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Preference: Nutrition

644

Australian clinical trial activity and burden of disease: an analysis of registered trials in National Health Priority Areas

To improve Australia’s health, clinical research programs should devote substantial activity to advancing practice in areas of high clinical need. Clinical trials are designed to provide high-quality evidence of the effectiveness of new interventions to establish best clinical practice. However, few studies have examined the extent to which Australian clinical trials address priority areas of clinical need.

The Australian Institute of Health and Welfare (AIHW) National Health Priority Areas (NHPAs) were introduced to encourage appropriate targeting of health services and clinical research to improve health. Currently, there are nine NHPAs: cancer control, cardiovascular health, mental health, injury prevention and control, diabetes mellitus, obesity, arthritis and musculoskeletal conditions, dementia and asthma. These NHPAs account for approximately three-quarters of the total estimated burden of disease in Australia (1 915 600 of 2 632 800 disability-adjusted life-years [DALYs]).1

Previous studies have reported a disparity between the level of National Health and Medical Research Council (NHMRC) grant funding for studies investigating NHPA conditions relative to their disease burden.2,3 The founding of clinical trial registries, including the Australian New Zealand Clinical Trial Registry (ANZCTR) in 2005, provides the first opportunity to examine how well clinical trial activity in Australia is targeted to NHPAs.

Methods

We conducted a retrospective analysis using ANZCTR and ClinicalTrials.gov (CT.gov) data to report on Australian trial activity and characteristics for NHPAs; and to compare the level of trial activity to the relative burden of disease for each NHPA.

Ethics approval was not required for this analysis of publicly available trial data.

Data sources

Trial registration is voluntary in Australia.4

The ANZCTR is an online public registry of clinical trials maintained by the NHMRC Clinical Trials Centre, the University of Sydney. It collects information about trial interventions, investigated health conditions, planned recruitment, outcomes, funding and sponsorship using the World Health Organization-defined 20-item minimum dataset.5 Health conditions are coded using the United Kingdom Clinical Research Collaboration Health Research Classification System (http://www.hrcsonline.net). Additional data are collected about trial design, including randomisation and blinding. The ANZCTR 2011 Data Quality and Completeness Audit reported that, on average, at least 93 of 94 data fields for 148 trials were complete.6

CT.gov is an online public registry of clinical trials maintained by the United States National Library of Medicine (https://clinicaltrials.gov). It records similar data items to the ANZCTR.

Trial sample and characteristics

The trial sample included all trials of health-related interventions registered on the ANZCTR or CT.gov between 1 January 2008 and 31 December 2012 that included Australia as a country of recruitment. To avoid entering duplicate trial data, trials that listed a CT.gov or ANZCTR registration number as a secondary identifier were only included in the ANZCTR trial list.

Condition categories and codes were used to classify individual trials as addressing one or more NHPA conditions, or other, non-NHPA conditions. For each trial, we extracted information for: purpose of intervention (treatment, prevention, diagnosis, education/counselling/training, other/missing); allocation of intervention (randomised, non-randomised); trial phase (I–IV, not applicable, missing), blinding (blinded, open, other/missing), planned recruitment (reported as target sample size, and classified as < 100, 100–1000, > 1000 participants); participant age range (< 18 years, 18–69 years, ≥ 70 years); and countries of recruitment (Australia only, Australia and overseas).

Analysis

To measure trial activity, we recorded the total number and planned recruitment of registered trials investigating NHPA conditions. To assess whether trial activity reflected the burden of disease for each NHPA, we compared the relative trial activity targeted to each NHPA, measured as a proportion of the total trial activity, with the “expected” distribution of trial activity estimated from the relative burden of disease for that NHPA. Burden of disease was estimated from published estimates of DALYs for each NHPA expressed as a percentage of the total burden of disease and injury in Australia (%DALY).1

To describe disparities in relative trial activity by NHPA, we identified NHPAs where the observed trial activity was less than 50% or more than 200% of expected values. The χ2 goodness-of-fit test was also used to test for statistically significant differences between observed and expected trial activity for each NHPA. For these analyses, a two-sided P < 0.006 was regarded as statistically significant using the Bonferroni adjustment for multiple comparisons (nine comparisons).

For assessment of trial recruitment across NHPA, we also conducted a sensitivity analysis to examine trial recruitment to NHPA from Australian sites, where Australian recruitment was estimated from the planned recruitment from all ANZCTR trials plus 10% of the planned recruitment from CT.gov trials that included at least one Australian site. The figure of 10% was estimated from a randomly selected sample of 100 CT.gov registered trials that included at least one Australian site and represents the number of Australian sites as a proportion of all sites for each trial.

We also calculated the frequency distribution of trial characteristics for each NHPA. SAS, version 9.3 (SAS Institute) was used for data analyses.

Results

There were 5143 intervention trials registered during 2008–2012 that planned to recruit in Australia (ANZCTR, 3379; CT.gov, 1764). Of these, 3032 (59%) related to NHPA conditions (ANZCTR, 1908; CT.gov, 1124). Total planned recruitment for the trial sample was 2 404 609 participants, including 1 532 064 (64%) for NHPA trials (ANZCTR, 670 832; CT.gov, 861 232).

Trial activity in NHPA

The three disease areas that contribute the largest %DALY — cancer, cardiovascular diseases and mental disorders — also attracted the largest number of trial registrations and the largest planned recruitment (Box 1; Box 2).

The proportions of registered trials that investigated dementia or injury interventions were less than half those expected from their %DALYs (65/185 [35%] and 137/360 [38%], respectively; Box 1). The proportions of obesity and asthma trials were also lower than expected (195/386 [51%] and 68/123 [55%], respectively). In contrast, the proportion of registered arthritis and musculoskeletal diseases trials was about twice as high as expected on the basis of the %DALY (Box 1).

The proportions of planned recruitment to trials investigating obesity and dementia were also substantially lower than expected from their %DALYs (33 948/180 346 [19%] and 24 248/86 566 [28%], respectively), and was also low for asthma (29 468/57 711 [51%]) (Box 1).

When this analysis was repeated using estimated recruitment from Australian sites only, a similar pattern was observed, with the exception of recruitment to diabetes trials. For diabetes trials, total trial planned recruitment was relatively high (185 929/132 253 [141%]) compared with Australian sites (44 201/66 607 [66%]).

Trial characteristics

Overall, 2335 of 3032 (77%) NHPA trials used a randomised design and 1509 (50%) planned recruitment of ≤ 100 participants (Box 3). Of the 2931 NHPA trials that reported information about blinding, 1504 (51%) reported using it (Box 3).

About three-quarters of NHPA intervention trials investigated treatments (2321 [76%]) and 397 (13%) investigated prevention interventions (Box 3). The ratio of treatment to prevention trials ranged from less than 2 : 1 for obesity trials to 14 : 1 for cancer trials.

Most NHPA trials excluded children, whereas 2252 (75%) specified a maximum participant age of ≥ 70 years, or did not specify a maximum age (Box 3). International recruitment sites were reported in 1081 (36%) of NHPA trials (169 ANZCTR trials, 912 CT.gov trials) and varied by condition (Box 3).

Discussion

This study provides the first overview of clinical trial activity in Australia. We found that more than half of Australian registered intervention trials and planned trial recruitment are targeted to NHPA conditions.

Trial activity for cancer, cardiovascular diseases and mental disorders was high relative to other NHPA conditions, consistent with their position as the three major contributors to disability and premature death in Australia. In contrast, trial activity for obesity and dementia interventions was substantially less than the level expected from their contribution to the total DALY.

