Gestational Diabetes Prevalence Estimates from Three Data Sources, 2018.

INTRODUCTION: We investigated 2018 gestational diabetes mellitus (GDM) prevalence estimates in three surveillance systems (National Vital Statistics System, State Inpatient Database, and Pregnancy Risk Assessment Monitoring Survey). METHODS: We calculated GDM prevalence for jurisdictions represented in each system; a subset of data was analyzed for people 18-39 years old in 22 jurisdictions present in all three systems to observe dataset-specific demographics and GDM prevalence using comparable categories. RESULTS: GDM prevalence estimates varied widely by data system and within the data subset despite comparable demographics. DISCUSSION: Understanding the differences between GDM surveillance data systems can help researchers better identify people and places at higher risk of GDM.

Trends in the Diagnosed Prevalence and Incidence of Major Eye Diseases in Medicare Part B Fee-for-Service Beneficiaries 68 Years of Age or Older.

PURPOSE: To study contemporary trends in the diagnosed prevalence and incidence of age-related eye diseases among Medicare Fee-for-Service (FFS) beneficiaries. DESIGN: Analysis of Medicare administrative claims data. PARTICIPANTS: Medicare FFS beneficiaries 68 years of age and older from 2005 through 2020 who were enrolled continuously in both Part A and Part B for 3 years, including the index year and a 2-year lookback period. METHODS: Annual cross-sectional diagnosed prevalence and incidence rates were calculated. Age standardization was performed using the direct standardization method to account for changes in the age structure of the study population. Rates stratified by demographics (age, sex, race, and ethnicity) also were calculated. MAIN OUTCOME MEASURES: Annual prevalence and incidence of diagnosed age-related macular degeneration (AMD), diabetic retinopathy (DR) (among those with diabetes), and glaucoma. RESULTS: At baseline, in 2005, 60% of included beneficiaries were female, 20% were 85 years of age or older, 86% were non-Hispanic White, and one-quarter had a diagnosis of diabetes. From 2005 through 2019, the prevalence of a diagnosis of any of the conditions studied increased from 16.4% (n = 3 628 996) to 17.9% (n = 3 731 281). Diagnosed incidence decreased over this period from 4.9% (n = 954 878) in 2005 to 4.2% in 2019 (n = 757 696). The diagnosed prevalence of AMD increased from 6.8% (n = 1 504 770) to 9.4% (n = 1 965 176); the diagnosed prevalence of any DR among those with diabetes decreased from 9.3% (n = 504 135) to 9.0% (n = 532 859), although the diagnosed prevalence of vision-threatening DR increased from 2.0% to 3.4%; and the diagnosed prevalence of any diagnosed glaucoma decreased from 8.8% (n = 1 951 141) to 8.1% (n = 1 692 837). In 2020, the diagnosed prevalence and incidence of all diagnoses decreased. During the study period, we detected demographic differences in the prevalence and incidence of diagnosis of each condition. CONCLUSIONS: This study presents updated data on the prevalence and incidence of diagnosed major chronic, age-related eye diseases among Medicare FFS beneficiaries. Compared with older epidemiologic estimates, we found that the diagnosed prevalence of each condition studied was higher in more recent years. These findings may inform public health and policy planning and resource allocation to address the eye health of an increasingly older United States population. FINANCIAL DISCLOSURE(S): The author(s) have no proprietary or commercial interest in any materials discussed in this article.

Prevalence of Testing for Diabetes Among US Adults With Overweight or Obesity, 2016-2019.

