Obesity and the Built Environment: A Reappraisal

Examining Diabetes Status by the Social Determinants of Health Among Adults in Hawai'i

The social determinants of health (SDoH) influence health outcomes based on conditions from birth, growth, living, and age factors. Diabetes is a chronic condition, impacted by race, education, and income, which may lead to serious health consequences. In Hawai'i, approximately 11.2% of adults have been diagnosed with diabetes. The objective of this secondary cross-sectional study is to assess the relationship between the prevalence of diabetes and the social determinants of health among Hawai'i adults who participated in the Behavioral Risk Factor Surveillance System between 2018-2020. The prevalence of diabetes among adults was 11.0% (CI: 10.4-11.5%). Filipino, Japanese and Native Hawaiian adults had the highest prevalence of diabetes at 14.4% (CI: 12.7-16.2%), 14.2% (CI: 12.7-15.7%), and 13.2% (CI: 12.0-14.4%), respectively. Poverty level and education were significantly associated with diabetes status. Within employment categories, the adjusted odds ratio (AOR) for retired and unable to work adults were large at AOR: 1.51 (CI: 1.26-1.81) and AOR: 2.91 (CI: 2.28-3.72), respectively. SDoH can impact the development and management of diabetes. Understanding the role SDoH plays on diabetes status is crucial for promoting health equity, building community capacity, and improving diabetes management.

Residential Density Is Associated With BMI Trajectories in Children and Adolescents: Findings From the Moving to Health Study

Introduction

This study investigates the associations between built environment features and 3-year BMI trajectories in children and adolescents.

Methods

This retrospective cohort study utilized electronic health records of individuals aged 5-18 years living in King County, Washington, from 2005 to 2017. Built environment features such as residential density; counts of supermarkets, fast-food restaurants, and parks; and park area were measured using SmartMaps at 1,600-meter buffers. Linear mixed-effects models performed in 2022 tested whether built environment variables at baseline were associated with BMI change within age cohorts (5, 9, and 13 years), adjusting for sex, age, race/ethnicity, Medicaid, BMI, and residential property values (SES measure).

Results

At 3-year follow-up, higher residential density was associated with lower BMI increase for girls across all age cohorts and for boys in age cohorts of 5 and 13 years but not for the age cohort of 9 years. Presence of fast food was associated with higher BMI increase for boys in the age cohort of 5 years and for girls in the age cohort of 9 years. There were no significant associations between BMI change and counts of parks, and park area was only significantly associated with BMI change among boys in the age cohort of 5 years.

Conclusions

Higher residential density was associated with lower BMI increase in children and adolescents. The effect was small but may accumulate over the life course. Built environment factors have limited independent impact on 3-year BMI trajectories in children and adolescents.

The effect of discretionary snack consumption on overall energy intake, weight status, and diet quality: A systematic review

The consumption frequency and portion size of discretionary snacks are thought to contribute to a greater food intake and risk of overweight or obesity in the developed world but evidence from epidemiological studies is inconclusive. To investigate this, we systematically evaluated evidence on the effects of discretionary snack consumption on weight status, energy intake, and diet quality. Articles involving discretionary snacks reported against the outcome measures of any primary, peer-reviewed study using human participants from free-living conditions for all age groups were included. A total of 14,780 titles were identified and 40 eligible publications were identified. Three key outcomes were reported: weight status (n = 35), energy intake (n = 11), and diet quality (n = 3). Increased discretionary snack consumption may contribute modestly to energy intake, however, there is a lack of consistent associations with increased weight/BMI. Although cross-sectional analyses offered conflicting findings, longitudinal studies in adults showed a consistent positive relationship between discretionary snack intake and increasing weight or body mass index. Given that experimental findings suggest reducing the size of discretionary snacks could lead to decreased consumption and subsequent energy intake, food policy makers and manufacturers may find it valuable to consider altering the portion and/or packaging size of discretionary snacks.

Systematic review of best practices for GPS data usage, processing, and linkage in health, exposure science and environmental context research

Global Positioning System (GPS) technology is increasingly used in health research to capture individual mobility and contextual and environmental exposures. However, the tools, techniques and decisions for using GPS data vary from study to study, making comparisons and reproducibility challenging.

OBJECTIVES

The objectives of this systematic review were to (1) identify best practices for GPS data collection and processing; (2) quantify reporting of best practices in published studies; and (3) discuss examples found in reviewed manuscripts that future researchers may employ for reporting GPS data usage, processing and linkage of GPS data in health studies.

DESIGN

A systematic review.

DATA SOURCES

Electronic databases searched (24 October 2023) were PubMed, Scopus and Web of Science (PROSPERO ID: CRD42022322166).

ELIGIBILITY CRITERIA

Included peer-reviewed studies published in English met at least one of the criteria: (1) protocols involving GPS for exposure/context and human health research purposes and containing empirical data; (2) linkage of GPS data to other data intended for research on contextual influences on health; (3) associations between GPS-measured mobility or exposures and health; (4) derived variable methods using GPS data in health research; or (5) comparison of GPS tracking with other methods (eg, travel diary).

DATA EXTRACTION AND SYNTHESIS

We examined 157 manuscripts for reporting of best practices including wear time, sampling frequency, data validity, noise/signal loss and data linkage to assess risk of bias.

RESULTS

We found that 6% of the studies did not disclose the GPS device model used, only 12.1% reported the per cent of GPS data lost by signal loss, only 15.7% reported the per cent of GPS data considered to be noise and only 68.2% reported the inclusion criteria for their data.

CONCLUSIONS

Our recommendations for reporting on GPS usage, processing and linkage may be transferrable to other geospatial devices, with the hope of promoting transparency and reproducibility in this research.

PROSPERO REGISTRATION NUMBER

CRD42022322166.

Advancing application of satellite remote sensing technologies for linking atmospheric and built environment to health

Background

The intricate interplay between human well-being and the surrounding environment underscores contemporary discourse. Within this paradigm, comprehensive environmental monitoring holds the key to unraveling the intricate connections linking population health to environmental exposures. The advent of satellite remote sensing monitoring (SRSM) has revolutionized traditional monitoring constraints, particularly limited spatial coverage and resolution. This innovation finds profound utility in quantifying land covers and air pollution data, casting new light on epidemiological and geographical investigations. This dynamic application reveals the intricate web connecting public health, environmental pollution, and the built environment.

Objective

This comprehensive review navigates the evolving trajectory of SRSM technology, casting light on its role in addressing environmental and geographic health issues. The discussion hones in on how SRSM has recently magnified our understanding of the relationship between air pollutant exposure and population health. Additionally, this discourse delves into public health challenges stemming from shifts in urban morphology.

Methods

Utilizing the strategic keywords "SRSM," "air pollutant health risk," and "built environment," an exhaustive search unfolded across prestigious databases including the China National Knowledge Network (CNKI), PubMed and Web of Science. The Citespace tool further unveiled interconnections among resultant articles and research trends.

