Next Article in Journal
Cluster-Based Ensemble Learning Model for Aortic Dissection Screening
Next Article in Special Issue
Alleviating Doctors’ Emotional Exhaustion through Sports Involvement during the COVID-19 Pandemic: The Mediating Roles of Regulatory Emotional Self-Efficacy and Perceived Stress
Previous Article in Journal
Pet Ownership and Mental and Physical Health in Older White and Black Males and Females
Previous Article in Special Issue
Effects of Montmorency Tart Cherry and Blueberry Juice on Cardiometabolic and Other Health-Related Outcomes: A Three-Arm Placebo Randomized Controlled Trial
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
IJERPH
Volume 19
Issue 9
10.3390/ijerph19095656
ijerph-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

A Cross-Sectional Study on Self-Perceived Health and Physical Activity Level in the Spanish Population

by
Ángel Denche-Zamorano
1,
María Mendoza-Muñoz
2,3,*,
Jorge Carlos-Vivas
4,*,
Laura Muñoz-Bermejo
5,
Jorge Rojo-Ramos
5,
Raquel Pastor-Cisneros
4,
Frano Giakoni-Ramírez
6,
Andrés Godoy-Cumillaf
7 and
Sabina Barrios-Fernandez
5
1
Health Economy Motricity and Education (HEME), Faculty of Sport Sciences, University of Extremadura, 10003 Caceres, Spain
2
Research Group on Physical and Health Literacy and Health-Related Quality of Life (PHYQOL), Faculty of Sport Sciences, University of Extremadura, 10003 Caceres, Spain
3
Departamento de Desporto e Saúde, Escola de Saúde e Desenvolvimento Humano, Universidade de Évora, 7004-516 Évora, Portugal
4
Promoting a Healthy Society Research Group (PHeSO), Faculty of Sport Sciences, University of Extremadura, 10003 Caceres, Spain
5
Social Impact and Innovation in Health (InHEALTH), University of Extremadura, 10003 Caceres, Spain
6
Faculty of Education and Social Sciences, Universidad Andres Bello, Las Condes, Santiago 7550000, Chile
7
Grupo de Investigación en Educación Física, Salud y Calidad de Vida, Facultad de Educación, Universidad Autónoma de Chile, Temuco 4780000, Chile
*
Authors to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2022, 19(9), 5656; https://doi.org/10.3390/ijerph19095656
Submission received: 30 March 2022 / Revised: 29 April 2022 / Accepted: 4 May 2022 / Published: 6 May 2022
(This article belongs to the Special Issue 2nd Edition of Physical Activity for Health)
Browse Figures
Versions Notes

Abstract

:
One-third of the Spanish population over 15 years of age did not achieve a reasonable amount of physical activity (PA) before the COVID-19 pandemic. We aim to analyse the associations between the PA level (PAL) and self-perceived health (SPH) in the Spanish population aged 15–69 years during the pre-pandemic period. A cross-sectional study was conducted using the Spanish National Health Survey 2017 (ENSE 2017) data, with 17,777 participants. We carried out a descriptive analysis, analysed intergroup differences with non-parametric statistical tests, and calculated the Odds Ratio (OR) and Relative Risk (RR) of having a negative SPH according to PAL. In addition, correlations between PAL and SPH were studied, finding associations between them (p < 0.001). Thus, performing moderate and intense PA was related to better SPH than just walking or inactive. Weak and moderate correlations were found between PAL and SPH (p < 0.001). We also found high ORs and RRs of negative SPH as PAL decreased. Moderate and intense PA were related to positive SPH, while the risk of negative perception in inactive people was higher.

1. Introduction

By 2011, it was estimated that one in five people worldwide performed insufficient PA [1]. This prevalence has been increasing in recent years; before the COVID-19 pandemic, a third of the global population over 15 years performed insufficient physical activity (PA), according to the World Health Organization (WHO) and other organisations’ recommendations [2,3,4]. One of the goals established by the WHO in its Global Action Plan on Physical Activity 2018–2030 [5] is to reduce physical inactivity by 10% in 2025 and by 15% in 2030. Thus, in the last guideline published by this organisation before the COVID-19 pandemic, The WHO Guidelines on Physical Activity and Sedentary Behavior [6], it was recommended to engage in 150–300 min of moderate PA per week, 75–150 min at a vigorous intensity, or an equivalent combination of both [6]. In Spain, these recommendations were not reached by more than a third of the population in 2017, with a higher insufficient PA in women (37% women; 33.5% men), according to the report published by the Spanish Ministry of Health, Consumer Affairs and Social Welfare General Technical Secretary [7].
PA, defined as any bodily movement produced by skeletal muscles that require energy expenditure, is associated with multiple health benefits [8]. PA is inversely correlated with weight gain, decreased obesity, and associated comorbidities [9], and reduced risk of suffering some types of cancer, including breast, colon, liver, and lung cancer [10,11]. Other findings suggest an association with lower incidence and/or better glycemic control in type II diabetes and metabolic syndrome [12]. In addition, there is evidence of an association with improved symptoms related to mental illness [13,14], reduced pain [15], and better health-related quality of life [16]. In contrast, physical inactivity, which represents the non-achievement of physical activity guidelines [8], is associated with a deterioration in health indicators such as the increased prevalence of overweight and obesity [9], is related to cardiovascular diseases [17], some forms of cancers [18], increased prevalence of pain [19], and increased symptomatology in mental illnesses [20], thus influencing individuals’ perception of health.
Self-Perceived Health (SPH) “represents a summary statement about how numerous aspects of health, both subjective and objective, are combined within the perceptual framework of the individual respondent”, being a powerful indicator of people’s health status [21]. Thus, SPH is associated with age, sex, educational level, marital status, socioeconomic status, social environment, support, and behaviours that impact physical and mental health [22]. Furthermore, associations have been found between SPH and objective health, being a reliable predictor of people’s health status [23], as it integrates objective knowledge of potential medical conditions with the interpretation of the individual’s physical and mental signs [24].
This study aims to analyse the potential associations between PA level (PAL) and self-perceived health (SPH) in the Spanish adult population in the last Spanish National Health Survey, the ENSE 2017, [25] before the COVID-19 pandemic, providing a frame of reference for research comparing with post-pandemic periods. Data will be examined in the general population and between ages and sexes. In addition, the odds ratios (OR) and relative risks (RR) of negative health perception, according to the population’s PAL, will be presented. It was hypothesised that PAL would be positively correlated with SPH, so the population who perform moderate or vigorous-intensity PA will exhibit better SPH than those who only walked or were sedentary.

2. Materials and Methods

2.1. Study Desing

A descriptive correlational study was conducted using The Adult Questionnaire from the ENSE 2017 [25]. The Spanish Ministry of Health, Consumer Affairs and Social Welfare, together with the National Institute of Statistics, conducts the ENSE every five years to explore a variety of health-related factors in the Spanish population to plan and evaluate health policies. The ENSE 2017 was conducted between October 2016 and October 2017. After the random selection of participants, the Ministry sends a letter to the participants, providing information on the goals and characteristics of the study, explaining its confidential nature, requesting their voluntary collaboration, and warning them of the arrival of the accredited interviewers.

2.2. Ethical Concerns

Following the 2016/679 Regulation from the European Parliament and the Council of 27 April 2016 on the protection of individuals in the field of personal data processing and on the free movement of personal data and derogating Directive 95/46/EC (General Data Protection Regulation) [26], public use files are not considered confidential, so there is no requirement to apply data protection principles to anonymised information or the approval of accredited ethics committees, even for statistical or research purposes.

2.3. Participants

In order to conduct the ENSE 2017, 23,089 people (10,595 men and 12,494 women) residing in Spain and aged 15 and over were selected using a random stratified 3-phase sampling system [27]. To configure the final sample for this research, those over 70 years (5312 individuals) were excluded as they were not asked about their PA level. Thus, the sample consisted of 17,777 people, 8529 men and 9248 women, aged between 15 and 69, who were interviewed using the Adult Questionnaire [28]. Nevertheless, 60 additional participants were excluded for non-response to Q.113 and Q.114 items related to intense and moderate PA frequency and duration. Finally, 17,717 people were included in the analyses, as shown in Figure 1.

