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. Author manuscript; available in PMC: 2021 May 3.
Published in final edited form as: Acad Pediatr. 2020 Dec 3;21(2):312–320. doi: 10.1016/j.acap.2020.11.026

Body Mass Index and Blood Pressure Improvements With a Pediatric Weight Management Intervention at Federally Qualified Health Centers

Omoye E Imoisili 1,*, Elizabeth A Lundeen 2,*, David S Freedman 3, Lindsay S Womack 4, Jessica Wallace 5, Simon J Hambidge 6, Steven Federico 7, Rachel Everhart 8, Delia Harr 9, Jillian Vance 10, Lyudmyla Kompaniyets 11, Carrie Dooyema 12, Sohyun Park 13, Heidi M Blanck 14, Alyson B Goodman 15
PMCID: PMC8091487  NIHMSID: NIHMS1693394  PMID: 33279738

Abstract

Objective:

The Mind, Exercise, Nutrition, Do It! 7–13 (MEND 7–13) program was adapted in 2016 by 5 Denver Health federally qualified health centers (DH FQHC) into MEND+, integrating clinician medical visits into the curriculum and tracking health measures within an electronic health record (EHR). We examined trajectories of body mass index (BMI, kg/m2) percentile, and systolic and diastolic blood pressures (SBP and DBP) among MEND+ attendees in an expanded age range of 4 to 17 years, and comparable nonattendees.

Methods:

Data from April 2015 to May 2018 were extracted from DH FQHC EHR for children eligible for MEND+ referral (BMI ≥85th percentile). The sample included 347 MEND+ attendees and 21,061 nonattendees. Mixed-effects models examined average rate of change for BMI percent of the 95th percentile (%BMIp95), SBP and DBP (mm Hg), after completion of the study period.

Results:

Most children were ages 7 to 13 years, half were male, and most were Hispanic. An average of 4.2 MEND+ clinical sessions were attended. Before MEND+, %BMIp95 increased by 0.247 units/month among MEND+ attendees. After attending, %BMIp95 decreased by 0.087 units/month (P < .001). Eligible nonattendees had an increase of 0.084/month in %BMIp95. Before MEND+ attendance, SBP and DBP increased by 0.041 and 0.022/month, respectively. After MEND+ attendance, SBP and DBP decreased by 0.254/month (P < .001) and 0.114/month (P < .01), respectively. SBP and DBP increased by 0.033 and 0.032/month in eligible nonattendees, respectively.

Conclusions:

%BMIp95, SBP, and DBP significantly decreased among MEND+ attendees when implemented in community-based clinical practice settings at DH FQHC.

Keywords: blood pressure, electronic health record, federally qualified health center, pediatric obesity, pediatric weight management intervention


In 2015–2016, approximately 30% of school-age children in Denver, Colorado, were affected by obesity (body mass index (BMI, weight [kg]/height [m]2) ≥95th percentile for age and sex) or overweight (85th≤ BMI <95th percentile for age and sex), as defined by the Centers for Disease Control and Prevention (CDC) growth charts.1,2 In 2019, the prevalence of obesity or overweight among children aged 2 to 18 years enrolled in Denver Health (DH) – a large, public nonprofit healthcare system associated with Denver Public Health – was 36.5% (internal communication). To address childhood obesity in their patients, in 2015 DH piloted implementation of the Mind, Exercise, Nutrition, Do It! 7–13 (MEND 7–13) program in 5 federally qualified health centers (FQHC) in the Denver metro area. MEND 7–13 is a pediatric weight management intervention (PWMI) targeting children aged 7 to 13 years that adheres to the United States Preventive Services Task Force recommendation for child obesity.3,4 Developed in the United Kingdom (UK), this evidence-based program is packaged, publicly available for purchase, readily implementable, and thus selected by DH.5,6 MEND 7–13 provided benefits to its participants: it decreased BMI z-scores and waist circumference in a UK randomized controlled trial,3 demonstrated long-term positive outcomes in community settings when delivered by nonspecialists,7 and improved BMI, cardiovascular fitness, and psychometric indices in low-income ethnically diverse United States children with overweight and obesity.8 However, another study raised the question of MEND 7–13 effects beyond decreased adiposity.9

The DH MEND pilot increased access, reach, recruitment, and retention for the patient population compared to other interventions in the community; it also demonstrated significant improvement in health behaviors, BMI, body image, and self-esteem (internal communication). However, retrospective chart review of MEND participants found high rates of weight-related comorbidities, such as prediabetes, affecting approximately 50% of pilot participants (internal communication). Therefore, in April 2016, DH integrated brief medical visits with children, their parents, and designated DH FQHC clinicians, which occurred during MEND 7–13 curriculum delivery, at 1 of 2 MEND visits per week of the 10-week program. These medical visits provided individualized treatment, counseling and goal-setting related to obesity comorbidities and addressed any specific barriers or issues that were not managed in the group setting (Fig. 1). This created a new program called MEND+, in which participant ages were also expanded to 4 to 17 years. The MEND+ curriculum included 20 visits, of which a maximum of 10 were documented medical visits in the electronic health record (EHR) (hereafter termed visit; the other nonmedical encounters were not formally documented). Children obtained referrals from their primary care providers (PCP) via EHR within the DH FQHC network, typically during well child visits when discussing children’s weight and growth chart. During these integrated visits, height, weight, and blood pressure (BP) measurements were entered into the participant’s EHR. The clinicians’ medical services were reimbursable health services and promoted program sustainability.

Figure 1.

Figure 1.