Introduction: Screening for prediabetes and type 2 diabetes may allow earlier detection, diagnosis, and treatment. The US Preventive Services Task Force recommends screening every 3 years for abnormal blood glucose among adults aged 40 to 70 years with overweight or obesity. Using IQVIA Ambulatory Electronic Medical Records, we estimated the proportion of adults aged 40 to 70 years with overweight or obesity who received blood glucose testing within 3 years from baseline in 2016. Methods: We identified 1,338,509 adults aged 40 to 70 years with overweight or obesity in 2016 and without pre-existing diabetes. We included adults whose records were present in the data set for at least 2 years before their index body mass index (BMI) in 2016 and 3 years after the index BMI (2017-2019), during which we examined the occurrence of blood glucose testing. We calculated the unadjusted and adjusted prevalence of receiving blood glucose testing. Results: The unadjusted prevalence of receiving blood glucose testing was 33.4% when it was defined as having a hemoglobin A1c or fasting plasma glucose measure. The unadjusted prevalence was 74.3% when we expanded the definition of testing to include random plasma glucose and unspecified glucose measures. Adults with obesity were more likely to receive the test than those with overweight. Men (vs women) and adults aged 50 to 59 years (vs other age groups) had higher testing rates. Conclusion: Our findings could inform clinical and public health promotion efforts to improve screening for blood glucose levels among adults with overweight or obesity.

The Economic Burden of Vision Loss and Blindness in the United States.

PURPOSE: To estimate the economic burden of vision loss (VL) in the United States and by state. DESIGN: Analysis of secondary data sources (American Community Survey [ACS], American Time Use Survey, Bureau of Labor Statistics, Medical Expenditure Panel Survey [MEPS], National and State Health Expenditure Accounts, and National Health Interview Survey [NHIS]) using attributable fraction, regression, and other methods to estimate the incremental direct and indirect 2017 costs of VL. PARTICIPANTS: People with a yes response to a question asking if they are blind or have serious difficulty seeing even when wearing glasses in the ACS, MEPS, or NHIS. MAIN OUTCOME MEASURES: We estimated the direct costs of medical, nursing home (NH), and supportive services and the indirect costs of absenteeism, lost household production, reduced labor force participation, and informal care by age group, sex, and state in aggregate and per person with VL. RESULTS: We estimated an economic burden of VL of $134.2 billion: $98.7 billion in direct costs and $35.5 billion in indirect costs. The largest burden components were NH ($41.8 billion), other medical care services ($30.9 billion), and reduced labor force participation ($16.2 billion), all of which accounted for 66% of the total. Those with VL incurred $16 838 per year in incremental burden. Informal care was the largest burden component for people 0 to 18 years of age, reduced labor force participation was the largest burden component for people 19 to 64 years of age, and NH costs were the largest burden component for people 65 years of age or older. New York, Connecticut, Massachusetts, Rhode Island, and Vermont experienced the highest costs per person with VL. Sensitivity analyses indicate total burden may range between $76 and $218 billion depending on the assumptions used in the model. CONCLUSIONS: Self-reported VL imposes a substantial economic burden on the United States. Burden accrues in different ways at different ages, leading to state differences in the composition of per-person costs based on the age composition of the population with VL. Information on state variation can help local decision makers target resources better to address the burden of VL.

Risk for Newly Diagnosed Diabetes >30 Days After SARS-CoV-2 Infection Among Persons Aged <18 Years - United States, March 1, 2020-June 28, 2021.

The COVID-19 pandemic has disproportionately affected people with diabetes, who are at increased risk of severe COVID-19.* Increases in the number of type 1 diabetes diagnoses (1,2) and increased frequency and severity of diabetic ketoacidosis (DKA) at the time of diabetes diagnosis (3) have been reported in European pediatric populations during the COVID-19 pandemic. In adults, diabetes might be a long-term consequence of SARS-CoV-2 infection (4-7). To evaluate the risk for any new diabetes diagnosis (type 1, type 2, or other diabetes) >30 days† after acute infection with SARS-CoV-2 (the virus that causes COVID-19), CDC estimated diabetes incidence among patients aged <18 years (patients) with diagnosed COVID-19 from retrospective cohorts constructed using IQVIA health care claims data from March 1, 2020, through February 26, 2021, and compared it with incidence among patients matched by age and sex 1) who did not receive a COVID-19 diagnosis during the pandemic, or 2) who received a prepandemic non-COVID-19 acute respiratory infection (ARI) diagnosis. Analyses were replicated using a second data source (HealthVerity; March 1, 2020-June 28, 2021) that included patients who had any health care encounter possibly related to COVID-19. Among these patients, diabetes incidence was significantly higher among those with COVID-19 than among those 1) without COVID-19 in both databases (IQVIA: hazard ratio [HR] = 2.66, 95% CI = 1.98-3.56; HealthVerity: HR = 1.31, 95% CI = 1.20-1.44) and 2) with non-COVID-19 ARI in the prepandemic period (IQVIA, HR = 2.16, 95% CI = 1.64-2.86). The observed increased risk for diabetes among persons aged <18 years who had COVID-19 highlights the importance of COVID-19 prevention strategies, including vaccination, for all eligible persons in this age group,§ in addition to chronic disease prevention and management. The mechanism of how SARS-CoV-2 might lead to incident diabetes is likely complex and could differ by type 1 and type 2 diabetes. Monitoring for long-term consequences, including signs of new diabetes, following SARS-CoV-2 infection is important in this age group.

