Institute of Mental Health, Singapore and School of Psychiatry, University of New South Wales, Australia
Woodbridge Hospital, Singapore
NMRC Clinical Trials and Epidemiology Research Unit, Singapore
Correspondence: Professor Gordon Parker, Institute of Mental Health, 10 Buangkok View, Singapore 539747
Declaration of interest Funded by the Institute of Mental Health, Singapore.
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ABSTRACT |
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Aims To investigate whether there is any variation in month of birth among patients from equatorial Singapore with a diagnosis of schizophrenia.
Method All 9655 patients discharged from Singapore's national psychiatric hospital with a diagnosis of schizophrenia were included (year of birth range 1930-1984). We analysed aggregated data, as well as the data of subsamples grouped according to birth-year periods, in order to examine secular trends. One patient subsample (those born 1960-84) allowed exact matching against the general population data set and close testing of any seasonal influence.
Results Monthly variation in births was evident for both patients and controls; the patterns were very similar, apart from the patient sample showing a trough in March-April.
Conclusions In an equatorial region, where seasons are absent, no seasonal excess in births of those later developing schizophrenia was evident.
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INTRODUCTION |
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METHOD |
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Subjects
The subjects were obtained from computerised records of all patients from
Woodbridge Hospital (Singapore's national psychiatric hospital) who were
discharged with a recorded diagnosis of schizophrenia (ICD codes of
295.0-295.4 and 295.9) (World Health
Organization, 1992). Subjects with multiple discharges were
counted only once, while those without a national identity card number were
excluded (in order to minimise the chance of including those not born in
Singapore). Region of birth was not recorded on the computerised record and we
therefore undertook a record review of one in four of the selected cases in an
attempt to establish place of birth. Monthly general population birth data
were only available from 1960 onwards.
Statistical analyses
Adjustment for varying numbers of days per calendar month and for leap
years was made. A 2 test examined for goodness of fit between
observed and expected monthly births in the patient sample, but it is a
limited test for cyclic data. Following earlier suggestions by Mardia
(1972), Machin & Chong
(1998) described a method for
estimating the peak date of birth with grouped data. This technique requires
establishing the magnitude of this peak (termed the mean resultant or
R). If all the data are concentrated at a particular date the
resultant will equal unity, whereas, if the distribution is uniform over the
year, the resultant will equal zero (although values of zero are also possible
if the distribution has two peaks six months apart). It is important to note
that quoting the peak day when using monthly data as the unit of analysis
risks spurious accuracy, so any such identified day should be interpreted
with caution. Once the peak is calculated, approximate confidence intervals
can be obtained, while the Mardia statistic (which has two degrees of freedom)
tests specifically for the presence of a single peak in the data.
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RESULTS |
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The monthly distribution of births is shown in Table 1, both for the whole sample of subjects with schizophrenia and for sub-samples from three intervals (1930-49, 1950-59 and 1960-84) comprising 2702, 3046 and 3393 subjects respectively. Subsample analyses examined for consistency in any birth pattern in the subjects with schizophrenia over time. The pattern in the raw (and adjusted) distributions was relatively consistent across the subsamples, with, in essence, the lowest birth rates occurring in March or April, and the highest in September or October. For the 1960-84 sub-sample (where we possessed matched general population year of birth data), we calculated the number of schizophrenia sufferers expected to have been born in each month by using the season of birth pattern in the general population and then made a comparison against the observed distribution. Observed and expected births showed the most distinct difference in March (with a decrement of 12%), but the overall distributions of observed and expected births across all 12 months did not differ.
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Analyses of the data in Table 2 estimating the peak date of births of people later diagnosed with schizophrenia identified the peak months as October for the 1930-49 subsample and September for both the 1950-59 and 1960-84 subsamples. In the first and third subsamples, the values of P are small, indicating the presence of a single peak, but these peaks were of little epidemiological importance as the corresponding values of this mean resultant are so small. A similar pattern is evident in two subsamples of the general population birth data (subdivided again in order to examine for any secular trend), with the peak occurring at the beginning of October.
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Returning to Table 1, key data are the adjusted monthly birth data for the 1960-84 patient subsample, the general population data for the same period, and the monthly ratio of patient to control births for that matched period. The adjusted data (see Table 1) showed peaks in each group in mid-October (and within one week of each other), indicating that if there is any seasonality in birth patterns, it is remarkably similar in both patients with schizophrenia and the general population. Figure 1 plots the monthly birth rates for the two groups. As the scale on the y-axis does not include zero, fluctuations are graphically exaggerated. The figure nevertheless offers strong impressionistic support to the analyses, with both samples showing fairly variable rates across the year, a strikingly consistent peak in October, and a generally similar pattern (albeit with a more distinct March-April trough in the patient group).
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We also examined the distribution of monthly births for those whose case file did not formally record birth in Singapore. Both in comparison with the whole sample of those with schizophrenia and in comparison with the general population, their monthly distribution was not significantly different.
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DISCUSSION |
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General population control data were used (not always the case in the seasonality literature) and, in case there had been any variation in birth patterns across the decades (for either the patients or the general population), we focused on monthly birth data for patients and general population subjects born over the same interval (1960-84). Nevertheless, subsamples of patients born over other periods (and of the general population data) revealed relative consistency over time. We analysed by month, as opposed to the quarters or half years used in many other studies, and had a larger sample than the estimate (by Hare, 1975) of 4500 required if monthly distributions are to be examined. Our principal analytic strategy focused on determining peaks in the patient and general population samples - and any peak in the excess of patients over the general population.
Absence of seasonality
While there was a monthly variation in the births of those later developing
schizophrenia, the variation was largely parallel to the seasonal pattern
found in the general population. The study has therefore delivered a highly
suggestive finding - that in a season-less equatorial region where there is
monthly variation in birth patterns, those later developing schizophrenia fail
to show any monthly excess of births relative to the general population. These
results contrast with a previous equatorial study undertaken in the
Philippines (Parker & Balza,
1977), where an extremely large December-February excess of 15%
was found. However, the Philippines is less equatorial than Singapore (being
15 degrees north of the equator), and has relatively distinct wet and dry
seasons; moreover, matching of patient and general population data was limited
in that study.
Why is there any birth peak?
The reason for there being any September-October birth peak in Singapore
(as evidenced in both groups) - and for it being such a consistent one -
remains unclear but, if it relates to variation in procreation, some variable
must operate across the December-January period. Christmas is in this period,
and Chinese New Year usually falls in January or February; it is a two-day
public holiday in Singapore and many businesses close for several days. There
is, however, no known significance in becoming pregnant at such times, at
least to the majority Chinese population; the Chinese astrological calendar
gives more importance to auspicious and inauspicious years, rather than
months, of birth.
Do the results reflect absence of seasonality in virus
infections?
The extent to which seasonality may be a proxy for environmental risk
factor has encouraged previous researchers to pursue a range of factors,
particularly seasonal variation in viral illness. We therefore sought such
data for Singapore. Doraisingham et al
(1988) reported on influenza
surveillance data for the period 1973-86 in Singapore. Despite being
equatorial, Singapore showed the same seasonal pattern in viral illnesses as
that found in temperate zones (i.e. a bimodal pattern, with a major seasonal
increase occurring from April to June, and usually extending into July, and a
second increase during the last quarter of the year and extending into the
beginning of the next year). Doraisingham et al
(1988) speculated that patterns
might reflect temperature changes, noting that the major seasonal peak in
influenza occurred during the warmest period of the year (when mean monthly
temperatures ranged from 26.4°C to 28.2°C), while the second peak
occurred during the coldest months (mean temperature 24.8-26.6°C). Both
periods preceded the periods of the greatest daily temperature fluctuations,
which, the authors suggested, might indicate vulnerability effected by the
"host's defence mechanisms". The alternative explanation (one
considered by the authors) points to Singapore's busy airport, which would
facilitate the rapid spread of influenza from less temperate regions which
have marked seasons - so imposing or importing a seasonal pattern to
Singapore's temperate region.
Torrey et al (1997) concluded that the seasonal birth factor in schizophrenia is more likely to affect those "born in, or raised in, urban areas". In the equatorial region of urbanised Singapore, however, the monthly distribution of births in those with diagnosed schizophrenia appears consistent with the pattern recorded in the general population, while monthly peaking was identical. Such a finding suggests that in the absence of seasons, there is no evidence of a distinctive seasonal birth pattern in schizophrenia. If valid, the importance of such a negative result lies in reducing the list of putative risk factors that have been postulated over a lengthy period.
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Clinical Implications And Limitations |
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LIMITATIONS
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ACKNOWLEDGMENTS |
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REFERENCES |
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Hare, E. H. (1975) Season of birth in schizophrenia and neurosis. American Journal of Psychiatry, 132, 1168 -1171.[Abstract]
Hare, E. H., Price, J. & Slater, E. (1974) Mental disorder and season of birth: a national sample compared with the general population. British Journal of Psychiatry, 124, 81-86.[Medline]
Machin, D. & Chong, S. F. (1998) On the detection of the seasonal onset of disease. Journal of Epidemiology and Biostatistics, 3, 385 -394.
Mardia, K. V. (1972) Statistics of Directional Data. London: Academic Press.
McGrath, J. J. & Welham, J. L. (1999) Season of birth and schizophrenia: a systematic review and meta-analysis of data from the Southern Hemisphere. Schizophrenia Research, 35, 237 -242.[CrossRef][Medline]
Mortensen, P. B. B., Pedersen, C. B., Westergaard, T., et al (1999) Effects of family history and place and season of birth on the risk of schizophrenia. New England Journal of Medicine, 8, 603 -608.[CrossRef]
Parker, G. & Balza, B. (1977) Season of birth and schizophrenia - an equatorial study. Acta Psychiatrica Scandinavica, 56, 143 -146.[Medline]
Torrey, E. F., Miller, J., Rawlings, R., et al (1997) Seasonality of births in schizophrenia and bipolar disorder: a review of the literature. Schizophrenia Research, 28, 1 -38.[CrossRef][Medline]
World Health Organization (1992) The Tenth Revision of the International Classification of Diseases and Related Health Problems (ICD-10). Geneva: WHO.
Received for publication April 6, 1999. Revision received July 9, 1999. Accepted for publication July 9, 1999.
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