Introduction
Pregnancy and childbirth are remarkable life-changing events, from personal, social, and biological perspectives. Motherhood is an extensive adaptation, altering behavior, motivation, and emotion in the service of offspring care. Such peripartum changes in brain function have been postulated as homeostatic mechanisms to mitigate the substantially elevated risk for the onset or exacerbation of psychiatric disorders in the postpartum period [
1‐
5].
Apart from functional changes, there is growing evidence that the maternal brain exhibits considerable structural plasticity in association with pregnancy and parturition [
6‐
8]. Studies using animal models provide evidence that pregnancy and parturition induce profound neurobiological changes on the maternal brain in rodents [
9‐
12]. However, few brain imaging studies have been performed to examine the structural brain changes that occur in women during pregnancy and the postpartum period. The few that do exist concluded that pregnancy is associated with a reduction of gray matter volume [
13,
14]. Hoekzema and collegues [
14] found that the observed postpartum reductions in specific regions of cortical gray matter remained evident two years after childbirth, suggesting that pregnancy can exert enduring structural changes on the human maternal brain. However, a study by Oatridge [
13] following a small sample of healthy pregnant women serving as a control group for women with pre-eclampsia throughout pregnancy and the early postpartum period showed that global brain volume decreased during pregnancy with a nadir around the time of delivery, followed by a return to pre-pregnancy global brain volume within six months postpartum. Additional support for increasing brain size during the early postpartum period comes from a longitudinal within-subject analysis comparing images acquired 2–4 weeks postpartum with those acquired 3–4 months postpartum, which demonstrated increases of cortical gray matter volume in multiple brain regions [
15]. A more recent study applied a machine learning algorithm to a longitudinal within-subject brain imaging dataset to estimate brain age in the first 2 days postpartum and again at 4–6 weeks postpartum, which revealed a “younger” brain age at 4–6 weeks postpartum [
16].
Taken together, the currently available data suggest a robust morphological plasticity of the human maternal brain during pregnancy and the early postpartum period. These changes are considered to be adaptive and essential for the mother-infant bonding and sensitive caregiving. However due to relatively short and differential postpartum periods in earlier studies, the nature of the relationship between pregnancy and childbirth with brain structure remains unresolved. Considering mounting evidence of the effects of neuroendocrine physiology on brain structure and function [
17,
18], it is plausible that pregnancy and childbirth might present a critical yet understudied factor that is crucial for understanding the brain processes over the life course. However, the impact of parenting behavior on the brain is also credible. Parenting is recognized to affect brain development of the offspring [
19], necessitating flexibility, skill acquisition and adaptation to environment, and is reciprocally affected by the inputs from the offspring [
15,
20,
21].
Therefore, we utilized data from the population-based Rotterdam Study cohort to investigate the long-term association of parity with global brain structure and vascular integrity. Advances in Magnetic resonance imaging (MRI) including Diffusion tensor imaging (DTI) methods allowed us to study the brain by integrating macrostructural morphological findings with information regarding white matter microstructural integrity. Therefore, we also investigated DTI metrics of white matter to explore if parity related to more subtle structural changes preceding macroscopic focal or global vascular alterations. Further, considering the relationship between parity and coronary heart disease and hemorrhage stroke [
22,
23], we also examined white matter lesions, brain infarcts and microbleeds which are considered to be potentially important imaging markers in relation to parity.
Results
In total, 2,834 women were included in the analyses. Of these, 441 were nulliparous (parity = 0) and 2393 were parous (parity > = 1). Further categorizing the group of parous women, 474 women were primiparous, 1697 women had 2–3 pregnancies, and 222 women had 4 or more pregnancies. The sample characteristics classified by parity are shown in Table
1.
