A MULTILEVEL HEALTH PROFILE OF MOSCOW

1

• A MULTILEVEL HEALTH PROFILE OF MOSCOW
• Irina Campbell, PhD, MPH
• ivm1_at_columbia.edu
• www.CampbellHealthAssociates.com

2
Objectives

• 1.) identify macro and micro risk factors for
  poor physical health in Moscow
• 2.) assess the effect of two dimensions of micro
  determinants personal health habits and social
  connectivity, such as social cohesion, social
  support, and social networks
• 3.) examine the hypothesis that relative social
  inequality is a significant structural condition
  at the community level which influences the
  physical health of individuals, as a main and as
  a joint effect with psychosocial behaviors.

3
Results of this study demonstrate that the social
context in a community affects the health of
people living there independently from the
effects of individual health lifestyle or social
connectivity.
4
INTRODUCTION

• The objective of this paper is to describe a
  cross-sectional multilevel health profile of the
  city of Moscow, which was obtained before
  implementation of macro economic changes of
  January, 1992, in a social epidemiological
  survey. The development of a multilevel theory
  and model of health was undertaken in keeping
  with the WHO Healthy City Program and policy for
  the twenty-first century of Health For All by
  the year 2000, the actual difference in health
  status betweengroupsshould be reducedby
  improving the level of health of
  disadvantagedgroups (WHO, 1985).

5
Social epidemiology has traditionally been
concerned with the distribution of morbidity or
mortality in relation to a causal triad personal
characteristics, geographical or community
determinants, and change in occurrence over time.
These parameters were included in the design of
the health profile, which examined the
differential effect of community level social
inequality, a characteristic of the environment
which was hypothesized to increase vulnerability
to poor health-related quality of life (HRQOL) in
the individual host, in addition to the
individual psychosocial risk factors of the host.

6
The 3 research questions addressed in this
paper are

• 1.) to identify the macro and micro level and
  array of risks for poor physical health among
  individuals in the city of Moscow
• 2.) to assess the additive or interactive effects
  on physical health of two dimensions of micro
  level risks - personal health habits and
  psychosocial behaviors, such as social
  connections in the form of cohesion, support,
  formal and informal networks
• 3.) to examine the hypothesis that the
  distribution of social inequality at the
  community level influences the physical health of
  individuals, as a main and joint effect with
  personal health habits and psychosocial behaviors.

7
Multilevel models

• A multilevel theoretical perspective of health
  provides explanations for multidimensional
  problems such as the health patterns among
  individuals in groups as a consequence of social
  relationships between groups and among
  individuals within groups. Multilevel models may
  explain the variation in physical health by
  apportioning the effect directly to
  characteristics of the individual, to community
  contexts, or to the interaction between the
  individual and community context. Multilevel
  models are thus able to provide a robust
  statistical analysis of clustered, hierarchical
  data, such as individuals within groups or
  multistage sampling designs, without losing
  information about the independent effect of
  groups or strata on individuals.

8
Multilevel models of health can analyze the
emergent properties of social structure, such as
social inequality or relative income inequality,
in conjunction with micro level properties, such
as smoking, drinking, distress, gender, or
educational level. Context or the emergent
properties of structure at each level refer to
those characteristics which exemplify aspects of
the whole unit of analysis and not the separate
components of that unit (Blau, 1980). Contextual
analysis can explain the influences which the
structure of a unit has within a hierarchy and
upon its individual components.
9
Macro determinants of health in Moscow

• Reduction of inequalities in health has become a
  major concern of both national and international
  public health policy (Kaplan, 1997 WHO, 1994).
  There has been some debate on the lack of
  standard definitions and measurement of
  health-related inequality as a risk factor or
  outcome, as a micro and macro level indicator, or
  as a relative versus average indicator. Absolute
  standards of living as well as income
  distributions have become conventional
  determinants of public health.

10
Inequality in health has been successfully
related to multiple dimensions of socioeconomic
position occupational status and prestige,
education, and income or access to resources
(Siegrist, 1995). Each dimension of social
inequality may not only have a unique
distribution in a community, but be related to
different sets of health determinants. The
theoretical contribution of the relative
definition of social inequality addresses the
structural issue that an individual has a variety
of social relations which are associated with a
variety of social positions within an array of
social units (Blau, 1980).
11
The health patterns of East European countries
have followed the deterioration of sociopolitical
structure with the ideological and market
transformations of the 1980s. A similar dynamic
operated in Perestroika Russia prior to the
collapse of the Soviet Union, when widening
income differentials within the country were due
to exogenous changes set in motion by fiscal
policies. Many of these policies cut back the
communist welfare state to stimulate economic
growth and privatization, changing the relative
and average distributions of social status and
health.
12
Three dimensions of social inequality,
occupational status and prestige, education, and
income, were measured by relative indicators as

• 1.) occupational status and prestige - the ratio
  of blue-collar to white-collar residents within
  areas2.) income - the ratio of below average to
  above average apartment size or per capita living
  space in areas 3.) education - the ratio of
  lower to higher educated residents in areas.

