The effect of adverse pregnancy outcomes on early vascular aging in young women:The Kailuan Study

doi:10.21203/rs.3.rs-1724369/v1

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The effect of adverse pregnancy outcomes on early vascular aging in young women:The Kailuan Study

https://doi.org/10.21203/rs.3.rs-1724369/v1

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published 07 Feb, 2023

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Backgroud: Adverse pregnancy outcomes (APOs) are at increased future cardiovascular risk and require effective risk mitigation. However, data regarding appropriate postpartum screening for young women with APOs are lacking. We aimed to investigate the association between APOs and early vascular aging (EVA) in young women.

Methods: Women who gave birth from 1990 to 2020 and underwent brachial-ankle pulse wave velocity (baPWV) assessments in the postpartum period were recruited. We excluded women with age≥50 years at the baPWV assessment or missing postpartum health examinations. The history of APOs including hypertensive disorders of pregnancy, gestational diabetes, preterm delivery and low birth weight were assessed by medical records. EVA was defined as baPWV above the 90th percentile for different age group. Multivariable Logistic regression was used to evaluate the association of APOs and EVA.

Results: 3,193 participants were included in the analysis, including 912 (28.6%) individuals with APOs. The detection rates of EVA in the non-APO group and the APOs group were 7.19% (164) and 13.9% (127), respectively (P<0.05). Compared with non-APO group, the OR (95% CI) of APO-induced EVA was 1.67(1.29-2.16). The risks in the 20-29, 30-39, and 40-49 age groups were 2.51 (1.13-5.59), 1.83 (1.30-2.59), and 1.35 (0.82-2.21) (P for trend <0.05).

Conclusions: APOs are risk factors of EVA for young women and the risk decreased with increasing age. EVA should be an important indicator for preventive cardiovascular risk management in young women with APOs.

Clinical trial registration

registration number ChiCTR-TNRC-11001489 http://www.chictr.org.cn/showproj.aspx?proj=8050

What is known about topic

Women with adverse pregnancy outcomes have increased risks of post-pregnancy hypertension and cardiovascular diseases.
Guidelines suggest that women with adverse pregnancy outcomes should be monitored and screened, yet other than the traditional risk factors, they do not indicate specific monitoring indicators and appropriate screening ages.

What this study adds

Women with a history of adverse pregnancy outcomes have a higher risk of early vascular aging and the risk decreased with increasing age.
A healthy lifestyle including ideal sleep, an ideal BMI, a low-salt diet, and exercise can slow the progression of vascular aging.
Early vascular aging should be used as a screening indicator for ASCVD risk in women with adverse pregnancy outcomes and that the first screening should be performed between the ages of 20-29 years.

Adverse pregnancy outcomes (APOs), including hypertensive disorders of pregnancy (HDP), gestational diabetes (GD), preterm birth, and intrauterine growth restriction, are common, occurring in 10–30% of pregnancies worldwide [1, 2]. APOs are not only a major factor in perinatal maternal and infant mortality, but also a risk factor for future cardiovascular risk factors profile in women [3] and the development of atherosclerotic cardiovascular disease (ASCVD) [4] and peripheral vascular diseases [5]. A study by Søndergaard et al. [6] confirmed that APOs increased the risk of ASCVD in women by 23–38%. In line with these and previous population-based studies from more than 2 decades ago [7], the American Heart Association recommends including a history of APOs in the risk assessment of ASCVD in women [8, 9] and as one of the bases for intensive statin therapy [10]. The European Cardiology Association Guidelines for Cardiovascular Diseases Prevention in Women and the Expert Consensus on Cardiovascular Diseases Prevention in Chinese Women both listed APOs as major risk factors for cardiovascular diseases in women [11, 12].

