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"Levy, Steven"
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Active lifestyle in childhood and adolescence prevents obesity development in young adulthood
Objective
To test the hypothesis that individuals who are active but who decrease physical activity (PA) over time have a higher risk of becoming obese in young adulthood, when compared to individuals who are consistently active throughout childhood and adolescence.
Methods
Iowa Bone Development Study cohort members (242 males and 251 females) participated in accelerometry assessments, dual‐energy X‐ray absorptiometry scans, and dietary questionnaire surveys at ages 5, 8, 11, 13, 15, 17, and 19 years. Group‐based trajectory analyses identified distinct trajectory patterns of moderate‐ to vigorous‐intensity PA (MVPA), percentage of body fat, and energy intake. A multivariable logistic regression model was fit to estimate the odds of “becoming obese” based on the MVPA trajectories, adjusted for mother's education, somatic maturation, and energy intake.
Results
Among males, 74.7% had a “normal” body fat pattern, 14.6% had a “becoming obese” pattern, and 10.7% had a “consistently obese” pattern, while among females, the percentages were 58.6%, 28.6%, and 12.8%, respectively. Participants who were active (≥45 min MVPA) as children but decreased MVPA with age were more likely to become obese, compared to consistently active participants (adjusted OR = 2.77; 95% CI = 1.16, 6.58).
Conclusions
An active lifestyle throughout childhood and adolescence could prevent obesity development in young adulthood.
Journal Article
Hackers : heroes of the computer revolution
\"This 25th anniversary edition of Steven Levy's classic book traces the exploits of the computer revolution's original hackers---those brilliant and eccentric nerds from the late 1950s through the earlyل 80s who took risks, bent the rules, and pushed the world in a radical new direction. With updated material from noteworthy hackers such as Bill Gates, Mark Zuckerberg, Richard Stallman, and Steve Wozniak, Hackers is a fascinating story that begins in early computer research labs and leads to the first home computers.\" \"Levy profiles the imaginative brainiacs who found clever and unorthodox solutions to computer engineering problems. They had a shared sense of values, known as \"the Hacker Ethic,\" that still thrives today. Hackers captures a seminal period in recent history when underground activities blazed a trail for today's digital world, from MIT students finagling access to clunky computer-card machines to the DIY culture that spawned the Altair and the Apple II.\" \"If you want to change the world in some big way, that's where you should start---biological molecules. Those are all pretty deep problems that need the same type of crazy fanaticism of youthful genius and naivetâe that drove the PC industry, and can have the same impact on the human condition.\"--Bill Gates, Bill and Melinda Gates Foundation\"--Jacket.
Book
Objectively measured physical activity trajectories predict adolescent bone strength: Iowa Bone Development Study
Background Physical activity improves bone strength and reduces the risk for osteoporotic fractures. However, there are substantial gaps in our knowledge as to when, how and how much activity is optimal for bone health. Purpose In this cohort study, we examined developmental trajectories of objectively measured physical activity from childhood to adolescence to discern if moderate-and-vigorous intensity physical activity (MVPA) predicts bone strength. Methods Starting at age 5 and continuing at 8, 11, 13, 15 and 17 years, Iowa Bone Development Study participants (n=530) wore an accelerometer for 3–5 days. At age 17, we assessed dual X-ray energy absorptiometry outcomes of mass and estimated geometry (femoral neck cross-sectional area and section modulus). We also assessed geometric properties (bone stress index and polar moment of inertia) of the tibia using peripheral computer quantitative tomography. Latent class modelling was used to construct developmental trajectories of MVPA from childhood to late adolescence. General linear models were used to examine the trajectory groups as predictors of age 17 bone outcomes. Results Girls and boys who accumulated the most MVPA had greater bone mass and better geometry at 17 years when compared to less active peers. The proportion of participants achieving high levels of MVPA throughout childhood was very low (<6% in girls) and by late adolescence almost all girls were inactive. Conclusions Bone health benefits of physical activity are not being realised due to low levels of activity for most youth, especially in girls.
Journal Article
شراكات المدرسة والأسرة والمجتمع : دليلك للعمل =
كتاب ثري وعملي يشجعك على البدء في بناء شراكة فاعلة بين المدرسة والأسرة والمجتمع ويقدم لك مختلف الأدوات التي تحتاجها لتبدأ ستجد نموذجا مميزا لمساعدة كل مدرسة على بناء خطة العام للشراكة مع الأسر والمجتمع بالتفصيل ستحصل على خطوات تكوين فرق الشراكة في داخل المدرسة ستحصل على نماذج جاهزة للعمل أيضا قوائم بأنشطة هادفة يمكن تنفيذها وأثبتت جدواها عبر دراسات.
Book
Marginal regression models for clustered count data based on zero-inflated Conway-Maxwell-Poisson distribution with applications
Community water fluoridation is an important public health measure to prevent dental caries, but it continues to be somewhat controversial. The Iowa Fluoride Study (IFS) is a longitudinal study on a cohort of Iowa children that began in 1991. The main purposes of this study (http://www.dentistry.uiowa.edu/preventive-fluoride-study) were to quantify fluoride exposures from both dietary and nondietary sources and to associate longitudinal fluoride exposures with dental fluorosis (spots on teeth) and dental caries (cavities). We analyze a subset of the IFS data by a marginal regression model with a zero-inflated version of the Conway–Maxwell–Poisson distribution for count data exhibiting excessive zeros and a wide range of dispersion patterns. In general, we introduce two estimation methods for fitting a ZICMP marginal regression model. Finite sample behaviors of the estimators and the resulting confidence intervals are studied using extensive simulation studies. We apply our methodologies to the dental caries data. Our novel modeling incorporating zero inflation, clustering, and overdispersion sheds some new light on the effect of community water fluoridation and other factors. We also include a second application of our methodology to a genomic (next-generation sequencing) dataset that exhibits underdispersion.
Journal Article
Predicting dental caries outcomes in young adults using machine learning approach
To predict the dental caries outcomes in young adults from a set of longitudinally-obtained predictor variables and identify the most important predictors using machine learning techniques.
This study was conducted using the Iowa Fluoride Study dataset. The predictor variables - sex, mother's education, family income, composite socio-economic status (SES), caries experience at ages 9, 13, and 17, and the cumulative estimates of risk and protective factors, including fluoride, dietary, and behavioral variables from ages 5-9, 9-13, 13-17, and 17-23 were used to predict the age 23 D
MFS count. The following machine learning models (LASSO regression, generalized boosting machines (GBM), negative binomial (NegGLM), and extreme gradient boosting models (XGBOOST)) were compared under 5-fold cross validation with nested resampling techniques.
The prevalence of cavitated level caries experience at age 23 (mean D
MFS count) was 4.75. The predictive analysis found LASSO to be the best performing model (compared to GBM, NegGLM, and XGBOOST), with a root mean square error (RMSE) of 0.70, and coefficient of determination (R
) of 0.44. After dichotomization of the predicted and observed values of the LASSO regression, the classification results showed accuracy, precision, recall, and ROC AUC of 83.7%, 85.9%, 93.1%, 68.2%, respectively. Previous caries experience at age 13 and age 17 and sugar-sweetened beverages intakes at age 13 and age 17 were found to be the four most important predictors of cavitated caries count at age 23.
Our machine learning model showed high accuracy and precision in the prediction of caries in young adults from a longitudinally-obtained predictor variables. Our model could, in the future, after further development and validation with other diverse population data, be used by public health specialists and policy-makers as a screening tool to identify the risk of caries in young adults and apply more targeted interventions. However, data from a more diverse population are needed to improve the quality and generalizability of caries prediction.
Journal Article
Associations between body mass index and body composition measures in a birth cohort
Associations among body composition measures have been limited to cross-sectional analyses of different subjects. We identified cross-sectional relationships between body mass index (BMI) and other body composition measures and predicted body composition measures from BMI throughout childhood and adolescence.
