Identifying Foods That Optimize Intake of Key Micronutrients During Pregnancy

Abstract

Background

Most pregnant women in the United States are at risk of inadequate intake of vitamin A, vitamin D, folic acid, calcium, iron, and omega-3 fatty acids from foods alone. Very few United States dietary supplements provide sufficient doses of all 6 nutrients without inducing excess intake.

Objective

We aimed to identify energy-efficient foods that provide sufficient doses of these nutrients and could be consumed in lieu of dietary supplements to achieve the recommended intake in pregnancy.

Methods

In a previous analysis of 2,450 pregnant women, we calculated the range of additional intake needed to shift 90% of participants to intake above the estimated average requirement and keep 90% below the tolerable upper level for these 6 nutrients. Here, we identified foods and beverages from the 2019 to 2020 Food and Nutrient Database for Dietary Studies that provide target levels of these nutrients without exceeding the additional energy intake recommended for pregnancy beginning in the second trimester (340 kilocalories).

Results

We identified 2358 candidate foods meeting the target intake range for at least one nutrient. No candidate foods provided target amounts of all 6 nutrients. Seaweed (raw or cooked without fat) provided sufficient vitamin A, folate, calcium, iron, and omega-3s (5 of 6 nutrients) but would require an intake of >5 cups/d. Twenty-one other foods/beverages (mainly fish, vegetables, and beverages) provided target amounts of 4 of the 6 nutrients. Few foods met targets for vitamin D (n = 54) or iron (n = 93).

Conclusions

Results highlight the difficulty in meeting nutritional requirements from diet alone and imply that dietary supplements are likely necessary to meet vitamin D and iron targets in pregnancy, as well as omega-3 fatty acid targets for individuals who do not consume fish products. Other foods could be added in limited amounts to help meet intake targets without exceeding caloric recommendations or nutrient safety limits.

Introduction

Inadequate and/or excessive intake of nutrients in pregnancy is associated with adverse maternal and offspring health outcomes [[1], [2], [3], [4], [5], [6]]. More than half of pregnant women in the United States are at risk of inadequate intake of vitamin D, folate, and iron based on food intake alone, and one-third are at risk of inadequate intake of vitamin A and calcium [7]. Although dietary supplement use is common (>70% of pregnant women) [8] and can help ensure adequate micronutrient intake in pregnancy, there are multiple challenges in relying on dietary supplements to address micronutrient deficiencies in the United States. First, current United States supplementation practices do not eliminate risk of inadequate intake and may inadvertently place up to 50% of women at risk of excessive intake of other micronutrients [7, 9]. Second, the United States Food and Drug Administration regulates dietary supplements as foods rather than drugs and, therefore, does not monitor the efficacy of dietary supplements nor require third-party verification of supplement contents [10]. Products marketed for pregnant women must reference the daily value defined by the Federal Drug Administration (FDA) for pregnant or lactating women but are not required to undergo special testing or oversight for promotion to this population [11]. This includes prescription prenatal vitamins that are made available by provider prescription to facilitate reimbursement by third-party payers, including Medicaid [12], but are not registered as prescription drugs subject to premarket evaluation by the FDA [13]. As such, the integrity and efficacy of United States dietary supplements, including prescription prenatal supplements, are uncertain. Third, some pregnant women experience gastrointestinal side effects with supplementation, particularly of iron, resulting in low or inconsistent adherence [14]. Fourth, higher-quality supplements may be more costly and/or not covered by insurance, restricting access for individuals with limited resources. Thus, modifying food intake may be preferable to dietary supplements for meeting micronutrient needs during pregnancy in the United States for some individuals.

The goal of this analysis was to identify foods that could be recommended to achieve intake targets for key nutrients among pregnant women in lieu of dietary supplements. The foods were selected by utilizing our previously published data on the distribution of usual intake in pregnancy from food sources alone among 2450 United States women pregnant from 2007 to 2020 [15]. Our previous publication focused on nutrients with the strongest evidence for a potential benefit for maternal-child health outcomes: vitamin A [16], vitamin D [17], folate/folic acid [18, 19], calcium [20, 21], iron [19], and omega-3 fatty acids [22]. In this previous analysis, we calculated the range of additional intake needed to shift 90% of pregnant women to intake above the estimated average requirement but keep intake of 90% below the tolerable upper level for each nutrient. We had identified only one dietary supplement currently available in the United States that provided doses within these ranges for all 6 nutrients. Unfortunately, this product is inconvenient (consists of 7 pills/d) and may be cost-prohibitive (∼$200/mo for this over-the-counter product). To help pregnant women who wish to use food-based alternatives to dietary supplements to improve nutrient intake, we now aim to identify foods and beverages that could bridge the gap between usual food-based intake and estimated requirements of key micronutrients in pregnancy.

Materials and Methods

The participants, data collection procedures, and analytic methods used to estimate usual intake during pregnancy were described previously [15]. Briefly, we analyzed dietary intake data collected from pregnant participants in the National Institutes of Health Environmental influences on Child Health Outcomes (ECHO) observational cohorts program [23]. ECHO is a consortium of 69 observational cohorts of mothers and offspring established to understand the effects of early life exposures on child health and development. Sixteen cohorts assessed dietary intake during pregnancy from 1999 to 2019, with 6 using 24-h recall methods and 10 using food frequency methods. This analysis included 2,450 participants from the 6 cohorts using recall methods (Supplemental Table 1) because of evidence that food frequency questionnaires may overestimate micronutrient intake relative to recalls [24] and biomarker recovery studies [25]. All data collection protocols were approved by the institutional review boards with jurisdiction, and participants provided informed consent. Participant-level sociodemographic, pregnancy, and weight data were collected via self-report at enrollment and/or medical records.

