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Geriatr Gerontol Int 2016; 16: 606–611
ORIGINAL ARTICLE: EPIDEMIOLOGY, CLINICAL PRACTICE AND HEALTH
Association between employee benefits and frailty in community-dwelling older adults José Alberto Avila-Funes,1,3 Diana Leticia Paniagua-Santos,1 Vicente Escobar-Rivera,2 Ana Patricia Navarrete-Reyes,1 Sara Aguilar-Navarro1 and Hélène Amieva3 1
Department of Geriatrics, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, and 2Medicine, Benemérita Universidad Autónoma de Puebla, Puebla, Mexico; and 3Centre de recherche INSERM, U897, Univ Victor Segalen Bordeaux 2, Bordeaux, France
Aim: The phenotype of frailty has been associated with an increased vulnerability for the development of adverse health-related outcomes. The origin of frailty is multifactorial and financial issues could be implicated, as they have been associated with health status, well-being and mortality. However, the association between economic benefits and frailty has been poorly explored. Therefore, the objective was to determine the association between employee benefits and frailty. Methods: A cross-sectional study of 927 community-dwelling older adults aged 70 years and older participating in the Mexican Study of Nutritional and Psychosocial Markers of Frailty was carried out. Employee benefits were established according to eight characteristics: bonus, profit sharing, pension, health insurance, food stamps, housing credit, life insurance, and Christmas bonus. Frailty was defined according to a slightly modified version of the phenotype proposed by Fried et al. Multinomial logistic regression models were run to determine the association between employee benefits and frailty adjusting by sociodemographic and health covariates. Results: The prevalence of frailty was 14.1%, and 4.4% of participants rated their health status as “poor.” Multinomial logistic regression analyses showed that employee benefits were statistically and independently associated with the frail subgroup (OR 0.85; 95% CI 0.74–0.98; P = 0.027) even after adjusting for potential confounders. Conclusions: Fewer employee benefits are associated with frailty. Supporting spreading employee benefits for older people could have a positive impact on the development of frailty and its consequences. Geriatr Gerontol Int 2016; 16: 606–611. Keywords: developing countries, employee benefits, epidemiology, frail elderly.
Introduction Aging involves a multidimensional process of physical, psychological and social changes. Retirement is one of them, a transition event faced by older people with consequences in emotional, social and financial aspects. Up to 30% of retirees experience trouble coping with this transition, and 7% report their retirement as not
Accepted for publication 3 April 2015. Correspondence: José Alberto Avila-Funes MD, PhD, Department of Geriatrics, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Vasco de Quiroga 15, Colonia Belisario Domínguez Sección XVI, CP 14080, Tlalpan, Distrito Federal, Mexico City, México. Email: [email protected]
606 | doi: 10.1111/ggi.12523
satisfying, which might be explained by poor health status as well as by the lack of economic resources.1,2 There is variability in income and employee benefits (EB) worldwide; such disparities are more evident in developing countries. In Mexico, the legal age to retire oscillates around 60 and 65 years. According to the Organization for Economic Cooperation and Development, Mexico has the highest effective retirement age for men and the second highest for women; however just 41% of the Mexican population have paid contributions at some point in their lives in order to be able to receive a retirement pension or health insurance. Therefore in Mexico, 74.4% of older people have no pension and 28.3% have no health insurance;3,4 these individuals often rely on their family income or in government aid programs aimed at citizens aged over 68 years for economic support. For instance, all adults aged over 68 years living in Mexico City are eligible for © 2015 Japan Geriatrics Society
Employee benefits and frailty
monthly financial aid. The absence of EB could lead to adverse health-related outcomes, such as frailty. Frailty describes a state of increased vulnerability to external stressors characterized by decreased resilience and diminished physiological reserves.5,6 It has been associated with increased risk for disability, institutionalization, hospitalization, falls and mortality.7–13 In contrast, financial issues have been associated with health status, well-being and risk of death.2 Previous studies have shown that worrying about health insurance can lead to adverse health-related outcomes, such as depression, anxiety, fatigue, pain and sleep disorders.14,15 The proposed effects of economics on health are access to primary care, health risk behaviors and trouble taking care of unexpected health events; however, there is a lack of data regarding these social issues. The main objective of the present study was to determine the association between fewer EB and frailty among community-dwelling older people. We hypothesized an inverse association between the number of EB and frailty status.
