Educational Level and Osteoporosis Risk in Postmenopausal Chinese Women
Suzanne C. Ho1,
Yu-ming Chen1,2 and
Jean L. F. Woo3
1 Department of Community and Family Medicine, Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China
2 Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, People's Republic of China
3 Department of Medicine and Therapeutics, Chinese University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China
Reprint requests to Suzanne C. Ho, Department of Community and Family Medicine, Chinese University of Hong Kong, 4th Floor, School of Public Health, Prince of Wales Hospital, Shatin NT, Hong Kong Special Administrative Region, People's Republic of China (e-mail: suzanneho{at}cuhk.edu.hk).
Received for publication May 13, 2004.
Accepted for publication September 8, 2004.
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ABSTRACT
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Many studies have shown that better education is favorable for lowering the risks for a number of chronic diseases, but little information is available on the relation with bone health. The authors examined the association of educational level, classified as levels IIV, with bone mineral density (BMD) and with the prevalence of osteoporosis among 685 population-based, postmenopausal, Chinese women aged 4863 years during 19992001. They observed a significant dose-response positive relation between educational level and BMDs at the total-body (p = 0.011), lumbar spine, and hip sites (p < 0.001) after adjusting for age, years since menopause, and body weight. Mean BMDs of educational level IV women were higher by 4.211.9% at the various sites compared with level I women (analysis of covariance, p < 0.05). Similarly, the authors also observed a significant inverse dose-response relation between educational level and prevalence of osteoporosis. Women of educational level I were 3.58.6 times more likely to be osteoporotic compared with those of level IV at the various sites. The proportion of BMD or osteoporosis variations accounted for by educational level was attenuated by about 40% after further controlling for potentially explanatory covariates. In conclusion, a higher level of education is independently associated with better BMDs and lower prevalence of osteoporosis among postmenopausal Chinese women.
Asian continental ancestry group; bone density; education; osteoporosis, postmenopausal; women
Abbreviations:
BMD, bone mineral density; SD, standard deviation
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INTRODUCTION
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Osteoporosis is an increasing public health problem worldwide (1
, 2
). It has been estimated that, in 1990, 1.7 million people globally suffered from osteoporotic hip fractures. The number might increase to 6.3 million by 2050 (3
). Osteoporotic fractures are a great burden to the individual and the community, and they pose great economic costs to society (3
).
Although therapeutic measures are presently available for the prevention of bone loss and/or restoration of bone health, their long-term benefits are inconsistently reported (4
, 5
). As such, an understanding of the determinants of bone health and the early prevention of bone loss are important to reduce osteoporotic fractures in later life (6
, 7
).
Many studies have demonstrated that socioeconomic status or educational level is associated with a number of chronic diseases, such as obesity, diabetes, and some cancers (8
10
). Woo et al. (10
) have reported that a higher level of education is associated with a healthier diet and lower cardiovascular risk. However, inconsistent findings between educational level and osteoporosis have been noted (11
), and little is known about how education affects bone health in postmenopausal Chinese women (12
). Better-educated individuals might tend to have better health knowledge and behavior (13
17
) in developed countries and regions. On the other hand, increasing affluence and education in developing regions might lead to better nutrition but also to a change of traditional-but-healthy behaviors toward less healthy lifestyles, such as a reduction of physical activities. As such, a "double-edged sword" phenomenon might occur.
We examined the association of the level of education with bone mineral density (BMD) and with the occurrence of osteoporosis to assess if the education-BMD/osteoporosis association could be attributable to education and relevant lifestyle and behavioral factors among 685 Chinese women in Hong Kong within the first 12 years of natural menopause.
