Explore the vast range of titles available.

Intake of sweet food, beverages and added sugars has been linked with depressive symptoms in several populations. Aim of this study was to investigate systematically cross-sectional and prospective associations between sweet food/beverage intake, common mental disorder (CMD) and depression and to examine the role of reverse causation (influence of mood on intake) as potential explanation for the observed linkage. We analysed repeated measures (23,245 person-observations) from the Whitehall II study using random effects regression. Diet was assessed using food frequency questionnaires, mood using validated questionnaires. Cross-sectional analyses showed positive associations. In prospective analyses, men in the highest tertile of sugar intake from sweet food/beverages had a 23% increased odds of incident CMD after 5 years (95% CI: 1.02, 1.48) independent of health behaviours, socio-demographic and diet-related factors, adiposity and other diseases. The odds of recurrent depression were increased in the highest tertile for both sexes, but not statistically significant when diet-related factors were included in the model (OR 1.47; 95% CI: 0.98, 2.22). Neither CMD nor depression predicted intake changes. Our research confirms an adverse effect of sugar intake from sweet food/beverage on long-term psychological health and suggests that lower intake of sugar may be associated with better psychological health.

Prediabetes (intermediate hyperglycaemia) is a high-risk state for diabetes that is defined by glycaemic variables that are higher than normal, but lower than diabetes thresholds. 5–10% of people per year with prediabetes will progress to diabetes, with the same proportion converting back to normoglycaemia. Prevalence of prediabetes is increasing worldwide and experts have projected that more than 470 million people will have prediabetes by 2030. Prediabetes is associated with the simultaneous presence of insulin resistance and β-cell dysfunction—abnormalities that start before glucose changes are detectable. Observational evidence shows associations between prediabetes and early forms of nephropathy, chronic kidney disease, small fibre neuropathy, diabetic retinopathy, and increased risk of macrovascular disease. Multifactorial risk scores using non-invasive measures and blood-based metabolic traits, in addition to glycaemic values, could optimise estimation of diabetes risk. For prediabetic individuals, lifestyle modification is the cornerstone of diabetes prevention, with evidence of a 40–70% relative-risk reduction. Accumulating data also show potential benefits from pharmacotherapy.

BACKGROUND: Although overweight and obesity have been studied in relation to individual cardiometabolic diseases, their association with risk of cardiometabolic multimorbidity is poorly understood. Here we aimed to establish the risk of incident cardiometabolic multimorbidity (ie, at least two from: type 2 diabetes, coronary heart disease, and stroke) in adults who are overweight and obese compared with those who are a healthy weight. METHODS: We pooled individual-participant data for BMI and incident cardiometabolic multimorbidity from 16 prospective cohort studies from the USA and Europe. Participants included in the analyses were 35 years or older and had data available for BMI at baseline and for type 2 diabetes, coronary heart disease, and stroke at baseline and follow-up. We excluded participants with a diagnosis of diabetes, coronary heart disease, or stroke at or before study baseline. According to WHO recommendations, we classified BMI into categories of healthy (20·0-24·9 kg/m2), overweight (25·0-29·9 kg/m2), class I (mild) obesity (30·0-34·9 kg/m2), and class II and III (severe) obesity (≥35·0 kg/m2). We used an inclusive definition of underweight (<20 kg/m2) to achieve sufficient case numbers for analysis. The main outcome was cardiometabolic multimorbidity (ie, developing at least two from: type 2 diabetes, coronary heart disease, and stroke). Incident cardiometabolic multimorbidity was ascertained via resurvey or linkage to electronic medical records (including hospital admissions and death). We analysed data from each cohort separately using logistic regression and then pooled cohort-specific estimates using random-effects meta-analysis. FINDINGS: Participants were 120  813 adults (mean age 51·4 years, range 35-103; 71 445 women) who did not have diabetes, coronary heart disease, or stroke at study baseline (1973-2012). During a mean follow-up of 10·7 years (1995-2014), we identified 1627 cases of multimorbidity. After adjustment for sociodemographic and lifestyle factors, compared with individuals with a healthy weight, the risk of developing cardiometabolic multimorbidity in overweight individuals was twice as high (odds ratio [OR] 2·0, 95% CI 1·7-2·4; p<0·0001), almost five times higher for individuals with class I obesity (4·5, 3·5-5·8; p<0·0001), and almost 15 times higher for individuals with classes II and III obesity combined (14·5, 10·1-21·0; p<0·0001). This association was noted in men and women, young and old, and white and non-white participants, and was not dependent on the method of exposure assessment or outcome ascertainment. In analyses of different combinations of cardiometabolic conditions, odds ratios associated with classes II and III obesity were 2·2 (95% CI 1·9-2·6) for vascular disease only (coronary heart disease or stroke), 12·0 (8·1-17·9) for vascular disease followed by diabetes, 18·6 (16·6-20·9) for diabetes only, and 29·8 (21·7-40·8) for diabetes followed by vascular disease. INTERPRETATION: The risk of cardiometabolic multimorbidity increases as BMI increases; from double in overweight people to more than ten times in severely obese people compared with individuals with a healthy BMI. Our findings highlight the need for clinicians to actively screen for diabetes in overweight and obese patients with vascular disease, and pay increased attention to prevention of vascular disease in obese individuals with diabetes.

Little is known about the timing of changes in glucose metabolism before occurrence of type 2 diabetes. We aimed to characterise trajectories of fasting and postload glucose, insulin sensitivity, and insulin secretion in individuals who develop type 2 diabetes. We analysed data from our prospective occupational cohort study (Whitehall II study) of 6538 (71% male and 91% white) British civil servants without diabetes mellitus at baseline. During a median follow-up period of 9·7 years, 505 diabetes cases were diagnosed (49·1% on the basis of oral glucose tolerance test). We assessed retrospective trajectories of fasting and 2-h postload glucose, homoeostasis model assessment (HOMA) insulin sensitivity, and HOMA β-cell function from up to 13 years before diabetes diagnosis (diabetic group) or at the end of follow-up (non-diabetics). Multilevel models adjusted for age, sex, and ethnic origin confirmed that all metabolic measures followed linear trends in the group of non-diabetics (10 989 measurements), except for insulin secretion that did not change during follow-up. In the diabetic group (801 measurements), a linear increase in fasting glucose was followed by a steep quadratic increase (from 5·79 mmol/L to 7·40 mmol/L) starting 3 years before diagnosis of diabetes. 2-h postload glucose showed a rapid increase starting 3 years before diagnosis (from 7·60 mmol/L to 11·90 mmol/L), and HOMA insulin sensitivity decreased steeply during the 5 years before diagnosis (to 86·7%). HOMA β-cell function increased between years 4 and 3 before diagnosis (from 85·0% to 92·6%) and then decreased until diagnosis (to 62·4%). In this study, we show changes in glucose concentrations, insulin sensitivity, and insulin secretion as much as 3–6 years before diagnosis of diabetes. The description of biomarker trajectories leading to diabetes diagnosis could contribute to more-accurate risk prediction models that use repeated measures available for patients through regular check-ups. Medical Research Council (UK); Economic and Social Research Council (UK); British Heart Foundation (UK); Health and Safety Executive (UK); Department of Health (UK); National Institute of Health (USA); Agency for Health Care Policy Research (USA); the John D and Catherine T MacArthur Foundation (USA); and Academy of Finland (Finland).

Aortic stiffness is closely linked with cardiovascular diseases (CVDs), but recent studies suggest that it is also a risk factor for cognitive decline and dementia. However, the brain changes underlying this risk are unclear. We examined whether aortic stiffening during a 4-year follow-up in mid-to-late life was associated with brain structure and cognition in the Whitehall II Imaging Sub-study. The Whitehall II Imaging cohort is a randomly selected subset of the ongoing Whitehall II Study, for which participants have received clinical follow-ups for 30 years, across 12 phases. Aortic pulse wave velocity (PWV) was measured in 2007-2009 (Phase 9) and at a 4-year follow-up in 2012-2013 (Phase 11). Between 2012 and 2016 (Imaging Phase), participants received a multimodal 3T brain magnetic resonance imaging (MRI) scan and cognitive tests. Participants were selected if they had no clinical diagnosis of dementia and no gross brain structural abnormalities. Voxel-based analyses were used to assess grey matter (GM) volume, white matter (WM) microstructure (fractional anisotropy (FA) and diffusivity), white matter lesions (WMLs), and cerebral blood flow (CBF). Cognitive outcomes were performance on verbal memory, semantic fluency, working memory, and executive function tests. Of 542 participants, 444 (81.9%) were men. The mean (SD) age was 63.9 (5.2) years at the baseline Phase 9 examination, 68.0 (5.2) at Phase 11, and 69.8 (5.2) at the Imaging Phase. Voxel-based analysis revealed that faster rates of aortic stiffening in mid-to-late life were associated with poor WM microstructure, viz. lower FA, higher mean, and radial diffusivity (RD) in 23.9%, 11.8%, and 22.2% of WM tracts, respectively, including the corpus callosum, corona radiata, superior longitudinal fasciculus, and corticospinal tracts. Similar voxel-wise associations were also observed with follow-up aortic stiffness. Moreover, lower mean global FA was associated with faster rates of aortic stiffening (B = -5.65, 95% CI -9.75, -1.54, Bonferroni-corrected p < 0.0125) and higher follow-up aortic stiffness (B = -1.12, 95% CI -1.95, -0.29, Bonferroni-corrected p < 0.0125). In a subset of 112 participants who received arterial spin labelling scans, faster aortic stiffening was also related to lower cerebral perfusion in 18.4% of GM, with associations surviving Bonferroni corrections in the frontal (B = -10.85, 95% CI -17.91, -3.79, p < 0.0125) and parietal lobes (B = -12.75, 95% CI -21.58, -3.91, p < 0.0125). No associations with GM volume or WMLs were observed. Further, higher baseline aortic stiffness was associated with poor semantic fluency (B = -0.47, 95% CI -0.76 to -0.18, Bonferroni-corrected p < 0.007) and verbal learning outcomes (B = -0.36, 95% CI -0.60 to -0.12, Bonferroni-corrected p < 0.007). As with all observational studies, it was not possible to infer causal associations. The generalisability of the findings may be limited by the gender imbalance, high educational attainment, survival bias, and lack of ethnic and socioeconomic diversity in this cohort. Our findings indicate that faster rates of aortic stiffening in mid-to-late life were associated with poor brain WM microstructural integrity and reduced cerebral perfusion, likely due to increased transmission of pulsatile energy to the delicate cerebral microvasculature. Strategies to prevent arterial stiffening prior to this point may be required to offer cognitive benefit in older age. ClinicalTrials.gov NCT03335696.

There is uncertainty around the health impact and economic costs of the recent slowing of the historical decline in cardiovascular disease (CVD) incidence and the future impact on dementia and disability. Previously validated IMPACT Better Ageing Markov model for England and Wales, integrating English Longitudinal Study of Ageing (ELSA) data for 17,906 ELSA participants followed from 1998 to 2012, linked to NHS Hospital Episode Statistics. Counterfactual design comparing two scenarios: Scenario 1. CVD Plateau-age-specific CVD incidence remains at 2011 levels, thus continuing recent trends. Scenario 2. CVD Fall-age-specific CVD incidence goes on declining, following longer-term trends. The main outcome measures were age-related healthcare costs, social care costs, opportunity costs of informal care, and quality adjusted life years (valued at £60,000 per QALY). The total 10 year cumulative incremental net monetary cost associated with a persistent plateauing of CVD would be approximately £54 billion (95% uncertainty interval £14.3-£96.2 billion), made up of some £13 billion (£8.8-£16.7 billion) healthcare costs, £1.5 billion (-£0.9-£4.0 billion) social care costs, £8 billion (£3.4-£12.8 billion) informal care and £32 billion (£0.3-£67.6 billion) value of lost QALYs.

Studies of diet and depression have focused primarily on individual nutrients. To examine the association between dietary patterns and depression using an overall diet approach. Analyses were carried on data from 3486 participants (26.2% women, mean age 55.6 years) from the Whitehall II prospective cohort, in which two dietary patterns were identified: 'whole food' (heavily loaded by vegetables, fruits and fish) and 'processed food' (heavily loaded by sweetened desserts, fried food, processed meat, refined grains and high-fat dairy products). Self-reported depression was assessed 5 years later using the Center for Epidemiologic Studies - Depression (CES-D) scale. After adjusting for potential confounders, participants in the highest tertile of the whole food pattern had lower odds of CES-D depression (OR = 0.74, 95% CI 0.56-0.99) than those in the lowest tertile. In contrast, high consumption of processed food was associated with an increased odds of CES-D depression (OR = 1.58, 95% CI 1.11-2.23). In middle-aged participants, a processed food dietary pattern is a risk factor for CES-D depression 5 years later, whereas a whole food pattern is protective.

Although it has been hypothesized that the association of physical activity with depressive and anxiety symptoms is bidirectional, few studies have examined this issue in a prospective setting. We studied this bidirectional association using data on physical activity and symptoms of anxiety and depression at three points in time over 8 years. A total of 9,309 participants of the British Whitehall II prospective cohort study provided data on physical activity, anxiety and depression symptoms and 10 covariates at baseline in 1985. We analysed the associations of physical activity with anxiety and/or depression symptoms using multinomial logistic regression (with anxiety and depression symptoms as dependent variables) and binary logistic regression (with physical activity as the dependent variable). There was a cross-sectional inverse association between physical activity and anxiety and/or depressive symptoms at baseline (ORs between 0.63 and 0.72). In cumulative analyses, regular physical activity across all three data waves, but not irregular physical activity, was associated with reduced likelihood of depressive symptoms at follow-up (OR = 0.71, 95 % CI 0.54, 0.99). In a converse analysis, participants with anxiety and depression symptoms at baseline had higher odds of not meeting the recommended levels of physical activity at follow-up (OR = 1.79, 95 % CI 1.17, 2.74). This was also the case in individuals with anxiety and/or depression symptoms at both baseline and follow-up (OR = 1.70, 95 % CI 1.10, 2.63). The association between physical activity and symptoms of anxiety and/or depression appears to be bidirectional.

Background High-sensitivity cardiac troponin testing is a promising tool for cardiovascular risk prediction, but whether serial testing can dynamically predict risk is uncertain. We evaluated the trajectory of cardiac troponin I in the years prior to a cardiovascular event in the general population, and determine whether serial measurements could track risk within individuals. Methods In the Whitehall II cohort, high-sensitivity cardiac troponin I concentrations were measured on three occasions over a 15-year period. Time trajectories of troponin were constructed in those who died from cardiovascular disease compared to those who survived or died from other causes during follow up and these were externally validated in the HUNT Study. A joint model that adjusts for cardiovascular risk factors was used to estimate risk of cardiovascular death using serial troponin measurements. Results In 7,293 individuals (mean 58 ± 7 years, 29.4% women) cardiovascular and non-cardiovascular death occurred in 281 (3.9%) and 914 (12.5%) individuals (median follow-up 21.4 years), respectively. Troponin concentrations increased in those dying from cardiovascular disease with a steeper trajectory compared to those surviving or dying from other causes in Whitehall and HUNT ( P interaction  < 0.05 for both). The joint model demonstrated an independent association between temporal evolution of troponin and risk of cardiovascular death (HR per doubling, 1.45, 95% CI,1.33–1.75). Conclusions Cardiac troponin I concentrations increased in those dying from cardiovascular disease compared to those surviving or dying from other causes over the preceding decades. Serial cardiac troponin testing in the general population has potential to track future cardiovascular risk.

Current evidence on the association between body mass index (BMI) and age at menopause remains unclear. We investigated the relationship between BMI and age at menopause using data from 11 prospective studies. A total of 24,196 women who experienced menopause after recruitment was included. Baseline BMI was categorised according to the WHO criteria. Age at menopause, confirmed by natural cessation of menses for ≥ 12 months, was categorised as < 45 years (early menopause), 45-49, 50-51 (reference category), 52-53, 54-55, and ≥ 56 years (late age at menopause). We used multinomial logistic regression models to estimate multi variable relative risk ratios (RRRs) and 95% confidence intervals (CI) for the associations between BMI and age at menopause. The mean (standard deviation) age at menopause was 51.4 (3.3) years, with 2.5% of the women having early and 8.1% late menopause. Compared with those with normal BMI (18.5-24.9 kg/m²), underweight women were at a higher risk of early menopause (RRR 2.15, 95% CI 1.50-3.06), while overweight (1.52, 1.31-1.77) and obese women (1.54, 1.18-2.01) were at increased risk of late menopause. Overweight and obesity were also significantly associated with around 20% increased risk of menopause at ages 52-53 and 54-55 years. We observed no association between underweight and late menopause. The risk of early menopause was higher among obese women albeit not significant (1.23, 0.89-1.71). Underweight women had over twice the risk of experiencing early menopause, while overweight and obese women had over 50% higher risk of experiencing late menopause.