Bibliographic record
Abstract
To the Editor: So there I was, reviewing my upcoming lecture notes for third year students in the Geriatric (or, as I prefer to call it, ‘Healthy Aging’) course at CMCC when I saw with great interest the title of Dr. Morgan’s article in the September 2004 issue of the JCCA.1 In roughly two weeks time I was going to review the principle theories of the aging process from telomeres to caloric restriction, from superoxidases to comparing aging to Darwinian evolution,2 and here was an article that might augment, and possibly even provide an interesting perspective, on this topic. Regretfully, my hopes where dashed on the shores of an article with such an unusual study design that it was, in my opinion, unable to successfully answer the question it asked. Dr. Morgan sought to compare mortality rates of chiropractors (gathered over two different time periods) to the general population and to mortality rates of medical doctors. The mortality rates of chiropractors were drawn from two data pools: 1969 to 1979 and 1990 to 2003 (what I will refer to as the ‘first’ and ‘second’ data pools respectively). Using data gleamed from either Dynamic Chiropractic’s ‘In Remembrance’ or ‘Who’s Who in Chiropractor-a Necrology’, Dr. Morgan reported that the mortality rate amongst chiropractors was not only lower than that observed in the general male population, it was also lower than the mortality rate reported among medical doctors. There are several problems with the structure of this study. First, as Dr. Morgan noted, he could only obtain mortality rates from a select few male chiropractors in these two time periods. The problem is that women live, on average, 4 to 10 years longer than their male counterparts.3 Since this study only had access to the mortality rates of male chiropractors, whereas data from medical doctors undoubtedly had data from both sexes (Dr. Morgan was uncertain on this point) it is not surprising that chiropractic mortality rates would score lower. In fact, it would have gone against every other epidemiological study published in the past 50 years if it had reported any else but. Another problem was the age of male life expectancy from the general population Dr. Morgan chose to use as a reference point. Specifically, Dr. Morgan compared the life expectancy of chiropractors (calculated to be 73.4 years and 74.2 years from each data pool respectively) to an average life expectancy of men in the general population of 76.9 years, using a reference from the year 2002.4 However, since the data gathered from chiropractors covered a 35-year time span, Dr. Morgan could have just as readily used a value of 72.7 years (taken from a 1990 source)5 or 73 years (taken from a 2000 source).6 Had he done so, this study would then have had to report that the male chiropractors did, in fact, live longer than their male counterparts from the general population. Another problem with this study was both the total numbers of deaths among practitioners examined as well as the time frame over which they were collected. The total number of chiropractors included in Dr. Morgan’s study, from all the hundreds, (if not thousands) that no doubt died between 1969 and 2003, were 55 from the first data pool and 67 from the second data pool. This represents roughly three persons a year over the 35 years spanned in this study. These numbers were then compared to 530 medical doctor deaths recorded in only one year – 1995. In essence, Dr. Morgan may have been trying to draw statistical conclusion based on a practitioner’s age at the time of death of three or so male chiropractors compared to over 500 medical doctors (sexes unknown) in the same year. One of the greatest problems with Dr. Morgan’s study is that it cannot control for advances in health care made during the time covered by this study. For example, the 55 chiropractors in the first data set died somewhere in the years between 1969 to 1979. Thus, they could not have benefited from the strides made in the fields of diagnosis (CAT scans, MRIs and so on) or treatment (cardiac surgery, cancer therapy, transplantation technology and pharmaceuticals) that medical doctors from the 1990s would have had access to prior to their deaths in 1995. A list of the technologies available to a person in the 1970s compared to a similar list of available technologies in 1995 would indeed be a formidable group of health care options, particularly among those illnesses responsible for the highest rates of mortality: heart disease, cancer, lung disease, stroke and diabetes. Chiropractors, of course, do not live in isolation. Even if spinal care conveyed oncostatic or antihypertensive benefits such gains would most likely be obscured not only by lifestyle, but also by an even more omnipresent force. A few years ago, I had the opportunity to attend the 17th Congress of the International Association of Gerontology in Vancouver, BC. One of the keynote speakers was Dr. Thomas B.L Kirkwood, a molecular geneticist recognized as a world expert in the area of the aging process.7 After taking the audience through the evidence of the more common theories of aging, he then stated that the most important factor that he had found that determines which individual in a population lives longer than another individual in the same population, the factor that seems to trump all others, is good old fashion chance. Certainly the finding from Dr. Morgan’s study, resting on a small number of chiropractors from the gender most likely to shed their mortal coil, roughly half of whom died during a less technologically advanced time in health care as compared to a sample of medical doctors, using arbitrarily chosen statistics from the general population, may easily be attributed to chance alone. I submit that, as alluded to by Dr. Morgan, a more insightful study would be to monitor qualitative outcomes among persons (perhaps chiropractors) receiving chiropractic care as compared to persons not receiving chiropractic care (perhaps medical doctors), if such a study could be constructed. Thus, rather than look at raw numbers of longevity, it might be more informative if outcome measures included a practitioner’s morbidity, abilities to perform both their Activities of Daily Living (ADLs) and Instrumented Activities of Daily Living (IADLs), ability to optimize their level of health and the ability to maintain their independence. In my experience, virtually every expert in the field of geriatric care emphasizes the importance of health promotion and prevention over life span. I understand the intent of Dr. Morgan’s study, to challenge what he sees is an oft-quoted adage emanating from within some chiropractic circles. Not unlike a study by Grod et al.,8 unsubstantiated claims made within the profession must be challenged for their veracity, and perhaps the claim that chiropractic care can purportedly prolong life is such a claim. Unfortunately, it seems to me that this study did not, and could not, answer the question it meant to answer. Respectfully submitted, Brian J. Gleberzon, DC Associate Professor, Canadian Memorial Chiropractic College
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".