Modelling socioeconomic position as a driver of the exposome in the first 18 months of life of the NINFEA birth cohort children
The exposome drivers are less studied than its consequences but may be crucial in identifying population subgroups with unfavourable exposures. We used three approaches to study the socioeconomic position (SEP) as a driver of the early-life exposome in Turin children of the NINFEA cohort (Italy). Fo...
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| Published in | Environment international Vol. 173; pp. 107864 - 13 |
|---|---|
| Main Authors | , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Netherlands
Elsevier Ltd
01.03.2023
Elsevier |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0160-4120 1873-6750 1873-6750 |
| DOI | 10.1016/j.envint.2023.107864 |
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| Abstract | The exposome drivers are less studied than its consequences but may be crucial in identifying population subgroups with unfavourable exposures.
We used three approaches to study the socioeconomic position (SEP) as a driver of the early-life exposome in Turin children of the NINFEA cohort (Italy).
Forty-two environmental exposures, collected at 18 months of age (N = 1989), were classified in 5 groups (lifestyle, diet, meteoclimatic, traffic-related, built environment).
We performed cluster analysis to identify subjects sharing similar exposures, and intra-exposome-group Principal Component Analysis (PCA) to reduce the dimensionality. SEP at childbirth was measured through the Equivalised Household Income Indicator.
SEP-exposome association was evaluated using: 1) an Exposome Wide Association Study (ExWAS), a one-exposure (SEP) one-outcome (exposome) approach; 2) multinomial regression of cluster membership on SEP; 3) regressions of each intra-exposome-group PC on SEP.
In the ExWAS, medium/low SEP children were more exposed to greenness, pet ownership, passive smoking, TV screen and sugar; less exposed to NO2, NOX, PM25abs, humidity, built environment, traffic load, unhealthy food facilities, fruit, vegetables, eggs, grain products, and childcare than high SEP children.
Medium/low SEP children were more likely to belong to a cluster with poor diet, less air pollution, and to live in the suburbs than high SEP children.
Medium/low SEP children were more exposed to lifestyle PC1 (unhealthy lifestyle) and diet PC2 (unhealthy diet), and less exposed to PC1s of the built environment (urbanization factors), diet (mixed diet), and traffic (air pollution) than high SEP children.
The three approaches provided consistent and complementary results, suggesting that children with lower SEP are less exposed to urbanization factors and more exposed to unhealthy lifestyles and diet. The simplest method, the ExWAS, conveys most of the information and is more replicable in other populations. Clustering and PCA may facilitate results interpretation and communication. |
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| AbstractList | The exposome drivers are less studied than its consequences but may be crucial in identifying population subgroups with unfavourable exposures.BACKGROUNDThe exposome drivers are less studied than its consequences but may be crucial in identifying population subgroups with unfavourable exposures.We used three approaches to study the socioeconomic position (SEP) as a driver of the early-life exposome in Turin children of the NINFEA cohort (Italy).OBJECTIVESWe used three approaches to study the socioeconomic position (SEP) as a driver of the early-life exposome in Turin children of the NINFEA cohort (Italy).Forty-two environmental exposures, collected at 18 months of age (N = 1989), were classified in 5 groups (lifestyle, diet, meteoclimatic, traffic-related, built environment). We performed cluster analysis to identify subjects sharing similar exposures, and intra-exposome-group Principal Component Analysis (PCA) to reduce the dimensionality. SEP at childbirth was measured through the Equivalised Household Income Indicator. SEP-exposome association was evaluated using: 1) an Exposome Wide Association Study (ExWAS), a one-exposure (SEP) one-outcome (exposome) approach; 2) multinomial regression of cluster membership on SEP; 3) regressions of each intra-exposome-group PC on SEP.METHODSForty-two environmental exposures, collected at 18 months of age (N = 1989), were classified in 5 groups (lifestyle, diet, meteoclimatic, traffic-related, built environment). We performed cluster analysis to identify subjects sharing similar exposures, and intra-exposome-group Principal Component Analysis (PCA) to reduce the dimensionality. SEP at childbirth was measured through the Equivalised Household Income Indicator. SEP-exposome association was evaluated using: 1) an Exposome Wide Association Study (ExWAS), a one-exposure (SEP) one-outcome (exposome) approach; 2) multinomial regression of cluster membership on SEP; 3) regressions of each intra-exposome-group PC on SEP.In the ExWAS, medium/low SEP children were more exposed to greenness, pet ownership, passive smoking, TV screen and sugar; less exposed to NO2, NOX, PM25abs, humidity, built environment, traffic load, unhealthy food facilities, fruit, vegetables, eggs, grain products, and childcare than high SEP children. Medium/low SEP children were more likely to belong to a cluster with poor diet, less air pollution, and to live in the suburbs than high SEP children. Medium/low SEP children were more exposed to lifestyle PC1 (unhealthy lifestyle) and diet PC2 (unhealthy diet), and less exposed to PC1s of