SEARCH

SEARCH BY CITATION

Keywords:

  • Diet;
  • environment;
  • obesity;
  • weight status

Summary

  1. Top of page
  2. Summary
  3. Introduction
  4. Method
  5. Findings
  6. Discussion
  7. Conflict of Interest Statement
  8. References

This study examined whether physical, social, cultural and economical environmental factors are associated with obesogenic dietary behaviours and overweight/obesity among adults. Literature searches of databases (i.e. PubMed, CSA Illumina, Web of Science, PsychInfo) identified studies examining environmental factors and the consumption of energy, fat, fibre, fruit, vegetables, sugar-sweetened drinks, meal patterns and weight status. Twenty-eight studies were in-scope, the majority (n= 16) were conducted in the USA. Weight status was consistently associated with the food environment; greater accessibility to supermarkets or less access to takeaway outlets were associated with a lower BMI or prevalence of overweight/obesity. However, obesogenic dietary behaviours did not mirror these associations; mixed associations were found between the environment and obesogenic dietary behaviours. Living in a socioeconomically-deprived area was the only environmental factor consistently associated with a number of obesogenic dietary behaviours. Associations between the environment and weight status are more consistent than that seen between the environment and dietary behaviours. The environment may play an important role in the development of overweight/obesity, however the dietary mechanisms that contribute to this remain unclear and the physical activity environment may also play an important role in weight gain, overweight and obesity.


Introduction

  1. Top of page
  2. Summary
  3. Introduction
  4. Method
  5. Findings
  6. Discussion
  7. Conflict of Interest Statement
  8. References

Obesity is a major cause of morbidity and mortality from chronic diseases such as cardiovascular and musculoskeletal diseases, some cancers and negative psychological wellbeing (1,2). The prevalence of overweight and obesity is high and ranges from 40% to 60% among adults in developed countries (2,3). In the last two decades there have been marked increases in the prevalence of overweight and obesity (4). Overweight and obesity results in substantial health and economic burdens, and these negative consequences are predicted to escalate as the population ages (5,6).

Overweight and obesity are the result of positive energy balance. Low levels of physical activity and/or dietary behaviours that deviate from recommendations are thought to contribute to the epidemic of obesity. In terms of dietary factors, population trends in overweight and obesity would suggest that energy intake exceeds energy expenditure (7). High energy intakes have been associated with higher fat intakes, greater intakes of energy-dense foods, including takeaway foods, higher intakes of foods providing ‘empty calories’ (e.g. sugar-sweetened drinks), lower intakes of foods and nutrients that may have appetite-controlling properties (i.e. fruit and vegetables, fibre) and meal patterns that interfere with the regulation of energy intakes (e.g. skipping breakfast) (7). Despite the health-related benefits of consuming a diet that promotes a healthy weight, many adults do not consume a diet consistent with these recommendations. Population-level dietary estimates show that fat intakes exceed recommendations by at least 10%, the majority of the population do not consume sufficient fruit, vegetables or fibre and a significant proportion of the population skip meals (8–11).

Given the rapid rise in overweight and obesity among populations of developed countries, many health practitioners and health researchers have postulated that the environment, rather than individual-level factors, may be driving the obesity epidemic. Policymakers are increasingly considering environments for the development of policy, however, have been limited by insufficient research documenting the role of the environment. Recent studies have shown that overweight and obesity cluster within areas, suggesting that shared environments may contribute to a positive energy balance (12–14). The postulated relationships between the environment and weight status is shown in Fig. 1. The current review primarily focuses on environmental factors that may influence dietary behaviours. ‘Obesogenic’ food environments are thought to facilitate high energy intakes by increasing access to stores that promote unhealthy food choices, such as takeaway and fast food shops, convenience stores and other outlets that are less likely to sell healthy food choices (15–17). Areas characterized by obesogenic food environments may also be associated with physical activity environments that promote decreased energy expenditure and sedentariness. The presumed importance of these environmental factors has resulted in a myriad of policies and interventions aimed at improving food environments (4,18,19). Despite widespread support for these policies and interventions, the discourse about their supposed importance has largely been discussed in position papers and narrative reviews, without synthesis of the evidence on how food environments are associated with overweight and obesity and the mechanisms by which environmental factors contribute to overweight/obesity.

image

Figure 1. Hypothesized relationship between the environment and weight status.

Download figure to PowerPoint

Two systematic reviews examining environmental correlates of obesogenic dietary intakes were conducted in 2004 (20,21). At this stage, there were few replicated studies that examined associations between obesogenic dietary intakes and the food environment. Given the increased research activity on environmental determinants of health-related behaviours in recent years, we sought to review the more recent literature on how features of the food environment are associated with both dietary intakes and overweight/obesity to identify factors to be targeted in policy and interventions to reduce overweight/obesity and to ascertain how shared environments may contribute to the obesity epidemic.

Method

  1. Top of page
  2. Summary
  3. Introduction
  4. Method
  5. Findings
  6. Discussion
  7. Conflict of Interest Statement
  8. References

Study scope

This review focused on studies of dietary intakes among adults (i.e. ≥18 years). The prevalence of overweight and obesity is greatest in adulthood (especially middle-age), and significant weight gains continue to occur in early and middle adulthood (6). The review examined studies conducted among developed countries, as defined by the World Bank (22).

Environmental factors

For the purposes of this study, the environment was defined as physical and infrastructural features of areas. A framework used in previous reviews (20,21,23) was used to guide the classification of different environmental factors during the review process. The framework shares common features with ecological models (24,25), stressing the importance of multiple types of environmental influences. The four categories that form this framework are:

  • 1
    Accessibility and availability. Including physical and financial accessibility of products and shops that are needed for an (un)healthy diet (e.g. access to shops, and availability of high fat foods and less healthy snacks);
  • 2
    Social conditions. These arise from inter-personal interactions (e.g. marketing) and social support;
  • 3
    Material conditions. Including unfavourable working, housing and neighbourhood conditions (e.g. neighbourhood deprivation).

These may affect behaviour through one of the previous environmental factors. For instance, living or working in an unfavourable environment might induce stress, which may relate to indifference concerning a healthy diet.

