Abstract
Background:
Prospective evidence on how offspring number influences morbidity and mortality remains limited. This study investigated the associations between number of offspring and morbidity and mortality risks among 0.5 million Chinese adults.
Methods:
By using data from the China Kadoorie Biobank (CKB; n = 512,723, an approximately 12-year follow-up), sex-stratified phenome-wide association study (PheWAS) analyses were conducted to investigate associations between offspring number (without vs. with offspring; more than one vs. one offspring) and risks of ICD10-coded morbidity and mortality. Sex-specific adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) were estimated by Cox proportional-hazards models.
Results:
Among 210,129 men and 302,284 women aged 30–79 years, 1,338,837 incident events were recorded. PheWAS results revealed that offspring number was associated with disease risks across multiple systems. Cox models showed that childless men (vs. one offspring) had higher risks for nine of 36 diseases, while childless women for five of 37. Each additional offspring was associated with reduced risks of mental and behavioral disorders in men (aHR [95% CI] = 0.93 [0.87–0.98]) and both mental and behavioral disorders (aHR [95% CI] = 0.93 [0.89–0.97]) and breast cancer (aHR [95% CI] = 0.82 [0.78–0.86]) in women. However, each additional offspring was associated with a 4% increase in the risk of cholelithiasis and cholecystitis in women (aHR [95% CI] = 1.04 [1.02–1.07]). Among 282,630 patients, 44,533 deaths were documented. Childless patients had higher mortality risk in both men (aHR [95% CI] = 1.37 [1.28–1.47]) and women (aHR [95% CI] = 1.27 [1.15–1.41]). For men, each additional offspring reduced mortality by 4% (aHR [95% CI] = 0.96 [0.95–0.98]), while for women, the lowest risk was observed among those with three to four offspring (Pnonlinear <0.0001).
Conclusions:
Offspring number is closely linked to morbidity and mortality risks. Further research is warranted to verify our findings and clarify the underlying mechanisms involved.
Keywords: Offspring, Phenome-wide, Morbidity risk, Mortality risk
Introduction
Increasing evidence suggested that parenthood or fertility was associated with health outcomes.[1–4] However, previous research on the health implications of the number of offspring mainly focused on women and narrow health outcomes, resulting in inconsistent findings. This is due to various factors, including inconsistent definitions, inadequate adjustments for confounding factors, and short follow-up periods. There remains uncertainty regarding the impact of the number of offspring on various health conditions, particularly within Asian populations.
In this study, we aimed to establish sex-specific disease association maps between the number of offspring and morbidity risks and over 500 diseases in men and women, respectively, based on 0.5 million Chinese adults enrolled in the China Kadoorie Biobank (CKB).[9] Furthermore, we aimed to assess associations between number of offspring and phenome-wide significant diseases and the top 10 sex-specific causes of death in the Chinese population,[10] and further explore mortality risks associated with number of offspring among patients with major chronic disorders or diseases at baseline.
Methods
Ethics approval
Ethics approvals were obtained from the Ethical Review Committee of the Chinese Center for Disease Control and Prevention (No. 005/2004) and the Oxford Tropical Research Ethics Committee, University of Oxford (No. OXTREC 025-04). All participants signed an informed consent form.
Study population
The CKB is a large prospective, population-based cohort study.[5] The study was conducted across ten regional centers coordinated by a central project management team based in Beijing and Oxford. Oversight was provided by an independent Steering Committee, and scientific input was managed by a Collaborative Group. The members of the steering committee and collaborative group are listed in the Supplementary Materials, http://links.lww.com/CM9/C606. Briefly, a total of 512,723 adults aged 30–79 years were recruited from five rural and five urban areas during 2004–2008. Electronic questionnaires (including information on the number of offspring and women’s reproductive factors) and physical measurements were collected by trained staff. Approximately 95% of the study participants were covered by medical insurance.[7]
Based on 512,723 participants enrolled in CKB[5], we excluded those with missing data of body mass index (BMI) (n = 2) and those with abnormal information (n = 308). The latter group comprised 39 men and 45 women who self-reported implausibly high numbers of offspring, pregnancies, or live births (up to 20), 35 men who reported a history of pregnancy, and 189 women reported having no pregnancies and no live births yet claimed to have one or more biological offspring. Finally, 512,413 participants were included in the relevant analysis. Supplementary Figure 1, http://links.lww.com/CM9/C606 shows a flowchart detailing the inclusion process of study participants.
Ascertainment of the number of offspring and other covariates
In this study, the number of offspring ascertained through face-to-face interviews during the baseline survey served as the primary variable for analysis in both men and women. The term “offspring” was used throughout the text to refer to “biological offspring” in this study. The group having one offspring was designated as a reference group in the principal analysis of the number of offspring and morbidity risks. Detailed reproductive history information collected for women (pregnancy, live birth, stillbirth, number of miscarriages, etc.) was used in sensitivity analyses.
Ascertainment of outcomes
The incident disease and death events during follow-up were ascertained through the data linkage of local official death and disease registries and with the national health insurance databases until December 31, 2018. Causes of death were primarily obtained from official death certificates and, when necessary, supplemented by reviews of medical records. Data linkage with health insurance agencies was conducted every six months in each region, and all hospitalization events from the previous half-year were retrieved for matched study participants.[5] The primary outcomes examined in this study were coded following the International Classification of Diseases, Tenth Revision (ICD-10) [Supplementary Table 1, http://links.lww.com/CM9/C606].
In the preliminary exploration of the spectrum of diseases based on phenome-wide association study (PheWAS) analyses, self-reported diseases at baseline (also coded with ICD-10) and newly identified diseases during follow-up were used to define participants who had developed any disease as of December 31, 2018. We used a tool for PheWAS in the R environment, known as R PheWAS,[8] to convert unique 6934 ICD-10 codes to PheWAS cases and control groups. A total of 1747 and 1805 hierarchical PheWAS codes (PheCodes) formed from grouped ICD-10 codes for men and women, respectively. After excluding diseases with fewer than 30 cases to ensure adequate statistical power, 568 diseases for men and 654 diseases for women were retained for analysis. The subsequent prospective analysis only included 38 diseases, and the corresponding ICD-10 codes are shown in Supplementary Table 1, http://links.lww.com/CM9/C606. The determination of disease categories in subsequent prospective analysis adhered to two principles: (1) Diseases were included if their association with the number of offspring (without vs. with offspring; more than one vs. one offspring) achieved statistical significance following adjustment for all covariates in the PheWAS analysis, with the parent categories retained in cases where hierarchical relationships existed. (2) Alternatively, diseases were included if they were among the sex-specific top-10 death causes reported in the 2019 China Health Statistical Yearbook.[6]
Statistical analysis
The baseline characteristics of all participants stratified by the number of offspring were represented as mean ± standard deviation for normally distributed continuous variables, median (interquartile range [Q1–Q3]) for non-normally distributed continuous variables, or n (%) for categorical variables. Unconditional logistic regression was used for sex-specific PheWAS analysis to investigate the relationship between the number of offspring and morbidity risks first. Three models were stepwise adjusted: Model 1 was adjusted for age (groups of 30–34 years, 35–39 years, 40–44 years, 45–49 years, 50–54 years, 55–59 years, 60–64 years, 65–69 years, 70–74 years, and 75–79 years), study area (10 region groups, including Qingdao, Harbin, Haikou, Suzhou, Liuzhou, Chengdu, Tianshui, Xinxiang, Jiaxing, and Changsha), marital status, highest education level, household income, and household size; Model 2 was further adjusted for alcohol drinking, smoking, dietary habits, physical activity, and BMI; and Model 3 was additionally adjusted for the history of diabetes, hypertension, respiratory disease, cardiovascular disease (CVD), and cancer at baseline; family history of the analyzed disease (adjusted only in relevant analyses); self-reported satisfaction level of life; and menopausal status (for women only) [detailed in Supplementary Table 2, http://links.lww.com/CM9/C606].
