Interaction of Socioeconomic Status and Provider Practices as Predictors of Immunization Coverage in Virginia Children

PEDIATRICS ◽  
1995 ◽  
Vol 96 (3) ◽  
pp. 439-446
Author(s):  
Ian T. Williams ◽  
Jack D. Milton ◽  
James B. Farrell ◽  
Neil M. H. Graham

Objective. To describe the pattern of immunization in the cohort of children who entered public schools in Virginia in 1992. Design. This was a historic cohort study using stratified cluster sampling. Three strata were created based on the socioeconomic status (SES) of the children in the catchment area of each public school in Virginia. Setting. The random sample included public elementary schools throughout Virginia. Participants. Immunization records were obtained for a randomly selected cohort of 2519 first-grade children in Virginia. Outcome Measures. Age at completion of recommended childhood vaccines was determined from birth to school entry by SES, race, and population density. Provider practices were assessed by ascertaining missed opportunities for simultaneous administration of vaccinations according to recommended schedules. Results. Although immunization completion rates were high at school entry, low levels of immunization coverage were found in all areas of Virginia at 24 months of age regardless of SES (as measured by per capita income), population density, or race. However, under-immunization was more severe for poor children in urban areas (42.3% of children in low-SES urban areas were age-appropriately immunized at 24 months of age versus 64.0% in children in high-SES rural areas). By multivariate logistic regression, race and gender were not predictors of which children were appropriately immunized at 2 years of age after adjusting for the following: SES, population density, receiving the first DTP (diphtheria, tetanus, and pertussis) or OPV (oral polio) vaccination after 3 months of age, and failure to have the first DTP administered simultaneously with the first OPV or the second DTP administered simultaneously with the second OPV. Receiving the first DTP or OPV vaccination after 3 months of age and failure to have the first and second DTP and OPV administered simultaneously were the strongest predictors of not being age-appropriately immunized at 2 years of age. The effect of failure to vaccinate simultaneously on predicting vaccination coverage at 2 years of age was strongly modified by SES. Children who attended schools located in census tracts with per capita incomes less than $10 600 and who did not have the first and second doses of DTP and OPV administered simultaneously were 33.19 times more likely not to be age-appropriately immunized at 2 years of age compared with children who attended schools located in census tracts with per capita incomes greater than $18 800 and who received the first and second doses of DTP and OPV simultaneously (95% confidence interval: 18.29 to 60.22). Conclusions. Although beginning the immunization schedule at the recommended age was crucial to appropriate vaccination later in life, provider practices were important predictors of under-immunization. Failure to administer vaccinations simultaneously strongly influenced poorer children in Virginia. Serious delays in vaccine administration were observed not only for poor children in urban areas, but also in all areas of Virginia before school entry.

Author(s):  
Patrick McCarthy ◽  
Junda Wang

Private vehicle ownership has rapidly grown with China’s economic development and increasing incomes. This paper analyzes China’s provincial demands for private vehicles during the post-opening period 2000 – 2012. Based on estimates from pooled, fi xed effects and Hausman-Taylor models, private vehicle ownership during this period grew at an average annual rate of over 20%, all else constant. The study focuses on the roles of economic, spatial, investment and regulatory factors in shaping private vehicle demands. The study fi nds that increases in GDP per capita and vehicle use cost reinforce and constrain, respectively, the strong trend toward increased ownership. And absent changes in population density, higher percentages of the population in urban areas increase the demand for private vehicles. But increasing population density provides stronger incentives for reducing vehicle demands. Municipal restrictions aimed at reducing the congestion and environmental effects of vehicle ownership and use are effective in reducing provincial demands. A separate analysis of provinces that are at least 60% urbanized identifi es important differences. Vehicle demands are income elastic and infrastructure investments have stronger effects in the most urbanized provinces than in less urbanized provinces.


2020 ◽  
Vol 41 (S1) ◽  
pp. s128-s129
Author(s):  
Hannah E. Reses ◽  
Cedric Brown ◽  
Ghinwa Dumyati ◽  
Marion Kainer ◽  
Daniel Muleta ◽  
...  