Results

Synthesizing insights from a myriad of articles spanning 1988 to 2023, our findings unveil how SRMS bridges gaps in ground-based monitoring through continuous spatial observations, empowering global air quality surveillance. High-resolution SRSM advances data precision, capturing multiple built environment impact factors. Its application to epidemiological health exposure holds promise as a pioneering tool for contemporary health research.

Conclusion

This review underscores SRSM's pivotal role in enriching geographic health studies, particularly in atmospheric pollution domains. The study illuminates how SRSM overcomes spatial resolution and data loss hurdles, enriching environmental monitoring tools and datasets. The path forward envisions the integration of cutting-edge remote sensing technologies, novel explorations of urban-public health associations, and an enriched assessment of built environment characteristics on public well-being.

Association of census-tract level gentrification and income inequality with 6-year incidence of metabolic syndrome in the Hispanic Community Health Study/Study of Latinos, an epidemiologic cohort study

BACKGROUND

Metabolic syndrome varies by socio-demographic characteristics, with younger (18-29 years) and older (50-69 years) Hispanic/Latino having higher prevalence compared to other groups. While there is substantial research on neighborhood influences on cardiometabolic health, there are mixed findings regarding the effects of gentrification and few studies have included Hispanic/Latinos. The role of neighborhood income inequality on metabolic health remains poorly understood.

OBJECTIVES

Examined associations of neighborhood gentrification and income inequality with metabolic syndrome (MetSyn) using data from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL).

DESIGN, SETTING AND PARTICIPANTS

The HCHS/SOL is a community-based cohort of adults of Hispanic/Latinos (aged 18-74). Analyses included 6710 adults who did not meet criteria for MetsS at baseline (2008-2011) and completed the visit 2 examination (2014-2017). Poisson regressions estimated odds ratios (IRR) and 95% confidence intervals (CI) for neighborhood gentrification and change in income inequality with MetSyn incidence.

MAIN OUTCOME AND EXPOSURE MEASURES

Gentrification was measured with an index that included changes (2000 to 2006-2010) in education, poverty, and income. Change in neighborhood income inequality (2005-2009 to 2012-2016) was measured using the Gini coefficient of income distribution. MetSyn was defined using National Cholesterol Education Program Adult Treatment Panel III criteria.

RESULTS

Among 6647 Hispanic/Latino adults, 23% (N = 1530) had incident MetSyn. In models adjusted for socio-demographic, health insurance status, and neighborhood characteristics, gentrification (IRR, 1.00, 95%CI, 0.96-1.03) and income inequality change (IRR, 1.00, 95%CI, 0.99-1.00) were not associated with MetSyn at visit 2. There was no association between cross-sectional income inequality (2005-2009) and MetSyn at visit 2 (IRR, 0.97, 95%CI, 0.82-1.15).

CONCLUSION

Neighborhood gentrification and income inequality change were not associated with incidence of MetSyn over 6 years among Hispanic/Latino adults. This study demonstrated that income-based residential changes alone may not be sufficient to explain neighborhood influences on health outcomes among this population.

A geospatial analysis of cardiometabolic diseases and their risk factors considering environmental features in a midsized city in Argentina

New approaches to the study of cardiometabolic disease (CMD) distribution include analysis of built environment (BE), with spatial tools as suitable instruments. We aimed to characterize the spatial dissemination of CMD and the associated risk factors considering the BE for people attending the Non-Invasive Cardiology Service of Hospital Nacional de Clinicas in Córdoba City, Argentina during the period 2015-2020. We carried out an observational, descriptive, cross-sectional study performing non-probabilistic convenience sampling. The final sample included 345 people of both sexes older than 35 years. The CMD data were collected from medical records and validated techniques and BE information was extracted from Landsat-8 satellite products. A geographic information system (GIS) was constructed to assess the distribution of CMD and its risk factors in the area. Out of the people sampled, 41% showed the full metabolic syndrome and 22.6% only type-2 diabetes mellitus (DM2), a cluster of which was evidenced in north-western Córdoba. The risk of DM2 showed an association with high values of the normalized difference vegetation index (NDVI) (OR= 0.81; 95% CI: - 0.30 to 1.66; p=0.05) and low normalized difference built index (NDBI) values that reduced the probability of occurrence of DM2 (OR= -1.39; 95% CI: -2.62 to -0.17; p=0.03). Considering that the results were found to be linked to the environmental indexes, the study of BE should include investigation of physical space as a fundamental part of the context in which people develop medically within society. The novel collection of satellite-generated information on BE proved efficient.

Diet composition and energy intake in humans

Absolute energy from fats and carbohydrates and the proportion of carbohydrates in the food supply have increased over 50 years. Dietary energy density (ED) is primarily decreased by the water and increased by the fat content of foods. Protein, carbohydrates and fat exert different effects on satiety or energy intake (EI) in the order protein > carbohydrates > fat. When the ED of different foods is equalized the differences between fat and carbohydrates are modest. Covertly increasing dietary ED with fat, carbohydrate or mixed macronutrients elevates EI, producing weight gain and vice versa. In more naturalistic situations where learning cues are intact, there appears to be greater compensation for the different ED of foods. There is considerable individual variability in response. Macronutrient-specific negative feedback models of EI regulation have limited capacity to explain how availability of cheap, highly palatable, readily assimilated, energy-dense foods lead to obesity in modern environments. Neuropsychological constructs including food reward (liking, wanting and learning), reactive and reflective decision making, in the context of asymmetric energy balance regulation, give more comprehensive explanations of how environmental superabundance of foods containing mixtures of readily assimilated fats and carbohydrates and caloric beverages elevate EI through combined hedonic, affective, cognitive and physiological mechanisms. This article is part of a discussion meeting issue 'Causes of obesity: theories, conjectures and evidence (Part II)'.

Neighborhood Built Environment and Sleep Health: A Longitudinal Study in Low-Income and Predominantly African-American Neighborhoods

In the present study, we examined the associations between physical characteristics of neighborhoods and sleep health outcomes and assessed the mediating role of physical activity in these associations. A longitudinal study (the Pittsburgh Hill/Homewood Research on Eating, Shopping, and Health (PHRESH) Zzz Study; n = 1,051) was conducted in 2 low-income, predominately African-American neighborhoods in Pittsburgh, Pennsylvania, with repeated measures of neighborhood characteristics and sleep health outcomes from 2013 to 2018. Built environment measures of walkability, urban design, and neighborhood disorder were captured from systematic field observations. Sleep health outcomes included insufficient sleep, sleep duration, wakefulness after sleep onset, and sleep efficiency measured from 7-day actigraphy data. G-computations based on structural nested mean models were used to examine the total effects of each built environment feature, and causal mediation analyses were used to evaluate direct and indirect effects operating through physical activity. Urban design features were associated with decreased wakefulness after sleep onset (risk difference (RD) = -1.26, 95% confidence interval (CI): -4.31, -0.33). Neighborhood disorder (RD = -0.46, 95% CI: -0.86, -0.07) and crime rate (RD = -0.54, 95% CI: -0.93, -0.08) were negatively associated with sleep efficiency. Neighborhood walkability was not associated with sleep outcomes. We did not find a strong and consistent mediating role of physical activity. Interventions to improve sleep should target modifiable factors, including urban design and neighborhood disorder.

