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dc.contributor.authorLópez-Cepero, Andrea A
dc.contributor.authorMcClain, Amanda C.
dc.contributor.authorRosal, Milagros C
dc.contributor.authorTucker, Katherine L.
dc.contributor.authorMattei, Josiemer
dc.date2022-08-11T08:08:28.000
dc.date.accessioned2022-08-23T15:56:28Z
dc.date.available2022-08-23T15:56:28Z
dc.date.issued2022-01-01
dc.date.submitted2022-02-08
dc.identifier.citation<p>López-Cepero A, McClain AC, Rosal MC, Tucker KL, Mattei J. Examination of the Allostatic Load Construct and Its Longitudinal Association With Health Outcomes in the Boston Puerto Rican Health Study. Psychosom Med. 2022 Jan 1;84(1):104-115. doi: 10.1097/PSY.0000000000001013. PMID: 34581702; PMCID: PMC8678200. <a href="https://doi.org/10.1097/PSY.0000000000001013">Link to article on publisher's site</a></p>
dc.identifier.issn0033-3174 (Linking)
dc.identifier.doi10.1097/PSY.0000000000001013
dc.identifier.pmid34581702
dc.identifier.urihttp://hdl.handle.net/20.500.14038/29975
dc.description.abstractOBJECTIVE: Despite evidence on allostatic load (AL) as a model explaining associations between stress and disease, there is no consensus on its operationalization. This study aimed to contrast various AL constructs and their longitudinal associations with disease and disability. METHODS: Baseline and 5-year follow-up data from 738 adults participating in the Boston Puerto Rican Health Study were used. Five AL scores were created by summing the presence of 21 dysregulated multisystem physiological parameters using the following: a) z scores, b) population-based quartile cutoffs, c) clinical-based cutoffs, d) 10 preselected clinical-based cutoffs (AL-reduced), and e) 12 clinical-based cutoffs selected a posteriori based on association with disease (AL-select). Adjusted logistic regression models examined associations between each AL score at baseline and 5-year incident type 2 diabetes (T2D), cardiovascular disease (CVD), activities (or instrumental activities) of daily living (ADL; IADL) for physical impairment, and cognitive impairment. RESULTS: AL-quartile was associated with greater odds of T2D (odds ratio [OR] = 1.20; 95% confidence interval [CI] = 1.07-1.35) and CVD (OR = 1.14; 95% CI = 1.06-1.22). AL-reduced was associated with higher odds of IADL (OR = 1.21; 95% CI = 1.07-1.37) and AL-clinical with CVD (OR = 1.14; 95% CI = 1.07-1.21), IADL (OR = 1.11; 95% CI = 1.04-1.19), and ADL (OR = 1.15; 95% CI = 1.04-1.26). AL-select showed associations with T2D (OR = 1.35; 95% CI = 1.14-1.61), CVD (OR = 1.21; 95% CI = 1.11-1.32), IADL (OR = 1.15; 95% CI = 1.04-1.26), and ADL (OR = 1.24; 95% CI = 1.08-1.41). No associations were found with AL z-score. CONCLUSIONS: AL scores computed with clinical-based cutoffs performed robustly in our sample of mainland Puerto Ricans, whereas z scores did not predict disease and disability. AL-select was the most consistent predictor, supporting its use as a disease-predicting model. Future assessment of AL-select in other populations may help operationalize AL.
dc.language.isoen_US
dc.relation<p><a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&list_uids=34581702&dopt=Abstract">Link to Article in PubMed</a></p>
dc.relation.urlhttps://doi.org/10.1097/psy.0000000000001013
dc.subjectUMCCTS funding
dc.subjectDiseases
dc.subjectPsychiatry and Psychology
dc.subjectPublic Health
dc.subjectRace and Ethnicity
dc.titleExamination of the Allostatic Load Construct and Its Longitudinal Association With Health Outcomes in the Boston Puerto Rican Health Study
dc.typeJournal Article
dc.source.journaltitlePsychosomatic medicine
dc.source.volume84
dc.source.issue1
dc.identifier.legacyfulltexthttps://escholarship.umassmed.edu/cgi/viewcontent.cgi?article=3210&amp;context=faculty_pubs&amp;unstamped=1
dc.identifier.legacycoverpagehttps://escholarship.umassmed.edu/faculty_pubs/2177
dc.identifier.contextkey28133374
refterms.dateFOA2022-08-23T15:56:28Z
html.description.abstract<p>OBJECTIVE: Despite evidence on allostatic load (AL) as a model explaining associations between stress and disease, there is no consensus on its operationalization. This study aimed to contrast various AL constructs and their longitudinal associations with disease and disability.</p> <p>METHODS: Baseline and 5-year follow-up data from 738 adults participating in the Boston Puerto Rican Health Study were used. Five AL scores were created by summing the presence of 21 dysregulated multisystem physiological parameters using the following: a) z scores, b) population-based quartile cutoffs, c) clinical-based cutoffs, d) 10 preselected clinical-based cutoffs (AL-reduced), and e) 12 clinical-based cutoffs selected a posteriori based on association with disease (AL-select). Adjusted logistic regression models examined associations between each AL score at baseline and 5-year incident type 2 diabetes (T2D), cardiovascular disease (CVD), activities (or instrumental activities) of daily living (ADL; IADL) for physical impairment, and cognitive impairment.</p> <p>RESULTS: AL-quartile was associated with greater odds of T2D (odds ratio [OR] = 1.20; 95% confidence interval [CI] = 1.07-1.35) and CVD (OR = 1.14; 95% CI = 1.06-1.22). AL-reduced was associated with higher odds of IADL (OR = 1.21; 95% CI = 1.07-1.37) and AL-clinical with CVD (OR = 1.14; 95% CI = 1.07-1.21), IADL (OR = 1.11; 95% CI = 1.04-1.19), and ADL (OR = 1.15; 95% CI = 1.04-1.26). AL-select showed associations with T2D (OR = 1.35; 95% CI = 1.14-1.61), CVD (OR = 1.21; 95% CI = 1.11-1.32), IADL (OR = 1.15; 95% CI = 1.04-1.26), and ADL (OR = 1.24; 95% CI = 1.08-1.41). No associations were found with AL z-score.</p> <p>CONCLUSIONS: AL scores computed with clinical-based cutoffs performed robustly in our sample of mainland Puerto Ricans, whereas z scores did not predict disease and disability. AL-select was the most consistent predictor, supporting its use as a disease-predicting model. Future assessment of AL-select in other populations may help operationalize AL.</p>
dc.identifier.submissionpathfaculty_pubs/2177
dc.contributor.departmentPrevention Research Center
dc.contributor.departmentDepartment of Population and Quantitative Health Sciences
dc.source.pages104-115


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