Prevalence and comparison of select health behaviours among urban and rural residents: an Atlantic PATH cohort brief report

Transcription

1 Prevalence and comparison of select health behaviours among urban and rural residents: an Atlantic PATH cohort brief report Introduction Cynthia C. Forbes and Zhijie Michael Yu Research in developed countries indicates that rural residents generally have poorer health than those living in urban areas [1-4]. Rural residents have been shown to be more obese and have higher prevalence of chronic disease [1-4]. These differences in obesity may be due to health-related behaviours that influence body mass [1-4]. Literature also suggests that rural residents are more likely to be inactive, sedentary, have poor diets, smoking and drinking behaviour [1-4]. Approximately 19% of all Canadians are classified as rural; however, in Atlantic Canada, an average 46% of the population are considered rural (43% NS, 47% NB, 41% NL, and 53% PEI) [5]. Atlantic Canada has higher prevalence rates of poor health behaviours and chronic disease [6] when compared to Canadian averages. It is unclear what mechanisms may be responsible for these differences, but considering the suggestion that rural residents experience poorer health than urban residents, we felt this was a factor worth exploring. This research brief uses data from the Atlantic Partnership for Tomorrow Health (PATH) study to identify the characteristics and behaviours of urban/rural residents in all four provinces. We also examine any possible mediators of these behaviours between the urban/rural groups. The purpose of this brief is to 1) describe and compare the characteristics of urban/rural residents in terms of health behaviours and chronic disease status; 2) describe and compare the following

2 behaviours of urban/rural residents: physical activity level, time spent sitting, fruit intake, vegetable intake, fruit or vegetable juice intake, smoking, and alcohol consumption; and 3) identify any characteristics from purpose #1 that mediate behaviours in purpose #2 of urban/rural residents. We hypothesized that those designated as rural would have poorer health behaviours than those in urban areas. Methods Study Design This study is a cross-sectional analysis of the Atlantic PATH cohort, a population-based dataset which is part of the Canadian Partnership for Tomorrow Project [7]. Detailed methods were previously published [8]. Briefly, Atlantic PATH collected various sociodemographic factors, health status, medication use, diet, and physical activity information from 31,173 participants aged across all four Atlantic Provinces. Physical measurements of body composition and anthropometrics were measured by trained research nurses at assessment centres. This study includes data from 12,575 participants that have completed body composition measures and self-reported physical activity using the long form version of the International Physical Activity Questionnaire (IPAQ-LF) [9]. Measures Based on the completed self-report measures, average weekly physical activity (minutes) and average daily sitting time (hours) were computed. We also calculated metabolic equivalent minutes per week (MET-min/week) for physical activities at work and leisure-time, respectively, for each participant according to the IPAQ scoring protocol [10]. A Tanita bioelectrical impedance device (Tanita BC-418, Tanita Corporation of America Inc., Arlington Heights, Illinois) was used to measure body weight, percentage fat mass, fat mass, and fat free mass;

3 height was measured with a Seca stadiometer. Height and weight measures were used to calculate BMI (weight in kilograms divided by height in meters squared). We also calculated fat mass index (FMI) and fat free mass index (FFMI) by dividing fat mass and fat free mass in kilograms by height in meters squared, respectively. Select demographic variables were used to describe the sample. For analyses, categorical variables were collapsed into the smallest number of groups as follows: ethnicity (white/nonwhite), education (high school or lower/college level/university level or higher), marital status (married or living together/single, divorced, separated, or widowed), smoking behaviour (nonsmoker/former smoker/current smoker), and alcohol behaviour (abstainer/occasional drinker/regular drinker/habitual drinker). Chronic disease was determined as having self-reported any of the following: diabetes mellitus, cardiovascular disease (coronary heart disease and stroke), and cancer. A modified healthy eating index (HEI) score for each participant was calculated according to a previously developed protocol [8]. We utilized the Postal Code Conversion File Plus (PCCF+, version 6C, Statistics Canada), to classify study participants as living in urban or rural areas according to their reported residential postal code [11]. Analyses Multiple linear regression and logistic regression models were applied to explore differences in body adiposity measures, health behaviours, and chronic disease based on residence location. Model 1 was adjusted for age, sex, and province of residence; model 2 was further adjusted for ethnicity, education, marital status, HEI, smoking, alcohol use, chronic disease, BMI, and total physical activity as applicable [3]. Participants living in urban areas were chosen as the reference group.

