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Datasets on factors influencing the urban environmental quality of intra-urban motor parks across density areas of Lagos metropolis.

ABSTRACT: This survey data examined the factors influencing commuters' perception of environmental quality in the selected intra-urban motor parks of Ibeju Lekki, Ifako Ijaiye and Ikeja local government areas, Lagos State, Nigeria. A survey of 376 commuters was carried out. The purposive sampling technique was used for the survey while the sampling procedure evolved from the identification of the study area to the administration of questionnaire with commuters in the motor parks. Data were analyzed using descriptive (likert scale outputs) and inferential statistical techniques (factor analysis for data reduction and categorization). The datasets can be considered in the transport and environmental policies of Lagos State and Nigeria with a view to engendering a conducive environment in the intra-urban motor parks of Lagos State, Nigeria.

SUBMITTER: Agunloye OO

PROVIDER: S-EPMC6141441 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Datasets on factors influencing the urban environmental quality of intra-urban motor parks across density areas of Lagos metropolis.

Agunloye Olayinka O OO Ajakaiye Olabisi O OO Akinola Adedotun O AO Okagbue Hilary I HI Afolabi Adedeji O AO

Data in brief 20180703

This survey data examined the factors influencing commuters' perception of environmental quality in the selected intra-urban motor parks of Ibeju Lekki, Ifako Ijaiye and Ikeja local government areas, Lagos State, Nigeria. A survey of 376 commuters was carried out. The purposive sampling technique was used for the survey while the sampling procedure evolved from the identification of the study area to the administration of questionnaire with commuters in the motor parks. Data were analyzed using ...[more]

PMID: 30229088

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Project description:Previous efforts to estimate the travel time to comprehensive emergency obstetric care (CEmOC) in low- and middle-income countries (LMICs) have either been based on spatial models or self-reported travel time, both with known inaccuracies. The study objectives were to estimate more realistic travel times for pregnant women in emergency situations using Google Maps, determine system-level factors that influence travel time and use these estimates to assess CEmOC geographical accessibility and coverage in Lagos state, Nigeria. Data on demographics, obstetric history and travel to CEmOC facilities of pregnant women with an obstetric emergency, who presented between 1st November 2018 and 31st December 2019 at a public CEmOC facility were collected from hospital records. Estimated travel times were individually extracted from Google Maps for the period of the day of travel. Bivariate and multivariate analyses were used to test associations between travel and health system-related factors with reaching the facility >60 minutes. Mean travel times were compared and geographical coverage mapped to identify 'hotspots' of predominantly >60 minutes travel to facilities. For the 4005 pregnant women with traceable journeys, travel time ranges were 2-240 minutes (without referral) and 7-320 minutes (with referral). Total travel time was within the 60 and 120 minute benchmark for 80 and 96% of women, respectively. The period of the day of travel and having been referred were significantly associated with travelling >60 minutes. Many pregnant women living in the central cities and remote towns typically travelled to CEmOC facilities around them. We identified four hotspots from which pregnant women travelled >60 minutes to facilities. Mean travel time and distance to reach tertiary referral hospitals were significantly higher than the secondary facilities. Our findings suggest that actions taken to address gaps need to be contextualized. Our approach provides a useful guide for stakeholders seeking to comprehensively explore geographical inequities in CEmOC access within urban/peri-urban LMIC settings.

Project description:Inappropriate and excessive antibiotic use fuels the development of antibiotic resistance. Determinants of antibiotic use, including knowledge and attitudes, are manifold and vary on different spatial scales. The objective of this study was to examine the associations between socio-spatially diverse urban areas and knowledge, attitudes, practices and antibiotic use within a metropolitan city. A cross-sectional survey was conducted in the general population in socio-spatially different areas in Dortmund, Germany, in February and March 2020. Three urban areas were chosen to represent diverse socio-spatial contexts (socio-spatially disadvantaged: A, intermediate: B, socio-spatially disadvantaged: C). Participants were selected via simple random sampling. The questionnaire comprised knowledge and attitude statements and questions around antibiotic use and handling practices. Differences between the areas were examined by estimating odds ratios (OR) and corresponding 95% confidence intervals by multiple logistic regression. Overall, 158 participants were included. Participants of Area C showed the lowest proportions of correct knowledge statements, indicated more often attitudes contrary to common recommendations, lower risk awareness and reported more often antibiotic use (C: 40.8%; A: 32.7%; B: 26.5%) and potential mishandling practices (C: 30.4%; A: 9.6%; B: 17.3%). The multiple logistic regression confirmed these differences. Around 42.3% (C), 33.3% (A) and 20.0% (B) of the diseases mentioned for which an antibiotic was used are mainly caused by viral pathogens. A common misconception across all areas was the perception of antibiotic resistance as an individual rather than a universal issue. This study reveals distinct differences between socio-spatially diverse urban areas within a metropolitan city, regarding knowledge, attitudes and practices around antibiotics and ABR. Our findings confirm that enhanced efforts are required to better inform the population about the adequate use and handling of antibiotics. This study emphasizes the need for future interventions to be tailored to the specific local socio-economic context.

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Datasets on factors influencing the urban environmental quality of intra-urban motor parks across density areas of Lagos metropolis.

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Datasets on factors influencing the urban environmental quality of intra-urban motor parks across density areas of Lagos metropolis.

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