Iris Publishers- Open access Journal of Yoga, Physical Therapy and Rehabilitation | Yoga and Its Effect on Glycemic Control and Oxidative Stress in People with Type 2 Diabetes in A Randomized Trial: Systematic Review and Meta- Analysis

 

authored by Rashmi Shiju*

Abstract

Background:b> Yoga is being evaluated for its potential beneficial effect on people with type 2 diabetes(T2DM) as an adjuvant therapy by researchers around the globe. Few systematic reviews and meta-analyses previously performed have indicated mixed effect of yoga. In this review we aimed to evaluate further whether yoga has an impact on metabolic parameters in people with T2DM.

Methods: Systematic review and meta-analysis of randomized controlled trials (RCTs) comparing the practice of any type of yoga, asanas or pranayamas vs. standard care in adults with T2DM. The primary outcome was change in fasting plasma glucose and glycated haemoglobin (HbA1c). The secondary outcome was serum lipid profile and oxidative stress. The electronic databases such as, Cochrane CENTRAL, Scopus, Medline, Embase and CINAHL were searched from the year 1990 to August 2015 to find out the studies done on yoga as per the eligibility criteria. Meta-analysis was conducted using the inverse variance method of analysis with random-effect models with checks of heterogeneity using the I2 test.

Results:b> From a total of 788 articles screened, nine RCTs were included involving 788 participants. In five trials yoga group had a significant reduction in HbA1c ( mean difference(MD) -0.51% , 95%CI -0.57 to -0.44, P =0.006, fasting plasma glucose (mean difference(MD) as -25.2 ,95 % CI -25.31 to -25.2mg/dl, P <0.00001, and serum LDL (mean difference(MD) -26.8mg/dl , 95% CI -42.1 to -11.5 mg/dl, p =0.0006), HDL (mean difference(MD) 6.8 mg/dl (95% CI 4.8 to 8.7, p <0.00001), total cholesterol (mean difference(MD) -33.3 mg/dl (95% CI -35.8 to -30.8, p <0.00001), triglycerides (mean difference(MD) 39.4 mg/dl( 95% CI -50.0 to -28.8, p <0.00001), cortisol (mean difference(MD) -5.5 μg /l ( 95% CI -7.1 to -4.0, p <0.00001), malondialdehyde (mean difference(MD) 16.6 nanomol/dl (95%CI -22.0 to -11.2, p<0.00001).

Conclusion:The results from the available trials indicate that yoga may be a potentially beneficial intervention for improving glycemic control, lipid profile and indicators of oxidative stress in people with T2DM. Further studies are required to corroborate yoga’s effect on other outcomes such as psychosocial profiles.

Keywords: Yoga; Systematic review; Meta-analysis; T2DM; Stress

Abbreviations: BMI: Body Mass Index; CAM: Complementary and Alternative Medicine; FBG: Fasting Blood Glucose; HDL: High Density Lipoprotein; LDL: Low Density Lipoprotein; MENA: Middle East and North Africa; MDA: Malondialdehyde; RCT: Randomized Controlled Trials; T2DM: Type 2 Diabetes Mellitus

Introduction

Diabetes mellitus is a progressive disease affecting large numbers of the people globally. According to the International Diabetes Federation (IDF) Atlas 9th edition, globally 463 million adults are affected with diabetes, and is estimated to rise to 700 million by 2045 without intervention [1]. Managing diabetes can be challenging and requires a multifaceted approach involving lifestyle changes and pharmacological intervention. People with diabetes do not infrequently use complementary and alternative medicine (CAM) with estimates ranging from 17% and 73% and involved lifestyle modification, yoga, qi gong, massage and herbs [2]. Yoga is the most common alternative holistic approach adopted by adults in many countries. According to national survey in the US, yoga use increased from 9.5% to 14.3% between 2012 and 2017 [3]. Yoga originated from India has been a traditional contemplative practice since time immemorial for the therapeutic intervention and health maintenance [4]. Yoga may be beneficial in almost all the ailments. [5-11]. It may have positive impact on endocrine system, nervous system, circulatory system, metabolism, psychology and cognition [12]. Yoga has also been shown to influence hormone regulation and studies suggest that regular practice of yoga can reduce cortisol and sympathetic activation while increasing serotonin, gaba aminobutyric acid (GABA) and oxytocin levels. [5,7,13,14]. This may in turn reduce anxiety, depression, perceived stress and improving sleep quality and male sexual functioning [15]. Yoga may have beneficial effect in people with T2DM, in terms of modifiable risk factors and metabolic syndrome [16-24]. The systematic review by Innes et al. [25] measured the influence of yoga-based programs on risk profiles in adults with type 2 diabetes. The review indicated that yoga may help in reducing the risk in adults with T2DM. The author also indicated that there are limited reviews to show the promising effect of yoga on psychological profiles in adults with diabetes. The systematic analysis by AlJasir et al. [26] showed that short-term benefit can be achieved by T2DM patient with the practice of yoga were however inconclusive and non-significant for the long-term outcomes of yoga practice. A systematic review and meta-analysis by Harpreet et al. [27] indicated that yoga participants successfully improved their glycated haemoglobin (HbA1c) as compared with the control people. Yoga also had significant improvements in lipid profiles, blood pressure, body mass index (BMI), waist/hip ratio and cortisol levels. A systematic review by Divya et al. [28] on effects of yoga on physical health and health related quality of life concluded that there were significant improvements in physical health and quality of life. In another systematic review and meta-analysis by Ramamoorthi et al. [29] reported significant improvements of yoga on glycaemic control, serum lipid profiles and other parameters in prediabetic populations. The present systematic review and meta-analysis will focus on patients with T2DM conducted through randomized controlled trials (RCTs) with yoga intervention such as Sudarshan kriya yoga, asanas, pranayamas and hatha yoga with duration at least four weeks. This review will give more focus to specific type of yoga intervention and its effect on glycaemic control, serum lipids and stress biomarkers. To our knowledge, this will be the first meta-analysis on oxidative stress markers.