4 Results A detailed description of both urban and rural groups can be found in Table 1. Briefly, approximately 35% of participants that were coded with PCCF+ were classified as rural residents. Multiple logistic regression analyses found that when compared to urban participants, rural residents were significantly less likely to be regular or habitual drinkers, be obese, and were significantly more likely to be highly active. Significant differences remained after further adjustment with potential confounding factors. Other common health behaviours did not differ significantly between urban and rural residents (Table 2). Differences in body composition can be found in Table 3. The fully adjusted analyses (Model 2) revealed that rural residents had significantly lower levels of percent body fat and FMI. Discussion This brief s aim was to describe and compare the health behaviours of Atlantic PATH participants based on urban or rural residency. We found that in general, participants living in a rural area engaged in more healthy behaviours than urban residents. Our results also showed lower levels of body adiposity among rural residents. These results are contrary to our hypothesis and much of the literature that suggests rural residents are less healthy in general than urban residents [1-4]. Studies using data from the US National Health and Nutrition Examination Survey (NHANES) found that obesity levels were higher among rural participants while physical activity levels were lower [1, 2, 4]. Another study among Australian adults found similar results [3]. It is unclear why the results of Atlantic PATH are contrary to these studies but a potential explanation may be the method used to assess physical activity. The IPAQ-LF measures multiple domains of activity including occupational, active transportation, household activity, and leisure-

5 time activity. Two of the US studies used self-report leisure-time activity only [1, 4], while the Australian study assessed total steps per day using a pedometer [3]. Using the total physical activity measure from the IPAQ-LF may explain the differences in our results. Fan and colleagues [2] compared self-reported measures and objective measures of total activity using an accelerometer. The accelerometer data shows rural participants were less active than urban residents; however, when subjective measures were used, rural residents reported more total physical activity than urban residents [2]. Similarly, it may be the case that rural residents are reporting activities as moderate or vigorous in nature when accelerometry classifies them as light activity. Even so, this would not change the other results indicating that rural Atlantic Canadians are engaging in more healthy behaviours and have more favourable body composition measures than urban residents. Additional research is needed to corroborate these results. Conclusions Contrary to previous research, rural residents in the Atlantic PATH cohort were generally healthier than the urban residents. Many of the measures examined, including alcohol consumption, physical activity levels, and multiple body adiposity assessments favoured the rural group. Additional research is necessary with more objective measures to determine whether this relationship holds true for physical activity levels.

6 References 1. Befort CA, Nazir N, Perri MG. Prevalence of Obesity Among Adults From Rural and Urban Areas of the United States: Findings From NHANES ( ). Journal of Rural Health. 2012;28(4): doi: /j x. 2. Fan JX, Wen M, Kowaleski-Jones L. Rural-urban differences in objective and subjective measures of physical activity: Findings from the National Health and Nutrition Examination Survey (NHANES) Preventing Chronic Disease. 2014;11. doi: /pcd Patterson KAE, Cleland V, Venn A, Blizzard L, Gall S. A cross-sectional study of geographic differences in health risk factors among young Australian adults: The role of socioeconomic position. BMC Public Health. 2014;14(1). doi: / Trivedi T, Liu J, Probst J, Merchant A, Jones S, Martin AB. Obesity and obesity-related behaviors among rural and urban adults in the USA. Rural and Remote Health. 2015;15(4). 5. Statistics Canada. Population, urban and rural, by province and territory (Nova Scotia) Accessed March Canadian Fitness and Lifestyle Research Insititute. Physical Activity of Canadians. Canadian Fitness and Lifestyle Research Institute sen.pdf. Accessed April Borugian MJ, Robson P, Fortier I, Parker L, McLaughlin J, Knoppers BM et al. The Canadian Partnership for Tomorrow Project: Building a pan-canadian research platform for disease prevention. CMAJ. 2010;182(11): doi: /cmaj

7 8. Yu ZM, Parker L, Dummer TJB. Depressive symptoms, diet quality, physical activity, and body composition among populations in Nova Scotia, Canada: Report from the Atlantic Partnership for Tomorrow's Health. Preventive Medicine. 2014;61: doi: /j.ypmed Craig CL, Marshall AL, Sjostrom M, Bauman AE, Booth ML, Ainsworth BE et al. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exer. 2003; IPAQ scoring protocol - International Physical Activity Questionnaire. Accessed February Saint-Jacques N, Dewar R, Cui Y, Parker L, Dummer TJB. Premature mortality due to social and material deprivation in Nova Scotia, Canada. International Journal for Equity in Health. 2014;13(1). doi: /s

