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Good data curation is integral to cohort studies, but it is not always done to a level necessary to ensure the longevity of the data a study holds. In this opinion paper, we introduce the concept of data curation debt-the data curation equivalent to the software engineering principle of technical debt. Using the context of UK cohort studies, we define data curation debt-describing examples and their potential impact. We highlight that accruing this debt can make it more difficult to use the data in the future. Additionally, the long-running nature of cohort studies means that interest is accrued on this debt and compounded over time-increasing the impact a debt could have on a study and its stakeholders. Primary causes of data curation debt are discussed across three categories: longevity of hardware, software and data formats; funding; and skills shortages. Based on cross-domain best practice, strategies to reduce the debt and preventive measures are proposed-with importance given to the recognition and transparent reporting of data curation debt. Describing the debt in this way, we encapsulate a multi-faceted issue in simple terms understandable by all cohort study stakeholders. Data curation debt is not only confined to the UK, but is an issue the international community must be aware of and address. This paper aims to stimulate a discussion between cohort studies and their stakeholders on how to address the issue of data curation debt. If data curation debt is left unchecked it could become impossible to use highly valued cohort study data, and ultimately represents an existential risk to studies themselves. [ABSTRACT FROM AUTHOR]

Background: With genome-wide association data for many exposures and outcomes now available from large biobanks, one-sample Mendelian randomization (MR) is increasingly used to investigate causal relationships. Many robust MR methods are available to address pleiotropy, but these assume independence between the gene-exposure and gene-outcome association estimates. Unlike in two-sample MR, in one-sample MR the two estimates are obtained from the same individuals, and the assumption of independence does not hold in the presence of confounding.Methods: With simulations mimicking a typical study in UK Biobank, we assessed the performance, in terms of bias and precision of the MR estimate, of the fixed-effect and (multiplicative) random-effects meta-analysis method, weighted median estimator, weighted mode estimator and MR-Egger regression, used in both one-sample and two-sample data. We considered scenarios differing by the: presence/absence of a true causal effect; amount of confounding; and presence and type of pleiotropy (none, balanced or directional).Results: Even in the presence of substantial correlation due to confounding, all two-sample methods used in one-sample MR performed similarly to when used in two-sample MR, except for MR-Egger which resulted in bias reflecting direction and magnitude of the confounding. Such bias was much reduced in the presence of very high variability in instrument strength across variants (IGX2 of 97%).Conclusions: Two-sample MR methods can be safely used for one-sample MR performed within large biobanks, expect for MR-Egger. MR-Egger is not recommended for one-sample MR unless the correlation between the gene-exposure and gene-outcome estimates due to confounding can be kept low, or the variability in instrument strength is very high. [ABSTRACT FROM AUTHOR]

Background: Two-sample Mendelian randomization (MR) allows the use of freely accessible summary association results from genome-wide association studies (GWAS) to estimate causal effects of modifiable exposures on outcomes. Some GWAS adjust for heritable covariables in an attempt to estimate direct effects of genetic variants on the trait of interest. One, both or neither of the exposure GWAS and outcome GWAS may have been adjusted for covariables.Methods: We performed a simulation study comprising different scenarios that could motivate covariable adjustment in a GWAS and analysed real data to assess the influence of using covariable-adjusted summary association results in two-sample MR.Results: In the absence of residual confounding between exposure and covariable, between exposure and outcome, and between covariable and outcome, using covariable-adjusted summary associations for two-sample MR eliminated bias due to horizontal pleiotropy. However, covariable adjustment led to bias in the presence of residual confounding (especially between the covariable and the outcome), even in the absence of horizontal pleiotropy (when the genetic variants would be valid instruments without covariable adjustment). In an analysis using real data from the Genetic Investigation of ANthropometric Traits (GIANT) consortium and UK Biobank, the causal effect estimate of waist circumference on blood pressure changed direction upon adjustment of waist circumference for body mass index.Conclusions: Our findings indicate that using covariable-adjusted summary associations in MR should generally be avoided. When that is not possible, careful consideration of the causal relationships underlying the data (including potentially unmeasured confounders) is required to direct sensitivity analyses and interpret results with appropriate caution. [ABSTRACT FROM AUTHOR]

