Population Health Metrics - Latest Comments

Why are we only given information on 3 out of the 8 SF-36 subscales?

Tom Kindlon — 2009-11-05T00:00:00Z

Reading this paper, one could be forgiven for thinking that the SF-36 questionnaire only has 3 subscales: Physical Functioning, Mental Health and Social Functioning as that is all we are given information on. In fact, of course, the SF-36 questionnaire has 8 subscales: Physical function, Role physical, Bodily pain, General health, Vitality, Social function, Role emotional and Mental health[1].

The authors use the empiric definition for CFS[2] which requires at a minimum that the "role physical" and "role emotional" subscales also be measured.

We also know that all 8 subscales were measured in this cohort[3]. So why was the information not given? If one was not giving the authors the benefit of the doubt, one could speculate that it was because Table 4 would not look as good, as the Chi-squared calculations would not reach statistical significance for the missing data. But that would be speculation - there could be other reasons for the missing information. Perhaps the authors could post the relevant data now. I am not simply being mischievous - I would be interested in particular to see what are the scores for Classes 1 and 2 which include nearly all of the CFS patients (88/92, 95.7%).

Tom Kindlon

References:

[1] Ware JE, Sherbourne CD: The MOS 36-item short form health survey (SF-36): conceptual framework and item selection. Med Care 1992, 30:473-483.

[2] Reeves WC, Wagner D, Nisenbaum R, Jones JF, Gurbaxani B, Solomon L, Papanicolaou DA, Unger ER, Vernon SD, Heim C: Chronic fatigue syndrome--a clinically empirical approach to its definition and study. BMC Medicine 2005, 3:19.

[3] An evaluation of exclusionary medical/psychiatric conditions in the definition of chronic fatigue syndrome. Jones JF, Lin JM, Maloney EM, Boneva RS, Nater UM, Unger ER, Reeves WC. BMC Med. 2009 Oct 12;7(1):57. - see Tables 5 and 6.

There has been criticism of how CFS is defined in this study

Tom Kindlon — 2009-11-05T00:00:00Z

I thought it would be useful to point out that there is controversy [1,2] with regard to the criteria [3] used in this study to define Chronic Fatigue Syndrome (CFS).

For example, the criteria for CFS used in this study do not even require a patient to have fatigue. The authors say: “We used the Multidimensional Fatigue Inventory (MFI-20) [4] to measure characteristics of fatigue” but they do not give the thresholds. Given the MFI-20 has five subscales: (General fatigue, Physical fatigue, Mental fatigue, Activity reduction and Motivation reduction), one would probably suspect that a patient would have to score poorly on one of the headings which have fatigue in their title. But the actual criteria are: a patient needs to score >=13 on MFI general fatigue or >=10 on reduced activity. Note, one could score >=10 on the MFI reduced activity questions without necessarily being fatigued (one could be depressed or even lazy) (only current major depressive disorder with melancholic features (MDDm) is an exclusion for this definition of CFS). This is despite the fact that in the current paper, the authors say: “Chronic fatigue syndrome (CFS) is a common, debilitating illness whose hallmark symptoms involve fatigue and fatigability”.

Many other questions have been raised about the criteria for CFS that were used in this study. For example, the authors only considered current MDDm to be exclusionary for CFS while the International CFS Study group recommended that conditions (including MDDm) were considered exclusions unless they had been “resolved for more than 5 years before the onset of the current chronically fatiguing illness”[5].

Prevalence figures show that the criteria, that were used for this cohort, are selecting a broader group than previous criteria for CFS. Based on the figures derived from this cohort, the prevalence of CFS was estimated at 2.54% [6]. Other studies using similar methodology (but which did not operationalize the criteria [7] for the CFS in the same way as this study) estimated the prevalence of CFS to be 0.235% (95% confidence interval, 0.142%-0.327%) and 0.422% (95% confidence interval, 0.29%-0.56%) [8,9].

Tom Kindlon

References:

[1]. Jason LA, & Richman JA. How science can stigmatize: The case of chronic fatigue syndrome. Journal of CFS 2007;14:85-103.

[2]. Jason LA, Najar N, Porter N, Reh C. Evaluating the Centers for Disease Control's empirical chronic fatigue syndrome case definition. Journal of Disability Policy Studies 2009;20;93.

