from reportlab.lib.pagesizes import A4
from reportlab.lib import colors
from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
from reportlab.lib.units import mm, cm
from reportlab.platypus import (SimpleDocTemplate, Paragraph, Spacer, Table,
                                 TableStyle, HRFlowable, PageBreak, KeepTogether)
from reportlab.lib.enums import TA_CENTER, TA_LEFT, TA_JUSTIFY
from reportlab.platypus import ListFlowable, ListItem

OUTPUT = "/tmp/workspace/community-health-nursing/CHN_Study_Guide.pdf"

doc = SimpleDocTemplate(
    OUTPUT,
    pagesize=A4,
    rightMargin=2*cm, leftMargin=2*cm,
    topMargin=2.5*cm, bottomMargin=2.5*cm,
    title="Community Health Nursing - I Study Guide",
    author="B.Sc. Nursing 5th Semester",
)

styles = getSampleStyleSheet()
W = A4[0] - 4*cm  # usable width

# ── Custom styles ──────────────────────────────────────────────
cover_title = ParagraphStyle('CoverTitle', parent=styles['Title'],
    fontSize=24, textColor=colors.HexColor('#1a3a5c'), spaceAfter=6,
    leading=30, alignment=TA_CENTER)

cover_sub = ParagraphStyle('CoverSub', parent=styles['Normal'],
    fontSize=13, textColor=colors.HexColor('#2e6da4'), spaceAfter=4,
    alignment=TA_CENTER)

cover_info = ParagraphStyle('CoverInfo', parent=styles['Normal'],
    fontSize=11, textColor=colors.HexColor('#555555'), spaceAfter=3,
    alignment=TA_CENTER)

q_heading = ParagraphStyle('QHeading', parent=styles['Heading1'],
    fontSize=14, textColor=colors.white,
    backColor=colors.HexColor('#1a3a5c'),
    spaceBefore=14, spaceAfter=8, leading=20,
    leftIndent=-6, rightIndent=-6,
    borderPad=6)

section_heading = ParagraphStyle('SectionHeading', parent=styles['Heading2'],
    fontSize=12, textColor=colors.HexColor('#1a3a5c'),
    spaceBefore=10, spaceAfter=4, leading=16,
    borderPad=3)

sub_heading = ParagraphStyle('SubHeading', parent=styles['Heading3'],
    fontSize=11, textColor=colors.HexColor('#2e6da4'),
    spaceBefore=8, spaceAfter=3, leading=14)

body = ParagraphStyle('Body', parent=styles['Normal'],
    fontSize=10, textColor=colors.HexColor('#222222'),
    leading=15, spaceAfter=4, alignment=TA_JUSTIFY)

bullet_style = ParagraphStyle('Bullet', parent=body,
    leftIndent=14, bulletIndent=4, spaceAfter=2)

code_style = ParagraphStyle('Code', parent=styles['Code'],
    fontSize=9, textColor=colors.HexColor('#333333'),
    backColor=colors.HexColor('#f0f4f8'),
    borderPad=6, leading=13, spaceAfter=6)

definition_style = ParagraphStyle('Definition', parent=body,
    backColor=colors.HexColor('#e8f4fd'),
    borderColor=colors.HexColor('#2e6da4'),
    borderWidth=1, borderPad=6,
    leftIndent=8, spaceAfter=6,
    fontName='Helvetica-Oblique')

tip_style = ParagraphStyle('Tip', parent=body,
    backColor=colors.HexColor('#fff8e1'),
    borderColor=colors.HexColor('#f9a825'),
    borderWidth=1, borderPad=6,
    leftIndent=8, spaceAfter=6)

# ── Helper functions ────────────────────────────────────────────
def H1(text):
    return Paragraph(f"<b>{text}</b>", q_heading)

def H2(text):
    return Paragraph(text, section_heading)

def H3(text):
    return Paragraph(text, sub_heading)

def P(text):
    return Paragraph(text, body)

def DEF(text):
    return Paragraph(text, definition_style)

def TIP(text):
    return Paragraph(f"<b>Study Tip:</b> {text}", tip_style)

def HR():
    return HRFlowable(width="100%", thickness=1,
                      color=colors.HexColor('#ccddee'), spaceAfter=6, spaceBefore=6)

def bullets(items):
    els = []
    for item in items:
        els.append(Paragraph(f"• {item}", bullet_style))
    return els