Background: It is commonly assumed that high oestradiol levels in women are cardioprotective. We assessed the association between oestradiol and the risk of incident myocardial infarction (MI) in women.Methods: We used data from 263 295 female UK Biobank participants [mean age 56.2; standard deviation (SD) 8.0 years] without previous cardiovascular disease (CVD). Associations of oestradiol with age and other cardiovascular risk factors were assessed. Cox proportional hazards models estimated crude, ag- and multiple-adjusted hazard ratios (HR) for MI associated with oestradiol levels.Results: After a mean follow-up of 9 years, 2206 incident cases of MI had been recorded, including 230 events among the 57 204 women (mean age 48) with detectable oestradiol levels. In the unadjusted analyses, a unit higher in log-transformed oestradiol was associated with an HR [95% confidence interval (CI) for MI of 0.73 (0.58; 0.92)]. After adjusting for age, this HR became 0.94 (0.75; 1.17), and after further adjusting for classical CVD risk factors, it was 1.05 (0.83; 1.31. Results were similar in subgroup analyses defined by age, menopausal status, socioeconomic status, contraceptive pill use and the use of hormone replacement therapy. The multivariable-adjusted HR for the 171 431 women (mean age 59) with undetectable levels of oestradiol, compared with those with detectable levels, was 0.97 (0.92; 1.02).Conclusions: Higher levels of oestradiol were not associated with a decreased risk of MI. The presumed cardioprotective effects of oestradiol seem to be largely confounded by age and further confounded by other cardiovascular risk factors. [ABSTRACT FROM AUTHOR]

Background: Low socio-economic position (SEP) is a risk factor for multiple health outcomes, but its molecular imprints in the body remain unclear.Methods: We examined SEP as a determinant of serum nuclear magnetic resonance metabolic profiles in ∼30 000 adults and 4000 children across 10 UK and Finnish cohort studies.Results: In risk-factor-adjusted analysis of 233 metabolic measures, low educational attainment was associated with 37 measures including higher levels of triglycerides in small high-density lipoproteins (HDL) and lower levels of docosahexaenoic acid (DHA), omega-3 fatty acids, apolipoprotein A1, large and very large HDL particles (including levels of their respective lipid constituents) and cholesterol measures across different density lipoproteins. Among adults whose father worked in manual occupations, associations with apolipoprotein A1, large and very large HDL particles and HDL-2 cholesterol remained after adjustment for SEP in later life. Among manual workers, levels of glutamine were higher compared with non-manual workers. All three indicators of low SEP were associated with lower DHA, omega-3 fatty acids and HDL diameter. At all ages, children of manual workers had lower levels of DHA as a proportion of total fatty acids.Conclusions: Our work indicates that social and economic factors have a measurable impact on human physiology. Lower SEP was independently associated with a generally unfavourable metabolic profile, consistent across ages and cohorts. The metabolites we found to be associated with SEP, including DHA, are known to predict cardiovascular disease and cognitive decline in later life and may contribute to health inequalities. [ABSTRACT FROM AUTHOR]

Objective: We assess the existence of unfair inequalities in health and death using the normative framework of inequality of opportunities, from birth to middle age in Great Britain.Methods: We use data from the 1958 National Child Development Study, which provides a unique opportunity to observe individual health from birth to the age of 54, including the occurrence of mortality. We measure health status combining self-assessed health and mortality. We compare and statistically test the differences between the cumulative distribution functions of health status at each age according to one childhood circumstance beyond people's control: the father's occupation.Results: At all ages, individuals born to a 'professional', 'senior manager or technician' father report a better health status and have a lower mortality rate than individuals born to 'skilled', 'partly skilled' or 'unskilled' manual workers and individuals without a father at birth. The gap in the probability to report good health between individuals born into high social backgrounds compared with low, increases from 12 percentage points at age 23 to 26 at age 54. Health gaps are even more marked in health states at the bottom of the health distribution when mortality is combined with self-assessed health.Conclusions: There is increasing inequality of opportunities in health over the lifespan in Great Britain. The tag of social background intensifies as individuals get older. Finally, there is added analytical value to combining mortality with self-assessed health when measuring health inequalities. [ABSTRACT FROM AUTHOR]

