Peer-reviewed international research papers published open-access with EOI assignment and global indexing across engineering, computer science, environmental science, social sciences, and more.
The rising trend in the prevalence of dylipidemia-associated medical conditions has been linked with poor dietary and lifestyle choices. The present study was aimed at investigating the effects of hydro-ethanolic fruit extract of Solanum aethiopicum on the lipid profile of wistar rats. A total of 24 wistar rats weighing about 140–180g were divided into 4 groups of 6 rats each. Group 1 served as control, groups 2, 3 and 4 received 200, 400 and 600 mg/kg body weight of the extract respectively for a period of 14 days. Thereafter, the animals were sacrificed and serum lipid profile determined using standard methods. The findings showed that the administration of the hydro-ethanolic fruit extract of S. aethiopicum resulted in a significant reduction in the serum Total Cholesterol, Triglycerides, Low Density Lipoproteins (LDL) and atherogenic index whereas the High Density Lipoproteins was increased. These findings suggest lipid lowering potential and could be beneficial in prevention and management of management dyslipidemia-associated conditions.
Because of the increasing risks and complexities in terms of cybercrimes globally, there is an urgency to secure the cyber system more tightly. Cyber security methods must be more intelligent and robust when it comes to securing the matter of saving the data. For that purpose, cyber security systems should have the capability to complete it from the recent era’s competition and complexities.It should be capable of taking decisions that show the effect of these attacks and responding to them more sophisticatedly. In terms of getting optimum security against cybercrimes, researchers and practitioners are paying deep attention to securing data and information from any deportation. The main objective behind conducting this study is to get aware of the basic terminologies associated with Artificial Intelligence, Cyber security, cyberbullying, and cybercrimes. To fulfill this particular objective, we have taken almost a sample study of articles probably of the past ten years. The articles are studied from Google scholars, IEEE landscape-based study.[3] The articles are analyzed on a quantitative and qualitative basis. It is observed that Artificial Intelligent methods are being contributed to securing data and information. AI is also essential in stopping or minimizing cyber crimes and providing cyber security. This article also highlights the methods through which cyber threats are kept sent. To design the algorithm that can be useful to secure the data and information. Most studies have focused on detection, prevention systems, and intrusion. The most dominant technique used was in support of Vector machines. This study also emphasized the drawbacks of AI as well as helps understand the future of Artificial Intelligence in securing Cybersystems.
Introduction: Good oral health is vital for overall health as well as the quality of life and depends on oral health literacy. This study’s aim was to assess the level of knowledge, attitudes, and oral hygiene practices among patients attending Rwanda Military Hospital in dental services. Methods: This study was a cross-sectional study design. A tested and structured questionnaire was used for the included 390 patients attending the RMH dental clinic. The analysis of the significance of factors towards oral hygiene was set at a P-value equal to 0.05 and a certainty level of 95%. Findings: The results showed that 54.4% of females dominated 45.6% of males. The findings showed that 50.5%,47.2%, and 61.35 were respectively with high knowledge, a positive attitude, and a good level of oral hygiene practice. It was also found that a low level of knowledge was three-fold significantly associated with poor oral knowledge, [AOR=3.80; 95%CI:1.30-7.20, p=0.01]. In addition, the negative attitude was four-fold significantly associated with poor oral hygiene with [AOR=4.76; 95CI: 2.30-9.83, p<0.001. Conclusion: The study concluded that around half of the population have a low level of knowledge and a negative attitude. Moreover, the low level of knowledge and negative attitude was three-fold associated with poor oral hygiene. This study recommended implementing and strengthening the systematic oral health promotion program.
