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Bruckner F, Gruber JR, Ruf A, Edwin Thanarajah S, Reif A, Matura S. Exploring the Link between Lifestyle, Inflammation, and Insulin Resistance through an Improved Healthy Living Index. Nutrients 2024; 16:388. [PMID: 38337673 PMCID: PMC10857191 DOI: 10.3390/nu16030388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Revised: 01/18/2024] [Accepted: 01/24/2024] [Indexed: 02/12/2024] Open
Abstract
Lifestyle factors-such as diet, physical activity (PA), smoking, and alcohol consumption-have a significant impact on mortality as well as healthcare costs. Moreover, they play a crucial role in the development of type 2 diabetes mellitus (DM2). There also seems to be a link between lifestyle behaviours and insulin resistance, which is often a precursor of DM2. This study uses an enhanced Healthy Living Index (HLI) integrating accelerometric data and an Ecological Momentary Assessment (EMA) to explore differences in lifestyle between insulin-sensitive (IS) and insulin-resistant (IR) individuals. Moreover, it explores the association between lifestyle behaviours and inflammation. Analysing data from 99 participants of the mPRIME study (57 women and 42 men; mean age 49.8 years), we calculated HLI scores-ranging from 0 to 4- based on adherence to specific low-risk lifestyle behaviours, including non-smoking, adhering to a healthy diet, maximally moderate alcohol consumption, and meeting World Health Organization (WHO) PA guidelines. Insulin sensitivity was assessed using a Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) and C-reactive protein (CRP) levels were used as a proxy for inflammation. Lifestyle behaviours, represented by HLI scores, were significantly different between IS and IR individuals (U = 1529.0; p = 0.023). The difference in the HLI score between IR and IS individuals was mainly driven by lower adherence to PA recommendations in the IR group. Moreover, reduced PA was linked to increased CRP levels in the IR group (r = -0.368, p = 0.014). Our findings suggest that enhancing PA, especially among individuals with impaired insulin resistance, holds significant promise as a preventive strategy.
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Affiliation(s)
- Franz Bruckner
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital, Goethe University Frankfurt, Heinrich-Hoffmann-Str. 10, 60528 Frankfurt am Main, Germany; (F.B.); (J.R.G.); (A.R.); (S.E.T.); (A.R.)
| | - Judith R. Gruber
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital, Goethe University Frankfurt, Heinrich-Hoffmann-Str. 10, 60528 Frankfurt am Main, Germany; (F.B.); (J.R.G.); (A.R.); (S.E.T.); (A.R.)
| | - Alea Ruf
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital, Goethe University Frankfurt, Heinrich-Hoffmann-Str. 10, 60528 Frankfurt am Main, Germany; (F.B.); (J.R.G.); (A.R.); (S.E.T.); (A.R.)
| | - Sharmili Edwin Thanarajah
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital, Goethe University Frankfurt, Heinrich-Hoffmann-Str. 10, 60528 Frankfurt am Main, Germany; (F.B.); (J.R.G.); (A.R.); (S.E.T.); (A.R.)
| | - Andreas Reif
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital, Goethe University Frankfurt, Heinrich-Hoffmann-Str. 10, 60528 Frankfurt am Main, Germany; (F.B.); (J.R.G.); (A.R.); (S.E.T.); (A.R.)
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany
| | - Silke Matura
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital, Goethe University Frankfurt, Heinrich-Hoffmann-Str. 10, 60528 Frankfurt am Main, Germany; (F.B.); (J.R.G.); (A.R.); (S.E.T.); (A.R.)
