Changes in mortality due to Chronic Liver Diseases (CLD) during the COVID-19 pandemic: Data from the United States' National Vital Statistics System.

INTRODUCTION: We assessed chronic liver disease (CLD)-related mortality in the U.S. using death data (2011-2021) obtained from National Vital Statistics System (NVSS). The average annual percentage change (AAPC) from the models selected by Joinpoint regression analysis over the pre-pandemic (2011-2019) and the 2019-2021 were reported because non-linear trend in death rates were observed over the 2011-2021. Liver-specific death was defined as an underlying cause of death and Chronic liver disease (CLD)-related death was defined as any cause of death. During the pre-pandemic, age-standardized HCC- and cirrhosis-specific death rates were annually increased by AAPC = +1.18% (95% confidence interval, 0.34% to 2.03%) and AAPC = +1.95% (1.56% to 2.35%). In contrast, during the 2019-2021, the AAPC in age-standardized cirrhosis-specific death rate (per 100,000) accelerated by up to AAPC +11.25% (15.23 in 2019 to 18.86 in 2021) whereas that in age-standardized HCC-specific death rate slowed to -0.39 (-1.32% to 0.54%) (3.86 in 2019 to 3.84 in 2021). Compared to HCC-specific deaths, cirrhosis-specific deaths were more likely to be non-Hispanic white (72.4% vs. 62.0%) and non-Hispanic American Indian and Alaska native (AIAN) (2.2% vs. 1.1%) and have NAFLD (45.3% vs. 12.5%) and ALD (27.6% vs. 22.0%). During the 2019-2021, the age-standardized HCV- and HBV-related death rate stabilized, whereas the age-standardized NAFLD- and ALD-related deaths rate increased to 20.16 in 2021 (AAPC = +12.13% [7.76% to 16.68%]) and to 14.95 in 2021 (AAPC = +18.30% [13.76% to 23.03%]), which were in contrast to much smaller incremental increases during the pre-pandemic (AAPC = +1.82% [1.29% to 2.35%] and AAPC = +4.54% [3.97% to 5.11%]), respectively). The most pronounced rise in the age-standardized NAFLD-related death rates during the pandemic was observed among AIAN (AAPC = +25.38%), followed by non-Hispanic White female (AAPC = +14.28%), whereas the age-standardized ALD-related death rates during the pandemic were highest among AIAN (AAPC = +40.65%), followed by non-Hispanic Black female (AAPC = +26.79%). CONCLUSIONS: COVID-19 pandemic had a major negative impact on cirrhosis-specific and CLD-related mortality in the U.S. with significant racial and gender disparities.

Automated mortality coding for improved health policy in the Philippines.

In 2016, the Bloomberg Philanthropies Data for Health initiative assisted the Philippine Statistical Authority in implementing Iris, an automated coding software program that enables medical death certificates to be coded according to international standards. Iris was implemented to improve the quality, timeliness, and consistency of coded data as part of broader activities to strengthen the country's civil registration and vital statistics system. This study was conducted as part of the routine implementation of Iris to ensure that automatically coded cause of death data was of sufficient quality to be released and disseminated as national mortality statistics. Data from medical death certificates coded with Iris between 2017 and 2019 were analysed and evaluated for apparent errors and inconsistencies, and trends were examined for plausibility. Cause-specific mortality distributions were calculated for each of the 3 years and compared for consistency, and annual numeric and percentage changes were calculated and compared for all age groups. The typology, reasons, and proportions of records that could not be coded (Iris 'rejects') were also studied. Overall, the study found that the Philippine Statistical Authority successfully operates Iris. The cause-specific mortality fractions for the 20 leading causes of death showed reassuring stability after the introduction of Iris, and the type and proportion of rejects were similar to international experience. Broadly, this study demonstrates how an automated coding system can improve the accuracy and timeliness of cause of death data-providing critical country experiences to help build the evidence base on the topic.

Mortality in the United States - Provisional Data, 2023.