def numbered(items):
    els = []
    for i, item in enumerate(items, 1):
        els.append(Paragraph(f"{i}. {item}", bullet_style))
    return els

def make_table(headers, rows, col_widths=None):
    data = [headers] + rows
    if col_widths is None:
        col_widths = [W / len(headers)] * len(headers)
    t = Table(data, colWidths=col_widths, repeatRows=1)
    style = TableStyle([
        ('BACKGROUND', (0,0), (-1,0), colors.HexColor('#1a3a5c')),
        ('TEXTCOLOR', (0,0), (-1,0), colors.white),
        ('FONTNAME', (0,0), (-1,0), 'Helvetica-Bold'),
        ('FONTSIZE', (0,0), (-1,0), 9),
        ('FONTSIZE', (0,1), (-1,-1), 9),
        ('ROWBACKGROUNDS', (0,1), (-1,-1), [colors.white, colors.HexColor('#eaf2fb')]),
        ('GRID', (0,0), (-1,-1), 0.5, colors.HexColor('#aaaaaa')),
        ('VALIGN', (0,0), (-1,-1), 'TOP'),
        ('LEFTPADDING', (0,0), (-1,-1), 5),
        ('RIGHTPADDING', (0,0), (-1,-1), 5),
        ('TOPPADDING', (0,0), (-1,-1), 4),
        ('BOTTOMPADDING', (0,0), (-1,-1), 4),
        ('WORDWRAP', (0,0), (-1,-1), True),
    ])
    t.setStyle(style)
    return t

def page_number(canvas, doc):
    canvas.saveState()
    canvas.setFont('Helvetica', 8)
    canvas.setFillColor(colors.HexColor('#888888'))
    canvas.drawString(2*cm, 1.2*cm,
        "Community Health Nursing - I Study Guide | B.Sc. Nursing 5th Semester")
    canvas.drawRightString(A4[0]-2*cm, 1.2*cm, f"Page {doc.page}")
    canvas.restoreState()

# ═══════════════════════════════════════════════════════════════
# BUILD CONTENT
# ═══════════════════════════════════════════════════════════════
story = []

# ── COVER PAGE ─────────────────────────────────────────────────
story.append(Spacer(1, 3*cm))
story.append(Paragraph("COMMUNITY HEALTH NURSING - I", cover_title))
story.append(Paragraph("Including Environmental Sciences & Epidemiology", cover_sub))
story.append(Spacer(1, 0.5*cm))

cover_box_data = [[
    Paragraph("<b>Study Guide with Model Answers</b><br/>Essay Type Practice Questions (15 Marks Each)", ParagraphStyle('CB', parent=cover_sub, textColor=colors.white, fontSize=13))
]]
cover_box = Table(cover_box_data, colWidths=[W])
cover_box.setStyle(TableStyle([
    ('BACKGROUND', (0,0), (-1,-1), colors.HexColor('#2e6da4')),
    ('ALIGN', (0,0), (-1,-1), 'CENTER'),
    ('VALIGN', (0,0), (-1,-1), 'MIDDLE'),
    ('TOPPADDING', (0,0), (-1,-1), 16),
    ('BOTTOMPADDING', (0,0), (-1,-1), 16),
    ('ROUNDEDCORNERS', [8,8,8,8]),
]))
story.append(cover_box)
story.append(Spacer(1, 1*cm))

toc_items = [
    ("Q.1", "Epidemiology - Triad, Natural History & Levels of Prevention"),
    ("Q.2", "Primary Health Care - Elements, Principles & Nursing Role"),
    ("Q.3", "Communicable Diseases - TB Epidemiology & Community Nursing"),
    ("Q.4", "Environmental Health - Air Pollution Causes, Effects & Prevention"),
    ("Q.5", "Non-Communicable Diseases - Diabetes Mellitus & Community Management"),
]
toc_data = [[Paragraph("<b>#</b>", body), Paragraph("<b>Topic</b>", body)]]
for num, topic in toc_items:
    toc_data.append([Paragraph(f"<b>{num}</b>", body), Paragraph(topic, body)])
toc_table = Table(toc_data, colWidths=[1.5*cm, W-1.5*cm])
toc_table.setStyle(TableStyle([
    ('BACKGROUND', (0,0), (-1,0), colors.HexColor('#1a3a5c')),
    ('TEXTCOLOR', (0,0), (-1,0), colors.white),
    ('FONTNAME', (0,0), (-1,0), 'Helvetica-Bold'),
    ('ROWBACKGROUNDS', (0,1), (-1,-1), [colors.white, colors.HexColor('#eaf2fb')]),
    ('GRID', (0,0), (-1,-1), 0.4, colors.HexColor('#bbbbbb')),
    ('FONTSIZE', (0,0), (-1,-1), 10),
    ('TOPPADDING', (0,0), (-1,-1), 6),
    ('BOTTOMPADDING', (0,0), (-1,-1), 6),
    ('LEFTPADDING', (0,0), (-1,-1), 8),
]))
story.append(Paragraph("<b>Contents</b>", section_heading))
story.append(toc_table)
story.append(Spacer(1, 1*cm))
story.append(Paragraph("Fifth Semester B.Sc. Nursing | 2025-26", cover_info))
story.append(PageBreak())

