Does exposure to green or blue space impact dietary intake and food choices among adults? A Systematic Literature Review.

doi:10.21203/rs.3.rs-2230809/v1

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Does exposure to green or blue space impact dietary intake and food choices among adults? A Systematic Literature Review.

https://doi.org/10.21203/rs.3.rs-2230809/v1

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The health benefits of exposure to greenspace are well researched; however, causal pathways for improved health outcomes are complex, and evidence is minimal on potential moderating factors. This review aimed to assess the strength of the evidence and potential impact of exposure to green and blue spaces on dietary outcomes in adults. The inclusion criteria for the review were based on the PICO criteria. Five databases were searched: CINAHL, GreenFILE, AMED, Medline, and PubMed, accessed on 14th June 2021. The Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Analytical Cross-Sectional Studies was used for quality assessment in all studies. Due to heterogeneity, narrative synthesis was conducted to evaluate the relationships between the included studies. Four observational studies which reported diet-related outcomes were included in the review, and participants within the studies ranged from 554 to > 350,000 participants. Other health outcomes, including physical activity and obesity, have also been reported. Socioeconomic status (SES) was identified as a significant determinant of dietary intake and food choice. Two studies found that dietary patterns were not correlated with exposure to greenspace. Due to the small number of articles retrieved and the paucity of evidence, the findings need to be interpreted with caution. Further research is required to elucidate the complex mechanisms involved. Research is also needed to determine which greenspace attributes impact dietary intake and food choices among adults. When developing public health interventions, the significant health benefits associated with different socioeconomic groups should be considered.

Greenspace

blue space

diet

nutrition

food choices

There is increasing literature available on the health benefits of greenspace exposure, including perceived improvement in mental health (Stigsdotter et al. 2010; van den Berg et al. 2016; Wood et al. 2017; Twohig-Bennett and Jones 2018; White et al. 2019), improved weight status and obesity-related health outcomes (Lachowycz and Jones 2011; Ghimire et al. 2017; Luo et al. 2020) and all-cause mortality (Burkart et al. 2016). Additionally, there is also some evidence linking green space to perceived general health (Markevych et al. 2017; Kondo et al. 2018; Rigolon et al. 2021). During the COVID-19 pandemic, the time spent outdoors accessing green and blue natural spaces highlighted the beneficial effects of nature on mental health. Individuals surveyed during the lockdown reported better coping mechanisms when accessing nature and greenspace (Pouso et al. 2020). Similarly, growing evidence suggests that higher levels of exposure to blue space are also associated with better mental health outcomes for individuals in urban areas (Nutsford et al. 2016), and there is a range of positive health benefits for people who can avail of safe, clean blue spaces (White et al. 2020).

One of the causal pathways explored in the existing body of evidence for the association between greenspace and better physical and psychological health outcomes is related to increased opportunities for outdoor activities, relaxation, and exercise, thus promoting beneficial health effects (van den Berg et al. 2015). A novel theoretical framework has also been developed for these interactions using socio-ecological theories to identify causal pathways and outcomes (Lachowycz and Jones 2013). However, evidence on the mechanisms of these interactions remains elusive and the results are inconsistent (Astell-Burt et al. 2014; Fong et al. 2018; MacMillan et al. 2018; Song et al. 2019; Jimenez et al. 2021). The relationship between exposure to greenspace and improved health outcomes is confounded and mediated by many factors, including socioeconomic factors and greenspace, characteristics including, the quality, quantity, and use of greenspace (Freeman 2010; Wham et al. 2012; Picavet et al. 2016; Triguero-Mas, Donaire-Gonzalez, Seto, Valentín, Martínez, et al. 2017; Nieuwenhuijsen et al. 2019; Orioli et al. 2019a; Zandieh et al. 2019; Zijlema et al. 2020). Zandieh et al. (2019) reported that the quantity of available greenspace was significantly associated with increased walking levels in high-poverty neighbourhoods. Knobel et al. (2021) investigated the quality of urban greenspace and found that higher-quality greenspace was associated with more frequent use of physical activity. However, a study by Picavet et al. (2016) found that the percentage of greenspace in the living environment was not associated with improved health benefits but did report that the distinction between greenspace types may be relevant for increased levels of physical activity. Increased levels of urban greenspace were associated with more time spent on sports, whereas increased levels of agricultural green were associated with more time spent gardening.

To date, research on the potential health benefits of exposure to greenspace and obesity has focused on physical activity and the causal mechanisms and interactions for these health improvements. The definition of greenspace used in studies influences the association between outdoor physical activity and obesity (Klompmaker et al. 2018). Dietary habits and food consumption patterns are evolving, and environmental and societal changes have resulted in an increase in the consumption of energy-dense foods. Reduced levels of physical activity and increased sedentary lifestyles have resulted in a threefold increase in obesity worldwide (World Health Organisation, 2021). Dietary factors are associated with five of the 10 leading causes of death, including ischaemic heart disease, cancer, stroke, and type II diabetes mellitus ) (Swinburn et al. 2011, Mueller et al. 2019).

