Severe obesity is a limitation for the use of body mass index standard deviation scores in children and adolescents

The relationship between obesity and oral-health status in North African adults: A comparative study

INTRODUCTION

The strength of the association between obesity and oral health is still indecisive.

OBJECTIVE

The objectives of the study were to compare some oral-health data between two groups involving obese (OG) and normal weight (NWG) participants and determine the influencing factors of the periodontal probing depth (PPD).

METHODS

This was a cross-sectional study including 67 Tunisian adults [OG (n = 33, body mass index (BMI) > 30 kg/m2 ), NWG (n = 34, BMI: 18.5-25.0 kg/m2 )]. The plaque level was recorded using the plaque index (PI). Gingival index (GI) was used to evaluate gingival inflammation. The depths of the sulci/pockets were probed using a periodontal probe. Stimulated saliva was collected for 5 min, and salivary flow rate (SFR) was determined. Salivary baseline pH (SBpH) was measured. A multivariable regression analysis was performed between PPD and some independent variables [i.e. obesity status, age, sex, socioeconomic status, systemic diseases and PI data].

RESULTS

The OG and NWG were age- and sex-matched and included comparable percentages of participants with systemic diseases (27.3 vs. 29.4%, respectively). The OG included a higher percentage of participants having a low socioeconomic status (87.9 vs. 64.7%, respectively). Compared with the NWG, the OG: (i) had comparable values of daily toothbrushing frequency, PI, GI and tooth mobility, (ii) included comparable percentages of irregular brushers, of participants with periodontitis, PI classes [0-1]and [1-2]; and GI classes [0-1], [1-2] and [2, 3]; (iii) had a higher PPD (2.02 ± 0.41 vs. 2.35 ± 0.22 mm, respectively), (iv) had lower SBpH (7.59 ± 0.21 vs. 7.45 ± 0.22, respectively) and SFR (1.98 ± 0.28 vs. 1.60 ± 0.32 mL/mn, respectively) and (v) included a higher percentage of participants having a PI class [2, 3] (67.6 vs. 87.9%, respectively). The multivariable regression analysis revealed that only obesity status, age and PI classes influenced the PPD, altogether explained 29.62% of the PPD variance.

CONCLUSION

Obesity poses a risk for oral health, and obese adults had altered PPD and lower BSpH and SFR. Dentists should make obese patients aware of the health risks of obesity in an attempt to reduce the potential oral complications associated with this epidemic.

A long-term follow-up of treatment for young children with obesity: a randomized controlled trial

BACKGROUND

Early childhood obesity interventions supporting parents have the largest effects on child weight status. However, long-term follow-ups are lacking.

OBJECTIVE

To examine weight status 48 months after obesity treatment initiation for 4- to 6-year-olds.

METHODS

177 families were recruited to the More and Less study, a 12-month randomized controlled trial (RCT) conducted in Sweden (2012-2017); 6 children were excluded due to medical diagnoses. Thus, 171 families (non-Swedish origin 59%, university degree 40%) were eligible for this 48-month follow-up with modified intention-to-treat (n = 114 had 48-month data, n = 34 dropped out, n = 23 lost to follow-up). The RCT compared 3 treatment approaches: a 10-week parent support program (1.5 h/w) with follow-up booster sessions (PGB) or without (PGNB), and standard outpatient treatment (ST). Treatment effects on primary outcome (BMI-SDS) and secondary outcomes (BMI, %IOTF25 i.e., the distance, in percent, above the cut-off for overweight) were assessed. Clinically significant reduction of BMI-SDS (≥0.5) was assessed with risk ratio. Sociodemographic factors and attendance were examined by three-way interactions.

RESULTS

After 48 months (mean 50 months, range 38-67 months) mean (95% CI) BMI-SDS was reduced in all groups: PGB -0.45 (-0.18 to -0.73, p < 0.001), PGNB -0.34 (-0.13 to -0.55, p < 0.001), ST -0.25 (-0.10 to -0.40, p < 0.001), no significant difference between groups. A clinically significant reduction of BMI-SDS ≥ 0.5 was obtained in 53.7% of PGB which was twice as likely compared to ST, 33.0%, RR 2.03 (1.27 to 3.27, p = 0.003), with no difference to PGNB, 46.6% (p = 0.113). %IOTF25 was unchanged from baseline for PGB 4.50 (-1.64 to 10.63), and significantly lower compared to ST 11.92 (8.40 to 15.44) (p = 0.043). Sociodemographics or attendance had no effect.

