Category Archives: Nutrition

Drug Shortages and Selenium Deficiency

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If you participate in the care of patients who are dependent on parenteral nutrition, then you are familiar with frequent component drug shortages.  Generally, attempts to manage these shortages involve rationing and targeting those with the greatest need.  In one institution, this was not effective in preventing biochemical deficiency of selenium (JPEN 2013; DOI 10.1177/0148607113486005).  Thanks to Kipp Ellsworth for this reference.

The authors describe five pediatric patients who were completely dependent on parenteral nutrition due to intestinal failure.  During a 9-month shortage of intravenous selenium, all five who were previously selenium replete had deficiency identified (level <20 ng/mL).

After these deficiencies were identified, the patients were placed on Multitrace-5 (MTE-5).  This multivitamin contains 20 mcg/mL of selenium.  While patients prior to the shortage typically received 50-75 mcg/day, after instituting MTE-5, they received 10-26 mcg/day.  Nevertheless, this helped prevent any clinical evidence of deficiency.  In patients with selenium deficiency, there is an increased risk of cardiomyopathy, chronic illness, and death.

The authors note that their preference is to individually dose the specific trace elements and that MTE-5 can contribute to elevated levels of manganese and chromium with long-term usage.

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Related references:

  • -Gastroenterol 2009; 137: S61-S69.
  • -J Pediatr 2011; 159: 39.

An easy tool to assess cardiometabolic risk

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There are a large number of anthropometrics to assess nutrition; however, simplifying the assessment would facilitate broader usage.  To that end, a recent publication suggests that checking triglyceride level and waist circumference is helpful to identify cardiometabolic risk (J Pediatr 2013; 162: 746-52).

This study used a cross-sectional design; anthropometrics, biochemistries, and cardiorespiratory fitness were assessed in 234 participants between 10-19 years of age.

Specific measurements included the following: weight, height, waist-to-height ratio (WHTR), lipid panel, blood pressure, and a cardiorespiratory fitness (CRF) as assessed by a progressive cycle ergometer tests.  The authors defined a HW or hypertriglyceridemic waist phenotype characterized as having a triglyceride ≥110 mg/dL and a waist circumference ≥ 90% for age/sex.

Key findings:

  • Participants with the HW phenotype were unlikely to have a high CRF (OR 0.045).  In addition, they had a high likelihood of elevated LDL (OR 4.41), impaired fasting blood glucose (OR 3.37).
  • Those with high WHTR were at higher odds for having low HDL (OR 2.57), high diastolic BP (OR 3.21) compared with normal WHTR participants.

Lunchroom Makeover

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A recent pilot study indicates that $50 and three hours can increase the chances that teens will eat their fruits and vegetables (J Pediatr 2013; 162: 867-9).  While the US Department of Agriculture has mandated alterations in what foods that schools offer for lunch, schools cannot force students to eat specific foods.  As such, the authors tried changing the convenience, attractiveness, and ‘normative nature of healthy foods’ in the lunchroom. These changes are part of a behavioral science called “libertarian paternalism.”

These field studies took place at two schools in western New York with students at 7-12 grade levels.  After implementing changes in the lunchrooms, researchers recorded tray waste on multiple dates.

Specific changes included the following:

Improved convenience:

  • “Healthy convenience line” with only submarine sandwiches and healthier sides (fruits/vegetables)
  • Salad served in see-through to-go containers

Improved attractiveness:

  • Lunch menu posted with nice color photos of fruits and vegetables
  • Fruit displayed in nice bowls or tiered stands

Normative behavior:

  • Verbal prompts by staff: “Would you like to try…”, “No veggie? How about…” “You can get another side with your meal. How about grabbing a piece of fruit?”
  • “Last chance for Fruit” sign displayed next to fruit basket at the cash register

The impact of the “smarter lunchroom:” actual fruit consumption increased by 18% and vegetable consumption increased by 23%.  The limitations of this study: no control school, did not track individual consumption, and small number of measured days.

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How to gain too much weight –attend daycare?

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According to a provocative study (J Pediatr 2013; 162: 753-8), receiving childcare as opposed to parental care was associated with increased weight.

1649 children were enrolled in a prospective birth cohort in Quebec.  Information about childcare was completed by their mothers at ages 1.5, 2.5, 3.5 and 4 years.  In addition, body mass index (BMI) was checked at ages 4, 6, 7, and 10 years of age.