Cardiovascular Disease Risk Factors in US Adults With Vision Impairment.

INTRODUCTION: Adults with vision impairment (VI) have a higher prevalence of cardiovascular disease (CVD) compared with those without VI. We estimated the prevalence of CVD and CVD risk factors by VI status in US adults. METHODS: We used nationally representative data from the 2018 National Health Interview Survey (N = 22,890 adults aged ≥18 years). We estimated the prevalence of self-reported diagnosis of CVD (coronary heart disease [including angina and myocardial infarction], stroke, or other heart disease) by VI status. We used separate logistic regression models to generate adjusted prevalence ratios (aPRs), controlling for sociodemographic covariates, for those with VI (reference group, no VI) for CVD and CVD risk factors: current smoking, physical inactivity, excessive alcohol intake, obesity, hypertension, high cholesterol, and diabetes. RESULTS: Overall, 12.9% (95% CI, 12.3-13.5) of the sample had VI. The prevalence of CVD was 26.6% (95% CI, 24.7-28.6) in people with VI versus 12.2% (95% CI, 11.7-12.8) in those without VI (aPR = 1.65 [95% CI, 1.51-1.80]). Compared with adults without VI, those with VI had a higher prevalence of all risk factors examined: current smoking (aPR = 1.40 [95% CI, 1.27-1.53]), physical inactivity (aPR = 1.14 [95% CI, 1.06-1.22]), excessive alcohol intake (aPR = 1.29 [95% CI, 1.08-1.53]), obesity (aPR = 1.28 [95% CI, 1.21-1.36]), hypertension (aPR = 1.29 [95% CI, 1.22-1.36]), high cholesterol (aPR = 1.21 [95% CI, 1.14-1.29]), and diabetes (aPR = 1.54 [95% CI, 1.38-1.72]). CONCLUSION: Adults with VI had a higher prevalence of CVD and CVD risk factors compared with those without VI. Effective clinical and lifestyle interventions, adapted to accommodate VI-related challenges, may help reduce CVD risk in adults with VI.

Health Care Access and Use Among Adults With and Without Vision Impairment: Behavioral Risk Factor Surveillance System, 2018.

INTRODUCTION: Adults with vision impairment may have unique needs when accessing health care to maintain good health. Our study examined the relationship between vision status and access to and use of health care. METHODS: We analyzed data on adults aged 18 years or older who participated in the 2018 Behavioral Risk Factor Surveillance System. Vision impairment was identified by a yes response to the question "Are you blind or do you have serious difficulty seeing, even when wearing glasses?" Survey questions assessed health care access over the past year (having health insurance coverage, a usual health care provider, or unmet health care needs because of cost) and use of health care during that period (routine checkup and dental visit). We estimated age-adjusted prevalence of our outcomes of interest and used bivariate analyses to compare estimates of the outcomes by vision impairment status. RESULTS: The prevalence of self-reported vision impairment was 5.3%. Compared with adults without impaired vision, adults with vision impairment had a lower prevalence of having health insurance coverage (80.6% vs 87.6%), a usual health care provider (71.9% vs 75.7%), or a dental visit in the past year (52.9% vs 67.2%) and a higher prevalence of having an unmet health care need in the past year because of cost (29.2% vs 12.6%). CONCLUSION: Adults with vision impairment reported lower access to and use of health care than those without. Further research can better identify and understand barriers to care to improve access to and use of health care among this population.

