{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T15:16:33Z","timestamp":1787584593359,"version":"build-2736575974"},"reference-count":25,"publisher":"BMJ","issue":"10","content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":["J Epidemiol Community Health"],"accepted":{"date-parts":[[2022,7,3]]},"published-print":{"date-parts":[[2022,10]]},"abstract":"<jats:sec>\n                  <jats:title>Background<\/jats:title>\n                  <jats:p>Limited evidence exists on how the presence of multiple conditions affects breast cancer (BC) risk.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>We used data from a network hospital-based case\u2013control study conducted in Italy and Switzerland, including 3034 BC cases and 3392 controls. Comorbidity patterns were identified using latent class analysis on a set of specific health conditions\/diseases. A multiple logistic regression model was used to derive ORs and the corresponding 95% CIs for BC according to the patterns, adjusting for several covariates. A second model was fitted including an additional effect of FH on the comorbidity patterns.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>With respect to the \u2018healthy\u2019 pattern, the \u2018metabolic disorders\u2019 one reported an OR of 1.23 (95% CI 1.02 to 1.49) and the \u2018breast diseases\u2019 an OR of 1.86 (95% CI 1.23 to 2.83). The remaining two patterns reported an inverse association with BC, with ORs of 0.77, significant only for the \u2018hysterectomy, uterine fibroids and bilateral ovariectomy\u2019. In the second model, FH was associated with an increased risk of the \u2018breast diseases\u2019 pattern (OR=4.09, 95% CI 2.48 to 6.74). Non-significant increased risk of the other patterns according to FH emerged.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>We identified mutually exclusive patterns of comorbidity, confirming the unfavourable role of those related to metabolic and breast disorders on the risk of BC, and the protective effect of those related to common surgical procedures. FH reported an incremented risk of all the comorbidity patterns.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Impact<\/jats:title>\n                  <jats:p>Identifying clusters of comorbidity in patients with BC may help understand their effects and enable clinicians and policymakers to better organise patient and healthcare management.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1136\/jech-2022-219279","type":"journal-article","created":{"date-parts":[[2022,7,16]],"date-time":"2022-07-16T13:20:14Z","timestamp":1657977614000},"page":"867-872","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":3,"title":["Comorbidity patterns, family history and breast cancer risk: a latent class 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