Early life factors and their relevance to intimamedia thickness of the common carotid artery in early adulthood

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Study Justification:
This study aimed to investigate the associations between early life factors and the thickness of the carotid artery wall (intimamedia thickness or IMT) in a healthy German population. The researchers wanted to determine if early life factors, such as maternal age at childbirth, birth weight, gestational weight gain, and breastfeeding, could influence the development of atherosclerosis (hardening of the arteries) in adulthood. Understanding these associations could provide insights into the potential long-term effects of early life factors on cardiovascular health.
Study Highlights:
– The study analyzed data from the Dortmund Nutritional and Anthropometric Longitudinally Designed (DONALD) Study, which has been collecting information on diet, growth, development, and metabolism since 1985.
– A total of 265 participants, aged 18-40 years, were included in the analysis.
– Measurements of IMT were taken from the common carotid artery, which is a surrogate marker of atherosclerosis.
– The study found that advanced maternal age at childbirth was associated with increased IMT levels in female offspring, but not in males. Other early life factors did not show significant associations with IMT levels in both males and females.
Recommendations for Lay Readers:
Based on the findings of this study, it is recommended that individuals, particularly females, be aware of the potential impact of advanced maternal age at childbirth on cardiovascular health in later life. This information may be relevant for women planning to have children or those who have already given birth at an older age. It is important to note that other early life factors, such as birth weight, gestational weight gain, and breastfeeding, did not show significant associations with IMT levels in this study.
Recommendations for Policy Makers:
Policy makers should consider the implications of advanced maternal age at childbirth on cardiovascular health, particularly for females. This information may be useful in developing public health strategies aimed at promoting healthy pregnancies and optimizing maternal and child health outcomes. Further research is needed to better understand the underlying mechanisms and potential interventions to mitigate the adverse effects of advanced maternal age on cardiovascular health.
Key Role Players:
– Researchers and scientists: Conduct further studies to validate the findings and explore the underlying mechanisms.
– Healthcare professionals: Provide counseling and education to women of reproductive age about the potential impact of advanced maternal age on cardiovascular health.
– Public health officials: Incorporate information on the association between early life factors and cardiovascular health into public health campaigns and initiatives.
– Policy makers: Consider the findings when developing policies related to maternal and child health.
Cost Items for Planning Recommendations:
– Research funding: Allocate resources for further studies investigating the associations between early life factors and cardiovascular health outcomes.
– Healthcare services: Provide access to counseling and education for women regarding the potential risks associated with advanced maternal age at childbirth.
– Public health campaigns: Budget for the development and implementation of campaigns aimed at raising awareness about the long-term effects of early life factors on cardiovascular health.
– Training and education: Invest in training healthcare professionals to effectively communicate and provide evidence-based guidance on maternal and child health.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is rated 7 because it provides a clear description of the study design, sample size, and statistical analysis. However, it lacks information on potential limitations and generalizability of the findings. To improve the evidence, the abstract could include a discussion of the study’s limitations, such as the potential for selection bias due to non-participation or missing data. Additionally, it could provide information on the generalizability of the findings to other populations or settings.

Background Early life factors may predispose an offspring to cardiovascular disease in later life; relevance of these associations may extend to “healthy” people in Western populations. We examined the prospective associations between early life factors and adult carotid intimamedia thickness (IMT), a surrogate marker of atherosclerosis, in a healthy German population. Methods We studied term participants (n = 265) of the DONALD Study, with bilateral sonographic measurements of IMT (4-8 measurements on both left and right carotid artery) at age 18- 40 years and prospectively collected data on early life factors (maternal and paternal age at child birth, birth weight, gestational weight gain and full breastfeeding (>17weeks). Mean IMT values were averaged from mean values of both sides. Associations between early life factors and adult IMT were analyzed using multivariable linear regression models with adjustment for potential confounders. Results Adult mean IMT was 0.56mm, SD 0.03, (range: 0.41 mm-0.78 mm). Maternal age at child birth was of relevance for adult IMT, which was sex specific: Advanced maternal age at child birth was associated with an increased adult IMT among female offspring only (β 0.03, SE 0.009 mm/decade, P = 0.003), this was not affected by adult waist circumference, BMI or blood pressure. Other early life factors were not relevant for IMT levels in males and females. Conclusion This study suggests that advanced maternal age at child birth is of prospective relevance for adult IMT levels in a healthy German population and this association may be of adverse relevance for females only.