[3]. Reeves WC, Wagner D, Nisenbaum R, Jones JF, Gurbaxani B, Solomon L, Papanicolaou DA, Unger ER, Vernon SD, Heim C: Chronic fatigue syndrome--a clinically empirical approach to its definition and study. BMC Medicine 2005, 3:19.

[4]. Smets EM, Garssen B, Bonke B, De Haes JC. The multidimensional fatigue inventory (MFI) psychometric qualities of an instrument to assess fatigue. J Psychosom Res 1995; 39: 315–25.

[5]. Reeves WC, Lloyd A, Vernon SD, Klimas N, Jason LA, Bleijenberg G, Evengard B, White PD, Nisenbaum R, Unger ER; International Chronic Fatigue Syndrome Study Group. Identification of ambiguities in the 1994 chronic fatigue syndrome research case definition and recommendations for resolution. BMC Health Serv Res. 2003 Dec 31;3(1):25.

[6]. Reeves WC, Jones JF, Maloney E, Heim C, Hoaglin DC, Boneva RS, Morrissey M, Devlin R. Prevalence of chronic fatigue syndrome in metropolitan, urban, and rural Georgia. Popul Health Metr. 2007 Jun 8;5:5.

[7]. Fukuda K, Straus SE, Hickie I, Sharpe MC, Dobbins JG, Komaroff A. The chronic fatigue syndrome; a comprehensive approach to its definition and study. Ann Int Med 1994, 121:953-959.

[8]. Reyes M, Nisenbaum R, Hoaglin DC, Unger ER, Emmons C, Randall B, Stewart JA, Abbey S, Jones JF, Gantz N, Minden S, Reeves WC: Prevalence and incidence of chronic fatigue syndrome in Wichita, Kansas. Arch Int Med 2003, 163:1530-1536.

[9]. Jason LA, Richman JA, Rademaker AW, Jordan KM, Plioplys AV, Taylor RR, McCready W, Huang CF, Plioplys S. A community-based study of chronic fatigue syndrome. Arch Intern Med. 1999 Oct 11;159(18):2129-37.

A more detailed comparison would need to be made before one could say this replicates the previous study

Tom Kindlon — 2009-11-05T00:00:00Z

Part of the aim of this study [1] appears to be to compare the classes that were drawn up with a previous cohort[2-4]. However it does not, to my mind, deal with this in a particularly rigorous fashion.

The main quantitative comparisons are the percentages that fall in each class (Tables 6 and 7). However, the percentages will be influence by the quantity and type of non-CFS controls used which are not the same in each cohort [to explain why this is important using an extreme example: if there were 1000 non-CFS cases for everyone one CFS case in one cohort, the percentages in each class would be different than if there was a 1:1 ratio of CFS to non-CFS cases in the other cohort].

The first study involved the following[5]: "This population-based case control study enrolled 227 adults identified from the population of Wichita with: (1) CFS (n = 58); (2) non-fatigued controls matched to CFS on sex, race, age and body mass index (n = 55); (3) persons with medically unexplained fatigue not CFS, which we term ISF (n = 59); (4) CFS accompanied by melancholic depression (n = 27); and (5) ISF plus melancholic depression (n = 28)."

This was based on the classification in 1997-2000. These were then assessed during 2003. As one can see in Table 2, in 2003, 6 out of the original 58 CFS patients satisfied the CFS definition[6] as originally operationalized, along with 4 out of the controls. 6 more who had previously been excluded because of previous diagnosis of Major Depressive Disorder with melancholic features (MDDm) were also said to satisfy the original CFS diagnosis. The method for operationalizing the CFS definition[6] was then changed so there was then 43 individuals with CFS (see Table 5).

Although the same method[5] of operationalizing the CFS definition[6] is used when comparing the Wichita and Georgia cohorts, it is a very different way to select patients and controls than the current study[1]. So it is questionable how interesting it is to compare the percentages in each class.

A comparison of the percentages of CFS in each class might have been interesting but that was not done.

Also, apart from the percentages, no tables with quantitative information are presented in the current paper to help the reader compare the class groups to see how valid the comparisons are.

This is made more difficult because the original study gave much more detailed data on the six class solution rather than the five class solution [2]: "As the five- and six-class solutions produced practically identical classes, with the exception of the fifth group in the five-class solution being divided into the fifth and sixth classes in the six-class solution, only the six-class solution is presented in Table 2."

