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Adolescents in a complex world: what to eat and why?
Adolescents have to engage with a social environment of increasing complexity and diversity. The agents in this engagement include family and peer relationships, the internet, television, mobile phones, the media and electronic gadgetry. All of these provide a flow of information that influences adolescents’ perception of their size and shape, self-esteem, fashions and ways of behaving (including dietary choices, skipping meals, eating fruits and vegetables and fast foods). In order to implement public health policies that are effective against adolescent overweight and obesity (and which contribute to health in other ways), it seems essential to obtain a picture of the relationship between the social environment, frequency of obesity and key dietary variables.
Recent surveys have been based on large numbers of adolescents ranging in age from 11 to 17 years. In the largest study – of more than 162 thousand adolescents in 35 countries – there were some surprises. For example, the relationship between the percentage of overweight/obese adolescents and economic inequality – or the social gradient (differences in wealth between top and bottom) – was different for the high income countries compared with those of middle income. Why should this be?
Clearly social dynamics operate differently in distinct cultures and in countries which vary in wealth. The sheer complexity of the relationship between country based economics and adolescent obesity is mirrored by the complexity of the relationships between family circumstances and adolescent dietary behaviours. These outcomes raise the question of whether it is possible to draw a single all embracing conclusion from such complicated arenas.
Although large surveys have value, they may not provide the elements for policy development. We can ask, is there an average adolescent? Answer – No! Consequently we are unlikely to find solutions in the ‘average’ values of variables that influence adolescent behaviour and body weight. In dealing with complicated environments where predictability is low, it may be better to do our research locally, and to uncover relationships in the areas where we live and work.