1 Introduction

Some medical and biological studies have identified a strong link between the season during which a child is born and early childhood development and adult health (Atun-Einy et al., 2013; Boland et al., 2015; Weber et al., 1998). A better understanding of the seasonal birth peaks and troughs would help to prevent the spread of childhood diseases. In addition, understanding the monthly distribution of births and seasonal birth peaks and troughs can help improve annual birth projections and this, in turn, facilitates better planning and allocation of public resources, especially for maternal and child health and childcare.

The seasonality of births varies from geographic place to place, between historical periods, and in different cultural milieus; it differs across and within countries. The seasonal pattern of fertility is relatively stable even after a long period of time and along with the society and culture change, i.e., the birth peaks and troughs are unchangeable and unvarying. Some scholars believe that the seasonality of births changes in parallel with the transition process from high fertility to low fertility context (Lam & Miron, 1991; Shimura et al., 1981).

Existing birth timing studies in China focus mainly on factors like age of childbearing, birth interval, number of births, etc., and pay scant attention to the seasonality of births (i.e., monthly distribution pattern) (Bai et al., 2018; Si et al., 2017; Zhang, 2011). Some early studies conducted in the 1980s and 1990s suggested that November and December were peak birth months in China, meaning that more babies were born in winter than in summer (Liu, 1989; Zhang, 2011; Zheng, 1991). In the wake of China's booming socioeconomic development in recent decades and the multiple adjustments to its family planning policy, there has been a fundamental shift in people's attitudes towards childbearing and their reproductive behaviors. How such factors have affected the seasonality of births in China is the key question of this study. To deepen our understanding of observed seasonal birth patterns, this study disaggregates the social factors into parity, locale of residence (in an urban or rural area) and fertility policy adjustments (before or after), and investigates the effects of these factors on seasonal fluctuations of births in China since 1960.

2 Literature review

2.1 Close correlation between birth season and early childhood development & adult health

A number of studies have found that birth season is correlated with both early childhood development and adult development and health. Studies conducted in developed countries such as Australia, Israel and the United States have found that babies born in winter scored higher on cognitive tests than those born in summer (Atun-Einy et al., 2013; Weber et al., 1998). In the United States, babies born in the summer were often at an educational disadvantage after they became primary school students (Angrist & Keueger, 1991; Martin et al., 2004). In terms of lifetime disease risk, other studies have pointed to the strong influence of birth season on early childhood development. For example, a study of the medical records of patients in New York found that 55 diseases were associated with a patient's birth month (Boland et al., 2015). In the UK and Poland, a study found that winter-born adults were more likely to develop Addison's disease (primary adrenal insufficiency) than their summer-born peers (Pazderska et al., 2016). Studies conducted in developing countries, however, are relatively few. A study conducted in China's Qinba Mountains area found that babies born in winter had lower rate of anemia and significantly higher scores on cognitive development and psychomotor development than babies born in summer (Bai et al., 2018). An analysis with a sample size of 833 adult males from rural areas of Hebei province showed that adult males born in winter (November–January) were on average 1.04 cm shorter than those born during the rest of the year (Zhang, 2011). An analysis of data for 300,000 women from the Kadoorie Study of Chronic Disease in China (KSCDC) showed that women born in spring had earlier menarche and menopause. Such season-related patterns might be associated with the early development of the female reproductive system (Si et al., 2017). A most recent study, demonstrated a significant association of birth month with educational attainment based on 2010 China Family Panel Studies survey. The authors found that rural respondents born in the months of March and April are much less likely to obtain a high school degree than those born late in the year from October to December. The seasonal pattern is also found to significantly affect current cognitive achievements of the respondents (Chen & Ren, 2022).

2.2 Regional differences in birth seasonality

The seasonality of human birth varies among different populations as well as from one geographic region to another. Such seasonality is mainly manifested in two distinct modes. In the first mode, births generally peak at the beginning of the year (usually in the early spring) and then drop month by month. This pattern is usually called the "European pattern". In the second mode, births hit their low point in spring (usually April) and then edge up month by month until reaching a peak in early autumn, after which the births begin to edge down. This is called the "American pattern" (Doblhammer, 1999; Seiver, 1985). The seasonality of births tends to remain relatively stable within geographic regions, although there can be subtle differences within a given region. For instance, in northern Europe, births peak in spring (March–May) and bottom out in autumn (October–November), while in southern Europe, births generally peak in summer or late summer (Lam & Miron, 1994).

