Census Area Unit Research Articles

Testing methods to estimate population size for wastewater treatment plants using census data: Implications for wastewater-based epidemiology

In wastewater-based epidemiology (WBE), wastewater loads are commonly reported as a per capita value. Census population counts are often used to obtain a population size to normalise wastewater loads. However, the methods used to calculate the population size of wastewater treatment plants (WWTPs) from census data are rarely reported in the WBE literature. This is problematic because the geographical extents of wastewater catchments and census area units rarely align perfectly with each other and exist at different spatial scales. This complicates efforts to estimate the number of people serviced by WWTPs in these census area units. This study compared four geospatial methods to combine wastewater catchment areas and census area units to calculate the census population size of wastewater treatment plants. These methods were applied nationally to WWTPs across New Zealand. Population estimates varied by up to 73 % between the methods, which could skew comparisons of per capita wastewater loads between sites. Variability in population estimates (relative standard deviation, RSD) was significantly higher in smaller catchments (rs = −0.727, P < .001), highlighting the importance of method selection in smaller sites. Census population estimates were broadly similar to those provided by wastewater operators, but significant variation was observed for some sites (ranging from 42 % lower to 78 % higher, RSD = 262 %). We present a widely applicable method to calculate population size from census, which involves disaggregating census area units by individual properties. The results reinforce the need for transparent reporting to maintain confidence in the comparison of WBE across sites and studies.

Influences on Public Transport Utilization: The Case of Auckland

Regression analysis is applied to cross-sectional data for 318 census area units served by the public transportation system in Auckland, New Zealand. The goal is to ascertain the determinants of public transport patronage for the purpose of commuting to work in the region. The analysis addresses both the modifiable areal units problem and spatial autocorrelation. Elasticity estimates are derived for a number of hypothesized drivers of patronage. The paper shows that adjusting for spatial autocorrelation improves the fit of the regression model to the data, a finding that should be of interest to public transportation planners and analysts working with cross-sectional data of a geographic nature.

Rising immigration and falling native-born home ownership: a spatial econometric analysis for New Zealand

In the last two decades the foreign-born share of New Zealand’s population increased far faster than in other rich countries. We apply spatial econometric models to a three-wave panel of 1851 census area units to examine impacts of higher foreign-born population shares on home ownership rates, especially for native-born residents. A standard deviation higher foreign-born share is associated with a one-sixth of a standard deviation lower ownership rate for the native-born. Much of the impact is indirect, with higher foreign-born shares in one area spilling over into lower native-born ownership rates elsewhere.

Spatial behavior of cancer care utilization in distance decay in the Northeast region of the U.S.

PurposeSpatial behavior of patients in utilizing health care reflects their travel burden or mobility, accessibility for medical service, and subsequently outcomes from treatment. This paper derives the best-fitting distance decay function to capture the spatial behaviors of cancer patients in the Northeast region of the U.S., and examines and explains the spatial variability of such behaviors across sub-regions. Principal results(1) 46.8%, 85.5%, and 99.6% of cancer care received was within a driving time of 30, 60, and 180 min, respectively. (2) The exponential distance decay function is the best in capturing the travel behavior of cancer patients in the region and across most sub-regions. (3) The friction coefficient in the distance decay function is negatively correlated with the mean travel time. (4) The best-fitting function forms are associated with network structures. (5) The variation of the friction coefficient across sub-regions is related to factors such as urbanicity, economic development level, and market competition intensity. Major conclusionsThe distance decay function offers an analytic metric to capture a full spectrum of travel behavior, and thus a more comprehensive measure than average travel time. Examining the geographic variation of travel behavior needs a reliable analysis unit such as organically defined “cancer service areas,” which capture relevant health care market structure and thus are more meaningful than commonly-used geopolitical or census area units.

Spatial-temporal patterns of childhood immunization in New Zealand (2006-2017): an improving pattern but not for all?

