Background: The beneficial impacts of greenspace availability on mental health are well-documented. However, longitudinal evidence using a spatial lifecourse perspective is rare, leaving the dynamics of how greenspace influences mental health across the lifecourse unclear. This study first uses prospective birth cohort data to examine the associations between greenspace availability in childhood (0-16 years) and mental health in adolescence (16 years) and between greenspace availability and mental health across adulthood (18-40 years). Method: Data were obtained from the Christchurch Health and Development Study, comprised 1,265 cohort members born in Christchurch, New Zealand, in 1977. Mental health outcomes including depressive symptoms, anxiety disorders and suicidal ideation were assessed in adolescence (16 years), and in adulthood (18-40 years). Greenspace availability from birth to age 40 years was measured as the proportion of vegetated areas within circular buffers (radius from 100m to 3000m) around members' geocoded residential addresses using a timeseries impervious surfaces data from 1985 to 2015. Bayesian Relevant Lifecourse exposure models examined the associations between childhood greenspace availability and adolescent mental health and tested for critical/ sensitive age periods. Generalised Estimating Equation logistic regression models assessed the associations between greenspace availability and mental health across adulthood. These analyses were adjusted for various important individual, family, and area-level covariates. Results: No associations were found between childhood greenspace availability and any adolescent mental health conditions. However, in adulthood, a one standard deviation increase in greenspace availability within 1500m and 2000m buffers was associated with a 12% and 13% reduced risk of depressive symptoms, respectively, after adjusting for various covariates. Discussion: This study supports the protective effects of greenspace on adult depressive symptoms, highlighting the significance of employing a spatial lifecourse epidemiology framework to examine the long-term effects of environmental factors on health over the lifecourse.

Internationally, there are observable sex differentials in mortality in many countries, most notably in affluent countries, with women living longer than men. To understand if this is also the case in Aotearoa New Zealand (NZ), we visualise the precise nature and evolution of sex differentials in mortality by age over time, within a wider context of increasing life expectancy and falling mortality. This allows us to determine if NZ mirrors other affluent countries in having a male/female inequality in mortality, and how the inequality has evolved over several generations in NZ. We use newly available single-year mortality data by sex in NZ to visualise and analyse the sex differentials in mortality using an observational study design. Sex and age-specific mortality data were obtained from the human mortality database from 1948 to 2021 for NZ. The data were then processed to create a smoothed data series using a geometric mean of those two years older and younger as well as aggregating the single-year age groups over 90 into a single category due to small numbers. The processed data was then visualised using a lexis diagram. There are clear patterns of elevated mortality ratios at younger ages (18-30) for males compared to females. The relative difference in mortality inequality between the sexes grew between 1950 and 1980 in NZ, before converging between 2000 and 2020. There is a consistent gap of at least 3 years in life expectancy across the study period by sex. Particularly striking is the longstanding nature of this inequality in mortality by sex in NZ and the relative lack of focus from policymakers. This focus on one country, NZ, allows examination of this specific context to understand how policy changes may have exacerbated or ameliorated trends in male/female mortality inequality.

•Examines association between earthquake exposure and weight-change at age 40 years.•The associations were adjusted by prior life course covariates.•Exposure to an earthquake did not increase body mass index at six-years follow-up.•Exposure to an earthquake increased waist circumference at six-years follow-up.•A dose-response relationship was evident by severity of exposure for waist circumference.

BACKGROUND:A growing body of evidence supports an association between air pollution exposure and adverse mental health outcomes, especially in adulthood however, very little is known about the effects of early life air pollution exposure during childhood. We examined longitudinal associations between the extent and timing of children's annual air pollution exposure from conception to age 10 years and a wide range of cognitive, educational and mental health outcomes in childhood and adolescence that were assessed prospectively as part of a large birth cohort study. METHODS:We linked historical air pollution data (μg.m-3) from pregnancy to age 10 years (1976-1987) using the addresses of all cohort members (n = 1265) of the Christchurch Health and Development Study (CHDS) who were born in New Zealand in mid-1977. Latent Class Growth Mixture Models were used to characterise different trajectories of air pollution exposure from the prenatal period to age 10 years. We then examined associations between these air pollution exposure trajectories and 16 outcomes in childhood and adolescence using R Studio and Stata V18. FINDINGS:Four air pollution exposure trajectories were identified: i) low, ii) persistently high, iii) high prenatal and postnatal, and iv) elevated pre-school exposure. While some associations were attenuated, after adjusting for a variety of covariates spanning childhood, family sociodemographic background and family functioning characteristics, several associations remained. Relative to the lowest exposure trajectory, persistently high and high prenatal and postnatal exposure were both related to attentional problems. High prenatal and postnatal was also related to higher risk of substance abuse. Elevated pre-school exposure was associated with conduct problems, lower educational attainment and substance abuse and persistently high childhood exposure increased risk of substance abuse. CONCLUSIONS:Our study highlights potential adverse and longer-term impacts of air pollution exposure during childhood on subsequent development in later life.