Cox proportional hazards regression models, with age as the time scale, were used to evaluate the relationship between the number of offspring and the risk of developing 38 specific diseases among participants without the related diseases at baseline, as well as the mortality risks among patients with self-reported diseases. Kaplan–Meier survival curves were utilized among patients with any of the 26 chronic diseases at baseline to explore the association between mortality risks related to the number of offspring. The Cox models were stratified by age at risk (five-year bands) and study areas (10 region groups) and adjusted for other covariates as per the PheWAS analysis, yielding estimates of adjusted hazard ratios (aHRs) along with 95% confidence intervals (CIs). Person-years were calculated from the enrollment date until the onset of the outcome of interest, death, loss to follow-up, or December 31, 2018, whichever came first. Furthermore, we used restricted cubic splines to fit the association between the number of offspring and mortality risks separately for men and women. Sensitivity analyses included the following: (1) further adjustment for additional variables (for men: passive smoking and food shortages, based on Model 3; for women: passive smoking, food shortages, oral contraceptives, stillbirth, spontaneous abortion, induced abortion, and age at last delivery, based on Model 3); (2) exclusion of participants followed for two years or less; (3) stratification by birth cohort; and (4) stratification by region areas (urban or rural). Likelihood ratio tests were performed to examine the interaction between gender and number of offspring on morbidity or mortality risks by comparing models with and without cross-product interaction terms. The proportional hazards assumption was tested through Schoenfeld residual plots, and no violations were visually detected.
All analyses were conducted using R (version 4.1.1, R Foundation for Statistical Computing, Vienna, Austria). R-package PheWAS[8] was used for PheWAS analysis, with Bonferroni-corrected P-values utilized in relevant analyses (0.05 divided by the number of diseases in the corresponding group). The significance level for Cox proportional hazards regression was set at a two-sided P <0.05.
Results
Basic characteristics of participants
This study included 210,129 men and 302,284 women; 97.1% (203,971/210,129) of men and 98.6% (298,143/302,284) of women had at least one offspring at baseline. Among those having offspring, 38.2% (77,820/203,971) of men and 35.4% (105,590/298,143) of women had one offspring. Participants with one offspring tended to be younger, had higher incomes, had more physical activity, and were more likely to have healthy dietary habits [Table 1].
Table 1.
Basic characteristics of the participants by number of offspring.
| Items | Men | Women | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | ≥4 | 0 | 1 | 2 | 3 | ≥4 | |
| Number (%) | 6158 (2.9) | 77,820 (37.0) | 66,987 (31.9) | 35,908 (17.1) | 23,256 (11.1) | 4141 (1.4) | 105,590 (34.9) | 99,310 (32.9) | 54,311 (18.0) | 38,932 (12.9) |
| Age (years) | 50.0 ± 12.1 | 46.5 ± 7.8 | 52.6 ± 9.7 | 59.4 ± 9.3 | 65.4 ± 7.9 | 50.2 ± 11.9 | 45.2 ± 7.0 | 50.2 ± 9.0 | 57.1 ± 9.3 | 64.0 ± 8.3 |
| Urban | 2328 (37.8) | 50,323 (64.7) | 20,930 (31.2) | 11,011 (30.7) | 6736 (29.0) | 2635 (63.6) | 68,786 (65.1) | 32,108 (32.3) | 17,899 (33.0) | 13,292 (34.1) |
| Without a spouse* | 3767 (61.2) | 3571 (4.6) | 2689 (4.0) | 2241 (6.2) | 2632 (11.3) | 1269 (30.6) | 6869 (6.5) | 6998 (7.0) | 7758 (14.3) | 10,428 (26.8) |
| Highest education | ||||||||||
| Primary school and lower | 3410 (55.4) | 19,176 (24.6) | 30,574 (45.6) | 19,728 (54.9) | 15,854 (68.2) | 1654 (39.9) | 32,809 (31.1) | 60,586 (61.0) | 41,617 (76.6) | 34,784 (89.3) |
| Middle or high school | 2101 (34.1) | 48,661 (62.5) | 32,741 (48.9) | 14,579 (40.6) | 6774 (29.1) | 1861 (44.9) | 62,747 (59.4) | 36,721 (37.0) | 12,074 (22.2) | 4000 (10.3) |
| College and higher | 647 (10.5) | 9,983 (12.8) | 3672 (5.5) | 1601 (4.5) | 628 (2.7) | 626 (15.1) | 10,034 (9.5) | 2003 (2.0) | 620 (1.1) | 148 (0.4) |
| Household income (CNY/year) | ||||||||||
| <10,000 | 3155 (51.2) | 12,124 (15.6) | 16,036 (23.9) | 12,301 (34.3) | 11,085 (47.7) | 1315 (31.8) | 20,221 (19.2) | 27,331 (27.5) | 20,911 (38.5) | 20,156 (51.8) |
| 10,000–20,000 | 1356 (22.0) | 19,694 (25.3) | 20,030 (29.9) | 11,499 (32.0) | 6945 (29.9) | 1299 (31.4) | 29,529 (28.0) | 30,585 (30.8) | 17,000 (31.3) | 10,925 (28.1) |
| ≥20,000 | 1647 (26.7) | 46,002 (59.1) | 30,921 (46.2) | 12,108 (33.7) | 5226 (22.5) | 1527 (36.9) | 55,840 (52.9) | 41,394 (41.7) | 16,400 (30.2) | 7851 (20.2) |
| Household size† | ||||||||||
| 1 | 1909 (31.0) | 1049 (1.3) | 735 (1.1) | 721 (2.0) | 864 (3.7) | 516 (12.5) | 1470 (1.4) | 1610 (1.6) | 2306 (4.2) | 3364 (8.6) |
| 2 | 1730 (28.1) | 7612 (9.8) | 10,279 (15.3) | 9648 (26.9) | 8075 (34.7) | 1316 (31.8) | 12,788 (12.1) | 13,982 (14.1) | 12,719 (23.4) | 11,171 (28.7) |
| 3–5 | 2116 (34.4) | 67,114 (86.2) | 45,045 (67.2) | 18,149 (50.5) | 8728 (37.5) | 1973 (47.6) | 88,875 (84.2) | 68,444 (68.9) | 29,022 (53.4) | 16,229 (41.7) |
| ≥6 | 403 (6.5) | 2045 (2.6) | 10,928 (16.3) | 7390 (20.6) | 5589 (24.0) | 336 (8.1) | 2457 (2.3) | 15,274 (15.4) | 10,264 (18.9) | 8168 (21.0) |
| Smoking | ||||||||||
| Non-smoker | 1934 (31.4) | 20,416 (26.2) | 16,623 (24.8) | 8857 (24.7) | 6037 (26.0) | 3949 (95.4) | 103,395 (97.9) | 97,053 (97.7) | 52,001 (95.7) | 36,107 (92.7) |
| Former smoker | 257 (4.2) | 4597 (5.9) | 4647 (6.9) | 2766 (7.7) | 1808 (7.8) | 16 (0.4) | 182 (0.2) | 252 (0.3) | 355 (0.7) | 395 (1.0) |
| Current smoker (cigarette or equivalent per day) | ||||||||||
| 1–9 | 883 (14.3) | 7512 (9.7) | 7459 (11.1) | 5159 (14.4) | 4362 (18.8) | 95 (2.3) | 1061 (1.0) | 1076 (1.1) | 1080 (2.0) | 1378 (3.5) |
| 10–19 | 1017 (16.5) | 14,953 (19.2) | 11,262 (16.8) | 6463 (18.0) | 4334 (18.6) | 54 (1.3) | 585 (0.6) | 564 (0.6) | 578 (1.1) | 682 (1.8) |
| ≥20 | 2067 (33.6) | 30,342 (39.0) | 26,996 (40.3) | 12,663 (35.3) | 6715 (28.9) | 27 (0.7) | 367 (0.3) | 365 (0.4) | 297 (0.5) | 370 (1.0) |
| Alcohol consumption | ||||||||||
| Not daily | 4772 (77.5) | 53,573 (68.8) | 47,735 (71.3) | 25,604 (71.3) | 16,780 (72.2) | 4042 (97.6) | 103,925 (98.4) | 97,809 (98.5) | 53,178 (97.9) | 37,857 (97.2) |
| Daily (pure alcohol per day) | ||||||||||
