BACKGROUND:In people with multimorbidity, traditional, disease-oriented approaches may overlook the impact of symptoms on daily functioning. OBJECTIVE:To explore the assumption that symptoms and signs provide information on functional limitations beyond that of diseases in older adults, specifically those with multimorbidity. SUBJECTS:4025 participants in the Longitudinal Aging Study Amsterdam (1995-2022). METHODS:Analyses included six symptoms, five signs and eight diseases as exposures and a sum score of six functional limitations as the outcome. Partial Information Decomposition was used to partition the total variability in functional limitations into unique, redundant and synergistic information provided by the exposures in the total sample and in the multimorbidity subgroup. Random forest prediction models were run to examine the added predictive value of symptoms, signs and diseases. RESULTS:In the total sample, 59% had multimorbidity. Symptoms, signs and diseases together explained 13.3% of variability in functional limitations. None of the three domains contributed unique information. Synergy accounted for most of the explained variability (signs = 9.2%, symptoms = 34.3%, diseases = 34.3%). In the multimorbidity subgroup, symptoms, signs and diseases together explained 8.7% of variability in functional limitations. Symptoms uniquely contributed 35.5% of their information, while signs and diseases were redundant. Prediction models showed that symptoms provided substantial predictive value beyond diseases alone, with a 110% increase in predictive agreement when symptoms were added to diseases in the multimorbidity subgroup, compared to 58% in the total sample. CONCLUSIONS:In people with multimorbidity, symptoms and signs explain more variability in functional limitations than diseases alone, supporting the need for a symptom-oriented approach in clinical care and research.

This study examined the association of disease-specific symptoms (e.g., chest or joint pain) and nonspecific symptoms (e.g., fatigue, dizziness, anxiety) with functional limitations in community-dwelling older adults over a 23-year follow-up. The nonspecific symptoms ‘fall or injury’, ‘arm or leg weakness’, and ‘dizziness’ demonstrated the strongest cross-sectional associations with functional limitations in community-dwelling older adults. Memory or thinking problems was the only symptom with a significant positive association with more functional limitations 1 month later, suggesting that most symptoms relate more closely to current than future daily functioning. This study demonstrates that nonspecific symptoms often have stronger cross-sectional associations with functional limitations than most disease-specific symptoms, highlighting the need to assess nonspecific symptoms for a comprehensive understanding of the functional burden in older adults. Older adults often have multiple diseases and age-related physiologic changes that may present with nonspecific symptoms such as fatigue or dizziness. Identifying symptoms that are most strongly associated with functioning may guide symptom management. This study examined the association of nonspecific and disease-specific symptoms with functional limitations in community-dwelling older adults over a 23-year period. Data were from the Precipitating Events Project, a longitudinal cohort study, involving 754 adults aged 70 and older [mean (standard deviation) age of 78.9 (5.3) years, 64.6

In the context of multimorbidity, clinical features seldom act in isolation: symptoms, signs and behaviours form interdependent systems in which joint effects on function can be demonstrated only when features are considered together. We introduce an open, reusable workflow that detects and interprets these "together-only" interactions using bivariate Partial Information Decomposition (PID; two sources to one target), linking synergy-based dependence to the broader network of clinical variables rather than to a single target. The workflow estimates synergy with small-sample bias correction and summarises each pair in a Breadth-Uniformity-Synergy-Total (BUST) map: breadth of synergy across target variables (broad "generalist" vs narrow "specialist" patterns), cross-stratum uniformity across age, sex and multimorbidity (uniform vs subgroup-specific), synergy strength, and total shared information. Simple diagnostics contrast observed targets with additive expectations, revealing the specific joint configurations through which non-additive effects arise. Applied to data from the Longitudinal Ageing Study Amsterdam, we treated all health-related variables-covering symptoms, clinical signs, behaviours, lifestyle factors, and self-rated health indicators-as both sources and targets in the PID framework. This symmetric design permits synergy to be quantified for every pair of variables with respect to every other variable. The workflow identifies synergistic constellations that additive models miss. Multidomain cliques involving subjective health, pain, cognition and grip strength showed multiple non-additive configurations, whereas pairs such as alcohol use with grip strength exhibited focused, narrow but uniform synergy. Notably, the pairs with the strongest synergistic contributions were largely distinct from those with the highest total mutual information, indicating that synergy captures dependency structure overlooked by conventional association measures. Rather than a new measure, this work provides a bias-aware workflow that makes higher-order dependence visible and transferable. Our results support synergy-aware mapping as a practical complement to conventional multimorbidity analyses: it highlights specific combinations of routinely assessed features whose joint states may be especially informative across multiple health targets and therefore candidates for prioritised joint assessment and future multi-domain intervention studies.

