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    Family upbringing has no impact on adolescents’ food preferences

    By Alison Fildes, on 11 July 2016

    Written by Andrea Smith, Alison Fildes and Clare Llewellyn

    Understanding the factors behind food likes and dislikes has important implications for politicians and clinicians. Our food preferences strongly influence what we chose to eat, affecting our health in the short- and long-term. Previous studies carried out by our group have shown that aspects of the shared family environment played an important role in shaping young children’s food preferences.  However, the relative influences of genes and the environment on older teenagers’ preferences was previously unknown.

    In a new study published this week in the American Journal of Clinical Nutrition we explored the relative importance of genetic and environmental influences on adolescents’ food preferences using a twin design. The findings revealed that the effects of family upbringing on teenagers’ food preferences seem to disappear as they start to make their own meal choices, to the point where they have no detectable impact by late adolescence. Instead the ‘unique environment’ – aspects of the environment that are not shared by both twins in a pair (e.g. experiences  unique to each twin, such as having different friends) were found to effect food likes and dislikes at this age. Genes were also found to have a moderate impact on food preferences in late adolescence, in keeping with earlier findings from young children.

    The research involved 2,865 twins aged 18-19 years from the Twins Early Development Study (TEDS), a large population based cohort of British twins born in 1994 to 1996. Food preferences were measured using a self-report questionnaire of 62 individual foods which were categorised into six food groups – fruits, vegetables, meat/fish, dairy, starch food and snacks. It is the first study to show how substantial influences of the shared family environment in early childhood are replaced by environmental influences unique to each individual by the time they enter young adulthood. The decreasing influence of the family environment in adolescence has also been observed for other traits, such as body weight.

    The results of this study mean that efforts to improve adolescent nutrition may be best targeted at the wider environment rather than the home, with strategies focused on increasing the availability and lowering the cost of ‘healthier foods’. The substantial influence of the non-shared environment, suggests that food preferences can be successfully shifted towards more healthy choices in late adolescence. Policies that make the healthier food choice, the easier choice for everyone, have potential to achieve substantial public health improvements. In particular, the UK sugar-sweetened beverage levy soon to be introduced is one initiative that has the potential to promote a healthy food and drink environment.

     

    Article link:

    Smith AD, Fildes A, Cooke L, Herle M, Shakeshaft N, Plomin R, and Llewellyn C. Genetic and environmental influences on food preferences in adolescence. American Journal of Clinical Nutrition. First published ahead of print July 6, 2016. doi:10.3945/ajcn.116.133983

    http://ajcn.nutrition.org/content/early/2016/07/05/ajcn.116.133983.full.pdf+html

    Measuring appetitive traits in adults. What do we know about their relationships to weight.

    By Claudia M E Hunot, on 6 July 2016

    By Claudia Hunot, Alison Fildes and Rebecca Beeken.
    Some people are more likely to put on weight than others, and may find it harder to lose weight. One of the ways in which people differ is in how they respond to food; their ‘appetitive traits’. For example, how full you tend to feel after a meal, how much you want to eat when you see or smell delicious foods, or how fast you eat. These traits are partly influenced by genes, and they explain individual differences in the way we all eat. In the present-day food-filled environment people who are more responsive to food cues (want to eat when they see or smell delicious food), and less sensitive to satiety (take longer to feel full) are more susceptible to over-eat and gain weight.

    For a number of years, appetitive traits have been measured in children using the ‘Child Eating Behaviour Questionnaire’ (CEBQ) and more recently in infancy using the ‘Baby Eating Behaviour Questionnaire’ (BEBQ). These questionnaires measure a number of appetitive traits that can be grouped into two broad categories: food approach and food avoidance traits. Food approach traits, such as ‘food responsiveness’, are associated with a larger appetite or greater interest in food, while food avoidance traits such as ‘satiety responsiveness’ are associated with a smaller appetite and/or a lower interest in food. Research has shown higher scores on food approach traits and lower scores on food avoidance traits are associated with increased weight and weight gain. However, so far most of this research has been carried out in children. Until now no matched questionnaire existed for measuring the same appetitive traits in adults.

    Therefore, in our latest study we developed the ‘Adult Eating Behaviour Questionnaire’ (AEBQ) to measure these appetitive traits in adults. We also wanted to explore whether these traits relate to adult weight, as they do in children. Adult samples were recruited at two time points, one-year apart, from an on-line survey panel. Participants completed the AEBQ and provided their weight and height measurements to calculate BMI. Data from a total of 1662 adults was analysed and showed the 35 item AEBQ to be a reliable questionnaire measuring 8 appetitive traits similar to the CEBQ.

