Pregnant cow nutrition and its effects on foetal weight a ... · Then, cow nutrition is an important strategy to improve efficiency in produc-tion systems. Considering the variability

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Animal Research Paper

Cite this article: Zago D, Canozzi M E A,Barcellos J O J (2019). Pregnant cow nutritionand its effects on foetal weight – a meta-analysis. The Journal of Agricultural Science1–13. https://doi.org/10.1017/S0021859619000315

Received: 5 December 2018Revised: 5 March 2019Accepted: 3 April 2019

Key words:Beef cattle; birth weight; cow–calf herd; foetalprogramming; foetal weight

Author for correspondence:J. O. J. Barcellos,E-mail: [email protected]

© Cambridge University Press 2019

Pregnant cow nutrition and its effects on foetalweight – a meta-analysis

D. Zago1, M. E. A. Canozzi2 and J. O. J. Barcellos1

1Department of Animal Science, Federal University of Rio Grande do Sul. Av. Bento Gonçalves n. 7712, 91540-000,Porto Alegre, RS, Brazil and 2Instituto Nacional de Investigación Agropecuaria (INIA), Programa Producción deCarne y Lana, Estación Experimental INIA La Estanzuela, Ruta 50, km 11, 39173, Colonia, Uruguay

Abstract

The prenatal development of cattle has influence on productive performance throughout post-natal life. The number of muscle and fat cells that the animal will have throughout its life isdetermined in the foetal stage and is influenced by nutrition of the pregnant cow. A systematicreview and meta-analysis was performed to evaluate the effect of different energy levels (totaldigestible nutrient, TDN) and crude protein (CP) supplied to pregnant cows on foetal weightat 4 (FW4) and 8 months (FW8) and calf birth weight (CBW). Four studies and six trialsinvolving 170 animals were assessed for FW4; four studies, four trials and 156 animals forFW8 and 48 studies, 125 trials and 9053 animals for CBW. High heterogeneity across studieswas presented in FW4 (I2 = 94.4%), FW8 (I2 = 91.08%) and CBW (I2 = 96.9%). Dietary TDNand CP levels did not influence FW4. The FW8 was reduced by 2.24 kg when cows were fed100% of their CP and TDN requirements (I2 = 0%), relative to those fed 70% of their require-ments during the first and second trimesters. The CBW was reduced by 0.45 kg (I2 = 96.9%)when cows were fed 130% of their CP requirements relative to other dietary CP levels. Whencows were fed 140% of their TDN requirements, CBW decreased by 2.71 kg (I2 = 98.3%) rela-tive to other TDN levels. Dietary energy or CP levels fed above the requirements to pregnantcows restrict foetal development and CBW.

Introduction

Foetal growth restriction has been reported as a problem in ruminant production due to thelimitations it causes in postnatal productivity (Du et al., 2010a). Prenatal development haslong-term effects on the growth and physiological functions of animals and foetal program-ming has been shown to influence new-borns’ survival and their subsequent productivityand meat quality (Rehfeldt et al., 2011).

At the beginning of gestation, protein restriction changes placental development, whichmay reduce foetal weight (Perry et al., 1999). Cow malnutrition during the first two trimestersof gestation reduces the number of muscle fibres, while in the third trimester it results in lowcalf birth and postnatal body weights (Greenwood et al., 2000).

It was demonstrated that bovine foetuses that experience nutritional restriction at somestage of gestation show compensatory gain, larger muscle fibre diameter and greater adiposity(Gonzalez et al., 2013; Gutiérrez et al., 2014). On the other hand, nutrient intake by pregnantcows above their requirements can also be detrimental to foetal development (Du et al.,2010a). The main effects of cow over-nutrition on the foetus are metabolic disorders, suchas insulin resistance (Radunz et al., 2012), over-expression of genes responsible for the forma-tion of adipocytes in the foetus and down-regulation of myogenesis (Tong et al., 2009), result-ing in reduced calf birth weight (CBW). Therefore, conflicting results on the influence of cownutrition on foetal development have been reported.

The efficiency of cow–calf herds is measured by the number and weight of calves produced(Dickerson, 1970). Then, cow nutrition is an important strategy to improve efficiency in produc-tion systems. Considering the variability in results previously reported on foetal programming inbeef cattle, the aim of the current study was to evaluate data published in the literature on effectsof dietary energy and crude protein (CP) fed to pregnant cows on foetal weight and CBW.

Method and materials

Research question and protocol

The current study aims to identify the effects of different dietary total digestible nutrients(TDN) and CP levels fed to pregnant beef cows on foetal weight at two gestation stages andbirth weight. The literature search strategy was defined based on the main concepts interms of PICO: population, intervention, comparator and outcome (Table 1). The populationstudied was pregnant cows and heifers. The interventions of interest were dietary energy and

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protein levels fed to pregnant cows and heifers. Similar groups ofanimals subjected to the same treatment with or without interven-tion were considered as comparative groups. The outcomes ofinterest were foetal weight at 4 (FW4) and 8 months (FW8) ofgestation and CBW.

To be considered relevant, the studies had to include at leastone of the outcomes of interest. Therefore, studies on animaldevelopment related to female reproductive function were notincluded. A search protocol was developed and each screeningtool was adapted from forms applied in earlier studies (Mederoset al., 2012; Canozzi et al., 2017). The protocol was tested beforebeing implemented.

