Influencing factors of abnormal bone mass in perimenopausal and postmenopausal women based on health ecology model: A cross-sectional study

Influencing factors of abnormal bone mass in perimenopausal and postmenopausal women based on health ecology model: A cross-sectional study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Influencing factors of abnormal bone mass in perimenopausal and postmenopausal women based on health ecology model: A cross-sectional study Haiyang He, Jialing Yang, Qian Wen, Yaoyao Zhou, Meng Wang, Zhifeng Cheng, and 11 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3848504/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background As the world's population ages, bone health has become a major public problem. The incidence of osteoporosis in women will further increase due to the decline of oestrogen after menopause. In this study, we used a health ecology model to explore the factors affecting abnormal bone mass in perimenopausal and postmenopausal women at different levels, and to provide a basis for the management and prevention of abnormal bone mass in women at this stage of life in China. Methods From October 2022 to September 2023, perimenopausal and postmenopausal women aged ≥ 40 years admitted to five recruited hospitals in China were recruited by purposive sampling method.Information on five levels of the health ecology model, including personal traits, behavioral characteristics, interpersonal network, working and living conditions, and policy environment was collected through structured questionnaires, and the data were analyzed using a structural equation model. Results Among 531 participants, 248 subjects had normal bone mass, 230 had osteopenia and 53 had osteoporosis. The results of the structural equation model showed that personal traits had the strongest direct positive effect on bone mass abnormality (β = 0.417, P < 0.05); behavioural characteristics had a direct positive effect on bone mass abnormality (β = 0.253, P < 0.05); interpersonal network had a direct negative effect on bone mass abnormality (β=-0.268, P < 0.05) and an indirect effect through personal traits; living conditions have a direct negative effect on bone mass abnormalities (β=-0.248,P < 0.05), and indirect effect through behavioural traits and interpersonal network; medical insurance can have an indirect effect on bone mass abnormalities through living conditions and interpersonal network. Conclusion Currently, the prevalence of abnormal bone mass in perimenopausal and postmenopausal women is high in China. Combined with the health ecology model, we found that personal characteristics and unhealthy behavior characteristics are risk factors for abnormal bone mass, higher social support and living conditions are protective factors for abnormal bone mass, which could indirectly affect abnormal bone mass, and medical insurance can indirectly affect abnormal bone mass. Future policy recommendations for the prevention of abnormal bone mass can be based on the factors and pathways that affect abnormal bone mass in perimenopausal and postmenopausal women identified in this study, in order to reduce the incidence of abnormal bone mass and improve the quality of life of perimenopausal and postmenopausal women. Health Ecology Model Perimenopause and Postmenopausal Abnormal Bone Mass Influencing Factors Structural Equation Model Figures Figure 1 Figure 2 1. Introduction With the rapid growth of aging population worldwide, osteoporosis (OP) has become an important public issue facing the world.( 1 )Osteoporosis is a systemic metabolic bone disease caused by a variety of reasons, which is characterized by decreased bone mass, decreased bone density, and destruction of bone microstructure, resulting in increased bone fragility and prone to fracture.( 2 )Osteoporosis often occurs quietly, without obvious symptoms in the early stage. With the aggravation of the disease, patients will have severe pain in the lower back and limited activity. Short body length and hunchback are the other important hazards of osteoporosis after low back pain. When the spinal canal Narrows to a certain extent due to hunchback, the spinal cord or nerve root is compressed, there will be lower limb activity and sensory dysfunction, or even paralysis, which seriously affects the quality of life of patients.( 3 ) Fractures caused by osteoporosis pose a significant burden on China’s medical system, with an estimated 23.3 million osteoporotic fractures occurring in 2010 at a cost of US $ 945 million (only direct costs, including direct medical costs, direct non-medical costs).( 4 ) It was predicted that both the number of cases and their associated expenses will double by 2035.( 5 ) While the disease burden of osteoporosis is mounting, our comprehension of its prevalence and risk factors in China remains limited. Osteopenia is a bone state with decreased bone strength and abnormal bone mineral density that has not yet reached the definition of osteoporosis.( 6 ) We refer to osteoporosis and osteopenia together as abnormal bone mass. While osteopenia is the precursor of osteoporosis, with a hidden onset, once it develops into osteoporosis, it will not only increase the risk of fracture in patients, causing physical and psychological effects on patients, but also bring heavy burden to the family and society. Prevention is the key to the clinical management of osteoporosis. Therefore, it is of great significance to pay attention to perimenopausal and postmenopausal women with osteopenia and carry out early intervention for the prevention and treatment of osteoporosis. At present, most studies focus on osteoporosis population, and lack of attention is paid to osteopenia, osteopenia and osteoporosis were investigated simultaneously in our study. According to WHO STRAW + 10 staging, perimenopause is defined as the beginning of clinical, endocrine and biological signs of menopausal trend until 1 year after menopause. Women over 40 years of age who have not had menses for 12 months after the last menstrual period can be clinically diagnosed as menopause if pregnancy is excluded.( 7 ) Osteoporosis often occurs in women, and the incidence of osteoporosis in postmenopausal women will further increase. Postmenopausal osteoporosis caused by estrogen deficiency is the most common type of primary osteoporosis, which generally occurs within 5 to 10 years after menopause. Bone loss begins before menopause, and there are varying degrees of bone loss during the menopausal transition.( 8 , 9 ) Since bone loss begins before menopause, the perimenopausal period is also a critical period for women to prevent and treat osteoporosis and reduce the risk of fractures. Osteoporosis is four times more common in women than men.( 10 ) In a cross-sectional study involving 20,000 samples, the prevalence of osteoporosis among adults aged 40 and older in mainland China was 5% in males and 20.6% in females.( 11 ) A 10-year Chinese clinical study involving 75 321 Chinese adults from seven medical centers showed that the prevalence of osteoporosis of the spine or hip was 6.46% in men and 29.13% in women aged 50 years or older in China.( 12 ) The ecological theory first originated in biological sciences to elucidate the interrelationship between the organism and its environment, and the theory has been continuously improved and optimised to gradually form a detailed and complete model elaboration, that is, the health ecology model. In recent years, the health ecology model has been widely used in the field of medicine and health. Health ecology believes that human health is affected by a mixture of multiple factors.( 13 ) health ecological model (HEM) believes that the impact of the environment on individuals is multi-level and complex, that is, individual and population health is the result of interdependence, coupling or restriction of individual characteristics, environmental and social factors at multiple levels.( 14 ) HEM is a comprehensive framework that includes factors such as an individual's biological characteristics, lifestyle and behavioral habits, interpersonal relationships, Living and working conditions and policy environment (The health ecology model framework is shown in Fig. 1 ).Therefore, this model can be used to study and explain the occurrence and influencing factors of abnormal bone mass in perimenopausal and postmenopausal women to overcome the shortcomings of previous studies that only analyzed the influencing factors at a single level, and to provide a more systematic and comprehensive perspective to find the best way to prevent and control abnormal bone mass, so as to promote the health of perimenopausal and postmenopausal women. This study uses the health ecology model to explore the influencing factors of abnormal bone mass in perimenopausal and postmenopausal women from different levels, so as to provide a basis for the management and prevention of abnormal bone mass in Chinese women at this stage. 2. Materials and methods 2.1 Survey design and participants An institutional-based multi-center cross-sectional study was conducted among patients admitted at five recruited hospitals(Two of the five hospitals are located in the south-west region of China, while the remaining three are in the south, central and north-east regions, respectively) of China from October 2022 to September 2023. Purposive sampling method was used to select the survey subjects who met the inclusion and exclusion criteria. 2.2 Participants' inclusion and exclusion criteria. Inclusion criteria:( 1 )Perimenopausal and postmenopausal women aged ≥ 40 years. Exclusion criteria:( 1 )Patients with major organic diseases;( 2 )Patients who had received treatment for relevant osteoporosis;( 3 )Patients with previous mental illness or a history of mental illness. 2.3 Health Ecology Model (HEM) Based on the five dimensions of the Health Ecology Model (HEM), personal traits, behavior and lifestyle, interpersonal network, working and living conditions, and policy environment, this study selected indicators that may affect bone mass abnormalities in perimenopausal and postmenopausal women for analysis. These indicators included:( 1 ) personal characteristics: age, body mass index, menstrual status, disease history, family history, etc.( 2 )Behavior and lifestyle: psychology, physical activity, diet, calcium supplement, VD supplement, smoking and drinking history, outdoor activity habits, awareness of osteoporosis knowledge, MHT, etc.( 3 )Interpersonal network: social support, marital status, etc.( 4 )Working and living conditions: education level, occupation, monthly income, residence, etc.( 5 )Policy environment: medical insurance. 2.4 Measurement tools 2.4.1 Social demographic data questionnaire The general information of the women and the factors that may affect osteoporosis were collected by the researchers according to the situation. The data included name, age, height, weight, residence area, education, marital status, occupation, income, menstrual status, current diseases, history of non-traumatic fracture, family history of osteoporosis, family history of fragility fracture, parents' hump, and medical payment method of perimenopausal and postmenopausal women. 2.4.2 Anxiety Disorder Scale (GAD-7)( 15 ) Generalized Anxiety Disorder Scale-7 (GAD-7) was developed by Spitzer et al., in 2006, originally as the anxiety module of the Patient Health Questionnaire (PHQ), and has good reliability and validity. GAD-7 was a self-rating scale consisting of 7 items, which was used to evaluate the mental and emotional changes in the past 2 weeks, including nervousness and anxiety, uncontrollable worry, excessive worry, inability to relax, inability to sit, irritability, and foreboded feeling. The scale was rated on a 4-point scale, and each symptom item was scored on a 0–3 scale. The scale was based on the number of days of target symptoms in the last two weeks, and the score was 0 (not at all), 1 (some days), 2 (more than half of the days), and 3 (almost every day). The main statistical measure of this scale is the sum of item scores, with a total score ranging from 0 to 21, with higher scores indicating more severe anxiety symptoms :0–4 as normal, 5–9 as mild, 10–14 as moderate, and 15–21 as severe. The internal consistency of the GAD-7 was excellent (Cronbach α = 0.92), Test-retest reliability was also good (intraclass correlation = 0.83). 2.4.3 The Patient Health Questionnaire Depression Scale (PHQ-9)( 16 ) The Patient Health Questionnaire Depression Scale (PHQ-9) is the depression module of Patient Health Questionnaire (PHQ) developed by Spitzer et al., and PHQ-9 has good reliability and validity. PHQ-9 is a self-rating scale, which is mainly used for the screening of depression. It has 9 symptom items, which are evaluated respectively: loss of interest, low mood, sleep quality, fatigue, appetite, inferiority complex, difficulty in concentration, psychomotor retardation, and negative ideation. Each symptom item in the scale was scored on a 4-point scale from 0 to 3, which was evaluated by the number of days of symptoms in the last 2 weeks. The score was 0 (not at all), 1 (some days), 2 (more than half of the days), and 3 (almost every day). The main statistical measure of this scale is the sum of item scores, and the total score ranges from 0 to 27 to assess the severity of depressive symptoms. 0–4 points are normal, 5–9 points are mild, 10–14 points are moderate, 15–19 points are moderate to severe, and 20–27 points are severe. The internal reliability of the PHQ-9 was excellent(Cronbach α = 0.89), Test-retest reliability was also good (intraclass correlation = 0.84). 2.4.4 the International Physical Activity Questionnaire (IPAQ)( 17 ) Physical activity level was measured by the Chinese version of the International Physical Activity Questionnaire Short Questionnaire (IPAQ). The scale consists of a total of seven questions, with the first six assessing the individual's physical activity and the seventh assessing the individual's sedentary behavior. The questionnaire metabolic equivalent (MET) was 3.3 for walking, 4.0 for moderate-intensity activity, and 8.0 for vigorous-intensity activity. The official recommended method for measuring the weekly physical activity (MET-minutes/week) of the respondents was as follows: the corresponding MET assignment * weekly frequency (days/week) * daily time (minutes/day). The sum of three kinds of physical activity levels was the total physical activity level. It was measured to be reliable and valid in evaluating physical activity, with an internal correlation coefficients of 0.89.( 18 ) 2.4.5 Dietary nutritional status questionnaire On the basis of the Dietary Nutrition and Health Questionnaire prepared by the Nutrition Intervention Committee of the High Health Commission of China, the researchers revised the dietary nutrition questionnaire according to the purpose of this study, the actual situation of perimenopausal and postmenopausal women and the feasibility of the questionnaire. The patients were investigated by food frequency method and dietary habit questionnaire. To analyze the current status of dietary habits, dietary structure and nutritional status of perimenopausal and postmenopausal women, and to propose corresponding intervention strategies and programs for osteoporosis. The internal reliability of the self-administered Dietary Nutritional Status Questionnaire in this study was acceptable (Cronbach α = 0.771), and the KMO value of the test structural validity was 0.744, which gave the scale good reliability and validity. 2.4.6 Social Support Rating Scale( 19 ) Social Support Rating Scale developed by Chinese scholar Xiao Shuiyuan was used to evaluate the social support of perimenopausal and postmenopausal women. The scale was divided into three dimensions of subjective support, objective support and utilization of support, with a total of 10 items. Subjective support included questions 1, 3, 4 and 5, and the full score was 32. Objective support included questions 2, 6 and 7, with a full score of 22; The utilization of support included questions 8, 9, and 10 with a full score of 12. The total scale scores ranged from 12 to 66, with higher scores indicating higher levels of social support. The scoring method of this study was as follows: ≤22 was defined as low level, 23–44 as medium level, and 45–66 as high level. The Cronbach's α of each domain of the scale was 0.89–0.94, and the test-retest reliability of the total scale was 0.92. 2.4.7 Osteoporosis related knowledge awareness scale According to the relevant literature, 10 questions about osteoporosis related knowledge were designed. The full score was 10 points. If “yes” was selected, 1 point was recorded, and if “no” or “don't know” was selected, no point was recorded. The final score was used to evaluate the awareness of osteoporosis knowledge, with scores of 0–3 as low awareness rate, 4–7 as medium awareness rate, and 8–10 as high awareness rate. The internal consistency of the self-administered Knowledge of Knowledge Scale in this study was very good (Cronbach α = 0.900), and the test of structural validity had a KMO value of 0.907, which gave the scale great reliability and validity. 2.5 Bone mineral density Dual-energy X-ray BMD is currently the gold standard for BMD measurement.( 20 ) In this study, we used dual-energy X-ray absorptiometry (DXA) to measure Bone mineral density (BMD).Using the lowest T-score of either lumbar spine (L1-L4) or total hip, we defined osteoporosis and osteopenia according to the World Health Organization (WHO) criteria of T-score of > -1.0 as normal; -1.0 to -2.5 as osteopenia and < -2.5 as osteoporosis. 2.6 Data collection The questionnaire in this study was filled out by scanning the two-dimensional code of the mobile phone. Any questions were explained in detail before the investigation began. The researchers did not give any suggestive guidance during the filling process. Questionnaires were completed with the help of our investigators if patients encountered difficulties during the process. Clinical data were obtained from electronic medical records by two researchers. 