So in that paper, one has classes which have a median BMI of 32, 30 and 30 which are described in the current paper[1] as obese classes while class 5 would be a combination of classes 5 and 6 which have a median BMI of 26 and 27 are classed as non-obese. So numerical comparisons would have been of more use rather than looking at verbal descriptions - describing two groups which have a median BMI of 30 as obese (so approx 50% would have a BMI under 30, one threshold for obesity) and another group which has a median BMI of around 26.5 as non-obese, seems a bit unsatisfactory.

There is a 5 class LCA solution in Figure 1 in one of the Wichita papers which gives some verbal descriptions[4]. As one can see, "obese" is only used to describe two of the five LCA groups:
- Obese, hypnoea (27.93%)
- Obese, hypnoea and stressed (15.32%)
- Interoception (16.22%)
- Interoception, depression (19.82%)
- Well (20.72%)

However, this does not seem to be the same five class solution for the Wichita cohort as the one described in this paper as the percentages don't match up.

References:

1. Aslakson E, Vollmer-Conna U, Reeves WC, White PD. Replication of an empirical approach to delineate the heterogeneity of chronic unexplained fatigue. Popul Health Metr. 2009 Oct 5;7:17.

2. Vollmer-Conna U, Aslakson E, White PD: An empirical delineation of the heterogeneity of chronic unexplained fatigue in women. Pharmacogenomics 2006, 7(3):355-364.

3. Aslakson E, Vollmer-Conna U, White PD. The validity of an empirical delineation of heterogeneity in chronic unexplained fatigue. Pharmacogenomics. 2006 Apr;7(3):365-73.

4. Carmel L, Efroni S, White PD, Aslakson E, Vollmer-Conna U, Rajeevan MS. Gene expression profile of empirically delineated classes of unexplained chronic fatigue. Pharmacogenomics. 2006 Apr;7(3):375-86.

5. Reeves WC, Wagner D, Nisenbaum R, Jones JF, Gurbaxani B, Solomon L, Papanicolaou DA, Unger ER, Vernon SD, Heim C. Chronic fatigue syndrome--a clinically empirical approach to its definition and study. BMC Med. 2005 Dec 15;3:19.

6. Fukuda K, Straus SE, Hickie I, Sharpe MC, Dobbins JG, Komaroff A: The chronic fatigue syndrome; a comprehensive approach to its definition and study. Ann Int Med 1994, 121:953-959.

Authors' response to reader comment

Jolayne Houtz — 2009-10-30T00:00:00Z

We appreciate the attention to this detail by Dr Cheng. The point raised is correct and was indeed due to a skip pattern in the NHANES questionnaire. We repeated the analysis to evaluate the influence on the coefficients of regression within NHANES and predicted diabetes prevalence. Three coefficients (smoking, age 60-69, and age 70+) changed by less than 10%, and the rest remained unchanged. Predicted diabetes prevalence for different state-sex-age-race-insurance categories changed on average by 1.3% and at the most by 3.5% of the values reported in the manuscript, and hence were not sensitive to this error.
Goodarz Danaei and Majid Ezzati, on behalf of the authors

Comments on the missing values of smoking and insurance status

Yiling Cheng — 2009-10-29T00:00:00Z

This article demonstrated a simple and innovative approach to answer an important question that is what the total diabetes prevalences by US states are. I read it with great interesting and noticed the authors mentioned that there were “…50.2% of observations in NHANES were missing either smoking or insurance status…” According to the documentations, this is extremely too high. For example, in NHANES 2003-2004, persons aged 20 years or older had one missing value on question “Smoked at least 100 cigarettes in life” (http://www.cdc.gov/nchs/data/nhanes/nhanes_03_04/smq_c.pdf) and persons aged 0 years or older had only 133 missing values on question “Covered by health insurance”(http://www.cdc.gov/nchs/data/nhanes/nhanes_03_04/hiq_c.pdf). The authors might ignore the skip pattern of these two variables. Incorrectly handling these variables may make incorrect predictions and incorrect conclusions. I am wondering whether the authors can check the document and dataset again and rerun the analyses.

Caution required when making numerical comparisons between Wessely (1997) and the current study

Tom Kindlon — 2007-10-03T00:00:00Z

In his editorial[1], Prof. White says:

"Comorbid psychiatric conditions may have inflated the prevalence. A previous study found an equally high point prevalence of CFS (2.6%), by surveying United Kingdom primary care patients [10]. However, when those patients who also had a comorbid psychiatric disorder were excluded, the prevalence fell to 0.5%."

