## THESE DE DOCTORAT DE

L'UNIVERSITE DE RENNES 1
Comue Université Bretagne Loire

ECOLE DOCTORALE N° 605
Biologie Santé

Spécialité : Epidémiologie, analyse des risques, recherche clinique

Par

Aviane AUGUSTE

# Epidémiologie des cancers des voies aéro-digestives supérieures aux Antilles Françaises

## Facteurs de risque comportementaux, viraux et environnementaux

### Epidemiology of head and neck cancer in the French West Indies

### Behavioural, viral and environmental risk factors

Thèse présentée et soutenue à Pointe-à-Pitre, le 2 décembre 2019

Unité de recherche : Irset (Institut de recherche en santé, environnement et travail) – Inserm UMR 1085

Thèse N° :

Rapporteurs avant soutenance :

Mathieu NACHER Professeur, Praticien Hospitalier, Université de Guyane

Marie-Claude ROUSSEAU Professeure, Institut National de la Recherche Scientifique, Laval, Canada

### Composition du Jury :

- Président : Eustase JANKY

- Examinateurs : Moana GELU-SIMEON

- Rapporteurs : Mathieu NACHER
Marie-Claude ROUSSEAU

- Professeur, Praticien Hospitalier, Université des Antilles

- Maître de conférences, Praticien Hospitalier, Université des Antilles

- Professeur, Praticien Hospitalier, Université de Guyane

- Professeure, Institut National de la Recherche Scientifique, Canada

Dir. de thèse : Danièle LUCE

Directrice de recherche Inserm, Université de Rennes
## THESE DE DOCTORAT DE

L'UNIVERSITE DE RENNES 1

COMUE UNIVERSITE BRETAGNE LOIRE

ECOLE DOCTORALE N° 605

Biologie Santé

Spécialité : Epidémiologie, analyse des risque, recherche clinique

Par

**Aviane AUGUSTE**

# Epidémiologie des cancers des voies aéro-digestives supérieures aux Antilles Françaises

Facteurs de risque comportementaux, viraux et environnementaux

## Epidemiology of head and neck cancer in the French West Indies

Behavioural, viral and environmental risk factors

### Thèse présentée et soutenue à Pointe-à-Pitre, le 2 décembre 2019

Unité de recherche : Irset (Institut de recherche en santé, environnement et travail) – Inserm UMR 1085

### Rapporteurs avant soutenance :

Mathieu NACHER Professeur, Praticien Hospitalier, Université de Guyane

Marie-Claude ROUSSEAU Professeure, Institut National de la Recherche Scientifique, Laval, Canada

### Composition du Jury :

- Président : Eustase JANKY

- Examinateurs : Moana GELU-SIMEON

- Rapporteurs : Mathieu NACHER
Marie-Claude ROUSSEAU

- Professeur, Praticien Hospitalier, Université des Antilles

- Maître de conférences, Praticien Hospitalier, Université des Antilles

- Professeur, Praticien Hospitalier, Université de Guyane

- Professeure, Institut National de la Recherche Scientifique, Canada

- Dir. de thèse : Danièle LUCE

- Directrice de recherche Inserm, Université de Rennes
**Résumé :**

L'objectif était d'évaluer le rôle de différents facteurs de risque dans la survenue des cancers des voies aéro-digestives supérieures (VADS) aux Antilles françaises. Dans un premier temps, nous avons utilisé les données d'une enquête transversale sur la santé pour décrire la prévalence du tabagisme, de la consommation d'alcool et de l'obésité, et mis en évidence des disparités sociales. Nous avons ensuite analysé les données d'une étude cas-témoins menée en Martinique et en Guadeloupe entre 2013 et 2016, comprenant 145 cas de cancers des VADS et 405 témoins. Une prévalence élevée d'infection orale par le papillomavirus (HPV) a été mise en évidence, avec une distribution par génotype spécifique, en particulier une faible fréquence d'HPV16. L'infection orale aux HPV à haut risque (Hr-HPV) était associée à une augmentation significative du risque de cancer des VADS. Les consommations de tabac et d'alcool augmentaient fortement le risque de cancer des VADS, avec un effet combiné synergique.

Un faible indice de masse corporelle (IMC), des antécédents familiaux de cancer des VADS, et plusieurs activités professionnelles étaient également associés à un risque accru. L'utilisation du préservatif diminuait le risque, indépendamment de l'infection à Hr-HPV. Chez les femmes, un âge précoce aux premières règles était associé à une diminution du risque. Les consommations de thé, de café, de fruits et de légumes n'étaient pas associées au cancer des VADS.

Dans la population, la majorité des cas de cancers des VADS étaient attribuables au tabagisme (62,5 %) et à l'alcool (55,4 %). Environ 14 % des cas étaient attribuables à l'infection orale à Hr-HPV, 11 % à un faible IMC, 27 % à la profession et 7 % aux antécédents familiaux. Étant donné l'impact prépondérant des facteurs modifiables, de nombreuses opportunités de prévention des cancers des VADS se présentent dans cette population.

**Abstract:** The objective was to assess the potential influence of a large spectrum of risk factors on head and neck cancer (HNC) development in the French West Indies (FWI). As a first step, we used data from a cross-sectional

health survey to describe the prevalence of tobacco smoking, alcohol drinking and obesity. This work highlighted significant social disparities in these risk factors in the population.

We then analysed data from a population-based case-control study conducted in Martinique and Guadeloupe between 2013 and 2016, including 145 cases of HNC and 405 controls.

The study revealed a high prevalence of oral infection with human papillomavirus (HPV) in the population, and a specific distribution of HPV genotypes. HPV52 was the most prevalent type and HPV16 was found in only 4% of cases. Tobacco smoking and alcohol drinking increased the risk of HNC, with a synergetic combined effect.

High risk HPV (Hr-HPV) was associated with a significant increase in HNC risk, particularly in non-smokers and non-drinkers. Elevated risks of HNC were found in several occupations. A low body mass index (BMI) and family history of HNC were also associated with an increased risk of HNC. Condom use was found to decrease the risk of HNC, independently of oral HPV. In women, exposure to hormones, notably having menarche before 13, was associated with a decrease in HNC risk. Consumptions of tea, coffee, fruits and vegetables were not associated with HNC.

In the population, the majority of HNC cases were attributable to tobacco smoking (62.5%) and alcohol (55.4%). About 14% of the cases were attributable to Hr-HPV, 11% to low BMI, 27% to occupation and 7% to family history of HNC. Given the predominant role of modifiable factors in HNC aetiology, there are many opportunities for prevention in this population.
Acknowledgements

My deepest heartfelt appreciation goes to my PhD advisor, Dr Danièle Luce. Words cannot
express my gratitude towards you. I count myself extremely lucky to do my PhD under your
supervision. Never have I met someone who makes exceptional things seem so normal. I am
truly greatful for your many teachings and your mentorship. Thank you for your availability,
your immense humility, your patience, your encouragement (especially towards the end).
Thank you for the general knowledge and geography lessons. An enormous thank you for the
many opportunities you granted me to go outside of Guadeloupe to attend training seminars to
better my research skills. Thanks so much for allowing me to monopolise your time and for
not abandoning me at the most crucial times. Working on this PhD thesis with you has been a
real pleasure for me and I am elated to have reached this point.

I would like to express my gratitude to Pr Marie-Claude Rousseau for having agreed to be a
primary examiner on my PhD panel and for accepting the responsibility of evaluating my
work. Pr Mathieu Nacher, I thank you as well for accepting without hesistation the
responsibility of primary examiner, and I take the moment to thank you for your trust in me in
assisting in your epidemiology classes at the *Université des Antilles* these past years. I am
deeply grateful to Pr Eustase Janky, president of *Université des Antilles*, and Dr Moana
Siméon-Gélu for taking time off their busy schedule to be part of my PhD panel.

I thank Dr Nathalie Théret, the director of the doctoral school Biology and Health (Ecole
doctoral Biologie-Santé, EDBS) and fellow member of Irset, for allowing me to enroll in your
establishment and for authorizing me to participate in the training seminars at the *Université
des Antilles*. I thank as well Badia Mssassi, the administrative manager of the doctoral school
Biology and Health for her efficient service during my PhD training.

I would like to offer my special thanks to the co-investigators of the case-control study
(ICARE-Antilles), without which this thesis would not have been possible. Thank you Dr
Jacqueline Deloumeaux for your good sense of humour, your immense dedication and
committment to advance public health research in the region. Thank you Pr Suzie Duflo for
your ambition to participate in the realisation of this project. Many thanks to Stanie Gaete for
your enthousiam in the ICARE-Antilles study, your availability and willingness to assist in
the preparation of the manuscripts. Not forgetting Benard Bhakkan, many thanks to you as
well for your presence and assistance throughout my thesis. Thanks for all the advice you
have given me and thanks for book on SAS macro-language, it really helped a lot. My thanks
go out to Lucina Lipau who was nice enough to explain to me her role in the study and for the
allowing me to observe her work for the day. I would like to express my gratitude to Dr
Clarisse Joachim and the team at the Martinique Cancer registry for their participation in the
study and having agreed to meet with me when I started my PhD in Guadeloupe.

I would like to thank Dr Michel Samson, current director of Irset, my Inserm unit whose
assistance was instrumental in the procurement of funds for my PhD grant. My deepest
appreciation goes to you Dr Bernard Jégou, former director of Irset. Thank you for your
efficiency, your advice, your sincereity and your many visits to Guadeloupe throughout my
PhD which were very much appreciated. I would like to thank Pr Yves Roquelaure, the head
the ESTER team for your contribution the team as a whole and for your warm welcome
during my visits in Angers.

To my tutors, Dr Gwenn Menvielle and Dr Loredana Radoï for thank you very much for
having accepted this responsibility without hesistation, and for our discussions during our
annual meetings and for being good role models.

I would like to thank all my colleagues at Irset Guadeloupe, past and present for the conducive working environment and for our numerous group discussions in the office. Special thanks to Nathalie for your bubbly personality, and your encouragement and for the many outings and hikes you’ve suggested to us. Thank you Léïla for accepting my crazy experiment of inviting you into our research team as a Masters intern. Thank you for kindness and remembering everyone’s birthday etc. Many thanks to Léah and Mrs Michineau for your efficiency and the many times you have assisted me administratively. Thank you to Julien for coming to my rescue that first day we met in Guadeloupe. I will never forget the day we met and the mess that I was in when I arrived. Thanks for your immense kindness and for always being eager to share your knowledge in statistics with me. My deepest heartfelt appreciation goes to Christy. From day one you were like a bigger sister to me. You supported me from day one and still right now you’re cheering me on. Thank you for your advice whether personal or professional. Thanks for your kind spiritedness and for our many conversations that made life in the office a lot more enjoyable.

I am deeply grateful to my African brother and fellow team member, Abou. What can I say, your ambition just baffles me sometimes. Many thanks to you for uniting all the other PhD students in our team for our monthly meetings. Thanks for your advice and assistance in methodology when I needed help. Thank you to all the other PhD students in the ESTER team, in particular Hai, Déborah and Laure.

I am deeply grateful to my parents who have always supported my academic and professional decisions and who have always encouraged me to fight for what I want in life. I would like to thank my family, in particular my brothers, Lester and Darius, and my cousin Esai for their support and interest in what I do. Many thanks to my cousin Jean who always pushed me to go as far I as can.

I would like acknowledge my friends in Guadeloupe who have made my stay on this island more meaningful and allowed me to put aside the stresses of being a PhD student. Special thanks to Yasmine for your company and your positive energy. Thank you to René and Marie-Laure for your continuous support and encouragement.

I would like to offer my special thanks to my colleagues in Saint Lucia, in particular Dr Owen Gabriel and Dr Carlene Radix for taking the time to listen to my crazy ideas and trusting me
enough to execute them. Your support has had considerable impact on me as a professional
and has renewed the confidence I have in Saint Lucia as a developing nation. Thank you to
my fellow AC3 members Dr Camille Ragin and Dr Glenn Jones for your advice and your
commitment to the training of the future generation of Caribbean scientists.

Finally, I would like to thank everyone who participated in the success of this PhD thesis and
to those who helped me to get to this point.

SPECIALS THANKS TO THE LIGUE CONTRE LE CANCER FOR THEIR
SUPPORT

<figure><img src="image_1.png" /></figure>

ILLE-ET-VILAINNE

This PhD thesis was made possible by the funding of the "Ligue contre le Cancer, comité d'Ille-et-Vilaine"
Scientific communications relative to the doctoral thesis

Articles

**Aviane Auguste**, Stanie Gaete, Cécile Herrmann-Storck, Leah Michineau, Clarisse Joachim, Jacqueline Deloumeaux, Suzy Duflo, Danièle Luce.

Prevalence of oral HPV infection among healthy individuals and head and neck cancer cases in the French West Indies. Cancer Causes Control (2017) 28: 1333

**Aviane Auguste**, Julien Dugas, Gwenn Menvielle, Christine Barul, Jean-Baptiste Richard, Danièle Luce. Social distribution of tobacco smoking, alcohol drinking and obesity in the French West Indies. BMC Public Health 19, 1424 (2019)

**Aviane Auguste**, Jacqueline Deloumeaux, Clarisse Joachim, Stanie Gaete, Léah Michineau, Cécile Herrmann-Storck, Suzy Duflo, Danièle Luce.

Joint effect of Tobacco, Alcohol and Oral HPV infection on Head and Neck Cancer risk in the French West Indies (submitted for publication)

**Aviane Auguste**, Clarisse Joachim, Jacqueline Deloumeaux, Stanie Gaete, Léah Michineau, Cécile Herrmann-Storck, Suzy Duflo, Danièle Luce.

Population attributable fractions of head and neck cancer risk factors in the French West Indies (submitted for publication)

**Aviane Auguste**, et al.

Association between Sexual Behaviour and Head and neck cancer in the French West Indies
(ongoing preparation for submission)
## Oral presentations

**Aviane Auguste**, Stanie Gaete, Cécile Herrmann-Storck, Leah Michineau, Clarisse Joachim, Jacqueline Deloumeaux, Suzy Duflo, Danièle Luce.

Epidemiology of Head and Neck Cancer in the French West Indies: The Role of Tobacco, Alcohol and Viral Factors. Inaugural annual scientific symposium, Ecole doctorale Biologie-Santé, Université de Bretagne-Loire, Rennes, France, 12-13th December 2018.

**Aviane Auguste**, Stanie Gaete, Cécile Herrmann-Storck, Leah Michineau, Clarisse Joachim, Jacqueline Deloumeaux, Suzy Duflo, Danièle Luce.

Prevalence of oral HPV infection among healthy individuals and head and neck cancer cases in the French West Indies.

- Clinical research symposium of the Guadeloupe University Hospital, Abymes, Guadeloupe, 22nd -23rd November 2018

- Caribbean Biomedical Research Days, International Stress and Behaviour Society, Gros-Islet, Saint Lucia, 16-18th January 2018

- Young researchers of Irset symposium, Irset, Rennes, France, 11th January 2018

**Aviane Auguste**, Stanie Gaete, Cécile Herrmann-Storck, Leah Michineau, Clarisse Joachim, Jacqueline Deloumeaux, Suzy Duflo, Danièle Luce.

Epidemiology of HNC in the French West Indies. 15th Annual INHANCE Meeting, Milan, Italy, 29th June 2018
## Posters

**Aviane Auguste**, Jacqueline Deloumeaux, Clarisse Joachim, Stanie Gaete, Léah Michineau, Cécile Herrmann-Storck, Suzy Duflo, Danièle Luce.

Exposition professionnelles et cancer des voies aérodigestives supérieures aux Antilles Françaises. 20<sup>th</sup> Aderest symposium on occupation health, Toulouse, France, 14-16th November 2019.

**Aviane Auguste**, Jacqueline Deloumeaux, Clarisse Joachim, Stanie Gaete, Léah Michineau, Cécile Herrmann-Storck, Suzy Duflo, Danièle Luce.

Joint effect of Tobacco, Alcohol and Oral HPV infection on Head and Neck Cancer risk in the French West Indies. 7th biannual meeting of the African Caribbean Cancer Consortium, Kingston, Jamaica, 11-14th October 2019.

**Aviane Auguste**, Julien Dugas, Gwenn Menvielle, Christine Barul, Jean-Baptiste Richard, Danièle Luce.

Social Distribution of Tobacco Smoking, Alcohol Drinking and Obesity in the French West Indies.

- Inaugural international BIOSPHERES symposium, Fort-de-France, Martinique, June 2019

- 6<sup>th</sup> biannual meeting of the African Caribbean Cancer Consortium, Miami, USA, October 2017

**Aviane Auguste**, Stanie Gaete, Cécile Herrmann-Storck, Leah Michineau, Clarisse Joachim, Jacqueline Deloumeaux, Suzy Duflo, Danièle Luce.

Prevalence of oral HPV infection among healthy individuals and head and neck cancer cases in the French West Indies. 6th biannual meeting of the African Caribbean Cancer Consortium, Miami, USA, October 2017
## Other scientific communications

### Articles

Christine Barul, Mireille Matrat, **Aviane Auguste** Julien Dugas, Loredana Radoï, Gwenn Menvielle, Joelle Févotte, Emilie Marrer, Isabelle Stücker, and Danièle Luce

Welding and the risk of head and neck cancer: the ICARE Study (manuscript under review in Occupational and Environmental Medicine)

### Oral presentations

#### Aviane Auguste.

CME lecture: Population science to the service of cancer control in the OECS and presentation of study concept. Monthly CME lecture for medical practitioners in Saint Lucia (breaking the paradigm in disease prevention), Saint Lucia Medical and Dental Association, Castries, Saint Lucia, 4th July 2019.

#### Aviane Auguste.

Project concept presentation for AC3 Mentor-Mentee program: Description of the Cancer Health Services in Saint Lucia: Diagnosis and Treatment and Pathways (DCAP) study. Young investigators retreat, Caribbean Institute for Health Research (CAIHR), Kingston, Jamaica, 4th April 2019.

#### Aviane Auguste.

Regional Workshop on HIV Drug Resistance Study Results: Report on Data Management and Analysis. HIV-TB elimination programme, Organisation of Eastern Caribbean States (OECS), Port-of-Spain, Trinidad, 21st-22nd March 2019.
## Posters

Loïc Delannay, Carlene Radix, Dorothy Phillip, James St. Catherine, Elizabeth Dos Santos, Owen Gabriel, Aviane Auguste.

Description of the Cancer Health Services in Saint Lucia: Diagnosis and Treatment and Pathways (DCAP). 7th biannual meeting of the African Caribbean Cancer Consortium, Kingston, Jamaica, 11-14th October 2019.

Leïla Cabréra, Aviane Auguste, Jacqueline Deloumeaux, Clarisse Joachim, Leah Michineau, Suzy Duflo, Danièle Luce.

Expositions professionnelles et cancer du poumon aux Antilles Française. Inaugural international BIOSPHERES symposium, Fort-de-France, Martinique, June 2019

## Grants and awards

Organisation of Eastern Caribbean States (OECS), Saint Lucia

- Attribution of a small grant to conduct pilot survey on cancer care pathways in Saint Lucia from January 2019

National Institute of Health/National Cancer Institute (NCI) of the USA

- Junior investigator travel award for the 15th Annual INHANCE Meeting in Milan on the 29th June 2018

- Travel grant from the Centre for Global Health to attend the National Cancer Institute's (NCI) 2018 Summer Curriculum course titled "Principles and Practice of Cancer Prevention and Control" on July 9th-August 3rd, 2018.

## International training programs

- **Principles and Practice of Cancer Prevention and Control**

National Cancer Institute (NCI) of the USA, 9th July-3rd August 2018 (4 weeks), Washington D.C, MD, USA

- **Genetic epidemiology and Aetiological epidemiology**

European Educational Program in Epidemiology (EEPE), 3rd-7th July 2017 (5 days), Florence, Italy
Table of contents

<table><tr><td>1</td><td>Introduction</td><td>15</td></tr><tr><td>1.1</td><td>Anatomy and pathology of head and neck cancer</td><td>16</td></tr><tr><td>1.2</td><td>Descriptive epidemiology of head and neck cancer</td><td>17</td></tr><tr><td>1.2.1</td><td>Incidence and mortality data in the world</td><td>17</td></tr><tr><td>1.2.2</td><td>Incidence and mortality data in the French West Indies</td><td>19</td></tr><tr><td>1.3</td><td>Risk factors</td><td>21</td></tr><tr><td>1.3.1</td><td>Tobacco consumption</td><td>21</td></tr><tr><td>1.3.2</td><td>Alcohol drinking</td><td>22</td></tr><tr><td>1.3.3</td><td>Joint effect of tobacco and alcohol</td><td>23</td></tr><tr><td>1.3.4</td><td>Oral hygiene</td><td>23</td></tr><tr><td>1.3.5</td><td>Oral HPV infections</td><td>23</td></tr><tr><td>1.3.6</td><td>Body mass index</td><td>24</td></tr><tr><td>1.3.7</td><td>Socioeconomic status</td><td>24</td></tr><tr><td>1.3.8</td><td>Occupational exposures</td><td>25</td></tr><tr><td>1.3.9</td><td>Diet and non-alcoholic beverages</td><td>25</td></tr><tr><td>1.3.10</td><td>Hereditary and genetic factors</td><td>26</td></tr><tr><td>1.4</td><td>Presentation of the French West Indies</td><td>27</td></tr><tr><td>2</td><td>Objectives of the thesis</td><td>30</td></tr><tr><td>3</td><td>Materials and methods</td><td>31</td></tr><tr><td>3.1</td><td>Baromètre santé DOM</td><td>31</td></tr><tr><td>3.1.1</td><td>Study Design</td><td>31</td></tr><tr><td>3.1.2</td><td>Study population</td><td>31</td></tr><tr><td>3.1.3</td><td>Data collection</td><td>33</td></tr><tr><td>3.1.4</td><td>Statistical analysis</td><td>33</td></tr><tr><td>3.2</td><td>Case-control study</td><td>37</td></tr><tr><td>3.2.1</td><td>Study design</td><td>37</td></tr><tr><td>3.2.2</td><td>Study population</td><td>37</td></tr><tr><td>3.2.3</td><td>Data collection</td><td>39</td></tr><tr><td>3.2.4</td><td>Biological specimen collection</td><td>41</td></tr><tr><td>3.2.5</td><td>DNA extraction and biological assays</td><td>42</td></tr><tr><td>3.2.6</td><td>Study Sample</td><td>43</td></tr><tr><td>3.2.7</td><td>Data-entry and management</td><td>43</td></tr><tr><td>4</td><td>Results</td><td>55</td></tr><tr><td>4.1</td><td>Social Distribution of Tobacco Smoking, Alcohol Drinking and Obesity in the French West Indies</td><td>56</td></tr><tr><td>4.2</td><td>Prevalence of oral HPV infection among healthy individuals and head and neck cancer cases in the French West Indies</td><td>65</td></tr><tr><td>4.3</td><td>Joint effect of Tobacco, Alcohol and Oral HPV infection on Head and Neck Cancer risk in the French West Indies</td><td>75</td></tr><tr><td>4.4</td><td>Population attributable fractions of head and neck cancer risk factors in the French West Indies</td><td>104</td></tr><tr><td>4.5</td><td>Association between Sexual Behaviour and Head and neck cancer in the French West Indies</td><td>132</td></tr><tr><td>4.6</td><td>Supplementary results</td><td>157</td></tr><tr><td>4.6.1</td><td>Fruits and vegetable consumption and head and neck cancer</td><td>157</td></tr><tr><td>4.6.2</td><td>Tea, coffee and juice/soda consumption and head and neck cancer</td><td>161</td></tr><tr><td>4.6.3</td><td>Occupational exposures and head and neck cancer in the French West Indies</td><td>162</td></tr><tr><td>5</td><td>General discussion</td><td>171</td></tr><tr><td>5.1</td><td>Background</td><td>171</td></tr></table>
<table><tr><td>5.2</td><td>Main findings</td><td>171</td></tr><tr><td>5.3</td><td>Strengths and limitations</td><td>176</td></tr><tr><td>6</td><td>Conclusion and perspectives</td><td>178</td></tr><tr><td>7</td><td>Résumé en Français</td><td>180</td></tr><tr><td>7.1</td><td>Introduction</td><td>180</td></tr><tr><td>7.2</td><td>Objectifs</td><td>181</td></tr><tr><td>7.3</td><td>Matériel et Méthodes</td><td>182</td></tr><tr><td>7.4</td><td>Principaux résultats</td><td>183</td></tr><tr><td>7.4.1</td><td>Tabagisme, consommation d'alcool et obésité dans la population antillaise</td><td>183</td></tr><tr><td>7.4.2</td><td>Prévalence de l'infection orale à HPV dans la population générale et les cas de cancer des VADS</td><td>183</td></tr><tr><td>7.4.3</td><td>Effets conjoints du tabac, de l'alcool et de l'infection orale à HPV sur le risque de cancer des VADS</td><td>184</td></tr><tr><td>7.4.4</td><td>Fractions de cancers des VADS attribuables aux différents facteurs de risque</td><td>184</td></tr><tr><td>7.4.5</td><td>Comportement sexuel et risque de cancer des VADS</td><td>185</td></tr><tr><td>7.5</td><td>Conclusion et perspectives</td><td>185</td></tr><tr><td>8</td><td>Bibliography</td><td>187</td></tr></table>
AC3- African Caribbean Cancer Consortium

BMI- Body Mass Index

CI- Confidence interval

FWI- French West Indies

HNC- Head and neck Cancer

HNSCC- Head and neck squamous cell carcinoma

HPV-Human papillomavirus

Hr-HPV- High-risk Human papillomavirus

IARC – International Agency for Research on Cancer

INHANCE- International Head and Neck Cancer Epidemiology Consortium

MICE- Multiple imputation by chained equations

OR- Odds ratio

PAF- Population attributable fraction

PR- Prevalence ratio

SES- Socioeconomic status
<table><tr><td>Table 1: Estimated age-standardized incidence rates (World) in 2018, all ages, both sexes (per 100,000)</td><td>28</td></tr><tr><td>Table 2: Estimated age-standardized incidence rates (World) in 2018, all ages</td><td>29</td></tr><tr><td>Table 3: Breakdown of participation in the Baromètre Santé DOM survey in Martinique and Guadeloupe</td><td>32</td></tr><tr><td>Table 4: Explanation of the concept of interaction - Notations</td><td>52</td></tr><tr><td>Table 5: Association between fruits and vegetable consumption and HNSCC</td><td>158</td></tr><tr><td>Table 6: Association between fruits and vegetable consumption and ever tobacco smoking</td><td>159</td></tr><tr><td>Table 7: Association between fruits and vegetable consumption and daily alcohol drinking</td><td>159</td></tr><tr><td>Table 8: Association between fruits and vegetable consumption and HNSCC stratified by daily alcohol drinking</td><td>160</td></tr><tr><td>Table 9: Association between tea,coffee and juice/soda consumption and HNSCC</td><td>161</td></tr><tr><td>Table 10: Association between occupations and HNSCC using major occupational groups</td><td>163</td></tr><tr><td>Table 11: Association between occupations and HNSCC using two-digit ISCO codes</td><td>164</td></tr><tr><td>Table 12: Association between occupations and HNSCC using five-digit ISCO codes</td><td>166</td></tr><tr><td>Table 13: Association between industries and HNSCC using two-digit NAF codes</td><td>169</td></tr><tr><td>Table 14: Summary of statistical associations from the thesis</td><td>175</td></tr></table>
# 1 Introduction

My doctoral research consisted of examining the role and impact of various known and suspected risk factors on the development of head and neck cancer (HNC) in the French West Indies (FWI) in an attempt to better understand the etiology of this disease and consequently inform public health policies that are adapted to the local context. The main tool for my research was data from a case-control study conducted in the FWI between 2013 and 2016. I also used data from a cross-sectional survey, the Baromètre Santé DOM (2014).

The first part of this doctoral thesis gives an overview of the research topic and a brief literature review on HNC in particular the behavioural, viral and environmental risk factors. The second part lists my objectives; the third part provides details of the methodology and tools used during my PhD. The fourth section displays the results of this doctoral work in the form of scientific articles, followed by a general discussion on the work in its entirety and finally a summary in French.
## 1.1 Anatomy and pathology of head and neck cancer

Head and neck cancer affects the upper aerodigestive tract (UADT), which comprises the sino-nasal cavities, pharynx, oral cavity and the larynx (Figure 1). The oesophagus is also sometimes counted in the subsites of HNC but generally dissociated because of its histological and aetiological particularities compared to the other HNC sites. The nasal cavity is subdivided into a right and a left nasal fossa by the median nasal septum, consisting of bony and cartilaginous components. The pharynx is a muscular tube lined with mucous membrane. It extends downward from the base of the cranium to the level of the sixth cervical vertebra, where it becomes continuous with the oesophagus. The pharynx is composed of three main portions, the nasopharynx, the oropharynx and the hypopharynx. The oropharynx is positioned in the buccal portion of the pharynx positioned at the first three cervical vertebrae. The hypopharynx is positioned further down at the fourth and fifth cervical vertebrae just before the larynx at the sixth cervical vertebrae. The larynx comprises three sections, the supraglottis, glottis and subglottis [1]. The UADT support functions in respiration, phonation, deglutination, and sense apparatus for olfaction and taste.
<figure><img src="image_2.png" /><figcaption>**Figure 1:** Main anatomical zones of human upper aerodigestive tract (source: Liebertz D et al., 2010) [2]</figcaption></figure>

The majority of head and neck cancers occur in the squamous cells that line the moist, mucosal surfaces of the upper aerodigestive tract. Squamous cells are thin, flat cells that form the lining of various internal organs, including the hollow organs and ducts of some glands, the skin and eyes. These squamous cell cancers are referred to as head and neck squamous cell carcinomas (HNSCC). Other histological manifestations include adenocarcinomas and undifferenciated carcinomas. The latter histological types are found mainly in nasopharyngeal cancer, sinonasal cancer and salivary gland cancer. For the purpose of this doctoral thesis we focused primarily on cancers of the oral cavity, oropharynx, hypopharynx and the larynx.

## 1.2 Descriptive epidemiology of head and neck cancer

### 1.2.1 Incidence and mortality data in the world

Head and neck cancer accounts for more than 650,000 cases worldwide. The most common malignancy is squamous cell carcinoma (SCC) of the lip and oral cavity followed by the
pharynx and the larynx. Cancer of the salivary gland is the least frequent when compared to the other head and neck subsites [3]. Men and older persons are consistently more affected by head and neck cancer worldwide. Regions which have elevated incidence rates around the world (≥ 9.6 new cases annually per 100 000 inhabitants in 2018) are The United states of America, India, Australia, Cuba, Papua New Guinea and Most of Western Europe. Countries in Africa and South America have fewer cases annually (Figure 2).

<figure><img src="image_3.png" /><figcaption>**Figure 2:** Heat map of age standardised incidence and mortality rate for cancers of the lip, oral cavity, oropharynx, hypopharynx and larynx in both men and women among worldwide (Source: Global Cancer Observatory: Cancer Today 2018. IARC, 2018) [4]</figcaption></figure>

France is ranked overall 8th in the world for head and neck cancer (lip, oral cavity, larynx, oropharynx and hypopharynx). In 2018, age-standardized (world) incidence rates of head and neck cancer per 100,000 in France were estimated to be 25.9 in men and 7.2 in women. In terms of mortality, head and neck cancer is responsible for more than 330,000 deaths worldwide annually. Among all continents, age-standardized (world) mortality rates of head and neck cancer per 100,000 were the highest in Europe. In France, the mortality rates were 6.6 in men and 1.3 in women [4] (Figure 3-4).
<figure><img src="image_4.png" /><figcaption>**Figure 3:** Age standardised incidence and mortality rate for cancers of the lip, oral cavity, oropharynx, hypopharynx and larynx in men among the first 15 countries worldwide (Source: Global Cancer Observatory: Cancer Today 2018. IARC, 2018) [4]</figcaption></figure>

<figure><img src="image_5.png" /><figcaption>**Figure 4:** Age standardised incidence and mortality rate for cancers of the lip, oral cavity, oropharynx, hypopharynx and larynx in women among the first 15 countries worldwide (Source: Global Cancer Observatory: Cancer Today 2018. IARC, 2018) [4]</figcaption></figure>

### 1.2.2 Incidence and mortality data in the French West Indies

Guadeloupe and Martinique are two French overseas territories in the French West Indies (FWI). The population of the French West Indies which is predominantly Afro-Caribbean is
covered by two regional cancer registries, the cancer registry of Guadeloupe which was
established in 2008, and the Martinique cancer registry which was established in 1983. In
2018, age-standardized (world) incidence rates of head and neck cancer per 100,000 were
estimated to be 8.1 in Guadeloupe (men: 15.5; women: 2.1) and 5.7 in Martinique (men: 12.1;
women: 0.6). These incidence rates, especially in men, are among the highest in Latin
America and the Caribbean. In terms of mortality, in 2018, age-standardized (world) rates per
100,000 were estimated to be 3.0 in Guadeloupe (men: 6.5; women: 0.2) and 2.5 in
Martinique (men: 5.7; women: 0) [4] (Figure 5).
Estimated age-standardized incidence and mortality rates (World) in 2018, all ages

<figure><img src="image_6.png" /><figcaption>**Figure 5:** Age standardised incidence and mortality rate for cancers of the lip, oral cavity, oropharynx, hypopharynx and larynx in both men and women among the first 15 countries in Latin America and the Caribbean (Source: Global Cancer Observatory: Cancer Today 2018. IARC, 2018) [4]</figcaption></figure>

## 1.3 Risk factors

### 1.3.1 Tobacco consumption

Tobacco smoking is an established risk factor for head and neck cancer. Tobacco smoking have been shown to induce a 4-5-fold increase in risk for oral cavity, oropharyngeal and hypopharyngeal cancer, whereas the increase was 10-fold for cancer of the larynx [5]. All forms of tobacco smoking are causally associated with head and neck cancer, including cigarettes, cigars, pipes and bidi smoking, a common form of tobacco smoking in India [6, 7].
It is however unclear whether one of these products confer a greater risk than the others [6]. On the other hand, head and neck cancer risk has been shown to differ according to the type of cigarette smoked. Rolled cigarettes and black tobacco confers a higher risk of head and neck cancer compared to manufactured cigarettes and blond tobacco [6]. There is also limited evidence that second-hand smoke, whether at home or at work, is associated with the risk of cancer of the larynx and the pharynx [6-8]. Other tobacco related practices, including tobacco chewing and using snuff tobacco, are also causally associated with cancer of the oral cavity. People in certain regions in Asia chew betel quids, containing areca nut, betel and often tobacco, which are known to increase the risk of oral and pharyngeal cancer [6, 7].

In epidemiological studies, dose-response relations have been consistently reported between head and neck cancer and intensity (cigarette/day), duration, and cumulative consumption of cigarettes (pack-years of lifetime consumption) [6]. In addition, a study from the INHANCE consortium demonstrated that the duration of cigarette smoking is the strongest determinant of the risk of head and neck cancer. Indeed the risk was more elevated in persons smoking fewer cigarettes/day for a longer duration than in person smoking greater cigarettes/day for a shorter duration [9]. The association between age at initiation of tobacco has been studied in previous reports that tended to show an inverse relationship with age and HNSCC risk [10-13]. However, a large pooled analysis by the INHANCE consortium did not show any significant increase in HNSCC risk and age at initiation of tobacco smoking [14].

### 1.3.2 Alcohol drinking

Alcohol drinking is associated with head and neck cancer. High intensity of alcohol drinking (50g per day) has been shown to increase the risk of cancers of the oral cavity and pharynx by three-fold, and two-fold for laryngeal cancer [15]. Alcohol drinking duration was also associated with head and neck cancer risk but had a less important role than the intensity [9]. On the other hand, age at initiation of alcohol drinking have not been demonstrated to be
associated with head and cancer risk [14, 16]. Regarding the types of beverages consumed, no clear differences have been demonstrated in head and neck cancer risk from one beverage to the next [17]. However the overall consensus is that the most frequently consumed beverage in a particular area is associated to the greatest increase in risk [15, 18].

### 1.3.3 Joint effect of tobacco and alcohol

It is well established in the literature that tobacco and alcohol act synergistically on head and neck cancer risk. Previous studies have shown strong evidence of more than additive and at least multiplicative joint effects [19]. The population attributable risk fraction for ever tobacco and alcohol drinking was estimated at 72% by a pooled study from the INHANCE consortium; whereas the attributable fractions for tobacco and alcohol individually were only 33% and 4% respectively. There was as well some heterogeneity in the attributable fractions between subsites. The majority of the laryngeal cancer cases were explained by the joint effect of tobacco and alcohol, whereas the attributable fraction was lower for cancers of the oral cavity and the pharynx (64% and 72% respectively).

### 1.3.4 Oral hygiene

Proper oral hygiene has been shown to be inversely associated to head and neck risk. A pooled analysis by the INHANCE consortium found that brushing of teeth daily, annual visits to the dentist and having not more than 5 teeth missing decreased the risk of head and neck cancer [20]. In contrast, mouthwash containing alcohol increased the risk of oral and oropharyngeal cancer [21, 22].

### 1.3.5 Oral HPV infections

The human papillomavirus (HPV) has long been associated to ano-genital cancers and since 1990, there has been growing evidence towards an association with head and neck cancer. Unlike cervical cancer, HPV has not been demonstrated as an indispensable driver of head and neck carcinogenesis. However, in 2007, the IARC stated for the first time that there was
adequate epidemiological and molecular knowledge to deduce an etiological role of HPV in non-ano-genital cancers [23]. Studies are providing growing evidence on a role of HPV to the oropharynx and more specifically cancers of the tonsils and the base of the tongue. Sexual transmission is thought to be involved in oral HPV infection, in particular oral sex and a high number of oral sex partners [24]. There are many different genotypes of HPV which are classified mainly according the oncogenic risk associated with them [25]. The low-risk types e.g HPV 6 and 11, are have been associated with laryngeal cancer [26] and are known to cause benign warts [27]. HPV16 and 18 are well known high-risk types and are well known to be involved in head and neck carcinogenesis [27]. Numerous studies have demonstrated significant associations with HPV16, HPV18 and other high-risk HPV types and head and neck cancer [25, 28–31].

### 1.3.6 Body mass index

Previous studies have shown that a low body mass index (<18.5 kg) was significantly associated with an increase in head and neck risk [32, 33]. A large pooled analysis from the INHANCE consortium showed that persons with low BMI were two times more likely to develop head and neck cancer than those with a normal BMI. Furthermore, inverse associations for obesity have been observed. These findings oppose the conventional positive association between BMI and most other cancers.

### 1.3.7 Socioeconomic status

Regardless of the indicator used (education, occupation or income), lower socioeconomic status has been associated with an increase in head and neck cancer when compared to persons of higher socioeconomic status [34, 35]. Health behaviour of persons across socioeconomic is thought of as a driver for these social disparities in head and neck cancer risk. However, after adjustment for tobacco smoking and alcohol drinking the association with socioeconomic status remains suggesting that these social disparities are not entirely
explained by behavioural factors [34]. Occupational exposure on the hand, could explain partially the association between socioeconomic status and head and neck cancer [36].

### 1.3.8 Occupational exposures

Laryngeal cancer is more consistently associated to occupational exposure than the other head and neck subsites. The International Agency for Research on Cancer (IARC) has indicated that the occupational exposures for which sufficient evidence exist for laryngeal cancer are asbestos and strong inorganic acid mists [37]. Although the evidence is limited, other occupational factors such as manufacturing of rubber have been associated with and elevated risk of laryngeal cancer. Similarly, exposure to asbestos and work in the printing industry was associated to cancer of the pharynx [38–40]. No evidence has been shown to support any causal link between occupational exposures and cancer of the oral cavity [40]. On the other hand, an augmented risk of head and neck cancer has been associated with numerous occupations such as textile and leather workers, butchers, carpet workers, machinists, female electronics workers, welders, painters, and construction workers [41, 42]. Laryngeal cancer in particular has been associated with formaldehyde, man-made mineral fibres, mustard gas, organic solvents and dusts from cement, metal, coal, leather and wood [43–46].

### 1.3.9 Diet and non-alcoholic beverages

Diet and nutrition have been suggested to play an important role in the etiology of head and neck cancer. Particularly, a high consumption of fruits and vegetables has been consistently associated to a decreased risk of oral and oropharyngeal cancer and to a lesser extent laryngeal cancer [47–49]. Previous studies from Italy showed that approximately 20–25% of cancers of the head and neck low were attributable to a low vegetable and fruit consumption [50]. Vegetables and fruits are rich in vitamins C and E, carotenoids as well as flavonoids, with antioxidant and antitumor effects which may help prevent head and neck cancer [51–53]. In terms of coffee and tea, no consistent evidence in the association with cancer of the oral
cavity and pharynx arose from epidemiological studies [54–56]. However, there is some
evidence of an elevated risk for maté drinkers, popular herbal infusion traditionally consumed
in Argentina and some areas of Brazil [57].

1.3.10 Hereditary and genetic factors

A family history of head and neck cancer among first-degree relatives is associated with an increased risk of head and neck cancer [58, 59]. Single nucleotide polymorphisms related to alcohol metabolism (ex. Alcohol dehydrogenase and aldehyde dehydrogenase) were shown to be associated with an increase of head and neck cancer [60]. Other studies investigating polymorphisms and genes involved in alcohol or tobacco metabolism, notably the genes glutathione-S-transferase M1 (GSTM1) and GSTT1 show some evidence that these genes may act as markers to determine the genetic susceptibility in HNSCC patients and in their first-degree relatives [61–63]. The INHANCE consortium conducted a genome wide association study to identify common genetic variation involved in susceptibility to head and neck cancer. Their study revealed 5 variants associated with HNSCC that in combination explained approximately 4% of HNSCC familial risk [64].
## 1.4 Presentation of the French West Indies

The French West Indies is a region in the Caribbean Sea and comprises overseas territories of France (départements et collectivités d'outre-mer), which include Guadeloupe, Martinique, Saint-Martin and Saint Barthelemy. Saint-Martin and Saint-Barthélemy were initially a part of the Guadeloupe region but became separate collectivités d'outre mer after a referendum in 2007. For the purpose of this thesis, we focused on Guadeloupe and Martinique, the two départements d'outre-mer. Guadeloupe is an archipelago of 1628 km² and is composed of two main islands, Basse-Terre and Grande-Terre which are joint together side-by-side by two bridges. The archipelago comprises as well several other islands like Marie-Galante, les Saintes and Désirade. Martinique is an island of 1128 km² south of Guadeloupe. In 2016, the population of Guadeloupe and Martinique were each approximately 400 000 inhabitants and are primary of Afro-Caribbean ethnicity [65]. Compared to mainland France, the French West Indies possess a younger population and a higher unemployment rate, in particular among persons under 20 years old. In addition, the population suffers from high levels of precarity measured by the great proportion of persons benefiting from universal health care coverage (Couverture maladie universelle) and from support for low income (Revenu de solidarité active). Further disparities exist in terms of health care. The French West Indies have a lower medical density, notably for specialist doctors. Cardio-metabolic diseases and cancer are the leading causes of death in the French West Indies. In addition, sickle cell is regarded as the leading genetic disorder in this population [66]. The cancer incidence in the FWI is generally in-between mainland France and other Caribbean territories [4, 67]. The two most frequent cancer sites in the French West Indies are prostate and breast cancer. The cancer incidence for the French West Indies is lower than that of metropolitan France for lung cancer, but higher for stomach cancer, cervical cancer and especially for prostate cancer (table 1 and table 2). These differences in cancer epidemiology could partly attributable to the African ancestry of
the French West Indian population which is notably strongly associated with high prostate cancer incidence [67] or to differences in the prevalence of risk factors [68]. The prevalence of tobacco smoking is low in the FWI [69]. It should be noted that the difference between mainland France and the French West Indies in head and neck cancer incidence is less marked than for lung cancer despite their association with tobacco. Alcohol consumption is also moderate in the FWI population and lower than in mainland France, although the types of alcoholic beverages differ [69]. A high prevalence of high-risk HPV cervical infection has been reported in Guadeloupe, but the prevalence of oral HPV infection in the FWI is not known [70]. The FWI also have some distinctive features in terms of occupational hazards, with special activities such as banana and sugar cane farming and sugar cane industry that confers onto the population specific occupational and environmental exposures. Pesticides have been extensively used in the French West Indies over the years. Chlordecone in particular was widely used in banana plantations and the exposure to this organochlorine pesticide has been shown to increase the risk of prostate cancer [71].

<table><caption>**Table 1:** Estimated age-standardized incidence rates (World) in 2018, all ages, both sexes (per 100,000). (Source: Global Cancer Observatory: Cancer Today 2018. IARC, 2018) [4]</caption><thead><tr><th></th><th>Guadeloupe</th><th>Martinique</th><th>France</th><th>Latin America and Caribbean</th></tr></thead><tbody><tr><td>Prostate</td><td>189.1</td><td>158.4</td><td>99.0</td><td>56.4</td></tr><tr><td>Breast</td><td>68.9</td><td>78.3</td><td>99.1</td><td>51.9</td></tr><tr><td>Colorectum</td><td>19.8</td><td>23.9</td><td>30.4</td><td>16.8</td></tr><tr><td>Stomach</td><td>12.3</td><td>10.0</td><td>4.9</td><td>8.7</td></tr><tr><td>Lung</td><td>9.4</td><td>10.6</td><td>36.1</td><td>11.8</td></tr><tr><td>Cervix uteri</td><td>9.3</td><td>7.6</td><td>6.7</td><td>14.6</td></tr><tr><td>Head and neck</td><td>8.1</td><td>5.7</td><td>16.2</td><td>6.6</td></tr><tr><td>All cancers</td><td><strong>254.6</strong></td><td><strong>250.8</strong></td><td><strong>344.1</strong></td><td><strong>189.6</strong></td></tr></tbody></table>
<table><caption>**Table 2:** Estimated age-standardized incidence rates (World) in 2018, all ages. (Source: Global Cancer Observatory: Cancer Today 2018. IARC, 2018) [4]</caption><thead><tr><th rowspan="2"></th><th colspan="3">Men</th><th colspan="3">Women</th></tr><tr><th>Guadeloupe</th><th>Martinique</th><th>France</th><th>Guadeloupe</th><th>Martinique</th><th>France</th><th>Latin America & Caribbean</th></tr></thead><tbody><tr><td>Prostate</td><td>189.1</td><td>158.4</td><td>99.0</td><td>56.4</td><td>NA</td><td>NA</td><td>NA</td></tr><tr><td>Breast</td><td>NA</td><td>NA</td><td>NA</td><td>NA</td><td>68.9</td><td>78.3</td><td>51.9</td></tr><tr><td>Colorectum</td><td>21.2</td><td>29.0</td><td>36.9</td><td>18.4</td><td>18.5</td><td>19.8</td><td>15.5</td></tr><tr><td>Stomach</td><td>16.1</td><td>13.1</td><td>7.2</td><td>11.3</td><td>9.3</td><td>7.5</td><td>6.6</td></tr><tr><td>Lung</td><td>13.0</td><td>12.3</td><td>51.3</td><td>15.1</td><td>6.5</td><td>9.2</td><td>9.2</td></tr><tr><td>Head and neck</td><td>15.5</td><td>12.1</td><td>25.9</td><td>10.9</td><td>2.1</td><td>0.6</td><td>2.9</td></tr><tr><td>Cervix uteri</td><td>NA</td><td>NA</td><td>NA</td><td>NA</td><td>9.3</td><td>7.6</td><td>14.6</td></tr><tr><td>All cancers</td><td><strong>342.9</strong></td><td><strong>308.9</strong></td><td><strong>405.6</strong></td><td><strong>200.3</strong></td><td><strong>183.1</strong></td><td><strong>201.1</strong></td><td><strong>292.9</strong></td><td><strong>183.7</strong></td></tr></tbody></table>
Despite a low prevalence of tobacco smoking and alcohol drinking, incidence rates of head and neck cancer in Guadeloupe and Martinique are among the highest in the Americas. Consequently, the HNC burden in this region was thought to be attributable to other risk factors such as human papillomavirus (HPV), diet, family history of cancer, occupational and environmental risk factors.

The overall objective of this doctoral thesis was to assess the potential influence of various risk factors on head and neck cancer development in the FWI.

Considering the lack of published data on behavioural risk factors in the FWI, the initial work of this thesis consisted of a secondary analysis of the data from a cross-sectional survey, the Baromètre Santé, to produce a detailed description of tobacco smoking, alcohol and obesity prevalence in the general population, according to gender, age and socioeconomic status.

The main part of the work was the analysis of a population-based case-control study on head and neck cancer conducted in the FWI. This is the first epidemiological study of this kind in an Afro-Caribbean population. A large spectrum of risk factors was examined, with a focus on tobacco smoking, alcohol drinking and oral HPV infection. More precisely, the objectives were:

* to study and quantify the associations between head and neck cancer risk and behavioural risk factors (tobacco, alcohol, diet, sexual behaviour), viral risk factors (HPV infection), occupational exposures, anthropometric measures, family history of cancer,

* to evaluate possible interactions between these risk factors,

* to estimate the impact of these different risk factors in this population, by calculating population attributable risks.
3.1 Baromètre santé DOM

3.1.1 Study Design

The Baromètre Santé DOM is a national cross-sectional health survey conducted in the FWI
in 2014. The survey was based on a random two stage sampling method, in Martinique and
Guadeloupe, to obtain a sample representative of the general population [72].

3.1.2 Study population

Landlines and mobile phone numbers were randomly generated and individuals were
randomly selected from that list and contacted by field investigators to conduct the interview
over the phone. Participants aged between 15 and 75 years of age residing in Martinique or
Guadeloupe and able to speak either French or Creole were eligible for inclusion. The survey
sample was separated into two subgroups, the sample of persons contacted by a landline
telephone, and a sample of persons contacted through a mobile phone. For the landlines
group, once the eligible household was successfully reached by telephone, one person
satisfying the inclusion criteria was interviewed. Replacement by another member of the
family was not allowed in the survey. The method for the selection of members of a
household used for this survey was the method proposed by Leslie Kish as described
elsewhere [73]. In the mobile phone sample, the regular users of the mobile phone lines were
selected. Conventionally, a mobile phone is a personal item; however, the number of users of
that mobile phone line was verified by asking "how many persons between 15 and 75 years
use regularly use this phone to receive calls including yourself". In the case of multiple users
of the same mobile phone line, the Kish method was applied in the same manner as the
landline sample but this time it was among the users of the mobile phone [73].
Out of 12236 usable numbers from the phone listing, 8057 were dialled. In the end, 4089 subjects were included in the final sample for Martinique and Guadeloupe. The overall participation rate for the French West Indies was 51%.

<table><caption>**Table 3:** Breakdown of participation in the Baromètre Santé DOM survey in Martinique and Guadeloupe.</caption><thead><tr><th></th><th colspan="2">Martinique</th><th colspan="2">Guadeloupe</th></tr><tr><th></th><th>n</th><th>%</th><th>n</th><th>%</th></tr></thead><tbody><tr><td>landline and mobile phone sample</td><td></td><td></td><td></td><td></td></tr><tr><td>Usable numbers</td><td>5866</td><td></td><td>6370</td><td></td></tr><tr><td>Numbers dialled</td><td>3736</td><td></td><td>4321</td><td></td></tr><tr><td>Unreachable after dialling</td><td>1177</td><td>32</td><td>1655</td><td>38</td></tr><tr><td>Refusal (household and individual)</td><td>404</td><td>11</td><td>488</td><td>11</td></tr><tr><td>Abandon</td><td>134</td><td>4</td><td>110</td><td>3</td></tr><tr><td><strong>Participation rate</strong></td><td><strong>2021</strong></td><td><strong>54</strong></td><td><strong>2068</strong></td><td><strong>48</strong></td></tr></tbody></table>

<figure><img src="image_7.png" /><figcaption>**Figure 6:** Difference between observed and expected frequency (Chi-square test) by municipality</figcaption></figure>
### 3.1.3 Data collection

Field investigators were briefed on the sampling procedures and were trained to administer the questionnaire over the phone. The questionnaire covered multiple themes surrounding health including health care seeking habits, screening, health risk awareness, mental health and consumption of psychoactive substances. The field data collection was performed between April and November 2014. The study questionnaire was administered through computer-assisted telephone interviews (CATI). Every telephone number was dialled 20 times and each attempt to reach the potential participant, the field investigator allowed the phone to ring 6 times before hanging up. In the case of a busy phone line, a new attempt was made 15 minutes later. When there was no response, the number was dialled later that same day. Every number had to be dialled several days with at least two calls on Saturday before excluding the potential participant. For the purpose of this doctoral thesis, we selected a subset of variables set pertaining to cancer risk factors and socioeconomic status from the final data. We selected information on tobacco, alcohol consumption, body mass index (BMI). We used as well 4 variables related to socioeconomic status: education, occupational category, income and availability of hot water at home.

### 3.1.4 Statistical analysis

#### 3.1.4.1 Univariate analysis

The details for the prevalence calculations for the cancer risk factors in the French West Indies are detailed below. Consider the contingency table below as a reference for the notations used in formulas shown in this section.

<table><thead><tr><th>SES indicator</th><th>Risk factor+</th><th>Risk factor-</th><th>Total</th></tr></thead><tbody><tr><td>SES<sub>1</sub></td><td>a</td><td>b</td><td>E<sub>1</sub></td></tr><tr><td>SES<sub>2</sub></td><td>c</td><td>d</td><td>E<sub>0</sub></td></tr><tr><td>Total</td><td>H<sub>1</sub></td><td>H<sub>0</sub></td><td>E<sub>t</sub></td></tr></tbody></table>
**SES:** socioeconomic indicator/sociodemographics (education, occupational category, income and availability of hot water at home/age and sex)

**a:** Person in first SES category exposed to a given risk factor

**b:** Person in first SES category not exposed to a given risk factor

**c:** Person in the 2nd SES category exposed to a given risk factor

**d:** Person in the 2nd SES category not exposed to a given risk factor

**E:** Total number of persons in a given SES stratum

**H:** Total number of persons exposed to a given risk factor

The overall prevalence for each risk factor in our population was calculated in the following manner:

$$P_{factor} = H_1/E_t (overall)$$

The prevalence for each risk factor by age and sex was calculated in the following manner, and then for each category of the four socioeconomic indicators stratified by sex:

$$P_{factor} = a/E_1 (SES_1)$$

$$P_{factor} = c/E_0 (SES_2)$$

### 3.1.4.2 Multivariate analysis

#### 3.1.4.2.1 Poisson regression

In statistics, Poisson regression is a generalized linear model form of regression analysis used to model count data and contingency tables. This model was used to fit the data for our analyses on social inequalities in cancer risk factors because it is robust and produces prevalence ratios which are more appropriate than estimating odds ratios which would otherwise tend to overestimate the actual effect size when the event of interest is not rare [74].
The Poisson regression is based on the assumption that the outcome variable, Y and the linear combination of explanatory variables are independent and follow a Poisson distribution and assumes the logarithm of its expected value can be modelled by a linear combination of unknown parameters. The logarithm of μ is used as the link function in this model.

The basic Poisson regression model can be written as follows

$$E(Y_i|X_i) = \mu_i = e^{\beta_0 + \beta_1 x_{i1} + \beta_2 x_{i2} + \dots + \beta_n x_{in}}$$

When introducing an offset term nᵢ, to take into the account of the weight of the observation.

The model can be written in this manner:

$$E(Y_i|X_i) = \mu_i = n_i + e^{\beta_0 + \beta_1 x_{i1} + \beta_2 x_{i2} + \dots + \beta_n x_{in}}$$

It can also be expressed as follows:

$$\ln(\mu_i) = \ln(n_i) + \beta_0 + \beta_1 x_{i1} + \beta_2 x_{i2} + \dots + \beta_n x_{in}$$

Where μ: The mathematical expectancy of the outcome variable

β₀: intercept

βᵢ: regression coefficient showing the association between each explanatory variable and the outcome variable

xᵢ: explanatory variable

nᵢ: The offset term accounting the weight of the observation

The regression parameters for the Poisson regression are estimated using the maximum likelihood method which consists of maximising the likelihood function. The likelihood is the probability of observing a sample and can be written as follows:

$$V(\beta) = \prod_{i=1}^{n} \left[ \frac{e^{-\mu_i} - \mu_i^{\beta_i}}{\beta_i!} \right]$$

The exponential of the regression parameters from the poisson model was calculated to generate the prevalence ratios (PR) their 95% confidence intervals (CI) for our study.
3.1.4.2.2 Weighting adjustments

A sample should be representative of the source population from which it is drawn in regards to all measured variables in a survey. Usually the sample obtained deviates from this ideal situation due to several issues including non-response. The over- and under-representation of certain groups or characteristics could occur as a result of non-response. When issues such as this one arise, weighting adjustment can be used to correct for the lack of representativity. The method consists of assigning a survey weight to each participant. Persons in under-represented groups get a weight larger than 1, and those in over-represented groups get a weight smaller than 1. The individual weights are determined based on the auxiliary variables used. Auxiliary variables (e.g. age and sex) are characteristics that are measured in the study sample and for which data are available on the population distribution. This adjustment weight is used for the calculation of means, totals and percentages as well as the raw values of the variables.

In the Baromètre Santé DOM, data were weighted in two steps [72]. To account for the
sampling design, sample weights were computed according to the probability of selection of
the telephone number, the number of eligible individuals for each telephone number, the
number of landline and cell phones of the individual. To correct for non-response, a post-
stratification was then performed to match the distribution of the population, according to sex,
age, education level and household structure, using data from the 2011 census in Martinique
and Guadeloupe. This method works under the assumption that in each defined category by
the adjustment variables, the respondents and non-respondents are on average similar in
regards to the variables of interest for the survey.
## 3.2 Case-control study

### 3.2.1 Study design

The majority of data from this thesis were drawn from a population-based case-control study which was conducted in the two overseas French departments in the FWI, Martinique and Guadeloupe, and was performed with the collaboration of the cancer registries from these departments. The study is an extension of a large nationwide case-control study, the ICARE study, which has already been conducted in ten French regions covered by a cancer registry [75].

### 3.2.2 Study population

#### 3.2.2.1 Recruitment of cases

Cases were all patients suffering from a primary, malignant tumor of the oral cavity, pharynx, larynx, (International Classification of Diseases, 10th Revision, codes C00-C14; C32), newly diagnosed during the study period in the two "départements" of the FWI (Martinique and Guadeloupe), of any histological type. Only histologically confirmed cases aged over 18 and less than 75 years old at the time of diagnosis were included

Poor survival for some of the cancers included in this study did not allow relying on routine inclusion of cases in the registries for their identification. A procedure was set up to expedite case identification, in order to reduce the delay between diagnosis and interview of cases.

Cases were identified through active search, by regular contacts and visits to the pathology laboratories and hospital departments that usually diagnose and treat head and neck cancers.

A list of these laboratories and hospital departments was established by each registry, based on data of the previous years. In each region, more than 95% of recorded cases have been treated in only 3 hospitals departments, and 80% of the recorded cases have been treated in the ENT departments of the two University hospitals, Pointe-à-Pitre in Guadeloupe and Fort-
de-France in Martinique. The local pathology laboratories (3 in Guadeloupe and 2 in Martinique) have notified more than 98% of the cases.

Eligible cases were invited to participate by the ENT surgeons as far as possible, at the time they find most appropriate, otherwise by another physician. A letter of information was handed to them or sent to their home. If the patient agreed, written consent was collected, notably for the donation of biological specimens, and an appointment was made for the interview. If the diagnosis was not histologically confirmed at the time of interview, cases with a strong clinical suspicion were interviewed, pending subsequent confirmation.

### 3.2.2.2 Recruitment of controls

The control group was a random sample of the general population of the study area. Controls were frequency matched to the cases by age, sex and study centre (Martinique or Guadeloupe). Additional stratification was used to obtain a distribution by socioeconomic category comparable to that of the population (obtained from census data), in order to control for possible selection bias arising from differential participation rates across socioeconomic status categories.

Recruitment of controls was done by telephone (landlines and cell phones) in collaboration with a polling institute experienced in this type of procedure and possessing the necessary tools and personnel. First, a random sample of numbers was generated. Each number was called 10 times before being abandoned as not answered. Calls were made in the evening on weekdays and during the day on Saturdays. Recruitment was done by trained interviewers from the polling institute. These interviewers received a half-day specific training to better understand the objectives of the study, so that they can better answer eventual queries from the contacted subjects. When an eligible subject was identified by telephone call, the objectives of the study and terms of participation were explained and agreement to participate was sought. If contacted persons agreed to participate, they were informed that an interviewer
from INSERM would contact them soon, and a letter of information was sent. A list of
persons agreeing to participate was given to the study interviewer who contacted them in turn,
to confirm their agreement and to make an appointment for the interview.

Control recruitment waves were conducted every two months, by groups of 40 subjects (20 by department). The number of recruits was based on the estimated total number of cases and the expected participation rate among controls. Their distribution by sex and age were initially based on the characteristics of cases notified to the registries in the two previous years, and was later adjusted as necessary depending on the age and sex distributions of cases and controls recruited at that time. Their distribution by socioeconomic status was based on census data, taking age and sex into account.

3.2.3 Data collection

Cases and controls were interviewed face-to-face. The following information was collected
during the interview:

* Socio-demographic characteristics (sex, age, marital status, educational level, occupation of parents and spouse, place of birth and parents' place of birth);

* Residential history;

* Anthropometric characteristics (height, weight at interview, weight 2 years before interview, weight at 30 years of age);

* History of cancer and various diseases;

* History of cancer among first-degree relatives;

* Hormonal and reproductive factors (for women only): age at menarche, age at menopause, oral contraceptives, menopausal hormonal therapy, number and outcomes of pregnancies number of children, age at first birth
* Smoking of cigarettes, cigars, cigarillos and pipe, with beginning and end dates, quantity per day, type of cigarette (blond or brown tobacco, filtered or not, brand), for each smoking episode; questions on snuff or chewing tobacco;

* Passive smoking during childhood, at workplace and at home during adulthood;

* Alcohol consumption, with beginning and end dates, quantities, types of alcohol for each period of regular consumption (wine, beer, rum, other spirits);

* Usual diet, with a food frequency questionnaire

* Occupational history, with a detailed description of each job held, and specific occupational questionnaires for tasks or occupations frequently encountered or of special interest for the study.

* Agriculture

* Sugarcane industry

* Construction

* Hair dressing

* Motor vehicle maintenance

* Wood worker

* Tool maker and machinist

* Painting

* Plumbing

* Welding

* Textile

* Leather worker

* Sexual history and behavior (number of lifetime sexual partners, age at first intercourse, use of condoms, frequency of oral sex, and history of sexually transmitted infections...)
### 3.2.4 Biological specimen collection

#### 3.2.4.1 Saliva samples

During face-to-face interviews, participants were asked to provide a saliva sample, using the Oragene® OG-500 kit (DNA Genotek). Samples were sent to the Biological Resource Centre of Guadeloupe for storage at 24°C. Oragene® saliva specimen may be stored for at least 5 years at room temperature without DNA degradation [76].

Each subject included in the study gave a written and informed consent. In order to protect the confidentiality of personal data, the questionnaire included only an identification number, without any nominative information.

#### 3.2.4.2 Buccal swabs

Exfoliated oral cells in cases and controls were also be collected by performing superficial scrapes of the oral mucosa with cytobrushes (2 per subject). Cytobrushes were sent to the Biological Resource Center of Guadeloupe, where they were stored at -80°C.

#### 3.2.4.3 Fresh frozen tumour samples

Fresh tumor samples were collected from biopsy or surgery at the University hospital of Guadeloupe. Samples were put in a labeled cryotube and directly immersed in a liquid nitrogen non-pressurized container, placed permanently in the operating room. Samples were then stored at -80°C in a controlled freezer (Forma 900, Thermo Fischer Scientific /Massachusetts, USA) at the Center for Biological Resources Karubiotec. Fresh frozen samples were obtained for 86 cases. This procedure could not be set-up in Martinique, for practical reasons.
### 3.2.5 DNA extraction and biological assays

#### 3.2.5.1 DNA extraction from saliva

The extraction of DNA was manually performed on saliva samples. Genomic DNA extraction was carried out using prepIT®•L2P reagent. The samples were mixed and incubated overnight (16 hours) at 50°C to ensure that DNA was released and that nucleases were permanently inactivated. Addition of the prepIT®•L2P reagent revealed all impurities and the DNA in the supernatant was precipitated by adding EtOH 100%. The DNA was washed and the pellet re-suspended in a solution of DNA Hydration (Qiagen®) and then stored at -20°C.

#### 3.2.5.2 HPV detection and genotyping

The detection of Human Papilloma Virus was performed with InnoLipa® kit, which allows the detection of the following genotypes: HPV16, HPV18, HPV31, HPV33, HPV35, HPV39, HPV45, HPV51, HPV52, HPV56, HPV58, HPV59, HPV68 (High-risk), HPV26, HPV53, HPV66, HPV70, HPV73, HPV82 (Probable high risk), HPV06, HPV11, HPV40, HPV42, HPV43, HPV44, HPV54, HPV61, HPV81 (Low risk), HPV62, HPV67, HPV83, HPV89 (Other). The InnoLipa HPV genotyping assay is based on the detection of a specific region (SFP10) that is the most conserved in the L1 ORF of many HPV (6,7).

The amplification was performed using SFP10 based primers that amplify a 65-bp region, and with adding primers to amplify human HLA-DPB1 region for having a control of the DNA quality at the same time. The amplification was performed in a reagent mixture containing biotinylated primers in buffer with dNTP/dUTP mix, MgCl2 and 0.05% NaN3 as preservative and ampliTaq Gold and uracil-N-glycosylase (UNG) to prevent RNA from contaminating the sample. Before amplification, DNA was added.

All of PCR reactions were performed with a positive and a negative control. The biotinylated PCR products were genotyped by denaturation and hybridization on nitrocellulose strips
followed by a stringent wash. After the addition of the conjugate and the substrate, a colorimetric analysis revealed all the genotypes present in the sample. The hybridization process was automatically performed on the Autoblot 3000H, at the end, the strip was fixed on a support to read the HPV genotypes lines correspondence.

Due to the presence of primers that amplify all genotypes simultaneously, if there was more competition between particular genotypes, only the presence of a broad range of HPV was detected with the line control HPV1 and/or the line control HPV2. This kind of sample was notified HPV-positive without specifying the genotype. These samples were classified as “undetermined” and were included in the calculation for the prevalence of oral HPV infection regardless of the genotype. However, these samples were excluded from the individual genotype analysis.

### 3.2.6 Study Sample

#### 3.2.6.1 Controls

Among the 497 eligible controls, 405 (81.5%) answered the questionnaire and among them 311 (76.2%) provided a saliva sample.

#### 3.2.6.2 Cases

Among 257 cases identified as potentially eligible, 192 (74.7%) agreed to participate and were interviewed. Among them, after diagnosis review, 22 did not meet the inclusion criteria. Among the remaining 170 cases, 114 (72.3%) provided a saliva sample. The analyses were restricted to squamous cell carcinomas of the oral cavity, oropharynx, hypopharynx and larynx (145 cases); among them 92 had provided a saliva sample.

### 3.2.7 Data-entry and management

The questionnaire data from the case-control study were entered on an encrypted Excel spreadsheet. Biological data from the genotyping assays were entered on an excel spreadsheet provided by our partners at the Centre for Biological Resources Karubiotec. The international
Standard Classification of Occupations (ISCO) and the French Nomenclature of Activities (NAF) were used by a trained coder to blindly code occupations and branches of the industry, independently of the case-control status of the participants [77, 78]. This information relative to occupational history was then entered on a Microsoft Excel spreadsheet.

All the separate data set were merge together on the unique study identifier that served as a key variable. The final database was verified for incoherences and the data were coded. Variables for statistical analysis were created or derived from existing variables in the dataset. The data-management procedures were performed using SAS 9.4 software (SAS Institute, Carry, NC USA).

### 3.2.7.1 Creation of variables

#### Age

The age was calculated as the difference between the interview date and the date of birth for the controls. For the cases, the difference between diagnosis date and date of birth was used.

#### Smoking quantity

A smoker was defined as someone who smoked at least 100 cigarettes in their lifetime. Smoking quantity assessed as the average number of cigarettes per day over the lifetime. For smokers who responded in number of cigarettes per week, the number of daily cigarettes were calculated by dividing the weekly amount by 7. Questionnaire responses were used as is for smokers who responded in cigarettes per day.

$$ \frac{\sum_{i}^{n} Q_{i} * D_{i}}{\sum_{i}^{n} D_{i}} $$

**i:** Period of identical smoking habits

**n:** The maximum number of distinct periods of identical smoking habits noted for a participant

**Qi:** The number of cigarettes smoked during a given period

**Di:** Length of time in years of a given period in participant's lifetime
The smoking quantity was then categorised into 3 groups (1 to 10, 11 to 20 and >20 cigarettes/day).

## Smoking duration

Smoking duration was calculated by calculating the difference between the age at last cigarette and the age at which the participant began smoking. The total duration of smoking cessation was subtracted from the lifetime smoking duration. For participants who never stopped smoking, age at last cigarette was the same as the age at the moment of the interview/diagnosis. For participants who quit smoking prior to interview (at least 2 years before): age at end was noted as the response to the question “at what age did you stop smoking”

$$ (Age_{end} - Age_{start}) - Y_{stop} $$

Age$_{start}$: Age when first started to smoke

Age$_{end}$: Age at last cigarette

Y$_{stop}$: Total duration of cigarette cessation during participant's lifetime

Smoking duration was then expressed in years and was divided into 4 categories (1 to 20, 21 to 30, 31 to 40, > 40 years).

Cigarette smoking was also expressed in pack-years by calculating the product of the average daily cigarettes and the smoking duration divided by 20. Smoking in pack-years was then categorised into 3 groups (< 10, 11-20 and > 20 pack-years).

There were very few persons having smoked pipes of cigars/cigarillos and thus, we accounted for this behaviour as a binary variable for ever smoking of pipes or cigars.

## Ever daily alcohol drinking

For each type of beverage, ever daily alcohol drinking was defined as at least one glass per day during at least one year.

## Alcohol quantity
The average number of glasses per day was calculated over the lifetime, for each type of beverage. The individual average daily amount for each alcoholic beverage was summed to give the average number of glasses of alcohol daily.

$$ \frac{\sum_{i}^{n} Q_{i} * D_{i}}{\sum_{i}^{n} D_{i}} $$

Where i: Period of identical drinking habits

n: The maximum number of distinct periods of identical drinking habits noted for a participant

Q: The number of drink daily during a given period

D: Length of time in years of a given period in participant's lifetime

The average number of glasses per day was then categorised into 3 groups (<1 glass/day, 1 to 5 glasses/day and >5 glasses per day). The same calculation was used to produce the variables for quantity of tea, coffee and juice/soda

## Body mass index (BMI)

BMI was calculated at different time points (at interview, 2 years before the interview and at age 30). BMI was computed as weight (kg) divided by height squared (m²). In relation to BMI, the study population was divided into four categories according to the World Health Organization (WHO) international classification [79]: underweight subjects (BMI < 18.5 kg/m²), subjects with normal weight (18.5 kg/m² ≥ BMI < 24.9 kg/m²), overweight subjects (25.0 kg/m² ≥ BMI < 29.9 kg/m²), and obese subjects (BMI ≥ 30 kg/m²).
### 3.2.8 Statistical analysis

#### 3.2.8.1 Univariate analysis

##### 3.2.8.1.1 HPV prevalence

The details for the prevalence calculations of oral HPV in the French West Indies are detailed below. Consider the contingency table below as a reference for the notations used in formulas shown in this section.

<table><thead><tr><th>HPV Status</th><th>HNSCC</th><th>Control</th><th>Total</th></tr></thead><tbody><tr><td>HPV+</td><td>a</td><td>b</td><td>E<sub>1</sub></td></tr><tr><td>HPV-</td><td>c</td><td>d</td><td>E<sub>0</sub></td></tr><tr><td>Total</td><td>H<sub>1</sub></td><td>H<sub>0</sub></td><td>E<sub>t</sub></td></tr></tbody></table>

**HPV+/-:** Oral HPV infection regardless of the type

a: Head and neck cancer cases tested positive for oral HPV

b: Control tested positive for oral HPV

c: Head and neck cancer cases tested negative for oral HPV

d: Control tested negative for oral HPV

E: Total number of persons in the exposure group

H: Total number of persons in one of the outcome groups.

The prevalence of oral HPV infections was estimated separately among the HNC cases and the controls. The prevalence calculation was performed by determining the absolute number of HPV-positive cases/controls and then dividing by the total number of cases/controls included in this study and 95% CI were calculated.

$$P_{Hpv+} = a/H_1 (cases)$$

$$P_{Hpv+} = b/H_0 (controls)$$
This was then repeated for the different category of carcinogenic risk (high risk, probable high risk, low risk and other) and the various HPV genotypes. The prevalence was also calculated for different categories of the subject characteristics: age, sex recruitment site, tobacco smoking (ever vs never), alcohol drinking (ever daily drinker, i.e. at least one glass per day during at least one year; never daily drinker).

### 3.2.8.1.2 Exact confidence intervals

In the case of our analyses on HPV prevalence, there were certain calculation which had too few events and did not produce accurate confidence intervals using the Wald method. The Wald methods for calculating confidence intervals for proportions is simple to compute, and is well known and used conventionally in epidemiological studies. Unfortunately, it produces intervals that are too narrow and inaccurate values when samples are small. To overcome this limitation of Wald method, we employed the Clopper-Pearson or “Exact” method, a more complicated computational method. The Clopper-Pearson interval is an exact interval since it is based directly on the binomial distribution rather than any approximation to the binomial distribution. The exact method provides more reliable confidence intervals with small samples which was appropriate for our study on HPV prevalence [80].

### 3.2.8.1.3 Statistical tests

A Chi-squared test was used to test the association between characteristics and HNC. The same test was performed to determine any associations between these same characteristics and oral HPV infection. An exact Fisher test was performed to assess this association for each HPV genotype individually. Tests giving a p-value lower than 5% were considered to be statistically significant.
### 3.2.8.2 Multivariate analysis

#### 3.2.8.2.1 Unconditional logistic regression

The logistic regression is used to model the probability of a binary event such as alive/dead or healthy/sick. In the logistic model, the log-odds (the logarithm of the odds) for the dependent variable (outcome of interest noted as "1" and the opposite condition "0") is a linear combination of one or more independent variables ("predictors"). In the logistic model, the increase of one of the independent variables multiplicatively scales the odds of the given outcome at a constant rate, with each independent variable having its own parameter (denoted as $\beta$). The estimates for the value of parameters of the independent variables are determined using the maximum likelihood estimator by maximising the likelihood function. The exponential of these regression parameters was calculated to determine the odds-ratios (OR) and 95% CI in our case-control study.

$$Logit(p) = \ln(\frac{p}{1-p}) = \alpha + \sum_{i} (\beta_{i}X_{i})$$

Where $p$: probability of begin diagnosed with head and neck cancer (outcome variable)

$\alpha$: intercept

$\beta_i$: regression coefficient showing the association between each explanatory variable and the outcome variable

$x_i$: explanatory variable

#### 3.2.8.2.2 Selection of adjustment variables

Firstly, the variables that were used to frequency match the controls to the cases (age, sex and region) were systematically added to all the multivariate models that we constructed. Given the strong evidence on tobacco smoking and alcohol drinking as risk factors of head and neck
cancer in the literature we adjusted for them systematically in all multivariate model where we attempted to look at the link between head and neck cancer and other known or suspected risk factors. We also considered variables which followed the strict definition of a confounding factor. That is to say, a third variable which is associated simultaneously to the outcome and the exposure variable without being the consequence of that exposure.

Tobacco smoking was considered under several forms for the adjustment, ever smoking, smoking status, smoking quantity, smoking duration, the combination of quantity and duration and pack-years. Alcohol drinking was considered as either daily drinking or quantity of alcohol per day. Given the small sample size of the study, we were unable to fit our regression models with many variables, thus we tested several models for adjustment to determine the one that was the most parsimonious. We used the Akaike information criterion (AIC) to assist us the selection of the model that best fit our data without losing too much precision. The AIC is a criterion that is based on the balance between goodness-of-fit and simplicity. The AIC assess the quality of adjustment of the model whilst penalising for the number of parameters computed in the model.

Akaike information criterion is calculated as follows:

$$AIC = 2k - 2 \ln(L)$$

Where k: the number of parameters to be estimated in the model

L: the maximum of likelihood function for that model.

### 3.2.8.3 Mesures of impact

The measures of impact are used to assess the pertinence of a risk factor from a public health point of view. Contrarily to the measures of association, the measures of impact take into consideration not only the strength of the association but also the frequency of the exposure to the risk factor and thus, the importance of that factor for prevention. The measures of
impact are known under a variety of names such as attributable risk, attributable fraction and etiological fraction. The attributable fraction indicates the proportion of cases would be prevented if it were possible to eliminate one or more exposures from a particular target population [81]. This proportion could be calculated in the exposure group exclusively or for the population. For the purpose of this doctoral thesis, the emphasis will be placed on population attributable fractions (PAF). To compute the PAF, the relative risks need to be estimated for the risk factor(s) of interest as well as those for additional risk factors which may be potential confounders for the disease outcome in a multivariate model. The formula used to calculate the PAF in case-control studies is detailed below:

$$ \frac{PE_{case}(OR - 1)}{OR} $$

**PEcase:** proportion of exposed subjects among the cases

To calculate the PAFs for the analyses in our study, the aflogit procedure was used in the STATA software package [82].

### 3.2.8.4 Mesures of interaction

An effect modifier is characterised by a change in the effect of one risk factor on an outcome according to whether it is present or not. If the effect of the studied variable is the same within strata of the suspected effect modifier, then there is no interaction. When the effect of one risk factor is different within strata defined by the other, then there is an interaction. Assessing interactions between variables is useful and may provide insight into the mechanisms for the outcome. In epidemiology, interactions are most often measured on either an additive scale (biological interaction) or a multiplicative scale (statistical interaction) [83].
<table><caption>**Table 4:** Explanation of the concept of interaction - Notations</caption><thead><tr><th rowspan="2">Factor B</th><th colspan="2">Factor A</th></tr><tr><th>Unexposed</th><th>Exposed</th></tr></thead><tbody><tr><td>Unexposed</td><td>1 (ref)</td><td>OR<sub>01</sub></td></tr><tr><td>Exposed</td><td>OR<sub>10</sub></td><td>OR<sub>11</sub></td></tr></tbody></table>

### 3.2.8.4.1 Additive scale

Additive interactions are assessed by measuring the extent to which the effect of two factors together exceeds the sum of each effect considered individually. The relative excess risk due to interaction (RERI) is a common measure used for interactions on an additive scale and it is calculated in the following manner.

$$RERI = OR_{11} - OR_{10} - OR_{01} + 1$$

If RERI = 0, there is no additive interaction

If RERI > 0, the interaction is said to be positive or “super-additive”

If RERI < 0, the interaction is said to be negative or “sub-additive”

### 3.2.8.4.2 Multiplicative scale

Multiplicative interactions are assessed by measuring the extent to which the effect of two factors together exceeds the product of each effect considered individually. The Ψ (Phi) is a common measure used for interactions on a multiplicative scale and it is calculated in the following manner:

$$\psi = \frac{OR_{11}}{OR_{10} \times OR_{01}}$$

If Ψ = 1, there is no multiplicative interaction

If Ψ > 1, the interaction is said to be positive or “super-multiplicative”
If $\Psi < 1$, the interaction is said to be negative or "sub-multiplicative"

The $\Psi$ as well as its confidence interval is also equivalent to the regression coefficient of the cross-product term of two variables in a logistic regression model.

### 3.2.8.5 Management of missing data and multiple imputations

HPV status was missing for 151 (27%) subjects (53 cases and 98 controls) that refused to provide a saliva sample. In addition, missing data were observed for smoking status (one case) smoking quantity (19 cases, 3 controls), smoking duration (6 cases, 1 control) and alcohol quantity (4 controls).

Missing data are a common problem in epidemiological research. Multiple imputation by chained equations (MICE) (also known as "fully conditional specification") has emerged in the statistical literature as a popular method to deal with missing data. MICE operates under the assumption that given the variables to be imputed are Missing At Random (MAR), meaning that the probability that a value is missing depends only on observed values and not on unobserved values [84]. In the MICE procedure a series of regression models are run whereby each variable with missing data is modelled conditional upon the other variables in the data. This is conditionally according to the distribution of the variable to be imputed rather than assuming a joint normal distribution for all the variables. The MICE method consists of regressing on the variable with missing data on the other variables in an imputation model containing other variables in the data set without missing data. The missing data are then replaced by predictions from the regression models and these variables are then used an explanatory variable the values for other variables in a subsequent regressions [84]. For the analyses in this doctoral thesis, we used MICE to deal with missing data. The imputation model contained all the basic characteristics of the study subjects (age, sex recruitment site and education level), variables related to alcohol and smoking (ever daily alcohol drinking, quantity of alcohol, smoking status, smoking duration, and smoking
quantity), HPV status (low-risk, probable high-risk, high-risk, and other HPV types) and the
case-control status, Missing values for continuous variables (smoking quantity and duration,
quantity of alcohol) were imputed by fitting a linear regression model. Categorical variables
were imputed by fitting a logistic regression model with maximum likelihood estimate based
on augmented data. The logistic regression with augmented data is a method employed to
deal with issues associated with perfect prediction during the computation of the maximum
likelihood estimate [16]. All variables in the imputation model which had missing values
were imputed for our analyses. We generated 20 datasets. The MICE method was performed
using the PROC MI procedure from SAS 9.4 software (SAS Institute, Carry, NC USA). The
MIANALYZE procedure on SAS was invoked to combine the estimates and their
variances/covariances into one data set using the pooling algorithm suggested by Rubin et al.
to perform statistical inferences [85].
The results of this PhD thesis are presented in the form of five research manuscripts in the following order:

**Barometre Santé DOM:**

1. Social Distribution of Tobacco Smoking, Alcohol Drinking and Obesity in the French West Indies

**Case-control study:**

2. Prevalence of oral HPV infection among healthy individuals and head and neck cancer cases in the French West Indies

3. Joint effect of tobacco, alcohol and oral hpv infection on head and neck cancer risk in the French West Indies

4. Population attributable fractions of head and neck cancer risk factors in the French West Indies

5. Association between sexual behaviour and head and neck cancer in the French West Indies

Other analyses were performed on certain risk factors but were not sufficiently advanced to produce a manuscript draft. There results are presented in a chapter called “Supplementary results”. The risk factors in this section are:

- Fruits and vegetables

- Non-alcoholic beverages

- Occupational risk factors
## 4.1 Social Distribution of Tobacco Smoking, Alcohol Drinking and Obesity in the French West Indies

This work has been published BMC Public Health in October 2019
RESEARCH ARTICLE

Open Access

<figure><img src="image_8.png" /></figure>

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# Social distribution of tobacco smoking, alcohol drinking and obesity in the French West Indies

Aviane Auguste<fnref n="1" />, Julien Dugas<fnref n="1" />, Gwenn Menvielle², Christine Barul<fnref n="1" />, Jean-Baptiste Richard³ and Danièle Luce<fnref n="1" />*

## Abstract

**Background:** Tobacco smoking, alcohol and obesity are important risk factors for a number of non-communicable diseases. The prevalence of these risk factors differ by socioeconomic group in most populations, but this socially stratified distribution may depend on the social and cultural context. Little information on this topic is currently available in the Caribbean. The aim of this study was to describe the distribution of tobacco smoking, alcohol drinking and obesity by several socioeconomic determinants in the French West Indies (FWI).

**Methods:** We used data from a cross-sectional health survey conducted in Guadeloupe and Martinique in 2014 in a representative sample of the population aged 15–75 years (n = 4054). All analyses were stratified by gender, and encompassed sample weights, calculated to account for the sampling design and correct for non-response. For each risk factor, we calculated weighted prevalence by income, educational level, occupational class and having hot water at home. Poisson regression models were used to estimate age-adjusted prevalence ratios (PR) and 95% confidence intervals (CI).

**Results:** Current smoking and harmful chronic alcohol use were more common in men than in women (PR = 1.80, 95% CI = 1.55–2.09; PR = 4.53, 95% CI = 3.38–6.09 respectively). On the other hand, the prevalence of obesity was higher in women than in men (PR = 0.67, 95% CI = 0.57–0.79). Higher education, higher occupational class and higher income were associated with lower prevalence of harmful alcohol drinking in men (PR = 0.43, 95% CI = 0.25–0.72; PR = 0.73, 95% CI = 0.53–1.01; PR = 0.72, 95% CI = 0.51–1.03 respectively), but not in women. For tobacco smoking, no variation by socioeconomic status was observed in men whereas the prevalence of current smoking was higher among women with higher occupational class (PR = 1.47, 95% CI = 1.13–1.91) and higher income (PR = 1.50, 95% CI = 1.11–2.03). In women, a lower prevalence of obesity was associated with a higher income (PR = 0.43, 95% CI = 0.33–0.56), a higher occupational class (PR = 0.63, 95% CI = 0.50–0.80), a higher educational level (PR = 0.36, 95% CI = 0.26–0.50) and having hot water at home (PR = 0.65, 95% CI = 0.54–0.80).

**Conclusion:** Women of high socio-economic status were significantly more likely to be smokers, whereas alcohol drinking in men and obesity in women were inversely associated with socioeconomic status.

**Keywords:** Social disparities, Tobacco smoking, Alcohol drinking, Obesity, Non-communicable diseases, Caribbean, France

<footnote>* Correspondence: daniele.luce@inserm.fr</footnote>

<footnote n="1">¹Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) -UMR_S 1085, F-97100 Pointe-à-Pitre, France
Full list of author information is available at the end of the article</footnote>
## Background

The French West Indies (FWI) is a part of the Caribbean region which is made up of the two overseas French regions, Martinique and Guadeloupe. The French West Indies have a particular situation in the Caribbean. As French territories, Martinique and Guadeloupe are classified as high-income countries, whereas most of other Caribbean states are low or middle-income countries. The FWI population benefits from the same health insurance and financial redistribution systems as the mainland French population. While the French West Indies appear to be a privileged region within the Caribbean, the comparison with the mainland is much less favourable. Although the gross domestic product per capita is one of the highest in the Caribbean, it is only about 65% of the French national average. When compared to the national average, the population of the FWI is characterized by a lower median income, a lower educational level and a higher rate of unemployment. On the other hand, the FWI are close to their Caribbean neighbours with regards to the cultural, historical and climatic context. This unique situation reflects in health conditions, with for most of them an intermediate position between mainland France and other countries in the Caribbean. Cancer and cardiovascular diseases were in 2016 the leading causes of death in the FWI, accounting each for about 25% of all deaths [1]. Cancer incidence rates are overall lower than in mainland France, with the exception of prostate, stomach and cervical cancer, but higher than in other Caribbean countries for most cancer sites. Mortality rates from cardiovascular diseases, although higher than in mainland France, are among the lowest in the Caribbean [1-5]. The prevalence of diabetes is also high in the FWI [6]. Tobacco smoking, alcohol drinking and obesity are important risk factors for a number of non-communicable diseases (NCD), including cancer, diabetes and cardiovascular disease. These risk factors were described in previous studies to be inequitably distributed across the different socio-economic strata. Worldwide, the prevalence of these risk factors tends to be higher in persons of lower socioeconomic status (SES) than in the more affluent groups [7, 8]. This trend however varies with country-level development and the indicators used [7-10]; in mainland France, and other developed countries, lower SES is usually associated to a greater prevalence of these risk factors; whereas, in low and middle-income countries, the reverse association is usually observed [7, 11-13]. However, data in regards to social disparities and NCD risk factors are very scarce in the Caribbean. A study in Barbados addressed the social distribution of NCD risk factors [14]. A systematic review reported data on social determinants of obesity and alcohol consumption in the Caribbean; however, they provide unclear conclusions on the social disparities in this population, due to few data [15]. Knowing the social distribution of risk factors is

crucial for the designing of prevention programs and policy in these regions [15]. The specific features of the FWI further warrant a sound understanding of the social distribution of the known NCD risk factors to take appropriate measures for prevention.

In this study, we performed a secondary data analysis from a national survey in order to describe the social distribution of tobacco smoking, alcohol drinking and obesity in the French West Indies.

## Methods

### Study population, data collection

The data for this study were drawn from a national cross-sectional health survey conducted in the FWI in 2014 ("Baromètre Santé DOM", Health Barometer) [16]. The survey was based on a random two stage sampling method: telephone numbers (landlines and cell phones) were randomly generated, then one person was randomly selected among eligible household members or among cell phone users, using the Kish method [17]. Persons aged between 15 and 75 years of age living in Martinique or Guadeloupe who spoke French or Creole were eligible for inclusion. Field investigators conducted the interview over the phone.

Participation was anonymous and voluntary. Anonymity and respect of confidentiality were guaranteed using a procedure erasing the phone number. All included subjects gave informed consent before the telephone interview. Partial consent was obtained for participants under 18. As the participants were contacted exclusively over the phone, the consents were verbal. The overall procedure was approved by the French regulatory authority, the Commission Nationale de l'Informatique et des Libertés (CNIL).

Overall, 8057 numbers were dialled (3687 landlines and 4407 cell phones). Among them, 35% could not be reached, 11% refused to participate and 3% abandoned the survey before the end of the interview. In the end, 4054 subjects were included in the final sample for Martinique and Guadeloupe. The overall participation rate for the French West Indies was 51% (56% for landlines, 46% for cell phones).

Data were weighted in two steps. To account for the sampling design, sample weights were computed according to the probability of selection of the telephone number, the number of eligible individuals for each telephone number, the number of landline and cell phones of the individual. To correct for non-response, a post-stratification was then performed to match the distribution of the population, according to sex, age, education level and household structure, using data from the 2011 census in Martinique and Guadeloupe.

### Variables

All risk factors analysed in our current study were dichotomised. Current smokers were persons who smoked any
tobacco product. Lifetime tobacco smokers were those who had smoked tobacco in their lifetime regardless of the duration or frequency. Daily alcohol drinkers were persons who drank at least one glass of alcohol per day. Harmful chronic alcohol use was defined as drinking more than 21 drinks a week for a man and 14 for a woman or drinking six drinks or more on a single occasion weekly [18]. Self-reported height and weight were collected during the phone call and body mass index (BMI) was calculated (weight in kg/height in m²). An obese person was regarded as someone with a BMI of at least 30 kg/m². We used four variables related to socioeconomic status: education, occupational category, income and having hot water at home. Education was defined as the highest educational attainment achieved by an individual participant and categorised into four groups: without diploma or primary education (up to approximately 6 years of schooling), less than high school diploma (up to approximately 9 years of schooling), high school diploma (up to approximately 12 years), and tertiary education (associate's degree or higher) [19]. Occupation was defined as the current occupation for active workers and as the last occupation for retired or unemployed persons, and was classified into three groups based on the French classification of occupations and socio-professional categories [20, 21]: qualified workers (self-employed and entrepreneurs, professionals and managers), unqualified workers (farmers, clerical, sales and service workers, manual workers) and inactive, who were persons who never worked. Individual income was split into three groups according to the tertiles of the overall distribution of income in our sample. Having hot water at home described someone living in a household where a water heating system was available to heat the running water in the house. Hot water at home is strongly linked to the household income in the FWI and can therefore be viewed as a surrogate for self-reported income, which may be more subject to misclassification or misreporting [22].

## Statistical analysis

The prevalence for each risk factor was calculated by gender, age and according to the four socio-economic indicators. Age-adjusted prevalence ratios (PR) and their 95% confidence intervals (CI) estimating the associations of the different socio-economic indicators with the risk factors were calculated using a Poisson-regression model. Chi-squared tests were performed to assess the statistical trend between the socio-demographics and gender. All analyses encompassed sample weights.

## Results

### Characteristics and risk factor prevalence

In total 4054 persons were included for the purpose of our analysis. Table 1 shows the distribution of

socio-demographic characteristics of participants in our sample. The participants were equally distributed between Martinique and Guadeloupe and there were slightly more women than men (ratio of women to men 1.2). Men were more frequently under 25 years of age and had higher income when compared to women. On the other hand, women had more frequently tertiary education and hot water at home when compared to men. Very few data were missing for most variables (≤1%) with the exception of individual income and body mass index (14 and 6% respectively). Table 2 shows the prevalence of risk factors. Overall, ever tobacco smoking was the most prevalent risk factor among participants. Men were significantly more likely to be smokers and alcohol drinkers. The prevalence of ever and current smokers was two-fold grater in men than in women (PR = 1.98, 95% CI = 1.75–2.24 and PR = 1.80, 95% CI = 1.55–2.09 respectively). Similarly, the prevalence of daily alcohol drinking and harmful chronic drinking was 4 times greater in men than in women (PR = 4.15, 95% CI = 3.11–5.55 and PR = 4.53, 95% CI = 3.38–6.09 respectively). Inversely men were significantly less likely to be obese than women (PR = 0.67, 95% CI = 0.57–0.79).

Table 3 shows the prevalence of risk factors by gender and age. In both men and women, for all tobacco and alcohol-related variables, the highest prevalence was consistently observed in the 25 to 34 age group when compared to the other age groups. We observed a regular decrease of the prevalence of current tobacco smoking from 24 to 75 years of age, A similar trend, although less apparent, was found for ever smoking. On the other hand, in both men and women, daily alcohol drinking increased with age whereas harmful chronic alcohol drinking decreased with age. In terms of obesity, women between 55 and 64 years were the most frequently obese (28.9%), followed by the 25 to 34 age group with 23.8%. The obesity prevalence in men was quite homogenous across age groups with the exception of men under 24 years for whom the prevalence was notably lower (4.9%).

### Social distribution of risk factors

Tables 4 and 5 show in women and men respectively, the prevalence of risk factors by socio-economic category, as well as age-adjusted prevalence ratios, and 95% CI of the Poisson regression model, estimating the associations between the socio-economic indicators and those risk factors. In women, ever smoking prevalence was seen to increase with higher socio-economic status. The prevalence was significantly greater in women who had tertiary education (PR = 1.45, 95% CI = 1.07–1.96), and who occupied qualified jobs (PR = 1.60, 95% CI = 1.30–1.98) and who had the highest incomes (PR = 1.63, 95% CI = 1.28–2.08). Similarly, compared to persons in lower SES class, current smoking prevalence was significantly greater in women of in qualified jobs, and those
<table><caption>**Table 1** Distribution of socio-demographic characteristics of participants by gender</caption><thead><tr><th rowspan="2">Characteristic</th><th rowspan="2">Category</th><th colspan="2">Men</th><th colspan="2">Women</th><th colspan="2">Overall</th><th rowspan="2">p<sup>†</sup></th></tr><tr><th>n = 1849</th><th>%<sup>a</sup></th><th>n = 2205</th><th>%<sup>a</sup></th><th>n = 4054</th><th>%<sup>a</sup></th></tr></thead><tbody><tr><td rowspan="6">Age (years)</td><td>15-24</td><td>351</td><td>(19.0)</td><td>348</td><td>(15.8)</td><td>699</td><td>(17.2)</td><td rowspan="6">0.0721</td></tr><tr><td>25-34</td><td>232</td><td>(12.5)</td><td>311</td><td>(14.1)</td><td>543</td><td>(13.4)</td></tr><tr><td>35-44</td><td>348</td><td>(18.8)</td><td>459</td><td>(20.8)</td><td>807</td><td>(19.9)</td></tr><tr><td>45-54</td><td>396</td><td>(21.4)</td><td>466</td><td>(21.1)</td><td>862</td><td>(21.3)</td></tr><tr><td>55-64</td><td>303</td><td>(16.4)</td><td>359</td><td>(16.3)</td><td>662</td><td>(16.3)</td></tr><tr><td>65-75</td><td>219</td><td>(11.8)</td><td>263</td><td>(11.9)</td><td>481</td><td>(11.9)</td></tr><tr><td rowspan="2">Recrutement site</td><td>Martinique</td><td>922</td><td>(49.9)</td><td>1104</td><td>(50.1)</td><td>2026</td><td>(50.0)</td><td rowspan="2">0.9135</td></tr><tr><td>Guadeloupe</td><td>927</td><td>(50.1)</td><td>1101</td><td>(49.9)</td><td>2028</td><td>(50.0)</td></tr><tr><td rowspan="5">Education level</td><td>Up to primary education</td><td>462</td><td>(25.2)</td><td>511</td><td>(23.3)</td><td>973</td><td>(24.2)</td><td rowspan="5">&lt; 0.0001</td></tr><tr><td>Less than high school diploma</td><td>811</td><td>(44.3)</td><td>818</td><td>(37.4)</td><td>1629</td><td>(40.5)</td></tr><tr><td>High school diploma</td><td>279</td><td>(15.2)</td><td>421</td><td>(19.2)</td><td>700</td><td>(17.4)</td></tr><tr><td>Tertiary education</td><td>280</td><td>(15.3)</td><td>439</td><td>(20.1)</td><td>719</td><td>(17.9)</td></tr><tr><td>Missing</td><td>17</td><td></td><td>16</td><td></td><td>33</td><td></td></tr><tr><td rowspan="4">Occupational Class</td><td>Inactive</td><td>245</td><td>(13.2)</td><td>339</td><td>(15.4)</td><td>584</td><td>(14.4)</td><td rowspan="4">0.0567</td></tr><tr><td>Non-qualified</td><td>1032</td><td>(55.9)</td><td>1241</td><td>(56.4)</td><td>2273</td><td>(56.1)</td></tr><tr><td>Qualified</td><td>571</td><td>(30.9)</td><td>621</td><td>(28.2)</td><td>1191</td><td>(29.4)</td></tr><tr><td>Missing</td><td>1</td><td></td><td>4</td><td></td><td>5</td><td></td></tr><tr><td rowspan="4">Individual income</td><td>Low-income</td><td>471</td><td>(30.3)</td><td>724</td><td>(37.7)</td><td>1195</td><td>(34.4)</td><td rowspan="4">&lt; 0.0001</td></tr><tr><td>Middle-income</td><td>523</td><td>(33.7)</td><td>630</td><td>(32.8)</td><td>1153</td><td>(33.2)</td></tr><tr><td>High-income</td><td>561</td><td>(36.1)</td><td>566</td><td>(29.5)</td><td>1127</td><td>(32.4)</td></tr><tr><td>Missing</td><td>294</td><td></td><td>285</td><td></td><td>579</td><td></td></tr><tr><td rowspan="3">Hot water at home</td><td>Yes</td><td>1283</td><td>(69.5)</td><td>1609</td><td>(73.0)</td><td>2892</td><td>(71.4)</td><td rowspan="3">0.0153</td></tr><tr><td>No</td><td>563</td><td>(30.5)</td><td>596</td><td>(27.0)</td><td>1159</td><td>(28.6)</td></tr><tr><td>Missing</td><td>3</td><td></td><td>0</td><td></td><td>3</td><td></td></tr></tbody></table>

Baromètre Santé DOM survey, 2014

had higher income. In contrast, daily alcohol and harmful chronic alcohol drinking were not associated with SES in women. However, though the prevalence difference for occupational class was not significant, women with qualified jobs, and hot water at home tended to engage less in harmful chronic drinking. Having hot water at home was not significantly associated with tobacco and daily alcohol consumption. In men, no distinct trend or significant association was found in regards to tobacco and socio-economic status. However, in men, a harmful chronic drinking and daily alcohol drinking were inversely and significantly associated with

educational level. With the exception of daily alcohol in women, we found that occupationally inactive persons had significantly lower alcohol drinking prevalence for both genders when compared to unqualified workers. Obesity prevalence was inversely associated with socio-economic status, in particular in women, where we observed significant decreases of at least 35% in obesity prevalence in those of the highest stratum for each socio-economic indicator (education PR = 0.36, 95% CI = 0.26-0.50; occupational class PR = 0.63, 95% CI = 0.50-0.80; income PR = 0.43, 95% CI = 0.33-0.56; hot water at home PR = 0.65, 95% CI = 0.54-0.80).

<footnote><sup>a</sup>Column percentage calculated by dividing the total number of men, women or overall sample</footnote>

<footnote>†: p-value of Chi-squared test, assessing the association between participant's socio-demographic characteristics and gender</footnote>
<table><caption>**Table 2** Prevalence of risk factors and prevalence ratios comparing men to women</caption><thead><tr><th rowspan="2">Risk factor</th><th colspan="2">Men</th><th colspan="2">Women</th></tr><tr><th colspan="2">n = 1849</th><th colspan="2">n = 2205</th></tr></thead><tbody><tr><td><strong>Ever tobacco smoking</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>Prevalence (%)</td><td>682 (38)</td><td></td><td>421 (19)</td><td></td></tr><tr><td>Adjusted PR (95% CI)</td><td>1.98 (1.75-2.24)</td><td></td><td>1 ref</td><td></td></tr><tr><td>Missing (n)</td><td>36</td><td></td><td>8</td><td></td></tr><tr><td><strong>Current tobacco smoking</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>Prevalence (%)</td><td>422 (23)</td><td></td><td>286 (13)</td><td></td></tr><tr><td>Adjusted PR (95% CI)</td><td>1.80 (1.55-2.09)</td><td></td><td>1 ref</td><td></td></tr><tr><td>Missing (n)</td><td>43</td><td></td><td>0</td><td></td></tr><tr><td><strong>Daily alcohol drinking</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>Prevalence (%)</td><td>201 (11)</td><td></td><td>59 (3)</td><td></td></tr><tr><td>Adjusted PR (95% CI)</td><td>4.15 (3.11-5.55)</td><td></td><td>1 ref</td><td></td></tr><tr><td>Missing (n)</td><td>1</td><td></td><td>0</td><td></td></tr><tr><td><strong>Harmful chronic alcohol use</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>Prevalence (%)</td><td>213 (12)</td><td></td><td>57 (3)</td><td></td></tr><tr><td>Adjusted PR (95% CI)</td><td>4.53 (3.38-6.09)</td><td></td><td>1 ref</td><td></td></tr><tr><td>Missing (n)</td><td>1</td><td></td><td>0</td><td></td></tr><tr><td><strong>Obesity</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>Prevalence (%)</td><td>209 (12)</td><td></td><td>443 (22)</td><td></td></tr><tr><td>Adjusted PR (95% CI)</td><td>0.67 (0.57-0.79)</td><td></td><td>1 ref</td><td></td></tr><tr><td>Missing (n)</td><td>100</td><td></td><td>146</td><td></td></tr></tbody></table>

PR Prevalence ratio, 95%CI 95% confidence interval

Baromètre Santé DOM survey, 2014

## Discussion

Social disparities in NCD risk factors distribution were reported in previous studies in many countries [7, 14, 15, 23] but data on this topic are scarce in the Caribbean. We attempted to shed some light on disparities in chronic diseases by describing the social distribution of these risk factors in the French West Indies. We were able to highlight gender-specific social disparities in regards to these risk factors, in this population.

While tobacco smoking was predominantly found in women of high SES, in men, the prevalence did not differ in regards to SES. The social pattern for tobacco smoking did not correspond to what has been described in developed countries, and in particular in mainland France, where persons of lower SES were more frequently smokers [24–26]. Furthermore, the social distribution of tobacco smoking in Barbados and Cuba was discordant with what we found. In men, a negative association between smoking and SES was found in both countries. In women, the social distribution for tobacco smoking in Barbados did not have any distinct pattern and in Cuba it went in the opposite direction to ours [14, 27]. Previous reports have shown that economic development and urbanicity affect socio-economic behaviour and would explain

the variation of our results from other studies [7, 8]. Data from the World Health Surveys in 53 countries showed that in the most urban countries, which were mainly middle-income countries in this study, smoking in women was concentrated in the higher education groups, whereas in men smoking was inversely associated with education, regardless of urbanicity [7]. The FWI have a high level of urbanicity, with more than 80% of the population living in urban areas, and our results are consistent with these findings for women, but not for men. The global tobacco epidemic, as described elsewhere, explains well these differences [26]. It is a process which begins first in the most affluent men in society; then, it spreads through the other socioeconomic classes. The same habit then initiates in women of high SES; before finally transitioning to the lower socioeconomic class, since those in higher SES tend to become conscious of their unhealthy lifestyle and possess greater means to alter their behaviour or environment. Our findings suggest that the FWI have not reached the last stage of tobacco epidemic, and that tobacco consumption could increase in the lower SES categories in the future.

The association between alcohol use and SES is complex, vary across genders, country development level and cultures, and depends on the measures used for alcohol drinking [12, 28]. Alcohol drinking measures differ in the previous studies, which made comparisons difficult. We found that in men the prevalence of daily alcohol drinking and harmful alcohol use was lower in the highest socioeconomic strata, a pattern consistent with the inverse association with SES reported in Barbados for heavy episodic alcohol consumption [14] and in a multinational study (including France) for heavy drinking [12]. In women, no clear trend was found, similarly to Barbados [14] but inconsistent with mainland France where the prevalence of heavy drinking was higher in the highest educational level [12].

In terms of obesity, there was an inverse association with the socio-economic status for both genders with a more marked socioeconomic gradient in women. This gradient was the most apparent for income, where the prevalence was twice as high in women of low income when compared to those of high income. A French study [29] and a study in Guadeloupe [6] reported a social pattern for obesity in men and women concordant to our sample. In contrast, the study in Barbados reported no socioeconomic gradient for obesity [14]. Previous studies showed that in developed countries, women of high socio-economic status are more sensitive to body image because small body size is viewed as attractive [30, 31]. Although in our study height and weight were self-reported, our findings were globally similar to those of studies that used anthropometric measurements [6, 29].

Our findings are also consistent with the local context. A previous study conducted in the FWI investigating
<table><caption>**Table 3** Risk factor prevalence by age group</caption><thead><tr><th rowspan="2">Risk factor</th><th colspan="2">15-24 yrs</th><th colspan="2">25-34 yrs</th><th colspan="2">35-44 yrs</th><th colspan="2">45-54 yrs</th><th colspan="2">55-64 yrs</th><th colspan="2">65-75 yrs</th></tr><tr><th>n = 699</th><th>%</th><th>n = 543</th><th>%</th><th>n = 807</th><th>%</th><th>n = 862</th><th>%</th><th>n = 662</th><th>%</th><th>n = 481</th><th>%</th></tr></thead><tbody><tr><td><strong>Ever tobacco smoking</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Total</td><td>180 (25.8)</td><td>191 (35.2)</td><td>224 (27.7)</td><td>227 (26.4)</td><td>174 (26.2)</td><td>227 (26.4)</td><td>174 (26.2)</td><td>174 (26.2)</td><td>174 (26.2)</td><td>174 (26.2)</td><td>174 (26.2)</td><td>174 (26.2)</td></tr><tr><td>Women</td><td>72 (20.9)</td><td>87 (28.4)</td><td>101 (22.0)</td><td>90 (19.3)</td><td>48 (13.3)</td><td>90 (19.3)</td><td>48 (13.3)</td><td>48 (13.3)</td><td>48 (13.3)</td><td>48 (13.3)</td><td>48 (13.3)</td><td>48 (13.3)</td></tr><tr><td>Men</td><td>108 (32.4)</td><td>104 (46.5)</td><td>123 (35.7)</td><td>137 (35.1)</td><td>126 (41.7)</td><td>137 (35.1)</td><td>126 (41.7)</td><td>126 (41.7)</td><td>126 (41.7)</td><td>126 (41.7)</td><td>126 (41.7)</td><td>126 (41.7)</td></tr><tr><td><strong>Current tobacco smoking</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Total</td><td>167 (24.5)</td><td>155 (29.2)</td><td>153 (19.1)</td><td>133 (15.5)</td><td>68 (10.2)</td><td>133 (15.5)</td><td>68 (10.2)</td><td>68 (10.2)</td><td>68 (10.2)</td><td>68 (10.2)</td><td>68 (10.2)</td><td>68 (10.2)</td></tr><tr><td>Women</td><td>64 (18.6)</td><td>69 (22.6)</td><td>69 (15.0)</td><td>65 (14.0)</td><td>13 (3.6)</td><td>65 (14.0)</td><td>13 (3.6)</td><td>13 (3.6)</td><td>13 (3.6)</td><td>13 (3.6)</td><td>13 (3.6)</td><td>13 (3.6)</td></tr><tr><td>Men</td><td>102 (30.6)</td><td>86 (38.4)</td><td>84 (24.6)</td><td>68 (17.2)</td><td>55 (18.2)</td><td>68 (17.2)</td><td>55 (18.2)</td><td>55 (18.2)</td><td>55 (18.2)</td><td>55 (18.2)</td><td>55 (18.2)</td><td>55 (18.2)</td></tr><tr><td><strong>Daily alcohol drinking</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Total</td><td>17 (2.4)</td><td>41 (7.6)</td><td>41 (5.1)</td><td>43 (5.0)</td><td>63 (9.5)</td><td>43 (5.1)</td><td>63 (9.5)</td><td>63 (9.5)</td><td>63 (9.5)</td><td>63 (9.5)</td><td>63 (9.5)</td><td>63 (9.5)</td></tr><tr><td>Women</td><td>1 (0.2)</td><td>14 (4.4)</td><td>15 (3.3)</td><td>7 (1.4)</td><td>9 (2.6)</td><td>7 (1.4)</td><td>9 (2.6)</td><td>9 (2.6)</td><td>9 (2.6)</td><td>9 (2.6)</td><td>9 (2.6)</td><td>9 (2.6)</td></tr><tr><td>Men</td><td>16 (4.6)</td><td>27 (11.8)</td><td>26 (7.5)</td><td>37 (9.3)</td><td>54 (17.7)</td><td>37 (9.3)</td><td>54 (17.7)</td><td>54 (17.7)</td><td>54 (17.7)</td><td>54 (17.7)</td><td>54 (17.7)</td><td>54 (17.7)</td></tr><tr><td><strong>Harmful chronic alcohol use</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Total</td><td>73 (10.4)</td><td>60 (11.1)</td><td>56 (7.0)</td><td>44 (5.1)</td><td>23 (3.4)</td><td>44 (5.1)</td><td>23 (3.4)</td><td>23 (3.4)</td><td>23 (3.4)</td><td>23 (3.4)</td><td>23 (3.4)</td><td>23 (3.4)</td></tr><tr><td>Women</td><td>15 (4.4)</td><td>14 (4.5)</td><td>13 (2.9)</td><td>10 (2.1)</td><td>1 (0.2)</td><td>10 (2.1)</td><td>1 (0.2)</td><td>1 (0.2)</td><td>1 (0.2)</td><td>1 (0.2)</td><td>1 (0.2)</td><td>1 (0.2)</td></tr><tr><td>Men</td><td>58 (16.4)</td><td>46 (20.0)</td><td>43 (12.3)</td><td>34 (8.6)</td><td>22 (7.3)</td><td>34 (8.6)</td><td>22 (7.3)</td><td>22 (7.3)</td><td>22 (7.3)</td><td>22 (7.3)</td><td>22 (7.3)</td><td>22 (7.3)</td></tr><tr><td><strong>Obesity</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Total</td><td>51 (7.9)</td><td>96 (19.0)</td><td>130 (17.1)</td><td>159 (19.6)</td><td>139 (21.8)</td><td>159 (19.6)</td><td>139 (21.8)</td><td>139 (21.8)</td><td>139 (21.8)</td><td>139 (21.8)</td><td>139 (21.8)</td><td>139 (21.8)</td></tr><tr><td>Women</td><td>35 (11.0)</td><td>70 (23.8)</td><td>83 (19.6)</td><td>103 (23.4)</td><td>101 (28.9)</td><td>103 (23.4)</td><td>101 (28.9)</td><td>101 (28.9)</td><td>101 (28.9)</td><td>101 (28.9)</td><td>101 (28.9)</td><td>101 (28.9)</td></tr><tr><td>Men</td><td>16 (4.9)</td><td>26 (12.3)</td><td>47 (13.9)</td><td>56 (15.1)</td><td>38 (13.3)</td><td>56 (15.1)</td><td>38 (13.3)</td><td>38 (13.3)</td><td>38 (13.3)</td><td>38 (13.3)</td><td>38 (13.3)</td><td>38 (13.3)</td></tr></tbody></table>

Baromètre Santé DOM survey, 2014

<table><caption>**Table 4** Associations between SES and risk factors in women</caption><thead><tr><th rowspan="2">SES indicator</th><th colspan="2">Ever tobacco</th><th colspan="2">Current tobacco</th><th colspan="2">Daily alcohol</th><th colspan="2">Harmful chronic alcohol use</th><th colspan="2">Obesity</th></tr><tr><th>Prev</th><th>PR (95% CI)</th><th>Prev</th><th>PR (95% CI)</th><th>Prev</th><th>PR (95% CI)</th><th>Prev</th><th>PR (95% CI)</th><th>Prev</th><th>PR (95% CI)</th></tr></thead><tbody><tr><td><strong>Education level</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Up to primary education</td><td>14.8</td><td>1 (ref)</td><td>10.4</td><td>1 (ref)</td><td>2.9</td><td>1 (ref)</td><td>2.7</td><td>1 (ref)</td><td>31.3</td><td>1 (ref)</td></tr><tr><td>Less than high school diploma</td><td>16.2</td><td>1.00 (0.75-1.33)</td><td>11.1</td><td>0.89 (0.63-1.25)</td><td>3.2</td><td>1.29 (0.67-2.48)</td><td>1.9</td><td>0.55 (0.26-1.16)</td><td>24.5</td><td>0.79 (0.63-0.98)</td></tr><tr><td>High school diploma</td><td>23.2</td><td>1.30 (0.96-1.78)</td><td>16.8</td><td>1.13 (0.79-1.63)</td><td>1.9</td><td>1.71 (0.68-4.28)</td><td>4.0</td><td>0.97 (0.46-2.02)</td><td>14.9</td><td>0.53 (0.39-0.73)</td></tr><tr><td>Tertiary education</td><td>26.2</td><td>1.45 (1.07-1.96)</td><td>16.5</td><td>1.09 (0.76-1.58)</td><td>2.2</td><td>0.72 (0.30-1.70)</td><td>2.3</td><td>0.50 (0.21-1.19)</td><td>12.1</td><td>0.36 (0.26-0.50)</td></tr><tr><td><strong>Occupational Class</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Inactive</td><td>18.9</td><td>1.04 (0.73-1.49)</td><td>16.4</td><td>1.02 (0.68-1.53)</td><td>0.7</td><td>1.19 (0.35-4.04)</td><td>1.6</td><td>0.21 (0.08-0.55)</td><td>17.2</td><td>1.27 (0.88-1.83)</td></tr><tr><td>Non-qualified</td><td>15.6</td><td>1 (ref)</td><td>10.3</td><td>1 (ref)</td><td>3.0</td><td>1 (ref)</td><td>3.1</td><td>1 (ref)</td><td>25.4</td><td>1 (ref)</td></tr><tr><td>Qualified</td><td>26.3</td><td>1.60 (1.30-1.98)</td><td>16.7</td><td>1.47 (1.13-1.91)</td><td>3.2</td><td>1.07 (0.61-1.85)</td><td>2.0</td><td>0.54 (0.27-1.05)</td><td>16.2</td><td>0.63 (0.50-0.80)</td></tr><tr><td><strong>Individual income</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Low-income</td><td>16.6</td><td>1 (ref)</td><td>11.6</td><td>1 (ref)</td><td>2.5</td><td>1 (ref)</td><td>2.5</td><td>1 (ref)</td><td>31.8</td><td>1 (ref)</td></tr><tr><td>Middle-income</td><td>17.6</td><td>1.12 (0.86-1.45)</td><td>13.3</td><td>1.21 (0.89-1.63)</td><td>2.4</td><td>0.87 (0.43-1.76)</td><td>3.0</td><td>1.14 (0.60-2.18)</td><td>19.2</td><td>0.59 (0.47-0.74)</td></tr><tr><td>High-income</td><td>25.5</td><td>1.63 (1.28-2.08)</td><td>15.6</td><td>1.50 (1.11-2.03)</td><td>3.7</td><td>1.38 (0.74-2.61)</td><td>3.0</td><td>1.22 (0.63-2.38)</td><td>14.3</td><td>0.43 (0.33-0.56)</td></tr><tr><td><strong>Hot water at home</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Yes</td><td>19.3</td><td>1.06 (0.85-1.32)</td><td>13.1</td><td>1.06 (0.81-1.37)</td><td>2.6</td><td>0.76 (0.40-1.30)</td><td>2.1</td><td>0.60 (0.35-1.02)</td><td>19.0</td><td>0.65 (0.54-0.80)</td></tr><tr><td>No</td><td>18.5</td><td>1 (ref)</td><td>13.0</td><td>1 (ref)</td><td>2.9</td><td>1 (ref)</td><td>3.8</td><td>1 (ref)</td><td>28.6</td><td>1 (ref)</td></tr></tbody></table>

Prev Risk factor prevalence, PR Age-adjusted prevalence ratio, 95%CI 95% confidence interval
Baromètre Santé DOM survey, 2014
<table><caption>**Table 5** Associations between SES and risk factors in men</caption><thead><tr><th rowspan="2">SES indicator</th><th colspan="2">Ever tobacco</th><th colspan="2">Current tobacco</th><th colspan="2">Daily alcohol</th><th colspan="2">Harmful chronic alcohol use</th><th colspan="2">Obesity</th></tr><tr><th>Prev</th><th>PR (95% CI)</th><th>Prev</th><th>PR (95% CI)</th><th>Prev</th><th>PR (95% CI)</th><th>Prev</th><th>PR (95% CI)</th><th>Prev</th><th>PR (95% CI)</th></tr></thead><tbody><tr><td><strong>Education level</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Up to primary education</td><td>40.3</td><td>1 (ref)</td><td>22.9</td><td>1 (ref)</td><td>15.2</td><td>1 (ref)</td><td>13.2</td><td>1 (ref)</td><td>15.2</td><td>1 (ref)</td></tr><tr><td>Less than high school diploma</td><td>36.2</td><td>0.91 (0.75-1.09)</td><td>22.6</td><td>0.91 (0.72-1.17)</td><td>12.0</td><td>0.87 (0.64-1.18)</td><td>12.1</td><td>0.82 (0.59-1.13)</td><td>11.4</td><td>0.79 (0.57-1.10)</td></tr><tr><td>High school diploma</td><td>35.9</td><td>0.89 (0.69-1.14)</td><td>26.2</td><td>0.88 (0.65-1.21)</td><td>6.0</td><td>0.46 (0.26-0.80)</td><td>12.7</td><td>0.74 (0.48-1.15)</td><td>9.7</td><td>0.77 (0.48-1.22)</td></tr><tr><td>Tertiary education</td><td>40.1</td><td>0.98 (0.77-1.25)</td><td>23.9</td><td>0.90 (0.66-1.23)</td><td>5.5</td><td>0.40 (0.23-0.70)</td><td>6.8</td><td>0.43 (0.25-0.72)</td><td>10.0</td><td>0.64 (0.40-1.01)</td></tr><tr><td><strong>Occupational Class</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Inactive</td><td>27.1</td><td>0.67 (0.48-0.94)</td><td>24.5</td><td>0.63 (0.44-0.91)</td><td>2.4</td><td>0.31 (0.12-0.81)</td><td>9.9</td><td>0.37 (0.22-0.62)</td><td>5.2</td><td>1.11 (0.43-2.87)</td></tr><tr><td>Non-qualified</td><td>38.6</td><td>1 (ref)</td><td>24.1</td><td>1 (ref)</td><td>12.2</td><td>1 (ref)</td><td>13.4</td><td>1 (ref)</td><td>13.4</td><td>1 (ref)</td></tr><tr><td>Qualified</td><td>40.3</td><td>1.04 (0.88-1.22)</td><td>21.3</td><td>0.95 (0.76-1.19)</td><td>12.2</td><td>0.93 (0.69-1.25)</td><td>8.9</td><td>0.73 (0.53-1.01)</td><td>12.1</td><td>0.88 (0.65-1.18)</td></tr><tr><td><strong>Individual income</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Low-income</td><td>36.1</td><td>1 (ref)</td><td>24.4</td><td>1 (ref)</td><td>11.8</td><td>1 (ref)</td><td>15.1</td><td>1 (ref)</td><td>13.2</td><td>1 (ref)</td></tr><tr><td>Middle-income</td><td>34.8</td><td>0.98 (0.79-1.21)</td><td>19.2</td><td>0.84 (0.64-1.10)</td><td>10.4</td><td>0.85 (0.59-1.24)</td><td>9.6</td><td>0.68 (0.48-0.98)</td><td>11.0</td><td>0.70 (0.48-1.02)</td></tr><tr><td>High-income</td><td>42.7</td><td>1.18 (0.97-1.44)</td><td>24.4</td><td>1.08 (0.84-1.40)</td><td>9.3</td><td>0.74 (0.50-1.08)</td><td>10.0</td><td>0.72 (0.51-1.03)</td><td>12.1</td><td>0.76 (0.52-1.09)</td></tr><tr><td><strong>Hot water at home</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Yes</td><td>38.1</td><td>1.02 (0.87-1.21)</td><td>23.5</td><td>1.02 (0.83-1.26)</td><td>10.8</td><td>0.94 (0.69-1.26)</td><td>10.0</td><td>0.68 (0.52-0.89)</td><td>10.4</td><td>0.65 (0.49-0.87)</td></tr><tr><td>No</td><td>36.8</td><td>1 (ref)</td><td>22.9</td><td>1 (ref)</td><td>11.2</td><td>1 (ref)</td><td>15.0</td><td>1 (ref)</td><td>15.6</td><td>1 (ref)</td></tr></tbody></table>

Prev Risk factor prevalence, PR Age-adjusted prevalence ratio, 95%CI 95% confidence interval

Baromètre Santé DOM survey, 2014

area-level socio-economic status and incidence of cancer revealed that women living in deprived areas were found to have a lower incidence of lung and head and neck cancers when compared to more affluent areas, which is consistent with the lower prevalence of tobacco smoking (a major risk factor for respiratory cancer) among women of low SES reported in our study [32]. That same study showed that breast cancer incidence was higher in women from deprived areas. Our results on obesity, a known risk factor for breast cancer, coincided well with the incidence data in that study, since our female obesity was consistently more prevalent in the lower SES strata.

In addition to the social distribution, our analysis revealed interesting estimates for the prevalence of risk factors by gender. The FWI were found to have a particular NCD risk factor profile, especially when compared to Caribbean neighbours and mainland France. Overall, the prevalence of risk factors in the FWI was in-between mainland France and other Caribbean territories. The prevalence of current smokers was 23% in men and 13% in women, lower than in mainland France (32.3 and 24.3%) [33], and similar in men to the other territories in the Caribbean [4]. However, in the FWI the prevalence of current smokers in women was higher than in other Caribbean territories (5.9% in Jamaica and 3.7% in Barbados) [14, 34]. Daily alcohol drinking prevalence was also lower in the FWI (12% in men, 3% in women) than in mainland France (15% in men, 5% in women) [35]. Harmful chronic alcohol use was however similar in men (FWI:

12%, mainland France: 11%) and in women (FWI: 3%, mainland France: 4%). The other reports in the Caribbean used different definitions for alcohol drinking to us which made it difficult to evaluate differences between countries.

In our study obesity prevalence was assessed from self-reported data and may be underestimated [36]. In a survey in mainland France using the same methodology than ours, obesity prevalence in women (12%) was lower to that in the FWI (22%), whereas in men the prevalence was similar in both territories (12%) [37]. In a survey based on measurements of height and weight conducted in 2008 in the FWI obesity prevalence was slightly higher than in our study (17% in men and 27% in women) [38]. A national survey in mainland France, also using measurements, reported an obesity prevalence of 16% in men and 17% in women [29]. It should be noted that regardless the method used (self-report or measurements): the prevalence of obesity in men is similar in mainland France and in the FWI; the prevalence of obesity in women is higher in the FWI; in mainland France, the prevalence of obesity is similar in men and women, whereas in the FWI obesity is much more frequent in women. On the contrary, obesity among men and women in the FWI was much lower compared to the prevalence reported by Caribbean neighbours and Nicaragua [14, 39-42]. These observed differences could be due to the FWI being overseas French regions, and the population may share similar behaviour patterns from their mainland counterparts; however, they are
under the Caribbean influence due to their geographic position. These conditions could explain this particular risk factor profile in the FWI.

Our study presents some limitations that should be taken into consideration when interpreting our results. The socio-economic indicators and risk factors were measured through self-reported data from our study participants and thus, are subject to misclassification bias. We cannot exclude the possibility that this misclassification was related to SES, which may have impacted our results on the social distribution of risk factors. Our study has also several strengths. Our sample size was quite large (4054 participants), and therefore could provide fairly reliable estimates and we corrected for the non-response bias by using sample weights. Our sample was representative of the FWI and included participants from both rural and urban areas; hence, our results can be considered generalisable to the FWI.

## Conclusion

Our analysis revealed gender-specific social disparities in NCD risk factor distribution. Women of high socioeconomic status were significantly more likely to be smokers, whereas alcohol drinking in men and obesity in women were inversely associated with socioeconomic status. Future prevention programs and policies should take into consideration our findings.

## Abbreviations

BMI: Body mass index; CI: Confidence interval; FWI: French West Indies;

PR: Prevalence ratio; SES: Socioeconomic status

## Acknowledgements

Not applicable.

## Authors' contributions

JBR designed the "Baromètre Santé DOM" survey and coordinated the original collection of the data; AA and DL designed the present study, conducted the analyses and draft the manuscript; JD, CB and GM contributed to the statistical analysis and interpretation of the results. All authors critically reviewed the manuscript and approved the final version.

## Funding

The « Baromètre Santé DOM » survey was funded by the French Public Health Agency (Santé Publique France). Aviane Auguste was supported by a grant from the "Ligue contre le Cancer, comité d'Ille-et-Vilaine" for this work. The funders had no role in study design, data analysis, interpretation of the results or writing of the manuscript.

## Availability of data and materials

Data are from the "Baromètre Santé DOM" carried out by the French National Public Health Agency (Santé Publique France). This analysis has been subject to a license for the use of data issued by Santé Publique France. Readers may contact Jean-Baptiste Richard (jean-baptiste.richard@santepubliquefrance.fr) to request the data.

## Ethics approval and consent to participate

The survey was approved by the relevant national ethics committee, the French Data Protection Authority (Commission Nationale de l'Informatique et des Libertés, CNIL). Participation was anonymous and voluntary. In accordance with the guidelines of the CNIL, all included subjects gave verbal informed consent before the telephone interview, and parental verbal consent was obtained for participants under 18.

## Consent for publication

Not applicable.

## Competing interests

The authors declare that they have no competing interests.

## Author details

¹Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) -UMR_S 1085, F-97100 Pointe-à-Pitre, France.

²Sorbonne Université, INSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique (IPLESP), F75012 Paris, France. ³Santé publique France, French National Public Health Agency, 12 rue du val d'Osne, F-94415 Saint Maurice, France.

Received: 23 April 2019 Accepted: 17 October 2019

Published online: 30 October 2019

## References

1. French epidemiological center on medical causes of deaths (2019) Causes of deaths. http://cepidc-data.inserm.fr/inserm/html/index2.htm. Accessed 28 Sep 2019.

2. Joachim C, Veronique-Baudin J, Ulric-Gervaise S, et al. Cancer burden in the Caribbean: an overview of the Martinique cancer registry profile. BMC Cancer. 2019;19:239. https://doi.org/10.1186/s12885-019-5434-6.

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4.2 Prevalence of oral HPV infection among healthy individuals and head and neck cancer cases in the French West Indies

Work published in the journal Cancer Causes and Control in September 2017
<figure><img src="image_9.png" /></figure>

# Prevalence of oral HPV infection among healthy individuals and head and neck cancer cases in the French West Indies

Aviane Auguste<fnref n="1" />,<fnref n="2" /> · Stanie Gaëte<fnref n="3" /> · Cécile Herrmann-Storck<fnref n="4" /> · Leah Michineau<fnref n="1" />,<fnref n="2" /> ·

Clarisse Joachim<fnref n="5" /> · Jacqueline Deloumeaux<fnref n="3" />,<fnref n="6" /> · Suzy Duflo<fnref n="7" /> · Danièle Luce<fnref n="1" />,<fnref n="2" />,<fnref n="8" />

Received: 12 June 2017 / Accepted: 16 September 2017

© Springer International Publishing AG 2017

## Abstract

**Purpose** Human papillomavirus (HPV) is known to play a role in the development of head and neck squamous cell carcinomas (HNSCC) and to date, no study has reported on the association between oral HPV infection and HNSCC in the Caribbean. The objective was to determine the prevalence of oral HPV infection in the French West Indies (FWI), overall and by HPV genotype, among HNSCC cases and healthy population controls.

**Method** We used data from a population-based case-control study conducted in the FWI. The prevalence of oral HPV was estimated separately among 100 HNSCC cases (mean age 59 years) and 308 population controls (mean age 57 years). Odds ratios (OR) and 95% confidence intervals

(CI) were estimated using a logistic regression adjusting for age, sex, tobacco, and alcohol consumption, to assess the association between oral HPV infection and HNSCC.

**Results** Prevalence of oral HPV infections was 26% in controls (30% in men and 14% in women) and 36% in HNSCC cases (36% in men, 33% in women). HPV52 was the most commonly detected genotype, in cases and in controls. The prevalence of HPV16, HPV33, and HPV51 was significantly higher in cases than in controls (p = 0.0340, p = 0.0472, and 0.0144, respectively). Oral infection with high-risk HPV was associated with an increase in risk of HNSCC (OR 1.99, 95% CI 0.95–4.15). HPV16 was only associated with oropharyngeal cancer (OR 16.01, 95% CI 1.67–153.64).

<figure><img src="image_10.png" /></figure>

Danièle Luce
daniele.luce@inserm.fr

Aviane Auguste
aviane-Auguste@inserm.fr

Stanie Gaëte
stanie.gaete@chu-guadeloupe.fr

Cécile Herrmann-Storck
cecile.herrmann@chu-guadeloupe.fr

Leah Michineau
leah.michineau@inserm.fr

Clarisse Joachim
clarisse.joachim@chu-martinique.fr

Jacqueline Deloumeaux
jacqueline.deloumeaux@chu-guadeloupe.fr

Suzy Duflo
suzy.duflo@chu-guadeloupe.fr

<footnote n="1">¹ INSERM U 1085 - IRSET (Research Institute for Environmental and Occupational Health), Pointe-à-Pitre, Guadeloupe, France</footnote>

<footnote n="2">² University of Rennes 1, Rennes, France</footnote>

<footnote n="3">³ Centre de Ressources Biologiques de Guadeloupe, Pointe-à-Pitre, Guadeloupe, France</footnote>

<footnote n="4">⁴ Laboratory of Microbiology, University Hospital of Guadeloupe, Pointe-à-Pitre, Guadeloupe, France</footnote>

<footnote n="5">5 Martinique Cancer Registry, UF 1441 Registre des cancers, Pôle de Cancérologie Hématologie Urologie Pathologie, University Hospital of Martinique, Fort-de-France, Martinique, France</footnote>

<footnote n="6">⁶ General Cancer Registry of Guadeloupe, University Hospital of Guadeloupe, Pointe-à-Pitre, Guadeloupe, France</footnote>

<footnote n="7">⁷ Department of Oto-Rhino-Laryngology and Head and Neck Surgery, University Hospital of Guadeloupe, Pointe-à-Pitre, Guadeloupe, France</footnote>

<footnote n="8">⁸ INSERM U 1085 - IRSET, Faculté de Médecine, Campus de Fouillole, BP 145, 97154 Pointe-à-Pitre, France</footnote>
**Conclusion** This study revealed a high prevalence of oral HPV infection in this middle-aged Afro-Caribbean population, and a specific distribution of HPV genotypes. These findings may provide insight into HNSCC etiology specific to the FWI.

**Keywords** Human papillomavirus · Oral HPV · Head and neck cancer · Saliva samples · Caribbean · France

## Introduction

Head and neck cancer remains a major public health problem worldwide. In the Caribbean, the estimated age-standardized (world) incidence rates for 100,000 person-years in 2012 for cancer of the lip, oral cavity, larynx, and pharynx combined are 16.8 in men and 3.7 in women, similar to incidence rates in the United States (men: 16.6; women: 5.4), but higher than in Central (men: 7.8; women: 2.6) or South America (men: 13.9; women 3.8) (1). Guadeloupe and Martinique are two French overseas territories in the French West Indies (FWI). The population consists primarily of persons of African descent (about 85%). Incidence rates of head and neck cancer in men are 25.5 per 100,000 in Guadeloupe and 15.8 per 100,000 in Martinique. Despite being lower or of the same order of magnitude than that of mainland France (22.7 per 100,000), a well-known high incidence area, these rates are among the highest in the Caribbean islands. Particularly, for pharyngeal cancer (excluding nasopharynx), Martinique (6.0 per 100,000) and Guadeloupe (6.2 per 100,000) have the top two highest incidence rates among men in the Caribbean [1]. The reasons for this relatively high incidence remain unclear. Tobacco smoking and alcohol drinking are the major risk factors for these cancers. However, a recent survey has shown that tobacco and alcohol consumption are much lower in the FWI than in mainland France [2].

Human papillomavirus (HPV) is known to play a role in the development of head and neck squamous cell carcinomas (HNSCC). There are many HPV genotypes, which all have varying levels of carcinogenic capacities, ranging from no risk to high risk. HPV16 is a recognized risk factor for oropharyngeal and base of the tongue cancer, but the evidence remains inadequate for the role of other HPV types and the association between HPV and other subsites of HNSCC [3]. In addition, significantly better clinical outcomes have been demonstrated in patients with HPV-related oropharyngeal cancer, whereas no consistent results were found for nonoropharynx subsites [4–6]. Knowing the distribution of HPV in the population is therefore a great concern for the prevention and control of HNSCC in the region. The prevalence of HPV infection, the distribution of HPV genotypes, and the proportion of head and neck cancers caused by HPV may

vary substantially between different geographical regions [7–9]. To this date, no study has been conducted to address the prevalence of oral HPV infection in the FWI; furthermore, little data are available in the Caribbean. The objective of this report was primarily to determine the prevalence of oral HPV infection in the FWI population and describe the distribution of the different genotypes among HNSCC cases and healthy individuals. In addition, we evaluated the association between HPV-integrated-DNA detected in saliva and the risk of developing HNSCC.

## Methods

### Study population, data and specimen collection

The present report is based on data obtained from a population-based case-control study, which was conducted in the two overseas French regions in the FWI: Martinique and Guadeloupe. The study is an extension of a large nationwide case-control study, the ICARE study, which has already been conducted in ten French regions covered by a cancer registry [10]. The study in the FWI used the same protocol and questionnaire, described in details elsewhere [10], with some adaptations to the local context. Eligible cases were patients residing in the FWI, suffering from a primary, malignant tumor of the oral cavity, pharynx, sinonasal cavities, and larynx (International Classification of Diseases, 10th Revision, codes C00–C14; C30–C32) of any histological type, aged between 18 and 75 years at diagnosis, newly diagnosed, and histologically confirmed between 1 April 2013 and 30 June 2016. The inclusion of cases was performed with the collaboration of the cancer registries of Martinique and Guadeloupe. A procedure was set up to expedite case identification, in order to reduce the delay between diagnosis and interview of cases. Cases were identified through active search, by regular contacts and visits to the pathology laboratories and hospital departments that usually diagnose and treat head and neck cancers. A list of these laboratories and hospital departments was established by each registry, based on data of the previous years. The control group was selected from the general population of the FWI by random digit dialing, using incidence density sampling method. In each region (Guadeloupe or Martinique), controls were frequency-matched to the cases by sex and age. Additional stratification was used to achieve a distribution by socioeconomic status among the controls comparable to that of the general population.

Cases and controls were interviewed face-to-face with a standardized questionnaire including in particular sociodemographic characteristics and lifetime tobacco and alcohol consumption. Participants were asked to provide a saliva sample, using the Oragene® OG-500 kit (DNA Genotek).
Samples were sent to the Biological Resource Centre of Guadeloupe for storage at 24 °C. Oragene® saliva specimens may be stored for at least 5 years at room temperature without DNA degradation [11].

Among 257 cases identified as potentially eligible, 192 (74.7%) agreed to participate and were interviewed. Among them, after diagnosis review, 22 did not meet the inclusion criteria. Among the remaining 170 cases, 114 (72.3%) provided a saliva sample. Among the 497 eligible controls, 405 (81.5%) answered the questionnaire and among them 311 (76.2%) provided a saliva sample. Each subject included in the study gave a written and informed consent. In order to protect the confidentiality of personal data, the questionnaire included only an identification number, without any nominative information. The same identification number was used for biological specimen. The link between the name and the identification number (to the exclusion of any other data) was kept by the cancer registry of the area where the subject was interviewed.

The study was approved by the Institutional Review Board of the French National Institute of Health and Medical Research and by the French Data Protection Authority.

## DNA extraction

The extraction of DNA was manually performed on saliva samples. Genomic DNA extraction was carried out using prepIT®-L2P reagent. The samples were mixed and incubated overnight (16 h) at 50 °C to ensure that DNA was released and that nucleases were permanently inactivated. Addition of the prepIT®-L2P reagent revealed all impurities and the DNA in the supernatant was precipitated by adding EtOH 100%. The DNA was washed and the pellet re-suspended in a solution of DNA Hydration (Qiagen®) and then stored at -20 °C.

## HPV detection and genotyping

The detection of HPV was performed with the INNO-LiPA® kit, which allows the detection of the following genotypes: HPV16, HPV18, HPV31, HPV33, HPV35, HPV39, HPV45, HPV51, HPV52, HPV56, HPV58, HPV59, HPV68 (high-risk), HPV26, HPV53, HPV66, HPV70, HPV73, HPV82 (probable high-risk), HPV06, HPV11, HPV40, HPV42, HPV43, HPV44, HPV54, HPV61, HPV81 (low-risk), HPV62, HPV67, HPV83, HPV89 (other). The INNO-LiPA HPV genotyping assay is based on the SPF10 consensus primer system to amplify a 65 bp fragment of the L1 region of the HPV genome [12]. The assay was carried out according to the manufacturer's instructions (INNO-LiPA HPV Genotyping Extra; Innogenetics, Ghent, Belgium).

The amplification was performed using SPF10 primers, with adding primers to amplify the human HLA-DPB1

region for having a control of the DNA quality at the same time. The amplification was performed in a reagent mixture containing biotinylated primers in buffer with dNTP/dUTP mix, MgCl₂, NaN₃ as preservative, AmpliTaq Gold® polymerase, and uracil-N-glycosylase. Before amplification, DNA was added. All PCR reactions were performed with a positive and a negative control. The biotinylated PCR products were genotyped by denaturation and hybridization on nitrocellulose strips followed by a stringent wash. After the addition of the conjugate and the substrate, a colorimetric analysis revealed all the genotypes present in the sample. The hybridization process was automatically performed on the AutoBlot 3000H; at the end, the strip was fixed on a support to read the HPV genotypes lines correspondence.

Due to the presence of primers which amplify all genotypes simultaneously, if there was more competition between particular genotypes, only the presence of a broad range of HPV was detected with the line control HPV1 and/or the line control HPV2. This kind of sample was notified HPV-positive without specifying the genotype. These samples were classified as “undetermined” and were included in the calculation for the prevalence of oral HPV infection regardless of the genotype. However, these samples were excluded from the individual genotype analyses.

## Statistical analysis

The analysis was restricted to squamous cell carcinomas (100 cases). For three controls, the quality of the specimen collected was considered inadequate for HPV detection. Our analysis finally included 408 subjects among which 100 were cases and 308 were controls. A univariate analysis was performed to describe the characteristics of the subjects included in the study. A Chi-squared test was used to test the association between these characteristics and HNSCC. The prevalence of oral HPV infections was estimated separately among the HNSCC cases and the controls. Subjects with DNA-HPV detected in saliva sample were referred to as HPV-positive. This was then repeated for the different categories of carcinogenic risk (high-risk, probable high-risk, low-risk, and other) and the various HPV genotypes. The prevalence was also calculated for different categories of the subject characteristics: age, sex recruitment site, tobacco smoking (ever vs never), alcohol drinking (ever daily drinker, i.e., at least one glass per day during at least 1 year; never daily drinker). The prevalence calculation was performed by determining the absolute number of HPV-positive cases/controls and then dividing by the total number of cases/controls included in the study and 95% CI were calculated. The association between the oral HPV infection and the occurrence of HNSCC was assessed by estimating odds ratios (OR) adjusted for age, sex, tobacco smoking, and alcohol drinking and 95% confidence intervals
(CI), using a logistic regression model. An exact Fisher test was performed to assess this association for each HPV genotype individually. Tests giving a *p* value lower than 5% were considered statistically significant. Statistical analysis was performed using SAS 9.4 software (SAS Institute, Carry, NC USA).

## Results

### Characteristics of study population

Table 1 provides a description of selected characteristics of the cases and controls included in the study. The mean age was similar in both cases and controls (59 and 57 years, respectively), but the age distribution differed (*p*=0.0163). The proportion of women was significantly greater in the control group (*p*=0.0026). The proportion of subjects by region did not differ between cases and controls (*p*=0.9311). As expected, tobacco smoking (*p*<0.0001) and alcohol drinking (*p*<0.0001) were more frequent among cases than among controls.

### Oral HPV prevalence

Table 2 provides the oral HPV prevalence by age group, sex, recruitment site, tobacco smoking, and alcohol drinking for HNSCC cases and controls separately. Overall, oral HPV was found in 36.0% (95% CI 27.6–47.2) of the cases and 26.0% (95% CI 21.2–31.3) of the controls. The

subjects aged between 55 and 64 years had the highest prevalence of HPV in both cases and controls (48.8%; 95% CI 33.35–65.5 and 35.8%; 95% CI 26.2–46.3, respectively), when compared to the other age groups. Among the controls, oral HPV was found to be twice as prevalent in men as in women, whereas the prevalence was similar in men and women among the cases. A significantly greater HPV prevalence was observed in Guadeloupe than in Martinique regardless of the cancer status. Among the controls, the prevalence of oral HPV was higher in smokers (34.0%; 95% CI 25.0–43.8) than in never smokers (22.0%; 95% CI 16.5–28.4), and in daily drinkers (38.4%; 95% CI 28.1–49.5) compared to never daily drinkers (21.2%; 95% CI 16.0–27.1). An opposite trend was observed among the cases, with a slightly lower prevalence in smokers (35.0%; 95% CI 25.5–45.9) and drinkers (32.9%; 95% CI 22.3–44.9) than in never smokers (40.0%; 95% CI 19.1–63.9) and never drinkers (44.4%; 95% CI 25.5–64.7).

Table 3 shows the prevalence of high-risk, probable high-risk, low-risk, and other HPV types, and of the individual HPV genotypes. The prevalence of high-risk HPV types was found to be 23.3% in the cases and 10.7% in the controls (*p*=0.005). Concerning the other risk categories (probable high-risk, low-risk, and other), the prevalence did not differ significantly between cases and controls. The most frequent HPV genotypes detected among the controls were HPV66 (5.0%) and HPV52 (4.3%); whereas the genotypes HPV52, HPV56, and HPV16 were the most frequent among the cases (8.9, 5.6, and 4.4% respectively). The prevalences of HPV16, HPV33, and HPV51 were significantly higher

<table><caption>**Table 1** Main characteristics of HNSCC cases and controls</caption><thead><tr><th>Variable</th><th>Category</th><th>Cases (n=100)<br>n (%)</th><th>Controls (n=308)<br>n (%)</th><th>p value</th></tr></thead><tbody><tr><td>Age</td><td></td><td></td><td></td><td>0.0163</td></tr><tr><td></td><td>&lt;45</td><td>4 (4.0)</td><td>44 (14.3)</td><td></td></tr><tr><td></td><td>45–54</td><td>27 (27.0)</td><td>81 (26.3)</td><td></td></tr><tr><td></td><td>55–64</td><td>43 (43.0)</td><td>95 (30.8)</td><td></td></tr><tr><td></td><td>≥ 65</td><td>26 (26.0)</td><td>88 (28.6)</td><td></td></tr><tr><td>Sex</td><td></td><td></td><td></td><td>0.0026</td></tr><tr><td></td><td>Male</td><td>88 (88.0)</td><td>226 (73.4)</td><td></td></tr><tr><td></td><td>Female</td><td>12 (12.0)</td><td>82 (26.6)</td><td></td></tr><tr><td>Recruitment site</td><td></td><td></td><td></td><td>0.9311</td></tr><tr><td></td><td>Martinique</td><td>44 (44.0)</td><td>134 (43.5)</td><td></td></tr><tr><td></td><td>Guadeloupe</td><td>56 (56.0)</td><td>174 (56.5)</td><td></td></tr><tr><td>Tobacco smoking</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>Ever</td><td>80 (80.0)</td><td>106 (34.4)</td><td>&lt;0.0001</td></tr><tr><td></td><td>Never</td><td>20 (20.0)</td><td>202 (65.6)</td><td></td></tr><tr><td>Daily alcohol drinking</td><td></td><td></td><td></td><td>&lt;0.0001</td></tr><tr><td></td><td>Ever</td><td>73 (73.0)</td><td>86 (27.9)</td><td></td></tr><tr><td></td><td>Never</td><td>27 (27.0)</td><td>222 (72.1)</td><td></td></tr></tbody></table>

French West Indies, 2013–2016
<table><caption>**Table 2** Prevalence of oral HPV infection by age, sex, recruitment site, tobacco, and alcohol consumption among HNSCC cases and controls</caption><thead><tr><th rowspan="2">Variable</th><th rowspan="2">Category</th><th colspan="3">Cases (n = 100)</th><th colspan="3">Controls (n = 308)</th></tr><tr><th>HPV+</th><th>Prevalence<sup>a</sup></th><th>95% CI</th><th>HPV+</th><th>Prevalence<sup>a</sup></th><th>95% CI</th></tr></thead><tbody><tr><td rowspan="4">Age</td><td>&lt;45</td><td>0</td><td></td><td></td><td>6</td><td>13.6</td><td>5.1-27.1</td></tr><tr><td>45-54</td><td>10</td><td>37.0</td><td>21.4-57.6</td><td>21</td><td>25.9</td><td>16.8-36.9</td></tr><tr><td>55-64</td><td>21</td><td>48.8</td><td>33.3-65.5</td><td>34</td><td>35.8</td><td>26.2-46.3</td></tr><tr><td>≥65</td><td>5</td><td>19.2</td><td>6.5-39.3</td><td>19</td><td>21.6</td><td>13.5-31.7</td></tr><tr><td rowspan="2">Sex</td><td>Male</td><td>32</td><td>36.3</td><td>263-47.3</td><td>68</td><td>30.1</td><td>24.2-36.5</td></tr><tr><td>Female</td><td>4</td><td>33.3</td><td>9.9-65.11</td><td>12</td><td>14.6</td><td>7.8-24.1</td></tr><tr><td rowspan="2">Recruitment site</td><td>Martinique</td><td>9</td><td>20.1</td><td>9.8-35.3</td><td>23</td><td>17.2</td><td>11.28-24.6</td></tr><tr><td>Guadeloupe</td><td>27</td><td>48.2</td><td>34.7-62.0</td><td>57</td><td>32.8</td><td>25.8-40.3</td></tr><tr><td rowspan="2">Tobacco smoking</td><td>Ever</td><td>28</td><td>35.0</td><td>25.5-45.9</td><td>36</td><td>34.0</td><td>25.0-43.8</td></tr><tr><td>Never</td><td>8</td><td>40.0</td><td>19.1-63.9</td><td>44</td><td>22.0</td><td>16.5-28.4</td></tr><tr><td rowspan="2">Daily alcohol drinking</td><td>Ever</td><td>24</td><td>32.9</td><td>22.3-44.9</td><td>33</td><td>38.4</td><td>28.1-49.5</td></tr><tr><td>Never</td><td>12</td><td>44.4</td><td>25.5-64.7</td><td>47</td><td>21.2</td><td>16.0-27.1</td></tr><tr><td colspan="2">Total</td><td>36</td><td>36.0</td><td>27.6-47.2</td><td>80</td><td>26.0</td><td>21.1-30.9</td></tr></tbody></table>

French West Indies, 2013–2016

in cases than in controls ($p=0.0340$, 0.0472, and 0.0144, respectively).

We also looked at the HPV prevalence and genotype distribution by cancer site. The following sites were distinguished: oral cavity (oral tongue, gum, mouth, floor of mouth, lips; 22 cases), oropharynx (base of tongue, tonsil, other parts of the oropharynx; 41 cases), larynx/hypopharynx (23 cases), and other sites (sinonasal cavities four cases). The prevalence rates of oral HPV infection were 34.1, 32.0, and 34.6% in cancers of the oropharynx, oral cavity, and larynx/hypopharynx, respectively. The prevalence of high-risk HPV was similar in oropharyngeal (22.0%) and non- oropharyngeal (23.0%) cancer cases. HPV-16 was detected exclusively in oropharyngeal cancer cases (four cases). The three cases positive for HPV33 were two oropharyngeal cancers cases and one oral cavity cancer. HPV51 was detected in one oropharyngeal cancer, in one oral cavity cancer, and in one laryngeal cancer. Other HPV types were not found to be associated with specific cancer sites.

### Association between oral HPV and HNSCC

Table 4 gives the results of the logistic regression adjusted for age, sex, tobacco smoking, and alcohol drinking, modeling the risk of developing a HNSCC. The overall HPV infection regardless of the level of carcinogenicity was not found significantly associated to HNSCC. Oral infection with high-risk HPV was associated with a two-fold increase in risk of HNSCC (OR 1.99, 95% CI 0.95–4.15). The association between HPV16 and HNSCC risk (OR 6.24 95% CI 0.76–51.35) was limited to oropharyngeal cancer (OR 16.01 95% CI 1.67–153.64).

### Discussion

This is the first study in the Caribbean reporting on oral HPV infection in both HNSCC cases and healthy individuals of African descent. We found an overall HPV prevalence of 36% among HNSCC cases, with little variation by cancer site. Our results are globally compatible with those of a recent meta-analysis that estimated for tumors from patients of Central and South America an overall HPV DNA prevalence of 33.1% (95% CI 15.4–53.6) for cancer of the oral cavity, 14.9% (95% CI 5.6–27.0) for oropharyngeal cancer, and 32.2% (95% CI 15.5–51.4) for laryngeal/hypopharyngeal cancer [7]. Another meta-analysis of HPV prevalence in tumors from HNSCC patients of African descent reported a prevalence of 17% (95% CI 8.8–27.0%), higher among oropharyngeal cancers (31.5%) than in non- oropharyngeal cancers (14.5%) [13]. The prevalence of oral HPV infection in our study was similar for oropharyngeal cancer (29.3%), but was higher for other cancer sites (28.6%). In recent case-control studies on HNSCC [14–18], the prevalence of HPV infection in the oral cavity varied from 19 to 49% for all HNSCC, and from 37 to 61% for oropharyngeal cancers. Contrary to most other studies, HPV16 was not the most frequently detected HPV type in our study, resulting in a low prevalence of HPV16 among cases. However, the prevalence of HPV16 was similar for oropharyngeal cancer (10%) to that observed in Central and South America (14.5%) [7].

