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\begin{document}

\title{The association of number of births on women's biological aging,
premature mortality and life expectancy: a prospective cohort study of
UK biobank}



\author[1]{Dandan Zhang}%
\author[1]{Huanyu Guo}%
\author[1]{Yuqing Liu}%
\author[1]{Ruiming Yang}%
\author[1]{* Weiwei}%
\affil[1]{Harbin Medical University}%


\vspace{-1em}



  
  \date{May 27, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
\textbf{Objective:} Few studies have examined whether number of births
is associated with women's aging. This study aims to evaluate the
association of number of births with women's biological aging, premature
mortality and life expectancy. \textbf{Methods:} A total of 272,494
participants from UK biobank who completed the questionnaire on number
of live births were enrolled at baseline. The number of births was
categorized into 6 groups, and participants with one live birth was the
reference group. General linear regression model and cox proportional
hazards model were performed to evaluate the association of number of
births with women's biological aging and premature mortality. Restricted
cubic spline (RCS) was used to visualize dose-response relationship.
Moreover, the latest Office for National Statistics life tables rom was
used to calculate the life expectancy. \textbf{Results}: During a median
follow-up of 11.9 years, a total of 10,992 cases of all-cause premature
death were documented. After adjustment for potential confounders,
compared to women had one birth, childless women had greater premature
death (hazard ratio, HR=1.17, 95\%CI: 1.09-1.25), whereas women with two
or three children had lower risk of premature death (HR=0.87,
95\%CI:0.82-0.93, HR=0.90, 95\%CI: 0.82-0.99), which showed a U-shaped
relationship visualized by RCS (P\textless{}0.05 for non-linearity).
Further, at age 40, childless women had 1.41 years lower life
expectancy, and women with two children was related to 1.10 years higher
life expectancy. Moreover, compared to women had one birth, the women
with two or three children had lower corrected estimated values of FI,
\selectlanguage{greek}Δ\selectlanguage{english}KDM-biological age and HD, and the women with five or more children had
higher corrected estimated values of FI, \selectlanguage{greek}Δ\selectlanguage{english}KDM-biological age, and HD
(all the P\textless{}0.05). \textbf{Conclusions}: The association of
number of live births with women's biological aging, premature mortality
and life expectancy had a U-shape relation. The childless or five more
child women were more likely to be aging with increased risk of
premature death and decreased life expectancy years. The double-child
women decreased aging process with lower risk of premature death and
high life expectancy.%
\end{abstract}%



\sloppy


\textbf{Introduction}

Aging-related diseases and premature death pose significant threats to
health\textsuperscript{{[}1-4{]}}. Given the global impact of these
issues, it is crucial to comprehend the influence of modifiable risk
factors. Women childbirth is a fundamental aspect of human behavior,
playing a vital role in maintaining women's health. Current studies on
childbirth and women's health predominantly focus on the health effects
of the number of births, leading to two contrasting viewpoints. Some
studies propose that childbirth may reduce the risk of breast cancer,
uterine cancer and ovarian cancer by decreasing exposure to progesterone
and estrogen\textsuperscript{{[}5,6{]}}, which is believed to counteract
negative physiological changes that accumulate with an increasing number
of births, potentially delaying the aging
process\textsuperscript{{[}7{]}}. Conversely, other studies argue that
childbirth consumes a significant portion of resources through
reproduction, diverting resources away from the maintenance and repair
of somatic tissues, consequently accelerating the aging process.
Therefore, it remains largely uncertain whether and how the number of
childbirths influences women's health.