Vision Impairment and Blindness Prevalence in the United States: Variability of Vision Health Responses across Multiple National Surveys.

PURPOSE: To support survey validation efforts by comparing prevalence rates of self-reported and examination evaluated presenting visual impairment (VI) and blindness measured across national surveys. DESIGN: Cross-sectional comparison. PARTICIPANTS: Participants in the 2016 American Community Survey, the 2016 Behavioral Risk Factor Surveillance System, the 2016 National Health Interview Survey, the 2005-2008 National Health and Nutrition Examination Survey (NHANES), and the 2016 National Survey of Children's Health. METHODS: We estimated VI and blindness prevalence rates and confidence intervals for each survey measure and age group using the Clopper-Pearson method. We used inverse variance weighting to estimate the central tendency across measures by age-group, fitted trend lines to age-group estimates, and used the trend-line equations to estimate the number of United States persons with VI and blindness in 2016. We compared self-report estimates with those from NHANES physical evaluations of presenting VI and blindness. MAIN OUTCOME MEASURES: Variability of prevalence estimates of VI and blindness. RESULTS: Self-report estimates of blindness varied between 0.1% and 5.6% for those younger than 65 years and from 0.6% to 16.6% for those 65 or older. Estimates of VI varied between 1.6% and 24.8% for those younger than 65 years and between 2.2% and 26.6% for those 65 years or older. For summarized survey results and NHANES physical evaluation, prevalence rates for VI increased significantly with increasing age group. Blindness prevalence increased significantly with increasing age group for summarized survey responses but not for NHANES physical examination. Based on extrapolations of NHANES physical examination data to all ages, we estimated that in 2016, 23.4 million persons in the United States (7.2%) had VI or blindness, an evaluated presenting visual acuity of 20/40 or worse in the better-seeing eye before correction. Based on weighted self-reported surveys, we estimated that 24.8 million persons (7.7%) had presenting VI or blindness. CONCLUSIONS: Prevalence rates of VI and blindness obtained from national survey measures varied widely across surveys and age groups. Additional research is needed to validate the ability of survey self-report measures of VI and blindness to replicate results obtained through examination by an eye health professional.

Hospital Length of Stay, Charges, and Costs Associated With a Diagnosis of Obesity in US Children and Youth, 2006-2016.

BACKGROUND: Childhood obesity is linked with adverse health outcomes and associated costs. Current information on the relationship between childhood obesity and inpatient costs is limited. OBJECTIVE: The objective of this study was to describe trends and quantify the link between childhood obesity diagnosis and hospitalization length of stay (LOS), costs, and charges. RESEARCH DESIGN: We use the National Inpatient Sample data from 2006 to 2016. SUBJECTS: The sample includes hospitalizations among children aged 2-19 years. The treatment group of interest includes child hospitalizations with an obesity diagnosis. MEASURES: Hospital LOS, charges, and costs associated with a diagnosis of obesity. RESULTS: We find increases in obesity-coded hospitalizations and associated charges and costs during 2006-2016. Obesity as a primary diagnosis is associated with a shorter hospital LOS (by 1.8 d), but higher charges and costs (by $20,879 and $6049, respectively); obesity as a secondary diagnosis is associated with a longer LOS (by 0.8 d), and higher charges and costs of hospitalizations (by $3453 and $1359, respectively). The most common primary conditions occurring with a secondary diagnosis of obesity are pregnancy conditions, mood disorders, asthma, and diabetes; the effect of a secondary diagnosis of obesity on LOS, charges, and costs holds across these conditions. CONCLUSIONS: Childhood obesity diagnosis-related hospitalizations, charges, and costs increased substantially during 2006-2016, and obesity diagnosis is associated with higher hospitalization charges and costs. Our findings provide clinicians and policymakers with additional evidence of the economic burden of childhood obesity and further justify efforts to prevent and manage the disease.