| 1–14 g/day | 27 (0.4) | 481 (0.6) | 553 (0.8) | 419 (1.2) | 335 (1.4) | 19 (0.5) | 238 (0.2) | 205 (0.2) | 193 (0.4) | 151 (0.4) |
| 15–29 g/day | 136 (2.2) | 3275 (4.2) | 2360 (3.5) | 1382 (3.8) | 895 (3.8) | 14 (0.3) | 305 (0.3) | 262 (0.3) | 179 (0.3) | 193 (0.5) |
| 30–59 g/day | 306 (5.0) | 6348 (8.2) | 4313 (6.4) | 2182 (6.1) | 1230 (5.3) | 9 (0.2) | 242 (0.2) | 203 (0.2) | 125 (0.2) | 112 (0.3) |
| Excessive-drinker or ≥60 g/day | 917 (14.9) | 14,143 (18.2) | 12,026 (18.0) | 6321 (17.6) | 4.016 (17.3) | 57 (1.4) | 880 (0.8) | 831 (0.8) | 636 (1.2) | 619 (1.6) |
| Physical activity (MET-h/day) | 18.0 (10.7–30.7) | 22.8 (13.9–34.2) | 20.0 (9.7–35.5) | 14.6 (7.0–28.1) | 10.5 (5.6–21.3) | 14.7 (8.9–24.3) | 19.9 (12.5–31.2) | 17.3 (11.2–29.5) | 14.3 (9.8–25.2) | 11.2 (8.4–18.6) |
| BMI (kg/m2) | 22.5 ± 3.4 | 24.0 ± 3.2 | 23.3 ± 3.2 | 23.0 ± 3.2 | 22.7 ± 3.3 | 23.4 ± 3.7 | 23.8 ± 3.3 | 23.9 ± 3.4 | 23.9 ± 3.6 | 23.7 ± 3.8 |
| Healthy dietary habit‡ | 308 (5.0) | 6,991 (9.0) | 4374 (6.5) | 2018 (5.6) | 1080 (4.6) | 487 (11.8) | 14,665 (13.9) | 7321 (7.4) | 3291 (6.1) | 1750 (4.5) |
| Life satisfaction | ||||||||||
| Very satisfied | 675 (11.0) | 9564 (12.3) | 12,365 (18.5) | 8279 (23.1) | 5922 (25.5) | 474 (11.4) | 13,264 (12.6) | 18,968 (19.1) | 11,697 (21.5) | 8624 (22.2) |
| Satisfied | 2552 (41.4) | 41,648 (53.5) | 34,925 (52.1) | 18,598 (51.8) | 11,924 (51.3) | 1958 (47.3) | 54,351 (51.5) | 49,387 (49.7) | 27,062 (49.8) | 18,955 (48.7) |
| Neither satisfied nor dissatisfied | 2308 (37.5) | 21,671 (27.8) | 17,288 (25.8) | 8144 (22.7) | 4933 (21.2) | 1373 (33.2) | 32,461 (30.7) | 27,540 (27.7) | 13,907 (25.6) | 10,275 (26.4) |
| Dissatisfied | 560 (9.1) | 4668 (6.0) | 2278 (3.4) | 832 (2.3) | 447 (1.9) | 312 (7.5) | 5235 (5.0) | 3206 (3.2) | 1516 (2.8) | 991 (2.5) |
| Very dissatisfied | 63 (1.0) | 269 (0.3) | 131 (0.2) | 55 (0.2) | 30 (0.1) | 24 (0.6) | 279 (0.3) | 209 (0.2) | 129 (0.2) | 87 (0.2) |
| Prevalent diseases at baseline | ||||||||||
| Type 2 diabetes | 256 (4.2) | 4047 (5.2) | 3496 (5.2) | 2309 (6.4) | 1570 (6.8) | 235 (5.7) | 4016 (3.8) | 5768 (5.8) | 4500 (8.3) | 4080 (10.5) |
| Hypertension | 2141 (34.8) | 23,504 (30.2) | 24,892 (37.2) | 16,225 (45.2) | 12,038 (51.8) | 1276 (30.8) | 21,411 (20.3) | 32,903 (33.1) | 24,617 (45.3) | 21,460 (55.1) |
| Respiratory disease§ | 787 (12.8) | 5444 (7.0) | 6704 (10.0) | 5161 (14.4) | 4373 (18.8) | 410 (9.9) | 6268 (5.9) | 6246 (6.3) | 4720 (8.7) | 4857 (12.5) |
| CVD | 188 (3.1) | 1860 (2.4) | 3077 (4.6) | 2656 (7.4) | 2284 (9.8) | 182 (4.4) | 2181 (2.1) | 3788 (3.8) | 3572 (6.6) | 3325 (8.5) |
| Cancer | 15 (0.2) | 217 (0.3) | 300 (0.4) | 239 (0.7) | 196 (0.8) | 38 (0.9) | 474 (0.4) | 475 (0.5) | 341 (0.6) | 280 (0.7) |
| Postmenopause | – | – | – | – | – | 2088 (50.4) | 27,970 (26.5) | 51,385 (51.7) | 41,527 (76.5) | 35,853 (92.1) |
| Born in or after 1955 | 3487 (56.6) | 57,808 (74.3) | 29,407 (43.9) | 7610 (21.2) | 1606 (6.9) | 2358 (56.9) | 85,897 (81.3) | 51,825 (52.2) | 14,556 (26.8) | 3595 (9.2) |
Data are expressed as n (%), mean ± standard deviation, or interquartile range (Q1–Q3). *Participants without a spouse include those who were separated/divorced, widowed, or never married. †Household size refers to the number of individuals who have long-term cohabitation and shared meals in the same household. ‡The dietary habit was scored based on the self-reported eating habits of participants, including eating fresh fruit daily, fresh vegetables daily, red meat one to six days per week, fish at least one day per week, and legumes at least four days per week. Each healthy or unhealthy habit is given a score of one or zero, respectively, and those with a diet score of four or five were classified into the “healthy diet” group. §Respiratory disease includes COPD/emphysema/pulmonary heart disease, tuberculosis, and asthma. BMI: Body-mass index; COPD: Chronic obstructive pulmonary disease; CVD: Cardiovascular disease; MET: Metabolic equivalent of task; –: Not available.
PheWAS of the number of offspring
Without vs. with offspring
In this study, we first divided the total participants into two groups based on the number of offspring (without vs. with offspring) for the sex-stratified PheWAS analysis. Figure 1 illustrates the disease landscapes, taking into account socio-demographic characteristics, lifestyle behaviors, anthropometric measures, individual and family history of diseases, self-reported satisfaction level of life, and menopausal status, while Supplementary Figures 2 and 3, http://links.lww.com/CM9/C606 display plots for Models 1 and 2. The PheWAS plot depicted 556 and 644 health outcomes mapped for men and women, respectively. After Bonferroni correction, two associations in men reached PheWAS significance (P <8.99 × 10−5), specifically related to schizophrenia, as well as schizophrenia and other psychotic disorders. For women, four associations were found after adjusting for all covariates (P <7.76 × 10−5). Irrespective of gender, the strongest association observed was with schizophrenia (odds ratio [OR] = 2.31, 95% CI = 1.95–2.67 for men; OR = 2.19, 95% CI = 1.89–2.49 for women) in the final model (without vs. with offspring).
Figure 1.
PheWAS plot of diseases related to the number of offspring among Chinese men and women. The X-axis denotes the categorical group of diseases, and the Y-axis represents the negative log (10) of the phenome-wide P-value. Purple and red lines indicate the thresholds for significance levels of 0.05 and phenome-wide significance, respectively. Upward and downward triangles indicate OR ≥1 and OR <1, respectively. The models were adjusted for age, study area, marital status, highest education, household income, and household size, alcohol drinking, smoking, dietary habits, physical activity, BMI, the history of diabetes, hypertension, respiratory disease, cardiovascular disease (CVD) or cancer at baseline, family history of the analyzed disease (adjusted only in relevant analyses), self-reported satisfaction level of life, and menopausal status (for women only). (A) PheWAS plot for men without vs. with offspring. (B) PheWAS plot for women without vs. with offspring. (C) PheWAS plot for men with more than one vs. with one offspring. (D) PheWAS plot for women with more than one vs. one offspring. BMI: Body mass index; CVD: Cardiovascular disease; OR: Odds ratio; PheWAS: Phenome-wide association study.