Reference to this paper[2] is also made in the editorial's concluding paragraph and in the accompanying Reeves paper[3].

A close inspection of table 2 of the referenced paper[2] reveals some strange figures (with regard to the estimates for the CDC '94 criteria mentioned above):

(i) The Oxford criteria for CFS were found to have a lower prevalence, of 2.2%. Given that the CDC 94 criteria would be seen as more restrictive than the Oxford criteria (e.g. requiring symptoms as well as fatigue lasting six months), this suggests an error with one or both of the figures?

(ii) the mean and 95% confidence intervals given for the prevalence rates without co-morbid psychological disorders for CFS (CDC 94) are given as 0.5 (0.1, 0.3) which makes no sense (the confidence intervals should be above and below the mean).

So these two observations mean that I'm not sure how much faith should be placed with some of the figures given in that study.

The methodology of the Wessely study was also different, using attendance at primary care physicians to screen for patients, which could lead to skewed data. The random number methodology in the Reeves study seems stronger.

It should also be remembered that the authors of the Reeves study[3] did exclude many patients with psychological disorders before giving the diagnosis of CFS. So even if one accepts the curious data presented in Table 2 in Wessely et al[2], it seems unlikely we can extrapolate from the drop in the figures found the Wessely study to produce a similar drop in figures found in the current study[3].

Tom Kindlon

[1] How common is chronic fatigue syndrome; how long is a piece of string? Peter D White Population Health Metrics 2007, 5:6 doi:10.1186/1478-7954-5-6

[2] Wessely S, Chalder T, Hirsch S, Wallace P, Wright D. The prevalence and morbidity of chronic fatigue and chronic fatigue syndrome: a prospective primary care study. Am J Pub Health 1997, 87:1449-1455.

Available online at:

http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1380968

[3] Prevalence of chronic fatigue syndrome in metropolitan, urban, and rural Georgia. William C Reeves, James F Jones, Elizabeth Maloney, Christine Heim, David C Hoaglin, Roumiana S Boneva , Marjorie Morrissey and Rebecca Devlin. Population Health Metrics 2007, 5:5 doi:10.1186/1478-7954-5-5

Many possibilities to consider for metropolitan, urban, and rural differences in sex ratio.

Claire C. — 2007-08-15T00:00:00Z

One of the most interesting and potentially informative findings from this study is the finding that the gender ratio of CFS was strikingly different among metropolitan, urban, and rural populations.

The only suggestion that the authors make regarding this finding is that "The striking differences between female and male rates in the 3 strata may indicate risk effects of gender (a social construct) in distinction to sex (a biologic attribute)."

This is a very interesting suggestion, in light of all the research demonstrating that CFS is a physical disorder with biological markers. We should not fall under the line of thinking that medical observations whose causes are not yet explained are psychological or social constructs, or psychosomatic. This suggestion also assumes that gender constructs are different among metropolitan, urban, and rural populations.

There are many more obvious factors that are different among metropolitan, urban, and rural populations that should be investigated. Namely environmental factors including pollution, exposure to sunlight, microbes, and other things that may be different among metropolitan, urban, and rural populations.

There are many interesting studies which show that other illnesses such as multiple sclerosis have different prevalence rates by geography (latitude), and that asthma and allergies have different prevalence rates between urban and rural children. Could it be possible that the sexes have different levels of biological susceptibility to environmental triggers of some illnesses such as CFS?

Observations on apparent changes in methods of assessing symptoms

Tom Kindlon — 2007-07-06T00:00:00Z

I notice that the "Symptom Inventory collects information about the presence, frequency, and intensity of .. symptoms during the month preceding the interview".

However the Fukuda et al '94 definition [1] is supposed to look for "the concurrent occurrence of four or more of the following symptoms, all of which must have persisted or recurred during 6 or more consecutive months of illness and must not have predated the fatigue".

Was there a particular reason why a time frame of one month was chosen? This would suggest that relatively short-lived symptoms would be counted. If the reasoning was that asking people detailed questions about symptom severity and frequency over a longer period would might not be as accurate, perhaps a two-stage question could be asked: firstly asking whether symptoms "have persisted or recurred during 6 or more consecutive months of illness" and then asking a more detailed question about frequency and intensity.

