Emily J. Tomayko

Electronic Health Records and Community Health Surveillance of Childhood Obesity

BACKGROUND Childhood obesity remains a public health concern, and tracking local progress may require local surveillance systems. Electronic health record data may provide a cost-effective solution. PURPOSE To demonstrate the feasibility of estimating childhood obesity rates using de-identified electronic health records for the purpose of public health surveillance and health promotion. METHODS Data were extracted from the Public Health Information Exchange (PHINEX) database. PHINEX contains de-identified electronic health records from patients primarily in south central Wisconsin. Data on children and adolescents (aged 2-19 years, 2011-2012, n=93,130) were transformed in a two-step procedure that adjusted for missing data and weighted for a national population distribution. Weighted and adjusted obesity rates were compared to the 2011-2012 National Health and Nutrition Examination Survey (NHANES). Data were analyzed in 2014. RESULTS The weighted and adjusted obesity rate was 16.1% (95% CI=15.8, 16.4). Non-Hispanic white children and adolescents (11.8%, 95% CI=11.5, 12.1) had lower obesity rates compared to non-Hispanic black (22.0%, 95% CI=20.7, 23.2) and Hispanic (23.8%, 95% CI=22.4, 25.1) patients. Overall, electronic health record-derived point estimates were comparable to NHANES, revealing disparities from preschool onward. CONCLUSIONS Electronic health records that are weighted and adjusted to account for intrinsic bias may create an opportunity for comparing regional disparities with precision. In PHINEX patients, childhood obesity disparities were measurable from a young age, highlighting the need for early intervention for at-risk children. The electronic health record is a cost-effective, promising tool for local obesity prevention efforts.

Linking electronic health records with community-level data to understand childhood obesity risk

Environmental and socioeconomic factors should be considered along with individual characteristics when determining risk for childhood obesity.

The Healthy Children, Strong Families intervention promotes improvements in nutrition, activity and body weight in American Indian families with young children

Objective American Indian children of pre-school age have disproportionally high obesity rates and consequent risk for related diseases. Healthy Children, Strong Families was a family-based randomized trial assessing the efficacy of an obesity prevention toolkit delivered by a mentor v. mailed delivery that was designed and administered using community-based participatory research approaches. Design During Year 1, twelve healthy behaviour toolkit lessons were delivered by either a community-based home mentor or monthly mailings. Primary outcomes were child BMI percentile, child BMI Z-score and adult BMI. Secondary outcomes included fruit/vegetable consumption, sugar consumption, television watching, physical activity, adult health-related self-efficacy and perceived health status. During a maintenance year, home-mentored families had access to monthly support groups and all families received monthly newsletters. Setting Family homes in four tribal communities, Wisconsin, USA. Subjects Adult and child (2–5-year-olds) dyads (n 150). Results No significant effect of the mentored v. mailed intervention delivery was found; however, significant improvements were noted in both groups exposed to the toolkit. Obese child participants showed a reduction in BMI percentile at Year 1 that continued through Year 2 (P<0·05); no change in adult BMI was observed. Child fruit/vegetable consumption increased (P=0·006) and mean television watching decreased for children (P=0·05) and adults (P=0·002). Reported adult self-efficacy for health-related behaviour changes (P=0·006) and quality of life increased (P=0·02). Conclusions Although no effect of delivery method was demonstrated, toolkit exposure positively affected adult and child health. The intervention was well received by community partners; a more comprehensive intervention is currently underway based on these findings.

