Health-Related Quality of Life and Medical Resource Use in Patients with Osteoporosis and Depression: A Cross-Sectional Analysis from the National Health and Nutrition Examination Survey

The Impact of Depression on Detrimental Changes in Bone Microstructure in Female Mice

Background

Several clinical studies have examined the connection between depression and bone loss, but the cause-and-effect relationship between the two conditions, especially in animal models, is not well-studied.

Methods

A total of 32 female mice were, randomly divided into control group (CON, n=19) and depression group (DEP, n=13). The mice in the DEP group were subjected to 21 consecutive days of restraint stress, following depressive-like behaviors were assessment. The femurs were collected using Micro-Computed Tomography (μCT) and histochemical staining. In parallel, levels of serotonin-related proteins in the brain were measured using Western blot analysis, and sex hormone profiles were determined through liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS).

Results

The mice in the DEP group exhibited clear signs of depressive-like behaviors and an increase in serotonin transporter levels (t=-2.435, P< 0.05). In comparison to the CON mice, the DEP mice showed a decrease in bone mineral density (t =3.741, P< 0.05), bone surface area density (t =8.009, P<0.01), percent bone volume (t =4.293, P< 0.05), trabecular number (t =5.844, P<0.01), and connected density (t =11.000, P< 0.05). Additionally, there was an increase in trabecular separation (t =-7.436, P<0.01) in DEP mice. Furthermore, the DEP mice displayed a significant reduction in serum estrogen levels (t =4.340, P< 0.05) and changes in its metabolite (t =-3.325, P< 0.05), while the levels of androgens remained unchanged.

Conclusion

The restraint stress not only led to the development of depressive-like behaviors but also disrupted the estrogen metabolism pathway, resulting in damage to bone mass and microstructure in female mice. These findings suggest that stress-induced depression may pose a risk for bone loss in female mice by altering estrogen metabolism pathways.

The role of quality of life data as an endpoint for collecting real-world evidence within geroscience clinical trials

With geroscience research evolving at a fast pace, the need arises for human randomized controlled trials to assess the efficacy of geroprotective interventions to prevent age-related adverse outcomes, disease, and mortality in normative aging cohorts. However, to confirm efficacy requires a long-term and costly approach as time to the event of morbidity and mortality can be decades. While this could be circumvented using sensitive biomarkers of aging, current molecular, physiological, and digital endpoints require further validation. In this review, we discuss how collecting real-world evidence (RWE) by obtaining health data that is amenable for collection from large heterogeneous populations in a real-world setting can help speed up validation of geroprotective interventions. Further, we propose inclusion of quality of life (QoL) data as a biomarker of aging and candidate endpoint for geroscience clinical trials to aid in distinguishing healthy from unhealthy aging. We highlight how QoL assays can aid in accelerating data collection in studies gathering RWE on the geroprotective effects of repurposed drugs to support utilization within healthy longevity medicine. Finally, we summarize key metrics to consider when implementing QoL assays in studies, and present the short-form 36 (SF-36) as the most well-suited candidate endpoint.

Application of machine learning algorithms to identify people with low bone density

Background

Osteoporosis is becoming more common worldwide, imposing a substantial burden on individuals and society. The onset of osteoporosis is subtle, early detection is challenging, and population-wide screening is infeasible. Thus, there is a need to develop a method to identify those at high risk for osteoporosis.

Objective

This study aimed to develop a machine learning algorithm to effectively identify people with low bone density, using readily available demographic and blood biochemical data.

Methods

Using NHANES 2017-2020 data, participants over 50 years old with complete femoral neck BMD data were selected. This cohort was randomly divided into training (70%) and test (30%) sets. Lasso regression selected variables for inclusion in six machine learning models built on the training data: logistic regression (LR), support vector machine (SVM), gradient boosting machine (GBM), naive Bayes (NB), artificial neural network (ANN) and random forest (RF). NHANES data from the 2013-2014 cycle was used as an external validation set input into the models to verify their generalizability. Model discrimination was assessed via AUC, accuracy, sensitivity, specificity, precision and F1 score. Calibration curves evaluated goodness-of-fit. Decision curves determined clinical utility. The SHAP framework analyzed variable importance.

Results

A total of 3,545 participants were included in the internal validation set of this study, of whom 1870 had normal bone density and 1,675 had low bone density Lasso regression selected 19 variables. In the test set, AUC was 0.785 (LR), 0.780 (SVM), 0.775 (GBM), 0.729 (NB), 0.771 (ANN), and 0.768 (RF). The LR model has the best discrimination and a better calibration curve fit, the best clinical net benefit for the decision curve, and it also reflects good predictive power in the external validation dataset The top variables in the LR model were: age, BMI, gender, creatine phosphokinase, total cholesterol and alkaline phosphatase.

