To examine the relationship between stress and perceived social support among high school students, we asked 3, 254 students in Okinawa to respond to questionnaires pertaining to depressive symptoms, daily hassles, and social support. We measured depressive symptomsas stresses by using the Zung Self-rating Depressive Scale (SDS). A junior high school version of the Scale of Expectancy for Social Support (SESS) was used to measure the expectancy of social support. As a result, females showed significantly higher scores on depressive symptoms, and support from mother, siblings and friends than males, while males reported significantly higher scores on support form father and teachers than females. There were no gender differences in daily hassles. Daily hassles and each support resource had significant main effects on depressive symptoms, but no interaction was found between them in both males and females. In other words, social support had direct effects on depressive symptoms, and it was highly probable that the expectancies of social supports reduce the depressive symptoms, regardless of intensity of daily hassles. When the expectancies of other support resources were adjusted, we found that supports only from father and friends reduce depressive symptoms in males, while supports from father, mother, siblings, and friends do in females. These findings demonstrate that daily hassles and social support are independently related to depressive symptoms of high school students, and that depressive symptoms could be reduced directly by the expectancy of social support such as support from father and friends in both males and females, and support from mother and siblings in females only. In conclusion, these findings support the direct effect hypothesis of social support for high school students.
We analyzed data on 84 women who had self-recorded dates of menstruation prospectively for nearly 10 years since their entrance to a college of physical education in April 1981. In terms of changes in the menstrual cycle length by age, 70% of the women could be classified into the following three patterns: (1) the length remained almost within gynecological normal range from age 18 to 27 (?gpattern A?h, 28.6%), (2) the length fluctuated only during their college student days (from age 18 to 22) and then became stable (?gpattern B?h, 21.4%), and (3) the length fluctuated considerably throughout the period observed (?gpattern C?h, 19.0%). The mean ages at menarche were higher among the pattern B and C subjects than that among the pattern A subjects . Distribution of the three patterns was different according to the age at menarche: proportion of pattern A was highest (50.0%) among those who had experiencedmenarche at age 11 and decreased to 9 .1% among those who had experienced menarche at age 13. Proportions of patterns B and C increased accordingly, and pattern A dominated among those with the menarcheal age 14. Proportion of patterns B and C was higher (that of pattern A was lower) among athletes than among non-athletes. However, pattern A was also observed in some athletes and pattern C in some non-athletes . In conclusion, the cyclicity of menstruation after age 18 is relatively stable among non-athlete women with early menarche, though there still existed some cases who did not show stabilization, suggesting that the length of menstrual cycle in women who graduated from college of physical education does not always become stabilized.
In order to elucidate the influence of drinking water components and lifestyle on bone density, we carried out chemical analysis of the water drunk by 463 adult females (mean age: 49.9 ± 11.0 years) living in Saitama Prefecture, together with questionnaire survey and ultrasonic bone densitometry measurement. It was found that, in both pre- and post-menopausal women, the larger the body weight the higher the bone density. In the pre-menopausal group, furthermore, bone density tended to increase as the subjects did more frequently out-door activities and as Ca concentration in their drinking water was higher. In the post-menopausal women, higher bone density was associated with higher intake of milk and dairy products at present. According to statistical analysis, the factors whose correlations with bone density were greater in the order: frequency of out-door activities, Ca concentration in drinking water, and body weight for pre-menopausal women; body weight, and the consumption of milk and dairy products for post-menopausal women. Our present results indicated that, in addition to physical factors and lifestyle, Ca concentration in water was related to bone density, though only among women before menopause. In this particular area, therefore, the quality of drinking water might be an important factor which is related to bone density.
The incidence of retinopathy among diabetic workers in the gas industry was studied. 281 workers with diabetes mellitus were followed up from the onset of disease to retirement. Of them, 106 developed retinopathy. The relation between the incidence of retinopathy and the following 12 factors pertaining to diabetic workers was analysed: l) classification according to Keith-Wagener criteria of fundus oculi, 2) classification according to control of the cardiovascular system, 3) classification according to control of diabetes mellitus, 4) weight control, 5) total cholesterol levels, 6) triglyceride levels, 7) HbA1C, 8) urinary protein, 9) age at present, 10) age at diagnosis, 11) duration of diabetes, 12) family history of diabetes. Hayashi's Quantification II Analysis was used for calculation of risk factors. The major results were as follows: 1. The factor most closely associated with the development of retinopathy was the classification according to Keith-Wagener criteria. 2. Factors closely associated with the development of retinopathy in order were: Keith-Wagener classification> control of diabetes (insulin therapy) > HbAlc (greater than 8.1%)= low weight > urinary protein positive = the age at diagnosis (younger than 29) = Age at present (40 to 49). 3. Controllable parameters such as weight, hyperlipidemia, and blood glucose level are factors less closely associated with the development of retinopathy. 4. Although Keith-Wagener classification, age, and duration of diabetes are uncontrollable, these factors are associated with the development of retinopathy. 5. The risk score for each risk factor was calculated as follows:Risk factor Risk scoreKeith-Wagener classification 3 ---------10Insulin (less than 40 U per day)--------- 5Keith-Wagener classification 2 --------- 4HbAlc>8.1%--------------------------------- 2Low weight <95% --------------------------- 2Keith-Wagener classification 1 --------- 1Urinary protein positive ------------------ 1Age at diagnosis (younger than 29) --- 1Age at present (40 to 49) ------------------ 16. Based on the total risk score for each individual, the probability values of development of retinopathy were estimated as follows:Risk score Probability0 0.171.0 0.302.05.0 0.526.09.0 0.8610 1.00 These findings demonstrate difficulties in management of diabetes and suggest that assessment of individuals and long-term care is important for diabetic patients.