Today, in the business world, it is more of brain work than physical work. This is intellectual capital at work. Economic wealth is much more driven by this, is knowledge and information than depending wholly on physical assets. By this, the business organization can be of more value and substance, meeting expectations with zero tolerance for failure. This is organizational efficacy. This study investigates the relationship between intellectual capital and organizational efficacy. Two dimensions and measures were dwelt on from the criterion and the dependent variable respectively. Abased on the findings it was concluded strong relationship exists between intellectual capital and organizational efficacy. This study recommends that management and workers play their as favourably as possible for intellectual for all it offers for organizational efficacy. Keywords: Organizational Efficacy, Intellectual Capital, Human Capital, Productivity Efficiency, Quality, Structural Capital
The unanimous verdict from the global scientific community and environmental scientists is that there appears to be a discernable human influence exacerbating the climate crises and that human activity is at the root of the problem. The use of predominantly fossils in the energy sector since the industrial revolution and to power the energy needs of our ultramodern 21st century civilization had thrown spanner into the wheels of a friendly and habitable environment with the ecosystem at a terrible risk. However, Sustainable Architecture presents within the built environment a mitigation route on how to design and construct buildings that use resources efficiently in a way that meets the requirements of ecological sustainability and biodiversity. Sustainability is the new normal in order to live responsibly in our human induced climate crises. This paper seeks to delve into how architecture can play a key role in our eco- reappraisal involving relationship of species and the environment, especially as it patterns to the built environment and to reduce the existing carbon footprint and pollutions that put the global climate at a colossal risk. KEYWORDS: Sustainable Architecture, Climate Crisis and Global warming
Patients Characteristics Associated with Tuberculosis Treatment Default: A case control study in high incidence are in western Kenya Kepha N. Mosiori1, Aminer O. Titus1 , Asito S. Amolo1, Affiliations: 2Jaramogi Oginga Odinga University of Science and Technology, JOOUST, Bondo, Kenya; 3Jaramogi Oginga Odinga Teaching and Referral Hospital, JOOTRH, Ministry of Health, Kisumu-Kenya. Email of corresponding Authors: 1.jakogwanjo@gmail.com Abstract Background: Poor adherence to treatment is a common occurrence and is associated with patients remaining infectious for longer periods, relapse, treatment failure and the emergence of multidrug resistant or extreme drug resistant TB. This problem is further compounded by TB-Human Immunodeficiency virus (HIV) co-infection putting a further burden on the drug burden that TB patients are taking. Our objective was to identify risk factors associated with tuberculosis (TB) treatment default in western Kenya. Methods: We conducted retrospective case control study design utilizing both primary and secondary data to identify factors associated with treatment default using data from a cohort of patients (adults and children) registered during the period January 2012 and March 2014 in Rachuonyo North Sub-County Homabay County. The secondary data was abstracted from TB register while primary data was collected using a standardized patient questionnaire. We defined default as interrupting TB treatment for two or more consecutive months during treatment. Cases were a sample of registered TB patients receiving treatment under DOTS that defaulted from treatment. Controls were those who began therapy and were cured, completed or failed treatment. We use bivariate logistic regression analysis to identify independent risk factors associated with default. Results: We enrolled a total of 297 of cases and controls (135 cases and 162 controls). The main reasons for defaulting included distance from health facility, relocation, stigma, longer time waiting and side effects of anti TB drugs, ignorance, drug shortage and feeling better. The risk factor for default included paying service charge (OR, 2.93; 95%CI 1.24-6.94), residing 6 Km from the health facility (OR, 5.06; 95%CI 2.05-12.49), staff having negative attitude (OR, 4.42; 95%CI 2.07-9.42), perception that staff in health facility were not skilled (OR, 2.97; 95%CI 1.52-5.77), health facility not well equipped (OR, 2.76; 95%CI 1.36-5.59), lack patient Support Structure (OR, 3.05; 95%CI 1.62-5.75) and lack of patient recognition (OR, 13.36; 95%CI 4.47-39.98).. Further analysis revealed that those who had not disclosed their TB status (OR, 2.90; 95%CI 1.27-6.60), those who were not getting household support (OR, 1.11; 95%CI 0.67-1.83) and those taking drugs and substances (OR, 2.37; 95%CI 1.37-4.20) were more likely to default from TB treatment. Conclusions: Multiple factors including distance, staff having negative attitude, lack of patient