Seasonal variations in acute diverticular disease hospitalisations in New Zealand.

PURPOSE: Seasonal variation of acute diverticular disease is variably reported in observational studies. This study aimed to describe seasonal variation of acute diverticular disease hospital admissions in New Zealand. METHODS: A time series analysis of national diverticular disease hospitalisations from 2000 to 2015 was conducted among adults aged 30 years or over. Monthly counts of acute hospitalisations' primary diagnosis of diverticular disease were decomposed using Census X-11 times series methods. A combined test for the presence of identifiable seasonality was used to determine if overall seasonality was present; thereafter, annual seasonal amplitude was calculated. The mean seasonal amplitude of demographic groups was compared by analysis of variance. RESULTS: Over the 16-year period, 35,582 hospital admissions with acute diverticular disease were included. Seasonality in monthly acute diverticular disease admissions was identified. The mean monthly seasonal component of acute diverticular disease admissions peaked in early-autumn (March) and troughed in early-spring (September). The mean annual seasonal amplitude was 23%, suggesting on average 23% higher acute diverticular disease hospitalisations during early-autumn (March) than in early-spring (September). The results were similar in sensitivity analyses that employed different definitions of diverticular disease. Seasonal variation was less pronounced in patients aged over 80 (p = 0.002). Seasonal variation was significantly greater among Maori than Europeans (p < 0.001) and in more southern regions (p < 0.001). However, seasonal variations were not significantly different by gender. CONCLUSIONS: Acute diverticular disease admissions in New Zealand exhibit seasonal variation with a peak in Autumn (March) and a trough in Spring (September). Significant seasonal variations are associated with ethnicity, age, and region, but not with gender.

Lonely in a crowd: loneliness in New Zealand retirement village residents.

OBJECTIVES: The number of older people choosing to relocate to retirement villages (RVs) is increasing rapidly. This choice is often a way to decrease social isolation while still living independently. Loneliness is a significant health issue and contributes to overall frailty, yet RV resident loneliness is poorly understood. Our aim is to describe the prevalence of loneliness and associated factors in a New Zealand RV population. DESIGN: A resident survey was used to collect demographics, social engagement, loneliness, and function, as well as a comprehensive geriatric assessment (international Resident Assessment Instrument [interRAI]) as part of the "Older People in Retirement Villages Study." SETTING: RVs, Auckland, New Zealand. PARTICIPANTS: Participants included RV residents living in 33 RVs (n = 578). MEASUREMENTS: Two types of recruitment: randomly sampled cohort (n = 217) and volunteer sample (n = 361). Independently associated factors for loneliness were determined through multiple logistic regression with odds ratios (ORs). RESULTS: Of the participants, 420 (72.7%) were female, 353 (61.1%) lived alone, with the mean age of 81.3 years. InterRAI assessment loneliness (yes/no question) was 25.8% (n = 149), and the resident survey found that 37.4% (n = 216) feel lonely sometimes/often/always. Factors independently associated with interRAI loneliness included being widowed (adjusted OR 8.27; 95% confidence interval [CI] 4.15-16.48), being divorced/separated/never married (OR 4.76; 95% CI 2.15-10.54), poor/fair quality of life (OR 3.37; 95% CI 1.43-7.94), moving to an RV to gain more social connections (OR 1.55; 95% CI 0.99-2.43), and depression risk (medium risk: OR 2.58, 95% CI 1.53-4.35; high risk: OR 4.20, 95% CI 1.47-11.95). CONCLUSION: A considerable proportion of older people living in RVs reported feelings of loneliness, particularly those who were without partners, at risk of depression and decreased quality of life and those who had moved into RVs to increase social connections. Early identification of factors for loneliness in RV residents could support interventions to improve quality of life and positively impact RV resident health and well-being.

Predictive factors for entry to long-term residential care in octogenarian Maori and non-Maori in New Zealand, LiLACS NZ cohort.