Table 1
Group characteristics
Number, n | 441 | 474 | 1,697 | 222 |
Characteristics | | | | |
Age at time of MRI, years | 64.45 (11.51) | 62.93 (9.81) | 64.20 (10.42) | 69.08 (12.25) |
Age at first child, years | – | 27.56 (5.4) | 25.23 (4) | 23.96 (3.51) |
Married, ever. % (n) | 72 (288) | 97 (415) | 99 (1555) | 99 (199) |
Education, % (n) | | | | |
0 | 8 (35) | 12 (57) | 9 (148) | 14 (30) |
1 | 38 (168) | 52 (245) | 50 (854) | 43 (96) |
2 | 30 (131) | 19 (92) | 24 (405) | 31 (69) |
3 | 24 (105) | 17 (77) | 17 (284) | 13 (28) |
Body mass index, kg/m2 | 26.64 (4.83) | 27.03 (4.70) | 27.56 (4.52) | 28.05 (4.73) |
Smoking, n | | | | |
Never | 33 (146) | 37 (177) | 40 (684) | 51 (114) |
Past smoking | 47 (208) | 40 (191) | 44 (743) | 34 (76) |
Current smoking | 20 (87) | 22 (103) | 16 (264) | 13 (29) |
Brain volumes | | | | |
Total brain volume, ml | 905.99 (81.46) | 902.65 (83.42) | 900.88 (81.86) | 883.45 (94.44) |
Gray matter volume, ml | 505.65 (45.92) | 506.69 (43.09) | 507.93 (44.91) | 500.07 (50.20) |
White matter volume, ml | 393.22 (50.69) | 389.59 (52.46) | 387.05 (52.91) | 375.15 (10.40) |
Frontal lobe volume, ml | 85.48 (8.69) | 85.65 (8.43) | 85.86 (8.60) | 84.27 (9.87) |
Temporal lobe volume, ml | 58.81 (5.19) | 59.07 (5.05) | 59.00 (5.11) | 57.75 (5.62) |
Occipital lobe volume, ml | 31.66 (3.61) | 31.87 (3.25) | 31.93 (3.41) | 31.27 (3.52) |
Parietal lobe volume, ml | 49.92 (5.30) | 49.89 (4.85) | 50.16 (5.15) | 49.63 (5.60) |
Brain Microstructure | | | | |
Fractional anisotropy | 0.34 (0.02) | 0.34 (0.02) | 0.34 (0.01) | 0.34 (0.02) |
Mean diffusivity, 10–3 mm2/s | 0.75 (0.03) | 0.74 (0.03) | 0.74 (0.03) | 0.76 (0.04) |
Markers of cerebral small vessel disease | | | | |
White matter hyperintensity volume, ml | 7.12 (13.18) | 6.37 (11.59) | 5.90 (8.47) | 8.23 (10.40) |
Lacunar infarct (Y/N) | 4% | 6% | 6% | 7% |
Microbleed (Y/N) | 20% | 17% | 17% | 29% |
With respect to brain tissue volumes, we found that parity was associated with a larger global gray matter volume [adjusted mean difference (β) = 0.14, 95% confidence intervals (CI) = 0.09;0.19] (Tables
2,
3). This association persisted following adjustment for smoking, BMI, education, and history of marital status (β = 0.10, 95% CI = 0.04;0.17). We found no differences in white matter volume associated with parity. The relationship between gray matter volume and parity was consistent across temporal, frontal, occipital and parietal regions (Supplementary Table 1, Model I). These relationships were attenuated after adjustment for sociodemographic factors (Supplementary Table 1, Model II). No disproportionate lobar changes were found.
