Elizabeth A. Lundeen

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

Although the Centers for Disease Control and Prevention (CDC) growth charts are widely used, BMI‐for‐age z‐Scores (BMIz) are known to be uninformative above the 97th percentile. This study compared the relations of BMIz and other BMI metrics (%BMIp95, percent of 95th percentile, and ΔBMIp95, BMI minus 95th percentile) to circumferences, skinfolds, and fat mass. We were particularly interested in the differences among children with severe obesity (%BMIp95 ≥ 120).

Obesity Prevalence Among Adults Living in Metropolitan and Nonmetropolitan Counties - United States, 2016.

Approximately 46 million persons (14%) in the United States live in nonmetropolitan counties.* Compared with metropolitan residents, nonmetropolitan residents have a higher prevalence of obesity-associated chronic diseases such as diabetes (1), coronary heart disease (1), and arthritis (2). The 2005-2008 National Health and Nutrition Examination Survey (NHANES) found a significantly higher obesity prevalence among adults in nonmetropolitan (39.6%) than in metropolitan (33.4%) counties (3). However, this difference has not been examined by state. Therefore, CDC examined state-level 2016 Behavioral Risk Factor Surveillance System (BRFSS) data and found that the prevalence of obesity (body mass index [BMI] ≥30 kg/m2) was 34.2% among U.S. adults living in nonmetropolitan counties and 28.7% among those living in metropolitan counties (p<0.001). Obesity prevalence was significantly higher among nonmetropolitan county residents than among metropolitan county residents in all U.S. Census regions, with the largest absolute difference in the South (5.6 percentage points) and Northeast (5.4 percentage points). In 24 of 47 states, obesity prevalence was significantly higher among persons in nonmetropolitan counties than among those in metropolitan counties; only in Wyoming was obesity prevalence higher among metropolitan county residents than among nonmetropolitan county residents. Both metropolitan and nonmetropolitan counties can address obesity through a variety of policy and environmental strategies to increase access to healthier foods and opportunities for physical activity (4).

Adolescent Sugar-Sweetened Beverage Intake is Associated With Parent Intake, Not Knowledge of Health Risks:

Purpose: To examine associations of adolescent sugar-sweetened beverage (SSB) intake with parent SSB intake and parent and adolescent knowledge of SSB-related health risks. Design: Quantitative, cross-sectional. Setting: 2014 SummerStyles survey. Subjects: Nine hundred and ninety parent and adolescent (12-17 years) pairs. Measures: The outcome was self-reported adolescent intake (0, >0 to <1, or ≥1 time/day) of SSBs (soda, fruit drinks, sports/energy drinks, other SSBs). The exposures were self-reported parent SSB intake (0, >0 to <1, ≥1 to <2, or ≥2 times/day) and parent and adolescent knowledge of SSB-related health risks (weight gain, diabetes, and dental caries). Analysis: Separate multinomial logistic regression models were used to estimate adjusted odds ratios (aORs) for adolescent SSB intake ≥1 time/day (ref: 0 times/day), according to (1) parent SSB intake and (2) parent and (3) adolescent knowledge. Results: About 31% of adolescents consumed SSBs ≥1 time/day, and 43.2% of parents consumed SSBs ≥2 times/day. Adolescent and parent knowledge that SSB intake is related to health conditions ranged from 60.7% to 80.4%: weight gain (75.0% and 80.4%, respectively), diabetes (60.7% and 71.4%, respectively), and dental caries (77.5% and 72.9%, respectively). In adjusted models, adolescent SSB intake ≥1 time/day was associated with parent intake ≥2 times/day (aOR = 3.30; 95% confidence interval = 1.62-6.74) but not with parent or adolescent knowledge of health risks. Conclusion: Parental SSB intake may be an important factor in understanding adolescent behavior; knowledge of SSB-related health conditions alone may not influence adolescent SSB behavior.

