Authors: Alex Ghanouni, Cristina Renzi & Jo Waller

We have previously written about ‘overdiagnosis’ – the diagnosis of an illness that would never have caused symptoms or death had it remained undetected – and how the majority of the public are unfamiliar with the concept and find it difficult to understand. We have also looked at the various ways that health websites describe it in the context of breast cancer screening; we previously found that most UK websites include some relevant information, in contrast to the last similar study from 10 years ago. This led us to think about how it might be possible to better explain the concept to people. Although ‘overdiagnosis’ is the most commonly used label, its meaning is probably difficult to infer if people are unfamiliar with it (and most people are). We wanted to test whether other terms might be seen as more intuitive labels that would help communicate the concept to the public.

We carried out a large survey in which we asked around 2,000 adult members of the public to read one of two summaries describing overdiagnosis. These summaries were based on information leaflets that the NHS has already used extensively in England. We asked people whether any of a series of possible alternative terms made sense to them as a label for the concept described and whether they had encountered any of the terms before.

What did we find?

A fairly large proportion of people (around 4 out of 10) did not think any of the seven terms we suggested were applicable labels for the concept as we described it. We also found that no single term stood out as being seen as particularly appropriate. The term most commonly endorsed (“unnecessary treatment”) was only rated as appropriate by around 4 out of 10 people. Another important finding was that around 6 out of 10 people had never encountered any of the terms we suggested and that the most commonly encountered term (“false positive test results”) was only familiar to around 3 out of 10 people. You can read the full paper here.

What were our conclusions?

We were disappointed that we did not find a term that was clearly considered to be an intuitive label for the concept of overdiagnosis. However, this was not entirely surprising because we know from several studies that it is unfamiliar to most people. It is not a given that this will always be the case: Organisations like the NHS and health charities are continually telling the public about overdiagnosis in various ways and if the concept becomes more familiar and better understood, people may be more inclined to identify a term that makes sense and which can then be used to communicate the concept. It is also possible that terms other than the 7 we looked at might already be suitable. Since the terms we looked at were generally unfamiliar, one recommendation we can make in the meantime is that it might be better to avoid specific labels like “overdiagnosis” when communicating the issue to people; explicit descriptions might be more helpful.

Rises in obesity prevalence over recent decades have corresponded with increasing stigmatisation of, and discrimination against, individuals living with obesity. Weight stigma is often justified on the basis that it might encourage people to lose weight, but a growing evidence base indicates that experiences of weight-related stigmatisation may in fact encourage behaviours that promote obesity.

A few small studies have indicated that people who face weight stigma are more inclined to avoid physical activity, but none have been able to clearly establish what effect experiencing stigma has on actual exercise behaviour.

In a new study published today in BMJ Open we explored the relationship between weight discrimination and physical activity. The research involved 5,480 men and women aged 50 years and older taking part in the English Longitudinal Study of Ageing, a large population-based cohort of middle-aged and older adults living in England.

Overall, one in twenty people said they had been discriminated against because of their weight, ranging from lack of respect or courtesy to being threatened or harassed. Rates of weight discrimination varied considerably according to how overweight a person was, from 0.9% of people with a body mass index (BMI) in the overweight range (25-29.9) to 13.4% of people with obesity (BMI greater than 30).

Importantly, we found that people who had experienced weight-related discrimination had almost 60% higher odds of being inactive and 30% lower odds of engaging in moderate or vigorous exercise once a week than their peers.

Interestingly, a person’s BMI in itself did not affect the relationship between weight discrimination and exercise, indicating that people who experience weight-related discrimination are likely to be less physically active, regardless of their weight.

There could be several reasons for our findings. People who feel stigmatised may be more self-conscious about exercising in front of others for fear they will attract undesirable attention, leading to embarrassment or teasing. They may also begin to believe the negative stereotypes against themselves as lazy and worthless, leaving them wondering why they should bother trying to be active.

Given the substantial benefits of being physically active for both physical and mental health, interventions that aim to reduce weight bias at a population level – for example through schools, local communities or national campaigns – may have greater impact on health than those that encourage people to lose weight. A Health at Every Size approach may be helpful in encouraging people to develop and maintain healthy habits, including regular physical activity, for the sake of health and wellbeing as opposed to weight control.