There have been few studies of seasonality in Asia, especially China, though there have been a handful of international comparative studies. One study of Singapore, Malaysia, Hong Kong and Taiwan found that Chinese people residing in these four countries/regions exhibited unique birth seasonality that differed from the patterns in both the United States and Europe. Specifically, births generally peaked in October in Singapore, Malaysia and Hong Kong, but in November in Taiwan, whilst the birth troughs of the respective locales were entirely different. One explanation is that the homogeneous influence of traditional Chinese culture on these four countries/regions may be so strong that even economic development can do little to change birth seasonality. The peak season for marriage occurs during the Spring Festival (the lunar new year period in January or February) in Taiwan, but in November and December in Singapore and Hong Kong. The seasonality of marriages well explains the seasonality of first births (Abeysinghe, 1991). Another study of Taiwan found that seasonal variations in births showed a U-shaped pattern (Qiu, 2005). Vital statistics in Hong Kong also revealed that live births showed salient and stable seasonality, with fewer births taking place in the first half of the year (especially between February and May) (Census & Statistics Department of the Government of the Hong Kong Special Administrative Region, 2017).

2.3 Determinants of birth seasonality

Doblhammer et al. (1999) classified studies on birth seasonality into three types. The first type of study attempted to discern the relationship between birth seasonality and environmental, social, and biological determinants. The second type sought to identify the reason why the patterns of birth seasonality varied over time, and the third type tried to pinpoint the fundamental causes of birth peaks and troughs (Doblhammer et al., 1999).

It is generally believed that social, environmental and physiological determinants, including income level, cultural traditions, ethnicity, holidays, rainfall, cold weather and seasonal variations in sperm quality, contribute together to the seasonality of births (Bobak & Gjonca, 2001; Bronson, 1995; Lam & Miron, 1991, 1994; Levine et al., 1990; Randall, 1987; Rojansky et al., 1992; Spira, 1991). Some scholars argue that seasonal changes of the occurrence of puberty (Rodgers & Buster, 1994; Valšík, 1965) and variations in sexual behaviors, could have an impact on the cyclical pattern of births (Naeye & Peters, 1980; Udry & Morris, 1967). Another broad category of studies focus on the seasonal changes in women's reproductive behaviors, the timing they are more or less likely to become pregnant or have an abortion, and their use of contraceptives (Peterson & Alexander, 1992; Rodgers & Udry, 1988).

2.4 Current status of research on birth seasonality in China

Studies of birth seasonality in China are generally part of research efforts focused on maternal and child health care resources. National level studies have shown that the peak month for neonatal births is November, with the peak for preterm births occurring in mid-November (Ying et al., 2017). More studies based on data from particular regions have shown different results; for example, the peak birth month was September in Zhaoqing City, Guangdong Province (Zeng, 2007), November in Huoshan County, Anhui Province (Tao & Jiang, 2010), and December in Guangzhou City (Li et al., 2009). However, due to the small scale of these studies, they are not representative of birth seasonality at the national level. As analyses from large-scale surveys rely mostly on data from the 1980s and 1990s (Liu, 1989), the undated knowledge on birth seasonality in China is on demand,

Drawing on a variety of data sources, this study examines birth seasonality in China from 1960 to 2019 and attempts to discern similarities and differences between the Chinese pattern and the American and European patterns. Given the characteristics and limitations of the data, we took 1960 as the starting year and calculated the average deviation of births for each month of every decade as the basis for our comparative analysis. This study takes into account the evolution of national fertility policies in China when comparing birth seasonality over periods. Furthermore, in order to deepen our understanding of the seasonality of births in China, additional two factors influencing seasonality—parity, locale of residence (urban or rural area) are also investigated.

