ИСТОРИЧЕСКИЕ АСПЕКТЫ БЕЗОПАСНОСТИ
73
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УДК 301-053.9(571.1)
RISK OF SOCIAL EXCLUSION
AND SOCIAL SECURITY
OF THE ELDERLY AGE PERSONS
IN RUSSIAN REGIONS
S.G. Maximova, O.E. Noyanzina, D.A. Omelchenko
Altai State University, Russia, Barnaul,
e-mail: svet-maximova@yandex.ru
An article presents results of the construction and approbation of a theoretical
model of evaluation of risk social exclusion of population in the context of social se-
curity of elderly age groups in Siberian regions. It bases on the results of sociological
research (2016) in three Russian regions: Altai region, Trans-Baikal region and Ke-
merovo oblast (n =779 age of respondents from 55 (women) and 60 (men) years and
older). In theory, the model lays on the following: in is determined by economic (ma-
terial) deprivation, deprivation of social rights (access to social institutes and servic-
es) and deprivation of security (safe environment), deprivation of social participation,
cultural (normative) disintegration and social autism; the above named components
are specic for the group of elderly people, that is a priori a high risk of exclusion;
risk of social exclusion, as a condition and situation of exclusion can be estimated
straightly through the manifestation of its dimensions; the model has a one-way cau-
sality, i.e. the manifestation of one of its dimensions can lead to the high manifesta-
tion of the social exclusion. Basing on dimensions, operationalized in questionnaire,
we calculated as an index of components of the social exclusion, as the total social
exclusion index for elderly people including its regional correlations.
Keywords: social risk, security, social exclusion, people of elderly age groups, mod-
el of social exclusion, condition and situation of exception, indexes of social exclusion.
РИСК СОЦИАЛЬНОЙ ЭКСКЛЮЗИИ
И СОЦИАЛЬНАЯ БЕЗОПАСНОСТЬ
ЛИЦ ПОЖИЛОГО ВОЗРАСТА
В РЕГИОНАХ РОССИИ
*
С.Г. Максимова, О.Е. Ноянзина, Д.А. Омельченко
Алтайский государственный университет, Россия, Барнаул,
e-mail: svet-maximova@yandex.ru
* Публикация подготовлена в рамках выполнения гранта Президента Российской Федерации для
государственной поддержки ведущих научных школ НШ-6535.2018.6 «Социальные риски и безо-
пасность в условиях трансформации миграционных процессов в азиатском приграничье России»
(2018-2019 гг.).
SOCIETY AND SECURITY INSIGHTS
74 № 1 2018
В статье представлены результаты построения и апробации модели
для оценки риска социальной эксклюзии населения старших возрастных
групп регионов России в контексте сохранениях их социальной безопасно-
сти на основе социологического исследования, проведенного в 2016 г. в Ал-
тайском и Забайкальском краях, Кемеровской области (779 человек 55 (жен-
щины) и 60 (мужчины) лет и старше). Теоретически предложенная модель
основана на следующем: она определяется депривацией социально-экономи-
ческой (материальной), социальных прав (доступ к социальным институтам
и услугам) и безопасности (безопасная среда), социального участия, куль-
турной (нормативной) дезинтеграцией и социальным аутизмом. Названные
компоненты и индикаторы специфичны для группы индивидов пенсионного
возраста, которая a priori потенциально является группой риска социальной
исключенности. Риск социальной эксклюзии как состояние и ситуация ис-
ключенности может быть прямо измерен через выраженность компонентов
модели. Модель имеет одностороннюю казуальность, то есть выраженность
одного из индикаторов компонентов эксклюзии может привести к большей
выраженности социальной эксклюзии. На основе операционализированных
компонентов социальной эксклюзии проведен расчет как индекса компонен-
тов, так и общего индекса социальной эксклюзии пожилых, в том числе его
региональные сравнения.
Ключевые слова: социальный риск, безопасность, социальная эксклюзия,
население старших возрастных групп, модель социальной эксклюзии, состо-
яние и ситуация исключенности, индексы социальной эксклюзии.
Problems of the ageing are usually considered in connection with global processes,
such as industrialization or globalization (Bashkireva, Vylegzhanin, Kachan, 2013). Yu.
O.V. Krasnova (2017) characterizes the ageing as ‘the age of bad adaptation», because
the aged person has certain somatic and psychical changes, promoting to transformations
in relation to family life and the environment, as a rule. Psychic and social statuses of
the elderly people are changing, it reects in reducing of physic and social opportunities
(Saponov, Smolkin, 2012).
According to M.E. Elyutina (2015), I.A. Grigoryeva, A.S. Bikulov (2015), the pro
-
cesses are complicated by dominating social understanding about contiguity of the age-
ing, illness and death and negatively inuence on individual status of the elderly man
and makes his/her dependent from the others and, consequently, leads to social exclusion
(Maximova et al.).
An idea about “social exclusion”, initially described deprivation of citizens with
limited abilities, obtained its conceptualization in works by K. Walsh, coauthors (Walsh,
Scharf, Keating, 2017), and was described by indexes of risk and protective factors, dier
-
ent political conditions people need to deal with. In wider sense, social exclusion could be
determined as “process, resulting for individuals and their groups became fully or partly
excluded from participation in social aairs” (Hrast, Mrak, Rakar, 2013). Hence, two prin
-
cipal moments could be specied in the concept of social exclusion. First, social exclusion
ИСТОРИЧЕСКИЕ АСПЕКТЫ БЕЗОПАСНОСТИ
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is the multidimensional notion. People, for example, could be excluded from society be-
cause of unemployment, wage, property, minimal consumption, level of education, quality
of life in country, and citizenship. Owing to it, excluded people testify about insucient
close contacts and respect. However, the concept of exclusion focus attention on multi
-
dimensional nature of deprivation, i.e. people often deprived from many “social factors”
simultaneously. At the same time, exclusion (deprivation) can reveal in economic, social
and political spheres (Saponov, Smolkin, 2012). Second, social exclusion assumes rela
-
tion to certain interconnections between individuals, their groups, and processes, which
led to deprivation. Individuals could be excluded from dierent types of groups at the
same time (Bonfatti, 2015).
Factors of inclusion into social exclusion are poverty, subordination in the sys
-
tem of social identities (race, ethnicity, religion, and gender), social positions (refugees,
migrants), demographic characteristics (education, professional qualication, and age),
and health condition, disabilities or stigma, such as the HIV or the AIDS.
A model of social exclusion, developed by The Social Exclusion Knowledge Net
-
work (SEKN) (Popay, Escorel, Hernández et al., 2008) presents it as result of action of
four interdependent factors (social, cultural, economic and political) at dierent levels
(individual, group, household, local communities, countries, and the world in whole).
The given multidimensional model often lies in the base of scientic analysis of exclusion.
Hence, the explicit connection between exclusion and rights let to cover discrimination
basing on gender, ethnic and religious peculiarities, limitations in health, and so on.
The purpose of the paper is the conceptualization, creation and approbation
of the model of social exclusion of the elderly age population in Siberian regions.
Theoretical model of exclusion
We suggest conceptual model of exclusion for empirical testing and evaluating
of the level of exclusion of the elderly population of three Russian regions. The abovemen
-
tioned approaches formed the bases of the model. The model correlates with the poverty
concept, but its opportunities are rather limited in explanation because social exclusion
reects not only the process of exclusion (dynamic characteristics) but also the condition
of exclusion (static characteristics). Social exclusion can have material (economic) ex
-
pression (distributive dimension of exclusion) and non-material characteristics (relative
dimension of exclusion). The reasons of social exclusion should be considered as at col
-
lective as at individual level.
That is, initially we specify two dimensions of exclusion situation and condition
of exclusion, material and non-material dimensions. However, material component (or sit
-
uation of exclusion) is described by such components as social-economic (material) dep-
rivation (MD), deprivation of social rights (DA) – access to social institutes and services,
and deprivation of security (Envr) (safe environment). Non-material component (condi
-
tion of exclusion) disclosed through the deprivation of social participation (SP), cultural
(normative) disintegration (CD) and social autism (SA).
Material factors of risk of social exclusion often underlie in the base of individual
factors of risk, interact with biological factors of risk, less sensitive to invasions, but often
SOCIETY AND SECURITY INSIGHTS
76 № 1 2018
act as means identication of citizens (families or other groups). They include situation
aspects of life in poverty, low consumption standards, and overcrowding of living (Mil
-
bourne, Doheny, 2012; Najsztub, Bonfatti, Duda, 2015). Thus, N. Delfani and coauthors
(2015) demonstrated inuence of stable poverty on social exclusion.
Social-cultural components of exclusion are described in the concept of cultural
capital by P. W. Kingston (Kingston, 2001), he describes how shared norms determine
individual’s behavior and attach importance to the group membership. Through norms and
socialization, cultural norms “limit and prescribe opportunities of individuals, including in
control of own life” (Rozanova, Keating, Eales, 2012).
Social resources reect inclusion and aliation to social networks, providing per
-
sonal access to information and support of others (Saponov, Smolkin, 2012). Social re-
sources could include weak and strong networks (Victor, Bowling, 2012) and networks,
providing emotional and instrumental supports (Warburton, Cowan, Winterton et al.,
2014), build on the community of interests, activity, family or other ties, uniting indi
-
viduals and dominantly localized in private sphere (Ogg, Renaut, 2012). We suggest to
consider social resources as indexes of social-cultural components of social exclusion,
because individual do not select own gender of ethnicity, but they are able to choose or not
to choose friends, interests and even relatives.
Many researches consider civic and politic participation as separate spheres of ex
-
clusion (Serrat, Villar, Celdrán, 2015), but include them into social resources, because
political and civic participation is highly formalized, and public social resources are con
-
nected with organization structures (Popay, Escorel, Hernández et al., 2008).
SA component, called as “social autism”, reects personal resources, ability to see
advantages in current situation and does not depend on economic, cultural or social status.
These are micro-level resources, including psychical attitudes, psychological wellbeing
and abilities (Anisimov, Zharinov, 2013; Dahlberg, McKee, 2014).
Hence, the model bases on a number of assumptions: 1) social exclusion – is a mul
-
tidimensional phenomenon, reecting as economic-structural as social-cultural aspects
of life; theoretically it is determined by MD, DA and Envr, SP, CD и SA; 2) the above
-
named components and indicators are specic for the group of individual at the elderly
age, which is potential groups of risk of social exclusion; 3) social exclusion as a condition
and situation of exclusion could be directly measured through the expression of its com
-
ponents; 4) the model has one-way casualty, i.e. the expression of one of indexes of exclu-
sion components could lead to higher social exclusion.
Materials and methods
In testing of the model of social exclusion of persons of the elderly age participated
779 citizens of three regions of the Russian Federation of 55 (women) and 60 (men) years
and older, 28.5 % of men and 71.5 % of women among them. In women’s subsampling was
30.7 % of women at the age of 55 – 59 years, 32 % - 60 - 64 years, 21 % - 65 - 69 years,
16.3 % - 70 years and older; among men: 55 % - 60 64 years, 27.5 % - 65 – 69 years,
15.8 % - 70 – 74 years, and 1.8 % 75 years and older. With taking into consideration re
-
lations between spatial characteristics and expressing of social exclusion (K. Walsh [26]),
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we stress, that the research was realized in the Altai and the Transbaikal kray, and the Ke-
merovo oblast.
Thus, each theoretical statement about indexes of social exclusion was operation
-
alized in terms of the questionnaire. Social-cultural component of exclusion, or situa-
tion of exclusion, was described by three components with selected indexes of exclusion:
1) MD (20 indexes); 2) DA (27 indexes); Envr (22 indexes). Social-cultural exclusion,
or condition of exclusion, was also described by three components, including a number
of indexes: 1) SP (25 indexes); 2) CD (19 indexes); 3) SA (13 indexes)
In addition, we specied a number of micro-level risk factors of exclusion, par
of which presented non-corrected factors, and the other – by the corrected ones. Non-cor
-
rected (independent) risk factors of social exclusion: sex, age (for women ≥55 years, for
men ≥60 years); single living; status (employed / unemployed pensioner); pension amount;
marital status; religion; pensionable service; type of settlement (urban / rural). Corrected
(dependent) risk factors: physical activity; health condition; absence of own home; low
education level; coping-strategies; evaluation of material condition; level of adaptation
after retirement.
We calculated the social exclusion index, which is the summary value of expres
-
sion of six components of social exclusion: MD, DA, Envr, SP, CD, and SA. To determine
the expression of each index we transformed the estimation scales: the higher the index
value, the higher social exclusion of the elderly people. Each index in the set were es
-
timated basing on self-estimations of the elderly population by suggested scales, xed
in the questionnaire. Possible summary point by MD was 81 (by result of summarizing
min=32, max=75), by DA - 156 (min=40, max=137), Envr - 157 (min=40, max=150),
SP - 104 (min=43, max=77), CD – 66 (min=21, max=55), SA - 60 (min=15, max=55), that
corresponds maximal expression of social exclusion of each component.
Further, to provide the opportunity of comparative analysis we formed summary in
-
dexes by each component and transformed them into 10-piont scales, calculate summary
indexes of Situation (SitExclInd) and Condition (CondExclInd) of exclusion of respondents;
in total, their summary values composed General Index of Social Exclusion (GenExclInd)
of population of the elderly and senile age in three regions of the Russian Federation, fur
-
ther transformed into 10-point scale. Transformation of indexes into 10-point scale realized
with taking into consideration the accepted regulations about return of fractional numbers,
i.e. 0–0,49 points equaled to 0 points, 0,5- ,49 – to 1 point and so on. Programs IBM SPSS
23.0 and MS Excel were used for statistical possession and visualization of results.
Results and discussion
Index of situation of social exclusion consisted of summary indexes of normal
-
ized indexes of three components – MD, DA, and Envr. By the rst component, 83.3%
of persons of the elderly age have index in the range of 0–0,49 points, i.e. in this group
of non-excluded respondents there are no any deprivation of economic behavior. In result,
in the group of materially deprived respondents of the elderly and senile age the MD index
(MDInd) vary between 4 and 9 points, herewith 4 points described 0.4% of the elderly
population, 5 – 2.4%, 6 – 4.9%, 7 – 3.5%, 9 – 1.4%.
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A non-zero value of the DA index (DAInd) xed for 36.5 55 of the elderly persons –
it varies between 3 and 9 points, the largest group by the DA (15.3%) it equals 6 points.
The Envr index (EnvrInd) is in range of 3 – 10 point for 42.5% of the elderly.
Thus, almost ½ of research participants are deprived from safe environment. It is the only
component of social exclusion with maximal value of 10 points for 0.4 % of respondents,
and for 11.2 % of the elderly population the exclusion in the sphere of safe environment
is expressed at the level of 8 points. In result, the summary index of situation of social
exclusion (SitExclInd) of population of the elderly age in three Russian regions is distrib
-
utes in the range 1 – 8 points, it higher than 1 point for more than a half of respondents
– 60.3%. Hence, the situation of social exclusion is highly expressed for the most part
of respondents: 4 % are described by the summary index of 6 points, 0.5 % – 7 points.
The mean value of the situation of social exclusion index is at the level of 5 point, 8.2 %
with 4 points, 5.8 % with 3 points, 27.9 % with 2 points, and 3.2 % with 1 point are lower
than the mean value.
The condition of social exclusion index (CondExclInd), according to the suggested
conceptual model, described by values of indexes of deprivation of social participation
(SPInd), cultural (normative) disintegration (CDInd), and social autism (SAInd). We note
the distribution of indexes towards higher concentration and evident asymmetry towards
higher values testies about relation between indexes of condition of social exclusion,
unlike the indexes of situation of social exclusion.
Non-zero values of the SP index (SPInd) xed among 15 % of people of the elderly
age, and the values are rather high – 4 – 7 points. Concluding, the exclusion of an indi
-
vidual from the system of social networks has multidimensional character, the alienation
from a number of ties – family, friendship, relative, and neighbor and so on – occurs.
Hence, 0.6% of respondents have SPInd at 4 points, 6.4% – 5 points, 5.8% – 6 points, and
0.6% – 7 points.
The CD became the most expressed – 72.8% of respondents are culturally deprived
with the CDInd at the level of 3 – 8 points. Herewith, the majority of excluded respondents
have highly expressed CD: for 31.3 % the index consisted 6 points, for 16.2% – 7 points,
for 1.8% – 8 points.
41.8% of the elderly and senile age persons have the SA index (SAInd), varying
between 5 and 0 points: for 0.4 % of respondents it expressed at the level of 9 points,
1% – 8 points, 5.6% – 7 points, 11.6% – 6 points, the mean value at the level of 5 points
describes 15.4% of the elderly age persons.
By results of the construction of the summary index of situation of social exclu
-
sion (CondExclInd) we concluded, that the largest part of respondents are in the situation
of social exclusion (79.2%), expressed at the level of 1 – 7 points. Considerable part of the
elderly age persons have value of the CondExclInd of 2 points, 0.5% of respondents 0
at the level of 7 points, 4% – 6 points, 7.6% – 5 points, for other groups the CondExclInd
is lower.
We shall now proceed to consider the General Index of Social Exclusion (GenEx
-
clInd) of the elderly age persons in the Altai krai, the Transbaikal krai and the Kemerovo
oblast.
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In all three regions, the majority of the elderly people are vulnerable to the exclusion
in several extent (86.4 %), social exclusion of the elderly is weakly and averagely expressed,
in whole. Hence, 1/5 part of the elderly population (21.1%) has the GenExclInd in range of 0.5 –
1.49 points, almost the same part of the elderly (20.2%) are in the range of 1.5 – 2.49 points,
17.2% are excluded at the level of 3 points, 13.9% – 4 points. In three regions, 8.1 % of the elderly
have the GenExclInd at the level of 4.50 – 5.49 points. Socially excluded at the level higher than
average are 3.6% of the elderly with the GenExclInd value about 6 points and 0.6 5 – 7 points.
Thus, the maximal valued of the GenExclInd for the elderly and senile population
in three regions was 7 points (index values from 6.50 to 7.49 points). Table 1 presents the
distribution of calculated index values.
Table 1
Distribution of index values of social exclusion of the elderly age persons, %
Index value
MDInd
DAInd
En-
vrInd
SPInd
CDInd
SAInd
SitEx-
clInd
Con-
dEx-
clInd
GenEx-
clInd
0–0,49 (0) 83,1 63,5 57,5 85,0 27,2 58,2 39,7 20,8 15,4
0,50–1,49 (1) – – – – – – 3,2 1,7 21,1
1,50–2,49 (2) – – – – – – 27,9 35, 8 20,2
2,50–3,49 (3) – 0,6 0,5 – 0,1 0,5 5,8 9,8 17,2
3,50–4,49 (4) 0,4 4,4 2,4 0,6 2,7 7,3 8, 2 19,9 13,9
4,50–5,49 (5) 2,4 8,2 10,7 6,4 20,7 15,4 8, 3 7,6 8,1
5,50–6,49 (6) 4, 9 15, 3 10,8 5,8 31, 3 11,6 2,7 4,0 3,6
6,50–7,49 (7) 4,4 6,3 0,6 2,2 16,2 5,6 3,2 0,5 0,6
7,50–8,49 (8) 3,5 1,5 11, 2 – 1,8 1,0 1,0 – –
8,50–9,49 (9) 1,4 0,1 5,8 – – 0,4 – – –
9,49–10 (10) – – 0,4 – – – – – –
Note. Maximal value corresponds to maximal exclusion. Here and further in table
2: maximal mean values are in the bold; values of indexes of situation and condition of so
-
cial exclusion are in italics; MDInd – the index of social-economic (material) deprivation;
DAInd – the index of deprivation of social rights; EnvrInd – the index of deprivation of se
-
curity; SPInd – the index of deprivation of social participation; CDInd – the index of cul-
tural (normative) disintegration; SAInd – the index of social autism; SitExclInd – the sum-
mary index of situation of social exclusion of respondents; CondExclInd – the summary
index of condition of social exclusion of respondents; GenExclInd – the general index
of social exclusion of population.
