Dietary essential fatty acids, long-chain polyunsaturated fatty acids, and visual resolution acuity in healthy fullterm infants: a systematic review

Early Human Development 57 (2000) 165–188 www.elsevier.com / locate / earlhumdev

Dietary essential fatty acids, long-chain polyunsaturated fatty acids, and visual resolution acuity in healthy fullterm infants: a systematic review a, b,c John Paul SanGiovanni *, Catherine S. Berkey , a,d,e c,f Johanna T. Dwyer , Graham A. Colditz a

Department of Maternal and Child Health, Harvard School of Public Health, Boston, MA, USA Department of Health Policy and Management, Harvard School of Public Health, Boston, MA, USA c Channing Laboratory, Harvard Medical School, Boston, MA, USA d Frances Stern Nutrition Center, New England Medical Center Hospital, Boston, MA, USA e Schools of Medicine and Nutrition Science and Policy, Tufts University Medical School, Boston, MA, USA f Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA b

Accepted 18 October 1999

Abstract Background: Biologically active neural tissue is rich in docosahexaenoic acid (DHA), an omega-3 long-chain polyunsaturated fatty acid (LCPUFA). We conducted a systematic review to examine the nature of discordant results from studies designed to test the hypothesis that dietary DHA leads to better performance on visually-based tasks in healthy, fullterm infants. We also conducted a meta-analysis to derive combined estimates of behavioral- and electrophysiologic-based visual resolution acuity differences and sample sizes that would be useful in planning future research. Study design and methods: Twelve empirical studies on LCPUFA intake during infancy and visual resolution acuity were identified through bibliographic searches, examination of monograph and review article reference lists, and written requests to researchers in the field. Works were reviewed for quality and completeness of information. Study design and conduct information was extracted with a standardized protocol. Acuity differences between groups consuming a source of DHA and groups consuming *Corresponding author. Present address: International Nutrition Foundation, Charles Street Station, Box 500, Boston, MA, 02114-0500, USA. E-mail address: [email protected] (J.P. SanGiovanni) 0378-3782 / 00 / $ – see front matter  2000 Elsevier Science Ireland Ltd. All rights reserved. PII: S0378-3782( 00 )00050-5

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DHA-free diets were calculated as a common outcome from individual studies; this difference score was evaluated against a null value of zero and then used, with the method of DerSimonian and Laird (Meta-analysis in clinical trials. Control Clin Trials 1986;7:177–188), to derive combined estimates of visual resolution acuity differences within seven age categories. Results of randomized comparisons: The combined visual resolution acuity difference measured with behaviorally based methods between DHA-supplemented formula fed groups and DHA-free formula fed groups is 0.3260.09 octaves (combined difference6S.E.M., P 5 0.0003) at 2 months of age. The direction of this value indicates higher acuity in DHA-fed groups. Results of non-randomized study designs: The combined visual resolution acuity difference measured with behaviorally based methods between human milk fed groups and DHA-free formula fed groups is 0.4960.09 octaves (P # 0.000001) at 2 months of age and 0.1860.08 octaves (P 5 0.04) at 4 months of age. Acuity differences for electrophysiologicbased measures are also greater than zero at 4 months (0.3760.16 octaves, P 5 0.02). Conclusion: Some aspect of dietary n-3 intake is associated with performance on visual resolution acuity tasks at 2, and possibly, 4 months of age in healthy fullterm infants. Whether n-3 intake confers lasting advantage in the development of visually based processes is still in question.  2000 Elsevier Science Ireland Ltd. All rights reserved. Keywords: Docosahexaenoic acid; Alpha-linolenic acid; Human milk; Infant; Meta-analysis; Omega-3 fatty acids; Vision; Acuity

1. Introduction Visual representation of pattern information is a fundamental perceptual function necessary for recognition, identification, and determination of object properties. The effectiveness of pattern vision is dependent upon the accuracy with which the observer detects and encodes the spatial distribution of intensity / wavelength differences that define points and surfaces within the physical world [1]. Visual resolution acuity is a sensory-perceptual capacity necessary for ensuring accuracy in this encoding process [2]. The development of pattern vision is dependent upon the quality of input to brain systems in the visual pathway and may subsequently influence the development of visually guided behavior and learning. A number of dietary- [3], ocular- (optical, retinal) [1,2] and cerebral cortex-based factors [4] have been suggested to influence the development of acuity; among the dietary factors is early postnatal intake of omega-3 (n-3) long-chain polyunsaturated fatty acids (LCPUFAs). Docosahexaenoic acid (DHA or C22:6n-3), an LCPUFA derived from the n-3 essential fatty acid (EFA) family, is found predominantly in metabolically active neural membranes of brain and retina [3,5,6]. As an integral component of phospholipid membranes, DHA is efficiently incorporated and selectively retained within retinal photoreceptor outer-segments [7,8]. Because of its long carbon chain length and highly unsaturated nature, DHA may influence retinal membrane dynamics [9]. Dietary n-3 LCPUFAs can affect nervous system function by altering membrane physical properties, enzymatic activities, receptor structure and number, carrier-

