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Regional variations in mortality and causes of death in Israel, 2009–2013

Overview of attention for article published in Israel Journal of Health Policy Research, August 2017
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Title
Regional variations in mortality and causes of death in Israel, 2009–2013
Published in
Israel Journal of Health Policy Research, August 2017
DOI 10.1186/s13584-017-0164-1
Pubmed ID
Authors

Ethel-Sherry Gordon, Ziona Haklai, Jill Meron, Miriam Aburbeh, Inbal Weiss Salz, Yael Applbaum, Nehama F. Goldberger

Abstract

Regional variations in mortality can be used to study and assess differences in disease prevalence and factors leading to disease and mortality from different causes. To enable this comparison, it is important to standardize the mortality data to adjust for the effects of regional population differences in age, nationality and country of origin. Standardized mortality ratios (SMR) were calculated for the districts and sub-districts in Israel, for total mortality by gender as well as for leading causes of death and selected specific causes. Correlations were assessed between these SMRs, regional disease risk factors and socio-economic characteristics. Implications for health policy were then examined. Total mortality in the Northern District of Israel was not significantly different from the national average; but the Haifa, Tel Aviv, and Southern districts were significantly higher and the Jerusalem, Central, Judea and Samaria districts were lower. Cancer SMR was significantly lower in Jerusalem and not significantly higher in any region. Heart disease and diabetes SMRs were significantly higher in many sub-districts in the north of the country and lower in the south. SMRs for septicemia, influenza/pneumonia, and for cerebrovascular disease were higher in the south. Septicemia was also significantly higher in Tel Aviv and lower in the North, Haifa and Jerusalem districts. SMRs for accidents, particularly for motor vehicle accidents were significantly higher in the peripheral Zefat and Be'er Sheva sub-districts. The SMR, adjusted for age and ethnicity, is a good method for identifying districts that differ significantly from the national average. Some of the regional differences may be attributed to differences in the completion of death certificates. This needs to be addressed by efforts to improve reporting of causes of death, by educating physicians. The relatively low differences found after adjustment, show that factors associated with ethnicity may affect mortality more than regional factors. Recommendations include encouraging good eating habits, exercise, cancer screening, control of hypertension, reduction of smoking and improving road infrastructure and emergency care access in the periphery.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 54 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 17%
Student > Ph. D. Student 6 11%
Student > Master 4 7%
Student > Doctoral Student 4 7%
Student > Bachelor 4 7%
Other 9 17%
Unknown 18 33%
Readers by discipline Count As %
Medicine and Dentistry 10 19%
Psychology 5 9%
Nursing and Health Professions 4 7%
Immunology and Microbiology 2 4%
Sports and Recreations 2 4%
Other 10 19%
Unknown 21 39%
Attention Score in Context

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 01 August 2017.
All research outputs
#19,654,541
of 24,171,511 outputs
Outputs from Israel Journal of Health Policy Research
#427
of 606 outputs
Outputs of similar age
#248,038
of 320,861 outputs
Outputs of similar age from Israel Journal of Health Policy Research
#10
of 13 outputs
Altmetric has tracked 24,171,511 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 606 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 13th percentile – i.e., 13% 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 320,861 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 13 others from the same source and published within six weeks on either side of this one. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.