Population Health Metrics最新文献

Background: Measurement of excess mortality attributable to the COVID-19 pandemic is essential for quantifying the direct and indirect effects on mortality and informing future public health control strategies. This study assessed the impact of COVID-19 on excess mortality and life expectancy at birth in rural northern Ghana.

Methods: Data was obtained from the Navrongo Health and Demographic Surveillance System (NHDSS) in Ghana. We computed the number of deaths and person-years contributed from January 1, 2015, to December 31, 2021, and estimated mortality rates for each year, age group, and gender. Mortality rate differences were calculated by comparing the period before (2018-2019) and during (2020-2021) the pandemic. To estimate excess mortality, a generalised additive model was fitted to the historical data from 2015 to 2019 to predict the expected mortality rates in the COVID-19 period (2020-2021). A Cox proportional hazards model was fitted to assess the risk factors associated with mortality, adjusting for socio-demographic variables. Conventional life table techniques were used to estimate period life expectancy at birth for males and females.

Results: Overall, 12,413 deaths and 1,227,115 person-years were included in the analysis. This consists of 5,930 (49%) deaths and 572,963 person-years for the pre-pandemic period (2015-2019) and 6,483 (52%) deaths and 654,153 person-years for the pandemic period (2020-2021). From 2020 to 2021, the crude mortality rate was 23.9 deaths per 1000 person-years compared with 20.7 deaths per 1000 person-years predicted if COVID-19 had not occurred. COVID-19 also caused a decline in life expectancy at birth, especially in males, by 3.4 years. In addition, the adjusted risk of dying during the pandemic was higher in males (12.1%) compared to females and higher in the 65 + years age group (69.2%) compared to the younger population.

Conclusion: The COVID-19 pandemic caused an increase in deaths and a decrease in life expectancy in the NHDSS population in Ghana, particularly among men and those aged 65 years and older. These results reinforce the critical role of routine surveillance data in assessing the impact of public health emergencies such as the COVID-19 pandemic and informing public health strategies.

Background: Globally, the COVID-19 pandemic greatly interrupted healthcare programmes, and resulted in excess deaths. The age-specific mortality profile of the COVID-19 disease indicates that older people and those with comorbidities, specifically diabetes and hypertension, face a higher risk of mortality. In South Africa, excess deaths from natural causes in 2020 and 2021 were estimated to be nearly three times higher than the reported COVID-19 deaths. The study aims to characterise and compare mortality changes over the period 2015-2021 among individuals receiving care for HIV, hypertension and diabetes, in a rural South African setting.

Methods: Data from the Agincourt Health and Demographic Surveillance System and the Hospital-Clinic link system was used to characterise the sex and age-specific mortality patterns for HIV, hypertension, and diabetes for the period before (2015-2019) and during the COVID-19 pandemic (2020-2021). Cox regression model was used to investigate the risk factors associated with death before and during the COVID-19 period for individuals receiving care for these three major chronic conditions of interest in South Africa.

Results: Among individuals receiving care for chronic conditions in primary healthcare facilities there was a general increase across the years from 2015 to 2021; HIV from 23.3 to 48.8%; for hypertension from 31.1 to 46.1%; and for diabetes from 5.1 to 6.4%. Mortality rates, particularly among females, as well as individuals, aged 65+, increased from 2019 to 2021 (during the pandemic) reversing the progressive declining trend from 2016 to 2019. Mortality rate among persons with HIV, and diabetes or hypertension increased by up to 26% and 70%, respectively during the COVID-19 pandemic period, particularly among women. Differences were noted across individual and household factors, with age, sex, and education being associated with mortality risk for persons living with HIV, hypertension and/or diabetes.

Conclusions: This study shows increased mortality during the COVID-19 pandemic for individuals with chronic conditions in a rural South African setting, particularly among the elderly with hypertension, and diabetes, as well as those with comorbidity. The findings highlight the need to strengthen HIV, diabetes, and hypertension screening and care programmes to improve survival outcomes, especially in times of pandemics like COVID-19.

Background: Before COVID-19, knowledge on pandemic vulnerability and mortality in South Africa was largely limited to the context of HIV/AIDS. We evaluated mortality rates and risk of death, prior to and during the COVID-19 pandemic, in relation to an individual's COVID-19 vulnerability, based on a scoring algorithm developed in South Africa.

