Environmental health influences in pregnancy and risk of gestational diabetes mellitus: a systematic review.

BACKGROUND: Gestational diabetes mellitus (GDM) is one of the most common pregnancy complications globally. Environmental risk factors may lead to increased glucose levels and GDM, which in turn may affect not only the health of the mother but assuming hypotheses of "fetal programming", also the health of the offspring. In addition to traditional GDM risk factors, the evidence is growing that environmental influences might affect the development of GDM. We conducted a systematic review analyzing the association between several environmental health risk factors in pregnancy, including climate factors, chemicals and metals, and GDM. METHODS: We performed a systematic literature search in Medline (PubMed), EMBASE, CINAHL, Cochrane Library and Web of Science Core Collection databases for research articles published until March 2021. Epidemiological human and animal model studies that examined GDM as an outcome and / or glycemic outcomes and at least one environmental risk factor for GDM were included. RESULTS: Of n = 91 studies, we classified n = 28 air pollution, n = 18 persistent organic pollutants (POP), n = 11 arsenic, n = 9 phthalate n = 8 bisphenol A (BPA), n = 8 seasonality, n = 6 cadmium and n = 5 ambient temperature studies. In total, we identified two animal model studies. Whilst we found clear evidence for an association between GDM and air pollution, ambient temperature, season, cadmium, arsenic, POPs and phthalates, the findings regarding phenols were rather inconsistent. There were clear associations between adverse glycemic outcomes and air pollution, ambient temperature, season, POPs, phenols, and phthalates. Findings regarding cadmium and arsenic were heterogeneous (n = 2 publications in each case). CONCLUSIONS: Environmental risk factors are important to consider in the management and prevention of GDM. In view of mechanisms of fetal programming, the environmental risk factors investigated may impair the health of mother and offspring in the short and long term. Further research is needed.

Effectivness of specific mobile health applications (mHealth-apps) in gestational diabtetes mellitus: a systematic review.

BACKGROUND: Gestational diabetes mellitus (GDM) emerges worldwide and is closely associated with short- and long-term health issues in women and their offspring, such as pregnancy and birth complications respectively comorbidities, Type 2 Diabetes (T2D), metabolic syndrome as well as cardiovascular diseases. Against this background, mobile health applications (mHealth-Apps) do open up new possibilities to improve the management of GDM. Therefore, we analyzed the clinical effectiveness of specific mHealth-Apps on clinical health-related short and long-term outcomes in mother and child. METHODS: A systematic literature search in Medline (PubMed), Cochrane Library, Embase, CINAHL and Web of Science Core Collection databases as well as Google Scholar was performed. We selected studies published 2008 to 2020 analyzing women diagnosed with GDM using specific mHealth-Apps. Controlled clinical trials (CCT) and randomized controlled trials (RCT) were included. Study quality was assessed using the Effective Public Health Practice Project (EPHPP) tool. RESULTS: In total, n = 6 publications (n = 5 RCTs, n = 1 CCT; and n = 4 moderate, n = 2 weak quality), analyzing n = 408 GDM patients in the intervention and n = 405 in the control groups, were included. Compared to control groups, fasting blood glucose, 2-h postprandial blood glucose, off target blood glucose measurements, delivery mode (more vaginal deliveries and fewer (emergency) caesarean sections) and patient compliance showed improving trends. CONCLUSION: mHealth-Apps might improve health-related outcomes, particularly glycemic control, in the management of GDM. Further studies need to be done in more detail.

Impact of COVID-19 lockdown on glycemic control in patients with type 1 and type 2 diabetes mellitus: a systematic review.

BACKGROUND: In 2019, a new virus known as severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) has emerged. Coronavirus disease 2019 (COVID-19) was classified as a pandemic in a short period of time. In order to reduce the spread of COVID-19, many countries have imposed a lockdown with movement restrictions, social distancing and home confinement, which has affected routine healthcare activities and everyday life. The aim of this systematic review was to examine the impact of the COVID-19 lockdown on glycemic control in patients with type 1 diabetes (T1D) and type 2 diabetes (T2D). METHODS: We systematically identified studies by searching the databases Cochrane Library, MEDLINE via PubMed, Web of Science Core Collection, EMBASE, and CINAHL until April 2021. We included n = 33 observational studies of which n = 25 investigated T1D and n = 8 T2D. RESULTS: Overall, we analyzed n = 2881 T1D patients and n = 1823 T2D patients. Glycemic values in patients with T1D improved significantly during lockdown. Overall, n = 18 (72%) T1D studies indicated significant improvements in glycemic outcomes. Meta-analysis revealed a mean difference in HbA1c of - 0.05% (95% CI - 0.31 to 0.21) due to lockdown, and in time in range (TIR) of + 3.75% (95% CI 2.56 to 4.92). Lockdown determined a short-term worsening in glycemic values in patients with T2D. Overall, n = 4 (50%) publications observed deteriorations in glycemic control. Meta-analysis demonstrated a mean difference in HbA1c of + 0.14 (95% CI - 0.13 to 0.40) through the lockdown. Moreover, n = 3 (75%) studies reported a not significant deterioration in body weight. CONCLUSIONS: Glycemic values in people with T1D significantly improved during COVID-19 lockdown, which may be associated with positive changes in self-care and digital diabetes management. In contrast, lockdown rather determined a short-term worsening in glycemic parameters in patients with T2D. Further research is required, particularly into the causes and effective T2D management during lockdown.

