Regional disparities in suicide among patients with cancer: A nationwide population-based study in Japan

BACKGROUND

This study aimed to explore prefecture-level differences in suicide risk among patients with cancer in Japan.

METHODS

Data from the National Cancer Registry, which covers the entire Japanese population, were used. Patients diagnosed with cancer between 2016 and 2017 were included. The standardized mortality ratio (SMR) for suicide within 2 years after cancer diagnosis was quantified compared with the general population for each prefecture. Multivariate Poisson regression analysis was conducted to quantify the adjusted relative risk using Hokkaido as the reference.

RESULTS

The analysis included 2,133,502 patients. The SMRs were high among patients with cancer residing in certain prefectures, such as the Hokuriku region (the middle and western parts of Japan's main island). These areas also exhibited a significant relative risk in the Poisson regression model.

CONCLUSION

The results demonstrated that patients with cancer in certain prefectures in Japan have a high suicide risk.

Barriers to the Utilization of Primary Health Centers (PHCs) in Iraq

Primary care has been viewed as a means to ensure equitable access to care, enhance efficiency within healthcare systems, and improve health service quality. In recent decades, Iraq has transformed its compromised health system, shifting the healthcare model from hospital-based to primary care through primary health centers (PHCs) and referral mechanisms. Based on an extensive literature review, this qualitative paper explores the healthcare utilization of PHCs in different regions of Iraq. It also identifies some barriers to PHC use and recommends evidence-based approaches for improving PHCs' performance. Some reported challenges to better utilizing PHCs were the poor quality of services, patient dissatisfaction, long walking distance to a health center, and limited availability and affordability of the medications. If Iraq is to use primary care as a tool in achieving sustainable development goals (SDGs), collaborative efforts addressing the facility-related factors should be a priority.

Mapping the quality of basic and comprehensive emergency obstetric care services in Haiti

OBJECTIVE

To investigate geographical inequalities and changes in the quality of emergency obstetric care services available in Haiti over time.

METHODS

We utilized data from the Service Provision Assessment survey of all health facilities in Haiti in 2013 and 2017.We developed a quality index for basic emergency obstetric care (BEmOC) and comprehensive emergency obstetric care (CEmOC) based on the items in the signal functions of an emergency obstetric care framework, using a structure, process and outcome framework. We measured the quality index of all facilities in 2013 and 2017. We also assessed geographical trends and changes in quality between 2013 and 2017 using geospatial analysis.

RESULT

Our analysis showed that basic structure items such as connection to electricity grid, manual vacuum extractors, vacuum aspirators and dilation and curettage kits were widely unavailable at healthcare facilities. There was a significant improvement in indicators of structure (P < 0.001) and BEmOC (P = 0.03) in primary facilities; however, there was no significant change in the quality of CEmOC in primary facilities (P = 0.18). Similarly, there was no significant change in any of the structure or process indicators at secondary care facilities.

CONCLUSION

The availability of BEmOC at several Haitian facilities remains poor; however, there was significant improvement at primary care facilities, with little to no change in overall quality at secondary health facilities.

Neighbourhood Social Determinants of Health and Geographical Inequalities in Premature Mortality in Taiwan: A Spatiotemporal Approach

Geographical inequalities in premature mortality and the role of neighbourhood social determinants of health (SDOH) have been less explored. This study aims to assess the geographical inequalities in premature mortality in Taiwan and how neighbourhood SDOH contribute to them and to examine the place-specific associations between neighbourhood SDOH and premature mortality. We used township-level nationwide data for the years 2015 to 2019, including age-standardized premature mortality rates and three upstream SDOH (ethnicity, education, and income). Space-time scan statistics were used to assess the geographical inequality in premature mortality. A geographical and temporal weighted regression was applied to assess spatial heterogeneity and how neighbourhood SDOH contribute to geographic variation in premature mortality. We found geographical inequality in premature mortality to be clearly clustered around mountainous rural and indigenous areas. The association between neighbourhood SDOH and premature mortality was shown to be area-specific. Ethnicity and education could explain nearly 84% variation in premature mortality. After adjusting for neighbourhood SDOH, only a handful of hotspots for premature mortality remained, mainly consisting of rural and indigenous areas in the central-south region of Taiwan. These findings provide empirical evidence for developing locally tailored public health programs for geographical priority areas.

Spatial and Temporal Impacts of Socioeconomic and Environmental Factors on Healthcare Resources: A County-Level Bayesian Local Spatiotemporal Regression Modeling Study of Hospital Beds in Southwest China

Comprehensive investigation on understanding geographical inequalities of healthcare resources and their influencing factors in China remains scarce. This study aimed to explore both spatial and temporal heterogeneous impacts of various socioeconomic and environmental factors on healthcare resource inequalities at a fine-scale administrative county level. We collected data on county-level hospital beds per ten thousand people to represent healthcare resources, as well as data on 32 candidate socioeconomic and environmental covariates in southwest China from 2002 to 2011. We innovatively employed a cutting-edge local spatiotemporal regression, namely, a Bayesian spatiotemporally varying coefficients (STVC) model, to simultaneously detect spatial and temporal autocorrelated nonstationarity in healthcare-covariate relationships via estimating posterior space-coefficients (SC) within each county, as well as time-coefficients (TC) over ten years. Our findings reported that in addition to socioeconomic factors, environmental factors also had significant impacts on healthcare resources inequalities at both global and local space–time scales. Globally, the personal economy was identified as the most significant explanatory factor. However, the temporal impacts of personal economy demonstrated a gradual decline, while the impacts of the regional economy and government investment showed a constant growth from 2002 to 2011. Spatially, geographical clustered regions for both hospital bed distributions and various hospital bed-covariates relationships were detected. Finally, the first spatiotemporal series of complete county-level hospital bed inequality maps in southwest China was produced. This work is expected to provide evidence-based implications for future policy making procedures to improve healthcare equalities from a spatiotemporal perspective. The employed Bayesian STVC model provides frontier insights into investigating spatiotemporal heterogeneous variables relationships embedded in broader areas such as public health, environment, and earth sciences.