Final annual mortality data from the National Vital Statistics System for a given year are typically released 11 months after the end of the calendar year. Provisional data, which are based on preliminary death certificate data, provide an early estimate of deaths before the release of final data. In 2023, a provisional total of 3,090,582 deaths occurred in the United States. The age-adjusted death rate per 100,000 population was 884.2 among males and 632.8 among females; the overall rate, 750.4, was 6.1% lower than in 2022 (798.8). The overall rate decreased for all age groups. Overall age-adjusted death rates in 2023 were lowest among non-Hispanic multiracial (352.1) and highest among non-Hispanic Black or African American persons (924.3). The leading causes of death were heart disease, cancer, and unintentional injury. The number of deaths from COVID-19 (76,446) was 68.9% lower than in 2022 (245,614). Provisional death estimates provide an early signal about shifts in mortality trends. Timely and actionable data can guide public health policies and interventions for populations experiencing higher mortality.

Mortality Surveillance for the COVID-19 Pandemic: Review of the Centers for Disease Control and Prevention's Multiple System Strategy.

Mortality surveillance systems can have limitations, including reporting delays, incomplete reporting, missing data, and insufficient detail on important risk or sociodemographic factors that can impact the accuracy of estimates of current trends, disease severity, and related disparities across subpopulations. The Centers for Disease Control and Prevention used multiple data systems during the COVID-19 emergency response-line-level case‒death surveillance, aggregate death surveillance, and the National Vital Statistics System-to collectively provide more comprehensive and timely information on COVID-19‒associated mortality necessary for informed decisions. This article will review in detail the line-level, aggregate, and National Vital Statistics System surveillance systems and the purpose and use of each. This retrospective review of the hybrid surveillance systems strategy may serve as an example for adaptive informational approaches needed over the course of future public health emergencies. (Am J Public Health. 2024;114(10):1071-1080. https://doi.org/10.2105/AJPH.2024.307743).

Risk Factors for Heart Failure and Coronary Artery Disease Mortality Based on the National Vital Statistics During a 25-Year Follow-up in Japan　- NIPPON DATA90.

BACKGROUND: Prevention of heart failure (HF) is a public health issue. Using the National Vital Statistics, we explored risk factors for HF and coronary artery disease (CAD) mortality. METHODS AND RESULTS: Altogether, 7,556 Japanese individuals aged ≥30 years in 1990 were followed over 25 years; of these, 139 and 154 died from HF and CAD, respectively. In multivariable Cox proportional hazard analysis, common risk factors for CAD and HF mortality were hypertension (hazard ratio [HR] 1.48 [95% confidence interval {CI} 1.00-2.20] and 2.31 [95% CI 1.48-3.61], respectively), diabetes (HR 2.52 [95% CI 1.63-3.90] and 2.07 [95% CI 1.23-3.50], respectively), and current smoking (HR 2.05 [95% CI 1.27-3.31) and 1.86 [95% CI 1.10-3.15], respectively). Specific risk factors for CAD were male sex, chronic kidney disease, history of cardiovascular disease, and both abnormal T and Q waves, with HRs (95% CIs) of 1.75 (1.05-2.92), 1.78 (1.19-2.66), 2.50 (1.62-3.88), and 11.4 (3.64-36.0), respectively. Specific factors for HF were current drinking (HR 0.43; 95% CI 0.24-0.78) and non-high-density lipoprotein cholesterol (non-HDL-C; HR 0.81; 95% CI 0.67-0.98). There was an inverse association between non-HDL-C and HF in those aged ≥65 years (HR 0.71; 95% CI 0.56-0.90), but not in those aged <65 years. CONCLUSIONS: We identified common risk factors for HF and CAD deaths; a history of cardiovascular disease was a specific risk for CAD.

The trend of the quality of cause-of-death data and its association with socio-economic indicators in Serbia in the period 2005-19.

This study aims to evaluate the temporal trend in the quality of cause-of-death data and garbage code profiles and to determine its association with socio-economic status in Serbia. A longitudinal study was assessed using data from mortality registers from 2005 to 2019. Computer application Analysis of Causes of National Deaths for Action (ANACONDA) calculates the distribution of garbage codes by severity and composite quality indicator: Vital Statistics Performance Index for Quality (VSPI(Q)). A relationship between VSPI(Q) and country development was estimated by analysing two socio-economic indicators: the Socio-demographic Index and the Human Development Index (HDI). Serbia indicates progress in strengthening cause-of-death statistics. The steady upward trend of the VSPI(Q) index has risen from 55.6 (medium quality) to 70.2 (high quality) over the examined years. Significant reduction of 'Insufficiently specified causes with limited impact' (Level 4) and an increase in the trend of 'High-impact garbage codes' (Levels 1 to 3) were evident. Decreased deaths of no policy value (annual percentage change of -1.41%) have manifested since 2014. A strong positive association between VSPI(Q) and socio-economic indicators was assessed, where the HDI has shown a stronger association with VSPI(Q). Improved socio-economic conditions on the national level are followed by enhanced cause-of-death data quality. Upcoming actions to improve quality should be directed at high-impact garbage codes. The study underlines the need to prioritise the education and training of physicians with a crucial role in death certification to overcome many cause-of-death quality issues identified in this assessment.