Sugar-Sweetened Beverage Intake Among Pregnant and Non-pregnant Women of Reproductive Age.

OBJECTIVES: Frequent sugar-sweetened beverage (SSB) intake is associated with weight gain in women, and pre-pregnancy overweight and excessive gestational weight gain are linked to adverse pregnancy outcomes. SSB intake information for women of reproductive age (WRA) is limited. We described SSB intake among non-pregnant and pregnant WRA and identified correlates of daily intake. METHODS: Using 2017 Behavioral Risk Factor Surveillance System data, we analyzed SSB intake (regular soda, fruit drinks, sweet tea, sports/energy drinks) for 11,321 non-pregnant and 392 pregnant WRA (18-49 years) in 12 states and D.C. Adjusted odds ratios (aOR) for daily (≥ 1 time/day) SSB intake (reference: < 1 time/day) by characteristics were estimated using multivariable logistic regression. RESULTS: Overall, 27.3% of non-pregnant and 21.9% of pregnant women reported consuming SSBs ≥ 1 time/day; 12.6% and 9.7%, respectively, consumed SSBs ≥ 2 times/day. Among non-pregnant women, odds of daily SSB intake were higher for women who were non-Hispanic black (aOR 2.04, 95% CI 1.55-2.69) vs. non-Hispanic white; had ≤ high school education (aOR 2.79, CI 2.26-3.44) or some college (aOR 1.85, CI 1.50-2.27) vs. college graduates; lived in nonmetropolitan counties (aOR 1.35, CI 1.11-1.63) vs. metropolitan; had no physical activity (aOR 1.72, CI 1.43-2.07) vs. some; were former (aOR 1.51, CI 1.17-1.94) or current (aOR 3.48, CI 2.82-4.28) smokers vs. nonsmokers. Among pregnant women, those not married had higher odds (aOR 2.81, CI 1.05-7.51) for daily SSB intake than married women. CONCLUSIONS: One in five pregnant women and one in four non-pregnant women of reproductive age consumed SSBs at least once per day. Sociodemographic and behavioral correlates of daily SSB intake were identified.

Sugar-Sweetened Beverage Intake Among Adults, by Residence in Metropolitan and Nonmetropolitan Counties in 12 States and the District of Columbia, 2017.

The objective of this study was to describe the prevalence of sugar-sweetened beverage (SSB) intake among US adults (n = 68,896) residing in metropolitan and nonmetropolitan counties, by state, using data from the Behavioral Risk Factor Surveillance System. We used multinomial logistic regression to calculate adjusted prevalence ratios for daily (≥1 time per day) SSB intake. Overall, 26.0% of respondents reported daily SSB intake, with significantly higher prevalence in nonmetropolitan counties (30.9%) than in metropolitan counties (24.8%) (adjusted prevalence ratio = 1.32, 95% confidence interval, 1.26-1.39). This same pattern was significant in 5 of 11 states with metropolitan and nonmetropolitan counties. These findings could inform efforts to reduce frequent SSB intake in nonmetropolitan areas.

Disparities in Receipt of Eye Exams Among Medicare Part B Fee-for-Service Beneficiaries with Diabetes - United States, 2017.

