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Heavy Metal Index

Assessing Dietary Consumption of Toxicant-Laden Foods and Beverages by Age and Ethnicity in California: Implications for Proposition 65

Overview

This is a population dietary-intake study, not a contamination occurrence study. The authors deployed a one-week online food frequency questionnaire to 186 Southern California residents (60.8% adults, 39.2% adolescents) covering staple foods and the food categories most commonly targeted under California’s Proposition 65 for lead and acrylamide exposure: root vegetables, rice, leafy greens, pasta/noodles, tea, juice, seafood, twenty individual herbs/spices, stuffed grape leaves, tamarind/chili candy, chocolate products, nutritional powders, and traditional beverage powders such as matcha. The study reports daily intake (g/day), portion size, eating-occasion frequency, and home-food behaviors (homegrown food, store-bought soil use, tap-water reliance, pre-1978 housing) by age and race/ethnicity, then uses one Prop 65 consent-judgment threshold to demonstrate the magnitude of underestimated single-day lead exposure from stuffed grape leaves. The contribution to the Heavy Metal Index corpus is exposure-side: it provides population intake denominators that downstream synthesis can multiply against published contamination concentrations to estimate dietary exposure, and it documents underestimation patterns in Prop 65’s product-by-product exposure assessment methodology for herbs and spices (which cumulate to ~8.3 g/day mean across the food category but are conventionally assessed at a 0.5 g RACC per single herb). The study itself measures no metal concentrations and proposes no contamination thresholds.

Key numbers

All values are intake in g/day or g/person/day; consumption frequency in eating occasions (EO) per day or per week. Where stated, “per capita” means averaged across all N = 186 respondents (including non-consumers); “consumers only” means averaged across the subset who reported any consumption of that item over the past 7 days. Daily intake = portion size × consumption frequency × USDA volume-to-mass conversion. No analytical metal measurements were made in this study; lead exposure values quoted below are arithmetic products of reported intake and externally-cited consent-judgment contamination ceilings.

Sample characteristics (N = 186)

QuantityValue
Surveys completed207
Excluded (below age, non-CA, completion < 3.38 min)21
Retained for analysis186
Median completion time (min)8.15 (IQR 5.9–11.6)
Female / Male / Other62.9% / 36.0% / 1.1%
Adults (≥18) / Adolescents (13–17)60.8% / 39.2%
Asian/Pacific Islander40.9% (n=76)
Latino/Hispanic28.0% (n=52)
White/Caucasian11.8% (n=22)
Middle Eastern11.8% (n=22)
Indian6.5% (n=12)
Other1.1% (n=2)

Per capita daily intake of selected food categories (g/day, all N=186)

Selection limited to categories most relevant to the heavy-metals corpus; full Table 2 contains additional entries. ”% (consumers)” = percentage of N=186 reporting any consumption of the item in the past 7 days.

Food / beverageMean per-capita intake (g/day)Median (g/day)% consumersMean consumer-only intake (g/day)
Water14131440100.01436
Root vegetables83.948.396.387.2
Juice72.468.659.8120.5
Tea70.20.046.0151.7
Rice (cooked)52.637.291.057.8
Leafy greens33.629.484.139.5
Pasta/noodles30.922.581.038.0
Other meat (fried)20.26.156.635.7
Other seafood (non-fish)21.80.039.255.8
Tomato sauce16.911.665.625.8
Cookies15.35.765.623.3
Nuts/seeds14.94.959.325.0
Fish (not fried)11.00.046.024.1
Pickled products10.10.045.022.4
Salsa10.40.044.423.2
Chocolate foods9.66.178.812.2
Potato chips8.85.463.513.8
Mushrooms8.20.036.522.5
Wine7.90.07.4105.7
Nutritional powder6.80.027.524.3
Tortilla chips5.10.046.011.1
Fish (fried)4.20.020.620.3
Food paste4.20.027.515.0
Stuffed grape leaves2.60.05.844.5
Chocolate drink powder2.40.022.210.8
Tamarind/chili candy1.50.024.16.4
Tostadas/taco shells1.30.029.64.2
Popcorn1.20.021.75.4
Traditional beverage powder (e.g., matcha)0.30.033.30.8

Beverage portion-size assumptions (paper-specified)

  • Wine: 5 oz = ~150 g per glass.
  • Other liquids (water, juice, tea): 8 oz = ~240 g per cup.
  • Nutritional powder and chocolate drink powder portion-size from USDA FoodData Central (mean portion 44.3 g and 23.3 g respectively); traditional drink powder 2.1 g per serving.