Under-5 mortality surveillance in low-income and middle-income countries: insights from two Health and Demographic Surveillance Systems in rural Gambia.

Without complete data on under-5 mortality, tracking progress towards achieving Sustainable Development Goal 3.2 will be challenging. Such data are also needed to ensure proper planning and prioritisation of scarce resources in low-income and middle-income countries. However, most low-income and middle-income countries have weak Civil Registration and Vital Statistics (CRVS) systems, leaving a critical gap in understanding under-5 mortality dynamics. This paper outlines a community-based approach to enhance under-5 mortality surveillance in low-income countries, using The Gambia as a case study. The methodology involves Health and Demographic Surveillance Systems (HDSSs) in Basse and Fuladu West, employing unique identification numbers, periodical household visits and collaboration with communities, village reporters and project field workers to ensure comprehensive data collection. Verbal autopsies (VAs) are conducted by trained field workers, and causes of death are determined using the physician-certified VA method. Between 1 September 2019 and 1 September 2023, 1333 deaths were detected, for which causes of death were determined for 97.1% (1294 of 1333). The most common causes of death detected were acute respiratory infections including pneumonia, sepsis, diarrhoeal diseases and birth asphyxia. Challenges include the cost of maintaining the HDSSs, poor road infrastructure, Electronic Data Capture transition challenges, and the need for national integration of HDSS data into the CRVS system. The success of this model highlights its potential for scalable and adaptable under-5 mortality surveillance in resource-limited settings.

Mortality risk following end-of-life caregiving: A population-based analysis of hospice users and their families.

Experiencing the death of a family member and providing end-of-life caregiving can be stressful on families - this is well-documented in both the caregiving and bereavement literatures. Adopting a linked-lived theoretical perspective, exposure to the death and dying of one family member could be conceptualized as a significant life stressor that produces short and long-term health consequences for surviving family members. This study uses familial-linked administrative records from the Utah Population Database to assess how variations in family hospice experiences affect mortality risk for surviving spouses and children. A cohort of hospice decedents living in Utah between 1998 and 2016 linked to their spouses and adult children (n = 37,271 pairs) provides an ideal study population because 1) hospice typically involves family members in the planning and delivery of end-of-life care, and 2) hospice admission represents a conscious awareness and acknowledgment that the decedent is entering an end-of-life experience. Thus, hospice duration (measured as the time between admission and death) is a precise measure of the family's exposure to an end-of-life stressor. Linking medical records, vital statistics, and other administrative microdata to describe decedent-kin pairs, event-history models assessed how hospice duration and characteristics of the family, including familial network size and coresidence with the decedent, were associated with long-term mortality risk of surviving daughters, sons, wives (widows), and husbands (widowers). Longer hospice duration increased mortality risk for daughters and husbands, but not sons or wives. Having other family members in the state was protective, and living in the same household as the decedent prior to death was a risk factor for sons. We conclude that relationship type and sex likely modify the how of end-of-life stressors (i.e., potential caregiving demands and bereavement experiences) affect health because of normative gender roles. Furthermore, exposure to dementia deaths may be particularly stressful, especially for women.

Variability in Alzheimer's disease mortality from European vital statistics, 2012-2020.

OBJECTIVE: Data regarding the trends in Alzheimer's disease (AD) mortality in the modern European Union (EU-27) member states are lacking. We assess the sex- and age-specific trends in AD mortality in the EU-27 member states between years 2012 and 2020. METHODS: Data on cause-specific deaths and population numbers by sex for each country of the EU-27 were retrieved through publicly available European Statistical Office (EUROSTAT) dataset from 2012 to 2020. AD-related deaths were ascertained when the ICD-10 code G30 was listed as the primary cause of death in the medical death certificate. To calculate annual trends, we assessed the average annual percent change (AAPC) with relative 95% confidence intervals (CIs) using Joinpoint regression. RESULTS: During the study period, 751,493 deaths (1.7%, 233,271 males and 518,222 females) occurred in the EU-27 because of AD. Trends in the proportion of AD-related deaths per 1000 total deaths slightly increased from 16.8% to 17.5% (p for trend <0.001). The age-adjusted mortality rate was higher in women over the entire study period. Joinpoint regression analysis revealed a stagnation in age-adjusted AD-related mortality from 2012 to 2020 among EU-27 Member States (AAMR: -0.1% [95% CI: -1.8-1.79], p = 0.94). Stratification by Country showed relevant regional disparities, especially in the Northern and Eastern EU-27 member states. CONCLUSIONS: Over the last decade, the age-adjusted AD-related mortality rate has plateaued in EU-27. Important disparities still exist between Western and Eastern European countries.

