- Research article
- Open Access
Greater family size is associated with less cancer risk: an ecological analysis of 178 countries
BMC Cancer volume 18, Article number: 924 (2018)
Greater family size measured with total fertility rate (TFR) and with household size, may offer more life satisfaction to the family members. Positive psychological well-being has been postulated to decrease cancer initiation risk. This ecological study aims to examine the worldwide correlation between family size, used as the measure of positive psychological well-being, and total cancer incidence rates.
Country specific estimates obtained from United Nations agencies on total cancer incidence rates (total, female and male rates in age range 0–49 years and all ages respectively), all ages site cancer incidence (bladder, breast, cervix uteri, colorectum, corpus uteri, lung, ovary and stomach), TFR, household size, life expectancy, urbanization, per capita GDP PPP and self-calculated Biological State Index (Ibs) were matched for data analysis. Pearson’s, non-parametric Spearman’s, partial correlations, independent T-test and multivariate regressions were conducted in SPSS.
Worldwide, TFR and household size were significantly and negatively correlated to all the cancer incidence variables. These correlations remained significant in partial correlation analysis when GDP, life expectancy, Ibs and urbanization were controlled for. TFR correlated to male cancer incidence rate (all ages) significantly stronger than it did to female cancer incidence rate (all ages) in both Pearson’s and partial correlations. Multivariate stepwise regression analysis indicated that TFR and household size were consistently significant predictors of all cancer incidence variables.
Countries with greater family size have lower cancer risk in both females, and especially males. Our results seem to suggest that it may be worthwhile further examining correlations between family size and cancer risk in males and females through the cohort and case-control studies based on large samples.
Total fertility rate (TFR) representing the total number of births during a lifetime of a female [1, 2] has been used to measure childbearing and family size [3,4,5] in a number of studies. The prevalent conclusions were that more childbearing (greater TFR) may protect against female breast cancer [6, 7], corpus uteri cancer  and ovarian cancer  due to less oestrogen production or less menstrual cycles  and more oxytocin secretion [11, 12], but may contribute to cervix uteri cancer because of more exposure to infection risk .
The number of children born into a family does not only influence the mother’s physiological health of her reproductive system, but also has effects on health, including cancer development, and on her other systems and on all the other family members. For instance, greater family size has been postulated to protect family members from developing colorectal cancer , melanoma of skin , bladder cancer , breast cancer  and stomach cancer (in males only) . Relationships between greater family size /household size and lung cancer [5, 15] and stomach cancer (females)  were explored, but without much success of seeing a clear trend. Aldrich et al.  reported that household size was in significant association with a risk of developing lung cancer in African Americans, but not in Latinos.
These controversial and circumstantial correlations between reproductive behaviour and a comprehensive health effect on all family members directed our attention to seeking alternative explanation of the relationship between TFR and risk factors for cancer. Psychological factors have been suggested to be linked with cancer initiation, but the mechanism has been intriguing professionals and laypeople for decades [16, 17]. Although studies on the possible effects of positive and negative psychological factors arising from life events on cancer incidence and prognosis are numerous, the literature remains contradictory as to methods and impacts [15, 18,19,20]. Extensive studies have suggested that adverse life events and the associated psychological stress may predispose to cancers in various body sites [21,22,23,24,25]. Everson et al.  reported that more stress may increase the cancer risk. This might be because people tend to recall adverse life events, but easily forget those positive ones, which constantly happen in the daily life. Cancer patients may more easily recall those negative life events which have been considered as cancer risks [27,28,29,30,31]. Only a limited number of studies have addressed the relationship between life satisfaction and cancer risk [15, 32], but the conclusions were controversial.
Research conducted into health effects of positive psychological well-being has concluded that family life satisfaction may stimulate oxytocin production in the human body [33,34,35,36,37,38,39], which may have the inhibitory effect on specific cancers [11, 12, 40, 41]. For example, positive psychological wellbeing has been postulated to protect against cancer risk in Israeli women , reduce the number of American cancer patients from going into metastasis  and help cancer patients with cancer’s detection, treatment, and survival . Large families have greater life satisfaction in both Western and Eastern populations [43, 44]. Nan et al.  have also concluded that the bigger family size is, the higher Subjective Happiness Scale (SHS) result is in the family, regardless of cultural backgrounds.
Therefore, in this study, we assessed, from a global perspective, whether greater family size, measured with TFR  and household size may lower cancer risk using empirical, macro-level data obtained from international organizations.
The population specific data were collected for this ecological study.
The GLOBOCAN 2012 estimates of incidence rates (age standardised, world) of all cancers excluding non-melanoma skin cancer (C00–97, but C44) in total, and separately for males and females of all ages  were used. Crude estimates of incidence rates of all cancers excluding non-melanoma skin cancer (C00–97, but C44) in total, and for males and females in age group 0–49 years were also obtained.
The incidence rates of the individual site-specific cancers (bladder, breast, cervix uteri, colorectum, corpus uteri, lung, melanoma and ovary) were extracted as the dependent variables for data analysis in this study. The results from this study were aligned with the findings of previous studies of the relationships between family/household size and each of these site-specific cancers namely lung cancer , bladder cancer, melanoma and colon cancer .
GLOBOCAN is a project conducted by the International Agency for Research on Cancer (IARC) of the World Health Organization. This project provides contemporary population level estimates by cancer site and sex using the best available data in each population and uses nine comprehensive methods of estimation .
The United Nations Statistics Division estimates of the life expectancy , the total population in households and the number of households .