Further, results from observational studies regarding the potential link
between number of births and women's risk of mortality are
inconsistent\textsuperscript{{[}8-12{]}}. Some studies found that there
is a negative association between number of birth and women's risk of
mortality, whereas other studies showed that such association is
U-shape\textsuperscript{{[}13,14{]}}. There are even studies suggesting
a non-significant association\textsuperscript{{[}15{]}}. Despite the
relatively large sample sizes in some studies, they often failed to
account for potential confounding factors such as economic, behavioral,
and dietary variables\textsuperscript{{[}13,14,16{]}}. At the
sociological level, raising children can avoid unhealthy behaviors by
improving their lifestyle and often involves more social
participation\textsuperscript{{[}17,18{]}}, but it may also increase
women's stress, related depression risks, and significant economic
costs\textsuperscript{{[}19-23{]}}. Therefore, there is a need for a
comprehensive study with a sufficiently large sample size that considers
a wide range of confounding variables.

To fill this knowledge gap, this study utilize data from the UK Biobank
(UKB) to assess the association between the number of live births and
women's aging, premature all-cause mortality, and life expectancy.
Meanwhile, extensive confounding including socioeconomic factors,
lifestyle factors and biological factors were adjusted for accurate
evaluation. This study may add insights into relationships between
childbirth and women's aging, premature all-cause mortality, and life
expectancy for the first time, for clinical and public health reference,
being useful for future production interventions.

\textbf{Materials and methods}

\textbf{Study population}

A brief overview of the UK Biobank study design is provided below, as
the study design and methods have been reported elsewhere in detail
previously\textsuperscript{{[}24{]}}. In short, the data used in this
study came from the baseline survey at 22 assessment centers throughout
England, Wales, and Scotland from 2006 to 2010, a total of 502411
participants (5.5\% response rate) aged between 37 and 73 years. Data
from 273325 women were available for our study, we excluded 478
participants with incomplete data on the number of live births and 352
participants who prefer not to answer. Among them, we considered only
the subjects above 40 years of age at recruitment, as there are few
deaths at younger ages\textsuperscript{{[}25{]}} (Supplementary Figure
1). As a result, a total of 272494 women (99.7\%) were included in this
study. All participants provided written informed consent, and the study
was approved by the North West Multi-Centre Research Ethics Committee
and the Tulane University (New Orleans, LA, USA) Biomedical Committee
Institutional Review Board.

\textbf{Exposure assessment}

Female specific factors in the touch-screen questionnaire included
reproductive history and menstrual history, such as the number of live
births, use of oral contraceptive pills, history of stillbirth,
spontaneous miscarriage or termination, and menarche, age at menopause
(last menstrual period), length of menstrual cycle. The number of live
births is a useful indicator of reproductive history. To determine the
number of live births, participants were asked `How many children have
you given birth to? (Please include live births only)' through a
touch-screen questionnaire at baseline (2006--2010). Due to small
numbers at the highest parities, we pooled women with five or more
births. In accordance with previous
studies\textsuperscript{{[}13,26,27{]}}, participants were divided into
six groups based on the number of live births: `` 0, 1, 2, 3, 4, [?]5 ''.
Our exposure was number of live births, as we wanted to account for
number of complete reproductive cycles, including a full pregnancy, a
potential breastfeeding period and behavioral changes related to child
rearing. Thus, stillbirths, spontaneous miscarriages or terminations
were not included in the exposure, and were adjusted in analyses.

\textbf{Ascertainment of premature mortality, life expectancy, and
biological aging}

Death information and date of death were confirmed by reference to the
death certificates held by the National Health Service Information
Centre for participants in England and Wales and the National Health
Service Central Register Scotland for participants from Scotland. The
participants were defined as premature mortality if their deaths
occurred at ages younger than 75\textsuperscript{{[}28{]}}. We
calculated the follow up person-years at risk of observation from the
date of consenting to join assessment center until the date of loss to
follow-up, the date of death, or March 1, 2021, whichever came first.
Causes of death were determined by using the International
Classification of Diseases Tenth Revision (ICD-10) codes, and its
detailed information was described in the Supplementary material.

We used the latest Office for National Statistics life tables rom age 40
to age 100 years to calculate the life expectancy of participants with
the distinct number of live births\textsuperscript{{[}29,30{]}}. The
detailed methods used for estimating the difference in the life
expectancy was described in the Supplementary material.