Background: We aimed to estimate the causal effect of health conditions and risk factors on social and socioeconomic outcomes in UK Biobank. Evidence on socioeconomic impacts is important to understand because it can help governments, policy makers and decision makers allocate resources efficiently and effectively.Methods: We used Mendelian randomization to estimate the causal effects of eight health conditions (asthma, breast cancer, coronary heart disease, depression, eczema, migraine, osteoarthritis, type 2 diabetes) and five health risk factors [alcohol intake, body mass index (BMI), cholesterol, systolic blood pressure, smoking] on 19 social and socioeconomic outcomes in 336 997 men and women of White British ancestry in UK Biobank, aged between 39 and 72 years. Outcomes included annual household income, employment, deprivation [measured by the Townsend deprivation index (TDI)], degree-level education, happiness, loneliness and 13 other social and socioeconomic outcomes.Results: Results suggested that BMI, smoking and alcohol intake affect many socioeconomic outcomes. For example, smoking was estimated to reduce household income [mean difference = -£22 838, 95% confidence interval (CI): -£31 354 to -£14 321] and the chance of owning accommodation [absolute percentage change (APC) = -20.8%, 95% CI: -28.2% to -13.4%], of being satisfied with health (APC = -35.4%, 95% CI: -51.2% to -19.5%) and of obtaining a university degree (APC = -65.9%, 95% CI: -81.4% to -50.4%), while also increasing deprivation (mean difference in TDI = 1.73, 95% CI: 1.02 to 2.44, approximately 216% of a decile of TDI). There was evidence that asthma decreased household income, the chance of obtaining a university degree and the chance of cohabiting, and migraine reduced the chance of having a weekly leisure or social activity, especially in men. For other associations, estimates were null.Conclusions: Higher BMI, alcohol intake and smoking were all estimated to adversely affect multiple social and socioeconomic outcomes. Effects were not detected between health conditions and socioeconomic outcomes using Mendelian randomization, with the exceptions of depression, asthma and migraines. This may reflect true null associations, selection bias given the relative health and age of participants in UK Biobank, and/or lack of power to detect effects. [ABSTRACT FROM AUTHOR]

Background: Little is known about population levels of energy expenditure, as national surveillance systems typically employ only crude measures. The National Diet and Nutrition Survey (NDNS) in the UK measured energy expenditure in a 10% subsample by gold-standard doubly labelled water (DLW).Methods: DLW-subsample participants from the NDNS (383 males, 387 females) aged 4-91 years were recruited between 2008 and 2015 (rolling programme). Height and weight were measured and body-fat percentage estimated by deuterium dilution.Results: Absolute total energy expenditure (TEE) increased steadily throughout childhood, ranging from 6.2 and 7.2 MJ/day in 4- to 7-year-olds to 9.7 and 11.7 MJ/day for 14- to 16-year-old girls and boys, respectively. TEE peaked in 17- to 27-year-old women (10.7 MJ/day) and 28- to 43-year-old men (14.4 MJ/day), before decreasing gradually in old age. Physical-activity energy expenditure (PAEE) declined steadily with age from childhood (87 kJ/day/kg in 4- to 7-year-olds) through to old age (38 kJ/day/kg in 71- to 91-year-olds). No differences were observed by time, region and macronutrient composition. Body-fat percentage was strongly inversely associated with PAEE throughout life, irrespective of expressing PAEE relative to body mass or fat-free mass. Compared with females with <30% body fat, females with >40% recorded 29 kJ/day/kg body mass and 18 kJ/day/kg fat-free mass less PAEE in analyses adjusted for age, geographical region and time of assessment. Similarly, compared with males with <25% body fat, males with >35% recorded 26 kJ/day/kg body mass and 10 kJ/day/kg fat-free mass less PAEE.Conclusions: This first nationally representative study reports levels of human-energy expenditure as measured by gold-standard methodology; values may serve as a reference for other population studies. Age, sex and body composition are the main determinants of energy expenditure. Key Messages This is the first nationally representative study of human energy expenditure, covering the UK in the period 2008-2015. Total energy expenditure (MJ/day) increases steadily with age throughout childhood and adolescence, peaks in the 3rd decade of life in women and 4th decade of life in men, before decreasing gradually in old age. Physical activity energy expenditure (kJ/day/kg or kJ/day/kg fat-free mass) declines steadily with age from childhood to old age, more steeply so in males. Body-fat percentage is strongly inversely associated with physical activity energy expenditure. We found little evidence that energy expenditure varied by geographical region, over time, or by dietary macronutrient composition. [ABSTRACT FROM AUTHOR]

