Text in English with abstracts in English, Venda and Sepedi / Background: Suitable complementary feeding practices in young children can ensure optimal nutrition status and reduce under 5 mortality rates (Jones et al., 2014). Inadequate dietary diversity (DD) of the complementary diet both in quality and quantity is one of the major problems affecting infants and young children worldwide (Ntila et al., 2017). Adequate and appropriate nutrition during infancy and early childhood is vital for the growth and development of every child to reach full human potential (PAHO, 2003; WHO, 2008a; UNICEF, 2016). Nutritional vulnerability increases when other factors are also involved, such as poor breast and complementary feeding practices combined with high rates of infectious diseases (Solomons & Vossenaar, 2013; Ntila et al., 2017). There are pockets of information available on complementary feeding practices and its social determinants from specific areas in South Africa, regarding infant and young child feeding practices beyond six months of age and requires further investigation (Issaka et al., 2015; Seonandan & McKerrow, 2016). Aim: To explore the association between mothers’ socio-cultural environment and the dietary diversity of their children between the ages of 6 and 24 months, who attend the health care clinic in Olievenhoutbosch Township, Gauteng. Methodology: A quantitative cross-sectional explorative study was implemented. Data collection was conducted at Olievenhoutbosch clinic in Gauteng during February and March 2019. Mothers of children aged between 6 and 24 months were included and interviewed. Consecutive sampling was applied. The data collection instruments were a set of structured questions to obtain socio-demographic, nutritional knowledge, maternal attitude and feeding practices data. The infant and young child minimum dietary diversity (IYCMDD) questionnaire adapted from the WHO questionnaire was used to determine the DD of each child. Ethical clearance was obtained from the Ethics Committee of the College of Agriculture and Environmental Sciences (CAES) at the University of South Africa. Descriptive and inferential statistics was applied using SPSS version 25 (SPSS Inc, Chicago, IL, USA). Results: The sample of mothers (n=103) were educated (75% completed matric and 18% completed post-school education), unemployed (73%) and mostly single (53%) which are all factors playing a role in child nutrition. The majority (58%) of children were between the ages of 6 and 11 months while 42% were between the ages of 12 and 24 months. The milk feeding practices differed significantly between the younger and older groups of children with 35% of the younger children receiving breastmilk (in addition to complementary foods), compared to 21% of the older group. Almost half (44%) of the total group reported that maize meal porridge was the first food introduced to their children. Less than half of the mothers (45%) initiated the first foods at the recommended age of 6 months but started as early as one month of age (13%). All children (100%) consumed foods from the “grains, roots and tubers” food group the previous day. Significantly less children from the younger age group were reported to have consumed dairy (38% vs 77%, p<0.001) (other than breast or formula milk), animal flesh foods (31% vs 59%, p=0.014) and legumes (8% vs 24%, p=0.034), compared to the older age group. Significantly more children from the older group met the minimum dietary diversity (MDD) of four food groups compared to the younger group (67% vs 38%, p=0.019). No association was found between most socio-cultural factors (maternal age, marital status, education and employment status) and DD. However, there was an association between maternal ethnicity and DD (𝑥2=16.62, p=0.002). Also, maternal nutrition knowledge and