Methods: The analysis was undertaken using data from a health and demographic surveillance system (HDSS) in Soweto and Thembelihle, Gauteng, South Africa. Health and demographic population-based data have been collected from the HDSS area since 2018. Using indicators included in a COVID-19 Vulnerability Index, previously developed in South Africa, the current study established a composite COVID-19 vulnerability index, stratified into tertiles. The risk of death pre-COVID-19 (1 January 2018-28 February 2020) and during the COVID-19 period (1 March 2020-31 December 2021) was analysed. A Cox proportional hazard model was used to compare the risk of death between the two time periods. Statistical analyses were conducted using Stata software version 17.

Results: Before COVID-19, overall mortality rates were 8.1 (95% CI 7.6-8.8), 7.0 (95% CI 6.4-7.7) and 6.1 (95% CI 5.5-6.7) per 1000 person-years in the lowest, middle, and highest tertile of vulnerability index, respectively. All cause-mortality across all tertiles more than doubled during the COVID-19 period compared to pre-COVID-19 (15.5 against 7.2). The mortality rates during the COVID-19 era were 17.1 (95% CI 16.3-18.0), 14.5 (95% CI 13.4-15. 7) and 13.7 (95% CI 12.8-14.7) per 1000 person-years in the lowest, middle, and highest tertiles, respectively. Overall, individuals in the highest tertile of COVID-19 vulnerability were at a significantly lower risk of death relative to those in the lowest tertile (aHR 0.9, 95% CI 0.8-1.0, p < 0.05). The risk of dying during the COVID-19 period for vulnerable individuals was at least double compared to the pre-COVID-19 period for each of the individual vulnerability indicators.

Conclusions: All-cause mortality during the COVID-19 era was significantly higher than the pre- COVID-19 period, with the increase observed across all vulnerability tertiles. It is important to identify vulnerable individuals and communities during the early stages of a pandemic to inform prioritisation of public health intervention.

Background: Single-child families represent an expanded phenomenon in recent years due to prevailing socio-economic challenges. The single childbirth phenomenon can potentially cause negative population growth and undesirable effects on families. Thus, this study aimed to determine the prevalence (percent) of single-child families with an emphasis on interfering associated factors.

Methods: For paper collection, valid databases of PubMed, Embase, ScienceDirect, Web of Science, Scopus, and Google Scholar search engine were systematically searched. All relevant studies were transferred to EndNote software (v.8) for duplicate detection. Primary and secondary screenings were applied and eligible studies enrolled for meta-analysis (CMA v.2). In this regard, the random effect model was employed and the I² index was used for heterogeneity assessment.

Results: Following the examination of 33 studies, the prevalence (percent) of single-child families was found 41.3% (95% CI:33.1-49.9%). Meta-regression analysis revealed that following the acceleration in sample size and year of paper publication, the prevalence (percent) of single-child family increases and decreases (p < 0.05). Additionally, various influential factors effective on single-child families were listed as income status, financial difficulties, religious beliefs, educational level, and employment status.

Conclusion: According to the relatively high prevalence (percent) of single-child families and the influential impacts on families and communities, the findings of this study can provide valuable insights for policymakers to design appropriate policies and achieve demographic balance.

Many studies have recognized that a woman's reproductive history influences the survival status of her fetus and the newborn. In the esteemed literature of demography, abundant evidence acknowledges the linkage between maternal exposure to offspring and their associated adult outcomes and the other way around. This study examines the link between maternal risk factors at birth and long-term outcomes for daughters in India. Using national health survey data, it focuses on three maternal risks: young age, high parity, and short birth intervals. Applying regression analysis to cohort data, the study finds these early-life disadvantages are associated with daughters experiencing stunted growth, undernutrition, child mortality, and low birth weight, as well as limited education and employment. Conversely, daughters of educated mothers have better outcomes, highlighting the importance of maternal education. The pseudo-cohort approach provides valuable longitudinal insights from cross-sectional surveys. The study underscores the need for policies promoting healthy reproductive practices and education access to improve long-term outcomes for women in India.

