The impact of socioeconomic position on non-communicable diseases: what do we know about it?

Epidemiological breast cancer prediction by country: A novel machine learning approach

Breast cancer remains a significant contributor to cancer-related deaths among women globally. We seek for this study to examine the correlation between the incidence rates of breast cancer and newly identified risk factors. Additionally, we aim to utilize machine learning models to predict breast cancer incidence at a country level. Following an extensive review of the available literature, we have identified a range of recently studied risk factors associated with breast cancer. Subsequently, we gathered data on these factors and breast cancer incidence rates from numerous online sources encompassing 151 countries. To evaluate the relationship between these factors and breast cancer incidence, we assessed the normality of the data and conducted Spearman's correlation test. Furthermore, we refined six regression models to forecast future breast cancer incidence rates. Our findings indicate that the incidence of breast cancer is most positively correlated with the average age of women in a country, as well as factors such as meat consumption, CO2 emissions, depression, sugar consumption, tobacco use, milk intake, mobile cells, alcohol consumption, pesticides, and oral contraceptive use. As for prediction, the CatBoost Regressor successfully predicted future breast cancer incidence with an R squared value of 0.84 ± 0.03. An increased incidence of breast cancer is mainly associated with dietary habits and lifestyle. Our findings and recommendations can serve as a baseline for developing educational programs intended to heighten awareness amongst women in countries with heightened risk.

Exploring the variation in associations between socioeconomic indicators and non-communicable diseases in the Tromsø Study: an algorithmic approach

AIMS

We contribute to the methodological literature on the assessment of health inequalities by applying an algorithmic approach to evaluate the capabilities of socioeconomic variables in predicting the prevalence of non-communicable diseases in a Norwegian health survey.

METHODS

We use data from the seventh survey of the population based Tromsø Study (2015-2016), including 11,074 women and 10,009 men aged 40 years and above. We apply the random forest algorithm to predict four non-communicable disease outcomes (heart attack, cancer, diabetes and stroke) based on information on a number of social root causes and health behaviours. We evaluate our results using the classification error, the mean decrease in accuracy, partial dependence statistics.

RESULTS

Results suggest that education, household income and occupation to a variable extent contribute to predicting non-communicable disease outcomes. Prediction misclassification ranges between 25.1% and 35.4% depending on the non-communicable diseases under study. Partial dependences reveal mostly expected health gradients, with some examples of complex functional relationships. Out-of-sample model validation shows that predictions translate to new data input.

CONCLUSIONS

Algorithmic modelling can provide additional empirical detail and metrics for evaluating heterogeneous inequalities in morbidity. The extent to which education, income and occupation contribute to predicting binary non-communicable disease outcomes depends on both non-communicable diseases and socioeconomic indicator. Partial dependences reveal that social gradients in non-communicable disease outcomes vary in shape between combinations of non-communicable disease outcome and socioeconomic status indicator. Misclassification rates highlight the extent of variation within socioeconomic groups, suggesting that future studies may improve predictive accuracy by exploring further subpopulation heterogeneity.

Identification of nutrition factors in the metabolic syndrome and its progression over time in older adults: analysis of the TUDA cohort

BACKGROUND

Nutrition is recognized as playing an important role in the metabolic syndrome (MetS), but the dietary components involved are unclear. We aimed to investigate nutrition factors in relation to MetS and its progression in older adults over a follow-up period of 5.4 years.

METHODS

Community-dwelling adults (≥ 60y) from the Trinity-Ulster-Department-of-Agriculture study, sampled at baseline (2008-12) and follow-up (2014-18; n 953), were classified as 'with MetS' by having three or more of: waist circumference (≥ 102 cm, males; ≥ 88 cm, females); HDL-cholesterol (< 1.0 mmol/L, males; < 1.3 mmol/L, females); triglycerides (≥ 1.7 mmol/L); blood pressure (systolic ≥ 130 and/or diastolic ≥ 85 mmHg); and hemoglobin A1c (≥ 39 mmol/mol).