More than one vs. one offspring
We subsequently performed sex-specific PheWAS analyses among participants who reported having offspring (more than one vs. one) [Figure 1]. In the PheWAS plot with adjustment for all covariates, 549 and 643 health outcomes were mapped for men and women, respectively, with 16 associations for men (P <9.11 × 10−5) and 17 associations for women (P <7.78 × 10−5). Irrespective of gender, the identified associations were predominantly within the circulatory system. Cerebral ischemia (OR = 1.30, 95% CI = 1.24–1.36) in men and cerebrovascular disease (OR = 1.17, 95% CI = 1.13–1.20) in women exhibited the strongest association, respectively (more than one vs. one offspring).
Number of offspring and morbidity risks of 38 disease categories
In the association analyses of 38 disease categories, the median follow-up time ranged from 11.64 years (Q1–Q3: 10.53–12.80 years; 5.27 million person-years) to 12.12 years (Q1–Q3: 11.16–13.09 years; 3.90 million person-years). A total of 1,338,837 health events were recorded, among which, there were 4924 experiencing mental and behavioral disorders, 118,504 CVDs, and 32,565 cancers [Supplementary Table 3, http://links.lww.com/CM9/C606].
Table 2 shows the association between the number of offspring and major systemic diseases in men and women after adjusting for all disease-specific covariates in the final model. In comparison to men with one offspring, men without offspring demonstrated an increased risk of developing nine of the 36 diseases analyzed (excluding breast cancer and polyp of female genital organs), and primarily, these risks were observed in mental and behavioral disorders, CVD, and respiratory diseases. Compared to men with one offspring, those without offspring had the highest risk increase of dementia (aHR [95% CI] = 2.70 [1.57–4.65]). In contrast, men with two or three offspring may have a reduced risk of schizophrenia and other psychotic disorders (two offspring: aHR [95% CI] = 0.65 [0.45–0.94]; three offspring: aHR [95% CI] = 0.56 [0.33–0.95]). Additionally, each additional offspring was associated with a reduced risk of mental and behavioral disorders (aHR [95% CI] = 0.93 [0.87–0.98]) and of schizophrenia and other psychotic disorders (aHR [95% CI] = 0.77 [0.65–0.91]) in men. For men with more than one offspring, lower risks were also found in intracerebral hemorrhage of participants with three offspring (aHR [95% CI] = 0.86 [0.77–0.96]) and ≥four offspring (aHR [95% CI] = 0.89 [0.80–0.99]), and ischemic heart disease of participants with two offspring (aHR [95% CI] = 0.93 [0.89–0.98]) and three offspring (aHR [95% CI] = 0.93 [0.88–0.99]). In addition, compared to men with one offspring, we observed increased risks of respiratory diseases in certain groups. Men with four or more offspring had an increased risk of chronic obstructive pulmonary disease (COPD, four offspring: aHR [95% CI] = 1.13 [1.02–1.26]). Men without offspring had higher risks of COPD (aHR [95% CI] = 1.56 [1.34–1.81]), chronic airway obstruction (aHR [95% CI] = 1.38 [1.08–1.77]), and bronchitis (aHR [95% CI] = 1.43 [1.24–1.65]).
Table 2.
Association between the number of offspring and morbidity risks among men and women.
| Diseases | Number of offspring in men | Number of offspring in women | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | ≥4 | Each additional offspring | 0 | 1 | 2 | 3 | ≥4 | Each additional offspring | |
| Mental and behavioral disorders | 1.56* (1.20–2.03) | 1.00 | 0.98 (0.84–1.15) | 0.88 (0.72–1.08) | 0.87 (0.68–1.10) | 0.93* (0.87–0.98) | 1.34* (1.06–1.69) | 1.00 | 0.98 (0.87–1.09) | 0.89 (0.77–1.03) | 0.79* (0.66–0.94) | 0.93* (0.89–0.97) |
| Schizophrenia and other psychotic disorders | 1.39 (0.81–2.39) | 1.00 | 0.65* (0.45–0.94) | 0.56* (0.33–0.95) | 0.51 (0.24–1.10) | 0.77* (0.65–0.91) | 2.82* (1.75–4.53) | 1.00 | 0.98 (0.73–1.32) | 0.63* (0.41–0.97) | 0.61 (0.35–1.06) | 0.77* (0.67–0.89) |
| Dementia | 2.70* (1.57–4.65) | 1.00 | 0.86 (0.56–1.31) | 0.86 (0.56–1.34) | 0.87 (0.55–1.37) | 0.88* (0.81–0.97) | 0.96 (0.43–2.17) | 1.00 | 0.83 (0.52–1.31) | 0.70 (0.44–1.12) | 0.63 (0.30–1.01) | 0.92 (0.84–1.00) |
| CVD | 1.10* (1.03–1.16) | 1.00 | 0.98 (0.95–1.01) | 0.97 (0.94–1.01) | 0.99 (0.95–1.03) | 0.99* (0.98–1.00) | 1.02 (0.95–1.09) | 1.00 | 0.97* (0.94–1.00) | 0.97* (0.93–1.00) | 0.98 (0.95–1.02) | 1.00 (0.99–1.01) |
| Intracerebral hemorrhage | 1.10 (0.94–1.29) | 1.00 | 0.93 (0.85–1.03) | 0.86* (0.77–0.96) | 0.89* (0.80–0.99) | 0.97* (0.95–0.99) | 1.28* (1.01–1.63) | 1.00 | 1.05 (0.93–1.18) | 1.10 (0.96–1.25) | 1.09 (0.95–1.25) | 1.02 (0.99–1.04) |
| Cerebrovascular disease | 1.06 (0.98–1.14) | 1.00 | 0.97 (0.94–1.01) | 0.96 (0.92–1.00) | 0.99 (0.95–1.04) | 1.00 (0.98–1.01) | 1.00 (0.92–1.08) | 1.00 | 0.97 (0.94–1.01) | 0.97 (0.93–1.01) | 0.97 (0.93–1.01) | 1.00 (0.99–1.01) |
| Ischemic heart disease | 1.17* (1.06–1.29) | 1.00 | 0.93* (0.89–0.98) | 0.93* (0.88–0.99) | 0.94 (0.89–1.00) | 0.98* (0.96–0.99) | 1.05 (0.95–1.16) | 1.00 | 0.96 (0.91–1.00) | 0.95 (0.90–1.00) | 0.98 (0.93–1.04) | 1.01 (0.99–1.02) |
| Ischemic stroke | 1.02 (0.93–1.13) | 1.00 | 0.97 (0.92–1.01) | 0.96 (0.91–1.01) | 1.01 (0.95–1.07) | 1.00 (0.99–1.01) | 1.11* (1.01–1.23) | 1.00 | 0.99 (0.95–1.04) | 0.98 (0.93–1.03) | 0.97 (0.92–1.03) | 0.99 (0.98–1.00) |
