Trade-offs constrain the success of glyphosate-free farming.

Glyphosate, the most widely used herbicide, is linked with environmental harm and there is a drive to replace it in agricultural systems. We model the impacts of discontinuing glyphosate use and replacing it with cultural control methods. We simulate winter wheat arable systems reliant on glyphosate and typical in northwest Europe. Removing glyphosate was projected to increase weed abundance, herbicide risk to the environment, and arable plant diversity and decrease food production. Weed communities with evolved resistance to non-glyphosate herbicides were not projected to be disproportionately affected by removing glyphosate, despite the lack of alternative herbicidal control options. Crop rotations with more spring cereals or grass leys for weed control increased arable plant diversity. Stale seedbed techniques such as delayed drilling and choosing ploughing instead of minimum tillage had varying effects on weed abundance, food production, and profitability. Ploughing was the most effective alternative to glyphosate for long-term weed control while maintaining production and profit. Our findings emphasize the need for careful consideration of trade-offs arising in scenarios where glyphosate is removed. Integrated Weed Management (IWM) with more use of cultural control methods offers the potential to reduce chemical use but is sensitive to seasonal variability and can incur negative environmental and economic impacts.

Adherence to guideline recommendations for Barrett's esophagus (BE) surveillance endoscopies: Effects of dedicated BE endoscopy lists.

Background and study aims For non-dysplastic Barrett's Esophagus (BE) patients, guidelines recommend endoscopic surveillance every 3 to 5 years with four-quadrant random biopsies every 2 cm of BE length. Adherence to these guidelines is low in clinical practice. Pooling BE surveillance endoscopies on dedicated endoscopy lists performed by dedicated endoscopists could possibly enhance guideline adherence, detection of visible lesions, and dysplasia detection rates (DDRs). Patients and methods Data were used from the ACID-study (Netherlands Trial Registry NL8214), a prospective trial of BE surveillance in the Netherlands. BE patients with known or previously treated dysplasia were excluded. Guideline adherence, detection of visible lesions, and DDRs were compared for patients on dedicated and general endoscopy lists. Results A total of 1,244 patients were included, 318 on dedicated lists and 926 on general lists. Endoscopies on dedicated lists showed significantly higher adherence to the random biopsy protocol (85% vs. 66%, P <0.01) and recommended surveillance intervals (60% vs. 47%, P <0.01) compared to general lists. Detection of visible lesions (8.8% vs. 8.1%, P =0.79) and DDRs were not significantly different (6.9% and 6.6%, P =0.94). None (0.0%) of the patients scheduled on dedicated lists and 10 (1.1%) on general lists were diagnosed with esophageal adenocarcinoma ( P =0.07). In multivariable analysis, dedicated lists were significantly associated with biopsy protocol adherence and adherence to surveillance interval recommendations with odds ratios of 4.45 (95% confidence interval [CI] 2.07-9.57) and 1.64 (95% CI 1.03-2.61), respectively. Conclusions Dedicated endoscopy lists are associated with better adherence to the random biopsy protocol and surveillance interval recommendations.

A loss function to evaluate agricultural decision-making under uncertainty: a case study of soil spectroscopy.

Modern sensor technologies can provide detailed information about soil variation which allows for more precise application of fertiliser to minimise environmental harm imposed by agriculture. However, growers should lose neither income nor yield from associated uncertainties of predicted nutrient concentrations and thus one must acknowledge and account for uncertainties. A framework is presented that accounts for the uncertainty and determines the cost-benefit of data on available phosphorus (P) and potassium (K) in the soil determined from sensors. For four fields, the uncertainty associated with variation in soil P and K predicted from sensors was determined. Using published fertiliser dose-yield response curves for a horticultural crop the effect of estimation errors from sensor data on expected financial losses was quantified. The expected losses from optimal precise application were compared with the losses expected from uniform fertiliser application (equivalent to little or no knowledge on soil variation). The asymmetry of the loss function meant that underestimation of P and K generally led to greater losses than the losses from overestimation. This study shows that substantial financial gains can be obtained from sensor-based precise application of P and K fertiliser, with savings of up to £121 ha-1 for P and up to £81 ha-1 for K, with concurrent environmental benefits due to a reduction of 4-17 kg ha-1 applied P fertiliser when compared with uniform application. Supplementary Information: The online version contains supplementary material available at 10.1007/s11119-022-09887-2.