    We also showed that food approach traits such as ‘food responsiveness’, ‘emotional over-eating’ and ‘enjoyment of food’ were positively associated with BMI. This means people with higher scores for these traits were heavier on average. While food avoidance traits including ‘satiety responsiveness’, ‘emotional under-eating’ and ‘slowness in eating’ were negatively associated with BMI. This means people with higher scores for these traits were lighter on average.

    These findings suggest appetitive traits are likely to be important for weight across the life course. The newly developed AEBQ is a reliable instrument, which together with the BEBQ and the CEBQ, could be used to track weight-related appetitive traits from infancy into adulthood. The AEBQ may also help to identify individuals at risk of weight gain and could inform targeted interventions tailored to help people manage their appetitive traits, and in turn control their weight.

    Article link:
    Hunot, C., Fildes, A., Croker, H., Llewellyn, C. H., Wardle, J., & Beeken, R. J. (2016). Appetitive traits and relationships with BMI in adults: Development of the Adult Eating Behaviour Questionnaire. Appetite. http://dx.doi.org/10.1016/j.appet.2016.05.024
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    Internet use promotes cancer preventive behaviours, but mind the ‘digital divide’

    By Lindsay C Kobayashi, on 4 November 2013

    The saturation of the Internet into daily life in many parts of the world has characterised the early part of the 21st century.  As a communication medium, the Internet has huge potential to increase health-related knowledge and behaviours among the general population to ultimately help prevent chronic diseases such as cancer.  However, the actual effectiveness of the Internet in improving cancer-preventive behaviours among older adults, who are among the most at risk for cancer, is unclear.  Importantly, there is unequal access to and use of the Internet in the population.  In the United Kingdom, women, older adults, and those with low income are less likely to use the Internet; this phenomenon is called the ‘digital divide’.  If using the Internet leads to participation in healthy behaviours and ultimately lower chances of cancer, then inequalities in access to online health information may increase inequalities in cancer outcomes.

    Our study examined whether Internet use is associated with cancer-preventive behaviours and whether a ‘digital divide’ exists. To do this we used data from 5,943 participants in the English Longitudinal Study of Ageing: a nationally-representative study of English adults aged 50 years and older.  The study participants responded to questions about Internet and email use, self-reported colorectal and breast cancer screening, physical activity, eating habits, physical and cognitive abilities, and demographics every two years from 2002 to 2011.

    We found that 41.4% of older English adults reported not using the Internet at all between 2002 and 2011, while 38.3% used the Internet intermittently and 20.3% used the Internet continuously during this time period.  Men and women who consistently used the Internet were two times more likely to participate in colorectal cancer screening than those who never used the Internet. They were also 50% more likely to take part in regular physical activity, 24% more likely to eat at least five daily servings of fruit and vegetables, and 44% less likely to be current smokers.

    In short, we found that Internet plays a positive role in promoting healthy cancer-preventive behaviours.  Our research also confirmed that a ‘digital divide’ exists: Internet use in this study was higher in younger, male, white, wealthier, and more educated adults and lower in older, female, non-white, poorer, and less well-educated adults.  Age is a particularly important factor in the ‘digital divide’, as over 40% of all adults aged 50 and up reported never using the Internet.  Providing appropriate support and opportunities for Internet access among older adults may be a key first step to improving health among the ageing population. More generally, increasing Internet access among groups with low rates of Internet usage may have substantial public health benefits.  Policymakers must understand this potential for ‘digital divides’ to influence inequalities in cancer outcomes – whether for worse, or, for better if targeted efforts are made to increase Internet access and literacy among vulnerable groups.

    References

    Office for National Statistics. Internet access quarterly update, 2013 Q1. 2013 [cited 25 October 2013]. Available from: http://www.ons.gov.uk/ons/rel/rdit2/internet-access-quarterly-update/2013-q1/stb-ia-q1-2013.html

    Viswanath K, Nagler R, Bigman-Galimore C, McCauley MP, Jung M, Ramanadhan S. The communications revolution and health inequities in the 21st century: implications for cancer control. Cancer Epidemiol Biomarkers Prev 2012;21:1701-8.

