Models of acculturation and health behaviors among Latino immigrants to the US

2001 ◽  
Vol 53 (1) ◽  
pp. 41-53 ◽  
Author(s):  
E Arcia ◽  
M Skinner ◽  
D Bailey ◽  
V Correa
Keyword(s):  
Health Behaviors ◽  
Latino Immigrants ◽  
The Us

scholarly journals Sex in Late Life: Assessing Adults’ Expectations and the Role of Healthcare Professionals

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 313-313
Author(s):  
Jill Naar ◽  
Raven Weaver ◽  
Shelbie Turner
Keyword(s):  
Older Adults ◽  
Sexual Health ◽  
Health Behaviors ◽  
Healthcare Professionals ◽  
Late Life ◽  
Sexual History ◽  
Growth Curve Models ◽  
The Us ◽  
Sexual Health Behaviors ◽  
The Life Course

Abstract Sexual activity contributes to quality of life throughout the lifespan. However, stigma about sex in late life influences older adults’ perceptions and healthcare professionals’ perceptions of older adults’ sexual health/behaviors. Using a multi-methods approach, we examined attitudes and knowledge about sexual health/behaviors in late life. Using longitudinal data from the Midlife in the US Study (Wave 1-3; N=7049), we ran age-based growth curve models to analyze changes in levels of optimism about sex in their future. We also piloted a survey with healthcare professionals assessing attitudes, knowledge, and awareness of policy about sexual health/behaviors among older adults. Adults’ expectations became less optimistic with increased age (β = -0.1, SE = 0.003, p < .0001). Men were more optimistic than women at age 20 (p = 0.016), but men’s optimism decreased over the life course at a faster rate than did women’s (p < .0001), so that from ages 40-93, men were less optimistic than women. Among healthcare professionals (N=21), the majority indicated never or rarely asking their clients about sexual history or health/behaviors; however, they indicated some knowledge about issues relevant to older adults (e.g., safe-sex practices, sexual dysfunction). Few indicated awareness about policies related to sexual behavior among residents (i.e., issues of consent, STIs). Among adults, there is a need to address declining optimism for expectations about sex in late life. Health professionals are well-situated to raise awareness and normalize discussions about sexual health, thus countering negative stigma and contributing to increasing optimism for expectations to remain sexually active.

Do Latino Immigrants Link Self-rated Health with BMI and Health Behaviors?

2007 ◽  
Vol 31 (5) ◽  
pp. 535-544 ◽  
Author(s):  
Deanna Kepka ◽  
Guadalupe X. Ayala ◽  
Andrea Cherrington
Keyword(s):  
Health Behaviors ◽  
Latino Immigrants ◽  
Self Rated Health

scholarly journals Characterizing the US Population by Patterns of Mobile Health Use for Health and Behavioral Tracking: Analysis of the National Cancer Institute's Health Information National Trends Survey Data (Preprint)

2019 ◽  
Author(s):  
Camella J Rising ◽  
Roxanne E Jensen ◽  
Richard P Moser ◽  
April Oh
Keyword(s):  
Health Behaviors ◽  
Health Information ◽  
Mobile Health ◽  
Technology Use ◽  
Older Age ◽  
Health Apps ◽  
Behavioral Tracking ◽  
The Us ◽  
Health Related ◽  
National Trends

BACKGROUND Multiple types of mobile health (mHealth) technologies are available, such as smartphone health apps, fitness trackers, and digital medical devices. However, despite their availability, some individuals do not own, do not realize they own, or own but do not use these technologies. Others may use mHealth devices, but their use varies in tracking health, behaviors, and goals. Examining patterns of mHealth use at the population level can advance our understanding of technology use for health and behavioral tracking. Moreover, investigating sociodemographic and health-related correlates of these patterns can provide direction to researchers about how to target mHealth interventions for diverse audiences. OBJECTIVE The aim of this study was to identify patterns of mHealth use for health and behavioral tracking in the US adult population and to characterize the population according to those patterns. METHODS We combined data from the 2017 and 2018 National Cancer Institute Health Information National Trends Survey (N=6789) to characterize respondents according to 5 mutually exclusive reported patterns of mHealth use for health and behavioral tracking: (1) mHealth nonowners and nonusers report not owning or using devices to track health, behaviors, or goals; (2) supertrackers track health or behaviors and goals using a smartphone or tablet plus other devices (eg, Fitbit); (3) app trackers use only a smartphone or tablet; (4) device trackers use only nonsmartphone or nontablet devices and do not track goals; and (5) nontrackers report having smartphone or tablet health apps but do not track health, behaviors, or goals. RESULTS Being in the mHealth nonowners and nonusers category (vs all mHealth owners and users) is associated with males, older age, lower income, and not being a health information seeker. Among mHealth owners and users, characteristics of device trackers and supertrackers were most distinctive. Compared with supertrackers, device trackers have higher odds of being male (odds ratio [OR] 2.22, 95% CI 1.55-3.19), older age (vs 18-34 years; 50-64 years: OR 2.83, 95% CI 1.52-5.30; 65+ years: OR 6.28, 95% CI 3.35-11.79), have an annual household income of US $20,000 to US $49,999 (vs US $75,000+: OR 2.31, 95% CI 1.36-3.91), and have a chronic condition (OR 1.69, 95% CI 1.14-2.49). Device trackers also have higher odds of not being health information seekers than supertrackers (OR 2.98, 95% CI 1.66-5.33). CONCLUSIONS Findings revealed distinctive sociodemographic and health-related characteristics of the population by pattern of mHealth use, with notable contrasts between those who do and do not use devices to track goals. Several characteristics of individuals who track health or behaviors but not goals (device trackers) are similar to those of mHealth nonowners and nonusers. Our results suggest patterns of mHealth use may inform how to target mHealth interventions to enhance reach and facilitate healthy behaviors.

Legal status history, gender, and the health of Latino immigrants in the US

2021 ◽  
Author(s):  
Gabriela León‐Pérez ◽  
Evelyn J. Patterson ◽  
Larissa Coelho
Keyword(s):  
Legal Status ◽  
Latino Immigrants ◽  
The Us

scholarly journals Are American Indian/Alaska Native Adolescent Health Behaviors Different? A Review of AI/AN Youth Involved in Native STAND Curriculum, 2014–2017 United States

2021 ◽  
Author(s):  
Megan Skye ◽  
Stephanie Craig ◽  
Caitlin Donald ◽  
Allyson Kelley ◽  
Brittany Morgan ◽  
...  
Keyword(s):  
Health Behavior ◽  
Health Behaviors ◽  
Alaska Native ◽  
Suicide Attempts ◽  
Future Research ◽  
Chi Square ◽  
Sti Testing ◽  
The Us ◽  
Behavior Profiles ◽  
Health Profiles

Abstract Objectives To explore health behavior profiles of AI/AN youth involved in native students together against negative decisions (STAND), a national culture-based curriculum. Methods We analyzed data from 1236 surveys conducted among AI/AN youth at 40 native STAND implementation sites located in 16 states throughout the US from 2014 to 2017. Health profiles included demographics, sexual orientation, sexual activity, STI testing, cigarette use, and suicide attempts in the past 12-months. We used t-tests and chi square tests of independence to compare risk behavior prevalence among the sample. Results Health behavior profiles of AI/AN youth indicate that 45.6% of youth did not use condoms the last time they had sex, and 82.7% have never been tested for STIs. Differences in cigarette smoking were observed in questioning youth (questioning: 80.3%, straight/heterosexual: 63.8%, LGBTQ2S + : 49.9%, p = 0.03). Conclusions for Practice Health behaviors related to sex, substance, violence and self-harm, are at least as common for AI/AN youth as those observed in other US teens. Future research should consider similarities and differences in health profiles of AI/AN youth when designing interventions that affect them. Further, our findings underscore the need for culturally-relevant curricula like native STAND, not because their health behavior is different, but because their socio-ecologic environment is different.

scholarly journals Characterizing the US Population by Patterns of Mobile Health Use for Health and Behavioral Tracking: Analysis of the National Cancer Institute's Health Information National Trends Survey Data

10.2196/16299 ◽  
2020 ◽  
Vol 22 (5) ◽  
pp. e16299 ◽  
Author(s):  
Camella J Rising ◽  
Roxanne E Jensen ◽  
Richard P Moser ◽  
April Oh
Keyword(s):  
Health Behaviors ◽  
Health Information ◽  
Mobile Health ◽  
Technology Use ◽  
Older Age ◽  
Health Apps ◽  
Behavioral Tracking ◽  
The Us ◽  
Health Related ◽  
National Trends

Background Multiple types of mobile health (mHealth) technologies are available, such as smartphone health apps, fitness trackers, and digital medical devices. However, despite their availability, some individuals do not own, do not realize they own, or own but do not use these technologies. Others may use mHealth devices, but their use varies in tracking health, behaviors, and goals. Examining patterns of mHealth use at the population level can advance our understanding of technology use for health and behavioral tracking. Moreover, investigating sociodemographic and health-related correlates of these patterns can provide direction to researchers about how to target mHealth interventions for diverse audiences. Objective The aim of this study was to identify patterns of mHealth use for health and behavioral tracking in the US adult population and to characterize the population according to those patterns. Methods We combined data from the 2017 and 2018 National Cancer Institute Health Information National Trends Survey (N=6789) to characterize respondents according to 5 mutually exclusive reported patterns of mHealth use for health and behavioral tracking: (1) mHealth nonowners and nonusers report not owning or using devices to track health, behaviors, or goals; (2) supertrackers track health or behaviors and goals using a smartphone or tablet plus other devices (eg, Fitbit); (3) app trackers use only a smartphone or tablet; (4) device trackers use only nonsmartphone or nontablet devices and do not track goals; and (5) nontrackers report having smartphone or tablet health apps but do not track health, behaviors, or goals. Results Being in the mHealth nonowners and nonusers category (vs all mHealth owners and users) is associated with males, older age, lower income, and not being a health information seeker. Among mHealth owners and users, characteristics of device trackers and supertrackers were most distinctive. Compared with supertrackers, device trackers have higher odds of being male (odds ratio [OR] 2.22, 95% CI 1.55-3.19), older age (vs 18-34 years; 50-64 years: OR 2.83, 95% CI 1.52-5.30; 65+ years: OR 6.28, 95% CI 3.35-11.79), have an annual household income of US $20,000 to US $49,999 (vs US $75,000+: OR 2.31, 95% CI 1.36-3.91), and have a chronic condition (OR 1.69, 95% CI 1.14-2.49). Device trackers also have higher odds of not being health information seekers than supertrackers (OR 2.98, 95% CI 1.66-5.33). Conclusions Findings revealed distinctive sociodemographic and health-related characteristics of the population by pattern of mHealth use, with notable contrasts between those who do and do not use devices to track goals. Several characteristics of individuals who track health or behaviors but not goals (device trackers) are similar to those of mHealth nonowners and nonusers. Our results suggest patterns of mHealth use may inform how to target mHealth interventions to enhance reach and facilitate healthy behaviors.

Abstract MP62: The Role of Primary Care Physician Visits in Promoting Medication Adherence as Part of a Randomized Controlled Diabetes Management Intervention in American Samoa

Circulation ◽  
2013 ◽  
Vol 127 (suppl_12) ◽  
Author(s):  
Smriti Shivpuri ◽  
Shira Dunsiger ◽  
Andrew D Seiden ◽  
Rochelle K Rosen ◽  
Judith D DePue ◽  
...  
Keyword(s):  
Physical Activity ◽  
Primary Care ◽  
Medication Adherence ◽  
Health Behaviors ◽  
Diabetes Management ◽  
American Samoa ◽  
Care Physician ◽  
Management Intervention ◽  
Randomized Controlled ◽  
The Us

Background: The Native Hawaiian/Pacific Islander group is one of the fastest growing US ethnic groups, and Samoans make up the second largest Pacific Islander group in the US. Samoans are at a disproportionately high risk of type 2 diabetes mellitus (T2DM) and other cardiovascular disease risk factors, with prevalence rates of T2DM in adults in the US Territory of American Samoa around 20%, nearly double that of US Hispanics. A randomized, controlled trial of a community health worker (CHW)-facilitated diabetes management intervention in American Samoans with T2DM showed improved HbA1c levels in part through promoting health behaviors associated with diabetes management, including diet, physical activity, and most strongly, medication adherence. The current study sought to examine a potential intermediate variable through which the CHW intervention influenced health behaviors, in particular, whether the CHW intervention resulted in more frequent primary care physician (PCP) visits, which in turn, were associated with increased engagement in health behaviors. We also examined if relationships differed by baseline PCP utilization. Methods: Participants were 266 Samoan adults diagnosed with T2DM, randomized to the CHW intervention or wait-list control condition. Participants were additionally classified as meeting American Diabetes Association guidelines for PCP utilization at baseline (i.e., ≥4 PCP visits in the year prior to the intervention, “high utilizers”) or not (“low utilizers”). Regression models were used to examine the association between treatment assigned and frequency of PCP utilization, and whether PCP utilization was associated with the probability of engaging in diabetes management health behaviors (at least moderate intensity physical activity, healthy diet, medication adherence). Results: After adjustment for covariates including age, gender, and comorbidities, results indicate that CHW participants had greater rates of PCP visits over the intervention period, but only amongst low utilizers (RR = 1.94, 95% CI= 1.27, 2.97). A greater number of PCP visits, in turn, was associated with a higher odds of medication adherence (but not diet or physical activity), only amongst low utilizers (OR = 1.40, 95% CI= 1.12, 1.74). Conclusions: Results suggest that a CHW-facilitated diabetes intervention in the Samoan population may have promoted diabetes medication adherence (which has previously been associated with lower HbA1c in this cohort) by increasing the frequency with which participants encountered and interacted with their PCPs, specifically those participants in greatest need (i.e., those who had fewer PCP visits than recommended at baseline). Future research should further examine how increasing engagement with PCPs can serve as a mechanism through which to elicit behavior change in diabetic minority populations at high risk for cardiovascular disease.

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