Background: Extended-spectrum β-lactamase–producing Enterobacteriaceae (ESBL-Ent) have emerged as a significant antimicrobial-resistance threat in the community in recent years. To better characterize ESBL-Ent in the community, we examined associations between community-associated ESBL-Ent incidence rates and area-based socioeconomic status (SES) characteristics. Methods: Cases were identified through active, laboratory- and population-based surveillance for ESBL-Ent in 3 Emerging Infections Program (EIP) sites (New Mexico, New York, and Tennessee) from October through December 2017. We defined a case as first isolation of Escherichia coli, Klebsiella pneumoniae, or K. oxytoca from a normally sterile body specimen or urine in a surveillance-site resident, with resistance to ≥1 extended-spectrum cephalosporin and nonresistance to all carbapenems tested. Epidemiologic data were abstracted from medical records. Cases were considered community associated if no significant prior healthcare exposures (ie, inpatient healthcare facility stay, surgery, chronic dialysis, indwelling devices, or external catheters) were documented. Case residential addresses were geocoded and linked to US Census Bureau data to obtain census-tract level SES measures. Census tracts were dichotomized by the percentage living in rural areas (0–49% or ≥50%); census tracts were stratified into quartiles for all other characteristics. Incidence rate ratios (IRR) for each measure, controlling for EIP site, were calculated using Poisson regression. Results: Among 742 ESBL-Ent cases with medical records available, 355 (47.1%) were community associated; of these, 327 case addresses (92.1%) were successfully geocoded. The combined annualized 2017 incidence rate for community-associated ESBL-Ent was 83.2 cases per 100,000 persons. The highest incidence of community-associated ESBL-Ent was seen in census tracts with the lowest median income (IRR, 1.4; 95% CI, 1.0–2.0) and with the highest percentages of persons without health insurance (IRR, 1.3; 95% CI, 1.0–1.7), with <12th-grade education (IRR, 1.5; 95% CI, 1.1–2.1), living in urban areas (IRR, 1.5; 95% CI, 1.0–2.2), foreign-born (IRR, 1.4; 95% CI, 1.0–2.0), or speaking limited English (IRR, 1.5; 95% CI, 1.1–2.0). There were no significant differences across quartiles for population density, income inequality, the percentage of the population living below poverty, or the percentage of households with crowding (>1 occupant or room). Conclusions: Social determinants of health, such as coverage for healthcare, appear to be important contributors to community-associated ESBL-Ent transmission. Higher rates in areas with more foreign-born persons and persons with limited English proficiency suggest a role for recent travel in importation and spread in specific communities. These findings provide additional information about the epidemiology of ESBL-Ent in the community and have potential implications for control efforts.Funding: NoneDisclosures: None


2011 ◽  
Vol 6 (3) ◽  
pp. 200
Author(s):  
Suci Apriani ◽  
Yayuk Farida Baliwati

The aims of study were to analyze the ecological factors such as food availability, land capacity, population density, poverty, GDP, education; and their association to the consumption of carbohydrate food sources in some rural and urban areas of Indonesia. This ecological study was conducted by analysing the 62 districts in Indonesia. The data of food consumption was part of set Riset Kesehatan Dasar (Riskesdas 2007). The data of food production, population density, poverty, GDP, and education collected from the Central Statistic Agency (BPS). The statistical test was pearson correlation and stepwise linear regression. The study shows that consumption of carbohydrate food sources in rural more than in urban area and dominated by rice. Energy contribution from carbohydrate food sources is a half of total energy contribution (55.9% in rural and 48.05% in urban). In rural area, consumption of rice, corn, cassava, and sweet potato per capita per year were 109 kg, 4.69 kg, 2.51 kg, and 0.66 kg. While in urban area, consumption of rice, corn, cassava, and sweet potato per capita per year were 95 kg, 1.24 kg, 3.51 kg, and 0.209 kg. The food availability was significantly affected to the consumption of carbohydrate food sources in rural and urban areas.


