@article {6811, title = {Association of Cardiometabolic Multimorbidity With Mortality.}, journal = {JAMA}, volume = {314}, year = {2015}, month = {2015 Jul 7}, pages = {52-60}, abstract = {

IMPORTANCE: The prevalence of cardiometabolic multimorbidity is increasing.

OBJECTIVE: To estimate reductions in life expectancy associated with cardiometabolic multimorbidity.

DESIGN, SETTING, AND PARTICIPANTS: Age- and sex-adjusted mortality rates and hazard ratios (HRs) were calculated using individual participant data from the Emerging Risk Factors Collaboration (689,300 participants; 91 cohorts; years of baseline surveys: 1960-2007; latest mortality follow-up: April 2013; 128,843 deaths). The HRs from the Emerging Risk Factors Collaboration were compared with those from the UK Biobank (499,808 participants; years of baseline surveys: 2006-2010; latest mortality follow-up: November 2013; 7995 deaths). Cumulative survival was estimated by applying calculated age-specific HRs for mortality to contemporary US age-specific death rates.

EXPOSURES: A history of 2 or more of the following: diabetes mellitus, stroke, myocardial infarction (MI).

MAIN OUTCOMES AND MEASURES: All-cause mortality and estimated reductions in life expectancy.

RESULTS: In participants in the Emerging Risk Factors Collaboration without a history of diabetes, stroke, or MI at baseline (reference group), the all-cause mortality rate adjusted to the age of 60 years was 6.8 per 1000 person-years. Mortality rates per 1000 person-years were 15.6 in participants with a history of diabetes, 16.1 in those with stroke, 16.8 in those with MI, 32.0 in those with both diabetes and MI, 32.5 in those with both diabetes and stroke, 32.8 in those with both stroke and MI, and 59.5 in those with diabetes, stroke, and MI. Compared with the reference group, the HRs for all-cause mortality were 1.9 (95\% CI, 1.8-2.0) in participants with a history of diabetes, 2.1 (95\% CI, 2.0-2.2) in those with stroke, 2.0 (95\% CI, 1.9-2.2) in those with MI, 3.7 (95\% CI, 3.3-4.1) in those with both diabetes and MI, 3.8 (95\% CI, 3.5-4.2) in those with both diabetes and stroke, 3.5 (95\% CI, 3.1-4.0) in those with both stroke and MI, and 6.9 (95\% CI, 5.7-8.3) in those with diabetes, stroke, and MI. The HRs from the Emerging Risk Factors Collaboration were similar to those from the more recently recruited UK Biobank. The HRs were little changed after further adjustment for markers of established intermediate pathways (eg, levels of lipids and blood pressure) and lifestyle factors (eg, smoking, diet). At the age of 60 years, a history of any 2 of these conditions was associated with 12 years of reduced life expectancy and a history of all 3 of these conditions was associated with 15 years of reduced life expectancy.

CONCLUSIONS AND RELEVANCE: Mortality associated with a history of diabetes, stroke, or MI was similar for each condition. Because any combination of these conditions was associated with multiplicative mortality risk, life expectancy was substantially lower in people with multimorbidity.

