cmgpd-ln substantive lecture day 2 longitudinal, historical data and comparative studies of family...
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CMGPD-LNSubstantive Lecture
Day 2Longitudinal, Historical Data and Comparative
Studies of Family and Population
Traditional approach to historical comparison
• Countries, societies or entire continents as units of comparison
• Even comparisons of quantitative phenomena are fundamentally qualitative– Conference volume with chapters written by
individual authors, and a conclusion– Integrated volume by single author, or small number
of co-authors, making use of secondary evidence– Measures rarely directly comparable
A new approach
• Starting in the 1980s, various teams of researchers in Europe and Asia independently began constructing databases from historical household registers
• Akira HAYAMI (Reitaku) recognized the possibilities for systematic comparison in the early nineties
• Convened the first ‘Eurasia Project’ meeting in Kyoto in 1994, bringing together scholars working with European and Asian household registers.
• Tommy Bengtsson (Lund) convened a follow-up meeting in Lund in fall of 1994.
Lund and Kyoto (1994)• Five teams introduced their household register data and
research– Belgium, China, Italy, Japan, Sweden
• Identified basic themes and principles– Household organization– Compare communities, not countries– Volumes on mortality, fertility, marriage– Event-history models for comparable results– Iterative development of models and conclusions– Consensual approach
Life Under Pressure• The first comparative volume• Lead-authored by Tommy Bengtsson, Cameron
Campbell, and James Lee• Mortality patterns as a window into household
organization– We thought mortality was the best to start with
because it was the most clearly defined and easiest to compare
• Meeting in Venice in 1996 led to development of an initial template for analysis
• 8 years of iterations before volume appeared
Meetings• 2 initial meetings at Kyoto and Lund (1994)• 8 conferences in Arild, Beijing, Bloomington, the Hague,
Kyoto, Liege, Osaka, and Venice (1997, 1998, 1999, 2000, and 2001)
• 7 side meetings at the Population Association of America (1998, 1999, 2000) and Social Science History Association (1998, 1999, 2000, 2001)
• 3 side meetings at the International Economic History Congress (1997), International Congress of Historical Sciences (2000), and International Union for the Scientific Study of Population (2001)
• Extended stays in Los Angeles by Tommy Bengtsson, and in Lund by Cameron Campbell
Life Under Pressure
• Basic goal: understand the social organization of demographic responses to economic pressure
• Move beyond the Malthusian framework in which response to pressure were driven largely by SES
• Event-history to study mortality by– Community and household context, individual
characteristics– Price– Price * context, characteristics
Table A.2. Household Register Data Used in the Analysis
PopulationTime Period
Average Pop. Size
Person Years
DeathsBegin End
Total Yearsa
Sart 1812 1900 89 2133 189798 3754Polleur 1847 1900 54 1324 71477 1361Tilleur 1847 1866 20 3541 70830 1291Limbourg 1847 1866 20 3343 66856 849
Dami 1789 1909 45 759 34169 951Daoyi 1792 1906 72 3013 216939 4896Feicheng
Yimiancheng1792 1909 69 1587 106172 2227
Gaizhou 1789 1885 54 1384 74715 1350Gaizhou Manhan
1792 1837 12 1417 16500 338
Gaizhou Mianding
1792 1858 27 1640 43070 807
Niuzhuang Liuerbao
1789 1825 27 2156 56810 937
Casalguidi 1819 1859 40 2402 95398 2485Madregolo 1800 1883 80 572 42735 999
1850 1869 19 5361 101864 2546
Niita 1720 1870 146 472 68844 16431199Shimomoriya 1716 1869 145 346 50197
Swedenb
Hög 1829 1867 39 456 18258 302Kävlinge 1829 1867 39 492 19672 399Halmstad 1829 1867 39 618 24727 506Sireköpinge 1829 1867 39 581 23252 424
ConclusionsComparative Results
• Mortality overall was always responsive to economic pressure.– More so in Europe than in Asia
• The response to economic pressure was socially determined
• Responding to economic pressure, households favored some members, and discriminated against others.
• Accordingly, patterns of responses were highly variable across communities.
Table 3.1 Life expectancies at selected ages.
e0 e1 e15 E25 e55
M F M F M F M F M F
Sart 42.8 42.5 51.8 48.4 45.3 43.3 38.1 35.8 16.0 15.8
Chinaa
Dami 39.0b 36.7b 47.7 44.8 41.8 38.0 34.4 34.6 17.7 21.4
Daoyi 35.0b 29.9b 42.7 36.3 42.7 39.3 35.1 34.5 14.7 17.3
Feicheng Yimiancheng
37.3b 30.0b 45.6 36.4 45.6 40.5 37.3 35.0 16.7 17.1
Gaizhou 43.0b 40.6b 52.6 49.6 44.8 45.5 37.9 40.3 18.6 21.3
Gaizhou Manhan36.9b 34.9b 46.3 42.5 44.1 41.2 36.9 36.3 17.2 18.0
Gaizhou
Mianding
40.3b 34.5b 49.3 42.0 41.8 42.7 33.9 37.0 12.7 16.7
Niuzhuang
Liuerbao
37.3b 41.4b 45.6 50.7 45.0 43.9 37.8 38.0 15.9 17.4
Casalguidi 36.0 33.6 44.2 40.8 44.9 43.3 36.8 35.8 15.9 17.4
Madregolo 36.0 34.4 46.0 42.2 47.4 43.8 39.0 36.2 15.8 16.1
Japanc
Niita, Shimo-moriya
35.1d 35.0d 42.2 42.1 44.8 41.8 38.3 35.5 16.4 16.3
Hög, Kävlinge, Halmstad, Sireköpinge
40.2 41.2 49.4 49.3 45.8 45.7 37.5 38.2 15.2 14.8
Table 3.3. Percent change in infant and child mortality associated with a 10% price increasea
Infants (0-24 months) Children (2-15 years)
Females Males Females Males
Country Site % p % p % p % p
Belgium Sart 5.07 0.14 -0.60 0.83 7.91 0.06 13.51 0.00
China Liaodong North -0.42 0.79 -0.32 0.74
Liaodong South 2.27 0.08
Italy Casalguidi 0.21 0.94 8.29 0.00 12.84 0.00 10.55 0.04
Madregolo -3.73 0.10 5.72 0.00 4.95 0.16 11.83 0.00
Japan Niita and Shimomoriya
7.80 0.00 -0.87 0.83 4.00 0.00 0.88 0.61
Sweden 4 Scanian parishes 5.61 0.04 5.39 0.02 8.28 0.02 7.80 0.02
a Based on results from the comparative individual models.
Table 3.4. Percent change in adult and elderly mortality associated with a 10% price increase
Ever-married adults Ever-married elderly
Females Males Females Males
Country Site % p % p % p % p
Belgium Sart 6.85 0.10 0.71 0.88 -3.72
0.35 -5.50
0.11
Liaoning Liaodong North 1.62 0.02 2.62 0.00 -0.12
0.88 2.05 0.01
Liaodong South -0.09
0.93 -2.39
0.01 -0.24
0.82 -1.51
0.13
Italy Casalguidi 14.02
0.00 16.91
0.00 15.69
0.00 -0.22
0.96
Madregolo 5.66 0.07 13.65
0.00 8.24 0.05 4.20 0.27
Japan Niita and Shimomoriya
1.67 0.29 4.59 0.00 0.81 0.64 7.59 0.00
Sweden 4 Scanian parishes
7.77 0.03 4.62 0.22 6.23 0.08 5.32 0.13
a Based on results from the comparative individual models.
Table 3.7. Price responses by age and gendera
Infants Children Ever-married
Working-ageAdults
Ever-marriedElderlyAdults
Country Site F M F M F M F M
Sart No No Yes Yes Yes No No No
Liaodong North No No Yes Yes No Yes
Liaodong South Yes No Yes No No
Casalguidi No Yes Yes Yes Yes Yes Yes No
Madregolo Yes Yes No Yes Yes Yes Yes No
Niita and Shimomoriya
Yes No Yes No No Yes No Yes
4 Scanian parishesb
Yes Yes Yes Yes Yes No Yes No
a Based on results from comparative individual models summarized in Tables 3.3 and 3.4. Price effects were considered statistically significant if p < 0.10.
Table 3.8. Differences by socioeconomic status in the response to pricesa
Infants Children Ever-marriedWorking-
ageAdults
Ever-marriedElderlyAdults
Country Site F M F M F M F M
Sart Yes No Yes Yes Yes No No Yes
Liaodong North Yes No No No No Yes
Liaodong South No No Yes No No
Casalguidi No Yes No Yes No Yes No Yes
Madregolo
Niita and Shimomoriya
Yes No No No No No No No
4 Scanian parishesb
No No Yesb Yesb Yesb Yesb No No
Table 5.1. Proportional change in mortality associated with adding 1 adult to the householda
Infants Children
Ever-married Adults
Ever-marriedElderly
Country Site Ratio p Ratio p Ratio p Ratio p
Sart Female 0.97 0.65 0.95 0.50 0.95 0.32 0.89 0.05
Male 1.04 0.48 0.90 0.15 0.92 0.23 0.97 0.49
Liaodong Female 0.98 0.11 1.01 0.06 1.00 0.62
Male 1.01 0.17 0.99 0.03 1.00 0.39
Casalguidi Female 0.96 0.26 0.89 0.07 0.93 0.12 1.08 0.22
Male 0.94 0.05 0.93 0.30 0.95 0.38 0.91 0.15
Madregolo Female 0.98 0.51 1.01 0.89 1.02 0.60 1.04 0.54
Male 0.97 0.25 1.00 0.95 0.99 0.87 0.98 0.69
Niita and Female 0.85 0.18 1.08 0.08 1.05 0.05 0.98 0.75
Shimomoriya Male 0.90 0.22 1.00 0.96 1.00 0.89 1.08 0.05
4 Scanian parishes
Female
0.96 0.13 1.07 0.02 1.04 0.18 1.06 0.18
Male 0.98 0.32 0.99 0.82 0.95 0.24 1.07 0.01
a Source: Comparative household model.
Table 5.2 Proportional change in mortality associated with increasing the proportion of household members aged 0-15 by 20 percentage pointsa
Infants ChildrenEver-married
AdultsEver-married
ElderlyCountry Site Ratio p Ratio P Ratio p Ratio p
Sart Female1.07 0.3
70.97 0.7
80.86 0.01 1.05 0.49
Male0.99 0.9
10.86 0.1
60.92 0.23 1.09 0.16
LiaodongFemale
1.16 0.20
0.98 0.57 1.03 0.50
Male1.14 0.0
1 0.96 0.25 0.99 0.74
CasalguidiFemale
1.16 0.04
1.25 0.08
0.91 0.23 1.18 0.11
Male1.05 0.5
40.98 0.8
91.15 0.17 0.86 0.18
MadregoloFemale
0.96 0.71
0.98 0.94
0.79 0.03 1.22 0.21
Male0.93 0.4
81.05 0.7
71.29 0.10 1.17 0.33
Niita and Female
0.88 0.76
1.13 0.10
0.98 0.81 0.94 0.62
ShimomoriyaMale
0.80 0.74
0.88 0.57
0.93 0.59 1.07 0.28
4 Scanian parishes Female
0.89 0.19
1.15 0.34
1.12 0.21 0.92 0.45
Male0.93 0.3
80.96 0.7
41.11 0.23 1.04 0.73
a Source: Authors’ calculations from coefficients reported by participants from the comparative household models. Adding a child to a household with two adults and a child would increase the proportion below age 15 by 0.17, that is from 0.33 to 0.50.
Table 5.3 Proportional change in mortality associated with increasing the proportion of household members aged 55 and above by 20 percentage pointsa
Infants Children
Ever-marriedAdults
Ever-marriedElderly
Country Site Ratio p Ratio P Ratio p Ratio p
Sart Female1.18 0.2
01.10 0.5
80.91 0.4
40.91 0.17
Male0.95 0.7
00.64 0.0
51.17 0.2
90.99 0.83
LiaodongFemale
1.30 0.06
1.06 0.08
0.98 0.54
Male0.99 0.8
01.01 0.8
10.96 0.11
CasalguidiFemale
1.43 0.00
1.13 0.44
1.06 0.57
1.20 0.10
Male0.86 0.2
80.52 0.0
01.16 0.4
10.86 0.24
MadregoloFemale
1.04 0.84
0.96 0.87
0.92 0.71
1.18 0.32
Male0.84 0.2
90.70 0.2
60.98 0.9
51.05 0.73
Niita and Shimomoriya Female
0.54 0.90
1.30 0.00
1.09 0.09
1.01 0.92
Male1.02 0.9
30.95 0.7
10.98 0.8
31.13 0.00
4 Scanian parishes Female
0.58 0.02
1.06 0.83
0.94 0.74
1.06 0.66
Male0.93 0.6
70.84 0.5
21.31 0.1
91.13 0.37
a Source: Authors’ calculations from coefficients reported by participants from the comparative household models. Adding a child to a household with two adults and a child would increase the proportion below age 15 by 0.17, that is from 0.33 to 0.50.
Table 5.4. Effects of presence of parents on infant and child mortalitya
Parents (Ref: Both)
Infants (0-24 months) Children (2-15 years)Females Males Females Males
Country Site Ratio p Ratio p Ratio p Ratio pSart Father 3.23 0.00 2.01 0.01 1.07 0.78 1.53 0.09
Mother 2.00 0.00 1.57 0.01 1.14 0.52 1.45 0.11Neither 1.72 0.11 1.51 0.19 0.38 0.11 1.34 0.51
Liaodong Father 1.00 0.99 1.30 0.03Mother 0.89 0.74 1.02 0.89Neither 3.29 0.00 1.15 0.50
Casalguidi Father 2.10 0.06 2.54 0.02 1.55 0.22 2.01 0.08Mother 0.79 0.69 0.42 0.22 0.93 0.84 0.88 0.78Neither 4.14 0.05 2.00 0.53
Madregolo Father 1.24 0.42 1.47 0.15 2.19 0.16 1.36 0.62Mother 1.22 0.48 1.85 0.01 2.68 0.03 1.71 0.27Neither
Niita and Shimomoriya Father 0.54 0.76 0.73 0.75 0.90 0.80 0.53 0.38
Mother 0.91 0.84 0.83 0.74 1.26 0.20 0.81 0.49Neither 1.52 0.05 1.52 0.01
4 Scanian parishes
Either or none 2.44 0.01 3.00 0.00 1.16 0.67 0.78 0.50
aSource: Comparative relationship model
Table 5.5. Effects of widowhood on adult and elderly mortalitya
Adults Elderly
Females Males Females Males
Country Site Ratio p Ratio p Ratio p Ratio
Sart 1.08 0.68 1.61 0.02 1.09 0.37 1.21
Liaodong 1.40 0.00 1.15 0.05 1.23 0.00 1.10
Casalguidi 0.77 0.03 1.12 0.23 0.82 0.15 0.97
Madregolo 3.01 0.03 1.31 0.59 0.23 0.17 0.69
Niita and Shimomoriya 1.40 0.12 1.33 0.20 1.31 0.01 1.50
a Source: Comparative relationship model
Prudence and Pressure
• Follow-up volume focusing on reproduction• Fertilty
Prospects for future comparisons
• Extensive published results from Dutch/Taiwanese comparisons
• New databases constructed or being constructed in a variety of settings.
• Some proprietary, some public• New project on East Asian household registers– First topic: migration
• Examples of other datasets follow…
Other databasesPublicly available
• Chosun-era Korean registers– Tansung and Taegu publicly available– Projects at Sungkyunkwan and Seoul National
• Union Army Samples• Historical Sample of the Netherlands• Various other European databases in the next
few years
Union Army Samples
• http://www.cpe.uchicago.edu• P01 AG10120 (Fogel, PI)• Union Army (UA) sample– 40,000 white enlisted men (no commissioned officers)– 331 companies randomly drawn
• US Colored Troops (USCT) sample– 6,000 black soldiers and white officers– 52 companies randomly drawn– Funding obtained to increase sample size
Union Army Samples
• Begin with military records, link forward to pension records (including detailed surgeons’ exams)
• Linkage to manuscript censuses– 1850,1860, 1900, 1910 for white sample• Work in progress on further linkage
– 1850,1860 for free blacks and 1870,1880, 1900,1910, 1920, 1930 for all blacks
Topics Examined with UA Data
• Income effects on retirement• Income effects on living arrangements• Effects of early life disease environment and
occupation type on older age health and mortality
• Effects of wartime stress on older age health and mortality
• Social capital: did it determine willingness to risk death and survival during the war?
HSNHistorical Sample of the Netherlands
- 80.000 Sampled persons (0,5%)from birth certificates 1812-1922
- Whole country (no specific region)- 37.000 Life courses completed: from cradle to grave (1850-2005)- Migration followed all over country- 800.000 Persons (including family)
HSNHistorical Sample of the Netherlands
- Open system (oversamplings, new sources, etc.)
