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Topic 2 ( quantitative research):
- Same menu, seperate tables: The institutionalist turn in political

science and the study of European integration.
Research question:
- What is a positive way of conceptual diversity?
Research objectives:
- analyse the neo–institutionalist turn in political science and European studies.
- move on to a detailed analysis and comparison of the three competing approaches — sociological, historical, and rational choice institutionalism.
Samples:
-historical institutionalists argue that ‘not just the strategies but also the goals actors

pursue are shaped by the institutional context’.
Sources:
- European Journal of Political Researchhttps://ejpr.onlinelibrary.wiley.com/doi/abs/10.1111/1475-6765.00526

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Participants: how many men aged 18-36 exercise? (and are they obese?)
By age:
(1) Men aged 18-24
(2) Men aged 25-30
(3) Men aged 31-36
Do men of these three different ages have the habit of exercising?
Do people who exercise regularly, occasionally and never exercise have the same figure?
(quantitative survey), (qualitative survey)
Come to the conclusion, do their habits affect their health and figure?（https://academic.oup.com/ajcn/article/69/3/373/4694139?login=true）

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ABSTRACT

INTRODUCTION

Obesity is a public health problem in the United States ( 1) and the prevalence of obesity has increased substantially over the past few decades ( 2). However, the health effects of body fatness in relation to longevity are unclear. Many studies show increased mortality in the leanest as well as the most obese individuals ( 3- 6), but others do not observe this trend ( 7- 9). Manson et al ( 9) suggest that findings of high mortality rates in individuals with low weight-for-height are associated with methodologic limitations such as failure to control for cigarette smoking, failure to eliminate early mortality due to preexisting disease, and inappropriate control for obesity-related biological factors. Nonetheless, a recent meta-analysis documented elevated mortality in association with leanness after accounting for smoking and preexisting disease ( 10).

Another unexplored methodologic limitation in obesity research is that body mass index (BMI; in kg/m ²) is commonly used to examine the obesity-mortality association even though BMI is not an accurate measure of obesity. Rather, it mainly indicates overweight for height but does not discriminate between fat mass and fat-free mass (FFM). Some studies show higher death rates in individuals with low BMIs and high waist-to-hip circumference ratios (WHRs), but not in those with high BMIs and low WHRs ( 11- 13). The health effects of overweight on height and body composition in relation to cardiovascular disease (CVD) risk factors need further research ( 14, 15). There has been little research on the relation between measured body fatness and mortality ( 16).

We believe that cardiorespiratory fitness should also be considered in examining the relation between body composition and mortality. Cardiorespiratory fitness is a powerful predictor of all-cause and CVD mortality ( 17- 19) and appeared to attenuate the relation between BMI and mortality in an earlier study ( 20). However, the health effects of body fatness and cardiorespiratory fitness in relation to longevity remain unexplored. Therefore, the purpose of this study was to examine the health consequences of body fatness and cardiorespiratory fitness in relation to all-cause and CVD mortality in men. We also assessed the associations of fat mass, FFM, and waist circumference to mortality after taking cardiorespiratory fitness into account.

SUBJECTS AND METHODS

Subjects and measurements

Subjects were 21925 men aged 30-83 y who had complete preventive medical evaluations between 1971 and 1989 at the Cooper Clinic in Dallas. All subjects were residents of the United States and had no personal history of myocardial infarction, stroke, or cancer at baseline. All received body composition assessments and reached ≥85% of their age-predicted maximal heart rate [220 − age (in y)] during their treadmill tests.

The study protocol was reviewed and approved annually by the Institutional Review Board. All subjects gave their informed, written consent for the medical evaluation and subsequent registration in the follow-up study. The medical evaluation, performed after subjects had fasted overnight for ≥12 h, included a physical examination, anthropometric measurements, electrocardiogram, blood chemistry analyses, blood pressure assessment, maximal exercise treadmill test, self-report of health habits, and recording of demographic characteristics. Additional details of examination procedures are published elsewhere ( 17- 19).

