The researchers speculate, based on the findings of other studies, why seasonal factors may contribute to specific disease risk, suggesting it could be the result of exposure to antigens such as pollen, varying vitamin D levels, and possibly how old a child is when they first start school. Many unmeasured factors may also be involved in any links.
Overall, this study is not proof that being born in a particular month means you are more or less likely to develop any particular disease.
But there are effective ways you can reduce your risk of developing chronic diseases in later life. These include stopping smoking, drinking alcohol in moderation, and maintaining a healthy weight through diet and exercise. These steps should help keep your cholesterol and blood pressure at a healthy level.
Where did the story come from?
The study was carried out by researchers from Colombia University and was funded by National Library of Medicine training grants.
It was published in the peer-reviewed Journal of the American Medical Informatics Association. The study has been published on an open access basis, so it is free to read online or download as a PDF.
This story was covered widely by the press. Most sources took a light-hearted, tongue-in cheek approach, with the Metro saying: "It's still not fully understood why this should be – but just to cheer you up, here's a calendar of the diseases you're at increased risk of, depending on when you're born."
What kind of research was this?
This modelling study aimed to explore the relationship between season or birth month and lifetime disease risk.
The researchers carried out their study using health record data collected from a large US medical centre database. They say similar studies have focused on looking at associations with specific diseases, so sometimes do not look at rarer diseases.
For this reason, they didn't carry out this research with any particular theory in mind, but just aimed to look at any associations found when looking at millions of records.
This large-scale analysis of massive chunks of data is often referred to as data mining. Data mining is now widely used thanks to improvements in the speed and capabilities of modern computers.
Such a study is good for looking at associations on a large scale, as it can encompass a large number of diseases.
But without testing any particular theory – such as exposure X increases your risk of disease Y – the study can only give us observations and associations. These may not be causative links, and many other unmeasured factors may be involved in any of the links found.
What did the research involve?
The researchers called their approach the Season-Wide Association Study (SeaWAS), an algorithm looking for diseases with seasonal associations.
They used health record data from the Colombia University Medical Center, where diseases were recorded using standard disease codes (International Classification of Diseases version 9, ICD-9) that were then mapped to specific codes developed for this database (Systemized Nomenclature for Medicine-Clinical Terms, SNOMED-CT).
This coding method is said to capture more medical information than ICD-9 codes and is designed to be transferable across institutions, which will enhance data sharing.
All data was extracted for individuals born between 1900 and 2000 – 1,749,400 people – who were treated at the Colombia University Medical Center between 1985 and 2013. The average age (median) was 38 years.
Analyses were performed to check whether yearly and sex-based variation in the birth month distribution would affect the results. This was found to be minimal.
Associations were investigated between birth month and all recorded conditions. A control group of randomly sampled individuals from the same population without any disease was used to compare monthly birth rate between the case and control populations for each condition.
The study was supplemented by a search of the literature to identify other studies that also looked at links between birth month and disease to see how the SeaWAS findings compared.
What were the basic results?
The researchers found 55 diseases that were significantly dependent on birth month. Nineteen diseases had been reported in the literature – 20 were for conditions with close relationships to those reported, and 16 were previously unreported.
The 16 previously unreported associations included nine with cardiovascular conditions, such as atrial fibrillation, high blood pressure and heart failure. The remainder included a mixed bag of other conditions, ranging from prostate cancer to coughs, colds and sexually transmitted infections, and bruising and non-venomous insect bites.
Overall, most disease associations were found with October births and the fewest were with May births. Asthma was most associated with July and October babies, and attention deficit hyperactivity disorder (ADHD) with November. March births had most associations with heart problems and winter births with neurological problems.
How did the researchers interpret the results?
The researchers concluded that, "SeaWAS confirms many known connections between birth month and disease, including: reproductive performance, ADHD, asthma, colitis [bowel inflammation], eye conditions, otitis media (ear infection), and respiratory syncytial virus [a common cause of chest infection in young babies]."
They went on to state they discovered 16 associations with birth month that had never been explicitly studied previously, nine of which were related to cardiovascular conditions.
This modelling study used a large US medical centre database to explore the relationship between month of birth and lifetime disease risk. The study found a number of associations between birth month and risk of disease, some of which had been previously reported in the literature, as well as other new associations.
While these findings are of interest, this study can only demonstrate observations and associations. The study does not provide proof that being born in any particular month is the direct cause of any future disease development.
There may be many unmeasured factors behind any associations between disease risk and birth month. The study has not been able to look into interactions or explore the lifetime genetic, medical, lifestyle or environmental influences on any individual.
Though the study had strengths in that it used a large medical database where conditions were coded according to a valid system, this is data from just one source. The findings are representative of people from only one region in the US, and they may not be generalisable to other regions or countries.
The researchers addressed this issue and state that the effects observed are likely the result of the climate effects of the region, saying their findings would be most comparable to northern European climates. The researchers hope that lifestyle and diet recommendations can be made once associations are drawn.
But the media reporting of this study, which suggests the month you're born in is a way to predict how you will become ill or die, should be taken very cautiously at this stage. Future research will be needed to see if the same links are observed in studies conducted in different regions, and then explore possible reasons behind these associations.
For now, this study does not provide proof that being born in a particular month means you are more or less likely to develop any particular disease.
There is nothing you can do about the month you were born in, but you can take steps to reduce your risk of disease in later life: have a healthy diet, take regular exercise, avoid smoking, moderate your alcohol intake and maintain a healthy weight.