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Luby JL, Herzberg MP, Hoyniak C, Tillman R, Lean RE, Brady R, Triplett R, Alexopoulos D, Loseille D, Smyser T, Rogers CE, Warner B, Smyser CD, Barch DM. Basic Environmental Supports for Positive Brain and Cognitive Development in the First Year of Life. JAMA Pediatr 2024; 178:465-472. [PMID: 38497981 PMCID: PMC10949150 DOI: 10.1001/jamapediatrics.2024.0143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Accepted: 01/17/2024] [Indexed: 03/19/2024]
Abstract
Importance Defining basic psychosocial resources to facilitate thriving in the first year of life could tangibly inform policy and enhance child development worldwide. Objective To determine if key environmental supports measured as a thrive factor (T-factor) in the first year of life positively impact brain, cognitive, and socioemotional outcomes through age 3. Design, Setting, and Participants This prospective longitudinal cohort study took place at a Midwestern academic medical center from 2017 through 2022. Participants included singleton offspring oversampled for those facing poverty, without birth complications, congenital anomalies, or in utero substance exposures (except cigarettes and marijuana) ascertained prenatally and followed up prospectively for the first 3 years of life. Data were analyzed from March 9, 2023, through January 3, 2024. Exposures Varying levels of prenatal social disadvantage advantage and a T-factor composed of environmental stimulation, nutrition, neighborhood safety, positive caregiving, and child sleep. Main outcomes & measures Gray and white matter brain volumes and cortical folding at ages 2 and 3 years, cognitive and language abilities at age 3 years measured by the Bayley-III, and internalizing and externalizing symptoms at age 2 years measured by the Infant-Toddler Social and Emotional Assessment. Results The T-factor was positively associated with child cognitive abilities (β = 0.33; 95% CI, 0.14-0.52), controlling key variables including prenatal social disadvantage (PSD) and maternal cognitive abilities. The T-factor was associated with child language (β = 0.36; 95% CI, 0.24-0.49), but not after covarying for PSD. The association of the T-factor with child cognitive and language abilities was moderated by PSD (β = -0.32; 95% CI, -0.48 to -0.15 and β = -0.36; 95% CI, -0.52 to -0.20, respectively). Increases in the T-factor were positively associated with these outcomes, but only for children at the mean and 1 SD below the mean of PSD. The T-factor was negatively associated with child externalizing and internalizing symptoms over and above PSD and other covariates (β = -0.30; 95% CI, -0.52 to -0.08 and β = -0.32; 95% CI, -0.55 to -0.09, respectively). Increasing T-factor scores were associated with decreases in internalizing symptoms, but only for children with PSD 1 SD above the mean. The T-factor was positively associated with child cortical gray matter above PSD and other covariates (β = 0.29; 95% CI, 0.04-0.54), with no interaction between PSD and T-factor. Conclusions and Relevance Findings from this study suggest that key aspects of the psychosocial environment in the first year impact critical developmental outcomes including cognitive, brain, and socioemotional development at age 3 years. This suggests that environmental resources and enhancement in the first year of life may facilitate every infant's ability to thrive, setting the stage for a more positive developmental trajectory.
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Affiliation(s)
- Joan L Luby
- Department of Psychiatry, School of Medicine, Washington University in St. Louis, . St Louis, Missouri
| | - Max P Herzberg
- Department of Psychiatry, School of Medicine, Washington University in St. Louis, . St Louis, Missouri
| | - Caroline Hoyniak
- Department of Psychiatry, School of Medicine, Washington University in St. Louis, . St Louis, Missouri
| | - Rebecca Tillman
- Department of Psychiatry, School of Medicine, Washington University in St. Louis, . St Louis, Missouri
| | - Rachel E Lean
- Department of Psychiatry, School of Medicine, Washington University in St. Louis, . St Louis, Missouri
| | - Rebecca Brady
- Department of Neurology, School of Medicine, Washington University in St. Louis, . St. Louis Missouri
| | - Regina Triplett
- Department of Neurology, School of Medicine, Washington University in St. Louis, . St. Louis Missouri
| | - Dimitrios Alexopoulos
- Department of Neurology, School of Medicine, Washington University in St. Louis, . St. Louis Missouri
| | - David Loseille
- Department of Neurology, School of Medicine, Washington University in St. Louis, . St. Louis Missouri
| | - Tara Smyser
- Department of Psychiatry, School of Medicine, Washington University in St. Louis, . St Louis, Missouri
| | - Cynthia E Rogers
- Department of Psychiatry, School of Medicine, Washington University in St. Louis, . St Louis, Missouri
| | - Barbara Warner
- Department of Pediatrics, School of Medicine, Washington University in St. Louis, St. Louis, Missouri
| | - Christopher D Smyser
- Department of Neurology, School of Medicine, Washington University in St. Louis, . St. Louis Missouri
| | - Deanna M Barch
- Department of Psychiatry, School of Medicine, Washington University in St. Louis, . St Louis, Missouri
- Department of Psychological & Brain Sciences, School of Medicine, Washington University in St. Louis, School of Medicine, St Louis, Missouri