RESULTS

MetS was identified in 67% of participants, increasing to 74% at follow-up. Predictors at baseline for the development of metabolic syndrome (MetS) at follow-up were higher waist circumference (odds ratio [95%CI]; 1.06 [1.01-1.11]), but not BMI, and increased triglyceride concentrations (2.01 [1.29-3.16]). In dietary analysis (at follow-up), higher protein (g/kg bodyweight/day) and monounsaturated fatty acid (g/day) intakes were each associated with lower risk of MetS (0.06 [0.02-0.20] and 0.88 [0.78-1.00], respectively), whilst higher protein was also associated with lower abdominal obesity (0.10 [0.02-0.51]) and hypertension (0.22 [0.00-0.80]). Furthermore, participants with, compared to without, MetS consumed less high-quality protein foods (P = 0.006) and more low-quality protein foods (P < 0.001), as defined by the protein digestibility-corrected amino acid score.

CONCLUSIONS

Dietary interventions targeting protein quantity and quality may have specific benefits in preventing or delaying the progression of MetS in at-risk older people, but this requires investigation in the form of randomized trials.

Perspectives for the Prevention of Noncommunicable Diseases in Tanzania: Is Knowledge Translated into Practice?

Background

In Tanzania, where over a third of the society is impoverished, the burden of NCDs which account for about two-fifths of all disability-adjusted life years (DALYs) and one-third of premature deaths has doubled in the past two decades. However, notwithstanding a wider realization of the escalating burden of NCDs across Tanzania, the link between NCD awareness and lifestyle practices at the population level is not well characterized. We aimed to establish the gap between NCD knowledge and healthy behaviors.

Methods

This multi-regional community-based cross-sectional study was conducted in 5 regions of Tanzania between September 2022 and June 2023. A 22-item standardized tool evaluating various NCD risk behaviors was used in knowledge assessment and a cut-off of ≥70% was used to denote good knowledge. Bivariate analyses were performed to compare knowledge of NCD risk factors across various NCD risk subgroups. All tests were two tailed, and the significance was set at p<0.05.

Results

A total of 5121 individuals were consecutively enrolled. The mean age was 47.2 years and females comprised over three-fifths (60.8%) of the participants. With regard to behavioral NCD risks, physical inactivity, unhealthy diet, smoking and alcohol consumption were present in 79.0%, 70.2%, 2.1% and 17.6% of participants, respectively. Moreover, biological risk factors, ie, excess body weight, hypertension, and diabetes were present in 68.4%, 55.8% and 13.0% of participants, respectively. The mean knowledge score was 77.1% and 70.3% of participants demonstrated good knowledge of NCD risk factors. Except for smoking, individuals who showed awareness of various NCD risk factors were found to have significant rates of risky behaviors.

Conclusion

Despite sufficient NCD risk knowledge, incongruent lifestyle practices persist, highlighting a crucial concern. This suggests that awareness of NCDs and their risks may influence motivation for change but may not necessarily result in lifestyle modification.

Social inequality in prevalence of NCD risk factors: a cross-sectional analysis from the population-based Tromsø Study 2015-2016

OBJECTIVE

We aimed to examine associations between educational level, serving as an indicator of socioeconomic position, and prevalence of WHO-established leading behavioural and biological risk factors for non-communicable diseases (NCDs), in middle-aged to older women and men.

DESIGN

Population-based cross-sectional study.

SETTING

All inhabitants of the municipality of Tromsø, Norway, aged ≥40 years, were invited to the seventh survey (2015-2016) of the Tromsø Study; an ongoing population-based cohort study.

PARTICIPANTS

Of the 32 591 invited; 65% attended, and a total of 21 069 women (53%) and men aged 40-99 years were included in our study.

OUTCOME MEASURES

We assessed associations between educational level and NCD behavioural and biological risk factors: daily smoking, physical inactivity (sedentary in leisure time), insufficient fruit/vegetable intake (<5 units/day), harmful alcohol use (>10 g/day in women, >20 g/day in men), hypertension, obesity, intermediate hyperglycaemia and hypercholesterolaemia. These were expressed as odds ratios (OR) per unit decrease in educational level, with 95% CIs, in women and men.

