Paper for presentation at the IUSSP International Population - - PDF document

Umeå University September 2017 [2017-09-28] Authors (among whom the 1st is corresponding/presenting author):

• 1. Lotta Vikström, Professor of History | Centre for Demographic and Ageing Research (CEDAR)

Umeå University | SE-901 87 Umeå, Sweden | E-mail: lotta.vikstrom@umu.se

• 2. Erling Häggström Lundevaller, Dr. in Statistics | Centre for Demographic and Ageing Research

(CEDAR) | Umeå University | SE-901 87 Umeå, Sweden | E-mail: erling.lundevaller@umu.se

• 3. Helena Haage, Dr. in History | Centre for Demographic and Ageing Research (CEDAR) Umeå

University | SE-901 87 Umeå, Sweden | E-mail: helena.haage@umu.se

Paper for presentation at the IUSSP International Population Conference, Cape Town, South Africa, October 28 to November 4, 2017

Session: 909. Migration and Health Organizer: Philippe Bouquier, Université de Montréal

[NB. This paper is work in progress. Please, don’t quote without authors’ permission.]

On how disability interfered with individuals’ migration, life and death in a past population: Demographic evidence from 19th-century Sweden*

ABSTRACT

Historically, little is known about how disability shaped humans’ participation in work and family which often implied migration. Swedish parish registers digitized by the Demographic Data Base (DDB), Umeå University, enable life course analyses to picture a group long hidden. First, sequence analysis of the trajectories of 8,874 individuals show that disability implied lower levels of work, marriage, parenthood, migration and survival. Second, extending our dataset into 35,109 cases Cox regression models estimate the migration and mortality propensity. Disability significantly impeded relocation and survival albeit with variation across gender and type of disability. We argue that our findings are not only nor directly due to the impairment itself, but also to indirect effects coupled with difficulties and attitudes that disabled people met in society. This jeopardized their socio- economic resources and health across life and makes us discuss their mobility and survival from labeling and ‘healthy migrant’ perspectives.

* This study is part of a project headed by Lotta Vikström that has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme, Grant Agreement

• No. 647125, ‘DISLIFE Liveable Disabilities: Life courses and opportunity structures across time’, 2016–2021 (see

DISLIFE website). This study is also part of another disability project, led by Lotta Vikström, that enjoys funding from one Wallenberg Foundation (Stiftelsen Marcus och Amalia Wallenbergs Minnesfond).

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• 1. INTRODUCTION

In both past and present-day society, migrations are part of young people’s life as they search for work and income to establish themselves and a family on their own. Historically, little is known about how the health status in terms of disability shaped humans’ life and engagement in work and family which often implied relocations. Contemporary disability studies indicate that disability tend to jeopardize humans’ health status and make them weaker positioned in both the labor and partner market than the ’able’ majority (Arvidsson et al 2015; European Commission 2010; Franklin 1977; Mont 2007; National Board of Health and Welfare Report 2010; Schur et al. 2013). Disability history studies are primarily occupied with analyses of records from health institutions to which some people with disabilities were admitted, or the relatively few number of them recognized in

• ther sources because they deviated from the appearances or behaviors perceived as ‘normal’ at

the time (Förhammar & Nelson 2004). Such sources fail to recognize the variety of people with disabilities, many of whom were not institutionalized, and tell little about the lives they led regarding work, family formation, migration and death. The data of this study enable us to analyze the life courses of a large quantity of disabled individuals and to compare the findings with a group of non-

• disabled. Consequently, we can examine one issue that has been insufficiently investigated both

from historical and empirical perspectives, i.e. how humans’ health in terms of disability interfered with individuals’ migration and mortality, and with their involvement in work and family. Thus,

• ur analysis makes a minority group long hidden in society and research come to the fore.

1.1 AIMS OF THE ANALYSIS

The aim of this life course study is twofold, one of which is to provide results on disabled people’s trajectories by using sequence analysis of a series of events in their life compared to non-disabled

• people. The latter function as a control group that helps find out whether and to what extent the

five events of: (1) getting a job (1st occupation recorded); (2) marrying (1st union recorded); (3) experiencing parenthood (1st child); (4) migration (1st departure from parish); and (5) premature death, were less present events in the life of disabled people. Second, we estimate the migration and mortality propensities paying higher attention to the former event as this is less investigated both by us and other scholars. To differentiate the findings, we consistently examine if the

• utcomes vary significantly by gender and disability.

1.2 DISABILITY IN NINETEENTH-CENTURY SOCIETY

Being ill or impaired may have a direct negative impact on people’s health which limit their mobility

• r cut life short in terms of years. However, disability studies of both past and present times show

that people with impairments confront difficulties indirectly, not only with immediate respect to a less healthy status or functionality but primarily due to discriminatory attitudes based on social classifications and prevailing norms in society. Being subject to the label of ‘otherness’ tends to limit people’s opportunities to find work and subsistence, or a partner to share life and a family with (Jaeger & Bowman 2005; Kudlick 2003; Solvang 2000). According to Anne Borsay (2005), disabled people in past Britain were denied citizenship through policymaking, which denied them full rights and inclusion in society, causing them to differ even more from ‘abled’ and ‘normal’

• citizens. Studies further suggest that the economic modernization in terms of industrialization

promoted disabled individuals’ exclusion from society as agricultural work and handicraft were replaced by factory work, having undermined their occupational options and inflicted poverty on them (Barnes, Mercer & Shakespeare 2000; Oliver 1990). In turn, this built on the negative view

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• f disabled people as a ‘social problem’, which jeopardized their chances to fit into society and
• survive. The scientific development in medicine further contributed to this view, calling for a

classification of those who were ill or disabled (Stone 1994). Disabled people thus became subject to definitions depicting them as normal or abnormal, healthy or insane and sick, which increased the perception of them as being both a social and a medical problem. However, in his study of disabled people in 19th-century Scotland, Hutchison (2007) finds that they did not have a uniform experience of marginalization simply due to having a disability. The main issue was rather whether they possessed any ability to work and could support themselves, which varied given their different disabilities. This makes Hutchison conclude that individuals’ disability was above all an economic concern for society and themselves. Olsson (1999) makes use Swedish parish registers in the in the nineteenth century Swedish town of Linköping. While disabled men primarily worked as unskilled laborers or craftsmen or farmhands, their female peers did as maidservants or seamstresses. Olsson further finds that about 25% of them married and recognizes work as key to it, showing that they could support their spouse and future children without rendering any cost to society. Her longevity average measures demonstrate that disabled women grew older than their male counterparts. Since Olsson does not conduct comparisons with non-disabled people, however, the extent to which disability limited individuals’ opportunities it is difficult to assess. Such a comparison is present in the thesis of Sofie De Veirman (2015), who makes quantitative life course analyses of people with auditory impairment and their hearing siblings in Flanders before and during industrialization. De Veirman concludes that hearing impairments impeded the employment and marriage patterns of people, particularly among the

• men. Similarly, in his thesis on revolutionary war veterans in the USA, Daniel Blackie (2010)

examines the experiences of some 300 men, of whom about 150 had disabilities. He contends there were similarities between these men regarding their post-war working and family lives. Our own life course studies show that disability decreased both the survival chances and marital prospects

• f individuals, as a possible consequence of disadvantaged opportunities in the labor market

(Haage, Häggström Lundevaller & Vikström 2016; Haage, Vikström & Häggström Lundevaller, 2017). How disability worked to shape people’s migrations seem to be an issue largely overlooked in research, both past and present, probably because impairments is intuitively associated with low levels of spatial mobility or none at all.

• 2. THEORETICAL FRAMEWORKS

Given many of the above notions from literature, there is little wonder why disabled people have become conceptualized within labeling theories (Goffman 1972; Lemert 1967). These theories have not escaped our works in suggesting that social exclusion is the outcome of ‘secondary deviance’. This implies that the labeling, or ‘stigma’, gives rise to a negative social role, status and/or self- identity for the persons it afflicts, which is hard to overcome and risk to damage their access to social networks and occupational options (Vikström 2008, 2011). In the longer run, this can accumulate hardship and bad health that may limit spatial mobility and survival. In treating disabled people as passive and victimized, labeling theorists have received criticism from scholars and particularly within disability studies (Barnes, Mercer & Shakespeare 2000; Susman 1994). Yet the labeling concepts have promoted the recognition of social interaction between people and thus impact of environmental factors pertaining to attitudes. This helps to understand why human life tend to develop in unfortunate directions when disability interferes with it. That this fact cannot

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be explained by the impairment only, the proponents of the ‘social model’ have argued in their rejection to the ‘medical model’ entirely focusing on the individual impairment (Oliver 1990). In recent decades, the healthy migrant hypothesis has appeared in epidemiological and demographic

• research. It has been used less for historical populations and internal migrants and with specific

respect to disability. One of its ideas is to explain why migrants seem to gain a positive health effect from their relocation in comparison with non-migrants (Abraido-Lanza et. al. 1999; Evans 1987; Friesbie et. al. 2001; Kolcić & Polašec 2009; Kristiansen et. al. 2007; Lu 2008). Even though the healthy migrant hypothesis has primarily been tested and verified among immigrant versus native- born populations, it is beneficial for our study in suggesting that migrants are positively selected in that persons who are too old, weak or impoverished less likely to migrate. While the healthier ones set themselves on the move, disabled people would do to a lesser extent. If this theoretical notion holds true, low migration levels would characterize the disabled layer of the population we study, also because disabled people may particularly be subject to lock-in mechanisms since authorities in 19th-century Sweden rejected parishioners unable to provide for themselves through employment,

• r who did not have someone supporting them, to settle in another parish.

The life course approach constitutes one major basis to our analysis, both theoretically and methodologically, as it examines human life across time and since we seek to trace how disability interfered with it. Glen H. Elder (1985) has defined the life course in terms of trajectories (Giele & Elder 1998; Elder, Kirkpatrick Johnson & Crosnoe 2006; Kok 2007). He recognizes a line of development which during young adulthood includes events such as getting a job or having a child, marrying or moving away. These events shape the line of development and are of major interest to us beside premature death, because being disabled may limit one’s chances to take the trajectory

• ne would otherwise have taken. Further, some disabilities may more than others impede the
• pportunities to work or may entail hardship resulting in non-mobility or premature mortality. In

research, life course analyses are still few regarding the quantitative examination of disability impacts (Priestley 2003; Siminiski 2003). As for this lack of studies on past populations, it is primarily due to poor access to data documenting a comprehensive number of disabled people and their trajectories.

• 3. AREA, DATA AND METHODS

The Sundsvall region (Figure 1) is representative of the demographic and economic structures found elsewhere in nineteenth-century Sweden and north-western Europe. The regional population depended on agricultural production until the middle of the century but, in four parishes (Alnö, Skön, Njurunda and Timrå), the demographic and socio-economic structure came to change from the 1860s, as economic activity and the labor market became increasingly based on the sawmill industry. The stimulus given to business and commerce were most evident in the town of Sundsvall, the only significant urban parish in the region (Bergman 2010; Tedebrand 1997). While the 19th-century mortality decline served to bring about a natural increase in population, the sawmill industry exerted a pull on migrants which added to the population growth (Edvinsson, 1992; Vikström, 2003). While there were 18,793 inhabitants in the Sundsvall region in 1840, this number had increased to 46,418 in 1880 (Alm Stenflo 1994).

[Figure 1: Map of Sweden and the Sundsvall region showing the parishes included in the study]

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3.1 DATASET AND DEFINITIONS

The data originate from the 19th-century parish registers of the Sundsvall region, digitized by the Demographic Data Base (DDB), Umeå University, Sweden. It provides linked parish records composed of original records of birth and baptism, marriage, migration, death and burial, as well as catechetical examination records. From selected parishes in Sweden from the 18th and 19th centuries, the DDB registers are linked on an individual level and thus provide demographic data summarized for each parishioner (Nilsdotter Jeub 2009; Vikström et al. 2006). In these records, the ministers made marks about parishioners’ impairments (lytesmarkeringar). Although it is difficult to interpret these marks to know how severe or painful the impairments were (Grönvik 2009; Mont 2007), they show commonly used terms in this historical context to report limits in people’s physical and mental functions (Haage 2012; Rogers & Nelson 2003; Drugge 1988). We use these impairment marks to identify the disabled individuals, and view the concept of ‘disability’ as socially constructed in relation to a physical or mental status that was perceived to be ‘normal’ or ‘healthy’ at the time. The parish registers reflect these circumstances and inform us about differences distinguishing ‘normal’ or ‘able’ parishioners from others who the ministers recognized as ‘disabled’ due to their behavior, ability or health status. This means that those who the ministers recognized as disabled in the 19th-century context are defined as such in our study. Governed by these considerations, we first categorized the disabilities into five groups (Table 1), then modified into three groups: sensory disabilities (visual or hearing defects, being blind or deafmute); physical disabilities (bodily defects, cripples); mental disabilities (due to ‘idiocy’, ‘insanity’).1

[Table 1. Descriptive statistics of the study population (15–35 years old) in the Sundsvall region 1835– 1892: absolute and relative number by disability and gender and other socio-demographic characteristics.]

As the DDB parish registers are recorded longitudinally at the micro-level, we can reconstruct the lives of disabled individuals to conduct statistical life-course analysis. Our whole dataset includes those the ministers report as disabled, as explained above, between 15 and 35 years (N=504). From then onward, we observe them for a maximum of 18 years to focus on the transitional phase in life associated with the major events we study (1st job, 1st marriage, 1st child and 1st out-migration from the parish). Hence, ‘migration’/’departure’ is defined as moves crossing administrative parish

• borders. The observation duration also works to define premature death (<54 years of age). The

DDB digitization further allows us to construct a control group made up by individuals who did not have any impairments and lived in the same time-space context (the 19th-century Sundsvall region). This makes the entire dataset includes a population of 35,610 individuals, where both the disabled and non-disabled cases were 15–35 years old at observation start. However, the majority were below 20 years old as the impairment marks were primarily found among young adult persons.

3.2 METHODS: EVENT HISTORY ANALYSIS AND SEQUENCE ANALYSIS

Event history analysis (EHA) is one of two methods we employ in this study to reveal variations in the individuals’ life courses over time. The method of sequence analysis (SA) is detailed below. EHA models the time it takes before the event in question occurs, in this case migration and death, and enables us to highlight distinctions and similarities between disabled and non-disabled

• individuals. Cox regressions constitute our tool using the statistical computing environment of R

1 These disability concepts were those commonly used in 19th-century society and the sources we use. While these

concepts may be offensive, due to the derogatory meaning they carry today, we have no intention to offend readers in the few cases we use them. The problem of using concepts which risk to be offensive has been discussed (Eggeby 1993).

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(Broström 2012). Cox regression is a standard technique for modelling time to event data and allows the study of the combinational effects of several variables, making it a suitable choice for this study (Kok 2007; Mayer & Tuma 1990; Vikström 2008, 2011). Hazard ratios estimate the covariates’ effects on the propensity to experience the event under analysis during the observation

• time. Because the individuals included in the entire dataset enter the study at different ages (left

truncation) and the observation period is quite extended, using time to event as the time scale is not appropriate (Korn et al. 1997; Thiébaut & Bénichou 2004). To both control for the effect of age on migration or mortality and handle the effect of left truncation, we use age as the time scale in the Cox regressions. This means that the individual’s age at observation start is the enter-value, and the exit-value is their age when observation stops due to death or right censoring. The covariate of major concern is whether individuals are disabled or not and according into the three categories of sensory, physical and mental disabilities. The non-disabled cases constitute the control group. The second covariate of major concern is gender, since research shows that gender determines most outcomes. We also include some other covariates in the EHA models, which can impact on the migration or mortality risks. One covariate is socio-economic status manifested by the father’s occupation, which is grouped into three categories: lower strata, upper/middle strata and the unknown/undefined cases.2 This categorization is based on occupational codes that researchers at the DDB have developed from the parish registers.3 Another covariate concerns periodic cohort by distinguishing between when the individuals lived and are under observation: during pre-industrial time (observation starts between 1835 and 1844), or during industrial time (observation starts between 1865 and 1874). We account for yet another few covariates in the Cox regression models such as birth place, marital status and having occupation or not, of which the latter two we treat as time-dependent variables beside having disability or not. While EHA is run on the entire dataset, the SA is used for the subset (Abbott 1990, 1995; Ritschard & Oris 2005). According to Abbott (1990), sequence analysis (SA) can be applied to identify: (1) typical trajectories; (2) factors contributing to shaping these trajectories; and (3) if different trajectories affect some outcome variable. This study refers to all these applications, as it concerns whether disabilities (cf. factor) made people’s trajectories differ from the typical ones, and with what consequences for the migration or mortality (cf. outcome). We start to observe all disabled and non-disabled individuals in the subset after their 15th birthday to investigate five events: 1st

• ccupation, 1st marriage, 1st child, 1st out-migration (from parish) and death. The observation

period is the same as for the entire dataset (maximum 18 years), but as the individuals targeted for the SA are aged 15 at observation start we follow them at the longest until 33 years of age. All our analyses are performed in the statistical environment R, complemented with the package and toolbox TraMineR (Life Trajectory Miner for R) (Gabadinho et al. 2011; Gabadinho et al. 2015). This package makes it possible to analyze categorical sequential data to mine and visualize the life course sequences in our distinct dataset. A sequence is the chronological states that the individual in the subset holds over his/her lifetime. Any shift in state is due to an event or transition in life, here first job, marriage, childbearing, out-

2 We selected father’s occupation at the start of the observation of the individuals or immediately before the start.

Socio-economic status is divided into three categories because of small numbers in some of the groups.

3 The DDB classification does not completely correspond to the two commonly used classification schemes in

historical studies, SOCPO and HISCLASS, but there are many similarities between them; for a comparison between the schemes, see the Appendix in Edvinsson and Broström (2012).

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migration or death. These events result in a sequence of different states called ‘life trajectories’. SA enables us not only to analyze single events and their transitions from one point in time to another isolated from other events, but also to study multiple events and their sequential continuity or change in the same analysis (Aisenbrey et al. 2010; Abbott & Forrest 1986; Abbott & Tsay 2000). In this study, all the dates of events are discretized into ‘age years’ whereby the order and spacing

• f events within one age year is ignored. A ‘state’ describes a person that particular year of his/her
• life. The length of each state is consequently one year and the whole sequence is 18 years long

corresponding to the observation time. The first state starts at the 15th birthday and the second state starts at the 16th birthday etcetera. For example, the most common state at observation start is 0. This refers to ‘zero’ events, hence that the individuals had no occupation, were not married, and had no children. If an occupation is recorded at the age of 20, the state changes into 1 at the time point representing that age. During the individual sequences the states change if one event in the series of event we analyze occur.

• 4. RESULTS

The first sub-section below examines the population in the smaller dataset using sequence analysis (N=8,874), followed by two sub-sections showing migration and mortality results based on the larger dataset (N=35,109). We highlight the migration findings as they are fresh and because the relocation of disabled people has been less investigated by scholars.

4.1 LIFE TRAJECTORIES FROM SEQUENCE ANALYSIS

Figure 2 shows the relative distribution by disability and gender among those who died, migrated from the parish of residence or stayed in it during the whole observation period consisting of 18 years (from 15 to 33 years of age). The events of dying and moving out are special, in that they break the completeness of the sequences. About 24% of the disabled individuals, both men and women, departed from their parish during observation. This was a small share compared to the great proportion of migrants found among the non-disabled, where more women than men left the parish (53% and 41% respectively). The low level of migration among disabled people helps explain their high share of mortality in Figure 2, as non-disabled migrants may have passed away in parishes beyond our observation. Disabled men died to a slightly larger degree than did disabled women (13% and 9.5% respectively). The differences between the disabled and non-disabled groups we observe are statistically significant at the 5-% level within each gender.4

[Figure 2: Relative distribution of end states by gender and disability at end of observation: out-migration, death and the proportion possible to follow the entire observation period (from 15 to 33 years of age).]

Our sequence analysis results further show how the trajectories of young adults developed across their lifetime concerning all the five events examined (work, marriage, parenthood, migration, death). Figure 3 displays entire life sequences that indicate the occurrence and timing of these events during observation by plotting the state distributions by time points (here age) per gender and disability (Gabadinho et al. 2011). These plots give another image of the smaller share of migrants found among the disabled than non-disabled people. This share is highest among the non-disabled women, while disabled men and women departed to about the same degree. That the share of migrants drops at a slightly slower pace and later in time among the latter, indicates that

4 Pearson’s Chi-squared tests show P-value=0.00713 for men and P-value=0.000757 for women. The groups in the test are defined

by a contingency table relating disability status (disabled or non-disabled) to the outcomes (observed whole period, moved or died).

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• ut-migration was ‘delayed’ if disability was part of life. The share of men who did not get any job,

stayed unmarried and did not have any children (green-colored state) is considerably larger among the disabled men than their non-disabled peers. At the age of 28, the slope for the former men levels off at about 20%, while for the latter men it continues to decrease. This suggests that men who left the ‘green’ state due to gaining an occupation took up work later in life, if disabled. Death (red-colored state) is the only state where the disabled men were consistently proportionally greater than the non-disabled men. The development over time for the state equal to occupation, marriage and parenthood (purple-colored state) shows no large differences between men according to

• disability. However, this similarity is partly due to that a greater proportion of non-disabled men

(and women) migrated from the parish (grey-colored state), which limit our longitudinal study of their life events. Figure 3 displays a more irregular trajectory patterns for disabled women, due to smaller number of cases and higher number of states, since women and not men were associated with illegitimate offspring. The state equal to having a child without marriage and occupation (blue- and orange-colored states) and the state representing death (red-colored state) show higher shares

• f disabled than non-disabled women.

[Figure 3: Relative distribution of states by time points per gender and disability during observation]

4.2 MIGRATION PATTERNS AND PROPENSITIES

The below results clarify the migration differences between the disabled and non-disabled groups taking the large dataset (N=35,109) into consideration. This means that individuals between 15-34 years of age (hence not only those 15 years old) are subject to our longitudinal observation (of max 18 years) during which we study how disability interfered with migration, equal to the first event

• f departure from the parish of residence.

[Figure 4: Relative distribution of migrations (departure from parish of residence) by age and disability the Sundsvall region 1835–1892.]

Figures 4 illustrate how disability shaped the of age of departure. Beside the small number of departures among disabled migrants, which partly explains their irregular age distribution, their timing in terms of when in life they departed differed markedly compared with those in the control

• group. While the latter primarily set themselves on the move in the age of 20-26, this pattern is less

typical among the former which suggests that disability affected individuals’ migratory behavior. In Sweden, one legislation is of interest from migration perspectives in having enforced people’s work and involvement in the labor market, i.e. The Servant and Master Act (tjänstehjonsstadgan). It was in effect 1664-1926 and stipulated that citizens who were not self-employed or did not live off some property must find subsistence through employment to enjoy their civil rights. Historians argue that the government’s aim with this law was to cut local authorities’ costs for poor relief and to supply employers’ call for a workforce (Harnesk, 1990; Petersson, 1983). This also meant that employment or support from relatives awaited migrants at their new destination. There is reason to assume that these legislation circumstances worked to cut the migration possibilities of people having disabilities, as the graphs of Figure 5 clearly demonstrates for both genders. It plots the cumulative hazards of departure from parish when stratified on disability and gender (all three categories of disability are merged into one category) The larger and more rapidly the curve raises upwards, the more events of departures occurred for individuals within each disability group and gender during observation. Disability did not only decrease the risk to migrate substantially, it also worked to limit the gendered gap concerning this risk.

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[Figure 5: Plotted cumulative hazards showing the migration propensity (departure from parish of residence) by disability and gender the Sundsvall region 1835–1892.] [Table 2: Cox regression of the migration propensity (departure from parish of residence) among disabled and non-disabled individuals in the region of Sundsvall 1835–1892: three Cox regression models.]

Table 2 confirms that the migration propensity differed by disability to a most significant degree. It shows three Cox regression models, also accounting for other factors that may influence the propensity to migrate. Due to assumed differences between and within the genders, Models 2-3 show separate outcomes for men and women, while Model 1 includes all. The individual’s age is compensated for, as age is used as a time scale in the regressions. According to Table 2 (Model 1) there are some variations regarding disability type, one of which is that mental disabilities limited migration the most (with about 70% compared to non-disabled) while having sensory or physical disabilities did to about 50%. The hazards within each gender (Models 2-3) suggest that women’s migration was slightly less affected by disability than men’s, especially among blind and deafmute

• women. The impacts of the other factors go in the expected directions given previous migration

findings (Dribe 2000; Vikström 2003), for example, that the relocation ratios are higher among individuals living in the industrial era than during pre-industrial times. That the hazards in general are higher among unmarried than married people and lower among native-born parishioners than those born elsewhere come as no surprise; nor that having an occupation is associated with higher migration propensity than not having a job since relocations must be afforded and the servant act legislation emphasized employability moving to another parish. Yet, the overall negative effect of disability on departure remains both strong and statistically significant.

4.3 PRE-MATURE MORTALITY RISKS AND DEATH CAUSES

Figure 6 shows similar type of graphs as Figure 5 by replacing the outcome variable of departure from the parish of residence with the event of pre-mature death (<54 years of age). The results emphasize that men with disabilities confronted the highest risk of dying early in life. Even though disability increased women’s mortality too, the gap between them and the curves of non-disabled women is smaller than that separating their male counterparts. Hence, the mortality hazards for disabled men were highest among all other individuals under consideration. We do not show the multivariable regression outcomes for other factors influencing the mortality propensities (since we do in another IUSSP 2017 paper accepted for poster presentation) high and statistically significant, especially for men and people having mental disabilities.

[Figure 6: Plotted cumulative hazards showing the mortality propensity (premature death in the parish of residence) by disability and gender the Sundsvall region 1835–1892]

Now, what did those who passed away while we observed them die from? As the causes of death are in general under-reported in Swedish parish registers and often document symptoms rather than actual death causes, this information is difficult to interpret (Edvinsson 1992, Willner 1999). However, it appears that this under-registration was less the case among the adult individuals we study, probably because their premature death was less expected than among infants and elderly, who made up the mortality majority. As for the entire dataset, the ministers made notations that inform about death causes in about 60% of the total number of death cases (N=2,702), albeit to a lower extent (50%) in the small group of disabled people (in 50 out of 99 cases). Table 3 shows the relative distribution of the most frequent death causes among them and the control group according to the ICD-10 classification system (WHO 2004). There are no statistically significant

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differences between the two groups, but a couple of things stand out. First, disabled people suffered less from infectious diseases (e.g. tuberculosis, typhoid fever, measles, diarrhea) than did control group (17% vs. 26%). Second, the share of external death causes (e.g. murder, suicide, violence, drowning, accidents, poisoned) reveal that disabled people were not subject to dramatic death causes to any exceptional extent.

[Table 3: Relative distribution of frequent death causes by disease groups among individuals who died during observation: comparison between the disabled and non-disabled group.]

Even if being a most preliminary examination, the higher share of the disabled people dying from infectious diseases suggest that they led lives in isolation and thus were lesser exposed to such diseases than was the control group. This notion is further supported by the fact that so few individuals with disabilities died from external death causes, possibly indicating their low participation in the labor market or social life and in society where people tend to confront dangers resulting in such death causes.

• 5. CONCLUDING DISCUSSION

The overarching aim of our study was to advance the knowledge on whether and how disabilities have interfered with individuals’ opportunities in society historically. Making use of micro-level longitudinal parish registers digitized by the Demographic Data Base (DDB), Umeå University, we employed sequence analysis and event history analysis on a 19th-century population comprising some 35,000 individuals in the Sundsvall region, Sweden. This section sums up the major findings

• n how disability shaped individuals’ migration, life and death in the past followed by a theoretical

discussion on why we come across the results we obtain. First, the life trajectories of disabled people were outlined and compared with a control group using sequence analysis. The outcomes yield a comparatively complete picture of how disabled people moved through life as young adults. With regards to work and family, there were substantial differences between their trajectories and the controls. Whereas the latter often experienced several

• f the events under study while we observe them (job, marriage, parenthood and migration),

disabled people did to a lower extent. Even if it was not impossible for them to find occupation, considerably fewer of both the men and women worked or married a spouse as compared to the controls; and if they did, they did later in life. When disabled men took up work, this did not render many of them earnings to eventually afford a family. That no less than one disabled woman in five gave birth to illegitimate offspring is indicative for that disability was coupled with vulnerability. In all, the life sequences we outline suggest that disability had negative effects for individuals’

• pportunities in both the labor and marriage markets.

Second, the migration outcomes of the event history analysis (Cox regression models) demonstrate that disability decreased the propensity to migrate to a statistically significant and profound degree, among both genders but slightly more among the men. However, type of disability mattered more than gender. The lowest risks to relocate was associated with mental disabilities followed by physical disabilities, while sensory disabilities did not impede the migration propensity as much, especially not among the women. Yet hearing and visual disabilities limited migration to most significant levels, as well. This variety suggests that disabled people comprised a heterogenous group with different obstacles in life. The Cox regression results showing how disability increased premature mortality add to this conclusion with specific respect to gender. Men’s survival decreased substantially more if disability was part of life, than if it was for women albeit they suffered, too.

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In uncovering life course development during young adulthood our trajectory findings help explain empirically why disability resulted in low migration levels and high levels of premature mortality. Yet there is reason to consider these results from the theoretical perspectives introductory

• addressed. Proposing that migrants are positively selected while impoverished or weak people are

less likely to take to the road, the ‘healthy migrant hypothesis’ seems to hold true for the disabled people we study given their low migration propensity. This indicates that they were subject to unhealthy living conditions and insufficient resources for realizing relocation. Their untimely death further suggests that these poor conditions accumulated over lifetime. In recognizing weaker layers

• f populations as non-migrants, the healthy migrant hypothesis and accumulation of disadvantages

across life suggests why considerably fewer of the disabled people experienced work, marriage and family formation compared to the controls. Basically, death constituted the only event under study that disability did not impede. Most likely, lock-in mechanisms contributed to these results since authorities in 19th-century Sweden rejected citizens to settle in another parish if they were unable to provide for themselves through employment, or did not have someone else supporting them. Our preliminary study of death causes yielded yet some evidence of lock-in mechanisms. That disabled people did not die from infectious diseases to the same extent as did the controls suggests that the former led lives less exposed to such diseases by few interactions with others. This notion

• f isolation is also supported by the fact that disabled people rarely died from external death causes,

possibly due to low participation in the labor and marriage markets and society at large. Yet they ran far higher risks to meet an untimely death than did the non-disabled. Although the results we obtain demonstrate that disability brought difficulties in human life, the impairment per se must not immediately have jeopardized the health status or prospects in the labor and partner markets or the relocation between these markets. It takes more to explain why work, marriage and migration were less present events in the life of disabled individuals and to understand their high premature mortality propensity. We argue that our findings are not only nor directly due to the impairment itself, but also to indirect effects coupled with socio-economic hardship and negative attitudes in society that afflicted people labeled disabled. These circumstances explain the limited opportunities to take up occupation and start family formation if disability interfered with individual life. Less work or no job cut their income and chances to migrate, marry and survive, because the disability label accumulated disadvantages across the life course.

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• f a Survey: Choice of the Time-scale, American Journal of Epidemiology, 145: 72–80

Kudlick, C.J. (2003), Disability history: Why we need another ‘Other’, American Historical Review, 108: 763– 793 Lemert, E. M. (1967). Human Deviance, Social Problems, & Social Control. New Jersey: Prentice-Hall Inc. Lu, Y. (2008), Test of the ‘healthy migrant hypothesis’: A longitudinal analysis of health selectivity of internal migration in Indonesia’, Social Science & Medicine 67, 1331–1339 Mayer, K.U. & N.B. Tuma, eds, (1990), Event history analysis in life course research, Madison Wisconsin: Univ

• f Wisconsin Press

Mont, D. (2007), Measuring health and disability, Lancet, 369, 1658–1663 National Board of Health and Welfare (2010), Alltjämt ojämt! [Still unequal!], Report, Stockholm Nilsdotter Jeub, U. (1993). Parish Records: 19th Century Ecclesiastical Registers. Umeå, Umeå University: Information from the Demographic Data Base Oliver, M. (1990). The Politics of Disablement. Hampshire: The MacMillan Press Ltd. Olsson, I. (1999). “Att leva som lytt. Handikappades livsvillkor i 1800-talets Linköping.” PhD Diss., Linköping University Petersson, B. (1983). Den farliga underklassen: Studier i fattigdom och brottslighet i 1800-talets Sverige. Umeå: Umeå universitet Priestley, M. (2003) Disability: A Life Course Approach. Cambridge: Polity Press Schur, L. et al (2013), People with disabilities: Sidelined or mainstreamed? Cambridge University Press Ritschard, G. & Oris, M. (2005), Life Course Data in Demography and the Social Sciences: Statistical and Data Mining Approaches, in R. Lévy et al. (eds), Advances in Life Course Research, pp. 283-314, Oxford: Elsevier Rogers, J. and Nelson, M.C. (2003), Lapps, Finns, Gypsies, Jews and Idiots Modernity and the Use of Statistical Categories in Sweden. Annales de démographie historique 1 no 105: 61–79 Schur, L., Kruse, D., & Blanck, P. (2013). People with disabilities: Sidelined or mainstreamed? Cambridge University Press Siminski, P. (2003), Patterns of disability and norms of participation through the life course: Empirical support for a social model of disability, Disability & Society, Vol.18, 707–718 Solvang, P. (2000), The Emergence of an Us and Them Discourse in Disability Theory. Scandinavian Journal of Disability Research 2: 3–20 Stone, D. A (1984). The Disabled State. Philadelphia: Temple University Press Susman, J. (1994), Disability, stigma and deviance, Social Science & Medicine, Vol.38, 15–22

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Tedebrand, L. (1997) Gamla och nya stadsbor efter 1860. In Sundsvalls Historia Del II, edited by L. Tedebrand, 101–136. Sundsvall: Stadshistoriska Kommittén Sundsvalls Kommun Thiébaut, A. C. M., Jacques Bénichou, J. (2004), Choice of Time-scale in Cox’s Model Analysis of Epidemiologic Cohort Data: a Simulation Study. Statistics in Medicine 23: 3803–3820 Vikström, L. (2003) Gendered routes and courses: The socio-spatial mobility of migrants to nineteenth-century Sundsvall,

• Sweden. Diss: Umeå University, Demographic Data Base

Vikström, L. (2008), Illuminating the Labeling Impact of Incarceration: Life-Course Perspectives of Young Offenders’ Pathways in Comparison to Non-Offenders in Nineteenth-Century Northern Sweden. Crime, History and Societies 12: 81–117 Vikström, L. (2011), Before and After Crime: Life-Course Analyses of Young Offenders Arrested in Nineteenth-Century Northern Sweden. Journal of Social History 44: 861–888 Vikström, L. (2017), E. Häggström Lundevaller & H. Haage (2017). Sequence analysis of how disability influenced life trajectories in a past population from the nineteenth-century Sundsvall region, Sweden, Historical Life Course Studies, 4: 97-119 Vikström, P., Brändström, A. & Edvinsson, S. (2006), Longitudinal Databases: Sources for Analyzing the Life Course, History and Computing 14, 109-128 Willner, S. (1999) Det svaga könet? Kön och vuxendödlighet i 1800-talets Sverige. [The Weaker Sex? – Gender and Adult Mortality in 19th Century Sweden.] PhD diss. Linköping: Linköping University World Health Organization (2004) International statistical classification of diseases and health related problems (The) ICD-10. World Health Organization

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TABLES AND FIGURES

Table 1. Descriptive statistics of the study population (15–35 years old) in the Sundsvall region 1835– 1892: absolute and relative number by disability and gender and other socio-demographic characteristics.

Covariates Men N= 17,431 N (% of men) Women N=17,678 N (% of women) Total N=35,109 N (% of total) Disability Sensory disabled (blind, deafmute) 91 (0.5) 60 (0.3) 151 (0.4) Physically disabled 106 (0.6) 54 (0.3) 160 (0.5) Mentally disabled 111 (0.6) 82 (0.5) 193 (0.5) Non-disabled 17,123 (98.2) 17,482 (98.9) 34,605 (98.6) Periodic cohort Pre-industrial 6,187 (35.5) 6,463 (36.6) 12,650 (36.0) Industrial 11,244 (64.5) 11,215 (63.4) 22,459 (64.0) SES Lower strata 3,811 (21.9) 3,723 (21.1) 7,534 (21.5) Upper/middle strata 5,669 (32.5) 5,682 (32.1) 11,351 (32.3) Unknown/undefined 7,951 (45.6) 8,273 (46.8) 16,224 (46.2) Residence Rural parish 8,504 (48.8) 8,699 (49.2) 17,203 (49.0) Urban parish 3,806 (21.8) 3,880 (21.9) 7,686 (21.9) Rural/industrial parish 5,121 (29.4) 5,099 (28.8) 10,220 (29.1) Source: Digitized parish registers, the Sundsvall region, Demographic Data Base (DDB), Umeå University, Sweden Notes: The socio-economic status (SES) is based on the occupational status of fathers. In the pre-industrial cohort, the longitudinal observation of individuals started 1835–1844, while it for the industrial cohort is 1865–1874. Explanations of disability type: Sensory disabilities: Blind (visual defects ranging from weak-sighted to short-sighted to blind) Deafmute (communication dysfunctions from bad hearing, deafness, stammering, mute) Physical disabilities: Bodily dysfunctions (e.g. crippled, lame, limping, using crutches, missing body parts, small in size, hare-lipped) Mental disabilities: Mental dysfunctions since childhood or from not having developed a full intellect as an adult (e.g. foolish, silly insane, feeble-minded and crazy, less cognizant) Explanations of socio-economic categories: Upper strata

• 1. Large-scale business entrepreneurs
• 2. Higher civil officials

Middle strata

• 3. Small-scale entrepreneurs in trade and industry, master artisans and

craftsmen; farmers, tenant farmers

• 4. Lower civil officials

Lower strata

• 5. Skilled labourers, craftsmen and artisans below the rank of master
• 6. Unskilled labourers in trade and industry; farmhands, crofters,

maidservants

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Table 2: Cox regression of the migration propensity (departure from parish of residence) among disabled and non-disabled individuals in the region of Sundsvall 1835–1892: three Cox regression models.

Covariates sh s showing d dis isabilit ility a and d demographic ic features o es of t the i individuals Cox R Regress ssion ( (Model 1 1) Both genders (N=54,847) Cox R Regress ssion ( (Model 2 2) Men (N=28,152) Cox

• x Regress

ssion ( (Model 3 3) Women (N=26,695) Hazard ratio P-value Hazard ratio P-value Hazard ratio P-value

Disability – Non-disabled (ref.) – Sensory disabled (blind, deafmute) – Physically disabled – Mentally disabled 1 0.494 0.507 0.300

• 0.000

0.000 0.000 1 0.583 0.579 0.215

• 0.008

0.021 0.000 1 0.361 0.437 0.381

• 0.001

0.006 0.000 Gender – Women (ref.) – Men 1 0.785

• 0.000
• Marital status

– Unmarried (ref.) 1 1 1 – Married 0.724 0.000 0.647 0.000 0.763 0.000 SES (by father’s occupation) – Lower strata (ref.) – Upper/middle strata – Unknown/undefined 1 0.800 1.577

• 0.000

0.000 1 0.776 1.715

• 0.000

0.000 1 0.812 1.436

• 0.000

0.000 Employment status – No occupation/unknown/undefined 1 1 1 – Having occupation 1.488 0.000 1.655 0.000 1.426 0.000 Periodic cohort – Pre-industrial (ref.) – Industrial 1 1.402

• 0.000

1 1.327

• 0.000

1 1.457

• 0.000

Birth area – In the regional parish of residence (ref.) – In a neighboring regional parish – In a Swedish parish beyond the region 1 1.504 1.943

• 0.000

0.000 1 1.506 2.078

• 0.000

0.000 1 1.518 1.816

• 0.000

0.000 – Born abroad 1.641 0.000 1.774 0.000 1.573 0.000 – Birth area unknown/undefined 3.566 0.000 3.634 0.000 3.515 0.000

Source: Digitized parish registers, the Sundsvall region, Demographic Data Base (DDB), Umeå University, Sweden Comments and explanations: See Table 1. Notes: Treating the covariates showing disability, marital status and employment status as time-dependent variables makes the number of cases under observation per model increase substantially. The distinct number of individuals are N=35,109 (Men=17,431 & Women=17,678), see Table 1.

Table 3: Relative distribution of frequent death causes by disease groups among individuals who died during

• bservation: comparison between the disabled and non-disabled group.

Charact cter eristics cs o

• f t

the i e ind ndividuals Total Disea ease ca e categ egories es Di Disabled (%) %) Non

• n-disabled

(%) %) N Infectious diseases 17.2 26.4 705 Respiratory diseases 8.1 7.9 214 External death causes 7.1 10.0 266 Other diseases 17.2 17.2 465 Unknown/unspecified 50.5 38.5 1,052 Tot

• tal %

% Total ( (N) N) 100 (99) 100 (2,603) 100 (2,702) Source: Digitized parish registers, the Sundsvall region, Demographic Data Base (DDB), Umeå University, Sweden Comments: Disease categories according to the ICD-10-Code Classification where only the most frequent types of disease causes reported for individuals are accounted for.

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Figure 1. Map of Sweden and the Sundsvall region showing the parishes included in the study. Figure 2: Relative distribution of end states by gender and disability at the end of observation: out- migration, death and the proportion possible to follow the entire observation period (15-33 years of age).

Source: Digitized parish registers, the Sundsvall region, Demographic Data Base (DDB), Umeå University, Sweden Notes: The category ‘Followed 18 years’ includes individuals who are subject for study during the entire observation period (from 15 to 33 years of age). This means they remained in the parish or survived in it until end of observation.

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Figure 3: Relative distribution of states by time points per gender and disability during observation (15-33 years of age).

Source: Digitized parish registers, the Sundsvall region, Demographic Data Base (DDB), Umeå University, Sweden

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Figure 4: Relative distribution of migrations (departure from parish of residence) by age and disability the Sundsvall region 1835–1892.

Source: Digitized parish registers, the Sundsvall region, Demographic Data Base (DDB), Umeå University, Sweden

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Figure 5: Plotted cumulative hazards showing the migration propensity (departure from parish of residence) by disability and gender the Sundsvall region 1835–1892.

Source: Digitized parish registers, the Sundsvall region, Demographic Data Base (DDB), Umeå University, Sweden

Figure 6: Plotted cumulative hazards showing the mortality propensity (premature death in the parish of residence) by disability and gender the Sundsvall region 1835–1892.

Source: Digitized parish registers, the Sundsvall region, Demographic Data Base (DDB), Umeå University, Sweden