Biological aging was measured from different perspectives, including
frailty index (FI), \selectlanguage{greek}Δ\selectlanguage{english}KDM-biological age and Homeostatic disorder (HD).
The FI, \selectlanguage{greek}Δ\selectlanguage{english}biological age and HD were previously constructed and validated
in the UK Biobank\textsuperscript{{[}31{]}}. For each person, FI is
calculated as the proportion of health attributes that a person has in a
deficit state. FI scores range from 0 (indicating no health deficits) to
1 (indicating every health deficit that was assessed). \selectlanguage{greek}Δ\selectlanguage{english}Biological age
represented the value of biological age minus chronological age,
representing premature aging\textsuperscript{{[}32{]}}. HD represents
the degree of variability in individual physiological functions and
health parameters, and the HD values are positively correlated with
biological aging. Detailed calculations of FI, \selectlanguage{greek}Δ\selectlanguage{english}KDM-biological age and
HD are provided in Supplementary material.

\textbf{Covariates}

We also controlled a series of confounders, including age (years), race
(White, Mixed, Asian or Asian British, Black or Black British, Chinese
or Other ethnic group), education (age at completing continuous full
time education), Townsend Deprivation index (a composite measure of
deprivation based on unemployment, non-car ownership, non-home
ownership, and household overcrowding), smoking statues (never, past and
current), drinking (daily or almost daily, three or four times a week,
once or twice a week, one to three times a month, special occasions only
or never), moderrate activity (Metabolic Equivalent Task (MET) minutes
per week for moderate activity), the body mass index (BMI), histories of
diseases (diabetes, hypertension, asthma, emphysema and chronic
bronchitis), female specific factors (use of oral contraceptive pills,
history of stillbirth, spontaneous miscarriage or termination, menarche,
age at menopause and length of menstrual cycle) in all models. Details
of the assessment of covariates are described in Supplementary material.

\textbf{Statistical analysis}

The baseline characteristics in terms of demographics, lifestyle, health
conditions and female specific factors were presented as mean (standard
deviation, SD) and numbers (percentage). General linear models and a
chi-square test was used to compare the differences for baseline
characteristics by each parity. Also, we used general linear model to
calculate the estimated values of FI, \selectlanguage{greek}Δ\selectlanguage{english}KDM-biological age and HD
corrected for multiple covariates for each pairty. A Cox proportional
hazards model was performed to calculate hazard ratios (HRs) and 95\%
confidence intervals (CIs) for all-cause premature mortality using the
``1 production'' group as a reference, with the follow-up time as the
time scale. The dose-response relationship was fexibly modeled by the
restricted cubic spline (RCS) to explore the potential nonlinear
correlation between parity and the hazard of all-cause premature
mortality.

We performed stratified analyses by following factors: Born year (<1980
or [?]1980), race/ethnicity (White, Mixed, Asian or Asian British, Black
or Black British, Chinese or Other ethnic group), Townsend deprivation
index (<median or [?]median), BMI (<25, 25--29.9, or [?]30
kg/m\textsuperscript{2} ), smoking (never, ever, current), Alcohol
intake frequency (<once/mouth,[?]once/mouth), hypertension (no or yes),
diabetes (no or yes), hypertension (no or yes), asthma (no or yes),
emphysema and chronic bronchitis (no or yes). To evaluate interactions
between the number of live births and these factors, multiplicative
interaction was assessed by adding interaction terms to the Cox models.

Three sensitivity analyses were performed. The first analysis excluded
the participants whoes follow-up duration was less than 1 or 2 years, to
check if the severe illness would affect the results. The second
analysis evaluated the participants with additional adjusting for
covariates dietary factors (including fresh fruit intake, dried fruit
intake, oily fish intake, salt added to food, cereal intake, processed
meat intake,mineral and other dietary supplements), to examinte whether
dietary factorshad had effect on the relationship. The third analysis
further adjusted covariate biochemical indicators (including albumin,
triglyceride, glucose, LDL, cholesterol, total bilirubin) for
participants, to remove the impact of certain biochemical indicators
unrelated to production on outcomes.