2.4. Measures and Variables

After the extraction of ENSE 2017 microdata, two types of variables were used:
  • Extracted variables: Related to the items “Age”, “Sex” (male and female), G21 (self-perceived health, with possible answers: very bad, bad, fair, good, good, very good, do not know, or no response (NS/NC)), Q.113 (weekly frequency of intense PA), Q.114 (average duration of intense PA performed), Q.115 (weekly frequency of moderate PA), Q.116 (average duration of moderate PA performed), and Q.117 (time spent walking in the last seven days).
  • Elaborated variables:
    • Age groups: Taking data from the item “Age”, the new variable Age groups were created: young people (15–35 years), young adults (35–49 years), older adults (50–64 years), and older adults (65–69 years) [29].
    • Physical Activity Index (PAI): With data from the PA-related items, the procedure followed in previous studies were used to build the PAI variable [30,31], using an adaptation of the Nes et al. Physical Activity Index [32], with values between 0 and 67.5 using the items Q.113, Q.114, Q.115, and Q.116. These corresponded to questions on the PA of the participants using the Spanish version of the International Physical Activity Questionnaire (IPAQ) [33]. The PAI was calculated using the following formula: (intensity factor for intense activity × frequency factor for intense activity × duration factor for in-tense activity) + (intensity factor for moderate activity × frequency factor for moderate activity × duration factor for moderate activity). Previously, different factors had been assigned to the participants’ answers to ENSE 2017 [28] items Q.113, Q.114, Q.115, and Q.116. The intensity factor was 10 for intense activity and 5 for moderate activity, questions Q.114 and Q.116. Frequency factor: to the answers given by the participants to items Q.114 (“How many days did you do intense PA?”) and Q.116 (“How many days did you do moderate PA?”), the following factors were applied: 0 for never, 1 for one day a week, 2 for 2–3 days a week, and 3 for more than three days a week [26]. Duration factor: to the answers given by the participants to items Q.115 (“How much time did you spend in total on intense PA?”) and Q.116 (“How much time did you spend in total on moderate PA?”), factor 1 (<30 min) and 1.5 (>30 min) were applied.
    • Physical Activity Level (PAL): Participants were grouped according to their PAI. In addition, item Q.117 regarding the time spent walking during the last seven days was used to discriminate between walkers and inactive people within PAI = 0. A total of 6 levels were established. On the one hand, there were two levels corresponding to individuals with PAI = 0: “Inactive”, those who did not perform moderate or intense PA for more than 10 min any day of the week and those who responded with “no day more than 10 min consecutively”, and “Walkers”, who responded with “one or more days, more than 10 min consecutively”. On the other hand, there were 4 PA levels for people with PAI > 0. These last four levels correspond to the 75th, 90th, 95th, and higher percentiles concerning all participants’ PAI considering the following: “Low” for persons with a PAI between 1 and 5, 75th percentile; “Medium” for PAI between 16a and 30, 90th percentile; “High”, PAI between 31 and 45, 95th percentile; and “Very high”, PAI > 45, values higher than the 95th percentile.

2.5. Statistical Analysis

Statistical analysis was conducted with the Statistical Package for the Social Sciences software (SPSS, Version 25, IBM SPSS, Armonk, NY, USA). The distribution followed by the data of the variables of interest was studied using the Kolmogorov–Smirnov test. After performing the Kolmogorov–Smirnov test, we could not assume that variables followed a normal distribution, so median, interquartile range (continuous variables), and absolute and relative frequencies (categorical variables) were taken as reference, and non-parametric tests were used. A descriptive analysis was carried out to characterise the sample. Potential intergroup differences were explored: the Mann–Whitney U test for continuous variables, the Chi-Square statistic, and a Z-test to compare proportions for the ordinal ones. According to the PAL, odds ratios (OR) and relative risks (RR) of perceiving negative health were also calculated. A correlation study was performed using Spearman’s rho between variables of interest. Finally, stepwise regression analysis to predict self-perceived health was performed considering age group, sex, and physical activity level as dependent variables. A significance level lower than 0.001 was required to introduce a new variable into each prediction model. The overall predictive power was evaluated by adjusted R2.

3. Results

In Table 1, several aspects are displayed. No intergroup differences in age were found between sexes (p = 0.295), nor dependency associations between sex and age group (p = 0.260). Overall, 74% perceived their health status as “Good” (52%) or “Very good” (22%), with a higher sex-dependent association in men than in women (p < 0.001). Men’s proportion with “Good/Very good” SPH was higher than women’s by 6 points (77.1% vs. 71.1%, with significant differences in SPH between sexes (p < 0.05). However, 59.8% of the population reported not performing moderate or intense PA. Furthermore, one of seven reported not performing any PA, not even walking, finding dependency relations between PAL and sex (p < 0.001). A higher proportion of women (50.7% vs. 39.9%, p < 0.05) stated that they only walked. In contrast, the men’s proportion with “Medium” to “Very high” PA was higher than in women (33% vs. 20.4%), with significant differences between sexes in all PA (p < 0.05), except for inactive ones.
Table 2 reveals how PAL relates to age, with a dependency relation with the age group (p < 0.001). A decrease in moderate or intense PA was found while the age increases: 4.6% of the population aged 65–69 years had a “High/Very high” PA, compared to 20.9% under 35 years. In contrast, there was an increase in the people proportions which only walked, from 35.8% of 35 years to 58% over 65 years.
PAL is also related to SPH, with a dependency relation both in the general population and by sex (p < 0.001). In the general population, the highest “Bad/Very bad” SPH proportions were found in the “Inactive” (15.6%) and “Walkers” (7.1%) groups compared to “Medium to Very high” levels (less than 3%). The highest “Good/Very good” health proportions were found in the “High” (88.2%) and “Very high” (86.9%) levels, compared to 58.6% proportion in the “Inactive” and 69.9% in “Walkers” groups. By sex, women (16.4%) and men (14.7%) in the “Inactive” group also had the highest prevalence of “Bad/Very bad” SPH and the lowest prevalence of “Good/Very good” health (Table 3).
Table S1 (Supplementary Material) shows that the same dependency relations between the highest prevalence of “Very good” SPH were found in the groups with the highest PAL (Figure 2).
In Table 4, higher ORs and RRs of perceiving health as “Very poor” were found in the “Inactive” and “Walking” groups, while the lowest risk was found in the “High” group. For the “Poor” and “Fair” health states, ORs and RRs were also found to be higher for the lowest PAL compared to the highest (Table 4).
Finally, Table 5 reveals moderate correlations between age and SPH and weak ones between the PA level, age, and SPH.
A stepwise regression analysis to predict SPH was performed considering age group, sex and PAL as dependent variables. A significance level lower than 0.001 was required to introduce a new variable into each prediction model. The overall predictive power was evaluated by adjusted R2. The linear regression model presented a coefficient of determination R2 = 11.8%, positively explained by SPH (Constant: β = 1.778, t = 85.4, p < 0.001; Age Group: β = 0.227, t = 32.1, p < 0.001; PAL: β = −0.127, t = −27.4, p < 0.001; Gender: β = 0.060, t = 4.9, p < 0.001).

