Keyword search (4,163 papers available)

"CLSA" Keyword-tagged Publications:

Title Authors PubMed ID
1 Age- and sex-specific associations between obstructive sleep apnea risk and cognitive decline in middle-aged and older adults: A 3-year longitudinal analysis of the Canadian longitudinal study on aging Julie Legault 37832163
HKAP
2 Does social connection mediate the association between neuroticism and cognition? Cross-sectional analysis of the Canadian Longitudinal Study on Aging Bethell J; Andrew MK; Hothi S; Mick P; Morgan D; O' Connell ME; Phillips NA; Stewart S; Walker JD; Wittich W; McGilton KS; 37667914
CRDH
3 A Cluster Analysis of Oral and Cognitive Health Indicators: An Exploratory Study on Cholinergic Activity as the Link Rohani K; Nicolau B; Madathil S; Booij L; Jafarpour D; Haricharan PB; Feine J; Alchini R; Tamimi F; de Souza R; 37608643
PSYCHOLOGY
4 Clustering of Health Behaviors in Canadians: A Multiple Behavior Analysis of Data from the Canadian Longitudinal Study on Aging van Allen Z; Bacon SL; Bernard P; Brown H; Desroches S; Kastner M; Lavoie KL; Marques MM; McCleary N; Straus S; Taljaard M; Thavorn K; Tomasone JR; Presseau J; 37155331
HKAP
5 Hearing loss is associated with gray matter differences in older adults at risk for and with Alzheimer's disease Giroud N; Pichora-Fuller MK; Mick P; Wittich W; Al-Yawer F; Rehan S; Orange JB; Phillips NA; 36911511
CRDH
6 Insomnia disorder increases the risk of subjective memory decline in middle-aged and older adults: a longitudinal analysis of the Canadian Longitudinal Study on Aging Zhao JL; Cross N; Yao CW; Carrier J; Postuma RB; Gosselin N; Kakinami L; Dang-Vu TT; 35877203
PERFORM
7 Clustering of Unhealthy Behaviors: Protocol for a Multiple Behavior Analysis of Data From the Canadian Longitudinal Study on Aging van Allen Z; Bacon SL; Bernard P; Brown H; Desroches S; Kastner M; Lavoie K; Marques M; McCleary N; Straus S; Taljaard M; Thavorn K; Tomasone JR; Presseau J; 34114962
HKAP
8 The Prevalence of Hearing, Vision, and Dual Sensory Loss in Older Canadians: An Analysis of Data from the Canadian Longitudinal Study on Aging. Mick PT, Hämäläinen A, Kolisang L, Pichora-Fuller MK, Phillips N, Guthrie D, Wittich W 32546290
PSYCHOLOGY
9 Association between insomnia disorder and cognitive function in middle-aged and older adults: a cross-sectional analysis of the Canadian Longitudinal Study on Aging Cross NE; Carrier J; Postuma RB; Gosselin N; Kakinami L; Thompson C; Chouchou F; Dang-Vu TT; 31089710
PERFORM

 

Title:Clustering of Health Behaviors in Canadians: A Multiple Behavior Analysis of Data from the Canadian Longitudinal Study on Aging
Authors:van Allen ZBacon SLBernard PBrown HDesroches SKastner MLavoie KLMarques MMMcCleary NStraus STaljaard MThavorn KTomasone JRPresseau J
Link:https://pubmed.ncbi.nlm.nih.gov/37155331/
DOI:10.1093/abm/kaad008
Publication:Annals of behavioral medicine : a publication of the Society of Behavioral Medicine
Keywords:CLSACluster analysisHealth behaviorsMultiple behaviors
PMID:37155331 Category: Date Added:2023-05-08
Dept Affiliation: HKAP

Description:

Background: Health behaviors such as physical inactivity, unhealthy eating, smoking tobacco, and alcohol use are each leading risk factors for non-communicable chronic disease. Better understanding which behaviors tend to co-occur (i.e., cluster together) and co-vary (i.e., are correlated) may provide novel opportunities to develop more comprehensive interventions to promote multiple health behavior change. However, whether co-occurrence or co-variation-based approaches are better suited for this task remains relatively unknown.

Purpose: To compare the utility of co-occurrence vs. co-variation-based approaches for understanding the interconnectedness between multiple health-impacting behaviors.

Methods: Using baseline and follow-up data (N = 40,268) from the Canadian Longitudinal Study of Aging, we examined the co-occurrence and co-variation of health behaviors. We used cluster analysis to group individuals based on their behavioral tendencies across multiple behaviors and to examine how these clusters are associated with demographic characteristics and health indicators. We compared outputs from cluster analysis to behavioral correlations and compared regression analyses of clusters and individual behaviors predicting future health outcomes.

Results: Seven clusters were identified, with clusters differentiated by six of the seven health behaviors included in the analysis. Sociodemographic characteristics varied across several clusters. Correlations between behaviors were generally small. In regression analyses individual behaviors accounted for more variance in health outcomes than clusters.

Conclusions: Co-occurrence-based approaches may be more suitable for identifying sub-groups for intervention targeting while co-variation approaches are more suitable for building an understanding of the relationships between health behaviors.





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