INTRODUCTION: Connections between environmental factors and mental health issues have been postulated in many different countries around the world. Previously undertaken research has shown many possible connections between these fields, especially in relation to air quality and extreme weather events. However, research on this subject is lacking in New Zealand, which is difficult to analyse as an overall nation due to its many micro-climates and regional differences.OBJECTIVES: The aim of this study and subsequent analysis is to explore the associations between environmental factors and poor mental health outcomes in New Zealand by region and predict the number of people with mental health-related illnesses corresponding to the environmental influence.METHODS: Data are collected from various public-available sources, e.g., Stats NZ and Coronial services of New Zealand, which comprised four environmental factors of our interest and two mental health indicators data ranging from 2016 up until 2020. The four environmental factors are air pollution, earthquakes, rainfall and temperature. Two mental health indicators include the number of people seen by District Health Boards (DHBs) for mental health reasons and the statistics on suicide deaths. The initial analysis is carried out on which regions were most affected by the chosen environmental factors. Further analysis using Auto-Regressive Integrated Moving Average(ARIMA) creates a model based on time series of environmental data to generate estimation for the next two years and mental health projected from the ridge regression.RESULTS: In our initial analysis, the environmental data was graphed along with mental health outcomes in regional charts to identify possible associations. Different regions of New Zealand demonstrate quite different relationships between the environmental data and mental health outcomes. The result of later analysis predicts that the suicide rate and DHB mental health visits may increase in Wellington, drop-in Hawke's Bay and slightly increase in Canterbury for the year 2021 and 2022 with different environmental factors considered.CONCLUSION: It is evident that the relationship between environmental and mental health factors is regional and not national due to the many micro-climates that exist around the nation. However, it was observed that not all factors displayed a good relationship between the regions. We conclude that our hypotheses were partially correct, in that increased air pollution was found to correlate to increased mental health-related DHB visits. Rainfall was also highly correlated to some mental health outcomes. Higher levels of rainfall reduced DHB visits and suicide rates in some areas of the country.
One of the great challenges facing human systems today is how to prepare for, manage, and adapt successfully to the profound and rapid changes wreaked by disasters. Wellington, New Zealand, is a capital city at significant risk of devastating earthquake and tsunami, potentially requiring mass evacuations with little or short notice. Subsequent hardship and suffering due to widespread property damage and infrastructure failure could cause large areas of the Wellington Region to become uninhabitable for weeks to months. Previous research has shown that positive health and well-being are associated with disaster-resilient outcomes. Preventing adverse outcomes before disaster strikes, through developing strengths-based skill sets in health-protective attitudes and behaviours, is increasingly advocated in disaster research, practise, and management. This study hypothesised that well-being constructs involving an affective heuristic play vital roles in pathways to resilience as proximal determinants of health-protective behaviours. Specifically, this study examined the importance of health-related quality of life and subjective well-being in motivating evacuation preparedness, measured in a community sample (n=695) drawn from the general adult population of Wellington’s isolated eastern suburbs. Using a quantitative epidemiological approach, the study measured the prevalence of key quality of life indicators (physical and mental health, emotional well-being or “Sense of Coherence”, spiritual well-being, social well-being, and life satisfaction) using validated psychometric scales; analysed the strengths of association between these indicators and the level of evacuation preparedness at categorical and continuous levels of measurement; and tested the predictive power of the model to explain the variance in evacuation preparedness activity. This is the first study known to examine multi-dimensional positive health and global well-being as resilient processes for engaging in evacuation preparedness behaviour. A cross-sectional study design and quantitative survey were used to collect self-report data on the study variables; a postal questionnaire was fielded between November 2008 and March 2009 to a sampling frame developed through multi-stage cluster randomisation. The survey response rate was 28.5%, yielding a margin of error of +/- 3.8% with 95% confidence and 80% statistical power to detect a true correlation coefficient of 0.11 or greater. In addition to the primary study variables, data were collected on demographic and ancillary variables relating to contextual factors in the physical environment (risk perception of physical and personal vulnerability to disaster) and the social environment (through the construct of self-determination), and other measures of disaster preparedness. These data are reserved for future analyses. Results of correlational and regression analyses for the primary study variables show that Wellingtonians are highly individualistic in how their well-being influences their preparedness, and a majority are taking inadequate action to build their resilience to future disaster from earthquake- or tsunami-triggered evacuation. At a population level, the conceptual multi-dimensional model of health-related quality of life and global well-being tested in this study shows a positive association with evacuation preparedness at statistically significant levels. However, it must be emphasised that the strength of this relationship is weak, accounting for only 5-7% of the variability in evacuation preparedness. No single dimension of health-related quality of life or well-being stands out as a strong predictor of preparedness. The strongest associations for preparedness are in a positive direction for spiritual well-being, emotional well-being, and life satisfaction; all involve a sense of existential meaningfulness. Spiritual well-being is the only quality of life variable making a statistically significant unique contribution to explaining the variance observed in the regression models. Physical health status is weakly associated with preparedness in a negative direction at a continuous level of measurement. No association was found at statistically significant levels for mental health status and social well-being. These findings indicate that engaging in evacuation preparedness is a very complex, holistic, yet individualised decision-making process, and likely involves highly subjective considerations for what is personally relevant. Gender is not a factor. Those 18-24 years of age are least likely to prepare and evacuation preparedness increases with age. Multidimensional health and global well-being are important constructs to consider in disaster resilience for both pre-event and post-event timeframes. This work indicates a need for promoting self-management of risk and building resilience by incorporating a sense of personal meaning and importance into preparedness actions, and for future research into further understanding preparedness motivations.
