Prevalence of childhood asthma in US military and non-military families: Comparisons by rural–urban residence and geographic region

Objective We sought to determine variables associated with asthma among children from military and non-military families. Methods We performed secondary data analysis on the 2016 Behavioral Risk Factor Surveillance System. Parents with and without military experience ( n = 61,079) were asked whether a child ever had asthma and currently has asthma. We used two multiple logistic regression models to determine the influence of rurality and geographic region on “ever” and “current” asthma in children of military and non-military families, while controlling for socio-demographic and behavioral variables. Results Overall childhood asthma prevalence for children in military families was lower than non-military families (ever, 9.7% vs. 12.9%; currently, 6.2% vs. 8.2%) in 2016. However, multiple logistic regression showed variation in “ever” and “current” asthma among children of military and non-military families by rurality and race. Discussion Developers of public health asthma interventions should consider targeting African-American children of military families living in urban areas. This population is approximately twice as likely to have asthma as Caucasian children of non-military families.

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Asthma Among Adults and Children by Urban–Rural Classification Scheme, United States, 2016-2018

Public Health Reports ◽

10.1177/00333549211047552 ◽

2021 ◽

pp. 003335492110475

Author(s):

Zijing Guo ◽

Xiaoting Qin ◽

Cynthia A. Pate ◽

Hatice S. Zahran ◽

Josephine Malilay

Keyword(s):

Classification Scheme ◽

Asthma Prevalence ◽

Behavioral Risk ◽

Local Policy ◽

Current Asthma ◽

Control Programs ◽

Behavioral Risk Factor Surveillance ◽

Urban Rural ◽

Adults And Children ◽

State And Local

Objectives Although data on the prevalence of current asthma among adults and children are available at national, regional, and state levels, such data are limited at the substate level (eg, urban–rural classification and county). We examined the prevalence of current asthma in adults and children across 6 levels of urban–rural classification in each state. Methods We estimated current asthma prevalence among adults for urban–rural categories in the 50 states and the District of Columbia and among children for urban–rural categories in 27 states by analyzing 2016-2018 Behavioral Risk Factor Surveillance System survey data. We used the 2013 National Center for Health Statistics 6-level urban–rural classification scheme to define urban–rural status of counties. Results During 2016-2018, the current asthma prevalence among US adults in medium metropolitan (9.5%), small metropolitan (9.5%), micropolitan (10.0%), and noncore (9.6%) areas was higher than the asthma prevalence in large central metropolitan (8.6%) and large fringe metropolitan (8.7%) areas. Current asthma prevalence in adults differed significantly among the 6 levels of urban–rural categories in 19 states. In addition, the prevalence of current asthma in adults was significantly higher in the Northeast (9.9%) than in the South (8.7%) and the West (8.8%). The current asthma prevalence in children differed significantly by urban–rural categories in 7 of 27 states. For these 7 states, the prevalence of asthma in children was higher in large central metropolitan areas than in micropolitan or noncore areas, except for Oregon, in which the prevalence in the large central metropolitan area was the lowest. Conclusions Knowledge about county-level current asthma prevalence in adults and children may aid state and local policy makers and public health officers in establishing effective asthma control programs and targeted resource allocation.

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Air Pollutants, Climate, and the Prevalence of Pediatric Asthma in Urban Areas of China

BioMed Research International ◽

10.1155/2016/2935163 ◽

2016 ◽

Vol 2016 ◽

pp. 1-8 ◽

Cited By ~ 3

Author(s):

Juanjuan Zhang ◽

Jihong Dai ◽

Li Yan ◽

Wenlong Fu ◽

Jing Yi ◽

...

Keyword(s):

Regression Analysis ◽

Multiple Regression Analysis ◽

Multiple Regression ◽

Childhood Asthma ◽

Urban Areas ◽

Air Pollutants ◽

Climatic Factors ◽

Pearson Correlation ◽

Predictor Variable ◽

Asthma Prevalence

Background. Prevalence of childhood asthma varies significantly among regions, while its reasons are not clear yet with only a few studies reporting relevant causes for this variation.Objective. To investigate the potential role of city-average levels of air pollutants and climatic factors in order to distinguish differences in asthma prevalence in China and explain their reasons.Methods. Data pertaining to 10,777 asthmatic patients were obtained from the third nationwide survey of childhood asthma in China’s urban areas. Annual mean concentrations of air pollutants and other climatic factors were obtained for the same period from several government departments. Data analysis was implemented with descriptive statistics, Pearson correlation coefficient, and multiple regression analysis.Results. Pearson correlation analysis showed that the situation of childhood asthma was strongly linked with SO2, relative humidity, and hours of sunshine (p<0.05). Multiple regression analysis indicated that, among the predictor variables in the final step, SO2was found to be the most powerful predictor variable amongst all (β=-19.572,p< 0.05). Furthermore, results had shown that hours of sunshine (β=-0.014,p< 0.05) was a significant component summary predictor variable.Conclusion. The findings of this study do not suggest that air pollutants or climate, at least in terms of children, plays a major role in explaining regional differences in asthma prevalence in China.