Herb and spice intake — top categories (Table 4)

Per-capita (“All N=186”) and consumer-only daily mass intake of the 20 herbs/spices surveyed. Eating-occasion (EO) frequency averaged across all participants. Unit conversion (g/tsp) from USDA where available; “1.8 ᵇ” is the paper’s fallback value when not separately reported.

Herb / spice% consumersPer-capita mean (g/day)Median per-capita (g/day)g/tspMean EO/dayConsumer-only mean (g/day)
Garlic powder75.11.470.663.10.611.95
Basil59.00.280.081.10.430.47
Oregano53.30.310.101.40.420.58
Chili powder52.71.110.192.70.612.10
Paprika50.00.840.082.30.621.68
Italian mix48.10.340.001.8 ᵇ0.420.71
Parsley47.50.120.000.50.490.26
Other45.70.670.001.8 ᵇ0.741.46
Cumin45.20.540.001.8 ᵇ0.551.19
Cinnamon43.80.580.002.60.471.34
Cayenne41.80.430.001.8 ᵇ0.451.05
Turmeric38.90.860.003.00.592.23
Ginger36.80.390.001.80.511.06
Rosemary34.40.210.001.20.420.62
Curry powder33.70.560.002.00.631.66
Thyme32.40.190.001.20.400.59
Masala mix21.30.480.001.8 ᵇ0.802.26
Sage15.30.060.000.70.460.40
Za’atar13.70.170.001.8 ᵇ0.531.24
Ground mustard seed13.30.190.002.00.561.41
Average across all 20—0.49—1.80.541.21

Cumulative herb/spice intake (all 20 categories aggregated to a single food category)

QuantityPer capita (N=186)Consumers only
Mean cumulative daily intake (g/day)8.3(not reported as separate aggregate)
Median cumulative daily intake (g/day)2.7—
Mean cumulative EO frequency3.7 EO/day—
Median cumulative EO frequency2.6 EO/day—
Mean herb/spice intake per EO1.51 g/EO (IQR 1.1–2.6)—
Mean volumetric intake per EO0.83 tsp/EO—
Median volumetric intake per EO0.75 tsp/EO—

Age and race/ethnicity differentials (Table 3, regression analyses, β estimates in g/day relative to reference)

Reference group for race/ethnicity: White/Caucasian. Reference for age: adolescents (13–17). Bold β = p < 0.01; underlined β = p < 0.05. Values reproduced as printed; only categories with at least one statistically significant differential are listed here.