BackgroundThe global impact of COVID-19 restrictions on people with dementia (PWD) living at home and their informal caregivers has been described extensively. However, adoption of this knowledge into policy and practice is limited because of a lack of coordinated, inclusive, and regionally sensitive prioritization.ObjectiveTo establish key regional research priorities for Europe and the Global South.MethodsFollowing consensus-based prioritization methods, we applied a three-step approach: 1) a systematic literature review to derive a list of topics describing how PWD and caregivers were impacted by the COVID-19 restrictions; 2) an online survey distributed to PWD, caregivers and health care professionals (HCP) across 14 countries asking respondents to select the 10 most important topics; and 3) an iterative consultation process with stakeholders from each country to translate the top-ranked topics into a research agenda.ResultsWe identified 51 quantitative and 18 qualitative relevant publications, from which we derived 38 topics. 29 PWD, 110 caregivers and 117 HCP across 14 countries prioritized these topics, which largely overlapped across stakeholder groups and countries. The top ranked priorities cluster into four themes: daily routine and physical function, mental health, disease progression, and access to care. The consultancy process with stakeholders resulted in three lines of research to address these themes: understanding mechanisms, designing and improving education, and information access.ConclusionsThis research agenda offers a roadmap to guide future research and policy aimed at strengthening support for PWD and their caregivers in times of public health crises.

The application of complex systems science is gaining traction in the field of ageing research. A complex system is a large collection of components whose dynamic interactions lead to 'emergent properties' that cannot be understood or predicted based on knowledge of the components in isolation. Here we conceptualise human ageing as resulting from integrated, multi-scale systems characterised by dynamic interactions within and between biological, behavioural, functional and environmental domains. Complexity science provides tools to study these joint dynamics, allowing researchers to address research questions that examine (1) interactions across levels or domains, (2) dynamic processes over time, or (3) emergent behaviour of the system as a whole, which is not reducible to individual components. Studying complex systems can benefit from these methodological tools, which are still underexplored in gerontology and geriatrics. With this article, we intend to inspire and support researchers in the field of ageing to explore the potential of complexity science methods for their own research. We explain four different methodological approaches to study complex systems: causal loop diagrams, system dynamics modelling, psychometric network analysis, and dynamical indicators of resilience and complexity. For each of these approaches, we explain their purpose and theoretical assumptions, provide examples from the scientific literature, and discuss their strengths and limitations. As it remains challenging to operationalise complexity-driven research questions and select appropriate methods from the growing range of available methodological approaches, particularly for researchers unfamiliar with them, we hope to have lowered this threshold.

Objective:Up to 30% of patients with osteoarthritis experience suboptimal recovery after total knee arthroplasty (TKA), increasing interest in prehabilitation as a potential strategy to improve postoperative outcomes. This study compared the efficacy of individual prehabilitation modalities versus standard care for physical function, quadriceps strength, pain, and health-related quality of life (HR-QoL) at 3 months after TKA, with additional analyses at 4-8 weeks. Design:We conducted a systematic review and network meta-analysis (NMA) of randomized controlled trials (RCTs) following PRISMA guidelines. Eligible studies included adults undergoing TKA for osteoarthritis who received preoperative prehabilitation targeting physical, educational, nutritional, or behavioral domains. Comparators were standard care or alternative prehabilitation interventions. Confidence in the evidence was assessed using the CINeMA framework. Results:20 RCTs (1095 patients) comparing eight prehabilitation modalities were included. At 3 months after TKA, no prehabilitation modality demonstrated statistically significant improvements in physical function, quadriceps strength, pain, or HR-QoL compared with standard care. Similar findings were observed at 4-8 weeks after TKA, except that lower-extremity strength training significantly improved quadriceps strength compared with standard care. Confidence in the evidence was predominantly low to very low, primarily because of imprecision, although three treatment comparisons were supported by moderate confidence. Conclusion:Current evidence does not support recommending one prehabilitation modality over another before TKA. Although lower-extremity strength training improved short-term quadriceps strength, this finding was supported by low-confidence evidence. Larger, adequately powered head-to-head trials are needed to determine whether specific prehabilitation modalities provide clinically meaningful postoperative benefits. Registration:PROSPERO (CRD42024490615).

BACKGROUND:Prehabilitation has been proposed to enhance recovery after total hip arthroplasty (THA). Understanding its preoperative effectiveness across modalities is an important step towards clarifying its potential role in optimizing recovery. OBJECTIVE:To compare the preoperative effectiveness of various prehabilitation modalities with standard care on physical function, pain, health-related quality of life (HR-QoL), and Timed Up and Go (TUG) performance in individuals awaiting THA, and to summarize other performance-based, strength, and hip-specific outcomes when data were insufficient for network meta-analysis. METHODS:A systematic review and network meta-analysis of randomized controlled trials (RCTs) was conducted following PRISMA guidelines. Eligible studies included individuals undergoing THA for end-stage osteoarthritis who received any form of preoperative prehabilitation targeting physical, educational, nutritional, or behavioral domains, either alone or in combination. Comparators were standard care or another prehabilitation intervention. Confidence in the evidence was assessed using CINeMA. RESULTS:21 RCTs involving 1061 participants were included, comprising 10 prehabilitation modalities: lower-extremity strength training, clinic-based multidomain exercise, home-based exercise (with or without protein supplementation), tele-prehabilitation, neuromuscular electrical stimulation, Tai Chi, upper-body high-intensity training, heat-plus-resistance training, and education. Multidomain exercise, lower-extremity strength training, and Tai Chi demonstrated beneficial preoperative effects, whereas no statistically significant effects were observed for the other modalities. Tai Chi improved physical function (SMD = 0.94; 95% CI 0.07-1.80; I2 = 54%) and TUG performance (SMD = 1.50; 95% CI 0.92-2.07; I2 = 0%). Multidomain exercise reduced pain (SMD = 0.54; 95% CI 0.16-0.92; I2 = 52%) and enhanced HR-QoL (SMD = 0.44; 95% CI 0.16-0.71; I2 = 30%). Lower-extremity strength training improved HR-QoL (SMD = 0.49; 95% CI 0.03-0.94; I2 = 30%). Overall confidence was low to very low due to imprecision, and moderate for Tai Chi versus standard care (TUG). CONCLUSION:Tai Chi, multidomain exercise, and lower-extremity strength training showed preoperative benefits, with moderate-to-low confidence in the evidence. Well-powered trials with standardized outcomes are needed to confirm these effects. REGISTRATION:PROSPERO (CRD42024490615).

ABSTRACT Background COVID‐19 control measures have had a unique impact on people with dementia (PWD) and their carers living at home. Yet, uncertainty exists regarding the global impact of such measures and whether differences exist between countries and global regions. We aimed to synthesize evidence on this topic. Methods We searched Medline, PsycINFO, EMBASE, Web of Science, CINAHL, Latin American and Caribbean Health Literature (LILACS), Scientific Electronic Library Online (SciELO), and EM Premium from the start of the pandemic to July 2022. At least two researchers independently screened citations and performed quality assessment following recommended criteria for critical appraisal according to study methodology. We analyzed data by country and region and synthesized results descriptively. Results Sixty‐nine studies met inclusion criteria (74% quantitative and 26% qualitative; 22% included PWD, 44% carers of PWD, and 4% dyads), with a total of 209,738 participants. Most studies were conducted in Europe (59%), followed by Asia and North America (15% each), South America (7%), and Oceania (1%). Two studies presented data from multiple regions (3%). The quality of the studies varied, with the majority (62%) being of moderate quality. Across the study populations and global regions, COVID‐19 control measures had implications for PWD and carers’ access to health services, physical and mental health and daily routine, cognition, behavior, with accompanying social and economic costs. The impact on mental health for PWD and on loneliness and well‐being for carers were the two most frequently studied outcomes. Conclusion People with dementia and their carers represent a heterogeneous group of people across countries and communities; despite that, the impacts of COVID‐19 control measures on PWD and their carers were broadly consistent across regions. Our evidence synthesis highlights the critical need for decision‐makers to account for the needs of PWD and their carers when designing and implementing public health measures. Other This work was funded by the JPND Call for Expert Working Groups: The Impact of COVID‐19 on Neurodegenerative Diseases in partnership with the CIHR‐Institute of Aging and the Public Health Agency (CIHR #02342‐000). PROSPERO CRD42024554701.

