scholarly journals Rural–urban differences in body mass index and obesity-related behaviors among low-income preschoolers

2020 ◽  
Author(s):  
Dawn A Contreras ◽  
Tiffany L Martoccio ◽  
Holly E Brophy-Herb ◽  
Mildred Horodynski ◽  
Karen E Peterson ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Low Income ◽  
Screen Time ◽  
Urban Areas ◽  
Eating Behaviors ◽  
Structural Changes ◽  
Dietary Quality ◽  
Public Health Issue ◽  
The Usa

Abstract Background With one in eight preschoolers classified as obese in the USA, childhood obesity remains a significant public health issue. This study examined rural–urban differences in low-income preschoolers’ body mass index z-scores (BMIz), eating behaviors, dietary quality, physical activity (PA) and screen time. Methods Pre-intervention data from 572 preschooler-parent dyads participating in a randomized, controlled obesity prevention trial in the Midwest USA were analyzed. We examined the associations among living in rural versus urban areas, child BMIz and child obesity-related behaviors, including eating behaviors, dietary quality, PA and screen time. Results Rural children had higher BMIz, more emotional overeating behaviors and more time spent playing outdoors compared with urban children. We found no associations between children living in rural versus urban areas and dietary quality and screen time. Conclusions The study found that rural–urban differences in BMIz may start as early as 3–4 years of age, if not earlier. To reverse the weight-related health disparities between rural and urban low-income preschoolers, structural changes in rural locations and family supports around coping skills may be needed.

scholarly journals Subjective Social Status Is Associated with Dysregulated Eating Behaviors and Greater Body Mass Index in an Urban Predominantly Black and Low-Income Sample

Nutrients ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 3893
Author(s):  
Monika M. Stojek ◽  
Paulina Wardawy ◽  
Charles F. Gillespie ◽  
Jennifer S. Stevens ◽  
Abigail Powers ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Social Status ◽  
Body Mass ◽  
Low Income ◽  
Emotional Eating ◽  
Eating Behaviors ◽  
Small Sample Size ◽  
Food Addiction ◽  
Subjective Social Status ◽  
Small Sample

Background: Higher subjective social status (SSS) or a person’s perception of their social standing is related to better health outcomes, but few studies examined SSS in relation to obesity. Emotional eating and food addiction have been linked to obesity. Some studies indicated that manipulating SSS may lead to altered food intake, but the relationship between SSS and dysregulated eating, such as emotional eating and food addiction (FA), has not been examined. The goal of this study was to examine the associations between SSS in the community and the larger society, dysregulated eating (emotional eating and FA), and body mass index (BMI) in a majority racial minority sample. Methods: The participants (N = 89; 93% Black, 86% women, and 56% with obesity; 72% income lower than USD 2000), recruited from a publicly funded hospital in Atlanta, GA, completed the MacArthur Scale, Dutch Eating Behaviors Questionnaire, Yale Food Addiction Scale, Beck Depression Inventory, PTSD Symptom Checklist, and demographics questionnaire. Results: Twenty-two percent of the sample met the criteria for FA; those with FA had significantly higher BMI than those without (p = 0.018). In the hierarchical linear regression, the SSS community (but not in society) predicted higher severity of emotional eating (β = 0.26, p = 0.029) and FA (β = 0.30, p = 0.029), and higher BMI (β = 0.28, p = 0.046), independent from depression and PTSD symptoms. Conclusions: The findings indicate that, among Black individuals with predominantly low income in the U.S., perceived role in their community is associated with eating patterns and body mass. Given the small sample size, the results should be interpreted with caution.

KEJADIAN PENYAKIT HIPERTENSI DAN INDEKS MASSA TUBUH PADA PEREMPUAN YANG TINGGAL DI PEDESAAN DAN PERKOTAAN

2019 ◽  
pp. 127-136
Author(s):  
Venti Agustina
Keyword(s):  
Blood Pressure ◽  
Body Mass Index ◽  
Body Mass ◽  
Rural Women ◽  
Urban Areas ◽  
Stage I ◽  
Normal Body Mass Index ◽  
Cross Sectional ◽  
Normal Body ◽  
Stadium I