Foodr²InterceptAsianHispanicIndianMiddle EasternAdult
Juice0.0658.1738.74 (ns)46.28 (p<0.01)22.63 (ns)54.10 (p<0.01)−36.08 (p<0.05)
Tea0.1081.93−36.82 (ns)−67.35 (p<0.05)−35.99 (ns)19.55 (ns)33.76 (p<0.1)
Wine0.0529.68−23.91 (ns)−26.66 (p<0.05)−29.68 (p<0.05)−23.91 (p<0.05)0.00 (ns)
Root vegetables0.0892.266.21 (ns)−34.26 (ns)65.59 (p<0.01)9.08 (ns)−24.34 (ns)
Dried fruit0.0717.02−11.08 (p<0.05)−14.58 (p<0.05)−8.51 (ns)−15.08 (p<0.01)1.16 (ns)
Rice (cooked)0.2750.9359.05 (p<0.05)−4.16 (ns)20.19 (ns)23.79 (ns)−41.38 (p<0.05)
Pasta/noodles0.0752.27−15.29 (p<0.01)−20.29 (ns)−20.29 (ns)−23.86 (p<0.01)−4.44 (ns)
Tostadas/taco shells0.182.24−1.12 (p<0.05)0.89 (ns)−1.14 (ns)−1.11 (p<0.01)−0.89 (p<0.05)
Salsa0.1817.42−10.32 (p<0.01)6.15 (ns)−8.74 (p<0.01)−7.48 (p<0.01)−4.67 (ns)
Food paste0.039.32−4.84 (ns)−8.00 (p<0.01)2.66 (ns)−3.84 (ns)−0.95 (ns)
Cookies0.0827.67−18.45 (p<0.01)−12.06 (p<0.01)−8.58 (p<0.01)−17.03 (p<0.01)−2.22 (p<0.01)
Crackers0.108.48−4.29 (p<0.05)−5.26 (p<0.01)−6.06 (p<0.01)−5.52 (p<0.01)−2.56 (p<0.05)
Potato chips0.0715.83−7.11 (p<0.01)−3.82 (ns)−6.69 (p<0.01)−6.47 (p<0.01)−2.88 (p<0.01)
Tortilla chips0.0712.04−6.36 (p<0.01)−5.83 (p<0.01)−6.48 (p<0.01)−6.21 (p<0.01)−2.53 (p<0.01)
Chocolate foods0.0615.01−4.35 (p<0.01)−8.63 (p<0.01)−9.18 (p<0.01)−7.02 (p<0.01)0.52 (ns)
Popcorn0.135.43−3.16 (p<0.01)−4.41 (p<0.01)−3.58 (p<0.01)−2.77 (p<0.01)−1.89 (p<0.01)
Tamarind/chili candy0.130.090.70 (ns)3.71 (p<0.01)0.00 (ns)0.12 (ns)−0.21 (ns)
Nutritional powder0.1217.04−12.27 (p<0.01)−13.72 (p<0.01)−8.01 (p<0.01)−18.16 (p<0.01)1.83 (ns)
Stuffed grape leaves0.181.96−2.08 (p<0.05)−2.47 (p<0.05)−2.47 (p<0.05)18.44 (p<0.01)1.15 (ns)
Total herbs/spices0.0812.3−1.8 (ns)−7.0 (p<0.05)13.1 (p<0.01)3.3 (ns)−4.6 (p<0.01)

Adolescent vs adult differential (Section 3.3 summary)

QuantityValue
Adolescent portion-size increase vs adults (average across all foods)+17%
Adolescent daily-intake increase vs adults (average across all foods)+24%
Foods with adolescent intake significantly higher (p < 0.05 multivariate)rice, tostadas/taco shells, juice, tea (p < 0.1), crackers, popcorn
Mass difference rice (adolescent − adult)+41.4 g/day
Variance explained for rice (r²)0.27

Stuffed grape leaves — single-serving lead exposure calculation (paper’s own arithmetic, Discussion §4.4)

Reference threshold: California Prop 65 consent-judgment lead ceiling for stuffed grape leaves, 0.018 ppm (Superior Court of California 2021, paper Reference 73).

QuantityValue
Average portion size among consumers242 g (~6 stuffed leaves)
Label-based serving size (typical)~1 stuffed leaf
lead (Pb) concentration (consent-judgment ceiling)0.018 ppm = 0.018 µg/g
Single-serving lead (Pb) exposure at consent ceiling4.3 µg/day
California Prop 65 lead MADL0.5 µg/day
Exceedance vs MADL~8.6-fold (paper states “by over 8-fold”)

Other Prop 65 consent-judgment ceilings cited in Discussion (paper’s report, not measurements)

The paper references the following lead ceilings as context for population exposure interpretation (not as findings of this study):

