EJINME-02882; No of Pages 6 European Journal of Internal Medicine xxx (2015) xxx–xxx

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European Journal of Internal Medicine journal homepage: www.elsevier.com/locate/ejim

Original article

Chronic conditions, disability, and quality of life in older adults with multimorbidity in Spain Maria João Forjaz a,⁎, Carmen Rodriguez-Blazquez b, Alba Ayala a, Vicente Rodriguez-Rodriguez c, Jesús de Pedro-Cuesta b, Susana Garcia-Gutierrez d, Alexandra Prados-Torres e a

National School of Public Health, Carlos III Institute of Health, Red de Investigación en Servicios de Salud en Enfermedades Crónicas (REDISSEC), Madrid, Spain National Centre of Epidemiology, Carlos III Institute of Health and CIBERNED, Madrid, Spain Institute of Economics, Geography and Demography, Spanish National Research Council, Madrid, Spain d Research Unit, Hospital Galdakao-Usansolo [Osakidetza] – Red de Investigación en Servicios de Salud en Enfermedades Crónicas (REDISSEC), Galdakao, Bizkaia, Spain e IIS Aragon, Aragon Health Sciences Institute–Miguel Servet University Hospital, Red de Investigación en Servicios de Salud en Enfermedades Crónicas (REDISSEC), Zaragoza, Spain b c

a r t i c l e Available online xxxx Keywords: Aged Morbidity Disability evaluation Quality of life Cohort studies

i n f o

a b s t r a c t Background: As the population ages, the prevalence of multimorbidity also increases, with consequences to several health outcomes such as disability and quality of life (QoL). This study aimed at analyzing the relationships between chronic conditions, disability, and QoL of older adults with multimorbidity in Spain. Method: Data on older adults aged 65 years or more, with at least two chronic health conditions were drawn from three cohort studies. Sample size was 705, 443, and 4995, respectively. For each cohort, the impact of the following chronic health conditions was analyzed: asthma, cancer, cardiac, diabetes, hypertension, mental health disorders, osteoarticular conditions, and stroke. Disability and QoL measures varied according to the survey. Results: In older adults with multimorbidity, the most prevalent conditions were osteoarticular (59.08–67.80%) and hypertension (50.64–60.03%). The presence of disability was significantly associated to having osteoarticular (OR range: 1.53 to 2.646), diabetes (OR: 1.86 to 1.71), or mental health disorders (OR: 2.19 to 3.36) in most cohorts. Disability (OR: 1.67 to 7.67), osteoarticular conditions (OR: 3.37 to 5.10), and mental health disorders (OR: 1.83 to 4.27) showed the highest effects on lower QoL than the population. Conclusion: The presence of disability and diverse chronic conditions has a negative effect on QoL of older adults affected by multimorbidity in Spain. Public health and primary care interventions focusing on the integrated care of older adults with multimorbidity might give special attention to mental health and osteoarticular conditions. © 2015 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.

1. Introduction European population is rapidly aging due to the rise in life expectancy and the decline in birth rates. Studies evidence that multimorbidity, the co-existence of several of these diseases in the same individual [1] is increasing, being present in up to 70% of people aged 65 or more. It represents a challenge for the health system, not only due to the cumulative effect of concurrent diseases but also due to the physical, cognitive, and psychosocial consequences [2]. Multimorbidity is strongly and consistently associated to adverse health outcomes, such as disability and dependence, mortality, increased use of health and social services and polypharmacy, and diminished quality of life (QoL) [2–4]. Most studies have found a relationship between the presence of chronic diseases and impaired QoL in older people [3,5], although this was not specifically studied in the population ⁎ Corresponding author at: Instituto de Salud Carlos III, Escuela Nacional de Sanidad, Monforte de Lemos 5, Madrid 28029, Spain. Tel.: +34 91 822 2062. E-mail address: [email protected] (M.J. Forjaz).

with multimorbidity. The effect of the increasing number of chronic conditions and patterns of diseases on QoL has been also shown [5,6]. However, less is known about the variables that mediate this relationship. Socio-demographic, emotional, and economic aspects, such as age, sex, depression, social support, and socio-economic status, as well as some characteristics of the care process, have been suggested as intermediate factors between chronic conditions and QoL [7–9]. The International Classification of Functioning, Disability and Health (ICF) [10] model can provide the framework for the connection between multimorbidity and QoL. In the ICF system, disability is conceptualized as a deficit in any of three domains (body functions and structure, activity, and participation) and the negative result of the “dynamic interaction between a person's health condition, environmental factors and personal factors” [11]. Any health condition that results in deficits in body function, activity limitation, or participation restriction can have a negative influence on QoL [12]. Multimorbidity has been directly related to disability [2,5], some studies showing not only additive effects of combination of diseases on disability but also multiplicative ones [13–15].

http://dx.doi.org/10.1016/j.ejim.2015.02.016 0953-6205/© 2015 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.

