Differences in Intakes of Select Nutrients by Urbanization Level in the United States Population 2 Years and Older, NHANES 2013-2018.

BACKGROUND: Differences in nutrient intakes by urbanization level in the Unites States is not well understood. OBJECTIVE: Describe, by urbanization level: 1) intake of protein, fiber, percent of energy from added sugars (AS) and saturated fat (SF), calcium, iron, potassium, sodium, and vitamin D; 2) the percent of the population meeting nutrient recommendations. METHODS: Twenty-four-hour dietary recalls from 23,107 participants aged 2 y and over from the 2013-2018 National Health and Nutrition Examination Surveys were analyzed. Usual intakes were estimated, and linear regression models adjusted for age, sex, race and Hispanic origin, and whether family income met the 130% threshold examined intake differences by urbanization levels-large urban areas (LUA), small to medium metro areas (SMMA), and rural areas (RA). RESULTS: A small percentage of the population met the nutrient recommendations, except for protein (92.8%) and iron (70.5%). A higher percentage of the population met recommendations than SMMA and RA for fiber (11.8% compared with 8.1% and 5.3%, P < 0.001), AS (40.2% compared with 33.4% and 31.3%, P < 0.001), SF (26.8% compared with 18.2% and 20.1%, P < 0.001), and potassium (31.5% compared with 25.5% and 22.0%, P < 0.001). Mean protein intake were also higher in LUA than RA (80.0 g compared with 77.7 g, P = 0.003) and fiber intake higher in LUA than SMMA (16.5 g compared with 15.9 g, P = 0.01) and RA (16.5 g compared with 15.2 g, P = 0.001). In addition, contributions to energy intake were lower in LUA than SMMA for AS (11.3% compared with 12.0%, P < 0.001) and SF (11.5% compared with 11.7%, P < 0.001), and for LUA than RA for AS (11.3% compared with 12.9%, P < 0.001) and SF (11.5% compared with 11.8%, P < 0.001). CONCLUSIONS: RA had some markers of poorer diet quality-lower protein and fiber intake and higher AS intake-compared with LUA, and these differences persisted in adjusted regression models. These results may inform public health efforts to address health disparities by urbanization levels in the Unites States.

Development of a sustainable diet index in US adults.

BACKGROUND: A transformation towards healthy diets through a sustainable food system is essential to enhance both human and planet health. Development of a valid, multidimensional, quantitative index of a sustainable diet would allow monitoring progress in the US population. We evaluated the content and construct validity of a sustainable diet index for US adults (SDI-US) based on data collected at the individual level. METHODS: The SDI-US, adapted from the SDI validated in the French population, was developed using data on US adults aged 20 years and older from the National Health and Nutrition Examination Survey, 2007-2018 (n = 25,543). The index consisted of 4 sub-indices, made up of 12 indicators, corresponding to 4 dimensions of sustainable diets (nutritional quality, environmental impacts, affordability (economic), and ready-made product use behaviors (sociocultural)). A higher SDI-US score indicates greater alignment with sustainable diets (range: 4-20). Validation analyses were performed, including the assessment of the relevance of each indicator, correlations between individual indicators, sub-indices, and total SDI-US, differences in scores between sociodemographic subgroups, and associations with selected food groups in dietary guidelines, the alternative Mediterranean diet (aMed) score, and the EAT-Lancet diet score. RESULTS: Total SDI-US mean was 13.1 (standard error 0.04). The correlation between SDI-US and sub-indices ranged from 0.39 for the environmental sub-index to 0.61 for the economic sub-index (Pearson Correlation coefficient). The correlation between a modified SDI-US after removing each sub-index and the SDI-US ranged from 0.83 to 0.93. aMed scores and EAT-Lancet diet scores were significantly higher among adults in the highest SDI-US quintile compared to the lowest quintile (aMed: 4.6 vs. 3.2; EAT-Lancet diet score: 9.9 vs. 8.7 p < .0001 for both). CONCLUSIONS: Overall, content and construct validity of the SDI-US were acceptable. The SDI-US reflected the key features of sustainable diets by integrating four sub-indices, comparable to the SDI-France. The SDI-US can be used to assess alignment with sustainable diets in the US. Continued monitoring of US adults' diets using the SDI-US could help improve dietary sustainability.

Trends in Food Consumption Among Children Aged 1-4 Years by Participation in the Special Supplemental Nutrition Program for Women, Infants, and Children, United States, 2005-2018.