All statistical analyses were conducted by R 4.2.2, and p-values
\textless{} 0.05 were considered statistically significant.

\textbf{Result}

\textbf{Basic characteristics of participants according to the number of
live births}

Basic characteristics of participants according to the number of live
births are shown in Table 1. Compared with participants with one live
births, both participants with zero and five or more children were more
likely to be non-white with higher levels of Townsend deprivation index,
and a higher percentage of asthma but a lower percentage of use of oral
contraceptive pills. Meanwhile, childless participants were more likely
to have a higher levels of education, and lower levels of BMI and
moderrate activity time, and a lower percentage of current smoking rate
but a higher percentage drinking rate; as well as a lower prevalence of
diabetes, hypertension, emphysema and chronic bronchitis, and history of
stillbirth, spontaneous miscarriage or termination. Reversely,
participants with five or more children were more likely to have a lower
level of education, and higher levels of BMI and moderrate activity
time, and a higher percentage of current smoking rate but a lower
percentage drinking rate, as well as higher prevalences of diabetes,
hypertension, asthma, emphysema and chronic bronchitis, and history of
stillbirth, spontaneous miscarriage or termination, comparied with
correspondings in women without child. The age at menarche, age at
menopause (last menstrual period), and the length of menstrual cycle are
relatively average in each group, which are nearly 13 years old, 50
years old, and 27 days, respectively.

\textbf{Association between the number of live births and hazard of
all-cause premature mortality}

Table 2 shows the results of the multivariate Cox proportional hazard
regression models between the number of live births and hazard of
all-cause premature mortality. After adjustment for age, race,
education, Townsend deprivation index, BMI, smoking statues, moderate
drinking, moderrate activity, we found that the nulliparous women
(HR\textsubscript{0}=1.17, 95\% CI: 1.10-1.25) had higher risk of
premature all-cause death, and the women with two, three and four
childern had lower risk of premature all-cause death
(HR\textsubscript{2}=0.86, 95\% CI: 0.82-0.92, HR\textsubscript{3}=0.87,
95\% CI: 0.82-0.93, HR\textsubscript{4}=0.91, 95\% CI: 0.83-0.99),
compared with the reference group. These results did not change
appreciably after further adjustment for diabetes, hypertension, asthma,
emphysema and chronic bronchitis, or female specific factors (use of
oral contraceptive pills, history of stillbirth, spontaneous miscarriage
or termination, age at menarche, age at menopause, and length of
menstrual). The HR (95\%CI) of all-cause premature mortality across
groups were 1.17(1.09-1.25), 1.00(reference), 0.87(0.82-0.93),
0.88(0.82-0.94), 0.90(0.82-0.99) and 0.94(0.83-1.08), respectively
(P-trend<0.001). The hazard of all-cause premature mortality was higher
among childless women, comparied with those who had only one child, and
women with two, three, or four children have lower all-cause premature
mortality, and this is true across models 3 to 5.

The potential nonlinear association between all-cause premature
mortality and the number of live births was intuitively described using
restricted cubic spline (RCS) based on model5. As shown in Supplementary
Figure 1, there was a non-linear relationship between the number of live
births and all-cause premature mortality (P for
non-linear\textless{}0.001), which proves the above conclusion. The
nadir for all-cause premature death risk was estimated from RCS to be at
two live births, which was significantly lower than one live birth.
Also, the all-cause premature mortality of mothers with three or four
children was lower than mothers who had one child. Moreover, women
without child was signifcant increases in risk were observed for
premature all-cause death than women with one child. Although the data
for the women with five or more children was not significant, there is a
clear upward trend in the RCS curve. More specifcally, we prefer to
describe this nonlinear relationship with approximates U-shape where
women with none, one, or four children have higher all-cause premature
mortality than those with two or three children.

