We are therefore able to examine associations of both parent's education with CVD risk factors in offspring followed into adulthood in more detail than prior studies. The Oslo Youth Study began in when students in combined primary and secondary schools mean age 13 years, range 11—16 years attending six schools in Oslo were invited to participate in a school-based health education intervention.
Begun in autumn and described in detail elsewhere, 17 , 20 , 21 the health intervention aimed to discourage smoking initiation and modify physical activity and dietary habits. The students were administered a questionnaire and underwent a health examination in , , , questionnaire only and Data from were used in the present analyses, with substitution from if missing. In and data collection took place in the schools. Subsequently, questionnaires were mailed to the study participants and respondents were invited to attend a health examination at the study centre in Oslo or with their physician These examinations included measurement of height, weight, pubertal development in and , 22 , 23 cardio-respiratory fitness 19 and and waist and hip circumferences and Resting blood pressure was ascertained using a random-zero sphygmomanometer in and two measurements , while three readings taken by two trained nurses using a Dinamap device was used in In , two measurements were taken by the participant's general practitioner type of instrument not recorded.
The mean of these values for each year was used herein. Serum measurements included total cholesterol, high-density lipoprotein HDL cholesterol, triglycerides , , , and glycosylated haemoglobin HbA1c Both fasting and non-fasting values of serum measurements were used in the analyses. Questionnaires in , and included items about intake frequency of sugared soft drinks, chocolate, cakes, confectionary, fruit, fruit juice, vegetables and potatoes.
The responses were summed range: 0—8. Similar enquiries were made in more detailed food frequency questionnaires in , and Parental physical activity level and smoking habits in and were assessed by self-report. The physical activity measure was identical to the one used for the offspring in and with the smoking enquiry essentially unchanged. Pearson correlation analysis was used to explore the correlations between parental and offspring's education.
Linear and logistic regression analyses were used to summarize the relation of parental education with CVD risk factors in separate models for paternal and maternal education. In final models, we show coefficients for participant's own education after adjusting for father's education. In preliminary analyses, there was no evidence of differential associations in male and female participants so data were pooled and sex adjusted.
Given the narrow age range of the participants 11—15 years in , no adjustment was made for chronological age. All analyses were adjusted for sex and intervention status; data from adolescence were controlled for pubertal development. All analyses were conducted using SPSS At each wave, some participants completed the questionnaire on behavioural factors, but declined the physical health assessment.
Of participants in mean age 13 years , complete data on behavioural and physiological factors were available for and , respectively, and, of these, and subjects in mean age 15 years , and in mean age 25 years , in behavioural factors only collected mean age 33 years and and in mean age 40 years.
In , and relatively few participated in the physical examinations. In and questionnaires were mailed to participants, while the physical examination required that participants travelled to the examination site, which probably increased the drop-out rate. In , filling in the questionnaire and the health examination was completed at school.
Nearly all repsondents took part in the physical examination, but a high proportion did not take part in the fitness measurements and were excluded from the analyses. Missing data raises concerns regarding selection bias. We therefore compared the baseline characteristics of participants and non-participants in the physical examination. As we have previously demonstrated, 24 there were few significant differences.
Participants were more likely to be female 53 vs. There were no differences for other variables. The differences in baseline characteristics between participants and non-participants in and were similar to those observed in except from baseline systolic blood pressure which was higher vs.
Table 1 presents values of the variables included in the main analyses. Mothers and fathers with higher education had offspring with a lower unhealthy eating score and higher fruit and vegetable intake at age 15 years, while father's education predicted healthier eating at age Mother's and father's education each predicted physical activity at age 33, but not at other ages.
The associations did not change materially after adjusting for physical activity among mothers and fathers. There were no statistically significant associations with unhealthy eating or fruit and vegetable intake at other ages, and after adjustment for own education, the association with father's education and age eating patterns was non-significant.
Standardised regression coefficients B for the relation of parental educational level to unhealthy eating habits left a and fruit and vegetable intake right a at ages 15, 25, 33 and 40 years, leisure time physical activity at ages 15, 25, 33 and 40 years b and binge drinking at ages 25, 33 and 40 years c : the Oslo Youth Study follow-up.
Although neither father's nor mother's education predicted binge drinking in models adjusted only for sex and intervention status, after adjustment for the subject's own educational achievement, mother's education was positively associated with binge drinking in the offspring at the age of 40 years.
In table 2 , we present the associations between the offspring's own education and behavioural CVD risk factors. Own education predicted sweet food intake at ages 33 and 40 years and physical activity at ages 25 and 33 years, although the former became non-significant after adjusting for father's education.
Own education predicted cigarette smoking at all ages, higher education was associated with lower odds of cigarette smoking. There was an inverse association between paternal education and offspring BMI at ages 15 and 25 years, such that children whose fathers had higher education were leaner in adolescence and adulthood table 3. These associations were only marginally changed after adjustments for paternal BMI results not shown.
Commensurate with this observation, higher paternal education was related to more favourable levels of total cholesterol in the offspring at age 25 and 40 years, triglycerides at 25 years, and systolic blood pressure at 15 and 25 years.
There was no evidence that either waist-hip ratio or HbA1c in adulthood or cardio-respiratory fitness during adolescence was associated with father's education results not shown. Maternal education did not predict any of the physiological risk factors except BMI at age 15 years. Participants' own education in adulthood predicted total and HDL cholesterol and triglycerides at 25 years of age as well as BMI at 25 and 40 years of age.
In all cases, a higher level of education was associated with a more favourable CVD risk profile. Maternal educational level showed no consistent associations with most risk factors. Few studies have examined the effect of father's and mother's education on offspring's CVD risk factors. Ball and Mishra 6 found that childhood socio-economic status was inversely associated with adult BMI, with a stronger association with father's than for mother's education.
Our findings for BMI are consistent with these results. That a significantly lower proportion of Norwegian women than men had higher education in the 70s and 80s might partly explain the weak association between maternal education and offspring CVD risk factors 20—30 years later.
In contrast to other studies, we found no evidence for an effect of either parental or own education on fruit and vegetable intake in adulthood. These attenuations therefore could be due to mediation of parental SEP effects by the offspring's own education; to confounding of the associations between offspring education and CVD risk factors; or to insufficient statistical power to detect modest direct effects.
Achieved education in adulthood might be a measure of early life circumstances, 31 and therefore, adjusting for own adult education might represent an over-adjustment.
Analyses in which a consequence of the dependent variable is included as an independent variable are commonly biased towards the null, so analyses should be interpreted with great caution. In accordance with results from other studies, we showed that smoking in adulthood was more strongly associated with own education than parental education. Findings from other studies are equivocal, but mostly they have found that upwardly mobile subjects have more favourable lifestyles than the class they left, but less favourable than the class they join.
The only other behavioural risk factor in adult life that was predicted by parental education after adjusting for own education was binge drinking at age 40 years, for which the risk increased with increased parental education.
This is discordant with results from some studies, 35 but an earlier study from Norway has found that alcohol consumption was inversely related to educational attainment. The strengths of this study include repeated assessments of physiological and behavioural CVD risk factors across the life course until middle age, and prospectively self-reported data on education.
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