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MATERIALS AND METHODS
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Subjects
We conducted a cross-sectional study of social and lifestyle factors and bone mass among 685 population-based, postmenopausal, Chinese women from October 1999 to January 2001. The study methods have been described in detail in a previous report (18
). In brief, the study participants were community-dwelling subjects residing in housing estates in Shatin, Hong Kong Special Administrative Region, People's Republic of China. Stratified-cluster sampling was used to select the housing estates in the Shatin district of Hong Kong. Recruitment included both door-to-door and written invitations placed in mailboxes. Eligibility criteria included Hong Kong residents of Chinese origin who were aged between 48 and 63 years and within 12 years of natural menopause, defined as at least 12 months since the last menstrual cycle. Subjects who had received hormone replacement therapy for 3 months or more or had any medication known to affect bone mass were excluded. Written, informed consent was obtained from all the participants prior to enrollment. A total of 685 volunteers were recruited and met the screening criteria. The ethics committee of the Chinese University of Hong Kong approved the study.
Data collection
Trained interviewers conducted face-to-face interviews based on a structured and previously validated questionnaire. Information collected included sociodemographic data; final grade of formal education attained; years since menopause; and physical activities including average hours spent in sitting, standing, and walking and in mild and vigorous physical activities. Lifestyle factors included smoking, drinking, and dietary intake (19
, 20
). Dietary intakes of calcium, protein, and other nutrients were based on a quantitative food frequency questionnaire that included 60 food groups/items as described in previous studies (18
, 21
). Nutrients were calculated from food composition tables (22
, 23
).
Anthropometric and bone mass measurements
Height was measured to the nearest 0.5 cm, and weight was measured to the nearest 0.1 kg in light clothing and without shoes. Body mass index was calculated as weight (kg)/height (m)2. The BMD of the whole body and subsites, the lumbar spine (L1L4) and the left hip sites, was measured by dual-energy x-ray absorptiometry using a Hologic QDR-4500 densitometer (Hologic, Inc., Waltham, Massachusetts) (18
, 21
). The BMD was calculated as bone mineral content (g)/bone area (cm2) at the relevant sites. Whole-body BMD represents bone mineral content per unit (cm2) of total bone area of the whole body. All subjects were measured with the same densitometer and by the same operator. The coefficient of variation of measurements with the spine phantom was 0.4 percent. The in vivo coefficients of variation for BMD measurements were 1.53 percent, 1.72 percent, 1.15 percent, 4.86 percent, and 1.2 percent for the spine, femoral neck, trochanter, intertrochanter, and whole body, respectively. Osteoporosis of the whole body, spine, and hips was defined as T scores of BMDs at the relevant sites equal to or less than 2.5 standard deviations using the Oriental population referent values established by Hologic, Inc. The BMD peak mean referent values in the Oriental population for the calculation of T scores were 1.102 (standard deviation (SD): 0.087) (whole body), 1.047 (SD: 0.110) (lumbar spine), 0.975 (SD: 0.120) (total hip), 0.895 (SD: 0.100) (neck), 0.722 (SD: 0.090) (trochanter), 1.148 (SD: 0.141) (intertrochanter), and 0.796 (SD: 0.110) (Ward's triangle) g/cm2.
Statistical analysis
The independent variable (educational level) was classified into four groups including no formal education (I), primary school education (II), secondary school education (III), and college education or above (IV). The dependent variable included bone mineral density of the whole body, lumbar spine (L1L4), and left hip. Means and covariate-adjusted means of the BMDs at the various bone sites among the education groups were compared by post hoc multiple comparison tests (method: least significant difference) of one-way analysis of variance and analysis of covariance. The linear dose-response relations between educational level and BMDs were also calculated using analysis of variance and analysis of covariance models. In the multivariate analyses, age, body weight, and years since menopause were first adjusted for to examine the independent association between educational level and BMDs. Potentially explanatory covariates, including height, age at menarche, duration of pregnancy and lactation, physical activities, dietary intakes, and current job, were further controlled for to evaluate whether the education-BMD association could be explained by these covariates. Only the covariates that remained significant at borderline significance (p < 0.10) were retained in the final model. A manual forward stepwise method was used in adding the potential covariates, with educational level forced into the models. F-to-entry and -remove criteria were 0.05 and 0.10. Partial
2 was used to assess the percentage of the BMD variations accounted for by educational level in the final models.