Background: Most of the previous studies on diet and colorectal cancer were based on diets consumed during the 1990s.Methods: We used Cox-regression models to estimate adjusted hazard ratios for colorectal cancer by dietary factors in the UK Biobank study. Men and women aged 40-69 years at recruitment (2006-10) reported their diet on a short food-frequency questionnaire (n = 475 581). Dietary intakes were re-measured in a large sub-sample (n = 175 402) who completed an online 24-hour dietary assessment during follow-up. Trends in risk across the baseline categories were calculated by assigning re-measured intakes to allow for measurement error and changes in intake over time.Results: During an average of 5.7 years of follow-up, 2609 cases of colorectal cancer occurred. Participants who reported consuming an average of 76 g/day of red and processed meat compared with 21 g/day had a 20% [95% confidence interval (CI): 4-37] higher risk of colorectal cancer. Participants in the highest fifth of intake of fibre from bread and breakfast cereals had a 14% (95% CI: 2-24) lower risk of colorectal cancer. Alcohol was associated with an 8% (95% CI: 4-12) higher risk per 10 g/day higher intake. Fish, poultry, cheese, fruit, vegetables, tea and coffee were not associated with colorectal-cancer risk.Conclusions: Consumption of red and processed meat at an average level of 76 g/d that meets the current UK government recommendation (≤90 g/day) was associated with an increased risk of colorectal cancer. Alcohol was also associated with an increased risk of colorectal cancer, whereas fibre from bread and breakfast cereals was associated with a reduced risk. [ABSTRACT FROM AUTHOR]

Background: Short and long sleep duration have been linked with poorer cognitive outcomes, but it remains unclear whether these associations are causal.Methods: We conducted the first Mendelian randomization (MR) study with 77 single-nucleotide polymorphisms (SNPs) for sleep duration using individual-participant data from the UK Biobank cohort (N = 395 803) and summary statistics from the International Genomics of Alzheimer's Project (N cases/controls = 17 008/37 154) to investigate the potential impact of sleep duration on cognitive outcomes.Results: Linear MR suggested that each additional hour/day of sleep was associated with 1% [95% confidence interval (CI) = 0-2%; P = 0.008] slower reaction time and 3% more errors in visual-memory test (95% CI = 0-6%; P = 0.05). There was little evidence to support associations of increased sleep duration with decline in visual memory [odds ratio (OR) per additional hour/day of sleep = 1.10 (95% CI = 0.76-1.57); P = 0.62], decline in reaction time [OR = 1.28 (95% CI = 0.49-3.35); P = 0.61], all-cause dementia [OR = 1.19 (95% CI = 0.65-2.19); P = 0.57] or Alzheimer's disease risk [OR = 0.89 (95% CI = 0.67-1.18); P = 0.41]. Non-linear MR suggested that both short and long sleep duration were associated with poorer visual memory (P for non-linearity = 3.44e-9) and reaction time (P for non-linearity = 6.66e-16).Conclusions: Linear increase in sleep duration has a small negative effect on reaction time and visual memory, but the true association might be non-linear, with evidence of associations for both short and long sleep duration. These findings suggest that sleep duration may represent a potential causal pathway for cognition. [ABSTRACT FROM AUTHOR]

Background: Mendelian randomization (MR) is a powerful tool in epidemiology that can be used to estimate the causal effect of an exposure on an outcome in the presence of unobserved confounding, by utilizing genetic variants that are instrumental variables (IVs) for the exposure. This has been extended to multivariable MR (MVMR) to estimate the effect of two or more exposures on an outcome.Methods and Results: We use simulations and theory to clarify the interpretation of estimated effects in a MVMR analysis under a range of underlying scenarios, where a secondary exposure acts variously as a confounder, a mediator, a pleiotropic pathway and a collider. We then describe how instrument strength and validity can be assessed for an MVMR analysis in the single-sample setting, and develop tests to assess these assumptions in the popular two-sample summary data setting. We illustrate our methods using data from UK Biobank to estimate the effect of education and cognitive ability on body mass index.Conclusion: MVMR analysis consistently estimates the direct causal effect of an exposure, or exposures, of interest and provides a powerful tool for determining causal effects in a wide range of scenarios with either individual- or summary-level data. [ABSTRACT FROM AUTHOR]