BACKGROUND: Long-term residential care (LTC) supports the most vulnerable and is increasingly relevant with demographic ageing. This study aims to describe entry to LTC and identify predictive factors for older Maori (indigenous people of New Zealand) and non-Maori. METHODS: LiLACS-NZ cohort project recruited Maori and non-Maori octogenarians resident in a defined geographical area in 2010. This study used multivariable log-binomial regressions to assess factors associated with subsequent entry to LTC including: self-identified ethnicity, demographic characteristics, self-rated health, depressive symptoms and activities of daily living [ADL] as recorded at baseline. LTC entry was identified from: place of residence at LiLACS-NZ interviews, LTC subsidy, needs assessment conducted in LTC, hospital discharge to LTC, and place of death. RESULTS: Of 937 surveyed at baseline (421 Maori, 516 non-Maori), 77 already in LTC were excluded, leaving 860 participants (mean age 82.6 +/- 2.71 years Maori, 84.6 +/- 0.52 years non-Maori). Over a mean follow-up of 4.9 years, 278 (41% of non-Maori, 22% of Maori) entered LTC; of the 582 who did not, 323 (55%) were still living and may yet enter LTC. In a model including both Maori and non-Maori, independent risks factors for LTC entry were: living alone (RR = 1.52, 95%CI:1.15-2.02), self-rated health poor/fair compared to very good/excellent (RR = 1.40, 95%CI:1.12-1.77), depressive symptoms (RR = 1.28, 95%CI:1.05-1.56) and more dependent ADLs (RR = 1.09, 95%CI:1.05-1.13). For non-Maori compared to Maori the RR was 1.77 (95%CI:1.39-2.23). In a Maori-only model, predictive factors were older age and living alone. For non-Maori, factors were dependence in more ADLs and poor/fair self-rated health. CONCLUSIONS: Non-Maori participants (predominantly European) entered LTC at almost twice the rate of Maori. Factors differed between Maori and non-Maori. Potentially, the needs, preferences, expectations and/or values may differ correspondingly. Research with different cultural/ethnic groups is required to determine how these differences should inform service development.

Diverticulosis and nine connective tissue disorders: epidemiological support for an association.

Purpose: An underlying connective tissue disorder (CTD) may predispose to formation of intestinal diverticula. We assess the association of diverticulosis with nine selected CTDs, to inform the pathophysiology of diverticula. Methods: A population-based period-prevalence study. Individuals (3.5 million New Zealand residents born 1901-1986) with a health system record 1999-2016 were grouped into those with a hospital diagnosis of diverticulosis or diverticulitis (ICD-10-AM K57), and those without. Also recorded were any hospital diagnoses of nine selected CTDs. The association of exposure to diverticulosis and each CTD was assessed using logistic regressions adjusted for age, gender, ethnicity and region. Results: In all, 85,958 (2.4%) people had a hospital diagnosis of diverticulosis. Hospitalisation with diverticulosis was highly significantly associated with rectal prolapse (adjusted odds ratio [OR] = 3.9), polycystic kidney disease (OR = 3.8), heritable syndromes (Marfan or Ehlers-Danlos) (OR = 2.4), female genital prolapse (OR = 2.3), non-aortic aneurysm (OR = 2.3), aortic aneurysm (OR = 2.2), inguinal hernia (OR = 1.9) and dislocations of shoulder and other joints (OR = 1.7), but not subarachnoid haemorrhage (OR = 1.0). Conclusion: People with diverticulosis are more likely to have colonic extracellular matrix (ECM)/connective tissue alterations in anatomical areas other than the bowel, suggesting linked ECM/connective tissue pathology. Although biases may exist, the results indicate large-scale integrated studies are needed to investigate underlying genetic pathophysiology of colonic diverticula, together with fundamental biological studies to investigate cellular phenotypes and ECM changes.

Study protocol of a randomised controlled trial to examine the impact of a complex intervention in pre-frail older adults.