Table 2
Relationship between parity (parous/nulliparous) and structural brain imaging markers
Total brain volume | 0.08 (0.04;0.12) | 0.07 (0.03;0.12) |
Gray matter volume | 0.14 (0.09;0.19) | 0.11 (0.04;0.17) |
White matter volume | 0.00 (− 0.05;0.06) | 0.02 (− 0.04;0.09) |
Fractional anisotropy | 0.05 (− 0.04;0.15) | 0.03 (− 0.08;0.14) |
Mean Diffusivity | − 0.07 (− 0.14;0.00) | − 0.06 (− 0.14;0.02) |
White matter hyperintensity volume | − 0.01 (− 0.09;0.06) | − 0.00 (− 0.08;0.08) |
Lacunar Infarct | 0.02 (− 0.01;0.04) | 0.01 (− 0.01;0.04) |
Microbleed | − 0.01 (− 0.05;0.03) | 0.01 (− 0.04;0.05) |
Table 3
Relationship between the parity and structural brain imaging markers
| Beta (95% CI) | Beta (95% CI) | Beta (95% CI) |
Model I | | | |
Total brain volume | 0.07(0.02;0.12) | 0.09(0.05;0.13) | 0.07 (0.01;0.13) |
Gray matter volume | 0.10 (0.03;0.17) | 0.15 (0.09;0.21) | 0.15 (0.06;0.24) |
White matter volume | 0.01 (− 0.06;0.08) | 0 (− 0.06;0.06) | − 0.02 (− 0.11;0.07) |
Fractional anisotropy | 0 (− 0.12;0.12) | 0.08 (− 0.01;0.17) | − 0.01 (− 0.16;0.13) |
Mean Diffusivity | − 0.08 (− 0.17;0.00) | − 0.08 (− 0.15;− 0.01) | 0.00 (− 0.10;0.11) |
White matter hyperintensity volume | 0.03 (− 0.06;0.12) | − 0.03 (− 0.1;0.05) | − 0.01 (− 0.12;0.11) |
Lacunar Infarct | 0.02 (− 0.01;0.05) | 0.02 (− 0.01;0.04) | 0.02 (− 0.02;0.05) |
Microbleed | − 0.01 (− 0.06;0.04) | − 0.02 (− 0.06;0.02) | 0.05 (− 0.01;0.12) |
Model II | | | |
Total brain volume | 0.06(0.01;0.11) | 0.07 (0.03;0.12) | 0.09 (0.02;0.15) |
Gray matter volume | 0.08 (0.00;0.16) | 0.11 (0.05;0.18) | 0.13 (0.03;0.22) |
White matter volume | 0.02 (− 0.06;0.10) | 0.02 (− 0.05;0.09) | 0.02 (− 0.07;0.12) |
Fractional anisotropy | − 0.04 (− 0.17;0.09) | 0.06 (− 0.05;0.17) | − 0.03 (− 0.19;0.13) |
Mean Diffusivity | − 0.07 (− 0.17;0.03) | − 0.06 (− 0.15;0.02) | 0.01 (− 0.11;0.13) |
White matter hyperintensity volume | 0.02 (− 0.08;0.12) | − 0.01 (− 0.09;0.08) | 0.02 (− 0.11;0.14) |
Lacunar Infarct | 0.02 (− 0.01;0.06) | 0.01 (− 0.02;0.04) | 0.01 (− 0.03;0.05) |
Microbleed | 0.00 (− 0.06;0.06) | 0.00 (− 0.05;0.05) | 0.08(0.01;0.14) |
For analyses involving microstructural outcomes, mean diffusivity was lower in parous women (β = − 0.07, 95% CI = − 0.14;0.00). No relationships were observed between parity and fractional anisotropy in normal-appearing white matter (NAWM). There was also no relationship between parity and markers of cerebral small vessel disease, with the exception of an increase of microbleeds observed in multiparous (parity ≥ 4) women compared to nulliparous women [β = 0.07, 95% CI = 0.01;0.13] (Table
3, Model II).
We next examined whether the association between parity and brain structure might be differentially influenced by parity. Nulliparous women were considered as the reference group. The results showed a perceived incremental increase in the association between parity and gray-matter volume (Table
3, Model I in reference to nulliparous women; primiparous [β = 0.10, 95% CI = 0.03;0.17], multiparous women (parity: 2–3) [β = 0.15, 95% CI = 0.09;0.21], multiparous women (parity ≥ 4) [β = 0.15, 95% CI = 0.06;0.24]). However, there is no significant difference between primiparous and multiparous women (2–3, and 4 +). Furthermore, these associations attenuated after adjustment for sociodemographic factors (Table
3, Model II; primiparous [β = 0.07, 95% CI = ¬ 0.00;0.15], multiparous (parity = 2–3) [β = 0.12, 95% CI = 0.05;0.18], multiparous (parity ≥ 4) [β = 0.12, 95% CI = 0.02;0.22]). No other brain imaging marker studied exhibited an increase in association strength with respect to parity (Table
3).
Sensitivity analysis
In total, 894 women had information on pregnancy-related complications. Of these, 664 women reported no complications, and 230 women reported a history of complications during pregnancy. The subsample characteristics are shown in Table
4, stratified by pregnancy complications (parous without pregnancy complications, parous with pregnancy complications).