Dietary intake data

Dietary intake was assessed via 24-h recalls that queried all foods, beverages, and dietary supplements consumed in the prior 24 h using standardized and validated methods [26, 27]. We excluded dietary supplement data from this analysis as our goal was to understand intake from food alone. Participants completed 1 or more 24-h dietary recalls at times ranging from 6 wk gestation until delivery. Individual cohorts processed dietary data locally using appropriate databases for nutritional content at the time of data collection (2007–2020). For each recall, cohorts provided food-based intake data (excluding dietary supplements) for vitamin A (total retinol activity equivalents and preformed retinol only), vitamin D (total), folate (total dietary folate equivalents and synthetic folic acid only), calcium (total), iron (total), and omega-3 fatty acids (total eicosapentaenoic acid + docosapentaenoic acid + docosahexaenoic acid).

Dietary Reference Intakes

We defined target intake with the estimated average requirement (EAR) and tolerable upper intake level (UL) for pregnant women specified by the Dietary Reference Intakes (DRIs) [28]. The EAR reflects the average daily nutrient intake level estimated to meet the requirements of half of the healthy individuals in a group. The UL is the highest daily nutrient intake likely to pose no risk of adverse health effects to most individuals. Risk of inadequacy for a population can be estimated with the cut-point method, whereby the percentage of individuals with intake below the EAR or above the UL reflects the percentage at risk of inadequate or excessive intake, respectively [29]. For omega-3 fatty acids, the EAR and UL are not defined. We selected a target of 100 mg/d based on meta-analytic findings of the benefits of long-chain omega-3 fatty acids for perinatal outcomes [22].

Food and beverage data

The Food and Nutrient Database for Dietary Studies (FNDDS) is a publicly available database of all foods and beverages (hereafter referred to as foods) consumed in the United States as reported by participants of the What We Eat In America, the dietary component of the National Health and Nutrition Examination Survey (NHANES) [30]. It includes nutrient profiles of all foods, along with preparation and portion size. It is updated every 2 y in conjunction with the NHANES data releases; the latest version (2019–2020) was released in October 2022 [31].

Statistical analyses

As previously reported [15], participant-level demographic and dietary data were provided by cohorts to the ECHO Data Analysis Center for analysis, including nutrient data for each recall day. We used macros developed to implement the National Cancer Institute method to produce the mean and standard error for usual intake and the percentiles of intake using an analytic approach to adjust the intake distribution for random within-person error (ie, day-to-day variation) using information provided from repeat recalls [32]. This method has been shown to be valid for obtaining usual intake distributions even when not all participants have repeated recalls [33, 34]. The statistical model fit using this procedure incorporated covariate adjustment for the day of the week of the dietary recall (weekday vs. weekend) and a random effect accounting for the clustering of participants within ECHO cohorts. Dietary intake analyses were conducted separately for participants aged 14 to18 y versus 19 to 50 y because intake varies by age [9], and the DRIs for pregnancy vary by age [28]. Based on the 10^th and 90^th percentiles of usual intake for each age group, we calculated the minimum and maximum amounts of each nutrient needed to shift 90% of participants above the EAR (or 100 mg/d for omega-3 fatty acids) and keep 90% of participants below the UL. For simplicity, we defined the overall range as that which would provide sufficient (but not excessive) intake for both age groups. For example, in our data, younger participants required 383 to 1598 mg to meet the calcium target, whereas older participants required 95 to 943 mg; thus, the overall range was defined as 383 to 943 mg for calcium.

Candidate foods to recommend for pregnant women were identified through a stepwise process based on all foods in FNDDS 2019 through 2020. First, we excluded foods that did not contain any of the 6 nutrients of interest. We also excluded foods that were either not appropriate for pregnant women (eg, infant foods, alcoholic beverages) or too vague to inform a recommendation (mixed dishes without specific recipes, duplicates, foods that were nonspecific as to type, form, preparation method, or type of fat). We then calculated the number of portions needed from each food or beverage to meet target amounts for each nutrient, using standard serving sizes defined by What We Eat In America (eg, for milk, 8-oz cup servings instead of 100 g servings). We excluded foods that did not provide target amounts of any nutrient with a limit of 340 kcal/d. This limit reflects the additional intake recommended for pregnancy beginning in the second trimester [35], which we deemed a reasonable average target given calorie allowances are lower in the first trimester, higher in the third trimester, and vary by body size. Whereas we recognize that higher calorie limits could be appropriate if participants first reduced consumption of high-calorie, nutrient-poor foods, we focused this analysis on foods that can supplement usual intake to meet nutrient targets without requiring broader dietary modifications (mirroring the way that dietary supplements augment one’s diet, generally without modifying). We also excluded foods that exceeded the UL for any one nutrient at the serving size required to meet the minimum targets for all other nutrients (eg, if the serving size required to meet the vitamin D target for a food resulted in excessive calcium or iron intake). We identified the number of nutrient targets that could be met by each food or beverage without exceeding 340 kcal and the minimum target portion that met as many nutrients as possible at <340 kcal (eg, if 0.2 portions were needed to meet vitamin A targets but 0.4 portions were needed to meet vitamin D targets, the minimum target portion was set at 0.4).

Last, we identified the 100 lowest calorie foods that meet individual targets for each nutrient. Among these, we highlight foods most reasonable to recommend at the population level by ensuring they fulfilled the following criteria: 1) were readily available in stores (determined by reviewing common national grocery chain websites in February 2023), 2) were not discouraged during pregnancy (eg, raw seafood), 3) had lower calorie or lesser added sugar forms (eg, baked tilapia versus fried tilapia), 4) matched typical forms of preparation (eg, low-fat milk versus reconstituted dry low-fat milk), 5) had the simplest forms of preparation (eg, fresh raw carrots versus cooked canned carrots), 6) were not highly processed (eg, milk versus fortified diet soft drinks), and 7) required only reasonable portions to meet targets (eg, 2 cups of Boston lettuce is a serving which seems more reasonable than 8 cups of arugula for meeting the vitamin A target).