4. Discussion

4.1. Main Findings and Theoretical Implications

The main purpose of this research was to examine the association between PAL and SPH in the Spanish population between 15 and 69 years. Thus, being “Inactive” could have a negative impact on SPH compared to people who “Walk” or those who perform moderate or vigorous PA. The risk of perceiving a negative health status is elevated in “Inactive” individuals compared to those who walk and completed moderate or vigorous PA. Although being a “Walker” reduces the risk of negative SPH, the risk is higher concerning those engaged in higher-intensity PA. These findings have been found when classifying the population by sex and different age groups. No significant differences neither in age nor associations between sex and age group were found; it was assumed that the differences found between sexes in the rest of the analyses were not conditioned by age.
SPH was better in men than women, with a dependency ratio between SPH and sex. Higher proportions of people with a negative SPH were found in women than in men. This has been observed in other studies in Spain and other countries [34,35]. Women had a worse HPS than men for greater concern for their health [36], cultural, physiological, or biological issues [37]. Individuals in the “Walker” group had lower proportions of negative SPH states than the “Inactive” ones. This is in line with other studies that reported improvements when walking in different health indicators: decreased blood pressure, total cholesterol, BMI, resting heart rate, increased aerobic capacity, and improvement in depressive or anxiety symptoms [38,39,40]. Despite this, introducing moderate or vigorous intensities of PA produces more significant improvements [41,42,43].
Furthermore, most of the Spanish population was not physically active or did not practice moderate or vigorous PA enough to comply with the recommendations: three out of five persons (59.8%) reported not having practised moderate or vigorous PA during the week before the survey. Moreover, PAL was related to sex, and women’s proportion of not performing moderate or vigorous PA reached 65.4%, 11.7 points higher than men’s (53.7%). These findings are worrying compared to those found in other studies. For example, in works performed with 1.6 and 1.9 million people across 146 and 168 countries, a worldwide trend towards a prevalence of insufficient PA (27.5%), confirming the gap between men and women (23.4% vs. 31.7%) [3,4]. Given that SPH is related to PAL, this lower PAL in women could be one of the causes explaining the lower SPH found in women, with a 6% difference in the proportion of women with “Good/Very good” SPH. Among those who did not engage in moderate or vigorous PA, 45.5% at least walked for more than 10 min at a time, a minimum of 1 day a week. In this case, the women’s proportion was 10.8 percentage points higher than men’s, as found in other countries [38]. Women would prefer walking more than men instead of moderate or vigorous PA. The reasons for this must be still clarified. However, it is expected to be multi-causal, including different ways of understanding PA and obtaining pleasure, social, educational, economic issues, availability of vehicles for transport, lack of support, etc. [44,45,46].
In addition, associations were found between PAL and age, with a PAL decrease when increasing age. Other studies have documented 40–80% decreases in PA with growing age, related to muscle loss, the onset of metabolic disorders and other diseases [47]. In our study, the age group with the highest proportion of people performing moderate or vigorous PA was the young group, with 52%. However, up to 48% of Spanish young people did not perform at least moderate-intensity PA. The data were worse as age increased, reaching 73.5% of people who did not perform moderate or vigorous PA in the 65–69 age group. Only one in four people performed moderate or vigorous intensities PA in this population. However, up to 58% of the elderly did walk at least one day a week for more than 10 min at a time, 22.2% more than the younger proportion. People aged 65–69 had a greater preference for walking activities than moderate or intense PA. Some research has found these preferences among older adults and older people for slower-paced PA than younger people [47,48].
In the same way, SPH also decreased with age; these findings were shared with other papers [49]. Higher PAL was associated with a lower proportion of people with “Poor or Very poor” SPH. At the other extreme, “Very good” SPH went from 13.1% in sedentary people to 17.1% in people who only walked. The relationship between PAL and SPH found in this study reinforces the findings of other studies conducted in Spanish with youth and adolescents [50] or adult populations in other countries [51,52], confirming that PA influences health perception throughout the life cycle. Whether in the general population or across sexes or age groups, walking was associated with improved SPH than a sedentary lifestyle, given the multiple demonstrated health benefits [50,51,52]. Although walking is associated with a higher proportion of people with better SPH in the general population and across age groups, moderate or vigorous PA would be more beneficial even in older people (65–69 years) [42,43]. Following the above, the ORs and RRs of negative SPH were higher in population groups with lower PA. As an example, the probability of having a “Very bad” SPH was more than three times higher in “Inactive” than in “Walkers” and ten times higher concerning the highest PA levels when including moderate or intense PA. There is considerable scientific evidence to support our findings regarding the relationship between PAL and SPH [53,54,55] so that a higher PAL results in a lower risk of worse SPH.
The world has faced a pandemic that has led to, among other effects, social isolation of the population, affecting their lifestyle, PA [56], and SPH [57]. Numerous studies have shown that PA decreased during the pandemic [56,58,59,60] and that SPH worsened [61,62]. In line with our findings, studies in the pandemic showed positive associations between increased PAL and physical health and inverse associations between sedentary behaviour and physical and mental health outcomes [63,64,65].

4.2. Practical Implications

As found in different studies, the COVID-19 pandemic had negatively impacted SPH [66,67,68,69] and PAL [70,71,72,73]. Therefore, the significance of this study lies in the analysis of the associations between PAL and SPH in the Spanish adult population during the last period before the COVID-19 pandemic, serving as a frame of reference for future research analysing pre- and post-pandemic periods. Moreover, these results may support decision-making in creating strategic actions to promote active lifestyles and the practice of PA to improve the SPH of the population throughout the life cycle since PA could act in a preventive way to preserve the population’s SPH. Thus, a higher PAL is related to a better SPH, which could imply a lower psychological discomfort and an improvement in the physical and mental health of the population. Therefore, PAL and SPH could be considered important determinants of well-being and a psychosocial protective factor against the consequences of physical inactivity and low SPH during pandemic periods. These actions should have a gender perspective, as women have lower PALs, influencing their SPH [44,45].
It would be advisable for physical educators, health professionals, governments, or stakeholders to promote PA programs for all ages, including moderate or vigorous PA, to increase the population’s SPH. If this is not feasible, walking programs should be encouraged, as they are beneficial [42,43,74], although minor, especially in older people. Taking advantage of this willingness of older people to walk, programs to increase PA in this population group should be based on walking, especially in natural areas [75], to improve adherence and include moderate and vigorous activities to optimise results in health status indicators, whenever possible; not forgetting that play also involves movement and PA so that playfulness alternatives may also be considered because of its benefits in SPH and other areas [76].

4.3. Limitations and Future Lines

However, one of the study’s limitations is that differences between moderate and intense PA were not analysed, which should be considered in future research. Other limitations include the lack of participants’ medical history, PA objective and physiological data, and a follow-up. It would be advisable to carry out a 24-h compositional analysis, including devices to quantify PA or intensity or other measures that could overcome the limitations in this type of study based on surveys and the participants’ subjective perceptions. In this sense, PA measurement through questionnaires has significant limitations, and it would be advisable to use devices that can objectively quantify PA in these types of national surveys. In addition, the introduction of METs calculation from the IPAQ questionnaire could improve the validity of the study so that if we relate different possibilities of quantifying PA with the SPH, it could be the basis for future research. This work is a cross-sectional study based on national health surveys, which is already an intrinsic limitation regarding the study design. For this reason, it would be interesting to carry out complementary research with research designs which would allow establishing causal relationships. Carrying out this same study longitudinally through public institutions such as the Ministry of Health and the inclusion of objective PA data would be an excellent opportunity to improve the quality of the information obtained in this type of survey.

5. Conclusions

PAL is positively related to SPH, both in men and women and in the different age groups of the Spanish population.
The population groups that walked or performed moderate or vigorous PA had lower proportions of people with negative SPH. Walking could be an effective alternative to reduce the population with negative SPH compared to remaining inactive. However, it would be insufficient to reduce the proportions and risks of having negative SPH.
Age is associated with less SPH and lower PAL. However, increasing the population’s PAL in all age groups could reduce the proportions of people with negative SPH.
Being Inactive leads to elevated ORs and RRs in the population prevalence of negative health perception compared to walking or higher intensity PA. Only walking presents high ORs and RRs in this prevalence concerning those who perform moderate or intense PA.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijerph19095656/s1, Table S1: Associations between the level of physical activity and self-perceived health by age groups in the Spanish population through the ENSE 2017.