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mediated transport, as well as cellular interactions [10]. DHA may serve an important role in the photopigment-membrane microenvironment of retinal photoreceptor outersegments. DHA-containing phospholipids appear to associate strongly with rhodopsin, the trans-membrane photopigment essential for phototransduction [3,11]. Furthermore, a subset of DHA-containing phospholipids is selectively retained within photoreceptor outer-segment disk membranes across their entire 9–15 day life; these membrane components may be strongly bound to rhodopsin [12]. DHA is the product of the elongation and desaturation of the EFA a-linolenic acid (a-LLNA or C18:3n-3). Maternal preconceptional [13,14], prenatal [15], and postnatal dietary balance and composition of EFAs / LCPUFAs [16] influence the quantity of DHA available to the fetus and human milk-fed infant. Lipolysis of subcutaneous maternal EFA / LCPUFA stores and fetal accretion of n-3 EFA / LCPUFAs takes place throughout pregnancy, but mainly during the third trimester [17,18]. Dietary DHA is more likely to be efficiently transferred from the mother to the fetus or young infant than the DHA that is synthesized from n-3 EFAs [14]. While enzymatic factors necessary for DHA biosynthesis are active in the first postnatal week, it is uncertain whether infants receiving only a source of a-LLNA would be able to produce amounts of DHA similar to those infants who have received a preformed source in human milk [19]. Because metabolites of the omega-6 (n-6) EFA family compete with those of the n-3 family for desaturation and elongation enzymes, the dietary balance of n-6 / n-3 can also affect maternal and infant DHA biosynthesis [20]. Dietary intake is the only practical means for the young infant to attain adequate LCPUFA tissue status. If DHA is necessary for optimal nervous system functional development, then feeding practices may influence functional outcome because DHA is present in human milk but not in most standard fullterm infant formulae. Post-mortem studies in human infants dying of sudden infant death syndrome (SIDS) or dehydration support the hypothesis that some aspect of n-3 fatty acid intake influences neural DHA status [21–24]. These studies compared neural tissue phospholipids between human milk- and formula-fed infants. Higher levels of DHA were present in brain areas of human milk-fed groups. The positive association of erythrocyte (RBC) phospholipid DHA with neural tissue phospholipid DHA has provided a rationale for using RBC DHA as a surrogate marker for neural tissue stores of the fatty acid; however, the validity of this measure has been questioned [25,26].

1.1. Omega-3 fatty acids and functional development Non-human primates with experimentally induced n-3 deficiencies show reduced retinal response to light [27], lower visual resolution acuity, measured using behavioral methods [28], and reduced average look duration to a novel stimulus, measured using visual recognition memory tasks [29]. For human visual development, the role LCPUFAs is supported both by clinical reports of infants fed EFA-free diets [13] and populations with naturally occurring metabolic n-3 LCPUFA insufficiencies [30–35]. Both groups show gross deficits in visual performance that respond to n-3 fatty acid supplementation.

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EFA / LCPUFA supplementation studies in pre- and fullterm human infants have provided limited-suggestive evidence of an association between LCPUFA intake and visual function measured with behaviorally based tests at 2 and 4 months corrected postnatal age, but researchers in the field hold differing opinions about the efficacy. As one means to improve the planning and implementation of future studies, a systematic review was conducted to evaluate the nature of discordant results in empirical studies on n-3 LCPUFA intake and visual acuity development in healthy fullterm infants. Analysis included assessment of experimentally and methodologically based threats to validity. Also, because a number of existing individual studies may have been under-powered, a meta-analysis was conducted to derive combined estimates and standard errors of visual resolution acuity differences between groups who did or did not consume a source of n-3 LCPUFAs early in infancy.

2. Methods

2.1. Research synthesis protocol 2.1.1. Search strategy and study selection Prospective, empirical studies on acuity development and EFA / LCPUFA intake in healthy fullterm infants were identified through bio-medical reference database searches to June1999 ( MEDLINE and HEALTH STAR). Review article / chapter / monograph reference sections were searched. Consultation was made with groups publishing original research. Publications were considered for review if they contained adequate methodological information on study design and conduct. If data from one study were published in more than one paper, then duplicated information was excluded from the meta-analysis. 2.1.2. Information extraction Each article or chapter that met the search criteria was reviewed to obtain specific information about: (1) dietary intake and tissue status of EFAs / LCPUFAs; (2) formation, surveillance and follow-up of study groups; (3) estimated age of the subjects; (4) appropriateness of control / comparison groups; and, (5) outcome measure administration and measurement properties. The search yielded a total of twelve studies, with eleven retained for the meta-analysis. Four review articles and one monograph provided additional information on study design and conduct issues. For behaviorally based tests the extraction process yielded a total of two, nine, four, eleven, nine, five, and eight comparisons to be analyzed for subjects at # 1, 2, 3, 4, 6, 9, and 12 months of age, respectively. For electrophysiologic tests there were six, ten, one, six, two, three, and six comparisons at 2, 4, 5, 6, 7, 9, and 12 months of age, respectively. Data extraction took place with a standardized protocol; information included test-, tester-, and subject-based factors such as publication year, approximate time period in

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which the study was conducted, study location, demographics, study design, functional outcome measured (behaviorally based or electrophysiologic-based acuity), number / characteristics of subjects enrolled and completing the study protocol, and LCPUFA intake-status (composition, duration of intake). Acuity was measured both through behaviorally and electrophysiologic methods. For all of the behaviorally based tests stimuli were high-contrast square-wave gratings of two discrete luminances, presented in an equal duty cycle. Such stimuli appear to adults as a series black and white stripes of equal width. Grating acuity can be expressed in units of cycles per degree (Cy / deg) of visual angle. A cycle is one period (a single black and the adjacent white stripe). The spatial extent of the projected retinal stimulus is conventionally represented in degrees of arc. For example, the lateral extent of the image of one’s thumb, viewed at arm’s length, subtends approximately one degree. If one black and one white stripe of the same width were placed adjacently and viewed at arm’s length, the projected image could be described as having a spatial frequency of one Cy / deg. To relate the measure to familiar metric — when vision is corrected to a Snellen equivalent of 20 / 20, the observer has the ability to resolve 30 Cy / deg. Cy / deg can then be seen as a measure of visual resolving power per degree; higher values indicate response to finer patterns. Square wave gratings or checkerboards were used as stimuli in the electrophysiologic studies (visual evoked potential or VEP) reviewed in this manuscript. In acuity research, measures of dispersion, such as the standard error of the mean, are commonly represented in units of octaves. A one octave change represents a doubling or a halving of the stimulus spatial frequency (or a thinning of the width of the individual stimulus lines by one half). Conversion to octaves is useful for the comparison of relative differences between exposure groups because it allows the researcher to estimate a difference that is standardized across all stimuli. Such standardization is an important control for measurement biases that may be introduced due to characteristics of the tester’s behavior or experimental technique. For example, a tester can consistently underestimate the threshold of visual resolution, but if the same decision rules are applied by that tester across all tests performed, then the relative differences in performance between exposure groups should be preserved when they are compared to the results of another tester. Absolute acuity levels of a group may then be observed vary between experienced testers, but the relative acuity differences between groups between testers would not be expected to do so. Mayer and Dobson [36] reviewed factors related to study design and conduct that influence validity and reliability in behaviorally based experiments using grating stimuli and acuity cards containing grating stimuli; we used this information as a basis for extracting information from studies using the Teller Acuity Card Procedure (ACP) or the Forced Choice Preferential Looking Procedure (FPL). Test-based factors included: grating spatial frequency between successive square wave grating stimuli (step-size in octaves), testing protocol, spatial frequency of the initial stimulus, subject distance from the stimulus, and stimulus luminance. Tester-based differences included: tester knowledge of stimulus spatial frequency, number of testers, tester experience and training, and monitoring of performance. Subject-based