Cereal grain mineral micronutrient and soil chemistry data from GeoNutrition surveys in Ethiopia and Malawi.

The dataset comprises primary data for the concentration of 29 mineral micronutrients in cereal grains and up to 84 soil chemistry properties from GeoNutrition project surveys in Ethiopia and Malawi. The work provided insights on geospatial variation in the micronutrient concentration in staple crops, and the potential influencing soil factors. In Ethiopia, sampling was conducted in Amhara, Oromia, and Tigray regions, during the late-2017 and late-2018 harvest seasons. In Malawi, national-scale sampling was conducted during the April-June 2018 harvest season. The concentrations of micronutrients in grain were measured using inductively coupled plasma mass spectrometry (ICP-MS). Soil chemistry properties reported include soil pH; total soil nitrogen; total soil carbon (C); soil organic C; effective cation exchange capacity and exchangeable cations; a three-step sequential extraction scheme for the fractionation of sulfur and selenium; available phosphate; diethylenetriaminepentaacetic acid (DTPA)-extractable trace elements; extractable trace elements using 0.01 M Ca(NO3)2 and 0.01 M CaCl2; and isotopically exchangeable Zn. These data are reported here according to FAIR data principles to enable users to further explore agriculture-nutrition linkages.

Soil and landscape factors influence geospatial variation in maize grain zinc concentration in Malawi.

Dietary zinc (Zn) deficiency is widespread globally, and in particular among people in sub-Saharan Africa (SSA). In Malawi, dietary sources of Zn are dominated by maize and spatially dependent variation in grain Zn concentration, which will affect dietary Zn intake, has been reported at distances of up to ~ 100 km. The aim of this study was to identify potential soil properties and environmental covariates which might explain this longer-range spatial variation in maize grain Zn concentration. Data for maize grain Zn concentrations, soil properties, and environmental covariates were obtained from a spatially representative survey in Malawi (n = 1600 locations). Labile and non-labile soil Zn forms were determined using isotopic dilution methods, alongside conventional agronomic soil analyses. Soil properties and environmental covariates as potential predictors of the concentration of Zn in maize grain were tested using a priori expert rankings and false discovery rate (FDR) controls within the linear mixed model (LMM) framework that informed the original survey design. Mean and median grain Zn concentrations were 21.8 and 21.5 mg kg-1, respectively (standard deviation 4.5; range 10.0-48.1). A LMM for grain Zn concentration was constructed for which the independent variables: soil pH(water), isotopically exchangeable Zn (ZnE), and diethylenetriaminepentaacetic acid (DTPA) extractable Zn (ZnDTPA) had predictive value (p < 0.01 in all cases, with FDR controlled at < 0.05). Downscaled mean annual temperature also explained a proportion of the spatial variation in grain Zn concentration. Evidence for spatially dependent variation in maize grain Zn concentrations in Malawi is robust within the LMM framework used in this study, at distances of up to ~ 100 km. Spatial predictions from this LMM provide a basis for further investigation of variations in the contribution of staple foods to Zn nutrition, and where interventions to increase dietary Zn intake (e.g. biofortification) might be most effective. Other soil and landscape factors influencing spatially dependent variation in maize grain Zn concentration, along with factors operating over shorter distances such as choice of crop variety and agronomic practices, require further exploration beyond the scope of the design of this survey.

Comparing the effect of different sample conditions and spectral libraries on the prediction accuracy of soil properties from near- and mid-infrared spectra at the field-scale.