Cause-Specific Mortality Among Adults Aged ≥65 Years in the United States, 1999 Through 2020.

OBJECTIVE: Reports on recent mortality trends among adults aged ≥65 years are lacking. We examined trends in the leading causes of death from 1999 through 2020 among US adults aged ≥65 years. METHODS: We used data from the National Vital Statistics System mortality files to identify the 10 leading causes of death among adults aged ≥65 years. We calculated overall and cause-specific age-adjusted death rates and then calculated the average annual percentage change (AAPC) in death rates from 1999 through 2020. RESULTS: The overall age-adjusted death rate decreased on average by 0.5% (95% CI, -1.0% to -0.1%) per year from 1999 through 2020. Although rates for 7 of the top 10 causes of death decreased significantly, the rates of death from Alzheimer disease (AAPC = 3.0%; 95% CI, 1.5% to 4.5%) and from unintentional injuries (AAPC = 1.2%; 95% CI, 1.0% to 1.4%), notably falls (AAPC = 4.1%; 95% CI, 3.9% to 4.3%) and poisoning (AAPC = 6.6%; 95% CI, 6.0% to 7.2%), increased significantly. CONCLUSION: Public health prevention strategies and improved chronic disease management may have contributed to decreased rates in the leading causes of death. However, longer survival with comorbidities may have contributed to increased rates of death from Alzheimer disease and unintentional falls.

U.S. stillbirth surveillance: The national fetal death file and other data sources.

The National Vital Statistics System is the primary source of information on fetal deaths of 20 weeks of gestation or more in the United States. Data are cooperatively produced by jurisdiction vital statistics offices and the National Center for Health Statistics. In order to promote the uniformity of data, the National Center for Health Statistics issues The Model State Vital Statistics Act and Regulations, and produces standard certificates and reports, developed in collaboration with the states, to inform the development of jurisdictional vital records laws and regulations and data collection. While there are challenges in collecting national fetal death data, there are ongoing data quality improvement efforts to address them. Improved national fetal death data and data from other sources will continue to add insights into the risks, causes and prevention of fetal death.

Suicide Rates by Industry and Occupation - National Vital Statistics System, United States, 2021.

The suicide rate among the U.S. working-age population has increased approximately 33% during the last 2 decades. To guide suicide prevention strategies, CDC analyzed suicide deaths by industry and occupation in 49 states, using data from the 2021 National Vital Statistics System. Industry (the business activity of a person's employer or, if self-employed, their own business) and occupation (a person's job or the type of work they do) are distinct ways to categorize employment. The overall suicide rates by sex in the civilian noninstitutionalized working population were 32.0 per 100,000 among males and 8.0 per 100,000 among females. Major industry groups with the highest suicide rates included Mining (males = 72.0); Construction (males = 56.0; females = 10.4); Other Services (e.g., automotive repair; males = 50.6; females = 10.4); Arts, Entertainment, and Recreation (males = 47.9; females = 15.0); and Agriculture, Forestry, Fishing, and Hunting (males = 47.9). Major occupation groups with the highest suicide rates included Construction and Extraction (males = 65.6; females = 25.3); Farming, Fishing, and Forestry (e.g., agricultural workers; males = 49.9); Personal Care and Service (males = 47.1; females = 15.9); Installation, Maintenance, and Repair (males = 46.0; females = 26.6); and Arts, Design, Entertainment, Sports, and Media (males = 44.5; females = 14.1). By integrating recommended programs, practices, and training into existing policies, workplaces can be important settings for suicide prevention. CDC provides evidence-based suicide prevention strategies in its Suicide Prevention Resource for Action and Critical Steps Your Workplace Can Take Today to Prevent Suicide, NIOSH Science Blog.