3 Methodology and data

3.1 Data sources

This study mainly relies on three types data sources:

  1. (1)

    The 1988 National Fertility and family planning Sampling Survey. The 1988 National Fertility and Family Planning Survey adopted a stratified, systematic, clustered, and unequal proportion sampling method with a national sampling ratio of 1.98 ‰. A total of 2,152,044 respondents surveyed, including 467,162 married women, whose detailed pregnancy history and childbearing history were collected.

  2. (2)

    The 120 Counties Population Dynamics Monitoring System (hereafter also labelled 120 CMS). County level units included in the system were randomly selected from eastern, central and western regions based on the 2000 National Population Census. This system was intended to provide information on population dynamics, first established in 2008 by the National Health and Family Planning Commission (NHFPC), terminated and replaced in 2018 by other monitoring systems. It collected individual demographic information and recorded population dynamics, including births, marriages and deaths. The latest available 2016 data cover 117 counties in 28 provinces excluding Zhejiang, Yunnan and Tibet, and include a total population of 128.4 million, accounting for 9.4% of China’s total population. Previous research proved the overall good representativeness of the 120 CMS (Wang, 2013; Zhang et al., 2016).

  1. (3)

    The national Birth Registration System in China, established by the NHFPC (hereafter also labelled BRS). This system collected the date of birth, sex, place of birth for each live birth and the names and birth dates of the new live birth’s parents, etc. through health departments at all and is ideally expected with a national coverage. The annual number of births for 2015–2020 in this data set is more than 10 million.Footnote 1

In order to verify the birth seasonality based on each dataset is consistency with other available data source, we compared birth seasonality for the same period 1960–1980 based on the 1988 National Fertility and family planning Sampling Survey with that based on the 1982 National 1% Fertility and Family Planning survey. Similar comparison also is conducted to explore the birth seasonality in the period 1987–2014 based on 120 CMS and other data sources, which including the 1990 national census and the annual population sample surveys in 2003–2011. The 2015–2019 BRS data were verified against records of live births taken from hospital delivery nationwide as well. These comparisons confirm the consistency of the monthly distribution pattern of the years under-examined both by the data source we relied on and other various data sources, and we could believe the bias is very limited in developing the knowledge of birth seasonality in China based on the data source we selected.

3.2 Data analysis

We used the method developed by He and Earn (2007) and converted the births for each month in the annual time-series into a percentage of deviation from the monthly mean for a given year [– 100, 100]. Other relevant parameters include the maximum and minimum deviations, and the period-average monthly deviation (He & Earn, 2007). The relevant equations are as follows:

$$\overline{X}_{i} = \frac{1}{12}\sum\limits_{j = 1}^{12} {X_{ij} }$$
(1)
$$C_{ij} = \frac{{({\text{Days}}\;{\text{in}}\;{\text{year}}\;i)/12}}{{{\text{Days}}\;{\text{in}}\;{\text{month}}\;j\;{\text{of}}\;{\text{year}}\;i}}$$
(2)
$$Y_{ij} = \frac{{C_{ij} X_{ij} - \overline{X}_{i} }}{{\overline{X}_{i} }}$$
(3)
$$Z_{j} = \frac{1}{{N_{yr} }}\sum\limits_{j = 1}^{i + 9} {Y_{ij} }$$
(4)

The number of births in the jth month of each year is denoted by Xij. Equation 1 represents the average number of births per month in year i. Equation 2 defines the scale factor Cij to correct for differences caused by the different number of days in each month. Equation 3 calculates the deviation Yij of monthly births corrected by the length of month and the scale factor. Equation 4 calculates the mean value Zj (Nyr = 10) of the deviation of monthly births in a certain period (every decade).

4 Results

4.1 Variations in the seasonality of births in China since 1960

4.1.1 Seasonality in the monthly distribution of births in China is easily observable

The seasonality of births in China has a distinct pattern that differs from the European and American patterns but is similar to the patterns of overseas Chinese. The monthly distribution of births is uneven; March through June are the lean months, while October through December stand out as peak months. The number of births in October through December was 15–30% higher than the monthly average, whereas the number in April through June was roughly 10–20% lower than the monthly average (see Fig. 1).