Please cite this article as: Forjaz MJ, et al, Chronic conditions, disability, and quality of life in older adults with multimorbidity in Spain, Eur J Intern Med (2015), http://dx.doi.org/10.1016/j.ejim.2015.02.016

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M.J. Forjaz et al. / European Journal of Internal Medicine xxx (2015) xxx–xxx

The purpose of this study is to determine the impact of chronic conditions within multimorbidity on disability and QoL. Specifically, this study aimed at (1) describing the prevalence of individual chronic conditions in older people with multimorbidity in Spain, (2) ascertaining the impact of the chronic conditions on functional status and QoL, and (3) analyzing how disability influences the relationship between chronic conditions and QoL. To increase external validity, the same research question was analyzed in three different population-based cohorts that measured similar variables. It allows seeing if, despite methodological differences between the cohorts, results are consistent, and drawing trustworthy conclusions. Therefore, this study contributes to the previous literature on QoL, disability, and chronic conditions by adding three novel aspects: it provides information about how disability acts in the relationship between QoL and chronic conditions, it specifically focuses on older adults with multimorbidity, and it answers the same research question simultaneously in several cohorts.

2. Methods 2.1. Study design and participants This study used observational, retrospective cross-sectional design with three independent cohorts (Table 1). The analyzed samples were restricted to participants that met the following inclusion criteria: aged 65 years or older and positive for multimorbidity status, defined as having two or more chronic health conditions [16]. The first cohort was drawn from the survey “Quality of life in older adults–Spain” (Spanish acronym: CadeVima), which collected information in 2008 about 1,106 community-dwelling older adults in a representative sample [17]. Of these, 705 older adults met inclusion criteria. The second cohort used data from Ageing in Spain Longitudinal Study, Pilot Survey [18] (ELES). In 2011, the ELES sampled 1,747 community-dwelling older adults, using complex sample design to ensure representativeness. We selected 443 older adults who met inclusion criteria. Finally, the third cohort was the National Health Survey in Spain (ENSE), administered to community-dwelling people during the period of 2011–2012. The ENSE used a complex sample design and 4,995 subjects met inclusion criteria.

All cohort studies were approved by their respective institutions' ethics committees, participants gave informed consent, and anonymity was preserved.

2.2. Instruments 2.2.1. Chronic health conditions checklists All studies used checklists for chronic health conditions. The one used in the CadeVima was adapted from the Cumulative Illness Rating Scale (CIRS-G) and inquired about 20 chronic medical problems [19]. The ELES survey contained a 21-item questionnaire specifically designed for that study. Finally, the ENSE contained a list of 30 chronic medical conditions. For this study, we selected the chronic health problems that were common to all data bases (Table 1).

2.2.2. Quality of life measures The analyzed studies applied two QoL questionnaires. The EQ-5D index is a generic measure of health-related QoL [20–22]. It is formed by 5 dimensions: mobility, self-care, usual activities, pain/discomfort, and anxiety/depression. The EQ-5D index is calculated based on the profile of the dimensions scores, and it ranges from worse to better health state (−1 to 1). Negative values indicate a health status valued as worse than death. The EQ-5D was used in the CadeVima cohort in its 3-level (EQ-5D-3L) version, and in its new 5-levels (EQ-5D-5L) version in the ENSE cohort. The Personal Wellbeing Index (PWI) is a general measure of QoL with seven questions about standard of living, health, achievements in life, personal relationships, safety, feeling part of the community, and future security [23,24]. The total score ranges from 0 to 100, with higher scores indicating a better QoL. This instrument was used in the CadeVima and ELES studies. Each sample was divided into two groups, with lower or higher QoL than population values [25]. In the CadeVima data base, the EQ-5D-3L index was divided according to the 64 to 75 years population mean (0.891). Due to the lack of population data, the PWI was grouped by the median of each sample: 71.4 years for CadeVima and 75.7 years for ELES. Since the ENSE is a population survey based on a very large, representative sample, the median of the EQ5D-5L (0.849) was used.