The Dortmund Nutritional and Anthropometric Longitudinally Designed (DONALD Study), is a continual, open cohort study undertaken in Dortmund, Germany. Since its commencement in 1985, elaborate records on diet, growth, development, and metabolism has been gathered from over 1,700 children between infancy and adulthood. About 35–40 infants are newly enrolled each year while initial examination commences at the age of 3–6 months, afterwards each child returns for 2–3 more visits in the first year, 2 in the second year and then once yearly until adulthood. The study protocol conforms to the ethical guidelines of the 1975 Declaration of Helsinki. The study was approved by the Ethics Committee of the University of Bonn. The data protection officer is Dr. Jörg Hartmann and requests for data access may be sent to the local data protection coordinator Heinz Rinke, email: ed.nnob-inu@eknir at the University of Bonn. All examinations are performed with written consent of parent and adult participant [24–28]. The children who were initially recruited for the DONALD Study differed considerably in age and prospectively collected data on breastfeeding was not always available. Follow-up into adulthood was not planned at the inception of the study. Since 2004 participants are invited to return for further visits at ages 18, 21, 25, 30, 35 etc. However, not all participants followed this invitation. In addition, due to the open cohort design, many DONALD participants had not yet reached young adulthood by the time of this analysis. IMT measurements are offered to adolescents and adult participants since 2008. In this analysis only IMT measurements in adulthood (≥18 years of age) are used. Mean follow-up until IMT measurement is equivalent to the mean age at IMT-measurement. 607 IMT measurements were available with two persons excluded due to the presence of plaques and stenosis in their measurement. 58 others did not have a minimum of four measurements each on the right and left common carotid artery to be included in the analysis whilst 178 persons were not considered because the images did not fulfill the quality control criteria (see below). Among the remaining 369 persons with acceptable IMT measurements, data from 349 persons were considered who were born term (37–42 weeks of gestation) singletons with a birthweight ˃ = 2500g. A further 84 persons were excluded because they did not fulfill the following minimum requirements: Parents had to have provided information on maternal age at birth, only available for 262, paternal age at birth, only available for 256, birth year, birth weight, gestational weight gain only available for 258 and gestational duration. Hence the sample considered for this analysis includes 265 participants with information on IMT collected between 2009 and 2014. See Fig 1, for the sample size of early life factors and for relevant covariates see Table 1. Values are presented as means (SD) medians (IQR) or frequencies (percentage). AGA: appropriate for gestational age, LGA: large for gestational age, SGA: small for gestational age. AGA, LGA and SGA defined according to German sex-specific birth weight and length-for-gestational-age curves. 1Average IMT: mean of intima media thickness (IMT). 2Participation in organized or unorganized sport: (yes/no). 3Estimated energy expenditure during participation in organized or unorganized sport. 4High gestational weight gain: yes (>16kg), no (≤16kg). 5 Birth weight by gestation age 6Maternal overweight: yes (≥ 25kg), no (<25kg). 7High educational status: yes (≥12yrs of school attendance), no (<12yrs of school attendance). Child birth and maternal characteristics were extracted from the “Mutterpass,” a standard document given to all pregnant women in Germany. Gestational duration is calculated according to the mother’s last menstrual period. Maternal weight at first visit at the gynecologist during pregnancy and at the end of pregnancy weight were abstracted from the “Mutterpass,” and from these the gestational weight gain was computed. Birth weight and birth length were recorded at birth. Birth weight-for-gestational-age is defined according to the German sex-specific birth weight and length-for-gestational-age curves [29]. Small-for-gestational-age (SGA) is defined as birth weight and length <10th percentile, and large-for-gestational-age (LGA) is defined as birth weight and length ˃90th percentile. All other infants were classified as appropriate-for gestational age (AGA). Maternal and paternal age at the time of child birth is assessed at first visit. Breastfeeding data was assessed upon the child’s admission to the study. During first visit either at 3 or 6 months the study pediatrician and/or dietitian enquired from the mothers the duration (in weeks) the infant had been fully breastfed (not given solid foods and no liquids daily except breast milk, tea, or water). If the child is still being fully breastfed, the length of breastfeeding is assessed at successive visits at ages 6, 9, 12 and 18 months until commencement of complementary feeding. The duration of feeding formula or solid foods is also assessed during the visits. A coherent check is conducted on all breast feeding information collected such as the recording of breast milk in 3-day dietary records and information acquired by the dietitians before analysis to minimize errors. From this information the duration (in weeks) of full breastfeeding is calculated [30]. Vascular conditions of the left and right common carotid artery (CA) were studied ultrasonographically using high-resolution technology. The Mindray