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To consider regional dierences in distribution of indexes of components of social
exclusion we realized comparative analysis of the mean values of the indexes (table 2).
According to the table 2, there are no any considerable dierences between the expressions
of components of social exclusion. Hence, the most excluded are people of the elderly age
in the Kemerovo oblast with the mean values of social exclusion by all components, and
summary indexes of situation and condition of exclusion are higher. The only component
is highly expressed in the Transbaikal krai, but not in the Kemerovo oblast, - deprivation
of social rights DA (the mean value is 2.15 points in the Transbaikal krai, in the Kemeror
-
vo oblast – 2.10 points, and in the Altai region – 2.05 points).
Herewith, the elderly age persons in the Altai krai have similar level as of condition
(1.9885), as situation (1.9237) of social exclusion, in the Kemerovo oblast and the Transbaikal
krai the condition of social exclusion is highly expressed: μSitExclInd = 1.7588 and μCondEx
-
clInd = 2.3385 in the Transbaikal krai and μSitExclInd = 2.2462 and μCondExclInd = 3.1000
in the Kemerovo oblast. Hence, in the Kemerovo oblast μGenExclInd = 2.8115, in the Trans
-
baikal krai μGenExclInd = 2.1595, in the Altai krai μGenExclInd = 2.0763 (μ – mean value).
Table 2
Mean values of the indexes of social exclusion
of the elderly age groups in regional comparisons
Region
MDInd
DAInd
EnvrInd
SPInd
CDInd
SAInd
SitEx-
clInd
CondEx-
clInd
GenEx-
clInd
The Altai krai
Mean
1,0000
2,0458
2,6660
0,7214
3,2939
1,9771
1,9237
1,9885
2,0763
N
262
262
262
262
262
262
262
262
262
Standard
deviation
2,32264
2,84292
3,17920
1,86381
2,91933
2,67374
2,01001
1,72536
1,75782
The Trasbaikal krai
Mean
0,8872
2,1479
2,2159
0,7121
4,0000
2,2451
1,7588
2,3385
2,1595
N
257
257
257
257
257
257
257
257
257
Standard
deviation
2,20416
2,85481
2,94960
1,87572
2,87228
2,75678
1,87609
1,72476
1,55179
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Region
MDInd
DAInd
EnvrInd
SPInd
CDInd
SAInd
SitEx-
clInd
CondEx-
clInd
GenEx-
clInd
The Kemerovo oblast
Mean
1,5308
2,0962
2,9903
1,1038
5,6115
2,6308
2,2462
3,1000
2,8115
N
260
260
260
260
260
260
260
260
260
Standard
deviation
3,07610
2,84923
3,30067
2,31846
1,69688
2,89358
2,33179
1,52381
1,69915
Total
Mean
1,1399
2,0963
2,6258
,8460
4,3004
2,2837
1,9769
2,4750
2,3492
N
779
779
779
779
779
779
779
779
779
Standard
deviation
2,57628
2,84559
3,15924
2,03615
2,73455
2,78545
2,08914
1,72247
1,70250
Note. Maximal value corresponds to maximal exclusion.
Identication of posterior model of social exclusion
To test the correlation between theoretical and empirical models of exclusion we
used the method of structural equation modeling (SEM) [9], based on conrmatory ap
-
proach. The model was tested with help of quality conrmation tests in the SEM to reveal
the extent of coherence between patterns of dispersion and covariations in initial data
with the structural (path) model, specied by researches. During the modelling and model
testing, we used the AMOS module (Analysis of Moment Structures) version 22.0.0 for
the IBM SPSS.