| Cancer | 1.00 (0.89–1.12) | 1.00 | 1.02 (0.96–1.07) | 1.01 (0.95–1.08) | 1.04 (0.97–1.11) | 1.01 (0.99–1.02) | 1.03 (0.90–1.17) | 1.00 | 0.94* (0.90–0.99) | 0.92* (0.87–0.99) | 0.89* (0.83–0.96) | 0.98 (0.97–1.00) |
| Stomach | 0.99 (0.73–1.33) | 1.00 | 1.03 (0.90–1.18) | 1.06 (0.91–1.24) | 1.07 (0.91–1.27) | 1.01 (0.97–1.05) | 0.70 (0.40–1.25) | 1.00 | 0.82* (0.67–0.99) | 0.89 (0.71–1.12) | 0.82 (0.64–1.05) | 1.00 (0.95–1.06) |
| Lung | 0.94 (0.75–1.18) | 1.00 | 0.96 (0.86–1.06) | 0.94 (0.83–1.06) | 1.03 (0.91–1.18) | 1.02 (0.99–1.06) | 0.85 (0.59–1.20) | 1.00 | 0.97 (0.85–1.10) | 0.98 (0.84–1.14) | 0.96 (0.81–1.13) | 1.02 (0.98–1.06) |
| Liver | 1.09 (0.81–1.45) | 1.00 | 1.00 (0.87–1.14) | 0.97 (0.82–1.14) | 0.98 (0.82–1.18) | 1.00 (0.95–1.04) | 1.29 (0.81–2.05) | 1.00 | 0.95 (0.77–1.18) | 0.91 (0.71–1.15) | 0.91 (0.70–1.18) | 0.97 (0.92–1.03) |
| Breast | NA | NA | NA | NA | NA | NA | 1.09 (0.83–1.42) | 1.00 | 0.82* (0.74–0.92) | 0.61* (0.52–0.72) | 0.49* (0.39–0.60) | 0.82* (0.78–0.86) |
| Diseases of the respiratory system | 1.15* (1.05–1.25) | 1.00 | 1.02 (0.98–1.07) | 1.06* (1.00–1.11) | 1.10* (1.04–1.17) | 1.02* (1.01–1.03) | 1.01 (0.92–1.12) | 1.00 | 0.98 (0.95–1.02) | 0.99 (0.94–1.03) | 1.04 (0.99–1.09) | 1.02* (1.01–1.03) |
| COPD | 1.56* (1.34–1.81) | 1.00 | 1.02 (0.93–1.12) | 1.06 (0.96–1.17) | 1.13* (1.02–1.26) | 1.00 (0.98–1.02) | 1.09 (0.87–1.38) | 1.00 | 1.03 (0.94–1.14) | 1.10 (0.98–1.23) | 1.16* (1.03–1.31) | 1.04* (1.01–1.06) |
| Chronic airway obstruction | 1.38* (1.08–1.77) | 1.00 | 1.00 (0.85–1.17) | 1.15 (0.98–1.36) | 1.18 (0.99–1.41) | 1.03 (0.99–1.06) | 0.96 (0.63–1.47) | 1.00 | 0.94 (0.77–1.14) | 0.93 (0.75–1.15) | 1.09 (0.88–1.35) | 1.04* (1.00–1.08) |
| Bronchitis | 1.43* (1.24–1.65) | 1.00 | 1.02 (0.95–1.11) | 1.08 (0.98–1.18) | 1.08 (0.98–1.19) | 0.99 (0.97–1.01) | 0.97 (0.81–1.16) | 1.00 | 0.94* (0.88–1.00) | 0.93 (0.86–1.01) | 0.96 (0.88–1.05) | 1.00 (0.98–1.02) |
| Pneumonia | 1.08 (0.96–1.21) | 1.00 | 0.99 (0.93–1.05) | 1.02 (0.96–1.09) | 1.08* (1.00–1.16) | 1.02* (1.01–1.04) | 0.98 (0.86–1.12) | 1.00 | 0.98 (0.94–1.03) | 0.99 (0.93–1.05) | 1.05 (0.98–1.12) | 1.02* (1.01–1.04) |
| Tuberculosis | 1.16 (0.85–1.60) | 1.00 | 1.03 (0.87–1.22) | 1.10 (0.90–1.34) | 1.12 (0.90–1.40) | 1.01 (0.96–1.06) | 1.12 (0.69–1.80) | 1.00 | 1.10 (0.89–1.36) | 0.97 (0.75–1.25) | 1.27 (0.96–1.67) | 1.05 (0.98–1.12) |
| Acute upper respiratory infections of multiple and unspecified sites | 0 (0–Inf) | 1.00 | 0.61 (0.06–6.32) | 0.12 (0.01–2.62) | 0.10 (0–3.24) | 0.94 (0.39–2.25) | 873757.01 (0-Inf) | 1.00 | 43657.38 (0-Inf) | 32764.74 (0-Inf) | 0.93 (0-Inf) | 0.32 (0.02–5.08) |
| Diseases of the digestive system | 0.94 (0.86–1.03) | 1.00 | 1.01 (0.97–1.05) | 1.00 (0.95–1.05) | 0.99 (0.94–1.05) | 1.00 (0.99–1.02) | 1.01 (0.92–1.11) | 1.00 | 0.98 (0.95–1.01) | 0.96 (0.92–1.00) | 0.99 (0.94–1.04) | 1.00 (0.99–1.01) |
| Gastric and duodenal ulcers | 1.07 (0.76–1.49) | 1.00 | 1.07 (0.91–1.25) | 1.18 (0.98–1.44) | 1.21 (0.97–1.52) | 1.04 (0.98–1.10) | 0.89 (0.55–1.44) | 1.00 | 1.01 (0.85–1.20) | 0.92 (0.75–1.13) | 0.90 (0.71–1.13) | 0.99 (0.93–1.05) |
| Liver disease | 1.14 (0.87–1.48) | 1.00 | 1.11 (0.97–1.25) | 1.00 (0.85–1.17) | 0.96 (0.79–1.17) | 0.99 (0.94–1.04) | 0.97 (0.68–1.39) | 1.00 | 1.04 (0.92–1.17) | 1.01 (0.86–1.19) | 1.03 (0.86–1.23) | 1.01 (0.97–1.06) |
| Cholelithiasis and cholecystitis | 1.07 (0.85–1.34) | 1.00 | 0.98 (0.89–1.08) | 0.90 (0.79–1.02) | 0.98 (0.85–1.13) | 0.98 (0.95–1.02) | 1.10 (0.89–1.35) | 1.00 | 1.09* (1.02–1.17) | 1.10* (1.02–1.20) | 1.17* (1.07–1.29) | 1.04* (1.02–1.07) |
| Diseases of the genitourinary system | 1.01 (0.90–1.13) | 1.00 | 1.03 (0.97–1.08) | 1.07* (1.01–1.14) | 1.05 (0.97–1.13) | 1.02 (1.00–1.03) | 0.99 (0.88–1.11) | 1.00 | 1.03 (0.99–1.07) | 1.03 (0.98–1.09) | 1.07* (1.00–1.14) | 1.02* (1.00–1.04) |
| Glomerular and tubulointerstitial diseases | 1.22 (0.89–1.68) | 1.00 | 0.96 (0.82–1.12) | 0.96 (0.79–1.17) | 0.90 (0.72–1.14) | 0.96 (0.91–1.02) | 1.74* (1.20–2.52) | 1.00 | 0.94 (0.78–1.13) | 1.10 (0.89–1.36) | 1.09 (0.86–1.37) | 1.01 (0.96–1.06) |
| Urinary calculus | 1.12 (0.94–1.34) | 1.00 | 1.05 (0.97–1.13) | 1.03 (0.92–1.14) | 1.15* (1.01–1.31) | 1.02 (0.99–1.06) | 0.69* (0.50–0.94) | 1.00 | 1.04 (0.96–1.13) | 1.06 (0.95–1.18) | 1.09 (0.96–1.25) | 1.03 (1.00–1.07) |
| Hyperplasia of prostate | 0.98 (0.76–1.26) | 1.00 | 1.03 (0.92–1.16) | 1.13 (1.00–1.28) | 1.03 (0.89–1.18) | 1.02 (0.99–1.05) | NA | NA | NA | NA | NA | NA |
| Polyp of female genital organs | NA | NA | NA | NA | NA | NA | 1.10 (0.73–1.65) | 1.00 | 1.34* (1.16–1.56) | 1.42* (1.13–1.79) | 1.20 (0.84–1.73) | 1.10* (1.01–1.19) |
| Other important diseases | ||||||||||||
| Type 2 diabetes | 1.08 (0.87–1.34) | 1.00 | 1.07 (0.99–1.17) | 1.13* (1.01–1.26) | 1.09 (0.94–1.25) | 1.02 (0.99–1.06) | 1.03 (0.83–1.30) | 1.00 | 1.01 (0.94–1.08) | 1.11* (1.01–1.21) | 1.09 (0.98–1.21) | 1.02 (1.00–1.05) |
| Hypertension | 0.90 (0.71–1.13) | 1.00 | 1.00 (0.90–1.10) | 1.00 (0.89–1.13) | 0.96 (0.84–1.11) | 0.99 (0.96–1.03) | 1.10 (0.91–1.33) | 1.00 | 1.00 (0.93–1.07) | 0.94 (0.86–1.03) | 0.87* (0.78–0.96) | 0.95* (0.93–0.98) |
| Injury and poisoning | 1.05 (0.92–1.20) | 1.00 | 1.06* (1.00–1.13) | 1.07 (0.99–1.15) | 1.02 (0.94–1.12) | 1.00 (0.98–1.02) | 1.03 (0.89–1.18) | 1.00 | 0.99 (0.94–1.04) | 0.96 (0.90–1.02) | 0.92* (0.85–0.98) | 0.98* (0.96–0.99) |