Search methods for the identification of studies

A list of search terms and final algorithms was summarized bypopulation, intervention and outcome components: (‘cow calf’ or‘beef cattle’ or ‘beef heifer’ or ‘beef dams’ or ‘cow calf herd’or cow*) AND (nutrition or energy or supplemen* or proteinor feed* or aliment*) AND (‘foetal programming’ or ‘foetalgrowth’ or ‘birth weight’ or ‘compensatory growth’ or ‘weaningweight’ or ‘quality of muscle fibre’ or adipogenesis or myogen-esis). This search strategy also retrieved relevant publications oncarcase evaluation. However, the word ‘carcass’ was not includedin order to avoid non-relevant citations.

The search was carried out in May 2015 and updatedin October 2016 using two electronic databases, Scopus(Elsevier, 1960–2016) and Web of Science (Clarivate Analytics,1945–2016). The search was validated by manually searchingthe reference lists of two literature reviews on foetal programmingin ruminants (Du et al., 2013; Funston and Summers, 2013). Allreferences were exported into software EndNote Web® (ThomsonReuters, New York, USA) for organization and removal of dupli-cate references.

Study selection criteria and relevance screening

Four reviewers were trained for the relevance screening stepsusing 30 abstracts. Potentially relevant studies were identified atthis stage. The abstracts were assessed independently by tworeviewers by reading the title, abstract text and keywords. No lan-guage or year of publication restrictions were applied.

When the response of all reviewers was ‘no’ to one or morequestions, the reference was deleted. Any conflicts were solvedby agreement; if no agreement was reached, another reviewerwas consulted. Randomized and non-randomized studies wereincluded. Microsoft Excel® software was used during all relevantscreening stages.

Methodological assessment and data extraction process

The data extraction form was developed based on previous mod-els. Manuscripts reporting more than one trial were duplicatedand the data extracted as separate studies to obtain as much detailas possible. Information extracted from each study was dividedinto general information (study population, intervention, para-meters evaluated and outcome data) and manuscript-relatedinformation (authors, publication year and original language).

Considerations for data collection and manipulation

For each outcome, a database including the mean, the standarderror of the mean or other available dispersion measure, the prob-ability value and the number of animals evaluated in each group(control and treatment) was built.

In order to compare dietary nutrient supply, the levels (kg) ofTDN and CP fed to the cows were separately calculated as a per-centage (%) of their requirements published in the NRC (1996).When the studies did not report TDN and CP dietary levels,these were calculated based on the amount of each ingredientthat composed the diets, multiplied by their TDN and CP content(%) (NRC, 1996). For each comparison, differences in both TDNand CP levels between the treatment and control groups were cal-culated. The data were organized so that the control group alwaysreceived nutrient supply equal to the demands and the treatmentgroup levels above or below.

When studies reported the probability value, the standarddeviation was estimated using the t-statistic, assuming that thedata presented a normal distribution, according to the followingequation (Ceballos et al., 2009; Mederos et al., 2012):

Sp = (x2 − x1)t(adfE) ��(1/n2) + (1/n1)

√

where x2− x1 represents the difference between the means, t(αdfΕ) is the percentile of the reference distribution and n isthe sample size of each group.

Quality assessment

The Cochrane Collaboration Risk Bias Tool (Higgins and Green,2011) assessed the risk of publication bias in individual studiesincluded in this meta-analysis (MA). However, interpretation ofthe risk of bias due to blind use of the outcome assessors was con-sidered low for all studies, as the outcomes evaluated were mea-sured using a scale or other objective measurement equipment.

Meta-analysis

Studies included in this MA reported sufficient quantitative datato estimate the mean difference (MD) between the control and thetreatment groups and 95% confidence interval (95% CI). Foetalweight values referred to the gestation period when foetuses wereweighed in each study, 4 and 8 months of gestation, and theincluded birth weight values were obtained when calves wereweighed up to 24 h after calving.

Because the studies had different experimental designs,between-study heterogeneity was assumed and estimated usingthe DerSimonian and Laird method (DerSimonian and Laird,1986). All statistical analyses were performed using softwareStata V 14.0 (StataCorp., Texas, USA).

Table 1. Search terms for population, intervention and outcome used in thesystematic review on the nutrition of the pregnant cow and its effects onfoetal development

Acronym Search string

Population ‘cow calf’ or ‘beef cattle’ or ‘beef heifer’ or ‘beef dams’or ‘cow-calf herd’ or cow*

Intervention nutrition or energy or supplemen* or protein or feed* oraliment*

Outcome ‘foetal programming’ or ‘foetal growth’ or ‘birth weight’or ‘compensatory growth’ or ‘weaning weight’ or‘quality of muscle fibre’ or adipogenesis or myogenesis

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Each outcome was evaluated separately as a group, and apooled effect on MD and 95% CI (forest plot) was generated.Cochran’s Q test (χ2 test of heterogeneity) and I2 (percentageof total variation across studies due to heterogeneity rather thanchance) were calculated based on dietary TDN and CP levelsand on the outcome of interest. The magnitude of I2 was inter-preted in the order of 25, 50, and 75%, and considered as low,moderate or high heterogeneity, respectively (Higgins et al., 2003).

Publication bias

Publication bias was evaluated graphically (funnel plot) and stat-istically (Begg’s correlation and Egger’s linear regression tests) foreach outcome of interest. If there was any trend in publicationbias (P < 0.10), the ‘trim and fill’ method was applied to estimatethe extent of bias (Duval and Tweedie, 2000). This method indi-cates the number of studies that should be included in the analysisto achieve symmetry in the weight distribution graph.

