Hotspots of childhood obesity in a large metropolitan area: does neighbourhood social and built environment play a part?

Ribeiro, Ana Isabel; Santos, Ana Cristina; Vieira, Verónica M.; Barros, Henrique

doi:10.1093/ije/dyz205

Cited by 17 publications

(7 citation statements)

References 54 publications

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“…GAMs are extensions of typical linear regressions models (e.g., logistic regression model for binary data) that include smoothed terms that allow for the relaxing of typical assumptions of linearity between predictors and outcomes [40]. In the field of spatial epidemiology, mixed-mode GAMs, in which only location coordinates are non-parametrically smoothed, whereas other covariates keep a form of linear parametric prediction [36], have been used to investigate the geographic variation of diseases [36,[41][42][43][44][45][46][47]. The below model was used to calculate ORs in this study:…”

Section: Discussionmentioning

confidence: 99%

Environmental and Household-Based Spatial Risks for Tungiasis in an Endemic Area of Coastal Kenya

et al. 2021

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Tungiasis is a cutaneous parasitosis caused by an embedded female sand flea. The distribution of cases can be spatially heterogeneous even in areas with similar risk profiles. This study assesses household and remotely sensed environmental factors that contribute to the geographic distribution of tungiasis cases in a rural area along the Southern Kenyan Coast. Data on household tungiasis case status, demographic and socioeconomic information, and geographic locations were recorded during regular survey activities of the Health and Demographic Surveillance System, mainly during 2011. Data were joined with other spatial data sources using latitude/longitude coordinates. Generalized additive models were used to predict and visualize spatial risks for tungiasis. The household-level prevalence of tungiasis was 3.4% (272/7925). There was a 1.1% (461/41,135) prevalence of infection among all participants. A significant spatial variability was observed in the unadjusted model (p-value < 0.001). The number of children per household, earthen floor, organic roof, elevation, aluminum content in the soil, and distance to the nearest animal reserve attenuated the odds ratios and partially explained the spatial variation of tungiasis. Spatial heterogeneity in tungiasis risk remained even after a factor adjustment. This suggests that there are possible unmeasured factors associated with the complex ecology of sand fleas that may contribute to the disease’s uneven distribution.

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Section: Discussionmentioning

confidence: 99%

Environmental and Household-Based Spatial Risks for Tungiasis in an Endemic Area of Coastal Kenya

et al. 2021

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“…On the other hand, obesity is a risk factor for acne, which implies that types and numbers of restaurants around the residential and work location of people could be related to their obesity. A number of studies in the US ( 139 ), New York ( 105 ), Utah ( 106 ), the UK ( 13 , 140 ), Porto ( 104 ), New Orleans ( 141 ), and China ( 142 ) showed higher fast food restaurant density was significantly associated with higher obesity rates among students. Therefore, an increased number of fast food restaurants near the address may increase the risk of obesity, which may indirectly affect the occurrence of acne.…”

Section: Discussionmentioning

confidence: 99%

“…At present, a growing number of studies have focused on the impact of built environment on health (Table 4 in Appendix), especially those chronic diseases such as obesity (13), cardiovascular disease (15) and mental health (14). Studies indicated that obesity was positively associated with population density and the availability of fast-food outlets from the people's residence (104)(105)(106)(107)(108). Moreover, other studies also found the incidence of cardiovascular disease was significantly higher with more fast-food outlets than areas with no fast-food outlets (15,109).…”

Section: Built Environmental Factorsmentioning

confidence: 99%

A Review of Advancement on Influencing Factors of Acne: An Emphasis on Environment Characteristics

