Analyzing neonatal deaths in Zimbabwe using box-jenkins arima modelsSubmissionResearchpa
Using annual time series data on neonatal deaths in Zimbabwe from 1966 to 2018, we model and forecast number of neonatal deaths over the next 25 years using the Box – Jenkins ARIMA technique. Diagnostic tests such as the ADF tests show that Neonatal Deaths (ND) series is I (2). Based on the AIC, the study presents the ARIMA (8, 2, 0) model as the optimal model. The diagnostic tests further indicate that the presented model is stable and its residuals are stationary in levels. The results of the study reveal that the numbers of neonatal deaths per year are expected to decline sharply in the next 25 years. In order to keep on reducing neonatal deaths in Zimbabwe, the study offered a four-fold policy prescription. by Dr. Smartson. P. Nyoni and Mr. Thabani NyonI 2020. Analyzing neonatal deaths in Zimbabwe using box-jenkins arima models. International Journal on Integrated Education. 3, 7 (Jul. 2020), 39-50. DOI:https://doi.org/10.31149/ijie.v3i7.462. https://journals.researchparks.org/index.php/IJIE/article/view/462/441 https://journals.researchparks.org/index.php/IJIE/article/view/462
Elderly population is increasing due to demographic shift in favor of geriatric population. This age group is susceptible for many health problems. So this cross-sectional study was carried out from September 2009 to August 2010 on 1620 elderly residing in Municipal corporation area of Jaipur city with the aim to study episodes of acute illness and its associating factors. Study population consist of 1620 elderly with M:F ratio 0.95. Mean age of elderly was 66.08 years with slight female predominance i.e. 1048 females for 1000 males in Jaipur city. It can be concluded from this study that 44.37% of elderly had one or more episodes of acute illness in last one month. These numbers of episodes of acute illness in last one month was found more in males and in older age groups.
Analyzing neonatal deaths in Zimbabwe using box-jenkins arima modelsSubmissionResearchpa
Using annual time series data on neonatal deaths in Zimbabwe from 1966 to 2018, we model and forecast number of neonatal deaths over the next 25 years using the Box – Jenkins ARIMA technique. Diagnostic tests such as the ADF tests show that Neonatal Deaths (ND) series is I (2). Based on the AIC, the study presents the ARIMA (8, 2, 0) model as the optimal model. The diagnostic tests further indicate that the presented model is stable and its residuals are stationary in levels. The results of the study reveal that the numbers of neonatal deaths per year are expected to decline sharply in the next 25 years. In order to keep on reducing neonatal deaths in Zimbabwe, the study offered a four-fold policy prescription. by Dr. Smartson. P. Nyoni and Mr. Thabani NyonI 2020. Analyzing neonatal deaths in Zimbabwe using box-jenkins arima models. International Journal on Integrated Education. 3, 7 (Jul. 2020), 39-50. DOI:https://doi.org/10.31149/ijie.v3i7.462. https://journals.researchparks.org/index.php/IJIE/article/view/462/441 https://journals.researchparks.org/index.php/IJIE/article/view/462
Elderly population is increasing due to demographic shift in favor of geriatric population. This age group is susceptible for many health problems. So this cross-sectional study was carried out from September 2009 to August 2010 on 1620 elderly residing in Municipal corporation area of Jaipur city with the aim to study episodes of acute illness and its associating factors. Study population consist of 1620 elderly with M:F ratio 0.95. Mean age of elderly was 66.08 years with slight female predominance i.e. 1048 females for 1000 males in Jaipur city. It can be concluded from this study that 44.37% of elderly had one or more episodes of acute illness in last one month. These numbers of episodes of acute illness in last one month was found more in males and in older age groups.
Epidemiological Determinants affecting Caesarean Section in a Rural Block of ...iosrjce
IOSR Journal of Dental and Medical Sciences is one of the speciality Journal in Dental Science and Medical Science published by International Organization of Scientific Research (IOSR). The Journal publishes papers of the highest scientific merit and widest possible scope work in all areas related to medical and dental science. The Journal welcome review articles, leading medical and clinical research articles, technical notes, case reports and others.