Table 4
Pregnancy-related complications: group characteristics
Number, n | 664 | 230 |
Characteristics | | |
Age at MRI, years; mean (SD) | 57.51 (6.48) | 57.65 (6.02) |
Age at first child, years | 25.88 (4.70) | 26.04 (4.67) |
Number of children | 2.08 (0.94) | 2.13 (0.81) |
Married % (n) | 98 (650) | 100 (230) |
Education % (n) | | |
0 | 10 (67) | 6 (14) |
1 | 42 (276) | 44 (102) |
2 | 23 (155) | 24 (56) |
3 | 25 (165) | 25 (57) |
Body mass index, kg/m2 | 26.89 (4.29) | 28.33 (5.48) |
Smoking, n | | |
Never | 35 (230) | 40 (91) |
Past smoking | 43 (287) | 43 (100) |
Current smoking | 22 (146) | 17 (38) |
Brain Volumes | | |
Total brain volume, ml | 927.18 (79.52) | 922.45 (82.96) |
Gray matter volume, ml | 517.69 (46.24) | 514.71 (43.67) |
White matter volume, ml | 401.11 (49.96) | 404.43 (52.45) |
Frontal lobe volume, ml | 88.08 (8,70) | 87.74 (8.42) |
Temporal lobe volume, ml | 60,31 (5.22) | 59.83 (5.02) |
Occipital lobe volume, ml | 32.65 (3.46) | 32.54 (3.20) |
Parietal lobe volume, ml | 50.96 (5.38) | 50.55 (4.88) |
Brain Microstructure | | |
Fractional anisotropy | 0.33 (0.01) | 0.33 (0.01) |
Mean diffusivity, 10–3 mm2/s | 0.74 (0.02) | 0.73 (0.02) |
Markers of cerebral small vessel disease | | |
White matter hyperintensity volume, ml | 3.22 (4.46) | 3.31 (6.01) |
Infarct (Y/N) | 3% | 4% |
Microbleed (Y/N) | 12% | 13% |
Evaluation of the subsample of women for whom information on pregnancy-related complications was available yielded differences exclusively in white matter between women with complications during pregnancy compared to parous women without pregnancy-related complications. Women with pregnancy-related complications exhibited larger white matter volumes (Table
5, Model I; β = 0.08, 95% CI = 0.01;0.16). This relationship attenuated after adjustment for smoking, BMI, and education (Table
5). Analysis of the relationship of parity with gray matter volume and MD showed similar effects as in the overall sample (Table
5, Model 1).
Table 5
Relationship between pregnancy complications and parity and structural brain imaging markers
Model I | | | |
Total brain volume | − 0.04(− 0.01;0.08) | 0.11(0.07;0.16) | 0.15(0.09;0.21) |
Gray matter volume | − 0.02 (− 0.11;− 0.05) | 0.14 (0.07;0.21) | 0.11 (0.02;0.20) |
White matter volume | 0.08 (0.01;0.16) | 0.05 (− 0.02;0.012) | 0.13 (0.05;0.22) |
Fractional anisotropy | − 0.04 (− 0.17;0.09) | 0.04 (− 0.15;0.08) | − 0.08 (− 0.23;0.07) |
Mean diffusivity | − 0.02 (− 0.11;0.06) | − 0.13 (− 0.21;-0.04) | − 0.15 (− 0.26;-0.04) |
White matter hyperintensity volume | 0.06 (− 0.03;0.15) | − 0.09 (− 0.18;0.00) | − 0.02 (− 0.14;0.09) |
Lacunar Infarct | 0.00 (− 0.02;0.03) | 0.01 (− 0.01;0.04) | 0.01 (− 0.02;0.05) |
Microbleed | 0.00 (− 0.04;0.05) | − 0.02 (− 0.07;0.02) | − 0.02 (− 0.08;0.04) |
Model II | | | |
Total brain volume | 0.04(− 0.01;0.09) | 0.09(0.04;0.14) | 0.12(0.06;0.19) |
Gray matter volume | − 0.01 (− 0. 09;0.08) | 0.09 (0.01;0.17) | 0.07 (− 0.03;0.16) |
White matter volume | 0.07 (− 0.01;0.15) | − 0.07 (− 0.01;0.15) | 0.13 (0.04;0.23) |
Fractional anisotropy | − 0.02 (− 0.15;0.11) | − 0.08 (− 0.21;0.04) | − 0.09 (− 0.26;0.07) |
Mean diffusivity | − 0.03 (− 0.12;0.06) | − 0.08 (− 0.18;0.00) | − 0.12 (− 0.25;0.00) |
White matter hyperintensity volume | 0.01 (− 0.08;0.11) | − 0.03 (− 0.12;0.07) | 0.01 (− 0.12;0.13) |
Lacunar Infarct | 0.00 (− 0.02;0.03) | 0.01 (− 0.02;0.03) | 0.01 (− 0.03;0.04) |
Microbleed | 0.01 (−0.05;0.06) | − 0.02 (− 0.07;0.03) | 0.01 (− 0.06;0.19) |
A sensitivity analysis for the influence of menopause status and HRT on the relationship between parity and larger gray matter volume yielded no significant effects (β = 0.10, 95% CI = 0.02;0.17) (Supplementary Table 2).
