Energy transition pathways amongst low-income urban households: A mixed method clustering approach
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SUBMITTER: Neto-Bradley A
PROVIDER: S-EPMC8563469 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Epidemiological studies considered water use and hygiene practices as central risk factors for diarrhea. Few studies focused on independent association of water quantity with diarrheal diseases. This study aimed to describe the methodological protocol that adapted multidisciplinary and mixed-method research approach to assess how water usage including water quantity influences the attributable risk for diarrhea in a low-income urban community in Bangladesh. The quantitative, anthropological and microbiological approaches were threaded together to provide a greater understanding of the infrastructural, behavioral and microbial interactions to fathom the dimensions of fecal oral transmission pathways within the households. The use of the 'Choleraphone' (i.e. a mobile phone based real time diarrheal reporting system) was a contemporary approach intended to cut down on resources, reduce research fatigue and provide more accurate data compared to the 'gold standard' (i.e. visiting a household of diarrhea cases within 48?hours) for measuring diarrhea incidence. Development of methods to measure water quantity using qualitative and quantitative approach within a setting where meter water connection is rare was another unique feature of this protocol. This protocol provided guidance and insight on how multiple methods of different disciplines can be combined to enrich understanding of waterborne diseases.
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Project description:Background: Prepartum depression is common among pregnant women and has not been studied much in low and middle-income countries. Evidence shows that mental illnesses are prevalent in urban than in rural areas. The study objective was to determine the magnitude of prepartum depression, risk factors, and real-life experiences of depression among pregnant women. Method: A mixed-method cross-sectional study was conducted. It included 262 pregnant women attending antenatal clinics in two public health facilities in urban low-income settlement Nairobi, Kenya. Edinburgh Postnatal Depression Scale (EPDS) with cut-off >13 was used to classify clinical depressive illness. Further, a focus group discussion was conducted with 20 women identified with depression. Univariable analysis with Odd's Ratio was used to test associations. Variables with a p<0.05 in multivariable regression were considered significant. Result: Out of the 262 women, 33.6% were found to have clinical depression as indicated by EPDS score of >13. Women's gestational age was statistically significantly associated with prepartum depression [OR 4.27 (95% C.I. 2.08 - 8.79), p < 0.001]. Income level ≤ 5000 KES was statistically significantly associated with prepartum depression [OR 3.64 (95% C.I.1.25 -10.60), p=0.018]. Further, thematic analysis of qualitative indicated that poverty, lack of social support, domestic violence, and unfriendly health care were major contributors to prepartum depression. Conclusion: Significant numbers of pregnant women were found to experience depression. This prevalence rate indicates a high disease burden of women who live with depression, which is not diagnosed because screening of depression is not done in primary health care centers. This study calls for a need and consideration for screening for perinatal depression in primary health care facilities, mainly in resource-poor areas. Interventions targeting means of resolving conflicts in families are highly needed. Such steps would help achieve key sustainable development goals where maternal and child health remains key priority.
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Project description:BackgroundPsychosocial factors are important determinants of health behaviors and diet-related outcomes, yet relatively little work has explored their relation to food-purchasing and preparation behaviors in low-income populations.AimTo evaluate the psychosocial factors associated with food-related behaviors.MethodsCross-sectional data collected from 465 low-income African American adult caregivers in the baseline evaluation of the B'more Healthy Communities for Kids obesity prevention trial. Questionnaires were used to assess household sociodemographic characteristics, food sources frequently used, and food preparation and food acquisition behaviors. Multiple linear regression models explored the associations between caregiver psychosocial variables and food-related behaviors, controlling for caregivers' age, sex, household income, household size, and food assistance participation.ResultsCaregivers purchased prepared food at carry-outs on average 3.8 times (standard deviation [ SD] = 4.6) within 30 days. Less healthy foods were acquired 2 times more frequently than healthier foods ( p < .001). Higher food-related behavioral intention and self-efficacy scores were positively associated with healthier food acquisition (β = 0.7; 95% confidence interval [CI] [0.09, 1.4]; β = 0.04; 95% CI [0.02, 0.06]) and negatively associated with frequency of purchasing at prepared food sources (β = -0.4; 95% CI [-0.6, -0.2]; β = -0.5; 95% CI [-0.7, -0.3]), respectively. Higher nutrition knowledge was associated with lower frequency of purchasing food at prepared food venues (β = -0.7; 95% CI: [-1.2, -0.2]).DiscussionOur findings indicate a positive association between psychosocial determinants and healthier food acquisition and food preparation behaviors.ConclusionInterventions that affect psychosocial factors (i.e., food-related behavioral intentions and self-efficacy) may have the potential to increase healthier food preparation and food-purchasing practices among low-income African American families.
