PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of wtpaEurope PMCEurope PMC Funders GroupSubmit a Manuscript
 
Hum Reprod. Author manuscript; available in PMC 2010 November 16.
Published in final edited form as:
PMCID: PMC2981771
EMSID: UKMS32957

Month of birth and offspring count of women: data from the Southern hemisphere

Abstract

BACKGROUND

Several studies indicate that the month of birth affects later reproductive output of women in the Northern hemisphere.

METHODS

To investigate whether a comparable but time-shifted effect is also present in the Southern hemisphere where the seasonal variation of the environment is reversed, we analysed the association between birth month and offspring count in post-reproductive New Zealand women. We further examined whether this association differed with the hemisphere of birth as well as the socio-economic background.

RESULTS

We find that the association between birth month and offspring count of New Zealand women born in the Southern, albeit not Northern, hemisphere is a mirror image of the pattern reported from Austrian women: on average, women born during the Southern hemisphere summer months have fewer children than women born in winter. This association is highly significant within the lowest family income category but insignificant within higher family income categories.

CONCLUSIONS

This study provides evidence for a causal link between the seasonality of the environment during the pre- and perinatal period and offspring count of women. It further indicates that the main contribution of the birth month effect found in the present study comes from the lowest family income category.

Keywords: birth date, season, hemisphere, female, reproduction

Introduction

There is accumulating evidence that the seasonal variation of environmental and maternal factors may differently influence pre- and early post-natal developmental processes of individuals born at different times of the year, causing potential down-stream effects on later life events. These effects may impact a variety of physical, physiological, and psychological traits in human populations, such as growth (Weber et al., 1998), longevity (Doblhammer and Vaupel, 2001; Gavrilov and Gavrilova, 2003; Lerchl, 2004), susceptibility to diseases (Torrey et al., 1997; Castrogiovanni et al., 1998; Brenner et al., 2004), performance (Kihlbom and Johansson, 2004; Fieder et al., 2006; McGrath et al., 2006) and reproductive output (reviewed in Huber and Fieder, 2007). The latter has been demonstrated in several historic and modern populations of the Northern hemisphere (Smits et al., 1997; Lummaa and Tremblay, 2003; Huber et al., 2004a,b). In Austria, for instance, women born in summer have, on average, fewer children than those born during the remainder of the year provided they reproduce at all (Huber et al., 2004b).

The seasonal variation of the external environment is shifted by 180° between the Northern and the Southern hemisphere. If a causal link existed between the seasonality of environmental and maternal factors during the pre- and perinatal period and reproductive output in adulthood, a corresponding 6-month lag in the association between birth month and later reproduction should be expected between the hemispheres. Thus, the present study investigates (i) the association between the month of birth and offspring count of women in the Southern hemisphere, and (ii) whether such an association, if it exists, is shifted by half a year compared with the Northern hemisphere pattern. We analysed microdata of the contemporary New Zealand population and compared the pattern of the found association with that previously reported from Austrian women (Huber et al., 2004b), because both countries are fairly comparable regarding latitude and society. In the Austrian study, we had used the ‘Microcensus Austria 2001 on family survey’ (Statistik Austria, 2001) to analyse differences in offspring count respective to month of birth, which had been performed among the adult female members of the households examined during microcensus analysis (~25 000 households); the sample had been limited to women born after World War II and aged >45 years to obtain data about lifetime reproductive output (n = 3227). We had found that among the reproducing individuals in this sample, on average, women born in summer months (June–August) had fewer children than women born during any other month (Huber et al., 2004b). A third question in the present study concerns a part of the study population who had been born in the Northern hemisphere. We therefore investigated (iii) whether the association between the month of birth and offspring count differed between New Zealand women born in the Southern versus the Northern hemisphere.

Another potentially important issue concerns a possible influence of the socio-economic background. The degree of the seasonality of conceptions and births, for instance, reportedly varies with socio-economic status: several authors find a higher amplitude among poorer socio-economic groups (Pasamanick et al., 1960; Cowgill, 1966; Warren and Tyler, 1979), others report a more pronounced variation among higher socio-economic groups (James, 1971; Bobak and Gjonca, 2001). The present study therefore investigated (iv) whether the association between birth month and offspring count differs with the socio-economic group, as indicated by family income.

