Associations of Demographic and Social Factors on Health-Related Quality-of-Life Changes Among Older Women With Breast or Gynecologic Cancer.

OBJECTIVES: To examine associations of sociodemographic factors and social limitations with health-related quality of life (HRQOL) from pre- to postdiagnosis in older female cancer survivors. SAMPLE & SETTING: 9,807 women aged 65 years or older with breast or gynecologic cancer from the Surveillance, Epidemiology, and End Results-Medicare Health Outcomes Survey. METHODS & VARIABLES: Physical and mental HRQOL were assessed using the physical component summary (PCS) and mental component summary (MCS) of the Veterans RAND 12-Item Health Survey. Descriptive statistics and mixed-effects models for repeated measures were used. RESULTS: Social limitations were the only significant factor associated with changes in MCS scores. Race and ethnicity, rurality, and social interference were associated with significant decreases in PCS scores. IMPLICATIONS FOR NURSING: Nurses can assess mental and physical HRQOL after diagnosis and advocate for appropriate referrals. Oncology care should be tailored to cultural considerations, including race and ethnicity, rurality, and social support.

The burden of premature adult mortality associated with lack of access to electricity in India.

BACKGROUND: The impact of electricity access on all-cause premature mortality is unknown. METHODS: We use a national dataset from India to compare districts with high access to electricity (>90% of households) to districts with middle (50-90%) and low (<50%) access to electricity and estimate the effect of lack of electricity access on all-cause premature mortality. RESULTS: In 2014, out of 597 districts in India, 174 districts had high access, 228 had middle access, and 195 had low access to electricity. When compared to districts with high access, districts with low access had higher rates of age-standardized premature mortality in both women (2.09, 95% CI: 1.43-2.74) and men (0.99, 0.10-1.87). Similarly, these districts had higher rates of conditional probability of premature death in both women (9.16, 6.19-12.13) and men (4.04, 0.77-7.30). Middle access districts had higher rates of age-standardized premature mortality and premature death in women, but not men. The total excess deaths attributable to reduced electricity access were 444,225 (45,195 in middle access districts and 399,030 in low access districts). In low access districts, the proportion of premature adult deaths attributable to low electricity access was 21.3% (14.4%- 28.1%) in women and 7.9% (1.5%- 14.3%) in men. CONCLUSION: Poor access to electricity is associated with nearly half a million premature adult deaths. One out of five premature deaths in adult women were linked to low electricity access making it a major social determinant of health.

Hierarchy of demographic and social determinants of mental health: analysis of cross-sectional survey data from the Global Mind Project.

OBJECTIVES: To understand the extent to which various demographic and social determinants predict mental health status and their relative hierarchy of predictive power in order to prioritise and develop population-based preventative approaches. DESIGN: Cross-sectional analysis of survey data. SETTING: Internet-based survey from 32 countries across North America, Europe, Latin America, Middle East and North Africa, Sub-Saharan Africa, South Asia and Australia, collected between April 2020 and December 2021. PARTICIPANTS: 270 000 adults aged 18-85+ years who participated in the Global Mind Project. OUTCOME MEASURES: We used 120+ demographic and social determinants to predict aggregate mental health status and scores of individuals (mental health quotient (MHQ)) and determine their relative predictive influence using various machine learning models including gradient boosting and random forest classification for various demographic stratifications by age, gender, geographical region and language. Outcomes reported include model performance metrics of accuracy, precision, recall, F1 scores and importance of individual factors determined by reduction in the squared error attributable to that factor. RESULTS: Across all demographic classification models, 80% of those with negative MHQs were correctly identified, while regression models predicted specific MHQ scores within ±15% of the position on the scale. Predictions were higher for older ages (0.9+ accuracy, 0.9+ F1 Score; 65+ years) and poorer for younger ages (0.68 accuracy, 0.68 F1 Score; 18-24 years). Across all age groups, genders, regions and language groups, lack of social interaction and sufficient sleep were several times more important than all other factors. For younger ages (18-24 years), other highly predictive factors included cyberbullying and sexual abuse while not being able to work was high for ages 45-54 years. CONCLUSION: Social determinants of traumas, adversities and lifestyle can account for 60%-90% of mental health challenges. However, additional factors are at play, particularly for younger ages, that are not included in these data and need further investigation.