| Diseases of the nervous system | 1.26* (1.07–1.47) | 1.00 | 1.05 (0.97–1.14) | 1.08 (0.98–1.18) | 1.13* (1.02–1.26) | 1.02 (0.99–1.04) | 1.10 (0.93–1.29) | 1.00 | 1.01 (0.95–1.08) | 1.09* (1.01–1.18) | 1.12* (1.02–1.22) | 1.03* (1.01–1.05) |
| Cataract | 1.16 (0.98–1.39) | 1.00 | 1.00 (0.91–1.09) | 0.98 (0.89–1.08) | 1.02 (0.92–1.14) | 0.99 (0.97–1.01) | 1.09 (0.92–1.29) | 1.00 | 1.07 (0.99–1.16) | 1.02 (0.94–1.11) | 0.94 (0.86–1.02) | 0.96* (0.95–0.98) |
| Osteoarthrosis | 5.21 (0.34–79.53) | 1.00 | 0.79 (0.13–4.65) | 0.30 (0.02–4.55) | 1.41 (0.13–15.30) | 1.06 (0.57–1.95) | 0.47 (0.06–3.58) | 1.00 | 0.50* (0.25–0.98) | 0.27* (0.11–0.65) | 0.36* (0.15–0.90) | 0.83 (0.65–1.06) |
| Disorders of lipoid metabolism | 1.00 (0.59–1.72) | 1.00 | 1.33* (1.08–1.63) | 1.26 (0.95–1.67) | 1.36 (0.97–1.92) | 1.07 (0.98–1.17) | 1.09 (0.73–1.62) | 1.00 | 1.09 (0.73–1.62) | 0.95 (0.80–1.15) | 0.94 (0.76–1.17) | 0.96 (0.90–1.01) |
| Disorders of conjunctiva | 0.88 (0.53–1.48) | 1.00 | 1.26* (1.03–1.54) | 1.45* (1.13–1.85) | 1.60* (1.20–2.14) | 1.12* (1.05–1.20) | 0.90 (0.52–1.55) | 1.00 | 1.37* (1.17–1.61) | 1.25* (1.03–1.51) | 1.20 (0.96–1.49) | 1.02 (0.97–1.08) |
| Varicose veins | 1.08 (0.73–1.58) | 1.00 | 1.14 (0.99–1.31) | 1.15 (0.96–1.39) | 0.98 (0.75–1.28) | 1.01 (0.94–1.08) | 1.01 (0.59–1.74) | 1.00 | 1.10 (0.93–1.29) | 1.32* (1.08–1.63) | 1.04 (0.78–1.38) | 1.04 (0.96–1.12) |
*P <0.05. Models were stratified by age at risk (five-year bands) and study areas (10 groups) and further adjusted for marital status, highest education, household income, household size, alcohol drinking, smoking, dietary habits, BMI, physical activity, satisfaction level with life, history of diabetes, hypertension, respiratory disease, CVD, or cancer at baseline, family history of the analyzed disease (adjusted for corresponding analyses), self-reported satisfaction level of life, and menopausal status (for women only). aHR: Adjusted hazard ratio; BMI: Body mass index; CI: Confidence interval; COPD: Chronic obstructive pulmonary disease; CVD: Cardiovascular disease; NA: Not applicable.
In the association analyses of 37 diseases among women (excluding hyperplasia of the prostate), those without offspring were found to have increased risks for five diseases compared to women with one offspring. These increased risks were primarily observed in mental and behavioral disorders, CVD, and glomerular and tubulointerstitial diseases. Women with more than one offspring demonstrated lower risks of certain diseases, such as breast cancer (two offspring: aHR [95% CI] = 0.82 [0.74–0.92]; three offspring: aHR [95% CI] = 0.61 [0.52–0.72]; four or more offspring: aHR [95% CI] = 0.49 [0.39–0.60]). Moreover, each additional offspring was associated with an 18% reduction in breast cancer risk (aHR [95% CI] = 0.82 [0.78–0.86]). Conversely, higher risks were found for diseases such as cholelithiasis and cholecystitis (two offspring: aHR [95% CI] = 1.09 [1.02–1.17]; three offspring: aHR [95% CI] = 1.10 [1.02–1.20]; four or more offspring: aHR [95% CI] = 1.17 [1.07–1.29]), and COPD (four or more offspring: aHR [95% CI] = 1.16 [1.03–1.31]). Specifically, each additional offspring was associated with a 4% increase in the risk of cholelithiasis and cholecystitis (aHR [95% CI] = 1.04 [1.02–1.07]) and COPD (aHR [95% CI] = 1.04 [1.01–1.06]). The overall risks of mental and behavioral disorders (aHR [95% CI] = 0.79 [0.66–0.94]), cancers (aHR [95% CI] = 0.89 [0.83–0.96]), hypertension (aHR [95% CI] = 0.87 [0.78–0.96]), injury and poisoning (aHR [95% CI] = 0.92 [0.85–0.98]), and osteoarthrosis (aHR [95% CI] = 0.36 [0.15–0.90]) were diminished among women with four or more offspring.
Moreover, each additional offspring was associated with a lower risk of overall CVD in men, and with lower risks of mental and behavioral disorders, hypertension, injury and poisoning, and cataract in women [Table 2]. Sex-specific results of sensitivity analyses are presented in Supplementary Tables 4 and 5, http://links.lww.com/CM9/C606. No significant changes were found in risk estimates after adjusting for additional covariates, such as passive smoking, or excluding participants who were followed for no more than two years. There is a modifying effect of urban–rural and birth cohorts on the association between the number of offspring and the morbidity risks of certain diseases (corresponding Pinteraction <0.05). For instance, rural men without offspring exhibited a more pronounced increase in the risk of respiratory diseases compared to their urban counterparts.
Number of offspring and mortality risk among patients
Among patients with any of the 26 diseases at baseline in CKB, 123,284 men and 159,346 women were included in the analysis. During a median follow-up of 12.01 years, a total of 44,533 deaths were recorded. Among them, the smallest and largest numbers of patients with a single disease were those with prostate cancer and hypertension, corresponding to five and 180,467 patients at baseline, respectively. During the follow-up period, two and 32,546 deaths were recorded among the baseline patients with these two diseases, respectively [Supplementary Table 6, http://links.lww.com/CM9/C606].