Effects of Telemetric Interventions on Maternal and Fetal or Neonatal Outcomes in Gestational Diabetes: Systematic Meta-Review.

BACKGROUND: In 2019, 1 of 6 births was affected by gestational diabetes mellitus (GDM) globally. GDM results in adverse maternal, fetal, and neonatal outcomes in the short and long term, such as pregnancy and birth complications, type 2 diabetes, metabolic syndrome, and cardiovascular disease. In the context of "transgenerational programming," diabetes mellitus during pregnancy can contribute to "programming" errors and long-term consequences for the child. Therefore, early therapy strategies are required to improve the clinical management of GDM. The interest in digital therapy approaches, such as telemetry, has increased because they are promising, innovative, and sustainable. OBJECTIVE: This study aimed to assess the current evidence regarding the clinical effectiveness of telemetric interventions in the management of GDM, addressing maternal glycemic control, scheduled and unscheduled visits, satisfaction, diabetes self-efficacy, compliance, maternal complications in pregnancy and childbirth, as well as fetal and neonatal outcomes. METHODS: Medline via PubMed, Web of Science Core Collection, Embase, Cochrane Library, and CINAHL databases were systematically searched from January 2008 to April 2020. We included randomized controlled trials, systematic reviews, meta-analyses, and clinical trials in English and German. Study quality was assessed using "A MeaSurement Tool to Assess systematic Reviews" and "Effective Public Health Practice Project." RESULTS: Our search identified 1116 unique studies. Finally, we included 11 suitable studies (including a total of 563 patients and 2779 patient cases): 4 systematic reviews or meta-analyses (1 of high quality and 3 of moderate quality), 6 randomized controlled trials (2 of high quality and 4 of moderate quality), and 1 low-quality nonrandomized controlled trial. We classified 4 "asynchronous interventions" and 3 "asynchronous and real-time interventions." Our findings indicate that telemetric therapy clearly improves glycemic control and effectively reduces glycated hemoglobin A1c levels. Furthermore, in 1 study, telemetry proved to be a significant predictor for a better glycemic control (hazard ratio=1.71, 95% CI 1.11-2.65; P=.02), significantly fewer insulin titrations were required (P=.04), and glycemic control was achieved earlier. Telemetric therapy significantly reduced scheduled and unscheduled clinic visits effectively, and women were highly satisfied with the treatment (P<.05). From fetal and neonatal short-term outcomes, some improving tendencies in favor of telemetry were determined. No long-term outcomes were detected. CONCLUSIONS: Telemetric interventions clearly improved glycemic control, notably glycated hemoglobin A1c levels, and reduced scheduled and unscheduled clinic visits effectively, which reinforces this digital approach in the treatment of GDM.

SARS-CoV-2 in diabetic pregnancies: a systematic scoping review.

BACKGROUND: Currently, we suffer from an increasing diabetes pandemic and on the other hand from the SARS-CoV-2 pandemic. Already at the beginning of the SARS-CoV-2 pandemic, it was quickly assumed that certain groups are at increased risk to suffer from a severe course of COVID-19. There are serious concerns regarding potential adverse effects on maternal, fetal, and neonatal outcomes. Diabetic pregnancies clearly need special care, but clinical implications as well as the complex interplay of diabetes and SARS-CoV-2 are currently unknown. We summarized the evidence on SARS-CoV-2 in diabetic pregnancies, including the identification of novel potential pathophysiological mechanisms and interactions as well as clinical outcomes and features, screening, and management approaches. METHODS: We carried out a systematic scoping review in MEDLINE (PubMed), EMBASE, CINAHL, Cochrane Library, and Web of Science Core Collection in September 2020. RESULTS: We found that the prognosis of pregnant women with diabetes mellitus and COVID-19 may be associated with potential underlying mechanisms such as a simplified viral uptake by ACE2, a higher basal value of pro-inflammatory cytokines, being hypoxemic as well as platelet activation, embolism, and preeclampsia. In the context of "trans-generational programming" and COVID-19, life-long consequences may be "programmed" during gestation by pro-inflammation, hypoxia, over- or under-expression of transporters and enzymes, and epigenetic modifications based on changes in the intra-uterine milieu. COVID-19 may cause new onset diabetes mellitus, and that vertical transmission from mother to baby might be possible. CONCLUSIONS: Given the challenges in clinical management, the complex interplay between COVID-19 and diabetic pregnancies, evidence-based recommendations are urgently needed. Digital medicine is a future-oriented and effective approach in the context of clinical diabetes management. We anticipate our review to be a starting point to understand and analyze mechanisms and epidemiology to most effectively treat women with SARS-COV-2 and diabetes in pregnancy.