Table 1 Sample size, measures, and chronic health conditions by study. CadeViMa

ELES

Study focus

Quality of life

Aging

General population national health survey

Initial sample size Sample size for the analyses a Quality of live measure Disability measure

1,106 705 EQ-5D-3L/PWI [20,22,23] Barthel Index [26]

1,747 443 PWI [23] Specific disability measure (24 items)

21,007 4,995 EQ-5D-5L [21] Specific disability measure (27 items)

Respiratory problems (asthma, bronchitis) Tumors, cancer Heart problems (circulatory)

Asthma

Chronic allergy (allergic asthma excluded), asthma Malignant tumors Other heart problems

Chronic health conditions Asthma Cancer Cardiac Diabetes Hypertension Mental health disorders

Osteoarticular Stroke

Diabetes Hypertension (high tension) Alzheimer; other mental disorders, senile dementia; Parkinson; depression, sadness, anxiety Bone problems (osteoarthritis, arthritis, rheumatism) Cerebral infarction

Malignant tumors/cancer Cardiac insufficiency; circulatory problems (varices excluded)/intermittent claudication Diabetes High tension Diseases related with memory; depression, anxiety; Parkinson

ENSE

Diabetes High tension Chronic depression; chronic anxiety

Osteoarthritis/arthritis

Osteoarthritis, arthritis, or rheumatism

Cerebral infarction/embolism

Cerebral infarction/embolism/hemorrhage

Note: Chronic health conditions presented by alphabetical order. a Age 65+ years, with multimorbidity.

Please cite this article as: Forjaz MJ, et al, Chronic conditions, disability, and quality of life in older adults with multimorbidity in Spain, Eur J Intern Med (2015), http://dx.doi.org/10.1016/j.ejim.2015.02.016

M.J. Forjaz et al. / European Journal of Internal Medicine xxx (2015) xxx–xxx

2.2.3. Disability measures The Barthel Index is a functional measure of independence that inquires about need of help to perform activities of daily living. Its total score ranges from 0 (completely dependent) to 100 (completely independent) [26]. The Barthel Index was used in the CadeVima survey and people with a score lower than 100 were considered as presenting a disability. The ELES and ENSE studies included specific disability measures, based on the difficulty to perform listed activities. The ELES disability measure asks to rate 24 activities from 1 (always) to 4 (never has difficulty). Scores b96 indicated the presence of a disability. The ENSE provided a questionnaire of 27 activities that asked if the person can perform each activity with no help, with some help, or if he or she cannot perform the activity at all (from 1 to 3, respectively). Scores higher than 27 reflect the presence of a disability. 2.3. Data analysis For older adults with multimorbidity, aged 65 years or more, gender, age, number of chronic health conditions, and disability status each of data base were described. In addition, we also calculated the prevalence of the eight chronic health conditions common to the surveys, for people with multimorbidity: asthma, cancer, cardiac, diabetes, hypertension, mental health disorders, osteoarticular, and stroke. The three main multimorbidity patterns or clusters described in the literature [27] were represented: mental health disorders, musculoskeletal (by osteoarticular conditions), and cardiovascular and metabolic diseases (by cardiac, diabetes, hypertension and stroke). To determine the impact of each chronic condition in disability status, a logistic regression model was computed for each data base. The dependent variable was disability status, as previously defined. The explaining variables for these models were the eight chronic health conditions. All regression models controlled for age and gender. Although the number of chronic health conditions was initially controlled for, it had to be removed due to multicollinearity problems. A second set of logistic regression models was performed for QoL, divided in two categories as previously detailed: lower and higher QoL than the population. The independent variables were the eight chronic health conditions, disability status, and, in case of significant main effects, the interaction between disability and each chronic health condition. We also analyzed the interaction between diabetes, cardiac, and hypertension. Non-significant interactions were removed from the models. Statistical analyses were performed in SPSS 20. 3. Results Sociodemographic characteristics of older adults with multimorbidity are presented in Table 2. Mean age ranged from 74.22 (standard error, SE: 6.44) years for the ELES sample to 75.77 (SE: 7.41) years for the ENSE sample. In all cohorts, there was a lower percentage of men than women, ranging between 39.57% in the CadeVima and 40.39% in the ENSE sample. The proportion of people with disability ranged from 10.00% (ELES) to 51.25% (ENSE sample). The mean number of health conditions was 4.08 (SE: 2.00, ELES sample) to 5.70 (SE: 3.11, ENSE sample). The prevalence of each chronic health condition also varied by cohort (Table 2). The most frequent was osteoarticular (59.08– 67.80%) followed by hypertension (50.64–60.03%), and the least prevalent were stroke (0.20–4.46%) and cancer (3.55–13.92%). Diabetes showed a very consistent prevalence across samples (20.2– 24.0%). When analyzing the contribution of chronic health conditions to disability status of older adults with multimorbidity (Table 3), osteoarticular conditions showed a significant effect on disability in all cohorts (OR range: 1.53 to 2.64). Diabetes (OR: 1.86 to 1.71). Mental health disorders (OR: 2.19 to 3.36), and cardiac conditions