Obesogenic dietary factors

Dietary factors influence overweight/obesity through the energy balance pathway; excess energy intake is arguably the most important dietary factor in relation to weight gain and the development of overweight/obesity (26). As there are physiological limitations on the quantity of food/drink that can be consumed by individuals, excess energy intakes are often the consequence of energy-dense diets (i.e. high in kilojoules per unit weight) (7). Population-based studies have shown that energy-dense diets are characterized by: high intakes of fat and sugar, and low intakes of water-holding factors, such as fibre, fruit and vegetables, high intakes of sugar-sweetened beverages (e.g. soft drinks) and irregular meal patterns (27–30). These factors are suspected to contribute to overriding the normal physiological regulation of appetite and food intakes, and are associated with weight gain and overweight/obesity (6,26,29,31,32). Therefore, the dietary factors examined in this review included intakes of energy, total fat, fibre, fruit, vegetables, sugar-sweetened beverages and meal patterns.

Weight status

Any measure of weight status, including absolute weight or any equivilized weight scale such as body mass index (BMI), weight for height or categorization of weight status into groups was included in the current study.

Search strategy

Databases and search terms

A review protocol based on guidelines from the Cochrane Reviewer's Handbook (33) was used. Studies conducted among human subjects between 1 January 2005 and 1 October 2008 were located by searches of several major databases (i.e. PubMed, CSA Illumina, Web of Science and PsychInfo).

Broad search terms were used in the database searches to ensure that all potentially relevant articles entered the screening process. Each database was searched using database-specific indexing terms; suitable search terms were selected from lists of the database indexing system. For databases that did not have their own indexing terms (i.e. CSA Illumina) we searched for keywords in titles. The sensitivity of searches was tested by examining whether they located several key articles. The searches yielded 6014 potentially relevant titles (3580 in PubMed, 84 in CSA Illumina, 2322 in Web of Science and 28 in PsychInfo). The search terms and syntax used for each database are available from the authors on request.

Inclusion criteria

This review only included studies published in the peer-reviewed literature. Therefore, information from web sites, reports and conference abstracts were not included. Studies must have been published in English and conducted among a population-based sample (i.e. studies examining disease or patient sub-groups were excluded) of adults (i.e. ≥18 years of age). They must have examined at least one of the in-scope dietary factors, which could be summarized either as quantity consumed (e.g. grams of fruit consumed per day), frequency of consumption (e.g. how many times fruit was consumed per week) or compliance with recommendations (e.g. whether consumed two or more portions of fruit per day) or weight status. In-scope studies were required to have assessed at least one environmental factor. Studies that combined in-scope dietary factors with out-of-scope factors into summary indices of diet (e.g. dietary outcomes derived from factor analyses) were excluded as associations with the obesogenic dietary factors could not be distinguished from other dietary factors.

Title scanning

The title screening process was performed by two reviewers (KG and FvL), and took place in three steps. First, the titles located from the search results were scanned, to exclude those out of the scope of the current study. Fifty-five studies were selected at this stage. Subsequently, the Abstracts of all titles were independently examined by the two reviewers. At this step, each reviewer read all study abstracts, and produced a list of in-scope articles. Discrepancies between reviewers in the selected articles were discussed, and a consensus was reached on whether or not the article(s) in question would be incorporated. A total of 31 articles were identified for inclusion at this stage. Third, the reference lists of these articles were scanned and literature searches on major authors in the area were performed, a further five publications were included at this step. Seven manuscripts were subsequently excluded at the data extraction phase due to not meeting scope/inclusion criteria of the study. Therefore, 28 articles were included in the current review.

Data extraction and summary

Study details (i.e. country, study name, sample size, response rate, dietary assessment method, dietary/weight status outcome variable, environmental measure and the direction and magnitude of associations found) were summarized in data extraction tables. Because each study was designed to address different outcomes and associations, we reported associations adjusted for the relevant confounders (i.e. gender, age), where available. Some studies examined associations with more than one outcome of interest, in which case they were considered in more than one data extraction table.

Differences in intakes between environmental factors were ascertained by statistical significance and clinically relevant differences. In terms of clinically relevant differences, a 3% relative difference in energy intakes between groups equates to a weight gain of 2–4 kg year−1 for an average-sized adult (26), therefore differences of this magnitude are likely to have a marked long-term influence on BMI and overweight/obesity. Studies have shown that a 10% reduction in total fat intake is associated with a reduction in weight of 1.5–2 kg year−1(34). Likewise, a 10% increase in dietary fibre intakes is estimated to contribute to a weight loss of 1.5–2 kg year−1(26). Greater fruit and vegetable intakes are associated with a lower body weight among adults; however, there is insufficient evidence examining the magnitude of weight changes associated with intakes (35). Therefore, an arbitrary cut-off of a 10% difference in intakes of fruits and vegetables was used.

The magnitude of differences between environmental exposures was ascertained by calculating the relative difference between groups differing in their exposure to the environmental factor. This was calculated by:

  • image

Odds ratio estimates for differences were reported for dichotomous outcome variables.

Relative differences were considered small if they were ≤10% (or OR 0.80–1.0), moderate if relative differences were 10–20% (or OR 0.70–0.80) and large if relative differences were ≥20% (or OR ≤ 0.70).

Findings

  1. Top of page
  2. Summary
  3. Introduction
  4. Method
  5. Findings
  6. Discussion
  7. Conflict of Interest Statement
  8. References

The characteristics of the 28 studies included in the review are shown in Table 1. Twenty-three of these were conducted among separate study samples, and five studies were sourced from two study populations. The vast majority of in-scope studies (n = 16) were conducted in the USA, with other studies taking place in Australia or New Zealand (n = 7) and Japan (n = 2). Three Australian studies were sourced from one sample (SESAW), and two American studies were sourced from one sample (Stanford Heart Disease Prevention Program). Only three of the studies were conducted in Europe – two of these were among British samples (16,36) and one among a Dutch sample (37). With the exception of one natural experiment (16), all studies were cross-sectional. Study sample sizes ranged from 102 to 714 054 participants, with the majority of studies (n = 22) having sample sizes above 1000 participants. Response rates ranged from 10% to 87%, just under one half of the studies had response rates of ≥60% and one quarter (n = 7) did not report response rates.

Table 1.  Characteristics of in-scope studies
Author (date)CountryStudy nameSample size (response rate)Environmental assessment methodDietary/weight assessment methodEnvironmental factors examinedOutcome measure(s)Unit of outcome measure
  1. BMI, body mass index; FFQ, food frequency questionnaire.

