Validation of the Health Assessment Tool (HAT) based on four aging cohorts from the Swedish National study on Aging and Care.

BACKGROUND: As global aging accelerates, routinely assessing the functional status and morbidity burden of older patients becomes paramount. The aim of this study is to assess the validity of the comprehensive clinical and functional Health Assessment Tool (HAT) based on four cohorts of older adults (60 + years) from the Swedish National study on Aging and Care (SNAC) spanning urban, suburban, and rural areas. METHODS: The HAT integrates five health indicators (gait speed, global cognition, number of chronic diseases, and basic and instrumental activities of daily living), providing an individual-level score between 0 and 10. The tool was constructed using nominal response models, first separately for each cohort and then in a harmonized dataset. Outcomes included all-cause mortality over a maximum follow-up of 16 years and unplanned hospital admissions over a maximum of 3 years of follow-up. The predictive capacity was assessed through the area under the curve (AUC) using logistic regressions. For time to death, Cox regressions were performed, and Harrell's C-indices were reported. Results from the four cohorts were pooled using individual participant data meta-analysis and compared with those from the harmonized dataset. RESULTS: The HAT demonstrated high predictive capacity across all cohorts as well as in the harmonized dataset. In the harmonized dataset, the AUC was 0.84 (95% CI 0.81-0.87) for 1-year mortality, 0.81 (95% CI 0.80-0.83) for 3-year mortality, 0.80 (95% CI 0.79-0.82) for 5-year mortality, 0.69 (95% CI 0.67-0.70) for 1-year unplanned admissions, and 0.69 (95% CI 0.68-0.70) for 3-year unplanned admissions. The Harrell's C for time-to-death throughout 16 years of follow-up was 0.75 (95% CI 0.74-0.75). CONCLUSIONS: The HAT is a highly predictive, clinically intuitive, and externally valid instrument with potential for better addressing older adults' health needs and optimizing risk stratification at the population level.

Implementation of a virtual community of practice to promote the empowerment of middle-aged people with multimorbidity: study protocol of a randomised controlled trial.

INTRODUCTION: Empowering people living with multimorbidity (multiple chronic conditions) to gain greater confidence in managing their health can enhance their quality of life. Education focused on self-management is a key tool for fostering patient empowerment and is mostly provided on an individual basis. Virtual communities of practice (VCoP) present a unique opportunity for online education in chronic condition self-management within a social context. This research aims to evaluate the effectiveness/cost-effectiveness of individualised, online self-management education compared with VCoP among middle-aged individuals living with multiple chronic conditions. METHODS AND ANALYSIS: People aged 30-60, living with ≥2 chronic conditions and receiving care in primary care (PC) centres and outpatient hospital-based clinics in Madrid and Canary Islands will enrol in an 18-month parallel-design, blinded (intervention assessment and data analysts), pragmatic (adhering to the intention-to-treat principle), individually randomised trial. The trial will compare two 12-month web-based educational offers of identical content; one delivered individually (control) and the other with online social interaction (VCoP, intervention). Using repeated measures mixed linear models, with the patient as random effect and allocation groups and time per group as fixed effects, we will estimate between-arm differences in the change in Patient Activation Measure from baseline to 12 months (primary endpoint), including measurements at 6-month and 18-month follow-up. Other outcomes will include measures of depression and anxiety, treatment burden, quality of life. In addition to a process evaluation of the VCoP, we will conduct an economic evaluation estimating the relative cost-effectiveness of the VCoP from the perspectives of both the National Health System and the Community. ETHICS AND DISSEMINATION: The trial was approved by Clinical Research Ethics Committees of Gregorio Marañón University Hospital in Madrid/Nuestra Señora Candelaria University Hospital in Santa Cruz de Tenerife. The results will be disseminated through workshops, policy briefs, peer-reviewed publications and local/international conferences. TRIAL REGISTRATION NUMBER: NCT06046326.

Somatic disease burden and depression risk in late life: a community-based study.