Despite documented associations between childhood area-level socioeconomic status (SES), residential mobility and health, studies in this domain rarely use lifecourse study designs. This study examined temporal patterns of four residential mobility typologies based on area-level SES exposure from birth to 16 years. We devised four main residential mobility typologies: advantaged stayers (remaining in high SES areas), disadvantaged stayers (remaining in low SES areas), advantaged or upward movers (moving between high SES areas or transitioning from low to high SES areas), and disadvantaged or downward movers (moving between low SES areas or transitioning from high to low SES areas). Secondly, the research examined selected sociodemographic characteristics associated with the residential mobility typologies and whether these associations varied by age. Data from the Christchurch Health and Development (CHDS) prospective birth cohort study were used to obtain individual (i.e., gender, ethnic) and family sociodemographic (i.e., family SES) characteristics, and home addresses from birth to 16 years. Geocoded home addresses were linked to area-level SES. Two-level multinomial logistic regression models examined associations between sociodemographic characteristics and residential mobility typologies and their variations by age. Disadvantaged stayers constituted over one-fifth of the cohort during most of childhood. Children with Māori ethnicity, younger mothers, family instability, and childhood adversity are more vulnerable to frequent moves coupled with exposure to low area-level SES. Our study paves the way for the exploration of childhood environmental exposures and later-life health within a spatial lifecourse epidemiology framework.

Mental health conditions pose a significant public health challenge, and low area-level socioeconomic status (SES) is a potentially important upstream determinant. Childhood exposure might have influences on later-life mental health. This study, utilises data from the Christchurch Health and Development Study birth cohort, examining the impact of area-level SES trajectories in childhood (from birth to age 16) on mental health at age 16 and from age 18-40 years. Findings revealed some associations between distinct SES trajectories and mental health. The study underscores the importance of using a spatial lifecourse epidemiology framework to understand long-term environmental impacts on later-life health.

This commentary primarily discusses new data sources featuring fine grained spatio-temporal data that have emerged in recent years from a variety of sources that previously did not exist or that were not easily accessible either from public or commercial entities. The focus here is on mobile phone location data (MPLD) as one avenue for potential new directions that have emerged and become increasingly relevant to a constellation of thematic areas across population research. I also discuss how new data sources, principally MPLD, aid in addressing some of the longstanding challenges and limitations of existing secondary data sources, while simultaneously creating both opportunities and limitations for researchers.Furthermore, a discussion of some salient potential applications and pitfalls of big geospatial data are articulated when these are applied to population research internationally, but also in Aotearoa New Zealand. It could be argued that there is an explicit challenge to the longstanding conceptualisation of static residence-based measures applied to a range of thematic areas across population research, such as understanding movement or migration. We further posit that it is timely to (re)consider the role that big geospatial data, specifically MPLD, plays in understanding central questions in both geography and demography, such as where, when and why do people move?It can be demonstrated that there is a wealth of big geospatial data that now can be exploited leading to opportunities for better understanding of the dynamic processes related to people and places. It could be argued that it is time for a more fulsome engagement with MPLD and other big geospatial data sets and techniques to grapple with both the opportunities and challenges for understanding population dynamics, as well as the patterns and processes that give rise to inequalities and inequities between people and places in Aotearoa New Zealand and further afield.

Few metrics of area-level socioeconomic deprivation exist that are comparable over time and space. This study aimed to create a consistent historic time-series area-level deprivation metric for 1981, 1986 and 1991 in Aotearoa New Zealand (hereafter, New Zealand) using census data at census area unit (CAU) level. Consistent variables, geography and statistical methods were employed over time. The metric revealed a gradual worsening of area-level deprivation in NZ from 1981 to 1991. We provide a historical perspective on New Zealand’s socioeconomic conditions during the 1980s and early 1990s, which provides a platform for longitudinal studies in New Zealand to account for historical area-level deprivation.

Spatial life course epidemiological approaches offer promise for prospectively examining the impacts of air pollution exposure on longer-term health outcomes, but existing research is limited. An essential aspect, often overlooked is the comprehensiveness of exposure data across the lifecourse. The primary objective was to meticulously reconstruct historical estimates of air pollution exposure to include prenatal exposure as well as annual exposure from birth to 10 years (1977-1987) for each cohort member. We linked these data from a birth cohort of 1,265 individuals, born in Aotearoa/New Zealand in mid-1977 and studied to age 40, to historical air pollution data to create estimates of exposure from birth to 10 years (1977-1987). Improvements in air quality over time were found. However, outcomes varied by demographic and socioeconomic factors. Future research should examine how inequitable air pollution exposure is related to health outcomes over the life course.