the child’s DD had a significant, positive linear relationship (p=0.026). Lastly, maternal attitude towards feeling confident in not overfeeding the child were associated with meeting the MDD. Conclusion: The diets of young children residing in Olievenhoutbosch, do not meet the criteria for a minimally acceptable diet with only 50% meeting the MDD. Legumes and animal source foods are not consumed in sufficient quantities for complementary feeding. Maternal ethnicity and nutritional knowledge were associated with the child’s DD. More emphasis should be placed on DD for young children. / Vhubvo: Maitele o teaho a thikhedzo ya kuṋetshedzele kwa zwiḽiwa kha vhana vhaṱuku a nga khwaṱhisedza vhuimo ha gumofulu ha pfush na u fhungudza phimo ya dzimpfu dza vhana vha fhasi ha miṅwaha ya fhasi ha 5 (Jones na vhaṅwe, 2014). U sa lingana ha u fhambana ha kuḽele (DD) ha nndyo thikhedzi kha ndeme na tshivhalo ndi dziṅwe dza thaidzo khulwane dzi kwamaho dzitshetshe na vhana vhaṱuku u mona na shango (Ntila na vhaṅwe, 2017). Mufusho wo linganaho na wo teaho musi vhe dzitshetshe na kha vhuhana thangeli ndi dza ndeme kha nyaluwo na nyaluso ya ṅwana muṅwe na muṅwe uri a vhe na vhukoni hoṱhe (PAHO, 2003; WHO, 2008a; UNICEF, 2016). U vha khomboni ha mufusho zwi a ṋaṋa musi hu na zwiṅwe zwithu zwi dzhenelelaho, sa maitele a sa fushi a u mamisa na u tikedza zwo ṱangana na phimo ya nṱha ya malwadze a phirela (Solomons & Vossenaar, 2013; Ntila na vhaṅwe., 2017). Haya ndi mafhungo u ya nga zwipiḓa are hone kha maitele a u ḽisa ha thikhedzo na zwivhangi zwa matshilisano u bva kha vhuṅwe vhupo ha Afrika Tshipembe, maelana na u ḽisa dzitshetshe na vhana vho no fhirisaho miṅwedzi ya rathi, naho ṱhoho iyi i tshi ṱoḓa u senguluswa hafhu (Issaka na vhaṅwe, 2015; Seonandan & McKerrow, 2016). Ndivho: U itela u lavhelesa u elana ha vhupo ha zwa matshilisano na ikonomi ha mme na DD ya vhana vhavho vha vhukati ha miṅwedzi ya 6 na 24, vhane vha ya kiḽiniki ya ndondola mutakalo ngei kha Tshikolobulasi tsha Olievenhoutbosch, Gauteng. Ngona: Ngudo dza vhubuḓasia dza ndingedzo dzo shumiswa. Data yo kuvhanganywa ngei kha kiḽiniki ya Olievenhoutbosch kha ḽa Gauteng nga Luhuhi na Ṱhafamuhwe 2019. Vhomme a vhana vha miṅwedzi ya vhukati ha 6 na 24 vho dzheniswa vha vhudziswa. Vhukhethatsumbonanguludzwa ha thevhekano ho shumiswa. Sethe ya mbudziso dzo dzudzanywaho yo shumiswa u wana u phambano dza matshilisano, nḓivho ya mufusho, kusedzele kwa vhomme na data ya phatheni dza kuḽele. Mbudzisombekanywa ya phambano ya gumofulu ya kuḽele kwa dzitshetshe na vhana vhaṱuku (IYCMDD) u bva kha WHO yo shumiswa u vhona DD ya ṅwana muṅwe na muṅwe. Ṱhanziela dza vhuḓifari dzo wanala u bva kha Komiti ya zwa Vhuḓifari ya Khoḽidzhi ya zwa Vhulimi na Saintsi dza zwa Mupo (CAES) kha Yunivesithi ya Afrika Tshipembe. Mbalombalo dza ṱhalutshedzo na dza u sumbedzisa dzo shumiswa nga u shumisa vesheni ya SPSS 25. Mvelelo: Tsumbonanguludzwa dza vhomme (n = 103) vho funzwaho (75% vho fhedza maṱiriki na 18% yo bvelaphanḓa ya fhedza pfunzo ya nṱha ha tshikolo, vha sa shumi ndi (73%) nahone vhanzhi ndi vha tshilaho vhe vhoṱhe (53%), zwi re zwivhumbi zwoṱhe zwine zwa dzhenelela kha mufusho wa ṅwana. Vhunzhi (60%) ya vhana vho vha vhe vhukati ha miṅwedzi ya 6 u ya kha ya 11, 40% vhe vhukati ha ya 12 u ya kha 24. Kumamisele kwo fhambana vhukuma vhukati ha zwigwada zwa vhaswa na zwa vhahulwane, hune 35% ya vhana vhaṱuku vha vha vha khou wana mikando ya vhomme avho (nṱhani ha zwiḽiwa zwa u tikedza), hu tshi vhambedzwa na 21% ya tshigwada tsha vhahulwane. U ṱoḓa u swika kha hafu (44%) ya tshigwada tshoṱhe vho amba uri mukapu wa mugayo ndi zwone zwiḽiwa zwo thomaho u ḓivhadzwa vhana vhavho. Vhomme vha re fhasi ha hafu (45%) vho them zwiḽiwa zwa u thoma kha miṅwedzi yo themendelwaho ya 6 fhedzi vhaṅwe vha thoma u ṱavhanya vhe kha ṅwedzi muthihi (13%). Vhana vhoṱhe (100%) vho