AIMS: Co-occurring somatic diseases exhibit complex clinical profiles, which can differentially impact the development of late-life depression. Within a community-based cohort, we aimed to explore the association between somatic disease burden, both in terms of the number of diseases and their patterns, and the incidence of depression in older people. METHODS: We analysed longitudinal data of depression- and dementia-free individuals aged 60+ years from the population-based Swedish National Study on Aging and Care in Kungsholmen. Depression diagnoses were clinically ascertained following the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition Text Revision over a 15-year follow-up. Somatic disease burden was assessed at baseline through a comprehensive list of chronic diseases obtained by combining information from clinical examinations, medication reviews and national registers and operationalized as (i) disease count and (ii) patterns of co-occurring diseases from latent class analysis. The association of somatic disease burden with depression incidence was investigated using Cox models, accounting for sociodemographic, lifestyle and clinical factors. RESULTS: The analytical sample comprised 2904 people (mean age, 73.2 [standard deviation (SD), 10.5]; female, 63.1%). Over the follow-up (mean length, 9.6 years [SD, 4 years]), 225 depression cases were detected. Each additional disease was associated with the occurrence of any depression in a dose-response manner (hazard ratio [HR], 1.16; 95% confidence interval [CI]: 1.08, 1.24). As for disease patterns, individuals presenting with sensory/anaemia (HR, 1.91; 95% CI: 1.03, 3.53), thyroid/musculoskeletal (HR, 1.90; 95% CI: 1.06, 3.39) and cardiometabolic (HR, 2.77; 95% CI: 1.40, 5.46) patterns exhibited with higher depression hazards, compared to those without 2+ diseases (multimorbidity). In the subsample of multimorbid individuals (85%), only the cardiometabolic pattern remained associated with a higher depression hazard compared to the unspecific pattern (HR, 1.71; 95% CI: 1.02, 2.84). CONCLUSIONS: Both number and patterns of co-occurring somatic diseases are associated with an increased risk of late-life depression. Mental health should be closely monitored among older adults with high somatic burden, especially if affected by cardiometabolic multimorbidity.

Early growth, stress, and socioeconomic factors as predictors of the rate of multimorbidity accumulation across the life course: a longitudinal birth cohort study.

BACKGROUND: Early growth, stress, and socioeconomic factors are associated with future risk of individual chronic diseases. It is uncertain whether they also affect the rate of multimorbidity accumulation later in life. This study aimed to explore whether early life factors are associated with the rate at which chronic diseases are accumulated across older age. METHODS: In this national birth cohort study, we studied people born at Helsinki University Central Hospital, Helsinki, Finland between Jan 1, 1934, and Dec 31, 1944, who attended child welfare clinics in the city, and were living in Finland in 1971. Individuals who had died or emigrated from Finland before 1987 were excluded, alongside participants without any registry data and who died before the end of the registry follow-up on Dec 31, 2017. Early anthropometry, growth, wartime parental separation, and socioeconomic factors were recorded from birth, child welfare clinic, or school health-care records, and Finnish National Archives. International Classification of Diseases codes of diagnoses for chronic diseases were obtained from the Care Register for Health Care starting from 1987 (when participants were aged 42-53 years) until 2017. Linear mixed models were used to study the association between early-life factors and the rate of change in the number of chronic diseases over 10-year periods. FINDINGS: From Jan 1, 1934, to Dec 31, 2017, 11 689 people (6064 [51·9%] men and 5625 [48·1%] women) were included in the study. Individuals born to mothers younger than 25 years (ß 0·09; 95% CI 0·06-0·12), mothers with a BMI of 25-30 kg/m2 (0·08; 0·05-0·10), and mothers with a BMI more than 30 kg/m2 (0·26; 0·21-0·31) in late pregnancy accumulated chronic diseases faster than those born to older mothers (25-30 years) and those with a BMI of less than 25 kg/m2. Individuals with a birthweight less than 2·5 kg (0·17; 0·10-0·25) and those with a rapid growth in height and weight from birth until age 11 years accumulated chronic diseases faster during their life course. Additionally, paternal occupational class (manual workers vs upper-middle class 0·27; 0·23-0·30) and wartime parental separation (0·24; 0·19-0·29 for boys; 0·31; 0·25-0·36 for girls) were associated with a faster rate of chronic disease accumulation. INTERPRETATION: Our findings suggest that the foundation for accumulating chronic diseases is established early in life. Early interventions might be needed for vulnerable populations, including war evacuee children and children with lower socioeconomic status. FUNDING: Finska Läkaresällskapet, Liv och Hälsa rf, the Finnish Pediatric Research Foundation, and Folkhälsan Research Center. TRANSLATIONS: For the Finnish and Swedish translations of the abstract see Supplementary Materials section.