Declining childhood immunization represents a serious public health problem globally and in New Zealand. To guide efforts to increase immunization coverage, this study monitors nationwide change in immunization coverage since the introduction of the National Immunisation Register (NIR) in 2005 and spatiotemporal patterns of immunization coverage from 2006 to 2017. The study population consisted of 4482499 individual immunization records that were obtained from the NIR (2005-2017). Data on yearly and average immunization coverage in census area units (CAUs) in New Zealand were calculated by milestone age (6/8/12/18/24/60/144 months). Data for 2005 were excluded due to missing records in the introductory period of the NIR. We analyzed spatial and spatiotemporal patterns using Gi* and SaTScan methods. Immunization coverage improved since the introduction of the NIR in 2005, reaching a peak in 2014 and 2015 with a slight decrease in 2016 and 2017. Well and insufficiently immunized areas were identified with spatial autocorrelation analyses highlighting several hot- and cold-spots. Comparison of CAUs with neighbouring CAUs allowed for the identification of places where immunization coverage was significantly higher or lower than expected, over both time and space. We provide the first spatiotemporal analysis of childhood immunization in New Zealand that utilizes a large sample of over 4.4 million individual immunization records. Our spatial analyses enable policymakers to understand the development of childhood immunization coverage and make more effective prevention strategies in New Zealand.

Investigating spatial variation and change (2006-2017) in childhood immunisation coverage in New Zealand.

Immunisation is a safe and effective way of protecting children and adults against harmful diseases. However, immunisation coverage of children is declining in some parts of New Zealand. Use a nationwide sample to first, examine the socioeconomic and demographic determinants of immunisation coverage and spatial variation in these determinants. Second, it investigates change in immunisation coverage in New Zealand over time. Individual immunisation records were obtained from the National Immunisation Register (NIR) (2005-2017; 4,482,499 events). We calculated the average immunisation coverage by year and milestone age for census area units (CAU) and then examined the immunisation coverage by selected socioeconomic and demographic determinants. Finally, local variations in the association between immunisation coverage and selected determinants were investigated using geographically weighted regression. Findings showed a decrease of immunisation rates in recent years in CAUs with high immunisation coverage in the least deprived areas and increasing immunisation rates in more deprived areas. Nearly all explanatory variables exhibited a spatial variation in their association with immunisation coverage. For instance, the strongest negative effect of area-level deprivation is observed in the northern part of the South Island, the central-southern part of the North Island, around Auckland, and in Northland. Our findings show that childhood immunisation coverage varies by socioeconomic and demographic factors across CAUs. We also identify important spatial variation and changes over time in recent years. This evidence can be used to improve immunisation related policy in New Zealand.

Area-level deprivation, childhood dental ambulatory sensitive hospitalizations and community water fluoridation: evidence from New Zealand.

We examined the association between area-level deprivation and dental ambulatory sensitive hospitalizations (ASH) and considered the moderating effect of community water fluoridation (CWF). The hypothesis was that higher levels of deprivation are associated with higher dental ASH rates and that CWF will moderate this association such that children living in the most deprived areas have greater health gain from CWF. Dental ASH conditions (dental caries and diseases of pulp/periapical tissues), age, gender and home address identifier (meshblock) were extracted from pooled cross-sectional data (Q3, 2011 to Q2, 2017) on children aged 0-4 and 5-12 years from the National Minimum Dataset, New Zealand (NZ) Ministry of Health. CWF was obtained for 2011 and 2016 from the NZ Institute of Environmental Science and Research. Dental ASH rates for children aged 0-4 and 5-12 years (/1000) were calculated for census area units (CAUs). Multilevel negative binomial models investigated associations between area-level deprivation, dental ASH rate and moderation by CWF status. Relative to CWF (2011 and 2016), no CWF (2011 and 2016) was associated with increased dental ASH rates in children aged 0-4 [incidence rate ratio (IRR) = 1.171 (95% confidence interval 1.064, 1.288)] and aged 5-12 years [IRR = 1.181 (1.084, 1.286)]. An interaction between area-level deprivation and CWF showed that the association between CWF and dental ASH rates was greatest within the most deprived quintile of children aged 0-4 years [IRR = 1.316 (1.052, 1.645)]. CWF was associated with a reduced dental ASH rate for children aged 0-4 and 5-12 years. Children living in the most deprived areas showed the greatest effect of CWF on dental ASH rates, indicating that the greater health gain from CWF occurred for those with the highest socio-economic disadvantage. Variation in CWF contributes to structural inequities in oral-health outcomes for children.

