Emily McFadden

The Relationship Between Obesity and Exposure to Light at Night: Cross-Sectional Analyses of Over 100,000 Women in the Breakthrough Generations Study

There has been a worldwide epidemic of obesity in recent decades. In animal studies, there is convincing evidence that light exposure causes weight gain, even when calorie intake and physical activity are held constant. Disruption of sleep and circadian rhythms by exposure to light at night (LAN) might be one mechanism contributing to the rise in obesity, but it has not been well-investigated in humans. Using multinomial logistic regression, we examined the association between exposure to LAN and obesity in questionnaire data from over 100,000 women in the Breakthrough Generations Study, a cohort study of women aged 16 years or older who were living in the United Kingdom and recruited during 2003-2012. The odds of obesity, measured using body mass index, waist:hip ratio, waist:height ratio, and waist circumference, increased with increasing levels of LAN exposure (P < 0.001), even after adjustment for potential confounders such as sleep duration, alcohol intake, physical activity, and current smoking. We found a significant association between LAN exposure and obesity which was not explained by potential confounders we could measure. While the possibility of residual confounding cannot be excluded, the pattern is intriguing, accords with the results of animal experiments, and warrants further investigation.

Timing of pubertal stages and breast cancer risk: the Breakthrough Generations Study

IntroductionBreast development and hormonal changes at puberty might affect breast cancer risk, but epidemiological analyses have focussed largely on age at menarche and not at other pubertal stages.MethodsWe investigated associations between the timing of pubertal stages and breast cancer risk using data from a cohort study of 104,931 women (Breakthrough Generations Study, UK, 2003–2013). Pubertal variables were reported retrospectively at baseline. Breast cancer risk was analysed using Cox regression models with breast cancer diagnosis as the outcome of interest, attained age as the underlying time variable, and adjustment for potentially confounding variables.ResultsDuring follow-up (mean = 4.1 years), 1094 breast cancers (including ductal carcinoma in situ) occurred. An increased breast cancer risk was associated with earlier thelarche (age when breast growth begins; HR [95% CI] = 1.23 [1.02, 1.48], 1 [referent] and 0.80 [0.69, 0.93] for ≤10, 11–12 and ≥13 years respectively), menarche (initiation of menses; 1.06 [0.93, 1.21], 1 [referent] and 0.78 [0.62, 0.99] for ≤12, 13–14 and ≥15 years), regular periods (0.99 [0.83, 1.18], 1 [referent] and 0.74 [0.59, 0.92] for ≤12, 13–14 and ≥15 years) and age reached adult height (1.25 [1.03, 1.52], 1 [referent] and 1.07 [0.87, 1.32] for ≤14, 15–16 and ≥17 years), and with increased time between thelarche and menarche (0.87 [0.65, 1.15], 1 [referent], 1.14 [0.96, 1.34] and 1.27 [1.04, 1.55] for <0, 0, 1 and ≥2 years), and shorter time between menarche and regular periods (1 [referent], 0.87 [0.73, 1.04] and 0.66 [0.50, 0.88] for 0, 1 and ≥2 years). These associations were generally similar when considered separately for premenopausal and postmenopausal breast cancer.ConclusionsBreast duct development may be a time of heightened susceptibility to risk of carcinogenesis, and greater attention needs to be given to the relation of breast cancer risk to the different stages of puberty.

Optimal strategies for monitoring lipid levels in patients at risk or with cardiovascular disease: a systematic review with statistical and cost-effectiveness modelling

BACKGROUND Various lipid measurements in monitoring/screening programmes can be used, alone or in cardiovascular risk scores, to guide treatment for prevention of cardiovascular disease (CVD). Because some changes in lipids are due to variability rather than true change, the value of lipid-monitoring strategies needs evaluation. OBJECTIVE To determine clinical value and cost-effectiveness of different monitoring intervals and different lipid measures for primary and secondary prevention of CVD. DATA SOURCES We searched databases and clinical trials registers from 2007 (including the Cochrane Central Register of Controlled Trials, MEDLINE, EMBASE, the Clinical Trials Register, the Current Controlled Trials register, and the Cumulative Index to Nursing and Allied Health Literature) to update and extend previous systematic reviews. Patient-level data from the Clinical Practice Research Datalink and St Lukes Hospital, Japan, were used in statistical modelling. Utilities and health-care costs were drawn from the literature. METHODS In two meta-analyses, we used prospective studies to examine associations of lipids with CVD and mortality, and randomised controlled trials to estimate lipid-lowering effects of atorvastatin doses. Patient-level data were used to estimate progression and variability of lipid measurements over time, and hence to model lipid-monitoring strategies. Results are expressed as rates of true-/false-positive and true-/false-negative tests for high lipid or high CVD risk. We estimated incremental costs per quality-adjusted life-year. RESULTS A total of 115 publications reported strength of association between different lipid measures and CVD events in 138 data sets. The summary adjusted hazard ratio per standard deviation of total cholesterol (TC) to high-density lipoprotein (HDL) cholesterol ratio was 1.25 (95% confidence interval 1.15 to 1.35) for CVD in a primary prevention population but heterogeneity was high (I(2) = 98%); similar results were observed for non-HDL cholesterol, apolipoprotein B and other ratio measures. Associations were smaller for other single lipid measures. Across 10 trials, low-dose atorvastatin (10 and 20 mg) effects ranged from a TC reduction of 0.92 mmol/l to 2.07 mmol/l, and low-density lipoprotein reduction of between 0.88 mmol/l and 1.86 mmol/l. Effects of 40 mg and 80 mg were reported by one trial each. For primary prevention, over a 3-year period, we estimate annual monitoring would unnecessarily treat 9 per 1000 more men (28 vs. 19 per 1000) and 5 per 1000 more women (17 vs. 12 per 1000) than monitoring every 3 years. However, annual monitoring would also undertreat 9 per 1000 fewer men (7 vs. 16 per 1000) and 4 per 1000 fewer women (7 vs. 11 per 1000) than monitoring at 3-year intervals. For secondary prevention, over a 3-year period, annual monitoring would increase unnecessary treatment changes by 66 per 1000 men and 31 per 1000 women, and decrease undertreatment by 29 per 1000 men and 28 per 1000 men, compared with monitoring every 3 years. In cost-effectiveness, strategies with increased screening/monitoring dominate. Exploratory analyses found that any unknown harms of statins would need utility decrements as large as 0.08 (men) to 0.11 (women) per statin user to reverse this finding in primary prevention. LIMITATION Heterogeneity in meta-analyses. CONCLUSIONS While acknowledging known and potential unknown harms of statins, we find that more frequent monitoring strategies are cost-effective compared with others. Regular lipid monitoring in those with and without CVD is likely to be beneficial to patients and to the health service. Future research should include trials of the benefits and harms of atorvastatin 40 and 80 mg, large-scale surveillance of statin safety, and investigation of the effect of monitoring on medication adherence. STUDY REGISTRATION This study is registered as PROSPERO CRD42013003727. FUNDING The National Institute for Health Research Health Technology Assessment programme.

Menopausal hormone therapy and breast cancer: what is the true size of the increased risk?

Background:Menopausal hormone therapy (MHT) increases breast cancer risk; however, most cohort studies omit MHT use after enrolment and many infer menopausal age.Methods:We used information from serial questionnaires from the UK Generations Study cohort to estimate hazard ratios (HRs) for breast cancer among post-menopausal women with known menopausal age, and examined biases induced when not updating data on MHT use and including women with inferred menopausal age.Results:Among women recruited in 2003–2009, at 6 years of follow-up, 58 148 had reached menopause and 96% had completed a follow-up questionnaire. Among 39 183 women with known menopausal age, 775 developed breast cancer, and the HR in relation to current oestrogen plus progestogen MHT use (based on 52 current oestrogen plus progestogen MHT users in breast cancer cases) relative to those with no previous MHT use was 2.74 (95% confidence interval (CI): 2.05–3.65) for a median duration of 5.4 years of current use, reaching 3.27 (95% CI: 1.53–6.99) at 15+ years of use. The excess HR was underestimated by 53% if oestrogen plus progestogen MHT use was not updated after recruitment, 13% if women with uncertain menopausal age were included, and 59% if both applied. The HR for oestrogen-only MHT was not increased (HR=1.00; 95% CI: 0.66–1.54).Conclusions:Lack of updating MHT status through follow-up and inclusion of women with inferred menopausal age is likely to result in substantial underestimation of the excess relative risks for oestrogen plus progestogen MHT use in studies with long follow-up, limited updating of exposures, and changing or short durations of use.

Domestic light at night and breast cancer risk: a prospective analysis of 105 000 UK women in the Generations Study

Background:Circadian disruption caused by exposure to light at night (LAN) has been proposed as a risk factor for breast cancer and a reason for secular increases in incidence. Studies to date have largely been ecological or case-control in design and findings have been mixed.Methods:We investigated the relationship between LAN and breast cancer risk in the UK Generations Study. Bedroom light levels and sleeping patterns at age 20 and at study recruitment were obtained by questionnaire. Analyses were conducted on 105 866 participants with no prior history of breast cancer. During an average of 6.1 years of follow-up, 1775 cases of breast cancer were diagnosed. Cox proportional hazard models were used to calculate hazard ratios (HRs), adjusting for potential confounding factors.Results:There was no association between LAN level and breast cancer risk overall (highest compared with lowest LAN level at recruitment: HR=1.01, 95% confidence interval (CI): 0.88–1.15), or for invasive (HR=0.98, 95% CI: 0.85–1.13) or in situ (HR=0.96, 95% CI: 0.83–1.11) breast cancer, or oestrogen-receptor (ER) positive (HR=0.98, 95% CI: 0.84–1.14); or negative (HR=1.16, 95% CI: 0.82–1.65) tumours separately. The findings did not differ by menopausal status. Adjusting for sleep duration, sleeping at unusual times (non-peak sleep) and history of night work did not affect the results. Night waking with exposure to light, occurring around age 20, was associated with a reduced risk of premenopausal breast cancer (HR for breast cancer overall=0.74, 95% CI: 0.55–0.99; HR for ER-positive breast cancer=0.69, 95% CI: 0.49–0.97).Conclusions:In this prospective cohort analysis of LAN, there was no evidence that LAN exposure increased the risk of subsequent breast cancer, although the suggestion of a lower breast cancer risk in pre-menopausal women with a history of night waking in their twenties may warrant further investigation.

Systematic review and metaanalysis comparing the bias and accuracy of the modification of diet in renal disease and chronic kidney disease epidemiology collaboration equations in community-based populations

BACKGROUND The majority of patients with chronic kidney disease are diagnosed and monitored in primary care. Glomerular filtration rate (GFR) is a key marker of renal function, but direct measurement is invasive; in routine practice, equations are used for estimated GFR (eGFR) from serum creatinine. We systematically assessed bias and accuracy of commonly used eGFR equations in populations relevant to primary care. CONTENT MEDLINE, EMBASE, and the Cochrane Library were searched for studies comparing measured GFR (mGFR) with eGFR in adult populations comparable to primary care and reporting both the Modification of Diet in Renal Disease (MDRD) and the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations based on standardized creatinine measurements. We pooled data on mean bias (difference between eGFR and mGFR) and on mean accuracy (proportion of eGFR within 30% of mGFR) using a random-effects inverse-variance weighted metaanalysis. We included 48 studies of 26875 patients that reported data on bias and/or accuracy. Metaanalysis of within-study comparisons in which both formulae were tested on the same patient cohorts using isotope dilution-mass spectrometry-traceable creatinine showed a lower mean bias in eGFR using CKD-EPI of 2.2 mL/min/1.73 m2 (95% CI, 1.1-3.2; 30 studies; I2 = 74.4%) and a higher mean accuracy of CKD-EPI of 2.7% (1.6-3.8; 47 studies; I2 = 55.5%). Metaregression showed that in both equations bias and accuracy favored the CKD-EPI equation at higher mGFR values. SUMMARY Both equations underestimated mGFR, but CKD-EPI gave more accurate estimates of GFR.

Implications of lower risk thresholds for statin treatment in primary prevention: analysis of CPRD and simulation modelling of annual cholesterol monitoring.

Objective To estimate numbers affected by a recent change in UK guidelines for statin use in primary prevention of cardiovascular disease. Method We modelled cholesterol ratio over time using a sample of 45,151 men (≥ 40 years) and 36,168 women (≥ 55 years) in 2006, without statin treatment or previous cardiovascular disease, from the Clinical Practice Research Datalink. Using simulation methods, we estimated numbers indicated for new statin treatment, if cholesterol was measured annually and used in the QRISK2 CVD risk calculator, using the previous 20% and newly recommended 10% thresholds. Results We estimate that 58% of men and 55% of women would be indicated for treatment by five years and 71% of men and 73% of women by ten years using the 20% threshold. Using the proposed threshold of 10%, 84% of men and 90% of women would be indicated for treatment by 5 years and 92% of men and 98% of women by ten years. Conclusion The proposed change of risk threshold from 20% to 10% would result in the substantial majority of those recommended for cholesterol testing being indicated for statin treatment. Implications depend on the value of statins in those at low to medium risk, and whether there are harms.

Handling missing data in propensity score estimation in comparative effectiveness evaluations: A systematic review

Aim Even though systematic reviews have examined how aspects of propensity score methods are used, none has reviewed how the challenge of missing data is addressed with these methods. This review there-fore describes how missing data are addressed with propensity score methods in observational comparative effectiveness studies. Methods Published articles on observational comparative effectiveness studies were extracted from MEDLINE and EMBASE databases. Results Our search yielded 167 eligible articles. Majority of these studies (114; 68%) conducted complete case analysis with only 53 of them stating this in the methods. Only 16 articles reported use of multiple imputation. Conclusion Few researchers use correct methods for handling missing data or reported missing data methodology which may lead to reporting biased findings.

Comparative effectiveness of injectable penicillin versus a combination of penicillin and gentamicin in children with pneumonia characterised by indrawing in Kenya: a retrospective observational study

Introduction WHO treatment guidelines are widely recommended for guiding treatment for millions of children with pneumonia every year across multiple low-income and middle-income countries. Guidelines are based on synthesis of available evidence that provides moderate certainty in evidence of effects for forms of pneumonia that can result in hospitalisation. However, trials have included fewer children from Africa than other settings, and it is suggested that African children with pneumonia have higher mortality. Thus, despite improving access to recommended treatments and deployment with high coverage of childhood vaccines, pneumonia remains one of the top causes of mortality for children in Kenya. Establishing whether there are benefits of alternative treatment regimens to help reduce mortality would require pragmatic clinical trials. However, these remain relatively expensive and time consuming. This protocol describes an approach to using secondary analysis of a new, large observational dataset as a potentially cheaper and quicker way to examine the comparative effectiveness of penicillin versus penicillin plus gentamicin in treatment of indrawing pneumonia. Addressing this question is important, as although it is now recommended that this form of pneumonia is treated with oral medication as an outpatient, it remains associated with non-trivial mortality that may be higher outside trial populations. Methods and analysis We will use a large observational dataset that captures data on all admissions to 13 Kenyan county hospitals. These data represent the findings of clinicians in practice and, because the system was developed for large observational research, pose challenges of non-random treatment allocation and missing data. To overcome these challenges, this analysis will use a rigorous approach to study design, propensity score methods and multiple imputation to minimise bias. Ethics and dissemination The primary data are held by hospitals participating in the Kenyan Clinical Information Network project with de-identifed data shared with the Kenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme for agreed analyses. The use of data for the analysis described received ethical clearance from the KEMRI scientific and ethical review committee. The findings of this analysis will be published.

Diabetes screening intervals based on risk stratification.

BackgroundGuidelines for frequency of Type 2 diabetes mellitus (DM) screening remain unclear, with proposed screening intervals typically based on expert opinion. This study aims to demonstrate that HbA1c screening intervals may differ substantially when considering individual risk for diabetes.MethodsThis was a multi-institutional retrospective open cohort study. Data were collected between April 1999 to March 2014 from one urban and one rural cohort in Japan. After categorization by age, we stratified individuals based on cardiovascular disease risk (Framingham 10-year cardiovascular risk score) and body mass index (BMI). We adapted a signal-to-noise method for distinguishing true HbA1c change from measurement error by constructing a linear random effect model to calculate signal and noise of HbA1c. Screening interval for HbA1c was defined as informative when the signal-to-noise ratio exceeded 1.ResultsAmong 96,456 healthy adults, 46,284 (48.0%) were male; age (range) and mean HbA1c (SD) were 48 (30–74) years old and 5.4 (0.4)%, respectively. As risk increased among those 30–44 years old, HbA1c screening intervals for detecting Type 2 DM consistently decreased: from 10.5 (BMI <18.5) to 2.4 (BMI > 30) years, and from 8.0 (Framingham Risk Score <10%) to 2.0 (Framingham Risk Score ≥20%) years. This trend was consistent in other age and risk groups as well; among obese 30–44 year olds, we found substantially shorter intervals compared to other groups.ConclusionHbA1c screening intervals for identification of DM vary substantially by risk factors. Risk stratification should be applied when deciding an optimal HbA1c screening interval in the general population to minimize overdiagnosis and overtreatment.