the built environment (urbanization factors), diet (mixed diet), and traffic (air pollution) than high SEP children.RESULTSIn the ExWAS, medium/low SEP children were more exposed to greenness, pet ownership, passive smoking, TV screen and sugar; less exposed to NO2, NOX, PM25abs, humidity, built environment, traffic load, unhealthy food facilities, fruit, vegetables, eggs, grain products, and childcare than high SEP children. Medium/low SEP children were more likely to belong to a cluster with poor diet, less air pollution, and to live in the suburbs than high SEP children. Medium/low SEP children were more exposed to lifestyle PC1 (unhealthy lifestyle) and diet PC2 (unhealthy diet), and less exposed to PC1s of the built environment (urbanization factors), diet (mixed diet), and traffic (air pollution) than high SEP children.The three approaches provided consistent and complementary results, suggesting that children with lower SEP are less exposed to urbanization factors and more exposed to unhealthy lifestyles and diet. The simplest method, the ExWAS, conveys most of the information and is more replicable in other populations. Clustering and PCA may facilitate results interpretation and communication.CONCLUSIONSThe three approaches provided consistent and complementary results, suggesting that children with lower SEP are less exposed to urbanization factors and more exposed to unhealthy lifestyles and diet. The simplest method, the ExWAS, conveys most of the information and is more replicable in other populations. Clustering and PCA may facilitate results interpretation and communication. Background: The exposome drivers are less studied than its consequences but may be crucial in identifying population subgroups with unfavourable exposures. Objectives: We used three approaches to study the socioeconomic position (SEP) as a driver of the early-life exposome in Turin children of the NINFEA cohort (Italy). Methods: Forty-two environmental exposures, collected at 18 months of age (N = 1989), were classified in 5 groups (lifestyle, diet, meteoclimatic, traffic-related, built environment).We performed cluster analysis to identify subjects sharing similar exposures, and intra-exposome-group Principal Component Analysis (PCA) to reduce the dimensionality. SEP at childbirth was measured through the Equivalised Household Income Indicator.SEP-exposome association was evaluated using: 1) an Exposome Wide Association Study (ExWAS), a one-exposure (SEP) one-outcome (exposome) approach; 2) multinomial regression of cluster membership on SEP; 3) regressions of each intra-exposome-group PC on SEP. Results: In the ExWAS, medium/low SEP children were more exposed to greenness, pet ownership, passive smoking, TV screen and sugar; less exposed to NO2, NOX, PM25abs, humidity, built environment, traffic load, unhealthy food facilities, fruit, vegetables, eggs, grain products, and childcare than high SEP children.Medium/low SEP children were more likely to belong to a cluster with poor diet, less air pollution, and to live in the suburbs than high SEP children.Medium/low SEP children were more exposed to lifestyle PC1 (unhealthy lifestyle) and diet PC2 (unhealthy diet), and less exposed to PC1s of the built environment (urbanization factors), diet (mixed diet), and traffic (air pollution) than high SEP children. Conclusions: The three approaches provided consistent and complementary results, suggesting that children with lower SEP are less exposed to urbanization factors and more exposed to unhealthy lifestyles and diet. The simplest method, the ExWAS, conveys most of the information and is more replicable in other populations. Clustering and PCA may facilitate results interpretation and communication. The exposome drivers are less studied than its consequences but may be crucial in identifying population subgroups with unfavourable exposures. We used three approaches to study the socioeconomic position (SEP) as a driver of the early-life exposome in Turin children of the NINFEA cohort (Italy). Forty-two environmental exposures, collected at 18 months of age (N = 1989), were classified in 5 groups (lifestyle, diet, meteoclimatic, traffic-related, built environment). We performed cluster analysis to identify subjects sharing similar exposures, and intra-exposome-group Principal Component Analysis (PCA) to reduce the dimensionality. SEP at childbirth was measured through the Equivalised Household Income Indicator. SEP-exposome association was evaluated using: 1) an Exposome Wide Association Study (ExWAS), a one-exposure (SEP) one-outcome (exposome) approach; 2) multinomial regression of cluster membership on SEP; 3) regressions of each intra-exposome-group PC on SEP. In the ExWAS, medium/low SEP children were more exposed to greenness, pet ownership, passive smoking, TV screen and sugar; less exposed to NO₂, NOX, PM₂₅ₐbₛ, humidity, built environment, traffic load, unhealthy food facilities, fruit, vegetables, eggs, grain products, and childcare than high SEP children. Medium/low SEP children were more likely to belong to a cluster with poor diet, less air pollution, and to live in the suburbs than high SEP children. Medium/low SEP children were more exposed to lifestyle PC1 (unhealthy lifestyle) and diet PC2 (unhealthy diet), and less exposed to PC1s of the built environment (urbanization factors), diet (mixed diet), and traffic (air pollution) than high SEP children. The three approaches provided consistent and complementary results, suggesting that children with lower SEP are less exposed to urbanization factors and more exposed