Results from 46 studies synthesising maternal nutritional effects on coping styles in rodents.

dat.besson2016

Format

The data frame contains the following columns:

comp_IDcharactereffect-size unique identifier
study_IDcharacterstudy unique identifier
dam_IDcharacterdam unique identifier (group of dams subjected to the same treatment)
animal_IDcharacteroffspring unique identifier (group of offspring from the same dam group subjected to the same treatment)
Referencecharacterauthor’s names and date
speciescharacterspecies [rats or mice]
straincharacterstrain
manip_typecharactermaternal nutritional manipulation type [protein or calorie]
manip_directioncharacterdirection of maternal nutritional manipulation [- = restriction, + = overfeeding]
nom_manip_valcharacterdegree of maternal nutritional manipulation as described in the original publications [% = percentage of caloric or protein restriction, # = increase in caloric intake]
expcharacterpercentage of caloric or protein maternal restriction or increase in caloric intake of the experimental group
controlcharacterpercentage of caloric or protein maternal restriction or increase in caloric intake for the control group
manip_parametercharacterprotein content, percentage fat or intake
vitmin_eqlcharacterwere vitamins equalized across maternal diets? [yes or no]
adlib_concharacterwere maternal control groups fed ad libitum? [yes or no]
adlib_expcharacterwere maternal experimental groups fed ad libitum? [yes or no]
diet_concharactername of maternal control diet?
diet_expcharactername of maternal experimental diet?
dam_diet_start_dPCnumericstart of the dam diet [in days post-conception]
dam_diet_end_dPCnumericend of the dam diet [in days post-conception]
diet_labelcharacterperiod of maternal diet manipulation [pregestation = pre-gestation, pre = pregnancy, lact = lactation, or pre+lact = pregnancy and lactation]
age_matingnumericdam age at mating if known
n_con_damintegersample size of the control dam groups
n_exp_damintegersample size of the experimental dam groups
multi_use_concharacterwere control groups used multiple time? [yes or no]
dam_housingcharacterhow were dams housed? [pair, group, or single]
temperaturenumerictemperature during the experiment [°C]
photoperiodintegerphotoperiod during the experiment [number of hours of light]
litter_sizeintegersize of the litter [number of pups per dam]
litter_size_equalizedcharacterhas litter size been equalized? [yes or no]
crossfosteredcharacterhave pups been cross-fostered? [yes or no]
sexcharactersex of the offspring that were tested [m = male, f = female, both = mixed sex]
housingcharacteroffspring housing during the test period [dam, pair, single, or group]
bodymass_mean_contrnumericmean body mass of control offspring close to or during the testing period [g]
bodymass_SE_contrnumericS.E. for body mass of control offspring close to or during the testing period
bodymass_mean_expnumericmean body mass of experimental offspring close to or during the testing period [g]
bodymass_SE_expnumericS.E. for body mass of experimental offspring close to or during the testing period
bm_N_contrintegersample size for body mass of control offspring close to or during the testing period
bm_N_expintegersample size for body mass of experimental offspring close to or during the testing period
bm_dPPintegerage of offspring when body mass was measured [in days post-parturition]
offspring_dietcharacteroffspring diet after weaning [type of control diet]
offspring_con_adlibcharacterwere control offspring fed ad libitum after weaning? [yes or no]
offspring_diet_levelcharactername of offspring diet after weaning
offspring_diet_end_dPPintegerend of the offspring diet [in days post-parturition]
post_diet_adlibcharacterwere experimental offspring fed ad libitum after weaning? [yes or no]
response_age_dPPnumericoffspring age when behavioural testing started [in days post-parturition]
authors_behaviour_classificationcharacterauthor's classification of offspring behaviour [anxiety, exploration, or activity]
our_behaviour_classificationcharacterour classification of offspring behaviour [anxiety, exploration, or activity]
response_testcharactertype of test used [elevated T-maze (ETM), open field, etc.] to measure offspring behaviour
time_trialintegerduration of the testing [min]
measurecharactermeasures taken during testing [total distance moved, time spent in open arm, etc.]
unitcharacterunit of the behavioural measure taken [min, s, m, number (#), etc.]
high_bettercharacterfor activity and exploration, a higher number is assumed to be better (i.e., animals were more active), but the opposite was assumed for anxiety (i.e., they were more anxious) [yes or no]
night.daycharactertime of day when behaviours were measured [night or day]
comparisoncharacterfor a given control-treatment group comparison, animal group codes as used in the original article [e.g., LP, HP]. This field allows identification of exactly which data (i.e., comparison of which pairs of groups) were extracted from the original paper, and is not used in our analyses. For our analyses the groups were re-coded as control/experimental.
exp_meannumericmean of the offspring behaviour measured for the experimental group
exp_senumericS.E. of the offspring behaviour measured for the experimental group
exp_nintegersample size for the offspring experimental group
con_meannumericmean of offspring behaviour measured for the control group
con_senumericS.E. of the offspring behaviour measured for the control group
con_nintegersample size for the offspring control group
con_IDcharacteridentifier for shared control groups within experiment
percentagecharacteris the offspring behaviour measure a percentage? [yes or no]
Data_sourcecharacterfigure or table number in the original paper from which the data were extracted
measure_commentscharacterany comments on the offspring behaviour measures
SE_imputedcharacterwas S.E. imputed for the offspring behaviour measure? [yes or no]
Commentscharacterany comments on the data

