SOCIAL DETERMINANTS IN ASTHMA

Population-based studies on asthma and respiratory symptoms in relation to occupation, occupational exposure and

socioeconomic status

The Obstructive Lung disease in Northern Sweden

Thesis XXI

Christian Schyllert

Department of Public Health and Clinical Medicine Section of Sustainable Health

Umeå 2019

Responsible publisher under Swedish law: the Dean of the Medical Faculty This work is protected by the Swedish Copyright Legislation (Act 1960:729) Dissertation for PhD ISBN: 978-91-7855-068-5 ISSN: 0346-6612 New Series No: 2034 Cover: Bridge between Haparanda and Tornio, photography by Christian Schyllert Electronic version available at: http://umu.diva-portal.org/ Printed by: CityPrint i Norr AB Umeå, Sweden 2019

To mum and dad – working class heroes (it’s something to be)

“Rabbit's clever," said Pooh thoughtfully.

"Yes," said Piglet, "Rabbit's clever."

"And he has Brain."

"Yes," said Piglet, "Rabbit has Brain."

There was a long silence.

"I suppose," said Pooh, "that that's why he never understands anything.”

A.A. Milne, Winnie-the-Pooh

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Table of Contents

Abstract ............................................................................................ iv Background ...................................................................................................................... iv Aim ................................................................................................................................... iv Method ............................................................................................................................. iv Results ............................................................................................................................... v Conclusions ....................................................................................................................... v

Abbreviations .................................................................................. vii Enkel sammanfattning på svenska ................................................. viii

Bakgrund ....................................................................................................................... viii Delarbete I och II .................................................................................................... viii Delarbete III .............................................................................................................. ix Delarbete IV ............................................................................................................... ix

Syfte .................................................................................................................................. ix Metod ............................................................................................................................... ix Resultat ............................................................................................................................. x

Delarbete I .................................................................................................................. x Delarbete II ................................................................................................................. x Delarbete III .............................................................................................................. xi Delarbete IV ............................................................................................................... xi

Sammanfattning .............................................................................................................. xi Slutsats ............................................................................................................................. xi

Original papers .............................................................................. xiii Introduction ....................................................................................... 1 Background ....................................................................................... 3

Asthma, an overview.........................................................................................................3 A historical perspective ..............................................................................................3 Definition of asthma .................................................................................................. 4 Epidemiology today .................................................................................................. 8

Social determinants of health ......................................................................................... 9 Job and occupational exposure ............................................................................... 10 Socioeconomic status ............................................................................................... 11 Behavioural factors .................................................................................................. 12 Social determinants in asthma ................................................................................ 13

Summary ......................................................................................................................... 15 Aims ................................................................................................. 16

Paper I ............................................................................................................................. 16 Paper II............................................................................................................................ 16 Paper III .......................................................................................................................... 16 Paper IV .......................................................................................................................... 16

Materials and Methods .................................................................... 17 Study area ....................................................................................................................... 17

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The OLIN studies ............................................................................................................ 18 Study samples ................................................................................................................ 20

Paper I ...................................................................................................................... 20 Papers II and III ....................................................................................................... 21 Paper IV ................................................................................................................... 22

Data sources ................................................................................................................... 23 The OLIN-questionnaires ....................................................................................... 23 Structured interview – Paper I .............................................................................. 23 Postal questionnaire survey – Papers II and III ................................................... 24 Register – Paper III ................................................................................................ 24 Questionnaire surveys – Paper IV ......................................................................... 24

Definitions...................................................................................................................... 25 Population sample characteristics ......................................................................... 25 Occupations and socioeconomics ........................................................................... 25 Occupational exposure ............................................................................................ 26 Respiratory symptoms, allergy and asthma .......................................................... 27

Statistical methods ........................................................................................................ 29 Ethics .............................................................................................. 30 Results ............................................................................................. 31

Behavioural factors in papers I-IV ................................................................................. 31 Paper I ............................................................................................................................. 31

Asthma and respiratory symptoms ........................................................................ 31 Occupational exposure ............................................................................................. 31 Occupational exposure and concomitant asthma and rhinitis ............................ 32

Paper II........................................................................................................................... 33 Asthma and respiratory symptoms ....................................................................... 33 Socioeconomic status, job and occupational exposure ......................................... 33 Socioeconomic status, job, occupational exposure and their associations with asthma and respiratory symptoms ....................................................................... 33

Paper III ......................................................................................................................... 34 Asthma and respiratory symptoms ....................................................................... 34 Behavioural factors and socioeconomic status ..................................................... 34 Socioeconomic status and asthma and respiratory symptoms ............................35

Paper IV ......................................................................................................................... 36 Asthma in childhood and adolescence ................................................................... 36 Socioeconomic measures and behavioural factors in childhood and adolescence ................................................................................................................................... 37 Socioeconomic status, job and occupational exposure in young adulthood ........ 37 Asthma in childhood and adolescence in relation to socioeconomic status, job and occupational exposure in young adulthood ................................................... 38

Discussion of methodology ............................................................. 39 Epidemiological concepts .............................................................................................. 39

Validity and reliability ............................................................................................ 39 Systematic errors .................................................................................................... 39

Data sources ................................................................................................................... 42 Questionnaire .......................................................................................................... 42

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Register .................................................................................................................... 43 Discussion of main results .............................................................. 44

Cohort-effect .................................................................................................................. 44 Behavioural factors – Smoking and BMI...................................................................... 44 Asthma and respiratory symptoms ............................................................................... 46 Social determinants of health ........................................................................................ 47

Job and occupational exposure ............................................................................... 47 Socioeconomic status .............................................................................................. 50

Conclusions ..................................................................................... 54 Social determinants in asthma ...................................................................................... 54

Future perspectives ......................................................................... 56 Acknowledgement ........................................................................... 58 References ...................................................................................... 60 Appendix ............................................................................................ i

Appendix 1 – AFA insurance in brief .............................................................................. ii Appendix 2 – List of incomesosurces in the LISA-database ......................................... iii Appendix 3 – Short overview of the Swedish education system ................................... iv Appendix 4 - Smoking habits and BMI-categories by income and educational levels in Sweden 2018 ..................................................................................................................... v

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Abstract

Background Asthma is one of the most common chronic obstructive airway diseases among children and adults, with a prevalence between 6-11% in European countries. It is also the most common work-related occupational respiratory disease. There are different methods to classify occupational exposure and, even though there is no clear consensus on which method is the most accurate, the single-item question on exposure to the composite measure vapour, gas, dust or fumes (VGDF) is commonly used in epidemiological research. Low socioeconomic status is associated with asthma and also behavioural factors such as smoking and over-weight, which by themselves are risk factors for asthma. Socioeconomic status is, however, truly a multifaceted concept and using only one measure does not encompass its entire effect on health-related outcomes. Asthma does also have a negative impact on the quality of life among adolescents: they report less physical fitness compared to their peers and more school absenteeism due to respiratory symptoms. Still, research on whether childhood asthma has any impact on socioeconomic status in young adulthood is scarce.

Aim The overall aim is to study social determinants of health such as socioeconomic status, occupation and occupational exposure and their relationship with asthma and respiratory symptoms among adults and further, to evaluate if asthma during childhood or adolescence is associated with social determinants in young adulthood.

Method This thesis includes four papers based on data from the Obstructive Lung Disease in Northern Sweden (OLIN) studies. Papers I-III are cross-sectional studies among adults; a structured interview from clinical examinations between 2002-04 (paper I, n=4036) and postal questionnaire surveys from 2006 (paper II, n=9992) and 2016 (paper III, n=6854) with the addition of register-based data in paper III. Paper IV is a longitudinal prospective cohort study; the first OLIN paediatric cohort followed from 7 to 19 years of age and a postal questionnaire follow-up at ages 27-28 in 2015 (n=2017). Asthma was defined as physician diagnosis (paper I) together with respiratory symptoms (paper II-IV) or use of asthma medication (paper IV). In paper IV asthma was further categorized based on age of onset and persistence throughout childhood

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and adolescence. Main or longest held occupation was used to categorize occupational and socioeconomic groups. In papers III and IV additional measures of socioeconomic status were included; educational level (papers III and IV) and income (paper III). In all papers, occupational exposure to vapour and/or gas, dust and fumes (VGDF or GDF) were taken into consideration and in paper I further divided into subgroups based on a detailed questionnaire on occupational exposure.

Results In paper I we found that the association between occupational exposure to VGDF and asthma and rhinitis was driven by the component of chemicals rather than dusts. In paper II, the ISCO-based manual Swedish Standard Classification of Occupations (SSYK) and the manual Socioeconomic classification (SEI), could both identify occupational and socioeconomic groups at risk for respiratory symptoms and asthma, while the older ISCO-based manual Nordic Classification of Occupations (NYK) was not as sensitive.

In paper III, behavioural risk factors for respiratory symptoms and asthma such as smoking and obesity and, occupational exposure to GDF were associated with low educational level. Interaction analyses between income level and sex revealed different patterns among women and men. Among women, low income was associated with all respiratory symptoms as well as asthma, while among men only with productive cough.

In paper IV, early onset asthma was associated with lower educational level in young adulthood, especially not continuing after compulsory school. Further, those with asthma during childhood or adolescence did not seem to refrain from smoking at age 19, nor did they as young adults seem to avoid occupations with known or expected exposure to GDF.

Conclusions Increased automation in industries have decreased the number of manual workers in industries with typically dirty tasks, meaning that the interrelationships between the subgroups included in VGDF may have changed. This may also affect the meaning of occupational exposure to VGDF, at least with regard to asthma and rhinitis, and according to our findings exposure to the component of chemicals may be the most important. We also found that the use of an ISCO-based manual (SSYK) as well as socioeconomic classification based on job-title (SEI) can be useful and easily applicable tools to identify occupational and socioeconomic groups at risk for respiratory symptoms and asthma. Further, low socioeconomic status is associated with respiratory

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symptoms and asthma. It seems as these associations relies more on low income than low educational level. Low educational level as well as low income are furthermore related to known behavioural risk factors for respiratory symptoms and asthma such as obesity, smoking and, also potentially modifiable risk factors as occupational exposure to gas dust or fumes. Having a persisting asthma since childhood is associated with lower educational level as a young adult. This may, in turn, be related with behavioural risk factors as discussed above and, there were no indications that those with child or adolescent asthma refrained from smoking at age 19. Neither did they in young adulthood avoid occupations with known or expected exposure to gas, dust or fumes, such as manufacturing, construction and transportation work. To conclude, our results indicate a vicious circle with regard to the relationship between the studied social determinants of health and asthma and respiratory symptoms.

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Abbreviations

95%CI 95% confidence interval ARC Allergic rhinoconjunctivitis ATS American Thoracic Society BCE Before the Common Era BMI Body Mass Index CE Common Era COPD Chronic Obstructive Pulmonary Disease ECRHS European Community Respiratory Health Survey ETS Environmental tobacco smoke GA2LEN Global Allergy and Asthma European Network GDF Gas, dust or fumes GINA Global Initiative for Asthma HWE Healthy worker effect ILO International Labour Organization ISAAC International Study of Asthma and Allergies in Childhood ISCED International Standards of Classification of Education ISCO International Standard of Classification of Occupations IUATLD International Union Against Tuberculosis and Lung Disease JEM Job-exposure matrix LISA Longitudinell integrationsdatabas för sjukförsäkrings- och arbetsmarknadsstudier Longitudinal integrated database for health insurance and labour market studies MRC Medical Research Council ns Statistical non-significance NSAID Non-steroidal anti-inflammatory drugs NSI National statistical institute NYK Nordisk Yrkesklassificering Nordic Classification of Occupations OECD Organisation for Economic Co-operation and Development OLIN Obstructive Lung disease in Northern Sweden OR Odds ratio PY Pack-years SEI Socioekonomisk indelning Socioeconomic Classification SES Socioeconomic status SoB Shortness of breath SSYK Standard för svensk yrkesklassificering Swedish Standard Classification of Occupations SUN Svensk utbildningsnomenklatur Swedish Standards of Classification of Education UK United Kingdom US United States UNESCO United Nations Educational, Scientific and Cultural Organization USD United States dollar VGDF Vapours, gas, dust and fumes WHO World Health Organization

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Enkel sammanfattning på svenska

Bakgrund Astma är en av de vanligaste kroniska obstruktiva lungsjukdomarna både hos barn och vuxna med en prevalens mellan 6-11% hos vuxna och 10-15% hos barn. Astma är associerat med allergi och det finns en ärftlig komponent. Bland andra kända riskfaktorer bör livsstilsfaktorer som tobaksrökning och övervikt nämnas men även yrkesexponering för gaser, damm och rök och andra miljöfaktorer. Tidigare studier har visat att astma varit associerat till hög socioekonomisk status men fler och fler studier har under senare tid visat på motsatsen. Hälsans sociala bestämningsfaktorer innefattar de förhållanden där vi föds, växer upp, utbildar oss, arbetar, bildar familj och så småningom dör. Dessa faktorer påverkar var och hur vi lever likväl som förväntad livslängd och dödlighet. Ojämn fördelning av dessa bestämningsfaktorer beror på sociala ojämlikheter och påverkar riskfaktorer för sjukdom.

Relationerna mellan socioekonomisk status, luftvägssjukdom och påverkningsbara beteendefaktorer är komplexa. Både låg utbildning och låg inkomst är associerade med nyinsjuknande i astma, ökade luftvägssymtom och försämrad astma-kontroll samtidigt som de också är associerade till livsstilsfaktorer som utgör kända riskfaktorer för luftvägssymtom såsom rökning och övervikt. Yrkesexponering för gas, damm och rök utgör i sig en riskfaktor för astma men är också vanligare i yrkesgrupper som vid socioekonomisk klassificering baserat på yrke räknas till låg socioekonomisk status.