Alaimo et al. (2008) (48)USASpeak to Your Health! Community SurveyN = 766 (15% response)Self-reportedFFQCommunity participationFrequency of fruit and vegetable consumptionNumber of times consumed per day
Ball et al. (2006) (49)AustraliaSESAWN = 1 347 women (42% response)Objective and self-reportedFFQSocial support, density of supermarkets and fruit and vegetable storesFruit and vegetable consumption.Mean daily servings
Beydoun et al. (2008) (50)USACSFII 1994–1996N = 7 331 (response not provided)Objective24-h diet recallPrice of fruit and vegetables, price of fast foodIntakes of energy, total fat, fibre, fruit and vegetablesMean daily intakes (continuous)
Binkley (2006) (51)USADiet and Health Knowledge SurveyN = 4 361 (response not provided)Self-reported24-h diet recallHousehold income, hours worked, receipt of food stamps, urban/rural residenceFast food consumptionWhether consumed fast food in previous 24 h (yes/no)
Bodor et al. (2008) (52)USAN = 102 (53% response)Objective24-h recallLocation of small food store and supermarket, availability of fresh fruit and vegetablesFruit and vegetable consumptionMean daily servings
Boutelle et al. (2007) (53)USAProject EATN = 902 (70% response)Self-reportedFFQFrequency of fast food for family mealFruit and vegetable, breakfast and lunch consumptionMean daily servings fruit and vegetables, days per week that breakfast/lunch is consumed
Crawford et al. (2007) (54)AustraliaSESAWN = 1 136 (42% response)Self-reportedFFQEating takeaway/fast-foodFruit and vegetable consumptionConsumption of ≥1 serve daily (yes/no)
Cummins et al. (2005) (16)UKN = 412 (∼10% response)ObjectiveFFQLocation of supermarketFruit and vegetable consumptionMean daily servings
Dubowitz et al. (2008) (55)USANHANES III (1988–1994)N = 13 300 (response not provided)Objective24-h recallNeighbourhood socioeconomic characteristicsFruit and vegetable consumptionMean daily servings
Fukuda et al. (2007) (56)Japan2001 Comprehensive Survey of the Living Conditions of People on Health and WelfareN = 30 386 (87% response)Objective and self-reportedFFQPer capita income of prefecture, unemployment of prefectureRegular meal consumptionPoor dietary score (yes/no)
Giskes et al. (2003) (37)NetherlandsGLOBEN = 1 339 (81% response)ObjectiveFFQ (81% RR)Neighbourhood socioeconomic characteristicsFat and fruit intake, breakfast consumptionHighest and lowest quartile of fat and fruit intake, respectively (yes/no), skips breakfast at least once per week (yes/no)
Inagami et al. (2006) (17)USALAFANS studyN = 2 620 adults (RR not provided)ObjectiveNot specifiedLocation of closest grocery storeBMIContinuous
Inglis et al. (2008) (57)AustraliaSESAWN = 1 580 (42% response)Self-reportedFFQPerceptions of the availability of: high-quality fresh produce, fast-food and café proximityFruit, vegetable and fast-food consumptionBeing a high fruit/vegetable consumer (yes/no), being a frequent fast-food consumer (yes/no)
Jeffery et al. (2006) (58)USA N = 1 033 (RR not provided)ObjectiveSelf-reported height and weightDensity of fast food outletsBMIContinuous
Li et al. (2009) (59)USA N = 1 221 48% RRObjectiveSelf-reported height and weightDensity of fast food outletsOverweight/obesityYes/no
Mehta and Chang (2008) (60)USABehavioural Risk Factor Surveillance SystemN = 714 054 (RR not provided)ObjectiveNot specifiedDensity of fast food and full-service restaurantsBMI, overweight/obesityBMI (continuous), overweight/obesity (yes/no)
Mohr et al. (2007) (61)AustraliaN = 20 527 (60% response)Self-reportedFFQTV viewingFast food consumptionFrequency of fast food consumption per week
Moore et al. (2008) (62)USAMulti-Ethnic Study of AthersclerosisN = 2 384 (46% response)Objective and self-reportedFFQDensity of supermarkets, availability of healthy foodsFat intakeBeing in highest quartile of fat intake
Morland et al. (2006) (40)USAARICN = 10 763 82% RRObjectiveMeasured height and weightPresence of: supermarket, grocery store, convenience store, restaurant, fast-food outletOverweight/obesityYes/no
Morikawa et al. (2008) (63)JapanN = 4 736 (78% response)Self-reportedDiet HistoryShift workIntakes of energy, fat, fibre and vegetablesMean daily intakes (continuous)
Pearce et al. (2008) (39)New ZealandNew Zealand Health Survey (2002/2003)N = 12 529 (RR not provided)ObjectiveFFQAccess to takeaway food outletsFruit and vegetable consumptionWhether meets recommendations (yes/no)
Simmons et al. (2005) (64)AustraliaAusDiabN = 1 454 (61% RR)ObjectiveMeasured height and weightAvailability of takeaway outlets and restaurantsObesityYes/no
Stafford et al. (2007) (36)UKHealth Survey for England and the Scottish Health SurveyN = 12 605 RR ranged 69–81%ObjectiveMeasured height and weightPresence of supermarketBMIContinuous
Turrell and Giskes (2008) (46)AustraliaBrisbane Food StudyN = 1 001 (66% response)ObjectiveFFQArea socioeconomic characteristics, access to takeaway food outletsTakeaway food consumptionConsumption at least once per month
Wang et al. (2008) (65)USAStandford Heart Disease Prevention ProgramN = 5 779 (56–69% response)ObjectiveFFQ, measured height and weightDensity of: supermarkets, grocery stores, convenience stores, fast-food outletsFat consumptionMean daily intake (continuous)
Wang et al. (2007) (66)USAStandford Heart Disease Prevention ProgramN = 5 779 (56–69% response)ObjectiveFFQ, measured height and weightDensity of: supermarkets, grocery stores, convenience stores, fast-food outletsBMIContinuous
Watters et al. (2007) (67)USAN = 747 (18% response)Self-reportedFFQUrban/rural residence, social supportFruit and vegetable consumptionMean daily servings
Zenk et al. (2005) (68)USAEast Side Village Health Worker PartnershipN = 365 (∼65% response)Self-reportedFFQType of food store participants shopped at, assortment/selection/quality of fruits and vegetables in storeFruit and vegetable consumptionFrequency of intake

Most studies (n = 13) examined fruit and vegetable consumption, two investigated energy intakes, six assessed fat intakes and three examined fibre intakes. Four of the in-scope studies examined takeaway or fast food consumption and three studies explored meal patterns (i.e. breakfast consumption and/or the regularity of meals). No study examined environmental factors in relation to the consumption of sugar-rich beverages. Eight studies assessed associations between environmental factors and weight status.