Methods

Study selection criteria and PICOS

Cochrane review guidance was followed in conducting the systematic review [30].

Population for this systematic review was defined as:b> Adult patients aged 18 years or greater having T2DM for more than one year confirmed by a physician based on the guidelines for diagnosis of T2DM. Exclusion criteria included ;studies on infants and children, gestational diabetes, pregnant women, non-diabetic patients, type 1 diabetic patients, complication of diabetes and studies with herbal drug intervention.

The intervention included:b> any type of yoga (hatha, bikram, iyengar, sudarshan kriya yoga, pranayama, astanga, asanas), and minimum four week of duration of yoga. Comparison was control groups receiving standard treatment of care.

Outcomes:b> The primary outcomes were changes in fasting plasma glucose (FPG) and HbA1c. Secondary outcomes included changes in serum high density lipoprotein (HDl), low density lipoprotein (LDL) and total cholesterol, BMI, stress biomarkers and quality of life.

Study design: Only randomized clinical trial was selected for inclusion.

Database search strategy

The search strategy was implemented in ; Pubmed, Embase, Scopus, Cochrane, Medline, CINAHL Plus were searched using the key words “Yoga OR asana* OR Bikram OR Iyengar OR pranayama OR hatha OR ashtanga OR Sudarshan Kriya Yoga AND diabetes OR diabet* OR non-insulin dependent OR diabetes mellitus OR T2 DM OR Type II diabetes mellitus”. Apart from the database, the bibliography of the articles selected were also searched. Limits applied were for age greater than 18, articles published from 1990 to 2015, English language. Moreover, an internet searching was done through Google Scholar and also clinical trial.gov website for randomized controlled trials. Literature on systematic reviews and metaanalysis of yoga and diabetes published until 2019 were included.

The results obtained from searching each electronic database using the above-mentioned key words were saved in the computer and online End Note in order to keep a track of all searches which included number of hits, database name, time period searched, limitations applied. The results of search from each database also exported to Excel to sort out duplication and based on the eligibility criteria of systematic review.

Data extraction and screening

All the six databases were searched with key words mentioned and then screened for duplicates. The title and the abstract were screened for relevance. Full text articles were then scanned according to the eligibility criteria. The details of the number of articles excluded with reason are depicted in the flow chart (Figure 1). The results obtained from the database were extracted using the extraction form (Appendix I).

Quality assessment

A short scale of seven criteria customized to yoga studies were used to assess the quality of the included studies established by the Cochrane collaboration [30].

Following questions were included in the quality checklist:

• Whether participants were randomized to groups randomly or through software or independantly.

• Were the baseline characteristics of the study groups properly assessed or there was any correction done to balance.

• Whether the study has calculated sample size through power analysis.

• Whether the study has considered loss of follow up, attrition.

• Whether the study had properly handled the missing data by using intention-to-treat analysis,

• Study integrity; was the study followed as planned.

• Whether the study was conducted with certified progessional yoga instructor or not. Each criterion was rated as 0(study does not meet criteria) or 1 (study met criteria).

When a criterion meets six or seven points then the study is assessed as high quality and when four or five criteria were mint then assessed as low and very low when zero or one criteria were met. Data collected were assessed for the quality of studies based on the quality criteria. If a trial meets first three criteria, then it is categorized as low risk of bias. (Table 1).

Data Analysis

Meta-analysis of the eligible studies was conducted using statistical RevMan software measuring the mean differences using the generic inverse variance method of analysis. Meta-analysis was performed for HbA1c reported as a percentage and FPG reported as mg/dl. When the units for reported values of FPG in the articles differed, the units were Mmol/L they were converted into mg/ dl by multiplying the mmol/L value by 18. The generic inversevariance method of analysis was used to pool all mean differences for continuous data and for combining intervention effect estimates reporting results from fixed-effect and random-effects models. Statistical heterogeneity was assessed using the I-squared statistic. Mean difference was calculated for the yoga group and the control group. Standard deviation was also extracted from the reviewed articles. Standard errors were converted to standard deviation were appropriate.