Results

Participants

Characteristics of the 2450 participants in our analytic sample are presented in Table 1. Our sample was diverse in terms of self-identified race and ethnicity (43% identified as non-Hispanic White, 33% as Hispanic, 14% as non-Hispanic Black), education (33% had high school degree or less; 37% had a 4-y college degree or more), and prepregnancy weight classification (44% lean weight, 51% with overweight or obesity). Participants completed 6106 recalls total, with 76% completing ≥2 recalls.

TABLE 1.

Characteristics of pregnant female participants (n = 2,450)

	Mean (SD) or n (%)
Age (y)	28.1	6.0
≤18	141	6%
19-50	2309	94%
Self-identified race and ethnicity (n)
Hispanic, any race	813	33%
Non-Hispanic, American Indian, Native Hawaiian	63	3%
Non-Hispanic, Asian	68	3%
Non-Hispanic, Black	353	14%
Non-Hispanic, White	1062	43%
Non-Hispanic, multiple or other races	66	3%
Race and/or ethnicity unknown	25	1%
Education
<High school degree	330	13%
High school diploma or GED	495	20%
Some college or 2 y degree	546	22%
4 y degree or more	916	37%
Missing	163	7%
Prepregnancy BMI
Underweight (<18.5 kg/m2)	61	2%
Lean (18.5-24.9 kg/m2)	1075	44%
Overweight (25-30 kg/m2)	625	26%
Obese (≥30 kg/m2)	610	25%
Missing	79	3%
Number of 24-h dietary recalls completed
1	597	24%
2	1001	41%
3 or more	852	35%

GED, General Educational Development.

Dietary intake

Usual intake of vitamin A (all forms), retinol only, vitamin D, folate (all forms), folic acid only, calcium, iron, and omega-3 fatty acids from food sources alone at the 10^th and 90^th percentiles are reported in Supplemental Table 2. The range of additional intake needed to bring 90% of participants above the EAR (or 100 mg/d for omega-3 fatty acids) whereas keeping 90% of participants below the UL for each nutrient was ≥198 μg of retinol activity equivalents of total vitamin A (with ≤2063 μg of preformed retinol); 7 to 91 μg of vitamin D; 169 to 720 μg dietary folate equivalents of folic acid; 383 to 943 mg of calcium; 13 to 22 mg of iron; and ≥59 mg of omega-3 fatty acids.

Foods

The 2019-2020 FNDDS contained 5,624 foods. We excluded 3266 foods from consideration (Supplemental Figure 1) and classified the remaining 2358 candidate foods according to the number and type of key nutrients they provided in a) any amount, b) the minimum target amount without exceeding 340 kcal, and c) the minimum target amount without exceeding either 340 kcal or the maximum target amount for any nutrient (Table 2). Of the 2358 candidate foods, 470 contained all 6 key nutrients, but none provided the minimum target amounts for all 6 nutrients at <340 kcal (range of kcal required: 892 to 383,500; median 9633). Two foods provided the minimum target amounts for 5 nutrients (vitamin A, folate, calcium, iron, and omega-3 fatty acids) at <340 kcal without exceeding any maximum target amounts: seaweed (raw) and seaweed (cooked without added fat). Specifically, a daily intake of 234 kcal of either food would be required, corresponding to 7.1 cups of raw seaweed or 5.7 cups of cooked seaweed. Another 21 foods (n = 1 fish protein, n = 2 beverages, n = 18 green vegetables) provided the minimum target amounts for 4 nutrients at <340 kcal without exceeding any maximum target amounts (Table 3). The portions necessary to meet these targets were 1.2 cups/d for fish (canned mackerel), 1.2 cups/d for a ready-to-drink nutritional shake, 82.5 cups/ d for chamomile tea, and ranged from 2.6 to 58.0 cups/ d among the 18 green vegetables (minimum: cooked spinach, maximum: raw lettuce).

TABLE 2.

Classification of candidate foods in the 2019-2020 Food and Nutrient Database for Dietary Studies based on nutrient contents and kilocalorie limits

Candidate foods and beverages:	Containing key nutrients	Meeting minimum nutrient amounts at <340 kcal	Without exceeding maximum amount for any nutrient
Total	2,358	992	958
Vitamin A	1,626	478	473
Vitamin D	841	63	54
Folate	2,149	441	432
Calcium	2,310	347	339
Iron	2,265	106	93
Omega-3 fatty acids	761	157	157
1 key nutrient	53	577	577
2 key nutrients	118	269	259
3 key nutrients	463	109	99
4 key nutrients	816	35	21
5 key nutrients	438	2	2
6 key nutrients	470	0	0

TABLE 3.

Foods and beverages in the 2019-2020 Food and Nutrient Database for Dietary Studies providing the minimum target amounts for ≥4 key nutrients at <340 kcal without exceeding any maximum target amounts for pregnancy.^∗

