Morbidity Dataset of High Risk Patients with Hypertension
over 60a in Xiji County of China
Zhang, M. X.1* Wang, Y. J.1 Li, H. 2 Wang, X. Z. 3
1. School of Geography and
Planning, Ningxia University, Yinchuan 750021, China;
2. School of Geography and Tourism,
Shaanxi Normal University, Xi??an 710119, China;
3. Department of Cardiology,
General Hospital of Ningxia Medical University, Yinchuan 750006, China
Abstract: By selecting the
patients?? data from hospitals of Xiji county and
surrounding hospitals in Ningxia Hui autonomous region of China, the incidence
rate of high-risk hypertensive patients in towns of Xiji county from 2015 to
2016 were analyzed. The incidence rate of hypertension in various towns of Xiji
county was charted by ArcGIS. Different incidence grades were used to indicate
the incidence rate of high risk patients with hypertension over 60a among
towns, and to get dataset of high-risk elderly patients in Xiji county of China,
to reveal the spatio-temporal distribution of elderly hypertension in Xiji
county and to provide a scientific basis for the follow-up development of
effective prevention and control measures. The spatial data in the dataset
includes the vector data of national highway, provincial highway and towns in
Xiji county. Data in the table include (1) Statistics on number of monthly
elderly patients with high-risk hypertension in Xiji county from 2015 to 2016;
(2) Statistics on the number of elderly patients with high-risk hypertension in
each township of Xiji county from 2015 to 2016; (3) Statistics on the morbidity
of high-risk elderly patients with hypertension in each township of Xiji county
from 2015 to 2016. The dataset is archived in .shp and .xls formats in 25 data
files with the data size 302 KB.
Keywords: Xiji county; Elderly people; High-risk hypertension
patients; Morbidity
DOI:
https://doi.org/10.3974/geodp.2021.02.14
CSTR: https://cstr.escience.org.cn/CSTR:20146.14.2021.02.14
Dataset Availability Statement:
The
dataset supporting this paper was published and is accessible through the Digital Journal of Global Change Data
Repository at: https://doi.org/10.3974/geodb.2021.03.11.V1 or https://cstr.escience.org.cn/CSTR:20146.11.2021.03.11.V1.
1 Introduction
According
to the World Health Organization, the number of people died with cardiovascular
and cerebrovascular diseases was as high as 15 million every year, ranking the
first among all kinds of death causes, the characteristics of high morbidity,
high disability rate and high mortality[1]. Xiji county is located
in the south of Ningxia Hui autonomous region of China, at the West foot of
Liupan Mountain and the arid hilly region of the Loess Plateau, with low
terrain in the South and high terrain in the north, with altitude of 1,688-2,633 m. By the end
of 2015, the residental population in Xiji county was 359,085, of which the Han
nationality accounted for 42.57%, the Hui nationality accounted for 57.40%, and
the Hui nationality was more than the Han nationality[4]. Xiji
county has three towns and 16 townships[5]. Datasets of elderly
hypertension patients in Xiji county represented the incidence and morbidity of
elderly hypertensive high-risk patients from 2015 to 2016, and revealed the spatio-temporal distribution
of elderly hypertension patients.
2 Metadata of the Dataset
The
metadata of the High risk analysis dataset on elderly patients with hypertension
In Xiji, Ningxia of China (2015-2016) [7] is summarized in Table 1.
It includes the full name, short name, authors, year of the dataset, data
format, data size, data files, data publisher, and data sharing policy, etc.
