The determinants of health among the population aged 50 and over: evidence from Croatia

Author(s)

General research strategy

Time period

Countries included

Main findings

Bobak et al. (1998)

Cross-sectional study in a national sample of the Russian population of social and psychosocial determinants of two self-reported health indicators: self-rated health and physical functioning. Logistic regression for two dichotomised outcomes: poor self-rated health and low physical functioning.

Russia

Material deprivation is strongly related to both outcomes. Education was inversely related to self-rated health. Unmarried men reported poor physical functioning substantially more often. Subjects not approving the economic changes reported poorer health. Subjects who could not rely on informal social structures when in problems reported worse health.

Bobak et al. (2000)

Study examined the association between perceived control and several socioeconomic variables and self-rated health in seven post-communist countries. The associations between poor health and socioeconomic factors were estimated by logistic regression.

1996-1998

Russia, Estonia, Lithuania, Latvia, Hungary, Poland, Czech Republic

Education and material deprivation are strongly related to self-rated health.

Damian et al. (1999)

The five-category dependent variable was grouped into two categories: good and poor self-assessed health. Age, sex, social class, use of physician services, number of chronic conditions, and functional capacity were included as main explanatory factors. Adjusted odds ratios were estimated through multiple logistic regression models.

1994-1995

Spain

Age, chronic conditions, and functional status were the main determinants of perceived health among the Spanish elderly. The effect of social class on perceived health markedly decreases with age.

Desesquelles, Egidi and Salvatore (2009)

The prevalence of self-rated bad health is studied in a cross-national comparative study based on the data of National Health Surveys conducted in France and Italy. Logistic regression models were applied.

2002-2003 (France); 1999-2000 (Italy)

Italy, France

Differences in population structure regarding the individual characteristics (sociodemographic characteristics, diseases and disabilities, lifestyle, and others) significantly affected the SAH in two countries.

Franks, Gold and Fiscella (2003)

Ordinary linear regression analyses were used in this study of adjusted relationships among baseline self-reported health, derived from SF-20 subscales (health perceptions, physical function, role function and mental health) and sociodemographics (age, sex, race/ethnicity, income and education) and subsequent mortality.

1987

USA

Physical function showed the greatest decline with age, whereas mental health increased slightly.

Women reported lower health for all scales except role function. Greater income was associated with better health. Greater education was associated with better health. Compared with whites, blacks reported lower health, whereas Latinos reported higher health.

Hujits and Kraaykamp (2011)

Multilevel regression analyses exploring the extent the often found association between marital status and self-assessed health is influenced by the marital composition of the country people live in.

2002, 2004, 2006

29 European countries

Living in a country with a high proportion of married people appears to be beneficial to the health of never married persons, but detrimental for widowed people.

Divorced, widowed, and never married persons may be worst off when living in countries with high proportions of people who are in the same situation.

The never married are worst off in countries with a high proportion of cohabitants.

Hujits, Monden and Kraaykamp (2010)

Multilevel regression analyses is applied to examine whether own educational level and spouse’s educational level are independently associated with self-assessed health throughout European societies.

2002, 2004, 2006

29 European countries

Educational level and the spouse’s level of education positively affect SAH in Europe. The degree of educational heterogamy does not influence the average level of self-assessed health in a country.

Idler and Benyamini (1997)

Review of 27 international studies

1982-1997

Sweden, Lithuania, Israel, UK, The Netherlands, France, Poland, Hong Kong, Japan, Australia, Canada, USA

Global self-rated health is an independent predictor of mortality in nearly all of the studies, despite the inclusion of numerous specific health status indicators and other relevant covariates known to predict mortality.

Jürges, Avendano and Mackenbach (2008)

Ordered probit regression on SHARE data. Study compares the WHO recommended version (ranging from ‘very good’ to ‘very bad’) with the US version (ranging from ‘excellent’ to ‘poor’) in European countries.

2004

Germany, Spain, Greece, The Netherlands, Austria

Authors assessed the difference of answers of US and WHO version so the SAH questions. They found less than 10% of respondents provided discordant answers.

Jylhä (2009)

Paper presents model describing the health assessment process to show how self-rated health can reflect the states of the human body and mind. Based on the proposed model, it examines the association of self-rated health with mortality.

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Analytic distinction is made between the different types of information on which people base their health assessments and the contextual frameworks in which this information is evaluated and summarized.

Mackenbach [et al.], (2005)

The proportion of respondents with SAH less than ‘good’ was measured in relation to educational level and income level. Inequalities were measured by means of age-standardized prevalence rates and odds ratios.

1980s-1990s

Finland, Sweden, Norway, Denmark, England, The Netherlands, West Germany, Austria, Italy, Spain

Socioeconomic inequalities in self-assessed health showed a high degree of stability in European countries.

The relatively favourable trends in the Nordic countries suggest that these countries’ welfare states were able to buffer many of the adverse effects of economic crises on the health of disadvantaged groups

Leinsalu (2002)

Study examined differences in self-rated health by eight main dimensions of the social structure on the basis of the Estonian Health Interview Survey, carried out in 1996/1997. A multistage random sample (n=4711) of the Estonian population aged 15–79 was interviewed. This study includes those respondents aged 25–79 (n=4011) with analyses being performed separately for men and women.

1996/97

Estonia

Low educational level, Russian nationality, low personal income, and for men only, rural residence were the most influential factors underlying poor health. Education had the biggest independent effect on health ratings. Material resources, in this study measured by personal income, were important factors in explaining some of the educational and ethnic differences in poor self-rated health. No differences between men and women in their health ratings were found.

Mackenbach [et al.], (2005)

Study examined the shape of the relationship between household equivalent income and SAH. Data were obtained from nationally representative health, level of living, or similar surveys and applied to men and women aged 25 years and older in the 1990s.

1990s

Belgium, Denmark, England, Finland, France, The Netherlands, Norway

A higher household equivalent income is associated with better self-assessed health among men and women in all countries, particularly in the middle-income range.

McFadden [et al.], (2009)

Study examined the relationship between SAH and mortality by occupational social class in a prospective study of 22,457 men and women aged 39–79 years, without prevalent disease.

1993-1997

Norfolk - UK

SAH was related to subsequent mortality. The prevalence of poor or moderate SAH was higher in manual than in non-manual classes. However, SAH was similarly related to mortality in manual and non-manual classes.

Meng and D’Arcy (2016)

Study compares determinants of SAH among a large community-dwelling cohort of Canadian seniors (N = 3255) at three points in time (1991, 1996, and 2001), and examines the effects of determinants on change in SAH over a 10-year period. Multivariate ordinal logistic regression on Canadian Study of Health and Ageing data

1991, 1996, 2001

Canada

Factors including cognition, daily functioning, chronic disease, and availability of help were significantly linked to self-rated health over time.

Nicholson et al. (2005)

Study examined the influence of socioeconomic risk factors over the life course on the SAH of older Russian men and women. A random sample of the general population of the Russian Federation in 2002 included 1004 men and 1930 women aged 50 years and over in a cross-sectional study.

2002

Russia

Self-rated health in older Russians reflects social exposures accumulated over the life course, with the differentials observed only partially explained by current social conditions. Health behaviours were not involved in mediating social differences in self-rated health.

Pirani and Salvini (2012)

Stepwise multilevel logistic regression models using the data on health conditions which come from a survey conducted by the Italian National Statistics Institute (ISTAT).

2004-2005

Italy

Each component of the socioeconomic status is autonomously correlated with individual perceptions of health. The lack of a network of relationships was also found to be strongly associated with a poor health status for elderly Italians.

Reile and Leinsalu (2013)

Multinomial logistic regression analysis was used to study the association of socio-demographic, physical and psychological health and well-being characteristics

with positive (good or very good) and negative (bad or very bad) SAH as compared to fair SAH.

2006

Estonia

Negative SAH was related to male gender, the presence of chronic illnesses, limitations in daily activities and physical functioning, emotional distress, an external locus of control, and to low satisfaction with life and physical fitness.

Positive SAH was related to younger age, an Estonian ethnic identity, and to higher education and income.

Schnittker and Bacak (2014)

Cox regression of SAH predicting mortality on GSS data

1980-2002

Germany

More schooling and more cognitive ability increase the predictive validity of SAH, but neither of these influences explains the growing association between SAH and mortality.

Sun et al. (2007)

Multivariate logistic regression was used to identify the factors associated with good SAH and sex specific effect was tested by stepwise logistic regression.

2005

Japan

Good SAH is correlated with "can go out alone to distant places", no depression, no weight loss, absence of self-rated chronic disease, good chewing ability, and good visual ability in men; whereas with "can go out alone to distant places", absence of self-rated chronic disease, no weight loss, no depression, no risk of falling, independent IADL, good chewing ability, good visual ability, and social integration (attend) in women.