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Determinants of Growth of Women Enterprises in Kiambu County, Kenya
(Kenyatta University, 2017) Ndanuko, Geoffrey Kimani
According to the census carried out in year 2009, women constitute more than half of the population of Kenya and make a significant contribution to the economy accounting for about 48% of all micro, small, and medium sized enterprises contributing about 20% to Kenya's Gross Domestic Product. The micro, small and medium enterprises (MSMEs) are considered as sources of employment generation, economic growth, and social transformation. The crucial role of MSMEs is underscored in Kenya's Vision 2030, the development blueprint which seeks to transform Kenya into an industrialized middle-income country, providing a high-quality life to all its citizens by the year 2030. The MSMEs sector has been identified and prioritized as a key growth driver for achievement of the development.
This study was aimed at establishing whether financial and credit availability and accessibility, human capital and social structure determine growth of women enterprises in Kiambu County. Significance of the study was to uncover specific issues that women enterprises face, findings are useful to policy makers and also provide basis for further research. Financial capital theory, human capital theory and sociological theory were adopted as the theoretical framework for the study.
Descriptive research design was used in this study where questionnaires were administered to the targeted population of women enterprises from Kiambu County where stratified random sampling was used. To ensure validity of the research instrument to be used in collecting data, the researcher ensured that the questionnaire is thoroughly checked for validity and assesses the relevance of the questions and content of the study. Reliability of the questionnaire was tested through a pilot study in which the questionnaires were pre-tested to a sample group similar to the actual sample.
The information was coded and analysed using descriptive statistics and through use of percentages by using Statistical Package for Social Science (SPSS). Regression type of statistic model was used to find out relationship between independent and dependent variables. The findings indicate that access to finance had positive and significant effect on growth of women enterprises. Human capital was found to have a positive significant in explaining the variation of growth of women enterprises and lastly social structure was found to have a significant effect on growth of women enterprises.
The study concludes that access to finance affected the growth of women enterprises. The study also concludes that most women entrepreneurs get the initial capital from personal savings. Also, the study concludes that most of women entrepreneurs have tried getting financial assistance from the lending institutions. The study concludes that access to finance affect women enterprises to a high extent. The study also concludes that collateral requirement affects the growth of women enterprises. On human capital and growth of women enterprises the study concludes that human capital affected the growth of women enterprises. The study also concludes that education level had an impact on the growth of women enterprises. The study also concludes that employees in women enterprises are able to read and write thus influencing the growth of women enterprises. Further the study concludes that most women entrepreneurs are trained in business skills through formal training. Lastly, on social structure and growth of women enterprises, the study concludes that social structure affected the growth of women entrepreneurs. The study also concludes most women entrepreneurs handle household chores. Also, the study concludes that most women manage the enterprises. Further the study concludes that cultural norms affect the growth of women enterprises to a great extent
Predictors of AIDS-defining and Non-AIDS-defining Cancers Among PLHIV Accessing Services in Selected Hospitals in Nairobi City County, Kenya
(Science Publishing Group, 2025-12) Omollo, Peter Onyango; Orago, Alloys; Mwanzo, Isaac
Human infection with HIV compromises the immune system and reduces the body’s ability to fight viral infections that may
promote the development of certain types of cancers. The diagnosis of AIDS-defining cancers in PLHIV indicates the
progression of an HIV infection to the AIDS stage. Non-AIDS-defining cancers occur in HIV-positive individuals without
necessarily being caused or exacerbated by HIV infection. WHO estimates that 39.9 million are PLHIV, whereas 42.3 million
lives have been lost to HIV. Kenya’s HIV prevalence was 3.3% and in Nairobi, 4.3%. NCD mortalities in Kenya were 39%,