Table 1 Metadata
summary of the High risk analysis dataset on elderly patients with hypertension
In Xiji, Ningxia of China (2015-2016)
Items
|
Description
|
Dataset full name
|
High risk analysis dataset on elderly patients with hypertension
In Xiji, Ningxia of China (2015-2016)
|
Dataset short name
|
ElderlyPatients_HypertensionXiji
|
Authors
|
Zhang,
M. X. L-8674-2018, Ningxia University, 1014279339@qq.com
Wang,
Y. J. AAO-8514-2021, Ningxia University, wyj8690@163.com
|
|
Li,
H. L-8078-2018, Shaanxi Normal University, 584001860@qq.com
Wang,
X. Z., Department of Cardiology, General Hospital of Ningxia Medical
University,
pingwa1967@sina.com
|
Geographical region
|
Xiji
county
Year 2015, 2016
|
Data format
|
.shp,.xls
Data
size
|
302 KB
(131 KB after compression)
|
Data files
|
The
dataset comprises two parts. One is the spatial data including the vector
data of national highway, provincial highway and township in Xiji county of
Ningxia. The second are the number of monthly cases in Xiji county between
2015 to 2016, the number of cases in Xiji county between 2015 to 2016, the
table of morbidity over 60a in Xiji county between 2015 to 2016
|
Foundation
|
Ningxia
Natural Science Foundation of China (2020AAC03114)
|
Data publisher
|
Global Change Research Data Publishing &
Repository, http://www.geodoi.ac.cn
|
Address
|
No.
11A, Datun Road, Chaoyang District, Beijing 100101, China
|
Data sharing policy
|
Data from
the Global Change Research Data Publishing & Repository includes metadata, datasets
(in the Digital Journal of Global Change Data Repository), and
publications (in the Journal of Global Change Data & Discovery). Data sharing policy
includes: (1) Data are openly available and can be free downloaded via the
Internet; (2) End users are encouraged to use Data subject to
citation; (3) Users, who are by definition also value-added service
providers, are welcome to redistribute Data subject to written permission
from the GCdataPR Editorial Office and the issuance of a Data redistribution
license; and (4) If Data are used to compile new
datasets, the ??ten per cent principal?? should be followed such that Data
records utilized should not surpass 10% of the new dataset contents, while
sources should be clearly noted in suitable places in the new dataset[8]
|
Communication and searchable system
|
DOI, CSTR, Crossref, DCI, CSCD, CNKI, SciEngine, WDS/ISC, GEOSS
|
3 Data Statistics
Taking
Xiji county of Ningxia Hui autonomous region of China as the geographical
statistical unit, the case data of permanent residents in Xiji county were
treated in related hospitals and surrounding hospitals in Ningxia, were
selected to calculate the incidence of hypertension in each town. The clinical
data of elderly patients with hypertension for circulatory system diseases in
related general hospitals of Ningxia from January 2015 to December 2016 were
selected to conduct a retrospective analysis on the general incidence,
etiological composition, clinical manifestations, risk factors, target organ
damage and other influencing factors of elderly patients with hypertension. In
order to analyze the elderly hypertension high-risk patients in Xiji county, The
main selection criteria was:
(1) Hypertension level 1, and is accompanied by
three or more other risk factors or target organ damage;
(2) Secondary hypertension with three or more
other risk factors or target organ damage; Grade 3 hypertension without any
risk factors and medical history.
The main information
include: gender, age, address, onset time, onset address of elderly patients
with high risk. To provide scientific basis for formulating prevention and
control strategies and measures through the analysis of the influence factors
on the incidence of hypertension in the elderly.
According to the place of residence of the
affected population, the total number of elderly people over 60a were
registered by the statistical department of each town. The incidence rate in
town was calculated by equation (1). The incidence of hypertension in certain
region is I, the number of patients
in this area is A, the total population
of the area is S. The incidence rate
of cerebrovascular diseases among people over 60a in each town of Xiji was
obtained as follow.
I=A??S??1000?? (1)
4 Data Results
4.1 Temporal Distribution of
High Risk Elderly Patients with Hypertension in Xiji
The
data of population incidence in Xiji county from January 2015 to December 2016
were collected monthly. The data of the incidence of high-risk elderly patients
in each month were collected and the distribution regularity of the morbidity
was estimated. The regularity of morbidity of hypertension changed over time.
As shown in Table 2, the number of cases in March is the highest, followed by
June and November again. The number of cases in September is the least,
followed by February.
Table 2 The
number of monthly cases in Xiji county between 2015 to 2016 (person)
Year
|
Jan
|
Feb
|
Mar
|
Apr
|
May
|
Jun
|
Jul
|
Aug
|
Sept
|
Oct
|
Nov
|
Dec
|
2015
|
55
|
45
|
67
|
56
|
53
|
61
|
53
|
52
|
44
|
45
|
57
|
49
|
2016
|
57
|
46
|
68
|
59
|
53
|
64
|
50
|
53
|
46
|
47
|
58
|
54
|
4.2 Spatial Distribution of Morbidity
of Elderly Hypertensive Patients in Xiji
Through
the statistics of the incidence of different hypertension cases in Xiji county,
according to the place of residence of the affected population, the total
population of each town was inquired. Cartographic expression of incidence and
incidence rate of hypertension were given according to the incidence of
different ages in different towns of Xiji county. The different incidence data
were classified by using the hierarchical color mapping method, and the different
grades of color were taken to distinguish different towns. The morbidity of
hypertension in different towns were divided into six levels in different
years. The morbidity is high in Xinglong, Jiangtai and Jiqiang in general, and
morbidity is low in Shagou, and the incidence of township in Pingfeng is low.
As shown in Figure 1 and Figure 2.
Figure 1 Thematic map of cases in Xiji county from 2015 to 2016
Figure 2 Thematic map of morbidity rate of cases in Xiji county from 2015
to 2016
5 Discussion and Conclusion
Based
on geographical statistical units, the number of high risk patients with
hypertension in each town of Xiji was calculated, through the analysis of the
elderly patients at high risk of hypertension incidence data, and comprehensive
analysis of various factors on the risk assessment of elderly patients, to
explore the incidence of the elderly patients at high risk of hypertension. By
sorting out the occurrence regularity of elderly patients with high risk of
hypertension in different seasons and each month, the distribution regularity
of hypertension disease was explored, and the regional environmental factors
affecting the occurrence of elderly patients with high risk of hypertension
were analyzed.
This study is the first effect of regional
geographical environment on human blood pressure health and regional
geographical environment changes on the incidence of human hypertension disease
in small scale counties in the western region of China with better ecological
environment protection. The aim was to raise public awareness, reduce the
incidence of adverse cardiovascular events through reasonable protection,
thereby reducing the economic burden on families and society, and to provide
reasonable recommendations for the government and relevant ministries to
develop long-term early warning and prevention policies.
The prevalence of hypertension is higher in cold
regions than in warm regions[12], and higher altitudes are higher than lower
altitudes. The main reason is that when the temperature drops in winter, the
level of adrenaline in the body rises and the blood vessels on the surface of
the body contract to reduce heat release. At the same time, adrenaline may
accelerate the heart rate and increase the output of the heart, which will lead
to the increase of blood pressure. National hypertension epidemiological survey
shows that in north China region of minorities (Manchus, Mongol and Hui
Nationality) population of hypertension prevalence is south (Miao, Zhuang,
Bouyei, Tujia, Hani, Yi Nationality), high trend for lower from north to south,
is likely to be the north cold lead to peripheral vascular contraction, blood
pressure to rise. The elderly are also particularly poor at adapting to the
environment. When the temperature begins to plummet, their blood vessels will
constrict, reducing blood flow and ultimately increasing the heart??s ability to
load. However, when the heart and brain vessels contracted after cold
stimulation, their collateral circulation supply decreased, and the
establishment and opening of collateral circulation were affected. When
cerebral thrombosis or watershed infarction occurred, collateral circulation
could not effectively play its protective role, and it was easy to form infarction
lesions. At the same time, cold stimulation can induce coronary artery spasm
and lead to acute coronary insufficiency and even myocardial infarction[14].
Through sorting of the hypertension cases in
Xiji county, in terms of population distribution, we found that the elderly
patients with high risk of hypertension showed an increasing trend with the
increase of age. In this study, patient over 70a are more likely to be affected
by temperature and have cardiovascular and cerebrovascular events. In this
study, primary data were obtained from hospitals, which were reliable. However,
it is estimated that the data were incomplete in the statistics. The data were
screened by professional cardiologists, and the data selection was basically
reliable.
Author Contributions
Zhang, M. X. designed the algorithms of dataset. Wang, Y.
J. Li, H. wrote the data paper. Wang, X. Z. contributed to the data processing
and analysis.
Conflicts
of Interest
The authors declare no conflicts
of interest.
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