Logistic regression analyses were used to test the independent association of levels of education with the occurrence of osteoporosis as defined by T scores of less than 2.5 standard deviations from the respective bone sites after controlling for the covariates. Forward stepwise and enter procedures were used, respectively, for adding the covariates and educational level. F-to-entry and -remove criteria were 0.05 and 0.10 in the stepwise procedure. The proportion of variations in the prevalence of osteoporosis accounted for by educational level was estimated by the change of Nagelkerke R2 statistics produced by adding the independent variable. SPSS for Windows, release 11, software (SPSS, Inc., Chicago, Illinois) was used for the analysis.
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RESULTS
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The study subjects had a mean age of 55 (SD: 3.5) years, ranging from 48 to 63 years. The mean years since menopause were 4.6 (SD: 2.8) years, with a range from 1 to 12.5 years. Better-educated subjects tended to be taller and to have a lower body mass index and higher intakes of dietary energy, calcium, phosphorus, plant protein, soy protein, and fresh fruits. Higher education is also associated with a younger age at menarche and a shorter duration of pregnancy and lactation (table 1). The primary and secondary education groups were younger and had fewer years since menopause. There were few differences in physical activities among the four education groups. Better-educated individuals tended to spend less time in walking and in weight-bearing physical activities. Only a few individuals drank alcohol more than once per week (3.74.8 percent) or were smokers (
1 cigarette/week for 3 months) (<2 percent) (table 1).
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TABLE 1. Characteristics of 685 postmenopausal Chinese women aged 4863 years by educational levels, Hong Kong, 19992001
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The mean BMDs were significantly higher among groups with a higher level of education. We observed dose-response linear relations between educational level and mean BMDs at the lumbar spine (L1L4) (p = 0.008), total hip (p = 0.001), and subhip (p < 0.003) sites. The mean BMDs of education group IV were 4.0 percent (whole body), 7.8 percent (lumbar spine), and 8.018.1 percent higher at the hip sites compared with those of group I (p < 0.05) (data not shown).
After adjustments for age, years since menopause, and body weight in analysis of covariance models (table 2), the differences in covariate-adjusted means and the linear trends between education and BMDs were much more pronounced than those in the univariate models. We also observed very significant linear trends of increasing BMDs and educational level (p < 0.008) at all study sites except for the arms. The proportion of BMD variations explained by educational level ranged between 1.1 percent for the whole body and 3.5 percent for the total hip.
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TABLE 2. Age-, body weight-, and years since menopause-adjusted means of bone mineral density among 685 postmenopausal Chinese women aged 4863 years by educational levels, Hong Kong, 19992001
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The prevalences of osteoporosis, as defined by a BMD T score of less than 2.5 at the various bone sites, decreased with increases in levels of education (table 3). Logistic regression analyses revealed a significant independent increase in risk of osteoporosis from 3.5- to 8.6-fold among subjects with no formal education (group I) when compared with those with tertiary education (group IV), even after adjustment for age, years since menopause, and body weight. The educational level accounted for 1.93.9 percent of the variations in prevalences of osteoporosis. The educational level still remained significant when it was treated as a linear variable (I = no formal, II = primary, III = secondary, IV = tertiary) (data not shown).
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TABLE 3. Prevalence of osteoporosis and odds ratios for educational levels among 685 postmenopausal Chinese women aged 4863 years, Hong Kong, 19992001*
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To explore whether the education-BMD/osteoporosis association is attributable to the measured covariates, including body height, reproductive factors, habitual dietary intakes, physical activities, and current job, we performed further adjustments for these covariates. Although the associations between educational levels and BMD or prevalences of osteoporosis still remained significant at the lumbar spine and hip sites (table 4), the proportions of BMD variations (partial
2) were attenuated by 39 (range: 1948) percent (percent variations in the partial
2) after further including these covariates in the models compared with the models including only age, years since menopause, and body weight (tables 2 and 4). Similarly, we also observed a significantly increased risk of osteoporosis with a lower level of education after the further adjustments (table 3). Women with no formal education had a significant increased risk of having osteoporosis of from 2.9- to 5.8-fold. The covariates accounted for an average of 43 (range: 3565) percent (percent variations in the R2 change) of the association of education with prevalences of osteoporosis.