Sensitivity analyses did not affect the assessment of the relationship
between parity and all-cause premature mortality risk (Supplementary
Table 1). Similar results were observed after excluding participants
with less than 1 and 2 years of follow-up, respectively. To avoid the
possible influence of biochemical indicators on the results, we repeated
our analyses by adjusting the covariate biochemical indicators
additionally. The results were barely changed. The results of furthur
adjusting for covariates dietary factors showed the conclusion remains
alomost the same.

\textbf{Association between the number of live births and hazard of
all-cause premature mortality stratied by potential risk factors}

We also conducted stratified analyses according to the potential risk
factors including age (born year), race, BMI, Townsend deprivation
index, smoking status, moderate drinking, diabetes, hypertension,
asthma, emphysema and chronic bronchitis in Supplementary Table 2. The
association of parity with hazard of all-cause premature mortality
appeared was not significant in Other ethnic group participants (P-trend
= 0.447), where the protective effect of mothers with double children on
all-cause premature death had disappeared (HR\textsubscript{2}=1.02,
95\% CI: 0.31-3.31). We also found the harmful effects of the
nulliparous women on all-cause premature death had become not
significant in obese participants (BMI[?] 30 kg/m\textsuperscript{2})
(HR\textsubscript{0}=1.12, 95\% CI: 0.99-1.27). Notably, the observed
significant association of the number of live births with hazard of
all-cause premature mortality appeared to be abolished in
current-smokers (P-trend = 0.003) and overdrinker (P-trend = 0.114).
Meanwhile, the chronic diseases such as diabetes, asthma, emphysema and
chronic bronchitis also had an impact on the relationship between parity
and all-cause premature mortality. We did not find significant
interactions between other potential confounders and the number of live
births on hazard of all-cause premature mortality.

\textbf{Association between the number of live births and hazard of
cause-specific premature mortality}

The results of the multivariate Cox proportional hazard regression
models between the number of live births and hazard of cause-specific
premature mortality are presented in Supplementary table 3. We
documented 1552 incident cases of premature mortality of cardiovascular
disease (CVD) and 6878 incident cases of cancer-specific premature
mortality during follow-up. After adjustment for multiple covariates,
compared with the reference group, we found that the women with two,
three and four childern had lower risk of CVD-specific premature
mortality (HR\textsubscript{2}=0.69, 95\% CI: 0.60-0.80,
HR\textsubscript{3}=0.71, 95\% CI: 0.60-0.84, HR\textsubscript{4}=0.78,
95\% CI: 0.62-0.99); the female who gave two or three births had lower
risk of premature mortality of coronary heart disease (CHD)
(HR\textsubscript{2}=0.71, 95\% CI: 0.55-0.91, HR\textsubscript{3}=0.68,
95\% CI: 0.51-0.91) and the female with three childern had lower risk of
stroke-specific premature mortality (HR\textsubscript{3}=0.66, 95\% CI:
0.48-0.91). Compared to the reference group, the childless women had
higher risk of cancer-specific premature mortality
(HR\textsubscript{0}=1.16, 95\% CI: 1.07-1.27); the women with four
childern had lower risk of premature mortality of breast cancer
(HR\textsubscript{4}=0.55, 95\% CI: 0.39-0.79); the female without
childbirth history had higher risk of premature mortality of ovarian
cancer (HR\textsubscript{0}=1.37, 95\% CI: 1.02-1.83), and the female
who gave three births had lower risk of premature mortality of ovarian
cancer (HR\textsubscript{3}=0.71, 95\% CI: 0.52-0.98); and the women
with five or more children had higher risk of premature mortality of
cervical cancer (HR\textsubscript{5}=8.01, 95\% CI: 1.08-59.60).

