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      Psychological distress in relation to site specific cancer mortality: pooling of unpublished data from 16 prospective cohort studies

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          Abstract

          Objective To examine the role of psychological distress (anxiety and depression) as a potential predictor of site specific cancer mortality.

          Design Pooling of individual participant data from 16 prospective cohort studies initiated 1994-2008.

          Setting Nationally representative samples drawn from the health survey for England (13 studies) and the Scottish health survey (three studies).

          Participants 163 363 men and women aged 16 or older at study induction, who were initially free of a cancer diagnosis, provided self reported psychological distress scores (based on the general health questionnaire, GHQ-12) and consented to health record linkage.

          Main outcome measure Vital status records used to ascertain death from 16 site specific malignancies; the three Scottish studies also had information on cancer registration (incidence).

          Results The studies collectively contributed an average of 9.5 years of mortality surveillance during which there were 16 267 deaths (4353 from cancer). After adjustment for age, sex, education, socioeconomic status, body mass index (BMI), and smoking and alcohol intake, and with reverse causality (by left censoring) and missing data (by imputation) taken into account, relative to people in the least distressed group (GHQ-12 score 0-6), death rates in the most distressed group (score 7-12) were consistently raised for cancer of all sites combined (multivariable adjusted hazard ratio 1.32, 95% confidence interval 1.18 to 1.48) and cancers not related to smoking (1.45, 1.23 to 1.71), as well as carcinoma of the colorectum (1.84, 1.21 to 2.78), prostate (2.42, 1.29 to 4.54), pancreas (2.76, 1.47 to 5.19), oesophagus (2.59, 1.34 to 5.00), and for leukaemia (3.86, 1.42 to 10.5). Stepwise associations across the full range of distress scores were observed for colorectal and prostate cancer.

          Conclusion This study contributes to the growing evidence that psychological distress might have some predictive capacity for selected cancer presentations, in addition to other somatic diseases.

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          Most cited references71

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          Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010.

          Reliable and timely information on the leading causes of death in populations, and how these are changing, is a crucial input into health policy debates. In the Global Burden of Diseases, Injuries, and Risk Factors Study 2010 (GBD 2010), we aimed to estimate annual deaths for the world and 21 regions between 1980 and 2010 for 235 causes, with uncertainty intervals (UIs), separately by age and sex. We attempted to identify all available data on causes of death for 187 countries from 1980 to 2010 from vital registration, verbal autopsy, mortality surveillance, censuses, surveys, hospitals, police records, and mortuaries. We assessed data quality for completeness, diagnostic accuracy, missing data, stochastic variations, and probable causes of death. We applied six different modelling strategies to estimate cause-specific mortality trends depending on the strength of the data. For 133 causes and three special aggregates we used the Cause of Death Ensemble model (CODEm) approach, which uses four families of statistical models testing a large set of different models using different permutations of covariates. Model ensembles were developed from these component models. We assessed model performance with rigorous out-of-sample testing of prediction error and the validity of 95% UIs. For 13 causes with low observed numbers of deaths, we developed negative binomial models with plausible covariates. For 27 causes for which death is rare, we modelled the higher level cause in the cause hierarchy of the GBD 2010 and then allocated deaths across component causes proportionately, estimated from all available data in the database. For selected causes (African trypanosomiasis, congenital syphilis, whooping cough, measles, typhoid and parathyroid, leishmaniasis, acute hepatitis E, and HIV/AIDS), we used natural history models based on information on incidence, prevalence, and case-fatality. We separately estimated cause fractions by aetiology for diarrhoea, lower respiratory infections, and meningitis, as well as disaggregations by subcause for chronic kidney disease, maternal disorders, cirrhosis, and liver cancer. For deaths due to collective violence and natural disasters, we used mortality shock regressions. For every cause, we estimated 95% UIs that captured both parameter estimation uncertainty and uncertainty due to model specification where CODEm was used. We constrained cause-specific fractions within every age-sex group to sum to total mortality based on draws from the uncertainty distributions. In 2010, there were 52·8 million deaths globally. At the most aggregate level, communicable, maternal, neonatal, and nutritional causes were 24·9% of deaths worldwide in 2010, down from 15·9 million (34·1%) of 46·5 million in 1990. This decrease was largely due to decreases in mortality from diarrhoeal disease (from 2·5 to 1·4 million), lower respiratory infections (from 3·4 to 2·8 million), neonatal disorders (from 3·1 to 2·2 million), measles (from 0·63 to 0·13 million), and tetanus (from 0·27 to 0·06 million). Deaths from HIV/AIDS increased from 0·30 million in 1990 to 1·5 million in 2010, reaching a peak of 1·7 million in 2006. Malaria mortality also rose by an estimated 19·9% since 1990 to 1·17 million deaths in 2010. Tuberculosis killed 1·2 million people in 2010. Deaths from non-communicable diseases rose by just under 8 million between 1990 and 2010, accounting for two of every three deaths (34·5 million) worldwide by 2010. 8 million people died from cancer in 2010, 38% more than two decades ago; of these, 1·5 million (19%) were from trachea, bronchus, and lung cancer. Ischaemic heart disease and stroke collectively killed 12·9 million people in 2010, or one in four deaths worldwide, compared with one in five in 1990; 1·3 million deaths were due to diabetes, twice as many as in 1990. The fraction of global deaths due to injuries (5·1 million deaths) was marginally higher in 2010 (9·6%) compared with two decades earlier (8·8%). This was driven by a 46% rise in deaths worldwide due to road traffic accidents (1·3 million in 2010) and a rise in deaths from falls. Ischaemic heart disease, stroke, chronic obstructive pulmonary disease (COPD), lower respiratory infections, lung cancer, and HIV/AIDS were the leading causes of death in 2010. Ischaemic heart disease, lower respiratory infections, stroke, diarrhoeal disease, malaria, and HIV/AIDS were the leading causes of years of life lost due to premature mortality (YLLs) in 2010, similar to what was estimated for 1990, except for HIV/AIDS and preterm birth complications. YLLs from lower respiratory infections and diarrhoea decreased by 45-54% since 1990; ischaemic heart disease and stroke YLLs increased by 17-28%. Regional variations in leading causes of death were substantial. Communicable, maternal, neonatal, and nutritional causes still accounted for 76% of premature mortality in sub-Saharan Africa in 2010. Age standardised death rates from some key disorders rose (HIV/AIDS, Alzheimer's disease, diabetes mellitus, and chronic kidney disease in particular), but for most diseases, death rates fell in the past two decades; including major vascular diseases, COPD, most forms of cancer, liver cirrhosis, and maternal disorders. For other conditions, notably malaria, prostate cancer, and injuries, little change was noted. Population growth, increased average age of the world's population, and largely decreasing age-specific, sex-specific, and cause-specific death rates combine to drive a broad shift from communicable, maternal, neonatal, and nutritional causes towards non-communicable diseases. Nevertheless, communicable, maternal, neonatal, and nutritional causes remain the dominant causes of YLLs in sub-Saharan Africa. Overlaid on this general pattern of the epidemiological transition, marked regional variation exists in many causes, such as interpersonal violence, suicide, liver cancer, diabetes, cirrhosis, Chagas disease, African trypanosomiasis, melanoma, and others. Regional heterogeneity highlights the importance of sound epidemiological assessments of the causes of death on a regular basis. Bill & Melinda Gates Foundation. Copyright © 2012 Elsevier Ltd. All rights reserved.
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            'Mendelian randomization': can genetic epidemiology contribute to understanding environmental determinants of disease?