Serum samples were analyzed by automated techniques in a laboratory that participates in the Centers for Disease Control and Prevention Lipid Standardization Program, and blood pressure was measured by auscultatory methods with a mercury sphygmomanometer. Body weight and stature were measured with a standard physician's scale and stadiometer. In a subgroup of 14043 men, waist circumference was measured at the level of the umbilicus with a plastic tape measure. Body composition was assessed either by hydrostatic weighing, by skinfold-thickness measurements, or both following a standard procedure ( 21). We determined percentage body fat in men by hydrodensitometry using Siri's ( 22) two-component model. We also measured the sum of 7 (Σ7) skinfold thicknesses and estimated skinfold fat using a generalized body density equation ( 23).

We assigned subjects to categories of lean, normal, or obese. These categories correspond to <25th, 25th to <75th, and ≥75th percentile scores. We also classified subjects as having low, moderate, and high categories of fat mass, FFM, and waist circumference by using these same percentile scores cutoff points.

Alcohol use, cigarette smoking habit, and parental history of ischemic heart disease (IHD; either parent died of IHD) were assessed by self-report on a medical history questionnaire. Alcohol consumption was classified as none, light (<15 units/wk), moderate (15-30 units/wk), and heavy (≥31 units/wk). One unit of alcohol intake was defined as a bottle or can of beer [355 mL (12 oz)], a glass of wine [148 mL (5 oz)], or 44 mL (1.5 oz) of hard liquor. Smoking status was classified as never smoked, former smoker, or current smoker. Current smokers were further classified as smoking <20, 20 to <40, and ≥40 cigarettes/d.

Cardiorespiratory fitness was measured by using a maximal treadmill exercise test as described previously ( 17). Total treadmill endurance time was used as an index of aerobic power; time on treadmill with this protocol correlated highly ( r = 0.92) with maximal oxygen uptake (V̇O ₂max) ( 24). Men in the least-fit 20% of each age group were classified as physically unfit, and all others as physically fit ( 18). We also calculated V̇O ₂max in mL*kg FFM −1*min −1 and classified men in the lowest quartile of oxygen uptake in each age group as physically unfit, and all others as physically fit. All subjects were cross-tabulated by cardiorespiratory fitness levels across body fatness categories as follows: 1) fit and lean, 2) unfit and lean, 3) fit and normal, 4) unfit and normal, ( 5) fit and obese, and 6) unfit and obese. We also cross-tabulated by cardiorespiratory fitness levels across fat mass, FFM, and waist circumference categories.

All subjects were followed for mortality from the baseline examination to the date of death or to December 31, 1989. Deaths among study subjects were identified from the National Center for Health Statistics National Death Index and official death certificates from the departments of vital records of the various states. The underlying cause of death was determined by a nosologist according to the International Classification of Diseases, Ninth Edition, with CVD defined as codes 390 to 449.9.

Statistical analysis

All-cause and CVD death rates per 10000 man-years (for which a man-year is 1 man followed for 1 y) of follow-up, adjusted for age and examination year, were calculated across body fatness and waist circumference categories. Proportional hazards regression was used to examine the associations among cardiorespiratory fitness, body fatness, and all-cause and CVD mortality ( 25). We also examined the associations among cardiorespiratory fitness, fat mass, FFM, and waist circumference to all-cause and CVD mortality. The relative risks (RRs) of all-cause and CVD mortality were estimated after adjustment for age and examination year and further adjustment for cigarette smoking, alcohol intake, and parental history of IHD. Physically fit men in the lowest quartile of each body composition variable were the reference category. The 95% CIs were calculated for each RR. All statistical procedures were performed with SAS software ( 26).

RESULTS

During an average of 8 y of follow-up (176742 man-years), there were 428 deaths: 144 from CVD, 143 from cancer, and 141 from other causes. Baseline descriptive characteristics of the subjects across body fatness categories and cardiorespiratory fitness level are shown in Table 1. Unfit men had a slightly higher degree of body fatness than did their fit counterparts within lean, normal, and obese categories [0.6%, 0.8%, and 1.8% higher, respectively ( P < 0.001)]; treadmill times were progressively lower in unfit men, indicating lower cardiorespiratory fitness, across lean, normal, and obese categories. Fit, lean men had the highest average estimated maximal aerobic power [13.4 metabolic equivalents (METs); 1 MET = V̇O ₂ (3.5 mL*kg −1*min −1)], whereas unfit, obese men had the lowest average maximal aerobic power (8.7 METs). We tested differences between groups with a two-factor analysis of variance (continuous data) or log linear models (categorical data). The main effects for both fitness and fatness were highly significant ( P < 0.001) for all variables except that height was not related to fatness. We also tested fitness and fatness interactions, and all were significant ( P ≤ 0.001) except height, diastolic blood pressure, and serum glucose.