Delarbete I och II Det finns flera sätt att definiera yrkesexponering varav ett, inom epidemiologin, etablerat sätt är en fråga om exponering för gas, damm och/eller rök. och det är känt att den övergripande engelska termen VGDF (vapours, gas, dust and fumes; ångor, gaser, damm och rök) är associerat till astma och rinit. De olika ingående delkomponenterna kan dock ha olika betydelse som riskfaktorer för astma och rinit. Samtidig analys av VGDF och dess delkomponenter som kemikalier, organisk och oorganiskt damm och hur de associerar till astma och rinit, är dock inte tidigare gjort. Ett annat sätt att definiera yrkesexponering är genom att konstruera ett JEM (job-exposure matrix; yrkesexponeringsmatris) där experter inom yrkes- och miljömedicin klassificerar yrkestitlar i olika grupper baserat uppskattad exponeringsgrad för substanser relaterade till sjukdom (t.ex. astma). Det finns även andra sätt att klassificera yrken på. Det finns idag två aktuella system för gruppering av yrken baserat på yrkestitel som är aktuella och ges ut av Statistiska Centralbyrån, Standard för svensk

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Yrkesklassificering 2012 (SSYK) och Socioekonomisk Indelning (SEI). Ett äldre, tidigare använt system är Nordisk Yrkesklassificering (NYK). SSYK och NYK grupperar yrken med fokus på arbetsuppgifter, medan SEI tar större hänsyn till socioekonomiska aspekter såsom utbildningsnivå. SSYK och NYK är baserade på system framtagna av Internationella arbetsorganisationen (International Labour Organization, ILO). Det är dock oklart i vilken omfattning dessa tre klassificeringssystem, SEI, SSYK och NYK, kan användas för att identifiera yrkesgrupper med ökad risk för luftvägssymtom.

Delarbete III Socioekonomisk status är ett mångfacetterat begrepp men de tre vanligaste måtten som används som indikatorer för socioekonomiskt status är inkomst, utbildningsnivå och gruppering baserat på yrkestitel. De har förmodligen olika betydelse för olika hälsorelaterade utfall, och inget enskilt mått kan omfatta alla hälsorelaterade, socioekonomiska aspekter. De flesta studier värderar dock enskilda indikatorer för socioekonomisk status. Genom att kombinera ett epidemiologiskt populationsurval med säkra frågor gällande yrkes-titel, luftvägssymtom och astma med register-baserade data av hög kvalité på inkomst och utbildningsnivå, kunde de tre vanligaste måtten på socioekonomisk status studeras i förhållande till astma och luftvägssymtom i ett och samma populationsurval.

Delarbete IV Det är känt att låg socioekonomisk status är associerat till insjuknande i astma, och försämrad astma-kontroll av, både hos barn och vuxna. Det finns få studier som rekryterar barn och följt dem till vuxen ålder, där det också finns data gällande insjuknande och remission av astma under barn- och ungdomsåren. Det är oklart i vilken omfattning förekomst av astma under barn- och ungdomsåren påverkar socioekonomiskt status i ung vuxen ålder.

Syfte Det övergripande syftet var att studera olika sociala bestämningsfaktorer såsom socioekonomisk status, yrke och yrkesexponering och hur dessa associerar till astma och luftvägssymtom hos vuxna samt att studera huruvida astma i barn- och ungdomsåren påverkar sociala bestämningsfaktorer i ung vuxen ålder.

Metod Avhandlingen inkluderar fyra delarbeten som baseras på befolkningsundersökningar i Norrbotten inom ramen för det epidemiologiska forskningsprogrammet Obstruktiv Lungsjukdom i Norrbotten (OLIN)

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studierna. Delarbete I är baserat på intervjuer av 4036 vuxna individer som gjordes mellan 2002-04; samtliga individer som tidigare medverkat vid kliniska undersökningar bjöds in till dessa undersökningar. Delarbete II och III är baserat på slumpurval av vuxna individer som inbjöds till postala enkätundersökningar 2006 (delarbete II, 9992 individer deltog) respektive 2016 (delarbete III, 6854 individer deltog). Till individerna som svarade på enkäten 2016 (delarbete III) kopplades även data från Statistiska Centralbyråns longitudinella integrationsdatabas för sjukförsäkrings- och arbetsmarknadsstudier, med information om bland annat inkomst och utbildningsnivå. Delarbete IV baseras på en enkät-uppföljning i ung vuxen ålder (27-28 år gamla) av OLINs första barnkohort. Deltagarna rekryterades 1996 vid 7-8 års ålder och sedan följts årligen fram till 19 års ålder. Delarbetet baserades på de 2017 individer som deltagit vid samtliga tillfällen, vid 7-8, 11-12, 19 och 27-28 års ålder.

Resultat

Delarbete I Studien bekräftade tidigare kända associationer mellan yrkesexponering för VGDF och astma och rinit. Dessutom fann vi med hjälp av detaljerade frågeformulär om yrkesexponering att exponering för kemikalier (t.ex. hårvårdsprodukter, färger, lacker, bekämpningsmedel) var den drivande faktorn bakom associationerna mellan VGDF och astma och rinit. Detta samband kvarstod även då substanser som man vet är associerade till astma, som isocyanater, exkluderats från kemikaliegruppen. Män rapporterade generellt mer yrkesexponering för VGDF än kvinnor och hos män fanns ett samband mellan astma och oorganiskt damm.

Delarbete II Baserat på SSYK-systemet hade yrkesgrupperna administratörer, service, byggnads-, och tillverkningsarbetare hade ökad risk för hosta och pipande/väsande andning jämfört med chefsyrken. Detta stämde väl överens med SEI-systemet där grupperna arbetare inom industri och service samt tjänstemän på både låg- och mellannivå hade liknande mönster i jämförelse högre tjänstemän inklusive fria yrkesutövare inom akademikeryrken och företagare. Således, genom att använda de redan etablerade systemen SSYK och SEI kunde vi identifiera yrkesgrupper med ökad risk för luftvägssymtom och astma. Däremot var inte NYK lika känsligt, vilket kan förklaras med att system är äldre och har blivit ersatt med SSYK. Genomgående fanns inga uppenbara skillnader mellan könen.

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Delarbete III Låg utbildning var tydligt associerat till kända riskfaktorer för luftvägssjukdom; livsstilsfaktorer som rökning och övervikt, men också yrkesexponering för gas, damm och rök. Låg inkomst föreföll, framförallt hos kvinnor, vara en starkare riskfaktor än låg utbildningsnivå för astma och luftvägssymtom, oberoende av ålder, rökning, BMI, fuktskador i hemmet och yrkesexponering för gas, damm och rök. Luftvägssymtom som pipande/väsande andning, attackvis andfåddhet och hosta var alla tydligt associerade med låg socioekonomisk status, medan astma var relaterat till både hög och låg socioekonomisk status beroende vilken indikator som användes.

Delarbete IV Astma under barn- och ungdomsåren var associerat till lägre utbildningsnivå än universitetsstudier hos unga vuxna. Astma med debut i barndomen är framförallt associerat till att inte fortsätta sina studier från grundskolan, oberoende av socioekonomisk status i familjen under uppväxten. Hos kvinnor var det framförallt astma som kvarstod under barn- och ungdomsåren som visade detta mönster, medan det hos män var astma som debuterade i barndomen men som gått i remission under ungdomen. Vi fann dock inte att unga vuxna med astma under barn- och ungdomsåren undvek yrken med risk för exponering för gaser, damm eller rök.

Sammanfattning Vi fann att yrkesexponering för kemikalier var den faktor som drev den observerade associationen mellan det övergripande och komplexa begreppet VGDF och astma samt rinit. De redan etablerade systemen SSYK och SEI som grupperar yrken baserat på yrkestitel kan användas för att identifiera yrkesgrupper med ökad risk för luftvägssymtom. Låg inkomst förefaller vara en starkare riskfaktor för astma och luftvägssymtom än låg utbildning, framförallt hos kvinnor. Astma med debut före 12 års ålder är associerat med en låg utbildningsnivå i ung vuxen ålder, bland kvinnor tydligast hos dem med kvarstående astma under ungdomen medan bland männen hos dem med astma som gått i remission. Det fanns dock inte några tecken på att individer med astma i barn- och ungdomsåren undvek yrken med ökad risk för yrkesexponering för gas, damm och rök.

Slutsats Studierna visar att det finns ett samband mellan astma under barn- och ungdomsåren och lägre utbildning i ung vuxen ålder. Låg utbildning utgör i sin tur riskfaktor för rökning och övervikt men också yrkesexponering för gas, damm och rök vilket är kända riskfaktorer för luftvägssymtom och astma. Bland

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vuxna har låg inkomst, en indikator för låg socioekonomisk status, samband med astma och luftvägssymtom. Det förefaller således finnas en ond cirkel där socioekonomiska bestämningsfaktorer inverkar på riskfaktorer för och förekomst av astma och luftvägssymtom vilket involverar såväl barn som vuxna. Ökad kunskap om och förståelse för dessa samband kan bidra till underlag för riktade folkhälsointerventioner som utöver livsstilsfaktorer även inkluderar insatser som stöd under skolgång, studentrådgivning och yrkesvägledning. Målet för astmabehandling är symtomfrihet och astma inte ska ha någon negativ inverkan på det dagliga livet. För detta kan det behövas insatser som större folkhälsointerventioner för att minska bördan av rökning och övervikt men även riktade insatser med ökad patientutbildning gällande astma och dess potentiella negativa effekter, och tidiga förebyggande som extra stöd i skolan, studentrådgivning och yrkesvägledning.

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Original papers

I. Schyllert C, Rönmark E, Andersson M, Hedlund U, Lundbäck B, Hedman L, Lindberg A. Occupational exposure to chemicals drives the increased risk of asthma and rhinitis observed for exposure to vapours, gas, dust and fumes: a cross-sectional population-based study. Occup Environ Med. 2016 Oct;73(10):663-9.1

II. Schyllert C, Andersson M, Hedman L, Ekström M, Backman H, Lindberg A, Rönmark E. Job-titles classified into socioeconomic and occupational groups identify subjects with increased risk for respiratory symptoms independent of exposure to vapours, gas, dust and fumes. Eur Clin Respir J. 2018 May 15;5(1):1468715.2

III. Schyllert C, Lindberg A, Hedman L, Stridsman C, Ilmarinen P, Piirilä P, Krokstad S, Lundbäck B, Rönmark E, Backman H. Low socioeconomic status is associated with asthma and respiratory symptoms in northern Sweden, especially among women – The OLIN and Nordic EpiLung studies. In manuscript.

IV. Schyllert C, Rönmark E, Andersson M, Backman H, Lindberg A, Hedman L. Childhood asthma affects educational level in young adults – a prospective cohort study. Submitted.

1 Published with permission under author’s license

2 Published in paper with open access

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Introduction

Health inequalities are preventable differences in health-related outcomes. Due to several public health measures, smoking and alcohol consumption in Sweden is lower than in Europe in general. Still about a quarter of all disease in Sweden can be attributed to modifiable or behavioural risk factors, mainly related to smoking, diet, alcohol or sedentary lifestyle (1). These risk factors are more prevalent among individuals with low income or low education (2) and living in deprived and socially vulnerable areas (3). In England, living in the most deprived areas are related to a seven years shorter life expectancy compared to the most affluent areas (3), and while life expectancy in Sweden generally is high, individuals with a higher, post-secondary education have a 6 year longer life expectancy than those with only compulsory education (4,5). Although access to healthcare and medicine in Sweden is available to all residents equally by law (6), some geographical inequalities exists (1); local county councils or caregivers can decide to not accept certain medical treatment options due to budget restrictions and can also experience difficulty recruiting physicians and nurses leading to short-staffed caregivers (7).

Figure 13 – Development of A) Gini coefficient4 and B) Percentage of individuals at risk of poverty5 in Sweden between 1991-2016. Data from Statistics Sweden.

3 The statistics are based on the surveys Household Finances (1975-2013) and Incomes and taxes (from 2011). Due to that a break occurs in the time series when the statistics change source figures are presented in parallel for the years 2011–2013.

4 The Gini coefficient is a number measuring the degree of inequality in a distribution. It is used to measure how far a country's wealth or income distribution deviates from a totally equal distribution (Gini coefficient=0).

5 At risk of poverty or a low-income standard is defined as having an equalized disposable income less than 60% of the Swedish median by Statistics Sweden.

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Sweden is regarded as a high-income country according to the World Bank standard (8) and one of the most equal OECD-countries. However, it has seen a surge of income inequality since the 1990’s (figure 1), the most rapid increase among all OECD-countries (9,10). Income inequality is likely to act by strengthening many causal processes through which social class imprints itself on people throughout life (11–13). Decreased income inequality could lead to increased life expectancy, improvement in quality of life of many individuals as well as lead to governmental expenditure savings from for example physical and mental illness (11,14).

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Background

Asthma, an overview

A historical perspective The word asthma is a derivative of the Greek word aazein meaning to gasp for breath or to pant heavily and was first described by Hippocrates (460 BCE) (15). However, the earliest records of respiratory symptoms and distress comes from ancient China where “noisy breathing” was described in 2600 BCE, something akin to what we today would call wheezing (16,17). There are many tales of herbal remedies: in India, smoking stramonium (an anticholinergic drug) was used to relax the airways when Alexander the Great invaded in 327 BCE. Pliny the Elder (Rome, 50 CE) also recommended ephedra to treat these symptoms, although this drug had already been used in ancient China. Ephedra was later used to extract ephedrine (16–18).

Figure 26 – Historical treatment options for asthma: A) Mudge inhalator invented in 1778 using hot water-steam with opium to cure catarrhous cough. B) Adrenaline inhaler used in the 1930’s to inhale Adrenalin Chloride (epinephrine) solution 1:100 to reverse bronchial constriction. C) Page’s asthma cigarettes from the 1960’s, not containing tobacco, but stramonium (anticholinergic), tea leaves, chestnut leaves, and gum benzoin.

Both Hippocrates and Pliny the Elder recognized the importance of environmental agents. The former described that aazein was more prevalent among metal workers and tailors, while the latter found that pollen could trigger respiratory symptoms (16). In more modern history, Henry Hyde Salter (1823-1871) (19,20) was a major contributor to how we understand and describe asthma today. He classified stimuli triggering acute episodes as extrinsic (such as cold air, chemical irritants, sneezing etc.) but also realized that these factors

6 © Inhalatorium 2019. All Rights Reserved, published with permission.

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were not the root cause of the condition. He believed asthma to be based on both neural and vascular mechanisms: “The inflammation or congestion of the mucous surface appears to be the stimulus that, through the nerves of the air tubes, excites the muscular wall to contract” (15,19), and this idea was long supported by others (21).