2.7 Statistical analysis SPSS27.0 and AMOS21.0 was used for data processing and analysis in this study. Firstly, the sample data were analysed by descriptive statistics using SPSS27.0, count data were expressed as percentages or frequencies, while the measurements data were described by mean ± standard deviation (𝑥̅±s) and comparisons between two groups were made using the chi-square test. AMOS21.0 was used to establish the structural equation model and path model, The normed χ 2 (χ 2 /df), root mean square error of approximation (RMSEA), goodness-of‐fit index (GFI), normed fit index (NFI), and comparative fit index(CFI)were selected to evaluate the model fit degree. Their values should meet the following standards: χ 2 /df < 3, RMSEA 0.8 indicate that the model fit is acceptable and > 0.9 indicate excellent. The significance level of all indicators was set at P < 0.05. 3. Results 3.1Sample characteristics In this study, a total of 575 questionnaires were distributed. After excluding 44 invalid questionnaires, 531 questionnaires were eventually included in the data analysis. The age of the subjects ranged from 40 to 73 years, with a mean age of 51.73 ± 6.04 years. There were 248 subjects with normal bone mass, 230 with osteopenia and 53 with osteoporosis, The incidence of abnormal bone mass was 53.30%. Table 1 . Table 1 Descriptive Analysis Independent Variable Categorisation Normal bone mass(%) Abnormal bone mass(%) P 248(46.7) 283(53.3) Age(years) 49.75 ± 4.57 53.47 ± 6.62 ≤ 44 31(12.5) 19(6.7) < 0.001 45–49 97(39.1) 57(20.1) 50–54 94(37.9) 115(40.6) ≥ 55 26(10.5) 92(32.5) Current Address Urban 213(85.9) 251(88.7) 0.538 Suburban 12(4.8) 9(3.2) Rural 23(9.3) 23(8.1) Educational Level Undergraduate and above 46(18.5) 39(13.8) 0.228 Junior college 25(10.1) 33(11.7) High school and secondary school 36(14.5) 38(13.4) Junior high school 87(35.1) 90(31.8) Primary and below 54(21.8) 83(29.3) Income( $ ) More than 10,000 10(4.0) 8(2.8) 0.023 5001–10000 22(8.9) 22(7.8) 3000–5000 80(32.3) 62(21.9) Less than 3000 136(54.8) 191(67.5) Marital Status Married 224(90.3) 257(90.8) 0.847 Widowed/Divorced/Unmarried/Divorced 24(9.7) 26(9.2) Menstrual Situation Normal Menstruation 34(13.7) 17(6.0) < 0.001 Perimenopause 155(62.5) 93(32.9) Menopause 10 years 7(2.8) 52(18.6) BMI Thin 2(0.8) 12(4.2) 0.035 Normal 130(52.4) 162(57.2) Overweight 94(37.9) 88(31.1) Obesity 22(8.9) 21(7.4) MHT Yes 39(15.7) 38(13.4) 0.453 No 209(84.3) 245(86.6) Anxiety Normal 204(82.3) 233(82.3) 0.089 Mild 37(14.9) 32(11.3) Moderately Severe 7(2.8) 18(6.4) Depression Normal 208(83.9) 238(84.1) 0.264 Mild 35(14.1) 33(11.7) Moderately Severe 5(2.0) 12(4.2) Calcium Supplementation Everyday 40(16.1) 38(13.4) 0.543 Often 28(11.3) 41(14.5) Occasionally 69(27.8) 85(30.0) Never 111(44.8) 119(42.0) VD Supplementation Everyday 27(10.9) 22(7.8) 0.156 Often 16(6.5) 19(6.7) Occasionally 34(13.7) 58(20.5) Never 171(69.0) 184(65.0) Catering Excellent 8(3.2) 6(2.1) 0.064 Good 136(54.8) 130(45.9) Fail 104(41.9) 147(51.9) Sunshine > 30min 49(19.8) 65(23.0) 0.037 15-30min 88(35.5) 68(24.0) < 15min 64(25.8) 90(31.8) Sunburn Protection Never 64(25.8) 94(33.2) 0.055 Sometimes 124(50.0) 113(39.9) Always 60(24.2) 76(26.9) OP Knowledge High 82(33.1) 78(27.6) 0.280 Medium 92(37.1) 105(37.1) Medium 74(29.8) 100(35.3) Social support Higher level 128(51.6) 63(22.3) < 0.001 Medium level 120(48.4) 213(75.3) Low level 0(0) 7(2.5) Physical Activity High 147(59.3) 145(51.2) 0.106 Medium 89(35.9) 115(40.6) Medium 12(4.8) 23(8.1) 3.2 Analysis of structural equation model 3.2.1 Model construction and fitting Based on the health ecology theoretical model and domestic and international literature research, according to the content of the questionnaire and the hypotheses of this study, this study takes personal traits, behavioural characteristics, living conditions, interpersonal networks, and medical insurance as latent variables, and abnormal bone mass as the dependent variable, and constructs the path relationship between observational variable and the latent variables. Maximum likelihood estimation was used to estimate the model, and in this study, a validation factor analysis was conducted on personal traits, behavioural traits, living conditions, interpersonal networks, and their respective observables, to exclude variables with small factor loadings and to increase model fitness. Estimation of the initial model showed that the coefficients of the paths of health insurance→ bone mass abnormality, behavioural traits→personal traits, and living conditions→personal traits did not reach the level of significance (P > 0.05),so these paths were removed step by step and re-fitted.The model was iteratively revised and fitted under the indication of the modification index (MI), and the final model met the fit criteria. The validity of the revised model was good and the indicators meet the corresponding reference standards, the chi-square degrees of freedom ratio (χ 2 /df) of 2.137 meets the criterion of 0.90 criterion, and the value of RMR was 0.095 ,which meets the criterion of < 0.1, and the value of RMSEA is 0.046, which meets the criterion of < 0.05. Overall, the adjusted model fitted the data well, as shown in Table 2 . Table 2 Results of model fit indicators fit indicators χ 2 df χ 2 /df GFI AGFI RMSEA RMR CFI TLI IFI Recommended standards - - 0.9 > 0.9 < 0.05 0.9 > 0.9 > 0.9 values 224.399 105 2.137 0.952 0.930 0.046 0.095 0.939 0.920 0.940 3.2.2 Path analysis The effects of each factor on bone mass abnormality were, in descending order, personal traits, interpersonal network, behavioural characteristics, and living conditions, as shown in Table 3 . Personal traits had the strongest direct positive effect on bone mass abnormality (β = 0.417, P < 0.05); behavioural characteristics had a direct positive effect on bone mass abnormality (β = 0.253, P < 0.05); interpersonal network had a direct negative effect on bone mass abnormality (β=-0.268, P < 0.05) and an indirect effect through personal traits; living conditions have a direct negative effect on bone mass abnormalities (β=-0.248,P < 0.05), and indirect effect through behavioural traits and interpersonal network; medical insurance can have an indirect effect on bone mass abnormalities through living conditions and interpersonal network, as shown in Fig. 2 . Table 3 Structural equation model path coefficients Path Direct effects Indirect effects Total effects Personal traits→ Abnormal bone mass 0.417 - 0.417 Behavior characteristics→Abnormal bone mass 0.253 - 0.253 Social network→ Abnormal bone mass -0.268 -0.146 -0.414 Living conditions→Abnormal bone mass -0.248 0.363 0.115 Medical insurance→Abnormal bone mass - 0.062 0.062 4. DISCUSSION The present study showed that the prevalence of abnormal bone mass in peri- and postmenopausal women was 53.30%. The prevalence of bone mass abnormalities varied considerably among different studies, and the results of the present study were lower than the findings of Feng J (58.62%)( 21 ), CHEN P H (769.59%)( 22 ), and Gu Q P (69.72%)( 23 ), but higher than those of Luo W (23.69%)( 24 ) and TIAN L (36.74%)( 25 ). This may be due to the different age ranges of the subjects included in the study and the different weight of the population in each age group. In addition, factors such as the area of investigation, dietary habits, and hours of sunlight may also have a greater impact on the results of the prevalence of abnormal bone mass. Perimenopausal and postmenopausal women have decreased ovarian function, disorders of the vegetative nervous system, dysregulation of the bone resorption-bone remodelling balance, and high incidence of osteoporosis. The study of high risk factors for osteoporosis in this population has important clinical significance in the prevention and treatment of osteoporosis. Among the five layers of influencing factors in the health ecology model, the individual trait layer belongs to the downstream factors, which are determined by people's own genetic and physiological differences,this layer directly affect people's health. The behavioral characteristics layer belong to the middle factors, which act on people with time and individual growth, this layer indirectly affect people's health. Interpersonal relationship layer 、the layers of living and working conditions and policy environment belong to the upstream factors, which represent the macro-social economic and material environment and are the fundamental environmental factors determining people's health, known as "the reasons behind the reasons", these layers affect the middle factors and indirectly affect people's health. Most of the health management of chronic diseases in China is to educate individuals about their bad behaviours and lifestyles, while ignoring the influence of the social environment, national policies and other factors on the health management of chronic diseases. At present, many scholars have realized that the relationship between human health and its social environment is closely linked, if we ignore the role of the environment in shaping the behaviour of individuals, and only rely on health education to change the individual's bad behaviour and lifestyle, the effect is very small. ( 14 )Health ecology emphasises the multi-level influence of the social environment on individuals and the complexity of the influencing factors, which is conducive to analysing the prevalence of bone mass abnormalities in peri-menopausal and post-menopausal women in China, and to exploring the influencing factors and the interactions between the influencing factors in a hierarchical manner, and the following will discuss the five levels of health ecology and the roles between the levels. 4.1 Personal characteristics Personal characteristics lie at the core level of the health ecology model.The results of this study showed that the path coefficient from personal traits to abnormal bone mass was 0.440, which was significant at the 5% level, suggesting a higher prevalence of bone mass abnormality in perimenopausal and postmenopausal women with older age and years of menopause and a history of disease. Oestrogen acts through oestrogen receptors in osteoclasts, osteoblasts and bone cells, and when oestrogen is deficient it leads to abnormal bone metabolism and an increased risk of osteoporosis.( 26 ) As women age, oestrogen levels decline after menopause, and the synthesis of active vitamin D in the kidneys and liver decreases accordingly, leading to a decrease in intestinal absorption of calcium and the fastest rate of bone loss after the age of 65. ( 27 , 28 ) Our results found that perimenopausal and postmenopausal women with a history of hypertension and diabetes are more likely to have abnormal bone mass. Some studies have found that high blood pressure reduces bone density in certain parts of the body, ( 29 ) that people with high blood pressure have a higher prevalence of osteoporosis,( 30 )studies have also found an association between high blood pressure and abnormal calcium metabolism, and a link between some antihypertensive medications and fractures.( 31 ) In patients with T2DM, sustained elevated levels of pro-inflammatory cytokines such as TNF-α, IL-1β, IL-6 and IL-18 enhance lipid peroxidation and dyslipidaemia, leading to increased osteoclastogenesis. Increases in advanced glycosylation end products (AGE), reactive oxygen species (ROS) and pro-inflammatory cytokines accelerate bone loss. Prolonged inflammation also stimulates the expression of pro-apoptotic genes such as bcl-2-like protein (Bax), which reduces the expression of genes that stimulate osteoclast formation, leading to decreased bone formation. Oxidative stress reduces differentiation to osteoblasts and can directly degrade bone.( 32 ) Some studies have shown that common medication side effects of diabetes can lead to abnormal bone metabolism, and that metformin, sulfonylureas, and insulin can all increase the risk of fracture in diabetic patients.( 33 ) Changes in bone metabolism in diabetic patients are affected by a variety of factors, and different factors have different effects on bone mass, the specific influencing factors and related mechanisms still need to be further studied. 4.2 Behavioural traits Behavioural traits are located outside the core layer of the model.In our study, unhealthy behavioural traits positively contribute to bone mass abnormalities in peri- and postmenopausal women. Calcium and vitamin D supplementation are effective in preventing bone mass abnormalities. Calcium is an important and indispensable element in the human body and plays a major role in the regulation of various cellular functions. Calcium helps bones to become strong, it not only replenishes skeletal muscle strength, but also improves bone density. The clinician’s guide to prevention and treatment of osteoporosis published by BHOF recommend a diet with adequate total calcium intake (1000 mg/day for men aged 50–70 years; 1200 mg/day for women ≥ 51 years and men ≥ 71 years), incorporating calcium supplements if intake is insufficient. Vitamin D can promote the intestinal absorption of calcium, to maintain normal bone mass. Maintain serum vitamin D sufficiency (≥ 30 ng/mL but below ≤ 50 ng/mL). Prescribe supplemental vitamin D (800–1000 units/day) as needed for individuals aged 50 years and older to achieve a sufficient vitamin D level. Higher doses may be necessary in some adults, especially those with malabsorption. ( 34 ) In this study, irrational dietary habits have a positive contribution to bone mass abnormalities and increase the incidence of bone mass abnormalities. Numerous guidelines refer to the need to maintain a healthy lifestyle in order to prevent osteoporosis. A balanced diet means ensuring a varied and low-salt diet, and consuming foods that are high in calcium, vitamin D or protein. ( 35 , 36 ) Elderly women and women with longer menopausal years should be instructed to consume calcium-rich foods, such as fish, milk and dairy products, etc. In addition, more vitamins should be added to supplement the nutrition to maintain bone density, ensure the balance of bone metabolism and prevent osteoporosis. Related studies have shown that protein intake affects the production of insulin-like growth factor-1, which promotes bone growth. The 2020 Expert consensus on the nutrition and exercise management for patients with primary osteoporosis mentions the need to ensure cereal and potato intake and that dark green vegetables make up more than 1/2 of the vegetables, which favours vitamin K supplementation.( 36 ) Vegetables and fruits simultaneously raise pH, inhibit osteoclast activity, and promote new bone formation by osteoblasts, while vegetables are rich in substances such as vitamins and phytoestrogens, which promote bone resorption and bone matrix formation.( 37 ) Also the results of this study show that inadequate knowledge about osteoporosis is also a major factor in the occurrence of abnormal bone mass in perimenopausal and menopausal women. Yi rong showed that remote monitoring and education for primary osteoporosis patients can effectively improve patients' knowledge of the disease and improve bone metabolism and bone mineral density.( 38 ) Gu Youhua pointed out that health education for postmenopausal osteoporosis patients can effectively improve the knowledge of the disease, strengthen patients' self-efficacy, and improve the quality of life.( 39 ) Scientific and effective health education on osteoporosis is conducive to the establishment of correct health concepts for menopausal women, which is conducive to the improvement of health behaviours and has a positive significance on the improvement of women's quality of life. This also suggests that medical personnel or health educators need to continuously carry out various forms of OP prevention knowledge dissemination activities, including expert lectures, popularisation competitions, distribution of paper promotional treatments, and video education in the community, schools, television, micro-video, health marketing accounts, and the hospital public, among other media. Only through more extensive and sustained knowledge dissemination activities can we continue to promote the development of healthy behaviours among perimenopausal and postmenopausal women. Menopausal hormone therapy is a protective factor against abnormal bone mass in perimenopausal and menopausal women in our study. Menopausal hormone therapy is a primary preventive measure for perimenopausal and postmenopausal osteoporosis, and the use of menopausal hormone therapy is effective in preventing bone loss in perimenopausal and early menopausal women and helps to increase or maintain bone density.( 40 ) The American Endocrine Society released the ENDO Clinical Practice Guidelines for the Pharmacological Treatment of OP in Postmenopausal Women in 2019, which suggests that standardised menopausal hormone therapy may be administered to women younger than 60 years of age, with a duration of menopause of less than 10 years, and with menopause-related symptoms, following a detailed and adequate assessment by a clinician and the exclusion of hormone therapy contraindications.( 41 ) 4.3 Interpersonal networks Interpersonal network is located in the third layer of the model. In this study, the social support degree was used to reflect the interpersonal network, and it was found that the lower the social support degree the more likely to have abnormal bone mass. Social support is an important social factor, which refers to the spiritual and material help and support from individuals and organisations such as family, relatives, friends, colleagues and party groups, as well as the degree to which an individual makes use of social support. A large number of studies have confirmed the health-promoting effects of social support.( 42 ) This may be due to the fact that marital partners, family members and children of people with high social support will give each other more mental comfort and related life care, thus forming good life habits to reduce the prevalence of bone mass abnormality.( 43 ) At the same time, social participation prevents the development of chronic diseases such as osteoporosis, improves muscle mass and strengthens bone function.