OBJECTIVES:Hand grip measures offer potential indicators for recovery after hospitalization in older adults. We investigated prospective associations of the grip indicators maximal grip strength (GSmax), fatigue resistance (FR) and grip work (GW) with post-discharge functional limitations, health-related quality of life (HRQOL) and survival in older inpatients. METHODS:Grip indicators were evaluated at admission in general geriatric inpatients (GGI, n = 149) and geriatric hip fracture inpatients (HIP, n = 109). Questionnaires on functional limitations (10-40, lower is better) were collected for two weeks pre-admission, admission, three months follow-up, and six months follow-up. HRQOL (-4-10, higher is better) was assessed at admission, three months follow-up and six months follow-up. With individual growth modeling, we established the associations between grip indicators and the outcome trajectories. Three-month survival was analyzed using Cox proportional hazards models. RESULTS:In GGI, higher FR and GW were associated with better functional recovery from admission to three months follow-up (FR: B = -1.0 points per 10s increase, 95 %CI -1.9, -0.14; GW: B = -0.33 points per 100 kPa × s increase, 95 %CI -0.59, -0.07). HIP with higher grip indicators showed a better functional recovery towards three months follow-up (GSmax: B = -2.4 per 10 kPa increase, 95 %CI -3.9, -0.89; FR: B = -1.1, 95 %CI -2.4, 0.20; GW: B = -0.31, 95 %CI -0.61, -0.02). No or weak associations were found between grip indicators and HRQOL recovery. Hazard ratios pointed towards a better survival for better scores on grip indicators, but associations were not statistically significant. CONCLUSION:Higher FR and GW at admission were associated with better recovery post-discharge in geriatric inpatients. Future research should examine the added clinical value of grip indicators in addition to known patient characteristics.

BACKGROUND:Although physical activity (PA) is known to improve physical function (PF), and functional decline impacts the capacity to engage in PA, the reciprocal relationship between PA and PF remains unclear. METHODS:Data were from participants in the 1921-1926 cohort of the Australian Longitudinal Study on Women's Health (N = 8 238). PA and PF were assessed at 3-year intervals from 1999 (73-78 y) to 2011 (85-90 y). Group-based trajectory modeling was used to identify PA and PF trajectories, and associations between PA and PF were examined using mixed-effects models and restricted cubic spline modeling. RESULTS:Three trajectories for PA and PF were identified: Low, Moderate, and High. Women in the High PA group maintained high PF and did not reach the starting PF level of the Low PA group (at age 73) until they were 87. Similarly, women in the High PF group maintained higher PA than those in the other groups. Women in the Low PF group never met PA guidelines and had PF scores below the disability threshold throughout the study. Restricted cubic splines showed that higher PA was associated with better PF 3 years later, and vice versa, indicating that PA and PF influence each other. CONCLUSION:There are reciprocal relationships between PF and PA; higher levels of PA promote better PF, and higher PF may help slow the decline in PA. Although rates of decline in PF show little variation with PA in women during their 80s, habitually high PA confers considerable benefits, contributing to additional years of healthy life.

Loneliness is a growing public health concern with a wide-range of impacts on mental and physical well-being. While most interventions adopt a uniform, one-size-fits-all approach, emerging evidence suggests that the effectiveness of loneliness interventions depends on individual psychological traits and the structure of social environments. Previous work has shown that mental health outcomes are shaped not only by personal vulnerabilities but also by complex feedback processes embedded in social networks. However, it remains unclear which types of interventions work best for which individuals, and how social context modulates these effects. We develop and apply an agent-based model that simulates mental health on a continuum with loneliness as a latent state at its lower end. The model is shaped by baseline resilience, self-reinforcement, and social influence mechanisms, across a realistic synthetic population. We target these mechanisms for specific individuals and varying proportions of their social networks. Outcomes for the individual and sequential neighbors are compared to a counterfactual. We use a random forest model and compute SHAP values that identify which features of the individuals and their social networks predict intervention success.We show that interventions improving baseline resilience consistently benefit individuals, particularly those with low socioeconomic status embedded in moderately diverse networks. In contrast, interventions targeting self-reinforcement or peer influence exhibit greater variability and may produce adverse effects in overly homogeneous or fragmented contexts. Surprisingly, classical network centrality metrics fail to explain these patterns; instead, similarity in baseline and mental health traits across social layers emerges as a strong predictor of intervention efficacy.These findings suggest that personalization based on social and psychological similarity is more informative than topological metrics when designing interventions for loneliness. The results challenge assumptions about “scaling up” interventions and highlight the importance of tailoring to social context and individual vulnerability. More broadly, our approach demonstrates how computational models can capture the complex interplay between individual traits and cumulative, self-consistent social feedbacks, offering a concrete framework for designing socially aware, targeted public health interventions.