Most (n = 18) examined accessibility factors; social factors and material factors were explored in three and seven studies, respectively. Only two studies looked at associations between cultural factors and obesogenic dietary intakes. The majority of studies used food frequency questionnaires to ascertain dietary intakes and measured height and weight to assess weight status. Most (n = 16) measured environmental factors using objective measures, nine studies assessed environmental factors using self-reported information and the remaining three studies used a combination of objective and self-reported data.

Accessibility factors

Associations between accessibility factors and obesogenic dietary intakes or weight status are shown in Table 2.

Table 2.  Summary of study findings examining associations between accessibility factors, dietary behaviours and weight status*
Author (date)EnergyFatFibreFruit/vegetablesWeight statusOther
  • *Differences reported are relative to the reference group (i. e. ‘+’ refers to higher intakes relative to the reference group, ‘−‘ refers to lower intakes relative to the reference group and ‘=‘ refers to no differences). Differences were reported as higher or lower if they were statistically significant (P < 0.05) or if relative differences in intakes were ≥10%.

  • Relative difference (%) in intakes between lowest and highest socioeconomic groups calculated by: ([value lowest group − value highest group]/value highest group) × 100.

  • Odds ratios (OR) were reported where outcome variable were dichotomous.

  • F, fruit; FV, fruit and vegetables (combined); V, vegetables.

Access to supermarkets (high vs low)
 Ball et al. (2006) (49)   (=) F (=) V  
 Bodor et al. (2008) (52)   (=) F (=) V  
 Cummins et al. (2005) (16)   (=) FV  
 Moore et al. (2008) (62) (−) 85%   (−) 85% processed meat
 Morland et al. (2006) (40)    (−) 10% overweight (−) 35% obese 
 Stafford et al. (2007) (36)    (−) <1% BMI 
 Wang et al. (2007) (66) (=)    
 Wang et al. (2008) (65)    (=) men (−) <1% BMI women 
 Zenk et al. (2005) (68)   (+) 19% FV  
Access to grocery or convenience store (high vs low)
 Bodor et al. (2008) (52)   (−) 25%F (−) 38%V  
 Inagami et al. (2006) (17)    (−) 3% BMI 
 Morland et al. (2006) (40)    Grocery store: (=) overweight (+) 17% obesity Convenience store: (=) overweight (+) 12% obesity 
 Wang et al. (2007) (66)(+) 20–32%     
 Wang et al. (2008) (65)    Grocery store: (=) men (+) <1% women Convenience store: (=) men (=) women 
Access to takeaway food outlets (high vs low)
 Inglis et al. (2008) (57)   (=) FV (=) fast food
 Jeffery et al. (2006) (58)    (=) BMI 
 Li et al. (2009) (59)    (+) 7% overweight/obesity 
 Mehta and Chang (2008)(60)    (+) <1% BMI (+) 5% obesity 
 Morland et al. (2006) (40)    (+) 6% overweight (+) 14% obesity 
 Pearce et al. (2008) (39)   (=) F (=) V multinational (−) OR 0.85 (0.73 to 1.00) V local  
 Simmons et al. (2005) (64)    (=) overweight/obesity 
 Turrell and Giskes (2008) (46)     (=) takeaway
 Wang et al. (2007) (66) (−) 20–32%    
 Wang et al. (2008) (65)    (=) BMI 
Access to restaurants and cafes (high vs low)
 Inglis et al. (2008) (57)   (=) FV (=) fast food
 Mehta and Chang (2008) (60)    (−) 1% BMI (−) 11% obesity 
 Morland et al. (2006) (40)    (=) overweight (=) obesity 
 Simmons et al. (2005) (64)    (=) obesity 
Access to fruit and vegetable stores (high vs low)
 Ball et al. (2006) (49)   (=) FV  
Availability/shelf space of healthy foods in stores (high vs low)
 Bodor et al. (2008) (52)   (=) F (+) 47%V  
 Inglis et al. (2008) (57)   (+) OR 0.70 (0.56 to 0.93) F (+) OR 0.60 (0.46 to 0.81) V (=) fast food
 Moore et al. (2008) (62) (−) 28%    
 Zenk et al. (2005) (68)   (=) FV  
Prices (high vs low)      
 Beydoun et al. (2008) (50)(=)(=)(−) 14%(=)(=)(=) fast food

For fruit and vegetable consumption, access to supermarkets, grocery/convenience, takeaway and fruit and vegetable stores was examined in 14 associations. The number of associations measured was greatest and most consistent for access to supermarkets; five out of six associations found that greater accessibility to supermarkets was not associated with fruit and vegetable consumption. Three out of four associations assessing access to takeaway outlets and fruit and vegetable consumption showed no significant/meaningful differences. Furthermore, there were no consistent associations between availability/shelf space of fruits and vegetables and their consumption.

Five associations measured differences in weight status by access to supermarkets; four of these found that people with greater access to supermarkets had lower BMI/prevalence of overweight/obesity compared with those with less access. These differences were small-to-moderate in magnitude (i.e. differences of between 1–35%). The majority of associations (five out of eight) examining access to takeaway food outlets and weight status found that greater access was associated with greater BMI/prevalence of overweight/obesity. However, associations with access to grocery/convenience stores were found to be mixed. Five associations looked at takeaway consumption in relation to takeaway outlets, shelf space and prices of healthy foods, and also found no association with takeaway consumption. Another five associations examined access to restaurants/cafes and weight status, three of these found no differences in weight status by access.

Social factors

Table 2 summarizes associations between social factors and dietary intakes or weight status. There were mixed associations found between social support and fruit and vegetable consumption. Only one study examined community participation, and found no association with fruit and vegetable consumption.

Cultural factors

Associations between cultural factors and obesogenic dietary intakes are summarized in Table 3. Only two studies were located, and these found mixed associations with TV viewing and consumption of fruit and vegetables or takeaway foods (Table 4).