Discussion
This population-based study observed an association between parity and brain structure decades following pregnancy and childbirth. Specifically, we found that parity was associated with larger total gray matter volume later in life, a finding that persisted following adjustment for sociodemographic factors. The larger gray matter volume associated with parity appeared not to be driven by specific lobar brain regions, but rather was globally proportional across lobes. Further, the analysis revealed lower MD in relation to pregnancy suggesting healthier white matter status, however the observed effect was significantly reduced when adjusting for psychosocial factors. Moreover, we did not find evidence for an association between parity and markers of cerebral small vessel disease, which supports the theory of the adaptation of the brain and cerebral circulation during pregnancy to maintain brain homeostasis, despite substantial peripartum hormonal and cardiovascular changes [
29].
A recently published study suggested that pregnancy-induced reductions in gray matter remained evident for at least two years after childbirth, implying a long-term reduction in brain tissue volume, primarily located in specific lobe regions [
14]. Here we found that decades after pregnancy, gray matter volume is actually larger, a finding that remained robust following adjustment for age, BMI, smoking, education, and marital status [
31,
32]. Moreover, similar association of parity and gray matter volume was also found in women who have experienced pregnancy-related complications. Despite extensive reports on associations between pre-eclampsia and changes in cortical volumes [
13,
33‐
35], this finding is in line with a prior study reporting no influence of preeclampsia on the association of parity and global gray matter volume in the early postpartum period [
13].
Surprisingly, white matter volume was larger in women with pregnancy-related complications versus nulliparous women and compared to women without pregnancy-related complications. A possible link underlying the association of larger white matter volume and hypertension-related complications might relate to a homeostatic compensation for chronic vascular insufficiency. However, there is also a possibility that acute vascular events early in adulthood might have led to compensatory mechanisms later in life, which increased neuroplasticity or reduced white matter degeneration. Finally, we cannot discard the possibility of a chance finding. We also acknowledge that exclusion of women who suffered from stroke, dementia, or cortical infarct might have introduced a selection bias. However, our decision to exclude those women was predicated upon the reliability of the (automated segmentation of) imaging markers.
There is a consensus that pregnancy, delivery, and puerperium expose women to a diversity of health changes that extend beyond direct obstetric complications of pregnancy. For example, emerging evidence suggests that women in the early postpartum period have a substantially increased risk of a first-onset or exacerbation of psychiatric disorders, cardiovascular, and autoimmune diseases [
36‐
38]. However, investigations of the long-term risks associated with pregnancy and delivery have been inconclusive [
39‐
42]. While some studies have argued that childbirth is associated with accelerated cellular aging due to higher levels of oxidative stress [
39], other studies have contradicted these findings by demonstrating elongated telomeres suggestive of an attenuation of risk [
40,
43]. Although no unifying biological explanation has emerged to explain these apparently contrasting findings, it remains a distinct possibility that pregnancy and childbirth have an enduring influence on the endocrine system, and consequently on brain structure, long after childbirth. Pregnancy and childbirth are accompanied by dramatic changes in the hormonal profile. Prolactin, androgens, and estrogens exhibit multiple orders of magnitude increases that are thought to create an anti-inflammatory environment to support pregnancy, fetal growth, and delivery [
37,
44,
45]. For example, during pregnancy increased levels of progesterone stimulate the differentiation of T cells into T-helper type 2 cells, which release anti-inflammatory cytokines [
46]. Circulating estradiol also functions during pregnancy in the mediation and control of immunosuppressive regulatory B cells [
47]. Hormonal fluctuations and their interactions with immune processes have been suggested to modulate several forms of brain plasticity, including changes in glial proliferation, neuronal morphology, and neurogenesis [
48,
49], however their long-term effects on brain aging are not completely understood.
