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Data were analysed using SPSS TM Version Logistic regression was used to examine the relationship between PLB score, self-rated health, probable depressive disorder and obesity levels after adjusting for age, sex, education and social class.
Additionally, we examined the relationship between PLB score and past diagnoses of medically diagnosed chronic illness. Table 1 shows a breakdown of the relevant participant characteristics differentiated by gender.
Higher proportions of women were of normal weight and consumed five or more daily servings of fruit and vegetables compared with men. Men were more likely to be smokers, to consume more alcohol and to be physically active compared with women.
Women were more likely to have adopted more of the PLBs. Table 2 shows the age, gender, social demographic profile and the distribution of key outcome variables in five groups of study participants defined on the basis of number of PLBs.
Clear and highly significant trends were seen for age, gender, education and social classification status. Distribution of variables for SLÁN participants included in this analysis participants who did not complete a FFQ were excluded from the analysis.
Demographic breakdown by number of protective lifestyle behaviours practised. The association between PLB score, self-rated health, healthy weight and better mental health adjusted for age, sex, education and social class is shown in table 3.
For self-rated health and depressive state, clear and highly significant trends in odds ratios were observed across the five groups of study participants. These trends were not as obvious for body weight. These trends persisted even when the model was adjusted for depressive disorders.
Those with four PLBs were also four times more likely to have better mental health [OR 4. Higher scores were also less likely to be associated with being diagnosed with a cardiovascular event and being diagnosed with any illness by a doctor in the last 12 months.
While our results are congruent with the work by Khaw et al. However, this is similar to response rates seen in other major National Health and Lifestyle Surveys.
Unfortunately, data on non-participation are not available. However, sample weights were used derived from the most recent Census. It can be argued that persons with better than average self-rated health and better mental health are more likely to engage in health seeking behaviour.
The issue of reverse causation cannot be resolved in this study; however, it is likely that the causal effects of these health seeking behaviours flow in both directions are mutually beneficial: better mental health and better self-rated health leading to increased health seeking behaviours and vice versa.
What is clear is that there is no evidence to suggest that the presence of health seeking behaviours is associated with poorer mental health and well-being. A key challenge for future research is to better understand the individual and societal determinants of health-seeking behaviour.
For instance, there is emerging data highlighting the importance of adverse childhood experiences as a determinant of health-related behaviour in adult life. Given the association between self-rated health, better mental health and higher numbers of PLBs, we propose that the four lifestyle behaviours detailed in this article be used as outcome measures from which effectiveness of public health policy can be gauged.
Being a non-smoker, being physically active, having a moderate alcohol intake and consuming five portions of fruit and vegetables daily are associated with better self-rated health, better mental health and a healthier weight. We would propose that the four lifestyle behaviours detailed in this article be used as outcome measures from which effectiveness of public policy can be gauged.
The authors thank other SLÁN Consortium members for their contribution to this research. Consortium members: Professor Hannah McGee Project Director RCSI , Professor Ivan Perry PI UCC , Professor Margaret Barry PI NUIG , Dr.
Dorothy Watson PI ESRI , Dr Karen Morgan Research Manager, RCSI , Dr. Emer Shelley RCSI , Professor Ronan Conroy RCSI , Professor Ruairí Brugha RCSI , Dr. Michal Molcho NUIG , Ms. Janas Harrington UCC and Professor Richard Layte ESRI , Ms Nuala Tully RCSI , Ms Jennifer Lutomski UCC , Mr Mark Ward RCSI and Mr Eric Van Lente NUIG.
Also Jan van den Broeck for his helpful comments during the drafting of the paper. SLÁN was approved by the Ethics Committee of the Royal College of Surgeons of Ireland. Google Scholar. Google Preview. Oxford University Press is a department of the University of Oxford.
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Abstract Background: The combination of four protective lifestyle behaviours being physically active, a non-smoker, a moderate alcohol consumer and having adequate fruit and vegetable intake has been estimated to increase life expectancy by 14 years. lifestyle behaviours , self-rated health , obesity , depression , protective factors.
Table 1 Distribution of variables for SLÁN participants included in this analysis participants who did not complete a FFQ were excluded from the analysis. Mean SD. Age years — of protective lifestyle behaviours 0 54 2. a: Smoker was classified as someone who smokes either everyday or some days.