Telemedical Approaches to Managing Gestational Diabetes Mellitus During COVID-19: Systematic Review.

BACKGROUND: In 2019, a new coronavirus emerged in China, and the disease caused by the virus (COVID-19) was rapidly classified as a pandemic. Pregnant women with gestational diabetes mellitus (GDM) are considered to be at risk for severe COVID-19. In the context of the pandemic, there are serious concerns regarding adverse effects on maternal and neonatal outcomes for women with GDM. Effective treatments for patients with GDM are therefore particularly important. Due to contact restrictions and infection risks, digital approaches such as telemedicine are suitable alternatives. OBJECTIVE: This systematic review aims to summarize currently available evidence on maternal and offspring outcomes of pregnant women with GDM and COVID-19 and to examine telemedical interventions to improve maternal glycemic control during the COVID-19 pandemic. METHODS: Publications were systematically identified by searching the Cochrane Library, MEDLINE via PubMed, Web of Science Core Collection, Embase, and CINAHL databases for studies published up to March 2021. We sorted the COVID-19 studies by outcome and divided the telemedical intervention studies into web-based and app-based groups. We analyzed case reports (COVID-19) and both randomized and nonrandomized controlled clinical trials (telemedicine). To determine the change in glycated hemoglobin A1c (HbA1c), we pooled appropriate studies and calculated the differences in means, with 95% CIs, for the intervention and control groups at the end of the interventions. RESULTS: Regarding COVID-19 studies, we identified 11 case reports, 3 letters, 1 case series, and 1 retrospective single-center study. In total, 41 patients with GDM and COVID-19 were analyzed. The maternal and neonatal outcomes were extremely heterogeneous. We identified adverse outcomes for mother and child through the interaction of GDM and COVID-19, such as cesarean deliveries and low Apgar scores. Furthermore, we selected 9 telemedicine-related articles: 6 were randomized controlled trials, 2 were clinical controlled trials, and 1 was a quasi-experimental design. In total, we analyzed 480 patients with GDM in the intervention groups and 494 in the control groups. Regarding the quality of the 9 telemedical studies, 4 were rated as strong, 4 as moderate, and 1 as weak. Telemedical interventions can contribute to favorable impacts on HbA1c and fasting blood glucose values in the context of the COVID-19 pandemic. Meta-analysis revealed a mean difference in HbA1c of -0.19% (95% CI 0.34% to 0.03%) for all telemedical interventions, -0.138% (95% CI -0.24% to -0.04%) for the web-based interventions, and -0.305% (96% CI -0.88% to 0.27%) for the app-based interventions. CONCLUSIONS: Telemedicine is an effective approach in the context of COVID-19 and GDM because it enables social distancing and represents optimal care of patients with GDM, especially with regard to glycemic control, which is very important in view of the identified adverse maternal and neonatal outcomes. Further research is needed.

Clinical Effectiveness of Different Technologies for Diabetes in Pregnancy: Systematic Literature Review.

