| Literature DB >> 21556174 |
Marie Lynn Miranda1, Sharon Edwards, Pamela J Maxson.
Abstract
The adverse effects of prenatal mercury exposure, most commonly resulting from maternal fish consumption, have been detected at very low exposure levels. The omega-3 fatty acids found in fish, however, have been shown to support fetal brain and vision development. Using data from a prospective, cohort study of pregnant women from an inland area in the US South, we sought to understand the fish consumption habits and associated mercury levels across subpopulations. Over 30% of women had at least 1 μg/L of mercury in their blood, and about 2% had blood mercury levels above the level of concern during pregnancy (≥ 3.5 μg/L). Mercury levels were higher among Asian/Pacific Islander, older, higher educated, and married women. Fish consumption from any source was reported by 2/3 of the women in our study, with older women more likely to consume fish. Despite eating more fish meals per week, lower income, lower educated women had lower blood mercury levels than higher income, higher educated women. This suggests the different demographic groups consume different types of fish. Encouraging increased fish consumption while minimizing mercury exposure requires careful crafting of a complex health message.Entities:
Keywords: fish consumption; mercury; pregnant women
Mesh:
Substances:
Year: 2011 PMID: 21556174 PMCID: PMC3083665 DOI: 10.3390/ijerph8030698
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Distribution of blood mercury levels by demographic and socioeconomic characteristics and results from simple cumulative logistic models for mercury levels.
| N | 927 | 646 | 263 | 18 | |||
| row % | 69.7% | 28.4% | 1.9% | ||||
| <0.01 | |||||||
| Non-Hispanic white | N | 181 | 122 | 56 | 3 | A | |
| row % | 67.4% | 30.9% | 1.7% | ||||
| Non-Hispanic black | N | 629 | 455 | 165 | 9 | A | |
| row % | 72.3% | 26.2% | 1.4% | ||||
| Hispanic | N | 58 | 40 | 17 | 1 | A | |
| row % | 69.0% | 29.3% | 1.7% | ||||
| Asian/Pacific Islander | N | 40 | 13 | 22 | 5 | ||
| row % | 32.5% | 55.0% | 12.5% | ||||
| <0.01 | |||||||
| 18–19 years | N | 134 | 109 | 23 | 2 | ||
| row % | 81.3% | 17.2% | 1.5% | ||||
| 20–34 years | N | 662 | 472 | 178 | 12 | ||
| row % | 71.3% | 26.9% | 1.8% | ||||
| ≥35 years | N | 131 | 65 | 62 | 4 | ||
| row % | 49.6% | 47.3% | 3.1% | ||||
| <0.01 | |||||||
| Less than high school | N | 114 | 86 | 26 | 2 | B | |
| row % | 75.4% | 22.8% | 1.8% | ||||
| Completed high school | N | 358 | 276 | 78 | 4 | B | |
| row % | 77.1% | 21.8% | 1.1% | ||||
| Beyond high school | N | 455 | 284 | 159 | 12 | ||
| row % | 62.4% | 34.9% | 2.6% | ||||
| <0.01 | |||||||
| <$20, 000 | N | 441 | 341 | 96 | 4 | ||
| row % | 77.3% | 21.8% | 0.9% | ||||
| $20,000–$39,999 | N | 169 | 118 | 47 | 4 | ||
| row % | 69.8% | 27.8% | 2.4% | ||||
| ≥$40,000 | N | 217 | 122 | 88 | 7 | ||
| row % | 56.2% | 40.6% | 3.2% | ||||
| <0.01 | |||||||
| Married | N | 326 | 192 | 123 | 11 | ||
| row % | 58.9% | 37.7% | 3.4% | ||||
| Not married | N | 599 | 452 | 140 | 7 | ||
| row % | 75.5% | 23.4% | 1.2% | ||||
Maternal blood mercury level categories are defined as: below the detection limit (<1 μg/L), detectable but not elevated (1–3 μg/L), and elevated (≥4 μg/L).
A separate cumulative logistic model for mercury level was fit for each covariate. Mercury level was defined as (1) below the detection limit, (2) detectable but not elevated, and (3) detectable and elevated. Score tests in each model indicated that the proportional odds assumption was not violated (p > 0.05).
Levels of each covariates identified with the same letter were not significantly different at α = 0.05.
Percent reporting fish consumption from various sources (among those answering each survey question) and mean total reported fish meals per week by demographic and socioeconomic characteristics.