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M H, N B, L M, J W, J K, R T, T R, J B, H T, S H, B M. The environment a young person grows up in is associated with their mental health: A nationwide geospatial study using the integrated data infrastructure, New Zealand. Soc Sci Med 2023; 326:115893. [PMID: 37119566 DOI: 10.1016/j.socscimed.2023.115893] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Revised: 03/19/2023] [Accepted: 04/06/2023] [Indexed: 05/01/2023]
Abstract
BACKGROUND Mental health conditions often arise during adolescence, are multifaceted in aetiology, and may be related to the type of environment in which young people reside. This study used nationwide population-level data to investigate whether the environment a young person grows up in is associated with their mental health. METHOD Data were extracted from the Integrated Data Infrastructure (IDI), a large nationwide research repository, for 917,211 young people (aged 10-24 years) including sociodemographic and mental health data (i.e. emotional, behavioural, substance problems, and self-harm). Environmental data were sourced from the nationwide area-based Healthy Location Index (HLI), which has comprehensive data on the location of several health-constraining (i.e. fast-food outlets) and health-promoting features (i.e. physical activity facilities). Environments were classified as: i) health-promoting, ii) health-constraining, or iii) neither. Associations between the HLI and mental health were investigated using multi-level mixed effects logistic regression modelling. RESULTS Overall, there was evidence of an association between the environment a young person resided in and their mental health. Young people residing in health-constraining environments had higher odds of any mental health condition (Adjusted Odds Ratio (AOR) = 1.020 [1.001, 1.040]) and any emotional condition (AOR = 1.037 [1.012, 1.062]). Young people residing in health-promoting environments had lower odds of substance problems (AOR = 0.950 [0.905, 0.997]). There were no significant effects of the environment on behavioural conditions. CONCLUSION Our study utilises a large national sample of almost one million young people to confirm the importance of environmental determinants for mental health. It is possible that leverage points for improving the mental health of young people, and reducing the burden to the health system of mental health, can be sought in upstream environmental based interventions.
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Affiliation(s)
- Hobbs M
- Faculty of Health, University of Canterbury, Christchurch, Canterbury, New Zealand; GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Christchurch, Canterbury, New Zealand.
| | - Bowden N
- Department of Women's and Children's Health, University of Otago, Dunedin, New Zealand
| | - Marek L
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Christchurch, Canterbury, New Zealand
| | - Wiki J
- GeoHealth Laboratory, Geospatial Research Institute, University of Canterbury, Christchurch, Canterbury, New Zealand
| | - Kokaua J
- Va'a O Tautai - Centre for Pacific Health, Health Sciences, University of Otago, Dunedin, New Zealand
| | - Theodore R
- National Centre for Lifecourse Research, University of Otago, Dunedin, New Zealand
| | - Ruhe T
- Va'a O Tautai - Centre for Pacific Health, Health Sciences, University of Otago, Dunedin, New Zealand
| | - Boden J
- Christchurch Health and Development Study, Department of Psychological Medicine, University of Otago Christchurch, New Zealand
| | - Thabrew H
- The Werry Centre, Department of Psychological Medicine, University of Auckland, Auckland, New Zealand
| | - Hetrick S
- The Werry Centre, Department of Psychological Medicine, University of Auckland, Auckland, New Zealand
| | - Milne B
- Centre of Methods and Policy Application in the Social Sciences, University of Auckland, Auckland, New Zealand
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Duthie C, Pocock T, Curl A, Clark E, Norriss D, Bidwell S, McKerchar C, Crossin R. Online on-demand delivery services of food and alcohol: A scoping review of public health impacts. SSM Popul Health 2023; 21:101349. [PMID: 36845670 PMCID: PMC9950721 DOI: 10.1016/j.ssmph.2023.101349] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 01/19/2023] [Accepted: 01/22/2023] [Indexed: 01/25/2023] Open
Abstract
The increase in availability of online on-demand food and alcohol delivery services has changed the way unhealthy commodities are accessed and understood. We conducted a systematic scoping review of academic and grey literature to map the current knowledge of public health and regulatory/policy outcomes arising from on-demand food and alcohol delivery (defined as delivery within 2 h). We systematically searched three electronic databases and completed supplementary forward citation searches and Google Scholar searches. In total, we screened 761 records (de-duplicated) and synthesised findings from 40 studies by commodity types (on-demand food or alcohol) and outcome focus (outlet, consumer, environmental, labour). Outlet-focused outcomes were most common (n = 16 studies), followed by consumer (n = 11), environmental (n = 7), and labour-focused (n = 6) outcomes. Despite geographical and methodological diversity of studies, results indicate that on-demand delivery services market unhealthy and discretionary foods, with disadvantaged communities having reduced access to healthy commodities. Services that deliver alcohol on-demand can also subvert current alcohol access restrictions, particularly through poor age verification processes. Underpinning these public health impacts is the multi-layered nature of on-demand services and context of the COVID-19 pandemic, which creates ongoing complications as to how populations access food and alcohol. Changing access to unhealthy commodities is an emerging issue in public health. Our scoping review considers priority areas for future research to better inform policy decisions. Current regulation of food and alcohol may not appropriately cover emerging on-demand technologies, necessitating a review of policy.
