Go Back   This Blue Marble, a Global Current Events Discussion Forum > Health and Medicine > Flu Clinic

Flu Clinic A special wing of TBM's Health and Medicine forum set aside for discussing all issues related to influenza, pH1N1, H5N1 or seasonal. Please use the subrooms as appropriate.

Reply
 
Thread Tools Search this Thread Display Modes
Old 12-31-2014, 06:44 AM   #1
gsgs
searching for truth
 
gsgs's Avatar
 
Join Date: Sep 2008
Location: Germany
Posts: 3,743
Thanks: 3
Thanked 152 Times in 107 Posts
Default mortality statistics links

Euro-deaths 1960-2014
http://ec.europa.eu/eurostat/en/web/.../-/DEMO_MMONTH
http://ec.europa.eu/eurostat/estat-n..._mmonth.tsv.gz
16 countries with available monthly data since 1960
(plus 2 small omitted countries)
missing years are estimated from neighbors-data (i.e. France~NL+B+CH)
normed to season 2010-2011 = 1
you can see the larger amount of seasonality in Southern Countries
you can also see how the upward-trend since 1960 was stopped ~1974
in middle-Europe, although it is less pronounced than in USA 1974-1976
(look at the yearly minima in chart #17)---------------------------------------
mortalitylinks
=======UNO,WHO====================================
UNO: http://unstats.un.org/unsd/demograph...s/dyb/dyb2.htm
http://unstats.un.org/unsd/demograph.../HistTab10.csv
http://unstats.un.org/unsd/demograph.../HistTab11.pdf
since 1948, all causes , x countries
WUP2014-F04-Rural_Population.xls
2950-2050 in thousands, by sex and agegroup, every 6th year
WUP2014-F05-Total_Population.xls
WUP2014-F03-Urban_Population.xls

debates : http://www.onlinemodelunitednations.org/user/register
WHO: http://www.who.int/healthinfo/morttables/en/index.html
http://apps.who.int/healthinfo/stati...ality/whodpms/
(tables by cause,7 agegroups,selected countries, since 1979)
WHO Mortality Database Updated as of Dec.2016
----------edit 2015/01/04-----------
they also provide the raw data from their database !:
http://www.who.int/healthinfo/statis...ty_rawdata/en/
{77 google hits for that link, 128 hits on 2015/08/31,
428 hits on 2016/01/21}
Last updated: 15 Sep. 2016
Data files - Last updated: 29 March 2017

WHO-Europe causes of death with subnational regions, since 1980 ---updated July,2016 ---:
Aus(9),Bel(10),Bul(6),Cze(8),Fin(5),Fra(22),Hun(7) ,
Ire(2),NL(12),Rus(80),Spa(20),UK(37),Uzb(14)
http://data.euro.who.int/hfamdb/
[added 2015/06/05] WHO health for all database
http://data.euro.who.int/hfadb/
demographics,life style,mortality,morbidity,environment,health care,
etc. Europe,since 1970 , updated Sep.2015
Statistical year-book of the League of Nations, 1940/41, ($50)
===========================================
HMD: http://www.mortality.org/
CDC: http://www.nber.org/data/multicause.html
http://www.uni-ulm.de/mawi/mawi-mort [link dead]
Japan: http://www.stat.go.jp/english/data/chouki/02.htm
eurostat: http://appsso.eurostat.ec.europa.eu/...cd_anr&lang=en
yearly,1994-2010,37 countries,87 causes,3 sexes,22 agegroups = 3611718 numbers
download as zips, only 10 causes at once, else there are problems
18MB zipped in total, takes a while to create the data
~1 hour to download the whole database (1994-2010)
eurostat: http://appsso.eurostat.ec.europa.eu/...mmonth&lang=en
deaths by month
62 countries,1960-2013,14 months=46872 numbers ---udate 2014/02/14---
Canada: 1921-1970 http://hdl.handle.net/1974/8177
Canada 1965-1999 : http://qspace.library.queensu.ca/handle/1974/8175
Massachusetts: https://archive.org/details/annualreportvita1933mass
France:
http://www.insee.fr/fr/service/bibli...domaine=mvtpop
http://www.ined.fr/1999
http://www.ined.fr/en/everything_abo...es_since_1925/
http://www.ined.fr/en/everything_abo...th-since-1950/
240 causes, 1950-1999 , 18 circulatory causes
http://www.ined.fr/Xtradocs/1999/

Belgium:
USA: http://www.nber.org/data/multicause.html
IPUMS: http://<br /> ---added---2015/08/26...crodata_Series
freeBMD: http://www.freebmd.org.uk/cgi/EntryCounts.pl
England+Wales, 1838-1966, quarterly, for genealogy,not statistics, restricted search
they have name,age,district - not cause of death , no stat-counts
--------------------------------------------------------------------
France 1906, monthly , >80 regions
http://translate.google.de/translate...76%26bih%3D539
-------------------------------------------------------------------
USA, public health reports weekly since 1896
weekly deaths in ~100 cities worldwide , total+11 infectious diseases (until 1912)
weekly temperature and rainfall in ~100 US-cities
http://www.ncbi.nlm.nih.gov/pmc/?ter...eports%22+1900
starts 1896 all the weeks at pubmed
------------------------------------------------------------------Donaldson
and Keatinge [77], for example, obtained the daily population in their study
of winter excess mortality in southeast England “by linear interextrapolation
from the 1981 and 1991 censuses”----------------------------------
Aus Oberösterreich wurden tägliche Sterbefälle für die Jahre 1990 bis 2004 zur Ver-
fügung gestellt, wobei neben Alter, Geschlecht und Haupttodesursache auch der
Wohnbezirk bekannt ist. --------------------------------------
Canada 1921-1970: http://qspace.library.queensu.ca/jspui/handle/1974/8177
cansim: since 1991 : http://www5.statcan.gc.ca/cansim/a33...ables&lang=eng
since 1946 only per quartal and province
Ontario yearly statistical surveys (.pdf) on my HD 1877-1988
http://archive.org/details/provinceofontari1974onta
---------------------------------------------
wonder: http://wonder.cdc.gov/mcd-icd10.html
(you have to click "I agree" for that they mat punish you by $10000
and 5 years in prison for whatever they might consider a violation of their
terms, te main issue of which seems to be that you don't try to track
for individuals but rather only statistics. However, it's more
complicated with the details ... So I prefer NCHS, whenever possible.
But NCHS has no data by State or region since 2005, which wonder has)
--------------------------------------------------------
Anuario estadístico de México Mexico, statistical yearbook
---------------------------------------------------
PAHO: http://ais.paho.org/dwld/mort/VENEZUELA2004.csv
http://new.paho.org/hq/index.php?opt...&Ite mid=2392
=----------------------------------------------------
Australia , AIHW , ABS , 150 EXCEL , GRIM Books >1906
-----------------------------------------------------------England 1848-1900
http://www.geog.cam.ac.uk/research/p...undeathcauses/
by cause, sex and age for England & Wales 1848-1900 SN5705
-------------------------------------------------------------
France: 1946- http://www.persee.fr/web/revues/home...3_1946_num_1_1
=================================================
http://www.nhlbi.nih.gov/about/factbook-11/chapter4.htm
http://www.bmj.com/content/323/7312/541
http://www.cdc.gov/mmwr/preview/mmwrhtml/mm4843a2.htm
================================================== =============
University of Minnesota links:
https://www.lib.umn.edu/libdata/page...l?page_id=2031
================================================== ========
OECD: http://www.oecd.org/els/health-syste...lance-2013.pdf
http://stats.oecd.org/index.aspx?Dat...e=HEALTH_STAT#
34 OECD-countries, yearly since 1960, ~50 causes, years of life lost, health-status
================================================== ========
populations:
http://esa.un.org/unpd/wpp/ASCII-Dat...By_Single_Age2
600MB , single year , world , interpolated
http://esa.un.org/unpd/wpp/ASCII-Dat...GLE_MEDIUM.CSV
=================================================
---------------added 2015/07/24------------------
US-census has mortality data (deaths by cause,age,sex,...)
for 1850,1860,1870,1880,1890
http://www2.census.gov/prod2/decennial/documents/
also for 1900,(...?) for the whole USA, not only the "registration are"
CDC has the data for the registration area since 1900
http://www.cdc.gov/nchs/products/vsu..._1890_1938.htm
since 1933 the registration area covers the whole USA
---------------added 2015/07/24--------------------------------------
Germany interactive tables (I couldn't create tables with that page)
https://www.gbe-bund.de/oowa921-inst...OTATE/_XWD_246
---edit 2015/07/25------I managed to create and download tables now.
You must put the indicators into "zeile" or "spalte" , not "seite".
Neat. It has almost the same functionality and dataset as CDC-wonder,
but for Germany, of course. 1980-1997 (ICD9) and 1998-2013 (ICD10)
No multiple conditions, though.
Max. is 10000 values per table.
It may also be available in English, they had some language=d or such
in the URL, but I didn't yet figure it out. The url which google uses is:
https://www.gbe-bund.de/gbe10/i?i=St...erbeziffern_6D
(should be clickable ?!)

