A ‘Standard of Care Plus’ Model for Preterm Birth Prevention: Integrating Nutrient and Gene Variant Analysis with Targeted Interventions: A Prospective Observational Study

A ‘Standard of Care Plus’ Model for Preterm Birth Prevention: Integrating Nutrient and Gene Variant Analysis with Targeted Interventions: A Prospective Observational Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A ‘Standard of Care Plus’ Model for Preterm Birth Prevention: Integrating Nutrient and Gene Variant Analysis with Targeted Interventions: A Prospective Observational Study Leslie Stone, Emily Rydbom, P Michael Stone, Daniel Kim This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6739623/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose: High rates of adverse maternal and neonatal outcomes, such as preterm birth (PTB), hypertensive disorders of pregnancy (HDP), gestational diabetes mellitus (GDM), small for gestational age (SGA), and large for gestational age (LGA) persist in the US, highlighting the need for prevention and effective interventions beyond the current standard of care (SOC) particularly in diverse, socio-economically challenged populations. Objective: A prospective observational study evaluated a targeted diet and lifestyle intervention incorporating select nutrient and gene variant analysis and personalized trimester-based nutrition counseling and supplementation in collaboration with in-person standard of care (PLUS) compared to standard of care alone (SOC) in reducing adverse outcomes. The impact of mode of PLUS delivery was also evaluated: individual-virtual vs in-person group. Results: This study compared a Nevada PLUS cohort (N=15): high-risk participants, all covered by Medicaid, who received the PLUS intervention virtually and an Oregon PLUS cohort (N=387): moderate-risk participants with 50% Medicaid coverage who received the PLUS intervention through in-person group sessions, against each other and against regional SOC outcomes. The Nevada PLUS data showed non-significant reductions across all measured adverse outcomes because of small sample size. The Oregon PLUS showed highly significant risk reductions in all outcomes (p-value < .001). When comparing the outcomes of the Nevada (virtual) and Oregon (in-person) PLUS cohorts directly, no statistically significant differences were found based on how the PLUS model was delivered. Given no significant difference by delivery mode, the two PLUS cohorts were combined (pooled N=402). This pooled group revealed highly significant risk reductions in all outcomes (p -value < .001): PTB (RR = .229), HDP (RR .114), GDM (RR .057), SGA (RR .246), and LGA (RR .347) compared to regional SOC outcomes. Conclusion: These findings suggest that implementing select nutrient and gene variant analysis with targeted nutritional and lifestyle interventions in collaboration with in-person standard of care is associated with significant reductions in the incidence of key adverse maternal and neonatal outcomes in diverse pregnant populations, and that an individual-virtual mode of PLUS delivery appears as effective as an in-person group mode. Figures Figure 1 Figure 2 Figure 3 Introduction The United States (US) faces a significant public health challenge with preterm birth (PTB) rates that are alarmingly high compared to other affluent nations. This disparity is particularly pronounced within socioeconomically disadvantaged communities & within racial minorities [1]. In the U.S. (2022), infant mortality rates due to prematurity/low birthweight account for 14.0% of all infant death [2]. The consequences of PTB extend far beyond the neonatal period, contributing to increased lifelong morbidity and mortality, and imposing a substantial economic burden on healthcare systems. Furthermore, infants born small for SGA, even at term, represent a distinct population at heightened risk for chronic disease development, not only during their neonatal period (F1 generation), but also throughout their adult lives, underscoring the critical role of the intrauterine environment in shaping long-term health trajectories [3,4,5]. In the US, severe maternal morbidity (SMM) rose from 69.5 to 79.7 per 10,000 delivery hospitalizations between 2012 and 2019 [6]. Concurrently, US obesity rates increased from 30.5% (1999-2000) to 44.9% (2017-2020), elevating risks for conditions like hypertension (HTN), diabetes (DM), and cardiovascular disease (CVD), as well as pregnancy-specific issues such as hypertensive disorders (HDP), preeclampsia (PreE), preterm birth (PTB), gestational diabetes (GDM), and large for gestational age (LGA) infants [7]. Chronic HTN in pregnancy doubled between 2007 and 2021, with only 60% treated [8]. Uncontrolled HTN significantly raises risks for PreE, PTB, and SGA, which in turn increases future non-communicable disease (NCD) risk in offspring. Preterm birth occurred in 10.4% of US births in 2022 and is associated with increased risk for HTN, CVD, DM, osteoporosis, maternal complications of PTB, GDM, HDP, and neonatal SGA [9]. SGA occurred in 11.1% of the US population in 2021 and is associated with neurodevelopmental delay, infant and neonatal mortality, and chronic disease in the offspring [10]. LGA neonates comprised 11% of US neonates in 2018 [11], and are prone to develop insulin resistance, obesity, diabetes mellitus, early cardiovascular disease, and several cancer types [12]. Accelerating NCDs in reproductive adults drives a feed forward cycle of chronic illness and negative maternal/infant outcomes, with greater impact on populations facing racial, environmental, socio-economic, and food access disparities [13]. Nutrition While tackling the rising burden of NCDs is challenging due to multiple factors, predispositions appear modifiable in the perinatal period through interventions related to macro/micro-nutrient availability, gut microbiota, dietary composition (fatty acids, carbohydrates, protein), and toxic exposure [14]. Proper nutrition during critical periods significantly impacts fertility, pregnancy outcomes, and the lifelong health of mothers and their children [15, 16]. However, prevalent Western diets rich in processed, nutrient-poor, calorie-dense foods lacking essential micronutrients (like iron, iodine, folate, B12, D, choline, and omega-3s) pose a challenge [15]. Access to nutrient-dense food is difficult for women across socioeconomic levels, meaning balanced diets in pregnancy cannot be assumed, and single-nutrient solutions are likely ineffective [15, 17]. Standard obstetric care typically screens for iron deficiency anemia, not other nutrient deficiencies. While pregnancy-specific nutrient standards are lacking, applying reproductive age norms reveals common key micronutrient deficiencies that increase risk for adverse maternal and neonatal outcomes. In fact, 95% of pregnant women in the US fail to meet dietary recommendations for at least one nutrient through diet alone, with one in three remaining at risk even with supplements [15, 18]. Iron [19,20,21], carnitine [22], zinc [23,24], and Vitamin D [25, 26, 27, 28] deficiencies are associated with many maternal and neonatal morbidities. Interestingly, giving docosahexaenoic acid (DHA) in pregnancy irrespective of maternal serum status decreases the risk of PTB [29]. Understanding how these prevalent nutritional deficiencies translate into significant health risks for both mother and child is paramount, and epigenetic processes provide a critical explanatory framework. Epigenetics Pre- and post-transcriptional epigenetic processes may explain how gestational nutrition and exposures impact immediate pregnancy outcomes and long-term mother/child disease risk. Optimizing both epigenetic and metabolic function requires a remarkable, overlapping set of micronutrients and vitamins (e.g., iron, calcium, B vitamins, zinc, magnesium, among others [30]. For example, methylation for these functions depends on dietary factors like betaine and choline, plus co-factors such as 5-methyl tetrahydrofolate and Vitamin B12 [30]. To bridge the gap between burgeoning genomic data and tangible clinical benefits, the investigators undertook a systematic process of single nucleotide polymorphism (SNP) selection based on the following criteria: Strength of association with maternal and neonatal adverse outcomes under study Overlapping association with SNPs implicated in risk for chronic disease SNP frequency in the population Modifiability of the gene or gene product through nutrition, nutrient supplementation, and lifestyle modification. To further personalize nutritional and lifestyle advice, 42 SNPs in 27 genes across 11 key biological processes were selected. Interventions, incorporated into time-sensitive plans, prioritized processes with multiple variants and high overlap with adverse maternal/neonatal outcomes and chronic disease risk. SNPs without diet or lifestyle remediation were excluded, and a polygenic risk score was not created. (Figure 1: Venn diagram) [31]. A Personalized and Proactive Approach It is in this context that a Standard of Care Plus (PLUS) model was conceived, augmenting current Standard of Care (SOC) by providing preventive collaborative nutritional counseling and lifestyle care, based on select micronutrient and genomic analysis, in a highly personalized and time-cognizant manner. The original 50% Medicaid, in-person group educational model realized statistically significant reductions in aggregate occurrence of preeclampsia, GDM, SGA and LGA compared to local private practice and community health clinic SOC [14]. The current applications recognize the need for risk reduction evaluation of PTB, a virtual application, a larger and more diverse population under study, and a prospective observational study design. Methods Primary Application Between January 1, 2011, and December 31, 2017, all pregnant women at a Jackson County, Oregon private practice received a PLUS model of prenatal care, augmenting standard obstetric care with in-person group sessions led by a board-certified holistic nutritionist. These sessions, up to 90 minutes per trimester and postpartum, included nutrition/lifestyle assessment, education, and personalized plans (covering diet, vitamins, lifestyle) based on health history, anthropometrics, select serum micronutrients, and gene variants. An extra 30 minutes of nutritionist time per trimester/postpartum was allocated for plan adjustments. Postpartum support was ongoing, and all deliveries were in-hospital. Secondary Application From August 1, 2022, to July 1, 2023, a prospective intervention study in a Clark County, NV private practice provided a cost-free virtual PLUS model to pregnant women (<20 weeks’ gestation) with managed care organization (MCO) coverage. This model included six hours of individual virtual assessment, education, and intervention by a BCHN, supplementing standard in-person OB/GYN care. Exclusions were multiple gestations and fetal demise. All deliveries were in-hospital and completed by October 2023. All materials were adapted to an 8th-grade reading level and translated into Spanish. Nutrition and lifestyle interventions involved HIPAA-compliant virtual communication: an initial BCHN phone call, three scheduled contacts (per trimester/postpartum), and unlimited participant-initiated texting. Clinic providers and staff received a 30-minute virtual training and an in-clinic logistical visit. Further OB provider communication regarding intervention changes or nutrient diagnoses occurred via secure email. Data was stored in a separate, secure