Determinants for deployment of climate-smart integrated pest management practices: a meta-analysis approach

Following the development and dissemination of new climate-smart agricultural technologies to farmers globally, there has been an increase in the number of socio-economic studies on the adoption of climate-smart integrated pests’ management (CS-IPM) technologies over the years. In this study, we review empirical evidence on adoption determinants of CS-IPM technologies and identify possible science-policy interfaces. Generally, our review shows that socioeconomic and institutional factors are influential in shaping CS-IPM adoption decisions of farmers. More specifically, income was found to positively influence the adoption of CS-IPM technologies while land size owned influences CS-IPM adoption negatively. Registered land tenure (registered secure rights) positively influences CS-IPM technologies’ adoption, implying that efficient land markets that enable competitive and fair distribution and access to land, more so by the vulnerable but efficient smallholder producers do indeed increase the adoption of CS-IPMs technologies. Social capital, achieved via farmers’ organizations is also central in fostering CS-IPM technologies’ adoption, just as markets reforms that minimize market failures regarding access to credit, labor, and agricultural information, which could indirectly hinder farmers’ use of CS-IPM practices. Functional extension systems that improve farmers’ awareness of CS-IPM do also improve CS-IPM technologies’ adoption. However, the adoption of CS-IPM technologies in Ghana and Benin is slow-paced because of factors like lack of access to farm inputs that facilitate uptake of these technologies, lack of credit facilities, and limited extension services among others. Interestingly, our review confirms that CS-IPM technologies do indeed reduce and minimize the intensity of pesticide usage and foster ecosystem (environmental and human) health. Therefore, this review unearths strategic determinants of CS-IPM adoption and makes fundamental guidance around climate-smart innovations transfer and environmental policies that should be prioritized to curb environmental pollution and ensure agricultural ecosystems’ sustainability

Self-reported diabetes is associated with self-management behaviour: a cohort study

<p>Abstract</p> <p>Background</p> <p>The purposes of this cohort study were to establish how frequently people with physician-diagnosed diabetes self-reported the disease, to determine factors associated with self-reporting of diabetes, and to evaluate subsequent differences in self-management behaviour, health care utilisation and clinical outcomes between people who do and do not report their disease.</p> <p>Methods</p> <p>We used a registry of physician-diagnosed diabetes as a reference standard. We studied respondents to a 2000/01 population-based health survey who were in the registry (n = 1,812), and we determined the proportion who reported having diabetes during the survey. Baseline factors associated with self-report and subsequent behavioural, utilisation and clinical differences between those who did and did not self-report were defined from the survey responses and from linkage with administrative data sources.</p> <p>Results</p> <p>Only 75% of people with physician-diagnosed diabetes reported having the disease. People who did self-report were more likely to be male, to live in rural areas, to have longer disease duration and to have received specialist physician care. People who did not report having diabetes in the survey were markedly less likely to perform capillary blood glucose monitoring in the subsequent two years (OR 0.05, 95% CI 0.02 to 0.08). They were also less likely to receive specialist physician care (OR 0.55, 95% CI 0.37 to 0.86), and were less likely to require hospital care for hypo- or hyperglycaemia (OR 0.09, 95% CI 0.01 to 0.28).</p> <p>Conclusion</p> <p>Many people with physician-diagnosed diabetes do not report having the disease, but most demographic and clinical features do not distinguish these individuals. These individuals are much less likely to perform capillary glucose monitoring, suggesting that their diabetes self-management is inadequate. Clinicians may be able to use the absence of glucose monitoring as a screening tool to identify people needing a detailed evaluation of their disease knowledge.</p

Multimorbidity prevalence and patterns across socioeconomic determinants: a cross-sectional survey

