Revisiting the effects of maternal education on adolescents' academic performance: Doubly robust estimation in a network-based observational study.

In many contexts, particularly when study subjects are adolescents, peer effects can invalidate typical statistical requirements in the data. For instance, it is plausible that a student's academic performance is influenced both by their own mother's educational level as well as that of their peers. Since the underlying social network is measured, the Add Health study provides a unique opportunity to examine the impact of maternal college education on adolescent school performance, both direct and indirect. However, causal inference on populations embedded in social networks poses technical challenges, since the typical no interference assumption no longer holds. While inverse probability-of-treatment weighted (IPW) estimators have been developed for this setting, they are often highly unstable. Motivated by the question of maternal education, we propose doubly robust (DR) estimators combining models for treatment and outcome that are consistent and asymptotically normal if either model is correctly specified. We present empirical results that illustrate the DR property and the efficiency gain of DR over IPW estimators even when the treatment model is misspecified. Contrary to previous studies, our robust analysis does not provide evidence of an indirect effect of maternal education on academic performance within adolescents' social circles in Add Health.

Early Lifestyle Determinants of Adiposity Trajectories from Childhood into Late Adolescence.

Objective: The aim of this study was to examine associations of childhood physical activity, sedentary behavior, and dietary intake with adiposity trajectories from childhood to adolescence. Methods: Quebec Adipose and Lifestyle Investigation in Youth (QUALITY) cohort (n = 630) data from 3 time points (8-10, 10-12, and 15-17 years) for 377 Caucasian children with parental obesity were analyzed. Height and weight, physical activity and sedentary behavior (7-day accelerometry), screen time (self-reported), and dietary intake (three 24-hour diet recalls) were measured. Group-based trajectory modeling identified longitudinal trajectories of body-mass index z-scores (zBMIs). Inverse probability of exposure-weighted multinomial logistic regressions examined associations between baseline lifestyles and zBMI trajectory groups. Results: Six trajectory groups were identified: Stable-Low-Normal-Weight (two groups, 5.7% and 33.0%, which were combined), Stable-High-Normal-Weight (24.8%), Stable-Overweight (19.8%), Stable-Obesity (8.8%), and Overweight-Decreasers (7.9%). For every additional portion of fruits and vegetables, the likelihood of being in the group of Overweight-Decreasers increased by 29% (odds ratio [OR]: 1.29, 95% confidence interval [CI]: 1.09-1.55) compared with the reference group (Stable-Low-Normal-Weight). For every additional hour of sedentary behavior, the likelihood of belonging to the group of Overweight-Decreasers increased 2-fold (OR: 1.99, 95% CI: 1.28-3.21) and Stable-Obesity increased 1.5-fold (OR: 1.56, 95% CI: 1.08-2.23), compared with the reference. Every additional 10 minutes of moderate-to-vigorous physical activity was associated with a lower likelihood of belonging to the Stable-Obesity group (OR: 0.75, 95% CI: 0.61-0.89) and to the group of Overweight-Decreasers (OR: 0.79, 95% CI: 0.64-0.95) compared with the reference. Finally, children were more likely to belong to the Stable-Obesity group with each additional hour/day of screen time (OR: 1.23, 95% CI: 1.01-1.58). Conclusions: Trajectories of zBMIs from childhood to late adolescence were stable, except for one group which decreased from overweight in childhood to normal weight in adolescence. The latter had more favorable baseline dietary intake of fruits and vegetables. ClinicalTrials.org no. NCT03356262.

Body Mass Index Z Score vs Weight-for-Length Z Score in Infancy and Cardiometabolic Outcomes at Age 8-10 Years.

OBJECTIVES: To confirm that World Health Organization weight-for-length z scores (zWFL) and World Health Organization body mass index z scores (zBMI) in infancy are associated with adiposity and cardiometabolic measures at 8-10 years old and to compare the predictive ability of the 2 methods. STUDY DESIGN: zWFL and zBMI at 6, 12, and 18 months of age were computed using data extracted from health booklets, among participants in the Québec Adipose and Lifestyle InvesTigation in Youth prospective cohort (n = 464). Outcome measures at 8-10 years included adiposity, lipid profile, blood pressure, and insulin dynamics. The relationships between zWFL, zBMI, and each outcome were estimated using multivariable linear regression models. Outcome prediction at 8-10 years was compared between the 2 methods using eta-squared and the Lin concordance correlation coefficient. RESULTS: zWFL and zBMI were associated with all measures of adiposity at 8-10 years. Associations with other cardiometabolic measures were less consistent. For both zWFL and zBMI across infancy, eta-squared were highly similar and the Lin coefficients were markedly high (≥0.991) for all outcomes. CONCLUSIONS: There was no evidence that zBMI and zWFL in infancy differed in their ability to predict adiposity and cardiometabolic measures in childhood. This lends support to the sole use of zBMI for growth monitoring and screening of overweight and obesity from birth to 18 years. TRIAL REGISTRATION: ClinicalTrials.gov: NCT03356262.