All-cause and CVD death rates per 10000 man-years of follow-up, adjusted for age and examination year across body fatness categories, are shown in Figure 1. There was a direct relation between body fatness and all-cause ( P = 0.01 for linear trend) and CVD ( P = 0.004 for linear trend) death rates.

The associations among cardiorespiratory fitness, body fatness, and all-cause and CVD mortality are shown in Table 2. Cox proportional hazards regression analyses, adjusted for age and examination year, showed that fit men had lower death rates than did their unfit counterparts within lean, normal, and obese categories. Unfit, lean men had twice the risk of all-cause mortality as did fit, lean men ( P = 0.02) and also had higher risk (2.2 times) of all-cause mortality when compared with fit, obese men ( P = 0.008). The all-cause mortality rate of fit, obese men was not significantly different from that of fit, lean men. These results were similar after additional adjustment for cigarette smoking, alcohol intake, and parental history of IHD. To evaluate further the possible bias of subclinical disease at baseline, we constructed another multivariate model by adding baseline electrocardiographic status (normal or abnormal). This analysis led to adjusted RRs that were nearly identical to those reported in Table 2. Exclusion for early mortality also made little difference in these results ( Figure 2).

We observed similar associations among cardiorespiratory fitness, body fatness, and all-cause mortality in nonsmokers and in nonsmokers with exclusion for early mortality and adjustment for age, examination year, alcohol intake, and parental history of IHD ( Figure 2). Of nonsmokers, unfit, lean men had 1.7 times the risk of all-cause mortality of fit, lean men, with the highest all-cause mortality in unfit, obese men (RR: 1.97; 95% CI: 1.35, 2.88). Unfit nonsmokers in all body-composition groups had higher mortality risks than did fit nonsmokers after further exclusion for early mortality.

Unfit, lean men also had a high risk of CVD mortality when compared with their fit counterparts in all body fatness categories ( Table 2). After multivariate adjustment for age, examination year, cigarette smoking, alcohol intake, and parental history of IHD, we observed that fit, lean men had the lowest CVD mortality, and that unfit, obese men had the highest. Unfit, lean men had 3.2 times the risk of CVD mortality of fit, lean men (95% CI: 1.12, 8.92; P = 0.03). However, fit, obese men had a lower risk of CVD mortality than did unfit, lean men.

When we further examined the relation of estimated V̇O ₂max (in mL*kg FFM −1*min −1) and body fatness with all-cause and CVD mortality ( Figure 3), similar results were obtained as for analyses in which fitness was expressed in mL*kg −1*min −1. Mortality risk was elevated in unfit, lean men, with the highest all-cause and CVD mortality in unfit, obese men. Unfit men had substantially higher risk of CVD in all fatness categories, but there also was a direct association between body fatness and CVD mortality in fit men ( P = 0.05 for linear trend).

We also examined the relations of cardiorespiratory fitness, fat mass, and FFM to all-cause and CVD mortality ( Figure 4). Unfit men had a higher risk of all-cause and CVD mortality than did fit men in all fat mass and FFM categories. Unfit men in the lowest quartile of fat mass and FFM had a greater risk of all-cause and CVD mortality than did fit men in the highest quartile of fat mass and FFM.

We also observed results similar to the analyses presented above when the men were stratified by waist circumference. There were 162 deaths (40 from CVD, 54 from cancer, and 68 from other causes) during an average of 5.6 y of follow-up (78008 man-years of observation) in the subgroup of 14043 men who had waist girth assessed at baseline. We calculated all-cause and CVD death rates per 10000 man-years of follow-up and adjusted for age and examination year across waist circumference categories. All-cause and CVD death rates directly increased with larger sizes of waist girth, although the trends were not significant ( Figure 5).