<p>Abstract</p> <p>Background</p> <p>Studies on the prevalence of multimorbidity, defined as having two or more chronic conditions, have predominantly focused on the elderly. We estimated the prevalence and specific patterns of multimorbidity across different adult age groups. Furthermore, we examined the associations of multimorbidity with socio-demographic factors.</p> <p>Methods</p> <p>Using data from the Health Quality Council of Alberta (HQCA) 2010 Patient Experience Survey, the prevalence of self reported multimorbidity was assessed by telephone interview among a sample of 5010 adults (18 years and over) from the general population. Logistic regression analyses were performed to determine the association between a range of socio-demographic factors and multimorbidity.</p> <p>Results</p> <p>The overall age- and sex-standardized prevalence of multimorbidity was 19.0% in the surveyed general population. Of those with multimorbidity, 70.2% were aged less than 65 years. The most common pairing of chronic conditions was chronic pain and arthritis. Age, sex, income and family structure were independently associated with multimorbidity.</p> <p>Conclusions</p> <p>Multimorbidity is a common occurrence in the general adult population, and is not limited to the elderly. Future prevention programs and practice guidelines should take into account the common patterns of multimorbidity.</p

How many people have had a myocardial infarction? Prevalence estimated using historical hospital data

<p>Abstract</p> <p>Background</p> <p>Health administrative data are increasingly used to examine disease occurrence. However, health administrative data are typically available for a limited number of years – posing challenges for estimating disease prevalence and incidence. The objective of this study is to estimate the prevalence of people previously hospitalized with an acute myocardial infarction (AMI) using 17 years of hospital data and to create a registry of people with myocardial infarction.</p> <p>Methods</p> <p>Myocardial infarction prevalence in Ontario 2004 was estimated using four methods: 1) observed hospital admissions from 1988 to 2004; 2) observed (1988 to 2004) and extrapolated unobserved events (prior to 1988) using a "back tracing" method using Poisson models; 3) DisMod incidence-prevalence-mortality model; 4) self-reported heart disease from the population-based Canadian Community Health Survey (CCHS) in 2000/2001. Individual respondents of the CCHS were individually linked to hospital discharge records to examine the agreement between self-report and hospital AMI admission.</p> <p>Results</p> <p>170,061 Ontario residents who were alive on March 31, 2004, and over age 20 years survived an AMI hospital admission between 1988 to 2004 (cumulative incidence 1.8%). This estimate increased to 2.03% (95% CI 2.01 to 2.05) after adding extrapolated cases that likely occurred before 1988. The estimated prevalence appeared stable with 5 to 10 years of historic hospital data. All 17 years of data were needed to create a reasonably complete registry (90% of estimated prevalent cases). The estimated prevalence using both DisMod and self-reported "heart attack" was higher (2.5% and 2.7% respectively). There was poor agreement between self-reported "heart attack" and the likelihood of having an observed AMI admission (sensitivity = 63.5%, positive predictive value = 54.3%).</p> <p>Conclusion</p> <p>Estimating myocardial infarction prevalence using a limited number of years of hospital data is feasible, and validity increases when unobserved events are added to observed events. The "back tracing" method is simple, reliable, and produces a myocardial infarction registry with high estimated "completeness" for jurisdictions with linked hospital data.</p

Interactive “Video Doctor” Counseling Reduces Drug and Sexual Risk Behaviors among HIV-Positive Patients in Diverse Outpatient Settings

, an interactive, patient-tailored computer program, was developed in the United States to improve clinic-based assessment and counseling for risky behaviors.We conducted a parallel groups randomized controlled trial (December 2003–September 2006) at 5 San Francisco area outpatient HIV clinics. Eligible patients (HIV-positive English-speaking adults) completed an in-depth computerized risk assessment. Participants reporting substance use or sexual risks (n = 476) were randomized in stratified blocks. The intervention group received tailored risk-reduction counseling from a “Video Doctor” via laptop computer and a printed Educational Worksheet; providers received a Cueing Sheet on reported risks. Compared with control, fewer intervention participants reported continuing illicit drug use (RR 0.81, 95% CI: 0.689, 0.957, p = 0.014 at 3 months; and RR 0.65, 95% CI: 0.540, 0.785, p<0.001 at 6 months) and unprotected sex (RR 0.88, 95% CI: 0.773, 0.993, p = 0.039 at 3 months; and RR 0.80, 95% CI: 0.686, 0.941, p = 0.007 at 6 months). Intervention participants reported fewer mean days of ongoing illicit drug use (-4.0 days vs. -1.3 days, p = 0.346, at 3 months; and -4.7 days vs. -0.7 days, p = 0.130, at 6 months) than did controls, and had fewer casual sex partners at (−2.3 vs. −1.4, p = 0.461, at 3 months; and −2.7 vs. −0.6, p = 0.042, at 6 months)., including Video Doctor counseling, is an efficacious and appropriate adjunct to risk-reduction efforts in outpatient settings, and holds promise as a public health HIV intervention