Ecological and social factors influence interspecific pathogens occurrence among bees.

The interspecific transmission of pathogens can occur frequently in the environment. Among wild bees, the main spillover cases are caused by pathogens associated with Apis mellifera, whose colonies can act as reservoirs. Due to the limited availability of data in Italy, it is challenging to accurately assess the impact and implications of this phenomenon on the wild bee populations. In this study, a total of 3372 bees were sampled from 11 Italian regions within the BeeNet project, evaluating the prevalence and the abundance of the major honey bee pathogens (DWV, BQCV, ABPV, CBPV, KBV, Nosema ceranae, Ascosphaera apis, Crithidia mellificae, Lotmaria passim, Crithidia bombi). The 68.4% of samples were positive for at least one pathogen. DWV, BQCV, N. ceranae and CBPV showed the highest prevalence and abundance values, confirming them as the most prevalent pathogens spread in the environment. For these pathogens, Andrena, Bombus, Eucera and Seladonia showed the highest mean prevalence and abundance values. Generally, time trends showed a prevalence and abundance decrease from April to July. In order to predict the risk of infection among wild bees, statistical models were developed. A low influence of apiary density on pathogen occurrence was observed, while meteorological conditions and agricultural management showed a greater impact on pathogen persistence in the environment. Social and biological traits of wild bees also contributed to defining a higher risk of infection for bivoltine, communal, mining and oligolectic bees. Out of all the samples tested, 40.5% were co-infected with two or more pathogens. In some cases, individuals were simultaneously infected with up to five different pathogens. It is essential to increase knowledge about the transmission of pathogens among wild bees to understand dynamics, impact and effects on pollinator populations. Implementing concrete plans for the conservation of wild bee species is important to ensure the health of wild and human-managed bees within a One-Health perspective.

Energy and social factor decomposition to identify drivers impeding sustainable environmental transition in emerging countries: SDGs-2030 progress assessment using LMDI analysis.

The balance between human growth, economic prosperity, and the consumption of hydrocarbon energy factors has become a prerequisite for environmental sustainability. However, the complexities of these factors force researchers to work for more viable combinations of such a balance. Therefore, this study attempted to determine the factors driving environmental sustainability in leading populated economies. For this purpose, the Logarithmic Mean Division Index (LMDI) utilized to decompose critical factors such as activity, economy, real density, energy intensity, and suburban effects for the period 1999-2022. Both population and its consequences (economic activity) have been found to be the leading factors behind environmental fluctuations, and energy has a negative impact on hydrocarbon forms, while contributing positively to environmental sustainability with high efficiency and low intensity. Therefore, sustainable demographic and energy transitions can be leading pathways for environmental sustainability in developing economies.

Addressing the Impact of Race and Ethnicity on Musculoskeletal Spine Care in the United States.

➤ Despite being a social construct, race has an impact on outcomes in musculoskeletal spine care.➤ Race is associated with other social determinants of health that may predispose patients to worse outcomes.➤ The musculoskeletal spine literature is limited in its understanding of the causes of race-related outcome trends.➤ Efforts to mitigate race-related disparities in spine care require individual, institutional, and national initiatives.

The regulation of social factors on anxiety and microglial activity in nucleus accumbens of adolescent male mice: Influence of social interaction strategy.

BACKGROUND: Adolescence is a period characterized by a high vulnerability to emotional disorders, which are modulated by biological, psychological, and social factors. However, the underlying mechanisms remain poorly understood. METHODS: Combining physical or emotional social defeat stress (PS and ES) and pair or isolation rearing conditions, we investigated the effects of stress type and social support on emotional behavior and central immune molecules in adolescent mice, including anxiety, social fear, and social interaction strategies, as well as changes in microglia-specific molecules (ionized calcium-binding adaptor molecule 1 (Iba1) and a cluster of differentiation molecule 11b (CD11b)) in the medial prefrontal cortex (mPFC), hippocampus (HIP), amygdala (AMY), and nucleus accumbens (NAc). RESULTS: Mice exposed to both physical stress and isolated rearing condition exhibited the highest levels of anxiety, social fear, and microglial CD11b expression in the NAc. In terms of social support, pair-housing with siblings ameliorated social fear and NAc molecular changes in ES mice, but not in PS mice. The reason for the differential benefit from social support was attributed to the fact that ES mice exhibited more active and less passive social strategies in social environment compared to PS mice. Further, the levels of stress-induced social fear were positively associated with the expression of microglial CD11b in the NAc. CONCLUSION: These findings offer extensive evidence regarding the intricate effects of multiple social factors on social anxiety and immune alteration in the NAc of adolescent mice. Additionally, they suggest potential behavioral and immune intervention strategies for anxiety-related disorders in adolescents.

Carbon sinks/sources' spatiotemporal heterogeneity and their spatial response to economic-social factors in relatively developed regions: A case of China's coastal area.

With the global climate change, carbon reduction in economically active regions has gradually become a focus of attention and its underlying drivers were essential for understanding alterations in ecosystems in response to human behavior. However, the exploration of Carbon Sinks/Sources Patterns (CSSP) in an Economic-Social context was lacking. Distinguished from traditional Net Ecosystem Productivity (NEP) estimation methods, we optimized model parameters, adjusted estimation logic, and revealed CSSP more reasonably. Moreover, spatial econometric model was used to reveal the spatial effects mechanism of Economic-Social Development on CSSP. Over the past 20 years, we revealed that: (a) The pattern of NEP exhibited distinct spatial heterogeneity, with higher sinks observed in the north and offshore regions. It demonstrated regular cyclic fluctuations, averaging a 3-4-year cycle, featuring a gradual ascent followed by a rapid descent; (b) The Carbon Sequestration Capacity (CSC) of vegetation significantly increased. Based on the carbon sink properties, the study area was distinctly divided into three clusters; (c) CSSP have been profoundly affected by economic-social factors. Economic growth and industrial structure optimization contributed to the enhancement of CSC, but population aggregation and urban expansion had negative impacts. The direct effect of innovation capacity and the spatial spillover effect of industrial structure optimization were negative. Overall, exploring CSSP against the backdrop of economic-social factors not only provides a new perspective for understanding the regularities of change and the underlying mechanisms driven by human factors but also offers valuable insights for achieving sustainable development and green growth in other coastal regions globally.

Social factors associated with self-reported changes in mental health symptoms among youth in the COVID-19 pandemic: a cross-sectional survey.

BACKGROUND: Children and youth experienced marked impacts on day-to-day life in the COVID-19 pandemic that were associated with poorer familial and friend relationships, and greater mental health challenges. Few studies provide self-report data on mental health symptoms from children and youth themselves. We sought to examine the associations between social factors and child and youth self-reported symptoms of worsened mood, anxiety, and irritability during the COVID-19 pandemic. METHODS: A nationally representative cross-sectional survey was administered online to collect self-report data across 10 Canadian provinces among children (11-14 years) and youth (15-18 years), April-May 2022. Age-appropriate questions were based on The Partnership for Maternal, Newborn & Child Health and the World Health Organization of the United Nations H6 + Technical Working Group on Adolescent Health and Well-Being consensus framework and the Coronavirus Health and Impact Survey. Associations between a priori defined social factors (e.g., relationship quality) and respondent self-reported mental health were evaluated using ordinal logistic regression models adjusted for age, sex, and geographic location. RESULTS: We analyzed data from 483 (51.7%) children (11-14 years; 227, 47.0% girls) and 450 (48.3%) youth (15-18 years; 204, 45.3% girls). The parents of most children and youth had resided in Canada for over 20 years (678, 72.7%). Over one-quarter of children and youth self-identified as Black, Indigenous, or a Person of Color (134, 27.7%; 134, 29.8%, respectively). Over one-third of children and youth self-reported symptoms of worsened mood (149, 30.9%; 125, 27.8%, respectively), anxiety (181, 37.5%; 167, 37.1%, respectively), or irritability (160, 33.1%; 160, 35.6%, respectively) during, compared to pre-pandemic. In descending order of odds ratios (OR), for children and youth, worsened familial relationships (during compared to pre-pandemic) was associated with the self-reported symptoms of worsened mood (child: OR 4.22, 95%CI 2.51-6.88; youth: OR 6.65 95%CI 3.98-11.23), anxiety (child: OR 4.24, 95%CI2.69-6.75; youth: OR 5.28, 95%CI 3.17-8.86), and irritability (child: OR 2.83, 95%CI 1.76-4.56; youth: OR 6.46, 95%CI 3.88-10.90). CONCLUSIONS: Self-reported data from a nationally representative sample of children and youth suggest strong associations between social factors and mental health during the COVID-19 pandemic. Interventions targeting child and youth familial relationships may positively impact child and youth mental health.

