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Diagnosing heart failure (HF) in primary care can be challenging, especially
in elderly patients with comorbidities. Insight in the prevalence, age,
comorbidity and routine practice of diagnosing HF in general practice may
improve the process of diagnosing HF.
To examine the prevalence of HF in relation to ageing and comorbidities, and
routine practice of diagnosing HF in general practice.
A retrospective cohort study was performed using data from electronic health
records of 56 320 adult patients of 11 general practices. HF patients were
compared with patients without HF using descriptive analyses and
χ2 tests. The following comorbidities were considered: chronic
obstructive pulmonary disorder (COPD), diabetes mellitus (DM), hypertension,
anaemia and renal function disorder (RFD). Separate analyses were performed
for men and women.
The point prevalence of HF was 1.2% (95% confidence interval
1.13–1.33) and increased with each age category from 0.04%
(18–44 years) to 20.9% (⩾85 years). All studied
comorbidities were significantly (P<0.001) more
common in HF patients than in patients without HF: COPD (24.1% versus
3.1%), DM (34.7% versus 6.5%), hypertension
(52.7% versus 16.0%), anaemia (10.9% versus
2.3%) and RFD (61.8% versus 7.5%). N-terminal pro-BNP
(NT-proBNP) was recorded in 38.1% of HF patients.
HF is highly associated with ageing and comorbidities. Diagnostic use of
NT-proBNP in routine primary care seems underutilized. Instruction of GPs to
determine NT-proBNP in patients suspected of HF is recommended, especially
In elderly patients with comorbidities.
We analyzed intestinal contents of two late-glacial mastodons preserved in lake sediments in Ohio (Burning Tree mastodon) and Michigan (Heisler mastodon). A multi-proxy suite of macrofossils and microfossils provided unique insights into what these individuals had eaten just before they died and added significantly to knowledge of mastodon diets. We reconstructed the mastodons’ habitats with similar multi-proxy analyses of the embedding lake sediments. Non-pollen palynomorphs, especially spores of coprophilous fungi differentiated intestinal and environmental samples. The Burning Tree mastodon gut sample originates from the small intestine. The Heisler mastodon sample is part of the large intestine to which humans had added clastic material to anchor parts of the carcass under water to cache the meat. Both carcasses had been dismembered, suggesting that the mastodons had been hunted or scavenged, in line with other contemporaneous mastodon finds and the timing of early human incursion into the Midwest. Both mastodons lived in mixed coniferous-deciduous late-glacial forests. They browsed tree leaves and twigs, especially Picea. They also ate sedge-swamp plants and drank the lake water. Our multi-proxy estimates for a spring/summer season of death contrast with autumn estimates derived from prior tusk analyses. We document the recovered fossil remains with photographs.
The north-west European population of Bewick’s Swan Cygnus columbianus bewickii declined by 38% between 1995 and 2010 and is listed as ‘Endangered’ on the European Red List of birds. Here, we combined information on food resources within the landscape with long-term data on swan numbers, habitat use, behaviour and two complementary measures of body condition, to examine whether changes in food type and availability have influenced the Bewick’s Swan’s use of their main wintering site in the UK, the Ouse Washes and surrounding fens. Maximum number of Bewick’s Swans rose from 620 in winter 1958/59 to a high of 7,491 in winter 2004/05, before falling to 1,073 birds in winter 2013/14. Between winters 1958/59 and 2014/15 the Ouse Washes supported between 0.5 and 37.9 % of the total population wintering in north-west Europe (mean ± 95 % CI = 18.1 ± 2.4 %). Swans fed on agricultural crops, shifting from post-harvest remains of root crops (e.g. sugar beet and potatoes) in November and December to winter-sown cereals (e.g. wheat) in January and February. Inter-annual variation in the area cultivated for these crops did not result in changes in the peak numbers of swans occurring on the Ouse Washes. Behavioural and body condition data indicated that food supplies on the Ouse Washes and surrounding fens remain adequate to allow the birds to gain and maintain good body condition throughout winter with no increase in foraging effort. Our findings suggest that the recent decline in numbers of Bewick’s Swans at this internationally important site was not linked to inadequate food resources.