# ═══════════════════════════════════════════════════════════════
# Q1
# ═══════════════════════════════════════════════════════════════
story.append(H1("Q.1  Epidemiology: Triad, Natural History & Levels of Prevention  [15 Marks]"))
story.append(P("Define epidemiology. Explain the epidemiological triad. Describe the natural history of disease with levels of prevention."))
story.append(HR())

story.append(H2("1. Definition of Epidemiology"))
story.append(DEF("<b>Epidemiology</b> (John Last): \"Epidemiology is the study of the distribution and determinants of health-related states or events in specified populations and the application of this study to the control of health problems.\""))
story.append(P("It forms the <b>foundation of community health practice</b> - helping us understand who gets disease, why they get it, and how to prevent it."))

story.append(H2("2. The Epidemiological Triad (Host-Agent-Environment Model)"))
story.append(P("The epidemiological triad explains how disease occurs through the interaction of <b>three components</b>. Breaking any one component prevents the disease."))

triad_data = [
    [Paragraph("<b>Component</b>", body), Paragraph("<b>Description</b>", body), Paragraph("<b>Examples</b>", body)],
    [Paragraph("<b>Agent</b>", body), Paragraph("Causative factor producing disease", body),
     Paragraph("Biological: TB bacillus, Malaria parasite\nChemical: pesticides, lead\nPhysical: radiation, noise\nNutritional: deficiency or excess", body)],
    [Paragraph("<b>Host</b>", body), Paragraph("Living organism susceptible to agent", body),
     Paragraph("Age, sex, immunity, nutrition, genetics, occupation, lifestyle", body)],
    [Paragraph("<b>Environment</b>", body), Paragraph("All external conditions influencing disease", body),
     Paragraph("Physical: climate, water quality\nBiological: vectors, reservoirs\nSocial: poverty, overcrowding\nCultural: food habits, beliefs", body)],
]
story.append(make_table([], triad_data[0:1] + triad_data[1:], col_widths=[3*cm, 6*cm, W-9*cm]))
story.append(Spacer(1, 0.3*cm))
story.append(P("<b>Disease occurs when:</b> Agent is virulent + Host is susceptible + Environment favors transmission. <b>Health is maintained when the triad is in BALANCE.</b>"))

story.append(H2("3. Natural History of Disease"))
story.append(P("The natural history describes the <b>course a disease takes from its onset to final outcome</b> without medical intervention. It has two main periods:"))

nh_data = [
    [Paragraph("<b>Period</b>", body), Paragraph("<b>Stage</b>", body), Paragraph("<b>Description</b>", body)],
    [Paragraph("Pre-pathogenesis", body), Paragraph("Before disease", body),
     Paragraph("Host, agent, environment interact but no overt disease yet. Risk factors present (e.g. smoking, malnutrition).", body)],
    [Paragraph("Pathogenesis", body), Paragraph("Incubation period", body),
     Paragraph("Agent entered host but no symptoms yet. Time varies by disease.", body)],
    [Paragraph("", body), Paragraph("Early disease", body),
     Paragraph("Mild/non-specific symptoms. Difficult to diagnose.", body)],
    [Paragraph("", body), Paragraph("Advanced disease", body),
     Paragraph("Clear clinical features, complications may appear.", body)],
    [Paragraph("", body), Paragraph("Outcome", body),
     Paragraph("Recovery, disability, or death.", body)],
]
story.append(make_table([], nh_data[0:1] + nh_data[1:], col_widths=[3.5*cm, 3.5*cm, W-7*cm]))