A modern understanding of asthma starts to form in the 20th century, with the idea of asthma and its relation to allergy starting to gain ground at the turn of the century (21). Between the 1920’s and 1970’s numerous studies found different mediators that had a fundamental effect on the airways of patients suffering from asthma, such as histamine, prostaglandins and leukotrienes. Further research highlighted the importance of mast cells, basophils and eosinophils and implemented the concept of asthma as an inflammatory disease (15).

Definition of asthma The definition of asthma has changed over the years. At the CIBA guest symposium in 1959 asthma was defined has having an intermittent or reversible airway obstruction (22). Later, the hyperresponsiveness of the airways as well as variable bronchial obstruction were added (23,24). The definition expanded in the 1990’s to include the inflammatory component (25), and it is still this combined definition that is used in the Global Initiative for Asthma (GINA) strategy document (26):

“Asthma is a heterogeneous disease, usually characterized by chronic airway inflammation. It is defined by the history of respiratory symptoms such as wheeze, shortness of breath, chest tightness and cough that vary over time and in intensity, together with variable expiratory airflow limitation.”

However, recent research indicates that asthma is an even more complex and multifaceted disease (27–29) with several subgroups, phenotypes and endotypes (figure 3) such as allergic, eosinophilic, exercise-induced, obesity-related, work-related etc. with different clinical features, therapeutic response and pathophysiology (28). The Lancet Commission “After asthma: redefining airway diseases” from 2018 recommends that asthma, again, should be used as a description of symptoms, without pathophysiological assumptions (29), the most common symptoms being cough, shortness of breath, wheezing or whistling and a sense of chest tightness (26,30).

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Figure 37–The complexity of asthma

Thus, defining asthma and its subgroups can be a challenge, both in a clinical setting as well as in epidemiological research. Due to this complexity, there have been, and still is, both an under- and overdiagnosis of asthma (31–33), meaning that the question regarding physician-diagnosed asthma has its weaknesses. However, used together with questions on respiratory symptoms or with information on use of medication, will increase the sensitivity, but, at the same time, decrease the specificity since they are not necessarily pathognomonic for asthma (33–35).

Nonetheless, using a validated questionnaire on diagnoses, symptoms and medication has shown to be a reliable source of information and remains in use (36–39). Since the 1960’s several questionnaires have been developed for use in epidemiological research on asthma of which the following are only a few examples: the British Medical Research Council (MRC) questionnaire (40,41), which have since been revised (42), the US National Heart, Lung and Blood Institute (43), the Tucson study (44), the American Thoracic Society (ATS) (45) and in 1984-85, the Obstructive Lung Disease in Northern Sweden (OLIN) questionnaire was developed (46).

In summary, there are several subgroups of asthma, of which four are described below.

7 All pictures CC0 1.0 Public Domain, composition by C Schyllert

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Allergic and non-allergic asthma A broad and well-known classification of asthma is the division of asthma into allergic and non-allergic asthma. Asthma is in many cases closely related to allergic diseases such as eczema, atopic dermatitis, allergic rhinoconjunctivitis and allergic sensitization (47–53) thus constituting an allergic asthma which usually debuts earlier in life than non-allergic asthma (54,55). Allergic asthma is also closely related to a hereditary component; a family history of asthma or allergy increases the risk of allergic asthma (56). Non-allergic asthma is more common among adults and adult-onset asthma (54,57,58). While nasal symptoms exist in both phenotypes, non-allergic asthma is associated to nasal polyposis rather than allergic rhinitis. Intolerance to non-steroidal anti-inflammatory drugs (NSAID) is also associated with non-allergic asthma (55,59). The co-existence of asthma, NSAID-intolerance and nasal polyposis is a well-known syndrome, Samters triad.

Figure 4 – Work-related asthma

Work-related asthma Asthma is considered work-related if the symptoms are clearly associated with the work conditions (such as worsening during work or relief during time off). Occupational exposure to vapours, gas, dust and fumes (VGDF) is a known risk factor for asthma and contributes to around 15% of all adult-onset asthma (60–62). Work-related asthma (figure 4) includes two major entities: work-exacerbated asthma and occupational asthma, where the former is a condition worsened due to non-specific work conditions and the latter an asthma induced by specific exposures in the work environment (60,63,64).

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The frequency of occupational asthma varies between types of industries and depend on the inhaled agent, level and duration of exposure, industrial preventative measures and host factors (64). To determine if asthma is work-related, a precise diagnosis is required as this can have considerable effect on the individuals’ vocational future and a diagnosis of 0ccupational asthma can also make the individual eligible for workers compensation. In Sweden, this requires a diagnosis of asthma as defined above, together with occupational exposure to a known asthma-genic agent as well as a temporal relationship between exposure and symptoms (64).

United airways disease Nasal symptoms such as nasal congestion or runny nose are common among both children and adults, with a prevalence varying from around 10 to 25% in European countries (65–69). Between 50-80% of individuals with asthma also have nasal symptoms, likewise a large proportion of individuals with rhinitis also have asthma (ranging from 10-50%) (70–75) but as described above, the ground cause of the nasal symptoms may differ. While rhinitis can be a risk factor for asthma and vice versa, the upper and lower respiratory tracts can be considered as one unit, thus asthma and rhinitis may constitute parts of the same the disease; the united airway disease (70,71,76,77).

The idea is not new; Aulus Cornelius Celsus (Rome, 25 BCE-50 CE), documented the medical knowledge of the Roman Empire in his work De Medicine, and noted the possibility of a united airways when discussing lung infections emanating from the nose. Claudius Galenus (Rome 129-216 CE), physician and enthusiastic anatomist, described the upper respiratory tract in great detail and supported the idea that the nose was only the beginning of the respiratory tract (78).

While the upper and lower respiratory tracts share respiratory epithelium and mucosal sensibility, the mechanism behind airway obstruction differ between the two: the upper respiratory tract through vascular swelling and the lower respiratory tract by contraction of smooth muscle fibers. They are however, functionally linked: a nasal irritation can lead to a bronchial obstruction (71,77).

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Epidemiology today Asthma is one of the most common chronic obstructive airway diseases among adults and children (79), with a prevalence between 6-11% among adults and 10-15 % among children in European countries (56,80–83). Further, work-related asthma (figure 4) is the most common occupational respiratory disease (62). Asthma usually presents in childhood and while there is a high degree of remission in adolescence, with a risk of relapse in adulthood, persisting asthma throughout childhood and adolescence has a low likeliness to remit in adulthood (84–86). Childhood asthma is more prevalent among boys, while in adulthood, asthma is more prevalent among women. This shift can be explained by a high incidence rate among adolescent girls combined with a high degree of remission among boys (56,86–89).

During the second half of 20th century, Europe has seen a dramatic increase in asthma prevalence, from 2-4% to 6-11% (90). These trends are found both among children and adults, and have been more pronounced in high-income countries as well as urbanized megacities in low- and middle-income countries (56,80,90,91). The increasing urbanization has been proposed as one reason, but increased asthma-awareness in the general population could also mean that individuals with respiratory symptoms are more prone to seek medical attention, which may contribute to an increase diagnosis of asthma. However, there is also a disparity between epidemiological studies on how to define asthma (e.g. only physician diagnosis of asthma, the use of asthma-medication, or a selection of symptoms and if so, which ones?), that can lead to differences in prevalence estimates (90,91). In adults, and particularly among smokers, it can be difficult to differentiate between asthma and COPD (chronic obstructive pulmonary disease), a review found that nearly 30% of all COPD also features components of asthma (92).

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Social determinants of health Social determinants of health (figure 5) include the conditions in which we live, give birth, age, work and educate ourselves. These conditions influence the risk of illness and perceived illness as well as life expectancy and mortality. Uneven distribution of social determinants is the result of social inequities. Over the last centuries, health has improved greatly in Europe, but it has not been evenly improved across the continent or even across countries (93,94).

Figure 5 – Illustration of social determinants of health, model by Dahlgren and Whitehead (94)

There is a multitude of factors affecting our health and wellbeing; behavioural (smoking, alcohol consumption), physiological (obesity, high blood pressure), demographic (age, sex) and environmental (social settings, air pollution) (95,96). Multimorbidity is usually defined as a combination of diseases or conditions that presumably makes the individual “ill”. Most research on which factors (except strictly medical factors) that contribute to multimorbidity focus on sex, education and income, and less so on ethnicity, occupation or a more complex definition of socioeconomic status than income alone (97). Children growing up in poverty have an increased risk of “adverse childhood experiences” which in turn can have long-term effect on physical and mental health, both personally and in the family and ultimately a low socioeconomic status that may be carried over generations (98). Some social determinants are difficult to address for the individuals themselves; for example, you can’t choose where, or to whom, you are born. Poverty or low socioeconomic status is related to living in deprived areas with neglected housing and life-style factors such as smoking

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and obesity, each of which constitute risk factors for respiratory and allergic symptoms and diseases (99). In summary, the social determinants of health can be seen as working on a macro-level, being the cause of the cause of the disease.

Job and occupational exposure Bernardino Ramazzini (Italy, 1633-1714) is a key figure in occupational medicine. With his work De Morbis Artificum Diatriba (100) he presented a systematized text of occupational disease after visiting workplaces, observing the workers and discussing their ailments with them. He also recognized that not only could environmental exposure to irritants be the cause of illness, but also that repetitive tasks and posture, leading to a prolonged trauma, could contribute to disease (101).

Modern research on occupational asthma and rhinitis has been carried out both on specific workplaces and –tasks, as well as on a general population level. Exposure to VGDF is clearly associated with asthma, COPD, rhinitis, impaired lung function and other respiratory symptoms such as wheezing and shortness of breath (62,75,110–112,102–109) and a myriad of agents have been identified to cause asthma; some examples include high-molecular weight agents such as mould, flour and enzymes and low-molecular-weight agents such as diisocyanates, biocides and metals (113). Occupational asthma generally has a poor prognosis (114,115). A review from 2014 found that 75% had persisting bronchial hyperresponsiveness and ca 30% of those suffering from occupational asthma remained unemployed after diagnosis and following dismissal, with associated loss of income (115). Exposure cessation improves the prognosis, but this may require the individual leaving the job and workplace with risk of reduced income and unemployment (116). Further, the costs of occupational asthma is high and seldom falls on the employer but instead on the state or the affected individuals themselves (62). However, existing Swedish social security systems will, to some degree, support individuals with work injuries, including diseases caused by work (appendix 1) (117).

In epidemiological research on occupational exposure and asthma, two common ways to assess occupational exposure are either to use a job-exposure matrix (JEM) or to use the single-item question “have you, in your work, been exposed to vapours, gas, dust and/or fumes?” (VGDF). A JEM is considered a more objective way to measure occupational exposure; job titles are collected whereafter professionals such as occupational hygienists or physicians classify each job title into groups based on estimated levels of exposure to harmful (or potentially harmful) agents. The single-item question of exposure to VGDF is based on self-reported data with a risk of recall bias, i.e. that individuals suffering from asthma or respiratory symptoms are more prone to report

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occupational exposure. However, studies have shown that the differences between the two methods are less than expected. Thus, there is no consensus on whether one method is better than the other, and a single-item question of exposure to VGDF is considered applicable in epidemiological research (118–120).

Classification of occupations The intended use of classifying occupations into clearly defined groups based on job assignments is for statistical purposes such as identifying occupational areas lacking in workers and organize information between job vacancies and job applicants (121–124). It can potentially also be used to stratify population samples and identify social mobility over time, economic distribution or recruitment imbalance (121,122,125). In Sweden, Statistics Sweden has developed the Swedish Standard Classification of Occupations (SSYK – Standard för svensk yrkesklassificering). The latest update of SSYK released in 2012 (126) is based on the International Standard Classification of Occupations (ISCO) -08. The Nordic Classification of Occupations (NYK – Nordisk yrkesklassicificering) antecedes SSYK and was released in its latest version in 1983 and based on ISCO-58. A revision from NYK to SSYK was found to be necessary due to archaic descriptions making it difficult to fit into a more modern context (127).

Socioeconomic status Socioeconomic status (SES) is a multifaceted factor that is important to take into consideration in population-based studies of health and illness. There are many indicators of SES and using only one measure does not encompass the entire effect of SES on health-related outcomes (128,129). In this thesis, mainly three different ways have been used to define SES, as described below.

Educational level Educational level is a commonly used indicator of SES. It can be considered a form of received SES from the family with, for example, the intellectual and material resources to influence access to, and performance in, compulsory and secondary schools. A high level of education may also make the individual more receptive to health education. However, measuring the number of years of education do not take into account the quality of the education given (128,129), nor does it take into account employment status or current income of the individual.

Income Income is the SES-indicator that most directly measures material resources. As with high education, a higher material wealth can give access to health

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commodities and services. For younger and older individuals, income may be a less reliable indicator of SES due to income usually following a curvilinear trajectory with age. To compare income between households, additional information can be used to adjust for family size and living-costs (128,129). Absolute poverty is defined as not having enough for basic needs, the United Nations Educational, Scientific and Cultural Organization (UNESCO) defines this as a daily income of USD 1 or less. In high-income countries, a measure of relative poverty may be more useful as this puts the individuals’ income in relation to the rest of the society (130). There is no one clear definition of what is low or high income. One way is to divide into deciles or quintiles (131). Another way to define a low-income standard is to have an income of less than 60% than the national median income (132) while high income can be defined as 200% of the national median income (133).

Job-title Using current or longest held job is another common way to characterize SES. Occupation is strongly associated with income and also reflects social standing, both of which may influence health by access to services. Using this method, however, usually excludes individuals such as students, unemployed or retirees. Previous held job can be used, but this may not necessarily reflect the current SES of the individual (128,129). In the 1980’s Statistics Sweden developed a socioeconomic classification system (SEI – Socioekonomisk indelning) (134). The system is based on job title, broadly grouped into blue- and white-collar workers, professional and executives and self-employed. Further division is based on educational- and skill level. If the individual is currently not working, previously held job is used, but additional coding is added based on the reason of being off work (e.g. student, retired, sick leave, parental leave or conscription). The manual in itself has not been updated, but new job titles are continuously coded and added to the list (134,135).

