This web page was created programmatically, to learn the article in its authentic location you possibly can go to the hyperlink bellow:
https://pmc.ncbi.nlm.nih.gov/articles/PMC13164820/
and if you wish to take away this text from our website please contact us
Abstract
Background/Objectives: Preterm beginning (PTB) is a significant public well being concern worldwide, which can result in detrimental maternal and neonatal outcomes. Maternal dietary standing, gestational weight achieve (GWG), and way of life components are probably modifiable determinants of antagonistic being pregnant outcomes. This examine examined the affiliation between PTB and maternal GWG and assessed whether or not maternal dietary habits and way of life components had been associated to GWG in ladies delivering preterm versus at time period. Methods: A retrospective case–management examine was carried out at a tertiary heart in Hungary (MANOR Study, 2019). The case group included n = 100 ladies with PTB, whereas n = 200 matched time period deliveries served as controls (1:2 ratio). Data had been collected utilizing a self-administered questionnaire and medical information. Pre-pregnancy physique mass index (BMI) was categorized utilizing customary definitions, whereas GWG was labeled as insufficient, beneficial, or extreme in keeping with the US 2009 Institute of Medicine tips. A 7-item dietary index rating was calculated based mostly on gestational dietary habits. Results: Pre-pregnancy BMI distribution didn’t significantly differ between teams (p > 0.05); over one-third of girls in each teams had been obese or had weight problems (38.7% vs. 36.7%). Previous PTB (p < 0.001) and gestational hypertension (GHT) (p = 0.003) had been extra frequent amongst present PTB circumstances, whereas smoking, alcohol consumption, and gestational diabetes mellitus (GDM) confirmed negligible variations (p > 0.05)—28.0% of circumstances, and 34.5% of controls had been labeled as having wholesome dietary habits, based mostly on the dietary index rating calculated. Inadequate GWG was extra prevalent amongst PTB circumstances (49.0% vs. 26.8%), whereas extreme GWG was much less frequent amongst circumstances (21.9% vs. 38.4%). Being throughout the beneficial GWG vary and the manifestation of gestational hypertension had been related to decrease (aOR: 0.39; 95% CI: 0.18–0.87; p = 0.020) and better (aOR: 3.43; 95% CI: 1.44–8.19; p = 0.005) odds of PTB, respectively. Conclusions: Inadequate GWG was extra frequent in PTB, whereas extreme GWG was extra frequent in time period pregnancies. Fast-food consumption was related to extreme GWG amongst time period births. Optimizing GWG and enhancing maternal food plan high quality must be included as key, cross-cutting interventions concentrating on the advance of antenatal care.
Keywords: case–management examine, gestational weight achieve, maternal food plan, preterm beginning
1. Introduction
Preterm beginning (PTB) is characterised by a supply occurring between the twenty fourth and thirty seventh accomplished weeks of gestation [1]. According to the World Health Organization (WHO), PTBs have an effect on 4–16% of all stay births, and issues associated to prematurity are one of many main causes of demise in kids underneath 5 years of age, related to ~900,000 deaths in 2019 alone [1]; in keeping with the U.S. Centers for Disease Control and Prevention (CDC) information, round 14% of toddler deaths are linked to PTB or low beginning weight (LBW) [2,3]. Furthermore, 2021 estimations from the Global Burden of Disease (GBD) examine highlighted that—whereas excessive Socio-Demographic Index (SDI) areas managed to scale back their annual incidence of PTB by 9.6% (−11.45% to −7.79%)—its incidence has been elevated by 43.1% (+40.17 to +46.09%) in low SDI areas, within the final 30 years, constituting a large burden of disability-adjusted life-years (DALYs) globally [4]. In Hungary, the speed of PTBs has remained fixed between 8 and 9% amongst stay births because the Nineteen Nineties [5], even in 2023, the speed was 8.2% and eight.4% nationwide, and within the Southern area of Hungary, respectively [6].
Advances in medical science have contributed to a discount in toddler mortality; nonetheless, PTBs could have a detrimental impression on inhabitants morbidity with out resulting in an toddler’s demise straight: amongst preterm infants who survive, the emergence of a variety of long-term antagonistic outcomes has been documented, together with cerebral palsy, delayed cognitive growth, sensory and motor impairments [2], developmental issues of the respiratory system, cardiovascular anomalies, weight problems [7] and diabetes mellitus [8]. As the potential sequelae related to PTBs could impression a person’s complete life course, sustained, cross-cutting preventive efforts are mandatory [9]. Depending on the size and severity of PTB-related penalties, impacted households could carry appreciable direct and oblique financial and psychosocial burden [2].
Numerous maternal components have been recognized as potential threat components for PTB, together with maternal age (underneath 18 or over 35 years) [10,11], persistent illnesses (e.g., hypertension, pre-gestational diabetes) [12], uterine anomalies [13], the shortage of prenatal care [14], a number of pregnancies [15] and related way of life components, similar to smoking [16,17], substance use [18], alcohol consumption [19], persistent psychosocial stress [20], lack of leisure-time bodily exercise [21], dietary deficiencies [22,23,24], dietary habits, and appreciable weight modifications throughout being pregnant [25]. Nonetheless, within the majority of circumstances, the principal explanation for PTB has remained unidentified, or could contain a number of causal contributing components [26].
Inadequate gestational weight achieve (GWG) and poor dietary habits could also be key contributors to the elevated threat of untimely supply [27]. In the context of gestational weight standing, decrease pre-pregnancy maternal physique mass index (BMI) has additionally been related to PTB [26]. Women with a BMI < 20 kg/m2 have had almost a four-fold improve within the threat of PTB in comparison with ladies with larger BMI [25].
A meta-analysis printed by Liu et al. studies that pre-pregnancy BMI exterior the beneficial vary (i.e., under- or obese/weight problems) is related to antagonistic neonatal outcomes, together with PTB, small-for-gestational age (SGA), large-for-gestational age (LGA), macrosomia, and neonatal asphyxia, indicating that each the pre-pregnancy BMI and GWG play key roles in perinatal outcomes [28].
According to the rules printed by the Institute of Medicine (IOM) (Washington, DC, USA, 2009) [29], the beneficial GWG for singleton pregnancies are decided by ladies’s pre-pregnancy BMI classes, i.e., ladies throughout the regular pre-pregnancy BMI (18.5–24.9 kg/m2) vary are suggested to realize between 11.5 and 16.0 kg throughout being pregnant in case of a full-term supply (40 weeks of gestation). In comparability, for ladies being underweight (BMI < 18.5 kg/m2) within the pre-pregnancy interval, the beneficial weight achieve is larger (between 12.5 and 18.0 kg), whereas for obese (BMI 25.0–29.9 kg/m2) and girls with weight problems (BMI ≥ 30.0 kg/m2), the beneficial optimum weight features are decrease, between 7.0 and 11.5 kg and 5.0–9.0 kg, respectively. GWG beneath, inside, or above these ranges is classed as “inadequate,” “recommended,” or “excessive” GWG [29,30]. A scientific evaluate and meta-analysis, comparable to a cohort from 10 nations, by Goldstein et al. [31] state that 23% of girls gained much less and 47% gained extra weight than the US 2009 IOM suggestions described above. GWG beneath tips is related to larger dangers of PTB and SGA infants, whereas GWG above tips is related to larger dangers of cesarean part, LGA infants, and barely decrease threat of PTB [28,31]. Data from nations in any respect revenue ranges additional underscore that GWG beneath guideline suggestions is linked to elevated dangers of PTB, SGA, and LBW. However, findings about extreme GWG and the probability of PTB are inconsistent throughout printed research [31,32,33].
Nutritional components have additionally been linked to a number of maternal, fetal, and toddler well being outcomes. A balanced food plan is important throughout being pregnant, as research have proven that it might lower the danger of gestational diabetes mellitus (GDM), gestational hypertension (GHT), LBW (<2500 g), and PTB [34,35]. In addition, an unhealthy maternal food plan could have appreciable long-term influences on the well being and well-being of the kid, contributing to poor cognitive growth, elevating the danger of weight problems, allergic reactions, bronchial asthma, diabetes, and hypertension later in life [36,37,38]. In addition to the above, interventional research recommend that way of life interventions throughout being pregnant could restrict extreme GWG and scale back the danger of GDM, GHT, LGA, and, in some analyses, PTB, though the proof associated to this consequence isn’t strong [39,40].
During being pregnant, the general dietary patterns seem to have a higher impression on well being outcomes than the presence of particular person vitamins. Systematic opinions and meta-analyses comparable to each growing and developed areas have discovered that wholesome dietary behaviors (together with excessive consumption of greens, fruits, complete grains, legumes, dairy merchandise, and fish) and restricted consumption of the elements of the “Western diet” (i.e., energy-dense, extremely processed meals) and sugar-sweetened mushy drinks scale back the danger of GDM, GHT, and antagonistic being pregnant outcomes [34,35,41]. The underlying mechanism—instructed by the literature—is that diets wealthy in ultra-processed, energy-dense meals, fat, and sugars are characterised by excessive vitality but low dietary high quality, linked to extreme GWG and insufficient toddler beginning weight [42].
Several research have highlighted that pre-pregnancy BMI, GWG, and maternal way of life are all vital determinants of toddler well being, they usually could act as modifiable threat components within the prevention of PTB and perinatal issues [28,31]. However, an important information hole has remained: the energy of the associations has been extremely inconsistent throughout the prevailing literature, doubtless because of variations in regional demographics, population-level well being standing, and scientific practices. As present proof has lacked granularity or native context, it leads to a bottleneck that impedes the efficient planning and implementation of main preventive interventions in particular native contexts through the gestational interval. Thus, the target of our current examine was to evaluate this hole: particularly, we aimed to evaluate the connection between PTB and gestational weight change, whereas concurrently investigating whether or not prior obstetric occasions, persistent maternal illnesses, and sure way of life components had been related to maternal weight trajectories throughout being pregnant amongst ladies who delivered preterm versus those that delivered at time period. The purpose of this examine was to contribute to the proof base mandatory for extra exact, localized prenatal care protocols.
