How socioeconomic circumstances, school achievement and reserve capacity in adolescence predict adult education level : a three-generation study in Finland
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Full Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalInformation?journalCode=rady20 International Journal of Adolescence and Youth ISSN: 0267-3843 (Print) 2164-4527 (Online) Journal homepage: http://www.tandfonline.com/loi/rady20 How socioeconomic circumstances, school achievement and reserve capacity in adolescence predict adult education level: a three-generation study in Finland Paulyn Jean Acacio-Claro, David Teye Doku, Leena Kristiina Koivusilta & Arja Hannele Rimpelä To cite this article: Paulyn Jean Acacio-Claro, David Teye Doku, Leena Kristiina Koivusilta & Arja Hannele Rimpelä (2018) How socioeconomic circumstances, school achievement and reserve capacity in adolescence predict adult education level: a three-generation study in Finland, International Journal of Adolescence and Youth, 23:3, 382-397, DOI: 10.1080/02673843.2017.1389759 To link to this article: https://doi.org/10.1080/02673843.2017.1389759 © 2017 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group Published online: 15 Oct 2017. Submit your article to this journal Article views: 653 View Crossmark data
InternatIonal Journal of adolescence and Youth, 2018 Vol. 23, no. 3, 382–397 https://doi.org/10.1080/02673843.2017.1389759 How socioeconomic circumstances, school achievement and reserve capacity in adolescence predict adult education level: a three-generation study in Finland Paulyn JeanAcacio-Claroa, David TeyeDokua,b, Leena KristiinaKoivusiltac and Arja HanneleRimpeläa,d afaculty of social sciences, health sciences, university of tampere, tampere, finland; bdepartment of Population and health, university of cape coast, cape coast, Ghana; cfaculty of social sciences, university of turku, turku, finland; ddepartment of adolescent Psychiatry, tampere university hospital, nokia, finland ABSTRACT Family socioeconomic circumstances directly influence adult education level. Adolescent psychosocial resources and health-promoting behaviour collectively termed as ‘reserve capacity’ and school achievement may likely mediate the effect of family socioeconomic circumstances on adult education level. We tested these relationships using 1985–1995 survey data on 12–18-year-old Finns (N=41,822) linked with three-generation registry data of Statistics Finland until 2009. Results of the multinomial logistic regression models, adjusted for sex and age at end of follow-up, showed that socioeconomic circumstances of parents and grandparents predicted adult education level. School achievement and reserve capacity dimensions of perceived health, health-promoting behaviour and social support in adolescence also positively predicted adult education. Moreover, these tended to decrease the effect of family socioeconomic circumstances on educational level. Our findings suggest that formulating interventions which build reserve capacity and improve school performance, especially among adolescents from disadvantaged socioeconomic backgrounds, could likely reduce educational inequalities. Introduction Education is a strong predictor of health (Freudenberg & Ruglis, 2007; Liu & Hummer, 2008). Studies have robustly shown that a low educational attainment is associated with poorer health outcomes (Fergusson, Horwood, & Boden, 2008; Matthews & Gallo, 2011) and shorter life expectancies (Mackenbach et al., 2015; Spittel, Riley, & Kaplan, 2015). Additionally, education predicts an individual’s future occupational prospects and earning capacities (Adler & Newman, 2002; Matthews & Gallo, 2011) and influences one’s life-course opportunities, including those of the offspring (Fergusson et al., 2008). It is commonly used as an indicator of socioeconomic status (SES) and recognized as a key marker of success in adulthood (Slominski, Sameroff, Rosenblum, & Kasser, 2011). Thus, one of the goals included in the 2030 Agenda for Sustainable Development by multilateral groups in partnership with the United Nations, is universal access to education at all levels (United Nations, n.d.). ARTICLE HISTORY received 14 september 2017 accepted4 october 2017 KEYWORDS education; socioeconomic; psychosocial; reserve capacity; school achievement © 2017 the author(s). Published by Informa uK limited, trading as taylor & francis Group. this is an open access article distributed under the terms of the creative commons attribution license (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. CONTACT Paulyn Jean acacio-claro [email protected] OPEN ACCESS