Approximately 30 million persons in the United States have diabetes.* Persons with diabetes are at risk for vision loss from diabetic retinopathy and other eye diseases (1). Diabetic retinopathy, the most common diabetes-related eye disease, affects 29% of U.S. adults aged ≥40 years with diabetes (2) and is the leading cause of incident blindness among working-age adults (1). It is caused by chronically high blood glucose damaging blood vessels in the retina.† Annual dilated eye exams are recommended for persons with diabetes because early detection and timely treatment of diabetic eye diseases can prevent irreversible vision loss§,¶ (3,4). Studies have documented prevalence of annual eye exams among U.S. adults with diabetes (5,6); however, a lack of recent state-level data limits identification of geographic disparities in adherence to this recommendation. Medicare claims from the 50 states, the District of Columbia (DC), Puerto Rico, and U.S. Virgin Islands (USVI) were examined to assess the prevalence of eye exams in 2017 among beneficiaries with diabetes who were continuously enrolled in Part B fee-for-service insurance, which covers annual eye exams for beneficiaries with diabetes.** This report also examines disparities, by state and race/ethnicity, in receipt of eye exams. Nationally, 54.1% of beneficiaries with diabetes had an eye exam in 2017. Prevalence ranged from 43.9% in Puerto Rico to 64.8% in Rhode Island. Fewer than 50% of beneficiaries received an eye exam in seven states (Alabama, Alaska, Kentucky, Louisiana, Nevada, West Virginia, and Wyoming) and Puerto Rico. Non-Hispanic white (white) beneficiaries had a higher prevalence of receiving an eye exam (55.6%) than did non-Hispanic blacks (blacks) (48.9%) and Hispanics (48.2%). Barriers to receiving eye care (e.g., suboptimal clinical care coordination and referral, low health literacy, and lack of perceived need for care) might limit Medicare beneficiaries' ability to follow this preventive care recommendation. Understanding and addressing these barriers might prevent irreversible vision loss among persons with diabetes.

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.

Stunting at 24 Months Is Not Related to Incidence of Overweight through Young Adulthood in an Urban South African Birth Cohort.

Background: The role that childhood stunting plays in the development of overweight and obesity later in life is not well understood, particularly in adolescence and young adulthood, because most studies have only followed up through midchildhood. Objective: The objective of this study was to examine the relation between stunting and age-specific patterns of overweight and obesity incidence from early childhood to young adulthood in the context of a country in the process of the nutrition transition while these children were growing up. Methods: We analyzed data from 895 participants in the Birth-to-Twenty Plus Cohort (Bt20+), an urban South African birth cohort initiated in 1990. Anthropometric data were collected at multiple ages and participants were included if they provided height at age 24 mo and ≥1 measure of body mass index [BMI; weight (kg)/height (m)2] in each of the following time periods: 4-8 y, 11-12 y, 13-15 y, 16-18 y, and 22-24 y. We defined stunting at age 24 mo as height-for-age z score <2 and overweight as BMI z score (BMIZ) >1 in childhood (4-8 y) and adolescence (11-12 y, 13-15 y, and 16-18 y) and BMI ≥25 in young adulthood (22-24 y). We compared BMI, BMIZ, and the prevalence of overweight by stunting status, stratified by sex. Results: Our sample was 93% black and 51% female. The prevalence of stunting at 24 mo was 26% in males and 19% in females. In young adulthood, the prevalence of overweight and obesity was 15.5% (men) and 47.5% (women). Among both males and females, neither mean BMI nor a combined measure of overweight and obesity in any subsequent period differed by stunting status at 24 mo (P ≥ 0.05). Conclusion: Stunting at 24 mo was not related to the risk of overweight or obesity in this cohort. Stunting may not be an important contributor to the increasing obesity rates in urban South Africa.

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).

Daily Intake of Sugar-Sweetened Beverages Among US Adults in 9 States, by State and Sociodemographic and Behavioral Characteristics, 2016.

We examined associations between sugar-sweetened beverage (SSB) intake - a chronic disease risk factor - and characteristics of 75,029 adults (≥18 y) in 9 states by using 2016 Behavioral Risk Factor Surveillance System (BRFSS) data. We used multinomial logistic regression to estimate adjusted odds ratios for SSB intake categorized as none (reference), fewer than 1 time per day, and 1 or more times per day, by sociodemographic and behavioral characteristics. Overall, 32.1% of respondents drank SSBs 1 or more times per day. We found higher odds for 1 or more times per day among younger respondents, men, Hispanic and non-Hispanic black respondents, current smokers, respondents residing in nonmetropolitan counties, employed respondents, and those with less than high school education, obesity, and no physical activity. Our findings can inform the targeting of efforts to reduce SSB consumption.