Foodcode	Description	Cups required	Calories	Vitamin A (RAE) [target: (≥198]	Retinol (μg) [target: ≤2063]	Vitamin D (μg) [target: 7-91]	Folate (DFE) [target: 169-720]	Folic acid (μg) [target: ≤424]	Calcium (mg) [target: 383-943]	Iron (mg) [target: 13-22]	Omega-3s (g) [target: ≥59]
95101000	Nutritional drink or shake, ready-to-drink (Boost)	1.2	305	476	476	7.5	217	127	383	5.7	0.00
92306700	Tea, hot, chamomile	82.5	198	198	0	0.0	198	0	396	15.8	0.00
26121180	Fish, mackerel, canned	1.2	248	207	207	11.6	8	0	383	3.2	2.12
75202011	Asparagus, fresh, cooked, no added fat	8.2	309	575	0	0.0	692	0	383	33.7	0.00
75100800	Asparagus, raw	11.8	319	606	0	0.0	830	0	383	34.2	0.00
72103030	Broccoli raab, cooked	3.5	277	825	66	0.0	379	0	656	13.0	0.00
72103000	Broccoli raab, raw	15.2	134	796	0	0.0	504	0	656	13.0	0.00
72104100	Chard, raw	33.5	229	3694	0	0.0	169	0	616	21.7	0.00
72110100	Cress, raw	20.0	320	3460	0	0.0	800	0	810	13.0	0.00
75205120	Green beans, canned, reduced sodium, cooked, no added fat	8.8	270	221	0	0.0	331	0	466	13.0	0.00
75113060	Lettuce, Boston, raw	46.4	151	4352	0	0.0	418	0	383	13.9	0.00
75113000	Lettuce, raw	58.0	284	4022	0	0.0	691	0	548	13.0	0.00
75114000	Mixed salad greens, raw	39.9	238	3676	0	0.0	769	0	545	13.0	0.00
75117010	Onions, green, raw	8.8	281	439	0	0.0	562	0	632	13.0	0.00
72116000	Romaine lettuce, raw	43.2	227	5593	0	0.0	574	0	544	13.0	0.00
75232110	Seaweed, cooked, no added fat	5.7	234	513	0	0.0	844	0	736	13.0	0.51
75513010	Seaweed, pickled	3.5	190	264	0	0.0	379	0	383	6.6	0.26
75127500	Seaweed, raw	7.1	234	542	0	0.0	992	0	736	13.0	0.51
75231012	Snowpea, frozen, cooked, no added fat	4.1	338	428	0	0.0	227	0	383	15.5	0.00
72125228	Spinach, canned, cooked with butter or margarine	2.6	245	2909	128	0.6	525	0	723	13.0	0.01
72125227	Spinach, canned, cooked with oil	2.6	284	2763	0	0.0	522	0	714	13.0	0.00
72125213	Spinach, canned, cooked, no added fat	2.6	130	2770	0	0.0	526	0	718	13.0	0.00
72125100	Spinach, raw	41.3	279	2920	0	0.0	1197	0	702	13.0	0.00

RAE, retinol activity equivalents; DFE, dietary folate equivalents

^∗Target amounts reflect the range of additional intake needed to bring 90% of participants above the EAR (or 100 mg/d for omega-3 fatty acids) while keeping 90% of participants below the UL for each nutrient

The 100 lowest calorie options for meeting individual nutrient targets are detailed in Supplemental Tables 3–8, with selected foods deemed most reasonable for population-level recommendations featured in Table 4.

TABLE 4.

Featured lowest calorie food and beverage options to meet individual nutrient targets.