The prediction accuracy of soil properties by proximal soil sensing has made their application more practical. However, in order to gain sufficient accuracy, samples are typically air-dried and milled before spectral measurements are made. Calibration of the spectra is usually achieved by making wet chemistry measurements on a subset of the field samples and local regression models fitted to aid subsequent prediction. Both sample handling and wet chemistry can be labour and resource intensive. This study aims to quantify the uncertainty associated with soil property estimates from different methods to reduce effort of field-scale calibrations of soil spectra. We consider two approaches to reduce these expenses for predictions made from visible-near-infrared ((V)NIR), mid-infrared (MIR) spectra and their combination. First, we considered reducing the level of processing of the samples by comparing the effect of different sample conditions (in-situ, unprocessed, air-dried and milled). Second, we explored the use of existing spectral libraries to inform calibrations (based on milled samples from the UK National Soil Inventory) with and without 'spiking' the spectral libraries with a small subset of samples from the study fields. Prediction accuracy of soil organic carbon, pH, clay, available P and K for each of these approaches was evaluated on samples from agricultural fields in the UK. Available P and K could only be moderately predicted with the field-scale dataset where samples were milled. Therefore this study found no evidence to suggest that there is scope to reduce costs associated with sample processing or field-scale calibration for available P and K. However, the results showed that there is potential to reduce time and cost implications of using (V)NIR and MIR spectra to predict soil organic carbon, clay and pH. Compared to field-scale calibrations from milled samples, we found that reduced sample processing lowered the ratio of performance to inter-quartile range (RPIQ) between 0% and 76%. The use of spectral libraries reduced the RPIQ of predictions relative to field-scale calibrations from milled samples between 54% and 82% and the RPIQ was reduced between 29% and 70% for predictions when spectral libraries were spiked. The increase in uncertainty was specific to the combination of soil property and sensor analysed. We conclude that there is always a trade-off between prediction accuracy and the costs associated with soil sampling, sample processing and wet chemical analysis. Therefore the relative merits of each approach will depend on the specific case in question.

The nutritional quality of cereals varies geospatially in Ethiopia and Malawi.

Micronutrient deficiencies (MNDs) remain widespread among people in sub-Saharan Africa1-5, where access to sufficient food from plant and animal sources that is rich in micronutrients (vitamins and minerals) is limited due to socioeconomic and geographical reasons4-6. Here we report the micronutrient composition (calcium, iron, selenium and zinc) of staple cereal grains for most of the cereal production areas in Ethiopia and Malawi. We show that there is geospatial variation in the composition of micronutrients that is nutritionally important at subnational scales. Soil and environmental covariates of grain micronutrient concentrations included soil pH, soil organic matter, temperature, rainfall and topography, which were specific to micronutrient and crop type. For rural households consuming locally sourced food-including many smallholder farming communities-the location of residence can be the largest influencing factor in determining the dietary intake of micronutrients from cereals. Positive relationships between the concentration of selenium in grain and biomarkers of selenium dietary status occur in both countries. Surveillance of MNDs on the basis of biomarkers of status and dietary intakes from national- and regional-scale food-composition data1-7 could be improved using subnational data on the composition of grain micronutrients. Beyond dietary diversification, interventions to alleviate MNDs, such as food fortification8,9 and biofortification to increase the micronutrient concentrations in crops10,11, should account for geographical effects that can be larger in magnitude than intervention outcomes.

Predicting the growth of lettuce from soil infrared reflectance spectra: the potential for crop management.

How well could one predict the growth of a leafy crop from reflectance spectra from the soil and how might a grower manage the crop in the light of those predictions? Topsoil from two fields was sampled and analysed for various nutrients, particle-size distribution and organic carbon concentration. Crop measurements (lettuce diameter) were derived from aerial-imagery. Reflectance spectra were obtained in the laboratory from the soil in the near- and mid-infrared ranges, and these were used to predict crop performance by partial least squares regression (PLSR). Individual soil properties were also predicted from the spectra by PLSR. These estimated soil properties were used to predict lettuce diameter with a linear model (LM) and a linear mixed model (LMM): considering differences between lettuce varieties and the spatial correlation between data points. The PLSR predictions of the soil properties and lettuce diameter were close to observed values. Prediction of lettuce diameter from the estimated soil properties with the LMs gave somewhat poorer results than PLSR that used the soil spectra as predictor variables. Predictions from LMMs were more precise than those from the PLSR using soil spectra. All model predictions improved when the effects of variety were considered. Predictions from the reflectance spectra, via the estimation of soil properties, can enable growers to decide what treatments to apply to grow lettuce and how to vary their treatments within their fields to maximize the net profit from the crop.

Prefrontal High Gamma in ECoG Tags Periodicity of Musical Rhythms in Perception and Imagination.