How strong is the relationship between scabies and acute rheumatic fever? An analysis of neighbourhood factors.

Recent studies have linked scabies with acute rheumatic fever (ARF). We explored the relationship, by neighbourhood, between permethrin dispensing as an indicator of scabies prevalence and ARF cases over the same period. Incident cases of ARF notified to public health between September 2015 and June 2018 and the annual incidence of prescribing by neighbourhood over the same period were analysed. Evidence of an association between permethrin and ARF was obtained by carrying out Poisson regression of the rate of ARF in terms of permethrin rate at the census area unit level, with adjustment for ethnicity and socio-economic deprivation. A total of 413 neighbourhoods were included. The incidence of ARF varied between 0 and 102 per 100 000 people per year (mean 4.3). In contrast, the annual incidence of dispensing of permethrin varied between 0 and 3201 per 100 000 people per year (mean 771). A strong association was observed between the two variables. In an adjusted quasi-Poisson model, permethrin-dispensing rates were strongly associated with ARF incidence, with a change from the 16th to the 84th centile associated with a 16.5-fold increase in incidence (95% confidence interval: 3.82-71.6). Permethrin prescribing as an indicator of scabies is strongly associated with the incidence of ARF. Considered together with other studies, this evidence suggests that improving scabies control may reduce the burden of ARF in New Zealand.

Commuting to Diversity

Does commuting increase workers' exposure to difference and diversity? The uneven spatial distribution of different population subgroups within cities is well documented. Individual neighbourhoods are generally less diverse than cities as a whole. Auckland is New Zealand's most diverse city, but the impacts of diversity are likely to be less if interactions between different groups are limited by spatial separation. Studies of spatial sociodemographic diversity generally measure the diversity of local areas based on who lives in them. In this study, we examine measures of exposure to local cultural diversity based on where people work as well as where they live. Our measure of cultural diversity is based on country of birth, with ethnicity breakdowns for the New Zealand (NZ) born. The study also examines whether the relationship between commuting and exposure to diversity differs between workers with different skills or types of job. The study focuses on diversity and commuting patterns within Auckland, using 2013 census microdata, and using local diversity measures calculated for each census area unit. We find that commuters who self-identify as NZ-born Europeans and residents born in England (together accounting for close to half of all commuters) are, of all cultural groups, the least exposed to diversity in the neighbourhoods where they live. Overall, commuting to the workplace raises exposure to cultural diversity, and to the greatest extent for these two groups.

Geosimulation approach for filling the gap of non‐response smoking data from the census 2013: A spatial analysis of census area unit geographies

AbstractNew Zealand has a goal of becoming a smoke‐free nation by 2025, with the aim of reducing smoking prevalence 5% or less. While the 2013 census provides good coverage about smoking prevalence, 9.3% of the population did not return valid responses. The aim of this article is to use the tool, spatial microsimulation, to estimate the missing non‐response data based on demographics and income at the census area unit (CAU) level to provide a more complete picture of the New Zealand smoking landscape. Results show that, including estimated non‐response data, only two CAUs meet the current smoke‐free goal.

Mitigating the zonal effect in modeling urban population density functions by Monte Carlo simulation

Most empirical studies indicate that the pattern of declining urban population density with distance from the city center is best captured by a negative exponential function. Such studies usually use aggregated data in census area units that are subject to several criticisms such as modifiable areal unit problem, unfair sampling, and uncertainty in distance measure. In order to mitigate these concerns associated, this paper uses Monte Carlo simulation to generate individual residents that are consistent with known patterns of population distribution. By doing so, we are able to aggregate population back to various uniform area units to examine the scale and zonal effects explicitly. The case study in Chicago area indicates that the best fitting density function remains exponential for data in census tracts or block groups, however, the logarithmic function becomes a better fit when uniform area units such as squares, triangles or hexagons are used. The study also suggests that the scale effect remain to some extent in all area units, and the zonal effect be largely mitigated by uniform area units of regular shape.