Although previous studies have confirmed that APOs are risk factors for ASCVD in middle-aged and elderly women [4], the mechanisms linking APOs to future ASCVD in women remain uncertain. Current used risk evaluators are inadequate in assessing cardiovascular disease in premenopausal women after APOs [13]. Early vascular aging (EVA) was proposed by Nilsson in 2008 [14]. The risk factors for EVA include genetics, environment, inflammation, oxidative stress, endothelial dysfunction, hypertension, and abnormal glucose and lipid metabolism [15–21]. Protective factors include a reduction in salt intake, regular physical exercise, weight control, and a reduction in alcohol intake [22, 23]. Bruno et al. [24] found that women accounted for 71.3–85.3% of the EVA population despite women having fewer traditional risk factors and that APOs are early exposures unique to women. Therefore, we speculate that APOs may be important risk factors for EVA in women. In addition, healthy lifestyle may reduce the impact of APOs on EVA. To confirm this hypothesis, we used data from the Kailuan cohort to investigate the effects of APOs and healthy behaviors on EVA.

2.1 Study participants

Our study participants were from the Kailuan study (registration number ChiCTR-TNRC-11001489 http://www.chictr.org.cn/showproj.aspx?proj=8050). The Kailuan study is a large prospective cohort study investigating cardiovascular disease (CVD) risk factors and interventions in functional community populations. The study started in 2006 and conducts follow-ups every 2 years. In addition to routine follow-ups, information on childbirth and pregnancy complications are obtained through hospitalization medical records. Since 2010 (the 2nd follow-up visit), the brachial-ankle pulse-wave velocity (baPWV) test has been performed on part of the Kailuan study population. We selected the population with complete childbirth information who had completed the baPWV test as the study participants. For women giving multiple births, if there was only once occurrence of APO, the data for the delivery at that time would be taken; if the APO occurred twice or more, the data for the earliest APO occurrence would be used; if no APO occurred for each delivery, the data for the first delivery would be used. The inclusion criteria were as follows: (1) individuals who gave birth between January 1990 and December 2020 and had complete childbirth data; (2) Women who participated in the baseline (2006) or follow-up study of the Kailuan study; (3) individuals who completed the baPWV test after childbirth; and (4) individuals who agreed to participate in this study and signed the informed consent form. The exclusion criteria were as follows: (1) individuals aged ≥ 50 years at the time of the baPWV test; and (2) individuals with missing physical examination data after childbirth.

2.2 Data collection

2.2.1 Collection of childbirth data

Using the date of childbirth and the hospital provided by the participant on the questionnaire survey, the following childbirth data were obtained from hospitalization medical records by medical staff who received uniform training: maternal information such as previous history of hypertension and medication, history of diabetes and medication, age, time, and methods of childbirth delivery, blood pressure before and after delivery, height, and body weight; information about the newborns such as neonatal sex, gestational age, weight, body length, and survival conditions; laboratory test results (including platelet count, fasting blood glucose (FBG), and urinary protein); auxiliary examination (including electrocardiogram (ECG) and obstetrical B-mode ultrasound); and maternal and neonatal complications.

2.2.2 Collection of health examination data

The contents of the epidemiological survey and the anthropometric indicators were described in a study previously published by our group [25]. Biochemical index tests were conducted on the day of the physical examination from 7:00 to 9:00; 5 mL of fasting blood was drawn from the cubital vein, and the serum was isolated and retained. Using the same blood sample, concentrations of FBG, total cholesterol, triglycerides, LDL-C (low-density lipoprotein cholesterol), HDL-C (high-density lipoprotein cholesterol), and hs-CRP (high-sensitivity C-reactive protein) were measured by auto analyzer (Hitachi 747; Hitachi, Tokyo, Japan).

2.2.3 BaPWV Measurement

baPWV was measured using a BP-203RPEIII networked vascular screening device manufactured by Omron Healthcare (China) Co., Ltd. Before measurement, the participants were instructed not to smoke and to rest for more than 5 min. At the beginning of the test, the participants rested quietly in a supine position with the pillow removed. The hands were placed palms up on either side of the body. Sphygmomanometer cuffs were wrapped around the upper arm and ankles. The cuff balloon mark on the upper arm was aligned with the brachial artery, and the lower edge of the cuff was 2–3 cm from the cross-striation of the cubital fossa. The cuff balloon mark on the lower limb was located on the medial lower limb, and the lower edge of the cuff was 1–2 cm from the medial malleolus. One heart sound detector was placed at the left edge of the sternum. The measurement was repeated twice for each participant, and the second data point was used as the final result. The maximum of left and right sides of baPWV was used for analysis.