The associations among cardiorespiratory fitness, waist circumference, and all-cause mortality are shown in Table 3. After multivariate adjustment for age, examination year, cigarette smoking, alcohol intake, and parental history of IHD, we observed that fit men had lower risk of all-cause mortality in all waist circumference categories than unfit men. Unfit men in the lowest quartile of waist girth had 4.9 times ( P < 0.001) the risk of all-cause mortality of their peers who were fit. In contrast, fit men in the highest quartile of waist girth had no elevated risk of all-cause mortality and had much lower mortality risk than unfit men in the lowest quartile of waist girth.

DISCUSSION

Although there is a strong direct relation between BMI and mortality ( 27), there has been little research on the relation between measured body fatness and mortality ( 16). We examined the health effects of body composition among 21925 men after taking cardiorespiratory fitness into account. Our database is unique, with measures of body composition and maximal exercise test data on a large sample of men. We observed a direct relation between body fatness and all-cause and CVD mortality. However, being fit apparently decreased high mortality risk in obese men. This association was similar in nonsmokers and after exclusion for early mortality in both the entire population and in nonsmokers.

We observed similar results across strata of fat mass and FFM. Unfit men in the lowest quartile of fat mass and FFM had a greater risk of all-cause and CVD mortality than their fit counterparts. Fit men in the highest quartile of fat mass and FFM had a lower risk of all-cause and CVD mortality than did unfit, lean men. Our data indicate that cardiorespiratory fitness levels in men influence the health effects of obesity. We did not observe elevated mortality risk in men with high amounts of fat mass and FFM if they also were fit.

Several studies report that abdominal obesity is associated with elevated death rates ( 11- 13). Although WHR has been commonly used to examine abdominal obesity, some studies suggest that waist girth rather than WHR is a better predictor of abdominal obesity ( 28- 30). Measurement of waist girth instead of WHR for risk stratification is recommended in recent guidelines from the US National Institutes of Health and the World Health Organization ( 31, 32). Björntorp ( 33) reports that abdominal obesity, rather than peripheral obesity, also is associated with increased risk. Some studies show higher death rates in those with abdominal obesity who were underweight (a low BMI and high WHR) than in those without abdominal obesity who were overweight (a high BMI and low WHR) ( 11- 13). No prior studies have reported the health effects of waist girth while also considering cardiorespiratory fitness. Our data show that fit men with low waist girth had lower risk of all-cause mortality than did unfit men in the same waist girth category. Unfit men with a high waist girth had a death rate 2.4 times greater than did the fit men with low waist girth, and fit men in the high waist girth category had a rate of all-cause mortality similar to fit men with low waist girth.

Our results support the hypothesis that moderate-to-high cardiorespiratory fitness reduces mortality risk across categories of body composition. Although most researchers agree that obesity is associated with health hazards and leanness is associated with health benefits, lean men in our study had increased longevity only if they were physically fit; furthermore, obese men who were fit did not have elevated mortality. In general, unfit, lean men were inactive and had low aerobic power despite their favorable IHD risk factor profiles at baseline, whereas fit, obese men were highly active and had high aerobic power at baseline.

A limitation of our study was that our subjects were white men in the middle and upper socioeconomic levels, although this homogeneity reduces the likelihood of confounding by socioeconomic characteristics. We hope that other investigators will examine these issues in other populations. The possibility of bias due to baseline health status is a consideration in all observational studies, including this one, but we think that serious bias is unlikely in this case because all study participants were given extensive medical examinations at baseline, which enabled us to exclude those with a history of myocardial infarction, stroke, or cancer. In addition, men who failed to achieve ≥85% of their age-predicted maximal heart rate on the maximal exercise test were excluded; this should have eliminated men who did not have a history of disease but were not feeling well as a result of an undiagnosed condition. We also adjusted the analyses for presence or absence of an abnormal electrocardiogram result. This exclusion eliminated men with angina, arrhythmia, or electrocardiographic abnormalities on the treadmill test, as well as resting electrocardiographic abnormalities. The effect of all these exclusion criteria was to minimize the possible bias of baseline subclinical disease. Another limitation of our study was that we estimated, rather than directly measured, residual lung volume during underwater weighing. Morrow et al ( 34) reported that the prediction accuracy of body fatness measured by densitometry when residual lung volume was estimated was only slightly better than anthropometric assessments. Nonetheless, the densitometry and skinfold-thickness estimates of body composition were likely to be more accurate measures of body fatness than BMI or height-weight indexes. Finally, we had only a one-time assessment of the exposure variables of cardiorespiratory fitness and body composition, and we do not know the extent to which these characteristics might have changed during follow-up. However, changes in the exposure variables during follow-up would cause misclassification and would be likely to lead to underestimates of RRs. Therefore, the true associations between fitness or body fatness and mortality may have actually been stronger than indicated by our results.