Life expectancy is the average number of years a person of a given age, residing in a given country is expected to live. We extracted the life expectancy at age 60 years (e60, 2005–2010) from abridged life Tables (1950–2100)  published online. Ageing has been a significant risk predictor of cancer. In this study, life expectancy (e60) was considered as the indicator of ageing.
As instructed by the United Nations Statistics Division, we created a new variable, household size, through dividing the total population in households  by the number of households  in each country.
The World Bank published data  on Gross Domestic Product (GDP), total fertility rate (TFR) and urbanization.
GDP was expressed in per capita purchasing power parity (PPP in current international $) in 2010. The World Bank also clusters countries into 4 classifications in terms of their GDP per capita (High Income, Upper Middle Income, Low Middle Income and Low Income). In this study, we grouped countries with High Income and Upper Middle Income as developed countries, and countries with Low Middle Income and Low Income as developing countries.
Urbanization was expressed with the percentage of total population living in urban areas in 2010.
Total Fertility Rate (TFR) represents total births per woman during her lifetime. It indicates the number of children that would be born to a woman if she were to live to the end of her childbearing years and bear children in accordance with age-specific fertility rates of the specified year.
Total births per woman have been used to indicate the family size in studies at an individual level [3, 4]. Therefore, we used TFR as the measure of family size in this study, and terms “TFR” and “family size” were interchangeably used thereafter. Household size is used as the proxy of family size in this study that has been calculated from data independent from those used for TFR.
Biological State Index (Ibs) was self-calculated [49, 50] with the fertility data of each country published by United Nations in 2008  and the mortality data of life Tables (2009) published by World Health Organization (WHO) in 2012 .
Ibs was included as one of the confounding factors that indicates the level of adaptation of a population . The Ibs values range between 0 and 1.0. A greater Ibs value of a population means less opportunity for natural selection, and vice versa. The simplest interpretation of Ibs is that it indicates a probability with which an average person born into a population is able to pass her/his genes to the next generation. Recent studies have postulated that Ibs may indicate the magnitude of deleterious gene/mutation accumulation in a population due to relaxed natural selection [53,54,55,56]. The greater Ibs value means that a population has accumulated more deleterious gene/mutations of cancer , obesity  and type 1 diabetes , and vice versa [53,54,55,56]. Inclusion of Ibs as a confounder may remove the influence of cancer gene/mutation accumulation on the correlation between family size and cancer incidence.
We used country specific cancer incidence rates, TFR, GDP, urbanization, household size and life expectancies for all countries where the most updated and recent data were available (N = 178). In order to capture as many countries as we could for this study, we aligned country specific TFR with all cancer incidence rates, and then we matched other country-specific variables with the TFR.
Each country was treated as an individual subject in the analysis. Numbers of countries included in analyses of relationships with other variables may differ somewhat because all information was not uniformly available for all countries. The list of countries included in this study can be found in Additional file 1.
We singled out the population segment aged 0–49 years because females enter menopause at around 50 years of age and since then they produce less and less female hormones. Numerous studies have associated female oestrogen level with cancer risk [10, 11].
All the aforementioned data were freely available from the websites of the UN agencies. No ethical approval or written informed consent for participation was required.
Scatter plots were produced in Excel (Microsoft® 2016) to explore and visualize the correlations between family size and cancer incidence rates for all ages in total population, males and females respectively. Scatterplots were repeated in the age group (0–49) for further testing the relationships between family size and cancer incidence rates. Scatter plots allowed us to assess data quality and distributions of variables. In the supplemental material, family size was replaced with household size for performing the scatter plots (Additional file 2).
Prior to correlation/regression analyses all data were log-transformed (ln) in order to reduce non-homoscedascity of their distributions and possible curvilinearity of regressions. To assess the relationships between each cancer incidence rate and family size, the analysis proceeded in four steps.
Pearson’s and nonparametric correlations (Spearman’s rho) were used to evaluate the strength and direction of the associations between family size and all other variables, including independent variables and confounders.
Partial correlation of Pearson’s moment-product approach was used to assess the relationship between each cancer incidence rate and family size respectively while we controlled for GDP PPP [45, 46], urbanization [57, 58], Ibs and life expectancy  which have been commonly considered as the contributing factors of cancer.
Fisher’s r-to-z transformation was performed to test significance of differences between correlation coefficients.
Standard multiple linear regression (stepwise) was performed to identify the most significant predictor(s) of cancer risk. The dependent variables included cancer incidence rate by sex (total, male and female, age group 0–49 and all ages respectively). The independent variables/predictors entered into analyses were family size, urbanization, GDP, Ibs and life expectancy (not for cancer variables for 0–49 years).
The independent samples t-test was performed to compare the means of each cancer variable in high and low fertility countries divided at the cut point of TFR = 2.36. We used 2.36 as the cut point because it is the world average TFR published by the United Nations for the period of 2010–2015 .
Socioeconomic level plays a critical role in family happiness. In parallel to the analyses of the relationship between family size and cancer variables worldwide, the relationships between family size and each cancer variable in developed and developing country groupings were also examined respectively. Descriptive statistics including standard deviations of all variables were calculated for analysing and comparing the covariance (relationship between family size and cancer incidence) in all countries (n = 178), in developed world (n = 98) and in developing world (n = 80).
Subsequently, family size was substituted with household size for reanalysing the associations and regressions. The results were reported in Additional files 3 and 4 (Tables S2 and S3). There was no stratification of country grouping in the supplemental analyses due to limited sample size of countries for which household size was available (n = 58).
