Skip to main content
Download PDF

Prevalences of cardiometabolic risk and lifestyle factors in young parents: evidence from a German birth cohort study

BMC Cardiovascular Disorders volume 22, Article number: 469 (2022) Cite this article

Abstract

Background

Studies show that parents significantly impact their children’s health through their cardiometabolic risk profile and health behavior. There is only little information about the prevalence of cardiometabolic risk factors and lifestyle factors among new parents yet. The aims of this study are therefore to evaluate the prevalences of cardiometabolic risk factors in parents of infants in Germany and to examine their lifestyle and health behavior.

Methods

In the KUNO-Kids health study, an ongoing birth cohort, parents (n = 930 mothers and 769 fathers) were asked about cardiometabolic risk factors (obesity/hypertension/type 2 diabetes mellitus) and lifestyle factors (dietary/sports/smoking habits/alcohol consumption) during the first year after the birth of their children via questionnaires. Chi-square as well as fisher exact tests were conducted to analyse associations between lifestyle factors and cardiometabolic risk factors.

Results

34.2% of mothers and 58.5% of fathers were overweight or obese. In 11.8% of the families, at least one parent suffered from hypertension, in 2.4% from type 2 diabetes mellitus. One year after delivery, 8.5% of mothers were smoking, 6.9% showed a risky alcohol consumption (> 10 g/d). 16.0% of fathers were smoking 4 weeks after childbirth, 10.7% showed risky alcohol consumption (> 20 g/d). 21.6% of mothers carried out sports activity for more than 2 h a week then. Parental hypertension was linked to a higher prevalence of risky alcohol consumption, obesity to a lower prevalence of daily fruits consumption.

Conclusions

Cardiometabolic risk factors were widespread among new parents with obesity and overweight having the highest prevalences. A considerable number of parents also practiced an unhealthy lifestyle showing that there is potential for improvement to promote the healthy development of their children.

Peer Review reports

Background

Cardiovascular disease and its underlying lifestyle and metabolic risk factors are responsible for about 31% of deaths worldwide [1].

Studies on cardiovascular risk factor burden usually focus on general or older populations and often exclude pregnant women when addressing younger populations. However, complications during pregnancy such as preeclampsia and gestational diabetes also predict cardiovascular morbidity and mortality [2, 3].

Pregnancy imposes some distinct physiologic changes upon the cardiovascular and metabolic systems that could make women vulnerable to hypertensive disorders of pregnancy and gestational diabetes, particularly when underlying pre-pregnant risk factors such as obesity, sedentary lifestyle with little physical activity and unhealthy nutrition, are present [4, 5].

Moreover, it is well known that the cardiometabolic risk is often transmitted into the next generation. It is not only clear that most if not all components of the metabolic syndrome aggregate within families, but maternal as well as paternal overweight and cardiovascular disease are also predictors of childhood adiposity [6,7,8]. The basis for some of these effects might be set at a very early point in time as the concepts of fetal and early life programming suggest that adverse conditions like hyperinsulinism in critical early periods of life (pre- and postnatal) could alter the metabolism of children having a lasting effect on their health and on the risk of obesity, diabetes, and cardiovascular diseases in later life [8, 9]. Although much of the agglomeration of cardiovascular risk factors within families has a genetic basis, environmental influences of a shared household contribute to a transmission of cardiometabolic risk from parents to their offspring as well [10].

Exemplarily, exposure to parental smoking does not only have a tremendous influence on the risk of lower respiratory infections in infants but is also associated with higher exercise systolic blood pressure and atherosclerotic vascular disease in the offspring [11,12,13]. Furthermore, children of current and former smokers are more likely to start smoking themselves [14]. Familial resemblance has also been observed for physical activity, dietary patterns and alcohol consumption [15,16,17].

Expecting and new parents might therefore be the right target for health prevention strategies aiming to prepare them for a healthy parenthood and child education with regard to healthy nutrition and lifestyle.

Indeed, while research shows that cardiometabolic risk factors and an unhealthy lifestyle are common among the general German population, there is only little information about the specific group of new parents among whom a considerable part showed a limited health literacy in previous studies [18,19,20,21,22,23,24].

The aims of this study are therefore to evaluate the prevalences of cardiometabolic risk factors like obesity, arterial hypertension and type 2 diabetes mellitus (T2DM) in parents of infants in Germany and to examine their lifestyle and health behavior (food habits, alcohol consumption, smoking habits and physical activity).

Methods

Data collection and measurements

This project is based on data from the KUNO-Kids health study, an ongoing birth cohort.

Since the start in 2015, all mothers planning to deliver their baby at the clinic St. Hedwig Regensburg and their partners have been invited to participate in the study. Exclusion criteria were mothers younger than 18 years of age or with insufficient German language skills limiting the understanding of the rationale of the study. Parents participated on a voluntary basis and provided written informed consent. The process was approved by the ethics board of the University of Regensburg in December 2014 (file number: 14–1010347).

Information was gathered through an interview with the mothers after they gave birth and follow-up-questionnaires mailed to the parents after 4 weeks, 6 months and hereafter on every birthday of the child [25]. For this specific project, parents having participated in the study for at least 1 year were included. Included parents are shown in Fig. 1: Participation throughout the course of the study.