Socioeconomic differences in older adults' unplanned hospital admissions: the role of health status and social network.

BACKGROUND: the socioeconomic distribution of unplanned hospital admissions in older adults is poorly understood. We compared associations of two life-course measures of socioeconomic status (SES) with unplanned hospital admissions while comprehensively accounting for health, and examined the role of social network in this association. METHODS: in 2,862 community-dwelling adults aged 60+ in Sweden, we derived (i) an aggregate life-course SES measure grouping individuals into Low, Middle or High SES based on a summative score, and (ii) a latent class measure that additionally identified a Mixed SES group, characterised by financial difficulties in childhood and old age. The health assessment combined measures of morbidity and functioning. The social network measure included social connections and support components. Negative binomial models estimated the change in hospital admissions over 4 years in relation to SES. Stratification and statistical interaction assessed effect modification by social network. RESULTS: adjusting for health and social network, unplanned hospitalisation rates were higher for the latent Low SES and Mixed SES group (incidence rate ratio [IRR] = 1.38, 95% confidence interval [CI]: 1.12-1.69, P = 0.002; IRR = 2.06, 95% CI: 1.44-2.94, P < 0.001; respectively; ref: High SES). Mixed SES was at a substantially greater risk of unplanned hospital admissions among those with poor (and not rich) social network (IRR: 2.43, 95% CI: 1.44-4.07; ref: High SES), but the statistical interaction test was non-significant (P = 0.493). CONCLUSION: socioeconomic distributions of older adults' unplanned hospitalisations were largely driven by health, although considering SES dynamics across life can reveal at-risk sub-populations. Financially disadvantaged older adults might benefit from interventions aimed at improving their social network.

Multimorbidity, social determinants and intersectionality in chronic patients. Results from the EpiChron Cohort.

Background: Multimorbidity is influenced in an interconnected way, both in extent and nature, by the social determinants of health. We aimed at implementing an intersectional approach to analyse the association of multimorbidity with five important axes of social inequality (i.e. gender, age, ethnicity, residence area and socioeconomic class). Methods: We conducted a cross-sectional observational study of all individuals who presented with at least one chronic disease in 2019 (n = 1 086 948) from the EpiChron Cohort (Aragon, Spain). Applying intersectional analysis, the age-adjusted likelihood of multimorbidity was investigated across 36 intersectional strata defined by gender, ethnicity, residence area and socioeconomic class. We calculated odds ratios (OR) 95% confidence interval (CI) using high-income urban non-migrant men as the reference category. The area under the receiver operator characteristics curve (AUC) was calculated to evaluate the discriminatory accuracy of multimorbidity. Results: The prevalence of multimorbidity increased with age, female gender and low income. Young and middle-aged low-income individuals showed rates of multimorbidity equivalent to those of high-income people aged about 20 years older. The intersectional analysis showed that low-income migrant women living in urban areas for >15 years were particularly disadvantaged in terms of multimorbidity risk OR = 3.16 (95% CI = 2.79-3.57). Being a migrant was a protective factor for multimorbidity, and newly arrived migrants had lower multimorbidity rates than those with >15 years of stay in Aragon, and even non-migrants. Living in rural vs. urban areas was slightly protective against multimorbidity. All models had a large discriminatory accuracy (AUC = 0.7884-0.7895); the largest AUC was obtained for the model including all intersectional strata. Conclusions: Our intersectional approach uncovered the large differences in the prevalence of multimorbidity that arise due to the synergies between the different socioeconomic and demographic exposures, beyond their expected additive effects.

12-year evolution of multimorbidity patterns among older adults based on Hidden Markov Models.

