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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">ETM</journal-id>
<journal-title-group>
<journal-title>Experimental and Therapeutic Medicine</journal-title>
</journal-title-group>
<issn pub-type="ppub">1792-0981</issn>
<issn pub-type="epub">1792-1015</issn>
<publisher>
<publisher-name>D.A. Spandidos</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3892/etm.2016.3137</article-id>
<article-id pub-id-type="publisher-id">ETM-0-0-3137</article-id>
<article-categories>
<subj-group>
<subject>Review</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Protein intake and obesity in young adolescents</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author"><name><surname>XU</surname><given-names>SHUMEI</given-names></name>
<xref rid="af1-etm-0-0-3137" ref-type="aff"/></contrib>
<contrib contrib-type="author"><name><surname>XUE</surname><given-names>YING</given-names></name>
<xref rid="af1-etm-0-0-3137" ref-type="aff"/>
<xref rid="c1-etm-0-0-3137" ref-type="corresp"/></contrib>
</contrib-group>
<aff id="af1-etm-0-0-3137">Department of Endocrinology, Xuzhou Children&#x0027;s Hospital, Xuzhou, Jiangsu 221002, P.R. China</aff>
<author-notes>
<corresp id="c1-etm-0-0-3137"><italic>Correspondence to</italic>: Dr Ying Xue, Department of Endocrinology, Xuzhou Children&#x0027;s Hospital, 18 Sudibei Road, Xuzhou, Jiangsu 221002, P.R. China, E-mail: <email>xueying96@yeah.net</email></corresp>
</author-notes>
<pub-date pub-type="ppub">
<month>05</month>
<year>2016</year></pub-date>
<pub-date pub-type="epub">
<day>09</day>
<month>03</month>
<year>2016</year></pub-date>
<volume>11</volume>
<issue>5</issue>
<fpage>1545</fpage>
<lpage>1549</lpage>
<history>
<date date-type="received"><day>01</day><month>12</month><year>2015</year></date>
<date date-type="accepted"><day>09</day><month>03</month><year>2016</year></date>
</history>
<permissions>
<copyright-statement>Copyright: &#x00A9; Xu et al.</copyright-statement>
<copyright-year>2016</copyright-year>
<license license-type="open-access">
<license-p>This is an open access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by-nc-nd/4.0/">Creative Commons Attribution-NonCommercial-NoDerivs License</ext-link>, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.</license-p></license>
</permissions>
<abstract>
<p>The abundance of protein and its functional diversity in living systems makes it essential for virtually all life processes. Dietary protein and amino acid requirements are affected by age, body size, body composition, physiological state, and the level of energy output. The requirement for dietary protein is based on the indispensable amino acids under all conditions and under specific physiological and pathological conditions as well as the synthesis of dispensable amino acids and other nitrogen-containing compounds. Previous findings have shown the influence of early intake of proteins on the development of overweight in healthy children. The present review focused on the possible association (if any) between protein intake and later development of obesity. The aim is to benefit physicians, dieticians as well as parents to understand future consequences of incorrect dietary habits in young adolescents and encourage healthy dietary habits to avoid obesity.</p>
</abstract>
<kwd-group>
<kwd>obesity</kwd>
<kwd>protein intake</kwd>
<kwd>infant</kwd>
<kwd>diet</kwd>
</kwd-group>
</article-meta>
</front>
<body>
<sec sec-type="intro">
<label>1.</label>
<title>Introduction</title>
<p>Protein intake during childhood has a paramount effect on growth and development (<xref rid="b1-etm-0-0-3137" ref-type="bibr">1</xref>). It is an essential macronutrient necessary for building and repairing tissues, defending the immune system, coordinating cell activity, serving as a catalyst, and providing energy. Factors including food availability and absorptive capacity affect the quantity and quality of a child&#x0027;s intake of protein. Animal sources of dietary protein include meat, eggs, cheese, fish, and dairy (<xref rid="b2-etm-0-0-3137" ref-type="bibr">2</xref>). Protein is also found in plant products such as nuts, seeds, grains, legumes, beans, and vegetables. In general, animal protein varies from plant protein in that it has higher saturated fat content and contains cholesterol. Plant protein is higher in fibre and carbohydrates (<xref rid="b3-etm-0-0-3137" ref-type="bibr">3</xref>). Vegetarian diets, which are typically high in plant proteins, are associated with health advantages such as lower blood cholesterol levels, lower risk of heart disease, lower body mass index (BMI), lower overall cancer rates, lower blood pressure levels, and lower risk of hypertension and type 2 diabetes (<xref rid="b4-etm-0-0-3137" ref-type="bibr">4</xref>).</p>