To interpret these results, the number of trials can be considered to provide a proxy measure for the number of active research questions being investigated to identify more effective interventions in each area. Planned trial recruitment provides a measure of the number of patients actively participating in research to determine best practice in each area.

These findings suggest there is a need to further examine research activity for obesity, dementia and asthma to determine if and how clinical trials research in these areas should be increased. However, this study does not allow us to define the optimum level of trial activity for each condition. Clearly, not all important research questions for NHPAs are amenable to investigation through clinical trials. For conditions where trial activity is already high relative to other disease areas, further increases may still represent good value for money by improving health care. For example, if promising new interventions are available; or practice variations or controversies exist with gaps in evidence to guide best practice. Conversely, for some conditions where trial activity is currently low, research priorities may warrant other study designs, such as those used in translational research or behavioural science, to develop new interventions.

This study also provides the first opportunity to assess the extent to which Australian trials are designed to provide robust, high-quality evidence for guiding practice. The use of randomisation and blinding provides a measure of trial quality; trial size provides an indicator of study power. Trials enrolling more than 100 participants are generally required to assess clinically meaningful health outcomes and to weigh up the benefits and harms of the new strategy, whereas smaller trials are generally designed to assess surrogate outcomes. About three-quarters of Australian trials used a randomised design; however, only around half reported blinding, or planned recruitment of more than 100 participants. These findings are slightly more favourable than those of a recent analysis of 79 413 intervention trials registered on CT.gov between 2000 and 2010, which reported that 70% used a randomised design, 44% used a blinded design and 38% enrolled 100 or more participants.7

One commonly raised concern about clinical trials research is the applicability of trial data to routine clinical practice populations and settings. Our finding that more than two-thirds of trials in NHPA areas did not exclude participants aged 70 years or older is encouraging.

The main strength of our study is that it provides a unique, timely overview of Australian clinical trials to inform current debate on the achievements, limitations and future directions for clinical trials research in Australia. Clinical researchers can use the same methods to further explore gaps for conditions within specific disease areas, as has been performed for cancer trials.8

There are two main limitations to our study that could affect our estimates of trial activity in different directions. First, we relied on trial registrations to estimate trial activity. As trial registration is not compulsory in Australia, we may have underestimated trial activity. Additionally, we only included international trials registered on the ANZCTR or CT.gov. A search using the WHO International Clinical Trials Registry Platform Search Portal (http://www.who.int/ictrp/search/en) showed that 11 096 of 11 412 (97%) trials with Australian sites are registered on these two registries. The total number of registered trials may therefore be 3% higher than our study estimate.

Second, our estimates of trial participation may overestimate the number of Australians participating in clinical trials, because 1622 of 5143 trials (32%) included sites outside Australia. Nevertheless, by including Australian sites, these trial recruitment figures capture participation in trials that can be expected to provide evidence relevant to Australian practice.

Despite these limitations, we believe our findings are valuable in informing initiatives to increase clinical trial activity.9,10 It is well documented that trial research is often not available to guide many routine clinical decisions about selecting interventions.11 To guide practice, large trials with adequate long-term follow-up are needed to identify small incremental improvements in health outcomes and/or adverse events. Our findings on trial size suggest that further efforts are needed to promote and support the conduct of large trials, or support the conduct of small high-quality trials that can later contribute data to meta-analyses.

Overall, we demonstrate the feasibility and value of using publicly available trial registry data to examine the profile of trials research for particular conditions and identify gaps in trial activity to inform trial initiatives. The ANZCTR provides a valuable resource for researchers to ensure new studies build on, or contribute to, existing trials.

1 Number of registered Australian intervention trials and total planned recruitment in National Health Priority Areas, as a percentage of total trial activity, and comparison to the expected number based on %DALY, Australian New Zealand Clinical Trials Registry and ClinicalTrials.gov, 2008–2012

 

DALY

Trials

Planned recruitment

National Health Priority Area

Rank

%

Rank

Observed
no. (%)

Expected no.

Observed/
expected %

P*

Rank

Observed no. (%)

Expected no.

Observed/
expected %

P*

Cancer control

1

19.0%

1

871 (16.9%)

977

89%

0.007

2

427 188 (17.8%)

456 876

94%

< 0.001

Cardiovascular health

2

18.0%

3

646 (12.6%)

926

70%

< 0.001

1

577 178 (24.0%)

432 830

133%

< 0.001

Mental health

3

13.3%

2

693 (13.5%)

684

101%

0.82

3

196 826 (8.2%)

319 813

62%

< 0.001

Obesity

4

7.5%

6

195 (3.8%)

386

51%

< 0.001

7

33 948 (1.4%)

180 346

19%

< 0.001

Injury prevention and control

5

7.0%

7

137 (2.7%)

360

38%

< 0.001

5

125 256 (5.2%)

168 323

74%

< 0.001

Diabetes mellitus

6

5.5%

5

282 (5.5%)

283

100%

1.00

4

185 929 (7.7%)

132 253

141%

< 0.001

Arthritis and musculoskeletal conditions

7

4.0%

4

410 (8.0%)

206

199%

< 0.001

6

109 107 (4.5%)

96 184

113%

< 0.001

Dementia

8

3.6%

9

65 (1.3%)

185

35%

< 0.001

9

24 248 (1.0%)

86 566

28%

< 0.001

Asthma

9

2.4%

8

68 (1.3%)

123

55%

< 0.001

8

29 468 (1.2%)

57 711

51%

< 0.001

DALY = disability-adjusted life-years. %DALY = DALYs expressed as a proportion of the total burden of disease in Australia.1 Observed number of trials is expressed as a percentage of total 5143 registered intervention trials. Observed planned recruitment is expressed as a % of total 2 404 609 planned recruitment. Expected number of trials is calculated by applying %DALY to total 5143 registered intervention trials. Expected planned recruitment is calculated by applying %DALY to total 2 404 609 planned recruitment. * χ2 goodness-of-fit test for comparison of observed versus expected values.

2 Relationship between trial characteristics and %DALY for each NHPA, Australian New Zealand Clinical Trials Registry and ClinicalTrials.gov, 2008–2012

The diagonal line represents the line of equality where %DALY is equal to trial number as a percentage of total registered trials (A) or planned trial participation as % of total planned trial participation (B). Dots below the line show NHPAs where the variable falls below the %DALY. The size of dots corresponds to the size of planned trial participation (A) or number of trials (B) for the NHPA.

%DALY = disability-adjusted life-years expressed as a proportion of the total burden of disease in Australia.1 NHPA = National Health Priority Area.

3 Australian intervention trial characteristics, overall and by National Health Priority Area (NHPA),* Australian New Zealand Clinical Trials Registry and ClinicalTrials.gov, 2008–2012

Characteristic

All trials

NHPA
trials

Cancer

Cardio-
vascular

Mental
health

Obesity

Injury

Diabetes

Arthritis/
musculoskeletal

Dementia

Asthma

Total

5143

3032

871

646

693

195

137

282

410

65

68

Randomisation

                     

Yes

3990 (78%)

2335 (77%)

564 (65%)

494 (77%)

579 (84%)

163 (84%)

125 (91%)

253 (90%)

321 (78%)

53 (82%)

59 (87%)

No

1137 (22%)

691 (23%)

304 (35%)

150 (23%)

113 (16%)

31 (16%)

12 (9%)

28 (10%)

89 (22%)

12 (18%)

9 (13%)

Missing

16

6

3

2

1

1

  

1

      

Intervention type

                      

Treatment

3834 (75%)

2321 (76%)

732 (84%)

444 (69%)

494 (71%)

108 (55%)

103 (75%)

210 (75%)

357 (87%)

50 (77%)

46 (68%)

Prevention

781 (15%)

397 (13%)

52 (6%)