The diets of socially disadvantaged groups frequently lack nutritious items, such as fruits and vegetables (Martin et al. 2017) and with increasing urbanisation, food insecurity has also increased in cities worldwide. By 2050, the United Nations predicts that over 68% of the world's population will live in urban areas. (United Nations, Department of Economic and Social Affairs 2018). Sustainable urbanisation, including access to greenspace and improved dietary patterns are crucial in meeting the UN 2030 Agenda for Sustainable Development Goals to ensure that social, cultural, economic and environmental determinants of health and well-being are addressed (de Vries et al. 2020).

As outlined, most research to date on exposure to green and blue spaces has focused on specific health outcomes. However, the evidence is inconclusive, and the findings concerning this association are inconsistent. Given the global burden of non-communicable diseases and urbanisation of countries, research into other mechanisms which may influence better health outcomes concerning greenspace is required. This includes a systematic review of the potential moderating factors that incorporate demographic and living context factors, which are currently lacking. Physical activity and diet are modifiable risk factors for the development and progression of various illnesses (MacMillan et al. 2018).

This review aimed to explore the relationship and strength of the evidence between exposure to green or blue spaces on dietary intake and food choices among adults. It is envisaged that the findings of this review will provide evidence that can inform researchers and policymakers to develop and implement appropriate context-specific public health interventions for improved health benefits.

2.1 Search Strategy

Standards as documented in the PRISMA 2020 statement: An updated guideline for reporting systematic reviews was followed throughout this review (Page et al. 2021). The PRISMA checklist is presented in Table S1. Details of the protocol for this systematic review were registered on PROSPERO (PROSPERO 2021 CRD42021297100) and can be accessed at the following address

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021297100 .

Databases were selected and agreed with the author group, which best represented health, health-related topics, human impact on the environment, alternative medicine topics, biomedical, and life sciences. Five electronic databases were reviewed from 1st January 2010 to 14th June 2021 to retrieve relevant articles for inclusion in the review (Cumulative Index to Nursing and Allied Health Literature (CINAHL) Complete, GreenFILE, Allied and Complementary Medicine Database (AMED), Medline, and PubMed). The electronic databases were accessed on 14th June 2021.

To construct an appropriate search strategy, previously published systematic reviews on greenspace and blue space were searched (Markevych et al. 2017; Britton et al. 2018; Rigolon et al. 2021). The definition of greenspace was constructed for this review to utilise both quantitative and qualitative aspects of exposure to greenspace (Taylor and Hochuli 2017). Greenspace is defined as a concept of nature, and this review included all areas of greenspace, vegetation, open space, and parklands. Blue space was defined as either man-made (canals), naturally occurring freshwater bodies (e.g. rivers and lakes), or saltwater bodies (oceans and seas) (Britton et al. 2018).

The search terms and definitions of green and blue spaces that formed the basis of the search strategy were identified to capture relevant articles (i.e. exposure to greenspace or blue space and dietary outcomes).

A search string was developed for each green and blue space concept and applied to all the electronic databases (S2). Truncation and phrase searching were used as part of the search strings to capture the nutritional and dietary outcomes (Nutri* and Diet *). The search strategy identified studies that contained at least one keyword or synonym in each string. Each concept was then combined to obtain the final search results for each database. Limiters and additional filters were applied to ensure the implementation of the review eligibility criteria outlined in Section 2.3. Specific information concerning each database are presented in the search strategy document (S3).

2.2 Selection Process

All articles retrieved using the search strategy were imported into Rayyan (www.rayyan.ai). Duplicate articles were identified and deleted. One reviewer (CG) independently screened titles and abstracts. A second reviewer (AS) screened 20% of titles and abstracts independently to ensure that the inclusion and exclusion criteria were functioning and being applied correctly. When there were disagreements, full-text articles were retrieved.

Full-text screening was then conducted independently by one reviewer (CG) of the remaining articles using the inclusion and PICO criteria.

Population

Male and Female adults > 18 years

Intervention

Exposure to greenspace or blue space

Comparison

There was no comparator restrictor

Outcome

Study reports a diet related outcome

Articles were screened against this criterion by a second reviewer (AS), and any disagreements in the selection of articles were resolved through discussion. Studies were not included if the outcome of interest was not reported, and the reasons for excluding articles were documented in the PICO Research Checklist (Table S4).

2.3 Eligibility Criteria

The inclusion and exclusion criteria were specified for the review and agreed with the authors’ group (Table 1). Empirical studies in which dietary outcomes were attributable to exposure to greenspace or blue space were also included. Dietary outcomes were identified as dietary intake or food choices among adults, which was essential for inclusion. The study population included adults (> 18 years). Only studies that included human participants were included, and children or adolescents (< 18 years) were excluded. This review included quantitative studies with both experimental and observational designs. Studies that were not peer-reviewed were excluded.

The primary aim of this review is to examine the relationship between exposure to greenspace or blue space and dietary outcomes, including studies that incorporated outcomes concerning food practices and food habits. Studies that mediated or controlled diet or dietary patterns in statistical analysis and reported multiple results should be included to help further explain the complex interactions and causal relationship between exposure to the intervention and the outcome.