INTERNATIONAL JOURNAL OF ADOLESCENCE AND YOUTH 383 Evidence points to socioeconomic circumstances of the family as largely shaping the mechanisms and processes of an individual’s educational attainment (Conger, Conger, & Martin, 2010; Fergusson et al., 2008; Koivusilta, West, Saaristo, Nummi, & Rimpelä, 2013; Merritt & Buboltz, 2015; Slominski et al., 2011). The socioeconomic circumstances of the family determine available resources for investments in the human capital formation of children, such as health and education (Bird, 2007), and also the transfer of these resources from one generation to another (Albertini & Radl, 2012). Hence, even in high income countries, children born in low SES families have higher risk of educational failure and underachievement (Fergusson et al., 2008). They also have increased tendencies to acquire low SES in adulthood (Matthews, Gallo, & Taylor, 2010). Aside from family SES, cognitive ability, usually measured through academic competence or school achievement, strongly determines educational attainment in adulthood. Good grades obtained in secondary school were strong predictors of enrolment in higher education (Brekke, 2015). Even grades obtained early in elementary school had predicted adult educational attainment (Entwisle, Alexander, & Olson, 2005). Academic competence incites higher academic aspirations and enables one to meet the rigors of post-secondary education (Merritt & Buboltz, 2015). A low SES family background is the earliest exposure and risk factor for having less education and low adult SES in the life-course perspective (Kuh, Ben-Shlomo, Lynch, Hallqvist, & Power, 2003). Adolescence follows this early life environment and further shapes psychosocial development, (Kroenke, 2008) which is a potential pathway for adult educational outcomes (Murasko, 2007). Researchers found that low SES families who provided psychosocial resources through cognitive and emotional support raised resilient children who succeeded academically (Merritt & Buboltz, 2015) and functioned well in life compared to their low SES counterparts without such resources (Kroenke, 2008). These psychosocial resources were integrated as the concept of reserve capacity and include interpersonal resources such as social support and integration and intrapersonal characteristics such as self-efficacy, mastery or a sense of perceived control (Gallo, Espinosa de los Monteros, & Shivpuri, 2009; Gallo & Matthews, 2003; Matthews & Gallo, 2011; Matthews et al., 2010). It was proposed that individuals with high reserve capacity gain the coping skills necessary to attain higher education while those with low reserve capacity may lack these skills and attain lower education (Matthews et al., 2010). Such a mechanism raises the question of how reserve capacity can mediate the effect of family SES on future educational attainment. We further extend the reserve capacity framework to include dental brushing behaviour and physical activity as these have been shown to improve with high self-efficacy (Cinar, Tseveenjav, & Murtomaa, 2009; Pakpour & Sniehotta, 2012; Robbins, Pender, Ronis, Kazanis, & Pis, 2004). Our study, therefore, focuses on three dimensions of reserve capacity: perceived health, health-promoting behaviour and social support. While most empirical data dealt with transmission of SES from parents to offspring, recent findings have demonstrated that grandparents’ occupational class could be transmitted to grandchildren (Chan & Boliver, 2013; Erola & Moisio, 2007) and that other capital of grandparents could influence their grandchildren’s educational success (Møllegaard & Jæger, 2015). This implies that transmission of low education across generations of families could perpetuate a cycle of socioeconomic disadvantage. In order to break this, it is important to elucidate the origin of inequalities in education and understand the processes which create these. It is in this perspective that we aim to investigate if the effect of family SES on adult education level persists across three generations, implying that educational inequalities may have originated from socioeconomic circumstances of grandparents. Moreover, we want to determine how reserve capacity and school achievement in adolescence modify the associations between family socioeconomic circumstances and adult education level. Methods Study design A longitudinal study design was constructed using two data sources linked through unique national personal identification numbers. Baseline data were obtained from the Adolescent Health and Lifestyle
384 P. J. ACACIO-CLARO ET AL. Surveys (AHLS) of 1985, 1987, 1991, 1993 and 1995. The AHLS, conducted biennially since 1977, monitors the health and health-related lifestyle of adolescents in Finland. Nationally representative samples of 12-, 14-, 16-, and 18-year-old Finns born on certain days in June, July and August were drawn each study year from the Population Register Centre. Variables measured across all survey rounds were used. A self-administered questionnaire was sent in February, followed by two re-inquiries to non-respondents. Eligible data from 41,822 adolescents (79.2% response rate) were included. Response rates by sex and age groups were as follows: 72.4% in boys (n=19,504), 86.3% in girls (n=22,318), at least 80% in adolescents aged 12years (n=3,948), 14years (12,583) and 16years (n=13,582), respectively and 75.4% in those aged 18years (n=11,709). Follow-up data were obtained from registries of Statistics Finland, which contained socioeconomic information for the AHLS participants, their parents and grandparents. The data from Statistics Finland covered censuses every fifth year from 1970 to 1995 and yearly registry data from 2000 until the end of 2009. Follow-up started on 30 April, each survey year, and ended on 31 December 2009. At the end of the follow-up, the participants’ ages ranged from 27 to 43years. Statistics Finland had constructed family formation data to link generations. In the earlier censuses, children (parents in this study) who were no longer living with their parents (grandparents in this study) during the time of the census could not be linked to their families, which explains the large number of grandchildren with unknown data for grandparents (Table 1). Part of the missing information is due to the late digitalization of the censuses (from 1970 onwards). The proportion of adolescents with unknown grandparents’ data by adult education level was similar to those of adolescents whose grandparents had low education and rented dwellings. In terms of other variables, the pattern of distribution found in adolescents with unknown grandparents followed the distributions obtained in the total population. Further analyses were made to assess the effect of including this group in our study (Appendix 1). Statistics Finland performed the data linkage according to a contract specifying the rights and duties of both parties. The Institutional Review Board of Statistics Finland and the Data Protection Ombudsman approved the study protocol. Identification of the study participants was withheld from the investigators. Outcome variable Adult education level The adolescent’s highest educational level was used and grouped according to years of schooling: low (9years or less), middle (10–12years), and high education (>12years). Predictor variables Several indicators of family socioeconomic circumstances were used. All parents’ and grandparents’ data were obtained nearest to the year when the adolescent was aged 15years. Parental data obtained more than five years away from the child’s 15th birthday and data from those whose parents died before the AHLS year were considered missing to ensure that only parental influences within adolescence were measured. Education level of father, mother, maternal and paternal grandparents Education levels of parents and grandparents were categorized in the same way as that of the adolescents’. Data on grandfather and grandmother from either maternal or paternal side were combined. Where both grandparents existed and information was different, the one with the higher category was used. In case of missing data from one grandparent, the available information from the other grandparent was used.