EHR. Participant and publication consent in both primary and secondary application was procured in accordance with the Declaration of Helsinki 1964, and ethics approval was obtained through Southern Oregon Internal Review Board. Upon consent, the participants underwent SOC evaluation by their OB provider, including height, weight, BMI, and standard laboratory and imaging evaluation. In addition, each PLUS participant received the following assessments: Nutritionist care – 60 minutes per trimester by phone Serum micronutrients zinc, carnitine and 25-hydroxy cholecalciferol (25-OH D) drawn at intake, 24–28-week gestation, and 6-8 weeks postpartum. Dried blood spot DHA levels at intake, 24–28-week gestation, and breast milk DHA at 6-8 weeks postpartum. Buccal swab 42 gene variant panel obtained at intake. At intake the PLUS participants virtually received their individualized food and lifestyle plans based on OB provider anthropometric, laboratory and imaging assessments, followed by trimester-by-trimester personalized adaptations dependent on subsequent PLUS testing and clinical response obtained through real-time chart review by board-certified MD investigator. Interventions The PLUS diet was based on an adapted Mediterranean Diet modified by a low glycemic index with a 40% carbohydrate / 30% fat / 30% protein ratio. Macronutrient requirements were calculated, and adjustments were made each trimester to the core food plan based on nationally accepted pregnancy-specific Mifflin standards, with further refinement based on body mass index (BMI), activity, and dietary preferences. Nutrition education was emphasized & outlined (Appendix-3). Sleep quality, movement, exogenous stress and mood were assessed at intake, 24-28 weeks’ gestation, and 6-8 weeks postpartum. Other common pregnancy-related concerns were addressed at each visit (Appendix-4). PLUS patients received a multi-nutrient prenatal supplement pack (Appendix-1) and a probiotic (Appendix-2). Customized Vitamin D3 and iron supplementation occurred if identified needs could not be met with diet and lifestyle modification alone. Other identified micronutrient insufficiencies were managed with nutrient-rich food incorporation in the diet. Table 1: Intervention Comparisons Component SOC Intervention PLUS Oregon Intervention PLUS Nevada Intervention Routine Nutrition Professional None X In-person group – 90 minutes per trimester + additional 30 minutes as needed X Virtual – 60 minutes per trimester + additional 30 minutes as needed Meal Plan None X Initiated at any trimester upon first intake, with individual needs adjusted throughout pregnancy. X Initiated at any trimester upon first intake, with individual needs adjusted throughout pregnancy. Prenatal Vitamins X Prenatal with iron and folic acid. 200-400 mg of DHA. X Prenatal nutrient packet (Appendix-1) was taken daily from the 1st trimester (or earliest possible) through postpartum X Prenatal nutrient packet (Appendix-1) was taken daily from the 1st trimester (or earliest possible) through postpartum Probiotic None X Probiotic (Appendix-2) was taken daily from the 1st trimester (or earliest possible) through postpartum X Probiotic (Appendix-2) was taken daily from the 1st trimester (or earliest possible) through postpartum Standard Labs X 1 st , 2 nd , 3 rd Trimesters (Appendix-6) X SOC Labs X SOC Labs Micronutrient Labs None X Serum zinc, carnitine (free, total, acyl), 25-OH D drawn at intake, 24–28-week gestation, and 6-8 weeks postpartum. X Serum zinc, carnitine, and 25-OH D were tested at intake, 24-28 weeks, and 6-8 weeks postpartum. DHA was measured from dried blood spots (intake) and breast milk (6-8 weeks postpartum). Nutrigenomics None X MTHFR C677T & MTHFR A1298C X 42 SNPs in 27 genes The 42 SNP panel was utilized in the Nevada PLUS group to personalize diet and lifestyle recommendations versus a 2 SNP panel in the Oregon PLUS group. RS numbers, maternal and neonatal outcome associations, and prevalence in the Nevada PLUS population are included in Appendix 8. The SNP datasets generated during the current study are deposited in the National Center for Biotechnology Information dbSNP databank under BioProject Accession number PRJNA1283159. Primary and Secondary Outcomes 2-prop Z test, odds ratio (OR), and relative risk (RR) analysis were accomplished through Python. De-identification of all personal data occurred prior to analysis. The primary outcome measure evaluated the frequency of preterm birth (PTB) <37 weeks’ gestation. Secondary outcomes measured included the frequency of hypertensive disorders of pregnancy, gestational diabetes mellitus, small for gestational age, and large for gestational age with defined diagnostic criteria (Appendix-7). The frequency of each adverse outcome in the Nevada PLUS population was compared to the frequency of adverse outcomes in two populations. Clark County, NV Medicaid SOC population from healthysouthernnevada.org 2021, representing the regional comparator Oregon PLUS population, representing the program comparator in a different region. Results Comparative Characteristics Nevada PLUS study group and Clark County, NV SOC group share similar age, locality, gravidity, parity, race, (BMI), and drug use (healthysouthernnevada.org 2021), except that the Nevada PLUS study group was 100% insured through Medicaid. The Oregon PLUS study group share several characteristics with the Nevada PLUS group, including gravidity, parity, and smoking, alcohol, and drug use history, but differ significantly in age (31.6 vs 25.4 years, respectively) and race (93.3% vs 17% Caucasian, respectively) (Table 1 ). A Medicaid payor source accounted for 100% of the Nevada PLUS group vs 50% of the Oregon PLUS group. Table 2 Comparative Characteristics of Nevada PLUS and Oregon PLUS Characteristic Nevada PLUS (n = 15) Oregon PLUS (n = 387) Age (years) 25.4 (SD 5.187) 31.6 (SD 5.378) Advanced for Maternal Age (%) 0 29 Teen (%) 20 0.74 Gravidity 2.4 (SD 1.665) 2.97 (SD 1.76) Parity 1 (SD 1.264) 1.13 (SD 1.17) Race (%) Black 33 < 1 Hispanic 28 5 Asian 11 < 1 Native American 0 < 1 Not Specified 11 0 Caucasian 17 93.3 Smoking, alcohol, drug history (%) 22 21.7 Payer Source: Nevada − 100% Medicaid & Oregon − 50% Medicaid More nuanced are the differences in BMI and excessive weight gain between the 2 study groups. Although the average BMI at first visit was not significantly different, the maximum BMI in the Nevada PLUS group was 35.1 kg/m 2 compared to 54 kg/m 2 in the Oregon PLUS group. BMI > 30 kg/m 2 occurred in 20% of the Nevada PLUS group and only 11% in the Oregon PLUS group. Weight gain > 40 lbs occurred in 31% of the Nevada PLUS group vs 25.4% of the Oregon PLUS group (Table 2 ). Table 3 Body Mass Index (BMI) and Excessive Gestational Weight Gain (EGWG) Descriptive Statistics in Nevada (SOC Plus) and Oregon (SOC Plus) Characteristic Nevada PLUS Oregon PLUS BMI at First Visit Mean 25.37 (4.716) 24.8 (SD 5.3) Minimum 17.72 17 Maximum 35.1 54 BMI Ranges : 25–30 27% 33% > 30 20% 11% EGWG > 40 lbs 31% 25.4% Primary and Secondary Outcomes Compared to their respective SOC populations, the PLUS pooled cohort exhibited substantially lower risks across all five outcomes, including preterm birth (RR = 0.23), hypertensive disorders of pregnancy (RR = 0.11), gestational diabetes (RR = 0.06), small for gestational age (RR = 0.25), and large for gestational age (RR = 0.35). These findings suggest that individuals in the SOC group were between three and seventeen times more likely to experience each adverse outcome than those in the PLUS intervention cohort. The Nevada PLUS study group experienced no PTB, no HDP, no SGA, one GDM, and one LGA. Comparison of Nevada PLUS to the Clark County, Nevada population revealed reduced rates of all adverse outcomes measured, but p-values were not significant because of a smaller Nevada PLUS sample size, p-values ranging from 0.4003 for PTB to > 0.99 for HDP (Table 3 ). The smaller sample size reflects the commonly encountered challenge of identifying first and early second trimester pregnancies. Table 4 Prevalence of Adverse Outcomes: Nevada SOC Plus compared to Clark County Medicaid (SOC) Outcome Nevada PLUS* (n = 15) Clark County SOC** (per 100) P-value: Exact Binomial Test Preterm Birth 0 11.2 0.4003 Hypertensive Disorders of Pregnancy 0 5 > 0.99 Gestational DM 1 8.3 > 0.99 Small for Gestational Age 0 9.7 0.389 Large for Gestational Age 1 13 0.7097 *N = 15 **healthysouthernevada.org 2021 No significant difference in outcome frequencies between the Nevada PLUS and the Oregon PLUS was found (Table 4 ). Table 5 Prevalence of Adverse Outcomes: Nevada PLUS compared to Oregon PLUS Outcome Nevada PLUS (n = 15) Oregon PLUS (n = 387) P-value: Fisher's Exact Test Preterm Birth 0 8 > 0.99 Hypertensive Disorders of Pregnancy 0 4 > 0.99 Gestational DM 1 1 0.0733 Small for Gestational Age 0 6 > 0.99 Large for Gestational Age 1 13 0.418 Therefore, the populations were pooled and compared to Oregon SOC adverse outcomes obtained from March of Dimes Report (2022) and from chart review of all Oregon SOC deliveries between 2011 and 2017 at the low-risk community hospital where the Oregon PLUS deliveries occurred concurrently. PTB gestational age at delivery improved over time. The first two PTB occurred in the first year of Oregon PLUS application at 23 and 24 weeks, with all 6 subsequent PTB occurring after 36 0/7 weeks gestation. Highly significant reductions of all adverse maternal and neonatal outcomes appeared in the PLUS pooled study group (Table 5 ). Table 6 Prevalence of Adverse Outcomes: Nevada & Oregon (PLUS Pooled) compared to Oregon SOC Outcome PLUS Pooled Oregon SOC p-value: 1-Prop Z-test Relative Risk of SOC Plus Likelihood of Adverse Outcome in SOC Preterm Birth 2.0% (8/402) 8.7% < 0.0001 0.229 4.37 Hypertensive Disorders 1.0% (4/402) 4.5% < 0.0001 0.114 8.74 Gestational DM 0.5% (2/402) 3.7% < 0.0001 0.057 17.48 Small for Gestational Age 1.5% (6/402) 6.1% < 0.0001 0.246 4.09 Large for Gestational Age 3.5% (14/402) 9.4% < 0.0001 0.347 2.87 1 March of Dimes, Oregon, 2022 / 2 GAHMJ, November 2014, vol 3;6. N = 553, combined community clinic and private practice deliveries 2011–2012 in the same hospital as Oregon (PLUS) Having a PTB in the comparator SOC group appeared 4.37 times more likely than in the pooled PLUS group (RR .229), while HDP were 8.74 times more likely to occur in the SOC group than in the pooled PLUS group (RR .1143). GDM appeared 17.48 times more likely in the SOC group than in the PLUS (RR .057). SGA appeared 4.087 times more likely to occur in the SOC group (RR .246), while LGA appeared 2.87 times more likely to occur in the SOC group than in the pooled PLUS group (RR .347). Figure 2 illustrates a comparative analysis of adverse outcome rates for Oregon PLUS and Oregon SOC, across five key maternal and neonatal health indicators. Figure 3 compares regional and national PTB rates in the PLUS Oregon group emphasizing benefit likely to occur when applied across a larger and broader population. Numbers needed to treat (NNT) calculations were added for clinical relevance and potential cost savings analysis, finding favorably low numbers of patients treated to obtain one fewer adverse event in all outcomes tested (Table 7 ). Table 7 Numbers Needed to Treat (NNT): Nevada with Oregon (PLUS Pooled) compared to Oregon (SOC) Outcomes PLUS Pooled SOC NNT N = 402 Preterm Birth 1.99% 8.7% 1 14.90 Hypertensive Disorders of Pregnancy 1.00% 4.5% 2 28.57 Gestational Diabetes Mellitus 0.50% 3.7% 2 31.25 Small for Gestational Age 1.49% 6.1% 1 21.69 Large