Social factors and age play a significant role in cervical cancer and advanced-stage disease among Danish women.

BACKGROUND: For cervical cancer (CC), the implementation of preventive strategies has the potential to make cervical cancer occurrence and death largely avoidable. To better understand the factors possibly responsible for cervical cancer, we aimed to examine possible differences in age and social parameters as well as screening status between women with low- or high-stage cervical cancer and matched controls. METHODS: Through the Danish Cancer Registry (DCR), women diagnosed with cervical cancer in Denmark between 1987 and 2016 were included. These were age- and residence-matched in a 1:5 ratio with controls from the general female population. The study population was sub grouped into a low-stage subpopulation with women with early-stage cervical cancer and matched controls and a high-stage subpopulation with women with late-stage cervical cancer and matched controls. Age and social parameters were compared within the subpopulations as well as between low- and high-stage cases. For part of the study population, screening attendance was examined to compare differences in adherence. RESULTS: Overall, we found that the risk of cervical cancer is significantly increased in socially disadvantaged women and not least non-attenders in screening. Interestingly, the high-stage subpopulation was significantly older than the low-stage subpopulation (p < 0.001), and when examining the impact of age further, we found that for cervical cancer cases, the risk of having low-stage disease decreases significantly with increasing age, whereas the risk of having high-stage disease increases significantly with increasing age. In the screening cohort, significantly less cases than controls were attenders in screening with the most pronounced differences seen in the old subpopulation (women aged 50-64 years) and in the high-stage subpopulation (p-values all < 0.001). Interestingly, when examining the risk of CC for attenders and non-attenders, we demonstrated that many social parameters continue to influence the risk of cervical cancer, even in women attending screening. CONCLUSIONS: Older women, socially disadvantaged women, and non-attenders in screening are particularly vulnerable in terms of developing cervical cancer, especially high-stage disease. Therefore, improvements in the participating rate in screening as well as a revision of the current screening guidelines are needed.

Microbial transmission in the social microbiome and host health and disease.

Although social interactions are known to drive pathogen transmission, the contributions of socially transmissible host-associated mutualists and commensals to host health and disease remain poorly explored. We use the concept of the social microbiome-the microbial metacommunity of a social network of hosts-to analyze the implications of social microbial transmission for host health and disease. We investigate the contributions of socially transmissible microbes to both eco-evolutionary microbiome community processes (colonization resistance, the evolution of virulence, and reactions to ecological disturbance) and microbial transmission-based processes (transmission of microbes with metabolic and immune effects, inter-specific transmission, transmission of antibiotic-resistant microbes, and transmission of viruses). We consider the implications of social microbial transmission for communicable and non-communicable diseases and evaluate the importance of a socially transmissible component underlying canonically non-communicable diseases. The social transmission of mutualists and commensals may play a significant, under-appreciated role in the social determinants of health and may act as a hidden force in social evolution.

Social Determinants of Health Screening in Type 1 Diabetes Management.

Type 1 diabetes management is intricately influenced by social determinants of health. Economic status impacts access to vital resources like insulin and diabetes technology. Racism, social injustice, and implicit biases affect equitable delivery of care. Education levels affect understanding of self-care, leading to disparities in glycemic outcomes. Geographic location can limit access to health care facilities. Stressors from discrimination or financial strain can disrupt disease management. Addressing these social factors is crucial for equitable diabetes care, emphasizing the need for comprehensive strategies that go beyond medical interventions to ensure optimal health outcomes for all individuals with type 1 diabetes.

Climate-Informed Patient Care as a Social Determinant of Health.

This JAMA Forum discusses the implications for patient care by recognizing climate change as a social determinant of health.

The Impact of Biological and Social Factors on Mortality in Older Adults Living in Rural Communities.

BACKGROUND: Information on factors that increase mortality in remote settings is limited. This study aims to estimate the independent and joint role of several factors on mortality risk among older adults living in rural Ecuador. METHODS: Participants were selected from community-dwelling older adults who were included in previous studies targeting mortality risk factors in the study population. Generalized structural equation modeling (GSEM) was utilized to evaluate prior causal assumptions, to redraw causal links, and to introduce latent variables that may help to explain how the independently significant variables are associated with mortality. RESULTS: The study included 590 individuals (mean age: 67.9 ± 7.3 years; 57% women), followed for a median of 8.2 years. Mortality rate was 3.4 per 100 person-years. Prior work on separate multivariate Poisson and Cox models was used to build a tentative causal construct. A GSEM containing all variables showed that age, symptoms of depression, high social risk, high fasting glucose, a history of overt stroke, and neck circumference were directly associated with mortality. Two latent variables were introduced, 1 representing the impact of biological factors and another, the impact of social factors on mortality. The social variable significantly influenced the biological variable which carried most of the direct effect on mortality. CONCLUSIONS: Several factors contributed to mortality risk in the study population, the most significant being biological factors which are highly influenced by social factors. High social risk interact with biological variables and play an important role in mortality risk.

Measuring Associations Between Community-Level Social Determinants of Health and Bariatric Surgery Weight Loss Outcomes.

Bariatric surgery is a crucial intervention in managing obesity and related conditions. However, weight loss outcomes can vary significantly, and social determinants of health (SDoH) at the community level may play a role. Our objective is to identify community-level SDoH factors associated with reduced weight loss after bariatric surgery. We conducted an analysis of electronic health records and the social vulnerability index (SVI) of 3,800 patients who underwent bariatric surgery at Vanderbilt University Medical Center. We measured the associations between SVI social factors and the percent change in body mass index three months after surgery using linear regression. The SVI factors with a false discovery rate-adjusted p-value < 0.05 were deemed significant. Statistical results show that patients who reside in communities with racial minority groups or lower insurance rates had reduced weight loss three months after surgery.

Social Determinants of Health and Preoperative Care.

Preoperative care exists as part of perioperative continuum during which anesthesiologists and surgeons optimize patients for surgery. These multispecialty efforts are important, particularly for patients with complex medical histories and those requiring major surgery. Preoperative care improves planning and determines the clinical pathway and discharge disposition. The role of nonmedical social factors in the preoperative planning is not well described in anesthesiology. Research to improve outcomes based on social factors is not well described for anesthesiologists but could be instrumental in decreasing disparities and advancing health equity in surgical patients.

Does the number of social factors affect long-term patient-reported outcomes and satisfaction in those with cervical myelopathy? A QOD study.

OBJECTIVE: It is not clear whether there is an additive effect of social factors in keeping patients with cervical spondylotic myelopathy (CSM) from achieving both a minimum clinically important difference (MCID) in outcomes and satisfaction after surgery. The aim of this study was to explore the effect of multiple social factors on postoperative outcomes and satisfaction. METHODS: This was a multiinstitutional, retrospective study of the prospective Quality Outcomes Database (QOD) CSM cohort, which included patients aged 18 years or older who were diagnosed with primary CSM and underwent operative management. Social factors included race (White vs non-White), education (high school or below vs above), employment (employed vs not), and insurance (private vs nonprivate). Patients were considered to have improved from surgery if the following criteria were met: 1) they reported a score of 1 or 2 on the North American Spine Society index, and 2) they met the MCID in patient-reported outcomes (i.e., visual analog scale [VAS] neck and arm pain, Neck Disability Index [NDI], and EuroQol-5D [EQ-5D]). RESULTS: Of the 1141 patients included in the study, 205 (18.0%) had 0, 347 (30.4%) had 1, 334 (29.3%) had 2, and 255 (22.3%) had 3 social factors. The 24-month follow-up rate was > 80% for all patient-reported outcomes. After adjusting for all relevant covariates (p < 0.02), patients with 1 or more social factors were less likely to improve from surgery in all measured outcomes including VAS neck pain (OR 0.90, 95% CI 0.83-0.99) and arm pain (OR 0.88, 95% CI 0.80-0.96); NDI (OR 0.90, 95% CI 0.83-0.98); and EQ-5D (OR 0.90, 95% CI 0.83-0.97) (all p < 0.05) compared to those without any social factors. Patients with 2 social factors (outcomes: neck pain OR 0.86, arm pain OR 0.81, NDI OR 0.84, EQ-5D OR 0.81; all p < 0.05) or 3 social factors (outcomes: neck pain OR 0.84, arm pain OR 0.84, NDI OR 0.84, EQ-5D OR 0.84; all p < 0.05) were more likely to fare worse in all outcomes compared to those with only 1 social factor. CONCLUSIONS: Compared to those without any social factors, patients who had at least 1 social factor were less likely to achieve MCID and feel satisfied after surgery. The effect of social factors is additive in that patients with a higher number of factors are less likely to improve compared to those with only 1 social factor.

Prevalence and associated factors for depressive symptoms among the general population from 31 provinces in China: The utility of social determinants of health theory.

BACKGROUND: Depression is one of the most common types of mental disorders. Guided by the theory of social determinants of health (SDH), the study aimed to assess the prevalence of depressive symptoms and to identify factors related to depressive symptoms in the general population of China. METHODS: A cross-sectional, online survey was conducted among 101,392 residents from 31 provinces of mainland China from January to March 2019, and 97,126 survey responses were included in the final analysis. Multilevel linear regression models were used to identify SDH associated with depressive symptoms. RESULTS: The prevalence of depressive symptoms (PHQ-9 scores ≥10) in Chinese residents was 15.81 %. The results of the multilevel analysis demonstrated that depressive symptoms were affected by various factors on five levels, including individual characteristics, behavioral lifestyle, community support network, social structural factors, and macro social factors. LIMITATIONS: The cross-sectional design of the study makes it difficult to establish causality between variables. CONCLUSIONS: The prevalence of depressive symptoms is high among general population in China. According to the theory of SDH, the study shows that the depressive symptoms are complex and involves all areas of social life. Therefore, adopting a multi-level, cross-sectoral intervention approach will be instrumental to improving the mental health of residents in China.

Development and validation of a community-level social determinants of health index for drug overdose deaths in the HEALing Communities Study.

INTRODUCTION: Social determinants of health (SDoH), such as socioeconomic status, education level, and food insecurity, are believed to influence the opioid crisis. While global SDoH indices such as the CDC's Social Vulnerability Index (SVI) and Area Deprivation Index (ADI) combine the explanatory power of multiple social factors for understanding health outcomes, they may be less applicable to the specific challenges of opioid misuse and associated outcomes. This study develops a novel index tailored to opioid misuse outcomes, tests the efficacy of this index in predicting drug overdose deaths across contexts, and compares the explanatory power of this index to other SDoH indices. METHODS: Focusing on four HEALing Communities Study (HCS) states (Kentucky, Massachusetts, New York and Ohio; encompassing 4269 ZIP codes), we identified multilevel SDoH potentially associated with opioid misuse and aggregated publicly available data for each measure. We then leveraged a random forest model to develop a composite measure that predicts age-adjusted drug overdose mortality rates based on SDoH. We used this composite measure to understand HCS and non-HCS communities in terms of overdose risk across areas of varying racial composition. Finally, we compared variance in drug overdose deaths explained by this index to variance explained by the SVI and ADI. RESULTS: Our composite measure included 28 SDoH measures and explained approximately 89 % percent of variance in age-adjusted drug overdose mortality across HCS states. Health care measures, including emergency department visits and primary care provider availability, were top predictors within the index. Index accuracy was robust within and outside of HCS communities and states. This measure identified high levels of overdose mortality risk in segregated communities. CONCLUSIONS: Existing SDoH indices fail to explain much variation in area-level overdose mortality rates. Having tailored composite indices can help us to identify places in which residents are at highest risk based on their composite contexts. A comprehensive index can also help to develop effective community interventions for programs such as HCS by considering the context in which people live.