Yang

et al. 2020

Front. Public Health

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Background: Acne vulgaris is known as a commonly-seen skin disease with a considerable impact on the quality of life. At present, there have been a growing number of epidemiological, medical, demographic and sociological researches focusing on various influencing factors in the occurrence of acne. Nevertheless, the correlation between environmental factors and acne has yet to be fully investigated. Objective: To assess the impacts of individual, natural and social environmental factors on acne and to construct a framework for the potential impact of built environment on acne. Methods: A thorough review was conducted into the published social demographical, epidemiological, and environmental studies on acne through PubMed, Google Scholar and Web of Science, with reference made to the relevant literature. Results: The influencing factors in acne are classed into four major categories. The first one includes individual socioeconomic and biological factors, for example, gender, age, economic level, heredity, obesity, skin type, menstrual cycle (for females), diet, smoking, cosmetics products, electronic products, sleep quality and psychological factors. The second one includes such natural environmental factors as temperature, humidity, sun exposure, air pollution and chloracne. The third one relates to social environment, including social network and social media. The last one includes built environmental factors, for example, population density, food stores, green spaces, as well as other built environment characteristics for transport. Acne can be affected negatively by family history, overweight, obesity, oily or mixed skin, irregular menstrual cycles, sugary food, greasy food, dairy products, smoking, the improper use of cosmetics, the long-term use of electronics, the poor quality of sleep, stress, high temperature, sun exposure, air pollution, mineral oils and halogenated hydrocarbons. Apart from that, there are also potential links between built environment and acne. Yang et al. Acne Conclusions: It is necessary to determine the correlation between the built environment and acne based on the understanding of the impact of traditional factors (sociology of population and environment) on acne gained by multidisciplinary research teams. Moreover, more empirical studies are required to reveal the specific relationship between built environment and acne.

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“…These locals of eating out are more appeal for the more vulnerable due to lower food prices, especially by spending per unit of energy (46) and also because they are possibly exposed to a high density of fast-food outlets in the places of residence (43,45) . In a study, using data from the population-based cohort Generation XXI was also found that neighbourhood deprivation and paedestrian access to fast-food outlets could increase the prevalence of obesity in children with 7 years (47) . This double burden, higher exposure to fast-food outlets and low income represent an additive effect for lower diet quality and can be a possible explanation for our results.…”

Section: Discussionmentioning

confidence: 99%

Interaction effects of socio-economic position in the association between eating location and diet quality in Portuguese children and adolescents: results from the National Food, Nutrition and Physical Activity Survey 2015–2016

et al. 2021

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This study aims to evaluate the interaction effect of socioeconomic environment (SEE) in the relationship between the eating location (EL) and diet quality, in children and adolescents. Data included children and adolescents (3-17y) from a National Dietary Survey Sample (IAN-AF 2015/2016, n=987). Dietary intake was obtained by 2-day food diaries (children) or 2-24-hour-recall (adolescents). Participants were classified into four groups of EL: “Home”, “Other homes”, “School” and “Restaurants”. Diet quality was measured as a higher adherence to a healthy eating pattern. A previous developed socioeconomic classification was used, and participants were grouped as belonging to a low socioeconomic environment (LSE) or middle-high socioeconomic environment (MHSE). Linear regression models were used to evaluate the association between EL and diet quality, stratified by the SEE. One-quarter of participants was classified in the “Home” group, 14% in “Other homes”, 17% in “Restaurants” and 45% in “School”. A statistically significant interaction effect was found (p<0.01) for the SEE in the association between eating location and diet quality. After adjustment for potential confounders, in LSE, children and adolescents belonging to “Other homes” (β̂=−2.07; 95%CI:−3.70;−0.44) and “Restaurants” (β̂=−3.31; 95%CI:−5.08;−1.54) had lower scores in the diet quality score, comparing to “Home”. In MHSE, comparing to “Home”, “Restaurants” showed lower diet quality (β̂=−1.56; 95%CI:−2.65;−0.48), while the “School” had better diet quality (β̂=0.90; 95%CI:0.16;1.64). The SEE influences the association between EL and diet quality and, belonging to more disadvantaged SEE, might represent a higher risk of unhealthy eating habits when eating out-of-home compared to when eating at home.

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Hotspots of childhood obesity in a large metropolitan area: does neighbourhood social and built environment play a part?

Cited by 17 publications

References 54 publications

Environmental and Household-Based Spatial Risks for Tungiasis in an Endemic Area of Coastal Kenya

Environmental and Household-Based Spatial Risks for Tungiasis in an Endemic Area of Coastal Kenya

A Review of Advancement on Influencing Factors of Acne: An Emphasis on Environment Characteristics

Interaction effects of socio-economic position in the association between eating location and diet quality in Portuguese children and adolescents: results from the National Food, Nutrition and Physical Activity Survey 2015–2016

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