Clinical relevance and validity of tools to predict infant, childhood and adulthood obesity: a systematic review

To determine the global availability of a multicomponent tool predicting overweight/obesity in infancy, childhood, adolescence or adulthood; and to compare their predictive validity and clinical relevance.Design/SettingThe PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were followed. The databases PubMed, EMBASE, CINAHL, Web of Science and PsycINFO were searched. Additional articles were identified via reference lists of included articles. Risk of bias was assessed using the Academy of Nutrition and Dietetics' Quality Criteria Checklist. The National Health and Medical Research Council's Levels of Evidence hierarchy was used to assess quality of evidence. Predictive performance was evaluated using the ABCD framework.Eligible studies: tool could be administered at any life stage; quantified the risk of overweight/obesity onset; used more than one predictor variable; and reported appropriate prediction statistical outcomes.Of the initial 4490 articles identified, twelve articles (describing twelve tools) were included. Most tools aimed to predict overweight and/or obesity within childhood (age 2-12 years). Predictive accuracy of tools was consistently adequate; however, the predictive validity of most tools was questioned secondary to poor methodology and statistical reporting. Globally, five tools were developed for dissemination into clinical practice, but no tools were tested within a clinical setting.To our knowledge, a clinically relevant and highly predictive overweight/obesity prediction tool is yet to be developed. Clinicians can, however, act now to identify the strongest predictors of future overweight/obesity. Further research is necessary to optimise the predictive strength and clinical applicability of such a tool

Building a Children’s Health Service and System Research Strategy: development and integration in an Australian paediatric healthcare setting

Background Health services and systems research (HSSR) strategies dedicated to paediatric health care and service delivery are limited. Strategies are available but are outdated and yet to be optimised for use in a paediatric health system. We aim to describe the development and integration of a Children’s Health Service and System Research Strategy (CHSSR-S) in Children’s Health Queensland (CHQ), a large specialist quaternary hospital and health service caring for children and young people in Queensland and northern New South Wales, Australia. Methods The CHSSR-S was developed using an inductive, bottom-up, participatory systems approach across three phases: (1) Identifying local HSSR capacity; (2) Development; (3) Integration. A HSSR “Champion” was appointed to lead all phases. Clinical, research and system-based stakeholders (n = 14) were individually identified, contacted and participated in dedicated meetings and a workshop to iteratively design the CHSSR-S. A health system-wide CHSSR-S governance committee was established to drive phase three. Health system integration was achieved by multicomponent, action-based strategies. Results The final CHSSR-S comprised ten Research Priorities and three Research Enablers, and was successfully integrated within CHQ via a range of platforms. Research Priorities included: (1) Population Health; (2) Adolescent and Young Adult (AYA) Cancer; (3) Indigenous Health; (4); Mental Health; (5) Nutrition and Obesity; (6) Rare Neurodevelopmental Disorders; (7) Sepsis; (8) Screening, surveillance and monitoring; (9) Innovation; and (10) Electronic Medical Record (EMR). Research Priorities were supported by three Research Enablers: (1) Data; (2); Evaluation and Health Economics; and (3) Policy. Conclusions The CHSSR-S is the first known paediatric HSSR strategy developed and integrated within a large dedicated paediatric health system. The CHSSR-S may be used to guide global paediatric healthcare systems to prioritise HSSR in their local setting to optimise health service delivery and patient outcomes

Interventions to prevent or treat childhood obesity in Māori & Pacific Islanders: a systematic review