for Gestational Age 3.48% 9.4% 1 16.89 Sources ¹ March of Dimes Oregon, 2022 ² gahmj, November 2014, vol 3;6; n = 553, combined community clinic and private practice deliveries 2011–2012 in the same hospital as Oregon (PLUS) Micronutrient and Macronutrient Analysis A matched two tail T-test was used to analyze first-trimester micro- and macro-nutrient deficiency rates for hemoglobin/hematocrit (as a surrogate for iron deficiency), serum zinc, carnitine, Vitamin 25-OH D, and whole blood spot DHA during the first trimester comparing the Nevada PLUS population and the Oregon PLUS population birthing during 2011 and 2012. Regional and national comparators proved difficult to find, poorly validated, and temporally remote. Instead, nutrient deficiency rates were compared to reproductive age women 18–35 years of age, as presented in Lancet 2022: global, regional, and national burdens of common micronutrient deficiencies from 1990–2019 [ 32 ]. No meaningful difference in hemoglobin concentration between the Nevada PLUS and Oregon PLUS populations, (p-value .875) was found, and the national deficiency rate was insignificantly lower, as well (p-value .074), with a range of 15.1%-22%. Hematocrit percentages were not significantly different between Nevada PLUS, Oregon PLUS, and the national rate (p-value range .125-.25), with a range of 11%-22%. Insignificant differences between the study group comparators for serum zinc were found (p-value .388, range 37%-50%), however the pooled study group was significantly lower than the national average for reproductive women of 22% (p-value 4.866 x 10 − 8 ). First trimester 25-OH D insufficiency rate in the Nevada PLUS was 83%, the Oregon PLUS insufficiency rate was 58%, and when pooled were significantly more commonly insufficient than the national rate of 3% (p-value 3.24 x 10 ) and the rate in the United Kingdom of 55% (p-value .0017) [ 32 ]. DHA deficiency rates were compared to reproductive age females in an NHANES analysis during 2011–2012 [ 33 ]. The Nevada PLUS DHA deficiency (< 5%) rate was 89% and was significantly higher than the national average of 68% (p .029). No meaningful regional, national or global comparator for carnitine was found [ 34 ], but both study populations were commonly deficient based on assay reference ranges, and not significantly different from each other. The free carnitine deficiency rate was 77.8% and 56.7%, Nevada PLUS and Oregon PLUS, respectively. The esterified carnitine rate was 55% and 53%, Nevada PLUS and Oregon PLUS, respectively. Lastly, second trimester or early third trimester abnormal one-hour 50 gm oral glucose tolerance test (1-hour OGTT) rate in the Nevada SOC group did not statistically differ from that of the nation, .12% vs 20%, respectively (p-value.198), but the Nevada and Oregon PLUS abnormal occurrence rate is significantly less than the nation, .02% vs 20%, (p-value .01), most likely related to early first and second trimester intervention for elevated maternal BMI and excessive weight gain in the Oregon PLUS group. Compliance The Oregon in-person PLUS group had 85% intake attendance and 70% ongoing compliance (customized nutrition, lifestyle and micronutrient supplementation). In Nevada's PLUS virtual model, intake compliance was 83%, decreasing to 47% (third trimester) and 45% (postpartum). Nevada PLUS nutritionist calls were returned 74% of the time; all subject-initiated calls were completed. Nutrition/lifestyle adherence in Nevada varied (78% second trimester to 53% third), while supplement compliance was 80–94%. Nutrition and lifestyle adherence was assessed each trimester via direct patient questioning using a 5-food frequency questionnaire (Appendix 5). Qualitative data showed the nutrition plan aided food awareness and shopping. Discussion These results suggest that late first/early second trimester application of targeted nutrient, nutrition, and lifestyle guidance based on select micro/macronutrient and genomic analysis, further adjusted for changing physiologic pregnancy need, is associated with reductions in the incidence of PTB, HDP, GDM, SGA, and LGA neonates compared to standard of care alone. Risk reduction is demonstrated over seven years in the Oregon PLUS group. Comparable results were achieved in the slightly younger population in Nevada PLUS, with a more socio-economically disadvantaged and ethnically diverse population. The data also suggest that virtual delivery of the program to pregnant individuals appears as effective as an in-person group mode. The virtual interface solved for many of the factors that compromised compliance in the 2011–2012 Oregon SOC Plus study, specifically: (1) geographic, financial, and social requirements of travel to a classroom four times throughout pregnancy and postpartum care, and (2) lack of immediate text and phone-based support for each subject who might struggle with the dietary and lifestyle changes demanded by the program. In fact, compliance appeared slightly better in the virtual group, and may represent a generational preference, convenience factor, or resource availability. Despite the dissimilarities between the Oregon PLUS group and Nevada PLUS group they shared micronutrient insufficiencies for zinc, carnitine, and 25-OH D. Difficulty in locating applicable and current micronutrient references ranges during pregnancy reveal a glaring need for updated maternal and neonatal standards. Reliance on diet survey-based consumption data do not address the declining nutrient density in our food supply under current agricultural practices [ 35 , 36 , 37 ]. They do not recognize the individual genomic uniqueness that is responsible for much of our diversity, and influences bioavailability of macro/micronutrients. The 42 SNP panel used to customize nutrition and lifestyle recommendations in the high-risk Nevada PLUS group compared to the 2 SNP panel in the moderate-risk Oregon PLUS may have contributed to the statistically equivalent prevalence of adverse outcomes, but principal component analysis of larger data sets are needed to elucidate which features of the model are most effective and identify those that need optimization. More rigorous and time-sensitive peri-natal micro- and macro-nutrient reference ranges need to be established. Food sources need evaluation for nutrient density, with interrogation of agricultural practices that influence food quality. Further work is planned to expand understanding of nutrigenomic impact and durability of effect through interrogation of the imprintome [ 38 , 39 , 40 ]. Lastly, a human-centered, AI-driven digital health platform is being developed to scale the PLUS model and to potentiate early access to preventive care for the reproductive age population. Comparing improved outcomes in PTB, SGA, LGA, GDM, and HDP under the PLUS model to US average rates and associated costs, investigators project potential annual savings [ 41 , 42 , 43 , 44 , 45 ]. Based on 3.6 million births per year [ 46 ], national adoption of the PLUS model is estimated to save the US healthcare system between $ 4.435 billion (NNT model) and $ 43.42 billion (percent reduction model) gross, annually. Declarations Ethics Approval and Consent: Participant consent in both primary and secondary application was procured in accordance with the Declaration of Helsinki 1964, and ethics approval was obtained through Southern Oregon Internal Review Board. Consent for Publication: Consent for publication was obtained simultaneously with participation consent, stipulating de-identification of all data in a HIPAA compliant fashion with dedicated and secure storage. Competing Interests: 1 CMO for GrowBabyHealth.com, Consultant for Metagenics.com, Consultant for DNALife.healthcare: 2 CEO for GrowBabyHealth.com and GrowBabyLifeProject.org (501c3), Consultant for ThisIsNeeded.com, Consultant for Metagenics.com, Consultant for DNALife.healthcare: 3 no competing interest for this publication: 4 no competing interest for this publication. Funding: Molina Health of Nevada Availability of Data & Materials: Generated raw data sets are not publicly available to preserve participant privacy. Publicly available comparative data sets were used in raw data analysis and are referenced throughout the manuscript. Acknowledgements: Tracey Green Chittenden, MD, the Molina-Nevada maternal healthcare team, and Michael Easterday of Molina Healthcare. Anita Gondy, OB-GYN, Ankita Raman, OB-GYN, Saovaros Michaels, OB-GYN, Jenny Schrader, & Bryan Iriye, OB-GYN. Lisa Portera, DC, David Dzielak, PhD, & Sheila Clough. Brent Eck, Ilissa Larimore, Lisa McDonald, Nilima Desai, RD, MPH, & Anu Desai, PhD. Helen Gautschi, MS & Chris Moore. Kristina Harris Jackson, PhD & Bill Harris, PhD. Lucia Aronica, PhD, Joseph Lamb, MD & Stone Medical Family Practice. And to all the mothers & families who have been a part of this empowering project. Authors Information: No additional information. Authors Contribution: 1 conception, design, acquisition, analysis, interpretation, and drafting /revision of the study, specifically abstract, body of work, appendices, references, Tables 2, 3, and 7: 2 conception, design, acquisition, analysis, interpretation, and drafting/revision of the study, specifically abstract, body of work, appendices, Figures 1, 2, and 3, and Tables 1 and 2: 3 conception, design, interpretation and revision, specifically body of work and appendices: 4 conception, design, interpretation and revision, specifically body of work and appendices. 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Katz, Paul Leeson, Bernard Thébaud and Anne-Monique Nuyt, Preterm Birth: Risk Factor for Early-Onset Chronic Disease. CMAJ July 12, 2016, 188 (10) 736-746; https://doi.org/10.1503/cmaj.150450. Korede K Yusef, Deepa Dongarwar, et al, Temporal Trends and Risk of Small for Gestational Age (SGA) infants among Asian American mothers by ethnicity. doi.org/10.1016/jannepidem.2021.07.004. Sneha B Sridhar, Assiamira Ferrara, et al, Risk of Large for Gestational Age Infants in Women with GDM by Race, Ethnicity and BMI Categories. Obstet Gynecol. 2013 Jun; 121(6): 1255-1262. doi: 10.1097/AOG.0b013e318291b15c. Shu-Kay Ng, Adriana Olog, et al. Risk Factors and Obstetric Complications of Large for Gestational Age with Adjustments for Community Effects: Results from a New Cohort Study. BMC Public Health 10, Article: 460 (2010). Maternal Vulnerability in the US-A Shameful Problem for One of the World’s Wealthiest Countries. Surgo Ventures, accessed April 10, 2024. httpss://mvi.surgoventures.org. L Stone, P Michael Stone, E Rydbom, et al. Customized Nutritional Enhancement for Pregnant Women Appears to Lower Incidence of Certain Common Maternal and Neonatal Complications: An Observational Study. Glob Adv Health and Med. 2014 Nov;3(6): 50-5. doi: 10.7453/gahmj. 2014.053. Needed Labs. State of Perinatal Nutrition . Needed Labs, 2023. Marshall NE, Abrams B, Barbour LA, et al. The importance of nutrition in pregnancy and lactation: lifelong consequences. Am J Obstet Gynecol. 2022;226(5):607"632. doi: 10.1016/j.ajog.2021.12.035 AV Perkins, JJ Vanderlelie. Multiple Micronutrient Supplementation and Birth Outcomes: The Potential Importance of Selenium. Placenta. 