Foodcode		Description	Portion		Calories
Options to achieve daily Vitamin A goal (≥198 μg retinol activity equivalents)
73105010	Beverages	Carrot juice, 100%	0.7	fl oz	8
92550400	Beverages	Vegetable and fruit juice drink, with high vitamin C, diet	6.3	fl oz	8
92552020	Beverages	Fruit juice drink, reduced sugar (Sunny D)	10.1	fl oz	6
81104010	Dairy	Margarine-oil blend, tub, light	0.1	cups	52
81104020	Dairy	Margarine-oil blend, stick, light	0.1	cups	52
63109010	Fruits	Cantaloupe, raw	0.6	cups	32
25110140	Meat and poultry	Liver, beef	0.13	oz	4
25110450	Meat and poultry	Liver, chicken	0.4	oz	13
25230560	Meat and poultry	Liverwurst	0.02	cups	15
72101100	Vegetables	Beet greens, raw	1.6	cups	14
72103000	Vegetables	Broccoli raab, raw	3.8	cups	33
72104100	Vegetables	Chard, raw	1.8	cups	12
72107211	Vegetables	Collards, fresh, cooked, no added fat	0.6	cups	26
72107213	Vegetables	Collards, canned, cooked, no added fat	0.4	cups	13
72110100	Vegetables	Cress, raw	1.1	cups	18
72116000	Vegetables	Romaine lettuce, raw	1.5	cups	8
72119190	Vegetables	Kale, raw	3.3	cups	35
72119221	Vegetables	Kale, fresh, cooked, fat added	0.6	cups	54
72122100	Vegetables	Mustard greens, raw	2.3	cups	35
72125100	Vegetables	Spinach, raw	2.8	cups	19
72125213	Vegetables	Spinach, canned, cooked, no added fat	0.2	cups	9
72126001	Vegetables	Taro leaves, cooked	0.5	cups	54
72128211	Vegetables	Turnip greens, fresh, cooked, no added fat	0.4	cups	10
72128213	Vegetables	Turnip greens, canned, cooked, no added fat	0.4	cups	13
73101010	Vegetables	Carrots, raw	0.2	cups	10
73201013	Vegetables	Pumpkin, canned, cooked	0.1	cups	14
73303010	Vegetables	Winter squash, cooked, no added fat	0.3	cups	28
73403010	Vegetables	Sweet potato, baked, no added fat	0.3	small	19
73407050	Vegetables	Sweet potato, canned, no added fat	0.2	cups	45
75113000	Vegetables	Lettuce, raw	2.9	cups	14
75113060	Vegetables	Lettuce, Boston, raw	2.1	cups	7
75114000	Vegetables	Mixed salad greens, raw	2.2	cups	13
75122200	Vegetables	Pepper, sweet, red, raw	0.8	cups	33
75210010	Vegetables	Cabbage, Chinese, cooked, no added fat	0.5	cups	13
Options to achieve daily Vitamin D goal (7-92 μg)
11112110	Dairy	Milk, reduced fat (2%)	2.6	cups	318
11112210	Dairy	Milk, low fat (1%)	2.6	cups	274
11113000	Dairy	Milk, fat free (skim)	2.6	cups	216
11114300	Dairy	Milk, lactose free, low fat (1%)	2.6	cups	274
11114320	Dairy	Milk, lactose free, fat free (skim)	2.6	cups	216
11114330	Dairy	Milk, lactose free, reduced fat (2%)	2.6	cups	318
11360000	Dairy	Rice milk	2.9	cups	329
26115120	Seafood	Fish, flounder, baked or broiled	10.0	oz	256
26118010	Seafood	Fish, halibut	7.0	oz	245
26121180	Seafood	Fish, mackerel, canned	0.7	cups	150
26133110	Seafood	Fish, snapper	3.2	oz	120
26137120	Seafood	Fish, salmon, baked or broiled	2.6	oz	140
26137180	Seafood	Fish, salmon, canned	0.4	cups	68
26137190	Seafood	Fish, salmon, smoked	0.3	cups	48
26139180	Seafood	Fish, sardines, canned	12.2	sardines	303
26151120	Seafood	Fish, trout, baked or broiled	1.8	oz	76
26158010	Seafood	Fish, tilapia, baked or broiled	9.0	oz	287
Options to achieve daily folate goal (≥169 dietary folate equivalents)
57151000	Grains	Cereal, rice crispy, plain	0.7	cups	61
57237100	Grains	Cereal, oat bunches	0.4	cups	65
57308400	Grains	Cereal, O's, multigrain	0.6	cups	62
57344000	Grains	Cereal, K's, plain	0.5	cups	58
25110450	Meat and poultry	Liver, chicken	1.5	oz	55
41305000	Vegetables	Lentils, from dried, no added fat	0.5	cups	114
41420020	Vegetables	Edamame, cooked	0.4	cups	83
72107211	Vegetables	Collards, fresh, cooked, no added fat	1.3	cups	55
72107213	Vegetables	Collards, canned, cooked, no added fat	1.1	cups	37
72110100	Vegetables	Cress, raw	4.2	cups	68
72125213	Vegetables	Spinach, canned, cooked, no added fat	0.8	cups	42
72128211	Vegetables	Turnip greens, fresh, cooked, no added fat	1.0	cups	29
72128213	Vegetables	Turnip greens, canned, cooked, no added fat	1.2	cups	37
75103000	Vegetables	Cabbage, green, raw	4.4	cups	98
75201013	Vegetables	Artichoke, canned, cooked, no added fat	6.3	hearts	101
75208011	Vegetables	Beets, fresh, cooked, no added fat	1.0	cups	79
75209012	Vegetables	Brussels sprouts, frozen, cooked, no added fat	1.1	cups	70
75210010	Vegetables	Cabbage, Chinese, cooked, no added fat	1.7	cups	41
75220012	Vegetables	Okra, frozen, cooked, no added fat	0.9	cups	49
75236500	Vegetables	Yeast extract spread	0.5	teaspoons	5
75502520	Vegetables	Kimchi	2.2	cups	49
Options to achieve daily calcium goal (383 to 943 mg)
11513310	Beverages	Chocolate milk, made from dry mix with non-dairy milk	0.9	cups	138
11514360	Beverages	Hot chocolate / Cocoa, made with no sugar added dry mix and non-dairy milk	1.1	packets, reconstituted	137
61201225	Beverages	Grapefruit juice, 100%, with calcium added	8.5	fl oz	102
61210250	Beverages	Orange juice, 100%, with calcium added, canned, bottled or in a carton	8.8	fl oz	128
95110010	Beverages	Nutritional drink or shake, ready-to-drink, sugar free (Slim Fast)	1.0	cups	136
11112210	Dairy	Milk, low fat (1%)	1.2	cups	131
11113000	Dairy	Milk, fat free (skim)	1.2	cups	99
11350020	Dairy	Almond milk, unsweetened	0.9	cups	33
11370000	Dairy	Coconut milk	0.8	cups	63
11411200	Dairy	Yogurt, low-fat milk, plain	1.9	4 oz containers	132
11411300	Dairy	Yogurt, nonfat milk, plain	1.7	4 oz containers	108
14104115	Dairy	Cheese, Cheddar, nonfat or fat free	0.4	cups, shredded	67
14107060	Dairy	Cheese, Mozzarella, nonfat or fat free	0.4	cups, shredded	56
14109030	Dairy	Cheese, Swiss, reduced fat	0.4	cups, shredded	71
14109040	Dairy	Cheese, Swiss, nonfat or fat free	0.4	cups, shredded	51
14120020	Dairy	Cheese, Mexican blend, reduced fat	0.3	cups, shredded	94
14410130	Dairy	Cheese, American, nonfat or fat free	0.4	cups, shredded	61
14410330	Dairy	Cheese spread, American or Cheddar cheese base, reduced fat	0.6	cups, shredded	121
14410380	Dairy	Cream cheese spread, fat free	0.5	cups	115
51300050	Grains	Bread, whole grain white	1.6	regular slice	133
72107211	Vegetables	Collards, fresh, cooked, no added fat	1.2	cups	52
72107213	Vegetables	Collards, canned, cooked, no added fat	1.9	cups	62
72125213	Vegetables	Spinach, canned, cooked, no added fat	1.4	cups	69
72128211	Vegetables	Turnip greens, fresh, cooked, no added fat	1.9	cups	56
72128213	Vegetables	Turnip greens, canned, cooked, no added fat	2.0	cups	62
75210010	Vegetables	Cabbage, Chinese, cooked, no added fat	2.1	cups	49
Options to achieve daily iron goal (13 to 22 mg)
56201210	Grains	Grits, instant, made with water, no added fat	0.7	cups, cooked	115
56203086	Grains	Oatmeal, instant, plain, made with water, no added fat	1.2	cups, cooked	189
56203096	Grains	Oatmeal, instant, plain, made with milk, no added fat	1.2	cups, cooked	308
56203106	Grains	Oatmeal, instant, plain, made with non-dairy milk, no added fat	1.1	cups, cooked	242
56205050	Grains	Cream of rice	1.1	cups, cooked	179
56207016	Grains	Cream of wheat, regular or quick, made with water, no added fat	1.4	cups, cooked	176
56207030	Grains	Cream of wheat, instant, made with water, no added fat	1.3	cups, cooked	212
57123000	Grains	Cereal, O's, plain	1.4	cups	157
57132000	Grains	Cereal, corn squares	1.5	cups	168
57134000	Grains	Cereal, corn flakes, plain	1.5	cups	169
57137000	Grains	Cereal, corn puffs	1.9	cups	172
57151000	Grains	Cereal, rice crispy, plain	1.9	cups	174
57207000	Grains	Cereal, bran flakes, plain	0.9	cups	167
57214000	Grains	Cereal, shredded wheat, flavored	0.9	cups	172
57237100	Grains	Cereal, oat bunches	1.0	cups	181
57304100	Grains	Cereal, oat squares	1.0	cups	164
57308400	Grains	Cereal, O's, multigrain	0.9	cups	104
57336000	Grains	Cereal, rice squares	1.6	cups	173
57344000	Grains	Cereal, K's, plain	1.3	cups	158
57344010	Grains	Cereal, K's, flavored	1.4	cups	175
57411000	Grains	Cereal, wheat squares	0.8	cups	166
57418000	Grains	Cereal, wheat flakes	1.2	cups	169
26211100	Seafood	Caviar	6.8	tablespoons	289
Options to achieve daily omega-3 fatty acid goal (≥0.059 g)
24198570	Meat and poultry	Chicken, canned, meat only	0.1	cups	47
24206000	Meat and poultry	Turkey, canned	0.2	5 oz can	47
26101110	Seafood	Fish, anchovy	0.70	anchovies	6
26109120	Seafood	Fish, cod, baked or broiled	1.8	oz	44
26115120	Seafood	Fish, flounder, baked or broiled	0.9	oz	22
26117120	Seafood	Fish, haddock, baked or broiled	1.7	oz	43
26118010	Seafood	Fish, halibut	1.3	oz	47
26121180	Seafood	Fish, mackerel, canned	0.03	cups	7
26133110	Seafood	Fish, snapper	0.7	oz	28
26137120	Seafood	Fish, salmon, baked or broiled	0.12	oz	7
26137180	Seafood	Fish, salmon, canned	0.04	cups	8
26137190	Seafood	Fish, salmon, smoked	0.08	cups	13
26139180	Seafood	Fish, sardines, canned	0.5	sardines	12
26151120	Seafood	Fish, trout, baked or broiled	0.29	oz	12
26155110	Seafood	Fish, tuna, canned	0.2	cups	22
26157120	Seafood	Fish, whiting, baked or broiled	1.0	oz	30
26158010	Seafood	Fish, tilapia, baked or broiled	1.8	oz	56
26211100	Seafood	Caviar	0.05	tablespoons	2
26213120	Seafood	Calamari, cooked	0.1	cups	15
26303160	Seafood	Clams, steamed or boiled	2.7	clams	45
26305160	Seafood	Crab	0.8	crabs	28
26305180	Seafood	Crab, canned	0.2	cups	28
26311110	Seafood	Lobster	0.3	tails	26
26313110	Seafood	Mussels	0.7	mussels	11
26315130	Seafood	Oysters, steamed	1.0	oysters	9
26315180	Seafood	Oysters, canned	0.7	oysters	8
26317120	Seafood	Scallops, baked or broiled	3.0	scallops	56
26319130	Seafood	Shrimp, steamed or boiled	6.5	tiny shrimp	29
26319180	Seafood	Shrimp, canned	0.07	cups	10
27150110	Seafood	Shrimp cocktail	0.2	cups	43