BACKGROUND: In 2009, the US Department of Agriculture Food and Nutrition Service's Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) food packages were revised to include more whole fruits, vegetables, whole grains, and lower-fat milk. OBJECTIVE: The aim of this study was to describe trends over time in the consumption of fruits (total and whole), vegetables, whole grains, milk (whole, reduced fat, low-fat or nonfat (LFNF), and flavored), and added sugars, including breakfast cereals, by WIC participation status (current WIC recipient, WIC income-eligible nonrecipient, and WIC income-ineligible nonrecipient). METHODS: Dietary intakes on a given day for 1- to 4-y-old children (n = 5568) from the 2005-2018 National Health and Nutrition Examination Survey (NHANES) were analyzed to examine trends in the percentage of individuals consuming and amounts consumed over time using linear regression adjusted for age, sex, and race and Hispanic origin. RESULTS: From 2005 through 2018, the percentage of WIC recipients or WIC income-eligible nonrecipients consuming fruits and vegetables on a given day did not change, but the percentage of fruit consumed as whole fruit increased significantly among WIC recipients (36.4%-62.1%), but not among income-eligible nonrecipients. Among the WIC recipients, the percentage of consumption (5.5%-29.3%), the amount of LFNF milk servings consumed (0.1-0.4 cups), and the percentage of the total milk consumed as LFNF milk (4.8%-27%) significantly increased from 2005 to 2018. Conversely, the percentage of energy (12.3%-10.8%) and servings (11.4-10.6 teaspoons) from added sugars declined significantly. Among WIC-eligible nonrecipients, the servings of whole grains increased significantly, whereas servings and percentage of energy from added sugars declined significantly. CONCLUSIONS: From 2005 through 2018, changes in dietary patterns for WIC recipients did not always mirror those of US children of the same age. The percentage of fruit consumed as whole fruit, and the percentage and quantity of milk consumed as LFNF milk increased significantly among WIC recipients, but not among income-eligible nonrecipients. J Nutr 20XX;xx:xx-xx.

Federal Housing Assistance and Chronic Disease Among US Adults, 2005-2018.

Introduction: Housing insecurity is associated with poor health outcomes. Characterization of chronic disease outcomes among adults with and without housing assistance would enable housing programs to better understand their population's health care needs. Methods: We used National Health and Nutrition Examination Survey (NHANES) data from 2005 through 2018 linked to US Department of Housing and Urban Development (HUD) administrative records to estimate the prevalence of obesity, diabetes, and hypertension and to assess the independent associations between housing assistance and chronic conditions among adults receiving HUD assistance and HUD-assistance-eligible adults not receiving HUD assistance at the time of their NHANES examination. We estimated propensity scores to adjust for potential confounders among linkage-eligible adults who had an income-to-poverty ratio less than 2 and were not receiving HUD assistance. Sensitivity analysis used 2013-2018 NHANES cycles to account for disability status. Results: Adults not receiving HUD assistance had a significantly lower adjusted prevalence of obesity (42.1%; 95% CI, 40.4%-43.8%) compared with adults receiving HUD assistance (47.5%; 95% CI, 44.8%-50.3%), but we found no differences for diabetes and hypertension. We found significant associations between housing assistance and obesity (adjusted odds ratio = 1.29; 95% CI, 1.12-1.47), but these were not significant in the sensitivity analysis with and without controlling for disability status. We found no significant associations between housing assistance and diabetes or hypertension. Conclusion: Based on data from a cross-sectional survey, we observed a higher prevalence of obesity among adults with HUD assistance compared with HUD-assistance-eligible adults without HUD assistance. Results from this study can help inform research on understanding the prevalence of chronic disease among adults with HUD assistance.

The association of nativity/length of residence and cardiovascular disease risk factors in the United States.

Differences by nativity status for cardiovascular disease (CVD) risk factors have been previously reported. Recent research has focused on understanding how other acculturation factors, such as length of residence, affect health behaviors and outcomes. This study examines the association between CVD risk factors and nativity/length of US residence. Using cross-sectional data from 15,965 adults in the 2011-2016 National Health and Nutrition Examination Surveys (analyzed in 2018), prevalence ratios and predicted marginals from logistic regression models are used to estimate associations of CVD risk factors (i.e., hypertension, hypercholesterolemia, diabetes, overweight/obesity and smoking) with nativity/length of residence (<15 years, ≥15 years) in the US. In sex-, age-, education- and race and Hispanic origin- adjusted analyses, a higher percentage of US (50 states and District of Columbia) born adults (86.4%) had ≥1 CVD risk factor compared to non-US born residents in the US <15 years (80.1%) but not ≥15 years (85.1%). Compared to US born counterparts, regardless of length of residence, hypertension overall and smoking among non-Hispanic white and Hispanic adults were lower among non-US born residents. Overweight/obesity overall and diabetes among Hispanic adults were lower among non-US born residents in the US <15 years. In contrast, non-US born non-Hispanic Asian residents in the US <15 years had higher prevalence of diabetes. Non-US born adults were less likely to have most CVD risk factors compared to US born adults regardless of length of residence, although, for smoking and diabetes this pattern differed by race and Hispanic origin.

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

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

A method for calculating BMI z-scores and percentiles above the 95th percentile of the CDC growth charts.

BACKGROUND: The 2000 CDC growth charts are based on national data collected between 1963 and 1994 and include a set of selected percentiles between the 3rd and 97th and LMS parameters that can be used to obtain other percentiles and associated z-scores. Obesity is defined as a sex- and age-specific body mass index (BMI) at or above the 95th percentile. Extrapolating beyond the 97th percentile is not recommended and leads to compressed z-score values. AIM: This study attempts to overcome this limitation by constructing a new method for calculating BMI distributions above the 95th percentile using an extended reference population. SUBJECTS AND METHODS: Data from youth at or above the 95th percentile of BMI-for-age in national surveys between 1963 and 2016 were modelled as half-normal distributions. Scale parameters for these distributions were estimated at each sex-specific 6-month age-interval, from 24 to 239 months, and then smoothed as a function of age using regression procedures. RESULTS: The modelled distributions above the 95th percentile can be used to calculate percentiles and non-compressed z-scores for extreme BMI values among youth. CONCLUSION: This method can be used, in conjunction with the current CDC BMI-for-age growth charts, to track extreme values of BMI among youth.

Prevalence of Obesity Among Youths by Household Income and Education Level of Head of Household - United States 2011-2014.

Obesity prevalence varies by income and education level, although patterns might differ among adults and youths (1-3). Previous analyses of national data showed that the prevalence of childhood obesity by income and education of household head varied across race/Hispanic origin groups (4). CDC analyzed 2011-2014 data from the National Health and Nutrition Examination Survey (NHANES) to obtain estimates of childhood obesity prevalence by household income (≤130%, >130% to ≤350%, and >350% of the federal poverty level [FPL]) and head of household education level (high school graduate or less, some college, and college graduate). During 2011-2014 the prevalence of obesity among U.S. youths (persons aged 2-19 years) was 17.0%, and was lower in the highest income group (10.9%) than in the other groups (19.9% and 18.9%) and also lower in the highest education group (9.6%) than in the other groups (18.3% and 21.6%). Continued progress is needed to reduce disparities, a goal of Healthy People 2020. The overall Healthy People 2020 target for childhood obesity prevalence is <14.5% (5).

Disparities in plain, tap and bottled water consumption among US adults: National Health and Nutrition Examination Survey (NHANES) 2007-2014.

OBJECTIVE: Differences in bottled v. tap water intake may provide insights into health disparities, like risk of dental caries and inadequate hydration. We examined differences in plain, tap and bottled water consumption among US adults by sociodemographic characteristics. DESIGN: Cross-sectional analysis. We used 24 h dietary recall data to test differences in percentage consuming the water sources and mean intake between groups using Wald tests and multiple logistic and linear regression models. SETTING: National Health and Nutrition Examination Survey (NHANES), 2007-2014. SUBJECTS: A nationally representative sample of 20 676 adults aged ≥20 years. RESULTS: In 2011-2014, 81·4 (se 0·6) % of adults drank plain water (sum of tap and bottled), 55·2 (se 1·4) % drank tap water and 33·4 (se 1·4) % drank bottled water on a given day. Adjusting for covariates, non-Hispanic (NH) Black and Hispanic adults had 0·44 (95 % CI 0·37, 0·53) and 0·55 (95 % CI 0·45, 0·66) times the odds of consuming tap water, and consumed B=-330 (se 45) ml and B=-180 (se 45) ml less tap water than NH White adults, respectively. NH Black, Hispanic and adults born outside the fifty US states or Washington, DC had 2·20 (95 % CI 1·79, 2·69), 2·37 (95 % CI 1·91, 2·94) and 1·46 (95 % CI 1·19, 1·79) times the odds of consuming bottled water than their NH White and US-born counterparts. In 2007-2010, water filtration was associated with higher odds of drinking plain and tap water. CONCLUSIONS: While most US adults consumed plain water, the source (i.e. tap or bottled) and amount differed by race/Hispanic origin, nativity status and education. Water filters may increase tap water consumption.

Trends in Prescription Medication Use Among Children and Adolescents-United States, 1999-2014.