( 44 ) As the physical quality and energy of the postmenopausal body decreases, the opportunities for social activities become fewer and fewer, but the basic needs for social interaction, respect and self-realisation still exist. Therefore, social participation must play a positive social support role through the strength of the family and society as a whole, so as to make postmenopausal women feel the concern and respect of the family and society from various aspects, and to help postmenopausal women satisfy the basic needs for social self-realisation. In addition, our study found that upstream factors in health ecology modelling can influence downstream factors in the model, indirectly impacting on health. Interpersonal networks are strongly associated with personal traits (P < 0.05), can indirectly through personal traits affect bone abnormalities. Interpersonal networks were found to be beneficial to health by maintaining a favourable emotional experience in individuals( 45 ). Interpersonal network as a mediator variable plays an indirect role in the pathway of personal traits affecting bone density, the lower the social support, the more likely to suffer from hypertension, diabetes and other chronic diseases, the reason can be hypothesised that the participation in social activities can increase the sense of belonging of the individual, easy to resolve the bad emotions, maintain physical and mental happiness, and thus reduce the likelihood of the occurrence of chronic diseases. Family involvement and support should be encouraged, counselling and social services should be valued, and avenues for social functioning should be provided wherever possible in order to reduce the prevalence of chronic diseases. 4.4 Living conditions Living conditions are located in the fourth level of the model. Living in the city, having a high income, and having a high level of education are more likely to have abnormal bone mass in our study. Living in the city is more likely to suffer from osteoporosis, which is consistent with Zhang Zhenzhen's findings, ( 46 ) while some reports indicate that the prevalence is higher in rural areas than in urban areas, ( 47 ) and in-depth analyses suggest that the place of residence may only be superficial, and that the real influencing factors are the physical activity and the economic level. Urban residents have a higher standard of living, higher family income than rural areas, relatively more knowledge, long years of education, so the content of osteoporosis health education can be accepted at an early stage. And the intake of high nutrition is relatively balanced, and the purchasing power is strong, which can meet the needs of the organism. However, the urban population has more brain workers, most of them have less activity, short exposure to sunlight, and have bad habits such as drinking coffee and strong tea. In rural areas, where there is more farm work, a certain amount of load training may increase bone mass or slow down bone mass loss in menopausal women, which may make up for the shortcomings of an unbalanced diet. The higher incomes and higher levels of education may also be associated with the fact that people with higher incomes and higher levels of education are more likely to be involved in mental labour and less in physical labour. Our analyses showed that living conditions were strongly associated with interpersonal networks (P < 0.05) and could indirectly influence bone mass abnormalities through interpersonal networks. Our study shows that the higher the cultural level and the higher the income, the higher the level of social support. Studies by different scholars have shown that individuals from different cultural backgrounds have greater differences in their ability to perceive social support, suggesting that literacy is also an important influence on social support. ( 48 , 49 )This is because people with a certain level of cultural quality can get more support and respect in life and work, their own ability to seek and make use of social resources is higher, it is easier for them to adapt to the society, get a sense of satisfaction, and realise their own self-worth, and the people who have a good level of economic participation in more social activities and spend more time interacting with people, thus obtaining more objective support and making higher use of support. A high level of education, high income and living in the city are beneficial for the development of various healthy lifestyles, and at the same time help to increase the level of social support, which in turn creates a protective effect against abnormal bone mass. In addition, the results of our analyses show that the upstream factors of a health ecology model can also influence the midstream factors of the model, indirectly impacting on health. living conditions were closely related to behavioural characteristics(P < 0.05), could indirectly through behavioural characteristics affect bone abnormalities. Knowledge of osteoporosis was affected by factors such as literacy, income and place of residence, and was relatively lower among those with lower literacy, lower income and those in rural areas. ( 50 ) It may be due to the fact that higher education level usually predicts better job, higher income, better living conditions and socio-economic status, which leads to more access to resources and greater ability to acquire bone health care knowledge. At the same time, more educated people attach more importance to healthy lifestyles and are more willing to accept osteoporosis preventive healthcare measures, such as MHT. Therefore, in the implementation of health management and bone health care interventions for patients with abnormal bone mass, high attention should be paid to the literacy level of patients, and appropriate bone health popularisation and education should be provided to patients with relatively low literacy level, in order to reduce the inequality of health services, improve the bone health care ability of patients in various aspects, and maximise the quality of life related to bone health of patients. 4.5 Medical insurance Policy environment is at the outermost level of the health ecology model. In our results, although the effect of medical insurance on abnormal bone mass in perimenopausal and postmenopausal women was not statistically significant, medical insurance was closely associated with interpersonal networks and living conditions (P < 0.05), which implies that the role of perfecting social security in the prevention of abnormal bone mass in perimenopausal and postmenopausal women should not be overlooked as well. Social security belongs to the category of national policy and represents the policy environment dimension in the theoretical model of health ecology. The behaviour of any organ, department, enterprise or institution and individual is constrained by the macro-policy environment, with the national system directly influencing sectoral decision-making and the will of the people. Government-led scientific planning of community services for the elderly at the policy level and calls for healthy living by the nation can encourage communities to provide rationalised services for the elderly, raise residents' health awareness and cultivate healthy living habits, thereby reducing the risk of bone mass abnormalities. In summary, this study analysed the factors influencing abnormal bone mass in perimenopausal and postmenopausal women using a health ecology model, from distal to proximal, integrating multiple dimensions and factors, and concluded that the factors influencing abnormal bone mass in perimenopausal and postmenopausal women are complex. In addition to the direct effects that can occur between levels of the model, there can also be indirect effects on bone health by influencing other levels. Interpersonal networks can influence bone mass abnormalities directly or indirectly by influencing personal traits. Living conditions can directly influence bone mass abnormality and indirectly influence bone mass abnormality by influencing behavioural characteristics and interpersonal networks. Personal traits and behavioural characteristics directly influence bone mass abnormalities. Health insurance does not have a direct effect on bone mass abnormalities, but it can have an indirect effect on bone mass abnormalities by influencing interpersonal networks and living conditions. Therefore, in combination with the theory of health ecology, attention should be paid to the upstream influencing factors, and the government should actively play a leading role in improving social security, encouraging and guiding the relevant units, communities, families, and individual residents to take action together, reinforcing the synergistic effect of the relevant main bodies, adopting effective interventions on the influencing factors of bone mass abnormalities, forming a favourable situation in which there is extensive participation in the society and autonomous and conscientious prevention on the part of individuals, and actively exerting the positive effect of the middle-stream factors to continually improve the quality of life of periand postmenopausal and postmenopausal women in China by improving the level of social support, strengthening health education, and maintaining the individual's state of health. Specific policy recommendations for the prevention of bone mass abnormalities can be based on the above factors and pathways affecting bone mass abnormalities in perimenopausal and postmenopausal women. At the same time, the relevant authorities are asked to focus on the importance of micro-factors such as improving the health insurance system, organising regular social activities, adopting good dietary habits, and preventing high blood pressure and diabetes in the prevention of bone mass abnormalities in perimenopausal and postmenopausal women. 5. LIMITATIONS We should be cautious when generalizing the results of this study due to the following limitations. First, this study used a cross-sectional design, so the causality of each variable in the SEM cannot be determined. Future longitudinal follow-up investigations are needed to further verify the causal mechanism and to expand this study. Second, the lack of healthcare institutions in North, East and Northwest China among the multicentre units recruited for this study may have led to a lack of representativeness of the prevalence of abnormal bone mass in this study, and larger multicentre studies are needed in the future. 6. CONCLUSIONS The prevalence of abnormal bone mass is high in perimenopausal and postmenopausal women in China. In this study, personal characteristics and unhealthy behavior characteristics are risk factors for abnormal bone mass. Higher social support and living conditions are protective factors for abnormal bone mass, and can indirectly affect bone mass abnormalities. Medical insurance can indirectly affect abnormal bone mass. Future policy recommendations for the prevention of abnormal bone mass can be made based on the factors and pathways identified in this study that affect abnormal bone mass in perimenopausal and postmenopausal women. The government can establish a three-level prevention and control system for osteoporosis in the elderly, adopt the strategy of prevention first, combination of prevention and treatment, hierarchical diagnosis and treatment, and whole-process management to improve the whole society's awareness of bone health knowledge and reduce the harm of osteoporosis and its fractures, so as to realize the "Healthy China" strategy. Declarations Acknowledgments We thanked all women who took the time to participate in this study and all the staff who assisted in data collection. Authors' contributions HYH participated in design of the study, field investigation, data collection, and drafting of the manuscript. JLY participated in field investigation and data collection. QW, YYZ, MW, ZFC, NL, MHR, HS, LT and JD participated in field investigation and data collection. YML participated in the design of the study and field investigation and data collection. DYL participated data analysis. YF and MFZ participated in the design of the study. XL and LLY participated in the design of the study, field investigation, data collection, and review of the manuscript. All authors saw and approved the final version. Funding This work was supported by National Natural Science Foundation of China (No. 72174033), the Science and Technology Research Program of Chongqing Municipal Education Commission (No. KJZD-K202100403), and Program for Youth Innovation in Future Medicine, Chongqing Medical University (No. W0013) Data availability The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Ethics statement The studies involving human participants were reviewed and approved by the Institutional Review Board of the Third Affiliated Hospital of Chongqing Medical University (202281). We obtained informed consent from all participants. Competing interests The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Consent for publication References Rachner TD, Khosla S, Hofbauer LC. Osteoporosis: now and the future. Lancet (London, England). 2011;377(9773):1276-87. Compston JE, McClung MR, Leslie WD. Osteoporosis. Lancet (London, England). 2019;393(10169):364-76. Editorial Board of Osteoporosis Prevention and Treatment (China White Paper) CHPF. White paper on osteoporosis. Chinese Journal of Health Management. 2009;3(3):148-54. Si L, Winzenberg TM, Jiang Q, Palmer AJ. Screening for and treatment of osteoporosis: construction and validation of a state-transition microsimulation cost-effectiveness model. Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA. 2015;26(5):1477-89. Si L, Winzenberg TM, Jiang Q, Chen M, Palmer AJ. Projection of osteoporosis-related fractures and costs in China: 2010-2050. Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA. 2015;26(7):1929-37. Martinez-Lopez A, Blasco-Morente G, Giron-Prieto MS, Arrabal-Polo MA, Luque-Valenzuela M, Luna-Del Castillo JD, et al. Linking of psoriasis with osteopenia and osteoporosis: A cross-sectional study. Indian journal of dermatology, venereology and leprology. 2019;85(2):153-9. Harlow SD, Gass M, Hall JE, Lobo R, Maki P, Rebar RW, et al. Executive summary of the Stages of Reproductive Aging Workshop + 10: addressing the unfinished agenda of staging reproductive aging. The Journal of clinical endocrinology and metabolism. 2012;97(4):1159-68. Sowers MR, Zheng H, Jannausch ML, McConnell D, Nan B, Harlow S, et al. Amount of bone loss in relation to time around the final menstrual period and follicle-stimulating hormone staging of the transmenopause. The Journal of clinical endocrinology and metabolism. 2010;95(5):2155-62. Seifert-Klauss V, Prior JC. Progesterone and bone: actions promoting bone health in women. Journal of osteoporosis. 2010;2010:845180. Bonjour JP, Chevalley T, Ferrari S, Rizzoli R. The importance and relevance of peak bone mass in the prevalence of osteoporosis. Salud publica de Mexico. 2009;51 Suppl 1:S5-17. Wang L, Yu W, Yin X, Cui L, Tang S, Jiang N, et al. Prevalence of Osteoporosis and Fracture in China: The China Osteoporosis Prevalence Study. JAMA network open. 2021;4(8):e2121106. Zeng Q, Li N, Wang Q, Feng J, Sun D, Zhang Q, et al. The Prevalence of Osteoporosis in China, a Nationwide, Multicenter DXA Survey. Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research. 2019;34(10):1789-97. Reifsnider E, Gallagher M, Forgione B. Using ecological models in research on health disparities. Journal of professional nursing : official journal of the American Association of Colleges of Nursing. 2005;21(4):216-22. Buse CG, Oestreicher JS, Ellis NR, Patrick R, Brisbois B, Jenkins AP, et al. Public health guide to field developments linking ecosystems, environments and health in the Anthropocene. Journal of epidemiology and community health. 2018;72(5):420-5. Spitzer RL, Kroenke K, Williams JB, Löwe B. A brief measure for assessing generalized anxiety disorder: the GAD-7. Archives of internal medicine. 2006;166(10):1092-7. Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. Journal of general internal medicine. 2001;16(9):606-13. Hagströmer M, Oja P, Sjöström M. The International Physical Activity Questionnaire (IPAQ): a study of concurrent and construct validity. Public health nutrition. 2006;9(6):755-62. Deng HB, Macfarlane DJ, Thomas GN, Lao XQ, Jiang CQ, Cheng KK, et al. Reliability and validity of the IPAQ-Chinese: the Guangzhou Biobank Cohort study. Medicine and science in sports and exercise. 2008;40(2):303-7. XIAO s. Theoretical basis and research applications of the Social Support Rating Scale (SSRS). Journal of Clinical Psychiatry. 1994(02):98-100. Kanis JA, McCloskey EV, Johansson H, Oden A, Melton LJ, 3rd, Khaltaev N. A reference standard for the description of osteoporosis. Bone. 2008;42(3):467-75. FENG J, WANG X, ZHANG T, CEHNG L, WANG Q, CEHNG X. Analysis of prevalence and influencing factors of abnormal bone density rate in Weifang. Chinese Journal of Osteoporosis. 2023;29(10):1484-9. Chen PH, Lin MS, Huang TJ, Chen MY. Prevalence of and factors associated with adopting bone health promoting behaviours among people with osteoporosis in Taiwan: a cross-sectional study. BMJ open. 2017;7(9):e015980. GU Q, WU L, SUN W. Study on the prevalence rate and risk factors of osteoporosis in postmenopausal women. Maternal and Child Health Care of China. 2020;35(22):4158-62. LUO W, LIU Z, LIU H, WANG J. Investigation of bone mineral density and prevalence of bone mass abnormality in 3 859 healthy subjects in Bejjin. Chinese Journal of Osteoporosis. 2020;26(05):719-22. Tian L, Yang R, Wei L, Liu J, Yang Y, Shao F, et al. Prevalence of osteoporosis and related lifestyle and metabolic factors of postmenopausal women and elderly men: A cross-sectional study in Gansu province, Northwestern of China. Medicine. 2017;96(43):e8294. Anagnostis P, Bosdou JK, Vaitsi K, Goulis DG, Lambrinoudaki I. Estrogen and bones after menopause: a reappraisal of data and future perspectives. Hormones (Athens, Greece). 2021;20(1):13-21. YU L, BAI Y, LUO X, DENG R, YANG J, LI Y, et al. Ｒisk factors and preventive /therapeutic status of osteoporotic fracture in postmenopausal women in two communities of Beijing. Chinese Journal of Osteoporosis and Bone Mineral Research. 2020;13(02):110-5. Veiga Silva AC, da Rosa MI, Fernandes B, Lumertz S, Diniz RM, dos Reis Damiani ME. [Factors associated with osteopenia and osteoporosis in women undergoing bone mineral density test]. Revista brasileira de reumatologia. 