8 Table 1. Characteristics of study participants a Urban (n=8189) Rural (n=4386) Age, yr 53.4 (8.9) 54.2 (8.6) Female, n, (%) 5700 (69.6) 3143 (71.7) Province, n (%) Nova Scotia 5869 (71.7) 3060 (69.8) New Brunswick 1406 (17.2) 930 (21.2) Newfoundland and Labrador 843 (10.3) 343 (7.8) Prince Edward Island 71 (0.9) 53 (1.2) Ethnicity, n (%) White 7456 (91.0) 3959 (90.3) Non-white 432 (5.3) 215 (4.9) DNK/PNA 301 (3.7) 212 (4.8) Education, n (%) Less than high school 1219 (14.9) 936 (21.3) College level 3027 (37.0) 1937 (44.2) University level or higher 3924 (47.9) 1498 (34.2) DNK/PNA 19 (0.2) 15 (0.3) Marital status, n (%) Married or living together 6321 (77.2) 3777 (86.1) Single, divorced, separated, or widowed 1855 (22.7) 602 (13.7) DNK/PNA 13 (0.2) 7 (0.2) Smoking status, n (%) Never 4253 (51.9) 2221 (50.6) Former 3209 (39.2) 1774 (40.4) Current 677 (8.3) 352 (8.0) DNK/PNA 50 (0.6) 39 (0.9) Alcohol drinking, n (%) Abstainer 729 (8.9) 505 (11.5) Occasional drinker 3281 (40.1) 1824 (41.6) Regular drinker 2590 (31.6) 1245 (28.4) Habitual drinker 1445 (17.6) 702 (16.0) DNK/PNA 144 (1.8) 110 (2.5) Chronic disease b, yes, n (%) 909 (11.1) 517 (11.8) Physical activity level, n (%) Inactive 4828 (60.8) 2407 (56.8) Low active 1197 (15.1) 601 (14.2) Active 914 (11.5) 528 (12.5) Very active 1008 (12.7) 704 (16.6) Total physical activity, MET-hr/week 5135 (4563) 5737 (4933) Body weight, kg 75.6 (15.7) 74.9 (14.8) Body height, cm (7.7) (7.4) Body mass index, kg/m (5.0) 27.0 (4.7) Percentage fat mass, % 32.5 (8.7) 32.4 (8.2) Fat mass index, kg/m (3.7) 8.9 (3.4) Fat free mass index, kg/m (2.9) 18.1 (2.8) Occupational activity, MET-hr/week 1356 (3263) 1674 (3685) Leisure time activity, MET-hr/week 3695 (3687) 4232 (3982) Healthy eating index score 38.9 (9.0) 39.4 (8.8) Fruit intake, serving/day 2.1 (1.4) 2.1 (1.3) Vegetable intake, serving/day 2.5 (1.6) 2.6 (1.5)

9 100% fruit or vegetable juice intake, serving/day 0.7 (1.0) 0.7 (1.0) Sitting time, hr/day 5.7 (2.8) 5.2 (2.7) DNK=do not know; PNA=prefer not to answer. a Data are means (standard deviation) and number of participants (percentage). b Self-reported diabetes mellitus, cardiovascular disease (coronary heart disease and stroke), and cancer.

10 Table 2. Differences in the prevalence of selected behavioral factors, obesity, and chronic disease between participants living in urban and rural areas ORs (95% CIs) Case/n Urban Case/n Rural Current smoker Model 1 677/8189 Reference 352/ (0.86, 1.13) Model 2 a Reference 0.96 (0.84, 1.11) Regular or habitual alcohol drinker Model /8189 Reference 1947/ (0.77, 0.89) Model 2 b Reference 0.82 (0.76, 0.89) High physical activity Model /8189 Reference 1618/ (1.15, 1.34) Model 2 c Reference 1.26 (1.16, 1.37) Obesity Model /8189 Reference 1058/ (0.82, 0.98) Model 2 d Reference 0.89 (0.81, 0.97) Chronic disease Model 1 909/8189 Reference 517/ (0.91, 1.15) Model 2 e Reference 1.00 (0.89, 1.13) Model 1, adjusted for age, sex, and province. Model 2 a, further adjusted for ethnicity, education, marital status, healthy eating index, alcohol use, chronic disease, BMI, and total physical activity based on model 1. Model 2 b, further adjusted for ethnicity, education, marital status, healthy eating index, smoking, chronic disease, BMI, and total physical activity based on model 1. Model 2 c, further adjusted for ethnicity, education, marital status, healthy eating index, smoking, alcohol use, chronic disease, BMI, and active commuting (yes/no) based on model 1. Model 2 d, further adjusted for ethnicity, education, marital status, healthy eating index, smoking, alcohol use, chronic disease, and total physical activity based on model 1. Model 2 e, further adjusted for ethnicity, education, marital status, healthy eating index, smoking, alcohol use, chronic disease, BMI, and total physical activity based on model 1.

11 Table 3. Differences in body adiposity measures between participants living in urban and rural areas β coefficients (95% CIs) Body adiposity measures Urban (n=8189) Rural (n=4386) BMI, kg/m 2 Model 1 Reference (-0.30, 0.05) Model 2 Reference (-0.32, 0.03) Percentage body fat, % Model 1 Reference (-0.56, 0.02) Model 2 Reference (-0.63, -0.04) Fat mass index, kg/m 2 Model 1 Reference (-0.30, -0.04) Model 2 Reference (-0.32, -0.06) Model 1, adjusted for age, sex, and province. Model 2, further adjusted for ethnicity, education, marital status, smoking, alcohol use, chronic disease, healthy eating index, and total physical activity based on model 1.