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Geary RS, Thompson DA, Garrett JK, Mizen A, Rowney FM, Song J, White MP, Lovell R, Watkins A, Lyons RA, Williams S, Stratton G, Akbari A, Parker SC, Nieuwenhuijsen MJ, White J, Wheeler BW, Fry R, Tsimpida D, Rodgers SE. Green-blue space exposure changes and impact on individual-level well-being and mental health: a population-wide dynamic longitudinal panel study with linked survey data. PUBLIC HEALTH RESEARCH 2023; 11:1-176. [PMID: 37929711 DOI: 10.3310/lqpt9410] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2023] Open
Abstract
Background Cross-sectional evidence suggests that living near green and blue spaces benefits mental health; longitudinal evidence is limited. Objectives To quantify the impact of changes in green and blue spaces on common mental health disorders, well-being and health service use. Design A retrospective, dynamic longitudinal panel study. Setting Wales, UK. Participants An e-cohort comprising 99,682,902 observations of 2,801,483 adults (≥ 16 years) registered with a general practice in Wales (2008-2019). A 5312-strong 'National Survey for Wales (NSW) subgroup' was surveyed on well-being and visits to green and blue spaces. Main outcome measures Common mental health disorders, general practice records; subjective well-being, Warwick-Edinburgh Mental Well-being Scale. Data sources Common mental health disorder and use of general practice services were extracted quarterly from the Welsh Longitudinal General Practice Dataset. Annual ambient greenness exposure, enhanced vegetation index and access to green and blue spaces (2018) from planning and satellite data. Data were linked within the Secure Anonymised Information Linkage Databank. Methods Multilevel regression models examined associations between exposure to green and blue spaces and common mental health disorders and use of general practice. For the National Survey for Wales subgroup, generalised linear models examined associations between exposure to green and blue spaces and subjective well-being and common mental health disorders. Results and conclusions Our longitudinal analyses found no evidence that changes in green and blue spaces through time impacted on common mental health disorders. However, time-aggregated exposure to green and blue spaces contrasting differences between people were associated with subsequent common mental health disorders. Similarly, our cross-sectional findings add to growing evidence that residential green and blue spaces and visits are associated with well-being benefits: Greater ambient greenness (+ 1 enhanced vegetation index) was associated with lower likelihood of subsequently seeking care for a common mental health disorder [adjusted odds ratio (AOR) 0.80, 95% confidence interval, (CI) 0.80 to 0.81] and with well-being with a U-shaped relationship [Warwick-Edinburgh Mental Well-being Scale; enhanced vegetation index beta (adjusted) -10.15, 95% CI -17.13 to -3.17; EVI2 beta (quadratic term; adj.) 12.49, 95% CI 3.02 to 21.97]. Those who used green and blue spaces for leisure reported better well-being, with diminishing extra benefit with increasing time (Warwick-Edinburgh Mental Well-being Scale: time outdoors (hours) beta 0.88, 95% CI 0.53 to 1.24, time outdoors2 beta -0.06, 95% CI -0.11 to -0.01) and had 4% lower odds of seeking help for common mental health disorders (AOR 0.96, 95% CI 0.93 to 0.99). Those in urban areas benefited most from greater access to green and blue spaces (AOR 0.89, 95% CI 0.89 to 0.89). Those in material deprivation benefited most from leisure time outdoors (until approximately four hours per week; Warwick-Edinburgh Mental Well-being Scale: time outdoors × in material deprivation: 1.41, 95% CI 0.39 to 2.43; time outdoors2 × in material deprivation -0.18, 95% CI -0.33 to -0.04) although well-being remained generally lower. Limitations Longitudinal analyses were restricted by high baseline levels and limited temporal variation in ambient greenness in Wales. Changes in access to green and blue spaces could not be captured annually due to technical issues with national-level planning datasets. Future work Further analyses could investigate mental health impacts in population subgroups potentially most sensitive to local changes in access to specific types of green and blue spaces. Deriving green and blue spaces changes from planning data is needed to overcome temporal uncertainties. Funding This project was funded by the National Institute for Health and Care Research (NIHR) Public Health Research programme (Project number 16/07/07) and will be published in full in Public Health Research; Vol. 11, No. 10. Sarah Rodgers is part-funded by the NIHR Applied Research Collaboration North West Coast.
