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X Demographics
Mendeley readers
Attention Score in Context
| Title |
The influence of temperature on mortality and its Lag effect: a study in four Chinese cities with different latitudes
|
|---|---|
| Published in |
BMC Public Health, May 2016
|
| DOI | 10.1186/s12889-016-3031-z |
| Pubmed ID | |
| Authors |
Junzhe Bao, Zhenkun Wang, Chuanhua Yu, Xudong Li |
| Abstract |
Global climate change is one of the most serious environmental issues faced by humanity, and the resultant change in frequency and intensity of heat waves and cold spells could increase mortality. The influence of temperature on human health could be immediate or delayed. Latitude, relative humidity, and air pollution may influence the temperature-mortality relationship. We studied the influence of temperature on mortality and its lag effect in four Chinese cities with a range of latitudes over 2008-2011, adjusting for relative humidity and air pollution. We recorded the city-specific distributions of temperature and mortality by month and adopted a Poisson regression model combined with a distributed lag nonlinear model to investigate the lag effect of temperature on mortality. We found that the coldest months in the study area are December through March and the hottest months are June through September. The ratios of deaths during cold months to hot months were 1.43, 1.54, 1.37 and 1.12 for the cities of Wuhan, Changsha, Guilin and Haikou, respectively. The effects of extremely high temperatures generally persisted for 3 days, whereas the risk of extremely low temperatures could persist for 21 days. Compared with the optimum temperature of each city, at a lag of 21 days, the relative risks (95 % confidence interval) of extreme cold temperatures were 4.78 (3.63, 6.29), 2.38 (1.35, 4.19), 2.62 (1.15, 5.95) and 2.62 (1.44, 4.79) for Wuhan, Changsha, Guilin and Haikou, respectively. The respective risks were 1.35 (1.18, 1.55), 1.19 (0.96, 1.48), 1.22 (0.82, 1.82) and 2.47 (1.61, 3.78) for extreme hot temperatures, at a lag of 3 days. Temperature-mortality relationships vary among cities at different latitudes. Local governments should establish regional prevention and protection measures to more effectively confront and adapt to local climate change. The effects of hot temperatures predominantly occur over the short term, whereas those of cold temperatures can persist for an extended number of days. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 101 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 101 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 17 | 17% |
| Student > Ph. D. Student | 14 | 14% |
| Student > Master | 12 | 12% |
| Student > Doctoral Student | 7 | 7% |
| Lecturer > Senior Lecturer | 2 | 2% |
| Other | 11 | 11% |
| Unknown | 38 | 38% |
| Readers by discipline | Count | As % |
|---|---|---|
| Environmental Science | 17 | 17% |
| Medicine and Dentistry | 12 | 12% |
| Nursing and Health Professions | 6 | 6% |
| Social Sciences | 6 | 6% |
| Engineering | 3 | 3% |
| Other | 15 | 15% |
| Unknown | 42 | 42% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 May 2016.
All research outputs
#21,264,673
of 23,881,329 outputs
Outputs from BMC Public Health
#14,502
of 15,466 outputs
Outputs of similar age
#259,344
of 301,242 outputs
Outputs of similar age from BMC Public Health
#176
of 184 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 15,466 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.3. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 301,242 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 184 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.