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.

Unhealthy environments are associated with adverse mental health and psychological distress: Cross-sectional evidence from nationally representative data in New Zealand

This study combines data on the location of health-constraining 'bads' (i: fast-food outlets, ii: takeaway outlets, iii: dairy outlets and convenience stores, iv: alcohol outlets, and v: gaming venues) and health-promoting 'goods' (i: green spaces, ii: blue spaces, iii: physical activity facilities, and iv: fruit and vegetable outlets) into a nationwide Healthy Living Index. This was applied to pooled (2015/16-2017/18) nationally representative New Zealand Health Survey data, with mental health conditions (depression, bipolar, and anxiety) and psychological distress as population-level outcomes. Mental health was associated with proximity to environmental 'goods' and 'bads'. Compared to those individuals who reside within the unhealthiest environments, there was a steady reduction in the odds of adverse mental health outcomes and psychological distress as the environment became more health-promoting.

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.

Close proximity to alcohol outlets is associated with increased crime and hazardous drinking: Pooled nationally representative data from New Zealand

This nationwide study investigated the relationship between proximity to alcohol outlets (off-licence, on-licence, and other-licence) and two adverse outcomes; hazardous drinking and crime (common assault, non-aggravated sexual assault, aggravated sexual assault, and tobacco and liquor offences). After adjustment for important individual- and area-level factors, close proximity to alcohol outlets was associated with increased risk of hazardous drinking, with strong associations for on-licence outlets. Proximity alcohol outlets was also strongly associated with all crime outcomes, often with a dose-response relationship. Nationally representative New Zealand data showed that close proximity to alcohol outlets was associated with increased crime and hazardous drinking.

Painting a picture of trans-Tasman mortality

OBJECTIVES

The determinants of health and mortality inequalities in New Zealand and Australia have been subjected to research, with the influence of a range of socio-economic and demographic influences (deprivation, social class, ethnicity) receiving notable attention. Both countries are considered privileged, positioned amongst the world leaders in rankings of mortality and life expectancy. This paper reports on observed rates of mortality and views how the countries have fared over time with respect to one another.

STUDY DESIGN, OBSERVATIONAL, METHODS

This study derives comparable rates of mortality for both New Zealand and Australia, disaggregated by age and sex for the time period 1948-2008. The age-standardised rates are visualised using the Lexis mapping software program, showing the relative differences between the countries over time whilst simultaneously highlighting age, period and cohort effects.

RESULTS

Relative to Australia, New Zealand had advantageous rates of mortality across almost all age groups between the years 1948 and 1980 (approximately). For both sexes, a dramatic reversal of fortunes in New Zealand has followed relative to Australia. For example, for younger males in New Zealand, the reversal is startling. Over the time period observed, males aged 10-20 years in New Zealand have moved from an advantageous position of having a mortality rate 20% lower than Australia to a relative position of 50% higher.

CONCLUSIONS

The social and economic forces in both New Zealand and Australia which may have driven the divergence require further scrutiny. It is argued here, that the changing fortunes of the populations are linked to the process of selective migration and the large-scale population movements between the countries facilitated by the Trans-Tasman Travel Arrangement. These findings have important implications for policy formation and service planning, if the inequality in mortality between the areas of study is to be addressed.

A regression-based method for mapping traffic-related air pollution: application and testing in four contrasting urban environments

Accurate, high-resolution maps of traffic-related air pollution are needed both as a basis for assessing exposures as part of epidemiological studies, and to inform urban air-quality policy and traffic management. This paper assesses the use of a GIS-based, regression mapping technique to model spatial patterns of traffic-related air pollution. The model--developed using data from 80 passive sampler sites in Huddersfield, as part of the SAVIAH (Small Area Variations in Air Quality and Health) project--uses data on traffic flows and land cover in the 300-m buffer zone around each site, and altitude of the site, as predictors of NO2 concentrations. It was tested here by application in four urban areas in the UK: Huddersfield (for the year following that used for initial model development), Sheffield, Northampton, and part of London. In each case, a GIS was built in ArcInfo, integrating relevant data on road traffic, urban land use and topography. Monitoring of NO2 was undertaken using replicate passive samplers (in London, data were obtained from surveys carried out as part of the London network). In Huddersfield, Sheffield and Northampton, the model was first calibrated by comparing modelled results with monitored NO2 concentrations at 10 randomly selected sites; the calibrated model was then validated against data from a further 10-28 sites. In London, where data for only 11 sites were available, validation was not undertaken. Results showed that the model performed well in all cases. After local calibration, the model gave estimates of mean annual NO2 concentrations within a factor of 1.5 of the actual mean (approx. 70-90%) of the time and within a factor of 2 between 70 and 100% of the time. r2 values between modelled and observed concentrations are in the range of 0.58-0.76. These results are comparable to those achieved by more sophisticated dispersion models. The model also has several advantages over dispersion modelling. It is able, for example, to provide high-resolution maps across a whole urban area without the need to interpolate between receptor points. It also offers substantially reduced costs and processing times compared to formal dispersion modelling. It is concluded that the model might thus be used as a means of mapping long-term air pollution concentrations either in support of local authority air-quality management strategies, or in epidemiological studies.

Establishing links between air quality and health: searching for the impossible?

Traditional approaches in environmental spatial epidemiology have relied on assessing postulated links between environmental pollution and ill health, often as a response to a perceived public health problem; clearly it may be necessary to go beyond this stage in order to establish the nature of potential causal mechanisms. Different disciplines approach this issue in different ways. Many toxicologists favour approaches based on air quality monitoring, where raised levels of candidate pollutants may subsequently generate hypotheses about adverse health effects. Epidemiologists, however, assess the health of a population and then look for an associated cause. This paper suggests that neither approach is completely satisfactory and that a combination of both is needed. If spatially referenced data are available for both health status and air quality, then geographical analysis is needed to examine possible links, by using techniques such as atmospheric dispersion modelling and Geographical Information Systems. We discuss the benefits and constraints of these approaches, using empirical examples of environmental epidemiology studies for northern England. Taking into account the problems involved in such studies, allied to the high costs incorporated, the paper asks the question: Are we searching for the impossible?