131 (20%)

98 (14%)

67 (34%)

25 (18%)

46 (16%)

34 (8%)

5 (8%)

10 (15%)

Diagnosis

152 (3%)

78 (3%)

29 (3%)

26 (4%)

11 (2%)

3 (2%)

2 (2%)

8 (3%)

4 (1%)

4 (6%)

0

Educational/
counselling/training

263 (5%)

171 (6%)

39 (5%)

26 (4%)

73 (11%)

10 (5%)

4 (3%)

15 (5%)

9 (2%)

5 (8%)

7 (10%)

Other/missing

113 (2%)

65 (2%)

19 (2%)

19 (3%)

17 (2%)

7 (4%)

3 (2%)

3 (1%)

6 (2%)

1 (2%)

5 (7%)

Age group (years)

                      

Minimum age < 18†

987 (19%)

490 (16%)

122 (14%)

60 (9%)

156 (23%)

29 (15%)

42 (31%)

28 (10%)

57 (14%)

7(11%)

26 (38%)

Missing

5

2

1

            

1

  

Maximum age ≥ 70†

3652 (71%)

2252 (75%)

774 (89%)

558 (87%)

397 (57%)

69 (36%)

98 (72%)

199 (71%)

316 (77%)

59 (94%)

41 (60%)

Missing

18

10

2

2

  

1

    

2

2

  

Blinding

                      

Blinded

2639 (53%)

1504 (51%)

270 (31%)

347 (55%)

405 (61%)

93 (51%)

89 (67%)

141 (52%)

249 (64%)

47 (72%)

48 (72%)

Open

2322 (47%)

1427 (49%)

589 (69%)

281 (45%)

260 (39%)

91 (49%)

43 (33%)

129 (48%)

139 (36%)

18 (28%)

19 (28%)

Missing

182

101

12

18

28

11

5

12

22

0

1

Planned recruitment

                      

1–100

2689 (52%)

1509 (50%)

361 (41%)

325 (50%)

361 (52%)

132 (68%)

66 (48%)

133 (47%)

228 (56%)

22 (35%)

33 (49%)

101–1000

2066 (40%)

1274 (42%)

427 (49%)

244 (38%)

300 (43%)

58 (30%)

61 (45%)

119 (42%)

161 (39%)

35 (55%)

31 (46%)

> 1000

383 (7%)

246 (8%)

83 (10%)

77 (12%)

30 (4%)

5 (2%)

10 (7%)

30 (11%)

21 (5%)

6 (10%)

3 (5%)

Missing

5

3

1

  

2

        

2

1

Country of recruitment

Australia only

3521 (68%)

1951 (64%)

349 (40%)

401 (62%)

578 (83%)

184 (94%)

113 (82%)

192 (68%)

286 (70%)

37 (57%)

47 (69%)

Australia and overseas

1622 (32%)

1081 (36%)

522 (60%)

245 (38%)

115 (17%)

11 (6%)

24 (18%)

90 (32%)

124 (30%)

28 (43%)

21 (31%)

Data are no. (%) unless otherwise specified. * Trials may be classified under more than one NHPA (eg, obesity and diabetes). † Includes trials that did not specify age limits.

[Correspondence] Neonatal vitamin A: time to move on?

The three large randomised trials1–3 of vitamin A supplementation designed to improve neonatal vitamin A status do not demonstrate anticipated reductions in infant mortality, despite the large body of evidence showing that vitamin A deficiency is extremely common in women of childbearing age and their infants in many countries where under nutrition remains a major problem. Thus, resolution of the current debate as to whether vitamin A supplements can reduce infant mortality and morbidity in these populations is urgently needed.

Supporting the family doctor

At the recent AMA National Conference, during the Funding quality general practice – is it time for change? policy session, a number of speakers talked about the need to better support general practice, including through the adoption of different models of payment.

Some ideas were more radical than others, but all speakers emphasised the need to better reward and support the ‘usual GP’, that is, the family doctor, in providing quality, comprehensive and long-term care.

The policy session concluded with members of National Conference recognising that, while fee-for-service should remain the primary funding model for general practice, the AMA should remain open to other payment models that could complement this. This will guide the AMA’s contribution to the Primary Care Review that has been established by the Federal Government.

As GPs, we are facing a number of challenges, both now and into the future.

Our patients are ageing and developing multiple chronic conditions, and they want greater access to personalised health care.

Simultaneously, GPs are seeking a better work/life balance, increasingly working in larger practices and in multidisciplinary teams, and our traditional role is under threat from other health professionals that want to expand their scope of practice.

Practice viability is under threat with each funding cut and inadequate indexation – let alone the current four-year freeze on indexation. Quality care is poorly remunerated, and we are under ongoing pressure to deliver more with less, and for less.

We need to be able to spend the time on patients that they need, including to educate them on the benefits of good nutrition and being active, as well as informing them how to implement the lifestyle changes that will enable them to lead healthy lives. To identify and manage their risk factors. To hear their concerns and work with them in treating or managing a health issue. To plan and coordinate their care.

GPs need the comprehensive care they provide to be recognised and rewarded. We need to be remunerated in a way that supports and encourages us to continually do better.

The valuable role that we play as family doctors will be once again honoured by the profession, and highlighted to the community and Government in the coming weeks as we approach AMA Family Doctor Week (19-25 July).

Join us in this endeavour by downloading the Family Doctor Logo and using it on your signature block or web profile. Members can download it here: article/ama-family-doctor-logo.

You can also download the Family Doctor Week poster for printing or displaying on your website. It can be downloaded from here: family-doctor-week-2015.

The AMA will take advantage of a number of opportunities in the coming months to advocate for improved funding arrangements to support both the profession and our patients. These include in providing input to the MBS Review Taskforce, the Primary Health Care Advisory Group and the House of Representatives Standing Committee on Health inquiry into Chronic Disease Prevention and Management in Primary Health Care.

Our key objective will be to ensure that the outcomes of these reviews support, not devalue, the family doctor in caring for patients.

Australia ‘a climate change laggard’

The Federal Government needs to take “much more” action on climate change if the nation is to mitigate its most harmful effects on human health, AMA President Associate Professor Brian Owler has warned.

In an address to the AMA National Conference, A/Professor Owler defended the AMA’s advocacy on climate change against critics who claimed the issue lay outside the Association’s realm of expertise.

The AMA President said that although medical practitioners did not have expertise in climate science, they were well placed to comment on the likely health effects of climate change, which included the likely spread of mosquito-borne diseases into formerly temperate areas, increased deaths from heatwaves, storms and other extreme weather, and the health impact of changes in nutrition as farming patterns are disrupted.

“Our perspective is to come at climate change from the health perspective,” he said. “The best scientific evidence is that there is going to be climate change and there will be health consequences.”

Earlier this year, the AMA helped launch and Australian Academy of Science report on the health effects of climate change, and A/Professor Owler said that, just as doctors followed the scientific evidence on the efficacy of vaccinations, so they also followed the evidence on changes to the world’s climate.

He said that, while the issue had become heavily politicised, the overwhelming weight of evidence showed that it was occurring and “the vast majority of AMA members understand the importance that we mitigate against climate change and its potential health impacts”.

“There is overwhelming support at [the AMA] National Conference for the AMA to speak out on this issue,” A/Professor Owler said. “The health effects can be quite far reaching, and what we don’t want to see is people ignoring climate change.”

The Federal Government is coming under mounting pressure to take more action on climate change ahead of the next round of United Nations talks in Paris in November.

The AMA’s call for more work to mitigate its health effects have been echoed by the World Medical Association, which late last month called for the issue to be given a higher priority at the Paris talks.