The following working hypotheses directed our analyses: (i) ladies characterised by GWG beneath or above guideline-recommended ranges usually tend to expertise PTB, (ii) ladies characterised by GHT, GDM and prior PTB usually tend to expertise PTB, (iii) ladies who consumed tobacco and alcohol throughout gestation usually tend to expertise PTB, (iv) ladies reporting unhealthy dietary patterns and no bodily exercise throughout gestation usually tend to report GWG beneath or above guideline-recommended ranges, (v) ladies who consumed tobacco and alcohol throughout gestation usually tend to report GWG beneath or above guideline-recommended ranges.
2. Materials and Methods
2.1. Study Design
A retrospective, questionnaire-based, matched case–management observational examine was carried out on the Department of Obstetrics and Gynecology, Albert Szent-Györgyi Clinical Center (CC), and the Department of Public Health, Albert Szent-Györgyi Faculty of Medicine, University of Szeged, the place ladies who gave beginning on the CC had been thought of because the pool of potential examine individuals. The CC is a tertiary-care instructing hospital, offering entry to main and specialised well being services at each the county (Csongrád-Csanád) and regional (Southern Great Plain of Hungary) ranges. The present examine was carried out as part of a bigger investigation entitled “Quantifying MAternal Non-Obstetrical Risk Factors for Preterm Birth—Retrospective and Prospective Study” (the MANOR Study). The retrospective examine was carried out between March and December 2019.
2.2. Study Participants, Sample Size, Inclusion and Exclusion Criteria
Participants of the examine included the next two populations: circumstances (ladies with PTB), i.e., ladies who had been: (i) keen to take part within the examine, and had supplied knowledgeable consent, (ii) delivered earlier than the thirty seventh week of gestation, (iii) had been at the least 18 years of age, and (iv) had been singleton pregnancies. Women with PTB who refused participation within the examine or had any barring traits (e.g., twin pregnancies) had been excluded. During the examine interval, N = 2352 newborns had been born, out of which N = 277 (11.78%) had been preterm infants. Considering the inclusion and exclusion standards, N = 209 women-infant dyads had been eligible to take part, out of which n = 100 had been in the end included in our evaluation (Figure 1). With a 1:2 case–management ratio in thoughts, in submit hoc energy analyses, this pattern dimension supplied 80% energy to detect that modifications in a magnitude of ~1.5 in a quantitative variable, assuming a 20% publicity prevalence amongst controls, and a two-sided α = 0.05.
Figure 1.
Flowchart of the pattern choice course of.
The second inhabitants—i.e., the controls—had been ladies who had been: (i) keen to take part within the examine, and had supplied knowledgeable consent, (ii) delivered after the thirty seventh accomplished week of gestation (time period births), (iii) had been at the least 18 years of age, (iv) had singleton pregnancies. The examine employed a frequency matching method with a 1:2 case-to-control ratio (i.e., leading to n = 200 controls out of the N = 2075 eligible ladies, earlier than making use of the exclusion standards); matching was carried out based mostly on maternal age (±2 years) and parity, with out adjusting for extra confounding components. Exclusion standards had been equally utilized to circumstances as properly.
2.3. Data Collection, Outcome Measures
Data assortment was based mostly on three kinds of information sources: (i) a self-administered, structured, paper-based questionnaire, (ii) medical documentation, and (iii) outcomes of maternal serum and umbilical cord-blood vitamin D laboratory analyses. Cases and controls accomplished the questionnaires throughout their postpartum hospital keep. If the participant wanted to participate in a medical examination/session, then questionnaire-based information assortment was suspended, which was resumed after the affected person accomplished the required evaluation.
The questionnaire included objects associated to: (i) sociodemographic traits, (ii) lifestyle-related components, (iii) contraception, planning of being pregnant, variety of earlier pregnancies, earlier being pregnant issues (e.g., miscarriage) and PTB, and (iv) common well being standing. Sociodemographic information collected within the current evaluation included maternal age, degree of instructional attainment (main and secondary college had been labeled as decrease vs. school and college as larger), kind of residence (county city, city, and village), and relationship standing (single and widowed had been labeled as single vs. married and residing with a associate as in a relationship).
Assessment of way of life habits included self-reported pre-pregnancy and pre-delivery physique weight, recognized persistent circumstances throughout being pregnant (e.g., hypertension, GDM), behavioral threat/protecting components, similar to bodily exercise (sure vs. no), smoking (sure vs. no), alcohol consumption (sure vs. no), following a particular food plan (e.g., low-sodium, GDM food plan), and a 7-item questionnaire on dietary habits (i.e., consumption frequency of greens, fruits, fish, mushy drinks, salty snacks, quick meals, sweets). Based on the responses of the above meals frequency merchandise, a 0–12-point dietary index rating was developed, as described by Polanek et al. (see Table 1), the place larger scores point out more healthy dietary behaviors, together with common vegetable, fruit, and fish consumption, occasional or much less frequent quick meals, salty and candy snack, and sugary mushy drink consumption, respectively. The rationale for utilizing this temporary screening software was: (i) the similarity of our examine inhabitants traits (i.e., postpartum ladies in the identical geographical area), and (ii) because of the examine design, setting, and the information assortment time, a extra detailed dietary evaluation (e.g., meals frequency questionnaires with portion sizes) was impractical. Participants attaining ≥ 10 factors within the food plan area had been thought of as “healthy diet”, whereas scores ˂ 10 factors had been designated as “unhealthy diet”, respectively [43].
Table 1.
The 7-item dietary index scale utilized in our examine [43].
| Dietary Habits | Index Score Attained |
|---|---|
| Vegetable consumption | |
| Daily | 2 |
| Weekly | 1 |
| Less often | 0 |
| Fruit consumption | |
| Daily | 2 |
| Weekly | 1 |
| Less often | 0 |
| Fish consumption | |
| Weekly | 1 |
| Less often | 0 |
| Fast meals | |
| Monthly or by no means | 1 |
| More often | 0 |
| Salty snacks | |
| Monthly or by no means | 2 |
| Weekly | 1 |
| Daily | 0 |
| Sweets | |
| Monthly or by no means | 2 |
| Weekly | 1 |
| Daily | 0 |
| Soft drinks | |
| Monthly or by no means | 2 |
| Weekly | 1 |
| Daily | 0 |
| Maximum complete dietary index rating | 12 |
BMIs had been calculated from self-reported pre-pregnancy weight and top, and girls had been categorized as underweight, regular weight, obese, or overweight, in keeping with established BMI classes (Table 2).
Table 2.
Recommendations for complete weight achieve at 40 weeks by pre-pregnancy BMI 1 in keeping with the U.S. 2009 Institute of Medicine [29].
| Pre-Pregnancy BMI 1 | BMI 1 (kg/m2) | Total Weight Gain (kg) |
|---|---|---|
| Underweight | <18.5 | 12.5–18.0 |
| Normal weight | 18.5–24.9 | 11.5–16.0 |
| Overweight | 25.0–29.9 | 7.0–11.5 |
| Obese (contains all lessons) | ≥30.0 | 5.0–9.0 |
GWG was analyzed in keeping with classes described for beneficial weight achieve ranges outlined by the IOM [29], stratified by pre-pregnancy BMI classes (see Table 2).
Additionally, the anticipated GWG at any gestational age was estimated utilizing the next components, described by Palumbo et al. [30]: anticipated GWG = beneficial first-trimester achieve + (gestational age in weeks − 13) × beneficial weekly achieve within the second and third trimesters [30]. Women whose GWG fell beneath the beneficial vary had been labeled as “inadequate”, those that had been throughout the beneficial vary had been categorized as “within the recommended weight gain range”, and those that exceeded the breakpoint had been labeled within the “excessive” class.
2.4. Statistical Analysis
Data collected through the evaluation had been entered into spreadsheets (Microsoft Excel; Microsoft Corp., Redmond, WA, USA) for information administration, which had been later transferred to Statistical Package for Social Sciences v.28.0 (SPSS; IBM Corp., Endicott, NY, USA) for evaluation. Descriptive statistics had been used to current the traits of the pattern (frequencies (n) and percentages (%) for categorical variables, whereas means and 95% confidence intervals (95percentCI) for steady variables). Normality testing of steady variables (e.g., dietary index) was carried out utilizing Q-Q (quantile-quantile) diagrams and Kolmogorov–Smirnov assessments. The following univariate analyses had been carried out: (a) to detect variations between proportions, the χ2-test and Fisher’s precise assessments had been used; (b) comparisons between teams in regard to steady information had been finished utilizing Welch t-tests, and Welch-ANOVA with Tukey’s submit hoc assessments. Furthermore, multivariable logistic regression (LR) analyses had been additionally carried out. In Model 1, PTB expertise (sure/no) was the principle consequence measure, whereas in Model 2, extreme GWG (sure/no) was the principle consequence measure; inclusion of the predictor variables was based mostly on the specifics of the examine design, potential scientific relevance, and parsimony. p values beneath 0.05 (p < 0.05) had been thought of statistically important. During LR, the coefficients (β), customary error (SE), adjusted odds ratios (aORs), and 95% confidence intervals (95% CI) had been reported.
2.5. Ethical Considerations
The examine was carried out in accordance with the Declaration of Helsinki (1975, newest revision: 2024) [44] and nationwide and institutional moral requirements. Ethical approval for the examine protocol was obtained from the Human Institutional and Regional Biomedical Research Ethics Committee on the University of Szeged, Hungary (reference quantity: 256/2018-SZTE [4419]; approval date: 10 December 2018).