Pearson’s, non-parametric Spearman’s rho correlations, partial correlation, stepwise multiple linear regression, independent samples t-test analyses and descriptive statistics were calculated using SPSS v. 22 (SPSS Inc., Chicago Il USA). To increase homoscedasticity of data distributions, log-transformed variables were used for correlation analyses. The significance was reported when P-value was < 0.05, but the significance levels of p < 0.01 and p < 0.001 were also indicated in the tables. Regression analysis criteria were set at probability of F to enter ≤0.05 and probability of F to remove ≥0.10. The raw data were used for scatter plots.
Figure 1 shows a negative and strong correlation of family size to cancer incidence rates in total population and in males and females separately (all ages). The non-linear relationships between family size and group cancer incidence variables (total population, males, females in all ages) identified in the scatterplots show the strong correlation between family size and cancer incidence rate (R2 = 0.4901, 0.3755 and 0.5637 respectively). The relationships are also true in the age (0–49) group (Fig. 2). Household size as the proxy of family size has shown the similar correlation to all cancers incidence rates (total, female and male) (Additional file 1: Figure S1).
The subsequent analyses of log-transformed data proved these relationships. Globally (n = 178), Spearman’s rank correlation showed that family size was in significant negative correlation to all cancers incidence rates (both sexes) in all ages (r = − 0.716, p < 0.001) and in age group 0–49 years (r = − 0.752, p < 0.001), separately in females of all ages (r = − 0.640, p < 0.001) and age group 0–49 years (r = − 0.762, p < 0.001) and in males of all ages (r = − 0.761, p < 0.001) and age group 0–49 years (r = − 0.765, p < 0.001) (Table 1). Pearson’s r showed quite similar relationship trends between family size and the cancer variables (Table 1).
When family size was replaced with household size for supplemental data analysis, household size also showed significant, negative and strong correlation to each cancer variable (both sexes, female and male in age groups, 0–49 and all ages respectively) (Additional file 3: Table S1).
In developed countries grouping (n = 98), Spearman’s rank correlation showed that family size was in significant negative correlation to all cancers incidence rates (both sexes) in all ages (r = − 0.540, p < 0.001) and age group 0–49 years (r = − 0.705, p < 0.001), separately in females of all ages (r = − 0.477, p < 0.001) and age group 0–49 years (r = − 0.581, p < 0.001) (Table 1) and in males of all ages (r = − 0.582, p < 0.001) and age group 0–49 years (r = − 0.705, p < 0.001). Pearson’s r showed quite similar relationship trends between family size and the cancer variables (Table 1).
In developing countries grouping (n = 80), Spearman’s rank correlation showed that family size was in significant negative correlation to all cancers incidence rates in all ages (r = − 0.334, p < 0.001) and age group 0–49 years (r = − 0.498, p < 0.001), separately in females of age group 0–49 years (r = − 0.482, p < 0.001) but not at all ages (r = − 0.140) and in males of all ages (r = − 0.457, p < 0.001) and age group 0–49 years (r = − 0.449, p < 0.001) (Table 1). Pearson’s r showed quite similar relationship trends between family size and the cancer variables, except for all cancers incidence rate in females at all ages (r = − 0.200, r < 0.05) (Table 1).
When, in the partial correlation analyses, we controlled for the major confounders (GDP, urbanization, life expectancy (not for cancer variable in age group 0–49 years) and Ibs): 1) globally (n = 178), family size remained in the significant correlation to all cancer incidence rates (both sexes) in all ages (r = − 0.362, p < 0.001) and the age group 0–49 years (r = − 0.534, p < 0.001), in females of all ages (r = − 0.230 p < 0.001) and age group 0–49 years (r = − 0.492, p < 0.001) and in males of all ages (r = − 0.449, p < 0.001) and age group 0–49 years (r = − 0.542, p < 0.001) (Table 1). Family size correlated stronger with male cancers incidence than with female cancers in all ages group (n = 178). This difference was shown to be statistically significant by Fisher’s r-to-z transformation in both Pearson’s (z = 2.43, p = 0.015) and partial (z = 2.22, p = 0.026) correlations. 2) In developed world (n = 98), family size also remained in the significant correlation to all cancers incidence rates (both sexes) in all ages (r = − 0.625, p < 0.001) and the age group 0–49 years (r = − 0.658, p < 0.001), in males of all ages (r = − 0.470, p < 0.001) and age group 0–49 years (r = − 0.581, p < 0.001) and in females of all ages (r = − 0.362, p < 0.001) and the age group 0–49 years (r = − 0.534, p < 0.001) (Table 1). 3) In developing world (n = 80), family size remained in the significant correlation to all cancer incidence rates (both sexes) in the age group 0–49 years (r = − 0.430, p < 0.001) but not at all ages group, in females of age group 0–49 years (r = − 0.384, p < 0.001) but not at all ages and in males of all ages (r = − 0.303, p < 0.05) and the age group 0–49 years (r = − 0.430, p < 0.001) (Table 1).
Table 1 also shows that, globally (n = 178) and in developed world (n = 98), each of the incidence rates (all ages) of individual site cancers in bladder, breast, colorectum, corpus uteri, lung, skin (melanoma), ovary and stomach was in significant, negative and strong correlation to family size in both Pearson’s and partial correlation analyses (Table 1). Globally (n = 178), cervix uteri cancer correlated with family size significantly and positively in both Pearson’s r and non-parametric correlation, but the correlation was neither strong nor significant in partial correlation (Table 1). In developed world (n = 80), cervix uteri cancer did not show correlation (partial) or very weak correlation (Pearson’s r) with family size (Table 1) although it statistically significantly correlated with family size (r = 0.223, p < 0.05). In developing world (n = 80), only correlations between family size and lung cancer and cervix uteri cancer were consistent with those revealed globally and in developed world (Table 1).