Māori and Pacific Islander people are a priority population originating from Australasia. Māori and Pacific Islander children exhibit greater risk of obesity and associated morbidities compared to children of other descent, secondary to unique cultural practices and socioeconomic disadvantage. Despite these known risk factors, there is limited synthesised evidence for preventing and treating childhood obesity in this unique population. The objective of this systematic review was to identify and evaluate global prevention or treatment interventions for overweight or obesity that targeted Māori and Pacific Islander children and adolescents (aged 2-17 years).The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. The databases PubMed, EMBASE, Scopus, Web of Science and CINAHL were searched from inception to August 2018. Study quality and risk of bias was assessed using a modified Downs and Black Quality Checklist for Health Care Intervention Studies. Studies were included if RCT/intervention/case control/ or prevention study designs. The study group was defined under the search term 'Oceanic Ancestry Group'.Of the initial 94 articles identified, six were included describing two prevention and three treatment interventions. Interventions were heterogenous in setting, design, length and outcomes. Four interventions were implemented in New Zealand. Most studies were of 'fair' quality. One study recruited an exclusive population of Māori and Pacific Islander participants. In the five studies that recruited mixed populations, one performed sub-group analysis on Māori and Pacific Islander participants. No study reported an improvement in anthropometric outcomes post-intervention in complete or sub-group analysis. Improvements in cardiometabolic or psychological secondary outcomes were inconsistent across all studies.There is a lack of evidence to recommend specific intervention characteristics to optimise obesity prevention or treatment outcomes for Māori and Pacific Islander children. Future research requires greater consideration of cultural values and beliefs, community engagement, exclusive targeting of Māori and Pacific Islander children and families, and sub-group analyses for mixed-population studies. Incorporating co-design principles during study design and implementation can maximise the cultural specificity of interventions and may contribute to improved health and weight-related outcomes for this at-risk, priority population.PROSPERO CRD42019121790 (26 March 2019)

Digital health and precision prevention:Shifting from disease-centred care to consumer-centred health

Digital disruption and transformation of health care is occurring rapidly. Concurrently, a global syndemic of preventable chronic disease is crippling healthcare systems and accelerating the effect of the COVID-19 pandemic. Healthcare investment is paradoxical; it prioritises disease treatment over prevention. This is an inefficient break-fix model versus a person-centred predict-prevent model. It is easy to reward and invest in acute health systems because activity is easily measured and therefore funded. Social, environmental and behavioural health determinants explain ∼70% of health variance; yet, we cannot measure these community data contemporaneously or at population scale. The dawn of digital health and the digital citizen can initiate a precision prevention era, where consumer-centred, real-time data enables a new ability to count and fund population health, making disease prevention 'matter'. Then, precision decision making, intervention and policy to target preventable chronic disease (e.g. obesity) can be realised. We argue for, identify barriers to, and propose three horizons for digital health transformation of population health towards precision prevention of chronic disease, demonstrating childhood obesity as a use case. Clinicians, researchers and policymakers can commence strategic planning and investment for precision prevention of chronic disease to advance a mature, value-based model that will ensure healthcare sustainability in Australia and globally.</p

“We'd be really motivated to do something about it”:A qualitative study of parent and clinician attitudes towards predicting childhood obesity in practice

Issue addressed: In Australia, one in four (24.9%) children live with overweight or obesity (OW/OB). Identifying infants at risk of developing childhood OW/OB is a potential preventive pathway, but its acceptability is yet to be investigated in Australia. This study aimed to (1) investigate the acceptability of predicting childhood OW/OB with parents of infants (aged 0-2 years) and clinicians and (2) explore key language to address stigma and maximise the acceptability of predicting childhood OW/OB in practice. Methods: This was a cross-sectional and qualitative design, comprising individual semi-structured interviews. Participants were multidisciplinary paediatric clinicians (n = 18) and parents (n = 13) recruited across public hospitals and health services in Queensland, Australia. Data were analysed under the Framework Method using an inductive, thematic approach. Results: Five main themes were identified: (1) Optimism for prevention and childhood obesity prediction, (2) parent dedication to child's health, (3) adverse parent response to risk for childhood obesity, (4) language and phrasing for discussing weight and risk and (5) clinical delivery. Most participants were supportive of using a childhood OW/OB prediction tool in practice. Parents expressed dedication to their child's health that superseded potential feelings of judgement or blame. When discussing weight in a clinical setting, the use of sensitive (ie, “overweight”, “above average”, “growth” versus “obesity”) and positive, health-focused language was mostly supported. Conclusions: Multidisciplinary paediatric clinicians and parents generally accept the concept of predicting childhood OW/OB in practice in Queensland, Australia. So what?: Clinicians, public health and health promotion professionals and policymakers can act now to implement sensitive communication strategies concerning weight and obesity risk.</p