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Table 2 Descriptive statistics by sample.

Age Number of health conditions Sex (men) Disability Lower QoL

EQ-5D PWI

Chronic health conditions Asthma Cancer Cardiac Diabetes Hypertension Mental health disorders Osteoarticular Stroke

CadeVima (n = 705)

ELES (n = 443)

ENSE (n = 4,995)

M

SD

M

SE

M

SE

75.2 4.2 n 279 181 474 368

6.6 2.2 % 40 26 67 53

74.2 4.1 n 178 315

6.4 2.0 % 40 10

75.8 5.7 n 1,756 2,571 2,760

7.4 3.1 % 40 51 55

191

53

109 25 246 169 357 168 478 2

15.5 3.6 34.9 24.0 50.6 23.8 67.8 0.2

32 60 170 86 258 141 262 26

6.9 13.9 39.6 20.2 60.0 33.0 59.1 4.5

114 426 1,066 1,139 2,988 1,294 3,221 220

2.3 8.5 21.4 22.9 60.0 26.0 64.8 4.1

SD: standard deviation; SE: standard error (used for complex samples); CadeVima: Quality of Life in Older Adults Study; ELES: Longitudinal Study Ageing in Spain; ENSE: Spanish National Health Survey; QoL: quality of life.

(OR: 1.62 to 1.70) were associated with a higher probability of disability in CadeVima and ENSE cohorts. Hypertension was a significant disability factor in ELES and ENSE (OR: 1.63 and 1.25). Stroke only was significant in ENSE cohort (OR: 4.09). Asthma and cancer were not significantly associated to disability status in any sample. In sum, osteoarticular, diabetes, mental health disorders, and cardiac conditions had moderate effects on disability. Table 4 presents the results obtained from logistic regression models for lower QoL than the population, by sample. The presence of disability was associated with lower QoL (OR range: 1.68 to 7.67). Likewise, mental health disorders were statistically significant in all cohorts (OR: 1.83 to 4.27). Osteoarticular conditions (OR: 3.37 to 5.10) and asthma (OR: 2.36 tot 2.42) were significant in CadeVima and ENSE. Cardiac and diabetes were only significantly associated to a lower QoL in the ENSE sample (OR: 1.58 and 1.62, respectively). Hypertension and cancer were not statistically significant in any model. There were no significant interactions. In general, disability was the strongest risk factor of lower QoL, and independently, mental health and osteoarticular conditions were significant, consistent and strong risk factors of lower QoL than the population.

Table 3 Logistic regression models (odds ratio and 95% confidence interval) of presence of disability as dependent variable, by sample.