Background: Diabetes prevalence is increasing worldwide, particularly in developing countries and disadvantaged groups. Alongside this phenomenon, the expansion of educational attainment has led to changes in population educational composition, which can significantly influence social disparities in diabetes and its risk factors, including obesity. This paper explores the role of changing educational composition in shaping the future burden of excess body weight and diabetes in Indonesia, a country with a rapidly growing prevalence of both diabetes and obesity.

Methods: We utilise three data sources as the inputs for our projection model. Panel data from the Indonesia Family Life Survey (IFLS) for 2007 and 2014 were used to compute health transition probabilities by age, sex, and education status using a multinomial logit model. Results from a dried blood test were used to adjust for undiagnosed diabetes in the projection model. The Indonesian National Health Surveys (Riskesdas) in 2007, 2013, and 2018 were used to estimate the prevalence of excess body weight and diabetes by age, sex, and education. Finally, we used projections of Indonesia's population size and composition by age, sex and education level for the period 2010 to 2060 from the Wittgenstein Centre Human Capital Data Explorer version WIC2018 v2. We employ a cohort component model with microsimulation to project the population forward.

Results: The estimated prevalence of diabetes from our projection model incorporating population education composition is 7.8% in 2010 and is expected to reach 16.7% by 2060. The most rapid increase in prevalence (14% growth in 50 years) is estimated among people with primary education, while other groups show smaller rises.

Conclusion: Incorporating population educational composition into projections of the burden of excess body weight and diabetes provides valuable insights into social disparities in diabetes over time. This can inform policy decisions by helping to prioritise healthcare budgets, targeted disease prevention programs, and diabetes treatment for high-risk groups based on educational status.

Introduction: Low socioeconomic status (SES) and unhealthy lifestyle are known risk factors for hypertension, but their impact on early-onset hypertension remains unclear.

Methods: A nationwide cohort study using UK Biobank data included 128,918 adults. SES was classified as high, medium, or low through latent class analysis of household income, employment, and education. A healthy lifestyle score was based on nonsmoking, moderate alcohol use, physical activity, and diet quality. Early-onset hypertension was defined as diagnosis before age 50; late-onset hypertension was diagnosed at 50 or older.

Results: Early-onset hypertension incidence was 2.93%, while late-onset was 14.45%. In early-onset hypertension, incidence increased from 2.03% in high SES to 7.35% in low SES (p < 0.001). For late-onset hypertension, incidence ranged from 9.70 to 20.74% (p < 0.001). Medium and low SES were significant risk factors for both forms of hypertension. The mediation effect of a healthy lifestyle on early-onset hypertension was 3.16%, and 0.42% for late-onset. Low SES combined with an unhealthy lifestyle increased early-onset hypertension risk by 356% and late-onset by 105%. The strength of the associations between risk factors for early-onset hypertension was greater than that for late-onset hypertension, particularly for low SES, obesity, and low education level.

Conclusions: Low SES is a stronger risk factor for early-onset hypertension than late-onset. A healthy lifestyle provides significant protection, especially in low SES groups. Tailored interventions addressing SES, education, and obesity are essential for preventing both early- and late-onset hypertension.

Background: The evolution of family structures in China has led to changes in the living arrangements of older adults, resulting in an increasing prevalence of individuals living alone. This shift has raised concerns about the impact on the well-being of older adults, particularly in relation to loneliness. The objective of this study is to examine the association between living alone and lonely life expectancy (LLE) among older adults, with particular attention to gender differences.

Methods: This study analyzed data from 9664 individuals aged 65-105, drawn from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) conducted in 2008, 2011, 2014, and 2018. A multistate life table approach, coupled with interpolation Markov Chain methods using IMaCh software (version 0.99r43), was employed to estimate age-specific transition probabilities, life expectancy (LE), lonely life expectancy (LLE), and the proportion of LLE to LE (LLE/LE). The analysis was stratified by gender and living arrangements, distinguishing between individuals living alone and those not living alone.

Results: The study identified several key findings. First, while LE has increased among older adults in China, they continue to experience a substantial duration of LLE. Second, older adults living alone experienced both longer LLE and higher LLE/LE ratios. Specifically, the LLE/LE among individuals not living alone was 13.61% higher for males and 15.18% higher for females compared to those living alone. Third, among females living alone, the LLE/LE was the highest, reaching 39.48% at age 65, compared to just 20.96% for males not living alone.