A language restriction was also applied to the studies, and only studies written in English were included because of a lack of translational capacity. As most of the research on green and blue space interventions has been published in the last ten years, the review was restricted to studies published from 2010 onwards.

Table 1

Inclusion and Exclusion criteria
Inclusion Criteria	Exclusion Criteria
Experimental or observational research testing the relationships between greenspace and blue space and dietary outcomes	Studies that do not include experimental or observational evidence
Study reports a dietary outcome	Studies not reporting a dietary outcome
Only studies written in the English language are included	Studies written in any other language
Population in the study are adults (> 18 years)	Population in the study are not adults (< 18 years)
Studies must be based on human participants	Studies that do not use human participants
Studies published since 2010	Studies published before 2010

2.4 Data Collection Process And Data Items

Data extraction was performed for all eligible full-text articles. Owing to the limited number of articles in the review, articles were grouped for synthesis based on the outcome of interest. The following information was extracted: author, title, year of publication, country, study design, participants, intervention, measurement tool used, outcome under investigation (food choices/dietary intake), and other outcomes/notes. Any disagreements in data collection were discussed, and if necessary, reviewed by a third investigator (EMOC or AT).

Where multiple results were available, the outcome considered most important for this review (dietary outcome) was recorded, and other outcomes were documented separately during the data extraction process.

2.5 Critical Appraisal

Two authors conducted rigorous critical appraisal of the included studies. The Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Analytical Cross-Sectional Studies is recommended as the preferred tool for assessing the quality of analytical cross-sectional studies (Ma et al. 2020). The (JBI) Critical Appraisal Checklist is a domain-based tool that includes eight criteria: three referring to the study population, one criterion related to validity and reliability concerning the measurement of exposure, one criterion related to validity and reliability concerning the measurement of outcomes, and three criteria related to statistical analysis and adjustment for confounding factors (Moola et al. 2020). A criterion was rated Yes if enough information was available to determine the criterion was met, No if it was not met, Unclear if a decision could not be applied with the information provided, and Not applicable if the criterion did not apply. The sum of all the positive scores was added to determine the overall quality score. A score of 100% indicated that the study was of high quality (HQ), and a score of–70–100% were rated medium quality (MQ). If a study scored < 70% on the critical appraisal, it was deemed low quality (LQ). A critical appraisal of all the included articles was conducted independently by one reviewer (CG) and checked by a second reviewer (AS). Disagreements were resolved through discussion and referral to the full text of the article if required. Critical appraisal checklists for all included articles are available in Supplementary Material S5.

2.6 Narrative Synthesis

Owing to the heterogeneity of greenspace measures and dietary outcomes, a meta-analysis approach was not pertinent. A narrative synthesis using synthesis without meta-analysis (SWiM) reporting guidelines was conducted for this review (Campbell et al. 2019). The synthesis covered how studies were grouped, synthesis methods used, presentation of data, and limitations of the synthesis. Owing to the limited number of studies included in the review, full-text articles were grouped for narrative synthesis based on the outcome of interest (Table 2) and standardised metrics for each outcome are reported in Table 3. To translate the data, thematic analysis was used to identify the main, recurrent, and most important themes and concepts across studies. Establishing a common rubric for the included studies was not considered useful as there was no unit of measurement that could form the basis of a common rubric due to the heterogeneity of measurements of intervention and outcomes. Due to the limited number of articles included in the review, specific criteria were not used to prioritise the reporting of some study findings over others, and the synthesis was not restricted to a subset of studies. An assessment of the certainty of evidence was not performed because of the limited number of studies included in the review. Study findings are presented in the same way as synthesis to facilitate the comparison of findings from each included study. Each outcome is described in the synthesis along with the limitations associated with each study.

3.1 Study Selection

A total of 10,897 records were identified through an electronic database search. After removing duplicates, 10,181 records were screened, of which 666 were retrieved for abstract screening. A total of 137 articles were read as full text for eligibility. Four studies were deemed eligible for inclusion after an independent assessment by a second reviewer (AS). The flowchart is shown in Fig. 1.

Several studies were retrieved from the original search concerning blue space. However, most of these studies did not specify a link to the outcome or the intervention, and were mostly related to the eutrophication of urban and rural waterways and their nutrient content. Several other studies on blue space have reported exposure to persistent pollutants, consumption of fish, and the assessment of drinking water quality (Zhou et al. 2016, 2017; Bawa et al. 2018; Baho et al. 2019).

Reasons for exclusion of all studies are documented in the detailed PICO Research Checklist Table (S4).

3.2 Study Characteristics

Although a date restriction was put on the search, 75% of the articles reviewed at the full-text stage were published within the last six years. Two of the four included studies were conducted in the United States (Michimi and Wimberly 2012; von Hippel and Benson 2014), one in South Korea (Choi and Yoon 2020) and one in Hong Kong (Yuen et al. 2019). All studies were observational, three were cross-sectional, and the fourth was a case-control study. The sample sizes under investigation varied across the four studies, and two studies used routinely collected data from the Behavioural Risk Factor Surveillance System (BRFSS) in the United States, accessing sample sizes of > 350,000 surveyed participants. One study used primary data collection from 554 residents, and the fourth study accessed the National Health and Nutrition Examination Survey in Korea (KNHNES) and included 577 samples.