The correlations, especially the partial correlations between family size and cancer variables in all countries (n = 178) and in developed world (n = 98) were stronger and more significant than those in developing world. Variances of cancer incidence variables in developing world (n = 80) were smaller than their counterparts in the developed world and all countries grouping (Additional file 5).
Table 2 shows that, globally (n = 178), the mean incidence rate of each cancer variable in country group (n = 95) with TFR ≥ 2.36 was significantly (p < 0.001) lower than that of country group (n = 83) with TFR < 2.36 except cervix uteri cancer. This trend remained in the developed country grouping (n = 98) except cervix uteri and stomach cancers, and in developing grouping (n = 80) except cancers in breast, cervix uteri, melanoma (skin) and ovary.
In the standard multiple linear (stepwise) regression analyses, family size was the significant predictor of the total, male and female cancer incidence rates (with exception of all female cancers at all ages) in samples of all ages and in age group 0–49 years respectively when family size, GDP, life expectancy (not for age group 0–49 years) and Ibs were entered as the independent variables/predictors (Table 3). Although family size is a significant predictor of the variable of all cancers in females at all ages, the value of its beta coefficient was smaller than for the variable of all cancers in males at all ages. This finding was consistent with those reported in Table 1 that family size was in significantly stronger negative association with all cancers in males at all ages than it was with all cancers in females at all ages in both Pearson’s (z = 2.43, p = 0.015) and partial (z = 2.22, p = 0.026) correlation analyses. This means that greater family size may have more protective effects on male cancer risk than on female (cancer risk.
Comparing with those correlations in all countries and in developed world, correlations between family size and cancer variables became weak and/or insignificant in the developing country grouping when standard deviation of cancer variable became low (Additional file 4: Table S2).
As the proxy of family size, household size was identified as the significant predictor of the total, male and female cancer incidence rates in samples of all ages and in age group 0–49 years respectively when household size, GDP, urbanisation, life expectancy (not for age group 0–49 years) and Ibs were entered as the independent variables/predictors in the standard multiple linear (stepwise) regression analysis (Additional file 5: Table S3).
Cancer risk has been associated with multiple aetiologies, which may act through various mechanisms. Our results showed that: 1) Worldwide, smaller family size may be an independent determinant of increased cancer risk. 2) increased family size may show more protecting effects on cancer risk in males than females.
It is necessary to note the limitations of our work before analysing the public health implications of this study:
First, the observational data were used in our work, which makes the results subject to inherent bias, i.e. “correlation between two variables does not mean causality”.
Second, we must highlight the ecological fallacy (intrinsic limitation) arising from the ecological study approach which was adopted in this study. The data included in this study were calculated for country/populations as a whole. Thus, values for risk-modifying factors do not always hold true for individuals to predict their cancer risk. However, we would like to note that it is nearly impossible to test the relationships at the individual family level due to rare occurrence rate of cancers, and even rarer in some individual site-specific cancers, such as ovarian cancer.
Finally, data compiled and/or collected by the major international agencies (WHO, IARC, the United Nations and the World Bank) might be crude, and may contain some random errors arising from methods of reporting incidence of specific diseases, reliability of diagnoses and possible administrative errors.
Despite these limitations, findings from different data analyses in this study consistently show that country with greater TFR (family size) has lower cancer incidence rate regardless of age range and sex. This relationship trend has been observed in the correlations between family size and not only the individual site cancers, but also all cancers (in males, females and both sexes). The broad correlations between family size and cancers expressed in different individual sites, sexes and groups, may not be simply explained by the female hormonal fluctuation due to pregnancy and breastfeeding.
The relationship between psychological well-being and diseases (body and mind) has been an old issue. In the past, research into well-being has mainly focused on negative attitudes and affects. The majority of the studies documented that negative life events (death, divorce, injury, car crash etc.,), stressful life style, depression and/or anxiety, may lead to developing cancers [32, 61]. However, there is a documented bias in the data collected from the individual based surveys. In general, cancer patients tend to report negative events in excess compared to other people with average or positive attitudes [28, 30, 31]. This has been reported or reflected in a number of studies [27,28,29,30] regarding the relationship between cancer risk and adverse life events. According to the ancient Chinese medicine textbook, which was compiled 2200 years ago, it has been believed that people have five internal organs of five gases (five emotions), i.e. happiness, anger, sadness, worry and fear. Among these five gases, only happiness makes the gas smooth , which keeps people healthy.
Family has long been cited as a health promoting factor [63, 64], and family size has been associated with life satisfaction [43, 44, 65]. From the perspective of evolution, humans have adapted early to cooperative breeding [66, 67], and then evolved alloparental care , and biological foundations of such human love may be heritable generation by generation . Our study has revealed that greater family size, and possibly its associated positive psychological well-being, may play a protective role against cancer initiation. The mechanisms may include following aspects:
Physiological and pathological functions of oxytocin in human health
Positive psychological well-being may make the functions of neuroendocrine and immune systems more efficient, which may reduce the risk of developing cancer [61, 70,71,72].
Oxytocin is a peptide hormone and neuropeptide. Its production is associated with good feelings and emotions . Males and females can produce and release similar quantities of oxytocin  within the hypothalamo-pituitary magnocellular systems. Researches constantly revealed that family related activities are the major promotors of oxytocin production. A stream of studies in the last decade reported that oxytocin release is not only associated with giving birth  and lactation , but also with daily interactions between family members, such as spouses [33,34,35], mother and children , and father and children . Oxytocin may be able to keep family happy and stable as it makes females and males stay monogamous [38, 39] and as it may bring positive psychological well-being to the family members. A self-reinforcing cycle is formed between family members interactions and oxytocin production.
