Longitudinal Associations Between White Matter Microstructure and Psychiatric Symptoms in Youth

Objective: Associations between psychiatric problems and white matter (WM) microstructure have been reported in youth. Yet, a deeper understanding of this relation has been hampered by a dearth of well-powered longitudinal studies and a lack of explicit examination of the bidirectional associations between brain and behavior. We investigated the temporal directionality of WM microstructure and psychiatric symptom associations in youth. Method: In this observational study, we leveraged the world's largest single- and multi-site cohorts of neurodevelopment: the Generation R (GenR) and Adolescent Brain Cognitive Development Studies (ABCD) (total n scans = 11,400; total N = 5,700). We assessed psychiatric symptoms with the Child Behavioral Checklist as broad-band internalizing and externalizing scales, and as syndrome scales (eg, Anxious/Depressed). We quantified WM with diffusion tensor imaging (DTI), globally and at a tract level. We used cross-lagged panel models to test bidirectional associations of global and specific measures of psychopathology and WM microstructure, meta-analyzed results across cohorts, and used linear mixed-effects models for validation. Results: We did not identify any longitudinal associations of global WM microstructure with internalizing or externalizing problems across cohorts (confirmatory analyses) before, and after multiple testing corrections. We observed similar findings for longitudinal associations between tract-based microstructure with internalizing and externalizing symptoms, and for global WM microstructure with specific syndromes (exploratory analyses). Some cross-sectional associations surpassed multiple testing corrections in ABCD, but not in GenR. Conclusion: Uni- or bi-directionality of longitudinal associations between WM and psychiatric symptoms were not robustly identified. We have proposed several explanations for these findings, including interindividual differences, the use of longitudinal approaches, and smaller effects than expected. Study registration information: Bidirectionality Brain Function and Psychiatric Symptoms; https://doi.org/10.17605/OSF.IO/PNY92</p

Intrauterine Exposure to Antidepressants or Maternal Depressive Symptoms and Offspring Brain White Matter Trajectories From Late Childhood to Adolescence

Background: During pregnancy, both selective serotonin reuptake inhibitor (SSRI) exposure and maternal depression have been associated with poor offspring neurodevelopmental outcomes. In a population-based cohort, we investigated the association between intrauterine exposure to SSRIs and depressive symptoms and offspring white matter development from childhood to adolescence. Methods: Self-reported SSRI use was verified by pharmacy records. In midpregnancy, women reported on depressive symptoms using the Brief Symptom Inventory. Using diffusion tensor imaging, offspring white matter microstructure, including whole-brain and tract-specific fractional anisotropy (FA) and mean diffusivity, was measured at 3 assessments between ages 7 to 15 years. The participants were divided into 4 groups: prenatal SSRI exposure (n = 37 with 60 scans), prenatal depression exposure (n = 229 with 367 scans), SSRI use before pregnancy (n = 72 with 95 scans), and reference (n = 2640 with 4030 scans). Results: Intrauterine exposure to SSRIs and depressive symptoms were associated with lower FA in the whole-brain and the forceps minor at 7 years. Exposure to higher prenatal depressive symptom scores was associated with lower FA in the uncinate fasciculus, cingulum bundle, superior and inferior longitudinal fasciculi, and corticospinal tracts. From ages 7 to 15 years, children exposed to prenatal depressive symptoms showed a faster increase in FA in these white matter tracts. Prenatal SSRI exposure was not related to white matter microstructure growth over and above exposure to depressive symptoms.Conclusions: These results suggest that prenatal exposure to maternal depressive symptoms was negatively associated with white matter microstructure in childhood, but these differences attenuated during development, suggesting catch-up growth.</p

Determinants and Predictors of Grief Severity and Persistence: The Rotterdam Study

Objective: We aimed to explore correlates and predictors of bereavement severity and persistence (triggered by “loss of a loved one”; referent group partner loss) in the Rotterdam cohort. Method: We used linear regression to examine factors associated with grief severity using a cross-sectional analysis and logistic regression to determine prospective associations. Results: Cross-sectionaly, females, child-lost, higher depressive symptoms, lower education, and difficulties in daily activities were independently associated with a higher bereavement severity. Prospectively (6 years; response rate 71%), the baseline value of the grief severity was the single predictor significantly associated with grief persistence. Discussion: Our results suggest that only grief severity is independently associated with grief persistence. Further studies are needed to confirm ou

Food Security Crop Price Transmission and Formation in Nigeria

The three studies in this dissertation explore the current conditions and operations of markets for seven key food security crops (cassava, cowpeas, maize, millet, rice, sorghum, and yams) in Nigeria. Chapter 2 is an empirical analysis of the current agricultural statistics system in Nigeria. A number of sources gather and report agricultural statistics for the country. Since there has not been an agricultural census implemented there for multiple decades, however, there is no objective source for data verification. Therefore, this study uses two additional types of “on the ground information” to assess if agricultural production estimates reflect growing conditions: prices and remote sensing data in the form of the normalized difference vegetation index (NDVI). The results show that existing production estimates are poorly correlated with both prices and the NDVI. Prices and the NDVI data are highly correlated, however. These findings imply that existing production estimates do not reflect growing conditions, and, therefore, are of poor quality. Chapter 3 is a comprehensive analysis of crop price transmission from global and neighbor country prices to Nigerian commercial hub and urban markets, and from commercial hubs to other urban and rural markets within the country. The results show that tradability matters for price transmission, but that tradability varies across crops and scopes of markets. Nigerian urban rice prices are highly correlated with prices on global markets and those in neighboring countries. Coarse grain prices appear disconnected from global markets, however, but move closely with those in neighboring countries. Large margins were estimated for prices of rice imported from global markets (in all regions), and for coarse grains to Southern Nigerian markets only. The existence of large margins implies that there are transactions costs and/or quality premiums that vary systematically with the world price, and/or mark-ups by traders with market power in these markets. While domestic market prices are almost always cointegrated, perfect price transmission is generally found only between commercial hubs and other urban markets. Moreover, long lags were found for price transmission across all scopes of markets, but especially between urban and rural prices in some regions. These results imply that local conditions (e.g., weather) are relatively more important than external market prices for explaining price variation in rural markets, especially in the short-run. Chapter 4 incorporates NDVI data into price formation models to estimate whether observable growing conditions explain price variation in Nigerian food security crop markets. Four issues related to use of NDVI data that exist within the literature are investigated: whether NDVI is a valid proxy for expected production, how NDVI is a proxy for seasonality, the relationship between market size and the area scope used to average NDVI values across space, and if anomalous harvest expectations can change long-run price variation and price relationships between markets. The results show that information on growing conditions is more informative for isolated than interconnected markets. Even for those local prices, however, other non-weather and non-external market price factors are relatively more important for explanation of price variation. An implication of these results is that Nigeria cannot plausibly rely solely on direct imports from global markets to meet short-run demand during future weather shock periods. Thus, storage is required to ensure stability of food security, either for imports or domestically produced surpluses acquired in non-crisis periods. Given the isolation of rural markets, local and on-farm stocks are at least as important as large facilities in commercial hubs. Improvement of village level and on-farm storage systems and elimination of other market distortions that inhibit trade between urban and rural markets would make public storage less needed. The findings on poor quality of agricultural statistics indicate a clear priority to improve agricultural data, to facilitate better planning of any food security strategies. A combination of surveys with remote sensed and crowd sourced data may improve feasibility in the funding constrained environment