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Affiliation(s)
- Rebecca S Geary
- Department of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK
| | | | - Joanne K Garrett
- European Centre for Environment and Human Health, University of Exeter Medical School, University of Exeter, Truro, UK
| | - Amy Mizen
- Department of Health Data Science, Swansea University, Swansea, UK
| | - Francis M Rowney
- European Centre for Environment and Human Health, University of Exeter Medical School, University of Exeter, Truro, UK
| | - Jiao Song
- Department of Health Data Science, Swansea University, Swansea, UK
| | - Mathew P White
- European Centre for Environment and Human Health, University of Exeter Medical School, University of Exeter, Truro, UK
| | - Rebecca Lovell
- European Centre for Environment and Human Health, University of Exeter Medical School, University of Exeter, Truro, UK
| | - Alan Watkins
- Department of Health Data Science, Swansea University, Swansea, UK
| | - Ronan A Lyons
- Department of Health Data Science, Swansea University, Swansea, UK
| | | | | | - Ashley Akbari
- Department of Health Data Science, Swansea University, Swansea, UK
| | - Sarah C Parker
- Department of Health Data Science, Swansea University, Swansea, UK
| | | | - James White
- Centre for Trials Research, School of Medicine, Cardiff University, Cardiff, UK
| | - Benedict W Wheeler
- European Centre for Environment and Human Health, University of Exeter Medical School, University of Exeter, Truro, UK
| | - Richard Fry
- Department of Health Data Science, Swansea University, Swansea, UK
| | - Dialechti Tsimpida
- Department of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK
| | - Sarah E Rodgers
- Department of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK
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Hobbs M, McLeod GFH, Mackenbach JD, Marek L, Wiki J, Deng B, Eggleton P, Boden JM, Bhubaneswor D, Campbell M, Horwood LJ. Change in the food environment and measured adiposity in adulthood in the Christchurch Health and development birth cohort, Aotearoa, New Zealand: A birth cohort study. Health Place 2023; 83:103078. [PMID: 37517383 DOI: 10.1016/j.healthplace.2023.103078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 06/11/2023] [Accepted: 06/21/2023] [Indexed: 08/01/2023]
Abstract
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.
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Affiliation(s)
- Matthew Hobbs
- Faculty of Health, University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand; Te Taiwhenua o Te Hauora - GeoHealth Laboratory, University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand; The Cluster for Community and Urban Resilience (CURe), University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand.
| | - Geraldine F H McLeod
- Christchurch Health and Development Study, University of Otago - Te Whare Wānanga o Ōtākou, Christchurch, Canterbury, New Zealand
| | - Joreintje D Mackenbach
- Department of Epidemiology and Data Science, Amsterdam UMC Location Vrije University, Amsterdam, the Netherlands; Upstream Team, www.upstreamteam.nl, Amsterdam UMC, Amsterdam, the Netherlands
| | - Lukas Marek
- Faculty of Health, University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand; Te Taiwhenua o Te Hauora - GeoHealth Laboratory, University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand
| | - Jesse Wiki
- Te Taiwhenua o Te Hauora - GeoHealth Laboratory, University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand; School of Population Health, Faculty of Medical and Health Sciences, The University of Auckland - Waipapa Taumata Rau, Auckland, New Zealand
| | - Bingyu Deng
- Faculty of Health, University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand; Te Taiwhenua o Te Hauora - GeoHealth Laboratory, University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand
| | - Phoebe Eggleton
- Faculty of Health, University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand; Te Taiwhenua o Te Hauora - GeoHealth Laboratory, University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand
| | - Joseph M Boden
- Christchurch Health and Development Study, University of Otago - Te Whare Wānanga o Ōtākou, Christchurch, Canterbury, New Zealand
| | - Dhakal Bhubaneswor
- Christchurch Health and Development Study, University of Otago - Te Whare Wānanga o Ōtākou, Christchurch, Canterbury, New Zealand
| | - Malcolm Campbell
- Te Taiwhenua o Te Hauora - GeoHealth Laboratory, University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand; School of Earth and Environment, University of Canterbury - Te Whare Wānanga o Waitaha, Christchurch, Canterbury, New Zealand
| | - L John Horwood
- Christchurch Health and Development Study, University of Otago - Te Whare Wānanga o Ōtākou, Christchurch, Canterbury, New Zealand
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Tsai WL, Nash MS, Rosenbaum DJ, Prince SE, D'Aloisio AA, Neale AC, Sandler DP, Buckley TJ, Jackson LE. Types and spatial contexts of neighborhood greenery matter in associations with weight status in women across 28 U.S. communities. ENVIRONMENTAL RESEARCH 2021; 199:111327. [PMID: 34019899 PMCID: PMC8457404 DOI: 10.1016/j.envres.2021.111327] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Revised: 04/20/2021] [Accepted: 05/10/2021] [Indexed: 06/12/2023]