Article link:
Jackson SE, Steptoe A. Association between perceived weight discrimination and physical activity: a population-based study in English middle-aged and older adults. BMJ Open. 2017;7:e014592.
http://bmjopen.bmj.com/content/7/3/e014592.info

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

Authors: Alex Ghanouni, Cristina Renzi & Jo Waller

In our last blog, we talked about ‘overdiagnosis’, a concept that many people are unfamiliar with – that is, when a medical test finds an illness that would never have caused any harm during a person’s lifetime.

As a follow-up study, we were interested in how much information the UK and Australian public could find online about overdiagnosis in the specific context of breast cancer screening.

Why breast cancer screening?

We chose breast screening because it is a setting in which the issue of overdiagnosis has received a lot of attention in the UK in recent years: in 2011, Cancer Research UK and the Department of Health commissioned a review of studies with the aim of understanding how much overdiagnosis happens in breast screening.

Likewise, the NHS recently made substantial changes to the information leaflets provided to women invited for breast screening, with the aim of ensuring that they would understand that overdiagnosis was one possible outcome of being tested.

Breast screening sometimes diagnoses ‘ductal carcinoma in situ’ or ‘DCIS’, which is an abnormality that can become a symptomatic cancer over time. However, it can also be slow growing and never pose a health risk, meaning that a large proportion of overdiagnosis in breast screening is due to DCIS.

As well as finding out what kind of information people could find about overdiagnosis on health websites, we were interested in what explanations those websites provided about DCIS, and also what kinds of statistics were used to give the public a sense of how many people are affected by overdiagnosis.

We used a Google search for ‘breast cancer screening’ to find the most relevant health websites in the UK and Australia (such as NHS Choices and Cancer Australia). We examined in detail ten websites from the UK and eight from Australia.

What did we find?

Our main findings were that most UK websites included some information about overdiagnosis and also DCIS. The websites provided a range of statistics stating, for example, that every year around 4,000 women in the UK are overdiagnosed and overtreated following screening and that around 3 in 200 women screened would be overdiagnosed and overtreated (considering women aged between 50 and 70 years undergoing screening every three years).

Such information was available less often on Australian websites, although the kind of information was similar when it was present (and several websites linked to more detailed websites instead of hosting the information themselves).

Why is this important?

One reason for doing this research was that a similar study had been carried out more than ten years ago in 2000, showing that overdiagnosis and DCIS were rarely described. We thought that things might have changed in the meantime as more and more people use the internet to understand health issues.

In fact, we found that although not every piece of information on overdiagnosis and DCIS is available on every website, it is more available than it was in the past. In time, this might lead to a greater level of public awareness about the issue.

Authors: Alex Ghanouni, Cristina Renzi & Jo Waller

In recent years, doctors and academics have become more and more interested in a problem referred to as ‘overdiagnosis’. There are several ways that overdiagnosis can be defined.

One particularly useful way is to think of it as the diagnosis of a disease that would never have caused a person symptoms or led to their death, whether or not it had been found through a medical test. In other words, even if a person had not had the test, the disease would never have caused them any harm.

Catching it early

It may not be obvious how this can happen. As an example, imagine a woman going for breast screening, which tries to find cancer at an early stage, before it starts causing symptoms.

The thinking behind this type of test is that if the disease is found early, it will be easier to treat and there is a higher chance of curing it. Most people are familiar with this idea that ‘catching it early’ is a good thing.

So, suppose a woman who has no symptoms goes for screening and the test finds cancer: she would usually go on to have treatment (e.g. surgery).

However, although she has no way of knowing for sure, it is possible that the cancer was growing so slowly that she would have lived into old age and died of something unrelated, without ever knowing about the cancer, had she not gone for screening.

The cancer is real but the diagnosis does not benefit the woman at all; it results in treatment that she did not need (‘overtreatment’). In fact, if she had not had the screening test, she would have avoided all the problems that come with a cancer diagnosis and treatment.

What research has found

If you find the idea of overdiagnosis counter-intuitive, you are not alone. Several studies have tried to gauge public opinion on the issue and found that this is a fairly typical view, partly because the notion that some illnesses (like cancer) might never cause symptoms or death is one that does not receive much attention and is often at odds with our personal experiences.