BACKGROUND: Frailty is a multidimensional geriatric syndrome associated with functional loss. The Senior Chef (SC, nutrition) and SAYGO (strength and balance exercise) programmes are well accepted among older adults but the impact of each, or a combination of both, on the frailty syndrome in pre-frail older adults is unknown. AIMS: To determine the effectiveness and cost-effectiveness of a complex intervention consisting of the SC and/or SAYGO programmes to prevent progression of frailty in pre-frail older adults. METHODS: A multi-centre randomised controlled assessor-blinded study. The four intervention groups are SC, an 8-week nutrition education and cooking class; SAYGO, a 10-week strength and balance exercise class; SC plus SAYGO, and a social group (Control). Community-dwelling adults aged 75+ (60 + Maori and Pasifika) in New Zealand are recruited through health providers. Participants are not terminally ill or with advanced dementia, and have a score of 1 or 2 on the FRAIL questionnaire. Baseline assessments are completed using standardised questionnaires prior to randomisation. Four follow-up assessments are completed: immediately after intervention, 6, 12 and 24 months post-intervention. The primary outcome is frailty score, secondary outcomes are falls, physical function, quality of life, food intake, physical activity, and sustainability of the strategy. Study outcomes will be analysed using intention-to-treat approach. Cost analyses will be completed to determine if interventions are cost effective relative to the control group. DISCUSSION: This trial is designed to be a real world rigorous assessment of whether the two intervention strategies can prevent progression of frailty in older people. If successful, this will generate valuable information about effectiveness of this nutrition and exercise strategy, and provide insights for their implementation. TRIAL REGISTRATION: Australian and New Zealand Clinical Trials Registry number-ACTRN12614000827639.

Patterns of multi-morbidity and prediction of hospitalisation and all-cause mortality in advanced age.

Background: multi-morbidity is associated with poor outcomes and increased healthcare utilisation. We aim to identify multi-morbidity patterns and associations with potentially inappropriate prescribing (PIP), subsequent hospitalisation and mortality in octogenarians. Methods: life and Living in Advanced Age; a Cohort Study in New Zealand (LiLACS NZ) examined health outcomes of 421 Maori (indigenous to New Zealand), aged 80-90 and 516 non-Maori, aged 85 years in 2010. Presence of 14 chronic conditions was ascertained from self-report, general practice and hospitalisation records and physical assessments. Agglomerative hierarchical cluster analysis identified clusters of participants with co-existing conditions. Multivariate regression models examined the associations between clusters and PIP, 48-month hospitalisations and mortality. Results: six clusters were identified for Maori and non-Maori, respectively. The associations between clusters and outcomes differed between Maori and non-Maori. In Maori, those in the complex multi-morbidity cluster had the highest prevalence of inappropriately prescribed medications and in cluster 'diabetes' (20% of sample) had higher risk of hospitalisation and mortality at 48-month follow-up. In non-Maori, those in the 'depression-arthritis' (17% of the sample) cluster had both highest prevalence of inappropriate medications and risk of hospitalisation and mortality. Conclusions: in octogenarians, hospitalisation and mortality are better predicted by profiles of clusters of conditions rather than the presence or absence of a specific condition. Further research is required to determine if the cluster approach can be used to target patients to optimise resource allocation and improve outcomes.

Scared behind the wheel: what impact does driving anxiety have on the health and well-being of young older adults?

BACKGROUND: Driving anxiety can range from driving reluctance to driving phobia, and 20% of young older adults experience mild driving anxiety, whereas 6% report moderate to severe driving anxiety. However, we do not know what impact driving anxiety has on health and well-being, especially among older drivers. This is problematic because there is a growing proportion of older adult drivers and a potential for driving anxiety to result in premature driving cessation that can impact on health and mortality. The purpose of the current study was to examine the impact of driving anxiety on young older adults' health and well-being. METHOD: Data were taken from a longitudinal study of health and aging that included 2,473 young older adults aged 55-70 years. The outcome measures were mental and physical health (SF-12) and quality of life (WHOQOL-8). RESULTS: Hierarchical multiple regression analyses demonstrated that driving anxiety was associated with poorer mental health, physical health, and quality of life, over and above the effect of socio-demographic variables. Sex moderated the effect of driving anxiety on mental health and quality of life in that, as driving anxiety increased, men and women were more likely to have lower mental health and quality of life, but women were more likely to have higher scores compared to men. CONCLUSION: Further research is needed to investigate whether driving anxiety contributes to premature driving cessation. If so, self-regulation of driving and treating driving anxiety could be important in preventing or reducing the declines in health and quality of life associated with driving cessation for older adults affected by driving anxiety.