story.append(H2("4. Levels of Prevention (Leavell & Clark)"))

lop_data = [
    [Paragraph("<b>Level</b>", body), Paragraph("<b>Stage</b>", body), Paragraph("<b>Interventions</b>", body), Paragraph("<b>Examples</b>", body)],
    [Paragraph("<b>Primary Prevention</b>", body), Paragraph("Pre-pathogenesis", body),
     Paragraph("Health promotion + Specific protection", body),
     Paragraph("BCG vaccine, mosquito nets, iodized salt, health education", body)],
    [Paragraph("<b>Secondary Prevention</b>", body), Paragraph("Early disease", body),
     Paragraph("Early diagnosis + Prompt treatment", body),
     Paragraph("Pap smear, sputum microscopy, blood sugar screening", body)],
    [Paragraph("<b>Tertiary Prevention</b>", body), Paragraph("Advanced disease", body),
     Paragraph("Disability limitation + Rehabilitation", body),
     Paragraph("Physiotherapy for stroke, leprosy rehabilitation, dialysis", body)],
]
story.append(make_table([], lop_data, col_widths=[3.5*cm, 3*cm, 5*cm, W-11.5*cm]))

story.append(H2("5. Role of Community Health Nurse in Epidemiology"))
story.extend(bullets([
    "Disease surveillance and reporting to IDSP",
    "Contact tracing during outbreaks",
    "Immunization programs and health education",
    "Screening camps and early case detection",
    "Monitoring cases and follow-up home visits",
]))
story.append(TIP("Always remember the mnemonic: 'Agent breaks, Host protects, Environment supports' - when you modify all three, you control the disease."))
story.append(PageBreak())

# ═══════════════════════════════════════════════════════════════
# Q2
# ═══════════════════════════════════════════════════════════════
story.append(H1("Q.2  Primary Health Care - Elements, Principles & Nursing Role  [15 Marks]"))
story.append(P("Define Primary Health Care. Explain its elements and principles. Describe the role of the community health nurse in implementing PHC."))
story.append(HR())

story.append(H2("1. Definition"))
story.append(DEF("<b>WHO/UNICEF, Alma-Ata Declaration (1978):</b> \"Primary Health Care is essential health care based on practical, scientifically sound, and socially acceptable methods and technology made universally accessible to individuals and families in the community through their full participation and at a cost that the community and country can afford.\""))
story.append(P("Theme: <b>\"Health for All by 2000 AD\"</b> | Venue: Alma-Ata, USSR (now Almaty, Kazakhstan)"))

story.append(H2("2. Eight Essential Elements of PHC"))
elements = [
    ("Education", "Health education on common health problems and prevention methods"),
    ("Nutrition", "Promotion of food supply and proper nutrition"),
    ("Safe Water & Sanitation", "Adequate supply of safe water; basic environmental sanitation"),
    ("Maternal & Child Health", "Including family planning services"),
    ("Immunization", "Against major infectious diseases (UIP)"),
    ("Prevention & Control of Disease", "Including endemic disease control"),
    ("Treatment", "Appropriate treatment of common diseases and injuries"),
    ("Essential Drugs", "Provision of essential medicines at all levels"),
]
el_data = [[Paragraph("<b>No.</b>", body), Paragraph("<b>Element</b>", body), Paragraph("<b>Description</b>", body)]]
for i, (el, desc) in enumerate(elements, 1):
    el_data.append([Paragraph(str(i), body), Paragraph(f"<b>{el}</b>", body), Paragraph(desc, body)])
story.append(make_table([], el_data, col_widths=[1*cm, 4.5*cm, W-5.5*cm]))
story.append(Spacer(1, 0.2*cm))
story.append(P("<i>* Mental health was later added as a 9th element.</i>"))

story.append(H2("3. Principles of PHC"))
principles = [
    ("Equitable Distribution", "Services reach ALL people equally - rural poor, women, marginalized groups. No discrimination."),
    ("Community Participation", "Communities actively involved in planning, implementing, evaluating health services."),
    ("Intersectoral Coordination", "Agriculture, education, water, housing and health sectors work together."),
    ("Appropriate Technology", "Methods must be scientifically sound, culturally acceptable, affordable, and simple."),
    ("Focus on Prevention", "Primary prevention prioritized over curative care - immunization, sanitation, nutrition."),
]
for name, desc in principles:
    story.append(Paragraph(f"• <b>{name}:</b> {desc}", bullet_style))
story.append(Spacer(1, 0.2*cm))