2016 Dec: 48 Suppl 1: S61-S65. doi: 10.1016/j.placenta.2016.02.007. Epub 2016 Feb 15. PMID: 26919772. Bailey RL, Pac SG, Fulgoni VL, Reidy KC, Catalano PM. Estimation of Total Usual Dietary Intakes of Pregnant Women in the United States. JAMA Netw Open. 2019;2(6). Viteri FE, Consequences of Iron Deficiency in pregnancy. SCN News 2, 14-18 (1994). Lee HS, Kim S, et al. Iron Status and Pregnancy outcomes in Korean pregnant women. Eur J Clin Nutr. 60, 1130-1135, doi.org/10.1038/sj.ejcn.1602429(2006). Srour MA, et al, Prevalence of anemia and iron-def. anemia among Palestinian pregnant women and association with fetal outcome. Anemia 2018, 9135625, doi.org/10.1155/2018/9135625(2018). Fetal consequences: increased spontaneous miscarriage, PTB, IUFD, IUGR and SGA, HTN, neurologic impairment. A Lohninger, U Radler, et al. Carnitine Supplementation Decreases Rise in FFA, Insulin Resistance and Gestational Diabetes in Pregnant Women. Gynakol Geburtschilfliche Rundsch. 2009;(49(40):230-5. JC King, RJ Cousins, et al. In: Modern Nutrition in Health and Disease. 11 th ed. Baltimore, MD: Lippencott Williams & Wilkens; 2014:189-205. JG Mercer. Neurological Development. In: Nutrition and Development: Short and Long Term Consequences for Health. Hoboken, NJ: Wiley-Blackwell; 2013:87-115. Karras S, Paschou SA, Kandaraki E, Anagnostis P, Annweiler C, Tarlatzis BC, et al. Hypovitaminosis D in pregnancy in the Mediterranean region: a systematic review. Eur J Clin Nutr. 2016; 70:979–86. Sharma S, Kumar A, Prasad S, Sharma S. Current Scenario of Vitamin D Status During Pregnancy in North Indian Population. J Obstet Gynaecol India. 2016; 66:93–100. Palacios C, Gonzalez L. Is vitamin D deficiency a major global public health problem? J Steroid Biochem Mol Biol. 2014; 144:138–45. M-C Chien, C-Y Huang, et al. Effects of Vitamin D in Pregnancy on Maternal and Offsppring Health-related Outcomes: An Umbrella Review of Systematic Review and Meta-analyses. Nutrition and Diabetes (2024) 14:35; https://doi.org/10.1038/s41387-024-00296-0. Jiang Y, Chen Y, Wei L, Zhang H, Zhang J, Zhou X, Zhu S, Du Y, Su R, Fang C, Ding W, Feng L. DHA supplementation and pregnancy complications. J Transl Med. 2023 Jun 17;21(1):394. doi: 10.1186/s12967-023-04239-8. PMID: 37330569; PMCID: PMC10276458. RL Jirtle, FL Tyson, editors. Environmental Epigenomics in Health and Disease. Springer-Verlag publishers, Berlin Heidelberg 2013, Library of Congress Control Number 2013938740. doi: 10.1007/978-3-642-36827-1. Rydbom, Emily Stone, BCHN, CNP. Venn Diagram. 2018. Modified for DNA Life GrowBaby Sample Report. Xu Han, S Ding, J Lu, et al: Global, Regional, and National Burdens of Common Micronutrient Deficiencies from 1990 to 2019: A Secondary Trend Analysis Based on the Global Burden of Disease 2019 Study. Lancet, Vol 44, 101299, February 2022. https://doi.org/101.1016/jeclinm.2022.101299. RA Murphy, et al: Long-chain Omega-3 Fatty Acid Serum Concentrations Across the Life Stages in the USA: an analysis of NHANES 2011-2012, BMJ Open; 11: e 043301. doi: 10.1136/bmjopen-2020-043301. Carnitine: NIH Home>Health Information>Dietary Supplement Fact Sheets>carnitine>carnitine-Health Professional, 4/2023 and 8/7/2023. AB Mayer, L Trenchard, F Rayns. Historical Changes in the Mineral Content of Fruit and Vegetables in the UK From 1940 to 2019: A Concern for Human Nutrition and Agriculture. Inter J of Food Sci and Nut. 2022; 73 (3): 315-326. doi: 10.1080/09637486.2021.1981831. S Debnath, A Dey, R Khanam, et al. Historical Shifting in Grain Mineral Density of Landmark Rice and Wheat Cultivars Released Over the Past 50 years in India. Scientific Reports. 2023; 13 (1): 21164. doi: 10.1038/s41598-023-48488-5. C Zhu, K Kobayashi, I Loladze, et al. Science Advances. 2018; 4 (5): eaaq1012. doi: 10.1126/sciadv.aaq 1012. Aronica, Lucia, PhD. "Imprintome Plain Summary." [Document]. Jima DD, Skaar DA, Planchart A, Motsinger-Reif A, Cevik SE, Park SS, Cowley M, Wright F, House J, Liu A, Jirtle RL, Hoyo C. Genomic map of candidate human imprint control regions: the imprintome. Epigenetics. 2022 Dec;17(13):1920-1943. doi: 10.1080/15592294.2022.2091815. Epub 2022 Jul 4. PMID: 35786392; PMCID: PMC9665137. Skaar DA, Li Y, Bernal AJ, Hoyo C, Murphy SK, Jirtle RL. The human imprintome: regulatory mechanisms, methods of ascertainment, and roles in disease susceptibility. ILAR J. 2012;53(3-4):341-58. doi: 10.1093/ilar.53.3-4.341. PMID: 23744971; PMCID: PMC3683658. "U economists tally societal cost of preterm birth - UNews." UNews , 4 Nov. 2019, https://unews.utah.edu/cost-of-preterm-birth/. Dall TM, et al. The Economic Burden of Elevated Blood Glucose Levels in 2017: Diagnosed and Undiagnosed Diabetes, Gestational Diabetes Mellitus, and Prediabetes. Diabetes Care. 2019 Sep;42(9):1661-1668. doi: 10.2337/dc18-1226. Epub 2019 Apr 2. PMID: 30940641; PMCID: PMC6702607. Hao J et al., Maternal and Infant Health Care Costs Related to Preeclampsia. Obstet Gynecol. 2019 Dec;134(6):1227-1233. doi: 10.1097/AOG.0000000000003581. PMID: 31764733; PMCID: PMC6882523. Lenoir-Wijnkoop I, van der Beek EM, Garssen J, et al. Health economic modeling to assess short-term costs of maternal overweight, gestational diabetes, and related macrosomia - a pilot evaluation. Front Pharmacol. 2015 May 20; 6:103. doi: 10.3389/fphar.2015.00103. PMID: 26042038; PMCID: PMC4438224. Marzouk A, Filipovic-Pierucci A, Baud O, et al. Prenatal and post-natal cost of small for gestational age infants: a national study. BMC Health Serv Res. 2017 Mar 21;17(1):221. doi: 10.1186/s12913-017-2155-x. PMID: 28320392; PMCID: PMC5359886. Stevens W, Shih T, Incerti D, Ton TGN, et al. Short-term costs of preeclampsia to the United States health care system. Am J Obstet Gynecol. 2017 Sep;217(3):237-248.e16. doi: 10.1016/j.ajog.2017.04.032. Epub 2017 Jul 11. PMID: 28708975. Births: Final Data for 2022." National Vital Statistics Reports , vol. 73, no. 2, 4 Apr. 2024, pp. 1-64. Centers for Disease Control and Prevention, National Center for Health Statistics . Additional Declarations Competing interest reported. Potential competing interests for each author include: Leslie Stone MD: CMO for GrowBabyHealth.com, Consultant for Metagenics.com, Consultant for DNALife.healthcare. Emily Rydbom BCHN, CNP: CEO for GrowBabyHealth.com and GrowBabyLifeProject.org (501c3), Consultant for ThisIsNeeded.com, Consultant for Metagenics.com, Consultant for DNALife.healthcare. P Michael Stone MD: no competing interest for this publication. Daniel Kim PhD: no competing interest for this publication. Supplementary Files Appendices.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6739623","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":486403293,"identity":"51d51170-e279-4962-9cfc-dcb7650540ef","order_by":0,"name":"Leslie Stone","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzElEQVRIiWNgGAWjYBACPijN2A8iEwqI0MLGwAzRMrMBpMWAFC0bDoAoorTwnz/4uKBim+zm86sTPzwwYJDnFztAQItEMrPxjDO3jbfdeLtZAugww5mzEwhpYWaT5m27nbjtxtkNIC0JBrcJaeE/DNTy73bi5hlnN/8gTgtDMlBLw+3EDfy924i0RSLZ2Jjn2G3jGTd4t1kkGEgQ9gs//8GHj3lqbsv295/dfPNHhY08vzQBLQggAVYpQaxysH0HSFE9CkbBKBgFIwkAAKx4QgcRSJCjAAAAAElFTkSuQmCC","orcid":"","institution":"Ashland, Stone Medical PC","correspondingAuthor":true,"prefix":"","firstName":"Leslie","middleName":"","lastName":"Stone","suffix":""},{"id":486403294,"identity":"7b9c8e1b-05b8-4291-896f-f1028aa4d33b","order_by":1,"name":"Emily Rydbom","email":"","orcid":"","institution":"growbabyhealth.com","correspondingAuthor":false,"prefix":"","firstName":"Emily","middleName":"","lastName":"Rydbom","suffix":""},{"id":486403295,"identity":"c1e7b462-66a4-4df1-a96f-547daa48eed1","order_by":2,"name":"P Michael Stone","email":"","orcid":"","institution":"University of Georgia","correspondingAuthor":false,"prefix":"","firstName":"P","middleName":"Michael","lastName":"Stone","suffix":""},{"id":486403300,"identity":"f84b6d15-1f35-4aa2-8bc0-bd17669b5743","order_by":3,"name":"Daniel Kim","email":"","orcid":"","institution":"Southern Oregon University","correspondingAuthor":false,"prefix":"","firstName":"Daniel","middleName":"","lastName":"Kim","suffix":""}],"badges":[],"createdAt":"2025-05-24 14:38:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6739623/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6739623/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87047235,"identity":"6ab41c25-dcfb-4328-bd1c-eb6f396c0134","added_by":"auto","created_at":"2025-07-18 14:41:08","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":117994,"visible":true,"origin":"","legend":"\u003cp\u003eGene Single Nucleotide Polymorphism with overlapping influences on pregnancy and fetal outcomes. Small for Gestational Age: PR, IL6, AhR, VDR, MTHFR C677T; Preterm Birth: VDR, APOE2, CYP1A1, PR, PEMT; Large for Gestational Age: ENPP1, GCK-30G \u0026gt;A, MTNRI B; Gestational Diabetes: CYP1A2, IGF2BP2, APOE4, CYP1A1, APOE2; Gestational/Pregnancy Induced Hypertension and Preeclampsia: GSTP1,GSTT1, GSTA1, GSTM1, MTHFR C677T, VDR, CYP1A1, APOE4; Recurrent Pregnancy Loss: APOE4, AhR, MTHFR A1298C, PR, TCN2, GSTA1, GSMT1, MTHFRC677T; Miscarriage: APOE2, CBS, TCN2; Stress Dysregulation Phenotype: BDNF, COMT, MAOA; Neural Tube Defects: MTHFR A1298C, PEMT, MTHFR C677T, CBS, MTHFD1\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6739623/v1/e88ea512d03fcf288e65731d.png"},{"id":87047234,"identity":"659beaf5-40a3-4fa9-bde8-827123950fb8","added_by":"auto","created_at":"2025-07-18 14:41:08","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":32919,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparative Plot Between Oregon PLUS vs Oregon SOC\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6739623/v1/ec18463f6b76b20e6b41c7d8.png"},{"id":87045725,"identity":"a2272cba-12fd-4fc5-b41f-6706bf1fe73d","added_by":"auto","created_at":"2025-07-18 14:33:08","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":28629,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparative Plot for Preterm Birth between National, Regional and Ethnic Data vs Oregon PLUS\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e (47)\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6739623/v1/6821da988320629defeac8f6.png"},{"id":96450356,"identity":"bcaecdcb-8681-494c-b0e1-44577eb013f2","added_by":"auto","created_at":"2025-11-21 08:54:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1218139,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6739623/v1/a7a5bd01-1442-4c8d-abdc-534e3236663d.pdf"},{"id":87045723,"identity":"b00cf4b8-551a-4f7a-b2f0-cb4e08c3e42e","added_by":"auto","created_at":"2025-07-18 14:33:08","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":28797,"visible":true,"origin":"","legend":"","description":"","filename":"Appendices.docx","url":"https://assets-eu.researchsquare.com/files/rs-6739623/v1/d2dbd0e87beeb525bff35b39.docx"}],"financialInterests":"Competing interest reported. Potential competing interests for each author include:\n1.\tLeslie Stone MD: CMO for GrowBabyHealth.com, Consultant for Metagenics.com, Consultant for DNALife.healthcare.\n2.\tEmily Rydbom BCHN, CNP: CEO for GrowBabyHealth.com and GrowBabyLifeProject.org (501c3), Consultant for ThisIsNeeded.com, Consultant for Metagenics.com, Consultant for DNALife.healthcare.\n3.\tP Michael Stone MD: no competing interest for this publication.\n4.\tDaniel Kim PhD: no competing interest for this publication.","formattedTitle":"A ‘Standard of Care Plus’ Model for Preterm Birth Prevention: Integrating Nutrient and Gene Variant Analysis with Targeted Interventions: A Prospective Observational Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe United States (US) faces a significant public health challenge with preterm birth (PTB) rates that are alarmingly high compared to other affluent nations. This disparity is particularly pronounced within socioeconomically disadvantaged communities \u0026amp; within racial minorities [1]. In the U.S. (2022), infant mortality rates due to prematurity/low birthweight account for 14.0% of all infant death [2].