vha vho no ḽa ḽiwa zwi fanaho na thoro, midzi na khufhi sa zwigwada zwa zwiḽiwa ḓuvha ḽo fhiraho. Vha si gathi vhukuma kha vhana vha tshigwada tsha vhaṱuku vho pfi vho ḽa zwiḽiwa zwa mafhi (38% i tshi vhambedzwa na 77%, p < 0.001) (zwi si mafhi a mikando kana a boḓelo), zwiḽiwa zwa ṋama ya phukha (31% i tshi vhambedzwa na 59%, p = 0.014) ḽingaṋawa (8% vha tshi vhambedzwa na 24%, p = 0.034), vha tshi vhambedzwa na zwigwada zwa vhahulwane. Vhunzhi ha vhana vha bvaho kha tshigwada tsha vhahulwane vho swikelela phambano ya gumoṱuku ya nndyo (MDD) ya zwigwada zwiṋa zwi tshi vhambedzwa na tshigwada tsha vhaṱuku (67% i tshi vhambedzwa na 38%, p = 0.019). Ahuna u elana ho wanalaho vhukati ha zwivhumbi zwa mvelele na matshilisano (vhukale ha vhomme, vhuimo ha mbingano, pfunzo na vhuimo ha mushumo) na DD. Fhedzi, ho vha na u elana vhukati ha murafho wa vhomme na DD (𝑥2 = 16.62, p = 0.002). Zwiṅwe hafhu, nḓivho ya mufusho ya vhomme na DD ya ṅwana zwo vha na vhushaka, ha ndeme hu elanaho huvhuya (p = 0.026). Tsha u fhedzisela, kusedzele kwa vhomme kha u ḓipfa vhe na vhuḓifulufheli na u sa ḽisa ṅwana u fhira tshikalo zwo elana na u swikelela MDD. Khunyeledzo: Nndyo ya vhana vhaṱuku vha dzulaho ngei Olievenhoutbosch a i swikeleli maga a gumoṱuku a ṱanganedzwaho a nndyo; ho swikelelwa fhedzi 50% ye ya swikelela MDD. Ḽingaṋawa na tshiko tsha zwiḽiwa zwa zwipuka a zwi khou ḽiwa lwo linganaho kha thikhedzo ya kuḽele. Murafho wa vhomme na nḓivho ya mufusho zwo elana na DD ya ṅwana. Ho vha na khwaṱhisedzo hafhu kha DD ya vhana vhaṱuku. / Tšweletšo ya taba: ditiro tša maleba tša phepo ya tlaleletšo mo go bana ba bannyane di ka netefatša maemo a godimo a phepo le go fokotša kelo ya mahu mo go bana ba ka fase ga mengwaga ye 5 (Jones et al., 2014). Go fapafapana ga dijo fao go sa lekanago (DD) ga dijo tša tlaleletšo go bobedi boleng le bontši ke ye nngwe ya mathata a magolo ao a amago masea le bana ba bannyane lefase ka bophara (Ntila et al., 2017). Phepo ye e lekanego gape ya maleba nako ya bosea le bonnyane e bohlokwa go kgolo le tlhabollo ya ngwana yo mongwe le yo mongwe go fihlelela bogolo bjo bo feletšego (PAHO, 2003; WHO, 2008a; UNICEF, 2016). Kgolo ya hlaelela ya dijo ge dintlha tše dingwe le tšona di amega, go swana le ditshepedišo tša go fokola le phepo ya tlaleletšo go hlakanywa le malwetši a mantši a go fetela (Solomons & Vossenaar, 2013; Ntila et al., 2017). Go na le dipotla tša tshedimošo tšeo di lego gona go ditiro tša phepo ya tlaleletšo le dikelo tša leago go tšwa mafelong a go ikgetha mo Afrika Borwa, mabapi le masea le bana ba bannyane ka morago ga dikgwedi tše tshela, mme hlogo ye e nyaka dinyakišišo (Issaka et al., 2015; Seonandan & McKerrow, 2016). Nepo: go nyakišiša dikamano gare ga bomme le tikologo ya leago le setšo le DD ya bana ba gare ga dikgwedi tše 6 le tše 24, bao ba tsenetšego kliniki ya tša maphelo ya Olievenhoutbosch Township, Gauteng. Mekgwatshepetšo: thuto ya diphatišišo tša go hlakanela ga dikgao e phethagaditšwe. Kgoboketšo ya tshedimošo e dirilwe kliniking ya Olievenhoutbosch mo Gauteng nakong ya Febereware le Matšhe 2019. Bommago bana ba dikgwedi tša gare ga tše 6 le 24 di akareditšwe le go botšišwa. Sehlopha sa go latelana se šomišitšwe. Sete ya dipotšišo tšeo di hlamilwego di šomišitšwe go hwetša tsebo ya dimokrafi ya leago, dijo, maikemišetšo a bomme le tshedimošo ka ga mekgwa ya go fepa. Masea le mehuta ya go fapana ya dijo tša bana (IYCMDD) letlakalapotšišo go tšwa go WHO le šomišitšwe go ela DD ya ngwana yo mongwe le yo mongwe. Hlakišo ya maitshwaro e hweditšwe go Komiti ya Maitshwaro ya Kholetšhe ya Temo le Disaense tša Tikologo (CAES) mo Yunibesithing ya Afrika Borwa. Dipalopalo tša tlhaloso le taetšo di šomišitšwe ge go diragatšwa mohuta wa SPSS 25. Dipoelo: Sekgao sa bomme (n = 103) ba be go ba rutegile (75% ba phethile mphato wa marematlou le 18% ba tšwetšepele