With respect to acute illness and infectious disease the outcomes were in some respects surprising. As might be expected, unvaccinated children were significantly (4-10 times) more likely to have come down with chicken pox, rubella or pertussis. Perhaps unexpectedly, the unvaccinated children were less likely to suffer from otitis media and pneumonia: vaccinated children had 3.8 times greater odds of a middle ear infection and 5.9 times greater odds of a bout with pneumonia.
The study was based on a survey with participants recruited in a process led by NHERI and coordinated through 84 state and local homeschool groups. The survey itself was, according to the authors, "nonbiased and neutrally worded."
These findings in a study population of 666 children, 261 of whom (39%) were unvaccinated, are sure to stir controversy, in part because it is the first of its kind. The scientific literature on the long-term effects of the vaccination program is virtually silent. Most studies on the safety of vaccines only consider immediate or short-term effects. There was no obvious explanation for the differences in health outcomes observed between the vaccinated and unvaccinated groups of children other than vaccination itself.
The finding that vaccination is a significant risk for autism is the most explosive finding in the paper. For well over a decade, parents concerned that vaccines were involved in autism's sharp rise have been calling for what has long been labelled the "vax/unvax" study. P
I'll trade chickenpox for mild ear infection every day.
Same for pertussis, I'd rather have a pneumonia
And it is a study based on a survey, wow ! much scientific
And 666 children, if it is the devil's number, then they must definitely be right.
This danish study on 657 000 kids followed during 13 years (for the first kids, and only to 4 years for the one joining last) showed that there was no relation between MMR and autism.
https://www.acpjournals.org/doi/10.7326/M18-2101But, hey, that large scale study must have been faked, but yours is the truth.
Did they have a control group? Are Danish vaccines different than USA vaccines? Not enough details in the study as listed in your link.
A control group, (did yours had one ?). I'll let you read the extract below showing that they indeed assessed kids based on if siblings or family already had autism. Age of the parents, smoking, and other factors that are known to increase the risk of autism in babies.
The anti-Vax people believe that ALL the vaccines that exist in the word cause/give autism.
Hence, to prove them wrong, we just need a vaccine that doesn't cause autism. (even though the burden of proof should really be done by the anti-vax).
Even if Danish vaccines are different than USA ones, it shows that some danish vaccines don't cause autism and are safe. Maybe you guys should source yours from the Danes.
I'll put here an extract of the Danish link :
Statistical Analysis
The main goal of our modeling strategy was to evaluate whether the MMR vaccine increases the risk for autism in children, subgroups of children, and time periods after vaccination. We defined subgroups according to 1) sibling history of autism (“genetic susceptibility”), sex, birth cohort, and prior vaccinations in the first year of life and 2) a summary index estimated from a disease risk model combining multiple environmental risk factors. The motivation for a summary index was that the combination of several factors each associated with only a moderate risk increase in autism had the potential of identifying children at higher risk through multiple risk factors, in contrast to many stratified analyses of single moderate risk factors.
We analyzed the study cohort by using survival analysis (14). Children in the cohort contributed person-time to follow-up from 1 year of age and until a first diagnosis of autism, death, emigration, unexplained disappearance from the source registers, diagnoses of autism-associated conditions or syndromes, or end of the study on 31 August 2013.
The MMR vaccination status was considered a time-varying variable; children could contribute time as both unvaccinated and vaccinated in our study. Using the cases of autism among siblings, we constructed a time-varying variable summarizing each child's sibling history of autism with the states “no siblings,” “siblings without autism,” or “siblings with at least one case of autism”; a missing value category covered the children who had unknown fathers. We used sibling history at study entry unless otherwise specified.
In a preliminary analysis based on maternal age, paternal age, smoking during pregnancy, method of delivery, preterm birth, 5-minute Apgar score, low birthweight, and head circumference, we estimated a disease risk score (15) (termed “autism risk score” throughout) for each child in the cohort. The autism risk score was derived in the complete study cohort by fitting a proportional hazards model of autism risk with attained age as underlying time-scale comprising the preselected variables as covariates. For each child, a score (in the form of a hazard ratio
relative to a child with reference values for all variables included) was calculated as the exponential of the sum of the estimated regression coefficients corresponding to the characteristics of the child. The score was categorized according to deciles which were combined into 4 risk groups: very low (first to third decile), low (fourth to sixth decile), moderate (seventh to ninth decile), or high (10th decile).
Survival times were then analyzed by using Cox regression with attained age as underlying time scale, producing HRs according to vaccination status. For fully adjusted models, the baseline hazard function was stratified on birth year, sex, other childhood vaccines received, sibling history of autism and autism risk score (in deciles). We evaluated the proportional hazards assumption of the main analysis by a joint test of homogeneity allowing the effect of vaccination to vary between the age intervals 1 to 3 years, 3 to 5 years, 5 to 7 years, 7 to 10 years, and more than 10 years (16).
We estimated autism HRs (aHRs) according to MMR vaccination status (yes or no), overall in the cohort and in several subanalyses: 4 analyses, each restricting risk time to young children by censoring observed survival times at 3, 5, 7, or 10 years of age; in subgroups characterized by sex, birth cohort, other childhood vaccines received, autism risk score, or autism history in siblings (joint tests for homogeneity of aHRs between levels of each factor were carried out [16]); and in specific periods after vaccination (comparing the hazard rates of autism in the first, second, third, and fourth year after vaccination and more than 4 years after vaccination, respectively, with the rate among unvaccinated children. A test for homogeneity of aHRs between intervals was conducted using a type 3 test (16).
We conducted several sensitivity analyses. To increase the validity of our autism case definition further, we conducted a main analysis with a case definition requiring at least 2 autism diagnosis registrations; an event was defined at date of second autism diagnosis. We evaluated specific autism phenotypes by conducting main analyses of autistic disorder and other autism spectrum disorder separately (with right censoring of other autism spectrum disorder when analyzing autistic disorder and vice versa). We conducted a dose-dependent fully adjusted analysis taking the second MMR dose into account by estimating the increase in HR per vaccination. Instead of adjusting for birth year, sex, other childhood vaccines received, sibling history of autism, and autism risk score by stratification of the baseline hazard, we included these as covariates. Finally, we replaced the autism risk score of the previous model with the 8 variables on which it was based.
Crude associations between variables included in the analyses and autism were estimated in proportional hazards models with attained age as underlying time-scale and autism as outcome, including only the specific variable of interest as a covariate.
Data management and statistical analyses were conducted by using SAS, version 9.4; the figures were created by using R, version 3.5.1. All Cox regressions were fitted by using the SAS PHREG procedure with the Breslow option for handling ties. Cumulative risks were calculated from the Kaplan-Meier estimates using the survfit function in R with the log-log option for confidence limits.Based on more than 500 000 kids.