\textbf{Association between the number of live births and estimated life
expectancy}

We estimated the lower or higher survival time (years) due to the
different parities, as shown in Figure 1. At age 40, childless women had
an average 1.41 (95\% CI: 0.78--2.01) lower years of life expectancy,
and women with two, three, or four had an average 1.10 (95\% CI:
0.63--1.74), 1.00 (95\% CI: 0.54--1.74), and 1.00 (95\% CI: 0.05--1.84)
higher years of life expectancy, respectively, as compared with women
who had one child. The corresponding lower years of life expectancy at
the age of 60 years were 1.20 (95\% CI: 0.66--1.71) years in unproduced
women, and the corresponding higher years of life expectancy at the age
of 60 years were 0.97 (95\% CI: 0.56--1.52), 0.88 (95\% CI: 0.48--1.52),
and 0.79 (95\% CI: 0.05--1.61) years in women who gave two, three, or
four births, respectively.

\textbf{Association between the number of live births and aging}

The estimated values of FI, \selectlanguage{greek}Δ\selectlanguage{english}KDM-biological age and HD for each pairty
after multiple covariates corrections calculated using a general linear
model are presented in a box plot in Figure 2, which shows the results
of the relationship between the number of live births and biological
aging. As shown in Figure 2 and Supplementary table 4, the estimated FI,
\selectlanguage{greek}Δ\selectlanguage{english}KDM-biological age and HD box charts for two or three live births are
located at the lowest position, while the corresponding box charts for
five or more live births are located at the highest position; and the
corresponding box charts for zero, one, and four live births is located
between these above. In other word, the estimated values of FI,
\selectlanguage{greek}Δ\selectlanguage{english}KDM-bioage and HD adjusted for multiple covariates of mothers with two
or three children were lower, and the correspondings of mothers with
five or more children were higher, comparied with females who had one
children (all P \textsubscript{for trend}<0.001).

\textbf{Discussion}

In this prospective study of 272494 participants from UK Biobank, we
found that compared with those who had only one child, childless women
had the higher all-cause premature mortality and the lower years of life
expectancy, whereas those with two, three, or four children had the
lower all-cause premature mortality and the higher years of life
expectancy. And these associations were independent of biological
factors, lifestyle, socioeconomic level, and pre-existing diseases.
Similarly, this study found that the relationship between parity and
all-cause premature mortality was also observed in sensitivity analyses,
demonstrating the robustness of the results. Moreover, comparied with
women who had one child, the estimated values of FI, \selectlanguage{greek}Δ\selectlanguage{english}KDM-biological age
and HD adjusted for multiple covariates in women with two or three
children were lower, and the correspondings in females with five or more
chilldren were higher.

Our study found that the childless women had the higher all-cause
mortality, and women who had two, three, or four children had the lower
all-cause mortality, compared to women with one child, which are similar
with the results reported in a Sweden
population\textsuperscript{{[}13{]}}. Differently, the relationship
between five or more live births and all-cause premature mortality was
significant in the Sweden population. Although the correspondings
relationship in our study was not significant, there is also a clear
upward trend in the RCS curve, which may be attributed to the more
covariates we have corrected. The finding in subgroup analyses suggested
that association between the number of live births and hazard of
all-cause premature mortality appeared to be different among different
races, which may be attributed to the genetic reasons of race being a
potential factor affecting this relationship. In addition, obesity,
current-smoking, and excessive alcohol consumption mask the relationship
between parity and all-cause premature mortality, possibly due to the
fact that obesity\textsuperscript{{[}33,34{]}},
smoking\textsuperscript{{[}35{]}}, and alcohol
consumption\textsuperscript{{[}36{]}} themselves can cause a series of
physiological changes, damage health, and even lead to premature death.
For example, the obese persons are more likely to experience metabolic
changes during pregnancy than their normal weight
counterparts\textsuperscript{{[}37,38{]}}. And in obese individuals,
lipids, oxidized LDL particles, and free fatty acids activate the
inflammatory process and trigger the atherosclerosis and
CVD\textsuperscript{{[}39-40{]}}; and obesity leads to changes in the
structure and function of the heart\textsuperscript{{[}41{]}}, leading
to heart failure\textsuperscript{{[}42{]}}, atrial
fibrillation\textsuperscript{{[}43,44{]}} and sudden cardiac
death\textsuperscript{{[}45{]}}. Similarly,the chronic diseases also had
an impact on the relationship between parity and all-cause premature
mortality.