carried out in two phases. In the first phase, data were collected through a face-to-face interview using a standardized questionnaire administered by interviewers who were previously trained for standardized assessment. Sociodemographic factors (age, sex, social networks, education, employment status and EB) as well as health problems (cognition, functionality, chronic disease, comorbidity, smoking, alcoholism, depressive symptoms and self-reported health status) were investigated during this phase. In the second phase, participants were evaluated by a multidisciplinary team (physician, nutritionist and dentist), and a Comprehensive Geriatric Assessment was carried out including the evaluation of functional status, comorbidity, pharmacological treatments, physical performance, nutritional state, oral health, blood pressure and several measures of anthropometry. Each participant signed an informed consent, and the ethical committees of the National Institute of Medical Sciences and Nutrition, and the National Institute of Public Health approved the study protocol.
Methods
Measures
Participants
Definition of frailty
A cross-sectional study was carried out of a subset of participants of the Mexican Study of Nutritional and Psychosocial Markers of Frailty (Estudio de marcadores nutricios y psicosociales del síndrome de fragilidad) or “the Coyoacán cohort”, a prospective cohort study designed to evaluate nutritional and psychosocial determinants of frailty among Mexican community-dwelling older adults. Coyoacán is one of the 16 districts of Mexico City, its inhabitants represented 3.6% (628 063 inhabitants) of the total population of Mexico City in 2005. This district was selected for recruitment purposes because of logistical convenience reasons. A more detailed description of the methodology of the present study has been reported previously.9 Briefly, participants were identified through the database of the “Food Support, Medical Care and Free Drugs Program,” a government program that includes 95% of communitydwelling older adults aged ≥70 years in Mexico City. Recruitment was drawn from a random sample procedure, stratified by age and sex. The sampling frame was constituted by the “Food Support, Medical Care and Free Drugs Program” database, and the sample unit was individuals (one per house). A sample of 1294 was calculated to ensure a sample size that could estimate a prevalence of at least 14% of frailty among participants, with α = 5% and ß = 20%. The acceptance rate was 86.9%, with a total of 1124 participants being finally included in the study. Baseline data were collected between April 2008 and July 2009 through a questionnaire and a clinical evaluation. Data collection was
Frailty was defined according to the construct validated by Fried et al.; however, the metrics were slightly different, but have been previously validated.9 Weight loss was defined as self-reported unintentional weight loss of 5 kg or more in the previous year. Exhaustion was identified by two questions from the Center for Epidemiological Studies-Depression scale:16 “I felt that everything I did was an effort” and “I could not get going”, participants whose answer was “a moderate amount of the time” or “most of the time” to either of these questions were categorized as frail for this component. Slowness was defined by a positive answer to the next two questions “Does your present state of health limit you to climb a single flight of stairs?” and “Does your present state of health limit you to walk a 100 m block?” Low physical activity was established as the lowest quintile adjusted for sex on the Spanish version of the Physical Activity Scale for the Elderly.17 Weakness was identified when participants answered yes to the following question: “Does your present health status limit you to carry a groceries bag?” As recommended, participants were considered frail if they fulfilled three or more criteria, prefrail if they fulfilled one or two, and non-frail if none.
© 2015 Japan Geriatrics Society
EB EB were established according to eight components: bonus (incentives for attendance, punctuality, efficiency), profit sharing (incentive to employees depending on company’s profitability in addition to regular | 607
JA Avila-Funes et al.
salary), pension (fixed sum paid regularly to a person following retirement), health insurance, food stamps (allows the holder to obtain food and other goods), housing credit, life insurance and Christmas bonus (additional benefit paid by the second week of December). The presence of each item was summed up in a score ranging from 0 to 8, where a higher score indicates more EB.