Exome-wide analysis of rare coding variation identifies novel associations with COPD and airflow limitation in MOCS3, IFIT3 and SERPINA12.

BACKGROUND: Several regions of the genome have shown to be associated with COPD in genome-wide association studies of common variants. OBJECTIVE: To determine rare and potentially functional single nucleotide polymorphisms (SNPs) associated with the risk of COPD and severity of airflow limitation. METHODS: 3226 current or former smokers of European ancestry with lung function measures indicative of Global Initiative for Chronic Obstructive Lung Disease (GOLD) 2 COPD or worse were genotyped using an exome array. An analysis of risk of COPD was carried out using ever smoking controls (n=4784). Associations with %predicted FEV1 were tested in cases. We followed-up signals of interest (p<10(-5)) in independent samples from a subset of the UK Biobank population and also undertook a more powerful discovery study by meta-analysing the exome array data and UK Biobank data for variants represented on both arrays. RESULTS: Among the associated variants were two in regions previously unreported for COPD; a low frequency non-synonymous SNP in MOCS3 (rs7269297, pdiscovery=3.08×10(-6), preplication=0.019) and a rare SNP in IFIT3, which emerged in the meta-analysis (rs140549288, pmeta=8.56×10(-6)). In the meta-analysis of % predicted FEV1 in cases, the strongest association was shown for a splice variant in a previously unreported region, SERPINA12 (rs140198372, pmeta=5.72×10(-6)). We also confirmed previously reported associations with COPD risk at MMP12, HHIP, GPR126 and CHRNA5. No associations in novel regions reached a stringent exome-wide significance threshold (p<3.7×10(-7)). CONCLUSIONS: This study identified several associations with the risk of COPD and severity of airflow limitation, including novel regions MOCS3, IFIT3 and SERPINA12, which warrant further study.

Hospitalisation of older people before and after long-term care entry in Auckland, New Zealand.

INTRODUCTION: global population projections forecast large growth in demand for long-term care (LTC) and acute hospital services for older people. Few studies report changes in hospitalisation rates before and after entry into LTC. This study compares hospitalisation rates 1 year before and after LTC entry. METHODS: the Older Persons' Ability Level (OPAL) study was a 2008 census-type survey of LTC facilities in Auckland, New Zealand. OPAL resident hospital admissions and deaths were obtained from routinely collected national databases. RESULTS: all 2,244 residents (66% = female) who entered LTC within 12 months prior to OPAL were included. There were 3,363 hospitalisations, 2,424 in 12 months before and 939 in 12 months after entry, and 364 deaths. In the 6 to 12 months before LTC entry, the hospitalisation rate/100 person-years was 67.3 (95% confidence interval [CI] 62.5-72.1). Weekly rates then rose steeply to over 450/100 person-years in the 6 months immediately before LTC entry. In the 6 months after LTC entry, the rate fell to 49.1 (CI 44.9-53.3; RR 0.73 (CI 0.65-0.82, P < 0.0001)) and decreased further 6 to 12 months after entry to 41.1 (CI 37.1-45.1; rate ratio [RR] 0.61 (CI 0.54-0.69, P < 0.0001)). CONCLUSIONS: increased hospitalisations a few months before LTC entry suggest functional and medical instability precipitates LTC entry. New residents utilise hospital beds less frequently than when at home before that unstable period. Further research is needed to determine effective interventions to avoid some hospitalisations and possibly also LTC entry.