Author Contributions

Conceptualisation, L.M.-B., M.M.-M., and J.R.-R.; methodology, J.C.-V. and Á.D.-Z.; formal analysis, Á.D.-Z.; writing—original draft preparation, S.B.-F., R.P.-C., and J.C.-V.; writing—review and editing, L.M.-B., M.M.-M., and J.R.-R.; visualisation, R.P.-C., F.G.-R., and A.G.-C.; supervision, Á.D.-Z. and S.B.-F.; funding acquisition, F.G.-R. and A.G.-C. All authors have read and agreed to the published version of the manuscript.

Funding

The author Á.D.-Z. (FPU20/04201) was supported by a grant from the Spanish Ministry of Education, Culture, and Sport Grants FPU20/04201 funded by MCIN/AEI/10.13039/501100011033 and, as appropriate, by the “European Social Fund Investing in your future” or by the “European Union NextGenerationEU/PRTR”. The author M.M.-M. was supported by a grant from the Universities Ministry and the European Union (NextGenerationUE) (MS-12).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Datasets will be available under reasonable request.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. González, K.; Fuentes, J.; Márquez, J.L. Physical Inactivity, Sedentary Behavior and Chronic Diseases. Korean J. Fam. Med. 2017, 38, 111–115. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Park, J.H.; Moon, J.H.; Kim, H.J.; Kong, M.H.; Oh, Y.H. Sedentary Lifestyle: Overview of Updated Evidence of Potential Health Risks. Korean J. Fam. Med. 2020, 41, 365–373. [Google Scholar] [CrossRef] [PubMed]
  3. Guthold, R.; Stevens, G.A.; Riley, L.M.; Bull, F.C. Worldwide Trends in Insufficient Physical Activity from 2001 to 2016: A Pooled Analysis of 358 Population-Based Surveys with 1·9 Million Participants. Lancet Glob. Health 2018, 6, 1077–1086. [Google Scholar] [CrossRef] [Green Version]
  4. Guthold, R.; Stevens, G.A.; Riley, L.M.; Bull, F.C. Global Trends in Insufficient Physical Activity among Adolescents: A Pooled Analysis of 298 Population-Based Surveys with 1·6 Million Participants. Lancet Child Adolesc. Health 2020, 4, 23–35. [Google Scholar] [CrossRef]
  5. World Health Organization. Global Action Plan on Physical Activity 2018–2030: More Active People for a Healthier World; World Health Organization: Geneva, Switzerland, 2018; ISBN 978-92-4-151418-7. [Google Scholar]
  6. World Health Organization. WHO Guidelines on Physical Activity and Sedentary Behaviour; World Health Organization: Geneva, Switzerland, 2020; ISBN 978-92-4-001512-8. [Google Scholar]
  7. Secretaría General de Información Sanitaria Serie Informes Monográficos 2: Actividad Física, Descanso y Sueño. In Encuesta Nacional de Salud de España 2017; Gobierno de España: Madrid, Spain, 2019.
  8. Thivel, D.; Tremblay, A.; Genin, P.M.; Panahi, S.; Rivière, D.; Duclos, M. Physical Activity, Inactivity, and Sedentary Behaviors: Definitions and Implications in Occupational Health. Front. Public Health 2018, 6, 288. [Google Scholar] [CrossRef] [PubMed]
  9. Jakicic, J.M.; Rogers, R.J.; Davis, K.K.; Collins, K.A. Role of Physical Activity and Exercise in Treating Patients with Overweight and Obesity. Clin. Chem. 2018, 64, 99–107. [Google Scholar] [CrossRef] [PubMed]
  10. Sangrajrang, S.; Chaiwerawattan, A.; Ploysawang, P.; Nooklang, K.; Jamsri, P.; Somharnwong, S. Obesity, Diet and Physical Inactivity and Risk of Breast Cancer in Thai Women. Asian Pac. J. Cancer Prev. 2013, 14, 7023–7027. [Google Scholar] [CrossRef]
  11. Sanchis-Gomar, F.; Lucia, A.; Yvert, T.; Ruiz-Casado, A.; Pareja-Galeano, H.; Santos-Lozano, A.; Fiuza-Luces, C.; Garatachea, N.; Lippi, G.; Bouchard, C.; et al. Physical Inactivity and Low Fitness Deserve More Attention to Alter Cancer Risk and Prognosis. Cancer Prev. Res. 2015, 8, 105–110. [Google Scholar] [CrossRef] [Green Version]
  12. Amanat, S.; Ghahri, S.; Dianatinasab, A.; Fararouei, M.; Dianatinasab, M. Exercise and Type 2 Diabetes. In Advances in Experimental Medicine and Biology; Springer: Berlin/Heidelberg, Germany, 2020; Volume 1228, pp. 91–105. [Google Scholar]
  13. McDowell, C.P.; Dishman, R.K.; Gordon, B.R.; Herring, M.P. Physical Activity and Anxiety: A Systematic Review and Meta-Analysis of Prospective Cohort Studies. Am. J. Prev. Med. 2019, 57, 545–556. [Google Scholar] [CrossRef]
  14. Schuch, F.B.; Vancampfort, D.; Firth, J.; Rosenbaum, S.; Ward, P.B.; Silva, E.S.; Hallgren, M.; De Leon, A.P.; Dunn, A.L.; Deslandes, A.C.; et al. Physical Activity and Incident Depression: A Meta-Analysis of Prospective Cohort Studies. Am. J. Psychiatry 2018, 175, 631–648. [Google Scholar] [CrossRef]
  15. O’Neill, A.; O’Sullivan, K.; McCreesh, K. Lower Levels of Physical Activity Are Associated with Pain Progression in Older Adults, a Longitudinal Study. Eur. J. Pain 2021, 25, 1462–1467. [Google Scholar] [CrossRef]
  16. Koolhaas, C.M.; Dhana, K.; Rooij, F.J.A.; Schoufour, J.D.; Hofman, A.; Franco, O.H. Physical Activity Types and Health-Related Quality of Life among Middle-Aged and Elderly Adults: The Rotterdam Study. J. Nutr. Health Aging 2018, 22, 246–253. [Google Scholar] [CrossRef] [PubMed]
  17. Lavie, C.J.; Ozemek, C.; Carbone, S.; Katzmarzyk, P.T.; Blair, S.N. Sedentary Behavior, Exercise, and Cardiovascular Health. Circ. Res. 2019, 124, 799–815. [Google Scholar] [CrossRef]
  18. Patel, A.V.; Friedenreich, C.M.; Moore, S.C.; Hayes, S.C.; Silver, J.K.; Campbell, K.L.; Winters-Stone, K.; Gerber, L.H.; George, S.M.; Fulton, J.E.; et al. American College of Sports Medicine Roundtable Report on Physical Activity, Sedentary Behavior, and Cancer Prevention and Control. Med. Sci. Sports Exerc. 2019, 51, 2391–2402. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  19. Law, L.F.; Sluka, K.A. How Does Physical Activity Modulate Pain? Pain 2017, 158, 369–370. [Google Scholar] [CrossRef] [Green Version]
  20. Harris, M.A. The Relationship between Physical Inactivity and Mental Wellbeing: Findings from a Gamification-Based Community-Wide Physical Activity Intervention. Health Psychol. Open 2018, 5, 2055102917753853. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  21. Bonner, W.I.A.; Weiler, R.; Orisatoki, R.; Lu, X.; Andkhoie, M.; Ramsay, D.; Yaghoubi, M.; Steeves, M.; Szafron, M.; Farag, M. Determinants of Self-Perceived Health for Canadians Aged 40 and Older and Policy Implications. Int. J. Equity Health 2017, 16, 94. [Google Scholar] [CrossRef] [Green Version]
  22. Cloninger, C.R.; Zohar, A.H. Personality and the Perception of Health and Happiness. J. Affect. Disord. 2011, 128, 24–32. [Google Scholar] [CrossRef]
  23. Machón, M.; Vergara, I.; Dorronsoro, M.; Vrotsou, K.; Larrañaga, I. Self-Perceived Health in Functionally Independent Older People: Associated Factors. BMC Geriatr. 2016, 16, 66. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Pereira-de-Sousa, A.M.; López-Rodríguez, J.A. Salud autopercibida en ancianos jóvenes españoles y portugueses tras la recesión según la Encuesta Europea de Salud: Un estudio transversal. Aten. Primaria 2021, 53, 102064. [Google Scholar] [CrossRef]
  25. Ministerio de Sanidad, Consumo y Bienestar Social, Gobierno de España Encuesta Nacional de Salud. 2017. Available online: https://www.sanidad.gob.es/estadEstudios/estadisticas/encuestaNacional/encuesta2017.htm (accessed on 3 March 2022).
  26. European Parliament and of the Council. Regulation (EU) 2016/679 of the 27 April 2016 on the Protection of Natural Persons with Regard to the Processing of Personal Data and on the Free Movement of Such Data, and Repealing Directive 95/46/EC (General Data Protection Regulation); Official Journal of the European Union: Luxembourg, 2016. [Google Scholar]
