About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in Horse Cave, KY, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

Key observations

• Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 14,172, while the mean income for the highest quintile (20% of households with the highest income) is 109,819. This indicates that the top earners earn 8 times compared to the lowest earners.
• *Top 5%: * The mean household income for the wealthiest population (top 5%) is 144,102, which is 131.22% higher compared to the highest quintile, and 1016.81% higher compared to the lowest quintile.

Content

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

Income Levels:

• Lowest Quintile
• Second Quintile
• Third Quintile
• Fourth Quintile
• Highest Quintile
• Top 5 Percent

Variables / Data Columns

• Income Level: This column showcases the income levels (As mentioned above).
• Mean Household Income: Mean household income, in 2023 inflation-adjusted dollars for the specific income level.

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 Horse Cave median household income. You can refer the same here

Herbivores shape plant invasions through impacts on demography and dispersal, yet only demographic mechanisms are well understood. Although herbivores negatively impact demography by definition, they can affect dispersal either negatively (e.g. seed consumption), or positively (e.g. caching). Exploring the nuances of how herbivores influence spatial spread will improve forecasting of plant movement on the landscape. Here, we aim to understand how herbivores impact how fast plant populations spread through varying impacts on plant demography and dispersal. We strive to determine if, and under what conditions, we see net positive effects of herbivores, in order to find scenarios where herbivores can help promote spread. We draw on classic invasion theory to develop a stage-structured integrodifference equation model that incorporates herbivore impacts on plant demography and dispersal. We simulate seven herbivore `syndromes' (combinations of demographic and/or dispersal effects) drawn fro...

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Ecological and social factors underpinning the inequality of male mating success in animal societies can be related to sex ratio, sexual conflict between breeders, effects of non-breeders, resource dispersion, climatic conditions, and the various sequential stages of mating competition that constitute the sexual selection process. Here, we conducted an individual-based study to investigate how local resource availability and demography interact with annual climate conditions to determine the degree of male mating inequality, and thus opportunity for sexual selection across two sequential reproductive episodes (harem and subsequent mate acquisition) in a naturally regulated (feral) horse population in Sable Island National Park Preserve, Canada. Using a 5-year, spatially explicit, mark-resight dataset and hierarchical mixed-effects linear modelling, we evaluated the influence of adult sex ratio (ASR) on mating success, and then tested for effects of freshwater availability, density, unpaired male abundance, and precipitation during each breeding season. Unpaired male abundance, freshwater availability, and ASR differed in their effects on male mating success according to year and selection episode. Opportunity for sexual selection in males associated with harem acquisition increased with ASR, and unpaired male abundance further explained weather-related inter-annual variation after accounting for ASR. In contrast, once a harem was secured, ASR had little effect on male mating inequality in regards to acquiring additional females, while inter-annual variation in mating inequality increased with decreasing freshwater availability. Our findings show that local demography, resource availability, and weather effect opportunity for sexual selection in males differently depending on selection episode, and can attenuate or accentuate effects of ASR.

The Arabian horse ignites imagination throughout the world. Populations of this breed exist in many countries, and recent genetic work has examined the diversity and ancestry of a few of these populations in isolation. Here we explore seven different populations of Arabians represented by 682 horses. Three of these are Middle Eastern populations from near the historical origin of the breed, including Syrian, Persian, and Saudi Arabian. The remaining Western populations are found in Europe (the Shagya-Arabian and Polish-Arabian) and America (American-Arabian). Analysis of genetic structure was carried out using 15 microsatellite loci. Genetic distances, AMOVA, factorial correspondence analysis and a Bayesian method were applied. The results consistently show higher level of diversity within the Middle Eastern populations than the Western populations. The Western Arabian populations were the main source of among populations variation. Genetic differentiation was not strong among all Middle Eastern populations, but all American-Arabians showed differentiation from Middle Eastern populations and were somewhat uniform among themselves. Here, we explore the diversities of many different populations of Arabian horses, and find that populations not from the Middle East have noticeably lower levels of diversity, which may adversely affect the health of these populations.