BACKGROUND: Hyperglycemia in pregnancy occurs worldwide and is closely associated with health issues in women and their offspring, such as pregnancy and birth complications, respectively, as well as comorbidities, such as metabolic and cardiovascular diseases. To optimize the management of diabetic pregnancies, sustainable strategies are urgently needed. Investigation of constantly evolving technologies for diabetes that help to manage pregnancy and health is required. OBJECTIVE: We aimed to conduct a systematic review to assess the clinical effectiveness of technologies for diabetes in pregnancy. METHODS: Relevant databases including MEDLINE (PubMed), Cochrane Library, Embase, CINAHL, and Web of Science Core Collection were searched in September 2020 for clinical studies (2008-2020). Findings were organized by type of diabetes, type of technology, and outcomes (glycemic control, pregnancy- and birth-related outcomes, and neonatal outcomes). Study quality was assessed using Effective Public Health Practice Project criteria. RESULTS: We identified 15 randomized controlled trials, 3 randomized crossover trials, 2 cohort studies, and 2 controlled clinical trials. Overall, 9 studies focused on type 1 diabetes, 0 studies focused on gestational diabetes, and 3 studies focused on both type 1 diabetes and type 2 diabetes. We found that 9 studies were strong quality, 11 were moderate quality, and 2 were weak quality. Technologies for diabetes seemed to have particularly positive effects on glycemic control in all types of diabetes, shown by some strong and moderate quality studies. Positive trends in pregnancy-related, birth-related, and neonatal outcomes were observed. CONCLUSIONS: Technologies have the potential to effectively improve the management of diabetes during pregnancy. Further research on the clinical effectiveness of these technologies is needed, especially in pregnant women with type 2 diabetes.

Diabetology 4.0: Scoping Review of Novel Insights and Possibilities Offered by Digitalization.

BACKGROUND: The increasing prevalence of diabetes mellitus and associated morbidity worldwide justifies the need to create new approaches and strategies for diabetes therapy. Therefore, the ongoing digitalization offers novel opportunities in this field. OBJECTIVE: The aim of this study is to provide an updated overview of available technologies, possibilities, and novel insights into diabetes therapy 4.0. METHODS: A scoping review was carried out, and a literature search was performed using electronic databases (MEDLINE [PubMed], Cochrane Library, Embase, CINAHL, and Web of Science). The results were categorized according to the type of technology presented. RESULTS: Different types of technology (eg, glucose monitoring systems, insulin pens, insulin pumps, closed-loop systems, mobile health apps, telemedicine, and electronic medical records) may help to improve diabetes treatment. These improvements primarily affect glycemic control. However, they may also help in increasing the autonomy and quality of life of people who are diagnosed with diabetes mellitus. CONCLUSIONS: Diabetes technologies have developed rapidly over the last few years and offer novel insights into diabetes therapy and a chance to improve and individualize diabetes treatment. Challenges that need to be addressed in the following years relate to data security, interoperability, and the development of standards.

Telemetric Interventions Offer New Opportunities for Managing Type 1 Diabetes Mellitus: Systematic Meta-review.

BACKGROUND: The prevalence of diabetes mellitus (DM) is increasing rapidly worldwide. Simultaneously, technological advances are offering new opportunities for better management of type 1 diabetes mellitus (T1DM). Telemetry, the remote acquisition of patient data via a telecommunication system, is a promising field of application in eHealth and is rapidly gaining importance. OBJECTIVE: The aim of this study was to summarize the current evidences available on the effectiveness of telemetric approaches in T1DM management. This systematic meta-review examined different types of interventions of the technologies used in communication between health care professionals and patients as well as the key outcomes. METHODS: We performed a systematic search in Web of Science Core Collection, EMBASE, Cochrane Library, MEDLINE via PubMed, and CINAHL databases in April 2020 with regard to the effectiveness of telemetric interventions for T1DM. We classified the interventions into 4 categories according to the technology used: (1) real-time video communication, (2) real-time audio communication, (3) asynchronous communication, and (4) combined forms of communication (real-time and asynchronous). We considered various study designs such as systematic reviews, clinical trials, meta-analyses, and randomized controlled trials and focused on the key outcomes. Additionally, a funnel plot based on hemoglobin A1c (HbA1c) values and different quality assessments were performed. RESULTS: We identified 17 (6 high quality and 9 moderate quality) eligible publications: randomized controlled trials (n=9), systematic reviews and meta-analyses (n=5), cohort studies (n=2), and qualitative publications (n=1). Of 12 studies, 8 (67%) indicated a (significant or nonsignificant) reduction in HbA1c levels; 65% (11/17) of the studies reported overall (mildly) positive effects of telemetric interventions by addressing all the measured outcomes. Asynchronous interventions were the most successful for patients diagnosed with T1DM, but no technology was clearly superior. However, there were many nonsignificant results and not sustained effects, and in some studies, the control group benefited from telemetric support or increased frequency of contacts. CONCLUSIONS: Based on the currently available literature, this systematic meta-review shows that telemetric interventions cause significant reduction in HbA1c levels and result in overall positive effects in T1DM management. However, more specified effects of telemetric approaches in T1DM management should be analyzed in detail in larger cohorts.

Clinical Improvements by Telemedicine Interventions Managing Type 1 and Type 2 Diabetes: Systematic Meta-review.