  27. Sanidad Consumo, M.; Social, B. Encuesta Nacional de Salud 2017 ENSE 2017: Metodología. Available online: https://www.ine.es/metodologia/t15/t153041917.pdf (accessed on 3 March 2022).
  28. Ministerio de Sanidad, Consumo y Bienestar Social Cuestionario de Adultos. In Encuesta Nacional de Salud de España 2017; Gobierno de España: Madrid, Spain, 2019.
  29. Tenforde, M.W.; Kim, S.S.; Lindsell, C.J.; Billig Rose, E.; Shapiro, N.I.; Files, D.C.; Gibbs, K.W.; Erickson, H.L.; Steingrub, J.S.; Smithline, H.A.; et al. Symptom Duration and Risk Factors for Delayed Return to Usual Health Among Outpatients with COVID-19 in a Multistate Health Care Systems Network—United States, March–June 2020. MMWR Morb. Mortal. Wkly. Rep. 2020, 69, 993–998. [Google Scholar] [CrossRef]
  30. Denche-Zamorano, Á.; Franco-García, J.M.; Carlos-Vivas, J.; Mendoza-Muñoz, M.; Pereira-Payo, D.; Pastor-Cisneros, R.; Merellano-Navarro, E.; Adsuar, J.C. Increased Risks of Mental Disorders: Youth with Inactive Physical Activity. Healthcare 2022, 10, 237. [Google Scholar] [CrossRef]
  31. Galán-Arroyo, C.; Pereira-Payo, D.; Rojo-Ramos, J.; Hernández-Mocholí, M.A.; Merellano-Navarro, E.; Pérez-Gómez, J.; Denche-Zamorano, Á.; Adsuar, J.C. Increased Odds for Depression and Antidepressant Use in the Inactive Spanish Population. Int. J. Environ. Res. Public Health 2022, 19, 2829. [Google Scholar] [CrossRef] [PubMed]
  32. Nes, B.M.; Janszky, I.; Vatten, L.J.; Nilsen, T.I.L.; Aspenes, S.T.; WislØff, U. Estimating VO2peak from a Nonexercise Prediction Model: The HUNT Study, Norway. Med. Sci. Sports Exerc. 2011, 43, 2024–2030. [Google Scholar] [CrossRef] [PubMed]
  33. Craig, C.L.; Marshall, A.L.; Sjöström, M.; Bauman, A.E.; Booth, M.L.; Ainsworth, B.E.; Pratt, M.; Ekelund, U.L.; Yngve, A.; Sallis, J.F.; et al. International Physical Activity Questionnaire: 12-Country Reliability and Validity. Med. Sci. Sports Exerc. 2003, 35, 1381–1395. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  34. Gómez-Mármol, A.; Nicolás, M.M. Estudio de las dimensiones de la salud autopercibida en mujeres adultas. Rev. Esp. Comun. Salud 2013, 4, 93–103. [Google Scholar]
  35. Morcillo Cebolla, V.; de Lorenzo-Cáceres Ascanio, A.; Domínguez Ruiz de León, P.; Rodríguez Barrientos, R.; Torijano Castillo, M.J. Desigualdades en la salud autopercibida de la población española mayor de 65 años. Gac. Sanit. 2014, 28, 511–521. [Google Scholar] [CrossRef] [Green Version]
  36. Vela, Y.W. Presencia de Vulnerabilidad al Estrés e Impacto en la Salud Auto percibida: Un Estudio Comparativo entre Hombres y Mujeres. Rev. Electrón. Cienc. Soc. Humanid. Apoyadas Tecnol. 2014, 3, 47–56. [Google Scholar]
  37. Shooshtari, S. Determinants of Self-Perceived Health. Health Rep. 2001, 13, 19. [Google Scholar]
  38. Hanson, S.; Jones, A. Is There Evidence That Walking Groups Have Health Benefits? A Systematic Review and Meta-Analysis. Br. J. Sports Med. 2015, 49, 710–715. [Google Scholar] [CrossRef] [Green Version]
  39. Rodriguez-Hernandez, M.G.; Wadsworth, D.W. The Effect of 2 Walking Programs on Aerobic Fitness, Body Composition, and Physical Activity in Sedentary Office Employees. PLoS ONE 2019, 14, e0210447. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  40. Song, C.; Ikei, H.; Park, B.J.; Lee, J.; Kagawa, T.; Miyazaki, Y. Psychological Benefits of Walking through Forest Areas. Int. J. Environ. Res. Public Health 2018, 15, 2804. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  41. Chiang, T.L.; Chen, C.; Hsu, C.H.; Lin, Y.C.; Wu, H.J. Is the Goal of 12,000 Steps per Day Sufficient for Improving Body Composition and Metabolic Syndrome? The Necessity of Combining Exercise Intensity: A Randomized Controlled Trial. BMC Public Health 2019, 19, 1215. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  42. Gebel, K.; Ding, D.; Chey, T.; Stamatakis, E.; Brown, W.J.; Bauman, A.E. Effect of Moderate to Vigorous Physical Activity on All-Cause Mortality in Middle-Aged and Older Australians. JAMA Intern. Med. 2015, 175, 970–977. [Google Scholar] [CrossRef]
  43. O’Brien, M.W.; Kimmerly, D.S.; Mekari, S. Greater Habitual Moderate-to-Vigorous Physical Activity Is Associated with Better Executive Function and Higher Prefrontal Oxygenation in Older Adults. GeroScience 2021, 43, 2707–2718. [Google Scholar] [CrossRef]
  44. Pharr, J.R.; Lough, N.L.; Terencio, A.M. Sociodemographic Determinants of Physical Activity and Sport Participation among Women in the United States. Sports 2020, 8, 96. [Google Scholar] [CrossRef]
  45. Edwards, E.S.; Sackett, S.C. Psychosocial Variables Related to Why Women Are Less Active than Men and Related Health Implications. Clin. Med. Insights Women’s Health 2016, 9 (Suppl. 1), 34668. [Google Scholar] [CrossRef] [Green Version]
  46. Nienhuis, C.P.; Lesser, I.A. The Impact of COVID-19 on Women’s Physical Activity Behavior and Mental Well-Being. Int. J. Environ. Res. Public Health 2020, 17, 9036. [Google Scholar] [CrossRef]
  47. Suryadinata, R.V.; Wirjatmadi, B.; Adriani, M.; Lorensia, A. Effect of Age and Weight on Physical Activity. J. Public Health Res. 2020, 9, 187–190. [Google Scholar] [CrossRef]
  48. Alley, S.J.; Schoeppe, S.; Rebar, A.L.; Hayman, M.; Vandelanotte, C. Age differences in physical activity intentions and implementation intention preferences. J. Behav. Med. 2018, 41, 406–415. [Google Scholar] [CrossRef]
  49. Giacomozzi, C.; Palmieri, L.; Gargiulo, L.; Noce, C.L.; Iannucci, L.; Di Lonardo, A.; Vannucchi, S.; Onder, G.; Colivicchi, F.; Giampaoli, S.; et al. The Perceived Health Status from Young Adults to Elderly: Results of the Mehm Questionnaire within the Cuore Project Survey 2008–2012. Int. J. Environ. Res. Public Health 2020, 17, 6160. [Google Scholar] [CrossRef] [PubMed]
  50. Padilla-Moledo, C.; Fernández-Santos, J.D.R.; Izquierdo-Gómez, R.; Esteban-Cornejo, I.; Rio-Cozar, P.; Carbonell-Baeza, A.; Castro-Piñero, J. Physical Fitness and Self-Rated Health in Children and Adolescents: Cross-Sectional and Longitudinal Study. Int. J. Environ. Res. Public Health 2020, 17, 2413. [Google Scholar] [CrossRef] [PubMed]
  51. Cui, Y.; Sweeney, E.; Forbes, C.; DeClercq, V.; Grandy, S.A.; Keats, M.; Parker, L.; Yu, Z.M.; Dummer, T.J.B. The Association between Physical Activity and Self-Rated Health in Atlantic Canadians. J. Women Aging 2021, 33, 596–610. [Google Scholar] [CrossRef] [PubMed]
  52. Trachte, F.; Geyer, S.; Sperlich, S. Impact of Physical Activity on Self-Rated Health in Older People: Do the Effects Vary by Socioeconomic Status? J. Public Health 2016, 38, 754–759. [Google Scholar] [CrossRef] [Green Version]
  53. Kaleta, D.; Makowiec-Dąbrowska, T.; Dziankowska-Zaborszczyk, E.; Jegier, A. Physical Activity and Self-Perceived Health Status. Int. J. Occup. Med. Environ. Health 2006, 19, 61. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  54. Okano, G.; Miyake, H.; Mori, M. Leisure Time Physical Activity as a Determinant of Self-Perceived Health and Fitness in Middle-Aged Male Employees. J. Occup. Health 2003, 45, 286–292. [Google Scholar] [CrossRef] [Green Version]
  55. Moral-García, J.E.; Agraso-López, A.D.; Ramos-Morcillo, A.J.; Jiménez, A.; Jiménez-Eguizábal, A. The Influence of Physical Activity, Diet, Weight Status and Substance Abuse on Students’ Self-Perceived Health. Int. J. Environ. Res. Public Health 2020, 17, 1387. [Google Scholar] [CrossRef] [Green Version]