Excel book containing sheets with the data sets used. Sheet ‘Straight-line Hard Surface’, ‘Straight-line Soft Surface’ and ‘Lunge’ contains data from included horses for each condition. (XLSX)

Microsoft excel file containing data used in statistical analyses. (XLSX)

A high proportion of horses in training, perceived as free from lameness by their owner, exhibit vertical movement asymmetries. These types of asymmetries are sensitive measures of lameness, but their specificity as indicators of orthopaedic pathology or locomotor function remains unclear. Equine athletes performing at a high level could be assumed to exhibit a higher degree of movement symmetry compared with the general horse population, but this has not been confirmed. This study investigated the prevalence of movement asymmetries in horses performing at a high level in three equestrian disciplines; show jumping, dressage and eventing, as well as the association between riders’ perception of horse sidedness and said movement asymmetries. Using an inertial measurement unit-based system (Equinosis), gait analysis was performed on 123 high-performing horses. The mean difference between the two vertical minimum and between the two maximum values of each stride was recorded for the head (HDmin, HDmax) and pelvis (PDmin, PDmax). The horses were defined as asymmetric if one or multiple asymmetry parameters exceeded an absolute trial mean of: >6mm for HDmin or HDmax, and >3mm for PDmin or PDmax, with standard deviation less than the respective mean value. Based on the results, 70% of the horses were classified as asymmetric, which is similar to previous findings for young riding horses and horses competing at a lower level. More than one-third of these high-performing horses had asymmetry values of similar magnitude to those seen in clinically lame horses. No clear associations were observed between rider-perceived sidedness and the vertical movement asymmetry values, indicating that the perceived unevenness between sides is not a determinant of vertical movement asymmetry. Longitudinal studies on movement asymmetries in relation to training intensity and full clinical examinations with local or systemic analgesic testing are desired as further research to determine whether these movement asymmetries indicate a welfare problem.

The number of publicly owned, private, and commercial motorcycles registered in the U.S. states and the District of Columbia reached a total of some 9.6 million units in 2022. In that same year, there were 802,500 motorcycles registered in California. U.S. motorcycle registrations by state In 2022, California and New York reported the highest amount of registered private and commercial motorcycles in the country. Not only is California the U.S. states with the highest number of motorcycles, but it is also the most populous state in the U.S. overall, representing close to 12 percent of the country’s total population. At the bottom of the ranking are Rhode Island, Delaware, and the District of Colombia with fewer than 25,000 registrations, as well as less populous states, including Wyoming and Alaska, and Hawaii. Dangerous travel Riding a motorcycle is one of the most dangerous ways to travel in the U.S. with more than 200 fatalities per billion passenger miles as of 2019. Motorcycle crashes in the United States had decreased slightly in recent years, after peaking in 2016, but saw a strong rise in 2020.

The number of social media users in Indonesia was forecast to continuously increase between 2024 and 2029 by in total **** million users (+***** percent). After the ninth consecutive increasing year, the social media user base is estimated to reach ****** million users and therefore a new peak in 2029. Notably, the number of social media users of was continuously increasing over the past years.The shown figures regarding social media users have been derived from survey data that has been processed to estimate missing demographics.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to *** countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of social media users in countries like Vietnam and Thailand.

This statistic illustrates the share of Americans who rode a bike in the last 12 months. As of September 2024, ** percent of 18 - 29 year old consumers do so in the U.S. This is according to exclusive results from the Consumer Insights Global survey which shows that a similar percentage (**%) of 30 - 49 year old customers also fall into this category.Statista Consumer Insights offer you all results of our exclusive Statista surveys, based on more than ********* interviews.

Movement asymmetry values on the lunge of horses classified as either asymmetric or symmetric in straight-line trot on a hard surface.