Healthy Children, Strong Families 2: A randomized controlled trial of a healthy lifestyle intervention for American Indian families designed using community-based approaches:

Background/Aims Few obesity prevention trials have focused on young children and their families in the home environment, particularly in underserved communities. Healthy Children, Strong Families 2 is a randomized controlled trial of a healthy lifestyle intervention for American Indian children and their families, a group at very high risk of obesity. The study design resulted from our long-standing engagement with American Indian communities, and few collaborations of this type resulting in the development and implementation of a randomized clinical trial have been described. Methods Healthy Children, Strong Families 2 is a lifestyle intervention targeting increased fruit and vegetable intake, decreased sugar intake, increased physical activity, decreased TV/screen time, and two less-studied risk factors: stress and sleep. Families with young children from five American Indian communities nationwide were randomly assigned to a healthy lifestyle intervention (Wellness Journey) augmented with social support (Facebook and text messaging) or a child safety control group (Safety Journey) for 1 year. After Year 1, families in the Safety Journey receive the Wellness Journey, and families in the Wellness Journey start the Safety Journey with continued wellness-focused social support based on communities’ request that all families receive the intervention. Primary (adult body mass index and child body mass index z-score) and secondary (health behaviors) outcomes are assessed after Year 1 with additional analyses planned after Year 2. Results To date, 450 adult/child dyads have been enrolled (100% target enrollment). Statistical analyses await trial completion in 2017. Lessons learned Conducting a community-partnered randomized controlled trial requires significant formative work, relationship building, and ongoing flexibility. At the communities’ request, the study involved minimal exclusion criteria, focused on wellness rather than obesity, and included an active control group and a design allowing all families to receive the intervention. This collective effort took additional time but was critical to secure community engagement. Hiring and retaining qualified local site coordinators was a challenge but was strongly related to successful recruitment and retention of study families. Local infrastructure has also been critical to project success. Other challenges included geographic dispersion of study communities and providing appropriate incentives to retain families in a 2-year study. Conclusion This multisite intervention addresses key gaps regarding family/home-based approaches for obesity prevention in American Indian communities. Healthy Children, Strong Families 2’s innovative aspects include substantial community input, inclusion of both traditional (diet/activity) and less-studied obesity risk factors (stress/sleep), measurement of both adult and child outcomes, social networking support for geographically dispersed households, and a community selected active control group. Our data will address a literature gap regarding multiple risk factors and their relationship to health outcomes in American Indian families.

Food insecurity and physical activity insecurity among rural Oregon families

Among rural families, rates of both child obesity and household food insecurity (FI) are higher compared to non-rural families. These disparities result from a complex interplay of social and environmental conditions that influence behavior. The Transtheoretical Model suggests individual readiness to change underlies success in modifying obesity-preventing behaviors; however, whether an association between readiness to change obesity-related behaviors and FI status among rural families exists is unknown. We examined the association between readiness to change family-level nutrition and physical activity (PA) behaviors that predict child obesity and family FI status within a sample of rural families to better understand these relationships. Families (n = 144) were recruited from six rural Oregon communities in 2013. Families completed a FI screener and the Family Stage of Change Survey (FSOC), a measure of readiness to change family-level nutrition and PA behaviors associated with obesity. Demographic differences by FI status were explored, and regression was applied to examine relationships between FI and FSOC scores, adjusting for relevant covariates. Among FI families (40.2%), more were non-white (77.8% vs. 22.2%; p = 0.036) and had lower adult education (30.4% vs. 11.8% with > high school degree; p = 0.015) compared to non-FI families. After adjusting for education, race, ethnicity, and eligibility for federal meal programs, readiness to provide opportunities for PA was lower among FI families (p = 0.002). These data highlight a need to further investigate how food insecurity and low readiness to provide PA opportunities, i.e. “physical activity insecurity” may be contributing to the higher obesity rates observed among rural children and families.