support structure and recognition were independently associated with default. There is a need for integrated interventions that addressed patient and health facility related factors that lead to TB treatment default among patients Background Tuberculosis is a major global health problem second only to human immunodeficiency virus (HIV) in terms of mortality (WHO, 2011; WHO, 2012). Significantly TB is thought to infect a third of human population globally and by 2010 it was estimated that there were 12 million TB cases (WHO, 2012). This was further compounded by the fact that a majority of the cases present with HIV infection (Tola et al., 2015) and the brunt of these infections are borne by African countries (WHO, 2011). Indeed studies have indicated that a country like Kenya which is ranked 13th among the 22 countries with highest TB burden globally also have the highest HIV burden (MOH, 2007; Muture et al., 2011). Although treatment of TB requires long time medication regimen (Freiden et al., 2004; Lackey et al., 2015), evidence indicates that taking anti-tuberculosis drugs for at least six months can successfully treat TB (Muture et al., 2011; Hailu et al., 2015). This led the Kenyan Ministry of Health (MOH) to adopt the recommended World Health Organization (WHO) TB control strategies and treatment regimens (Muture et al., 2011). The TB treatment regimens takes 6 months and involves intensive phase that takes place within the first two months following initiation of treatment where patients collects drugs on weekly basis and the continuation phase were they collect drugs on fortnight basis (WHO, 2008; Muture et al., 2011). During the intensive phase the TB patients mainly take a combination dose of rifampicin (R), isoniazid (H), pyrazinamide (Z) and ethambutol (E) followed by four months of rifampicin and isoniazid (Muture et al., 2011; Tola et al., 2015). However, treatment of multi-drug resistant TB (MDR-TB) treatment regimen takes more than six months (Lackey et al., 2015). Overall the long period of medication has been associated with default or low adherence to TB treatment regimes resulting in drug resistance, continued transmission in communities, mortality and impact on health system costs (Toczek et al., 2012; Hailu et al., 2015). To ensure long term adherence to treatment several countries have adopted Direct Observed Therapy short course (DOT) strategy by a health worker or a close relationship during the treatment period (Muture et al., 2011; Lackey et al., 2015). However, despite the implementation of these policies and programs, treatment failures have been reported in many Africa countries (Muture et al., 2011;Tola et al., 2015) as a result of non-adherence and loss to follow up (Hailfu et al., 2015). In deed reports indicate that treatment success rate in Kenya is still below the WHO recommended rates and this has further been compounded by HIV co-infection (MOH, 2010). Although there is geographical variation of TB prevalence in Kenya (MOH, 2007; Muture et al., 2011), there is still a paucity of data on treatment default in counties with the highest HIV and TB co-infections like Homa Bay county (NASCOP, 2014;Yuen et al., 2014). Therefore, this study was designed to determine the prevalence of TB treatment default among TB patients in regions with high TB and HIV prevalence Default from TB treatment encompasses both non-adherence and lost to follow up (Tola et al., 2015). Whereas non-adherence to treatment refers to the patients inability, erratic, refusal or selective compliance in taking TB medications prescribed by health workers (Reichman and Lardizabal, 2013;WHO, 2013), lost to follow up refers to where TB patients do not start treatment or where the treatment is interrupted for 2 consecutive months or more (WHO, 2013). A previous study in Nairobi County found that the rate of TB treatment defaulters was higher during the intensive phase of treatment and decreased with each subsequent month (Muture et al., 2011). This is similar to findings from Brazil and Hong Kong (Chang-Yeung et al., 2003; Oliveira et al., 2006). However, other studies from Sub-Saharan Africa, and Singapore found that the rate of default is more during the continuation phase (Chee et al., 2000; Daniel et al., 2006). These data indicate that there are context-specific issues influencing the rate of default and the treatment phase where default occurs. More importantly, HIV-co-morbidity has been found to influence TB treatment default (Tola et al., 2015). The risk of default from TB treatment is a multifactorial process influenced by individual patient behavioral factors, health facility related factors, sociodemographic and economic factors, community related factors, therapy-related factors, knowledge-related factors (Muture et al., 2011; WHO, 2013; Tola et al., 2015). Of significance is that these factors are inter-related and form a network of causal pathways against TB patient tolerance ability to TB treatment (Hargreaves et al., 2011). Hence there is a need for a thorough understanding of how these factors influence TB patients’ tolerance ability and promote treatment non-adherence and lost to follow up. This will be critical in developing strategies and interventions to improve treatment outcomes in TB patients. In deed previous studies in Sub-Saharan Africa indicated that socioeconomic factors such as financial constraints are a major impediment to adherence to TB treatment (Tola et al., 2015). The other determinants include lack of social support or stigma especially for those co-infected with HIV, low education (Dodor et al., 2005). Yet other studies have also found that older age, being male, inadequate knowledge, and ignorance on need for treatment compliance, consumption of alcohol and cigarette smoking are also import determinants of default from TB treatment (Muture et al., 2011; WHO, 2013; Tola et al., 2015)). In addition, lack of food, HIV status of the TB patients, distance from health facilities, poor service provider attitudes, negative attitude by TB patients towards the treatment centers, drug stock outs, poor access to health services and living near to treatment centre, patients resorting to traditional medication or herbal medicine (Bagchi et al., 2010; Muture et al., 2011; Tola et al., 2015). The side effects of the drugs or where the patients feel better after initial treatment are important determinants of non-adherence and loss to follow up (Wasonga,2006; Tachfouti et al., 2012). Although these previous studies indicate that these factors are important determinants in influencing treatment default, there is a paucity of data on factors that influence treatment outcomes in regions with both high TB and HIV burden in western Kenya. Our primary objectives was to describe the frequency of treatment default in a high incidence region of Rachuonyo-North sub-county and to identify factors associated with treatment default in order to provide insight to the policy makers and clinicians in improving care. We therefore, conducted a case control study in the Sub-County, looking for determinants of treatment default. Methods Study design We performed a retrospective case control study design utilizing both primary and secondary data. Study population The study population comprised the cohort of patients (adults and children) registered during the period January 2012 and March 2014 distributed in all health districts in Rachuonyo North Sub-County Homabay County. The epidemiological data of all TB patients was abstracted from TB registers from all TB control program treatment sites in Rachuonyo North Sub-County, namely; Kendu Sub-County Hospital, Miriu Health Centers, Kandiege Health Centers, Olando Disp., Wagwe Health Centers, Simbi Dispensary, Chuowe Dispensary, Kobuya Dispensary, Chuthber Dispensary, Kosele Dispensary, Nyaoga Dispensary, Homalime Dispensary, Lela Dispensary and Alum Beach Dispensary. The Sub-County has a population of approximately 141,037 residents who are predominantly of Luo ethnicity and practice farming as the major economic activity. The HIV prevalence in this area stands at 26.8% (NASCOP, 2014).In addition recent data indicate that TB prevalence in western Kenya where RachuonyoSub-County is located is 32.1% (Videlis et al., 2015). This region also has high poverty levels standing at 45%(MOH, 2008; 2012).The TB control program registers and gives medication to all TB patients in the sub county health facilities including those with HIV co-infection. The ministry of health as also integrated TB and HIV services since the year 2005 in the whole country (Sitienei et al., 2013). Cases were patients whose treatment were interrupted for 2 consecutive months or more (as defined by WHO) or did not start treatment while controls will be those who adhere to treatment regimes. Sampling procedure From the sampled facilities, all patients who defaulted within the study period will be enrolled. Controls will be randomly selected from among the patients who had completed treatment course. Cases and controls will be matched for site (approximately equal number of each per treatment site). To enhance understanding of risk factors for default, a sample of 335 cases and 335 controls aged 15 years and above (adults) will be randomly selected from the target study population from which 335 cases and all 335 controls will be traced and interviewed. Study procedure Statistical analysis Data collected was checked on the field and cleaned at the end of each day to ensure completeness, consistency, credibility and eligibility. This was done to correct errors or to fill-in missing information before another day of data collection. The study participants were stratified into cases and controls and analysis was carried out for both secondary and primary data. Anthropometric data was analyzed using Epi Info for Windows, Version 3.3.2 while STATA 13 statistical software (Stata corp., College Station, TX, USA) packages were used for data analysis. An association was analyzed using two-tailed Yates-corrected chi-square or Fisher exact test. Odds ratios were used as measure of association and corresponding 95% confidence intervals calculated using Taylor (T) series. Variables significant at the two-tailed 0.2 levels during univariate analysis were included in multivariate