Children are more likely to develop diabetes in winter, newspapers have reported. The Times said that a large international study of 31,000 children from 53 countries suggests there is a correlation between the seasons...
Children are more likely to develop diabetes in winter, newspapers have reported. The Times said that a large international study of 31,000 children from 53 countries suggests there is a correlation between the seasons and type 1 diabetes. It said the trend was more prevalent in boys and older children (5-14 year olds) of both sexes. See The Times' article on whether diabetes is seasonal.
The news stories are based on a large, well-conducted time series study that demonstrates a seasonal variation in the diagnoses of type 1 diabetes across the world. The researchers conclude that the seasonality “is a real phenomenon”, but that more data are needed on populations living in the southern hemisphere, such as southern Africa, Australia and South America “to complete the picture”. There are no explanations that account for the differences seen between girls and boys and the differences in the age groups.
The study has highlighted an issue that needs more research. At present, the implications of these findings for individuals are unknown as these rates were calculated for clinics and countries. More research into how seasonality influences the onset of diabetes at an individual level is needed. It is also important to acknowledge the possibility that the study was biased by differences between the diabetes centres in different countries.
Where did the story come from?
The research was carried out by Dr Moltchanova and colleagues from the National Institute for Health and Welfare, Helsinki, Finland. The research was funded by the EU GEOBENE Project and by the Academy of Finland and published in the peer-reviewed medical journal Diabetic Medicine.
What kind of scientific study was this?
The aim of this study was to determine whether there is a worldwide seasonal pattern in the clinical onset of type 1 diabetes. It is a time series study (a type of ecological study), for which the researchers used statistics from the World Health Organization (WHO) on the incidence (number of new cases) of type 1 diabetes in 0 to 14 year olds during the period 1990 to 1999. This information was collected as part of the WHO DiaMond (Diabetes Mondiale) study: a 10-year project involving 105 treatment centres across 53 countries.
Each country submitted annual data on gender, ethnicity, date of birth and treatment, using standardised forms. The rate of new cases occurring in each geographical area was calculated as the number of new cases of type 1 diabetes divided by the total number of resident children under 15 years of age. Out of 40.5million ‘at risk’ children under the age of 15 years, a total of 31,091 cases of type 1 diabetes were diagnosed in this period.
In their analyses, the researchers divided the children into three age groups: 0-4, 5-9 and 10-14 years. Statistical techniques were used to determine whether there were variations in the monthly totals of diabetes diagnosed and whether these trends corresponded with the seasons in both the northern and southern hemispheres. Essentially, the researchers were analysing the annual trends in incidence, comparing the actual incidence per month with that expected if there were a completely uniform monthly distribution (calculated by dividing the total annual incidence by 12 months).
What were the results of the study?
There was seasonal variation in the numbers of new cases of type 1 diabetes in 42 of the 53 centres. Of these, 28 had the highest number of new cases in the winter months (October to January), while 33 had their lowest in the summer months (June to August). Two of the four southern hemisphere countries demonstrated a different pattern (a peak during July to September and a trough in January to March).
Distance from the equator had an effect, with countries further away from the equator (with a high or low latitude) more likely to show a seasonality effect. Longitude did not make a difference. Boys had a more pronounced pattern of seasonality than girls, and seasonality was also more evident in older children (5-14 year olds) than younger children (0-4).
The link between number of new cases and the seasons seemed to depend on the total number of cases diagnosed in a centre, with the centres that diagnosed more cases having a stronger association.
What interpretations did the researchers draw from these results?
The study confirms the findings of other smaller studies, that there is a global pattern of seasonality with type 1 diabetes. Cases tend to peak in the winter months and trough in the summer months in both the southern and the northern hemispheres.
What does the NHS Knowledge Service make of this study?
The results from this large, well-conducted study confirm what has been seen in previous small studies. However, any interpretation of these findings should take into account several shortcomings that the researchers themselves raise:
- Most of the centres that participated in the WHO DiaMond study were situated in the northern hemisphere. There is very limited information available for Africa and Asia and the researchers say that the correlation is far from conclusive.
- The link between new cases and the seasons was influenced by the total number of cases diagnosed in a centre. The researchers suggest that this might be because a larger number of cases gives the study more power to find an association if it exists. If this is the case, it may also explain why seasonality was more evident in the older age groups (which usually have more people with diabetes) than the youngest one. However, they also say it is possible that an as yet unidentified factor could be behind the association.
- The researchers make several suggestions explaining a seasonal variation for type 1 diabetes, including children getting more exercise in the summer, more infections in the winter and seasonal variations in their levels of blood glucose. However, none of these fully explains the differences seen in age groups and across the genders.
Although the study was well conducted and efforts were made to standardise the data from the different centres, it is possible that there were differences in diagnostic practice or reporting between the centres that may have biased the results. As an ecological design, the study looked at the effect of seasons on the incidence of diabetes in a population group, such as a clinic or country. This means that there are no definite implications for individuals. The study’s value is in generating theories of how diabetes may be caused and in pointing future investigation in a particular direction, rather than showing that season is a definite factor.
Overall, the researchers conclude that the seasonality of type 1 diabetes “is a real phenomenon”, but that more data are needed on populations living below the 30th parallel (for example southern Africa, Australia and South America) “to complete the picture”.