Background: The metabolic syndrome (MetS) represents a clustering of risk factors for cardiovascular diseases that includes abdominal obesity, hypertension, dyslipidemia, and insulin resistance. Objectives: The objective of this study was to reassess the parent-offspring association of MetS since the available findings are still controversial. Methods: The Cochrane Library, PubMed, Embase, and Web of Science databases were searched to identify relevant articles. All studies comparing MetS status between the offspring of parents with MetS and offspring of parents without MetS were included in the analysis. Results: A total of 9 studies met the inclusion criteria and they were analyzed. Offspring of at least 1 parent with MetS had a higher risk of MetS (OR 3.88, 95% CI 2.58–5.83, p < 0.001). Sons and daughters of fathers with MetS both had a higher risk of MetS (OR 2.31, 95% CI 1.70–3.12, p < 0.001, and OR 1.73, 95% CI 1.37–2.18, p < 0.001, respectively). Sons and daughters of mothers with MetS both had a higher risk of MetS (OR 1.95, 95% CI 1.37–2.76, p = 0.0002, and OR 1.91, 95% CI 1.54–2.35, p < 0.001, respectively). Conclusion: This meta-analysis showed that there is a higher risk of MetS in the offspring of parents with MetS. However, there was no differential association of MetS according to gender and/or age of the offspring.

The metabolic syndrome (MetS) represents a clustering of risk factors for cardiovascular diseases that includes abdominal obesity, hypertension, dyslipidemia, and insulin resistance [1]. It is usually diagnosed when at least 3 of the following conditions are present: hypertension, impaired fasting glucose (or impaired glucose tolerance or insulin resistance), central adiposity, systemic inflammation, decreased high-density lipoproteins, and elevated triglycerides [2].

Several definitions for MetS have been developed, which can make comparison between separate studies difficult [1]. Of the definitions of MetS, the most widely used are the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) and the International Diabetes Federation (IDF) [1]. However, a consensus between the American Heart Association/National Heart, Lung and Blood Institute (AHA/NHLBI), and IDF has recently elaborated the AHA/NHLBI definition of MetS. This definition does not include central obesity as a prerequisite [1].

It is important to note that the prevalence of MetS is increasing worldwide [3]. The available evidence indicates that 23% of the population has this syndrome in Western countries [3]. According to IDF criteria, 1 in 4 adults in the world has MetS [3]. In subjects with MetS, the risk of death, stroke, and heart attacks could be 2–3 times more compared to individuals without this syndrome [3].

The prevalence of MetS is increasing in children and young adults globally [3]. Family is one of the main factors for metabolic risk factors in children. In fact, Mamun et al. [4] showed that excess gestational weight gain does influence offspring obesity over the short and long term, and should therefore be avoided. A meta-analysis by Kawasaki et al. [5] also concluded that exposure to maternal hyperglycemia was associated with offspring obesity and abnormal glucose tolerance. Furthermore, familial factors have been considered as risk factors for MetS, including genetic and environmental factors shared among family members [3, 6, 7].

Several studies have been recently conducted on the association between parental MetS and offspring MetS [2, 8]. They have shown a parental-offspring association of MetS [2, 8]. Nevertheless, whether this association depends on the gender of the offspring is still conflicting. In fact, one cross-sectional study found a differential association of MetS according to sex of the offspring, while another cohort study did not [9, 10].

To further analyze the parental-offspring association of MetS, we performed a meta-analysis comparing the offspring of parents with MetS and those of parents without MetS. To the best of our knowledge, this is the first meta-analysis on this topic.

Study Selection and Data Extraction

The PubMed, Embase, Web of Science, and Cochrane library databases were searched for relevant papers. The last search was performed on March 14, 2019. To identify all the relevant studies, the search terms were “metabolic syndrome” and “offspring” and “parent” or “parents” or “parental.” Furthermore, reference lists of included studies were searched manually to see whether there are additional studies. The Meta-Analysis of Observational Studies in Epidemiology (MOOSE) guidelines were followed for observational studies [11]. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) were also followed [12] (online suppl. material; for all online suppl. material, see www.karger.com/doi/10.1159/000513370).

The eligibility criteria were as follows: (1) a study (cohort or cross-sectional study) where there is comparison of MetS status between offspring of parents with MetS and offspring of parents without MetS; (2) the study should be written in English; (3) the study should be published as a full text; (4) the study should have enough data of interest (data presented at least as odds ratios [OR] and confidence intervals [CIs]). The studies which did not fulfill the eligibility criteria were excluded.