The 'Big Five'. Hypothesis generation: a multidisciplinary intervention package reduces disease-specific hospitalisations from long-term care: a post hoc analysis of the ARCHUS cluster-randomised controlled trial.

INTRODUCTION: long-term care (LTC) residents have higher hospitalisation rates than non-LTC residents. Rapid decline may follow hospitalisations, hence the importance of preventing unnecessary hospitalisations. Literature describes diagnosis-specific interventions (for cardiac failure, ischaemic heart disease, chronic obstructive pulmonary disease, stroke, pneumonia-termed 'big five' diagnoses), impacting on hospitalisations of older community-dwellers, but few RCTs show reductions in acute admissions from LTC. METHODS: LTC facilities with higher than expected hospitalisations were recruited for a cluster-randomised controlled trial (RCT) of facility-based complex, non-disease-specific, 9-month intervention comprising gerontology nurse specialist (GNS)-led staff education, facility benchmarking, GNS resident review and multidisciplinary discussion of residents selected using standard criteria. In this post hoc exploratory analysis, the outcome was acute hospitalisations for 'big five' diagnoses. Re-randomisation analyses were used for end points during months 1-14. For end points during months 4-14, proportional hazards models are adjusted for within-facility clustering. RESULTS: we recruited 36 facilities with 1,998 residents (1,408 female; mean age 82.9 years); 1,924 were alive at 3 months. The intervention did not impact overall rates of acute hospitalisations or mortality (previously published), but resulted in fewer 'big five' admissions (RR = 0.73, 95% CI = 0.54-0.99; P = 0.043) with no significant difference in the rate of other acute admissions. When considering events occurring after 3 months (only), the intervention group were 34.7% (HR = 0.65; 95% CI = 0.49-0.88; P = 0.005) less likely to have a 'big five' acute admission than controls, with no differences in likelihood of acute admissions for other diagnoses (P = 0.96). CONCLUSIONS: this generic intervention may reduce admissions for common conditions which the literature shows are impacted by disease-specific admission reduction strategies.

Falls risk assessment for hospitalised older adults: a combination of motion data and vital signs.

Health monitoring systems have rapidly evolved during the past two decades and have the potential to change the way healthcare is currently delivered. Currently hospital falls are a major healthcare concern worldwide because of the ageing population. Current observational data and vital signs give the critical information related to the patient's physiology, and motion data provide an additional tool in falls risk assessment. These data combined with the patient's medical history potentially may give the interpretation model high information accessibility to predict falls risk. This study aims to develop a robust falls risk assessment system, in order to avoid falls and its related long-term disabilities in hospitals especially among older adults. The proposed system employs real-time vital signs, motion data, falls history and other clinical information. The falls risk assessment model has been tested and evaluated with 30 patients. The results of the proposed system have been compared with and evaluated against the hospital's falls scoring scale.

Genome-wide protein QTL mapping identifies human plasma kallikrein as a post-translational regulator of serum uPAR levels.

The soluble cleaved urokinase plasminogen activator receptor (scuPAR) is a circulating protein detected in multiple diseases, including various cancers, cardiovascular disease, and kidney disease, where elevated levels of scuPAR have been associated with worsening prognosis and increased disease aggressiveness. We aimed to identify novel genetic and biomolecular mechanisms regulating scuPAR levels. Elevated serum scuPAR levels were identified in asthma (n=514) and chronic obstructive pulmonary disease (COPD; n=219) cohorts when compared to controls (n=96). In these cohorts, a genome-wide association study of serum scuPAR levels identified a human plasma kallikrein gene (KLKB1) promoter polymorphism (rs4253238) associated with serum scuPAR levels in a control/asthma population (P=1.17 × 10(-7)), which was also observed in a COPD population (combined P=5.04 × 10(-12)). Using a fluorescent assay, we demonstrated that serum KLKB1 enzymatic activity was driven by rs4253238 and is inverse to scuPAR levels. Biochemical analysis identified that KLKB1 cleaves scuPAR and negates scuPAR's effects on primary human bronchial epithelial cells (HBECs) in vitro. Chymotrypsin was used as a proproteolytic control, while basal HBECs were used as a control to define scuPAR-driven effects. In summary, we reveal a novel post-translational regulatory mechanism for scuPAR using a hypothesis-free approach with implications for multiple human diseases.