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.

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.

Early Life Growth Predicts Pubertal Development in South African Adolescents.

BACKGROUND: Given global trends toward earlier onset of puberty and the adverse psychosocial consequences of early puberty, it is important to understand the childhood predictors of pubertal timing and tempo. OBJECTIVE: We examined the association between early growth and the timing and tempo of puberty in adolescents in South Africa. METHODS: We analyzed prospectively collected data from 1060 boys and 1135 girls participating in the Birth-to-Twenty cohort in Soweto, South Africa. Height-for-age z scores (HAZs) and body mass index-for-age z scores (BMIZs) were calculated based on height (centimeters) and body mass index (kilograms per meter squared) at ages 5 y and 8 y. The development of genitals, breasts, and pubic hair was recorded annually from 9 to 16 y of age with the use of the Tanner sexual maturation scale (SMS). We used latent class growth analysis to identify pubertal trajectory classes and also characterized children as fast or slow developers based on the SMS score at 12 y of age. We used multinomial logistic regression to estimate associations of HAZ and BMIZ at ages 5 and 8 y with pubertal development. RESULTS: We identified 3 classes for pubic hair development (for both girls and boys) and 4 classes for breast (for girls) and genital (for boys) development. In girls, both HAZ and BMIZ at age 5 y were positively associated with pubic hair development [relative risk ratio (RRR): 1.57, P < 0.001 and RRR: 1.51, P < 0.01, respectively], as was BMI at age 8 y (RRR: 2.06, P = 0.03); similar findings were observed for breast development. In boys, HAZ and BMIZ at age 5 y were positively associated with pubic hair development (RRR: 1.78, P < 0.001 and RRR: 1.43, P < 0.01, respectively); HAZ at age 5 y was associated with development of genitals (RRR: 2.19, P < 0.01). CONCLUSION: In boys and girls, both height and body mass index in early childhood predicted the trajectory of pubertal development. This may provide a tool to identify children at risk of early pubertal onset.

Pubertal Development and Prepubertal Height and Weight Jointly Predict Young Adult Height and Body Mass Index in a Prospective Study in South Africa.

BACKGROUND: Height and adiposity track over childhood, but few studies, to our knowledge, have longitudinally examined the mediating relation of the timing and progression of puberty. OBJECTIVE: We assessed interrelations between prepubertal height and body mass index, the progression through puberty, and young adult height and adiposity. METHODS: We analyzed data from the Birth to Twenty Plus study (females, n = 823; males, n = 765). Serial measures of anthropometry and pubertal development were obtained between ages 9 and 16 y. We used latent class growth analysis to categorize pubertal development with respect to pubic hair (females and males), breasts (females), and genitalia (males) development. Adult height and weight were obtained at ages 18 to 20 y. RESULTS: Among females, higher latent class (earlier initiation and faster progression through puberty) was associated with an increased risk of obesity [pubic hair class 3 compared with class 1: RR, 3.41 (95% CI: 1.57, 7.44)] and inconsistent associations with height. Among males, higher latent class was associated with increased adult height [pubic hair development class 3 compared with class 1: 2.43 cm (95% CI: 0.88, 4.00)] and increased risk of overweight/obesity [pubic hair development class 3 compared with class 1: OR, 3.44 (95% CI: 1.44, 8.20)]. In females, the association with adult height became inverse after adjusting for prepubertal height [pubic hair development class 3 compared with class 1: females, -1.31 cm (95% CI: -2.32, -0.31)]; in males, the association with height was attenuated with this adjustment [-0.56 cm (95% CI: -1.63, 0.52)]. Associations with adiposity were attenuated after adjusting for prepubertal adiposity. CONCLUSIONS: Progression through puberty modifies the relation between prepubertal and adult anthropometry. Screening for early or rapid progression of puberty might identify children at an increased risk of becoming overweight or obese adults.