Comparative performance of national civil registration and vital statistics systems: a global assessment.

Objective: To assess the current state of the world's civil registration and vital statistics systems based on publicly available data and to propose strategic development pathways, including priority interventions, for countries at different levels of civil registration and vital statistics performance. Methods: We applied a performance assessment framework to publicly available data, using a composite indicator highly correlated with civil registration and vital statistics performance which we then adjusted for data incomparability and missing values. Findings: Globally, civil registration and vital statistics systems score on average 0.70 (0-1 scale), with substantial variations across countries and regions. Scores ranged from less than 0.50 in emerging systems to nearly 1.00 in the most developed systems. Approximately one fifth of the world's population live in the 43 countries with low system performance (< 0.477). Irrespective of system development, health sector indicators consistently scored lower than other determinants of civil registration and vital statistics performance. Conclusion: From our assessment, we provide three main recommendations for how the health sector can contribute to improving civil registration and vital statistics systems: (i) enhanced health sector engagement in birth and death notification; (ii) a more systematic approach to training cause of death diagnostics; and (iii) leadership in the implementation of verbal autopsy methods. Four different civil registration and vital statistics improvement pathways for countries at different levels of system development are proposed, that can constitute a blueprint for regional civil registration and vital statistics strengthening activities that countries can adapt and refine to suit their capabilities, resources, and particular challenges.

Global analysis of birth statistics from civil registration and vital statistics systems.

Objective: To assess civil registration and vital statistics completeness for births in World Health Organization's Member States and identify data completeness gaps. Methods: For the 194 Member States, we sourced birth registration data from the United Nations Children's Fund database of national surveys, and, where available, vital registration reports. We acquired publicly available vital statistics compiled by national authorities. We determined civil registration completeness as the percentage of living children younger than five years whose births have been reported as registered. We evaluated vital statistics completeness against the United Nations World Population Prospects' live birth estimates, and grouped countries into seven categories based on their civil registration and vital statistics completeness. Findings: Globally, civil registration completeness for births was 77%, exceeding vital statistics completeness for births at 63%. Twenty countries had limited civil registration (25% to 74% completeness) and had nascent or no vital statistics data (completeness < 25%) for births. Five countries had nascent or no civil registration and vital statistics for births. Twenty countries had functional civil registration (75% to 94% completeness) but nascent or no available vital statistics. Approximately half (96) of the countries had complete civil registration and vital statistics for births, but contributed to only 22% of global births. Conclusion: The gap in completeness between civil registration data and vital statistics for births is most pronounced in countries with lower civil registration completeness. Enhancing data transfer processes for birth registration, along with targeted investments to elevate registration rates, is crucial for yielding comprehensive fertility statistics for governmental planning.

Temporal, seasonal, and spatial patterns in fall-related mortality in Japan: Analysis of national vital statistics from 1975 to 2019.

BACKGROUND: Falls are a significant public health issue in aging societies. This study aimed to examine the temporal, seasonal, and spatial patterns in fall-related mortality in Japan, and to investigate the potential factors associated with fall-related mortality. METHODS: The number of unintentional fall-related deaths from 1979 to 2019 were obtained from Japanese vital statistics and crude and direct age-standardized mortality rates (DSR) were calculated. We also calculated the standardized mortality ratio (SMR) to determine seasonal and prefectural differences. In addition, spatial regression was conducted to examine the potential factors associated with fall-related mortality. RESULTS: The DSR among those over 65 years old showed a decreasing trend from 1979, but remained unchanged from 1990 to 2019. Based on the spatial regression model, the factors significantly associated with SMRs were the proportion of the aged population (Coefficient: 0.049), the number of hospitals (0.118), the number of clinics (1.169), the number of hospital beds (-0.060), and the number of physiotherapists (-0.069) for men; and the proportion of aged single households (-0.060), the number of hospitals (0.132), the number of clinics (1.498), the number of hospital beds (-0.051), and the number of physicians (-0.308) for women. CONCLUSIONS: Fall-related mortality among Japanese elderly people has remained unchanged in recent years. In addition, seasonal and spatial patterns were also observed, and it was found that demographic data and healthcare resources in the prefectures affected fall-related mortality rates. Appropriate prevention measures of fall-related deaths should be considered according to the region-specific characteristics and issues.

A novel comorbidity index in Italy based on diseases detected by the surveillance system PASSI and the Global Burden of Diseases disability weights.

