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INTRODUCTION: Sleep is increasingly being viewed as an issue of public health concern, yet few epidemiologic studies have explored associations between sleep habits and metabolomic profile. OBJECTIVES: To assess the association between sleep and blood metabolites. METHODS: We examined the association between sleep and 891 fasting plasma metabolites in a subgroup of 106 participants from the Dietary Approaches to Stop Hypertension (DASH)-Sodium feeding trial (1997-1999). We produced two sleep variables to analyze, sleep midpoint (median time between bedtime and waketime) and sleep duration, as well as bedtime and wake time. Metabolites were measured using liquid and gas chromatography, coupled with mass spectrometry. We assessed associations between sleep variables and log transformed metabolites using linear mixed-effects models. We combined the resulting p-values using Fisher's method to calculate associations between sleep and 38 metabolic pathways. RESULTS: Sixteen pathways were associated (p < 0.05) with midpoint. Only the γ-glutamyl amino acid metabolism pathway reached Bonferroni-corrected threshold (0.0013). Eighty-three metabolites were associated with midpoint (FDR < 0.20). Similar associations were found for wake time. Neither bed time nor duration were strongly associated. The top metabolites (pathways given in brackets) associated with sleep were erythrulose (advanced glycation end-product) (positive association) and several γ-glutamyl pathway metabolites, including CMPF (fatty acid, dicarboxylate), isovalerate (valine, leucine and isoleucine and fatty acid metabolism) and HWESASXX (polypeptide) (inverse association). CONCLUSION: Within our study, several metabolites that have previously been linked to inflammation and oxidative stress (processes involved in diseases such as cardiovascular disease and cancer) were found to be associated with sleep.
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Redes e Vias Metabólicas/fisiologia , Sono/fisiologia , Adulto , Idoso , Doenças Cardiovasculares , Comportamento Alimentar/fisiologia , Feminino , Cromatografia Gasosa-Espectrometria de Massas/métodos , Humanos , Hipertensão/sangue , Masculino , Metabolômica/métodos , Pessoa de Meia-IdadeRESUMO
Given the long latency period of pancreatic cancer, exploring the influence of early and midlife exposures will further advance our understanding of the disease. We assessed associations between diet and pancreatic cancer incidence in the National Institutes of Health (NIH)-AARP (formerly American Association of Retired Persons) Diet and Health Study. In 1996, a total of 303,094 participants completed 2 food frequency questionnaires that assessed diet at ages 12-13 years and 10 years previously. We used Cox proportional hazards regression to estimate adjusted hazard ratios and 95% confidence intervals. Through the end of 2006, a total of 1,322 pancreatic cancer cases occurred (average follow up time = 10.1 years). When comparing the highest tertiles with the lowest, carbohydrate intake during adolescence (hazard ratio (HR) = 0.87, 95% confidence interval (CI): 0.76, 0.99), but not 10 years before baseline, was inversely associated with pancreatic cancer risk. Total fat intake 10 years before baseline was significantly associated with increased risk (HR = 1.17, 95% CI: 1.02, 1.34), while risk was higher for high fat intake during both adolescence and midlife. Calcium intake 10 years before baseline was associated with reduced risk (HR = 0.87, 95% CI: 0.76, 0.99), as was a change from low intake in adolescence to high intake in midlife (HR = 0.71, 95% CI: 0.54, 0.93). Our study found a number of dietary factors present during adolescence and midlife to be associated with pancreatic cancer.
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Dieta/efeitos adversos , Neoplasias Pancreáticas/etiologia , Adolescente , Idoso , Criança , Estudos de Coortes , Dieta/estatística & dados numéricos , Inquéritos sobre Dietas , Gorduras na Dieta/efeitos adversos , Feminino , Humanos , Incidência , Masculino , Pessoa de Meia-Idade , Neoplasias Pancreáticas/epidemiologia , Modelos de Riscos Proporcionais , Fatores de Risco , Inquéritos e QuestionáriosRESUMO
BACKGROUND: The extent that controlled diabetes impacts upon mortality, compared with uncontrolled diabetes, and how pre-diabetes alters mortality risk remain issues requiring clarification. METHODS: We carried out a cohort study of 22,106 Health Survey for England participants with a HbA1C measurement linked with UK mortality records. We estimated hazard ratios (HRs) of all-cause, cancer and cardiovascular disease (CVD) mortality and 95% confidence intervals (CI) using Cox regression. RESULTS: Average follow-up time was seven years and there were 1,509 deaths within the sample. Compared with the non-diabetic and normoglycaemic group (HbA1C <5.7% [<39 mmol/mol] and did not indicate diabetes), undiagnosed diabetes (HbA1C ≥6.5% [≥48 mmol/mol] and did not indicate diabetes) inferred an increased risk of mortality for all-causes (HR 1.40, 1.09-1.80) and CVD (1.99, 1.35-2.94), as did uncontrolled diabetes (diagnosed diabetes and HbA1C ≥6.5% [≥48 mmol/mol]) and diabetes with moderately raised HbA1C (diagnosed diabetes and HbA1C 5.7-<6.5% [39-<48 mmol/mol]). Those with controlled diabetes (diagnosed diabetes and HbA<5.7% [<39 mmol/mol]) had an increased HR in relation to mortality from CVD only. Pre-diabetes (those who did not indicate diagnosed diabetes and HbA1C 5.7-<6.5% [39-<48 mmol/mol]) was not associated with increased mortality, and raised HbA1C did not appear to have a statistically significant impact upon cancer mortality. Adjustment for BMI and socioeconomic status had a limited impact upon our results. We also found women had a higher all-cause and CVD mortality risk compared with men. CONCLUSIONS: We found higher rates of all-cause and CVD mortality among those with raised HbA1C, but not for those with pre-diabetes, compared with those without diabetes. This excess differed by sex and diabetes status. The large number of deaths from cancer and CVD globally suggests that controlling blood glucose levels and policies to prevent hyperglycaemia should be considered public health priorities.