story.append(H2("4. Levels of PHC Infrastructure in India"))
phc_data = [
    [Paragraph("<b>Level</b>", body), Paragraph("<b>Infrastructure</b>", body), Paragraph("<b>Coverage</b>", body)],
    [Paragraph("Sub-Health Centre (SHC)", body), Paragraph("1 ANM + 1 MPW", body), Paragraph("5,000 population (3,000 tribal)", body)],
    [Paragraph("Primary Health Centre (PHC)", body), Paragraph("1 Doctor + supporting staff", body), Paragraph("30,000 population (20,000 tribal)", body)],
    [Paragraph("Community Health Centre (CHC)", body), Paragraph("4 Specialists + 30 beds", body), Paragraph("1,20,000 population", body)],
]
story.append(make_table([], phc_data, col_widths=[5*cm, 5*cm, W-10*cm]))
story.append(P("<i>Now upgraded to Ayushman Arogya Mandirs (AAM) providing comprehensive primary care.</i>"))

story.append(H2("5. Role of Community Health Nurse in PHC"))
roles = [
    ("Health Promotive", "Conduct health education, motivate healthy behaviors, organize immunization campaigns"),
    ("Preventive", "Immunization programs, ANC/PNC care, family planning, disease screening, vector control"),
    ("Curative", "First-level management of common illnesses, wound care, first aid, dispensing ORS/IFA"),
    ("Rehabilitative", "Follow-up of TB/leprosy/diabetes patients, counselling, facilitate rehabilitation access"),
    ("Managerial", "Maintain health records, conduct outreach camps, coordinate ASHA/AWW, prepare reports"),
    ("Research", "Community surveys, needs assessment, participate in health studies"),
    ("Advocacy", "Advocate for vulnerable groups, link community with schemes (PM-JAY, JSY, ICDS)"),
]
role_data = [[Paragraph("<b>Role</b>", body), Paragraph("<b>Key Activities</b>", body)]]
for role, act in roles:
    role_data.append([Paragraph(f"<b>{role}</b>", body), Paragraph(act, body)])
story.append(make_table([], role_data, col_widths=[3.5*cm, W-3.5*cm]))
story.append(TIP("PHC questions are guaranteed in every paper. Memorize the 8 elements, 5 principles, and 7 nursing roles. The Alma-Ata Declaration year (1978) is frequently asked."))
story.append(PageBreak())

# ═══════════════════════════════════════════════════════════════
# Q3
# ═══════════════════════════════════════════════════════════════
story.append(H1("Q.3  Tuberculosis - Epidemiology & Community Nursing Management  [15 Marks]"))
story.append(P("Define communicable diseases. Explain the chain of infection. Describe the epidemiology and nursing management of tuberculosis in the community."))
story.append(HR())

story.append(H2("1. Definition of Communicable Disease"))
story.append(DEF("<b>WHO:</b> \"Communicable diseases are illnesses caused by an infectious agent or its toxic products that arise through transmission from an infected person, animal, or reservoir to a susceptible host, directly or indirectly through an intermediate plant or animal host, vector, or the inanimate environment.\""))

story.append(H2("2. Chain of Infection (6 Links)"))
story.append(P("Breaking <b>any one link</b> in the chain stops disease transmission:"))
chain_data = [
    [Paragraph("<b>Link</b>", body), Paragraph("<b>Description</b>", body), Paragraph("<b>Example (TB)</b>", body), Paragraph("<b>How to Break</b>", body)],
    ["1. Infectious Agent", "Causative pathogen", "Mycobacterium tuberculosis", "Kill with antibiotics (DOTS)"],
    ["2. Reservoir", "Where agent lives/multiplies", "Human lungs (active TB patient)", "Treat all active TB cases"],
    ["3. Portal of Exit", "How agent leaves reservoir", "Respiratory droplets (coughing)", "Cough etiquette, masks"],
    ["4. Mode of Transmission", "How agent travels to new host", "Airborne droplet nuclei (<5 microns)", "Ventilation, UV light"],
    ["5. Portal of Entry", "How agent enters new host", "Inhalation via respiratory tract", "Masks, N95 respirators"],
    ["6. Susceptible Host", "Person with low resistance", "Immunocompromised, malnourished, HIV+", "BCG vaccine, good nutrition"],
]
chain_rows = [[Paragraph(str(r[0]), body), Paragraph(r[1], body), Paragraph(r[2], body), Paragraph(r[3], body)] for r in chain_data[1:]]
story.append(make_table([Paragraph(h, body) for h in ["Link","Description","Example (TB)","How to Break"]], chain_rows,
                        col_widths=[3*cm, 3.5*cm, 3.5*cm, W-10*cm]))