DP3300, tragbares portable digital system was used for this study. The participants were measured in a supine position, head slightly to the right or left after having rested for 10 min. The start point of the measurement was at the beginning of the bifurcation at the left edge of the image with a horizontal vessel course. IMT was measured at 4 points 1 cm before the carotid bifurcation. Images were always taken in the systole. Two images were first taken each on the right and left CA on the participants and the images were frozen. Subsequently, measurements were taken at four measurement points on each image. Quality control was carried out on all images and only images that met the criteria were used for analysis. The criteria for IMT measurement quality control are based on 1) clear representation of the Intima-Media-Complex of the “far wall “shown as echo-rich/echo-poor uninterrupted line, 2) echo-free imaging of the vessel lumen and clear separation of the intima from the lumen, 3) localization of the image section at the beginning of the bifurcation and 4) horizontal course of the vessel within the image. Individual measurement points were discarded, if they were set incorrectly (i.e. the point for measurement was set below or above the visible IMT lines). Mean IMT values were firstly averaged for the right and left sides (i.e. 4–8 measurements), and then an overall mean was calculated from the two averages. All measurements were performed by the study physicians. Each year, a quality control of IMT measurement by the physicians is carried out. Coefficient of variation (CV) which considers the precision of the measurements within and between the physicians is computed and from 2009 to 2015, the values are CVintra = 6.95 and CVinter = 3.70. An acceptable precision is given at a value less than 10. Anthropometry of study participants were taken at each visit using standard protocol by trained nurses. The participants are dressed in only underwear and are barefooted. Recumbent length of children until 2 years of age is measured to the nearest 0.1 cm using a Harpenden (UK) stadiometer, whilst standing height is measured in children aged older than 2 years to the nearest 0.1 cm with a digital stadiometer (Harpenden Ltd., Crymych, UK). Body weight is measured to the nearest 100 g using an electronic scale (Seca 753E; Seca Weighing and Measuring Systems, Hamburg, Germany). Waist circumference is measured at the midpoint between the lower rib and iliac crest to the nearest 0.1 cm. The trained nurses who perform the measurements undergo quality control, conducted with healthy young adult volunteers [28]. This same measurement procedure is used to measure anthropometry of parents at regular intervals. The number of smokers in the household was enquired and from this smoking exposure was assessed. The years of schooling was also enquired and from this a proxy of parental socioeconomic status was created. A high educational status is defined as (≥ 12 years of schooling). All statistical analysis was conducted using SAS 9.4. Prospective association between early life factors and IMT during young adulthood were analyzed using multivariable linear regression models. IMT was adjusted for age and sex using the residual method. To evaluate whether sex modifies the association between early life factors and IMT, an interaction analysis was carried out and if a significant sex difference existed, analysis was carried out separately for men and women. Interaction analysis indicated sex interactions for maternal age at child birth and breastfeeding (Pinteraction = 0.03 to 0.09). Initial regression models (A) included IMT as the dependent continuous variable and individual inclusion of an early life predictor as the independent variable, adjusted for age at IMT measurement, sex and the physician measuring IMT. Next, multivariable adjusted models (B) were constructed considering covariates individually for potential confounding in the models in a hierarchical manner [31]. Covariates which substantially modified the predictor–outcome associations by (≥10%) or significantly predicted the outcome were included in the final multivariable adjusted models. These early life factors were considered as mutual potential covariates in this model (1) early life factors: birth weight (g) considered as both a continuous and categorical variable (i.e., 16kg), breastfeeding for >2 weeks (Yes/No and >16 weeks (Yes/No), first born status (Yes/No) and birth year regressed on age at IMT measurement as a continuous variable. (2) Socioeconomic factors: paternal school education ≥12 years (Yes/No), presence of an overweight parent BMI≥25 kg/m2, (Yes/No), smokers in the household (Yes/No). Sensitivity analyses were conducted in subsamples who had provided either information on participation in sport (Yes/No) (n = 123) or on estimated energy expenditure during participation in sports (n = 68) in early adulthood, so as to account for potential confounding arising from adult physical activity levels. Finally, four sets of conditional models were constructed adding adult waist circumference, adult BMI or adult systolic or diastolic blood pressure to the models, so as to investigate whether observed associations were partly attributable to these variables in adulthood. Results from regression analysis are presented as adjusted least-square means (95% confidence interval (CI) by tertiles of the respective predictor while P-value is obtained from models using the predictors as continuous and categorical variables. Significance was determined at a p-value of 0.05.