CONCLUSION

The intensive parent-support early childhood obesity intervention led to better weight status outcomes over time, though BMI-SDS alone did not reflect this. Further research should investigate how to assess weight changes in growing children.

CLINICAL TRIAL REGISTRATION

Clinicaltrials.gov, NCT01792531 .

Family-based treatment of children with severe obesity in a public healthcare setting: Results from a randomized controlled trial

To compare the effectiveness of family-based behavioural social facilitation treatment (FBSFT) versus treatment as usual (TAU) in children with severe obesity. Parallel-design, nonblinded, randomized controlled trial conducted at a Norwegian obesity outpatient clinic. Children aged 6-18 years referred to the clinic between 2014 and 2018 were invited to participate. Participants were randomly allocated using sequentially numbered, opaqued, sealed envelopes. FBSFT (n = 59) entailed 17 sessions of structured cognitive behavioural treatment, TAU (n = 55) entailed standard lifestyle counselling sessions every third month for 1 year. Primary outcomes included changes in body mass index standard deviation score (BMI SDS) and percentage above the International Obesity Task Force cut-off for overweight (%IOTF-25). Secondary outcomes included changes in sleep, physical activity, and eating behaviour. From pre- to posttreatment there was a statistically significant difference in change in both BMI SDS (0.19 units, 95% confidence interval [CI]: 0.10-0.28, p < .001) and %IOTF-25 (5.48%, 95%CI: 2.74-8.22, p < .001) between FBSFT and TAU groups. FBSFT participants achieved significant reductions in mean BMI SDS (0.16 units, (95%CI: -0.22 to -0.10, p < .001) and %IOTF-25 (6.53%, 95% CI: -8.45 to -4.60, p < .001), whereas in TAU nonsignificant changes were observed in BMI SDS (0.03 units, 95% CI: -0.03 to 0.09, p = .30) and %IOTF-25 (-1.04%, 95% CI: -2.99 to -0.90, p = .29). More FBSFT participants (31.5%) had clinically meaningful BMI SDS reductions of ≥0.25 from pre- to posttreatment than in TAU (13.0%, p = .021). Regarding secondary outcomes, only changes in sleep timing differed significantly between groups. FBSFT improved weight-related outcomes compared to TAU.

Packaging and Scaling the Stanford Pediatric Weight Control Program: A Family-Based, Group, Behavioral Weight Management Program for Children with Obesity and Their Families: Background, Rationale, and Design of the Stanford CORD 3.0 Project

Efficacious treatments for children with obesity have not been broadly disseminated. The Stanford Pediatric Weight Control Program (SPWCP) is grounded in behavioral theory and prior observations, follows a proven treatment model, and is consistent with the US Preventive Services Task Force (USPSTF) recommendations. It has shown high levels of participation and retention and reductions in BMI and percent of median BMI for age and sex comparable to many studied programs, as well as improvements in physiological risk factors, psychological measures, and diet, activity, and screen time behaviors in children with obesity when delivered as a real-world clinical program with sociodemographically diverse families in multiple clinic and community settings. The Stanford CORD 3.0 Project proposes to use technology, design, behavioral theory, and biomedical business innovation strategies to package and scale the SPWCP to reach low-income children throughout the United States. Efficacy and success of implementation of the new packaged program will be tested in a one-arm pilot implementation study when delivered by community partners.

'Now she prefers jeans, like everyone else…' - Parents' experiences of group- and web-based treatment of children's obesity

AIM

Web-based interventions have shown promising results in paediatric obesity treatment with the potential to increase coverage of care. This study aimed to explore parental experiences about participating in an intervention to improve healthy behaviours and lower BMI-SDS in children with obesity.

METHODS

This was an interview study with an inductive qualitative approach. Data were collected from individual interviews with 14 parents of 5- to 13-year-old children with obesity. The respondents had participated in a family-based treatment intervention consisting of four group sessions followed by 12-week web-based support. The interviews were analysed using qualitative manifest and latent content.

RESULTS

The overarching theme 'A transformative journey of lifestyle changes for the whole family' described how the participation impacted the lifestyle of the whole family. Four categories: parental awareness, introducing new routines, negotiating family battles and a feeling of support, represented various experiences made by respondents. The parents shared predominantly positive experiences of the intervention but also expressed feelings of guilt and struggled to address their child's obesity.

CONCLUSION

Parents who participated in a study for children with obesity with a web-based component found the programme helpful for achieving healthier lifestyles for the whole family.