Concurrently with the research into oxytocin production, physiological and pathological functions of oxytocin in humans have been the foci of numerous studies. Oxytocin has been postulated to have a role in inhibiting proliferation of human cancer cells, which may offer protective role in preventing cancer initiation . The inhibitory role of oxytocin has been tested in individual site specific cancers, such as human breast cancer [41, 77] and ovarian cancer (animal model) . A recent study reported that oxytocin, selectively activated by peptidylglycine α -amidating monooxygenase (PAM), may play a role in preventing and controlling a small cell lung cancer .
Bai et al.  reported that women with overall life satisfaction had less chance developing breast cancer. This may partly be true because life satisfaction may promote women to produce more oxytocin to prevent breast cancer cell initiation and proliferation. Another mechanism may be that greater TFR may make women produce less oestrogen and less menstrual cycles .
Less cancer genes/mutations accumulated in population with greater TFR/family size
Natural selection acts on each population [53, 79]. The total opportunity for natural selection in each population has been previously measured with the Biological State Index (Ibs) [49, 50, 53,54,55,56, 80]. An Ibs value of one indicates total adaptation of the population to their environment. An Ibs value of zero signifies a total lack of adaptation (inability to overcome natural selection pressures that are present), and an impossibility to give life to the next generation [49, 50, 53,54,55,56, 80].
Our study indicated that Biological State Index (Ibs) was in negative, strong and significant correlation to TFR/family size globally, in developed world and developing country groups respectively (Table 1). This means that population with greater TFR/family size is subject to more effective natural selection. As the consequence of less fitness, mortality rate due to various diseases, such as cancers, may increase [49, 50, 53,54,55,56, 79, 80]. Thus, cancer genes/mutations would be more often eliminated from a population with greater TFR/family size. Moreover, greater total fertility rates indicate less birth control therefore allowing more biological variation in fertility . A portion of this variation, however small, provides opportunity for natural selection .
Family support and healthy lifestyle
Family members from the greater family size may interact with each other more often to create life satisfaction [43, 44]. Meanwhile, one family member can remind and/or recommend other members to have necessary medical examination and have a healthy lifestyle .
Bai et al.  reported that people with positive psychological well-being may practice healthy lifestyle, have the knowledge of cancer risks and benefits of regular physical examination. It was reported that such positive psychological well-being may decrease the risk in the development of breast cancer [27, 32, 82].
In this study, we have also observed in Fisher’s analysis that family size was in significantly stronger correlation with all cancers incidence in males (all ages) than it was with all cancers incidence in females (all ages). This finding is supported by the studies which found that males psychologically benefited more from having an extended kinship network than females [42, 63, 64]. However, this finding is inconsistent with Feller’s finding that reduced life satisfaction was more related to the development of cancer in women than in men . The reason for this inconsistency might be that Feller’s data collection was based on the individual survey, which could be easily biased .
Family size has been implicated in the aetiologies of several individual site cancers, in previous studies based on the data collected at the individual level. Our findings were in agreement with the conclusions from the previous studies that greater family size was negatively correlated to the risks of developing bladder cancer , breast cancer [5, 6], colorectum cancer  and melanoma of skin. Although correlation does not necessarily imply causality, it may be suggested that increased family size may protect against the incidence of corpus uteri cancer and ovary cancer, but increase the risk of developing cervical cancer. These findings were in agreement with the prevailing dogma about the relationship between parity and gynecologic cancers, that is that more childbearing (greater TFR) may protect against corpus uteri cancer  and ovary cancer  due to less oestrogen production (less menstrual cycles) , but may contribute to cervix uteri cancer because of more exposure to infection risk . However, our results were not supported by the findings from the study conducted by Hemminki et al.  that there were no reportable significant correlations between family size and risks of cervix uteri cancer, corpus uteri cancer and ovarian cancer. A number of studies have reported that ageing is one of the major contributors of corpus uteri cancer  and ovary cancer . That findings of Hemminki et al.  were not compatible with our findings may be because only young females (aged mostly 5–43 years, up to 55 years) were included in their studies.
Poor hygiene level related infection with human papillomavirus is associated with cervical cancer initiation . In the developed world, like Sweden, high level of hygiene or sanitation is accessible to almost all the residents. This reduces risk for females to have human papilloma virus infection, which may decrease the cervical cancer risk. This may be the explanation why Hemminki et al.  did not find the correlation between family size and cervical cancer incidence.
Blaser et al.  have reported that greater family size increased the risk of developing stomach cancer only for male family members, but not for all family members or female family members . Aldrich et al.  reported that greater household size correlated with higher risk of lung cancer only in African Americans, but not in Latinos. However, sex specific or ancestry specific site cancer incidence was not included in our study. Thus, we may not be able to align our findings with the conclusions drawn by Blaser et al.  or Aldrich et al. .
The correlations, especially the partial correlations between family size and cancer variables in developing world were not as strong or significant as those identified in all countries (n = 178) and developed world (n = 98). This may be due to small variances (low standard deviations) of cancer incidence variables, which may reduce the covariance (correlation between family size and cancer variable), compared to those in the developed world and all countries grouping.
We must note an important strength of our study. Cancer risk studies based on surveys of individual persons have demonstrated a bias that is, in general, cancer patients tend to exaggerate negative life events in comparison to people with average or positive attitudes . The methods employed in this study may have excluded this major bias because: 1) we used the objective measurement (TFR), instead of individual subjective psychological feeling assuming that TFR may be the family happiness index; 2) ecological study at population/group level, rather than individual based research method was adopted in this study. Ecological studies are based on aggregated quantitative data, not on the interviews with individual patients, so they are often used to determine the presence of effect of cancer risk-modifying factors in advance of, or impossible to identify in other epidemiological or laboratory approaches. Therefore, ecological study may be a better method to conduct the study of cancer incidence and its potential predictors, as cancer is one of the relatively rare diseases.