(1) Grace General Hospital St. John’s, Newfoundland (Canada) (2) Janeway Child Health Centre St. John’s, Newfoundland (Canada) (1) Children’s Mercy Hospital Kansas City, MO (USA) (2) Oregon Health Sciences U. Portland, OR (USA) (3) Children’s Hospital Seattle, WA (USA) (1) Austin, TX (USA) (2) Edmonton, AB (Canada) (3) Louisville, KY (USA) (4) Lutherville, MD (USA) (5) Raleigh, NC (USA) (6) Salem, VA (USA) (7) Vancouver, BC (Canada)

Auestad et al. (1997) [41]

Innis et al. (1997) [42]

(1) Medical City Columbia Hospital Dallas, TX (USA) (2) Presbyterian Medical Center Dallas, TX (USA)

Study sites

Courage et al. (1998) [40]

Behaviorally based tests Birch et al. (1998) [39]

Study

Table 1 Experiment-based characteristics of reviewed studies a

Teller acuity cards (Square-wave gratings)

Recruitment: around birth Standardized across sites Testers trained by one person Two testers

Recruitment: around birth Standardized across sites From TAC Handbook $Five testers

Recruitment: around birth From TAC Handbook One tester

Teller acuity cards b

Teller acuity cards (Square-wave gratings)

Recruitment: around birth FPL protocol (staircase) Seven testers

Vision testing protocol

Square-wave gratings

Stimuli

0.32/0.50 (3)

0.44/0.50 (2, 4) 0.63/0.50 (6, 9, 12)

0.32/0.50 (3, 6)

0.40/0.50 (1.5, 4, 6.5, 12)

Spatial frequency of 1st stimulus in Cy/deg /Difference between successive cards in octaves (age in months)

38 (0.5, 3)

38 (2, 4) 55 (6, 9, 12)

55 (3, 6)

NR

Subject distance in cm (age in months)

Yes

Yes

NR

NR

Ophthalmic exam

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Crump Women’s Hospital Memphis, TN (USA)

Teller acuity cards (Square-wave gratings)

Recruitment: ,2 days Mainly one tester

0.32/0.50 (2, 4) 1.6/0.50 (12)

38 (2, 4, 6, 9, 12)

Yes

Jorgensen et al. (1996) [44]

NR (Scandinavia)

Teller acuity cards (Square-wave gratings)

Recruitment: |1 month PNA From TAC Handbook One tester

NR/0.50 (1, 2, 4)

38 (1, 2, 4)

NR

Innis et al. (1994) [45]

British Columbia Children’s Hospital Vancouver, BC (Canada)

Teller acuity cards (Square-wave gratings)

Recruitment: around birth From TAC Handbook 2 testers

0.32/0.50 (0.5, 3)

38 (0.5, 3)

Yes

Birch et al. (1993) [46]

NR (Texas, USA)

Square-wave gratings

Recruitment: NR FPL Protocol Number of testers NR

Randomized (range NR)/0.50 (4)

57 (4)

Infants with known eye disorder were not recruited

Birch et al. (1992) [47]

NR (Texas, USA)

Square-wave gratings

Recruitment: NR FPL Protocol Number of testers NR

Randomized (range not reported)/0.50 (4)

57 (4)

NR

(1) Medical City Columbia Hospital Dallas, TX (USA) (2) Presbyterian Medical Center Dallas TX (USA)

Square-wave gratings, 6.6 Hz

Recruitment: around birth VEP (steady-state)

0.50/0.50 (1.5) 1.0/0.50 (4, 6.5) 2.0/0.50 (12)

NR

NR

Auestad et al. (1997) [41]

(1) Children’s Mercy Hospital Kansas City, MO (USA) (2) Oregon Health Sciences U. Portland, OR (USA) (3) Children’s Hospital Seattle, WA (USA)

Square-wave gratings, 6 Hz

Recruitment: around birth VEP (steady-state)

0.50/NR (2,4) 1.0/NR (6, 9, 12)

72 (2, 4) 114 (6, 9, 12)

Yes

Makrides et al. (1995) [48]

Flinders Medical Center Adelaide (Australia)

Checkerboard pattern, 2 Hz

Recruitment: ,5 days VEP (transient)

|0.50/1.0 (5, 7)

100 (4, 7)

Yes

Birch et al. (1993) [46]

NR (Texas)

Checkerboard pattern, 2 Hz

Recruitment: NR VEP (steady-state)

|0.16/1.0 (4)

50 (4)

NR

Makrides et al. (1993) [49]

Flinders Medical Center Adelaide (Australia)

Checkerboard pattern, 2 Hz

Recruitment: |4 months VEP (transient)

|0.25/1.0 (5)

100 (5)

Yes

Electrophysiologically based tests Birch et al. (1998) [39]

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Carlson et al. (1996) [43]

a

171

Note: Studies using randomized comparisons are represented in italicized text in the first column. NR, not reported; ACP, Teller Acuity Card Procedure; FPL, Forced Choice Preferential Looking Procedure; VEP, visual evoked potential; Cy / deg, cycle per degree; TAC, Teller Acuity Card; Hz, Hertz (cycles / second). b Teller acuity cards are square wave gratings positioned on a background of space-averaged luminance. All square-wave gratings and checkerboard patterns were black and white. The square-wave gratings for the behaviorally based tests were of equal duty cycle (all stripes were the same width).