Fig. 1
figure 1

Seasonality of births in China from 1960 to 2017

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If we go back about 9 months from the month of birth, we can see the seasonal distribution of conception months (see the x-axis in Fig. 1). Regarding the seasonality of conception, June through October are the low months for conception, while December, January through March, and May are the peak months for conception. The Chinese Spring Festival (the Chinese new year) occurs in January or February, indicating that China has a “holiday effect”, which is akin to the “Christmas effect” in Western countries—couples are more inclined to conceive a child during the periods around holidays like May Day and Spring Festival. According to the 1982 National 1% Fertility and Family Planning Survey, from 1946 to 1981, the peak months for marriages were January, February, October, November and December (Zheng, 1991), which are consistent with the seasonal patterns of conceptions.

4.1.2 There exist distinct differences in the monthly distribution of births in China across periods

Although China long maintained a salient pattern of birth seasonality that peaked in winter and bottomed out in summer, seasonality has gradually evolved with the lapse of time. Birth seasonality patterns during the 1960s, 1970s and 1980s were almost identical—the first birth peak lasted from October to December at the end of the year, the second birth peak occurred in February at the beginning of the year, and the birth trough was evident in May and June.

Prior to the 1990s, the deviation in peak months was as high as 30%, whilst that in lean months was as low as 20%. Since the 1990s, the deviations in peak and lean months have decreased to roughly 10–20% and less than 10%, respectively. In addition to the shift in monthly deviation, the curve has also become increasingly flatter. During the first three decades, September through December were the peak months for births; however, since 1990, births have gradually edged down in September and December with a drop in deviations, while edging up steadily in August to make it one of the peak months for births. Some experts argue that this phenomenon is the result of choices made by couples in response to changes in school enrollment dates introduced in the Compulsory Education Law of the People's Republic of China (1986).Footnote 2

An examination of changes in China's population and family planning policy reveals that in periods when fertility policy remained relatively stable after its initial introduction (such as during the 1970s, 1990s, and 2000s), the seasonality of births also remained quite stable from year to year, with scant variations between years. In periods of frequent policy adjustments (such as during the 1980s and the years 2014–2019), the seasonality of births saw major fluctuations, with noticeable variations observed between years. This highlights the correlation between birth seasonality and fertility policy adjustments in the respective periods, as well as the correlation between birth seasonality and the contraceptive prevalence rate (CPR), especially the prevalence of long-acting contraceptive use during these periods.

In the 1960s (CPR = 4.3%) and the 1970s (CPR = 30.8%) when the prevalence of contraceptive use was quite low, China’s economy was still primarily agricultural and agriculture was the source of most people’s livelihood. Couples gave birth to as many children as they wanted without any intervention by the state. Therefore, the seasonality of births during these decades was largely consistent, with winter being the peak season for births. With the introduction of One-child policy in the 1980s, CPR soared to over 85% and the prevalence of long-acting contraceptive use also topped 80% (Wang, 2011). The seasonality of births in China changed along with the widespread use of long-acting contraceptive pattern gradually.

4.2 Parity differences in birth seasonality

The seasonal pattern of child birth by parity has experienced a process characterized by convergence, divergence and re-convergence. The monthly deviation of births also saw noticeable changes for different birth orders during the respective decades covered in this study (see Fig. 2).

Fig. 2
figure 2

Average monthly deviation of births by period and parity in China

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During the 1960s, the seasonality of births was relatively similar between birth orders. The first birth peak occurred from October through December and the second peak was in February, while the low point for births was in the summer. A pattern of fewer births during busy farming seasons and more births during slack seasons reflected the fact that China’s economy was largely agricultural at this time.

With the introduction of the “Later, Longer, Fewer” fertility policy in 1973, the seasonality of births began to differentiate slightly for middle and last born children—the positive deviation of second and third births in peak months declined slightly, whilst the negative deviation of second and third births in lean months also declined to a certain extent.Footnote 3 Differentiation increased further in the 1980s, with the seasonality of second births deviating the most from the pattern of first births, whereas third births lagged slightly. In the 1990s, against the backdrop of implementation of a more stringent family planning policy, the seasonality of second and third births became almost the same, both peaking in February, August and October, with deviation staying at around 10%. Such differentiation in the seasonality of high-order births remained until 2009.