Development of Action Threshold to Manage Common Leaf Spot and Black Seed Disease of Strawberry Caused by Mycosphaerella fragariae.

The fungus Mycosphaerella fragariae is responsible for two strawberry diseases: common leaf spot (CLS) and black seed disease (BSD). In June-bearing strawberry plantings, CLS influences vigor, yield, and winter survival. During production years, BSD causes black lesions around strawberry seeds, reducing the market value of the berries. The objective of this study was to characterize the relationships between CLS and BSD and to develop action thresholds for the management of BSD. Data on the number of lesions per leaf, number of black seeds per berry, and percentage of diseased berries were collected at two experimental and six commercial sites from 2000 to 2011, corresponding to 50 farm-years. First, logistic regression was used to model the relationship between BSD occurrence in its binary data form and the number of lesions per leaf assessed at 7, 14, 21, and 28 days before 10% bloom. Second, linear regression was used to model the relationship between BSD severity, BSD incidence, and number of lesions per leaf assessed at 7, 14, 21, and 28 days before 10% bloom. Resulting action thresholds of 15, 25, or 33 lesions per leaf at 21, 14, or 7 days before 10% bloom, respectively, were compared with the recommended practice at three commercial sites in 2014, 2015, and 2016. The percentage of diseased berries was significantly (P = 0.0016; least significant difference = 7.140) higher in the sections of the fields that were not managed for BSD, with an average of 15.22% diseased berries, in comparison with 3.22 and 2.44% diseased berries in sections managed according to the recommendations and the thresholds, respectively. Overall, 40% less fungicide was used when the thresholds were applied. Hence, these thresholds can be used as an additional decision tool to optimize fungicide applications during the prebloom period.

Association Between Weather Variables, Airborne Inoculum Concentration, and Raspberry Fruit Rot Caused by Botrytis cinerea.

Botrytis fruit rot (BFR), one of the most important diseases of raspberry (Rubus spp.), is controlled primarily with fungicides. Despite the use of fungicides, crop losses due to BFR are high in most years. The aim of this study was to investigate the association between airborne inoculum, weather variables, and BFR in order to improve the management of the disease as well as harvest and storage decisions. Crop losses, measured as the percentage of diseased berries during the harvest period, were monitored in unsprayed field plots at four sites in three successive years, together with meteorological data and the number of conidia in the air. Based on windowpane analysis, there was no evidence of correlation between crop losses and temperature, vapor pressure deficit, wind, solar radiation, or probability of infection. There were significant correlations between crop losses and airborne inoculum and between crop losses and humidity-related variables, and the best window length was identified as 7 days. Using 7-day average airborne inoculum concentration combined with 7-day average relative humidity for periods ending 6 to 8 days before bloom, it was possible to accurately predict crop losses (R2 of 0.86 to 0.89). These models could be used to assist with managing BFR, timing harvests, and optimizing storage duration in raspberry crops.

Identification of Weather Conditions Associated with the Occurrence, Severity, and Incidence of Black Seed Disease of Strawberry Caused by Mycosphaerella fragariae.

Black seed disease (BSD) of strawberry is a sporadic disease caused by Mycosphaerella fragariae. Because little is known about potential crop losses or the weather conditions conducive to disease development, fungicides are generally not applied or are applied based on a preset schedule. Data collected from 2000 to 2011 representing 50 farm-years (total of 186 strawberry fields) were used to determine potential crop losses and to study the influence of weather on disease occurrence and development. First, logistic regression was used to model the relationship between occurrence of BSD and weather variables. Second, linear and nonlinear regressions were used to model the number of black seed per berry (severity) and the percentage of diseased berries (incidence). Of the 186 fields monitored, 78 showed black seed symptoms, and the number of black seed per berry ranged from 1 to 10, whereas the percentage of diseased berries ranged from 3 to 32%. The most influential weather variable was total rainfall (in millimeters) in May, with a threshold of 103 mm of rain (absence of BSD < 103 mm < presence of BSD). Similarly, nonlinear models with the total rainfall in May accurately predicted both disease severity and incidence (r = 0.94 and 0.97, respectively). Considering that management actions such as fungicide application are not needed every year in every field, these models could be used to identify fields that are at risk of BSD.