Working conditions and public health risks in slaughterhouses in western Kenya

Background: Inadequate facilities and hygiene at slaughterhouses can result in contamination of meat and occupational hazards to workers. The objectives of this study were to assess current conditions in slaughterhouses in western Kenya and the knowledge, and practices of the slaughterhouse workers toward hygiene and sanitation. Methods: Between February and October 2012 all consenting slaughterhouses in the study area were recruited. A standardised questionnaire relating to facilities and practices in the slaughterhouse was administered to the foreperson at each site. A second questionnaire was used to capture individual slaughterhouse workers’ knowledge, practices and recent health events. Results: A total of 738 slaughterhouse workers from 142 slaughterhouses completed questionnaires. Many slaughterhouses had poor infrastructure, 65% (95% CI 63–67%) had a roof, cement floor and walls, 60% (95% CI 57–62%) had a toilet and 20% (95% CI 18–22%) had hand-washing facilities. The meat inspector visited 90% (95% CI 92–95%) of slaughterhouses but antemortem inspection was practiced at only 7% (95% CI 6–8%). Nine percent (95% CI 7–10%) of slaughterhouses slaughtered sick animals. Only half of workers wore personal protective clothing - 53% (95% CI 51–55%) wore protective coats and 49% (95% CI 46–51%) wore rubber boots. Knowledge of zoonotic disease was low with only 31% (95% CI 29–33%) of workers aware that disease could be transmitted from animals. Conclusions: The current working conditions in slaughterhouses in western Kenya are not in line with the recommendations of the Meat Control Act of Kenya. Current facilities and practices may increase occupational exposure to disease or injury and contaminated meat may enter the consumer market. The findings of this study could enable the development of appropriate interventions to minimise public health risks. Initially, improvements need to be made to facilities and practices to improve worker safety and reduce the risk of food contamination. Simultaneously, training programmes should target workers and inspectors to improve awareness of the risks. In addition, education of health care workers should highlight the increased risks of injury and disease in slaughterhouse workers. Finally, enhanced surveillance, targeting slaughterhouse workers could be used to detect disease outbreaks. This “One Health” approach to disease surveillance is likely to benefit workers, producers and consumers

The Prevalence of Sexually Transmitted Infections in Papua New Guinea: A Systematic Review and Meta-Analysis

Patellofemoral osteoarthritis (PF OA) is more prevalent than previously thought and contributes to patient's suffering from knee OA. Synthesis of prevalence data can provide estimates of the burden of PF OA

Technical Note: Recommendations for Assessing Unit Nonresponse Bias in Dyadic Focused Empirical Supply Chain Management Research

The last decade has seen an increase in empirical supply chain management research with dyadic data. Such data structures can further complicate the assessment of nonresponse bias, which plays a key role in establishing the credibility of research results. A survey of 75 research articles with dyadic data, published in five empirically focused supply chain management academic journals, over the last decade, reveals a lack of agreement on methods used in the assessment for potential unit nonresponse bias. Of the various statistical tests found, only the Multivariate Analysis of Variance (MANOVA) approach allows for a single statistical test to be utilized in assessing for potential unit nonresponse bias via incorporation of the design structure of the dyadic data. We investigate the use of an effect size confidence interval coverage, of a MANOVA, to detect a meaningful difference between respondents and nonrespondents correctly. Our results show that with dyadic data, such meaningful differences can be detected with significantly smaller sample size requirements than traditional approaches such as t‐tests or ANOVA. Recommendations are provided for setting up and executing a MANOVA to assess for potential unit nonresponse bias with dyadic data.This accepted article is published as Clottey, T. and Benton, W.C., Jr. (2020), Technical Note: Recommendations for Assessing Unit Nonresponse Bias in Dyadic Focused Empirical Supply Chain Management Research. Decision Sciences, 51: 423-447. Doi: 10.1111/deci.12431. Posted with permission. </p