Table 3.  Summary of study findings examining associations between social factors, dietary behaviours and weight status*
Author (date)EnergyFatFibreFruit/vegetablesWeight statusOther
  • *

    Differences reported are relative to the reference group (i.e. ‘+’ refers to higher intakes relative to the reference group, ‘−’ refers to lower intakes relative to the reference group and ‘=’ refers to no differences). Differences were reported as higher or lower if they were statistically significant (P < 0.05) or if relative differences in intakes were ≥10%.

  • Relative difference (%) in intakes between lowest and highest socioeconomic groups calculated by: ([value lowest group − value highest group]/ value highest group) × 100.

  • Odds ratios (OR) and 95% confidence intervals were reported where outcome variable were dichotomous.

  • F, fruit; FV, fruit and vegetables (combined); V, vegetables.

Social support (high vs. low)      
 Ball et al. (2006) (49)   (+) 13 to 18% F (+) 11 to 19% V  
 Watters et al. (2007) (67)   (=) FV  
Community participation (high vs. low)      
 Alaimo et al. (2008) (48)   (=) FV  
Table 4.  Summary of study findings examining associations between cultural factors, dietary behaviours and weight status*
Author (date)EnergyFatFibreFruit/vegetablesWeight statusOther
  • *Differences reported are relative to the reference group (i. e. ‘+’ refers to higher intakes relative to the reference group, ‘−’ refers to lower intakes relative to the reference group and ‘=’ refers to no differences). Differences were reported as higher or lower if they were statistically significant (P < 0.05) or if relative differences in intakes were ≥10%.

  • Relative difference (%) in intakes between lowest and highest socioeconomic groups calculated by: ([value lowest group − value highest group]/value highest group) × 100.

  • Odds ratios (OR) were reported where outcome variable were dichotomous.

  • F, fruit; FV, fruit and vegetables (combined); V, vegetables.

TV viewing (high vs. low)      
 Crawford et al. (2007) (54)   (−) OR 0.70 (0.50 to 1.0) F (−) OR 0.60 V  
 Mohr et al. (2007) (61)     (+) 12% takeaway food

Material factors

Study findings examining associations between material factors and obesogenic dietary intakes are shown in Table 5.

Table 5.  Summary of study findings examining associations between material factors, dietary behaviours and weight status*
Author (date)EnergyFatFibreFruit/vegetablesWeight statusOther
  • *Differences reported are relative to the reference group (i. e. ‘+’ refers to higher intakes relative to the reference group, ‘−’ refers to lower intakes relative to the reference group and ‘=’ refers to no differences). Differences were reported as higher or lower if they were statistically significant (P < 0.05) or if relative differences in intakes were ≥10%.

  • Relative difference (%) in intakes between lowest and highest socioeconomic groups calculated by: ([value lowest group − value highest group]/value highest group) × 100.

  • Odds ratios (OR) were reported where outcome variable were dichotomous.

  • F, fruit; FV, fruit and vegetables (combined); V, vegetables.

Area deprivation characteristics (advantaged vs. deprived)
 Dubowitz et al. (2008) (55)   (+) 24%FV  
 Fukuda et al. (2007) (56)     (−) 9–12% irregular meal pattern
 Giskes et al. (2003) (37)(=)  (+) OR 1.18 (0.79 to 1.72) F (−) OR 0.67 (0.43 to 1.05) skipping breakfast
 Turrell and Giskes (2008) (46)     (=) takeaway purchase
Urban/rural residence (urban vs rural)
 Binkley (2006) (51)     (+) 14% takeaway consumption
 Watters et al. (2007) (67)   (+) 21%FV  
Shift work (yes vs no)
 Morikawa et al. (2008) (63)(+) 7–10%  (−) 22%V  

The two studies examining area deprivation and fruit and vegetable consumption found that living in a socioeconomically advantaged area was associated with greater fruit and vegetable consumption or a higher likelihood of their consumption. Only two studies looked at fruit and vegetable consumption in relation to urban/rural residence and shift work; these found that residing in a rural area and not being a shift worker were associated with higher fruit and vegetable intakes.

There was only one study examining associations in takeaway consumption with each of the following material factors: area deprivation, urban/rural residence and receipt of welfare. Only living in an urban area was associated with higher takeaway consumption. Two associations that examined area deprivation and meal patterns found that living in a socioeconomically advantaged area was associated with more regular meal patterns.

Discussion

  1. Top of page
  2. Summary
  3. Introduction
  4. Method
  5. Findings
  6. Discussion
  7. Conflict of Interest Statement
  8. References

We conducted a systematic review of the literature examining environmental factors associated with obesogenic dietary intakes and overweight/obesity. Weight status was most consistently associated with features of the environment; residents of areas with greater access to supermarkets or lower accessibility to takeaway outlets had a lower prevalence of overweight/obesity compared with those living in areas with limited supermarket access or a greater accessibility to takeaway outlets. Paradoxically however, the findings of studies examining environmental factors in relation to obesogenic dietary behaviours were less consistent, with mixed associations reported. The only exception to this was area-level deprivation, with residents of socioeconomically deprived areas having a greater likelihood of obesogenic dietary intakes than their counterparts in advantaged areas.

The current review updated two systematic reviews conducted in 2004 that examined environmental correlates of energy, fat, fruit and vegetable intakes (20,21). These previous reviews found that most studies focussed on work conditions and seasonal/day-of-the-week variations in dietary intakes. However, the current review found an increasing amount of research that examined accessibility factors (i.e. locations of supermarkets, takeaway food stores, availability of healthy food choices within stores) and area-level socioeconomic deprivation than reported in previous reviews. Furthermore, we found a greater number of studies that examined these environmental factors in relation to the distal outcome, weight status, rather than the more ‘intermediate’ outcome of dietary intakes.

Greater access to takeaway outlets may increase the ease at which people make food choices less consistent with dietary recommendations by minimizing barriers to making these choices (15,38). A limited access to supermarkets may result in reliance on convenience stores or takeaway outlets; these stores tend to sell foods less consistent with long-term health (16,39,40). Living in a socioeconomically deprived area may influence dietary behaviours by limiting access to supermarkets (through lower servicing of these areas by supermarkets or lower access to transport) and increasing access to corner/convenience stores (40). This later association is predominantly seen in the USA, however, is not consistently observed in other countries (41). Despite an increase in research examining accessibility factors, relatively few studies have examined other environmental factors implicated in the obesity epidemic, such as: portion sizes and the marketing of energy-dense foods (4,18).