story.append(H2("3. Epidemiology of Tuberculosis"))
story.append(P("<b>Causative Agent:</b> Mycobacterium tuberculosis (acid-fast bacillus, AFB)"))
story.append(P("<b>India's burden:</b> Highest TB burden globally - ~2.8 million new cases/year (26% of world total). Goal: <b>Eliminate TB by 2025.</b>"))

story.append(H3("Host Factors"))
story.extend(bullets(["Most common in 15-45 years (productive age group)", "More common in males",
    "Malnutrition greatly increases susceptibility", "HIV+ patients have 20x higher risk of active TB",
    "Overcrowding, poverty, poor ventilation increase risk"]))

story.append(H3("Types of TB"))
tb_types = [
    [Paragraph("<b>Type</b>", body), Paragraph("<b>Site</b>", body), Paragraph("<b>Features</b>", body)],
    [Paragraph("Pulmonary TB", body), Paragraph("Lungs (most common)", body), Paragraph("Most infectious; sputum smear positive", body)],
    [Paragraph("Extrapulmonary TB", body), Paragraph("Lymph nodes, spine (Pott's disease), meninges, kidneys", body), Paragraph("Less infectious; sputum negative", body)],
    [Paragraph("MDR-TB", body), Paragraph("Lungs/others", body), Paragraph("Resistant to Rifampicin + Isoniazid; harder to treat", body)],
]
story.append(make_table([], tb_types, col_widths=[3.5*cm, 5*cm, W-8.5*cm]))

story.append(H3("Diagnosis"))
diag_data = [
    [Paragraph("<b>Test</b>", body), Paragraph("<b>Purpose</b>", body)],
    ["Sputum smear microscopy (ZN stain)", "Detect AFB - most common, cheapest"],
    ["CBNAAT / TrueNat", "Molecular test; also detects drug resistance"],
    ["Chest X-ray", "Shows cavities, infiltrates, consolidation"],
    ["Mantoux test", "Tuberculin skin test; shows past exposure"],
    ["IGRA", "Interferon Gamma Release Assay; more specific"],
]
diag_rows = [[Paragraph(r[0], body), Paragraph(r[1], body)] for r in diag_data[1:]]
story.append(make_table([Paragraph(h, body) for h in ["Test","Purpose"]], diag_rows,
                        col_widths=[5*cm, W-5*cm]))

story.append(H2("4. NTEP - National TB Elimination Programme"))
story.append(P("<b>Strategy:</b> DOTS (Directly Observed Treatment Short-course) - ensures compliance, prevents drug resistance."))
story.append(P("<b>Nikshay Poshan Yojana:</b> ₹500/month nutritional support to all TB patients during treatment."))
treat_data = [
    [Paragraph("<b>Category</b>", body), Paragraph("<b>Regimen</b>", body), Paragraph("<b>Duration</b>", body)],
    ["New cases (Drug-sensitive)", "2HRZE + 4HR", "6 months"],
    ["MDR-TB", "Bedaquiline-based regimen", "6-9 months"],
    ["XDR-TB", "Injectable + oral combination", "18-20 months"],
]
treat_rows = [[Paragraph(r[0], body), Paragraph(r[1], body), Paragraph(r[2], body)] for r in treat_data[1:]]
story.append(make_table([Paragraph(h, body) for h in ["Category","Regimen","Duration"]], treat_rows,
                        col_widths=[5*cm, 4*cm, W-9*cm]))
story.append(P("<b>H</b>=Isoniazid, <b>R</b>=Rifampicin, <b>Z</b>=Pyrazinamide, <b>E</b>=Ethambutol"))