| 67.8% | 35.8% | 56.3% | 10.3% | 1.7 | 2.5 | |||||
| Non-Hispanic white | 67.6% | 35.2% | 56.7% | 3.9% | 1.0 | 1.1 | ||||
| Non-Hispanic black | 68.0% | 36.6% | 56.0% | 12.1% | 2.0 | 2.9 | ||||
| Hispanic | 59.7% | 37.5% | 42.1% | 14.3% | 1.3 | 1.8 | ||||
| Asian/Pacific Islander | 79.0% | 23.7% | 79.0% | 5.4% | 1.4 | 1.6 | ||||
| 18–19 years | 60.5% | 31.5% | 43.6% | 12.1% | 1.6 | 2.6 | ||||
| 20–34 years | 67.6% | 35.6% | 56.9% | 10.1% | 1.7 | 2.5 | ||||
| ≥35 years | 76.0% | 40.6% | 65.9% | 9.4% | 1.7 | 2.4 | ||||
| Less than high school | 63.9% | 39.1% | 48.6% | 14.3% | 2.0 | 2.9 | ||||
| Completed high school | 68.2% | 38.0% | 55.1% | 13.8% | 2.0 | 2.8 | ||||
| Beyond high school | 68.6% | 33.3% | 59.1% | 6.7% | 1.4 | 2.0 | ||||
| <$20,000 | 64.5% | 37.5% | 51.4% | 12.6% | 1.9 | 2.9 | ||||
| $20,000–$39,999 | 72.7% | 30.9% | 58.9% | 7.4% | 1.7 | 2.6 | ||||
| ≥$40,000 | 70.4% | 34.3% | 64.6% | 5.7% | 1.2 | 1.3 | ||||
| Married | 71.5% | 36.3% | 65.9% | 7.6% | 1.5 | 1.9 | ||||
| Not married | 65.7% | 35.6% | 52.5% | 11.8% | 1.8 | 2.8 | ||||
p < 0.01,
p < 0.05 for an association between fish consumption measures and the demographic or socioeconomic characteristic.
Distribution of mercury levels among participants reporting fish consumption from various sources.
| N | 601 | 381 | 205 | 15 | 2.56 | (1.82, 3.60) | |
| row % | 63.4% | 34.1% | 2.5% | ||||
| N | 313 | 194 | 114 | 5 | 1.68 | (1.25, 2.26) | |
| row % | 62.0% | 36.4% | 1.6% | ||||
| N | 496 | 298 | 184 | 14 | 2.87 | (2.10, 3.92) | |
| row % | 60.1% | 37.1% | 2.8% | ||||
| N | 89 | 55 | 31 | 3 | 1.51 | (0.96, 2.36) | |
| row % | 61.8% | 34.8% | 3.4% | ||||
Maternal blood mercury level categories are defined as: below the detection limit (<1 μg/L), detectable but not elevated (1–3 μg/L), and elevated (≥4 μg/L).
A separate cumulative logistic model for mercury level was fit for each measure of fish consumption. The OR indicates the relative odds of being in a higher mercury category when mercury level was defined as (1) below the detection limit, (2) detectable but not elevated, and (3) detectable and elevated. Score tests in each model indicated that the proportional odds assumption was not violated (p > 0.05).
Row percents are among those who reported consumption from the specified source, not among those who responded to the survey question.
Covariate-adjusted odds ratios and 95% confidence intervals from multivariate cumulative logistic models for blood mercury level.
| Non-Hispanic white | 1.0 | — | 1.0 | — | 1.0 | — |
| Non-Hispanic black | 1.27 | (0.80, 2.02) | 1.29 | (0.80, 2.07) | 1.22 | (0.76, 1.94) |
| Hispanic | 1.59 | (0.72, 3.51) | 1.68 | (0.75, 3.75) | 1.52 | (0.70, 3.31) |
| Asian/Pacific Islander | 4.16 | (1.93, 8.94) | 4.31 | (1.96, 9.49) | 4.44 | (2.04, 9.68) |
| 18–19 years | 1.0 | — | 1.0 | — | 1.0 | — |
| 20–34 years | 2.07 | (1.11, 3.86) | 1.85 | (0.98, 3.48) | 2.03 | (1.09, 3.79) |
| ≥35 years | 3.22 | (1.54, 6.74) | 2.81 | (1.32, 5.97) | 3.14 | (1.49, 6.62) |
| Less than high school | 1.12 | (0.62, 2.00) | 1.16 | (0.63, 2.11) | 1.10 | (0.60, 2.00) |
| Completed high school | 1.0 | — | 1.0 | — | 1.0 | — |
| Beyond high school | 1.29 | (0.85, 1.95) | 1.38 | (0.90, 2.12) | 1.37 | (0.90, 2.08) |
| <$20,000 | 0.81 | (0.52, 1.26) | 0.73 | (0.47, 1.15) | 0.77 | (0.49, 1.20) |
| $20,000–$39,999 | 1.0 | — | 1.0 | — | 1.0 | — |
| ≥$40,000 | 1.25 | (0.74, 2.10) | 1.18 | (0.69, 2.00) | 1.27 | (0.75, 2.13) |
| Married | 1.0 | — | 1.0 | — | 1.0 | — |
| Not married | 0.82 | (0.53, 1.25) | 0.86 | (0.55, 1.33) | 0.81 | (0.53, 1.25) |
| Any source | 2.56 | (1.75, 3.74) | ||||
| Canned tuna | 1.68 | (1.19, 2.38) | ||||
| Store/restaurant-bought fish | 2.44 | (1.70, 3.51) | ||||
| Caught fish | 1.04 | (0.60, 1.80) | ||||
| Total fish meals per week | 1.10 | (1.03, 1.17) | ||||