13
Click for larger picture
14
Micro determinants of health in MoscowThere were
three dimensions of micro determinants of
physical health which were included in the Moscow
health profile

• 1.) age, gender, education, marital status,
• 2.) the personal health habits of smoking,
  drinking alcohol, exercise, as well as the body
  mass index (the ratio of body weight to
  height-squared) as an indicator of diet quality,
• 3.) psychosocial factors, such as social
  cohesion, social support, formal networks of
  group memberships and informal networks of
  friends and family who would provide help when
  needed.

15
Social connectivity has been hypothesized as
sustaining individual well-being or physical
health through the integration of the public and
private spheres. The lack of formal networks,
such as participation in religious and community
groups, the lack of informal networks, such as
close friends and family, and the lack of social
cohesion have been associated with greater
mortality from cardiovascular diseases (Bruhn,
1979), declines in life expectancy (House et al.,
1988), increases in homicides, the infant
mortality rate (Kawachi et al., 1997), and crime
(Wilkinson et al., 1998).
16
METHODS

• A random sample of Muscovites with telephones was
  collected, September 15-17, 1991. Only adults 18
  years and older were interviewed. The total
  sample size of nearly 2000 telephone numbers
  (n1991) had a completed interview rate of 81.8
  (n1629). There was a two-stage sample selection
  of respondents. The first stage was a random
  sample of telephone numbers within the 33 Moscow
  administrative districts the second stage was
  the random selection of one respondent using Kish
  probability tables.

17

• The Physical Health Profile is constructed from a
  series of questions concerning disability, 13
  specific chronic conditions, 11 specific
  symptoms, and three energy levels. The four
  dimensions were combined into a mutually
  exclusive seven-point spectrum, based on
  frequency of conditions within the past 12
  months from optimum health of having 1) high
  energy to 2) low/medium energy levels 3) one or
  more symptoms 4) one chronic condition or
  impairment 5) two or more chronic conditions or
  impairments 6) restricting activities, type or
  hours of work for 6 months or longer and 7)
  severe disability, reported as difficulty with
  feeding, dressing, mobility, or inability to work
  for 6 months or longer.

18
Social inequality indicators were derived from
the 1989 City of Moscow census. Average
inequality was measured by two factors extracted
by varimax rotation access to material resources
(eigenvalue 8.64) and new development of
resources (eigenvalue2.51). The two factors had
an inverse relationship and varied with
geographic location centrally located areas with
access to resources around the Kremlin and
peripherally located areas with less access but
greater new development of resources on the outer
boundaries of the city.
19
The multilevel model was estimated in stages.
Initially the null model was estimated to derive
the intraclass correlation coefficient (ICC) the
proportion of variance in physical health that is
due to the variation of physical health between
areas as a portion of the total variance ?
?00/(?00 ?2).
20
RESULTSGeographic variation

• Average inequality varied by geographic location.
  Most areas scored consistently as centrally
  located near the Kremlin with high access/low new
  development, or peripherally located with high
  new development/low access. Areas with a larger
  ratio of big families (5 or more members) were
  correlated with areas which had greater ratios of
  smaller than average apartments, lower educated
  and blue collar residents, and were located in
  the periphery of Moscow.

21
Logistic regression

• The array of factors which predicted poor
  physical health at the individual level did not
  vary by the average inequality within areas.
  Average inequality was not a significant
  predictor for the fully adjusted model. Almost
  identical models were significant for the sample
  as a whole, and within both high access and new
  development urban areas. There was a slight
  effect of living in areas which had high access
  to material resources as compared to areas of new
  development areas on the poor physical health of
  women (Table 2)

22
(No Transcript)
23
Click for larger picture
24
Hierarchical Linear Regression

• The multilevel model of physical health is shown
  in Table 3 . The coefficients may be contrasted
  to the base intercept category of a 45.22 year
  old man, with better than a secondary/technical
  level education, and who consumed about 0.26
  liters of alcohol per month.

25
Click for larger picture
26
Click for larger picture
27
Model 2, in Table 3 , illustrates that gender,
age, and education had fixed main effects in
a bivariate model of physical health, which
varied significantly between individuals but not
between urban areas. Individual level education
was a significant predictor, in contrast to the
absence of this expected relationship in the
logistic regression. Neither marital status nor
informal networks were significant predictors of
physical health, consistent with the logistic
model. Lack of social cohesion and social
support, as well as membership in either social
or child related groups, also had significant
fixed effects on poor physical health.
28
None of the level 2 macro indicators varied
randomly or were significantly related to
physical health outcome in a bivariate model.
Several alternative variables were included in
the model as possible explanations of the
significant contextual effect shown by model 1.
An interaction between level 1 and level 2
variables may still be significant even if
individual slopes are not random because the test
for detecting an interaction has a higher power
than the test for detecting a random slope.
29
Macro-micro interactions

• The multilevel model explains the change in the
  intercept of physical health by the main effect
  of level 1 or level 2 variables, as outlined
  above. It also explains the effect of individual
  level variables on the intercept of physical
  health by urban area variables through an
  interaction effect. The cross-level model
  formally addresses the hypothesis of the third
  research question. This posits that physical
  health for individuals varies across Moscow due
  not only to gender, age, and education groups
  with various psychosocial factors, but also to
  the moderating effect of relative social
  inequality in the urban areas in which they live
  (Table 4) .

30
Click for larger picture
31
Click for larger picture
32
In the first interaction, poor physical health
was predicted by living in areas with a greater
poverty risk (ratio of large families to all
families) for individuals with poor social
support (model 6), or membership in child/social
(model 8), or religious groups (model 9). While
lack of social support, or greater involvement in
religious activities or other social groups had a
negative effect on physical health, being older
and living in urban areas with a greater ratio of
larger families had a beneficial effect on
physical health while being younger compounded
the negative effect.
33
The second interaction involved gender and
relative income inequality. While poor physical
health was significantly greater among women than
men, it was even worse if women resided in areas
with greater inequality of apartment sizes (Ymen
? 4.12 Ywomen ? 5.34). Obesity, lack of social
cohesion and social support increased the risk
for poor physical health significantly more among
women living in areas with greater inequality
than men. This relationship also held for those
women with an array of formal networks.
34
In the third interaction, the expected positive
association between physical health status and
education was significantly moderated by the
contextual effect of alcohol consumption level in
urban areas when social support was lacking, or
there was participation in professional or
child-related groups. The main effect of
education on physical health was positive for
individuals living in areas with mean alcohol
consumption, as was the main effect of urban area
alcohol consumption levels for individuals with a
secondary/technical level of education.
35
This interaction is partially due to average
inequality and relative inequality being
geographically related to mean alcohol
consumption in urban areas. Greater access to
material resources and lower ratios of inequality
in education were found in central areas, which
had average alcohol consumption levels.
Individuals living in such areas with lower
education had better physical health than if they
lived in other urban areas. About half of the
peripheral urban areas with low access to
material resources and higher ratios of
inequality in education were also areas with
higher than mean alcohol consumption.
36
DISCUSSION

• In this cross-sectional multilevel study of the
  city of Moscow, the context of social inequality
  characterizing the urban area in which
  individuals lived was found to have significant
  main, additive, and interactive effects on
  individual physical health, controlling for
  gender, age, educational level, personal health
  habits, and social connectivity. Although
  proximal individual lifestyle behaviors have been
  most often examined as causes of poor health, the
  structural effects of social context have not
  been systematically addressed in the same model.

37
Variation in physical health was due to gender,
age, education, lack of social cohesion, and
involvement in two types of formal networks
religious groups and child related or other
social groups. Hierarchical linear regressions
indicated that physical health was also due to
the relative social inequality in urban areas,
regardless of which psychosocial factors
influenced health. In addition, the random effect
of formal networks supported the hypothesis that
the distribution of physical health was
significantly different between urban areas due
to the distribution of professional group
membership between urban areas, as well as social
inequality.
38
However, education, poor diet, professional
group membership and lack of social support in
the form of poor marital relations were found to
have direct effects on the physical health of
individuals by the multilevel model. Although
individual educational status and increased
alcohol use were not related to better physical
health in the expected direction in the logistic
regression, a similar relation was not replicated
by the hierarchical regression. The multilevel
model indicated that a contextual effect of area
level alcohol consumption was significant in
moderating the effect of education on physical
health, while individual alcohol consumption did
not have a significant main effect, accounting
for the unexpectedly disparate finding of the
logistic model.
39
The identification of conditions which increase
the health disadvantage of some social groups is
important for defining the targets of preventive
health policy. The multilevel city health profile
of Moscow demonstrated which specific structural
conditions at the community level and which
specific psychosocial factors at the individual
level could be improved by health policy.
40
CONCLUSION

• The Moscow City Health Profile found that
  individual physical health depended upon macro
  indicators of relative social inequality, and
  micro indicators of social connectivity and
  personal health habits. There was support for the
  hypothesis that the contextual effects of
  relative social inequality acted upon physical
  health independently from psychosocial factors.
  The structural conditions in Moscow which
  increased the vulnerability of specific social
  groups for poor physical health were identified
  for health policy as relative income inequality,
  poverty risks, and mean levels of alcohol
  consumption in urban areas.

41
Although political liberty and economic
prosperity were low in Soviet Russia relative to
western democracies, the centralized planning
within Perestroika Russia nevertheless
distributed economic and social assets more
evenly than the transitional market of today. An
increase in relative social inequality, as a
contextual precursor to individual lifestyles for
example, may be a fundamental structural
condition underlying the current health crisis in
Russia.