The available science often demonstrates the need for feral horse population control but not the degree of control required to achieve environmental conservation objectives. To better manage the influence of feral horses, we must first understand the relationship between feral horse density and environmental impact. We recorded vegetation and soil disturbance, and the sign of potential causes of this impact in two parts of the Australian Alps, the Bogong High Plains (BHP) and the Eastern Victorian Alps (EVA). We calculated density-impact functions to assist managers with determining feral horse density targets for control programmes. Minimal sign of feral horse impact was detected on the BHP, with no impact of feral horses observed along 99% of the length of transects. In contrast, impacts assigned to feral horses were significantly higher in the EVA, where a larger, higher-density population of feral horses existed. However, greater than 83% of the walked transect length was still undisturbed by feral horses in the EVA. We detected a threshold of horse impact at ~250 horse faecal piles per ha. Above this threshold, a slight increase in horse density resulted in a disproportionately large increase in impact. In this context, a relatively small population control effort may substantially reduce direct horse impact. But where horse densities exist below this threshold, considerably more expense and control effort (resulting from the difficulties related to control at low density) is likely to make very little difference to an already low level of direct impact. The combined impacts associated with the sign of deer, feral pigs, fire and humans were large compared to that of feral horses. Management of feral horses to reduce their direct impact is unlikely to be beneficial without complementary management to reduce the effects of these other agents of impact.

The five questions on rider-perceived sidedness and the respective asymmetry parameter/s used for statistical analysis of the association between rider-perceived sidedness and objectively measured vertical movement asymmetry of the head and pelvis.

The study of selection signatures helps to find genomic regions that have been under selective pressure and might host genes or variants that modulate important phenotypes. Such knowledge improves our understanding of how breeding programmes have shaped the genomes of livestock. In this study, 942 stallions were included from four, exemplarily chosen, German warmblood breeds with divergent historical and recent selection focus and different crossbreeding policies: Trakehner (N=44), Holsteiner (N=358), Hanoverian (N=319) and Oldenburger (N=221). Blood samples were collected during the health exams of the stallion preselections before licensing and were genotyped with the Illumina EquineSNP50 BeadChip. Autosomal markers were used for a multi-method search for signals of positive selection. Analyses within and across breeds were conducted by using the integrated Haplotype Score (iHS), cross-population Extended Haplotype Homozygosity (xpEHH) and Runs of Homozygosity (ROH). Oldenburger and Hanoverian showed very similar iHS signatures, but breed specificities were detected on multiple chromosomes with the xpEHH.

Abstract

The CIAS 2019 was a comprehensive statistical undertaking for the collection and compilation of information on crop cultivation, raising livestock and poultry, and aquaculture and capture fishing operations.

The main objective of the CIAS 2019 is to provide data on the current agricultural situation in the country that can be utilized by the planners and policy-makers. Specifically, the survey data is useful for:

1. Providing data at the national and province level throughout the country
2. Providing data on the current structure of the agricultural holdings growing crops and/or raising livestock and/or poultry and/or aquaculture and fishery activities in the country
3. Provide data that is comparable to the 2013 Agriculture Census data and allows for comparisons and change analysis

The data collected and generated from this survey effort will help reflect progress towards the 2030 Sustainable Development goals for the agricultural sector, focusing on:

• Goal 1: End poverty in all forms everywhere
• Goal 2: End hunger, achieve food security and improved nutrition and promote sustainable agriculture
• Goal 5: Achieve gender equality and empower all women and girls
• Goal 6: Ensure availability and sustainable management of water and sanitation for all

The survey covers the following topics:

1. Basic characteristics of agricultural holdings
2. Crop Production during the last 12 months (crop production and purpose, area utilized, crop production modes during the next 12 months)
3. Livestock Production during the last 12 months (cattle, buffalo, horse, pigs, goats, poultry, insects, raising practices during the next 12 months)
4. Aquaculture and/or Fishing Production during the last 12 months (aquaculture, fishing activity)
5. Economy during the last 12 months (other activities of the holding, shocks)
6. Households of the Holders and Co-holders (socio-demographic characteristics)
7. Labour Used by the Holding (work on the holding by the holder and household members, work by external or occasional workers)
8. Household Dwelling and Assets

The collected data is used to produce a set of tables and indicators for tracking and evaluating the impacts of government and development programs on agriculture and to compute SDG indicators related to the above Goals. For main findings from the CIAS 2019, see the Executive Summary of the CIAS 2019 Final Report.

Data was collected from household agricultural holdings and juridical agricultural holdings. Only the household agricultural holdings are included in the released microdata.

Geographic coverage

The CIAS 2019 provides national coverage and is representative at national, regional and provincial level.