Importance: Access to appropriate prescription medications, use of inappropriate or ineffective treatments, and adverse drug events are public health concerns among US children and adolescents. Objective: To evaluate trends in use of prescription medications among US children and adolescents. Design, Setting, and Participants: US children and adolescents aged 0 to 19 years in the 1999-2014 National Health and Nutrition Examination Survey (NHANES)-serial cross-sectional, nationally representative surveys of the civilian noninstitutionalized population. Exposures: Sex, age, race and Hispanic origin, household income and education, insurance status, current health status. Main Outcomes and Measures: Use of any prescription medications or 2 or more prescription medications taken in the past 30 days; use of medications by therapeutic class; trends in medication use across 4-year periods from 1999-2002 to 2011-2014. Data were collected though in-home interview and direct observation of the prescription container. Results: Data on prescription medication use were available for 38 277 children and adolescents (mean age, 10 years; 49% girls). Overall, use of any prescription medication in the past 30 days decreased from 24.6% (95% CI, 22.6% to 26.6%) in 1999-2002 to 21.9% (95% CI, 20.3% to 23.6%) in 2011-2014 (ß = -0.41 percentage points every 2 years [95% CI, -0.79 to -0.03]; P = .04), but there was no linear trend in the use of 2 or more prescription medications (8.5% [95% CI, 7.6% to 9.4%] in 2011-2014). In 2011-2014, the most commonly used medication classes were asthma medications (6.1% [95% CI, 5.4% to 6.8%]), antibiotics (4.5% [95% CI, 3.7% to 5.5%]), attention-deficit/hyperactivity disorder (ADHD) medications (3.5% [95% CI, 2.9% to 4.2%]), topical agents (eg, dermatologic agents, nasal steroids) (3.5% [95% CI, 3.0% to 4.1%]), and antihistamines (2.0% [95% CI, 1.7% to 2.5%]). There were significant linear trends in 14 of 39 therapeutic classes or subclasses, or in individual medications, with 8 showing increases, including asthma and ADHD medications and contraceptives, and 6 showing decreases, including antibiotics, antihistamines, and upper respiratory combination medications. Conclusions and Relevance: In this study of US children and adolescents based on a nationally representative survey, estimates of prescription medication use showed an overall decrease in use of any medication from 1999-2014. The prevalence of asthma medication, ADHD medication, and contraceptive use increased among certain age groups, whereas use of antibiotics, antihistamines, and upper respiratory combination medications decreased.

Differences in Obesity Prevalence by Demographics and Urbanization in US Children and Adolescents, 2013-2016.

Importance: Differences in childhood obesity by demographics and urbanization have been reported. Objective: To present data on obesity and severe obesity among US youth by demographics and urbanization and to investigate trends by urbanization. Design, Setting, and Participants: Measured weight and height among youth aged 2 to 19 years in the 2001-2016 National Health and Nutrition Examination Surveys, which are serial, cross-sectional, nationally representative surveys of the civilian, noninstitutionalized population. Exposures: Sex, age, race and Hispanic origin, education of household head, and urbanization, as assessed by metropolitan statistical areas (MSAs; large: ≥ 1 million population). Main Outcomes and Measures: Prevalence of obesity (body mass index [BMI] ≥95th percentile of US Centers for Disease Control and Prevention [CDC] growth charts) and severe obesity (BMI ≥120% of 95th percentile) by subgroups in 2013-2016 and trends by urbanization between 2001-2004 and 2013-2016. Results: Complete data on weight, height, and urbanization were available for 6863 children and adolescents (mean age, 11 years; female, 49%). In 2013-2016, the prevalence among youth aged 2 to 19 years was 17.8% (95% CI, 16.1%-19.6%) for obesity and 5.8% (95% CI, 4.8%-6.9%) for severe obesity. Prevalence of obesity in large MSAs (17.1% [95% CI, 14.9%-19.5%]), medium or small MSAs (17.2% [95% CI, 14.5%-20.2%]) and non-MSAs (21.7% [95% CI, 16.1%-28.1%]) were not significantly different from each other (range of pairwise comparisons P = .09-.96). Severe obesity was significantly higher in non-MSAs (9.4% [95% CI, 5.7%-14.4%]) compared with large MSAs (5.1% [95% CI, 4.1%-6.2%]; P = .02). In adjusted analyses, obesity and severe obesity significantly increased with greater age and lower education of household head, and severe obesity increased with lower level of urbanization. Compared with non-Hispanic white youth, obesity and severe obesity prevalence were significantly higher among non-Hispanic black and Hispanic youth. Severe obesity, but not obesity, was significantly lower among non-Hispanic Asian youth than among non-Hispanic white youth. There were no significant linear or quadratic trends in obesity or severe obesity prevalence from 2001-2004 to 2013-2016 for any urbanization category (P range = .07-.83). Conclusions and Relevance: In 2013-2016, there were differences in the prevalence of obesity and severe obesity by age, race and Hispanic origin, and household education, and severe obesity was inversely associated with urbanization. Demographics were not related to the urbanization findings.