\u003c/p\u003e\n\u003cp\u003eThe consequences of PTB extend far beyond the neonatal period, contributing to increased lifelong morbidity and mortality, and imposing a substantial economic burden on healthcare systems. Furthermore, infants born small for SGA, even at term, represent a distinct population at heightened risk for chronic disease development, not only during their neonatal period (F1 generation), but also throughout their adult lives, underscoring the critical role of the intrauterine environment in shaping long-term health trajectories [3,4,5].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the US, severe maternal morbidity (SMM) rose from 69.5 to 79.7 per 10,000 delivery hospitalizations between 2012 and 2019 [6]. Concurrently, US obesity rates increased from 30.5% (1999-2000) to 44.9% (2017-2020), elevating risks for conditions like hypertension (HTN), diabetes (DM), and cardiovascular disease (CVD), as well as pregnancy-specific issues such as hypertensive disorders (HDP), preeclampsia (PreE), preterm birth (PTB), gestational diabetes (GDM), and large for gestational age (LGA) infants [7]. Chronic HTN in pregnancy doubled between 2007 and 2021, with only 60% treated [8]. Uncontrolled HTN significantly raises risks for PreE, PTB, and SGA, which in turn increases future non-communicable disease (NCD) risk in offspring.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePreterm birth occurred in 10.4% of US births in 2022 and is associated with increased risk for HTN, CVD, DM, osteoporosis, maternal complications of PTB, GDM, HDP, and neonatal SGA [9]. SGA occurred in 11.1% of the US population in 2021 and is associated with neurodevelopmental delay, infant and neonatal mortality, and chronic disease in the offspring [10]. LGA neonates comprised 11% of US neonates in 2018 [11], and are prone to develop insulin resistance, obesity, diabetes mellitus, early cardiovascular disease, and several cancer types [12]. Accelerating NCDs in reproductive adults drives a feed forward cycle of chronic illness and negative maternal/infant outcomes, with greater impact on populations facing racial, environmental, socio-economic, and food access disparities [13].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNutrition\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWhile tackling the rising burden of NCDs is challenging due to multiple factors, predispositions appear modifiable in the perinatal period through interventions related to macro/micro-nutrient availability, gut microbiota, dietary composition (fatty acids, carbohydrates, protein), and toxic exposure [14].\u0026nbsp;Proper nutrition during critical periods significantly impacts fertility, pregnancy outcomes, and the lifelong health of mothers and their children [15, 16]. However, prevalent Western diets rich in processed, nutrient-poor, calorie-dense foods lacking essential micronutrients (like iron, iodine, folate, B12, D, choline, and omega-3s) pose a challenge [15]. Access to nutrient-dense food is difficult for women across socioeconomic levels, meaning balanced diets in pregnancy cannot be assumed, and single-nutrient solutions are likely ineffective [15, 17].\u0026nbsp;Standard obstetric care typically screens for iron deficiency anemia, not other nutrient deficiencies. While pregnancy-specific nutrient standards are lacking, applying reproductive age norms reveals common key micronutrient deficiencies that increase risk for adverse maternal and neonatal outcomes.\u0026nbsp;In fact, 95% of pregnant women in the US fail to meet dietary recommendations for at least one nutrient through diet alone, with one in three remaining at risk even with supplements [15, 18]. Iron [19,20,21], carnitine [22], zinc [23,24], and Vitamin D [25, 26, 27, 28] deficiencies are associated with many maternal and neonatal morbidities. Interestingly, giving docosahexaenoic acid (DHA) in pregnancy irrespective of maternal serum status decreases the risk of PTB [29]. Understanding\u0026nbsp;how\u0026nbsp;these prevalent nutritional deficiencies translate into significant health risks for both mother and child is paramount, and epigenetic processes provide a critical explanatory framework.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEpigenetics\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePre- and post-transcriptional epigenetic processes may explain how gestational nutrition and exposures impact immediate pregnancy outcomes and long-term mother/child disease risk. Optimizing both epigenetic and metabolic function requires a remarkable, overlapping set of micronutrients and vitamins (e.g., iron, calcium, B vitamins, zinc, magnesium, among others [30]. For example, methylation for these functions depends on dietary factors like betaine and choline, plus co-factors such as 5-methyl tetrahydrofolate and Vitamin B12 [30].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo bridge the gap between burgeoning genomic data and tangible clinical benefits, the investigators undertook a systematic process of single nucleotide polymorphism (SNP) selection based on the following criteria:\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eStrength of association with maternal and neonatal adverse outcomes under study\u003c/li\u003e\n \u003cli\u003eOverlapping association with SNPs implicated in risk for chronic disease\u003c/li\u003e\n \u003cli\u003eSNP frequency in the population\u003c/li\u003e\n \u003cli\u003eModifiability of the gene or gene product through nutrition, nutrient supplementation, and lifestyle modification.\u0026nbsp;\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eTo further personalize nutritional and lifestyle advice, 42 SNPs in 27 genes across 11 key biological processes were selected. Interventions, incorporated into time-sensitive plans, prioritized processes with multiple variants and high overlap with adverse maternal/neonatal outcomes and chronic disease risk. SNPs without diet or lifestyle remediation were excluded, and a polygenic risk score was not created. (Figure 1: Venn diagram) [31].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA Personalized and Proactive Approach\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIt is in this context that a Standard of Care Plus (PLUS) model was conceived, augmenting current Standard of Care (SOC) by providing preventive collaborative nutritional counseling and lifestyle care, based on select micronutrient and genomic analysis, in a highly personalized and time-cognizant manner. The original 50% Medicaid, in-person group educational model realized statistically significant reductions in aggregate occurrence of preeclampsia, GDM, SGA and LGA compared to local private practice and community health clinic SOC [14]. The current applications recognize the need for risk reduction evaluation of PTB, a virtual application, a larger and more diverse population under study, and a prospective observational study design.\u0026nbsp;\u003c/p\u003e"},{"header":"Methods ","content":"\u003cp\u003e\u003cstrong\u003ePrimary Application\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBetween January 1, 2011, and December 31, 2017, all pregnant women at a Jackson County, Oregon private practice received a PLUS model of prenatal care, augmenting standard obstetric care with in-person group sessions led by a board-certified holistic nutritionist. These sessions, up to 90 minutes per trimester and postpartum, included nutrition/lifestyle assessment, education, and personalized plans (covering diet, vitamins, lifestyle) based on health history, anthropometrics, select serum micronutrients, and gene variants. An extra 30 minutes of nutritionist time per trimester/postpartum was allocated for plan adjustments. Postpartum support was ongoing, and all deliveries were in-hospital.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSecondary Application\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFrom August 1, 2022, to July 1, 2023, a prospective intervention study in a Clark County, NV private practice provided a cost-free virtual PLUS model to pregnant women (\u0026lt;20 weeks\u0026rsquo; gestation) with managed care organization (MCO) coverage. This model included six hours of individual virtual assessment, education, and intervention by a BCHN, supplementing standard in-person OB/GYN care. Exclusions were multiple gestations and fetal demise. All deliveries were in-hospital and completed by October 2023. All materials were adapted to an 8th-grade reading level and translated into Spanish. Nutrition and lifestyle interventions involved HIPAA-compliant virtual communication: an initial BCHN phone call, three scheduled contacts (per trimester/postpartum), and unlimited participant-initiated texting. Clinic providers and staff received a 30-minute virtual training and an in-clinic logistical visit. Further OB provider communication regarding intervention changes or nutrient diagnoses occurred via secure email. Data was stored in a separate, secure EHR.\u003c/p\u003e\n\u003cp\u003eParticipant and publication consent in both primary and secondary application was procured in accordance with the Declaration of Helsinki 1964, and ethics approval was obtained through Southern Oregon Internal Review Board. Upon consent, the participants underwent SOC evaluation by their OB provider, including height, weight, BMI, and standard laboratory and imaging evaluation. In addition, each PLUS participant received the following assessments:\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eNutritionist care \u0026ndash; 60 minutes per trimester by phone\u003c/li\u003e\n \u003cli\u003eSerum micronutrients zinc, carnitine and 25-hydroxy cholecalciferol (25-OH D) drawn at intake, 24\u0026ndash;28-week gestation, and 6-8 weeks postpartum.\u003c/li\u003e\n \u003cli\u003eDried blood spot DHA levels at intake, 24\u0026ndash;28-week gestation, and breast milk DHA at 6-8 weeks postpartum.\u003c/li\u003e\n \u003cli\u003eBuccal swab 42 gene variant panel obtained at intake.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eAt intake the PLUS participants virtually received their individualized food and lifestyle plans based on OB provider anthropometric, laboratory and imaging assessments, followed by trimester-by-trimester personalized adaptations dependent on subsequent PLUS testing and clinical response obtained through real-time chart review by board-certified MD investigator. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInterventions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe PLUS diet was based on an adapted Mediterranean Diet modified by a low glycemic index with a 40% carbohydrate / 30% fat / 30% protein ratio. Macronutrient requirements were calculated, and adjustments were made each trimester to the core food plan based on nationally accepted pregnancy-specific Mifflin standards, with further refinement based on body mass index (BMI), activity, and dietary preferences. Nutrition education was emphasized \u0026amp; outlined (Appendix-3).\u0026nbsp;Sleep quality, movement, exogenous stress and mood were assessed at intake, 24-28 weeks\u0026rsquo; gestation, and 6-8 weeks postpartum.\u0026nbsp;Other common pregnancy-related concerns were addressed at each visit (Appendix-4). PLUS patients received a multi-nutrient prenatal supplement pack (Appendix-1) and a probiotic (Appendix-2). Customized Vitamin D3 and iron supplementation occurred if identified needs could not be met with diet and lifestyle modification alone. Other identified micronutrient insufficiencies were managed with nutrient-rich food incorporation in the diet.