<p>Scoring systems have been developed to determine the quality of a dietary protein source by quantifying the amino acids profile (<xref rid="b5-etm-0-0-3137" ref-type="bibr">5</xref>). The protein digestibility-corrected amino acid score (PDCAAS) is a measurement of the protein quality in human nutrition (<xref rid="b6-etm-0-0-3137" ref-type="bibr">6</xref>). The higher the PDCAA score, the higher the amino acid profile and quality of protein. Animal proteins (i.e., egg) and purified plant proteins (i.e., soy) have higher scores than plant proteins (i.e., wheat) with intact cell walls. Previous studies focusing on overall protein intake during infancy and early childhood showed that a high protein intake (&#x003E;15&#x0025; of energy) during early childhood may increase the risk of obesity. Furthermore, high protein intake during certain periods of childhood (12 months, 18&#x2013;24 months, and 5&#x2013;6 years) results in an increased BMI in subsequent years and even into adulthood. A child with a high BMI-for-age percentile has an increased risk of being overweight or obese in adulthood (<xref rid="b7-etm-0-0-3137" ref-type="bibr">7</xref>&#x2013;<xref rid="b10-etm-0-0-3137" ref-type="bibr">10</xref>). The present review article primarily focused to impart knowledge pertaining to crucial relationships among protein intake and future aspects of incorrect dietary inputs based on quality, quantity and time of protein intake. The review covered important aspects essential for the proper diet of young adolescents in order to secure their future from the lethal effects of obesity.</p>
</sec>
<sec>
<label>2.</label>
<title>Protein load and obesity</title>
<p>The &#x2018;early protein hypothesis&#x2019;, initially identified by Rolland-Cachera, suggested that a high protein intake in early infancy increases the risk of obesity (<xref rid="b11-etm-0-0-3137" ref-type="bibr">11</xref>). Infancy and early childhood protein intakes are of interest because of differing macronutrient distribution found in infant formula versus human milk and the stimulating effect protein has on insulin-like growth factor-1 (IGF-1) and insulin secretion (<xref rid="b12-etm-0-0-3137" ref-type="bibr">12</xref>). Insulin and IGF-1 have anabolic effects that stimulate growth in children. Higher concentrations are found in infants fed formula compared to infants fed human milk. However, children breast-fed during infancy are taller and have higher IGF-1 concentrations later in life (<xref rid="b13-etm-0-0-3137" ref-type="bibr">13</xref>). A low IGF-1 concentration later in life is associated with increased risk of non-communicable diseases (NCDs) facilitated through IGF-1. There is a concern that high protein intakes during the first years of life may cause obesity later by altering IGF-1 concentrations.</p>
<p>It is thought that infants experience a rapid increase of protein intake when transitioning to solid foods, typically 3- to 4-fold greater than the physiological requirements of the average infant (<xref rid="b14-etm-0-0-3137" ref-type="bibr">14</xref>). The protein energy percentage is 7&#x2013;8&#x0025; in infant formula, 20&#x0025; in full fat cow&#x0027;s milk, ~5&#x0025; in breastfed infants, and 15&#x2013;20&#x0025; in the typical family diet. In turn, breast-fed infants are shorter, weigh less, and have a lower BMI than formula-fed infants. Furthermore, an inverse relationship between IGF-1 measured in infancy and in late adolescence has been identified. The type of protein consumed may have different effects on IGF-1. For example, it has been shown that early intake of cow&#x0027;s milk increases linear growth in well-nourished populations by stimulating circulating IGF-1 (<xref rid="b15-etm-0-0-3137" ref-type="bibr">15</xref>). The risk factor for NCDs later in life is associated more with a poor protein quality intake with no animal protein than with high intakes of total protein. A systematic literature review conducted by H&#x00F6;rnell <italic>et al</italic> (<xref rid="b10-etm-0-0-3137" ref-type="bibr">10</xref>) aimed to assess the health effects of different intakes and sources of protein (animal- or plant-based) in infancy and childhood in a Nordic setting (<xref rid="b10-etm-0-0-3137" ref-type="bibr">10</xref>) The above systematic review concluded that a high intake of protein in infancy and early childhood is associated with an increased risk of obesity later in life.</p>