$4 $4 $4

$4 $4 $4

Carlson et al. (1996) [43]

No solids No solids

3 3

HM FF 1DHA1AA FF 2DHA

2

1

FF 2DHA FF 2DHA

No solids

1, after that #180 ml formula/day

4 4 4 4

HM

3 4 4 4

Innis et al. (1997) [42]

$ $ $ $

12 of 34 infants receiving 1–4% of total energy through solids by 3

HM FF 1DHA1AA FF 1DHA FF 2DHA

FF 2DHA

Three of 35 infants by 3

4

$4

FF 2DHA |3 Five of 35 infants receiving 5–30% of total energy through formula at 3 |3

4

$4

FF 1DHA

HM

4

$4

FF 1DHA1AA

Auestad et al. (1997) [41]

Courage et al. (1998) [40]

4

$4

HM

Birch et al. (1998) [39]

Age at which solids may have been introduced

Duration of exclusive feeding in months

Intake group

Study

Table 2 Design and analytic characteristics of reviewed studies a

HM Egg yolk

HM

HM Egg yolk Tuna oil

HM

35 31 28

69 70

99

76 68 65 65

35

35

26

26

27

Single cell oils ‡

Single cell oil

29

Subjects in study population

HM

Source of DHA or AA (1.5) (4, 6.5) (12) (1.5) (4, 6.5) (12) (1.5, 4) (6.5) (12) (1.5, 4, 6.5) (12)

19 20 19

75 56 † 59 57

63 46 43 45

34 (3) 30 (6)

35 (3) 30 (6)

25 21 20 26 23 19 22 21 20 23 21

Subjects analyzed (age in months)

PMA

PMA

PNA

PMA

PCA

Basis for computing test age estimates

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HM FF 2DHA

4 13 of 16 infants had HM by 1

One of 17 infants by 3 Nine of 16 infants by 3

HM

22 17

17 16

NR

Makrides et al. (1995) [48]

HM

4 to 6

HM

4 to 6

Fish (blend) Evening primrose

47 23* 13

FF 2DHA

$4

4 to 6

28 (4) 18 (7) 8 (4) 9 (7) 18 (4) 17 (7)

PNA

FF 1DHA

4, after that #120 ml formula/day $4

Innis et al. (1994) [45]

HM FF 2DHA

3 3 (no HM after first 72 h of life)

No solids No solids

HM

18 17

18 17

PMA

Birch et al. (1993) [46]

HM FF 2DHA

4 4

No solids NR

HM

NR NR

18 12

PCA

Makrides et al. (1993) [49]

HM FF 2DHA

5 .70% of nutrition from infant formula

Receiving solids at 5 Receiving solids at 5

HM

9 9

8 8

PNA

Birch et al. (1992) [47]

HM

$2 post-term, after that $75% of intake from HM NR

NR

HM

NR

35

PCA

NR

14

FF 2DHA a

NR

19

Note: HM, human milk; FF, formula-fed; NR, not reported; DHA, docosahexanoic acid; AA, arachidonic acid; EPA, eicosapentanoic acid; a-LLNA, alpha linolenic acid (the precursor to DHA); LA, linoleic acid; PCA, postnatal age corrected for post-conceptional age based upon a set of obstetric measures; PMA, postnatal age corrected for mother’s last menstrual period; PNA, postnatal age uncorrected for gestational age. * Exclusively human milk-fed for 7 months. † Exclusively human milk-fed for 3 months. ‡ DHASCO  and ARASCO  (Martek Biosciences, Columbia, MD).

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Jorgensen et al. (1996) [44]

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174

differences included: alertness, attention, general health, wellness at the time of testing, and correction for gestational age at birth.

2.1.3. Selection of a common outcome variable Difference in visual resolution acuity between groups consuming a source of DHA and groups not consuming a source of DHA was the outcome measure. Values for outcomes were extracted from figures when exact values were not available from publications or author correspondence. Difference scores in visual resolution acuity between dietary groups were calculated from individual values from a dietary group and then transformed into octaves as: (log 10 (mean acuity in Cy / deg DHA-supplemented group ) 2 log 10 (mean acuity in Cy / deg DHA-free group )) / 0.301 Estimates of standard errors of the mean (S.E.M.) from each study were necessary for deriving combined estimates and were calculated in octaves as: ((S.E.M. DHA-supplemented group )2 1 (S.E.M. DHA-free group )2 )0.5

2.2. Meta-analysis The DerSimonian and Laird [37,38] random-effects method was used to obtain combined estimates of visual resolution acuity differences and their standard errors within seven age categories. A random-effects model was chosen because it accounts for the possibility of among-study, as well as within-study, heterogeneity. The DerSimonian and Laird method provides a weighted mean of the study results where the weights are partly determined by the size of the individual studies and partly by the amount of variation among their results. In the case that the between study variance is negligible, the DerSimonian and Laird random-effects model degenerates to a fixed-effects model. The fixed-effects model assumes sampling occurs from a homogeneous universe of study populations; as such, reported standard errors are smaller than those that would be produced by the random-effects model. Analyses were conducted in SAS for Windows version 6.12 (Cary, NC) with software developed at the Harvard School of Public Health by Dr Catherine Berkey. A priori subgroup analyses were specified to include separate evaluation of randomized (DHA-supplemented formula vs. DHA-free formula) and non-randomized (human milk diet vs. DHA-free diet) comparisons of dietary groups.