Traditionally, personalised nutrition was delivered at an individual level. However, the concept of delivering tailored dietary advice at a group level through the identification of metabotypes or groups of metabolically similar individuals has emerged. Although this approach to personalised nutrition looks promising, further work is needed to examine this concept across a wider population group. Therefore, the objectives of this study are to: (1) identify metabotypes in a European population and (2) develop targeted dietary advice solutions for these metabotypes. Using data from the Food4Me study (n 1607), k-means cluster analysis revealed the presence of three metabolically distinct clusters based on twenty-seven metabolic markers including cholesterol, individual fatty acids and carotenoids. Cluster 2 was identified as a metabolically healthy metabotype as these individuals had the highest Omega-3 Index (6·56 (sd 1·29) %), carotenoids (2·15 (sd 0·71) µm) and lowest total saturated fat levels. On the basis of its fatty acid profile, cluster 1 was characterised as a metabolically unhealthy cluster. Targeted dietary advice solutions were developed per cluster using a decision tree approach. Testing of the approach was performed by comparison with the personalised dietary advice, delivered by nutritionists to Food4Me study participants (n 180). Excellent agreement was observed between the targeted and individualised approaches with an average match of 82 % at the level of delivery of the same dietary message. Future work should ascertain whether this proposed method could be utilised in a healthcare setting, for the rapid and efficient delivery of tailored dietary advice solutions.
Objectives: Multicomponent interventions (MCIs), consisting of at least two interventions, are common in rehabilitation and other healthcare fields. When the effectiveness of the MCI versus that of its single interventions is comparable or unknown, evidence of their expected incremental cost-effectiveness can be helpful in deciding which intervention to recommend. As such evidence often is unavailable this study proposes an approach to estimate what is more cost-effective; the MCI or the single intervention(s).
Methods: We reviewed the literature for potential methods. Of those identified, headroom analysis was selected as the most suitable basis for developing the approach, based on the criteria of being able to estimate the cost-effectiveness of the single interventions versus that of the MCI (a) within a limited time frame, (b) in the absence of full data, and (c) taking into account carry-over and interaction effects. We illustrated the approach with an MCI for cancer survivors.
Results: The approach starts with analyzing the costs of the MCI. Given a specific willingness-to-pay-value, it is analyzed how much effectiveness the MCI would need to generate to be considered cost-effective, and if this is likely to be attained. Finally, the cost-effectiveness of the single interventions relative to the potential of the MCI for being cost-effective can be compared.
Conclusions: A systematic approach using headroom analysis was developed for estimating whether an MCI is likely to be more cost effective than one (or more) of its single interventions.
Individual response to dietary interventions can be highly variable. The phenotypic characteristics of those who will respond positively to personalised dietary advice are largely unknown. The objective of this study was to compare the phenotypic profiles of differential responders to personalised dietary intervention, with a focus on total circulating cholesterol. Subjects from the Food4Me multi-centre study were classified as responders or non-responders to dietary advice on the basis of the change in cholesterol level from baseline to month 6, with lower and upper quartiles defined as responder and non-responder groups, respectively. There were no significant differences between demographic and anthropometric profiles of the groups. Furthermore, with the exception of alcohol, there was no significant difference in reported dietary intake, at baseline. However, there were marked differences in baseline fatty acid profiles. The responder group had significantly higher levels of stearic acid (18 : 0, P=0·034) and lower levels of palmitic acid (16 : 0, P=0·009). Total MUFA (P=0·016) and total PUFA (P=0·008) also differed between the groups. In a step-wise logistic regression model, age, baseline total cholesterol, glucose, five fatty acids and alcohol intakes were selected as factors that successfully discriminated responders from non-responders, with sensitivity of 82 % and specificity of 83 %. The successful delivery of personalised dietary advice may depend on our ability to identify phenotypes that are responsive. The results demonstrate the potential use of metabolic profiles in identifying response to an intervention and could play an important role in the development of precision nutrition.
To characterise clusters of individuals based on adherence to dietary recommendations and to determine whether changes in Healthy Eating Index (HEI) scores in response to a personalised nutrition (PN) intervention varied between clusters.
Food4Me study participants were clustered according to whether their baseline dietary intakes met European dietary recommendations. Changes in HEI scores between baseline and month 6 were compared between clusters and stratified by whether individuals received generalised or PN advice.
Individuals in cluster 1 (C1) met all recommended intakes except for red meat, those in cluster 2 (C2) met two recommendations, and those in cluster 3 (C3) and cluster 4 (C4) met one recommendation each. C1 had higher intakes of white fish, beans and lentils and low-fat dairy products and lower percentage energy intake from SFA (P<0·05). C2 consumed less chips and pizza and fried foods than C3 and C4 (P<0·05). C1 were lighter, had lower BMI and waist circumference than C3 and were more physically active than C4 (P<0·05). More individuals in C4 were smokers and wanted to lose weight than in C1 (P<0·05). Individuals who received PN advice in C4 reported greater improvements in HEI compared with C3 and C1 (P<0·05).
The cluster where the fewest recommendations were met (C4) reported greater improvements in HEI following a 6-month trial of PN whereas there was no difference between clusters for those randomised to the Control, non-personalised dietary intervention.
To characterise participants who dropped out of the Food4Me Proof-of-Principle study.
The Food4Me study was an Internet-based, 6-month, four-arm, randomised controlled trial. The control group received generalised dietary and lifestyle recommendations, whereas participants randomised to three different levels of personalised nutrition (PN) received advice based on dietary, phenotypic and/or genotypic data, respectively (with either more or less frequent feedback).
Seven recruitment sites: UK, Ireland, The Netherlands, Germany, Spain, Poland and Greece.
Adults aged 18–79 years (n 1607).
A total of 337 (21 %) participants dropped out during the intervention. At baseline, dropouts had higher BMI (0·5 kg/m2; P<0·001). Attrition did not differ significantly between individuals receiving generalised dietary guidelines (Control) and those randomised to PN. Participants were more likely to drop out (OR; 95 % CI) if they received more frequent feedback (1·81; 1·36, 2·41; P<0·001), were female (1·38; 1·06, 1·78; P=0·015), less than 45 years old (2·57; 1·95, 3·39; P<0·001) and obese (2·25; 1·47, 3·43; P<0·001). Attrition was more likely in participants who reported an interest in losing weight (1·53; 1·19, 1·97; P<0·001) or skipping meals (1·75; 1·16, 2·65; P=0·008), and less likely if participants claimed to eat healthily frequently (0·62; 0·45, 0·86; P=0·003).
Attrition did not differ between participants receiving generalised or PN advice but more frequent feedback was related to attrition for those randomised to PN interventions. Better strategies are required to minimise dropouts among younger and obese individuals participating in PN interventions and more frequent feedback may be an unnecessary burden.
The interplay between the fat mass- and obesity-associated (FTO) gene variants and diet has been implicated in the development of obesity. The aim of the present analysis was to investigate associations between FTO genotype, dietary intakes and anthropometrics among European adults. Participants in the Food4Me randomised controlled trial were genotyped for FTO genotype (rs9939609) and their dietary intakes, and diet quality scores (Healthy Eating Index and PREDIMED-based Mediterranean diet score) were estimated from FFQ. Relationships between FTO genotype, diet and anthropometrics (weight, waist circumference (WC) and BMI) were evaluated at baseline. European adults with the FTO risk genotype had greater WC (AAv. TT: +1·4 cm; P=0·003) and BMI (+0·9 kg/m2; P=0·001) than individuals with no risk alleles. Subjects with the lowest fried food consumption and two copies of the FTO risk variant had on average 1·4 kg/m2 greater BMI (Ptrend=0·028) and 3·1 cm greater WC (Ptrend=0·045) compared with individuals with no copies of the risk allele and with the lowest fried food consumption. However, there was no evidence of interactions between FTO genotype and dietary intakes on BMI and WC, and thus further research is required to confirm or refute these findings.