2.3 Relevant definitions and diagnostic criteria

2.3.1 EVA

Reference population: To determine the cutoff value for EVA, previous research methods were used as references [24]. A total of 52,302 individuals in the Kailuan study who underwent physical examinations from 2010–2018 and completed the baPWV measurement during the same period were selected. Twelve individuals with missing baPWV measurements or outliers, 1,024 individuals with a previous history of CVD, 1,224 individuals with missing relevant covariates, 36,174 men and 5,415 individuals aged ≥ 50 years at the time of the baPWV measurement were excluded; ultimately, 8453 women were used as the reference population (Fig. 1).

Participants were divided into the following age groups: 20–29, 30–39, and 40–49 years. baPWV above the 90th percentile was used as the reference value for each age group. EVA was defined as baPWV above the 90th percentile for each age group [26].

The attached Table 1 defines EVA based on the baPWV value for different age groups within the reference population.

Table 1

Cutoff Values for Early Vascular Aging According to Different baPWV Percentiles in the Reference Population (cm/s)
Age group^*, y	n	75th	90th	97.5th
20–29	844	1204	1299	1463
30–39	3169	1264	1382	1552
40–49	4440	1398	1548	1795
baPWV, brachial-ankle pulse-wave velocity.^*Age when measuring baPWV.

2.3.2 Healthy behaviors

(1) Salt intake: Ideal salt intake was defined as < 6 g/d, and nonideal salt intake was defined as ≥ 6 g/d. Salt intake was derived from the answer to the questionnaire on salt preference, with response options of “light (< 6 g/d)”, “fair (6–10 g/d)”, or “salty (> 10 g/d)”.

(2) Physical exercise: Ideal exercise was defined as ≥ 80 min/week (often), and nonideal exercise was defined as < 80 min/week (never or occasionally). Physical exercise was derived from the answer to the questionnaire on physical exercise, with response options of “often”, “occasionally”, or “never”.

(3) Body mass index (BMI): The ideal BMI was defined as < 25 kg/m², and the nonideal BMI was defined as ≥ 25 kg/m².

(4) Sleep time (h/day): The ideal sleep time was defined as 6 h < sleep time < 8 h, and nonideal sleep time was defined as ≤ 6 h or ≥ 8 h.

Healthy behavior score: Ideal healthy behavior was scored as 1 point, and nonideal healthy behavior was scored 0 points [27].

2.3.3 APOs

APOs were defined as the presence of 1 or more of the following 4 diseases:

(1) HDP: 1) gestational hypertension – hypertension occurring for the first time after 20 weeks of pregnancy, with SBP ≥ 140 mmHg and/or DBP ≥ 90 mmHg and a negative proteinuria test; 2) preeclampsia-eclampsia – after 20 weeks of pregnancy, the SBP ≥ 140 mmHg and/or DBP ≥ 90 mmHg, accompanied by a positive urine protein test; and 3) pregnancy with chronic hypertension – patients with a history of hypertension or SBP ≥ 140 mmHg and/or DBP ≥ 90 mmHg before 20 weeks of pregnancy, with no significant aggravation during pregnancy or manifestation of acute severe hypertension [28];

(2) GD: FBG higher than or equal to 5.1 mmol/L occurring for the first time during pregnancy [29];

(3) Preterm birth: neonate with a gestational age less than 37 weeks at birth [30]; and

(4) Low birth weight: neonate with a birth weight < 2,500 g [30].