The seasonality of first births remained largely stable until 2010, after which the variations between peak and the trough decreased, which resulted in the convergence of the seasonality of all-order births. The monthly deviation of births has dropped from 30% in 1960s to less than 10% since 2010. In parallel, due to the weakening of the seasonality of all-order births, monthly distribution has also become more even.

4.3 Urban–rural differences in birth seasonality

In an effort to understand how birth seasonality can differ under different fertility policies, we compared the monthly distributions of first and second births in urban and rural areas. Considering the availability of data for the location of residence (in an urban or rural area), this comparison is only covers first and second births during the years 1980–2014.

During One-child policy period, the majority urban couples have to follow the one-child-per-couple-rule while rural couples have been allowed a second child, subject to province-specific conditions. Contraceptive measures are also popularized earlier in cities, and fertility policies are implemented earlier and more strictly. The implementation of fertility policy generally more relaxed in rural areas as well. In addition, urban populations have stronger planning and control over childbirth, leading to earlier changes in people's reproductive behavior and awareness, resulting in faster seasonal convergence of first and second birth. In the 1990s, cities had already formed absolute peak births of first and second child in August and October, as well as summer lows.

Our analysis found that both urban and rural areas exhibited significant seasonality of births, but seasonality was more significant in rural areas. The monthly deviation of births was higher in rural areas than in urban areas, and the seasonal differences between birth orders were always more pronounced in rural areas than in urban areas. In both urban and rural areas, the seasonal distribution of first births diminished gradually over time, and has become similar to the monthly distribution of second births since 2010 (see Fig. 3). From a longitudinal perspective, the deviation in the peak birth month decreased over time in both urban and rural areas. The positive deviation in November, the peak month for first births in rural areas, has gradually decreased from 35 to 18% since the 1980s, and the deviation in the peak month for first births in urban areas has decreased from 30% (November) to 10% (August) since the 1980s.

Fig. 3
figure 3

Average monthly deviation of births by parity, period and residence in China

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In addition, the concentration of births in August in Urban area has gradually increased. In the 1980s, August became one of the peak months of births in cities, while this phenomenon began to appear in rural areas in the 1990s. At the same time, the positive deviation of August births in cities has always been higher than 10%, and the deviation since 2010 has been greater than other traditional peak months (such as October and November), while the positive deviation of August births in rural areas is only about 5%, indicating that the intentional selection effect of August births is more prominent in cities.

4.4 Variations in the seasonality of second births following policy adjustments

As there are multiple adjustments and improvements to China's fertility policies, people’s childbearing behavior, the number of children they have, the birth timing, birth spacing also changed accordingly. This section is focused on the monthly distribution of second births since 2013 to examine people's responses to fertility policy adjustments.

Our analysis found that after policy adjustments in 2014 and 2016, the monthly distribution of second births underwent noticeable changes. Following introduction of the Selective Two-child Policy that all couples where one partner was single child were eligible to have a second child in 2014, the seasonality of second births underwent structural changes, with dramatic changes to both the monthly distribution and concentration of second births. Before the new two-child policy, the peak months for second births were January, November and October in 2013, in which the monthly deviation of second births was 12.88%, 9.68%, and 7.16% respectively (see the panel A of Fig. 4). However, the peak months for second child births in 2014 have shifted to October to December with much higher monthly deviation of second births for these three months as 23.27%, 10.95% and 5.92% for each correspondingly, Similar fertility response was observed in January and February of 2015 with a 16.5% and 6.4% monthly deviation for these two months (the panel B of Fig. 4). This clearly indicating the strong effect of the selective two child policy implementation on the rising of monthly second births since 2014.