Materials and Methods

New Zealand is located between 34° and 47° South. It has a temperate type of climate with warm summers and cool winters, 6 months out of phase from the Northern hemisphere. We used individual-level census data where names and other identifying information have been removed, purchased from, and in cooperation with, Statistics New Zealand. This data set consists of the following variables for female New Zealand residents aged 15 years and over from the 1996 Census of Population: month of birth, year of birth (grouped into 5-year blocks to protect the confidentiality of individual information), ethnicity, country of birth, number of children born alive, educational level and total family income. Major advantages of this data set are its accuracy and that it represents a whole population census. We limited our analyses to women of European origin to avoid any influence of ethnic group, as well as to women aged older than 44 years to yield data about lifetime reproductive success, resulting in a sample of ~463 000 individuals. As ~22% of these individuals have been born in the Northern hemisphere, we compared the association between birth month and offspring count between New Zealand residents born in the Southern hemisphere versus those born in the Northern hemisphere (mainly Great Britain), who had migrated to New Zealand. In addition, we investigated the effect of socio-economic background at the time of the census on the association between birth month and offspring count: this association was analysed separately for each family income group. (Family income has been classified into four income categories which represent the quartiles of family incomes, calculated separately for each 5-year age interval from age 45–49 to age 95–99: income 1, lowest income quartile; income 4, highest income quartile.) We also estimated the distribution of New Zealand women born in the Southern and Northern hemisphere, respectively, across the four income categories. Finally, we accounted for the time trend in fertility rate by additionally analysing mean offspring count and the association between birth month and offspring count for each 10-year age cohort from age 45 to 74. (We limited this analysis to women younger than 75 years of age owing to the small sample size of older women.).

For statistical analyses, we used the statistical package SPSS 12.1 for Windows, Mathematica 5.2 as well as R 2.6. Sample sizes differ due to partially lacking income data. We analysed the association between birth month and offspring count using a Kruskal–Wallis test and confidence intervals were calculated on the basis of a Monte Carlo sampling ‘with replacement’ of 50 000 cases. In addition, we estimated peak locations as the birth month(s) with the lowest/highest mean offspring count and calculated the amplitude as the difference between the lowest and the highest mean offspring count, separately for each income category. We also calculated peak location and amplitude of mean offspring count per month of birth separately for the age intervals 45–54, 55–64 and 65–74 years.

To test the presence of 12-months rhythm, we further analysed the 12 monthly means of offspring count using a Halberg cosinor regression (Bingham et al., 1982): mean offspring count per month of birth was fitted to the following regression equation: yt = a0 + a1 × cos [(2π12) × t + Φ1], where yt is the estimate of the dependent variable mean offspring count per month of birth; a0 mesor, i.e. mean value of the periodic function; a1 amplitude of the periodic function; and Φ1 acrophase, i.e. difference between time zero and the first peak of the periodic function. We also calculated the bootstrapped lower and upper confidence interval (CI) of this regression. Significance level was set at P = 0.05.

Results

We find an association between the month of birth and offspring count of New Zealand women, of European origin, older than 44 years of age, who had been born in the Southern hemisphere: women born in summer months had, on average, 0.06 fewer children than winter born ones (Fig. 1, cosinor regression, P = 0.0865; Table I, Kruskal–Wallis test, Monte Carlo sampled, P = 0.015). This association is a mirror image of the pattern previously reported from Austrian women older than 45 years of age, where birth during the European summer (June–August) was associated with below average offspring count, albeit only among reproducing individuals (Huber et al., 2004b). Although in our study, fertility rate declines across 10-year age cohorts from age 74 to 45 years, the overall pattern of the association between birth month and offspring count remains essentially unchanged (Table II).

Figure 1
Mean (±SE) offspring count per month of birth (symbols) as well as cosinor regression (±95% CI bootstrapped) on the monthly means of offspring count (lines) of New Zealand women of European origin older than 44 years of age and born in ...
Table I
Amplitude and peaks of the monthly means of offspring count for each family income category of New Zealand women of European origin older than 44 years of age and born in the Southern hemisphere.
Table II
Mean (±SD) offspring count and amplitude and peaks of the monthly means of offspring count for 10 year age cohorts from age 45 to 74 years of New Zealand women of European origin.

The relationship between birth month and offspring count differs by socio-economic group: it is highly significant among women of the lowest family income category (Fig. 2) but non-significant within higher family income categories (Table I). The overall pattern represented by the peak locations of the monthly means of offspring count, however, are similar across income categories (Table I).

Figure 2
Mean (±SE) offspring count per month of birth (symbols) as well as cosinor regression (±95% CI bootstrapped) on the monthly means of offspring count (lines) of Southern hemisphere born New Zealand women of European origin older than 44 ...

