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Ultra-processed and fast food consumption, exposure to phthalates during pregnancy, and socioeconomic disparities in phthalate exposures

Baker, Brennan H., Melough, Melissa M., Paquette, Alison G., Barrett, Emily S., Day, Drew B., Kannan, Kurunthachalam, HN Nguyen, Ruby, Bush, Nicole R., LeWinn, Kaja Z., Carroll, Kecia N., Swan, Shanna H., Zhao, Qi, Sathyanarayana, Sheela·2024·Environment International
DOI 10.1016/j.envint.2024.108427PMC PMC10834835
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Fig. 1. Distributions of 2nd trimester urinary phthalate metabolite levels among CANDLE participants (N = 827). Boxplots with 1.5 interquartile range (IQR) whiskers show distribution of log10-adjusted, specific gravity corrected urinary phthalate levels, and log10-adjusted DEHP molar sum. DEHP metabolites indicated in bold. DEHP molar sum calculated as (MEHP * (1/278.34)) + (MEHHP * (1/294.34)) + (MEOHP * (1/292.33)) + (MECPP * (1/308.33)) + (MCMHP * (1/308.33)).
Fig. 1. Distributions of 2nd trimester urinary phthalate metabolite levels among CANDLE participants (N = 827). Boxplots with 1.5 interquartile range (IQR) whiskers show distribution of log10-adjusted, specific gravity corrected urinary phthalate levels, and log10-adjusted DEHP molar sum. DEHP metabolites indicated in bold. DEHP molar sum calculated as (MEHP * (1/278.34)) + (MEHHP * (1/294.34)) + (MEOHP * (1/292.33)) + (MECPP * (1/308.33)) + (MCMHP * (1/308.33)).CC BY-NC-ND · PubMed Central
Fig. 2. NOVA food groups. Manual categorization of Block food frequency questionnaire frequency data into NOVA food groups.
Fig. 2. NOVA food groups. Manual categorization of Block food frequency questionnaire frequency data into NOVA food groups.CC BY-NC-ND · PubMed Central
Fig. 3. Associations of NOVA groups and ultra-processed foods with phthalate levels. Histogram (A) shows the distribution of CANDLE participants with respect to food frequency for ultra-processed and minimally processed food groups as a percentage of total food frequency. Linear model coefficients and 95% confidence intervals depict: (B) Associations of ultra-processed and minimally processed NOVA food group dietary proportions with phthalates from separate models for each NOVA group by phthalate outcome combination; (C) Associations of individual ultra-processed food items with DEHP molar sum from separate models per food item; and (D) A sensitivity analysis for the top four ultra-processed foods associated with sum DEHP where food items were modeled as percent of total daily energy intake rather than frequency of intake. All models in B-D were adjusted for maternal age, education, race, ethnicity, household income, number of individuals in the household, neighborhood deprivation index, pre-pregnancy BMI, tobacco and alcohol use, and daily caloric intake.
Fig. 3. Associations of NOVA groups and ultra-processed foods with phthalate levels. Histogram (A) shows the distribution of CANDLE participants with respect to food frequency for ultra-processed and minimally processed food groups as a percentage of total food frequency. Linear model coefficients and 95% confidence intervals depict: (B) Associations of ultra-processed and minimally processed NOVA food group dietary proportions with phthalates from separate models for each NOVA group by phthalate outcome combination; (C) Associations of individual ultra-processed food items with DEHP molar sum from separate models per food item; and (D) A sensitivity analysis for the top four ultra-processed foods associated with sum DEHP where food items were modeled as percent of total daily energy intake rather than frequency of intake. All models in B-D were adjusted for maternal age, education, race, ethnicity, household income, number of individuals in the household, neighborhood deprivation index, pre-pregnancy BMI, tobacco and alcohol use, and daily caloric intake.CC BY-NC-ND · PubMed Central