<p>A review by Martorell <italic>et al</italic> (<xref rid="b16-etm-0-0-3137" ref-type="bibr">16</xref>) examined the relationship between overall nutrition in early life and the development of adiposity later in life. Three hypotheses were posited: i) overnutrition increases the risk of later obesity; ii) undernutrition is associated with increased risk of obesity; and iii) optimal nutrition during infancy, the gold standard being breastfeeding, is protective against future obesity. Possible mechanisms for these outcomes include disruptions in organ function, increase in the number and/or size of fat cells or alterations in adipose tissue function, and dysfunction of the central nervous system resulting in appetite regulation disturbances. The authors of that study (<xref rid="b16-etm-0-0-3137" ref-type="bibr">16</xref>) reviewed observational, experimental, and quasi-experimental studies. Birth weight and adult BMI were used to indicate the influence of fetal nutrition on adult obesity. The results from those studies are conflicting. Some studies (<xref rid="b17-etm-0-0-3137" ref-type="bibr">17</xref>,<xref rid="b18-etm-0-0-3137" ref-type="bibr">18</xref>) identified a J-shaped relationship between birth weight and adult BMI, while others only found an association between high birth weight and increased adult BMI. A majority of the studies (<xref rid="b19-etm-0-0-3137" ref-type="bibr">19</xref>,<xref rid="b20-etm-0-0-3137" ref-type="bibr">20</xref>) found that higher birth weights, particularly birth weights &#x003E;10 pounds, led to increased obesity in adulthood. In addition, intrauterine overnutrition is associated with a greater risk of obesity and may play a role in childhood obesity.</p>
<p>A longitudinal study conducted by Gunther <italic>et al</italic> (<xref rid="b21-etm-0-0-3137" ref-type="bibr">21</xref>) examined whether certain time points or periods of protein intake in infancy, early childhood, or the preschool years contribute to BMI at 7 years of age, and whether the association is attributed to distinct protein sources (animal, vegetable, dairy, meat, or cereal protein). The aim of that study was to investigate the validity of the early protein hypothesis, which suggested that high protein intake during infancy increases the risk of obesity later in life. The early protein hypothesis is based on the consideration that infant formula has significantly higher protein content than human milk and that children experience a rapid increase in protein intake when transitioning to solid foods. Previous studies (<xref rid="b22-etm-0-0-3137" ref-type="bibr">22</xref>,<xref rid="b23-etm-0-0-3137" ref-type="bibr">23</xref>) have failed to investigate whether distinct protein sources are associated with the early protein hypothesis. The study population was derived from the DONALD study (<xref rid="b24-etm-0-0-3137" ref-type="bibr">24</xref>), an ongoing cohort study that follows subjects through young adulthood. An average of 40&#x2013;50 infants from Dortmund, Germany were recruited on an annual basis and examined at the age of 3&#x2013;6 months. Up until early adulthood, investigators intermittently collected information from participants on nutrition, growth, metabolism, and health status. A similar prospective study by Scaglioni <italic>et al</italic> (<xref rid="b8-etm-0-0-3137" ref-type="bibr">8</xref>) examined the effects of the early intake of macronutrients on the development of overweight in healthy children.</p>
<p>Skinner <italic>et al</italic> (<xref rid="b25-etm-0-0-3137" ref-type="bibr">25</xref>) examined longitudinal growth and energy intake in children aged 2&#x2013;8 years and identified factors associated with the children&#x0027;s BMI. Weight, height, and BMI percentiles were determined based on the Center for Disease Control (CDC) growth charts. Dietary intakes from 3-day food records were averaged and analyzed using Nutritionist IV, version 3.5 (Axxya Systems LLC, Stafford, TX, USA). Each child was assessed 15&#x2013;17 times by the end of the study and additional behavior information was obtained at certain time points. Dietary fat and dietary protein had a positive relationship to BMI whereas a negative association was identified with dietary carbohydrate intake. The findings suggested that childhood obesity is multifactorial and impacted primarily by BMI. Thus, the quantity and quality of protein intake during childhood affects BMI and body fat percentage (BF&#x0025;) subsequently in life.</p>
</sec>
<sec>
<label>3.</label>
<title>BMI and obesity</title>