| S-EPMC6119507 | biostudies-literature
Project description:Rising temperatures are causing distress across the world, and for those most vulnerable, it is a silent killer. Information about indoor air temperature in residential dwellings is of interest for a range of reasons, such as health, thermal comfort and coping practices. However, there have been only few studies that measure indoor heat exposure, and contrast these to outdoor temperatures in rural-urban areas, of which none are in South Asia. We aim to close this knowledge gap with our indoor and outdoor heat measurement dataset, covering five low-income sites in South Asia. Two sites are in rural areas (Maharashtra, India), while three sites focus on urban areas (Dhaka, Delhi and Faisalabad). Data are based on 206 indoor temperature data loggers and complemented by data from five outdoor automated weather stations. The data-set can be used to examine temperature and humidity variation in low-socioeconomic status households in rural and urban areas and to better understand factors aggravating heat stress. This is important to plan and implement actions for combating heat stress.
| S-EPMC9184534 | biostudies-literature
Project description:In energy systems' economic models, people's behaviour is often underestimated, and they are generally unaware of how habits impact energy efficiency. Improving efficiency is challenging, and recommendations alone may not be sufficient. Changing behaviour requires understanding the direct impact of needs and habits on energy efficiency. This research introduces a methodology that retrieves human expert knowledge from four key aspects of the current energy transition: everyday appliances, buildings, mobility, flexibility, and energy efficiency. The aim is to examine the causal relationship between energy consumption and human behaviour, gaining a deeper understanding of the links among the factors that drive final energy consumers to change habits through the adoption of energy-saving measures. Working in collaboration with expert panels, this study provides a methodology for extracting expert human knowledge based on a set of future energy transition scenarios aligned with the achievement of the Paris Agreement, a taxonomy of 32 factors that have a strong influence on households' investment decisions, and the results of a survey that characterises the European population through the 32-factor taxonomy and some socioeconomic conditions. In addition, the survey included a sample of the Latin American population to analyse how socioeconomic conditions (region, education, gender, etc.) influence the prioritisation of these factors. We discuss the high priority given to competence and autonomy over financial factors by inhabitants of the European Union residential sector. We provide an analysis of the factors through which other similar projects are focused and on which we converge. In addition, we contribute by presenting the hierarchy of priorities assigned by people. This highlights the importance for policymakers to take these aspects seriously when implementing energy policy interventions that go beyond purely financial measures and fiscal incentives.
| S-EPMC10956834 | biostudies-literature
Project description:This paper explores the public perception of energy transition pathways, that is, individual behaviors, political strategies, and technologies that aim to foster a shift toward a low-carbon and sustainable society. We employed affective image analysis, a structured method based on free associations to explore positive and negative connotations and affective meanings. Affective image analysis allows to tap into affective meanings and to compare these meanings across individuals, groups, and cultures. Data were collected among university students in Norway (n = 106) and Germany (n = 125). A total of 25 energy transition pathway components were presented to the participants who generated one free association to each component by indicating the first that came to mind when thinking of the component. Participants evaluated their associations by indicating whether they considered each association to be positive, negative, or neutral. These associations were coded by two research assistants, which resulted in 2650 coded responses in the Norwegian sample and 2846 coded responses in the German sample. Results for the two samples are remarkably similar. The most frequent type of association is a general evaluation of the component, for example concerning its valence or its importance. The second most frequent types of association are requirements needed to implement the component (e.g., national policies) and consequences of the component (e.g., personal or environmental consequences). Individual behaviors (e.g., walking) elicited thoughts about consequences and requirements, but also about the prevalence of such behaviors. Associations in response to technologies (e.g., carbon capture and storage) mainly referred to some descriptive aspect of the technology. Evaluations of the free responses were predominantly positive, but some components also elicited negative associations, especially nuclear power. The free associations that people generate suggest that they have vague and unspecific knowledge about energy transition pathways, that they process them in an automatic and intuitive rather than deliberative manner, and that they have clear affective evaluations of the presented components.