Anthropometric Outcomes of Children and Adolescents Using Telehealth with Weight Management Interventions Compared to Usual Care: A Systematic Review and Meta-analysis

Objective:This systematic review and meta-analysis evaluated the effect of telehealth (TH) weight management interventions compared to usual care on anthropometric outcomes in children and adolescents with overweight and obesity.Methods: Comprehensive searches were conducted identifying randomized controlled trials (RCTs) published between January 1, 2005 and June 1, 2019. Studies using a web-based, smartphone or email TH intervention in children between 2-18 years of age were included. Outcome measures of interest included body mass index (BMI) z-score, BMI percentile, waist circumference (WC) and waist-to-hip-ratio (WHR). The Grade Recommendations, Assessment, Development and Evaluation (GRADE) approach was used to rate strength of evidence (SOE) and a random-effects meta-analysis was performed when five or more RCTs reported the same outcome.Results: Thirteen RCTs met the inclusion criteria for the systematic review. Random effects meta-analysis of 10 RCTs detected a small effect for TH interventions compared to usual care in reducing BMI z-score (pooled net change in BMI z-score = -0.04; 95% CI -0.07, 0.00: I2 = 12%). No significant differences were found between groups for other outcomes. Strength of evidence ratings were low or very low in part due to concerns with heterogeneity in study designs, intervention durations, ages of participants, the type of TH used and risk of bias (ROB) of included studies.Conclusions: There is a low strength of evidence that TH had a small effect on anthropometric outcomes compared to usual care. Future RCTs should be well designed to minimize clinical heterogeneity and ROB. Studies of longer intervention duration with adequate, statistically powered analyses should be conducted. Key teaching pointsStudies using TH with pediatric weight management interventions may be effective to improve health of children with overweight and obesity.Future RCTs should consider clinical heterogeneity of study design for setting, age-group of children, preferences for type of TH and ROB.Studies that include children with severe obesity (<95th%) may need more sensitive outcome measures.Studies of longer duration are needed to better understand long-term weight management success.

What Change in Body Mass Index Is Required to Improve Cardiovascular Outcomes in Childhood and Adolescent Obesity through Lifestyle Interventions: A Meta-Regression

Background: Using meta-regression, this article aims at establishing the minimum change in BMI-standard deviation score (SDS) needed to improve lipid profiles and blood pressure in children and adolescents with obesity, to aid future trials and guidelines. Methods: Studies with participants involved in lifestyle interventions, aged 4-19 years, with a diagnosis of obesity according to defined BMI thresholds, were considered for inclusion in a large systematic review. Interventions had to report pre- and post-intervention (or mean change in) BMI-SDS, plus either systolic blood pressure (SBP), high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, and/or triglycerides (TGs). Random-effects meta-regression quantified the relationship between mean change in BMI-SDS and mean change in cardiovascular outcomes. Results: Seventy-one papers reported various cardiovascular measurements and mean change in BMI-SDS. Fifty-four, 59, 46, and 54 studies were analyzed, reporting a change in SBP, HDL, LDL, and TG, respectively. Reduction in mean BMI-SDS was significantly related to improvements in SBP, LDL, TG, and HDL (p < 0.05); BMI-SDS reductions of 1, 1.2, and 0.7 ensured a mean reduction of SBP, LDL, and TG, respectively, although an equivalent value for HDL improvement was indeterminate. Conclusion: Reductions in mean BMI-SDS of >1, >1.2, or >0.7 are likely to reduce SBP, LDL, and TG, respectively. Further studies are needed to clarify the optimal duration, intensity, and setting for interventions. Consistency is required regarding derived BMI values to facilitate future systematic reviews and meta-analyses.

Distance and percentage distance from median BMI as alternatives to BMI z score

BMI z (BMIz) score based on the Centers for Disease Control and Prevention growth charts is widely used, but it is inaccurate above the 97th percentile. We explored the performance of alternative metrics based on the absolute distance or % distance of a child's BMI from the median BMI for sex and age. We used longitudinal data from 5628 children who were first examined <12 years to compare the tracking of three BMI metrics: distance from median, % distance from median and % distance from median on a log scale. We also explored the effects of adjusting these metrics for age differences in the distribution of BMI. The intraclass correlation coefficient (ICC) was used to compare tracking of the metrics. Metrics based on % distance (whether on the original or log scale) yielded higher ICCs compared with distance from median. The ICCs of the age-adjusted metrics were higher than that of the unadjusted metrics, particularly among children who were (1) overweight or had obesity, (2) younger and (3) followed for >3 years. The ICCs of the age-adjusted metrics were also higher compared with that of BMIz among children who were overweight or obese. Unlike BMIz, these alternative metrics do not have an upper limit and can be used for assessing BMI in all children, even those with very high BMIs. The age-adjusted % from median (on a log or linear scale) works well for all ages, while unadjusted % from median is better limited to older children or short follow-up periods.