Discussion

We identified surprisingly few foods that can be consumed during pregnancy in lieu of dietary supplements to meet nutrient recommendations without inducing excess caloric intake. No single food filled the nutrient gap for all 6 nutrients of interest, and the one food that met 5 of the nutrient targets (seaweed) would have to be consumed in amounts unlikely to be acceptable to pregnant women (5+ cups/d). Further, seaweed may be difficult to procure, is expensive, and contains undesirable levels of other nutrients (eg, >2100 mg of sodium in 5 cups). We did identify numerous low-energy, widely available food options that would meet individual nutrient targets, including many with reasonable servings needed to meet targets and appropriate for consumption during pregnancy. Women hoping to optimize nutrient intakes in pregnancy should consider incorporating these foods into a healthy dietary pattern.

Our objective was to find a nutrient-rich food to supplement the usual intake of foods to meet nutrient targets in the same way that dietary supplements augment (rather than alter) the usual intake of foods. However, our analysis indicates that more substantial shifts in dietary intake are likely needed to meet nutrient intake targets, as well as improve prenatal intake more generally. Dozens of prenatal trials have aimed to optimize intake to prevent excessive gestational weight gain and/or gestational diabetes, optimize neonatal body size, and improve other related maternal/neonatal outcomes [36]. Rather than simply endorsing or providing dietary supplements, trials generally support eucaloric dietary modifications to improve diet quality (defined in various ways) [37]. However, only nominal shifts in dietary intake have been reported (eg, +0.6 vegetable servings/week [38], -0.85% calories from saturated fat [39]). At a pragmatic level, changing dietary habits with routine clinic visits instead of intensive programming is less promising [28]. As such, we focused this analysis on nutrients of concern that are commonly addressed with dietary supplements rather than intensive nutritional counseling. By examining low-calorie, nutrient-rich foods that could be added to the diet rather than replacing high-calorie, nutrient-poor foods, we offer practical guidance for clinicians and pregnant women seeking to achieve recommended nutrient intakes with food-based options versus dietary supplements alone.

Unfortunately, our goal to generate a list of foods that could replace prenatal dietary supplements in the United States was hampered by the limited number of foods that provide key nutrients in serving sizes that are likely to be acceptable to pregnant women. This was particularly challenging for vitamin D. We identified multiple fish varieties that facilitate meeting vitamin D goals but would require consuming ∼3-4 oz/d, substantially more than the ∼4 oz/wk of fish currently consumed by pregnant women [40]. Although this level of fish intake would also facilitate meeting omega-3 fatty acid targets defined herein (∼1 oz/d), it would exceed the recommended limit of 8 to 12 oz/wk in pregnancy to minimize methylmercury exposure [41]. Women who do not consume fish will be challenged to meet omega-3 fatty acid targets with low-calorie foods. Beyond other animal products (eg, canned poultry organ meats), seaweed was the only nonanimal option that supported meeting omega-3 fatty acid targets. However, consuming multiple cups a day of seaweed is atypical in the American diet. For vitamin D, cow’s milk may be an attractive alternative. Additionally, sun exposure can help achieve vitamin D sufficiency, although this varies widely by latitude and season, and prevention of skin damage and cancerous growth must be considered [42]. Thus, dietary supplements are likely necessary to help women meet the vitamin D and omega-3 fatty acid targets in pregnancy. Since two-thirds of prenatal dietary supplements contain no omega-3 fatty acids and one-fifth contain no vitamin D [15], standalone supplements rather than multivitamin/multimineral products may be required.