Fig. 4. Mediation analyses of sociodemographic characteristics, ultra-processed foods, and sum DEHP. Causal mediation analysis examining the role of ultra-processed food intake as a mediator on the pathway between socioeconomic factors and DEHP exposure during pregnancy. Regression-based mediation approach was implemented in the ‘CMAverse’ R package with closed-form parameter function estimation and bootstrap inference with 1,000 iterations. Models estimated the percent change in DEHP (95 % confidence interval) associated with: (A) being in the 75th ($71,440.5) versus 25th ($17,909.0) percentiles of income, (B) higher education versus no higher education, and (C) being in the 75th versus 25th percentiles of neighborhood deprivation index. The no higher education group includes individuals self-reporting “High School completion” and “<High School” while the higher education group includes individuals self-reporting “Some graduate work or graduate/professional degree” and “Graduated college or technical school.” P values < 0.05 indicated in bold.
Fig. 4. Mediation analyses of sociodemographic characteristics, ultra-processed foods, and sum DEHP. Causal mediation analysis examining the role of ultra-processed food intake as a mediator on the pathway between socioeconomic factors and DEHP exposure during pregnancy. Regression-based mediation approach was implemented in the ‘CMAverse’ R package with closed-form parameter function estimation and bootstrap inference with 1,000 iterations. Models estimated the percent change in DEHP (95 % confidence interval) associated with: (A) being in the 75th ($71,440.5) versus 25th ($17,909.0) percentiles of income, (B) higher education versus no higher education, and (C) being in the 75th versus 25th percentiles of neighborhood deprivation index. The no higher education group includes individuals self-reporting “High School completion” and “<High School” while the higher education group includes individuals self-reporting “Some graduate work or graduate/professional degree” and “Graduated college or technical school.” P values < 0.05 indicated in bold.CC BY-NC-ND · PubMed Central
Fig. 5. Associations of FFQ factors with phthalate levels. Exploratory factor analysis with 5 factors for 114 food item frequencies from the Block FFQ (A). Top 12 loadings for each factor shown. Loadings are approximately equal to Pearson correlations between the food items and factors (i.e., milk on cereal is nearly 100% correlated with the “Cereal” factor). Coefficients and 95% confidence intervals depict one-percent increase in phthalate exposures per one-standard deviation (std. dev) increase in FFQ factors (B). Linear models include all 5 factors and covariates as predictors of phthalates, with one model per metabolite. Covariates included age, education, race, ethnicity, household income, number of individuals in the household, neighborhood deprivation index, pre-pregnancy BMI, tobacco and alcohol use, and daily caloric intake.
Fig. 5. Associations of FFQ factors with phthalate levels. Exploratory factor analysis with 5 factors for 114 food item frequencies from the Block FFQ (A). Top 12 loadings for each factor shown. Loadings are approximately equal to Pearson correlations between the food items and factors (i.e., milk on cereal is nearly 100% correlated with the “Cereal” factor). Coefficients and 95% confidence intervals depict one-percent increase in phthalate exposures per one-standard deviation (std. dev) increase in FFQ factors (B). Linear models include all 5 factors and covariates as predictors of phthalates, with one model per metabolite. Covariates included age, education, race, ethnicity, household income, number of individuals in the household, neighborhood deprivation index, pre-pregnancy BMI, tobacco and alcohol use, and daily caloric intake.CC BY-NC-ND · PubMed Central

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Authors
Baker, B. H., Melough, M. M., Paquette, A. G., Barrett, E. S., Day, D. B., Kannan, K., HN Nguyen, R., Bush, N. R., LeWinn, K. Z., Carroll, K. N., Swan, S. H., Zhao, Q., & Sathyanarayana, S.
ORCID
Venue
Environment International
Publisher
Elsevier BV
Published
2024-01
Volume
183
Pages
108427
ISSN
0160-4120
DOI
10.1016/j.envint.2024.108427
PMC
PMC10834835
Cited by
64
References
4
Language
en
Update notices
erratum (2024-04-01)
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Funders
  • National Institutes of Health (UG3/UH3OD023271)
  • Urban Child Institute
  • Eunice Kennedy Shriver National Institute of Child Health and Human Development (K99/R00HD096112, P30ES005022)
  • National Institute of Environmental Health Sciences (1R01ES033785, T32ES015459)

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