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Affiliation(s)
- Cassian Duthie
- University of Otago Medical School, Christchurch, New Zealand
| | - Tessa Pocock
- School of Nursing, Faculty of Medical and Health Sciences, The University of Auckland, Auckland, New Zealand,Department of Population Health, University of Otago Christchurch, Christchurch, New Zealand
| | - Angela Curl
- Department of Population Health, University of Otago Christchurch, Christchurch, New Zealand
| | - Elinor Clark
- University of Otago Medical School, Christchurch, New Zealand
| | - Dru Norriss
- Department of Population Health, University of Otago Christchurch, Christchurch, New Zealand
| | - Susan Bidwell
- Department of Population Health, University of Otago Christchurch, Christchurch, New Zealand
| | - Christina McKerchar
- Department of Population Health, University of Otago Christchurch, Christchurch, New Zealand
| | - Rose Crossin
- Department of Population Health, University of Otago Christchurch, Christchurch, New Zealand,Corresponding author. Department of Population Health University of Otago (Christchurch), 34 Gloucester St, Christchurch, 8140, New Zealand.
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Milne BJ, D'Souza S, Andersen SH, Richmond-Rakerd LS. Use of Population-Level Administrative Data in Developmental Science. ANNUAL REVIEW OF DEVELOPMENTAL PSYCHOLOGY 2022; 4:447-468. [PMID: 37284522 PMCID: PMC10241456 DOI: 10.1146/annurev-devpsych-120920-023709] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Population-level administrative data-data on individuals' interactions with administrative systems (e.g., health, criminal justice, and education)-have substantially advanced our understanding of life-course development. In this review, we focus on five areas where research using these data has made significant contributions to developmental science: (a) understanding small or difficult-to-study populations, (b) evaluating intergenerational and family influences, (c) enabling estimation of causal effects through natural experiments and regional comparisons, (d) identifying individuals at risk for negative developmental outcomes, and (e) assessing neighborhood and environmental influences. Further advances will be made by linking prospective surveys to administrative data to expand the range of developmental questions that can be tested; supporting efforts to establish new linked administrative data resources, including in developing countries; and conducting cross-national comparisons to test findings' generalizability. New administrative data initiatives should involve consultation with population subgroups including vulnerable groups, efforts to obtain social license, and strong ethical oversight and governance arrangements.