Based on the provided information, it is not clear what specific innovations are being discussed or how they relate to improving access to maternal health. The information provided seems to be focused on a study examining the associations between early life factors and adult carotid intimamedia thickness (IMT) in a healthy German population.

To improve access to maternal health, some potential innovations and recommendations could include:

1. Telemedicine: Implementing telemedicine platforms that allow pregnant women to remotely access healthcare professionals for prenatal check-ups, consultations, and monitoring.

2. Mobile clinics: Setting up mobile clinics in rural or underserved areas to provide prenatal care, screenings, and education to pregnant women who may have limited access to healthcare facilities.

3. Community health workers: Training and deploying community health workers who can provide basic prenatal care, education, and support to pregnant women in their communities.

4. Digital health tools: Developing and utilizing mobile apps or online platforms that provide information, resources, and support for pregnant women, including tracking tools for prenatal appointments, vaccinations, and health indicators.

5. Maternal health vouchers: Implementing voucher programs that provide pregnant women with financial assistance to access prenatal care, delivery services, and postnatal care.

6. Transportation support: Providing transportation assistance or subsidies for pregnant women who may face challenges in accessing healthcare facilities due to distance or lack of transportation options.

7. Maternity waiting homes: Establishing maternity waiting homes near healthcare facilities to accommodate pregnant women who live far away and need to stay closer to the facility during the final weeks of pregnancy.

8. Task-shifting: Training and empowering midwives and other healthcare professionals to provide a wider range of maternal health services, including prenatal care, delivery, and postnatal care.

9. Public awareness campaigns: Conducting public awareness campaigns to educate communities about the importance of maternal health, the available services, and how to access them.

10. Health financing reforms: Implementing health financing reforms that prioritize maternal health and ensure that pregnant women have access to affordable and quality care.

These are just a few potential innovations and recommendations that could be explored to improve access to maternal health. It is important to consider the specific context, resources, and needs of the population when implementing any innovation or recommendation.
AI Innovations Description
The description provided does not directly relate to improving access to maternal health. It appears to be a research study on the association between early life factors and carotid artery thickness in adulthood. To improve access to maternal health, here are some recommendations:

1. Increase availability of healthcare facilities: Ensure that there are enough healthcare facilities, including hospitals, clinics, and maternity centers, in both urban and rural areas. This will make it easier for pregnant women to access prenatal care and delivery services.

2. Improve transportation infrastructure: Develop and maintain transportation infrastructure, such as roads and bridges, to ensure that pregnant women can easily reach healthcare facilities. This is particularly important in remote or underserved areas.

3. Provide financial support: Implement policies that provide financial support to pregnant women, such as subsidies for prenatal care, delivery, and postnatal care. This will help reduce the financial burden of accessing maternal healthcare services.