3. Results Experiment-based characteristics are summarized in Table 1. Studies varied widely in geographic location, the number of sites, the number of vision testers, and the vision testing protocol. All studies were conducted in industrialized countries

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(Australia, Canada, Denmark, and the United States of America). All stimuli used in behaviorally based tests were a form of square-wave grating. The majority of behavioral tests were conducted with the ACP, but the FPL was also used frequently. There was some degree of variability in the spatial frequency of the initial stimulus. In studies employing the ACP, the order of stimulus presentation went from low to high spatial frequency (from wide to thin stimulus spatial attributes). In studies using the FPL, studies stimulus presentation order was randomized. Most studies employed an ophthalmic exam or pre-experiment screening criteria to rule out the effects of optical or ophthalmic problems. The protocols of the electrophysiologic tests also varied considerably. Table 2 shows that a number of different dietary groups were used across studies and that the duration of exclusive feeding was approximately 3–4 months of age. Different patterns of solid food supplementation were also evident. Some studies attempted to attain strong compliance in the protocol; other studies did not report on this issue. Different sources of LCPUFAs included human milk, egg yolk, single cell oil, and fish oil. Age at test was calculated with different methods and was not always corrected for gestational age at birth. Dietary characteristics in Table 3 indicate that levels of DHA and arachidonic acid (AA) intake varied across studies. Among groups receiving a dietary source of LCPUFAs, DHA intake ranged from 0.12 to 0.53 g / 100 g lipids and AA intake ranged from 0.01 to 0.60 g / 100 g lipids. The lipid profile also was different across studies for EFA precursors to LCPUFAs (a-LLNA and linolenic acid (LA)) and other LCPUFAs, like eicosapentanoic acid (EPA). The ratio of LA / a-LLNA ranged from 7.13 to 36.75 and EPA ranged from 0.05 to 0.58 g / 100 g lipids. Tables 4 and 5 report visual resolution acuity differences in octave scale by dietary groups and assessment technique. The results of studies listed under the heading FF 1DHA vs. FF 2DHA represent acuity differences obtained in randomized comparisons and should be considered to provide the strongest evidence of effect. A value of 1.0 is equivalent to doubling the width of stimulus elements. Only comparisons with acuity differences significantly greater than zero will be discussed in the text.

3.1. Behaviorally based acuity differences One of two acuity differences was significantly less than zero at #1 month. At 2 months, four of nine acuity differences were significantly greater than zero. At 4 months, two of 11 were significantly greater.

3.2. Electrophysiologically based acuity differences Three of six acuity differences at 2 months were significantly greater than zero. At 4 months, five of ten were significantly greater. At 6 months, one comparison was significantly less than zero. Two of two were significantly greater than zero at 7 months and six were significantly greater than zero at 12 months.

Intake group

HM FF 1DHA1AA FF 1DHA FF 2DHA HM FF 2DHA HM 3.0 months FF 1DHA1AA FF 1DHA FF 2DHA1 FF 2DHA2 HM 0.5 months HM 3.0 months FF 2DHA 1 FF 2DHA 2 HM FF 1DHA1AA FF 2DHA

Study

Birch et al. (1998) [39]

Courage et al. (1998) [40]

Auestad et al. (1997) [41]

Innis et al. (1997) [42]

Carlson et al.(1996) [43]

NM 0.10 0.00

0.30 (0.10) 0.20 (0.10) 0.00 0.00

NM* 0.12 0.23 0.00 0.00

0.20 (0.20) 0.00

0.29 0.36 0.35 0.00

DHA 22:6n-3

NM 0.43 0.00

0.60 (0.10) 0.50 (0.10) 0.00 0.00

NM* 0.43 0.00 0.00 0.00

0.40 (0.10) 0.00

0.56 0.72 0.02 0.00

AA 20:4n-6

Composition [g/100 g lipid (S.D.)]

Table 3 Lipid composition of formulas reported in reviewed studies a

NM 0.00 0.00

0.05 0.05 0.00 0.00

NR 0.00 0.07 0.00 0.00

0.10 (0.10) 0.00

0.10 0.00 0.00 0.00

EPA 20:5n-3

NM 2.00 2.20

1.00 (0.40) 1.20 (0.60) 1.90 4.70

NR 1.90 1.90 2.20 4.80

1.2 (0.40) 4.9 (0.20)

0.80 1.53 1.54 1.49

a-LLNA 18:3n-3

NM 21.80 21.90

14.40 14.60 18.00 34.20

NR 21.70 20.70 21.90 34.20

12.1 (2.9) 30.5 (0.50)

12.7 14.90 15.10 14.60

LA 18:2n-6

NM 10.9 10.0

14.4 12.2 9.5 7.3

NR 11.4 10.9 10.0 7.1

10.1 6.2

9.8 9.8 9.7 15.9

18:2n-6/18:3n-3

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HM 2.0 months HM 4.0 months FF 2DHA

0.43 (0.24) 0.53 (0.56) 0.00

0.47 (0.07) 0.44 (0.09) TR

0.13 (0.04) 0.23 (0.35) TR

1.39 (0.47) 1.52 (0.24) 1.70

10.97 (2.47) 11.38 (3.36) 14.40

7.9 7.5 8.5

Makrides et al. (1995) [48]

HM FF 1DHA FF 2DHA

0.21 (0.13) 0.36 (0.03) 0.00

0.40 (0.07) 0.01 (0.01) 0.00

0.07 (0.04) 0.58 (0.04) 0.00

0.94 (0.25) 1.52 (0.02) 1.58 (0.01)

13.92 (3.02) 16.79 (0.08) 17.44 (0.16)

14.8 11.1 11.0

Innis et al. (1994) [45]

HM FF 2DHA

0.20 (0.09) 0.00

0.50 (0.12) 0.00

0.10 (0.04) 0.00

1.50 (0.55) 2.10

13.40 (3.26) 17.90

8.9 8.5

Birch et al. (1993) [46]