I also see no mention of the requirement, that was in the initial definition [1], that the symptoms didn't predate the fatigue. Again, if this is a change, it would seem to risk reducing the specificity of the symptom criteria (i.e. increasing the chences that symptoms from other causes are counted) so perhaps again a yes/no question would be good.

Tom Kindlon

[1] Fukuda K, Straus SE, Hickie I, Sharpe MC, Dobbins JG, Komaroff A: The chronic fatigue syndrome; a comprehensive approach to its definition and study. Ann Int Med 1994, 121:953-959.

More symptoms could be added to a CFS Symptom Inventory

Tom Kindlon — 2007-06-21T00:00:00Z

Many would feel that the 8 symptoms used in the CDC '94 definition [1] were chosen in a somewhat arbitrary fashion; so it is to be welcomed that the CDC itself has started to look beyond these symptoms with the CDC CFS Symptom Inventory. The idea of a Short Form of the CDC Symptom Inventory is also interesting.

However, it is not clear to me where the extra symptoms that are on the CDC CFS Symptom Inventory came from. For example, I didn't see some of the symptoms listed in Reeves et al [2].

In 2001, De Becker et al [3] published data on the symptoms found in over 2500 patients. They tried to improve on the 1988 [4] and 1994 CDC criteria. They suggested a list of symptoms that could be used to strengthen the ability to select ME/CFS patients. Many of the symptoms they mentioned are not in the CDC CFS Symptom Inventory. So to claim that the "CDC Symptom Inventory assesses the full range of CFS associated symptoms" seems questionable.

It would be interesting if in future these symptoms (that De Becker et al were suggesting) were added before statistical analyses are performed.

The fatigue criteria and functional impairment criteria have become much less restrictive [5]. For example, to satisfy the fatigue criteria, the fatigue is required to be greater than or equal to the medians of the MFI general fatigue (≥ 13) or reduced activity (≥ 10) scales. So it now seems particularly important that the symptom criteria have good sensitivity and specificity or one is going to end up with a definition that leads to very heterogeneous samples.

Tom Kindlon

[1] Fukuda K, Straus SE, Hickie I, Sharpe MC, Dobbins JG, Komaroff A: The chronic fatigue syndrome; a comprehensive approach to its definition and study.

Ann Int Med 1994, 121:953-959.

[2] Reeves WC, Lloyd A, Vernon SD, Klimas N, Jason LA, Bleijenberg G, Evengard B, White PD, Nisenbaum R, Unger ER, International Chronic Fatigue Syndrome Study Group: Identification of ambiguities in the 1994 chronic fatigue syndrome research case definition and recommendations for resolution.

BMC Health Services Research 2003, 3:25.

http://dx.doi.org/10.1186/1472-6963-3-25

[3] A definition-based analysis of symptoms in a large cohort of patients with

chronic fatigue syndrome, P. De Becker, N. McGregor, and K. De Meirleir.

Journal of Internal Medicine 2001;250:234-240

[4] Holmes GP, Kaplan JE, Gantz NM, Komaroff AL, Schonberger LB, Straus SE, et al.: Chronic fatigue syndrome: a working case definition. Ann Intern Med 1988, 108:387-389.

[5] Reeves WC, Wagner D, Nisenbaum R, Jones JF, Gurbaxani B, Solomon L, Papanicolaou DA,

Unger ER, Vernon SD, Heim C: Chronic fatigue syndrome — a clinically empirical approach

to its definition and study. BMC Medicine 2005, 3:16.

Whither Post-exertional Fatigue?

cort johnson — 2007-06-21T00:00:00Z

The Empirical Definition has many positive aspects; better characterization of CFS patients, a way to track treatment efficacy and perhaps identify symptom based subsets and it does appear to identify a very ill population. But does it single out the peculiar condition called CFS. Some aspects of it suggest to me that it does not.

Some researchers have proposed that post-exertional fatigue is a hallmark symptom in CFS. The Canadian Consensus and 1990 Australian definition require post-exertional fatigue to be present for a CFS diagnosis. The Fukuda definition does not; although it is one of eight major symptoms it is not required for a CFS diagnosis. The empirical definition appears to dilute the importance of this symptom further. Some evidence produced by CDC studies and others, however, suggests it is a central component of CFS.