Overall, this ecological study indicated that family size was negatively correlated with cancer incidence at population level. We also observed that family size correlated negatively with cancer incidence in males significantly stronger than with cancer incidence in females. Our results seem to suggest that it may be worthwhile further examining correlations between family size and cancer risk in males and females through the cohort and case-control studies based on large samples.
Gross Domestic Product
The International Agency for Research on Cancer of World Health Organization
Total fertility rate
World Health Organization
World Bank Open Data [http://data.worldbank.org].
United Nations-Department of Economic and Social Affairs-Population Division: World Population Prospects: The 2015 Revision, DVD Edition. In.; 2015.
Bevier M, Weires M, Thomsen H, Sundquist J, Hemminki K. Influence of family size and birth order on risk of cancer: a population-based study. BMC Cancer. 2011;11:163.
Australian Social Trends, 1996.
Hemminki K, Mutanen P. Birth order, family size, and the risk of cancer in young and middle-aged adults. Br J Cancer. 2001;84(11):1466–71.
Collaborative Group on Hormonal Factors in Breast Cancer. Breast cancer and breastfeeding: collaborative reanalysis of individual data from 47 epidemiological studies in 30 countries, including 50 302 women with breast cancer and 96 973 women without the disease. Lancet. 2002;360(9328):187–95.
You W, Symonds I, Rühli FJ, Henneberg M. Decreasing birth rate determining worldwide incidence and regional variation of female breast Cancer. Adv Breast Cancer Res. 2018;7(01):1.
Saso S, Chatterjee J, Georgiou E, Ditri AM, Smith JR, Ghaem-Maghami S. Endometrial cancer. BMJ. 2011;343:d3954.
Ovarian cancer risks and causes [http://www.cancerresearchuk.org].
WHO. Bulletin of the World Health Organization: the breast cancer conundrum: Bull World Health Organ; 2013. p. 626–7.
Imanieh MH, Bagheri F, Alizadeh AM, Ashkani-Esfahani S. Oxytocin has therapeutic effects on cancer, a hypothesis. Eur J Pharmacol. 2014;741:112–23.
Morita T, Shibata K, Kikkawa F, Kajiyama H, Ino K, Mizutani S. Oxytocin inhibits the progression of human ovarian carcinoma cells in vitro and in vivo. Int J Cancer. 2004;109(4):525–32.
Risk factors for cervical cancer [http://www.cancer.ca].
Blaser MJ, Nomura A, Lee J, Stemmerman GN, Perez-Perez GI. Early-life family structure and Microbially induced Cancer risk. PLoS Med. 2007;4(1):0053–8.
Aldrich MC, Selvin S, Wrensch MR, Sison JD, Hansen HM, Quesenberry CP, Seldin MF, Barcellos LF, Buffler PA, Wiencke JK. Socioeconomic status and lung cancer: unraveling the contribution of genetic admixture. Am J Public Health. 2013;103(10):e73.
Garssen B. Psychological factors and cancer development: evidence after 30 years of research. Clin Psychol Rev. 2004;24(3):315–38.
Levenson JL, Bemis C. The role of psychological factors in Cancer onset and progression. Psychosomatics. 1991;32(2):124–32.
Chen CC, David AS, Nunnerley H, Michell M, Dawson JL, Berry H, Dobbs J, Fahy T. Adverse life events and breast cancer: case-control study. BMJ. 1995;311(7019):1527.
Lillberg K, Verkasalo P, Kaprio J, Teppo L, Helenius H, Koskenvuo M. A prospective study of life satisfaction, neuroticism and breast cancer risk (Finland). Cancer Causes Control. 2002;13(2):191–8.
Eskelinen M, Ollonen P. Life stress and losses and deficit in adulthood as breast cancer risk factor: a prospective case-control. In Vivo. Nov-Dec. 2010;24(6):899–904.
Lillberg K. Stressful life events and risk of breast Cancer in 10,808 women: a cohort study. Am J Epidemiol. 2003;157(5):415–23.
Chorot P, Sandín B. Life events and stress reactivity as predictors of cancer, coronary heart disease and anxiety disorders. Int J Psychosom Res. 1994;41:34–40.
Ginsberg A, Price S, Ingram D, Nottage E. Life events and the risk of breast cancer: a case- control study. Eur J Cancer. 1996;32(12):2049–52.
Kune S, Kune GA, Watson LF, Rahe RH. Recent life change and large bowel cancer. Data from the Melbourne colorectal cancer study. J Clin Epidemiol. 1991;44(1):57–68.
Levav I, Kohn R, Iscovich J, Abramson JH, Tsai WY, Vigdorovich D. Cancer incidence and survival following bereavement. Am J Public Health. October;90(10):160–1607.
Everson SA, Goldberg DE, Kaplan GA, Cohen RD, Pukkala E, Tuomilehto J, Salonen JT. Hopelessness and risk of mortality and incidence of myocardial infarction and cancer. Psychosom Med. 1996;58(2):113.
Bai A, Li H, Huang Y, Liu X, Gao Y, Wang P, Dai H, Song F, Hao X, Chen K. A survey of overall life satisfaction and its association with breast diseases in Chinese women. Cancer medicine. 2016;5(1):111–9.
Courtney JG, Longnecker MP, Theorell T, Deverdier MG: Stressful life events and the risk of colorectal Cancer: results from a case-control study. Epidemiology 1993, 138(8):628–628.