http://www.gesis.org/histat/de/table...48AA7B#tabelle

---------------added 2015/07/30----------------------------------------
Italy ~30 causes by sex and age5group, 1895-1955 [only 1 google-hit for that link]
http://lipari.istat.it/digibib/cause...e1887-1955.pdf
-ttp://lipari.istat.it/digibib/causedimorte/Causedimorte1887-1955.pdf
---------------added 2015/08/21-----------------------------------------
Switzerland, 1891-1988
http://www.bfs.admin.ch/bfs/portal/d...ch-archiv.html
-----------------------------------------------------------------
Sweden 1914-
http://www.scb.se/sv_/Hitta-statisti...ok+(SOS)+1914-
e.g. 1932:
http://www.scb.se/H/SOS%201911-/Stat...erige-1932.pdf
---------------------------------------------------------------
links at nber: http://admin.nber.org/data/#demographic
--------------------------------------------------------------
links at scotpho: http://www.scotpho.org.uk/publicatio...l-data-sources
----------------------------------------------------
Norway: Norway: http://www.ssb.no/a/en/histstat/
-------------------------------------------------------
Ukraine: 1965-2005
http://www.demogr.mpg.de/en/projects... ine_4571.htm
------------------------------------------------------------
http://digital.library.northwestern....ague/stat.html
League of Nations, statistical yearbook , 1926-1944
population,deaths,deathrates by age5groups and sex ~1930-1942
Ceylon, 1937-1948 :
__________________
a chart says more than 1000 words

Last edited by gsgs; 04-25-2017 at 02:12 PM.
gsgs is offline   Reply With Quote
Old 01-04-2015, 06:19 AM   #2
gsgs
searching for truth
 
gsgs's Avatar
 
Join Date: Sep 2008
Location: Germany
Posts: 3,743
Thanks: 3
Thanked 152 Times in 107 Posts
trend in mortality causes
--------------------------

deaths from 5 causes as % of all cause-assigned deaths
1979-2012, 6 age-sex-groups, 5 causes, 71 countries


http://magictour.free.fr/w832d.gif {1000*10000 pixel}

the occasional big changes in 2000 are probably due to the change
from ICD9 to ICD10 in the causes of deaths definitions.


maybe I can add more years and causes later,
I just found that WHO
also provides the raw data from their database !:
http://www.who.int/healthinfo/statis...ty_rawdata/en/
{77 google hits for that link}
{1 google hit for "77 google hits for that link"}

download - 9 .zip files with 54.5MB in total , unpacked: 9files with 389MB
not checked,converted,analyzed yet

---------------------------

bad data - different countries use different lists for disease encoding
and the lists change over time, entries are double counted ...

someone should already have processed/improved this
converted the encoding systems, put all the data
in one table
[country/geography,sex-age(group),cause,year]

human motality database estimated total deaths by single year of age
from age-5-groups, but noy deaths by cause and only few countries
but it is possible/reasonable to build that 4-dim-table with estimates
for missing values, so it can be used for computer-analysis


"year" is also unfortunate, since most countries are in the northern
hemisphere and flu-epidemics peak in winter, total deaths
minus flu also peak in winter, around the change of the year.
start the statistical year with May

I (mainly) need this to examine the 1975-US-deaths-decline-mystery
French paradox,hispanic paradox
(why fewer cardiovascular deaths in France vs. England,
Mexico vs. USA , Quebec vs. Ontario, Japan vs. Russia)


-------------------------------------------------------------

the WHO-data was used in: [cardiovascular-related only)

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4045191/
Conclusions
In the countries for which there are good longitudinal data, predominantly European countries,
recent years have shown a continuing decline in age-standardised IHD mortality.
However, the progressive aging of populations has kept crude IHD mortality high.
It is not known whether the pattern is consistent globally because many countries
have not provided regular annual data including wealthy countries such as the
United Arab Emirates and large countries such as India and China.

http://rgm22.nig.ac.jp/mediawiki-oga.../index.php/WHO

Divergent Paths for Adult Mortality in Russia and Central Asia ...
www.ncbi.nlm.nih.gov/pmc/articles/PMC3792976/
We find that, as in ussia, fluctuations in Kyrgyzstan have been primarily due to changes
in external causes and circulatory causes, and acohol appears to play an important role.
However, in contrast with Russia, mortality from these causes in Kyrgyzstan has been
lower and has increased by a smaller amount.

Alcohol and mortality in Russia: prospective observational study of ...
www.ncbi.nlm.nih.gov/pmc/articles/PMC4007591/

Cardiovascular disease in Europe 2014: epidemiological update ...
http://eurheartj.oxfordjournals.org/content/35/42/2950

https://ardoris.wordpress.com/
who.int/healthinfo/statistics/mortality_rawdata/en/ is a comprehensive dataset providing
mortality rates for all reporting countries, but difficult to find from the navigation.

------------------------------------------------------
googling: subdiv admin1 country "frmat" = 15 hits

http://demogr.nes.ru/images/uploads/Lecture_6PH.pdf

https://github.com/tony-kerz/hadoop-...ityMapper.java

--------------------------------------------------

so far I have 157MB = 20MB compressed , ~1 mio entries = lines with 68 files
(I put male+female into one line)
only 07A(150),08A(150),09A(320),09B(320),104(2500) with sum of 3-digit entries

icd09 and icd10 (1979-2012) are already processed by WHO, uniformized,
integrated into the WHO-online database
(only 5 agegroups,~100 diseases though)

1950-1968 07A,08A A-list (150 causes) only should be really easy to add
as compared to what they did with 1979-2012


respiratory deaths by age in the pandemics of 1957 and 1968
(1969/70 in Europe) are also interesting to study immunity
from H2,H3 in the 19th century

---------------------------------------------
googling: subdiv admin1 country "frmat" = 15 hits

http://demogr.nes.ru/images/uploads/Lecture_6PH.pdf

https://github.com/tony-kerz/hadoop-...ityMapper.java

-----------------------------------------------

http://magictour.free.fr/78-59a.GIF
file 78.be4
92 countries,7 death-causes+pop,agegroup 55-74,2 sexes,58 years (1950-2008)

50720~54*8*59*2 nonzero entries

pop,all,ill,can,cir,res,isc,cer


-----------------------------------------------------
WHO asks users to cooperate in the provision of electronically
transmitted data by adhering to the following guidelines:-
(a) Material drawn from the MDB for publication must be accompanied
by an acknowledgment of WHO as the source and a disclaimer crediting
analyses, interpretations or conclusions to the author of the published
data and not to WHO, which is responsible only for the provision of
the original information.
(b) Users wishing to publish a technical description or qualification of
the data will make a reasonable effort to ensure that it is not inconsistent
with any published by WHO.
(c) Recipients of electronically transmitted data wishing to, or asked to
make these, or copies thereof available to a third party are asked to
refer such party to WHO, who will transmit the data directly accompanied
with the necessary documentation. This will prevent circulation of
out-of-date data, as the MDB is updated regularly.
It should be noted that these data are transmitted on the understanding
that no use will be made of them for commercial purposes and that no
such permission or right to use may be implied thereby.
Responsible person:
Dr Colin Mathers
Department of Health Statistics and Information Systems
Innovation, Information, Evidence and Research Cluster
World Health Organization,CH-1211 Geneva 27,Switzerland
For questions related to data or file structure, please e-mail to
Doris Ma Fat
Colin Mathers
http://en.wikipedia.org/wiki/Colin_Mathers
theoretical physics , no papers about influenza
Doris Ma Fat
http://www.statssa.gov.za/assd2012/A...of%20death.pdf

----------------------------------------------------
wayback machine has the first entry in March 2014
http://web.archive.org/web/201403161...ity_rawdata/en
Data files - Last updated: 25 February 2014
=----------------------------------------------------
so far (2015/05/02) I have 15 conditions , 1950-2013 , where available,
in one file all84.15 ,
166 countries * 64 years * 15 conditions * 36 age5groups
5736960 values, 19MB , 4MB compressed,
3634317 missing values are set to zero
pop,all,bim,can,cer,cir,dig,hea,ill,inf,isc,ner,re s,unn,uro
male,female
all,0-4,5-9,...,80-84,>84
1950,...,2013
(population data from the UNO-link, where available and
WHO population data is missing , USA-population data from
human mortality database)
USA 2011-2013 is available at NCHS, not yet included)
------------added 2015/06/02-------------------------------------------
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4091993/
Period-Based Mortality Change: Turning Points in Trends since 1950
> However, because of the inconsistencies in the classification
> schemes used in the WHO database for the successive ICD periods,
> we were only able to construct four large disease categories
> selected for the relative uniformity in their definition over time.
> These four categories are: heart diseases, cerebrovascular diseases,
> smoking-related cancers, and all other cancers.

they didn't publish their data. So far I have for the 166 countries,
64 years, 2 sexes, 17 age5groups
file all84.15 ("major groups"): pop,all,bim,can,cer,cir,dig,hea,ill,inf,isc,
ner,res,unn,uro
file all84.18 ("chapters") : pop,all,bir,blo,can,cir,cog,dig,eay,ill,inf,met,
ner,psy,res,sk2,unn,uro
made from file all with 2556314 lines (I merged male and female into one line)
then file allst with 567439 lines and
1226=(151+50)+(151+50)+(57+57+17+17)+(17+214+215+2 13+17)
filtered diseases
(working today on tbc(tuberculosis),luc(lung cancer) )
there could be errors,holes, and many zeros, of course,
where WHO has no data.
----------------------------------------------------
annuaire statistique de la ville de Paris (e.g. 1892)
annuaire statistique de la ville de Buenos Ayres (e.g.1897)
__________________
a chart says more than 1000 words

