Depression is a principal leading cause of disability-adjusted life years lost and is associated
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with increased healthcare utilization in the elderly (Golden et al., 2008; Penninx et al., 1999). In a longitudinal study, depressed older persons had increased risks of disability in activities of daily living (67%) and mobility (73%) at the end of 6 years, irrespective of their chronic medical conditions at baseline (Penninx et al., 1999). An increase in the number of depressive symptoms is also associated with increased mortality, suggesting a dose-response relationship (Whooley and Browner, 1998). The severity of depressive symptoms is inversely related to patients’ health-related quality of life even after controlling for age, gender, and medical comorbidities (Unützer et al., 2000; Pyne et al., 1997). Effective treatment of depression on the other hand improves functional outcomes (Coulehan et al., 1997). The nature of the combined impact of both physical and mental disorders on functional wellbeing and quality of life in an aging population is not well delineated, and may be described by additive and interactive models of comorbidity (Schettini Evans and Frank, 2004). An additive model suggests that the individual components of comorbid disorders have independent effects on functioning and the combined effect is approximately equal to the sum of the parts. On the other hand, an interactive model suggests that multiple comorbidities may be associated with significantly greater levels of functional outcomes than the summed effect of each individual disorder, as the presence of one disorder may alter the association of another disorder. Some studies have reported that the combined negative effects of mental disorders and chronic medical conditions on functioning are additive in nature (Buist-Bouwman et al., 2005; Wells et al., 1989), while others have found that the combined effects are interactive and nonadditive (Lim et al., 2012; Scott et al., 2009). These studies have mainly focused on the effects of individual chronic medical disorders with mental conditions not limited to solely depression. Furthermore, the populations surveyed in these studies were of relatively younger age at 20–59 years old (Lim et al., 2012) and had lesser Asian representation that comprised of people from only Japan and several parts of China out of a total of 17 countries surveyed (Scott et al., 2009). In this population-based prospective cohort study with 2-year follow up of older persons, we investigated whether the presence of depression and medical comorbidity was independently associated with poorer functional and/or quality of life outcomes, and whether their combined presence had a multiplicative (nonadditive) association with function and/or quality of life outcomes.
Method Study population This study was based on baseline and follow up data collected from the first wave cohort (SLAS1, N = 2805) of participants who were older adults aged 55 or above, who were recruited from door-to-door census in South East region of Singapore between 2003 and 2004, and followed up at 2 years after baseline interviews. Details of the SLAS study design, population sampling and measurements have been described in previous publications. (Niti et al., 2008) Residents who were physically or mentally incapacitated, such as those suffering from terminal illnesses, aphasia from stroke, and profound dementia were excluded. The study was approved by the National University of Singapore Institutional Review Board and all participants provided written informed consent. Trained interviewers conducted the interviews in the language or dialect that the respondents were most conversant in. Baseline data Socio-demographic characteristics included age, gender, ethnicity, education, marital status, living arrangement (as surrogate of socio-emotional support), and housing type and size (as surrogate of income and socio-economic status). Chronic medical illnesses. Baseline data on chronic medical illnesses within the past 1-year was based on questions asked by the trained interviewer: “Have you been told by the doctor that you had any of the following medical conditions?” The list of medical conditions included hypertension, diabetes, dyslipidaemia, ischemic heart diseases, heart failure, asthma, chronic obstructive pulmonary disease, stroke, gastric problems, thyroid problems, arthritis, and major eye problems (cataract and glaucoma). Chronic medical conditions reported were further corroborated with related reports of surgical operations or procedures, and physical identification of medications that they took for their illnesses. Comorbidity was defined as the cooccurrence of two or more medical disorders. Depressive symptoms. The presence of depressive symptoms in the past week was assessed using the locally validated English, Chinese, and Malay versions (Nyunt et al., 2009) of the 15-item Geriatric Depression Scale (GDS) (Yesavage, 1998). The total score was based on counting the responses that were in yes/no format and it ranged from 0 (no depressive symptoms) to 15 (severe depressive symptoms), with scores of 5 or more indicating the presence of depression. GDS is an appropriate scale to use in this study, as it
Depression and medical comorbidity outcomes
