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Chronic pain is common in older people. However, little is known about how pain is experienced in residents of retirement villages ('villages'), and how pain intensity and associations are experienced in relation to characteristics of residents and village living. We thus aimed to examine pain levels, prevalence and associated factors in village residents. The current paper is a cross‐sectional analysis of baseline data from the 'Older People in Retirement Villages' study in Auckland, New Zealand. Between July 2016 and August 2018, 578 village residents were interviewed face‐to‐face by gerontology nurse specialists, using interRAI Community Health Assessment (CHA) and customised survey. We used a validated pain scale and multivariable logistic regression analyses adjusted for pre‐specified confounders. Residents' median age was 82 years; 420 (73%) were female; 270 (47%) exhibited/reported daily pain, and in 11% this was severe. After controlling for confounders, daily pain was positively associated with self‐reported arthritis (OR = 3.88, 95% CI = 2.57–5.87), poor/fair self‐reported health (OR = 3.19, 95% CI = 1.29–7.93), having no health clinic on‐site (OR = 1.76, 95% CI = 1.10–2.83), and minimal fatigue (diminished energy but completes normal day‐to‐day activities) (OR = 1.77, 95% CI = 1.11–2.81). Similar associations were observed for levels of pain. We conclude that levels of pain and prevalence of daily pain are high in village residents. Self‐reported arthritis, self‐reported poor/fair health, no health clinic on‐site and minimal fatigue are all independently associated with a higher risk of daily pain and with levels of pain. This study suggests potential opportunities for villages to better provide on‐site support to decrease prevalence and severity of pain for their residents, and thus potentially increase wellbeing and quality‐of‐life, though as we cannot prove causality, more research is needed. [ABSTRACT FROM AUTHOR]

This paper considers the support networks of older people in populations with a preponderance of multigenerational households and examines the most vulnerable network types in terms of loneliness and isolation. Current common typologies of support networks may not be sensitive to differences within and between different cultures. This paper uses cross-sectional data drawn from 590 elders (Gujaratis, Punjabis and Sylhetis) living in the United Kingdom and South Asia. Six variables were used in K-means cluster analysis to establish a new network typology. Two logistic regression models using loneliness and isolation as dependent variables assessed the contribution of the new network type to wellbeing. Four support networks were identified: ‘Multigenerational Households: Older Integrated Networks’, ‘Multigenerational Households: Younger Family Networks’, ‘Family and Friends Integrated Networks’ and ‘Non-kin Restricted Networks’. Older South Asians with ‘Non-kin Restricted Networks’ were more likely to be lonely and isolated compared to others. Using network typologies developed with individualistically oriented cultures, distributions are skewed towards more robust network types and could underestimate the support needs of older people from familistic cultures, who may be isolated and lonely and with limited informal sources of help. The new typology identifies different network types within multigenerational households, identifies a greater proportion of older people with vulnerable networks and could positively contribute to service planning. [ABSTRACT FROM PUBLISHER]

This paper considers the support networks of older people in populations with a preponderance of multigenerational households and examines the most vulnerable network types in terms of loneliness and isolation. Current common typologies of support networks may not be sensitive to differences within and between different cultures. This paper uses cross-sectional data drawn from 590 elders (Gujaratis, Punjabis and Sylhetis) living in the United Kingdom and South Asia. Six variables were used in K-means cluster analysis to establish a new network typology. Two logistic regression models using loneliness and isolation as dependent variables assessed the contribution of the new network type to wellbeing. Four support networks were identified: ‘Multigenerational Households: Older Integrated Networks’, ‘Multigenerational Households: Younger Family Networks’, ‘Family and Friends Integrated Networks’ and ‘Non-kin Restricted Networks’. Older South Asians with ‘Non-kin Restricted Networks’ were more likely to be lonely and isolated compared to others. Using network typologies developed with individualistically oriented cultures, distributions are skewed towards more robust network types and could underestimate the support needs of older people from familistic cultures, who may be isolated and lonely and with limited informal sources of help. The new typology identifies different network types within multigenerational households, identifies a greater proportion of older people with vulnerable networks and could positively contribute to service planning. [ABSTRACT FROM AUTHOR]