}, keywords = {Adult, Aged, Comorbidity, Diabetes Mellitus, Female, Humans, Life Expectancy, Male, Middle Aged, Mortality, Myocardial Infarction, Risk Factors, Stroke}, issn = {1538-3598}, doi = {10.1001/jama.2015.7008}, author = {Di Angelantonio, Emanuele and Kaptoge, Stephen and Wormser, David and Willeit, Peter and Butterworth, Adam S and Bansal, Narinder and O{\textquoteright}Keeffe, Linda M and Gao, Pei and Wood, Angela M and Burgess, Stephen and Freitag, Daniel F and Pennells, Lisa and Peters, Sanne A and Hart, Carole L and H{\r a}heim, Lise Lund and Gillum, Richard F and Nordestgaard, B{\o}rge G and Psaty, Bruce M and Yeap, Bu B and Knuiman, Matthew W and Nietert, Paul J and Kauhanen, Jussi and Salonen, Jukka T and Kuller, Lewis H and Simons, Leon A and van der Schouw, Yvonne T and Barrett-Connor, Elizabeth and Selmer, Randi and Crespo, Carlos J and Rodriguez, Beatriz and Verschuren, W M Monique and Salomaa, Veikko and Sv{\"a}rdsudd, Kurt and van der Harst, Pim and Bj{\"o}rkelund, Cecilia and Wilhelmsen, Lars and Wallace, Robert B and Brenner, Hermann and Amouyel, Philippe and Barr, Elizabeth L M and Iso, Hiroyasu and Onat, Altan and Trevisan, Maurizio and D{\textquoteright}Agostino, Ralph B and Cooper, Cyrus and Kavousi, Maryam and Welin, Lennart and Roussel, Ronan and Hu, Frank B and Sato, Shinichi and Davidson, Karina W and Howard, Barbara V and Leening, Maarten J G and Leening, Maarten and Rosengren, Annika and D{\"o}rr, Marcus and Deeg, Dorly J H and Kiechl, Stefan and Stehouwer, Coen D A and Nissinen, Aulikki and Giampaoli, Simona and Donfrancesco, Chiara and Kromhout, Daan and Price, Jackie F and Peters, Annette and Meade, Tom W and Casiglia, Edoardo and Lawlor, Debbie A and Gallacher, John and Nagel, Dorothea and Franco, Oscar H and Assmann, Gerd and Dagenais, Gilles R and Jukema, J Wouter and Sundstr{\"o}m, Johan and Woodward, Mark and Brunner, Eric J and Khaw, Kay-Tee and Wareham, Nicholas J and Whitsel, Eric A and Nj{\o}lstad, Inger and Hedblad, Bo and Wassertheil-Smoller, Sylvia and Engstr{\"o}m, Gunnar and Rosamond, Wayne D and Selvin, Elizabeth and Sattar, Naveed and Thompson, Simon G and Danesh, John} } @article {7451, title = {REPEATED MEASUREMENTS OF BLOOD PRESSURE AND CHOLESTEROL IMPROVES CARDIOVASCULAR DISEASE RISK PREDICTION: AN INDIVIDUAL-PARTICIPANT-DATA META-ANALYSIS.}, journal = {Am J Epidemiol}, year = {2017}, month = {2017 May 26}, abstract = {

The added value of incorporating information from repeated measurements of blood pressure and cholesterol for cardiovascular disease (CVD) risk prediction has not been rigorously assessed. We used data from the Emerging Risk Factors Collaboration on 191,445 adults (38 cohorts from across 17 countries with data from 1962-2014) with~>~1 million measurements of systolic blood pressure, total cholesterol and high-density lipoprotein cholesterol; over a median 12 years of follow-up, 21,170 CVD events occurred. Risk prediction models using cumulative means of repeated measurements and summary measures from longitudinal modelling of the repeated measurements were compared to models using measurements from a single time point. Risk discrimination (C-index) and net reclassification were calculated, and changes in C-indices were meta-analysed across studies. Compared to the single time point model, the cumulative means and the longitudinal models increased the C-index by 0.0040 (95\% CI: 0.0023, 0.0057) and 0.0023 (0.0005, 0.0042), respectively. Reclassification was also improved in both models; compared to the single time point model, overall net reclassification improvements were 0.0369 (0.0303, 0.0436) for the cumulative means model and 0.0177 (0.0110, 0.0243) for the longitudinal model. In conclusion, incorporating repeated measurements of blood pressure and cholesterol into CVD risk prediction models slightly improves risk prediction.