We found more consistent evidence of associations between environmental factors and weight status than studies examining associations between environmental factors and dietary intakes. If the environment is hypothesized to influence weight status, we would expect to find an association between environmental factors and diet, and between environmental factors and weight status. A potential explanation of this finding is that environmental factors may influence BMI through a more complex interplay of factors, including physical activity, which has not been well explored in other studies. However, this is difficult to ascertain as no known studies have assessed features of the environment, dietary intakes, physical activity and weight status simultaneously. This may also be due (in part) to the complexity in measuring dietary intakes and physical activity; calculating these requires accurate recall and description of dietary intakes and physical activity (42). This is particularly difficult to achieve in studies of population-representative samples, where the self-administered data collection methods frequently used generally involve a high degree of participant burden (42). Furthermore, obesogenic food and physical activity environments may co-exist, making it difficult to attribute which feature of the environment contributes to the development of overweight and obesity. This is an area that requires increased research activity to disentangle the pathways that contribute to the spatial patterning in weight status in urban areas that has been documented in a number of studies from North America (13,43,44), Europe (45) and Australia (12).

The majority of studies included in the current review were conducted in the USA, UK or Australia/New Zealand. It is therefore unclear whether findings from this review can be generalized to other regions. Previous research has shown that the USA represents an anomaly with respect to the geographic size of urban areas and the residential segregation of socioeconomic and ethnic groups compared with other developed countries (41,46). This has raised the issue of whether the associations seen between environmental factors and dietary behaviours in the USA are relevant to other developed countries, especially in the European region (41).

This study considered a number of dietary outcomes; however, the findings showed that associations between obesogenic dietary behaviours and environmental factors have been studied most frequently for fruit and vegetable intakes. This may be because fruit and vegetable consumption is positively associated with other healthy dietary intakes and behaviours, such as intakes that are less energy dense, lower in fat, higher in fibre and less frequent consumption of fast food (20,47). However, it is likely that environmental factors are associated with each nutrient, food group or dietary intake pattern differentially (18,20). For example, accessibility to fruit and vegetable shops may influence fruit, vegetable and fibre consumptions; however, it is less plausible that accessibility to fruit and vegetable shops may influence the consumption of sugar-rich beverages or meal patterns. Therefore, it is important for future research to investigate environmental influences on all dietary factors that may contribute to obesogenic dietary intakes.

Several limitations of our review must be considered in light of our findings. Our search strategy only located studies that were published in peer-reviewed journals and referenced in electronic databases, excluding ‘grey’ literature. We tried to minimize any potential bias that may be induced from only examining peer-reviewed literature by also performing searches in smaller and more specialized databases (e.g. CSA Illumina). There was also great variation between studies included in the current review in terms of the conceptualization, measurement and summary of both the environmental factors and dietary behaviours which may have contributed to heterogeneous findings. Furthermore, although strict inclusion criteria were used, environmental or dietary intake measures sometimes differed markedly between studies. Little is known about appropriate confounders to adjust for when examining associations between environmental factors and dietary intakes/weight status (20). Some studies may have ‘over-corrected’ for such factors, which may diminish the magnitude or significance of associations with environmental factors. Whereas other studies that did not correct for appropriate individual-level confounders and therefore may over-estimate the strength or significance of these associations. Furthermore, most of the studies included in this review were cross-sectional, making it difficult to ascertain causality between environmental factors and obesogenic dietary intakes.

The current review suggested that accessibility to supermarkets/takeaway outlets or residing in a socioeconomically deprived area are environmental factors that may contribute to overweight or obesity and/or obesogenic dietary behaviours. These factors need to be targeted in multilevel health promotion interventions and policies aimed at decreasing overweight/obesity. The role of other environmental factors, however, should not be discarded without further investigation, namely those whose associations with dietary behaviours/weight status were not examined or are not possible to infer from the limited number of studies. Despite the limitations in the evidence base to date, we should not refrain from policies and interventions promoting healthy environments because waiting for such evidence to emerge before action is taken may simply represent a delay to addressing the obesity epidemic. To understand the role of environmental factors, studies are required that simultaneously examine a broad range of environmental factors, obesogenic dietary behaviours and physical activity and that utilize prospective study designs.

Conflict of Interest Statement

  1. Top of page
  2. Summary
  3. Introduction
  4. Method
  5. Findings
  6. Discussion
  7. Conflict of Interest Statement
  8. References

No conflict of interest was declared.