Total Sugar-Sweetened Beverage Intake Among US Adults Was Lower When Measured Using a 1-Question Versus 4-Question Screener:

Purpose: To compare the performance of a 1-question survey screener measuring total sugar-sweetened beverage (SSB) intake to a screener measuring SSB types separately using 4 questions. Design: Cross-sectional. Setting: Web-based 2014 SummerStyles survey. Participants: A total of 4167 US adults (≥18 years). Measures: Frequency of SSB intake measured using a 1-question screener was compared to frequency using a 4-question screener (regular soda, fruit drinks, sports/energy drinks, sweetened coffee/tea). SSB intake (number of time/day) was categorized as 0, >0 to <1, and ≥1 time/day; difference in mean intake was calculated between 4 questions versus 1. Analysis: Paired t tests were used, and agreement was evaluated using weighted κ and Lin’s concordance correlation coefficient (CCC). Results: Mean SSB intake was 1.7 (95% confidence interval [CI]: 1.65-1.79) times/day using 4 questions and 0.6 (95% CI: 0.56-0.62) times/day using 1 question (P < .001). Intake frequency based on 4 questions versus 1 was 16.0% versus 38.5% for 0 time/day, 15.6% versus 42.5% for >0 to <1 time/day, and 68.4% versus 18.9% for ≥1 time/day. There was fair agreement for the 3 SSB intake categories (κ: .27) and poor absolute agreement between the 2 continuous measures (Lin’s CCC: 0.31). Conclusion: Daily SSB intake was significantly lower using a 1-question screener versus a 4-question screener. Researchers should assess SSB types separately or consider that daily SSB intake is likely underestimated with 1 question.

Impact of Knowledge of Health Conditions on Sugar-Sweetened Beverage Intake Varies Among US Adults

Purpose: This study examined associations between knowledge of sugar-sweetened beverage (SSB)-related health conditions and SSB intake among US adults. Design: Quantitative, cross-sectional study. Subject: The 2014 SummerStyles survey data for 4163 US adults (≥18 years) were used. Measures: The outcome measure was frequency of SSB intake (regular soda, fruit drinks, sports or energy drinks, sweetened coffee/tea drinks). Exposure measures were knowledge of 6 SSB-related health conditions: weight gain, diabetes, cavities, high cholesterol, heart disease, and hypertension. Analysis: Six logistic regression models were used to estimate adjusted odds ratios (ORs) for consuming SSBs ≥2 times/d according to knowledge of SSB-related health conditions. Results: Overall, 37.8% of adults reported consuming SSBs ≥2 times/d. Although most adults identified that weight gain (80.2%), diabetes (73.6%), and cavities (71.8%) are related to drinking SSBs, fewer adults identified high cholesterol (24.1%), heart disease (31.5%), and hypertension (33.0%) as being related to drinking SSBs. Crude analyses indicated that lower SSB intake was significantly associated with knowledge of the associations between SSBs and weight gain, diabetes, cavities, and heart disease. However, after adjustment for covariates, only lack of knowledge of the association between heart disease and SSBs was significantly associated with consuming SSBs ≥2 times/d (OR = 1.29) than non-SSB consumers. Conclusions: The finding that knowledge of SSB-related health conditions, in general, was not associated with high SSB intake suggests that knowledge on SSB-related health conditions alone may not be sufficient for adult behavior change.

Unhealthy Weight Management Practices and Non-medical Use of Prescription Drugs

INTRODUCTION Non-medical use of prescription drugs (NMUPD) has reached epidemic proportions in the U.S. With approximately one in five high school students engaging in NMUPD, it is important to understand behavioral correlates. METHODS Data were combined from the 2011 and 2013 cycles of the Youth Risk Behavior Survey, a nationally representative, cross-sectional survey. After restricting the analytic sample to students who reported a weight loss goal of either staying the same weight or losing weight, logistic regression models were used to estimate adjusted prevalence ratios and 95% CIs for associations between unhealthy weight management practices (UWMPs) and lifetime NMUPD. Individual UWMPs-fasting; taking diet pills, powders, or liquids without a doctors advice; and vomiting or taking laxatives-and total number of UWMPs were examined. Data were analyzed in 2016. RESULTS UWMPs were more prevalent among female students (21.1% vs 10.7% for fasting; 7.5% vs 5.2% for taking diet pills, powders, or liquids; and 7.6% vs 3.2% for vomiting or taking laxatives). Significant associations between individual UWMPs and NMUPD and between the number of UWMPs and NMUPD were observed. DISCUSSION UWMPs were associated with NMUPD. Health educators in the school setting, as well as other health professionals who provide services to an adolescent population, can focus on healthy weight management strategies, and other substance-specific messages. CONCLUSIONS The association between UWMPs and NMUPD may reflect a constellation of problem behaviors exhibited among some adolescents.

Do Schools That Screen for Body Mass Index Have Recommended Safeguards in Place

The Centers for Disease Control and Prevention recommends that schools adopt 10 safeguards before launching a body mass index (BMI) screening program; however, little is known about schools’ safeguard adoption. Authors identified questions from the 2014 School Health Policies and Practices Study that aligned with 4 of the 10 safeguards to estimate safeguard prevalence among schools that screened students for BMI (40.7%, N = 223). Among these schools, 3.1% had all four safeguards and 56.5% had none or one. The most prevalent safeguard was having reliable and accurate equipment (54.1%, 95% confidence interval [CI] = [46.1, 62.1]). Providing staff with appropriate expertise and training was the least prevalent; respondents in 26.4% (95% CI [17.1, 35.6]) of schools received recent training on weight status assessment, weight management, and eating disorder identification. School-based BMI screening is common, but adopting multiple recommended safeguards is not. Absent these safeguards, BMI screening programs may fall short of intended outcomes and potentially incur unintended consequences.

Clinical-Community Partnerships to Identify Patients With Food Insecurity and Address Food Needs

Introduction More than 42 million people in the United States are food insecure. Although some health care entities are addressing food insecurity among patients because of associations with disease risk and management, little is known about the components of these initiatives. Methods The Systematic Screening and Assessment Method was used to conduct a landscape assessment of US health care entity–based programs that screen patients for food insecurity and connect them with food resources. A network of food insecurity researchers, experts, and practitioners identified 57 programs, 22 of which met the inclusion criteria of being health care entities that 1) screen patients for food insecurity, 2) link patients to food resources, and 3) target patients including adults aged 50 years or older (a focus of this assessment). Data on key features of each program were abstracted from documentation and telephone interviews. Results Most programs (n = 13) focus on patients with chronic disease, and most (n = 12) partner with food banks. Common interventions include referrals to or a list of food resources (n = 19), case managers who navigate patients to resources (n = 15), assistance with federal benefit applications (n = 14), patient education and skill building (n = 13), and distribution of fruit and vegetable vouchers redeemable at farmers markets (n = 8). Most programs (n = 14) routinely screen all patients. Conclusion The programs reviewed use various strategies to screen patients, including older adults, for food insecurity and to connect them to food resources. Research is needed on program effectiveness in improving patient outcomes. Such evidence can be used to inform the investments of potential stakeholders, including health care entities, community organizations, and insurers.

Availability and Promotion of Healthful Foods in Stores and Restaurants ― Guam, 2015

Chronic disease, which is linked to unhealthy nutrition environments, is highly prevalent in Guam. The nutrition environment was assessed in 114 stores and 63 restaurants in Guam. Stores had limited availability of some healthier foods such as lean ground meat (7.5%) and 100% whole-wheat bread (11.4%), while fruits (81.0%) and vegetables (94.8%) were more commonly available; 43.7% of restaurants offered a healthy entrée or main dish salad, 4.1% provided calorie information, and 15.7% denoted healthier choices on menus. Improving the nutrition environment could help customers make healthier choices.

Sodium in Store and Restaurant Food Environments — Guam, 2015

Compared with the United States overall, Guam has higher mortality rates from cardiovascular disease and stroke (1). Excess sodium intake can increase blood pressure and risk for cardiovascular disease (2,3). To determine the availability and promotion of lower-sodium options in the nutrition environment, the Guam Department of Public Health and Social Services (DPHSS) conducted an assessment in September 2015 using previously validated tools adapted to include sodium measures. Stores (N = 114) and restaurants (N = 63) were randomly sampled by region (north, central, and south). Data from 100 stores and 62 restaurants were analyzed and weighted to account for the sampling design. Across the nine product types assessed, lower-sodium products were offered less frequently than regular-sodium products (p<0.001) with <50% of stores offering lower-sodium canned vegetables, tuna, salad dressing, soy sauce, and hot dogs. Lower-sodium products were also less frequently offered in small stores than large (two or more cash registers) stores. Reduced-sodium soy sauce cost more than regular soy sauce (p<0.001) in stores offering both options in the same size bottle. Few restaurants engaged in promotion practices such as posting sodium information (3%) or identifying lower-sodium entrées (1%). Improving the availability and promotion of lower-sodium foods in stores and restaurants could help support healthier eating in Guam.