Conclusion

The machine learning model demonstrated effective classification of low BMD using blood biomarkers. This could aid clinical decision making for osteoporosis prevention and management.

Emotional distress and multimorbidity patterns in Chinese Han patients with osteoporosis: a network analysis

With the aging of the population, the prevalence of osteoporosis and multimorbidity is increasing. Patients with osteoporosis often experience varying levels of emotional distress, including anxiety and depression. However, few studies have explored the patterns of multiple conditions and their impact on patients' emotional distress. Here, we conducted a network analysis to explore the patterns of multimorbidities and their impact on emotional distress in 13,359 Chinese Han patients with osteoporosis. The results showed that multimorbidity was prevalent in Chinese patients with osteoporosis and increased with age, and was more frequent in males than in females, with the most common pattern of multimorbidity being osteoporosis and essential (primary) hypertension. Finally, we found that patients' emotional distress increased with the number of multimorbidities, especially in female patients, and identified eight multimorbidities with high correlation to patients' emotional distress.

Osteoporosis is associated with depression among older adults: a nationwide population-based study in the USA from 2005 to 2020

OBJECTIVES

The global prevalence of osteoporosis is rising, yet it is unclear whether people with osteoporosis have a higher risk of depression than those without osteoporosis.

STUDY DESIGN

A cross-sectional study.

METHODS

We used nationally representative data from the US National Health and Nutrition Examination Survey (NHANES) in 2005-2006, 2007-2008, 2009-2010, 2013-2014, and 2017-2020. The diagnosis of osteoporosis was based on the bone mineral density of the femoral neck measured by dual-energy X-ray absorptiometry. Depression was assessed by the Patient Health Questionnaire-9 (PHQ-9), with a score ≥5 as depressive symptoms and a score ≥10 as probable depression. We used logistic regression models to evaluate the association between osteoporosis and depressive symptoms and probable depression.

RESULTS

We included 11,603 adults (aged 50 years and older, 52.3% male) and observed 5.2% of them had osteoporosis. 31.9% of these osteoporotic people had depressive symptoms, and 10.0% had probable depression. Compared to participants without osteoporosis, those with osteoporosis were 1.73 times more likely to experience depressive symptoms (odds ratio [OR] = 1.73, 95% confidence interval [CI] 1.20-2.50) and 1.91 times more likely to experience probable depression (OR = 1.91, 95% CI 1.02-3.59), after adjusting for sex, age, race/ethnicity, education, marital status, family income, body mass index, smoking, physical activity, and alcohol abuse. Moderate-to-vigorous activities mediated the associations between osteoporosis and depression and depressive symptoms.

CONCLUSIONS

Osteoporosis is an independent risk factor for depression. This study highlights the need to evaluate the mental well-being of patients with osteoporosis in clinical and primary health care.

Evaluation of the correlation between depression and physical activity among older persons with osteoporosis: a cross-sectional study

Background

Osteoporosis is a common chronic disease in older persons. Physical activity can prevent chronic diseases as well as many diseases associated with aging. Older persons often suffer from depression and other psychological problems. However, there are few studies on the correlation between depression and physical activity in older persons with osteoporosis in China.

Methods

This cross-sectional study was conducted from June 1 to December 28, 2021. A total of 207 subjects who met the inclusion and were exclusion criteria were selected from the outpatient department of West China Hospital and evaluated using a self-designed demographic data questionnaire, the Self-rating Depression Scale (SDS), and the Physical Activity Scale for the Elderly (PASE). Multivariate linear regression was performed to analyze the factors affecting physical activity, and multivariate logistic regression analysis was performed to analyze the factors affecting depression. Spearman's correlation coefficients were calculated to analyze the correlation between depression and physical activity in older persons with osteoporosis.

Results

A total of 173 valid questionnaires were statistically analyzed. A total of 122 (70.5%) participants were identified as having depression (SDS ≥ 50 points). The median depression score was 62.5 (24.38), and the median PASE score was 69.29 (116.64). Multivariate logistic regression model results showed that physical activity and pain were the main risk factors for depression in older persons with osteoporosis (p < 0.05). Multivariate linear regression model results showed that gender, participation in social activities, activities of daily living status (ADLs), and depression status were the main risk factors associated with physical activity in older persons with osteoporosis (p < 0.05). The results of the correlation analysis showed that physical activity was negatively correlated with depression (R = -0.510, p = 0.000).