story.append(H2("5. Nursing Management of TB in Community"))
nursing_tb = [
    ("Case Finding", "Identify presumptive TB (cough >2 weeks) during home visits; refer for sputum examination"),
    ("DOTS Supervision", "Observe drug intake directly in intensive phase; monitor for adverse drug reactions"),
    ("Health Education", "Cough etiquette, complete treatment, nutrition counselling, danger of MDR-TB"),
    ("Contact Screening", "Screen all household contacts; give IPT (Isoniazid Preventive Therapy) to eligible contacts"),
    ("Infection Control", "Cross-ventilation, sunlight exposure, separate sleeping, mask use"),
    ("Nutritional Support", "High-protein diet; help access Nikshay Poshan Yojana ₹500/month"),
    ("Recording & Reporting", "Mandatory Nikshay notification; maintain treatment card; report outcomes"),
    ("Psychosocial Support", "Reduce stigma, counselling, mobilize Nikshay Mitras (community supporters)"),
]
tb_nr = [[Paragraph(f"<b>{n}</b>", body), Paragraph(d, body)] for n, d in nursing_tb]
story.append(make_table([Paragraph("<b>Role</b>", body), Paragraph("<b>Actions</b>", body)], tb_nr,
                        col_widths=[4*cm, W-4*cm]))
story.append(TIP("TB questions: Always include the chain of infection, DOTS strategy, NTEP goals (eliminate by 2025), Nikshay Poshan Yojana, and contact tracing in your answer."))
story.append(PageBreak())

# ═══════════════════════════════════════════════════════════════
# Q4
# ═══════════════════════════════════════════════════════════════
story.append(H1("Q.4  Environmental Health - Air Pollution  [15 Marks]"))
story.append(P("Define environmental health. Classify environmental pollution. Explain the causes, effects, and prevention of air pollution with the role of nurse."))
story.append(HR())

story.append(H2("1. Definition of Environmental Health"))
story.append(DEF("<b>WHO:</b> \"Environmental health addresses all the physical, chemical, and biological factors external to a person, and all the related factors impacting behaviours. It encompasses the assessment and control of those environmental factors that can potentially affect health.\""))

story.append(H2("2. Classification of Environmental Pollution"))
poll_data = [
    [Paragraph("<b>Type</b>", body), Paragraph("<b>Main Sources</b>", body), Paragraph("<b>Key Pollutants</b>", body)],
    ["Air Pollution", "Industries, vehicles, burning", "SOx, NOx, CO, PM2.5, PM10, ozone"],
    ["Water Pollution", "Sewage, industrial effluents", "Heavy metals, pathogens, nitrates"],
    ["Soil Pollution", "Pesticides, industrial waste", "DDT, lead, mercury, plastic"],
    ["Noise Pollution", "Traffic, industry, construction", "Excessive decibel levels (>85 dB)"],
    ["Radiation", "Nuclear plants, X-rays, UV", "Gamma rays, UV radiation"],
    ["Thermal Pollution", "Hot water from power plants", "Elevated water temperature"],
]
poll_rows = [[Paragraph(r[0], body), Paragraph(r[1], body), Paragraph(r[2], body)] for r in poll_data[1:]]
story.append(make_table([Paragraph(h, body) for h in ["Type","Main Sources","Key Pollutants"]], poll_rows,
                        col_widths=[3*cm, 5.5*cm, W-8.5*cm]))

story.append(H2("3. Sources/Causes of Air Pollution"))
story.append(H3("Outdoor (Ambient) Air Pollution"))
out_data = [
    [Paragraph("<b>Source</b>", body), Paragraph("<b>Pollutants Released</b>", body)],
    ["Motor vehicles", "CO, NOx, hydrocarbons, PM2.5, PM10"],
    ["Industries/factories", "SO₂, NOx, heavy metals, toxic gases"],
    ["Power plants (coal)", "SO₂, CO₂, fly ash"],
    ["Agricultural burning", "CO, black carbon, PM"],
    ["Construction", "Dust, silica particles"],
]
out_rows = [[Paragraph(r[0], body), Paragraph(r[1], body)] for r in out_data[1:]]
story.append(make_table([Paragraph(h, body) for h in ["Source","Pollutants Released"]], out_rows,
                        col_widths=[4.5*cm, W-4.5*cm]))