In contrast to New Zealand women born in the Southern hemisphere, among those born in the Northern hemisphere, no significant association between birth month and offspring count was found (Fig. 3). The lack of significance seems not to result from differences in socio-economic background as the proportion of women within the lowest income category was similar between female New Zealanders born in the Northern and those born in the Southern hemisphere (Table III).

Figure 3
Mean (±SE) offspring count per month of birth (symbols) as well as cosinor regression (±95% CI bootstrapped) on the monthly means of offspring count (lines) of New Zealand women of European origin older than 44 years of age and born in ...
Table III
Distribution of New Zealand women of European origin older than 44 years of age across family income categories, separately for native individuals and European immigrants.

Discussion

We show that the association between birth month and offspring count of New Zealand women is a mirror image of the pattern previously reported from Austrian women (Huber et al., 2004b): women born during the summer months (New Zealand: December, January, February; Austria: June, July, August) have, on average, fewer children than those born during the remainder of the year. Also in two historic populations of the Northern hemisphere, a lower average reproductive output in summer born women has been reported (Smits et al., 1997; Lummaa and Tremblay, 2003).

Several studies demonstrate a comparable 6 months shift between the Northern and the Southern hemisphere, considering the association between birth month and: longevity (Doblhammer and Vaupel, 2001), the risk of developing schizophrenia (Castrogiovanni et al., 1998; Tochigi et al., 2004), epilepsy (Procopio et al., 2006), and type 1 diabetes mellitus (Willis et al., 2002). Other studies on the association between birth season and later life events, however, find less pronounced patterns in the Southern when compared with the Northern hemisphere or even fail to find an association between the month of birth and the investigated parameter in the Southern hemisphere at all (Henderson et al., 1991; McGrath and Welham, 1999; Willoughby et al., 2002). McGrath and Welham (1999) assume that the considerable milder winters in the studied countries might be a reason for the less consistent results in the Southern hemisphere.

The socio-economic background largely affected the association between birth month and offspring count: only among women of the lowest family income category, a significant association between birth month and offspring count was found; when analysing women of higher income categories, no significant association emerged. Thus, in the present study, the main contribution of the birth month effect on later reproduction apparently comes from the lowest family income category. We assume that lower protection from exposure to seasonally varying environmental factors (e.g. in the quality of housing) may be a major reason for the more pronounced birth month pattern found in poorer women. Our data are consistent with a study by Kihlbom and Johansson (2004), who reported a significant association between birth date and height among men of lower socio-economic background but no such association within the higher socio-economic group. Studies considering the effect of socio-economic category on the seasonal fluctuation of births and conceptions, on the other hand, are contradictory in their findings: some studies report increased seasonal variation among poorer groups (Pasamanick et al., 1960; Cowgill, 1966; Warren and Tyler, 1979), whereas others find increased seasonal variation within wealthier groups (James, 1971; Bobak and Gjonca, 2001).

Approximately one-fifth of our study population has been born in the Northern hemisphere. This affords the opportunity to compare the effect of seasonality during early development between New Zealand residents born in the Southern hemisphere versus those born in the Northern hemisphere, and who have migrated to New Zealand. We found that the association between birth month and reproductive output was non-significant in New Zealand women born in the Northern hemisphere, and the peak location was shifted when compared with the association found among native New Zealanders. This finding supports the assumption that the month of birth is an indicator for the pre- and perinatal exposure to seasonally fluctuating environmental and maternal factors, thus, suggesting an early effect. The lack of significance in the Northern hemisphere born sample, however, may also be caused by the smaller sample size as well as the fact that these women have been born in one hemisphere and migrated to another. Both reasons may also account for the finding that the results from the Northern hemisphere born New Zealanders were not compatible with the published data from Austria (Huber et al., 2004b). However, differences in socio-economic background are unlikely causes of the non-significant pattern found among immigrants, as this group contained a similar proportion of women in the lowest income category, where the strongest association between birth month and offspring count is found, among those born in the Southern and the Northern hemisphere.

A corresponding effect of the hemisphere of birth among Southern hemisphere residents has also been reported for the risk of developing schizophrenia and the risk of developing depressive symptoms as well as longevity (McGrath et al., 1995; Doblhammer and Vaupel, 2001; Joiner et al., 2002). The lifespan pattern of British immigrants to Australia, e.g. resembled that of Austrians and Danes rather than that of Australians, even though the results were noisier (Doblhammer and Vaupel, 2001).