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TABLE 4. Adjusted means of bone mineral density of 685 postmenopausal Chinese women aged 4863 years by educational levels, Hong Kong, 19992001
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DISCUSSION
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Many studies have demonstrated that increases in educational level are associated with lower risks for many chronic diseases, such as obesity, cardiovascular diseases, and diabetes (8
10
). However, it is unclear whether better education is favorable to bone health. del Rio Barquero et al. (24
) first reported that Spanish men and women with lower socioeconomic status had significantly lower BMD values than those with higher socioeconomic status, but other studies had found higher BMD values at the lumbar spine and femoral neck among men with lower socioeconomic status (25
). Similar inconsistent associations between education and bone mass or risk of fractures have been reported (11
, 26
28
). Lauderdale et al. (11
, 26
) found a favorable association between better bone density and higher educational status among premenopausal women from the United States but not among postmenopausal immigrant women from Vietnam, Cambodia, and Laos. Shaw (27
) found no significant associations in a cross-sectional study of healthy volunteers in Taiwan. Colon-Emeric et al. (28
) observed a positive association between educational levels and risk of hip fracture (odds ratio = 2.0, 95 percent confidence interval: 1.2, 3.2) among ambulatory non-Hispanic White men.
In this population-based, cross-sectional study of postmenopausal Chinese women, we found that a higher level of formal education, in particular tertiary education, was strongly associated with better BMD values at various sites and with lower prevalence of osteoporosis. The associations held, even after adjustments for strong confounders such as age, years since menopause, and body weight. We also observed a linear dose-response relation between BMD values or osteoporosis prevalence and levels of education. We observed quite large BMD differences of 912 percent for the spine or femoral neck between women with no formal education and those with tertiary education. A meta-analytical study (29
) of the effect of 2-year hormone replacement therapy on BMD revealed differences of about 7 percent for the spine and 4 percent for the femoral neck. The substantial difference found in our study suggests that the enhancement of educational level could be an important social determinant for the prevention of osteoporosis in this population.
Educational attainment is a major determinant of income and occupation and, thus, an essential marker of an individual's social economic status, especially in regions undergoing economic transitions. Income and socioeconomic status are also important determinants of a host of social and environmental exposures (30
, 31
). Lifestyle, behavior, diet, and nutrition are closely linked with education and socioeconomic status, although such influences may vary among different population groups and stages of economic development.
Our data showed that taller height and younger age at menarche were significantly associated with higher educational level. Body height and age at menarche are important markers of nutrition and health status in childhood and adolescence. Adequate intakes of protein, calcium, and other vitamins and minerals are required for bone accretion and the attainment of the full genetic potential for peak bone mass. Many studies have demonstrated that dietary intakes in early life have a long-term effect on bone mass in adulthood (32
, 33
). Age at menarche is also a reflection of childhood nutrition, and previous studies have also reported an inverse association with bone mass in postmenopausal women (34
, 35
). Therefore, early nutritional status might contribute to the education-bone mass association.
After the early years, better education might directly influence bone health through the positive effect of better health knowledge on individuals' lifestyles and behaviors. Many studies have shown that better-educated individuals tend to exercise more, smoke less, and have better maintenance of body weight. They also tend to have more positive attitudes toward use of medications and more efficient use of health-care resources (16
). Better educated individuals also tend to adopt healthier eating habits, including more dietary calcium, vegetables, soy foods, and fruits and less saturated fat and alcohol (10
, 12
, 36
38
). An association between higher intakes of calcium, soy, and/or fresh fruits or vegetables with better bone mass in postmenopausal women has been reported (18
, 21
, 39
, 40
). Such education-associated favorable dietary habits might play a role in the improvement of bone health.