Covariates Sociodemographic variables included age (years), sex and educational level. Participants were asked whether they had a diagnosis of coronary heart disease, cancer, stroke, hypertension, diabetes, thyroid disorders, arthritis or pain. Self-reported economic status was recorded (good, fair or poor). Current smoking and alcohol intake were also investigated (yes or no). Cognitive function was evaluated through the MiniMental State Examination, the score ranges from 0 to 30, where lower scores indicate poorer cognitive performance.18 Disability for activities of daily living (ADL) was evaluated according to the Katz Index.19 Participants were asked about their ability to carry out the following activities: bathing, dressing, toileting, transferring, continence and feeding themselves. Those participants indicating that they were unable to carry out at least one of the activities without help were considered as having ADL disability.
Sample For the present study, 927 participants aged 70 years and older were considered. However, participants whose phenotype of frailty or employee benefits could not be determined were excluded from the analyses (n = 197). In comparison with excluded participants, those who were included in the statistical analyses were no different regarding age, sex, cognitive function, depressive symptoms or disability for ADL.
Statistical analysis Variables were described using frequencies and proportions or arithmetic means and standard deviations (±SD) where appropriate. In some cases, medians and ranges were also stated. The χ2-test or analysis of variance (ANOVA) test were used according to the analyzed variables. In the case of an abnormal distribution, equivalent non-parametric tests were carried out. To assess the unadjusted effect of the association between EB and frailty, multinomial logistic regression analyses were run. In a second step, multivariate multinomial regression models were built in order to adjust for potential confounder covariates, such as age, sex, edu608 |
cation level, the sum of eight comorbidities (myocardial infarction, stroke, hypertension, cancer, diabetes, thyroid disease, arthritis and pain), cognitive function, disability for ADL and self-perceived economic status. Interaction terms EB*sex and EB*education level were also tested, and were not statistically significant. All statistical tests were carried out at the 0.05 level of confidence and 95% confidence intervals (CI) were given. SPSS software for Windows (version 20.0; SPSS, Chicago, IL, USA) was used to carry out all statistical analyses.
Results Table 1 shows the sociodemographic and clinical characteristics of the study population. The median age was 76.5 years (range 70.3–104.4 years), 54.9% were women and 52.6% lived alone. The most common chronic disease was hypertension (55.9%). Disability for ADL was present in 29.1% of participants. Frailty was present in 14.1% of participants, whereas 37.4% and 48.5% were considered prefrail and non-frail, respectively. A total of 8.7% rated their financial situation as poor and 33.1% reported worsening of financial situation over the past year. Regarding EB, participants that reported receiving a bonus were 12.3%, profit sharing 23.6%, pension 44.9%, health insurance 50.6%, food stamps 15.7%, housing credit 11.6%, life insurance 13.2% and Christmas bonus 54.8%. The mean score of global benefits was 2.3 ± 2.2. In comparison with non-frail participants, frail individuals were older (P < 0.001), mostly female (P < 0.001), more likely to live alone (P < 0.001) and to have a lower Mini-Mental State Examination score (P < 0.001). In addition, frail individuals had more disability for ADL (P < 0.001), more chronic diseases and were more likely to have been hospitalized during the previous year (P < 0.001 for both). Frail participants were also more likely to rent their house (P = 0.036), rated more frequently their financial situation as poor (P = 0.004) and reported worsening of financial situation over the past year (P = 0.001; Table 1). There were fewer frail participants among those who received bonuses (P = 0.033), profit sharing (P = 0.017), health insurance (P = 0.002), food stamps (P = 0.001), housing credit (P = 0.028), life insurance (P = 0.014) and Christmas bonus (P = 0.001). Multinomial logistic regression analyses of frailty status according EB are shown in Table 2. The unadjusted model showed a negative and statistically significant association between EB on prefrail and frail status. However, after adjusting for the aforementioned covariates, EB were no longer associated with prefrail status, but remained statistically associated with the frail subgroup (OR 0.85; 95% CI 0.74–0.98; P = 0.027). For © 2015 Japan Geriatrics Society
Employee benefits and frailty
Table 1 Sociodemographic and clinical characteristics according frailty status
Median age, years (range) Women (%) Years of education (mean ± SD) Living alone (%) Poor financial situation (%) Hypertension (%) Diabetes (%) Cancer (%) Stroke (%) Chronic diseases† (mean ± SD) MMSE
Geriatr Gerontol Int 2016; 16: 606–611
