Towards Understanding Post-Socialist Migrants’ Access to Physical Activity in the Nordic Region: A Critical Realist Integrative Review

Experiences of, and access and barriers to, physical activity (PA) differ between individuals. This becomes perpetuated in a migration context. Although there is super-diversity between migrant groups, health research rarely accounts for this cultural diversity. More concerningly, the matter of context is rarely scrutinized or juxtaposed with the specifics of certain ethnic groups. This integrative review assessed the evidence on post-socialist migrants’ PA levels, constraints, and enablers for PA in the Nordic region. The results show that post-socialist female migrants have an especially high risk of being physically inactive. The qualitative work elucidates socio-cultural factors that impose specific constraints on females when attempting to engage in PA. Furthermore, in scrutinizing the context, Nordic nature (Friluftsliv) is a viable way for migrants to access PA with additional health benefits (e.g., mental). However, the Nordic environment also poses specific PA challenges, such as harsh winters. This can be understood by considering post-socialist migrants’ prior use of, and attitude to, nature. The review highlights the importance of understanding specifics about both migrant groups and contexts through a critical-realist lens in the pursuit of providing PA opportunities. Future PA programs need to understand the contextual, sociohistorical, and cultural settings in which they and migrants are embedded.

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Cultural factors associated with physical activity among U.S. adults: An integrative review

Applied Nursing Research ◽

10.1016/j.apnr.2018.06.006 ◽

2018 ◽

Vol 42 ◽

pp. 98-110 ◽

Cited By ~ 3

Author(s):

Nitha Mathew Joseph ◽

Padmavathy Ramaswamy ◽

Jing Wang

Keyword(s):

Physical Activity ◽

Cultural Factors ◽

Integrative Review ◽

Factors Associated

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Physical activity as a therapeutic strategy in mental health: an integrative review with implication for nursing care

Escola Anna Nery ◽

10.1590/2177-9465-ean-2016-0390 ◽

2017 ◽

Vol 21 (3) ◽

Author(s):

Bruno da Silva Lourenço ◽

Maria Angélica de Almeida Peres ◽

Isaura Setenta Porto ◽

Rosane Mara Pontes de Oliveira ◽

Virginia Faria Damásio Dutra

Keyword(s):

Physical Activity ◽

Mental Disorders ◽

Nursing Care ◽

Therapeutic Strategy ◽

Scientific Evidence ◽

Well Being ◽

Integrative Review ◽

Healthy Lifestyles ◽

Practical Effect ◽

Selection Of

Abstract This study is an integrative review with the aim to identify and describe the scientific evidence of the practical effect of physical activity in people with mental disorders. For the selection of articles, the databases CINAHL, MEDLINE, LILACS, SciELO, Cochrane and Scopus were used. The sample of this review consisted of eight articles. Their analysis resulted in the categories: obesity and metabolic syndrome, specialized nursing, sedentary and healthy lifestyles, support and social network, incentive to the practice of physical activity, and anxiety and physical activity. The benefits to physical health were partially elucidated by the sample. The implications for nursing care arise from the therapeutic efficacy of physical activity by people with mental disorders, adding individual and collective benefits that provide socialization and promotion of well-being.

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Should Physical Activity Intervention Efforts Take a Whole Population, High-Risk, or Middle Road Strategy?

Journal of Physical Activity and Health ◽

10.1123/jpah.2012-0275 ◽

2014 ◽

Vol 11 (5) ◽

pp. 966-970 ◽

Cited By ~ 4

Author(s):

Geeske Peeters ◽

Richard Hockey ◽

Wendy Brown

Keyword(s):

Physical Activity ◽

Heart Disease ◽

Longitudinal Study ◽

High Risk ◽

Chronic Conditions ◽

Physical Activity Intervention ◽

Incidence Rates ◽

Theoretical Modeling ◽

Actual Distribution ◽

Mail Surveys

Purpose:This study was designed to compare theoretical strategies for changing physical activity (PA) in terms of their potential to reduce the incidence of chronic conditions in midage women: (1) whole population: +30 minutes/week in all, (2) high-risk: +60 minutes/week in the lowest 25% of the PA distribution, and (3) middle road: shift all those not meeting guidelines to a level commensurate with meeting guidelines.Methods:10,854 participants (50–55 years in 2001) in the Australian Longitudinal Study of Women’s Health completed mail surveys in 2001, 2004, 2007, and 2010. PA was calculated as MET·minutes/week spent in walking, moderate and vigorous PA in the previous week. Incidence rates per 1000 person-years for diabetes, heart disease, hypertension, cancer, and depression were calculated for the actual distribution and after modeled shifts in PA.Results:The incidence rates were 10.6 for diabetes, 7.0 for heart disease, 30.7 for hypertension, 8.0 for cancer, and 28.4 for depression. Greater reductions in incidence were found for the middle road strategy than for the whole population and high-risk strategies, with reductions ranging from –6.3% for cancer to –12.3% for diabetes.Discussion:This theoretical modeling showed that a middle road strategy to increasing PA was superior to the whole population and high-risk strategies, in terms of reducing incidence rates of chronic conditions in middle-aged women.

