Category Archives: Nutrition

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:

New lipid emulsions — lacking data to support usage

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According to a systematic review of the literature regarding ω-3 (n-3FA) fatty acid lipid emulsions, there is a “lack of sufficient high-quality data to support the use of parenteral n-3FA lipid emulsions in children” (JPEN 2013; 37: 44-55). Thanks to Kipp Ellsworth for this reference.

The authors of this study researched 4 databases up to March 2011 and extracted relevant studies.  Five randomized controlled trials and 3 high-quality prospective cohort studies were included.  The strength of evidence was “consistently low or very low across all lipid emulsion comparisons and outcomes.”

Specific criticisms:

  • Few studies examined important outcomes like length of hospital stay or intensive care stay.
  • There was lack of data on growth, cognitive development or potential long-term effects/harms.
  • All of the studies in children varied considerably with regard to the dosing regimens, duration of administration, and duration of followup.
  • The studies were small with sample sizes ranging from 28-91 patients.
  • The 5 RCTs had unclear risk of bias due to inadequate blinding of participants and study personnel.
  • All of the RCTs were funded by the manufacturer.
  • While some biochemical outcomes improved, no difference in mortality has been identified.  A biochemical response is a poor measure of effectiveness.  In fact, several studies have shown deterioration in liver histology and fibrosis despite improved biochemical measures in infants on Omegaven.
  • For Omegaven (fish oil) treatment, all studies used a historical control group.  In these studies, typically the Omegaven dose was half the dose of Intralipid used in the control group.

This article (in its Table 1) identifies the constituents in the commercial available lipid products which include Intralipid, Clinoleic, Liposyn II, Omegaven, SMOFLipid, and Lipoplus.  Intralipid which is widely used is devoid of substantial arachidonic acid (ARA) and docosahexaenoic adic (DHA).  This is particularly important in premature infants as noted in recent blogs:

Omegaven, in particular, and SMOFLipid, to a lesser degree, have much more AA and DHA.  As such, both of these emulsions have the potential improve vision and cognitive outcome in premature infants.

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Is fasting needed before checking lipids?

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Not really.  According to a recent study involving 209,180 individuals, fasting times showed little association with lipid levels in a community-based population (Arch Intern Med 2012; 172: 1707-10).

Although current guidelines suggest obtaining lipid levels after fasting, lipid levels do not vary much between fasting and nonfasting states.  Furthermore, fasting may not be reflective of the patient’s typical metabolic state.

Design: cross-sectional study over a 6-month period in 2011 (Calgary) using a large community-based cohort.  The average age of the participants was 52.8 years.

Results: In tables 1 and 2, the authors provide the cholesterol values for fasting times that varied from 1 hour to 16 hour.  The vast majority fasted for 10 hours or more.  For example, less than 1% of the cohort fasted for only 1 hour.  However, fasting time showed little association with lipid subclass levels, suggesting that fasting for routine levels is not necessary.

There were several limitations of the study.  The meal choices in the nonfasting groups were not known and the study was not randomized.  In addition, LDL values were not calculated when triglycerides were >400 mg/dL; this represented 1.5% of the study population.  The authors recommend that in individuals with triglycerides >400 mg/dL that fasting lipid levels could be considered.

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Microbiome and the risk of Kwashiokor

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On the way home from work, NPR highlighted a study that suggests that altered microbiome may increase the risk of Kwashiokor (Gut Microbes May Play Deadly Role In Malnutrition : Shots … – NPR).

Interestingly, a separate article indicates that antibiotics lowers the mortality in severe acute malnutrition (NEJM 2013; 368: 425-35).  In this study, 2767 children from 18 feeding clinics in Malawi (2009-2011) were enrolled in a randomized, double-blind, placebo-controlled trial.  Children were 6 to 59 months of age with severe acute malnutrition.  Those who received amoxicillin, cefdinir, and placebo recovered in 88.7%, 90.9%, and 85.1% respectively.  The relative risk of death in the placebo group was 1.55 compared to amoxicillin and 1.80 compared to cefdinir.  The children in the antibiotic group also had improved growth.

The authors suggest that the reason for improvement is likely to be due to fewer invasive bacterial infections.  These infections are frequent and thought to be related to translocation across compromised mucosal surfaces.  However, perhaps the antibiotics act by producing a more favorable microbiome which in turn promotes improvement.  As such, microbes have a role in contributing to obesity (Microbial transfer for metabolic syndrome? | gutsandgrowth) and to starvation.

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