In summary, we found that obesity did not appear to increase mortality risk in fit men. For long-term health benefits we should focus on improving fitness by increasing physical activity rather than relying only on diet for weight control. Aerobic exercise improves IHD risk factors ( 35), and increases in physical activity or fitness extend longevity ( 18, 36). Although some studies show that there is no difference between diet and aerobic exercise in reducing IHD risk factors ( 37- 39), or even report that diet is better than aerobic exercise for improving IHD risk factors in overweight men ( 40), our data show that fit men had greater longevity than unfit men regardless of their body composition or risk factor status. Obese men should be encouraged to increase their cardiorespiratory fitness by engaging in regular, moderate-intensity physical activity; this should benefit them even if they remain overweight.

We thank the physicians and technicians of the Cooper Clinic for collecting the data for this study; Kenneth H Cooper, for initiating the Aerobics Center Longitudinal Study; Carolyn E Barlow, for data management support; and Melba S Morrow, for editorial assistance. We are grateful for the guidance of the Scientific Advisory Board of the Cooper Institute for Aerobics Research.

REFERENCES

# data[].attributes.attachment_link.title
Cardiorespiratory fitness, body composition, and all-cause and cardiovascular disease mortality in men

# data[].attributes.attachment_link.description
Obesity is a public health problem in the United States ( 1) and the prevalence of obesity has increased substantially over the past few decades ( 2). However, the health effects of body fatness in relation to longevity are unclear.

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Quantitative Research

Topic

Economic Growth and Urbanization

Research Question

What is the relationship between urbanization and economic growth

Research Objectives

The research objective is to find out the relationship between urbanization and economic development to encourage more of the positive impacts of urbanization.

Samples

Location: United Kingdom

Sources

Du. (2016). The causal relationship between land urbanization quality and economic growth: evidence from capital cities in China. Quality & Quantity, 51(6), 2707–2723. https://doi.org/10.1007/s11135-016-0417-z

Zhao, & Wang, S. (2015). The relationship between urbanization, economic growth and energy consumption in China: An econometric perspective analysis. Sustainability (Basel, Switzerland), 7(5), 5609–5627. https://doi.org/10.3390/su7055609
Qualitative Research

Topic

Education, parents and children

Research Question

how the educated  level of parents impact their children

Research Objectives

The research objective is to find out the influence educated or non educated parents have on their children

Samples

Participants: Parents, children

Gender: both

Location: worldwide

Sources

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Side affects of Covid 19 vaccine

Will male become impotence after they injected covid 19 vaccine? If vaccine could negatively affect male reproductive function.

Objectives: men who infected Covid 19

Sample:
60 male injected A company vaccine
60 male injected B company vaccine
60 male injected C company vaccine

20of60 18-30
20of60 30-50
20of60 50-60

Effects of SARS CoV-2, COVID-19, and its vaccines on male sexual health and reproduction: where do we stand?

Lo, Sharon P ; Hsieh, Tung-Chin ; Pastuszak, Alexander W ; Hotaling, James M ; Patel, Darshan P

ISSN: 0955-9930 EISSN: 1476-5489 DOI: 10.1038/s41443-021-00483-y

International journal of impotence research, 2021-10-27

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Quantitative
Topic | relationship between high school students' acadamic performance (score) and time they spend on study
Research Question |  How to plan study time can improve academic performance more effectively？
Research Objectives | students in high school
Samples | students in A class --which have highest average score for exam ---spend more time in review
students in F class--which have lowest average score for exam ---spend less time