2015;55(3):223-8. Yang S, Nguyen ND, Center JR, Eisman JA, Nguyen TV. Association between hypertension and fragility fracture: a longitudinal study. Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA. 2014;25(1):97-103. Wu HL, Yang J, Wei YC, Wang JY, Jia YY, Li L, et al. Analysis of the prevalence, risk factors, and clinical characteristics of osteoporosis in patients with essential hypertension. BMC endocrine disorders. 2022;22(1):165. GUO L, WANG Y, HOU X, TIAN F. Relationship between cardiovascular and cerebrovascular disease and osteoporotic fracture. Chinese Journal of Osteoporosis and Bone Mineral Research. 2022;15(06):683-90. Rathinavelu S, Guidry-Elizondo C, Banu J. Molecular Modulation of Osteoblasts and Osteoclasts in Type 2 Diabetes. Journal of diabetes research. 2018;2018:6354787. Ha J, Lim Y, Kim MK, Kwon HS, Song KH, Ko SH, et al. Comparison of the Effects of Various Antidiabetic Medication on Bone Mineral Density in Patients with Type 2 Diabetes Mellitus. Endocrinology and metabolism (Seoul, Korea). 2021;36(4):895-903. LeBoff MS, Greenspan SL, Insogna KL, Lewiecki EM, Saag KG, Singer AJ, et al. The clinician's guide to prevention and treatment of osteoporosis. Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA. 2022;33(10):2049-102. Compston J, Cooper A, Cooper C, Gittoes N, Gregson C, Harvey N, et al. UK clinical guideline for the prevention and treatment of osteoporosis. Archives of osteoporosis. 2017;12(1):43. Nutrition and Bone Health Committee CNS, Chinese Society of Osteoporosis Bone Mineral Research CMA. Expert consensus on the nutrition and exercise management for patients with primary osteoporosis. Chinese Journal of Osteoporosis and Bone Mineral Research. 2020;13(05):396-410. ZHANG C, ZHAO Y. Influencing factors of knowledge，attitude and practice of prevention of osteoporosis in perimenopausal women. Shanghai Nursing. 2018;18(09):27-31. YI R, CHEN H. Effects of remote health education and nutritional guidance on bone metabolism in patients with primary osteoporotic fractures. The Medical Forum. 2022;26(33):85-7+109. GU Y, ZHOU H. Effect of health education based on management by objectives on the patients' awareness of postmenopausal osteoporosis disease and quality of life. Medical Higher Vocational Education and Modern Nursing. 2019;2(06):417-20. Expert consensus on prevention and treatment of osteoporosis in perimenopausal and postmenopausal women. Chinese Journal for Clinicians. 2020;48(08):903-8. Eastell R, Rosen CJ, Black DM, Cheung AM, Murad MH, Shoback D. Pharmacological Management of Osteoporosis in Postmenopausal Women: An Endocrine Society* Clinical Practice Guideline. The Journal of clinical endocrinology and metabolism. 2019;104(5):1595-622. Kobayashi T, Kawachi I, Iwase T, Suzuki E, Takao S. Individual-level social capital and self-rated health in Japan: an application of the Resource Generator. Social science & medicine (1982). 2013;85:32-7. MAO Y, ZHU B, LIU J, WANG X. Empirical evidence on the factors influencing chronic diseases in the middle-aged and elderly population from the perspective of health ecology. Journal of Xi'an Jiaotong University(Social Sciences). 2015;35(05):15-24. MA L, FENG M, LI G, YANG W. The association between quality of life and social support in the elderly patients with osteoporosis. Practical Geriatrics. 2013;27(08):634-6. Çalişkan Pala S, Ünsal A, Arslantaş D, Öcal EE, Dağtekin G. Evaluation of depression, social support and quality of life in perimenopausal and postmenopausal women in semi-rural Turkey. Psychogeriatrics : the official journal of the Japanese Psychogeriatric Society. 2022;22(5):679-87. ZHANG Z, LI L, SHEN Y. A Survey on Influence Factors of Osteoporosis in Perimenopausal Women from Northern Anhui and Health Education. Chinese Journal of General Practice. 2013;11(11):1745-6. Kang SW, Yang JH, Shin WC, Kim YJ, Choi MH. Influence of Residence Area and Basic Livelihood Conditions on the Prevalence and Diagnosis Experience of Osteoporosis in Postmenopausal Women Aged over 50 Years: Evaluation Using Korea National Health and Nutrition Examination Survey Data. International journal of environmental research and public health. 2021;18(18). QI Y, ZHANG X, SHI X, HU Y, GAO H, LI W. Social support status and influencing factors of the elderly in urban community. Chinese General Practice. 2016;19(25):3099-102. Hurdle DE. Native Hawaiian traditional healing: culturally based interventions for social work practice. Social work. 2002;47(2):183-92. Kadam N, Chiplonkar S, Khadilkar A, Khadilkar V. Low knowledge of osteoporosis and its risk factors in urban Indian adults from Pune city, India. Public health nutrition. 2019;22(7):1292-9. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3848504","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":266284165,"identity":"1e9b6f38-b5cb-47e7-a605-89ccff2cd1d7","order_by":0,"name":"Haiyang He","email":"","orcid":"","institution":"Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Haiyang","middleName":"","lastName":"He","suffix":""},{"id":266284166,"identity":"8504c3ce-e577-4ccb-ad4e-43773dbf60ee","order_by":1,"name":"Jialing Yang","email":"","orcid":"","institution":"Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jialing","middleName":"","lastName":"Yang","suffix":""},{"id":266284167,"identity":"6f649d09-9a6b-4a8e-9ca1-f8ab8810bcaa","order_by":2,"name":"Qian Wen","email":"","orcid":"","institution":"Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Qian","middleName":"","lastName":"Wen","suffix":""},{"id":266284168,"identity":"cdb97c74-41dd-4842-b4cf-6607b225eb92","order_by":3,"name":"Yaoyao Zhou","email":"","orcid":"","institution":"Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yaoyao","middleName":"","lastName":"Zhou","suffix":""},{"id":266284169,"identity":"868595c1-b3d8-471c-9f1e-a7a13e227333","order_by":4,"name":"Meng Wang","email":"","orcid":"","institution":"Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Meng","middleName":"","lastName":"Wang","suffix":""},{"id":266284170,"identity":"ef5058d8-cc76-4ea6-b5b2-f748eb73cd4f","order_by":5,"name":"Zhifeng Cheng","email":"","orcid":"","institution":"The fourth Affiliated Hospital of Harbin Medical University","correspondingAuthor":false,"prefix":"","firstName":"Zhifeng","middleName":"","lastName":"Cheng","suffix":""},{"id":266284171,"identity":"ed25bc7d-b67b-48fb-b38a-024aa45f6104","order_by":6,"name":"Ning Li","email":"","orcid":"","institution":"Shapingba Hospital Affiliated to Chongqing University","correspondingAuthor":false,"prefix":"","firstName":"Ning","middleName":"","lastName":"Li","suffix":""},{"id":266284172,"identity":"d2443d70-066c-4f53-a853-da31d3e6cea0","order_by":7,"name":"Yangmei Li","email":"","orcid":"","institution":"The People's Hospital of Chongqing Liang Jiang New Area","correspondingAuthor":false,"prefix":"","firstName":"Yangmei","middleName":"","lastName":"Li","suffix":""},{"id":266284173,"identity":"b82de37b-1ecd-4bcd-8354-43521c2a743c","order_by":8,"name":"Dongyang Liu","email":"","orcid":"","institution":"Southwest Medical University","correspondingAuthor":false,"prefix":"","firstName":"Dongyang","middleName":"","lastName":"Liu","suffix":""},{"id":266284174,"identity":"0505c09d-db5e-4de8-944b-da0667fa1785","order_by":9,"name":"Meihong Ren","email":"","orcid":"","institution":"Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Meihong","middleName":"","lastName":"Ren","suffix":""},{"id":266284175,"identity":"af63850d-72e3-4412-b4b3-66e4dfffd0ef","order_by":10,"name":"Han Su","email":"","orcid":"","institution":"Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Han","middleName":"","lastName":"Su","suffix":""},{"id":266284176,"identity":"110bf4db-9c14-4ac2-955d-734abcdf7f75","order_by":11,"name":"Ling Tang","email":"","orcid":"","institution":"Affiliated Hospital of Guilin Medical College","correspondingAuthor":false,"prefix":"","firstName":"Ling","middleName":"","lastName":"Tang","suffix":""},{"id":266284177,"identity":"02eb7b74-1ec7-4b74-94d8-13e08c55cbb7","order_by":12,"name":"Jie Deng","email":"","orcid":"","institution":"Xiang Yang No.1 People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jie","middleName":"","lastName":"Deng","suffix":""},{"id":266284178,"identity":"d76cd359-0de4-4411-8ce1-c05a1160e710","order_by":13,"name":"Yao Fan","email":"","orcid":"","institution":"Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yao","middleName":"","lastName":"Fan","suffix":""},{"id":266284179,"identity":"c8cc0f6f-6dba-44fe-af23-72cb737c571b","order_by":14,"name":"Mingfang Zhou","email":"","orcid":"","institution":"The Third Affiliated Hospital of Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Mingfang","middleName":"","lastName":"Zhou","suffix":""},{"id":266284180,"identity":"80478610-20bb-48b0-a32d-e7996c267def","order_by":15,"name":"Lili Yu","email":"","orcid":"","institution":"The Third Affiliated Hospital of Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Lili","middleName":"","lastName":"Yu","suffix":""},{"id":266284181,"identity":"1ecbe457-bb73-4710-9fe2-0f9a4564292a","order_by":16,"name":"Xun Lei","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5ElEQVRIiWNgGAWjYBACPgbGBiD1T46NvQEqdICAFjaIlgPGfDwwpYS1QJQlzpNIIFYLe3ObNO+OO4xtko8f3rrZxiDHdyOB8XMBPi08B5uNec88Y2aTTjO2zm1jMJa8kcAsPQOfFonExse8bcxsbNI5bNJALYkbbiSwMfPg0yL/sOEwUAsPm+QZsJZ6wlokGEG2HJZgk+ABa0kwIKiFJ7HZcG5bmgEbD9AvOeckDGeeedgsjU8LP/vxZxJv22zq57cffng7p8xGnu948sHP+LSgAAkwgkQu8VpGwSgYBaNgFGACAI/SQ4O6d00BAAAAAElFTkSuQmCC","orcid":"","institution":"Chongqing Medical University","correspondingAuthor":true,"prefix":"","firstName":"Xun","middleName":"","lastName":"Lei","suffix":""}],"badges":[],"createdAt":"2024-01-09 14:29:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3848504/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3848504/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":49543374,"identity":"da391c33-7471-4241-b7ab-7c1ef589a7e5","added_by":"auto","created_at":"2024-01-12 17:43:43","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":130685,"visible":true,"origin":"","legend":"\u003cp\u003eHealth ecology model frame\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-3848504/v1/3527d79db90fd041d0db8557.png"},{"id":49543373,"identity":"76af2e57-58e7-4575-a5bb-eef47989d217","added_by":"auto","created_at":"2024-01-12 17:43:43","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":339565,"visible":true,"origin":"","legend":"\u003cp\u003eRevised standard structural equation model of influencing factors of abnormal bone mass\u003c/p\u003e\n\u003cp\u003eNote: The path coefficients in the figure all reached the significant level (P\u0026lt;0.05).\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-3848504/v1/201c540e8837fd97d3eb5fdc.png"},{"id":55624163,"identity":"15c86203-f676-4de9-82a3-7149d48257fa","added_by":"auto","created_at":"2024-04-30 17:35:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1397933,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3848504/v1/cef4ab01-45fa-4e34-a5a4-e7f1fea1a496.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Influencing factors of abnormal bone mass in perimenopausal and postmenopausal women based on health ecology model: A cross-sectional study","fulltext":[{"header":"1. Introduction ","content":"\u003cp\u003e With the rapid growth of aging population worldwide, osteoporosis (OP) has become an important public issue facing the world.(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)Osteoporosis is a systemic metabolic bone disease caused by a variety of reasons, which is characterized by decreased bone mass, decreased bone density, and destruction of bone microstructure, resulting in increased bone fragility and prone to fracture.(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)Osteoporosis often occurs quietly, without obvious symptoms in the early stage. With the aggravation of the disease, patients will have severe pain in the lower back and limited activity. Short body length and hunchback are the other important hazards of osteoporosis after low back pain. When the spinal canal Narrows to a certain extent due to hunchback, the spinal cord or nerve root is compressed, there will be lower limb activity and sensory dysfunction, or even paralysis, which seriously affects the quality of life of patients.(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) Fractures caused by osteoporosis pose a significant burden on China\u0026rsquo;s medical system, with an estimated 23.3\u0026nbsp;million osteoporotic fractures occurring in 2010 at a cost of US\u003cspan\u003e$\u003c/span\u003e945\u0026nbsp;million (only direct costs, including direct medical costs, direct non-medical costs).(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) It was predicted that both the number of cases and their associated expenses will double by 2035.(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) While the disease burden of osteoporosis is mounting, our comprehension of its prevalence and risk factors in China remains limited. Osteopenia is a bone state with decreased bone strength and abnormal bone mineral density that has not yet reached the definition of osteoporosis.(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) We refer to osteoporosis and osteopenia together as abnormal bone mass. While osteopenia is the precursor of osteoporosis, with a hidden onset, once it develops into osteoporosis, it will not only increase the risk of fracture in patients, causing physical and psychological effects on patients, but also bring heavy burden to the family and society. Prevention is the key to the clinical management of osteoporosis. Therefore, it is of great significance to pay attention to perimenopausal and postmenopausal women with osteopenia and carry out early intervention for the prevention and treatment of osteoporosis. At present, most studies focus on osteoporosis population, and lack of attention is paid to osteopenia, osteopenia and osteoporosis were investigated simultaneously in our study.\u003c/p\u003e \u003cp\u003eAccording to WHO STRAW\u0026thinsp;+\u0026thinsp;10 staging, perimenopause is defined as the beginning of clinical, endocrine and biological signs of menopausal trend until 1 year after menopause. Women over 40 years of age who have not had menses for 12 months after the last menstrual period can be clinically diagnosed as menopause if pregnancy is excluded.(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) Osteoporosis often occurs in women, and the incidence of osteoporosis in postmenopausal women will further increase. Postmenopausal osteoporosis caused by estrogen deficiency is the most common type of primary osteoporosis, which generally occurs within 5 to 10 years after menopause. Bone loss begins before menopause, and there are varying degrees of bone loss during the menopausal transition.(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) Since bone loss begins before menopause, the perimenopausal period is also a critical period for women to prevent and treat osteoporosis and reduce the risk of fractures. Osteoporosis is four times more common in women than men.(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) In a cross-sectional study involving 20,000 samples, the prevalence of osteoporosis among adults aged 40 and older in mainland China was 5% in males and 20.6% in females.(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) A 10-year Chinese clinical study involving 75 321 Chinese adults from seven medical centers showed that the prevalence of osteoporosis of the spine or hip was 6.46% in men and 29.13% in women aged 50 years or older in China.(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThe ecological theory first originated in biological sciences to elucidate the interrelationship between the organism and its environment, and the theory has been continuously improved and optimised to gradually form a detailed and complete model elaboration, that is, the health ecology model. In recent years, the health ecology model has been widely used in the field of medicine and health. Health ecology believes that human health is affected by a mixture of multiple factors.(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) health ecological model (HEM) believes that the impact of the environment on individuals is multi-level and complex, that is, individual and population health is the result of interdependence, coupling or restriction of individual characteristics, environmental and social factors at multiple levels.(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) HEM is a comprehensive framework that includes factors such as an individual's biological characteristics, lifestyle and behavioral habits, interpersonal relationships, Living and working conditions and policy environment (The health ecology model framework is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).Therefore, this model can be used to study and explain the occurrence and influencing factors of abnormal bone mass in perimenopausal and postmenopausal women to overcome the shortcomings of previous studies that only analyzed the influencing factors at a single level, and to provide a more systematic and comprehensive perspective to find the best way to prevent and control abnormal bone mass, so as to promote the health of perimenopausal and postmenopausal women. This study uses the health ecology model to explore the influencing factors of abnormal bone mass in perimenopausal and postmenopausal women from different levels, so as to provide a basis for the management and prevention of abnormal bone mass in Chinese women at this stage.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Survey design and participants\u003c/h2\u003e \u003cp\u003eAn institutional-based multi-center cross-sectional study was conducted among patients admitted at five recruited hospitals(Two of the five hospitals are located in the south-west region of China, while the remaining three are in the south, central and north-east regions, respectively) of China from October 2022 to September 2023. Purposive sampling method was used to select the survey subjects who met the inclusion and exclusion criteria.