Progress towards predicting 1-year mortality in older people living in residential long-term care.

BACKGROUND: frail older people living in residential long-term care (LTC) have limited life expectancy. Identifying those with poor prognosis may improve management and facilitate transition to a palliative approach to care. OBJECTIVE: to develop methods for predicting mortality in LTC. DESIGN: a population-based cohort study. SETTING: LTC facilities, Auckland, New Zealand. SUBJECTS: five hundred randomly selected older people in a census-type survey of those living in LTC in 2008. METHODS: mortality data were obtained from New Zealand Ministry of Health. Two methods for assessing mortality risk were developed using demographic, functional and health service information: (i) two geriatricians blinded to identifying data and to mortality, independently reviewed survey, medications and pre-survey hospitalisations data, and grouped residents according to perceived risk of death within 12 months; (ii) multivariate logistic regression model used the same survey and medication items as the geriatricians. RESULTS: for the geriatricians' assessment, each quintile of perceived risk was associated with a significant increase in mortality (P < 0.001). Area under the curve (AUC) for both physicians was 0.64. The logistic regression model included age, gender, assistance with feeding and requiring night attention, all variables which are easily available from LTC records. AUC for the model was 0.70, but when validated against the entire OPAL cohort, it was 0.65. When either or both geriatrician and the model together predicted high risk of death, 1-year mortality was >50%. CONCLUSION: two methods with the potential to identify older people with limited prognosis are described. Use of these methods allowed identification of over half of those who died within 12 months.

Selecting long-term care facilities with high use of acute hospitalisations: issues and options.

BACKGROUND: This paper considers approaches to the question "Which long-term care facilities have residents with high use of acute hospitalisations?" It compares four methods of identifying long-term care facilities with high use of acute hospitalisations by demonstrating four selection methods, identifies key factors to be resolved when deciding which methods to employ, and discusses their appropriateness for different research questions. METHODS: OPAL was a census-type survey of aged care facilities and residents in Auckland, New Zealand, in 2008. It collected information about facility management and resident demographics, needs and care. Survey records (149 aged care facilities, 6271 residents) were linked to hospital and mortality records routinely assembled by health authorities. The main ranking endpoint was acute hospitalisations for diagnoses that were classified as potentially avoidable. Facilities were ranked using 1) simple event counts per person, 2) event rates per year of resident follow-up, 3) statistical model of rates using four predictors, and 4) change in ranks between methods 2) and 3). A generalized mixed model was used for Method 3 to handle the clustered nature of the data. RESULTS: 3048 potentially avoidable hospitalisations were observed during 22 months' follow-up. The same "top ten" facilities were selected by Methods 1 and 2. The statistical model (Method 3), predicting rates from resident and facility characteristics, ranked facilities differently than these two simple methods. The change-in-ranks method identified a very different set of "top ten" facilities. All methods showed a continuum of use, with no clear distinction between facilities with higher use. CONCLUSION: Choice of selection method should depend upon the purpose of selection. To monitor performance during a period of change, a recent simple rate, count per resident, or even count per bed, may suffice. To find high-use facilities regardless of resident needs, recent history of admissions is highly predictive. To target a few high-use facilities that have high rates after considering facility and resident characteristics, model residuals or a large increase in rank may be preferable.

The Association between Frailty, Quality of Life and Resilience in Community-dwelling Retirement Village Residents.