Sources |

Qualitative
Topic |  The relationship between job satisfaction and employee turnover
Research Question |   How to improve company employee satisfaction?
Research Objectives |  employees in a company
Samples |  interview -- employees in A company-- about their comment of their jobs and treatment/ whether they plan to turnover

Sources |  https://d1wqtxts1xzle7.cloudfront.net/33282172/Gregory-with-cover-page-v2.pdf?Expires=1637247054&Signature=JmJ3byO-6ReRI3E-kw9ffJI6Bw~RUSb6~xq67WoW7Mw5CFTXCox7KswN6xqXGkb~9tEY-bD-LOYuJfMNwT401DbNmWkfj3f9BbajbZ4IeaRViPJzHpkwyMkCd~wF5qoS7IuxC0-bW1I0oAvUsC73n520lwJD0cfYaHFeSIIJTPPJm-LWX6sRginF3afdkdRtZtAh01uRdg8h5LbmE8Kn3Y8MJr~KPy4-I~rKNhETCQZF4Z7p8l4W4JczZSWY8j-KkRyLkKjcLXWTnB0SsOVfHKG3hRFk3zLpM3lDcMBK~Qyk39DBtjOheTniWVt6mfMBtJOh6CzlyoCPjGTIwlXUiw__&Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA

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1. Quantitative topic: cultural pluralism
Qualitative topic: social media

2. Quantitative Question: What do you understand by cultural pluralism?
Qualitative  Question:  Social Media its Impact on Positive and Negative Aspects.

3. Research objectives:
Qualitative: analyze the current internet environment and effects on adolescents.

4. Samples: teens, 12-18 years old

5. Sources：
Qualitative https://journals.sagepub.com/doi/abs/10.1177/1461444818755634
https://jogamayadevicollege.ac.in/uploads/1586197536.pdf

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Social media use is nearly universal among US-based teens. How do daily interactions with social apps influence adolescents' affective well-being? Survey self-reports ( n = 568) portray social media use as predominantly positive. Exploratory principal component analysis further indicates that positive and negative emotions form orthogonal response components. In-depth interviews with a sub-sample of youth ( n = 26), selected for maximum variation, reveal that affect experiences can be organized across four functional dimensions. Relational interactions contribute to both closeness and disconnection; self-expression facilitates affirmation alongside concern about others' judgments; interest-driven exploration confers inspiration and distress; and browsing leads to entertainment and boredom, as well as admiration and envy. All interviewees describe positive and negative affect experiences across multiple dimensions. Analyses suggest the relationship between social technology usage and well-being-whether enhanced or degraded-is not confined to an "either/or" framework: the emotional see-saw of social media use is weighted by both positive and negative influences.

References

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Krasnova, H, Wenninger, H, Widjaja, T. (2013) Envy on Facebook: a hidden threat to users' life satisfaction? Wirtschaftsinformatik 92: 1-16.
Google Scholar

Kross, E, Verduyn, P, Demiralp, E. (2013) Facebook use predicts declines in subjective well-being in young adults. PloS One 8(8): e69841.
Google Scholar

Stern, S (2008) Producing sites, exploring identities: youth online authorship. Youth, Identity, and Digital Media 6: 95-117.
Google Scholar

Yau, JC, Reich, SM (2017) Are the qualities of adolescents' offline friendships present in digital interactions? Adolescent Research Review DOI 10.1007/s40894-017-0059-y.
Google Scholar

# data[].attributes.attachment_link.title
The social media see-saw: Positive and negative influences on adolescents' affective well-being - Emily Weinstein, 2018

# data[].attributes.attachment_link.description
Social media use is nearly universal among US-based teens. How do daily interactions with social apps influence adolescents' affective well-being? Survey self-reports ( n = 568) portray social media use as predominantly positive. Exploratory principal component analysis further indicates that positive and negative emotions form orthogonal response components.

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Quantitative Research：
Topic: Globalization
Research Question:What is he impact of globalization on the economy?
Research Objective: The market
Samples: actual flows or trade, foreign direct investment, portfolio investment.

Qualitative Research:
Topic: Social media
Research Question:How Social media is affecting the physical social engagement of Teenagers in Urban areas.
Research Objective: The teenagers
Samples: The time teenagers spend on social media