Conclusion

We found that depression was negatively correlated with physical activity in older persons with osteoporosis in China. This means that the less physical activity there is, the more serious the depression status and having depression may result in reduced physical activity in older persons with osteoporosis. To better help older persons with osteoporosis, medical staff should give more attention to influencing factors of depression and physical activity.

Composite dietary antioxidant intake and osteoporosis likelihood in premenopausal and postmenopausal women: a population-based study in the United States

OBJECTIVE

Osteoporosis is a skeletal disease characterized by low bone mass, reduced bone strength, and increased fracture risk. We aimed to investigate the association between combined dietary antioxidant intake and the likelihood of osteoporosis in premenopausal and postmenopausal women, based on data from the National Health and Nutrition Examination Survey.

METHODS

Nutrient intake data were obtained using two 24-hour recalls. Composite dietary antioxidant index (CDAI), which refers to the intake amounts of β-carotene, vitamin A, vitamin C, vitamin E, selenium, zinc, copper, and iron, was then constructed. Prevalent osteoporosis was defined according to bone mineral density T scores of ≤ -2.5 and self-reports. Multiple logistic and Poisson regression models were used for association analyses.

RESULTS

A total of 3,418 participants (1,157 premenopausal and 2,261 postmenopausal women) 40 years or older were included, 776 (22.70%) of whom had prevalent osteoporosis. In terms of individual nutrients, postmenopausal women in the highest CDAI quartiles for dietary β-carotene, vitamin A, vitamin C, and iron intakes had a low likelihood of osteoporosis. Regarding the CDAI-osteoporosis association, postmenopausal women in the highest quartile were less likely to have osteoporosis (OR Q3 vs Q1 , 0.64; 95% CI, 0.43-0.96; OR Q4 vs Q1 , 0.56; 95% CI, 0.35-0.89; P for trend = 0.013), after controlling for covariates.

CONCLUSIONS

CDAI was negatively associated with the likelihood of osteoporosis in postmenopausal women. Our findings suggest that the combined intake of antioxidant nutrients can help reduce the likelihood of osteoporosis in women.

Health-related quality of life, medical resource use and physical function in patients with diabetes mellitus and depression: A cross-sectional analysis from the National Health and Nutrition Examination Survey

BACKGROUND

Patients with either diabetes (DM) or depression (DP) are prone to developing other diseases and require more medical resources than do the general population. This study aimed to examine health-related quality of life, medical resource use, and physical function of patients with both diabetes mellitus and depression, and the magnitude of effects among patients with different combinations of comorbid diseases.

METHODS

A retrospective cross-sectional study was conducted using the National Health and Nutrition Examination Survey data from 2009 to 2014. Total 16,159 patients were studied and classified into one of 4 groups: both DM and DP(DM+/DP+), DM+/without DP(DP-), without DM (DM-)/DP+, and DM-/DP-, according to the perceived score in Patient Health Questionnaire and diabetes questionnaire in NHANES. Health-related quality of life (HRQoL), medical resource use, and physical function were measured as outcomes of interests. Multivariate logistic regression models were used.

RESULTS

Compared with DM-/DP- patients, the DM+/DP+ (adjusted odds ratio [AOR]: 2.59; 95 % CI: 1.77-3.80) and DM-/DP+ (AOR: 2.44; 95 % CI: 1.94-3.06) had greater likely to have worse health. In addition, the DM+/DP+ (AOR: 5.40; 95 % CI: 1.30-22.41) and DM+/DP- (AOR: 2.49; 95 % CI: 1.91-3.25) were more likely to have medical visits, and worse physical function.

CONCLUSIONS

This study found that both depression and diabetes mellitus worsen HRQoL, increase medical resource use, and decrease physical function. Depression status should be considered by clinicians treating diabetes mellitus patients in order to improve their HRQoL, reduce medical resource use, and improve physical function.

Food Insecurity is Associated With Mortality Among U.S. Adults With Nonalcoholic Fatty Liver Disease and Advanced Fibrosis

BACKGROUND & AIMS

Food insecurity is a growing public health challenge in the United States (U.S.) and has been linked to nonalcoholic fatty liver disease (NAFLD) and advanced fibrosis. However, little is known of how food insecurity impacts mortality risk and health care utilization in chronic liver disease.

METHODS

Using a population-based cohort study of U.S. adults (≥20 years) in the National Health and Nutrition Examination Survey, 1999 to 2014, with NAFLD (estimated by the U.S. Fatty Liver Index) and advanced fibrosis (estimated by the NAFLD fibrosis score, aspartate aminotransferase-to-platelet ratio index, or Fibrosis-4 Index), food security was measured using the Department of Agriculture Food Security Survey Module. The primary outcome was all-cause mortality from National Death Index data and the secondary outcome was health care utilization, defined as ≥2 inpatient and ≥4 outpatient visits, with Cox and logistic regression, respectively, estimating associations between food insecurity and outcomes.

