Rank, number of deaths, percentage of deaths, and age-specific mortality rates for the leading causes of death, by age group and sex, 2000 to most recent year.

Number of deaths and age-specific mortality rates for selected grouped causes, by age group and sex, 2000 to most recent year.

Demographic Trends and Health Outcomes in the U.S

Inequalities,Risk Factors and Access to Care

By Data Society [source]

About this dataset

This dataset contains key demographic, health status indicators and leading cause of death data to help us understand the current trends and health outcomes in communities across the United States. By looking at this data, it can be seen how different states, counties and populations have changed over time. With this data we can analyze levels of national health services use such as vaccination rates or mammography rates; review leading causes of death to create public policy initiatives; as well as identify risk factors for specific conditions that may be associated with certain populations or regions. The information from these files includes State FIPS Code, County FIPS Code, CHSI County Name, CHSI State Name, CHSI State Abbreviation, Influenza B (FluB) report count & expected cases rate per 100K population , Hepatitis A (HepA) Report Count & expected cases rate per 100K population , Hepatitis B (HepB) Report Count & expected cases rate per 100K population , Measles (Meas) Report Count & expected cases rate per 100K population , Pertussis(Pert) Report Count & expected case rate per 100K population , CRS report count & expected case rate per 100K population , Syphilis report count and expected case rate per 100k popuation. We also look at measures related to preventive care services such as Pap smear screen among women aged 18-64 years old check lower/upper confidence intervals seperately ; Mammogram checks among women aged 40-64 years old specified lower/upper conifence intervals separetly ; Colonosopy/ Proctoscpushy among men aged 50+ measured in lower/upper limits ; Pneumonia Vaccination amongst 65+ with loewr/upper confidence level detail Additionally we have some interesting trend indicating variables like measures of birth adn death which includes general fertility ratye ; Teen Birth Rate by Mother's age group etc Summary Measures covers mortality trend following life expectancy by sex&age categories Vressionable populations access info gives us insight into disablilty ratio + access to envtiromental issues due to poor quality housing facilities Finally Risk Factors cover speicfic hoslitic condtiions suchs asthma diagnosis prevelance cancer diabetes alcholic abuse smoking trends All these information give a good understanding on Healthy People 2020 target setings demograpihcally speaking hence will aid is generating more evience backed policies

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How to use the dataset

What the Dataset Contains

This dataset contains valuable information about public health relevant to each county in the United States, broken down into 9 indicator domains: Demographics, Leading Causes of Death, Summary Measures of Health, Measures of Birth and Death Rates, Relative Health Importance, Vulnerable Populations and Environmental Health Conditions, Preventive Services Use Data from BRFSS Survey System Data , Risk Factors and Access to Care/Health Insurance Coverage & State Developed Types of Measurements such as CRS with Multiple Categories Identified for Each Type . The data includes indicators such as percentages or rates for influenza (FLU), hepatitis (HepA/B), measles(MEAS) pertussis(PERT), syphilis(Syphilis) , cervical cancer (CI_Min_Pap_Smear - CI_Max\Pap \Smear), breast cancer (CI\Min Mammogram - CI \Max \Mammogram ) proctoscopy (CI Min Proctoscopy - CI Max Proctoscopy ), pneumococcal vaccinations (Ci min Pneumo Vax - Ci max Pneumo Vax )and flu vaccinations (Ci min Flu Vac - Ci Max Flu Vac). Additionally , it provides information on leading causes of death at both county levels & national level including age-adjusted mortality rates due to suicide among teens aged between 15-19 yrs per 100000 population etc.. Furthermore , summary measures such as age adjusted percentage who consider their physical health fair or poor are provided; vulnerable populations related indicators like relative importance score for disabled adults ; preventive service use related ones ranging from self reported vaccination coverage among men40-64 yrs old against hepatitis B virus etc...

Getting Started With The Dataset

To get started with exploring this dataset first your need to understand what each column in the table represents: State FIPS Code identifies a unique identifier used by various US government agencies which denote states . County FIPS code denotes counties wi...

Abstract Mortality indicators for Brazilians aged between 10 and 24 years old were analyzed. Data were obtained from the Global Burden of Disease (GBD) 2019 Study, and absolute numbers, proportion of deaths and specific mortality rates from 1990 to 2019 were analyzed, according to age group (10 to 14, 15 to 19 and 20 to 24 years), sex and causes of death for Brazil, regions and Brazilian states. There was a reduction of 11.8% in the mortality rates of individuals aged between 10 and 24 years in the investigated period. In 2019, there were 13,459 deaths among women, corresponding to a reduction of 30.8% in the period. Among men there were 39,362 deaths, a reduction of only 6.2%. There was an increase in mortality rates in the North and Northeast and a reduction in the Southeast and South states. In 2019, the leading cause of death among women was traffic injuries, followed by interpersonal violence, maternal deaths and suicide. For men, interpersonal violence was the leading cause of death, especially in the Northeast, followed by traffic injuries, suicide and drowning. Police executions moved from 77th to 6th place. This study revealed inequalities in the mortality of adolescents and young adults according to sex, causes of death, regions and Brazilian states.

Annual age-standardised mortality rates for causes considered avoidable, treatable and preventable in England and Wales for children and young people (aged 0 to 19 years), 2001 to 2023.

Number of deaths and mortality rates, by age group, sex, and place of residence, 1991 to most recent year.