Compared with care at home, children who attended a center-based childcare or were cared for by a relative were at increased risk of being overweight or obese, with odds ratios of 1.65 for center-based care and 1.5 for relative-based care.  Furthermore, increased hours away from home was associated with increased odds; every 5 hours increased the likelihood by 9% in the first decade of life.

These associations could not be explained by a number of potential confounding factors including socioeconomic status, breastfeeding, maternal employment, and maternal BMI (along with many other factors). In addition, the authors note in their discussion that these results are in line with other large studies from a number of countries.  One hypothesis for relative-based care has been that this may involve less physical activity, especially by grandparents.

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Food Marketing Detectable on Functional MRI

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The applications of functional magnetic resonance imaging (MRI) are burgeoning.  One recent usage has been on the effect of food logos on brain activation in obese and healthy children (J Pediatr 2013; 162: 759-64 & editorial 672-73).

After a pilot validation study to select food and nonfood logos, the authors recruited 10 healthy children with mean body mass index (BMI) at 50th percentile and 10 obese children with mean BMI at the ~98 percentile.  After completing reports on measures of self-control, the children underwent functional MRI while viewing food and nonfood logos.

The key findings were that healthy weight children, when viewing food logos, demonstrated greater activation in brain regions associated with cognitive control/self-control including Brodmann’s area 10 and the inferior frontal gyrus bilaterally.  Obese children showed greater activation in ‘reward’ regions of the brain when shown food logos.

While these studies should be considered preliminary due to the small sample size, they are intriguing nevertheless.  The editorial takes these findings and places them into context.

  • Children view ~6000 commercials annually; the majority feature calorie-dense and nutrient poor foods
  • “Any food can be marketed in any way, to any age group, and even the most vulnerable demographic groups can be targeted.”
  • “It is tempting to suggest interventions…to help resist marketed foods.”  However, the author notes that this strategy will fail due to increases in the “toxic influence” of advertising.
  • “Food brands are already commonplace in …sporting facilities, schools..in online advergaming..and in social media.”
  • “Targeted advertising has been related to greater consumption of high-calorie foods (eg. fast foods) by African-American and Hispanic children”
  • Policy initiatives “to turn back the tide of childhood obesity” are needed; studies that show a direct impact on children’s brains may be persuasive in compelling change.  Without these changes, companies will continue doing neuroscience research and will exploit their findings.

Bottom-line:  If one uses an analogy to tobacco, it is not quite 1964 for the food industry.

“In 1964 the Surgeon General of the U.S. (the chief doctor for the country) wrote a report about the dangers of cigarette smoking. He said that the nicotine and tar in cigarettes cause lung cancer. In 1965 the Congress of the U.S. passed the Cigarette Labelling and Advertising Act. It said that every cigarette pack must have a warning label on its side stating ‘Cigarettes may be hazardous to your health.'” History of Tobacco – Health & Literacy Special Collection

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Life Cut Short by Obesity

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When someone is too heavy, everyone knows that this is associated with numerous health risks.  A recent estimate on the amount of life lost due to obesity has been published (Obesity 2013; 21: 405-12).

Using data from the National Health and Nutrition Examination Survey (NHANES) I (1971-75), II (1976-80), and III (1988-94), the author was able to follow-up for 15 years and prospectively analyzed the data to calculate the relative risk of death and the “advancement period” of death due to obesity.  Stratification of death was adjusted for covariates including pre-existing illness, smoking, and older age.

The study focused on otherwise healthy nonsmokers to isolate the effects of obesity on mortality.  The averages of the cohorts was 46-48 years of age. While the author studied only 37,632 patients who had 8,791 deaths during the study, these results are relevant to about one-third of American adults.

Key finding: Compared to reference weight (BMI 23-25 kg/meter-squared), mortality was likely to occur 9.44 years earlier for those who were obese (BMI ≥ 30).

When the data was divided by weight, overweight (BMI 25-30 kg/meter-squared), mild obesity (BMI 30-35 kg/meter-squared), and obesity grades 2-3 (BMI >35 kg/meter-squared), the results were 4.40 years, 6.69 years, and 14.16 years respectively. The effect on advancement period mortality was less in older age groups (>55 years).

The main limitation of the study was its reliance on statistical analysis.  For those without a statistical background, Figure 2 which describes the mortality risk advancement period formula could as easily be written in Chinese.  Nevertheless, in the discussion the author underscores that these estimates are consistent with prior studies.