Behavioural factors

Smoking and obesity It is generally accepted that tobacco smoking and obesity are related to morbidity and mortality. Through public health initiatives, the prevalence of smoking has decreased throughout the years in Sweden. Still, there is a social gradient: while the prevalence of current smoking in Sweden 2018 is low (7%), it is considerably higher among individuals with low education or income. Overweight and obesity is a growing problem in Sweden and also here a social gradient exists, with obesity being more common among individuals with lower SES (figure 6).

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Figure 6 – Changes in smoking habits and BMI between 2004-2018 by income and educational levels, data from the Swedish Public Health Agency

Social determinants in asthma Globally, low SES and poverty are associated to risk factors for illness (136,137), perceived illness, diseases such as asthma (138–140) and poor asthma control (141,142), as well as impaired general health (143) and limitations in activities for daily living (144). Low education is associated with incident asthma and respiratory symptoms (139,145) and increased asthma morbidity (146). In a cohort from the 1960’s UK, fathers low socioeconomic status based on job-title was related to asthma in young adulthood (147). Low socioeconomic status is also related to obesity (148), smoking and living in areas more exposed to air pollution, all of which are risk factors for asthma (149–151). Further, being diagnosed with occupational asthma can have an negative impact on the socioeconomic status of the individual with potential loss of employment and reduced income (152–154).

It is well established that respiratory symptoms and asthma may be caused by occupational factors. There are different methods to classify occupational exposure; in large population-based studies, occupational exposures can be assessed by (i) using a JEM based on job title, (ii) using a single-item question

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Socio-economic

status

Respira-tory

disease

Risk factors

of exposures to VGDF or, (iii) classifying job-titles in different categories, not based on risk for illness, but based on for example skill-levels and tasks. There is no clear consensus on which method is the most accurate. The purpose of the study must also be considered regarding what method to use; if it is to assess the risk for asthma, maybe a JEM is more appropriate, but if more sociological aspects are to be investigated, other systems to classify job-titles may be better suited. Further, while a single-item question on VGDF is a well-established method to assess occupational exposure, VGDF includes a large number of both specific and non-specific agents, and it is unclear to what extent the different components explain the observed association with respiratory symptoms and conditions.

A systematic review found evidence of low socioeconomic status (with various definitions such as education level or personal or household income or housing status) being related to asthma (155). But; how SES and asthma correlate can be difficult to disentangle: does asthma lead to low SES, or does low SES lead to asthma, or does low SES lead to risk factors that lead to asthma? It is of importance to evaluate different indicators of SES to be able to understand the complex association between low SES and asthma.

Research on whether childhood asthma has any impact on socioeconomic status in young adults is scarce. A review from 2004 found inconsistent evidence (156), but there are studies showing that chronic illness in childhood can lead to poorer academic career (157). Asthma has a negative impact on the quality of life among adolescents (158–160), they report less physical fitness compared to their peers and more school absenteeism due to respiratory symptoms (159,161) in comparison to those without asthma, and the school attendance in this age group (14-15 years old) did not improve over a ten-year period, from 2003 to 2013, in northern Sweden (159). A US report likewise showed that asthma was associated with many lost days of schooling (162). Extensive school absence may affect school performance, subsequent vocational and educational choices and socioeconomic status in adulthood. ?

?

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Childhood asthma

Low education

Smoking, obesity, VGDF-

exposure

Respiratory symptoms

Low income

Low family SES

Summary Low socioeconomic status is related to asthma and respiratory symptoms. Occupational exposure is a considerable risk-factor for asthma to which 15% of all adult asthma can be attributed. Work-related asthma can be detrimental with respect to the possible need to change workplace or occupation with risk of lower salary or even unemployment which in turn can affect socioeconomic status.

Using the composite measure VGDF is well established when assessing occupational exposure, but are there components in this wide term more strongly related to respiratory symptoms? Further, if data on occupational exposure is lacking and a job-exposure matrix to costly, can existing ISCO-based manuals be used as proxies for occupational exposure and identify occupational groups at risk for respiratory symptoms?

The associations between socioeconomic status, respiratory disease and behaviouralmodifiable and risk factors for respiratory disease are complex.

Smoking, obesity and occupational exposure are examples on factors related to socioeconomic status as well as to respiratory disease. Socioeconomic status is also a complex concept and can be defined by numerous different measures. Does it make any difference what measure we use, and do different measures relate differently to respiratory disease?

Low socioeconomic status is related to asthma both among children and adults, but it is still largely unknown if asthma in childhood is associated with low socioeconomic status in adulthood.

In summary, the associations between asthma and social determinants such as occupation, occupational exposure and socioeconomic status is complex and multifaceted and it is necessary to approach the matter from different angles to elucidate these complex associations.

?

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Aims

The overall aim of this thesis is to study social determinants such as socioeconomic status, occupation and occupational exposure and their relationship to asthma and respiratory symptoms among adults. Furthermore, to evaluate if asthma during childhood or adolescence is associated with these social determinants in young adulthood.

Paper I To evaluate the association between occupational exposure to the composite measure VGDF and asthma, rhinitis and concomitant asthma and rhinitis, but also to assess the importance of the exposure to each of the components chemicals, inorganic and organic dust.

Paper II To evaluate three different classification systems based on job title for classification of socioeconomic (SEI) and occupational groups (SSYK and NYK), with respect to the ability to identify groups at risk for asthma and respiratory symptoms, regardless of reported occupational exposure to VGDF.

Paper III To study the associations between different measures of socioeconomic status based on both questionnaire and national register data, and asthma and respiratory symptoms.

Paper IV To study whether asthma in childhood and adolescence is associated with socioeconomic status including level of education and occupation in young adulthood.

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Materials and Methods

Study areaNorrbotten County (figure 7) is the northernmost county of Sweden. It is the largest county in Sweden but sparsely populated with around 250 000 inhabitants in towns, villages and countryside in an area of ca 100 000 square kilometres (population density 2.6/km2). The county of Norrbotten borders Norway in the west and Finland in the east. It includes parts of the Scandinavian mountains in the west and a coastline towards the Gulf of Bothnia in the east as well as numerous lakes and large forests. A majority of the population (ca 155 000) lives in the coastal area around the county town of Luleå. The coast is characterized by heavy industries such as steel, wood and pulp and the inland by forestry, ore mining and hydroelectric plants. While the importance of traditional industries diminishes, other areas such as tourism, wind power, server halls, car testing, trade, research and education are gaining in importance.

Figure 78– Europe, Sweden and Norrbotten County

8 CC BY-SA 4.0 Rob984, Wikimedia Commons; CC BY-SA 2.5 by Lokal_Profil, Wikimedia Commons; Region Norrbotten; modification of colour-scheme and combining the maps made by C Schyllert.

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The OLIN studies The Obstructive Lung Disease in Northern Sweden (OLIN) is an epidemiological research programme that started in 1985. With focus on COPD, asthma and allergies and related health economics, the overall aim is to identify modifiable risk factors to prevent obstructive lung disease. As of 2019, more than 60 000 individuals between the ages of 7 and 90+ have participated, throughout different cohorts. The epidemiological research methods applied include cross-sectional and longitudinal designs as well as case-control and clinical studies.

Research is conducted along four lines:

1) Asthma and allergy among adults

2) Asthma and allergy among children

3) Chronic Obstructive Pulmonary Disease (COPD)

4) Health economics with regard to obstructive lung disease

The current thesis is based on the research programmes for studies of asthma and allergy among adults (papers I-III) and among children (paper IV). An overview of the papers is presented in table 1, and details are presented in the text below.

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Study samples

Paper I The study sample in paper I is a compilation of the first three adult cohorts in the OLIN-studies. The recruitment process was similar for all cohorts (flowchart in figure 8) with a postal questionnaire survey followed by clinical examinations including structured interviews and spirometry of random and stratified samples of the responders. In cohorts 1 and 2 the sample selection was based on age stratification, while cohort 3 was a random sample of the population.

Figure 89 – Flowchart of study sample paper I

Cohort 1 was recruited in 1985-86 by a postal questionnaire survey distributed to all inhabitants born in the years 1919-20, 1934-35 and 1949-50 (n=6610) living in 8 geographical areas of Norrbotten representing the county in terms of urbanization, industrialization and coast/inland. In 1992-93, cohort 2 was recruited, and in a similar fashion; all individuals born in the years 1925-26, 1940-41, 1955-56 and 1970-71 in the same areas were invited (n=9128). Cohort

9 From paper I

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3 was also recruited in 1992-93 but included a random sample of the adult population between the ages 20-69 (n=5682) in the county of Norrbotten. Further, the participants of cohort 1 were also invited to a followed-up postal questionnaire survey. In 1986-87, all individuals in cohort 1 reporting respiratory symptoms (n=1655), were invited to a clinical examination consisting of a structured interview and a spirometry along with n=315 of respiratory healthy individuals. In 1993-94, cohort 2 underwent a similar process including all individuals reporting respiratory symptoms together with a smaller number of individuals without respiratory symptoms. In the same year, a random sample of Cohort 3 (n=970) was also invited to a clinical examination. In 1996-99 a follow-up clinical examination was carried out in Cohort 1. On this occasion, a random sample of the participants of the postal survey of 1992-93 were invited to a clinical examination together with a group of individuals, all those reporting respiratory symptoms in the same survey.

During the years 2002-2004, all individuals in cohorts 1-3 who previously had participated in a clinical examination, were invited to clinical re-examination, where 4036 individuals participated. Paper I includes data from the structured interviews and a questionnaire regarding occupational exposure collected from the participants.

Papers II and III In the years 1996, 2006 and 2016 random samples of the Norrbotten population were invited to postal questionnaire surveys. The surveys in 2006 and 2016 also included a follow-up of the previously recruited cohorts, (flowchart in figure 9).

Figure 9 – Flowchart of the postal questionnaire surveys 1996, 2006, 2016 and recruitment of study samples to papers II and III. Paper II is based on Cohort06 and Follow-up 1 of Cohort96, and paper III is based on Cohort16.

2016

2006

1996 Cohort96

Invited = 8704 Responded = 7420

Cohort06 Invited = 7997

Responded = 6165

Cohort16 Invited= 11755

Responded = 6854

Follow-up 1 Invited = 5819

Responded = 4552

Follow-up 1 Invited = 7004

Responded = 5890

Follow-up 2 Invited = 6080

Responded = 4822

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In 1996 and 2006 the baseline age range was 20-69 and in 2016 this was increased to 20-79. Paper II is based on the postal questionnaire survey in 2006 compiling individuals from both the follow-up of Cohort96 and the newly recruited Cohort06. however only including the individuals between the ages 30-69 (n=9992) since the younger and older individuals were professionally active to a lesser extent (45% of individuals <30 were students or did not report an occupation). Paper III is based on the new Cohort16 recruited in 2016 (n=6854).

Paper IV Paper IV is based on a prospective cohort study on asthma and allergic diseases among school children; the OLIN paediatric cohort I (flowchart in figure 10). The cohort was recruited in 1996, when all children in grade 1 and 2 of compulsory school (aged 7-8 years) in the municipalities of Luleå, Piteå and Kiruna (n=3525) were invited to a parental questionnaire survey, where n=3430, 97% participated. The cohort was followed with annual questionnaires until they graduated from upper secondary school at age 19 years. In 2015, at 27-28 years of age, a postal questionnaire was sent out to all individuals still alive and with a Swedish postal address, and 71% responded (n=2291). The study sample in paper IV consists of the individuals who participated in the follow-up as well as in the surveys conducted at ages 7-8, 11-12 and 19 years, in total n=2017.

Figure 1010 – Flowchart of the study sample in paper IV, n=number of participants, recruited in 1996 and last follow-up in 2015

10 From paper IV

Questionnaire 7-8 years of age

(n=3430)

Questionnaire 11-12 years of

age (n=3151)

Questionnaire 19 years of age

(n=2861)

Questionnaire 27-28 years of

age (n=2291)

Study sample: responded to all questionnaires

(n=2017)

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Data sources

The OLIN-questionnaires The adult OLIN-questionnaires exists in a shorter version used for postal surveys and an extended version used in structured interviews. The shorter postal questionnaire was developed from the revised version of the British Medical Research Council questionnaire (42) but also includes questions from US National Heart, Lung and Blood Institute (43), the Tucson study (44) and the American Thoracic Society (ATS) (45). In short, it includes questions about respiratory symptoms such as cough, breathlessness, wheezing and physician diagnoses of respiratory diseases such as asthma or chronic bronchitis. Additionally, questions were added on exposure to environmental tobacco smoke (ETS) and smoking habits, family history of asthma and allergies and use of medication. The core questions regarding respiratory symptoms and conditions have been similar throughout the years but the questionnaire has been somewhat modified, for example questions on occupational exposure to gas, dust or fumes (GDF) and use of electronic cigarettes have been added. The extended version used in structured interviews includes additional questions from the International Union against Tuberculosis and Lung Disease (IUATLD) (163) and the European Community Respiratory Health Survey (ECRHS) (164,165). This questionnaire is more detailed regarding respiratory symptoms and diseases, medication use, comorbidity, environmental exposures, anthropometric measures and lifestyle factors. The questionnaires have been validated against the GA2LEN-questionnaire (36), the prevalence of asthma (defined by a cluster of symptoms such as wheezing, breathlessness and attacks of shortness of breath) has been validated by clinical examinations and methacholine-testing (166) and they have been used in several Swedish and international epidemiological studies (167–171)

The paediatric questionnaire includes questions from the International Study of Asthma and Allergies in Childhood (ISAAC) protocol (172) regarding symptoms of asthma, rhinitis and eczema as well as additional questions on diagnoses, use of medication, family history of respiratory and allergic diseases and factors such as ETS-exposure, recreational activities, sports and pets or other animals at home (173).

Structured interview – Paper I Paper I is based on data from the structured interview at the clinical examination in 2002-04. The interview follows the expanded adult OLIN-questionnaire. In addition to the interview, the participants were asked to fill out a detailed questionnaire including questions on occupational exposure

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Postal questionnaire survey – Papers II and III Papers II and III are based on data from postal questionnaire surveys; the same shortened version of the OLIN adult questionnaire was used. In paper III, in addition to the standard OLIN-questionnaire, a questionnaire from the Global Allergy and Asthma European Network (GA2LEN) was added. The GA2LEN-questionnaire included similar questions on respiratory symptoms and medication but also on visible housing damage due to dampness, exposure to traffic, exercise habits, current employment status and highest reached educational level as well as height and weight.

