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1.
J Clin Child Adolesc Psychol ; : 1-17, 2023 Dec 20.
Article in English | MEDLINE | ID: mdl-38118056

ABSTRACT

OBJECTIVE: Sexual and gender minority (SGM) stigmatization is a key factor related to transgender adolescent mental health. While previous research has focused on direct associations between stigmatization and mental health, the present study of transgender youth, equitably recruited across the autism spectrum, examines cognitive and developmental factors in relation to the self-report of experienced and perceived SGM stigmatization. METHOD: 65 binary transgender adolescents (43% transfeminine; ages 13-21 years) were intentionally recruited across the spectrum of autism traits from no traits to full criteria autism. Participants completed measures of autism-related social differences, cognitive abilities, and self-reported directly experienced and perceived SGM stigma. Autism-related social differences, cognitive abilities, and age were studied in relation to both SGM stigma factors. RESULTS: Autism-related social differences were negatively associated with level of directly experienced SGM stigma but unassociated with perceived stigma. Greater cognitive ability was positively associated with level of perceived SGM stigma, but unassociated with report of directly experienced stigma. Older age was positively associated with level of perceived SGM stigma. There was a statistical trend toward older age positively associated with level of directly experienced stigma. CONCLUSIONS: The present study identifies candidate cognitive and developmental influences on self-reported SGM stigmatization among transgender adolescents, evenly recruited across the autism spectrum. The factors which may impact the perception and experience of stigmatization have been notably under-explored in the mental health field. The examination of these individual characteristics may allow for more precise predictive models for research with transgender youth, and ultimately, in clinical care.

2.
Am J Prev Med ; 57(2): 165-171, 2019 08.
Article in English | MEDLINE | ID: mdl-31239087

ABSTRACT

INTRODUCTION: This study presents a framework for identifying "high-risk" days for asthma attacks associated with elevated concentrations of criteria pollutants using local information to warn citizens on days when the concentrations differ from Environmental Protection Agency Air Quality Index (AQI) warnings. Studies that consider the unique mixture of pollutants and the health data specific to a city provide additional information for asthma self-management. This framework is applied to air pollution and asthma data to identify supplemental warning days in Houston, Texas. METHODS: A four-step framework was established to identify days with pollutant levels that pose meaningful increased risk for asthma attacks compared with baseline. Historical associations between 18,542 ambulance-treated asthma attacks and air pollutant concentrations in Houston, Texas (2004-2016; analyzed in 2018), were analyzed using a case-crossover study design with conditional logistic regression. Days with historically high associations between pollution and asthma attacks were identified as supplemental warning days. RESULTS: Days with 8-hour maximum ozone >66.6 parts per billion for the 3 previous days and same-day 24-hour nitrogen dioxide >19.3 parts per billion pose an RR of 15% above baseline; concentrations above these levels pose an increased risk of 15% (RR=1.15, 95% CI=1.14, 1.16) and 30% (RR=1.30, 95% CI=1.29, 1.32), respectively. These warnings add an additional 12% days per year over the AQI warnings. CONCLUSIONS: Houston uses this framework to identify supplemental air quality warnings to improve asthma self-management. Supplemental days reflect risk lower than the National Ambient Air Quality Standards and consecutive poor air quality days, differing from the AQI.


Subject(s)
Air Pollutants/toxicity , Air Pollution/adverse effects , Asthma/chemically induced , Asthma/drug therapy , Self-Management , Ambulances/statistics & numerical data , Asthma/ethnology , Cities , Cross-Over Studies , Humans , Models, Statistical , Nitrogen Dioxide/adverse effects , Nitrogen Dioxide/analysis , Ozone/adverse effects , Ozone/analysis , Particulate Matter/adverse effects , Particulate Matter/analysis , Texas
3.
J Sch Health ; 87(4): 253-261, 2017 04.
Article in English | MEDLINE | ID: mdl-28260242

ABSTRACT

BACKGROUND: Rates of uncontrolled asthma vary by demographics, space, and time. This article uses data on ambulance-treated asthma attacks in children to analyze these variations so that school districts can improve their asthma management interventions. METHODS: Incidence rates of 1826 ambulance-treated asthma attacks for children aged 5-18 years were calculated for school zones for elementary, middle, and high schools in the Houston (Texas) Independent School District (HISD). Zones with rates in the upper quartile were identified as the highest rate zones and were compared with other school zones in the district by demographics, location, and timing of attacks. RESULTS: The ambulance-treated asthma rate was respectively 5, 3, and 2 times greater in the highest rate school zones compared with all other school zones for those school levels. Ambulance-treated asthma attacks in the high-rate school zones occurred most at midday and in the evening and high-rate zones were often geographically contiguous. Schools in the high-rate zones had a higher percent of socioeconomically disadvantaged students and were more often without a school nurse. CONCLUSION: Spatial and temporal analysis of ambulance data can be valuable tools for schools to focus policy and program interventions for the students in need of improved asthma management.


Subject(s)
Ambulances/statistics & numerical data , Asthma/epidemiology , Asthma/therapy , School Health Services/organization & administration , Absenteeism , Adolescent , Asthma/ethnology , Child , Child, Preschool , Female , Health Policy , Humans , Incidence , Male , School Nursing/organization & administration , School Nursing/statistics & numerical data , Socioeconomic Factors , Spatio-Temporal Analysis , Texas/epidemiology , Time Factors
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