logistic regression model to determine the factors that influence default. Kaplan-Meier survival analysis method was used to determine probabilities of defaulters continuing with thetreatment program over different durations Ethical considerations This was a retrospective study and did not involve any experimental procedures on the patients. This study was approved by the Ethical Review Board of University of East Africa, Baraton (UEAB/02/11/2015). All the study participants provided written informed consent and received a copy of the form. Data was managed securely and anonymously. Names and address of the patients of the patients were only collected for the purpose of follow up. Results Characteristics of the study population As shown in table 1, a total of 297 of cases and controls (135 cases and 162 controls) were enrolled. Among the cases there were 71 males and 89 were young adults aged between 20-40 years. Most of the cases (65) had secondary education and 44 had 4-6 people in their households. Of the 135 cases, 49 used bicycle as a means of transport to the health facilities, 115 had disclosed their TB status and 89 were getting household support. In addition 46 were taking drugs and substances and 98 had under five year old children in their households. Table1 Sociodemographic characteristics of the study population Characteristics Cases (n = 135) Controls (n = 162) N(%) N(%) Total n(%) Chi square p - value Sex Male 71(45.4) 91(56.2) 162(54.6) 0.3807 0.537 Female 64(47.4) 71(52.6) 135(45.4) Age Group Adolescent(<20 Years) 7(77.8) 2(22.2) 9(3.0) 4.9172 0.178 Young Adults (20-40) 89(42.8) 119(57.2) 208(69.8) Middle-Age Adults(41-59Years) 29(50) 29(50) 58(19.5) Elderly (<59 Years) 11(47.8) 12(52.2) 23(7.7) Highest level of education None 2(66.7) 1(33.3) 3(1.0) 2.4847 0.478 Primary 59(41.3) 84(58.7) 143(48.0) Secondary 65(49.2) 67(50.8) 132(44.3) Tertiary 10(50) 10(50) 20(6.7) No. of people in household 1 - 3 People 40(39.2) 62(60.8) 102(40.3) 11.7258 0.003 4-6 people 44(47.3) 49(52.7) 93(36.8) Above 6 people 39(67.2) 19(32.8) 58(22.9) Mode of transport On foot 44 60 104 5.8008 0.122 Bicycles 49 48 97 Motocycles 30 47 77 vehicles 13 7 20 Disclosure of patient TB status Yes 115 150 256 6.8817 0.009 No 20 9 29 Household support Yes 89(45.18%) 108(45.82%) 197(69.12 0.1592 0.69 No 42(47.73%) 46(52.27%) 88(30.88%) Taking drugs or substances Yes 46 27 73 9.832 0.002 No 89 124 213 No. of under five year old in households underfive year old 98(44.95%) 120(55.05%) 218 3.0305 0.692 All the data was analyzed using Pearson Chi-square Reasons for defaulting To enhance reasons for defaulting, all the 135 cases who had defaulted were interviewed. Data obtained from the interviews were used to identify the main reasons for defaulting. As shown in figure 1, of 135 cases interviewed distance was cited to have the highest effect leading to TB default 25.61% followed by relocation 23.17%, stigma 10.98%, longer time waiting and side effects had similar contribution at 9.76%, ignorance 6.1%, drug shortage and facility factors had equal effects at 4.88% while those who felt better at 3.66% and lastly inadequate food had the least effect at 1.22% Risk factors for default Sociodemographic related factors Univariate analysis was carried out to find the sociodemographic risk factors associated with TB default. As shown in table 2, univariate analysis shows that male (OR, 0.92; 95% CI 0.544- 1.572), young adults (OR, 0.19; 95%CI 0.021 - 1.679), middle age adults (OR, 0.28; 95%CI 0.029 - 2.728) and elderly (OR, 0.21; 95%CI 0.020 - 2.174) were less likely to default from TB treatment. Those with secondary (OR, 1.51; 95%CI 0.881 - 2.597) and tertiary (OR, 1.17; 95%CI 0.394 - 3.450) education were more likely to default relative to those with primary education. The mode of transports to health facility was an important determinant with those using bicycles (OR, 1.39; 95%CI 0.80-2.43) and vehicles (OR, 2.53; 95%CI 2.53) relative to those who went on foot. Moreover, those who considered distance to health facility as a challenge (OR, 3.67; 95%CI 2.44-6.00) and those who paid for transport (OR, 1.64; 95%CI 1.01-2.66) relative to those who did not considered distance as a challenge and those who did not pay for transport respectively. Those with 4-6 people (OR, 1.37; 95%CI 0.76- 2.46) and above 6 people (OR, 3.19; 95%CI 1.58 - 6.42) in their households were more likely to default relative to those with 1-3 people in their households. Further analysis revealed that those who had not disclosed their TB status (OR, 2.90; 95%CI 1.27-6.60), those who were not getting household support (OR, 1.11; 95%CI 0.67-1.83) and those taking drugs and substances (OR, 2.37; 95%CI 1.37-4.20) were more likely to default from TB treatment. Characteristics Cases (n = 135) Controls (n = 162) N(%) N(%) Total n(%) OR p - value Sex Male 71(45.4) 91(56.2) 162(54.6) 0.92(0.544- 1.572) 0.773 Female 64(47.4) 71(52.6) 135(45.4) ref Age Group Adolescent(<20 Years) 7(77.8) 2(22.2) 9(3.0) ref Young Adults (20-40) 89(42.8) 119(57.2) 208(69.8) 0.19(0.021 - 1.679) 0.134 Middle-Age Adults(41-59Years) 29(50) 29(50) 58(19.5) 0.28(0.029 - 2.728) 0.275 Elderly (>59 