Population Health Metrics最新文献

Background: The prevalence of mental illness, substance use disorders, and their dual diagnosis is disproportionately high among people in prisons compared to the community. Accurate prevalence estimates are required to inform resourcing of prison health services and reduce the risk of harm to people experiencing these conditions. Existing estimates, where available, often rely on only one data source.

Method: We used three data sources - self-reported history of diagnoses, in-prison medical records, and administrative data to estimate the prevalence of mental illness, substance use disorder, and dual diagnosis among two large cohorts of non-Indigenous and Aboriginal and Torres Strait Islander people in Australian prisons. We calculated population-weighted proportions of the samples with each condition. Inter-rater reliability metrics inform data source agreement.

Results: The prevalence of mental illness only, substance use disorder only, and dual diagnosis was 17.0% (95%CI 12.0-24.5), 14.8% (95%CI 9.6-18.1), and 44.2% (95%CI 33.2-54.7), respectively, for incarcerated, non-Indigenous adults. For incarcerated Aboriginal and Torres Strait Islander adults, our corresponding estimates were 7.0% (95%CI 4.3-11.5), 26.8% (95%CI 18.9-33.5), and 40.9% (95%CI 30.1-48.2). These estimates differed significantly from those derived from singular data sources. Individual data sources' agreement was weakest for substance use disorder diagnoses and strongest for dual diagnoses.

Conclusions: Individual data sources likely have high specificity and low sensitivity, thus under-ascertaining diagnoses. We recommend using multiple data sources to estimate prevalence to ensure adequate ascertainment of these conditions among people in prison and to ensure in-prison and transitional health services are appropriately resourced.

The COVID-19 pandemic affected Europe unevenly, with surges in infections and deaths fluctuating across different regions and time periods. Hyper-localised hotspots and staggered timelines created intense, asynchronous waves of infections and deaths that distort country-level and cumulative data, obscuring the pandemic's spatiotemporal dynamics through aggregation. Despite extensive research comparing states and analysing subnational variance within individual countries, the detailed subnational and transnational dynamics of the COVID-19 pandemic across Europe as a whole have not been comprehensively described. Here we show that time-series clustering, applied to weekly excess mortality estimates for subnational NUTS3 administrative regions of 27 countries in Europe, identifies five distinct pandemic trajectories which map to spatial patterns. The trajectories comprise two subgroups, representing contrasting pandemic dynamics in eastern and western Europe. Western Europe exhibits concentric arrangements of mortality impact, with secondary and tertiary impact zones surrounding outbreak epicenters. Eastern Europe exhibits internally homogeneous spatial dynamics, possibly due to the deferral of the first major mortality wave.

Background: Despite the high level of economic development in the Group of Seven (G7) countries, injury deaths remain a public health concern in these countries. This paper examines the contribution of injury deaths to changes in life expectancy (LE) and life disparity (LD) in the G7 countries.

Methods: We used annual data from the WHO mortality database to compute LE and LD during 2001-03 and 2017-19. The contributions of injury deaths to LE and LD changes for each sex were decomposed by age and cause using a continuous-change model.

Results: Across the G7 countries combined, LE (LD) increased by 2.12 (0.25) and 2.73 (0.16) years for females and males, respectively. While most injury-related deaths contributed to increases in LE and decreases in LD, these gains were offset by negative contributions of unintentional poisoning, resulting in an overall negligible net contributions of injury deaths to changes in LE/LD across the G7 countries combined. The country-specific patterns revealed notable variations. Positive contributions of injury-related causes to changes in LE were more prominent in France (+ 0.38/+0.64 years for females/males), while negative contributions were most evident in the USA (-0.23/-0.42 years for females/males). Transport accidents emerged as the leading contributors to improvements in both LE and LD among both sexes in all countries, with more pronounced effects in males. In contrast, unintentional poisoning had a substantial negative impact, particularly among younger populations in the USA, UK, and Canada.

Conclusion: Injury deaths made negligible contributions to overall changes in LE and LD across the G7 countries combined during the study period. However, there were important variations by sex, age, cause and country. Specifically, unfavourable contributions of injury deaths were mainly observed in the USA, UK, and Canada. These findings highlight the need for targeted, country-specific injury prevention strategies to mitigate premature and unequal mortality.

Background: Although chronic diseases represent a growing global health priority, significant gaps remain in understanding the burden of multimorbidity. This study developed an original methodology to estimate the burden of thirty major chronic diseases at the individual patient level, in terms of Disability-Adjusted Life years (DALYs), Years Lived with Disability (YLD), and Years of Life Lost due to premature death (YLL).

Methods: The Disability weights (DWs) estimated by the Global Burden of Disease (GBD) study were integrated with information from healthcare databases. A panel of medical specialists established the criteria for assigning the level of severity, and thus a specific DW, to each chronic disease. The patient-centred YLD metric was estimated as the cumulative of the combined DWs over the previous ten years. We also measured the Disability Weight Fraction of each coexisting disease (DWF). We illustrated this method using healthcare databases from a large Italian region to assess the impact of chronic diseases and multimorbidity at progressive levels of analysis: health status of the regional chronic disease population, burden of individual chronic diseases and patient clinical complexity.

Results: Unlike the standard GBD estimates, the new method provided precise metrics for multimorbidity, as shown by the comparison on the disability calculated for 4 main chronic diseases. Real-world estimates from the new method highlighted that comorbidity accounted for most of the YLD: for instance, about 88% of the YLD of patients with heart failure was explained by concomitant conditions. DALYs were higher among females than males in most age groups. In the younger groups, psychiatric conditions explained approximately 40% and 25% of YLD among males and females, respectively. Finally, the patient-centred YLD metric was a good predictor of death (c-statistic = 0.779).

Conclusions: This novel method provides insights into the measurement of multimorbidity, based on the disability fraction of each concomitant health condition, which is crucial for defining priority areas for healthcare interventions. The patient-centred estimates may serve to identify subgroups of chronic disease patients with specific healthcare needs and trajectories among a given population. Importantly, measuring the relative contribution of each disease to the patient's burden of multimorbidity favours the planning of multidisciplinary care pathways that are more responsive to individual needs.

Background: Life's Crucial 9 (LC9), an extension for Life's Essential 8 with the addition of psychological health, provides a new tool for assessing cardiovascular health. However, the association between LC9 and cardiovascular diseases (CVD) in elderly hypertensive patients remains unclear.

Methods: A cross-sectional survey was carried out among elderly hypertensive patients from the National Basic Public Health Service Programs in Jia County, Henan Province, from July 1 to August 31, 2023. The primary outcome was defined as a composite CVD (coronary heart disease and stroke). The LC9 consisted of 9 metrics (diet, physical activity, nicotine exposure, sleep, psychological health, body mass index, blood pressure, fasting blood glucose, and non-high-density lipoprotein cholesterol). The logistic regression model was established to estimate the odds ratio (OR) and 95% CI of CVD across different LC9 groups.

Results: A total of 13,032 elderly hypertensive patients (mean age: 73.45) were analyzed. 5,664 (43.46%) patients were diagnosed with CVD (including 4,455 coronary heart disease and 2,062 stroke). The median (interquartile range) of the LC9 score in all patients, those without CVD, and those with CVD were 65.56 (58.33-72.22), 66.67 (59.44-73.33), and 64.44 (56.67-71.11), respectively. As the number of ideal LC9 metrics increased, the prevalence of CVD decreased (P_trend <0.05). After adjusting for potential confounders, the OR (95%CI) of CVD in the LC9 score was 0.80 (0.76 - 0.83). Compared with the low group, the OR (95%CI) of CVD in the moderate group was 0.66 (0.58-0.76), and 0.49 (0.41-0.59) for the high group, respectively. Notably, there was a negative dose-response relationship between LC9 and its domain scores and CVD (P-nonlinear > 0.05).

Conclusion: Higher LC9 scores and more ideal health metrics, including psychological health, are associated with lower CVD risk in elderly hypertensive patients, highlighting the need for policy efforts to strengthen primary healthcare, expand access to preventive services, and promote comprehensive CVH management in this high-risk population.

