| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
RESEARCH REPORT |
1 Department of Social Policy, FIN-20014 University of Turku, Finland;
2 Faculty of Dentistry, Kuwait University, Kuwait; and
3 School of Public Health, University of Tampere, Finland;
* corresponding author, leena.koivusilta{at}utu.fi
 |
ABSTRACT |
|---|
 TOP ABSTRACT INTRODUCTIONMATERIALS & METHODSRESULTSDISCUSSIONREFERENCES |
|---|
KEY WORDS: toothbrushing • adolescence • education level • lifestyle
|
INTRODUCTION |
|---|
|
TOPABSTRACTINTRODUCTIONMATERIALS & METHODSRESULTSDISCUSSIONREFERENCES |
|---|
Neglecting dental health care may be connected with a wider complex of problems in adolescent lifestyles. Problem behaviors are intercorrelated (Donovan et al., 1993; Neumark-Sztainer et al., 1996) and form several dimensions (Rajala et al., 1980; Aarø et al., 1995). However, dental behaviors have seldom been included in studies examining interrelationships between and among behaviors. In Finland, sporadic toothbrushing was clearly and positively associated with the consumption of sugar-containing snacks and weakly but positively associated with alcohol use and smoking. In girls, orientation to sports was associated with regular toothbrushing (Rajala et al., 1980). Factor analysis supported a bi-dimensional model among adolescents in the Nordic countries (Aarø et al., 1995). The first dimension of addictive behaviors concentrated around smoking, and the second one included health-enhancing behaviors, such as oral hygiene, physical activity, and healthy nutrition. Thus, young people who take care of their teeth behave in ways promoting other dimensions of health as well (Wannamethee et al., 1998).
The aims of this study were to discover: (a) if toothbrushing frequency in adolescence predicts attained education level in early middle age, (b) if that association exists after controlling for school achievement and sociodemographic background, and (c) how toothbrushing frequency is linked with other health-related behaviors in adolescence.
|
MATERIALS & METHODS |
|---|
|
TOPABSTRACTINTRODUCTIONMATERIALS & METHODSRESULTSDISCUSSIONREFERENCES |
|---|
From their Register of Completed Education and Degrees, Statistics Finland (2000) released the data on the highest level of education attained. These data were linked to questionnaire data without revealing the names of individual participants. Participants in the longitudinal data study consisted of all respondents to the baseline surveys, a total of 9407 persons. The participation rates were 74%–88% in boys and 85%–92% in girls.
At the end of the follow-up in 1998, the sample members had reached ages 27–33 (Appendix 1, www.dentalresearch.org). By that age, most people have attained at least their first level of education after compulsory lower secondary schooling (Statistics Finland, 2000). The register assigns the lowest education level to every person without any higher level of education.
Study Variables
Attained education level (follow-up) consisted of four categories according to length of respondents’ education (Appendix 2, www.dentalresearch.org).
Health behaviors were classified into "not health-compromising" (0) and "health-compromising" (1):
Sociodemographic background:
School achievement/education track (Table 1
):
|
Statistical Analysis
Since the outcome variable was polychotomous and ordinal-scaled, cumulative logistic models (Hosmer and Lemeshow, 2000) were used for associations between toothbrushing frequency and attained education level. Then, we included sociodemographic background and school achievement/education track variables to see if this changed the associations. Stepwise backward elimination was applied. Age groups were analyzed separately.
The cumulative odds ratios with 95% confidence intervals (CI) were calculated for significant (p < 0.05) associations. Cumulative odds ratio expresses the incidence of higher categories of the outcome variable as compared with the lower categories on various values of the explanatory variables.
Father’s education level and occupation were not requested from part of the sample of 16-year-olds in 1985. Thus, 19% of the questionnaires lacked information on father’s education and 20% lacked information on occupation. The replacement of the missing value by the most probable, modal, value on the basis of data in the other variable yielded 54 more values for father’s occupation and 103 values for education level.
We applied exploratory factor analysis to find the dimensions for health behaviors. For the dichotomized behavior variables, tetrachoric correlation coefficients were used (Muthen, 1978). Principal component analysis with oblique (direct oblimin) rotation was applied.