Meta-regression

Univariate MAwas performed to explore the sources of data hetero-geneity, applying the method-of-moments approach (Borensteinet al., 2009). The following variables were explored: randomization(yes or no); cluster control (not applicable, systematic, convenienceor deliberate, randomized, not reported); confounders identified andcontrolled (no, yes or not applicable); year of publication; continent(North America, South America, Central America, Asia, Oceania,Europe or Africa); dam and sire groups (Bos indicus, Bos taurus(British breeds) purebreds, B. indicus × B. taurus (British breeds)crossbreds, B. indicus × B. taurus (Continental breeds) crossbreds,B. taurus (British × Continental) crossbreds, B. indicus × B. taurus(British and continental) crossbreds); evaluation period (days), sam-ple size; parity (primiparous or multiparous); gestation period (first(1TRI), second (2TRI) or third (3TRI) trimester); production system(grazing or feedlot) and body condition score (1–9 scale accordingto Pruitt and Momont (1987)) (Appendix A).

Cumulative MA and sensitivity analysis

Cumulative MA are often performed to update the overall treat-ment effect each time a new study is published. It allows identifi-cation of the time when the treatment effect was significantrelative to the control. Sensitivity analyses were conducted to ver-ify whether determined studies influenced the measure of effect(MD), by manually removing one study at a time and evaluatingwhether the MD varied ±30% before including the next study(Egger et al., 2001; Borenstein et al., 2009).

Results

Study selection

The search identified 2470 citations, from which 443 full-textswere assessed for eligibility for reading in their entirety and 389were excluded after methodological validation and data extraction(Appendix B). Out of the remaining manuscripts, eight did notreport sufficient data to perform the quantitative analysis(Appendix C) and, finally, 39 manuscripts on foetal weight andCBW were included in this SR-MA. In the current study, theFW4 was evaluated in four studies; the FW8 in four studies;and the CBW in 48 studies. Relative to dietary nutrient levels

fed to pregnant cows, 34 studies evaluated energy levels; 12, pro-tein level and seven, both energy and protein levels. In total, 170foetuses and 9053 calves were included. The body weight of 146foetuses and 3998 calves were evaluated as a function of dietaryenergy levels, and 46 foetuses and 1399 calves as a function ofdietary protein level.

The 39 publications included in this SR-MA comprised 56studies and 135 trials. The main characteristics of studies includedin this MA are presented in Tables 2 and 3.

Risk of bias

Few studies allowed a detailed analysis of the risk of bias. The riskof bias due to blinding was assumed to be ‘low’ because the out-come parameter was body weight, which is an objective measurewith low probability of error (Table 4 and Appendix A).

Meta-analysis

In the MA included studies, the FW4 and FW8 were assessed inthe same four publications (Table 2), out of which only Duarteet al. (2013) also reported CBW results.

Foetal weight

Only foetuses weighed at 4 (n = 4 studies, 6 trials) and at 8months (n = 4 studies, 4 trials) of gestation were included in thecurrent MA. The stratified analysis revealed high heterogeneitybetween studies both at 4 (I2 = 94.4%) and at 8 months (I2 =91.08%) of pregnancy.

Mean foetal weight at 4 months of pregnancy was 1.13 kg andno significant influence of the treatments on this outcome wasdetected.

Mean foetal weight at 8 months of pregnancy was 27.93 kg. Asignificant reduction in FW8 (−2.23 kg) was determined whenthe cows were fed CP and TDN levels corresponding to 100%of the NRC (1996) (95% CI =−2.68, −1.79, P < 0.001, n = 2studies, I2 = 0%) compared with 70% (Table 5) both in 1TRIand 2TRI.

Calf birth weight

Overall average CBWwas 37.11 kg. The analysis showed high hetero-geneity across the 48 studies (n = 125 trials) evaluating CBW (I2 =96.9%). In the studies in which cows were fed 130% of their CPrequirements (NRC, 1996), CBW was reduced by 0.45 kg (95%CI =−0.90, −0.01, P = 0.045, n = 15 trials, I2 = 96.9%). Where cowswere fed 140% of their TDN requirements (NRC, 1996), CBWwas reduced by 2.71 kg (95% CI =−1.04, −0.05, P = 0.001, n = 7trials, I2 = 98.3%) relative to the other dietary TDN levels.

Publication bias

The studies included in the current MA are highly heterogeneousand, therefore, the results should be interpreted with caution.There was no evidence of publication bias in the studies evaluat-ing FW4 and FW8, as determined by the symmetrical results ofthe funnel plot and the lack of significance in the Egger’s andBegg’s statistical tests. However, Begg’s test detected a publicationbias (P = 0.058) for CBW, and the ‘trim and fill’ test indicated 17additional tests would be required to remove this possible bias(Fig. 1).

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Meta-regression analysis

Meta-regression analysis is not indicated when the number ofstudies evaluated is lower than ten (Borenstein et al., 2009).

Therefore, it was not performed for FW4 (n = 4 studies and 6trials) or FW8 (n = 4 studies and 4 trials) data.