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Affiliation(s)
- Barry J Milne
- School of Social Sciences and Centre of Methods and Policy Application in the Social Sciences (COMPASS), University of Auckland, Auckland, New Zealand
| | - Stephanie D'Souza
- School of Social Sciences and Centre of Methods and Policy Application in the Social Sciences (COMPASS), University of Auckland, Auckland, New Zealand
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Sadler RC, Wojciechowski TW, Buchalski Z, Smart M, Mulheron M, Todem D. Validating a geospatial healthfulness index with self-reported chronic disease and health outcomes. Soc Sci Med 2022; 311:115291. [PMID: 36088720 PMCID: PMC9968825 DOI: 10.1016/j.socscimed.2022.115291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 04/28/2022] [Accepted: 08/10/2022] [Indexed: 10/15/2022]
Abstract
Leveraging community engagement from past research may yield frameworks on which to build new inquiries. We previously integrated community voice into the development of a healthfulness index to increase awareness of social determinants of health in the built environment and inform deployment of public health interventions in the Flint (Michigan, USA) Center for Health Equity Solutions. Here we combine the healthfulness index with self-reported chronic disease and health outcomes (n = 12,279) from a community-based healthcare entity, the Genesee Health Plan. The healthfulness index purports to predict how health-promoting a neighborhood is based on many spatially varying characteristics; by linking our health plan data to this index, we validate the effectiveness of the healthfulness index. After geocoding all enrollees and joining their healthfulness scores, we conducted a series of logistic regressions to compare the relationship between self-reported outcomes and healthfulness. Matching the two intervention projects of our center (revolving around healthy eating & physical activity in project 1 and mental health sustainment & substance use prevention in project 2), our analyses also focused on classes of outcomes related to a) cardiovascular disease and b) mental health. In only select cases, higher (better) healthfulness scores from each project were independently associated with better cardiovascular and mental health outcomes, controlling for age, race, and sex. Generally, however, healthfulness did not add predictive strength to the association between health and sociodemographic covariates. Even so, the use of composite healthfulness indices to describe the health-promoting or degrading qualities of a neighborhood could be valuable in identifying differences in health outcomes. Future researchers could further explore healthcare claims datasets to increase understanding of the links between healthfulness and health outcomes. This and future work will be valuable in advocacy toward additional healthfulness indices to aid other communities in enriching understanding between the built environment and health.
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Affiliation(s)
| | | | | | - Mieka Smart
- Division of Public Health, Michigan State University, USA
| | - Megan Mulheron
- Division of Public Health, Michigan State University, USA
| | - David Todem
- Department of Epidemiology and Biostatistics, Michigan State University, USA
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Hobbs M, Stewart T, Marek L, Duncan S, Campbell M, Kingham S. Health-promoting and health-constraining environmental features and physical activity and sedentary behaviour in adolescence: a geospatial cross-sectional study. Health Place 2022; 77:102887. [DOI: 10.1016/j.healthplace.2022.102887] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 08/01/2022] [Accepted: 08/02/2022] [Indexed: 11/04/2022]
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Hobbs M, Milfont TL, Marek L, Yogeeswaran K, Sibley CG. The environment an adult resides within is associated with their health behaviours, and their mental and physical health outcomes: a nationwide geospatial study. Soc Sci Med 2022; 301:114801. [PMID: 35366459 DOI: 10.1016/j.socscimed.2022.114801] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Revised: 01/24/2022] [Accepted: 02/07/2022] [Indexed: 11/18/2022]
Abstract
BACKGROUND The determinants of health behaviours and health outcomes are multifaceted and the surrounding environment is increasingly considered as an important influence. This pre-registered study investigated the associations between the geospatial environment people live within and their health behaviours as well as their mental and physical health outcomes. METHOD We used the newly developed Healthy Location Index (HLI) to identify health-promoting and health-constraining environmental features where people live. We then used Time 10 (2018) data from the New Zealand Attitudes and Values Survey (NZAVS; N = 47,951), a national probability sample of New Zealand adults, to gauge mental health outcomes including depression, anxiety and psychological distress, physical health outcomes including BMI and type II diabetes, and health behaviours such as tobacco smoking and vaping. Linear and logistic multilevel mixed effect regression models with random intercepts of individuals nested within geographical areas (meshblocks) were employed. RESULTS The presence of health-constraining environmental features were adversely associated with self-reported mental health outcomes of depression, anxiety and psychological distress, physical health outcomes of BMI and type II diabetes, and negative health behaviours of tobacco smoking and vaping. By contrast, health-promoting environmental features were uniquely associated only with physical health outcomes of BMI and type II diabetes. CONCLUSION The current study advances research on environmental determinants of health behaviours by demonstrating that close proximity to health-constraining environmental features is related to a number of self-reported physical and mental health outcomes or behaviours. We provide some evidence to support the notion that preventive population-health interventions should be sought.