RESULTS

In women (results were not significantly different in men), we observed statistically significant associations between lower educational levels and higher odds of daily smoking (OR 1.69; 95% CI 1.60 to 1.78), physical inactivity (OR 1.38; 95% CI 1.31 to 1.46), insufficient fruit/vegetable intake (OR 1.54, 95% CI 1.43 to 1.66), hypertension (OR 1.25; 95% CI 1.20 to 1.30), obesity (OR 1.23; 95% CI 1.18 to 1.29), intermediate hyperglycaemia (OR 1.12; 95% CI 1.06 to 1.19), and hypercholesterolaemia (OR 1.07; 95% CI 1.03 to 1.12), and lower odds of harmful alcohol use (OR 0.75; 95% CI 0.72 to 0.78).

CONCLUSION

We found statistically significant educational gradients in women and men for all WHO-established leading NCD risk factors within a Nordic middle-aged to older general population. The prevalence of all risk factors increased at lower educational levels, except for harmful alcohol use, which increased at higher educational levels.

Finance, race, ethnicity, and spoken language impact clinical outcomes for children with acute liver failure

BACKGROUND

Pediatric acute liver failure (PALF) is an emergency, necessitating prompt referral and management at an experienced liver transplant center. Social determinants of health (SDOH) drive healthcare disparities and can affect many aspects of disease presentation, access to care, and ultimately clinical outcomes. Potential associations between SDOH and PALF outcomes, including spontaneous recovery (SR), liver transplant (LT) or death, are unknown. This study aims to investigate how SDOH may affect PALF and therefore identify areas for intervention to mitigate unrecognized disparities.

METHODS

A retrospective, single-center cohort was analyzed and then compared and validated with data from the multicenter National Institutes of Health PALF Study Group. The single-center review included 145 patients admitted with PALF using diagnostic codes. Medical records were reviewed to extract patient demographics, family structure, inpatient social worker assessments, and clinical outcomes. Data were stratified by outcome.

RESULTS

This analysis determined that level of family support (p = .02), caretaker employment (p = .02), patient age, race, and language (p = .01) may impact clinical outcomes. Specifically, the cohort of children that died had the largest proportion of non-English speaking patients with limited support systems and parents who worked full-time. Conversely, patients who underwent LT more often belonged to English-speaking families with a homemaker and extensive support systems.

CONCLUSION

This study suggests that SDOH impact PALF outcomes and highlights patient populations facing additional challenges during an already complex healthcare emergency. These associations may indicate unconscious biases held by transplant teams when evaluating waitlist candidacy, as well as barriers to healthcare access. Strategies to better understand the broader applicability of our findings and, if confirmed, efforts to mitigate social disparities, may improve clinical outcomes in PALF.

Contrasting socioeconomic inequality with noncommunicable diseases: Insights from a population-based survey using the concentration index in Kong cohort study

Background

Noncommunicable diseases (NCDs) are the major causes of mortality across the globe, which impose a substantial burden on health care systems, particularly in low- and middle-income countries. The present study aimed to determine socioeconomic inequality in the prevalence of NCDs using the concentration index (CI).

Methods

This cross-sectional study was conducted on the baseline data of the Bandar Kong cohort. The principal component analysis was used to determine people's socioeconomic status (SES). The CI and Lorenz Curve were used for the assessment of socioeconomic inequality. Multivariate logistic regression was used to assess the relationship between SES and the prevalence of NCDs. A p Value less than 0.05 is considered significant.

