Lucile Sesé

MD Julien Caliez

MD Isabella Annesi-Maesano

PhD Vincent Cottin

PhD Giancarlo Pesce

MD Morgane Didier

MD Zohra Carton

MD Dominique Israel-Biet

PhD Bruno Crestani

Guillot Stéphanie

Dudoret

PhD, Stéphanie Guillot Dudoret

MD Jacques Cadranel

PhD Benoit Wallaert

PhD Abdellatif Tazi

PhD Bernard Maître

PhD Grégoire Prévot

PhD Sylvain Marchand-Adam

PhD Sandrine Hirschi

MD Sandra Dury

MD Violaine Giraud

MD Anne Gondouin

MD Philippe Bonniaud

PhD Julie Traclet

MD Karine Juvin

MD Raphael Borie

PhD Jean François Bernaudin

PhD Dominique Valeyre

PhD Catherine Cavalin

PhD Hilario Nunes
email: hilario.nunes@aphp.fr

MD, PhD Cofi Collaborators

Diane Bouvry

Pierre Yves Brillet

Philippe Camus

Juliette Chabrol

Jean François Cordier

Christophe Cracco

Philippe Delaval

Boris Duchemann

Sevrine Feuillet

Olivia Freynet

Frédéric Gagnadoux

Patrick Germaud

Louise Gindre

André Guetta

Patrick Haussman

Stephane Jouneau

Marianne Kambouchner

Chahera Khouatra

Jacques Lacronique

Anita Molard

Clément Picard

Carole Planes

Paul Andrés Rosental

Olivier Sanchez

Thomas Similowski

Luc Thiberville

Yurdagül Uzuhnan

Hilario Pr

Nunes

Low income and outcome in idiopathic pulmonary fibrosis: An association to uncover

Keywords: idiopathic pulmonary fibrosis, socioeconomic status, income, air pollution, occupational exposure

niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

respiratory system, and socioeconomic background is considered one of the major causes of these disparities [START_REF] Schraufnagel | An Official American Thoracic Society/European Respiratory Society Policy Statement: Disparities in Respiratory Health[END_REF]. While many epidemiological studies have demonstrated a substantial impact of SES on the severity of chronic lung diseases such as chronic obstructive pulmonary disease (COPD), asthma and lung cancer [START_REF] Gershon | Chronic obstructive pulmonary disease and socioeconomic status: a systematic review[END_REF] , [START_REF] Forno | Asthma and ethnic minorities: socioeconomic status and beyond[END_REF] , [START_REF] Tannenbaum | Survival disparities in non-small cell lung cancer by race, ethnicity, and socioeconomic status[END_REF], little data is available for interstitial lung diseases (ILDs) except for sarcoidosis [START_REF] Harper | Income and Other Contributors to Poor Outcomes in US Sarcoidosis Patients[END_REF]. Idiopathic pulmonary fibrosis (IPF) is one of the most frequent and severe ILDs, with a gradual deterioration of respiratory function, a median survival of 3 to 5 years, and few therapeutic options. Its natural history and physiopathology are yet to be elucidated [START_REF] Lederer | Idiopathic Pulmonary Fibrosis[END_REF]. Although of unknown cause, IPF is believed to be due to repeated alveolar injury on a senescent lung, in response to aerocontaminants, followed by an aberrant repair. Genetic factors are associated to sporadic and family IPF [START_REF] Lederer | Idiopathic Pulmonary Fibrosis[END_REF]. Moreover, several exposures are associated with an increased risk of IPF: tobacco smoke, occupational exposures (wood or metal dust, crystalline silica, agricultural environment/farming activities, asbestos) and air pollution [START_REF] Sack | IDIOPATHIC PULMONARY FIBROSIS: Unmasking Cryptogenic Environmental Factors[END_REF].

Available data on the role of socioeconomic factors are exceedingly rare in IPF. A study conducted in the United States (US) on lung transplant IPF candidates showed an increased mortality in "Black" and "Hispanic" compared to "White" and "Asian" patients, whether or not they were listed, probably because of more disadvantaged SES [START_REF] Lederer | Racial and ethnic disparities in survival in lung transplant candidates with idiopathic pulmonary fibrosis[END_REF]. From a US database of hospitalized patients, Gaffney et al. suggested that IPF patients with lower income or poorer insurance coverage had reduced access to transplantation, rehabilitation and lung biopsy, but no difference in hospital mortality [START_REF] Gaffney | Disparities in pulmonary fibrosis care in the United States: an analysis from the Nationwide Inpatient Sample[END_REF]. However, data from registries have significant limitations, including measurement biases and risk of diagnosis misclassification. Moreover, no such study has been carried out so far in Europe.

We hypothesize that a low SES may have an impact on IPF prognosis. For that purpose, we conducted an ancillary study including patients from a national prospective cohort of incident patients with well-characterized IPF, named COFI ("COhorte FIbrose"), and we used median city incomes from the French National Institute of Statistics and Economic Studies (INSEE). The main objective of the study was to determine the role of income on IPF survival. The secondary objective was to evaluate the relationship between income and IPF severity, occupational exposure and air pollution.

Patients and methods:

For our study we selected patients from COFI, a multicentre prospective cohort involving the 24 respiratory departments from all University Hospitals in France. The enrolment period extended from 2007 to 2010, with a 5-year follow-up. The study was approved by the ethics committee (Comité de Protection des Personnes Ile-de-France) and by the French data protection authority (CNIL: 908198).

COFI study design

Patients were included provided they fulfilled the 2000 ATS/ERS consensus criteria for IPF, which were slightly amended. First, basal and subpleural honeycombing on high resolution computed tomography (HRCT) was required for patients not submitted to surgical lung biopsy (SLB), in keeping with the definition of usual interstitial pneumonia (UIP) pattern of the 2011 [START_REF] Raghu | ATS/ERS/JRS/ALAT Committee on Idiopathic Pulmonary Fibrosis, An official ATS/ERS/JRS/ALAT statement: idiopathic pulmonary fibrosis: evidence-based guidelines for diagnosis and management[END_REF] and 2018 [START_REF] Raghu | Diagnosis of Idiopathic Pulmonary Fibrosis. An Official ATS/ERS/JRS/ALAT Clinical Practice Guideline[END_REF] updated consensus for IPF diagnosis. Second, SLB was mandatory for patients under 50 years of age.

Only incident cases with a diagnosis ≤ 9 months were eligible. IPF diagnosis was prospectively adjudicated for each case by a centralized expert board involving several pulmonologists, a radiologist and a pathologist during monthly multidisciplinary meetings. Data were collected in an electronic Case Report Form (eCRF). At inclusion, demographics, smoking status, clinical information, including history of comorbidities, pulmonary function tests (PFTs), and six-minute walk test (6MWT) were detailed. After inclusion, patients were monitored every 3 months with spirometry, and diffusing capacity for carbon monoxide (DLCO). At each visit, investigators reported every health problem, including hospitalization or acute exacerbation (AE), as defined by Akira et al. [START_REF] Akira | CT findings during phase of accelerated deterioration in patients with idiopathic pulmonary fibrosis[END_REF]. Vital status at 5-year follow-up and the causes of death, when applicable, were recorded. Gender Age Physiology (GAP) staging was based on Ley et al. [START_REF] Ley | A multidimensional index and staging system for idiopathic pulmonary fibrosis[END_REF] and the composite physiologic index (CPI) was calculated according to Wells et al. [START_REF] Wells | Idiopathic pulmonary fibrosis: a composite physiologic index derived from disease extent observed by computed tomography[END_REF]. Three hundred and nine patients were recruited in COFI, 64 of whom were excluded (not UIP pattern on HRCT: n=39, not UIP on SLB: n=2, recognized cause of ILD: n=13, bronchoalveolar lavage (BAL) not available: n=3, BAL lymphocytes > 30%: n=5, and disease duration > 9 months: n=2).

Study population

All patients enlisted in COFI were eligible, provided that their residential address was informed and median city level income was available from the INSEE database. Of the 245 patients included in COFI, 25 patients had no residential address in the database, 11 patients lived in small towns with no available income data for such areas, and 9 patients who withdrew their consent were excluded. In total, 200 patients were selected for the current study (Figure 1).

Socioeconomic status

Since there was no specific socioeconomic data collected in COFI, the income of each patient was estimated using the median city-level income per consumption unit (CU) provided by the INSEE [START_REF] Revenus | pauvreté et niveau de vie en 2014 (IRIS)[END_REF].

For the biggest cities the median income per borough was available. INSEE estimates a city-based median annual income per CU throughout the national territory on the basis of individual tax declaration. Income per CU is a weighting system assigning a coefficient to each member of the household using an equivalence scale (1 CU for the first adult in the household, 0.5 CU for each other person aged 14 years or more, 0.3 CU for each child under 14 years). In France, data are not provided for municipalities with less than 100 inhabitants for reasons of personal data protection and statistical secrecy. In our study, incomes were imputed to patients according to their residential address. We used the latest (2014) available data from INSEE [START_REF] Revenus | pauvreté et niveau de vie en 2014 (IRIS)[END_REF]. The population was divided into two groups depending on city-level incomes: "low income", when values were within the first quartile of the study population, under 18 170€ euros per year versus the remainder in the "higher income" group. Along with INSEE data, we obtained the price per square meter of the patients' residential address from notarial registries (i.e. official sale property prices as registered by the state) [START_REF]La base de données immobilières des notaires de France -statistiques immobilier notaires[END_REF]. Prices from 2018 sales were taken into account as they were the only available.

Environmental exposures

Assuming that SES could have a prognostic impact via higher level of exposures, we looked at occupational exposures and air pollution. Some patients included in COFI cohort had a job exposure assessment by an occupational health physician. The COFI investigators were asked to fill a box in the eCRF regarding patients' exposures to asbestos, crystalline silica, wood, organic, livestock, and metal dust. However, hypersensitivity pneumonitis or pneumoconiosis were excluded by the COFI expert board. As previously described, air pollutant levels obtained from the air quality monitoring station closest to the patient's residential address were assigned to each patient [START_REF] Sesé | Role of atmospheric pollution on the natural history of idiopathic pulmonary fibrosis[END_REF]. Cumulative exposure to each pollutant was expressed as the average concentration of the pollutant during the exposure period, which was defined as the entire period from inclusion to the date of disease progression or the end of the study.

Statistical analysis:

Results are expressed as percentages or mean ± SD. Percentages and means in the "low income" and "higher income" groups were compared using a Chi-squared test and ANOVA, as appropriate. We evaluated the association of income with both overall survival and progression free survival (PFS).

Overall survival was defined as the time from the date of inclusion to death or transplantation. PFS was defined as the time from the date of inclusion to the first occurrence of one of the following events: (i) absolute decrease in forced vital capacity (FVC) > 10% of predicted value (pred) or absolute decrease in DLCO > 15%pred compared to baseline values, after exclusion of other causes of worsening, (ii) AE, (iii) transplantation, or (iv) death. The survival probability of "low income" and "higher income" groups was estimated using the Kaplan-Meier method and compared by a log-rank test. A Cox proportional hazards model was used for studying the survival after adjustment for potential confounders. Key IPF outcome variables known to be strongly associated with IPF mortality in the literature, including age, sex and FVC at inclusion were chosen as adjustment parameters for the Cox model. In order to precise the relative contribution of low income compared to geographical origin and occupational exposure, these parameters were also integrated in the model. Results of the Cox model are reported as hazard ratio (HR) and 95% confidence interval. Data were analysed in R software V3.0.1 and p<0.05 was considered significant.

Results:

Socioeconomic characteristics of IPF patients

Among the 200 IPF patients included, 154 (77%) were men, aged 68±11 years. The SES of IPF patients compared with the general population is presented in Table 1. The distribution of income in our IPF cohort was generally comparable to that in the French population. Conversely, the distribution of IPF patients' geographical ancestry was significantly different, with a low proportion of patients having European origin (77% vs 95%, p<0.001) (Table 1). As expected, the IPF patients' city-level income was strongly correlated to the property square meter price (r=0.7, p<0.001).

Comparison of characteristics at inclusion between "low income" and "higher income" groups

The findings are summarized in Table 2. "Low income" patients were more likely to be from a non-European origin (42% vs 17%, p<0.006), and to live in a cheaper residential area (2 337± 837€.m 2 vs 4 255 ± 3107€/m 2 , p<0.001), whereas no differences were found between groups in terms of age, sex, cigarette smoking, or comorbidities (Table 2). With respect to disease severity, "low income" patients were more dyspnoeic (p=0.049), with a shorter distance on 6MWT at inclusion (74.1 % ± 18.3% vs 81.5% ± 21.8% p= 0.021), whereas functional impairment, GAP stages and CPI were similar between the two groups.

Comparison of outcomes between "low income" and "higher income" groups

The mean duration of follow-up was 33.8 ± 22.7 months. At the end of the study, 6 (3%) patients had been lost to follow-up, 32 (16%) had experienced an AE, 17 (9%) had been transplanted, and 120 (60%) had died. The large majority of deaths resulted from respiratory cause (n=94, 78%), including fibrosis progression (n=33), AE (n=26), pulmonary hypertension (n=5), lung cancer (n=7), pulmonary embolism (n=2), respiratory infection (n=16), and acute respiratory distress syndrome (n=5). The proportion of AE, hospitalization, lung transplantation and deaths were equivalent in both income groups. The median PFS was 15.6 months (CI95%: 13.0-20.4) for the entire cohort. In the "low income" group, the median PFS was significantly worse (11.6 months (CI95%: 6.9-21.1) vs 16.0 months (CI95%: 13.1-23.8), p=0.038). Low incomes remained an independent risk factor of poor PFS after a multivariate analysis adjusted for age, sex and FVC (% predicted) at inclusion, geographical origin and occupational exposure with an HR of 1.81 (CI95%: 1.24-2.62, p=0.001) (Figure 2) (Table 3). Considering survival, the median survival in the "low income" group was lower than "higher income" group, but the difference did not reach the level of significance (22.4 months (CI95%: 19.7-40.2) vs 36.7 months (CI95%: 31.5-42.5, p=0.3). Nevertheless, on multivariate analysis adjusted for age, sex and FVC (% predicted) at inclusion, geographical origin and occupational exposure, low incomes were associated with an increased overall mortality (HR: 1.49; CI95%: 1.0006 -2.23, p=0.049) (Table 3).

Comparison of exposures between "low income" and "higher income" groups

Nineteen patients had a job exposure assessment by an occupational health physician confirming at least one exposure among: asbestos (n=15), crystalline silica (n=1), wood dust (n=5), organic dust (n=1), and metal dust (n=8). In 34 additional patients, one or more exposures were reported by the investigator, yet without being based on a specialized evaluation (asbestos (n=15), silica (n=3), wood dust (n=1), organic dust (n=11), metal dust (n=13), and livestock exposure (n=6)) (Figure 3). Because of the small number of patients, the analyses combined all exposures. Patients in the "low income" group were more likely than those with higher income to have been exposed at least to one occupational pollutant (46% vs 20%, p<0.0001). With regard to the cumulative exposure to air pollution during follow-up, the "low income" group was more frequently exposed to fine particles matter ((PM)2.5), the difference being almost significant (20.4 ± 3.62 vs 19.0±2.26 μg/m 3 , p=0.057).

Discussion:

As far as we know, for the first time in IPF patients our study highlights that low income (i.e. estimated < 18 170€ per year) is related to poorer PFS and overall survival, even after adjusting for other prognostic factors, including age, sex and FVC, geographical origin, and occupational exposure.

In addition, patients having low income are more frequently exposed to toxic inorganic particles in occupational settings and tend to have higher long-term PM2.5 exposure.

Our results in IPF are consistent with the literature. In a recent American epidemiological study, the difference in life expectancy between the richest and poorest people was 14.6 years for men and 10.1 years for women [START_REF]The Association Between Income and Life Expectancy in the United States[END_REF]. Such inequalities are also present across Europe [START_REF]Life expectancy by standard of living: in men, 13 years of difference between the most affluent and the most modest -Insee Première -1687[END_REF] , [START_REF]Socioeconomic Inequalities in Health in 22 European Countries[END_REF]. COPD patients of the lowest socioeconomic stratum are at least twice as likely to have poor outcomes as those of the highest one [START_REF] Gershon | Chronic obstructive pulmonary disease and socioeconomic status: a systematic review[END_REF]. In addition, beyond the effects of current smoking, income disparity is a strong predictor of disease progression in COPD [START_REF] Lowe | Association of low income with pulmonary disease progression in smokers with and without chronic obstructive pulmonary disease[END_REF]. Similarly, a worse survival is observed for patients with lung cancer and low income [START_REF] Finke | Socioeconomic Differences and Lung Cancer Survival-Systematic Review and Meta-Analysis[END_REF]. So far, only few studies have assessed the role of SES in ILDs. Gaffney et al. analysed a database consisting of all hospitalizations from a 20% sample of US hospitals and failed to find any association between insurance status or low income and death.

However, the studied sample only represented hospitalizations, which could bias the results, since disadvantaged patients may be less likely to be admitted to hospitals that offer better quality of care. Moreover, IPF diagnosis was based on ICD-9 coding, with potential misclassification. Last, the model used in-hospital mortality. In our study, we may hypothesize that the effect of low income on overall survival, the most meaningful endpoint in IPF [START_REF] Raghu | Idiopathic Pulmonary Fibrosis: Clinically Meaningful Primary Endpoints in Phase 3 Clinical Trials[END_REF], was not significant probably because of lack of statistical power observed only in multivariate analysis. The impact of income was more pronounced in PFS, which for some authors is a relevant surrogate that takes into account several events related to the IPF natural history [START_REF] Vancheri | A progression-free end-point for idiopathic pulmonary fibrosis trials: lessons from cancer[END_REF].

There are several possible explanations for our findings on the impact of SES on IPF PFS.

First, having low income may inhibit the access to medical care, contributing to disease severity and mortality. There is a large body of evidence in the literature supporting the existence of a negative correlation between SES and lung function in the general population [START_REF] Gray | Explaining the social patterning of lung function in adulthood at different ages: the roles of childhood precursors, health behaviours and environmental factors[END_REF] , [START_REF] Hegewald | Socioeconomic status and lung function[END_REF]. In IPF, Lamas et al.

suggested that delayed access to a tertiary care center was associated with a higher mortality, but surprisingly, this was independent from lung function, education attainment, or insurance coverage [START_REF] Lamas | Delayed Access and Survival in Idiopathic Pulmonary Fibrosis[END_REF]. In the study by Gaffney et al., there was no information on lung function, but hospitalized IPF patients with low SES, Medicaid coverage and without insurance were less likely to receive several clinical interventions, including transplantation. A prospective cohort of sarcoidosis, another fibrotic ILD, showed that low income and other barriers to healthcare access, including the absence of private or Medicare health insurance, were associated with respiratory severity at presentation [START_REF] Rabin | Sarcoidosis: social predictors of severity at presentation[END_REF]. In our study, IPF patients with low income tended to have a more severely impaired lung function, worse dyspnoea and reduced 6MWT distance at inclusion, which may reflect a potential delay in their diagnosis. Conversely, the proportion of transplanted patients was not different according to income.

Second, the levels and types of exposure to air and occupational pollutants are strongly linked to the SES [START_REF] Schraufnagel | An Official American Thoracic Society/European Respiratory Society Policy Statement: Disparities in Respiratory Health[END_REF]. In a previous publication, our group has raised the possibility of an association between mortality and cumulative exposure to PM10 and PM2.5 in IPF [START_REF] Sesé | Role of atmospheric pollution on the natural history of idiopathic pulmonary fibrosis[END_REF]. Similarly, IPF patients exposed at the workplace have a worse prognosis than non-exposed [START_REF] Lee | Association Between Occupational Dust Exposure and Prognosis of Idiopathic Pulmonary Fibrosis[END_REF]. Accordingly, our patients with low income were more frequently exposed to occupational pollutants. They could could also be submitted to higher air pollution levels, with a nearly significant over-exposure to PM2.5.

Third, SES and education are intertwined, and inadequate education about preventive measures regarding health habits, comorbidities or IPF itself (e.g. vaccinations, smoking cessation, control of cardiovascular risk factors) may have promoted disease progression. Yet, even though these indicators were not explored in our study, the causes of death were similar between patients with low or higher income, which does not fully support this hypothesis. The evaluation of SES is complex because it is multidimensional and changes over time, but income has been established to be the best socioeconomic marker of health disparities [START_REF] Schraufnagel | An Official American Thoracic Society/European Respiratory Society Policy Statement: Disparities in Respiratory Health[END_REF]. Given the absence of individual income in COFI, we applied the method of area-based income estimates 8 . We decided to define the first quartile of income as our group of interest, because 18 170€/year (1 514€/month) corresponds approximately to the gross minimum wage in France, which makes our results expressive. As expected, city-level incomes were strongly correlated with real estate sale prices in IPF patients. Moreover, the associations highlighted in our study between level of income, geographical origin and occupational exposure are in line with previous reports on respiratory health status [START_REF] Schraufnagel | An Official American Thoracic Society/European Respiratory Society Policy Statement: Disparities in Respiratory Health[END_REF].