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Participants' inclusion and exclusion criteria.\u003c/h2\u003e \u003cp\u003eInclusion criteria:(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)Perimenopausal and postmenopausal women aged\u0026thinsp;\u0026ge;\u0026thinsp;40 years.\u003c/p\u003e \u003cp\u003eExclusion criteria:(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)Patients with major organic diseases;(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)Patients who had received treatment for relevant osteoporosis;(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e)Patients with previous mental illness or a history of mental illness.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Health Ecology Model (HEM)\u003c/h2\u003e \u003cp\u003eBased on the five dimensions of the Health Ecology Model (HEM), personal traits, behavior and lifestyle, interpersonal network, working and living conditions, and policy environment, this study selected indicators that may affect bone mass abnormalities in perimenopausal and postmenopausal women for analysis. These indicators included:(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) personal characteristics: age, body mass index, menstrual status, disease history, family history, etc.(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)Behavior and lifestyle: psychology, physical activity, diet, calcium supplement, VD supplement, smoking and drinking history, outdoor activity habits, awareness of osteoporosis knowledge, MHT, etc.(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e)Interpersonal network: social support, marital status, etc.(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e)Working and living conditions: education level, occupation, monthly income, residence, etc.(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e)Policy environment: medical insurance.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Measurement tools\u003c/h2\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.4.1 Social demographic data questionnaire\u003c/h2\u003e \u003cp\u003eThe general information of the women and the factors that may affect osteoporosis were collected by the researchers according to the situation. The data included name, age, height, weight, residence area, education, marital status, occupation, income, menstrual status, current diseases, history of non-traumatic fracture, family history of osteoporosis, family history of fragility fracture, parents' hump, and medical payment method of perimenopausal and postmenopausal women.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.4.2 Anxiety Disorder Scale (GAD-7)(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e)\u003c/h2\u003e \u003cp\u003eGeneralized Anxiety Disorder Scale-7 (GAD-7) was developed by Spitzer et al., in 2006, originally as the anxiety module of the Patient Health Questionnaire (PHQ), and has good reliability and validity. GAD-7 was a self-rating scale consisting of 7 items, which was used to evaluate the mental and emotional changes in the past 2 weeks, including nervousness and anxiety, uncontrollable worry, excessive worry, inability to relax, inability to sit, irritability, and foreboded feeling. The scale was rated on a 4-point scale, and each symptom item was scored on a 0\u0026ndash;3 scale. The scale was based on the number of days of target symptoms in the last two weeks, and the score was 0 (not at all), 1 (some days), 2 (more than half of the days), and 3 (almost every day). The main statistical measure of this scale is the sum of item scores, with a total score ranging from 0 to 21, with higher scores indicating more severe anxiety symptoms :0\u0026ndash;4 as normal, 5\u0026ndash;9 as mild, 10\u0026ndash;14 as moderate, and 15\u0026ndash;21 as severe. The internal consistency of the GAD-7 was excellent (Cronbach α\u0026thinsp;=\u0026thinsp;0.92), Test-retest reliability was also good (intraclass correlation\u0026thinsp;=\u0026thinsp;0.83).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.4.3 The Patient Health Questionnaire Depression Scale (PHQ-9)(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e)\u003c/h2\u003e \u003cp\u003eThe Patient Health Questionnaire Depression Scale (PHQ-9) is the depression module of Patient Health Questionnaire (PHQ) developed by Spitzer et al., and PHQ-9 has good reliability and validity. PHQ-9 is a self-rating scale, which is mainly used for the screening of depression. It has 9 symptom items, which are evaluated respectively: loss of interest, low mood, sleep quality, fatigue, appetite, inferiority complex, difficulty in concentration, psychomotor retardation, and negative ideation. Each symptom item in the scale was scored on a 4-point scale from 0 to 3, which was evaluated by the number of days of symptoms in the last 2 weeks. The score was 0 (not at all), 1 (some days), 2 (more than half of the days), and 3 (almost every day). The main statistical measure of this scale is the sum of item scores, and the total score ranges from 0 to 27 to assess the severity of depressive symptoms. 0\u0026ndash;4 points are normal, 5\u0026ndash;9 points are mild, 10\u0026ndash;14 points are moderate, 15\u0026ndash;19 points are moderate to severe, and 20\u0026ndash;27 points are severe. The internal reliability of the PHQ-9 was excellent(Cronbach α\u0026thinsp;=\u0026thinsp;0.89), Test-retest reliability was also good (intraclass correlation\u0026thinsp;=\u0026thinsp;0.84).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e2.4.4 the International Physical Activity Questionnaire (IPAQ)(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e)\u003c/h2\u003e \u003cp\u003ePhysical activity level was measured by the Chinese version of the International Physical Activity Questionnaire Short Questionnaire (IPAQ). The scale consists of a total of seven questions, with the first six assessing the individual's physical activity and the seventh assessing the individual's sedentary behavior. The questionnaire metabolic equivalent (MET) was 3.3 for walking, 4.0 for moderate-intensity activity, and 8.0 for vigorous-intensity activity. The official recommended method for measuring the weekly physical activity (MET-minutes/week) of the respondents was as follows: the corresponding MET assignment * weekly frequency (days/week) * daily time (minutes/day). The sum of three kinds of physical activity levels was the total physical activity level. It was measured to be reliable and valid in evaluating physical activity, with an internal correlation coefficients of 0.89.(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e2.4.5 Dietary nutritional status questionnaire\u003c/h2\u003e \u003cp\u003e On the basis of the Dietary Nutrition and Health Questionnaire prepared by the Nutrition Intervention Committee of the High Health Commission of China, the researchers revised the dietary nutrition questionnaire according to the purpose of this study, the actual situation of perimenopausal and postmenopausal women and the feasibility of the questionnaire. The patients were investigated by food frequency method and dietary habit questionnaire. To analyze the current status of dietary habits, dietary structure and nutritional status of perimenopausal and postmenopausal women, and to propose corresponding intervention strategies and programs for osteoporosis. The internal reliability of the self-administered Dietary Nutritional Status Questionnaire in this study was acceptable (Cronbach α\u0026thinsp;=\u0026thinsp;0.771), and the KMO value of the test structural validity was 0.744, which gave the scale good reliability and validity.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e2.4.6 Social Support Rating Scale(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e)\u003c/h2\u003e \u003cp\u003eSocial Support Rating Scale developed by Chinese scholar Xiao Shuiyuan was used to evaluate the social support of perimenopausal and postmenopausal women. The scale was divided into three dimensions of subjective support, objective support and utilization of support, with a total of 10 items. Subjective support included questions 1, 3, 4 and 5, and the full score was 32. Objective support included questions 2, 6 and 7, with a full score of 22; The utilization of support included questions 8, 9, and 10 with a full score of 12. The total scale scores ranged from 12 to 66, with higher scores indicating higher levels of social support. The scoring method of this study was as follows: \u0026le;22 was defined as low level, 23\u0026ndash;44 as medium level, and 45\u0026ndash;66 as high level. The Cronbach's α of each domain of the scale was 0.89\u0026ndash;0.94, and the test-retest reliability of the total scale was 0.92.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e2.4.7 Osteoporosis related knowledge awareness scale\u003c/h2\u003e \u003cp\u003eAccording to the relevant literature, 10 questions about osteoporosis related knowledge were designed. The full score was 10 points. If \u0026ldquo;yes\u0026rdquo; was selected, 1 point was recorded, and if \u0026ldquo;no\u0026rdquo; or \u0026ldquo;don't know\u0026rdquo; was selected, no point was recorded. The final score was used to evaluate the awareness of osteoporosis knowledge, with scores of 0\u0026ndash;3 as low awareness rate, 4\u0026ndash;7 as medium awareness rate, and 8\u0026ndash;10 as high awareness rate. The internal consistency of the self-administered Knowledge of Knowledge Scale in this study was very good (Cronbach α\u0026thinsp;=\u0026thinsp;0.900), and the test of structural validity had a KMO value of 0.907, which gave the scale great reliability and validity.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Bone mineral density\u003c/h2\u003e \u003cp\u003eDual-energy X-ray BMD is currently the gold standard for BMD measurement.(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) In this study, we used dual-energy X-ray absorptiometry (DXA) to measure Bone mineral density (BMD).Using the lowest T-score of either lumbar spine (L1-L4) or total hip, we defined osteoporosis and osteopenia according to the World Health Organization (WHO) criteria of T-score of \u0026gt; -1.0 as normal; -1.0 to -2.5 as osteopenia and \u0026lt; -2.5 as osteoporosis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Data collection\u003c/h2\u003e \u003cp\u003eThe questionnaire in this study was filled out by scanning the two-dimensional code of the mobile phone. Any questions were explained in detail before the investigation began. The researchers did not give any suggestive guidance during the filling process. Questionnaires were completed with the help of our investigators if patients encountered difficulties during the process. Clinical data were obtained from electronic medical records by two researchers.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Statistical analysis\u003c/h2\u003e \u003cp\u003eSPSS27.0 and AMOS21.0 was used for data processing and analysis in this study. Firstly, the sample data were analysed by descriptive statistics using SPSS27.0, count data were expressed as percentages or frequencies, while the measurements data were described by mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (\u0026#119909;̅\u0026plusmn;s) and comparisons between two groups were made using the chi-square test. AMOS21.0 was used to establish the structural equation model and path model, The normed χ\u003csup\u003e2\u003c/sup\u003e (χ\u003csup\u003e2\u003c/sup\u003e/df), root mean square error of approximation (RMSEA), goodness-of‐fit index (GFI), normed fit index (NFI), and comparative fit index(CFI)were selected to evaluate the model fit degree. Their values should meet the following standards: χ\u003csup\u003e2\u003c/sup\u003e/df\u0026thinsp;\u0026lt;\u0026thinsp;3, RMSEA\u0026thinsp;\u0026lt;\u0026thinsp;0.08, and GFI, NFI, and CFI values\u0026thinsp;\u0026gt;\u0026thinsp;0.8 indicate that the model fit is acceptable and \u0026gt;\u0026thinsp;0.9 indicate excellent. The significance level of all indicators was set at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.1Sample characteristics\u003c/h2\u003e \u003cp\u003eIn this study, a total of 575 questionnaires were distributed. After excluding 44 invalid questionnaires, 531 questionnaires were eventually included in the data analysis. The age of the subjects ranged from 40 to 73 years, with a mean age of 51.73\u0026thinsp;\u0026plusmn;\u0026thinsp;6.04 years. There were 248 subjects with normal bone mass, 230 with osteopenia and 53 with osteoporosis, The incidence of abnormal bone mass was 53.30%. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive Analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndependent Variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategorisation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNormal bone mass(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAbnormal bone mass(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e248(46.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e283(53.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge(years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49.75\u0026thinsp;\u0026plusmn;\u0026thinsp;4.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53.47\u0026thinsp;\u0026plusmn;\u0026thinsp;6.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31(12.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19(6.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97(39.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e57(20.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50\u0026ndash;54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94(37.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e115(40.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26(10.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e92(32.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent Address\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e213(85.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e251(88.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.538\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSuburban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12(4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9(3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23(9.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23(8.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducational Level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUndergraduate and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46(18.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e39(13.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.228\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJunior college\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25(10.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33(11.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh school and secondary school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36(14.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38(13.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJunior high school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87(35.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e90(31.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary and below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54(21.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e83(29.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eIncome(\u003cspan\u003e$\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMore than 10,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10(4.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8(2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5001\u0026ndash;10000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22(8.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22(7.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3000\u0026ndash;5000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80(32.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e62(21.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLess than 3000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e136(54.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e191(67.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital Status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e224(90.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e257(90.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.847\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWidowed/Divorced/Unmarried/Divorced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24(9.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26(9.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMenstrual Situation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal Menstruation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34(13.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17(6.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePerimenopause\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e155(62.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e93(32.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMenopause\u0026thinsp;\u0026lt;\u0026thinsp;5 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37(14.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e80(28.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMenopause 5\u0026ndash;10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15(6.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41(14.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMenopause\u0026thinsp;\u0026gt;\u0026thinsp;10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7(2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52(18.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12(4.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e130(52.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e162(57.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverweight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94(37.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e88(31.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eObesity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22(8.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21(7.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMHT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39(15.