BACKGROUND: The evolution of multimorbidity patterns during aging is still an under-researched area. We lack evidence concerning the time spent by older adults within one same multimorbidity pattern, and their transitional probability across different patterns when further chronic diseases arise. The aim of this study is to fill this gap by exploring multimorbidity patterns across decades of age in older adults, and longitudinal dynamics among these patterns. METHODS: Longitudinal study based on the Swedish National study on Aging and Care in Kungsholmen (SNAC-K) on adults ≥60 years (N=3,363). Hidden Markov Models were applied to model the temporal evolution of both multimorbidity patterns and individuals' transitions over a 12-year follow-up. FINDINGS: Within the study population (mean age 76.1 years, 66.6% female), 87.2% had ≥2 chronic conditions at baseline. Four longitudinal multimorbidity patterns were identified for each decade. Individuals in all decades showed the shortest permanence time in an Unspecific pattern lacking any overrepresented diseases (range: 4.6-10.9 years), but the pattern with the longest permanence time varied by age. Sexagenarians remained longest in the Psychiatric-endocrine and sensorial pattern (15.4 years); septuagenarians in the Neuro-vascular and skin-sensorial pattern (11.0 years); and octogenarians and beyond in the Neuro-sensorial pattern (8.9 years). Transition probabilities varied across decades, sexagenarians showing the highest levels of stability. INTERPRETATION: Our findings highlight the dynamism and heterogeneity underlying multimorbidity by quantifying the varying permanence times and transition probabilities across patterns in different decades. With increasing age, older adults experience decreasing stability and progressively shorter permanence time within one same multimorbidity pattern.

Health trajectories after age 60: the role of individual behaviors and the social context.

BACKGROUND: This study aimed to detect health trajectories after age 60, and to explore to what extent individual and social factors may contribute to healthier aging. METHODS: Twelve-year health trajectories were identified in subjects from the Swedish National Study on Aging and Care in Kungsholmen (N=3108), integrating five indicators of disease, physical and cognitive function, and disability through nominal response models. Growth mixture models were applied to explore health trajectories in terms of rate and pattern of change. Baseline information about health-related behaviors and the social context was collected through standardized questionnaires. The strength of the associations was estimated using logistic regression, and their impact through population attributable fractions (PAF). RESULTS: Three trajectories were identified grouping 78%, 18%, and 4% of people with respectively increasing rates of health decline. Compared to the best trajectory, subjects in the middle and worst trajectories became functionally dependent 12.0 (95% CI: 11.4-12.6) and 12.1 (95% CI: 11.5-12.7) years earlier, respectively. Insufficient physical activity (OR: 3.38, 95% CI: 2.58-4.42), financial strain (OR: 2.76, 95% CI: 1.77-4.30), <12 years education (OR: 1.53, 95% CI: 1.14-2.04), low social connections (OR: 1.45, 95% CI: 1.09-1.94), low social participation (OR: 1.39, 95% CI: 1.06-1.83) and a body mass index ≥25 (OR: 1.34, 95% CI: 1.03-1.75) were associated with belonging to the middle/worst trajectories. The highest PAFs were observed for insufficient physical activity (27.1%), low education (19.3%) and low social participation (15.9%); a total PAF of 66.1% was obtained. CONCLUSIONS: Addressing the social determinants of health in its broadest sense, complementarily considering life-long factors belonging to the socioeconomic, psychosocial, and behavioral dimensions, should be central to any strategy aimed at fostering health in older age.

Overuse or underuse? Use of healthcare services among irregular migrants in a north-eastern Spanish region.

BACKGROUND: There is little verified information on global healthcare utilization by irregular migrants. Understanding how immigrants use healthcare services based on their needs is crucial to establish effective health policy. We compared healthcare utilization between irregular migrants, documented migrants, and Spanish nationals in a Spanish autonomous community. METHODS: This retrospective, observational study included the total adult population of Aragon, Spain: 930,131 Spanish nationals; 123,432 documented migrants; and 17,152 irregular migrants. Healthcare utilization data were compared between irregular migrants, documented migrants and Spanish nationals for the year 2011. Multivariable standard or zero-inflated negative binomial regression models were generated, adjusting for age, sex, length of stay, and morbidity burden. RESULTS: The average annual use of healthcare services was lower for irregular migrants than for documented migrants and Spanish nationals at all levels of care analyzed: primary care (0.5 vs 4 vs 6.7 visits); specialized care (0.2 vs 1.8 vs 2.9 visits); planned hospital admissions (0.3 vs 2 vs 4.23 per 100 individuals), unplanned hospital admissions (0.5 vs 3.5 vs 5.2 per 100 individuals), and emergency room visits (0.4 vs 2.8 vs 2.8 per 10 individuals). The average annual prescription drug expenditure was also lower for irregular migrants (€9) than for documented migrants (€77) and Spanish nationals (€367). These differences were only partially attenuated after adjusting for age, sex, and morbidity burden. CONCLUSIONS: Under conditions of equal access, healthcare utilization is much lower among irregular migrants than Spanish nationals (and lower than that of documented migrants), regardless of country of origin or length of stay in Spain.