Abstract
Excess body weight is a risk factor for many chronic diseases. Studies have identified neighborhood greenery as supportive of healthy weight. However, few have considered plausible effect pathways for ecosystem services (e.g., heat mitigation, landscape aesthetics, and venues for physical activities) or potential variations by climate. This study examined associations between weight status and neighborhood greenery that capture ecosystem services most relevant to weight status across 28 U.S. communities. Weight status was defined by body mass index (BMI) reported for 6591 women from the U.S. Sister Study cohort. Measures of greenery within street and circular areas at 500 m and 2000 m buffer distances from homes were derived for each participant using 1 m land cover data. Street area was defined as a 25 m-wide zone on both sides of street centerlines multiplied by the buffer distances, and circular area was the area of the circle centered on a home within each of the buffer distances. Measures of street greenery characterized the pedestrian environment to capture physically and visually accessible greenery for shade and aesthetics. Circular greenery was generated for comparison. Greenery types of tree and herbaceous cover were quantified separately, and a combined measure of tree and herbaceous cover (i.e., aggregate greenery) was also included. Mixed models accounting for the clustering at the community level were applied to evaluate the associations between neighborhood greenery and the odds of being overweight or obese (BMI > 25) with adjustment for covariates selected using gradient boosted regression trees. Analyses were stratified by climate zone (arid, continental, and temperate). Tree cover was consistently associated with decreased odds of being overweight or obese. For example, the adjusted odds ratio [AOR] was 0.92, 95% Confidence Interval [CI]: 0.88-0.96, given a 10% increase in street tree cover at the 2000 m buffer across the 28 U.S. communities. These associations held across climate zones, with the lowest AOR in the arid climate (AOR: 0.74, 95% CI: 0.54-1.01). In contrast, associations with herbaceous cover varied by climate zone. For the arid climate, a 10% increase in street herbaceous cover at the 2000 m buffer was associated with lower odds of being overweight or obese (AOR: 0.75, 95% CI: 0.55-1.03), whereas the association was reversed for the temperate climate, the odds increased (AOR: 1.19, 95% CI: 1.05-1.35). Associations between greenery and overweight/obesity varied by type and spatial context of greenery, and climate. Our findings add to a growing body of evidence that greenery design in urban planning can support public health. These findings also justify further defining the mechanism that underlies the observed associations.
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Affiliation(s)
- Wei-Lun Tsai
- Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA.
| | - Maliha S Nash
- Office of Research and Development, U.S. Environmental Protection Agency, Newport, OR, USA
| | - Daniel J Rosenbaum
- Oak Ridge Institute for Science and Education Research Fellow, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Steven E Prince
- Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | | | - Anne C Neale
- Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Dale P Sandler
- National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA
| | - Timothy J Buckley
- Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Laura E Jackson
- Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
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Oliver J, Robertson O, Zhang J, Marsters BL, Sika-Paotonu D, Jack S, Bennett J, Williamson DA, Wilson N, Pierse N, Baker MG. Ethnically Disparate Disease Progression and Outcomes among Acute Rheumatic Fever Patients in New Zealand, 1989-2015. Emerg Infect Dis 2021; 27. [PMID: 34153221 PMCID: PMC8237904 DOI: 10.3201/eid2707.203045] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
We investigated outcomes for patients born after 1983 and hospitalized with initial acute rheumatic fever (ARF) in New Zealand during 1989-2012. We linked ARF progression outcome data (recurrent hospitalization for ARF, hospitalization for rheumatic heart disease [RHD], and death from circulatory causes) for 1989-2015. Retrospective analysis identified initial RHD patients <40 years of age who were hospitalized during 2010-2015 and previously hospitalized for ARF. Most (86.4%) of the 2,182 initial ARF patients did not experience disease progression by the end of 2015. Progression probability after 26.8 years of theoretical follow-up was 24.0%; probability of death, 1.0%. Progression was more rapid and ≈2 times more likely for indigenous Māori or Pacific Islander patients. Of 435 initial RHD patients, 82.2% had not been previously hospitalized for ARF. This young cohort demonstrated low mortality rates but considerable illness, especially among underserved populations. A national patient register could help monitor, prevent, and reduce ARF progression.