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Environmental, Policy, and Cultural Factors Related to Physical Activity in a Diverse Sample of Women: The Women's Cardiovascular Health Network Project-Summary and Discussion

Women & Health ◽

10.1300/j013v36n02_09 ◽

2002 ◽

Vol 36 (2) ◽

pp. 121-132 ◽

Cited By ~ 12

Author(s):

Amy A. Eyler ◽

Joshua R. Vest ◽

Bonnie Sanderson ◽

JoEllen Wilbur ◽

Dyann Matson-Koffman ◽

...

Keyword(s):

Physical Activity ◽

Environmental Policy ◽

Cardiovascular Health ◽

Cultural Factors ◽

Health Network ◽

Network Project

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Can wearable technology be used to approximate cardiopulmonary exercise testing metrics?

Perioperative Medicine ◽

10.1186/s13741-021-00180-w ◽

2021 ◽

Vol 10 (1) ◽

Author(s):

Laura Jones ◽

Laura Tan ◽

Suzanne Carey-Jones ◽

Nathan Riddell ◽

Richard Davies ◽

...

Keyword(s):

Physical Activity ◽

High Risk ◽

Oxygen Uptake ◽

Anaerobic Threshold ◽

Exercise Testing ◽

Low Cost ◽

Cardiopulmonary Exercise Testing ◽

Peak Oxygen Uptake ◽

Wearable Device ◽

Cardiopulmonary Exercise

Abstract Background Consumer wrist-worn wearable activity monitors are widely available, low cost and are able to provide a direct measurement of several markers of physical activity. Despite this, there is limited data on their use in perioperative risk prediction. We explored whether these wearables could accurately approximate metrics (anaerobic threshold, peak oxygen uptake and peak work) derived using formalised cardiopulmonary exercise testing (CPET) in patients undergoing high-risk surgery. Methods Patients scheduled for major elective intra-abdominal surgery and undergoing CPET were included. Physical activity levels were estimated through direct measures (step count, floors climbed and total distance travelled) obtained through continuous wear of a wrist worn activity monitor (Garmin Vivosmart HR+) for 7 days prior to surgery and self-report through completion of the short International Physical Activity Questionnaire (IPAQ). Correlations and receiver operating characteristic (ROC) curve analysis explored the relationships between parameters provided by CPET and physical activity. Device selection Our choice of consumer wearable device was made to maximise feasibility outcomes for this study. The Garmin Vivosmart HR+ had the longest battery life and best waterproof characteristics of the available low-cost devices. Results Of 55 patients invited to participate, 49 (mean age 65.3 ± 13.6 years; 32 males) were enrolled; 37 provided complete wearable data for analyses and 36 patients provided full IPAQ data. Floors climbed, total steps and total travelled as measured by the wearable device all showed moderate correlation with CPET parameters of peak oxygen uptake (peak VO2) (R = 0.57 (CI 0.29–0.76), R = 0.59 (CI 0.31–0.77) and R = 0.62 (CI 0.35–0.79) respectively), anaerobic threshold (R = 0.37 (CI 0.01–0.64), R = 0.39 (CI 0.04–0.66) and R = 0.42 (CI 0.07–0.68) respectively) and peak work (R = 0.56 (CI 0.27–0.75), R = 0.48 (CI 0.17–0.70) and R = 0.50 (CI 0.2–0.72) respectively). Receiver operator curve (ROC) analysis for direct and self-reported measures of 7-day physical activity could accurately approximate the ventilatory equivalent for carbon dioxide (VE/VCO2) and the anaerobic threshold. The area under these curves was 0.89 for VE/VCO2 and 0.91 for the anaerobic threshold. For peak VO2 and peak work, models fitted using just the wearable data were 0.93 for peak VO2 and 1.00 for peak work. Conclusions Data recorded by the wearable device was able to consistently approximate CPET results, both with and without the addition of patient reported activity measures via IPAQ scores. This highlights the potential utility of wearable devices in formal assessment of physical functioning and suggests they could play a larger role in pre-operative risk assessment. Ethics This study entitled “uSing wearable TEchnology to Predict perioperative high-riSk patient outcomes (STEPS)” gained favourable ethical opinion on 24 January 2017 from the Welsh Research Ethics Committee 3 reference number 17/WA/0006. It was registered on ClinicalTrials.gov with identifier NCT03328039.

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Metabolic and lifestyle determinants of glycemic variability in persons at high risk of type 2 diabetes: a study with continuous monitoring of diet, physical activity, and glucose level. (Preprint)

10.2196/preprints.30105 ◽

2021 ◽

Author(s):

Su Hyun Park ◽

Jiali Yao ◽

Clare Whitton ◽

Xin Hui Chua ◽

Suresh Rama Chandran ◽

...

Keyword(s):

Physical Activity ◽

High Risk ◽

Glycemic Variability ◽

Tolerance Test ◽

Glucose Levels ◽

Intensity Physical Activity ◽

Time In Range ◽

Vigorous Intensity ◽

Mean Glucose

BACKGROUND Frequent and large fluctuations in blood glucose concentration during the day may increase risk of type 2 diabetes. It remains unclear how diet and physical activity affect glycemic variability in real-world conditions in persons without diabetes. OBJECTIVE We examined metabolic and lifestyle determinants (diet, physical activity, and sleep) of blood glucose levels over a seven-day period in people at high risk for diabetes METHODS Twenty-eight participants with a mean age of 46.0 (SD 9.9) years and a mean body mass index (BMI) of 27.5 (SD 1.8) kg/m2 underwent a mixed meal tolerance test to assess glucose homeostasis at baseline. Subsequently, they wore an accelerometer to assess movement behaviors, recorded their dietary intakes through a mobile phone application, and wore a flash glucose monitoring device that measured glucose levels every 15 min for seven days. Generalized estimating equation models were used to assess the associations of metabolic and lifestyle risk factors with daily mean glucose levels (mmol/L), the coefficient of variation (CV%) of glucose levels, and time-in-range (3.0 to 7.8 mmol/L, %). RESULTS A higher BMI (β = 0.12 per kg/m2; P = 0.01), body fat (β = 0.03 per kg; P = 0.01), and selected markers of hyperglycemia and insulin resistance from the meal tolerance test were associated with higher mean glucose levels during the seven days. Moderate-to-vigorous intensity physical activity (β = -1.77 per hr./d, P = 0.008) and polyunsaturated fat intake (β = -2.23 per 5 energy %, P < 0.001) were independently associated with less variation in glucose levels (CV%). Higher protein (β = 0.90, P = 0.007) and polyunsaturated fatty acid (β = 3.21, P = 0.02) intakes were associated with more time-in-range. In contrast, higher carbohydrates intake was associated with less time-in-range (β = -0.59, P = 0.04). Sleep, sedentary behavior, or light intensity physical activity were not independently associated with glucose measures. CONCLUSIONS Body fatness was associated with higher mean glucose levels, and moderate-to-vigorous intensity physical activity was associated with less glycemic variability throughout a week. Diets with higher protein and polyunsaturated fat, and lower carbohydrates were associated with more time in normal glucose range. Physical activity and dietary composition can substantially influence glucose variation in people at high risk of diabetes.

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Examining Influences of Parenting Styles and Practices on Physical Activity and Sedentary Behaviors in Latino Children in the United States: Integrative Review

JMIR Public Health and Surveillance ◽

10.2196/publichealth.8159 ◽

2018 ◽

Vol 4 (1) ◽

pp. e14 ◽

Cited By ~ 5

Author(s):

Ana Cristina Lindsay ◽

Minerva Wasserman ◽

Mario A Muñoz ◽

Sherrie F Wallington ◽

Mary L Greaney

Keyword(s):

Physical Activity ◽

United States ◽

Parenting Styles ◽

The United States ◽

Integrative Review ◽

Latino Children ◽

Sedentary Behaviors

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A Clinical Study to Evaluate the Preventive Aspect of Amalaki Swarasa and Haridra Churna with Madhu in Pre-diabetes (Borderline Type2 DM)

International Journal of Health Sciences and Research ◽

10.52403//ijhsr.20210810 ◽

2021 ◽

Vol 11 (8) ◽

pp. 67-78

Author(s):

Swathi. M. Somayaji

Keyword(s):

Physical Activity ◽

Diabetes Mellitus ◽

Clinical Study ◽

High Risk ◽

Key Words ◽

Fast Food ◽

Diabetes Prevention ◽

Lifestyle Modification ◽

Calorie Intake ◽

Borderline Diabetes

Diabetes mellitus is rising to an alarming epidemic level. Pre-diabetes (intermediate hyperglycemia) is a high-risk state for diabetes that is defined by glycemic variables that are higher than normal, but lower than diabetes thresholds. It stems up in persons who are physically inactive, obese, takes more kaphakara medokara abhishyandi ahara. Diabetes if not treated can cause a severe burden on society. The rising prevalence is closely associated with urbanization because of increasing obesity and inclination towards fast food. For pre-diabetic individuals, lifestyle modification is the cornerstone of diabetes prevention. Physical activity and decreased calorie intake can reduce the occurrence of Diabetes. So an attempt was made to find out the efficacy of Amalaki swarasa and haridra churna with madhu in pre-diabetes (borderline diabetes) Key words: Pre-Diabetes, Amalaki, Haridra, Madhu, Borderline Diabetes Mellitus.

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