Details

Data from experiments where dams were subject to caloric or protein restriction or were overfed around gestation were included. Offspring activity, exploration, or anxiety were measured outcomes variables from maternal experimental treatments. Multilevel meta-analysis and meta-regression models were used to analyze the meta-analytic data.

Source

Besson, A. A., Lagisz, M., Senior, A. M., Hector, K. L., & Nakagawa, S. (2016). Effect of maternal diet on offspring coping styles in rodents: A systematic review and meta-analysis. Biological Reviews, 91(4), 1065–1080. https://doi.org/10.1111/brv.12210

Author

Daniel Noble, daniel.noble@anu.edu.au

Concepts

ecology, evolution, standardized mean differences

Examples

### copy data into 'dat' and examine data
dat <- dat.besson2016
head(dat)
#>   comp_ID study_ID dam_ID animal_ID                   Reference species strain manip_type
#> 1 comp_01     s_01   D_01      A_01 Reyes-Castro et al. (2012a)    rats Wistar    protein
#> 2 comp_02     s_01   D_02      A_02 Reyes-Castro et al. (2012a)    rats Wistar    protein
#> 3 comp_03     s_01   D_03      A_03 Reyes-Castro et al. (2012a)    rats Wistar    protein
#> 4 comp_04     s_01   D_01      A_01 Reyes-Castro et al. (2012a)    rats Wistar    protein
#> 5 comp_05     s_01   D_02      A_02 Reyes-Castro et al. (2012a)    rats Wistar    protein
#> 6 comp_06     s_01   D_03      A_03 Reyes-Castro et al. (2012a)    rats Wistar    protein
#>   manip_direction nom_manip_val exp control manip_parameter vitmin_eql adlib_con adlib_exp
#> 1               -           50% 10%     20% protein content        yes       yes       yes
#> 2               -           50% 10%     20% protein content        yes       yes       yes
#> 3               -           50% 10%     20% protein content        yes       yes       yes
#> 4               -           50% 10%     20% protein content        yes       yes       yes
#> 5               -           50% 10%     20% protein content        yes       yes       yes
#> 6               -           50% 10%     20% protein content        yes       yes       yes
#>                diet_con                     diet_exp dam_diet_start_dPC dam_diet_end_dPC diet_label
#> 1  Zeiger_Rodent_RQ22-5 Zeiger_Rodent_RQ22-5_LP_isoc                  1               22        pre
#> 2  Zeiger_Rodent_RQ22-6 Zeiger_Rodent_RQ22-5_LP_isoc                 22               43       lact
#> 3  Zeiger_Rodent_RQ22-7 Zeiger_Rodent_RQ22-5_LP_isoc                  1               43   pre+lact
#> 4  Zeiger_Rodent_RQ22-8 Zeiger_Rodent_RQ22-5_LP_isoc                  1               22        pre
#> 5  Zeiger_Rodent_RQ22-9 Zeiger_Rodent_RQ22-5_LP_isoc                 22               43       lact
#> 6 Zeiger_Rodent_RQ22-10 Zeiger_Rodent_RQ22-5_LP_isoc                  1               43   pre+lact
#>   age_mating n_con_dam n_exp_dam multi_use_con dam_housing temperature photoperiod litter_size
#> 1        122        20        20           yes      single          22          12          10
#> 2        122        20        20           yes      single          22          12          10
#> 3        122        20        20           yes      single          22          12          10
#> 4        122        20        20           yes      single          22          12          10
#> 5        122        20        20           yes      single          22          12          10
#> 6        122        20        20           yes      single          22          12          10
#>   litter_size_equalized crossfostered sex housing bodymass_mean_contr bodymass_SE_contr
#> 1                   yes            no   f   group                 209                 4
#> 2                   yes            no   f   group                 209                 4
#> 3                   yes            no   f   group                 209                 4
#> 4                   yes            no   f   group                 209                 4
#> 5                   yes            no   f   group                 209                 4
#> 6                   yes            no   f   group                 209                 4
#>   bodymass_mean_exp bodymass_SE_exp bm_N_contr bm_N_exp bm_dPP     offspring_diet offspring_con_adlib
#> 1               200               7         10       10     90 20% casein control                 yes
#> 2               190               6         10       10     90 20% casein control                 yes
#> 3               199              10         10       10     90 20% casein control                 yes
#> 4               200               7         10       10     90 20% casein control                 yes
#> 5               190               6         10       10     90 20% casein control                 yes
#> 6               199              10         10       10     90 20% casein control                 yes
#>    offspring_diet_level offspring_diet_end_dPP post_diet_adlib response_age_dPP
#> 1  Zeiger_Rodent_RQ22-5                      1             yes               90
#> 2  Zeiger_Rodent_RQ22-6                     21             yes               90
#> 3  Zeiger_Rodent_RQ22-7                     21             yes               90
#> 4  Zeiger_Rodent_RQ22-8                      1             yes               90
#> 5  Zeiger_Rodent_RQ22-9                     21             yes               90
#> 6 Zeiger_Rodent_RQ22-10                     21             yes               90
#>   authors_behaviour_classification our_behaviour_classification response_test time_trial
#> 1                          ANXIETY                     ACTIVITY           EPM          5
#> 2                          ANXIETY                     ACTIVITY           EPM          5
#> 3                          ANXIETY                     ACTIVITY           EPM          5
#> 4                          ANXIETY                      ANXIETY           EPM          5
#> 5                          ANXIETY                      ANXIETY           EPM          5
#> 6                          ANXIETY                      ANXIETY           EPM          5
#>            measure unit high_better night.day comparison exp_mean exp_se exp_n con_mean con_se con_n
#> 1     T_dist_moved    m         yes     night      cc-rc    13.90   1.28     8    11.97   1.28     8
#> 2     T_dist_moved    m         yes     night      cc-cr    13.90   0.96     8    11.97   1.28     8
#> 3     T_dist_moved    m         yes     night      cc-rr    10.69   0.32     8    11.97   1.28     8
#> 4 Open_arm_entries    #         yes     night      cc-rc     3.59   0.70     8     5.00   0.89     8
#> 5 Open_arm_entries    #         yes     night      cc-cr     4.29   0.70     8     5.00   0.89     8
#> 6 Open_arm_entries    #         yes     night      cc-rr     3.20   0.48     8     5.00   0.89     8
#>   con_ID percentage Data_source measure_comments SE_imputed
#> 1 con_01         no      Fig. 1             <NA>         no
#> 2 con_01         no      Fig. 1             <NA>         no
#> 3 con_01         no      Fig. 1             <NA>         no
#> 4 con_02         no      Fig. 1             <NA>         no
#> 5 con_02         no      Fig. 1             <NA>         no
#> 6 con_02         no      Fig. 1             <NA>         no
#>                                                   Comments
#> 1 details of diet can be found in Zambrano et al. (2005). 
#> 2 details of diet can be found in Zambrano et al. (2005). 
#> 3 details of diet can be found in Zambrano et al. (2005). 
#> 4 details of diet can be found in Zambrano et al. (2005). 
#> 5 details of diet can be found in Zambrano et al. (2005). 
#> 6 details of diet can be found in Zambrano et al. (2005). 

# \dontrun{

### load metafor
library(metafor)

### compute SD from SE
dat$sd_c <- with(dat, con_se * sqrt(con_n))
dat$sd_e <- with(dat, exp_se * sqrt(exp_n))

### compute standardized mean differences and corresponding sampling variances
dat <- escalc(measure="SMD", m1i=exp_mean, m2i=con_mean, sd1i=sd_e, sd2i=sd_c,
              n1i=exp_n, n2i=con_n, data=dat, add.measure=TRUE)

### fit model
mod1 <- rma.mv(yi ~ 1, V = vi, random = list(~ 1 | study_ID, ~ 1 | comp_ID), data = dat)
#> Warning: Rows with NAs omitted from model fitting.
mod1
#> 
#> Multivariate Meta-Analysis Model (k = 389; method: REML)
#> 
#> Variance Components:
#> 
#>             estim    sqrt  nlvls  fixed    factor 
#> sigma^2.1  0.1179  0.3433     46     no  study_ID 
#> sigma^2.2  0.3698  0.6081    389     no   comp_ID 
#> 
#> Test for Heterogeneity:
#> Q(df = 388) = 1262.0967, p-val < .0001
#> 
#> Model Results:
#> 
#> estimate      se     zval    pval    ci.lb   ci.ub    
#>  -0.1067  0.0712  -1.4994  0.1338  -0.2462  0.0328    
#> 
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#> 

# }