HM FF 2DHA

NR 0.00

NR 0.00

NR 0.00

0.80 0.80

12.70 29.40

15.9 36.8

Makrides et al. (1993) [49]

HM FF 2DHA

NM 0.00

NM 0.00

NM 0.00

NM 1.30

NM 13.50

NM 10.4

Birch et al. (1992) [47]

HM FF 2DHA

NR 0.00

NR 0.00

NR 0.00

0.80 0.80

12.70 29.40

15.9 36.8

a

Note: HM, human milk; FF, formula-fed; NM, not measured; NR, not reported; TR, trace amounts (#0.05 g / 100 g); DHA, docosahexanoic acid; AA, arachidonic acid; EPA, eicosapentanoic acid; a-LLNA, alpha linolenic acid (the precursor to DHA); LA, linoleic acid; * Values were presented in the text from a superset of women containing some mothers whose infants were part of the Portland cohort of this multicenter study; here DHA50.1860.09 g, AA50.4760.09 g per 100 g of total lipids, EPA50.0760.03, a-LLNA51.360.6.

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Jorgensen et al. (1996) [44]

177

178 Table 4 Behaviorally based visual acuity differences (octaves6S.E.M.) between infants receiving a source of docosahexanoic acid (DHA) and those consuming DHA-free diets a Behavioral test

Age at Test (months)† #1

2

3

4

6

9

12

FPL

–

–

ACP

–

Carlson et al. (1996) [43]

ACP

–

20.2860.20 or 20.2860.20 20.0160.16 or 20.0660.15 20.1860.16

20.0860.15 or 20.0860.18 0.1660.14 or 20.0760.13 0.0160.17

–

Auestad et al. (1997) [41]

0.2660.22 or 0.3360.21 0.1660.20 or 0.1560.22 0.546 0.16*

20.2060.20 or 20.1360.21 20.0160.13 or 20.1960.11 0.0360.16

HM vs. FF 2DHA Birch et al. (1998) [39] Courage (1998) [40] Auestad et al. (1997) [41] Innis et al. (1997) [42]

FPL ACP ACP ACP

– – – –

0.3360.21 – 0.4060.19* –

–

20.0360.20 – 0.0560.14 –

20.0260.16 0.1060.12 0.1260.12 –

– –

Carlson et al. (1996) [43] Jorgensen et al. (1996) [44] Innis et al. (1994) [45] Birch et al. (1993) [46] Birch et al. (1992) [47]

ACP ACP ACP FPL FPL

– 20.0760.08 20.6460.23* – –

0.6660.16* 0.4960.21* – – –

FF 1DHA vs. FF 2DHA Birch et al. (1998) [39]

a

– –

0.1560.11 – 0.1560.12 or 0.0660.13 – – 20.2860.17 – –

0.0060.16 0.7060.41 – 0.2760.13* 0.4260.14*

0.1860.17 – – – –

20.0460.14 or 20.1860.12 20.0860.17

–

20.0360.20 – 20.0560.09 –

20.1660.17 – – – –

– – – –

0.0360.10

0.0860.17

Note: Randomized comparisons are represented in italicized text. Results reported from randomized studies represent differences in performance between infants fed formulas enriched with DHA (1DHA) and infants fed formulas devoid of DHA (2DHA). Results reported from non-randomized studies represent differences in performance between infants fed human milk and infants on 2DHA diets. The duration of exposure is not constant between studies. Values for Auestad et al., Carlson et al., Jorgensen et al., and Makrides et al. were communicated directly from the authors. S.E.M. values for the Birch et al. studies are estimated from a range of values reported in the text or derived from test statistics that they have provided in other publications. * Differences between groups are significantly greater than those expected to occur by chance. † Classification is based upon ages at test, and not duration of DHA intake. For the Birch et al. 1998 measures of dispersion were not reported for human milk groups; an estimate of the S.E.M. for this dietary group was derived from the median value reported for the three other groups. FF, formula-fed; HM, human milk; ACP, Acuity Card Procedure; FPL, Forced Choice Preferential Looking Procedure; (–) Age group not tested.

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Dietary regimen

Dietary regimen

FF 1DHA vs. FF 2DHA Birch et al. (1998) [39]

VEP

Age at test (months)†

protocol

2

4

5

6

7

9

12

Steady-state

0.2660.13* or 0.2360.14 20.0960.09 or 20.1360.12 0.6660.20*

–

–

–

–

–

–

0.1660.14 or 0.0560.11 20.0260.12 or 20.1960.13 –

20.1260.10 or 20.1160.11 –

0.4260.15* or 0.4460.15* 0.0060.10 or 20.1660.11 –

0.2660.14 20.0360.10 0.8060.15* 0.3760.24* – 0.5060.17*

– – – – 1.0660.47* –

0.2160.14 20.2660.11* – – – –

– 20.1260.11 – – – –

0.5260.14* 20.0560.11 – – – –

Auestad et al. (1997) [41]

Steady-state

Makrides et al. (1995) [48]

Transient

0.5560.14* or 0.6060.12* 20.0360.16 or 20.0760.18 –

Steady-state Steady-state Transient Steady-state Transient Steady-state

0.5560.12* 20.2360.15 – – – –

HM vs. FF 2DHA Birch et al. (1998) [39] Auestad et al. (1997) [41] Makrides et al. (1995) [48] Birch et al. (1993) [46] Makrides et al. (1993) [49] Birch et al. (1992) [47] a

Note: See note for Table 4. VEP, visual evoked potential.

1.0360.42*

– – 1.1660.29* – –

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Table 5 Electrophysiologically based visual acuity differences (octaves6S.E.M.) between infants receiving a source of docosahexanoic acid (DHA) and those consuming DHA-free diets a

179

180

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3.3. Meta-analysis results Results of the meta-analysis are reported in Table 6 and Fig. 1. Combined acuity differences are presented by test type (behavioral vs. electrophysiologic) and design (random vs. non-random). Positive difference values represent a beneficial (although not necessarily clinically significant) effect of DHA. Comparisons have not been collapsed across electrophysiologically and behaviorally based tests for the reasons that: (1) some subjects tested with behavioral methods were also tested with electrophysiologic methods; and, (2) behavioral and electrophysiologic tasks may tap different visual processes. Only acuity differences significantly different than zero at a P value of #0.05 will be described in the text.

