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1.
BMC Public Health ; 23(1): 1390, 2023 07 19.
Article in English | MEDLINE | ID: mdl-37468866

ABSTRACT

BACKGROUND: The COVID-19 pandemic has exacerbated the psychological burden on young people around the world and may have disproportionately large impacts for young people with disabilities. This review aims to systematically review the quantitative evidence on the impact of the COVID-19 pandemic on the mental health of young people with disabilities and evaluate the quality of included studies. METHODS: A systematic search was conducted using 5 electronic databases. The quality of the studies was assessed using the SIGN risk of bias assessment tool. A narrative synthesis was performed to synthesize the results of included studies. RESULTS: The initial search yielded 1935 studies, of which two met the eligibility criteria, one longitudinal study and one cross-sectional study, both assessed to be of low quality. In the cross-sectional study, young people with intellectual and developmental disabilities self-reported an increase in mental health symptoms. The longitudinal study found no evidence of a change in mental health symptoms from pre-pandemic to during the pandemic among young people with autism spectrum disorder, although these individuals reported negative impacts of the COVID-19 pandemic on their emotional or mental health. CONCLUSIONS: The findings of this review provide some weak evidence of a negative impact of the COVID-19 pandemic on the mental health of young people with disabilities. Importantly, the findings highlight the lack of research in this area. More research is needed to investigate the impact of the pandemic on the mental health of young disabled people, in order for governments to develop emergency preparedness plans to safeguard the well-being of this population.


Subject(s)
Autism Spectrum Disorder , COVID-19 , Disabled Persons , Humans , Adolescent , Mental Health , COVID-19/epidemiology , Pandemics , Cross-Sectional Studies , Longitudinal Studies
2.
PLoS Negl Trop Dis ; 17(2): e0010631, 2023 02.
Article in English | MEDLINE | ID: mdl-36780568

ABSTRACT

Dengue is among the fastest-spreading vector-borne infectious disease, with outbreaks often overwhelm the health system and result in huge morbidity and mortality in its endemic populations in the absence of an efficient warning system. A large number of prediction models are currently in use globally. As such, this study aimed to systematically review the published literature that used quantitative models to predict dengue outbreaks and provide insights about the current practices. A systematic search was undertaken, using the Ovid MEDLINE, EMBASE, Scopus and Web of Science databases for published citations, without time or geographical restrictions. Study selection, data extraction and management process were devised in accordance with the 'Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies' ('CHARMS') framework. A total of 99 models were included in the review from 64 studies. Most models sourced climate (94.7%) and climate change (77.8%) data from agency reports and only 59.6% of the models adjusted for reporting time lag. All included models used climate predictors; 70.7% of them were built with only climate factors. Climate factors were used in combination with climate change factors (13.4%), both climate change and demographic factors (3.1%), vector factors (6.3%), and demographic factors (5.2%). Machine learning techniques were used for 39.4% of the models. Of these, random forest (15.4%), neural networks (23.1%) and ensemble models (10.3%) were notable. Among the statistical (60.6%) models, linear regression (18.3%), Poisson regression (18.3%), generalized additive models (16.7%) and time series/autoregressive models (26.7%) were notable. Around 20.2% of the models reported no validation at all and only 5.2% reported external validation. The reporting of methodology and model performance measures were inadequate in many of the existing prediction models. This review collates plausible predictors and methodological approaches, which will contribute to robust modelling in diverse settings and populations.


Subject(s)
Dengue , Disease Outbreaks , Humans , Forecasting , Linear Models , Dengue/epidemiology
4.
Eur J Nutr ; 61(3): 1133-1142, 2022 Apr.
Article in English | MEDLINE | ID: mdl-34748060

ABSTRACT

PURPOSE: The significance of niacin in embryonic development has clinical implications in the counseling of pregnant women and may be used to inform nutrition recommendations. This study, therefore, aims to review the associations between maternal periconceptional niacin intake and congenital anomalies. METHODS: A systematic search of Ovid MEDLINE, ClinicalTrials.gov, AMED, CENTRAL, Emcare, EMBASE, Maternity & Infant Care and Google Scholar was conducted between inception and 30 September 2020. Medical subject heading terms included "nicotinic acids" and related metabolites, "congenital anomalies" and specific types of congenital anomalies. Included studies reported the association between maternal niacin intake and congenital anomalies in their offspring and reported the measure of association. Studies involved solely the women with co-morbidities, animal, in vitro and qualitative studies were excluded. The risk of bias of included studies was assessed using the Newcastle-Ottawa Scale (NOS). A random effects-restricted maximum likelihood model was used to obtain summary estimates, and multivariable meta-regression model was used to adjust study-level covariates. RESULTS: Of 21,908 retrieved citations, 14 case-control studies including 35,743 women met the inclusion criteria. Ten studies were conducted in the U.S, three in Netherlands and one in South Africa. The meta-analysis showed that expectant mothers with an insufficient niacin intake were significantly more likely to have babies with congenital abnormalities (odds ratio 1.13, 95% confidence interval 1.02-1.24) compared to mothers with adequate niacin intake. A similar association between niacin deficiency and congenital anomalies was observed (OR 1.15, 95% CI 1.03-1.26) when sensitivity analysis was conducted by quality of the included studies. Meta-regression showed neither statistically significant impact of study size (p = 0.859) nor time of niacin assessment (p = 0.127). The overall quality of evidence used is high-thirteen studies achieved a rating of six or seven stars out of a possible nine based on the NOS. CONCLUSION: Inadequate maternal niacin intake is associated with an increased risk of congenital anomalies in the offspring. These findings may have implications in dietary counseling and use of niacin supplementation during pregnancy.


Subject(s)
Niacin , Case-Control Studies , Diet , Female , Humans , Nutritional Status , Odds Ratio , Pregnancy
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