Consumption of fortified cereals or green vegetables is well-suited to meet iron and folate targets. Less than 2 cups/d of fortified cereals are needed to meet both targets and can be consumed with lower-fat milk to simultaneously meet vitamin D targets. Leafy and nonleafy green vegetables such as collards, spinach, asparagus, and brussels sprouts contain naturally occurring folate and generally require an intake of only ∼1 cup (∼75 calories) to meet intake targets, an amount that may be feasible for many individuals. Green vegetables such as asparagus, snow peas, and leafy greens also provide iron, but large quantities (ranging from ∼2-3 cups for dark green vegetables up to 40+ cups for leafy greens) are required to meet intake targets. As more than 4 in 5 pregnant women are at risk of low iron intake [7], and up to 18% exhibit iron deficiency anemia [43], boosting iron intake among the United States population of pregnant women appears warranted. Yet, further studies are needed to determine if increased iron intake in this population will translate to improved perinatal outcomes beyond maternal or neonatal iron status [44].

We identified many low-calorie foods abundant in calcium and vitamin A, many of which overlapped with foods optimal for meeting targets for the other nutrients we examined. Green vegetables (leafy and otherwise) provide both nutrients, with relatively small amounts required to meet vitamin A requirements (generally ∼0.5 cups or less), whereas larger amounts are needed to achieve calcium targets (generally 1–2 cups). Orange vegetables like carrots and sweet potatoes also provide sufficient vitamin A in small servings (∼0.2 cups; ∼25 calories). Dairy products like milk and cheese are rich sources of calcium, requiring approximately half of the amount to meet calcium targets compared with the amount needed to meet vitamin D targets (eg, 1.2 cups of skim milk vs. 2.6 cups). As the daily intake of both orange vegetables and dairy products during pregnancy falls well below food group recommendations in the Dietary Guidelines for Americans [41], increasing consumption of these foods may help pregnant women achieve not only these specific nutrient intake requirements but also an overall healthier eating pattern associated with lower chronic disease risk.

The present analysis was prompted by our recent report that just one dietary supplement product in the United States provides doses of the 6 nutrients studied here to help 90% of our population achieve recommended intakes without inducing excess consumption [15]. We concluded that the United States dietary supplement market is not meeting the nutrient needs of pregnant women and called for reformulation or development of products that can do so. Herein, we aimed to identify food-based solutions given the dearth of appropriate dietary supplements, but our conclusions are similarly unsatisfactory. We recognize assessing dietary intake and providing individualized guidance on foods and/or supplements to each patient is not possible in busy clinics, which is why clinics default to a standard list of foods they recommend or a standard prenatal vitamin they prescribe. Yet without appropriate foods or dietary supplements to recommend across a population, this approach of standard lists is insufficient— confirmed by our prior report that up to half of pregnant women are not meeting nutrient intake recommendations even with dietary supplement use [7, 9]. Thus, we reiterate our call for reformulations of dietary supplements to meet the nutritional needs of United States pregnant women in the 21^st century and note the opportunity for nutrition scientists to inform such reformulations by enhancing the evidence base surrounding physiological needs, usual intake, and supplementation targets for a broader range of nutrients. There is also an opportunity for nutrient scientists to develop efficient tools that can effectively differentiate the nutritional needs of individual patients within clinical settings so that tailored food and/or supplement recommendations can be easily provided in real-world settings. Until then, clinicians can encourage patients to reduce their intake of nutrient-poor, energy-dense foods so that more nutrient-rich foods can be consumed without inducing excess energy intake.

As our sample included participants with diversity in terms of race, ethnicity, education, and prepregnancy body mass index, our results are broadly generalizable. However, we acknowledge that some subgroups may face more barriers to healthy, nutrient-rich eating in pregnancy and require assistance from programs like WIC or Supplemental Nutrition to access healthier food options and/or procure prenatal dietary supplements to meet persistent nutrient gaps. We previously reported that risk of inadequate intake from foods alone did not differ by race, ethnicity, or educational attainment in ECHO pregnant participants for vitamin D, folate, calcium, and iron [9]. Risk of inadequate intake of vitamin A from foods alone was higher among pregnant women with a high school education or less or self-identity as Hispanic, Black, or other races besides White. However, we identified many widely available, low-cost foods that could provide sufficient vitamin A, such that disparities in vitamin A adequacy should not be propagated by our results. For omega-3s, others have reported that among United States women of child-bearing age, intake is inversely correlated with household income and education but not food security status or receipt of supplemental nutrition assistance [45]. Yet our work demonstrates that regardless of personal identity or available resources, pregnant women in the United States continue to fall short of the recommended intake for key nutrients. As the specific prenatal dietary supplements covered by Medicaid vary by state, it is likely that even women receiving Medicaid services have limited access to products providing appropriate doses [46]. Thus, as few foods (shown herein) or dietary supplements (reported previously [15]) can address the nutrient gaps pervasive with current prenatal eating patterns, substantial shifts in usual intake are needed and likely require multi-level approaches to address individual, environmental, clinical, and access-related barriers.

