Longer sleep is associated with lower BMI and favorable metabolic profiles in UK adults: Findings from the National Diet and Nutrition Survey

Ever more evidence associates short sleep with increased risk of metabolic diseases such as obesity, which may be related to a predisposition to non-homeostatic eating. Few studies have concurrently determined associations between sleep duration and objective measures of metabolic health as well as sleep duration and diet, however. We therefore analyzed associations between sleep duration, diet and metabolic health markers in UK adults, assessing associations between sleep duration and 1) adiposity, 2) selected metabolic health markers and 3) diet, using National Diet and Nutrition Survey data. Adults (n = 1,615, age 19–65 years, 57.1% female) completed questions about sleep duration and 3 to 4 days of food diaries. Blood pressure and waist circumference were recorded. Fasting blood lipids, glucose, glycated haemoglobin (HbA1c), thyroid hormones, and high-sensitivity C-reactive protein (CRP) were measured in a subset of participants. We used regression analyses to explore associations between sleep duration and outcomes. After adjustment for age, ethnicity, sex, smoking, and socioeconomic status, sleep duration was negatively associated with body mass index (-0.46 kg/m2 per hour, 95% CI -0.69 to -0.24 kg/m2, p < 0.001) and waist circumference (-0.9 cm per hour, 95% CI -1.5 to -0.3cm, p = 0.004), and positively associated with high-density lipoprotein cholesterol (0.03 mmol/L per hour, 95% CI 0.00 to 0.05, p = 0.03). Sleep duration tended to be positively associated with free thyroxine levels and negatively associated with HbA1c and CRP (p = 0.09 to 0.10). Contrary to our hypothesis, sleep duration was not associated with any dietary measures (p ≥ 0.14). Together, our findings show that short-sleeping UK adults are more likely to have obesity, a disease with many comorbidities

Investigating the Bidirectional Associations of Adiposity with Sleep Duration in Older Adults: The English Longitudinal Study of Ageing (ELSA)

Cross-sectional analyses of adiposity and sleep duration in younger adults suggest that increased adiposity is associated with shorter sleep. Prospective studies have yielded mixed findings, and the direction of this association in older adults is unclear. We examined the cross-sectional and potential bi-directional, prospective associations between adiposity and sleep duration (covariates included demographics, health behaviours, and health problems) in 5,015 respondents from the English Longitudinal Study of Ageing (ELSA), at baseline and follow-up. Following adjustment for covariates, we observed no significant cross-sectional relationship between body mass index (BMI) and sleep duration [(unstandardized) B?=??0.28?minutes, (95% Confidence Intervals (CI)?=??0.012; 0.002), p?=?0.190], or waist circumference (WC) and sleep duration [(unstandardized) B?=??0.10?minutes, (95% CI?=??0.004; 0.001), p?=?0.270]. Prospectively, both baseline BMI [B?=??0.42?minutes, (95% CI?=??0.013; ?0.002), p?=?0.013] and WC [B?=??0.18?minutes, (95% CI?=??0.005; ?0.000), p?=?0.016] were associated with decreased sleep duration at follow-up, independently of covariates. There was, however, no association between baseline sleep duration and change in BMI or WC (p?>?0.05). In older adults, our findings suggested that greater adiposity is associated with decreases in sleep duration over time; however the effect was very small

Impact of time to antibiotics on clinical outcome in paediatric febrile neutropenia: a target trial emulation of 1685 episodes.

BACKGROUND: Prompt antibiotic administration for febrile neutropenia (FN) is standard of care, and targets of time to antibiotics (TTA) <60 min are common. We sought to determine the effect of TTA ≥60 versus <60 min on adverse outcomes (intensive care unit (ICU) admission or death) in children with cancer and FN. Effect modification by a decision rule that predicts infection (AUS-rule) and bacteraemia were also investigated. METHODS: The prospective, multi-centre (n = 8), Australian PICNICC study dataset was analysed. To control for confounding, we used outcome regression adjusted for propensity score modelled as restricted cubic spline with two degrees of freedom. The propensity score was estimated from a logistic regression model for the exposure on the confounders, identified a priori (age, sex, severely unwell, disease, chemotherapy intensity and site). TTA was defined as time from from emergency triage to first antibiotic dose. FINDINGS: 1685 FN episodes in 976 patients were included. Median TTA was 53 min (IQR 37-77 min, 1542 (92%) <120 min). An adverse outcome occurred in 43 (2.6%) episodes (39 ICU; 5 deaths). The confounder-adjusted point estimate suggested a lower risk for adverse outcome associated with TTA ≥60 min (RR 0.62, 95% CI 0.32-1.21), but the wide 95% CI precluded definitive judgement about strength and direction of the effect (unadjusted RR 0.52; 95% CI 0.26, 1.05). Similarly, although the point estimates were suggestive of a null association or reduced risk for adverse outcome associated with TTA ≥60 min for all comparisons across bacteraemia or AUS-rule strata, the 95% CIs were imprecise. INTERPRETATION: For children with FN, there was no definite evidence that TTA ≥60 min from hospital triage (but within 2 h), increased risk of adverse outcome or prolonged hospital admission. This study has important implications for FN TTA mandates, suggesting a more nuanced approach is required. FUNDING: National Health and Medical Research Council and Medical Research Future Fund