Structure of MEND+ visits. MEND, Mind, Exercise, Nutrition, Do It!; *Visits integrated throughout the duration of the first hour.

Though MEND 7–13 has been studied in settings of normal service delivery in the United States,8 there are no known studies of MEND 7–13 in FQHC settings, or use of the MEND+ model in which medical visits were integrated into the curriculum. FQHCs aim to provide quality primary care for low-income, underserved, and marginalized populations.10-12 Examining EHR data from MEND+ integrated visits created an unprecedented opportunity to examine the effects of MEND+ on childhood obesity and associated comorbidities under real-world conditions at FQHCs. This study’s objective was to examine among MEND+ attendees changes in BMI percentile as a measure of weight status, as well as BP since hypertension is a comorbidity related to pediatric obesity; additional metabolic indicators of insulin resistance, hypercholesterolemia, and nonalcoholic fatty liver diseases (NAFLD) were also examined.

Methods

Study Design and Population

We examined observational data from the DH FQHC EHR on a retrospective cohort of children. Demographic and biometric outpatient data from April 2015 to May 2018 were extracted for children aged 4 to 17 years eligible for MEND+ referral (BMI ≥85th percentile) after the introduction of MEND+. Though MEND+ began in April 2016, data were included from one year prior to MEND+ implementation to capture biometric values prior to program participation. The end date was the last day of completed MEND+ programming prior to data extraction. Data were analyzed in 2018–2019.

This family-oriented PWMI welcomes “all-comers” among children aged 4 to 17 years with obesity or overweight, and siblings may join. Therefore, siblings of referred children can participate without referral themselves, even if siblings have a healthy weight. All MEND+ attendees were combined into one group after sensitivity analyses showed no differences in outcome measures with regard to referral status—whether MEND+ participants had received a formal program referral from a PCP or attended with a referred sibling — or whether the few children with healthy weight were included in the analysis. Final analytic groups were: “Attendees,” any child who attended MEND+ (primary group of interest); “Referred,” children who received at least one MEND+ referral but never attended; and “Eligible,” children in the DH FQHC system with a BMI ≥85th percentile but did not attend nor receive a referral to MEND+.

This project was reviewed by the Quality Improvement Committee of Denver Health, authorized by the Colorado Multiple Institutional Review Board at University of Colorado, Denver, and was determined not to be human subjects’ research, thus deemed exempt from Institutional Review Board review. The CDC, in collaboration with DH, implemented a retrospective program effectiveness evaluation. All EHR data were provided in a securely transferred limited dataset.

Outcome Measures

Body mass index:

The use of BMI z-scores to measure changes in weight among children with severe obesity can result in erroneous conclusions due to previously described statistical limitations of z-scores.13,14 Relative measures such as BMI % of the 95th percentile for age and sex more accurately track changes in adiposity.14 Therefore, BMI percentile was expressed as % of the 95th BMI percentile for age and sex (%BMIp95).

Blood pressure (Systolic [SBP] and Diastolic [DBP], millimeters of mercury, mm Hg):

In children, hypertension is defined as SBP or DBP ≥95th percentile for age, sex, and height.15 For BP measurements without a same day height measurement, we calculated percentiles using the closest measured height (within 3 months of the date of the measurement).16 Designation of hypertension was based on 2017 pediatric BP guidelines.15 BP measurements documented during primary care and MEND+ visits were included; however, those from urgent care and emergency room visits were excluded.

Hemoglobin A1c (HbA1c, Diabetes Control and Complications Trial units, %):

The use of HbA1c among children and adolescents with obesity has become increasingly common to screen for prediabetes and type 2 diabetes.17,18

Alanine transaminase (ALT, units/liter):

There are no definitive biomarkers of NAFLD; definitive diagnosis is made by liver biopsy and ruling out other potential causes of liver steatosis.19 However, elevated ALT in children with obesity can be suggestive of NAFLD and is endorsed by the American Academy of Pediatrics as a screening and tracking measure for NAFLD.

Lipids (milligrams/deciliter):

There is an association between obesity and dyslipidemia in children, including high levels of triglycerides (TG) and low-density lipoprotein cholesterol (LDL).20

Covariates

Covariates included sex, race/ethnicity, age, participation in another PWMI at DH FQHC (a multidisciplinary Healthy Lifestyles Clinic [HLC], which PCPs could also refer children to), and for Attendees, FQHC site, referral status and number of MEND+ visits attended. Demographic covariates were selected at specified time points: for Attendees – first MEND+ visit (or closest antecedent time point); for Referred children – time of last referral (or closest antecedent time point), for Eligible children – the last available data point during their eligibility period for MEND+ referral.

Data Cleaning and Statistical Analyses

Data cleaning was performed in Stata 16.0 and analyses performed in SAS Version 9.4 and R Version 3.2.2. Weight and height data from the EHR were cleaned using an algorithm based on an exponentially weighted moving average method that uses the CDC growth charts and accounts for multiple errors that can occur with measurements from EHRs21 (Supplementary Table). Thereafter, Lowess (locally weighted scatterplot smoothing) or Friedman’s Super Smoother package22,23 was applied to identify additional erroneous body weight observations not flagged by the automated algorithm (Supplementary Table). Children’s %BMIp95 values were calculated using the CDC SAS Macro.24 Clinicians reviewed BP for biological plausibility; no exclusions were made. Clinicians also reviewed laboratory values. Chi-square tests were performed to determine any significant demographic differences between groups.

