Paris and Milan

Sociodemographic characteristics and other lifestyle factors are known to influence diet and health (269, 299, 335, 368). Those investigated in this thesis include age, relationship status, urban-rural location, education, employment status, physical activity, smoking status and BMI.

Age

The age range of this study is from 55 years to 65 years. This is a life-stage in transition where people at the lower ages (possibly pre-retirement) may have very different requirements than those at the upper ages (possibly post

retirement). In the baseline questionnaire, participants’ were asked their date of birth which was used to calculate their age at survey. Each subsequent

questionnaire (2012 and 2014) obtained date of birth information and age calculations were duly computed. Age was considered as a confounder variable due to its associations with QoL, dietary intake and potential determinants of dietary behaviours.

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Relationship status

Relationship status was considered since it has shown to be an important

determinant of dietary intake (241). It was measured using the question: “Which of the following best describes your current relationship status?” Response options were “living in a registered marriage”, “living in a de facto relationship”,

“separated”, “divorced”, “widowed”, and “never married”. These responses were subsequently collapsed into three categories: married-living together, separated-divorced-widowed, and never married. Married and living together are closely linked; given people in de facto relationships have legal rights akin to those who are married, the combination of the two are a natural pairing.

Separated-divorced-widowed have been combined on the basis that individually, these groups had a common factor in that previously they had lived with

another. This may be pertinent in this age group as there is evidence that shows a division in gender roles including women taking on a greater burden of

domestic chores, including food shopping and food preparation. Where the woman as the food provider is no longer present through either the breakdown of a relationship or death, it may affect the remaining spouse in his ability to provide nourishing meals. Those participants that were never married were considered as a separate category. Although we cannot know with an absolute degree of certainty, it was assumed those individuals had been caring for

themselves throughout their lives, and therefore had at least a basic level of food skills.

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Urban-rural location

The location of where one lives has been shown to influence health outcomes (369-371). The urban-rural classification is described in detail in Chapter 3. In all analyses in this thesis, urban was treated as the reference category.

Education

Educational attainment is a useful tool in determining socioeconomic advantage and disadvantage (372). Participants were asked: “What is the highest

qualification you have completed?” Responses options were: “no formal qualifications”, “year 10 or equivalent”, “year 12 or equivalent”, “trade-apprenticeship”, “certificate-diploma”, “university degree”, “higher university degree”. These options were collapsed into “up to and including year 10”, “year 12-trade-diploma”, and “university degree and higher”.

Employment status

As a group of adults aged 55 to 65 years, the working status of the WELL study cohort is an important factor to be considered. Considering the age group of WELL study participants, it is likely they are approaching retirement or may have already retired. As discussed previously, retirement is an important lifestyle transition, and therefore this is a period that may affect health outcomes.

Participants were asked “Which of the following best describes your current main daily activities and/or responsibilities”. Response options were: “working full-time”, “working part-time”, “unemployed or laid off”, “keeping house and/or raising children full-time”, “studying full-time”, “retired”. For the purposes of this thesis, categories were grouped into the following: “working full-time”, “working

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part-time” “unemployed, keeping house/raising children time, studying full-time” and “retired” (373, 374).

Physical activity

Studies have shown physical activity (PA) to benefit health outcomes, particularly those in mid to late adulthood (183, 375). Physical activity can include any

activity within the home, work, active transport or gained through leisure

pursuits. It has been shown that leisure-time PA better predicts self-rated health than work related PA (376), therefore leisure-time PA only has been used in this thesis. Leisure-time PA was measured using the International Physical Activity Questionnaire (IPAQ). Participants were asked about activities they did in the last seven days. Questions included: “Not counting any walking you have already mentioned, during the last seven days, on how many days did you walk for at least 10 minutes at a time in your leisure time?” Response options were open ended with “days per week” or “not at all in the last week”. Participants were then asked “How much time did you usually spend on one of those days walking in your leisure time?” The response was open ended and participants were asked to report in hours and minutes per day. Further questions asked “vigorous” and

“moderate” leisure-time PA. Response options were the same as those listed above. A final question relating to muscle strength was asked: “During the last seven days, did you do any activities designed to increase muscle strength or tone, such as lifting weights, pull-ups, push-ups, or sit-ups?” Response options were “yes”, “no”, “don’t know”. Leisure-time PA was then converted to

metabolic equivalent of task (MET) hours, using methods recommended in the

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IPAQ protocol. The reliability and validity of the IPAQ instrument has been assessed in a 12-country study (377). Four short questionnaires (9 items) and four long questionnaires (31 items) were developed from the IPAQ instrument.

These were then either self-administered by participants or telephone interviews were conducted in fourteen locations from 12 countries. Data were collected on at least two of the eight instruments within one week. Repeatability was

evaluated, and the instrument found to be satisfactory for the measurement of physical activity at the population level (377).

Smoking status

Cigarette smoking is a well-documented behaviour that affects health outcomes (378-380). Smoking status was self-reported, and in response to the question

“Which of the following best describes your current smoking status?” Response options were: “I have never smoked”, “I used to smoke”, “I now smoke

occasionally”, and “I now smoke regularly”. These responses were collapsed into

“never smoked”, “used to smoke” and “smoker” for all studies in this thesis.

Body mass index

Body mass index is a well-known instrument used to measure healthy or

unhealthy body weight (381-383). Body mass index, classified as weight/height², was calculated and categorized into under-, normal-, over-weight and obese groups. The underweight and normal weight categories were collapsed due to the small numbers in the underweight category.

Although considered an important aspect of health, alcohol consumption was not controlled for in this analysis. Historically, people underestimate alcohol

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consumption when they complete questionnaires (384). In addition, the FFQ used in this analysis did not enquire into the amount of alcohol consumed, only frequency of alcohol consumption events. A study comparing a FFQ and

quantity-frequency questionnaire showed the FFQ to be less robust in identifying risky alcohol consumption in participants (385). The alcohol information gained from the current FFQ did not provide necessary information and therefore it was decided to not include alcohol in the models.