Results

Characteristics of the studies

1201 titles and abstract were identified and, nine trials met the eligibility criteria that included 788 participants. Characteristics of included trials depicted in Table 2. Four trials (44.4%) reported HbA1C as primary outcome. Seven trials reported FPG an outcome but only one trial (11.1%) reported serum cholesterol, LDL, HDL triglycerides as an outcome. Two trials (22.2%) reported quality of life as an outcome. Most trials (55.6%) practiced three months of yoga as an intervention whilst this ranged from eight weeks to nine months in the remaining trials. The duration of each yoga class also varied between the trials from one and two hours.

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Iris Publishers- Open access Journal of Yoga, Physical Therapy and Rehabilitation | Meditation for Health, Happiness, and Meaning-Making

 

authored by Ani Kalayjian*

Short Communication

“Meditation” in its modern sense refers to the yogic meditation that originated in India. In the late 19th century, theosophists adopted the word “meditation” to refer to various spiritual practices drawn from Eastern religions such as Hinduism, Buddhism, and Sikhism. Thus, the English word meditation does not exclusively translate into any single term or concept. Meditation has been helpful to reduce stress, reduce symptoms of Post-traumatic Stress Disorder (PTSD), as well as anxiety and depression. Meditation is an ancient practice that has been in existence for centuries, but only in the last two decades has scientific research supported its usefulness and effectiveness. This article will provide an overview of the benefits of meditation for those traumatized, as well as share its general benefits.

Through breath, meditation links our body with our heart and mind, providing emotional self-mastery and mindfulness. Mindfulness helps us practice self-love. Love is the center and the pendulum of duality swinging back and forth from positive/ negative, masculine/feminine, light/darkness, yin/yang… Remember, throughout the course of existence, we have swung farther and farther into the realm of polarities.

All disciplined religions incorporate some form of meditation. Meditative quiescence is said to have a quality of healing and of enhancing creativity. The Prophet Muhammad spent sustained periods in contemplation and meditation. It was during one such period that he began to receive the revelations of the Qur’an.

There is an abundance of research studies indicating the effectiveness and usefulness of meditation for relaxation, stress reduction, cognitive decline, reduction of anxiety, and PTSD related disorders. A recent research study conducted by [1] looked at how meditation impacted adults ages 55-90. Results showed that 8-week meditation significantly improved retrieving memories, decrease atrophy in the hippocampus, and decrease anxiety and stress.

Seventy years ago, the United Nations was founded on the principles of dignity, peace, justice and cooperation. UN’s Secretary- General Dag Hammarskjold stressed the relevance of these values stating: “Unless there is a spiritual renaissance, the world will know no peace.” There is a special designated room for meditation at the United Nations, and Mr. Hammarskjold, Delegates, Ambassadors and Non-Governmental Organization Representatives frequent the meditation room before important meetings.

Meditate for Peace by [2] indicated that 7000 people got together and meditated-- and global terrorism went down by 72 percent. Similarly, dramatic decreases were seen in war, fatalities and violent crime. Of course, there are always skeptics who want to argue about whether or not this is “real,” the fact is that those who meditate have reported improvements in their lives.

This positive impact of meditation has been documented in numerous peer-reviewed publications, including the Journal of Offender Rehabilitation. According to several research studies, mindfulness meditation -- a practice that encourages focusing attention on the present moment -- can ease emotional stress. And evidence is mounting that mindfulness also may have key benefits for physical health from lowering blood pressure to helping curb addiction. A new study conducted by researchers working in Wisconsin, Spain, and France shows that mindfulness can even affect our genes. Specifically, the study shows that mindfulness can limit the “expression” of genes associated with inflammation.

A recent National Institutes of Health (NIH) grant proved meditation’s effectiveness in generating alpha brain waves, which are relaxing and conducive to the sleep state. When our mind is tranquil and serene, our body then follows the mind’s lead and relaxes, thereby releasing fears and creating a metabolic state that is tranquil and pure consciousness. This state is not only free of fear and pessimism, it’s also a more optimistic state that heightens problem-solving skills and promotes an expanded view of the world in which we live and our role in it. A review of scientific studies identified relaxation, concentration, an altered state of awareness while suspending logical thought, and the maintenance of a selfobserving attitude as the behavioral components of meditation; this mode is accompanied by a host of biochemical and physical changes in the body that alter metabolism and decrease heart rate, respiration, blood pressure, and brain chemistry. Meditation has been used in clinical settings as a method of stress and pain reduction [3]. Meditation has also been used to reduce stress.

According to the 2012 National Health Interview Survey (NHIS), which included a comprehensive survey on the use of complementary health approaches by Americans, 17.7 percent of American adults had used a dietary supplement other than vitamins and minerals in the past year. These products were the most popular complementary health approach in the survey. Approximately 8% used meditation.

Meditation is used widely for traumatized individuals. ATOP Meaningfulworld Humanitarian Teams have used meditation in over 45 countries around the world with great success, meditators stating: “I came in with a headache and after the meditation my headache is gone,” “I had a pressure in my chest, feeling short of breath from my trauma, now after the meditation I feel the pressure is released,” exemplified some of the responses. Research conducted with veterans’ to address the levels of PTSD. Interventions included yoga [4], meditation and mindfulness based cognitive therapy [5]. Results indicated a statistically significant reduction of stress and anxiety (Stoller et al. 2012), daytime dysfunction and Hyperarousal (Staples et al, 2013), decrease of depression [6].

Meditation has been integral in all deliberations in the Association for Trauma Outreach & Prevention (ATOP) at Meaningfulworld. Meditation is utilized at the beginning and end of all our monthly training and empowerment programs as well as at all of our humanitarian global outreach projects in more than 45 countries. Although most religions incorporate some form of meditation, at ATOP Meaningfulworld we focus on the healing and integrative aspects of meditation and its mind-body-eco-spirit effect, and therefore, it is not based on any religious foundation.

ATOP integrates meditation in the final stage of the sevenstep healing framework, in the 7-Step Integrative Healing Model (Biopsychosocial and Eco-Spiritual Model). At ATOP Meaningfulworld we use meditation to reduce stress in the central nervous system (CNS) and to strengthen the immune system. Our mind wanders and moves inward and outward like a pendulum: When we are able to relax the CNS, we are relaxing our mind. Of course, relaxation is challenging for many individuals, since we live in a culture that over-identifies with production and volume of doing, rather than being mindful and conscious.

Breath is the foundation and center of any meditation. This is very essential for traumatized people, when they experience shallow chest breathing, and shortness of breath. Based on the fight-freeze-flight protection system, our past traumatic history may have inhibited complete expression of our breath. When we start breathing deeply, diaphragmatically, or through our belly, we bring the breath below the chest and lungs, we are able to heal the remaining suffering of old trauma, we are empowered – we establish a healthy distance between the traumatic memory and its effect on our emotions and our physical body [7-9].

Meditation also helps us ignite the fire within, activating our passion and love for humanity and Mother Earth. In order to create fire, we need two things: oxygen and fuel. Oxygen intake and distribution improves with meditation. Oxygen helps us expand our thoughts, concentrate on the important, and relax the joints, muscles, and all of our internal organs. The fuel is our passion and commitment to serve ourselves, our families, and the human family at large.

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Iris Publishers- Open access Journal of Gynecology & Womens Health | Validation and Clinical Use of the Non-Invasive Prenatal Test “Veracity”

 

authored by Valentina Gnetetskaya*

Introduction

Cell-free DNA has been utilized as a novel analyse for the development of non-invasive approaches to prenatal genetic testing using different methodologies [1-4]. Following the publication of a number of major research and clinical studies that revealed high accuracy to detect fetal aneuploidies, the use of noninvasive prenatal testing (NIPT) has been widely adopted in clinical practice. NIPT technologies provide significant improvements over conventional invasive prenatal testing and consequently, international bodies endorse NIPT as a routine screening option [5,6]. This has resulted in many institutions adopting NIPT within the scope of standard of care for autosomal and sex chromosomal aneuploidy detection (SCA). Mother and Child Clinic is a primary clinical centre certified by the Russian Ministry of Health and specialises in screening and diagnosing prenatal chromosomal aneuploidies. NIPT has been offered as a prenatal screening option in our clinic since (May 2017). This study aims to summarize the NIPT results and clinical performance of NIPT in the detection of trisomy 13,18,21 and SCAs using the Veracity non-invasive prenatal test in a cohort of 1382 samples among mixed-risk participants. In this report we convey a complete and robust clinical picture of the performance of Veracity under routine NIPT testing conditions and describe examples of unique clinical cases.

Materials and Methods

Patient cohort

This study included 1382 pregnant women between the ages 18-52 between 9-28 gestational weeks who visited Mother and Child Clinic from May 2017 until October 2018. Of these women 1325 were singleton pregnancies, 37 were twin pregnancies, 20 were vanished twin pregnancies and 169 conceived by in-vitro fertilization including 65 with the use of egg donation. Testing options included detection of trisomy 13,18,21 and optional detection of Sex chromosome aneuploidies (SCAs) and fetal sex. The panel offered for SCAs includes 45X, XXX, XXY, XXYY and XYY constitution. Women provided informed consent and maternal blood (20ml) collected in BCT StreckTubes (Streck, Inc, Omaha, NE) and was sent via courier for testing at the CAP accredited, CLIA certified laboratory of NIPD Genetics Public company Ltd. Sample demographics and outcome information was provided by the clinician and was compiled and reviewed to determine the characteristics of this patient population, as well as estimate the assay performance in our clinical setting.

Pre-test and post-test counselling

Patients were provided with a careful and detailed counselling regarding the benefits, risks and limitations of NIPT testing and provided the relevant consent form. NIPT analysis was conducted immediately for each sample and results were delivered using an electronic web-system within 7 days from sample receipt at NIPD Genetics (Nicosia, Cyprus). Women with a positive NIPT were provided the option of invasive testing. Post-test counselling was given to all participants on the basis of their test results.

Invasive testing

For invasive testing chorionic villus sampling (CVS) or amniocentesis was performed. Comparative genomic hybridization (aCGH) analysis was performed using a customized 60K CGX Chip v2 (Perkin Elmer by Agilent Technologies, Inc, Finland) and the data were analysed by a Genoglyphix aCGH software (PerkinElmer, Finland). Banding cytogenetic was performed using routine techniques on G-banded metaphase chromosomes of CVS or cultured amniotic fluid cells. Centromeric probes were used for FISH analysis. Karyotypes were interpreted according to ISCN.

Results

The median gestational age of this patient cohort (n=1382) was 12+3 weeks (Table 1), and the median maternal age was 34.4 (IQR 7.2) years. The median weight was 61 kg (IQR) (Table 1). The overall distributions of gestational weeks and maternal age are depicted in Figure 1 and Figure 2 respectively. In this cohort twin pregnancy samples represented 2.68% of all referrals (Table 1). In this cohort of 1382 cases, 246 cases requested detection of trisomy’s 13,18 and 21, 47 cases requested detection of trisomy’s 13,18,21 and fetal sex and 1089 cases requested the detection of trisomy’s 13,18,21, fetal sex and SCAs. The detection of SCAs was not an available option in twin pregnancies. In this cohort, 1325 cases were singleton pregnancies, 37 were twin pregnancies and 20 were vanished twin pregnancies. The cohort included 169 pregnancies conceived by in-vitro fertilization out of which 65 were performed with the use of egg donation. In the cohort of twin pregnancies, 23 were dichorionic and 14 were monochorionic. The median fetal fraction of reported samples was 10.2% (Figure 3). The fetal fraction increased as gestational weeks increased and exhibited a weak positive correlation (r= 0.19) (Figure 4).

In this sample cohort 99.5% of samples received a result (1375/1382). 1.9% of samples exhibited insufficient fetal fraction and a redraw was requested (27/1382). Specifically, 27 samples exhibited insufficient fetal fraction of which 22 samples were redrawn and sent to NIPD Genetics laboratories for retesting. Twenty out of 22 samples received a result following re-testing (91%). Overall, the median TAT time for reporting was 5 business days (Table 2).

The incidence of trisomy’s 13,18,21 was 1.6% and the incidence of SCAs was 0.5% (Table 3). In summary, 14 trisomy 21 cases were detected by Veracity NIPT. Follow-up information was available for 13/14 cases and all were confirmed (13/13). Four samples were reported as trisomy 18. Follow-up information was available for all samples and all were confirmed (4/4). One sample was reported as trisomy 13 and was confirmed with follow-up confirmatory testing (1/1). Two cases were reported as 45X with no available confirmatory testing information. One pregnancy loss was reported. One sample was reported as trisomy X and was confirmed with follow-up confirmatory testing (1/1). Two samples were reported as XXY and were confirmed with follow-up confirmatory testing (2/2). One case was reported as XYY with no available follow-up information.

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Iris Publishers- Open access Journal of Gynecology & Womens Health | Gestational Weight Gain and Large for Gestational Age Neonates in a Predominantly Hispanic Population Community Hospital

 

authored by Brittany N Robles*

Abstract

To analyse changes in Gestational Weight Gain (GWG) in different Body Mass Index (BMI) categories at start of pregnancy and neonatal birth weight outcomes in a predominantly Hispanic population living in a low-income environment.

We conducted a cross sectional study of women with singleton gestation who delivered at Wyckoff Heights Medical Centre from January 1st to December 31st, 2017. BMI was categorized at first prenatal visit as normal weight (BMI= 18.5-24.9), overweight (BMI= 25-29.9) and obese (BMI >30). BMI was collected at 16-20, 24-28, and 36-38 weeks of gestation. Stratified by BMI, appropriate GWG were 25–35 pounds for normal weight (27.9%), 15–25 pounds for overweight (34.5%), and 11–20 pounds for obese (24.5%). Neonatal birth weight was categorized by Duryea percentiles and gestational age in weeks. From 831 women, normal weight (n=269), overweight (n=263), and obese (n=299) women were found. GWG was categorized as: inadequate, appropriate, or excessive based on the Institute of Medicine guidelines. The prevalence of excessive GWG was 23.1% for normal weight, 35.8% for overweight, and 37.5% for obese women. The prevalence of inadequate GWG was 48.9% for normal weight, 31.0% for overweight, and 40.6% for obese women. A significant association was found between obese women and >90 percentile neonatal birth weight (OR:2.3, 95% CI: 1.15-4.97). Obese women were more likely to have excessive GWG which is associated with maternal and neonatal adverse outcomes such as NICU admissions, gestational diabetes, hypertensive disorders in pregnancy, delivery by caesarean section, large for gestational age, and shoulder dystocia.

Keywords: Gestational weight gain; Maternal obesity; Pregnancy weight gain; Pregnancy complications

Introduction

Gestational weight gain (GWG) is the amount of weight one gains throughout the pregnancy. This weight gain can be influenced by many factors including: age, socioeconomic factors, ethnicity, and maternal comorbidities, such as pre-gestational obesity [1-4]. Excessive gestational weight can lead to numerous adverse maternal and neonatal events such as the development of gestational diabetes, gestational hypertension, and preeclampsia, delivery via caesarean section, macrosomia, neonatal hypoglycaemia and shoulder dystocia. Due to the complications that can arise, recommendations were set forth by The Institute of Medicine (IOM) designating the appropriate amount of weight women should gain based on her pre-pregnancy BMI [5]. Although these guidelines were set forth just eleven years ago in 2009, they are debatable and do not take into consideration various important factors such as: weight gain among different ethnic groups, those of low socioeconomic status and/or those with a lower education level [5].

In the United States, more than 40% of pregnant women exceed the Institute of Medicines guidelines [6]. Excessive gestational weight gain varies by ethnicity and socioeconomic status with low income populations and non-whites being at the greatest risk [1].

Hispanics are the largest minority group living in the United States. They have the highest rates of inadequate and excessive GWG and are the group with the highest birth rate [6]. Hispanic women, specifically those from the Caribbean, experience the greatest health disparity. Furthermore, this subgroup of women has the highest prevalence of maternal comorbidities including obesity and type 2 diabetes mellitus and exhibit adverse outcomes associated with poor nutrition [6].

Women who are classified as severely obese at conception have an increased risk of infant mortality, stillbirth, congenital malformations, large for gestation infants, hypertensive disorders of pregnancy, gestational diabetes, prolonged second stage of delivery, delivery via caesarean section and maternal mortality than non-obese women [7].

In our predominantly Hispanic population, we sought to determine whether the pattern of maternal gestational weight gain was associated with clinically significant changes in the neonatal birth weight.

Materials and Methods

Design and settings

We performed a single‐centre, retrospective study of patients enrolled in the prenatal service and delivered at Wyckoff Heights Medical Centre in Brooklyn, New York. The hospital is located in a community comprised of primarily Latinos living below the poverty line [8]. We enrolled women who received prenatal care and delivered a live born singleton gestation presenting to the obstetrics and gynaecology department between January 1st to December 31st, 2017 and delivered a singleton infant. This study was approved by our Institutional Review Board at Wyckoff Heights Medical Centre.

Study population

We enrolled a sample of adult women, 18 years or older, who received prenatal care and delivered at Wyckoff Heights Medical Centre. One thousand three hundred fifty-six charts were reviewed and eight hundred forty-five women met the inclusion criteria. Fourteen women who were classified as underweight at the initial prenatal visit were excluded due to inadequate sample size.

Data collection and data management

Baseline demographic data were collected on all enrolled women and neonates (Table 1). Maternal data such as maternal age at delivery, height, body weight at: first prenatal visit, 16-20 weeks’ gestation, 24-28 weeks’ gestation, 36-38 weeks’ gestation, as well as reproductive characteristics such as gravidity, parity, mode of delivery, past medical history and blood which were extracted from the hospital medical record. Neonatal data including gestational age at delivery, birth weight, and neonatal intensive care unit admission (Figure 2) as well as length of stay were collected from the hospital medical record.

Gestational age was calculated from the first day of the last menstrual period which was confirmed by ultrasound, or from the first dating ultrasound scan performed if the last menstrual period was unknown [9].

We conducted analyses of birth weight based on gestational age. Large for gestational age (LGA) and small for gestational age (SGA) were based on the 90th and 10th percentiles of weight for gestational age, respectively, based on the Duryea birth weight chart [10].

Measurements

Body mass index was calculated as the woman’s first documented pregnancy weight in kilograms divided by height in squared meters. Based on BMI, women were classified as normal weight (18.5–24.9 kg/m2), overweight (25.0 to 29.9 kg/m2) or obese (≥30 kg/m2). According to the 2009 IOM GWG recommendations, patients who are normal weight should gain 25-35lbs with an average weight gain of 1lb per week in the second and third trimester [11]. Patients categorized as overweight, should gain 15-25lbs with an average weight gain of 0.6lbs per week in the second and third trimester, and lastly patients categorized as obese, should gain 11-20lbs with an average weight gain of 0.5lbs per week in the second and third trimester [11].

Gestational weight gain was calculated by subtracting the pregnancy weight measured at the first prenatal visit from the weight recorded at the 36-38-week visit. This gestational weight gain was then compared with the IOM recommended GWG for each BMI category and categorized as inadequate, adequate or excessive. Specifically, adequate GWG was defined as weight gain of 25 to 35 pounds for women of normal BMI, 15 to 25 pounds was for overweight women and 11 to 20 pounds for obese women. Inadequate and excessive GWG were defined as less and more than adequate GWG according to the IOM guidelines, respectively. Gestational weight gain and body mass index were also examined with respect to other sociodemographic and health determinants. Ethnicity was self-reported by different ethnic categories such as: Caucasian, Hispanic, Asian, African American, or Other.

Statistical analysis

Statistical analyses were performed using STATA software package (STATA version 15.1, College Station, Texas). We used Wald chi-square tests to identify statistically significant differences of women gaining inadequate, adequate or excessive weight in each category. We examined associations between characteristics of interest and gestational weight gain adequacy using multinomial logistic regression to estimate odds ratios (OR) and 95% confidence intervals (CI). Statistical significance was claimed at P < 0.05.

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Iris Publishers- Open access Journal of Annals of Public Health & Epidemiology| Using Cellphone While Driving Among Saudi Drivers in Saudi Arabia, Cross Section Study 2018

 

authored by Samar A Amer*

Abstract

Background: Recently, the use of cell phone has increased among people nevertheless use it while driving lead to driver distraction which increases the risk of accidents and it is considered as a main cause of deaths in Kingdom of Saudi Arabia (KSA).