Differences in Obesity Prevalence by Demographic Characteristics and Urbanization Level Among Adults in the United States, 2013-2016.

Importance: Differences in obesity by sex, age group, race and Hispanic origin among US adults have been reported, but differences by urbanization level have been less studied. Objectives: To provide estimates of obesity by demographic characteristics and urbanization level and to examine trends in obesity prevalence by urbanization level. Design, Setting, and Participants: Serial cross-sectional analysis of measured height and weight among adults aged 20 years or older in the 2001-2016 National Health and Nutrition Examination Survey, a nationally representative survey of the civilian, noninstitutionalized US population. Exposures: Sex, age group, race and Hispanic origin, education level, smoking status, and urbanization level as assessed by metropolitan statistical areas (MSAs; large: ≥1 million population). Main Outcomes and Measures: Prevalence of obesity (body mass index [BMI] ≥30) and severe obesity (BMI ≥40) by subgroups in 2013-2016 and trends by urbanization level between 2001-2004 and 2013-2016. Results: Complete data on weight, height, and urbanization level were available for 10 792 adults (mean age, 48 years; 51% female [weighted]). During 2013-2016, 38.9% (95% CI, 37.0% to 40.7%) of US adults had obesity and 7.6% (95% CI, 6.8% to 8.6%) had severe obesity. Men living in medium or small MSAs had a higher age-adjusted prevalence of obesity compared with men living in large MSAs (42.4% vs 31.8%, respectively; adjusted difference, 9.8 percentage points [95% CI, 5.1 to 14.5 percentage points]); however, the age-adjusted prevalence among men living in non-MSAs was not significantly different compared with men living in large MSAs (38.9% vs 31.8%, respectively; adjusted difference, 4.8 percentage points [95% CI, -2.9 to 12.6 percentage points]). The age-adjusted prevalence of obesity was higher among women living in medium or small MSAs compared with women living in large MSAs (42.5% vs 38.1%, respectively; adjusted difference, 4.3 percentage points [95% CI, 0.2 to 8.5 percentage points]) and among women living in non-MSAs compared with women living in large MSAs (47.2% vs 38.1%, respectively; adjusted difference, 4.7 percentage points [95% CI, 0.2 to 9.3 percentage points]). Similar patterns were seen for severe obesity except that the difference between men living in large MSAs compared with non-MSAs was significant. The age-adjusted prevalence of obesity and severe obesity also varied significantly by age group, race and Hispanic origin, and education level, and these patterns of variation were often different by sex. Between 2001-2004 and 2013-2016, the age-adjusted prevalence of obesity and severe obesity significantly increased among all adults at all urbanization levels. Conclusions and Relevance: In this nationally representative survey of adults in the United States, the age-adjusted prevalence of obesity and severe obesity in 2013-2016 varied by level of urbanization, with significantly greater prevalence of obesity and severe obesity among adults living in nonmetropolitan statistical areas compared with adults living in large metropolitan statistical areas.

The Limitations of Transforming Very High Body Mass Indexes into z-Scores among 8.7 Million 2- to 4-Year-Old Children.

OBJECTIVE: To examine the associations among several body mass index (BMI) metrics (z-scores, percent of the 95th percentile (%BMIp95) and BMI minus 95th percentile (ΔBMIp95) as calculated in the growth charts from the Centers for Disease Control and Prevention (CDC). It is known that the widely used BMI z-scores (BMIz) and percentiles calculated from the growth charts can differ substantially from those that directly observed in the data for BMIs above the 97th percentile (z = 1.88). STUDY DESIGN: Cross-sectional analyses of 8.7 million 2- to 4-year-old children who were examined from 2008 through 2011 in the CDC's Pediatric Nutrition Surveillance System. RESULTS: Because of the transformation used to calculate z-scores, the theoretical maximum BMIz varied by >3-fold across ages. This results in the conversion of very high BMIs into a narrow range of z-scores that varied by sex and age. Among children with severe obesity, levels of BMIz were only moderately correlated (r ~ 0.5) with %BMIp95 and ΔBMIp95. Among these children with severe obesity, BMIz levels could differ by more than 1 SD among children who had very similar levels of BMI, %BMIp95 and ΔBMIp95 due to differences in age or sex. CONCLUSIONS: The effective upper limit of BMIz values calculated from the CDC growth charts, which varies by sex and age, strongly influences the calculation of z-scores for children with severe obesity. Expressing these very high BMIs relative to the CDC 95th percentile, either as a difference or percentage, would be preferable to using BMI-for-age, particularly when assessing the effectiveness of interventions.