ProductCeilingSource citation in paper
Rice grain (California)0.056 ppm Pb (2018)Ref 69 (Superior Court of California Los Angeles, Consent Judgement)
Rice grain (California, 2023 court finding)“comparable” amount of Pb deemed acceptableRef 70 (Consumer Advocacy Group v. Gulf Pacific Rice)
Nutritional powders3 µg/day PbRef 73
Nutritional powders containing chocolate4 µg/day PbRef 73
Chocolate products0.225 ppm Pb, 0.960 ppm Cd (depending on cocoa content)Ref 73
Lead in tamarind/chili candy (“naturally occurring”)0.02 ppm Pb allowanceOEHHA Title 27 §28500, 2021 (Ref 30)

Behavioral patterns affecting exposure (Sections 3.5, 4.3)

PatternValue
Tea consumers who “always” or “sometimes” reuse tea bags across cups~33% (paper text: “roughly one-third”)
Tea consumers who use “fresh teabags multiple times per day”~67% (Discussion §4.1)
Participants reporting home built before 197823.1%
Participants reporting home built after 197839.2%
Participants unsure of construction year37.6%
Participants growing any food at home35%
Of home-growers, those growing food in store-bought soil (majority)31%
Of home-growers, those growing none in store-bought soil40%
Participants reporting >70% of daily water from unfiltered tap26% (1 in 4)
Participants reporting >70% of daily water from bottled / delivery20%
Participants who “never” or “rarely” use single-serving labels for herb/spice quantity”overwhelming majority” — teenagers >43%, adults >74% never; only 15% “often”/“always” (Chi-Square < 0.001)

Race/ethnicity discrepancies — largest gaps reported in Section 3.4 and 3.5

ItemGapDirection
Tamarind/chili candy0% (Caucasian, Middle Eastern) → 59.5% (Hispanic/Latino) consumersHispanic/Latino concentrated
Stuffed grape leaves0% (Hispanic/Latino, Indian) → 38.9% (Middle Eastern) consumersMiddle Eastern concentrated
Masala mix4% (Hispanic) → 83% (Indian) consumersIndian concentrated
Za’atar<25% all other groups → 72.2% (Middle Eastern) consumersMiddle Eastern concentrated
Cumin / turmeric / ginger consumption2–3× higher among Indian and Middle Eastern vs other groupsIndian / Middle Eastern concentrated
Total herbs/spices participation<40% all other groups → ~60% (Indian, Middle Eastern)Indian / Middle Eastern concentrated

Methods (brief)

Study design. Cross-sectional online dietary survey administered via Qualtrics (Provo, UT) between 1 March and 15 June 2023 to Southern California residents (adults ≥18 and adolescents 13–17). Recruitment by snowball sampling through community contacts (university groups, non-profit organizations) circulating the survey link in English and Spanish via email listservs and social media (Facebook, Instagram). Targeted at popular staple foods consumed in high quantities and/or foods most commonly pursued under California’s Proposition 65 enforcement for lead and acrylamide contamination, as reported by the California Attorney General. Concentration measurements were not performed.

Instrument. Adapted from the NHANES Food Frequency Questionnaire with the recall window reduced from one year to one week. Participants were asked whether they consumed each item in the past 7 days, then (multiple-choice) how often and how much per typical occasion. Beverages were pre-assigned a serving size (5 oz wine, 8 oz other liquids); food/beverage powder serving size estimated from USDA FoodData Central. For 20 individual herbs/spices, only frequency was asked separately; quantity per occasion was asked once for the herb/spice food category as a whole (per FDA’s RACC guidance). Additional questions on tea-bag reuse, cumulative water intake, tap vs bottled water source, home gardening, store-bought soil use, and pre-1978 housing year. Full survey instrument in Supplementary Table S1.

Data reduction. Range-response options converted to range midpoint (e.g., “1–2 cups” → 1.5); “less than” responses converted to half-unit; “greater than” responses converted to plus-one-unit; consumption frequencies converted similarly (“2–4 times per week” → 3). Volume responses (cups, teaspoons) converted to grams via USDA FoodData Central density values. Daily intake (g/day) = portion size × consumption frequency. Per-capita statistics retained all participants including non-consumers; “consumers only” statistics excluded participants reporting zero consumption.