BACKGROUND: Diabetes mellitus (DM) is one of the world's greatest health threats with rising prevalence. Global digitalization leads to new digital approaches in diabetes management, such as telemedical interventions. Telemedicine, which is the use of information and communication technologies, may provide medical services over spatial distances to improve clinical patient outcomes by increasing access to diabetes care and medical information. OBJECTIVE: This study aims to examine whether telemedical interventions effectively improve diabetes control using studies that pooled patients with type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM), and whether the benefits are greater in patients diagnosed with T2DM than in those diagnosed with T1DM. We analyzed the primary outcome glycated hemoglobin A1c (HbA1c) and the secondary outcomes fasting blood glucose (FBG), blood pressure (BP), body weight, BMI, quality of life (QoL), cost, and time saving. METHODS: Publications were systematically identified by searching Cochrane Library, MEDLINE via PubMed, Web of Science Core Collection, Embase, and CINAHL databases for studies published between January 2008 and April 2020, considering systematic reviews (SRs), meta-analyses (MAs), randomized controlled trials (RCTs), and clinical trials (CTs). Study quality was assessed using the A Measurement Tool to Assess Systematic Reviews, Effective Public Health Practice Project, and National Institute for Health and Care Excellence qualitative checklist. We organized the trials by communication technologies in real-time video or audio interventions, asynchronous interventions, and combined interventions (synchronous and asynchronous communication). RESULTS: From 1116 unique citations, we identified 31 eligible studies (n=15 high, n=14 moderate, n=1 weak, and n=1 critically low quality). We selected 21 SRs and MAs, 8 RCTs, 1 non-RCT, and 1 qualitative study. Of the 10 trials, 3 were categorized as real-time video, 1 as real-time video and audio, 4 as asynchronous, and 2 as combined intervention. Significant decline in HbA1c levels based on pooled T1DM and T2DM patients data ranged from -0.22% weighted mean difference (WMD; 95% CI -0.28 to -0.15; P<.001) to -0.64% mean difference (95% CI -1.01 to -0.26; P<.001). The intervention effect on lowering HbA1c values might be significantly smaller for patients with T1DM than for patients with T2DM. Evidence on the impact on BP, body weight, FBG, cost effectiveness, and time saving was smaller compared with HbA1c but indicated potential in some publications. CONCLUSIONS: Telemedical interventions might be clinically effective in improving diabetes control overall, and they might significantly improve HbA1c concentrations. Patients with T2DM could benefit more than patients with T1DM regarding lowering HbA1c levels. Further studies with longer duration and larger cohorts are necessary.

Effectiveness of Disease-Specific mHealth Apps in Patients With Diabetes Mellitus: Scoping Review.

BACKGROUND: According to the World Health Organization, the worldwide prevalence of diabetes mellitus (DM) is increasing dramatically and DM comprises a large part of the global burden of disease. At the same time, the ongoing digitalization that is occurring in society today offers novel possibilities to deal with this challenge, such as the creation of mobile health (mHealth) apps. However, while a great variety of DM-specific mHealth apps exist, the evidence in terms of their clinical effectiveness is still limited. OBJECTIVE: The objective of this review was to evaluate the clinical effectiveness of mHealth apps in DM management by analyzing health-related outcomes in patients diagnosed with type 1 DM (T1DM), type 2 DM (T2DM), and gestational DM. METHODS: A scoping review was performed. A systematic literature search was conducted in MEDLINE (PubMed), Cochrane Library, EMBASE, CINAHL, and Web of Science Core Collection databases for studies published between January 2008 and October 2020. The studies were categorized by outcomes and type of DM. In addition, we carried out a meta-analysis to determine the impact of DM-specific mHealth apps on the management of glycated hemoglobin (HbA1c). RESULTS: In total, 27 studies comprising 2887 patients were included. We analyzed 19 randomized controlled trials, 1 randomized crossover trial, 1 exploratory study, 1 observational study, and 5 pre-post design studies. Overall, there was a clear improvement in HbA1c values in patients diagnosed with T1DM and T2DM. In addition, positive tendencies toward improved self-care and self-efficacy as a result of mHealth app use were found. The meta-analysis revealed an effect size, compared with usual care, of a mean difference of -0.54% (95% CI -0.8 to -0.28) for T2DM and -0.63% (95% CI -0.93 to -0.32) for T1DM. CONCLUSIONS: DM-specific mHealth apps improved the glycemic control by significantly reducing HbA1c values in patients with T1DM and T2DM patients. In general, mHealth apps effectively enhanced DM management. However, further research in terms of clinical effectiveness needs to be done in greater detail.