go phetha dithuto tša ka morago ga mphato wa marematlou), ga ba šome (73%) le bontši ga se ba nyalwe (53%), tšeo ka moka e lego dintlha tša go raloka karolo ye kgolo go phepo ya bana. Bontši (60%) bja bana ba magareng ga mengwaga ye 6 le ye 11, le 40% e be e le magareng a dikgwedi tše 12 le tše 24. Ditiro tša go nyantšha di fapana kudu gare ga bana ba bannyane le dihlopha tša bana ba bagolwane, ka 35% tša bana ba bannyane bao ba amogelago maswi a letswele (go tlaleletša dijo tša tlaleletšo), ge go bapetšwa le 21% tša batho ba bagolwane. Go nyaka go ba seripagare (44%) sa palomoka seo se begilego gore bogobe bja mabele ke dijo tša mathomo tšeo di tšweleditšwego go bana ba bona. Ka fase ga seripagare sa bomma (45%) ba thomile dijo tša bona tša mathomo ka mengwaga ye e digetšwego ya dikgwedi tše 6 efela di thomile ka kgwedi ya mathomo (13%). Bana ka moka (100%) ba jele dijo go tšwa go dithoro, medu le sehlopha sa dijo tša digwere mo letšatšing le le fetilego. Palo ye ntši ya bana ba bannyane go tšwa go mengwaga ye mennyane ba begilwe ba jele dijo tša maswi (38% vs 77%, p < 0.001) (ntle le maswi a letswele goba a go rekwa), dijo tša nama ya phoofolo (31% vs 59%, p = 0.014) le dinawa (8% vs 24%, p = 0.034), ge go bapetšwa le batho ba mengwaga ya bagolo. Bontši bja bana go tšwa go sehlopha sa ba bagolo ba kgotsofaditše dinyakwa tša go fapana tša dijo (MDD) ya dihlopha tše nne ge go bapetšwa le dihlopha tše dinnyane (67% vs 38%, p = 0.019). Ga go dikamano tšeo di humanwego gare ga dintlha tše dintši tša leago le setšo (mengwaga ya tswalo, maemo a lenyalo, thuto le maemo a mošomo DD. Le ge go le bjalo, go bile le dikamano gare setšo le DD (𝑥2 = 16.62, p = 0.002). Le, tsebo ya dijo le DD ya bana, tswalano ya maleba ya tatelano (p = 0.026). Sa mafelelo, mmono wa bomme go ikwa ba na le boitshepo ka go se fepe ngwana go feta tekanyo tšeo di amanago le go kopana le MDD. Thumo: Dijo tša bana ba bannyane ba go dula Olievenhoutbosch ga ba kgotsofatše dinyakwa tša dijo tše di amogelegago; fela 50% e kopane le MDD. Dinawa le dijo tša mothopo ya diphoofolo ga di lewe ka bontši bja go lekana go dira dijo tša tlaleletšo. Mohlobo le tsebo ya dijo di be di amane le DD ya ngwana. Kgatelelo ye kgolo e swanetše go bewa go DD go bana ba bannyane. / Department of Life and Consumer Science / M.A. (Consumer Science)

For the first time in history, more people in the world live in urban areas than in rural areas. Almost half of this world urban population now live in metropolitan areas, which are becoming central spaces of world economic and social activity, and where major global challenges happen and should be tackled. Metropolitan areas are defined by urban spaces of integrated mobility flows and markets, but also by high institutional fragmentation and political decomposition. This fragmentation interferes in decision-making processes leading to difficulties for the design and implementation of adequate responses to metropolitan problems. In this context, the study of how metropolitan areas should be governed is gaining relevance in the field of urban studies, among other fields. The normative debates about metropolitan governance has been framed by three traditions. From the 60s to the late 80s these debates were restricted to the ‘old regionalism’ dialectics between the metropolitan reform and public choice scholars. More recently, new regionalism recognize in flexible and cooperative governance instruments the most effective way to deal with metropolitan problems. From this perspective metropolitan areas are governed by complex governance relations between diverse actors through multiple and concurrent instruments, in the form of policy networks, voluntary cooperation, strategic planning, and so on. The Öresund Region is a metropolis that spans from eastern Denmark to southern Sweden, and includes cities such as