is relatively free of measurement artifact due to overlapping somatic symptoms of physical illness and depression. The translated versions of GDS have been found to have good reliability (coefficient of 0.90), sensitivity (96.3%) and specificity (87.5%) for assessing late-life depression in communityliving older Asian adults (Lim et al., 2000; Nyunt et al., 2009). Cognitive functioning was measured using the modified Mini-Mental State Examination (MMSE) (Folstein et al., 1975), which has been validated in the local population with high sensitivity and specificity in identifying dementia (Ng et al., 2007) Respondents with MMSE score of 23 or less were classified as cognitively impaired. Outcome measures Functional disability, quality of life, and hospitalization were measured at baseline and at follow-up. Physical functioning This was assessed by the respondent’s level of dependency in performing basic activities of daily living (BADL) (Mahoney and Barthel, 1965) and instrumental activities of daily living (IADL) (Lawton and Brody, 1969). Functional disability was defined as needing at least some personal assistance in at least one task, and was divided into two categories (IAD-BADL disability versus none). Good construct validity for the basic and instrumental ADL scales were previously demonstrated (Ng et al., 2006; Niti et al., 2007). Quality of life This was measured using the Medical Outcomes Study 12-item Short Form (SF-12) (Ware et al., 1998), which comprised of two subscales: the Mental Component Summary (MCS) and the Physical Component Summary (PCS) measuring mental and physical health functioning, respectively. The scores were computed using the weighted summed scores from the 12 questions, and ranged in values from 0 to 100, with 0 score indicating the lowest level of functioning and 100 score indicating the highest possible level of functioning. The scores of SF12 were measured at baseline and at 1 year later. Hospitalization. Participants were asked whether they were hospitalized and the number of hospitalizations in the previous 1 year at baseline and follow-up interviews. From among 1,850 participants who were reinterviewed at 2-year follow-up visit, and after excluding 6 participants with missing data on depression, the present study included 1,844 participants with complete data for hospitalization and IADL-BADL outcomes. The analytical sample for PCS and MCS quality of life measures was
1223
based on 1,822 participants with complete data at baseline, and 1,788 participants with complete data at follow up. Compared to the participants in the study, those who were excluded were significantly (p < 0.05) more likely to be male, lived in lower end public housing apartments, and showed a higher rate of cognitive impairment and depressive symptoms. Statistical analysis The baseline covariates and outcome variables were compared between depressed and nondepressed participants by t test or Wilcoxon rank-sum tests for continuous variables or by Chi-square test for categorical variables. Hospitalization and functional disabilities at baseline and follow up were analysed as binary variables, and PCS and MCS measures of quality of life at baseline and follow up were analysed as continuous variables. Multiple logistic and linear regression analyses were performed to examine the main and interactive effects of medical comorbidities and depression on binary and continuous outcome variables. Adjustment covariates in the models included age, gender, education, ethnicity, marital status, housing type, living arrangement, cognitive impairment, and their corresponding baseline outcome measurements (in longitudinal analyses). Main effects (omitting interaction term from the model) in the whole sample for all the outcomes were reported as odds ratio (OR) and 95% confidence interval (CI) for binary outcomes, and regression coefficients and their standard errors (SE) for continuous outcomes. When there was a significant interaction effect of medical comorbidity and depression, OR and corresponding 95% CI of association of medical comorbidity and outcomes were estimated separately for strata of depressed and nondepressed participants, least square means for continuous outcomes based on depression and medical comorbidity subgroups. Bonferroni correction was used to control type I error due to multiple comparison. The family-wise error rate (overall significance level) was controlled at 0.05 for twosided test, and all analysis was performed with SAS 9.2 (SAS Institute, Inc., Cary, NC).
Results Among the total of 1,844 respondents in the survey, 11.4% had a GDS score of 5 or more, and they were classified as depressed. Subjects in both depressed and nondepressed groups had a mean age of greater than 65 and the majority was female. Significantly more individuals in the depressed group were unmarried and living in lower
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Table 1. Baseline characteristics of the study population by depressive status (n = 1,844) DEPRESSED N = 211(%)
NONDEPRESSED N = 1,633 (%)
P
.........................................................................................................................................................................................................................................................................................
Age, mean (SD) Gender (male) Education: Primary and below Secondary/ITE Pre-u/above Ethnicities: Chinese Malay Indian Married (vs. others) Housing type: 12 rooms 3 rooms 45 rooms/private Live alone (vs. others) GDS score, mean (SD) MMSE total score, mean (SD) Normal (26) Mild (2125) Moderate (1120) Severe (110) Cognitive impairment C-morbidities, mean (SD), median Comorbidities: 0 or 1 2 or above Any hospitalization in past year At baseline First follow up IADL-BADL disability At baseline First follow up MCS, mean (SD) At baseline First follow up PCS, mean (SD) At baseline First follow up
66.4 (8.23) 72 (34.1) 121 (57.4) 70 (33.2) 20 (9.5) 202 (95.7) 5 (2.4) 4 (1.9) 135(64.0) 31 (14.7) 63 (29.9) 117 (55.5) 17 (8.1) 7.8 (2.60) 26.0 (4.45) 144 (68.3) 45 (21.3) 19 (9.0) 3 (1.4) 42 (19.9) 1.7 (1.37), 1.0 106 (50.2) 105 (49.8)
65.9 (7.27) 567 (34.7) 820 (50.2) 542 (33.2) 271 (16.6) 1530 (93.7) 54 (3.3) 49 (3.0) 1223 (74.9) 92 (5.6) 371 (22.7) 1170 (71.7) 109 (6.7) 0.98 (1.17) 27.3 (2.96) 1319 (80.8) 250 (15.3) 60 (3.7) 4 (0.2) 160 (9.8) 1.5 (1.20), 1.0 908 (55.6) 725 (44.4)
0.47 0.86 0.02
0.50