2.4 Statistical methods

Statistical analysis was performed using SAS 9.4. Normally distributed measurement data are expressed as the mean ± standard deviation (x̅ ±ན). Analysis of variance (ANOVA) was used for intergroup comparisons. Measurement data with a skewed distribution are represented by M (P₂₅, P₇₅), and intergroup comparisons were performed using the rank sum test. Count data are represented as percentages (%), and intergroup comparisons were performed using the χ² test. We selected the first physical examination data after childbirth as the baseline. The effect of APOs on EVA was analyzed using a multivariate logistic regression model. With APOs as the independent variable and EVA as the dependent variable, 3 models were established. Model 1 was a single-factor model, Model 2 was additionally adjusted for age, heart rate, hs-CRP, LDL-C, BMI, education level, salt intake, and physical exercise during the same period as the baPWV measurement, and Model 3, on the basis of Model 2, further adjusted for mean arterial pressure (MAP) and antihypertensive drugs during the same period as the baPWV measurement. To further investigate the impact of APOs in different age groups on EVA and whether healthy behaviors can alleviate the impact of APOs on EVA, we performed subgroup analysis: (1) the participants were divided into age groups, i.e., 20–29, 30–39, and 40–49 years; (2) the participants were divided into ideal and nonideal groups according to individual health behaviors; and (3) the participants were divided into groups according to the total scores, i.e., 0, 1, 2, and 3–4, for the 4 health behaviors to analyze the effect of APOs on EVA. P < 0.05 (bilateral) was considered statistically significant. Missing values of covariates were imputed using the multiple imputation method.

To date, no uniform standard definition of EVA has been established. To improve the robustness of the study results, we used the 75th percentile and 97.5th percentile of the baPWV of each age group of the reference population to define EVA and reperformed the statistical analysis. In addition, we further excluded women with multiple childbirths or women with chronic hypertension or diabetes mellitus for the sensitivity analysis and reexamined the effect of APOs on EVA. P < 0.05 (two-sided) was considered statistically significant.

3.1 Participants’ Characteristics

A total of 4,675 individuals had complete delivery data and gave birth from January 1990 to December 2020. Among them, 3,737 individuals completed the baPWV measurement during the postpartum period. A total of 267 individuals aged ≥ 50 years at the time of the baPWV measurement and 277 individuals with missing postpartum physical examination data were excluded (Fig. 2). Ultimately, 3,193 participants were included in the analysis, including 912 (28.6%) individuals with APOs, 723 (22.6%) of whom had a single APO, while 133 (4.17%), 53 (1.66%), and 3 (0.09%) had 2, 3, and 4 APOs, respectively. The prevalence of HDP, GD, preterm birth, and low birth weight calculated separately were 16.8% (537), 9.46% (302), 5.92% (189), and 4.13% (132), respectively. Compared with the non-APO group, the APOs group had a significantly higher SBP, DBP, heart rate, BMI, FBG, LDL-C, TC, TG, proportion using antihypertensive drugs, and prevalence of hypertension and diabetes (P < 0.05). In the total population, the baPWV was 1211 ± 185 cm/s; the baPWV level in the non-APO group was lower than that in the APOs group (1197 ± 175 vs. 1245 ± 203 cm/s, Table 2).