In addition, our study provides novel evidence to show the relationship
between parity and mortality. Our results on the cause-specific
premature mortality indicate that the hazard of all-cause premature
mortality associated with more number of live births could be partly
attributed to CVD-specific and cancer-specific premature mortality. Such
observations are consistent with previous evidence linking parity with
various conditions including cardiovascular
disease\textsuperscript{{[}46{]}} and cancer\textsuperscript{{[}47{]}}.
For the subtypes of CVD-specific premature mortality, we found that
higher number of live births was significantly associated with lower
hazard of CHD-specific and stroke-specific premature mortality, compared
with women with one child. These observations were supported by the
results from the parity and stroke study, and the parity and coronary
heart diseases study, in which parity may confer a moderate long-term
protective effect on the risk of subarachnoid hemorrhage
(SAH)\textsuperscript{{[}48,49{]}} and CHD\textsuperscript{{[}50{]}}.
Future investigations are warranted to explore the association of the
number of live births with various cardiovascular disease subtypes. In
addition, evidence from experimental and epidemiological studies has
shown that parity was related to breast
cancer\textsuperscript{{[}51-53{]}}, ovarian
cancer\textsuperscript{{[}53,54{]}}, cervical
cancer\textsuperscript{{[}55{]}}. We found that nulliparous women had
the highest hazard of all-cause premature mortality, which be partly
attributed to the continuous stimulation of ovarian hormones to the body
of nulliparous women may increases the cancer-specific premature
mortality, especially breast cancer and ovarian
cancer\textsuperscript{{[}5,6{]}}, and further increases the all-cause
premature mortality of nulliparous women.

For the first time, we reported that childless women was associated with
the lower life expectancy at the age of 40 years by 1.41 (95\% CI:
0.78--2.01) years for women, and women with two, or three or four
children had an average 1.10 (95\% CI: 0.63--1.74), 1.00 (95\% CI:
0.54--1.74), 1.00 (95\% CI: 0.05--1.84) higher years of life expectancy,
respectively, compared with participants who had one child. Meanwhile,
we found that accelerated biological aging and functional decline were
potential influencing factors, as the estimated values of FI,
\selectlanguage{greek}Δ\selectlanguage{english}KDM-biological age and HD adjusted for multiple covariates have
significant changes. Our research is similar with the changes in HD
caused by parity in previous articles, giving rise to the U-shape for
the overall relationship between parity and biological
aging\textsuperscript{{[}56{]}}. Moreover, we also found that women who
gave two or three births were the least likely to age, while women with
five or more children are the most likely to age, which can be
attributed the fact that reproduction can consume a large part of
resources, reducing the efforts invested in the maintenance and
repairment of somatic tissues, and then leading to aging and death in
women\textsuperscript{{[}57-60{]}}. In addition, studies have shown that
the social and psychological pressure caused by women's by high parity
may be another potential factor accelerating biological aging and
functional decline\textsuperscript{{[}61{]}}.

The present findings may have several public health implications. First,
the evidence is complementary to those on the association between the
number of live births and all-cause mortality and fills the gap in the
relationship between parity and all-cause premature mortality, life
expectancy, and aging. Second, the evidence may inform the
recommendations on behavioral changes regarding reproduce. The parity is
easily assessed in clinical and public settings, and may be useful for
future reproduce interventions.