Results

Frequency and prevalence of diabetes was 653 (16.22%), hypertension 848 (21.06%), chronic lung diseases 161 (4%), epilepsy 70 (1.74%), mental disorders 191 (4.74%), stillbirth 299 (13.94%), thyroid disorders 391 (9.71%) and depression 146 (3.63%). CI for the prevalence of diabetes was [-0.107, %95 CI: -0.146 to -0.068], hypertension [-0.122, %95 CI: -0.155 to -0.088], chronic lung disease [-0.116, %95 CI: -0.202 to -0.03], psychiatric disorders [-0.230, %95 CI: -0.304 to -0.155], depression [-0.132, %95 CI: -0.220 to-0.043] and stillbirth [-0.162, %95 CI: -0.220 to -0.105]. The Gini index was negative for all these diseases, indicating that these are significantly concentrated in people of poor SES.

Conclusions

The findings suggest that selected NCDs were concentrated among the poor and the low-income. Particular attention may be necessary to address the problem of NCDs among these groups.

Citizen science approaches to crowdsourcing food environment data: A scoping review of the literature

Globally, the adoption and implementation of policies to improve the healthiness of food environments and prevent population weight gain have been inadequate. This is partly because of the complexity associated with monitoring dynamic food environments. Crowdsourcing is a citizen science approach that can increase the extent and nature of food environment data collection by engaging citizens as sensors or volunteered computing experts. There has been no literature synthesis to guide the application of crowdsourcing to food environment monitoring. We systematically conducted a scoping review to address this gap. Forty-two articles met our eligibility criteria. Photovoice techniques were the most employed methodological approaches (n = 25 studies), commonly used to understand overall access to healthy food. A small number of studies made purpose-built apps to collect price or nutritional composition data and were scaled to receive large amounts of data points. Twenty-nine studies crowdsourced food environment data by engaging priority populations (e.g., households receiving low incomes). There is growing potential to develop scalable crowdsourcing platforms to understand food environments through the eyes of everyday people. Such crowdsourced data may improve public and policy engagement with equitable food policy actions.

A geospatial analysis of cardiometabolic diseases and their risk factors considering environmental features in a midsized city in Argentina

New approaches to the study of cardiometabolic disease (CMD) distribution include analysis of built environment (BE), with spatial tools as suitable instruments. We aimed to characterize the spatial dissemination of CMD and the associated risk factors considering the BE for people attending the Non-Invasive Cardiology Service of Hospital Nacional de Clinicas in Córdoba City, Argentina during the period 2015-2020. We carried out an observational, descriptive, cross-sectional study performing non-probabilistic convenience sampling. The final sample included 345 people of both sexes older than 35 years. The CMD data were collected from medical records and validated techniques and BE information was extracted from Landsat-8 satellite products. A geographic information system (GIS) was constructed to assess the distribution of CMD and its risk factors in the area. Out of the people sampled, 41% showed the full metabolic syndrome and 22.6% only type-2 diabetes mellitus (DM2), a cluster of which was evidenced in north-western Córdoba. The risk of DM2 showed an association with high values of the normalized difference vegetation index (NDVI) (OR= 0.81; 95% CI: - 0.30 to 1.66; p=0.05) and low normalized difference built index (NDBI) values that reduced the probability of occurrence of DM2 (OR= -1.39; 95% CI: -2.62 to -0.17; p=0.03). Considering that the results were found to be linked to the environmental indexes, the study of BE should include investigation of physical space as a fundamental part of the context in which people develop medically within society. The novel collection of satellite-generated information on BE proved efficient.

Inequalities in the burden of non-communicable diseases across European countries: a systematic analysis of the Global Burden of Disease 2019 study

BACKGROUND

Although overall health status in the last decades improved, health inequalities due to non-communicable diseases (NCDs) persist between and within European countries. There is a lack of studies giving insights into health inequalities related to NCDs in the European Economic Area (EEA) countries. Therefore, the aim of the present study was to quantify health inequalities in age-standardized disability adjusted life years (DALY) rates for NCDs overall and 12 specific NCDs across 30 EEA countries between 1990 and 2019. Also, this study aimed to determine trends in health inequalities and to identify those NCDs where the inequalities were the highest.

METHODS

DALY rate ratios were calculated to determine and compare inequalities between the 30 EEA countries, by sex, and across time. Annual rate of change was used to determine the differences in DALY rate between 1990 and 2019 for males and females. The Gini Coefficient (GC) was used to measure the DALY rate inequalities across countries, and the Slope Index of Inequality (SII) to estimate the average absolute difference in DALY rate across countries.