Background: Depression is more common in obese than non-obese individuals, especially in women, but the causal relationship between obesity and depression is complex and uncertain. Previous studies have used genetic variants associated with BMI to provide evidence that higher body mass index (BMI) causes depression, but have not tested whether this relationship is driven by the metabolic consequences of BMI nor for differences between men and women.Methods: We performed a Mendelian randomization study using 48 791 individuals with depression and 291 995 controls in the UK Biobank, to test for causal effects of higher BMI on depression (defined using self-report and Hospital Episode data). We used two genetic instruments, both representing higher BMI, but one with and one without its adverse metabolic consequences, in an attempt to 'uncouple' the psychological component of obesity from the metabolic consequences. We further tested causal relationships in men and women separately, and using subsets of BMI variants from known physiological pathways.Results: Higher BMI was strongly associated with higher odds of depression, especially in women. Mendelian randomization provided evidence that higher BMI partly causes depression. Using a 73-variant BMI genetic risk score, a genetically determined one standard deviation (1 SD) higher BMI (4.9 kg/m2) was associated with higher odds of depression in all individuals [odds ratio (OR): 1.18, 95% confidence interval (CI): 1.09, 1.28, P = 0.00007) and women only (OR: 1.24, 95% CI: 1.11, 1.39, P = 0.0001). Meta-analysis with 45 591 depression cases and 97 647 controls from the Psychiatric Genomics Consortium (PGC) strengthened the statistical confidence of the findings in all individuals. Similar effect size estimates were obtained using different Mendelian randomization methods, although not all reached P < 0.05. Using a metabolically favourable adiposity genetic risk score, and meta-analysing data from the UK biobank and PGC, a genetically determined 1 SD higher BMI (4.9 kg/m2) was associated with higher odds of depression in all individuals (OR: 1.26, 95% CI: 1.06, 1.50], P = 0.010), but with weaker statistical confidence.Conclusions: Higher BMI, with and without its adverse metabolic consequences, is likely to have a causal role in determining the likelihood of an individual developing depression. [ABSTRACT FROM AUTHOR]

Background: Mendelian randomization (MR) has developed into an established method for strengthening causal inference and estimating causal effects, largely due to the proliferation of genome-wide association studies. However, genetic instruments remain controversial, as horizontal pleiotropic effects can introduce bias into causal estimates. Recent work has highlighted the potential of gene-environment interactions in detecting and correcting for pleiotropic bias in MR analyses.Methods: We introduce MR using Gene-by-Environment interactions (MRGxE) as a framework capable of identifying and correcting for pleiotropic bias. If an instrument-covariate interaction induces variation in the association between a genetic instrument and exposure, it is possible to identify and correct for pleiotropic effects. The interpretation of MRGxE is similar to conventional summary MR approaches, with a particular advantage of MRGxE being the ability to assess the validity of an individual instrument.Results: We investigate the effect of adiposity, measured using body mass index (BMI), upon systolic blood pressure (SBP) using data from the UK Biobank and a single weighted allelic score informed by data from the GIANT consortium. We find MRGxE produces findings in agreement with two-sample summary MR approaches. Further, we perform simulations highlighting the utility of the approach even when the MRGxE assumptions are violated.Conclusions: By utilizing instrument-covariate interactions in MR analyses implemented within a linear-regression framework, it is possible to identify and correct for horizontal pleiotropic bias, provided the average magnitude of pleiotropy is constant across interaction-covariate subgroups. [ABSTRACT FROM AUTHOR]