Table 2

Characteristics According to Adverse Pregnancy Outcome (APO) Status during baPWV examination period
Variables	Non-APO (N = 2281)	≥ 1 APO (N = 912)	Hypertensive disorders of pregnancy (N = 537)	Gestational diabetes (N = 302)	Preterm delivery (N = 189)	Low birth weight (N = 132)
Age at delivery (y)	37.92 ± 6.04	37.62 ± 6.01	39.26 ± 5.97	34.31 ± 4.66	37.41 ± 6.06	37.44 ± 6.51
baPWV,cm/s	1197.14 ± 174.80	1245.15 ± 202.93	1281.22 ± 214.41	1214.92 ± 186.88	1218.05 ± 177.64	1205.28 ± 182.71
EVA, [n(%)]	164(7.19)	127(13.9)	85(15.8)	47(15.6)	21(11.1)	14(10.6)
SBP (mmHg)	113.84 ± 13.66	117.36 ± 14.81	119.59 ± 15.97	115.81 ± 13.14	115.97 ± 13.14	115.70 ± 13.39
DBP (mmHg)	73.25 ± 8.98	75.14 ± 9.67	77.33 ± 9.95	73.14 ± 9.06	74.37 ± 9.21	73.82 ± 9.84
Heart Rate (bpm)	74.62 ± 14.18	76.43 ± 13.01	76.22 ± 11.77	78.36 ± 14.97	75.51 ± 11.92	73.73 ± 15.38
BMI (kg/m²)	23.21 ± 3.37	24.07 ± 3.96	24.44 ± 3.94	24.00 ± 4.12	24.34 ± 4.23	23.99 ± 4.90
FBG (mmol/L)	5.01 ± 0.82	5.25 ± 1.31	5.26 ± 1.34	5.33 ± 1.22	5.36 ± 1.71	5.06 ± 1.09
HDL-C (mmol/L)	1.57 ± 0.47	1.52 ± 0.38	1.52 ± 0.37	1.50 ± 0.39	1.50 ± 0.41	1.55 ± 0.39
LDL-C (mmol/L)	2.41 ± 0.78	2.55 ± 0.80	2.51 ± 0.81	2.65 ± 0.79	2.57 ± 0.81	2.62 ± 0.79
Total cholesterol (mmol/L)	4.66 ± 0.94	4.71 ± 0.94	4.74 ± 0.89	4.72 ± 0.97	4.71 ± 1.00	4.72 ± 1.00
Triglycerides (mmol/L)	0.89(0.65–1.27)	0.93(0.66–1.42)	0.94(0.69–1.45)	0.99(0.64–1.52)	0.98(0.67–1.44)	0.93(0.65–1.50)
hs-CRP (mg/L)	0.98(0.40–2.23)	0.96(0.40–2.40)	1.06(0.42–2.47)	0.94(0.40–2.40)	1.16(0.43–2.60)	1.00(0.40–2.10)
Current dinker [n (%)]	102(4.47)	39(4.28)	19(3.54)	13(4.30)	13(6.88)	5(3.79)
Education level: college or more [n (%)]	1173(51.4)	448(49.1)	226(42.1)	176(58.3)	104(55.0)	62(47.0)
Light Salt^* [n (%)]	319(14.0)	125(13.7)	74(13.8)	36(11.9)	34(18.0)	16(12.1)
Physically active^†[n (%)]	270(11.8)	119(13.0)	79(14.7)	28(9.27)	18(9.52)	11(8.33)
Antihypertensive medication [n (%)]	43(1.89)	36(3.95)	31(5.77)	5(1.66)	7(3.70)	3(2.27)
Hypertension [n (%)]	156(7.12)	110(12.6)	88(16.8)	26(9.06)	18(10.2)	14(11.3)
Diabetes [n (%)]	46(2.05)	34(3.79)	20(3.77)	15(5.08)	9(4.84)	2(1.55)
Abbreviations: APO, Adverse Pregnancy Outcomes; baPWV, brachial-ankle pulse wave velocity; EVA, Early Vascular Aging; SBP, systolic blood pressure; DBP, diastolic blood pressure; BMI, body mass index; FBG, fasting blood glucose; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; hs-CRP, high-sensitivity C-reactive protein. ^* Light salt was defined as < 6 g/day according to the standard salt spoon in China. ^†Being physically active was defined as physical activity for ≥ 80 min/wk. The number of women with any APO does not equal the sum of each APO since some women had more than 1 APO.

3.2 Effect of APOs on EVA

The detection rate of EVA in the total population was 9.11% (291). The detection rates of EVA in the non-APO group and the APOs group were 7.19% (164) and 13.9% (127), respectively (P < 0.05). The detection rates of EVA in the HDP, GD, premature birth, and low birth weight groups were 15.8% (85), 15.6% (47), 11.1% (21), and 10.6% (14), respectively. Logistic regression model showed that compared with the non-APO group, the odds ratio (OR) (95% confidence interval (CI)) of the risk of developing EVA in the APOs group was 1.67 (1.29–2.16). Compared with the non-APO group, the OR values (95% CI) of the risk of EVA in the HDP, GD, preterm birth, and low birth weight groups were 1.76 (1.29–2.38), 2.07 (1.42–3.03), 1.42 (0.77–2.59) and 1.37 (0.83–2.27), respectively (Table 3).