Four different types of exposure to greenspaces were measured in studies using a number of different measurement tools to assess exposure. In one study, the percentage of greenspace within a 500m buffer around each participant's home was calculated using SPOT satellite imagery (Yuen et al. 2019). A second study (von Hippel and Benson 2014) calculated the percentage of the county area under investigation covered by forest and water. Information and data on forest cover were obtained from the US Forest Service and data on water cover were obtained from the Economic Research Service of the US Department of Agriculture. A third study (Choi and Yoon 2020) used data on built neighbourhood environments represented by walkability and leisure amenities collected from various sources, including the National Geographic Information Institute, Statistical Geographic Information Services (SGIS), Korea Forest Service, and Seoul Metropolitan Government. The final study in the review (Michimi and Wimberly 2012) measured exposure to greenspace at the cunty level using two indices of outdoor activity potential (OAP). These two indices include a recreational opportunity index and a natural amenities index. The recreational opportunity index was calculated using data from outdoor recreational facilities. Data from the USDA Forest Service Southern Research Station were obtained from the 1997 National Outdoor Recreation Supply Information System (NORSIS). The natural amenities index was created using data on physiography, cover, climate, and tourism employment.

Dietary and other health outcomes, including physical activity and obesity, were reported in each study. The characteristics of the studies are listed in Table 2. The dietary intake methodology for the study outcomes is described below.

Table 2

Study Characteristics of included studies
Study ID		Population			Intervention			Outcomes			Determinant
Author/Year	Study Design	Country	Sample Size	Gender & Age	Green space/Blue Space	Measurement of greenspace intervention	Measurement of dietary outcome	Dietary intake/Food Choice	BMI	Physical Activity	SES
John W. M. Yuen et al. (2019)	Cross sectional study	Hong Kong	554	Male:198 Female: 356 Age 48.05 years +- 20.98 years	Green space	% of greenspace within a 500m radius buffer around each participants residence calculated using SPOT satellite image derived-dataset	Four part likert scale self reported by participants	Low sugar Low salt Low fat High fruit	-	IPAQ-C MET –mins/week calculated	Monthly income Education
Paul Von Hippel & Rebecca Benson MPH (2014)	Cross sectional study	United States	350,000	> 20 years	Green space/Blue space	% water area, % forest area	BRFSS, Behavioural Risk Factor Surveillance System (BMI > 30) Self reported; To measure dietary patterns data from US Departement of Agriculture’s Food Environment Atlas retrieved	Soda Sweet/snacks Prepared foods Solid fats Meat	% obese	% physical activity	-
Yunwon Choi & Heeyeun Yoon (2020)	Case control study	South Korea	577	Samples were between 19–64 years old; 38.1% are male; 61.9% are female	Green space	Built environment data was collected from a number of sources including National Geographic Information Institute, Statistical Geographic Information Service, Korea Forest Service, Seoul Metropolitan Government.	KNHNES (Korea National Health & Nutrition Examination Survey) for BMI data on participants; Construct on Dietary patterns developed for analysis	Eat out Carbohydrate ProteinFat Sodium	Dependent variable	Frequency of weekly and daily physical activity	Education Monthly income
Akihiko Michimi & Michael C. Wimberly (2012)	Cross sectional study	United States	457,820 participants for obesity and 473,296 for physical activity	Adults aged over 18 years (48% males; 52% females)	Green space	Recreational and Natural amenities indices based on measurements of physiography and cover	BRFSS, Behavioural Risk Factor Surveillance System (BMI > 30) Self reported; Tourism variable to capture food services industry; data from US Census County Business Patterns Dataset 2000	Tourism variable classifed by NAICS	Odds Ratios for obesity OR 0.91 (95% CI 0.90, 0.93)	Odds Ratios for Physical Activity OR 1.08 (95% CI 1.07, 1.10)	Education Income

3.3 Study outcomes

Meta-analysis of the outcomes reviewed in this study was not possible due to the heterogeneity of the interventions and the results. The measurement of dietary outcomes varied across the four included studies, with three studies controlling for diet in their analysis. One study measured healthy eating practice on a four-part Likert scale, self-reported by the participants (Yuen et al. 2019). Three studies reviewed the adult obesity prevalence in different settings using statistical analysis, mediating, or controlling for diet within the analysis. One study retrieved five diet-related variables from the US Department of Agriculture’s Food Environment Atlas (von Hippel and Benson 2014). Another study developed a construct on dietary patterns using several different indicators (Choi and Yoon 2020) with data retrieved from a national health and nutrition survey. The final study captured information on the food services industry using data from the US Census County Business Patterns Dataset 2000 (Michimi and Wimberly 2012). Two of the studies also assessed measurements of body mass index (BMI) from the National Behavioural Risk Factor Surveillance System (BRFSS) (Michimi and Wimberly 2012; von Hippel and Benson 2014).

All studies in this review investigated more than one outcome, identifying the interrelationship between dietary choices, greenspace, and other health outcomes. The reported dietary outcomes included dietary intake and food choices. Physical activity and obesity have been reported to be separate health outcomes.