The disease course and outcome of COVID-19 greatly varies between individuals. To explore which biological systems may contribute to this variation, we examined how individual metabolites and three metabolic scores relate to COVID-19 outcomes in hospitalized COVID-19 patients. The metabolome of 346 patients was measured using the 1H-NMR Nightingale platform. The association of individual metabolomic features and multi-biomarker scores, i.e. MetaboHealth, MetaboAge, and Infectious Disease Score (IDS) (higher scores reflect poorer health), with in-hospital disease course, long-term recovery, and overall survival were analyzed. Higher values for the metabolites phenylalanine (HR = 1.33, CI = 1.14–1.56), glucose (HR = 1.37, CI = 1.16–1.62) and lactate (HR = 1.38, CI = 1.16–1.63) were associated with mortality. For all three metabolic scores, higher scores were significantly associated with higher odds of a poorer in-hospital disease course (MetaboHealth: OR = 1.61, CI = 1.29–2.02; ΔMetaboAge: OR = 1.42, CI = 1.16–1.74; IDS: OR = 1.55, 1.25–1.93) and with overall survival (MetaboHealth: HR = 1.57, CI = 1.28–1.92; ΔMetaboAge: HR = 1.34, CI = 1.15–1.57; IDS: HR = 1.56, CI = 1.27–1.93). MetaboHealth and ΔMetaboAge showed a stronger association in younger patients (< 70 yrs.) than older patients. No clear patterns were found in associations between the three scores and measures of long-term recovery. In conclusion, the heterogeneity in disease course after SARS-COV2 infection may be explained either by generic biological frailty reflected by the three metabolomics scores or by glycemic control (glucose, lactate) and respiratory distress (phenylalanine).

Abstract Background During the COVID-19 pandemic, nursing home (NH) residents faced the highest risk of severe COVID-19 disease and mortality. Due to their frailty status, comorbidity burden can serve as a useful predictive indicator of vulnerability in this frail population. However, the prognostic value of these cumulative comorbidity scores like the Charlson comorbidity index (CCI) remained unclear in this population. We evaluated the incremental predictive value of the CCI for predicting 28-day mortality in NH residents with COVID-19, compared to prediction using age and sex only. Methods We included older individuals of ≥ 70 years of age in a large retrospective observational cohort across NHs in the Netherlands. Individuals with PCR-confirmed COVID-19 diagnosis from 1 March 2020 to 31 December 2021 were included. The CCI score was computed by searching for the comorbidities recorded in the electronic patient records. All-cause mortality within 28 days was predicted using logistic regression based on age and sex only (base model) and by adding the CCI to the base model (CCI model). The predictive performance of the base model and the CCI model were compared visually by the distribution of predicted risks and area under the receiver operator characteristic curve (AUROC), scaled Brier score, and calibration slope. Results A total of 4318 older NH residents were included in this study with a median age of 88 years [IQR: 83–93] and a median CCI score of 6 [IQR: 5–7]. 1357 (31%) residents died within 28 days after COVID-19 diagnosis. The base model, with age and sex as predictors, had an AUROC of 0.61 (CI: 0.60 to 0.63), a scaled brier score of 0.03 (CI: 0.02 to 0.04), and a calibration slope of 0.97 (CI: 0.83 to 1.13). The addition of CCI did not improve these predictive performance measures. Conclusion The addition of the CCI as a vulnerability indicator did not improve short-term mortality prediction in NH residents. Similar (high) age and number of comorbidities in the NH population could reduce the effectiveness of these predictors, emphasizing the need for other population-specific predictors that can be utilized in the frail NH residents. Graphical Abstract

Social internet use might decrease loneliness, potentially by increasing social contact. Vice versa, loneliness might decrease social internet use by decreased social contact. However, few studies explored these associations longitudinally. This study aimed to assess the longitudinal, bidirectional associations between frequency of social internet use, loneliness, and social contact (measured as the number of frequently contacted personal network members). We used four waves of the Longitudinal Aging Study Amsterdam (2011-13, 2015-16, 2018-19, 2021-22) in a sample of 1923 Dutch older adults (age 55-98). We applied random intercept cross-lagged panel models to test the bidirectional and mediational relationships. We found a longitudinal association between social internet use and subsequent loneliness, β = -0.07, p = .008, but no evidence of mediation of social contact, nor of a reversed association. These results strengthen existing evidence for a positive association of social internet use in decreasing loneliness. In contrast, more loneliness did not predict a difference in social internet use, suggesting that this reversed relationship is more complex or dependent on individual characteristics.