Rhythmic auditory stimuli are known to elicit matching activity patterns in neural populations. Furthermore, recent research has established the particular importance of high-gamma brain activity in auditory processing by showing its involvement in auditory phrase segmentation and envelope tracking. Here, we use electrocorticographic (ECoG) recordings from eight human listeners to see whether periodicities in high-gamma activity track the periodicities in the envelope of musical rhythms during rhythm perception and imagination. Rhythm imagination was elicited by instructing participants to imagine the rhythm to continue during pauses of several repetitions. To identify electrodes whose periodicities in high-gamma activity track the periodicities in the musical rhythms, we compute the correlation between the autocorrelations (ACCs) of both the musical rhythms and the neural signals. A condition in which participants listened to white noise was used to establish a baseline. High-gamma autocorrelations in auditory areas in the superior temporal gyrus and in frontal areas on both hemispheres significantly matched the autocorrelations of the musical rhythms. Overall, numerous significant electrodes are observed on the right hemisphere. Of particular interest is a large cluster of electrodes in the right prefrontal cortex that is active during both rhythm perception and imagination. This indicates conscious processing of the rhythms' structure as opposed to mere auditory phenomena. The autocorrelation approach clearly highlights that high-gamma activity measured from cortical electrodes tracks both attended and imagined rhythms.

Spatial prediction of the concentration of selenium (Se) in grain across part of Amhara Region, Ethiopia.

Grain and soil were sampled across a large part of Amhara, Ethiopia in a study motivated by prior evidence of selenium (Se) deficiency in the Region's population. The grain samples (teff, Eragrostis tef, and wheat, Triticum aestivum) were analysed for concentration of Se and the soils were analysed for various properties, including Se concentration measured in different extractants. Predictive models for concentration of Se in the respective grains were developed, and the predicted values, along with observed concentrations in the two grains were represented by a multivariate linear mixed model in which selected covariates, derived from remote sensor observations and a digital elevation model, were included as fixed effects. In all modelling steps the selection of predictors was done using false discovery rate control, to avoid over-fitting, and using an α-investment procedure to maximize the statistical power to detect significant relationships by ordering the tests in a sequence based on scientific understanding of the underlying processes likely to control Se concentration in grain. Cross-validation indicated that uncertainties in the empirical best linear unbiased predictions of the Se concentration in both grains were well-characterized by the prediction error variances obtained from the model. The predictions were displayed as maps, and their uncertainty was characterized by computing the probability that the true concentration of Se in grain would be such that a standard serving would not provide the recommended daily allowance of Se. The spatial variation of grain Se was substantial, concentrations in wheat and teff differed but showed the same broad spatial pattern. Such information could be used to target effective interventions to address Se deficiency, and the general procedure used for mapping could be applied to other micronutrients and crops in similar settings.

Establishing a baseline for a national paediatric antimicrobial stewardship programme.

BACKGROUND: The majority of antimicrobial stewardship programmes focus on prescribing in adult populations; however, there is a recognized need for targeted paediatric antimicrobial stewardship to improve the quality and safety of prescribing amongst this patient group. OBJECTIVES: To describe the current epidemiology of antimicrobial prescribing in paediatric inpatient populations in Scotland to establish a baseline of evidence and identify priority areas for quality improvement to support a national paediatric antimicrobial stewardship programme. METHODS: A total of 559 paediatric inpatients were surveyed during the Scottish national point prevalence survey of healthcare-associated infections and antimicrobial prescribing, 2016. The prevalence of antimicrobial prescribing was calculated and characteristics of antimicrobial prescribing were described as proportions and compared between specialist hospitals and paediatric wards in acute hospitals. RESULTS: Prevalence of antimicrobial use in paediatric inpatients was 35.4% (95% CI = 31.6%-39.4%). Treatment of community- and hospital-acquired infections accounted for 47.1% and 20.7% of antimicrobial use, respectively, with clinical sepsis being the most common diagnosis and gentamicin the most frequently prescribed antimicrobial for the treatment of infection. The reason for prescribing was documented in the notes for 86.5% of all prescriptions and, of those assessed for compliance against local policy, 92.9% were considered compliant. CONCLUSIONS: Data from national prevalence surveys are advantageous when developing antimicrobial stewardship programmes. Results have highlighted differences in the prescribing landscape between paediatric inpatient populations in specialist hospitals and acute hospitals, and have informed priorities for the national antimicrobial stewardship programme, which reinforces the need for a targeted paediatric antimicrobial stewardship programme.

Modelling the effect of spatially variable soil properties on the distribution of weeds.