We took advantage of the controls recruited in this study to estimate the prevalence of oral HPV infections in the general population of the FWI. The overall prevalence for the two regions was 26%. The prevalence that we estimated in our study was on average greater than in previous studies

<footnote><sup>a</sup>Prevalence calculated by dividing the number of HPV+ by the total number of subjects for a given category</footnote>
<table><caption>**Table 3** Prevalence of oral HPV infection by genotype among HNSCC cases and controls</caption><thead><tr><th>Genotype<sup>a</sup></th><th>Cases (n=90)<br>n (%)<sup>b</sup></th><th>Controls (n=281)<br>n (%)<sup>b</sup></th><th>p value<sup>c</sup></th></tr></thead><tbody><tr><td>High-risk</td><td>21 (23.3)</td><td>30 (10.7)</td><td>0.0050</td></tr><tr><td>HPV16</td><td>4 (4.4)</td><td>2 (0.7)</td><td>0.0340</td></tr><tr><td>HPV18</td><td>2 (2.2)</td><td>1 (0.4)</td><td>0.1501</td></tr><tr><td>HPV31</td><td>2 (2.2)</td><td>6 (2.1)</td><td>1</td></tr><tr><td>HPV33</td><td>3 (3.3)</td><td>1 (0.4)</td><td>0.0472</td></tr><tr><td>HPV39</td><td>0 (0.0)</td><td>1 (0.4)</td><td>1</td></tr><tr><td>HPV45</td><td>1 (1.1)</td><td>2 (0.7)</td><td>0.5708</td></tr><tr><td>HPV51</td><td>3 (3.3)</td><td>0 (0.0)</td><td>0.0144</td></tr><tr><td>HPV52</td><td>8 (8.9)</td><td>12 (4.3)</td><td>0.1116</td></tr><tr><td>HPV56</td><td>5 (5.6)</td><td>6 (2.1)</td><td>0.1473</td></tr><tr><td>HPV58</td><td>0 (0.0)</td><td>4 (1.4)</td><td>0.5761</td></tr><tr><td>HPV59</td><td>1 (1.1)</td><td>1 (0.4)</td><td>0.4306</td></tr><tr><td>HPV68</td><td>2 (2.2)</td><td>8 (2.8)</td><td>1</td></tr><tr><td>Probable high-risk</td><td>6 (6.7)</td><td>24 (8.5)</td><td>0.6628</td></tr><tr><td>HPV26</td><td>1 (1.1)</td><td>0 (0.0)</td><td>0.2451</td></tr><tr><td>HPV53</td><td>0 (0.0)</td><td>4 (1.4)</td><td>0.5761</td></tr><tr><td>HPV66</td><td>4 (4.4)</td><td>14 (5.0)</td><td>1</td></tr><tr><td>HPV70</td><td>1 (1.1)</td><td>3 (1.1)</td><td>1</td></tr><tr><td>HPV73</td><td>0 (0.0)</td><td>2 (0.7)</td><td>1</td></tr><tr><td>HPV82</td><td>1 (1.1)</td><td>2 (0.7)</td><td>0.5708</td></tr><tr><td>Low-risk</td><td>6 (6.7)</td><td>13 (4.6)</td><td>0.4258</td></tr><tr><td>HPV06</td><td>3 (3.3)</td><td>3 (1.1)</td><td>0.1603</td></tr><tr><td>HPV42</td><td>1 (1.1)</td><td>0 (0.0)</td><td>0.2451</td></tr><tr><td>HPV44</td><td>1 (1.1)</td><td>5 (1.8)</td><td>1</td></tr><tr><td>HPV54</td><td>0 (0.0)</td><td>1 (0.4)</td><td>1</td></tr><tr><td>HPV61</td><td>2 (2.2)</td><td>2 (0.7)</td><td>0.2529</td></tr><tr><td>HPV81</td><td>0 (0.0)</td><td>3 (1.1)</td><td>1</td></tr><tr><td>Other</td><td>5 (5.6)</td><td>7 (2.5)</td><td>0.1769</td></tr><tr><td>HPV62</td><td>2 (2.2)</td><td>2 (0.7)</td><td>0.2529</td></tr><tr><td>HPV67</td><td>2 (2.2)</td><td>3 (1.1)</td><td>0.6000</td></tr><tr><td>HPV83</td><td>0 (0.0)</td><td>2 (0.7)</td><td>1</td></tr></tbody></table>

French West Indies, 2013–2016

reporting on oral HPV prevalence in healthy individuals from different geographic regions. In a literature review, oral HPV infection prevalence was estimated to be 4.5% (95% CI 3.9–5.1%) overall, 3.5% (95% CI 3.0–4.1%) for high-risk HPV types, and 1.3% (95% CI 1.0–1.7%) for HPV16 [9]. Our control group was, however, frequency-matched to the cases by age and sex, which skewed the results towards

<table><caption>**Table 4** Association between oral HPV infection and HNSCC risk</caption><thead><tr><th>HPV category</th><th>Cases<br>n</th><th>Controls<br>n</th><th>OR<sup>a</sup></th><th>95%CI</th></tr></thead><tbody><tr><td>HPV-negative</td><td>69</td><td>228</td><td>1</td><td>Ref</td></tr><tr><td>Any HPV</td><td>37</td><td>80</td><td>1.13</td><td>0.63–1.99</td></tr><tr><td>High-risk</td><td>21</td><td>30</td><td>1.99</td><td>0.95–4.15</td></tr><tr><td>HPV16</td><td>4</td><td>2</td><td>6.24</td><td>0.76–51.35</td></tr><tr><td>Probable high-risk</td><td>6</td><td>24</td><td>0.42</td><td>0.15–1.21</td></tr><tr><td>Low-risk</td><td>6</td><td>13</td><td>1.85</td><td>0.56–6.11</td></tr><tr><td>Other</td><td>5</td><td>7</td><td>1.35</td><td>0.33–5.63</td></tr></tbody></table>

French West Indies, 2013–2016

older ages and male gender. Furthermore, the small number of subjects below 45 years made it difficult to estimate precisely the HPV prevalence for this category. Consequently, the overall prevalence in our sample is likely to overestimate the prevalence in the general population of the FWI, but provides a fairly reliable estimate of the prevalence in the population of the FWI over 45 years of age. The prevalence of oral HPV infection in our controls is higher than that recently estimated in the US, in men (10.1%) and in women (3.6%), even in the older age categories (55–59: 11.2%, 60–64: 11.4%). The peak prevalence among individuals aged 55–64 years and the higher prevalence in men observed in this study are consistent with our results [19]. Our estimate is also higher than in a multinational sample of healthy men (6.1% in men aged 55–74 years) [20]. This distinct difference in prevalence was observed even in a study conducted in another Caribbean population. The prevalence in women in our control group (14.6%) was more than that of another study reporting on the oral HPV in Tobagonian women (6.6%) who were, however, younger (median age 42 years) than the women in our study [21]. In controls of case-control studies on HNSCC [14–18], who had an age and sex distribution similar to our controls, the prevalence of oral HPV infection varied from 5 to 17.3%. As noted above for the cases, in our controls also HPV16 was not the predominant genotype, and the high HPV prevalence observed in our control group was mainly due to genotypes other than HPV16. It is worth noting that a high prevalence of cervical infection with HPV genotypes other than 16 or 18 was also found among healthy women in Guadeloupe [22].

In our study, overall oral HPV was not found to be significantly associated with HNSCC. This absence of association was consistent with another study which found that the proportion of HPV-positive was almost identical between cases and controls [23]. Other studies reported significant associations between overall oral HPV infections and HNSCC, in particular for oral cancer and oropharyngeal cancer [14, 15,

<footnote><sup>a</sup>The following HPV genotypes were not detected in our sample and were omitted from the table: HPV35, HPV26, HPV11, HPV40, and HPV89</footnote>

<footnote><sup>b</sup>Percentage calculated by dividing by the number of cases/controls. Note that because of multiple infections the individual genotype percentages do not add up to give the total amount of the risk group that they belong to</footnote>

<footnote><sup>c</sup>p value from exact Fisher test</footnote>

<footnote><sup>a</sup>Logistic regression modeling the occurrence of HNSCC, odds ratios adjusted for age, sex, tobacco smoking, and daily alcohol drinking</footnote>
18]. The lack of association with overall HPV infection in our study may be due to the specific distribution of HPV genotypes in our population. Indeed, we found a borderline significant association between high-risk HPV and HNSCC, and a strong and significant association between HPV16 and oropharyngeal cancer. The latter result is consistent with previous studies [3, 18, 24]. Our study revealed also a larger proportion of HPV33 and HPV51 among the HNSCC cases than the controls. The associations with HPV33, HPV51, and HNSCC were not observed in previous studies [15, 20, 21]. In addition, HPV51 was found exclusively in cases and this could provide a good lead for subsequent studies. These findings could be useful to assess the potential efficiency of current HPV vaccination strategies for the prevention of HNSCC in these regions.

We are aware that our study has some limitations that need to be accounted for when interpreting the data. Firstly, the HPV was detected using saliva samples. This means that the HPV infections were prevalent and we had no means of determining whether or not the HPV infection preceded the HNSCC diagnosis. In addition, we had no information of HPV tumor status. However, several studies have reported a good correlation between HPV DNA detection in tumor tissue and saliva rinse [17, 25, 26], and the use of saliva samples was also shown to be sensitive and specific for p16-positive oropharyngeal tumors [27]. Secondly, the relatively small number of HNSCC cases hampered detailed analyses by cancer site and HPV genotype. Selection bias may not be excluded but is thought to be minimal in the present study. The distribution by sex, age, and cancer sites of the cases included in our study was similar to that of the cases in the local cancer registries. Our study population can thus be considered representative of the HNSCC cases. The method used to select the control group was previously demonstrated to yield unbiased samples and the controls could be considered representative of the general population of similar age and sex [10]. Furthermore, this is one of the very few case-control studies which has investigated the role of oral HPV infection in men and women of African descent and will allow comparison with French HPV data to investigate potential racial disparities between these populations [28]. This study may add valuable data supporting the prevention and control of HNSCC in the people of this ethnic group.

## Conclusion

To conclude, the prevalence of oral HPV infection in the French West Indies is 26.0% among healthy individuals and 36.0% in HNSCC patients. The detection of overall oral HPV was not found to influence significantly the occurrence of HNSCC. However, high-risk HPV and the individual

genotypes HPV16, HPV33, and HPV51 increased the risk of HNSCC. These findings are particularly interesting because they give valuable leads on the etiology of these cancers in the FWI. Subsequent analyses will examine the potential interactions with traditional risk factors.

**Acknowledgments** We would like to thank our clinical research associates Lucina Lipau and Audrey Pomier for their help in data collection. Aviane Auguste was supported by a grant from the “Ligue contre le Cancer, comité d’Ille-et-Vilaine” for this work. This study was funded by the French National Cancer Institute (Institut National du Cancer) and the Cancéropôle Ile-de-France.

## Compliance with ethical standards

**Conflict of interest** The authors have no conflict of interest.

**Ethical approval** French Data Protection Authority (CNIL, Commission Nationale de l'Informatique et des Libertés) n° DR-2015-2027; IRB INSERM n° 01-036.

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4.3 Joint effect of Tobacco, Alcohol and Oral HPV infection on Head and Neck Cancer
risk in the French West Indies

Submitted for publication
**Joint effect of Tobacco, Alcohol and Oral HPV infection on Head and Neck Cancer risk in the French West Indies**

**Authors:** Aviane Auguste<sup>a</sup>, Jacqueline Deloumeaux<sup>b,c</sup>, Clarisse Joachim<sup>d</sup>, Stanie Gaete<sup>c</sup>, Léah Michineau<sup>a</sup>, Cécile Herrmann-Storck<sup>e</sup>, Suzy Duflo<sup>f</sup>, Danièle Luce *<sup>a</sup>

**Affiliations**

<sup>a</sup>Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) -UMR_S 1085, F-97100 Pointe-à-Pitre, France

<sup>b</sup>General Cancer Registry of Guadeloupe, University Hospital of Guadeloupe, Pointe-à-Pitre, Guadeloupe, France

<sup>c</sup>Karubiotec™ Biological resources Center, Centre de Ressources Biologiques de Guadeloupe, Pointe-à-Pitre, Guadeloupe, France

<sup>d</sup>Martinique Cancer Registry, UF 1441 Registre des cancers, Pôle de Cancérologie Hématologie Urologie Pathologie, University Hospital of Martinique, Fort-de-France, Martinique, France

<sup>e</sup>Laboratory of Microbiology, University Hospital of Guadeloupe, Pointe-à-Pitre, Guadeloupe

<sup>f</sup>Department of Oto-Rhino-Laryngology and Head and Neck Surgery, University Hospital of Guadeloupe, Pointe-à-Pitre, Guadeloupe, France

**Author's e-mail addresses:**

AvianeAuguste:aviane.auguste@inserm.fr

Jacqueline Deloumeaux:jacqueline.deloumeaux@chu-guadeloupe.fr

Clarisse Joachim:clarisse.joachim@chu-martinique.fr

Stanie Gaete:stanie.gaete@chu-guadeloupe.fr

LéahMichineau:leah.michineau@inserm.fr

Cécile Herrmann-Storck:cecile.herrmann@chu-guadeloupe.fr

SuzyDuflo:suzy.duflo@chu-guadeloupe.fr

DanièleLuce:daniele.luce@inserm.fr

Danièle Luce, PhD
Inserm U 1085 - Irset
Faculté de Médecine
Campus de Fouillole
BP 145
97154 Pointe-à-Pitre
E-mail: daniele.luce@inserm.fr

Words count for the main-text: 3499

Word count of abstract: 232

<footnote>*Correspondence and requests for reprints to:</footnote>
**Abstract**

**Objectives:** To investigate the role of tobacco and alcohol consumption on the occurrence of head and neck squamous cell carcinomas (HNSCC), and the joint effects of these factors with oral HPV infection in the French West Indies, in the Caribbean.

**Materials and Methods:** We conducted a population-based case-control study (145 cases and 405 controls). We used logistic regression models to estimate adjusted odds-ratios (OR) and their 95% confidence intervals (CI). Two-way interactions were assessed on both multiplicative and additive scales.

**Results:** Current smoking (OR=11.6, 95%CI=6.7-20.1), drinking more than 5 glasses of alcohol per day (OR=2.7, 95% CI= 1.2-4.7), and oral infection with High-risk HPV (OR=2.4, 95% CI=1.1-5.0) were significantly associated with HNSCC. The combined exposure to tobacco and alcohol produced a significant synergistic effect on the incidence of HNSCC. Oral infection with High-risk HPV increased the risk of HNSCC in never smokers and non-drinkers. The effects of tobacco, alcohol and of the combined exposure of tobacco and alcohol were substantially lower in HPV-positive than in HPV-negative HNSCC.

**Conclusion:** This is the first case-control study to investigate the role of tobacco smoking, alcohol drinking and oral HPV infection in an Afro-Caribbean population. Although each of these risk factors has a significant effect, our findings indicate that tobacco and alcohol play a less important role in Hr-HPV-positive HNSCC. Further investigations are warranted notably on the interaction of these three risk factors by cancer site.

**Keywords:** Head and neck cancer; tobacco smoking; alcohol drinking; high-risk oral HPV; joint effect; interaction; French West Indies, Caribbean;
## Introduction

Worldwide, more than 700,000 cases of head and neck cancer (including cancers of the oral cavity, pharynx and larynx) are diagnosed each year [1]. Tobacco smoking and alcohol drinking are the major risk factors for these cancers, their joint effect being at least multiplicative [2,3]. Human papillomavirus (HPV) is also a recognized cause of a subset of head and neck squamous cell carcinomas (HNSCC) [4,5]. While the causal role of HPV16 in oropharyngeal cancer is well established, the role of other HPV genotypes or the association between HPV and other subsites of HNSCC is still debated [6]. The manner in which tobacco, alcohol and HPV interact on HNSCC risk remains unclear, with conflicting results. Some studies demonstrated a lack of association with tobacco and alcohol in HPV16-positive HNSCC [5,7,8]. Other more recent studies have shown that tobacco smoking and alcohol drinking have rather an independent role in the etiology of HPV16-positive oropharyngeal cancer [9–11].

Guadeloupe and Martinique are two French overseas territories in the French West Indies (FWI). The population is predominantly Afro-Caribbean. Their incidence rates of head and neck cancer, especially in men, are among the highest in Latin America and the Caribbean [1], despite a relatively low prevalence of tobacco smoking and alcohol drinking [12]. The prevalence of HPV in HNC and the distribution of HPV genotypes may vary substantially according to geographical regions [13–16] and ethnicity [17]. Racial/ethnic differences in the effects of tobacco and alcohol on HNSCC have also been suggested [18].

In order to elucidate the etiology of HNSCC in the FWI, we conducted a population-based case-control study. We previously showed that oral infection with high-risk HPV was associated with an increase in risk of HNSCC. Although oral infection with HPV16 was associated with oropharyngeal cancer, HPV16 was not the predominant genotype and we also found a higher prevalence of other high-risk HPV genotypes in cases than in controls [19].
In the present study, we aimed to investigate the role of tobacco and alcohol consumption on the occurrence of HNSCC, and the joint effects of these factors with oral HPV infection. To our knowledge, this is the first study on this topic in an Afro-Caribbean population.

## Methods

### Study population, data and specimen collection

We conducted a population-based case-control study in Martinique and Guadeloupe. The study is an extension of a large nationwide case-control study, the ICARE study, which has already been conducted in ten French regions covered by a cancer registry [20]. The study in the FWI used the same protocol and questionnaire, described in details elsewhere [20], with some adaptations to the local context. Eligible cases were patients residing in the FWI, suffering from a primary, malignant tumour of the oral cavity, pharynx, sinonasal cavities and larynx of any histological type, aged between 18 and 75 years old at diagnosis, newly diagnosed and histologically confirmed between April 1, 2013 and June 30, 2016. The control group was selected from the general population by random digit dialling, using incidence density sampling method. Controls were frequency matched to the cases by sex, age and region. Additional stratification was used to achieve a distribution by socioeconomic status among the controls comparable to that of the general population.

Cases and controls were interviewed face-to-face with a standardized questionnaire including in particular sociodemographic characteristics and lifetime tobacco and alcohol consumption. Participants were also asked to provide a saliva sample, using the Oragene® OG-500 kit (DNA Genotek).

Among 257 cases identified as potentially eligible, 192 (74.7%) agreed to participate and were interviewed. Among them, after diagnosis review, 22 did not meet the inclusion criteria. Among the remaining 170 cases, 114 (72.3%) provided a saliva sample. Among the 497 eligible controls, 405 (81.5%) answered the questionnaire and among them 311 (76.2%)
provided a saliva sample. Each subject included in the study gave a written and informed
consent. The study was approved by the Institutional Review Board of the French National
Institute of Health and Medical Research (IRB INSERM n°01-036) and by the French Data
Protection Authority (n° DR-2015-2027).

HPV detection and genotyping

The detection of HPV-integrated DNA from saliva samples was performed with the INNO-
LiPA ® kit, according to the manufacturer's instructions (INNO-LiPA HPV Genotyping
Extra; Innogenetics, Ghent, Belgium). The INNO-LiPA HPV genotyping assay allows the
detection of the following genotypes: HPV16, HPV18, HPV31, HPV33, HPV35, HPV39,
HPV45, HPV51, HPV52, HPV56, HPV58, HPV59, HPV68 (High-risk), HPV26, HPV53,
HPV66, HPV70, HPV73, HPV82 (Probable high-risk), HPV06, HPV11, HPV40, HPV42,
HPV43, HPV44, HPV54, HPV61, HPV81 (Low-risk), HPV62, HPV67, HPV83, HPV89
(Other). The full details on the method for HPV detection has been described elsewhere [19].

Exposure variables

Detailed information on lifetime cigarette smoking history was recorded, for each period of
identical smoking habits. The questionnaire included information on age at start and end of
the period, number of cigarettes per day or per week, type of tobacco (blond vs. black),
filtered or not, inhalation pattern, and whether or not the product was manufactured or hand-
rolled. Ever cigarette smokers were defined as persons who smoked at least 100 cigarettes in
their lifetime. Ex- smokers were defined as persons who stopped smoking for at least two
years. Smoking quantity was defined as the average number of cigarettes per day over the
lifetime, and categorised into 3 groups (1 to 10, 11 to 20 and >20 cigarettes/day). Smoking
duration was expressed in years and was divided into 4 categories (1 to 20, 21 to 30, 31 to 40,
> 40 years). Never smoker was the reference category used for all smoking-related variables
in our analyses. Information on smoking pipes, cigars, chewing and snuffing tobacco was also recorded.

Lifetime alcohol drinking information was recorded as well, with for each period of regular consumption, the age at beginning and end, and the number of standard glasses per day, week or month for each type of alcoholic beverage (wine, beer, rum and other strong spirits). For each type of beverage, ever daily alcohol drinking was defined as at least one glass per day during at least one year. The average number of glasses per day was calculated over the lifetime, regardless of the type of beverage, and categorised into 3 groups (<1 glass/day, 1 to 5 glasses/day and >5 glasses per day). The reference category comprised subjects who never drank alcohol or who had drunk less than one glass per week.

Exposure to HPV was assessed in several manners. Subjects with at least one HPV infection of any type were classified as HPV-positive, others were referred as HPV-negative. The group of HPV-positive was further divided in two categories: high-risk-HPV-positive (at least one HPV type in the high-risk group) and non-high-risk-HPV-positive. A final binary variable was used for the exposure to high-risk-HPV: high-risk-HPV-Positive versus high-risk-HPV-Negative, the latter category grouping HPV-negative and non-high-risk-HPV-positive.

## Statistical analysis

The current analysis was restricted to squamous cell carcinomas of the oral cavity (International Classification of Diseases 10th revision codes C00.3-C00.9, C02.0-C02.3, C03.0, C03.1, C03.9, C04.1, C04.8, C04.9, C05.0, C06.0-C06.2, C06.8 and C06.9, n=35), the oropharynx (ICD-10 codes C01.9, C02.4, C05.1, C05.2, C09, C10, C14.2, n=58), the hypopharynx (ICD-10 codes C12-C13, n=19) and the larynx (ICD-10 codes C32, n=32). Our analysis included 145 cases and 405 controls. The association between smoking, alcohol and oral HPV infection and the occurrence of HNSCC was assessed by estimating odds ratios