The aim: To measure the level of knowledge, the practice and the risk of using cell phone while driving and its’ related hazards in KSA, in order to decrease the prevalence of its use while driving.

Method: A cross-sectional study targeting 1320 randomly selected Saudi drivers, stratified to present the main 5 different regions (404 center, 386 west, 212 east, 232 souths, and 86 north), during October 2017-Jan year 2018. The data collected through online well-structured questionnaire and analyzed using the suitable tests.

Results: 1003(75.9%) of participants using cellphone recurrent while driving, 1076(81.5%) for calling, because 44.3% addicted to its use,85.1% by hands,90% when alone. 59.1% of drivers don’t use the Cellphone Holder or Bluetooth due to unavailability.82.8% had an accident, and 86% exposed to danger .97.9% had good knowledge only 12.1% had good practice, there was a significant association between using cell phone while driving and risk of accidents (p<0.05).

Conclusion: The central region had a highest prevalence of using cell phone while driving, most of the drivers have a good knowledge but they still using cell phone while driving in a bad practice.

Keywords: Cell phone use; Driving; Accident, KSA

Introduction

Road Injuries are the main cause of deaths in Kingdom of Saudi Arabia (KSA) [1]. However, driving cars is the most important transportation in developed countries, but most of the drivers are not fully aware of the driving rules that probability of occurrence hazards [2]. In recent years the importance of mobile phones has increased among people and they can use it in both positive and negative way [3], such as in Jeddah they estimated the number of using the cell phone while driving by 98.2% of them [4].

Moreover, the prevalence of using cell phone while driving was different between countries such as United States (US) 69% [5] and United Arab Emirates (UAE) 80% [6] are showed higher prevalence than the United Kingdom (UK) 21% [5] and Australia 39% [7]. In fact, using cell phone while driving lead to driver distraction which defined as ‘’the diversion of attention from activities critical for safe driving towards a competing activity, it is a behavior that jeopardizes the safety of drivers, passengers, and non-occupants alike’’ [8]. The distraction of using cell phone while driving can distract drivers’ eyes (visually) and minds to be attention to the road (cognitively) and their hands on the steering wheel (physically) [9]. Distraction crashes killed 3,092 people, 408 (13%) of them at least one driver was using cell phone when the crashes occurred [8] As well as 78% of the accidents in KSA related to using cell phone while driving [10]. A study showed, the risk of accident dramatically increasing with using cell phone while driving, (72%) of drivers believe that very likely to have a crash caused by texting/browsing cell phone, while (41%) very unlikely of a voice call (handheld) [7]. Moreover, Study show that uses cell phone while driving is similar dangerous with driving in the drunk situation at the legal limit [11].

Most governments develop their laws of using cell phone while driving, for instance in KSA, Ministry of Interior apply fines not less than 150 Saudi Riyal(S.R.) and not more than 300S.R. for using cell phone while driving [12] and in the UK the penalty of using handheld phone is 200£ while driving car and 2,500£ while driving lorry or bus [13]. As a global rank road traffic accident become the 11th leading cause of death [14]. Moreover, road traffic accident gave a higher rate of mortality in all Gulf countries [15,16]. While in KSA road injuries are the main cause leading to death [1]. Lately using cell phone while driving has become more common among drivers and it caused to injuries, disability, and accident.

Using cell phone while driving

Due to technological changes, the importance of cell phones services become more and more significant throughout the world. The reasons of that are what these devices have to software and features such as (social media, GPS, games, radio, internet and downloading, et al) that makes the daily life easier [17].

According to Sanbonmatsu D, Strayer D, et al. (2015) [18], the study conducted in Salt Lake City, Utah with 77 undergraduate participants to examine the impact of multitasking on performance monitoring and assessment showed there is a significant association between using cell phone while driving and the more serious errors of driving (p = .008). Also, people who use cell phone while driving is less aware than people who did not use it. These results indicate weak awareness among drivers about traffic safety [18].

A cross-sectional survey of 695 respondents was aimed to determine the prevalence of seat belt use and distracted driving behaviors among health-care providers in Saudi Arabia and its comparison with non-health-care providers in 2017. According to Jawadi H., et al Study showed most of the drivers using cell phone while driving but the highest rate was among who answer the cell phone while driving (98.5%).

Also, most of the drivers texting a message while driving (74.3%) but the accident that caused by text a messaging was only (28.7%) [19]. Open-ended interviews study with 228 sample conducted in U.S by Bergmark R, Gliklich E, Guo R, Gliklich R. [20] to describes the development and preliminary evaluation of the Distracted Driving Survey (DDS) and score in 2016. As we mentioned before, most of the drivers prefer to use cell phone to text a message while driving and study showed only 12.7% read the message while driving with any speed, 15.6% lowering them speed and 10.1% when stopped [2].

