Jesse Wiki

Increases in fuel prices can be driven by a range of factors such as supply chain disruption (e.g. COVID-19 and the 2026 Middle East conflict), general inflation, and changes to government policy settings (e.g climate related emissions reduction policies). Such increases have differential impacts and contribute to social inequity. We calculate a national level index of vulnerability to increases in motor fuel costs at the small area level for Aotearoa New Zealand, drawing on established methods. Those living in “accessible” rural areas near urban centres are more likely to be vulnerable.

The built and natural environment can facilitate (un)healthy behaviors in adolescence. However, most previous studies have focused on examining associations between singular aspects of the environment. This study examined the association between the mixture of health‐promoting and health‐constraining environmental features in a Healthy Location Index (HLI) and physical activity and screen time among adolescents. This cross‐sectional study used data from the Built Environment and Active Transport to School (BEATS) Research Program based in Dunedin, New Zealand. Data from 1,162 adolescents with complete demographic, health behavior and spatial records were included in the analysis. The environment was defined using the HLI based on access to health‐promoting (e.g., greenspace, blue space, physical activity facility) and health‐constraining (e.g., fast‐food outlets) features and their mixture. Quantile g‐computation and multilevel mixed effects models, with adolescents nested within schools, examined associations between the environment and the two health behaviors. A positive association existed between meeting physical activity guidelines and access to health‐promoting environments (OR = 1.23 [95% CI 1.03; 1.47]), particularly blue space. In addition, the mixture of health‐promoting and health‐constraining environments was also important (ψ = 1.18 [1.01; 1.37]). However, there was limited evidence of an association between the environment and screen time. We provide evidence of a relationship between health‐promoting environments, the mix of health‐promoting and health‐constraining environments, and physical activity among adolescents. The findings support the hypothesis that the environment has the potential to positively influence healthy behaviors of youth, particularly when it comes to physical activity.

COVID‐19 can affect the entire population, but it poses an increased risk for particular population groups. Socioeconomic and demographic factors, as well as long‐term health conditions, can make populations vulnerable to adverse health outcomes and mortality related to COVID‐19. This study uses geospatial methods to visualise metrics of vulnerability to COVID‐19 in New Zealand. Based on Ministry of Health guidelines, nationwide data on risk factors included age, ethnicity, population density, socioeconomic deprivation, smoking, long‐term health conditions (cancer, cardiovascular conditions, diabetes, renal conditions, and respiratory illnesses), and health service awareness. Data were sourced from the Census (2018), the New Zealand Deprivation Index (NZDep2018), and the National Minimum Dataset (2011–2016). Factor analysis and bivariate mapping were used to identify areas of high vulnerability. Results demonstrate the unequal social and spatial vulnerabilities to COVID‐19 across New Zealand. While some major cities were highlighted many areas also occurred outside of the major cities in smaller communities, which also typically have less access to healthcare and fewer resources. This study has generated data that may help mitigate potential inequality in our response to the COVID‐19 pandemic, or indeed for future pandemics.

Background The COVID-19 pandemic has asked unprecedented questions of governments around the world. Policy responses have disrupted usual patterns of movement in society, locally and globally, with resultant impacts on national economies and human well-being. These interventions have primarily centred on enforcing lockdowns and introducing social distancing recommendations, leading to questions of trust and competency around the role of institutions and the administrative apparatus of state. This study demonstrates the unequal societal impacts in population movement during a national ‘lockdown’. Methods We use nationwide mobile phone movement data to quantify the effect of an enforced lockdown on population mobility by neighbourhood deprivation using an ecological study design. We then derive a mobility index using anonymised aggregated population counts for each neighbourhood (2253 Census Statistical Areas; mean population n=2086) of national hourly mobile phone location data (7.45 million records, 1 March 2020–20 July 2020) for New Zealand (NZ). Results Curtailing movement has highlighted and exacerbated underlying social and spatial inequalities. Our analysis reveals the unequal movements during ‘lockdown’ by neighbourhood socioeconomic status in NZ. Conclusion In understanding inequalities in neighbourhood movements, we are contributing critical new evidence to the policy debate about the impact(s) and efficacy of national, regional or local lockdowns which have sparked such controversy.