Table 2. Descriptive summary of each relevant study included in this MA and meta-regression (39)

Comparative groupTested diet

(control/treatment)

Number ofstudies/

sample size Evaluation parameter Reference Country

Energy levels S/S and C 1 (194) Birth weight Beck et al. (1992) USA

H/H 2 (128) Birth weight Bellows and Short (1978) USA

H and C/ H and C 2 (101) Birth weight Corah et al. (1975) USA

Si and C/ Si and C 2 (8) Foetal weight and birth weight Duarte et al. (2013) USA

H/Fo 1 (198) Birth weight Durunna et al. (2014) Canada

C/Si and C 1 (160) Birth weight Houghton et al. (1990) USA

H, Fo and C/ H, Fo and C 3 (342) Birth weight Köster et al. (2002) USA

H and C/Fo 1 (20) Birth weight Long et al. (2010) USA

H and C/ H and C 1 (233) Birth weight Martin et al. (2005) USA

H/Sa 1 (116) Foetal weights Meyer et al. (2010) USA

H, Si and C/ H, Si and C 1 (30) Birth weight Moriel et al. (2016) USA

Fo and C/ Fo and C 1 (514) Birth weight Pate et al. (1990) USA

H and C/ H and C 1 (13) Birth weight Perry et al. (1991) USA

H/H and C 1 (147) Birth weight Radunz et al. (2010) USA

H/H and C 1 (270) Birth weight Radunz et al. (2012) USA

H/H 1 (20) Birth weight Shell et al. (1995) USA

Fo and C/ Fo and C 7 (658) Birth weight Sims and Bailey (1995) USA

H/H and Si 1 (276) Birth weight Soto-Murillo et al. (1993) USA

Fo/Fo and C 1 (177) Birth weight Wilson et al. (2015a) USA

H and C/ H and C 1 (86) Birth weight Wilson et al. (2016b) USA

H and C/ H and C 1 (85) Birth weight Wiltbank et al. (1962) USA

Protein levels Si and C/ Si and C 1 (22) Birth weight Carstens et al. (1987) USA

H and C/ H and C 1 (24) Foetal weights Ferrell et al. (1976) USA

Fo/S and C 1 (24) Birth weight Larson et al. (2009) USA

Fo/Fo and C 2 (90) Birth weight Lodman et al. (1990) USA

H, S and C/ H, S and C 1 (68) Birth weight Micke et al. (2011) Australia

H/H and C 1 (57) Birth weight Summers et al. (2015b) USA

H/H and C 1 (114) Birth weight Summers et al. (2015a) USA

Fo and C/Fo 1 (362) Birth weight Stalker et al. (2006) USA

H/C and S 1 (163) Birth weight Wilson et al. (2015b) USA

Si and C/ Si and C 1 (42) Birth weight Wilson et al. (2016a) USA

H/H 1 (71) Birth weight Wood et al. (2010) Canada

H and C/ H and C 1 (48) Birth weight Zehnder et al. (2010) USA

Energy and protein levels H, Sa and C/ H, Sa and C 1 (22) Foetal weights Long et al. (2009) USA

Fo/Fo and C 2 (116) Birth weight Miner et al. (1990) USA

H and C/ H and C 1 (8) Birth weight Perry et al. (1999) Australia

Fo, H and C/ Fo, H and C 1 (96) Birth weight Winterholler et al. (2009) USA

H and C/ H and C 1 (118) Birth weight Winterholler et al. (2012) USA

Sa, straw with added ammonia; C, concentrate; H, hay; Si, silage; Fo, forage; S, straw.

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The 48 studies (n = 125 trials) reporting CBW outcomes weresubjected to meta-regression analysis. The results showed that96.88% of the variation across studies was due to chance. It wasdetermined that 1 year of increase in publication year reducedthe MD by 0.07 kg (P = 0.003).

Cumulative MA and sensitivity analysis

Cumulative MA did not detect any significant chronologicaltrends for FW4 and FW8. However, CBW presented a slow andclear chronological shift. Until 1993, outcomes tended to favourthe treatment group, whereas from 1993, the control group pre-sented better results.

The sensitivity analysis of FW4 data showed that removingthree studies (Ferrell et al., 1976; Meyer et al., 2010; Duarteet al., 2013), one at a time, increased MD from 0.84 kg to 1.64,1.95 and 2.35 kg, respectively. As for FW8, the removal of threestudies (Ferrell et al., 1976; Long et al., 2009; Meyer et al.,2010), again one at a time, increased MD from −0.47 kg to−0.22, 0.37 and 0.67 kg, respectively. The sensitivity analysis forCBW showed that removing the study of Zehnder et al. (2010)decreased MD from −0.48 to −0.21 kg.

Discussion

A large number of studies on foetal programming in beef cattlehave been published and the majority included in the currentstudy were conducted in North America. The outcomes evaluatedare conflicting and inconclusive, possibly due to differences indiets, breeds and pregnancy periods evaluated. For instance,Beck et al. (1992) found similar CBW, regardless of whethercows consumed 104 or 114% CP in 2TRI and 3TRI. Perry et al.(1991) found cows that consumed 70% of their energy require-ments (NRC, 1984) produced heavier calves at birth than thosethat consumed 150% of their energy requirements. On theother hand, cows fed a diet with nutrient levels 24.5% abovetheir requirements (1.40 kg/day of CP and 19.70 Mcal/day ofME) during 2TRI produced 8.3% heavier calves at birth comparedwith those of cows fed a diet with low nutrient levels (0.38 kg/dayCP and 15 Mcal/day ME) (Micke et al., 2011).