A CDC study examining the symptoms in a wide variety of fatigued groups (prolonged fatigue, chronic fatigue, CFS-like, CFS) found that as the levels of fatigue increased the percentage of people reporting ‘unusual fatigue after exercise’ did as well (Nisenbaum 2006). That only 1.6% of people with no fatigue reported this symptom indicated it is rarely found in healthy people. (Problems with sleep, muscle and joint pain on the other hand were fairly common (10-20% of healthy people)). About 14% of people with prolonged fatigue and 33% with chronic fatigue reported unusual fatigue after exercise but from there the percentages jumped up markedly; 77 and 74% of CFS-like and CFS patients reported this symptom. This suggests there is a big difference between chronic fatigue patients (fatigued but don’t meet 1994 criteria for CFS) on the one hand and CFS-like (met the criteria but didn’t undergo the clinical evaluation) and CFS patients (meet the criteria, visited the clinic) with regard to this symptom.

Similarly CDC studies exploring the question of subsets in CFS (Conna et. al. 2006, Aslakson et. al. 2006) found that post-exertional fatigue – was the first and third most important differentiating variable in the PCA and Latent Class Analyses. Its discriminatory prowess was highlighted by the fact that it and concentration difficulties were the only variables not found at all in the Well Group. The very high levels of post exertional fatigue (78-91%) in the three classes dominated by CFS patients and the low to moderate levels of it (33-41%) in the classes dominated by idiopathic fatigue patients again indicated that this symptom plays a special role in CFS. CFS is often described as being an amalgam of very common symptoms but these studies indicate that post-exertional fatigue is only rarely found even a subset of the population one might expect it to; the BMI matched overweight, obese and even morbidly obese healthy controls in this study who presumably don’t exercise much.

Since the ‘chronic fatigue’ group in the Nisenbaum was the largest fatigued group studied in the Nisenbaum study (PF=575, CF=1085, CFS-like=263, CFS=43) this group will surely account for most of the increase in the prevalence rates under the empirical definition. This indicates that most CFS patients under the empirical definition will not be characterized by ‘unusual fatigue after exercise’. This is not in some ways surprising; Dr. White and Jason have pointed out patients can meet the new criteria for CFS simply by reporting they have low activity levels.

A Personal Response: For the first ten years after I got CFS I, who was formerly an avid exerciser, didn’t try to do anything more than walk. My symptoms at that point, while very disturbing, were nevertheless mostly not that unusual overall; I was very tired, I couldn’t concentrate well, my muscles hurt, I had constant sore throats, I felt out of it, I wasn’t strong. Basically I felt like I was shadow of my former self but I was able to get around, I was able to go to school. It probably could have been argued that I had some strange mental condition. Given the lack of information on CFS around that time – mid-1980’s, in the back of my mind I wondered if something like that had indeed occurred.

About 10 years into the disease I did something very unusual - I began an exercise program and have tried to do so several times since then. Each time my response was to it has been bizarre. The symptom exacerbation has been immense, not just at the beginning of the exercise program but throughout. Over time I was able to increase my strength and duration. In fact I usually felt good while I was exercising – but the aftermath was always devastating. Starting anywhere from ½ hour to several hours later I could feel that peculiar package of symptoms set in; the stiff, painful muscles, the heart yammering, the uncoordination, the need to lie down, the difficulty thinking or talking, the feelings of irritation. These symptoms would typically peak a day or so later and then slowly subside. It is an utterly strange response to exercise and it is the hallmark symptom of my CFS – it’s what convinced me that there was a physiological basis to my problems.

The idea that this vital part of CFS is being subsumed under this new definition suggests that while researchers may uncover important aspects of unwellness by studying this population they may very well have a very difficult time understanding the condition known as CFS.

Aslakson, E., Wollmer-Connar, U. and P. White. 2006. The validity of heterogeneity in chronic unexplained fatigue. Pharmacogenomics 7, 365-373

Conna, U., Aslakson, E. and P. White. 2006. An empirical delineation of the heterogeneity of chronic unexplained fatigue in women. Pharmacogenomics 7, 355-364.

Jason, Leonard. 2007. Problems with the new CDC CFS Prevalence Estimates. IACFS Website.

White, P. 2007. How common is chronic fatigue syndrome; how long is a piece of string? Population Health Metrics 5:6 doi:10.1186/1478-7954-5-6