  56. Tison, G.H.; Avram, R.; Kuhar, P.; Abreau, S.; Marcus, G.M.; Pletcher, M.J.; Olgin, J.E. Worldwide Effect of COVID-19 on Physical Activity: A Descriptive Study. Ann. Intern. Med. 2020, 173, 767–770. [Google Scholar] [CrossRef]
  57. López, J.; Pérez-Rojo, G.; Noriega, C.; Velasco, C.; Carretero, I.; López-Frutos, P.; Galarraga, L. Las Respuestas al Confinamiento Por La Pandemia de La COVID-19 Desde Una Perspectiva Emocional: La Función Familiar Como Patrón Diferencial En Las Personas Mayores. Behav. Psychol. Conduct. 2021, 29, 331–344. [Google Scholar] [CrossRef]
  58. Amini, H.; Isanejad, A.; Chamani, N.; Movahedi-Fard, F.; Salimi, F.; Moezi, M.; Habibi, S. Physical Activity during COVID-19 Pandemic in the Iranian Population: A Brief Report. Heliyon 2020, 6, e05411. [Google Scholar] [CrossRef]
  59. Dunton, G.F.; Do, B.; Wang, S.D. Early Effects of the COVID-19 Pandemic on Physical Activity and Sedentary Behavior in Children Living in the US. BMC Public Health 2020, 20, 1351. [Google Scholar] [CrossRef] [PubMed]
  60. Martinez, E.Z.; Silva, F.M.; Morigi, T.Z.; Zucoloto, M.L.; Silva, T.L.; Joaquim, A.G.; Dall’Agnol, G.; Galdino, G.; Martinez, M.O.Z.; Silva, W.R. da Physical Activity in Periods of Social Distancing Due to COVID-19: A Cross-Sectional Survey. Ciênc. Saúde Coletiva 2020, 25, 4157–4168. [Google Scholar] [CrossRef]
  61. Buneviciene, I.; Bunevicius, R.; Bagdonas, S.; Bunevicius, A. The Impact of Pre-Existing Conditions and Perceived Health Status on Mental Health during the COVID-19 Pandemic. J. Public Health 2022, 44, e88–e95. [Google Scholar] [CrossRef] [PubMed]
  62. Becerra-Canales, B.; Ybaseta-Medina, J. Salud Autopercibida En Trabajadores de Enfermería Del Primer Nivel de Atención Durnate La Pandemia de COVID-19. Rev. Med. Panacea 2020, 9, 113–117. [Google Scholar]
  63. Stanton, R.; To, Q.G.; Khalesi, S.; Williams, S.L.; Alley, S.J.; Thwaite, T.L.; Fenning, A.S.; Vandelanotte, C. Depression, Anxiety and Stress during COVID-19: Associations with Changes in Physical Activity, Sleep, Tobacco and Alcohol Use in Australian Adults. Int. J. Environ. Res. Public Health 2020, 17, 4065. [Google Scholar] [CrossRef] [PubMed]
  64. Cheval, B.; Sivaramakrishnan, H.; Maltagliati, S.; Fessler, L.; Forestier, C.; Sarrazin, P.; Orsholits, D.; Chalabaev, A.; Sander, D.; Ntoumanis, N.; et al. Relationships between Changes in Self-Reported Physical Activity, Sedentary Behaviour and Health during the Coronavirus (COVID-19) Pandemic in France and Switzerland. J. Sports Sci. 2021, 39, 699–704. [Google Scholar] [CrossRef]
  65. Findlay, L.; Arim, R. Canadians Report Lower Self-Perceived Mental Health during the COVID-19 Pandemic. Health Rep. 2020, 31, 2–27. [Google Scholar] [CrossRef]
  66. Broche-Pérez, Y.; Fernández-Fleites, Z.; Fernández-Castillo, E.; Jiménez-Puig, E.; Vizcaíno-Escobar, A.E.; Ferrer-Lozano, D.M.; Martínez-Rodríguez, L.; Martín-González, R. Anxiety, Health Self-Perception, and Worry About the Resurgence of COVID-19 Predict Fear Reactions Among Genders in the Cuban Population. Front. Glob. Womens Health 2021, 2, 634088. [Google Scholar] [CrossRef]
  67. Cabona, C.; Ferraro, P.M.; Meo, G.; Roccatagliata, L.; Schenone, A.; Inglese, M.; Villani, F.; Caponnetto, C. Predictors of Self-Perceived Health Worsening over COVID-19 Emergency in ALS. Neurol. Sci. 2021, 42, 1231–1236. [Google Scholar] [CrossRef]
  68. Ruiz-Frutos, C.; Palomino-Baldeón, J.C.; Ortega-Moreno, M.; Villavicencio-Guardia, M.d.C.; Dias, A.; Bernardes, J.M.; Gómez-Salgado, J. Effects of the COVID-19 Pandemic on Mental Health in Peru: Psychological Distress. Healthcare 2021, 9, 691. [Google Scholar] [CrossRef]
  69. Árbol, J.R.; Ruiz-Osta, A.; Montoro Aguilar, C.I.M. Personality Traits, Cognitive Styles, Coping Strategies, and Psychological Impact of the COVID-19 Pandemic Lockdown on Healthy Youngsters. Behav. Sci. 2021, 12, 5. [Google Scholar] [CrossRef] [PubMed]
  70. Puccinelli, P.J.; da Costa, T.S.; Seffrin, A.; de Lira, C.A.B.; Vancini, R.L.; Nikolaidis, P.T.; Knechtle, B.; Rosemann, T.; Hill, L.; Andrade, M.S. Reduced Level of Physical Activity during COVID-19 Pandemic Is Associated with Depression and Anxiety Levels: An Internet-Based Survey. BMC Public Health 2021, 21, 425. [Google Scholar] [CrossRef]
  71. López-Sánchez, G.F.; López-Bueno, R.; Gil-Salmerón, A.; Zauder, R.; Skalska, M.; Jastrzębska, J.; Jastrzębski, Z.; Schuch, F.B.; Grabovac, I.; Tully, M.A.; et al. Comparison of Physical Activity Levels in Spanish Adults with Chronic Conditions before and during COVID-19 Quarantine. Eur. J. Public Health 2021, 31, 161–166. [Google Scholar] [CrossRef] [PubMed]
  72. Wilke, J.; Mohr, L.; Tenforde, A.S.; Edouard, P.; Fossati, C.; González-Gross, M.; Sánchez Ramírez, C.; Laiño, F.; Tan, B.; Pillay, J.D.; et al. A Pandemic within the Pandemic? Physical Activity Levels Substantially Decreased in Countries Affected by COVID-19. Int. J. Environ. Res. Public Health 2021, 18, 2235. [Google Scholar] [CrossRef] [PubMed]
  73. Stockwell, S.; Trott, M.; Tully, M.; Shin, J.; Barnett, Y.; Butler, L.; McDermott, D.; Schuch, F.; Smith, L. Changes in Physical Activity and Sedentary Behaviours from before to during the COVID-19 Pandemic Lockdown: A Systematic Review. BMJ Open Sport Exerc. Med. 2021, 7, e000960. [Google Scholar] [CrossRef] [PubMed]
  74. An, K.Y. Comparison between Walking and Moderate-to-Vigorous Physical Activity: Associations with Metabolic Syndrome Components in Korean Older Adults. Epidemiol. Health 2021, 42, e2020066. [Google Scholar] [CrossRef]
  75. Reyes Rincón, H.; Campos Uscanga, Y. Beneficios de la actividad física en espacios naturales sobre la salud del adulto mayor. ENE Rev. Enferm. 2020, 14, 2. [Google Scholar] [CrossRef]
  76. Bronikowska, M.; Bronikowski, M.; Schott, N. “You Think You Are Too Old to Play?” Playing Games and Aging. Hum. Mov. 2011, 12, 24–30. [Google Scholar] [CrossRef]
Ijerph 19 05656 g001 550
Figure 1. Sample exclusion criteria.
Figure 1. Sample exclusion criteria.
Ijerph 19 05656 g001
Ijerph 19 05656 g002 550
Figure 2. Associations between the level of physical activity and self-perceived health by age groups in the Spanish population through the ENSE 2017.
Figure 2. Associations between the level of physical activity and self-perceived health by age groups in the Spanish population through the ENSE 2017.
Ijerph 19 05656 g002
Table
Table 1. Socio-demographic characteristics, self-perceived health, and the level of physical activity in the Spanish population through the ENSE 2017.
Table 1. Socio-demographic characteristics, self-perceived health, and the level of physical activity in the Spanish population through the ENSE 2017.
Ages (Years)Total = 17,777Men = 8529Women = 9248p
Median (IQR)47 (21)47 (21)47 (21)0.295
Mean (SD)45.8 (14.1)45.7 (14.1)46.0 (14.1)
Age Group (years)Total n (%)Men n (%)Women n (%)p *
15–343894 (21.9)1864 (21.9)2030 (22.0)0.260
35–496195 (34.8)3007 (35.3)3188 (34.5)
50–645977 (33.6)2874 (33.7)3103 (33.6)
65–691711 (9.6)784 (9.2)927 (10.0)
Self-perceived healthTotal = 17,777
n (%)		Men = 8529
n (%)		Women = 9248
n (%)
Very bad263 (1.5)97 (1.1)166 (1.8) b<0.001
Bad896 (5.0)392 (4.6)504 (5.4) b
Fair3462 (19.5)1457 (17.1)2005 (21.7) b
Good9252 (52.0)4584 (53.7)4668 (50.5) b
Very good3904 (22.0)1999 (23.4)1905 (20.6) b
PALTotal = 17,717
n (%)		Men = 8489
n (%)		Women = 9228
n (%)
Inactive2533 (14.3)1175 (13.8)1358 (14.7)<0.001
Walkers8067 (45.5)3390 (39.9)4667 (50.7)) b
Low2433 (13.7)1120 (13.2)1313 (14.2) b
Medium2456 (13.9)1341 (15.8)1115 (12.1) b
High1472 (8.3)954 (11.2)518 (5.6) b
Very high756 (4.3)509 (6.0)247 (2.7) b
IQR: Interquartile range; n: participants; %: percentage; Physical Activity Index (PAI) only considers intense and moderate physical activity. Scores between 0 and 67.5; Inactive: PAI = 0; reports not walking at least one day a week for more than 10 min at a time; Walkers PAI = 0; reports walking at least one day a week for more than 10 min at a time; Low: PAI = 1–15; Medium: PAI = 16–30; High: PAI = 31–45; Very high: PAI > 45; p: p-value from Mann–Whitney U test; p *: p-value from Chi-square test; b Significant differences between the proportions of each level, according to sex in the z-test for independent ratios (p < 0.05).
Table
Table 2. Association between physical activity level and age group in the Spanish population through the ENSE 2017.
Table 2. Association between physical activity level and age group in the Spanish population through the ENSE 2017.
PAL15–34 Years
n (%)		35–49 Years
n (%)		50–64 Years
n (%)		65–69 Years
n (%)		p
Inactive (n = 2533)472 (12.2)935 (15.1)878 (14.7)248 (14.5)<0.001
Walkers (n = 8067)1385 (35.8)2565 (41.5)3124 (52.5)993 (58.0)
Low (n = 2433)572 (14.8)970 (15.7)696 (11.7)195 (11.4)
Medium (n = 2456)637 (16.4)881 (14.3)743 (12.5)195 (11.4)
High (n = 1472)560 (14.5)554 (9.0)306 (5.1)52 (3.0)
Very high (n = 756)247 (6.4)272 (4.4)209 (3.5)28 (1.6)
Total (n = 17717)3873617759561711
n: participants; %: percentage; absolute and relative frequency data shown for individuals in age groups for each level of physical activity; PAI: Physical Activity Index; Inactive: PAI = 0; reports not walking at least one day a week for more than 10 min at a time; Walkers PAI = 0; reports walking at least one day a week for more than 10 min at a time; Low: PAI = 1–15; Medium: PAI = 16–30; High: PAI = 31–45; Very high: PAI > 45; p: p-value from Chi-square test.
Table
Table 3. Associations between the level of physical activity and self-perceived health in the Spanish population through the ENSE 2017.
Table 3. Associations between the level of physical activity and self-perceived health in the Spanish population through the ENSE 2017.
Self-Perceived Health: General Population
PALVery bad
n (%)		Bad
n (%)		Fair
n (%)		Good
n (%)		Very Good
n (%)		p
Inactive (n = 2533)120 (4.7)275 (10.9)603 (23.8)1202 (45.5)333 (13.1)<0.001
Walkers (n = 8067)110 (1.4)460 (5.7)1861 (23.1)4257 (52.8)1379 (17.1)
Low (n = 2433)11 (0.5)80 (3.3)399 (16.4)1353 (55.6)590 (24.2)
Medium (n = 2456)12 (0.5)44 (1.8)363 (14.8)1340 (54.6)697 (28.4)
High (n = 1472)6 (0.4)19 (1.3)148 (10.1)719 (48.8)580 (39.4)
Very high (n = 756)4 (0.5)17 (2.2)78 (10.3)353 (46.7)304 (40.2)
TOTAL (n = 17,717)263895345292243883
Self-Perceived Health: Women
PALVery bad
n(%)		Bad
n(%)		Fair
n(%)		Good
n(%)		Very Good
n(%)
Inactive (n = 1358)71 (5.2)152 (11.2)360 (26.5)599 (44.1)176 (13.0)<0.001
Walkers (n = 4677)80 (1.7)258 (5.5)1112 (23.8)2402 (51.4)825 (17.6)
Low (n = 1313)7 (0.5)57 (4.3)248 (18.9)699 (53.2)302 (23.0)
Medium (n = 1115)3 (0.3)23 (2.1)180 (16.1)596 (53.5)313 (28.1)
High (n = 518)4 (0.8)5 (1.0)62 (12.0)257 (49.6)190 (36.7)
Very high (n = 247)1 (0.4)9 (3.6)38 (15.4)107 (43.3)92 (37.2)
TOTAL (n = 9228)166504200046601898
Self-Perceived Health: Men
PALVery bad
n(%)		Bad
n(%)		Fair
n(%)		Good
n(%)		Very Good
n(%)
Inactive (n = 1175)49 (4.2)123 (10.5)243 (20.7)603 (51.3)157 (13.4)<0.001
Walkers (n = 3390)30 (0.9)202 (6.0)749 (22.1)1855 (54.7)554 (16.3)
Low (n = 1120)4 (0.4)23 (2.1)151 (13.5)654 (58.4)288 (25.7)
Medium (n = 1341)9 (0.7)21 (1.6)183 (13.6)744 (55.5)384 (28.6)
High (n = 954)2 (0.2)14 (1.5)86 (9.0)462 (48.4)390 (40.9)
Very high (n = 509)3 (0.6)8 (1.6)40 (7.9)246 (48.3)212 (41.7)
TOTAL (n = 8489)97391145245641985
n: participants; %: percentage; absolute and relative frequency data shown for individuals in age groups for each level of physical activity; PAI: Physical Activity Index; Inactive: PAI = 0; reports not walking at least one day a week for more than 10 min at a time; Walkers PAI = 0; reports walking at least one day a week for more than 10 min at a time; Low: PAI = 1–15; Medium: PAI = 16–30; High: PAI = 31–45; Very high: PAI > 45; p: p-value from Chi-square test.
Table
Table 4. Probability and relative risk of perceiving health as very poor, poor, or fair, according to the physical activity level in the Spanish population through the ENSE 2017.
Table 4. Probability and relative risk of perceiving health as very poor, poor, or fair, according to the physical activity level in the Spanish population through the ENSE 2017.
Self-Perceived Health: Very Bad
PALORCI 95%RRCI 95%p
InactivesWalkers3.602.77–4.683.482.69–4.48<0.001
Low10.955.89–20.3510.485.67–19.38<0.001
Medium10.135.58–18.389.705.37–17.51<0.001
High12.155.34–27.6611.625.13–26.32<0.001
Very high9.353.44–25.408.953.32–24.17<0.001
WalkersLow3.041.64–5.673.021.63–5.60<0.001
Medium2.821.55–5.122.791.54–5.06<0.001
High3.381.48–7.703.351.47–7.60<0.005
Very high2.600.96–7.072.580.95–6.970.052
Self-Perceived Health: Bad
PALORCI 95%RRCI 95%
InactivesWalkers2.011.72–2.361.901.65–2.20<0.001
Low3.582.78–4.633.302.59–4.21<0.001
Medium6.684.83–9.236.064.43–8.29<0.001
High9.315.82–14.908.415.31–13.33<0.001
Very high5.303.22–8.704.832.98–7.83<0.001
WalkersLow1.781.40–2.271.731.37–2.19<0.001
Medium3.322.43–4.533.182.34–4.32<0.001
High4.622.91–7.344.422.80–6.97<0.001
Very high2.631.61–4.292.541.57–4.09<0.001
Self-Perceived Health: Fair
PALORCI 95%RRCI 95%
InactivesWalkers1.040.94–1.161.030.95–1.120.444
Low1.591.38–1.831.451.30–1.63<0.001
Medium1.801.56–2.081.611.43–1.81<0.001
High2.802.31–3.392.372.00–2.80<0.001
Very high2.722.11–3.492.311.85–2.88<0.001
WalkersLow1.531.36–1.721.411.28–1.55<0.001
Medium1.731.53–1.961.561.41–1.73<0.001
High2.682.25–3.202.291.96–2.69<0.001
Very high2.612.05–3.312.241.81–2.77<0.001
OR: Odd ratio; CI95%: Confidence Interval; RR: Relative risk; p: p-valor from Chi-square; PAI: Physical Activity Index; Inactive: PAI = 0; reports not walking at least one day a week for more than 10 min at a time; Walkers PAI = 0; reports walking at least one day a week for more than 10 min at a time; Low: PAI = 1–15; Medium: PAI = 16–30; High: PAI = 31–45; Very high: PAI > 45; p: p-value from Chi-square test.
Table
Table 5. Associations between the physical activity level, age, and self-perceived health in the Spanish population through the ENSE 2017.
Table 5. Associations between the physical activity level, age, and self-perceived health in the Spanish population through the ENSE 2017.
PAL
VariablesTotalMenWomen
rhoprhoprhop
Age−0.161<0.001−0.229<0.001−0.092<0.001
SPH0.244<0.0010.269<0.0010.210<0.001
PAL: physical activity level; SPH: self-perceived health; Rho: Spearman’s correlation coefficient with Bonferroni correction factor (p = 0.01).
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Denche-Zamorano, Á.; Mendoza-Muñoz, M.; Carlos-Vivas, J.; Muñoz-Bermejo, L.; Rojo-Ramos, J.; Pastor-Cisneros, R.; Giakoni-Ramírez, F.; Godoy-Cumillaf, A.; Barrios-Fernandez, S. A Cross-Sectional Study on Self-Perceived Health and Physical Activity Level in the Spanish Population. Int. J. Environ. Res. Public Health 2022, 19, 5656. https://doi.org/10.3390/ijerph19095656