Our work has strengths and limitations. Dietary data were collected from a diverse group of participants experiencing pregnancy in the modern food fortification era with intakes similar to nationally-representative prenatal data [4]. We selected nutrients based on Cochrane reviews supporting their importance for maternal/offspring outcomes but acknowledge that other nutrients are important (eg, choline [47], iodine [48]) and should be explored in future analyses. Participants self-reported intake, limiting the accuracy of estimates (53), and we did not examine bioavailability or circulating concentrations of these nutrients, which is critical to determining actual deficiency. We evaluated candidate foods based on food and beverage nutrient profiles defined by the 2019 to 2020 FNDDS, as opposed to the databases used to evaluate the food-based intake of participants, which may have contributed to inaccuracies in estimates. It also restricts our list of candidate foods to those currently consumed in the United States, whereas foods consumed in other countries could have met our criteria. Our selection criteria also eliminated mixed foods that could be created to meet multiple nutrient targets (eg, a flax seed muffin for a vegan source of omega-3 fatty acids) and preferentially selected foods that may be less accessible to individuals with lower income, less access to fresh foods, or inability to digest dairy products, which could limit generalizability of findings. Our calorie limit of 340 was defined by the increased amount needed to support a healthy pregnancy beginning in the second trimester for women without overweight or obesity, but calorie allowances are lower in the first trimester and higher in the third trimester and vary by body size [35]. We acknowledge that our participants were pregnant at the time of dietary assessment and thus likely already consuming additional calories, such that adding another 340 calories to reach these goals might induce excess intake. Alternatively, if other foods are eliminated to accommodate these additions, the nutrient profile would shift, and our target ranges may no longer be appropriate. We also did not consider the bioavailability of nutrients, which can be affected by what other nutrients are consumed simultaneously.

In conclusion, multiple low-calorie, nutrient-rich foods can help pregnant women achieve nutrient intake recommendations, but we found few options that fill the gap for multiple nutrients simultaneously in acceptable serving sizes and/or caloric ranges. Pregnant women, obstetric providers, and nutritionists can focus on boosting prenatal intake of low-mercury fish, low-fat dairy, green and leafy green vegetables, and fortified cereals to achieve prenatal nutrient intake recommendations. The information and tables included in this manuscript can also serve as a tool to inform personalized nutrition recommendations, in which specific target nutrients may be of concern for an individual based on usual dietary intakes and, thus, could be addressed by increasing the intake of foods identified in our analysis. Pragmatic, scalable, and evidence-based methods for optimizing dietary intake during pregnancy are still needed.

Acknowledgments

The authors wish to thank our ECHO colleagues, the medical, nursing, and program staff, as well as the children and families participating in the ECHO cohorts. We also acknowledge the contribution of the following ECHO program collaborators: ECHO Components—Coordinating Center: Duke Clinical Research Institute, Durham, North Carolina: Smith PB, Newby KL, Benjamin DK; Data Analysis Center: Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland: Jacobson LP; Research Triangle Institute, Durham, North Carolina: Parker CB, Catellier DJ. ECHO Awardees and Cohorts— Rhode Island Hospital, Providence RI: Koinis Mitchell D; Rhode Island Hospital, Providence RI: Deoni S, D’Sa V; Avera Research Institute, Sioux Falls, SD: Elliott AJ; University of Southern California, Los Angeles, CA: Breton C; University of Southern California, Los Angeles, CA: Bastain T, Farzan S, Habre R; Henry Ford Health, Detroit, MI: Barone C; Michigan Department of Health and Human Services, Lansing, MI: Fussman C; Michigan State University, East Lansing, MI: Paneth N; University of Michigan, Ann Arbor, MI: Elliott M; Wayne State University, Detroit, MI: Ruden D.

Author contribution

The authors’ responsibilities were as follows—KMS, KL, JMK, DD, and TGO designed cohort-level research; KAS, CWH, KMS, KL, JMK, DD, LEM, and TGO conducted research; KAS, CCC, GLC, and DJC designed the research question and analysis; KAS, GLC, and DJC conducted the analysis; KAS wrote the paper. KAS had primary responsibility for the final content. CCC, NTM, CWH, KMS, LEM, KL, JMK, DD, TGO, DHG, MMM, GLC, and DJC provided input on the results and interpretation and then read, critically reviewed, and approved the final manuscript.

Disclaimer

The sponsors had no role in the study design, collection, analysis, and interpretation of data, writing of the report, or the decision to submit the report for publication. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Funding

This study was supported by the Environmental influences on Child Health Outcomes (ECHO) program, Office of The Director, National Institutes of Health, under Award Numbers U2COD023375 (Coordinating Center), U24OD023382 (Data Analysis Center), U24OD023319 with co-funding from the Office of Behavioral and Social Science Research (PRO Core), UG3/UH3OD023248 (Dabelea), UH3OD023313 (Koinis Mitchell), UG3/UH3OD023279 (Elliott), R01HD034568 (Switkowski), R01HD096032 (Switkowski), UG3/UH3OD023286 (Oken), UG3/UH3OD023287 (Breton), UG3/UH3OD023342 (Lyall), UG3/UH3OD023285 (Kerver), UG3/UH3OD023349 (O’Connor).

Conflict of Interest

KMS has served as a paid consultant on prenatal nutrition to Modern Fertility. NTM is a member of Tiny Health Inc. Scientific Advisory Board. All other authors report no conflicts of interest.

Data Availability

De-identified data from the ECHO Program are available through the National Institute of Child Health and Human Development’s Data and Specimen Hub (DASH). DASH is a centralized resource that allows researchers to access data from various studies via a controlled-access mechanism. Researchers can now request access to these data by creating a DASH account and submitting a Data Request Form. The DASH Data Access Committee will review the request and provide a response in approximately 2 to 3 wk. Once granted access, researchers will be able to use the data for 3 y. See the DASH Tutorial for more detailed information on the process. Some data described in this manuscript are not available on DASH. Requests to access the full datasets should be directed to the ECHO Data Analysis Center, ECHO-DAC@rti.org. Data described in the manuscript, code book, and analytic code will be made available upon request, pending request and approval.

Appendix A. Supplementary data

The following is the Supplementary data to this article: