Breastfeeding in Infancy and Blood Pressure in Later Life: Systematic Review and Meta-Analysis

2005 ◽  
Vol 161 (1) ◽  
pp. 15-26 ◽  
Author(s):  
R. M. Martin
Keyword(s):  
Systematic Review ◽  
Blood Pressure ◽  
Meta Analysis ◽  
Later Life

scholarly journals The associations of high birth weight with blood pressure and hypertension in later life: a systematic review and meta-analysis

2013 ◽  
Vol 36 (8) ◽  
pp. 725-735 ◽  
Author(s):  
Yong Zhang ◽  
Hui Li ◽  
Shang-jing Liu ◽  
Guang-jian Fu ◽  
Yong Zhao ◽  
...  
Keyword(s):  
Systematic Review ◽  
Blood Pressure ◽  
Birth Weight ◽  
Meta Analysis ◽  
Later Life ◽  
High Birth Weight

Cardiovascular risk factors in those born preterm – systematic review and meta-analysis

2020 ◽  
pp. 1-16
Author(s):  
Prabha H. Andraweera ◽  
Bradley Condon ◽  
Gemma Collett ◽  
Stefania Gentilcore ◽  
Zohra S. Lassi
Keyword(s):  
Risk Factors ◽  
Systematic Review ◽  
Blood Pressure ◽  
Early Adolescence ◽  
Gestational Age ◽  
Meta Analysis ◽  
Later Life ◽  
Cvd Risk Factors ◽  
Cvd Risk ◽  
Subgroup Analyses

Abstract Emerging evidence demonstrates a link between preterm birth (PTB) and later life cardiovascular disease (CVD). We conducted a systematic review and meta-analysis to compare conventional CVD risk factors between those born preterm and at term. PubMed, CINAHL, SCOPUS, and EMBASE databases were searched. The review protocol is registered in PROSPERO (CRD42018095005). CVD risk factors including systolic blood pressure (SBP), diastolic blood pressure (DBP), body mass index, lipid profile, blood glucose, and fasting insulin among those born preterm (<37 weeks’ gestation) were compared with those born at term (≥37 weeks’ gestation). Subgroup analyses based on gender, age, gestational at birth (<32 weeks’ gestation and <28 weeks’ gestation), and PTB associated with small for gestational age or average for gestational age were also performed. Fifty-six studies provided data on 308,987 individuals. Being born preterm was associated with 3.26 mmHg (95% confidence interval [CI] 2.08 to 4.44) higher mean SBP and 1.32 mmHg (95% CI: 0.61 to 2.04) higher mean DBP compared to being born at term. Subgroup analyses demonstrated that SBP was higher among (a) preterm compared to term groups from early adolescence until adulthood; (b) females born preterm but not among males born preterm compared to term controls; and (c) those born at <32 weeks or <28 weeks compared to term. Our meta-analyses demonstrate higher SBP and DBP among those born preterm compared to term. The difference in SBP is evident from early adolescence until adulthood.

Effects of wearable technology on patients with diabetes: A systematic review and meta-analysis (Preprint)

2020 ◽  
Author(s):  
Dongjun Wu ◽  
Nicholas Buys ◽  
Guandong Xu ◽  
Jing Sun
Keyword(s):  
Systematic Review ◽  
Blood Pressure ◽  
Relapse Prevention ◽  
Diabetes Management ◽  
Meta Analysis ◽  
Intervention Group ◽  
Wearable Technologies ◽  
Patients With Diabetes ◽  
Hba1c Levels

UNSTRUCTURED Aims: This systematic review and meta-analysis aimed to evaluate the effects of wearable technologies on HbA1c, blood pressure, body mass index (BMI), and fastening blood glucose (FBG) in patients with diabetes. Methods: We searched PubMed, Scopus, Embase, the Cochrane database, and the Chinese CNKI database from last 15 years until August 2021. The quality of the 16 included studies was assessed using the PEDro scale, and random effect models were used to estimate outcomes, with I2 used for heterogeneity testing. Results: A significant reduction in HbA1c (-0.475% [95% CI -0.692 to -0.257, P<0.001]) was found following telemonitoring. However, the results of the meta-analysis did not show significant changes in blood pressure, BMI, and glucose, in the intervention group (P>0.05), although the effect size for systolic blood pressure (0.389) and diastolic blood pressure may indicate a significant effect. Subgroup analysis revealed statistically significant effects of wearable technologies on HbA1c when supported by dietetic interventions (P<0.001), medication monitoring (P<0.001), and relapse prevention (P<0.001). Online messages and telephone interventions significantly affected HbA1c levels (P<0.001). Trials with additional online face-to-face interventions showed greater reductions in HbA1c levels. Remote interventions including dietetic advice (P<0.001), medication (P<0.001), and relapse prevention (P<0.001) during telemonitoring showed a significant effect on HbA1c, particularly in patients attending ten or more intervention sessions (P<0.001). Conclusion: Wearable technologies can improve diabetes management by simplifying self-monitoring, allowing patients to upload their live measurement results frequently and thereby improving the quality of telemedicine. Wearable technologies also facilitate remote medication management, dietetic interventions, and relapse prevention.

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