Hypertension Prevalence, Awareness, Treatment, and Control Among Adults Aged ≥18 Years - Los Angeles County, 1999-2006 and 2007-2014.

Hypertension is an important and common risk factor for heart disease and stroke, two of the leading causes of death in adults in the United States. Despite considerable improvement in increasing the awareness, treatment, and control of hypertension, undiagnosed and uncontrolled hypertension remain public health challenges (1). Data from the National Health and Nutrition Examination Survey (NHANES) were used to estimate the prevalence of hypertension, as well as awareness, treatment, and control of hypertension among adults aged ≥18 years in Los Angeles County compared with adults aged ≥18 years in the United States during 1999-2006 and 2007-2014. During 2007-2014, the prevalence of hypertension was 23.1% among adults in Los Angeles County, lower than the prevalence of 29.6% among all U.S. adults. Among adults with hypertension in Los Angeles County, substantial improvements from 1999-2006 to 2007-2014 were found in hypertension awareness (increase from 73.8% to 84.6%), treatment (61.3% to 77.2%), and control (28.5% to 48.3%). Similar improvements were also seen among all U.S. adults. Although the prevalence of hypertension among adults in Los Angeles County meets the Healthy People 2020 (https://www.healthypeople.gov/) goal of ≤26.9%, continued progress is needed to meet the Healthy People 2020 goal of ≥61.2% for control of hypertension.

Prevalence of Obesity Among Adults, by Household Income and Education - United States, 2011-2014.

Studies have suggested that obesity prevalence varies by income and educational level, although patterns might differ between high-income and low-income countries (1-3). Previous analyses of U.S. data have shown that the prevalence of obesity varied by income and education, but results were not consistent by sex and race/Hispanic origin (4). Using data from the National Health and Nutrition Examination Survey (NHANES), CDC analyzed obesity prevalence among adults (aged ≥20 years) by three levels of household income, based on percentage (≤130%, >130% to ≤350%, and >350%) of the federal poverty level (FPL) and individual education level (high school graduate or less, some college, and college graduate). During 2011-2014, the age-adjusted prevalence of obesity among adults was lower in the highest income group (31.2%) than the other groups (40.8% [>130% to ≤350%] and 39.0% [≤130%]). The age-adjusted prevalence of obesity among college graduates was lower (27.8%) than among those with some college (40.6%) and those who were high school graduates or less (40.0%). The patterns were not consistent across all sex and racial/Hispanic origin subgroups. Continued progress is needed to achieve the Healthy People 2020 targets of reducing age-adjusted obesity prevalence to <30.5% and reducing disparities (5).

Trends in Obesity Among Adults in the United States, 2005 to 2014.

IMPORTANCE: Between 1980 and 2000, the prevalence of obesity increased significantly among adult men and women in the United States; further significant increases were observed through 2003-2004 for men but not women. Subsequent comparisons of data from 2003-2004 with data through 2011-2012 showed no significant increases for men or women. OBJECTIVE: To examine obesity prevalence for 2013-2014 and trends over the decade from 2005 through 2014 adjusting for sex, age, race/Hispanic origin, smoking status, and education. DESIGN, SETTING, AND PARTICIPANTS: Analysis of data obtained from the National Health and Nutrition Examination Survey (NHANES), a cross-sectional, nationally representative health examination survey of the US civilian noninstitutionalized population that includes measured weight and height. EXPOSURES: Survey period. MAIN OUTCOMES AND MEASURES: Prevalence of obesity (body mass index ≥30) and class 3 obesity (body mass index ≥40). RESULTS: This report is based on data from 2638 adult men (mean age, 46.8 years) and 2817 women (mean age, 48.4 years) from the most recent 2 years (2013-2014) of NHANES and data from 21,013 participants in previous NHANES surveys from 2005 through 2012. For the years 2013-2014, the overall age-adjusted prevalence of obesity was 37.7% (95% CI, 35.8%-39.7%); among men, it was 35.0% (95% CI, 32.8%-37.3%); and among women, it was 40.4% (95% CI, 37.6%-43.3%). The corresponding prevalence of class 3 obesity overall was 7.7% (95% CI, 6.2%-9.3%); among men, it was 5.5% (95% CI, 4.0%-7.2%); and among women, it was 9.9% (95% CI, 7.5%-12.3%). Analyses of changes over the decade from 2005 through 2014, adjusted for age, race/Hispanic origin, smoking status, and education, showed significant increasing linear trends among women for overall obesity (P = .004) and for class 3 obesity (P = .01) but not among men (P = .30 for overall obesity; P = .14 for class 3 obesity). CONCLUSIONS AND RELEVANCE: In this nationally representative survey of adults in the United States, the age-adjusted prevalence of obesity in 2013-2014 was 35.0% among men and 40.4% among women. The corresponding values for class 3 obesity were 5.5% for men and 9.9% for women. For women, the prevalence of overall obesity and of class 3 obesity showed significant linear trends for increase between 2005 and 2014; there were no significant trends for men. Other studies are needed to determine the reasons for these trends.