Register – Paper III In addition to the postal questionnaire in paper III, data was collected from the longitudinal integration database for health insurance and labour market studies (LISA) of Statistics Sweden. LISA keeps annual registers since 1990 and includes all individuals 15 years of age and older that were registered in Sweden as of December 31st. The database collects data from several reliable registers and provides a basis for longitudinal statistics and research about gainful employment and alternative employments (studies, parental leave, unemployment, labour market activities, etc.) as well as income from gainful employment or alternative income sources (appendix 2) (174,175). Data was gathered from the calendar year of 2015, the year before the questionnaire survey was conducted.

Keeping registers of the population has been practice in the Nordic countries since the 17th and 18th centuries. In the 1960’s, with the introduction of the unique personal identification numbers still used today, centralized population registers were established in all Nordic countries. Thus, there is a longstanding tradition of keeping national population-based registers of official statistics on more or less all residents (176,177).

All Nordic countries have laws that regulate the national statistical institutes (NSI) rights to access administrative data (177–182) with identification data and the ability to link them with other registers (177). In general, Nordic citizens have a high degree of social trust and trust in the government (183) and a high level of trust between residents, government and the NSI, as well as a high level of confidence in the accuracy of the data is imperative in establishing high quality databases (177).

Questionnaire surveys – Paper IV From recruitment at ages 7-8, the cohort was followed with annual paediatric questionnaires up to 19 years of age. The questionnaire was completed by a legal guardian up until 12-13 years of age and subsequently by the adolescents

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themselves before exiting the paediatric phase of the study at age 19 years. At 27-28 years of age, they were followed-up by a postal questionnaire similar to the surveys of paper II and III.

Definitions

Population sample characteristics Age (papers I-III): The age of the individual at completion of the questionnaire, in paper IV all individuals were 27-28 years of age and individual ages were not presented. BMI (body mass index) (papers I, III and IV): Calculated height/weigth2 and classified according to the World Health Organization (WHO) standard: underweight <18.5, normal weight 18.5-24.9, overweight 25.0-29.9, obese >30.0. In papers III and IV normal weight was defined as BMI <25.0. The metrics were measured during the clinical examinations for paper I and were self-reported in papers III and IV. Smoking habits: In papers I-III categorized as never-smoker/non-smoker, ex-smoker (stopped more than 12 months ago) and current smoker. Ever-smoker (paper I) was defined as ex- or current smokers. In paper III, current smokers were further divided into ‘current smoker of 14 cigarettes or less per day’ and ‘current smokers of 15 cigarettes or more per day’. In paper IV, smoking habits were reported at 19 years of age as non-smokers, occasional smoker (on weekends or socially) and current smokers. Pack-years (PY) (paper I): Calculated (number of smoked cigarettes per day x numbers of years smoked) / 20. Family history of asthma (papers II and III): Have any of your parents or siblings asthma, or have they had asthma?

Occupations and socioeconomics

Questionnaire data Main or longest held occupation/job-title was used to define occupational groups according to the Nordic Occupations Classification 1983 (NYK) (184) (papers I and II) and the Swedish Standard Classification of Occupations 2012 (SSYK) (124) (papers II and IV). It was also used to define socioeconomic groups according to the Swedish Socioeconomic classification (SEI) (abbreviated SES in paper I) (134) (papers I-IV), table 1. Educational level (papers III and IV): What is the highest level of education you have reached; Compulsory school, upper secondary school, higher education (university or college) on basic level (less than 3 years) or higher education on advanced or research level (3 years or longer)? This corresponds to the Swedish education nomenclature (SUN) (185) (overview in appendix 3). SUN is based on the International Standards of Classification of Education

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(ISCED) 97 (186). Housing status (paper III): Have you, in your home, noticed mould or signs of damage due to dampness? Working status (paper III): Professionally active (employed, self-employed or home person fulltime), jobless (unemployed or on sick leave), retired, student. In paper IV, the following variables was used as proxies for family SES: Socioeconomic measures at ages 7-8: Exposure to tobacco smoke at home, single-parent household and residence (house, flat or both).

Register data In paper III, data collected from the LISA-database were the following: Educational level: Divided similarly as data from questionnaires described above except that higher studies on university or college level were aggregated into one group. Equalized disposable income: Disposable income per consumption unit, i.e. the income of the household adjusted per number of individuals in the household (figure 11). Personal disposable income: The individuals’ personal contribution to the household disposable income. Income was reported as yearly income in SEK. The different sources of income are presented in appendix 2.

Figure 1111 – How to calculate equalized disposable income

Occupational exposure In all papers, occupational exposure was self-reported. In paper I, the following definitions and subgroups were based on the questionnaire including detailed

11 From paper III

2.45 consumption units

Second child 0.42

S

First child 0.52

Married couple

1.51

Annual disposable income of 500 000 500 000 / 2.45

Annual ED income = 204 000

Household composition Consumption unit

Single household 1.00

Cohabiting couple 1.51

Additional adult 0.60

First child aged 0-19 0.52

Second and subsequent children aged 0-19 0.42

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data on occupational exposure. The questions were stated “During your working career, have you more often than occasionally been exposed to…?” answers given were ‘yes’ or no response and classified as follows: Inorganic dust: mineral, stone, quartz, coal (in spite of not being strictly inorganic), coke and metal dust. Organic dust: wood, paper, textile and flour dust. Chemicals: oil products, solvents, cleaning products, dyes, fully or partly uncured plastics, colours/varnishes, insecticides/pesticides, handling materials releasing chemicals at drilling, grinding, sawing etc., aldehydes (formaldehyde, formalin), acrylates (thermoplastics or thermosets in colours, varnishes, glues, bone cement, dental filling materials), hair care products and isocyanates. Vapours, gas, dust or fumes (VGDF): Was defined as an affirmative answer on any of the above stated occupational exposures and/or affirmative answer including questions regarding welding fumes and diesel exhaust.

Occupational exposure to gas, dust or fumes (GDF) (papers II-IV, the term VGDF was used paper II): Was based on the single-item question: Have you been heavily exposed to gas, dust and/or fumes at work?

Respiratory symptoms, allergy and asthma

Among adults Attacks of shortness of breath (SoB) (paper III): Have you, during the last 12 months, had intermittent attacks or periodic breathlessness which can occur with or without cough or wheezing/whistling in your chest? Any wheeze (paper III): Have you at any time during the last 12 months had wheezing or whistling in your chest? Recurrent wheeze (paper II): Do you usually have wheeze, whistling or a noisy sound in your chest when breathing? Productive cough (papers II and III): Do you usually have phlegm when coughing, or do you have phlegm in your chest which is difficult to bring up, and have you had this during most days for at least three months? Allergy: History of allergy (paper I) or Allergic rhinoconjunctivitis (ARC) (papers II and III): Do you have allergic rhinitis (hay-fever) or allergic eye symptoms? Rhinitis: ‘Often being troubled by nasal congestion or rhinorrhoea’ (paper I).

Physician diagnosis of asthma: Have you been diagnosed as having asthma by a physician? (papers I-III), table 1. Current asthma: Affirmative answer to physician diagnosis of asthma and either wheeze or use of asthma medication (paper II) or attacks of shortness of breath (paper III) during the last 12 months. Allergic asthma: Current asthma and ARC (papers II and III). Non-allergic asthma: Current asthma and negative answer to ARC (papers II and III). Use of asthma medication (papers II-III): Do you use asthma medication (on a regular basis or when needed)? Asthmatic wheeze (papers I and III):

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affirmative answer to all of the following: ‘usually having wheezing or whistling in the chest during the last l2 months’, ‘any wheezing with shortness of breath’ and ‘any wheezing while not having a cold’. Concomitant asthma and rhinitis: both asthma and rhinitis, based on the definitions above (paper I), discriminating asthma only (asthma, no rhinitis) and rhinitis only (rhinitis, no asthma).

In childhood and adolescence In paper IV, asthma was defined by comprising data from questionnaires at ages 7-8, 11-12 and 19 years: Current asthma: Physician diagnosis of asthma and either wheeze or use of asthma medication during the last 12 months. Ever asthma: Current asthma at age 7-8, 11-12 or 19 years. Asthma categories at age 19: Based on prevalence of current asthma at age 7-8, 11-12 and 19 years respectively; “early-onset, persistent”, “early-onset, in remission”, and “late-onset” (figure 12). Allergic rhinitis (AR): Affirmative answer to the question: In the last 12 months, have you/has your child had a problem with sneezing or a runny or blocked nose when you/he/she did not have a cold or the flu? in any of the questionnaires at 7-8, 11-12 or 19 years of age. Asthma with or without allergic rhinitis: Current asthma with or without affirmative answer to AR and further classified into asthma categories at age 19 years as above.

Figure 1212 – Definition of asthma-categories at age 19 in paper IV

12 Modified version of one in paper IV

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Statistical methods Pearson’s χ2 test was used for comparing prevalence and Students t-test was used to compare means between groups. Bivariable logistic regression models were used to calculate crude odds ratios (OR) and 95% confidence intervals (95% CI). Multivariable logistic regression models were used to calculate OR and 95% CI adjusted for confounding factors. In all papers, corresponding analyses were also conducted stratified by sex. Statistical significance was defined as a two-sided p<0.05. Paper-specific statistical methods are mentioned below. All analyses were carried out using IBM SPSS Statistics versions 23 and 24 (IBM Corp, New York, USA).

In paper I, multinomial, multivariable logistic regression models were used to evaluate occupational exposures as risk factors for the mutually exclusive outcomes of rhinitis only, asthma only and concomitant asthma and rhinitis (reference category: neither asthma nor rhinitis). Exposure to VGDF and each of the components (chemicals, inorganic and organic dust) were analysed separately and in addition, an analysis was performed including all components at the same time. Chemicals were also analysed after excluding isocyanates, and further after excluding isocyanates and welding fumes. Analyses were also made stratified by smoking habits and allergy.

In paper II, for the variables productive cough, recurrent wheeze, and current asthma, the logistic regression analyses were performed stratified by quartiles of the number of years of working in the main occupation. The logistic regression analyses were also performed after excluding subjects with onset of asthma before the age of 18 years.

In paper III, analyses were also made stratified by working status. Analyses of interaction between income and sex were conducted: using equalized disposable income, the fifth (highest) income-group was used as reference regardless of sex, and the first and second as well as the third and fourth income-groups were aggregated into two groups and in turn combined with sex to form four outcomes below the reference: (1) men and (2) women with medium income and (3) men and (4) women with low income.

In paper IV, multinomial, multivariable logistic regression models were used to calculate OR and 95% CI with educational level, socioeconomic SEI-groups, occupational SSYK-groups or GDF-exposure as dependent variables and adding the asthma-variables among the independent variables. Corresponding analyses were conducted for asthma variables with and without allergic rhinitis.

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Ethics

Each paper is based on surveys conducted by the OLIN-studies, of which all have been approved by the Regional Ethical Review Board of Umeå (Dnr 04-045M, Dnr 05-157M, Dnr 2015-404-31M Dnr 2017-393-32M, Dnr 2014-365-31). All studies have been carried out in accordance with the Declaration of Helsinki. All subjects received a study specific ID-code and the code keys are stored within the OLIN studies premises. Data files distributed to researchers are de-identified. The participants received no financial compensation.

In epidemiological studies, subjects with previously unknown conditions may be identified, and information regarding a previously undiagnosed disease may be perceived negatively. However, the benefit of early diagnosis and possible treatment is expected to exceed the possible harm of information regarding previously undiagnosed disease. Responsible physicians have assessed pathological findings and, when appropriate, subjects have been informed and offered referral for further consultation and follow-up.

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Results

Behavioural factors in papers I-IV The distribution of BMI and smoking habits in the different papers are shown in table 2. Main results will be presented below, paper by paper.

Table 2 – Distribution of behavioural factors in papers I-IV Paper I Paper II Paper III Paper IV Age 19 Age 27-283 Data collection year 2002-04 2006 2016 2006 2015

BMI <25 38.0 1 42.5 79.8 60.2 25-30 43.7 1 39.9 15.9 27.6 >30 18.3 1 17.6 4.2 9.6

Smoking habits Non 41.2 54.7 61.1 79.3 81.4 Ex 38.0 25.7 22.9 12.02 12.4 Current 20.9 19.2 11.2 8.7 6.2

1data not available 2occasional smoker 3 data not published

Paper I

Asthma and respiratory symptoms In the total study sample (n=4036), 24.1% had asthma and 40.5% rhinitis, and both conditions were more common among women (27.3% vs 20.7%, p=0.001 and 42.1% vs 38.9%, p=0.038, respectively). Proportions of rhinitis only, asthma only and concomitant asthma and rhinitis are shown in figure 13.

Occupational exposure In the total study sample, 57.9% reported exposure to VGDF, and this was more common among men than women (77.7% vs 38.8%, p<0.001). The largest subgroup of VGDF-exposure among women was chemicals (26.8% exposed) while among men, the largest subgroup was inorganic dust (60.1% exposed).

Figure 13 – Overlap between asthma (physician diagnosis) and rhinitis, % of total study sample

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Occupational exposure and concomitant asthma and rhinitis Occupational exposure to VGDF was associated with asthma and concomitant asthma/rhinitis among women and with rhinitis and asthma among men, even though the analyses in the total study sample yielded no significant findings. In analyses adjusted for age, BMI-categories, smoking habits and sex, VGDF was associated with asthma only and concomitant asthma/rhinitis. In corresponding analyses stratified by sex, exposure to VGDF was associated with concomitant asthma/rhinitis among women, and rhinitis only and asthma only among men. When dividing VGDF into the components chemicals, inorganic and organic dust, analyses in similar models showed that occupational exposure to chemicals was the component which was driving the observed association between VGDF and rhinitis only, asthma only and concomitant asthma/rhinitis (figure 14). In analyses stratifying for sex, the pattern was similar among men, while among women the association between exposure to chemicals and rhinitis did not reach statistical significance and the risk for asthma only was borderline significant. The associations between chemicals and rhinitis only, asthma only and concomitant rhinitis/asthma remained with a similar pattern also when excluding isocyanates and welding fumes from the variable chemicals as well as in analyses stratified by smoking habits

Figure 1413 –Forrest plot of occupational exposure to VGDF and the subgroups of chemicals, inorganic dust and organic dust as risk factors (OR, 95% CI) for rhinitis only, asthma only and concomitant asthma and rhinitis in the total population, analysed in a multinomial regression model adjusting for sex, age, BMI and smoking habits. VGDF in model 1, and the components chemicals, inorganic dust and organic dust all included in model 2.