Open in new tab. Table 2 Demographic breakdown by number of protective lifestyle behaviours practised. Number of protective behaviours. P -value. Gender Male 85 Not having depressive disorder vs. depressive disorder. Odds ratio. Key points. Combined impact of health behaviours and mortality in men and women: the EPIC-Norfolk prospective population study.
Google Scholar Crossref. Search ADS. The Multiple Risk Factor Intervention Trial MRFIT —Importance then and now. Is relationship between serum cholesterol and risk of premature death from coronary heart disease continuous and graded?
Several studies 16 - 18 have reported trends of overall lifestyle among US adults prior to , but no study has reported trends of overall lifestyle during the past decade since To address these gaps, we used the recently released data from the National Health and Nutrition Examination Survey NHANES to examine trends in multiple lifestyle factors as well as combined healthy lifestyle factors among US adults from the cycle to the combined cycle from to March The NHANES is a series of cross-sectional surveys with a complex, multistage probability sample design conducted by the National Center for Health Statistics NCHS to obtain health-related information about the civilian noninstitutionalized population in the US.
Details of the study design, protocol, and data collection have been described elsewhere. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology STROBE reporting guideline.
In the present analyses, we included adults 20 years or older who had complete data for smoking, alcohol consumption, diet, physical activity, and BMI from the cycle through the to March cycle. In the main analysis, we only used the first hour dietary recall data to evaluate diet quality and did not use the second hour dietary recall, which was available since the cycle.
This was mainly because distributions of dietary intake were not comparable from single vs multiple dietary recalls, 22 and the survey method was different between the first dietary recall in-person and second recall telephone.
Data were collected during the household interview and a study visit in the mobile examination center MEC. This information was collected to report current status and changes in prevalence of lifestyle factors by race and ethnicity.
In line with a previous study conducted in the NHANES, 16 we included 5 lifestyle factors: smoking, alcohol consumption, diet quality, physical activity, and BMI.
Information on smoking was obtained by questions about whether the participant smoked at least cigarettes in life, whether they smoked at the time of the survey, and numbers of cigarettes, pipes, or cigars smoked during the past 30 days.
Alcohol consumption was assessed by self-reported drinking frequency and drinking quantity over the past year. Diet information was assessed using one hour dietary recall conducted in person in the MEC. In the dietary recall interview, the participant reported all foods and beverages consumed during the prior 24 hours.
For physical activity, the questionnaire changed from a specific Physical Activity and Physical Fitness Questionnaire before the cycle to the Global Physical Activity Questionnaire thereafter. Both questionnaires accessed the duration of physical activity from different domains. Briefly, the former assessed minutes of physical activity during the past 30 days from the household, transportation, and moderate to vigorous leisure time; the latter measured minutes of physical activity in a typical week from moderate to vigorous work, transportation, and moderate to vigorous leisure time.
Body weight and height were measured using a digital weight scale and a fixed stadiometer respectively, following standard procedures eg, wearing requirement and standing posture at the MEC. Details of the measurements of the 5 lifestyle factors can be found elsewhere.
The primary outcomes were 5 lifestyle factors and combined healthy lifestyle factors. To capture more detailed information in lifestyle factors, individual lifestyle factors were first classified into multiple levels.
Physical activity from the household and transportation was defined as moderate activity according to the NHANES guidelines. For each healthy lifestyle factor, the participant who met the criterion for a healthy level received a score of 1; others received 0.
The healthy lifestyle score was defined as the sum of all 5 scores and ranged from 0 to 5, with higher scores indicating healthier lifestyle. Since the number of participants with the highest lifestyle score was small across the 10 cycles ranging from 96 to eTable 2 in Supplement 1 , participants with 4 or 5 healthy lifestyle factors were combined into 1 group and defined as having a healthy lifestyle.
Secondary outcomes were trends in 5 healthy lifestyle factors and healthy lifestyle by major sociodemographic subgroups age, sex, race and ethnicity, educational level, and income assessed by standardized questionnaires.
The subgroups were chosen since previous research in US adults documented the co-occurrence of healthy lifestyle factors among sociodemographic strata.