Cohen LH, Towbes LC, Flocco R. Effects of induced mood on self- reported life events and perceived and received social support. J Pers Soc Psychol. 1988;55(4):669–74.
Brett JF, Brief AP, Burke MJ, George JM, Webster J. Negative affectivity and the reporting of stressful life events. Health Psychol. 1990;9(1):57–68.
Blaney PH. Affect and memory: a review. Psychol Bull. 1986;99(2):229–46.
Peled R, Carmil D, Siboni-Samocha O, Shoham-Vardi I. Breast cancer, psychological distress and life events among young women. BMC Cancer. 2008;8:245.
Carmichael MS, Humbert R, Dixen J, Palmisano G, Greenleaf W, Davidson JM. Plasma oxytocin increases in the human sexual response. J Clin Endocrinol Metab. 1987;64(1):27–31.
Carmichael MS, Warburton VL, Dixen J, Davidson JM. Relationships among cardiovascular, muscular, and oxytocin responses during human sexual activity. Arch Sex Behav. 1994;23(1):59–79.
Gordon G Jr, Burch RL, Platek SM. Does semen have antidepressant properties? Arch Sex Behav. 2002;31(3):289–93.
Kendrick KM. The neurobiology of social bonds. J Neuroendocrinol. 2004;16(12):1007–8.
Weisman O, Zagoory-Sharon O, Feldman R. Oxytocin administration to parent enhances infant physiological and behavioral readiness for social engagement. Biol Psychiatry. 2012;72(12):982–9.
Insel TR, Hulihan TJ. A gender-specific mechanism for pair bonding: oxytocin and partner preference formation in monogamous voles. Behav Neurosci. 1995;109(4):782.
Young LJ, Murphy Young AZ, Hammock EA. Anatomy and neurochemistry of the pair bond. J Comp Neurol. 2005;493(1):51–7.
Sapino A, Macri L, Tonda L, Bussolati G. Oxytocin enhances myoepithelial cell differentiation and proliferation in the mouse mammary gland. Endocrinology. 1993;133(2):838–42.
Cassoni P, Sapino A, Negro F, Bussolati G. Oxytocin inhibits proliferation of human breast cancer cell lines. Virchows Arch. 1994;425(5):467–72.
Aizer AA, Chen MH, McCarthy EP, Mendu ML, Koo S, Wilhite TJ, Graham PL, Choueiri TK, Hoffman KE, Martin NE, et al. Marital status and survival in patients with cancer. J Clin Oncol. 2013;31(31):3869–76.
Angeles L. Children and life satisfaction. J Happiness Stud. 2009;11(4):523–38.
Nan H, Ni MY, Lee PH, Tam WW, Lam TH, Leung GM, McDowell I. Psychometric evaluation of the Chinese version of the subjective happiness scale: evidence from the Hong Kong FAMILY cohort. Int J Behav Med. 2014;21(4):646–52.
GLOBOCAN 2012 v1.0, Cancer Incidence and Mortality Worldwide: IARC CancerBase No. 11 [Internet] [http://globocan.iarc.fr].
Ferlay J, Soerjomataram I, Dikshit R, Eser S, Mathers C, Rebelo M, Parkin DM, Forman D, Bray F. Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer. 2015;136(5):E359–86.
Abridged life table, for females, by major area, region and country, 1950–2100.
Demographic and Social Statistics [http://unstats.un.org].
Henneberg M. Reproductive possibilities and estimations of the biological dynamics of earlier human populations. J Hum Evol. 1976;5:41–8.
Henneberg M, Piontek J: Biological state index of human groups. Przeglad Anthropologiczny 1975, XLI:191–201.
World Fertility Data 2008 [http://www.un.org].
WHO. World health statistics, vol. 2012. Geneva: World Health Organization; 2012.
Stephan CN, Henneberg M. Medicine may be reducing the human capacity to survive. Med Hypotheses. 2001;57(5):633–7.
You W, Henneberg M. Cancer incidence increasing globally: the role of relaxed natural selection. Evol Appl. 2017;00:1–13.
Budnik A, Henneberg M. Worldwide increase of obesity is related to the reduced opportunity for natural selection. PLoS One. 2017;12(1).
You W-P, Henneberg M. Type 1 diabetes prevalence increasing globally and regionally: the role of natural selection and life expectancy at birth. BMJ Open Diabetes Res Care. 2016;4(1):e000161.
Allender S, Foster C, Hutchinson L, Arambepola C. Quantification of urbanization in relation to chronic diseases in developing countries: a systematic review. J Urban Health. 2008;85(6):938–51.
Greenberg M. Urbanization and Cancer: changing mortality patterns? Int Reg Sci Rev. 1983;8(2):127.
Majeed A, Babb P, Jones J, Quinn M. Trends in prostate cancer incidence, mortality and survival in England and Wales 1971–1998. BJU Int. 2000;85(9):1058–62.
United Nations DoEaSA, Population Division: World Population Prospects: The 2017 Revision, DVD Edition. In.
Williams RB, Schneiderman N. Resolved: psychosocial interventions can improve clinical outcomes in organic disease (pro). Psychosom Med. 2002;64:552–7.
Huangdi Qibo, Other ministers: Huangdi Neijing. Wuhan: Wuhan Publishing House; 2013.
Ploubidis GB, Silverwood RJ, DeStavola B, Grundy E. Life-course partnership status and biomarkers in midlife: evidence from the 1958 British birth cohort. Am J Public Health. 2015;105(8):1596–603.