Trends in Obesity Prevalence Among Children and Adolescents in the United States, 1988-1994 Through 2013-2014.

IMPORTANCE: Previous analyses of obesity trends among children and adolescents showed an increase between 1988-1994 and 1999-2000, but no change between 2003-2004 and 2011-2012, except for a significant decline among children aged 2 to 5 years. OBJECTIVES: To provide estimates of obesity and extreme obesity prevalence for children and adolescents for 2011-2014 and investigate trends by age between 1988-1994 and 2013-2014. DESIGN, SETTING, AND PARTICIPANTS: Children and adolescents aged 2 to 19 years with measured weight and height in the 1988-1994 through 2013-2014 National Health and Nutrition Examination Surveys. EXPOSURES: Survey period. MAIN OUTCOMES AND MEASURES: Obesity was defined as a body mass index (BMI) at or above the sex-specific 95th percentile on the US Centers for Disease Control and Prevention (CDC) BMI-for-age growth charts. Extreme obesity was defined as a BMI at or above 120% of the sex-specific 95th percentile on the CDC BMI-for-age growth charts. Detailed estimates are presented for 2011-2014. The analyses of linear and quadratic trends in prevalence were conducted using 9 survey periods. Trend analyses between 2005-2006 and 2013-2014 also were conducted. RESULTS: Measurements from 40,780 children and adolescents (mean age, 11.0 years; 48.8% female) between 1988-1994 and 2013-2014 were analyzed. Among children and adolescents aged 2 to 19 years, the prevalence of obesity in 2011-2014 was 17.0% (95% CI, 15.5%-18.6%) and extreme obesity was 5.8% (95% CI, 4.9%-6.8%). Among children aged 2 to 5 years, obesity increased from 7.2% (95% CI, 5.8%-8.8%) in 1988-1994 to 13.9% (95% CI, 10.7%-17.7%) (P < .001) in 2003-2004 and then decreased to 9.4% (95% CI, 6.8%-12.6%) (P = .03) in 2013-2014. Among children aged 6 to 11 years, obesity increased from 11.3% (95% CI, 9.4%-13.4%) in 1988-1994 to 19.6% (95% CI, 17.1%-22.4%) (P < .001) in 2007-2008, and then did not change (2013-2014: 17.4% [95% CI, 13.8%-21.4%]; P = .44). Obesity increased among adolescents aged 12 to 19 years between 1988-1994 (10.5% [95% CI, 8.8%-12.5%]) and 2013-2014 (20.6% [95% CI, 16.2%-25.6%]; P < .001) as did extreme obesity among children aged 6 to 11 years (3.6% [95% CI, 2.5%-5.0%] in 1988-1994 to 4.3% [95% CI, 3.0%-6.1%] in 2013-2014; P = .02) and adolescents aged 12 to 19 years (2.6% [95% CI, 1.7%-3.9%] in 1988-1994 to 9.1% [95% CI, 7.0%-11.5%] in 2013-2014; P < .001). No significant trends were observed between 2005-2006 and 2013-2014 (P value range, .09-.87). CONCLUSIONS AND RELEVANCE: In this nationally representative study of US children and adolescents aged 2 to 19 years, the prevalence of obesity in 2011-2014 was 17.0% and extreme obesity was 5.8%. Between 1988-1994 and 2013-2014, the prevalence of obesity increased until 2003-2004 and then decreased in children aged 2 to 5 years, increased until 2007-2008 and then leveled off in children aged 6 to 11 years, and increased among adolescents aged 12 to 19 years.

Comparing Methods for Identifying Biologically Implausible Values in Height, Weight, and Body Mass Index Among Youth.

As more epidemiologic data on childhood obesity become available, researchers are faced with decisions regarding how to determine biologically implausible values (BIVs) in height, weight, and body mass index. The purpose of the current study was 1) to track how often large, epidemiologic studies address BIVs, 2) to review BIV identification methods, and 3) to apply those methods to a large data set of youth to determine the effects on obesity and BIV prevalence estimates. Studies with large samples of anthropometric data (n > 1,000) were reviewed to track whether and how BIVs were defined. Identified methods were then applied to a longitudinal sample of 13,662 students (65% African American, 52% male) in 55 urban, low-income schools that enroll students from kindergarten through eighth grade (ages 5-13 years) in Philadelphia, Pennsylvania, during 2011-2012. Using measured weight and height at baseline and 1-year follow-up, we compared descriptive statistics, weight status prevalence, and BIV prevalence estimates. Eleven different BIV methods were identified. When these methods were applied to a large data set, severe obesity and BIV prevalence ranged from 7.2% to 8.6% and from 0.04% to 1.68%, respectively. Approximately 41% of large epidemiologic studies did not address BIV identification, and existing identification methods varied considerably. Increased standardization of the identification and treatment of BIVs may aid in the comparability of study results and accurate monitoring of obesity trends.