2003-2015. Global School dataset. The Global School-based Student Health Survey (GSHS) was developed by the World Health Organization (WHO) in collaboration with the United Nations' UNICEF, UNESCO, and UNAIDS; and with technical assistance from CDC. The GSHS is a school-based survey conducted primarily among students aged 13-17 years in countries around the world. It uses core questionnaire modules that address the leading causes of morbidity and mortality among children and adults worldwide: 1) Alcohol use, 2) dietary behaviors, 3) drug use, 4) hygiene, 5) mental health, 6) physical activity, 7) protective factors, 8) sexual behaviors that contribute to HIV infection, other sexually-transmitted infections, and unintended pregnancy, 9) tobacco use, and 10) violence and unintentional injury. This dataset contains global data from 2003 – 2015. Additional information about the GSHS can be found at https://www.cdc.gov/gshs/index.htm.

Malaria is a major cause of illness and death particularly among children under five years. It was estimated that more than one million children living in Africa especially, in remote areas with poor access to health services die annually from the direct and indirect effects of malaria.

This is not a large dataset. The data in the dataset was gathered for four years by a data analyst from 2019-2022. This entails many purchases of antimalarial drugs for children, teenagers, and adults. It was produced manually from sales records and with inventory software in KOTZ PETHABAM PHARMACY LTD, Ogun state, Nigeria. The dataset has twelve columns and four rows.

****Task**** - Analyze the dataset of adults, teenagers and children.

• Give your observations about each category and which year or month shows a drastic increase in the number of cases of malaria.

• Analyze pre-covid malaria cases, post-covid and during covid malaria cases.

• How can the dataset be used to help community pharmacy to stock antimalaria drugs?

• Does seasons and weather condition have an impact on cases of malaria?

IntroductionSuicide is the leading cause of death among Korean adolescents. Suicide has been found to be associated with body mass index (BMI), height, and subjective body image among adults, but investigations of these associations among adolescents are limited. Thus, we aimed to examine to what extent suicide ideation is associated with height, BMI, and subjective body image among Korean adolescents.MethodsThis study examined the data of 6,261 adolescents, selected from a nationally representative survey. The participants were divided into subgroups by sex, suicide ideation, and subjective body image. Logistic regression analyses were performed to examine the association of suicide ideation with height, BMI, and subjective body image.ResultsThe proportion of perceived obesity was high in the total sample; the height Z-score was lower for the group with suicide ideation than the group without suicide ideation; the height Z-scores were also lower for female participants with suicide ideation than those female participants without suicide ideation. The proportions of depressed mood, suicide ideation, and suicide attempts were higher among the total sample and female participants with perceived obesity than among those with a normal body image. On logistic regression, perceived obesity was positively associated with suicide ideation even after adjusting for age, height Z-score, weight Z-score, and depressed mood, whereas height Z-score was negatively associated with suicide ideation. These relationships were more prominent among female participants than among male participants.ConclusionLow height and perceived obesity, not real obesity, are associated with suicide ideation among Korean adolescents. These findings indicate that the need for an integrated approach to growth, body image, and suicide in adolescents is warranted.

BackgroundChildhood and adolescent brain and central nervous system cancers (CABCs) represent the leading cause of cancer-related mortality among individuals aged 0–19 years; however, global trends and socio-demographic disparities remain insufficiently explored.MethodsWe utilized the Global Burden of Disease (GBD) 2021 dataset to evaluate the evolving burden of CABCs across 204 countries from 1990 to 2021. We analyzed age-standardized prevalence rate (ASPR), age-standardized incidence rate (ASIR), age-standardized mortality rate (ASMR), and age-standardized disability-adjusted life years (ASDR) among individuals aged 0–19 years. Methodological approaches, including Joinpoint regression, decomposition analysis, and age-period-cohort modeling, were applied to assess trends across five Sociodemographic Index (SDI) levels. Data robustness was further enhanced through temporal smoothing and adjustments to the mortality-to-incidence ratio for pediatric populations.ResultsGlobally, ASPR exhibited a modest increase (average annual percentage change [AAPC] = 0.42, 95% CI: 0.29–0.54), while ASIR, ASMR, and ASDR demonstrated significant declines (AAPC = −0.29, −1.31, and −1.34, respectively). High-SDI regions experienced the highest ASPR (18.0 per 100,000) and ASIR (2.6 per 100,000), a reflection of advanced diagnostic capabilities and improved survival outcomes. In contrast, Low-SDI regions saw an upward trajectory in both mortality (AAPC = 0.06) and disability-adjusted life years (DALYs) with the burden disproportionately affecting children under 5 years of age. East Asia accounted for the highest burden of cases (63,271 prevalent cases in 2021), while Sub-Saharan Africa exhibited alarming increases in the incidence among young children. Decomposition analysis revealed that the global reduction in DALYs (−498,553) was predominantly offset by population growth and rising prevalence in low-resource settings.ConclusionWhile advancements in medical care have contributed to the reduction of CABC mortality in high-SDI regions, persistent disparities in Low-SDI areas necessitate urgent interventions. Targeted strategies—such as scalable diagnostic tools, establishment of regional treatment hubs, and equitable financial support through global initiatives like the WHO Childhood Cancer Initiative—are crucial to addressing these disparities. This study underscored the dual challenge of enhancing survivorship outcomes in high-income settings while rectifying systemic healthcare gaps in low-resource regions to promote global equity in pediatric oncology care.