Socioeconomic position and risk of unplanned hospitalization among nursing home residents: a nationwide cohort study.

BACKGROUND: Socioeconomic inequalities in health and healthcare use in old age have been on the rise during the past two decades. So far, it is unknown whether these inequalities have permeated the nursing home setting. This study aimed to assess whether the socioeconomic position of newly admitted nursing home residents had an influence on their risk of unplanned hospitalization. METHODS: We identified older persons (≥75 years) who were newly admitted to a nursing home between March 2013 and December 2014 using a set of linked routinely collected administrative and healthcare data in Sweden. The number of unplanned hospitalizations for any cause and the cumulative length of stay were defined as primary outcomes. Unplanned hospitalizations for potentially avoidable causes (i.e. fall-related injuries, urinary tract infections, pneumonia and decubitus ulcers) were considered as our secondary outcome. RESULTS: Among 40 545 newly admitted nursing home residents (mean age 86.8 years), the incidence rate of unplanned hospitalization ranged from 53.9 per 100 person-years among residents with tertiary education up to 55.1 among those with primary education. After adjusting for relevant confounders, we observed no meaningful difference in the risk of unplanned hospitalization according to the education level of nursing home residents (IRR for tertiary vs. primary education: 0.96, 95% CI 0.92-1.00) or to their level of income (IRR for highest vs. lowest quartile of income: 0.98, 0.95-1.02). There were also no differences in the cumulative length of hospital stays or in the risk of experiencing unplanned hospitalizations for potentially avoidable causes. CONCLUSIONS: In sum, in this large cohort of newly admitted nursing home residents, we found no evidence of socioeconomic inequalities in the risk of unplanned hospitalization.

Beyond the social gradient: the role of lifelong socioeconomic status in older adults' health trajectories.

Inequalities in older adults' health rarely consider life-course aspects of socioeconomic status (SES). We examined the association between lifelong SES and old-age health trajectories, and explored the role of lifestyle factors and depressive symptoms in this association. We followed 2760 adults aged 60+ from the Swedish National Study on Care and Aging, Kungsholmen. SES groups were derived using latent class analysis incorporating seven socioeconomic measures spanning childhood, midlife, and late life. We measured health using the Health Assessment Tool, which combines gait speed, cognition, multimorbidity, and disability. Linear mixed models were used to estimate health trajectories. Four SES groups were identified: High (34.9%), Middle (40.2%), Low (21.2%), and Mixed (3.8%). The Mixed group reported greater financial difficulties in childhood and older age, but varying SES attainment in midlife. Baseline health scores indicated that Mixed SES experienced substantial cognitive and physical deficits 12 years earlier than the High SES group. Compared to the High SES group, the Mixed SES group had the fastest health deterioration (ß×time=-0.07, 95% CI:-0.11,-0.02); other groups followed a gradient (High>Middle>Low). Lifestyle factors and depressive symptoms attenuated the gradient but did not explain Mixed group's health disadvantage. Life-long SES measures are crucial for understanding older adults' health inequalities.

COVID-19: risk accumulation among biologically and socially vulnerable older populations.

Emerging data show that the health and economic impacts of COVID-19 are being disproportionately borne by individuals who are not only biologically, but also socially vulnerable. Based on preliminary data from Sweden and other reports, in this paper we propose a conceptual framework whereby different factors related to biological and social vulnerability may explain the specific COVID-19 burden among older people. There is already some evidence showing large social disparities in the prevention, treatment, prognosis and/or long-term consequences of COVID-19. The remaining question is to what extent these affect older adults specifically. We provide the rationale to address this question with scientific methods and proper study designs, where the interplay between individuals' biomedical status and their social environment is the focus. Only through interdisciplinary research integrating biological, clinical and social data will we be able to provide new insights into the SARS-CoV-2 pandemic and inform actions aimed at reducing older adults' vulnerability to COVID-19 or other similar pandemics in the future.

Social support, social context and nonadherence to treatment in young senior patients with multimorbidity and polypharmacy followed-up in primary care. MULTIPAP Study.