Last edited by gsgs; 08-08-2015 at 12:12 PM.
gsgs is offline   Reply With Quote
Old 02-04-2015, 02:37 AM   #3
gsgs
searching for truth
 
gsgs's Avatar
 
Join Date: Sep 2008
Location: Germany
Posts: 3,743
Thanks: 3
Thanked 152 Times in 107 Posts
preliminary estimated monthly deaths
from all causes for Europe,
28 countries from Eurostat


Code:
Jan.2012:462840
Feb.2012:471338
Mar.2012:464996
Apr.2012:415276
May.2012:409165
Jun.2012:379881
Jul.2012:395023
Aug.2012:389211
Sep.2012:366171
Oct.2012:408406
Nov.2012:406297
Dec.2012:441407
Jan.2013:473379
Feb.2013:438443
Mar.2013:456363
Apr.2013:443062
May.2013:404782

the 2011/2012 flu-season was particularly mild in the
whole Northern Hemisphere

Code:
total,8197920(42),6506475(42),0(0)
unassigned,1352(3),22(1),0(0)


mon, 2011     ,  2012    ,   2013
------------------------------------
Jan,767970(42),600105(42),489523(34)
Feb,688447(42),605210(42),454438(34)
Mar,739220(42),597280(42),473842(34)
Apr,668221(42),541300(42),459584(34)
May,685691(42),532432(42),420197(34)
Jun,640205(42),496421(42),345264(33)
Jul,657904(42),519914(42),312158(29)
Aug,646335(42),505892(42),298742(29)
Sep,628393(42),476807(42),273416(24)
Oct,678732(42),532617(42),167905(12)
Nov,678090(42),527837(42),164708(9)
Dec,717360(42),570638(42),171629(9)

additional deaths in Jan+Feb+Mar as compared to Apr+May+Jun
in 0/00 for 2011,2012,2013 for several European countries


Code:
Europe,000,161,613
Europe,000,162,614
Euro a,000,190,630
Euro a,000,190,630
Euro a,000,190,630
Belgiu,000,200,145
Bulgar,140,222,175
Czech ,109,082,163
Denmar,101,063,185
German,082,096,000
German,082,096,049
Estoni,131,155,134
Irelan,116,130,091
Greece,070,196,097
Spain ,164,302,106
France,126,187,196
France,129,190,200
Croati,142,135,085
Italy ,131,266,704
Cyprus,165,308,104
Latvia,100,152,167
Lithua,068,054,093
Luxemb,107,083,182
Hungar,122,141,097
Malta ,304,584,461
Nether,049,094,152
Austri,100,151,045
Poland,111,058,122
Portug,233,391,197
Romani,128,170,052
Sloven,133,215,160
Slovak,090,064,071
Finlan,052,139,091
Sweden,116,164,153
United,139,100,103
Europe,000,161,000
Europe,000,161,000
Europe,096,138,000
Icelan,150,304,105
Liecht,314,938,045
Norway,082,107,000
Switze,103,154,192
Monten,202,118,064
Former,127,168,077
Serbia,134,101,978
Turkey,162,144,000
Albani,000,000,000
Andorr,670,499,000
Belaru,047,055,000
Bosnia,000,000,000
Kosovo,138,000,000
Moldov,189,133,000
Monaco,000,000,000
Russia,050,000,000
San Ma,000,132,000
Ukrain,091,081,000
Armeni,000,000,000
Azerba,000,075,000
Georgi,103,000,000
winter-mortality is worse in the South : Portugal,Spain,Greece

yearJan+Feb+Mar)/(Apr+May+Jun) Europe and USA
2011:1.099,1.092
2012:1.136,1.066
2013:1.110,
2014:
2015:

for the most actual estimates see www.euromomo.eu


I'd like to examine whether this is related to weather/temperature

2014 warmest year in Europe since 1500s

who has the data ... average winter temperature in 2011,2012,2013
for several European Capitals
__________________
a chart says more than 1000 words

Last edited by gsgs; 02-04-2015 at 09:25 AM.
gsgs is offline   Reply With Quote
Old 02-04-2015, 05:50 AM   #4
gsgs
searching for truth
 
gsgs's Avatar
 
Join Date: Sep 2008
Location: Germany
Posts: 3,743
Thanks: 3
Thanked 152 Times in 107 Posts
USA,2013 is already available (surprise, after the delay in 2011,2012)
http://www.cdc.gov/nchs/data/databriefs/db178.htm
http://www.cdc.gov/nchs/data_access/...tatsonline.htm
ftp://ftp.cdc.gov/pub/Health_Statist...mort2013us.zip
[99MB compressed, 1280MB uncompressed,
one data-line for each of the 2601452 anonymized US-death certificates
from 2013]

I'm now downloading,decompressing,changing,processing... this
and integrating it into my 1959-2013 US-mortality-database of
size 4.5 GB ...

more in some hours
main question : did the downtrend in cardiovascular diseases stop and
maybe revert ? There were some signs for this in 2012 and the weekly
MMWR provisional deaths are higher than in 2013 (even in summer)


monthly US deaths 1959-2013 from 19 major causes
monthly US deathrates 1990-2013, agegroup 70-74 from 19 major causes
US-population structure



the increase in deaths since ~2008 could be due to
an increase in the older population

data for the US-population by age for 2012,2013 is here:
https://www.census.gov/popest/data/n...013/index.html


there is a lower number of Americans born in the early 30s, these
were in the dying age in the last decade, the effect is running
out now and deaths increase
__________________
a chart says more than 1000 words

Last edited by gsgs; 02-06-2015 at 03:03 AM.
gsgs is offline   Reply With Quote
Old 02-06-2015, 11:41 AM   #5
gsgs
searching for truth
 
gsgs's Avatar
 
Join Date: Sep 2008
Location: Germany
Posts: 3,743
Thanks: 3
Thanked 152 Times in 107 Posts
I remember, this had already been shown for other holidays,
especially Christmas and New Year.
Now we have it for birthdays , although only 6.8%

http://www.ncbi.nlm.nih.gov/pubmed/25528555
A not so happy day after all: Excess death rates on birthdays in the U.S.

