The Relationship Between Housing Types and Metabolic and Weight Phenotypes: A Nationwide Survey

Lee, Kayoung

doi:10.1089/met.2018.0109

Cited by 2 publications

(3 citation statements)

References 18 publications

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“…Interestingly Soofu and coworkers [ 91 ] also report the effect that we found of an association of MetS to housing conditions and ownership of durable assets. Inadequate housing conditions, in particular, have been discussed to contribute to an increase in the risk of cardiovascular disease [ 93 ]. In fact, local residential environments may constitute significant risk factors for MetS, which is a fact that needs to be considered in order to develop environmental interventions to improve population health [ 94 ].…”

Section: Discussionmentioning

confidence: 99%

“…A similar association has been reported with regards to housing (QUA_HOUS in Figure 5 ) [ 98 , 99 ]. A study in an urban Korean population found that non-apartment residents were more likely to have MetS and related phenotypes compared to apartment residents in a model that was adjusted for confounding variables such as sociodemographic characteristics, residence area, health behavior, and nutritional information awareness [ 93 ]. Sanitary conditions are known to modify both environmental conditions and even intrinsic factors such as the gut microbiota, affecting the development of MetS [ 100 , 101 , 102 ].…”

Section: Discussionmentioning

confidence: 99%

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Sleep Quality, Nutrient Intake, and Social Development Index Predict Metabolic Syndrome in the Tlalpan 2020 Cohort: A Machine Learning and Synthetic Data Study

Gutiérrez-Esparza,

Martinez-Garcia,

Ramírez-delReal

et al. 2024

Nutrients

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This study investigated the relationship between Metabolic Syndrome (MetS), sleep disorders, the consumption of some nutrients, and social development factors, focusing on gender differences in an unbalanced dataset from a Mexico City cohort. We used data balancing techniques like SMOTE and ADASYN after employing machine learning models like random forest and RPART to predict MetS. Random forest excelled, achieving significant, balanced accuracy, indicating its robustness in predicting MetS and achieving a balanced accuracy of approximately 87%. Key predictors for men included body mass index and family history of gout, while waist circumference and glucose levels were most significant for women. In relation to diet, sleep quality, and social development, metabolic syndrome in men was associated with high lactose and carbohydrate intake, educational lag, living with a partner without marrying, and lack of durable goods, whereas in women, best predictors in these dimensions include protein, fructose, and cholesterol intake, copper metabolites, snoring, sobbing, drowsiness, sanitary adequacy, and anxiety. These findings underscore the need for personalized approaches in managing MetS and point to a promising direction for future research into the interplay between social factors, sleep disorders, and metabolic health, which mainly depend on nutrient consumption by region.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Sleep Quality, Nutrient Intake, and Social Development Index Predict Metabolic Syndrome in the Tlalpan 2020 Cohort: A Machine Learning and Synthetic Data Study

Gutiérrez-Esparza,

Martinez-Garcia,

Ramírez-delReal

et al. 2024

Nutrients

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“…Detached houses and apartment buildings have different structural properties, airtightness, ceiling heights, and so on, resulting in clear differences in residential environments. [14][15][16][17][18][19][20] For example, a room in an apartment is surrounded by other dwelling units; therefore, the outer surface area is small, resulting in better heat insulation and airtightness compared with detached houses. The thermal insulation and airtightness of houses affect the health of residents.…”

Section: Introductionmentioning

confidence: 99%

Influence of residential performance on residents' health status (part II): Nationwide survey of environmental performance of apartment buildings and residents' health status

Kawakubo

Kamata

Murakami³

et al. 2022

Japan Architectural Review

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The residential environment clearly affects health. For example, a previous study has established relationships between specific environmental factors and the health status of residents in detached houses. However, studies focused on apartment buildings are still insufficient. Therefore, in this study, a large nationwide questionnaire survey of residents of apartments was conducted. The residential environment was subjectively evaluated using a Japanese Comprehensive Assessment System for Built Environment Efficiency (CASBEE) tool: the CASBEE Health Checklist. The results showed that residents living in apartments who score higher on the checklist tend to have a lower prevalence of various diseases, indicating that residential environment may be an important determinant of health. Furthermore, the odds ratios for residents living in apartment buildings were lower for diabetes mellitus, hypertensive diseases, heart diseases, cerebrovascular diseases, chronic lower respiratory diseases, and inflammatory polyarthropathies compared with residents living in detached houses. These findings support the general link between the residential environment and residents' health and suggest that housing typology is an important factor.

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The Relationship Between Housing Types and Metabolic and Weight Phenotypes: A Nationwide Survey

Cited by 2 publications

References 18 publications

Sleep Quality, Nutrient Intake, and Social Development Index Predict Metabolic Syndrome in the Tlalpan 2020 Cohort: A Machine Learning and Synthetic Data Study

Sleep Quality, Nutrient Intake, and Social Development Index Predict Metabolic Syndrome in the Tlalpan 2020 Cohort: A Machine Learning and Synthetic Data Study

Influence of residential performance on residents' health status (part II): Nationwide survey of environmental performance of apartment buildings and residents' health status

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