We compared the average rate of change for the outcome measures before and after the initial MEND+ visit among Attendees; trajectories of BMI, SBP, DBP, HbA1c, ALT, TG, and LDL were examined pre- and postintervention. We used nested mixed-effects models25 with random intercepts and slopes for time (coded as months before and after initial MEND+ visit) and an interaction between time and an indicator variable designating measurements before and after the start of MEND+ (eMethods). These models account for all longitudinal data points for each child. The model also included sex, age, referral status, HLC participation, and FQHC site (as a nesting variable). Models for BMI change had %BMIp95 as the outcome.26,27 Models for SBP and DBP changes included height, which is required to normalize BP levels among children. Given that mixed-effects models accounted for starting BMI and BP, it was not necessary to incorporate their baseline status into the model. We tested for nonlinear functions of BMI and BP data in the Eligible group; the relationship was linear throughout the duration of eligibility. We assessed whether other characteristics, such as number of MEND+ visits, influenced results by comparing the Akaike information criterion of nested models. The same analytic technique was used for before and after the last date of referral for Referred children and was also applied to the Eligible group; these groups were analyzed separately. Within-group changes were analyzed for each group and considered in parallel. Statistically significant values had P < .05.

Results

The sample included 21,408 children: 347 were MEND+ Attendees, 831 Referred, and 20,230 Eligible for MEND+ (Table 1). Among Attendees, there was an even distribution by sex; most children were 7 to 13 years old, and the majority (87.3%) was Hispanic. A similar distribution was seen in the Referred and Eligible groups, with some significant differences (Table 1). The prevalence of severe obesity (BMI percentile ≥120% of 95th percentile for sex and age) was higher among Attendees and Referred (40.6% and 44.0%, respectively), than among Eligible (15.2%) children. Among Attendees, 30.0% had BP categorized as hypertensive, as did 16.2% of Referred and 10.2% of Eligible children. The number of MEND+ visits completed by Attendees is detailed in Table 2. The mean number of MEND+ visits for Attendees was 4.2 and 17.3% attended HLC at least once; among Referred children, the mean number of referrals was 1.1 (standard deviation 0.29) and 7.5% attended HLC at least once (data not shown). We used 101,201 same-day height and weight measurements to determine BMI (eMethods) and 96,781 records with same-day SBP and DBP (Table 3).

Table 1.

Demographic Characteristics of Children Eligible for or Who Attended MEND+, Denver Health, 2016–2018

Demographics Attended MEND+
n (%)
Referred to MEND+
But Did Not Attend n (%)
Eligible for MEND+
(No Referral, No Attendance) n (%)
All 347 (100)* 831 (100)* 20,230(100)*
Sex
  Male 182 (52.4) 449 (54.0) 10,407 (51.4)
  Female 165 (47.6) 382 (46.0) 9823 (48.6)
Race/Ethnicity
  Hispanic 303 (87.3) 662 (79.7) 14,261 (70.5)
  Black, non-Hispanic 9 (2.6) 80 (9.6) 2145 (10.6)
  White, non-Hispanic 19 (5.5) 21 (2.5) 1588 (7.8)
  Other, non-Hispanic 16 (4.6) 68 (8.2) 2236 (11.1)
Age (y)
  <7 32 (9.2) 74 (8.9) 3730 (18.6)
  7–8 81 (23.3) 198 (23.9) 2368 (11.8)
  9–10 104 (30.0) 221 (26.7) 2656 (13.2)
  11–13 114 (32.9) 281 (33.9) 5269 (26.3)
  ≥14 16 (4.6) 55 (6.6) 6039 (30.1)
FQHC site
  Site 1 73 150 2054
  Site 2 33 68 622
  Site 3 104 244 1104
  Site 4 25 20 483
  Site 5 112 342 5311
  Other - 7 10,371
Weight status
  All§ 347 (100)* 829 (100)* 20,062 (100)*
  Normal weight 12 (3.5) 4 (0.5) -
  Overweight 50 (14.4) 83 (10.0) 10,191 (50.8)
  Obesity 285 (82.1) 742 (89.5) 9871 (49.2)
  Severe obesity 141 (40.6) 365 (44.0) 3049 (15.2)
Blood pressure
  All 347 (100)* 823 (100)* 20,005 (100)*
  Normotensive (BP <95th percentile) 243 (70.0) 690 (83.8) 17,957 (89.8)
  Hypertensive (BP ≥95th percentile) 104 (30.0) 133 (16.2) 2048 (10.2)

BP indicates blood pressure; FQHC, Federally Qualified Health Center; MEND, Mind, Exercise, Nutrition, Do It!

Bold font indicates Chi-square test P-value < .05 vs Attended MEND+ group.

*

Percentages may not sum to 100% due to rounding.

Weight status defined as: overweight (85 ≤body mass index (BMI) percentile <95), obesity (BMI percentile ≥95), and severe obesity (BMI percentile ≥120% of 95th percentile).

Excludes children with implausible values for modified z-scores for weight, height, or BMI.

§

Children with BMI percentile <85 at analytic time point not shown.

Hypertension defined as SBP or DBP ≥95th percentile. MEND+ Attendees: demographics, weight status, and blood pressure were measured at the time of their first MEND+ visit. For weight, n = 318 children had a valid height and weight on the day of the first MEND+ visit; however, for n = 29 children their weight status was missing on the first day of the MEND+ visit and was calculated as the closest BMI preceding the day of the first MEND+ visit. Referred children: data were assessed at the time of last referral, as some children received multiple referrals (n = 668). For n = 161, interpolation was necessary to identify the closest value prior to the last referral date (for 2 children values could not be interpolated because they did not have any valid measures before or on the date of the last referral). Eligible children: data were examined at the last available data point during their period of eligibility for referral to MEND+.