An efficient and robust method to measure vitamin D (25-hydroxy vitamin D3 (25(OH)D3) and 25-hydroxy vitamin D2 in dried blood spots (DBS) has been developed and applied in the pan-European multi-centre, internet-based, personalised nutrition intervention study Food4Me. The method includes calibration with blood containing endogenous 25(OH)D3, spotted as DBS and corrected for haematocrit content. The methodology was validated following international standards. The performance characteristics did not reach those of the current gold standard liquid chromatography-MS/MS in plasma for all parameters, but were found to be very suitable for status-level determination under field conditions. DBS sample quality was very high, and 3778 measurements of 25(OH)D3 were obtained from 1465 participants. The study centre and the season within the study centre were very good predictors of 25(OH)D3 levels (P<0·001 for each case). Seasonal effects were modelled by fitting a sine function with a minimum 25(OH)D3 level on 20 January and a maximum on 21 July. The seasonal amplitude varied from centre to centre. The largest difference between winter and summer levels was found in Germany and the smallest in Poland. The model was cross-validated to determine the consistency of the predictions and the performance of the DBS method. The Pearson’s correlation between the measured values and the predicted values was r 0·65, and the sd of their differences was 21·2 nmol/l. This includes the analytical variation and the biological variation within subjects. Overall, DBS obtained by unsupervised sampling of the participants at home was a viable methodology for obtaining vitamin D status information in a large nutritional study.
In this study, we prospectively examined developmental trajectories of five anxiety disorder symptom dimensions (generalized anxiety disorder, panic disorder, school anxiety, separation anxiety disorder, and social anxiety disorder) from early to late adolescence in a community sample of 239 adolescents, assessed annually over 8 years. Latent growth modeling indicated different developmental trajectories from early into late adolescence for the different anxiety disorder symptoms, with some symptoms decreasing and other symptoms increasing over time. Sex differences in developmental trajectories were found for some symptoms, but not all. Furthermore, latent class growth analysis identified a normal developmental profile (including a majority of adolescents reporting persistent low anxiety disorder symptoms over 8 years) and an at-risk developmental profile (including a minority of adolescents reporting persistent high anxiety disorder symptoms over 8 years) for all of the anxiety disorder symptom dimensions except panic disorder. Additional analyses longitudinally supported the validity of these normal and at-risk developmental profiles and suggested differential associations between different anxiety disorder symptom dimensions and developmental trajectories of substance use, parenting, and identity development. Taken together, our results emphasize the importance of examining separate dimensions of anxiety disorder symptoms in contrast to a using a global, one-dimensional approach to anxiety.
A grazing study was undertaken to examine the effect of maintaining three levels of pre-grazing herbage mass (HM) on dairy cow performance, grass dry matter (DM) production and output from perennial ryegrass (Lolium perenne L.) pastures. Cows were randomly assigned to one of three pre-grazing HM treatments: 1150 – Low HM (L), 1400 – Medium HM (M) or 2000 kg DM/ha – High HM (H). Herbage accumulation under grazing was lowest (P<0.01) on the L treatment and cows grazing the L pastures required more grass silage supplementation during the grazing season (+73 kg DM/cow) to overcome pasture deficits due to lower pasture growth rates (P<0.05). Treatment did not affect daily milk production or pasture intake, although cows grazing the L pastures had to graze a greater daily area (P<0.01) and increase grazing time (P<0.05) to compensate for a lower pre-grazing HM (P<0.01). The results indicate that, while pre-grazing HM did not influence daily milk yield per cow, adapting the practise of grazing low HM (1150 kg DM/ha) pasture reduces pasture DM production and at a system level may increase the requirement for imported feed.
The application of metabolomics in multi-centre studies is increasing. The aim of the present study was to assess the effects of geographical location on the metabolic profiles of individuals with the metabolic syndrome. Blood and urine samples were collected from 219 adults from seven European centres participating in the LIPGENE project (Diet, genomics and the metabolic syndrome: an integrated nutrition, agro-food, social and economic analysis). Nutrient intakes, BMI, waist:hip ratio, blood pressure, and plasma glucose, insulin and blood lipid levels were assessed. Plasma fatty acid levels and urine were assessed using a metabolomic technique. The separation of three European geographical groups (NW, northwest; NE, northeast; SW, southwest) was identified using partial least-squares discriminant analysis models for urine (R2X: 0·33, Q2: 0·39) and plasma fatty acid (R2X: 0·32, Q2: 0·60) data. The NW group was characterised by higher levels of urinary hippurate and N-methylnicotinate. The NE group was characterised by higher levels of urinary creatine and citrate and plasma EPA (20 : 5 n-3). The SW group was characterised by higher levels of urinary trimethylamine oxide and lower levels of plasma EPA. The indicators of metabolic health appeared to be consistent across the groups. The SW group had higher intakes of total fat and MUFA compared with both the NW and NE groups (P≤ 0·001). The NE group had higher intakes of fibre and n-3 and n-6 fatty acids compared with both the NW and SW groups (all P< 0·001). It is likely that differences in dietary intakes contributed to the separation of the three groups. Evaluation of geographical factors including diet should be considered in the interpretation of metabolomic data from multi-centre studies.