Copenhagen and Malmö. While it has been largely referenced and praised as an example of cross-border metropolitan area, there is little evidence on how it is governed or which are the main governance instruments or who are the actors involved in the policy-making process. Taking an original approach to the study of metropolitan governance, this paper represents a first attempt to identify and understand the main features of metropolitan governance in the Öresund Region as a system, in a polycentric and multilayered crossborder metropolis. The results suggest that metropolitan governance in the Öresund Region is very ambiguous, with several agents acting in different and non-coincident scales, strongly focused in hard policies and development policies in contrast to social and environmental policy areas. Also, there are persistent barriers to cross-border governance despite the favorable context. And finally, there is a relevant democratic governance deficit, in terms of social actors’ participation and involvement in the metropolitan decision-making process. These first results recommend to go forward with further research in this issue. Particularly to grasp about governance networks operatives, policy-making processes, and citizens’ political orientations to, ultimately, propose improvements for a more effective, comprehensive and democratic governance in the Öresund metropolitan region.

A growing body of research emphasizes the development of an understanding of the relationship between older adults and their physical and social environments (Wahl & Weisman, 2003). Researchers, planners, policymakers, and community residents have been increasingly interested in shaping urban environments as places that foster active aging and independence among older adults. Senior centers have served a critical role in their communities as focal points for older adults, as individuals or in groups, to participate in services and activities that support their independence and encourage their involvement in and with the community (NCOA, 1979). The aging of the population and influx of baby boomers into the older demographic, along with declines in participation rates and funding, are challenging senior center staff to be innovative and adaptive in order to demonstrate senior centers’ relevance to future older adults while maintaining the programming and services for their current participants. This research is a multiple-case study of five unique senior centers located throughout the Portland metropolitan area in Oregon. Different types and models of senior centers are represented by the selected cases, as they operate under different governance structures and vary in aspects such as administration, funding, participant characteristics, community partnerships, transportation options, physical environments, and range of services and programs offered. This study aims to better understand challenges, strengths, and future directions for different types of senior centers serving a metropolitan area. Data collection at each site included interviews with staff as well as focus groups with senior center participants. Interviews with key informants enriched the findings and provided outside perspectives of senior center experiences. Data analysis revealed challenges and strengths that were common across and unique to the different senior centers in this study. This research contributes to the literature in urban studies, community development, and gerontology by exploring potential opportunities for urban senior centers to adapt and continue to serve older adults. Recommendations were developed for how senior centers might capitalize on these opportunities and for how their communities might provide mechanisms of support to facilitate the continuation and contributions of senior centers in metropolitan areas.