including cancers, up from 27% and HIV remains a major risk factor. This study’s main purpose was to identify the predictors of
AIDS-defining and non-AIDS-defining cancers among PLHIV accessing services in selected hospitals in Nairobi City County,
Kenya. An analytical cross-sectional design was used. Study sites were purposively selected, whereas a simple random method
was used to select 406 adults, aged 18 years and above, HIV positive and on ART. The study was conducted in seven selected
facilities in Nairobi County. Quantitative data were collected using semi-structured questionnaires, whereas qualitative data were
obtained from seven key informant interviews and three focus group discussions. Descriptive statistics (percentages, graphs, and
charts) and inferential statistics (chi-square and logistic regression models) were performed using SPSS v. 27. Qualitative data
were transcribed, coded, and grouped into themes. AIDS-defining cancers were the most prevalent (74.6%) among PLHIV
accessing services in the selected hospitals. A Pearson’s Chi-square (X2) test revealed that socio-demographic characteristics
such as sex (p = 0.00), age in years (45-54 for AIDS-defining cancer and 65 and above for Non-AIDS-defining cancers) (p =
0.00), marital status (married and widowers for ADC and NADC, p = 0.02) and level of education (secondary and ‘other’ for
ADC and NADC respectively; p = 0.005) were associated with the type of cancer development among people living with HIV. A
binary logistic regression model found that age (χ2(5) = 14.96, p = 0.011), income level (X2 (5) = 9.96; p = 0.076), history of
cigarette smoking (B = 1.53; p = 0.001; OR = 4.638; 95% CI: 2.28 – 9.42), alcohol consumption (B = 0.295; p = 0.356), family
history of cancers (B = 1.04; p = 0.001; OR = 2.827; 95% CI: 1.61 – 4.97), were statistically associated with AIDS and
non-AIDS-defining cancers. These findings will help formulate programmatic and policy interventions for ADC and NADC
among PLHIV
Media Accessibility and Use-Patterns on the Occurrence of Mental Health Conditions Among Youths in Nairobi City County, Kenya
(InternationalJournal of Health Sciences, 2026-04) Akinyi, Merab Stacya; Oyore, John Paul; Orago,Alloys Stevens Sigar
im: Globally, mental health problems affect 10 to 20% of adults and youngsters, with the onset age for 50% of cases being 14 years. In Kenya, estimates suggested that 1 in 10 individuals suffered from a known mental condition, with adult Kenyans having a 9.8% likelihood of experiencing depression. A study on social media use in Kenya revealed that the most active age group was 26-35 years, with a significant proportion using platforms like Facebook, WhatsApp, Snapchat, Instagram, and Twitter. The study assessed the impact of media accessibility and use patterns on the occurrence of mental health conditions among youths in Nairobi City County, Kenya. Methods: The study design was an analytical cross-sectional study with quantitative and qualitative methods. Data collection involved SSQs, KIIs, and FGDs, with 24 KIIs and 2 FGDs being conducted. A total of 385 participants were selected using a simple random sampling method, and data analysis was conducted using Advanced Excel, including descriptive statistics and regression analysis. Transcribing, coding, and classifying were employed to establish relationships and enable data summarization performance. Results: The results indicated a statistically significant difference in self-esteem scores between the two groups, t(766) = -2.84, p = .0047. Specifically, youths engaged in informal occupations (M = 19.01, SD ≈ 17.91) reported higher self-esteem compared to those in formal occupations (M = 15.42, SD ≈ 17.14). This suggested that employment type may influence how youths perceive their self-worth, possibly due to factors like increased autonomy or flexibility in informal settings. The regression analysis showed that media use-patterns were not a statistically significant predictor of self-esteem among youths in Nairobi City County, β = -0.08, t(382) = 1.03, p = .30. Media literacy had a positive and statistically significant effect on self-esteem, β = 0.21, t(382) = 2.23, p = .03. The regression model explained approximately 1.3% of the variance in self-esteem scores, R² = .013. Conclusion: Mental health issues are widespread, often fueled by digital exposure and compounded by structural limitations like poverty, stigma, and insufficient mental health infrastructure
Role of Public Secondary School Principals in Management of Education during Emergencies in Rorya District, Tanzania
(Kenyatta University, 2017-07) Magige Nicholaus Athanas
Abstract
Influence of sexual abuse on the school performance of girls aged 6-8 years in Mombasa county Kenya
(Kenyatta University, 2016-12) Kavyu Juliana Mutethya
abstract