Years) 11(47.8) 12(52.2) 23(7.7) 0.21(0.020 - 2.174) 0.189 Highest level of education None 2(66.7) 1(33.3) 3(1.0) - - Primary 59(41.3) 84(58.7) 143(48.0) ref Secondary 65(49.2) 67(50.8) 132(44.3) 1.51(0.881 - 2.597) 0.134 Tertiary 10(50) 10(50) 20(6.7) 1.17(0.394 - 3.450) 0.781 No. of people in household 1 - 3 People 40(39.2) 62(60.8) 102(40.3) ref 4-6 people 44(47.3) 49(52.7) 93(36.8) 1.37(0.762 - 2.459) 0.293 Above 6 people 39(67.2) 19(32.8) 58(22.9) 3.19(1.582 - 6.422) 0.001 Mode of transport On foot 44 60 ref Bicycles 48 48 1.39(0.80-2.43) 0.244 Motocycles 13 47 0.87(0.48-1.59) 0.651 vehicles 30 7 2.53(0.93-6.87) 0.068 Is distance a challenge Yes 97 64 3.67(2.44-6.00) 0.0001 No 38 92 ref Paid for Transport Yes 92 93 1.64(1.01-2.66) 0.045 No 41 68 ref Disclosure of patient TB status Yes 115 150 ref No 20 9 2.90(1.27-6.60) 0.011 Household support Yes 89(45.18%) 108(45.82%) ref No 42(47.73%) 46(52.27%) 1.11(0.67-1.83) 0.69 Taking drugs or substances Yes 46 27 2.37(1.37-4.20) 0.002 No 89 124 ref Health care and system-related factors As shown in table 3, univariate analysis showed that those who paid for the service charge (OR, 2.93; 95%CI 1.24-6.94) were more likely to default relative to those who did not pay. Relative to those who resided <1Km from health facility, those from 1-6 Km (OR, 3.10; 95%CI 1.63-5.93) and those from more than 6 Km (OR, 5.06; 95%CI 2.05-12.49) were more likely to default on treatment. Analysis also revealed health staff attitude was an import determinant of default with those who agreed that staff had negative attitude (OR, 4.42; 95%CI 2.07-9.42) were more likely to default relative to those who disagreed. Further analysis revealed that those who agreed that staff in health facility were not skilled (OR, 2.97; 95%CI 1.52-5.77), health facility not well equipped (OR, 2.76; 95%CI 1.36-5.59), lack patient Support Structure (OR, 3.05; 95%CI 1.62-5.75) and lack of patient recognition(OR, 13.36; 95%CI 4.47-39.98) were more likely to default from treatment. Characteristics Cases (n = 135) Controls (n = 162) N(%) N(%) Total n(%) OR p - value Waiting time at the facility Less than 30min 56(30.4) 128(69.6) 184(62.0) 0.15(0.0754 - 0.2958) 0.000 30min-1hr 41(74.6) 14(25.4) 55(18.5) ref More than 1hr 39(67.2) 19(32.8) 58(19.5) 0.70(0.3094 - 1.5879) 0.394 Schedule for TB treatment Once Every week 102(44.7) 126(55.3) 228(78.9) 0.69(0.3900 - 1.2112) 0.194 Once Every Two Weeks 33(54.1) 28(45.9) 61(21.1) ref Treatment Return date After one week 59(36.2) 104(63.8) 163(59.9) 0.24(0.1310 - 0.4580) 0.000 After fortnight 44(69.8) 19(30.2) 63(23.2) ref After one month 16(66.7) 8(33.3) 24(8.8) 0.86(0.3162 - 2.3591) 0.775 I don’t know 9(40.9) 13(59.1) 22(8.1) 0.30(0.1093 - 0.8174) 0.019 Frequency of taking drugs Once 124(45.3) 150(54.7) 274(94.2) 0.58(0.2140 - 1.5647) 0.281 More than Once 10(58.8) 7(41.2) 17(5.8) ref Defaulting consequences Cured 7(87.5) 1(12.5) 8(5.3) ref Dead 17(65.4) 9(34.6) 26(17.3) 0.27(0.0286 - 2.5491) 0.253 Resistance 49(67.1) 24(32.9) 73(48.7) 0.29(0.0339 - 2.5075) 0.262 Transmission to others 12(80.0) 3(20.0) 15(10.0) 0.57(0.0494 - 6.6062) 0.654 Others 7(25.0) 21(75.0) 28(18.7) 0.05(0.0050 - 0.4578) 0.008 Paid service charge Yes 19(70.4) 8(29.6) 27(9.5) 2.93(1.2386 - 6.9432) 0.014 No 115(44.7) 142(55.3) 257(90.5) ref Distance of health facility <1Km 15 47 ref 1-6 Km 96 97 3.10(1.63-5.93) 0.001 >6 Km 21 13 5.06(2.05-12.49) 0.0001 Staff have negative attitude Disagree 99 141 ref agree 31 12 4.42(2.07-9.42) 0.0001 Don't know 5 5 1.14(0.30-4.35) 0.849 Staff not skilled Disagree 100 139 ref agree 32 15 2.97(1.52-5.77) 0.001 Don't know 3 4 1.04(0.29-4.76) 0.957 Health facility not well equipped Disagree 46 58 ref agree 35 16 2.76(1.36-5.59) 0.005 Don't know 6.30(0.71-55.86) 0.098 Lack Patient Support Structure Disagree 95 137 agree 37 17 3.05(1.62-5.75) 0.001 Don't know 3 5 0.58(0.11-3.04) 0.516 Staff Lack patient recognition Disagree 65 139 ref agree 25 4 13.36(4.47-39.98) 0.0001 Don't know 5 5 2.14(0.60-7.65) 0.242 Discussion This study was carried out to identify the reasons and determinants default in a region with high HIV prevalence of western Kenya. We found that there are multiplicity of reasons for defaulting including distance from health facility, relocation, stigma, side effects of the drugs, period of treatment, ignorance, health facility factors and drug shortage suggesting that there context-specific issues influencing the rate of default and the treatment phase. This findings are in agreement with previous studies from Kenya (Muture et al., 2011), suggesting that although the Kenya, the government supports treatment of tuberculosis by availing free diagnostic services, drugs and direct observed therapy, there is a need of community targeted interventions to address these issues to ensure up-scaling of uptake of TB treatment in poor resource settings. Previous studies have shown that within the settings of the settings were directly observed therapy has been implemented; there are several factors that lead to default from TB treatment default (Hascker et al., 2008; Muture et al., 2011; Culqui et al., 2012; Lackey et al., 2015). Contrary to previous