Recently, cell phone has become a necessity of life and has spread among the world as much as there are advantages and disadvantages to using cell phone according to Billieux J, Maurage P, Lopez Fernandez O, Kuss D, Griffiths M [21] study conducted in 2015 show Enhancement of health education in terms of physical fitness, healthy food, and improved behavior was from advantage of using cell phone but using phone while driving, addiction to using cell phone and health damages were disadvantages of using phone [22]. In 2015 a qualitative study was done in Pennsylvania by McDonald C, and Sommers M, to describe teen drivers’ perceptions of cell phone use while driving in order to inform future interventions to reduce risky driving among 30 drivers, Study showed most adolescents know the risk and distracting of using mobile phone while driving but there still using for text message, calling and social applications while driving [23].

Prevalence of using cellphone while driving among drivers

The prevalence of using a cellphone while driving is different between countries [5]. However, most countries around the world their prevalence is above 50% while there are countries with lower prevalence but not one of the Gulf countries [4,6,20,24]. A crosssectional study conducted by Jawadi, A. et al. in 2017 [19]. The title of the study was (Seat belt usage and distracted driving behaviors in Saudi Arabia: Health-care providers versus Nonhealth-care providers). The sample size of the study was 695 Saudi respondents who live in Saudi Arabia, aged 18 years and above, 51.2% of them were health-care providers and the rest were Nonhealth-care providers. Data were collecting out of online questionnaire and distributed through the emails of Saudi health-care providers in Saudi Arabia and social media using a snowball. One of the results showed the prevalence of using a cell phone while driving and it was 99.1% health-care providers and 89.8% of Nonhealthcare providers (total prevalence =95.9%) [20]. In another hand Trespalacios, O. King, M. Haque, M. and Washington, s. conducted a cross-sectional study in Queensland (2017). The study aimed to investigates characteristics of usage, risk factors, compensatory strategies in use and characteristics of high-frequency offenders of mobile phone use while driving. The study conducted an anonymous online questionnaire distributed across social media, local press releases, and electronic mail through Queensland University of Technology mailing lists.

Not only-but also public face-to-face dissemination. The sample size was 484 drivers 49.8% were aged 17-25 years and 50.2% were aged 26–65 years, 65.1%of them were women. The results showed that 49% used a cell phone while driving [7]. Moreover, at 2016 a cross-sectional study was done by Ahamed H, and Hafian, M in Saudi Arabia, Jeddah with 882 sample size. The aim of the study was to investigate the effects of using a cell phone while driving. The sample included men drivers aged above 17 participants. The instrument of this study developed a 34-item closed-format questionnaire. As a result, the prevalence of the study was 98.2% of drivers use their cell phones while driving [4]. At 2015 Rasool, F. et al. [24] conducted a cross-sectional study aimed to raise awareness about road traffic accidents and their causes and consequences among medical students in Arabian Gulf University (AGU) in Bahrain.

The sample size was 200 students with Bahraini or non- Bahraini, aged between 20-24 years. Data instrument was a structured questionnaire and designed to be self-filled by the participants. The prevalence of using a cell phone while driving (49%) showed in a part of the results [25].

An observational study conducted in Texas, US (2015) by Wilkinson, M. Brown, A. Moussa, A. Day, R. the study aimed to assess the 3-year prevalence of cell phone use (CPU) of drivers and characteristics associated with its use in six cities across Texas, from 2011–2013. CPU and driver characteristics of 1280 motor vehicles observed at major intersections in Dallas, Austin, San Antonio, El Paso, and Brownsville at respective University of Texas medical and academic campuses. The main result showed an overall prevalence of CPU, which was 18.7% [26].

Another study evaluates relevant factors related to causes of Road Traffic Accidents, RTAs among drivers in Abu Dhabi, UAE, 2014. Quantitative data method used through questionnaire survey as it is developed and piloted in the UK and UAE with 600 drivers as a sample size, aged between 18 and less to 65 years, 49% of the questionnaires returned. The prevalence of using a cell phone while driving was 80% in both male and female [6]. In addition, Al-Rees, H. et al. have done a cross-sectional study conducted in Oman, 2013. The study aimed to investigate driving behavior as indexed in the Driving Behavior Questionnaire (DBQ). A sample of 1003 participants was token from Omani university, 632 of them were students and 371 were staffs aged with a range of 17-58 years. The instrument of this study is a standard questionnaire that called DBQ questionnaire. The results showed that 92% of the drivers are using a cell phone while driving [24].

Demographic factors associated with using cell phone while driving

A study was done in Kingdom of Saudi Arabia in 2017 by Ahamed and Hafian to investigate the effects of mobile phone usage while driving. The sample size was 882 drivers aged over 17 years, they surveyed by a 34 -item closed-format questionnaire to gather information on their mobile phone use while driving as well as their risk perception. The survey covers eight variables representing demographic characteristics of the participants; nationality of the participant, marital status, education, work status, age, driving experience, the time participant got a smart mobile phone and conversation with passengers. A part of result in this study show there was statistically significant differences in the use of mobile phone while driving according to their nationality (P=0.03). The frequency of using mobile phone while driving is higher for Saudi- driver than non- Saudi- driver. Also, there were statistically significant differences according to marital status (P=0.04) and work status (P = 0.04). However, there were no statistically significant differences in the use mobile phone while driving according to their age, education level and driving experience [4].

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