Hipertensiadalah penyebab kematian utama di Indonesia. Kematian akibat hipertensi lebih banyak terjadi di perkotaan dibandingkan di desa. Tingginya kejadian hipertensi dipengaruhi oleh faktor yang dapat dikontrol (obesitas,berat badan lebih, konsumsi garam berlebih,aktivitas fisik rendah, perokok, dan konsumsi alkohol) dan faktor yang tidak dapat dikontrol (genetik, usia, dan jenis kelamin). Penelitian bertujuan memberikan gambarandistribusi tekanan darah dan indeks massa tubuh (IMT) pendudukperempuan di kota maupun di desa.Desain penelitian adalah deskriptif kuatitatif dengan pendekatan cross sectional. Data primer didapatkan melalui pengukuran tekanan darah, tinggi badan dan berat badan. Penelitian dilakukan di Desa Kutowinangun Kidul, Kecamatan Tingkir,Salatiga yang mewakili penduduk perempuan di perkotaan dan Desa Batur, Kecamatan Getasan, Kabupaten Semarangyang mewakili penduduk perempuan pedesaan. Adapun jumlah sampel masing-masing 66 respondendan 72responden. Hasil penelitian menunjukkan bahwa kejadian penyakit hipertensi, resiko obese dan obese lebih didominasi oleh respondendi perkotaan dibandingkan di pedesaan dengan rentang usia di atas 46 tahun. Respondendi desa dengan indeks massa tubuh normal cenderung mengalami pre-hipertensi (8,3%) dan hipertensi stadium I (6,9%) sementararesponden dengan resiko obese dan obese cenderung mengalami hipertensi stadium I (1,4%).Respondendi kota dengan indeks massa tubuh normal cenderung mengalami pre hipertensi (6,06%), hipertensi stadium I (4,5%) dan II (7,5%). Responden dengan resiko obese cenderung mengalami hipertensi stadium I (4,5%), dan responden dengan obese I dan II cenderung mengalami pre-hipertensi (4,5%).   Hypertension is the leading cause of death in Indonesia. Deaths due to hypertension are more common in urban areas than in villages. The high incidence of hypertension is influenced by factors that can be controlled (obesity, overweight, excessive salt consumption, low physical activity, smokers, and alcohol consumption) and factors that cannot be controlled (genetic, age, and sex). The study aimed to provide an overview of blood pressure distribution and body mass index (BMI) of female residents in cities and villages. The study design was descriptive quantitative with a cross sectional approach. Primary data was obtained through measurements of blood pressure, height and weight. The study was conducted in Kutowinangun Kidul Village, Tingkir Subdistrict, Salatiga representing women in urban areas and Batur Village, Getasan Subdistrict, Semarang Regency, representing rural women. The number of samples was 66 respondents and 72 respondents respectively. The results showed that the incidence of hypertension, the risk of obese and obese was more dominated by respondents in urban areas than in rural areas with ages above 46 years. Respondents in villages with normal body mass index tended to experience pre-hypertension (8.3%) and stage I hypertension (6.9%) while respondents with obese and obese risk tended to experience stage I hypertension (1.4%). Respondents in cities with normal body mass index tended to experience pre-hypertension (6.06%), stage I hypertension (4.5%) and II (7.5%). Respondents with obese risk tended to experience stage I hypertension (4.5%), and respondents with obese I and II tended to experience pre-hypertension (4.5%).

scholarly journals Relationship between Gender, Physical Activity, Screen Time, Body Mass Index and Wellbeing in Irish Children from Social-Disadvantage

2021 ◽  
pp. 1-15
Author(s):  
Wesley O’Brien ◽  
Sarahjane Belton ◽  
Ben Fitzpatrick ◽  
Stephen Shannon ◽  
Deirdre Brennan ◽  
...  
Keyword(s):  
Physical Activity ◽  
Body Mass Index ◽  
Body Mass ◽  
Screen Time ◽  
Social Disadvantage

scholarly journals Sleep Timing Moderates the Concurrent Sleep Duration–Body Mass Index Association in Low-Income Preschool-Age Children

2014 ◽  
Vol 14 (2) ◽  
pp. 207-213 ◽  
Author(s):  
Alison L. Miller ◽  
Niko Kaciroti ◽  
Monique K. LeBourgeois ◽  
Yu Pu Chen ◽  
Julie Sturza ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Sleep Duration ◽  
Body Mass ◽  
Low Income ◽  
Preschool Age ◽  
Sleep Timing ◽  
Preschool Age Children

Analysis of Body Mass Index (BMI) Trends Among a Pediatric Dental Patient Population: A Pilot Study. (Preprint)

2021 ◽  
Author(s):  
Tengfei Su ◽  
Mac Jackson ◽  
Keaton Sacry ◽  
Karl Kingsley MPH
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Low Income ◽  
Patient Population ◽  
Pediatric Population ◽  
Primary Care Providers ◽  
Overweight And Obesity ◽  
Dental School ◽  
Care Providers ◽  
Over Time

BACKGROUND Over the past few decades, a growing trend of overweight and obesity has emerged among the pediatric population. This is a cause of significant concern as these are significantly correlated to other negative oral and systemic health outcomes over time. Although measurement of body mass index (BMI) is common among pediatric physicians and primary care providers, few studies have explored the feasibility of BMI measurement and analysis from pediatric dental providers. OBJECTIVE The primary objective of this study was to compile and analyze pediatric BMI measurements taken from a pediatric dental school patient population. METHODS This study was a retrospective analysis of previously collected data of pediatric patients between 2012 and 2019 (N=451), which was reviewed and approved by the Institutional Review Board (IRB). Descriptive statistics and trend analysis were compiled to determine the trends in pediatric BMI over time. RESULTS Nearly equal percentages of females and males were represented in the study (P=0.432), with the overwhelming majority identified as racial/ethnic minorities (84.5%), P=0.0075. These data revealed that pediatric BMI increased significantly from 25.6 in 2012 to 31.3 in 2018 (22.1%), P=0.031. No significant differences between males and females were observed (P=0.4824) or between minority and non-minority patients (P=0.8288). CONCLUSIONS This study provides significant novel temporal information regarding pediatric BMI among this low-income, minority patient population and highlights the need for expanding the dental school (and pediatric dental residency) curriculum to include more topics related to measuring and tracking overweight and obese children and the most appropriate methods for use in the pediatric dental office.

scholarly journals The Associations between Screen Time and Sleep Duration, and Body Mass Index (BMI) in under Five-Year-Old Children

2018 ◽  
Author(s):  
Hossein Sourtiji ◽  
Mehdi Rassafiani ◽  
Seyed Ali Hosseini ◽  
Mohammad Esmaeil Motlagh ◽  
Mehdi Noroozi
Keyword(s):  
Body Mass Index ◽  
Sleep Duration ◽  
Body Mass ◽  
Screen Time ◽  
Linear Regression Analysis ◽  
Cluster Sampling ◽  
Healthy Children ◽  
Cross Sectional ◽  
Under Five ◽  
Screen Viewing

Today, due to recent developments in technology, children devote plenty of time for screen viewing. However, its harmful effects are not yet clear. The purpose of present study was to examine the associations among screen viewing and sleep duration, and body mass index (BMI) in under-five years old children. This cross-sectional study was conducted with 322 under-five healthy children that were selected using multistage stratified cluster sampling method in 2017. The data that were gathered by time-use diary method were analyzed using Kolmogorov-Smirnov test, Spearman correlation tests, multiple linear regression analysis, one-way ANCOVA, two-way ANCOVA. There was a negative correlation between screen time and sleep duration (rs = -0.42, p = 0.00), positive correlation between screen time and BMI (rs = 0.38, p = 0.00) and sleep duration negatively correlated with BMI (rs = -0.22, p = 0.00). screen viewing was a predictive factor for both sleep duration (β = -0.26, p = 0.00) and BMI (β = -0.26, p = 0.00). screen viewing had a significant impact on sleep duration (4, 314) = 5.02, P = 0.001) and BMI (F (4, 314) = 1.16, P=0.298). Results of this study indicated that screen viewing is related to sleep duration and BMI in under-five children. furthermore, screen time has an impact on sleep duration and BMI scores of children. findings of our study suggest that sleep duration negatively is associated with BMI in under-five-year-old children.

scholarly journals Body Mass Index of First Nations youth in Ontario, Canada: influence of sleep and screen time

2013 ◽  
Author(s):  
Michelle Gates ◽  
Rhona Hanning ◽  
Ian Martin ◽  
Allison Gates ◽  
Leonard Tsuji
Keyword(s):  
Body Mass Index ◽  
First Nations ◽  
Body Mass ◽  
Screen Time

scholarly journals Socio-demographic Correlates of Pre-pregnancy Body Mass Index Among Low-income Women in Hawaii WIC Participating in a Randomised Trial

2021 ◽  
Author(s):  
Michelle Asinobi ◽  
Cristina Palacios ◽  
Yanyan Wu ◽  
Jinan Banna
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Low Income ◽  
Randomised Trial ◽  
Categorical Variables ◽  
Healthy Weight ◽  
Childbearing Age ◽  
Demographic Correlates ◽  
Race Ethnicity ◽  
Low Income Women

Abstract Background: A healthy pre-pregnancy BMI fosters positive outcomes for both mother and infant both during and after pregnancy. To design interventions to promote a healthy pre-pregnancy BMI in low-income women, it is important to understand correlates. The purpose of this study was to identify the socio-demographic correlates of pre-pregnancy body mass index (BMI) among low-income women.Methods: Participants were low-income pregnant women (n=83) in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) program in Hawai‘i enrolled in a four-month text message-based nutrition intervention program. Participants reported pre-pregnancy weight and height and completed a demographics questionnaire on age, race/ethnicity, education, employment status and number of children. Descriptive statistics (mean, standard deviation for continuous variables, and frequencies and proportions for categorical variables) were used to summarize the sample. Simply linear regression analyses were performed to examine if independent variables were associated with BMI before pregnancy. Results: Among the 83 women, 33 (39.8%) were 18-24 years old, 22 (26.5%) were between 25 and 29, 19 (22.9%) were 30-34 and 9 (10.8%) were 35-41. A total of 18 (21.7%) were Asian. Age and race/ethnicity were marginally associated with BMI before pregnancy. The age group 30-34 had the highest BMI before pregnancy (p=0.06) and Asian had lower BMI before pregnancy than the other races/ethnicities (p=0.01). Conclusions: Being classified as Asian was associated with lower BMI before pregnancy, while those who were 30-34 years old had the highest pre-pregnancy BMI compared to other age groups. These socio-demographic factors should be taken into account when designing interventions to promote healthy weight in women of childbearing age. Trial registration: The trial is registered on clinicaltrials.gov (NCT04330976). Date of registration April 2, 2020 (restrospectively registered). URL: https://clinicaltrials.gov/ct2/show/NCT04330976

Sign in / Sign up

Export Citation Format

Share Document