RESULTS

Between 1990 and 2019, there was an overall declining trend in DALY rate, with larger declines among females compared to males. Among EEA countries, in 2019 the highest NCD DALY rate for both sexes were observed for Bulgaria. For the whole period, the highest DALY rate ratios were identified for digestive diseases, diabetes and kidney diseases, substance use disorders, cardiovascular diseases (CVD), and chronic respiratory diseases - representing the highest inequality between countries. In 2019, the highest DALY rate ratio was found between Bulgaria and Iceland for males. GC and SII indicated that the highest inequalities were due to CVD for most of the study period - however, overall levels of inequality were low.

CONCLUSIONS

The inequality in level 1 NCDs DALYs rate is relatively low among all the countries. CVDs, digestive diseases, diabetes and kidney diseases, substance use disorders, and chronic respiratory diseases are the NCDs that exhibit higher levels of inequality across countries in the EEA. This might be mitigated by applying tailored preventive measures and enabling healthcare access.

Patterns of Non-Communicable Disease, Multimorbidity, and Population Awareness in Bahir Dar, Northwest Ethiopia: A Cross-Sectional Study

Objective

Ethiopia, like other developing countries, is going through an epidemiological transition, and high rates of non-communicable diseases (NCDs) are having a significant impact on the health system; however, there is limited evidence about community level NCD prevalence, multimorbidity, and population awareness that could inform targeted interventions and policy responses. This study aimed to identify factors associated with NCD prevalence, multimorbidity, and population awareness of NCDs in Bahir Dar, Northwest Ethiopia.

Methods

A community-based cross-sectional survey was conducted with 417 randomly sampled adults. We performed descriptive and logistic regression analyses to evaluate associations between NCD prevalence (cardiovascular diseases, diabetes, cancer, chronic respiratory diseases, chronic kidney disease, and hypertension) multimorbidity (2 or more NCDs) and demographic, socioeconomic, individual risk factors, anthropometrics, knowledge, and attitude.

Results

This study reveals that 24% of participating adults have an NCD, and 8% have multimorbidity. One-third (34.5%) have some NCD knowledge, and 75% consider NCDs more dangerous than communicable diseases. We find low NCD prevalence in participants: younger than 40 years of age (AOR 0.17, 95% CI 0.07 to 0.39); with normal body mass index (AOR 0.27, 0.10 to 0.77) and; with a family history of NCD (AOR 7.7, 4.2 to 14.1). Multimorbidity is lower in young adults (AOR 0.08, 0.03 to 0.26). NCD knowledge is higher in men (AOR 1.76, 1.06 to 2.93) and employed adults (AOR 2.91, 1.52 to 5.57), and NCD attitude in normal-weight adults (AOR 3.23, 1.42 to 7.39).

Conclusion

This study reveals a high prevalence of NCD and overall low NCD awareness in the population. Age above 40 years, family history of NCD, and weight in the obese category are significant predictors of NCD prevalence. These findings can help health professionals, health offices, and concerned stakeholders to plan targeted health interventions to reduce NCDs in the population.

Association between Mortality from Chronic Noncommunicable Diseases and Human Development Index in Brazil between 1980 and 2019

BACKGROUND

Chronic noncommunicable diseases (CNCDs) caused more than 734,000 deaths (55% of all deaths) in Brazil in 2019, with an important socioeconomic impact.

OBJECTIVES

To analyze the mortality rates from CNCDs in Brazil from 1980 to 2019 and their association with socioeconomic indicators.

METHOD

This was a descriptive, time-series study of deaths from CNCDs in Brazil from 1980 to 2019. Data on the annual frequencies of deaths and on population were obtained from the Department of Informatics of the Brazilian Unified Health System. Crude and standardized mortality rates per 100,000 inhabitants were estimated using the direct method (Brazilian population in 2000). The quartiles of each CNCD were calculated, where a quartile change, due to an increase in mortality rate, was represented by a chromatic gradient. The Municipal Human Development Index (MHDI) of each Brazilian federative unit was extracted from the Atlas Brasil website and correlated with the rates of CNCD mortality.

