The Association between High Fat Diet around Gestation and Metabolic Syndrome-related Phenotypes in Rats: A Systematic Review and Meta-Analysis

Abstract

Numerous rodent studies have evaluated the effects of a maternal high-fat diet (HFD) on later in life susceptibility to Metabolic Syndrome (MetS) with varying results. Our aim was to quantitatively synthesize the available data on effects of maternal HFD around gestation on offspring's body mass, body fat, plasma leptin, glucose, insulin, lipids and systolic blood pressure (SBP). Literature was screened and summary estimates of the effect of maternal HFD on outcomes were calculated by using fixed- or random-effects models. 362 effect sizes from 68 studies together with relevant moderators were collected. We found that maternal HFD is statistically associated with higher body fat, body weight, leptin, glucose, insulin and triglycerides levels, together with increased SBP in offspring later in life. Our analysis also revealed non-significant overall effect on offspring's HDL-cholesterol. A main source of variation among studies emerged from rat strain and lard-based diet type. Strain and sex -specific effects on particular data subsets were detected. Recommendations are suggested for future research in the field of developmental programming of the MetS. Despite significant heterogeneity, our meta-analysis confirms that maternal HFD had long-term metabolic effects in offspring.

Figure 1

Forest Plot for Body Fat, extended dataset. Summary estimates for standardized difference in means (D, effect); the corresponding 95% CI (lower and upper) and significance (p-value) were estimated by fixed and random effects analysis. The first author of the study and the year of publication are shown. In the graph, numbers indicate D values, filled squares stand for the effect of individual studies, and filled diamonds express combined fixed and random effects. NA: not available.

Figure 2

Forest Plot for Body Weight, extended dataset.

Figure 3

Forest Plot for Leptin, extended dataset.

Figure 4

Forest Plot for Glucose, extended dataset.

Figure 5

Forest Plot for Insulin, extended dataset.

Figure 6

Forest Plot for HDL-c, extended dataset.

Figure 7

Forest Plot for Triglycerides, extended dataset.

Figure 8

Forest Plot for Systolic Blood Pressure, extended dataset.

Figure 9

Subgroup analyses for extended dataset. Horizontal lines represent the 95% CIs for the data. The summarized effects (D) are considered statistically significant when their 95% CIs do not cross zero. We used a random-effect model (filled circles) whether heterogeneity was observed, while the fixed-effect model was applied in the absence of heterogeneity (filled squares). Included moderators for the extended data set are: strain (Sprague Dawley, Wistar), sex (male, female), offspring age at testing (young adult), maternal age (young adult), intervention timing [perinatal (gestation and lactation) vs. restricted to gestation period], maternal body weight (increased, not increased), birthweight (decreased, increased, not different), and main fat source (animal, vegetal, mixed; extended dataset). Subgroup analyses for HDL-c extended dataset is available in Supplementary Fig. S4. Subgroup analysis of subsets where heterogeneity was not significant was not performed (SBP subset). Abbreviations: n: number of data points, SD: Sprague Dawley, YA: Young Adult, GES: gestation period only, GES + LAC: gestation and suckling periods.

Figure 10

PRISMA flow chart summarizing study selection processes.