Social determinants of health, health disparities, and adiposity

Social determinants of health (SDoH), or the socioeconomic, environmental, and psychosocial conditions in which individuals spend their daily lives, substantially influence obesity as a cardiovascular disease (CVD) risk factor. The coronavirus disease 2019 (COVID-19) pandemic highlighted the converging epidemics of obesity, CVD, and social inequities globally. Obesity and CVD serve as independent risk factors for COVID-19 severity and lower-resourced populations most impacted by adverse SDoH have the highest COVID-19 mortality rates. Better understanding the interplay between social and biologic factors that contribute to obesity-related CVD disparities are important to equitably address obesity across populations. Despite efforts to investigate SDoH and their biologic effects as drivers of health disparities, the connections between SDoH and obesity remain incompletely understood. This review aims to highlight the relationships between socioeconomic, environmental, and psychosocial factors and obesity. We also present potential biologic factors that may play a role in the biology of adversity, or link SDoH to adiposity and poor adipo-cardiology outcomes. Finally, we provide evidence for multi-level obesity interventions targeting multiple aspects of SDoH. Throughout, we emphasize areas for future research to tailor health equity-promoting interventions across populations to reduce obesity and obesity-related CVD disparities.

Evoked sensory stimulation of the eating environment, impacts feeling of presence and food desires in an online environment

Online food choices are often made outside a regular food environment and suffer from sensory deprivation. The present study investigated if evoked multi-sensory stimulation can drive context specific food desires in an online environment. In a randomised between subject design, participants expressed their food desire on a visual analogue scale and feeling of presence (e.g., did you feel present on a beach) on a Likert scale, whilst looking online at a picture and reading a neutral description of a sensory laboratory (control condition), looking at a photo of a beach and reading a neutral description (beach condition), or looking at a photo of a beach and reading a sensory based description (beach + ). Participants (n = 725 participants, 622 females) who saw the beach photo increased their desire for cold, but not neutral foods (p < 0.05), those who were exposed to the sensory description in addition to the photo showed a higher desire for cold foods compared to those who just saw the beach photo (p < 0.001). These effects were modulated by an increased feeling of presence and how often participants visited the beach. Participants with a higher feeling of presence showed a higher desire for cold foods (p < 0.05). Food desires of those who visited the beach often were more impacted by the evoked sensory stimulation than food desires of those who visited the beach rarely. Food desires created in an online environment can be influenced by visual, and text based evoked sensory stimulation as long as consumers' feeling of presence in is high. The results can inform public health professionals how to impact healthy food choices in an online environment.

The CIVISANO protocol: a mixed-method study about the role of objective and perceived environmental factors on physical activity and eating behavior among socioeconomically disadvantaged adults

BACKGROUND

Overweight and obesity have a strong socioeconomic profile. Unhealthy behaviors like insufficient physical activity and an unbalanced diet, which are causal factors of overweight and obesity, tend to be more pronounced in socioeconomically disadvantaged groups in high income countries. The CIVISANO project aims to identify objective and perceived environmental factors among different socioeconomic population groups that impede or facilitate physical activity and healthy eating behavior in the local context of two peri-urban Flemish municipalities in Belgium. We also aim to identify and discuss possible local interventions and evaluate the participatory processes of the project.

METHODS

This study (2020-2023) will use community-based participatory tools, involving collaborative partnerships with civic and stakeholder members of the community and regular exchanges among all partners to bridge knowledge development and health promotion for socioeconomically disadvantaged citizens. Furthermore, a mixed-methods approach will be used. A population survey and geographic analysis will explore potential associations between the physical activity and eating behaviors of socioeconomically disadvantaged adults (25-65 years old) and both their perceived and objective physical, food and social environments. Profound perceptive context information will be gathered from socioeconomically disadvantaged adults by using participatory methods like photovoice, walk-along, individual map creation and group model building. An evaluation of the participatory process will be conducted simultaneously.

DISCUSSION

The CIVISANO project will identify factors in the local environment that might provoke inequities in adopting a healthy lifestyle. The combination of perceived and objective measures using validated strategies will provide a robust assessment of the municipality environment. Through this analysis, the project will investigate to what extent community engagement can be a useful strategy to reduce health inequities. The strong knowledge exchange and capacity-building in a local setting is expected to contribute to our understanding of how to maximize research impact in this field and generate evidence about potential linkages between a health enhancing lifestyle among socioeconomically disadvantaged groups and their physical, food and social environments.

The link between gentrification, children's egocentric food environment, and obesity

While advocates argue that gentrification changes the neighborhood food environment critical to children's diet and health, we have little evidence documenting such changes or the consequences for their health outcomes. Using rich longitudinal, individual-level data on nearly 115,000 New York City children, including egocentric measures of their food environment and BMI, we examine the link between neighborhood demographic change ("gentrification"), children's access to restaurants and supermarkets, and their weight outcomes. We find that children in rapidly gentrifying neighborhoods see increased access to fast food and wait-service restaurants and reduced access to corner stores and supermarkets compared to those in non-gentrifying areas. Boys and girls have higher BMI following gentrification, but only boys are more likely to be obese or overweight. We find public housing moderates the relationship between gentrification and weight, as children living in public housing are less likely to be obese or overweight.

Barriers to Creating Healthier Home Food Environments: Process Evaluation Results From 2 Home Food Environment Intervention Studies

Few studies have identified barriers to creating a home environment more supportive of healthy eating. We examined barriers faced by participants in a randomized controlled trial and an adaptation study of the Healthy Homes/Healthy Families intervention, which uses health coaches to support low-income families in creating healthier home food environments. Coaches maintained logs of participant interactions as part of a process evaluation. We thematically analyzed logs from interactions with participants, mostly lower-income African American women (n = 114), to identify barriers for each of 8 healthy actions that serve as core elements of the intervention. Difficulty of changing current habits was a barrier for 5 of the healthy actions. No time/convenience and limited family support each influenced 2 of the healthy actions, with interpersonal barriers also stemming from social situations and visitors, including grandchildren. Cost and economic challenges were barriers for 3 of the actions. Hunger, cravings, and limited access to resources (eg, transportation, fresh fruits and vegetables) were each noted as barriers for 1 healthy action. Overall, these findings provide insight for how to better support families who are trying to improve their home food environments and highlight the need for multilevel interventions.

The neighbourhood built environment and health-related fitness: a narrative systematic review

Background

There is increasing evidence demonstrating the importance of the neighbourhood built environment in supporting physical activity. Physical activity provides numerous health benefits including improvements in health-related fitness (i.e., muscular, cardiorespiratory, motor, and morphological fitness). Emerging evidence also suggests that the neighbourhood built environment is associated with health-related fitness. Our aim was to summarize evidence on the associations between the neighbourhood built environment and components of health-related fitness in adults.

Methods

We undertook a systematic review following PRISMA guidelines. Our data sources included electronic searches in MEDLINE, Embase, CINAHL, Web of Science, SPORTDiscus, Environment Complete, ProQuest Dissertations and Theses, and Transport Research International Documentation from inception to March 2021. Our eligibility criteria consisted of observational and experimental studies estimating associations between the neighbourhood built environment and health-related fitness among healthy adults (age ≥ 18 years). Eligible studies included objective or self-reported measures of the neighbourhood built environment and included either objective or self-reported measures of health-related fitness. Data extraction included study design, sample characteristics, measured neighbourhood built environment characteristics, and measured components of health-related fitness. We used individual Joanna Briggs Institute study checklists based on identified study designs. Our primary outcome measure was components of health-related fitness (muscular; cardiorespiratory; motor, and morphological fitness).

Results

Twenty-seven studies (sample sizes = 28 to 419,562; 2002 to 2020) met the eligibility criteria. Neighbourhood destinations were the most consistent built environment correlate across all components of health-related fitness. The greatest number of significant associations was found between the neighbourhood built environment and morphological fitness while the lowest number of associations was found for motor fitness. The neighbourhood built environment was consistently associated with health-related fitness in studies that adjusted for physical activity.

Conclusion

The neighbourhood built environment is associated with health-related fitness in adults and these associations may be independent of physical activity. Longitudinal studies that adjust for physical activity (including resistance training) and sedentary behaviour, and residential self-selection are needed to obtain rigorous causal evidence for the link between the neighbourhood built environment and health-related fitness.

Trial registration

Protocol registration: PROSPERO number CRD42020179807.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12966-022-01359-0.

Associations of four indexes of social determinants of health and two community typologies with new onset type 2 diabetes across a diverse geography in Pennsylvania

Evaluation of geographic disparities in type 2 diabetes (T2D) onset requires multidimensional approaches at a relevant spatial scale to characterize community types and features that could influence this health outcome. Using Geisinger electronic health records (2008–2016), we conducted a nested case-control study of new onset T2D in a 37-county area of Pennsylvania. The study included 15,888 incident T2D cases and 79,435 controls without diabetes, frequency-matched 1:5 on age, sex, and year of diagnosis or encounter. We characterized patients’ residential census tracts by four dimensions of social determinants of health (SDOH) and into a 7-category SDOH census tract typology previously generated for the entire United States by dimension reduction techniques. Finally, because the SDOH census tract typology classified 83% of the study region’s census tracts into two heterogeneous categories, termed rural affordable-like and suburban affluent-like, to further delineate geographies relevant to T2D, we subdivided these two typology categories by administrative community types (U.S. Census Bureau minor civil divisions of township, borough, city). We used generalized estimating equations to examine associations of 1) four SDOH indexes, 2) SDOH census tract typology, and 3) modified typology, with odds of new onset T2D, controlling for individual-level confounding variables. Two SDOH dimensions, higher socioeconomic advantage and higher mobility (tracts with fewer seniors and disabled adults) were independently associated with lower odds of T2D. Compared to rural affordable-like as the reference group, residence in tracts categorized as extreme poverty (odds ratio [95% confidence interval] = 1.11 [1.02, 1.21]) or multilingual working (1.07 [1.03, 1.23]) were associated with higher odds of new onset T2D. Suburban affluent-like was associated with lower odds of T2D (0.92 [0.87, 0.97]). With the modified typology, the strongest association (1.37 [1.15, 1.63]) was observed in cities in the suburban affluent-like category (vs. rural affordable-like–township), followed by cities in the rural affordable-like category (1.20 [1.05, 1.36]). We conclude that in evaluating geographic disparities in T2D onset, it is beneficial to conduct simultaneous evaluation of SDOH in multiple dimensions. Associations with the modified typology showed the importance of incorporating governmentally, behaviorally, and experientially relevant community definitions when evaluating geographic health disparities.

Differences in Weight Gain Following Residential Relocation in the Moving to Health (M2H) Study

BACKGROUND

Neighborhoods may play an important role in shaping long-term weight trajectory and obesity risk. Studying the impact of moving to another neighborhood may be the most efficient way to determine the impact of the built environment on health. We explored whether residential moves were associated with changes in body weight.

METHODS

Kaiser Permanente Washington electronic health records were used to identify 21,502 members aged 18-64 who moved within King County, WA between 2005 and 2017. We linked body weight measures to environment measures, including population, residential, and street intersection densities (800 m and 1,600 m Euclidian buffers) and access to supermarkets and fast foods (1,600 m and 5,000 m network distances). We used linear mixed models to estimate associations between postmove changes in environment and changes in body weight.

RESULTS

In general, moving from high-density to moderate- or low-density neighborhoods was associated with greater weight gain postmove. For example, those moving from high to low residential density neighborhoods (within 1,600 m) gained an average of 4.5 (95% confidence interval [CI] = 3.0, 5.9) lbs 3 years after moving, whereas those moving from low to high-density neighborhoods gained an average of 1.3 (95% CI = -0.2, 2.9) lbs. Also, those moving from neighborhoods without fast-food access (within 1600m) to other neighborhoods without fast-food access gained less weight (average 1.6 lbs [95% CI = 0.9, 2.4]) than those moving from and to neighborhoods with fast-food access (average 2.8 lbs [95% CI = 2.5, 3.2]).

CONCLUSIONS

Moving to higher-density neighborhoods may be associated with reductions in adult weight gain.

Associations between neighborhood built environment, residential property values, and adult BMI change: The Seattle Obesity Study III

Objective

To examine associations between neighborhood built environment (BE) variables, residential property values, and longitudinal 1- and 2-year changes in body mass index (BMI).

Methods

The Seattle Obesity Study III was a prospective cohort study of adults with geocoded residential addresses, conducted in King, Pierce, and Yakima Counties in Washington State. Measured heights and weights were obtained at baseline (n = 879), year 1 (n = 727), and year 2 (n = 679). Tax parcel residential property values served as proxies for individual socioeconomic status. Residential unit and road intersection density were captured using Euclidean-based SmartMaps at 800 m buffers. Counts of supermarket (0 versus. 1+) and fast-food restaurant availability (0, 1–3, 4+) were measured using network based SmartMaps at 1600 m buffers. Density measures and residential property values were categorized into tertiles. Linear mixed-effects models tested whether baseline BE variables and property values were associated with differential changes in BMI at year 1 or year 2, adjusting for age, gender, race/ethnicity, education, home ownership, and county of residence. These associations were then tested for potential disparities by age group, gender, race/ethnicity, and education.

Results

Road intersection density, access to food sources, and residential property values were inversely associated with BMI at baseline. At year 1, participants in the 3rd tertile of density metrics and with 4+ fast-food restaurants nearby showed less BMI gain compared to those in the 1st tertile or with 0 restaurants. At year 2, higher residential property values were predictive of lower BMI gain. There was evidence of differential associations by age group, gender, and education but not race/ethnicity.

Conclusion

Inverse associations between BE metrics and residential property values at baseline demonstrated mixed associations with 1- and 2-year BMI change. More work is needed to understand how individual-level sociodemographic factors moderate associations between the BE, property values, and BMI change.

•

Strong, inverse cross-sectional relationships between the built environment, residential property values (a proxy for individual socioeconomic status), and measured BMI were observed.

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Measures of the built environment and residential property values showed modest and inconsistent associations with 1- and 2-year BMI change.

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There was suggestive evidence that age may moderate the association between urban density and 1- and 2-year BMI change while education may moderate the association between residential property values and 2-year BMI change.

Benchmarking the driver acceleration impact on vehicle energy consumption and CO2 emissions

The study proposes a methodology for quantifying the impact of real-world heterogeneous driving behavior on vehicle energy consumption, linking instantaneous acceleration heterogeneity and CO₂ emissions. Data recorded from 20 different drivers under real driving are benchmarked against the Worldwide Harmonized Light Vehicle Test Cycle (WLTC), first by correlating the speed cycle with individual driver behavior and then by quantifying the CO₂ emissions and consumption. The vehicle-Independent Driving Style metric (IDS) is used to quantify acceleration dynamicity, introducing driving style stochasticity by means of probability distribution functions. Results show that the WLTC cycle assumes a relatively smooth acceleration style compared to the observed ones. The method successfully associates acceleration dynamicity to CO₂ emissions. We observe a 5% difference in the CO₂ emissions between the most favourable and the least favourable case. The intra-driver variance reached 3%, while the inter-driver variance is below 2%. The approach can be used for quantifying the driving style induced emissions divergence.

Using aggregated mobile phone location data to compare the realised foodscapes of different socio-economic groups

The foodscape (the built food environment) is considered one of the driving factors of the higher burden of obesity and chronic disease observed in low socio-economic status (SES) groups. Traditional data collection methods struggle to accurately capture actual access and exposure to the foodscape (realised foodscape). We assess the use of anonymised mobile phone location data (location data) in foodscape studies by applying them to a case study in Perth, Western Australia to test the hypothesis that lower SES groups have poorer realised foodscapes than high SES groups. Kernel density estimation was used to calculate realised foodscapes of different SES groups and home foodscape typologies, which were compared to home foodscapes of the different groups. The location data enabled us to measure realised foodscapes of multiple groups over an extended period and at the city scale. Low SES groups had poor availability of food outlets, including unhealthy outlets, in their home and realised foodscapes and may be more susceptible to a poor home foodscape because of low mobility.

Environments and situations as correlates of eating and drinking among women living with obesity and urban poverty

Objective

One path to improving weight management may be to lessen the self-control burden of physical activity and healthier food choices. Opportunities to lessen the self-control burden might be uncovered by assessing the spatiotemporal experiences of individuals in daily context. This report aims to describe the time, place, and social context of eating and drinking and 6-month weight change among 209 midlife women (n = 113 African-American) with obesity receiving safety-net primary care.

Methods

Participants completed baseline and 6-month weight measures, observations and interviews regarding obesogenic cues in the home environment, and up to 12 ecological momentary assessments (EMA) per day for 30 days inquiring about location, social context, and eating and drinking.

Results

Home was the most common location (62%) at times of EMA notifications. Participants reported "yes" to eating or drinking at the time of nearly one in three (31.1% ± 13.2%) EMA notifications. Regarding social situations, being alone was significantly associated with less frequent eating and drinking (OR = 0.75) unless at work in which case being alone was significantly associated with a greater frequency of eating or drinking (OR = 1.43). At work, eating was most common late at night, whereas at home eating was most frequent in the afternoon and evening hours. However, eating and drinking frequency was not associated with 6-month weight change.

Conclusions

Home and work locations, time of day, and whether alone may be important dimensions to consider in the pursuit of more effective weight loss interventions. Opportunities to personalize weight management interventions, whether digital or human, and lessen in-the-moment self-control burden might lie in identifying times and locations most associated with caloric consumption.

Clinical trial registration: NCT03083964 in clinicaltrials.gov.

Environmental risk factors of type 2 diabetes-an exposome approach

Type 2 diabetes is one of the major chronic diseases accounting for a substantial proportion of disease burden in Western countries. The majority of the burden of type 2 diabetes is attributed to environmental risks and modifiable risk factors such as lifestyle. The environment we live in, and changes to it, can thus contribute substantially to the prevention of type 2 diabetes at a population level. The 'exposome' represents the (measurable) totality of environmental, i.e. nongenetic, drivers of health and disease. The external exposome comprises aspects of the built environment, the social environment, the physico-chemical environment and the lifestyle/food environment. The internal exposome comprises measurements at the epigenetic, transcript, proteome, microbiome or metabolome level to study either the exposures directly, the imprints these exposures leave in the biological system, the potential of the body to combat environmental insults and/or the biology itself. In this review, we describe the evidence for environmental risk factors of type 2 diabetes, focusing on both the general external exposome and imprints of this on the internal exposome. Studies provided established associations of air pollution, residential noise and area-level socioeconomic deprivation with an increased risk of type 2 diabetes, while neighbourhood walkability and green space are consistently associated with a reduced risk of type 2 diabetes. There is little or inconsistent evidence on the contribution of the food environment, other aspects of the social environment and outdoor temperature. These environmental factors are thought to affect type 2 diabetes risk mainly through mechanisms incorporating lifestyle factors such as physical activity or diet, the microbiome, inflammation or chronic stress. To further assess causality of these associations, future studies should focus on investigating the longitudinal effects of our environment (and changes to it) in relation to type 2 diabetes risk and whether these associations are explained by these proposed mechanisms.

Food Acquisition Practices, Body Mass Index, and Dietary Outcomes by Level of Rurality

PURPOSE

Rural residents are more likely to be obese than urban residents. Research on how people navigate their local food environments through food acquisition behaviors, such as food shopping and restaurant use, in different types of communities may help to create a deeper understanding of the multilevel determinants of obesity.

METHODS

Data are from a national sample of US adults ages 18-75. Respondents were recruited from an online survey panel in 2015 and asked about food shopping, restaurant use, diet and weight (N = 3,883). Comparisons were made by level of rurality as assessed by Rural-Urban Continuum Codes (RUCC) and self-reported rurality of the area around their home.