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1: Intervention Comparisons\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"720\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComponent\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSOC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIntervention\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePLUS Oregon\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIntervention\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePLUS \u0026nbsp; \u0026nbsp; Nevada\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 176px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIntervention\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRoutine Nutrition Professional\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eIn-person group \u0026ndash; 90 minutes per trimester + additional 30 minutes as needed\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 176px;\"\u003e\n \u003cp\u003eVirtual \u0026ndash; 60 \u0026nbsp; \u0026nbsp; minutes per trimester + additional 30 minutes as needed \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMeal Plan\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eInitiated at any trimester upon first intake, with individual needs adjusted throughout pregnancy.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 176px;\"\u003e\n \u003cp\u003eInitiated at any trimester upon first intake, with individual needs adjusted throughout pregnancy.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrenatal Vitamins\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003ePrenatal with iron and folic acid. 200-400 mg of DHA.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003ePrenatal nutrient packet (Appendix-1) was taken daily from the 1st trimester (or earliest possible) through postpartum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 176px;\"\u003e\n \u003cp\u003ePrenatal nutrient packet (Appendix-1) was taken daily from the 1st trimester (or earliest possible) through postpartum\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eProbiotic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eProbiotic (Appendix-2) was taken daily from the 1st trimester (or earliest possible) through postpartum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 176px;\"\u003e\n \u003cp\u003eProbiotic (Appendix-2) was taken daily from the 1st trimester (or earliest possible) through postpartum\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStandard Labs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e1\u003csup\u003est\u0026nbsp;\u003c/sup\u003e, 2\u003csup\u003end ,\u0026nbsp;\u003c/sup\u003e3\u003csup\u003erd\u003c/sup\u003e Trimesters\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(Appendix-6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eSOC Labs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 176px;\"\u003e\n \u003cp\u003eSOC Labs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMicronutrient Labs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eSerum\u0026nbsp;zinc, carnitine (free, total, acyl), 25-OH D drawn at intake, 24\u0026ndash;28-week gestation, and 6-8 weeks postpartum.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 176px;\"\u003e\n \u003cp\u003eSerum zinc, carnitine, and 25-OH D were tested at intake, 24-28 weeks, and 6-8 weeks postpartum. DHA was measured from dried blood spots (intake) and breast milk (6-8 weeks postpartum).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNutrigenomics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eMTHFR C677T \u0026amp; MTHFR A1298C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 176px;\"\u003e\n \u003cp\u003e42 SNPs in 27 genes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe 42 SNP panel was utilized in the Nevada PLUS group to personalize diet and lifestyle recommendations versus a 2 SNP panel in the Oregon PLUS group. RS numbers, maternal and neonatal outcome associations, and prevalence in the Nevada PLUS population are included in Appendix 8. The SNP datasets generated during the current study are deposited in the National Center for Biotechnology Information dbSNP databank under BioProject Accession number PRJNA1283159.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrimary and Secondary Outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e2-prop Z test, odds ratio (OR), and relative risk (RR) analysis were accomplished through Python. De-identification of all personal data occurred prior to analysis. The primary outcome measure evaluated the frequency of preterm birth (PTB) \u0026lt;37 weeks\u0026rsquo; gestation. Secondary outcomes measured included the frequency of hypertensive disorders of pregnancy, gestational diabetes mellitus, small for gestational age, and large for gestational age with defined diagnostic criteria (Appendix-7).\u003c/p\u003e\n\u003cp\u003eThe frequency of each adverse outcome in the Nevada PLUS population was compared to the frequency of adverse outcomes in two populations.\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eClark County, NV Medicaid SOC population from healthysouthernnevada.org 2021, representing the regional comparator\u003c/li\u003e\n \u003cli\u003eOregon PLUS population, representing the program comparator in a different region.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eComparative Characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNevada PLUS study group and Clark County, NV SOC group share similar age, locality, gravidity, parity, race, (BMI), and drug use (healthysouthernnevada.org 2021), except that the Nevada PLUS study group was 100% insured through Medicaid. The Oregon PLUS study group share several characteristics with the Nevada PLUS group, including gravidity, parity, and smoking, alcohol, and drug use history, but differ significantly in age (31.6 vs 25.4 years, respectively) and race (93.3% vs 17% Caucasian, respectively) (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). A Medicaid payor source accounted for 100% of the Nevada PLUS group vs 50% of the Oregon PLUS group.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eComparative Characteristics of Nevada PLUS and Oregon PLUS\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNevada PLUS (n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOregon PLUS (n\u0026thinsp;=\u0026thinsp;387)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.4 (SD 5.187)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31.6 (SD 5.378)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdvanced for Maternal Age (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTeen (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGravidity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.4 (SD 1.665)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.97 (SD 1.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eParity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (SD 1.264)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.13 (SD 1.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRace (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBlack\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAsian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNative American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot Specified\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCaucasian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e93.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmoking, alcohol, drug history (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003ePayer Source: Nevada \u0026minus;\u0026thinsp;100% Medicaid \u0026amp; Oregon \u0026minus;\u0026thinsp;50% Medicaid\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eMore nuanced are the differences in BMI and excessive weight gain between the 2 study groups. Although the average BMI at first visit was not significantly different, the maximum BMI in the Nevada PLUS group was 35.1 kg/m\u003csup\u003e2\u003c/sup\u003e compared to 54 kg/m\u003csup\u003e2\u003c/sup\u003e in the Oregon PLUS group. BMI\u0026thinsp;\u0026gt;\u0026thinsp;30 kg/m\u003csup\u003e2\u003c/sup\u003e occurred in 20% of the Nevada PLUS group and only 11% in the Oregon PLUS group. Weight gain\u0026thinsp;\u0026gt;\u0026thinsp;40 lbs occurred in 31% of the Nevada PLUS group vs 25.4% of the Oregon PLUS group (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eBody Mass Index (BMI) and Excessive Gestational Weight Gain (EGWG) Descriptive Statistics in Nevada (SOC Plus) and Oregon (SOC Plus)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNevada PLUS\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOregon PLUS\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBMI at First Visit\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.37 (4.716)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.8 (SD 5.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMinimum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaximum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI Ranges\u003c/strong\u003e:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u0026ndash;30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEGWG\u0026thinsp;\u0026gt;\u0026thinsp;40 lbs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003ePrimary and Secondary Outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCompared to their respective SOC populations, the PLUS pooled cohort exhibited substantially lower risks across all five outcomes, including preterm birth (RR\u0026thinsp;=\u0026thinsp;0.23), hypertensive disorders of pregnancy (RR\u0026thinsp;=\u0026thinsp;0.11), gestational diabetes (RR\u0026thinsp;=\u0026thinsp;0.06), small for gestational age (RR\u0026thinsp;=\u0026thinsp;0.25), and large for gestational age (RR\u0026thinsp;=\u0026thinsp;0.35). These findings suggest that individuals in the SOC group were between three and seventeen times more likely to experience each adverse outcome than those in the PLUS intervention cohort.\u003c/p\u003e\n\u003cp\u003eThe Nevada PLUS study group experienced no PTB, no HDP, no SGA, one GDM, and one LGA. Comparison of Nevada PLUS to the Clark County, Nevada population revealed reduced rates of all adverse outcomes measured, but p-values were not significant because of a smaller Nevada PLUS sample size, p-values ranging from 0.4003 for PTB to \u0026gt;\u0026thinsp;0.99 for HDP (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). The smaller sample size reflects the commonly encountered challenge of identifying first and early second trimester pregnancies.