13 From paper I

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Paper II

Asthma and respiratory symptoms In the study sample (n=9992), 9.1% reported productive cough, 12.1% recurrent wheeze, 23.9% allergic rhinoconjunctivitis (ARC) and 21.6% rhinitis. Current asthma was reported by 9.2% of which more than half was classified allergic asthma (5.4% vs 3.8% non-allergic). All symptoms and conditions were more prevalent among women with the exception of cough, recurrent wheeze and non-allergic asthma which were equally as common in both sexes.

Socioeconomic status, job and occupational exposure According to SEI classification, about half of the study sample (49.3%) were ‘manual workers’, with predominantly men in industry and women in service. Almost every third (34.8%) were ‘non-manual employees’, 43.0% among women and 26.5% among men. ‘Professionals and executives’ and ‘self-employed non-professionals’ were predominantly men, however in total, fairly low numbers (6.3% and 2.4%). The largest occupational NYK-groups were ‘administration’ and ‘manufacturing’, each constituting 20.0% of the study sample with the former being predominantly women and the latter men. The largest SSYK-occupational group was ‘service’ with 20.8% and the second largest was ‘occupations requiring higher advanced education’ at 17.0%. Occupational exposure to VGDF was reported by 30.9% of the study sample, more commonly among men than women (47.2% vs 14.8%).

Socioeconomic status, job, occupational exposure and their associations with asthma and respiratory symptoms Compared to professionals and executives, all SEI-categories of manual workers and non-manual employees were associated with productive cough, and both manual worker-categories also with recurrent wheeze also when adjusting for sex, age, family history of asthma and smoking habits. In corresponding analyses, the NYK-occupational groups did not give any clear patterns, but ‘manufacturing was associated with recurrent wheeze, ‘health-care’ with current and non-allergic asthma and ‘service’ with non-allergic asthma. All SSYK-groups except ‘occupations requiring higher advanced’ or ‘higher education’ were associated with productive cough and, ‘building’, ‘manufacturing’ and ‘elementary’ were also associated with recurrent wheeze when compared with managers. Occupational exposure to VGDF was associated with all respiratory symptoms and asthma.

The associations between the SEI-groups ‘manual-workers service’, both non-manual employees’ categories, the SSYK-groups ‘administration’, ‘service’ and

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‘elementary’ and productive cough remained when also adjusting for VGDF-exposure. Excluding individuals with childhood asthma (those reporting asthma-debut before the age of 18) did not change the results. When stratifying for number of years in longest held job in quartiles, associations were mainly seen between productive cough and working 0-14 years, and between wheezing and current asthma and working 21-30 years.

Paper III

Asthma and respiratory symptoms Any wheeze, attacks of SoB and asthma were all more common among women than men, while productive cough was more common among men. The prevalence of ARC was similar among men and women (table 3)

Table 314 – Prevalence of asthma and respiratory symptoms in the study sample of paper III (%) Total Women Men p-value*

Respiratory and allergic symptoms

Any Wheeze 17.4 18.7 16.1 0.004 Attacks SoB 12.7 14.6 10.6 <0.001 Productive cough 9.1 8.4 9.9 0.030 Allergic rhinoconjunctivitis 24.8 25.4 24.1 0.217

Asthma

Physician diagnosis of asthma 12.5 13.9 11.0 <0.001 Current asthma 10.5 11.8 8.9 <0.001 Allergic asthma 6.3 7.2 5.5 0.004 Non-allergic asthma 4.1 4.7 3.5 0.013 Use of asthma medication 13.3 15.0 11.4 <0.001

Asthmatic wheeze 7.1 7.6 6.5 0.067 * comparing sex Pearson’s 2

Behavioural factors and socioeconomic status BMI>25 and current smoking were more common among those with lower education (figure 15). More women (40.0%) than men (30.4%) had proceeded to higher education but more women than men had low disposable income. More men than women reported exposure to GDF (43.1% vs 14.7%, p<0.001) and GDF exposure was most common in the medium-low to medium-high income-groups as well as among those with lower educational levels (figure 15). There were no differences in housing damage in relation to any socioeconomic indicator (figure 15).

14 Modified from one in paper III

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Figure 1515 – Distribution of behavioural factors and housing dampness by educational levels

Socioeconomic status and asthma and respiratory symptoms There were few significant associations between the indicators for socioeconomic status and asthma, with the exception of the SEI-group manual work in service which compared to professionals and executives was associated with current asthma also when adjusting for family history of asthma, age, smoking, housing dampness and BMI. The significance was however lost when adding GDF exposure to the model. The association between manual work in service and asthma was driven by the allergic asthma phenotype while low education level rather appeared to be protective with regard to the allergic asthma.These associations with indicators of both low and high socioeconomic status and asthma, mirrors the heterogeneity of the disease. In unadjusted analyses, the SEI-groups manual work were associated with any wheeze, asthmatic wheeze, attacks of SoB and productive cough when compared with professionals, while being a non-manual employee (lower) was associated with attacks of SoB only. The associations between manual work and any wheeze, asthmatic wheeze and productive cough, and between non-manual employees (lower) and attacks of SoB remained significant also when adjusted for age, smoking, BMI and housing dampness but after further adjustment for exposure to GDF, the significance for the association between manual work and wheeze was lost.

15 From paper III

0%10%20%30%40%50%60%70%80%90%

100%

Higher Upper Secondary Compulsory

Smoking habits

Non-smoker Ex-smoker Smoker <14 cig per day Smoker >15 cig per day

0%10%20%30%40%50%60%70%80%90%

100%

Higher Upper Secondary Compulsory

BMI

Normal weight Overweight Obese

0%10%20%30%40%50%60%70%80%90%

100%

Higher Upper Secondary Compulsory

Housing dampness

No damaged housing Damaged housing

0%10%20%30%40%50%60%70%80%90%

100%

Higher Upper Secondary Compulsory

GDF-exposure

No GDF-exposure GDF-exposure

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Interaction analyses based on sex and equalized disposable income (figure 16) revealed different patterns among men and women. Compared to those with high income, the group ‘low income women’ was associated with each of the respiratory symptoms as well as asthma, while the group ‘low income men’ was associated with productive cough while it was protective for asthma and ARC.

Figure 1616 – Forrest plot of interaction analysis between sex and income in relation to asthma and respiratory symptoms. High income, regardless of sex, as reference.

Paper IV

Asthma in childhood and adolescence In total, 12.7% of the study sample (n=2017) had ever had asthma; 4.9% early-onset persistent, 2.8% early-onset in remission, and 5.1% late-onset asthma.

16 From paper III

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Socioeconomic measures and behavioural factors in childhood and adolescence At 7-8 years of age, 23.2% were exposed to tobacco smoke at home, 10.6% lived in a single-parent household and a majority (16.9%) lived in a flat. Behavioural factors at age 19 as well as at ages 27-28 years are presented in table 2.

Socioeconomic status, job and occupational exposure in young adulthood In total 55.3% had compulsory school or upper secondary school as their highest educational level and more women than men reached higher education levels Within the SEI-groups, 43.2% were manual workers; more men than women in industry and the opposite in service. The SSYK-group occupations requiring higher education was the largest in both sexes. The level of education in the different SEI and SSYK-groups is illustrated in figure 17. Occupational exposure to GDF was more common among men than women.

Figure 1717 – Distribution of educational level in the A) SEI and B) SSYK-groups

17 From paper IV

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Asthma in childhood and adolescence in relation to socioeconomic status, job and occupational exposure in young adulthood Early-onset asthma was associated with low educational level in young adulthood, especially not continuing after compulsory school. Among women, this seemed to be related to early-onset persistent asthma, while among men to early-onset asthma in remission. We could also see a trend that individuals with early-onset asthma leans towards manual labour and avoidance of administrative or managerial jobs, while individuals with late-onset asthma rather leaned towards higher education and white-collar work such as administrative and managerial jobs and avoided manual labour

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Discussion of methodology

Epidemiological concepts Each paragraph will introduce a concept, followed by a discussion of the presented concept in relation to the papers included in this thesis.

Validity and reliability Validity or accuracy, is the ability of a scientific study to measure what it is intended to measure and to what extent it is unaffected by systematic errors. The validity can be affected by systematic errors such as selection bias, information bias and confounding factors. Internal validity describes how well a study describes the true situation in the study sample. External validity is the ability to apply the conclusions of a study outside the context of that study. It describes the extent to which the results of a study can be generalized to the population. Reliability is the overall consistency of a measure, the ability to obtain similar results using the same method (187).

Systematic errors

Selection bias Selection bias is the selection of individuals in such a way that proper randomization is not achieved, thereby making the study sample non-representative of the population it is intended survey. This can occur if one group of the population is less prone to participate in scientific studies. A random sampling design and a high participation rate decrease the risk for selection bias.

The study sample in paper I is, as described above, a compilation of three different cohorts, the participation rate was 79.2%. Due to the study design of cohorts 1 and 2, there is an enrichment of individuals reporting respiratory symptoms. This means that prevalence figures of asthma and rhinitis cannot be generalized. While the participation-rates in all papers have been fairly high, they were the lowest at around 60% in papers III and IV. In paper IV, males and individuals exposed to tobacco smoke at home were overrepresented in the non-participating group. In the population sample of paper III, a study of representativeness18 (188) likewise showed that non-responders were mainly younger, male and/or smokers but they did not report more symptoms or asthma than the responders. This is in line with other findings that have shown 18 Presented as a poster at the European Respiratory Societys Congress in Paris 2018

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that while non-responders are mainly young, male and/or smokers they are in other aspects a heterogeneous group and that the potential non-responder bias is small (189–191). While a low participation rate might lead to bias, this is not inevitably the case (192,193), and the internal validity of the results are not necessarily affected (189,190,192,193). A special type of selection bias that must be considered in research on occupational health is the healthy worker effect (HWE) described below.

Healthy worker effect HWE is a type of selection bias that is usually found in occupational epidemiology. Epidemiological research usually study population samples that represent, and can be generalized to, the general population. The HWE overturns this in a way: The general population is a mix of healthy and ill individuals, and everyone in-between, and of different ages. Individuals may, due to different diseases and conditions be unemployed, need to change or quit work due to impaired health, leaving a general workforce that is “healthier” than the general population. Further, certain occupations (such as fire-fighters, police officers or military service) have extensive testing to assess the “healthiness” of the applicants (187,194,195). The healthy worker effect comes in three guises: healthy hire, survival effect and workplace advantages. Healthy hire means than in certain occupations only able-bodied individuals can be employed due to the strenuous tasks that comes with the work. For example, individuals with asthma are excluded from certain occupations and may have a tendency to refrain from occupations with a high risk of work-exacerbated symptoms (194–197). In Sweden, this is regulated by the Swedish work environment authority. There is also a survival effect, a form of self-selection: a worker with declining health or chronic conditions tend to leave the workforce or be forced to retire early (194,195). Workplace advantages can include access to corporate health care, frequent or mandatory medical check-ups and screening which all contributes to maintain their health status (194,195).

As all of the included papers are based on general population samples, all individuals are included in the samples whether they are professionally active or not, and the classification of occupations (SEI, NYK and SSYK) are based on main or longest held occupation, which may decrease the HWE somewhat. Still, the observed associations between occupational exposure and respiratory conditions may be underestimated due to HWE. In paper II, individuals below the age of 30 and above the age of 69 were excluded, with the aim to minimize a possible bias caused by individuals not being professionally active, but increasing the risk of potential HWE-bias. Also, in paper III, analyses were made stratified for working status and the analyses conducted among those professionally active are thus affected by the HWE.

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Recall bias Recall bias, response bias, responder bias or reporting bias is caused by differences in the accuracy of the recollections retrieved by study participants regarding events or experiences from the past. This bias can be a methodological issue in studies based on interviews or questionnaires, where it could lead to misclassification of exposure (187).

Regarding using self-reported data on occupational exposure, individuals with asthma and respiratory symptoms may be more prone to report past exposures, which cannot be ignored in papers I-III. Using self-reported data usually yields stronger associations than, for example, using a JEM or other more objective methods of measuring exposure. However, using validated questionnaire data is cost-effective and considered applicable in epidemiological studies (118–120,198). In paper IV, the longitudinal prospective design with data from several time points reduced the risk of recall bias with regard to asthma in childhood and adolescence. Further recall bias with respect to occupational exposure is probably less prominent in paper IV due to a shorter time of being professionally active.

Confounding and mediation Confounding is the effect of a factor that influences both outcome and exposure causing a false relationship between them. Stratified analyses may contribute to control for confounding. For example, by, stratifying analyses for smoking habits, the effect smoking has on respiratory symptoms can be controlled for. Another way to control for confounding factors is by using multivariable regression models. Mediating factors are related to confounding factors. Rather than a direct causal relationship between the outcome and exposure, a mediation model proposes that the exposure influences the mediator variable, which in turn influences the outcome. Thus, the mediator variable serves to clarify the nature of the relationship between outcome and exposure. For example: (i) low SES is related to respiratory symptoms, (ii) low SES is related to smoking, (iii) smoking is related to respiratory symptoms (136,149–151,187).

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When studying occupational exposure and the association with asthma and respiratory symptoms, smoking and high BMI are confounding factors that must be considered. However, when studying SES and its associations to the same, smoking may instead be considered a mediating factor, as smoking (a risk factor for respiratory symptoms) also is associated with low SES. In all papers, the decision was made to handle these factors as confounders and they included smoking and occupational exposure (papers I-IV), BMI ( papers I, III and IV), age (papers I-III), family history of asthma ( papers II and IIII) and proxy-measures for the family SES (paper IV).

