a Centre for Digestive Diseases, The General Infirmary at Leeds, Leeds, UK.
b Paediatric Epidemiology Group, University of Leeds, Leeds, UK.
c Northern and Yorkshire Clinical Trials and Research Unit, University of Leeds, Leeds, UK.
d The Department of Public Health and Epidemiology, University of Birmingham, Birmingham, UK.
e Institute of Epidemiology and Health Services Research, University of Leeds, Leeds, UK.
f Department of General Practice, Wellington School of Medicine, New Zealand.
g Cancer Epidemiology Group, Epidemiology and Health Services Research Unit, University of Leeds, Leeds, UK.
Paul Moayyedi, The General Infirmary at Leeds, Great George Street, Leeds LS1 3EX, UK. E-mail: paulmo{at}ulth.northy.nhs.uk
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Abstract |
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Methods Subjects between aged 4049 years were randomly invited to attend their local primary care centre. Participants were interviewed by a researcher on smoking, coffee and alcohol intake, history of living with a partner, present and childhood socioeconomic conditions. Helicobacter pylori status was determined by 13C-urea breath test.
Results In all, 32 929 subjects were invited, 8429 (26%) were eligible and 2327 (27.6%) were H. pylori positive. Helicobacter pylori infection was more common in men and this association remained after controlling for childhood and adult risk factors in a logistic regression model (odds ratio [OR] = 1.15; 95% CI: 1.031.29). Living with a partner was also an independent risk factor for infection (OR = 1.30; 95% CI: 1.011.67), particularly in partners of lower social class (social class IV and VOR = 1.47; 95% CI: 1.191.81, compared with social class I and II). Helicobacter pylori infection was more common in lower social class groups (I and II22% infected, III29% infected, IV and V38% infected) and there was a significant increase in risk of infection in manual workers compared with non-manual workers after controlling for other risk factors (OR = 1.18; 95% CI: 1.031.34). Alcohol and coffee intake were not independent risk factors for infection and smoking was only a risk factor in those smoking >35 cigarettes a day.
Conclusions Male gender, living with a partner and poor adult socioeconomic conditions are associated with increased risk of H. pylori infection.
Keywords Helicobacter pylori, gender, socioeconomic status
Accepted 8 October 2001
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Introduction |
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The same strain of H. pylori has been isolated from husband and wife, raising the possibility of intrafamilial transmission between spouses.9 Epidemiological studies have not definitively confirmed living with a partner as a factor associated with prevalence for infection but most studies have been under-powered or have not adequately controlled for confounding factors.10,11 The relationship between lifestyle factors and H. pylori infection is also uncertain. Smoking has been reported as a factor associated with H. pylori prevalence12 but this has not been a universal finding.13,14 A recent study suggested alcohol protected against infection while coffee had the opposite effect,14 but results have been inconsistent.6,13 Again the reasons for these discrepancies may relate to the sample size and failure to control adequately for confounding variables.
We investigated the relationship between H. pylori infection, adult socioeconomic status, adult household crowding, marital status and lifestyle in a large cross-sectional study that controlled for childhood factors associated with prevalence.
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Methods |
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A trained research nurse interviewed eligible participants about past and present living conditions using a standard questionnaire. Household crowding at the age of 8 years and at present, was expressed as occupants/room (excluding bathroom and kitchen if less than 6 ft x 6 ft). Childhood socioeconomic conditions were recorded at the age of 8 years as this has been described by other workers.3 Social class was based on present occupation according to published guidelines.15 Tables 1 and 2 outline other questions asked in this survey. We also enquired about pet ownership but the details of this are not presented here. Informed written consent was obtained from all participants and the relevant local research ethics committees approved the study.
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Statistical analysis
Odds ratios (OR) for the unadjusted data were calculated using EpiInfo version 5.01 (Center for Disease Control, Atlanta, GA, US). All data (apart from pet ownership) were then incorporated into an unconditional logistic regression model to determine independent predictors of H. pylori infection. The categories were predefined before data collection apart from the groupings for number of siblings and household crowding. These were categorized retrospectively in a manner that avoided small numbers in any stratum. Calculations were performed using the SPSS statistical package version 7.0 (US).
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Results |
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Representativeness of the sample
The social class distribution of subjects participating in this survey was compared with the 1991 Census data for West Yorkshire. This suggested that there were differences between participants and the general population, particularly with an over-representation of social class III non-manual and an under-representation of social class III manual in the study (Figure 1).
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General factors associated with H. pylori infection
Infected subjects were marginally older than uninfected subjects (mean age of H. pylori positive cases = 45.4 ± standard deviation of 2.9 years, H. pylori negative cases = 45.2 ± 2.9 years P = 0.004) and infection was more common in non-Caucasians (Table 1). Helicobacter pylori infection was also more prevalent in men than women (29% versus 26%). This remained statistically significant after controlling for confounding factors (Table 1
).
Childhood factors associated with prevalence of H. pylori infection
Current H. pylori infection was associated with the following childhood variables in the unadjusted analysis: type of house, presence of bathroom, number of siblings, sharing a bedroom with a sibling, sharing a bed with a sibling, sharing a bed with a parent, household crowding and head of household social class (Table 1). All variables in Tables 1 and 2
were included in a multivariate model with prevalence of H. pylori as the dependent variable. Type of accommodation, sharing a bed with a sibling and number of siblings (OR = 1.16 per extra sibling, 95% CI: 1.131.20) remained strongly associated with prevalence of H. pylori. Childhood social class and household crowding (OR = 1.14 per extra occupant per room, 95% CI: 0.991.31) also remained associated with H. pylori infection (Table 1
).
Adult socioeconomic status and prevalence of H. pylori infection
The prevalence of H. pylori infection had a statistically significant association with present social class (Table 2) in an unadjusted analysis. Present social class is correlated with childhood social class (Pearson's correlation coefficient = 0.22, P < 0.0001) and the unadjusted results of present social class could be confounded by childhood socioeconomic conditions. However, the prevalence of H. pylori infection increased with decreasing social class even within levels of childhood social class (Table 3
).
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Marital status and prevalence of H. pylori infection
Subjects that had lived with a partner were more likely to be infected with H. pylori (lived with partner 2179/778628.0% infected, never lived with partner 120/50223.9% infected, P = 0.048 2). Prevalence of infection did not increase with increasing time spent with a partner (<10 years30% infected, 1020 years27% infected, >20 years28% infected, P = 0.79
2). Marital status remained independently associated with H. pylori infection in a logistic regression model controlling for factors outlined in Tables 1 and 2
with partners' social class omitted (OR = 1.30, 95% CI: 1.011.67, for subjects ever had a partner compared with never had a partner).
Lifestyle factors and prevalence of H. pylori infection
Smoking was associated with increased prevalence of H. pylori infection in both univariate and multivariate analysis (Table 2). The proportion of subjects infected increased with increasing numbers of cigarettes smoked (Table 4
) but when adjusted for childhood and adult socioeconomic status the 95% CI for the OR did not include unity only in those that smoked >35 cigarettes/day.
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The proportion of subjects infected with H. pylori was lower in those that drank coffee but this relationship was of borderline statistical significance in the multivariate model (Table 2). There was no clear dose response between the amount of coffee drunk and prevalence of H. pylori infection when adjusted for the childhood and adult factors associated with prevalence (Table 4
).
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Discussion |
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We have confirmed that childhood socioeconomic deprivation and overcrowding are important determinants of the prevalence of H. pylori infection as others have shown.4,5,19 Number of siblings was a strong predictor of infection suggesting that transmission between siblings is an important mode of acquisition. This is consistent with the observation that individuals of higher birth order have an increased prevalence of H. pylori, particularly if the age gap between sibs is small.20,21
The influence of adult socioeconomic factors on prevalence of infection has been less well characterized.4,22 Our survey suggests that some markers of adult socioeconomic status are independent factors associated with prevalences for infection supporting the hypothesis that either H. pylori can be acquired in adult life or that adult socioeconomic factors contribute to the persistence of infection. Odds ratios for adult socioeconomic variables were generally not as high as for childhood factors suggesting that the latter remain more important determinants of infection status.
Data from previous studies suggested an increased prevalence of H. pylori infection in men compared with women but it frequently did not reach statistical significance.23 A meta-analysis indicated that male gender was a factor associated with prevalence for infection but the authors acknowledged that the study was limited by the unavailability of primary data from some studies, making it difficult to control for confounding variables.24 This large study suggests that the odds of being H. pylori positive increase by 15% in middle-aged males. The reason for the possible gender difference in H. pylori prevalence is unclear but may relate to young boys having poorer hygiene than young girls.25
Studies investigating transmission of H. pylori within households have often assessed prevalence of H. pylori in spouses of infected and uninfected index cases.10,11 These case-control studies have given conflicting results due to possible bias in the patient groups selected and the lack of adjustment for confounding factors. This cross-sectional survey avoids some of these problems and has identified living with a partner as a factor associated with prevalence for H. pylori infection. The odds of infection for cohabiting are relatively small but the plausibility of this finding is strengthened by the observation that prevalence of infection increases in subjects with lower social class partners.
The influence of lifestyle on prevalence of H. pylori infection remains controversial. In our study smokers were more likely to have H. pylori infection than non-smokers but when adjusted for confounding factors this association was only observed in those smoking >35 cigarettes/day. Smaller cross-sectional surveys have reported an association between smoking and H. pylori prevalence12,26 but these may not have adequately controlled for confounding factors.
Several studies have investigated the association between H. pylori and alcohol or coffee intake with conflicting results.6,13,14,26 The mechanisms that would promote an association between coffee or alcohol intake are unclear and this hypothesis is not supported by our data. We cannot, however, formally exclude the possibility that participants may have altered their lifestyle in middle age and this has masked an earlier association between H. pylori and alcohol.
A weakness of the study is that only 26% of the invited subjects were evaluated for H. pylori status. It is, however, extremely rare for individuals to know their H. pylori status and so there is unlikely to be any systematic bias that would threaten the internal validity of our results. The study participants may, however, not be representative and indeed there were differences between this group and the general population in terms of social class distribution and frequency of consultation for dyspepsia. Our results concerning the estimated levels of infection prevalence may not, therefore, apply to the general population but this should not be the case for our estimates of relative risk for the identified variables.
KEY MESSAGES
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Appendix |
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Clinical co-ordinator
: Dr P Moayyedi, Senior Lecturer in Gastroenterology, Centre for Digestive Diseases, The General Infirmary at Leeds, Great George Street, Leeds LS1 3EX, UK.
Data management and trial co-ordinators
: Dr S Mason, Joint Operations Director, Northern and Yorkshire Clinical Trials and Research Unit, University of Leeds, Hospital Lane, Leeds LS16 6QB, UK. Mr W Crocombe, Senior Trial Co-ordinator, Mrs R Muthukumar, Assistant Trial Co-ordinator, Miss J Norton, Assistant Trial Co-ordinatorNorthern and Yorkshire Clinical Trials and Research Unit, University of Leeds, Hospital Lane, Leeds LS16 6QB, UK.
Data collection
: Mrs S Duffett, Research Sister. Mrs P Atha, Research Nurse, Mrs M Liptrott, Research Nurse, Mrs J Nathan, Research Nurse, Mrs C Youings, Research Nurse, Mrs R Hall, Research Nurse, Mrs J Greatrex, Research Nurse, Mrs J Hammacott, Research Nurse, Miss A Zilles, Research Nurse, Mrs J Welsby, Research Nurse, Miss C Walton, Research NurseInstitute of Epidemiology and Health Services Research, 30 Hyde Terrace, University of Leeds, Leeds LS2 9LN, UK.
Statistical support
: Dr D Braunholtz, Senior Statistician, The Department of Public Health and Epidemiology, University of Birmingham, Birmingham B15 2TT, UK. Mrs J Brown, Chief Medical Statistician, Northern and Yorkshire Clinical Trials and Research Unit, University of Leeds, Hospital Lane, Leeds LS16 6QB, UK. Dr P McKinney, Senior Research Fellow, Paediatric Epidemiology Group, 30 Hyde Terrace, University of Leeds, Leeds LS2 9LN, UK. Mr R Feltbower, Statistician, Paediatric Epidemiology Group, 30 Hyde Terrace, University of Leeds, Leeds LS2 9LN, UK. Dr S Eriksson, ASTRA Hassle AB, S-431 83, Molndal, Sweden.
