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Health profile of residents of retirement villages in Auckland, New Zealand: findings from a cross-sectional survey with health assessment.

ABSTRACT: OBJECTIVES:Retirement villages (RV) have expanded rapidly, now housing perhaps one in eight people aged 75+ years in New Zealand. Health service initiatives might better support residents and offer cost advantages, but little is known of resident demographics, health status or needs. This study describes village residents-their demographics, socio-behavioural and health status-noting differences between participants who volunteered and those who were sampled. DESIGN:Cross-sectional study of village residents. The cohort formed will also be used for a longitudinal study and a randomised controlled trial. Village managers (sometimes after consulting residents) decided if representative sampling could be undertaken in each village. Where sampling was not approved, volunteers were sought. SETTING:33 RV were included from a total of 65 villages in Auckland, New Zealand. PARTICIPANTS:Residents (n=578) were recruited either by sampling (n=217) or as volunteers (n=361) during 2016-2018. Each completed a survey and an International Resident Assessment Instrument (interRAI) health needs assessment with a gerontology nurse specialist. RESULTS:Median age of residents was 82 years, 158 (27%) were men; 61% lived alone. Downsizing (77%), less stress (63%) and access to healthcare assistance (61%) were most common reasons for entry. During the 2 weeks prior to survey, 34% received home supports and 10% personal care. Hypertension, heart disease, arthritis and pain were reported by over 40%. Most common unmet needs related to managing cardiorespiratory symptoms (50%) and pain (48%). Volunteers and sampled residents differed significantly, mainly in socio-behavioural respects. CONCLUSIONS:Common conditions including hypertension, arthritis and atrial fibrillation, are recorded in interRAI as text, and thus overlooked in interRAI reports. Levels of unmet need indicate opportunities to improve health services to better manage chronic conditions. Healthcare service providers and village operators could cooperate to design and test service initiatives that better meet residents' needs and offer cost benefits. TRIAL REGISTRATION NUMBER:ACTRN12616000685415.

SUBMITTER: Broad JB

PROVIDER: S-EPMC7511621 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Health profile of residents of retirement villages in Auckland, New Zealand: findings from a cross-sectional survey with health assessment.

Broad Joanna B JB Wu Zhenqiang Z Bloomfield Katherine K Hikaka Joanna J Bramley Dale D Boyd Michal M Tatton Annie A Calvert Cheryl C Peri Kathy K Higgins Ann-Marie AM Connolly Martin J MJ

BMJ open 20200918 9

<h4>Objectives</h4>Retirement villages (RV) have expanded rapidly, now housing perhaps one in eight people aged 75+ years in New Zealand. Health service initiatives might better support residents and offer cost advantages, but little is known of resident demographics, health status or needs. This study describes village residents-their demographics, socio-behavioural and health status-noting differences between participants who volunteered and those who were sampled.<h4>Design</h4>Cross-sectiona ...[more]

PMID: 32948550

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Project description:BackgroundA frailty paradigm would be useful in primary care to identify older people at risk, but appropriate metrics at that level are lacking. We created and validated a simple instrument for frailty screening in Europeans aged ?50. Our study is based on the first wave of the Survey of Health, Ageing and Retirement in Europe (SHARE, http://www.share-project.org), a large population-based survey conducted in 2004-2005 in twelve European countries.MethodsSubjectsSHARE Wave 1 respondents (17,304 females and 13,811 males).Measuresfive SHARE variables approximating Fried's frailty definition. Analyses (for each gender): 1) estimation of a discreet factor (DFactor) model based on the frailty variables using LatentGOLD. A single DFactor with three ordered levels or latent classes (i.e. non-frail, pre-frail and frail) was modelled; 2) the latent classes were characterised against a biopsychosocial range of Wave 1 variables; 3) the prospective mortality risk (unadjusted and age-adjusted) for each frailty class was established on those subjects with known mortality status at Wave 2 (2007-2008) (11,384 females and 9,163 males); 4) two web-based calculators were created for easy retrieval of a subject's frailty class given any five measurements.ResultsFemales: the DFactor model included 15,578 cases (standard R2 = 0.61). All five frailty indicators discriminated well (p < 0.001) between the three classes: non-frail (N = 10,420; 66.9%), pre-frail (N = 4,025; 25.8%), and frail (N = 1,133; 7.3%). Relative to the non-frail class, the age-adjusted Odds Ratio (with 95% Confidence Interval) for mortality at Wave 2 was 2.1 (1.4 - 3.0) in the pre-frail and 4.8 (3.1 - 7.4) in the frail. Males: 12,783 cases (standard R2 = 0.61, all frailty indicators had p < 0.001): non-frail (N = 10,517; 82.3%), pre-frail (N = 1,871; 14.6%), and frail (N = 395; 3.1%); age-adjusted OR (95% CI) for mortality: 3.0 (2.3 - 4.0) in the pre-frail, 6.9 (4.7 - 10.2) in the frail.ConclusionsThe SHARE Frailty Instrument has sufficient construct and predictive validity, and is readily and freely accessible via web calculators. To our knowledge, SHARE-FI represents the first European research effort towards a common frailty language at the community level.

Dataset Information

Health profile of residents of retirement villages in Auckland, New Zealand: findings from a cross-sectional survey with health assessment.

Publications

Health profile of residents of retirement villages in Auckland, New Zealand: findings from a cross-sectional survey with health assessment.

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