2.6. Informed Consent Statement
Before participating on this examine, individuals had been briefed concerning the nature and targets of the examine, privateness, anonymity, and confidentiality of their information; circumstances and controls who agreed to participate supplied written knowledgeable consent earlier than information assortment. All individuals had been made conscious that their participation within the analysis was voluntary, they usually could withdraw from the examine at any time with none penalties to their medical care. No incentives (e.g., financial, reward, or different remuneration) had been supplied to take part within the examine.
2.7. Reporting Guidelines
To guarantee transparency, readability, and consistency within the reporting of the outcomes of our examine, the current manuscript adheres to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) tips for observational research [45]; the STROBE guidelines has been supplied as Supplementary Material S1.
3. Results
3.1. Demographic Characteristics, Anamnestic Data, and Behavioral Factors of the Study Populations
Overall, 100 (n = 100) ladies with PTB (i.e., circumstances) had been included in our examine, along with 2 hundred (n = 200) matched management topics, who carried to time period. The general traits of the 2 teams are summarized in Table 3. Consistent with our sampling design and matching, the age distribution of the case and management teams confirmed no notable variations (p = 0.965); the imply age of circumstances and controls was 32.33 years and 32.25 years, respectively. 36.0% (n = 108) of girls general had been ≥35 years of age. No related variations had been noticed between the 2 teams, by relationship standing or residence, though an inclination in the direction of larger instructional attainment was noticed within the management group (62.0% vs. circumstances, 48.0%; p = 0.055) (Table 3).
Table 3.
Demographic traits and anamnestic information of girls with PTB 1 and controls.
| Variables of Interest | Total | Cases | Controls | p-Value * | |
|---|---|---|---|---|---|
| n (%) | n (%) | n (%) | |||
| Age-group (years) | 18–24 | 34 (11.3) | 12 (12.0) | 22 (11.0) | 0.965 |
| 25–34 | 158 (52.7) | 52 (52.0) | 106 (53.0) | ||
| ≥35 | 108 (36.0) | 36 (36.0) | 72 (36.0) | ||
| Level of instructional attainment | decrease | 122 (41.5) | 47 (49.5) | 75 (37.7) | 0.055 |
| larger | 172 (58.5) | 48 (50.5) | 124 (62.3) | ||
| Relationship standing | single | 7 (2.4) | 3 (3.0) | 4 (2.0) | 0.603 |
| in a relationship | 290 (97.6) | 97 (97.0) | 193 (98.0) | ||
| Residence | county city | 134 (45.0) | 38 (38.4) | 96 (48.2) | 0.224 |
| city | 89 (29.9) | 35 (35.4) | 54 (27.1) | ||
| village | 75 (25.2) | 26 (26.3) | 49 (24.6) | ||
| Pre-pregnancy BMI 2 teams | underweight | 15 (5.1) | 5 (5.1) | 10 (5.0) | 0.882 |
| regular weight | 171 (57.6) | 55 (56.1) | 116 (58.3) | ||
| obese | 59 (19.5) | 22 (22.4) | 37 (18.6) | ||
| overweight | 52 (17.5) | 16 (16.3) | 36 (18.1) | ||
| Smoking throughout being pregnant | no | 282 (94.0) | 91 (91.0) | 191 (95.5) | 0.122 |
| sure | 18 (6.0) | 9 (9.0) | 9 (4.5) | ||
| Physical exercise throughout being pregnant | no | 155 (52.4) | 100 (50.5) | 55 (56.1) | 0.362 |
| sure | 141 (47.6) | 98 (49.5) | 43 (43.9) | ||
| Alcohol consumption throughout being pregnant | no | 271 (91.2) | 94 (94.9) | 177 (89.4) | 0.110 |
| sure | 26 (8.8) | 5 (5.1) | 21 (10.5) | ||
| History of PTB 1 | no | 142 (83.0) | 41 (68.3) | 101 (91.0) | <0.001 |
| sure | 29 (17.0) | 19 (31.7) | 10 (9.0) | ||
| GHT 3 | no | 264 (89.2) | 80 (81.6) | 184 (92.9) | 0.003 |
| sure | 32 (10.8) | 18 (18.4) | 14 (7.1) | ||
| GDM 4 | no | 251 (84.8) | 80 (81.6) | 171 (86.4) | 0.286 |
| sure | 45 (15.2) | 18 (18.4) | 27 (13.6) | ||
| GDM 4 food plan throughout being pregnant | no | 65 (51.6) | 21 (44.7) | 44 (55.7) | 0.231 |
| sure | 61 (48.4) | 26 (55.3) | 35 (44.3) | ||
| Low-sodium food plan | no | 96 (76.8) | 36 (76.6) | 60 (76.9) | 0.967 |
| sure | 29 (23.2) | 11 (23.4) | 18 (23.1) | ||
The distribution of pre-pregnancy BMI was additionally related between the case and management teams (obese or overweight: 38.7% vs. 36.7%; p = 0.882). On the opposite hand, circumstances had a extra frequent historical past of PTB (31.7% vs. controls: 9.0%; p < 0.001). No important variations had been noticed for the frequency of smoking (p = 0.122), alcohol consumption (p = 0.110), or bodily exercise throughout being pregnant (p = 0.362) amongst circumstances vs. controls (Table 3). Furthermore, 15.2% of girls had GDM, and 48.4% adopted the GDM food plan (with no important variations between circumstances and controls; p = 0.286 and p = 0.231, respectively). Cases had been extra more likely to be affected by GHT (18.4% vs. controls: 7.1%; p = 0.003), however no more more likely to adhere to a low-sodium food plan (p = 0.967).
3.2. Dietary Habits and Dietary Index Score of Cases and Controls
The responses of girls with PTB and girls with time period deliveries (controls) relating to their dietary habits—which had been used as the idea of the willpower of the dietary index scores—are proven in Table 4. Daily greens (82.9% vs. circumstances: 69.4%; p = 0.025) and fruits (84.1% vs. 76.0%; p = 0.043) consumption had been extra frequent amongst controls, whereas no related variations had been described for the frequency of fish consumption (weekly: 35.6% general). Regarding extra disadvantageous well being habits, no notable disparities had been recognized within the frequency of consuming quick meals, consuming salty snacks, sweets and mushy drink every day (general: 23.0%, 6.4%, 29.3% and 9.4%, respectively; p < 0.05 in all circumstances); nonetheless, 51.0%, 58.6% and 77.0% reported the uncommon (month-to-month or by no means) consumption of salty snacks, mushy drinks and quick meals, respectively (Table 4).
Table 4.
The traits of maternal dietary habits throughout being pregnant amongst ladies with PTB 1 and controls.
| Dietary Habits * | Total | Cases | Controls | p-Value ** |
|---|---|---|---|---|
| n (%) | n (%) | n (%) | ||
| Vegetable consumption | ||||
| Daily | 233 (78.5) | 68 (69.4) | 165 (82.9) | 0.025 |
| Weekly | 61 (20.5) | 29 (29.6) | 32 (16.1) | |
| Less often | 3 (1.0) | 1 (1.0) | 2 (1.0) | |
| Fruit consumption | ||||
| Daily | 237 (81.4) | 73 (76.0) | 164 (84.1) | 0.043 |
| Weekly | 50 (17.2) | 23 (24.0) | 27 (13.8) | |
| Less often | 4 (1.4) | 0 (0.0) | 4 (2.1) | |
| Fish consumption | ||||
| Weekly | 106 (35.6) | 37 (37.0) | 69 (34.8) | 0.714 |
| Less often | 192 (64.4) | 63 (63.0) | 129 (65.2) | |
| Fast meals | ||||
| Monthly or by no means | 228 (77.0) | 72 (72.0) | 156 (79.6) | 0.142 |
| More often | 68 (23.0) | 28 (28.0) | 40 (20.4) | |
| Salty snacks | ||||
| Monthly or by no means | 151 (51.0) | 48 (48.5) | 103 (52.3) | 0.653 |
| Weekly | 126 (42.6) | 43 (43.4) | 83 (42.1) | |
| Daily | 19 (6.4) | 8 (8.1) | 11 (5.6) | |
| Sweets | ||||
| Monthly or by no means | 44 (15.0) | 16 (16.3) | 28 (14.3) | 0.506 |
| Weekly | 164 (55.8) | 50 (51.0) | 114 (58.2) | |
| Daily | 86 (29.3) | 32 (32.7) | 54 (27.6) | |
| Soft drinks | ||||
| Monthly or by no means | 174 (58.6) | 58 (58.0) | 116 (58.9) | 0.291 |
| Weekly | 95 (32.0) | 29 (29.0) | 66 (33.5) | |
| Daily | 28 (9.4) | 13 (13.0) | 15 (7.6) |
Based on individuals’ responses, imply dietary index scores had been 8.29 [95%CI: 7.90–8.68] for ladies with PTB vs. 8.65 [95%CI: 8.37–8.93], the place no related variations had been proven between circumstances and controls (p = 0.107; general: 8.53 [95%CI: 8.30–8.76]); according to our beforehand decided standards, they had been labeled as having a wholesome (≥10 factors) or unhealthy diets (˂10 factors): accordingly, 28.0% (n = 28) of circumstances, and 34.5% (n = 69) of controls had wholesome dietary habits (general: 32.3% [n = 97] of individuals had been labeled as wholesome). Based on age, solely a non-significant, however tendentious improve in imply dietary scores had been recognized amongst ladies with PTB (18–24 years: 7.18 [95%CI: 5.98–8.37] vs. 25–34 years: 8.29 [95%CI: 7.74–8.84] vs. ≥35 years: 8.67 [95%CI: 8.03–9.32]; p = 0.076), whereas a big and constant improve was proven amongst ladies who carried to time period (18–24 years: 7.43 [95%CI: 6.50–8.35] vs. 25–34 years: 8.53 [95%CI: 6.50–8.35] vs. ≥35 years: 9.21 [95%CI: 8.74–9.67]; p = 0.002); throughout submit hoc analyses, important variations had been recognized amongst all age teams (p < 0.05 in all circumstances). No related associations had been noticed amongst dietary index scores and academic attainment (i.e., decrease vs. larger) of pregnant ladies, both within the PTB group (8.21 [95%CI: 7.62–9.07] vs. 8.55 [95%CI: 7.90–9.37]; p = 0.397) or within the management group (8.34 [95%CI: 7.79–8.93] vs. 8.85 [95%CI: 8.21–9.09]; p = 0.093), respectively. Controls who adopted the GDM food plan throughout being pregnant had larger imply dietary scores (9.24 [95%CI: 8.95–9.67] vs. no GDM food plan: 8.70 [95%CI: 8.16–8.79]; p = 0.005), whereas related associations weren’t recognized amongst circumstances (9.91 [95%CI: 7.63–10.35] vs. no GDM food plan: 8.81 [95%CI: 6.98–9.45]; p = 0.266). Furthermore, no associations had been recognized amongst these following the low-sodium food plan throughout being pregnant and imply dietary scores, in both the PTB (9.02 [95%CI: 7.23–10.08] vs. no low-sodium food plan: 8.91 [95%CI: 7.15–9.82]; p = 0.816) or management (9.47 [95%CI: 8.22–10.03] vs. no low-sodium food plan: 8.66 [95%CI: 7.98–9.81]; p = 0.133) teams. Finally, solely non-significant tendentious variations within the dietary index scores had been noticed in both the circumstances and controls, on the idea of smoking (circumstances: 7.38 [95%CI: 6.87–9.04] vs. no smoking: 8.38 [95%CI: 7.16–9.45]; p = 0.151; controls: 7.43 [95%CI: 7.01–9.17] vs. no smoking: 8.69 [95%CI: 8.02–9.11]; p = 0.111), consumption of alcohol (circumstances: 7.60 [95%CI: 7.03–8.94] vs. no alcohol: 8.31 [95%CI: 7.23–9.34]; p = 0.220; controls: 8.52 [95%CI: 7.99–9.56] vs. no alcohol: 8.67 [95%CI: 7.64–9.39]; p = 0.355), or participating in bodily exercise (circumstances: 8.59 [95%CI: 7.43–9.83] vs. no bodily exercise: 7.96 [95%CI: 7.11–9.38]; p = 0.067; controls: 8.81 [95%CI: 8.12–9.56] vs. no bodily exercise: 8.47 [95%CI: 7.85–9.32]; p = 0.116) throughout being pregnant.