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38(13.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.453\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e209(84.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e245(86.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e204(82.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e233(82.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.089\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37(14.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32(11.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerately Severe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7(2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18(6.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e208(83.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e238(84.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.264\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35(14.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33(11.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerately Severe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12(4.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCalcium Supplementation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEveryday\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40(16.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38(13.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.543\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOften\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28(11.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41(14.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOccasionally\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69(27.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e85(30.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e111(44.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e119(42.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVD Supplementation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEveryday\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27(10.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22(7.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.156\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOften\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16(6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19(6.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOccasionally\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34(13.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e58(20.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e171(69.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e184(65.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCatering\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExcellent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8(3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6(2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.064\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e136(54.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e130(45.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFail\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e104(41.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e147(51.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSunshine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;30min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49(19.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e65(23.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15-30min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88(35.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e68(24.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;15min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64(25.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e90(31.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSunburn Protection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64(25.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e94(33.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.055\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSometimes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e124(50.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e113(39.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAlways\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60(24.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e76(26.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOP Knowledge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82(33.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e78(27.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.280\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92(37.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e105(37.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74(29.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e100(35.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigher level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e128(51.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e63(22.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedium level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e120(48.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e213(75.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7(2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical Activity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e147(59.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e145(51.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.106\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89(35.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e115(40.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12(4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23(8.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Analysis of structural equation model\u003c/h2\u003e \u003cdiv id=\"Sec20\" class=\"Section3\"\u003e \u003ch2\u003e3.2.1 Model construction and fitting\u003c/h2\u003e \u003cp\u003eBased on the health ecology theoretical model and domestic and international literature research, according to the content of the questionnaire and the hypotheses of this study, this study takes personal traits, behavioural characteristics, living conditions, interpersonal networks, and medical insurance as latent variables, and abnormal bone mass as the dependent variable, and constructs the path relationship between observational variable and the latent variables. Maximum likelihood estimation was used to estimate the model, and in this study, a validation factor analysis was conducted on personal traits, behavioural traits, living conditions, interpersonal networks, and their respective observables, to exclude variables with small factor loadings and to increase model fitness. Estimation of the initial model showed that the coefficients of the paths of health insurance\u0026rarr; bone mass abnormality, behavioural traits\u0026rarr;personal traits, and living conditions\u0026rarr;personal traits did not reach the level of significance (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05),so these paths were removed step by step and re-fitted.The model was iteratively revised and fitted under the indication of the modification index (MI), and the final model met the fit criteria. The validity of the revised model was good and the indicators meet the corresponding reference standards, the chi-square degrees of freedom ratio (χ\u003csup\u003e2\u003c/sup\u003e/df) of 2.137 meets the criterion of \u0026lt;\u0026thinsp;3. The remaining evaluation indicators of the model fit such as the GFI, AGFI, TLI, and CFI values of 0.952, 0.930, 0.920, and 0.939 were \u0026gt;\u0026thinsp;0.90 criterion, and the value of RMR was 0.095 ,which meets the criterion of \u0026lt;\u0026thinsp;0.1, and the value of RMSEA is 0.046, which meets the criterion of \u0026lt;\u0026thinsp;0.05. Overall, the adjusted model fitted the data well, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of model fit indicators\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003efit indicators\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e/df\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGFI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAGFI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRMSEA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eRMR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eCFI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eTLI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eIFI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRecommended standards\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003evalues\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e224.399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.952\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.930\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.095\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.939\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.920\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.940\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section3\"\u003e \u003ch2\u003e3.2.2 Path analysis\u003c/h2\u003e \u003cp\u003eThe effects of each factor on bone mass abnormality were, in descending order, personal traits, interpersonal network, behavioural characteristics, and living conditions, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Personal traits had the strongest direct positive effect on bone mass abnormality (β\u0026thinsp;=\u0026thinsp;0.417, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05); behavioural characteristics had a direct positive effect on bone mass abnormality (β\u0026thinsp;=\u0026thinsp;0.253, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05); interpersonal network had a direct negative effect on bone mass abnormality (β=-0.268, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and an indirect effect through personal traits; living conditions have a direct negative effect on bone mass abnormalities (β=-0.248,P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and indirect effect through behavioural traits and interpersonal network; medical insurance can have an indirect effect on bone mass abnormalities through living conditions and interpersonal network, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStructural equation model path coefficients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePath\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDirect effects\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIndirect effects\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal effects\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePersonal traits\u0026rarr;\u003c/p\u003e \u003cp\u003eAbnormal bone mass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.417\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBehavior characteristics\u0026rarr;Abnormal bone mass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.253\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.253\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial network\u0026rarr;\u003c/p\u003e \u003cp\u003eAbnormal bone mass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.414\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving conditions\u0026rarr;Abnormal bone mass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.248\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.363\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.115\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedical insurance\u0026rarr;Abnormal bone mass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"4. DISCUSSION","content":"\u003cp\u003eThe present study showed that the prevalence of abnormal bone mass in peri- and postmenopausal women was 53.30%. The prevalence of bone mass abnormalities varied considerably among different studies, and the results of the present study were lower than the findings of Feng J (58.62%)(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), CHEN P H (769.59%)(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e), and Gu Q P (69.72%)(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e), but higher than those of Luo W (23.69%)(\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) and TIAN L (36.74%)(\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). This may be due to the different age ranges of the subjects included in the study and the different weight of the population in each age group. In addition, factors such as the area of investigation, dietary habits, and hours of sunlight may also have a greater impact on the results of the prevalence of abnormal bone mass. Perimenopausal and postmenopausal women have decreased ovarian function, disorders of the vegetative nervous system, dysregulation of the bone resorption-bone remodelling balance, and high incidence of osteoporosis. The study of high risk factors for osteoporosis in this population has important clinical significance in the prevention and treatment of osteoporosis.\u003c/p\u003e \u003cp\u003eAmong the five layers of influencing factors in the health ecology model, the individual trait layer belongs to the downstream factors, which are determined by people's own genetic and physiological differences,this layer directly affect people's health. The behavioral characteristics layer belong to the middle factors, which act on people with time and individual growth, this layer indirectly affect people's health. Interpersonal relationship layer 、the layers of living and working conditions and policy environment belong to the upstream factors, which represent the macro-social economic and material environment and are the fundamental environmental factors determining people's health, known as \"the reasons behind the reasons\", these layers affect the middle factors and indirectly affect people's health. Most of the health management of chronic diseases in China is to educate individuals about their bad behaviours and lifestyles, while ignoring the influence of the social environment, national policies and other factors on the health management of chronic diseases. At present, many scholars have realized that the relationship between human health and its social environment is closely linked, if we ignore the role of the environment in shaping the behaviour of individuals, and only rely on health education to change the individual's bad behaviour and lifestyle, the effect is very small. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e)Health ecology emphasises the multi-level influence of the social environment on individuals and the complexity of the influencing factors, which is conducive to analysing the prevalence of bone mass abnormalities in peri-menopausal and post-menopausal women in China, and to exploring the influencing factors and the interactions between the influencing factors in a hierarchical manner, and the following will discuss the five levels of health ecology and the roles between the levels.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Personal characteristics\u003c/h2\u003e \u003cp\u003ePersonal characteristics lie at the core level of the health ecology model.The results of this study showed that the path coefficient from personal traits to abnormal bone mass was 0.440, which was significant at the 5% level, suggesting a higher prevalence of bone mass abnormality in perimenopausal and postmenopausal women with older age and years of menopause and a history of disease. Oestrogen acts through oestrogen receptors in osteoclasts, osteoblasts and bone cells, and when oestrogen is deficient it leads to abnormal bone metabolism and an increased risk of osteoporosis.(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e) As women age, oestrogen levels decline after menopause, and the synthesis of active vitamin D in the kidneys and liver decreases accordingly, leading to a decrease in intestinal absorption of calcium and the fastest rate of bone loss after the age of 65. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eOur results found that perimenopausal and postmenopausal women with a history of hypertension and diabetes are more likely to have abnormal bone mass. Some studies have found that high blood pressure reduces bone density in certain parts of the body, (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e) that people with high blood pressure have a higher prevalence of osteoporosis,(\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e)studies have also found an association between high blood pressure and abnormal calcium metabolism, and a link between some antihypertensive medications and fractures.(\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e) In patients with T2DM, sustained elevated levels of pro-inflammatory cytokines such as TNF-α, IL-1β, IL-6 and IL-18 enhance lipid peroxidation and dyslipidaemia, leading to increased osteoclastogenesis. Increases in advanced glycosylation end products (AGE), reactive oxygen species (ROS) and pro-inflammatory cytokines accelerate bone loss. Prolonged inflammation also stimulates the expression of pro-apoptotic genes such as bcl-2-like protein (Bax), which reduces the expression of genes that stimulate osteoclast formation, leading to decreased bone formation. Oxidative stress reduces differentiation to osteoblasts and can directly degrade bone.(\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e) Some studies have shown that common medication side effects of diabetes can lead to abnormal bone metabolism, and that metformin, sulfonylureas, and insulin can all increase the risk of fracture in diabetic patients.(\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e) Changes in bone metabolism in diabetic patients are affected by a variety of factors, and different factors have different effects on bone mass, the specific influencing factors and related mechanisms still need to be further studied.