Data sources for precision public health of obesity: a scoping review, evidence map and use case in Queensland, Australia

BackgroundGlobal action to reduce obesity prevalence requires digital transformation of the public health sector to enable precision public health (PPH). Useable data for PPH of obesity is yet to be identified, collated and appraised and there is currently no accepted approach to creating this single source of truth. This scoping review aims to address this globally generic problem by using the State of Queensland (Australia) (population > 5 million) as a use case to determine (1) availability of primary data sources usable for PPH for obesity (2) quality of identified sources (3) general implications for public health policymakers.MethodsThe Preferred Reporting Items for Systematic Review and Meta-Analyses extension for scoping reviews (PRISMA-ScR) was followed. Unique search strategies were implemented for ‘designed’ (e.g. surveys) and ‘organic’ (e.g. electronic health records) data sources. Only primary sources of data (with stratification to Queensland) with evidence-based determinants of obesity were included. Primary data source type, availability, sample size, frequency of collection and coverage of determinants of obesity were extracted and curated into an evidence map. Data source quality was qualitatively assessed.ResultsWe identified 38 primary sources of preventive data for obesity: 33 designed and 5 organic. Most designed sources were survey (n 20) or administrative (n 10) sources and publicly available but generally were not contemporaneous (> 2 years old) and had small sample sizes (10-100 k) relative to organic sources (> 1 M). Organic sources were identified as the electronic medical record (ieMR), wearables, environmental (Google Maps, Crime Map) and billing/claims. Data on social, biomedical and behavioural determinants of obesity typically co-occurred across sources. Environmental and commercial data was sparse and interpreted as low quality. One organic source (ieMR) was highly contemporaneous (routinely updated), had a large sample size (5 M) and represented all determinants of obesity but is not currently used for public health decision-making in Queensland.ConclusionsThis review provides a (1) comprehensive data map for PPH for obesity in Queensland and (2) globally translatable framework to identify, collate and appraise primary data sources to advance PPH for obesity and other noncommunicable diseases. Significant challenges must be addressed to achieve PPH, including: using designed and organic data harmoniously, digital infrastructure for high-quality organic data, and the ethical and social implications of using consumer-centred health data to improve public health

How do Twitter users feel about telehealth? A mixed-methods analysis of experiences, perceptions and expectations

Background: Telehealth use has increased considerably in the last years and evidence suggests an overall positive sentiment towards telehealth. Twitter has a wide userbase and can enrich our understanding of telehealth use by users expressing their personal opinions in an unprompted way. This study aimed to explore Twitter users' experiences, perceptions and expectations about telehealth over the last 5 years. Methods: Mixed-methods study with sequential complementary quantitative and qualitative phases was used for analysis stages comprising (1) a quantitative semiautomated analysis and (2) a qualitative research-led thematic analysis. A machine learning model was used to establish the data set with relevant English language tweets from 1 September 2017 to 1 September 2022 relating to telehealth using predefined search words. Results were integrated at the end. Results: From the initial 237,671 downloaded tweets, 6469 had a relevancy score above 0.8 and were input into Leximancer and 595 were manually analysed. Experiences, perceptions and expectations were categorised into three domains: experience with telehealth consultation, telehealth changes over time and the purpose of the appointment. The most tweeted experience was expectations for telehealth consultation in comparison to in-person consultations. Users mostly mentioned the hope that waiting times for the consultations to start to be less than in-person, more telehealth appointments to be available and telehealth to be cheaper. Perceptions around the use of telehealth in relation to healthcare delivery changes brought about by the COVID-19 pandemic were also expressed. General practitioners were mentioned six times more than other healthcare professionals. Conclusion/Implications: This study found that Twitter users expect telehealth services to be better, more affordable and more available than in-person consultations. Users acknowledged the convenience of not having to travel for appointments and the challenges to adapt to telehealth. Patient or Public Contribution: An open data set with 237,671 tweets expressing users' opinions in an unprompted way was used as a source for telehealth service users, caregivers and members of the public experiences, perceptions and expectations of telehealth.</p