3.3. Association Between Pregnancy Weight Gain, Pregnancy Term, and Other Obstetric Outcomes and Events
Out of the pregnant ladies taking part in our examine, lower than one-third (27.9%; n = 84) had been characterised by the beneficial GWG vary, as described by IOM standards beforehand. When evaluating circumstances and controls (p = 0.015), ladies who had insufficient weight achieve had been extra frequent amongst PTBs (39.6% vs. time period pregnancies: 25.8%), whereas sufficient GWG was comparatively much less frequent in PTBs (18.8% vs. time period pregnancies: 32.3%); alternatively, charges of extreme GWG had been related in each teams (41.7% vs. 41.9%).
No associations between GWG categorization and imply dietary scores had been recognized amongst ladies with PTB (insufficient: 8.48 [95%CI: 7.778–9.19] vs. inside beneficial vary: 8.29 [95%CI: 7.30–9.19] vs. extreme: 8.15 [95%CI: 7.55–8.76]; p = 0.776), whereas important variations had been proven amongst ladies who carried to time period (insufficient: 9.06 [95%CI: 8.57–9.56] vs. inside beneficial vary: 9.08 [95%CI: 8.64–9.48] vs. extreme: 8.08 [95%CI: 7.58–8.59]; p = 0.003); throughout submit hoc analyses, important variations had been recognized among the many inadequate-excessive (p = 0.018) and inside beneficial range-excessive (p = 0.007) classes.
The prevalence of earlier and present obstetric outcomes and occasions was additionally assessed throughout the context of GWG, stratified by present PTB vs. management standing (Table 5); amongst controls, no related associations had been famous between earlier PTB (p = 0.495), or an expertise of GHT (p = 0.256) or GDM (p = 0.589) and GWG. Similarly, amongst present PTBs, no associations had been proven amongst GHT (p = 0.705) or GDM (p = 0.721) and GWG; alternatively, there was weak proof in opposition to the null speculation (p = 0.090) when evaluating earlier prevalence of PTB and GWG standing, the place ladies exterior the beneficial weight achieve vary had been considerably extra frequent amongst these with earlier PTB expertise. Irrespective of GDM, the very best proportion of moms each within the case group (73.0%) and the management group (64.0%) belonged exterior of the “within recommended range” class (Table 5).
Table 5.
Association between earlier and current obstetric occasions and gestational weight achieve amongst ladies with PTB 1 and controls.
| Weight Gain Categories | Cases n (%) |
Controls n (%) |
||
|---|---|---|---|---|
| Previous PTB 1 | ||||
| sure | no | sure | no | |
| Inadequate | 4 (25.0) | 16 (40.0) | 1 (11.1) | 24 (24.0) |
| Within the beneficial vary | 1 (6.3) | 9 (22.5) | 3 (33.3) | 39 (39.0) |
| Excessive | 11 (68.8) | 15 (37.5) | 5 (55.6) | 37 (37.0) |
| p-values * | 0.090 | 0.495 | ||
| GHT 2 | ||||
| sure | no | sure | no | |
| Inadequate | 5 (27.8) | 28 (38.4) | 1 (7.7) | 45 (25.1) |
| Within the beneficial vary | 4 (22.2) | 14 (19.2) | 4 (30.8) | 60 (33.5) |
| Excessive | 9 (50.0) | 31 (42.5) | 8 (61.5) | 74 (41.3) |
| p-values * | 0.705 | 0.256 | ||
| GDM 3 | ||||
| sure | no | sure | no | |
| Inadequate | 8 (44.4) | 25 (34.2) | 8 (30.8) | 38 (22.9) |
| Within the beneficial vary | 3 (16.7) | 15 (20.5) | 9 (34.6) | 55 (33.1) |
| Excessive | 7 (38.9) | 33 (45.2) | 9 (34.6) | 73 (44.0) |
|
p -values * |
0.721 | 0.589 | ||
The consumption frequency of varied helpful and dangerous foodstuffs—included within the 7-item dietary index was in contrast throughout the context of GWG, stratified by case vs. management standing (Table 6): amongst ladies with PTB, no related associations had been famous between completely different GWG teams and the frequency of consuming greens (p = 0.333), fish (p = 0.894), quick meals (p = 0.277), salty snacks (p = 0.795), sweets (p = 0.483) and mushy drinks (p = 0.513), respectively; whereas there was an inclination proven about every day fruit shoppers being extra doubtless amongst PTBs exterior the beneficial GWG (p = 0.090). Among controls, no related associations had been famous between completely different GWG teams and the frequency of consuming greens (p = 0.133), fruits (p = 0.730), fish (p = 0.413), salty snacks (p = 0.484), sweets (p = 0.191) and mushy drinks (p = 0.117), respectively; as compared, these consuming quick meals extra often had been extra doubtless within the “excessive” GWG class (p = 0.013) (Table 6).
Table 6.
Consumption frequency of varied helpful and dangerous foodstuffs in keeping with gestational weight achieve classes in ladies with PTB 1 and controls.
| GWG 2 Categories | Cases | Controls | ||||
|---|---|---|---|---|---|---|
| n (%) | n (%) | |||||
| Vegetable consumption | ||||||
| Daily | Weekly | Less often | Daily | Weekly | Less often | |
| Inadequate | 27 (42.2) | 6 (23.1) | 1 (100.0) | 39 (24.4) | 7 (22.6) | 0 (0.0) |
| Within the beneficial vary | 11 (17.2) | 6 (23.1) | 0 (0.0) | 58 (36.3) | 6 (19.4) | 0 (0.0) |
| Excessive | 26 (40.6) | 14 (53.8) | 0 (0.0) | 63 (39.4) | 18 (58.1) | 2 (100.0) |
| p-values * | 0.333 | 0.133 | ||||
| Fruit consumption | ||||||
| Daily | Weekly | Less often | Daily | Weekly | Less often | |
| Inadequate | 28 (40.6) | 4 (20.0) | 0 (0.0) | 39 (24.4) | 5 (19.2) | 1 (33.3) |
| Within the beneficial vary | 15 (21.7) | 3 (15.0) | 0 (0.0) | 53 (33.1) | 8 (30.8) | 0 (0.0) |
| Excessive | 26 (37.7) | 13 (65.0) | 0 (0.0) | 68 (42.5) | 13 (50.0) | 2 (66.7) |
| p-values * | 0.090 | 0.730 | ||||
| Fish consumption | ||||||
| Weekly | Less often | Weekly | Less often | |||
| Inadequate | 11 (34.4) | 23 (37.7) | 14 (21.2) | 32 (25.2) | ||
| Within the beneficial vary | 7 (21.9) | 11 (18.0) | 26 (39.4) | 38 (29.9) | ||
| Excessive | 14 (43.8) | 27 (44.3) | 26 (39.4) | 57 (44.9) | ||
| p-values * | 0.894 | 0.413 | ||||
| Fast meals | ||||||
| More often | Monthly or by no means | More often | Monthly or by no means | |||
| Inadequate | 8 (34.8) | 26 (37.1) | 5 (12.5) | 41 (27.2) | ||
| Within the beneficial vary | 7 (30.4) | 11 (15.7) | 10 (25.0) | 54 (35.8) | ||
| Excessive | 8 (34.8) | 33 (47.1) | 25 (62.5) | 56 (37.1) | ||
| p-values * | 0.277 | 0.013 | ||||
| Salty snacks | ||||||
| Daily | Weekly | Less often | Daily | Weekly | Less often | |
| Inadequate | 3 (37.5) | 17 (41.5) | 13 (30.2) | 2 (18.2) | 18 (22.5) | 26 (25.7) |
| Within the beneficial vary | 2 (25.0) | 8 (19.5) | 8 (18.6) | 3 (27.3) | 23 (28.7) | 38 (37.6) |
| Excessive | 3 (37.5) | 16 (39.0) | 22 (51.2) | 6 (54.4) | 39 (48.8) | 37 (36.6) |
| p-values * | 0.795 | 0.484 | ||||
| Sweets | ||||||
| Daily | Weekly | Monthly or by no means | Daily | Weekly | Monthly or by no means | |
| Inadequate | 13 (29.5) | 13 (29.5) | 8 (53.3) | 8 (15.1) | 30 (27.0) | 8 (29.6) |
| Within the beneficial vary | 5 (15.6) | 9 (20.5) | 3 (20.0) | 17 (32.1) | 40 (36.0) | 6 (22.2) |
| Excessive | 14 (43.8) | 22 (50.0) | 4 (26.7) | 28 (52.8) | 41 (36.9) | 13 (48.1) |
| p-values * | 0.483 | 0.191 | ||||
| Soft drinks | ||||||
| Daily | Weekly | Monthly or by no means | Daily | Weekly | Monthly or by no means | |
| Inadequate | 3 (27.3) | 12 (44.4) | 19 (34.5) | 1 (7.1) | 16 (24.2) | 29 (25.9) |
| Within the beneficial vary | 1 (9.1) | 4 (14.8) | 13 (23.6) | 3 (21.4) | 19 (28.8) | 42 (37.5) |
| Excessive | 7 (63.6) | 11 (40.7) | 23 (41.8) | 10 (71.4) | 31 (47.0) | 41 (36.6) |
| p-values * | 0.513 | 0.117 | ||||
The distribution of GWG classes amongst completely different age teams of pregnant ladies is proven in Table 7: no notable variations had been proven both amongst ladies experiencing PTB or controls (p = 0.102 and p = 0.758, respectively). No affiliation was recognized between ladies’s degree of instructional attainment and probability of being exterior the beneficial GWG vary, both amongst circumstances (decrease: 86.9% vs. larger: 75.0%; p = 0.346) or controls (decrease: 70.2% vs. larger: 65.0%; p = 0.716).