Age Sex (men) Asthma Cancer Cardiac Diabetes Hypertension Mental health disorders Osteoarticular Stroke R2 Nagelkerke

CadeVima (n = 705)

ELES (n = 443)

ENSE (n = 4,995)

0.75 (0.51, 1.12) 1.15 (0.70, 1.89) 1.43 (0.53, 3.85) 1.62 (1.11, 2.37)a 1.86 (1.23, 2.81)a 0.84 (0.58, 1.22) 2.19 (1.45, 3.32)a 1.53 (1.00, 2.37)a – 0.125

2.64 (1.35, 5.14)a 1.9 (0.59, 6.12) 1.63 (0.83, 3.2) 1.15 (0.68, 1.93) 0.68 (0.42, 1.11) 1.63 (1.04, 2.54)a 1.59 (0.89, 2.84) 2.64 (1.43, 4.86)a 1.59 (0.66, 3.84) 0.251

1.24 (1.05, 1.48)a 1.57 (0.96, 2.56) 1.27 (0.94, 1.73) 1.7 (1.39, 2.07)a 1.71 (1.40, 2.08)a 1.25 (1.07, 1.47)a 3.36 (2.77, 4.07)a 2.38 (1.99, 2.84)a 4.09 (2.6, 6.45)a 0.350

a Significant associations. PWI: Personal Wellbeing Index; CadeVima: Quality of Life in Older Adults Study; ELES: Longitudinal Study Ageing in Spain; ENSE: National Health Survey. Models controlled by sex and age.

Please cite this article as: Forjaz MJ, et al, Chronic conditions, disability, and quality of life in older adults with multimorbidity in Spain, Eur J Intern Med (2015), http://dx.doi.org/10.1016/j.ejim.2015.02.016

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Table 4 Logistic regression models (odds ratio and 95% confidence interval) by sample of lower quality of life as dependent variable. CadeVima (n = 705)

Age Sex (men) Disability Asthma Cancer Cardiac Diabetes Hypertension Mental health disorders Osteoarticular Stroke R2 Nagelkerke a

ELES (n = 443)

ENSE (n = 4,995)

EQ-5D-3L

PWI

PWI

EQ-5D-5L

1.07 (1.04, 1.11)a 1.45 (0.98, 2.13)a 2.47 (1.47, 4.14)a 2.36 (1.31, 4.23)a 1.49 (0.48, 4.63) 1.29 (0.85, 1.94) 1.4 (0.88, 2.24) 1.15 (0.78, 1.68) 4.27 (2.37, 7.68)a 5.1 (3.42, 7.58)a – 0.235

1.02 (0.99, 1.04) 1.34 (0.96, 1.87) 1.68 (1.14, 2.48)a 1.16 (0.74, 1.81) 1.38 (0.57, 3.37) 0.96 (0.68, 1.34) 1.1 (0.75, 1.61) 0.96 (0.7, 1.31) 3.07 (2.03, 4.65)a 1.06 (0.75, 1.51) – 0.066

0.97 (0.94, 1) 1.02 (0.57, 1.82) 1.51 (0.91, 2.51) 1.04 (0.47, 2.34) 1.05 (0.56, 1.99) 1.22 (0.79, 1.89) 1.28 (0.69, 2.38) 0.66 (0.39, 1.12) 1.83 (1.09, 3.06)a 1.59 (0.94, 2.7) 0.6 (0.22, 1.66) 0.113

1.03 (1.01, 1.04)a 1.55 (1.28, 1.88)a 7.67 (6.36, 9.25)a 2.42 (1.14, 5.15)a 1.1 (0.79, 1.52) 1.58 (1.26, 1.99)a 1.62 (1.3, 2.03)a 0.99 (0.83, 1.19) 3.71 (2.94, 4.68)a 3.37 (2.81, 4.06)a 3.77 (2.4, 5.9)a 0.497

Significant associations. PWI: Personal Wellbeing Index; CadeVima: Quality of Life in Older Adults Study; ELES: Longitudinal Study Ageing in Spain; ENSE: National health survey.