This study aimed to investigate exposure to a major disaster by developing a more accurate representation of the exact exposure that individuals in a birth cohort experienced using geospatial data. Individuals were categorised by their residential and non-residential locations at the time of the disaster. Our results revealed that over two-thirds of individuals were misclassified when compared to using residential address as their sole point of exposure. We provide new insight into post-disaster exposure research where it is evident that the location in which an individual was at the time of disaster matters in determining ‘true’ exposure.

This short report of international case studies looks systematically at a select few case studies from across the world focused on various aspects of emission reduction best practice. After a brief overview of the location and background we discuss the neighbourhood design characteristics and interventions with a focus on the specific plans or policies enacted. We then turn to discuss the impact of the aforementioned policies and plans with a view to briefly covering the salient impacts. We conclude each case study with some relevant thoughts and potential applications to the Aotearoa New Zealand context. References to materials are given at the end of each case study. Each case study is designed to give a brief overview of the relevant impacts and applications rather than an exhaustive in-depth study of each place for brevity. We also include a brief overview of other relevant research in an appendix at the end of the document.

This study investigated associations between change in the food environment and change in measured body mass index (BMI) and waist circumference (WC) in the Christchurch Health and Development Study (CHDS) birth cohort. Our findings suggest that cohort members who experienced the greatest proportional change towards better access to fast food outlets had the slightly larger increases in BMI and WC. Contrastingly, cohort members who experienced the greatest proportional change towards shorter distance and better access to supermarkets had slightly smaller increases in BMI and WC. Our findings may help explain the changes in BMI and WC at a population level.

Aim: to illuminate what Spatial Microsimulation is; to define some key terminology and to outline the potential usefulness of Spatial Microsimulation to simulate policy scenarios.

The overarching aim of this short report is to provide a more digestible summary and overview of the international case studies report published previously; to identify and summarise the key policy in the area relating to our carbon-neutral neighbourhoods project; to provide some key lessons learned for New Zealand in order to understand better the potential avenues for meeting carbon reduction ambitions.

This nationwide geospatial study from Aotearoa New Zealand describes the frequency and spatial patterning of residential mobility and examines the interplay between patterns of residential mobility and the environments in which adults reside. Data from the Integrated Data Infrastructure (n = 4,781,268 adults) defined levels of residential mobility in 2016-2020. We then used nationwide environmental data included within the New Zealand Healthy Location Index to define access to a range of health-promoting and health-constraining features. We identified 29 spatial clusters based on the mobility characteristics of the population living within selected administrative units that were further classified into five groups based on the similarity of residential mobility groups. Each group was described by its relation to the Healthy Location Index, urbanicity and ethnicity. A greater proportion of residential mobility was related to metropolitan and large regional centres, and Ma over bar ori, Pacific and Asian ethnicities. Areas with higher levels of vulnerable mobile population were identified in the North Island (Northland, Gisborne, Whanganui and urban pockets of Auckland, Hamilton, Napier and Hastings). While there was poor access to health-promoting environments for the mobile population living in the inner cities, areas with higher residential mobility elsewhere are often associated with better access to health-promoting and neutral features.

The environment may be an important influence on adolescent behaviour. We combined accelerometry and global positioning system data to investigate how the environment was related to physical activity and sedentary behaviour. Adolescents spent most of their time in very close proximity to a range of both health-promoting and health-constraining features. Several associations were detected between time spent in areas with the greatest access to health-promoting features and reduced sedentary time and less travel time by motor vehicle. The environment may contribute to the variation in adolescent activity behaviour.

The COVID-19 pandemic continues to have unprecedented impacts on people and places globally, challenging the ability of both government and citizens to respond. The use of Nonpharmaceutical Interventions (NPIs) has been widespread in attempting to curtail the spread of COVID-19. However, there were important distinctions in how governments chose to use the public health tools at their disposal. We focus on the experience of Aotearoa New Zealand (NZ), a jurisdiction that has been featured as arguably one of the most successful and stringent in attempts to eliminate COVID-19 from the population. We also explore and examine the social and spatial patterns that exist and have widened within NZ as the pandemic has unfolded, exposing the underlying social structures and fractures that now exist and persist in many countries. Initially, a geographic approach was absent, but as the pandemic progressed, this became a key aspect of the public health response. This chapter explores a range of data sources from the ongoing pandemic in NZ. We conclude by discussing an emerging syndemic, concluding the chapter with policy implications and potential future research directions.