The Emerging Risk Factors Collaboration 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 MEASURESAll-cause mortality and estimated reductions in life expectancy. RESULTSIn 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 RELEVANCEMortality 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.

Background and Purpose-We have previously shown that treatment of acute stroke patients in our stroke unit (SU) compared with treatment in general ward (GWs) improves short-and long-term survival and functional outcome and increases the possibility of earlier discharge to home. The aim of the present study was to identify the differences in treatment between the SU and the GW and to assess which aspects of the SU care which were most responsible for the better outcome. Methods-Of the 220 patients included in our trial, only 206 were actually treated (SU, 102 patients; GW, 104 patients).For these patients, we identified the differences in the treatment and the consequences of the treatment. We analyzed the factors that we were able to measure and their association with the outcome, discharge to home within 6 weeks. Results-Characteristic features in our SU were teamwork, staff education, functional training, and integrated physiotherapy and nursing. Other treatment factors significantly different in the SU from the GW were shorter time to start of the systematic mobilization/training and increased use of oxygen, heparin, intravenous saline solutions, and antipyretics. Consequences of the treatment seem to be less variation in diastolic and systolic blood pressure (BP), avoiding the lowest diastolic BP, and lowering the levels of glucose and temperature in the SU group compared with the GW group. Univariate analyses showed that all these factors except the level of glucose were significantly associated with discharge to home within 6 weeks. In the final multivariate Cox regression model, shorter time to start of the mobilization/training and stabilized diastolic BP were independent factors significantly associated with discharge to home within 6 weeks. Conclusions-Shorter time to start of mobilization/training was the most important factor associated with discharge to home, followed by stabilized diastolic BP, indicating that these factors probably were important in the SU treatment. The effects of characteristic features of an SU, such as a specially trained staff, teamwork, and involvement of relatives, were not possible to measure. Such factors might be more important than those actually measured. (Stroke. 1999;30:917-923.)

We investigated the association between total and cause-specific mortality and individual measures of long-term air pollution exposure in a cohort of Norwegian men followed from 1972-1973 through 1998. Data from a follow-up study on cardiovascular risk factors among 16,209 men 40-49 years of age living in Oslo, Norway, in 1972-1973 were linked with data from the Norwegian Death Register and with estimates of average yearly air pollution levels at the participants' home addresses from 1974 to 1998. Cox proportional-hazards regression was used to estimate associations between exposure and total and cause-specific mortality. During the follow-up time 4,227 men died from a disease corresponding to an ICD-9 (International Classification of Diseases, Revision 9) code < 800. Controlling for a number of potential confounders, the adjusted risk ratio for dying was 1.08 [95% confidence interval (CI), 1.06-1.11] for a 10- microg/m3 increase in average exposure to nitrogen oxides (NOx) at the home address from 1974 through 1978. Corresponding adjusted risk ratios for dying from a respiratory disease other than lung cancer were 1.16 (95% CI, 1.06-1.26); from lung cancer, 1.11 (95% CI, 1.03-1.19); from ischemic heart diseases, 1.08 (95% CI, 1.03-1.12); and from cerebrovascular diseases, 1.04 (95% CI, 0.94-1.15). The findings indicate that urban air pollution may increase the risk of dying. The effect seemed to be strongest for deaths from respiratory diseases other than lung cancer.

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The aim of the study was to establish whether metabolic syndrome predicts the incidence of prostate cancer. The hypothesis was tested using the 27-year follow-up of the prospective cohort of 16,209 men aged 40-49 years who participated in the Oslo Study in 1972-1973. Men with established diabetes and men with cancer diagnosed before screening were excluded, leaving 15,933 for analyses. Metabolic syndrome is here composed of body mass index, nonfasting glucose, triglycerides, and blood pressure or drug-treated hypertension. Two analytical approaches were compared, namely, predefined (adjusted from National Cholesterol Education Program) and quartile values of risk factors. Age, body mass index, and sedentary versus intermediate physical activity at work were significant predictors in univariate proportional hazards regression analyses. Combinations of any two (relative risk = 1.23; p = 0.04) or any three (relative risk = 1.56; p = 0.00) factors of the metabolic syndrome using quartile values of risk factors were predictive of prostate cancer. The number of cases for four factors was too small for analyses. Predefined values of the risk factors were not found to be predictive. In conclusion, metabolic syndrome was found to predict prostate cancer during 27 years of follow-up, indicating an association between insulin resistance and the incidence of prostate cancer.