OBJECTIVE: To estimate the prevalence of nonadherence to treatment and its relationship with social support and social context in patients with multimorbidity and polypharmacy followed-up in primary care. METHODS: This was an observational, descriptive, cross-sectional, multicenter study with an analytical approach. A total of 593 patients between 65-74 years of age with multimorbidity (≥3 diseases) and polypharmacy (≥5 drugs) during the last three months and agreed to participate in the MULTIPAP Study. The main variable was adherence (Morisky-Green). The predictors were social support (structural support and functional support (DUFSS)); sociodemographic variables; indicators of urban objective vulnerability; health-related quality of life (EQ-5D-5L-VAS & QALY); and clinical variables. Descriptive, bivariate and multivariate analyses with logistic regression models and robust estimators were performed. RESULTS: Four out of ten patients were nonadherent, 47% had not completed primary education, 28.7% had an income ≤1050 €/month, 35% reported four or more IUVs, and the average perceived health-related quality of life (HRQOL) EQ-5D-5L-VAS was 65.5. The items that measure functional support, with significantly different means between nonadherent and adherent patients were receiving love and affection (-0.23; 95%CI: -0.40;-0.06), help when ill (-0.25; 95%CI: -0.42;-0.08), useful advice (-0.20; 95%CI: -0.37;-0.02), social invitations (-0.22; 95%CI:-0.44;-0.01), and recognition (-0.29; 95%CI:-0.50;-0.08). Factors associated with nonadherence were belonging to the medium vs. low tertile of functional support (0.62; 95%CI: 0.42;0.94), reporting less than four IUVs (0.69; 95%CI: 0.46;1.02) and higher HRQOL perception (0.98; 95%CI: 0.98;0.99). CONCLUSIONS: Among patients 65-74 years of age with multimorbidity and polypharmacy, lower functional support was related to nonadherence to treatment. The nonadherence decreased in those patients with higher functional support, lower urban vulnerability and higher perceived health status according to the visual analog scale of health-related quality of life.

Unplanned Hospital Care Use in Older Adults: The Role of Psychological and Social Well-Being.

OBJECTIVES: To explore the association of psychological and social well-being with unplanned hospital utilization in an older Swedish population. DESIGN: Data for this study were gathered from the Swedish National Study on Aging and Care in Kungsholmen (SNAC-K). Information on hospital care use was extracted from the Stockholm County Council Inpatient Register for up to 4 years after the baseline SNAC-K assessment (2001-2007). Participants with dementia or living in institutions were excluded from the study sample. SETTING: Community-based study of randomly selected adults, aged 60 years or older, living in the Kungsholmen district of Stockholm. PARTICIPANTS: A complete case analysis was performed on 2139 individuals. MEASUREMENTS: We created standardized indexes of psychological well-being (integrating life satisfaction and positive and negative affect) and social well-being (integrating social connections, support, and participation). Negative binomial models were used to estimate the association of psychosocial well-being with unplanned admissions, hospital days, and 30-day readmissions, considering potential sociodemographic, lifestyle, personality, and clinical confounders. RESULTS: Individuals with psychological well-being scores above the median had lower rates of unplanned hospital admissions (incidence rate ratio [IRR] = 0.67; 95% confidence interval [CI] = 0.55-0.82) and hospital days (IRR = 0.67; 95% CI = 0.49-0.92) compared to those with scores below the median. High levels of social well-being were also protective for unplanned admissions and hospital days, but the statistical significance was lost in the fully adjusted models. Relative to individuals with low well-being on both indexes, the rate of unplanned admissions and hospital days was lowest in those with both high psychological and social well-being (IRR = 0.72; 95% CI = 0.55-0.93; and IRR = 0.57; 95% CI = 0.39-0.85, respectively). For 30-day readmissions, a statistically significant negative association was found with psychological well-being, but only when operationalized as a continuous variable. CONCLUSION: Given their association with unplanned admissions and hospital days, targeting aspects of psychosocial well-being could be a viable strategy for reducing healthcare use and, eventually, costs. J Am Geriatr Soc 68:272-280, 2020.

Patterns of Multimorbidity in a Population-Based Cohort of Older People: Sociodemographic, Lifestyle, Clinical, and Functional Differences.