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePrevalence of Adverse Outcomes: Nevada SOC Plus compared to Clark County Medicaid (SOC)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOutcome\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNevada PLUS* (n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eClark County SOC** (per 100)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value: Exact Binomial Test\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePreterm Birth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.4003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypertensive Disorders of Pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGestational DM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmall for Gestational Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.389\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLarge for Gestational Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7097\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003e*N\u0026thinsp;=\u0026thinsp;15\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003e**healthysouthernevada.org 2021\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eNo significant difference in outcome frequencies between the Nevada PLUS and the Oregon PLUS was found (Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePrevalence of Adverse Outcomes: Nevada PLUS compared to Oregon PLUS\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOutcome\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNevada PLUS (n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOregon PLUS (n\u0026thinsp;=\u0026thinsp;387)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value: Fisher\u0026apos;s Exact Test\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePreterm Birth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypertensive Disorders of Pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGestational DM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0733\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmall for Gestational Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLarge for Gestational Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.418\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eTherefore, the populations were pooled and compared to Oregon SOC adverse outcomes obtained from March of Dimes Report (2022) and from chart review of all Oregon SOC deliveries between 2011 and 2017 at the low-risk community hospital where the Oregon PLUS deliveries occurred concurrently. PTB gestational age at delivery improved over time. The first two PTB occurred in the first year of Oregon PLUS application at 23 and 24 weeks, with all 6 subsequent PTB occurring after 36 0/7 weeks gestation.\u003c/p\u003e\n\u003cp\u003eHighly significant reductions of all adverse maternal and neonatal outcomes appeared in the PLUS pooled study group (Table \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab6\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePrevalence of Adverse Outcomes: Nevada \u0026amp; Oregon (PLUS Pooled) compared to Oregon SOC\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOutcome\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePLUS Pooled\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOregon SOC\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value: 1-Prop Z-test\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRelative Risk of SOC Plus\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLikelihood of Adverse Outcome in SOC\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePreterm Birth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.0% (8/402)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.229\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypertensive Disorders\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.0% (4/402)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGestational DM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5% (2/402)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.057\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmall for Gestational Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.5% (6/402)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.246\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLarge for Gestational Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.5% (14/402)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.347\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003e\u003csup\u003e1\u003c/sup\u003eMarch of Dimes, Oregon, 2022 / \u003csup\u003e2\u003c/sup\u003eGAHMJ, November 2014, vol 3;6. N\u0026thinsp;=\u0026thinsp;553, combined community clinic and private practice deliveries 2011\u0026ndash;2012 in the same hospital as Oregon (PLUS)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eHaving a PTB in the comparator SOC group appeared 4.37 times more likely than in the pooled PLUS group (RR .229), while HDP were 8.74 times more likely to occur in the SOC group than in the pooled PLUS group (RR .1143). GDM appeared 17.48 times more likely in the SOC group than in the PLUS (RR .057). SGA appeared 4.087 times more likely to occur in the SOC group (RR .246), while LGA appeared 2.87 times more likely to occur in the SOC group than in the pooled PLUS group (RR .347).\u003c/p\u003e\n\u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e illustrates a comparative analysis of adverse outcome rates for Oregon PLUS and Oregon SOC, across five key maternal and neonatal health indicators.\u003c/p\u003e\n\u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e compares regional and national PTB rates in the PLUS Oregon group emphasizing benefit likely to occur when applied across a larger and broader population.\u003c/p\u003e\n\u003cp\u003eNumbers needed to treat (NNT) calculations were added for clinical relevance and potential cost savings analysis, finding favorably low numbers of patients treated to obtain one fewer adverse event in all outcomes tested (Table \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab7\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eNumbers Needed to Treat (NNT): Nevada with Oregon (PLUS Pooled) compared to Oregon (SOC)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOutcomes\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePLUS Pooled\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSOC\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNNT\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;402\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePreterm Birth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.99%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.7%\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypertensive Disorders of Pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.5%\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGestational Diabetes Mellitus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.7%\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmall for Gestational Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.49%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.1%\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLarge for Gestational Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.48%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.4%\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16.89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eSources\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026sup1; March of Dimes Oregon, 2022\u003c/p\u003e\n\u003cp\u003e\u0026sup2; gahmj, November 2014, vol 3;6; n\u0026thinsp;=\u0026thinsp;553, combined community clinic and private practice deliveries 2011\u0026ndash;2012 in the same hospital as Oregon (PLUS)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMicronutrient and Macronutrient Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA matched two tail T-test was used to analyze first-trimester micro- and macro-nutrient deficiency rates for hemoglobin/hematocrit (as a surrogate for iron deficiency), serum zinc, carnitine, Vitamin 25-OH D, and whole blood spot DHA during the first trimester comparing the Nevada PLUS population and the Oregon PLUS population birthing during 2011 and 2012. Regional and national comparators proved difficult to find, poorly validated, and temporally remote. Instead, nutrient deficiency rates were compared to reproductive age women 18\u0026ndash;35 years of age, as presented in Lancet 2022: global, regional, and national burdens of common micronutrient deficiencies from 1990\u0026ndash;2019 [\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eNo meaningful difference in hemoglobin concentration between the Nevada PLUS and Oregon PLUS populations, (p-value .875) was found, and the national deficiency rate was insignificantly lower, as well (p-value .074), with a range of 15.1%-22%. Hematocrit percentages were not significantly different between Nevada PLUS, Oregon PLUS, and the national rate (p-value range .125-.25), with a range of 11%-22%. Insignificant differences between the study group comparators for serum zinc were found (p-value .388, range 37%-50%), however the pooled study group was significantly lower than the national average for reproductive women of 22% (p-value 4.866 x 10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e). First trimester 25-OH D insufficiency rate in the Nevada PLUS was 83%, the Oregon PLUS insufficiency rate was 58%, and when pooled were significantly more commonly insufficient than the national rate of 3% (p-value 3.24 x \u003csup\u003e10\u003c/sup\u003e) and the rate in the United Kingdom of 55% (p-value .0017) [\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eDHA deficiency rates were compared to reproductive age females in an NHANES analysis during 2011\u0026ndash;2012 [\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e]. The Nevada PLUS DHA deficiency (\u0026lt;\u0026thinsp;5%) rate was 89% and was significantly higher than the national average of 68% (p .029).\u003c/p\u003e\n\u003cp\u003eNo meaningful regional, national or global comparator for carnitine was found [\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e], but both study populations were commonly deficient based on assay reference ranges, and not significantly different from each other. The free carnitine deficiency rate was 77.8% and 56.7%, Nevada PLUS and Oregon PLUS, respectively. The esterified carnitine rate was 55% and 53%, Nevada PLUS and Oregon PLUS, respectively.\u003c/p\u003e\n\u003cp\u003eLastly, second trimester or early third trimester abnormal one-hour 50 gm oral glucose tolerance test (1-hour OGTT) rate in the Nevada SOC group did not statistically differ from that of the nation, .12% vs 20%, respectively (p-value.198), but the Nevada and Oregon PLUS abnormal occurrence rate is significantly less than the nation, .02% vs 20%, (p-value .01), most likely related to early first and second trimester intervention for elevated maternal BMI and excessive weight gain in the Oregon PLUS group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompliance\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Oregon in-person PLUS group had 85% intake attendance and 70% ongoing compliance (customized nutrition, lifestyle and micronutrient supplementation). In Nevada\u0026apos;s PLUS virtual model, intake compliance was 83%, decreasing to 47% (third trimester) and 45% (postpartum). Nevada PLUS nutritionist calls were returned 74% of the time; all subject-initiated calls were completed. Nutrition/lifestyle adherence in Nevada varied (78% second trimester to 53% third), while supplement compliance was 80\u0026ndash;94%. Nutrition and lifestyle adherence was assessed each trimester via direct patient questioning using a 5-food frequency questionnaire (Appendix 5). Qualitative data showed the nutrition plan aided food awareness and shopping.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThese results suggest that late first/early second trimester application of targeted nutrient, nutrition, and lifestyle guidance based on select micro/macronutrient and genomic analysis, further adjusted for changing physiologic pregnancy need, is associated with reductions in the incidence of PTB, HDP, GDM, SGA, and LGA neonates compared to standard of care alone. Risk reduction is demonstrated over seven years in the Oregon PLUS group. Comparable results were achieved in the slightly younger population in Nevada PLUS, with a more socio-economically disadvantaged and ethnically diverse population. The data also suggest that virtual delivery of the program to pregnant individuals appears as effective as an in-person group mode.