How Sleep, Exercise, and Smoking Shape Health Outcomes Across Jobs and Ages

By abhishek.verma75000 · June 13, 2026

Across multiple health and lifestyle analyses, several clear patterns emerged. Better sleep quality was strongly associated with higher productivity…

The analysis compared Health Score and Energy Level Score between Early Waker groups. Two visualizations were generated: a grouped bar chart showing the average Health Score and Energy Level Score for each Early Waker group side by side, and a box plot showing the full score distributions for both metrics across groups. These charts reveal how early wakers differ from non-early wakers in terms of both health and energy levels.

Sleep Quality Score has a moderate positive relationship with both Productivity and Focus/Concentration scores. People with higher sleep quality tend to score noticeably better on both metrics. Two charts and supporting data tables were generated to visualize these relationships.

Two line charts show how Health Score and Healthy Aging Score trend across six age groups (18-29 through 70-80), broken down by Female, Male, and Non-binary. Both scores generally decline with age, with Healthy Aging Score showing a steeper drop (80.5 → 65.2) compared to Health Score (76.0 → 71.7). Gender differences are small overall, with Non-binary individuals averaging slightly higher Health Scores (74.1) and Males and Non-binary tied on Healthy Aging (73.5).

The analysis compares Stress Level, Anxiety Score, and Depression Risk Score across 15 occupation groups. A grouped bar chart and a heatmap were generated to visualize the differences, along with detailed data tables. Overall, the variation between occupations is relatively modest, but Artists and Doctors tend to score highest across all three metrics, while Teachers and Software Engineers score the lowest. The overall dataset averages are: Stress Level 4.52, Anxiety Score 5.13, and Depression Risk Score 2.18.

The analysis produced two grouped bar charts and supporting data tables showing how Fast Food Meals Per Week and Sitting Hours Per Day relate to both Obesity Risk and Diabetes Risk levels (Low, Medium, High).

Exercising 7 days per week is associated with the highest average Wellness and Fitness scores (4.726 out of 5). There is a clear, consistent upward trend — the more frequently people exercise, the better their wellness and fitness outcomes. A grouped bar chart and detailed breakdown table were generated to visualize these patterns across all frequency levels.

The correlation analysis among six sleep-related variables has been completed, with results displayed in two data tables. The analysis reveals how different sleep habits relate to one another and to Sleep Quality Score.

Two grouped horizontal bar charts and detailed data tables were generated ranking the top 10 occupations by Life Satisfaction, Mood, Productivity, and Stress. Teachers rank 1 overall with the highest combined wellbeing scores (Satisfaction: 7.48, Mood: 6.91, Productivity: 7.10) and the lowest stress (4.41), making them the best work-life balance occupation. Software Engineers come in 2nd (Balance Score: 2.69) and Chefs 3rd (Balance Score: 2.59). Scores across all 10 occupations are remarkably close, suggesting wellbeing is relatively consistent across professions in this dataset.

The analysis breaks down cardiovascular and hypertension risk levels across all combinations of smoking status and alcohol consumption. Three grouped bar charts and supporting data tables were generated to compare risk profiles and vital signs across lifestyle choices. The standout finding is that Current Smokers who are Moderate Drinkers show the worst health indicators across the board — the highest average Systolic BP (142.5 mmHg), the highest average Resting Heart Rate (75.0 bpm), the greatest share of High Cardiovascular Risk (17.0%), and the greatest share of High Hypertension Risk (60.3%). Interestingly, Former Smokers who are Heavy Drinkers show the lowest average Systolic BP (136.6 mmHg), suggesting that quitting smoking may have a meaningful impact even with heavier alcohol use.

The analysis successfully identified outliers in BMI, Resting Heart Rate, Cholesterol Level, and Blood Sugar Level using the IQR 1.5x rule. Box plots were generated showing the distribution and outlier points for each metric, along with a bar chart comparing outlier counts and percentages across all four metrics. Cross-tabulation tables were also produced comparing outlier status against Obesity Risk, Hypertension Risk, and Diabetes Risk categories.