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By Shuangxiao Qu, CHINA
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Side Event: How Japan’s know-how can help address food and nutrition challenges in the developing world
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Epidemiological Determinants affecting Caesarean Section in a Rural Block of ...iosrjce
IOSR Journal of Dental and Medical Sciences is one of the speciality Journal in Dental Science and Medical Science published by International Organization of Scientific Research (IOSR). The Journal publishes papers of the highest scientific merit and widest possible scope work in all areas related to medical and dental science. The Journal welcome review articles, leading medical and clinical research articles, technical notes, case reports and others.
A Long-term Evaluation of Interventions on Preventing Preschool Children’s Injury in a Safe Community in Shanghai from 2009 to 2014
By Shuangxiao Qu, CHINA
Cost of hospitalization for foodborne diseasesILRI
Presented by Teng Srey, Communicable Diseases Control Department, Ministry of Health, Cambodia at the Safe Food, Fair Food for Cambodia project final workshop, Phnom Penh, Cambodia, 21-22 June 2021
Gloria Folson and Futoshi Yamauchi
Side Event: How Japan’s know-how can help address food and nutrition challenges in the developing world
Tokyo Nutrition for Growth (N4G) Summit 2021
NOV 30, 2021
9. Table 1: Socio-demographics and place of delivery *8,767 kip is equal to US$ 1 (8) (n=311) % Age (year) Mean (SD) 13-24 25-48 25.7 (6.1) 150 161 48.2 52.8 Ethnicity Lowland Lao (Lao Lum) Midland Lao (Lao Thung) Highland Lao (Lao Sung) 232 79 0 74.6 25.4 0.0 Household income (Kip)*/ month Mean (SD) >300,001 <300,000 1.7 (0.5) 214 97 68.8 31.2 Education of mothers Illiterate Educated 68 243 21.9 78.1 Education of fathers Illiterate Educated 50 261 16.1 83.9 Occupation of fathers Farmer Government official Daily wage worker 177 50 84 56.9 16.1 27.0 Number of children Mean (SD) ≤ 2 >2 2.6 (1.9) 190 121 61.1 38.9 Time from house go to health facility ( in minutes) by using personal transportation Mean (SD) ≤ 45 >45 44.2 (45.9) 189 113 63.7 36.6 Place of delivery Hospital Home 159 152 51.1 48.9
10. Table 2: History of reproductive health and antenatal care (9) (n=311) % Parity Mean (SD) ≤ 2 >2 193 118 2.6 (2.0) 62.1 37.9 Gravida Mean (SD) ≤ 2 >2 179 132 2.8 (2.1) 57.6 42.4 Abortion Mean (SD) Never had abortion Had abortion 259 52 0.2 (0.5) 83.3 16.7 Attend antenatal clinic during the last child Yes No 207 104 66.6 33.4 Times and attended ANC during pregnancy (207) Mean (SD) ≤ 4 > 4 128 79 4.3 (1.9) 61.8 38.2 Antenatal card or booklet Yes No 148 59 71.4 28.6
11. a 8,767 kip is equal to US$1 Table 3: Factors influencing place of delivery (10) Place of delivery No (%) n=311 Hospital Home OR (95% CI) P-value Ethnicity Midland Lao Lowland Lao 79 (25.4) 232 (74.6) 22 (27.8) 137 (59.1) 57 (72.2) 95 (40.9) 1 3.7 (2.1-6.5) 0.000*** Household income (Kip) a /month <300,000 >300,001 97 (31.2) 214 (68.8) 35 (36.1) 124 (57.9) 62 (63.9) 90 (42.1) 1 2.4 (1.5-4.0) 0.000*** Education of mothers No education Education 68 (21.9) 243 (78.1) 15 (22.1) 144 (59.3) 53 (77.9) 99 (40.7) 1 5.1 (2.7-9.6) 0.000*** Education of fathers No education Education 50 (16.1) 261 (83.9) 12 (24.0) 147 (56.3) 38 (76.0) 114 (43.7) 1 4.1 (2.0-8.2) 0.000*** Occupation of fathers Farmer Government official Daily wage worker 177 (56.9) 50 (16.1) 84 (27.0) 66 (37.3) 33 (66.0) 60 (71.4) 111 (62.7) 17 (34.0) 24 (28.6) 1 4.2 (2.4-7.4) 1.4 (0.6-2.7) 1 0.000*** 0.001***
12. Table 4: Factors influencing place of delivery (11) Place of delivery No (%) n=311 Hospital Home OR (95%CI) p-value Gravida (times) > 2 ≤ 2 132 (42.4) 179 (57.6) 52 (39.4) 107 (59.8) 80 (60.6) 72 (40.2) 1 2.3 (1.4-3.6) 0.000*** Number of children >2 ≤ 2 121 (38.9) 190(61.1) 47 (29.6) 112 (70.4) 74 (48.7) 78 (51.3) 1 2.3 (1.4-3.6) 0.001*** Time from house go to the facility (in minute) >45 ≤ 45 113 (36.3) 198 (63.7) 36 (31.9) 123 (62.1) 77 (68.1) 75 (37.9) 1 3.5 (2.2-5.7) 0.001*** Attend ANC during the last child No Yes 104 (33.4) 207(66.6) 22 (21.2) 137 (66.2) 82 (78.8) 70 (33.8) 1 7.3 (4.2-12.7) 0.000*** Times and attend ANC during pregnancy (n=207) ≤ 4 > 4 128 (41.2) 79 (25.4) 78 (60.9) 59 (74.7) 50 (39.1) 20 (25.3) 1 1.9 (1.0-3.5) 0.043* Process an antenatal card or booklet No Yes 59 (28.5) 148 (71.4) 30 (50.8) 107 (72.3) 29 (49.2) 41 (27.7) 1 2.5 (1.4-4.7) 0.003**
13. OR= Odd ratio; AOR= Adjusted odds ratio by Binary Logistic Regression (12) Table 5: Regression analysis: Factors influencing place of delivery Place of delivery No (%) n=311 Hospital Home AOR (95% CI) P-value Ethnicity Midland Lao Lowland Lao 79 (25.4) 232 (74.6) 22 (27.8) 137 (59.1) 57 (72.2) 95 (40.9) 1 1.3 (0.4-3.7) 0.632 Household income (Kip/month) <300,000 >300,001 97 (31.2) 214 (68.8) 35 (36.1) 124 (57.9) 62 (63.9) 90 (42.1) 1 1.0 (0.4-2.3) 0.952 Education of mothers No education Education 68 (21.9) 243 (78.1) 15 (22.1) 144 (59.3) 53 (77.9) 99 (40.7) 1 0.5 (0.1-1.8) 0.315 Education of fathers No education Education 50 (16.1) 261 (83.9) 12 (24.0) 147 (56.3) 38 (76.0) 114 (43.7) 1 0.9 (0.2-3.8) 0.883 Occupation of fathers Farmer Government official Daily wage worker 177 (56.9) 50 (16.1) 84 (27.0) 66 (37.3) 33 (66.0) 60 (71.4) 111 (62.7) 17 (34.0) 24 (28.6) 1 8.3 (2.9-23.5) 5.2 (1.7-16.2) 0.000*** 0.004** Gravida (times) >2 ≤ 2 132 (42.4) 179 (57.6) 52 (39.4) 107 (59.8) 80 (60.6) 72 (40.2) 1 0.5 (0.3-1.1) 0.092 Times and attended ANC (n=207) ≤ 4 >4 128 (41.2) 79 (25.4) 78 (60.9) 59 (74.7) 50 (39.1) 20 (25.3) 1 2.3 (1.1-4.8) 0.026* Process an antenatal Card or booklet No Yes 59 (28.5) 148 (71.4) 107 (72.3) 30 (50.8) 41 (27.7) 29 (49.2) 1 0.5 (0.2-1.1) 0.118 Time from home go to the facility (in minute) > 45 ≤ 45 113 (36.3) 198 (63.7) 36 (31.9) 123 (62.1) 77 (68.1) 75 (37.9) 1 2.3 (1.0-5.1) 0.042*
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