However, the results varied between studies (Table 3). Healthy eating habits were not directly linked to exposure to greenspace in one study (Yuen et al. 2019) and the results were not statistically significant for a number of dietary intakes, including low sugar (p < 0.051), low salt (p < 0.071), low fat (p < 0.084), and high fruit intake (p < 0.069). However, this study identified that dietary intake and food choices were correlated with other demographic and quality of life (QoL) variables and also identified a positive association between greenspace and physical activity (p < 0.031).

Two further studies (Michimi and Wimberly 2012; von Hippel and Benson 2014) reviewed obesity and the role of the natural environment on obesity outcomes, controlling for dietary patterns in the analysis, where both identified an association between these outcomes. Von Hippel and Benson (2014) hypothesised that the effect of the natural environment on obesity is mediated by diet. To test this, they used five variables from the US Department of Agriculture’s Food Environment Atlas measuring each county’s per capita purchases of soda, packaged sweet snacks, prepared foods, solid fats, meats, and fruits and vegetables for home consumption. They identified that exposure to green and blue spaces, as measured by percentage water area and forest cover, had no significant association with obesity (p < 0.1), with or without food as a mediator in the analysis. However, this study also identified a strong negative relationship between obesity and physical activity (Correlation coefficient R=-0.83).

Michimi and Wimberly (2012) identified a positive correlation between obesity and the natural environment, reporting a 9% reduction in the odds ratio for obesity with a 1-unit increase in the natural amenities index for outdoor activity potential (OR, 0.91; 95% CI, 0.90, 0.93). This result included a tourism variable to capture the importance of the food services sector.

The final study in the review (Choi and Yoon 2020) when controlling for dietary patterns, also reported the association between obesity and the built environment, quantified through walkability in neighbourhoods and access to leisure amenities. The dietary pattern construct measured individuals’ dietary habits and was constructed using the following indicators: the number of times individuals eat out per week (eat out) and the total daily intake of carbohydrate (carbohydrate), protein (protein), fat (fat), and sodium (sodium). This study reported a negative association between BMI and walkability (coefficient = -3.385) which indicated that higher walkability in a neighbourhood explained lower BMI levels among residents, as expected (Choi and Yoon 2020).

However, two studies in the review identified other findings concerning the association between obesity and the natural environment. One study (Choi and Yoon 2020) found that greater access to leisure amenities in a neighbourhood did not negatively affect BMI and was associated with an increase in BMI (coeff = 1.069). This study highlighted that although people have access to leisure amenities, including open spaces in their neighbourhood, this does not mean that people will use them. Another finding in one of the studies (von Hippel and Benson 2014) between obesity and the natural environment was concerning prevailing weather conditions, where extreme heat, cold, and dark rainy conditions increased obesity. The coefficients of several variables were statistically significant for obesity (P < 0.05). The association between obesity and exposure to the natural environment, including trees, waterfronts, hills, and mountains, was not statistically significant (p > 0.05).

Socioeconomic status (SES) was also reported in two studies, with results indicating in one study (Yuen et al. 2019) that dietary intake and food choices were correlated with different demographic and WHOQoL variables including education level (p < 0.001) and age (p < 0.001). According to this study, lower socioeconomic groups benefitted more from green areas in their urban environments (Yuen et al. 2019). A second study (Choi and Yoon 2020) reported a negative effect of SES on BMI (coeff = -9.091), and the magnitude of the effect is much greater on BMI than on other environmental conditions, including walkability (coeff = -3.385) and leisure amenities (1.069). In this study, SES showed a statistically insignificant relationship with dietary pattern.