Hand grip measures are promising candidate markers for recovery in geriatric patients. To advance interpretation of these measures, we examined: (1) the associations between grip measures at admission and measures of frailty, daily functioning and fatigue to understand the constructs they measure; (2) alternate operational definitions of grip measures. 181 geriatric inpatients completed twice daily grip measurements using the Eforto® vigorimeter, including maximum grip strength (GSmax), fatigue resistance (FR), grip work (GW) and capacity to perceived vitality ratio (CPV). Associations with each of these measures and the outcomes frailty index (range 0-100), functional limitations (10–40), and total (4–20) and physical (20–100) fatigue were examined using linear regression. Analyses were repeated for the baseline value, average of first two measurements, within-person standard deviation of all values, and the coefficient of variation of all values for each of the grip measures. Associations approached statistical significance for baseline GSmax and the outcomes frailty (B=-0.09, 99

INTRODUCTION:During the COVID19 pandemic, older patients hospitalized for COVID-19 exhibited an increased mortality risk compared to younger patients. While ageing is associated with compromised immune responses and frailty, their contributions and interplay remain understudied. This study investigated the association between inflammatory markers and mortality and potential modification by frailty among older patients hospitalized for COVID-19. METHODS:Data were from three multicenter Dutch cohorts (COVID-OLD, CliniCo, Covid-Predict). Patients were 70 years or older, hospitalized for COVID-19and categorized into three frailty groups: fit (Clinical frailty score (CFS) 1-3), pre-frail (CFS 4-5), and frail (CFS 6-9). Immunological markers (lymphocyte count, neutrophil count, C-reactive protein, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and systemic inflammation index (SII)) were measured at baseline. Associations with in hospital mortality were examined using logistic regression. RESULTS:A total of 1697 patients were included from COVID-OLD, 656 from Covid-Predict, and 574 from CliniCo. The median age was 79, 77, and 78 years for each cohort. Hospital mortality rates were 33 %, 27 % and 39 % in the three cohorts, respectively. A lower CRP was associated with a higher frailty score in all three cohorts (all p < 0.01). Lymphocyte count, neutrophil count, NLR, PLR, or SII, were similar across frailty groups. Higher CRP levels were associated with increased in-hospital mortality risk across all frailty groups, across all cohorts (OR (95 % CI), 2.88 (2.20-3.78), 3.15 (1.95-5.16), and 3.28 (1.87-5.92)), and frailty did not modify the association between inflammatory markers and in-hospital mortality (all p-interaction>0.05). CONCLUSION:While frailty is a significant factor in determining overall outcomes in older patients, our study suggests that the elevated risk of mortality in older patients with frailty compared to fit patients is likely not explained by difference in inflammatory responses.

The aim of this prospective cohort study was to compare changes in lifestyle behaviours over nine years in women who were and were not diagnosed with osteoarthritis (OA). Data were from the 1945-51 cohort of the Australian Longitudinal Study on Women's Health (aged 50-55 in 2001) who completed written surveys in 2001, 2004, 2007 and 2010. The sample included 610 women who were, and 3810 women who were not diagnosed with OA between 2004 and 2007. Descriptive statistics were used to assess changes in lifestyle behaviours (weight, sitting time, physical activity, alcohol and smoking) in the two groups, over three survey intervals: from 2001-2004 (prior to diagnosis); from 2004-2007 (around diagnosis); and from 2007-2010 (following diagnosis). Compared with women without OA (28%), a greater proportion of women with OA (38%) made at least one positive lifestyle change (p < 0.001). These included losing > 5 kg (9.8% vs. 14.4%, p < 0.001), and reducing sitting time by an hour (29.5% vs. 39.1%, p < 0.001) following diagnosis. However, women with OA also made negative lifestyle changes (35% vs. 29%, p < 0.001), for example, gaining > 5 kg around the time of diagnosis (21.4% vs. 14.5%, p < 0.001) and increasing sitting time by an hour following diagnosis (38.4% vs. 32.3%, p = 0.003). More women with OA also started smoking following diagnosis (8.9% vs. 0.8%, p < 0.001). While some women made positive changes in lifestyle behaviours during and following OA diagnosis, others made negative changes. Consistent support from clinicians for managing OA symptoms may enable patients to make more positive changes in lifestyle behaviours.