studies that indicated that TB treatment default is associated with male gender (Muture et al., 2011; Lackey et al., 2015; Kigonzi et al., 2017), we found that males were less likely to default from TB treatment. Although the reasons for difference between our findings and the previous studies are not clear, it has been shown that in areas with high HIV-TB co-infection, male gender is protective against death in TB patients (Kigonzi et al., 2017). This has been attributed to gender-based barriers including financial dependence, lower general literacy and household stigma (Krishnan et al., 2014). In line with research conducted in Morocco and Northwest Ethiopia (Tessema et al., 2009; Cherkaoui et al., 2014) it was observed that younger older cases (<24 years) were more likely to default treatment compared to their older counterparts (≥20 years) and this is probably due to the fact that older patients do not face barriers such as financial dependence and stigma that may led to default or that they had superior strategies to help them cope with TB than their younger counterparts. Together, these data indicate that there is a need of programmatic intervention that target younger patients. Furthermore transport cost associated weekly collection of drugs from health facility can lead to TB cases defaulting especially in households with limited resources (Muture et al., 2014). In line with this previous observation, our study reveals that TB patients who indicated that transport is a challenge or paid for transport were more likely default from TB treatment, indicating that there is need of programs that address issues of resources for transport and other opportunity costs to make the drugs easily available to TB patients. In poor resource settings such as our study area, patients have to choose between competing priorities like buying food for family members and paying for transport to get medication. It significant to note that our data also revealed that TB cases from households with ≤3 people were less likely to default compared to those with >4 people further suggesting that financial and opportunity cost are a major challenge to TB treatment and needs to be addressed in order to reduce the rate of default to TB treatment. This study showed that TB patients who had not disclosed their status were more likely to default from TB treatment. This can be attributed to the fact that in African societies TB patients are stigmatized due cultural factor associated with misinformation about the medical aspects of the disease and misinformation that TB is related to HIV (Muture et al., 2011; Kigonzi et al., 2017), this can influence patient health seeking behavior in terms of weekly collection of drugs since in areas with high HIV burden the patients are thought to be on antiretroviral drugs. This led the Kenyan Ministry of Health to integrate TB and HIV care where both the National tuberculosis control program (NTP) and the National AIDS and Sexually Transmitted Diseases (STD) Control Program (NASCOP) screen TB or HIV patients for both disease to enable early initiation to treatment and care (Lönnroth et al., 2010; Muture et al., 2011). Further our data reveal that TB cases that did not get household support were more likely to default and this can be attributed to household stigma (Krishnan et al., 2014). These data indicate that in order to reduce treatment default among TB patients there is need of advocacy programs against stigmatization directed at the community and at household levels to reduce stigma associated with TB. Several studies have shown that drug and alcohol use are associated with a higher risk of default (Culqui et al., 2011; Lackey et al., 2015; Kigonzi et al., 2017; Ramachandran et al., 2017). Consistent with these previous findings this study found that TB cases that were using drugs or substances were more likely to default. This is partly due to the fact that drug or substance use may lead to patients forgetting or failing to take drugs leading to default. More importantly, these drugs and substances can be cheaply obtained in poor resource setting and their combined effects with anti-tuberculosis drugs can liver damage(Muture et al., 2011). These exacerbated side effects can lead to TB treatment default. Of significance, behavior change intervention targeting reduction of patient alcohol has proven to be effective (Kaner et al., 2007). With respect to health facility related factors associated with TB treatment default. our data indicates that waiting time at the facility before provision of services, patient knowledge about TB treatment schedule or return data and frequency of taking drugs, paying for service charges, distance to health facility, health provider negative attitude, lack of patient recognition, perception that staff are not well trained and the hospitals are not well equipped were important determinants of TB treatment default. This is in agreement with previous observation that Health system related factors such as service provider or patient attitudes, drug stock outs and access to health facility are important determinants of adherence or default to TB treatment (Daniel et al., 2006; Muture et al., 2011). Indeed it has been shown that health system barriers that impact on TB treatment adherence including lack of adequate financing of health care programs and overstretched or overworked healthcare workers is a common phenomenon in poor resource countries like Kenya (Muture et al., 2011). However, these health facility factors can be mitigated through enhanced training of health care workers on communication and counseling, development of effective and patient centered materials that focus on adherence and self-monitoring, enhanced clinical follow up and surveillance of TB cases, provision of incentives like transport reimbursements, improved community participation in provision of based DOTS, integration of HIV and TB treatment and care, enhanced and efficient of TB programs and (adequate financial and human resources (Finlay et al., 2012). In addition, there is need to reduce waiting time, equip health facility and ensure that there are no drugs stock of TB drugs. . 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Reyes-Guillén, I.; Sánchez-Pérez, H.J.; Cruz-Burguete, J.; Izaurieta-de Juan, M. (2008). “Anti-Tuberculosis Treatment Defaulting. An Analysis of Perceptions and Interactions in Chiapas, Mexico.” Salud Publica Mex No.50 pp 251-257. Declarations Ethical Consideration The study was approved by the ethical review board of University of East Africa Baraton (REC: UEAB/17/02/2016). All the study participants parents and legal guardians gave their written Competing interest The authors declare they have no competing interests. Authors’ contributions KF, JOA and ASA conceived of the study and participated in its design; KF and AO carried out laboratory assays; ASA carried out statistical analysis. KF and AJO drafted the manuscript. All authors read and approved the final manuscript Acknowledgements We would like to thank the Health Department team of Rachuonyo North sub county for their technical support.
This study aims to explore the use of skim milk as fat replacer and at what level must use to replace pork fat in frankfurter sausage product. Emulsified frankfurter products are higher in fat than whole muscle fresh or cured products. Most cooked and smoked frankfurters may contain up to 30% fat but the industry average is approximately 20% (Keeton, 1994). In conventional frankfurters, animal fat is an essential ingredient representing 20–25% of overall composition. Animal fat is considered as rich in saturated fatty acids with negative effect on human health. From a nutritional point of view, it is of interest to reduce this high levels of lipids, but the elimination or reduction of fat reduces sensory quality in the final product, in particular affecting its texture (Ordonez et al., 2001). The study is delimited only to the effect of different herbs on the sensory characteristics of frankfurter sausage with the following parameters that will be using such as saltiness and folding test and the influence of the five herbs/spices to be added [white pepper, basil, dill, rosemary and citron pepper]. Keywords: skim milk, frankfurter sausage, herbs, Southern Mindanao
Spirulina are free floating gram negative bacteria which carry out photosynthesis. They are oxygenic, filamentous, photolithoautotroph, unbranched and multicellular blue-green algae with symbiotic bacteria that fix atmospheric nitrogen by the process of nitrogen fixation from air. Spirulina is commercially produced around the world and used as food and feed supplement in the human dietary and aquaculture industries, respectively. Spirulina is nutritionally rich in protein and has got worldwide attention to solve malnutrition problems. Moreover, it becomes more popular based on its best applicability on the utilization mechanism of carbon dioxide as in photosynthesis. The growth and productivity of spirulina are mainly dependent on temperature, light source, salinity, growth media, pH, size of inoculum, agitation and carbon dioxide. Spirulina have different applications in bio-fertilizer production, food industry, animal forage supplement, greasepaints, pharmaceutical industry, and energy making industry, waste water treatment and carbon dioxide alleviation. Therefore, this paper reviews how to increase the biomass productivity of Spirulina.
The extreme toxicity of cyanide, its wide industrial application as well as its continued illegal use generate research interest in different fields of science, imposing multidisciplinary approach to study cyanide poisoning. This seminar paper presents new data about cyanide exposure, toxicology, and antidote development. Cyanide concerned research in environmental and forensic sciences along with medicine closely depends on the recent achievements in cyanide determination methods. Newly reported cyanide detection systems and sample pretreatment procedures for environmental, biological and plant samples are summarized. The main requirements to analytical systems for cyanide determination and the trends in analytical research are also discussed.Key words: analytical methods, cyanide, matrices
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