Table 3

Study Results
Study ID	Results
Study ID	Dietary Outcomes	Body Mass Index (BMI)	Physical Activity	Socio-economic Status (SES)
John W. M. Yuen et al. (2019)	Low sugar 0.051 Low salt 0.071 Low fat 0.084 High fruit 0.069 Note: Correlational analysis among variables measured in the studied population, p-value; Table 3 Education p < 0.001; Age p < 0.001	-	MET – minutes/week increased with increased green space (p < 0.031) Note: Physical activities and dietary habits of participants living with different greenspace levels; Table 2	Education 0.227 Monthly income 0.002 Note: Correlational analysis among variables measured in the studied population, p-value; Table 3
Paul Von Hippel & Rebecca Benson MPH (2014)	Soda − 0.065 (-0.262, -1.851) Sweet/snacks − 0.165 (-0.389, 0.060) Prepared foods 0.320^(0.092, 05.48) Solid fats 0.149 (-0.030, 0.328) Meat 0.206^(0.065, 0.348) Note: Mutiple Regression predicting county obesity with physical activity and food, b (95% CI); Table 2	% obese 18–52%; SD 4% Strong negative correlation between obesity and physical activity (r=-0.83) Exposure to blue space/greenspace no significant association with obesity (p < 0.1) Weather variables with significant association with obesity extreme heat, cold and dark rainy conditions p < 0.05	% physical activity 32–74%; SD 6%	-
Yunwon Choi & Heeyeun Yoon (2020)	Eat out 1.000 Carbohydrate 1.200^* Fat 1.319^* Sodium − 0.329^*** Note: SEM Analysis of how neighbourhood environments effects BMI; Fig. 4^*p < 0.01 ^p < 0.05 ^*p < 0.1	Dependent variable Walkability − 3.385^ SES − 9.091 Urban Leisure 1.069 Dietary Pattern 0.700^ Note: SEM Analysis of how neighbourhood environments effects BMI; Fig. 4	Weekly vigorous work 1.000 Weekly moderate work 0.259^* Daily vigorous work 1.050^* Daily moderate work 0470^* Weekly vigorous recreation 0.002 Weekly moderate recreation − 0.001 Daily vigorous recreation − 0.069 Daily moderate recreation 0.080 Weekly active commuting 0.083 Daily active commuting 0.101^ Weekly walking 0.037 Note: SEM Analysis of how neighbourhood environments effects BMI; Fig. 4	Education 1.000 Monthly income 1.498^* SES to Walkability − 0.947* SES to Urban Leisure 1.162*** Note: SEM Analysis of how neighbourhood environments effects BMI; Fig. 4
Akihiko Michimi & Michael C. Wimberly (2012)	Tourism variable classifed by NAICS	Odds Ratios for obesity OR 0.91 (95% CI 0.90, 0.93) 9% reduction in the odds ratio for obesity with a 1-unit increase in the natural amenities index for outdoor activity potential	Odds Ratios for Physical Activity OR 1.08 (95% CI 1.07, 1.10) Physical activity increased with increasing education and income in both rereational opportunity index and natural amenities index Note: Table 3 Odds Ration for Physical Activity with OAP indices	Obesity decreased with increasing education and income in both rereational opportunity index and natural amenities index Note: Table 2 Odds Ration for Obesity with OAP indices

3.4 Critical Appraisal

All four articles in the review were critically assessed for quality using the Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Analytical Cross-Sectional Studies (S5). Two studies were deemed to be of high quality (HQ) (von Hippel and Benson 2014; Choi and Yoon 2020) and two studies were deemed to be of low quality (LQ) (Michimi and Wimberly 2012; Yuen et al. 2019)(Michimi and Wimberly 2012). However, none of the studies were excluded because of low-quality scores. Two studies deemed to be of low quality scored 63%, scoring five out of eight criteria. Two high-quality studies scored eight out of eight. The two checklist criteria missing from both studies concerned confounding factors and strategies for dealing with confounding factors. Individual quality analysis scores are shown in Supplementary Material S5.

4.1 Summary of findings

This study aimed to assess the potential impact of exposure to greenspace and blue space on the dietary intake and food choices of adults. Several studies have investigated the association between greenspace and different health outcomes, including improved mental health (Annerstedt et al. 2012; Triguero-Mas, Donaire-Gonzalez, Seto, Valentín, Smith, et al. 2017; Britton et al. 2018: Korn et al. 2018; Lee and Lee 2019), reduced prevalence of type 2 diabetes (Teufel-Shone et al., 2014; Burkart et al., 2016), reduced mortality (Burkart et al., 2016; Orioli et al., 2019) and improved pregnancy outcomes (Abelt and McLafferty 2017). However, this is the first review to examine changes in dietary patterns following exposure to green and blue spaces, and no conclusive data were found on the association between them.

The first significant finding of this review was the lack of evidence and studies available concerning blue space. A small number of articles were retrieved; however, none met the inclusion criteria (Goeminne et al., 2015; Burkart et al., 2016; Britton et al., 2018). Further research should be conducted on the potential health benefits of blue space on dietary patterns, changes in dietary habits, and the associated health benefits.

In contrast, although greenspace is well researched, limited evidence is available on exposure to greenspace and impact or changes to dietary patterns, and only four studies were included in this review. Interpreting the results is further complicated because of the heterogeneity of the documented interventions and outcomes.

However, despite the limited findings in this review, emerging evidence suggests the use of urban horticulture as a tool to improve population health and urban biodiversity, particularly in socially disadvantaged neighbourhoods. Urban horticulture is related to an increase in healthy food intake, exercise, exposure to nature, and social cohesion among communities with several recent studies reporting on these health benefits (Algert et al. 2014, Clendenning et al. 2016, Martin et al. 2017). However, more studies are needed to strengthen the evidence available on its benefits to human health (Piedrahita et al. 2020).

The four observational studies included in this review identified an association between greenspace exposure and obesity. Yuen et al. (2019) indicated that exposure to greenspace was not correlated directly with healthy eating patterns but with physical activity levels. This finding is consistent with that of von Hippel and Benson (2014), who found that diet had no effect on the association between obesity and the natural environment, and that the relationship was mediated by physical activity. A similar finding was also reported by Michimi and Wimberly (2012), who discovered that as recreational opportunities and natural amenities increased, physical activity levels increased, and the prevalence of obesity decreased. An association between obesity and physical activity was also identified in the final study conducted by Choi and Yoon 2020, in which a negative association between BMI and walkability in urban neighbourhoods was identified. While the main research question addressed in this review explicitly concerns dietary pattern changes, secondary outcomes concerning exposure to greenspace and obesity were addressed.