In all analyses, survey procedures were used to account for dietary sample weights, 37 stratification, and clustering of the complex sampling design to ensure nationally representative estimates. Characteristics of participants by different cycles were presented as numbers percentages for categorical variables and compared using the Rao-Scott χ 2 test.
Absolute differences in weighted prevalence were calculated between the first and the last cycle. P values for interactions were further adjusted with Benjamini—Hochberg false discovery rate FDR correction. In sensitivity analyses, to further incorporate the data of 2 dietary recalls since the cycle, trends in diet quality were assessed in adults with 2 valid recalls between the cycle and the to March cycle.
Similarly, due to the change in the physical activity questionnaire since the cycle, trends in physical activity were accessed separately from the to cycles and from the cycle to the to March cycle.
All analyses were conducted with SAS, version 9. Of the 47 US adults included in the analyses, the weighted mean SE age was In terms of race and ethnicity, weighted proportion, 8. Significant differences were observed in the distribution of participants by age and educational level groups over time Table 1.
Divergent trends were observed among 5 healthy lifestyle factors Figure 1 A. From the to the to March cycles, the estimated prevalence of never smoking increased from During this period, the estimated prevalence of moderate or lighter alcohol consumption remained stable from In addition, the cycle had the highest prevalence of healthy diet In sensitivity analyses, a similar increase in healthy diet based on 2 diet recalls was observed from the cycle to the to March cycle eTable 3 in Supplement 1 , and increases in sufficient physical activity remained consistent from the to cycles and from the to the to March cycles eTable 4 in Supplement 1.
Moreover, the adjustment of age or all sociodemographic characteristics did not alter the results eTable 5 in Supplement 1. Trends in the prevalence of multiclass lifestyle factors are shown in Table 2 and eTable 4 in Supplement 1.
From the to the to March cycles, improvements were observed in overall lifestyle Figure 1 B. The trend in healthy lifestyle was largely consistent after the adjustment for age or all sociodemographic characteristics eTable 6 in Supplement 1.
Trends in healthy lifestyle across subgroups are shown in Figure 2 and eTable 7 in Supplement 1. From the to the to March cycles, a greater change in healthy lifestyle was observed among younger vs older adults.
The estimated prevalence of healthy lifestyle increased among young adults aged 20 to 34 years difference, 8. In addition, there were no significant trends among groups with relatively high prevalence, including non-Hispanic White adults and adults with the highest income level.
Trends in individual healthy lifestyle factors across subgroups appear in eTables 8 to 13 in Supplement 1. Among adults 65 years or older, the estimated prevalence of never smoking and healthy diet was not significantly changed, and with a significant decrease in healthy weight.
From the to the to March cycles, increases were observed in never smoking, healthy diet, and sufficient physical activity, but a decrease in healthy weight was also observed.
Meanwhile, there was no significant change in moderate or lighter alcohol consumption. An improvement in healthy lifestyle was identified, with widening disparity by age group and persistent disparities by race and ethnicity, educational level, and income level.
However, similar to the present findings, both studies indicated relatively low prevalence and small net change. The increase in healthy diet is consistent with prior reports 11 , 22 that observed improvements in the American Heart Association diet score from to and the mean of HEI during to However, the improvement in healthy diet mainly accumulated before the cycle; the exact reasons were unclear, and future studies are needed.
In a diverse population, physical activity domains other than the leisure-time domain ie, occupation, household, and transportation could be important sources of physical activity level. Although the increase in obesity appeared to slow down or level off during to , 46 studies covering more recent years or a longer period still observed a significant increase.
To the best of our knowledge, the present study provides the most comprehensive evaluation of trends in lifestyle factors in the past 22 years. The increase in healthy lifestyle during the year study period was not consistent with the trends reported between and , when the prevalence of healthy lifestyle showed significant declines or little net change.
Our study observed widened disparity in healthy lifestyle by age group with relatively stable prevalence in healthy lifestyle among adults 65 years and older. The smaller improvement in lifestyle among old adults was reflected in no significant change in never smoking and healthy diet with a decrease in healthy weight.
Weight gain among old adults was associated with higher all-cause mortality in 2 meta-analyses, 55 , 56 and further studies are still needed to explain the weight gain among old adults given that skeletal muscle declines already happen in old adults.
Nevertheless, this study has several limitations. First, data about smoking, alcohol consumption, diet, and physical activity were self-reported and subjected to recall bias. However, the bias might be minimized through trained interviewers and computer-assisted personal interview systems.
Second, only 1 valid dietary recall was used in our main analyses. However, we further evaluated the trend in diet quality using 2 dietary recalls and observed similar results.
Third, as described, the physical activity questionnaire had changed to Global Physical Activity Questionnaire since the cycle. However, we used sufficient physical activity to construct the healthy lifestyle score, and the consistent increases in sufficient physical activity for the and the to March cycles provide some support for a modest effect of this change.
Fourth, the lifestyle score was derived from the number of healthy lifestyle factors, which may not reflect the unequal effect of individual healthy lifestyle factors. In this cross-sectional study from to March , we observed different change patterns across 5 healthy lifestyle factors and a modest improvement in overall lifestyle among US adults.
Medical care alone is not enough to improve health overall 61 ; preventive care is an indispensable component. Changes in food, physical, and policy environments are still needed to improve lifestyle, with attention on old adults and persistent disparity in healthy lifestyle by race and ethnicity and socioeconomic levels.
Future studies are warranted to validate our results using other US national surveys. Published: July 14, Open Access: This is an open access article distributed under the terms of the CC-BY License. JAMA Network Open.
Corresponding Author: Zhilei Shan, MD, PhD zhileishan hust. cn and An Pan, PhD panan hust. cn , School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan , China.
Author Contributions: Drs Shan and Pan had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Messrs Li and Xia contributed equally to this work. Acquisition, analysis, or interpretation of data: Li, Xia, Geng, Tu, Y. Zhang, Yu, J. Zhang, Guo, Yang, Liu, Pan. Critical revision of the manuscript for important intellectual content: All authors.
Conflict of Interest Disclosures: None reported. Dr Liu was supported by grants and from the National Natural Science Foundation of China, grant CFA from the Hubei Province Science Fund for Distinguished Young Scholars, and grant GCRC from the Fundamental Research Funds for the Central Universities.
Data Sharing Statement: See Supplement 2. full text icon Full Text. Download PDF Comment. Top of Article Key Points Abstract Introduction Methods Results Discussion Conclusions Article Information References.
Figure 1. Trends in Estimated Prevalence of Healthy Lifestyle Factors Among US Adults 20 Years or Older, to March View Large Download.
Figure 2. Table 1. Characteristics of US Adults 20 Years or Older, to March Table 2. Crude Trends in Estimated Prevalence of Lifestyle Factors Among US Adults 20 Years or Older, to March Supplement 1.
Healthy Eating Index— Components, Component Points, and Scoring Standards eTable 2. Number of Participants According to the Number of Healthy Lifestyle Factors Among US Adults 20 Years or Older, to March eTable 3. Crude Trends in Estimated Prevalence of Healthy Eating Index— Among US Adults 20 Years or Older, to March eTable 4.
Crude Trends in Estimated Prevalence of Physical Activity Among US Adults 20 Years or Older, to and to March eTable 5. Adjusted Trends in Estimated Prevalence of Healthy Lifestyle Factors Among US Adults 20 Years or Older, to March eTable 6.
Adjusted Trends in Estimated Prevalence of Healthy Lifestyle Among US Adults 20 Years or Older, to March eTable 7. Crude Trends in Estimated Prevalence of Healthy Lifestyle by Age Group, Sex, Race and Ethnicity, Educational Level, and Income, to March eTable 8.
Crude Trends in Estimated Prevalence of Never Smoking by Age Group, Sex, Race and Ethnicity, Educational Level, and Income, to March eTable 9.
Crude Trends in Estimated Prevalence of Moderate or Lighter Alcohol Consumption by Age Group, Sex, Race and Ethnicity, Educational Level, and Income, to March eTable Crude Trends in Estimated Prevalence of Healthy Diet by Age Group, Sex, Race and Ethnicity, Educational Level, and Income, to March eTable Crude Trends in Estimated Prevalence of Sufficient Physical Activity by Age Group, Sex, Race and Ethnicity, Educational Level, and Income, to eTable Crude Trends in Estimated Prevalence of Sufficient Physical Activity by Age Group, Sex, Race and Ethnicity, Educational Level, and Income, to March eTable Supplement 2.