ORIGINAL ARTICLE: EPIDEMIOLOGY, CLINICAL PRACTICE AND HEALTH
Association between employee benefits and frailty in community-dwelling older adults José Alberto Avila-Funes,1,3 Diana Leticia Paniagua-Santos,1 Vicente Escobar-Rivera,2 Ana Patricia Navarrete-Reyes,1 Sara Aguilar-Navarro1 and Hélène Amieva3 1
Department of Geriatrics, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, and 2Medicine, Benemérita Universidad Autónoma de Puebla, Puebla, Mexico; and 3Centre de recherche INSERM, U897, Univ Victor Segalen Bordeaux 2, Bordeaux, France
Aim: The phenotype of frailty has been associated with an increased vulnerability for the development of adverse health-related outcomes. The origin of frailty is multifactorial and financial issues could be implicated, as they have been associated with health status, well-being and mortality. However, the association between economic benefits and frailty has been poorly explored. Therefore, the objective was to determine the association between employee benefits and frailty. Methods: A cross-sectional study of 927 community-dwelling older adults aged 70 years and older participating in the Mexican Study of Nutritional and Psychosocial Markers of Frailty was carried out. Employee benefits were established according to eight characteristics: bonus, profit sharing, pension, health insurance, food stamps, housing credit, life insurance, and Christmas bonus. Frailty was defined according to a slightly modified version of the phenotype proposed by Fried et al. Multinomial logistic regression models were run to determine the association between employee benefits and frailty adjusting by sociodemographic and health covariates. Results: The prevalence of frailty was 14.1%, and 4.4% of participants rated their health status as “poor.” Multinomial logistic regression analyses showed that employee benefits were statistically and independently associated with the frail subgroup (OR 0.85; 95% CI 0.74–0.98; P = 0.027) even after adjusting for potential confounders. Conclusions: Fewer employee benefits are associated with frailty. Supporting spreading employee benefits for older people could have a positive impact on the development of frailty and its consequences. Geriatr Gerontol Int 2016; 16: 606–611. Keywords: developing countries, employee benefits, epidemiology, frail elderly.
Introduction Aging involves a multidimensional process of physical, psychological and social changes. Retirement is one of them, a transition event faced by older people with consequences in emotional, social and financial aspects. Up to 30% of retirees experience trouble coping with this transition, and 7% report their retirement as not
Accepted for publication 3 April 2015. Correspondence: José Alberto Avila-Funes MD, PhD, Department of Geriatrics, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Vasco de Quiroga 15, Colonia Belisario Domínguez Sección XVI, CP 14080, Tlalpan, Distrito Federal, Mexico City, México. Email: [email protected]
606 | doi: 10.1111/ggi.12523
satisfying, which might be explained by poor health status as well as by the lack of economic resources.1,2 There is variability in income and employee benefits (EB) worldwide; such disparities are more evident in developing countries. In Mexico, the legal age to retire oscillates around 60 and 65 years. According to the Organization for Economic Cooperation and Development, Mexico has the highest effective retirement age for men and the second highest for women; however just 41% of the Mexican population have paid contributions at some point in their lives in order to be able to receive a retirement pension or health insurance. Therefore in Mexico, 74.4% of older people have no pension and 28.3% have no health insurance;3,4 these individuals often rely on their family income or in government aid programs aimed at citizens aged over 68 years for economic support. For instance, all adults aged over 68 years living in Mexico City are eligible for © 2015 Japan Geriatrics Society
Employee benefits and frailty
monthly financial aid. The absence of EB could lead to adverse health-related outcomes, such as frailty. Frailty describes a state of increased vulnerability to external stressors characterized by decreased resilience and diminished physiological reserves.5,6 It has been associated with increased risk for disability, institutionalization, hospitalization, falls and mortality.7–13 In contrast, financial issues have been associated with health status, well-being and risk of death.2 Previous studies have shown that worrying about health insurance can lead to adverse health-related outcomes, such as depression, anxiety, fatigue, pain and sleep disorders.14,15 The proposed effects of economics on health are access to primary care, health risk behaviors and trouble taking care of unexpected health events; however, there is a lack of data regarding these social issues. The main objective of the present study was to determine the association between fewer EB and frailty among community-dwelling older people. We hypothesized an inverse association between the number of EB and frailty status.