Green Space and Depression during Pregnancy: Results from the Growing Up in New Zealand Study.

Background: Antenatal depression is an important contributor to poor maternal health experienced by some women. This study aimed to determine whether exposure to green space during pregnancy is associated with less depression, and whether this association is moderated by relevant factors, such as age, education, self-identified ethnicity, physical activity, residential rurality, and socioeconomic status. Methods: Health data were sourced from the cohort study “Growing Up in New Zealand” comprised of 6772 participants. Green space was estimated based on the proportion of green space within the Census Area Unit. Adjusted logistic mixed effect models were used to investigate the association between green space and antenatal depression after controlling for confounding variables. Results: Maternal exposure to green space were not associated with lower odds of antenatal depression. Indications of effect modifications due to relevant factors were not observed. Conclusions: This study did not determine an association between access to green space (measured based on the distance to the nearest green space) and antenatal depression. Therefore, a link between green space and antenatal depression was not established. For that reason, ensuring residential areas contain adequate green space may or may not be helpful in preventing antenatal depression and adverse health outcomes associated with this depression. More studies focusing on pregnant women in a range of social contexts, and considering both exposure and access to green space, are warranted to determine the relationships between green space and antenatal depression.

Mapping crime harm and priority locations in New Zealand: A comparison of spatial analysis methods

Despite progress being advanced with spatial approaches to crime and crime control, the geography of crime harm has to date received little attention. The recent development of “Crime Harm Indices”, which weight crimes by an estimate of the relative harm they cause, offers an opportunity to improve on volume based spatial analysis approaches to identify where crime harm concentrates.This study aims to address this issue via the use of a Crime Harm Index (CHI) developed for New Zealand. By contrast to localized ‘harm-spotting’ analysis, we apply a census unit based approach to identify, at a macro level, the neighborhoods and wider communities suffering the highest crime harm in New Zealand. This approach enables harm to be viewed not only as a total Index but as a rate controlled for population and allows for the identification of census based sociodemographic factors which predict harm. Specifically, this paper compares the CHI with the New Zealand Priority Locations Index (PLI), an existing census unit based crime analysis tool which combines crime and demographic variables to identify communities vulnerable to crime and disorder issues.In this study CHI and PLI scores were calculated for Census Area Units (normally containing 3000–5000 population) across New Zealand. Bivariate correlations and a general linear model were used to determine the relationships between the CHI and PLI and additional population related variables. The CHI and PLI were weakly correlated, with population size and urban/rural categorization also accounting for CHI variance. Mapping techniques are used to illustrate outlier locations where the CHI and PLI differ widely and to identify location features which may assist in explaining CHI/PLI differences.This work exemplifies a novel geographic approach to the problem of crime harm with implications for resource allocation at national through to local levels. Wider implications for the theory and practice of crime and crime harm control are discussed, along with limitations of the study and areas for further research.

A Multi-Scale Analysis of Single-Unit Housing Water Demand Through Integration of Water Consumption, Land Use and Demographic Data

Studies evaluating the determinants of water demand typically use household-scale data or aggregated data. The household-scale data basically is preferred since it can reveal the heterogeneity in responses to the demand drivers across different consumer groups. However, the scarcity of household-scale data and its high data collection cost generally have limited the studies to rely on small samples of household data. Thus, they failed to show the spatial variation of water demand. In contrast, the aggregated studies have assessed the spatial variation of water use however they overlooked the variations across households. Using a rich source of GIS-based urban databases in Auckland, New Zealand, this study overcame this challenge by developing a large sample of 31000 single-unit housing through integration of household-level water consumption and property data with micro-scale household demographics information. This large dataset enabled this study to evaluate the water consumption both at the household scale and the census area unit scale. Panel data models were used for the water demand analysis in both scales. The proposed multi-scale analysis approach provided detailed knowledge about water consumption and its major determinants across different consumer groups and urban areas. This information may help water planners to more reliably plan water supply systems and manage consumption in the complex urban environments.

Cryptosporidiosis Risk in New Zealand Children Under 5 Years Old is Greatest in Areas with High Dairy Cattle Densities.