The analyses were carried out by means of the PR, 4M, and 4F programs in the BMDP statistics package (Los Angeles, CA, USA).
|
RESULTS |
|---|
|
TOPABSTRACTINTRODUCTIONMATERIALS & METHODSRESULTSDISCUSSIONREFERENCES |
|---|
). At all ages, good school achievement, as well as father’s high education or occupational level, or living with both parents predicted a high education level. At age 12, female gender predicted a high education level. Living in a small town or village at ages 12 and 14, as well as living in the Central-West or the Northern part of Finland at age 16, anticipated a high education level.
Toothbrushing Frequency as a Part of Adolescent Health-related Lifestyle
The younger the respondents, the higher were the proportions of those who brushed their teeth seldom (Table 2). The proportions of those who smoked, used alcohol, drank coffee, consumed snackbar food, had an irregular bedtime, or did not participate in physical exercise increased along with age.
|
). Eigenvalues were smaller than 1 for solutions of 5 or more factors. In four-factor solutions, Eigenvalues were 1.03 in 12-year-olds, 1.09 in 14-year-olds, and 1.06 in 16-year-olds. The proportions of variance explained were highest for the four-factor solutions: 58% in 12- and 14-year-olds and 59% in 16-year-olds. If a two-factor solution was chosen, the proportions of variance explained would have varied between 37% and 38%. In three-factor solutions, the proportions would have varied between 48% and 49%.
|
). At ages 14 and 16, minor consumption of snackbar food also loaded this factor highly. However, at age 14, toothbrushing frequency also had a high loading on another factor, consisting of consumption of coffee, pastries, and milk fat ("traditional"). This pattern strengthened in 16-year-olds, when the loading of toothbrushing frequency on the "street-oriented" factor was modest. At every age, there were two further factors, one consisting of unhealthy dietary choices, namely, consumption of sweets, snackbar food, and pastries ("modern"), and another consisting of the physical exercise variables ("exercise").
|
|
DISCUSSION |
|---|
|
TOPABSTRACTINTRODUCTIONMATERIALS & METHODSRESULTSDISCUSSIONREFERENCES |
|---|
Social background seems to relate to parents’ ability to promote their children’s education. When the parents teach regular toothbrushing, they also transmit ideals of goal-directed behavior, enabling the children both to retain their (dental) health and to take care of their school duties. Toothbrushing may indicate familial inclination to common activities and to promote children’s healthy development (Paunio et al., 1993). The fact that living with both parents predicted a high education level further emphasized the role of the family’s resources in furthering children’s education and health (Mulkey et al., 1992).
The importance of school achievement may signify that adolescents brushing regularly are successful in school. Many health-related activities are motivated by a person’s desire to increase personal attractiveness (Prokhorov et al., 1993). Adolescents who do not brush regularly give up one possibility for achieving social acceptance and prestige among peers. This may indicate the existence of other problems, such as indifference, low self-esteem, and underestimation of their abilities (Macgregor et al., 1997; Källestål et al., 2000).
The boys’ lower participation rates led to a slightly higher proportion of girls in the study materials as compared with the entire Finnish population of the same age (Statistics Finland, 2000). In health-related studies, non-response is associated with poor school performance and negative health behaviors (Koivusilta, 2000). Adolescents who smoke, brush their teeth infrequently, and have poor school achievement were more weakly represented in this sample than were other adolescents. This is consistent with the finding that the respondents had, on average, a slightly higher education level than the total population of the corresponding age (Statistics Finland, 2000). The repeatability of variables describing behaviors, school achievement/education track, and sociodemographic background has previously been found to be very good (Koivusilta, 2000). At the beginning of the study program, a detailed analysis of drop-outs was accomplished by ’phone interviews and by the repeated mail questionnaires (Ahlström et al., 1979). The response rates in this study were very high, and therefore drop-out bias was very small.
At ages 12 and 14, infrequent toothbrushing was typical of adolescents involved with problem behaviors, namely, smoking, alcohol use, and having an irregular bedtime. At age 14, frequent consumption of snackbar food was related with a "street-oriented" lifestyle (West and Sweeting, 1997). Those behaviors are often practiced together with peers (Norton et al., 1998), and interest is directed toward spheres of life other than school, such as leisure and spending time out of home (Glendinning et al., 1995). Smoking is a strong predictor of a low education level (Koivusilta et al., 1998), and behaviors which accumulate around smoking may be part of a broader, "rebellious", lifestyle in which education is not much valued (West, 1991).
At age 14, toothbrushing frequency was also associated with consumption of coffee, pastries, and milk fat. These nutritional choices are typical of a rural (agricultural) population (Hemminki et al., 1988) and low socio-economic groups (James et al., 1997). This factor was called "traditional". At age 16, toothbrushing frequency loaded weakly on a "street-oriented" lifestyle but highly on a "traditional" lifestyle. By this age, an adult pattern of health behaviors has largely been established (Hurrelmann, 1989). In the two youngest age groups, toothbrushing frequency seemed to indicate the degree to which the values of normative society and its achievement ideology would be adopted. At age 14, identification with population groups with low education goals had already begun. By age 16, low toothbrushing frequency reflected the fact that a lifestyle in which education is not an important value had become quite firmly settled.
The third factor was called "modern" because it involved features of consumerism. Eating sweets loaded highly on this factor. At all ages, the loadings on this factor showed that when the consumption of sweets increased, toothbrushing frequency increased as well. Instead, on "traditional" and "street-oriented" factors at ages 12 and 14 and on the "street-oriented" factor at age 16, an increase in the consumption of sweets meant a decrease in toothbrushing frequency.
Physical exercise variables formed a distinct factor, called "exercise". At age 12, not taking part in physical exercise was typical of those who drank alcohol and who brushed their teeth infrequently. At other ages, only exercise variables loaded highly on this factor.
The four-factor solutions explained 58%–59% of the variance in health behaviors and had Eigenvalues higher than 1. A confirmatory factor analysis, using a set of somewhat different variables (Aarø et al., 1995), supported the hypothesis of bi-dimensionality in health behaviors of 15-year-olds. In our study, "street-oriented" lifestyle closely resembled the addictive one. The fact that health-enhancing behaviors loaded highly on both "traditional" and "modern" factors may reflect a division between rural and urban lifestyles. The physical exercise variables formed a dimension of their own with high loadings. When a two-factor solution was forced to our data, the factors closely resembled those of the previous study (Aarø et al., 1995). However, contrary to that study, nutritional and exercise variables were not combined as sumscores in our study, and thus, allowing for more factors made the picture of adolescent lifestyles more specific. The dichotomization of the original variables may have made them less informative. However, since these variables could not be regarded as continuous and normally distributed, tetrachoric correlation coefficients were used.
In conclusion, a low toothbrushing frequency indicates selection into the less-educated stratum of society. The fact that daily toothbrushing has become a habit of a high proportion of adolescents by age 16 may indicate that the fifth part of this age group is a quite select cluster of young people. The strong association between low toothbrushing frequency and other health-compromising behaviors is likely to be reflected in socio-economic health differences in adulthood. Those planning dental health interventions should remember that health behaviors are not practiced independently of each other. Dental care personnel might have a role in identifying adolescents who are in danger of becoming marginalized from society.
|
ACKNOWLEDGMENTS |
|---|
|
FOOTNOTES |
|---|
Received July 25, 2002; Last revision January 7, 2003; Accepted January 29, 2003
|
REFERENCES |
|---|
|
TOPABSTRACTINTRODUCTIONMATERIALS & METHODSRESULTSDISCUSSIONREFERENCES |
|---|
Ahlström S, Eskola A, Honkala E, Kannas L, Laakso L, Paronen O, et al. (1979). The Juvenile Health Habit Study. Study design, methods and material. Publications in Public Health, University of Tampere M 48/79. Tampere, Finland.
Donovan JE, Jessor R, Costa FM (1993). Structure of health-enhancing behavior in adolescence: a latent-variable approach. J Health Soc Behav 34:346–362.[ISI][Medline]
Glendinning A, Hendry L, Shucksmith J (1995). Lifestyle, health and social class in adolescence. Soc Sci Med 41:235–248.
Hemminki E, Rahkonen O, Rimpelä A, Rimpelä M (1988). Coffee drinking among Finnish youth. Soc Sci Med 26:259–264.