Although our study have some advantages including the large sample size,
the extensive covariate correction, and the consistent results in
several sensitivity and subgroup analyses, several potential limitations
should be carefully considered in this study. Firstly, we could not
exclude the possibility that high number of live births is a marker for
a lower socioeconomic level. However, subgroup analyses indicated that
the positive association between the number of live births and hazard of
mortality was consistent across the subgroups of socioeconomic level.
Secondly, in this study we obtained maternal live births by questioning
``How many children have you given birth to? (Please include live births
only) '' Because this question did not include the number of
stillbirths, spontaneous miscarriages or termination that women may have
had previously, we could not obtain specific date associated with these
situations. As described earlier, if the number of births affects
long-term health conditions, the number of stillbirths, spontaneous
miscarriages or termination will also be an important source of
information. We need a further study including these basic facts in
order to investigate the effects of number of stillbirths, spontaneous
miscarriages or termination on long-term health. Thirdly, although we
controlled for many socioeconomic factors and lifestyle factors, we
lacked explicit information on marital status, on age at first birth ,
and on attitudes and values that may be associated with both fertility
and health. These unmet covariates may affect the relationship between
parity and all-cause premature death. Fourthly, an important limitation
of this study is that the UK Biobank is not representative of the
general population due to the voluntary
participation\textsuperscript{{[}24{]}}. Further studies are needed to
conirm our findings, especially in populations that are more
representative of the UK population.

In conclusion, our study indicates that the relationships between the
number of live births and hazard of all-cause premature mortality, life
expectancy, and aging. obesity, current-smoking, and excessive alcohol
consumption may affect the association between the parity and all-cause
premature mortality. Further clinical trials are warranted to validate
these findings.

\textbf{Abbreviations}

HR: Hazard ratio; CI: Confidence interval; SD: Standard deviation; BMI:
Body mass index; FI: frailty index; HD: Homeostatic disorder; CVD:
Cardiovascular disease; CHD: coronary heart disease; MET: Metabolic
Equivalent Task; RCS: restricted cubic spline; ICD: International
classification of disease.

\textbf{Acknowledgments}

This research has been conducted using the UK Biobank Resource
(applicationID:103547). We thank the participants in the UK Biological
Sample Library and UKB's research team for their generous contributions
to creating an important research resource.

\textbf{Funding}

This work was supported by National Natural Science Foundation of China
{[}62102121 to D.Z.{]}.

\textbf{Author contributions}

D.Z. had full access to all of the data in the study and takes
responsibility for the integrity of the data and the accuracy of the
data analysis. D.Z., H.G., and W.W. conceived and designed the
experiment. H.G. performed the analysis with assistance and guidance
from Y.L., R.Y. contributed to data quality control of UKB data. H.G.,
D.Z., and W.W. wrote the manuscript with the participation of all
authors.

\textbf{Competing interests}

The authors declare that they have no competing interests.

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\textbf{Figure legend}

Figure 1: The estimates of cumulative survival time from 40 years of age
onward among women with distinct number of live births.

Figure 2: Frailty index, \selectlanguage{english}^KDM-biological age, HD adjusted for multiple
covariates. Adjusted covariates included age, race, education, Townsend
deprivation index, BMI, smoking statues, drink, moderrate activity,
diabetes, hypertension, asthma, emphysema and chronic bronchitis, use of
oral contraceptive pills, history of stillbirth, spontaneous miscarriage
or termination, and menarche, age at menopause (last menstrual period),
length of menstrual cycle at baseline.

Supplementary Figure 1: Flow chart of study population.

Supplementary Figure 2: RCS analysis of the relationship between the
number of live births and premature all-cause mortality. The model was
adjusted for age, race, education, Townsend deprivation index, BMI,
smoking statues, drink, moderrate activity, diabetes, hypertension,
asthma, emphysema and chronic bronchitis, use of oral contraceptive
pills, history of stillbirth, spontaneous miscarriage or termination,
and menarche, age at menopause (last menstrual period), length of
menstrual cycle at baseline.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/fig1/fig1}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/fig2/fig2}

\end{center}
\end{figure}

\textbf{Hosted file}

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