More of the less educated women were engaged in blue-collar work. They also tended to have higher levels of walking and of weight bearing and possibly vigorous activities compared with women who had a higher level of education. Thus, physical activity did not seem to serve as a crucial link between the positive association of education and bone mass. As few women in the study population smoked or consumed alcohol, we observed no differences in the prevalences of these behaviors among the different education groups. Because we excluded from this study all current or ever (>3 months) users of exogenous estrogens, corticosteroids, thiazine, and other medications known to affect bone mass, such factors are unlikely to influence the association between education and bone mass.
Reproductive factors may play a role in the maintenance of bone mass. Previous studies have found both positive and negative effects of pregnancy and lactation on BMD in postmenopausal women (41
43
). Although, in our study, better-educated individuals tended to have a shorter duration of pregnancy and lactation, these factors have not been shown to have a significant influence on bone mass.
Body weight and years since menopause or age had a significant influence on BMD or osteoporosis but had little influence on the independent association between education and bone mass or osteoporosis. As education per se could not be a plausible causal factor of bone health, other factors associated or influenced by education are the probable explanations. To assess to what extent the measured covariates might explain the education-BMD association, we made further adjustments for these covariates in multivariate analyses. The adjusted covariates included body height, dietary factors, physical activities, age at menarche, duration of pregnancy and lactation, and current job. The inclusion of significant biologic and lifestyle factors had attenuated about 40 percent of the education-BMD association, but education still remained a significant predictor. One possible reason could be that the current status of some of the covariates might not represent their levels of life-long exposures. Another reason might be due to measurement errors and biases in the assessment of these covariates. There is also the possibility that other potentially important, education-associated causal factors (e.g., genetically related) have not been included in this study.
Our findings showed that the education-BMD association was more pronounced at the weight-bearing sites, such as the hip sites and spine, but not in the arms. The latter, being a non-weight-bearing site and consisting mainly of cortical bone, might be influenced by some other factors and pathways.
Cumulative literature from the West has overwhelmingly suggested that income exerts a positive impact on health, but less is known about the nature and magnitude of the relation between wealth and health in regions such as Asia where rapid economic transitions have been taking place. However, it is inappropriate to generalize our findings to other populations and settings in the region. For example, in part of Asia, individuals with a lower level of education usually have high levels of physical activities due to engagement in manual labor. They also tended to have higher intakes of vegetables and plant protein due to limited income and availability of animal foods. Individuals with better education and income usually consume more animal foods and have less physical activities due to decreases in manual work and greater use of transportation by cars and elevators (44
, 45
). As such, the higher income and education group might have a "good," rather than a healthy, diet and a comfortable but not necessarily healthy lifestyle if their income increases more rapidly than their knowledge of health and diseases. In these settings, higher education might not be associated with better health outcomes (46
).
Although this study is cross-sectional in design, educational achievement is a relatively stable characteristic and unlikely to be influenced by recall bias. However, as we have not assessed the participants' knowledge of, attitudes toward, and activities involved in the prevention of osteoporosis, further studies in these areas might help to elucidate the mechanisms by which education improves bone health. Public health intervention programs might thus take into consideration the socioeconomic and educational backgrounds of target populations. Because half of the world's hip fractures are projected to occur in Asia by 2050 (30
), the steep rise of this disease and the income disparity in this part of the world would call for more research into the social determinants of osteoporosis.
In conclusion, our findings showed that a higher level of education was associated with significantly higher BMDs at the whole body, lumbar spine, and hip sites and with lower prevalences of osteoporosis at these sites in a dose-response manner, even after controlling for the strong confounders. More attention should be paid to education as a determinant of bone health in future research and health promotion activities.
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ACKNOWLEDGMENTS
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The study was partially supported by the Health Services Research Fund of Hong Kong.
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