Figure 2 and Table 3 present the association between the number of offspring and mortality risks among male and female patients with any of the 26 diseases at baseline in CKB. Sensitivity analyses are shown in Supplementary Table 7, http://links.lww.com/CM9/C606. Upon adjusting for all covariates in the final model, compared to patients with offspring, male and female patients without offspring had a 37% and 27% higher risk of all-cause mortality (men: aHR [95% CI] = 1.37 [1.28–1.47]; women: aHR [95% CI] = 1.27 [1.15–1.41]), respectively [Figure 2]. The restricted cubic spline plot revealed a deceleration in the reduction of mortality risk among male patients as the number of offspring reached two. Relative to male patients with one offspring, those without offspring had a 31% higher mortality risk (aHR [95% CI] = 1.31 [1.22–1.42]). In contrast, those with three offspring had a 6% lower mortality risk (aHR [95% CI] = 0.94 [0.89–0.99]), and those with four or more offspring had a 7% lower mortality risk (aHR [95% CI] = 0.93 [0.88–0.98]). Each additional offspring reduced mortality by 4% in male patients (aHR [95% CI] = 0.96 [0.95–0.98]) [Table 3]. Among female patients, the number of offspring corresponding to the lowest risk of all-cause mortality was between three and four (Pnonlinearity <0.0001). Compared with those with one offspring, female patients without offspring had a 19% higher mortality risk (aHR [95% CI] = 1.19 [1.06–1.34]), while those with three offspring had a 7% lower mortality risk (aHR [95% CI] = 0.93 [0.87–0.99]), and those with four or more offspring had a 8% lower mortality risk (aHR [95% CI] = 0.92 [0.86–0.99]) [Table 3]. Owing to none or few deaths observed during the follow-up among childless patients for statistical estimations, we listed death numbers among patients who had 1, 2, 3, and ≥4 offspring [Supplementary Table 6, http://links.lww.com/CM9/C606] and the detailed results of the mortality risk of patients with a single disease at baseline have been provided in Supplementary Tables 8 and 9, http://links.lww.com/CM9/C606. Mortality risks were not assessed among patients with lung, liver, and prostate cancer at baseline (n = 129, 37 and 5, respectively) due to insufficient statistical power.
Figure 2.
Kaplan–Meier estimates (without vs. with offspring) and results of the restricted cubic spline for associations between the number of offspring and mortality risks among male and female patients with any of the 26 diseases at baseline. Models were stratified by age at risk (five-year bands) and study areas (10 groups) and further adjusted for marital status, highest education, household income, household size, alcohol drinking, smoking, dietary habits, BMI, physical activity, satisfaction level with life, history of diabetes, hypertension, respiratory disease, CVD, and cancer at baseline, family history of the analyzed disease (adjusted for only in corresponding analysis), self-reported satisfaction level of life, and menopausal status (for women only). Kaplan–Meier estimates of the mortality risk are shown for male (A) and female (B) patients with any of the 26 diseases at baseline. In each analysis, patients with offspring were taken as the reference group. Sex-specific restricted cubic spline plots for the association between mortality risks and the number of offspring among men (C) and women (D). The blue dashed line represents the point corresponding to the number of offspring in the curve when aHR = 1. P-values of non-linearity and significance of the association were described in the graph. aHR: Adjusted hazard ratio; BMI: Body mass index; CI: Confidence interval; CVD: Cardiovascular disease.
Table 3.
Association between the number of offspring and mortality risks in patients with any of the 26 diseases at baseline*.
| Items | Number of offspring | Each additional offspring | ||||
|---|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | ≥4 | ||
| Men | ||||||
| Number of patients at baseline | 3476 | 40,962 | 38,817 | 23,428 | 16,601 | |
| Number of deaths | 1040 | 3791 | 6542 | 6552 | 7115 | |
| Deaths/1000 person-years | 28.38 | 7.90 | 14.77 | 25.83 | 42.92 | |
| Model 1, aHR (95% CI) | 1.36 (1.26–1.47) | 1.00 | 0.99 (0.94–1.03) | 0.95 (0.90–1.00) | 0.95 (0.90–1.00) | 0.97 (0.96–0.98) |
| Model 2, aHR (95% CI) | 1.35 (1.25–1.45) | 1.00 | 0.98 (0.93–1.03) | 0.94 (0.89–0.99) | 0.92 (0.88–0.98) | 0.96 (0.95–0.97) |
| Model 3, aHR (95% CI) | 1.31 (1.22–1.42) | 1.00 | 0.98 (0.94–1.03) | 0.94 (0.89–0.99) | 0.93 (0.88–0.98) | 0.96 (0.95–0.98) |
| Women | ||||||
| Number of patients at baseline | 659 | 43,951 | 50,694 | 34,257 | 28,290 | |
| Number of deaths | 372 | 1933 | 4101 | 5247 | 7840 | |
| Deaths/1000 person-years | 15.03 | 3.66 | 6.77 | 13.18 | 25.28 | |
| Model 1, aHR (95% CI) | 1.25 (1.11–1.41) | 1.00 | 0.95 (0.89–1.01) | 0.93 (0.87–1.00) | 0.93 (0.86–0.99) | 0.99 (0.98–1.00) |
| Model 2, aHR (95% CI) | 1.23 (1.09–1.38) | 1.00 | 0.95 (0.89–1.02) | 0.93 (0.87–1.00) | 0.92 (0.86–0.99) | 0.99 (0.98–1.00) |
| Model 3, aHR (95% CI) | 1.19 (1.06–1.34) | 1.00 | 0.95 (0.89–1.01) | 0.93 (0.87–0.99) | 0.92 (0.86–0.99) | 0.99 (0.98–1.00) |
*“Any of the 26 diseases” refers to the following diseases collected at baseline in CKB: Diabetes, coronary heart disease, stroke, hypertension, rheumatic heart disease, pulmonary tuberculosis, chronic bronchitis/emphysema/pulmonary heart disease, asthma, chronic hepatitis/cirrhosis, peptic ulcer, cholelithiasis/cholecystitis, chronic kidney disease, fracture, arthritis, psychosocial disorder, neurasthenia, brain trauma, and malignant tumor (lung, esophagus, stomach, liver, intestine, breast, prostate, cervix, and others). aHR: Adjusted hazard ratio; CI: Confidence interval; CKB: China Kadoorie Biobank.
Discussion
Our study sheds light on how the number of offspring impacts the health of adult men and women in China. It was discovered that having and raising children may affect an individual’s health outcomes. Compared to men with one offspring, men without offspring had a higher risk of overall mental and behavioral disorders and CVD. Conversely, men with two or more offspring showed similar or reduced risks for specific disorders, such as schizophrenia and other psychotic disorders (with two or three offspring), and certain CVD subtypes including intracerebral hemorrhage (with three, four or more offspring) and ischemic heart disease (with two or three offspring). Women with more than one offspring, particularly those with four or more, had a lower overall risk of mental and behavioral disorders and a significantly lower risk of breast cancer, but a higher risk of cholelithiasis and cholecystitis.
Both men and women with a higher number of offspring had an increased risk of COPD. Crucially, our findings extend to mortality risk among individuals with pre-existing conditions. Interestingly, compared to those with offspring, male and female patients without offspring had a 37% and 27% higher risk of all-cause mortality, respectively. Additionally, among male patients, each additional offspring was associated with a 4% reduction in mortality risk. For female patients, those with three to four offspring had the lowest risk of mortality. Our study presents novel epidemiological findings that are crucial for future basic research and exploration of causal relationships, which carry important implications for policymakers as they address the health challenges that may arise from demographic changes in China in the future.
Comparison with other studies and potential mechanism
Childless individuals have a higher risk of mental and behavioral disorders, while women with more offspring may have a lower risk. Children provide emotional support and companionship, which can positively impact mental health.[9] Nevertheless, it would be overly simplistic to attribute this solely to the protective effect of having more children against the development of mental illnesses. An alternative explanation for this finding could be related to the hereditary nature of mental illnesses deterring individuals from getting married and having children. The higher risks of mental illnesses or other conditions among childless men and women may be a cause, rather than a consequence, of their childlessness. Future research should aim to further explore these causal relationships.
The initial onset of schizophrenia typically manifests as a peak in diagnosis between the ages of 25 years and 35 years.[10] Therefore, studying the link between the number of offspring and mental illness risk is crucial for those of childbearing age or considering pregnancy. However, reverse causality might be a concern. Participants with asymptomatic schizophrenia were less likely to have offspring due to social impairment and the high heritability of the condition in their offspring.