Data sources

Questionnaire Using a standardized, validated questionnaire is a convenient and cost-effective method in large population-based studies. The quality of data relies of the validity and reliability of the questions. The adult questionnaires used in the OLIN-studies has been validated against GA2LEN (36), and in the studies among children, questions were used from the ISAAC protocol (51). The prevalence of asthma (defined by a physician diagnosis of asthma and a cluster of symptoms such as wheezing, breathlessness and attacks of shortness of breath) has been validated by clinical examination and methacholine-testing (166). In the OLIN-studies, the question used to define “physician diagnosis of asthma” has been validated and has high specificity but low sensitivity (33,199). While questions on smoking habits have not been validated, the responses have been consistent in both self-completed questionnaires and structured interviews and also corresponds to national Swedish data on smoking habits. A potential source of misclassification is the coding of job-titles into SEI, NYK and SSYK groups. However, the coding has been done by a group of individuals familiar with the manuals and any uncertainties has been discussed within the research group to reach consensus.

Definition of asthma In paper I, asthma was defined as physician diagnosis of asthma, which has risk of being unspecific and a degree of uncertainty. In papers II and IV the definition of ‘current asthma’ was similar with physician diagnosis and either wheezing or use of asthma medication, in paper III, ‘current asthma’ also included the possibility of attacks of shortness of breath. Adding current symptoms or use of asthma medication to the definition increases specificity but with a risk of decreasing sensitivity, thus with a possibility of underestimating the prevalence-estimates, although with increasing number of symptoms included, the more sensitive and less specific the definition becomes.

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Register Statistics Sweden is the Swedish NSI responsible for data-collection and is certified in its production of statistics according to the international standards for marketing, opinion and social research (ISO 20252) (200). Register-based research depends heavily on the quality, accuracy and representativeness of the data obtained from the register. But, as described above, the official databases and registers in all Nordic countries meets the very well the description of being representative of the population with accurate data of high quality.

An early Nordic population register; a Danish parish register from 186719

19 Wikimedia Commons, CC0 1.0 Public domain; Kirkebog for Burkal sogn, fødte i året 1867 (arkivalier online, KB 1864-1917, opslag 15)

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Discussion of main results

Cohort-effect A cohort is a group sharing common characteristics or experiences. A cohort effect occurs when a research result is impacted by the characteristics or shared experiences of the cohorts studied, for example changes in smoking habits over time or changes in regulations with regard to schooling and workplace environment. While the factors that make a group of people a cohort may seem broad and have little to do with each other, the characteristics the group have in common may influence findings in a research context. This is because different cohorts’ characteristics vary over time due to their shared experiences, even if those experiences were very general. For example, for an individual born in the 1930’s finishing 6 year of compulsory school might be have been the norm, while for someone born in 1990’s this is not only illegal (as the compulsory school has increased to 9 years), it is also very uncommon to not continue to upper secondary education (a total of 12 years education). Therefore, the individual with merely compulsory education born in the 30’s is most definitely different from the same individual born in the 90’s. This can also be seen in the changes of smoking habits, as smoking has decreased from the mid 20th century until the beginning of the 21st, also illustrated in table 2.

Behavioural factors – Smoking and BMI Current smoking was more common in the two oldest population samples (paper I, study sample from 2002-04) and paper II, study sample from 2006) compared to in the more recent study samples (table 2). This is in line with how the smoking habits have changed over the years in Sweden: in 2004, the percentage of current smokers was 16%, compared to 7% in 2018, and never-smokers increased from 56% in 2004 to 65% in 2018 according to the Swedish Public Health Agency (201). In papers I and III around 40% of the study sample had a BMI <25, while among young adults in paper IV, this number was around 60%, similar to data from the Swedish Public Health Agency’s survey in 2018 (201). There is however, still in 2018, a social gradient with current smoking being more prevalent among those with a low education or low income according to the Swedish Public Health Agency (appendix 4). While BMI generally has increased over the years in Sweden, overweight and obesity is still more common among those with lower education. Even though normal- and overweight is fairly equally common among those with high and low income, obesity is considerably more common among those with low income (appendix 4). These findings are in line with those of paper III, illustrated in figure 18. Health-related inequalities can be explained by the social gradient in these

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behavioural factors, why public health interventions that are aimed at socially vulnerable groups are of importance.

Figure 1820 –Smoking habits and BMI in the population sample of paper III by educational and income level. For comparison, data from Public Health Agency of Sweden 2018 is shown in appendix 4.

In paper III overweight (BMI > 25) was more common in the groups with a lower educational level than university level and obesity (BMI >30) was also more common in the lower income groups. In paper IV, high BMI was also more common in the categories of early-onset persistent and late onset asthma compared non-asthmatics (table 4). Individuals with asthma reports less physical fitness (159). Asthma might also lead to a higher BMI due to difficulties participating in physical activities, and obesity has previously been linked to low SES (158,159,202). On the other hand, studies have also linked low physical activity among adolescents to new-onset asthma (203). Thus, it seems, we land in a

20 From paper III

0%

20%

40%

60%

80%

100%

Higher Upper Secondary Compulsory

Educational level

Non-smoker Ex-smoker

Smoker <14 cig per day Smoker >15 cig per day

0%10%20%30%40%50%60%70%80%90%

100%

Higher Upper Secondary Compulsory

Educational level

Normal weight Overweight Obese

0%

20%

40%

60%

80%

100%

High MedHigh Med MedLow Low

Income levels in quintilesEqualized disposable income

Non-smoker Ex-smoker

Smoker <14 cig per day Smoker >15 cig per day

0%10%20%30%40%50%60%70%80%90%

100%

High MedHigh Med MedLow Low

Income levels in quintilesEqualized disposable income

Normal weight Overweight Obese

Smoking habits

BMI

Asthma

Low physical acitivity

High BMI

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circular reasoning: asthma is linked to low physical activity that is linked to high BMI that is linked to asthma.

In paper IV smoking was also more or equally as common among young adults in all asthma-categories compared to those without ever having had asthma (table 4). There are other studies suggesting that smoking may be more prevalent among asthmatic adolescents (204–206) and also that smoking is increasing among women (207,208). Smoking is also related to socioeconomic status (207) , as well as a factor that in some ways can be “inherited”: just over 50% of smoking adolescents had smoking parents, while 75% of non-smoking adolescents also had non-smoking parents (207). Smoking among asthmatics increases airway irritability and the number of exacerbations, (209) The benefits of smoking cessation among asthmatics are substantial as it improves lung function, quality of life and decrease daytime symptoms (210,211). Our findings support that increased smoking awareness among adolescents and young adults is still needed.

Table 4 – BMI and smoking habits in the different asthma-categories at age 19 years (year 2006) and at age 27-28 (year 2015) years (%). Data not published. Early onset,

persistent Early onset, in remission

Late onset Never asthma

Age

19

BMI <25 71.4 79.2 76.4 80.5 25-30 19.8 15.1 15.7 15.8 >30 8.8 5.7 7.9 3.7

Smoking habits

Non 77.8 75.9 74.3 79.8 Occasional 11.1 12.1 10.9 12.1 Current 11.1 12.1 14.9 8.1

Age

27-

28 BMI

<25 46.9 66.1 53.5 63.3 25-30 33.7 23.2 35.4 27.5 >30 19.4 10.7 11.1 9.1

Smoking habits

Non 83.3 70.2 74.0 82.1 Ex 10.4 21.0 17.0 12.0 Current 6.3 8.8 9.0 5.9

Asthma and respiratory symptoms The prevalence of asthma was highest in paper I (24.1%), which can be explained by an enrichment of individuals with respiratory symptoms due to the study design, as described above. In 2006 (paper II) the prevalence of asthma among adults was 10% and in 2016 (paper III) 11%, as previously published (80), which is in line other studies (91).

The prevalence of ever having had asthma up until 19 years of age was around 13%; ca 5% had an early-onset asthma, and 5% a late-onset asthma, with the rest having an early-onset asthma in remission before the age of 19. The prevalence of childhood asthma (which would be comparable to the definition of ‘ever asthma’ in paper IV) in northern and western Europe (with the exception of the UK) is between 10-15% (56,212–214).

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It has previously been shown in a study from 2014 that among those with a milder or intermittent asthma in childhood, about 60% were in remission at age 50, while this was true for 15% among those with a more severe asthma in childhood (215). In the study sample of paper IV, we found that around half of those with asthma in childhood or adolescence were in remission at the age of 27-28 years (table 5). While we can assume that the 5% of children with a persisting asthma has a more severe disease than those with asthma in remission, we cannot say if the actually can be classified as a “severe asthma” defined as uncontrolled asthma or asthma that requires high-dose treatments to remain under control (216). In this context, it is interesting to follow the change in asthma-prevalence until young adulthood, and in table 5 we can see how the categories of asthma in childhood and adolescence developed up until age 27-28 years. The total prevalence of asthma among young adults was 11.6% (data not published), in line with previous findings, of which a little more than every other had an asthma persisting from childhood or adolescence.

Table 5 – Development of asthma-categories throughout childhood, adolescence and young adulthood (%). Data not published. Total Women Men Early-onset persistent - persistent in adulthood 3.9 3.4 4.5 Early-onset persistent - in remission in adulthood 1.0 1.0 0.9 Early-onset in remission - relapse in adulthood 1.3 1.0 1.7 Early-onset in remission - in remission in adulthood 1.6 0.8 2.5 Late-onset - persistent in adulthood 2.7 3.6 1.7 Late-onset - in remission in adulthood 2.3 2.9 1.8 No asthma - adult onset 3.7 4.2 3.2 Asthma in childhood or adolescence persisting in adulthood 6.6 7.0 6.2 Ever asthma in childhood or adolescence in remission in adulthood 4.9 4.7 5.2 Adult onset or relapse in adulthood 5.0 5.2 4.9 Prevalence of asthma in adulthood 11.6 12.2 11.1

Social determinants of health

Job and occupational exposure The known associations between occupational exposure to VGDF and respiratory symptoms, asthma, and concomitant asthma and rhinitis (62) were confirmed in papers I and II, in paper I we found that this mainly seemed to be driven by exposure to chemicals. Increased automation in industries have decreased the number of manual workers in industries with typically dirty tasks, meaning that the burden of for examples dusts may have decreased and instead, exposure to chemical vapours, gases and fumes may have taken its place as the main contributing occupational exposure, at least with regard to asthma and rhinitis. It is well known that occupational exposure contributes to respiratory symptoms and asthma (60–62,217,218). A study among US nurses with asthma, suspected chemicals such as disinfectant agents to be the cause of asthma

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exacerbation and subsequent job change (219). Another US study found that inorganic dust was associated with work-related asthma exacerbations among men, while among women, the main occupational exposure associated to asthma exacerbations consisted of low-molecular weight agents such as highly reactive chemicals, epoxy and acrylates, all of which were included in the subgroup ‘chemicals’ of paper I (220). However, we did not find any indications that individuals with childhood asthma avoided occupations with exposure to GDF (paper IV), and further, we found trends that individuals with early-onset asthma leaned toward occupations in building and manufacturing, sector with possible risk of occupational exposure. Likewise, an Italian study published in 2017, showed that individuals with an established asthma (221) found that nearly half of the study sample (48.6%) reported occupational exposure to GDF and 41% had jobs where the risk of exposure to airway irritants was high.

Can occupational exposure among women be underestimated? A single-item question of VGDF or GDF in epidemiological studies is considered valid. However, in paper I we found that chemicals are the main contributing components in this composite term. While men reported more exposure to chemicals than women, it should be noted that chemicals was the most common exposure-group among women. Among these chemicals we find haircare-products, cleaning agents, solvents, dyes, colours/varnishes, insecticides/pesticides, glues etc., many of which are associated with occupations predominated by women. A question arises: would these individuals acknowledge that they were heavily exposed to vapours, gas, dust or fumes in their workplace? As seen in figure 19, occupational exposure was the most prevalent in occupational- and SEI-groups typically predominated by men and the patterns were similar in 2016 (paper III) and in 2006 (paper II). Thus, occupational exposure to VGDF might rather bring typically dirty, male dominated, industries to mind, and the burden of occupational exposure among women could be underestimated using a single-item question on occupational exposure to VGDF/GDF. These are my personal reflections, and this particular aspect has rarely been approached in studies using single-item questions of occupational exposure. However, an example of possible gender-bias in occupational asthma is reported in a Danish study of hairdressers which found that while hairdressers often reported asthma and respiratory symptoms, it was rarely reported as work-related or occupational asthma (222).

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Figure 19 – Distribution of occupational-exposure in the different SEI-groups in papers II21 and III.

Occupational groups In paper I, NYK was used to categorize occupations. This system was considered applicable to this population sample, as they were professionally active from the 1940’s onward. But, as discussed previously, the society has changed dramatically the last couple of decades and NYK has since been replaced by SSYK. As seen in paper II, SSYK can be used to identify groups at risk for respiratory symptoms, while NYK is less sensitive.

Between 25-30% of the study samples in 2006 (paper II) and of young adults in 2015 (paper IV) were in the SSYK-group of ‘occupations requiring higher education’ (a merging of the groups ‘managers’, ‘occupations requiring higher advanced education’ and ‘occupations requiring higher education’ in paper II) and overall the distribution of SSYK-groups seemed to be fairly similar among adults 2006 and young adults in 2015 (table 6). There were fewer workers in ‘agriculture’ and ‘manufacturing’ and more in ‘service’ and ‘occupations requiring higher education’. The numbers are in line with national data,

21 Modified version of one in paper II

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although the official statistics from Statistics Sweden are based on those currently employed in the ages 16-64 (223,224).

Table 6 – Distribution of SSYK-groups in papers II and IV respectively and nationally in Sweden during the same years according to Statistics Sweden (%). 2006 2015 Paper

II Swedish

population* Paper

IV Swedish

population* Occupations req higher education 26.7 41.1 31.6 42.1 Administration 10.4 9.0 7.1 8.1 Service 20.8 19.7 17.8 21.8 Agriculture 3.0 0.7 1.0 0.8 Building 13.9 8.8 12.9 9.0 Manufacturing 10.0 10.2 9.0 7.0 Elementary 5.0 5.9 3.0 5.4 Other and unspecified** 10.1 4.6 17.5 5.8 *percentage of employed aged 16-64, according to Statistics Sweden **‘other and unspecified’ includes students and non-employed individuals in papers II and IV.