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Affiliation(s)
- M Hobbs
- Faculty of Health, University, Christchurch, Canterbury, New Zealand; GeoHealth Laboratory, Geospatial Research Institute, College of Science, University of Canterbury, Christchurch, Canterbury, New Zealand.
| | - T L Milfont
- School of Psychology, University of Waikato, Tauranga, New Zealand
| | - L Marek
- GeoHealth Laboratory, Geospatial Research Institute, College of Science, University of Canterbury, Christchurch, Canterbury, New Zealand
| | - K Yogeeswaran
- School of Psychology, Speech and Hearing, College of Science, University of Canterbury, Christchurch, New Zealand
| | - C G Sibley
- School of Psychology, University of Auckland, Auckland, New Zealand
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Yang H, Cui X, Dijst M, Tian S, Chen J, Huang J. Association Between Natural/Built Campus Environment and Depression Among Chinese Undergraduates: Multiscale Evidence for the Moderating Role of Socioeconomic Factors After Controlling for Residential Self-Selection. Front Public Health 2022; 10:844541. [PMID: 35480591 PMCID: PMC9037627 DOI: 10.3389/fpubh.2022.844541] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Accepted: 02/02/2022] [Indexed: 11/13/2022] Open
Abstract
Aim Evidence on the association between natural-built environments and depression is largely derived from the general population and prone to residential self-selection bias because of the nature of cross-sectional research design. Despite emerging adulthood, which includes the university years, is a critical stage for forming life-long health habits, studies on this topic focusing on undergraduate students are limited. The current study aims to illustrate the underlying mechanisms for how the campus-based environments affect depression in undergraduate students. Methods Based on a nationwide representative analytical sample of 22,009 Chinese undergraduates in 2018, we examined participants' reports of depression and campus-centered natural/built environments within multiple buffer sizes including 0.5, 1.0, and 2.5 km. After disentangling residential self-selection, we explored the moderating role of the socioeconomic attributes of undergraduates. The depression outcome was measured by the nine-item Patient Health Questionnaire (PHQ9). Indicators of exposure to green and blue space, transportation infrastructure, and food environments were objectively assessed using different circular buffers around each campus address. Results Modeling results indicated that campus neighborhoods with more scattered trees (0.5 km), water (0.5, 1.0, and 2.5 km), and street intersections (1.0 and 2.5 km) were protective against depression. In contrast, those living near denser distributions of outlets serving take-away sweets and fast food (0.5, 1.0, and 2.5 km) were susceptible to depression. These associations were modified by undergraduates' socioeconomic attributes (e.g., grade, Hukou status, and ethnicity) and varied according to geographical scales and exposure metrics. Conclusion To deliver effective environmental interventions to curb the prevalence of depression among undergraduate students, further planning policies should focus on the careful conception of the campus-based environment, especially regarding different spatial scales.
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Affiliation(s)
- Haoran Yang
- The Centre for Modern Chinese City Studies, Research Center for China Administrative Division, Future City Lab, East China Normal University, Shanghai, China
| | - Xiangfen Cui
- Faculty of Environmental Science and Engineering, Kunming University of Science and Technology, Kunming, China
| | - Martin Dijst
- Department of Urban Development and Mobility, Luxembourg Institute of Socio-Economic Research (LISER), Esch-sur-Alzette, Luxembourg
| | - Senlin Tian
- Faculty of Environmental Science and Engineering, Kunming University of Science and Technology, Kunming, China
| | - Jie Chen
- Faculty of Land Resource Engineering, Kunming University of Science and Technology, Kunming, China
| | - Jianhong Huang
- Faculty of Environmental Science and Engineering, Kunming University of Science and Technology, Kunming, China
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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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