Fig. 1
figure 1

Participation throughout the course of the study

Full size image

Parental heights and weights were collected through questionnaires (mothers before pregnancy and 1 year after child’s birth and fathers 4 weeks after child’s birth). Weight categories were defined according to WHO classifications (BMI < 18.5 ≙ underweight, BMI 18.5–25≙normal weight, BMI 25–30≙overweight, BMI ≥ 30≙obesity) [26]. One year after the child was born, information on parents suffering or ever having suffered from hypertension or T2DM (self-reported diagnosis) was gathered. Information on mothers having suffered from gestational diabetes mellitus (GDM) during the pregnancy with the study child was gathered in an interview shortly after birth.

Smoking habits were evaluated by asking whether parents had ever smoked more than 100 cigarettes in their life and whether they were currently (mothers 1 year after the child’s birth, fathers 4 weeks after the child’s birth) smoking. Participants indicating that they had never smoked more than 100 cigarettes in their life were defined as never-smokers. Participants who declared that they had smoked more than 100 cigarettes in their life but did not currently smoke were defined as ex-smokers and participants that answered that they currently smoked cigarettes were defined as smokers.

Quantities of recent alcohol consumption (amount of bottles (0.5 l) of light beer or beer, glasses of wine (0.25 l) or sparkling wine (0.1 l) and shots (0.02 l) consumed per week) were evaluated 1 year after the child’s birth for mothers and 4 weeks after the child’s birth for fathers. In previous studies, an alcohol consumption of more than 10–12 g/day for healthy women and 20–24 g/day for healthy men was described as risky alcohol consumption [27]. An alcohol consumption of more than 10 g/day for mothers and 20 g/day for fathers was therefore defined as risky alcohol consumption.

Maternal breastfeeding at the time of potential alcohol consumption and smoking was evaluated by asking whether their child was still fed breast milk.

Parental raw or cooked vegetables and fresh fruits consumption (never, once a month, several times a month, once a week, several times a week, almost daily or several times a day) as well as mothers engagement in sports (amount of hours per week) were evaluated 1 year after the child’s birth. A choosing of an “almost daily” or “several times a day” consumption of fresh fruits was counted as daily fruits consumption. A choosing of an “almost daily” or “several times a day” consumption of either raw vegetables and salads or cooked vegetables or a “several times a week” consumption of both raw vegetables and cooked vegetables was counted as daily vegetables consumption. Mothers’ ages were obtained through the St. Hedwig clinic network, fathers’ ages were collected in the 2-year follow-up questionnaire. Information on further socio-demographic characteristics of the study population (parental migration background, education and employment as well as maternal marital status) was collected through an interview shortly after birth and questionnaires 4 weeks and 1 year after birth.

Statistics

Data was analysed using “SPSS” (version 25). Parental body mass indexes (BMI) and prevalences for parental overweight and obesity were calculated. For continuative analysis, a weighting factor taking into account the higher percentage of parents having graduated from grammar school in our study compared to the general population was applied [28].

Lifetime prevalences for parental hypertension and T2DM as well as prevalences for maternal GDM were calculated. Parental smoking habits were examined by calculating prevalences of never-smokers, ex-smokers and current smokers. Parental consumption of pure alcohol per day was calculated using common alcohol percentages (2.5% for light beer, 5% for beer, 11% for wine and sparkling wine and 38% for shots). Prevalences of parental risky alcohol consumption as well as daily fruits and vegetables consumption were calculated. Prevalences of maternal engagement in sports (none, < 2 h/week or > 2 h/week) were evaluated. 95% confidence intervals were calculated by bootstrap resampling.

Chi-square as well as fisher exact tests were conducted in order to analyse associations between lifestyle factors and cardiometabolic risk factors.

Results

Study population

Two thousand five hundred nine mothers agreed to participate in the KUNO-Kids study and completed the basic assessment. One thousand nine hundred thirty-six families have reached the 1-year follow-up and for this analysis a total of 930 mothers and 769 fathers could be included. Data on all variables analysed in this project was available for 599 mothers and 614 fathers. In this research project, the average age of mothers 1 year after delivery was 33.6 (±4.1) years. More than 60% of the parents had obtained a degree from a grammar school. The vast majority of mothers and fathers were of German origin (also see Table 1: Socio-demographic characteristics of the study population). For sociodemographic characteristics of the drop-outs see: Additional file 1: Basic characteristics of participants dropped out before 1-year-questionnaire.

Table 1 Socio-demographic characteristics of the study population
Full size table

Evaluation of cardiometabolic risk factors in parents

In 17.8% (95%CI: 15.0–20.5%) of families, one parent was obese, in 4.0% (95%CI: 2.6–5.5%) of families, both parents suffered from obesity. 9.0% (95%CI: 7.2–10.8) of mothers had already been obese before pregnancy (also see Table 2: Parental distribution into BMI classifications).