Herb/spice intake calculation. Consumption frequency per herb/spice multiplied by 0.83 tsp/EO (the average consumption quantity per EO across all herb/spice categories) and by the USDA density (g/tsp) of that specific herb/spice to yield mass intake per category. Total Herb/Spice daily intake = sum across all 20 categories per participant.

Statistics. SAS 9.4 (SAS Institute, Cary, NC). Means, medians, and group means by age and race/ethnicity. Multivariate regression with two covariates (age category, race/ethnicity) only — reference groups White/Caucasian and adolescent (13–17). Significance assessed at p < 0.10 and p < 0.05. No correction for multiple comparisons reported. The authors note that small-cell counts in some race/ethnicity strata may have lessened ability to detect intake differences.

Demographic distinctions. “Indian” and “Middle Eastern” were defined as distinct from “Asian” (East/Southeast Asia only) given the differing cuisine and ingredient profiles described in Section 2.2. The “Other” category was 1.1% (n = 2).

Survey-completion quality control. Of 207 surveys completed, 21 were excluded for being below the age threshold, residing outside California, or completion time < 3.38 min (the 1st-percentile threshold). N = 186 retained. Median completion time 8.15 min (IQR 5.9–11.6).

Ethics. IRB-exempt for adult survey (UC Irvine Office of Research, Kuali Research Protocols). Adolescent administration approved by IRB Committee C, approval code 2733, approval date 9 May 2023. Informed consent waived per exempt status.

Funding. NIH/NIEHS R01ES030353.

Limitations

  • Convenience snowball sample drawn from Orange County, California, with no probability framework. The retained sample over-represents Asian/Pacific Islander (40.9%) and Middle Eastern (11.8%) residents relative to background county demographics; White/Caucasian (11.8%) and Hispanic (28.0%) are under-represented vs the regional reference statistics the authors cite. Generalizability beyond Orange County is correspondingly limited.
  • N per race/ethnicity stratum is small (Indian n = 12, Middle Eastern n = 22, Other n = 2). Several regression coefficients in Table 3 are estimated on cells of n < 25; the authors flag that small-cell counts may have lessened ability to detect differences.
  • Two-covariate multivariate model (age and race/ethnicity only). Income, education, gender, household-size, and neighborhood confounders were not adjusted for despite being collected; the authors note residual confounding cannot be ruled out.
  • One-week recall is shorter than the NHANES 1-year recall but longer than the 2-day NHANES dietary-recall instrument; results are not directly comparable to either. The authors report cumulative-frequency values ~2× higher than NHANES FFQ and ~30% lower than 2-day NHANES dietary recall, attributed to the difference in window length and demographic composition.
  • Self-reported intake is subject to recall bias and social-desirability bias. The authors expect modest bias because the survey was not marketed as a “health” survey.
  • Volume-to-mass conversion uses standard USDA densities and may not match individual respondent product choice (e.g., dried vs fresh; powder density variation across brands).
  • Pre-added herbs/spices in processed foods are not captured; the authors note herb/spice intake may be “drastically underestimated” because participants do not know the herb content of prepared meals they consume.
  • No metal concentration measurements were performed. Exposure estimates require an external contamination ceiling (e.g., Prop 65 consent-judgment value, FDA action level, regulatory cap) to be multiplied against the intake values; the paper presents one such calculation (stuffed grape leaves) and references several other ceilings for context.
  • Stuffed grape leaves intake reflects only n = 11 consumers (5.8% of N = 186); the consumer-mean portion size of 242 g and intake of 44.5 g/day are estimated on a very small subgroup and should not be generalized to the broader Middle Eastern population without replication.
  • The Discussion’s lead-exposure calculation for stuffed grape leaves uses the consent-judgment ceiling (0.018 ppm) as the contamination value, which represents the legally allowable maximum after a court settlement rather than measured product concentrations; actual product lead (Pb) may be lower or higher.
  • “Less than” and “greater than” range conversions (e.g., “<1 cup” → 0.5 cups, “>3 cups” → 4 cups) introduce a directional bias toward central tendency; tail consumers are clipped.
  • Reuse-of-tea-bags behavior is reported as a frequency question, not as a quantification of additional lead leaching; the inference that fresh-leaching is greater than label-assumption is qualitative.