============================================

searching pubmed for seasonality,deaths on 2015/02/06
==============================================
avoid birthdays
http://www.ncbi.nlm.nih.gov/pubmed/25528555
A not so happy day after all: [6.8%] Excess death rates on birthdays in the U.S.
---------------------------------------------------------------------------------
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4265647/
There was a 21% increase in the number of deaths during the cold season
in Hanoi, Vietnam compared to the warm season.
[2008 was also the worst flu-wave in US,Europe]
------------------------------------------------------------------------------
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4242652/
For CVD mortality, the peak to nadir differences ranged from 0.185 to 0.466
in the Northern Hemisphere, from 0.087 to 0.108 near the Equator, and from
0.219 to 0.409 in the Southern Hemisphere. For cancer mortality, the seasonal
variation was nonexistent in most countries.
----------------------------------------------------------------------------------
http://www.ncbi.nlm.nih.gov/pubmed/25147283
An immediate decrease in AMI mortality rates was observed in January 2006
(smoking ban at work) in Flanders, Belgium. The effect was highest for women
younger than 60 years of age (-33.8%; 95% CI -49.6 to -13.0), compared with
an effect of -13.1% (95% CI -24.3 to -0.3) for male counterparts.
Estimates for
the elderly (≥60 years) were -9.0% (95% CI -14.1 to -3.7) for men and
7.9% (95% CI -13.5 to -2.0) for women. An additional effect of the
smoking ban in restaurants was observed for elderly men, with an
annual slope change of -3.8% (95% CI -6.5 to -1.0) after 1 January 2007.
-------------------------------------------------------------------------------------
http://www.ncbi.nlm.nih.gov/pubmed/24998952
47523 ED visits for CHD in Shanghai, 2010-2012. A 10-µg/m(3) increase
in PM10, SO2, and NO2 was associated with 1.10%, 0.90%, and 1.44%
for CHD. strong on sudden cardiac death, moderate on acute myocardial
infarction and angina, weak on ischemic cardiomyopathy, occult CHD.
stronger in winter
------------------------------------------------------------------------------------
http://www.ncbi.nlm.nih.gov/pubmed/24823666
Taipei, Taiwan, 2006-2008. PM2.5 effect on mortality on warm (>23 °C)
and cool days (<23 °C). no effect on respiratory, but on cardiovascular
on cool days. with SO2 and O3 on warm and cool days.
-----------------------------------------------------------------------------------------
http://www.ncbi.nlm.nih.gov/pubmed/24657768
Southern Europe, 2001-2010
For a 10μg/m(3) increase in 2d PM2.5 exposure there was a 1.23%
increase in diabetes deaths, 6d -> cardiac deaths by 1.33%
COPD by 2.53%, LRTI by 1.37% Stronger effects in the warm season.
---------------------------------------------------------------------------------------------
http://www.ncbi.nlm.nih.gov/pubmed/24322399
Beijing,2004-2008
PM2.5, PM10, SO2 and NO2 were 105.1 μg/m(3), 144.6 μg/m(3),
48.6 μg/m(3), and 64.2 μg/m(3)
All had effects on years of life lost YLL , 15.8, 15.8, 16.2, and 15.1 years
-----------------------------------------------------------------------------------------------
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3733298/
weak evidence for lower P+Ideaths due to increases in vaccination
in England and Wales 1998/9-2004/5
------------------------------------------------------------------------
http://www.ncbi.nlm.nih.gov/pubmed/23870087
Cold temp -->higher mortality in HK and Taipei lag<3weeks.
ozone also, humidity and solar radiation not
-----------------------------------------------------------------------
http://www.ncbi.nlm.nih.gov/pubmed/23734179
largest seasonal mortality amplitudes found in the southwestern
United States and the
smallest in the North, along with South Florida
environmental factors are more important than social factors
--------------------------------------------------------------------
http://www.ncbi.nlm.nih.gov/pubmed/23452890
CH,1968-2007 , CVD deaths and hospitalizations occurred less
frequently in the summer months. Similar patterns were found
for AMI and stroke
---------------------------------------------------------------------
http://www.ncbi.nlm.nih.gov/pubmed/23257953
UK, 13 years followup
higher concentrations of 25(OH)D were inversely and approximately
linearly (log-log scale)
associated with vascular and non-vascular mortality throughout
the range 40-90 nmol/L.
a doubling in 25(OH)D concentration was associated with 20% lower
vascular and 23% lower non-vascular mortality.
-------------------------------------------------------------------
http://www.ncbi.nlm.nih.gov/pubmed/23025494
48 US-cities, 1992-2000, The pooled estimated increase in
risk for a temperature decrease from 0 to -5°C was 1.6%
Influenza accounted for 2.3% of cardiac deaths
----------------------------------------------------------------
The risk of all-cause mortality is inversely related to serum
25(OH)D levels. Effect of influenza on cardiorespiratory and
all-cause mortality in Hong Kong,
Singapore and Guangzhou.
Weekend hospitalization and additional risk of death:
an analysis of inpatient data.
Excess mortality related to seasonal influenza and extreme
temperatures
in Denmark, 1994-2010.
Seasonal oscillation of human infection with influenza A/H5N1
in Egypt and Indonesia.
Seasonal variations of all-cause and cause-specific
mortality by age, gender, and
socioeconomic condition in urban and rural areas of Bangladesh.
[first #=100 articles]
-----------------------------------------------------------------------
Long-term projections and acclimatization scenarios of
temperature-related mortality in Europe.
Rainfall, household crowding, and acute respiratory infections in the tropics.
The seasonality of pandemic and non-pandemic influenzas: the roles of
solar radiation and vitamin D.
Disproportional effects in populations of concern for pandemic influenza:
insights from seasonal epidemics in Wisconsin, 1967-2004.
Explaining structural change in cardiovascular mortality in Ireland
1995-2005: a time series analysis.
Influenza infectious dose may explain the high mortality of the second
and third wave of 1918-1919 influenza pandemic.
Revisiting a population-dynamic model of air pollution and daily mortality
of the elderly in Philadelphia.
Human mortality seasonality in Castile-León, Spain, between
1980 and 1998: the influence of temperature, pressure and humidity.
Particulate air pollution and health effects for cardiovascular and
respiratory causes in Temuco, Chile: a wood-smoke-polluted urban area.
Incidence, seasonality and mortality associated with influenza pneumonia
in Thailand: 2005-2008.
Seasonality of mortality: the September phenomenon in Mediterranean
countries. Cyprus, France, Greece, Italy, Spain), Sweden,USA,Canada),
Australia, NZ, Japan
[several air pollution studies skipped]
Estimates of US influenza-associated deaths made using four
different methods.[2009]
The seasonality in heart failure deaths and total cardiovascular deaths.
Seasonality and coronary heart disease deaths in United States
firefighters.
Time series analysis of the epidemiological transition in Minorca, 1634-1997.
A deadly harvest: the effects of cold on older people in the UK.
Influenza-attributable deaths, Canada 1990-1999.
Seasonality and daily weather conditions in relation to myocardial
infarction and sudden cardiac death in Olmsted County, Minnesota,
1979 to 2002.
Seasonality and the dynamics of infectious diseases.
[#=200, 2006]

================================================== =
__________________
a chart says more than 1000 words

Last edited by gsgs; 07-25-2015 at 01:45 PM.
gsgs is offline   Reply With Quote
Old 02-10-2015, 02:59 PM   #6
gsgs
searching for truth
 
gsgs's Avatar
 
Join Date: Sep 2008
Location: Germany
Posts: 3,743
Thanks: 3
Thanked 152 Times in 107 Posts
monthly deaths in France, 1869-1897 [1873 also cholera in US , 1872 bad horseflu in US]
Italy 1870s N:winter and S:summer
England, cold, 1870s
England vs. Mass. 1850-1950
England, age, 1730-


to do: gather all the monthly deathcounts,
compare the countries and how it evolved until today
I made a computer-readable map now with the departments -->
progression charts for each month
__________________
a chart says more than 1000 words

Last edited by gsgs; 02-17-2015 at 07:26 AM.
gsgs is offline   Reply With Quote
Old 02-12-2015, 11:31 AM   #7
Exodia
Khan of the Golden Horde
 
Exodia's Avatar
 
Join Date: Aug 2008
Location: Southeast PA
Posts: 11,277
Thanks: 2,622
Thanked 4,844 Times in 2,174 Posts
Wow, nice finds. I'm haivng a little trouble reading the graphs though. Probably my fault, not yours.
__________________
"Now, mark my words. So long as we are a young and virtuous people, this instrument will bind us together in mutual interests, mutual welfare, and mutual happiness. But when we become old and corrupt, it will bind us no longer" - Alexander Hamilton about the US Constitution.
Exodia is offline   Reply With Quote
Old 04-06-2015, 11:50 PM   #8
gsgs
searching for truth
 
gsgs's Avatar
 
Join Date: Sep 2008
Location: Germany
Posts: 3,743
Thanks: 3
Thanked 152 Times in 107 Posts
A list of diseases with their ICD-codes through the different ICDs (ICD7,8,9,10) is needed.
So that we can compare the time-series through the boundary periods of the transitions
from one list to the next.
Does it exist ? Apparently neither WHO,UNO,NCHS,... do have it.
NCHS even has 3 different recoding lists (recode 39,recode 113,recode 358) but
these are not constant, they changed over time and the same code stands for different
diseases through different periods, just as in the ICD-lists. Even the number of entries
in the lists do change.
So, all the mortality-cause-databases are divided into parts, where each part is only
valid for the duration of one ICD-list. They are not merged, at least I didn't find it yet
anywhere.

One example: the different forms of influenza are encoded as
480-483 in ICD7
470-474 in ICD8
487-487 in ICD9
J09-J11 in ICD10

we need this list - as given above for influenza - for some dozends, hundreds of diseases
and conditions, so that we can reasonably work with the data, that had been collected
in history with so much effort through all the death certificates.

It's a common problem, that when a new coding system is being established, then
you need a program, a software that converts the old system to the new one.
It seems that this program is lacking for the ICD-codes.


if it exists, how to find it, what keywords

---------------------------------
here they seem to have such a list for ICD9-ICD10 conversion
http://www.icd10data.com/Convert
but they only show one item at a time, not the whole conversion list in computer-readable form
--------------------------------------
hmm, it's commercial ?! (-->copyright)
https://www.aapc.com/icd-10/crosswalks/
50 codes ICD9-ICD10 for $25
but ICD is from WHO and should be public, WHO should provide the conversion lists
same for CDC/NCHS, of course
--------------------------------------------------
says WHO at:
http://www.who.int/classifications/help/icdfaq/en/
> It is not possible to convert ICD-9 data sets into ICD-10 data sets or vice versa.

well, that impossible thing has been done already by others, see above.
There may be problems with a few encodings that are ambiguous, but
we must try to convert as good as possible. Some little errors in rare
diseases could be tolerated.
Just saying "it can't be done" is the wrong way.

> In order to provide users with details of the exact changes between ICD-9 and
> ICD-10 WHO has published detailed tables in electronic form.
> This five diskette set can be ordered from here [dead link]

hmm, they also did the impossible. On 5 diskettes which at some time may have been available
through snail mail. More reasonable would be just a list on a webpage. Just 1000 bytes
for the 100 most common diseases would already be fine. (in 1999 one diskette had 1.4MB,
but CDs were already common)
And we need the list for all the 10 ICD conversions. Or even better, a conversion program.

ICD11 should be OK
http://www.who.int/classifications/i...n/icd11faq/en/
it's progress, update, new knowledge.
But will it be possible to convert ICD10 to ICD11 ? As good as possible.
Freely available.

> ICD has been translated into 43 languages
43 languages ! But no translation ICD1-2-3-...-10

----------------------------------------------------------
WHO in its "WHO mortality database" (much appreciated) uses still another system
with additional different disease-lists for each ICD-period and the countries can choose,
which list to take in which year. (usually ending at the height of seasonal mortality rates
in the Northern Hemisphere, which makes it hard to track a full wave :-( --> make a
statistical year = Jul-Jun ) . This makes it even more non-uniform and hard to handle
by computer. (unless someone writes the conversion programs)


---------------------------------------------------------------
__________________
a chart says more than 1000 words

Last edited by gsgs; 04-07-2015 at 01:17 AM.
gsgs is offline   Reply With Quote
Old 04-07-2015, 01:38 AM   #9
gsgs
searching for truth
 
gsgs's Avatar
 
Join Date: Sep 2008
Location: Germany
Posts: 3,743
Thanks: 3
Thanked 152 Times in 107 Posts
here my first computer-readable list of the main classification into groups (ICD10:"chapters")
only the first 2 digits of the codes are taken, this is sufficient for the main-groups
[I should extend/improve this later by just editing here...]


inf:infections(and parasites),can:cancer,met:metabolic i.e.diabetes,blo:blood,
psy: psyxhic;mental,ner:nerves,cir:circulatory,res:resp iratory,dig:digestive,
uro:urological+genital,birregancy+puerperum,ske: bones+skin+muscles,
cog:congenital,eay:early infancy,ill:ill-defined+senility,
unn:unnatural(accident,violence,poison,suicide,



abbreviation of disease-group
ICD7 : first,last
ICD8 : first,last
ICD9 : first,last
ICD10 : frst,last
-----------------------------------------
inf,00,13,00,13,00,13,A0,B9
can,14,23,14,23,14,23,C0,D4
res,24,24,24,23,24,23,24,23
met,25,28,24,27,24,27,E0,E9
blo,29,29,28,28,28,28,D5,D8
psy,30,32,29,29,29,29,F0,F9
cir,33,33,33,32,33,32,A1,A0
ner,34,39,32,38,32,38,G0,H9
cir,40,46,39,45,39,45,I0,I9
res,47,52,46,51,46,51,J0,J9
dig,53,58,52,57,52,57,K0,K9
uro,59,63,58,62,58,62,N0,N9
bir,64,68,63,67,63,67,O0,O9
ske,69,74,68,73,68,73,L0,M9
cog,75,75,74,75,74,75,Q0,Q9
eai,76,77,76,77,76,77,P0,P9
ill,78,79,78,79,78,79,R0,R9
unn,80,99,80,99,80,99,U0,Z9


the same for WHO lists 07A,08A,09B,104
--------------------------------------------------------
inf,A001,A042,A001,A044,B01,B07,B9,A0
can,A043,A060,A045,A061,B08,B17,D4,C0
met,A061,A064,A062,A066,B18,B19,E9,E0
blo,A065,A066,A067,A068,B20,B20,D8,D5
psy,A067,A069,A069,A071,B21,B21,F9,F0
cir,A070,A070,A072,A071,B21,B20,A1,A0
ner,A071,A078,A072,A079,B22,B24,H9,G0
cir,A079,A086,A080,A088,B25,B30,I9,I0
res,A087,A097,A089,A096,B31,B32,J9,J0
dig,A098,A107,A097,A104,B33,B34,K9,K0
uro,A108,A114,A105,A111,B35,B37,N9,N0
bir,A115,A120,A112,A118,B38,B42,O9,O0
ske,A121,A126,A119,A125,B43,B43,M9,L0
cog,A127,A129,A126,A130,B44,B44,Q9,Q0
eai,A130,A134,A131,A135,B45,B45,P9,P0
ill,A135,A137,A136,A137,B46,B46,R9,R0
unn,A138,A150,A138,A150,B47,B56,Z9,U0


03,inf,A,01,Certain infectious and parasitic diseases (A00-B99)
23,can,C,02,Neoplasms (C00-D48)
01,blo,D,03,Diseases of the blood and ... immune system (D50-D89)
04,met,E,04,Endocrine, nutritional and metabolic diseases (E00-E88)
06,psy,F,05,Mental and behavioral disorders (F01-F99)
06,ner,G,06,Diseases of the nervous system (G00-G98)
31,cir,I,09,Diseases of the circulatory system (I00-I99)
10,res,J,10,Diseases of the respiratory system (J00-J98)
04,dig,K,11,Diseases of the digestive system (K00-K92)
01,ske,M,13,Diseases of the musculoskeletal system and connective tissue (M00-M99)
02,uro,N,14,Diseases of the genitourinary system (N00-N98)
00,bir,O,15,Pregnancy, childbirth and the puerperium (O00-O99)
00,cog,Q,17,Congenital malformations, deformations and chromosomal abnormalities (Q00-Q99)
01,ill,R,18,Symptoms, signs and ... findings, not elsewhere classified (R00-R99)
07,unn,U-Y,20,External causes of mortality (*U01-*U03,V01-Y89)

00,eye,H,07,Diseases of the eye and adnexa (H00-H57)
00,ear,h,08,Diseases of the ear and mastoid process (H60-H93)
00,ski,L,12,Diseases of the skin and subcutaneous tissue (L00-L98)
00,pna,P,16,Certain conditions originating in the perinatal period (P00-P96)


19 missing, H double

googling for 14,23,14,23,14,23,C0,D4 ...

WHO data selection webpage:
http://apps.who.int/healthinfo/stati...uery/start.php
__________________
a chart says more than 1000 words

Last edited by gsgs; 05-05-2015 at 07:45 AM.
gsgs is offline   Reply With Quote
Old 05-14-2015, 01:48 PM   #10
gsgs
searching for truth
 
gsgs's Avatar
 
Join Date: Sep 2008
Location: Germany
Posts: 3,743
Thanks: 3
Thanked 152 Times in 107 Posts
here are some keywords for those other people that might also be searching for someone
who had converted the -- 20th century mortality files -- from England
http://www.ons.gov.uk/ons/publicatio...cm%3A77-215593

1901-1910-ICD1.ZIP 628Kb)
1911-1920-ICD2.ZIP 1245Kb)
1921-1930-ICD3.ZIP 1182Kb)
1931-1939-ICD4.ZIP 1118Kb)
1940-1949-ICD5.ZIP 1524Kb)
1950-1957-ICD6.ZIP 1550Kb)
1958-1967-ICD7.ZIP 2773Kb)
1968-1978-ICD8.ZIP 2997Kb)
1979-1984-ICD9a.ZIP 2439Kb)
1985-1993-ICD9b.ZIP 2991Kb)
1994-2000-ICD9c.ZIP 2216Kb)
1901-2000 (Excel sheet 294Kb)

for the years since 1950 I prefer the WHO-data at
http://www.who.int/healthinfo/statis...ty_rawdata/en/
which includes England and Wales , among many other countries.

for deaths from all causes and population data by single year of age
I prefer human mortality database
http://www.mortality.org/

for deaths by month or actual European data see also eurostat euromomo
there is also a file of English deaths by quarter, 4 per year, since 1838

the data for Scotland 1855-1949 also exists and England 1850-1900,
althought I couldn't get the latter

1944 , 1949 , 1953 were missing
1910 , 1915 , 1920 , 1930 , 1935 , 1943 , 1948 , 1957
seem to have somehow reduced data
and 1901-1910 has only 10-year agegroups instead of the usual 5-year grouping.

ICD1 , 1901-1910 , 192 diseases
ICD2 , 1911-1920 , 319 diseases
ICD3 , 1921-1930 , 301 diseases
ICD4 , 1931-1939 , 329 diseases
ICD5 , 1940-1948 , 455 diseases
ICD6 , 1950-1957 , 2060 diseases
...

year , male deaths , female deaths

1901 , 285618 , 265967
1902 , 277216 , 258322
1903 , 266290 , 248338
1904 , 283206 , 266578
1905 , 267601 , 252430
1906 , 274233 , 257048
1907 , 269259 , 254962
1908 , 268714 , 251742
1909 , 265203 , 252800
1910 , 145076 , 128994
1911 , 272512 , 255298
1912 , 250232 , 236707
1913 , 261687 , 243288
1914 , 267359 , 249383
1915 , 181907 , 160821
1916 , 265030 , 243187
1917 , 262215 , 236707
1918 , 314704 , 297157
1919 , 258089 , 246114
1920 , 163179 , 152365
1921 , 234291 , 224338
1922 , 247221 , 239559
1923 , 226858 , 217927
1924 , 240620 , 232615
1925 , 225328 , 215330
1926 , 231549 , 222255
1927 , 246606 , 238003
1928 , 235542 , 224847
1929 , 269903 , 262589
1930 , 214608 , 203343
1931 , 249717 , 241913
1932 , 245715 , 238414
1933 , 250625 , 245840
1934 , 243120 , 233955
1935 , 150892 , 132438
1936 , 253319 , 242445
1937 , 260057 , 249517
1938 , 246731 , 232098
1939 , 254945 , 244023
1940 , 294196 , 278448
1941 , 270344 , 254090
1942 , 242089 , 228568
1943 , 156009 , 135006
1944 , 0 , 0
1945 , 245436 , 235838
1946 , 249452 , 239602
1947 , 265739 , 249852
1948 , 143276 , 119500
1949 , 0 , 0
1950 , 261152 , 249149
1951 , 281724 , 267656
1952 , 253679 , 237749
1953 , 0 , 0
1954 , 259797 , 242099
1955 , 266976 , 251888
1956 , 267904 , 253427
1957 , 14253 , 9174
__________________
a chart says more than 1000 words

Last edited by gsgs; 05-16-2015 at 11:22 AM.
gsgs is offline   Reply With Quote
Old 07-26-2015, 08:32 AM   #11
gsgs
searching for truth
 
gsgs's Avatar
 
Join Date: Sep 2008
Location: Germany
Posts: 3,743
Thanks: 3
Thanked 152 Times in 107 Posts
I found the Germany interactive mortality tables .
After some attempts I managed to create and download tables now.
You must put the indicators into "zeile" or "spalte" , not "blatt".
Neat. It has almost the same functionality and dataset as CDC-wonder,
but for Germany, of course.
It has 1980-1997 (ICD9) and 1998-2013 (ICD10)
No multiple conditions, though.
Max. is 50000 values per table.
It may also be available in English, they had some language=d or such
in some URL, but I didn't yet figure it out. The url which google uses is:
https://www.gbe-bund.de/gbe10/i?i=St...erbeziffern_6D
(should be clickable ?!)
zero google-hits for that url [plus the site itself plus this tbm-post now]
[available 2016/03/02/10:00 MET but not 11:00]

ICD9:
18 years
3 standards (total number,rate,age-adjusted rate)
3 sexes
24 regions
3 nationalities
142 diseases
21 agegroups

= 34782048 cells = 696 downloads for the whole database

Maximal sind 50000 Zellen, 10000 Zeilen, 250 Spalten möglich

You can better download the data for Germany (East and West) [and other countries]
from WHO, "raw data", whole WHO database, since 1950.
This is better for Germany [and other countries] as a whole,
but bde has also the data since 1980 for the German sub-regions
which I didn't find elsewhere. Shall they [Statistisches Bundesamt] please
submit it to WHO, and then WHO integrates it into their database !

I assume, this 50000-cells-restriction is because they don't want me to download the
whole database, which would be best/easiest for me, of course.
I saw this already with other statistical databases, so it's not special , more like "normal".
There should be a name, a keyword already for that phenomenon ...
It could be - I speculate - because they are afraid I could set up an own webpage where
I offer downloads , in "competition" to gbe. Or I could give it to others who set up that
webpage. I also made the experience, that database-offerers want to be quoted,cited
when their data is being used in published papers. This could be because the number of
such quotes is then being used to justify (federal) grants, fundings for their database project.
But I have no experience, how this database and research "business" works, and
apparently -to my experience- those people don't like to talk about this,
so it's probably somehow secret.
----------------------------------------------------------
1860 = Beginn der Veröffentlichungsreihe „Preussische Statistik“
Todesursachen (1869 bis 1907 jährlich)
Volkszählungen (1861/62, 1864/65, 1867, 1871, 1875;
1880,1885,1890,1895,1900,1905,1910,1925, 1933,1939)
-------------------------------------------------------

I was examining the West-East increase of current cardiovascular
mortality through Europe, which somehow starts at the former
border between West and East Germany.
Eastern, higher cardiovascular mortality declined sharply
in former DDR after reunification in 1989, more than in West Germany,
but since 2000 that speed slowed and now it declines at the same
speed as in Western Germany only, while still being a bit higher.
Not as high as in Poland,Czech or even Ukraine,Russia , though.

http://magictour.free.fr/LAEND1A.GIF
http://magictour.free.fr/CIRBIG12.GIF

------------------------------
are these up and downs in heart-disease mortality really just
behaviour-driven (nutrition,exercise,smoking,air-pollution,),
or is there some pathogen involved ? (virus,bacterium)
We see quite some differences in the countries over time,
so they should be able to figure out what one country/region
does better/worse than another country in another decade
I mean, how can that still be mainly unresolved ???
------------------------------------------
2014 now available (2016/01/16)
-----------------------------------------
2015 now available (2017/01/28)
----------------------------------------
__________________
a chart says more than 1000 words

Last edited by gsgs; 01-28-2017 at 02:35 PM.
gsgs is offline   Reply With Quote
Old 08-04-2015, 04:20 AM   #12
gsgs
searching for truth
 
gsgs's Avatar
 
Join Date: Sep 2008
Location: Germany
Posts: 3,743
Thanks: 3
Thanked 152 Times in 107 Posts
WHO has a new version now, dated 2015/05/25
http://www.who.int/healthinfo/statis...ty_rawdata/en/
updates are included for the following countries for the specified years:

Code:
eAlb,2005-2009
eAus,2013
eBel,2000-2002,2011-2012
eCro,2013
eCze,2013
eFin,2013
eGer,2013
eHun,2013
eIta,2012
eLux,2013
eMol,2013
eMot,2001-2004
eNla,2013
eNor,2013
ePol,2013
ePor,2013
eSer,2013
eSpa,2013
eSwe,2013
eSwi,2011-2012
eUKa,2011-2013
eUKE,2013
eUKN,2011-2013
eUKS,2013
fEgy,2012-2013
fMau,2013
fMor,2009-2010,2012
fRod,2013
fSAf,2011-2013
fTun,2009,2013
mAnB,2012
mBel,2011-2012
mBra,2012
mBVI,2011
mChi,2012
mCub,2012
mDom,2012-2013
mDoR,2011
mElS,2012
mGuy,2011
mHon,2008-2013
mMon,2012-2013
mNic,2012
mPan,2012
mPar,2012
mPer,2011-2012
mSKN,2012
mStL,2009
mSur,2010-2012
mSVG,2013
mTrT,2009
mViI,2008
oFij,2001-2008
oNZe,2011
sBah,2012-2013
sBru,2012
sHoK,2012-2013
sIsr,2012
sJap,2012-2013
sJor,2011
sKuw,2013
sPl1,2013
sSaA,2012
sSgp,2012-2013
sSyr,2010
sTur,2012-2013
2014: 5121 years*countries available , 5669 years*countries not available
2015: 5233 , 5687 (2.2% increase)
available data:

Code:
year:5-1950,...1=2010,...
fCaV,001,01,00000000000000000000000000000010000000000000000000000000000000000
fEgy,002,42,00001111111111111100111111111110000001000110000000111111111111110
fMau,003,57,00000001111111111111111111111111111111111111111111111111111111110
fMay,004,01,00000000000000000000000000000000000000000000000000000000000001000
fMor,005,05,00000000000000000000000000000000000000000000000000000000001111100
fReu,006,11,00000000000000000000000000000000000000000000000000011111111111000
fRod,007,12,00000000000000000000000000000000000000000000000000011011111111110
fSTP,008,03,00000000000000000000000000000000001101000000000000000000000000000
fSey,009,17,00000000000000000000000000000001100111000000000000011111111111100
fSAf,010,21,00000000000000000000000000000000000000000001111111111111111111110
fTun,011,02,00000000000000000000000000000000000000000000000000000000000100010
fZim,012,01,00000000000000000000000000000000000000001000000000000000000000000
mAng,013,28,00000000000000000000000101100000011111111111110000111111101111100
mAnB,014,40,00000000000111101001111111111000010111111111110011111111111100100
mArg,015,41,00000000000000001111100000011111111111111111111111111111111111100
mAru,016,17,00000000000000000000000000000000000001001000010001111111111111100
mBah,017,32,00000000000000000001011011110111011101000001111111111111111110000
mBar,018,53,00000111111111111111111111111111111111111111110000111111111111000
mBel,019,46,00000000000000111111111111111111111011011101111111111111111111100
mBer,020,43,00000000000000110111111111111010011111111111111111111111111110000
mBol,021,04,00000000000000000000000000000000000000000000000000111100000000000
mBra,022,36,00000000000000000000000000011111111111111111111111111111111111100
mBr1,023,17,00000000000000000000000000000000000011111111111111111000000000000
mBr2,024,17,00000000000000000000000000000000000011111111111111111000000000000
mBVI,025,35,00000000000000000011100001111001111111111111111111111110101110000
mCan,026,62,11111111111111111111111111111111111111111111111111111111111111000
mCaI,027,30,00000000000000000000000110001100001111111111111111111110111110000
mChi,028,59,00001111111111111111111111111111111111111111111111111111111111100
mCol,029,53,00011111111111111111101011110101001111111111111111111111111111000
mCoR,030,57,00000011111111111111111111111111111111111111111111111111111111100
mCub,031,48,00000000010000110011111111111111111111111111111111111111111111100
mDom,032,49,00000000000110000111111111111111111111111111111111111111111111110
mDoR,033,52,00000011111111011111111111111111111111111110111111110111110111000
mEcu,034,50,00000000000101111111111111011111111111111111111111111111111111100
mElS,035,51,11111111111111111111111110000001111000001111011111111111111111100
mFaI,036,12,00000000000110011010000010010111110000000000000000000000000000000
mFrG,037,23,00000000000000000011111111111100000000000000000000011111111111000
mGre,038,28,00000000000000000000000011111000001100111111111000011111111111100
mGud,039,22,00000000000000000000011110111111000000000000000000111111111111000
mGut,040,50,00000000111111111111110011111111001011111111111111111111111111100
mGuy,041,28,00000000000000000000000001110100001000111111111111011111111111000
mHai,042,09,00000000000000000000000000000011010000000000000101011110000000000
mHon,043,27,00000000000000001011111111111111110001111000000000000000001111110
mJam,044,30,00000000001100110111110001010011111111111100000000111111100000000
mMar,045,20,00000000000000000010110011000001100100000000000000111111111111000
mMex,046,58,00000111111111111111111111111111111111111111111111111111111111100
mMon,047,27,00000000000000000000000001001100000000001111111111111111111111110
mNlA,048,14,00000000000000000000000000000001000000111111111111100000000000000
mNic,049,38,00000000010111110011000111111000000000111111101111111111111111100
mPan,050,53,00001111111111111111111111111111111111110000001111111111111111100
mPn1,051,15,00000000000011011111111111011000000000000000000000000000000000000
mPar,052,19,00000000000000000000000000000000000000000000111111111111111111100
mPr1,053,30,00000000000111011111111111111111111111111100000000000000000000000
mPer,054,40,00000000000000001111111100011011110011111110111111111111111111100
mPuR,055,52,00000111111111111001111111110111111111111111111111111101111110000
mSKN,056,50,00000000000111011101111111111111111111111111111111111111111111100
mStL,057,41,00000000000000000011111111111111010011111111111111111111101111100
mSPM,058,09,00000000000000011000000001100000000000000000000000000001101110000
mSVG,059,33,00000000000000000000111010011100111111001000011111111111111111110
mSur,060,42,00000000000001111000011101111111101111111110011111111111111111100
mTrT,061,58,01111111111111111111111111111111111111111111111111111011111100000
mTCI,062,29,00000000000000000000000000000111001111111111111111111111111100000
mUSA,063,61,11111111111111111111111111111111111111111111111111111111111110000
mViI,064,20,00000000000001010000011100000010000000000000000111111111111110000
mUru,065,51,00000111111001111111111111111011111111111001111111111111111110000
mVen,066,52,00000111111111111111111111111111110111111011101111111111111100000
sBah,067,20,00000000000000000000000000000000000101100000000111111111111111110
sBru,068,17,00000000000000000000000000000000000000000000001111111111111111100
sCh1,069,14,00000000000000000000000000000000000001111111111111100000000000000
sCh2,070,14,00000000000000000000000000000000000001111111111111100000000000000
sCh3,071,14,00000000000000000000000000000000000001111111111111100000000000000
sCTw,072,16,00000111111111111111100000000000000000000000000000000000000000000
sCyp,073,11,00000000000000000000000000000000000000000000000001100011111111100
sHoK,074,59,00000111111111111111111111111111111111111111111111111111111111110
sIr1,075,11,00000000000000000000000011001111111101000000000000000000000000000
sIrq,076,01,00000000000000000000000000000000000000000000000000000000001000000
sIsr,077,38,00000000000000000000000001111111111111111111111111111111111111100
sIs1,078,27,11111111111111111111111111100000000000000000000000000000000000000
sJap,079,64,11111111111111111111111111111111111111111111111111111111111111110
sJor,080,20,00000000011011111010111111001100000000000000000000000000001111000
sKuw,081,35,00000000000000000000001001111111111111000001111111111111111111110
sMac,082,01,00000000000000000000000000000000000000000000100000000000000000000
sMay,083,09,00000000000000000000000000000000000000000000000000111111111000000
sMy1,084,01,00000000000000000000000000000000000000000000000100000000000000000
sMy2,085,03,00000000000000000000000000011100000000000000000000000000000000000
sMy3,086,01,00000000000000000000000000010000000000000000000000000000000000000
sMal,087,10,00000000000000000000000000000000000000000000000000111111011011000
sMon,088,01,00000000000000000000000000000000000000000000100000000000000000000
sMya,089,02,00000000000000000000000000011000000000000000000000000000000000000
sPl1,090,05,00000000000000000000000000000000000000000000000000000000001101110
sOma,091,02,00000000000000000000000000000000000000000000000000000000000110000
sPk1,092,02,00000000000000000000000000000000000000000001100000000000000000000
sPhi,093,30,00000000000001111111111111111001000000000011111111111100001000000
sQat,094,10,00000000000000000000000000000000000000000000010000000011111111100
sSKo,095,28,00000000000000000000000000000000000111111111111111111111111111100
sRKI,096,13,00000000111101111111110000000000000000000000000000000000000000000
sSaA,097,02,00000000000000000000000000000000000000000000000000000000000100100
sSgp,098,59,00000111111111111111111111111111111111111111111111111111111111110
sSrL,099,42,11111111111111111110000000010011111111110110011111111100100000000
sSyr,100,01,00000000000000000000000000000000000000000000000000000000000010000
sSy1,101,10,00000000000000000000000111111011001100000000000000000000000000000
sTha,102,48,00000111111111111111111111111111111111001110111111101111100000000
sTur,103,05,00000000000000000000000000000000000000000000000000000000000111110
sTu1,104,28,00000000000000000000000000001101111001111111111111111111111000000
eAlb,105,21,00000000000000000000000000000000000001110011111111111111111100000
eArm,106,27,00000000000000000000000000000001100111111111111111111100101111100
eAus,107,59,00000111111111111111111111111111111111111111111111111111111111110
eAze,108,23,00000000000000000000000000000001100111111111111111111110010000000
eBeR,109,24,00000000000000000000000000000001100111111111110111111100011101000
eBel,110,59,00001111111111111111111111111111111111111111111111111111111111100
eBoH,111,08,00000000000000000000000000000000000111111100000000000000000001000
eBul,112,49,00000000000000111111111111111111111111111111111111111111111111100
eCro,113,29,00000000000000000000000000000000000111111111111111111111111111110
eCzx,114,39,00011111111111111111111111111111111111111100000000000000000000000
eCze,115,28,00000000000000000000000000000000000011111111111111111111111111110
eDen,116,62,01111111111111111111111111111111111111111111111111111111111111100
eEst,117,30,00000000000000000000000000000001100111111111111111111111111111100
eFin,118,62,00111111111111111111111111111111111111111111111111111111111111110
eFra,119,61,10111111111111111111111111111111111111111111111111111111111111000
eGeo,120,26,00000000000000000000000000000001100111111110111111110011110111100
eGer,121,24,00000000000000000000000000000000000000001111111111111111111111110
eGeE,122,21,00000000000000000001111111111011111111111000000000000000000000000
eGeW,123,39,00111111111111111111111111111111111111111000000000000000000000000
eGeB,124,15,00000111111011111111100000000000000000000000000000000000000000000
eGre,125,57,00000011111111111111111111111111111111111111111111111111111111100
eHun,126,59,00000111111111111111111111111111111111111111111111111111111111110
eIce,127,59,01111111111111111111111111111111111111111111111111111111111100000
eIre,128,61,11111111111111111111111111111111111111111111111111111111111110000
eIta,129,60,01111111111111111111111111111111111111111111111111111100111111100
eKaz,130,29,00000000000000000000000000000001100111111111111111111111111110100
eKyr,131,31,00000000000000000000000000000001100111111111111111111111111111110
eLat,132,33,00000000000000000000000000000011111111111111111111111111111111100
eLit,133,30,00000000000000000000000000000001100111111111111111111111111111100
eLux,134,57,00000111111110011111111111111111111111111111111111111111111111110
eMac,135,20,00000000000000000000000000000000000000000111111111111111111110000
eMal,136,58,00000111111111111111111111111111111111111111111111111111111111100
eMon,137,02,00000000000000000000000000000000000011000000000000000000000000000
eMot,138,10,00000000000000000000000000000000000000000000000000111111111100000
eNla,139,64,11111111111111111111111111111111111111111111111111111111111111110
eNor,140,63,01111111111111111111111111111111111111111111111111111111111111110
ePol,141,53,00000000011111111111111111111111111111111111111001111111111111110
ePor,142,58,00000111111111111111111111111111111111111111111111111111011111110
eMol,143,31,00000000000000000000000000000001100111111111111111111111111111110
eRom,144,53,00000000011111111111111111111011111111111111111111111111111111100
eRus,145,32,00000000000000000000000000000011111111111111111111111111111111000
eSer,146,16,00000000000000000000000000000000000000000000000011111111111111110
eSlk,147,19,00000000000000000000000000000000000000000011111111111111111110000
eSaM,148,08,00000000000000000000000000000000000000000000011111101001000000000
eSln,149,26,00000000000000000000000000000000000111111111111111111111111110000
eSpa,150,63,01111111111111111111111111111111111111111111111111111111111111110
eSwe,151,63,01111111111111111111111111111111111111111111111111111111111111110
eSwi,152,62,01111111111111111111111111111111111111111111111111111111111111100
eTaj,153,23,00000000000000000000000000000001100111111111111111111111000000000
eTur,154,16,00000000000000000000000000000001100111111111111110000000000000000
eUkr,155,30,00000000000000000000000000000001100111111111111111111111111111100
eUSx,156,09,00000000000000000000000000000000111111111000000000000000000000000
eUKa,157,63,11111111111111111111111111111111111111111111111111011111111111110
eUKE,158,64,11111111111111111111111111111111111111111111111111111111111111110
eUKN,159,64,11111111111111111111111111111111111111111111111111111111111111110
eUKS,160,64,11111111111111111111111111111111111111111111111111111111111111110
eUzb,161,23,00000000000000000000000000000001100111111111111111111111000000000
eYux,162,31,00000000001111111111111111111111111111111000000000000000000000000
eSMx,163,06,00000000000000000000000000000000000000000000000111111000000000000
oAus,164,61,11111111111111111111111111111111111111111111111111111110111111000
oFij,165,13,00000000000000000000000000001000000000000000000001011111111101100
oKir,166,11,00000000000000000000000000000000000000000111111111110000000000000
oNZe,167,62,11111111111111111111111111111111111111111111111111111111111111000
oPNG,168,02,00000000000000000000000000010010000000000000000000000000000000000


,000,00,00000000000000000000000000000000000000000000000000000000000000000
,169,00,00000000000000000000000000000000000000000000000000000000000000000


I have not yet included these updates in my current
computer-readable database with all the ICDs,2005-2013,
15 major diseases and the population counts
by sex and age5groups, named all84.16 with 80 major
mortality-data-submitting countries extracted into files
big1.16,...,big8.16 This is still being improved/corrected,
missing values estimated etc.

I'm planning to upload a big charts-file for these 80 countries
for all diseases, circulatory causes, heart diseases,
cerebrovascular diseases, cancer, lung cancer, respiratory causes
for 1950-2013, male and female and the sex-ratio for age5groups
45-49,...,75-79

The main purpose is to figure out the course of the coronary heart
disease epidemic, where it started, how,how much, when and where it
declined and where it still increases.
Unfortunaltely these WHO data start at 1950 while in some countries
(i.e. USA,England) it started before 1930 and maybe well after the
1918 influenza pandemic.

So far only small subsets for a few countries and smaller periods
had been considered for that purpose in published papers, AFAIK.
The raw WHO-data are available only since 2014.

----------------------------------------------------------
whe should have an executable whochart.exe
(compiled from whochart.c)
which reads all84-16 - like files and processes them and
creates chart-files from it , (or directly displays the charts)

with command-line-parameters, e.g.

whochart.exe all84.16 mUSA cir log

(add cir-cer to xxx.16)

predefined chart-sets : all,cir-,cer,cir+,res,can,all-cir+-can,

male/female ratio

specifyable:
v=
k=
age5groups
multiple
merge chartfiles (horizontal,vertical, into one chart)
rescale

e : with estimated,interpolated data
c : with correction of obvious errors
g : automatically make moving averages on sparse data, small countries
l : logarithmic


[... they should have done it decades ago, this exists since 1950 ... ]


also : include all the WHO data into hmd
include some major causes into hmd also,
estimate missing data

--------edit 2016/01/17------------------------------------------------
another update dated 2015/11/25

now available:
2014:eAus,eGeo,eMal,eSlk,fMau,fRod,mAng,mMon,sPl1, sSgp
2013:eGer,eHun,ePol,eSpa,eUKa,mArg,mBra,mChi,mMex, mUSA,sHoK,sIsr,sJap,sSKo
__________________
a chart says more than 1000 words

Last edited by gsgs; 01-17-2016 at 04:07 PM.
gsgs is offline   Reply With Quote
Old 08-05-2015, 02:27 AM   #13
gsgs
searching for truth
 
gsgs's Avatar
 
Join Date: Sep 2008
Location: Germany
Posts: 3,743
Thanks: 3
Thanked 152 Times in 107 Posts
I need a new post for the search engines to fetch the keywords:

Country,Admin1,SubDiv,Year,List,Cause


Egypt,1950,male,107822,40543,18814,8192,
Egypt,1950,female,105750,39632,21606,9090,
USA,1950,male,827749,59727,4298,2514,
USA,1950,female,624705,44098,3424,2001,

(1950 is the first year in the WHO data, Egypt the first country in the list)

[what keywords should be used, so that others, who are searching for
improvements on that WHO-database will find it ?]

13 google hits for "country,admin1,subdiv"
as of 2015/08/05/14:50 UTC google has not yet fetched this very page

---------------------------------------------------
btw., is it possible that in some countries deaths
from coronary heart disease (acute myocardial infarction)
are being confused with deaths from cerebrovascular disease (stroke) ?
I usually don't see that typical coronary-mid-age-male excess
in stroke deaths (USA,Western Europe) but it is/was clearly there
in some other countries like Poland(since ~1970),Hungary,Bulgaria,
Mauritius,HongKong(1960)...
and to smaller degree in Japan,Italy,Austria,
Argentina,Philippines,Korea
------------------------------------------------
charts for 80 countries, 1950-2010 (where available) , male and female,
8 age5groups , cir(heart) , cer(stroke) [6 pages to print]
I made it logarithmic, since that better shows the trend in the sexratios:
circulatory without cerebrovascular : http://magictour.free.fr/sxg5l5.gif [last improved on 2015/08/07]
cerebrovascular (stroke) : http://magictour.free.fr/sxg4l2.gif

----------------------------------------------
__________________
a chart says more than 1000 words

Last edited by gsgs; 08-07-2015 at 11:45 AM.
gsgs is offline   Reply With Quote
Old 08-07-2015, 09:37 AM   #14
gsgs
searching for truth
 
gsgs's Avatar
 
Join Date: Sep 2008
Location: Germany
Posts: 3,743
Thanks: 3
Thanked 152 Times in 107 Posts
[another try, google didn't fetch it, although my
CDS-post here yesterday was fetched]

Country,Admin1,SubDiv,Year,List,Cause

http://magictour.free.fr/sxg5l5.gif

bing.com now (2015/08/08/18:42UTC) has this post,
they have 3 hits for "Country,Admin1,Subdiv"
__________________
a chart says more than 1000 words

Last edited by gsgs; 08-08-2015 at 02:43 PM.
gsgs is offline   Reply With Quote
Old 08-10-2015, 07:57 AM   #15
gsgs
searching for truth
 
gsgs's Avatar
 
Join Date: Sep 2008
Location: Germany
Posts: 3,743
Thanks: 3
Thanked 152 Times in 107 Posts
here is a useful link for the average, non-research people:
http://www.worldlifeexpectancy.com/w...s-total-deaths
You can get the rankings and maps and many other features.

They have all the WHO-data and NCHS/CDC-wonder
(they have all the US-counties)

They don't have data by ang and sex, AFAICS and no old, historic data.
Still they must have been unifying/converting all the ICD10-data.
From the WHO-data they extracted 80 causes.

Coronary Heart Disease and Stroke are -by far- the leading causes
of death worldwide in their list.
__________________
a chart says more than 1000 words
gsgs is offline   Reply With Quote
Old 01-21-2016, 12:45 PM   #16
gsgs
searching for truth
 
gsgs's Avatar
 
Join Date: Sep 2008
Location: Germany
Posts: 3,743
Thanks: 3
Thanked 152 Times in 107 Posts
related to posts 2,8,12,13 above
-----------------------------------------------------------
apparently Albert de Roos also thought that WHO gave a wealth of information
by providing the "raw data" of their database but that the data is not easily accessible
and needed to be improved/reorganized/transformed/uniformized .
So he made
"A Relational Database of WHO Mortality Data Prepared to Facilitate Global Mortality Research"

de Roos, Albert, 2015, “WHO Mortality database”, http://dx.doi.org/10.7910/DVN/28948
http://openhealthdata.metajnl.com/ar...y/33/download/

it seems that he somehow merging the ICD-codes

unfortunately I don't know MySQL , SQL


integrate the population data (estimates) (by sex and age) from the UNO-database
integrate the all-cause-deaths data from the UNO database (by sex and age)
since 1948
integrate earlier data, available for some countries England,Scotland since 1855,
USA since
integrate human mortality database, (all causes,population,20 countries,sex,single-year-of-age
e.g. France since 1816 etc.)

estimate missing values from available values, e.g. agegroup 5-9 when only 5-14 is available


(Quality Control Mortality Datasets_28122014.xls) [http://dx.doi.org/10.7910/DVN/28948].
5 google hits for that link, no external links (noone else linked to it - except me now)

https://dataverse.harvard.edu/datase...7910/DVN/28948
no google hits for that link

5 compressed files of 1.2MB,2.8MB,52.5MB,
1 xls of 58KB , 9 downloads (ahh, they didn't find it ?! WHO should link to it)

I haven't examined this yet

[email protected]
this project is not mentioned on his webpage and it's not related to his area of interest [2007]

-------------------------------------------
a first look :
looks complicated , lots of work - all the disease-names , 130 files , 80 directories
one big .sql file of 2.1GB , while WHO data is 400MB only
version from 2014/02/25
__________________
a chart says more than 1000 words

Last edited by gsgs; 01-21-2016 at 01:24 PM.
gsgs is offline   Reply With Quote
Old 05-28-2016, 02:37 AM   #17
gsgs
searching for truth
 
gsgs's Avatar
 
Join Date: Sep 2008
Location: Germany
Posts: 3,743
Thanks: 3
Thanked 152 Times in 107 Posts
http://sjp.sagepub.com/content/39/7_suppl/12.full.pdf
Danish registers contain information on many important health and social issues.
Because all Danish citizens have a unique personal identification number,
linkage at the individual level between these nationwide registers and other
data sources is possible and feasible.
[population Denmark = 5.6M]
data at Statistics Denmark www.statistikbanken.dk
English : http://www.statistikbanken.dk/statba...ult.asp?w=1024
Deaths by day of death and month of death (2007-2015)
Deaths by sex, age and cause of death (1981-2014)


> Statistics Denmark offers easy access to their data for research projects
Danish Data Archive (Dansk Data Arkiv) http://samfund.dda.dk/default-en.asp

The Register of Causes of Death , 1875
National Board of Health [hospital-data] 1977
National Board of Health [health service data] 1990
National Board of Health [drug prescriptions] 1994
Danish Medicines Agency [cancer incidence] 1943
National Board of Health [psychiatric hospitals] 1970
The National Diabetes Register 1995
The Multiple Sclerosis Registry 1949
The Cytogenetic Register [prenatal chromosomal] 1968
Arhus Universitetshospital 1997
Breast Cancer followup 1977
The Danish Heart Register [invasive procedures] 2000
The Colorectal Cancer Database 2001
The Hysterectomy Database 2004
__________________
a chart says more than 1000 words
gsgs is offline   Reply With Quote
Reply

Tags
links, mortality, statistics

Thread Tools Search this Thread
Search this Thread:

Advanced Search
Display Modes

Posting Rules
You may not post new threads
You may not post replies
You may not post attachments
You may not edit your posts

BB code is On
Smilies are On
[IMG] code is On
HTML code is Off

Forum Jump


All times are GMT -4. The time now is 06:39 AM.


Powered by vBulletin®
Copyright © Jelsoft Enterprises Ltd.