Honkala E, Rajala M, Rimpelä M (1981). Oral hygiene habits among adolescents in Finland. Community Dent Oral Epidemiol 9:61–68.[ISI][Medline]
Honkala E, Paronen O, Rimpelä M (1983). Familial aggregation of dental health habits in Finland. J Pedod 7:276–290.[Medline]
Hosmer DW, Lemeshow S (2000). Applied logistic regression. New York: John Wiley & Sons, Inc.
Hurrelmann K (1989). Human development and health. Berlin: Springer-Verlag.
James WP, Nelson M, Ralph A, Leather S (1997). Socioeconomic determinants of health. The contribution of nutrition to inequalities in health. Br Med J 314:1545–1549.
Källestål C, Dahlgren L, Stenlund H (2000). Oral health behaviour and self-esteem in Swedish children. Soc Sci Med 51:1841–1849.
Koivusilta L (2000). Health-related selection into educational tracks. A mechanism producing socio-economic health differences. Annales Universitatis Turkuensis. Ser D. Tom. 394. Medica-Odontologica. Turku: Painosalama Oy.
Koivusilta L, Rimpelä A, Rimpelä M (1998). Health related lifestyle in adolescence predicts adult educational level: a longitudinal study from Finland. J Epidemiol Community Health 52:794–801.[Abstract]
Koivusilta LK, Rimpelä AH, Rimpelä M, Vikat A (2001). Health behavior-based selection into educational tracks starts in early adolescence. Health Educ Res 16:201–214.
Kuusela S, Honkala E, Kannas L, Tynjälä J, Wold B (1997). Oral hygiene habits of 11-year-old schoolchildren in 22 European countries and Canada in 1993/1994. J Dent Res 76:1602–1609.
Macgregor ID, Regis D, Balding J (1997). Self-concept and dental health behaviours in adolescents. J Clin Periodontol 24:335–339.[ISI][Medline]
Mattila ML, Rautava P, Sillanpää M, Paunio P (2000). Caries in five-year-old children and associations with family-related factors. J Dent Res 79:875–881.
Mulkey LM, Crain RL, Harrington AJC (1992). One-parent households and achievement: economic and behavioural explanations of a small effect. Sociology of Education 65:48–65.
Muthen B (1978). Contributions to factor analysis of dichotomous variables. J Am Statist Assoc 74:807–811.
Neumark-Sztainer D, Story M, French S, Cassuto N, Jacobs DLJ, Resnick MD (1996). Patterns of health-compromising behaviors among Minnesota adolescents: sociodemographic variations. Am J Public Health 86:1599–1606.
Norton EC, Lindrooth RC, Ennett ST (1998). Controlling for the endogeneity of peer substance use on adolescent alcohol and tobacco use. Health Econ 7:439–453.[ISI][Medline]
Paunio P, Rautava P, Sillanpää M, Kaleva O (1993). Dental health habits of 3-year-old Finnish children. Community Dent Oral Epidemiol 21:4–7.[ISI][Medline]
Prokhorov AV, Perry CL, Kelder Sh, Klepp K-I (1993). Lifestyle values of adolescents: results from Minnesota Heart Health Youth Program. Adolescence 28:637–647.[ISI][Medline]
Rajala M, Honkala E, Rimpelä M, Lammi S (1980). Toothbrushing in relation to other health habits in Finland. Community Dent Oral Epidemiol 8:391–395.[ISI][Medline]
Statistics Finland (2000). Register of completed education and degrees. The 25–35-year-old Finnish population according to highest completed education, age and gender in 1998. Helsinki: Statistics Finland.
Wannamethee SG, Shaper AG, Walker M, Ebrahim S (1998). Lifestyle and 15-year survival free of heart attack, stroke, and diabetes in middle-aged British men. Arch Intern Med 158:2433–2440.
West P (1991). Rethinking the health selection explanation for health inequalities. Soc Sci Med 32:373–384.
West P, Sweeting H (1997). "Lost souls" and "rebels": a challenge to the assumption that low self-esteem and unhealthy lifestyles are related. Health Educ 5:161–167.
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
| IADR Journals | Advances in Dental Research ® |
| Journal of Dental Research ® | Critical Reviews (1990-2004) |