The patch spraying of weeds is an area of precision agriculture that has had limited uptake. This is in part due to the perceived risks associated with not controlling individual weeds. Nevertheless, the inherent patchiness of weeds makes them ideal targets for site-specific management. We propose using a mechanistic model to identify areas of a field vulnerable to invasion by weeds, allowing the creation of treatment maps that are risk averse. We developed a spatially-explicit mechanistic model of the life-cycle of Alopecurus myosuroides, a particularly problematic weed of cereal crops in the UK. In the model, soil conditions which vary across the field, affect the life-cycle of A. myosuroides. The model was validated using data on the within-field distribution of A. myosuroides on commercial farms and its co-location with soil properties. We demonstrate the important role played by soil properties in determining the within-field distribution of A. myosuroides. We also show that scale-dependent correlations between A. myosuroides and soil properties observed in the field are an emergent property of the modelled dynamics of the A. myosuroides life-cycle. Our model could therefore support effective site-specific management of A. myosuroides within fields by predicting areas that are vulnerable to A. myosuroides. The usefulness of this model in its ability to predict patch locations for A. myosuroides highlights the possibility of using similar models for other species where data are available on the response of the species to various soil properties.

The eastern extent of seasonal iron limitation in the high latitude North Atlantic Ocean.

The availability of iron (Fe) can seasonally limit phytoplankton growth in the High Latitude North Atlantic (HLNA), greatly reducing the efficiency of the biological carbon pump. However, the spatial extent of seasonal iron limitation is not yet known. We present autumn nutrient and dissolved Fe measurements, combined with microphytoplankton distribution, of waters overlying the Hebridean (Scottish) shelf break. A distinct biogeochemical divide was observed, with Fe deficient surface waters present beyond the shelf break, much further eastwards than previously recognised. Due to along and on-shelf circulation, the Hebridean shelf represents a much-localised source of Fe, which does not fertilise the wider HLNA. Shelf sediments are generally thought to supply large quantities of Fe to overlying waters. However, for this Fe to influence upper-ocean biogeochemical cycling, efficient off-shelf transport mechanisms are required. This work challenges the view that the oceanic surface waters in close proximity to continental margins are iron replete with respect to marine primary production demands.

Defining the habitat niche of Alopecurus myosuroides at the field scale.

The distribution of Alopecurus myosuroides (black-grass) in fields is patchy. The locations of these patches can be influenced by the environment. This presents an opportunity for precision management through patch spraying. We surveyed five fields on various types of soil using a nested sampling design and recorded both A. myosuroides seedlings in autumn and seed heads in summer. We also measured soil properties at those sampling locations. We found that the patches of seed heads within a field were smaller than the seedling patches, suggesting that techniques for patch spraying based on maps of heads in the previous season could be inherently risky. We also found that the location of A. myosuroides patches within fields can be predicted through their relationship with environmental properties and that these relations are consistent across fields on different soil types. This improved understanding of the relations between soil properties and A. myosuroides seedlings could allow farmers to use pre-existing or suitably supplemented soil maps already in use for the precision application of fertilisers as a starting point in the creation of herbicide application maps.

Results from the third Scottish National Prevalence Survey: is a population health approach now needed to prevent healthcare-associated infections?

BACKGROUND: Healthcare-associated infections (HCAIs) are a major public health concern and a significant cause of morbidity and mortality. A robust and current evidence base that is specific to local, national and Europe-wide settings is necessary to inform the development of strategies to reduce HCAI and contain antimicrobial resistance. AIM: To measure the prevalence of HCAI and antimicrobial prescribing and identify key priority areas for interventions to reduce the burden of infection. METHODS: A national rolling point-prevalence survey (PPS) in National Health Service (NHS) acute, NHS non-acute, NHS paediatric, and independent hospitals was carried out between September and November 2016 using the European Centre for Disease Prevention and Control protocol designed for the European PPS. FINDINGS: The prevalence of HCAI was 4.6%, 2.7%, and 3.2% in acute adults, paediatric and non-acute patient groups, respectively. The most frequent HCAI types reported in adult patients were urinary tract infection and pneumonia. The prevalence of antimicrobial prescribing was 35.7%, 29.3%, and 13.8% in acute adults, paediatric, and non-acute patient groups, respectively. Respiratory, skin and soft tissue, gastrointestinal, and urinary tract infections were the most common infections being treated at the time of survey. CONCLUSION: HCAI continues to be a public health concern in Scotland. Urinary tract infection and pneumonia continue to place a significant burden on patients and on healthcare delivery, including those that develop in the community and require hospital admission. A broader population health approach which focuses on reducing the risk of infection upstream would reduce these infections in both community and hospital settings.