WMA President Dr Xavier Deau said he was very concerned that crucial health issues were being ignored in the build up to the Paris meeting, and that time was running out for the voice of the health community to be heard.

The call came as a leading British think tank singled out Australia as a “climate change laggard” among the world’s developed countries.

The UK-based Grantham Institute on Climate Change and Environment reported that Australia was the only developed country to “take a legislative step backwards” from action on climate change.

A/Professor Owler said the Government’s approach to climate change was going to be very important in the lead-up to the Paris summit, “but so far the Government’s response has been disappointing. We want to see more action on climate change”.

Adrian Rollins   

Government action on diabetes prevention: time to try something new

Diabetes mellitus is the fastest-growing non-communicable disease (NCD) in Australia. Around one in 25 adults has type 2 diabetes, and half do not manage their condition effectively.1 By 2023, diabetes will account for around 9% of Australia’s burden of disease, compared with 5% in 2003.2 Health spending on diabetes has been predicted to rise by 400% between the 2002–03 and 2032–33 financial years, reaching $7 billion.2 The rising burden of diabetes is largely due to rising rates of overweight and obesity, to which poor diet is a key contributor.

In 2013, Australia and other members of the World Health Assembly committed to a range of global goals for reducing the burden of NCDs, including a halt in the rise of diabetes. Achieving these ambitious goals will require a paradigm shift from personal responsibility to shared responsibility, as well as greater accountability from governments and industry.3 Although individuals can take steps to improve their own diets, achieving healthier diets at the population level requires cost-effective public policy measures.

Until now, Australian government action to prevent diabetes has focused largely on encouraging individuals, through education and information, to change their lifestyles. In this article, we propose a new approach. We summarise four regulatory actions that the federal government could take to modify the preventable dietary risk factors of diabetes at the population level. These are:

  • Implementing a mandatory front-of-pack food-labelling system;
  • Restricting children’s exposure to junk food advertising;
  • Strengthening co-regulatory structures for food reformulation; and
  • Taxing sugar-sweetened carbonated beverages.

Unlike medical interventions, legal and regulatory interventions are rarely assessed in clinical trials. Priorities must therefore be identified according to well recognised criteria (effectiveness, cost impact) as well as other factors that are perhaps less quantifiable, including political feasibility. Each of the priorities we propose is supported by an evidence base and engages with at least one of the three policy domains that have been identified as crucial to prevention: food behaviours, the environments in which we make food choices (including price, marketing and advertising) and the nature and quality of the food supply.4 Importantly, these priorities do not override individual autonomy or personal choice, although they may constrain the actions of food businesses and alter the incentives for individual behaviour. These actions complement education and the provision of information to members of the population — they are not intended to be a substitute.

Unhealthy diets, obesity and diabetes

Overweight and obesity are the most important direct risk factors for diabetes.5 Between 2007–08 and 2011–12, rates of overweight and obesity in Australian adults rose by 1.6 percentage points, reaching nearly 63%.1 Overweight and obesity in children aged 5–17 years exceed 25%.6

Rather than illustrating a nationwide failure of personal responsibility, unhealthy diets and weight gain among Australian adults and children are the result of complex global and local processes. Social, economic and technological changes have profoundly reshaped the food supply, making unhealthy choices easier than healthy ones.7 The processed food industry has been influential, driving consumer tastes and spending patterns towards foods that are cheap to produce, highly profitable, energy-dense and nutritionally poor. The recent Australian Health Survey showed that we consume over 35% of energy as discretionary (or “junk”) foods — foods with little nutritional value that tend to be high in saturated fats, sugars, salt and/or alcohol.6 These dietary patterns contribute to chronic energy imbalances between kilojoules consumed and kilojoules expended at the individual level, and high rates of overweight and obesity at the population level.

The need for leadership on diabetes prevention

Governments have a duty to protect the population from risks that may lead to disability and premature death. Achieving this on a population scale often requires the use of laws and regulations. This is uncontroversial when it comes to infectious diseases and injuries: Australians rarely object to laws protecting them from exposure to asbestos particles, contaminated food, Ebola virus or motor vehicle injuries.

NCDs account for 85% of Australia’s disease burden,5 yet successive Australian governments have been slow to take regulatory action. Government action to improve diets has focused on health promotion and the provision of information, including through nutrition labelling, the Australian Dietary Guidelines and campaigns such as Shape Up Australia in 2013.

These approaches sit comfortably with the food industry, which emphasises personal responsibility for dietary choices. It also prefers voluntary, industry-led approaches to food labelling, marketing and reformulation.8 However, while individual responsibility is critical for individuals to manage their own diabetes risk, it has demonstrably failed as a public policy approach to growing rates of diabetes.7 While the food industry’s desire to demonstrate responsibility is laudable, little progress has been made through voluntary schemes. And although it is tempting to regard dietary risk factors for NCDs as being self-inflicted, effective prevention requires changes that can only be achieved with government action, including public policies to improve the food supply and the food environment.

Time to try something new: four priorities for government action

A mandatory front-of-pack food-labelling scheme

If consumers are to take responsibility for their health, they need clear and consistent nutritional information about the foods they buy.9 Australian law requires manufacturers to disclose the ingredient list and nutrition information panel on food packages; however, this can be time consuming to read and difficult to interpret. A front-of-pack label translates this information into simple visual messages about the quality of the nutrition of the food.9 In January 2015, the Australian Government announced it would proceed with a new front-of-pack labelling scheme, a star rating.10 Companies may implement the star rating voluntarily, and it may be accompanied on food packages by the industry’s preferred label, the daily intake guide.

However, voluntary use of two different labels perpetuates the status quo. Food companies that do not wish to draw attention to products high in sugar, salt or saturated fat are already ignoring the star rating,11 while those that act responsibly bear the cost of increased regulation. In 2011, the Blewett review of labelling law recommended a colour-coded (“traffic light”) front-of-pack label, supported by a comprehensive national nutrition policy.9 Four years on, there is no sign of a national nutrition policy, the food industry has successfully resisted colour-coded labels, and the front-of-pack label-development process has been drawn out and hampered by political controversy.

Time to try something new. It is time for Australia to have a legislated, mandatory front-of-pack labelling scheme, creating a level playing field for companies and clear choices for consumers.

Restricting children’s exposure to junk food advertising

In its 2004 Global strategy on diet, physical activity and health, the World Health Organization stated:

Food advertising affects food choices and influences dietary habits. Food and beverage advertisements should not exploit children’s inexperience or credulity.12

A variety of mechanisms have been adopted in different countries to restrict children’s exposure to junk food advertising.13 However, evidence suggests that government regulation is more effective than voluntary industry measures. A recent systematic review found that

self-regulatory pledges are unlikely to be sufficiently comprehensive to have the desired effect of reducing children’s exposure to promotional marketing of unhealthy food products unless tied to stronger government oversight. [emphasis added]14

It recommended as best practice “comprehensive, preferably statutory measures” including clear definitions of media and audience, monitoring of compliance, and sanctions for non-compliance.

In 2008, the Australian Government considered, but decided against, regulating junk food advertising to children. Instead, the food industry signed up to two voluntary codes of conduct. Empirical analysis has shown that these have done little to reduce children’s actual exposure to junk food advertising.15 This is because their commitments are vague, contain loopholes, cover a narrow range of media, and allow for subjective interpretation by companies.16

Time to try something new. Mandatory targets, broader coverage and real sanctions for non-compliance would significantly strengthen the ability of industry codes to limit children’s exposure to junk food advertising.

Stronger co-regulatory structures for food reformulation

Food reformulation has been described as

a realistic opportunity to improve the health of a population through improving the nutritional characteristics of commonly consumed processed foods.17

Reformulation could involve reducing the salt, sugar or saturated fat content of processed foods, or their portion sizes or energy density. This approach is regarded as cost-effective,18 since it does not depend on individually targeted behavioural changes.19

However, food reformulation in Australia has so far been limited to voluntary, industry-led approaches. Since 2009, the major national initiative has been the Food and Health Dialogue, which convenes representatives of government, the food industry and public health to collaborate on reformulation. The Dialogue sets targets on a range of common foods, and manufacturers choose which ones to implement.

A recent systematic assessment found that, in its first 4 years, the Food and Health Dialogue achieved none of its reformulation targets.19 The authors also found that few targets had been set, and that participants regularly failed to meet deadlines for reporting on progress. Further, evidence from other jurisdictions illustrates how commitments made under industry-led processes tend to be diluted to the point of meaninglessness,20 or simply remain unfulfilled.21

Time to try something new. Food reformulation processes need specific targets and timelines, robust oversight mechanisms, incentives for compliance, and independent review of progress and performance. If self-regulation fails to meet its targets, the government should progressively intervene.22

A tax on sugar-sweetened carbonated beverages

Taxes act on consumer behaviour by changing the cost of different choices relative to one another. If unhealthy foods are cheap to buy, then raising their price through taxation provides a price signal — although without removing choice altogether. A 2012 review of health-related food taxes found that, if carefully designed, these could be effective in shifting patterns of consumption towards healthier foods,23 with a 20% tax suggested as the minimum rate for effectiveness. Excise taxes (taxes levied on a specific kind of product) have been found to be particularly effective and are used to correct for negative externalities (harm to a third party external to the producer–consumer relationship — in this case, social harm) caused by persistent consumption of unhealthy products, such as tobacco, alcohol or unhealthy foods.24 Revenue from such taxes can also be hypothecated towards health promotion initiatives or healthy food subsidies.

Proposals to tax fats can be complex, with unintended consequences for basic products like dairy foods. By contrast, sugar-sweetened carbonated beverages (SSBs) are more straightforward targets. They add little nutritional value while contributing significantly to excess energy intake. In January 2014, Mexico joined 34 US states, Denmark, France, Tonga and several other jurisdictions by introducing a tax on SSBs.

In its response to the recommendations of the National Preventative Health Taskforce in 2010, the Australian government stated it would not be considering taxes to decrease the consumption of unhealthy foods and drinks.25 Since then, however, community support for a tax on SSBs has grown significantly. In 2013, a coalition of non-governmental health organisations (the Cancer Council, Diabetes Australia and the Heart Foundation) launched a national campaign calling on government to explore taxation as part of a suite of policies aimed at reducing SSB consumption.

Time to try something new. Thirty years ago, governments were similarly reluctant to take regulatory action on tobacco. Looking forward 30 years, which Australian governments will be seen as leaders and pioneers in regulating for diabetes prevention?

Conclusion

Individualised, education-based and voluntary approaches have dominated the diabetes prevention efforts of successive Australian governments, and rates of diabetes have continued to rise. Results matter. Dogged commitment to failed policy approaches makes no sense; and accountability for these failures is long overdue.

Using law and regulation, governments can have a real impact at a population level, influencing patterns of consumption and tackling the environmental influences on poor diet, obesity and diabetes. No single intervention will be a silver bullet. Instead, we need a quiver of arrows — a selection of public policies that, in the right combination, can begin to reshape our food supply and food environments in a healthier direction. With an ageing population, new cases of diabetes are inevitable. But these numbers can be reduced if governments take prevention seriously, and are willing to challenge the status quo.

Imported gluten-free foods: free of gluten?

To the Editor: The recent hepatitis A outbreak associated with imported berries has brought the problem of imported food quality acutely into the public spotlight. By contrast, the serious adverse effects for many people with coeliac disease of non-compliant imported foods being labelled “gluten-free” (GF) is more insidious and less easily assessed.

Concern has previously been expressed about proposals to raise the amount of gluten permitted in GF foods.1 In Australia, the current standard for claiming that a food is “gluten-free” is that it contains “no detectable gluten”;2 on the basis of the limits of current laboratory test sensitivity, this equates to less than 3 parts per million (ppm).

Closely aligned with this concern is the fact that imported food labelled “GF” may comply with standards in the country of manufacture but not with tighter Australian standards. For example, “GF” in Europe and North America indicates gluten levels of less than 20 ppm; accordingly, GF-labelled foods imported from these regions may contain detectable gluten. Further, gluten-level testing of GF-labelled foods is not mandatory in the United States;3 in one report, 20% of US foods labelled “GF” did not comply with the Food and Drug Administration standard.4

Governance of food regulation in Australia is unfortunately complex. Food Standards Australia New Zealand set food standards federally; individual states set laws based on the federal standards; local government health officials implement state laws and monitor compliance. The Australian Competition and Consumer Commission, responsible for consumer law, has also contributed to food regulation and compliance. Further, the federal Department of Agriculture has responsibility for regulating imported foods. Local importers and retailers should also facilitate food safety.

Testing of imported foods labelled “GF” is ad hoc, lacking coordination across multiple jurisdictions, and is hampered by financial constraints. There is a tendency for organisations to suggest that the responsibility for compliance lies elsewhere. Enhanced transparency of laboratory food testing outcomes is required, for there are scant published data that assure the consumer about food code compliance for foods labelled “GF”. It is to be hoped that some good will come of the hepatitis A food contamination incident, by providing the impetus for significant change in the governance of Australian food safety.

Joining the dots for the management of clinically severe obesity

Perceptions about the cause, prevention and management of obesity need to change

At its annual meeting in June 2013, the American Medical Association (AMA) adopted a policy that recognised obesity as “a disease requiring a range of medical interventions to advance … prevention and management”.1 On the first anniversary of this decision, with the firm support of relevant colleges and associations, the AMA went further by adopting a policy that supported patient access to the full spectrum of evidence-based obesity interventions, including behavioural, pharmaceutical, psychosocial, nutritional, pharmacological and surgical options.2 The next steps in delivering better integrated care in the United States will not be easy, as they will not only require a transformational change to health services, but also that community perceptions of obesity be confronted. These steps will need to recognise and manage clinically severe obesity (ie, significant health impairment, including comorbid conditions and functional status directly related to excess weight, regardless of whether body mass index [BMI] exceeds 35 kg/m2) as a chronic disease.3 We have already seen that incremental changes in health care service delivery, chronic disease models of care, and the widespread use of effective interventions have delivered markedly improved outcomes for people with type 2 diabetes in many countries.4 This experience provides a template for delivering better health outcomes for those with clinically severe obesity.

Health service delivery for obesity is undergoing major change in England, with several important initiatives instigated by the 2013 Royal College of Physicians report, Action on obesity: comprehensive care for all.5 The objective is to commission an integrated chronic disease model of care for patients with clinically severe obesity by providing specialised, multidisciplinary assessment and management services (tier 3 interventions) that are conceptually located between community and public health (tier 1) and primary care lifestyle interventions (tier 2) on the one hand, and bariatric surgical services (tier 4) on the other.6 This process of developing tier 3 interventions, initiated by the British Obesity and Metabolic Surgery Society and the Royal College of Surgeons, fills a logical gap in delivering integrated comprehensive care in the context of chronic disease management, irrespective of whether surgery may be an option. The National Health Service England and Public Health England also initiated a working group to examine urgent problems in the delivery of obesity care and recently published their consensus report, Joining up clinical pathways for obesity.7

Making informed treatment options

It is difficult to imagine how oncological, cardiac, endocrine or neurological interventions could be delivered effectively without the integration of specialised medical and surgical services, and it is no different for severe clinical obesity.

Delivery of anything more intensive than lifestyle and behavioural interventions requires three elements — that appropriate interventions are both available and understood by patients and physicians; that the range of options suitable for a particular individual are identified; and that a treatment plan is developed in a timely manner. However, the process of patient selection for many interventions currently lacks evidence-based clarity, and relies more on the preferences of the physician and on the BMI of the patient than on a more sophisticated risk–benefit evaluation of the individual’s condition. In providing appropriate treatment for clinically severe obesity, the benefits of planned weight loss need to be balanced against the potential mental, physical and metabolic complications and risks, as well as considering the patient’s age and BMI. Health outcomes beyond the degree of intended weight loss must be considered, with a focus on improving health-related psychosocial and physical functions and quality of life, avoiding end-organ damage, and reducing morbidity and mortality.

There are also fundamental but contentious concerns about planned weight loss that need careful analysis. Apart from weight loss after bariatric surgery in patients with clinically severe obesity and a BMI of at least 35 kg/m2, there is little evidence that intentional weight loss reduces mortality, despite improvements in cardiovascular risk factors.8,9 It is increasingly apparent that there is no single ideal BMI range; an optimal BMI depends on factors such as ethnicity, age and current state of health. In addition, the relationships between the degree of weight loss and improvements in health and function are not necessarily linear; indeed, much of the benefit may come with a modest 5%–15% reduction in weight. Attaining a BMI between 18.5 and 25 kg/m2 is therefore unlikely to be an appropriate target for patients with clinically severe obesity — whether we are discussing realistic expectations or achieving optimal health outcomes. Understanding the benefits and risks to each individual of more intensive weight loss interventions will allow resources to be better directed to those in need and help avoid unnecessary risk to those who are unlikely to benefit.

Integrated care is the key to effective treatment

Over the next century, Australian health care resources will be increasingly directed to treating the disorders associated with ageing and obesity. The inertia in delivering effective treatment options for clinically severe obesity is based on numerous factors, and manifested in several ways. The most notable include the systematic social stigmatisation of obesity (perceptions of failed willpower and compliance), including by health professionals;10 the frustration associated with difficulties in achieving and sustaining weight reduction; the poor uptake of bariatric surgery; barriers to gaining access to care; and the currently poor track record of medical systems in providing safe and effective pharmacotherapy.

“Failure” is a term that is often heard in this situation, but using it in the context of chronic disease management is unacceptable. It implies systemic failure in providing “care for all”, failure to engage the individual patient in the process of managing chronic disease, and failure to deliver improved health outcomes. We have learned that improving health outcomes in type 2 diabetes involves more than simply controlling glucose levels, and we expect a similar relationship will exist between treating clinically severe obesity and weight reduction strategies.

All effective evidence-based options, including intensive dietary approaches, pharmacotherapies, bariatric surgery, gastrointestinal devices and emerging surgical and endoluminal interventions, can be integrated with core behavioural and lifestyle therapies. The emphasis on particular approaches and combinations of treatments can be adjusted as required. Bariatric medicine — as a key evidence-based health care discipline — needs to mature, expand and develop a transdisciplinary approach over the next decade.

As with any chronic disease, all therapies — not only surgery — require indefinite follow-up, management of comorbid conditions, nutritional support, assessment for complications, and strategies to attenuate any long-term downside to therapy. This will ideally be performed in a primary care setting with support from a multidisciplinary bariatric team.

Medical practitioners and allied health professionals who provide effective interventions with improved health outcomes should not apologise for the appropriate medicalisation of obesity. Engaging patients in understanding their condition, empowering them with options for care, and providing enduring support is the very definition of quality chronic disease management. The opportunity to make informed evidence-based decisions and the resources to proceed with those decisions should be a pillar of modern health care.

In the US and England, with their contrasting health systems, there has been a clear decision to make a major change toward providing comprehensive care for those with clinically severe obesity. A broader range of effective tools, greater clarity about patient selection based on actual risks and benefits of weight loss interventions, and the establishment of effective clinical pathways are important research translation priorities in delivering comprehensive care for all. As shown in the US and England, this requires that many groups and organisations coordinate their activities to effect change. We should applaud and support these and similar activities in other countries and regions, while realising that problems of pejorative perceptions, stigmatisation and clinical inertia generate challenges that must also be tackled.

Around 1.5 million people in Australia have clinically severe obesity, and a similar number have diabetes.11 Each condition impairs quality of life, generates disability, is linked with serious complications and shortens life expectancy in a similar way — but only for the second of these conditions do we have established clinical pathways, responsibilities and resources. For clinically severe obesity it is time to critically examine our performance, to overcome the barriers to better care and to move forward.

Recommendations

  • Clinically severe obesity needs to be recognised and managed as a chronic disease.
  • Pervasive stigmatisation of severe obesity by the general public and by health care providers must be countered to enable appropriate treatment pathways to be developed. The AMA policy aims to do this by empowering care providers and patients to jointly manage their chronic condition, not to disempower or victimise them.
  • Perceptions about the cause, prevention and management of obesity need to change. Quality health literacy about obesity management needs to be improved in the community and among health professionals.
  • Major regional hospitals and health care providers need to develop integrated clinical pathways that include specialised multidisciplinary obesity assessment and management services that equitably deliver clinically effective therapies, including surgery.

Implementing these recommendations will need a broad transformational change to the way clinically severe obesity is assessed and managed. It will also require policy commitment and research, together with community and professional education, enabling the development of effective clinical pathways.

[Correspondence] Rising food insecurity in Europe

People queueing for food aid is an image reminiscent of the Great Depression in the 1930s, but one that has come to characterise many European nations in the grip of austerity today. In 2013–14, the UK’s Trussell Trust, a national network of food banks, provided emergency food aid to more than 900 000 adults and children, a 163% increase from the previous year.1 Greek, Spanish, and French charities have also reported marked rises in the number of people seeking emergency food support.2 Alongside clinical evidence of rising nutritional deficiencies,2,3 these reports suggest that a problem is emerging, but to what extent is food insecurity rising across Europe?

Sceptics undermine effective dietary and heart health advice

Recent reports questioning the link between saturated fats and coronary heart disease fail to convince

“Eat less saturated fat and more polyunsaturated fat” has been the central dietary advice for reducing early death from coronary heart disease (CHD) for more than four decades. This advice was based on evidence accumulated over many years, and the decline in developed countries in the numbers of premature deaths caused by CHD is attributable in some measure to its widespread acceptance.

In 2010 and 2014, two studies based on meta-analyses contradicted this longstanding advice,1,2 and their findings have been widely broadcast in the United States and the United Kingdom by the popular media, including the New York Times, Time magazine, New Scientist and the Independent.

The resulting discussion on the place of saturated fat in the diet and the management of cholesterol in the population has the potential to drastically impede further progress in reducing CHD. Why do the conclusions in these two articles depart so markedly from the international consensus that has been trusted until now?3

The first of these articles was the 2010 meta-analysis by Siri-Tarino and colleagues of prospective cohort studies.1 The authors found no significant association between saturated fat consumption and the risk of CHD. It is remarkable that this unconvincing review stimulated extensive interest in the media, whereas a large pooled analysis by experts from 10 universities, published in the same journal a year earlier, had not attracted the same attention. The 2009 article, by Jakobsen and colleagues, had reported that reducing saturated fat in the diet and replacing it with polyunsaturated fatty acids (PUFAs) was associated with a significantly reduced risk of CHD.4

The importance of experimental design

Experts in the US, Australia, the Netherlands, the UK, New Zealand and Norway have strongly criticised the conclusions reached by Siri-Tarino et al. Six major concerns were voiced.