Background: The Seven Countries Study in the 1960s showed very low mortality from coronary heart disease (CHD) in Japan, which was attributed to very low levels of total cholesterol. Studies of migrant Japanese to the USA in the 1970s documented increase in CHD rates, thus CHD mortality in Japan was expected to increase as their lifestyle became Westernized, yet CHD mortality has continued to decline since 1970. This study describes trends in CHD mortality and its risk factors since 1980 in Japan, contrasting those in other selected developed countries.Methods: We selected Australia, Canada, France, Japan, Spain, Sweden, the UK and the USA. CHD mortality between 1980 and 2007 was obtained from WHO Statistical Information System. National data on traditional risk factors during the same period were obtained from literature and national surveys.Results: Age-adjusted CHD mortality continuously declined between 1980 and 2007 in all these countries. The decline was accompanied by a constant fall in total cholesterol except Japan where total cholesterol continuously rose. In the birth cohort of individuals currently aged 50-69 years, levels of total cholesterol have been higher in Japan than in the USA, yet CHD mortality in Japan remained the lowest: >67% lower in men and > 75% lower in women compared with the USA. The direction and magnitude of changes in other risk factors were generally similar between Japan and the other countries.Conclusions: Decline in CHD mortality despite a continuous rise in total cholesterol is unique. The observation may suggest some protective factors unique to Japanese. [ABSTRACT FROM AUTHOR]

Background: The promotion and support of breastfeeding is a global priority with benefits for maternal and infant health, particularly in low-income and middle-income countries where its relevance for child survival is undisputed. However, breastfeeding rates are strikingly low in some higher-income countries, including the UK. Evidence to support the effectiveness of public health interventions to increase rates of breastfeeding initiation and duration in this setting is limited. We examined whether mothers were more likely to start and continue to breastfeed if they delivered in a UNICEF UK Baby Friendly accredited maternity unit, in a cohort with a high representation of disadvantaged and lower socioeconomic groups with traditionally low rates of breastfeeding.Methods: We analysed maternally reported breastfeeding initiation and prevalence of any breastfeeding at 1 month for 17 359 singleton infants according to maternity unit Baby Friendly Initiative participation status at birth (accredited, certificated, or neither award).Results: Mothers delivering in accredited maternity units were more likely to start breastfeeding than those delivering in units with neither award [adjusted rate ratio: 1.10, 95% confidence interval (CI) 1.05-1.15], but were not more likely to breastfeed at 1 month (0.96, 95% CI 0.84-1.09), after adjustment for social, demographic, and obstetric factors. Antenatal class attendance (1.14, 95% CI 1.11-1.17), vaginal delivery (1.05, 1.03-1.08), a companion at delivery (1.09, 1.04-1.16), and maternal post-partum hospital stay >24 h (1.06, 1.04-1.09) were also independently associated with breastfeeding initiation.Conclusions: Policies to increase the proportion of maternity units participating in the UNICEF UK Baby Friendly Initiative are likely to increase breastfeeding initiation but not duration. Other strategies are required in order to support UK mothers to breastfeed for the recommended duration. [ABSTRACT FROM AUTHOR]

Background: Two recent case-control studies by Meier et al. and van Staa et al. used the UK General Practice Research Database (GPRD) to examine the association between the use of statins and the risk of fractures, with different results. The objective of the present study was to examine methodological explanations for the discrepant results.Methods: We created two datasets, which mimicked the previous study designs: a 'selected population' (SP) case-control dataset, with fracture cases matched to controls nested within a selected cohort (Meier et al.), and an 'entire population' (EP) case-control dataset, with both cases and controls sampled from the total GPRD population (van Staa et al.). Cases and controls were matched by gender, age (year of birth or 5 year age bands), and general practice.Results: The study included 131 855 fracture cases. The crude odds ratio (OR) for hip fracture in statin users was 0.37 (95% CI 0.27-0.52) in the SP and 0.54 (95% CI 0.39-0.74) in the EP dataset. This difference was reduced when matching by year of birth, rather than by 5 year age bands: crude ORs were 0.58 (95% CI 0.43-0.79) and 0.61 (95% CI 0.44-0.88), respectively. In the SP dataset, 37% of the cases could be matched by year of birth, while this was achieved for 99% in the 'EP' dataset. The exposure time-window, the selection of confounders, and exclusion of high-risk patients also influenced results.Conclusion: Residual confounding by a matching variable and different definitions of the exposure time window explained differences in results. In case-control studies of drug use and fracture risk, broad matching criteria for age should be avoided and the selection of the time-window for exposure should be carefully considered. [ABSTRACT FROM AUTHOR]