3.3.1. Randomized studies Acuity differences are significantly greater than zero at 2 months of age for behaviorally based measures. The combined acuity difference at this age is 0.3260.09 octaves (estimate6S.E.M., P50.003). This estimate was computed with a total of 114 infants in the DHA-supplemented groups and 87 infants in the DHA-free groups. For electrophysiologically based outcomes, there were no instances in which acuity differences were significantly different than zero.

3.3.2. Non-randomized study designs Acuity differences for behaviorally-based tasks are 0.4960.09 octaves (P# 0.000001) at 2 months of age and 0.1860.08 octaves (P50.04) at 4 months of age. Combined acuity differences for the 2-month-old infants are computed from human milk-fed groups of 117 infants and groups of 174 infants consuming DHA-free diets. The corresponding values for the 4-month-olds are 148 and 113 infants, respectively. In the case of electrophysiologic-based tasks, acuity differences between human milk-fed infants and those consuming a DHA-free diets are also significantly greater than zero (0.3760.16 octaves, P50.02) at 4 months of age. These estimates are derived from groups composed of 146 human milk-fed infants and 108 infants consuming DHA-free formula.

3.3.3. All study designs The combined estimate of behaviorally based acuity differences for all study design types (randomized1non-randomized group comparisons) at 2 months is 0.4060.06 octaves (P#0.000001). For this analysis there is a total of 219 infants in the dietary DHA-present groups and 86 infants in the dietary DHA-free groups. Electrophysiologically measured differences are greater than zero at 4 months of age (0.2660.10, P50.009). This estimate is based on groups composed of 265 infants consuming a source of DHA and 109 infants on a DHA-free diet. Significant positive effects were also observed at 7 months of age, but both comparisons came from the same laboratory.

Age at test (months)

#1 2 3 4 5 6 7 9 12

Behavioral tests Randomized FF 1DHA vs. FF 2DHA – 0.3260.09 (5)* – 20.1460.08 – 20.0160.07 – 20.1160.08 20.1060.07

(5) (5) (3) (5)

Electrophysiologic tests Non-randomized HM vs. FF 2DHA

All groups

20.3160.28 0.4960.09 0.0560.09 0.1860.08 – 0.1060.07 – 0.0260.09 20.0260.07

20.3160.28 (2) 0.4060.06 (9)* 0.0560.09 (4) 0.0360.07 (11) – 0.0560.05 (9) – 20.0760.06 (5) 20.0660.05 (8)

(2) (4)* (4) (6)‡ (4) (2) (3)

Randomized FF 1DHA vs. FF 2DHA

Non-randomized HM vs. FF 2DHA

– 0.2860.18 (4) –

– 0.1660.39 (2) –

0.1560.12 (5) – 0.0060.07 1.0360.42 20.1260.08 0.1660.15

(4) (1)‡ (2) (4)

All groups

0.3760.16 1.0660.47 20.0260.23 1.1660.29 20.1260.11 0.2360.28

– 0.2460.15 (6) –

(5)† (1)‡ (2) (1)‡ (1) (2)

0.2660.10 (10)† – 20.0160.08 1.1160.24 20.1260.06 0.1860.12

(6) (2)‡ (3) (6)

a Note: Behavioral tests included Forced Choice Preferential Looking Procedure (FPL) and the Acuity Card Procedure (ACP) (see Table 4). Electrophysiologic tests included transient and steady-state visual-evoked potential (VEP) (see Table 5). * P#0.0005, † P#0.02, ‡ P#0.05. FF, formula-fed; HM, human milk; (–) Age group not tested. Results from randomized studies represent differences in acuity between infants fed formulas enriched with DHA (FF 1DHA ) and infants fed formulas devoid of DHA (FF 2DHA ). Results from non-randomized studies represent differences in acuity between infants fed human milk and infants on FF 2DHA diets.

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Table 6 Combined estimates of visual acuity differences in octaves6S.E.M. (number of studies): comparisons are between fullterm infants receiving dietary sources of docosahexaenoic acid (DHA) and those receiving no dietary DHAa

181

182

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Fig. 1. Visual acuity differences. Open symbols represent randomized comparisons (formula fed groups with LCPUFAs vs. formula fed groups without LCPUFAs). Shaded small symbols represent nonrandomized comparisons (human milk vs. formula without LCPUFAs). Diamonds represent combined acuity difference estimates of randomized comparisons. (A) Acuity differences measured with behaviorally based tests. (B) Acuity differences measured with visual evoked potentials.

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183

4. Discussion Results in Table 6 indicate, that if intake of DHA during infancy influences visual development, the effect is small to moderate. Randomized comparisons showed acuity differences as significantly greater than zero only at 2 months of age with and only with behaviorally based outcomes; the size of the acuity differences after this age is small or negligible. Table 5 shows the wide range across which significant differences in acuity have been observed when the visual evoked potential is used and, unlike the results in Table 4, effects are seen in both randomized and nonrandomized comparisons. Table 4 indicates that, mainly in the non-randomized comparisons, individual behaviorally based studies tend to show significant acuity increases from zero at ages #4 months. This pattern of results has been referred to as a transient effect of dietary supplementation, but it could have more to do with age-based changes in the psychometric properties of the testing instruments across periods in which feeding regimens are strict (prior to the introduction of solid foods). The information presented in Tables 1–3 indicates a need for more rigorous designs and more detailed reporting practice. Sources of variation in behaviorally based outcome measures, as described by Mayer and Dobson [36], are a function of the quality of testing conditions, the level of tester training and monitoring, ocular and / or optic conditions in the subject, calculation of age at test, and differences in the protocol. Test-based factors were usually reported, although tester- and subject-based factors were less likely to be. Using multiple testers in heterogeneous populations can contribute substantial random variation and hence attenuate results. There is currently no consensus on what levels of DHA intake would lead to saturation of tissue membranes. A World Health Organization (WHO) / Food and Agriculture Organization (FAO) Expert Committee [50] has recommended that the level of DHA present in human milk and the volume of human milk that is usually consumed should be used for determining the levels necessary for optimal structural and functional visual development. Levels of DHA in human milk vary widely between different geographically and ethnically defined populations. The WHO / FAO Committee also has recommended that: (1) fullterm infant formula contain 3.5% fat, of which 0.38% is DHA; and (2) pre-term infant formula contain 4.0% fat, of which 0.60% is DHA. The recommended fullterm formula concentration is approximately 20 mg DHA / kg bodyweight; the pre-term formula concentration is approximately 40 mg DHA / kg bodyweight. A number of other national and international expert committees have also published position papers on this issue [51–53]. In this analysis we have classified dietary groups through a dichotomous scheme as ‘no dietary DHA’ versus the level of DHA possibly available in human milk. If one accepts the FAO / WHO recommendations, it is important to note that only one study included in analyses provided levels over 0.30 g / 100 g lipids and that most of the comparison dietary groups analyzed were fed a DHA-free diet only until approximately 4 months. Clandinin et al. [54] have determined that supplementation of dietary DHA and AA in preterm infants at concentrations of 0.24–0.76 g / 100 g and 0.32–1.1 g / 100 g of lipids leads to dose-dependent accretion of DHA in RBC phospholipids similar to that of preterm infants fed human milk; to the extent that

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RBC phospholipids reflect neural tissue stores, this information may be important in the formation of nutritional policy. Most non-randomized studies have not reported of DHA levels in human milk. While these studies do not allow adjustment for uncontrolled confounding, they may provide useful information on dose–response relationships, if LCPUFA levels are reported. In general, more rigorous control of exposure variables is needed in order to make more definitive statements about causal processes within randomized studies. There are still many unanswered questions about what influences maternal-to-fetal accretion and how much dietary DHA is incorporated into neural membranes at the postnatal times. One of these factors may be n-6 / n-3 dietary lipid composition [55]. As such, the changing patterns of dietary lipid composition (an increase in n-6 consumption and a decrease in n-3 consumption) may be an important factor in recommending diets to women of reproductive age [56]. The current analysis does not take DHA status at birth into consideration because in most cases it is not reported. From a review of post-mortem studies and the few studies in living infants that report these values, it appears that a significant difference in DHA neural and RBC tissue status occurs initially at 2 months post-birth. The most accessible dietary source of LCPUFAs is marine animal products. There may be much to learn from testing healthy populations that may have intake and biosynthetic insufficiencies in n-3 LCPUFAs because of dietary practices; these groups include: (1) vegans; (2) Jain Hindus who do not consume animal products; (3) Seventh Day Adventists who do not consume animal products. It would be helpful to determine DHA intake and precisely characterize exposure in terms of intensity, duration, and ‘developmental timing.’ Information on maternal preconceptional and perinatal diet should be collected to assess effects of difference in DHA status in the perinatal period. Information on supplemental (non-liquid) feeding in the first months of life is also essential for accurately determining LCPUFA intake levels. Since a number of mineral cofactors such as zinc and selenium are involved in de novo synthesis of LCPUFAs, these should be measured. Issues related to the potential for sociodemographic heterogeneity of populations in fullterm infants are rarely discussed and could be measured with a variety of standardized techniques. Randomization may be effective in controlling for sociodemographic factors, but a large variance in physiologic function may attenuate any easily observable effect of differential exposure to DHA. Along these lines, the following questions require more research: (1) What are the levels of DHA considered sufficient to allow accretion to tissue lipids? (2) Is there a specific duration of intake necessary to ensure adequate accretion? (3) Is there a certain age range during which the effects of intake will influence structure and function more than at others? Fig. 2 presents sample size curves based upon the combined estimates from Table 6 at 2 and 4 months, with a standard deviation of 0.50 octave, a 50.05, and a two-tailed test. The S.D. used for sample-size estimation was obtained from a literature review of studies using acuity cards and represents a conservative estimate of variance in the case of a single-site study using two to three experienced testers [36]. While researchers have made efforts to control non-liquid feeding, the potential for

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185

Fig. 2. Sample-size curves. Curves are calculated for combined acuity differences for all comparisons, with a standard deviation of 0.50 octaves and a two-tailed a 50.05. (A) Two months of age. (B) Four months of age.

receiving some source of DHA was higher in all dietary groups as age increased. It is not surprising that the estimated magnitude of effect was lower across all ages for randomized blinded comparisons (DHA-supplemented vs. no DHA) vs. non-randomized comparisons (human milk-fed vs. no DHA); this relationship was observed across most age groups and test types. As age increased, the magnitude of acuity difference approached zero; this may be explained by a convergent similarity in non-liquid diets with age.

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Finally, one must consider the larger questions of how a more responsive visualbased system at 2 months of age may confer some developmental advantage across the life-span. The transient nature of differences in grating acuity between the dietary groups may lead to permanent alterations in the functional capacity of the visual system [10]. The issue here centers upon quality of stimulation early in life and the potential for such information to affect the development of brain systems using visual input [3,13,57,58].

Acknowledgements The authors would like to acknowledge Dr D. Luisa Mayer for her advice on technical matters related to visual resolution acuity measurement and representation. We also wish to acknowledge the support of the Auestad, Carlson, Connor, Innis, Jorgensen, and Makrides research groups in generously providing us with supplemental information. Dr San Giovanni was a doctoral student at the Harvard School of Public Health during the completion of this work. Partial support for Dr Dwyer was provided by the Gerber Foundation. Drs Berkey and Colditz were supported by Boston Obesity Nutrition Research Center Grant DK46200

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