BRICS, the UN, WHO, FAO and politics : Research versus ‘research’

Why some research reports should not be used to shape public opinion or legislation.

It is important (yet apparently contradictory) to address obesity and Non-communicable diseases (NCDs) in a positive, constructive manner. The aim in this article is not to address the interpretation of information by the pro-tax lobbyists. Since so much pro-tax discussion has taken place in different forums, the research interpreted and quoted in those forums are not the focus of this opinion. It is time to consider the other side of the argument as well. Questions that came to mind as a consequence of attended debates and/or literature research, form the basis for this article.

With the above mentioned perspective in mind it is important to distinguish between the following (as brilliantly addressed in the 2016 Rosalind Franklin Lecture by Dame Anne Glover, an internationally renowned scientist. The title of her presentation was: ‘Why evidence matters’):

? Evidence versus Assumption,

? Relevance versus Priorities / Agendas,

? Transparency versus Obfuscation,

? Controversial evidence / trustworthiness of evidence / ‘a hunch’ / inappropriate use (misuse) of evidence versus the appropriate use of evidence,

? Appropriate analysis, interpretation and conclusions from data versus misuse of data,

? A populist / controversial (newsworthy) view versus scientific reality.

Some interesting statements made by her in her lecture implied or stated:

? Politicians hate uncertainty, while science thrives on uncertainty and exists to obtain further clarity. The manner and substance regarding scientific facts must therefore be clear and attempt to address possible logical solutions.

? Just because something is not understood, it does not make it wrong.

? Empathy for public concern and well-being is at the heart of all scientific efforts.

? Without transparency in research and arguments, there can be no trust and without trust there is no innovation or progress.

? Research not communicated [correctly], is equal to research that has not been performed.

? The correct interpretation of ‘consensus scientific opinion’ and ‘peer review’.

? Vested interests can be a problem, yet, if company funded research is so mistrusted, it can be checked by governments. It is not correct to ignore company funded research and brand it as fraudulent without repeating the exact experiment. Most governments do not want to be involved in that function.

? It is important to understand the terminology definitions, their implications and correct use.

Listen to this interesting lecture at: https://m.youtube.com/watch?feature=youtu.be&v=dP3e67sqG6s  .

When reviewing the subject of NCDs, it seemed that there were (and are) several questions that apparently have not been adequately addressed in this debate. In scientific research these questions would have been the foundation of hypotheses to guide the research and its conclusions while laying the foundation (before capturing any information or doing any active research) for the statistical analysis of prospective data generated by the research.

This is a basic scientific research approach that sometimes apparently fell by the wayside in recent years. For example:

Different types of research should be interpreted differently. There is a difference between the value of, reason for and interpretation of the following that all result in research papers (in no specific order, for example):

·               Meta-analysis of research data. This is currently extremely popular and it sounds quite impressive when it is quoted as a source of research results. Let us start with the reliability of this type of ‘research’ as addressed for example in a publication from 2017 (https://arxiv.org/ftp/arxiv/papers/1710/1710.02219.pdf ). As background it states the following: “Many researchers have studied the relationship between diet and health. Specifically, there are papers showing an association between the consumption of sugar sweetened beverages and Type 2 diabetes. Many meta-analyses use individual (primary) studies that don’t adjust for multiple testing or multiple modeling – and thus provide biased estimates of effect. Hence the claims reported in a meta-analysis paper may be unreliable if the primary papers do not ensure unbiased estimates of effect”. It concluded: “Given that testing is at the 5% level and the number of comparisons is very large, nominal statistical significance is very weak support for a claim. The claims in these papers are not statistically supported and hence are unreliable. Thus, the claims of the meta-analysis paper lack evidentiary confirmation”. Note that this evaluation was carried out in a Department of Biostatistics;