To explicitly assess the effects of parental MetS on offspring, the included studies were divided into 6 subgroups: (a) parent-offspring association of MetS when at least 1 parent (1 or both) has MetS; (b) parent-offspring association of MetS when both parents have MetS; (c) father-son association of MetS; (d) father-daughter association of MetS; (e) mother-son association of MetS; (f) mother-daughter association of MetS.

Study Quality and Risk of Bias Assessment

Two authors (L.I. and A.M.) worked independently to search for and assess studies for their methodological quality. The Newcastle-Ottawa quality assessment scale (NOS) for cohort studies was used to assess the methodological quality of the included studies [13]. However, an adapted version of NOS was used to assess the methodological quality of cross-sectional studies [14]. The Newcastle-Ottawa scale assigns a maximum of 4 points for selection (5 points for the adapted version of NOS), 2 points for comparability, and 3 points for exposure or outcome [13, 14]. One or 2 points were awarded for each item present in the selection, comparability, and outcome categories. The highest methodological quality receives a maximum score of 9 stars for cohort studies and 10 stars for cross-sectional studies [15]. Scores ≥7 were considered to indicate high-quality studies, and of scores of 5–6 reflected moderate quality [13, 16]. Any disagreement in the study was resolved by consensus and, if necessary, a senior staff member was consulted.

Statistical Analysis

Pooled ORs with 95% CIs were calculated to assess the combined effect of extracted data (given as ORs and CIs) using StatsDirect version 3.2.8 statistical software. I2 and p values were calculated to assess the heterogeneity among studies (I2 >50% and p < 0.1 indicated substantial heterogeneity across studies). The ORs were pooled using only a random effects model to calculate a more conservative result. ORs <1 indicated that the offspring of parents with MetS had lower risk of MetS. ORs >1 indicated that the offspring of parents with MetS had a higher risk of MetS.

Sensitivity analyses were conducted in case there were no gender differences in offspring inheriting MetS from parents with MetS. They were therefore performed to assess whether the MetS status in offspring of parents with MetS is influenced by the age of the offspring. To assess this, the combined mean of the ages (CMA) of offspring was calculated in 2 groups of studies. The 2 groups consisted of studies with an individual study mean age of offspring <16 years, and those studies with an individual study mean age of offspring >18 years.

The Egger test for publication bias was not assessed due to the small number of studies in our meta-analysis. The Cochrane meta-analysis guidelines suggest the use of the Egger test for publication bias for analyses with more than 10 studies [17]. p < 0.05 indicated there was a difference in the outcomes between offspring of parents with MetS and offspring of parents without MetS.

A total of 528 papers were retrieved from the 4 databases. Of them, 92 were duplicates and 65 were reviews, which were consequently removed. Twenty-five potential studies were ultimately included for full-text view after reviewing the titles and abstracts. With further screening, a total of 9 studies met the inclusion criteria [9, 10, 18-24]. The flowchart of study selection is shown in Figure 1. The main characteristics of eligible studies are summarized in Table 1. The publication dates of all the included studies vary between 2006 and 2017.

Table 1.

Characteristics of the included studies

Characteristics of the included studies
Characteristics of the included studies
Fig. 1.

Flow chart of study selection.

Fig. 1.

Flow chart of study selection.

Close modal

Study Characteristics

In 5 studies, the parent-offspring association of MetS was analyzed when at least 1 parent had MetS [18-20, 22, 24]. In 4 studies, this association was analyzed when both parents had MetS [19, 20, 22, 24]. In 4 studies, the father-daughter association of MetS was assessed [9, 19, 21, 23]. In 5 studies, the father-son association of MetS was also analyzed [9, 10, 19, 21, 23]. In 5 studies, the mother-son association for MetS was analyzed [9, 10, 19, 21, 23]. The mother-daughter association of MetS was also assessed in the same studies [9, 10, 19, 21, 23]. In 2 of the included studies, ORs with adjusted models were preferred [23, 24]. In Lee et al. [20] ORs with a multivariate-adjusted model were chosen.

In 4 studies, the mean age of the offspring was <16 years [18, 19, 22, 24]. However, in 4 other studies the mean age of the offspring was more than 18 years [9, 20, 21, 23]. In 1 study, the mean of age of some of the offspring was more than 18 years, while it was <16 years in the remaining offspring [10]. The CMA of offspring was 14.06 years in studies with a mean age of offspring <16 years [10, 18, 19, 22, 24]. The CMA was 34.76 years in studies with a mean age of offspring >18 years [9, 10, 20, 21, 23].

