Assessment of lifestyle changes in combating the COVID-19 pandemic among people of Karachi, Pakistan.

Aim: COVID-19 arose as a pandemic that wreaked havoc all over the world. Study determines lifestyle changes adopted by people of Karachi in response to COVID-19 pandemic. Methods: This was the cross-sectional study and carried out at public sector hospital and 218 participants were selected through random sampling method. Results: Lifestyle changes a statistically significant difference in nutrition (p = 0.000), physical activity (p = 0.000), workout (p = 0.000), smoking (p = 0.000), sleep hours (p = 0.000), and supplements (p = 0.000) before and during lockdown. Face masks were utilized by 38% of individuals, gloves by 19%, and social isolation was observed by 26%. 11% of participants did not follow any protocols. Conclusion: Study found significant differences in lifestyle habits such as diet, sleep, smoking and physical activity.

COVID-19 pandemic affect every day life of all people. This study results fond that there are different domain of quality life were affected. Nutrition, physical activity and smoking were associated with poor quality of life and these changes affect the mental and physical health of community people. There is need to social and medical support for people affected by COVID-19 pandemic.

Assessment of Anxiety among People with Various Physical Activity Levels during Lockdown in Karachi, Pakistan.

Background The purpose of this study is to make it easier to counsel the general public on how to promote their psychological health and better lifestyle by boosting their physical activity in the event of more devastating future waves of coronavirus disease 2019. Coronavirus disease is a viral infection first reported in Wuhan, China, which led to a worldwide pandemic and lockdown. In addition to physical health, the uncertainty of situation and fear of infection have further affected the mental health of the individuals. Lockdown has also halted the physical activity of people further adding into the stress and anxiety. Methods A sample size of 376 was required, but a convenient sampling technique collected 400 responses due to overwhelming Participation. A well-structured questionnaire was used for data collection, which contained sections such as a demographics section. We used the International Physical Activity Questionnaire scale to measure various physical activity levels and the generalized anxiety disorder scale to measure anxiety levels, because of their considerate validity and feasibility. Later both of our variables were compared to find out the correlation of anxiety levels with different physical activity levels. Results Mean Anxiety and its prevalence rates in the sample were 7.32 ± 5.767 and 33%. On performing Pearson correlation, increasing age was found to be a risk factor for Anxiety. One-way analysis of variance showed a significant difference between Physical Activity and Anxiety. In the post-hoc Tukey test, a considerable difference in anxiety level was found between people with no physical activity and vigorous physical activity. Conclusion During the lockdown period, the mean anxiety was found to be 7.0 ± 5.56 with prevalence rate of 33% among the people with no, low, moderate or vigorous physically active levels was found to be associated with better perceived mental health status which suggests the need to promote physically active style to cope with anxiety and awareness sessions to be conducted especially among those who could not maintain a physically active lifestyle. Also, among the general population e-Health programs could provide an appropriate way to promote a physically active lifestyle.

Screen Time And Its Relationship With Attention Deficit Hyperactivity Disorder Among Children Attending A Tertiary Care Hospital.

Objective: To estimate the frequency of attention deficit hyperactivity disorder and its relationship with screen time and sociodemographic characteristics among children. METHODS: The cross-sectionalstudy was conducted at the National Institute of Child Health, Karachi, in June-July 2022, and comprised children of either gender aged 5-10 years visiting the paediatric outpatient department. Screen time was measured using a pretested questionnaire, while attention deficit hyperactivity disorder was measured using ADHD rating scale IV. The relationship of sociodemographic characteristics and screen time with the disorder was explored through multiple linear regression analysis. Data was analysed using SPSS 20. RESULTS: Of the 247 participants, 126(51%) were boys and 121(49%) were girls. The overall mean age was 7.84±1.87 years. There were 149(60.3%) children at the primary level of education, while 76(30.8%) had no formal education. There were 139(56.3%) children having screen time >2 hours/day with a mean of 3.36±3.14 hours. There were 15(6.1%) children with attention deficit hyperactivity disorderscore >26 with a mean of 11.58±9.27. Boys were more frequently affected by attention deficit hyperactivity disorder compared to girls (p=0.026), and there was a significant positive correlation between screen time and attention deficit hyperactivity disorder (p<0.001). Conclusion: The majority of children were found to be spending more than the recommended time on screen. Male gender and screen time were associated with attention deficit hyperactivity disorder.

Waist circumference centiles for UK South Asian children.

OBJECTIVES: To develop waist circumference (WC) centile curves for UK South Asian children, to make comparisons with published centiles for British, indigenous Indian and Pakistani children, as well as to make anthropometric comparisons with their UK white peers. DESIGN: Cross-sectional study. SETTING: School-aged children from London boroughs (main measures: 2004-2007). PARTICIPANTS: 1562 (652 boys, 910 girls) UK South Asian and 1120 (588 boys, 532 girls) UK white children aged 4.0-13.9 years. INTERVENTIONS: WC, height, weight and body mass index (BMI). MAIN OUTCOME MEASURES: The outcome measures were smoothed WC centile curves, constructed using the LMS (L = skewness, M = median, S = coefficient of variation) method. SD scores (SDS) were generated using UK90 and British (WC) growth references. RESULTS: WC increased with age for both sexes, rising more steeply at the upper centiles after the age of 6 years. Overall, UK South Asian children, similar to indigenous South Asian populations, had higher WC values than the British WC references. However, compared with their UK white peers, UK South Asian children had significantly (p<0.001) lower mean WC (UK white SDS=0.74 and SDS=0.64 vs UK South Asian SDS=0.32 and SDS=0.21 for boys and girls, respectively). Obesity prevalence was greater using WC than BMI for both ethnicities. At the 90th centile, for UK South Asian children, prevalence was 21.5% vs 24.4% for boys and 17% vs 24.5% for girls based on BMI and WC, respectively. CONCLUSIONS: These curves represent the first WC centiles for UK South Asian children up to the age of 14 years. With a continued rise in childhood obesity, they provide a useful historical control for future comparisons.