FINDINGS

Food acquisition behaviors varied minimally by RUCC-defined level of rurality, with the exceptions of type and distance to primary food store. Rural residents drove further and were more likely to shop at small grocery stores and supercenters than were residents of semiurban or urban counties. In contrast, all of the food acquisition behaviors varied by self-reported rurality of residential areas. Respondents living in rural areas shopped for groceries less frequently, drove further, more commonly shopped at small grocery stores and supercenters, and used restaurants less frequently. In multivariable analyses, rural, small town, and suburban areas were each significantly associated with BMI and fruit and vegetable intake, but not percent energy from fat.

CONCLUSION

Findings show that self-reported rurality of residential area is associated with food acquisition behaviors and may partly explain rural-urban differences in obesity and diet quality.

Sociodemographic disparities and contextual factors in obesity: updated evidence from a National Survey of Risk Factors for Chronic Diseases

OBJECTIVE

To assess the association of sociodemographic and environmental factors with the obesity occurrence in Argentina from a sex- and age-comparative perspective and a multilevel approach.

DESIGN

Cross-sectional study based on secondary data from the National Survey of Chronic Diseases Risk Factors (CDRF) 2018, Argentina. Two-level logistic regression models stratified by sex and age were used.

SETTING

The nationwide probabilistic sample of the CDRF survey and twenty-four geographical units.

PARTICIPANTS

16 410 adult people, living in Argentine towns of at least 5000 people, nested into 24 geographical units. Sex and age groups were defined as young (aged 18-44 years), middle-aged (45-64 years) and older (65 years and older) men and women.

RESULTS

Single men (all age groups) and divorced/widowed men (aged 45 years or older) had a lower obesity risk compared to married ones. In the middle-aged group, men with higher education showed a lower risk than men with incomplete primary education. In young women, a marked social gradient by educational level was observed. A low-income level coupled with highly urbanised contexts represents an unfavourable scenario for young and middle-aged women. Having a multi-person household was a risk factor for obesity (OR = 1·26, P = 0·038) in middle-aged women. Contextual factors linked to the availability of socially constructed recreational resources and green spaces were associated with obesity among young adults.

CONCLUSIONS

Socio-environmental determinants of obesity seem to operate differently according to sex and age in Argentina. This entails the need to address the obesity epidemic considering gender inequalities and the socio-environmental context at each stage of life.

Quantifying the Food and Physical Activity Environments in Rural, High Obesity Communities

The built environment contributes to an individual’s health, and rural geographies face unique challenges for healthy eating and active living. The purpose of this descriptive study was to assess the nutrition and physical activity environments in rural communities with high obesity prevalence. One community within each of six high obesity prevalence counties in a rural Midwest state completed the Nutrition Environment Measures Survey for Stores (NEMS-S) and the Rural Active Living Assessment (RALA). Data were collected by trained community members and study staff. All communities had at least one grocery store and five had at least one convenience store. Grocery stores had higher mean total NEMS-S scores than convenience stores (26.6 vs. 6.0, p < 0.001), and higher scores for availability (18.7 vs. 5.3, p < 0.001) and quality (5.4 vs. 0, p < 0.001) of healthful foods (higher scores are preferable). The mean RALA town-wide assessment score across communities was 56.5 + 15.6 out of a possible 100 points. The mean RALA program and policy assessment score was 40.8 + 20.4 out of a possible 100 points. While grocery stores and schools are important for enhancing food and physical environments in rural areas, many opportunities exist for improvements to impact behaviors and address obesity.

Obesity-Related Metabolic Dysfunction in Dairy Cows and Horses: Comparison to Human Metabolic Syndrome

Obesity has become a serious health problem with frequent occurrence both in human and animal populations. It is estimated that it may affect over 85% of the human population and 70–80% of horses and cows by 2030. Fat cow syndrome (FCS) is a combination of metabolic, digestive, infectious, and reproductive disorders that affects obese periparturient dairy cows, and occurs most frequently in loose-housing systems, where periparturient and dry cows are fed and managed in one group disregarding the lactation stages. Equine metabolic syndrome (EMS) was named after human metabolic syndrome (MetS) and has insulin dysregulation as a central and consistent feature. It is often associated with obesity, although EMS may occur in a lean phenotype as well. Other inconsistent features of EMS are cardiovascular changes and adipose dysregulation. Laminitis is the main clinical consequence of EMS. MetS holds a 30-years old lead in research and represents a clustering of risk factors that comprise abdominal obesity, dyslipidemia, hypertension, and hyperglycemia (impaired fasting glucose or type 2 diabetes mellitus—T2DM), which are associated with doubled atherosclerotic cardiovascular disease risk, and a 5-fold increased risk for T2DM. The main aim of this review is to provide critical information for better understanding of the underlying mechanisms of obesity-related metabolic dysfunction in animals, especially in cows and horses, in comparison with MetS. Human medicine studies can offer suitable candidate mechanisms to fill the existing gap in the literature, which might be indispensable for owners to tackle FCS, EMS, and their consequences.

Differential associations of the built environment on weight gain by sex and race/ethnicity but not age

OBJECTIVE

To explore the built environment (BE) and weight change relationship by age, sex, and racial/ethnic subgroups in adults.

METHODS

Weight trajectories were estimated using electronic health records for 115,260 insured Kaiser Permanente Washington members age 18-64 years. Member home addresses were geocoded using ArcGIS. Population, residential, and road intersection densities and counts of area supermarkets and fast food restaurants were measured with SmartMaps (800 and 5000-meter buffers) and categorized into tertiles. Linear mixed-effect models tested whether associations between BE features and weight gain at 1, 3, and 5 years differed by age, sex, and race/ethnicity, adjusting for demographics, baseline weight, and residential property values.

RESULTS

Denser urban form and greater availability of supermarkets and fast food restaurants were associated with differential weight change across sex and race/ethnicity. At 5 years, the mean difference in weight change comparing the 3rd versus 1st tertile of residential density was significantly different between males (-0.49 kg, 95% CI: -0.68, -0.30) and females (-0.17 kg, 95% CI: -0.33, -0.01) (P-value for interaction = 0.011). Across race/ethnicity, the mean difference in weight change at 5 years for residential density was significantly different among non-Hispanic (NH) Whites (-0.47 kg, 95% CI: -0.61, -0.32), NH Blacks (-0.86 kg, 95% CI: -1.37, -0.36), Hispanics (0.10 kg, 95% CI: -0.46, 0.65), and NH Asians (0.44 kg, 95% CI: 0.10, 0.78) (P-value for interaction <0.001). These findings were consistent for other BE measures.

CONCLUSION

The relationship between the built environment and weight change differs across demographic groups. Careful consideration of demographic differences in associations of BE and weight trajectories is warranted for investigating etiological mechanisms and guiding intervention development.