References

  1. Top of page
  2. Summary
  3. Introduction
  4. Method
  5. Findings
  6. Discussion
  7. Conflict of Interest Statement
  8. References
  • 1
    Murray C, Lopez A. Mortality by cause for eight regions of the world: Global Burden of Disease Study. Lancet 1997; 349: 12691276.
  • 2
    WHO. Diet, nutrition and the prevention of chronic diseases. Report of a WHO Study Group. World Health Organ Tech Rep Ser 1990; 797: 1204.
  • 3
    Hill JO, Peters JC, Catenacci VA, Wyatt HR. International strategies to address obesity. Obes Rev 2008; 9(Suppl. 1): 4147.
  • 4
    James WP. The fundamental drivers of the obesity epidemic. Obes Rev 2008; 9(Suppl. 1): 613.
  • 5
    Michaud C, Murray C, Bloom B. Burden of disease- implications for future research. J Am Med Assoc 2001; 285: 535539.
  • 6
    BrancaF, NikogosianH, LobsteinT (eds). The Challenge of Obesity in the WHO European Region and the Strategies for Response. WHO Regional Office for Europe: Copenhagen, 2007.
  • 7
    Branca F, Nikogosian H, Lobstein T. Dietary Determinants of Obesity. The Challenge of Obesity in the WHO European Region and the Strategies for Response. WHO Regional Office for Europe: Copenhagen, 2007, pp. 4654.
  • 8
    Giskes K, Lenthe FF, Brug HJ, Mackenbach J. Dietary intakes of adults in the Netherlands by childhood and adulthood socioeconomic position. Eur J Clin Nutr 2004; 58: 871880.
  • 9
    Giskes K, Turrell G, Patterson C, Newman B. Socio-economic differences in fruit and vegetable consumption among Australian adolescents and adults. Public Health Nutr 2002; 5: 663669.
  • 10
    Hulshof KF, Brussaard JH, Kruizinga AG, Telman J, Lowik MR. Socio-economic status, dietary intake and 10 y trends: the Dutch National Food Consumption Survey. Eur J Clin Nutr 2003; 57: 128137.
  • 11
    Song WO, Chun OK, Obayashi S, Cho S, Chung CE. Is consumption of breakfast associated with body mass index in US adults? J Am Diet Assoc 2005; 105: 13731382.
  • 12
    King T, Kavanagh AM, Jolley D, Turrell G, Crawford D. Weight and place: a multilevel cross-sectional survey of area-level social disadvantage and overweight/obesity in Australia. Int J Obes (Lond) 2006; 30: 281287.
  • 13
    Lebel A, Pampalon R, Hamel D, Theriault M. The geography of overweight in Quebec: a multilevel perspective. Can J Public Health 2009; 100: 1823.
  • 14
    Matheson FI, Moineddin R, Glazier RH. The weight of place: a multilevel analysis of gender, neighborhood material deprivation, and body mass index among Canadian adults. Soc Sci Med 2008; 66: 675690.
  • 15
    Burns CM, Inglis AD. Measuring food access in Melbourne: access to healthy and fast foods by car, bus and foot in an urban municipality in Melbourne. Health Place 2007; 13: 877885.
  • 16
    Cummins S, Petticrew M, Higgins C, Findlay A, Sparks L. Large scale food retailing as an intervention for diet and health: quasi-experimental evaluation of a natural experiment. J Epidemiol Community Health 2005 59: 10351040.
  • 17
    Inagami S, Cohen DA, Finch BK, Asch SM. You are where you shop: grocery store locations, weight, and neighborhoods. Am J Prev Med 2006; 31: 1017.
  • 18
    Glanz K, Sallis JF, Saelens BE, Frank LD. Healthy nutrition environments: concepts and measures. Am J Health Promot 2005; 19: 330333.
  • 19
    French SA. Public health strategies for dietary change: schools and workplaces. J Nutr 2005; 135: 910912.
  • 20
    Kamphuis C, Giskes K, Wendel-Vos W, de Bruijn G, Brug J, van Lenthe F. Environmental determinants of fruit and vegetable consumption among adults- a systematic review. Br J Nutr 2006; 96: 620635.
  • 21
    Giskes K, Kamphuis C, Kremers S, Droomers M, Brug J, van Lenthe F. A systematic review of associations between environmental factors, energy and fat intakes among adults: is there evidence for environments that encourage obesogenic dietary intakes. Public Health Nutr 2007; 10: 10051017.
  • 22
    World Bank. World Bank Web Site. [WWW document]. URL http://www.worldbank.com 2009 (updated 2009; accessed 14 March 2009).
  • 23
    van der Horst K, Oenema A, Ferreira I, Wendel-Vos W, Giskes K, Brug J. A systematic review of environmental correlates of obesity-related dietary behaviours in youth. Health Educ Res 2007; 22: 203226.
  • 24
    Cohen DA, Scribner RA, Farley TA. A structural model of health behaviour: a pragmatic approach to explain and influence health behaviours at the population level. Prev Med 2000; 30: 146154.
  • 25
    Hovell M, Wahlgren D, Gehrman C. The behavioural ecological model. In: DiClementeR, CrosbyR, KeglerM (eds). Emerging Theories in Health Promotion Practice and Research Strategies for Improving Public Health. Jossey-Bass: San Francisco, 2002, pp. 347385.
  • 26
    Roberts SB, McCrory MA, Saltzman E. The influence of dietary composition on energy intake and body weight. J Am Coll Nutr 2002; 21: 140S145S.
  • 27
    Johnson L, Mander AP, Jones LR, Emmett PM, Jebb SA. Energy-dense, low-fiber, high-fat dietary pattern is associated with increased fatness in childhood. Am J Clin Nutr 2008; 87: 846854.
  • 28
    Mendoza JA, Drewnowski A, Christakis DA. Dietary energy density is associated with obesity and the metabolic syndrome in U.S. adults. Diabetes Care 2007; 30: 974979.
  • 29
    Ledikwe JH, Blanck HM, Kettel Khan L, Serdula MK, Seymour JD, Tohill BC, Rolls BJ. Dietary energy density is associated with energy intake and weight status in US adults. Am J Clin Nutr 2006; 83: 13621368.
  • 30
    Togo P, Osler M, Sorensen TI, Heitmann BL. Food intake patterns and body mass index in observational studies. Int J Obes Relat Metab Disord 2001; 25: 17411751.
  • 31
    de Oliveira MC, Sichieri R, Venturim Mozzer R. A low-energy-dense diet adding fruit reduces weight and energy intake in women. Appetite 2008; 51: 291295.
  • 32
    Iqbal SI, Helge JW, Heitmann BL. Do energy density and dietary fiber influence subsequent 5-year weight changes in adult men and women? Obesity (Silver Spring) 2006; 14: 106114.
  • 33
    Higgins J, Green S. Cochrane Handbook for Systematic Reviews of Interventions. John Wiley & Sons Ltd: Chichester, 2005.
  • 34
    Astrup A. The role of dietary fat in the prevention and treatment of obesity. Efficacy and safety of low-fat diets. Int J Obes Relat Metab Disord 2001; 25(Suppl. 1): S46S50.
  • 35
    Tohill BC, Seymour J, Serdula M, Kettel-Khan L, Rolls BJ. What epidemiologic studies tell us about the relationship between fruit and vegetable consumption and body weight. Nutr Rev 2004; 62: 365374.
