| Literature DB >> 27399733 |
Yongjun Cao1, Xia Wang2,3, Danni Zheng4,5, Thompson Robinson6, Daqing Hong7, Sarah Richtering8, Tzen Hugh Leong9, Abdul Salam10,11, Craig Anderson12,13, Maree L Hackett14,15.
Abstract
BACKGROUND/AIMS: An influence of climate upon stroke risk is biologically plausible and supported by epidemiological evidence. We aimed to determine whether air pressure (AP) and humidity are associated with hospital stroke admission.Entities:
Keywords: air pressure; humidity; stroke; systematic review; weather
Mesh:
Year: 2016 PMID: 27399733 PMCID: PMC4962216 DOI: 10.3390/ijerph13070675
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Figure 1Flow chart of literature search.
Characteristics of studies included in the review.
| Author and Year of Publication | Title | Location | Latitude | Year(s) of Study | Sample Size | Age (mean, y) Female (%) | Only First-Ever Stroke | Stroke Subtype | Study Type | Study Quality |
|---|---|---|---|---|---|---|---|---|---|---|
| Abe 2008 [ | Effects of meteorological factors on the onset of subarachnoid hemorrhage: a time-series analysis | Japan, Tokyo | 35.6833° N | 2005 | 1729 | 63.3 Female (60%) | No | SAH | Population study | ACDEF |
| Dawson 2008 [ | Associations between meteorological variables and acute stroke hospital admissions in the west of Scotland | United Kingdom, Glasgow | 55.8580° N | 1990–2005 | 6389 | 71.2 Female (53%) | No | IS and ICH | Stroke registry | ACDE |
| Feigin 2000 [ | A population-based study of the associations of stroke occurrence with weather parameters in Siberia, Russia (1982–1992) | Russia, Siberia | 61.0137° N | 1982–1992 | 2208 | Age range: 25–74 Female (57%) | Yes | IS, ICH and SAH | Stroke registry | ABCEF |
| Han 2015 [ | Effect of seasonal and monthly variation in weather and air pollution factors on stroke incidence in Seoul, Korea | South Korea, Seoul | 37.5667° N | 2004–2013 | 3001 | Age >19 Female (49%) | No | IS and ICH | Stroke registry | ACDEF |
| Jimenez-Conde 2008 [ | Weather as a trigger of stroke: daily meteorological factors and incidence of stroke subtypes | Spain, Barcelona | 41.3833° N | 2001–2003 | 1286 | Not reported | No | IS and ICH | Population | ABDE |
| Lai 2014 [ | The association between meteorological parameters and aneurysmal subarachnoid hemorrhage: a nationwide analysis | USA, 41 states | 38.8833° N | 2001–2010 | 16,970 | Median: 53 (IQR 34-72) | No | SAH | Population | ADE |
| Lee 2008 [ | Seasonal variation in ischemic stroke incidence and association with climate, a six-year population-based study | Taiwan | 23.6978° N | 1998–2003 | 168,977 | Age range: 20–84 | No | IS | Population | AE |
| Lejeune 1994 [ | Association of occurrence of aneurysmal bleeding with meteorological variations in the north of france | France, North France region | 47.0000° N | 1989–1991 | 283 | 49.1 Female (53%) | No | SAH | Community | ABE |
| Magalhaes 2011 [ | Are stroke occurrence and outcome related to weather parameters? Results from a population-based study in Northern Portugal | Portugal, Porto | 41.1621° N | 1998–2000 | 462 | All ages Female (62%) | Yes | IS and ICH | Stroke registry | ACDEF |
| Morabito 2011 [ | Innovative approaches helpful to enhance knowledge on weather-related stroke events over a wide geographical area and a large population | Italy, Tuscany | 43.3500° N | 1997–2007 | 112,870 | All ages | No | IS, ICH and SAH | Hospital registry | ACDE |
| Oyoshi 1999 [ | Relationship between aneurysmal subarachnoid hemorrhage and climatic conditions in the subtropical region, Amami-Oshima, in Japan | Japan, Amami-Oshima | 28.2500° N | 1986–1996 | 210 | All ages, 64.3 | No | SAH | Hospital registry | AE |
Abbreviations: IS, ischemic stroke; ICH, intracerebral hemorrhage; SAH, subarachnoid hemorrhage; N, north; IQR, interquartile range; (A) presence of clear hypotheses; (B) prospective study design; (C) description of the population, at least including its size, and the gender ratio; (D) stroke assessed by CT, MRI or angiography, cerebrospinal fluid examination or autopsy; (E) a clear description of the meteorological determinants investigated, when possible including the unit of measurement; and (F) description of other risk factors for stroke.
Figure 2Meta analysis of mean daily air pressure and stroke with odds ratios qantifying the association between every one hPa increase in air pressure and stroke occurrence.
Figure 3Meta analysis of mean daily humidity and stroke with odds ratios quantifying the association between every one percent increase in humidity and stroke occurrence.