Although foetal programming is a recent research topic, the lit-erature search included studies published since 1976, when this

Table 3. Descriptive characteristics of 39 publications reporting 56 studiesincluded in the MA on the nutrition of the pregnant cow and its effects onfoetal development

Variable Categories

Number ofpublications(studies)

Study design Control studies 39 (56)

Treatment (type ofnutrient)

Energy level 21 (33)

Protein level 12 (16)

Energy and protein levels 6 (7)

Year of publication 1962–2000 15 (29)

2000–2016 24 (27)

Parity Primiparous 10 (14)

Multiparous 27 (34)

Primiparous and multiparous 2 (8)

Gestation period inwhich the study wasconducted

First trimester 1 (1)

Second trimester 2 (2)

Third trimester 21 (29)

First and second trimester 3 (3)

Second and third trimester 9 (18)

All pregnancy 3 (3)

Cows suckling or not calfof previous gestation

Suckling 2 (4)

No suckling 35 (49)

No data 2 (3)

Production system Extensive system 19 (30)

Intensive system 20 (26)

Duration of experiment 1–90 days 14 (18)

90–180 days 18 (29)

180–280 days 7 (9)

Dam groups Bos indicus 1 (2)

Bos taurus purebreds (Britishbreeds)

25 (39)

B. indicus × B. taurus (Britishbreeds)

1 (1)

B. indicus × B. taurus(British × Continental breeds)

1 (1)

B. taurus (British) × B. taurus(Continental breeds)

11 (13)

Sire groups B. taurus (British breeds) 10 (14)

B. taurus (Continental breeds) 2 (2)

B. indicus × B. taurus (Britishbreeds)

1 (1)

B. indicus × B. taurus(British × Continental breeds)

1 (1)

B. taurus (Continental ×British breeds)

1 (1)

Not reported 24 (37)

(Continued )

Table 3. (Continued.)

Variable Categories

Number ofpublications(studies)

Continent South America 1 (6)

Central America 0 (0)

North America 36 (48)

Oceania 2 (2)

Europe 0 (0)

Asia 0 (0)

Africa 0 (0)

Sample size n < 50 15 (18)

n = 51–100 10 (13)

n > 100 14 (25)




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term was not yet used. The effect of pregnant cow nutrition on pro-geny performance had already attracted researcher interest (Reidet al., 1948; Wiltbank et al., 1965; Corah et al., 1974; Ferrell

et al., 1976). Due to the need for intensification of animal produc-tion (Barcellos et al., 2011) and the demand for high-quality beef(Du et al., 2015), foetal programming has been increasingly studied.

Table 4. Methodological quality assessment of risk of bias (classified as low, not clear and high) of the 56 studies included in the MA on foetal weight and CBW