The public health risks associated with dairy farming intensification are an emerging concern. We examine the association between dairy cattle density and cryptosporidiosis risk in children <5years old in New Zealand from 1997 to 2008, a period of rapid intensification of the dairy industry. Multi-level Poisson regression was used to model reported cryptosporidiosis (N=3869 cases) incidence in relation to dairy cattle densities across urban and rural areas separately, after controlling for microbiological quality of public drinking water supplies and neighbourhood socio-economic factors using the Census Area Unit of residence. Within urban areas, the risk of cryptosporidiosis in children less than 5years old was significantly, positively associated with medium and high dairy cattle density IRR 1.3 (95% CI 1.2, 1.5) and 1.5 (95% CI 1.2, 1.9) respectively, when compared to areas with no dairy cattle. Within rural areas, the incidence risk of cryptosporidiosis in children less than 5years old were significantly, positively associated with medium and high dairy cattle density: IRR 1.7 (95% CI 1.3, 2.3) and 2.0 (95% CI 1.5, 2.8) respectively, when compared to areas with no dairy cattle. These results have public health implications for children living on and in proximity to intensively stocked dairy cattle farms.

Green Space and Physical Activity in Pregnant Women: Evidence From the Growing Up in New Zealand Study.

Exposure to green space has been associated with increased physical activity. However, it is not clear whether this association is because active people preferentially live in greener areas. Relationships between exposure to green space and physical activity during pregnancy are not well defined. Our objective was to determine whether exposure to green space was associated with physical activity in pregnant women. The current study was completed within the Growing Up in New Zealand cohort study of 6772 pregnant women. The proportion of green space in each census area unit was determined and geocoded to residential address. The association between exposure to green space and physical activity was determined using logistic regression analyses after controlling for confounding variables. Exposure to green space was not associated with participation in physical activity during first trimester and the remainder of pregnancy once preference for living in greener neighborhoods was taken into account. The lack of association between green space and physical activity found in this study does not necessarily mean that living in green space will not translate into better pregnancy health. Preference for living in greener neighborhoods should be considered when investigating relationships between green space and physical activity.

Alcohol outlet density and violence: A geographically weighted regression approach.

We investigate the relationship between outlet density (of different types) and violence (as measured by police activity) across the North Island of New Zealand, specifically looking at whether the relationships vary spatially. We use New Zealand data at the census area unit (approximately suburb) level, on police-attended violent incidents and outlet density (by type of outlet), controlling for population density and local social deprivation. We employed geographically weighted regression to obtain both global average and locally specific estimates of the relationships between alcohol outlet density and violence. We find that bar and night club density, and licensed club density (e.g. sports clubs) have statistically significant and positive relationships with violence, with an additional bar or night club is associated with nearly 5.3 additional violent events per year, and an additional licensed club associated with 0.8 additional violent events per year. These relationships do not show significant spatial variation. In contrast, the effects of off-licence density and restaurant/café density do exhibit significant spatial variation. However, the non-varying effects of bar and night club density are larger than the locally specific effects of other outlet types. The relationships between outlet density and violence vary significantly across space for off-licences and restaurants/cafés. These results suggest that in order to minimise alcohol-related harms, such as violence, locally specific policy interventions are likely to be necessary. [Cameron MP, Cochrane W, Gordon C, Livingston M. Alcohol outlet density and violence: A geographically weighted regression approach. Drug Alcohol Rev 2016;35:280-288].

Novel use of three administrative datasets to establish a cohort for environmental health research.