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Oldroyd RA, Hobbs M, Campbell M, Jenneson V, Marek L, Morris MA, Pontin F, Sturley C, Tomintz M, Wiki J, Birkin M, Kingham S, Wilson M. Progress Towards Using Linked Population-Based Data For Geohealth Research: Comparisons Of Aotearoa New Zealand And The United Kingdom. APPLIED SPATIAL ANALYSIS AND POLICY 2021; 14:1025-1040. [PMID: 33942015 PMCID: PMC8081771 DOI: 10.1007/s12061-021-09381-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Accepted: 04/20/2021] [Indexed: 06/12/2023]
Abstract
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.
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Affiliation(s)
- R. A. Oldroyd
- Leeds Institute for Data Analytics, University of Leeds, Leeds, UK
- School of Geography, University of Leeds, Leeds, UK
| | - M. Hobbs
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Christchurch, Canterbury, New Zealand
- Health Sciences, College of Education, Health and Human Development, University of Canterbury, Christchurch, Canterbury, New Zealand
| | - M. Campbell
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Christchurch, Canterbury, New Zealand
- School of Earth and Environment, College of Science, University of Canterbury, Christchurch, Canterbury, New Zealand
| | - V. Jenneson
- Leeds Institute for Data Analytics, University of Leeds, Leeds, UK
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Christchurch, Canterbury, New Zealand
| | - L. Marek
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Christchurch, Canterbury, New Zealand
| | - M. A. Morris
- Leeds Institute for Data Analytics, University of Leeds, Leeds, UK
- School of Medicine, University of Leeds, Leeds, UK
- Alan Turing Institute, London, UK
| | - F. Pontin
- Leeds Institute for Data Analytics, University of Leeds, Leeds, UK
| | - C. Sturley
- Leeds Institute for Data Analytics, University of Leeds, Leeds, UK
- School of Medicine, University of Leeds, Leeds, UK
| | - M. Tomintz
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Christchurch, Canterbury, New Zealand
| | - J. Wiki
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Christchurch, Canterbury, New Zealand
| | - M. Birkin
- Leeds Institute for Data Analytics, University of Leeds, Leeds, UK
- Alan Turing Institute, London, UK
| | - S. Kingham
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Christchurch, Canterbury, New Zealand
- School of Earth and Environment, College of Science, University of Canterbury, Christchurch, Canterbury, New Zealand
| | - M. Wilson
- Geospatial Research Institute, University of Canterbury, Christchurch, Canterbury, New Zealand
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Marek L, Hobbs M, Wiki J, Kingham S, Campbell M. The good, the bad, and the environment: developing an area-based measure of access to health-promoting and health-constraining environments in New Zealand. Int J Health Geogr 2021; 20:16. [PMID: 33823853 PMCID: PMC8025579 DOI: 10.1186/s12942-021-00269-x] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Accepted: 03/17/2021] [Indexed: 02/07/2023] Open
Abstract
Background Accounting for the co-occurrence of multiple environmental influences is a more accurate reflection of population exposure than considering isolated influences, aiding in understanding the complex interactions between environments, behaviour and health. This study examines how environmental ‘goods’ such as green spaces and environmental ‘bads’ such as alcohol outlets co-occur to develop a nationwide area-level healthy location index (HLI) for New Zealand. Methods Nationwide data were collected, processed, and geocoded on a comprehensive range of environmental exposures. Health-constraining ‘bads’ were represented by: (i) fast-food outlets, (ii) takeaway outlets, (iii) dairy outlets and convenience stores, (iv) alcohol outlets, (v) and gaming venues. Health-promoting ‘goods’ were represented by: (i) green spaces, (ii) blue spaces, (iii) physical activity facilities, (iv) fruit and vegetable outlets, and (v) supermarkets. The HLI was developed based on ranked access to environmental domains. The HLI was then used to investigate socio-spatial patterning by area-level deprivation and rural/urban classification. Results Results showed environmental ‘goods’ and ‘bads’ co-occurred together and were patterned by area-level deprivation. The novel HLI shows that the most deprived areas of New Zealand often have the most environmental ‘bads’ and less access to environmental ‘goods’. Conclusions The index, that is now publicly available, is able to capture both inter-regional and local variations in accessibility to health-promoting and health-constraining environments and their combination. Results in this study further reinforce the need to embrace the multidimensional nature of neighbourhood and place not only when designing health-promoting places, but also when studying the effect of existing built environments on population health. Supplementary Information The online version contains supplementary material available at 10.1186/s12942-021-00269-x.
