Impact of foreign interventions on forest development projects in Jigawa state, Nigeria

Since the inception of independent, local interventions have been coming to play in forest development inNigeria. Therefore, there is need to access the impact of foreign interventions on forest development projects in Nigeria. Therefore, the study examined the impact of foreign interventions on the forest development project in Jigawa State with the view to ascertaining the need. Purposive sampling design employed in the study. A total of two hundred and forty (240) copies of questionnaire were administered and the data were subjected to the descriptive statistical analysis. The mean age of the respondents is 32.7 years. Majority (62.1%) were males, married (48.8%). Most respondents were either students (37.1%), farmers (28.3%) or business men (18.8%). Below average have secondary education (43.3%). On awareness only Tree planting (x =1.733), Individual Wood Lot ( x=1.558) and Home Garden practices ( x=1.471) were known. There is a low involvement in home garden ( x=0.992), individual wood lot ( x=1.063) while tree planting (x =1.696) showed high involvement. No positive perception on FDP in the minds of the respondents. FDP has favorable impact on agronomic practices and the environment except pollution (12.9%). Awareness campaign show be instituted to the respondents in the community on the significance of FDP. Proper efforts should be made to involve the respondents more on FDP since the involvement of the respondents in FDP is low. It is recommended that Jigawa State government need foreign invention on forest development project in order to assist the State in arresting the spread of drought and desertification, enhance the productivity of the agricultural land, stimulates and increase the production of fuel wood, poles and other minor forest products in the State through improved perception of the respondents on FDP and bettered to improve the utilization and involvement in FDP as well as addressing, explored and addressed other agronomic practices to help agriculture Keywords: Foreign Interventions, Forest Development, Impact, Jigawa State and Project

Germination potentials of Synsepalum dulcificum (schumach. and thonn.) Daniell seeds to pre-treatment methods

The study was carried out to determine the germination intensity of Synsepalum dulcificum seeds to various pre-treatment methods. This research was carried out at the forest nursery of the Federal University of Agriculture Abeokuta, Ogun State, Nigeria. This present study aimed to determine the most effective mechanism of breaking dormancy to enhance germination intensity in seeds of Synsepalum dulcificum using mechanical scarification at three point on seeds namely microplye, distal end and around the circumference. Also, seeds were soaked in water of temperatures of 20°C, 40°C and 80°C for 10, 30 and 60 mins respectively, in 5,10 and 15% H2SO4 acid for 5, 10 and 15 mins respectively and, in GA3, IAA and IBA hormones of 0.01, 0.02 and 0.03ppm. Obtained data was analyzed using ANOVA and Fisher’s Least Significant Difference was used to separate significant means. Results showed that highest germination percentage was obtained in seeds mechanically scarified around the circumference (50%) which was not significantly different (p>0.05) from the control. Seeds soaked in 20°C water for 30 min was significantly (p<0.05) higher than other treatments in category with germination percentage of 62.5% while highest germination were also obtained in seeds soaked in 5% H2SO4 for 5mins (31.25%) and seeds soaked in 0.02 ppm GA3 (62.5%). The study concludes that S. dulcificum seeds will not have a problem of germination with the presence of suitable germination conditions. Keywords: Synsepalum dulcificum, seeds, pre-treatment, germination intensit

Economic analysis of Senegalia senegal (Gum Arabic) production in Yobe state, Nigeria

This work analyzed the economics of Senegalia senegal (gum Arabic) production in Yobe state, Nigeria. Specifically, it studied the socioeconomic characteristic of the farming respondents and the profitability of gum Arabic production in the state. Purposive and random sampling techniques were used to select Afunori, Nangere and Damaturu plantation areas as well as the sampled gum Arabic farmers respectively. Yero Yemeni`s model was used in the determination of the number of gum Arabic farmers involved in the study. Data was collected using a structured questionnaire and the variables on which data was collected included gum Arabic production inputs and output, marketing costs and revenues. Data was also collected on socioeconomic variables. Both financial and statistical tools were used in analyzing the data including Gross Margin (GM) and Profitability analyses. Socioeconomic data revealed that the gum Arabic production scenario was dominated by youth, the male gender, educated elites and public servants with small land holding. Financial results on the contrary, revealed US$805.86 (N241, 758.00) GM values per hectare per year, whereas US$ 345, 948.88 (N103, 784, 664.00) was the total net profit realized. On the average each respondent earned US$1, 572.49 (N 471, 747.00). Thus, it was concluded that gum Arabic production in the state was economically profitable. However, its resources were grossly under exploited. Other production constraints uncovered included land tenure problem, poor extension services, lack of improved planting stocks and poor support on the part of government. Creation of enabling environment for improved production and marketing as well as adequate stakeholder involvement were some of the major policy recommendations made. Keywords: Economic analysis, Senegalia senegal, production, Yobe Stat

Economic analysis of Neem (Azadirachta indica) production in Yobe state, Nigeria

This work determined the economics of Azadirachta indica (neem) production in Yobe State, Nigeria. Specifically, it studied the socioeconomic characteristic of the farming respondents and the profitability of neem production in the State. Multistage sampling technique was used to select Afunori, Nangere and Damaturu plantation areas as well as the sampled neem farmers respectively. Yero Yemeni`s model was used in the determination of the number of neem farmers involved in the study. Data was collected using a structured questionnaire and the variables on which data was collected included neem production inputs and output, marketing costs and revenues. Data was also collected on socioeconomic variables. Both descriptive statistics and economic tools were used in analyzing the data including percentages, frequency distribution tables and Gross Margin (GM) analyses. Socioeconomic data revealed that aged, male gender, individuals with no formal education as well those with small land holding constituted 50%, 95.45%, 54.55% and 90.91% respectively. Financial results revealed respective GM and net profit values of N3, 831.82 and N 3, 274.06 per hectare per year. Thus, it was concluded that neem production in the State was not economically viable and was attributed principally to ignorance of its economic potentials and lack of functional markets. Other production constraints uncovered included land tenure problem, poor extension services, lack of improved planting stocks and poor supportive services. Key words: Economic analysis, Azadirachta indica, productio

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021

Background Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions. Funding: Bill & Melinda Gates Foundation