Designing a sampling scheme to reveal correlations between weeds and soil properties at multiple spatial scales.

Weeds tend to aggregate in patches within fields, and there is evidence that this is partly owing to variation in soil properties. Because the processes driving soil heterogeneity operate at various scales, the strength of the relations between soil properties and weed density would also be expected to be scale-dependent. Quantifying these effects of scale on weed patch dynamics is essential to guide the design of discrete sampling protocols for mapping weed distribution. We developed a general method that uses novel within-field nested sampling and residual maximum-likelihood (reml) estimation to explore scale-dependent relations between weeds and soil properties. We validated the method using a case study of Alopecurus myosuroides in winter wheat. Using reml, we partitioned the variance and covariance into scale-specific components and estimated the correlations between the weed counts and soil properties at each scale. We used variograms to quantify the spatial structure in the data and to map variables by kriging. Our methodology successfully captured the effect of scale on a number of edaphic drivers of weed patchiness. The overall Pearson correlations between A. myosuroides and soil organic matter and clay content were weak and masked the stronger correlations at >50 m. Knowing how the variance was partitioned across the spatial scales, we optimised the sampling design to focus sampling effort at those scales that contributed most to the total variance. The methods have the potential to guide patch spraying of weeds by identifying areas of the field that are vulnerable to weed establishment.

Oxidative costs of reproduction: Oxidative stress in mice fed standard and low antioxidant diets.

Lactation is one of the most energetically expensive behaviours, and trade-offs may exist between the energy devoted to it and somatic maintenance, including protection against oxidative damage. However, conflicting data exist for the effects of reproduction on oxidative stress. In the wild, a positive relationship is often observed, but in laboratory studies oxidative damage is often lower in lactating than in non-breeding animals. We hypothesised that this discrepancy may exist because during lactation food intake increases many-fold resulting in a large increase in the intake of dietary antioxidants which are typically high in laboratory rodent chow where they are added as a preservative. We supplied lactating and non-breeding control mice with either a standard or low antioxidant diet and studied how this affected the activity of endogenous antioxidants (catalase, superoxide dismutase; SOD, and glutathione peroxidise; GPx) and oxidative damage to proteins (protein carbonyls, PC) in liver and brain tissue. The low antioxidant diet did not significantly affect activities of antioxidant enzymes in brain or liver, and generally did not result in increased protein damage, except in livers of control mice on low antioxidant diet. Catalase activity, but not GPx or SOD, was decreased in both control and lactating mice on the low antioxidant diet. Lactating mice had significantly reduced oxidative damage to both liver and brain compared to control mice, independent of the diet they were given. In conclusion, antioxidant content of the diet did not affect oxidative stress in control or reproductive mice, and cannot explain the previously observed reduction in oxidative stress in lactating mammals studied in the laboratory. The reduced oxidative stress in the livers of lactating mice even under low antioxidant diet treatment was consistent with the 'shielding' hypothesis.

Systematic review: plantar fasciitis and prolonged weight bearing.

BACKGROUND: Plantar fasciitis (PF) is one of the most common causes of foot pain. Work can involve factors that may predispose to foot pain. AIMS: To systematically review the evidence of the association between weight bearing (walking or standing) and PF among workers. METHODS: Literature search of relevant indexing databases from inception to May 2012, grey literature, websites of relevant organizations and reference lists for all identified articles. Two reviewers independently selected studies for full review, assessed methodological quality and graded evidence. Findings were summarized qualitatively. RESULTS: Four studies were included; all were assessed as high or unclear risk of bias. Three studies were case-control studies; two used clinic populations and one used volunteers. The other study was cross-sectional involving the workforce of an assembly plant. A number of associations between PF and risk factors were identified including sex, obesity, foot biomechanics and job factors (e.g. job tenure). Two case-control studies and the cross-sectional study found an association with weight bearing, but the assessment of weight bearing varied (e.g. time on feet, time walking or standing). There was low-quality evidence to confirm a causal relationship (Royal College of General Practitioners (RCGP) * grade). CONCLUSIONS: This systematic review found low-quality evidence of an association between PF and weight-bearing tasks such as walking and standing on hard surfaces. The only occupations specifically identified as having higher risk were those associated with the engine assembly plant. Further research is required to fully determine the association between weight bearing and PF.