To construct the structural model we used three latent unobserved variables: F1
describes situation of social exclusion, F2 – condition of exclusion, F3 – risk of social
exclusion. Basing on previous analysis, we supposed situation of exclusion as combining
indexes of MD, DA and Envr, and condition of exclusion – indexes of SP, CD and SA.
Indexes of latent variable F3 were sex, evaluation of material condition, educational level,
family status, presence of children, and pension amount.
In a result of the modeling, we tested the obtained null model (picture) for conr
-
mation. Results of testing demonstrated conrmation between theoretical and empirical
models: the model value χ
2
is not signicant with р<0,0001 and CMIN/DF≤4 (CMIN/
DF – the χ
2
value, divided the number of degrees of exibility in the model; the criteria
shows the adequacy of the χ
2
value for the model; optimal value of CMIN/DF varies from
SOCIETY AND SECURITY INSIGHTS
82 № 1 2018
1 to 3 points); the sampling is adequate for testing of the model (HOELTER, n=327), RM-
SEA (Root mean square error of approximation) ≤ 0,05, corresponds with researches by
L. Hu and P. M. Bentler [14].
Structural model of social exclusion of the elderly age persons.
MDInd – the index of social-economic (material) deprivation; DAInd – the index of deprivation of social
rights; EnvrInd – the index of deprivation of security; SPInd – the index of deprivation of social participation;
CDInd – the index of cultural (normative) disintegration; SAInd – the index of social autism; F1 – situation
of exclusion; F2 – condition of exclusion; F3 – risk of social exclusion; e1,2,3,4,5,6,7,8,9 – errors of endogen
(dependent) variables; material – evaluation of material condition; educ – educational level; familyst – family
status; child – presence of children; pension – pension amount; sex – sex.
Conclusion
Thus, indexes, determined at the stage of theoretical modelling, really determine
the probability of social exclusion in the empirical model; characterize condition, situation
and risk of social exclusion of the elderly age persons, living at the territory of the Siberian
Federal District of the Russian Federation.
REFERENCES
Anisimov, V.N., Zharinov, G.M. (2013). Life span and longevity in representatives of cre
-
ative professions. Gerontology advances, vol. 26, № 3, 405–416.
ИСТОРИЧЕСКИЕ АСПЕКТЫ БЕЗОПАСНОСТИ
83
№ 1 2018
Bashkireva, A.S., Vylegzhanin, S.V., Kachan, E.Yu. (2016). Actual problems of social gerontolo-
gy at the present state of development of Russia. Gerontology advances, vol. 29, № 2, 379–386.
Grigoryev, I.A., Bikkulov, A.S. (2015). Ageing, health and active longevity: semantic con-
text other mentioning in social networks. Gerontology advances, vol. 28, № 2, 354–359.
Elyutina, M.V. (2015).The elderly age persons: relation to death and tantric anxiety, Soci
-
ological researches, no 10, 111–119.
Kasnova, O. V. (2014). Retirement and identity of women. Psychological researches,
vol. 7, no 35, 6. URL: http://psystudy.ru (available at the date: 24.05.2017).
Maximova, S.G., Noyanzina, O.E., Maximova, M.M., Scheglova, D.K. (2015). Soial ex
-
clusion of the elderly age groups: social-economic aspects. Altai State Agrarian University
Bulletin, no 5 (127), 180–184.
Maximova, S.G., Omechenko, D.A., Avdeeva, G.S. etc. (2012). Empirical models of per
-
ception of the ageing in conditions of a new gerontology reality: comparative analysis
of results of sociological research in four Russian regions. The Altai State University
News, no 2–2(74), 242–245.
Saponov, D.I., Smolkin, А.А. (2012). Social exclusion of the elderly: to the working out
of the model of estimation. Monitoring, no 5 (111), 83–94.
Structural modelling in the SPSS AMOS [Electronic Resource] moodle.herzen.spb.ru
(available at the date: 29.10.2016).