How active can preschoolers be at home? Parents' and grandparents' perceptions of children's day-to-day activity, with implications for physical activity policy

BACKGROUND

The importance of physical activity in early childhood for establishing long-term health is well understood, yet with the exception of recent WHO guidelines, public health initiatives rarely focus on children below school age. Moreover, little is known about how domestic spaces and day-to-day caring activities influence preschool-age children's physical activity. To examine this, we explore caregivers' perceptions of young children's activities within and outside the home, and we consider how lived experiences of caregiving align (or not) with current physical activity policy.

METHODS

Semi-structured interviews with 49 parents and grandparents from 16 families were conducted in Oregon, USA; each family had a child aged 3-5 years. Questions focused on caregivers' perceptions of and involvement with children's body weights, activities, and food practices. The interviews were analysed using thematic analysis. Our analysis drew on a materialities framework, attending to relationships between children, caregivers, spaces in and around the home, and everyday activities.

RESULTS

Four themes were developed: appropriateness of outside versus inside spaces for physical activity; making accommodations for physical activity in the home; active spaces of care, referring to relationships among space, activity type, and caregiver attention; and mundane movement, or the low-intensity movement of everyday life. Together, the results highlight that children's day-to-day activities cut across a spectrum of movement, mediated by available spaces and caregiving affordances.

CONCLUSIONS

Attending to the full spectrum of children's movements highlights how children's activities interlink with family routines, available indoor and outdoor spaces, and the intended uses of these spaces. These interplays between space, care, and physical activity enacted at the household level should inform an integrated, systems-level public health approach to increasing health and well-being for preschool-age children. Suggestions for improvement include coordinating policy development across multiple fields (e.g., housing design, urban planning) that structure the activities of children and their caregivers across 'home' and 'outside' spaces.

More Frequent Food Shopping May Promote Fruit and Vegetable Intake: A Systematic Review

BACKGROUND

Food shopping frequency may be an important modifiable factor related to increasing fruit and vegetable (FV) intake. Because of mixed findings of individual studies of shopping frequency, a systematic review is needed to examine findings across studies and store types.

OBJECTIVE

To conduct a systematic review of articles examining the relationship between frequency of food shopping and FV intake including examination of participation in federal nutrition assistance programs on FV intake, if reported.

METHODS

A search, guided by the Preferred Reported Items for Systematic Reviews and Metanalyses, using terms related to FV consumption and food shopping across 4 online databases, was conducted. Studies conducted in the US and published through October, 2020, included adults, and had a cross-sectional, longitudinal, cohort, or randomized study design were eligible for inclusion.

RESULTS

Twenty-four articles were included. The majority of studies found at least 1 positive finding between the frequency of food shopping and FV intake, indicating that as the frequency of food shopping increased, FV intake increased. In studies with 100% participation in government/federal nutrition assistance programs, participation was associated with FV intake. Studies that included participation as a subset found participation not associated with FV intake.

IMPLICATIONS FOR FUTURE RESEARCH AND PRACTICE

The frequency of shopping may be modifiable to increase FV intake. Experimental research is needed to test the directionality and causality of the relationship. Federal nutrition assistance programs may be a logical place to test the relationship through the adjustment of fund disbursements.

From the clinic to the community: Can health system data accurately estimate population obesity prevalence?

OBJECTIVE

Health system data were assessed for how well they can estimate obesity prevalence in census tracts.

METHODS

Clinical visit data were available from two large health systems (Kaiser Permanente Washington and University of Washington Medicine) in King County, Washington, as were census tract-level obesity prevalence estimates from the Behavioral Risk Factor Surveillance System (BRFSS). The health system data were geocoded to identify each patient's tract of residence, and the cross-sectional concordance between census tract-level obesity prevalence estimates computed from the two health systems in 2005 to 2006 and the concordance between University of Washington Medicine and BRFSS from 2012 to 2016 were assessed.

RESULTS

The spatial distribution of obesity was similar between the health systems (Spearman r = 0.63). The University of Washington Medicine estimates of rank order correlated well with BRFSS estimates (Spearman r = 0.85), though prevalence estimates from BRFSS were lower (mean obesity prevalence = 26% for University of Washington Medicine versus 20% for BRFSS, Wilcoxon rank sum test p < 0.001). Across all data sources, obesity was more prevalent in tracts with less educational attainment.

CONCLUSIONS

Health system clinical weight data can reliably replicate census tract-level spatial patterns in the ranking of obesity prevalence. Health system data may be an efficient resource for geographic obesity surveillance.

Does the built environment have independent obesogenic power? Urban form and trajectories of weight gain

OBJECTIVE

To determine whether selected features of the built environment can predict weight gain in a large longitudinal cohort of adults.

METHODS

Weight trajectories over a 5-year period were obtained from electronic health records for 115,260 insured patients aged 18-64 years in the Kaiser Permanente Washington health care system. Home addresses were geocoded using ArcGIS. Built environment variables were population, residential unit, and road intersection densities captured using Euclidean-based SmartMaps at 800-m buffers. Counts of area supermarkets and fast food restaurants were obtained using network-based SmartMaps at 1600, and 5000-m buffers. Property values were a measure of socioeconomic status. Linear mixed effects models tested whether built environment variables at baseline were associated with long-term weight gain, adjusting for sex, age, race/ethnicity, Medicaid insurance, body weight, and residential property values.

RESULTS

Built environment variables at baseline were associated with differences in baseline obesity prevalence and body mass index but had limited impact on weight trajectories. Mean weight gain for the full cohort was 0.06 kg at 1 year (95% CI: 0.03, 0.10); 0.64 kg at 3 years (95% CI: 0.59, 0.68), and 0.95 kg at 5 years (95% CI: 0.90, 1.00). In adjusted regression models, the top tertile of density metrics and frequency counts were associated with lower weight gain at 5-years follow-up compared to the bottom tertiles, though the mean differences in weight change for each follow-up year (1, 3, and 5) did not exceed 0.5 kg.

CONCLUSIONS

Built environment variables that were associated with higher obesity prevalence at baseline had limited independent obesogenic power with respect to weight gain over time. Residential unit density had the strongest negative association with weight gain. Future work on the influence of built environment variables on health should also examine social context, including residential segregation and residential mobility.

