CDCB Communicable Disease Control Branch of South Australia
CI Confidence interval
DALY Disability adjusted life year
MH Mantel-Haenszel
OR Odds ratio
PAF Population attributable fraction
PPF Population preventative fraction
SA South Australia
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Prologue
My Role
During the design of the case control study I was responsible for liaising with Biosecurity SA, the Food and Controlled Drugs Branch in the Department of Health and Ageing, and with the following Communicable Disease Control Branch stakeholders:
Disease Surveillance and Investigation Section OzFoodNet
I was responsible for leading all aspects of the project and my roles included:
Preparing a research proposal and developing the epidemiological study design. Developing a case control questionnaire using the online tool Survey Monkey. Preparing the ethics submission and assisting to advocate for the study with the SA
Health and Australian National University, Human Research Ethics Committees. Data collection (conducting questionnaires via the telephone).
Data extraction, cleaning and analysis using Stata version 13. Interpretation of findings.
Lessons Learned
This was a challenging project taking commitment to complete during the narrow window of time provided by the Masters of Philosophy in Applied Epidemiology program.
Increasing cases of Salmonella Typhimurium phage type 9 (STM 9) in South Australia (SA) are a concern to the Communicable Disease Control Branch. Developing a study design to identify exposures contributing to the increase was a significant challenge. One of the challenges was balancing the need to include a comprehensive list of potential risk exposures with the need to have a manageable questionnaire. Through talking with stakeholders the need to ask about normal behaviours when handling food was identified as important and the approach to these questions needed to be different to questions about food exposures over a seven day period. Thinking through these issues was
challenging and through the implementation of the study issues such as these highlighted to me some of the limitations of case-control study designs, particularly when trying to measure something as complicated and diverse as human behaviours.
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I learnt that identifying an accessible control group with minimal bias required thought and care. This was my first experience preparing an ethics submission and taught me how to prepare a detailed submission targeted at a lay audience. The experience exposed me to the commitment required to initiate research projects. The process of the ethics
submission took four months to complete and much time was spent writing letters of response and justifying our methods and proposal. This process also helped me become more familiar with the South Australian Public Health Act 2011.
During the project I developed interview techniques for conducting questionnaires and providing public health information to participants (members of the public) via telephone. I spoke with over 400 people while enrolling participants in the study and conducted more than 300 interviews.I learnt how time consuming it can be to undertake a case control study as the process of contacting potential participants for their consent and to enrol them in a study was lengthy due to some people not wanting to participate or not meeting eligibility criteria. I also learnt the value of providing opportunities for people to participate at a variety of different times throughout the day, including after hours, as many people were not available at any other time. The experience helped me develop strategies to communicate medical information with members of the public in a language that was clear and logical.
Public Health Impact
During the study, approximately 600 cases and controls were contacted. Cases were provided with information on Salmonella and safe food and egg handling, potentially minimizing risks of future Salmonella infections. As controls were sourced from previously notified influenza cases they were provided with information on influenza and influenza vaccination to encourage them to minimize exposure and infection with influenza in the future.
An interim analysis was conducted as the study required 382 participants and at the time of writing the thesis, 322 participants had completed interviews. The interim analysis
identified a number of significant findings that could provide avenues for further investigation, potentially reducing STM 9 infections in the future.
Ethics
Permission was granted to conduct this project by the SA Health and ANU Human Research Ethics Committees.
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Master of Philosophy in Applied Epidemiology Requirements
This chapter addressed the core competency of designing and conducting an epidemiological study for the Master of Philosophy in Applied Epidemiology.
Acknowledgements
I would like to thank the following people for their assistance and contributions in this project:
Dr Megge Miller and Dr Jane Raupach, field supervisors Dr Emily Fearnley, academic supervisor
Emma Denehy, Manger, Disease Surveillance and Investigation Section (DSIS) Rebecca Beazley, Caitlin Graham, Cheryl Holland, Jacqueline Stephens, Hannah
Vogt, Jodie Halliday, Ann Weaver and Ingrid Tribe DSIS staff
Glen Martin and Alessia Centofanti, Food and Controlled Drugs Branch Margaret Sexton, Biosecurity SA
Barry Combs, OzFoodNet, Western Australia
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Abstract
Background
Notifications of Salmonella Typhimurium phage type 9 have been increasing in South Australia between 2005 and 2014. During this time, eggs and dishes containing raw eggs have been identified as the source of numerous outbreaks of Salmonella Typhimurium phage type 9 in South Australia. However, the majority of infections are sporadic and there is limited evidence to link eggs or other high risk exposures with sporadic cases. We
conducted a case control study that aimed to address this gap, identifying exposure risks for sporadic cases of Salmonella Typhimurium phage type 9 in South Australia.
Methods
Sporadic cases of Salmonella Typhimurium phage type 9 notified in South Australia after 21 January 2015 were questioned regarding food, environmental and behavioural exposures in the seven days prior to the onset of illness. Controls were frequency matched by age category and randomly selected from influenza cases notified in South Australia in 2014. Controls were asked to recall the same food, environmental and behavioural exposures in the seven day period prior to the date of interview.
Responses were collected using the online tool Survey Monkey and analysed using Stata version 13. A univariate analysis calculated age group adjusted odds ratios (OR) for all exposures. Exposures with an adjusted p value less than 0.1 were selected for inclusion in a full logistic regression model. A reduced logistic model was built including remaining exposures with an adjusted p value less than 0.05 or that were found to be contributing to the model with a likelihood ratio test p value less than 0.05. The reduced model was assessed for goodness of fit and discrimination. All variables remaining with p values less than 0.05 and 95% confidence intervals (CI) not including one were reported as significant findings. The population attributable fraction or population preventative fraction was calculated for remaining significant variables.