This project examined cyclist red light running behavior using two data sets. Previous studies of cyclist compliance have investigated the tendencies of cyclists to run red lights on the whole by generalizing different maneuvers to their end outcome, running a red light. This project differentiates between the different types of red light running and focuses on the most egregious case, gap acceptance, which is when a cyclist runs a red light by accepting a gap in opposing traffic. Using video data, a mathematical model of cyclist red light running was developed for gap acceptance. Similar to other studies, this analysis utilized only information about the cyclist, intersection, and scenario that can be outwardly observed. This analysis found that the number of cyclists already waiting at the signal, the presence of a vehicle in the adjacent lane, and female sex were deterrents to red light running. Conversely, certain types of signal phasing, witnessing a violation, and lack of helmet increased the odds that a cyclist would run the red light. Interestingly, while women in general are less likely to run a red light, those who witnessed a violation were even more prone that men who had witnessed a violation to follow suit and run the red light themselves. It is likely that the differing socialization of women and men leads to different effects of witnessing a previous violator. The analysis also confirmed that a small subset of cyclists, similar to that found in the general population, are more prone to traffic violations. These cyclists are more willing to engage in multiple biking-related risk factors that include not wearing a helmet and running red lights. Although the model has definite explanatory power regarding decisions of cyclist compliance, much of the variance in the compliance choices of the sample is left unexplained. This points toward the influence of other, not outwardly observable variables on the decision to run a red light. Analysis of survey data from cyclists further confirms that individual characteristics not visible to the observer interact with intersection, scenario, and visible cyclist characteristics to result in a decision to comply (or not) with a traffic signal. Furthermore, cyclist characteristics, in general, and unobservable individual characteristics, specifically, play a larger role in compliance decisions as the number of compliance-inducing intersection traits (e.g. conflicting traffic volume) decrease. One such unobservable trait is the regard for the law by some cyclists, which becomes a more important determinant of compliance at simpler intersections. Cyclists were also shown to choose non-compliance if they questioned the validity of the red indication for them, as cyclists. The video and survey data have some comparable findings. For instance, the relationship of age to compliance was explored in both data analyses. Age was not found to be a significant predictor of non-compliance in the video data analysis while it was negatively correlated with stated non-compliance for two of the survey intersections. Gender, while having significant effects on non-compliance in the video dataset, did not emerge as an important factor in the stated non-compliance of survey takers. Helmet use had a consistent relationship with compliance between the video and survey datasets. Helmet use was positively associated with compliance in the video data and negatively associated with revealed non-compliance at two of the survey intersections. When coupled with the positive association between normlessness and stated willingness to run a red light, the relationship between helmet use and compliance solidifies the notion that a class of cyclists is more likely to consistently violate signals. It points towards a link between red light running and individuals who do not adhere to social norms and policies as strictly as others. Variables representing cyclists and motorists waiting at the signal were positively related to signal compliance in the video data. While an increased number of cyclists may be a physical deterrent to red light running, part of the influence on compliance that this variable and the variable representing the presence of a vehicle may be due to accountability of cyclists to other road users. This relationship, however, was not revealed in the stated non-compliance data from the survey. Efforts to increase cyclist compliance may not be worth a jurisdiction's resources since nearly 90% of cyclists in the video data were already compliant. If a problem intersection does warrant intervention, different methods of ensuring bicyclist compliance are warranted depending on the intersection characteristics. An alternative solution is to consider the applicability of traffic laws (originally designed for cars) to bicyclists. Creating separation in how laws affect motorists and cyclists might be a better solution for overly simple types of intersections where cyclists have fewer conflicts, better visibility, etc. than motorists. Education or other messaging aimed at cyclists about compliance is another strategy to increase compliance. Since cyclists appear to feel more justified in running red lights at low-volume, simple-looking intersections, it would probably be prudent to target messaging at these types of intersections. Many cyclists are deterred by high-volume and/or complicated looking intersections for safety reasons. Reminding cyclists of the potential dangers at other intersections may be a successful messaging strategy. Alternatively, reminding cyclists that it is still illegal to run a red light even if they feel safe doing so may be prudent. Additionally, messaging about the purpose of infrastructure such as bicycle-specific signals or lights that indicate detection at a signal may convince cyclists that stopping at the signal is in their best interest and that the wait will be minimal and/or warranted.