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Behavioural traits\u003c/h2\u003e \u003cp\u003eBehavioural traits are located outside the core layer of the model.In our study, unhealthy behavioural traits positively contribute to bone mass abnormalities in peri- and postmenopausal women. Calcium and vitamin D supplementation are effective in preventing bone mass abnormalities. Calcium is an important and indispensable element in the human body and plays a major role in the regulation of various cellular functions. Calcium helps bones to become strong, it not only replenishes skeletal muscle strength, but also improves bone density. The clinician\u0026rsquo;s guide to prevention and treatment of osteoporosis published by BHOF recommend a diet with adequate total calcium intake (1000 mg/day for men aged 50\u0026ndash;70 years; 1200 mg/day for women\u0026thinsp;\u0026ge;\u0026thinsp;51 years and men\u0026thinsp;\u0026ge;\u0026thinsp;71 years), incorporating calcium supplements if intake is insufficient. Vitamin D can promote the intestinal absorption of calcium, to maintain normal bone mass. Maintain serum vitamin D sufficiency (\u0026ge;\u0026thinsp;30 ng/mL but below \u0026le;\u0026thinsp;50 ng/mL). Prescribe supplemental vitamin D (800\u0026ndash;1000 units/day) as needed for individuals aged 50 years and older to achieve a sufficient vitamin D level. Higher doses may be necessary in some adults, especially those with malabsorption. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eIn this study, irrational dietary habits have a positive contribution to bone mass abnormalities and increase the incidence of bone mass abnormalities. Numerous guidelines refer to the need to maintain a healthy lifestyle in order to prevent osteoporosis. A balanced diet means ensuring a varied and low-salt diet, and consuming foods that are high in calcium, vitamin D or protein. (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e) Elderly women and women with longer menopausal years should be instructed to consume calcium-rich foods, such as fish, milk and dairy products, etc. In addition, more vitamins should be added to supplement the nutrition to maintain bone density, ensure the balance of bone metabolism and prevent osteoporosis. Related studies have shown that protein intake affects the production of insulin-like growth factor-1, which promotes bone growth. The 2020 Expert consensus on the nutrition and exercise management for patients with primary osteoporosis mentions the need to ensure cereal and potato intake and that dark green vegetables make up more than 1/2 of the vegetables, which favours vitamin K supplementation.(\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e) Vegetables and fruits simultaneously raise pH, inhibit osteoclast activity, and promote new bone formation by osteoblasts, while vegetables are rich in substances such as vitamins and phytoestrogens, which promote bone resorption and bone matrix formation.(\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eAlso the results of this study show that inadequate knowledge about osteoporosis is also a major factor in the occurrence of abnormal bone mass in perimenopausal and menopausal women. Yi rong showed that remote monitoring and education for primary osteoporosis patients can effectively improve patients' knowledge of the disease and improve bone metabolism and bone mineral density.(\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e) Gu Youhua pointed out that health education for postmenopausal osteoporosis patients can effectively improve the knowledge of the disease, strengthen patients' self-efficacy, and improve the quality of life.(\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e) Scientific and effective health education on osteoporosis is conducive to the establishment of correct health concepts for menopausal women, which is conducive to the improvement of health behaviours and has a positive significance on the improvement of women's quality of life. This also suggests that medical personnel or health educators need to continuously carry out various forms of OP prevention knowledge dissemination activities, including expert lectures, popularisation competitions, distribution of paper promotional treatments, and video education in the community, schools, television, micro-video, health marketing accounts, and the hospital public, among other media. Only through more extensive and sustained knowledge dissemination activities can we continue to promote the development of healthy behaviours among perimenopausal and postmenopausal women.\u003c/p\u003e \u003cp\u003eMenopausal hormone therapy is a protective factor against abnormal bone mass in perimenopausal and menopausal women in our study. Menopausal hormone therapy is a primary preventive measure for perimenopausal and postmenopausal osteoporosis, and the use of menopausal hormone therapy is effective in preventing bone loss in perimenopausal and early menopausal women and helps to increase or maintain bone density.(\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e) The American Endocrine Society released the ENDO Clinical Practice Guidelines for the Pharmacological Treatment of OP in Postmenopausal Women in 2019, which suggests that standardised menopausal hormone therapy may be administered to women younger than 60 years of age, with a duration of menopause of less than 10 years, and with menopause-related symptoms, following a detailed and adequate assessment by a clinician and the exclusion of hormone therapy contraindications.(\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Interpersonal networks\u003c/h2\u003e \u003cp\u003eInterpersonal network is located in the third layer of the model. In this study, the social support degree was used to reflect the interpersonal network, and it was found that the lower the social support degree the more likely to have abnormal bone mass. Social support is an important social factor, which refers to the spiritual and material help and support from individuals and organisations such as family, relatives, friends, colleagues and party groups, as well as the degree to which an individual makes use of social support. A large number of studies have confirmed the health-promoting effects of social support.(\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e) This may be due to the fact that marital partners, family members and children of people with high social support will give each other more mental comfort and related life care, thus forming good life habits to reduce the prevalence of bone mass abnormality.(\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e) At the same time, social participation prevents the development of chronic diseases such as osteoporosis, improves muscle mass and strengthens bone function.(\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e) As the physical quality and energy of the postmenopausal body decreases, the opportunities for social activities become fewer and fewer, but the basic needs for social interaction, respect and self-realisation still exist. Therefore, social participation must play a positive social support role through the strength of the family and society as a whole, so as to make postmenopausal women feel the concern and respect of the family and society from various aspects, and to help postmenopausal women satisfy the basic needs for social self-realisation.\u003c/p\u003e \u003cp\u003eIn addition, our study found that upstream factors in health ecology modelling can influence downstream factors in the model, indirectly impacting on health. Interpersonal networks are strongly associated with personal traits (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), can indirectly through personal traits affect bone abnormalities. Interpersonal networks were found to be beneficial to health by maintaining a favourable emotional experience in individuals(\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e). Interpersonal network as a mediator variable plays an indirect role in the pathway of personal traits affecting bone density, the lower the social support, the more likely to suffer from hypertension, diabetes and other chronic diseases, the reason can be hypothesised that the participation in social activities can increase the sense of belonging of the individual, easy to resolve the bad emotions, maintain physical and mental happiness, and thus reduce the likelihood of the occurrence of chronic diseases. Family involvement and support should be encouraged, counselling and social services should be valued, and avenues for social functioning should be provided wherever possible in order to reduce the prevalence of chronic diseases.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Living conditions\u003c/h2\u003e \u003cp\u003eLiving conditions are located in the fourth level of the model. Living in the city, having a high income, and having a high level of education are more likely to have abnormal bone mass in our study. Living in the city is more likely to suffer from osteoporosis, which is consistent with Zhang Zhenzhen's findings, (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e) while some reports indicate that the prevalence is higher in rural areas than in urban areas, (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e) and in-depth analyses suggest that the place of residence may only be superficial, and that the real influencing factors are the physical activity and the economic level. Urban residents have a higher standard of living, higher family income than rural areas, relatively more knowledge, long years of education, so the content of osteoporosis health education can be accepted at an early stage. And the intake of high nutrition is relatively balanced, and the purchasing power is strong, which can meet the needs of the organism. However, the urban population has more brain workers, most of them have less activity, short exposure to sunlight, and have bad habits such as drinking coffee and strong tea. In rural areas, where there is more farm work, a certain amount of load training may increase bone mass or slow down bone mass loss in menopausal women, which may make up for the shortcomings of an unbalanced diet. The higher incomes and higher levels of education may also be associated with the fact that people with higher incomes and higher levels of education are more likely to be involved in mental labour and less in physical labour.\u003c/p\u003e \u003cp\u003eOur analyses showed that living conditions were strongly associated with interpersonal networks (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and could indirectly influence bone mass abnormalities through interpersonal networks. Our study shows that the higher the cultural level and the higher the income, the higher the level of social support. Studies by different scholars have shown that individuals from different cultural backgrounds have greater differences in their ability to perceive social support, suggesting that literacy is also an important influence on social support. (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e)This is because people with a certain level of cultural quality can get more support and respect in life and work, their own ability to seek and make use of social resources is higher, it is easier for them to adapt to the society, get a sense of satisfaction, and realise their own self-worth, and the people who have a good level of economic participation in more social activities and spend more time interacting with people, thus obtaining more objective support and making higher use of support. A high level of education, high income and living in the city are beneficial for the development of various healthy lifestyles, and at the same time help to increase the level of social support, which in turn creates a protective effect against abnormal bone mass.\u003c/p\u003e \u003cp\u003eIn addition, the results of our analyses show that the upstream factors of a health ecology model can also influence the midstream factors of the model, indirectly impacting on health. living conditions were closely related to behavioural characteristics(P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), could indirectly through behavioural characteristics affect bone abnormalities. Knowledge of osteoporosis was affected by factors such as literacy, income and place of residence, and was relatively lower among those with lower literacy, lower income and those in rural areas. (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e) It may be due to the fact that higher education level usually predicts better job, higher income, better living conditions and socio-economic status, which leads to more access to resources and greater ability to acquire bone health care knowledge. At the same time, more educated people attach more importance to healthy lifestyles and are more willing to accept osteoporosis preventive healthcare measures, such as MHT. Therefore, in the implementation of health management and bone health care interventions for patients with abnormal bone mass, high attention should be paid to the literacy level of patients, and appropriate bone health popularisation and education should be provided to patients with relatively low literacy level, in order to reduce the inequality of health services, improve the bone health care ability of patients in various aspects, and maximise the quality of life related to bone health of patients.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section2\"\u003e \u003ch2\u003e4.5 Medical insurance\u003c/h2\u003e \u003cp\u003ePolicy environment is at the outermost level of the health ecology model. In our results, although the effect of medical insurance on abnormal bone mass in perimenopausal and postmenopausal women was not statistically significant, medical insurance was closely associated with interpersonal networks and living conditions (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), which implies that the role of perfecting social security in the prevention of abnormal bone mass in perimenopausal and postmenopausal women should not be overlooked as well. Social security belongs to the category of national policy and represents the policy environment dimension in the theoretical model of health ecology. The behaviour of any organ, department, enterprise or institution and individual is constrained by the macro-policy environment, with the national system directly influencing sectoral decision-making and the will of the people. Government-led scientific planning of community services for the elderly at the policy level and calls for healthy living by the nation can encourage communities to provide rationalised services for the elderly, raise residents' health awareness and cultivate healthy living habits, thereby reducing the risk of bone mass abnormalities.\u003c/p\u003e \u003cp\u003eIn summary, this study analysed the factors influencing abnormal bone mass in perimenopausal and postmenopausal women using a health ecology model, from distal to proximal, integrating multiple dimensions and factors, and concluded that the factors influencing abnormal bone mass in perimenopausal and postmenopausal women are complex. In addition to the direct effects that can occur between levels of the model, there can also be indirect effects on bone health by influencing other levels. Interpersonal networks can influence bone mass abnormalities directly or indirectly by influencing personal traits. Living conditions can directly influence bone mass abnormality and indirectly influence bone mass abnormality by influencing behavioural characteristics and interpersonal networks. Personal traits and behavioural characteristics directly influence bone mass abnormalities. Health insurance does not have a direct effect on bone mass abnormalities, but it can have an indirect effect on bone mass abnormalities by influencing interpersonal networks and living conditions. Therefore, in combination with the theory of health ecology, attention should be paid to the upstream influencing factors, and the government should actively play a leading role in improving social security, encouraging and guiding the relevant units, communities, families, and individual residents to take action together, reinforcing the synergistic effect of the relevant main bodies, adopting effective interventions on the influencing factors of bone mass abnormalities, forming a favourable situation in which there is extensive participation in the society and autonomous and conscientious prevention on the part of individuals, and actively exerting the positive effect of the middle-stream factors to continually improve the quality of life of periand postmenopausal and postmenopausal women in China by improving the level of social support, strengthening health education, and maintaining the individual's state of health. Specific policy recommendations for the prevention of bone mass abnormalities can be based on the above factors and pathways affecting bone mass abnormalities in perimenopausal and postmenopausal women. At the same time, the relevant authorities are asked to focus on the importance of micro-factors such as improving the health insurance system, organising regular social activities, adopting good dietary habits, and preventing high blood pressure and diabetes in the prevention of bone mass abnormalities in perimenopausal and postmenopausal women.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. LIMITATIONS","content":"\u003cp\u003eWe should be cautious when generalizing the results of this study due to the following limitations. First, this study used a cross-sectional design, so the causality of each variable in the SEM cannot be determined. Future longitudinal follow-up investigations are needed to further verify the causal mechanism and to expand this study. Second, the lack of healthcare institutions in North, East and Northwest China among the multicentre units recruited for this study may have led to a lack of representativeness of the prevalence of abnormal bone mass in this study, and larger multicentre studies are needed in the future.