BACKGROUND: The aim of this study is to identify clusters of older persons based on their multimorbidity patterns and to analyze differences among clusters according to sociodemographic, lifestyle, clinical, and functional characteristics. METHODS: We analyzed data from the Swedish National Study on Aging and Care in Kungsholmen on 2,931 participants aged 60 years and older who had at least two chronic diseases. Participants were clustered by the fuzzy c-means cluster algorithm. A disease was considered to be associated with a given cluster when the observed/expected ratio was ≥2 or the exclusivity was ≥25%. RESULTS: Around half of the participants could be classified into five clinically meaningful clusters: respiratory and musculoskeletal diseases (RESP-MSK) 15.7%, eye diseases and cancer (EYE-CANCER) 10.7%, cognitive and sensory impairment (CNS-IMP) 10.6%, heart diseases (HEART) 9.3%, and psychiatric and respiratory diseases (PSY-RESP) 5.4%. Individuals in the CNS-IMP cluster were the oldest, with the worst function and more likely to live in a nursing home; those in the HEART cluster had the highest number of co-occurring diseases and drugs, and they exhibited the highest mean values of serum creatinine and C-reactive protein. The PSY-RESP cluster was associated with higher levels of alcoholism and neuroticism. The other half of the cohort was grouped in an unspecific cluster, which was characterized by gathering the youngest individuals, with the lowest number of co-occurring diseases, and the best functional and cognitive status. CONCLUSIONS: The identified multimorbidity patterns provide insight for setting targets for secondary and tertiary preventative interventions and for designing care pathways for multimorbid older people.

Geriatric Health Charts for Individual Assessment and Prediction of Care Needs: A Population-Based Prospective Study.

BACKGROUND: Geriatric health charts that are similar to pediatric growth charts could facilitate monitoring health changes and predicting care needs in older adults. We aimed to validate an existing composite score (Health Assessment Tool [HAT]) and provide provisional age-specific reference curves for the general older population. METHODS: Data came from the Swedish National study on Aging and Care in Kungsholmen (N = 3,363 participants aged 60 years and over examined clinically at baseline and 3 years later). HAT was validated by exploring its relationship with health indicators (logistic regression) and comparing its ability to predict care consumption with that of two of its components, morbidity and disability (receiver operating characteristic curve areas). A flowchart was developed to obtain individual-level HAT scores (nominal response method). Sex-specific health charts were derived by graphing seven percentile curves of age-related HAT change (logistic quantile regression). RESULTS: HAT scores above the age- and sex-specific median were related to good performance in chair-stand tests (odds ratio [OR] = 2.62, 95% confidence interval [CI]: 2.07-3.31), balance and grip tests (interaction balance grip test, OR = 1.15, 95% CI: 1.05-1.25), and good self-rated health (OR = 2.19, 95% CI: 1.77-2.71). Receiver operating characteristic curve areas (HAT vs number of chronic disorders) were formal care, 0.76 versus 0.58 (p value < .001); informal care, 0.74 versus 0.59 (p value < .001); hospital admission, 0.70 versus 0.66 (p value < .001); primary care visits, 0.71 versus 0.69 (p value > .05); and specialty care visits, 0.62 versus 0.65 (p value < .001). HAT consistently predicted medical and social care service use better than disability. CONCLUSIONS: HAT is a valid tool that predicts care consumption well and could be useful in developing geriatric health charts to better monitor health changes in older populations.

Comparing the prognostic value of geriatric health indicators: a population-based study.