More than half of US youth consume seafood and most have blood mercury concentrations below the EPA reference level, 2009-2012.

BACKGROUND: Consuming seafood has health benefits, but seafood can also contain methylmercury, a neurotoxicant. Exposure to methylmercury affects children at different stages of brain development, including during adolescence. OBJECTIVE: The objective was to examine seafood consumption and blood mercury concentrations in US youth. METHODS: In the 2009-2012 NHANES, a cross-sectional nationally representative sample of the US population, seafood consumption in the past 30 d and blood mercury concentrations on the day of examination were collected from 5656 youth aged 1-19 y. Log-linear regression was used to examine the association between frequency of specific seafood consumption and blood mercury concentration, adjusting for race/Hispanic origin, sex, and age. RESULTS: In 2009-2012, 62.4% ± 1.4% (percent ± SE) of youth consumed any seafood in the preceding month; 38.4% ± 1.4% and 48.5% ± 1.5% reported consuming shellfish and fish, respectively. In 2009-2012, the geometric mean blood mercury concentration was 0.50 ± 0.02 µg/L among seafood consumers and 0.27 ± 0.01 µg/L among those who did not consume seafood. Less than 0.5% of youth had blood mercury concentrations ≥5.8 µg/L. In adjusted log-linear regression analysis, no significant associations were observed between frequency of breaded fish or catfish consumption and blood mercury concentrations, but frequency of consuming certain seafood types had significant positive association with blood mercury concentrations: high-mercury fish (swordfish and shark) [exponentiated ß coefficient (expß): 2.40; 95% CI: 1.23, 4.68]; salmon (expß: 1.41; 95% CI: 1.26, 1.55); tuna (expß: 1.38; 95% CI: 1.29, 1.45); crabs (expß: 1.35; 95% CI: 1.17, 1.55); shrimp (expß: 1.12; 95% CI: 1.05, 1.20), and all other seafood (expß: 1.23; 95% CI: 1.17, 1.32). Age-stratified log-linear regression analyses produced similar results. CONCLUSION: Few US youth have blood mercury concentrations ≥5.8 µg/L, although more than half of US youth consumed seafood in the past month.

Interrelationships between BMI, skinfold thicknesses, percent body fat, and cardiovascular disease risk factors among U.S. children and adolescents.

BACKGROUND: Although the estimation of body fatness by Slaughter skinfold thickness equations (PBF(Slaughter)) has been widely used, the accuracy of this method is uncertain. We have previously examined the interrelationships among the body mass index (BMI), PBF(Slaughter), percent body fat from dual energy X-ray absorptiometry (PBF(DXA)) and CVD risk factor levels among children who were examined in the Bogalusa Heart Study and in the Pediatric Rosetta Body Composition Project. The current analyses examine these associations among 7599 8- to 19-year-olds who participated in the (U.S.) National Health and Nutrition Examination Survey from 1999 to 2004. METHODS: We analyzed (1) the agreement between (1) estimates of percent body fat calculated from the Slaughter skinfold thickness equations and from DXA, and (2) the relation of lipid, lipoprotein, and blood pressure levels to BMI, PBF(Slaughter) and PBF(DXA). RESULTS: PBF(Slaughter) was highly correlated (r ~ 0.85) with PBF(DXA). However, among children with a relatively low skinfold thicknesses sum (triceps + subscapular), PBF(Slaughter) underestimated PBF(DXA) by 8 to 9 percentage points. In contrast, PBF(Slaughter) overestimated PBF(DXA) by 10 points among boys with a skinfold thickness sum ≥ 50 mm. After adjustment for sex and age, lipid levels were related similarly to the body mass index, PBF(DXA) and PBF(Slaughter). There were, however, small differences in associations with blood pressure levels: systolic blood pressure was more strongly associated with body mass index, but diastolic blood pressure was more strongly associated with percent body fat. CONCLUSIONS: The Slaughter equations yield biased estimates of body fatness. In general, lipid and blood pressure levels are related similarly to levels of BMI (following adjustment for sex and age), PBF(Slaughter,) and PBF(DXA).