Premium
Animal models of maternal high fat diet exposure and effects on metabolism in offspring: a meta‐regression analysis
Author(s) -
Ribaroff G. A.,
Wastnedge E.,
Drake A. J.,
Sharpe R. M.,
Chambers T. J. G.
Publication year - 2017
Publication title -
obesity reviews
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.845
H-Index - 162
eISSN - 1467-789X
pISSN - 1467-7881
DOI - 10.1111/obr.12524
Subject(s) - offspring , pregnancy , meta analysis , biology , endocrinology , medicine , weight gain , publication bias , weaning , physiology , obesity , body weight , genetics
Summary Animal models of maternal high fat diet (HFD) demonstrate perturbed offspring metabolism although the effects differ markedly between models. We assessed studies investigating metabolic parameters in the offspring of HFD fed mothers to identify factors explaining these inter‐study differences. A total of 171 papers were identified, which provided data from 6047 offspring. Data were extracted regarding body weight, adiposity, glucose homeostasis and lipidaemia. Information regarding the macronutrient content of diet, species, time point of exposure and gestational weight gain were collected and utilized in meta‐regression models to explore predictive factors. Publication bias was assessed using Egger's regression test. Maternal HFD exposure did not affect offspring birthweight but increased weaning weight, final bodyweight, adiposity, triglyceridaemia, cholesterolaemia and insulinaemia in both female and male offspring. Hyperglycaemia was found in female offspring only. Meta‐regression analysis identified lactational HFD exposure as a key moderator. The fat content of the diet did not correlate with any outcomes. There was evidence of significant publication bias for all outcomes except birthweight. Maternal HFD exposure was associated with perturbed metabolism in offspring but between studies was not accounted for by dietary constituents, species, strain or maternal gestational weight gain. Specific weaknesses in experimental design predispose many of the results to bias.