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Background: Respiratory symptoms are a common public health issue that can partly be attributed to preventable risk factors, such as tobacco smoking and occupational exposure, which are more common in individuals with lower socioeconomic status. Objective: Our aim was to evaluate the social gradient in respiratory symptoms in Nordic countries. Methods: This study included participants aged 30–65 years from five cross-sectional population-based questionnaire surveys in 2016 in Finland and Sweden (N = 25,423) and in 2017–2019 in Norway (N = 27,107). Occupational skill levels 1 and 2 (occupations requiring compulsory education) were combined and compared to skill levels 3 and 4 (occupations requiring upper secondary and tertiary education). Meta-analysis was conducted to obtain pooled age- and sex adjusted odds ratios (aORs) of associations between occupational skill and the respiratory symptoms including recurrent wheeze, dyspnoea, and productive cough. Results: In the meta-analysis, recurrent wheeze, dyspnoea, and productive cough showed a social gradient. The participants with occupational skill 1 and 2 had higher risk for recurrent wheeze (aOR 1.78, 95% CI 1.34–2.22) and dyspnoea (aOR 1.59, 95% CI 1.29–1.90) compared to occupational skill 3 and 4 in Sweden and Finland. Similarly increased risk was observed for combined assessment of dyspnoea and wheeze (aOR 1.05, 95% CI 1.03–1.07) in Norway. In a meta-analysis including all three countries, the aOR for productive cough was 1.31 95% CI 1.07–1.56. Conclusions: Occupations with lower, compared to higher, skill levels were associated with an increased risk of recurrent wheeze, dyspnoea, and productive cough.

Background: Respiratory symptoms are a common public health issue that can partly be attributed to preventable risk factors, such as tobacco smoking and occupational exposure, which are more common in individuals with lower socioeconomic status. Objective: Our aim was to evaluate the social gradient in respiratory symptoms in Nordic countries. Methods: This study included participants aged 30–65 years from five cross-sectional population-based questionnaire surveys in 2016 in Finland and Sweden (N = 25,423) and in 2017–2019 in Norway (N = 27,107). Occupational skill levels 1 and 2 (occupations requiring compulsory education) were combined and compared to skill levels 3 and 4 (occupations requiring upper secondary and tertiary education). Meta-analysis was conducted to obtain pooled age- and sex adjusted odds ratios (aORs) of associations between occupational skill and the respiratory symptoms including recurrent wheeze, dyspnoea, and productive cough. Results: In the meta-analysis, recurrent wheeze, dyspnoea, and productive cough showed a social gradient. The participants with occupational skill 1 and 2 had higher risk for recurrent wheeze (aOR 1.78, 95% CI 1.34–2.22) and dyspnoea (aOR 1.59, 95% CI 1.29–1.90) compared to occupational skill 3 and 4 in Sweden and Finland. Similarly increased risk was observed for combined assessment of dyspnoea and wheeze (aOR 1.05, 95% CI 1.03–1.07) in Norway. In a meta-analysis including all three countries, the aOR for productive cough was 1.31 95% CI 1.07–1.56. Conclusions: Occupations with lower, compared to higher, skill levels were associated with an increased risk of recurrent wheeze, dyspnoea, and productive cough.

Background: Evidence abounds on the independent roles of social class and smoking in relation to obstructive airway diseases, but data are sparse on the impact of their interaction. We evaluated whether and to what extent social class and smoking interact in relation to risk of respiratory diseases in adults. Methods: Data from the population-based studies, West Sweden Asthma Study (WSAS, n = 23,753) and Obstructive Lung Disease in Northern Sweden studies (OLIN, n = 6519), were used, constituting randomly selected adults aged 20–75 years. Bayesian network analysis was used to estimate the probability for the interaction between smoking and socioeconomic status in relation to respiratory outcomes. Results: Occupational and educational SES modified the association between smoking and the probability of allergic and non-allergic asthma. Former smokers who were at intermediate non manual employees and manual workers in service had higher probability of allergic asthma compared to professionals and executives. Furthermore, former smokers with primary education had higher probability of non-allergic asthma than those with secondary and tertiary education. Similarly, former smokers among professionals and executives had higher probability of non-allergic asthma than manual and home workers and primary educated. Likewise, allergic asthma due to former smoking was higher among highly educated compared to low educated. Conclusions: Beyond their independent roles, socioeconomic status and smoking interact in defining the risk of respiratory diseases. Clearer understanding of this interaction can help to identify population subgroups at most need of public health interventions.