| S-EPMC6191516 | biostudies-literature
Project description:Rural residential energy consumption in China is experiencing a rapid transition towards clean energy, nevertheless, solid fuel combustion remains an important emission source. Here we quantitatively evaluate the contribution of rural residential emissions to PM2.5 (particulate matter with an aerodynamic diameter less than 2.5 μm) and the impacts on health and climate. The clean energy transitions result in remarkable reductions in the contributions to ambient PM2.5, avoiding 130,000 (90,000-160,000) premature deaths associated with PM2.5 exposure. The climate forcing associated with this sector declines from 0.057 ± 0.016 W/m2 in 1992 to 0.031 ± 0.008 W/m2 in 2012. Despite this, the large remaining quantities of solid fuels still contributed 14 ± 10 μg/m3 to population-weighted PM2.5 in 2012, which comprises 21 ± 14% of the overall population-weighted PM2.5 from all sources. Rural residential emissions affect not only rural but urban air quality, and the impacts are highly seasonal and location dependent.
| S-EPMC6667435 | biostudies-literature
Project description:BackgroundBeverages, especially sugar-sweetened beverages (SSBs), have been increasingly subject to policies aimed at reducing their consumption as part of measures to tackle obesity. However, precision targeting of policies is difficult as information on what types of consumers they might affect, and to what degree, is missing. We fill this gap by creating a typology of beverage consumers in Great Britain (GB) based on observed beverage purchasing behaviour to determine what distinct types of beverage consumers exist, and what their socio-demographic (household) characteristics, dietary behaviours, and weight status are.Methods and findingsWe used cross-sectional latent class analysis to characterise patterns of beverage purchases. We used data from the 2016 GB Kantar Fast-Moving Consumer Goods (FMCG) panel, a large representative household purchase panel of food and beverages brought home, and restricted our analyses to consumers who purchase beverages regularly (i.e., >52 l per household member annually) (n = 8,675). Six categories of beverages were used to classify households into latent classes: SSBs; diet beverages; fruit juices and milk-based beverages; beer and cider; wine; and bottled water. Multinomial logistic regression and linear regression were used to relate class membership to household characteristics, self-reported weight status, and other dietary behaviours, derived from GB Kantar FMCG. Seven latent classes were identified, characterised primarily by higher purchases of 1 or 2 categories of beverages: 'SSB' (18% of the sample; median SSB volume = 49.4 l/household member/year; median diet beverage volume = 38.0 l), 'Diet' (16%; median diet beverage volume = 94.4 l), 'Fruit & Milk' (6%; median fruit juice/milk-based beverage volume = 30.0 l), 'Beer & Cider' (7%; median beer and cider volume = 36.3 l; median diet beverage volume = 55.6 l), 'Wine' (18%; median wine volume = 25.5 l; median diet beverage volume = 34.3 l), 'Water' (4%; median water volume = 46.9 l), and 'Diverse' (30%; diversity of purchases, including median SSB volume = 22.4 l). Income was positively associated with being classified in the Diverse class, whereas low social grade was more likely for households in the classes SSB, Diet, and Beer & Cider. Obesity (BMI > 30 kg/m2) was more prevalent in the class Diet (41.2%, 95% CI 37.7%-44.7%) despite households obtaining little energy from beverages in that class (17.9 kcal/household member/day, 95% CI 16.2-19.7). Overweight/obesity (BMI > 25 kg/m2) was above average in the class SSB (66.8%, 95% CI 63.7%-69.9%). When looking at all groceries, households from the class SSB had higher total energy purchases (1,943.6 kcal/household member/day, 95% CI 1,901.7-1,985.6), a smaller proportion of energy from fruits and vegetables (6.0%, 95% CI 5.8%-6.3%), and a greater proportion of energy from less healthy food and beverages (54.6%, 95% CI 54.0%-55.1%) than other classes. A greater proportion of energy from sweet snacks was observed for households in the classes SSB (18.5%, 95% CI 18.1%-19.0%) and Diet (18.8%, 95% CI 18.3%-19.3%). The main limitation of our analyses, in common with other studies, is that our data do not include information on food and beverage purchases that are consumed outside the home.ConclusionsAmongst households that regularly purchase beverages, those that mainly purchased high volumes of SSBs or diet beverages were at greater risk of obesity and tended to purchase less healthy foods, including a high proportion of energy from sweet snacks. These households might additionally benefit from policies targeting unhealthy foods, such as sweet snacks, as a way of reducing excess energy intake.