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Malnutrition Redefined

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Defining malnutrition accurately is the focus of a new report (JPEN 2013; DOI: 10.1177/0148507113479972). Thanks to Kipp Ellsworth for this article.

The Pediatric Malnutrition Definitions Workgroup was formed in April 2010 and makes numerous relevant contributions to precisely defining malnutrition.  The reasons for this workgroup and report are to promote the following:

  • early identification of those at risk for malnutrition
  • allow better comparison of malnutrition prevalence & collect meaningful data
  • develop uniform screening tools
  • develop thresholds for intervention
  • improve assessment of outcomes

“Pediatric malnutrition (undernutrition) is defined as an imbalance between nutrient requirement and intake, resulting in cumulative deficits of energy, protein, or micronutrients that may negatively affect growth, development, or other relevant outcomes.”

First, malnutrition is subdivided into two categories: illness-related malnutrition and non-illness-related malnutrition.  Illness-related malnutrition refers to malnutrition caused by chronic conditions, burns, and surgery.  It is the predominant cause in developed countries.  Non-illness-related malnutrition refers to malnutrition caused by environmental or behavioral factors (including food aversions or anorexia).

Illness-related malnutrition occurs due to nutrient loss, increased energy expenditure, decreased nutrient intake, or altered nutrient utilization.

In brief, patients need to be assessed in five domains: anthropometrics, growth charts, chronicity, etiology/pathogenesis, and functional status.

Summary of recommendations:

  1. Record anthropometric variables on admission and serially.  These measurements include weight, height, BMI, mid-upper arm circumference (MUAC) and consider triceps skin fold (TSF) and mid-arm muscle circumference.  Obtain head circumference if younger than 2 years.
  2. In infants/children <2 years, measure length with recumbent board. In older patients unable to stand, consider alternative measurement like tibia length or knee height for a height proxy.
  3. Use the 2006 World Health Organization growth charts in patients younger than 2 years and the CBC 2000 growth charts for children 2-20 years. In addition, use corrected age (number of weeks/months premature + chronological age) for preterm infants until they are 3 years old.
  4. Use a decline in z score for individual anthropometric measurements as the indication of faltering growth.
  5. Use 3 months as a cutoff to classify as acute or chronic.
  6. Include description of predominant mechanism of malnutrition: decreased intake, increased requirements, excessive losses, or failure to assimilate/malabsorption.
  7. Recognize the role of inflammation on nutrition status.
  8. Assess impact of malnutrition: consider developmental assessment, lean body mass measurements, and measures of muscle strength.

By having a better established uniform definition of malnutrition, impact on outcomes will be easier to assess. In addition to the potential outcomes noted above (#8), others that will need to be examined in relation to malnutrition include length of hospital stay, wound healing, frequency of infections, behavioral problems, and disease-specific resource utilization.

This article also reviews previous definitions and potential problems with their usage.  For example, Waterlow criteria rely on percentiles and standard deviations and are used widely.  In hospitalized children, accurate serial weights and heights can be challenging due to fluid retention and poor mobility.

The authors note that malnutrition is likely underdiagnosed and inadequately treated.  Some recent estimates indicate that malnutrition is present “in 40% of patients with neurologic conditions, 34.5% in those with infectious diseases, 33.3% of those with cystic fibrosis, 28.6% in those with cardiovascular disease, 27.3% in oncology patients, and 23.6% in those with GI diseases. Patients with multiple diagnoses are most likely to be malnourished (43.8%).”

Bottomline: A lot of patients are malnourished.  Recognition of malnutrition (defining what is malnutrition) should improve outcomes.

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What happens to micronutrient levels in the hospital setting?

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When atypical labs need to be obtained, many times this is easier in the hospital setting for logistical reasons including insurance and accessibility to specialty labs.  One group of labs that may be less suited for checking in the hospital, despite convenience, would be micronutrients.  Many of the micronutrients can be affected by systemic inflammatory response (Am J Clin Nutr 2012; 95: 64-71).  Thanks to Kipp Ellsworth for this reference (from his @PedNutritionGuy twitter feed).

Previous studies on systemic inflammatory response (SIR), as assessed by elevated C-reactive protein (CRP) concentrations, has shown that with elective surgery there are transient decreases in plasma concentrations of zinc, selenium, iron, vitamin A, vitamin E, carotenoids, riboflavin, vitamin B-6, vitamin C, and vitamin D.

This current study adds to this body of information.  Between 2001-2011, 2217 whole-blood samples were taken from 1303 patients. Specific micronutrients that were studied: plasma zinc, copper, selenium, vitamins A, B-6, C, and E.  For vitamin D, the authors examined 4327 samples from 3677 patients. The authors did not include manganese, thiamine or riboflavin because these are measured in erythrocytes.

For each analyte, the concentrations were separated according to 6 categories of CRP values: <5, 6-10, 11-20, 21-40, 41-80, and >80 mg/L.

Key finding: Except for copper and vitamin E, all plasma micronutrient concentrations decreased with increasing severity of acute inflammatory response.  For selenium, vitamin B-6, and vitamin C, this occurred with only slight increases in CRP (5 to 10 mg/L).

The magnitude of the SIR effect on micronutrients was quite variable among patients and analytes.  When CRP was >80 mg/L, analyte deficiency rate was noted to be the following:

  • 60 % for selenium (vs. 33% with NL CRP)
  • 48% for vitamin A (vs. 7% with NL CRP)
  • 35% for vitamin B-6 (vs. 14% with NL CRP)
  • 80% for vitamin C (vs. 33% with NL CRP)
  • 88% for vitamin D (vs. 69% with NL CRP)
  • 81% for zinc (vs. 33% with NL CRP)
  • 9% for copper (vs. 4% with NL CRP)
  • 16% for vitamin E (vs. 9% with NL CRP)

**The specific normal value cutoffs and more data at all CRP values are noted in Table 9 of the manuscript.

The implications from this study are clear.  When micronutrient values are derived from plasma during a SIR, a false-positive diagnosis of a micronutrient deficiency is more likely. The study has several limitations and the findings may not be applicable to all types of medical conditions.

Authors conclusion: When CRP concentration is >20 mg/L (>2 mg/dL), “plasma concentrations of selenium, zinc, and vitamins A, B-6, C, and D are clinically uninterpretable.”

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Heart-healthy Mediterranean Diet

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From AJC (see link below): “The study lasted five years and involved about 7,500 people in Spain. Those who ate Mediterranean-style with lots of olive oil or nuts had a 30 percent lower risk of major cardiovascular problems compared to those who were told to follow a low-fat diet but who in reality, didn’t cut fat very much. Mediterranean meant lots of fruit, fish, chicken, beans, tomato sauce, salads, and wine and little baked goods and pastries.” Methods (at NEJM.org) “In a multicenter trial in Spain, we randomly assigned participants who were at high cardiovascular risk, but with no cardiovascular disease at enrollment, to one of three diets: a Mediterranean diet supplemented with extra-virgin olive oil, a Mediterranean diet supplemented with mixed nuts, or a control diet (advice to reduce dietary fat). Participants received quarterly individual and group educational sessions and, depending on group assignment, free provision of extra-virgin olive oil, mixed nuts, or small nonfood gifts. The primary end point was the rate of major cardiovascular events (myocardial infarction, stroke, or death from cardiovascular causes). On the basis of the results of an interim analysis, the trial was stopped after a median follow-up of 4.8 years.”

Related blog entry: Six years later-Mediterranean diet comes out on top | gutsandgrowth

Taking Folic Acid for Autism Prevention

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A large study in JAMA shows an association between taking folic acid and reducing the risk of autism by about 40% (JAMA. 2013;309(6):570-577. doi:10.1001/jama.2012.155925). JAMA Network | JAMA | Association Between Mater

“The study sample of 85,176 children was derived from the population-based, prospective Norwegian Mother and Child Cohort Study.”  The study took place between 2002-2008.  Pregancies in which mothers received folic acid for 4 weeks before the last menstrual period and for at least 8 weeks into the pregnancy were compared with those unexposed to folic acid.

Results:

“At the end of follow-up, 270 children in the study sample had been diagnosed with ASDs: 114 with autistic disorder, 56 with Asperger syndrome, and 100 with PDD-NOS. In children whose mothers took folic acid, 0.10% (64/61,042) had autistic disorder, compared with 0.21% (50/24,134) in those unexposed to folic acid. The adjusted OR for autistic disorder in children of folic acid users was 0.61 (95% CI, 0.41-0.90). No association was found with Asperger syndrome or PDD-NOS, but power was limited. Similar analyses for prenatal fish oil supplements showed no such association with autistic disorder, even though fish oil use was associated with the same maternal characteristics as folic acid use.”

While this study does not prove a causal relationship between maternal folic acid intake and autism, since folic acid is already recommended to prevent neural tube defects, this provides another potential benefit to this intervention.

From ABC news coverage: