Late-onset or chronic overweight/obesity predicts low self-esteem in early adolescence: a longitudinal cohort study

Background How weight status changes with time may affect self-esteem was seldom studied. We identified the distinct trajectories of overweight/obesity over age and assessed their associations with different domains of self-esteem in Hong Kong Chinese children. Methods Territory-wide longitudinal data of 48,558 children (girls: 50.0%; 6.3 ± 0.51 years) studying Primary 1 in the academic cohorts of 1995/96 and 1996/97 followed till Primary 6 were obtained from the Student Health Service of Hong Kong. Weight was annually measured and categorized as underweight/normal and overweight/obese and self-esteem was measured in Primary 6. Distinct trajectories of weight status were first identified using growth mixture modeling and their associations with low self-esteem were assessed by logistic regression. Results Four distinct overweight/obesity trajectories were identified: never (76.8%), late-onset (8.1%), early-onset (4.2%) and chronic (10.9%) overweight/obesity. Compared with children who were never overweight/obese, more of those in the late-onset or chronic overweight/obesity group showed low self-esteem and specific domains including general, social and academic/school-related (adjusted odds ratios: 1.20 - 1.43, all P < 0.001) except parent/home-related self-esteem (P = 0.36), whereas children being in the early-onset overweight/obesity group showed no significant difference (P ≥ 0.53) except a lower risk of low social self-esteem (adjusted odds ratio = 0.82, P = 0.03). Conclusions Late-onset or chronic overweight/obesity predicted low general, social and academic/school-related self-esteem. Children who successfully reduced weight may have equal levels of self-esteem or even better social self-esteem than those being always underweight/normal weight. Overweight/obese children had a vulnerability to self-esteem in non-domestic environments.

Profiles of competence development in mathematics and reading in early secondary education

This article examines the development of reading and mathematical competence in early secondary education and aims at identifying distinct profiles of competence development. Since reading and mathematical competences are highly correlated both cross-sectionally and longitudinally, we expected to find a generalized profile of competence development with students developing parallel in reading and mathematical competences. Moreover, previous research confirmed individuals’ specific focus on one of the two domains, for example, in their interest, self-concept, or motivation. Also, differences in competence levels between both domains were found in cross-sectional studies. Therefore, we hypothesized that additional to the generalized profile, there are specialized profiles of competence development with students developing distinctively faster in one of the two domains. To identify both types of profiles, latent growth mixture modeling was used on a sample of 5,301 students entering secondary education from the German National Educational Panel Study. To demonstrate the robustness of the results, these analyses were repeated using different model specifications and subgroups with higher homogeneity (with students belonging to the highest track, i.e., “Gymnasium”). The results indicate only small to non-existent specialized profiles of competence development in all conditions. This finding of roughly parallel development of reading and mathematical competences throughout early secondary education indicates that potential specializations are less important at this point in students’ educational careers.

Identification of Youthful Neurocognitive Trajectories in Adults Aging with HIV: A Latent Growth Mixture Model

Despite the neurocognitive risks of aging with HIV, initial cross-sectional data suggest a subpopulation of older people with HIV (PWH) possess youthful neurocognition (NC) characteristic of SuperAgers (SA). Here we characterize longitudinal NC trajectories of older PWH and their convergent validity with baseline SA status, per established SuperAging criteria in PWH, and baseline biopsychosocial factors. Growth mixture modeling (GMM) identified longitudinal NC classes in 184 older (age ≥ 50-years) PWH with 1–5 years of follow-up. Classes were defined using ‘peak-age’ global T-scores, which compare performance to a normative sample of 25-year-olds. 3-classes were identified: Class 1Stable Elite (n = 31 [16.8%], high baseline peak-age T-scores with flat trajectory); Class 2Quadratic Average (n = 100 [54.3%], intermediate baseline peak-age T-scores with u-shaped trajectory); Class 3Quadratic Low (n = 53 [28.8%], low baseline peak-age T-scores with u-shaped trajectory). Baseline predictors of Class 1Stable Elite included SA status, younger age, higher cognitive and physiologic reserve, and fewer subjective cognitive difficulties. This GMM analysis supports the construct validity of SuperAging in older PWH through identification of a subgroup with longitudinally-stable, youthful neurocognition and robust biopsychosocial health.

EXPRESS: Timing Market Entry – the Mediation Effect of Market Potential

Timing a multinational firm’s entry into a new country is a pivotal decision with long-term impact on the firm’s overall performance, thus a deeper understanding of the drivers of the decision and their interrelationship can yield significant managerial benefits. We explore the mediating role of market potential by decomposing the total effects of the decision’s main drivers—macro-economic attractiveness, market concentration, social heterogeneity, population density—into direct and indirect effects. These decompositions explain the countervailing effects of some drivers that simultaneously make both positive and negative impacts. Our dataset encompasses mobile 4G broadband penetration in 130 countries, including market entry timings for 28 international operators in 79 countries. We establish the nature of the mediation effect of market potential on the drivers of entry timing. Using early penetration data, we utilize growth mixture modeling to divide the countries into four latent segments. We validate this segmentation using machine learning with the four key drivers as classifiers; the process establishes macro-economic attractiveness as the predominant classifier. Our analysis offers entry-timing guidance at both pre- and post-launch stages.

The Association between Trajectories of Anthropometric Variables and Risk of Diabetes among Prediabetic Chinese

In order to explore the association between trajectories of body mass index (BMI) and mid-upper arm circumference (MUAC) and diabetes and to assess the effectiveness of the models to predict diabetes among Chinese prediabetic people, we conducted this study. Using a national longitudinal study, 1529 cases were involved for analyzing the association between diabetes and BMI trajectories or MUAC trajectories. Growth mixture modeling was conducted among the prediabetic Chinese population to explore the trajectories of BMI and MUAC, and logistic regression was applied to evaluate the association between these trajectories and the risk of diabetes. The receiver operating characteristic curve (ROC) and the area under the curve (AUC) were applied to assess the feasibility of prediction. BMI and MUAC were categorized into 4-class trajectories, respectively. Statistically significant associations were observed between diabetes in certain BMI and MUAC trajectories. The AUC for trajectories of BMI and MUAC to predict diabetes was 0.752 (95% CI: 0.690–0.814). A simple cross-validation using logistic regression indicated an acceptable efficiency of the prediction. Diabetes prevention programs should emphasize the significance of body weight control and maintaining skeletal muscle mass and resistance training should be recommended for prediabetes.

Socioeconomic disparities and infancy growth trajectory: a population-based and longitudinal study

Background The association of low socioeconomic status (SES) with childhood and adolescent obesity has been reported. It is unknown whether low SES affects body mass index (BMI) growth trajectory in the first 12 mo of life. Moreover, accelerated growth as a compensatory mechanism for low birth weight (LBW) during infancy, is an important predictor of later obesity. The aim of the present study was to examine the association of low SES with infancy BMI growth rate and trajectory for LBW and normal birth weight (NBW) infants. Methods From September 2012 to October 2014, a total of 387 infants in this longitudinal study was subjected to repeated measures of weight and length from birth to 12 mo in Hefei. Generalized growth mixture modeling was used to classify the infancy BMI growth trajectories. Differences in infancy BMI z score (zBMI) and BMI growth rate between low SES and high SES were estimated based on linear regression after adjusting for several confounders including maternal age, pregnancy BMI, physical activity during pregnancy, paternal BMI as well as alcohol use, paternal smoking status, breastfeeding duration and delivery mode. Results Infancy BMI trajectories in this study were classified into three categories: rapid growth (class 1), normal growth (class 2) and slow growth (class 3). Low SES infants had the higher zBMI than high SES infants for LBW group at age 6 mo [zBMI difference with 95% CI at 6 mo: 0.28(0.03, 0.53); at 12 mo: 0.21(0.01, 0.43)]. Low SES infants had more rapid zBMI growth rate than those with high SES for low birth weight between 0 and 6 months. Controlling for the confounders, these associations remained robust. We found the lower SES in the rapid growth group. Conclusions These findings highlighted the impact of low SES on increasing BMI and accelerated growth during early infancy. Health care and relatively optimal family environment in the first 12 mo of life, especially for LBW infants, are benefit to shape the better infancy growth trajectory.

Multimorbidity Trajectory Classes as Predicted by Race, Ethnicity, and Social Relationship Quality

Growth mixture modeling was used to classify multimorbidity (≥2 chronic conditions) trajectories over a 10-year period (2006-2016) in the Health and Retirement Study (N = 7,151, mean age = 68.6 years). Race/ethnicity (non-Hispanic Black, Hispanic, non-Hispanic White) and social relationship quality (positive social support and negative social exchanges, such as criticisms) were then used to predict trajectory class membership, controlling for age, sex, education, and wealth. We identified three trajectory classes: initial low levels and rapid accumulation of multimorbidity (increasing: 12.6%), initial high levels and gradual accumulation of multimorbidity (high: 19.5%), and initial low levels and gradual accumulation of multimorbidity (low: 67.9%). Blacks were more than twice as likely to be in the increasing (OR = 2.04, CI[1.29,3.21]) and high (OR = 2.28 CI[1.58,3.206]) multimorbidity groups compared with Whites, but there were no significant differences between Hispanics and Whites for either trajectory class (OR = .84 CI[.47,1.51]and OR = .74 CI[.41,1.34], respectively). Increments in perceived support were associated with significantly lower risk of membership in the increasing (OR = .59, CI[.46,.78]) and high classes (OR = .54 CI[.42,.69]), and increments in negative exchanges were associated with significantly higher risk of membership in the increasing (OR = 1.64 CI[1.19,2.25]) and high classes (OR = 2.22 CI[1.64,3.00]). These results provide important new information for understanding health disparities and the role of social relationships associated with multimorbidity in middle and later life that may aid in identifying those most at risk and suggesting possible interventions for mitigating that risk.

Individual Differences in Concurrent Developmental Trajectories of Pain and Insomnia in Adolescents Are Predicted by Chronotype and Arousal-causing Pre-sleep Behaviors.

The onset of both chronic pain and insomnia is high during adolescence. Although a bidirectional relationship between pain and insomnia has support, how pain and sleep co-develop throughout adolescence remains unknown. Both sleep-wake patterns and pre-sleep behaviors that cause arousal may influence the co-development of pain and insomnia. Four waves of longitudinal self-report data were used (Nbaseline = 2767, Agebaseline M = 13.65 years, SD = 0.65). Multidimensional growth mixture modeling was used to identify four subgroups of adolescents with different concurrent trajectories of pain and insomnia. The trajectories followed each other across time in all classes: one class of consistently low pain and insomnia (68.7 %), one class with persistent high symptoms (4.9 %), as well as one class of increasing (13.9 %), and one of decreasing (12.5 %), trajectories. Later sleep-wake patterns and more pre-sleep behaviors causing cognitive-emotional arousal predicted both increasing and decreasing trajectories of concurrent pain and insomnia. The current study showed that developmental trajectories of pain and insomnia follow each other within adolescents and across adolescence. Both sleep-phase focused interventions as well as psychological interventions that focus on pre-sleep behaviors causing cognitive-emotional arousal may prove beneficial for adolescents with comorbid pain and insomnia.