Our study found that childlessness was associated with increased risks of CVD in men and certain subtypes of CVD in both genders. The mechanism is complex, and previous research has produced inconsistent findings.[1–4] Two prior studies based on UK Biobank (UKB)[1,2] found a lower risk of CVD among participants without offspring compared to those with offspring across both genders. However, other evidence suggested that women without offspring may have a higher risk of CVD,[3] or variations may exist in the associations between the number of offspring and the risk of different CVD subtypes.[4] This study, conducted within the Chinese population, observed that having no offspring was associated with an increased risk of CVD or related subtypes in men and women. Furthermore, the association between the number of offspring and the risk of different CVD subtypes demonstrated inconsistencies. It was plausible that the association between the number of offspring and the risk of CVD was influenced by social and behavioral factors related to parenthood, such as smoking and unhealthy dietary habits, which were recognized as important risk factors for CVD.[11] Previous research has suggested that people may cease smoking as a result of pregnancy (including instances where men may quit smoking due to their partner’s pregnancy).[12] Moreover, to improve children’s health, people may shift toward healthier habits after becoming parents[13]; however, after adjusting for related factors, a higher risk of CVD persisted among those without offspring, indicating the involvement of other unidentified factors. In this study, disparities were noted in the association between the number of offspring and the risk of CVD among men and women, suggesting potential links to physiological and metabolic changes associated with female pregnancy. Higher levels of estrogen and progesterone were believed to influence the release of endothelial-derived vasodilator factors and the renin-angiotensin system, thereby potentially exerting a protective effect against the development of CVD.[14] Conversely, during pregnancy, women may experience alterations such as upregulation of the renin–angiotensin–aldosterone system,[15] increased peripheral insulin resistance,[16] lipid changes,[17] and changes in vascular endothelial function,[18] which may contribute to an increased risk of CVD. Similar associations in CVD but differences in the corresponding CVD subtypes were captured in men and women. The underlying mechanisms driving these differences warrant further investigation.
This study found that each additional offspring was associated with an 18% reduction in breast cancer risk among women. Specifically, those with four or more offspring had over 50% lower risk compared to the reference group. High levels of pregnancy-related estrogen may decrease breast cancer risk. The estrogen receptor beta (ER-β) may act as a tumor suppressor in breast cancer development by reducing cell growth and promoting cell death.[19,20]
Our observations indicated that, in both men and women, having four or more offspring was associated with an increased risk of developing COPD, a condition that primarily affects the lower airways of the lungs, where pathological processes and symptoms are concentrated. Indoor environmental air pollution has been proven to adversely affect lung health and increase the risk of lower respiratory diseases,[21] and household air pollution, stemming predominantly from solid fuels used in daily life, may contribute to an adverse living environment,[22] with larger household size possibly exacerbating these effects. Based on the same cohort, previous evidence from CKB has indicated that solid fuels used in cooking were associated with an increased risk of hospitalization and mortality due to major respiratory diseases among non-smokers.[23] In addition, our findings indicated that men without offspring had an increased risk of developing various respiratory diseases compared to those with one offspring. It was well established that adverse risk factors, such as smoking, significantly contribute to respiratory diseases.[24] As noted above, men may adopt healthier lifestyles after becoming fathers. In China, where the majority of smokers were men,[25] this shift in lifestyle could be a key factor explaining why we observed these associations predominantly among men. In women, having more offspring was associated with an increased risk of developing cholelithiasis and cholecystitis compared to the control group, which may be attributed to significant alterations in metabolic status resulting from dietary changes early in pregnancy.[26] Intriguingly, we found some novel links between the number of offspring and the risk of developing nervous or genitourinary system diseases. However, more research is needed to confirm these associations. Exploring the reasons behind the increased risk of genitourinary system diseases associated with having multiple offspring could be crucial for enhancing women’s reproductive health outcomes and reducing the burden of related diseases in the future.
Among patients with any of the 26 diseases at baseline in CKB, compared to those with offspring, male patients without offspring had an increased risk of all-cause mortality. In contrast, the lowest risk in female patients was observed among those with 3–4 offspring. Potential explanations for these findings included societal pressures and psychological burdens experienced by individuals without children in societies that strongly oppose childlessness, potentially leading to negative events.[27] On the other hand, children could provide emotional and economic support for disease treatment,[13] contributing to the observed differences in mortality risk. However, when the number of children reaches a certain level, the survival advantage of patients may be affected by various factors, potentially attributed to elevated levels of chronic stress and anxiety related to parenting, as well as unhealthy lifestyle habits such as sleep deprivation.[28–30]
Strengths and limitations of this study
Previous studies on the number of offspring and morbidity/mortality risks mostly focused on women,[31] neglecting men’s health. This study is the most comprehensive evidence on the impact of the number of offspring on the health outcomes of Chinese populations, considering both sexes. The study’s prospective cohort design, substantial sample size, and long-term follow-up provide valuable insights into this understudied area. The extensive dataset enables reasonable sensitivity or stratified analyses, considering potential confounding factors. Further research is needed to explore potential mechanisms.
There were some limitations in this study: (1) The information on the number of offspring came from self-report questionnaires, which may be impacted by recall bias. The parenthood represented a significant life event; thus, recall bias may be minimal. (2) The number of offspring was collected at the beginning of the study, so any changes during the follow-up were not accounted for. Due to the implementation of the one-child policy in China from 1980 to the early 2000s, participants who already had offspring were unlikely to have additional offspring. (3) Although our results have adjusted for the key confounding factors stepwise, the observed associations may be influenced by unmeasured confounding factors, such as physiological, cultural, or socio-economic factors in women before or during pregnancy. (4) Our follow-up data did not include outpatient records, which could lead to an underestimation of the prevalence of many diseases that do not require in-hospital treatment. This limitation may limit the applicability of our findings to the estimation of associations primarily focused on diseases of lower severity typically treated in outpatient and emergency settings. (5) Due to the social environment in China, the sample size of participants without offspring is relatively small, and information on whether they actively chose to be childless or had a history of infertility was not collected. There may be differences between being unable to conceive and choosing not to have offspring. Caution must be taken when generalizing our findings to the broader population.
In conclusion, this large-scale prospective study involving 0.5 million men and women from CKB revealed complex associations between the number of offspring and a wide range of health outcomes. Compared to individuals with one offspring, having two or more offspring may be associated with a reduced risk of certain diseases—such as schizophrenia in men with two or three offspring, and breast cancer in women with two, three or four or more offspring. However, risks of some conditions increased with each additional offspring, such as cholelithiasis/cholecystitis in women. Moreover, patients without offspring had a higher risk of all-cause mortality risk among those with pre-existing chronic conditions at baseline, compared to those with offspring. Further research is needed to validate these findings and elucidate the underlying biological, behavioral, and sociological mechanisms involved, as well as the causal relationship between the number of offspring and the risks of morbidity and mortality.
Acknowledgments
The chief acknowledgment goes to the participants in the study and the members of the survey teams in each of the ten regional centers, as well as to the project development and management teams based at Beijing, Oxford, and the ten regional centers.
Funding
This work was supported by grants from the National Key R&D Program of China (Nos. 2023YFC2509400 and 2020YFC2003405) and the National Natural Science Foundation of China (Nos. 82103920 and 82388102). The CKB baseline survey and the first re-survey were supported by a grant from the Kadoorie Charitable Foundation in Hong Kong. The long-term follow-up is supported by grants from the UK Wellcome Trust (Nos. 212946/Z/18/Z, 202922/Z/16/Z, 104085/Z/14/Z, and 088158/Z/09/Z), the National Key R&D Program of China (Nos. 2016YFC0900500 and 2020YFC2003405), the National Natural Science Foundation of China (Nos. 81390540, 91846303 and 81941018), and the Chinese Ministry of Science and Technology (No. 2011BAI09B01).
Conflicts of interest
None.
Data sharing
The access policy and procedures are available at www.ckbiobank.org. As stated in the access policy, the CKB study group must maintain the integrity of the database for future use and regulate data access to comply with prior conditions agreed with the Chinese government. Data security is an integral part of the CKB study protocols. Data can be released outside the CKB research group only with appropriate security safeguards.
Supplementary Material
Footnotes
How to cite this article: Xiao M, Li AL, Yu CQ, Pang YJ, Pei P, Yang L, Chen YP, Du HD, Hua YJ, Chen JS, Chen ZM, Lyu J, Li LM, Sun DJY; On Behalf of The China Kadoorie Biobank Collaborative Group. A phenome-wide spectrum of morbidity and mortality risks related to the number of offspring among 0.5 million Chinese men and women: A prospective cohort study. Chin Med J 2025;138:2925–2937. doi: 10.1097/CM9.0000000000003815
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