Background: Evidence abounds on the independent roles of social class and smoking in relation to obstructive airway diseases, but data are sparse on the impact of their interaction. We evaluated whether and to what extent social class and smoking interact in relation to risk of respiratory diseases in adults. Methods: Data from the population-based studies, West Sweden Asthma Study (WSAS, n = 23,753) and Obstructive Lung Disease in Northern Sweden studies (OLIN, n = 6519), were used, constituting randomly selected adults aged 20–75 years. Bayesian network analysis was used to estimate the probability for the interaction between smoking and socioeconomic status in relation to respiratory outcomes. Results: Occupational and educational SES modified the association between smoking and the probability of allergic and non-allergic asthma. Former smokers who were at intermediate non manual employees and manual workers in service had higher probability of allergic asthma compared to professionals and executives. Furthermore, former smokers with primary education had higher probability of non-allergic asthma than those with secondary and tertiary education. Similarly, former smokers among professionals and executives had higher probability of non-allergic asthma than manual and home workers and primary educated. Likewise, allergic asthma due to former smoking was higher among highly educated compared to low educated. Conclusions: Beyond their independent roles, socioeconomic status and smoking interact in defining the risk of respiratory diseases. Clearer understanding of this interaction can help to identify population subgroups at most need of public health interventions.

Background: Evidence abounds on the independent roles of social class and smoking in relation to obstructive airway diseases, but data are sparse on the impact of their interaction. We evaluated whether and to what extent social class and smoking interact in relation to risk of respiratory diseases in adults. Methods: Data from the population-based studies, West Sweden Asthma Study (WSAS, n = 23,753) and Obstructive Lung Disease in Northern Sweden studies (OLIN, n = 6519), were used, constituting randomly selected adults aged 20–75 years. Bayesian network analysis was used to estimate the probability for the interaction between smoking and socioeconomic status in relation to respiratory outcomes. Results: Occupational and educational SES modified the association between smoking and the probability of allergic and non-allergic asthma. Former smokers who were at intermediate non manual employees and manual workers in service had higher probability of allergic asthma compared to professionals and executives. Furthermore, former smokers with primary education had higher probability of non-allergic asthma than those with secondary and tertiary education. Similarly, former smokers among professionals and executives had higher probability of non-allergic asthma than manual and home workers and primary educated. Likewise, allergic asthma due to former smoking was higher among highly educated compared to low educated. Conclusions: Beyond their independent roles, socioeconomic status and smoking interact in defining the risk of respiratory diseases. Clearer understanding of this interaction can help to identify population subgroups at most need of public health interventions.

Background: Evidence abounds on the independent roles of social class and smoking in relation to obstructive airway diseases, but data are sparse on the impact of their interaction. We evaluated whether and to what extent social class and smoking interact in relation to risk of respiratory diseases in adults. Methods: Data from the population-based studies, West Sweden Asthma Study (WSAS, n = 23,753) and Obstructive Lung Disease in Northern Sweden studies (OLIN, n = 6519), were used, constituting randomly selected adults aged 20–75 years. Bayesian network analysis was used to estimate the probability for the interaction between smoking and socioeconomic status in relation to respiratory outcomes. Results: Occupational and educational SES modified the association between smoking and the probability of allergic and non-allergic asthma. Former smokers who were at intermediate non manual employees and manual workers in service had higher probability of allergic asthma compared to professionals and executives. Furthermore, former smokers with primary education had higher probability of non-allergic asthma than those with secondary and tertiary education. Similarly, former smokers among professionals and executives had higher probability of non-allergic asthma than manual and home workers and primary educated. Likewise, allergic asthma due to former smoking was higher among highly educated compared to low educated. Conclusions: Beyond their independent roles, socioeconomic status and smoking interact in defining the risk of respiratory diseases. Clearer understanding of this interaction can help to identify population subgroups at most need of public health interventions.