A family-oriented intervention programme to curtail obesity from five years of age had no effect over no intervention

AIM

To examine the effect of a family-oriented multidisciplinary intervention programme to curtail weight increase in young children with obesity.

METHODS

Children who weighed more than one kilogram above the 97th percentile for height at the preschool assessment in Oppland County, Norway, were identified. Parents residing in one part of the county were invited to participate in a group-based three-year intervention programme while the rest had no interventions. Body mass index (BMI) and family characteristics at entry and measurements at birth were explanatory variables, and change in BMI standard deviation score (SDS) the outcome measure. For the intervention group, outcome was also related to skinfold thicknesses, waist-to-height ratio and physical ability.

RESULTS

The programme was completed by 31 families in the intervention and 33 in the control group. At entry, the respective median (interquartile) age was 5.83 (0.36) and 5.74 (0.66) years, and the BMI SDS 2.35 (1.06) and 1.95 (0.49), P = .012. The median decrease in BMI SDS was 0.19 in both groups. The decline increased with increasing BMI SDS at entry, but irrespective of group. Social or behavioural factor or other anthropometric measures were not associated with outcome.

CONCLUSION

The intervention programme had no effect on BMI SDS.

Distinct age-related patterns of overweight development to guide school healthcare interventions

AIM

We aimed to identify groups of primary school children with similar overweight development, reveal age-related patterns of overweight development in the resulting groups and analyse overweight-related school healthcare interventions.

METHODS

This retrospective longitudinal register study utilised electronic health records from six primary school years. From a random sample of 2000 sixth graders, we derived a study cohort of 508 children meeting criteria for overweight at least once during primary school. We investigated how many different groups (latent classes) of children with similar weight development would emerge by applying flexible latent class mixed models on body mass index standard deviation score. We also explored the resulting groups with respect to offered overweight-related interventions.

RESULTS

Per child, the data consisted in median 7 growth measurements over 5.4 years. We identified five overweight development groups for girls and four for boys. The groups converged temporarily around age 10 after which only some continued into obesity. School nurses and physicians offered overweight-related interventions to children with obesity, less to children gaining weight or with overweight.

CONCLUSION

Obesity prevention might benefit from awareness of typical overweight development patterns when designing intervention studies or planning and timing multidisciplinary school health check programmes.

Monitoring children and adolescents with severe obesity: body mass index (BMI), BMI z-score or percentage above the International Obesity Task Force overweight cut-off?

AIM

Body mass index (BMI) metrics are widely used as a proxy for adiposity in children with severe obesity. The BMI expressed as the percentage of a cut-off percentile for overweight or obesity has been proposed as a better alternative than BMI z-scores when monitoring children and adolescents with severe obesity.

METHODS

Annual changes in BMI, BMI z-score and the percentage above the International Obesity Task Force overweight cut-off (%IOTF-25) were compared with dual-energy X-ray absorptiometry (DXA) derived body fat (%BF-DXA) in 59 children and adolescents with severe obesity.

RESULTS

The change in %BF-DXA was correlated with the change in %IOTF-25 (r = 0.68) and BMI (r = 0.70), and somewhat less with the BMI z-score (r = 0.57). Cohen's Kappa statistic to detect an increase or decrease in %BF-DXA was fair for %IOTF-25 (κ = 0.25; p = 0.04) and BMI (κ = 0.33; p = 0.01), but not for the BMI z-score (κ = 0.08; p = 0.5). The change in BMI was positively biased due to a natural increase with age.

CONCLUSION

Changes in the BMI metrics included in the study are associated differently with changes in %BF-DXA. The BMI z-score is widely used to monitor changes in adiposity in children and adolescents with severe obesity, but the %IOTF-25 might be a better alternative.

What change in body mass index is associated with improvement in percentage body fat in childhood obesity? A meta-regression

OBJECTIVE

Using meta-regression this paper sets out the minimum change in body mass index-SD score (BMI-SDS) required to improve adiposity as percentage body fat for children and adolescents with obesity.

DESIGN

Meta-regression.

SETTING

Studies were identified as part of a large-scale systematic review of the following electronic databases: AMED, Embase, MEDLINE via OVID, Web of Science and CENTRAL via Cochrane library.

PARTICIPANTS

Individuals aged 4-19 years with a diagnosis of obesity according to defined BMI thresholds.

INTERVENTIONS

Studies of lifestyle treatment interventions that included dietary, physical activity and/or behavioural components with the objective of reducing obesity were included. Interventions of <2 weeks duration and those that involved surgical and/or pharmacological components (eg, bariatric surgery, drug therapy) were excluded.

PRIMARY AND SECONDARY OUTCOME MEASURES

To be included in the review, studies had to report baseline and post-intervention BMI-SDS or change measurements (primary outcome measures) plus one or more of the following markers of metabolic health (secondary outcome measures): adiposity measures other than BMI; blood pressure; glucose; inflammation; insulin sensitivity/resistance; lipid profile; liver function. This paper focuses on adiposity measures only. Further papers in this series will report on other outcome measures.

RESULTS

This paper explores the potential impact of BMI-SDS reduction in terms of change in percentage body fat. Thirty-nine studies reporting change in mean percentage body fat were analysed. Meta-regression demonstrated that reduction of at least 0.6 in mean BMI-SDS ensured a mean reduction of percentage body fat mass, in the sense that the associated 95% prediction interval for change in mean percentage body fat was wholly negative.

CONCLUSIONS

Interventions demonstrating reductions of 0.6 BMI-SDS might be termed successful in reducing adiposity, a key purpose of weight management interventions.

TRIAL REGISTRATION NUMBER

CRD42016025317.

Data-intensive Undergraduate Research Project Informs to Advance Healthcare Analytics

The overarching framework for incorporating informatics into the Wesley College (Wesley) undergraduate curriculum was to teach emerging information technologies that prepared undergraduates for complex high-demand work environments. Federal and State support helped implement Wesley's undergraduate Informatics Certificate and Minor programs. Both programs require project-based coursework in Applied Statistics, SAS Programming, and Geo-spatial Analysis (ArcGIS). In 2015, the State of Obesity listed the obesity ranges for all 50 US States to be between 21-36%. Yet, the Center for Disease Control and Prevention (CDC) mortality records show significantly lower obesity-related death-rates for states with very high obesity-rates. This study highlights the disparities in the reported obesity-related death-rates (specified by an ICD-10 E66 diagnosis code) and the obesity-rate percentages recorded for all 50 US States. Using CDC mortality-rate data, the available obesity-rate information, and ArcGIS, we created choropleth maps for all US States. Visual and statistical analysis shows considerable disparities in the obesity-related death-rate record-keeping amongst the 50 US States. For example, in 2015, Vermont with the sixth lowest obesity-rate had the highest reported obesity-related death-rate. In contrast, Alabama had the fifth highest adult obesity-rate in the nation, yet, it had a very low age-adjusted mortality-rate. Such disparities make comparative analysis difficult.

Relationship of BMI z score to fat percent and fat mass in multiethnic prepubertal children

OBJECTIVE

The objective of the study is to examine the validity of body mass index z score (zBMI) as a measure of percent body fat in prepubertal children.

METHODS

One hundred eleven multiethnic, healthy, Tanner 1 children aged 6-12 years had fat percent and fat mass measured by the four-compartment method as part of the Paediatric Rosetta Body Composition Cohort. Multiple regression models were developed with fat percent as the dependent variable and zBMI, age, sex and ethnicity as independent variables.

RESULTS

Body mass index z score predicted fat percent, adjusted for age in both girls (P < 0.001, RMSE 5.67 and R² 0.54) and boys (P < 0.001, RMSE 4.71, R² 0.69). The average model percent error was 20.3% in girls and 21.6% in boys. zBMI² predicted fat mass when adjusted for age and zBMI in both girls (P < 0.001, RMSE 2.27 and R² 0.82) and boys (P < 0.001, RMSE 2.08 and R² 0.81). The average percent error was 7.2% in girls and 8.7% in boys. Age was associated with percentage body fat (P < 0.01), while ethnicity was not (P > 0.05).

CONCLUSIONS

Given the relatively large error in the models, zBMI are not a useful indicator of fat mass in healthy, Tanner 1 children. zBMI² scores are associated with significantly lower absolute percent errors in girls and boys.