1. With what did study participants replace dietary saturated fats?

Siri-Tarino et al did not consider most of the prospective studies in Jakobsen et al that reported dietary substitution of saturated fats by PUFAs.4

2. The validity of the dietary assessment methods varied between reports

In several studies, for example, participants were asked to recall what they had eaten during a single 24-hour period, an approach that is inadequate for assessing long-term dietary history.

3. A broader variety of dietary cultures should have been included

The optimum approach for evaluating an association between dietary saturated fats and CHD is to study groups from different dietary cultures. An example of this procedure was the Seven Countries Study (7CS), in which research dietitians watched meals being prepared, and collected foods from the local area and organised their transport to the University of Minnesota for chemical analysis of their fatty acid content.5Saturated fat intake in this study ranged between 2.5% and 22% of total energy intake, and its correlation with the number of CHD deaths was highly significant (r = 0.84).5

The media downplayed this finding when reporting the results, suggesting that the director of the 7CS had “cherry-picked” the seven countries. The cohorts described in the 7CS report had, however, been selected on the advice and support of Paul White, President Eisenhower’s cardiologist, and because enthusiastic and reliable local medical researchers, as well as local funding that supplemented US support, were available during the 1950s. Further, a total of 16 cohorts were studied across the seven countries, which also enabled within-country comparisons. Two quite different Finnish cohorts were included, for example, while rural farming and coastal farming villages were compared in Croatia and Japan, as were three dissimilar communities in Serbia.5,6

4. Evidence from metabolic ward studies

The major evidence on the relationship between dietary saturated fat and CHD has been delivered by metabolic ward studies. This type of study has consistently shown since 19567that dietary saturated fats increase plasma levels of total and low-density-lipoprotein (LDL) cholesterol, which are strongly implicated in the pathogenesis of CHD.

5. The evidence from long-term dietary studies

Meta-analysis of the limited number of long-term controlled dietary trials in humans indicates that diets including reduced amounts of saturated fat and an increased PUFA content lead to significantly fewer CHD events.8

6. Historical trends in the epidemiology of CHD

In the early 1960s, experts in Western countries recommended a diet that included less saturated fat and more PUFA for people at risk of CHD, and that advice was soon extended to the entire community. CHD mortality (age-standardised) reached a peak in North America, Australia, Finland and other Western countries around 1965, and has since declined dramatically; in Australian men the rate dropped from 610 per 100 000 in 1965 to 135 per 100 000 in 2000 (the fall was similar in women).3,9 The reduced mortality associated with heart attacks in Australia, the US and in Nordic countries consisted primarily of a reduction in the number of deaths in patients on their way to hospital, indicating that improvements in the management of risk factors, rather than of hospital treatment, explained the change. A cholesterol-lowering diet was a major influence, together with reduced smoking and efficient antihypertensive medication. Cholesterol-lowering statin medications were not introduced into therapy until the 1990s.

Omega-6 fatty acids and heart disease

In the second article that attracted recent media attention, Chowdhury and colleagues analysed four types of evidence from prospective studies or randomised controlled trials concerning the relationship between dietary fat type and CHD events: dietary fatty acid consumption, circulating fatty acid levels, adipose tissue fatty acid levels, and dietary and supplements trials. They concluded that the evidence did not support cardiovascular guidelines that encourage high consumption of PUFAs and low consumption of saturated fats.2 It quickly made headlines around the world, but the findings have been criticised by other experts.10

In my detailed examination of this publication and the associated supplementary material (57 pages in total), in which I focused on the data for omega-6 PUFAs, I also identified a number of problems. In particular, studies were omitted, and the findings of those included were often incorrectly reported. References for these articles are listed in the Appendix.

In their review of prospective studies, Chowdhury et al incorrectly reported the results of two reports (omega-6 PUFAs were protective in the original articles). Seven further published studies were overlooked. In five of these, including two based on large participant numbers,11,12 a negative correlation between omega-6 PUFA intake and the risk of CHD was found. Had all these studies been included in the forest plot in Chowdhury et al, 10 of 15 would have been located on the left-hand side (indicating that omega-6 PUFAs were protective).

In their review of circulating fatty acids and CHD, Chowdhury et al included 10 studies in which levels of linoleic acid, the major PUFA, were measured; two of these were incorrectly placed in the forest plot. Seven studies in the literature were overlooked, including two based on large participant numbers;13,14 linoleic acid tended to be protective in all seven. Overall, this means that 13 of 17 studies should have been placed on the left-hand side of the forest plot (indicating that omega-6 PUFAs were protective).

In their review of adipose tissue fatty acids and CHD, only one study measured linoleic acid, but a further eight reports have been published, of which six found linoleic acid to be protective. A 2007 review included seven articles about adipose tissue fatty acids and CHD,15 none of which were cited by Chowdhury et al.

In their review of dietary and supplements trials, Chowdhury et al made no distinction between these two very different types of investigation. Most of the trials analysed in this section reported simple supplementation with fish oil or capsules containing eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) capsules. It seems inappropriate, however, for supplements trials to be pooled with dietary trials in which participants consumed both less saturated fats and more PUFAs. In the randomised dietary trials, participants were assisted to make large changes to their diets and to maintain them for several years. In the omega-6 forest plot (figure 14 of Chowdhury et al), the Sydney Diet Heart Study (SDHS) is clearly an outlier; it was not included in other meta-analyses of dietary trials,8and its authors wrote that “comparison of the mean diets of those who died and the survivors revealed only trivial differences”.16 If the SDHS trial is removed, the relative risk for CHD in omega-6 dietary trials is 0.81.

In all, Chowdhury et al omitted or incorrectly reported 25 studies of omega-6 PUFAs and CHD. The protective effect of PUFAs would have been clear if all published studies had been included in their meta-analysis. Changes to established public health guidelines should not be advocated unless all the relevant evidence has been reviewed.

A warning about meta-analyses

Professor Walter Willett (Harvard School of Public Health) told Science Insider that “The controversy should serve as a warning about meta-analyses.” These analyses compile the data of individual studies to reach a clear-cut conclusion. “It looks like a sweeping summary of all the data, so it gets a lot of attention. … But these days meta-analyses are often done by people who are not familiar with a field, who don’t have the primary data or don’t make the effort to get it.” The results of drug trials can be more easily combined because they are similar in design, he explained, but nutritional studies are more diverse. “Often the strengths and weaknesses of individual studies get lost … It’s dangerous.”10

In conclusion, the findings of the two articles discussed here do not justify a change of longstanding cardiovascular dietary guidelines that have contributed to massive reductions of CHD in developed countries.

Listeriosis cluster in Sydney linked to hospital food

Three patients were diagnosed with listeriosis in different hospitals within a short period. Rapid molecular typing techniques and review of hospital menus using an electronic menu database allowed prompt identification of the source of infection and implementation of control measures that prevented further infections.

Clinical record

Between 4 and 12 April 2013, a public health unit in Sydney was notified of three patients in different tertiary hospitals in two local health districts (LHDs) who had tested positive for listeriosis. This unusual occurrence prompted concern that the cases might be linked through contaminated hospital meals because hospitals in these LHDs source food from the same suppliers. The public health unit led a public health investigation, which included representatives from the New South Wales Food Authority, OzFoodNet, two NSW reference laboratories, food services, dietetics services and hospital infection control staff, to determine whether there was a link between the cases.

Listeriosis is a notifiable disease in NSW, and cases are investigated in accordance with NSW Health control guidelines.1All listeriosis notifications in NSW between 2 April (when the first case was detected) and 25 June (70 days after control measures were implemented) were reviewed in the process of case finding. A case was defined as a confirmed diagnosis of listeriosis during this period in any person in NSW who had been an inpatient of a public hospital in the two LHDs at any time during the potential exposure period for listeriosis; ie, 3–70 days prior to symptoms. Food history information was supplemented by records obtained from the electronic menu database (CBORD, Sydney) of the two LHDs, which records all hospital food menu items ordered by patients during their admissions. Positive blood cultures collected from patients underwent molecular subtyping, including binary typing, multiple-locus variable-number tandem repeat analysis (MLVA), pulsed-field gel electrophoresis (PFGE) and molecular serotyping. Food and environmental specimens were screened for Listeria species, including L. monocytogenes, with a multiplex polymerase chain reaction (PCR) assay, and PCR-positive results were reported as presumptive positives and confirmed by culture; isolates from positive samples underwent molecular subtyping.

Only the initial three notified patients met the case definition. Patient 1 was an 82-year-old inpatient of hospital A with a history of heart failure and chronic obstructive pulmonary disease; blood cultures that tested positive for L. monocytogenes were collected on 2 April. Patient 2 was a 34-year-old inpatient of hospital B with myelofibrosis; blood cultures that tested positive for L. monocytogenes were collected on 6 April. Patient 3 was a 71-year-old with end-stage hepatocellular carcinoma and a history of two recent admissions to hospital C, and re-admitted on 8 April after a fall. Blood cultures collected that day were positive for L. monocytogenes. The patient died on 9 April.

Foods known to pose a risk of transmitting listeriosis, as well as food items consumed by all three patients during the overlapping periods of their admissions (20–26 March) were identified from hospital menus. Notable food items are listed in the Box.

The food safety profiles of the companies that manufactured these products were reviewed, and samples from local hospitals were tested on 16 April. There were no concerns about Companies Y and Z. Three weeks earlier, however, an environmental swab from the factory of Company X had tested positive for L. innocua during regular in-house testing, and a chocolate profiterole produced on 2 April had also tested positive for Listeria species; this batch had subsequently been discarded. Data from the menu database showed that all three patients had ordered chocolate profiteroles on 24 March. A leftover chocolate profiterole from the same batch was found in a local hospital and tested. The NSW Food Authority inspected the premises of Company X on 17 April and collected food and environmental samples for testing.

On 18 April, the isolates from the three patients were reported as having identical binary types (223), MLVA profiles (04-17-16-05-03-11-14-00-16) and serotypes (1/2b, possible 3b, 7), and on 15 May they were confirmed to share an identical PFGE pattern (4A : 4 : 1). On 19 April, PCR testing of the chocolate profiterole left over from the batch ordered by the patients on 24 March returned a presumptive positive result for L. monocytogenes, but repeat testing later indicated that this had been a false positive. All other samples of leftover hospital foods were negative for L. monocytogenes. Listeria was detected in seven environmental samples from Company X’s premises, and L. monocytogenes was detected in a further two environmental samples from the production facility; the results of molecular subtyping of one of these samples (binary typing, MLVA and PFGE) were identical with those of the clinical specimens.

Creamy rice pudding was the first high-risk food identified and was temporarily withdrawn from all hospitals in the LHDs on 12 April until all products had been tested for L. monocytogenes. On 16 April, desserts from Company X were withdrawn from all Sydney hospitals in which they were served. By the time of the presumptive positive PCR result, the risk of further infections in those who had consumed profiteroles was regarded as low, and it was decided not to proceed with the resource-intensive task of tracing all 1297 profiteroles served in hospitals within the LHDs on 24 March. Instead, active case finding was initiated by issuing a media release, alerting all treating doctors and general practitioners within the LHDs, and by establishing a public hotline number on 20 April.

Discussion

Listeriosis is an infection caused by L. monocytogenes and is transmitted through the ingestion of contaminated food, aided by the ability of the bacterium to survive some food processing techniques and to multiply at refrigerator temperatures.2,3 Listeriosis usually presents as non-invasive gastroenteritis in immunocompetent individuals, and as more severe invasive disease in older people, the immunocompromised and in pregnant women.2 Hospitalised patients are particularly likely to be older or immunocompromised, as were the patients in this cluster, and are therefore especially susceptible to listeriosis.4

Most cases of listeriosis are apparently sporadic, but foodborne outbreaks occur, and health care-associated listeriosis clusters have occasionally been reported.5,6 As the incubation period is quite long (3–70 days), it is often difficult to identify the vehicle of infection in listeriosis outbreaks.2,6 The increasing application and resolution of molecular subtyping of foodborne bacterial pathogens has, however, enabled investigators to detect clusters and track food sources of infection.7,8

Previous hospital outbreaks have not always identified specific vehicles of transmission,6 and inadequate records of the food items consumed by patients may have contributed to this failure.4 In the outbreak reported here, an electronic menu database enabled rapid identification of potential food sources and investigation of suppliers producing these foods, and prompt implementation of control measures. This would have been almost impossible with a manual menu system. The identification of this cluster led to the relevant services upgrading existing food safety plans to ensure that the future risk of hospital-acquired listeriosis is further minimised.

By identifying a rare and unique strain of L. monocytogenes in all three patients, the laboratory techniques used in this investigation were central to linking the affected patients with a food item produced by Company X. These techniques play an increasingly important role in detecting, investigating and controlling foodborne outbreaks.4,8–10 Binary typing and MLVA are PCR-based, and are the standard methods used in major Australian reference laboratories. Binary typing is rapid, with a turnaround time of 3 hours once DNA has been extracted from L. monocytogenes isolates. Binary type 223 is rare, and has been found in only one of 75 clinical L. monocytogenes food and environmental isolates in NSW since 2010, and in none of the 35 NSW isolates since 2012; its detection was the first indication of a link between the three patients in this report. MLVA has a greater discriminatory power than binary typing, with a turnaround time of 2–3 days; its use in parallel with binary typing was critical for the timely identification of a relationship between the isolates. PFGE is considered to be the gold standard of bacterial molecular typing because of its high discriminatory power. It is, however, time-consuming (requiring 4–5 days), technically demanding and not as portable as PCR-based typing methods. In this outbreak, it provided the confirmatory link between the clinical and environmental isolates.

Chocolate profiteroles were initially identified as the likely vehicle of transmission based on presumptive positive PCR results. PCR methods provide more rapid results than culture-based methods, and this prompted a public alert identifying profiteroles as the contaminated food source. When the PCR result was later deemed a false positive, chocolate profiteroles could no longer be viewed as the definite source of infection. Three further pieces of evidence nevertheless justified the decision to temporarily remove the products of Company X from hospital menus: the matching molecular profiles of isolates from the patients and from environmental samples from Company X; the patients’ food consumption histories; and the detection by Company X of Listeria species in a profiterole produced on 2 April. There were no further infections after this decision was taken.

Rapid molecular subtyping was combined with reviewing an electronic hospital menu database to provide timely microbiological and epidemiological evidence that the three patients in the reported cluster probably acquired their infections from a contaminated hospital dessert produced by Company X. The identification of a likely source of infection and the quickly implemented control measures probably prevented further cases. This cluster of infections highlights the need for vigilant regulation and approval processes for food suppliers who service hospital populations.

Foods with a high likelihood of transmitting listeriosis consumed by three Sydney patients diagnosed with listeriosis, by manufacturing company, 20–26 March 2013

 

Patient 1

Patient 2

Patient 3

Company

Creamy rice pudding

✓

✓

✓

Y

Chocolate profiterole

✓

✓

✓

X

Mango cheesecake

✓

✓

  

X

Bread and butter pudding

✓

  

✓

X

Sandwiches (cold meats)

✓

✓

  

Z