carried out in two phases. In the first phase, data were collected through a face-to-face interview using a standardized questionnaire administered by interviewers who were previously trained for standardized assessment. Sociodemographic factors (age, sex, social networks, education, employment status and EB) as well as health problems (cognition, functionality, chronic disease, comorbidity, smoking, alcoholism, depressive symptoms and self-reported health status) were investigated during this phase. In the second phase, participants were evaluated by a multidisciplinary team (physician, nutritionist and dentist), and a Comprehensive Geriatric Assessment was carried out including the evaluation of functional status, comorbidity, pharmacological treatments, physical performance, nutritional state, oral health, blood pressure and several measures of anthropometry. Each participant signed an informed consent, and the ethical committees of the National Institute of Medical Sciences and Nutrition, and the National Institute of Public Health approved the study protocol.
Methods
Measures
Participants
Definition of frailty
A cross-sectional study was carried out of a subset of participants of the Mexican Study of Nutritional and Psychosocial Markers of Frailty (Estudio de marcadores nutricios y psicosociales del síndrome de fragilidad) or “the Coyoacán cohort”, a prospective cohort study designed to evaluate nutritional and psychosocial determinants of frailty among Mexican community-dwelling older adults. Coyoacán is one of the 16 districts of Mexico City, its inhabitants represented 3.6% (628 063 inhabitants) of the total population of Mexico City in 2005. This district was selected for recruitment purposes because of logistical convenience reasons. A more detailed description of the methodology of the present study has been reported previously.9 Briefly, participants were identified through the database of the “Food Support, Medical Care and Free Drugs Program,” a government program that includes 95% of communitydwelling older adults aged ≥70 years in Mexico City. Recruitment was drawn from a random sample procedure, stratified by age and sex. The sampling frame was constituted by the “Food Support, Medical Care and Free Drugs Program” database, and the sample unit was individuals (one per house). A sample of 1294 was calculated to ensure a sample size that could estimate a prevalence of at least 14% of frailty among participants, with α = 5% and ß = 20%. The acceptance rate was 86.9%, with a total of 1124 participants being finally included in the study. Baseline data were collected between April 2008 and July 2009 through a questionnaire and a clinical evaluation. Data collection was
Frailty was defined according to the construct validated by Fried et al.; however, the metrics were slightly different, but have been previously validated.9 Weight loss was defined as self-reported unintentional weight loss of 5 kg or more in the previous year. Exhaustion was identified by two questions from the Center for Epidemiological Studies-Depression scale:16 “I felt that everything I did was an effort” and “I could not get going”, participants whose answer was “a moderate amount of the time” or “most of the time” to either of these questions were categorized as frail for this component. Slowness was defined by a positive answer to the next two questions “Does your present state of health limit you to climb a single flight of stairs?” and “Does your present state of health limit you to walk a 100 m block?” Low physical activity was established as the lowest quintile adjusted for sex on the Spanish version of the Physical Activity Scale for the Elderly.17 Weakness was identified when participants answered yes to the following question: “Does your present health status limit you to carry a groceries bag?” As recommended, participants were considered frail if they fulfilled three or more criteria, prefrail if they fulfilled one or two, and non-frail if none.
© 2015 Japan Geriatrics Society
EB EB were established according to eight components: bonus (incentives for attendance, punctuality, efficiency), profit sharing (incentive to employees depending on company’s profitability in addition to regular | 607
JA Avila-Funes et al.
salary), pension (fixed sum paid regularly to a person following retirement), health insurance, food stamps (allows the holder to obtain food and other goods), housing credit, life insurance and Christmas bonus (additional benefit paid by the second week of December). The presence of each item was summed up in a score ranging from 0 to 8, where a higher score indicates more EB.