The national territory is divided in four Regions or Zones, i.e. Plain Zone, Tonle Sap Lake Zone, Coastal Zone, the Plateau and Mountainous Zone, and 25 Provinces, i.e. Battambang, Banteay Meanchey, Kampong Cham, Kampong Chhnang, Kampong Speu, Kampong Thom, Kampot, Kandal, Kep, Koh Kong, Kratie, Mondul Kiri, Oddar Meanchey, Pailin, Phnom Penh, Preah Sihanouk, Preah Vihear, Prey Veng, Pursat, Ratanak Kiri, Siemreap, Stung Treng, Svay Rieng, Takeo, Tboung Khmum.

Analysis unit

Household agricultural holdings and juridical agricultural holdings NOTE: the juridical agricultural holdings are not included in the released microdata

Universe

Agricultural households (i.e. holdings in the household sector that are involved in agricultural activities, including the growing of crops, raising of livestock or poultry, and aquaculture or capture fishing activities. It was not considered a minimum threshold set to determine a household's engagement in the above mentioned activities).

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame used for CIAS 2019 listed around 14,000 villages, split in 2 or 3 Enumeration Areas (EAs) each, for a total of 35,000 EAs. For each village, the following information was available: province, district, commune, type (rural/urban), number of EAs and number of households. Given their low number of rural villages, the following districts were excluded from the frame: Province Preah Sihanouk, District Krong Preah Sihanouk, Province Siemreap, District Krong Siem Reab, Province Phnom Penh, District Chamkar Mon, Province Phnom Penh, District Doun Penh, Province Phnom Penh, District Prampir Meakkakra, Province Phnom Penh, District Tuol Kouk, Province Phnom Penh, District Ruessei Kaev, Province Phnom Penh, District Chhbar Ampov

Since the number of rural households per EA was not known, in order to calculate the number of rural households in each province the sum of the households in the villages that were classified as rural was computed. The listing operation in each sampled EA was conducted with the aim of identifying the target population, i.e. the households engaged in agricultural activities.

The adopted sampling design was a two-stage stratified sampling, with EAs as primary units and households engaged in agriculture as secondary units. It was decided to select 1,350 EAs and 12 agricultural households for each EA, for a total planned sample size of 16,000 households. The 1,350 EAs were allocated to the provinces (sampling domains) proportionally to the number of rural households. Since there are no rural villages in Phnom Penh, 50 EAs (that correspond to 60,000 rural households) were allocated to Phnom Penh Province by default and 1,300 EAs were allocated to the other provinces. In order to select the EAs within each province, the villages were ordered by district, then by commune, then by type of village (Rural-Urban) and a systematic sampling was performed, with probability proportional to size (number of households).

The screening procedure conducted in each of the 1,350 selected EAs allowed not only to identify the agricultural holdings, but also to make a partition in strata of the agricultural households in each province and apply a stratified sampling scheme for the secondary units. Details of these strata by province can be found in Annex 3 of the general CIAS 2019 report. Each province could have a different composition and definition of the strata. The units in some strata could all be selected, particularly if they were rare, while in most strata, households were sampled. In general, within provinces, the allocations in each stratum were computed proportionally to the size of the stratum in the population of the selected EAs in the province. Once the stratum allocations in each province were computed, the allocations within the province to the EAs were calculated proportionally to the size of the stratum in the selected EA with respect to the stratum size in the province, under the constraint that the total sampled households for each EA be 12. The total effective sample size of the survey was 15,994 agricultural households. The employed sampling procedure led to the production of representative estimates at the national, regional, provincial level.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The CIAS 2019 represents the first large scale survey effort conducted using Computer Assisted Personal Interview (CAPI) devices. The CIAS has been implemented using two different questionnaires for different stages of analysis.

1) Screening questionnaire: This form was used by enumerators to screen for agricultural activity among individual, private households. The form enabled the differentiation of agricultural households from non-agricultural households.

The main objective of this questionnaire was to determine which households were involved in agriculture and at what level. The information captured from the screening form was used to stratify household agricultural holdings for sample selection.