Table 2.

Number of Completed MEND+ Clinical Visits Among Attendees, Denver Health, 2015–2018

Number of MEND+
Clinical Visits
Number of MEND+ Attendees
Who Completed Number of Visits
Total 347
 1 85 (24.5%)
 2 39 (11.2%)
 3 39 (11.2%)
 4 37 (10.7%)
 5 27 (7.8%)
 6 35 (10.1%)
 7 35 (10.1%)
 8 19 (5.5%)
 9 17 (4.9%)
 10 8 (2.3%)
>10 6 (1.7%)

MEND indicates Mind, Exercise, Nutrition, Do It!

Table 3.

Number of MEND+ Attendees With Outcome Measures Documented Before and After Participation, Denver Health, 2015–2018

MEND+ Attendees
MEND+ Referred
Outcome of Interest All Children
Total Number of
Observations
Before MEND+
# Children
(# Observations)
After MEND+
# Children
(# Observations)
Children with
Values Both Before
and After MEND+ (n)#
Mean (SD) #
of Months Prior
to First MEND+
Visit That Outcome
Data Were Collected
Mean (SD) # of
Months Following
First MEND+ Visit
That Outcome Data
Were Collected
Mean (SD) # Months
Prior to Last MEND+
Referral that
Outcome Data
Were Collected
Mean (SD) # of
Months Following
Last MEND+ Referral
that Outcome
Data Were Collected
Body mass index 101,201 347 (2,235) 290 (1,285) 290 20.1 (9.0) 6.0 (4.7) 16.7 (10.4) 9.8 (6.4)
Systolic blood pressure 96,781 347 (2115) 289 (1232) 289 19.6 (9.0) 6.0 (4.7) 16.4 (10.4) 9.8 (6.3)
Diastolic blood pressure 96,781 347 (2115) 289 (1232) 289 19.6 (9.0) 6.0 (4.7) 16.4 (10.4) 9.8 (6.3)
Hemoglobin A1c 10,195 170 (243) 121 (146) 59 11.0 (8.5) 4.4 (4.8) 8.0 (9.3) 10.0 (6.1)
Alanine transaminase 9112 172 (235) 122 (138) 54 11.2 (8.5) 4.2 (4.6) 7.3 (8.9) 10.2 (6.4)
Low density lipoprotein 2457 77 (91) 31 (33) 8 11.0 (8.7) 3.8 (4.3) 6.1 (8.7) 7.9 (5.9)
Triglycerides 2540 78 (95) 33 (36) 10 10.9 (8.7) 3.7 (4.2) 6.2 (8.8) 7.5 (6.0)

MEND indicates Mind, Exercise, Nutrition, Do It!; SD, standard deviation.

Prior to MEND+, %BMIp95 increased by an average of 0.247/month among MEND+ Attendees (Table 4). After attending, %BMIp95 decreased by 0.087/month (P < .001). Attendees with referrals to MEND+ had a mean %BMIp95 of 122.5, which is 14 units higher than the mean %BMIp95 of 108.4 among those who attended without referral (data not shown). Among Referred children, before referral %BMIp95 increased by 0.233/month. After referral, %BMIp95 decreased by 0.056/month (P < .001). In contrast, Eligible children had a linear increase of 0.084/month in %BMIp95. Among each of the three groups, a robustness check to examine possible regression to the mean controlled for initial %BMIp95 and yielded similar and statistically significant results. Among Eligible children, a sensitivity analysis showed that if restricted to children with severe obesity at the initial measurement there is still a significant increase, although attenuated (data not shown). Overall, 67% of children showed a stabilization or decline in %BMIp95 trajectory after MEND+ attendance (data not shown). Before MEND+ attendance among Attendees, SBP and DBP increased by 0.041 and 0.022/month, respectively. After MEND+, SBP decreased by 0.254/month (P < .001) and DBP decreased by 0.114/month (P = .008). Among Referred children, before referral, SBP and DBP decreased by 0.028 and 0.008/month, respectively. After the last referral, neither SBP nor DBP significantly changed, with a decrease of 0.040 (P = .771) and 0.015 (P = .484)/month, respectively. Among Eligible children, there was a linear increase in SBP and DBP (0.033 and 0.032/month, respectively), during the study period (Table 4); among those with hypertension at their initial measurement the increase is attenuated. None of the examined characteristics substantially influenced the change in slope following the initial MEND visit (Table 5). For laboratory outcomes, there were no significant changes in HbA1c, ALT, LDL, or TG (Fig. 2).

Table 4.

Mixed-Effects Modeled Change in %BMIp95, SBP, and DBP Among MEND+ Attendees Before and After Participation, 2015–2018

Attendees
Referred
Eligible
Variable Slope Before
MEND+
(mos β)
Change in
Slope
(mos*intv β)
Slope After
MEND+
P* Value Slope Before
Referral
(mos β)
Change in Slope
(mos*lastref β)
Slope After
Referral
P Value Slope Over
Time
P Value
% BMI of the 95th percentile 0.247 −0.334 −0.087 <.001 0.233 −0.289 −0.056 <.001 0.084 <.001
SBP (mm Hg) 0.041 −0.295 −0.254 <.001 −0.028 −0.012 −0.040 .771 0.033 <.001
DBP (mm Hg) 0.022 −0.136 −0.114 .008 −0.008 0.023 0.015 .484 0.032 <.001

BMI indicates body mass index; DBP, diastolic blood pressure; MEND, Mind, Exercise, Nutrition, Do It!; SBP, systolic blood pressure; Mos β, amount of change per month prior to point of analysis; Mos* [variable] β, amount of change in unit between prior to analysis point and after analysis point; and After, amount of change per month after point of analysis.

Model sample sizes: Attendees (BMI: n = 3520 %BMIp95 measurements from n = 347 children; SBP: n = 3347 SBP measurements from n = 347 children; DBP: n = 3,347 DBP measurements from n = 347 children).

Referred (BMI: n = 4,549 %BMIp95 measurements from n = 831 children; SBP: n = 4,389 SBP measurements from n = 831 children; DBP: n = 4389 DBP measurements from n = 831 children).

Eligible (BMI: n = 93,132 %BMIp95 measurements from n = 20,224 children; SBP: n = 89,045 SBP measurements from n = 20,067 children; DBP: n = 89,045 DBP measurements from n = 20,067 children).

*

P value indicates the significance of the change in slope before and after first MEND+ visit for Attendees, and before and after last referral for Referred. For Eligible, P value shows the significance of the positive linear relationship between age in months and the outcome. For all, significant when P < .05.

Table 5.

Mixed Effects Modeled Change in %BMIp95, SBP, and DBP Over Time Among MEND+ Attendees Before and After Participation, Stratified by Characteristics, Denver Health, 2015–2018

Change in Variable Units Per Month
BMI
SBP
DBP
Population Characteristics Slope Before
MEND+ (mos β)
Change in Slope
(mos*intv β)
Slope After
MEND+
Slope Before
MEND+ (mos β)
Change in Slope
(mos*intv β)
Slope After
MEND+
Slope Before
MEND+ (mos β)
Change in Slope
(mos*intv β)
Slope After
MEND+
Sex
Male 0.251 −0.325 −0.074 0.059 −0.412 −0.353 0.007 −0.204 −0.197
Female 0.223 −0.343 −0.120 0.027 −0.157 −0.130 0.038 −0.074 −0.036
Attendance
With referral 0.292 −0.365 −0.073 0.019 −0.222 −0.203 0.000 −0.123 −0.123
Without referral 0.135 −0.233 −0.098 0.097 −0.522 −0.425 0.068 −0.186 −0.118
MEND+ visits
<5 0.173 −0.126 0.047 0.023 −0.186 −0.163 0.032 −0.129 −0.097
≥5 0.352 −0.476 −0.124 0.055 −0.381 −0.326 0.007 −0.143 −0.136
HLC attendance
No 0.221 −0.275 −0.054 0.028 −0.253 −0.225 0.002 −0.091 −0.089
Yes 0.488 −0.525 −0.037 0.106 −0.427 −0.321 0.098 −0.305 −0.207
Weight status
<Overall median 0.132 −0.324 −0.192 0.091 −0.292 −0.201 0.065 −0.250 −0.185
≥Overall median 0.207 −0.298 −0.091 0.009 −0.237 −0.228 0.000 −0.099 −0.099

BMI indicates body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; HLC, Healthy Living Clinic (another pediatric weight management program); Mos β, amount of change per month prior to intervention (MEND+); Mos*intv β, amount of change in unit between prior to intervention and after intervention; and After, amount of change per month after MEND+ intervention.

Figure 2.

Figure 2.

Laboratory outcome measures among MEND+ Attendees, before and after MEND+ participation Denver Health, 2015–2018. The vertical dashed line represents the initiation of MEND+ intervention. Dots represent children with a single laboratory measurement, and lines represent children with multiple laboratory measurements. HbA1c, Hemoglobin A1c; ALT, Alanine Aminotransferase; LDL, Low Density Lipid Cholesterol.

Discussion

We found significantly decreased %BMIp95, SBP and DBP among MEND+ Attendees, with BMI percentile decreased or stabilized among two-thirds of Attendees. To our knowledge, this is the first evaluation that demonstrates not only BMI decrease, but also a statistically significant decrease of BP, in an implementation of the MEND+ model in a FQHC setting. Though a relatively small change in the slope of BP was seen, over time and with sustained lifestyle changes, this rate of decline could lead to decreases in hypertension prevalence among MEND+ attendees. At baseline, Attendees had 3 times the prevalence of hypertension (30%) compared to the Eligible population (10.2%), which could be explained by: 1) the higher percentage of Hispanic children, among whom hypertension is more prevalent,15 2) higher likelihood of enrollment if hypertension had previously been diagnosed. The higher percentage of Hispanic children could potentially reflect a referral bias, as 63.7% of children ages 4 to 17 across all DH FQHC in 2017 were reported to be Hispanic (internal communication). Nevertheless, this study provides evidence that MEND 7–13 based programs can improve both obesity and its comorbidities, such as higher BP, thus contributing to the existing body of literature.7,8 Attendees, on average, attended four medical visits; few completed the full ten medical visits offered during MEND+. However, Attendees and their parents may have incorporated lessons from the intensive curriculum into their daily lifestyle and experienced improvements in both %BMIp95 and BP, even without receiving the maximum dose of the intervention though this cannot be ascertained.