RESULTS

There was a reduction in mortality rates due to diseases of the circulatory system during the period, except in the Northeast Region. There was also an increase in mortality from neoplasia and diabetes, while the rates of chronic respiratory diseases showed little variation. There was an inverse correlation between the federative units with greater reduction in CNCD mortality rates and the MHDI.

CONCLUSIONS

The observed decrease in mortality due to diseases of the circulatory system may reflect an improvement in socioeconomic indicators in Brazil during the period. The increase in mortality rates due to neoplasms is probably related to the aging of the population. The higher mortality rates of diabetes seem to be associated with an increase in the prevalence of obesity in Brazilian women.

Associations of socioeconomic status with infectious diseases mediated by lifestyle, environmental pollution and chronic comorbidities: a comprehensive evaluation based on UK Biobank

BACKGROUND

Socioeconomic status (SES) inequity was recognized as a driver of some certain infectious diseases. However, few studies evaluated the association between SES and the burden of overall infections, and even fewer identified preventable mediators. This study aimed to assess the association between SES and overall infectious diseases burden, and the potential roles of factors including lifestyle, environmental pollution, chronic disease history.

METHODS

We included 401,009 participants from the UK Biobank (UKB) and defined the infection status for each participant according to their diagnosis records. Latent class analysis (LCA) was used to define SES for each participant. We further defined healthy lifestyle score, environment pollution score (EPS) and four types of chronic comorbidities. We used multivariate logistic regression to test the associations between the four above covariates and infectious diseases. Then, we performed the mediation and interaction analysis to explain the relationships between SES and other variables on infectious diseases. Finally, we employed seven types of sensitivity analyses, including considering the Townsend deprivation index as an area level SES variable, repeating our main analysis for some individual or composite factors and in some subgroups, as well as in an external data from the US National Health and Nutrition Examination Survey, to verify the main results.

RESULTS

In UKB, 60,771 (15.2%) participants were diagnosed with infectious diseases during follow-up. Lower SES [odds ratio (OR) = 1.5570] were associated with higher risk of overall infections. Lifestyle score mediated 2.9% of effects from SES, which ranged from 2.9 to 4.0% in different infection subtypes, while cardiovascular disease (CVD) mediated a proportion of 6.2% with a range from 2.1 to 6.8%. In addition, SES showed significant negative interaction with lifestyle score (OR = 0.8650) and a history of cancer (OR = 0.9096), while a significant synergy interaction was observed between SES and EPS (OR = 1.0024). In subgroup analysis, we found that males and African (AFR) with lower SES showed much higher infection risk. Results from sensitivity and validation analyses showed relative consistent with the main analysis.

CONCLUSIONS

Low SES is shown to be an important risk factor for infectious disease, part of which may be mediated by poor lifestyle and chronic comorbidities. Efforts to enhance health education and improve the quality of living environment may help reduce burden of infectious disease, especially for people with low SES.

Exploring the Role of Physical Activity in Mediating the Association between Educational Level and Health-Related Quality of Life in an Adult Lifespan Sample from Madeira Island

Background: People more socioeconomically vulnerable tend to have a poorer health-related quality of life (HRQoL). Studies are trying to analyse the factors that may condition this relationship, including physical activity (PA), which may influence the relationship between socioeconomic status (SES) and HRQoL. This study aimed to analyse the relationship between SES and HRQoL through specific domains of PA. Methods: A total of 381 adults (≥18 years) from the Autonomous Region of Madeira completed the measurements. Mediation analyses using bootstrapping methods adjusted for confounding variables were performed to relate SES and HRQoL; the latter was evaluated using the physical component score (PCS) of the SF-12, the mental component score (MCS) of the SF-12, and the total score in the SF-12 questionnaire (SF-12 score), through physical activity. Results: Educational level was positively related to PCS and SF-12 score. Leisure-time PA (not including sports PA) and PA at work, as single mediating variables, did not mediate the relationship between SES and HRQoL. The total PA suppressed the socioeconomic gradient of HRQoL by 8–10%, 39–46%, and 15–16%, respectively, for the PCS, MCS, and the SF-12 score; sports PA mediated the relationship by 13–16%, 50%, and 15–21%, respectively. Conclusions: The results suggest that sports PA contributes to reducing the socioeconomic gradient of HRQoL.