In 3 studies, data on the father-son association for MetS were chosen for sensitivity analyses [9, 10, 21]. Data on the MetS association between both parents and their offspring were chosen in another 2 studies for sensitivity analyses [19, 24]. In Lee et al. [20] data on at least 1 parent-offspring association of MetS was considered for sensitivity analyses. In Khan et al. [23] data on the mother-daughter association of MetS were also selected for sensitivity analyses.

Patient Characteristics

Baseline characteristics such as gender, age, and level of education were comparable between the offspring of parents with MetS and offspring of parents without MetS. There were no significant differences.

Publication Bias

The risk of bias assessment for each study is summarized in Table 2. All included studies were considered to be of high quality.

Table 2.

Newcastle-Ottawa quality assessment scale

Newcastle-Ottawa quality assessment scale
Newcastle-Ottawa quality assessment scale

Outcomes

Offspring of at least 1 parent with MetS had a higher risk of MetS syndrome than offspring of parents without MetS (OR 3.88, 95% CI 2.58–5.83, p < 0.001). The heterogeneity was not high (I2 = 26.2%, p = 0.24; Fig. 2).

Fig. 2.

Summary meta-analysis of parent-offspring association of MetS (at least 1 parent had MetS).

Fig. 2.

Summary meta-analysis of parent-offspring association of MetS (at least 1 parent had MetS).

Close modal

Offspring of both parents with MetS had a higher risk of MetS when compared with the offspring of parents without MetS (OR 5.06, 95% CI 2.33–11, p < 0.001). There was a substantial heterogeneity (I2 = 62.5%, p = 0.05; Fig. 3).

Fig. 3.

Summary meta-analysis of parent-offspring association of MetS (both parents had MetS).

Fig. 3.

Summary meta-analysis of parent-offspring association of MetS (both parents had MetS).

Close modal

Compared with sons of fathers without MetS, sons of fathers with MetS had a higher risk of MetS (OR 2.31, 95% CI 1.70–3.12, p < 0.001). The heterogeneity was not high (I2 = 16%, p = 0.31; Fig. 4).

Fig. 4.

Summary meta-analysis of father-son and/or father-daughter association of MetS.

Fig. 4.

Summary meta-analysis of father-son and/or father-daughter association of MetS.

Close modal

Daughters of fathers with MetS had a higher risk of MetS syndrome when compared with daughters of fathers without MetS (OR 1.73, 95% CI 1.37–2.18, p < 0.001). There was no substantial heterogeneity (I2 = 0%, p = 0.62; Fig. 4).

Sons of mothers with MetS had a higher risk of MetS than sons of mothers without MetS (OR 1.95, 95% CI 1.37–2.76, p = 0.0002). The heterogeneity was not high (I2 = 43.4%, p = 0.13; Fig. 5).

Fig. 5.

Summary meta-analysis of mother-son and/or mother-daughter association of MetS.

Fig. 5.

Summary meta-analysis of mother-son and/or mother-daughter association of MetS.

Close modal

Daughters of mothers with MetS had a higher risk of MetS when compared with daughters of mothers without MetS (OR 1.91, 95% CI 1.54–2.35, p < 0.001). There was no substantial heterogeneity (I2 = 0%, p = 0.78; Fig. 5).

Sensitivity analyses showed that the offspring of parents with MetS with a CMA of 14.06 years and those with a CMA of 34.76 years both had higher risk of MetS (OR 4.35, 95% CI 2.82–6.69, p < 0.001, and OR 2.29, 95% CI 1.9–2.77, p < 0.001, respectively). There was no substantial heterogeneity (offspring with a CMA of 14.06 years, p = 0.28; offspring with a CMA of 34.76 years, p = 0.47; Fig. 6, 7).

Fig. 6.

Summary meta-analysis for MetS status in offspring of parents with MetS when offspring CMA is 14.06 years.

Fig. 6.

Summary meta-analysis for MetS status in offspring of parents with MetS when offspring CMA is 14.06 years.

Close modal
Fig. 7.

Summary meta-analysis for MetS status in offspring of parents with MetS when offspring CMA is 34.76 years.

Fig. 7.

Summary meta-analysis for MetS status in offspring of parents with MetS when offspring CMA is 34.76 years.

Close modal

The results of this meta-analysis show that offspring of parents with MetS syndrome have a higher risk of MetS (Fig. 2, 3). They also show that MetS in parents is associated with MetS in offspring, irrespective of the gender and/or age of the offspring (Fig. 4-7).