Results
The results presented are based on interim analysis of the case control study that includes 332 (166 cases and 166 controls) of the anticipated 372 participants.
The univariate analysis identified 22 exposures with an adjusted p value less than 0.1 for inclusion in the full logistic regression model, which was adjusted by age group, gender and
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residential location. Four exposures remained significant after running the full model, defrosting meat submerged in water, eating beef sausages, eating caged eggs and eating out at a bakery. A further 13 exposures were found to be significantly contributing to the model and included in the reduced model. The reduced model was also adjusted for age group and location. The reduced model was found to have a good fit and discrimination and the following four variables all remained significant:
Defrosting meat submerged in water, OR= 3 (95% CI 1.3 – 7.1, p = 0.01), Population attributable fraction (PAF) 9%
Eating beef sausages OR= 0.26 (95% CI 0.1 – 0.5, p < 0.01), Population preventative fraction (PPF) 15%
Eating eggs from caged hens OR= 0.29 (95% CI 0.1 – 0.8, p = 0.01), PPF 8% Eating out at a bakery= OR 0.27 (95% CI 0.1 – 0.5, p < 0.01), PPF 18%
Conclusions
The interim analysis identified defrosting meat submerged in water as a risk and eating caged eggs as protective for Salmonella Typhimurium phage type 9 infections in South Australia. However, these findings only explain a small portion of cases in the study population and other risk exposures have not been captured by the study. The inverse associations found with eating beef sausages and eating out at a bakery are potentially an indication of different dietary preferences of controls or could have been due to recall bias. Future investigations may need to consider using different study designs to better capture the complex nature of exposure to eggs and behavioural food handling risks within the home.
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Introduction
In South Australia (SA) over the last ten years to 2014, there has been a notable increase in
Salmonella Typhimurium phage type 9 (STM 9) notifications (1). In 2014, there were 1210 notifications of Salmonella in SA of which 709 were further classified as STM (59%) and a further 365 (30%) were further classified as STM 9, making it the most common subtype of
Salmonella infection (1, 2). STM 9 infections now represent more than a quarter of the burden of illness related to salmonellosis in SA. Nationally, the salmonellosis disease burden is estimated at 3856 disability adjusted life years (DALYs), ranking it second for all causes of gastrointestinal illness behind Campylobacter (18 222 DALYs). However, in terms of DALYs per 1000 cases, salmonellosis ranks highest with 54.1 DALYs per 1000 cases, as it is estimated to cause more fatalities than Campylobacter (3).
Despite salmonellosis being a notifiable infection in SA, the current disease surveillance system is not capable of capturing information to accurately define detailed exposures and potentially identify causes for the increased cases. In SA, most information on risk factors for salmonellosis is collected during outbreak investigations. Between 2005 and 2014 in SA STM 9 has been described as the aetiological agent in 29 outbreaks of gastroenteritis. Eggs or products containing raw eggs have been the most common source identified in these outbreak investigations (7/29, 24%) (1). However, outbreak related cases of STM 9 account for only 20% of cases, with the remainder being classified as sporadic (1, 4).
Until recently there has been no published literature on the risk factors for sporadic cases of STM 9 infection or more generally for sporadic salmonellosis in SA. In 2015 a paper was published in the journal Risk Analysis that used Bayesian source attribution methods to identify eggs as the major contributor of sporadic STM 9 cases in SA between 2000 and 2010 (4). Outside of this, there are no published reports addressing risk factors for sporadic STM 9 infections nationally or internationally. In Australia there have been a number of case control studies to identify risk factors for sporadic cases of other serotypes of
Salmonella (Birkenhead and Mississippi) (5, 6). These studies have been conducted to investigate unusually high numbers of the particular serotype in the state or jurisdiction. The Salmonella Birkenhead study identified eating from a fast food chicken chain, not peeling or washing fruit and vegetables and consumption of home cooked food as risk factors (5). The Salmonella Mississippi study identified indirect contact with native birds, consuming untreated drinking water and intrastate travel as risk factors (6). There have been a number of international studies investigating risk factors for sporadic salmonellosis.
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A meta-analysis of case control studies between 1989 and 2003 in 11 different countries (including the two Australian studies discussed above) identified international travel, undercooked eggs and eating chicken at a restaurant as significant risk factors for sporadic salmonellosis (7). The majority of studies conducted use case control methods and report a variety of findings. In Germany, raw ground pork, outdoor barbeques, foreign travel and gastric acidity inhibitors, were found to be risk factors for sporadic salmonellosis (8). Most studies address a specific Salmonella serotype which is of interest in the study area. In Israel exposures to breast feeding, consumption of carrots, drinking tap water, religious lifestyle and a large number of children in the household were identified as protective factors and consumption of eggs and thawing chicken in water were risk factors for
Salmonella Infantis (9). A Canadian study investigated Salmonella Enteritidis and identified poultry meat, processed chicken and not washing hands after handling raw eggs to be risk factors (9). In the United States of America eating eggs prepared outside the home was identified as a risk factor for Salmonella Heidelberg (10).
Our case control study investigated sporadic cases of STM 9 in SA, to address a knowledge gap regarding risk factors for sporadic STM 9 infections. The study intended to inform interventions for stakeholders including environmental health, the food industry and health promotion professionals, to minimize future STM 9 cases. It is anticipated that the study findings will help contribute to reducing the burden of illness caused by STM 9 infection in SA.