Health economic support
: Prof. M Drummond, Director, Dr J Mason, Senior Research FellowCentre for Health Economics, University of York, Heslington, York YO1 5DD, UK. Dr N-O Stalhammar, ASTRA Hassle AB, S-431 83, Molndal, Sweden.
Data monitoring committee
: Dr R Spiller, Reader in Gastroenterology, Queens Medical Centre, Nottingham, UK. Dr M Jones, Senior Statistician, ICRF, St James' and Seacroft University Hospitals, Beckett Street, Leeds LS9 7TF, UK. Prof. D Forman, Professor of Cancer Epidemiology, Centre for Cancer Research, University of Leeds, Arthington House, Cookridge Hospital, Leeds LS16 6QB, UK.
13C-UBT analysis
: Mr M Clough, MLSO, Centre for Digestive Diseases, The General Infirmary at Leeds, Great George Street, Leeds LS1 3EX, UK.
Trial pharmacist
: Ms C Bedford, Out-patient pharmacy manager, Out-patient pharmacy, The General Infirmary at Leeds, Great George Street, Leeds LS1 3EX, UK.
Financial administration
: Mrs A Starkey, Research School of Medicine, 24 Hyde Terrace, University of Leeds, Leeds LS2 9LN, UK.
Participating general practices
: Meanwood Health Centre, 548 Meanwood Road, Leeds; Kippax Health Centre, Gibson Lane, Kippax, Leeds; The Croft Surgery, Town Street, Horsforth, Leeds; Windsor House Surgery, Corporation Street, Morley, Leeds; Woodsley Health Centre, Woodsley Road, Leeds; Bridge Street Surgery, 3 Bridge Street, Otley; Marsh Street Surgery, 25a Marsh Street, Rothwell, Leeds; High Field Surgery, Holtdale Approach, Leeds; Lingwell Croft Surgery, Ring Road, Middleton, Leeds; Beeston Hill Health Centre, 134 Beeston Road, Leeds; Woodhouse Medical Centre, Woodhouse Street, Leeds; Leigh View Medical Practice, Bradford Road, Tingley, Wakefield; Fountain Medical Centre, Corporation Street, Morley, Leeds; Dib Lane Practice, 112A Dib Lane, Leeds; Hunslet Health Centre, 24 Church Street, Leeds; Grange Medical Centre, Seacroft Crescent, Leeds; Crossland Surgery, 218A Dewsbury Road, Leeds; St. Martin's Practice, 319 Chapeltown Road, Leeds; Robin Lane Medical Centre, Robin Lane, Pudsey, Leeds; Manor Park Surgery, Bellmount Close, Bramley, Leeds; Carlton Surgery, 27 Carlton Gardens, Leeds; Burton Croft Surgery, 5 Burton Crescent, Headingley, Leeds; Ridge Medical Practice, 3 Paternoster Lane, Great Horton, Bradford; West Lodge Surgery, New Street, Farsley, Leeds; Windmill Health Centre, Mill Green View, Leeds; Yeadon Health Centre, 17 South View Road, Yeadon, Leeds; The Medical Centre, 30 Buttershaw Lane, Bradford; Garforth Medical Centre, Church Lane, Leeds; The Chapeloak Practice, 347 Oakwood Lane, Leeds; The Health Centre, King;'s Road, Wrose, Bradford; Burley Park Medical Centre, 273 Burley Road, Leeds; The Street Lane Practice, 12 Devonshire Avenue, Leeds; Silver Lane Surgery, 1 Suffolk Court, Yeadon, Leeds; New Wortley Health Centre, 15 Green Lane, Leeds; Cullingworth Medical Centre, 12 Mill Street, Cullingworth, Bradford; Westcliffe Medical Centre, Westcliffe Road, Shipley, Bradford.
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Acknowledgments |
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