Background: High health risk and low management compliance pose significant challenges in controlling hypertensive patients' blood pressure. Therefore, this study aims to investigate the impact of follow-up services on blood pressure control at the primary level.

Methods: A total of 871 hypertensive patients consecutively enrolled from 2016 to 2021 were randomly selected from Qianjiang County, Hubei Province and Changsha County, Hunan Province of China. Blood pressure measurements (systolic blood pressure, SBP, and diastolic blood pressure, DBP) were defined as outcome variables, whereas the interval and regularity of follow-up visits served as key explanatory variables. A fixed-effects model was used to examine the influence of follow-up behaviors on blood pressure control among hypertensive patients.

Results: An increased frequency of follow-up visits, particularly those closer to or above the minimum threshold outlined in the 2020 Guidelines for Prevention and Control of Hypertension in China, was found to be beneficial for blood pressure control. The effectiveness of blood pressure control further improved with shorter follow-up intervals. However, when the number of follow-up visits deviated significantly from the minimum threshold, optimizing blood pressure control was achievable by extending follow-up intervals.

Conclusions: A moderate increase in follow-up visits may be more effective in reducing hypertension patients' blood pressure than limiting follow-up intervals. It is suggested that primary hypertension management should focus on the regularity and intervals of follow-up visits and flexibly complete follow-up tasks. Moreover, the formal review of follow-up frequency and intervals, along with the efficiency of interventions implemented, should not be overlooked in hypertension control.

Background: Evidence suggests that the COVID-19 pandemic has exacerbated social and demographic inequalities in the communities through pathways of unequal exposure, vulnerability, and susceptibility. In Tanzania, evidence on COVID-19-related mortality is limited to health facility data, with little to no information on the mortality patterns in the general population. This study assessed sociodemographic inequalities in all-cause mortality during the COVID-19 period in north-western Tanzania.

Methods: We utilized available longitudinal data from the Magu Health and Demographic Surveillance System (HDSS) from January 2018 to December 2021. We compared the crude death rates between subgroups of age, sex, area of residence, and wealth index for a period before (2018/2019) and during (2020/2021) the COVID-19 pandemic. To quantify how mortality risk varies across the subgroups we fitted a Cox proportional hazard model with an interaction of the COVID-19 period.

Results: Overall mortality declined from 5.9 in 2018/2019 to 5.4 and 5.5 deaths per 1000 person-years in 2020 and 2021, respectively. We observed an increase in differences in crude death rates by age groups, area of residence, and wealth quintiles during the COVID-19 period. In the Cox proportional hazards model, compared to adults aged 15-49, we observed greater mortality risk in children under five (AHR:2.9; 95%CI: 2.2-3.9), older individuals aged 50-64 years (AHR:3.02; 95%CI:2.11-4.33) and 65 + (AHR:18.65; 95%CI:14.28-24.35) during COVID-19 period. Males were also at greater risk of death compared to females (AHR:1.30; 95%CI:1.06-1.59).

Conclusion: Despite the overall mortality decline during the pandemic, we observed an increased risk of mortality among vulnerable subgroups (aged < 5 years and > 60 years) in the population. This highlights the need to take into account vulnerable subpopulations when addressing major public health issues in communities.

Effective identification and correction of diabetes mellitus (DM)-related garbage codes (GCs) in mortality surveillance data is crucial for accurately estimating regional DM mortality rates. This study applied a structured, three-step approach-using standard WHO ICD-10 mortality coding rules, coarsened exact matching (CEMM), and fixed proportion reassignment (FPRM)-to redistribute diabetes-related GCs in Weifang's mortality data (2010-2022). Using ICD-10 coding rules, we reclassified 29 deaths originally assigned to DM as the underlying cause of death (UCD) to other causes, and reassigned 1,945 records previously not attributed to DM to DM as the UCD. CEMM then reclassified 283 DM-related GC records to DM, followed by FPRM, which reassigned 160 "unknown cause" records to DM. Together, these steps increased the number of DM deaths by 22.82%. Based on the reallocated data, crude DM mortality rates rose from 7.64 to 17.75 per 100,000 between 2010 and 2022, with males experiencing a greater overall increase than females. While no new algorithms were developed, this study demonstrates how internationally recommended coding standards-often neglected in routine subnational settings-can be systematically and rigorously applied to improve DM mortality surveillance. This work highlights operational gaps in local death certification and presents a replicable protocol for enhancing mortality data reliability using existing tools.

Background: Utilization of unhygienic menstrual products has been associated with various adverse health consequences, particularly in many low- and middle-income countries (LMICs), including Bangladesh. In this context, this study attempted to measure socioeconomic inequalities in sanitary napkin use among women aged 15-49 and assess its spatial pattern at the disaggregated level (district).

Methods: We used the latest available nationally representative cross-sectional Bangladesh Multiple Indicator Cluster Survey (MICS) 2019 data. The analytical sample size was 54,702 reproductive-aged (15-49 years) women. The Erreygers Index (EI) and the Wagstaff Index (WI) were employed to measure and decompose the socioeconomic inequalities in sanitary napkin use. Natural Break (Jenks) classification method, Global Moran's I and the Cluster and Outlier Analysis were used to analyze the spatial pattern of socioeconomic inequalities at the district level.

Results: The findings reveal that approximately 26.22% of women used sanitary napkins at the national level. Both the EI (0.41208; p-value < 0.001) and the WI (0.53251; p-value < 0.001) indicate a pro-rich inequality in sanitary napkin use. Decomposition results indicated that wealth status, educational attainment, household characteristics (particularly educational attainment of household head) and exposure to media were the most important factors accounting for socioeconomic inequalities. From the spatial analyses, we found significant district-level variations in both sanitary napkin use and its socioeconomic inequalities. Global Moran's I value indicated positive spatial autocorrelation, meaning that similar values tend to cluster together. Notably, a northwestern and southeastern divide was found between High-High and Low-Low clusters of socioeconomic inequalities.

Conclusions: Our study provides evidence for informed policymaking targeting women from the lower socioeconomic stratum, especially those living in the northwestern and southeastern regions to increase sanitary napkin use.

Background: Climatic factors have been associated with the occurrence of several diseases known as climate-sensitive diseases (CSDs). We selected the following categories of disease to represent CSDs for this study: vector-borne diseases (dengue, leishmaniasis, malaria, schistosomiasis, yellow fever, and zika), infectious-diseases (respiratory infections), non-communicable diseases (chronic respiratory and cardiovascular diseases) and water-borne diseases (diarrhea). This study aimed to describe the historical trends and spatial distribution of mortality and morbidity of these selected Climate Sensitive Diseases in Brazil between 1990 and 2017. The analysis is based on findings obtained by the 2017 Brazilian Global Burden of Diseases (GBD) Study.

Methods: Yearly CSD data was taken from the 2017 Brazilian GBD Study for the years between 1990 and 2017. This data was organized by age group and sex at the country level, for 26 states and one Federal District (known as Federative Units), and at the regional level.

Results: Cardiovascular and respiratory diseases presented the greatest disability adjusted life-years (DALYs) in Brazil, followed by chronic and infectious respiratory diseases, although only a small fraction could be attributed to climate changes. Among the vector-borne diseases, the burden of leishmaniasis and malaria have decreased since 1990, while the burden of dengue has increased. The burden of other vector-borne diseases (malaria and yellow fever) increased since 2015, in addition to the recent introduction of zika virus in Brazil. The GBD rates of infectious diseases were greater in predominately the Amazon and northeast regions. This finding contrasts with dengue and zika for which an increase in DALYs rate was observed southeast and central-west, besides the northeast region. The lowest DALYs rates for dengue were observed in the south region, which also experiences the lowest temperatures.

Conclusions: The burden of CSDs in Brazil has increased since 1990 considering non-communicable and communicable diseases. The potential impact of climate change on such diseases must be evaluated considering disease dynamics and spatial specificities, such as land cover and climate patterns. The main challenges in Brazil related to CSDs are the investments needed for research regarding the increase in the burden of CSDs, for vector control and social health determinants mitigation.