Recommended sleep duration is associated with higher consumption of fruits and vegetables; cross-sectional and prospective analyses from the UK Women’s Cohort Study

Background: High intakes of fruit and vegetable has been shown to protect against diseases and all-cause mortality however, the associations between sleep and fruit and vegetable consumption are not well characterized. This study aims to explore both cross-sectional and prospective associations between sleep duration and fruit and vegetable intakes in UK women. This is the first study to demonstrate the prospective association between sleep duration and fruit and vegetable consumption. Methods: Cross–sectional and prospective data were obtained from the UK Women’s Cohort Study. Sleep duration was assessed by self-report of average hours slept on weekdays and weekends and diet was assessed by a 4-day food diary at baseline and follow-up (~ 4 years later). Sleep duration was categorized as short (≤6 h/d), recommended (7–9 h/d) and long (≥9 h/d). Regression analyses adjusting for age, socio-economic status, smoking, ethnicity and total energy intake were used and restricted cubic spline models were developed to explore potential non-linear associations between sleep duration and fruit and vegetable intakes. Results: In adjusted cross-sectional analyses, short sleepers had on average 17 g/d (95% CI -30 to-4, p = 0.01) and long sleepers had 25 g/d (95% CI -39 to − 12, p < 0.001) less total fruits and vegetables compared to Recommended Sleepers (RS). In adjusted prospective analyses, short sleepers had on average 85 g/d (95% CI -144 to − 26, p = 0.005) less total fruits and vegetables in comparison to RS. Restricted cubic spline models showed that the cross-sectional (p < 0.001) and prospective (p = 0.001) associations between sleep duration and fruit and vegetable intakes were non-linear with women sleeping 7–9 h/d having the highest intakes. Conclusions: Fruit and vegetable consumption differed between sleep duration categories with UK women sleeping the recommended 7–9 h/day having the highest intake of fruits and vegetables in cross-sectional and prospective analyses. These findings suggest that sleeping the recommended duration is associated with higher consumption of fruits and vegetables. Sleep is an overlooked lifestyle factor in relation to fruit and vegetable consumption and more notice is vital. Further studies are required to clarify the underlying mechanisms for these associations

Notes for genera: basal clades of Fungi (including Aphelidiomycota, Basidiobolomycota, Blastocladiomycota, Calcarisporiellomycota, Caulochytriomycota, Chytridiomycota, Entomophthoromycota, Glomeromycota, Kickxellomycota, Monoblepharomycota, Mortierellomycota, Mucoromycota, Neocallimastigomycota, Olpidiomycota, Rozellomycota and Zoopagomycota)

Compared to the higher fungi (Dikarya), taxonomic and evolutionary studies on the basal clades of fungi are fewer in number. Thus, the generic boundaries and higher ranks in the basal clades of fungi are poorly known. Recent DNA based taxonomic studies have provided reliable and accurate information. It is therefore necessary to compile all available information since basal clades genera lack updated checklists or outlines. Recently, Tedersoo et al. (MycoKeys 13:1--20, 2016) accepted Aphelidiomycota and Rozellomycota in Fungal clade. Thus, we regard both these phyla as members in Kingdom Fungi. We accept 16 phyla in basal clades viz. Aphelidiomycota, Basidiobolomycota, Blastocladiomycota, Calcarisporiellomycota, Caulochytriomycota, Chytridiomycota, Entomophthoromycota, Glomeromycota, Kickxellomycota, Monoblepharomycota, Mortierellomycota, Mucoromycota, Neocallimastigomycota, Olpidiomycota, Rozellomycota and Zoopagomycota. Thus, 611 genera in 153 families, 43 orders and 18 classes are provided with details of classification, synonyms, life modes, distribution, recent literature and genomic data. Moreover, Catenariaceae Couch is proposed to be conserved, Cladochytriales Mozl.-Standr. is emended and the family Nephridiophagaceae is introduced

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021

Background Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions. Funding: Bill & Melinda Gates Foundation