Table 2 Parental distribution into BMI classifications
Full size table

4.7% (95%CI: 3.2–6.2%) of mothers and 7.4% (95%CI: 5.7–9.4%) of fathers had ever suffered from arterial hypertension. 2.2% (95%CI: 1.3–3.3%) of mothers and 0.1% (95%CI: 0.0–0.4%) of fathers had ever suffered from T2DM. 14.4% (95%CI: 12.0–16.8%) of mothers had suffered from GDM.

Evaluation of lifestyle factors

In 14.7% (95%CI: 11.9–17.6%) of families, one parent was smoking and in 4.9% (95%CI: 3.4–6.7%) of families, both parents were smokers. In 14.6% (95%CI: 12.0–17.4%) of families, one parent had been engaging in risky alcohol consumption, in 2.3% (95%CI: 1.2–3.6%) of families, both parents had done so.

In 29.7% (95%CI: 26.3–33.2%) of families, no parent consumed fruits on a daily basis, in 25.1% (95%CI: 21.7–28.3%) of families, both parents did so. No parental daily vegetable consumption was found in 39.7% (95%CI: 35.8–43.2%) of families whereas in 24.6% (95%CI: 21.3–27.8%) of families, both parents showed daily vegetable consumption (also see Table 3: Lifestyle factors among parents during their child’s first year, Additional file 2:obesity and lifestyle factors in families as well as Additional file 3: Maternal alcohol and smoking habits by breastfeeding status).

Table 3 Lifestyle factors among parents during their child’s first year
Full size table

31.5% (95%CI: 28.5–34.5%) of mothers did not engage in any sports. 21.6% (95%CI: 19.2–24.2%) of mothers did sports for more than 2 h per week.

Associations between lifestyle factors and cardiometabolic risk factors

In the following, only significant results are listed, for all analysed relations, see Tables 4 and 5: Cardiometabolic risk factors stratified for lifestyle variables for mothers/fathers. Parents suffering from arterial hypertension were significantly more likely to consume risky amounts of alcohol (mothers: 17.9% vs. 6.3%, p = 0.036; fathers: 25.5% vs. 8.6%, p = 0.001). Obesity was linked to a lower prevalence of daily fruits consumption (mothers: 50.7% vs. 65.4%; fathers: 24.4% vs. 33.4%). This association was only statistically significant for mothers though (p = 0.014). Obese mothers were significantly less likely to engage in sports for at least 2 h per week (13.7% vs. 24.9%, p = 0.034). Never-smokers among mothers were significantly less likely to suffer from GDM (11.0% vs. 18.2%, p = 0.012).

Table 4 Cardiometabolic risk factors stratified for lifestyle variables for mothers
Full size table
Table 5 Cardiometabolic risk factors stratified for lifestyle variables for fathers
Full size table

Discussion

We demonstrate that a considerable number of parents report cardiometabolic risk factors and practice an unhealthy lifestyle with overweight and obesity constituting the most frequent health issue.

The prevalences of overweight and obesity among the parents in our study were slightly lower compared to other studies among the German general population of the same age [22]. After the application of a weighting factor taking into account the higher percentage of parents having graduated from grammar school in our study compared to the general population though, with 38% of mothers and 62% of fathers suffering from overweight and obesity our results were very similar to results from the general population of the same age. This goes along with previous findings that obesity is inversely correlated with socio-economic status, especially in women [29]. In 22% of the families, at least one parent suffered from obesity (also see Additional file 2: obesity and lifestyle factors in families). Almost every tenth mother suffered from obesity even before the pregnancy.

Parental obesity increases the risk of obesity in their children through genetic, biological and environmental influences and heightens the risk for cardiovascular disease in their offspring [7, 30, 31]. Furthermore, parental weight change was shown to be associated with weight change in their offspring and to alter the risk of their children to develop overweight [32, 33]. Maternal obesity during pregnancy is associated with GDM, preeclampsia and congenital anomalies within the fetus [34].

Given the widespread of overweight and obesity among parents found in our study, focusing on young parents’ cardiovascular health and especially parental obesity could therefore be an important factor to improve society’s overall and future health by benefitting both children and parents themselves.

According to perinatal statistics, the prevalence of gestational diabetes mellitus in Germany in 2016 was 5.4% which is clearly lower than the prevalence of 14% of mothers found in our study [35]. Melchior et al. already found a gestational diabetes prevalence of 13% in their study in 2017 though and figured that gestational diabetes prevalences were underestimated in Germany since their findings correlated with international estimates [36]. Our results support their considerations.

Comparable to the general German population, a considerable percentage of parents also reported the cardiometabolic risk factors arterial hypertension and T2DM [18, 37, 38]. Slight prevalence differences could be explained by the fact that previous studies did not distinguish between diabetes mellitus type 1 and 2 while we specifically asked about T2DM. Furthermore, we only conducted a survey, the estimated number of unreported cases might be higher given the known large number of undetected cases [39].

It is especially important to monitor and control maternal hypertension at childbearing age since during a possible subsequent pregnancy, a poorly-controlled blood pressure during the first trimester in pre-pregnancy hypertensive women could harm both the mother and the fetus increasing the risk for organ damage, low birth weight and pre-eclampsia [40].