This study has several strengths. It is the first to deal with SES in a well-characterized IPF population of incident cases. COFI is indeed a well-designed prospective cohort, with a long follow-up. Its multicentre nature throughout France ensures a representative sample of IPF population in terms of SES and environmental contexts. The study also has several limitations. First of all, city-based imputations of income are less precise than individual measurements. However, this method has been used and validated in the literature [START_REF] Sahni | Socioeconomic Status and Its Relationship to Chronic Respiratory Disease[END_REF][31] [START_REF] Jolly | Education, Zip Codebased Annualized Household Income, and Health Outcomes in Patients with Systemic Lupus Erythematosus[END_REF]. Patient's health insurance status is an important socioeconomic factor that could not be evaluated in our study. On the other hand, given that the low-income group had worse NYHA and 6MWT at baseline, a lead-time bias in IPF diagnosis between groups may exist. Unfortunately, the time lag between the first symptoms and the diagnosis was not recorded in the cohort database. There was no systematic comprehensive evaluation of patients' occupational exposure, which was left to the investigator's judgement. Some potentially relevant exposures may therefore have been missed. Last, the level of education, another important socioeconomic factor, was not collected in COFI. Patients included in cohorts have often achieved sufficient education to understand an informed consent and accept its terms, leading to potential selection biases.

Conclusion:

As for other chronic respiratory diseases, the income appears to be a prognostic factor of PFS in IPF.

Further studies using individual data on income and a holistic approach including SES, environmental and occupational exposures are required. In order to improve comparability between nations and across different levels of aggregation, a common definition for SES measurement would also be highly fruitful.

Data sharing:

The data are available on request Guarantor statement: LS takes responsibility for the content of the manuscript, including the data and analysis.

Legend of figures

Figure 1 :Figure 2 :Figure 3 :

 123 Figure 1: Study flow chart

Table 1 : Socioeconomic characteristics of the French population and the study population of IPF patients

 1 : provided by the French national institute for statistics and economic studies; †: provided by notarial registries; § : each patient could be exposed to several types of exposure.

	Abbreviations: IPF: idiopathic pulmonary fibrosis; NA : not available.

*

LS reports personal fees and non-financial support from Roche/Genentech, non-financial support from Boehringer Ingelheim, personal fees from Boehringer Ingelheim, non-financial support from Boehringer Ingelheim, outside the submitted work. HN reports grants and personal fees from Roche/Genentech, grants and personal fees from Boehringer Ingelheim, personal fees from Galapagos, other from Sanofi, other from Gilead, other from Novartis, other from Galecto Biotech AB, during the conduct of the study; personal fees from Actelion Pharmaceuticals, outside the submitted work. VC reports personal fees and non-financial support from Actelion, grants, personal fees and non-financial support from Boehringer Ingelheim, personal fees from Bayer / MSD, personal fees from Novartis, Astra Zeneca, grants, personal fees and nonfinancial support from Boehringer Ingelheim, personal fees and non-financial support from BMS, personal fees from Sanofi, grants, personal fees and non-financial support from Roche, outside the submitted work AT reports personal fees from Chiesi, other from VitAlaire, other from Astrazeneca, other from Boehringer Ingelheim, outside the submitted work. SM-A. reports other from roche, other from Boehringer Ingelheim, outside the submitted work. SH reports personal fees from Roche, personal fees from Boerhinger ingelheim, grants from CSL Behring, outside the submitted work. SD reports personal fees from Boehringer-Ingelheim, Chiesi, personal fees from AstraZeneca, other from Stallergene, outside the submitted work. RB reports grants and personal fees from Roche, grants and personal fees from Boerhinger Ingelheim, personal fees from Savara, outside the submitted work.; DV reports personal fees from Roche, personal fees from Boehringer Ingelheim, personal fees from Roche & BI, outside the submitted work;

Funding: Chancellerie des Universités de Paris (Legs Poix, grant # 637), PHRC (grant # AOR 07076), and the Medical Research Foundation

Author contributions: DV was the scientific leader of the COFI cohort. All authors and COFI collaborators contributed to the data collection. HN conceived and planned the study. LS performed the statistical analyses. LS, HN, DV, CC, IAM wrote the manuscript. All authors read the manuscript,