The impact of COVID ‐19 on cancer care of outpatients with low socioeconomic status

Patients with low socioeconomic status (SES) are among the most underserved groups of people regarding cancer care. Analyzing the impact of the coronavirus‐induced disease 2019 (COVID‐19) pandemic on health care disparities and calling attention to inequalities in cancer care is crucial to justify and initiate adequate countermeasures. We aimed to determine whether the COVID‐19 pandemic aggravated health care disparities of cancer outpatients related to their SES and analyzed patient data of the largest university center providing services for patients with hematologic and oncologic disorders in Austria from 2018 to 2021. SES was assessed using three indicators: monthly net household income, level of education and occupational prestige. In total, 1217 cancer outpatients (51.1% female) with a mean age of 59.4 years (SD = 14.2) participated. In the first year of the pandemic, the relative proportion of individuals with low income, low education level and low occupational prestige seeking cancer care at our outpatient center decreased significantly (P ≤ .015). The strongest indicator was income, with a consistent effect throughout the first pandemic year. Countermeasures and specific interventions to support cancer patients with low SES in their access to health care should be initiated and prioritized.

Physical inactivity, and its association with hypertension among employees in the district of Colombo

BACKGROUND

Physical inactivity is a leading cause of morbidity and mortality and is a major public health problem. Insufficient activity is responsible for a large proportion of non-communicable diseases such as hypertension.

OBJECTIVES

The purpose of this study was to assess socioeconomic variations in physical activity and to measure the association between physical inactivity and hypertension among government officials in Sri Lanka.

METHODS

A cross-sectional study was carried out among 275 senior-officers(SOs) and 760 managerial-assistants(MAs) aged 30-60 years and attached to Public Administration institutions in Colombo District in Sri Lanka. Physical-activity(PA) was gathered using the International Physical Activity Questionnaire(IPAQ) adopted and validated to the Sri Lankan context. Blood pressure(measured and classified using JNC-7 guidelines) and anthropometric indices were recorded. Energy utilization of all vigorous and moderated PA and walking was expressed as metabolic-equivalent-of-task(MET) min per week. A total-MET-score was calculated and categorized based on IPAQ guidelines.

RESULTS

Socioeconomic variations in PA levels were observed as 58.1%(n = 158) SOs and 30.6%(n = 226) MAs were involved in inadequate PA. Among the SOs diagnosed with hypertension, more half(59.1%; n = 52) were physically inactive, while among MAs, 65.9%(n = 143) with hypertension were physically inactive. After adjusting for potential confounding factors being physically inactive was associated with a higher risk of hypertension among SOs[OR 2.08 [95% CI 1.07, 4.6] and MAs[OR 2.8 [95% CI 1.8, 4.6]. The main modality of commuting to work for SOs(59%) was private transport, and MAs(64%) public transport Commuting distance was positively correlated(p < 0.05) with total transport MET among SOs and MAs. After adjusting for confounders, commuting distance of > 20 km was found to lower the odds of hypertension among SOs and MAs(OR = 0.713; 95% CI 0.4 to1.3; and OR = 0.63; 95% CI 0.46 to 0.87).

CONCLUSION

Despite the current knowledge that being physically active promotes health, the practice was different. Physical inactivity was associated with hypertension and prevalent among both SOs and MAs. Higher commuting distance is positively correlated with total transport MET and associated with lower odds of hypertension among SOs and MAs. Longitudinal studies are required to provide a causative association between physical inactivity and hypertension among these employees.