Fig. 4
figure 4

Monthly deviation of second births in the years before and following fertility policy adjustments in China

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The same kinds of changes were also observed following the introduction of the Universal Two-Child Policy in 2016 when every couple is allowed to have two children. Analysis found that the first half of 2016 (January through July) marked the trough and negative deviation for second births, whilst October, November and December stood out as the peak month, with the number of second births in those months being 29.0%, 32.9%, and 19.6% higher than the monthly average of second births in that year. This trend continued from January through March of 2017, with monthly deviation reaching 17.6%, 16.7% and 8.6%, respectively, in these three months. In subsequent months, the monthly deviation of second births was largely negative, meaning that second births were mainly concentrated in the first few months of the year and were, thus, a response to the Universal Two-child Policy. The pattern of second births in 2018 was akin to that in 2017 (see Fig. 4). Taken together, these two fertility policy adjustments altered the monthly distribution patterns of second births, reflecting the adjustments people made to achieve their fertility plans under new policies.

Further analysis found that following the introduction of the Universal Two-child Policy in 2016, the proportion of second births dropped in most months for the lower-age group (under 30 years old), but rose in the advanced-age group (over 30 years old). This rise was especially the case for women with urban household registration, among whom an increase of roughly 10 percentage points was observed. The greatest increase was observed in women aged 35–49, suggesting that women in advanced childbearing age were more eager to have a second child than younger women (see Panel A & Panel B in Fig. 5). The second-child fertility potential long accumulated in advanced women of childbearing age is still being unleashed.

Fig. 5
figure 5

Month-to-month variations in the proportion of second births by age group through 2015–2019 (the average proportion of second births in each age group from 2015 to 2019 as a base)

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5 Conclusions and discussion

Our study found that winter was the peak season of births in China, while spring and summer were the lean seasons, a pattern which is quite different from the European and American patterns. The seasonality of births in China remained relatively stable until the 1980s, after which the monthly deviation of births gradually diminished, and the differences in the numbers of births per month also narrowed. Although the seasonal distribution remained relatively stable during the study period, there are significant differences in birth season patterns among birth parity, residential type and fertility policy adjustments. The key points are:

  1. (1)

    While a high degree of seasonality was observed in first births, second and subsequent births did not show distinctive seasonal patterns, suggesting that higher-order births were more likely affected by self-choice and self-intervention. Such a shift in the seasonality of births probably resulted from the introduction of One-child policy in 1980 and the extensive use of modern contraceptives that began during that decade.

  2. (2)

    During One-child policy period, the majority urban couples have to follow the one-child-per-couple-rule while rural couples have been allowed a second child, subject to province-specific conditions. The implementation of fertility policy was uneven, with enforcement generally more relaxed in rural areas as well. Therefore, the monthly deviation of births was higher in rural areas than in urban areas, and seasonal differences between birth orders were always more prominent in rural areas than in urban areas. In both urban and rural areas, the seasonal distribution of first births diminished gradually over time, and since 2010 have been similar to the monthly distribution of second births.

  3. (3)

    The seasonality of births underwent dramatic changes after the introduction first of the Selective Two-child Policy and then the Universal Two-child Policy. After these two rounds of policy adjustments in 2014 and 2016, the monthly distribution of second births underwent significant changes, indicating noticeable shifts in people's reproductive behaviors. These shifts reflect the adjustments people made to achieve their fertility plans under the new policies context.

  4. (4)

    This study found that the monthly distribution of births was uneven in China, with marked variations observed after fertility policy adjustments, in certain years of the Chinese zodiac, in particular, the years of the Dragon and the Goat, and periods of time following major epidemics or catastrophic events. When using the number of babies born during several months to infer the number of babies born during the whole year, one must take into account the monthly distribution pattern of births in respective provinces.

This paper provides a brief look at the seasonality of births in China. Future research needs to differentiate more precisely between the push and pull factors that either enhance or weaken birth seasonality, and gradually incorporate additional variables such as weather conditions, seasonality of food supplies, farming seasons, conception and abortion rates, parental socioeconomic status, etc. Furthermore, there has been little research to determine what, if any, connection exists between births per month and fertility intentions. An examination into possible links between birth seasonality and fertility intentions would help verify the impact of external events (e.g., major epidemics, catastrophic events, special years) on people's fertility plans. Lastly, the seasonality of births in China’s enormous migrant population has yet to be explored. If a standardized approach (such as monthly birth rate) can be developed to indicate both month-to-month and birth-level differences, it will be possible for scholars to take the study of birth seasonality to a new stage.