Implications

For HMI evidence corpus. This source contributes California-specific population intake denominators for several food categories in the corpus: rice (52.6 g/day per capita; 57.8 g/day among consumers), leafy greens (33.6 / 39.5), root vegetables (83.9 / 87.2), tea (70.2 / 151.7), juice (72.4 / 120.5), pasta/noodles (30.9 / 38.0), seafood-other (21.8 / 55.8), fish-not-fried (11.0 / 24.1), chocolate foods (9.6 / 12.2), nutritional powder (6.8 / 24.3), traditional beverage powder including matcha (0.3 / 0.8), stuffed grape leaves (2.6 / 44.5), tamarind/chili candy (1.5 / 6.4), and twenty individual herb/spice categories with a cumulative mean intake of 8.3 g/day across the food category. These intake values may be used by downstream synthesis when multiplied against a per-ingredient or per-product contamination central tendency.

For exposure-assessment methodology coverage. The cumulative herb/spice intake of 8.3 g/day (vs 0.5 g RACC per single herb on FDA labeling guidance) is one of the cleaner exposure-side documentations in the recent literature of why product-by-product Prop 65 exposure assessment systematically underestimates aggregate herb/spice contaminant intake. The herb/spice food-category subdivisions documented in court enforcement (basil, oregano, etc. assessed separately) versus the USDA’s “seasonings, spices and herbs” single-category designation is a methodology gap relevant to regulatory crosswalks.

For Prop 65 / California regulatory crosswalk. The paper documents the following specific consent-judgment lead ceilings as context: stuffed grape leaves 0.018 ppm (2021); rice 0.056 ppm (2018); nutritional powders 3 µg/day; nutritional powders containing chocolate 4 µg/day; chocolate products 0.225 ppm Pb and 0.960 ppm cadmium (Cd); “naturally occurring” lead in tamarind/chili candy 0.02 ppm under OEHHA Title 27 §28500 (2021). These are settlement-derived legal maxima, not measured concentrations or population exposure benchmarks; they belong in the regulatory crosswalk rather than the contamination occurrence layer.

For age-stratified exposure. Adolescent (13–17) intake exceeded adult intake by an average of +17% in portion size and +24% in daily mass, with statistically significant differentials (p < 0.05 multivariate) for rice, tostadas/taco shells, juice (p < 0.1), tea (p < 0.1), crackers, and popcorn. Combined with lower body weight, the per-kg-bw adolescent exposure differential is larger than the per-capita differential; downstream age-stratified exposure modeling should account for both factors.

For race/ethnicity-stratified exposure. Hispanic/Latino participants reported tamarind/chili candy intake 3.71 g/day higher than the White/Caucasian reference (p < 0.01); Middle Eastern participants reported stuffed grape leaves intake 18.44 g/day higher (p < 0.01); Indian participants reported root-vegetable intake 65.5 g/day higher (p < 0.01) and total herb/spice intake 13.1 g/day higher (p < 0.01). The authors frame these differentials as a Proposition-65 environmental-justice concern when product-specific “naturally occurring” pollution exemptions overlap with foods consumed disproportionately by specific racial/ethnic groups.

For tea exposure pathway. Roughly two-thirds of tea consumers reported reusing tea bags across multiple cups per day, which the authors note creates greater opportunity for lead leaching than the 3–5 min single-infusion model used in conventional Prop 65 exposure assessment. Tea consumer-only intake of 151.7 g/day (~⅔ of an 8 oz cup) is the working denominator for tea-derived dietary lead in this population.

For homegrown-food and tap-water pathway exposure. 23.1% of respondents reported homes built before 1978 (lead-paint and lead-plumbing era), 35% reported home food gardening, 40% of home-growers reported growing food in non-store-bought soil, and 26% reported >70% of daily water from unfiltered tap water. These behaviors are exposure modifiers for lead-from-paint-and-soil and lead-from-plumbing pathways; the paper does not measure but documents their prevalence.

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