A variety of environmental and maternal factors as well as physiological mechanisms may underlie the observed association between birth month and offspring count. The conditions experienced early in life are the consequence of a diversity of seasonally varying environmental and maternal factors. Among them are parameters such as photoperiod, UV-radiation, ambient temperature, quantity and quality of nutrition, infections, or behavioural and emotional factors. Air pollution, particularly the spraying of pesticides during summer time, may be another important parameter: according to Colborn and Carroll (2007), pesticides are known to penetrate maternal reproductive tissues, providing a pathway to harm offspring during the pre- and post-natal period. As exposure to pesticide spraying presumably is higher among poorer families, an effect of summer pesticides would be in line with our finding that the birth month effect largely relied on women from low socio-economic background. On the other hand, exposure to temperature extremes and nutritional variation is also likely to be more pronounced in poorer women, which would be likewise consistent with the stronger birth month effect found among them.

Seasonal preferences in family planning may be another possible cause of our results. Basso et al. (1995), for instance, reported that in Denmark, women prefer to give birth in spring. Then fecund women are more likely to give birth in spring, and subfecund women are more likely not to give birth until summer. As a result, summer born daughters may have a higher chance of being born to a subfecund mother and, thus, to inherit a potential genetic cause of subfecundity.

The study has limitations as it lacks data on still-births, abortions and the socio-economic status of the parents at the time of the women’s birth. In addition, legal requirements of data security afforded the aggregation of data into 5-year intervals, thereby precluding time-series analyses. However, it is fair to state that the quality of the data used is high. The census questions were asked of all women aged 15 years and over and enumerated by census. During processing it was found that errors were occurring with optical recognition of particular digits, so extensive work was done, including manual checking, to ensure that the data recorded were as reported by respondents. We can therefore be confident that the captured data is of good quality. Among women aged 45 years and over, 10.1% were childless. Non-response (5.6%), objection to answering the question (5.5%) and under-enumeration (perhaps 2%) were factors that affected the data for the ages considered in this paper, but analysis has shown that this will have had little effect on the quality of the derived information used here.

Acknowledgements

We thank the anonymous reviewers for their valuable comments on the manuscript. Data source Statistics New Zealand, 1996 Census of Population and Dwellings dataset. Access to the data used in this study was provided by Statistics New Zealand in a secure environment designed to give effect to the confidentiality provisions of the Statistics Act 1975.

Funding Austrian Science Fund (P18089-B03); Austrian Academy of Sciences (APART) to S.H.; University of Veterinary Medicine Vienna.

Footnotes

Conflict of interests: none.

Author’s Role Conception and design, drafting the article, final approval—S.H.

Acquisition of data, revising the article, final approval—R.D.

Analysis and interpretation of data, revising the article, final approval—M.F.