Conclusions: Tackling persistent loneliness is essential for enhancing the quality of life among older adults, highlighting the need to integrate mental well-being into social welfare policies. As China's population ages and family structures continue to evolve, living arrangements emerge as crucial policy indicators. Prioritizing the mental health of older adults, particularly women living alone, is critical for the development of effective social security policies.

Background: In this scoping review, we aimed to examine evidence on methods used to construct disability indicators in linked administrative datasets and describe the approaches used to assess the validity of the indicators.

Methods: Medline (Ovid) and Embase (Ovid) were searched for studies published between January 2010 and June 2023. Original, peer-reviewed studies that aimed to construct a disability indicator using linked administrative data sources were included. Studies identifying any types of disability were included, but not those which defined the target population in terms of specific health conditions. We produced a narrative synthesis of findings related to disability indicator construction methods and validation approaches.

Results: Thirty-six relevant studies were included, with 30 of those identifying a cohort of people with intellectual and/or developmental disability. Health data sources were most commonly used for indicator construction, with 33 of the studies using at least one health data source. Disability and education sector data sources were also commonly used. Diagnostic codes were used for disability identification in 34 of the 36 studies; 16 used diagnostic codes alone and 18 used diagnostic codes along with other information. A subgroup of 19 studies had a primary aim to create a disability cohort or estimate disability prevalence. Thirteen of these 19 studies compared their estimated prevalence rates with previously published estimates. Only five studies conducted testing to investigate the extent to which their derived disability indicator captured the intended target population.

Discussion: We found a paucity of evidence on methods for identifying a target population of people with diverse disabilities. In the existing literature, diagnostic information is relied upon heavily for disability identification, likely due to a lack of other types of disability-relevant information in administrative data sources. Use of derived disability indicators within linked data holds potential to advance research regarding people with disability. It is crucial, however, to conduct and report validation testing to understand the strengths and limitations of the indicators and inform their use for specific purposes.

Background: Pregnancy is a period marked by significant physiological and psychological changes in women and increased fetal nutritional requirements, necessitating maternal adaptation and behavior modifications. Clinicians and health institutions recommend pregnant women engage in healthy practices, such as smoking and alcohol cessation, folic acid consumption, vaccinations, and the like. As behavioral changes in general, the individual's conduct during pregnancy is also influenced not only by personal socio-economic status but also by the socio-economic conditions of the individual's area of residence. This mechanism is recognized by the social epidemiological approach and relates to the concept of neighborhood effect on individual health-related choices. Leveraging such considerations, the work aims to explore the association between selected behaviors recommended by clinicians during pregnancy and specific contextual variables in the residential areas where pregnant women live.

Methods: Data from the "MAMI-MED" cohort, recruiting pregnant women during the first prenatal visit at a hospital in Catania (Italy), were analyzed. The cohort provides a valuable resource for investigating the relationship between various exposures during pregnancy and the health outcomes of both mothers and infants. Geocoding techniques were employed to link individual-level data to selected contextual variables related to education, income, unemployment, and housing costs in the participants' residential areas. Mann-Whitney test, Kruskal-Wallis tests, logistic regressions and mixtures of regressions models with concomitant variables are implemented 1) to investigate the associations between contextual covariates and individual responses, 2) to assess the presence of latent sub-groups of the population reacting differently to the same contextual factors.

Results: The results of Mann-Whitney and Kruskal-Wallis tests, and logistic regressions indicated that neighborhood's socio-economic characteristics, such as educational level and unemployment rate, are associated with women's behaviors during pregnancy, smoking cessation in particular. Results from the logistic regression for BMI showed that obese and overweight individuals tend to live in neighborhoods where the percentage of individuals holding at least a bachelor's degree is comparatively lower. A mixture of regressions predicting individual BMI detected the presence of two latent groups in the population under analysis. The main finding seems to suggest that people living in worse socio-economic environments have a higher sensitivity to changes in education conditions, with respect to individuals living in better-off neighborhoods.

Conclusions: These findings highlight the importance of considering social and contextual dimensions in understanding and promoting healthy behaviors during pregnancy.