You Won’t Believe the Startling Racial and Ethnic Disparities in Physical Activity Among Mothers of Young Children!

study sample

Secondary data analysis was conducted using data from the 2011-2012, 2013-2014, 2015-2016, and 2017-2018 US National Health and Nutrition Examination Survey (NHANES 2011-18). NHANES is a national survey that includes a representative sample of the US population using a complex staged sampling method. NHANES consists of two components: an interview and an exam. The NHANES face-to-face interview took place in the participant’s home. The NHANES exam was conducted at the Mobile Examination Center (MEC). The 2011-18 NHANES cycles were approved by the Ethics Review Board of the National Center for Health Statistics (protocol #2011-17 and protocol #2018-01).

For this secondary data analysis, we identified 5,111 female participants between the ages of 20 and 45 from the 2011-18 NHANES data sets. This age range was selected to include the majority of adult YC mothers, considering the age range for reproductive years among US women giving birth. [14]. Among the 5,111 women, we excluded 219 (3.9%) who self-identified as multiracial or races other than Asian, Black, Hispanic, or White, resulting in 4,892 women for data analysis. We did not exclude women who reported being pregnant (n = 247), because PA is recommended even during pregnancy; at least 150 min of moderate intensity AF per week [2].

measurements

Exposure: Type of children living in the same household. During the interview, a demographic survey was administered that included questions about the total number of YC living in the same household and the total number of children aged 6-17 years and older (OC) living in the same household with the participant. However, it did not ask about relationships (eg, child, relative) between the participant and other household members. Therefore, adopting the approach used by Adamo et al. [15], we defined women who reported at least one YC and no OC living in the same household (women with YC, hereinafter) as mothers of YC. In the same way, we defined OC mothers as women who reported at least one OC and no OC living in the same household (women with OC, hereinafter). Women who reported that both YC and OC lived in the same household (women with YC and OC, hereafter) were defined as mothers of YC and OC. Women who reported that they did not have children 17 years of age or younger living in the same household (childless women, hereinafter) served as the comparison group. As a result, the variable for the type of children living in the same household had four categories: no children, YC, OC, and YC and OC (YC + OC).

Moderator: Racial and ethnic background. The demographic survey asked participants to identify their Hispanic origin (Hispanic or non-Hispanic) and their race. Those who self-identified as of Hispanic origin were classified as Hispanic, regardless of race. Those who self-identified as of non-Hispanic origin were classified as Asian, Black, White, and Multiracial or Other based on their racial response. The multiracial or other race group was excluded from this study.

Result: physical activity. Among the physical activity domains, this study focused on transportation and leisure-time physical activity, but not on occupational physical activity or household chores. Occupational physical activity was excluded to align with the US Centers for Disease Control and Prevention (CDC) report that assessed the national prevalence of physical inactivity out of work [16]. Furthermore, taking into account the development of future interventions, occupational physical activity is less modifiable compared to transportation and leisure-time physical activity. BP was not considered in household tasks because it was not assessed in the NHANES PA 2011-18 questionnaire (PAQ).

During the interview, a PAQ was administered. The PAQ asked about the frequencies and durations of occupational, transportation, and leisure-time physical activity in a typical week. For transportation PA, participants were asked: “In a typical week, on how many days do you walk or bike for at least 10 minutes at a time to get to and from places?”; and “How much time do you spend walking or biking to commute in a typical day?” For leisure-time physical activity, questions about participation in vigorous-intensity and moderate-intensity physical activity were asked separately: “In a typical week, on how many days do you do vigorous-intensity sports, physical activity, or recreational activities? ; “How much time do you spend doing vigorous-intensity sports, physical activity, or recreational activities on a typical day?”; “In a typical week, on how many days do you do moderate-intensity sports, physical activity, or recreational activities that cause a small increase in breathing or heart rate, such as brisk walking, biking, swimming, or playing volleyball for at least 10 minutes straight? ?”; and “How much time do you spend doing moderate-intensity sports, fitness, or recreational activities on a typical day?”

Minutes (min/week) of weekly moderate and vigorous intensity transport PA (MVPA) were calculated by multiplying the frequency (days/week) and duration (min/day) of PA transport. Weekly MVPA minutes of leisure time (minutes/week) were calculated by adding weekly minutes of leisure-time vigorous-intensity physical activity and weekly minutes of leisure-time moderate-intensity physical activity. Weekly transportation MVPA minutes and weekly free time MVPA minutes were added together to calculate total weekly MVPA minutes. Physical inactivity was defined as participating in zero minutes of general MVPA in a typical week.

Confusing factors. We considered the following potential confounders: age in years, marital status, education, employment, pregnancy status, family income, and body mass index (BMI). During the interview, the demographic survey asked about age in years, marital status (categorized as married, living with partner, and widowed/divorced/separated/never married), education level (categorized as ≤ high school graduate, some college or Associate of Arts and ≥ college graduate), employment (categorized as employed and unemployed), pregnancy status (categorized as pregnant, not pregnant, and unknown), household income, and family size. A poverty ratio ratio, a ratio of household income to poverty, based on family size and income, was calculated and then classified as < 1.0 (below the current US poverty level). .; low income), 1 to < 3.0 (middle income) and ≥ 3.0 (high income). Anthropometric assessments (height and weight) were performed at the MEC. BMI was calculated as weight (kg) divided by height squared (m²) and categorized as < 25, 25 to < 30 and ≥ 30 kg/m².

statistic analysis

All analyzes were performed using the SAS 9.4 survey procedure (Cary, NC), taking into account complex sample design such as weighting and clustering. Descriptive analyses, including distribution analyses, were performed for all study variables. No missing data were found for any of the study variables, except for the categories of household income and BMI which were treated with a median imputation method: those with missing data for the poverty index (n = 444; 10%) were assigned to the middle income category, and those with missing data for BMI (n = 236; 5%) were assigned to the middle category, 25 to < 30 kg/m². The means and proportions of the FA variables were compared between women living with YC and without children in each of the four racial and ethnic groups, using 95% confidence intervals (CI).

Multivariate logistic regression analyzes, stratified by racial and ethnic groups, were performed to compare the likelihood of physical inactivity by type of children living in the same household (reference: no children group) within each racial and ethnic group. In the regression analyses, we included the following confounding factors as predictors: age in years, marital status, education level, employment, poverty rate category, and BMI category. Odds ratios (OR) and 95% CIs were obtained from logistic regression models. In the sensitivity analysis, the multivariable logistic regression analysis was repeated following the steps described above but excluding the participants who were pregnant. We also repeated the analysis excluding those with missing data for the poverty index or BMI to assess the impacts of the imputations on the results of the regression analysis. To explore a dose-response relationship between the number of children living in the household and physical inactivity, an exploratory analysis was performed using the number of YC (0, 1, or ≥ 2) and the number of OC (0, 1, or ≥ 2) at home as predictors in multivariate logistic regression models. To explore the effects of immigration status, a logistic regression analysis was performed, additionally including the variable immigration status, identified by place of birth (born abroad vs. born in the United States).

Among those who reported participating in at least one minute of MVPA in a typical week, multivariable linear regression analyzes stratified by racial and ethnic groups were performed to compare weekly minutes of MVPA by type of children living in the same household (group reference: no children). Because the distribution of the weekly MVPA minutes variable showed a long tail on the right side due to outliers, values ​​above the 99th percentile (>720 min) were recoded as 720 min to improve the distribution. These linear regression analyzes included the same set of predictors as the multivariable logistic regression analyzes described above. A significance level of 0.05 (bilateral) was set.