Damalita, Annisa Fitriana
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The Effectiveness of Health Management-Assisted Technology on Glycated Hemoglobin Levels in Patients with Type 2 Diabetes Mellitus: Meta-Analysis Novianto, Fajar; Amalin, Atika Mima; Handayani, Anggun Fitri; Ambarsari, Anggraini; Ode, Diana; Azizah, Alfi Makrifatul; Pamilih, Ayu Trisni; Damalita, Annisa Fitriana; Firda, Fathiyyatu Assa'diy; Mubarok, Ahmad Syauqi
Journal of Health Policy and Management Vol. 6 No. 2 (2021)
Publisher : Masters Program in Public Health, Universitas Sebelas Maret, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (34.166 KB)

Abstract

Background: Given the number of patients failing to achieve control of Diabetes Mellitus (DM), it causes an increase in the incidence of DM complications. Along with the rapid deve­lopment of technology in this era, this study aimed to prove the effectiveness of technology-based health management compared to usual treatment for levels glycated hemoglobin (HbA1c) in type 2 diabetes mellitus patients.Subjects and Method: This was a meta-ana­lysis using a randomized controlled trial. Arti­cles were obtained from PubMed, Google Scholar, and ResearchGate databases. The arti­cles used in this study were those published from 2012-2021. The search article was carried out by considering the eligibility of the criteria determined using the PICO model. Population: type 2 DM patients (HbA1c>7%), Intervention: health management-assisted technology, Com­parison: usual care Outcome: HbA1c levels. There were 10 articles used with a sample size of 1693 people who were divided into two groups (845 people in the health management-assisted technology group and 848 people in the group usual care). Articles were analyzed using Review Manager 5.3 Appli­cation to determine the Standard Mean Diffe­rence (SMD) and heterogeneity of the study sample.Results: From 10 articles that were processed using RevMan 5.3, significant results were obtained, this is indicated by the overall effect (diamond) which does not touch the vertical line H0 (d= 0) and can also be seen from the 95% CI range of -0.62 to -0.13 which shows significant because it does not pass the number 0 (SMD= -0.37; 95% CI= -0.62 to -0.13; p= 0.003). The heterogeneity of the research data shows I2 = 82% so that the distribution of the data is very heterogeneous (random effects model).Conclusion: Using technology to help health management of patients with type 2 diabetes mellitus can reduce HbA1c levels compared to usual care.Keywords: Health management, technology, diabetes mellitus, HbA1cCorrespondence: Fajar Novianto. Center for Research and Deve­lopment of Medicinal Plants and Traditional Medicine, National Institute of Health of Health, Jl. Raya Lawu No. 11 Karanganyar, Central Java. Email: dr.fajarnovianto@gmail.­com.Journal of Health Policy and Management (2021), 06(02): 81-93https://doi.org/10.26911/thejhpm.2021.06.02.01 
Excess Weight Gain in Pregnant Women and Prematurity: A Meta-Analysis Damalita, Annisa Fitriana; Dewi, Yulia Lanti Retno; Budihastuti, Uki Retno
Journal of Maternal and Child Health Vol. 7 No. 2 (2022)
Publisher : Masters Program in Public Health, Universitas Sebelas Maret, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (33.949 KB) | DOI: 10.26911/thejmch.2022.07.02.05

Abstract

Background: Premature birth as a cause of morbidity and mortality in neonates. Excessive weight gain in pregnant women is considered a risk factor for adverse pregnancy outcomes including preterm birth. This study aims to analyze the effect of excess weight gain in pregnant women on premature birth. Subjects and Method: This research is a systematic review and meta-analysis. Article searches were conducted using electronic databases such as Google Scholar, PubMed, Science Direct and Springerlink. The articles used are articles published from 2011-2021. The keywords to search for articles were: “gestational weight gain” AND “pregnancy” AND (“preterm birth” OR “premature birth”) AND “cohort study” AND “adjusted odds ratio”. The inclusion criteria used were full text articles in English with a cohort study design, multivariate analysis with Adjusted Odds Ratios (aOR), research subjects were pregnant women, intervention was excessive weight gain, compa­rison was normal weight gain (adequate). , the study outcome was preterm delivery (<37 weeks). The article search results are listed in the PRISMA diagram and analyzed using the Review Manager 5.3 application. Results: A total of 10 cohort study articles from China, Indonesia, Canada, Korea, Mexico, Puerto Rico, Saudi Arabia, and Taiwan were selected for systematic review and meta-analysis. The results showed that excess weight gain in pregnant women increased the risk of preterm birth and was statistically significant (aOR= 1.23; 95% CI= 1.01 to 1.48; p= 0.030). Conclusion: Excess weight gain in pregnant women increases the risk of premature birth.