2021 ◽  
Vol 13 (1) ◽  
pp. 409
Author(s):  
Ruogu Huang ◽  
Xiangyang Li ◽  
Yang Liu ◽  
Yaohao Tang ◽  
Jianyi Lin

Water scarcity has put pressure on city development in China. With a particular focus on urban and rural effects, logarithmic mean Divisia index decomposition (LMDI) was used to analyze the water footprint per capita (WFP) of food consumption in five East China cities (Beijing, Tianjin, Shanghai, Qingdao, and Xiamen) from 2008 to 2018. Results show that the WFP of food consumption exhibited an upward tendency among all cities during the research period. Food consumption structure contributed the most to the WFP growth, mainly due to urban and rural residents’ diet shift toward a livestock-rich style. Except in Beijing, the food consumption level mainly inhibited the WFP growth due to the decrease in food consumption level per capita in urban areas. Urbanization had less influence on WFP growth for two megacities (Beijing and Shanghai) due to the strictly controlled urban population inflow policy and more positive effects for other cities. The water footprint intensity effect among cities was mainly due to uneven water-saving efficiency. Meanwhile, Beijing and Tianjin have achieved advancement in water utilization efficiency.


2019 ◽  
Vol 31 (1) ◽  
Author(s):  
Stefan Nickel ◽  
Winfried Schröder

Abstract Background The aim of the study was a statistical evaluation of the statistical relevance of potentially explanatory variables (atmospheric deposition, meteorology, geology, soil, topography, sampling, vegetation structure, land-use density, population density, potential emission sources) correlated with the content of 12 heavy metals and nitrogen in mosses collected from 400 sites across Germany in 2015. Beyond correlation analysis, regression analysis was performed using two methods: random forest regression and multiple linear regression in connection with commonality analysis. Results The strongest predictor for the content of Cd, Cu, Ni, Pb, Zn and N in mosses was the sampled species. In 2015, the atmospheric deposition showed a lower predictive power compared to earlier campaigns. The mean precipitation (2013–2015) is a significant factor influencing the content of Cd, Pb and Zn in moss samples. Altitude (Cu, Hg and Ni) and slope (Cd) are the strongest topographical predictors. With regard to 14 vegetation structure measures studied, the distance to adjacent tree stands is the strongest predictor (Cd, Cu, Hg, Zn, N), followed by the tree layer height (Cd, Hg, Pb, N), the leaf area index (Cd, N, Zn), and finally the coverage of the tree layer (Ni, Cd, Hg). For forests, the spatial density in radii 100–300 km predominates as significant predictors for Cu, Hg, Ni and N. For the urban areas, there are element-specific different radii between 25 and 300 km (Cd, Cu, Ni, Pb, N) and for agricultural areas usually radii between 50 and 300 km, in which the respective land use is correlated with the element contents. The population density in the 50 and 100 km radius is a variable with high explanatory power for all elements except Hg and N. Conclusions For Europe-wide analyses, the population density and the proportion of different land-use classes up to 300 km around the moss sampling sites are recommended.


Author(s):  
Javier Cifuentes-Faura

The pandemic caused by COVID-19 has left millions infected and dead around the world, with Latin America being one of the most affected areas. In this work, we have sought to determine, by means of a multiple regression analysis and a study of correlations, the influence of population density, life expectancy, and proportion of the population in vulnerable employment, together with GDP per capita, on the mortality rate due to COVID-19 in Latin American countries. The results indicated that countries with higher population density had lower numbers of deaths. Population in vulnerable employment and GDP showed a positive influence, while life expectancy did not appear to significantly affect the number of COVID-19 deaths. In addition, the influence of these variables on the number of confirmed cases of COVID-19 was analyzed. It can be concluded that the lack of resources can be a major burden for the vulnerable population in combating COVID-19 and that population density can ensure better designed institutions and quality infrastructure to achieve social distancing and, together with effective measures, lower death rates.