4.2 Greenspace and obesity

The health benefits of exposure to greenspace and obesity have been well researched; however, the mechanisms and pathways underlying these associations are complex. Obesity is a complex disease and several factors play a role in gaining weight. However, one of the significant causes of obesity (BMI > 30) and overweight (BMI > 25) is the consumption of excessive energy dense foods combined with a lack of exercise (World Health Organisation, 2021). One of the potential mechanisms explored to explain the association between greenspace and health outcomes is the accessibility and availability of greenspace, which may influence individuals’ physical activity levels and subsequently, weight status. Yuen et al. (2019) found that physical activity levels were positively related to the percentage of greenspace and accessibility of open space facilities. In a study by von Hippel and Benson (2014), obesity was reported to be more prevalent in hot, dark, cold, and rainy counties in the US. These findings raise the possibility that individuals within these counties, owing to adverse weather conditions, are not engaging in outdoor physical activity, resulting in an increased prevalence of obesity. Attempts to promote physical activity should consider temperature extremes. Although little is known about how exercise affects dietary habits, evidence suggests that exercise motivates people to adopt healthier eating habits (Joo et al. 2019). Moderate physical activity can also serve as a gateway behaviour, leading to the adoption of other healthy habits (Blakely et al. 2004; Grant et al. 2020; Lounassalo et al. 2021).

Previous studies in this area have noted positive associations between greenspace and obesity-related indicators, including physical activity, BMI, and obesity-related health outcomes. According to a systematic review (Luo et al. 2020), there may be a link between increased access to greenspace and a lower risk of obesity. The results of the meta-analysis showed that individuals exposed to increased levels of NDVI were less likely to be overweight/obese [OR]: (0.88; 95% CI:0.84, 0.91); however, the review also identified that further high-quality studies are required to assess the evidence for this causal relationship. These findings are consistent with an earlier systematic review, which found a positive link between greenspace and obesity but mixed evidence on the association between greenspace access and physical activity (Lachowycz and Jones 2011). A study in the US reported lower BMI levels in individuals exposed to increased forest cover, and this association was stronger for those who participated in outdoor recreation (Ghimire et al. 2017). These studies reinforce the connection between opportunities for physical activity and a lower prevalence of obesity.

However, the results concerning greenspace exposure and obesity have been mixed across studies. One interesting finding in this review was that more urban leisure amenities in a neighbourhood were associated with higher BMI levels (Choi and Yoon 2020). This finding suggests that promoting walkability in neighbourhoods may be more successful in targeting obesity than leisure amenities.

Another finding of this review (von Hippel and Benson 2014) was that exposure to natural elements, such as wind, trees, waterfronts, and mountains, had little or no association with obesity. Recent Irish research (Dempsey et al. 2018) discovered evidence of a U-shaped relationship between obesity and greenspace. The study identified that people living in the highest and lowest areas assessed for greenspace had higher probabilities of obesity. These preliminary findings suggest that even though individuals may have access to greenspaces and other amenities in their neighbourhood, it does not mean they will avail of them to promote health. These relationships may partly be explained by other confounding and mediating factors.

Healthy eating habits also moderate obesity. However, this study discovered that healthy eating habits were not related to greenspace but rather to other demographic and quality of life (QoL) variables, such as education and age (Yuen et al. 2019). Again, this finding is consistent with the literature, and several factors are associated with food choices, including socioeconomic and demographic factors, and social mobility (Arruda et al. 2014).

Further research should be undertaken to investigate the implications of dietary patterns and physical activities on greenspace exposure to reveal a more solid relationship and determine causal pathways. Moreover, health interventions should target both health-promoting behavioural patterns (dietary habits and physical activity), as evidence suggests that individuals implementing one behaviour change are more likely to successfully implement another (Lippke et al. 2011). The features of the built environment should also be investigated, as walkability appears to be more strongly associated with obesity than with other urban or environmental amenities. Health interventions should consider temperature extremes as they are not conducive to outdoor physical activity.

4.3 Greenspace and Socio-economic Status (SES)

Evidence suggests that socioeconomic status (SES) is a significant indicator of obesity and food choice (Wham et al. 2015; Thorpe et al. 2019). There is also mounting evidence that greenspace exposure maybe “equigenic” (Mitchell et al., 2015), implying that those in the lowest socio-economic groups may experience the greatest benefits from greenspace exposure. This finding was reported by (Yuen et al., 2019), who identified that lower socioeconomic groups, such as the elderly, youth, and the less educated, appeared to benefit more from greenspace in their living urban environment. A similar finding was identified in a study by Maas et al., 2006), who reported that percentage greenspace within one and three kilometres radius was significantly related to improved self-perceived general health by individuals. This positive association was stronger for lower socioeconomic groups, including the elderly, youth, and second-level education. These results are consistent with those of Choi and Yoon (2020), who reported that SES has a negative effect on BMI, and identified that the impact of SES is much more significant on obesity than physical activity and access to environmental amenities. Similarly, Rigolon et al. 2021, discovered that greenspace has greater health benefits in low-income countries, and public greenspace has a greater protective effect for lower SES groups. There is a strong link between obesity and SES. According to a cross-sectional study conducted in the United States (Wen et al. 2017), obesity rates were found to be higher in rural areas, which was attributed to education level and median household income. Thorpe et al. (2019) found that a lower SES in education was a predictor of more deficient dietary patterns.

Other characteristics of greenspaces, including accessibility, quality, size, and facilities for certain activities, offer different opportunities for physical activity and other health benefits for individuals. Further research is necessary to determine the characteristics required for specific health outcomes. Individual user determinants are also crucial, including age, gender, ethnicity, and safety when using greenspace, and these should also be taken into account.

4.4 Limitations and Strengths of the study

The strengths of this study include the broad inclusion criteria used for greenspace and blue space and their effects on dietary outcomes to ensure that all relevant data were considered. Studies were not excluded based on the study design, type of greenspace, or measurement of exposure to greenspace. Consequently, a variety of greenspace exposures and outcomes were identified. However, this can also result in high heterogeneity across studies and difficulties in comparing and interpreting study results. Despite the inclusivity of this review, only a few articles which met the inclusion criteria were retrieved. Therefore, these findings should be cautiously interpreted. This review demonstrates the lack of research in this area, and further studies on dietary patterns, including food choices and dietary intake, should be undertaken.

Another limitation of this study was its methodological design. All included studies were observational, with a cross-sectional design being the most common. This review emphasises the need for longitudinal and experimental research in this area. In observational studies, there is a potential for bias, including selection bias, information bias, and confounding. In two of the studies used in this review (Michimi and Wimberly 2012; von Hippel and Benson 2014), BMI measurements for participants were based on self-reported heights and weights collected by the Behavioural Risk Factor Surveillance System (BRFSS), a telephone survey of more than 350,000 US adults per year. As this information is self-reported, there is a risk of over- and under-reporting, and compromised objectivity. To correct for self-reported bias in one study (von Hippel and Benson 2014) newly released bias-corrected estimates of county obesity prevalence were used.

Further bias can be introduced through confounding, and in two studies, quality appraisals (Michimi and Wimberly 2012; Yuen et al. 2019), it is unclear whether confounding factors were identified and strategies were implemented to deal with these. This can result in a biased estimate of the outcomes. A third study within the review (von Hippel and Benson 2014) identified that the associations reported in the study might be attributable to confounding factors that were not controlled for, and reverse causality is also possible. Due to complex associations and limited evidence on causal pathways for specific health outcomes in greenspaces, many confounding factors are possible. Strategies to avoid potential sources of bias should be adequately considered by careful planning, and future research should consider this.

This systematic review provides an updated overview of studies examining the associations between exposure to green and blue spaces and dietary intake and food choices among adults. This extensive review showed minimal evidence for an association between greenspace exposure and dietary patterns among adults. The most significant finding of this review is the paucity of evidence concerning this association, indicating that further research is required to understand the complex mechanisms involved and guide future interventions. Further research is needed to determine which greenspace attributes are required for specific health outcomes, including improved dietary intake and food choices among adults. The development of public health interventions concerning exposure to green or blue spaces with dietary outcomes should also consider the socio-economic status and substantial health benefits of this group.

Acknowledgements

We would like to thank Ms. Elizabeth Dore, Faculty Librarian, University of Limerick for help with designing the search strategy, Dr. Nuha Ibrahim, Dr. Diane O’ Doherty, and other members of the Public Health Team, University of Limerick for helpful advice, workshops, and comments.

Financial Support

This research received no specific grants from any funding agency, commercial, or not-for-profit sectors.

Conflict of Interest

None

Authorship

The search strategy was devised by CG, AS, AT, and EMOC, and was carried out by CG. The initial records were screened, and the data were extracted by the CG. AS has served as a second reviewer. Quality assurance was conducted by the CG and double-checked by the AS. Disagreements were resolved with a third party, the EMOC and AT, as needed. AS, EMOC, and AT provided critical feedback on the original manuscript written by the CG. EMOC work is part of the Go Green: Resilient Optimal Urban Natural, Technological, and Environmental Solutions (GoGreenRoutes) project, supported by the European Union’s Horizon 2020 framework programme under grant agreement no. 869764.

Appendix A Supporting Information

Supplementary data for the article can be found in the online version as well as the electronic file “Supplementary Material” that comes with it.

Declaration of interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Availability of data and materials

The following supporting information can be downloaded at: https: DOI 10.17605/OSF.IO/NCJDQ: PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analysis); Table S2: Search string used for this review, Table S3: Search terms used for this review and Table S5 critical appraisal for this review.

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Does exposure to green or blue space impact dietary intake and food choices among adults? A Systematic Literature Review.

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Abstract

Figures

Introduction

Methodology

2.1 Search Strategy

2.2 Selection Process

2.3 Eligibility Criteria

2.4 Data Collection Process And Data Items

2.5 Critical Appraisal

2.6 Narrative Synthesis

Results

3.1 Study Selection

3.2 Study Characteristics

3.3 Study outcomes

3.4 Critical Appraisal

Discussion

4.1 Summary of findings

4.3 Greenspace and Socio-economic Status (SES)

4.4 Limitations and Strengths of the study

Conclusion

Declarations

References

Figure 4

Supplementary Files

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