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Affiliation(s)
- Lukas Marek
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Christchurch, New Zealand.
| | - Matthew Hobbs
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Christchurch, New Zealand.,School of Health Sciences, University of Canterbury, Christchurch, Canterbury, New Zealand
| | - Jesse Wiki
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Christchurch, New Zealand
| | - Simon Kingham
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Christchurch, New Zealand.,School of Earth and Environment, University of Canterbury, Christchurch, Canterbury, New Zealand
| | - Malcolm Campbell
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Christchurch, New Zealand.,School of Earth and Environment, University of Canterbury, Christchurch, Canterbury, New Zealand
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Investigating the Association Between Child Television Viewing and Measured Child Adiposity Outcomes in a Large Nationally Representative Sample of New Zealanders: A Cross-Sectional Study. J Phys Act Health 2021; 18:524-532. [PMID: 33811187 DOI: 10.1123/jpah.2020-0192] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Revised: 12/16/2020] [Accepted: 01/26/2021] [Indexed: 11/18/2022]
Abstract
BACKGROUND This study investigates the association between television (TV) viewing and child adiposity and if parental education and child ethnicity moderate this association. METHOD Cross-sectional, pooled (2013/2014-2016/2017) adult and child New Zealand Health Survey were matched resulting in 13,039 children (2-14 y) and parent dyads. Child TV viewing was estimated using self-reported time for each weekday and weekend. The height (in centimeters), weight (in kilograms), and waist circumference of parents and children were measured. Childhood body mass index and obesity were defined using the International Obesity Task Force cutoff values. Effect modification was assessed by interaction and then by stratifying regression analyses by parent education (low, moderate, and high) and child ethnicity (Asian, European/other, Māori, and Pacific). RESULTS Overall, watching ≥2 hours TV on average per day in the past week, relative to <2 hours TV viewing, was associated with a higher odds of obesity (adjusted odds ratio = 1.291 [1.108-1.538]), higher body mass index z score (b = 0.123 [0.061-0.187]), and higher waist circumference (b = 0.546 [0.001-1.092]). Interactions considering this association by child ethnicity and parent education revealed little evidence of effect modification. CONCLUSION While TV viewing was associated with child adiposity, the authors found little support for a moderating role of parental education and child ethnicity.
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Hobbs M, Kingham S, Wiki J, Marek L, Campbell M. Unhealthy environments are associated with adverse mental health and psychological distress: Cross-sectional evidence from nationally representative data in New Zealand. Prev Med 2021; 145:106416. [PMID: 33524416 DOI: 10.1016/j.ypmed.2020.106416] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Revised: 11/18/2020] [Accepted: 12/30/2020] [Indexed: 01/23/2023]
Abstract
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.
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Affiliation(s)
- M Hobbs
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Christchurch, Canterbury, New Zealand; Health Sciences, University of Canterbury, Christchurch, Canterbury, New Zealand.
| | - S Kingham
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Christchurch, Canterbury, New Zealand; School of Earth and Environment, College of Science, University of Canterbury, Christchurch, Canterbury, New Zealand
| | - J Wiki
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Christchurch, Canterbury, New Zealand
| | - L Marek
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Christchurch, Canterbury, New Zealand
| | - M Campbell
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Christchurch, Canterbury, New Zealand; School of Earth and Environment, College of Science, University of Canterbury, Christchurch, Canterbury, New Zealand
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Gray L, Rushton A, Hobbs M. " We only have the one": Mapping the prevalence of people with high body mass to aid regional emergency management planning in aotearoa New Zealand. INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION : IJDRR 2020; 51:101859. [PMID: 32953440 PMCID: PMC7486187 DOI: 10.1016/j.ijdrr.2020.101859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Revised: 09/03/2020] [Accepted: 09/06/2020] [Indexed: 06/11/2023]
Abstract
INTRODUCTION People have been left behind in disasters directly associated with their size, shape, and weight and are disproportionately impacted in pandemics. Despite alignment with known vulnerabilities such as poverty, age, and disability, the literature is inaudible on body mass. Emergency managers report little or no information on body mass prevalence. This exploratory study aimed to illustrate population prevalence of high body mass for emergency planning. METHODS Cross-sectional data from the New Zealand Health Survey were pooled for the years 2013/14-2017/18 (n = 68 053 adults aged ≥15 years). Height and weight were measured and used to calculate body mass index. The prevalence of high body mass were mapped to emergency management boundary shapefiles. The resulting maps were piloted with emergency managers. RESULTS Maps highlight the population prevalence of high body mass across emergency management regions, providing a visual tool. A pilot with 14 emergency managers assessed the utility of such mapping. On the basis of the visual information, the tool prompted 12 emergency managers to consider such groups in regional planning and to discuss needs. CONCLUSIONS Visual mapping is a useful tool to highlight population prevalence of groups likely to be at higher risk in disasters. This is believed to be the first study to map high body mass for the purposes of emergency planning. Future research is required to identify prevalence at a finer geographical scale. More features in the local context such as physical location features, risk and vulnerability features could also be included in future research.