The objective of this experiment was to investigate the effect of four perennial ryegrass cultivars: Bealey, Astonenergy, Spelga and AberMagic on the milk yield and milk composition of grazing dairy cows. Two 4 × 4 latin square experiments were completed, one during the reproductive and the other during the vegetative growth phase of the cultivars. Thirty-two Holstein–Friesian dairy cows were divided into four groups, with each group assigned 17 days on each cultivar during both experiments. Within each observation period, milk yield and milk composition, sward morphology and pasture chemical composition were measured. During the reproductive growth phase, organic matter digestibility (OMD) was greater for Bealey and Astonenergy (P < 0.001; +1.6%). AberMagic contained a higher stem proportion (P < 0.01; +0.06) and a longer sheath height (P < 0.001; +1.9 cm). Consequently, cows grazing AberMagic recorded a lower milk yield (P < 0.001; −1.5 kg/day) and a lower milk solids yield (P < 0.001; −0.13 kg/day). During the vegetative growth phase, OMD was greater (P < 0.001; +1.1%) for Bealey, whereas the differences between the cultivars in terms of sward structure were smaller and did not appear to influence animal performance. As a result, cows grazing Bealey recorded a higher milk yield (P < 0.001; +0.9 kg/day) and a higher milk solids yield (P < 0.01; +0.08 kg/day). It was concluded that grass cultivar did influence milk yield due to variations in sward structure and chemical composition.
Energy is essential for human development and energy systems are a crucial entry point for addressing the most pressing global challenges of the 21st century, including sustainable economic, and social development, poverty eradication, adequate food production and food security, health for all, climate protection, conservation of ecosystems, peace, and security. Yet, more than a decade into the 21st century, current energy systems do not meet these challenges.
In this context, two considerations are important. The first is the capacity and agility of the players within the energy system to seize opportunities in response to these challenges. The second is the response capacity of the energy system itself, as the investments are long-term and tend to follow standard financial patterns, mainly avoiding risks and price instabilities. This traditional approach does not embrace the transformation needed to respond properly to the economic, environmental, and social sustainability challenges of the 21st century.
A major transformation is required to address these challenges and to avoid potentially catastrophic consequences for human and planetary systems. The GEA identifies strategies that could help resolve the multiple challenges simultaneously and bring multiple benefits. Their successful implementation requires determined, sustained, and immediate action.
The industrial revolution catapulted humanity onto an explosive development path, whereby reliance on muscle power and traditional biomass was replaced mostly by fossil fuels. In 2005, approximately 78% of global energy was based on fossil energy sources that provided abundant and ever cheaper energy services to more than half the world's population.
Energy is essential for human development and energy systems are a crucial entry point for addressing the most pressing global challenges of the 21st century, including sustainable economic and social development, poverty eradication, adequate food production and food security, health for all, climate protection, conservation of ecosystems, peace and security. Yet, more than a decade into the 21st century, current energy systems do not meet these challenges.
A major transformation is therefore required to address these challenges and to avoid potentially catastrophic future consequences for human and planetary systems. The Global Energy Assessment (GEA) demonstrates that energy system change is the key for addressing and resolving these challenges. The GEA identifies strategies that could help resolve the multiple challenges simultaneously and bring multiple benefits. Their successful implementation requires determined, sustained and immediate action.
Transformative change in the energy system may not be internally generated; due to institutional inertia, incumbency and lack of capacity and agility of existing organizations to respond effectively to changing conditions. In such situations clear and consistent external policy signals may be required to initiate and sustain the transformative change needed to meet the sustainability challenges of the 21st century.
The industrial revolution catapulted humanity onto an explosive development path, whereby, reliance on muscle power and traditional biomass was replaced mostly by fossil fuels. In 2005, some 78% of global energy was based on fossil energy sources that provided abundant and ever cheaper energy services to more than half the people in the world.