Risk factors for mental disorders in patients with hypertensive intracerebral hemorrhage following neurosurgical treatment

ObjectiveTo conduct a systematic review and meta-analysis of studies reporting on risk factors according to location of the intracerebral hemorrhage.MethodsWe searched PubMed and Embase for cohort and case-control studies reporting ≥100 patients with spontaneous intracerebral hemorrhage that specified the location of the hematoma and reported associations with risk factors published until June 27, 2019. Two authors independently extracted data on risk factors. Estimates were pooled with the generic variance-based random-effects method.ResultsAfter screening 10,013 articles, we included 42 studies totaling 26,174 patients with intracerebral hemorrhage (9,141 lobar and 17,033 nonlobar). Risk factors for nonlobar intracerebral hemorrhage were hypertension (risk ratio [RR] 4.25, 95% confidence interval [CI] 3.05–5.91, I2 = 92%), diabetes mellitus (RR 1.35, 95% CI 1.11–1.64, I2 = 37%), male sex (RR 1.63, 95% CI 1.25–2.14, I2 = 61%), alcohol overuse (RR 1.48, 95% CI 1.21–1.81, I2 = 19%), underweight (RR 2.12, 95% CI 1.12–4.01, I2 = 31%), and being a Black (RR 2.83, 95% CI 1.02-7.84, I2 = 96%) or Hispanic (RR 2.95, 95% CI 1.69-5.14, I2 = 71%) participant compared with being a White participant. Hypertension, but not any of the other risk factors, was also a risk factor for lobar intracerebral hemorrhage (RR 1.83, 95% CI 1.39–2.42, I2 = 76%). Smoking, hypercholesterolemia, and obesity were associated with neither nonlobar nor lobar intracerebral hemorrhage.ConclusionsHypertension is a risk factor for both nonlobar and lobar intracerebral hemorrhage, although with double the effect for nonlobar intracerebral hemorrhage. Diabetes mellitus, male sex, alcohol overuse, underweight, and being a Black or Hispanic person are risk factors for nonlobar intracerebral hemorrhage only. Hence, the term hypertensive intracerebral hemorrhage for nonlobar intracerebral hemorrhage is not appropriate.

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Risk Factors for Early Death in Acute Ischemic Stroke and Intracerebral Hemorrhage

Stroke ◽

10.1161/01.str.30.11.2326 ◽

1999 ◽

Vol 30 (11) ◽

pp. 2326-2330 ◽

Cited By ~ 49

Author(s):

K. S. Wong

Keyword(s):

Risk Factors ◽

Ischemic Stroke ◽

Intracerebral Hemorrhage ◽

Acute Ischemic Stroke ◽

Early Death

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Low Birth Weight Prevalence in Children Diagnosed with Neurodevelopmental Disorders in Dubai

Global Pediatric Health ◽

10.1177/2333794x211031782 ◽

2021 ◽

Vol 8 ◽

pp. 2333794X2110317

Author(s):

Faisal A. Nawaz ◽

Meshal A. Sultan

Keyword(s):

Risk Factors ◽

Birth Weight ◽

Mental Disorders ◽

Low Birth Weight ◽

Neurodevelopmental Disorders ◽

Autism Spectrum ◽

High Birth Weight ◽

Perinatal Risk Factors ◽

Perinatal Risk ◽

The Impact

The aim of this study is to evaluate the prevalence of low birth weight and other perinatal risk factors in children diagnosed with neurodevelopmental disorders. This is one of the first studies in the Arabian Gulf region focused on the contribution of these factors toward the development of various disorders such as attention-deficit/hyperactivity disorder, autism spectrum disorder, and other mental disorders. This descriptive study was based on qualitative data analysis. We reviewed retrospective information from the electronic medical records of 692 patients in Dubai, United Arab Emirates. The prevalence of low birth weight in children with mental disorders was significantly higher as compared to the general population (16% vs 6% respectively). Furthermore, other risk factors, including high birth weight and preterm birth were noted to have a significant association with neurodevelopmental disorders. Future research on the impact of perinatal risk factors will contribute to advancement of early intervention guidelines.

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Prevalence of Mental Disorders by Socioeconomic Status in Australia: A Cross-Sectional Epidemiological Study

American Journal of Health Promotion ◽

10.1177/0890117120968656 ◽

2020 ◽

pp. 089011712096865

Author(s):

Rubayyat Hashmi ◽

Khorshed Alam ◽

Jeff Gow ◽

Sonja March

Keyword(s):

Mental Health ◽

Risk Factors ◽

Socioeconomic Status ◽

Mental Disorders ◽

National Health Survey ◽

Cross Sectional ◽

Lower Odds ◽

Socioeconomic Groups ◽

Income Groups ◽

Weighted Prevalence

Purpose: To present the prevalence of 3 broad categories of mental disorder (anxiety-related, affective and other disorders) by socioeconomic status and examine the associated socioeconomic risk factors of mental disorders in Australia. Design: A population-based, cross-sectional national health survey on mental health and its risk factors across Australia. Setting: National Health Survey (NHS), 2017-2018 conducted by the Australian Bureau of Statistics (ABS) Participants: Under aged: 4,945 persons, Adult: 16,370 persons and total: 21,315 persons Measures: Patient-reported mental disorder outcomes Analysis: Weighted prevalence rates by socioeconomic status (equivalised household income, education qualifications, Socio-Economic Index for Areas (SEIFA) scores, labor force status and industry sector where the adult respondent had their main job) were estimated using cross-tabulation. Logistic regression utilizing subsamples of underage and adult age groups were analyzed to test the association between socioeconomic status and mental disorders. Results: Anxiety-related disorders were the most common type of disorders with a weighted prevalence rate of 20.04% (95% CI: 18.49-21.69) for the poorest, 13.85% (95% CI: 12.48-15.35) for the richest and 16.34% (95% CI: 15.7-17) overall. The weighted prevalence rate for mood/affective disorders were 20.19% (95% CI: 18.63-21.84) for the poorest, 9.96% (95% CI: 8.79-11.27) for the richest, and 13.57% (95% CI: 12.99-14.17) overall. Other mental disorders prevalence were for the poorest: 9.07% (95% CI: 7.91-10.39), the richest: 3.83% (95% CI: 3.14-4.66), and overall: 5.93% (95% CI: 5.53-6.36). These patterns are also reflected if all mental disorders were aggregated with the poorest: 30.97% (95% CI: 29.15-32.86), the richest: 19.59% (95% CI: 18.02-21.26), and overall: 23.93% (95% CI: 23.19-24.69). The underage logistic regression model showed significant lower odds for the middle (AOR: 0.75, 95% CI: 0.53 -1.04, p < 0.1), rich (AOR: 0.71, 95% CI: 0.5-0.99, p < 0.05) and richest (AOR: 0.6, 95% CI: 0.41-0.89, p < 0.01) income groups. Similarly, in the adult logistic model, there were significant lower odds for middle (AOR: 0.84, 95% CI: 0.72-0.98, p < 0.05), rich (AOR: 0.73, 95% CI: 0.62-0.86, p < 0.01) and richest (AOR: 0.76, 95% CI: 0.63-0.91, p < 0.01) income groups. Conclusion: The prevalence of mental disorders in Australia varied significantly across socioeconomic groups. Knowledge of different mental health needs in different socioeconomic groups can assist in framing evidence-based health promotion and improve the targeting of health resource allocation strategies.

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