Determinants of Primary Nonadherence to Medications Prescribed by General Practitioners Among Adults in Hungary: Cross-Sectional Evaluation of Health Insurance Data

Background: Primary nonadherence to prescribed medications occurs when patients do not fill or dispense prescriptions written by healthcare providers. Although it has become an important public health issue in recent years, little is known about its frequency, causes, and consequences. Moreover, the pattern of risk factors shows remarkable variability across countries according to the published results. Our study aimed to assess primary nonadherence to medications prescribed by general practitioners (GPs) and its associated factors among adults in Hungary for the period of 2012–2015.

Methods: Data on all general medical practices (GMPs) of the country were obtained from the National Health Insurance Fund and the Central Statistical Office. The ratio of the number of dispensed medications to the number of prescriptions written by a GP for adults was used to determine the medication adherence, which was aggregated for GMPs. The effect of GMP characteristics (list size, GP vacancy, patients’ education provided by a GMP, settlement type [urban or rural], and geographical location [by county] of the center) on adherence, standardized for patients’ age, sex, and eligibility for an exemption certificate, were investigated through generalized linear regression modeling.

Results: A total of 281,315,386 prescriptions were dispensed out of 438,614,000 written by a GP. Overall, 64.1% of prescriptions were filled. According to the generalized linear regression coefficients, there was a negative association between standardized adherence and urban settlement type (b = -0.099, 95%CI = -0.103 to -0.094), higher level of education (b = -0.440, 95%CI = -0.468 to -0.413), and vacancy of the general practices (b = -0.193, 95%CI = -0.204 to -0.182). The larger GMP size proved to be a risk factor, and there was a significant geographical inequality for counties as well.

Conclusions: More than one-third of the written prescriptions of GPs for adults in Hungary were not dispensed. This high level of nonadherence had great variability across GMPs, and can be explained by structural characteristics of GMPs, the socioeconomic status of patients provided, and the quality of cooperation between patients and GPs. Moreover, our findings suggest that the use of the dispensed-to-prescribed medication ratio in routine monitoring of primary health care could effectively support the necessary interventions.

Healthcare Utilization and All-Cause Premature Mortality in Hungarian Segregated Roma Settlements: Evaluation of Specific Indicators in a Cross-Sectional Study

Roma is the largest ethnic minority of Europe with deprived health status, which is poorly explored due to legal constrains of ethnicity assessment. We aimed to elaborate health indicators for adults living in segregated Roma settlements (SRS), representing the most vulnerable Roma subpopulation. SRSs were mapped in a study area populated by 54,682 adults. Records of all adults living in the study area were processed in the National Institute of Health Insurance Fund Management. Aggregated, age-sex standardized SRS-specific and non-SRS-specific indicators on healthcare utilization and all-cause premature death along with the ratio of them (RR) were computed with 95% confidence intervals. The rate of GP appointments was significantly higher among SRS inhabitants (RR = 1.152, 95% CI: 1.136–1.167). The proportion of subjects hospitalized (RR = 1.286, 95% CI: 1.177–1.405) and the reimbursement for inpatient care (RR = 1.060, 95% CI: 1.057–1.064) were elevated for SRS. All-cause premature mortality was significantly higher in SRSs (RR = 1.711, 1.085–2.696). Our study demonstrated that it is possible to compute the SRS-specific version of routine healthcare indicators without violating the protection of personal data by converting a sensitive ethical issue into a non-sensitive small-area geographical analysis; there is an SRS-specific healthcare utilization pattern, which is associated with elevated costs and increased risk of all-cause premature death.

Municipal-level differences in depressive symptoms among adolescents in Norway: Results from the cross-national Ungdata study

AIM

This study aimed to investigate municipal-level variations and individual- and municipal-level predictors of high levels of depressive symptoms among Norwegian adolescents.

METHODS

We used data from the Norwegian cross-national Ungdata study. We included 77,424 adolescents from 171 municipalities attending junior high school (Grades 8-10; age 13-16 years) from 2011 to 2013. Multilevel (two-level) logistic regression models were applied for the data analyses.

RESULTS

The study revealed that 11% of adolescents reported high levels of depressive symptoms. The median odds ratio without adjusting for any individual- or municipal-level predictors was 1.24, indicating a small between-municipalities variability for high levels of depressive symptoms. All individual-level factors, such as gender, school grade, family income, substance use behaviours, bullying and dissatisfaction with different aspects of life, were significantly associated with high levels of depressive symptoms (p < 0.05). As to municipal-level factors, a low annual budgets for municipal health services was the sole significant predictor of high levels of depressive symptoms between municipalities. Municipal-level factors and variables related to survey characteristics explained a moderate proportion of the variation in high levels of depressive symptoms between municipalities.

CONCLUSIONS

The cluster heterogeneity in high levels of depressive symptoms was small between municipalities in Norway. Further research should examine the geographic clustering of mental health problems at the school and neighbourhood level.