Many studies have been conducted on the parent-offspring association of MetS [9, 10, 19, 21, 23, 25]. They have shown an association of MetS between parents and offspring [9, 18, 22, 26]. However, it remains controversial whether there is a differential association of MetS according to gender or age of the offspring [9, 10, 21, 23]. In fact, Sabo et al. [21] concluded that MetS in parents is significantly associated with MetS in adult male offspring. Another study by Khan et al. [23] demonstrated that a mother’s MetS was strongly related with her daughter’s MetS, but the association was inconsistent with her son’s MetS. The same authors did not find any association between a father’s MetS and his offspring’s MetS [23]. Lee et al. [10] found that there were differential associations of MetS according to offspring gender and age group and the parent’s gender. In fact, the associations of MetS were significantly stronger in young adults versus adolescents and in male offspring versus female offspring [10]. However, this meta-analysis showed that there is an association of MetS between parents and offspring, irrespective of gender and/or age of the offspring (Fig. 4-7).

A biased design and/or smaller sample size in Sabo et al. [21], Khan et al. [23], and/or Lee et al. [10] might explain why there was a differential association of MetS status in the offspring according to sex and/or age. This is supported in part by a study by Klijs et al. [9] with a sufficiently larger sample size. In this study, the authors concluded that a high risk of MetS is transmitted from fathers and mothers to sons and daughters, irrespective of the gender of the offspring. They also suggested that this transmission is irrespective of the socioeconomic position and health behaviors of the offspring. Furthermore, an accumulating body of evidence suggests that maternal obesity and excessive weight gain during pregnancy is associated with offspring obesity over the short and long term [4, 27]. As obesity is at the core of MetS [28], this may also explain why MetS in parents is also associated with offspring MetS over the short and long term. However, this needs further verification.

There are several hypothesized mechanisms that explain the pathophysiology of MetS [29, 30]. The most widely accepted of these is insulin resistance with fatty acid flux [30]. Other important mechanisms including low-grade chronic inflammation and oxidative stress have also been mentioned [30]. The strong parent-offspring association of MetS may be due to hereditary or environmental factors. In fact, it is widely recognized that genetic and environmental factors both contribute to the development of MetS [22, 31-33]. Twin and family studies have revealed substantial familial aggregation of MetS risk factors [34]. Bellia et al. [26] showed high prevalence rates for the MetS and its related traits in an isolated and small Caucasian population. Obesity, at the core of MetS, is itself highly heritable through shared genetic and environmental factors [34]. If a parent is obese, his or her child is twice as likely to be obese [34]. Conversely, more than half of children with obesity have at least 1 parent with obesity [34].

In animal models, Li et al. [35] demonstrated that paternal hyperglycemia induces transgenerational inheritance of susceptibility to hepatic steatosis in rats involving altered methylation on the Pparα promoter. The same authors concluded that their findings might have implications for the understanding of father-offspring interactions with the potential to account for MetS. In addition, it has been shown that poor maternal and paternal periconceptional nutrition can increase the risk of MetS in offspring through epigenetic imprinting [2].

Patients with MetS may have an increased risk of disease, approximately 2-fold for cardiovascular disease and 5-fold or more for type 2 diabetes mellitus [28]. In addition, they are prone to some comorbidities, including non-alcoholic fatty liver disease, polycystic ovary syndrome, obstructive sleep apnea, and mental health disorders [34]. Therefore, treatments and/or lifestyle changes could be of great importance to reverse or delay MetS sequelae.

This study presents some limitations. First, there was a lack of enough studies. Second, most of those included were cross-sectional studies. Third, although most of the studies included used IDF or NCEP-ATP III criteria to define MetS, there are still variations in defining MetS, especially in young adolescents [34]. Fourth, whether parents and offspring lived under the same roof and were on the same diet is unclear. Lastly, there was an absence of studies in languages other than English, as only English published articles were considered. Therefore, further well-designed studies in humans and/or animal models should be conducted to verify these findings.

This meta-analysis showed that there is a higher risk of MetS in the offspring of parents with MetS. However, gender and/or age differences were not found to be associated with offspring inheriting MetS from their parents. Further studies are still needed to verify these findings.

We thank John Belly for his advice.

This report is exempt from Ethical Committee approval since it is based on previously conducted studies and does not involve any new studies of human or animal subjects performed by any of the authors.

All authors declare that they have no conflicts of interest.

The study was supported by Natural Science Foundation of China grants (81871222 and 81570763), and the Fundamental Science and Advanced Technology Research of Chongqing (major project, CSTC2015jcyjB0146 to X.X.).

L.I. contributed to the study design, researched the data, contributed to the discussion, and wrote and edited the manuscript. A.M. extracted data and participated in the statistical analyses. Y.Z., Ju.L., Ji.L., L.N., and S.D. contributed to the discussion and reviewed the manuscript. X.X. is guarantor of this work and has full access to all the data in the study. He takes responsibility for the integrity of the data and the accuracy of the data analysis.

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