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Postnatal care coverage and its determinants in Sri Lanka: analysis of the 2016 demographic and health survey

BMC Pregnancy and Childbirth ◽

10.1186/s12884-021-03770-0 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Upuli Amaranganie Pushpakumari Perera ◽

Yibeltal Assefa ◽

Uttara Amilani

Keyword(s):

Logistic Regression ◽

Health Survey ◽

Urban Areas ◽

Postnatal Care ◽

Maternal Age ◽

Secondary Analysis ◽

Demographic And Health Survey ◽

Multiple Logistic Regression ◽

Logistic Regression Models ◽

Socio Demographic Factors

Abstract Background Postnatal care (PNC) is important for preventing morbidity and mortality in mothers and newborns. Even though its importance is highlighted, PNC received less attention than antenatal care. This study determines the level of PNC coverage and its determinants in Srilanka. Methods This is a secondary analysis of the 2016 Demographic and Health Survey. Receiving full postnatal care (FPNC) was defined with a set of indicators to detect adequate care for mother and newborn. Demographic and socio-economic associated factors for receiving FPNC were identified using binary and multiple logistic regression. Variables that had marginal relationship with receiving FPNC which p-value less than or equal to 0.2 at binary analysis were selected and included in the multiple logistic regression models. We used manual backward stepwise regression to identify variables which had independent association with receiving FPNC on the basis of adjusted odds ratios (AOR), with 95% confidence interval (CI) and p-value less than 0.05. All analyses were performed in SPSS 25. Results Of the 8313 women with a live birth in the last 5 years, more than 98% had received postnatal care at facility at least 24 h. More than three-fourth of mothers (n = 5104) received the FPNC according to WHO guideline. Four factors were positively associated with receiving FPNC: mothers received antenatal home visits by Public health midwife (AOR = 1.98, 95% CI 1.65–2.39), mothers who got information about antenatal complications and places to go at antenatal clinics (AOR = 1.56, 95% CI 1.27–1.92), been Sinhala (AOR = 1.89, 95% CI 1.35–2.66) and having own mobile phone (AOR = 1.19, 95% CI 1.02–1.38). Mothers who are residing in rural area (AOR = 0.697 95% CI = 0.52–0.93] compared to those who reside in urban areas and maternal age between 20 and 34 years [AOR = 0.72, 95% CI 0.54–0.97] compared to maternal age less than 20 years were detected as negatively associated. Conclusion Receiving FPNC in Srilanka is high. However, inequity remains to be a challenge. Socio-demographic factors are associated with FPNC coverage. Strategies that aim to improve postnatal care should target improvement of non-health factors as well.

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SOME FACTORS ASSOCIATED WITH CONDOM USE AMONG BAR MAIDS IN TANZANIA

Journal of Biosocial Science ◽

10.1017/s0021932008002897 ◽

2009 ◽

Vol 41 (1) ◽

pp. 125-137 ◽

Cited By ~ 8

Author(s):

ROCKY R. J. AKARRO

Keyword(s):

Logistic Regression ◽

Urban Areas ◽

Logistic Regression Model ◽

Demographic Variables ◽

Individual Factors ◽

Policy Recommendation ◽

Multiple Logistic Regression ◽

Factors Associated ◽

The Government ◽

Socioeconomic And Demographic Factors

SummarySome socioeconomic and demographic factors contributing to the use of condoms among bar maids were studied in selected urban areas in Tanzania. Bar maids were classified according to whether or not they use condoms, and logistic regression was used in the analysis. Of the demographic variables studied, age, marital status, education level, use of alcohol and wage rate showed a significant relationship at the 1% level between individual factors and use of condoms. The odds ratios show that girls aged 10–14 are over 18,000 times more likely not to use condoms compared with women aged 30 and above. Those who drink are 6·6 times (1/0·165) less likely to use condoms compared with those who do not drink. In other words, alcohol consumption can be a stimulus for an individual not to use condoms. It is clear that young girls who drink are at the highest risk of contracting HIV/AIDS in comparison with older females. A multiple logistic regression model shows all the aforementioned factors to be significant at the 1% level. A policy recommendation is made that the government should impose restrictions as far as employment of bar maids is concerned.

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Postnatal Care Coverage and its Determinants in Sri Lanka : Analysis of the 2016 Demographic and Health Survey

10.21203/rs.3.rs-124954/v1 ◽

2020 ◽

Author(s):

Upuli Perera ◽

Uttara Amilani ◽

Yibeltal Assefa

Keyword(s):

Logistic Regression ◽

Health Survey ◽

Urban Areas ◽

Postnatal Care ◽

Maternal Age ◽

Secondary Analysis ◽

Institutional Care ◽

Demographic And Health Survey ◽

P Value ◽

Multiple Logistic Regression

Abstract Background: Postnatal care (PNC) is important for preventing morbidity and mortality in mothers and newborns. Even though its importance is highlighted, PNC received less attention than antenatal care. This study determines the level of PNC coverage and its determinants in Srilanka. Methods: This is a secondary analysis of the 2016 Demographic and Health Survey. Receiving full postnatal care (FPNC) was defined with a set of indicators to detect adequate care for mother and newborn. Demographic and socio-economic associated factors for receiving FPNC were identified using binary and multiple logistic regression. Variables that had marginal relationship with receiving FPNC which p-value less than or equal to 0.2 at binary analysis were selected and included in the multiple logistic regression models. We used manual backward stepwise regression to identify variables which had independent association with receiving FPNC on the basis of adjusted odds ratios (AOR), with 95% confidence interval (CI) and p-value less than 0.05. All analyses were performed in SPSS 25. Results: Of the 8813 women with a live birth in the last five years, more than 98% had timely institutional care from skilled staff. More than three-fourth of mothers (n=5104) received the FPNC according to WHO guideline. Four factors were positively associated with receiving FPNC: mothers received antenatal home visits by Public health midwife (AOR=1.98, 95% CI 1.65-2.39), mothers who got information about antenatal complications and places to go at antenatal clinics (AOR=1.56, 95% CI 1.27 -1.92), been Sinhala (AOR= 1.89, 95% CI 1.35-2.66) and having own mobile phone (AOR=1.19, 95% CI 1.02 -1.38). Mothers who are residing in rural area (AOR=0.697 95% CI = 0.52 – 0.93] compared to those who reside in urban areas and maternal age between 20 and 34 years [AOR= 0.72, 95% CI 0.54 – 0.97] compared to maternal age less than 20 years were detected as negatively associated. Conclusion: Receiving FPNC in Srilanka is found to be higher than other countries in the region. However, inequity remains to be a challenge. Few socio-demographic factors are associated with FPNC coverage. Strategies that aim to improve postnatal care should target improvement of social determinates of health.

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Impact of malaria control interventions on malaria infection and anaemia in areas with irrigated schemes: a cross-sectional population-based study in Sudan

BMC Infectious Diseases ◽

10.1186/s12879-021-06929-4 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Khalid Abdelmutalab Elmardi ◽

Ishag Adam ◽

Elfatih Mohammed Malik ◽

Hmooda Toto Kafy ◽

Mogahid Sheikheldien Abdin ◽

...

Keyword(s):

Logistic Regression ◽

Malaria Control ◽

Urban Areas ◽

Malaria Infection ◽

Multiple Logistic Regression Analysis ◽

Indoor Residual Spraying ◽

Multiple Logistic Regression ◽

Cross Sectional ◽

Malaria Interventions ◽

Children Under 5

Abstract Background While the overall burden of malaria is still high, the global technical strategy for malaria advocates for two sets of interventions: vector control-based prevention and diagnosis and prompt effective treatment of malaria cases. This study aimed to assess the performance of malaria interventions on malaria infection and anaemia in irrigated areas in Sudan. Methods Based on the Sudan 2016 national malaria indicator survey, data for two states (Gezira and Sennar), characterized by large-irrigated schemes, were analysed. Four community-level malaria interventions were used as contextual variables: utilization of malaria diagnosis, utilization of Artemisinin-based combination therapy (ACT), utilization of long-lasting insecticidal nets (LLINs) and coverage with indoor residual spraying (IRS). Association between these interventions and two outcomes: malaria infection and anaemia, was assessed separately. Malaria infection was assessed in all age groups while anaemia was assessed in children under 5 years. Multilevel multiple logistic regression analysis were conducted. Results Among 4478 individuals involved in this study distributed over 47 clusters, the overall malaria infection rate was 3.0% and 56.5% of the children under 5 years (total = 322) were anaemic. Except for IRS coverage (69.6%), the average utilization of interventions was relatively low: 52.3% for utilization of diagnosis, 33.0% for utilization of ACTs and 18.6% for LLINs utilization. The multi-level multiple logistic regression model showed that only IRS coverage was associated with malaria infection (Odds ratio 0.83 per 10% coverage, 95%Confidence Interval (95%CI) 0.74–0.94, p = 0.003) indicating that a higher level of IRS coverage was associated with less malaria infection. Anaemia was not associated with any intervention (all p values larger than 0.1). Conclusions Malaria transmission in Gezira and Sennar areas is low. IRS, with insecticide to which vectors are susceptible, is an effective malaria control intervention in irrigated schemes. Community utilization of other interventions was not associated with malaria infection in this study. This may be due to the low utilization of these interventions. However, individual use of LLINs provide personal protection. This study failed to establish an association between anaemia and malaria control interventions in low transmission areas. The higher level of malaria infection in urban areas is a cause for concern.

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Language and Literacy Predictors of Dialect Density Among School-Age African American Children From Two Geographic Regions

Language Speech and Hearing Services in Schools ◽

10.1044/2020_lshss-19-00063 ◽

2020 ◽

Vol 51 (3) ◽

pp. 807-820

Author(s):

Lena G. Caesar ◽

Marie Kerins

Keyword(s):

African American ◽

Multiple Regression ◽

Oral Language ◽

East Coast ◽

Geographic Region ◽

Literacy Skills ◽

School Age ◽

Regression Analyses ◽

Geographic Regions ◽

American Children

Purpose The purpose of this study was to investigate the relationship between oral language, literacy skills, age, and dialect density (DD) of African American children residing in two different geographical regions of the United States (East Coast and Midwest). Method Data were obtained from 64 African American school-age children between the ages of 7 and 12 years from two geographic regions. Children were assessed using a combination of standardized tests and narrative samples elicited from wordless picture books. Bivariate correlation and multiple regression analyses were used to determine relationships to and relative contributions of oral language, literacy, age, and geographic region to DD. Results Results of correlation analyses demonstrated a negative relationship between DD measures and children's literacy skills. Age-related findings between geographic regions indicated that the younger sample from the Midwest outscored the East Coast sample in reading comprehension and sentence complexity. Multiple regression analyses identified five variables (i.e., geographic region, age, mean length of utterance in morphemes, reading fluency, and phonological awareness) that accounted for 31% of the variance of children's DD—with geographic region emerging as the strongest predictor. Conclusions As in previous studies, the current study found an inverse relationship between DD and several literacy measures. Importantly, geographic region emerged as a strong predictor of DD. This finding highlights the need for a further study that goes beyond the mere description of relationships to comparing geographic regions and specifically focusing on racial composition, poverty, and school success measures through direct data collection.

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Determining the Most Valuable Clinical Variables : a Stepwise Multiple Logistic Regression Program

Methods of Information in Medicine ◽

10.1055/s-0038-1635158 ◽

1980 ◽

Vol 19 (01) ◽

pp. 42-49 ◽

Cited By ~ 5

Author(s):

B. W. Brown ◽

C. Engelhard ◽

J. Haipern ◽

J. F. Fries ◽

L. S. Coles

Keyword(s):

Logistic Regression ◽

Predictor Variable ◽

Clinical Problem ◽

Relevant Information ◽

Stepwise Logistic Regression ◽

Multiple Logistic Regression ◽

Binary Outcome ◽

Medical Problems ◽

Valuable Predictor ◽

Data Banks

In solving a clinical problem of diagnosis, prognosis, or treatment choice, a physician must select from among a large group of possible tests. In general, an ordering exists specifying which tests are most valuable in providing relevant information concerning the problem on hand. The computer program package to be described (MW) extracts appropriate data from the ARAMIS data banks and then analyzes the data by stepwise logistic regression. A binary outcome (diagnosis, prognostic event, or treatment response) is sequentially associated with possible tests, and the most powerful combination of tests is identified. For example, the most valuable predictor variable of early mortality in SLE is proteinuria, followed sequentially by anemia and absence of arthritis. Experience with these techniques suggests : 1. optimal certainty is usually reached after only three or four tests; 2. several different test sequences may lead to the same level of certainty; 3. diagnosis may usually be ascertained with greater certainty than prognosis; 4. many medical problems contain considerable non-reducible uncertainty; 5. a relatively small group of tests are typically found among the most powerful; 6. results are consistent across several patient populations; 7. results are largely independent of the particular statistic employed. These observations suggest strategies for maximizing information while minimizing risk and expense.

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