OBJECTIVE—We sought to examine the distribution of insulin and homeostasis model assessment of insulin resistance (HOMA-IR) and associations of HOMA-IR with sex, race/ethnicity, age, and weight status, as measured by BMI, among U.S. adolescents. RESEARCH DESIGN AND METHODS—Of 4,902 adolescents aged 12–19 years who participated in the National Health and Nutrition Examination Survey 1999–2002, analysis was performed for a nationally representative subsample of 1,802 adolescents without diabetes who had fasting laboratory measurements. The main outcome measure was HOMA-IR, calculated from fasting insulin and glucose and log transformed for multiple linear regression analyses. RESULTS—In adjusted regression models that included age and weight status, girls had higher HOMA-IR than boys and Mexican-American children had higher HOMA-IR levels than white children. There were no significant differences in adjusted HOMA-IR between black and white children. Obese children (BMI ≥95th percentile) had significantly higher levels of HOMA-IR compared with children of normal weight (BMI <85th percentile) in adjusted comparisons (mean HOMA-IR 4.93 [95% CI 4.56–5.35] vs. 2.30 [2.21–2.39], respectively). Weight status was by far the most important determinant of insulin resistance, accounting for 29.1% of the variance in HOMA-IR. The prevalence of insulin resistance in obese adolescents was 52.1% (95% CI 44.5–59.8). CONCLUSIONS—Obesity in U.S. adolescents represents the most important risk factor for insulin resistance, independent of sex, age, or race/ethnicity. The prevalence of insulin resistance in obese children foreshadows a worrisome trend for the burden of type 2 diabetes in the U.S.

OBJECTIVE. We sought to examine the association between weight status in early childhood and onset of puberty. PATIENTS AND METHODS. The study included 354 girls from the National Institute of Child Health and Human Development Study of Early Child Care and Youth Development. Girls were followed longitudinally with height and weight measurements at 36 and 54 months and grades 1, 4, 5, and 6 and with assessment of pubertal stage by physical examination and maternal report in grades 4 through 6. The main outcome was the presence of early puberty, indexed as follows: (a) breast development at or more than Tanner stage 2 by physical examination at grade 4; (b) breast development at or more than Tanner stage 3 by physical examination at grade 5; (c) maternal report of breast development at or more than Tanner stage 3 at grade 5; and (d) maternal report of menarche having already occurred (yes versus no) at grade 6. Multiple logistic regression models predicting early versus late puberty were constructed by using the covariate BMI z score at 36 months, rate of change of BMI and accelerated BMI between 36 months and grade 1, race, maternal education, and maternal age of menarche. RESULTS. BMI z score at 36 months, rate of change of BMI between 36 months and grade 1, an earlier age of maternal menarche, and nonwhite race were each consistently and positively associated with an earlier onset of puberty across the various measures of puberty. CONCLUSIONS. Higher BMI z score in girls as young as 36 months of age and higher rate of change of BMI between 36 months old and grade 1, a period well before the onset of puberty, are associated with earlier puberty, which suggests that increasing rates of obesity in the United States may result in an earlier average age of onset of puberty for US girls.

Plasma 25-hydroxyvitamin D was measured in 40 healthy, mostly Black, mother-infant pairs. Although a majority of mothers received a daily prenatal multivitamin, vitamin D deficiency (<30 nmol/L), was found in 50% of mothers and 65% of their newborn infants, with a positive correlation between maternal and infant plasma 25-hydroxyvitamin D concentrations. Maternal vitamin D deficiency may represent an important risk factor for the development of rickets in children.

We are in the midst of what some have called a “mobile health revolution”. Medical applications (“apps”) for mobile phones are proliferating in the marketplace and clinicians are likely encountering patients with questions about the medical value of these apps. We conducted a review of medical apps focused on endocrine disease. We found a higher percentage of relevant apps in our searches of the iPhone app store compared with the Android marketplace. For our diabetes search in the iPhone store, the majority of apps (33%) focused on health tracking (blood sugars, insulin doses, carbohydrates), requiring manual entry of health data. Only two apps directly inputted blood sugars from glucometers attached to the mobile phone. The remainder of diabetes apps were teaching/training apps (22%), food reference databases (8%), social blogs/forums (5%), and physician directed apps (8%). We found a number of insulin dose calculator apps which technically meet criteria for being a medically regulated mobile application, but did not find evidence for FDA‐approval despite their availability to consumers. Far fewer apps were focused on other endocrine disease and included medical reference for the field of endocrinology, access to endocrine journals, height predictors, medication trackers, and fertility apps. Although mobile health apps have great potential for improving chronic disease care, they face a number of challenges including lack of evidence of clinical effectiveness, lack of integration with the health care delivery system, the need for formal evaluation and review and organized searching for health apps, and potential threats to safety and privacy.

Context: Although recent trends in obesity have been well documented, generational patterns of obesity from early childhood through adulthood across birth cohorts, which account for the recent epidemic of childhood obesity, have not been well described. Such trends may have implications for the prevalence of obesity-associated conditions among population subgroups, including type 2 diabetes. Objective: Our objective was to evaluate trajectories of obesity over the life course for the US population, overall and by gender and race. Design, Setting and Participants: We conducted an age, period and birth cohort analysis of obesity for US individuals who participated in the National Health and Nutrition Examination Surveys (NHANES) (1971–2006). Main Outcome Measures: Obesity was defined as a body mass index ⩾95th percentile for individuals aged 2–16 years or ⩾30 kg m^–2 among individuals older than 16 years. Age was represented by the age of the individual at each NHANES, period was defined by the year midpoint of each survey, and cohort was calculated by subtracting age from period. Results: Recent birth cohorts are becoming obese in greater proportions for a given age, and are experiencing a greater duration of obesity over their lifetime. For example, although the 1966–1975 and 1976–1985 birth cohorts had reached an estimated obesity prevalence of at least 20% by 20–29 years of age, this level was only reached by 30–39 years for the 1946–1955 and 1956–1965 birth cohorts, by 40–49 years for the 1936–1945 birth cohort and by 50–59 years of age for the 1926–1935 birth cohort. Trends are particularly pronounced for female compared with male, and black compared with white cohorts. Conclusions: The increasing cumulative exposure to excess weight over the lifetime of recent birth cohorts will likely have profound implications for future rates of type 2 diabetes, and mortality within the US population.

Objective To examine the association between body mass index (BMI [calculated as weight in kilograms divided by height in meters squared]) and timing of pubertal onset in a population-based sample of US boys. Design Longitudinal prospective study. Setting Ten US sites that participated in the National Institute of Child Health and Human Development Study of Early Child Care and Youth Development. Participants Of 705 boys initially enrolled in the study, information about height and weight measures and pubertal stage by age 11.5 years was available for 401 boys. Main Exposure The BMI trajectory created from measured heights and weights at ages 2, 3, 4.5, 7, 9, 9.5, 10.5, and 11.5 years. Main Outcome Measure Onset of puberty at age 11.5 years as measured by Tanner genitalia staging. Results Boys in the highest BMI trajectory (mean BMIzscore at age 11.5 years, 1.84) had a greater relative risk of being prepubertal compared with boys in the lowest BMI trajectory (mean BMIzscore at age 11.5 years, −0.76) (adjusted relative risk = 2.63; 95% confidence interval, 1.05-6.61;P = .04). Conclusions The relationship between body fat and timing of pubertal onset is not the same in boys as it is in girls. Further studies are needed to better understand the physiological link between body fat and timing of pubertal onset in both sexes.