to unhealthy lifestyles and diet. The simplest method, the ExWAS, conveys most of the information and is more replicable in other populations. Clustering and PCA may facilitate results interpretation and communication. The exposome drivers are less studied than its consequences but may be crucial in identifying population subgroups with unfavourable exposures. We used three approaches to study the socioeconomic position (SEP) as a driver of the early-life exposome in Turin children of the NINFEA cohort (Italy). Forty-two environmental exposures, collected at 18 months of age (N = 1989), were classified in 5 groups (lifestyle, diet, meteoclimatic, traffic-related, built environment). We performed cluster analysis to identify subjects sharing similar exposures, and intra-exposome-group Principal Component Analysis (PCA) to reduce the dimensionality. SEP at childbirth was measured through the Equivalised Household Income Indicator. SEP-exposome association was evaluated using: 1) an Exposome Wide Association Study (ExWAS), a one-exposure (SEP) one-outcome (exposome) approach; 2) multinomial regression of cluster membership on SEP; 3) regressions of each intra-exposome-group PC on SEP. In the ExWAS, medium/low SEP children were more exposed to greenness, pet ownership, passive smoking, TV screen and sugar; less exposed to NO , NO , PM , humidity, built environment, traffic load, unhealthy food facilities, fruit, vegetables, eggs, grain products, and childcare than high SEP children. Medium/low SEP children were more likely to belong to a cluster with poor diet, less air pollution, and to live in the suburbs than high SEP children. Medium/low SEP children were more exposed to lifestyle PC1 (unhealthy lifestyle) and diet PC2 (unhealthy diet), and less exposed to PC1s of the built environment (urbanization factors), diet (mixed diet), and traffic (air pollution) than high SEP children. The three approaches provided consistent and complementary results, suggesting that children with lower SEP are less exposed to urbanization factors and more exposed to unhealthy lifestyles and diet. The simplest method, the ExWAS, conveys most of the information and is more replicable in other populations. Clustering and PCA may facilitate results interpretation and communication. The exposome drivers are less studied than its consequences but may be crucial in identifying population subgroups with unfavourable exposures. We used three approaches to study the socioeconomic position (SEP) as a driver of the early-life exposome in Turin children of the NINFEA cohort (Italy). Forty-two environmental exposures, collected at 18 months of age (N = 1989), were classified in 5 groups (lifestyle, diet, meteoclimatic, traffic-related, built environment). We performed cluster analysis to identify subjects sharing similar exposures, and intra-exposome-group Principal Component Analysis (PCA) to reduce the dimensionality. SEP at childbirth was measured through the Equivalised Household Income Indicator. SEP-exposome association was evaluated using: 1) an Exposome Wide Association Study (ExWAS), a one-exposure (SEP) one-outcome (exposome) approach; 2) multinomial regression of cluster membership on SEP; 3) regressions of each intra-exposome-group PC on SEP. In the ExWAS, medium/low SEP children were more exposed to greenness, pet ownership, passive smoking, TV screen and sugar; less exposed to NO2, NOX, PM25abs, humidity, built environment, traffic load, unhealthy food facilities, fruit, vegetables, eggs, grain products, and childcare than high SEP children. Medium/low SEP children were more likely to belong to a cluster with poor diet, less air pollution, and to live in the suburbs than high SEP children. Medium/low SEP children were more exposed to lifestyle PC1 (unhealthy lifestyle) and diet PC2 (unhealthy diet), and less exposed to PC1s of the built environment (urbanization factors), diet (mixed diet), and traffic (air pollution) than high SEP children. The three approaches provided consistent and complementary results, suggesting that children with lower SEP are less exposed to urbanization factors and more exposed to unhealthy lifestyles and diet. The simplest method, the ExWAS, conveys most of the information and is more replicable in other populations. Clustering and PCA may facilitate results interpretation and communication. |
| ArticleNumber | 107864 |
| Author | Sanavia, Tiziana Maule, Milena d'Errico, Antonio Pizzi, Costanza Nieuwenhuijsen, Mark J. Moccia, Chiara Fossati, Serena Zugna, Daniela Moirano, Giovenale Isaevska, Elena Richiardi, Lorenzo Popovic, Maja Fariselli, Piero |
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| Keywords | Environmental epidemiology Exposome Life course epidemiology Socioeconomic position Health inequalities |
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We used three... The exposome drivers are less studied than its consequences but may be crucial in identifying population subgroups with unfavourable exposures.BACKGROUNDThe... The exposome drivers are less studied than its consequences but may be crucial in identifying population subgroups with unfavourable exposures. We used three... Background: The exposome drivers are less studied than its consequences but may be crucial in identifying population subgroups with unfavourable exposures.... |
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| Title | Modelling socioeconomic position as a driver of the exposome in the first 18 months of life of the NINFEA birth cohort children |
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