BACKGROUND: The identification of individuals at increased risk of poor health-related outcomes is a priority. Geriatric research has proposed several indicators shown to be associated with these outcomes, but a head-to-head comparison of their predictive accuracy is still lacking. We therefore aimed to compare the accuracy of five geriatric health indicators in predicting different outcomes among older persons: frailty index (FI), frailty phenotype (FP), walking speed (WS), multimorbidity, and a summary score including clinical diagnoses, functioning, and disability (the Health Assessment Tool; HAT). METHODS: Data were retrieved from the Swedish National Study on Aging and Care in Kungsholmen, an ongoing longitudinal study including 3363 people aged 60+. To inspect the accuracy of geriatric health indicators, we employed areas under the receiver operating characteristic curve (AUC) for the prediction of 3-year and 5-year mortality, 1-year and 3-year unplanned hospitalizations (1+), and contacts with healthcare providers in the 6 months before and after baseline evaluation (2+). RESULTS: FI, WS, and HAT showed the best accuracy in the prediction of mortality [AUC(95%CI) for 3-year mortality 0.84 (0.82-0.86), 0.85 (0.83-0.87), 0.87 (0.85-0.88) and AUC(95%CI) for 5-year mortality 0.84 (0.82-0.86), 0.85 (0.83-0.86), 0.86 (0.85-0.88), respectively]. Unplanned hospitalizations were better predicted by the FI [AUC(95%CI) 1-year 0.73 (0.71-0.76); 3-year 0.72 (0.70-0.73)] and HAT [AUC(95%CI) 1-year 0.73 (0.71-0.75); 3-year 0.71 (0.69-0.73)]. The most accurate predictor of multiple contacts with healthcare providers was multimorbidity [AUC(95%CI) 0.67 (0.65-0.68)]. Predictions were generally less accurate among younger individuals (< 78 years old). CONCLUSION: Specific geriatric health indicators predict clinical outcomes with different accuracy. Comprehensive indicators (HAT, FI, WS) perform better in predicting mortality and hospitalization. Multimorbidity exhibits the best accuracy in the prediction of multiple contacts with providers.

Association Between Speed of Multimorbidity Accumulation in Old Age and Life Experiences: A Cohort Study.

Rapidly accumulating multiple chronic conditions (multimorbidity) during aging are associated with many adverse outcomes. We explored the association between 4 experiences throughout life-childhood socioeconomic circumstances, early-adulthood education, midlife occupational stress, and late-life social network-and the speed of chronic disease accumulation. We followed 2,589 individuals aged ≥60 years from the Swedish National Study on Aging and Care in Kungsholmen for 9 years (2001-2013). Information on life experiences was collected from detailed life-history interviews. Speed of disease accumulation was operationalized as the change in the count of chronic conditions obtained from clinical examinations, medical histories, laboratory data, drug use, and register linkages over 9 years. Linear mixed models were used to analyze the data. Speed of disease accumulation was lower in individuals with more than elementary education (for secondary, ß × time = -0.065, 95% CI: -0.126, -0.004; for university, ß × time = -0.118, 95% CI: -0.185, -0.050); for active occupations compared with high-strain jobs (ß × time = -0.078, 95% CI: -0.138, -0.017); and for richer social networks (for moderate tertile, ß × time = -0.102, 95% CI: -0.149, -0.055; for highest tertile, ß × time = -0.135, 95% CI: -0.182, -0.088). The association between childhood circumstances and speed of disease accumulation was attenuated by later-life experiences. Diverse experiences throughout life might decelerate chronic disease accumulation during aging.

The definition of immigrant status matters: impact of nationality, country of origin, and length of stay in host country on mortality estimates.

BACKGROUND: Mortality is a robust indicator of health and offers valuable insight into the health of immigrants. However, mortality estimates can vary significantly depending on the manner in which immigrant status is defined. Here, we assess the impact of nationality, country of origin, and length of stay in the host country on mortality estimates in an immigrant population in Aragón, Spain. METHODS: Cross-sectional retrospective study of all adult subjects from the EpiChron Cohort in 2011 (n = 1,102,544), of whom 146,100 were foreign-born (i.e., according to place of birth) and 127,213 were non-nationals (i.e., according to nationality). Directly standardized death proportions between years 2012-2015 were calculated, taking into account the age distribution of the European population in 2013. Binary logistic regression was used to compare the four-year probability of death. RESULTS: The age- and sex-standardized number of deaths per 1000 subjects were 45.1 (95%CI 44.7-45.2) for the Spanish-born population, 29.3 (95%CI 26.7-32.1) for the foreign-born population, and 18.4 (95%CI 15.6-21.6) for non-Spanish nationals. Compared with the Spanish-born population, the age- and sex-adjusted likelihood of dying was equally reduced in the foreign-born and non-national populations (OR 0.6; 95%CI 0.5-0.7) when the length of stay was less than 10 years. No significant differences in mortality estimates were detected when the length of stay was over 10 years. CONCLUSIONS: Mortality estimates in immigrant populations were lower than those of the native Spanish population, regardless of the criteria applied. However, the proportion of deaths was lower when immigrant status was defined using nationality instead of country of birth. Age- and sex-standardized death proportions tended to increase with increased length of stay in the host country.