2) Main survey questionnaire: This questionnaire form was used for both household agricultural holdings and for juridical, or commercial holdings. The form consisted of 9 sections, including: a. Screening for different types of agricultural activity b. Information on the holding and holders c. Crop production activity (including crop areas planted and harvested, quantity produced, share of production sold or for home use, use of fertilizer, irrigation, pesticide, uncertified or improved seed use, etc.) d. Livestock, poultry, and insect activity (including number of holdings raising animals during the last 12 months, the number of animals present on the holding, slaughter activity, etc.) e. Aquaculture and capture fishing activity (including the number of holdings involved in these activities, aquaculture species raised, catch from capture fishing activities, etc.) f. Economy during the last 12 months (including additional income activities, shocks experienced by the holdings, etc) g. Household of the holder and co-holders (including household member demographic data, education level, etc) h. Labour used by the holding (including household and external labour and occasional workers, breakouts by gender, etc.) i. Household dwelling and assets (including types of dwelling materials, presence of bank account, etc)

The main objective of this questionnaire was to collect data across all major specialties of the agricultural sector, including crops, livestock, aquaculture and capture fishing. Additionally, the economic data, household member demographic data, agricultural labour data collect help to provide an accurate overview of the household agricultural sector.

Questionnaires were drafted based on the standard AGRISurvey Core Questionnaire with customizations made for the Cambodia agricultural environment. Questionnaires were tested and reviewed by the Technical

An online survey was conducted to determine associations between transport management and transport-related injuries and diseases in horses in Australia. The survey was composed of three sections: respondents’ demographic information, transport management strategies or procedures (before, during and after transportation) and transport diseases experienced in the previous two year period. Univariate and multivariate modelling was performed exploring associations between variables (respondents’ details and transport management strategies) and the following transport-related diseases as outcomes: traumatic injuries, diarrhoea, heat stroke, muscular problems, laminitis, transport pneumonia and colic. The survey generated 797 responses. Traumatic injuries were the most common transport-related problem, with a reported incidence of 45.0%. Younger respondents (30 in a week) were more likely to report transport-related injuries. Injury risk was also linked to the use of protections and tranquilizers prior to transport, and checking horses after the journey. Diarrhoea (20.0%) and heat stroke (10.5%) were reported more by amateur than professional horse carers. Increased risk of heat stroke was linked to the restriction of hay and water prior to transportation. Muscular problems (13.0%) appeared to be exacerbated when horse health was not assessed before journey; whilst the risk of laminitis (2.9%) was around three fold greater when post transport recovery strategies were not applied. Associations were made between transport pneumonia (9.2%) and duration of journey, and with activity (horses involved in racing at greater risk). No associations were seen between the incidence of colic (10.3%) and the variables examined. Study findings should be interpreted with caution as they represent participant perceptions and recall. Nevertheless, results support many current recommendations for safe transportation of horses. They also highlight the need to further investigate many of identified management factors to refine existing policies and practices in equine transportation.

ANOVA results for questionnaire responses tested against asymmetry parameters.

Asymmetry parameters exceeding the threshold values (standard deviation (SD) less than mean) presented for horses (n) in straight-line trials on hard and soft surfaces.

Road traffic accident is a leading cause of death and various life deformities worldwide. This burden is even higher among motorcycle riders in lower-to-middle-income countries. Despite the various interventions made to address the menace, the fatalities continue to be on the ascendency. One major area that has received little attention is the attitude and behaviour of motorcycle riders. The present study aimed to examine the contribution of traffic Locus of Control (LoC) and health belief on road safety attitude and behaviour. 317 motorcycle riders participated in the study. The participants completed a questionnaire comprising various sections such as motorcycle riding behaviour, road safety attitude, risk perception, the intention to use helmets, and traffic LoC. The results showed a significant positive correlation between road safety attitude and behaviour (r (295) = .33, p < .001). Drifting towards internal LoC was associated with more positive behaviour on the roads (r (295) = -.23, p < .001). Intention to use helmet, health motivation, perceived susceptibility, perceived benefits, and perceived barriers were the factors in the health belief model that were associated with road safety attitude (r (295) = .404, p < .001). Finally, the multiple linear regression model showed that road safety attitude and traffic LoC made significant contributions to road user behaviour [F(3, 293) = 13.73, p < .001]. These findings have important implications towards shaping responsible behaviour among motorcycle riders.