AMA Style

Denche-Zamorano Á, Mendoza-Muñoz M, Carlos-Vivas J, Muñoz-Bermejo L, Rojo-Ramos J, Pastor-Cisneros R, Giakoni-Ramírez F, Godoy-Cumillaf A, Barrios-Fernandez S. A Cross-Sectional Study on Self-Perceived Health and Physical Activity Level in the Spanish Population. International Journal of Environmental Research and Public Health. 2022; 19(9):5656. https://doi.org/10.3390/ijerph19095656

Chicago/Turabian Style

Denche-Zamorano, Ángel, María Mendoza-Muñoz, Jorge Carlos-Vivas, Laura Muñoz-Bermejo, Jorge Rojo-Ramos, Raquel Pastor-Cisneros, Frano Giakoni-Ramírez, Andrés Godoy-Cumillaf, and Sabina Barrios-Fernandez. 2022. "A Cross-Sectional Study on Self-Perceived Health and Physical Activity Level in the Spanish Population" International Journal of Environmental Research and Public Health 19, no. 9: 5656. https://doi.org/10.3390/ijerph19095656

APA Style

Denche-Zamorano, Á., Mendoza-Muñoz, M., Carlos-Vivas, J., Muñoz-Bermejo, L., Rojo-Ramos, J., Pastor-Cisneros, R., Giakoni-Ramírez, F., Godoy-Cumillaf, A., & Barrios-Fernandez, S. (2022). A Cross-Sectional Study on Self-Perceived Health and Physical Activity Level in the Spanish Population. International Journal of Environmental Research and Public Health, 19(9), 5656. https://doi.org/10.3390/ijerph19095656

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop