Murra Mullangari — Pathways Alive and Well

A clinically qualified and culturally competent Aboriginal and Torres Strait Islander health workforce is vital if Australia is to make a difference to Indigenous health

The Murra Mullangari — Pathways Alive and Well program is an initiative of the Australian Indigenous Doctors’ Association (AIDA) in partnership with other peak Indigenous organisations. Using culture and identity as a strength, the program was developed with the aims of building the aspirations and capacity of Aboriginal and Torres Strait Islander senior high school students to remain in the academic pipeline and pursue careers in health.

In the language of the Ngambri people, upon whose lands the inaugural program was held, Murra is the path and Mullangari is health and wellbeing coming from the ceremonies, including the Bogong Moth Ceremony.

The program was informed by the Patty Iron Cloud National Native American Youth Initiative, run in Washington DC each year by AIDA’s peer organisation — the Association of American Indian Physicians. After attending the program in 2010, three senior members of AIDA returned committed to establishing a similar program across all health careers, rather than just medicine and biomedical research. After almost 2 years of seeking financial support for an Australian program, commitment was given by the Australian Government to establish a pilot program in June 2012.

In April 2013, the inaugural Murra Mullangari — Pathways Alive and Well program commenced, with 30 Indigenous senior secondary students (from almost 200 applicants) travelling to Canberra to participate in a 5-day residential component, which included a traditional welcome to country by Aunty Matilda House at the Aboriginal Tent Embassy, a smoking ceremony and the warm words of former Governor-General and AIDA Patron, Sir William Deane, who highlighted the importance of education and the pursuit of dreams.

The students visited local and national institutions such as the Winnunga Nimmityjah Aboriginal Health Service, the Australian Institute of Aboriginal and Torres Strait Islander Studies and the Australian Institute of Sport. Participants took part in interactive workshops at the Australian National University Medical School and University of Canberra Faculty of Health, as well as learning about university entry pathways and support at the Tjabal and Ngunnawal Indigenous Higher Education Centres. The program also featured workshops led by current health professionals in the disciplines of medicine, exercise science, nutrition, Aboriginal health work, psychology and nursing.

Murra Mullangari Facilitator Gregory Phillips encouraged participants to express themselves and their aspirations through painting. This artwork is a combination of the reflections of all 30 participants along with the program staff, facilitator and group leaders, on culture, the Murra Mullangari experience and their continuing personal goals.

Murra Mullangari partners continue to seek funding support to run further programs and would welcome contact from any MJA readers.

Murra Mullangari — Pathways Alive and Well. By 2013 participants, facilitator, group leaders and program staff.

The hobbit — an unexpected deficiency

A striking feature of fantasy literature has been the consistent victory of good characters over bad. While the consensus has been to attribute this to narrative conventions about morality and the necessary happiness of endings, we hypothesised that a major contribution to the defeat of evildoers in this context is their aversion to sunlight and their poor diet, which may lead to vitamin D deficiency and hence reduced martial prowess.

Vitamin D is a fat-soluble, secosteroid hormone, which in humans is largely synthesised in the skin when exposed to ultraviolet light, and is sometimes called “the sunshine vitamin”.1 Vitamin D is also found in some foods, particularly oily fish and, in small amounts, in egg yolks, cheese, beef, liver and some mushrooms. It has a well described role in calcium metabolism, with deficiency resulting in rickets and osteomalacia. Vitamin D also has immune-modulating roles with potential effects on susceptibility to conditions ranging from multiple sclerosis to tuberculosis and accelerated lung function decline.2,3 Skeletal muscle weakness is known to be a feature of vitamin D deficiency although it has not been found to contribute to muscle dysfunction in chronic obstructive pulmonary disease (COPD),4 despite patients with COPD being noted for poor diet and reduced time spent outdoors.5

A PubMed search performed on 29 July 2012 for studies that fulfilled both of the search terms “imaginary populations” and “vitamin D” returned no publications, suggesting that our hypothesis was untested, and leading to the work presented here.

Methods

We performed a pilot study using textual analysis to extract data relating to diurnal habits, dwelling, light exposure and diet from The hobbit by J R R Tolkien. Results are reported in an approximately consecutive narrative fashion. In addition, protagonists were identified as good or evil and victorious or defeated on binary scales by consensus. Sun exposure was scored from 3 (lots) to 0 (none at all) and diet was scored as 1 or 0 depending on whether any vitamin D-containing item was mentioned. These were summed to give a vitamin D score (range, 0–4), and this score was related to victoriousness by unpaired t tests.

Results

Bilbo Baggins, a hobbit, lives in a hole in the ground but with windows, and when he is first encountered he is smoking his pipe in the sun overlooking his garden (it is worth noting [parenthetically] that smoking is itself associated with skeletal muscle dysfunction6). Dwarves and wizards smoke too, and the production of smoke rings is unfortunately glamourised. The hobbit diet is clearly varied as he is able to offer cake, tea, seed cake, ale, porter, red wine, raspberry jam, mince pies, cheese, pork pie, salad, cold chicken, pickles and apple tart to the dwarves who visit to engage him in the business of burglary. The dwarves also show evidence of a mixed diet and, importantly, although they “like the dark, the dark for dark business”, they do spend much time above ground and have plenty of sun exposure during the initial pony ride in June that begins their trip to the Lonely Mountain.

Sun avoidance is a recurring theme among the evil characters. The trolls the party encounter shun the sunlight to avoid the petrification to which they eventually succumb and have been living on an exclusively mutton diet. They are certainly strong but undeniably stupid, and consuming jugs of “good drink” has further befuddled their wits.

Gollum, himself “as dark as darkness” lives in the dark, deep in the Misty Mountains. He does, however, eat fish, although the text describes these only as “blind” and it is not clear whether they are of an oily kind and thus a potential source of vitamin D. He sometimes eats goblins, but they rarely come down to his lake, suggesting that fish play little part in the goblin diet. Interestingly, these occasional trips to catch fish are undertaken at the behest of the Great Goblin, leading one to speculate that his enhanced diet may have helped him to achieve his pre-eminent position within goblin society. In due course, the Great Goblin is replaced by the Son of the Great Goblin. While simple nepotism is a likely explanation, we are unable to exclude an epigenetic process whereby the son’s fitness to rule has been influenced by parental vitamin D exposure.

Goblins’ aversion to sunlight includes bringing a huge cloud of bats to accompany their army on the march. Like the Spartans at the Battle of Thermopylae, they expect to gain some advantage from fighting in the shade.7 However, despite their numbers, the goblins are defeated by their enemies. At the Battle of Five Armies, the strongest goblins are defeated by Beorn, a vegetarian who can assume the shape of a bear. His diet is largely cream and honey, but he spends much time outdoors.

Wood elves linger “in the twilight of our sun and moon”, feasting merrily in clearings in the woods. They seem to be less potent than the high elves, perhaps because of their crepuscular habits, but their cave is described as “lighter and more wholesome” than goblin dwellings. Few details are given about their diet, but roast meat is involved, and butter and apples are brought to them by the river, as is wine.

Spiders dwell in the dark and seem to eat caught prey exclusively. The dragon Smaug comes out at night to eat people and particularly favours maidens, though he will also eat ponies and Lake-men.

The dietary and sun-exposure habits of the protagonists are shown in the Box. The mean vitamin D score was significantly higher among the victorious (mean, 3.4; SD, 0.5) than the non-victorious (mean, 0.2; SD, 0.4; P < 0.001). However, the absolute concordance between goodness and victoriousness precludes an assessment of this as an independent effect.

Discussion

Systematic textual analysis of The hobbit supports our initial hypothesis that the triumph of good over evil may be assisted to some extent by the poor diet and lack of sunlight experienced by the evil characters.

For the purpose of this study, we have not discriminated between creatures that can be considered, broadly speaking, to be mammalian and those that are not and whose physiology is more obscure. These include dragons, whose generation of fire has been discussed previously,8 as well as giant spiders and birds of unusual size.

Unfortunately, the principal purpose of the author of The hobbit was not to provide a systematic dietary history, so reporting bias is a possibility. In particular, there is an emphasis in the text on meat items similar to Homer’s Odyssey, where feasting is a recurrent motif but where few references to salad are made.

More research would be needed to establish whether the results of the current pilot investigation are representative of the wider Tolkien corpus and indeed of fantastic literature in general, although this will need to be balanced against the problems of proportionality of effort. A further limitation is that the concordance of dark-dwelling and evil make it more difficult to infer causation from the current data. Further reviews of the literature will need to focus on more morally ambiguous tales to elucidate this further, and the outcome of well constructed randomised controlled intervention studies may need to be imagined.

Characteristics of inhabitants of Middle Earth

Inhabitants

Good

Victorious

Vitamin D score

Hobbits

Yes

Dwarves

Yes

Beorn

Yes

Men

Yes

High elves

Yes

Wood elves

Yes

Eagles

Yes

Smaug the dragon

Trolls

Goblins

Gollum

Vitamin D and tuberculosis

There is little evidence to suggest that vitamin D has any therapeutic effect in treating tuberculosis

Before antimycobacterial medicines were introduced (around 1950), the best support for patients with tuberculosis (TB) appeared to be sunshine. For TB patients who needed bed rest, sun-facing balconies in sanatoria were considered to be more therapeutic than the usual dark hospital wards. In 1904, William Osler noted that rabbits inoculated with tubercle bacilli succumbed rapidly if kept in the dark, but not in the open air. He advised patients treated at home to have as many hours as possible in the sunshine. Cod liver oil was also used — a large controlled trial at the Brompton Hospital, London in 1848 showed clear benefit of cod liver oil in treating pulmonary consumption.1

However, sunlight is our major source of vitamin D and cod liver oil is rich in vitamin D3 (5 g oil provides 10 μg, the recommended daily intake for most adults). So can vitamin D help prevent or treat TB?

In the past 15 years, there has been a surge of research interest in whether vitamin D can be a protective influence in a range of diseases — notably, type 1 diabetes, multiple sclerosis, colorectal cancer, psoriasis and TB.2

The vitamin D receptor has been found in many different types of cells, including T and B lymphocytes, monocytes and macrophages, and respiratory epithelial cells. Most of these cells also express the enzyme that can make the active 1,25-dihydroxyvitamin D internally. In cell culture, macrophages exposed to vitamin D produce antimicrobial activity against intracellular Mycobacterium tuberculosis by induction of the peptide cathelicidin LL-37.3

In this issue of the Journal, MacLachlan and Cowie suggest that the seasonal incidence of TB in Australia (highest in October to December) is partly determined by differences in ultraviolet radiation exposure and subsequent vitamin D synthesis.4 In south-eastern Australia, serum 25-hydroxyvitamin D (25-OHD) levels are at their lowest in September.5 In Cape Town, at the same latitude as Sydney (33°S), TB notifications peak at the same time of the year, about 2 months after the lowest annual measured levels of 25-OHD. In the northern hemisphere, TB notifications peak in the United Kingdom at the opposite time of the year (March to May) and also in late spring (in reverse to the incidence times for other respiratory diseases). MacLachlan and Cowie report that TB notifications in Australia show a stronger seasonal pattern in the southern states.4 In contrast, in the United States, Willis and colleagues, although noting a seasonal pattern in new cases of TB, did not find an association between latitude and new TB cases (ie, TB notifications were not higher in the northern states compared with the southern states).6

A case–control study found that isoniazid and rifampicin reduced serum 25-OHD levels in patients with TB.7 To exclude this possible drug effect, Nnoaham and Clarke reviewed studies in which culture-positive TB patients had not yet started antimycobacterial treatment and found that in six of seven studies, patients had significantly lower 25-OHD levels.8 Talat and colleagues noted that in a cohort of household contacts of TB patients, those with low 25-OHD levels had a greatly increased risk of progression to active TB; however, this was only a small prospective study.9

Randomised controlled trials of vitamin D need to be carried out alongside antibacterial medications and the possibility of coexistent HIV infection. A trial in Guinea-Bissau did not show benefit;10 however, the trial may have used vitamin D doses that were too low to be effective. In a large UK trial,11 time to reach negative sputum culture averaged 36 days with vitamin D and 43.5 days with antimycobacterial agents alone (not significant). When analysed by genotypes of vitamin D receptor, adding vitamin D significantly hastened sputum culture conversion in patients with the TT genotype (only 10% of all patients). Based on the same trial, with additional data, among the 76% of the original patients who fulfilled criteria for per-protocol analysis, vitamin D was found to accelerate sputum smear conversion in all vitamin D receptor genotypes and, from differences in haematology and cytokines, appeared to enhance the anti-TB therapy.12

To summarise, available evidence suggests that low vitamin D levels increase the risk of reactivation of TB. However, there is relatively little evidence to support a clinically meaningful therapeutic effect alongside present anti-TB chemotherapy.

Vitamin D and tuberculosis: hope or hype?

It may be worthwhile to test for and treat vitamin D deficiency in latent infection, but not in active TB

In this issue of the Journal, MacLachlan and Cowie advocate increased testing of vitamin D (serum
25-hydroxyvitamin D [25-OHD]) for people with risk factors for vitamin D deficiency and tuberculosis (TB).1 This pertinent suggestion is based on the assumption that vitamin D deficiency is a risk factor for progression from latent to active TB, and that correction of deficiency could reduce this risk (the demonstration by MacLachlan and colleagues2 of TB seasonality in Australia is consistent
with this hypothesis). The proposal presents a timely opportunity to scrutinise evidence of an association between vitamin D deficiency and TB, temper the high hopes that vitamin D might be an important adjunctive treatment for active TB, and remind clinicians about problems with testing and interpreting 25-OHD levels.

Many communicable diseases are seasonal — for example, influenza, rotavirus and TB. But many potential risk factors are also seasonal — temperature, time spent indoors, household crowding, humidity, ultraviolet radiation (which has immunological effects independent of vitamin D),3 incidence of co-infections, and, potentially, nutritional intake. An important maxim to remember when interpreting the literature showing associations between vitamin D and seasonality — and a wide range
of conditions from cancer to cardiovascular disease, schizophrenia to bacterial vaginosis — is that, as MacLachlan and Cowie point out, correlation does
not imply causation.1

We know that serum 25-OHD levels are low in active TB.3 What might be the explanation? One hypothesis
is that it is appropriately low due to conversion to
1,25-dihydroxyvitamin D (activated vitamin D [calcitriol]). Indeed, calcitriol, an important factor in human innate antimycobacterial immunological responses,4,5 has
been found to be elevated in active TB.6 Also, 25-OHD concentration can spontaneously recover over time with TB treatment,3 but has been shown to fall during TB immune restoration syndrome,7 suggesting that low
25-OHD concentration could be a consequence of immunological activation (a negative acute phase reactant). Further data are needed; there may be
many factors accounting for low 25-OHD levels in
active TB, and the relationship could be bidirectional.

There is increasing evidence that in high TB-burden settings — using doses considered safe for programmatic deployment where calcium, 25-OHD or calcitriol levels cannot readily be measured — vitamin D supplementation in active TB is not beneficial for TB outcomes.8,9 The situation may be different in well resourced settings, where management of TB and underlying conditions (HIV, diabetes and, possibly, vitamin D deficiency) can be individually tailored. Using high vitamin D doses in a well resourced, monitored setting is generally safe10 (but not always)11 and may confer more rapid sputum smear conversion time.12 In a small subset of TB patients with
a specific vitamin D receptor genotype and low mean baseline 25-OHD concentration, it may be associated
with faster sputum culture conversion.10 Two other trials
of vitamin D supplementation for active TB have been published, but methodological issues impair the ability
to draw firm conclusions.13,14 A further article has been submitted for publication. A meta-analysis is needed —
it would probably conclude that supplementary vitamin D is not helpful in active TB overall, but may benefit some outcomes in a selected minority of patients. However, treating vitamin D deficiency in patients with TB may be relevant for non-TB end points.

Contrastingly, MacLachlan and Cowie are advocating a test-and-treat strategy for vitamin D status before active TB development. This makes immunological sense.4,5 The single prospective study examining risk of progression to active TB after exposure found that seven of 30 people with serum 25-OHD levels < 17 nmol/L developed TB, but that only one of 64 people with 25-OHD levels ≥ 17 nmol/L did so.15 Other factors may have explained both the profoundly low 25-OHD levels and increased TB risk; nevertheless, in light of the accumulating evidence, maintenance of latency appears to be the most appropriate stage of infection to target with a vitamin D intervention.16 However, since the 25-OHD concentration associated with TB reactivation in the above study was quite low (< 17 nmol/L), the impact of correcting all cases of vitamin D deficiency (< 50 nmol/L) on TB incidence at the population level may be small. A prospective study
of vitamin D replacement in latent TB would help in improving the evidence base for the association between vitamin D deficiency and TB. However, clinical trials in this field are challenging to conduct, due to the large sample sizes required, the fact that tests for latent TB (relying on immunological responses) may themselves be influenced by vitamin D status, and because correction of deficiency would need to show benefits over and above recognised latent TB treatments (eg, isoniazid preventive therapy and HIV treatment). This raises the question of whether we need to await randomised controlled trial evidence before making a public health recommendation. Given the potential benefits of correction of vitamin D deficiency independent of TB risk, MacLachlan and Cowie’s recommendation seems reasonable.

Notably, promotion of 25-OHD testing coincides with the Royal College of Pathologists of Australasia calling for restraint.17 They recommend measurement of 25-OHD in people with listed risks or clinical/laboratory evidence of deficiency only,17 as MacLachlan and Cowie advocate. A reason for restraint in ordering a 25-OHD test is that many widely used automated assays can lack accuracy and reproducibility.3,17 Clinicians need to understand the test’s limitations, including that different methods may give different results.17 Liquid chromatography–tandem mass spectrometry has better performance characteristics, but is less widely available and results are user-dependent.

It is becoming popular to routinely test 25-OHD in people with active TB. Based on the information above, this is misplaced, since not all patients with TB have vitamin D deficiency risk factors, there is potential for spontaneous recovery of low 25-OHD levels in active TB, and correction of low 25-OHD levels appears to be non-beneficial for TB outcomes.

Finally, to address the contentious issue of vitamin D reference intervals — these are unusual among laboratory assays, being no longer based on normal population data. The lower limit of normal has gradually crept up from 25 nmol/L to 75 nmol/L or higher.3 Inevitably, increasing proportions of the population are therefore now “deficient”. Although this move is motivated by concerns for bone health, the appropriateness of such targets requires scrutiny. Recent reviews conclude that most (> 80%) of the potential benefits of vitamin D for a range of diseases are achieved with 25-OHD levels around 50 nmol/L, with only marginal additional gains for higher levels.18 Further, there appears to be an upper safety limit which, although still poorly defined, should be recognised. U-shaped curves of disease risk in relation to 25-OHD concentration are reported for mortality (cancer, cardiovascular and all-cause) and active TB likelihood, with risks increasing at 25-OHD levels above 80–140 nmol/L.19–21 Popular advice promoting high target levels (eg, 125 nmol/L22) is unhelpful and potentially risky.

In summary, we support appropriately targeted testing and treatment of vitamin D deficiency, bearing in mind assay limitations and the implausibility of some proposed 25-OHD targets. Any effect that this strategy would have on risk of progression from latent to active TB remains hypothetical. Given that vitamin D deficiency is an easily preventable problem requiring a high index of suspicion, it is sensible to promote testing in at-risk groups. Correcting deficiency after the horse has bolted (after development of active TB) appears to be too late to have appreciable effects on TB outcome. 25-OHD deficiency detected at the time of active TB diagnosis may be self-limiting; a better assessment of vitamin D status might be gained by deferring testing for 2 months after treatment initiation, when the inflammatory milieu has subsided. More prospective studies of TB-exposed people would help answer the persisting question of the relationship between vitamin D deficiency and failure of latency. However, ethical considerations generally prohibit such studies if they exclude interventions to correct vitamin D deficiency or treat latent TB. In the meantime, further exploration of why 25-OHD levels are low in people with active TB will help answer this question.

Amanita phalloides poisoning and treatment with silibinin in the Australian Capital Territory and New South Wales

To the Editor: Roberts and colleagues recently reviewed the frequency and clinical outcomes of poisoning with Amanita phalloides (“deathcap”) mushrooms in the Australian Capital Territory and New South Wales.1 Two widely publicised cases of fatal ingestion occurred on 31 December 2011 after a chef had prepared a meal containing wild mushrooms for his colleagues in the kitchen of an ACT restaurant. The link with the restaurant was only discovered after emergency department staff notified public health authorities, who then interviewed unaffected associates of the index case. It was fortunate that no wild mushrooms were used to prepare food for the public. Material at the restaurant was inspected by the public health unit and destroyed to ensure no Amanita mushrooms entered the food supply.

However, the potential for a cluster of poisonings to occur, for people to be in the early stages of toxicity, and for uneaten mushrooms to pose an ongoing risk to food safety should be considered when a sentinel clinical case of poisoning occurs. Because acutely unwell patients may not provide a thorough account of who consumed wild mushrooms, public health units must seek out contacts to clarify the extent of exposure. The ultimate goal of public health programs is to prevent people collecting and eating the deadly A. phalloides mushroom. But, should poisoning occur, a potential public health emergency may arise. ACT Health has now formalised reporting of cases to the relevant public health unit in the protocol for managing cases of poisoning. Public health messaging has also been strengthened and targeted at high-risk groups.

Reinforcing the iodine message for pregnant women in Australia

To the Editor: The recently released clinical practice guidelines
on antenatal care,1 which have been endorsed by the National Health
and Medical Research Council, recommend nutritional supplementation with 500 μg/day
of folic acid, from 12 weeks before conception and for the first trimester, and 150 μg/day of iodine throughout pregnancy. This recommendation recognises that, despite the introduction in 2009 of mandatory fortification of bread with both iodine and folic acid, fortification does not meet the increased needs of pregnant and lactating women. Urinary iodine concentrations of pregnant women improved after the introduction of the iodine fortification program; however, a study in regional New South Wales found that only those women who were taking iodine-containing supplements had urinary concentrations indicating sufficiency (≥ 150 μg/L).2

A series of cross-sectional studies
of women attending a major public antenatal clinic in a regional area of NSW has consistently shown suboptimal dietary practices and knowledge, particularly with regard to the iodine requirements for optimal neurocognitive development of the fetus.2,3 While supplement use has increased from 59% in 2008 to 71%–77% in 2011–2012, only 20% of women in 2008 and 60%–66% in 2011–2012 were taking supplements containing iodine. We do not know why up to 40% of women are still
not taking recommended iodine supplements, but we surmise that women are not being informed about the need for supplementation by their antenatal care providers, despite there being written advice on supplements in the publication from NSW Health, Having a baby, which is provided in public health facilities statewide.4

We acknowledge that data on nutritional supplementation in pregnancy may differ in other states, and that nationally representative data are required, but we are not aware of any state or national campaign to promote iodine supplementation during pregnancy and breastfeeding.

Clearly, better service delivery models are required to ensure consistent messages about nutritional supplements are provided by all health care professionials. New data from Tasmania have shown for the first time in Australia that mild iodine deficiency during pregnancy is associated with reduced educational outcomes in children born to mothers with this deficiency (decreased performance in the NAPLAN [National Assessment Program — Literacy and Numeracy] of up to 10%).5 Similarly, in the United Kingdom, mild maternal iodine deficiency has been shown to result in decreased IQ in the offspring.6 It is indefensible that women of reproductive age, and especially pregnant women, are not being adequately informed about the need for iodine supplementation to prevent irreversible neurodevelopmental effects in their children. The time has come for a national public health education and supplementation program to ensure iodine requirements are met for all, not just
a few, women of childbearing age.

Inequalities in bariatric surgery in Australia: findings from 49 364 obese participants in a prospective cohort study

To the Editor: On behalf of the Medical Technology Association of Australia, we would like to commend the findings of Korda and colleagues on the inequalities in patient access to bariatric surgery in Australia.1

One issue that can be identified in the study is the inclusion of individuals with body mass index (BMI) in the range of 30–34 kg/m2. It is clinically accepted worldwide that individuals with BMI ≥ 30 kg/m2 are classified
as obese. However, according to Australian clinical guidelines and other clinical guidelines, bariatric surgery is recommended for individuals with morbid obesity (BMI ≥ 40 kg/m2) or with BMI 35–40 kg/m2 and comorbid conditions.2,3 Therefore, including only those individuals considered to “need” bariatric surgery would allow for more accurate findings in showing inequalities in patient access to bariatric surgery.

We agree with the finding that bariatric surgery is mostly taken up
by those who have private health insurance and who can afford the out-of-pocket costs associated with the procedure.4 In the past decade, there has been a significant increase Australia-wide in the number of bariatric surgeries performed, which is in line with the sharp increase in the prevalence of obesity (and morbid obesity) in recent years in Australia.5

The study by Korda and colleagues highlights the presence of inequalities in patient access to bariatric surgery. With the growing prevalence of obesity (including morbid obesity) in Australia, especially in those living in areas of lower socioeconomic status, improving access should be a priority health commitment.6

Prevalence and perceptions of overweight and obesity in Aboriginal and non-Aboriginal young people in custody

Incarcerated youth are one of the most disadvantaged population groups.1,2 Compared with their community peers, they have a higher prevalence of risk factors for chronic disease, including alcohol misuse, smoking, mental illness, Aboriginality and lower socioeconomic status.1 In 2010, almost a quarter of Australians aged 14–17 years were overweight or obese, and 6% were obese.3,4

A recent review highlighted the disparities in weight, physical activity and nutrition between incarcerated adults and the general population,5 but no studies have examined these factors in incarcerated young people. In Australia, New South Wales incarcerates the highest numbers of youths, half of whom are from Aboriginal backgrounds,1,2 a 17 times over-representation of Aboriginal youth in NSW custody.1 Metabolic syndrome and metabolic abnormalities are commonly associated with use of psychotropic medications6 and are found in up to a third of young patients treated for their first episode of psychosis.7,8 Almost 80% of incarcerated young people meet criteria for a lifetime mental health disorder (compared with 10% of 15–19-year-olds in the community), and a fifth are prescribed psychotropic medication.1,9 There are also racial, sex and age differences in the self-perception of weight.10 In addition, overweight and obese young people, particularly young men, underestimate their weight status.11,12 These factors can make weight control among incarcerated young people extremely challenging.

We aimed to examine measured and self-perceived weight status of incarcerated Aboriginal and non-Aboriginal young people in NSW, and determine sociodemographic, custodial and other risk factors associated with overweight and obesity at baseline and with self-perceived weight gain over 12 months of follow-up.

Methods

We conducted a prospective cohort study in eight juvenile justice centres and one high-security juvenile correctional centre, for the 2009 NSW Young People in Custody Health Survey.1 Data were collected at baseline and at 3, 6 and 12 months. Informed consent was provided by participants and/or their carers. Ethics approval was obtained from the Justice Health Human Research and Ethics Committee, Juvenile Justice Research Steering Committee, Corrective Services Ethics Committee (Corrective Services NSW) and Aboriginal Health and Medical Research Council Ethics Committee.

All young people in custody between August and October 2009 were invited to participate. Exclusion criteria included insufficient English language skills and being unavailable due to work or court commitments. Participants were followed up in custody (face-to-face or by telephone) or in the community (by telephone).

Anthropometric measurements

At baseline, height and weight measurements were used to calculate body mass index (BMI), which was used to categorise participants as underweight, healthy weight, overweight or obese. International paediatric definitions of BMI were used for participants aged ≤ 18 years,13 and adult definitions for those > 18 years.14 A non-extensible steel tape was used to measure waist circumference at the narrowest point between the lower costal border and iliac crest. Waist-to-height ratio (WHtR) was used to categorise participants as low metabolic risk (< 0.5) or increased metabolic risk (≥ 0.5).15,16

Self-perceived weight was determined by asking “how do you describe your weight?”, “how has your weight changed since being in custody?” and “what are you trying to do about your weight?” At each follow-up, participants were asked whether they felt their weight had increased, stayed the same or decreased since the previous occasion on which data were collected.

Risk factors

Participants completed a baseline questionnaire that was administered face-to-face. Aboriginality was determined by asking “are you of Aboriginal and/or Torres Strait Islander origin?” Postcode of usual residence was used as a proxy measure of socioeconomic status based on the Australian Bureau of Statistics Index of Relative Socio-economic Advantage and Disadvantage (IRSAD).17 IRSAD scores were categorised according to quintiles, with first and second quintiles indicating higher disadvantage.

Alcohol consumption in the year before entering custody was measured using the Alcohol Use Disorders Identification Test, with a score ≥ 8 indicating harmful alcohol use.18 To identify participants at higher cardiovascular risk, daily smoking was defined as smoking ≥ 10 cigarettes/day in the year before entering custody. Exercise levels were measured by asking “before custody, how often did you usually play sport or do exercises?” and “in the past 2 weeks, how often have you exercised or played sport or games that made you sweat and breathe hard?” Questions on diet before and since incarceration were adapted from standardised national health surveys of children and youth.19,20

Lifetime psychological disorders were assessed using the Schedule for Affective Disorders and Schizophrenia for Children — Present and Lifetime Version (KSADS-PL) 2009 Working Draft.21 Participants self-reported current psychotropic medication use, out-of-home care and age of first care placement. Time spent incarceration, at each occasion on which data were collected, was calculated through data linkage to the Juvenile Justice NSW and Corrective Services NSW databases.

Analysis

Participants with complete anthropometric measures were included in the analysis (SPSS version 19; SPSS Inc) and data were stratified by Aboriginality. We used χ2 analyses to compare categorical independent variables and t tests for continuous independent variables. Logistic regression was used to determine the association of risk factors for overweight and obesity at baseline and for self-perceived weight gain at follow-up, adjusted for age, sex, IRSAD quintiles and other confounders. P values < 0.05 were considered significant. “Final follow-up” was defined as the last follow-up for each participant.

Results

At baseline, 452 youths were incarcerated, 382 (84.5%) were eligible to participate, 361 (79.9%) consented to participate and 303 (67.0%) had complete anthropometry measurements taken (83.9% of those who consented) (see Appendix). There were no significant differences in age, sex, socioeconomic status or Aboriginality between participants and non-participants. At 3, 6 and 12 months, there were 231 (76.2%), 158 (52.1%) and 143 (47.2%) participants, respectively.

Most participants were male (87.1%), 50.2% were from areas of higher socioeconomic disadvantage, 49.8% were Aboriginal and 27.7% had been placed in out-of-home care before 16 years of age (Box 1). Most had at least one lifetime psychological disorder at baseline (78.4%) and 20.7% were taking psychotropic medications at baseline. Most smoked ≥ 10 cigarettes/day (76.7%) and consumed harmful levels of alcohol (77.9%) in the year before entering custody. Compared with non-Aboriginal participants, Aboriginal participants were significantly younger, were more likely to have been in care as a child and to have used harmful levels of alcohol, and were less likely to have been in custody for > 12 months at baseline.

Time already spent incarcerated at baseline was < 3 months for 47.9% participants, 3–12 months for 34.7% and > 12 months for 17.5%. Accumulated incarceration time at final follow-up was < 3 months for 28.1%, 3–12 months for 41.3% and > 12 months for 30.7%.

At baseline, 47.9% of all young people were either overweight or obese, 37.0% had an increased metabolic risk according to WHtR, and 1.0% were underweight (Box 2). However, only 24.1% reported feeling overweight and 20.4% reported feeling underweight. Compared to non-Aboriginal participants, Aboriginal participants were more likely to report feeling the right weight (P = 0.03). Overall, 37.6% were trying to gain weight at baseline and 27.5% were trying to lose weight. Since incarceration, 71.6% perceived a weight increase and 10.2% perceived a weight decrease. At each follow-up, about a third to a half of young people perceived a weight increase, and about a quarter perceived a weight decrease.

Before incarceration, participants’ diets were poor: low intake of fruit and vegetables; high intake of energy-dense, nutrient-poor foods; and high intake of sugar-sweetened beverages (Box 3). Aboriginal participants were more likely to drink cordial (P= 0.04). Daily exercise was reported by 35.1% of participants before incarceration. Since incarceration, diets improved significantly, but cordial consumption increased (P < 0.001). Daily exercise increased significantly (P < 0.001).

Increased metabolic risk, according to WHtR, was strongly associated with overweight or obesity at baseline for the whole group (adjusted odds ratio [AOR], 23.86; P < 0.001), with a particularly strong association for Aboriginal participants (AOR, 37.39; P < 0.001) (Box 4). Aboriginal participants trying to lose weight at baseline were six times more likely to be overweight or obese (AOR, 5.79; P < 0.001) compared with those not trying to lose weight. Aboriginal participants who had already spent > 12 months incarcerated at baseline were seven times more likely to be overweight or obese compared with those incarcerated for shorter periods (AOR, 6.92; P < 0.001).

Non-Aboriginal participants who had been placed in care before 16 years of age were four times more likely to have a self-perceived weight gain at follow-up compared with those who had not been in care as a child (AOR, 4.21; P= 0.04) (Box 5). Non-Aboriginal participants with an accumulated incarceration time of ≥ 12 months at follow-up were three times more likely to perceive weight gain compared with those incarcerated for shorter periods at follow-up (AOR, 2.79; P = 0.04). Young people who felt overweight at baseline had less than half the risk of self-perceived weight gain at follow-up (AOR, 0.44; P = 0.01).

Discussion

Incarcerated young people in NSW are at high risk of chronic disease. In our study, almost half were overweight or obese at baseline, and over a third had increased metabolic risk measured by WHtR. A WHtR of ≥ 0.5 was strongly associated with overweight or obesity in Aboriginal participants, confirming this as a useful marker of increased metabolic risk in Aboriginal youths. These are almost twice the rates of overweight, obesity and increased metabolic risk for adolescents in the Australian community,3,22 higher than rates seen in young NSW offenders on community orders,23 and higher than rates in young men incarcerated in Australian adult prisons (where food is individually rationed), in whom overweight and obesity rates are similar to or lower than community rates.5 Three-quarters of young people reported weight gain since being incarcerated, and those who spent a longer time in custody were more likely to report weight gain or be overweight or obese. This suggests that juvenile incarceration is obesogenic, particularly for Aboriginal youth, further increasing their higher background risk of chronic disease.22

Participants tended to underestimate their weight status, especially those who were Aboriginal, and many healthy weight and overweight youths wanted to gain weight. This desire for weight gain might be a normal expectation in younger men, and there may have been some ambiguity in the interpretation of “gaining weight”, but underestimation of weight status in adolescents has been shown in other studies.10–12 Despite inaccuracies in self-perceived weight status, Aboriginal young people who reported trying to lose weight at baseline were very likely to be overweight or obese. Those who reported feeling overweight may have been the most receptive to advice on weight control, as these participants were half as likely to report further weight gain at follow-up.

Incarceration is likely to be a proxy for obesity risk factors not measured in this study. There were improvements in diet and exercise for these young people when incarcerated, but, unlike adult prison where each individual receives a daily ration,24 juvenile custodial centres supplement breakfast and dinner with liberal access to bread and butter, and allow multiple helpings of meals. Despite drinking more water, participants drank more cordial during incarceration, probably because soft drinks were not readily available. An increase in daily exercise in custody is counterbalanced by daily “lock-downs” to accommodate staff changes and address security concerns, and many youths sleep during this time. Sport is compulsory and incentivised (“no sport, no points”), but points can be used to purchase energy-dense, nutrient-poor snacks and beverages.

Low intensity physical activity is a strong appetite stimulant,25 so it is likely that incarcerated youths are very hungry at meal times, when they have liberal access to food (in contrast to possibly more restricted access at home). This might explain why those with a history of being in out-of-home care (ie, inconsistent parenting) perceived weight gain at follow-up. These young people have poor track records of self-discipline and impulse control, and some have a tendency to hoard food due to previous scarcity, or because all other privileges have been removed in custody. Despite a lack of association between overweight and obesity and psychological disorders and psychotropic medication use, these relationships need further investigation with prospective measurements of medication type, doses and compliance. Supervision of psychotropic medication use in juvenile custody might lead to better compliance, resulting in weight gain.

This is the first study to document the high prevalence of overweight, obesity and increased metabolic risk in incarcerated young people. Youth incarceration should present opportunities to improve lifestyle and to encourage appropriate weight control measures. From a population health and policy perspective, the current liberal food environment needs to change and approaches to increasing physical activity beyond sport are needed.

1 Sociodemographic and incarceration characteristics by Aboriginality

	Number (percentage)*
	Total (n = 303)	Non-Aboriginal (n = 152)	Aboriginal (n = 151)

Mean age, years (SD)	17.1 (1.5)	17.4 (1.5)	16.7 (1.4)†
Age range, years	13–21	13–21	13–20
Age < 18 years	224 (73.9%)	96 (63.2%)	128 (84.8%)†
Male	264 (87.1%)	133 (87.5%)	131 (86.8%)
Placed in out-of-home care before 16 years of age‡	82 (27.7%)	27 (17.9%)	55 (37.9%)†
Higher socioeconomic disadvantage§	152 (50.2%)	74 (48.7%)	78 (51.7%)
Harmful alcohol use before incarceration‡	222 (77.9%)	99 (71.7%)	123 (83.7%)†
Smoking ≥ 10 cigarettes/day before incarceration‡	194 (76.7%)	98 (81.0%)	96 (72.7%)
Lifetime psychological disorder at baseline‡	210 (78.4%)	103 (75.2%)	107 (81.7%)
Current psychotropic medication use at baseline‡	61 (20.7%)	27 (18.0%)	34 (23.6%)
Time already spent incarcerated at baseline
< 3 months	145 (47.9%)	59 (38.8%)	86 (57.0%)
3–12 months	105 (34.7%)	56 (36.8%)	49 (32.5%)
> 12 months	53 (17.5%)	37 (24.3%)	16 (10.6%)†
Cumulative time incarcerated at final follow-up
< 3 months	86 (28.4%)	48 (31.6%)	38 (25.2%)
3–12 months	124 (40.9%)	53 (34.9%)	71 (47.0%)
> 12 months	93 (30.7%)	51 (33.6%)	42 (27.8%)

* Data are number (percentage) unless otherwise specified. † Significantly different (P < 0.05) compared with non-Aboriginal participants. ‡ Data do not total 303. § Index of Relative Socio-economic Advantage and Disadvantage score in quintile 1 (high disadvantage) or 2 (mid disadvantage).

2 Weight characteristics by Aboriginality

	Number (percentage)
	Total (n = 303)	Non-Aboriginal (n = 152)	Aboriginal (n = 151)

Baseline weight characteristics
Body mass index category
Underweight	3 (1.0%)	2 (1.3%)	1 (0.7%)
Healthy weight	155 (51.2%)	70 (46.1%)	85 (56.3%)
Overweight	98 (32.3%)	50 (32.9%)	48 (31.8%)
Obese	47 (15.5%)	30 (19.7%)	17 (11.3%)
Overweight or obese	145 (47.9%)	80 (52.6%)	65 (43.0%)
Waist-to-height ratio category
Low metabolic risk (< 0.5)	191 (63.0%)	91 (59.9%)	100 (66.2%)
Increased metabolic risk (≥ 0.5)	112 (37.0%)	61 (40.1%)	51 (33.8%)
Self-perceived weight*
Slightly or very underweight	61 (20.4%)	32 (21.2%)	29 (19.6%)
About the right weight	166 (55.5%)	73 (48.3%)	93 (62.8%)†
Slightly overweight	55 (18.4%)	37 (24.5%)	18 (12.2%)
Very overweight	17 (5.7%)	9 (6.0%)	8 (5.4%)†
Self-perceived weight change since incarcerated*
Increased a little or a lot	154 (71.6%)	78 (69.6%)	76 (73.8%)
Stayed the same	39 (18.1%)	20 (17.9%)	19 (18.4%)
Decreased a little or a lot	22 (10.2%)	14 (12.5%)	8 (7.8%)
What participants are trying to do about weight*
Lose weight	82 (27.5%)	48 (32.0%)	34 (23.0%)
Gain weight	112 (37.6%)	48 (32.0%)	64 (43.2%)
Stay the same	40 (13.4%)	24 (16.0%)	16 (10.8%)
Not trying to do anything	64 (21.5%)	30 (20.0%)	34 (23.0%)
Follow-up self-perceived weight status*
Increased a little or a lot
3-month follow-up	97 (42.0%)	44 (38.3%)	53 (45.7%)
6-month follow-up	59 (37.3%)	31 (37.3%)	28 (37.3%)
12-month follow-up	68 (47.6%)	34 (46.6%)	34 (48.6%)
Stayed the same
3-month follow-up	83 (35.9%)	46 (40.0%)	37 (31.9%)
6-month follow-up	59 (37.3%)	32 (38.6%)	27 (36.0%)
12-month follow-up	43 (30.1%)	26 (35.6%)	17 (24.3%)
Decreased a little or a lot
3-month follow-up	51 (22.1%)	25 (21.7%)	26 (22.4%)
6-month follow-up	40 (25.3%)	20 (24.1%)	20 (26.7%)
12-month follow-up	32 (22.4%)	13 (17.8%)	19 (27.1%)

* Data do not total 303. † Significantly different (P < 0.05).

3 Nutrition and exercise before incarceration and since being incarcerated, by Aboriginality

	Number (percentage)
	Before incarceration			Since incarcerated (at baseline)
	Total (n = 303)	Non-Aboriginal (n = 152)	Aboriginal (n = 151)	Total (n = 303)	Non-Aboriginal (n = 152)	Aboriginal (n = 151)

Foods eaten ≥ 3 times/week*
Breakfast	175 (58.3%)	79 (52.3%)	96 (64.4%)†	289 (96.3%)‡	144 (95.4%)	145 (97.3%)
Fresh fruit	128 (42.7%)	60 (39.7%)	68 (45.6%)	268 (89.3%)	139 (92.1%)	129 (86.6%)
Green salad	121 (40.3%)	61 (40.4%)	60 (40.3%)	193 (64.3%)	102 (67.5%)	91 (61.1%)
Fresh vegetables	168 (56.0%)	80 (53.0%)	88 (59.1%)	229 (76.6%)‡	116 (77.3%)	113 (75.8%)
Snacks§	214 (71.3%)	104 (68.9%)	110 (73.8%)	122 (40.7%)‡	55 (36.4%)	67 (45.0%)
Takeaway food¶	226 (75.3%)	106 (70.2%)	120 (80.5%)†	43 (14.3%)	27 (17.9%)	16 (10.7%)
Milk	210 (70.5%)	101 (66.9%)	109 (74.1%)	283 (94.3%)‡	142 (94.0%)	141 (94.6%)
Preferred fluids when thirsty*
Water	156 (51.8%)	76 (50.3%)	80 (53.3%)	227 (75.4%)‡	115 (76.2%)	112 (74.7%)
Soft drink	132 (43.9%)	66 (43.7%)	66 (44.0%)	15 (5.0%)‡	4 (2.6%)	11 (7.3%)
Fruit juice	52 (17.3%)	26 (17.2%)	26 (17.3%)	32 (10.6%)‡	15 (9.9%)	17 (11.3%)
Cordial	73 (24.3%)	29 (19.2%)	44 (29.3%)†	134 (44.5%)‡	65 (43.0%)	69 (46.0%)
Daily exercise*	104 (35.1%)	46 (30.9%)	58 (39.5%)	175 (58.5%)‡	80 (53.0%)	95 (64.2%)†

* Data do not total 303. † Significantly different (P < 0.05) between Aboriginal and non-Aboriginal groups. ‡ Significantly different (P < 0.05) between before incarceration and since being incarcerated. § Includes potato chips and crisps, biscuits, cakes, chocolate. ¶ Includes takeaway meals, hamburgers, meat pies, sausage rolls.

4 Associations with overweight and obesity at baseline by Aboriginality

Aboriginal (n = 151)

Non-Aboriginal (n = 152)

Total (n = 303)

Risk factor

OR (95% CI)

AOR (95% CI)

OR (95% CI)

AOR (95% CI)

OR (95% CI)

AOR (95% CI)

Male

0.45 (0.17–1.18)

—

1.11 (0.42–2.97)

—

0.71 (0.36–1.40)

—

Aboriginal

0.69 (0.44–1.08)

—

Age < 18 years

0.52 (0.21–1.29)

—

1.16 (0.60–2.25)

—

0.80 (0.48–1.33)

—

Placed in out-of-home care before 16 years of age

1.05 (0.54–2.09)

—

0.50 (0.21–1.18)

—

0.72 (0.43–1.21)

—

Daily exercise before incarceration

0.56 (0.28–1.11)

—

0.72 (0.36–1.45)

—

0.62 (0.38–1.00)

—

Daily exercise since incarcerated

0.75 (0.38–1.47)

—

0.71 (0.37–1.36)

—

0.70 (0.44–1.11)

—

Smoking ≥ 10 cigarettes/day before incarceration

1.33 (0.61–2.90)

—

1.44 (0.58–3.60)

—

1.41 (0.78–2.55)

—

Harmful alcohol use before incarceration

1.10 (0.45–2.66)

—

0.64 (0.30–1.36)

—

0.75 (0.43–1.32)

—

Lifetime psychological disorder at baseline

2.05 (0.79–5.35)

—

0.76 (0.35–1.66)

—

1.09 (0.61–1.96)

—

Psychotropic medication use at baseline

0.94 (0.43–2.05)

—

0.72 (0.31–1.67)

—

0.80 (0.45–1.41)

—

Increased metabolic risk according to WHtR at baseline

50.52
(14.34–177.94)*

37.39
(9.91–141.07)*

30.96
(10.22–93.84)*

17.28
(5.41–55.21)*

39.34
(17.13–90.32)*

23.86
(10.03–56.75)*

Self-perceived overweight at baseline

10.48
(3.39–32.40)*

2.08
(0.40–10.74)

10.56
(4.10–27.19)*

2.88 (0.82–10.21)

10.79
(5.24–22.19)*

2.54
(0.94–6.83)

Self-perceived weight gain since incarcerated

0.91
(0.38–2.20)

—

0.71
(0.32–1.62)

—

0.79
(0.43–1.44)

—

Trying to lose weight at baseline

13.09
(4.68–36.64)*

5.79
(1.37–24.39)†

7.88
(3.34–18.59)*

1.90
(0.57–6.38)

10.04
(5.21–19.35)*

3.13
(1.26–7.80)†

Already spent > 12 months incarcerated at baseline

4.64
(1.42–15.15)*

6.92
(1.66–28.84)*

2.31
(1.06–5.05)†

1.69
(0.59–4.84)

3.07
(1.62–5.81)*

2.93
(1.27–6.78)†

* P < 0.01. † P < 0.05. OR = crude odds ratio. AOR = adjusted odds ratio. na = not applicable. WHtR = waist-to-height ratio.

5 Associations with self-perceived weight gain at any follow-up by Aboriginality

Aboriginal (n = 130)

Non-Aboriginal (n = 129)

Total (n = 259)

Risk factor

OR (95% CI)

AOR (95% CI)

OR (95% CI)

AOR (95% CI)

OR (95% CI)

AOR (95% CI)

Male

1.73 (0.63–4.71)

—

1.20 (0.41–3.54)

–

1.47 (0.70–3.05)

—

Aboriginal origin

0.95 (0.58–1.56)

—

Age < 18 years

2.10 (0.83–5.34)

—

0.79 (0.39–1.62)

—

1.12 (0.65–1.93)

—

Placed in out-of-home care before 16 years of age

1.43 (0.69–2.96)

—

2.96 (1.10–7.99)†

4.21 (1.33–13.31)†

1.80 (1.03–3.16)†

2.22 (1.22–4.05)*

Daily exercise before incarceration

0.80 (0.39–1.65)

—

1.42 (0.65–3.09)

—

1.04 (0.62–1.76)

—

Daily exercise since incarcerated

1.24 (0.59–2.60)

—

0.76 (0.37–1.53)

—

0.94 (0.57–1.56)

—

Smoking ≥ 10 cigarettes/day before incarceration

1.00 (0.43–2.35)

—

1.01 (0.35–2.91)

—

1.03 (0.53–1.98)

—

Harmful alcohol use before incarceration

1.12 (0.44–2.89)

—

0.81 (0.36–1.85)

—

0.91 (0.50–1.68)

—

Lifetime psychological disorder at baseline

0.76 (0.29–2.01)

—

1.36 (0.58–3.17)

—

1.05 (0.56–1.98)

—

Psychotropic medication use at baseline

1.18 (0.52–2.66)

—

2.71 (1.01–7.33)†

3.37 (0.83–10.10)

1.66 (0.89–3.08)

—

Overweight or obesity at baseline

0.98 (0.49–1.97)

—

0.61 (0.30–1.25)

–

0.78 (0.48–1.28)

—

Increased metabolic risk according to WHtR at baseline

1.42 (0.67–3.00)

—

0.47 (0.23–0.96)†

0.61 (0.23–1.64)

0.80 (0.48–1.34)

—

Self-perceived overweight at baseline

0.50 (0.20–1.24)

—

0.40 (0.19–0.86)†

0.40 (0.14–1.17)

0.46 (0.26–0.81)†

0.44 (0.24–0.80)*

Self-perceived weight gain since incarcerated

1.22 (0.47–3.20)

—

1.75 (0.72–4.28)

—

1.45 (0.76–2.79)

—

Trying to lose weight at baseline

1.15 (0.51–2.60)

—

0.53 (0.25–1.12)

—

0.76 (0.44–1.33)

—

Spent > 12 months incarcerated at final follow-up (cumulative)

1.33 (0.63–2.83)

—

2.19 (1.04–4.58)†

2.79 (1.22–6.41)†

1.72 (1.02–2.92)†

1.83 (1.05–3.20)†

* P < 0.01. † P < 0.05. OR = crude odds ratio. AOR = adjusted odds ratio. na = not applicable. WHtR = waist-to-height ratio.

The impact of industry self-regulation on television marketing of unhealthy food and beverages to Australian children

Could recent initiatives in industry self-regulation be missing the mark?

Across the world, reports by reputable scientific organisations have concluded that food marketing influences the types of foods that children want to eat, children’s requests for food purchases and, ultimately, the foods that children consume.1 This type of evidence led to the National Preventative Health Taskforce’s recommendation to target food marketing to children as part of Australia’s strategy for tackling overweight and obesity.2

In 2009, industry groups introduced two voluntary initiatives to demonstrate their commitment to socially responsible marketing of foods to children: the Responsible Children’s Marketing Initiative (RCMI) and the Quick Service Restaurant Industry Initiative for Responsible Advertising and Marketing to Children. Signatories to these initiatives commit to refrain from advertising food and beverage products to children unless they represent healthy dietary choices (as per scientific or government standards), and the advertising message is in the context of a healthy lifestyle that incorporates good dietary habits and physical activity. We recently reviewed Australian studies to better understand the impact of these initiatives on the television advertising of unhealthy foods to children.3 Our systematic review was commissioned by the Australian National Preventive Health Agency.

We found that one of the challenges in this area is how to define “advertising to children”. Take for instance advertising regulations according to program classifications; there are limits on the ways companies can advertise during programs with a “C” (children) classification. However, few children watch C programs; many more watch television early in the evenings when other programs are broadcast.4 Australian research that has examined food advertising at times when many children watch television has reported between 0.7 and 6.5 unhealthy food advertisements per hour.3 At first glance this level of exposure might seem trivial. However, when we consider that on average, Australian children watch about 2 hours of television per day, children’s overall exposure to unhealthy food advertisements may be between 511 and 4700 advertisements every year, and this figure reflects advertising only on television and not from other sources.5 This also highlights the financial interest that the food, advertising and media industries have in food advertising.

By separating the data further according to whether a company is a signatory to the 2009 industry initiatives, we learn that signatories may advertise unhealthy foods on television more than non-signatories. For example, the authors of one major report on food advertising provided us with additional analyses showing that in November 2011, signatories to the RCMI advertised unhealthy foods at double the rate of non-signatories (0.36 versus 0.17 per hour) at times when children are watching television. Industry groups will argue that the initiatives do not apply in this case because the data do not relate to advertising that specifically targets children or is shown during programs that are developed for children. This distinction is pertinent; public health advocates are interested in reducing the unhealthy food advertisements that children see, not just those advertisements that specifically target children. From a public health point of view, these data are disappointing because they lower confidence in the usefulness of these initiatives in two ways. First, non-signatories to the initiatives have no obligation to address unhealthy food advertising to children, so they continue to advertise. Second, since signatories advertise at a higher rate than non-signatories when many children are watching television, the initiatives seem to be missing the mark as a socially responsible approach to the marketing of foods to children. One potentially positive finding is that the advertising of healthier fast foods has increased from 0 per hour in 2009, to 0.23 in 2010 and 0.26 in 2011.6 However, this must be contrasted against the higher rates of unhealthy fast-food advertising in the same period (1.29, 1.26 and 1.12 per hour, respectively). Disappointingly, researchers have identified a number of breaches of the industry initiatives and of the law governing advertising to children.7

Advertising is one part of our “food environment”. Given the high burden of disease attributed to poor dietary habits, it is important that we provide an environment that will support individuals to make healthier food choices. So does the community care about food advertising? Three reasonably large community surveys (over 1700 participants in each) conducted in South Australia revealed that 80%–90% of adults would support government regulation of the marketing of foods at times when children watch television.8 Stronger regulation of food advertising is also advocated by health and medical organisations. Despite the introduction of the industry initiatives and the widespread community support for regulation of food advertising, Australian children continue to be exposed to the advertising of unhealthy foods on television.

The impact of trans fat regulation on social inequalities in coronary heart disease in Australia

To the Editor: The evidence that industrially produced trans fatty acids (TFAs) increase the risk of coronary heart disease is compelling, and it is widely agreed that their use in food products should be minimised.1–3 Dietary TFAs are generally found in higher quantities in “unhealthy” food products,4 consumption of which is also found to follow predictable socio-demographic patterns.5 Thus, although the average TFA intake for Australians is relatively low, socioeconomically disadvantaged people are likely to disproportionately represent those with above average intakes.

Mandatory labelling of TFA content on all packaged foods in Australia has recently been advocated,1 so that individuals can make informed decisions about purchasing products with excessive levels of TFA. However, while such an intervention may reduce TFA intake at the population level, it is likely to increase social inequalities in TFA consumption and, therefore, inequalities in deaths from coronary heart disease. The reasons for this are as follows. First, research has shown that people who have healthier diets and who are from higher socioeconomic backgrounds are more likely to seek out and use food labels to make healthier choices,6 while those from more disadvantaged backgrounds who do not understand or act on nutrient labelling are much less likely to benefit. Second, mandatory TFA labelling may prompt food manufacturers to brand their products as “TFA-free”, which may bestow an undeserved “health halo” on energy-dense nutrient-poor foods.3 This “health halo” effect is likely to disproportionately influence the purchasing decisions of lower socioeconomic groups, among whom nutrition knowledge tends to be lower than among higher socioeconomic groups.4,5

The ability to replace industrially produced TFAs with healthier alternatives at minimal expense to consumers has prompted jurisdictions such as Denmark and New York City to introduce mandatory limits on the total amount of TFA permitted in all food products. Recent evaluation of the New York City policy showed a significant reduction of TFA in restaurant products, without a corresponding increase in saturated fat, and this effect was similar across high-income and low-income neighbourhoods.7

It is time that Australia introduced strong regulation to reduce TFA intake for all Australians.