Background: Evidence abounds on the independent roles of social class and smoking in relation to obstructive airway diseases, but data are sparse on the impact of their interaction. We evaluated whether and to what extent social class and smoking interact in relation to risk of respiratory diseases in adults. Methods: Data from the population-based studies, West Sweden Asthma Study (WSAS, n = 23,753) and Obstructive Lung Disease in Northern Sweden studies (OLIN, n = 6519), were used, constituting randomly selected adults aged 20–75 years. Bayesian network analysis was used to estimate the probability for the interaction between smoking and socioeconomic status in relation to respiratory outcomes. Results: Occupational and educational SES modified the association between smoking and the probability of allergic and non-allergic asthma. Former smokers who were at intermediate non manual employees and manual workers in service had higher probability of allergic asthma compared to professionals and executives. Furthermore, former smokers with primary education had higher probability of non-allergic asthma than those with secondary and tertiary education. Similarly, former smokers among professionals and executives had higher probability of non-allergic asthma than manual and home workers and primary educated. Likewise, allergic asthma due to former smoking was higher among highly educated compared to low educated. Conclusions: Beyond their independent roles, socioeconomic status and smoking interact in defining the risk of respiratory diseases. Clearer understanding of this interaction can help to identify population subgroups at most need of public health interventions.

Risk factors that contribute to inter-individual differences in the age-of-onset of allergic diseases are poorly understood. The aim of this study was to identify genetic risk variants associated with the age at which symptoms of allergic disease first develop, considering information from asthma, hay fever and eczema. Self-reported age-of-onset information was available for 117,130 genotyped individuals of European ancestry from the UK Biobank study. For each individual, we identified the earliest age at which asthma, hay fever and/or eczema was first diagnosed and performed a genome-wide association study (GWAS) of this combined age-of-onset phenotype. We identified 50 variants with a significant independent association (P<3x10-8) with age-of-onset. Forty-five variants had comparable effects on the onset of the three individual diseases and 38 were also associated with allergic disease case-control status in an independent study (n = 222,484). We observed a strong negative genetic correlation between age-of-onset and case-control status of allergic disease (rg = -0.63, P = 4.5x10-61), indicating that cases with early disease onset have a greater burden of allergy risk alleles than those with late disease onset. Subsequently, a multivariate GWAS of age-of-onset and case-control status identified a further 26 associations that were missed by the univariate analyses of age-of-onset or case-control status only. Collectively, of the 76 variants identified, 18 represent novel associations for allergic disease. We identified 81 likely target genes of the 76 associated variants based on information from expression quantitative trait loci (eQTL) and non-synonymous variants, of which we highlight ADAM15, FOSL2, TRIM8, BMPR2, CD200R1, PRKCQ, NOD2, SMAD4, ABCA7 and UBE2L3. Our results support the notion that early and late onset allergic disease have partly distinct genetic architectures, potentially explaining known differences in pathophysiology between individuals.

Risk factors that contribute to inter-individual differences in the age-of-onset of allergic diseases are poorly understood. The aim of this study was to identify genetic risk variants associated with the age at which symptoms of allergic disease first develop, considering information from asthma, hay fever and eczema. Self-reported age-of-onset information was available for 117,130 genotyped individuals of European ancestry from the UK Biobank study. For each individual, we identified the earliest age at which asthma, hay fever and/or eczema was first diagnosed and performed a genome-wide association study (GWAS) of this combined age-of-onset phenotype. We identified 50 variants with a significant independent association (P<3x10-8) with age-of-onset. Forty-five variants had comparable effects on the onset of the three individual diseases and 38 were also associated with allergic disease case-control status in an independent study (n = 222,484). We observed a strong negative genetic correlation between age-of-onset and case-control status of allergic disease (rg = -0.63, P = 4.5x10-61), indicating that cases with early disease onset have a greater burden of allergy risk alleles than those with late disease onset. Subsequently, a multivariate GWAS of age-of-onset and case-control status identified a further 26 associations that were missed by the univariate analyses of age-of-onset or case-control status only. Collectively, of the 76 variants identified, 18 represent novel associations for allergic disease. We identified 81 likely target genes of the 76 associated variants based on information from expression quantitative trait loci (eQTL) and non-synonymous variants, of which we highlight ADAM15, FOSL2, TRIM8, BMPR2, CD200R1, PRKCQ, NOD2, SMAD4, ABCA7 and UBE2L3. Our results support the notion that early and late onset allergic disease have partly distinct genetic architectures, potentially explaining known differences in pathophysiology between individuals.