ReferenceSequencegeneration

Allocationconcealment

Selectivereporting

Outcomemeasurement

Blinding ofoutcome

assessmentIncomplete

outcome data

Beck et al. (1992) High Unclear Unclear Birth weight Low Low

Bellows and Short (1978) High Unclear Unclear Birth weight Low Low

Carstens et al. (1987) High Unclear Unclear Birth weight Low Low

Corah et al. (1975) High Unclear Unclear Birth weight Low Low

Duarte et al. (2013) High Unclear Unclear Foetal weights andbirth weight

Low Low

Durunna et al. (2014) High Unclear Unclear Birth weight Low Low

Ferrell et al. (1976) High Unclear Unclear Foetal weights Low Low

Houghton et al. (1990) High Unclear Unclear Birth weight Low Low

Klein et al. (2014) High Low Unclear Birth weight Low Low

Köster et al. (2002) High Unclear Unclear Birth weight Low Low

Larson et al. (2009) High Unclear Unclear Birth weight Low Low

Lodman et al. (1990) High Unclear Unclear Birth weight Low Low

Long et al. (2009) High Unclear Unclear Foetal weights Low Low

Long et al. (2010) High Unclear Unclear Birth weight Low Low

Martin et al. (2005) High Unclear Unclear Birth weight Low Low

Meyer et al. (2010) High Unclear Unclear Foetal weights Low Low

Micke et al. (2011) High Unclear Unclear Birth weight Low Low

Miner et al. (1990) High Unclear Unclear Birth weight Low Low

Moriel et al. (2016) High Unclear Unclear Birth weight Low Low

Pate et al. (1990) High Unclear Unclear Birth weight Low Low

Perry et al. (1991) High Unclear Unclear Birth weight Low Low

Perry et al. (1999) High Unclear Unclear Birth weight Low Low

Radunz et al. (2010) High Unclear Unclear Birth weight Low Low

Radunz et al. (2012) High Unclear Unclear Birth weight Low Low

Shell et al. (1995) High Unclear Unclear Birth weight Low Low

Sims and Bailey, (1995) High Unclear Unclear Birth weight Low Low

Soto-Murillo et al. (1993) High Low Unclear Birth weight Low Low

Stalker et al. (2006) High Low Unclear Birth weight Low Low

Summers et al. (2015b) High Unclear Unclear Birth weight Low Low

Summers et al. (2015a) High Low Unclear Birth weight Low Low

Wilson et al. (2015a) High Unclear Unclear Birth weight Low Low

Wilson et al. (2015b) High Unclear Unclear Birth weight Low Low

Wilson et al. (2016b) High Unclear Unclear Birth weight Low Low

Wilson et al. (2016a) High Unclear Unclear Birth weight Low Low

Wiltbank et al. (1962) High Unclear Unclear Birth weight Low Low

Winterholler et al. (2009) High Low Unclear Birth weight Low Low

Winterholler et al. (2012) High Low Unclear Birth weight Low Low

Wood et al. (2010) High Unclear Unclear Birth weight Low Low

Zehnder et al. (2010) High Unclear Unclear Birth weight Low Low

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Meta-analysis

Foetal growth rate and subsequent birth weight are the maindeterminants of postnatal survival and growth (Reynolds andRedmer, 1995). In the current study, the effect of the cow’s dieton foetal weight was only significant when applied in 1TRI and2TRI and had an effect at 8 months of gestation. The dailybody energy deposition of 4-month-old foetuses is 31 kcal, oronly 4.8% of the 644 kcal daily deposited at 8 months of gestation(Ferrell et al., 1976). This requirement for foetal body growth islow relative to the subsequent periods and to the total require-ment of the cow, indicating that diets evaluated at 4 months ofgestation were not able to change foetal growth during this period.This is also because in early pregnancy the embryonic develop-ment is a maternal priority (Valadares Filho et al., 2010), regu-lated by an endocrine balance that directs nutrients to thematernal–foetal circulation (Bauman and Currie, 1980).

A similar result was found by Camacho et al. (2018), whooffered 100 or 60% of the NRC recommendations for pregnantcows from 30 to 85, 140 or 254 days of gestation and did notobserve reduction in foetal weight in any of treatments. Thoseauthors suggested that cows develop mechanisms of placentaladaptation on sub-optimal feeding conditions. For example, thecows are more efficient in delivering nutrients to the foetus

under restricted nutritional conditions if there are increases inplacental size, placentome weight and number, umbilical bloodflow and the placental ability to produce and secrete sex steroidsor hepatic clearance of progesterone oestradiol-17β.

Although in the current study nutritional restriction in the firstmonths of gestation did not seem to change the weight of foetusesat 4 months, it is known that it exerts an influence on placentalformation and development, producing alterations in foetusdevelopment in later periods of gestation (Long et al., 2009). Inthe current study, higher FW8 was obtained in cows fed 70%CP levels (NRC, 1996) during 1TRI and 2TRI, the period whenrestriction was applied, compared with 100% CP levels. During1TRI and 2TRI, placental growth in terms of mass and cell pro-liferation is maximal, and the size and function of the placentauntil the end of gestation depends on its early development(Erhardt and Bell, 1995), which Perry et al. (1999) found toimprove under conditions of low CP intake. These benefits aregenerated through improved microvilli development and increasesin cotyledon weight and trophectodermal volume, stimulatingplacental growth and function in cows, and promoting foetalgrowth (Perry et al., 1999). Moreover, it is believed that placentalgrowth of cows subjected to nutritional restriction at the begin-ning of gestation may be compensated by increasing the numberof caruncles to provide the nutrients required for foetal develop-ment (Bassett, 1991; Clarke et al., 1998). Therefore, the lowerFW8 observed when cows were fed 100% CP may be attributedto a reduction in placental development, in relation to therestricted level, as the placenta supplies nutrients to the foetus(Hyttel et al., 2012) and the development is directly influencedby foetal weight (Kelly, 1992).

In the current MA, when the TDN level matched cows’requirements (NRC, 1996) during 1TRI and 2TRI, FW8 waslower than those of animals fed 70% of their requirements.Gonzalez et al. (2013) reported that when the energy intake ofbeef cows was restricted to 60%, the size of the primary musclefibres of their foetuses at 85 days of gestation increased, as a resultof higher activity of the protein that acts as muscle growth factorin the foetus (insulin-like growth factor 2 or IGF-2), comparedwith non-restricted cows. Several authors also observed that myo-cyte size and number influence calf body weight by increasingmuscle hypertrophic efficiency, consequently increasing offspringbody weight (Du et al., 2010a; Rehfeldt et al., 2011; Radunz et al.,2012; Gonzalez et al., 2013).

Table 5. Foetal weight at 8 months of gestation according to dietary CP and total digestible nutrients levels fed to pregnant cows during different gestation periods

Variable Studies (trials) MDa (P) 95% CIb I2

Pregnancy period

First and second trimester 2 (2) −2.27 (<0.001) −2.68, −1.79 0

Second and third trimester 1 (1) 6.56 (0.001) 2.60, 10.52 0

Entire gestation 1 (1) −0.09 (0.835) −0.92, 0.75 0

Dietary CP level

100 v. 70%c 2 (2) −2.24 (<0.001) −2.68, −1.79 0

Dietary total digestible nutrients level

100 v. 70%c 2 (2) −2.24 (<0.001) −2.68, −1.79 0

aExpressed in kg.b95% confidence interval.cControl v. treatment group.

Fig. 1. Funnel plot obtained using Duval and Tweedie’s ‘trim-and-fill’ linear randomeffect model measuring standard MD in CBW.




https://doi.org/10.1017/S0021859619000315


Although some studies (Spitzer et al., 1995; Stalker et al., 2006)show that maternal overnutrition during 2TRI and 3TRI pro-motes foetal development and increases birth weight, detrimentaleffects on postnatal offspring growth was reported (Caton andHess, 2010). The results of the current MA indicated a negativerelationship between cow CP intake during the 3TRI of gestationand CBW, i.e. when cows were fed CP levels more than theirrequirement, CBW was reduced (Table 6). These effects weremore evident in 3TRI, as 75% of foetal growth occurs duringthis phase (Robinson, 1977).

Although high CP intake by pregnant cows should increasefoetal and calf weights, given the higher availability of aminoacids for foetal growth (Long et al., 2010), it may compromisebody development. A possible explanation is that foetuses fromoverfed dams may have low insulin sensitivity, which reduces glu-cose utilization by the cells and impairs body development(Radunz et al., 2012; Wilson et al., 2016a). In addition, pregnantcows fed high CP may present lower blood levels of IGF-I(Sullivan et al., 2009), the hormone responsible for nutrient par-tition between the dam and the foetus. For Herring et al. (2018),protein in ovine gestation caused delayed foetal growth beyondembryonic death. According to those authors, when the aminoacids methionine and cysteine are degraded, sulphuric acid andhomocysteine are produced, which reduces the blood pH of thepregnant sheep and increases oxidative stress in the cells of thefoetus, causing the foetuses to have low body weight or to die.

The current MA also determined lower CBW in cows fedhigher levels of TDN than their requirements compared withcows fed adequate TDN levels during gestation. Excess energyconsumption by ruminants can lead to reduced energy efficiency(Webster, 1981) and increased body tissue degradation (Joneset al., 1990). For Jones et al. (1990), the excretion of 3-methyl-histidine was higher in animals fed ad libitum than in thosewho had energy restricted diets. It is important to note that3-methyl-histidine is indicative of muscle protein degradation.Following this line of reasoning, in the current work, excessenergy consumption may have impaired foetal muscle deposition.

Although few reports in the literature address the influence ofdam TDN intake on foetal development in cattle, many studieswith other livestock species have been published. In pregnantewes fed energy levels above their requirements, adipogenic geneexpression was up-regulated, whereas myogenic genes were down-regulated, suggesting a direct negative effect of high energy intakeon lamb birth weight (Tong et al., 2009). Similarly, other authors

observed lower lamb birth weight in pregnant ewes fed 140% com-pared with 100% of their energy requirements, from day 40 of ges-tation until lambing, possibly as a result of 30–40% lower placentalgrowth (Da Silva et al., 2001; Wallace et al., 2006; Swanson andBewtra, 2008). In pigs, increasing protein and energy levels (43%)of a standard gestation diet (2.55 Mcal DE/kg and 12% CP), duringthe first 50 days of gestation, reduced piglet birth weight (Bee,2004). According to Han et al. (2000), feeding sows with dietarynutrients 40% above their requirements throughout gestationimpairs piglet survival and postnatal growth.

In humans (Du et al., 2010b) and in cattle (Moisá et al., 2015),the negative impacts of maternal over-nutrition on the progenymay be due to low-grade inflammation, causing epigeneticchanges in mesenchymal stem cells (MSC), limiting myogenesisand promoting adipogenesis. The shift of MSC function frommyogenesis to adipogenesis and fibrogenesis increases intramus-cular fat and connective tissue, and reduces the number and/ordiameter of muscle fibres, with negative and long-lasting effectson the muscle tissue (Du et al., 2010b). The reduction in birthweight is because skeletal muscle accounts for 40–50% of thebody mass and contains more water than other body constituents,such as adipose tissue.

In the current MA, restricting both TDN and CP levels in thediets fed to pregnant cows during 3TRI did not affect CBW(Table 6). Carstens et al. (1987) observed lower heat productionin calves from CP-restricted heifers compared with those of non-restricted heifers, indicating reduced foetal basal metabolism,which shows that the dam saves energy to maintain normalgrowth of foetus and CBW. In relation to energy, Fiems et al.(2005) did not observe changes in CBW in heifers fed 70 or100% of their energy requirements. However, those heifers fedthe lowest level of energy showed lower body condition score,which may compromise the calves’ body growth.

Meta-regression analysis

The meta-regression analysis showed that until 1993, the CBW ofthe control group was reduced when the publication dateincreased by 1 year. This result was also observed in the cumula-tive MA. This change in CBW values may be explained by theincreased selection for low birth weight of beef calves (Garayet al., 2014). It should be noted the genotype of the foetus alsoregulates foetal growth, particularly during the initial and inter-mediate stages of gestation, before the maternal genotype and

Table 6. CBW according to dietary CP and total digestible nutrients levels fed to pregnant cows during different gestation periods

Variable Studies (trials) MDa (P) 95% CIb I2

Gestation period

First trimester 1 (1) −1.04 (0.030) −1.98, −0.10 0

Second trimester 2 (4) 0.19 (0.904) −2.87, 3.24 98.2

Third trimester 22 (90) −0.76 (<0.001) −1.11, −0.41 96.4

Dietary CP level

100 v. 130%c 15 (26) −0.45 (0.045) −1.90, −0.01 96.9

Dietary total digestible nutrients level

100 v. 140%c 7 (23) −2.71 (0.001) −1.04, −0.05 98.3

aExpressed in kg.b95% confidence interval.cControl v. treatment group.

8 D. Zago et al.



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the foetal environment become the predominant influences onfoetal growth (Ferrell, 1991). Birth weight is an indicator of calfsurvival and calving ease; therefore, the genetic selection influ-ences production costs (Garay et al., 2014).

Conclusions

In the current MA, the NRC (1996) was used as a reference forenergy and protein levels for beef cows, because it presents con-solidated and globally-accepted information on the nutritionalrequirements of beef cattle. However, some of the results obtainedshowed that the NRC recommendations did not ensure higherCBW. The NRC (1996) provides important information, men-tioning factors influencing birth calf weight and presents pregnantcow nutrient requirements according to body weight, breed andpregnancy phase, but does not include foetal programming con-siderations. Then, the use of foetal programming informationmay be relevant to improve the efficiency in cow–calf productionsystems. To our knowledge, this is the first study to compile litera-ture data about the influence of pregnant cow nutrition on foetaldevelopment and its results may be used to improve the product-ivity of cow–calf production systems, particularly when cows arefed low nutritional levels.

In summary, protein restriction during the first and second tri-mesters of pregnancy was shown to be favourable for foetal weightgain at end of gestation. This could be an interesting managementoption, since in the first trimester of gestation and half of thesecond, multiparous cows are suckling the calf of the previous ges-tation, which may eventually reduce the availability of nutrients tothe foetus. In addition, the supply of protein and excess energy topregnant cows is not recommended because they cause a reductionin birth weight of progeny, a fact that may compromise the survivalof the new-born and its development in the first days of life(Reynolds and Redmer, 1995). With nutritional restriction beingsomewhat positive, the farmer can save on the diets of pregnantcows. For North American calf-fed and yearling-fed integratedbeef production systems, Basarab et al. (2012) estimated that thecow herd (cows, bulls and replacements) requires approximately82 and 64%, respectively, of total feed inputs. Thus, attempts toimprove efficiency of feed utilization and profitability of beef cattleoperations will need to focus on reducing cow herd feed inputsrelative to system outputs (Tedeschi et al., 2017).

Author ORCIDs. D. Zago, 0000-0003-3444-4323.

Financial support. The authors are grateful for the financial support of theBrazilian Council of Scientific and Technological Development (CNPq).

Conflict of interest. None.

Ethical standards. Not applicable.

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https://doi.org/10.1017/S0021859619000315


Appendix A

Table A1. Summary of the evaluation for the methodological validity of 39 publications reporting 56 studies included in this MA on the nutrition of the pregnant cowand its effects on foetal development

Variable Evaluation

Number of publication (studies)

Foetalweights

Birthweight

Was the sample size justified? Yes 0 (0) 0 (0)

No 4 (4) 35 (52)

How were cows assigned to groups? Randoma 0(0) 1(1)

Reported randomb 0(0) 0(0)

Systematicc 0(0) 0(0)

Convenience orunreportedd

4(4) 34(51)

Was the intervention protocol described in sufficient detail to be replicated? Yes 4(4) 35 (52)

No 0 (0) 0 (0)

Reference paper 0 (0) 0 (0)

Did the author report that blinding was used to evaluate the outcome? Yes 0 (0) 0 (0)

No 4(4) 35 (52)

Based on the study design, was clusteringe appropriately accounted for in theanalysis?

Yes 0 (0) 0 (0)

No 0 (0) 0 (0)

Not applicable 4(4) 35 (52)

Were identified confounders controlled or tested? Yes, analysisf 0 (0) 0 (0)

Yes, inclusion/exclusiong 0 (0) 0 (0)

Yes, matchingh 0 (0) 0 (0)

Noi 4(4) 35 (52)

Not applicablej 0 (0) 0 (0)

Was the statistical analysis described adequately so it can be reproduced? Yes 4(4) 35 (52)

No 0 (0) 0 (0)

Reference paper 0 (0) 0 (0)

Statistical analysis notdone

0 (0) 0 (0)

aComputer or random number table, a priori, stratified random sample, cluster, random sample.bAuthor(s) report random, but randomization is not described.c‘n’ samples obtained at x intervals or stratified by certain characteristics.dAuthor indicated convenience sampling or sampling was not reported in the paper.eClustering was evaluated when repeated measures were reported.fAuthor identified confounders and controlled for them in the analysis.gConfounders were identified and included/excluded a priori.hConfounders were controlled a priori by matching on certain characteristics.iNo adjustments were made for confounders/effect modifiers, etc., that were identified by the author.jConfounders were not identified by the author or randomization was used to control them.

12 D. Zago et al.



https://doi.org/10.1017/S0021859619000315


Appendix B

Figure B1. Flow diagram indicating the number of abstracts and publications included and excluded in each level of the systematic review on the pregnant cownutrition and its effects on foetal development, adapted from Moher et al. (2009). All search results are included in the diagram to allow better understanding ofthe total number of records found.

Appendix C

Table C1. Relevant publications excluded from the final MA database on the nutrition of the pregnant cow and its effects on foetal development

References Country Treatment Reason for exclusion

Camacho et al. (2014) USA Energy level No results of interest

Corah et al. (1974) USA Energy level No results of interest

Domokos et al. (2011) Hungary Different forages Insufficient data for this study

Funston et al. (2010) USA Protein level No results of interest

Lobato et al. (1998) Brazil Different forages Insufficient data for this study

Lobato et al. (1998) USA Energy and protein levels No results of interest

Micke et al. (2010) Australia Energy and protein levels Diet change throughout the study

Micke et al. (2015) Australia Protein level Diet change throughout the study




https://doi.org/10.1017/S0021859619000315


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