We can close the Indigenous nutrition gap – here’s how

After years of neglect and a notable absence in last week’s Closing the Gap report, nutrition is finally being recognised as integral to closing the gap on Indigenous disadvantage. This belated realisation is puzzling, given poor diet is a major cause of type 2 diabetes, heart disease, kidney disease and some cancers. Nutrition is particularly poor in Aboriginal and Torres Strait Islander communities, where it is estimated that at least 19% of the burden of disease is due to poor diet; much more than due to smoking...

Psychological distress may affect nutrition indicators in Australian adults

- Objective The purpose of this research was to explore which demographic and health status variables moderated the relationship between psychological distress and three nutrition indicators: the consumption of fruits, vegetables and takeaway. - Method We analysed data from the 2009 Self-Reported Health Status Survey Report collected in the state of Queensland, Australia. Adults (N = 6881) reported several demographic and health status variables. Moderated logistic regression models were estimated separately for the three nutrition indicators, testing as moderators demographic (age, gender, educational attainment, household income, remoteness, and area-level socioeconomic status) and health status indicators (body mass index, high cholesterol, high blood pressure, and diabetes status). - Results Several significant interactions emerged between psychological distress, demographic (age, area-level socioeconomic status, and income level), and health status variables (body mass index, diabetes status) in predicting the nutrition indicators. Relationships between distress and the nutrition indicators were not significantly different by gender, remoteness, educational attainment, high cholesterol status, and high blood pressure status. - Conclusions The associations between psychological distress and several nutrition indicators differ amongst population subgroups. These findings suggest that in distressed adults, age, area-level socio-economic status, income level, body mass index, and diabetes status may serve as protective or risk factors through increasing or decreasing the likelihood of meeting nutritional guidelines. Public health interventions for improving dietary behaviours and nutrition may be more effective if they take into account the moderators identified in this study rather than using global interventions.

Nutrition during noninvasive ventilation: clinical determinants and key practical recommendations

Malnutrition and poor nutritional intake have been identified as key issues associated with poorer clinical outcomes in chronic obstructive pulmonary disease (COPD) patients. There is strong evidence showing nutritional support is effective in treating malnutrition in stable COPD, but there is only limited research regarding nutritional status in patients treated with noninvasive ventilation (NIV). The impact of NIV during acute exacerbations of respiratory disease on nutritional status requires further investigation.

Playing the policy game: A review of the barriers and enablers of nutrition policy change

- Objective To progress nutrition policy change and develop more effective advocates, it is useful to consider real-world factors and practical experiences of past advocacy efforts to determine the key barriers and enablers to nutrition policy change. This review aimed to identify and synthesize the enablers and barriers to public policy change within the field of nutrition. - Design Electronic databases were searched systematically for studies examining policymaking in public health nutrition. An interpretive synthesis was undertaken. Setting: International, national, state and local government jurisdictions within high-income, democratic countries. - Results Sixty-three studies were selected for inclusion. Numerous themes were identified explaining the barriers and enablers to policy change, all of which fell under the overarching category, ‘political will’, underpinned by a second major category, ‘public will’. Sub-themes, including pressure from industry; neoliberal ideology; use of emotions and values, and being visible were prevalent in describing links between public will, political will and policy change. - Conclusions The frustration around lack of public policy change in nutrition frequently stems from a belief that policymaking is a rational process in which evidence is used to assess the relative costs and benefits of options. The findings from this review confirm that evidence is only one component of influencing policy change. For policy change to occur there needs to be the political will, and often the public will, for the proposed policy problem and solution. This review presents a suite of enablers which can assist health professionals to influence political and public will in future advocacy efforts.

Assessment of crop insect damage using unmanned aerial systems: A machine learning approach

Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising technology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of the approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labeling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means. The outcome of this approach is a soft K-means algorithm similar to the EM algorithm for Gaussian mixture models. The results show the algorithm delivers decision boundaries that consistently classify the field into three clusters, one for each crop health level. The methodology presented in this paper represents a venue for further research towards automated crop damage assessments and biosecurity surveillance.

Relating food literacy to nutrition and health

This chapter describes the evolution of a model to propose the relationship between food literacy and nutrition. This model can also be used as a framework for program planning, implementation and evaluation. Practitioners and policy makers invest in food literacy with outcome expectations beyond diet quality. For this reason, a second model was developed to conceptualise the role of food literacy with respect to food security, body weight and chronic disease risk. This second model is useful in positioning food literacy within multi-strategic public health nutrition and chronic disease plans.

A generic individual-based spatially explicit model as a novel tool for investigating insect-plant interactions: A case study of the behavioural ecology of frugivorous Tephritidae

Computational modelling of mechanisms underlying processes in the real world can be of great value in understanding complex biological behaviours. Uptake in general biology and ecology has been rapid. However, it often requires specific data sets that are overly costly in time and resources to collect. The aim of the current study was to test whether a generic behavioural ecology model constructed using published data could give realistic outputs for individual species. An individual-based model was developed using the Pattern-Oriented Modelling (POM) strategy and protocol, based on behavioural rules associated with insect movement choices. Frugivorous Tephritidae (fruit flies) were chosen because of economic significance in global agriculture and the multiple published data sets available for a range of species. The Queensland fruit fly (Qfly), Bactrocera tryoni, was identified as a suitable individual species for testing. Plant canopies with modified architecture were used to run predictive simulations. A field study was then conducted to validate our model predictions on how plant architecture affects fruit flies’ behaviours. Characteristics of plant architecture such as different shapes, e.g., closed-canopy and vase-shaped, affected fly movement patterns and time spent on host fruit. The number of visits to host fruit also differed between the edge and centre in closed-canopy plants. Compared to plant architecture, host fruit has less contribution to effects on flies’ movement patterns. The results from this model, combined with our field study and published empirical data suggest that placing fly traps in the upper canopy at the edge should work best. Such a modelling approach allows rapid testing of ideas about organismal interactions with environmental substrates in silico rather than in vivo, to generate new perspectives. Using published data provides a saving in time and resources. Adjustments for specific questions can be achieved by refinement of parameters based on targeted experiments.