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 Manhan 36.9b 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 MalesCountry Site % p % p % p % pBelgium 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 0.08Italy 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 0.02a 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 elderlyFemales Males Females Males

Country Site % p % p % p % pBelgium Sart 6.85 0.10 0.71 0.88 -

3.720.35 -

5.500.11

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 0.13a 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 MSart No No Yes Yes Yes No No NoLiaodong North No No Yes Yes No Yes

Liaodong South Yes No Yes No NoCasalguidi No Yes Yes Yes Yes Yes Yes No

Madregolo Yes Yes No Yes Yes Yes Yes NoNiita and Shimomoriya

Yes No Yes No No Yes No Yes

4 Scanian parishesb

Yes Yes Yes Yes Yes No Yes Noa 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 MSart Yes No Yes Yes Yes No No YesLiaodong North Yes No No No No Yes

Liaodong South No No Yes No NoCasalguidi No Yes No Yes No Yes No Yes

MadregoloNiita 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 pSart 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 0.49Liaodong Female 0.98 0.11 1.01 0.06 1.00 0.62

Male 1.01 0.17 0.99 0.03 1.00 0.39Casalguidi 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 0.15Madregolo 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 0.69Niita and Female 0.85 0.18 1.08 0.08 1.05 0.05 0.98 0.75Shimomoriya Male 0.90 0.22 1.00 0.96 1.00 0.89 1.08 0.054 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 0.01a 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 ElderlyFemales 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 (-> kma@iisg.nl)

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 3J7bertrand.desjardins@umontreal.caly.dillon@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 RECORDSFamily History Records 1,608,1311880 Census 142,711Birth Certificates (1915-21, 1947-2008) 2,281,411Marriage Certificates (1978-2008) 619,534Divorce Records (1978-2008) 268,616Death Certificates (1904-2008) 736,903Fetal Deaths (1978-2008) 8,088Social Security Death Index 479,491Utah Cancer Records (1966-2007) 244,949Idaho Cancer Records (1969-2007) 129,376Driver License 2,972,422Inpatient Hospital Claims (1996-2008) 3,004,956Voter Registration 1,586,962

TOTAL RECORDS 14.1 millionLINKS TO EXTERNAL RECORD SETS

University of Utah Health Sciences Center 1,375,673

Intermountain Healthcare 3,429,337Medicare 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 UPDBUtah Resource for Genetic and Epidemiologic Research

http://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