Carola T.M. Schrijvers

Explaining educational differences in mortality: the role of behavioral and material factors

OBJECTIVES This study examined the role of behavioral and material factors in explaining educational differences in all-cause mortality, taking into account the overlap between both types of factors. METHODS Prospective data were used on 15,451 participants in a Dutch longitudinal study. Relative hazards of all-cause mortality by educational level were calculated before and after adjustment for behavioral factors (alcohol intake, smoking, body mass index, physical activity, dietary habits) and material factors (financial problems, neighborhood conditions, housing conditions, crowding, employment status, a proxy of income). RESULTS Mortality was higher in lower educational groups. Four behavioral factors (alcohol, smoking, body mass index, physical activity) and 3 material factors (financial problems, employment status, income proxy) explained part of the educational differences in mortality. With the overlap between both types of factors accounted for, material factors were more important than behavioral factors in explaining mortality differences by educational level. CONCLUSIONS The association between educational level and mortality can be largely explained by material factors. Thus, improving the material situation of people might substantially reduce educational differences in mortality.

Socioeconomic inequalities in mortality and importance of perceived control: cohort study.

Perceived control has convincingly been suggested to be a key concept in explaining socioeconomic differences in health.1 Some empirical evidence exists of a higher prevalence of low control beliefs (such as powerlessness or fatalism) in lower socioeconomic groups and that this is relevant to socioeconomic inequalities in general health.2 However, a systematic examination of the extent to which perceived control contributes to socioeconomic inequalities in mortality is lacking. This is important, as attention has recently shifted towards psychological and psychosocial explanations of socioeconomic inequalities in health. Data were collected in 1991 within the framework of a general population study of the health and living conditions of the population of Eindhoven and its surroundings (the GLOBE study).3 We invited a random subsample for interview. The response rate was 80% and not related to demographic characteristics. Interviewdata were available for 1220 men and 1242 women aged 25-74 (51 on …

Educational level and decreases in leisure time physical activity: predictors from the longitudinal GLOBE study

STUDY OBJECTIVE This study describes educational differences in decreases in leisure time physical activity among an adult, physically active population and additionally attempts to identify predictors of these differences from information on health status and individual and environmental factors. DESIGN Prospective population based study. Baseline measurement were carried out in 1991 and follow up in 1997. SETTING South eastern part of the Netherlands. PARTICIPANTS The study included 3793 subjects who were physically active in 1991 and who participated in the follow up. METHODS Potential predictors of decreasing physical activity were measured in 1991. Logistic regression analyses were carried out for two age groups (<45 years; ⩾45 years) separately. MAIN RESULTS Lower educated respondents experienced statistically significant higher odds to decrease physical activity during follow up, compared with respondents with higher vocational schooling or a university degree. Perceived control was the main predictor of educational differences in decreasing physical activity in both age groups. In the older group, material problems and a poor perceived health experienced by lower educated people additionally predicted educational differences in decreases in physical activity during leisure time. CONCLUSIONS These findings have important implications for health promotion practice and policy to prevent socioeconomic differences in physical inactivity and health. There is a need for evidence-based interventions that improve perceived control and reduce material problems in lower educated groups.

Educational differences in leisure-time physical inactivity: a descriptive and explanatory study

In this study we aim to explain educational differences in leisure-time physical inactivity in terms of psychosocial and material factors. Cross-sectional data were obtained from the baseline of the Dutch GLOBE study in 1991, including 2598 men and women, aged 15-74 years. Physical inactivity during leisure time was defined as not participating in any activity, such as sports, gardening, walking or cycling. Psychosocial factors included in the study were coping resources, personality, and stressors. Material factors were financial situation, employment status, and living conditions. Logistic regression models were used to calculate educational differences in physical inactivity. Physical inactivity was more prevalent in lower educational groups. Psychosocial factors related to physical inactivity were locus of control, parochialism, neuroticism, emotional social support, active problem focussing, optimistic and palliative coping styles. Material factors associated with physical inactivity were income, employment status and financial problems. All correlates of physical inactivity were unequally distributed over educational groups, except optimistic and palliative coping. Personality and coping style were the main contributors to the observed educational differences in physical inactivity. That is to say, parochialism, locus of control, neuroticism and active problem focussing explained about half of elevated odds ratios of physical inactivity in the lower educational groups. The material factors, equivalent income and employment status explained about 40% of the elevated odds ratios. Psychosocial and material correlates together reduced the odds ratios of lower educational groups by on average 75%. These results have practical consequences for the design of more effective interventions to promote physical activity. In particular, personality and coping style of risk groups, such as lower educational groups, should be taken into consideration at the future development of these interventions, as well as inequalities in material restrictions related to engaging in physical activity. Supplementary interventions focussing on childhood conditions which, partly, influence both personality and physical inactivity may also contribute to a reduction of socio-economic differences in physical inactivity.

The influence of adult ill health on occupational class mobility and mobility out of and into employment in The Netherlands

In the debate about the explanation of socio-economic health inequalities one of the important issues is the relative importance of health selection. The aim of this study was to investigate to what extent occupational class mobility and mobility out of and into employment are health-related, and in addition, to estimate the contribution of health-related social mobility to socio-economic health differences in the working population. Data were taken from the Longitudinal Study on Socio-Economic Health Differences in the Netherlands, which started in 1991; follow-up data were collected in 1995. The analysis is based on 2533 persons aged 15-59 at baseline. The influence of health problems in 1991 (perceived general health, health complaints and chronic conditions) on changes in occupational class between 1991 and 1995 was negligible. Neither upward nor downward mobility was affected by health problems. However, health problems in 1991 were significantly associated with a higher risk of mobility out of employment and a lower risk of mobility into employment in 1995. For example, for mobility out of employment among persons that reported at least one chronic condition in 1991, the odds ratio was 1.46. Health-related mobility out of employment substantially influences the estimate of socio-economic health inequalities in the working population (measured by current occupation). For manual workers, as compared to non-manual workers, the odds ratio for a less-than-good perceived general health was underestimated by 34% in 1995. Selective mobility into employment overestimates socio-economic inequalities in health in the working population by 9%. Respondents that moved into and out of employment were healthier than those that remained economically inactive, but their health was worse than of those that remained employed (both manual and non-manual). Implications for health policy are that the prospects for people with health problems to stay in paid employment should be improved.

Socio-demographic variables and 6 year change in body mass index: longitudinal results from the GLOBE study

Background: Body mass index (BMI) differs by socio-demographic variables, but the origin of these associations remains relatively unknown.Objective: To investigate the association between socio-demographic variables and the subsequent change in BMI over six years.Design: A Dutch prospective cohort study (GLOBE) from which data were used from initially 20–49-year-old subjects (males: n=362; females: n=405). BMI was calculated from self-reported body height and weight data obtained in 1991 and 1997. Socio-demographic variables used were sex, age, educational level and the occupational level of the main breadwinner, family income, marital status, religious affiliation and degree of urbanization and measured in 1991.Results: Cross-sectionally, BMI was higher in males than in females. BMI was positively associated with age and negatively associated with educational level in both sexes, after adjustment for the other socio-demographic variables. A positive association of BMI with family income was found in males and a negative association with occupational level was found in females. During follow-up, BMI increased significantly more in females (from 23.0 (s.d. 3.3) to 24.2 (s.d. 3.8)) than in males (from 24.3 (s.d. 2.9) to 25.1 (s.d. 3.5)). With the exception of a significant lesser increase in BMI in initially 30–39-year-old women compared to initially 40–49-year-old women, no other statistically significant associations were found between socio-demographic variables and the 6-year change in BMI.Conclusions: Cross-sectional differences in BMI by socio-demographic variables are not due to different 6-year changes in BMI for categories of these variables in adulthood. Cross-sectional differences in BMI by educational level are probably established at the end of adolescence.

Occupational level of the father and alcohol consumption during adolescence; patterns and predictors

Study objective: This paper describes and attempts to explain the association between occupational level of the father and high alcohol consumption among a cohort of New Zealand adolescents from age 11 to 21. Design: Data were obtained from the longitudinal Dunedin multidisciplinary health and development study. At each measurement wave, those who then belonged to the quartile that reported the highest usual amount of alcohol consumed on a typical drinking occasion were categorised as high alcohol consumers. Potential predictors of high alcohol consumption included environmental factors, individual factors, and educational achievement measured at age 9, 11, or 13. Longitudinal logistic GEE analyses described and explained the relation between father’s occupation and adolescent alcohol consumption. Setting: Dunedin, New Zealand. Participants: About 1000 children were followed up from birth in 1972 until adulthood. Main results: A significant association between fathers’ occupation and adolescent alcohol consumption emerged at age 15. Overall adolescents from the lowest occupational group had almost twice the odds of being a large consumer than the highest occupational group. The association between father’s occupation and high alcohol consumption during adolescence was explained by the higher prevalence of familial alcohol problems and friends approving of alcohol consumption, lower intelligence scores, and lower parental attachment among adolescents from lower occupational groups. Conclusions: Socioeconomic background affects adolescent alcohol consumption substantially. This probably contributes to cumulation of disadvantage. Prevention programmes should focus on adolescents from lower socioeconomic groups and make healthier choices the easier choices by means of environmental change.

Deprivation and survival from breast cancer

We studied the association between deprivation and survival from breast cancer in 29,676 women aged 30 and over who were diagnosed during the period 1980-89 in the area covered by the South Thames Regional Health Authority. The measure of deprivation was the Carstairs Index of the census enumeration district of each womans residence at diagnosis. We studied the impact of stage at diagnosis, morphology and type of treatment on this association, with the relative survival rate and the hazard ratio as measures of outcome. There was a clear gradient in survival, with better survival for women from more affluent areas. At all ages, women in the most deprived category had a 35% greater hazard of death than women from the most affluent areas after adjustment for stage at diagnosis, morphological type and type of treatment. In younger women (30-64 years), the survival gradient by deprivation category cannot be explained by these prognostic factors. In older women (65-99 years), part of the unadjusted gradient in survival can be explained by differences in the stage of disease: older women in the most deprived category were more often diagnosed with advanced disease. Other factors, so far unidentified, are responsible for the gradient in breast cancer survival by deprivation category. The potential effect on breast cancer mortality of eliminating the gradient in survival by deprivation category is substantial (7.4%). In women aged 30-64 years, 10% of all deaths within 5 years might be avoidable, while in older women this figure is 5.8%.

Determinants of levels and changes of physical functioning in chronically ill persons: results from the GLOBE Study

STUDY OBJECTIVE Declines in physical functioning are a common result of chronic illness, but relatively little is known about factors not directly related to severity of disease that influence the occurrence of disability among chronically ill persons. The aim of this study was to assess the effect of a large number of potential determinants (sociodemographic factors, health related behaviour, structural living conditions, and psychosocial factors). DESIGN Longitudinal study of levels and changes of physical functioning among persons suffering from four chronic diseases (asthma/chronic obstructive pulmonary disease (COPD), heart disease, diabetes, chronic low back pain). In 1991, persons suffering from one or more of these diseases were identified in a general population survey. Self reported disabilities, using a subset of the OECD disability indicator, were measured six times between 1991 and 1997. These data were analysed using generalised estimating equations, relating determinants measured in 1991 to disability between 1991 and 1997, and controlling for a number of potential confounders (age, gender, year of measurement, and type and severity of chronic disease). SETTING Region of Eindhoven (south eastern Netherlands). PARTICIPANTS 1784 persons with asthma/COPD, heart disease, diabetes mellitus and/or low back pain. MAIN RESULTS In a “repeated prevalence” model, statistically significant (p<0.05) and strong associations were found between most of the determinants and the prevalence of disabilities. In a “longitudinal change” model, statistically significant (p<0.05) predictors of unfavourable changes in physical functioning were low income and excessive alcohol consumption, while we also found indications for effects of marital status, degree of urbanisation, smoking, and external locus of control. CONCLUSIONS Other factors than characteristics of the underlying disease have an important influence on levels and changes of physical functioning among chronically ill persons. Reduction of the prevalence of disabilities in the population not only depends on medical interventions, but may also require social interventions, health education, and psychological interventions among chronically ill persons.

Socioeconomic status and comorbidity among newly diagnosed cancer patients

Many studies found better cancer survival in patients with a high socioeconomic status (SES) than in patients with a low SES. Comorbidity at the time of diagnosis may be more frequent in patients of lower SES, and negatively influences their survival. The authors studied the association between SES and serious comorbidity at the time of diagnosis among newly diagnosed cancer patients in the Netherlands.