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Objective: Despite the usefulness of quantitative research, qualitative research methodologies are equally needed to allow researchers to better understand the important social and environmental factors affecting food choice and eating habits. The present paper contributes insights from narrative inquiry, a well-established qualitative methodology, to a food-related doctoral research study. The connections between food shoppers and the producer, family, friends and others in the food system, between eaters and the earth, and how these connections affect people's meaning-making of food and pathways to food citizenship, were explored in the research.Design: The research used narrative inquiry methodology and focus groups for data collection.Setting: Five different food-ways in the Canberra region of Australia were selected for the present research; that is, community gardens, community-supported agriculture, farmers' markets, fresh food markets and supermarkets.Subjects: Fifty-two people voluntarily attended eight focus groups with four to nine participants in each.Results: From a practical perspective, the present paper offers a guide to the way in which narrative inquiry has been applied to one research project. The paper describes the application of narrative inquiry methodology, revealing the important place of narratives in generating new knowledge. The paper further outlines how phased narrative analysis can lead to a defensible and rigorous interpretive framework grounded in the data generated from people's stories and meaning-making.Conclusions: We argue that individual, social and system change will not be possible without further rigorous qualitative studies to inform and complement the empirical basis of public health nutrition practice. [ABSTRACT FROM AUTHOR]

Understanding how seasonal patterns change from year to year is important for the management of infectious disease epidemics. Here, we present a mathematical formalization of the application of complex demodulation, which has previously only been applied in an exploratory manner in the context of infectious diseases. This method extracts the changing amplitude and phase from seasonal data, allowing comparisons between the size and timing of yearly epidemics. We first validate the method using synthetic data that displays the key features of epidemic data. In particular, we analyse both annual and biennial synthetic data, and explore the effect of delayed epidemics on the extracted amplitude and phase. We then demonstrate the usefulness of complex demodulation using national notification data for influenza in Australia. This method clearly highlights the higher number of notifications and the early peak of the influenza pandemic in 2009. We also identify that epidemics that peaked later than usual generally followed larger epidemics and involved fewer overall notifications. Our analysis establishes a role for complex demodulation in the study of seasonal epidemiological events. [ABSTRACT FROM AUTHOR]