    Xavier AJ, d’Orsi E, Wardle J, Demakakos P, Smith SG, von Wagner C. Internet use and cancer-preventive behaviours in older adults: findings from a longitudinal cohort study. Cancer Epidemiol Biomarkers Prev 2013 (in press).

     

    Busting the 21 days habit formation myth

    By Ben D Gardner, on 29 June 2012

    Have you ever made a New Year’s resolution? If so, you may have been assured – usually by a well-meaning supporter of your attempted transformation – that you only have to stick with your resolution for 21 days for it to become an ingrained habit. The magic number 21 creeps up in many articles about forming a new habit or making a change, but little is known about the origins of the ’21 days’ claim.

    Psychologists from our department have devoted extensive time and effort to find out what it takes to form ‘habits’ (which psychologists define as learned actions that are triggered automatically when we encounter the situation in which we’ve repeatedly done those actions).

    We know that habits are formed through a process called ‘context-dependent repetition’.  For example, imagine that, each time you get home each evening, you eat a snack. When you first eat the snack upon getting home, a mental link is formed between the context (getting home) and your response to that context (eating a snack). Each time you subsequently snack in response to getting home, this link strengthens, to the point that getting home comes to prompt you to eat a snack automatically, without giving it much prior thought; a habit has formed.

    Habits are mentally efficient: the automation of frequent behaviours allows us to conserve the mental resources that we would otherwise use to monitor and control these behaviours, and deploy them on more difficult or novel tasks. Habits are likely to persist over time; because they are automatic and so do not rely on conscious thought, memory or willpower.  This is why there is growing interest, both within and outside of psychology, in the role of ‘habits’ in sustaining our good behaviours.

    So where does the magic ’21 days’ figure come from?

    We think we have tracked down the source. In the preface to his 1960 book ‘Psycho-cybernetics’, Dr Maxwell Maltz, a plastic surgeon turned psychologist wrote:

    It usually requires a minimum of about 21 days to effect any perceptible change in a mental image. Following plastic surgery it takes about 21 days for the average patient to get used to his new face. When an arm or leg is amputated the “phantom limb” persists for about 21 days. People must live in a new house for about three weeks before it begins to “seem like home”. These, and many other commonly observed phenomena tend to show that it requires a minimum of about 21 days for an old mental image to dissolve and a new one to jell.’ (pp xiii-xiv)

    How anecdotal evidence from plastic surgery patients came to be generalised so broadly is unclear.  One possibility is that the distinction between the term habituation (which refers to ‘getting used’ to something) and habit formation (which refers to the formation of a response elicited automatically by an associated situation) was lost in translation somewhere along the line. Alternatively, Maltz stated elsewhere that:

    ‘Our self-image and our habits tend to go together. Change one and you will automatically change the other.’ (p108)

    Perhaps readers reasoned that, if self-image takes 21 days to change, and self-image changes necessarily lead to changes in habits, then habit formation must take 21 days. Although ‘21 days’ may perhaps apply to adjustment to plastic surgery, it is unfounded as a basis for habit formation. So, if not 21 days, then, how long does it really take to form a habit?

    Researchers from our department have done a more rigorous and valid study of habit formation (Lally, van Jaarsveld, Potts, & Wardle, 2010). Participants performed a self-chosen health-promoting dietary or activity behaviour (e.g. drinking a glass of water) in response to a once-daily cue (e.g. after breakfast), and gave daily self-reports of how automatic (i.e. habitual) the behaviour felt. Participants were tracked for 84 days. Automaticity typically developed indistinct pattern: initial repetitions of the behaviour led to quite large increases in automaticity, but these increases then reduced in size the more often the behaviour was repeated, until automaticity plateaued. Assumed that the point, at which automaticity is highest, is also the point when the habit has formed, it took, on average, 66 days for the habit to form. (To clarify: that’s March 6th for anyone attempting a New Year’s resolution.)

    Interestingly, however, there were quite large differences between individuals in how quickly automaticity reached its peak, although everyone repeated their chosen behaviour daily: for one person it took just 18 days, and another did not get there in the 84 days, but was forecast to do so after as long as 254 days.

    There was also variation in how strong the habit became: for some people habit strength peaked below the halfway point of the 42-point strength scale and for others it peaked at the very top. It may be that some behaviours are more suited to habit formation – habit strength for simple behaviours (such as drinking a glass of water) peaked quicker than for more complex behaviours (e.g. doing 50 sit-ups) – or that people differ in how quickly they can form habits, and how strong those habits can become.

    The bottom line is: stay strong. 21 days is a myth; habit formation typically takes longer than that. The best estimate is 66 days, but it’s unwise to attempt to assign a number to this process. The duration of habit formation is likely to differ depending on who you are and what you are trying to do. As long as you continue doing your new healthy behaviour consistently in a given situation, a habit will form. But you will probably have to persevere beyond January 21st.

    Benjamin Gardner and Susanne Meisel

    (www.ucl.ac.uk/hbrc/gardnerb)

     

    References

    Lally, P., van Jaarsveld, C. H. M., Potts, H. W. W., & Wardle, J. (2010). How are habits formed: Modelling habit formation in the real world. European Journal of Social Psychology, 40, 998-1009. (http://onlinelibrary.wiley.com/doi/10.1002/ejsp.674/abstract)

    Maltz, M. (1960) Psycho-cybernetics. NJ: Prentice-Hall.

    Do you want your kids eating their greens? Then, you better start, too…

    By Susanne Meisel, on 23 February 2012

    You don’t need to be Jamie Oliver to figure out what is going on with children’s diets – but his efforts certainly helped to pull the candyfloss from our eyes:  children in England are eating plenty of snacks high in fat, salt and sugar, but only one quarter eats their recommended minimum 5 portions of fruit and vegetables a day.  This can be problematic, because not only could it lead to nutritional deficiencies, but also to disproportionate weight gain.

    Unfortunately, it is not the case that children simply ‘outgrow’ their ‘puppy-fat’; the vast majority of overweight children grow into overweight teenagers and potentially obese adults.  This is because people naturally put on about 2 pounds per year as they age (unless they do something about it, of course) – and the higher the ‘starting weight’ is, the higher the chances are that people shift up across the weight spectrum as they get older. Furthermore, people who become overweight or obese early in life are often more severely affected by illnesses linked with an unhealthy weight, such as diabetes, heart disease and some cancers.

    This is why it is important to figure out what it is that makes children eat their greens (and all those other healthy fruit and veggies, even if cooking like Jamie isn’t your thing).  It has long been known that many different factors such as inherited taste preferences, family eating habits or the amount of time spent watching TV are important when looking at reasons why children eat (or don’t eat) certain foods; but rarely has research looked at factors related to healthy and unhealthy eating habits at the same time in the same group of families.

    In this study, the researchers were interested in the actual foods children in England eat (as opposed to specific nutrients, such as vitamins). The researchers had records of what children and their parents ate from several hundred families, along with information on factors which may influence what they eat.  They decided to look in particular at factors which affected how much fruit, vegetables, unhealthy snacks and sugary drinks children consume; focusing on preschool-aged children – as they are not yet strongly influenced by their peers, and are more dependent on eating what their caregivers provide for them.

    Perhaps unsurprisingly, the researchers found that when children liked the taste of fruit and veggies it predicted how much of these they ate.  However, what is more important, they also found that parents’ consumption of either fruit, vegetables, unhealthy snacks or sweetened drinks was a very important indicator of how much children ate of these foods.  This might be not only because caregivers may feed children what they themselves eat, but also because children tend to copy adults’ behaviour – so if mum eats healthily, children will be more likely to want to eat healthily too.  Of course, that is also true for unhealthy eating habits – which is why not having junk foods in the home in the first instance can help.  Because it was mainly mothers who filled out the questionnaires, these results focused only on mothers.

    Furthermore, praising children for eating fruit and veggies was a good indicator of how much children ate, and monitoring the unhealthy snacks children eat was linked with them eating less of these and more fruit and vegetables.  The amount of time children spent watching TV was also an indicator of children eating unhealthy snacks and having sweetened drinks, but it had no impact on their consumption of fruit and vegetables.

    The research provides a little more evidence on how eating habits are transmitted within a family.  It highlights that different strategies need to be used in order to increase the amount of healthy foods vs. decreasing amounts of unhealthy foods children eat.

    So, ultimately, if you want your children to eat their greens, you might not have any choice but to take a bite too and start singing their praises, and if you really want to cut down on their junk intake then get rid of it from within your home and turn off the telly – and at last Jamie will be happy.

     

    http://www.nature.com/ejcn/journal/vaop/ncurrent/full/ejcn2011224a.html