\u003c/p\u003e\u003cp\u003eThe virtual interface solved for many of the factors that compromised compliance in the 2011\u0026ndash;2012 Oregon SOC Plus study, specifically: (1) geographic, financial, and social requirements of travel to a classroom four times throughout pregnancy and postpartum care, and (2) lack of immediate text and phone-based support for each subject who might struggle with the dietary and lifestyle changes demanded by the program. In fact, compliance appeared slightly better in the virtual group, and may represent a generational preference, convenience factor, or resource availability.\u003c/p\u003e\u003cp\u003eDespite the dissimilarities between the Oregon PLUS group and Nevada PLUS group they shared micronutrient insufficiencies for zinc, carnitine, and 25-OH D. Difficulty in locating applicable and current micronutrient references ranges during pregnancy reveal a glaring need for updated maternal and neonatal standards. Reliance on diet survey-based consumption data do not address the declining nutrient density in our food supply under current agricultural practices [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. They do not recognize the individual genomic uniqueness that is responsible for much of our diversity, and influences bioavailability of macro/micronutrients.\u003c/p\u003e\u003cp\u003eThe 42 SNP panel used to customize nutrition and lifestyle recommendations in the high-risk Nevada PLUS group compared to the 2 SNP panel in the moderate-risk Oregon PLUS may have contributed to the statistically equivalent prevalence of adverse outcomes, but principal component analysis of larger data sets are needed to elucidate which features of the model are most effective and identify those that need optimization. More rigorous and time-sensitive peri-natal micro- and macro-nutrient reference ranges need to be established. Food sources need evaluation for nutrient density, with interrogation of agricultural practices that influence food quality. Further work is planned to expand understanding of nutrigenomic impact and durability of effect through interrogation of the imprintome [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Lastly, a human-centered, AI-driven digital health platform is being developed to scale the PLUS model and to potentiate early access to preventive care for the reproductive age population.\u003c/p\u003e\u003cp\u003eComparing improved outcomes in PTB, SGA, LGA, GDM, and HDP under the PLUS model to US average rates and associated costs, investigators project potential annual savings [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Based on 3.6\u0026nbsp;million births per year [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], national adoption of the PLUS model is estimated to save the US healthcare system between \u003cspan\u003e$\u003c/span\u003e4.435\u0026nbsp;billion (NNT model) and \u003cspan\u003e$\u003c/span\u003e43.42\u0026nbsp;billion (percent reduction model) gross, annually.\u003c/p\u003e"},{"header":"Declarations","content":"\u003col\u003e\n \u003cli\u003e\u003cstrong\u003eEthics Approval and Consent:\u0026nbsp;\u003c/strong\u003eParticipant consent in both primary and secondary application was procured in accordance with the Declaration of Helsinki 1964, and ethics approval was obtained through Southern Oregon Internal Review Board.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eConsent for Publication:\u0026nbsp;\u003c/strong\u003eConsent for publication was obtained simultaneously with participation consent, stipulating de-identification of all data in a HIPAA compliant fashion with dedicated and secure storage.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eCompeting Interests: \u003csup\u003e1\u003c/sup\u003e\u003c/strong\u003e CMO for GrowBabyHealth.com, Consultant for Metagenics.com, Consultant for DNALife.healthcare: \u003csup\u003e2\u003c/sup\u003e CEO for GrowBabyHealth.com and GrowBabyLifeProject.org (501c3), Consultant for ThisIsNeeded.com, Consultant for Metagenics.com, Consultant for DNALife.healthcare: \u003csup\u003e3\u0026nbsp;\u003c/sup\u003eno competing interest for this publication: \u003csup\u003e4\u003c/sup\u003e no competing interest for this publication.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e Molina Health of Nevada\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eAvailability of Data \u0026amp; Materials:\u003c/strong\u003e Generated raw data sets are not publicly available to preserve participant privacy. Publicly available comparative data sets were used in raw data analysis and are referenced throughout the manuscript.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eAcknowledgements:\u003c/strong\u003e Tracey Green Chittenden, MD, the Molina-Nevada maternal healthcare team, and Michael Easterday of Molina Healthcare. Anita Gondy, OB-GYN, Ankita Raman, OB-GYN, Saovaros Michaels, OB-GYN, Jenny Schrader, \u0026amp; Bryan Iriye, OB-GYN. Lisa Portera, DC, David Dzielak, PhD, \u0026amp; Sheila Clough. Brent Eck, Ilissa Larimore, Lisa McDonald, Nilima Desai, RD, MPH, \u0026amp; Anu Desai, PhD. Helen Gautschi, MS \u0026amp; Chris Moore. Kristina Harris Jackson, PhD \u0026amp; Bill Harris, PhD. Lucia Aronica, PhD, Joseph Lamb, MD \u0026amp; Stone Medical Family Practice. And to all the mothers \u0026amp; families who have been a part of this empowering project.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eAuthors Information:\u0026nbsp;\u003c/strong\u003eNo additional information.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eAuthors Contribution:\u003c/strong\u003e \u003csup\u003e1\u003c/sup\u003econception, design, acquisition, analysis, interpretation, and drafting /revision of the study, specifically abstract, body of work, appendices, references, Tables 2, 3, and 7: \u003csup\u003e2\u003c/sup\u003econception, design, acquisition, analysis, interpretation, and drafting/revision of the study, specifically abstract, body of work, appendices, Figures 1, 2, and 3, and Tables 1 and 2: \u003csup\u003e3\u003c/sup\u003e conception, design, interpretation and revision, specifically body of work and appendices: \u003csup\u003e4\u003c/sup\u003e conception, design, interpretation and revision, specifically body of work and appendices.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eHealthcare Cost and Utilization Project: hcup-us.ahrq.gov/reports/statbriefs/sb243-Severe-Maternal-Morbidity-Delivery-Trends-Disparities, 2006-2018.\u003c/li\u003e\n \u003cli\u003eAhmad, Farida B., et al. \u003cem\u003eInfant Mortality in the United States, 2022: Data from the Period Linked Birth/Infant Death File\u003c/em\u003e. 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Health economic modeling to assess short-term costs of maternal overweight, gestational diabetes, and related macrosomia - a pilot evaluation. Front Pharmacol. 2015 May 20; 6:103. doi: 10.3389/fphar.2015.00103. PMID: 26042038; PMCID: PMC4438224.\u003c/li\u003e\n \u003cli\u003eMarzouk A, Filipovic-Pierucci A, Baud O, et al. Prenatal and post-natal cost of small for gestational age infants: a national study. BMC Health Serv Res. 2017 Mar 21;17(1):221. doi: 10.1186/s12913-017-2155-x. PMID: 28320392; PMCID: PMC5359886.\u003c/li\u003e\n \u003cli\u003eStevens W, Shih T, Incerti D, Ton TGN, et al. Short-term costs of preeclampsia to the United States health care system. Am J Obstet Gynecol. 2017 Sep;217(3):237-248.e16. doi: 10.1016/j.ajog.2017.04.032. Epub 2017 Jul 11. PMID: 28708975.\u003c/li\u003e\n \u003cli\u003eBirths: Final Data for 2022.\u0026quot; \u003cem\u003eNational Vital Statistics Reports\u003c/em\u003e, vol. 73, no. 2, 4 Apr. 2024, pp. 1-64. \u003cem\u003eCenters for\u0026nbsp;\u003c/em\u003e\u003cem\u003eDisease Control and Prevention, National Center for Health Statistics\u003c/em\u003e.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6739623/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6739623/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose: \u003c/strong\u003eHigh rates of adverse maternal and neonatal outcomes, such as preterm birth (PTB), hypertensive disorders of pregnancy (HDP), gestational diabetes mellitus (GDM), small for gestational age (SGA), and large for gestational age (LGA) persist in the US, highlighting the need for prevention and effective interventions beyond the current standard of care (SOC) particularly in diverse, socio-economically challenged populations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective: \u003c/strong\u003eA prospective observational study evaluated a targeted diet and lifestyle intervention incorporating select nutrient and gene variant analysis and personalized trimester-based nutrition counseling and supplementation in collaboration with in-person standard of care (PLUS) compared to standard of care alone (SOC) in reducing adverse outcomes. The impact of mode of PLUS delivery was also evaluated: individual-virtual vs in-person group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eThis study compared a Nevada PLUS cohort (N=15): high-risk participants, all covered by Medicaid, who received the PLUS intervention virtually and an Oregon PLUS cohort (N=387): moderate-risk participants with 50% Medicaid coverage who received the PLUS intervention through in-person group sessions, against each other and against regional SOC outcomes. The Nevada PLUS data showed non-significant reductions across all measured adverse outcomes because of small sample size. The Oregon PLUS showed highly significant risk reductions in all outcomes (p-value \u0026lt; .001). \u0026nbsp;When comparing the outcomes of the Nevada (virtual) and Oregon (in-person) PLUS cohorts directly, no statistically significant differences were found based on how the PLUS model was delivered. Given no significant difference by delivery mode, the two PLUS cohorts were combined (pooled N=402). This pooled group revealed highly significant risk reductions in all outcomes (p -value \u0026lt; .001): PTB (RR = .229), HDP (RR .114), GDM (RR .057), SGA (RR .246), and LGA (RR .347) compared to regional SOC outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eThese findings suggest that implementing select nutrient and gene variant analysis with targeted nutritional and lifestyle interventions in collaboration with in-person standard of care is associated with significant reductions in the incidence of key adverse maternal and neonatal outcomes in diverse pregnant populations, and that an individual-virtual mode of PLUS delivery appears as effective as an in-person group mode.\u003c/p\u003e","manuscriptTitle":"A ‘Standard of Care Plus’ Model for Preterm Birth Prevention: Integrating Nutrient and Gene Variant Analysis with Targeted Interventions: A Prospective Observational Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-18 14:33:03","doi":"10.21203/rs.3.rs-6739623/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f3e494b6-8d3f-47c7-9132-3af46f233390","owner":[],"postedDate":"July 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-21T08:54:08+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-18 14:33:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6739623","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6739623","identity":"rs-6739623","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}