Trajectories of Suffering in the Last Year of Life Among Patients With a Solid Metastatic Cancer

BACKGROUND

Reducing suffering at the end of life is important. Doing so requires a comprehensive understanding of the course of suffering for patients with cancer during their last year of life. This study describes trajectories of psychological, spiritual, physical, and functional suffering in the last year of life among patients with a solid metastatic cancer.

PATIENTS AND METHODS

We conducted a prospective cohort study of 600 patients with a solid metastatic cancer between July 2016 and December 2019 in Singapore. We assessed patients' psychological, spiritual, physical, and functional suffering every 3 months until death. Data from the last year of life of 345 decedents were analyzed. We used group-based multitrajectory modeling to delineate trajectories of suffering during the last year of a patient's life.

RESULTS

We identified 5 trajectories representing suffering: (1) persistently low (47% of the sample); (2) slowly increasing (14%); (3) predominantly spiritual (21%); (4) rapidly increasing (12%); and (5) persistently high (6%). Compared with patients with primary or less education, those with secondary (high school) (odds ratio [OR], 3.49; 95% CI, 1.05-11.59) education were more likely to have rapidly increasing versus persistently low suffering. In multivariable models adjusting for potential confounders, compared with patients with persistently low suffering, those with rapidly increasing suffering had more hospital admissions (β=0.24; 95% CI, 0.00-0.47) and hospital days (β=0.40; 95% CI, 0.04-0.75) during the last year of life. Those with persistently high suffering had more hospital days (β=0.70; 95% CI, 0.23-1.17).

CONCLUSIONS

The course of suffering during the last year of life among patients with cancer is variable and related to patients' hospitalizations. Understanding this variation can facilitate clinical decisions to minimize suffering and reduce healthcare costs at the end of life.

Associations of psychosocial factors, knowledge, attitudes and practices with hospitalizations in internal medicine divisions in different population groups in Israel

BACKGROUND

Inequalities in healthcare utilization exist across ethnic groups; however, the contributions of health-related knowledge and psychosocial factors to these inequalities remain unclear. We examined associations of social determinants of health, psychological factors, knowledge, attitudes and health practices, with hospitalizations in internal medicine divisions, among Israeli adults, Jews and Arabs, with non-communicable diseases, in a setting of universal health insurance.

METHODS

A retrospective study was undertaken among 520 Jews and Arabs aged 40 years or older with non-communicable diseases, members of a large health maintenance organization. Hospitalization (at least once during 2008) in an internal medicine division was determined based on documentation in electronic health records. Participants were randomly selected in strata of sex, population-group and hospitalization status (yes/no). Data were collected from medical records and via face-to-face interviews using a structured questionnaire. Main independent variables included comorbidity burden, health behaviors, mental health wellbeing and self-rated health. Scales measuring health knowledge and attitudes/beliefs were constructed using factor analysis.

RESULTS

Comorbidity burden (OR 1.41 [95% CI 1.24-1.61]) and self-rated health (not good vs. good) (OR 1.88 [95% CI 1.13-3.12]) were positively associated with hospitalizations in an internal medicine division, while an inverse association was found with better mental health wellbeing (OR 0.98 [95% CI 0.96-0.99, for each 1-point score increase). Among Jewish participants, positive associations were found of the number of offspring, comorbidity burden and perceived difficulty, with hospitalizations. No significant associations were found with hospitalizations of other sociodemographics, health behaviors, knowledge and attitudes/beliefs.

CONCLUSIONS

Comorbidity burden was the main risk factor of hospitalizations in internal medicine divisions. Psychosocial factors, such as self-rated health, a complex variable affected by social capital, mental wellbeing, the number of offspring, and perceived burden and difficulty, seem also to contribute. These findings suggest the involvement of broad family and social factors, beyond individual level characteristics and medical needs, in hospitalizations in internal medicine divisions. Interventions to reduce hospitalizations should be comprehensive and integrate aspects of mental health wellbeing; they should build on familial characteristics (e.g., number of offspring), factors related to social capital such as self-rated health, and perceived burden and difficulty.