4. Discussion Multimorbidity is present in the majority of older adults and might deserve focused approaches. This study aimed at examining the effect of different chronic conditions on disability and QoL, as well as the potential effect of disability as an intermediate variable between single chronic conditions and QoL in three cohorts of older people with multimorbidity. Despite some limitations due to the heterogeneity of samples and measures, our results suggest that QoL is mainly affected by disability status and mental health and osteoarticular disorders. According to the Aging Task Force on Comorbidity, certain chronic health conditions are specially relevant in older adults: arthritis (included in our study in osteoarticular conditions), hypertension, cancer, diabetes, cardiovascular problems (cardiac in our study), Alzheimer's disease (included in mental health disorders), and stroke [1]. Although respiratory conditions are notably encountered in older adults, we only had information about one of them, asthma. The individual chronic health conditions had similar or higher prevalences than the ones reported in the literature for older adults [4, 28–30]. Differences might be due to the sample characteristics: while our analysis provides data only for older adults with multimorbidity, other studies reported prevalence in the general population. This is especially important taking into consideration that there are several chronic health conditions that tend to appear in clusters in the general population [27], but particularly in older adults [15,28]. Since diabetes, cardiac, and hypertension conditions have been commonly described in the literature as forming a cluster [15,27], we analyzed the interaction between them, but it was non-significant. Across all analyzed cohorts, hypertension and osteoarticular conditions were the most prevalent conditions and also similar results were found in another study [29]. Although hypertension does not seem to impact QoL, osteoarticular conditions have an important effect both in QoL and disability. In addition, hypertension is a known risk factor for other health problems and mortality at the long run [31]. Thus, these conditions should be a special target for interventions at different levels, including public health policies or programs developed by primary care facilities. On the other hand, asthma, cancer, and stroke showed the lowest prevalences, in line with other studies [29,30]. Previous studies have found a direct relationship between the presence of individual diseases, such as arthritis and arthrosis, stroke and diabetes, and lower functional status [32–34]. In the present study, mental health disorders such as dementia or depression powerfully determine disability, followed by osteoarticular conditions, as seen in other studies [2,5,35,36]. In a systematic review of the literature, poor QoL was identified as a major consequence of multimorbidity in older adults [2]. In our study, older adults with a mental health comorbid condition had a risk of presenting low QoL twice and a half higher than older adults

without mental health disorders. This effect had been consistently described previously [5] and can be explained by the deterioration that mental conditions produces in several QoL dimensions. The effect of osteoarticular disorders was significant for the EQ-5D abut not for the PWI. The PWI is a general QoL measure, focused on wellbeing and life satisfaction aspects [23], whereas the EQ-5D measures health-related QoL and health status [20–22]. Thus, osteoarticular conditions seem to affect only the health dimensions of QoL, particularly its physical aspects. Although the effect of musculoskeletal disorders on QoL was variable in previous studies [5], we found that older adults with osteoarticular comorbid disorders presented a risk of impaired QoL twice higher than their counterparts. This is coherent with the large and consistent effect of disability on QoL observed across the cohorts. Addressing the negative impact of mental health and osteoarticular disorders on disability and QoL is particularly relevant in this population, as it is shown that conditions such as depression, dementia, or arthritis are strongly associated with an increased risk of institutionalization [37] and health care utilization [4]. Previous studies indicated the effect of cancer, cardiac diseases, diabetes, asthma, and stroke on QoL is variable [5,29]. Likewise, we found that these conditions were not always associated to QoL. Although diabetes, respiratory diseases, and stroke were associated with low QoL in other studies [5,29,35], we found a relationship of diabetes and stroke with QoL in the largest sample and the association of asthma and QoL in two of the cohorts. Noteworthy is the absence of relationship between cancer and QoL in our study, although previous studies have found good QoL among long-term adult cancer survivors, with older age acting as a protective factor in some types of cancer [38]. Longitudinal studies are needed to clarify the impact of these conditions. Some limitations must be acknowledged, as results come from surveys and cohorts with significant differences in several characteristics, which may difficult the interpretation and conclusions. However, differences in age and sex were controlled for in the statistical analyses and the prevalence of chronic diseases was similar to that reported in other studies [2]. Also, due to the diversity of sources of data, ad hoc criteria for the definition of lower QoL and disability had to be adopted and the number of chronic conditions was not included in the data analysis, as it is influenced by collinearity and the type and length of the applied checklists. Nevertheless, all the selected participants fulfilled the criteria for multimorbidity (having two or more chronic diseases) [16]. The absence of assessment of disease severity and of other chronic conditions that may have effect on disability or QoL must be also taken into account among the limitations [3] and reflect the heterogeneity of data collection about chronic conditions. Although chronic health conditions were assessed only by self-report and did not include a health professional review, self-assessment has been shown to be a valid and cost-efficient method [39]. Furthermore, the cross-sectional design of

Please cite this article as: Forjaz MJ, et al, Chronic conditions, disability, and quality of life in older adults with multimorbidity in Spain, Eur J Intern Med (2015), http://dx.doi.org/10.1016/j.ejim.2015.02.016