The occupational groups of ‘building’, ‘manufacturing’ and ‘elementary’ were associated with wheeze, and ‘administration’, ‘service’ and ‘agriculture’ additionally with productive cough, but none were associated with asthma (paper II). These symptoms could in the future lead to the individuals having to change workplace due to respiratory disability, with impaired socioeconomic status as a possible effect, and enforcing the HWE. A Finnish study found that ca 5% of full-time workers with asthma had changed work-place mainly due to their asthma and 6% had changed occupation (225). Likewise the previously mentioned study among US nurses, asthma was associated with career change, and this was more pronounced among those with a severe asthma (219). As mentioned previously, also with regard to the HWE, asthma and respiratory symptoms can have adverse effects on career choices and socioeconomic status, and these socioeconomic aspects will be further discussed below.

Socioeconomic status

SEI-groups based on job-title The distribution of SEI-groups changed somewhat over time as illustrated in the different papers (figure 20). In the two older samples around half of the study samples were manual workers in service or industry (paper I and II) while in more recently recruited samples (paper III and IV) these groups were smaller. This might reflect a change in distribution of tasks in the society, where an increasing number of occupations fall in the category of non-manual employees. The large groups of other and unspecified in papers III and IV are probably due to a large number of students without job-title, an assumption based on the findings in paper II where 45% of those <30 years of age were students. The SEI-manual was first released in the 1980’s, it has been kept up to date, and as

51

shown in paper II, is a valid instrument to use for identifying groups at risk for respiratory conditions.

Figure 20 – Distribution of SEI-groups in papers I-IV

In paper II we found associations between manual workers and both productive cough and wheezing, while associations also were found between non-manual employees and productive cough. Previous Swedish studies have shown associations between low SES (based on occupation) and asthma (137,226), which also was found in paper III, where manual work in service was associated with asthma. Similarly, manual workers in service was associated with wheezing and rhinitis, manual workers in industry with productive cough and rhinitis and non-manual employees with attacks of SoB which has been shown previously (137). Among manual workers, the associations could possibly be explained by occupational exposure to GDF, as the associations lost statistical significance when adding this among the independent variables.

Educational level In papers III and IV women had proceeded to university level studies to a higher degree than men. Among all adults in paper III, ca 13% did not reach higher educational level than compulsory school, while this was true for ca 2% among 27-28-year olds (paper IV). In both samples, just over 50% had upper secondary school as their highest educational level and among young adults in 2015, the number of individuals that had not continued after compulsory school was low.

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This is in line with the trend of increasing educational level in general, according to official statistics from Statistics Sweden (figure 21) (227).

Figure 21 – Educational level among men and women every decade from 1985-2015, data from Statistics Sweden.

In paper IV we found that having persisting asthma throughout childhood and adolescence may have a negative impact on educational level in young adulthood. Although asthma since childhood might have a limited effect on grades from compulsory school (228), our findings suggest it seems to negatively affect the educational level in adulthood. It has previously been shown that chronic illness, such as asthma, has a negative effect on school attendance and poor academic career (157,159,161,162), which could be a possible explanation. In paper III, educational level below university was associated with productive cough. We also found that educational level below university was associated with all the behavioural factors such as smoking and high BMI as well as GDF-exposure (figure 18)

Income In paper III we found that women in general had lower income than men: 25.3% of the women had a low personal disposable vs 14.2% of the men (p<0.001), while on the contrary, for high personal disposable the numbers were 11.3% vs 29.6% respectively (p<0.001). For equalized disposable income, the income-groups were more evenly distributed, but for the lowest and highest groups, the pattern remained.

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Among adults in 2016 (paper III) a low or medium-low equalized disposable income were associated with attacks of SoB, productive cough and rhinitis, and for personal disposable income, this was also true for wheezing. This is in line with the findings from the Copenhagen General Population Study (229) where associations between low income and chronic cough were found. In the analysis of between income and sex, low-income women had an increased risk for asthma and respiratory symptoms (figure 16), similar to a US study (145). When looking at the behavioural risk factors for respiratory disease (smoking and BMI) and GDF-exposure, they were not as obviously related to low income, as to low education (figure 18). Thus, our results indicate that risk factors for respiratory disease seems more closely related to low education rather than low income while the reverse relationship was found for respiratory symptoms.

What is the point of using several measures of socioeconomic status in epidemiological research? As mentioned previously, socioeconomic status is a complex concept and using only one measure does not encompass the entire effect of SES on health-related outcomes (128,129). Using different measures of SES can yield differing, or even contradictory, results: asthma has been associated with being jobless (230) in an Iranian study as well as low income (145) in a US study, but an Israeli study on pre-recruit soldiers (231) found asthma to associate with high SES, based on place of residence. Previous studies on Swedish male conscripts have shown associations between low family SES (based on occupation) and asthma (226). In the papers of this thesis, using job-title as an indicator of socioeconomic status, manual work was associated with asthma. Regarding educational level, we did not find any clear associations between low education and asthma among adults, however, we found associations between childhood asthma and low education in young adulthood. Using income, we found that low income, especially among women, was associated with asthma. Thus, using different measures of SES, we see the associations between SES and asthma from different perspectives. By combining a population-based questionnaire survey with data from national registers (in paper III) we have combined the strengths of two methods of conducting epidemiological research. By using a validated questionnaire (46) we have a reliable source of information on respiratory symptoms, and from national register-based data of high quality, a reliable source on income and educational level (177,200).

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Conclusions

Social determinants in asthma Behavioural risk factors have changed. Smoking has decreased over the last few decades and BMI has increased, also illustrated in the included papers, however, there is still an obvious social gradient with increased burden among individuals with low socioeconomic status.

Occupational exposure to VGDF is associated with asthma, but we found that the component of chemicals seems to be the main contributor. This could introduce a gender-dependent bias, where occupational exposure to VGDF might not be recognized as such on typically female-dominated workplaces.

If detailed information on occupational exposure is unavailable and it is not feasible to construct a job-exposure matrix, the use of an ISCO-based manual such as SSYK or a socioeconomic classification system based on job-titles such as SEI, can be useful and easily applicable tools to identify occupational or socioeconomic groups at risk for respiratory symptoms and asthma.

In 2016, with the addition of register data to a large general population sample we could analyse several measures or indicators of socioeconomic status and found that low socioeconomic status is related to asthma and respiratory symptoms. It seems these associations relies more on low income than low educational level. Low educational level as well as low income, however, is related to known risk factors for respiratory symptoms and asthma such as obesity, smoking and occupational exposure to gas, dust or fumes in the workplace.

Having a persisting asthma since childhood is associated with lower educational level in young adulthood, with an increased risk for unfavourable behavioural factors such as smoking and obesity associated with respiratory symptoms and disease. Further, young adults with childhood asthma did not refrain from smoking during adolescence nor did they avoid occupations with exposure to gas, dust or fumes or occupations where such exposures can be expected (such as manufacturing, construction and transportation work).

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Thus, it seems, we find ourselves in a vicious circle regarding socioeconomic status and asthma. With increased knowledge of the interactions between the components in this circle we can tailor interventions and preventative measures both on public health and individual levels to break it. These measures can include broad public health interventions to decrease smoking and increase physical activity, and more individual ones, including patient-education on asthma, extra support during compulsory school and specific student counselling and vocational guidance

.

Childhood asthma

Low education

Smoking, obesity, VGDF-

exposure

Respiratory symptoms

Low income

Low family socioeconomic

status

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Future perspectives

Epidemiological research is an important field for understanding the “lie of the land” regarding the relationship between the disease under study and environmental factors, in the case of this thesis, social determinants in relation to asthma and respiratory symptoms. Reliable information can be gained from different sources. For example, data on current symptoms and asthma are more reliably collected from questionnaires or interviews, while for income and actual use of prescribed medication, register-based databases might be better sources. Thus, the combination of register-based data with epidemiological surveys gives an opportunity to display an image closer to the truth than what the both methods can give separately

There is limited knowledge on how asthma in childhood affects the individual in adulthood, why follow-ups on paediatric cohorts into adulthood is of great importance. Besides socioeconomic factors, further studies are needed on lung function development, persistence of asthma and how it remits and relapse over time. Taking off from the paper IV, it would be of interest to add register-based data to the follow-up of the paediatric cohort to gain a better, more multifaceted pictured of their socioeconomic status. Of course, continued follow-ups this cohort overtime is of interest, but there are also within the OLIN studies similar cohorts ten and twenty years younger to follow in the future.

There are several important research questions; Will the association between childhood asthma and socioeconomic status in young adulthood be of similar magnitude also in the later recruited paediatric cohorts? How large will the proportion with work-related asthma be in the future, and how large proportion will change workplace or occupation due to asthma? Further, conducting a qualitative study of the few individuals merely having compulsory school education could elucidate whether their asthma had any role in this. In perspective to paper III, it would be of interest to see if the associations found in 2016 were similar in 1996 and 2006 as well as if they still exist in 2026. It would also be of great interest to study the individuals followed from 1996 to 2016 to gain knowledge on what socioeconomic factors can be risk factor for disease, but also which factors that can be identified as determinants of health, possibly being able to prevent disease

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The associations between socioeconomic status and respiratory symptoms and asthma are complex, especially taking into consideration mediating and confounding factors such as obesity, smoking and occupational exposure. To further elucidate these associations, multidisciplinary research is required. Both quantitative cross-sectional studies, using different measures of socioeconomic status, and longitudinal studies to study the long-term health-related outcomes of socioeconomic measures are required. Also of importance are qualitative research to gain greater understanding of what factors on the individual’s level plays a role in the associations between socioeconomic status and respiratory illness. All of this if necessary to find the proper interventions and preventative measures for asthma to have as little negative impact on daily life as possible

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Acknowledgement

First of all, a great big Thank you! to all participants of the OLIN-studies. Without you, none of this would have been possible, for obvious reasons. Over the years, your willingness to participate has contributed considerably to increasing the knowledge on obstructive lung diseases. Secondly, thank you to all my colleagues, friends and family for your support during this process, also without you, none of this would have been possible. And of course, all of you research assistants, past present and future, who with unrelenting determination, makes sure all the data gets collected in the first place. One does not simply write a thesis on one’s own.

My supervisor Anne Lindberg, whose fault it is. Always encouraging and supportive. Thank you for introducing me and my fellow students to the OLIN-studies way back when and for easing me into the researcher’s way of life. Not only did you teach me how to “science” but also how to walk that fine line between research, clinical work and leisure. My co-supervisors: Eva Rönmark, for steering the OLIN ship with a steady hand. Martin Andersson, for expert knowledge on occupational medicine. Magnus Ekström, a scientific anchor in Blekinge, some 1500 km away from the OLIN-studies and for introducing me to the scientific activities and courses there. Also, your outside perspective on the OLIN methods gave valuable input. Linnea Hedman, who helped me the when I took my first trembling steps as a researcher that first summer as a research-assistant. All of you, thank you for invaluable guidance, scientific input and constructive and friendly criticism that always led to betterment of my work.

Further, Bo Lundbäck for initiating the OLIN-studies as well as for valuable scientific input. Helena Backman for all the help, advice, scientific input and attempts (most of them successful) to clarify statistical concepts. All other colleagues, students, fellow PhD-students and other “loose folk” for making the OLIN-studies such a great place “where everybody knows your name”. Sometimes when a paper comes back reviewed, completely torn to shreds, you just have to bite your upper lip and put sunglasses on (or maybe headphones), and having colleagues such as you, makes it that much easier.

My late parents Rose-Marie and Ingmar. Thank you for your never ending support, patience and for never, with regard to my life ambitions, ever uttering the words “nae, dä gaur ente” (approx. no, that won’t do). My sister Lena with family for all your support concerning everything from cat-guarding to house-keeping, boat-washing and house-letting and for always being by my side when life happens.

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My dear friend Markus for keeping me grounded throughout, and all the help with house- and cat-guarding as well as Magnus and Helena for providing me with much necessary game-related (as well as dog-related) distractions. Also, my friends Sofia and Kristofer with family also for helping out with cat- guarding as well as game-nights, not to mention pleasant baby-sitting-related distractions. Even if we aren’t golden girls just yet, thank you all for being a friend!

Thank you to Blekinge Centre for Research and Development of Applied Public Health, Blekinge Hospital and especially Kallinge primary health care centre, for giving me the possibility to extend my internship and your willingness to give me time for research as well as the Section of Sustainable Health at Umea University, all of you for giving me the possibility to participate in scientific activities and courses even if I was far away from my “scientific home”.

Last, but not least, but certainly smallest, the cats Trollet, Ebbot and Zelda, whom I have had the privilege to care for over the years and who, on more than one occasion, kept me on the right side of sanity when all the reviewer’s comments hit their hardest.

For financial support, the Swedish Research Council, the Swedish Heart-Lung Foundation, the Swedish Asthma and Allergy Association, VISARE NORR (Northern county councils’ regional federation), a regional agreement between Umeå University and Västerbotten County Council (Avtal om läkarutbildning och forskning, ALF), the Swedish Foundation for Health Care Science and Allergy research (Vårdalstiftelsen), Konsul Th C Berghs Stiftelse, NordForsk (an organisation under the Nordic Council of Ministers funding and facilitating Nordic cooperation on research), Norrbotten County Council and Blekinge County Council are all gratefully acknowledged.

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Appendix

Appendix 1 – AFA Insurance in brief

AFA Insurance (117) is an organisation owned by Sweden's labour market parties that insure employees within the private sector, municipalities and county councils. Today more than four point seven million people are covered by at least one of the insurances.

Appendix 2 – List of all incomesources gathered in the LISA-database

A comprehensive list of all incomesources that form the basis of disposable income in the LISA-database.

Appendix 3 – Short overview of the Swedish education system

A brief overview of the Swedish education system. Modified from the webpage of the Swedish National Agency for Education.

Appendix 4 – Smoking habits and BMI-categories by income and educational levels

Data from Public Health Reporting of 2018 by the Swedish Public Health Agency.

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Appendix 1 – AFA insurance in brief

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Appendix 2 – List of incomesosurces in the LISA-database

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Appendix 3 – Short overview of the Swedish education system

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Appendix 4 - Smoking habits and BMI-categories by income and educational levels in Sweden 2018