| S-EPMC7478648 | biostudies-literature
Project description:BackgroundAntimicrobial misuse is common in low-income and middle-income countries (LMICs), and this practice is a driver of antibiotic resistance. We compared community-based antibiotic access and use practices across communities in LMICs to identify contextually specific targets for interventions to improve antibiotic use practices.MethodsWe did quantitative and qualitative assessments of antibiotic access and use in six LMICs across Africa (Mozambique, Ghana, and South Africa) and Asia (Bangladesh, Vietnam, and Thailand) over a 2·5-year study period (July 1, 2016-Dec 31, 2018). We did quantitative assessments of community antibiotic access and use through supplier mapping, customer exit interviews, and household surveys. These quantitative assessments were triangulated with qualitative drug supplier and consumer interviews and discussions.FindingsVietnam and Bangladesh had the largest proportions of non-licensed antibiotic dispensing points. For mild illness, drug stores were the most common point of contact when seeking antibiotics in most countries, except South Africa and Mozambique, where public facilities were most common. Self-medication with antibiotics was found to be widespread in Vietnam (55·2% of antibiotics dispensed without prescription), Bangladesh (45·7%), and Ghana (36·1%), but less so in Mozambique (8·0%), South Africa (1·2%), and Thailand (3·9%). Self-medication was considered to be less time consuming, cheaper, and overall, more convenient than accessing them through health-care facilities. Factors determining where treatment was sought often involved relevant policies, trust in the supplier and the drug, disease severity, and whether the antibiotic was intended for a child. Confusion regarding how to identify oral antibiotics was revealed in both Africa and Asia.InterpretationContextual complexities and differences between countries with different incomes, policy frameworks, and cultural norms were revealed. These contextual differences render a single strategy inadequate and instead necessitate context-tailored, integrated intervention packages to improve antibiotic use in LMICs as part of global efforts to combat antibiotic resistance.FundingWellcome Trust and Volkswagen Foundation.
| S-EPMC8050200 | biostudies-literature
Project description:Dual-energy computed tomography (DECT) imaging plays an important role in advanced imaging applications due to its material decomposition capability. Image-domain decomposition operates directly on CT images using linear matrix inversion, but the decomposed material images can be severely degraded by noise and artifacts. This paper proposes a new method dubbed DECT-MULTRA for image-domain DECT material decomposition that combines conventional penalized weighted-least squares (PWLS) estimation with regularization based on a mixed union of learned transforms (MULTRA) model. Our proposed approach pre-learns a union of common-material sparsifying transforms from patches extracted from all the basis materials, and a union of cross-material sparsifying transforms from multi-material patches. The common-material transforms capture the common properties among different material images, while the cross-material transforms capture the cross-dependencies. The proposed PWLS formulation is optimized efficiently by alternating between an image update step and a sparse coding and clustering step, with both of these steps having closed-form solutions. The effectiveness of our method is validated with both XCAT phantom and clinical head data. The results demonstrate that our proposed method provides superior material image quality and decomposition accuracy compared to other competing methods.
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