-Website http://www.iisg.nl/hsn
- Data on request (by way of license)only for scientific use (-> [email protected])
Future HSNHistorical Sample of the Netherlands
- Easy download (like IPUMS) for public part (deceased persons)
- Integration with LINKS (matching all civil certificates1812-1912) - Including data on heights males- Life courses 1812-1850 (births)- Geo referencing all addresses
THE FRENCH-CANADIAN DATA BASE
• After a weak initial influx of immigrants, the French-Canadian population essentially grew fom natural increase; 20 000 in 1700, 70 000 in 1760, 200 000 in 1800 and 625 000 in 1850
• Complete set of parish registers dating back to first settlers; good identification allows systematic linking of baptisms, marriages and burials and thus « reconstitution » of population in the form of individual and family files. The growth of the entire population monitored over two centuries
• Research topics for those interested in the Quebec population per se, but also those interested in the Quebec population as a « laboratory population »: heritability of demographic phenomena; fertility vs infant Mortality; seasonality of demographic events; the biology of fertility; early life events and longevity; twinning…
- The French-Canadian data base was set up within the « Programme de recherche en démographie historique » (PRDH) (The Research Program in Historical Demography) at the Demography Department of the Université de Montréal.
- See http://www.genealogie.umontreal.ca/en/leprdh for a short description of the Program and a bibliography
-The PRDH has a policy of making the data available for university research purposes upon request. Contact:
Professor Bertrand Desjardins or Professor Lisa DillonDépartement de démographieUniversité de MontréalC.P. 6128, succ. Centre-villeMontréal (Qc)Canada H3C [email protected]@umontreal.ca
Other databasesAccessible, but not public
• Colonial-era Taiwanese registers– Analyzed by Arthur Wolf and collaborators– Housed at the Program in Historical Demography,
Academia Sinica• http://www.demography.sinica.edu.tw/nuke/
• The French Canadian Database• Utah Population Database• Swedish Demographic Databases
Utah Population Database (UPDB)
►University of Utah research resource
►Facilitate high-quality health related research
►35 years of research ►~7 million people►>100 approved projects
http://www.hci.utah.edu/groups/ppr/
Genealogies (Family History Library)
Vital Records(Births, Deaths/Fetal Marriages, Divorces)
Utah Department of Health
Cancer Records(Utah Cancer Registry, Cancer
Data Registry of Idaho)
Utah Inpatient Hospital Claims
(Utah Dept of Health)
University of Utah Health Sciences
Center
Intermountain Healthcare
Center for Medicare and Medicaid
Studies
Social Security Death Records
Driver Licenses(Utah Department of
Public Safety)
Utah Voter Registration
Utah Population Database
Records Available
in UPDB
RECORD TYPE RECORDS
Family History Records 1,608,131
1880 Census 142,711
Birth Certificates (1915-21, 1947-2008) 2,281,411
Marriage Certificates (1978-2008) 619,534
Divorce Records (1978-2008) 268,616
Death Certificates (1904-2008) 736,903
Fetal Deaths (1978-2008) 8,088
Social Security Death Index 479,491
Utah Cancer Records (1966-2007) 244,949
Idaho Cancer Records (1969-2007) 129,376
Driver License 2,972,422
Inpatient Hospital Claims (1996-2008) 3,004,956
Voter Registration 1,586,962
TOTAL RECORDS 14.1 millionLINKS TO EXTERNAL RECORD SETS
University of Utah Health Sciences Center 1,375,673
Intermountain Healthcare 3,429,337
Medicare Claims 25,666,447
Security and Confidentiality• Not a public database
– For research only– Researchers have no electronic access to identifying
information
• State of the art database• Policies and procedures on confidentiality
– All projects are reviewed by IRB and data contributions
• Require researchers to sign confidentiality agreements• Contact of potential subjects by an appropriate third
party
Wylie and Mineau, Biomedical databases: protecting privacy and promoting research.
Trends in Biotechnology, March, 2003.
Administration for UPDB
Utah Resource for Genetic and Epidemiologic Researchhttp://www.research.utah.edu/rge/
• 1982 Executive Order of Governor established RGE– A data resource for the collection, storage, study and
dissemination of medical and related information and for the purpose of reducing morbidity
• 2003 Utah State Code 26-15, modified to increase confidentiality of familial and other information
• RGE reports to Associate Vice President for Research, University of Utah