Effect of Telemetric Interventions on Glycated Hemoglobin A1c and Management of Type 2 Diabetes Mellitus: Systematic Meta-Review.

BACKGROUND: Diabetes mellitus is a chronic burden, with a prevalence that is increasing worldwide. Telemetric interventions have attracted great interest and may provide effective new therapeutic approaches for improving type 2 diabetes mellitus (T2DM) care. OBJECTIVE: The objective of this study was to analyze the clinical effectiveness of telemetric interventions on glycated hemoglobin A1c (HbA1c) specifically and T2DM management generally in a systematic meta-review. METHODS: A systematic literature search was performed in PubMed, CINAHL, Cochrane Library, Web of Science Core Collection, and EMBASE databases from January 2008 to April 2020. Studies that addressed HbA1c, blood pressure, fasting blood glucose, BMI, diabetes-related and health-related quality of life, cost-effectiveness, time savings, and the clinical effectiveness of telemetric interventions were analyzed. In total, 73 randomized controlled trials (RCTs), 10 systematic reviews/meta-analyses, 9 qualitative studies, 2 cohort studies, 2 nonrandomized controlled studies, 2 observational studies, and 1 noncontrolled intervention study were analyzed. RESULTS: Overall, 1647 citations were identified. After careful screening, 99 studies (n=15,939 patients; n=82,436 patient cases) were selected by two independent reviewers for inclusion in the review. Telemetric interventions were categorized according to communication channels to health care providers: (1) "real-time video" interventions, (2) "real-time audio" interventions, (3) "asynchronous" interventions, and (4) "combined" interventions. To analyze changes in HbA1c, suitable RCTs were pooled and the average was determined. An HbA1c decrease of -1.15% (95% CI -1.84% to -0.45%), yielding an HbA1c value of 6.95% (SD 0.495), was shown in studies using 6-month "real-time video" interventions. CONCLUSIONS: Telemetric interventions clearly improve HbA1c values in both the short term and the long term and contribute to the effective management of T2DM. More studies need to be done in greater detail.

Impact of maternal prenatal stress by glucocorticoids on metabolic and cardiovascular outcomes in their offspring: A systematic scoping review.

BACKGROUND: "Stress" is an emerging problem in our society, health care system as well as patient care, worldwide. Especially by focusing on pre-gestational, gestational but also lactation phases "stress" is to be considered as an own trans-generational risk factor which is associated with adverse metabolic as well cardiovascular outcomes in mothers and their children. Hence, the maternal hypothalamic-pituitary-adrenotrophic (HPA) axis may be stimulated by various "stress" mechanisms as well as risk factors leading to an adverse in utero environment, e.g. by excess exposure of glucocorticoids, contributing to cardio-metabolic disorders in mothers and their offspring. OBJECTIVE: To review the evidence of in utero programming by focusing on the impact of maternal "stress", on adverse cardio-metabolic outcomes on their offspring later in life, by identifying underlying (patho-) physiological mechanisms (1) as well as adverse short and long-term cardio-metabolic outcomes (2). METHODS: We conducted a systematic scoping review to identify publications systematically including reviews, interventional, observational, experimental studies as well as human and animal model studies. MEDLINE (PubMed) and EMBASE databases and reference lists were searched. Peer-reviewed articles from January 2000 until August 2020 were included. RESULTS: Overall, n = 2.634 citations were identified, n = 45 eligible studies were included and synthesized according to their key findings. In brief, maternal hypothalamic-pituitary-adrenotrophic (HPA) axis might play a key role modifying in utero milieu leading to cardio-metabolic diseases in the offspring later in life. However, maternal risk factor "stress", is clearly linked to adverse cardio-metabolic offspring outcomes, postnatally, such as obesity, hyperglycemia, insulin resistance, diabetes mellitus (DM), Metabolic Syndrome (MetS), cardiovascular disease (CD), hypertension, restricted fetal growth as well as reduced birth, adrenal, and pancreas weights. CONCLUSIONS: Women who experienced "stress" as risk factor, as well as their offspring, clearly have a higher risk of adverse short- as well as long-term cardio-metabolic outcomes. Future research work is needed to understand complex transgenerational mechanisms.

A combined in vivo and in silico model shows specific predictors of individual trans-generational diabetic programming.