Keeping in mind that especially for mothers, pregnancy may trigger the development of cardiovascular disease, a bigger focus on cardiovascular health post-partum and during the child’s early life could help to decelerate the progression of existing cardiovascular morbidity and prevent the development of further disease.

Lifestyle factors among parents

With 9% of mothers and 16% of fathers currently smoking, the prevalences of current smokers among our parents were clearly lower than the prevalences found in previous studies among the general German population. This applies accordingly to the group of mothers in our study who were not breastfeeding anymore at this point of time (also see Additional file 3: Maternal alcohol and smoking habits by breastfeeding status) [23]. This suggests that smokers might have stopped doing so before or shortly after becoming a parent. Still, almost every fifth of our study children grew up in a household with at least one smoking parent (also see Additional file 2: obesity and lifestyle factors in families).

While the prevalences of risky alcohol consumption among the non-breastfeeding mothers and fathers in our study were somewhat similar to results from previous studies among the general German population, with 40% of mothers and 19% of fathers, the prevalence of never-drinkers among our parents was clearly higher [41]. Parents of an infant might have less time or possibilities to go out or meet with other adults only and therefore might have fewer occasions to drink alcohol. Similarly to previous findings, we found relations between arterial hypertension and risky alcohol consumption [42].

While daily fruits and vegetables consumption was more common among our parents than among the general population in previous studies, in almost 40% of families, no parent consumed fruits daily and in almost 30% of families, no parent consumed vegetables daily [19, 20]. Considering that the recommendation of the “Deutsche Gesellschaft für Ernährung” (dge) is not only to consume fruits and vegetables daily but to have five portions a day, there is still much need for improvement in order for the parents to be a good role model for their kids [43]. Furthermore, we found that obese parents were less likely to consume fruits on a daily basis, which goes along with previous studies [44].

Like in previous studies among the general German population, more than 30% of the mothers in our study did not engage in any sports [45]. This shows that there is still room for significant improvement also to help reduce the prevalence of obesity keeping in mind the relations found in our and previous studies [46]. According to WHO guidelines, adults aged 18 to 64 should do at least 150 minutes of moderate-intensity aerobic physical activity per week or an equivalent combination of moderate- and vigorous-intensity activity [47].

Keeping in mind the immense influence of parents on their children’s health, parent education programs may be employed (for example in birth preparation seminars or in the child’s early screening examinations) with a greater focus on the impact of parental obesity, cardiometabolic health and associated lifestyle factors on their offspring both pre- and postnatal to improve awareness of healthy parenting behaviours and activities, and promote healthy parent–child relationships.

Strength and limitations of the study

The large study population and the data from both mothers and fathers enabled us to provide information in a broader context than most other cohort studies in a specific population sample of parents of infants. Nevertheless, in some analyses with small prevalences, the number of total cases is still very small indicating a limitation of the study.

As it is common in longitudinal cohort studies, there was a significant drop-out of parents throughout the course of the study. With the response rate being about 50% among the families having reached the 1-year follow-up, attrition bias might occur [25]. Furthermore, the drop-out among participants with a migration background was larger than among the participants of German origin which might lead to additional bias and therefore indicates another limitation of the study.

All information used in this study is self-reported by the parents. It might be prone to information bias like recall-bias or social desirability bias, especially for the lifestyle-related questions. Furthermore, due to a data collection only 2 years after delivery and a significant drop-out until that point of time, fathers’ ages are only known for 63% of the fathers. These fathers were 3.3 years older than the corresponding mothers on average which goes along with German birth statistics so we assumed the ages of the remaining fathers to be accordingly [48]. Information on mothers’ medical records was collected through a paper questionnaire given to the mothers shortly after birth. Apparently, it did not reach all mothers or was not sent back properly by all mothers. This explains the smaller basic population for some questions. Prevalences of certain risk factors are reported for different query periods for mothers and fathers. For example, paternal alcohol consumption and smoking habits were evaluated 4 weeks after birth. With mothers still being in childbed at this point of time and the majority of them still breast-feeding we thought it to be more reasonable to gather information on maternal smoking habits and alcohol consumption only 1 year after delivery. The different query periods may possibly have an influence on the prevalence of the risk factors in question.

Conclusions

In summary, we found that comparable to the general population, a substantial number of young parents reported cardiometabolic risk factors, particularly overweight and obesity. A considerable number of parents also engaged in an unhealthy lifestyle which shows that there is still potential for improvement in order to improve society’s todays and future cardiometabolic health.

Availability of data and materials

The datasets generated and/or analysed during the current study are not publicly available as they are part of the KUNO-Kids health study, an ongoing birth cohort with a still growing dataset that includes many more variables than the ones analysed in the current study. However, the datasets are available from the corresponding author on reasonable request.

References

  1. Finger JD, Busch MA, Du Y, Heidemann C, Knopf H, Kuhnert H, et al. Time Trends in Cardiometabolic Risk Factors in Adults. Dtsch Arztebl Int. 2016;113:712–9. https://doi.org/10.3238/arztebl.2016.0712.