Table 3

Association of Individual Adverse Pregnancy Outcomes (APOs) with early vascular aging
	Non-APO	≥ 1 APO	Hypertensive disorders of pregnancy	Gestational diabetes	Preterm delivery	Low birth weight
	(N = 2281)	(N = 912)	(N = 537)	(N = 302)	(N = 189)	(N = 132)
case,n(%)	164(7.19)	127(13.9)	85(15.8)	47(15.6)	21(11.1)	14(10.6)
Model1	1(referent)	2.08(1.63–2.67)	2.43(1.83–3.22)	2.38(1.68–3.37)	1.61(1.00-2.61)	1.53(0.86–2.73)
Model2	1(referent)	1.88(1.46–2.41)	2.18(1.63–2.91)	2.13(1.47–3.08)	1.43(0.80–2.57)	1.43(0.88–2.43)
Model3	1(referent)	1.67(1.29–2.16)	1.76(1.29–2.38)	2.07(1.42–3.03)	1.42(0.77–2.59)	1.37(0.83–2.27)
Abbreviations: APO, Adverse Pregnancy Outcomes; Model 1 is single factor model. Model 2 is adjusted for age at baPWV examination (year), heart rate (bpm), hs-CRP (< 1, 1–3, > 3 mg/L), LDL-C (mmol/L), BMI (kg/m²), education (college or more, yes/no), sodium intake (ideal/nonideal), and physical activity (ideal/nonideal).Model 3 is further adjusted MAP (mmHg), using antihypertensive medication. The number of women with any APO does not equal the sum of each APO since some women had more than 1 APO.

3.3 Effect of APOs on EVA after stratification by age

After adjusting for the same confounders as those in the main analysis, compared with non-APO group, the OR values (95% CI) of APO-induced EVA in the 20–29, 30–39, and 40–49 age groups were 2.51 (1.13–5.59), 1.83 (1.30–2.59), and 1.35 (0.82–2.21), respectively (P for trend < 0.05), as detailed in Table 4.

Table 4

Association of Individual Adverse Pregnancy Outcomes (APOs) with early vascular aging stratified by age.
Age group, y	baPWV,cm/s	Non-APO	≥ 1 APO	P for trend
				< 0.001
case/n		18/190	15/78
20–29	1130 ± 145	1(referent)	2.51(1.13–5.59)
case/n		91/1200	79/490
30–39	1182 ± 178	1(referent)	1.83(1.30–2.59)
case/n		55/891	33/344
40–49	1268 ± 185	1(referent)	1.35(0.82–2.21)
Abbreviations: APO, Adverse Pregnancy Outcomes; baPWV, brachial-ankle pulse wave velocity; Model is adjusted for age at baPWV examination (year), heart rate (bpm), hs-CRP (< 1, 1–3, > 3 mg/L), LDL-C (mmol/L), BMI (kg/m²), education (college or more, yes/no), sodium intake (ideal/nonideal), physical activity (ideal/nonideal),MAP (mmHg), and using antihypertensive medication.

3.4 The effect of APOs on EVA after stratification by healthy behavior

In the ideal sleep, BMI, physical exercise, and salt intake groups, compared with those in the non-APO group, the OR values (95% CI) of APO-induced EVA in the APOs group were 1.43 (0.89–2.30) 1.48 (1.06–2.07), 2.07 (0.98–4.33), and 0.92 (0.43-2.00), respectively. In the nonideal sleep, BMI, physical exercise, and salt intake groups, compared with those in the non-APO group, the OR values (95% CI) of APO-induced EVA in the APOs group were 1.75 (1.28–2.40) ,1.98 (1.28–3.07), 1.63 (1.23–2.16), and 1.77 (1.34–2.35), respectively. In the groups with health scores of 0, 1, 2, and 3–4, the OR values (95% CI) of APO-induced EVA were 2.62 (1.43–4.79), 1.57 (1.06–2.34), 1.22 (0.70–2.08), and 1.72 (0.65–4.56), respectively (P for interaction = 0.23), as detailed in Table 5.

Table 5

Association of Individual Adverse Pregnancy Outcomes (APOs) with early vascular aging stratified by health behaviors.
	case/n	Non-APO	≥ 1 APO	P interaction
Sleeping time^a				0.48
Ideal	92/1033	1(referent)	1.43(0.89–2.30)
non-ideal	199/2160	1(referent)	1.75(1.28–2.40)
BMI^b				0.26
Ideal	175/2264	1(referent)	1.48(1.06–2.07)
non-ideal	116/929	1(referent)	1.98(1.28–3.07)
Physical activity^c				0.85
Ideal	42/387	1(referent)	2.07(0.98–4.33)
non-ideal	249/2806	1(referent)	1.63(1.23–2.16)
Sodium intake^d				0.14
Ideal	37/441	1(referent)	0.92(0.43-2.00)
non-ideal	254/2752	1(referent)	1.77(1.34–2.35)
Health behavior score^e				0.23
0	67/503	1(referent)	2.62(1.43–4.79)
1	127/1535	1(referent)	1.57(1.06–2.34)
2	73/904	1(referent)	1.22(0.70–2.08)
3–4	24/251	1(referent)	1.72(0.65–4.56)
a: Model adjusted for age at baPWV examination(year), heart rate(bpm),hs-CRP (< 1, 1–3, > 3 mg/L),LDL-C(mmol/L),BMI(kg/m²),education(college or more, yes/no),sodium intake(ideal/nonideal),physical activity(ideal/nonideal), MAP(mmHg), Using antihypertensive drugs.
b: Model futher adjusted for sleeping time(ideal/nonideal) and excluded BMI(kg/m2).
c: Model futher adjusted for sleeping time(ideal/nonideal) and excluded physical activity(ideal/nonideal).
d: Model futher adjusted for sleeping time(ideal/nonideal) and excluded sodium intake(ideal/nonideal).
e: Model exclude sleeping time(ideal/nonideal),BMI(kg/m²),physical activity(ideal/nonideal),sodium intake(ideal/nonideal).

3.5 Sensitivity analysis

After redefining EVA based on the 75th percentile and 97.5th percentile of baPWV for each age group, the effect of APOs on EVA remained significant (Table S2). After excluding individuals with multiple childbirths, APOs remained a risk factor for EVA (Table S3). After excluding individuals with chronic hypertension or diabetes mellitus, the effect of APOs on EVA remained significant (Table S4).

Our important finding was not only the confirmation of APOs as a risk factor for EVA in young women, but also the finding that this risk is age-dependent, that is, the risk decreased with increasing age. More importantly, healthy behaviors can reduce the risk of APO-induced EVA.

Our study confirmed that APOs are risk factors for the development of EVA in women aged < 50 years with a low absolute risk of ASCVD. Compared with that in the non-APO group, the OR value (95% CI) for the occurrence of EVA in the APOs group was 1.67 (1.29–2.16). In addition, among different APOs, HDP and GD had the strongest role in increasing the risk of EVA, with OR values of 1.76 and 2.07, respectively. Although we did not find similar results, previous studies have reported that APOs are risk factors for the development of hypertension in women, with an OR (95% CI) of 2.4 (1.8–3.1) [31]. Because the degree of arterial stiffness is highly correlated with SBP, the increased risk of hypertension caused by APOs indirectly supports APOs as potential risk factors for arterial stiffness. In addition, Kaess et al. [32] and our previous study [33] found that the increase in arterial stiffness precede the increase in blood pressure and that arterial stiffness was the cause of hypertension. Therefore, APOs may induce hypertension by causing arterial stiffness.

We not only confirmed that APOs are a risk factor for EVA but also found that the increased risk of APO-induced EVA is age dependent. With increasing age, the risk of APO-induced EVA decreased from 2.51 in the 20- to 29-year age group to 1.35 in the 40- to 49-year age group. Our finding is similar to the observation that the risk of hypertension caused by APOs decreases with increasing age. Behrens et al. [34] found that the risk of hypertension caused by APOs decreased from 5.78 in the < 30-year age group to 2.26 in the ≥ 50-year age group. The increased risk of EVA and hypertension due to non-APOs with increasing age may be responsible for these findings.

Except for HDP and GD, we did not find that preterm birth or low birth weight alone was a risk factor for EVA. However, the risk of APO-induced EVA increases when the above 3 adverse outcomes are present concurrently (Table S5), which also suggests that the risk of APO-induced EVA may be dose-dependent. This finding is also similar to the increased risk of hypertension caused by APOs [31].

A healthy lifestyle is the cornerstone of the prevention of and improvements in chronic noncommunicable diseases. Our study verified the importance of a healthy lifestyle. Although the 4 health factors all reduced the risk of APO-induced EVA, the effect of low salt was more pronounced, which is consistent with the strong association between salt and arterial stiffness. A meta-analysis confirmed that restricting salt intake can reduce arterial stiffness [35]. Previous studies showed that a high-salt diet reduced the expression of endothelial nitric oxide synthase [36] and damages the glycocalyx sodium barrier of vascular endothelium [37], which in turn increases vascular stiffening.

Because MAP and the use of antihypertensive drugs are closely associated with arterial stiffness, in addition to adjusting for traditional confounding factors, we also further adjusted for the above factors to increase the reliability of the study results. Since no uniform standard for the definition of EVA has been established, we redefined EVA using different percentiles and found that APOs remained a risk factor for EVA in young women (see Table S2). In addition, the risk of APO-induced EVA remained significant after limiting the study population to women who had a single delivery (Table S3) or excluding women with chronic hypertension or diabetes mellitus (Table S4).

Although we observed that APOs were a risk factor for EVA in young women, we were unable to elucidate the mechanism because this was an observational study. Possible mechanisms based on previous studies and our own data are : stress test in pregnancy caused by APOs that do not stop after delivery, such as inflammatory response [38], postpartum metabolic abnormalities, sympathetic nerve excitation, and elevated soluble vascular endothelial growth factor to placental growth factor ratio [39]. In addition, the risk factors for APOs, including low socioeconomic level, prepregnancy overweight, hypertension, and abnormal glucose and lipid metabolism, are also risk factors for EVA.

Strengths: 1. APOs were diagnosed based on medical records rather than recall in this study, which yielded more accurate data. Stuart et al. [40] confirmed that the sensitivity of recalled APO history was low. EVA is the result of direct vascular damage caused by various risk factors, including APOs, and is more direct and reliable than evaluations of other risk factors. 2. This study used baPWV, a non-invasive, inexpensive and clinically convenient measure that correlates well with carotid-femoral pulse-wave velocity (cfPWV), as a measure of EVA. 3. The population of this study was young women, which was not conducive to the analysis of the effect of APOs on ASCVD but beneficial to analyze the effect of APOs on EVA.

Limitations: 1. This study lacked prepregnancy baPWV data; therefore, we could not determine whether APOs were the cause of EVA. 2. This study did not include placental abruption and stillbirth. 3. This study did not include the type of exercise. 4. This study did not use 24-hour urinary sodium excretion to estimate daily salt intake, but we randomly selected 231 people from the Kailuan cohort to conduct a confirmatory study. The results revealed a significant dose–response relationship between self-reported salt intake and estimated 24-hour urinary sodium excretion [41]. Previous studies have also found that self-reported salt intake can predict actual salt intake [42].

Conclusion

Adverse pregnancy outcomes have a substantial impact on the risk of early vascular aging and early vascular aging should be an important indicator for preventive cardiovascular risk management in young women.

Data Availability Statement

De-identified data are available to researchers upon request by contacting with the corresponding author.

Acknowledgments

We thank all the survey teams of the Kailuan study group for their contribution and the study participants who contributed their information. All authors revised and approved the article as submitted.

Funding

None.

Ethical Approval

This study complied with the Declaration of Helsinki and was approved by the Ethics Committee of Kailuan General Hospital.

Competing Interests

None.

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There is NO conflict of interest to disclose.

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The effect of adverse pregnancy outcomes on early vascular aging in young women:The Kailuan Study

Status:

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Abstract

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Summary Table

1 Introduction

2 Methods

2.1 Study participants

2.2 Data collection

2.2.1 Collection of childbirth data

2.2.2 Collection of health examination data

2.2.3 BaPWV Measurement

2.3 Relevant definitions and diagnostic criteria

2.3.1 EVA

2.3.2 Healthy behaviors

2.3.3 APOs

2.4 Statistical methods

3 Results

3.1 Participants’ Characteristics

3.2 Effect of APOs on EVA

3.3 Effect of APOs on EVA after stratification by age

3.4 The effect of APOs on EVA after stratification by healthy behavior

3.5 Sensitivity analysis

4 Discussion

Declarations

References

Additional Declarations

Supplementary Files

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