Covariates Sociodemographic variables included age (years), sex and educational level. Participants were asked whether they had a diagnosis of coronary heart disease, cancer, stroke, hypertension, diabetes, thyroid disorders, arthritis or pain. Self-reported economic status was recorded (good, fair or poor). Current smoking and alcohol intake were also investigated (yes or no). Cognitive function was evaluated through the MiniMental State Examination, the score ranges from 0 to 30, where lower scores indicate poorer cognitive performance.18 Disability for activities of daily living (ADL) was evaluated according to the Katz Index.19 Participants were asked about their ability to carry out the following activities: bathing, dressing, toileting, transferring, continence and feeding themselves. Those participants indicating that they were unable to carry out at least one of the activities without help were considered as having ADL disability.
Sample For the present study, 927 participants aged 70 years and older were considered. However, participants whose phenotype of frailty or employee benefits could not be determined were excluded from the analyses (n = 197). In comparison with excluded participants, those who were included in the statistical analyses were no different regarding age, sex, cognitive function, depressive symptoms or disability for ADL.
Statistical analysis Variables were described using frequencies and proportions or arithmetic means and standard deviations (±SD) where appropriate. In some cases, medians and ranges were also stated. The χ2-test or analysis of variance (ANOVA) test were used according to the analyzed variables. In the case of an abnormal distribution, equivalent non-parametric tests were carried out. To assess the unadjusted effect of the association between EB and frailty, multinomial logistic regression analyses were run. In a second step, multivariate multinomial regression models were built in order to adjust for potential confounder covariates, such as age, sex, edu608 |
cation level, the sum of eight comorbidities (myocardial infarction, stroke, hypertension, cancer, diabetes, thyroid disease, arthritis and pain), cognitive function, disability for ADL and self-perceived economic status. Interaction terms EB*sex and EB*education level were also tested, and were not statistically significant. All statistical tests were carried out at the 0.05 level of confidence and 95% confidence intervals (CI) were given. SPSS software for Windows (version 20.0; SPSS, Chicago, IL, USA) was used to carry out all statistical analyses.
Results Table 1 shows the sociodemographic and clinical characteristics of the study population. The median age was 76.5 years (range 70.3–104.4 years), 54.9% were women and 52.6% lived alone. The most common chronic disease was hypertension (55.9%). Disability for ADL was present in 29.1% of participants. Frailty was present in 14.1% of participants, whereas 37.4% and 48.5% were considered prefrail and non-frail, respectively. A total of 8.7% rated their financial situation as poor and 33.1% reported worsening of financial situation over the past year. Regarding EB, participants that reported receiving a bonus were 12.3%, profit sharing 23.6%, pension 44.9%, health insurance 50.6%, food stamps 15.7%, housing credit 11.6%, life insurance 13.2% and Christmas bonus 54.8%. The mean score of global benefits was 2.3 ± 2.2. In comparison with non-frail participants, frail individuals were older (P < 0.001), mostly female (P < 0.001), more likely to live alone (P < 0.001) and to have a lower Mini-Mental State Examination score (P < 0.001). In addition, frail individuals had more disability for ADL (P < 0.001), more chronic diseases and were more likely to have been hospitalized during the previous year (P < 0.001 for both). Frail participants were also more likely to rent their house (P = 0.036), rated more frequently their financial situation as poor (P = 0.004) and reported worsening of financial situation over the past year (P = 0.001; Table 1). There were fewer frail participants among those who received bonuses (P = 0.033), profit sharing (P = 0.017), health insurance (P = 0.002), food stamps (P = 0.001), housing credit (P = 0.028), life insurance (P = 0.014) and Christmas bonus (P = 0.001). Multinomial logistic regression analyses of frailty status according EB are shown in Table 2. The unadjusted model showed a negative and statistically significant association between EB on prefrail and frail status. However, after adjusting for the aforementioned covariates, EB were no longer associated with prefrail status, but remained statistically associated with the frail subgroup (OR 0.85; 95% CI 0.74–0.98; P = 0.027). For © 2015 Japan Geriatrics Society
Employee benefits and frailty
Table 1 Sociodemographic and clinical characteristics according frailty status
Median age, years (range) Women (%) Years of education (mean ± SD) Living alone (%) Poor financial situation (%) Hypertension (%) Diabetes (%) Cancer (%) Stroke (%) Chronic diseases† (mean ± SD) MMSE
