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1.
Case Reports Hepatol ; 2024: 5112461, 2024.
Article in English | MEDLINE | ID: mdl-38826497

ABSTRACT

Drug-induced liver injury resulting from herbal and dietary supplement use is increasingly common and underrecognized. We report a case of a 34-year-old male recreational bodybuilder who presented with muscle cramping, fatigue, and diffuse itching in the setting of bodybuilding supplement use. Labs showed cholestatic liver injury, and liver biopsy revealed bland cholestasis and sinusoidal dilation. He was diagnosed with anabolic-androgenic steroid-induced liver injury. He was symptomatically managed with plasmapheresis for debilitating pruritus. This case highlights drug-induced liver injury as a complication of bodybuilding supplement use containing unlabeled anabolic-androgenic steroids. Sports medicine providers should inquire on herbal and dietary supplement use and be aware of potential contaminants.

2.
J Expo Sci Environ Epidemiol ; 28(1): 21-30, 2018 01.
Article in English | MEDLINE | ID: mdl-28000685

ABSTRACT

The U.S. Food and Drug Administration's (FDA) Total Diet Study (TDS) monitors the US food supply for pesticide residues, industrial chemicals, radionuclides, nutrients, and toxic elements. Perchlorate and iodine intakes based on concentrations in TDS samples collected between 2008 and 2012 were estimated in order to update an earlier TDS dietary assessment. Perchlorate is used as an oxidizing agent in rocket and missile fuel, is formed naturally in the atmosphere, and occurs naturally in some soils. Because of perchlorate's presence in soil, and in irrigation, processing, and source water, it is widely found in food. Iodine was included in the study because perchlorate at high doses interferes with iodide uptake in the thyroid. Iodine (the elemental form of iodide) is essential for growth and development, and metabolism. This study uses a novel statistical method based on a clustered zero-inflated lognormal distribution model to estimate mean and 95th percentile confidence interval concentrations for perchlorate and iodine in US foods. These estimates were used to estimate mean perchlorate and iodine exposures for the total US population and for 14 age/sex groups in the US population. Estimated mean perchlorate intake for the total US population was 0.13 µg/kg bw/day, with mean intakes for the 14 age/sex groups between 0.09 and 0.43 µg/kg bw/day. The estimated mean intakes of perchlorate for all age/sex groups were below EPA's reference dose (RfD) of 0.7 µg/kg bw/day. The estimated mean iodine intake for the total US population was 216.4 µg/person/day, with mean intakes ranging from 140.9 to 296.3 µg/person/day for the 14 age/sex groups, with all age/sex groups exceeding their respective estimated average requirements (EARs).


Subject(s)
Environmental Exposure/analysis , Food Contamination/analysis , Iodine/analysis , Perchlorates/analysis , Adolescent , Adult , Age Distribution , Child , Child, Preschool , Diet Surveys , Female , Food Analysis , Humans , Infant , Male , Middle Aged , Sex Distribution , United States , United States Food and Drug Administration
3.
Am J Clin Nutr ; 104 Suppl 3: 868S-76S, 2016 Sep.
Article in English | MEDLINE | ID: mdl-27534627

ABSTRACT

The US Food and Drug Administration (FDA) and the Nutrient Data Laboratory (NDL) of the USDA Agricultural Research Service have worked independently on determining the iodine content of foods and dietary supplements and are now harmonizing their efforts. The objective of the current article is to describe the harmonization plan and the results of initial iodine analyses accomplished under that plan. For many years, the FDA's Total Diet Study (TDS) has measured iodine concentrations in selected foods collected in 4 regions of the country each year. For more than a decade, the NDL has collected and analyzed foods as part of the National Food and Nutrient Analysis Program; iodine analysis is now being added to the program. The NDL recently qualified a commercial laboratory to conduct iodine analysis of foods by an inductively coupled plasma mass spectrometry (ICP-MS) method. Co-analysis of a set of samples by the commercial laboratory using the ICP-MS method and by the FDA laboratory using its standard colorimetric method yielded comparable results. The FDA recently reviewed historical TDS data for trends in the iodine content of selected foods, and the NDL analyzed samples of a limited subset of those foods for iodine. The FDA and the NDL are working to combine their data on iodine in foods and to produce an online database that can be used for estimating iodine intake from foods in the US population. In addition, the NDL continues to analyze dietary supplements for iodine and, in collaboration with the NIH Office of Dietary Supplements, to publish the data online in the Dietary Supplement Ingredient Database. The goal is to provide, through these 2 harmonized databases and the continuing TDS focus on iodine, improved tools for estimating iodine intake in population studies.


Subject(s)
Databases, Factual , Diet , Dietary Supplements , Food Analysis/methods , Iodine/analysis , Humans , Internet , Iodine/administration & dosage , United States , United States Department of Agriculture
4.
Am J Clin Nutr ; 104 Suppl 3: 877S-87S, 2016 Sep.
Article in English | MEDLINE | ID: mdl-27534633

ABSTRACT

BACKGROUND: Food-composition tables typically give measured nutrient concentrations in foods as a single summary value, often the mean, without providing information as to the shape of the distribution. OBJECTIVE: Our objective was to explore how the statistical approach chosen to describe the iodine concentrations of foods affects the proportion of the population identified as having either insufficient or excessive iodine intakes. DESIGN: We used food intake data reported by the 2009-2010 NHANES and measured iodine concentrations of Total Diet Study (TDS) foods from 4 US regions sampled in 2004-2011. We created 4 data sets, each by using a different summary statistic (median, mean, and 10th and 90th percentiles), to represent the iodine concentration distribution of each TDS food. We estimated the iodine concentration distribution of each food consumed by NHANES participants as the 4 iodine concentration summary statistics of a similar TDS food and used these, along with NHANES food intake data, to develop 4 estimates of each participant's iodine intake on each survey day. Using the 4 estimates in turn, we calculated 4 usual iodine intakes for each sex- and age-specific subgroup. We then compared these to guideline values and developed 4 estimates of the proportions of each subgroup with deficient and excessive usual iodine intakes. RESULTS: In general, the distribution of iodine intakes was poorly characterized when food iodine concentrations were expressed as mean values. In addition, mean values predicted lower prevalences of iodine deficiency than did median values. For example, in women aged 19-50 y, the estimated prevalence of iodine deficiency was 25% when based on median food iodine concentrations but only 5.8% when based on mean values. CONCLUSION: For nutrients such as iodine with highly variable concentrations in important food sources, we recommend that food-composition tables provide useful variability information, including the mean, SD, and median.


Subject(s)
Diet , Iodine/administration & dosage , Nutrition Assessment , Nutritional Requirements , Research Design , Adolescent , Adult , Aged , Child , Child, Preschool , Datasets as Topic/statistics & numerical data , Feeding Behavior , Female , Food , Humans , Infant , Iodides/administration & dosage , Iodine/deficiency , Male , Middle Aged , Nutrition Policy , Nutrition Surveys , Overnutrition , Research Design/statistics & numerical data , United States , Young Adult
5.
J Fam Pract ; 64(9): 586-97, 2015 Sep.
Article in English | MEDLINE | ID: mdl-26546960

ABSTRACT

Breastfeeding support, beyond standard care, from lay people or professionals increases both short- and long-term breastfeeding duration.


Subject(s)
Breast Feeding , Health Promotion/methods , Maternal Health Services , Breast Feeding/psychology , Breast Feeding/statistics & numerical data , Female , Humans , Social Support , Time Factors
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