Have you identified a fatal flaw in this paper? Please explain your answer. If you answer "Yes", please skip questions 1.2-1.4.

Answer Explanations

• Yes (paper will receive a score of "0")

  user-250237
  The study on maternal fluoride exposure and child IQ, published in JAMA Pediatrics, is methodologically flawed due to significant weaknesses in its design and analysis. Key issues include reliance on unvalidated measures of fluoride exposure (e.g., maternal recall and urinary fluoride levels prone to variability), failure to account for major confounding factors such as postnatal fluoride exposure, socioeconomic status, and maternal IQ, and inconsistencies in findings (e.g., effects observed only in boys without a theoretical rationale). Subgroup analyses and marginally significant p-values suggest potential data overfitting and false-positive results. The study's observational nature and inadequate adjustments for confounders further limit its ability to establish causation, making its conclusions speculative and insufficient to warrant changes in public health recommendations. 
  
  
• No (paper will receive a score based on responses to Questions 2-4)

  user-428163
  
  

  • Lack of maternal IQ data could be a confounder, but the authors argue that maternal education (a proxy for IQ) was accounted for.

  • Self-reported dietary intake of fluoride may introduce recall bias, but this is a secondary measure compared to urinary fluoride.

  • The findings are specific to a North American population and may not be generalizable globally.

  
  
• No (paper will receive a score based on responses to Questions 2-4)

  user-868575
  I don't believe there is a fatal flaw but the study has limitations. It contributes to the growing understanding of the possible adverse effects of fluoride in drinking.
• No (paper will receive a score based on responses to Questions 2-4)

  user-480186
  I did not but I am not an epidemiologist.
• No (paper will receive a score based on responses to Questions 2-4)

  user-965103
  There are flaws but they don't appear fatal.
  
  Most importantly, the authors don't seem to realize that children born in areas with fluoridated water will continue to have increased fluoride exposure after birth. The conclusions of the study focus on exposure during pregnancy, but the observed associations may very well have resulted from exposure during the subsequent 3 to 4 years.
  From a water-fluoridation-policy perspective this may be less important, as lowering the fluoride content of the water would be the solution in either case. In terms of advice for pregnant women, or people raising small children, there could be important differences though.
  
  Further, without a clear biological explanation for the observed difference between boys and girls, and in the presence of multiple earlier studies showing no such difference, I find it doubtful that this difference is more than a chance association.
  If that's what it is, then you could also wonder whether it is chance that you do see an association in boys, or that you don't see one in girls. Either would be equally likely, casting doubt over the reliability of any conclusions from this study.
  
  In conclusion: although some tentative conclusions might be possible, these should be used solely to guide further research, as this study doesn't seem robust enough to base any kind of policy decisions on.
• No (paper will receive a score based on responses to Questions 2-4)

  user-134615
   The study employs a cohort design, which is a strong framework for investigating the association between maternal fluoride exposure and IQ in offspring. The methodologies, including exposure measurement and statistical analysis, are generally robust, even though there are areas for improvement (e.g., control of residual confounders and variability in urinary fluoride measurements). These limitations do not invalidate the study but rather temper the strength of its conclusions. 
• No (paper will receive a score based on responses to Questions 2-4)

  user-603573
  Although the study is cross sectional analysis, it gives a good analysis of the association between maternal fluoride consumption and children IQ. 
• Yes (paper will receive a score of "0")

  user-777357
  Many of the fluoride intakes were estimated and unvalidated. It's difficult to measure fluoride in urine samples. The data were compromised with estimated intakes. 
• No (paper will receive a score based on responses to Questions 2-4)

  user-2176
  I don’t think there is a fatal flaw, but I do believe that there may be other covariates affecting IQ that may not have been taken into account.
• No (paper will receive a score based on responses to Questions 2-4)

  user-698496
  The paper is reasonably well designed and the discussion addresses potential issues that coul affect the outcome.
• No (paper will receive a score based on responses to Questions 2-4)

  user-881218
  There are many studies supporting the finding of this study including three prospective cohorts. Scores should be given based on the following.
• user-850429
  Confidence in the findings of the study
  The study titled "Association between maternal fluoride exposure during fetal development and IQ in offspring in Canada" provides important findings on the effects of fluoride exposure during pregnancy on children IQ so doesn't give and the answer is "Yes" based on the following justifications;
  Study Design: The study is a prospective birth cohort study, which is generally considered a rigorous design to investigate causal relationships. It used data from the Mother-Child Research in the Environment (MIREC) program with a sample size of 601 mother-child pairs in several Canadian cities, providing methodologically applicable results the depth increased
  Exposure assessment: Researchers measured maternal urine fluoride levels and daily self-reported fluoride, and specific gravity was adjusted to calculate urine calculation of the softness. This approach provides a more accurate assessment of exposure relative to retrospective self-report alone.
  Statistical analysis: The use of multi linear regression analyzes to adjust for covariates such as maternal age, child sex, and environmental factors strengthens the validity of the findings. The results showed a significant association between high fluoride intake and lower IQ scores in children, especially boys.
  Limitations: Despite the intensity of the study, there are limitations. Relying on self-reported data on fluoride exposure may introduce bias, the observational nature of the study means that it is impossible to definitively establish causality and which in addition, although the sample size is adequate, it may not be completely representative of the entire population within Canada.
  Contextual Considerations: The findings align with previous studies suggesting potential neurotoxic effects of fluoride, but they also contrast with other research that supports water fluoridation as safe and effective for dental health.
  
  Based on the above considerations, this research can be evaluated using a scoring system that takes into account various factors such as methodology, relevance, limitations, and overall impact:
  Study design (score: 8/10): Strong design with anticipated but limited data collection due to the nature of observation.
  Sample size and diversity (score: 7/10): adequate sample size; However, the population representation could be improved.
  Exposure measurement (score: 8/10): Measurement method that is rigorous but potentially biased in the use of self-report.
  Statistical Rigor (Score: 9/10): Appropriate statistical methods for data analysis.
  Public health relevance (score: 7/10): Highly relevant but controversial due to conflicting evidence in the existing literature.
  Overall score: 39/50
  
  
• Yes (paper will receive a score of "0")

  user-406986
  It links IQ with a single variable, that is water fluoridation, when it is known this is influenced by multiple variables.  Six factors that can affect intelligence include: genetics, environment (including family background and education), nutrition, healthcare, exposure to toxins, and socio-economic status; with genetics and environment being considered the primary contributors to intelligence levels. 
  
  
  

  Explanation:

  • Genetics:
  • Inherited genes play a significant role in determining cognitive abilities and potential intelligence level. 
    
    
  • Environment:
  • Factors like parental education, home environment, access to quality education, and socio-economic status can significantly impact a person's intellectual development. 
    
    
  • Nutrition:
  • Adequate nutrition, especially during critical developmental stages, is essential for healthy brain function and cognitive development. 
    
    
  • Healthcare:
  • Access to proper healthcare can mitigate potential impacts on brain development caused by prenatal issues or illnesses. 
    
    
  • Exposure to toxins:
  • Exposure to harmful substances like lead or alcohol during pregnancy or early childhood can negatively affect cognitive abilities. 
    
    
  • Socio-economic status:
  • A person's socioeconomic background can influence access to educational opportunities and quality of life, impacting their cognitive development. 

  
  

   
• Yes (paper will receive a score of "0")

  user-881150
  no sufficient control or standard determination of fluoride formulation
• No (paper will receive a score based on responses to Questions 2-4)

  user-368556
  Fatal flow is not observed. 
• Yes (paper will receive a score of "0")

  user-751579
   

  Measuring MUF concentration was performed longitudinally, thus a multilevel data structure design is apparent, which should correspondingly had been accommodated for modelling in a mixed effects linear regression, instead of a simple regression model. Most importantly, although city was include as a dummy predictor, I believe it should have been included as a random effect term in order to accommodate both within city inter-dependence of observations, and to partition and account for all potential sources of variation. 
  
  

  The estimation of mean MUF, could be considered inaccurate or subject to bias, since extreme values can affect its measure. There is an ambiguous utility on the average as a measure of MUF central tendency. Perhaps geometric average would have been mor appropriate. 
  
  

  How did the described model specification account for the potential effect of pregnancy’s trimester in MUF concentration? 
  
  

  How was the described variability of urinary fluoride measurement and fluoride absorption during pregnancy accounted for? Is the moderately alleged correlation (ICC 0.37 – 0.40) negligible? 
  
  

  Concerning daily fluoride intake in mothers, as reported in the employed questionnaires, the assumed exposure, i.e. fluoride intake, practically remains subject to, at least, recall bias. How accurate or precise can each woman’s estimation of water consumption be considered? Was it validated somehow? 
  
  

  In the statistical analysis section, since the IQR of the difference of fluoride exposure was used, why didn’t the researchers use the more flexible quantile regression instead the linear one? 
  
  

  I believe, since Fluoride intake, regardless of the way it was estimated (either MUF or daily intake) was measured longitudinally, and most probably had different outcomes in the three or two occasions, it would have been more appropriate to incorporate its effect as in the form of a time varying covariate. 
  
  

  Based on Table 1, it is obvious that demographic characteristics contain a lot of missing values, rendering various comparisons and inferences unbalanced through an inconsistent number of observations for each association. 
  
  

  One major concern, despite the variety and information and stratification according to several properties and demographic data of participants, is the fact that in order to substantiate association between “exposure” and “disease”, and extending it to a causal relationship inference, the compared group should fundamentally be absolutely comparable besides the exposure factor. I cannot believe that such uniformity was achieved, judging for example from Table 1’s frequencies; 400 (MUF) or 512 (daily intake) cases of exposure and 610 cases of “disease” . Moreover, were other factors known to affect IQ data accounted for, or were they evenly distributed among exposed and not-exposed mothers? As stated in the study’s limitation there are probably many sources of confounding that were not accounted or controlled for, or perhaps its was not possible to be measured at all. Nevertheless, the above limitations could have been coped more efficiently in a multilevel multivariable regression analysis, where random effect terms could have ascribed this unknown, unmeasured or immeasurable sources of variation, also arising from unaccounted confounders.