4. Enhance community-based healthcare: Establish community-based healthcare programs that provide prenatal care, education, and support to pregnant women. This can include mobile clinics, community health workers, and educational campaigns to raise awareness about maternal health.

5. Strengthen healthcare workforce: Invest in training and recruiting healthcare professionals, including doctors, nurses, midwives, and other skilled birth attendants, to ensure that there are enough skilled providers to meet the needs of pregnant women.

6. Promote maternal health education: Implement comprehensive maternal health education programs that provide information on prenatal care, nutrition, breastfeeding, and postnatal care. This can help empower women to make informed decisions about their health and the health of their babies.

7. Utilize technology: Explore the use of technology, such as telemedicine and mobile health applications, to improve access to maternal healthcare services, especially in remote or underserved areas.

8. Address cultural and social barriers: Identify and address cultural and social barriers that may prevent women from accessing maternal healthcare, such as stigma, gender inequality, and traditional beliefs. This can be done through community engagement and awareness campaigns.

9. Collaborate with stakeholders: Foster partnerships and collaborations between government agencies, non-profit organizations, healthcare providers, and community leaders to work together in improving access to maternal health services.

10. Monitor and evaluate: Establish monitoring and evaluation systems to assess the effectiveness of interventions and identify areas for improvement. This will ensure that efforts to improve access to maternal health are evidence-based and sustainable.
AI Innovations Methodology
The provided text describes a study that examines the associations between early life factors and adult carotid intimamedia thickness (IMT), a marker of atherosclerosis, in a healthy German population. The study uses data from the Dortmund Nutritional and Anthropometric Longitudinally Designed (DONALD) Study, which is an ongoing cohort study that collects information on diet, growth, development, and metabolism from children to adulthood.

To improve access to maternal health, the following innovations could be considered:

1. Telemedicine: Implementing telemedicine platforms that allow pregnant women to remotely access healthcare services, including prenatal check-ups, consultations, and monitoring. This can be particularly beneficial for women in rural or remote areas who may have limited access to healthcare facilities.

2. Mobile health (mHealth) applications: Developing mobile applications that provide pregnant women with information, reminders, and tools for self-monitoring their health during pregnancy. These apps can also facilitate communication with healthcare providers and offer personalized recommendations based on individual needs.

3. Community-based interventions: Establishing community-based programs that provide education, support, and resources for pregnant women. These programs can include prenatal classes, breastfeeding support groups, and access to essential maternal health services within the community.

4. Task-shifting: Training and empowering non-medical healthcare workers, such as community health workers or midwives, to provide basic prenatal care and education. This can help alleviate the burden on healthcare professionals and increase access to maternal health services in underserved areas.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could include the following steps:

1. Define the target population: Identify the specific population or region where the recommendations will be implemented. Consider factors such as demographics, healthcare infrastructure, and existing maternal health indicators.

2. Collect baseline data: Gather data on the current state of maternal health in the target population, including indicators such as maternal mortality rates, prenatal care utilization, and access to essential services.

3. Model the interventions: Use mathematical modeling techniques to simulate the implementation of the recommended innovations. This may involve creating a simulation model that incorporates factors such as population size, healthcare resources, and the expected impact of each intervention.

4. Estimate the impact: Run the simulation model to estimate the potential impact of the recommended innovations on improving access to maternal health. This could include outcomes such as increased prenatal care utilization, reduced maternal mortality rates, and improved health outcomes for both mothers and infants.

5. Sensitivity analysis: Conduct sensitivity analysis to assess the robustness of the results and explore the potential impact of varying assumptions or parameters in the model.

6. Interpret and communicate the findings: Analyze the simulation results and interpret the findings in the context of the target population. Communicate the potential benefits and limitations of the recommended innovations to stakeholders, policymakers, and healthcare providers.

7. Implementation and evaluation: Based on the simulation findings, implement the recommended innovations in the target population. Continuously monitor and evaluate the impact of the interventions to inform further improvements and adjustments.

It is important to note that the methodology described above is a general framework and may need to be adapted based on the specific context and resources available for the simulation study.

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