\u003c/p\u003e"},{"header":"6. CONCLUSIONS","content":"\u003cp\u003eThe prevalence of abnormal bone mass is high in perimenopausal and postmenopausal women in China. In this study, personal characteristics and unhealthy behavior characteristics are risk factors for abnormal bone mass. Higher social support and living conditions are protective factors for abnormal bone mass, and can indirectly affect bone mass abnormalities. Medical insurance can indirectly affect abnormal bone mass. Future policy recommendations for the prevention of abnormal bone mass can be made based on the factors and pathways identified in this study that affect abnormal bone mass in perimenopausal and postmenopausal women. The government can establish a three-level prevention and control system for osteoporosis in the elderly, adopt the strategy of prevention first, combination of prevention and treatment, hierarchical diagnosis and treatment, and whole-process management to improve the whole society's awareness of bone health knowledge and reduce the harm of osteoporosis and its fractures, so as to realize the \"Healthy China\" strategy.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAcknowledgments\u003c/p\u003e\n\u003cp\u003eWe thanked all women who took the time to participate in this study and all the staff who assisted in data collection.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAuthors\u0026apos; contributions\u003c/p\u003e\n\u003cp\u003eHYH participated in design of the study, field investigation, data collection, and drafting of the manuscript.\u0026nbsp;JLY participated in field investigation and data collection. QW, YYZ, MW, ZFC, NL, MHR, HS, LT and JD\u0026nbsp;participated in field investigation and data collection. YML participated in the design of the study and field investigation and data collection. DYL participated data analysis. YF and MFZ participated in the design of the study. XL and LLY participated in the design of the study, field investigation, data collection, and review of the manuscript. All authors saw and approved the final version.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis work was supported by National Natural Science Foundation of China (No. 72174033), the Science and Technology Research Program of Chongqing Municipal Education Commission (No. KJZD-K202100403), and Program for Youth Innovation in Future Medicine, Chongqing Medical University (No. W0013)\u003c/p\u003e\n\u003cp\u003eData availability\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003eEthics statement\u003c/p\u003e\n\u003cp\u003eThe studies involving human participants were reviewed and approved by the Institutional Review Board of the Third Affiliated Hospital of Chongqing Medical University (202281). We obtained informed consent from all participants.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eRachner TD, Khosla S, Hofbauer LC. Osteoporosis: now and the future. Lancet (London, England). 2011;377(9773):1276-87.\u003c/li\u003e\n\u003cli\u003eCompston JE, McClung MR, Leslie WD. Osteoporosis. Lancet (London, England). 2019;393(10169):364-76.\u003c/li\u003e\n\u003cli\u003eEditorial Board of Osteoporosis Prevention and Treatment (China White Paper) CHPF. White paper on osteoporosis. Chinese Journal of Health Management. 2009;3(3):148-54.\u003c/li\u003e\n\u003cli\u003eSi L, Winzenberg TM, Jiang Q, Palmer AJ. Screening for and treatment of osteoporosis: construction and validation of a state-transition microsimulation cost-effectiveness model. Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA. 2015;26(5):1477-89.\u003c/li\u003e\n\u003cli\u003eSi L, Winzenberg TM, Jiang Q, Chen M, Palmer AJ. Projection of osteoporosis-related fractures and costs in China: 2010-2050. Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA. 2015;26(7):1929-37.\u003c/li\u003e\n\u003cli\u003eMartinez-Lopez A, Blasco-Morente G, Giron-Prieto MS, Arrabal-Polo MA, Luque-Valenzuela M, Luna-Del Castillo JD, et al. Linking of psoriasis with osteopenia and osteoporosis: A cross-sectional study. Indian journal of dermatology, venereology and leprology. 2019;85(2):153-9.\u003c/li\u003e\n\u003cli\u003eHarlow SD, Gass M, Hall JE, Lobo R, Maki P, Rebar RW, et al. Executive summary of the Stages of Reproductive Aging Workshop + 10: addressing the unfinished agenda of staging reproductive aging. The Journal of clinical endocrinology and metabolism. 2012;97(4):1159-68.\u003c/li\u003e\n\u003cli\u003eSowers MR, Zheng H, Jannausch ML, McConnell D, Nan B, Harlow S, et al. Amount of bone loss in relation to time around the final menstrual period and follicle-stimulating hormone staging of the transmenopause. The Journal of clinical endocrinology and metabolism. 2010;95(5):2155-62.\u003c/li\u003e\n\u003cli\u003eSeifert-Klauss V, Prior JC. Progesterone and bone: actions promoting bone health in women. Journal of osteoporosis. 2010;2010:845180.\u003c/li\u003e\n\u003cli\u003eBonjour JP, Chevalley T, Ferrari S, Rizzoli R. The importance and relevance of peak bone mass in the prevalence of osteoporosis. Salud publica de Mexico. 2009;51 Suppl 1:S5-17.\u003c/li\u003e\n\u003cli\u003eWang L, Yu W, Yin X, Cui L, Tang S, Jiang N, et al. Prevalence of Osteoporosis and Fracture in China: The China Osteoporosis Prevalence Study. JAMA network open. 2021;4(8):e2121106.\u003c/li\u003e\n\u003cli\u003eZeng Q, Li N, Wang Q, Feng J, Sun D, Zhang Q, et al. The Prevalence of Osteoporosis in China, a Nationwide, Multicenter DXA Survey. Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research. 2019;34(10):1789-97.\u003c/li\u003e\n\u003cli\u003eReifsnider E, Gallagher M, Forgione B. Using ecological models in research on health disparities. Journal of professional nursing : official journal of the American Association of Colleges of Nursing. 2005;21(4):216-22.\u003c/li\u003e\n\u003cli\u003eBuse CG, Oestreicher JS, Ellis NR, Patrick R, Brisbois B, Jenkins AP, et al. Public health guide to field developments linking ecosystems, environments and health in the Anthropocene. Journal of epidemiology and community health. 2018;72(5):420-5.\u003c/li\u003e\n\u003cli\u003eSpitzer RL, Kroenke K, Williams JB, L\u0026ouml;we B. A brief measure for assessing generalized anxiety disorder: the GAD-7. Archives of internal medicine. 2006;166(10):1092-7.\u003c/li\u003e\n\u003cli\u003eKroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. Journal of general internal medicine. 2001;16(9):606-13.\u003c/li\u003e\n\u003cli\u003eHagstr\u0026ouml;mer M, Oja P, Sj\u0026ouml;str\u0026ouml;m M. The International Physical Activity Questionnaire (IPAQ): a study of concurrent and construct validity. Public health nutrition. 2006;9(6):755-62.\u003c/li\u003e\n\u003cli\u003eDeng HB, Macfarlane DJ, Thomas GN, Lao XQ, Jiang CQ, Cheng KK, et al. Reliability and validity of the IPAQ-Chinese: the Guangzhou Biobank Cohort study. Medicine and science in sports and exercise. 2008;40(2):303-7.\u003c/li\u003e\n\u003cli\u003eXIAO s. Theoretical basis and research applications of the Social Support Rating Scale (SSRS). Journal of Clinical Psychiatry. 1994(02):98-100.\u003c/li\u003e\n\u003cli\u003eKanis JA, McCloskey EV, Johansson H, Oden A, Melton LJ, 3rd, Khaltaev N. A reference standard for the description of osteoporosis. Bone. 2008;42(3):467-75.\u003c/li\u003e\n\u003cli\u003eFENG J, WANG X, ZHANG T, CEHNG L, WANG Q, CEHNG X. Analysis of prevalence and influencing factors of abnormal bone density rate in Weifang. Chinese Journal of Osteoporosis. 2023;29(10):1484-9.\u003c/li\u003e\n\u003cli\u003eChen PH, Lin MS, Huang TJ, Chen MY. Prevalence of and factors associated with adopting bone health promoting behaviours among people with osteoporosis in Taiwan: a cross-sectional study. BMJ open. 2017;7(9):e015980.\u003c/li\u003e\n\u003cli\u003eGU Q, WU L, SUN W. Study on the prevalence rate and risk factors of osteoporosis in postmenopausal women. Maternal and Child Health Care of China. 2020;35(22):4158-62.\u003c/li\u003e\n\u003cli\u003eLUO W, LIU Z, LIU H, WANG J. Investigation of bone mineral density and prevalence of bone mass abnormality in 3 859 healthy subjects in Bejjin. Chinese Journal of Osteoporosis. 2020;26(05):719-22.\u003c/li\u003e\n\u003cli\u003eTian L, Yang R, Wei L, Liu J, Yang Y, Shao F, et al. Prevalence of osteoporosis and related lifestyle and metabolic factors of postmenopausal women and elderly men: A cross-sectional study in Gansu province, Northwestern of China. Medicine. 2017;96(43):e8294.\u003c/li\u003e\n\u003cli\u003eAnagnostis P, Bosdou JK, Vaitsi K, Goulis DG, Lambrinoudaki I. Estrogen and bones after menopause: a reappraisal of data and future perspectives. Hormones (Athens, Greece). 2021;20(1):13-21.\u003c/li\u003e\n\u003cli\u003eYU L, BAI Y, LUO X, DENG R, YANG J, LI Y, et al. Ｒisk factors and preventive /therapeutic status of osteoporotic fracture in postmenopausal women in two communities of Beijing. Chinese Journal of Osteoporosis and Bone Mineral Research. 2020;13(02):110-5.\u003c/li\u003e\n\u003cli\u003eVeiga Silva AC, da Rosa MI, Fernandes B, Lumertz S, Diniz RM, dos Reis Damiani ME. [Factors associated with osteopenia and osteoporosis in women undergoing bone mineral density test]. Revista brasileira de reumatologia. 2015;55(3):223-8.\u003c/li\u003e\n\u003cli\u003eYang S, Nguyen ND, Center JR, Eisman JA, Nguyen TV. Association between hypertension and fragility fracture: a longitudinal study. Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA. 2014;25(1):97-103.\u003c/li\u003e\n\u003cli\u003eWu HL, Yang J, Wei YC, Wang JY, Jia YY, Li L, et al. Analysis of the prevalence, risk factors, and clinical characteristics of osteoporosis in patients with essential hypertension. BMC endocrine disorders. 2022;22(1):165.\u003c/li\u003e\n\u003cli\u003eGUO L, WANG Y, HOU X, TIAN F. Relationship between cardiovascular and cerebrovascular disease and osteoporotic fracture. Chinese Journal of Osteoporosis and Bone Mineral Research. 2022;15(06):683-90.\u003c/li\u003e\n\u003cli\u003eRathinavelu S, Guidry-Elizondo C, Banu J. Molecular Modulation of Osteoblasts and Osteoclasts in Type 2 Diabetes. Journal of diabetes research. 2018;2018:6354787.\u003c/li\u003e\n\u003cli\u003eHa J, Lim Y, Kim MK, Kwon HS, Song KH, Ko SH, et al. Comparison of the Effects of Various Antidiabetic Medication on Bone Mineral Density in Patients with Type 2 Diabetes Mellitus. Endocrinology and metabolism (Seoul, Korea). 2021;36(4):895-903.\u003c/li\u003e\n\u003cli\u003eLeBoff MS, Greenspan SL, Insogna KL, Lewiecki EM, Saag KG, Singer AJ, et al. The clinician\u0026apos;s guide to prevention and treatment of osteoporosis. Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA. 2022;33(10):2049-102.\u003c/li\u003e\n\u003cli\u003eCompston J, Cooper A, Cooper C, Gittoes N, Gregson C, Harvey N, et al. UK clinical guideline for the prevention and treatment of osteoporosis. Archives of osteoporosis. 2017;12(1):43.\u003c/li\u003e\n\u003cli\u003eNutrition and Bone Health Committee CNS, Chinese Society of Osteoporosis Bone Mineral Research CMA. Expert consensus on the nutrition and exercise management for patients with primary osteoporosis. Chinese Journal of Osteoporosis and Bone Mineral Research. 2020;13(05):396-410.\u003c/li\u003e\n\u003cli\u003eZHANG C, ZHAO Y. Influencing factors of knowledge，attitude and practice of prevention of osteoporosis in perimenopausal women. Shanghai Nursing. 2018;18(09):27-31.\u003c/li\u003e\n\u003cli\u003eYI R, CHEN H. Effects of remote health education and nutritional guidance on bone metabolism in patients with primary osteoporotic fractures. The Medical Forum. 2022;26(33):85-7+109.\u003c/li\u003e\n\u003cli\u003eGU Y, ZHOU H. Effect of health education based on management by objectives on the patients\u0026apos; awareness of postmenopausal osteoporosis disease and quality of life. Medical Higher Vocational Education and Modern Nursing. 2019;2(06):417-20.\u003c/li\u003e\n\u003cli\u003eExpert consensus on prevention and treatment of osteoporosis in perimenopausal and postmenopausal women. Chinese Journal for Clinicians. 2020;48(08):903-8.\u003c/li\u003e\n\u003cli\u003eEastell R, Rosen CJ, Black DM, Cheung AM, Murad MH, Shoback D. Pharmacological Management of Osteoporosis in Postmenopausal Women: An Endocrine Society* Clinical Practice Guideline. The Journal of clinical endocrinology and metabolism. 2019;104(5):1595-622.\u003c/li\u003e\n\u003cli\u003eKobayashi T, Kawachi I, Iwase T, Suzuki E, Takao S. Individual-level social capital and self-rated health in Japan: an application of the Resource Generator. Social science \u0026amp; medicine (1982). 2013;85:32-7.\u003c/li\u003e\n\u003cli\u003eMAO Y, ZHU B, LIU J, WANG X. Empirical evidence on the factors influencing chronic diseases in the middle-aged and elderly population from the perspective of health ecology. Journal of Xi\u0026apos;an Jiaotong University(Social Sciences). 2015;35(05):15-24.\u003c/li\u003e\n\u003cli\u003eMA L, FENG M, LI G, YANG W. The association between quality of life and social support in the elderly patients with osteoporosis. Practical Geriatrics. 2013;27(08):634-6.\u003c/li\u003e\n\u003cli\u003e\u0026Ccedil;alişkan Pala S, \u0026Uuml;nsal A, Arslantaş D, \u0026Ouml;cal EE, Dağtekin G. Evaluation of depression, social support and quality of life in perimenopausal and postmenopausal women in semi-rural Turkey. Psychogeriatrics : the official journal of the Japanese Psychogeriatric Society. 2022;22(5):679-87.\u003c/li\u003e\n\u003cli\u003eZHANG Z, LI L, SHEN Y. A Survey on Influence Factors of Osteoporosis in Perimenopausal Women from Northern Anhui and Health Education. Chinese Journal of General Practice. 2013;11(11):1745-6.\u003c/li\u003e\n\u003cli\u003eKang SW, Yang JH, Shin WC, Kim YJ, Choi MH. Influence of Residence Area and Basic Livelihood Conditions on the Prevalence and Diagnosis Experience of Osteoporosis in Postmenopausal Women Aged over 50 Years: Evaluation Using Korea National Health and Nutrition Examination Survey Data. International journal of environmental research and public health. 2021;18(18).\u003c/li\u003e\n\u003cli\u003eQI Y, ZHANG X, SHI X, HU Y, GAO H, LI W. Social support status and influencing factors of the elderly in urban community. Chinese General Practice. 2016;19(25):3099-102.\u003c/li\u003e\n\u003cli\u003eHurdle DE. Native Hawaiian traditional healing: culturally based interventions for social work practice. Social work. 2002;47(2):183-92.\u003c/li\u003e\n\u003cli\u003eKadam N, Chiplonkar S, Khadilkar A, Khadilkar V. Low knowledge of osteoporosis and its risk factors in urban Indian adults from Pune city, India. Public health nutrition. 2019;22(7):1292-9.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Health Ecology Model, Perimenopause and Postmenopausal, Abnormal Bone Mass, Influencing Factors, Structural Equation Model","lastPublishedDoi":"10.21203/rs.3.rs-3848504/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3848504/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eAs the world's population ages, bone health has become a major public problem. The incidence of osteoporosis in women will further increase due to the decline of oestrogen after menopause. In this study, we used a health ecology model to explore the factors affecting abnormal bone mass in perimenopausal and postmenopausal women at different levels, and to provide a basis for the management and prevention of abnormal bone mass in women at this stage of life in China.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eFrom October 2022 to September 2023, perimenopausal and postmenopausal women aged\u0026thinsp;\u0026ge;\u0026thinsp;40 years admitted to five recruited hospitals in China were recruited by purposive sampling method.Information on five levels of the health ecology model, including personal traits, behavioral characteristics, interpersonal network, working and living conditions, and policy environment was collected through structured questionnaires, and the data were analyzed using a structural equation model.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAmong 531 participants, 248 subjects had normal bone mass, 230 had osteopenia and 53 had osteoporosis. The results of the structural equation model showed that personal traits had the strongest direct positive effect on bone mass abnormality (β\u0026thinsp;=\u0026thinsp;0.417, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05); behavioural characteristics had a direct positive effect on bone mass abnormality (β\u0026thinsp;=\u0026thinsp;0.253, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05); interpersonal network had a direct negative effect on bone mass abnormality (β=-0.268, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and an indirect effect through personal traits; living conditions have a direct negative effect on bone mass abnormalities (β=-0.248,P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and indirect effect through behavioural traits and interpersonal network; medical insurance can have an indirect effect on bone mass abnormalities through living conditions and interpersonal network.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eCurrently, the prevalence of abnormal bone mass in perimenopausal and postmenopausal women is high in China. Combined with the health ecology model, we found that personal characteristics and unhealthy behavior characteristics are risk factors for abnormal bone mass, higher social support and living conditions are protective factors for abnormal bone mass, which could indirectly affect abnormal bone mass, and medical insurance can indirectly affect abnormal bone mass. Future policy recommendations for the prevention of abnormal bone mass can be based on the factors and pathways that affect abnormal bone mass in perimenopausal and postmenopausal women identified in this study, in order to reduce the incidence of abnormal bone mass and improve the quality of life of perimenopausal and postmenopausal women.\u003c/p\u003e","manuscriptTitle":"Influencing factors of abnormal bone mass in perimenopausal and postmenopausal women based on health ecology model: A cross-sectional study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-12 17:43:38","doi":"10.21203/rs.3.rs-3848504/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"38d4a4db-27be-4b6f-8420-10e054590cd1","owner":[],"postedDate":"January 12th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-04-30T17:27:16+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-12 17:43:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3848504","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3848504","identity":"rs-3848504","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}