}, issn = {1476-6256}, doi = {10.1093/aje/kwx149}, author = {Paige, Ellie and Barrett, Jessica and Pennells, Lisa and Sweeting, Michael and Willeit, Peter and Di Angelantonio, Emanuele and Gudnason, Vilmundur and Nordestgaard, B{\o}rge G and Psaty, Bruce M and Goldbourt, Uri and Best, Lyle G and Assmann, Gerd and Salonen, Jukka T and Nietert, Paul J and Verschuren, Wm Monique and Brunner, Eric J and Kronmal, Richard A and Salomaa, Veikko and Bakker, Stephan Jl and Dagenais, Gilles R and Sato, Shinichi and Jansson, Jan-H{\r a}kan and Willeit, Johann and Onat, Altan and de la C{\'a}mara, Agustin G{\'o}mez and Roussel, Ronan and V{\"o}lzke, Henry and Dankner, Rachel and Tipping, Robert W and Meade, Tom W and Donfrancesco, Chiara and Kuller, Lewis H and Peters, Annette and Gallacher, John and Kromhout, Daan and Iso, Hiroyasu and Knuiman, Matthew and Casiglia, Edoardo and Kavousi, Maryam and Palmieri, Luigi and Sundstr{\"o}m, Johan and Davis, Barry R and Nj{\o}lstad, Inger and Couper, David and Danesh, John and Thompson, Simon G and Wood, Angela} } @article {9587, title = {Role of Polyunsaturated Fat in Modifying Cardiovascular Risk Associated With Family History of Cardiovascular Disease: Pooled De Novo Results From 15 Observational Studies.}, journal = {Circulation}, volume = {149}, year = {2024}, month = {2024 Jan 23}, pages = {305-316}, abstract = {

BACKGROUND: It is unknown whether dietary intake of polyunsaturated fatty acids (PUFA) modifies the cardiovascular disease (CVD) risk associated with a family history of CVD. We assessed interactions between biomarkers of low PUFA intake and a family history in relation to long-term CVD risk in a large consortium.

METHODS: Blood and tissue PUFA data from 40 885 CVD-free adults were assessed. PUFA levels <=25th percentile were considered to reflect low intake of linoleic, alpha-linolenic, and eicosapentaenoic/docosahexaenoic acids (EPA/DHA). Family history was defined as having >=1 first-degree relative who experienced a CVD event. Relative risks with 95\% CI of CVD were estimated using Cox regression and meta-analyzed. Interactions were assessed by analyzing product terms and calculating relative excess risk due to interaction.

RESULTS: After multivariable adjustments, a significant interaction between low EPA/DHA and family history was observed (product term pooled RR, 1.09 [95\% CI, 1.02-1.16]; =0.01). The pooled relative risk of CVD associated with the combined exposure to low EPA/DHA, and family history was 1.41 (95\% CI, 1.30-1.54), whereas it was 1.25 (95\% CI, 1.16-1.33) for family history alone and 1.06 (95\% CI, 0.98-1.14) for EPA/DHA alone, compared with those with neither exposure. The relative excess risk due to interaction results indicated no interactions.

CONCLUSIONS: A significant interaction between biomarkers of low EPA/DHA intake, but not the other PUFA, and a family history was observed. This novel finding might suggest a need to emphasize the benefit of consuming oily fish for individuals with a family history of CVD.

}, keywords = {Animals, Biomarkers, Cardiovascular Diseases, Docosahexaenoic Acids, Fatty Acids, Omega-3, Risk Factors}, issn = {1524-4539}, doi = {10.1161/CIRCULATIONAHA.123.065530}, author = {Laguzzi, Federica and {\r A}kesson, Agneta and Marklund, Matti and Qian, Frank and Gigante, Bruna and Bartz, Traci M and Bassett, Julie K and Birukov, Anna and Campos, Hannia and Hirakawa, Yoichiro and Imamura, Fumiaki and J{\"a}ger, Susanne and Lankinen, Maria and Murphy, Rachel A and Senn, Mackenzie and Tanaka, Toshiko and Tintle, Nathan and Virtanen, Jyrki K and Yamagishi, Kazumasa and Allison, Matthew and Brouwer, Ingeborg A and de Faire, Ulf and Eiriksdottir, Gudny and Ferrucci, Luigi and Forouhi, Nita G and Geleijnse, Johanna M and Hodge, Allison M and Kimura, Hitomi and Laakso, Markku and Riserus, Ulf and van Westing, Anniek C and Bandinelli, Stefania and Baylin, Ana and Giles, Graham G and Gudnason, Vilmundur and Iso, Hiroyasu and Lemaitre, Rozenn N and Ninomiya, Toshiharu and Post, Wendy S and Psaty, Bruce M and Salonen, Jukka T and Schulze, Matthias B and Tsai, Michael Y and Uusitupa, Matti and Wareham, Nicholas J and Oh, Seung-Won and Wood, Alexis C and Harris, William S and Siscovick, David and Mozaffarian, Dariush and Leander, Karin} }