Cecilia Damiano, Simona Costanzo, Benedetta Marcozzi, Teresa Panzera, Chiara Donfrancesco, Augusto Di Castelnuovo, Cinzia Lo Noce, Sara Magnacca, Federico Triolo, Maria Beatrice Zazzara, Luigi Palmieri, Licia Iacoviello, Graziano Onder, Davide Liborio Vetrano, for the BIO-SIGN Study Investigators
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Latent Class Analysis used to identify homogeneous groups of multimorbid individuals (≥ 2 diseases) with similar underlying disease patterns. Cox regression models used to assess the association of multimorbidity patterns and all-cause mortality (end of follow-up 12/31/2019). Results pooled in a random-effects meta-analysis.</p>\n \n <span>AbstractSection</span>\n Results\n <p>Total samples of 3,695 individuals in CUORE (48% male, mean age 68.8 years [SD 5.6]) and 7,801 in Moli-sani (51% male, mean age 68.2 years [SD 5.4]). In both cohorts, six multimorbidity patterns were identified and named after their overexpressed diseases: <i>hypercholesterolemia; metabolic</i>,<i> depression and cancer; cardiometabolic and respiratory; gastrointestinal</i>,<i> genitourinary and depression; respiratory; unspecific</i> (i.e., no diseases overexpressed). Overall mortality rates were 1.66 per 100 person/years in CUORE and 1.85 per 100 person/years in Moli-sani. Compared to the multimorbidity-free group (< 2 diseases), individuals displaying a <i>cardiometabolic and respiratory</i> pattern showed the highest mortality (pooled HR 2.62, 95% CI 2.15–3.10), followed by <i>unspecific</i> (pooled HR 1.45, 95% CI 1.21–1.68), <i>respiratory</i> (pooled HR 1.33, 95% CI 1.01–1.64) and <i>gastrointestinal</i>,<i> genitourinary and depression</i> (pooled HR 1.33, 95% CI 1.06–1.60).</p>\n \n <span>AbstractSection</span>\n Discussion\n <p>Multimorbidity patterns in older adults are differentially associated to shorter survival.</p>\n \n <span>AbstractSection</span>\n Conclusions\n <p>Their identification may help optimize clinical management by improving risk stratification, allowing for more targeted prevention and intervention strategies.</p>\n \n </div>","PeriodicalId":7720,"journal":{"name":"Aging Clinical and Experimental Research","volume":"37 1","pages":""},"PeriodicalIF":3.4000,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s40520-025-03150-0.pdf","citationCount":"0","resultStr":"{\"title\":\"Multimorbidity patterns and mortality in older adults: a two-cohort pooled analysis\",\"authors\":\"Cecilia Damiano, Simona Costanzo, Benedetta Marcozzi, Teresa Panzera, Chiara Donfrancesco, Augusto Di Castelnuovo, Cinzia Lo Noce, Sara Magnacca, Federico Triolo, Maria Beatrice Zazzara, Luigi Palmieri, Licia Iacoviello, Graziano Onder, Davide Liborio Vetrano, for the BIO-SIGN Study Investigators\",\"doi\":\"10.1007/s40520-025-03150-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n <span>AbstractSection</span>\\n Background\\n <p>Different multimorbidity patterns can affect health trajectories and influence survival.</p>\\n \\n <span>AbstractSection</span>\\n Aims\\n <p>We investigated their association with mortality in two population-based cohorts of older adults.</p>\\n \\n <span>AbstractSection</span>\\n Methods\\n <p>Two Italian cohorts of randomly selected individuals (60–79 years old) from general population: CUORE (baseline 2008–2012) and Moli-sani (baseline 2005–2010). Latent Class Analysis used to identify homogeneous groups of multimorbid individuals (≥ 2 diseases) with similar underlying disease patterns. Cox regression models used to assess the association of multimorbidity patterns and all-cause mortality (end of follow-up 12/31/2019). Results pooled in a random-effects meta-analysis.</p>\\n \\n <span>AbstractSection</span>\\n Results\\n <p>Total samples of 3,695 individuals in CUORE (48% male, mean age 68.8 years [SD 5.6]) and 7,801 in Moli-sani (51% male, mean age 68.2 years [SD 5.4]). In both cohorts, six multimorbidity patterns were identified and named after their overexpressed diseases: <i>hypercholesterolemia; metabolic</i>,<i> depression and cancer; cardiometabolic and respiratory; gastrointestinal</i>,<i> genitourinary and depression; respiratory; unspecific</i> (i.e., no diseases overexpressed). Overall mortality rates were 1.66 per 100 person/years in CUORE and 1.85 per 100 person/years in Moli-sani. 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引用次数: 0