<p>Children with a higher BMI-for-age and children who subsequently became obese ages had a greater risk of adult obesity. Childhood obesity also increases the risk of developing morbidities in adulthood. In a review, Maffeis and Tat&#x00F2; (<xref rid="b26-etm-0-0-3137" ref-type="bibr">26</xref>) addressed the association between childhood and adult obesity and the effects of childhood obesity on morbidity and mortality. Rates of diabetes, coronary heart disease, atherosclerosis, hip fracture, and gout were increased in individuals who were overweight as adolescents. Moreover, cardiovascular risk factors such as total blood cholesterol, blood low-density lipoprotein- and high-density lipoprotein-cholesterol, and blood pressure levels and being overweight continued from childhood into adulthood. High BMI-for-age values can be a useful tool in identifying children and adolescents at increased risk of becoming overweight or obese in adulthood. Furthermore, dietary factors such as protein sources affect childhood obesity and should be examined as potential contributors in the development of morbidities in adulthood. Identifying dietary intake markers for increased BMI in children may assist with the development of dietary recommendations that may decrease the risk of developing obesity as an adult. For example, if a high intake of animal protein compared to plant protein predisposes children to obesity, dietary recommendations for increasing plant protein intake and decreasing animal protein intake may be developed. In the case that high intakes of animal protein is associated with a high BMI in children, parents can intervene during early childhood by providing adequate amounts of animal and plant protein for proper growth and weight maintenance. To ensure that healthy children are raised into healthy adults, it is important for the public to be aware of contributing factors to obesity.</p>
</sec>
<sec>
<label>4.</label>
<title>Multi-factorial aspects of obesity</title>
<p>Previous findings have shown that the association between dietary inputs and resultant obese conditions in children are multi-dimensional or multi-factorial in nature. Possible mechanisms for the future outcomes of incorrect dietary habits include disruptions in organ function, increase in the number and/or size of fat cells or alterations in adipose tissue function, and dysfunction of the central nervous system resulting in appetite regulation disturbances. A majority of the studies found that higher birthweights, particularly birthweights &#x003E;10 pounds, led to increased overweight and obesity in adulthood (<xref rid="b21-etm-0-0-3137" ref-type="bibr">21</xref>). A proportion of the causes of high birthweight may be attributed to early exposure to famine or gestational diabetes. The fetuses of mothers with diabetes are exposed to high concentrations of blood glucose, which leads to hyperinsulinemia and increased growth of fat, lean body, glycogen stores, and overall birth weight.</p>
<p>On the other hand, increased risk of overweight and obesity from undernutrition is not well understood and contradictory. However, it has been suggested that individuals whose nutrient intake is scarce early in life move to abundance or excess in adulthood. In addition, intrauterine overnutrition is associated with a greater risk of overweight and obesity and may play a role in childhood obesity. A longitudinal study conducted by G&#x00FC;nther <italic>et al</italic> (<xref rid="b21-etm-0-0-3137" ref-type="bibr">21</xref>) evaluated whether certain time points or periods of protein intake in infancy, early childhood, or the preschool years contribute to BMI at 7 years of age, and whether the association is attributed to distinct protein sources (animal, vegetable, dairy, meat, or cereal protein). A previous study (<xref rid="b8-etm-0-0-3137" ref-type="bibr">8</xref>) confirmed an additional time period (5&#x2013;6 years of age) as a sensitivity period of total and animal protein intakes for later body obesity. Thus, the quantity and quality of protein intake during childhood affects BMI and BF&#x0025; in subsequent years. Future studies are needed to compare protein intake later in childhood and BMI as predictors for adult obesity.</p>
</sec>
<sec>
<label>5.</label>
<title>Importance of dietary intake assessment in children and young adolescents</title>
<p>Assessing dietary intakes in children is a challenging aspect of nutrition research. Erroneous methodology often limits dietary intake data in outcome evaluations. However, this information is essential for advancing dietary recommendations for overweight and obese children (<xref rid="b27-etm-0-0-3137" ref-type="bibr">27</xref>). Selection of the appropriate measuring tool or method for dietary intake in children proposes a challenge in itself, whether it is a total diet assessment, a targeted diet, or related behaviours assessment. Each method depends on the dietary features of interest and the characteristics of the study population. The weight status of subjects and study design are important factors when selecting an appropriate methodology for dietary assessment (<xref rid="b13-etm-0-0-3137" ref-type="bibr">13</xref>,<xref rid="b21-etm-0-0-3137" ref-type="bibr">21</xref>).</p>
<p>Dietary studies on children and adolescents have identified a positive association between under-reporting and increased body fatness. Collectively, reports from large-scale surveys have shown a decrease in energy intake over time despite weight gain worldwide, suggesting energy expenditure has decreased and/or measurements of dietary intake are flawed (<xref rid="b28-etm-0-0-3137" ref-type="bibr">28</xref>). One cross sectional study examined the extent of under-reporting of energy intake in children between the ages of 4&#x2013;18 years (<xref rid="b29-etm-0-0-3137" ref-type="bibr">29</xref>) The results of that study showed that the target group is also a critical element when selecting a dietary intake method.</p>
<p>Different age groups have varying literacy and numeracy skills, memory capabilities, attention spans, and cognitive abilities. For example, children &#x003C;8 years of age have limited competency in providing an accurate dietary recall and children &#x003C;10 years of age lack the conceptual skills required for reporting usual intake, serving sizes, and frequency of behaviors. Thus, assessing dietary intake in children &#x003C;10 years requires parental involvement. The dietary habits and level of structured eating environment should also be considered for different age groups, as older children tend to consume more meals away from home and follow a less stringent eating schedule. Total dietary methods such as food records, 24-hour recall, food frequency questionnaire, and targeted diet and/or behaviours methods have advantages and disadvantages (<xref rid="tI-etm-0-0-3137" ref-type="table">Table I</xref>).</p>
</sec>
<sec>
<label>6.</label>
<title>Body composition assessment in children and young adolescents</title>
<p>BMI is commonly used in clinical practice to represent adiposity status (normal, overweight, and obese) (<xref rid="b30-etm-0-0-3137" ref-type="bibr">30</xref>). BMI, formulated from weight and height, is an inexpensive and convenient indicator of body fat mass for most children and shows the relative position of the child&#x0027;s BMI among children of the same gender and age. BMI in children is often reported as a percentile ranking and subsequent weight status category. BMI is plotted on the CDC BMI-for-age gender-specific growth charts and is used to assess the size and growth patterns of children aged &#x2265;2 years in the United States (<xref rid="b31-etm-0-0-3137" ref-type="bibr">31</xref>).</p>
<p>The relationship between BMI and adiposity was demonstrated in a study on Italian children with a wide range in age (<xref rid="b32-etm-0-0-3137" ref-type="bibr">32</xref>). Although a strong positive relationship was found between BMI and total body fat, BMI compared across different age groups can be erroneous and results must be evaluated cautiously. Total body fat was shown to increase with age while the percentage of body fat decreased with age. The association between childhood BMI and adult adiposity has been supported in some studies but refuted in other studies (<xref rid="b33-etm-0-0-3137" ref-type="bibr">33</xref>). A large longitudinal study aimed to compare the accuracy of childhood levels of BMI and triceps skin-fold thickness in predicting adult adiposity. The study found that childhood BMI-for-age was significantly associated with adult levels of BMI. This correlation was stronger among girlsand among older children (9&#x2013;17 years). Adult obesity and excessive body fat mass consistently increased as childhood BMI-for-age increased, even among young children.</p>
</sec>
<sec sec-type="conclusions">
<label>7.</label>
<title>Conclusions</title>
<p>In conclusion, it is clear from the above citations that proper knowledge of dietary options is necessary to secure the future of young adolescents from the consequences of obesity.</p>
</sec>
</body>
<back>
<ref-list>
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<floats-group>
<table-wrap id="tI-etm-0-0-3137" position="float">
<label>Table I.</label>
<caption><p>Advantages and disadvantages of dietary assessment methods.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="bottom">Dietary assessment</th>
<th align="center" valign="bottom">Method</th>
<th align="center" valign="bottom">Advantages and disadvantages</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top">Food record</td>
<td align="left" valign="top">Frees participants from relying on memory</td>
<td align="left" valign="top">Sets a burden on participants</td>
</tr>
<tr>
<td/>