·               Clinical trials (human) According to the WHO such a trial “is any research study that prospectively assigns human participants or groups of humans to one or more health-related interventions to evaluate the effects on health outcomes. Interventions include but are not restricted to drugs, cells and other biological products, surgical procedures, radiological procedures, devices, behavioural treatments, process-of-care changes, preventive care, etc. (https://www.who.int/topics/clinical_trials/en/). According to a paper published in 2017, most interventions tested in ‘First in Human’ clinical trials will NOT lead to any societal benefit. (     https://www.sciencedirect.com/science/article/pii/S1359644616304342 ). Already in 2014 in an Article published in the Journal of Clinical Epidemiology (https://www.sciencedirect.com/science/article/pii/S0895435613004666 ), the conclusion was that “the statistically significant results of many randomized controlled trials (RCTs) hinge on small numbers of events. [It proposed a] Fragility Index [that] complements the P-value and helps identify less robust results”. Can these results be generalized to make headlines? Apparently not ;

·               Randomized placebo control trials In 2013 the following was stated about the use of a placebo “the placebo effect is caused by an expectation (people taking a placebo may experience something that they expect to happen, such as pain relief) or through classical conditioning, or both…” Different medical associations provide different guidance in the use of placebos in health situations or –research (https://theconversation.com/using-placebo-in-medical-practice-an-ethical-conundrum-14773);

·               Nested case control studies (an example of such research reports at: https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(16)31989-4/abstract?code=lancet-site) ;

·               Intervention studies (for guidelines for these studies, go to https://www.ncbi.nlm.nih.gov/pubmed/22129662 );

·               Randomized controlled trials or –studies (RCTs) In an article headed: "Perspective: Randomized Controlled Trials Are not a panacea for diet-related research" (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4863268/ ), it is stated by the authors: “As a practical matter, RCT designs allow for only a limited number of factors (usually 1 or 2) to be allocated at a time. Although RCTs can be used for “whole-diet” approaches [e.g., the Women’s Health Initiative (WHI) Dietary Modification arm (67, 68) and the PREDIMED (PREvencion con DIeta MEDiterranea) trial (69, 70)], more typically they focus on a single food or one or a few nutrients. This may reflect the perception that obtaining adherence to a request or demand to change one’s entire diet is difficult and therefore neither feasible except under exceptional conditions nor readily translatable to public health practice. Despite the appeal to focus narrowly , doing so does not represent a realistic way to make meaningful change to prevent chronic disease, especially when the preponderance of evidence indicates that eating patterns associated with whole foods are much more strongly predictive of health outcomes than are individual foods or nutrients (70–73).” This implies that such studies for example on sugar, fat or anything else will not reflect an overall view, and when overall diet is studied, conclusions cannot be drawn on specific food or beverage ingredients or –categories;

·               Observational studies It is stated that “An observational study is an epidemiological research study that doesn't include some intervention or experiment. Subjects are studied under natural living conditions… The scientists use information from things like surveys and medical records to see certain subjects have something or things in common. These things are called 'exposures.' When a sufficient amount of research indicates an exposure increases the risk of the outcome, then the exposure is known as a risk factor… Most observational studies fall into one of three categories, case/control studies, cohort studies/ and cross-sectional studies… Observational studies are extensive, often with thousands of participants, which gives strength to the results, but they usually can't determine any cause. Since subjects live normally, there are usually too many possible exposures that can confound the results.” (https://www.verywellfit.com/learn-about-research-observational-studies-2507082 );

·               Prospective cohort studies What is a cohort study (whether prospective or retrospective, case-controlled or not? According to https://www.statsdirect.com/help/basics/prospective.htm , “A prospective study watches for outcomes, such as the development of a disease, during the study period and relates this to other factors such as suspected risk or protection factor(s). The study usually involves taking a cohort of subjects and watching them over a long period. The outcome of interest should be common; otherwise, the number of outcomes observed will be too small to be statistically meaningful (indistinguishable from those that may have arisen by chance). All efforts should be made to avoid sources of bias such as the loss of individuals to follow up during the study. Prospective studies usually have fewer potential sources of bias and confounding than retrospective studies…. A retrospective study looks backwards and examines exposures to suspected risk or protection factors in relation to an outcome that is established at the start of the study. Many valuable case-control studies, such as Lane and Claypon's 1926 investigation of risk factors for breast cancer, were retrospective investigations. Most sources of error due to confounding and bias are more common in retrospective studies than in prospective studies. For this reason, retrospective investigations are often criticised. If the outcome of interest is uncommon, however, the size of prospective investigation required to estimate relative risk is often too large to be feasible. In retrospective studies the odds ratio provides an estimate of relative risk. You should take special care to avoid sources of bias and confounding in retrospective studies”. Also consult “Observational research methods. Research design II: cohort, cross sectional, and case-control studies” for more information: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1726024/pdf/v020p00054.pdf ;

·               Literature reviews According to the UQ Library (https://guides.library.uq.edu.au/c.php?g=210361&p=3605901 ) “[a] literature review is a critical assessment of the literature pertaining to a particular topic or subject. It is a 'systematic, explicit, and reproducible method for identifying, evaluating and synthesising the existing body of completed and recorded work produced by researchers, scholars, and practitioners' Fink, (2005).” A limitation of this type of review is “the complete reliance on previously published research and the availability of these studies using the method outlined in the search methodology [ ] and the appropriateness of these studies with the criteria of the selection/exclusion procedure [ ].(https://chesterrep.openrepository.com/bitstream/handle/10034/86824/chapter+5.pdf;jsessionid=F7A405A9C0E53358A8F795EA4711761B?sequence=6 );

·               Systematic research reviews Read more about it at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3415860/;

·               Toxicological studies Read more about it in Biomarkers in Toxicology, Chapter 2 – Rodents model for toxicity testing and biomarkers at https://www.sciencedirect.com/science/article/pii/B9780124046306000026 ;

·               Animal trials Read more about this at https://speakingofresearch.com/2008/07/25/92-of-statistics-are-taken-out-of-context/ . This is research where animals are used to predict what could happen in human trials and is therefore taken out of context many times to make a case that is poor or not yet proven. Indeed a case of ‘three rodents and a hamster does not justify a law or tax….’. Earlier this year a researcher actually found that transplants of human tissue into rodents start to change to display rodent genes – placing a question mark over many Animal Trial Outcomes reported and acted on by Organizations and governments…;

·               Laboratory trials https://www.fda.gov/food/foodscienceresearch/default.htm

and more.

Can the results from different types of research be ‘lumped together‘ to make a case? Not without reporting the limitations in such a document.

Other issues that seems to have fallen by the wayside when it comes to research is, for example:

Is the quantification of risk (as expressed by percentages) theoretical or aligned to reality?

Therefore:

?       When the influence of drugs, metabolic pathways or biological effects are addressed in the research, are interactions taken into account – if so to which extent and if not, why is the one-dimensional view of the research not placed in perspective to reality?

?       Doubt is surfacing regarding the ‘peers’ used in peer-reviewed publications. Who are checking their work? (‘Who are watching the watchers’)?

?       When can results from animal trials be extrapolated to humans, and when not? This is seldom addressed. Over time it seems that it became more acceptable just to ignore the real possibility that animal research results do not necessarily apply to humans (as studies on rodents with regard to the human microbiome seems to indicate).

?       With regard to statistical analysis, applying statistical analysis after the fact (not planned at the outset), can lead to many misinterpretations and the emphasis of issues that would otherwise not have warranted attention.

?       This seems to be exacerbated by the lure of large databases accrued over time (initially with little or no form of research or analysis in mind) and the potential for seemingly revolutionary results and insights that can catch the headlines.

?       It is important to understand that such databases can indeed provide some insight and direction provided it is analyzed and interpreted in the context within which the data accumulated.

?       This also applies to data obtained through (for example) marketing research and point of sale.

Inferential statistics should be a standard requirement to determine the significance of observed effects. It is still the measure used and accepted. Do we need to throw away 200 years of research to make a case for current research findings that requires the Bayesian Statistical Theorem from 17?? and make results a reality that ensure that current (otherwise perhaps questionable) research results are ‘acceptable’. The verdict is still out on that. Anything based on proving a ‘guess’ by the statistician about a field of study unknown to him or her must be questionable. Be that as it may, according to currently accepted research practice, the following is a concern:

?       The manner in which differences (such as increases in prevalence or decreases in blood glucose) were calculated or manipulated is very important. Sometimes a slight difference in real terms can become a high percentage depicting a huge difference after data manipulation and -calculation. Effectively a lie, or at the very least misleading.