    Article  PubMed  Google Scholar 

  2. Jasper R, Skelding K. Cardiovascular disease risk unmasked by pregnancy complications. Eur J Intern Med. 2018;57:1–6. https://doi.org/10.1016/j.ejim.2018.07.020.

    Article  PubMed  Google Scholar 

  3. Brown HL, Smith GN. Pregnancy Complications, Cardiovascular Risk Factors, and Future Heart Disease. Obstet Gynecol Clin N Am. 2020;47:487–95. https://doi.org/10.1016/j.ogc.2020.04.009.

    Article  Google Scholar 

  4. Mirghani Dirar A, Doupis J. Gestational diabetes from A to Z. World J Diabetes. 2017;8:489–511. https://doi.org/10.4239/wjd.v8.i12.489.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Kintiraki E, Papakatsika S, Kotronis G, Goulis DG, Kotsis V. Pregnancy-Induced hypertension. Hormones (Athens). 2015;14:211–23. https://doi.org/10.14310/horm.2002.1582.

    Article  Google Scholar 

  6. Francesquet M, Silva PT, Schneiders LB, Silveira JFC, Soares SS, Tornquist D, et al. Youth overweight/obesity and its relationship with cardiovascular disease and parental risk factors. Arch. Endocrinol Metab. 2019;63:411–6. https://doi.org/10.20945/2359-3997000000156.

    Article  Google Scholar 

  7. Labayen I, Ruiz JR, Ortega FB, Loit H-M, Harro J, Veidebaum T, et al. Intergenerational cardiovascular disease risk factors involve both maternal and paternal BMI. Diabetes Care. 2010;33:894–900. https://doi.org/10.2337/dc09-1878.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Brandt S, Moß A, Koenig W, Rothenbacher D, Brenner H, Wabitsch M. Intrafamilial associations of cardiometabolic risk factors--results of the Ulm Birth Cohort Study. Atherosclerosis. 2015;240:174–83. https://doi.org/10.1016/j.atherosclerosis.2015.02.045.

    Article  CAS  PubMed  Google Scholar 

  9. Dörner G, Plagemann A. Perinatal hyperinsulinism as possible predisposing factor for diabetes mellitus, obesity and enhanced cardiovascular risk in later life. Horm Metab Res. 1994;26:213–21. https://doi.org/10.1055/s-2007-1001668.

    Article  PubMed  Google Scholar 

  10. Knuiman MW, Divitini ML, Welborn TA, Bartholomew HC. Familial correlations, cohabitation effects, and heritability for cardiovascular risk factors. Ann Epidemiol. 1996;6:188–94. https://doi.org/10.1016/1047-2797(96)00004-x.

    Article  CAS  PubMed  Google Scholar 

  11. Jones LL, Hashim A, McKeever T, Cook DG, Britton J, Leonardi-Bee J. Parental and household smoking and the increased risk of bronchitis, bronchiolitis and other lower respiratory infections in infancy: systematic review and meta-analysis. Respir Res. 2011;12:5. https://doi.org/10.1186/1465-9921-12-5.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Hacke C, Weisser B. Effects of parental smoking on exercise systolic blood pressure in adolescents. J Am Heart Assoc. 2015;4. https://doi.org/10.1161/JAHA.115.001936.

  13. West HW, Juonala M, Gall SL, Kähönen M, Laitinen T, Taittonen L, et al. Exposure to parental smoking in childhood is associated with increased risk of carotid atherosclerotic plaque in adulthood: the Cardiovascular Risk in Young Finns Study. Circulation. 2015;131:1239–46. https://doi.org/10.1161/CIRCULATIONAHA.114.013485.

    Article  CAS  PubMed  Google Scholar 

  14. Vuolo M, Staff J. Parent and child cigarette use: a longitudinal, multigenerational study. Pediatrics. 2013;132:e568–77. https://doi.org/10.1542/peds.2013-0067.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Moore LL, Lombardi DA, White MJ, Campbell JL, Oliveria SA, Ellison RC. Influence of parents’ physical activity levels on activity levels of young children. J Pediatr. 1991;118:215–9. https://doi.org/10.1016/s0022-3476(05)80485-8.

    Article  CAS  PubMed  Google Scholar 

  16. Hebestreit A, Intemann T, Siani A, de Henauw S, Eiben G, Kourides YA, et al. Dietary Patterns of European Children and Their Parents in Association with Family Food Environment: Results from the I. Family Study. Nutrients. 2017;9:126. https://doi.org/10.3390/nu9020126.

    Article  PubMed Central  Google Scholar 

  17. Rossow I, Keating P, Felix L, McCambridge J. Does parental drinking influence children's drinking? A systematic review of prospective cohort studies. Addiction. 2016;111:204–17. https://doi.org/10.1111/add.13097.

    Article  PubMed  Google Scholar 

  18. Heidemann C, Kuhnert R, Born S, Scheidt-Nave C. 12-Monats-Prävalenz des bekannten Diabetes mellitus in Deutschland. J Health Monitor. 2017;2:48–56. https://doi.org/10.17886/RKI-GBE-2017-008.

    Article  Google Scholar 

  19. Mensink GBM, Schienkiewitz A, Lange C. Gemüsekonsum bei Erwachsenen in Deutschland. J Health Monitor. 2017;2:52–8. https://doi.org/10.17886/RKI-GBE-2017-029.

    Article  Google Scholar 

  20. Mensink GBM, Schienkiewitz A, Lange C. Obstkonsum bei Erwachsenen in Deutschland. J Health Monitor. 2017;2:45–51. https://doi.org/10.17886/RKI-GBE-2017-028.

    Article  Google Scholar 

  21. Neuhauser H, Kuhnert R, Born S. 12-Monats-Prävalenz von Bluthochdruck in Deutschland. J Health Monitor. 2017;2:57–63. https://doi.org/10.17886/RKI-GBE-2017-007.

    Article  Google Scholar 

  22. Schienkiewitz A, Mensink GBM, Kuhnert R, Lange C. Übergewicht und Adipositas bei Erwachsenen in Deutschland. J Health Monitor. 2017;2:21–8. https://doi.org/10.17886/RKI-GBE-2017-025.

    Article  Google Scholar 

  23. Zeiher J, Kuntz B, Lange C. Rauchen bei Erwachsenen in Deutschland. J Health Monitor. 2017;2:59–65. https://doi.org/10.17886/RKI-GBE-2017-030.

    Article  Google Scholar 

  24. Brandstetter S, Atzendorf J, Seelbach-Göbel B, Melter M, Kabesch M, Apfelbacher C. Sociodemographic factors associated with health literacy in a large sample of mothers of newborn children: cross-sectional findings from the KUNO-Kids birth cohort study. Eur J Pediatr. 2020;179:165–9. https://doi.org/10.1007/s00431-019-03483-9.

    Article  PubMed  Google Scholar 

  25. Brandstetter S, Toncheva AA, Niggel J, Wolff C, Gran S, Seelbach-Göbel B, et al. KUNO-Kids birth cohort study: rationale, design, and cohort description. Mol Cell Pediatr. 2019;6:1. https://doi.org/10.1186/s40348-018-0088-z.

    Article  PubMed  PubMed Central  Google Scholar 

  26. World Health Organisation. Obesity: preventing and managing the global epidemic. Report of a WHO consultation. World Health Organ Tech Rep Ser. Geneva; 2000;894:1–253.

  27. Burger M, Brönstrup A, Pietrzik K. Derivation of tolerable upper alcohol intake levels in Germany: a systematic review of risks and benefits of moderate alcohol consumption. Prev Med. 2004;39:111–27. https://doi.org/10.1016/j.ypmed.2003.11.011.

    Article  CAS  PubMed  Google Scholar 

  28. Statistisches Bundesamt (Destatis). Bildungsstandard der Bevölkerung: Ergebnisse des Mikrozensus 2019. 2020. https://www.destatis.de/DE/Themen/Gesellschaft-Umwelt/Bildung-Forschung-Kultur/Bildungsstand/Publikationen/Downloads-Bildungsstand/bildungsstand-bevoelkerung-5210002197004.pdf;jsessionid=8F1D771BABAA14FB065EB82CBE3A6A6C.live732?__blob=publicationFile. Accessed 4 Nov 2022.

  29. Sobal J, Stunkard AJ. Socioeconomic status and obesity: a review of the literature. Psychol Bull. 1989;105:260–75. https://doi.org/10.1037/0033-2909.105.2.260.

    Article  CAS  PubMed  Google Scholar 

  30. Harrap SB, Stebbing M, Hopper JL, Hoang HN, Giles GG. Familial patterns of covariation for cardiovascular risk factors in adults: The Victorian Family Heart Study. Am J Epidemiol. 2000;152:704–15. https://doi.org/10.1093/aje/152.8.704.

    Article  CAS  PubMed  Google Scholar 

  31. Wang Y, Min J, Khuri J, Li M. A systematic examination of the association between parental and child obesity across countries. Adv Nutr. 2017;8:436–48. https://doi.org/10.3945/an.116.013235.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Wrotniak BH, Epstein LH, Paluch RA, Roemmich JN. Parent weight change as a predictor of child weight change in family-based behavioral obesity treatment. Arch Pediatr Adolesc Med. 2004;158:342–7. https://doi.org/10.1001/archpedi.158.4.342.

    Article  PubMed  Google Scholar 

  33. Fasting MH, Nilsen TIL, Holmen TL, Vik T. Changes in parental weight and smoking habits and offspring adiposity: data from the HUNT-study. Int J Pediatr Obes. 2011;6:e399–407. https://doi.org/10.3109/17477166.2010.518238.

    Article  PubMed  Google Scholar 

  34. Leddy MA, Power ML, Schulkin J. The impact of maternal obesity on maternal and fetal health. Rev Obstet Gynecol. 2008;1:170–8.