Table 7.
Distribution of age teams in keeping with gestational weight achieve amongst ladies with PTB 1.
| GWG 2 Categories | Cases n (%) |
Controls n (%) |
||||
|---|---|---|---|---|---|---|
| Age Groups | ||||||
| 18–24 Years | 25–34 Years | ≥35 Years | 18–24 Years | 25–34 Years | ≥35 Years | |
| Inadequate | 5 (41.7) | 11 (23.9) | 18 (51.4) | 4 (20.0) | 24 (23.1) | 19 (29.7) |
| Within the beneficial vary | 1 (8.3) | 12 (26.1) | 5 (14.3) | 5 (25.0) | 35 (33.7) | 24 (34.3) |
| Excessive | 6 (50.0) | 23 (50.0) | 12 (34.3) | 11 (55.0) | 45 (43.3) | 27 (38.6) |
| p-value * | 0.102 | 0.758 | ||||
Both amongst PTB circumstances and controls, these ladies who had been extra doubtless exterior the beneficial GWG vary and didn’t adhere to the low-sodium food plan (PTBs: 9.0% vs. 27.0%; p = 0.015; controls: 6.0% vs. 19.5%; p = 0.031). On the opposite hand, no related associations had been proven between GWG classes and adherence to the GDM food plan, both in respect to circumstances (p = 0.309) or controls (p = 0.224).
The affiliation between varied way of life components throughout gestation and GWG is summarized in Table 8. No associations had been proven between GWG teams and smoking (p = 0.357) or alcohol consumption (p = 0.404) within the PTB group, whereas there was a better tendency of being within the beneficial GWG vary if one participated in bodily exercise throughout being pregnant (p = 0.088). Among controls, no associations had been proven between GWG teams and smoking (p = 0.509) or taking part in bodily exercise throughout being pregnant (p = 0.224), whereas there was a considerably larger probability of being within the beneficial GWG vary if one consumed alcohol throughout being pregnant (p = 0.045).
Table 8.
Association of way of life components throughout gestation and gestational weight achieve classes in ladies with PTB 1 and controls.
| GWG 2 Categories | Cases n (%) |
Controls n (%) |
||
|---|---|---|---|---|
| Smoking throughout being pregnant | ||||
| sure | no | sure | no | |
| Inadequate | 2 (22.2) | 32 (38.1) | 2 (25.0) | 45 (24.2) |
| Within the beneficial vary | 1 (11.1) | 17 (20.2) | 4 (50.0) | 60 (32.3) |
| Excessive | 6 (66.7) | 35 (41.7) | 2 (25.0) | 81 (43.5) |
|
p -value * |
0.357 | 0.509 | ||
| Physical exercise throughout being pregnant | ||||
| sure | no | sure | no | |
| Inadequate | 10 (25.0) | 23 (45.1) | 27 (28.1) | 19 (19.8) |
| Within the beneficial vary | 11 (27.5) | 7 (13.7) | 33 (34.4) | 30 (31.2) |
| Excessive | 19 (47.5) | 21 (41.2) | 36 (37.5) | 47 (49.0) |
|
p -value * |
0.088 | 0.224 | ||
| Alcohol consumption throughout being pregnant | ||||
| sure | no | sure | no | |
| Inadequate | 2 (40.0) | 32 (36.8) | 4 (19.0) | 42 (24.6) |
| Within the beneficial vary | 2 (40.0) | 16 (18.4) | 12 (57.1) | 52 (30.4) |
| Excessive | 1 (20.0) | 39 (44.8) | 5 (23.8) | 77 (45.0) |
|
p -value * |
0.404 | 0.045 | ||
Table 9 summarizes the outcomes of multivariable LR analyses (Model 1), the place expertise of PTB was the principle consequence variable, whereas the individuals’ age group, pre-pregnancy BMI class, GWG class, instructional attainment, bodily exercise, smoking and alcohol consumption throughout being pregnant, GDM, GHT, and dietary index rating had been included as predictors. Of notice, ladies throughout the beneficial vary had a 61.0% decrease (aOR: 0.39; 95% CI: 0.18–0.87; p = 0.020), whereas these presenting with GHT had a 243.0% larger (aOR: 3.43; 95% CI: 1.44–8.19; p = 0.005) odds of PTB, in keeping with the outcomes of the LR mannequin.
Table 9.
Model 1: Multivariable logistic regression analyses (consequence variable: PTB 1 expertise).
| Variables | β | SE 2 | aOR (95% CI) 3 | p-Value |
|---|---|---|---|---|
| Dietary index (rating) | −0.12 | 0.08 | 0.89 (0.76–1.03) | 0.120 |
| Age teams | ||||
| 18–24 (Ref.) | 1.00 | |||
| 25–34 | 0.28 | 0.55 | 1.32 (0.48–3.68) | 0.596 |
| ≥35 | 0.18 | 0.08 | 1.20 (0.41–3.52) | 0.738 |
| Pre-pregnancy BMI 4 class | ||||
| Underweight (Ref.) | 1.00 | |||
| Normal weight | −0.01 | 0.62 | 0.99 (0.29–3.34) | 0.991 |
| Overweight | 0.13 | 0.68 | 1.14 (0.31–4.30) | 0.845 |
| Obese | −0.34 | 0.71 | 0.71 (0.18–2.65) | 0.633 |
| GWG 5 classes | ||||
| Inadequate (Ref.) | 1.00 | |||
| Within the beneficial vary | −0.92 | 0.39 | 0.39 (0.18–0.87) | 0.020 |
| Excessive | −0.59 | 0.35 | 0.55 (0.28–1.10) | 0.092 |
| Level of instructional attainment | ||||
| Lower (Ref.) | 1.00 | |||
| Higher | −0.23 | 0.31 | 0.79 (0.42–1.48) | 0.466 |
| Physical exercise throughout being pregnant | ||||
| No (Ref.) | 1.00 | |||
| Yes | 0.134 | 0.296 | 1.14 (0.64–2.04) | 0.650 |
| Smoking throughout being pregnant | ||||
| No (Ref.) | 1.00 | |||
| Yes | 0.72 | 0.61 | 2.06 (0.62–6.81) | 0.236 |
| GDM 5 | ||||
| No (Ref.) | 1.00 | |||
| Yes | 0.62 | 0.40 | 1.86 (0.85–4.09) | 0.121 |
| GHT 6 | ||||
| No (Ref.) | 1.00 | |||
| Yes | 1.24 | 0.44 | 3.43 (1.44–8.19) | 0.005 |
Multivariable LR analyses (Model 2) had been additionally carried out to evaluate the connection between extreme GWG (as the principle consequence variable), and individuals’ age group, pre-pregnancy BMI class, instructional attainment, bodily exercise throughout being pregnant, PTB expertise (i.e., case vs. management standing) and dietary index rating (as predictors), respectively; the outcomes of those analyses are summarized in Table 10. Women who had been within the regular (aOR: 4.81; 95% CI: 1.01–22.99; p = 0.049), obese (aOR: 12.38; 95% CI: 2.44–62.81; p = 0.002) or overweight (aOR: 8.89; 95% CI: 1.71–46.22; p = 0.009) pre-pregnancy weight classes had been extra more likely to have extreme GWG; alternatively, the probability of extreme GWG decreased by 17% for each incremental improve within the dietary threat rating, in keeping with the outcomes of the LR mannequin (p = 0.011) (Table 10).
Table 10.
