About this dataset

Context

The dataset tabulates the Non-Hispanic population of Midwest City by race. It includes the distribution of the Non-Hispanic population of Midwest City across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Midwest City across relevant racial categories.

Key observations

Of the Non-Hispanic population in Midwest City, the largest racial group is White alone with a population of 32,954 (60.87% of the total Non-Hispanic population).

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (for Non-Hispanic) for the Midwest City
• Population: The population of the racial category (for Non-Hispanic) in the Midwest City is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Midwest City total Non-Hispanic population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Midwest City Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the Non-Hispanic population of Midwest by race. It includes the distribution of the Non-Hispanic population of Midwest across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Midwest across relevant racial categories.

Key observations

Of the Non-Hispanic population in Midwest, the largest racial group is White alone with a population of 205 (96.70% of the total Non-Hispanic population).

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (for Non-Hispanic) for the Midwest
• Population: The population of the racial category (for Non-Hispanic) in the Midwest is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Midwest total Non-Hispanic population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Midwest Population by Race & Ethnicity. You can refer the same here

The coronavirus disease (COVID-19) has revealed existing health inequalities in racial and ethnic minority groups in the US. This work investigates and quantifies the non-uniform effects of geographical location and other known risk factors on various ethnic groups during the COVID-19 pandemic at a national level. To quantify the geographical impact on various ethnic groups, we grouped all the states of the US. into four different regions (Northeast, Midwest, South, and West) and considered Non-Hispanic White (NHW), Non-Hispanic Black (NHB), Hispanic, Non-Hispanic Asian (NHA) as ethnic groups of our interest. Our analysis showed that infection and mortality among NHB and Hispanics are considerably higher than NHW. In particular, the COVID-19 infection rate in the Hispanic community was significantly higher than their population share, a phenomenon we observed across all regions in the US but is most prominent in the West. To gauge the differential impact of comorbidities on different ethnicities, we performed cross-sectional regression analyses of statewide data for COVID-19 infection and mortality for each ethnic group using advanced age, poverty, obesity, hypertension, cardiovascular disease, and diabetes as risk factors. After removing the risk factors causing multicollinearity, poverty emerged as one of the independent risk factors in explaining mortality rates in NHW, NHB, and Hispanic communities. Moreover, for NHW and NHB groups, we found that obesity encapsulated the effect of several other comorbidities such as advanced age, hypertension, and cardiovascular disease. At the same time, advanced age was the most robust predictor of mortality in the Hispanic group. Our study quantifies the unique impact of various risk factors on different ethnic groups, explaining the ethnicity-specific differences observed in the COVID-19 pandemic. The findings could provide insight into focused public health strategies and interventions.

BackgroundLymphocytic leukemia (LL) is a prominent group of hematological cancers afflicting both children and adults of all backgrounds and demographics. While treatment is improving, the confounding variables on mortality and prevalence within the patient population are poorly understood. This study utilizes the Center for Disease Control and Prevention (CDC)-WONDER database to further elucidate age-adjusted mortality rates (AAMRs) in the U.S. from 1999-2022.MethodsMortality data was obtained from the CDC-WONDER database from 1999-2022. AAMRs and trends by gender, race, region, state, urban vs. rural, and age were analyzed using a Joinpoint analysis program to calculate average annual percentage change. Statistical significance was set at p ≤0.05.ResultsBetween 1999 and 2022, there was a decrease in overall mortality rates up until 2018, followed by an increase from 2018 to 2022. Men experienced higher age-adjusted mortality rates (AAMRs) than women, though women saw a greater decrease in mortality. Patients aged 85 and older had the highest crude mortality rates from 1999 to 2019. From 2019 to 2022, the White patients/White population had the highest AAMRs, while the American Indian/Alaska Native population experienced the largest increase in mortality between 2016 and 2022. Regionally, the Midwest and West consistently had higher AAMRs compared to other regions, with the Midwest having the highest AAMR and the smallest decline in mortality. From 1999 to 2019, Iowa saw the largest increase in AAMRs, while Kansas experienced the largest increase from 2019 to 2022. Rural areas consistently had higher AAMRs than urban areas throughout the period from 1999 to 2022, with both regions showing a decline in AAMRs starting in 2020.ConclusionLL overall mortality decreased from 1999–2022 but varied significantly amongst demographic groups. The Midwest, rural, older, and non-Hispanic white populations experienced the largest mortality rates. Thus, policies and management plans should be developed accordingly to these biases in disparities.