During the past three decades, research in travel behavior has generally proceeded from broad-level, aggregate analysis of mode share--the proportions of walking, bicycling, transit, and vehicle travel occurring in traffic analysis zones, census tracts, neighborhood, or other geographical units--to fine-grained, disaggregate analysis of mode choices and other trip-making attributes at the individual level. One potential issue is whether there are differences in the types of conclusions drawn from results of analyses performed at these different levels, as these results directly inform transportation planning and policy. This thesis aims in part to confirm whether the types of conclusions drawn from different levels of analysis are different, and to what extent. We also examine the relationships between the built environment and non-work travel choices from a unique analysis perspective. To do this, we use data from a 2011 travel intercept survey in the Portland, Oregon metropolitan region that was administered at convenience store, bar, and restaurant establishments. We estimate, for each of the travel modes--walk, bicycle, and automobile--two analysis models: one binary logistic regression model for mode choice of the individual traveler going to the establishment and one multiple linear regression model for mode share of shoppers at the establishment. Both models control for socio-demographics, trip characteristics, and built environment measures of travelers. For the binary logistic regression models, the data are disaggregate and particular to the individual traveler. These models also controlled for attitudes and preference towards travel modes. For the multiple regression models, data are aggregated to the establishment. The built environment data in each model represent characteristics of urban form surrounding the establishment. The data being oriented to the destination-end of the trip, as well as providing controls on land use make this analysis unique in the literature, as most non-work travel studies use residential-based data. Results suggest that analyses performed at the two different levels provide policy-relevant but somewhat different conclusions. In general, characteristics of the individual and the trip have stronger associations with mode choices of individuals than when aggregated to the establishment and analyzed against the mode share patterns of shoppers. Instead, mode shares have stronger relationships with characteristics of the built environment. The built environment surrounding the destination has a much more pronounced association with mode shares at the establishment than with mode choices of individuals. The results highlight the usefulness of simple aggregate analysis, when appropriate. We also find large differences between modes in which characteristics are important for mode choice and mode share. Walking and automobile models behave somewhat similarly but in opposite directions, while bicycling behaves quite differently. These differences suggest on their own a move away from non-motorized travel to be considered as equivalent or assessed as one item in research and in practice.

Note:

Call number: LD2668 .T4 1978 M45 / Master of Arts

M. Tech. Business Administration / The capacity to render reliable and highly efficient emergency and rescue services is crucially important for metropolitan municipalities such as the City of Tshwane Metropolitan Municipality (CTMM) to grow on a sustainable basis. Such capacity is also needed for fulfilling the routine needs and operational requirements of businesses that operate in the CTMM. To this end, the City of Tshwane needs to develop adequate capacity for rendering reliable and efficient emergency and rescue services by utilizing modern technology and highly innovative methods and strategies. The purpose of the study was to identify and quantify gaps in the quality of emergency and rescue services that were provided to residents of Erasmuskloof, Centurion and Hazelwood by the City of Tshwane. One of the key aims of the study was to estimate gap scores that could be used for the assessment of discrepancies between perceptions and expectations among the residents.

M. Tech. Business Administration / Sport tourism events in recent years have become one of the fastest-growing types of tourism attractions globally. For the aim of this study, it is important to understand spending patterns, socio-economic characteristics and activities that relate to the sport tourist to have a greater understanding of the impact of these events on the host community. The sport tourism event spectator is a consumer who, through a process of decision making, obtains certain goods and services from the sport tourism event for personal consumption. Sport tourism event leverage begins by encouraging visitor spending and by retaining visitor expenditure within the host community, which can be achieved by fostering spending during the sport tourism event and by lengthening visitor stays The purpose of this research study was to determine the spending patterns and expectations of sport tourism event spectators. This research study was exploratory to determine spectator spending patterns, demands and possible economic impacts that a sport event being hosted at Loftus Versveld will have on shareholders involved.

This study examined African American social workers' opinions about genetic research, genetic services, and education in genetics and selected factors associated with their opinions. Those factors were professional/work experience with clients with genetic issues; mass media exposure to genetic information: t.v., movies, newspapers, magazines; graduate social work course/unit in a course in genetics; personal/family experience with genetic issues; and gender. There are no available studies on the readiness of African American social workers to practice in human genetic service delivery. This study was based on the premise that African American social workers' opinions about human genetics as a discipline would be an indicator of their readiness to practice in genetics. Frequency analysis, crosstabulation and multiple regression were the statistics employed to analyze the data. The findings indicated that African American social workers were supportive of genetic services and education in genetics, but had mixed opinions about genetic research. Based upon these findings, African American social workers appear to be a group that is ready to fill a unique need for social work practitioners in genetics. Mass media exposure to genetics and gender were the variables that were most associated with the African American social workers' opinions. Several of the independent variables had a slight relationship to the criterion variables. These relationships indicated an interplay of complex factors that were associated with African American social workers' support for genetic research, genetic services and education in genetics. Those factors indicated that experience with or exposure to genetics may have influenced African American social workers to support genetics in general. It was recommended that graduate schools of social work and social work professional associations develop educational programming that focuses on exposing African American graduate social work students and social work practitioners to genetics. This study employed convenience sampling to maximize the participation of African American social workers and conclusions apply only to the study sample.