Data Sharing Statement. World Health Organization. Accessed February 27, Zhang Y, Pan XF, Chen J, et al. Combined lifestyle factors and risk of incident type 2 diabetes and prognosis among individuals with type 2 diabetes: a systematic review and meta-analysis of prospective cohort studies.
doi: Zhang YB, Pan XF, Chen J, et al. Combined lifestyle factors, all-cause mortality and cardiovascular disease: a systematic review and meta-analysis of prospective cohort studies.
PubMed Google Scholar. Combined lifestyle factors, incident cancer, and cancer mortality: a systematic review and meta-analysis of prospective cohort studies.
Li Y, Pan A, Wang DD, et al. Impact of healthy lifestyle factors on life expectancies in the US population. Li Y, Schoufour J, Wang DD, et al. Healthy lifestyle and life expectancy free of cancer, cardiovascular disease, and type 2 diabetes: prospective cohort study.
l PubMed Google Scholar Crossref. Creamer MR, Wang TW, Babb S, et al. Tobacco product use and cessation indicators among adults—United States, mma2 PubMed Google Scholar Crossref.
Agaku IT, Odani S, Okuyemi KS, Armour B. Disparities in current cigarette smoking among US adults, PubMed Google Scholar Crossref. Grucza RA, Sher KJ, Kerr WC, et al. Trends in adult alcohol use and binge drinking in the early 21st-century United States: a meta-analysis of 6 national survey series.
Kanny D, Naimi TS, Liu Y, Brewer RD. Trends in Total Binge Drinks per Adult Who Reported Binge Drinking - United States, Shan Z, Rehm CD, Rogers G, et al. Trends in dietary carbohydrate, protein, and fat intake and diet quality among US adults, Du Y, Liu B, Sun Y, Snetselaar LG, Wallace RB, Bao W.
Trends in adherence to the physical activity guidelines for Americans for aerobic activity and time spent on sedentary behavior among US adults, to Centers for Disease Control and Prevention.
Hales CM, Fryar CD, Carroll MD, Freedman DS, Ogden CL. Trends in obesity and severe obesity prevalence in US youth and adults by sex and age, to Ogden CL, Fryar CD, Martin CB, et al. Trends in obesity prevalence by race and Hispanic origin— to King DE, Mainous AG III, Carnemolla M, Everett CJ.
Adherence to healthy lifestyle habits in US adults, Ford ES, Li C, Zhao G, Pearson WS, Tsai J, Greenlund KJ. Trends in low-risk lifestyle factors among adults in the United States: findings from the Behavioral Risk Factor Surveillance System Troost JP, Rafferty AP, Luo Z, Reeves MJ.
Temporal and regional trends in the prevalence of healthy lifestyle characteristics: United States, National Center for Health Statistics. NHANES survey methods and analytic guidelines. aspx sample-design. NHANES March pre-pandemic. Accessed May 23, NHANES response rates and population totals.
Rehm CD, Peñalvo JL, Afshin A, Mozaffarian D. Dietary intake among US adults, Moshfegh AJ, Rhodes DG, Baer DJ, et al.
Thank you HHealthy visiting nature. You are using Hydration and sports for older adults browser version Effective weight loss limited support for CSS. To obtain the ilfestyle experience, we recommend lifestype use Healthy lifestyle journal more up to date browser or turn off compatibility mode in Internet Explorer. In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. Rather than engineering consciously or unconsciously physical activity out of the lifestyle of youngsters and perpetuating an inactive phenotype and its attendant health consequences, we should assert the benefits of nutrition and physical activity for the growing child more aggressively. Crude trends in prevalence of healthy lifestyle factors Lifrstyle and changes in estimated Anti-aging diet of specific lifestyls of healthy Calcium and diabetes factors B are Calcium and diabetes. Data were adjusted for National Health and Nutrition Examination Survey survey weights. Heathy lifestyle was defined as 4 or 5 healthy lifestyle factors. Data were adjusted for National Health and Nutrition Examination Survey NHANES survey weights. FDR indicates false discovery rate. eTable 1. Healthy Eating Index— Components, Component Points, and Scoring Standards.
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