A recent publication focused on MEND 7–13 in low-income, ethnically diverse populations,8 found improvement in %BMIp95, waist circumference, cardiovascular fitness, body-esteem, self-esteem, and other physical and psychosocial measures. However, this study excluded children outside the 7- to 13-year age range, and those with serious clinical conditions, comorbidities, physical disabilities, or learning difficulties. In contrast, MEND+ has no formal exclusion criteria that prevent participation of eligible children. Our analysis shows improved BMI even when implemented with medical visits among “all-comers” in a broader age group within an ethnically diverse population. There were not enough children in the 4 to 6 years and ≥14 years groups to determine whether the intervention was more or less effective in these individual categories. Another study examined implementation of MEND 7–13 in UK community settings and followed up long-term outcomes at 2.4 years.7 There were significant improvements in all physical and psychological outcomes except BMI z-score; however, there were differences by sex, and longer sustained outcomes among boys compared to girls. In our investigation, there was no significant difference in outcomes by sex. The present evaluation also had a shorter follow-up time—a mean of approximately 6 months after the first MEND+ visit for BMI and BP outcome data to be collected—than the 2.4 years postintervention follow-up in the aforementioned study. Whether changes in BMI and BP after MEND+ will be sustained over periods of time beyond the duration of this analysis remains to be seen.

Among Attendees, there were no significant changes in assessed laboratory outcomes. Fewer than 20% of attendees had labs both before and after MEND+ participation; therefore, the analysis was underpowered to detect a significant difference. This may be due to the relatively short duration between program initiation and the opportunity to repeat a laboratory test after MEND+. For instance, HbA1c is typically drawn as determined by appropriate clinical care, usually only every 3 months,28 and a difference may not be detectable in a shorter time period. Laboratories such as ALT, LDL, and TG are typically ordered for Attendees at program initiation but are not often drawn immediately, since laboratories are closed during the time that MEND+ is offered in the evening. By the time these labs are drawn at a time convenient for the participants, it was often a few weeks after MEND+ initiation, and then would not be reordered by providers at graduation if there was insufficient time for a laboratory measure to show significant change. Overall, our result showing a significant change in blood pressure among PWMI Attendees, but not lipids or measures of insulin resistance, is consistent with prior reports.29

Referred patients also experienced a decline in %BMIp95, though less than Attendees; they did not have significant changes in BP. While there was no predefined, statistical control group for Attendees (as this study used EHR data collected at variable intervals), the Referred group was similar to Attendees by sex, age, percentage of Hispanic children, and an offer to participate in MEND+. The decline in BMI in the Referred group could have several explanations: 1) participation in HLC, the other DH PWMI (although 92.5% of Referred children never attended HLC); 2) “readiness factor30-32 – familial or environmental supports, and in turn higher likelihood to attend and engage – perceived by clinician and also driving the child’s ability to achieve BMI reduction even without formal program participation; 3) counseling from PCPs about strategies to improve behaviors related to healthy weight, as recommended by American Academy of Pediatrics.33,34 These possibilities should be considered, particularly given the relatively low dose of MEND+ achieved, with Attendees completing four medical visits on average. However, changes in BP among Attendees and not those Referred may suggest the education, skill building, or rigor associated with MEND+ curriculum. The BMI and BP changes within Attendees, and BMI changes among those Referred, are notable. As a comparison, Eligible children experienced substantial and significant increases in both BMI and BP over time in a linear manner. In the absence of MEND+, this increase may have otherwise been seen among the Attendees and Referred children as part of the DH FQHC population.

This study is subject to limitations. First, this was not a randomized controlled trial, but a retrospective analysis of clinical EHR data for children attending a PWMI in FQHCs. Therefore, unmeasured factors could contribute to observed outcomes. For example, we could not account for sibling status, other shared environmental factors, or selection bias among children who attended MEND+ as opposed to those who did not. Another factor could be error in clinical measurements, although these measurements were obtained by experienced Medical Assistants who received additional training on measurements as part of MEND. Additionally, participation was not uniform among the children, the majority of whom did not attend half of MEND+ medical visits, and the EMR did not include tracking for participation in the nonmedical portions of the program. All these factors should be taken into consideration when interpreting outcomes of the study. Second, there were a limited number of laboratory values in the analyses; the analytic period postintervention was on average shorter than the analytic period pre-intervention, yielding a smaller sample of children with pre- and postintervention laboratory data, and follow-up periods also differed between groups. For future evaluations, it is important that health measures continue to be collected in MEND+ Attendees as clinically appropriate well beyond the time of program participation, to better understand long-term program outcomes. Use of EHRs will likely facilitate ongoing follow-up longitudinally and doing so could lead to better understanding the effects of MEND+. Third, unlike the DH MEND pilot, this analysis of MEND+ did not include psychometric measures such as body image, self-esteem, or health behaviors; although previous studies have demonstrated significant improved overall quality-of-life scores after obesity treatment.29 Fourth, only a small percentage of eligible children were referred to MEND+, and a referral bias could exist that might not be accounted for in the analysis. MEND+ has addressed some barriers to program participation by allowing families to attend at no cost and encouraging PCP endorsement of the program (by presenting about MEND+ at FQHC system wide clinician meetings, providing informational and promotional material, and providing feedback about their patients who attend). Nevertheless, some barriers to participation still exist, such as transportation, parent work schedules, conflicting activities, and limited MEND+ spots to maintain adequate provider to participant ratio and program integrity. However, at the time of publication, MEND+ participation has grown to over 800 attendees (internal communication). Finally, this analysis included data from one FQHC system serving a predominantly Hispanic population in one city. Results may not be generalizable to other MEND implementations, other areas of the country, or in populations where the demographic composition significantly differs.