Image-Based Dietary Assessment Ability of Dietetics Students and Interns

Image-based dietary assessment (IBDA) may improve the accuracy of dietary assessments, but no formalized training currently exists for skills relating to IBDA. This study investigated nutrition and dietetics students’ and interns’ IBDA abilities, the training and experience factors that may contribute to food identification and quantification accuracy, and the perceived challenges to performing IBDA. An online survey containing images of known foods and serving sizes representing common American foods was used to assess the ability to identify foods and serving sizes. Nutrition and dietetics students and interns from the United States and Australia (n = 114) accurately identified foods 79.5% of the time. Quantification accuracy was lower, with only 38% of estimates within ±10% of the actual weight. Foods of amorphous shape or higher energy density had the highest percent error. Students expressed general difficulty with perceiving serving sizes, making IBDA food quantification more difficult. Experience cooking at home from a recipe, frequent measuring of portions, and having a food preparation or cooking laboratory class were associated with enhanced accuracy in IBDA. Future training of dietetics students should incorporate more food-based serving size training to improve quantification accuracy while performing IBDA, while advances in IBDA technology are also needed.

Overnight sleep duration and obesity in 2-5 year-old American Indian children: Sleep and obesity

Sleep has emerged as a potentially modifiable risk factor for obesity in children.

Understanding Correlates of Physical Activity in American Indian Families: The Healthy Children Strong Families-2 Study

BACKGROUND Little is known about factors contributing to physical activity (PA) in American Indian (AI) populations. Addressing this gap is paramount as sedentary activity and obesity continue to increase in this population. The purpose of this study was to determine factors associated with PA among AI families with young children. METHODS Height and weight of both adult (n = 423) and child (n = 390) were measured, and surveys assessed demographics, PA, stress (adult only), sleep, and screen time. Separate multivariate logistic regression models were constructed for adults and children (reported as adjusted odds ratios, aORs). RESULTS For adults, age (aOR = 0.952; P ≤ .001), television viewing (aOR = 0.997; P = .01), and computer use (aOR = 0.996; P = .003) decreased the odds of being active. For children, high adult activity (aOR = 1.795; P ≤ .01), longer weekday sleep (aOR = 1.004; P = .01), and family income >

Predictors of Overweight and Obesity in American Indian Families With Young Children

35,000 (aOR = 2.772; P = .01) increased the odds of being active. We found no association between adult PA with stress or adult sleep or between child PA with body mass index and screen time. CONCLUSIONS Given the complexity of the factors contributing to obesity among AI families, multigenerational interventions focused on healthy lifestyle change such as decreasing adult screen time and increasing child sleep time may be needed to increase PA within AI families.

Evaluation of a multi-year policy-focused intervention to increase physical activity and related behaviors in lower-resourced early care and education settings: Active Early 2.0

Objective: To describe sociodemographic factors and health behaviors among American Indian (AI) families with young children and determine predictors of adult and child weight status among these factors. Design: Descriptive, cross‐sectional baseline data. Setting: One urban area and 4 rural AI reservations nationwide. Participants: A total of 450 AI families with children aged 2–5 years participating in the Healthy Children, Strong Families 2 intervention. Intervention: Baseline data from a healthy lifestyles intervention. Main Outcome Measures: Child body mass index (BMI) z‐score and adult BMI, and multiple healthy lifestyle outcomes. Analysis: Descriptive statistics and stepwise regression. Results: Adult and child combined overweight and obesity rates were high: 82% and 40%, respectively. Food insecurity was high (61%). Multiple lifestyle behaviors, including fruit and vegetable and sugar‐sweetened beverage consumption, adult physical activity, and child screen time, did not meet national recommendations. Adult sleep was adequate but children had low overnight sleep duration of 10 h/d. Significant predictors of child obesity included more adults in the household (P = .003; &bgr; = 0.153), an adult AI caregiver (P = .02; &bgr; = 0.116), high adult BMI (P = .001; &bgr; = 0.176), gestational diabetes, high child birth weight (P < .001; &bgr; = 0.247), and the family activity and nutrition score (P = .04; &bgr; = 0.130). Conclusions and Implications: We found multiple child‐, adult‐, and household‐level factors influence early childhood obesity in AI children, highlighting the need for interventions to mitigate the modifiable factors identified in this study, including early life influences, home environments, and health behaviors.