RESULTS

Of 34,134 eligible participants (mean age, 47 years; 51% women; 14% in poverty), 4816 had NAFLD and 1654 had advanced fibrosis, with food insecurity present in 28% and 21%, respectively. All-cause age-adjusted mortality was 12 per 1000 person-years among participants with NAFLD (food-secure, 11; food-insecure, 15) and 32 per 1000 person-years among advanced fibrosis participants (food-secure, 28; food-insecure, 50). In multivariable analyses, food insecurity was independently associated with higher mortality among participants with NAFLD (hazard ratio, 1.46; 95% confidence interval [CI], 1.08-1.97) and advanced fibrosis (hazard ratio, 1.37; 95% CI, 1.01-1.86) and greater outpatient health care utilization in participants with NAFLD (odds ratio, 1.32; 95% CI, 1.05-1.67).

CONCLUSIONS

Food insecurity is significantly associated with greater all-cause mortality in adults with NAFLD and advanced fibrosis. Interventions that address food insecurity among adults with liver disease should be prioritized to improve health outcomes in this population.

Association between bipolar affective disorder, use of antidepressants and osteoporosis

Introduction/Objective. Osteoporosis is one of the most common comorbid disorders in depressive mood disorder. The aim of this study was to assess the association between the use of antidepressants and osteoporosis in patients with bipolar affective disorder (BPAD). Methods. The study included 73 inpatients, aged 50?72 years, male and female, hospitalized with a depressive episode of BPAD from 2016 to 2020 at the Clinic of Psychiatry, Clinical Centre of Vojvodina, divided into two groups: a) the first group (40) was treated with selective serotonin reuptake inhibitors (SSRIs) in combination with mood stabilizer (lithium carbonate/lamotrigine); b) the second group (33) was treated with mood stabilizer only. Study included two control groups as well. Clinical measurements of bone mineral density at lumbar spine and hip was made using dual energy X-ray absorptiometry. CrossLaps and levels of calcium and vitamin D were collected from blood samples. The data was analyzed by the analysis of variance and the Kruskal?Wallis test. Results. Osteoporosis was registered in 25% of patients in the first group and in 18% of patients in the second group, while osteopenia was observed within 40% of patients in the first group and in 37% of patients in the second group. There was significant difference in value of CrossLaps, and the level of 25(OH)D vitamin between the control groups and the first two groups, as well as in prevalence of osteoporosis and osteopenia. Conclusion. Depressive episodes in BPAD is connected with higher prevalence of osteoporosis. Patients treated with SSRIs have higher prevalence of osteoporosis than patients treated with mood stabilizers only.

Big Data, Decision Models, and Public Health

Unlike most daily decisions, medical decision making often has substantial consequences and trade-offs. Recently, big data analytics techniques such as statistical analysis, data mining, machine learning and deep learning can be applied to construct innovative decision models. With complex decision making, it can be difficult to comprehend and compare the benefits and risks of all available options to make a decision. For these reasons, this Special Issue focuses on the use of big data analytics and forms of public health decision making based on the decision model, spanning from theory to practice. A total of 64 submissions were carefully blind peer reviewed by at least two referees and, finally, 23 papers were selected for this Special Issue.

Bone Metabolism and Vitamin D Implication in Gastroenteropancreatic Neuroendocrine Tumors

Patients affected by gastroenteropancreatic–neuroendocrine tumors (GEP–NETs) have an increased risk of developing osteopenia and osteoporosis, as several factors impact on bone metabolism in these patients. In fact, besides the direct effect of bone metastasis, bone health can be affected by hormone hypersecretion (including serotonin, cortisol, and parathyroid hormone-related protein), specific microRNAs, nutritional status (which in turn could be affected by medical and surgical treatments), and vitamin D deficiency. In patients with multiple endocrine neoplasia type 1 (MEN1), a hereditary syndrome associated with NET occurrence, bone damage may carry other consequences. Osteoporosis may negatively impact on the quality of life of these patients and can increment the cost of medical care since these patients usually live with their disease for a long time. However, recommendations suggesting screening to assess bone health in GEP–NET patients are missing. The aim of this review is to critically analyze evidence on the mechanisms that could have a potential impact on bone health in patients affected by GEP–NET, focusing on vitamin D and its role in GEP–NET, as well as on factors associated with MEN1 that could have an impact on bone homeostasis.