References

  • Basso O, Olsen J, Bisanti L, Juul S, Boldsen J. Are seasonal preferences in pregnancy planning a source of bias in studies of seasonal variation in reproductive outcomes? The European Study Group on Infertility and Subfecundity. Epidemiology. 1995;6:520–524. [PubMed]
  • Bingham C, Arbogast B, Cornélissen GG, Lee JK, Halberg F. Inferential statistical methods for estimating and comparing cosinor parameters. Chronobiologia. 1982;9:397–439. [PubMed]
  • Bobak M, Gjonca A. The seasonality of live birth is strongly influenced by socio-demographic factors. Hum Reprod. 2001;16:1512–1517. [PubMed]
  • Brenner AV, Linet MS, Shapiro WR, Selker RG, Fine HA, Black PM, Inskip PD. Season of birth and risk of brain tumors in adults. Neurology. 2004;27:276–281. [PubMed]
  • Castrogiovanni P, Iapichino S, Pacchierotti C, Pieraccini F. Season of birth in psychiatry. Neuropsychobiology. 1998;37:175–181. [PubMed]
  • Colborn T, Carroll LE. Pesticides, sexual development, reproduction, and fertility: current perspective and future direction. Hum Ecol Risk Assess. 2007;13:1078–1110.
  • Cowgill UM. Season of birth in man: contemporary situation with special reference to Europe and the Southern hemisphere. Ecology. 1966;47:614–623.
  • Doblhammer G, Vaupel JW. Lifespan depends on month of birth. Proc Natl Acad Sci USA. 2001;98:2934–2939. [PubMed]
  • Fieder M, Prossinger H, Iber K, Schaefer K, Wallner B, Huber S. Season of birth contributes to variation in university examination outcomes. Am J Hum Biol. 2006;18:714–717. [PubMed]
  • Gavrilov L, Gavrilova N. Early-life factors modulating lifespan. In: Rattan SIS, editor. Modulating Ageing and Longevity. Kluwer; Dordrecht: 2003. pp. 27–50.
  • Henderson AS, Korten AE, Jorm AF, McCusker E, Creasey H, Broe GA. Season of birth for Alzheimer’s disease in the Southern Hemisphere. Psychol Med. 1991;21:371–374. [PubMed]
  • Huber S, Fieder M. Season of birth effects on reproduction in women. Curr Women Health Rev. 2007;3:182–189.
  • Huber S, Fieder M, Wallner B, Iber K, Moser G. Season of birth effects on reproduction in contemporary humans: brief communication. Hum Reprod. 2004a;19:445–447. [PubMed]
  • Huber S, Fieder M, Wallner B, Moser G, Arnold W. Brief communication: Birth month influences reproductive performance in contemporary women. Hum Reprod. 2004b;19:1081–1082. [PubMed]
  • James WH. Social class and season of birth. J Biosoc Sci. 1971;3:309–320. [PubMed]
  • Joiner TE, Pfaff JJ, Acres JG, Johnson F. Birth month and suicidal and depressive symptoms in Australians born in the Southern vs. the Northern hemisphere. Psychiatr Res. 2002;112:89–92. [PubMed]
  • Kihlbom M, Johansson SE. Month of birth, socio-economic background and development on Swedish men. J Biosoc Sci. 2004;36:561–571. [PubMed]
  • Lerchl A. Month of birth and life expectancy: role of gender and age in a comparative approach. Naturwissenschaften. 2004;91:422–425. [PubMed]
  • Lummaa V, Tremblay M. Month of birth predicted reproductive success and fitness in pre-modern Canadian women. Proc R Soc Lond B. 2003;270:2355–2361. [PMC free article] [PubMed]
  • McGrath JJ, Welham JL. Season of birth and schizophrenia: a systematic review and meta-analysis of data from the Southern Hemisphere. Schizophr Res. 1999;35:237–242. [PubMed]
  • McGrath J, Welham J, Pemberton M. Month of birth, hemisphere of birth and schizophrenia. Br J Psychiatry. 1995;167:783–785. [PubMed]
  • McGrath JJ, Saha S, Lieberman DE, Buka S. Season of birth is associated with anthropometric and neurocognitive outcomes during infancy and childhood in a general population birth cohort. Schizophr Res. 2006;81:91–100. [PubMed]
  • Pasamanick B, Dinitz S, Knoblock H. Socio-economic and seasonal variations in birth rates. Millbank Mem Fund Quart. 1960;38:248–254. [PubMed]
  • Procopio M, Marriott PK, Davies RJE. Seasonality of birth in epilepsy: a Southern hemisphere study. Seizure. 2006;15:17–21. [PubMed]
  • Smits LJ, Poppel FWA, Verduin JA, Jongbloet PH, Straatman H, Zielhuis GA. Is fecundability associated with month of birth? An analysis of 19th and early 20th century family reconstruction data from The Netherlands. Hum Reprod. 1997;12:2572–2578. [PubMed]
  • Statistik Austria Microcensus, Third Quarter. 2001
  • Tochigi M, Okazaki Y, Kato N, Sasaki T. What causes seasonality of birth in schizophrenia? Neurosci Res. 2004;48:1–11. [PubMed]
  • Torrey EF, Miller J, Rawlings R, Yolken RH. Seasonality of births in schizophrenia and bipolar disorders: a review of literature. Schizophr Res. 1997;28:1–38. [PubMed]
  • Warren CH, Tyler CW. Social status and season of birth: a study of a metroplotan area in the Southeastern United States. Soc Biol. 1979;26:275–288. [PubMed]
  • Weber GW, Prossinger H, Seidler H. Height depends on month of birth. Nature. 1998;391:754–755. [PubMed]
  • Willis JA, Scott RS, Darlow BA, Lewy H, Ashkenazi I, Laron Z. Seasonality of birth and onset of clinical disease in children and adolescents (0-19 years) with type 1 diabetes mellitus in Canterbury, New Zealand. J Pediatr Endocrinol Metab. 2002;15:645–647. [PubMed]
  • Willoughby K, Watkins B, Beumont P, Maguire S, Lask B, Waller G. Pattern of birth in anorexia nervosa II: a comparison of early-onset cases in the Southern and Northern hemisphere. Int J Eat Disord. 2002;32:18–23. [PubMed]