?       Descriptive statistics alone are not adequate when a report has far-reaching implications in (for example), political decisions.

?       Despite the debate that seems to be raging in the statistics discipline regarding the interpretation of the p-value and whether it still applicable (in an effort to accommodate ‘big data’ and the economic fortunes that can be made if truths are changed a little), any statistical interpretation (however much conflicted) will still always have to make sense.

?       Inferential statistics determining the level of significance (or the lack thereof) regarding the detected differences in the results, are essential – and still required.

?       Results can never be ‘almost significant’. It is either significant (or highly significant) or not significant (or not highly significant).

?       On the other hand, it is unfortunately true that statistics can indeed prove anything depending on the researcher and the reporter of the findings. Pages of explanations detailing incredible data analysis, research planning and –execution does not imply that the outcome of the research was significant, valid or a logical epiphany.

?       This also applies to causality. If there is no causality (logical cause and effect), a significant difference or –result means nothing. Usually such results are accidentally observed and are (at a stretch) indicative of further research being required to explain the apparently detected, yet unexplained significance.

This is especially important when the database in question is based on the collection of data generated through recall questionnaires, polls or surveys since the questions were posed in a specific context that is not necessarily taken into account years after the fact.

?       It is notably true of replies to open-ended questions in questionnaires or focus groups.

?       Although scientists would like to believe that respondents will follow instructions precisely and report use or reaction results correctly when left to their own devises, human nature is unfortunately not so precise. In the social sciences it is a field of study on its own addressing observation and reporting. It is not uncommon for respondents to respond in a manner that they think the researcher will find acceptable. This is certainly true in South Africa where consumer research has to be well planned and executed with checks and balances to prevent any halo-effects and more. It is indeed very important to follow the Sensory Science ‘rules of thumb’ (as listed for example by Heymann and Lawless) when conducting any research involving members of the public to obtain a true reflection of the topic being researched. This is also known to be true after decades of personal research experience in the field.

?       Sometimes the calculation and reporting of average values may be acceptable; sometimes frequency analysis would be more sensible. It is important to know the difference and use it correctly.

It is furthermore important to take into account that a survey conducted, for example, 5-10 years before another similarly named survey (reflecting a different set of, or other parameters) can only be compared with difficulty (the old yet valid ‘comparing apples with apples’ requirement).

?       If this is not done, the results and interpretation of data may be skewed quite significantly – something that no amount of statistical ‘tweaking’ can correct or validate.

?       In recent years some published and quoted research seems to lack this fundamental requirement, leading to the ignoring of causality in results and conclusions. Cause and effect in itself is a measuring instrument for the validity of data analysis, results, interpretations and conclusions. Without it, conclusions are no more than speculation.

Another requirement of valid research that apparently fell by the wayside in some instances, are the requirement for ‘repeat ability’ and its concomitant ‘certainty’.

?       If there is any question whether the same results would be obtained if the research in its totality was conducted again, it should be stated and the results interpreted in that manner.

?       Usually further research is suggested from the expert point of view of the researcher(s) – which is how it should be. It is when this aspect is lacking and speculation is produced as fact that very strange conclusions can be reached (and presented in highlights in the press to the unsuspecting public). It is then that the correlation between the irrelevant is elevated to fact and decisions result that has far reaching consequences.

?       If there is no logic to results, it is better to double check and check again – for example, can there really be a correlation between the greenness of trees, cancer and the color of cars passing a location? If there is no logic – make sure. If there is no causality, there is no case.

?       As mentioned previously, it is a well know saying that ‘statistics can prove anything’. Unfortunately it is true. It is a pity that some researchers (and the people that seek news to report irrespective of origin, logic or sense) seem to have lost track of that truth. It is even worse that researchers that know better are staying quiet in the face of scary decisions that are made based on such research conclusions.

Research is not about emotions and getting your work out into the public domain as fast as possible (complete or incomplete) – it is about facts and new insights (well proven, well researched). Being excited about research is highly recommended, provided it does not cloud judgement.

?       Even then, when the research methods are discussed in detail over several pages of a research paper, the data almost over-analyzed into the finest detail and reported in every possible manner – if the outcome cannot logically be caused by the variable(s), the rule in research used to be that such results should be proven through repetition or to abstain from reporting it as fact until it could be done.

?       Researchers have a responsibility – a very grave responsibility to people in their communities, countries and globally who, without the necessary knowledge, rely on the integrity of the work from scientists as reported; Information that they access and use.

?       Some arguments may be raised lauding peer review and the apparent value of this practice to validate research – apparently placing such publications and the research that they report, above reproach. Unfortunately, peer review is apparently also not what it used to be. Serious questions are being asked about the objectivity implied by the ‘review by peers’ process. Knowing (or not knowing) who the ‘peers’ are, is becoming an issue with articles being questions by proven experts in a specific field. The peer review process itself is suspect and cannot in itself be used as proof of the validity or logic (or lack thereof) of research reports.

It is true that a moment in the sun is very important to researchers that have to ‘publish or perish’ to stay in positions (tenure) at tertiary and research facilities.

?       Although this questionable state of affairs has to be viewed with great sympathy, it gave rise to a plethora of magazines (online) that publish anything – almost a magazine version of the Vanity Press where authors self-publish books and market them because the conventional publishers seem to take a long time to reach a decision regarding the publication of texts.

?       This is understandable, since we live in a time of instant information and social media frenzies where theft or usurping of research can easily take place, thus robbing a usually diligent researcher of vital publications.

?       It is also not uncommon nowadays for some researchers to publish almost 40 papers annually when other researchers manage only one or two papers. All of the above makes it important to note who the authors are and more importantly on which study the report is based. For example, quoting five reports based on the same study (with the author-list order slightly changed to give more individuals the primary author position), does not equate to increased validity of the findings or justification for the use of phrases such as ‘much research’ or ‘many reports’ to indicate additional proof – where there is actually little or none. It is only when viewing reports with the above mentioned in mind that it becomes clear just how many research papers published in different magazines (legitimate or not) are actually reflecting the same work by the same researchers. This should be a concern, since any mistakes made in the original research is diluted into several reports or articles where it can easily be overlooked.

?      A good example of this is the ‘different’ sources of information linked to obesity and the apparent effectiveness of a Sugar Tax in Mexico that comes from the analysis of health surveys conducted with a different purpose in mind. Another example is the apparent proof of tax success in Cook County USA that apparently left much to be desired and led to the repeal of the tax after a few months. Not to mention the court cases to label sugar sweetened beverages the same way as tobacco that failed in US courts.

In a sense it is a sad comment on the times and unfortunate that researchers should rather resort to additional caution when reporting research findings, than the statement of absolute, irrefutable fact when apparently desperate for the all-important publications. Yet this is what is required. It is incorrect to make absolute claims when research cannot be repeated to indicate that the same results can be obtained – especially when it comes to animal research. Also, taking findings out of context to prove a point, is deplorable and confusing to the consumers that only see the headlines.

Why is all of this crucial at this time?

With the BRICS Summit looming in South Africa and the third High Level Commission on Non-Communicable Diseases called for by the World Health Organization (WHO) of the United Nations (UN), some people are looking at the strange decisions by governments and the WHO – perhaps from the wrong perspective. Perhaps we have been looking for explanations in the wrong place?

The questions should be “Where do the WHO get their research results”, since governments seem to accept the advice of the WHO without question. A study of the WHO website specific to Non-communicable diseases makes for interesting reading. First of all, sugar seems to have ‘disappeared’ and Tuberculosis (a communicable disease) has appeared on the site.

‘Bad’ Lipids now seem to gain attention.

The source of all the research findings, tweets, messages is also provided – it is a well know external 'pay for research' group…. They use and instruct (actually seem to direct), what is said, how it is said, when, to whom and so on.

What about the level of research?

It seems to differ from good to really poor since there is no differentiation between the types of research reported. If it can make a headline, anything goes. So – if a research company also have clients (other than the WHO) that would like to blame sugar, carbohydrates or trees for that matter for dental caries (for example), a good business decision would be to also send the ‘results’ to the WHO where it is lauded as ‘independent research’.

Really?

The question is who is funding the research company and why their loyalty to the research ethic is not scrutinized or questioned as with research sponsored by targeted companies in the Food and Beverage Industries?

What about the research findings from such a source?

Structured? Yes.

Planned? Yes.

Manipulative? ….. Independent? ….. The answer is clear if it is done to a pre-determined plan, executed by anyone willing and reported in newly created Journals or Journals that will publish anything if they are paid (even the peer review is paid) in the ‘Vanity Press’…

Once again, it is important to note that the WHO acts and almost intimidates and pressures UN member nations, based on this type of research (irrespective of logic) without question, immediately -- and have been doing so for several years. In a previous article posted here, it was mentioned how decisions and directions from the WHO were highly questionable (https://www.nature.com/articles/ijo201771 ). Now we can perhaps begin to understand the source of the pressure on the WHO itself? What is even scarier is that some governments seem to be indicating that they would also prefer this source of research in future (at a price) and to the detriment of researchers in their own countries and on their own continents – all in the flurry of globalization.

What is the task of the WHO?

The WHO is tasked in general (inter alia) with health, food safety and –quality, human nutrition and well-being. From being a respected body lauded for the Codex Alimentarius that guides food formulation, ingredient safety and –limits and guiding food legislation internationally, another defined role emerged. This role, unfortunately, seems to be focused on an interpretation and validation of research and research findings that raise many questions.

The validity of research (both nationally and internationally, when using extrapolated data, as the WHO admitted to using) that is presented as the motivation for any drastic course of action, while taking note of the updated WHO global initiative appendix 3 from 3 May 2017 (https://www.who.int/ncds/governance/q-and-a-updated-appendix3-may2017.pdf?ua=1 ), is cause for concern. The scientific grounding of the studies reported are suspect – and in many cases even so indicated by the authors, since the research reported were methodologically compromised. As indicated earlier in this text, observational studies, meta-studies, laboratory experimental studies and more, all have severe limitations which are not always acknowledged.

The apparent inability to link research results to (for example) body mass index, glycemic index and more is a concern. (https://www.nature.com/ejcn/journal/v61/n1s/full/1602939a.html ). This has not improved since 2007. There seems to be a lack of balanced, scientific information and empirical research identifying the true nature of the NCD problem and how to address it successfully in South Africa and the world. It cannot be assumed that taxes/levies on sugar sweetened beverages (SSBs) or any other ingredient or food group will automatically cause individuals to make healthier, more expensive choices. What will ensure that individuals do not make ‘unhealthier’, cheaper choices? The research organization apparently does not address that? Not part of their brief?

It is interesting how reports on the assumed decrease of obesity in Mexico have faded away. This is the country used as the model for taxes and levies on ingredients and/or food- or beverage categories. Nobody seems to monitor the effectiveness of implemented taxes with regard to decreasing obesity and diabetes in countries that applied the tax. (This seems to be what happened also to tobacco – saying cancer due to tobacco has decreased and proving the facts are not the same thing). In the case of Mexico and non-communicable diseases (specifically sugar sweetened beverages), if any report is forthcoming at all, it is about sales figures which cannot be a reflection of consumption, obesity levels or the prevalence of diabetes. One publication actually stated that a small decrease in obesity levels and diabetes will only probably be seen by 2025 …. Not very effective then, since Mexico has been taxing sugar since 2014…

Does anyone actually care?

Apparently not.

In South Africa the emphasis would have shifted to cancer from 2018 (another non-communicable disease). The levy-principle is clearly in place and ready to be used at random to tax any food or drink product or ingredient deemed as ‘unsuitable or unhealthy food’ quickly and efficiently – and annually. This will be very bad news for countries with a 55% unemployment rate, hunger, water restrictions, budget deficits, and a fiscus under severe strain where salaries are worth less every month...

Since 01st June 2018 when the second meeting of the UN and WHO High Level Commission on non-communicable diseases did not agree on taxing of ingredients to address nutrition and health issues (confirmed on the 07th June 2018), the WHO (and probably the BRICS Summit in South Africa) will address Tuberculosis as the cause of approximately 80 000 deaths globally per annum, instead. At last, a logical, wise decision that can be applauded. At the same time South Africa released new figures from a study conducted in 2017 indicating that contracting HIV/AIDS has reduced by 44% (according to news reported by eNCA on the 18th June 2018) …. What would STATS SA say?

What happened to the ‘science’ and ‘research’?

It is probably difficult for some scientists to understand how figures or percentages for un-diagnosed diseases are derived, since they are not yet confirmed (being non-diagnosed and therefore not confirmed or ascertained). Symptoms can be similar for different diseases with completely different causes. Research used to motivate food- or ingredient taxation / levies especially, are now questioned, for example in:

?       Australasia -- a directional study indicated that the population of that region was considered to be one of the most obese in the world, despite a decrease in SSB consumption.

?       The USA -- an increase in heart disease (heart arrhythmia and heart attacks) were observed after the implementation of regulations to reduce the intake of sodium (e.g. table salt) since it causes an electrolyte imbalance. This is leading to questions about the delicate balance required between Sodium, Potassium and Calcium (as well as Magnesium required for energy exchange in the body), for the heart muscle (and the brain) to function correctly -- and the effect of reduced sodium consumption (by law) on this balance. Selective regulations, taxation or levies may have seemingly unrelated, unintended negative consequences.

?       The USA -- Despite many years trying to teach American consumers to eat healthier and make healthier food choices (by the American Dietetic Association) and using all means to ensure this, Americans are apparently more obese than ever.

?       The United Kingdom -- published research used to motivate tax/levy changes and adjustments were withdrawn from the publications with apology by the publishers’ years after the fact, since it was found to be radically flawed.

Unfortunately, sad and tragic circumstances caused by disease, leading to (for example) the development of Diabetes by lay individuals is exactly that – tragic. The experience of disease cannot automatically be elevated to the level of undisputed, undeniable fact and science, even when the apparent truth of the situation weighs heavily on the witnesses to or participants in such sad circumstances. The mere fact that a number of people are obese does not automatically equate to an obesity- and diabetes pandemic or a crisis caused by sugar or any other ‘dependency’.

Another example of layman’s expertise seems to implicate weight loss. Weight loss, after following a specific diet (sometimes somewhat peculiar in nature), is an individual cause for celebration – not automatically the panacea for weight loss and healthy living. It is unfortunate that this type of testimony take on increased, unwarranted pseudo-validity for some audiences. These audiences seem to consist of individuals associating with such an approach that is easier to understand, rather than with the difficult world of science and valid research that address the cause, not just the effect or outcomes of lifestyle diseases or its possible prevention.

Unfortunately, perceived facts must be tested and proven through well planned, precisely executed, repeatable, verifiable research delivering significant, correctly interpreted results, conclusions and/or suggestions that can be generalized to a statistical population.

It is also usual to indicate where research failed in its purpose or where further study is required. Without the aforementioned, any remarks, headlines or apparent facts spread through different types of media, can be viewed as sensationalist, misleading and dangerous due to its potential effect on the unsuspecting, trusting public.

It is owed to the voiceless and vulnerable among us. They, and generations to come are influenced by research ethics (or the lack thereof), displayed today.

An Excerpt from “From Healthy to Unhealthy: A perspective on non-communicable disease” Part 1. ?2018 Author: Dr. C M (Karin) Blignaut (Pr.Sci.Nat.) Ph.D (Interdisc.), Ph.D (Fd Sc.), CMB Consultants @ e-Wise Knowledge Library, South Africa.

Source list available on request.

Image source: 240_F_2632672_OTz0AK89JxkGQE1gM9J7mQs2BUnxF3

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