OBJECTIVES: Housing quality has significant impact on the wider determinants of health and quality of life (QoL). Retirement villages are considered age-friendly accommodation for community-dwelling older people, offering a variable range of services and supports. We wished to explore the relationship among frailty, QoL, and resilience in older people residing in retirement villages. DESIGN: Cross-sectional analysis within a longitudinal study. SETTING AND PARTICIPANTS: Residents from 33 retirement villages in Auckland, Aotearoa, New Zealand. METHODS: Frailty [using an interRAI-Community Health Assessment-based frailty index FI)], QoL [World Health Organization Quality of Life-Brief Version (WHOQOL-BREF) and WHOQOL-Older Adults Module (WHOQOL-OLD)], and resilience [Brief Resilience Scale (BRS)]. Associations among frailty, QoL, and resilience were examined using regression analysis adjusting for confounders. RESULTS: Mean (SD): FI 0.2 (0.1) in 479 residents, BRS 3.7 (0.8) in 395 residents, WHOQOL-OLD total score 69.9 (12.2). FI was inversely related to BRS [adjusted mean difference (MD) -0.35; 95% CI -0.43 to -0.26; P < .001] and WHOQOL-OLD (MD, -5.45; 95% CI -6.89 to 4.01; P < .001). FI inverse relationship was seen across all facets of WHOQOL-OLD and all WHOQOL-BREF facets except psychological. CONCLUSIONS AND IMPLICATIONS: Frailty was inversely related to resilience and multiple domains of QoL in those living in presumed age-friendly and relatively resource-rich environments. Studies exploring causal relationships between these facets could inform interventions necessary to improve QoL and resilience in those living with frailty. Specific multidimensional needs, wishes, and concerns of older people living with frailty needs to be explored in order to potentially intervene on frailty, QoL, and resilience.

Opportunities to be active in retirement villages and factors associated with physical activity in residents.

Introduction Physical activity (PA) in older people is associated with improved morbidity and mortality outcomes. Increasing numbers of older people are choosing to live in retirement villages, many of which promote themselves as providing opportunities for activity. Aim To explore the characteristics of PA village residents were undertaking and the associated individual and village factors. Methods Health, functional and wellbeing information was collected from 577 residents recruited from 34 villages in Auckland, New Zealand, using an International Resident Assessment Instrument and customised survey tools containing items on self-reported PA. Managers from villages completed a survey on village characteristics and facilities. Results The mean age (s.d.) of village residents was 82 (7) years, and 325 (56%) reporting doing one or more hours of PA in the 3 days prior to assessment. Moderate exercise was performed by 240 (42%) village residents, for a mean (s.d.) of 2.7 (3.4) h per week. The most common activities provided by villages included: bowls/petanque (22, 65%) and exercise classes (22, 65%), and walking was the most common activity undertaken (348, 60%). Factors independently associated with PA included individual factors (gender, fatigue, constipation, self-reported health, number of medications, moving to village for safety and security, utilising village fitness programme, use of the internet, and satisfaction with opportunities to be active) and village-related factors (access to unit, and ownership model). Discussion PA uptake is determined by many factors at both personal (physical and psychosocial) and environmental levels. Clinicians should focus on individualised PA promotion in those with identified risk factors for low levels of PA.

Changes in hospitalisation rates in older people before and after moving to a retirement village.

OBJECTIVES: An increasing proportion of older people live in Retirement Villages ('villages'). This population cites support for health-care issues as one reason for relocation to villages. Here, we examine whether relocation to villages is associated with a decline in hospitalisations. METHODS: Retrospective, before-and-after observational study. SETTING: Retirement villages, Auckland, New Zealand. PARTICIPANTS: 466 cognitively intact village residents (336 [72%] female); mean (SD) age at moving to village was 73.9 (7.7) years. Segmented linear regression analysis of an interrupted time-series design was used. MAIN OUTCOME MEASURES: all hospitalisations for 18 months pre- and postrelocation to village. SECONDARY OUTCOME: acute hospitalisations during the same time periods. RESULTS: The average hospitalisation rate (per 100 person-years) was 44.9 (95% confidence interval [CI] = 36.3-55.6) 18-10 months before village relocation, 58.9 (95% CI = 48.3-72.0) 9-1 months before moving, 47.9 (95% CI = 38.8-59.1) 1-9 months after moving and 62.4 (95% CI = 51.2-76.0) 10-18 months after moving. Monthly average hospitalisation rate (per 100 person-years) increased before relocation to village by an average of 1.2 (95% CI = 0.01-1.57, p = .04) per month from 18 to 1 month before moving, and there was a change in the level of the monthly average hospitalisation rate immediately after relocation (mean difference [MD] = -18.4 per 100 person-years, 95% CI = -32.8 to -4.1, p = .02). The trend change after village relocation did not differ significantly from that before moving. CONCLUSIONS: Although we cannot reliably claim causality, relocation to a retirement village is, for older people, associated with a significant but non-sustained reduction in hospitalisation.