Conclusions

Our evaluation demonstrated significant declines in BMI and BP among MEND+ participants at FQHCs that served low-income children and families. PWMIs such as MEND+, delivered in FQHCs, might play a key role in helping children with overweight or obesity who are at higher risk for developing cardiometabolic consequences. The unique implementation of MEND+ at DH FQHCs enables the use of EHRs to track both obesity and related comorbidities longitudinally and allows for sustainable integration of medical visits into an evidence-based PWMI implemented in health care settings. The integrated medical visits create more opportunities for reimbursement for health services that offset programmatic costs and facilitate additional clinician engagement with important MEND and health-related data entry into the EHR. Further studies of MEND+ could examine the cost-effectiveness and sustainability of the model. Other health systems could consider adoption of the MEND+ model to provide an evidence-based option to assist children and families in achieving healthy weight and related outcomes.

Supplementary Material

Supplement

WHAT’S NEW.

This is the first study that demonstrates not only BMI improvement, but also a statistically significant decrease of blood pressure in an implementation of the MEND 7–13 program model in real world, federally qualified health center settings.

Acknowledgments

The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.

Funding statement:

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Footnotes

The authors have no conflicts of interest to report.

Supplementary Data

Supplementary data related to this article can be found online at https://doi.org/10.1016/j.acap.2020.11.026.

Contributor Information

Omoye E. Imoisili, Obesity Prevention and Control Branch, Division of Nutrition, Physical Activity, and Obesity; National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Ga; Epidemic Intelligence Service, Center for Surveillance, Epidemiology, and Laboratory Services, Centers for Disease Control and Prevention, Atlanta, Ga; United States Public Health Service, Rockville, Md.

Elizabeth A. Lundeen, Obesity Prevention and Control Branch, Division of Nutrition, Physical Activity, and Obesity, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Ga.

David S. Freedman, Obesity Prevention and Control Branch, Division of Nutrition, Physical Activity, and Obesity, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Ga.

Lindsay S. Womack, Epidemic Intelligence Service, Center for Surveillance, Epidemiology, and Laboratory Services, Centers for Disease Control and Prevention, Atlanta, Ga; United States Public Health Service,Rockville, Md.

Jessica Wallace, Denver Health Ambulatory Care Services, Denver, Co.

Simon J. Hambidge, Denver Health Ambulatory Care Services, Denver, Co.

Steven Federico, Denver Health Ambulatory Care Services, Denver, Co.

Rachel Everhart, Denver Health Ambulatory Care Services, Denver, Co.

Delia Harr, Denver Health Ambulatory Care Services, Denver, Co.

Jillian Vance, Denver Health Ambulatory Care Services, Denver, Co.

Lyudmyla Kompaniyets, Obesity Prevention and Control Branch, Division of Nutrition, Physical Activity, and Obesity, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Ga.

Carrie Dooyema, Obesity Prevention and Control Branch, Division of Nutrition, Physical Activity, and Obesity, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Ga.

Sohyun Park, Obesity Prevention and Control Branch, Division of Nutrition, Physical Activity, and Obesity, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Ga.

Heidi M. Blanck, Obesity Prevention and Control Branch, Division of Nutrition, Physical Activity, and Obesity,National, Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Ga; United States Public Health Service, Rockville, Md.

Alyson B. Goodman, Obesity Prevention and Control Branch, Division of Nutrition, Physical Activity, and Obesity, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Ga; United States Public Health Service, Rockville, Md.