Cable N, Bartley M, Chandola T, Sacker A. Friends are equally important to men and women, but family matters more for men's well-being. J Epidemiol Community Health. 2013;67(2):166–71.
Institute of Population and Labor Economy of Chinese Academy of Social Sciences. Chinese family happiness hot issues investigation report. 1st ed. Beijing: Xinhua Publishing House; 2015.
Clark G, Henneberg M. The life history of Ardipithecus ramidus: a heterochronic model of sexual and social maturation. Anthropol Rev. 2015;78(2).
K H, RR P. The Evolution of Human Life History. Santa Fe: School of American Research Press; 2006.
Isler K, van Schaik CP. Allomaternal care, life history and brain size evolution in mammals. J Hum Evol. 2012;63(1):52–63.
Henneberg M, Saniotis A: The dynamic human, Sharjah Bentham science publishers ltd.; 2016.
Antonova L, Mueller CR. Hydrocortisone down-regulates the tumor suppressor gene BRCA1 in mammary cells: a possible molecular link between stress and breast cancer. Genes Chromosomes Cancer. 2008;47(4):341–52.
Cohen S, Rodriguez MS. Pathways linking affective disturbances and physical disorders. Health Psychol. 1995;14(5):374–80.
Diener E, Chan MY. Happy people live longer: subjective well-being contributes to health and longevity. Applied Psychology: Health and Well-Being. 2011;3(1):1–43.
Magon N, Kalra S. The orgasmic history of oxytocin: love, lust, and labor. Indian J Endocrinol Metabol. 2011;15(Suppl3):S156.
Ivell R, Balvers M, Rust W, Bathgate R, Einspanier A. Oxytocin and male reproductive function. Adv Exp Med Biol. 1997;424:253–264.
Takayanagi Y, Yoshida M, Bielsky IF, Ross HE, Kawamata M, Onaka T, Yanagisawa T, Kimura T, Matzuk MM, Young LJ. Pervasive social deficits, but normal parturition, in oxytocin receptor-deficient mice. Proc Natl Acad Sci U S A. 2005;102(44):16096–101.
White-Traut R, Watanabe K, Pournajafi-Nazarloo H, Schwertz D, Bell A, Carter CS. Detection of salivary oxytocin levels in lactating women. Dev Psychobiol. 2009;51(4):367–73.
Murrell TG. The potential for oxytocin ( OT) to prevent breast cancer: a hypothesis. Breast Cancer Res Treat. 1995;35(2):225.
Cao F, Gamble AB, H-k K, Onagi H, Gresser MJ, Kerr J, Easton CJ. Potent and selective inhibitors of human peptidylglycine - amidating monooxygenase. Med Chem Commun. 2011;2(8):760–3.
Darwin C: The descent of man, and selection in relation to sex, New edn. London: John Murray; 1901.
Rühli F, Henneberg M. Biological future of humankind – ongoing evolution and the impact of recognition of human biological variation. In: Tibayrenc M, Ayala FJ, editors. On human nature Biology, Psychology, Ethics, Politics, and Religion 2016. New York: Elsevier Science; 2016. p. 263–75.
Henneberg M. Natural selection through differential fertility in human populations: quantitative evaluation of selection intensity. Przeglad Antropologiczny. 1980;46:21–60.
Kim Y, Duhamel KN, Valdimarsdottir HB, Bovbjerg DH. Psychological distress among healthy women with family histories of breast cancer: effects of recent life events. Psycho-Oncology. 2005;14(7):555–63.
Feller S, Teucher B, Kaaks R, Boeing H, Vigl M. Life satisfaction and risk of chronic diseases in the European prospective investigation into cancer and nutrition (EPIC)-Germany study. PLoS One. 2013;8(8):e73462.
Purdie DM, Green AC. Epidemiology of endometrial cancer. Best Pract Res Clin Obstet Gynaecol. 2001;15(3):341–54.
Snijders PJ, Steenbergen RD, Heideman DA, Meijer CJ. HPV-mediated cervical carcinogenesis: concepts and clinical implications. J Pathol. 2006;208(2):152–64.
The authors express appreciation to Jacques Ferlay from the International Agency for Research on Cancer of World Health Organization for the assistance in locating and defining the data.
This research was supported by the Mäxi Foundation, Zurich, Switzerland.
Availability of data and materials
All data for this study are publicly available and are ready for the public to download at no cost from the official websites of the World Bank, IARC and the WHO. Use of these data for this research falls within these UN agency’s public permission in their terms and conditions. There is no need to have the formal permission to use data for this study. The sources and data robustness have been described in the section of “Methods”.
Ethics approval and consent to participate
All the data supporting our findings in this paper were freely downloaded from the UN agencies’ websites. No ethical approval or written informed consent for participation was required.
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The authors declare that they have no competing interests.
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Additional file 1:
The whole set of data for this study. (XLSX 47 kb)
Additional file 2:
SD Fig. 1. The relationship between household size and all cancers incidence rates (total, male and female, all ages). (TIF 737 kb)
Additional file 3:
Table S1. Pearson, Nonparametric and partial correlation between household size and each cancer variable and confounder. (DOCX 24 kb)
Additional file 4:
Table S2. Stepwise multiple linear regression to identify the significant predictors of cancer incidence risk. (DOCX 21 kb)
Additional file 5:
Table S3. Data descriptive and summary. (XLSX 16 kb)
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You, W., Rühli, F.J., Henneberg, R.J. et al. Greater family size is associated with less cancer risk: an ecological analysis of 178 countries. BMC Cancer 18, 924 (2018). https://doi.org/10.1186/s12885-018-4837-0
- Total fertility rate
- Household size
- Psychological well-being
- Family life
- Cancer initiation