BACKGROUND: Understanding comorbidity and its burden characteristics is essential for policymakers and healthcare providers to allocate resources accordingly. However, several definitions of comorbidity burden can be found in the literature. The main reason for these differences lies in the available information about the analyzed diseases (i.e., the target population studied), how to define the burden of diseases, and how to aggregate the occurrence of the detected health conditions. METHODS: In this manuscript, we focus on data from the Italian surveillance system PASSI, proposing an index of comorbidity burden based on the disability weights from the Global Burden of Disease (GBD) project. We then analyzed the co-presence of ten non-communicable diseases, weighting their burden thanks to the GBD disability weights extracted by a multi-step procedure. The first step selects a set of GBD weights for each disease detected in PASSI using text mining. The second step utilizes an additional variable from PASSI (i.e., the perceived health variable) to associate a single disability weight for each disease detected in PASSI. Finally, the disability weights are combined to form the comorbidity burden index using three approaches common in the literature. RESULTS: The comorbidity index (i.e., combined disability weights) proposed allows an exploration of the magnitude of the comorbidity burden in several Italian sub-populations characterized by different socioeconomic characteristics. Thanks to that, we noted that the level of comorbidity burden is greater in the sub-population characterized by low educational qualifications and economic difficulties than in the rich sub-population characterized by a high level of education. In addition, we found no substantial differences in terms of predictive values of comorbidity burden adopting different approaches in combining the disability weights (i.e., additive, maximum, and multiplicative approaches), making the Italian comorbidity index proposed quite robust and general.

Association between gestational weight gain and adverse neonatal outcomes in women conceiving with assisted reproductive technology: Evidence from the NVSS 2019-2021.

OBJECTIVE: To evaluate the association between gestational weight gain (GWG) and adverse neonatal outcomes in women who conceived using assisted reproductive technology (ART). METHODS: The National Vital Statistics System (NVSS) 2019-2021 provided data for this retrospective cohort study. Adverse neonatal outcomes included premature birth, small for gestational age (SGA), large for gestational age (LGA), macrosomia, low birth weight (LBW), and other abnormal conditions. Any adverse outcome was defined as at least one of the above six outcomes. Multivariate logistic regression analysis was employed to evaluate the associations between GWG and different outcomes, after adjusting for confounding factors. These associations were further assessed in subgroups of maternal age at delivery, paternal age at delivery, preconception body mass index (BMI), gestational age, maternal race, parity, gestational diabetes, and gestational hypertension. RESULTS: Totally 108201 women were included, with 22282 in the insufficient GWG group, 38034 in the sufficient GWG group, and 47885 in the excessive GWG group. Women with insufficient GWG [odds ratios (OR) = 1.11, 95%CI: 1.07-1.16, P<0.001] and excessive GWG (OR = 1.14, 95%CI: 1.10-1.18, P<0.001) had significantly greater risks of any adverse outcome than those with sufficient GWG. In contrast to sufficient GWG, insufficient GWG was associated with significantly elevated risks of premature birth (OR = 1.42, 95%CI: 1.35-1.48, P<0.001), SGA (OR = 1.45, 95%CI: 1.37-1.53, P<0.001), LBW (OR = 1.47, 95%CI: 1.37-1.58, P<0.001), and other abnormal conditions (OR = 1.32, 95%CI: 1.27-1.39, P<0.001), and excessive GWG was associated with significantly lower risks of premature birth (OR = 0.86, 95%CI: 0.83-0.90, P<0.001), SGA (OR = 0.79, 95%CI: 0.75-0.83, P<0.001), LBW (OR = 0.85, 95%CI: 0.79-0.91, P<0.001), and other abnormal conditions (OR = 0.92, 95%CI: 0.88-0.96, P<0.001). Infants born to women with insufficient GWG had significantly decreased risks of LGA (OR = 0.71, 95%CI: 0.66-0.75, P<0.001) and macrosomia (OR = 0.68, 95%CI: 0.63-0.74, P<0.001), and infants born to women with excessive GWG had significantly increased risks of LGA (OR = 1.50, 95%CI: 1.44-1.56, P<0.001) and macrosomia (OR = 1.60, 95%CI: 1.51-1.69, P<0.001). CONCLUSION: Insufficient GWG and excessive GWG were associated with increased risks of any adverse outcome than sufficient GWG in women who conceived with ART, indicating the applicability of recommended GWG by the Institute of Medicine (IOM) in this population.