References

  • 1.Denver Public Health. Denver Childhood Obesity Monitoring Report 2012-2016. 2017.
  • 2.Kuczmarski RJ, Ogden CL, Grummer-Strawn LM, et al. CDC growth charts: United States. Adv Data. 2000:1–27. [PubMed] [Google Scholar]
  • 3.Sacher PM, Kolotourou M, Chadwick PM, et al. Randomized controlled trial of the MEND program: a family-based community intervention for childhood obesity. Obesity (Silver Spring, Md). 2010;18(Suppl 1):S62–S68. [DOI] [PubMed] [Google Scholar]
  • 4.Grossman DC, Bibbins-Domingo K, Curry SJ, et al. Screening for obesity in children and adolescents: US Preventive Services Task Force recommendation statement. JAMA. 2017;317:2417–2426. [DOI] [PubMed] [Google Scholar]
  • 5.Fagg J, Cole TJ, Cummins S, et al. After the RCT: who comes to a family-based intervention for childhood overweight or obesity when it is implemented at scale in the community? J Epidemiol community health. 2015;69:142–148. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Healthy Weight Partnership. MEND: health lifestyle and weight management programs for children and families. 2020. Available at: https://healthyweightpartnership.org/. Accessed October 6, 2020.
  • 7.Kolotourou M, Radley D, Gammon C, et al. Long-term outcomes following the MEND 7-13 child weight management program. Child obes (Print). 2015;11:325–330. [DOI] [PubMed] [Google Scholar]
  • 8.Sacher PM, Kolotourou M, Poupakis S, et al. Addressing childhood obesity in low-income, ethnically diverse families: outcomes and peer effects of MEND 7-13 when delivered at scale in US communities. Int J Obes (2005). 2019;43:91–102. [DOI] [PubMed] [Google Scholar]
  • 9.Kolotourou M, Radley D, Chadwick P, et al. Is BMI alone a sufficient outcome to evaluate interventions for child obesity? Child obes (Print). 2013;9:350–356. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Chang CH PWB J, Lurie JD. Geographic expansion of federally qualified health centers 2007-2014. J Rural Health. 2019;35:385–394. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Kelleher KJ, Gardner W. Are FQHCs the solution to care access for underserved children? Pediatrics. 2016;138:e20162479. 10.1542/peds.2016-2479. [DOI] [PubMed] [Google Scholar]
  • 12.Murphy AD, Griffith VM, Mroz TM, et al. Primary care for underserved populations: navigating policy to incorporate occupational therapy into federally qualified health centers. Am J Occup Ther. 2017;71:7102090010p1–7102090010p5. 10.5014/ajot.2017.712001. [DOI] [PubMed] [Google Scholar]
  • 13.Freedman DS, Berenson GS. Tracking of BMI z scores for severe obesity. Pediatrics. 2017;140:e20171072. 10.1542/peds.2017-1072. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Freedman DS, Butte NF, Taveras EM, et al. BMI z-Scores are a poor indicator of adiposity among 2- to 19-year-olds with very high BMIs, NHANES 1999-2000 to 2013-2014. Obesity (Silver Spring, Md). 2017;25:739–746. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Flynn JT, Kaelber DC, Baker-Smith CM, et al. Clinical practice guideline for screening and management of high blood pressure in children and adolescents. Pediatrics. 2017;140:e20171904. 10.1542/peds.2017-1904. [DOI] [PubMed] [Google Scholar]
  • 16.Rosner B, Cook N, Portman R, et al. Determination of blood pressure percentiles in normal-weight children: some methodological issues. Am J Epidemiol. 2008;167:653–666. [DOI] [PubMed] [Google Scholar]
  • 17.Ehehalt S, Wiegand S, Korner A, et al. Diabetes screening in overweight and obese children and adolescents: choosing the right test. Eur J Pediatr. 2017;176:89–97. [DOI] [PubMed] [Google Scholar]
  • 18.Galhardo J, Shield J. The role of haemoglobin A1c in screening obese children and adolescents for glucose intolerance and type 2 diabetes. Acta Medica Portuguesa. 2015;28:307–315. [PubMed] [Google Scholar]
  • 19.Vos MB, Abrams SH, Barlow SE, et al. NASPGHAN clinical practice guideline for the diagnosis and treatment of nonalcoholic fatty liver disease in children: recommendations from the expert committee on NAFLD (ECON) and the North American Society of Pediatric Gastroenterology, hepatology and nutrition (NASPGHAN). J Pediatr Gastroenterol Nutr. 2017;64:319–334. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Expert panel on integrated guidelines for cardiovascular health and risk reduction in children and adolescents: summary report. Pediatrics. 2011;128(Suppl 5):S213–S256. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Daymont C, Ross ME, Russell Localio A, et al. Automated identification of implausible values in growth data from pediatric electronic health records. J Am Med Inform Assoc. 2017;24:1080–1087. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Cohen RA. An introduction to PROC LOESS for local regression. Paper presented at: Proceedings of the twenty-fourth annual SAS users group international conference, Paper 1999. [Google Scholar]
  • 23.Friedman JH. A Variable Span Smoother. Stanford Univ CA Lab for Computational Statistics; 1984. [Google Scholar]
  • 24.Centers for Disease Control Prevention. A SAS Program for the CDC Growth Charts. 2000. [Google Scholar]
  • 25.Bates D, Mächler M, Bolker B, et al. Fitting linear mixed-effects models using lme4. arXiv e-prints. 2014. Available at: https://ui.adsabs.harvard.edu/abs/2014arXiv1406.5823B. Accessed June 01, 2014. [Google Scholar]
  • 26.Flegal KM, Wei R, Ogden CL, et al. Characterizing extreme values of body mass index-for-age by using the 2000 Centers for Disease Control and Prevention growth charts. Am J Clin Nutr. 2009;90:1314–1320. [DOI] [PubMed] [Google Scholar]
  • 27.Kelly AS, Barlow SE, Rao G, et al. Severe obesity in children and adolescents: identification, associated health risks, and treatment approaches: a scientific statement from the American Heart Association. Circulation. 2013;128:1689–1712. [DOI] [PubMed] [Google Scholar]
  • 28.Copeland KC, Silverstein J, Moore KR, et al. Management of newly diagnosed type 2 diabetes mellitus (T2DM) in children and adolescents. Pediatrics. 2013;131:364–382. [DOI] [PubMed] [Google Scholar]
  • 29.Peirson L, Fitzpatrick-Lewis D, Morrison K, et al. Treatment of overweight and obesity in children and youth: a systematic review and meta-analysis. CMAJ Open. 2015;3:E35–E46. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Rhee KE, De Lago CW, Arscott-Mills T, et al. Factors associated with parental readiness to make changes for overweight children. Pediatrics. 2005;116:e94–101. [DOI] [PubMed] [Google Scholar]
  • 31.Warschburger P, Kröller K. Childhood overweight and obesity: maternal perceptions of the time for engaging in child weight management. BMC public health. 2012;12:295. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Kostadinov I, Daniel M, Jones M, et al. Assessing change in perceived community leadership readiness in the Obesity Prevention and Lifestyle program. Health Promotion J Australia. 2016;27:208–214. [DOI] [PubMed] [Google Scholar]
  • 33.Imoisili OE, Goodman AB, Dooyema CA, et al. Referrals and management strategies for pediatric obesity—DocStyles survey 2017. Front Pediatr. 2018;6:367. 10.3389/fped.2018.00367. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Barlow SE. Expert committee recommendations regarding the prevention, assessment, and treatment of child and adolescent overweight and obesity: summary report. Pediatrics. 2007;120(Suppl 4): S164–S192. [DOI] [PubMed] [Google Scholar]

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