Another potential explanation of enduring effects of pregnancy on brain structure is the bi-directional trafficking of maternal and fetal cells throughout gestation, which can acquire long-term residence in the human brain [
50‐
56]. Fetal cells have been found at the sites of inflammation and linked to preeclampsia and multiple autoimmune diseases [
54,
57]. Inflammation has also been associated with structural and functional brain changes [
57]. Fetal cells are able to integrate into maternal brain circuity and express appropriate immunochemical markers for brain tissues [
51,
53]. However, the extent to which fetal microchimerism is tolerated and whether dynamic changes occur over time remain unknown.
In parallel with underlying biological mechanisms of the observed association between parity and brain structure, the experience of parenting may also alter the brain, which is assumed to be necessary to support sensitive and responsive caregiving. A small number of studies have reported increased gray matter volume of the prefrontal cortex and in parietal lobes. Also, functional brain changes such as higher activation in superior temporal sulcus and amygdala activation were reported to be associated with parenthood in humans [
15,
20,
58]. Further, it has been shown that the duration of motherhood is associated with greater neural activation to infant-specific cues [
21,
59]. Another study found that foster mothers demonstrated an association between brain activity and caregiving behavior comparable to the associations observed in biological mothers [
60]. Furthermore, a recent neuroimaging study in older adults found a positive association between the number of offspring and cortical thickness, in both fathers and mothers [
61].
Our study has several limitations. Although data were sampled from a large, prospective, longitudinal population-based study allowing us to adjust for several covariates, we did not have information on infertility and gravidity which might have improved our ability to adjust for potential confounders. The limited available data did not allow us to explore the mechanistic pathways fully through more advanced methodologies such as directed acyclic graph. Hence, this study utilized a cross-sectional design, which precluded firm conclusions regarding the causality of the observed results. Furthermore, availability of time-varying cardiovascular risk factors might have been helpful to assess the mediating effects on the relationships between parity and brain volumes. The small sample of women with pregnancy-related complications restricted our ability to make distinctions among the various specific complications, which might have further clarified the observed results. Additionally, our sample consisted of a predominantly middle-class population of Caucasian descent, which may restrict the generalizability of our findings. Also, although structural volume segmentation at 1.5 T at the aggregated level we used is likely highly comparable to 3 T field strength, more in-depth investigations may benefit from higher resolution and/or higher field strength imaging [
62].
Moreover, information regarding pregnancy complications were available in a smaller subset of women from whom ~ 25% reported having experienced any pregnancy-related complications, which is larger than prior prevalence estimates of pregnancy-related complications [
63‐
65]. As this questionnaire–at its introduction in the Rotterdam Study–was not asked from all women, the possibility of selection bias cannot be entirely ruled out. Moreover, the data was acquired using a self-report questionnaire. Considering no external validation data such as use of medication or treatment for pregnancy complications was available [
66], recall bias cannot be excluded.
In addition, we acknowledge that we cannot distinguish between the effects of pregnancy, parity, and parenting on structural changes of the brain. Furthermore, it is possible that the observed effect of parity is a result of smaller brain volumes among nulliparous women, rather than larger gray matter volume in parous women. The important point in this context is that nulliparous and parous women might differ in several ways regarding their partnerships and unplanned pregnancies. Living in a relationship with a partner might have cognitive and social challenges that result in enduring changes of brain volume. Although we adjusted for the history of marital status, we cannot rule out residual confounding by factors such as unregistered partnerships. Hence, while speculative, considering the study design and advanced age of the cohort, the findings may be interpreted in several ways. One possible interpretation is that over the life course, pregnancy and childbirth lead to an increase in global gray matter volume. Alternatively, pregnancy and childbirth may serve as a protective factor for subsequent age-related brain atrophy. It is also possible that women who pursue motherhood might differ in their brain structure from those who do not. Lastly, it might be that parenting creates an enriched social network that is protective against brain ageing.
In conclusion, the current findings indicate that parity is associated with a relatively larger global gray matter volume, decades following childbirth. Although the mechanism and physiological relevance of the morphological alterations remain unknown, these data provide novel insight into the long-term impact of motherhood on the human brain.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.