Risk factors that contribute to inter-individual differences in the age-of-onset of allergic diseases are poorly understood. The aim of this study was to identify genetic risk variants associated with the age at which symptoms of allergic disease first develop, considering information from asthma, hay fever and eczema. Self-reported age-of-onset information was available for 117,130 genotyped individuals of European ancestry from the UK Biobank study. For each individual, we identified the earliest age at which asthma, hay fever and/or eczema was first diagnosed and performed a genome-wide association study (GWAS) of this combined age-of-onset phenotype. We identified 50 variants with a significant independent association (P<3x10-8) with age-of-onset. Forty-five variants had comparable effects on the onset of the three individual diseases and 38 were also associated with allergic disease case-control status in an independent study (n = 222,484). We observed a strong negative genetic correlation between age-of-onset and case-control status of allergic disease (rg = -0.63, P = 4.5x10-61), indicating that cases with early disease onset have a greater burden of allergy risk alleles than those with late disease onset. Subsequently, a multivariate GWAS of age-of-onset and case-control status identified a further 26 associations that were missed by the univariate analyses of age-of-onset or case-control status only. Collectively, of the 76 variants identified, 18 represent novel associations for allergic disease. We identified 81 likely target genes of the 76 associated variants based on information from expression quantitative trait loci (eQTL) and non-synonymous variants, of which we highlight ADAM15, FOSL2, TRIM8, BMPR2, CD200R1, PRKCQ, NOD2, SMAD4, ABCA7 and UBE2L3. Our results support the notion that early and late onset allergic disease have partly distinct genetic architectures, potentially explaining known differences in pathophysiology between individuals.

Risk factors that contribute to inter-individual differences in the age-of-onset of allergic diseases are poorly understood. The aim of this study was to identify genetic risk variants associated with the age at which symptoms of allergic disease first develop, considering information from asthma, hay fever and eczema. Self-reported age-of-onset information was available for 117,130 genotyped individuals of European ancestry from the UK Biobank study. For each individual, we identified the earliest age at which asthma, hay fever and/or eczema was first diagnosed and performed a genome-wide association study (GWAS) of this combined age-of-onset phenotype. We identified 50 variants with a significant independent association (P<3x10-8) with age-of-onset. Forty-five variants had comparable effects on the onset of the three individual diseases and 38 were also associated with allergic disease case-control status in an independent study (n = 222,484). We observed a strong negative genetic correlation between age-of-onset and case-control status of allergic disease (rg = -0.63, P = 4.5x10-61), indicating that cases with early disease onset have a greater burden of allergy risk alleles than those with late disease onset. Subsequently, a multivariate GWAS of age-of-onset and case-control status identified a further 26 associations that were missed by the univariate analyses of age-of-onset or case-control status only. Collectively, of the 76 variants identified, 18 represent novel associations for allergic disease. We identified 81 likely target genes of the 76 associated variants based on information from expression quantitative trait loci (eQTL) and non-synonymous variants, of which we highlight ADAM15, FOSL2, TRIM8, BMPR2, CD200R1, PRKCQ, NOD2, SMAD4, ABCA7 and UBE2L3. Our results support the notion that early and late onset allergic disease have partly distinct genetic architectures, potentially explaining known differences in pathophysiology between individuals.

Risk factors that contribute to inter-individual differences in the age-of-onset of allergic diseases are poorly understood. The aim of this study was to identify genetic risk variants associated with the age at which symptoms of allergic disease first develop, considering information from asthma, hay fever and eczema. Self-reported age-of-onset information was available for 117,130 genotyped individuals of European ancestry from the UK Biobank study. For each individual, we identified the earliest age at which asthma, hay fever and/or eczema was first diagnosed and performed a genome-wide association study (GWAS) of this combined age-of-onset phenotype. We identified 50 variants with a significant independent association (P<3x10-8) with age-of-onset. Forty-five variants had comparable effects on the onset of the three individual diseases and 38 were also associated with allergic disease case-control status in an independent study (n = 222,484). We observed a strong negative genetic correlation between age-of-onset and case-control status of allergic disease (rg = -0.63, P = 4.5x10-61), indicating that cases with early disease onset have a greater burden of allergy risk alleles than those with late disease onset. Subsequently, a multivariate GWAS of age-of-onset and case-control status identified a further 26 associations that were missed by the univariate analyses of age-of-onset or case-control status only. Collectively, of the 76 variants identified, 18 represent novel associations for allergic disease. We identified 81 likely target genes of the 76 associated variants based on information from expression quantitative trait loci (eQTL) and non-synonymous variants, of which we highlight ADAM15, FOSL2, TRIM8, BMPR2, CD200R1, PRKCQ, NOD2, SMAD4, ABCA7 and UBE2L3. Our results support the notion that early and late onset allergic disease have partly distinct genetic architectures, potentially explaining known differences in pathophysiology between individuals.