INTERNATIONAL JOURNAL OF ADOLESCENCE AND YOUTH 385 Table 1.distribution of family socioeconomic circumstances, school achievement and reserve capacity variables in adolescence according to education level in adulthood. Family socioeconomic circumstances, school achievement and reserve capacity in adolescence Education level in adulthood Total population N=41,822 Low n=3801 Middle n=23,073 High n=14,948 No. %Row % Row % Row % Family variables education father low 17,212 41.2 12.0 62.2 25.8 Middle 18,481 44.2 7.7 55.2 37.1 high 5500 13.1 3.3 32.4 64.3 Missing 629 1.5 18.4 63.0 18.6 Mother low 16,186 38.7 12.5 63.0 24.5 Middle 22,121 52.9 7.5 53.1 39.4 high 3483 8.3 3.4 31.5 65.1 Missing 32 .1 31.3 53.1 15.6 Paternal grandparents low 18,643 44.6 8.4 55.8 35.8 Middle 3969 9.5 7.1 48.1 44.8 high 1070 2.5 4.6 37.2 58.2 unknown 18,140 43.4 10.5 57.1 32.4 Maternal grandparents low 19,144 45.8 8.4 56.1 35.5 Middle 4324 10.3 7.6 48.4 44.0 high 938 2.3 4.5 36.0 59.5 unknown 17,416 41.6 10.4 56.9 32.7 dwelling ownership father rented 5972 14.3 16.9 60.1 23.0 owner-occupied 32,711 78.2 7.2 53.7 39.1 Missing 3139 7.5 14.1 60.7 25.2 Mother rented 7052 16.9 17.6 60.4 22.0 owner-occupied 33,659 80.4 7.1 53.9 39.0 Missing 1111 2.7 14.1 60.7 25.2 Paternal grandparents rented 3364 8.0 10.5 56.4 33.1 owner-occupied 19,302 46.2 7.5 53.2 39.3 unknown 19,156 45.8 10.4 67.0 32.6 Maternal grandparents rented 3554 8.5 11.6 58.2 30.2 owner-occupied 19,975 47.8 7.5 53.2 39.3 unknown 18,293 43.7 10.4 56.7 32.9 employment status father unemployed 4430 10.6 13.1 60.8 26.1 employed 35,076 83.9 8.2 54.1 37.7 Missing 2316 5.5 14.9 60.4 24.7 Mother unemployed 4923 11.8 13.9 58.3 27.8 employed 36,415 87.0 8.4 54.6 37.0 Missing 484 1.2 14.5 62.0 23.5 Adolescence variables school achievement low 19,533 46.7 15.8 68.2 16.0 average 13,152 31.4 3.9 51.8 44.3 high 8697 20.8 1.3 30.5 68.2 Missing 440 1.1 24.1 62.0 13.9 reserve capacity Perceived health chronic disease Yes 3905 9.3 11.8 54.8 33.4 no 37,917 90.7 8.8 55.2 36.0 Perceived stress symptoms 4–8/week 5100 12.2 12.3 55.4 32.3 2–3/week 10,376 24.8 9.4 53.7 36.9 1/week 9308 22.3 8.5 54.8 36.7 none 17,038 40.7 8.2 56.2 35.6 self-rated health Poor 785 1.9 16.3 54.9 28.8 average or good 27,198 65.0 9.3 55.8 34.9 Very good 13,695 32.8 8.3 53.8 37.9 Missing 144 .3 13.9 55.5 30.6 (Continued)
386 P. J. ACACIO-CLARO ET AL. Dwelling ownership of father, mother, maternal and paternal grandparents Dwelling ownership was classified as either owner-occupied (owned a house or had shares in the housing unit) or rented (living in a rented apartment). Employment status of father and mother Employment status was based on the indicated response (employed, unemployed, unknown) about one’s main activity. The category ‘unemployed’ also included those who had at least one month of unemployment during the preceding twelve months of the census. Because most grandparents had retired, this variable was used for parents only. Reserve capacity Reserve capacity was measured in three distinct dimensions of intraand interpersonal factors. Within each dimension of reserve capacity (AHLS data), correlations and associations of the variables were calculated. We found moderate positive correlations (Spearman’s) and statistically significant associations (Pearson chi-square tests) within the items described per dimension. (a) Perceived health included three items: reported chronic disease, injury or disability that restricts daily activities (no/yes); a summary index of weekly perceived stress symptoms (stomachaches, tension or nervousness, irritability or outbursts of anger, trouble falling asleep or waking at night, Family socioeconomic circumstances, school achievement and reserve capacity in adolescence Education level in adulthood Total population N=41,822 Low n=3801 Middle n=23,073 High n=14,948 No. %Row % Row % Row % health-promoting behaviour Physical activity does not exercise 8169 19.5 13.6 60.8 25.6 occasional/ low efficient exerciser 11,868 28.4 8.7 57.0 34.3 active efficient exerciser 12,639 30.2 7.9 52.8 39.3 Very active efficient exerciser 9040 21.6 7.0 51.1 41.9 Missing 106 .3 22.6 51.9 25.5 regular tooth brushing <1–5 times/ week 7443 17.8 17.6 62.9 19.5 about once/ day 19,421 46.4 8.3 56.5 35.2 several times/ day 14,807 35.4 5.8 49.5 44.7 Missing 151 .4 13.9 60.9 25.2 social support nuclear family no 9192 22.0 15.6 59.0 25.4 Yes 32,398 77.5 7.2 54.0 38.8 Missing 232 .5 17.7 59.0 23.3 talking about issues to father difficult/no father 22,363 53.5 9.3 54.8 35.9 easy 18,572 44.4 8.4 55.3 36.3 Missing 887 2.1 17.6 62.6 19.8 talking about issues to mother difficult/no mother 11,384 27.2 10.1 55.2 34.7 easy 29,930 71.6 8.5 55.1 36.4 Missing 508 1.2 18.3 59.5 22.2 talking about issues to friends difficult/no friends 6379 15.2 10.1 55.2 35.7 easy 34,833 83.3 8.7 55.1 36.2 Missing 610 1.5 17.5 60.7 21.8 Table 1.(Continued).
INTERNATIONAL JOURNAL OF ADOLESCENCE AND YOUTH 387 Table 2.Bivariate associations of each predictor variable with education level in adulthood (using low education as reference category), adjusting for sex and age at end of follow-up. *p<.05; **p<.01; ***p<.001 – significance levels. Family socioeconomic circumstances, school achievement and reserve capacity in adolescence Odds ratios, 95% confidence intervals Middle High Family variables education father low 1.0 1.0 Middle 1.3 (1.3–1.5)*** 2.1 (1.9–2.3)*** high 1.8 (1.5–2.1)*** 8.3 (7.0–9.8)*** Mother low 1.0 1.0 Middle 1.4 (1.3–1.5)*** 2.6 (2.4–2.8)*** high 1.9 (1.5–2.4)*** 9.4 (7.6–11.6)*** Paternal grandparents low 1.0 1.0 Middle 1.1 (.9–1.2) 1.5 (1.3–1.7)*** high 1.2 (.9–1.6) 2.9 (2.1–4.0)*** unknown .8 (.8–.9)*** .8 (.8–.9)*** Maternal grandparents low 1.0 1.0 Middle 1.0 (.9–1.2) 1.4 (1.2–1.6)*** high 1.2 (.8–1.6) 3.1 (2.2–4.3)*** unknown .8 (.8–.9)*** .9 (.8–.9)** dwelling ownership father rented 1.0 1.0 owner-occupied 2.1 (1.9–2.3)*** 4.0 (3.6–4.4)*** Mother rented 1.0 1.0 owner-occupied 2.2 (2.0–2.4)*** 4.3 (3.9–4.7)*** Paternal grandparents rented 1.0 1.0 owner-occupied 1.3 (1.1–1.5)*** 1.6 (1.4–1.9)*** unknown 1.0 (.9–1.2) 1.2 (1.0–1.3)* Maternal grandparents rented 1.0 1.0 owner-occupied 1.5 (1.3–1.8)*** 2.1 (1.9–2.5)*** unknown 1.2 (1.0–1.3)* 1.4 (1.3–1.7)*** employment status father unemployed 1.0 1.0 employed 1.4 (1.3–1.6)*** 2.4 (2.2–2.8)*** Mother unemployed 1.0 1.0 employed 1.6 (1.4–1.8)*** 2.4 (2.1–2.6)*** Adolescence variables school achievement low 1.0 1.0 average 3.0 (2.7–3.3)*** 10.7 (9.6–12.0)*** high 5.6 (4.5–7.0)*** 53.6 (43.0–66.8)*** reserve capacity Perceived health chronic disease Yes 1.0 1.0 no 1.2 (1.1–1.4)** 1.3 (1.1–1.5)*** Perceived stress symptoms 4–8/week 1.0 1.0 2–3/week 1.3 (1.2–1.5)*** 1.6 (1.4–1.8)*** 1/week 1.6 (1.4–1.8)*** 1.8 (1.6–2.1)*** none 1.7 (1.5–2.0)*** 2.0 (1.8–2.3)*** self-rated health Poor 1.0 1.0 average or good 1.4 (1.1–1.8)** 1.5 (1.2–2.0)** Very good 1.5 (1.2–1.9)** 1.9 (1.5–2.5)*** health-promoting behaviour Physical activity does not exercise 1.0 1.0 occasional/low efficient exerciser 1.3 (1.2–1.5)*** 1.8 (1.6–2.0)*** active efficient exerciser 1.4 (1.2–1.6)*** 2.3 (2.1–2.6)*** Very active efficient exerciser 1.6 (1.4–1.8)*** 2.9 (2.5–3.3)*** regular tooth brushing <1–5 times/week 1.0 1.0 about once/day 1.7 (1.6–1.9)*** 3.2 (2.8–3.5)*** several times/day 1.9 (1.7–2.2)*** 4.9 (4.4–5.5)*** social support nuclear family no 1.0 1.0 Yes 2.2 (2.0–2.4)*** 3.8 (3.4–4.2)*** talking about issues to father difficult/no father 1.0 1.0 easy 1.1 (1.0–1.2) 1.1 (1.0–1.2)* talking about issues to mother difficult/no mother 1.0 1.0 easy 1.1 (1.0–1.2) 1.1 (1.0–1.2) talking about issues to friends difficult/no friends 1.0 1.0 easy 1.0 (.9–1.1) .9 (.8–1.0)
388 P. J. ACACIO-CLARO ET AL. headache, trembling of hands, feeling tired or weak, feeling dizzy) categorized as no symptoms, one symptom/week, 2–3/week, 4–8/week; and self-rated health categorized as very good, good to average, poor. (b) Health-promoting behaviour included frequency of tooth brushing (several times a day, once a day, 1–5 times/week or less) and efficiency of physical activity. Efficiency of physical activity was measured by combining information from two variables: frequency of physical activity in leisure time and intensity of exercise (shortness of breath/sweating). This combination used the following categories: does not exercise, exercises with low/occasional efficiency, active efficient exerciser, very active efficient exerciser. (c) Social support was measured by four items: nuclear family (living with both parents or not); ease of talking about troubling issues to father, to mother and to friends (easy or difficult). Those who did not have a father (5%), mother (1%) or friends (.5%) were included in the ‘difficult’ category. School achievement Adolescents were categorized as having low, average or high academic achievement. The respondents were asked to assess whether their end-of-term school performance was much better, slightly better, average, slightly poorer or much poorer than the class average. For 12–14-year-olds (all in comprehensive schools), those who reported much better performance were classified as ‘high’, those with slightly better performance as ‘average’ while the rest were all classified as having ‘low’ achievement. For 16–18-year-olds, in addition to self-assessment of their school performance, school status (academic upper secondary school/vocational school/not attending school) was also used. Their achievement was classified as follows: high (in academic upper secondary school with better performance); average (in vocational school with better performance or academic upper secondary school with average performance); and, low (in vocational school with poor to average performance or high school with poor performance or not at school). Statistical analysis Descriptive statistics were presented as percentages for categorical variables. We used multinomial logistic regression analysis to investigate the associations of predictor variables with the outcome. In both bivariate and multivariate analyses, we adjusted for sex and age at the end of follow-up because of unequal follow-up times among the participants. Three multivariate models were fitted using a backward elimination approach. Variables included were only those statistically significant in bivariate analyses (Table 2). The first model named Model 1 examined family SES variables; Model 2 included the Model 1 variables plus school achievement; and, Model 3 (final model) consisted of all statistically significant family socioeconomic variables, school achievement and reserve capacity variables. Due to the numerous predictors considered in each model, statistical significance was set at p<.01 for retaining variables in the models. Model fit was assessed using Akaike information criterion (AIC) values and likelihood ratio tests. The model parameters were presented as odds ratios (ORs) with 95% confidence intervals (CIs). All analyses were performed using STATA version 12.1. Results A third (35.7%) of the adolescents achieved high education in adulthood, about half (55.2%) attained a middle education and less than a tenth (9.1%) had low adult education level. Table 1 presents the distributions of the predictor variables by adolescents’ adult education level. Generally, the proportion of adolescents who obtained high adult education level increased with better family socioeconomic circumstances, high achievement in school and positive reserve capacity characteristics. The opposite
INTERNATIONAL JOURNAL OF ADOLESCENCE AND YOUTH 389 Table 3.Multivariate associations of each predictor variable with education level in adulthood (using low education as reference category) in three models, adjusting for sex and age at end of follow-up. Family socioeconomic circumstances, school achievement and reserve capacity in adolescence Model 1aModel 2bModel 3 (final model)c Odds ratios, 95% confidence intervals Odds ratios, 95% confidence intervals Odds ratios, 95% confidence intervals Middle High Middle High Middle High Family variables education father low 1.0 1.0 1.0 1.0 1.0 1.0 Middle 1.2 (1.1–1.3)** 1.7 (1.6–1.9)** 1.2 (1.1–1.3)** 1.5 (1.4–1.7)** 1.2 (1.1–1.3)** 1.5 (1.4–1.7)** high 1.4 (1.2–1.7)** 4.5 (3.7–5.4)** 1.2 (1.0–1.5) 2.7 (2.3–3.3)** 1.1 (.9–1.4) 2.6 (2.1–3.1)** Mother low 1.0 1.0 1.0 1.0 1.0 1.0 Middle 1.3 (1.2–1.4)** 1.9 (1.8–2.1)** 1.2 (1.1–1.3)** 1.8 (1.6–1.9)** 1.3 (1.2–1.4)** 1.8 (1.6–2.0)** high 1.4 (1.1–1.8)* 3.6 (2.9–4.6)** 1.2 (1.0–1.5) 2.4 (1.9–3.0)** 1.3 (1.0–1.6) 2.5 (2.0–3.2)** dwelling ownership father rented 1.0 1.0 1.0 1.0 1.0 1.0 owner-occupied 1.4 (1.2–1.6)** 1.7 (1.5–2.0)** 1.4 (1.2–1.6)** 1.8 (1.6–2.2)** 1.4 (1.2–1.5)** 1.7 (1.5–2.0)** Mother rented 1.0 1.0 1.0 1.0 1.0 1.0 owner-occupied 1.6 (1.4–1.9)** 2.3 (2.0–2.7)** 1.5 (1.3–1.7)** 1.9 (1.6–2.2)** 1.3 (1.1–1.5)** 1.5 (1.3–1.7)** Maternal grandparents rented 1.0 1.0 1.0 1.0 1.0 1.0 owner-occupied 1.3 (1.2–1.5)** 1.6 (1.4–1.8)** 1.3 (1.1–1.5)** 1.5 (1.3–1.8)** 1.3 (1.1–1.5)* 1.5 (1.3–1.8)** unknown 1.0 (.9–1.2) 1.2 (1.0–1.4) 1.0 (.9–1.1) 1.1 (.9–1.3) 1.0 (.8–1.1) 1.0 (.9–1.2) employment status father unemployed 1.0 1.0 1.0 1.0 1.0 1.0 employed 1.2 (1.0–1.3)* 1.5 (1.4–1.8)** 1.1 (1.0–1.3) 1.4 (1.2–1.6)** 1.0 (.9–1.2) 1.2 (1.1–1.4)* Mother unemployed 1.0 1.0 1.0 1.0 1.0 1.0 employed 1.3 (1.2–1.5)** 1.6 (1.4–1.8)** 1.3 (1.2–1.4)** 1.4 (1.3–1.6)** 1.2 (1.1–1.4)** 1.4 (1.2–1.5)** Adolescence variables school achievement low 1.0 1.0 1.0 1.0 average – – 2.8 (2.5–3.1)** 9.0 (8.0–10.1)** 2.6 (2.3–2.9)** 7.9 (7.0–8.9)** high 5.1 (4.1–6.4)** 38.9 (31.1–48.6)** 4.6 (3.7–5.8)** 32.4 (25.9–40.6)** reserve capacity Perceived health chronic disease Yes 1.0 1.0 no – – – – 1.3 (1.1–1.4)** 1.3 (1.2–1.5)** Perceived stress symptoms 4–8/week 1.0 1.0 2–3/week 1.2 (1.1–1.4)* 1.5 (1.3-.1.7)** 1/week – – – – 1.4 (1.3–1.7)** 1.6 (1.4–1.9)** none 1.6 (1.4–1.8)** 1.8 (1.5–2.0)**