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the studies impedes drawing conclusions on causality. Finally, future works should take into consideration complex patterns of multimorbidity and differential impact of chronic conditions by QoL dimensions [40]. This study has two major strengths: instead of analyzing the general population as done by most previous studies, it offers specific data on older adults with multimorbidity, and it analyses the same research question three independent cohorts. In summary, chronic conditions have a negative effect on QoL of older people with multimorbidity, with mental health and osteoarticular conditions, and particularly disability as main independent risk factors. In this study, adjustment for disability did not substantially modified the effect of chronic disorders on QoL, suggesting it acted as an independent factor, in the sense Gijsen et al. [5] proposed. The results of this study may have several implications. The increasing prevalence of multimorbidity in older age means a challenge for health care and research [41]. For this population, the focus of health system should be in providing comprehensive care, involving medical specialists, mental health professionals, nurses, and social workers. The identification of high-risk patients, or those with chronic diseases more likely associated with increased disability and lower QoL, as this study has highlighted, should be at the basis of comprehensive care management programs [42]. Finally, the link between chronic diseases, disability, and QoL deserves further longitudinal studies to clarify the possible causal associations. Conflict of interests The authors state that they have no conflicts of interest. Acknowledgments This work arises from the Joint Action on Chronic Diseases and Promoting Healthy Ageing across the Life Cycle (JA-CHRODIS), which has received funding from the European Union, in the framework of the Health Programme (2008–2013). Sole responsibility lies with the author and the Consumers, Health, Agriculture and Food Executive Agency is not responsible for any use that may be made of the information contained therein. The Quality of Life in Older Adults Study (CadeVima) was supported by the Spanish Ministry of Science and Innovation (National Plan: SEJ2006-15122-C02-00). The Ageing in Spain Longitudinal Study, Pilot Survey (ELES) was supported by the Spanish Ministry of Science and Innovation, National Plan of Research and Development (ref. CSO2011-30210-C02-01). References [1] Yancik R, Ershler W, Satariano W, Hazzard W, Cohen HJ, Ferrucci L. Report of the national institute on aging task force on comorbidity. J Gerontol 2007;62:275–80. [2] Marengoni A, Angleman S, Melis R, Mangialasche F, Karp A, Garmen A, et al. Aging with multimorbidity: a systematic review of the literature. Ageing Res Rev 2011; 10:430–9. http://dx.doi.org/10.1016/j.arr.2011.03.003. [3] Fortin M, Lapointe L, Hudon C, Vanasse A, Ntetu AL, Maltais D. Multimorbidity and quality of life in primary care: a systematic review. Health Qual Life Outcomes 2004;2:51. http://dx.doi.org/10.1186/1477-7525-2-51. [4] Vogeli C, Shields AE, Lee TA, Gibson TB, Marder WD, Weiss KB, et al. Multiple chronic conditions: prevalence, health consequences, and implications for quality, care management, and costs. J Gen Intern Med 2007;22(Suppl. 3):391–5. http://dx.doi.org/10. 1007/s11606-007-0322-1. [5] Gijsen R, Hoeymans N, Schellevis FG, Ruwaard D, Satariano WA, van den Bos GA. Causes and consequences of comorbidity: a review. J Clin Epidemiol 2001;54:661–74. [6] Lawson KD, Mercer SW, Wyke S, Grieve E, Guthrie B, Watt GC, et al. Double trouble: the impact of multimorbidity and deprivation on preference-weighted health related quality of life a cross sectional analysis of the Scottish Health Survey. Int J Equity Health 2013;12:67. [7] Sullivan MD, Kempen GI, Van Sonderen E, Ormel J. Models of health-related quality of life in a population of community-dwelling Dutch elderly. Qual Life Res 2000;9:801–10. [8] Zulman DM, Asch SM, Martins SB, Kerr EA, Hoffman BB, Goldstein MK. Quality of care for patients with multiple chronic conditions: the role of comorbidity interrelatedness. J Gen Intern Med 2014;29:529–37. http://dx.doi.org/10.1007/s11606013-2616-9.

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Chronic conditions, disability, and quality of life in older adults with multimorbidity in Spain.

As the population ages, the prevalence of multimorbidity also increases, with consequences to several health outcomes such as disability and quality o...
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