Diabetic pregnancies are cleary associated with maternal type 2 diabetes and metabolic syndrome as well as atherosclerotic diseases in the offspring. The global prevalence of hyperglycemia in pregnancy was estimated as 15.8% of live births to women in 2019, with an upward trend. Numerous parental risk factors as well as trans-generational mechanisms targeting the utero-placental system, leading to diabetes, dysmetabolic and atherosclerotic conditions in the next generation, seem to be involved within this pathophysiological context. To focus on the predictable impact of trans-generational diabetic programming, we studied age- and gender-matched offspring of diabetic and nondiabetic mothers. The offspring generation consists of three groups: C57BL/6-J-Ins2Akita (positive control group), wild-type C57BL/6-J-Ins2Akita (experimental group), and C57BL/6-J mice (negative control group). We undertook intraperitoneal glucose tolerance tests at 3 and 11 weeks of age. Moreover, this in vivo model was complemented by a corresponding in silico model. Although at 3 weeks of age, no significant effects could be observed, we could demonstrate at 11 weeks of age characteristic and significant differences in relation to maternal diabetic imprinting based on the in silico model-based predictors. These predictors allow the generation of a concise classification tree assigning maternal diabetic imprinting correctly in 91% of study cases. Our data show that hyperglycemic in utero milieu contributes to trans-generational diabetic programming leading to impaired glucose tolerance in the offspring of diabetic mothers early on. These observations can be clearly and early distinguished from genetically determined diabetes, for example, type 1 diabetes, in which basal glucose values are significantly raised.

Paternal metabolic and cardiovascular programming of their offspring: A systematic scoping review.

BACKGROUND: There is lots of evidence that maternal peri-gestational metabolic, genomic and environmental conditions are closely linked to metabolic and cardiovascular outcomes in their offspring later in life. Moreover, there is also lotsof evidence that underlining mechanisms, such as molecular as well as epigenetic changes may alter the intrauterine environment leading to cardio-metabolic diseases in their offspring postnatal. But, there is also increasing evidence that cardio-metabolic diseases may be closely linked to their paternal metabolic risk factors, such as obesity, Type 2 Diabetes and other risk factors. OBJECTIVE: To analyse the evidence as well as specific risk factors of paternal trans-generational programming of cardio-metabolic diseases in their offspring. METHODS: Within a systematic scoping review, we performed a literature search in MEDLINE (PubMed) and EMBASE databases in August 2020 considering original research articles (2000-2020) that examined the impact of paternal programming on metabolic and cardiovascular offspring health. Epidemiological, clinical and experimental studies as well as human and animal model studies were included. RESULTS: From n = 3.199 citations, n = 66 eligible studies were included. We selected n = 45 epidemiological as well as clinical studies and n = 21 experimental studies. In brief, pre-conceptional paternal risk factors, such as obesity, own birth weight, high-fat and low-protein diet, undernutrition, diabetes mellitus, hyperglycaemia, advanced age, smoking as well as environmental chemical exposure affect clearly metabolic and cardiovascular health of their offspring later in life. CONCLUSIONS: There is emerging evidence that paternal risk factors, such as paternal obesity, diabetes mellitus, nutritional habits, advanced age and exposure to environmental chemicals or cigarette smoke, are clearly associated with adverse effects in metabolic and cardiovascular health in their offspring. Compared to maternal programming, pre-conceptional paternal factors might also have also a substantial effect in the sense of trans-generational programming of their offspring and need further research.

Climate factors and gestational diabetes mellitus risk - a systematic review.

BACKGROUND: Current and projected increases in global temperatures and extreme climate events have led to heightened interest in the impact of climate factors (i.e. ambient temperature, season/seasonality, and humidity) on human health. There is growing evidence that climate factors may impact metabolic function, including insulin sensitivity. Gestational diabetes mellitus (GDM) is a common pregnancy complication, with an estimated global prevalence of up to 14%. While lifestyle and genetic risk factors for GDM are well established, environmental factors may also contribute to GDM risk. Previous reviews have summarized the growing evidence of environmental risk factors for GDM including endocrine disrupting chemicals and ambient air pollution. However, studies of the effects of climate factors on GDM risk have not been systematically evaluated. Therefore, we conducted a systematic review to summarize and evaluate the current literature on the associations of climate factors with GDM risk. METHODS: We conducted systematic searches in PubMed and EMBASE databases for original research articles on associations of climate factors (i.e. ambient temperature, season/seasonality, and humidity) with GDM and/or related glycemic outcomes for all publication dates through September 20th, 2020. RESULTS: Our search identified 16 articles on the associations of ambient temperature and/or season with GDM and maternal glycemic outcomes during pregnancy, which were included in this review. Despite inconsistencies in exposure and outcome assessment, we found consistent evidence of a seasonal effect on GDM risk, with higher prevalence of GDM and higher pregnancy glucose levels in summer months. We found suggestive evidence of an association between higher ambient temperature and elevated glucose levels from GDM screening tests. CONCLUSION: Climate factors may be associated with GDM risk. However, further research is needed to evaluate these associations and to elucidate the specific mechanisms involved.