Goal setting as a feature of homecare services for older people: does it make a difference?

INTRODUCTION: Health services delivered in an older person's home are often implemented at a critical juncture in an individual's functional status. Although homecare has potential to improve this situation, it often focuses on treating disease and 'taking care' of the patient rather than promoting independence. The aim of restorative homecare is to change the philosophy from one where delivery of care may create dependency to provision of care which maximises independence, self-esteem, self-image and quality of life, and reduces the care required. AIMS: To assess impact of a designated goal facilitation tool on health-related quality of life (HRQoL), social support and physical function among community-dwelling older people referred for homecare. METHODS: A total of 205 participants [mean age 79.1 years, 71.3% female (intervention group) and 76.9 years with 60.8% female (control group)] were cluster randomised to an intervention or control assessor. The intervention arm involved participants completing a goal facilitation tool with assessors. This established rehabilitation aims. Control participants received a standard needs assessment. Clients from both groups were then referred to a homecare organisation for service delivery. RESULTS: There was greater change over time in HRQoL [measured by Short Form 36 Survey (SF-36)] in the intervention group (P = 0.0001). There was a marked variation across homecare providers in types of services provided (P < 0.001). Identification of a goal did not predict completion of a formalised review of participants' needs by the homecare organisation. CONCLUSIONS: Use of a goal facilitation tool in assessment of an older person's needs on referral for homecare leads to significant improvements in HRQoL. This may be through a higher proportion of individualised activities tailored to a successful identification of the person's goals. The findings contribute to greater understanding of factors necessary to implement improvements in homecare services for older people.

Aged Residential Care Health Utilisation Study (ARCHUS): a randomised controlled trial to reduce acute hospitalisations from residential aged care.

BACKGROUND: For residents of long term care, hospitalisations can cause distress and disruption, and often result in further medical complications. Multi-disciplinary team interventions have been shown to improve the health of Residential Aged Care (RAC) residents, decreasing the need for acute hospitalisation, yet there are few randomised controlled trials of these complex interventions. This paper describes a randomised controlled trial of a structured multi-disciplinary team and gerontology nurse specialist (GNS) intervention aiming to reduce residents' avoidable hospitalisations. METHODS/DESIGN: This Aged Residential Care Healthcare Utilisation Study (ARCHUS) is a cluster- randomised controlled trial (n = 1700 residents) of a complex multi-disciplinary team intervention in long-term care facilities. Eligible facilities certified for residential care were selected from those identified as at moderate or higher risk of resident potentially avoidable hospitalisations by statistical modelling. The facilities were all located in the Auckland region, New Zealand and were stratified by District Health Board (DHB). INTERVENTION: The intervention provided a structured GNS intervention including a baseline facility needs assessment, quality indicator benchmarking, a staff education programme and care coordination. Alongside this, three multi-disciplinary team (MDT) meetings were held involving a geriatrician, facility GP, pharmacist, GNS and senior nursing staff. OUTCOMES: Hospitalisations are recorded from routinely-collected acute admissions during the 9-month intervention period followed by a 5-month follow-up period. ICD diagnosis codes are used in a pre-specified definition of potentially reducible admissions. DISCUSSION: This randomised-controlled trial will evaluate a complex intervention to increase early identification and intervention to improve the health of residents of long term care. The results of this trial are expected in early 2013. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry: ACTRN 12611000187943.