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Affiliation(s)
- Lesley Gray
- Department of Primary Health Care & General Practice, University of Otago, Wellington, 6242, Aotearoa, New Zealand
| | - Ashleigh Rushton
- Joint Centre for Disaster Research, Massey University, Wellington, Aotearoa, New Zealand
| | - Matthew Hobbs
- Health Sciences, College of Education, Health and Human Development, University of Canterbury, Aotearoa, New Zealand
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Hobbs M, Schoeppe S, Duncan MJ, Vandelanotte C, Marek L, Wiki J, Tomintz M, Campbell M, Kingham S. Objectively measured waist circumference is most strongly associated in father-boy and mother-girl dyads in a large nationally representative sample of New Zealanders. Int J Obes (Lond) 2020; 45:438-448. [PMID: 33177613 DOI: 10.1038/s41366-020-00699-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/16/2020] [Revised: 09/09/2020] [Accepted: 10/14/2020] [Indexed: 11/09/2022]
Abstract
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.
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Affiliation(s)
- M Hobbs
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Canterbury, New Zealand. .,Health Sciences, University of Canterbury, Christchurch, Canterbury, New Zealand.
| | - S Schoeppe
- Central Queensland University, School of Health, Medical and Applied Sciences, Appleton Institute, Physical Activity Research Group, Rockhampton, QLD, Australia
| | - M J Duncan
- School of Medicine & Public Health, Priority Research Centre for Physical Activity and Nutrition, Faculty of Health and Medicine, University of Newcastle, Newcastle, NSW, Australia
| | - C Vandelanotte
- Central Queensland University, School of Health, Medical and Applied Sciences, Appleton Institute, Physical Activity Research Group, Rockhampton, QLD, Australia
| | - L Marek
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Canterbury, New Zealand
| | - J Wiki
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Canterbury, New Zealand
| | - M Tomintz
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Canterbury, New Zealand
| | - M Campbell
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Canterbury, New Zealand.,School of Earth and Environment, University of Canterbury, Christchurch, Canterbury, New Zealand
| | - S Kingham
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Canterbury, New Zealand.,School of Earth and Environment, University of Canterbury, Christchurch, Canterbury, New Zealand
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Investigating the prevalence of non-fluoride toothpaste use in adults and children using nationally representative data from New Zealand: a cross-sectional study. Br Dent J 2020; 228:269-276. [PMID: 32112020 DOI: 10.1038/s41415-020-1304-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Introduction Despite improvements in oral health outcomes in New Zealand over the last number of decades, there are still high levels of preventable tooth decay in adults and children. We investigate the prevalence and spatial variation of non-fluoride toothpaste use in a nationally representative sample of adults and children in New Zealand.Method Individual-level self-reported data were sourced from the New Zealand Health Survey (2017/18). Both child (n = 4,723) and adult (n = 13,869) data were used. Data included sociodemographic (for example, age), socioeconomic (for example, area-level deprivation) and dental-related (for example, type of toothpaste used) variables.Results Overall, 6.8% of adults and 6.4% of children use non-fluoride toothpaste. When split by deprivation, the highest prevalence of non-fluoride toothpaste use for children and adults was in the moderate to least deprived areas, while the lowest prevalence was in the most deprived areas. When disaggregated by ethnicity, the Asian population had the highest prevalence of non-fluoride toothpaste use for both adults and children compared to Māori, Pacific and European/Other. There was little difference in prevalence by rural/urban classification; however, prevalence varied geographically across the study area.Conclusion This is the first study that uses a nationally representative sample of adults and children to show variation in the use of non-fluoride toothpaste in New Zealand.
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