Model-driven Classification of Different Diabetes Types within a Personalized Diabetes Management.

In this paper, an approach for the classification of dynamic models of diabetes mellitus is presented. The parameter vector of a personalized patient model, which has been identified e.g. by parameter estimation, is used as a classification feature. Principle component analysis and a support vector machine are used to reduce the feature space and to find a suitable classifier. The data covers type 1, type 2, and non-diabetic virtual subjects. Classification results show a good distinguishability between the classes, whereby the method may serve as a supplement in the area of model-driven diabetes management.

Access to Difficult-to-reach Population Subgroups: A Family Midwife Based Home Visiting Service for Implementing Nutrition-related Preventive Activities - A Mixed Methods Explorative Study.

Health and social inequality are tightly linked and still pose an important public health problem. However, vulnerable and disadvantaged populations are difficult to reach for health-related interventions. Given the long-lasting effects of an adverse, particular nutrition-related, intrauterine and neonatal environment on health development (perinatal programming), an early and easy access is essential for sustainable interventions. The goal of this explorative study was therefore to elucidate whether an existing access of family midwives (FMs) to families in need of support could be an option to implement effective public health and nutrition interventions. To that end three research objectives were formulated: (1) to determine whether a discernible impact of home visits by FMs can be described; (2) to identify subgroups among these families in need of more specific interventions; (3) to determine how relevant nutrition-related topics are for both FMs and the supported families. For addressing these objectives a mixed methods design was used: Routine documentation data from 295 families visited by a family midwife (FM) were analyzed (secondary analysis), and structured expert interviews with FMs were conducted and analyzed. Study reporting followed the STROBE (STrengthening the Reporting of OBservational studies in Epidemiology) statement. Based on the FMs reports, a significant improvement (p < 0.001) regarding psycho-social variables could be determined after the home visits. Single mothers, however, seemed to benefit less from the FMs service compared to their counterparts (p = 0.015). Nutritional counseling was demanded by 89% of the families during the home visits. In addition, nutrition-related topics were reported in the interviews to be of high interest to both families and the FMs. Based on the obtained results it is concluded that FMs home visits offer a promising access to vulnerable and disadvantaged families for implementing nutrition-related preventive activities.

Novel individual metabolic profile characterizes the protein kinase B-alpha (pkbα-/-) in vivo model.

CONTEXT: Type 2 diabetes and associated co-morbidities run epidemic waves worldwide. Since pathophysiological constellations are individual and display a wide spread of dysmetabolic profiles personalized health care assessments start to emerge. Therefore, we established a specific in silico assessment tool targeting metabolic characterizations individually. MATERIALS AND METHODS: Values obtained from oral glucose and intraperitoneal insulin tolerance tests performed on pkbα(-/-) mice (KO) as well as age- and gender-matched controls (WT) were analysed using our established in silico model. RESULTS: Generally, male pkbα(-/-) mice (KO) presented significantly increased insulin sensitivity at an age of 6 months compared with age-matched WTs (p = 0.036). Female KO and WT groups displayed improved glucose sensitivities compared with age-matched males (for WT p ≤ 0.011). DISCUSSION AND CONCLUSION: Specific metabolic characterization should be assessed individually. Therefore, our in silico model enables novel insights inaugurating specific primary preventive strategies targeting individual metabolic profiling precisely.

Identification of tissue differentiation rates in a mechanobiological model of fracture healing.

As a basis for model-based analysis of the processes in secondary fracture healing, a dynamical model is presented that characterises the physiological status in the fracture area by the location-dependent composition of tissues. Five types of tissue are distinguished: connective tissue, cartilage, bone, haematoma and avascular bone. A rule base is given that describes dynamical tissue differentiation processes. The rules consider not only a mechanical stimulus but also osteogenic and a vasculative factors as biological stimuli. Within this model structure, it is possible, e.g., to distinguish intramembranous from endochondral ossification processes. An objective function is introduced to assess accordance between the model-based simulation results and reference healing stages. By minimising this objective function, relevant tissue differentiation rates can be determined. For a reference process of secondary fracture healing it could be shown that the intramembranous ossification rate of 0.313%/day (from connective tissue to bone) is much smaller than the endochondral ossification rate of 1.136%/day (from cartilage to bone). In order to verify the model approach, it is transferred to simulate long bone distraction. Results show that healing patterns of bone distraction can be predicted. Using this method, it is possible to identify model parameters for individual subjects. This will allow a patient-specific analysis of tissue healing processes in future.