Scaling up a community-led health promotion initiative: Lessons learned and promising practices from the Healthy Weights for Children Project

The increase in overweight and obesity among children has emerged as an important public health issue. This trend has highlighted the need for accessible and novel approaches to support healthy weights for children and their families to prevent childhood obesity. The purpose of this article is to describe the iterative development and scale-up of a community-led, national-level project to promote healthy weights among Canadian children and families who may be experiencing vulnerabilities. In this project, the Healthy Together program was designed to engage families in an interactive program to support healthy lifestyles. The program also provides a platform for creating supportive environments for healthful lifestyles through practice and policy change. Based on a process evaluation, we describe the iterative development of Healthy Together from Phase 1 through 3 to shed light on processes shaping implementation and scale-up of the program. Lessons learned during each phase were used to refine the program and further expansion. Indicators of successful scale-up include the Healthy Together program's cross-jurisdictional reach and promising evaluation results in real-world conditions. The practice-based program scaling approach provides practical guidance for planning and implementing similar health promotion programs in diverse communities.

The moderating role of the built environment in prenatal lifestyle interventions

This study examined whether the neighborhood built environment moderated gestational weight gain (GWG) in LIFE-Moms clinical trials. Participants were 790 pregnant women (13.9 weeks' gestation) with overweight or obesity randomized within four clinical centers to standard care or lifestyle intervention to reduce GWG. Geographic information system (GIS) was used to map the neighborhood built environment. The intervention relative to standard care significantly reduced GWG (coefficient = 0.05; p = 0.005) and this effect remained significant (p < 0.03) after adjusting for built environment variables. An interaction was observed for presence of fast food restaurants (coefficient = -0.007; p = 0.003). Post hoc tests based on a median split showed that the intervention relative to standard care reduced GWG in participants living in neighborhoods with lower fast food density 0.08 [95% CI, 0.03,0.12] kg/week (p = 0.001) but not in those living in areas with higher fast food density (0.02 [-0.04, 0.08] kg/week; p = 0.55). Interaction effects suggested less intervention efficacy among women living in neighborhoods with more grocery/convenience stores (coefficient = -0.005; p = 0.0001), more walkability (coefficient -0.012; p = 0.007) and less crime (coefficient = 0.001; p = 0.007), but post-hoc tests were not significant. No intervention x environment interaction effects were observed for total number of eating establishments or tree canopy. Lifestyle interventions during pregnancy were effective across diverse physical environments. Living in environments with easy access to fast food restaurants may limit efficacy of prenatal lifestyle interventions, but future research is needed to replicate these findings.

Associations between the built environment and obesity: an umbrella review

BACKGROUND

In the past two decades, the built environment emerged as a conceptually important determinant of obesity. As a result, an abundance of studies aiming to link environmental characteristics to weight-related outcomes have been published, and multiple reviews have attempted to summarise these studies under different scopes and domains. We set out to summarise the accumulated evidence across domains by conducting a review of systematic reviews on associations between any aspect of the built environment and overweight or obesity.

METHODS

Seven databases were searched for eligible publications from the year 2000 onwards. We included systematic literature reviews, meta-analyses and pooled analyses of observational studies in the form of cross-sectional, case-control, longitudinal cohort, ecological, descriptive, intervention studies and natural experiments. We assessed risk of bias and summarised results structured by built environmental themes such as food environment, physical activity environment, urban-rural disparity, socioeconomic status and air pollution.

RESULTS

From 1850 initial hits, 32 systematic reviews were included, most of which reported equivocal evidence for associations. For food- and physical activity environments, associations were generally very small or absent, although some characteristics within these domains were consistently associated with weight status such as fast-food exposure, urbanisation, land use mix and urban sprawl. Risks of bias were predominantly high.

CONCLUSIONS

Thus far, while most studies have not been able to confirm the assumed influence of built environments on weight, there is evidence for some obesogenic environmental characteristics. Registration: This umbrella review was registered on PROSPERO under ID CRD42019135857.

A cross-sectional analysis of physical activity and weight misreporting in diverse populations: The Seattle Obesity Study III

BACKGROUND

In-person assessments of physical activity (PA) and body weight can be burdensome for participants and cost prohibitive for researchers. This study examined self-reported PA and weight accuracy and identified patterns of misreporting in a diverse sample.

METHODS

King, Pierce and Yakima county residents, aged 21-59 years (n = 728), self-reported their moderate-to-vigorous PA (MVPA) and weight, in kilograms. Self-reports were compared with minutes of bout-level MVPA, from 3 days of accelerometer data, and measured weights. Regression models examined characteristics associated with underreporting and overreporting of MVPA and weight, the potential bias introduced using each measure and the relation between perceived and measured PA and weight.

RESULTS

MVPA underreporting was higher among males and college educated participants; however, there was no differential MVPA overreporting. Weight underreporting was higher among males, those age 40-49 years and persons with obesity. Weight overreporting was higher among Hispanic participants and those reporting stress, unhappiness and fair or poor health. The estimated PA-obesity relation was similar using measured and self-reported PA but not self-reported weight. Perceived PA and weight predicted measured values.

CONCLUSION

Self-reported PA and weight may be useful should objective measurement be infeasible; however, though population-specific adjustment for differential reporting should be considered.

Food Addiction and Psychosocial Adversity: Biological Embedding, Contextual Factors, and Public Health Implications

The role of stress, trauma, and adversity particularly early in life has been identified as a contributing factor in both drug and food addictions. While links between traumatic stress and substance use disorders are well documented, the pathways to food addiction and obesity are less established. This review focuses on psychosocial and neurobiological factors that may increase risk for addiction-like behaviors and ultimately increase BMI over the lifespan. Early childhood and adolescent adversity can induce long-lasting alterations in the glucocorticoid and dopamine systems that lead to increased addiction vulnerability later in life. Allostatic load, the hypothalamic-pituitary-adrenal axis, and emerging data on epigenetics in the context of biological embedding are highlighted. A conceptual model for food addiction is proposed, which integrates data on the biological embedding of adversity as well as upstream psychological, social, and environmental factors. Dietary restraint as a feature of disordered eating is discussed as an important contextual factor related to food addiction. Discussion of various public health and policy considerations are based on the concept that improved knowledge of biopsychosocial mechanisms contributing to food addiction may decrease stigma associated with obesity and disordered eating behavior.

Synergies in Design and Health. The role of architects and urban health planners in tackling key contemporary public health challenges

Background and aim:

Important public health improvements have been achieved over the past decades, but new challenges are emerging and progress cannot be taken for granted. Urban settlements host most of the global population, but they are also sources of several threats. The aim of the paper is to investigate the role of architects and planners in contributing to overcome these critical health challenges and propose strategic actions for collaboration with the public health workforce.

Methods:

Taking global trends and public health challenges as starting point, a scoping literature review has been conducted to illustrate the possible synergies that architecture and public health workforce should exploit to support population health improvement and tackle key public health challenges.

Results:

The built environment affects climate change and public health through the use of resources, site location, and green spaces. In architecture curricula, limited space is devoted to health and vice versa. There is an urgent need for recognition of the benefits of collaboration and cross-fertilisation between public health and planning workforce from local to global levels.

Conclusion:

Public health is evolving from a bio-medical to a socio-anthropological approach and architects/planners have fundamental roles; further collaboration, research and training are needed.