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Cohn AM, Sedani A, Niznik T, Alexander A, Lowery B, McQuoid J, Campbell J. Population and Neighborhood Correlates of Cannabis Dispensary Locations in Oklahoma. CANNABIS (ALBUQUERQUE, N.M.) 2023; 6:99-113. [PMID: 37287730 PMCID: PMC10212267 DOI: 10.26828/cannabis/2023.01.008] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Background Cannabis dispensaries have proliferated exponentially in Oklahoma since the state legalized medical cannabis in 2018. Oklahoma is unique from many other legalized states given its high number of lower income, rural, and uninsured residents, who may seek medical cannabis as an alternative to traditional medical treatment. Methods This study examined demographic and neighborhood characteristics associated with dispensary density (n = 1,046 census tracts) in Oklahoma. Results Compared to census tracts with no dispensaries, those with at least one dispensary had a higher proportion of uninsured individuals living below the poverty level and a greater number of hospitals and pharmacies. Almost half (42.35%) of census tracts with at least one dispensary were classified as a rural locale. In fully adjusted models, percent uninsured, percent of household rentals, and the number of schools and pharmacies were positively associated with greater number of cannabis dispensaries, while the number of hospitals was negatively associated. In the best fitting interaction models, dispensaries were predominant in areas with a higher percentage of uninsured residents and no pharmacies, suggesting that cannabis retailers may capitalize on the health needs of communities with limited healthcare outlets or access to medical treatment. Conclusions Policies and regulatory actions that seek to decrease disparities in dispensary locations should be considered. Future studies should examine whether people living in communities with a scarcity of health resources are more likely to associate cannabis with medical uses than those living in communities with more resources.
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Affiliation(s)
- Amy M Cohn
- Department of Pediatrics, College of Medicine, University of Oklahoma Health Sciences Center
- TSET Health Promotion Research Center, Stephenson Cancer Center, University of Oklahoma Health Sciences Center
| | - Ami Sedani
- Department of Biostatistics and Epidemiology, Hudson College of Public Health, University of Oklahoma Health Sciences Center
| | - Taylor Niznik
- Department of Pediatrics, College of Medicine, University of Oklahoma Health Sciences Center
| | - Adam Alexander
- Department of Pediatrics, College of Medicine, University of Oklahoma Health Sciences Center
- Department of Family and Preventive Medicine, University of Oklahoma Health Sciences Center
| | - Bryce Lowery
- Regional + City Planning, Christopher C. Gibbs College of Architecture, University of Oklahoma
| | - Julia McQuoid
- Department of Pediatrics, College of Medicine, University of Oklahoma Health Sciences Center
- Department of Family and Preventive Medicine, University of Oklahoma Health Sciences Center
| | - Janis Campbell
- Department of Biostatistics and Epidemiology, Hudson College of Public Health, University of Oklahoma Health Sciences Center
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Nassel A, Wilson-Barthes MG, Howe CJ, Napravnik S, Mugavero MJ, Agil D, Dulin AJ. Characterizing the neighborhood risk environment in multisite clinic-based cohort studies: A practical geocoding and data linkages protocol for protected health information. PLoS One 2022; 17:e0278672. [PMID: 36580446 PMCID: PMC9799318 DOI: 10.1371/journal.pone.0278672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Accepted: 11/21/2022] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Maintaining patient privacy when geocoding and linking residential address information with neighborhood-level data can create challenges during research. Challenges may arise when study staff have limited training in geocoding and linking data, or when non-study staff with appropriate expertise have limited availability, are unfamiliar with a study's population or objectives, or are not affordable for the study team. Opportunities for data breaches may also arise when working with non-study staff who are not on-site. We detail a free, user-friendly protocol for constructing indices of the neighborhood risk environment during multisite, clinic-based cohort studies that rely on participants' protected health information. This protocol can be implemented by study staff who do not have prior training in Geographic Information Systems (GIS) and can help minimize the operational costs of integrating geographic data into public health projects. METHODS This protocol demonstrates how to: (1) securely geocode patients' residential addresses in a clinic setting and match geocoded addresses to census tracts using Geographic Information System software (Esri, Redlands, CA); (2) ascertain contextual variables of the risk environment from the American Community Survey and ArcGIS Business Analyst (Esri, Redlands, CA); (3) use geoidentifiers to link neighborhood risk data to census tracts containing geocoded addresses; and (4) assign randomly generated identifiers to census tracts and strip census tracts of their geoidentifiers to maintain patient confidentiality. RESULTS Completion of this protocol generates three neighborhood risk indices (i.e., Neighborhood Disadvantage Index, Murder Rate Index, and Assault Rate Index) for patients' coded census tract locations. CONCLUSIONS This protocol can be used by research personnel without prior GIS experience to easily create objective indices of the neighborhood risk environment while upholding patient confidentiality. Future studies can adapt this protocol to fit their specific patient populations and analytic objectives.
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Affiliation(s)
- Ariann Nassel
- Lister Hill Center for Health Policy, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Marta G. Wilson-Barthes
- Center for Epidemiologic Research, Department of Epidemiology, Brown University School of Public Health, Providence, Rhode Island, United States of America
| | - Chanelle J. Howe
- Center for Epidemiologic Research, Department of Epidemiology, Brown University School of Public Health, Providence, Rhode Island, United States of America
| | - Sonia Napravnik
- Division of Infectious Diseases, Department of Medicine, School of Medicine, Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Michael J. Mugavero
- Division of Infectious Diseases, Department of Medicine, Center for AIDS Research, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Deana Agil
- Division of Infectious Diseases, Department of Medicine, School of Medicine, Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Akilah J. Dulin
- Center for Health Promotion and Health Equity, Department of Behavioral and Social Sciences, Brown University School of Public Health, Providence, Rhode Island, United States of America
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Brady RG, Rogers CE, Prochaska T, Kaplan S, Lean RE, Smyser TA, Shimony JS, Slavich GM, Warner BB, Barch DM, Luby JL, Smyser CD. The Effects of Prenatal Exposure to Neighborhood Crime on Neonatal Functional Connectivity. Biol Psychiatry 2022; 92:139-148. [PMID: 35428496 PMCID: PMC9257309 DOI: 10.1016/j.biopsych.2022.01.020] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Revised: 12/20/2021] [Accepted: 01/29/2022] [Indexed: 02/08/2023]
Abstract
BACKGROUND Maternal exposure to adversity during pregnancy has been found to affect infant brain development; however, the specific effect of prenatal crime exposure on neonatal brain connectivity remains unclear. Based on existing research, we hypothesized that living in a high-crime neighborhood during pregnancy would affect neonatal frontolimbic connectivity over and above other individual- and neighborhood-level adversity and that these associations would be mediated by maternal psychosocial stress. METHODS Participants included 399 pregnant women, recruited as part of the eLABE (Early Life Adversity, Biological Embedding, and Risk for Developmental Precursors of Mental Disorders) study. In the neonatal period, 319 healthy, nonsedated infants were scanned using resting-state functional magnetic resonance imaging (repetition time = 800 ms; echo time = 37 ms; voxel size = 2.0 × 2.0 × 2.0 mm3; multiband = 8) on a Prisma 3T scanner and had at least 10 minutes of high-quality data. Crime data at the block group level were obtained from Applied Geographic Solution. Linear regressions and mediation models tested associations between crime, frontolimbic connectivity, and psychosocial stress. RESULTS Living in a neighborhood with high property crime during pregnancy was related to weaker neonatal functional connectivity between the thalamus-anterior default mode network (aDMN) (β = -0.15, 95% CI = -0.25 to -0.04, p = .008). Similarly, high neighborhood violent crime was related to weaker functional connectivity between the thalamus-aDMN (β = -0.16, 95% CI = -0.29 to -0.04, p = .01) and amygdala-hippocampus (β = -0.16, 95% CI = -0.29 to -0.03, p = .02), controlling for other types of adversity. Psychosocial stress partially mediated relationships between the thalamus-aDMN and both violent and property crime. CONCLUSIONS These findings suggest that prenatal exposure to crime is associated with weaker neonatal limbic and frontal functional brain connections, providing another reason for targeted public policy interventions to reduce crime.
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Affiliation(s)
- Rebecca G Brady
- Division of Biology and Biomedical Sciences, Washington University School of Medicine, St. Louis, Missouri; Department of Neurology, Washington University School of Medicine, St. Louis, Missouri.
| | - Cynthia E Rogers
- Department of Pediatrics, Washington University School of Medicine, St. Louis, Missouri; Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri
| | - Trinidi Prochaska
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri
| | - Sydney Kaplan
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri
| | - Rachel E Lean
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri
| | - Tara A Smyser
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri
| | - Joshua S Shimony
- Mallinckrot Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri
| | - George M Slavich
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, California
| | - Barbara B Warner
- Department of Pediatrics, Washington University School of Medicine, St. Louis, Missouri
| | - Deanna M Barch
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri; Mallinckrot Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri; Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, Missouri
| | - Joan L Luby
- Department of Pediatrics, Washington University School of Medicine, St. Louis, Missouri; Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri
| | - Christopher D Smyser
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri; Department of Pediatrics, Washington University School of Medicine, St. Louis, Missouri; Mallinckrot Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri
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