Results from an Australian study in 2015 found that awareness of ‘overdiagnosis’ is low – in a study of 500 adults who were asked what they thought it meant, only four out of ten people gave a description of the term that was considered approximately correct and these descriptions were often inaccurate to varying degrees.

For example, people often thought in terms of a ‘false positive’ diagnosis (diagnosing someone with one illness when really they do not have that illness at all), or giving a person ‘too many’ diagnoses.
Is this the same in the UK?

We wanted to find out whether this was also true in the UK. We asked a group of 390 adults whether they had come across the term ‘overdiagnosis’ before and asked them to describe what they thought it meant in their own words, as part of an online survey.

We found that only a minority (three out of ten people) had encountered the term and almost no-one (10 people out of all 390) described it in a way that we thought closely resembled the concept described above.

It was not always clear how best to summarize people’s descriptions but we found that people often stated that they had no knowledge or had similar conceptions to the Australian survey such as ‘false positives’ and ‘too many’ diagnoses.

Some descriptions were somewhat closer to the concept of overdiagnosis such as an ‘overly negative or complicated’ diagnosis (e.g. where the severity of an illness is overstated) but there were also some descriptions that we found more surprising such as being overly health-conscious (e.g. worrying too much about health issues).

Room for improvement

Many people who work in public health and healthcare believe that people should be aware of the possibility of overdiagnosis, particularly since they will eventually be offered screening tests in which there is this risk.

In this respect, our findings show that there is substantial room for improvement in how we inform the public about overdiagnosis. In part, this may be due to the term itself not having an intuitive meaning, in which case other terms might be more helpful (for example the term ‘unnecessary detection’).

This could be tested in future studies. Our findings also motivated us to find out the extent to which trusted information sources (such as websites run by the NHS and leading health charities) are already providing information on overdiagnosis.

We would like to share the findings from this study in a follow-up blog post. We will be posting this here soon.

This was originally posted on the BioMed Central blog network.

Have you ever searched for information about cancer? Chances are, if you have, it was a Google search that led to a website like WebMD, the Mayo Clinic, or a charity such as the American Cancer Society or Cancer Research UK. Research on cancer information seeking behaviour of the public tells us that most people first turn to the Internet, with more in-depth searching possibly extending to talks with friends, family, and health professionals. But who searches for cancer information? We already know that people in America who actively seek out information about cancer are most often well educated, have a high income, are under age 65, are white, and have a usual source of health care (1).

Currently, the global rise in cancer incidence has coincided with the technological revolution that sees internet and mobile usage increasing across the globe (2). As a result, searches for cancer information have increased among the public, but these increases are occurring disproportionately among people with higher levels of education and income (3). This trend indicates that social inequalities in health communications are widening, and will continue to do so. The outcome would be that people who are the best educated and most economically advantaged would have the best opportunities for access to, and use of, information about cancer to help them make informed decisions about prevention and early diagnosis.

To learn more about this issue, we conducted a study investigating the relationships between literacy, cancer fatalism, and active seeking of cancer information (4). Cancer fatalism can be described as deterministic thoughts about the external causes of the disease, the inability to prevent it, and the inevitability of death at diagnosis (5). We wondered whether low literacy and cancer fatalism pose barriers to seeking cancer information, and in particular whether low literacy might lead to fatalistic beliefs about cancer, which might then in turn stop people from seeking out cancer information.

Our logic model of the relationships between low health literacy, cancer fatalism, and cancer information seeking

We used data from the publicly available U.S. Health Information National Trends Survey (HINTS). The HINTS is a great resource for anyone who interested in trends in the use of cancer-related information among the general American public. The survey is nationally representative of American adults aged 18 years and over. We used data from the third cycle of the fourth round of HINTS, which was conducted in 2013. We used data from 2,657 American adults who had no cancer history. The measures of interest were:

Health literacy

• Reading comprehension of a nutrition label, scored out of 4 points

Cancer fatalism

• Agreement/disagreement with each of three statements:
• “It seems like everything causes cancer”
• “There’s not much you can do to lower your chances of getting cancer”
• “When I think about cancer, I automatically think about death”

Cancer information seeking

• Asked respondents whether they had ever searched for cancer information

The results shown below are representative of the American public aged 18 years and over.

What did we find?

One-third (34%) of American adults had low literacy, according to our measure. This is a substantial proportion of the population, given that the measure assessed basic reading comprehension of a nutrition label, which is important for health.

Most American adults (66%) agreed that, “it seems like everything causes cancer”. However, most disagreed (71%) with “there’s not much you can do to lower your chances of getting cancer”. Responses were more evenly balanced to, “when I think about cancer, I automatically think of death”, with 58% agreeing.

Just over half (53%) of the American public had ever searched for information about cancer. Independently of sociodemographic factors, adults with low literacy were less likely to search for information than those with high literacy. People who agreed that, “there’s not much you can do to lower your chances of getting cancer” were also less likely to search for cancer information. The other two fatalistic beliefs were not associated with cancer information seeking, but people with low income and low education were less likely to actively seek out cancer information.

Finally, we found that while literacy had a strong direct effect on cancer information seeking, the fatalistic belief, “there’s not much you can do to lower your chances of getting cancer” explained about 14% of the effect of literacy on cancer information seeking. This means that people with low literacy are slightly more likely to hold this fatalistic belief, which in turns acts as a barrier to seeking out information.

What does it mean?

This study indicates that addressing health literacy and fatalism about cancer prevention should be a priority for future cancer communication strategies. Population groups with less access to health care, who are the most vulnerable to low literacy and fatalistic beliefs about cancer, are also the least likely to benefit from cancer information. We feel that strategies to improve public beliefs and knowledge about cancer might be best placed outside of the clinical environment. For example, advertising strategies and public events in opportunistic settings such as road shows might help to increase incidental exposure to cancer information among those people who are least likely to actively seek it (6-8). Communication strategies such as patient narratives, such as those found on the Prevent Cancer Foundation website, also show promise. Overall, fatalism and health literacy may represent useful targets for cancer control strategies aiming to increase all people’s abilities to manage their risk of cancer, and to reduce social inequalities across the continuum of cancer control.

The full paper is available at Health Education and Behavior.

References

1. Finney Rutten LJ, Squiers L, Hesse B. Cancer-Related Information Seeking: Hints from the 2003 Health Information National Trends Survey (HINTS). J Health Commun 2006;11:147-156. doi: 10.1080/10810730600637574
2. Viswanath K. The communications revolution and cancer control. Nat Rev Cancer 2015;5:828-835. doi:10.1038/nrc1718
3. Finney Rutten LJ, Agunwamba AA, Wilson P, Chawla N, Vieux S, Blanch-Hartigan D, et al. Cancer-related information seeking among cancer survivors: Trends over a decade (2003-2013). J Cancer Educ 2015 [Epub ahead of print]. doi:10.1007/s13187-015-0802-7
4. Kobayashi LC, Smith SG. Cancer fatalism, literacy, and cancer information seeking in the American public. Health Educ Behav 2015 [Epub ahead of print]. doi: 10.1177/1090198115604616
5. Niederdeppe J, Levy AG. Fatalistic beliefs about cancer prevention and three prevention behaviors. Cancer Epidemiol Biomarkers Prev 2007;16:998-1003.
6. Ironmonger L, Ohuma E, Ormiston-Smith N, Gildea C, Thomson CS, Peake MD. An evaluation of the impact of large-scale interventions to raise public awareness of a lung cancer symptom. Br J Cancer 2015;112:207- 216. doi:10.1038/bjc.2014.596
7. Power E, Wardle J. Change in public awareness of symptoms and perceived barriers to seeing a doctor following Be Clear on Cancer campaigns in England. Br J Cancer 2015;112:S22-S26. doi:10.1038/bjc.2015.32
8. Smith SG, Rendell H, George H, Power E. Improving cancer control through a community-based cancer awareness initiative. Prev Med 2014;60:121-123. doi:10.1016/j.ypmed.2013.11.002

Twitter is probably one of the most obvious resources available for gauging public sentiment. It offers a rich, large-scale data source that can give insight into what people are thinking without having to interview or survey them. However, the use of Twitter data for research is relatively unexplored terrain.  So before conceiving of any “serious” research studies, my colleague Alex Ghanouni and I decided to explore Twitter as a data resource. In this piece, I would like to share our thoughts about our first informal attempt at venturing into the ‘Twittersphere’.

The starting point of our adventure was a curiosity about what is being said about cancer treatment and cancer prevention in social media. We adapted publically available Python code to track keywords in real time. The first iteration was for one hour only (12th March 2015); the subsequent two iterations were for 24 hours each (24th March; 5th May).

One seemingly easy question to address was the volume of tweets about “cancer treatment” and “cancer prevention” in relation to each other and “cancer” in general. We naively assumed that a count of tweets would be able to address our question. However, after the second iteration, it became apparent how naive our initial searches had been: Many of the tweets found using the keyword “cancer” turned out to be referring to the zodiac sign. As we could not think of a select group of second keywords that would be (almost) guaranteed to be used in conjunction with “cancer” the disease, we gave up on tracking “cancer” alone.

We had more luck with “cancer treatment”, “cancer prevention” and their relatively unambiguous synonyms and permutations. The volume of tweets for “cancer treatment” (24th March: 8355; 5th May: 5558) was consistently larger than that for “cancer prevention” (24th March: 5156; 5th May: 1487). This was even true around the 24th of March, the day when the news broke about Angelina Jolie’s preventative surgical removal of her ovaries and fallopian tubes. Although these findings do not reveal what is said about these topics, it should nevertheless give an indication of how much interest they generate. When it comes to cancer, it appears the public discourse mainly revolves around treatment rather than prevention. This is also in line with what we expected based on our professional and personal experience. Although our present investigation could not have been more rudimentary, more serious attempts at tracking specific keywords over longer periods of time might lead to genuinely novel insights.

Of course, we were also at least as interested in the content of the tweets about “cancer treatment” versus “cancer prevention”. To avoid a time-consuming traditional content analysis, we used the free web-based tool, ‘Wordle’, to create word clouds which reflect the frequency of words in text. Before creating the word clouds, we first removed all search terms from the tweet texts. When we examined the word clouds it became clear that there were two reasons why words were frequently used. Firstly, the words could be related to “real” news, which was the case for cancer prevention on the 24th March from 12pm GMT:

However, in two of the four word clouds we inspected, the most prominent words related to an obscure news source tweeting about dubious cancer cures (most likely for commercial reasons) or out-of-date research findings (a cervical screening paper from 1979).  Finally, it was hard to interpret the results of the fourth word cloud, as there were few words that really stood out.  A few of the largest words originated from a poem line (“That smile could end wars, and cure cancer”).

As an academically-trained researcher, I felt compelled to do a quick – albeit not too rigorous – literature search for peer-reviewed publications as well. Both the PubMed and PsycINFO databases yielded around 750 hits containing the keyword “Twitter”. Compared with other one-word search terms, this is a modest number.  One review of published health studies using Twitter data concluded that most researchers lacked the knowledge and skills to process the large volumes of data and limited their samples in accordance with their ability to process and analyse the data (Finfgeld-Connett, 2014).  A second limitation they noted was the population-representativeness of Twitter users, or rather, the lack thereof.  Broadly speaking, we concurred with this review’s conclusions, although we would like to add a few nuances and additional observations.

Let’s start with looking at us, the researchers first.  Our first research experience with Twitter was in line with the challenges of using Big Data for health research that I discussed in a previous blog post.  Most of us who are interested in the content of social media tend to have a social science background.  Programming and data mining are therefore not part of our skillset acquired through formal education.  This obviously constrains what we can do with large volumes of data without help from those who are conventionally employed to work with Big Data.  Having said that, we felt that the lack of a reliable alternative to human judgement limited us more than our technical skills.  We repeatedly needed to resort to more simple forms of analysis (i.e. reading the tweets…) to determine what the data were actually telling us and there seemed to be no obvious way we could have outsourced this task to an algorithm.

Similarly, although there are probably sophisticated programmes to weed out bot-generated tweets, authenticity of the tweets might be a more general problem which cannot be easily addressed without human intervention.  The most obvious challenge is that tweets originate from a variety of users who have diverse professional, commercial and personal motives.  This is compounded by Fifgeld-Connett’s observation regarding the representativeness of Twitter users.

These challenges may not be insurmountable, but they do highlight that Twitter data is far from “clean” and straightforward to interpret for health research purposes.  I for one will be keeping a keen eye on future research endeavours tackling these issues.

References

Finfgeld-Connett, D. (2014), ‘Twitter and Health Science Research’, Western Journal of Nursing Research, 1-15.

Childhood obesity is becoming more common.  The latest available statistics show that about 1 in 5 of 4-5year old children (22%), and about 1 in 3 (33%) of 10-11year old children were overweight or obese in the UK .  This puts more and more children at risk of serious, chronic health conditions such as diabetes and heart disease which have traditionally only been observed in adults.  Overweight and very overweight children are also at risk of mental health problems such as depression; sometimes made worse because of weight-related teasing or bullying by their peers.  Preventing more children from becoming overweight, and helping those who already are overweight to prevent further weight gain, or to lose weight, is therefore important. 

However, a huge number of factors contribute to the rising obesity rates in adults and children.  The solution is certainly not simple, and our researchers are working at finding out more about the many different factors that contribute to the current ‘obesity epidemic’. 

Some people think that one factor that plays a part in childhood obesity is that some parents don’t know that their child is overweight and because they don’t know, they don’t do anything about it.  Therefore, it was thought that telling parents that their child is overweight could prompt some action to avoid further weight gain. However, studies so far have shown that telling parents about their child’s weight status has very little effect on behaviour change; although some parents are more likely to agree that their child is overweight after having been informed about it by researchers, many parents do not agree with the feedback or think that their child’s weight puts them at risk of health problems.  In other words, they seem to disregard the information for some reason.

Researchers from our department wanted to better understand why telling parents about their child’s weight status had so little effect; and in fact often resulted in negative reactions. 

They interviewed 52 parents, who received a letter from the National Child Measurement Programme (NCMP), which informed them that their child was overweight or very overweight.  The National Child Measurement Programme was established by the Department of Health in 2005 to monitor national trends in heights, weights and BMIs of children in Reception (aged 4-5 years) and Year 6 (10-11 years) in publicly funded primary schools in England.

The researchers asked questions about parents’ thoughts on the feedback, and whether they agreed with it.

It transpired that in all interviews, parents used a variety of markers, other than weight, to decide whether their child was a healthy weight or at risk of health problems caused by their weight.  The majority of parents felt that their child ate a healthy diet, was physically active, and was not teased or bullied, and therefore they were not concerned about their child’s weight.  Furthermore, many parents did not think their child ‘looked overweight’, often in comparison with the child’s peers. In this context parents also often referred to build (‘big bones’), or to ‘puppy fat’ which they expected their child to lose during puberty. Parents shared the view that ‘health and happiness is more important than weight.’

This means that simply telling some parents that their child is overweight might not be an effective means of raising awareness about potential health problems, because they might not think that weight is a very accurate measure of their child’s health.  Taking a child’s lifestyle into account (diet, physical activity, and emotional health) might be a good way to improve the dialogue with parents about a child’s health. 

Furthermore, because there seems to be an assumption that children will lose any extra weight during puberty, parents may think that overweight is an issue that will correct itself over time.  However, there is plenty of good research showing that overweight children are highly likely to turn into overweight adults; perhaps not least because of differences in appetite, as discussed in our previous blog.  Findings from this study showed us that more work needs to be done to communicate the link between child weight and adult weight better. 

Lastly, because parents compare their own children to others, and weight has overall gone up in the population, they may consider their child ‘normal weight’ when it is, in fact, overweight.  Although there is also the argument that all measures of weight status are somewhat arbitrary and not without their faults, they do give a good indication about where things are headed, particularly for those at the upper end of the range.

Although these findings are from only one study, and interviewed only a small number of parents and may therefore not hold true for a larger number of parents, they nonetheless bring up some points that might be worth thinking about in more detail. No doubt, weight is certainly not the only important marker for a child’s well-being, but given that many overweight children and adults suffer from related physical and mental difficulties, paying attention to a child’s weight is also not insignificant. Because ultimately, parents and health professionals want the same thing: keeping children happy and healthy.

Article Reference:  Syrad H, Falconer C, Cooke L et al. ‘Health and happiness is more important than weight‘: a qualitative investigation of the views of parents receiving written feedback on their child’s weight as part of the National Child Measurement Programme. J Hum Nutr Diet. 2014;n/a.  http://onlinelibrary.wiley.com/doi/10.1111/jhn.12217/abstract