BackgroundIn recent years publications have called for increased use of administrative data for research; predicted that use would rise; and discussed possible ethical parameters for that use. This paper describes the novel combination of three administrative datasets to create a population cohort for environmental health research, and investigates the potential use of a national health register as a total population denominator.MethodsWe matched a national health register (the New Zealand national health index or NHI) to Quotable Value New Zealand Ltd (QV) nationwide residential dwelling data, and to hospital admissions data, to create a national matched cohort with health outcomes for the period 2000 – 2006. We then compared population distribution and hospitalisation rates by gender, age, ethnic group and Census Area Unit-based socio-economic deprivation index across the Census, NHI and matched cohort populations.ResultsThe NHI population was 23% larger than the Census. Differences between the NHI and Census were most marked in those aged over 90 years; with ethnicity unknown or an unassigned Census area unit; and in Asian Peoples aged under 30 years. The match rate between QV and NHI data was 70%. There were further differences between the NHI and matched cohort populations, particularly for rural areas and older age groups. Compared to Census-based rates, NHI and cohort-based hospitalisation rates were higher in those aged 75 and over, differed by ethnicity, and had less socio-economic gradient.ConclusionsThe NHI was larger than the Census due to record duplication and entries for people residing overseas remaining on file under New Zealand addresses. NHI and QV matching was incomplete due to NHI address data being poor quality or not suitable for matching. To better approximate true hospitalisation rates, studies using the NHI as a cohort should exclude those aged over 90 years; or with ethnic group or Census area unit unknown. Cohort hospitalisation rates should also be adjusted for differences from the Census, particularly the lower hospitalisation rates for those aged 75 and over, and other differences by age, ethnic group and socio-economic deprivation.

Pasture, Poos and People: a Space-Time Analysis of Livestock Density and Cryptosporidium Infections in Humans

Enteric zoonotic infections in New Zealand are among the highest in the developed world. The country has recently experienced rapid intensification of livestock production, in response to the global demand for dairy products. However, the environmental health risks associated with agricultural intensification are poorly understood. We used spatio-temporal methods to analyse weekly notifications of human Cryptosporidium infections (1997-2008, N=8688) geocoded to census area units (N= 1769). Explanatory variables included livestock density (sheep, beef and dairy cattle, poultry, pigs), temperature, rainfall, drinking water quality and demographic data, interpolated where necessary to match the notification data. Infection hotspots recurred consistently in a region of intensified dairy cattle production (p&lt;0.05). Multivariate analysis identified living in a rural area (IR 1.64 (95%CI 1.48-1.83)), dairy cattle density (IR 1.058 (95% CI 1.02-1.09)), and the proportion of children under 4 years old (IR 1.16 (95% CI 1.10- 1.23)) as significant risk factors for infection. Population density (IR 0.88 (95% CI 0.82-0.93)), the proportion of the population = 65 years (IR 0.88 (95% CI 0.83- 0.93)), the proportion identifying with Maori (IR 0.21 (95% CI 0.11- 0.38), Pacific Island (IR 0.10 (95% CI 0.04- 0.25) and Asian ethnicities (IR 0.11 (95% CI 0.05-0.27) and weekly average temperature (IR 0.91 (95% CI 0.86- 0.97) were inversely associated with risk of infection. Further expansion of the dairy farming sector is likely. In New Zealand, such livestock intensification may lead to increases in zoonotic infections, especially in rural preschool children. These findings suggest opportunities for targeted interventions to reduce the health impacts of intensified livestock production.

Household crowding associated with childhood otitis media hospitalisations in New Zealand.

To examine the association between hospitalisations for otitis media and area-level measures of household crowding among children in New Zealand. Counts of hospital admissions for otitis media by census area unit were offset against population data from the 2006 national census. Area-level household crowding, exposure to tobacco smoke in the home, equivalised income and individual-level characteristics age and sex were adjusted for. To examine effect modification by ethnicity, three separate poisson models were examined for the total, Māori and non-Māori populations. Household crowding was significantly associated with hospital admissions for otitis media after adjustment in all three models. Neighbourhoods with the highest compared to the lowest proportion of crowded homes exhibited incidence rate ratios of 1.25 (95%CI 1.12-1.37) in the total population, 1.59 (95%CI 1.21-2.04) in the Māori restricted model and 1.17 (95%CI 1.06-1.32) in the non-Māori restricted model. Otitis media hospitalisations are associated with area-level measures of household crowding and other risk factors in this ecological study. The largest increase in otitis media incidence relative to neighbourhood rates of household crowding was exhibited among Māori cases of otitis media. This study adds weight to the growing body of literature linking infectious disease risk to overcrowding in the home.