Model 2: Multivariable logistic regression analyses (consequence variable: extreme GWG 1).
| Variables | β | SE 2 | aOR (95% CI) 3 | p-Value |
|---|---|---|---|---|
| Dietary index (rating) | −0.19 | 0.07 | 0.83 (0.72–0.96) | 0.011 |
| Age teams | ||||
| 18–24 (Ref.) | 1.00 | |||
| 25–34 | −0.12 | 0.48 | 0.88 (0.35–2.21) | 0.792 |
| ≥35 | −0.43 | 0.49 | 0.65 (0.25–1.73) | 0.390 |
| Pre-pregnancy BMI 4 class | ||||
| Underweight (Ref.) | 1.00 | |||
| Normal weight | 1.57 | 0.79 | 4.81 (1.01–22.99) | 0.049 |
| Overweight | 2.51 | 0.82 | 12.38 (2.44–62.81) | 0.002 |
| Obese | 2.18 | 0.84 | 8.89 (1.71–46.22) | 0.009 |
| Level of instructional attainment | ||||
| Lower (Ref.) | 1.00 | |||
| Higher | −0.155 | 0.29 | 0.86 (0.49–1.51) | 0.580 |
| Physical exercise throughout being pregnant | ||||
| No (Ref.) | 1.00 | |||
| Yes | −0.05 | 0.271 | 0.95 (0.56–1.61) | 0.846 |
| PTB 5 expertise | ||||
| No (Ref.) | 1.00 | |||
| Yes | −0.14 | 0.28 | 0.87 (0.49–1.53) | 0.618 |
4. Discussion
The excessive prevalence of PTB is a significant public well being concern, as issues of prematurity are the main causes of demise in kids underneath 5 years of age [1]. Due to the ensuing healthcare and societal burden, PTB stays a significant scientific concern, due to this fact figuring out related PTB threat components and growing cross-cutting, built-in preventive methods stay a essential precedence. In our single-center observational case–management examine, the connection between PTB and GWG was examined at a tertiary obstetric CC within the Southern area of Hungary, and we explored whether or not maternal dietary habits and way of life components present noteworthy associations with GWG amongst ladies delivering preterm versus at time period.
In our pattern, greater than one-third of girls—each among the many circumstances and controls—had been obese or had weight problems pre-pregnancy, and the distribution of BMI classes earlier than conception additionally didn’t differ significantly. These proportions are just like information of the most recent (2019) European Health Interview Survey (EHIS), the place 62.8% of Hungarian ladies—aged 15–34 years—had been self-reporting being throughout the regular weight vary, whereas of 19.4% of respondents had been obese and 10.3% had weight problems, respectively [46].
Previous PTB was considerably extra frequent amongst present PTB circumstances than in controls (p < 0.001), in line with prior research figuring out prior PTB as one of many strongest predictors of recurrence [47]; as well as, GHT was additionally extra frequent amongst circumstances (p = 0.003), according to current proof linking hypertensive issues to PTB and different antagonistic neonatal outcomes [12,25]. In distinction, we didn’t observe any related variations between circumstances and controls inside our pattern, in regard to smoking, alcohol consumption charges, or the prevalence of GDM.
As reported by earlier research, insufficient GWG and pre-pregnancy BMI (underweight or obese/weight problems) could improve the danger of PTB [25,26,27]. Our findings partly assist these observations: nearly half of the ladies within the case group had insufficient weight achieve (49.0% vs. 26.8% in controls), whereas extreme GWG was much less frequent amongst PTB circumstances (21.9% vs. 38.4%). This sample means that inadequate GWG could also be extra strongly associated to PTB on this pattern, whereas extreme GWG was additionally extremely prevalent amongst time period births.
We assessed the maternal food plan utilizing a easy 7-item dietary index [43], protecting the consumption frequency of greens, fruits, fish, mushy drinks, salty snacks, quick meals, and sweets. Women within the management group reported barely more healthy dietary behaviors than PTB circumstances, with larger proportions of every day vegetable and fruit consumption; nonetheless, the imply dietary index scores—used as a cumulative measure—didn’t present important variations between teams, and solely about one-third of girls general met the brink to be thought of for having a “healthy” food plan, in keeping with our pre-defined standards (index ≥ 10 factors) [43]. Interestingly, a constant tendency of upper dietary index scores was noticed amongst older pregnant ladies in our pattern.
Among controls, decrease dietary index scores and extra frequent fast-food consumption had been related to extreme GWG, whereas related associations weren’t noticed amongst PTB circumstances. These findings are in line with earlier studies that diets wealthy in ultra-processed, energy-dense meals, fat, and sugars are linked to extreme GWG and suboptimal toddler anthropometric outcomes [27,34,35,36,42], suggesting that food plan high quality and its constituents could play a very vital position for stopping extreme GWG in time period pregnancies.
In distinction, way of life components, similar to smoking and alcohol consumption, had been rare and confirmed no clear sample with GWG in ladies with PTB, though beforehand, a number of research have reported the existence of an affiliation [16,17,19]. The lack of observing this affiliation with PTB could also be because of the excessive proportion of girls reporting wholesome behaviors, and the small variety of people who smoke and shoppers of alcohol in our pattern. Physical exercise throughout being pregnant tended to be related to beneficial GWG amongst ladies with PTB, however no constant impact was seen in controls, and we couldn’t verify a protecting impact on PTB threat, as instructed by earlier research [21].
The multivariable LR evaluation (Model 1) confirmed the affiliation between PTB and GWG and GHT. GWG being throughout the beneficial vary decreased, whereas the presence of GHT elevated the probability of PTB. Furthermore, Model 2 discovered that girls who had been within the regular, obese, or overweight pre-pregnancy weight classes had been extra more likely to have extreme GWG, and the danger of extreme GWG decreased with the rise within the dietary threat rating, i.e., with more healthy dietary habits.
A notable discovering was the affiliation between self-reported adherence to a low-sodium food plan and GWG. Women who didn’t comply with a low-sodium food plan had been extra usually exterior the beneficial GWG vary, in comparison with those that reported following a low-sodium food plan, in each PTB circumstances (27.0% vs. 9.0%) and controls (19.5% vs. 6.0%). Sodium restriction is broadly thought to scale back water retention and thus, decrease physique weight or attenuate weight achieve, primarily by means of reductions in extracellular fluid quantity fairly than modifications primarily in vitality metabolism [48,49]. Although low-sodium diets are sometimes prescribed to forestall hypertensive issues [50,51]. A self-reported low-sodium food plan confirmed no correlation with GHT in our inhabitants, but it surely did affiliate strongly with pre-pregnancy BMI, indicating that girls who had been obese and girls with weight problems had been extra more likely to report following a low-sodium food plan. A believable clarification could also be that girls had been suggested to limit salt consumption because of a perceived elevated threat of GHT or preeclampsia, or due to extreme GWG, which raised suspicion of fluid retention and elevated cardiometabolic threat. However, we didn’t quantify precise sodium consumption, and the self-reported, observational nature of this measure doesn’t permit us to find out exactly whether or not sodium restriction itself influenced GWG or not.
The outcomes of the current examine have to be interpreted with warning, throughout the context of its limitations and potential sources of bias, together with the retrospective information assortment methodology, and using post-partum self-report on a number of key exposures of the examine, which can probably introduce recall bias and measurement inaccuracies. Mothers with PTB could recall pregnancy-related behaviors in another way in contrast with moms of time period infants. Additionally, dietary habits had been assessed utilizing a easy 7-item dietary index; due to this fact, it displays common dietary habits fairly than a complete quantification of dietary consumption of related macro- and micronutrients, respectively. Furthermore, our observational case–management examine was carried out at a single, tertiary-center regional well being facility in Hungary, together with a comparatively low pattern dimension (and thus, statistical energy), which can restrict statistical reliability, significantly in stratified analyses with small counts inside subgroups, improve the danger of kind II error, and should have launched choice bias, thereby affecting the exterior validity of our findings. Finally, some questions pertaining to way of life and dietary habits had been qualitative/categorical (e.g., whether or not the participant adopted the low-sodium food plan or not), with out truly measuring the salt consumption of the individuals. This methodology of information assortment from the individuals could replicate medical recommendation obtained or perceived well being dangers, fairly than precise dietary sodium consumption. Additionally, the shortage of detailed info on portion sizes and vitality consumption could have contributed to misclassification bias. Therefore, the noticed associations must be interpreted with warning, as they might replicate reverse causation or confounding by scientific indication.
Despite the constraints of our examine, our findings have notable strengths as properly, together with its matched case–management examine design, to scale back confounding by essential socio-demographic and pregnancy-related variables, using internationally accepted IOM tips to evaluate GWG classes, and the analysis of the standard of maternal food plan utilizing a multidimensional dietary index scale. The excessive prevalence of GWG beneath or above guideline-recommended ranges in each PTB and time period pregnancies means that nearer monitoring and counseling on managing gestational weight must be built-in into routine antenatal care. Our outcomes assist the position of insufficient GWG as a possible marker of PTB threat, and emphasize the necessity to optimize each pre-pregnancy BMI and GWG as modifiable determinants of maternal and neonatal well being outcomes. The patterns noticed amongst time period controls, linking frequent fast-food consumption and decrease dietary scores to extreme GWG, spotlight the significance of dietary interventions, focusing not solely on GWG, but additionally on food plan high quality and the discount in ultra-processed, energy-dense meals. Future research with bigger, potential cohorts and extra detailed, goal evaluation of food plan, bodily exercise, and sodium consumption are wanted to make clear the causal pathways between maternal diet, GWG, and PTB.
5. Conclusions
In this observational case–management examine, we discovered that insufficient GWG was extra frequent amongst ladies who delivered preterm, whereas extreme GWG was extremely prevalent amongst time period births. Pre-pregnancy obese and weight problems had been frequent in each teams. Only about one-third of girls reported a “healthy” dietary sample in keeping with our dietary index. Among time period pregnancies, extra frequent fast-food consumption was related to extreme GWG, suggesting that food plan high quality is a vital goal for stopping extreme GWG. Self-reported low-sodium food plan was associated to larger pre-pregnancy BMI, however its affiliation with GWG stays unsure, because of the lack of quantitative sodium consumption measurements.
In abstract, our findings recommend that GWG and food plan high quality must be thought of key targets in antenatal care, and that routine weight and diet counseling could assist scale back PTB and associated issues.
Abbreviations
The following abbreviations are used on this manuscript:
| aOR | adjusted odds ratio |
| BMI | Body Mass Index |
| CC | Clinical Center |
| CDC | Centers for Disease Control and Prevention |
| CI | confidence interval |
| DALYs | disability-adjusted life-years |
| EHIS | European Health Interview Survey |
| GBD | Global Burden of Disease, Injuries and Risk Factors |
| GDM | gestational diabetes mellitus |
| GHT | gestational hypertension |
| GWG | gestational weight achieve |
| IOM | Institute of Medicine |
| LBW | low beginning weight |
| LGA | large-for-gestational age |
| LR | logistic regression |
| PTB | preterm beginning |
| SDI | Socio-Demographic Index |
| SE | customary error |
| SGA | small-for-gestational age |
| SPSS | Statistical Package for Social Sciences |
| US | United States |
| WHO | World Health Organization |
| β | coefficient |
Supplementary Materials
The following supporting info may be downloaded at: https://www.mdpi.com/article/10.3390/nu18091403/s1, Supplementary Material S1: STROBE guidelines.
Author Contributions
Conceptualization: E.P., A.S. (Andrea Szabó), E.O.-P., A.S. (Anita Sisák), R.M., G.N. and H.O.; methodology: E.P., A.S. (Andrea Szabó), A.S. (Anita Sisák) and E.O.-P.; software program: E.P., A.S. (Anita Sisák) and M.G.; formal evaluation: E.P., A.S. (Anita Sisák), A.S. (Anna Szolnoki), and M.G.; writing—authentic draft preparation: E.P., A.S. (Anita Sisák), A.S. (Anna Szolnoki) and M.G.; writing—evaluate and modifying: E.P., A.S. (Anita Sisák), M.G., A.S. (Andrea Szabó), R.M. and H.O.; supervision: G.N., H.O. and E.P. All authors have learn and agreed to the printed model of the manuscript.
Institutional Review Board Statement
The examine protocol was authorized by the Regional and Institutional Human Medical Biological Research Ethics Committee of the University of Szeged, Hungary. Approval reference quantity: 4419; 256/2018-SZTE. Approval date: 10 December 2018.
Informed Consent Statement
Written knowledgeable consent was obtained from all topics concerned within the examine.
Data Availability Statement
The dataset is on the market from the Corresponding creator on affordable request.
Conflicts of Interest
The authors declare no conflicts of curiosity. The funders had no position within the design of the examine; within the assortment, analyses, or interpretation of information; within the writing of the manuscript; or within the choice to publish the outcomes.
Funding Statement
This analysis was supported by the Hetényi Géza Research Grant of the Faculty of Medicine, University of Szeged (2019). The APC was funded by the University of Szeged Open Access Fund, Grant Nr. 8502.
Footnotes
Disclaimer/Publisher’s Note: The statements, opinions and information contained in all publications are solely these of the person creator(s) and contributor(s) and never of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim accountability for any damage to individuals or property ensuing from any concepts, strategies, directions or merchandise referred to within the content material.
References
- 1.World Health Organization Preterm Birth. [(accessed on 24 February 2026)]. Available on-line: https://www.who.int/news-room/fact-sheets/detail/preterm-birth.
- 2.Centers for Disease Control and Prevention Preterm Birth. [(accessed on 24 February 2026)]; Available on-line: https://www.cdc.gov/maternal-infant-health/preterm-birth/index.html.
- 3.Perin J., Mulick A., Yeung D., Villavicencio F., Lopez G., Strong Okay.L., Prieto-Merino D., Cousens S., Black R.E., Liu L. Global, regional, and nationwide causes of under-5 mortality in 2000–2019: An up to date systematic evaluation with implications for the Sustainable Development Goals. Lancet Child Adolesc. Health. 2022;6:106. doi: 10.1016/S2352-4642(21)00311-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Liang X., Lyu Y., Li J., Li Y., Chi C. Global, regional, and nationwide burden of preterm beginning, 1990–2021: A scientific evaluation from the worldwide burden of illness examine 2021. eClinicalMedicine. 2024;76:102840. doi: 10.1016/j.eclinm.2024.102840. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Hungarian Central Statistical Office (KSH) Csecsemőhalálozás. [(accessed on 26 April 2026)];2019 Available on-line: https://www.ksh.hu/stadat_files/nep/hu/nep0058.html.
- 6.Hungarian Central Statistical Office (KSH) Demográfiai Évkönyv. [(accessed on 24 February 2026)];2023 Available on-line: https://www.ksh.hu/evkonyvek/2023/demografiai-evkonyv-2023/html/indexhun.html.
- 7.Raju T.N.Okay., Pemberton V.L., Saigal S., Blaisdell C.J., Moxey-Mims M., Buist S. Long-Term Healthcare Outcomes of Preterm Birth: An Executive Summary of a Conference Sponsored by the National Institutes of Health. J. Pediatr. 2017;181:309–318. doi: 10.1016/j.jpeds.2016.10.015. [DOI] [PubMed] [Google Scholar]
- 8.Turai R., Schandl M., Dergez T., Vass R.A., Kvárik T., Horányi E., Balika D., Mammel B., Gyarmati J., Fónai F., et al. Az extrém alacsony születési súlyú koraszülöttek hyperglykaemiájának korai és késői szövődményei. Orv. Hetil. 2019;160:1270–1278. doi: 10.1556/650.2019.31455. [DOI] [PubMed] [Google Scholar]
- 9.Stegmann-Woessner G., Bartmann P., Mitschdoerfer B., Wolke D. Forever untimely: Adults born preterm and their life challenges. Early Hum. Dev. 2025;204:106248. doi: 10.1016/j.earlhumdev.2025.106248. [DOI] [PubMed] [Google Scholar]
- 10.Cleveland Clinic Preterm Birth. [(accessed on 24 February 2026)]. Available on-line: https://my.clevelandclinic.org/health/diseases/21479-premature-birth.
- 11.Fuchs F., Monet B., Ducruet T., Chaillet N., Audibert F. Effect of maternal age on the danger of preterm beginning: A big cohort examine. PLoS ONE. 2018;13:e0191002. doi: 10.1371/journal.pone.0191002. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Keiser A.M., Salinas Y.D., DeWan A.T., Hawley N.L., Donohue P.Okay., Strobino D.M. Risks of preterm beginning amongst non-Hispanic black and non-Hispanic white ladies: Effect modification by maternal age. Paediatr. Perinat. Epidemiol. 2019;33:346–356. doi: 10.1111/ppe.12572. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Khander A., Stern E., Gerber R.S., Fox N.S. The affiliation between obstetrical historical past and preterm beginning in ladies with uterine anomalies. J. Matern. Neonatal Med. 2018;31:2550–2554. doi: 10.1080/14767058.2017.1347625. [DOI] [PubMed] [Google Scholar]
- 14.Orvos H., Hoffmann I., Frank I., Katona M., Pál A., Kovács L. The perinatal consequence of being pregnant with out prenatal care: A retrospective examine in Szeged, Hungary. Eur. J. Obstet. Gynecol. Reprod. Biol. 2002;100:171–173. doi: 10.1016/S0301-2115(01)00471-7. [DOI] [PubMed] [Google Scholar]
- 15.Blondel B., Macfarlane A., Gissler M., Breart G., Zeitlin J. General obstetrics: Preterm beginning and a number of being pregnant in European nations taking part within the PERISTAT challenge. BJOG Int. J. Obstet. Gynaecol. 2006;113:528–535. doi: 10.1111/j.1471-0528.2006.00923.x. [DOI] [PubMed] [Google Scholar]
- 16.Banderali G., Martelli A., Landi M., Moretti F., Betti F., Radaelli G., Lassandro C., Verduci E. Short and long run well being results of parental tobacco smoking throughout being pregnant and lactation: A descriptive evaluate. J. Transl. Med. 2015;13:327. doi: 10.1186/s12967-015-0690-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Fogarasi-Grenczer A., Balázs P. The correlation between smoking, environmental tobacco smoke and preterm beginning. Orv. Hetil. 2012;153:690–694. doi: 10.1556/OH.2012.29325. [DOI] [PubMed] [Google Scholar]
- 18.Baer R.J., Chambers C.D., Ryckman Okay.Okay., Oltman S.P., Rand L., Jelliffe-Pawlowski L.L. Risk of preterm and early time period beginning by maternal drug use. J. Perinatol. 2019;39:286–294. doi: 10.1038/s41372-018-0299-0. [DOI] [PubMed] [Google Scholar]
- 19.Ikehara S., Kimura T., Kakigano A., Sato T., Iso H., the Japan Environment Children’s Study Group Association between maternal alcohol consumption throughout being pregnant and threat of preterm supply: The Japan Environment and Children’s Study. BJOG Int. J. Obstet. Gynaecol. 2019;126:1448–1454. doi: 10.1111/1471-0528.15899. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Shenassa E.D., Widemann L.G., Hunt C.D. Antepartum Depression and Preterm Birth: Pathophysiology, Epidemiology, and Disparities because of structural racism. Curr. Psychiatry Rep. 2021;23:14. doi: 10.1007/s11920-021-01223-1. [DOI] [PubMed] [Google Scholar]
- 21.Aune D., Schlesinger S., Henriksen T., Saugstad O., Tonstad S. Physical exercise and the danger of preterm beginning: A scientific evaluate and meta-analysis of epidemiological research. BJOG Int. J. Obstet. Gynaecol. 2017;124:1816–1826. doi: 10.1111/1471-0528.14672. [DOI] [PubMed] [Google Scholar]
- 22.Baczyńska-Strzecha M., Kalinka J. Assessment of correlation between vitamin D degree and prevalence of preterm births within the inhabitants of pregnant ladies in Poland. Int. J. Occup. Med. Environ. Health. 2017;30:933–941. doi: 10.13075/ijomeh.1896.01146. [DOI] [PubMed] [Google Scholar]
- 23.Carmichael S., Yang W., Shaw G. Maternal dietary nutrient consumption and threat of preterm supply. Am. J. Perinatol. 2013;30:579–588. doi: 10.1055/s-0032-1329686. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Charoenratana C., Leelapat P., Traisrisilp Okay., Tongsong T. Maternal iodine insufficiency and antagonistic being pregnant outcomes. Matern. Child Nutr. 2015;12:680. doi: 10.1111/mcn.12211. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Behrman R.E., Butler A.S. Preterm Birth: Causes, Consequences, and Prevention. National Academies Press; Washington, DC, USA: 2007. [DOI] [PubMed] [Google Scholar]
- 26.Goldenberg R.L., Culhane J.F., Iams J.D., Romero R. Epidemiology and causes of preterm beginning. Lancet. 2008;371:75–84. doi: 10.1016/S0140-6736(08)60074-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Olafsdottir A.S., Skuladottir G.V., Thorsdottir I., Hauksson A., Steingrimsdottir L. Maternal food plan in early and late being pregnant in relation to weight achieve. Int. J. Obes. 2006;30:492–499. doi: 10.1038/sj.ijo.0803184. [DOI] [PubMed] [Google Scholar]
- 28.Liu L., Ma Y., Wang N., Lin W., Liu Y., Wen D. Maternal physique mass index and threat of neonatal antagonistic outcomes in China: A scientific evaluate and meta-analysis. BMC Pregnancy Childbirth. 2019;19:2249. doi: 10.1186/s12884-019-2249-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Instiute of Medicine . Weight Gain During Pregnancy: Reexamining the Guidelines. National Academies Press; Washington, DC, USA: 2009. [PubMed] [Google Scholar]
- 30.Palumbo A.M., Muraca G.M., Fuller A., Keown-Stoneman C.D., Birken C.S., Maguire J.L., Anderson L.N. The affiliation between self-reported complete gestational weight achieve by pre-pregnancy physique mass index and average to late preterm beginning. BMC Pregnancy Childbirth. 2025;25:27. doi: 10.1186/s12884-024-07106-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Goldstein R.F., Abell S.Okay., Ranasinha S., Misso M., Boyle J.A., Black M.H., Li N., Hu G., Corrado F., Rode L., et al. Association of Gestational Weight Gain with Maternal and Infant Outcomes: A Systematic Review and Meta-analysis. JAMA. 2017;317:2207–2225. doi: 10.1001/jama.2017.3635. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Rogozińska E., Zamora J., Marlin N., Betrán A.P., Astrup A., Bogaerts A., Cecatti J.G., Dodd J.M., Facchinetti F., Geiker N.R.W., et al. Gestational weight achieve exterior the Institute of Medicine suggestions and antagonistic being pregnant outcomes: Analysis utilizing particular person participant information from randomised trials. BMC Pregnancy Childbirth. 2019;19:2472. doi: 10.1186/s12884-019-2472-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Perumal N., Wang D., Darling A.M., Liu E., Wang M., Ahmed T., Christian P., Dewey Okay.G., Kac G., Kennedy S.H., et al. Suboptimal gestational weight achieve and neonatal outcomes in low and center revenue nations: Individual participant information meta-analysis. BMJ. 2023;382:e072249. doi: 10.1136/bmj-2022-072249. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Gete D.G., Waller M., Mishra G.D. Effects of maternal diets on preterm beginning and low beginning weight: A scientific evaluate. Br. J. Nutr. 2020;123:446–461. doi: 10.1017/S0007114519002897. [DOI] [PubMed] [Google Scholar]
- 35.Kibret Okay.T., Chojenta C., Gresham E., Tegegne T.Okay., Loxton D. Maternal dietary patterns and threat of antagonistic being pregnant and beginning outcomes: A scientific evaluate and meta-analysis. Public Health Nutr. 2019;22:506–520. doi: 10.1017/S1368980018002616. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.O’Reilly J.R., Reynolds R.M. The threat of maternal weight problems to the long-term well being of the offspring. Clin. Endocrinol. 2013;78:9–16. doi: 10.1111/cen.12055. [DOI] [PubMed] [Google Scholar]
- 37.Poston L. Maternal weight problems, gestational weight achieve and food plan as determinants of offspring long run well being. Best Pract. Res. Clin. Endocrinol. Metab. 2012;26:627–639. doi: 10.1016/j.beem.2012.03.010. [DOI] [PubMed] [Google Scholar]
- 38.Veena S.R., Gale C.R., Krishnaveni G.V., Kehoe S.H., Srinivasan Okay., Fall C.H. Association between maternal dietary standing in being pregnant and offspring cognitive perform throughout childhood and adolescence; a scientific evaluate. BMC Pregnancy Childbirth. 2016;16:220. doi: 10.1186/s12884-016-1011-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Teede H.J., Bailey C., Moran L.J., Khomami M.B., Enticott J., Ranasinha S., Rogozińska E., Skouteris H., Boyle J.A., Thangaratinam S., et al. Association of Antenatal Diet and Physical Activity-Based Interventions with Gestational Weight Gain and Pregnancy Outcomes: A Systematic Review and Meta-analysis. JAMA Intern. Med. 2022;182:106–114. doi: 10.1001/jamainternmed.2021.6373. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Mustafa H.J., Seif Okay., Javinani A., Aghajani F., Orlinsky R., Alvarez M.V., Ryan A., Crimmins S. Gestational weight achieve beneath as a substitute of throughout the tips per class of maternal weight problems: A scientific evaluate and meta-analysis of obstetrical and neonatal outcomes. Am. J. Obstet. Gynecol. MFM. 2022;4:100682. doi: 10.1016/j.ajogmf.2022.100682. [DOI] [PubMed] [Google Scholar]
- 41.Wang Z., Cui X., Yu H., Chan E.-M., Shi Z., Shi S., Shen L., Sun Z., Song Q., Lu W., et al. Association of Beverage Consumption throughout Pregnancy with Adverse Maternal and Offspring Outcomes. Nutrients. 2024;16:2412. doi: 10.3390/nu16152412. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Ferreira L.B., Lobo C.V., do Carmo A.S., Souza R.C.V.E., dos Santos L.C. Dietary Patterns During Pregnancy and Their Association with Gestational Weight Gain and Anthropometric Measurements at Birth. Matern. Child Health J. 2022;26:1464–1472. doi: 10.1007/s10995-022-03392-8. [DOI] [PubMed] [Google Scholar]
- 43.Polanek E., Karai A., Molnár R., Németh G., Orvos H., Balogh P., Paulik E. Association between sociodemographic, obstetric, and way of life components amongst Hungarian pregnant ladies—A cross-sectional examine. J. Obstet. Gynaecol. Res. 2022;48:2541–2551. doi: 10.1111/jog.15364. [DOI] [PubMed] [Google Scholar]
- 44.Nashwan A.J., Joy G.V. The 2024 Declaration of Helsinki Revision: Relevance to Nursing Research. J. Adv. Nurs. 2026;82:3986–3996. doi: 10.1111/jan.70082. [DOI] [PubMed] [Google Scholar]
- 45.von Elm E., Altman D.G., Egger M., Pocock S.J., Gøtzsche P.C., Vandenbroucke J.P., Initiative S. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) assertion: Guidelines for reporting observational research. Lancet. 2007;370:1453–1457. doi: 10.1016/S0140-6736(07)61602-X. [DOI] [PubMed] [Google Scholar]
- 46.Hungarian Central Statistical Officel (KSH) Táplálkozás, Tápláltság. [(accessed on 24 February 2026)];2019 Available on-line: https://www.ksh.hu/docs/hun/xftp/idoszaki/elef/taplalkozas_2019/index.html.
- 47.Tingleff T., Vikanes A., Räisänen S., Sandvik L., Murzakanova G., Laine Okay. Risk of preterm beginning in relation to historical past of preterm beginning: A population-based registry examine of 213 335 ladies in Norway. BJOG Int. J. Obstet. Gynaecol. 2022;129:900–907. doi: 10.1111/1471-0528.17013. [DOI] [PubMed] [Google Scholar]
- 48.Mihara Y., Kado H., Yokota I., Shiotsu Y., Sonomura Okay., Kusaba T., Hatta T., Matoba S., Tamagaki Okay. Rapid weight reduction with dietary salt restriction in hospitalized sufferers with persistent kidney illness. Sci. Rep. 2019;9:8787. doi: 10.1038/s41598-019-45341-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Juraschek S.P., Miller E.R., Chang A.R., Anderson C.A., Hall J.E., Appel L.J. Effects of Sodium Reduction on Energy Metabolism, Weight, Thirst, and Urine Volume: Results from the DASH-Sodium Trial. Hypertension. 2020;75:723. doi: 10.1161/HYPERTENSIONAHA.119.13932. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Ghada Y. Salt and Hypertension: Current Views. [(accessed on 24 February 2026)];Eur. Soc. Cardiol. 2022 22 Available on-line: [Google Scholar]
- 51.McEvoy J.W., McCarthy C.P., Bruno R.M., Brouwers S., Canavan M.D., Ceconi C., Christodorescu R.M., Daskalopoulou S.S., Ferro C.J., Gerdts E., et al. 2024 ESC Guidelines for the administration of elevated blood strain and hypertension. Eur. Heart J. 2024;45:3912–4018. doi: 10.1093/eurheartj/ehae178. [DOI] [PubMed] [Google Scholar]
Associated Data
This part collects any information citations, information availability statements, or supplementary supplies included on this article.
Supplementary Materials
Data Availability Statement
The dataset is on the market from the Corresponding creator on affordable request.
This web page was created programmatically, to learn the article in its authentic location you possibly can go to the hyperlink bellow:
https://pmc.ncbi.nlm.nih.gov/articles/PMC13164820/
and if you wish to take away this text from our website please contact us
