Progress Towards Using Linked Population-Based Data For Geohealth Research: Comparisons Of Aotearoa New Zealand And The United Kingdom.

Globally, geospatial concepts are becoming increasingly important in epidemiological and public health research. Individual level linked population-based data afford researchers with opportunities to undertake complex analyses unrivalled by other sources. However, there are significant challenges associated with using such data for impactful geohealth research. Issues range from extracting, linking and anonymising data, to the translation of findings into policy whilst working to often conflicting agendas of government and academia. Innovative organisational partnerships are therefore central to effective data use. To extend and develop existing collaborations between the institutions, in June 2019, authors from the Leeds Institute for Data Analytics and the Alan Turing Institute, London, visited the Geohealth Laboratory based at the University of Canterbury, New Zealand. This paper provides an overview of insight shared during a two-day workshop considering aspects of linked population-based data for impactful geohealth research. Specifically, we discuss both the collaborative partnership between New Zealand's Ministry of Health (MoH) and the University of Canterbury's GeoHealth Lab and novel infrastructure, and commercial partnerships enabled through the Leeds Institute for Data Analytics and the Alan Turing Institute in the UK. We consider the New Zealand Integrated Data Infrastructure as a case study approach to population-based linked health data and compare similar approaches taken by the UK towards integrated data infrastructures, including the ESRC Big Data Network centres, the UK Biobank, and longitudinal cohorts. We reflect on and compare the geohealth landscapes in New Zealand and the UK to set out recommendations and considerations for this rapidly evolving discipline.

A socio-spatial analysis of pedestrian falls in Aotearoa New Zealand.

Falls are a leading cause of injury and accidental death, particularly amongst older people. Evidence of environmental risk factors for pedestrian falls among older adults could support age-friendly urban design and contribute to efforts to reduce the incidence of pedestrian falls and support outdoor mobility among older adults. Yet investigation of the environment in which pedestrian falls occur is often hampered by its reliance on participant recall and self-report information. We identified the point locations of falls occurring on the road or street among adults that were attended by an ambulance in New Zealand over a two-year period (2016-2018) and connected these to a range of social (e.g. deprivation) and environmental (e.g. slope, greenspace) risk factors. Three types of analysis were used: a descriptive analysis of fall rates, logistic regression assessing whether a patient was transported to hospital following a fall, and a negative binomial regression analysis of the pedestrian falls by small area. We found a number of differences in the built environment surrounding fall locations between age groups. Compared with younger age groups, older adults showed high fall rates closer to home, and higher fall rates in areas with many types of destinations nearby. Additionally, our results showed a higher rate of pedestrian falls in more deprived areas. People who live in more deprived areas also fell over more frequently, but the pattern is stronger based on deprivation at the fall location, rather than home location. Residents of more deprived areas were less likely to be transported to hospital following a fall. Thus, our findings have equity implications for both environments and patient experience. These patterns could not have been identified without the novel use of spatially specific fall data.

Objectively measured waist circumference is most strongly associated in father-boy and mother-girl dyads in a large nationally representative sample of New Zealanders.

BACKGROUND: The prevalence of children with elevated weight or obesity is concerning for public health due to associated comorbidities. This study investigates associations between parental adiposity, physical activity (PA), fruit and vegetable consumption, and child adiposity and moderation by both child and parent gender. METHODS: Cross-sectional nationally representative data from the New Zealand Health Survey were pooled for the years 2013/14-2016/17. Parent and child surveys were matched resulting in 13,039 child (2-14 years) and parent (15-70 years) dyads. Parent and child, height (cm), weight (kg) and waist circumference (WC) were measured objectively. Height and weight were used to calculate BMI. Linear regression, accounting for clustered samples (b [95% CI]) investigated associations between parental characteristics and child BMI z-score and WC. Interactions and stratification were used to investigate effect moderation by parent gender, child gender, and parent adiposity. RESULTS: Parental PA and fruit and vegetable consumption were unrelated to child adiposity. Overall, higher parent BMI was related to a higher child BMI z-score (b = 0.047 [0.042, 0.052]) and higher parental WC was related to a higher child WC (0.15 [0.12, 0.17]). A three-way interaction revealed no moderation by parent gender, child gender, and parent BMI for child BMI z-score ((b = 0.005 [-0.017, 0.027], p = 0.318). However, a three-way interaction revealed moderation by parent gender, child gender, and parent WC for child WC (b = 0.13 [0.05, 0.22]). The slightly stronger associations were seen between father-son WC (b = 0.20 [0.15, 0.24]) and mother-daughter WC (b = 0.19 [0.15, 0.22]). CONCLUSIONS: The findings are highly relevant for those wishing to understand the complex relationships between child-parent obesity factors. Findings suggest that family environments should be a key target for obesity intervention efforts and show how future public health interventions should be differentiated to account for both maternal and paternal influences on child adiposity.