            Associations between modifiable exposures and disease seen in observational epidemiology are sometimes confounded and thus misleading, despite our best efforts to improve the design and analysis of studies. Mendelian randomization-the random assortment of genes from parents to offspring that occurs during gamete formation and conception-provides one method for assessing the causal nature of some environmental exposures. The association between a disease and a polymorphism that mimics the biological link between a proposed exposure and disease is not generally susceptible to the reverse causation or confounding that may distort interpretations of conventional observational studies. Several examples where the phenotypic effects of polymorphisms are well documented provide encouraging evidence of the explanatory power of Mendelian randomization and are described. The limitations of the approach include confounding by polymorphisms in linkage disequilibrium with the polymorphism under study, that polymorphisms may have several phenotypic effects associated with disease, the lack of suitable polymorphisms for studying modifiable exposures of interest, and canalization-the buffering of the effects of genetic variation during development. Nevertheless, Mendelian randomization provides new opportunities to test causality and demonstrates how investment in the human genome project may contribute to understanding and preventing the adverse effects on human health of modifiable exposures.
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              Physical status: the use and interpretation of anthropometry. Report of a WHO Expert Committee.

              Anthropometry provides the single most portable, universally applicable, inexpensive and non-invasive technique for assessing the size, proportions, and composition of the human body. It reflects both health and nutritional status and predicts performance, health, and survival. As such, it is a valuable, but currently underused, tool for guiding public health policy and clinical decisions. This report presents the conclusions and comprehensive recommendations of a WHO Expert Committee for the present and future uses and interpretation of anthropometry. In a section that sets the technical framework for the report, the significance of anthropometric indicators and indices is explained and the principles of applied biostatistics and epidemiology that underlie their various uses are discussed. Subsequent sections provide detailed guidance on the use and interpretation of anthropometric measurements in pregnant and lactating women, newborn infants, infants and children, adolescents, overweight and thin adults, and adults aged 60 years and over. With a similar format for each section, the report assesses specific applications of anthropometry in individuals and populations for purposes of screening and for targeting and evaluating interventions. Advice on data management and analysis is offered, and methods of taking particular measurements are described. Each section also includes a discussion of the extent, reliability and universal relevance of existing reference data. An extensive series of reference data recommended by the Expert Committee and not widely distributed by WHO hitherto is included in an annex.
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                Author and article information

                Contributors
                Role: reader in epidemiology
                Role: Marjorie MacBeath intermediate clinical fellow
                Role: associate professor
                Role: professor of social epidemiology
                Journal
                BMJ
                BMJ
                bmj
                The BMJ
                BMJ Publishing Group Ltd.
                0959-8138
                1756-1833
                2017
                25 January 2017
                : 356
                : j108
                Affiliations
                [1 ]Department of Epidemiology and Public Health, University College, London, UK
                [2 ]Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
                [3 ]Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
                [4 ]Charles Perkins Centre, Faculty of Health Sciences, University of Sydney, Sydney, Australia
                Author notes
                Correspondence to: D Batty david.batty@ 123456ucl.ac.uk
                Article
                batg033543
                10.1136/bmj.j108
                5266623
                28122812
                814c4030-8fd6-4cef-88a0-ac865e482864
                Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions

                This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 3.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/3.0/.

                History
                : 23 December 2016
                Categories
                Research

                Medicine
                Medicine

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