Road traffic death coding quality in the WHO Mortality Database.

Objective: To evaluate the precision and dependability of road traffic mortality data recorded in the World Health Organization Mortality Database and investigate how uncorrected data influence vital mortality statistics used in traffic safety programmes worldwide. Methods: We assessed country and territory-specific data quality from 2015 to 2020 by calculating the proportions of five types of nonspecific cause of death codes related to road traffic mortality. We compared age-adjusted road traffic mortality and changes in the average annual mortality rate before and after correcting the deaths with nonspecific codes. We generated road traffic mortality projections with both corrected and uncorrected codes, and redistributed the data using the proportionate method. Findings: We analysed data from 124 countries and territories with at least one year of mortality data from 2015 to 2020. The number of countries and territories reporting more than 20% of deaths with ill-defined or unknown cause was 2; countries reporting injury deaths with undetermined intent was 3; countries reporting unspecified unintentional injury deaths was 21; countries reporting unspecified transport crash deaths was 3; and countries reporting unspecified unintentional road traffic deaths was 30. After redistributing deaths with nonspecific codes, road traffic mortality changed by greater than 50% in 7% (5/73) to 18% (9/51) of countries and territories. Conclusion: Nonspecific codes led to inaccurate mortality estimates in many countries. We recommend that injury researchers and policy-makers acknowledge the potential pitfalls of relying on raw or uncorrected road traffic mortality data and instead use corrected data to ensure more accurate estimates when improving road traffic safety programmes.

Interaction between smoking during pregnancy and gestational diabetes mellitus and the risk of cesarean delivery: evidence from the National Vital Statistics System 2019.

OBJECTIVE: To explore the interaction between smoking during pregnancy (SDP) and gestational diabetes mellitus (GDM) on the risk of cesarean delivery. METHODS: This retrospective cohort study utilized data from the National Vital Statistics System (NVSS) 2019. The NVSS database provides data on births and deaths as well as maternal characteristics in the United States. The duration of follow-up was 38.74 ± 2.12 weeks. The outcome was the method of delivery, including vaginal and cesarean delivery. The multivariate logistic regression model was adopted to assess the associations of SDP and GDM with the method of delivery. The interaction between SDP and GDM was examined via calculating the relative excess risk of interaction (RERI), the attributable proportion of interaction (API) and the synergy index (S). Subgroup analyses were conducted based on age, race, prepregnancy body mass index (BMI), and primiparity. RESULTS: The study included 3352615 puerperae. Compared with women who did not smoke during pregnancy, those who smoked during pregnancy had a significantly higher risk of cesarean delivery [odds ratio (OR)=1.07, 95% confidence intervals (CI): 1.05-1.10, p < 0.001]; women with GDM had a significantly greater risk of cesarean delivery than those without (OR = 1.31, 95%CI: 1.30-1.33, p < 0.001). In contrast to women who did not smoke during pregnancy and did not have GDM, those who smoked during pregnancy and had GDM exhibited an increased risk of a cesarean section (OR = 1.47, 95%CI: 1.40-1.54, p < 0.001). RERI was 0.08 (95%CI: 0.01-0.15), API was 0.06 (95%CI: 0.01-0.10), and S was 1.21 (95%CI: 1.04-1.40) suggested that there was an interaction between SDP and GDM, and it was a synergistic effect. There was a synergism between SDP and GDM in women of non-advanced age (RERI = 0.07, 95%CI: 0.001-0.15; API = 0.05, 95%CI: 0.003-0.10; S = 1.17, 95%CI: 1.001-1.36), in white women (RERI = 0.08, 95%CI: 0.004-0.16; API = 0.05, 95%CI: 0.01-0.10; S = 1.19, 95%CI: 1.02-1.39), in women who were overweight before pregnancy (RERI = 0.13, 95%CI: 0.05-0.21; API = 0.08, 95%CI: 0.04-0.13; S = 1.33, 95%CI: 1.14-1.55), and in primiparae (RERI = 0.20, 95%CI: 0.08-0.31; API = 0.12, 95%CI: 0.06-0.19; S = 1.50, 95%CI: 1.23-1.84). CONCLUSION: SDP and GDM were associated with an increased risk of cesarean delivery, and a synergistic effect existed between SDP and GDM on the risk of cesarean delivery, especially in women of non-advanced age, white women, women who were overweight before pregnancy, and primiparae.