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Doenças Cardiovasculares/mortalidade , Diabetes Mellitus/mortalidade , Hemoglobinas Glicadas/metabolismo , Hiperglicemia/mortalidade , Neoplasias/mortalidade , Estado Pré-Diabético/mortalidade , Adulto , Idoso , Biomarcadores/sangue , Índice de Massa Corporal , Doenças Cardiovasculares/sangue , Doenças Cardiovasculares/complicações , Doenças Cardiovasculares/diagnóstico , Complicações do Diabetes , Diabetes Mellitus/sangue , Diabetes Mellitus/diagnóstico , Feminino , Inquéritos Epidemiológicos , Humanos , Hiperglicemia/sangue , Hiperglicemia/complicações , Hiperglicemia/diagnóstico , Incidência , Masculino , Pessoa de Meia-Idade , Neoplasias/sangue , Neoplasias/complicações , Neoplasias/diagnóstico , Estado Pré-Diabético/sangue , Estado Pré-Diabético/complicações , Estado Pré-Diabético/diagnóstico , Fatores de Risco , Fatores Sexuais , Classe Social , Análise de Sobrevida , Reino Unido/epidemiologiaRESUMO
BACKGROUND: Diabetes mellitus is associated with differing rates of all-cause and cause-specific mortality compared with the general population; although the strength of these associations requires further investigation. The effects of confounding factors, such as overweight and obesity and the presence of co-morbid cardiovascular disease (CVD), upon such associations also remain unclear. There is thus a need for studies which utilise data from nationally-representative samples to explore these associations further. METHODS: A cohort study of 204,533 participants aged 16+ years (7,199 with diabetes) from the Health Survey for England (HSE) (1994-2008) and Scottish Health Survey (SHeS) (1995, 1998 and 2003) linked with UK mortality records. Odds ratios (ORs) of all-cause and cause-specific mortality and 95% confidence intervals were estimated using logistic and multinomial logistic regression. RESULTS: There were 20,051 deaths (1,814 among those with diabetes). Adjusted (age, sex, and smoking status) ORs for all-cause mortality among those with diabetes was 1.68 (95%CI 1.57-1.79). Cause-specific mortality ORs were: cancer 1.26 (1.13-1.42), respiratory diseases 1.25 (1.08-1.46), CVD 1.96 (1.80-2.14) and 'other' causes 2.06 (1.84-2.30). These were not attenuated significantly after adjustment for generalised and/or central adiposity and other confounding factors. The odds of mortality differed between those with and without comorbid CVD at baseline; the ORs for the latter group were substantially increased. CONCLUSIONS: In addition to the excess in CVD and all-cause mortality among those with diabetes, there is also increased mortality from cancer, respiratory diseases, and 'other' causes. This increase in mortality is independent of obesity and a range of other confounding factors. With falling CVD incidence and mortality, the raised risks of respiratory and cancer deaths in people with diabetes will become more important and require increased health care provision.
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Doenças Cardiovasculares/mortalidade , Diabetes Mellitus/epidemiologia , Neoplasias/mortalidade , Doenças Respiratórias/mortalidade , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Causas de Morte , Estudos de Coortes , Inglaterra/epidemiologia , Feminino , Inquéritos Epidemiológicos , Humanos , Masculino , Pessoa de Meia-Idade , Obesidade/epidemiologia , Escócia/epidemiologia , Fatores Socioeconômicos , Adulto JovemRESUMO
This review explores the epidemiological evidence relating to type-1 diabetes (T1DM) and cancer incidence and mortality. Mortality rates among those with T1DM are higher in every age group compared with the general population; the majority of this mortality is due to factors related to the consequences of diabetes, such as cardiovascular and renal disease. For over 100 years, researchers have explored the relationships between diabetes and cancer and although there is now a large body of work on the subject, consensus has not been reached. Such research has tended to focus upon type-2 diabetes, with the result that very little is known about T1DM and cancer. As incidence of T1DM increases, by around 3% annually among children, the need for further research into its impact upon cancer incidence and mortality increases. Within this review, findings varied by study method utilised, T1DM definition used and study region and outcome measure explored. None of the case-control studies found a statistically significant link between the two diseases, whereas both of the meta-analyses did. Cohort studies produced mixed results. There were also mixed findings among research that defined T1DM in the same way (e.g. defining individuals with the disease as those diagnosed with diabetes before 30 years of age). The review found a number of studies which explored cause-specific cancer mortality among those with diabetes; such studies also had mixed findings. This inconsistency within results suggests the need for further research to understand better the potential relationships between T1DM and cancer.