BMI was calculated and % body fat (%BF), fat mass index (FMI), and fat-free mass index (FFMI) were measured using dual-energy x-ray absorptiometry at ages 5, 9, 11, 13, 15, and 17 years in a birth cohort (n = 629). Sex-specific body composition measures were calculated for BMI-for-age percentiles; associations between BMI and body composition measures were characterized; and body composition measures were predicted from BMI.
%BF, FMI, and FFMI generally increased with BMI-for-age percentiles at each age. Correlations between BMI and %BF or FMI were generally higher at BMI-for-age percentiles ≥95% than for lower BMI-for-age percentiles. Correlations between BMI and FFMI were generally higher for participants at very low and very high BMI-for-age percentiles than at moderate BMI-for-age percentiles. Age- and sex-specific predictions from BMI are provided for %BF, FM, and FFMI.
Sex-specific body composition measures throughout childhood and adolescence are presented. BMI is a better indicator of adiposity at higher than at lower BMI values.
Sex-specific body composition measures throughout childhood and adolescence are described. % BF, FMI, and FFMI generally increased with BMI-for-age percentiles for both sexes throughout childhood and adolescence. BMI is a better indicator of adiposity at higher BMI levels than at lower BMI values throughout childhood and adolescence.
Journal Article
Association between body mass index percentile trajectories in infancy and adiposity in childhood and early adulthood
Objective
To identify distinct body mass index (BMI) percentile trajectories during early childhood and examine adiposity levels in childhood and early adulthood according to the BMI percentile trajectories.
Methods
Iowa Fluoride Study cohort parents (n = 1,093) reported their child's anthropometric data on average six times between ages 0 and 23 months. A subset of the cohort underwent DXA scans at approximately age 8 years (n = 495) and again at approximately age 19 years (n = 314). Group‐based trajectory analysis was conducted to identify distinct BMI percentile trajectories from ages 0 to 23 months. Sex‐specific age‐adjusted linear regression analyses were conducted to compare fat mass index in childhood and early adulthood among subgroups that follow the distinct BMI percentile patterns.
Results
Four BMI percentile patterns were identified: consistently low (group 1: 9.8%), increase in the second year (group 2: 33.7%), increase in the first year (group 3: 23.9%), and consistently high (group 4: 32.6%). Compared with group 2 females, groups 3 and 4 females had higher fat mass index in childhood and early adulthood (P < 0.05). However, no significant difference was found in males.
Conclusions
Females who experience a steep increase of BMI percentile in the first year of life, as opposed to a steep increase in the second year of life, may have higher body fat later in life, but this was not found in males.
Journal Article
Factors Influencing Early Feeding of Foods and Drinks Containing Free Sugars-A Birth Cohort Study
Early feeding of free sugars to young children can increase the preference for sweetness and the risk of consuming a cariogenic diet high in free sugars later in life. This study aimed to investigate early life factors influencing early introduction of foods/drinks containing free sugars. Data from an ongoing population-based birth cohort study in Australia were used. Mothers of newborn children completed questionnaires at birth and subsequently at ages 3, 6, 12, and 24 months. The outcome was reported feeding (Yes/No) at age 6-9 months of common foods/drinks sources of free sugars (hereafter referred as foods/drinks with free sugars). Household income quartiles, mother's sugar-sweetened beverage (SSB) consumption, and other maternal factors were exposure variables. Analysis was conducted progressively from bivariate to multivariable log-binomial regression with robust standard error estimation to calculate prevalence ratios (PR) of being fed foods/drinks with free sugars at an early age (by 6-9 months). Models for both complete cases and with multiple imputations (MI) for missing data were generated. Of 1479 mother/child dyads, 21% of children had been fed foods/drinks with free sugars. There was a strong income gradient and a significant positive association with maternal SSB consumption. In the complete-case model, income Q1 and Q2 had PRs of 1.9 (1.2-3.1) and 1.8 (1.2-2.6) against Q4, respectively. The PR for mothers ingesting SSB everyday was 1.6 (1.2-2.3). The PR for children who had been breastfed to at least three months was 0.6 (0.5-0.8). Similar findings were observed in the MI model. Household income at birth and maternal behaviours were significant determinants of early feeding of foods/drinks with free sugars.
Journal Article