<td align="left" valign="top">Includes a specific time period</td>
<td align="left" valign="top">Proposes a challenge for participants to record foods not consumed within the home</td>
</tr>
<tr>
<td/>
<td align="left" valign="top">Allows investigators to be trained in groups</td>
<td align="left" valign="top">Alters dietary habits of participants in some cases</td>
</tr>
<tr>
<td/>
<td align="left" valign="top">Offers absolute and relative intakes</td>
<td align="left" valign="top">Requires participants to have literacy and numeracy skills</td>
</tr>
<tr>
<td/>
<td/>
<td align="left" valign="top">Proposes a high cost</td>
</tr>
<tr>
<td/>
<td/>
<td align="left" valign="top">Challenges feasibility for large studies</td>
</tr>
<tr>
<td/>
<td/>
<td align="left" valign="top">Proposes a burden on participants due to necessary multiple records</td>
</tr>
<tr>
<td align="left" valign="top">24-h recall</td>
<td align="left" valign="top">Frees participants from requiring literacy or numeracy skills</td>
<td align="left" valign="top">Requires participants to rely on memory for recall</td>
</tr>
<tr>
<td/>
<td align="left" valign="top">Allows dietary habits of participants to be left unaltered</td>
<td align="left" valign="top">Proposes a challenge for estimating food quantity</td>
</tr>
<tr>
<td/>
<td align="left" valign="top">Provides a low burden for participants</td>
<td align="left" valign="top">Requires training of investigators</td>
</tr>
<tr>
<td/>
<td align="left" valign="top">Provides a quick assessment</td>
<td align="left" valign="top">Proposes a high cost</td>
</tr>
<tr>
<td/>
<td align="left" valign="top">Includes a specific time period</td>
<td align="left" valign="top">Challenges feasibility for large studies</td>
</tr>
<tr>
<td/>
<td align="left" valign="top">Offers automated data entry</td>
<td align="left" valign="top">Proposes a burden on participants due to necessary multiple records</td>
</tr>
<tr>
<td align="left" valign="top">Food frequency questionnaire (FFQ)</td>
<td align="left" valign="top">Allows dietary habits of participants to be left unaltered</td>
<td align="left" valign="top">Requires participants to rely on memory for recall</td>
</tr>
<tr>
<td/>
<td align="left" valign="top">Offers a low burden for participants</td>
<td align="left" valign="top">Requires participants to have literacy and numeracy skills</td>
</tr>
<tr>
<td/>
<td align="left" valign="top">Frees the training of investigators</td>
<td align="left" valign="top">Proposes a challenge for estimating food quantity</td>
</tr>
<tr>
<td/>
<td align="left" valign="top">Allows administration in multiple formats</td>
<td align="left" valign="top">Bypasses food descriptions</td>
</tr>
<tr>
<td/>
<td align="left" valign="top">Offers a quick and inexpensive assessment</td>
<td align="left" valign="top">Bypasses assessment of meal patterns</td>
</tr>
<tr>
<td/>
<td align="left" valign="top">Allows automated data entry</td>
<td align="left" valign="top">Limits data when FFQ is nutrient specific</td>
</tr>
<tr>
<td/>
<td align="left" valign="top">Allows practicality for large studies</td>
<td/>
</tr>
<tr>
<td/>
<td align="left" valign="top">Offers assessment of total diet and select nutrients</td>
</tr>
<tr>
<td/>
<td align="left" valign="top">Offers assessment of current or past diet</td>
</tr>
<tr>
<td/>
<td align="left" valign="top">Allows participants to be divided into groups based on intake</td>
</tr>
<tr>
<td align="left" valign="top">Targeted diet and/or behavior assessments</td>
<td align="left" valign="top">Allows dietary habits of participants to be left unaltered</td>
<td align="left" valign="top">Requires participants to rely on memory for recall</td>
</tr>
<tr>
<td/>
<td align="left" valign="top">Provides a low burden for participants</td>
<td align="left" valign="top">Requires participants to have literacy and numeracy skills</td>
</tr>
<tr>
<td/>
<td align="left" valign="top">Allows practicality for large studies</td>
<td align="left" valign="top">Requires research before developing assessment</td>
</tr>
<tr>
<td/>
<td align="left" valign="top">Offers a simple and inexpensive assessment</td>
<td align="left" valign="top">Challenges validity</td>
</tr>
<tr>
<td/>
<td align="left" valign="top">Allows automated data entry</td>
<td align="left" valign="top">Bypasses the collection of of nutrient intakes</td>
</tr>
<tr>
<td/>
<td align="left" valign="top">Allows trends to be monitored</td>
<td align="left" valign="top">Limits food intake information</td>
</tr>
<tr>
<td/>
<td align="left" valign="top">Allows behaviors and environmental</td>
</tr>
<tr>
<td/>
<td align="left" valign="top">information to be assessed</td>
<td/>
</tr>
</tbody>
</table>
</table-wrap>
</floats-group>
</article>