    PubMed  PubMed Central  Google Scholar 

  35. Schäfer-Graf UM, Gembruch U, Kainer F, Groten T, Hummel S, Hösli I, et al. Gestational Diabetes Mellitus (GDM) - Diagnosis, Treatment and Follow-Up. Guideline of the DDG and DGGG (S3 Level, AWMF Registry Number 057/008, February 2018). Geburtshilfe Frauenheilkd. 2018;78:1219–31. https://doi.org/10.1055/a-0659-2596.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Melchior H, Kurch-Bek D, Mund M. The Prevalence of Gestational Diabetes. Dtsch Arztebl Int. 2017;114:412–8. https://doi.org/10.3238/arztebl.2017.0412.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Neuhauser H, Thamm M, Ellert U. Blutdruck in Deutschland 2008–2011 : Ergebnisse der Studie zur Gesundheit Erwachsener in Deutschland (DEGS1). Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz. 2013;56:795–801. https://doi.org/10.1007/s00103-013-1669-6.

    Article  CAS  PubMed  Google Scholar 

  38. Heidemann C, Du Y, Schubert I, Rathmann W, Scheidt-Nave C. Prävalenz und zeitliche Entwicklung des bekannten Diabetes mellitus: Ergebnisse der Studie zur Gesundheit Erwachsener in Deutschland (DEGS1). Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz. 2013;56:668–77. https://doi.org/10.1007/s00103-012-1662-5.

    Article  CAS  PubMed  Google Scholar 

  39. Gossain VV, Aldasouqi S. The challenge of undiagnosed pre-diabetes, diabetes and associated cardiovascular disease. Int J Diabetes Mellitus. 2010;2:43–6. https://doi.org/10.1016/j.ijdm.2009.10.004.

    Article  Google Scholar 

  40. Lu Y, Chen R, Cai J, Huang Z, Yuan H. The management of hypertension in women planning for pregnancy. Br Med Bull. 2018;128:75–84. https://doi.org/10.1093/bmb/ldy035.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Lange C, Manz K, Kuntz B. Alkoholkonsum bei Erwachsenen in Deutschland: Riskante Trinkmengen. J Health Monitor. 2017;2:66–73. https://doi.org/10.17886/RKI-GBE-2017-031.

    Article  Google Scholar 

  42. Roerecke M, Tobe SW, Kaczorowski J, Bacon SL, Vafaei A, Hasan OSM, et al. Sex-Specific Associations Between Alcohol Consumption and Incidence of Hypertension: A Systematic Review and Meta-Analysis of Cohort Studies. J Am Heart Assoc. 2018;7. https://doi.org/10.1161/JAHA.117.008202.

  43. Deutsche Gesellschaft für Ernährung. Vollwertig essen und trinken nach den 10 Regeln der DGE. 2017. https://www.dge.de/ernaehrungspraxis/vollwertige-ernaehrung/10-regeln-der-dge/. Accessed 25 Sept 2020.

    Google Scholar 

  44. Lin B-H, Morrison RM. Higher Fruit Consumption Linked With Lower Body Mass Index. FoodReview. 2002;25:28–32. https://doi.org/10.22004/ag.econ.234628.

    Article  Google Scholar 

  45. Krug S, Jordan S, Mensink GBM, Müters S, Finger J, Lampert T. Körperliche Aktivität : Ergebnisse der Studie zur Gesundheit Erwachsener in Deutschland (DEGS1). Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz. 2013;56:765–71. https://doi.org/10.1007/s00103-012-1661-6.

    Article  CAS  PubMed  Google Scholar 

  46. Swift DL, McGee JE, Earnest CP, Carlisle E, Nygard M, Johannsen NM. The Effects of Exercise and Physical Activity on Weight Loss and Maintenance. Prog Cardiovasc Dis. 2018;61:206–13. https://doi.org/10.1016/j.pcad.2018.07.014.

    Article  PubMed  Google Scholar 

  47. World Health Organisation. Global Recommendations on Physical Activity for Health. Geneva 2010.

  48. Pötzsch O, Klüsener S, Dudel C. Wie hoch ist die Kinderzahl von Männern? WISTA - Wirtschaft und Statistik. 2020;5:59–77.

    Google Scholar 

Download references

Acknowledgements

We would like to thank all families who participate in the KUNO-kids birth cohort study as well as all medical students, nurses, midwives, physicians, and researchers who facilitated the recruitment of participants and data assessment.

Further, we thank all members of the KUNO-kids study group:

Petra Arndt (ZNL Transfercenter of Neuroscience and Learning, University of Ulm, Ulm, Germany), Mark Berneburg (Department of Dermatology, University Medical Centre Regensburg, Regensburg, Germany), Stephan Böse-O’Reilly (Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, Munich, Germany), Romuald Brunner (Clinic of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Bezirksklinikum Regensburg (medbo), Regensburg, Germany), Wolfgang Buchalla (Department of Conservative Dentistry and Periodontology, University Hospital Regensburg, University of Regensburg, Regensburg, Germany), André Franke (Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Germany), Sebastian Häusler (Clinic of Obstetrics and Gynecology St. Hedwig, University of Regensburg, Regensburg, Germany), Iris Heid (Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany), Caroline Herr (Bavarian Health and Food Safety Authority (LGL), Munich, Germany), Wolfgang Högler (Department of Pediatrics and Adolescent Medicine, Johannes Kepler University Linz, Linz, Austria), Sebastian Kerzel (Department of Pediatric Pneumology and Allergy, University Children’s Hospital Regensburg, St. Hedwig Campus, Regensburg, Germany), Michael Koller (Center for Clinical Studies, University Hospital Regensburg, Regensburg, Germany), Michael Leitzmann (Department of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany), David Rothfuß (City of Regensburg, Coordinating Center for Early Interventions, Regensburg, Germany), Wolfgang Rösch (Department of Pediatric Urology, University Medical Center, Regensburg, Germany), Bianca Schaub (Pediatric Allergology, Dept of Pediatrics, Dr. von Hauner Children’s Hospital, University Hospital, LMU Munich, Munich, Germany), Bernhard H.F. Weber (Institute of Human Genetics, University of Regensburg, Regensburg, Germany), Stephan Weidinger (Department of Dermatology, Venereology and Allergy, University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany) and Sven Wellmann (Children’s Hospital St. Hedwig, University of Regensburg, Regensburg, Germany).

Funding

Open Access funding enabled and organized by Projekt DEAL. The KUNO-kids health study was funded by research grants of the EU (HEALS: 603946); the German Federal Ministry for Education and Research (SYSINFLAME: 01ZX1306E); the University Children’s Hospital Regensburg (KUNO-Clinics); and the clinic St Hedwig (Hospital Barmherzige Brüder Regensburg). The funding bodies played no role in the design of the study and collection, analysis and interpretation of data and in writing the manuscript.

Author information

Author notes

  1. Jana Brunner and Sara Fill Malfertheiner contributed equally to this work.

Authors and Affiliations

  1. University Department of Obstetrics and Gynecology, Hospital St. Hedwig of the Order of St. John, University Medical Center Regensburg, Regensburg, Germany

    Jana Brunner, Sara Fill Malfertheiner & Birgit Seelbach-Göbel

  2. Member of the Research and Development Campus Regensburg (WECARE) at the Clinic St. Hedwig, Regensburg, Germany

    Sara Fill Malfertheiner, Susanne Brandstetter & Michael Kabesch

  3. University Children’s Hospital Regensburg (KUNO-Clinics), University of Regensburg, Clinic St. Hedwig, Regensburg, Germany

    Susanne Brandstetter, Michael Melter & Michael Kabesch

  4. Institute of Social Medicine and Health Systems Research (ISMHSR), Otto von Guericke University Magdeburg, Magdeburg, Germany

    Christian Apfelbacher

  5. Clinic of Internal Medicine II, University Hospital of Regensburg, Franz-Josef-StrauĂź-Allee 11, 93053, Regensburg, Germany

    Andrea Baessler

Authors
  1. Jana Brunner
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sara Fill Malfertheiner
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Susanne Brandstetter
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Birgit Seelbach-Göbel
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Christian Apfelbacher
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Michael Melter
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Michael Kabesch
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Andrea Baessler
    View author publications

    You can also search for this author in PubMed Google Scholar

Consortia

KUNO-Kids Study Group

  • Petra Arndt
  • , Mark Berneburg
  • , Stephan Böse-O’Reilly
  • , Romuald Brunner
  • , Wolfgang Buchalla
  • , AndrĂ© Franke
  • , Sebastian Häusler
  • , Iris Heid
  • , Caroline Herr
  • , Wolfgang Högler
  • , Sebastian Kerzel
  • , Michael Koller
  • , Michael Leitzmann
  • , David RothfuĂź
  • , Wolfgang Rösch
  • , Bianca Schaub
  • , Bernhard H. F. Weber
  • , Stephan Weidinger
  •  & Sven Wellmann

Contributions

JB contributed to data collection, interpreted the study findings, drafted the manuscript and critically evaluated the manuscript and approved the final manuscript as submitted. JB, SFM, AB contributed to the design of the study, helped interpret the study findings, critically evaluated the manuscript and approved the final manuscript as submitted. CA and SB critically evaluated the statistical data, the data interpretation and approved the final manuscript. MK, MM and BSG evaluated the manuscript and approved the final manuscript as submitted. The author(s) read and approved the final manuscript.

Corresponding author

Correspondence to Andrea Baessler.

Ethics declarations

Ethics approval and consent to participate

The study was approved by the ethics board of the University of Regensburg (file number: 14–101-0347). All methods were carried out in accordance with relevant guidelines and regulations (declaration of Helsinki). Written informed consent from the participants was obtained.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1.

Basic characteristics of participants dropped out before 1-year-questionnaire.

Additional file 2.

Obesity and lifestyle factors in families.

Additional file 3.

Maternal alcohol and smoking habits by breastfeeding status.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Brunner, J., Fill Malfertheiner, S., Brandstetter, S. et al. Prevalences of cardiometabolic risk and lifestyle factors in young parents: evidence from a German birth cohort study. BMC Cardiovasc Disord 22, 469 (2022). https://doi.org/10.1186/s12872-022-02915-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12872-022-02915-z

Keywords

BMC Cardiovascular Disorders

ISSN: 1471-2261

Contact us