Bonfatti, A., Celidoni, M., Weber, G., Börsch-Supan, A. (2015). Coping with risks during
the great recession. In: Börsch-Supan A., Kneip T., Litwin H. et al. (eds). Ageing in Eu
-
rope – supporting policies for an inclusive society. (Pр. 225–234). Boston: De Gruyter.
Dahlberg, L., McKee, K.J. (2014). Correlates of social and emotional loneliness in older
people: evidence from an English community study. Aging Mental Hlth, vol. 18, 504–514.
Delfani, N., De Deken, J., Dewilde, C. (2015). Poor because of low pensions or expensive
housing? The combined impact of pension and housing systems on poverty among the
elderly. Int. J. Hous. Policy, no 15, 260–284.
Hrast, M.F., Mrak, A.K., Rakar, T. (2013). Social exclusion of elderly in Central and East
-
ern Europe. Int. J. Soc. Econ., no 40, 971–989.
Hu, L., Bentler, P.M. (1999). Cuto criteria for t indexes in covariance structure analysis:
Conventional criteria versus new alternatives. Structural Equation Modeling, vol. 6 (1), 1–55.
Kingston, P.W. (2001). The unfullled promise of cultural capital theory. Sociol. Educat,
vol. 74, 88–99.
Milbourne, P., Doheny, S. (2012). Older people and poverty in rural Britain: material hard
-
ships, cultural denials and social inclusions. J. Rural. Stud, vol. 28, 389–397.
Myck, M., Najsztub, M., Oczkowska, M. (2015). Measuring social deprivation and social
exclusion. In: Börsch-Supan A., Kneip T., Litwin H. et al. (eds). Ageing in Europe – sup
-
porting policies for an inclusive society. (Pр. 67–78). Boston: De Gruyter.
Najsztub, M., Bonfatti, A., Duda, D. (2015). Material and social de-privation in the macro
-
economic context. In: Börsch-Supan A., Kneip T., Litwin H. et al. (eds). Ageing in Europe
– supporting policies for an inclusive society. (Pр. 79–90). Boston: De Gruyter.
SOCIETY AND SECURITY INSIGHTS
84 № 1 2018
Ogg, J., Renaut, S. (2012). Social inclusion of elders in families. In: Scharf T., Keating N.
(eds.) From exclusion to inclusion in old age: a global challenge. (Pр. 89–108). Bristol:
Policy Press.
Popay, J., Escorel, S., Hernández, M. et al. (2008).Understanding and tracking social ex
-
clusion: nal report to the WHO Commission on Social Determinants of Health. (P. 207).
Lancaster: Social Exclusion Knowledge Network.
Rozanova, J., Keating, N., Eales, J. (2012). Unequal social engagement for older adults:
constraints on choice. Canad. J. Aging, vol. 31, 25–36.
Scharf, T., Keating, N. (2012). Social exclusion in later life: a global challenge. In: Scharf
T., Keating N. (eds.) From exclusion to inclusion in old age: a global challenge.( Pр. 1–16).
Bristol: Policy Press.
Serrat, R., Villar, F., Celdrán, M. (2015). Factors associated with Spanish older people’s
membership in political organizations: the role of active aging activities. Europ. J. Ageing,
vol. 12, 239–247.
Victor, C.R., Bowling, A. (2012). A longitudinal analysis of loneliness among older people
in Great Britain. J. Psychol, vol. 146, 313–331.
Walsh, K., Scharf, T., Keating, N. (2017). Social exclusion of older persons: a scoping
review and conceptual framework. Europ. J. Ageing, vol. 14, no 1, 81–98.
Walsh, K. (2015). Interrogating the ‘age-friendly community’ in austerity: myths, realties
and the inuence of place context. In: Walsh K., Carney G., Ní Léime Á. (eds.). Ageing
through auster- ity: critical perspectives from Ireland. (P. 79–95). Bristol: Policy Press.
Warburton, J., Cowan, S., Winterton, R. et al. (2014). Building social inclusion for rural
older people using information and communication technologies: perspectives of rural
practitioners. Aust. Soc. Work, vol. 67, 479–494.
