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Pediatric Obesity Algorithm 1 obesitymedicine orgPediatric Obesity Algorithm 2018 2020 Obesity Medicine Association Pediatric Obesity AlgorithmDisclaimer.
The Pediatric Obesity Algorithm was developed to assist health care professionals in medical decision making in themanagement and care of patients with overweight and obesity The Pediatric Obesity Algorithm is not intended to be asubstitute for a medical professional s independent judgment and should not be considered medical advice The contentherein is based on the medical literature and the clinical experience of obesity medicine specialists In areas regardinginconclusive or insufficient scientific evidence the authors used their professional judgment .
The Pediatric Obesity Algorithm is a working document that represents the state of obesity medicine at the time ofpublication OMA encourages medical professionals to use this information in conjunction with and not as a replacement for their best clinical judgment The presented recommendations may not be appropriate in all situations Any decision bypractitioners to apply these guidelines must be made in light of local resources and individual patient circumstances Permissions.
The Obesity Medicine Association owns the copyright to the Obesity Algorithm but invites you to use the slide set Access tothe Obesity Algorithm content and or permission for extensive quoting or reproducing excerpts and for the reproduction anduse of copyrighted text images or entire slides will not be granted until the requestor has signed the copyright consent andpermission agreement available at www ObesityAlgorithm org OMA reserves the right to deny a request for permission touse the Obesity Algorithm .
Pediatric Obesity Algorithm 2018 2020 Obesity Medicine Association Authors and CitationChair Suzanne E Cuda MD FAAP FOMACo authors Administrative Assistance Marisa Censani MD Lauren Rieck.
Madeline Joseph MD FAAP FACEPNancy T Browne MS PPCNP BC CBN FAANPValerie O Hara DO FAAPCitation Cuda S Censani M Joseph M Browne N O Hara V Pediatric Obesity Algorithm presented by the Obesity Medicine Association www obesitymedicine org childh... .
2018 2020 www obesitymedicine org childh... Accessed Insert date Pediatric Obesity Algorithm 2018 2020 Obesity Medicine Association To provide health care professionals an algorithm to guidethe treatment of children and adolescents with increasedbody fat based upon scientific evidence supported by the.
medical literature and derived from the clinicalexperiences of members of the Obesity MedicineAssociation Pediatric Obesity Algorithm 2018 2020 Obesity Medicine Association The Pediatric Obesity Algorithm was derived from input by.
volunteer OMA members consisting of Academicians Clinicians ResearchersThe Pediatric Obesity Algorithm did not receive industry funding .
had no input from industry and the authors received no paymentfor their contributions Pediatric Obesity Algorithm 2018 2020 Obesity Medicine Association Intent of UseThe Pediatric Obesity Algorithm 2018 2019 is intended to be a living document .
updated as needed It is intended as an educational tool to assist in thetranslation of medical science and the clinical experience of the authors towardsassisting health care professionals improve management of their pediatricpatients with overweight and obesity This algorithm is not intended to be interpreted as rules and or directives.
regarding medical care of an individual patient While it is hoped many clinicians may find this algorithm helpful the final decisionregarding the optimal care of the patient with overweight or obesity is dependentupon the individual clinical presentation and the judgment of the clinician who istasked with directing a treatment plan that is in the best interest of the patient .
Pediatric Obesity Algorithm 2018 2020 Obesity Medicine Association Table of ContentsOverall Management Goals 8 Co Morbidities 61Epigenetics 9 Behavioral Health Problems Associated with Obesity 78Assessment 17 Eating Disorders 84.
Obesity as a Disease 27 Miscellaneous Topics 89Differential Diagnosis 29 Social Consequences 97Review of Symptoms 31 Pharmacology 103Diagnostic Work Up 33 Medication Related Weight Gain 107Physical Examination 37 Appendices 116.
Nutritional Recommendations 41 Appendix A Staged Treatment Approach 117Food Insecurity 45 Appendix B Resources Tools 121Management 47 References 126Activity Recommendations 58 Disclosures 154Pediatric Obesity Algorithm 2018 2020 Obesity Medicine Association .
Overall Management GoalsPediatric patient with overweight or obesityDevelop healthy habits Improve health Improve bodyand lifestyle patterns quality.
compositionthrough adulthood of lifePrevent future adverse Improve body imagehealth consequences and self esteemPediatric Obesity Algorithm 2018 2020 Obesity Medicine Association .
Epigenetics Heritable regulation of gene expressionwithout a change in the base sequence of DNA9 obesitymedicine orgPediatric Obesity Algorithm 2018 2020 Obesity Medicine Association .
Common Manifestations of Epigenetics in Childhood ObesitySmall for Large for Very Low BirthGestational Age Weight InfantsInfants Intrauterine Gestational PrematureGrowth Restriction .
Age Infants infants Undergo significant periods of undernutritionfollowing birth Mothers with Tobacco abuse during Commonly leave the NICU at a smaller size.
preconception BMIs 30 than counterparts who remained in uteropregnancy Undergo a period of catch up growth when Use of folic acid may kg m2 they are provided with high nutrient formula Mothers with excessive or fortified human milkattenuate the effect Have higher levels of visceral fat suggesting.
gestational weight gain a set up for higher incidence of CV disease Insufficient gestational Gestational diabetes and T2DMweight gain Often receive prolonged courses ofmellitus antibiotics Highly stressed.
Pediatric Obesity Algorithm 2018 2020 Obesity Medicine Association Reference s 1 The Maternal Resource Hypothesis Each generation produces larger and moremetabolically compromised mothersIntense postprandial insulin responseAdipocyte hyperplasia establishes a and the relative number of adipocytes is.
competitive dominance over other so large that the competitive dominancetissues of adipocytes is inevitable and obesityunavoidablePediatric Obesity Algorithm 2018 2020 Obesity Medicine Association Reference s 2 Factors Associated with Epigenetic Changes that Increase Risk of Childhood Obesity.
Maternal NeonatalInsulin IntestinalResistance delivery Microbiome Maternal insulin resistance IR not Iatrogenic Artificial Selection Before delivery through first 2 years of life.
Larger infants secondary to excessive fetal growthprepregnancy BMI with or without glucose Colonization of the neonatal biome may be due toleads to larger infant head circumferences leading tointolerance predicts weight gain and adiposity transvaginal migration of organisms or trans locationincreased number of C section deliveries.
in infant from 0 12 months Increased numbers of C sections has facilitated the from the maternal GI tract Obesity in pregnancy associated with higher levels of Genes for lipid amino acids and inflammatory survival of larger infants and the mothers who producedBacteroides Clostridium and Staphylococcuspathways unregulated with maternal IR them.
C section delivery is strongly associated with childhood associated with increased energy harvest from diet Maternal IR causes specific defects in maternal and lower levels of bifidobacterium than normal weightskeletal muscle that can persist for 12 months The frequency of C section births is greatest in the Intestinal colonization of infants delivered by C sectionafter birth increasing risk for T2DM in mother closely related to maternal skin microbes vs vaginally.
population that is the most inactive sedentary andand higher risk in future pregnancies delivered infants which resemble vaginal microbesPediatric Obesity Algorithm 2018 2020 Obesity Medicine Association Reference s 3 4 Factors Associated with Epigenetic Changes that Increase Risk of Childhood ObesityExposure to Environmental Toxins Postnatal Exposures First 1000 days .
Microbes associated with low dose penicillin Bottle fedexposure can induce obese phenotype Early introduction of complementary foods Nutrients i e Folate methionine choline Maternal and paternal diets high in CHOs betaine vitamin B12 can change DNA low in fruits and vegetablesmethylation status Coercive feeding or reward feeding.
Bioactive food components curcumin Poor parental role modelsgenistein retinoic acid can cause micro Inappropriate amount of sleep and physicalRNAs to down regulate target RNA activityPediatric Obesity Algorithm 2018 2020 Obesity Medicine Association Reference s 5 Antibiotic Administration and the Development of Obesity in Children.
Epidemiol MicrobiotaChildhood Exposure to Antibioticsogical ModificatioEvidence n 33 of pregnancies Antibiotic mediated promotion of Germ free animals no microbiota require 30 .
45 of neonates exposed in prenatal period growth in animals widely practiced more calories to maintain their body mass Mothers with overweight more likely to Gut microbiota allow host to digest otherwise Effect on children greater if prescribedreceive antibiotics indigestible complex plant polysaccharides to Antibiotic treatment highest with C section.
before 6 months of age boys girls monosaccharides and short chain fatty acids 88 of premature and low birth weight higher cumulative orders associated Animals in overweight category have a 50 with progressive weight gain reduction in Bacteroides and a proportional By age 2 3 antibiotic courses Antibiotic use increases height by 0 04 increase in Firmicutes.
By age 10 10 courses Antibiotics change the milieu disrupt immune By age 20 17 courses cm per month and weight by 23 8 defenses at the intestinal border resulting in Also exposed through the food chain g month compared to placebo increased inflammatory and metabolic disordersPediatric Obesity Algorithm 2018 2020 Obesity Medicine Association Reference s 6 7 The Association of Antibiotics and the Development of Obesity.
Effects on Effect on CircumstaMitochond the ntialria Microbiome Evidence Antibiotics both decrease the number Early exposure is associated with Strong association in meta of mitochondria and impair their resistance developing in probiotic analyses for the association.
function microorganisms between antibiotic exposure in Mitochondria are important in Intestinal microbiota exposed toearly life and childhoodmaintaining energy metabolism antibiotics show reduced diversity Evidence suggests that antibiotics Data from animal studies shows adiposity.
cause mutations in the mitochondrial antibiotic induced changes in gut Strong dose responsegenome microbiota can result in fat relationship between antibiotic Mitochondrial genome shares accumulation by changing host exposure and childhoodcommon pathways with bacteria metabolism adiposity.
Pediatric Obesity Algorithm 2018 2020 Obesity Medicine Association Reference s 8 9 Gestational Diabetes Mellitus GDM Incidence and Impact of Breast Feeding Complementary Feeding PhysicalAssociations Activity 18 of pregnancies GDM infants fed milk from Associated with an increase in Physical activity.
Glycemic status of the biological mothers during 1st week protein intake from 5 breast levels are similarmother usually returns to of life had higher body weight at 2 milk to 25 of diet among non GDMIntent of Use. The Pediatric Obesity Algorithm 2018/2019 is intended to be a “living document” updated as needed. It is intended as an educational tool to assist in the translation of medical science and the clinical experience of the authors towards assisting health care professionals improve management of their pediatric patients with overweight and obesity.

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