2020 ◽  
pp. 002073142098374
Author(s):  
Ashutosh Pandey ◽  
Nitin Kishore Saxena

The purpose of this study is to find the demographic factors associated with the spread of COVID-19 and to suggest a measure for identifying the effectiveness of government policies in controlling COVID-19. The study hypothesizes that the cumulative number of confirmed COVID-19 patients depends on the urban population, rural population, number of persons older than 50, population density, and poverty rate. A log-linear model is used to test the stated hypothesis, with the cumulative number of confirmed COVID-19 patients up to period [Formula: see text] as a dependent variable and demographic factors as an independent variable. The policy effectiveness indicator is calculated by taking the difference of the COVID rank of the [Formula: see text]th state based on the predicted model and the actual COVID rank of the [Formula: see text]th state[Formula: see text]Our study finds that the urban population significantly impacts the spread of COVID-19. On the other hand, demographic factors such as rural population, density, and age structure do not impact the spread of COVID-19 significantly. Thus, people residing in urban areas face a significant threat of COVID-19 as compared to people in rural areas.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Stuti Haldar ◽  
Gautam Sharma

Purpose The purpose of this study is to investigate the impacts of urbanization on per capita energy consumption and emissions in India. Design/methodology/approach The present study analyses the effects of urbanization on energy consumption patterns by using the Stochastic Impacts by Regression on Population, Affluence and Technology in India. Time series data from the period of 1960 to 2015 has been considered for the analysis. Variables including Population, GDP per capita, Energy intensity, share of industry in GDP, share of Services in GDP, total energy use and urbanization from World Bank data sources have been used for investigating the relationship between urbanization, affluence and energy use. Findings Energy demand is positively related to affluence (economic growth). Further the results of the analysis also suggest that, as urbanization, GDP and population are bound to increase in the future, consequently resulting in increased carbon dioxide emissions caused by increased energy demand and consumption. Thus, reducing the energy intensity is key to energy security and lower carbon dioxide emissions for India. Research limitations/implications The study will have important policy implications for India’s energy sector transition toward non- conventional, clean energy sources in the wake of growing share of its population residing in urban spaces. Originality/value There are limited number of studies considering the impacts of population density on per capita energy use. So this study also contributes methodologically by establishing per capita energy use as a function of population density and technology (i.e. growth rates of industrial and service sector).


2014 ◽  
Vol 18 (2) ◽  
pp. 407-416 ◽  
Author(s):  
I. Vandecasteele ◽  
A. Bianchi ◽  
F. Batista e Silva ◽  
C. Lavalle ◽  
O. Batelaan

Abstract. In Europe, public water withdrawals make up on average 30% and in some cases up to 60% of total water withdrawals. These withdrawals are becoming increasingly important with growing population density; hence there is a need to understand the spatial and temporal trends involved. Pan-European public/municipal water withdrawals and consumption were mapped for 2006 and forecasted for 2030. Population and tourism density were assumed to be the main driving factors for withdrawals. Country-level statistics on public water withdrawals were disaggregated to a combined population and tourism density map (the "user" density map) computed for 2006. The methodology was validated using actual regional withdrawal statistics from France for 2006. The total absolute error (TAE) calculated was proven to be reduced by taking into account the tourism density in addition to the population density. In order to forecast the map to 2030 we considered a reference scenario where per capita withdrawals were kept constant in time. Although there are large variations from region to region, this resulted in a European average increase of water withdrawals of 16%. If we extrapolate the average reduction in per capita withdrawals seen between 2000 and 2008, we forecast a reduction in average total water withdrawals of 4%. Considering a scenario where all countries converge to an optimal water use efficiency, we see an average decrease of 28%.


2020 ◽  
Vol 2 (1) ◽  
pp. 107
Author(s):  
Nesyana Dewi ◽  
Melti Roza Adry

This study aims to determine the effect of education, income per capita, age and knowledge on waste management in urban areas West Sumatera. This study uses secondary data in the form of cross section data of urban West Sumatera. Data obtained from BPS- Susenas West Sumatera. This study uses logistic regression analysis. The result of this study indicate that (1) education has not significant effect on waste management in urban areas West Sumatera (2) income per capita has not significant effect on waste management  in urban areas West Sumatera (3) age has not significant effect on waste management in urban areas West Sumatera (4) knowledge has a significant effect on waste management in urban areas West Sumatera


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