  • 36
    Stafford M, Cummins S, Ellaway A, Sacker A, Wiggins RD, Macintyre S. Pathways to obesity: identifying local, modifiable determinants of physical activity and diet. Soc Sci Med 2007; 65: 18821897.
  • 37
    Giskes K, van Lenthe FJ, Brug J, Mackenbach JP. Dietary intakes of adults in the Netherlands by childhood and adulthood socioeconomic position. Eur J Clin Nutr 2003; 58: 871880.
  • 38
    Pearce J, Blakely T, Witten K, Bartie P. Neighborhood deprivation and access to fast-food retailing: a national study. Am J Prev Med 2007; 32: 375382.
  • 39
    Pearce J, Hiscock R, Blakely T, Witten K. The contextual effects of neighbourhood access to supermarkets and convenience stores onindividual fruit and vegetable consumption. J Epidemiol Community Health 2008; 62: 198201.
  • 40
    Morland K, Diez Roux AV, Wing S. Supermarkets, other food stores, and obesity: the atherosclerosis risk in communities study. Am J Prev Med 2006; 30: 333339.
  • 41
    Cummins S, Macintyre S. Food environments and obesity – neighbourhood or nation? Int J Epidemiol 2006; 35: 100104.
  • 42
    Gibson R. Principles of Nutritional Assessment. Oxford University Press: New York, 2005.
  • 43
    Stimpson JP, Ju H, Raji MA, Eschbach K. Neighborhood deprivation and health risk behaviors in NHANES III. Am J Health Behav 2007; 31: 215222.
  • 44
    Ford ES, Mokdad AH, Giles WH, Galuska DA, Serdula MK. Geographic variation in the prevalence of obesity, diabetes, and obesity-related behaviors. Obes Res 2005; 13: 118122.
  • 45
    van Lenthe FJ, Mackenbach JP. Neighbourhood deprivation and overweight: the GLOBE study. Int J Obes Relat Metab Disord 2002; 26: 234240.
  • 46
    Turrell G, Giskes K. Socioeconomic disadvantage and the purchase of takeaway food: a multilevel analysis. Appetite 2008; 51: 6981.
  • 47
    Mente A, de Koning L, Shannon HS, Anand SS. A systematic review of the evidence supporting a causal link between dietary factors and coronary heart disease. Arch Intern Med 2009; 169: 659669.
  • 48
    Alaimo K, Packnett E, Miles RA, Kruger DJ. Fruit and vegetable intake among urban community gardeners. J Nutr Educ Behav 2008; 40: 94101.
  • 49
    Ball K, Crawford D, Mishra G. Socio-economic inequalities in women's fruit and vegetable intakes: a multilevel study of individual, social and environmental mediators. Public Health Nutr 2006; 9: 623630.
  • 50
    Beydoun MA, Powell LM, Wang Y. The association of fast food, fruit and vegetable prices with dietary intakes among US adults: is there modification by family income? Soc Sci Med 2008; 66: 22182229.
  • 51
    Binkley J. The effect of demographic, economic and nutrition factors on the frequency of food away from home. J Consum Aff 2006; 40: 372391.
  • 52
    Bodor JN, Rose D, Farley TA, Swalm C, Scott SK. Neighbourhood fruit and vegetable availability and consumption: the role of small food stores in an urban environment. Public Health Nutr 2008; 11: 413420.
  • 53
    Boutelle KN, Fulkerson JA, Neumark-Sztainer D, Story M, French SA. Fast food for family meals: relationships with parent and adolescent food intake, home food availability and weight status. Public Health Nutr 2007; 10: 1623.
  • 54
    Crawford D, Ball K, Mishra G, Salmon J, Timperio A. Which food-related behaviours are associated with healthier intakes of fruits and vegetables among women? Public Health Nutr 2007; 10: 256265.
  • 55
    Dubowitz T, Heron M, Bird CE, Lurie N, Finch BK, Basurto-Davila R, Hale L, Escarce JJ. Neighborhood socioeconomic status and fruit and vegetable intake among whites, blacks, and Mexican Americans in the United States. Am J Clin Nutr 2008; 87: 18831891.
  • 56
    Fukuda Y, Nakamura K, Takano T. Accumulation of health risk behaviours is associated with lower socioeconomic status and women's urban residence: a multilevel analysis in Japan. BMC Public Health 2007; 5: 53.
  • 57
    Inglis V, Ball K, Crawford D. Socioeconomic variations in women's diets: what is the role of perceptions of the local food environment? J Epidemiol Community Health 2008; 62: 191197.
  • 58
    Jeffery RW, Baxter J, McGuire M, Linde J. Are fast food restaurants an environmental risk factor for obesity? Int J Behav Nutr Phys Act 2006; 3: 2.
  • 59
    Li F, Harmer P, Cardinal BJ, Bosworth M, Johnson-Shelton D. Obesity and the built environment: does the density of neighborhood fast-food outlets matter? Am J Health Promot 2009; 23: 203209.
  • 60
    Mehta NK, Chang VW. Weight status and restaurant availability a multilevel analysis. Am J Prev Med 2008; 34: 127133.
  • 61
    Mohr P, Wilson C, Dunn K, Brindal E, Wittert G. Personal and lifestyle characteristics predictive of the consumption of fast foods in Australia. Public Health Nutr 2007; 10: 14561463.
  • 62
    Moore LV, Diez Roux AV, Nettleton JA, Jacobs DR, Jr. Associations of the local food environment with diet quality – a comparison of assessments based on surveys and geographic information systems: the multi-ethnic study of atherosclerosis. Am J Epidemiol 2008; 167: 917924.
  • 63
    Morikawa Y, Miura K, Sasaki S, Yoshita K, Yoneyama S, Sakurai M, Ishizaki M, Kido T, Naruse Y, Suwazono Y, Higashiyama M, Nakagawa H. Evaluation of the effects of shift work on nutrient intake: a cross-sectional study. J Occup Health 2008; 50: 270278.
  • 64
    Simmons D, McKenzie A, Eaton S, Cox N, Khan MA, Shaw J, Zimmet P. Choice and availability of takeaway and restaurant food is not related to the prevalence of adult obesity in rural communities in Australia. Int J Obes 2005; 29: 703710.
  • 65
    Wang MC, Cubbin C, Ahn D, Winkleby MA. Changes in neighbourhood food store environment, food behaviour and body mass index, 1981–1990. Public Health Nutr 2008; 11: 963970.
  • 66
    Wang MC, Kim S, Gonzalez AA, MacLeod KE, Winkleby MA. Socioeconomic and food-related physical characteristics of the neighborhood environment are associated with body mass index. J Epidemiol Community Health 2007; 61: 491498.
  • 67
    Watters JL, Satia JA, Galanko JA. Associations of psychosocial factors with fruit and vegetable intake among African-Americans. Public Health Nutr 2007; 10: 701711.
  • 68
    Zenk SN, Schulz AJ, Hollis-Neely T, Campbell RT, Holmes N, Watkins G, Nwankwo R, Odoms-Young A. Fruit and vegetable intake in African Americans: income and store characteristics. Am J Prev Med 2005; 29: 19.