摘要
【摘要】背景不同的多病模式会影响健康轨迹，影响生存。摘要：本研究在两组以人群为基础的老年人队列中调查了它们与死亡率的关系。【摘要】【部分方法】从意大利普通人群中随机选择两组（60-79岁）：CUORE（基线2008-2012）和Moli-sani（基线2005-2010）。潜在分类分析用于识别具有相似基础疾病模式的多病个体（≥2种疾病）的同质组。用于评估多病模式与全因死亡率关联的Cox回归模型（随访结束于2019年12月31日）。结果汇总为随机效应荟萃分析。CUORE患者3695例（男性48%，平均年龄68.8岁[SD 5.6]）， Moli-sani患者7801例（男性51%，平均年龄68.2岁[SD 5.4]）。在这两个队列中，确定了六种多病模式，并以其过度表达的疾病命名：高胆固醇血症；代谢、抑郁和癌症；心脏代谢和呼吸；胃肠道、泌尿生殖系统和抑郁症；呼吸系统;非特异性（即没有疾病过度表达）。CUORE的总死亡率为每100人/年1.66人，Moli-sani为每100人/年1.85人。与无多种疾病组（2种疾病）相比，显示心脏代谢和呼吸模式的个体死亡率最高（总危险度2.62,95% CI 2.15-3.10），其次是非特异性（总危险度1.45,95% CI 1.21-1.68）、呼吸系统（总危险度1.33,95% CI 1.01-1.64）和胃肠道、泌尿生殖系统和抑郁症（总危险度1.33,95% CI 1.06-1.60）。老年人的多病模式与较短的生存期有不同的相关性。结论对其进行识别有助于优化临床管理，改善风险分层，制定更有针对性的预防和干预策略。
Multimorbidity patterns and mortality in older adults: a two-cohort pooled analysis
AbstractSection
Background
Different multimorbidity patterns can affect health trajectories and influence survival.
AbstractSection
Aims
We investigated their association with mortality in two population-based cohorts of older adults.
AbstractSection
Methods
Two Italian cohorts of randomly selected individuals (60–79 years old) from general population: CUORE (baseline 2008–2012) and Moli-sani (baseline 2005–2010). Latent Class Analysis used to identify homogeneous groups of multimorbid individuals (≥ 2 diseases) with similar underlying disease patterns. Cox regression models used to assess the association of multimorbidity patterns and all-cause mortality (end of follow-up 12/31/2019). Results pooled in a random-effects meta-analysis.
AbstractSection
Results
Total samples of 3,695 individuals in CUORE (48% male, mean age 68.8 years [SD 5.6]) and 7,801 in Moli-sani (51% male, mean age 68.2 years [SD 5.4]). In both cohorts, six multimorbidity patterns were identified and named after their overexpressed diseases: hypercholesterolemia; metabolic, depression and cancer; cardiometabolic and respiratory; gastrointestinal, genitourinary and depression; respiratory; unspecific (i.e., no diseases overexpressed). Overall mortality rates were 1.66 per 100 person/years in CUORE and 1.85 per 100 person/years in Moli-sani. Compared to the multimorbidity-free group (< 2 diseases), individuals displaying a cardiometabolic and respiratory pattern showed the highest mortality (pooled HR 2.62, 95% CI 2.15–3.10), followed by unspecific (pooled HR 1.45, 95% CI 1.21–1.68), respiratory (pooled HR 1.33, 95% CI 1.01–1.64) and gastrointestinal, genitourinary and depression (pooled HR 1.33, 95% CI 1.06–1.60).
AbstractSection
Discussion
Multimorbidity patterns in older adults are differentially associated to shorter survival.
AbstractSection
Conclusions
Their identification may help optimize clinical management by improving risk stratification, allowing for more targeted prevention and intervention strategies.
期刊介绍：
Aging clinical and experimental research offers a multidisciplinary forum on the progressing field of gerontology and geriatrics. The areas covered by the journal include: biogerontology, neurosciences, epidemiology, clinical gerontology and geriatric assessment, social, economical and behavioral gerontology. “Aging clinical and experimental research” appears bimonthly and publishes review articles, original papers and case reports.
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