396 P. J. ACACIO-CLARO ET AL. Appendix 1. Comparison of final model on associations with education level in adulthood (using low education as reference category), adjusting for sex and age at end of follow-up between population with unknown GP data and without unknown GP data. Family socioeconomic circumstances, school achievement and reserve capacity in adolescence Final modela N=36,517 Final modela N=15,328 (unknown GP data excluded in analysis) Odds ratios, 95% confidence intervals Odds ratios, 95% confidence intervals Middle Middle Middle High Family variables education father low 1.0 1.0 1.0 1.0 Middle 1.2 (1.1–1.3)** 1.5 (1.4–1.7)** 1.3 (1.1–1.5)** 1.7 (1.4–1.9)** high 1.1 (.9–1.4) 2.6 (2.1–3.1)** 1.2 (.9–1.6) 3.1 (2.2–4.2)** Mother low 1.0 1.0 1.0 1.0 Middle 1.3 (1.2–1.4)** 1.8 (1.6–2.0)** 1.2 (1.1–1.4)* 1.8 (1.6–2.2)** high 1.3 (1.0–1.6) 2.5 (2.0–3.2)** 1.8 (1.2–2.8)* 3.5 (2.3–5.4)** dwelling ownership father rented 1.0 1.0 1.0 1.0 owner-occupied 1.4 (1.2–1.5)** 1.7 (1.5–2.0)** 1.4 (1.1–1.6)* 1.7 (1.4–2.2)** Mother rented 1.0 1.0 1.0 1.0 owner-occupied 1.3 (1.1–1.5)** 1.5 (1.3–1.7)** 1.3 (1.1–1.6)* 1.6 (1.2–2.0)** Maternal grandparents rented 1.0 1.0 1.0 1.0 owner-occupied 1.3 (1.1–1.5)* 1.5 (1.3–1.8)** 1.2 (1.0–1.4) 1.4 (1.1–1.7)* unknown 1.0 (.8–1.1) 1.0 (.9–1.2) – – employment status father unemployed 1.0 1.0 employed 1.0 (.9–1.2) 1.2 (1.1–1.4)* – – Mother unemployed 1.0 1.0 1.0 1.0 employed 1.2 (1.1–1.4)** 1.4 (1.2–1.5)** 1.2 (1.0–1.4) 1.3 (1.1–1.6)* Adolescence variables school achievement low 1.0 1.0 1.0 1.0 average 2.6 (2.3–2.9)** 7.9 (7.0–8.9)** 2.6 (2.1–3.1)** 7.6 (6.2–9.2)** high 4.6 (3.7–5.8)** 32.4 (25.9–40.6)** 6.4 (4.1–10.0)** 42.0 (26.9–65.4)** reserve capacity Perceived health chronic disease Yes 1.0 1.0 no 1.3 (1.1–1.4)** 1.3 (1.2–1.5)** – – Perceived stress symptoms 4–8/week 1.0 1.0 1.0 1.0 2–3/week 1.2 (1.1–1.4)* 1.5 (1.3-.1.7)** 1.5 (1.2–1.9)** 2.2 (1.7–2.8)** 1/week 1.4 (1.3–1.7)** 1.6 (1.4–1.9)** 1.5 (1.2–1.9)** 2.1 (1.7–2.7)** none 1.6 (1.4–1.8)** 1.8 (1.5–2.0)** 1.8 (1.5–2.2)** 2.7 (2.2–3.4)** (Continued)
INTERNATIONAL JOURNAL OF ADOLESCENCE AND YOUTH 397 Family socioeconomic circumstances, school achievement and reserve capacity in adolescence Final modela N=36,517 Final modela N=15,328 (unknown GP data excluded in analysis) Odds ratios, 95% confidence intervals Odds ratios, 95% confidence intervals Middle Middle Middle High health-promoting behaviour Physical activity does not exercise 1.0 1.0 1.0 1.0 occasional/low efficient exerciser 1.2 (1.0–1.3)* 1.4 (1.2–1.6)** 1.1 (.9–1.3) 1.2 (1.0–1.5) active efficient exerciser 1.2 (1.0–1.3)* 1.5 (1.4–1.8)** 1.0 (.9–1.2) 1.3 (1.1–1.6)* Very active efficient exerciser 1.2 (1.1–1.4)* 1.6 (1.4–1.8)** 1.1 (.9–1.4) 1.5 (1.2–1.9)** regular tooth brushing <1–5 times/week 1.0 1.0 1.0 1.0 about once/day 1.5 (1.3–1.6)** 2.1 (1.9–2.4)** 1.4 (1.2–1.6)** 2.1 (1.7–2.5)** several times/day 1.5 (1.4–1.7)** 2.5 (2.2–2.9)** 1.5 (1.2–1.8)** 2.6 (2.1–3.2)** social support nuclear family no 1.0 1.0 1.0 1.0 Yes 1.7 (1.5–1.8)** 2.3 (2.0–2.5)** 1.8 (1.6–2.1)** 2.6 (2.3–3.1)** note: Includes statistically significant variables from table 2. a final Model: family ses+school achievement+reserve capacity variables. * p<.01; ** p<.001 – significance levels. Appendix 1. (Continued).