story.append(H3("Indoor Air Pollution"))
story.append(P("<b>Major issue in India:</b> Biomass cooking fuel (wood, dung, crop waste) affects ~700 million rural women and children."))
ind_data = [
    [Paragraph("<b>Source</b>", body), Paragraph("<b>Pollutants</b>", body)],
    ["Biomass burning for cooking", "CO, PM2.5, benzene, formaldehyde"],
    ["Tobacco smoke", "CO, tar, nicotine, 4000+ carcinogens"],
    ["Kerosene lamps", "Soot, PM2.5"],
    ["Synthetic paints/adhesives", "Volatile Organic Compounds (VOCs)"],
    ["Mold and dampness", "Fungal spores, mycotoxins"],
]
ind_rows = [[Paragraph(r[0], body), Paragraph(r[1], body)] for r in ind_data[1:]]
story.append(make_table([Paragraph(h, body) for h in ["Source","Pollutants"]], ind_rows,
                        col_widths=[5*cm, W-5*cm]))

story.append(H2("4. Effects of Air Pollution on Health"))
eff_data = [
    [Paragraph("<b>System</b>", body), Paragraph("<b>Effects</b>", body)],
    ["Respiratory", "ARI (children), COPD, asthma, bronchitis, lung cancer, silicosis"],
    ["Cardiovascular", "Heart attack, stroke (PM2.5 enters bloodstream), arteriosclerosis"],
    ["Neurological", "Lead/mercury → brain damage, reduced IQ in children; CO → coma, death"],
    ["Carcinogenic", "Lung cancer (PM2.5, benzene, tobacco), bladder cancer, leukemia"],
    ["Reproductive", "Low birth weight, preterm birth, fetal brain impairment"],
    ["Environmental", "Acid rain (SO₂+NOx), global warming (CO₂), ozone depletion (CFCs)"],
]
eff_rows = [[Paragraph(r[0], body), Paragraph(r[1], body)] for r in eff_data[1:]]
story.append(make_table([Paragraph(h, body) for h in ["System Affected","Effects"]], eff_rows,
                        col_widths=[3.5*cm, W-3.5*cm]))

story.append(H2("5. Prevention and Control of Air Pollution"))
story.extend(bullets([
    "<b>At source:</b> Renewable energy (solar, wind), catalytic converters in vehicles, CNG/electric vehicles, industrial emission standards (scrubbers, filters)",
    "<b>In transmission:</b> Tree plantation, green belts, air quality monitoring (NCAP), industrial zoning laws",
    "<b>At individual level:</b> PM Ujjwala Yojana (LPG), improved cookstoves, tobacco ban enforcement, masks during high AQI days",
    "<b>Legislative:</b> Air Act 1981, Environment Protection Act 1986, National Ambient Air Quality Standards (NAAQS), National Clean Air Programme (NCAP) - 20-30% PM reduction target",
]))

story.append(H2("6. Role of Community Health Nurse in Air Pollution Control"))
ap_roles = [
    ("Health Education", "Teach indoor/outdoor pollution sources; motivate families to switch to LPG/clean cookstoves"),
    ("Screening", "Identify respiratory symptoms in children/elderly; screen for COPD and ARI; refer promptly"),
    ("Advocacy", "Advocate for tree plantation, green spaces; report illegal burning; support anti-tobacco campaigns"),
    ("Community Mobilization", "Organize awareness meetings; motivate enrollment under PM Ujjwala Yojana"),
    ("Disease Prevention", "Ensure PCV, influenza immunization; promote breastfeeding for lung immunity"),
    ("Occupational Health", "Identify workers in high-risk industries; ensure PPE use; periodic health checks"),
]
ap_role_rows = [[Paragraph(f"<b>{n}</b>", body), Paragraph(d, body)] for n, d in ap_roles]
story.append(make_table([Paragraph("<b>Role</b>", body), Paragraph("<b>Actions</b>", body)], ap_role_rows,
                        col_widths=[4*cm, W-4*cm]))
story.append(TIP("Air pollution accounts for 7 million deaths/year globally (WHO). Always mention the Air Act 1981 and NCAP in your answer. Indoor air pollution from biomass fuel is highly relevant in Indian context."))
story.append(PageBreak())

# ═══════════════════════════════════════════════════════════════
# Q5
# ═══════════════════════════════════════════════════════════════
story.append(H1("Q.5  Non-Communicable Diseases - Diabetes Mellitus  [15 Marks]"))
story.append(P("Define non-communicable diseases. Explain the epidemiology of diabetes mellitus. Describe the nursing management of a diabetic patient in the community setting."))
story.append(HR())

story.append(H2("1. Definition of Non-Communicable Diseases"))
story.append(DEF("<b>WHO:</b> \"Non-communicable diseases (NCDs), also known as chronic diseases, tend to be of long duration and are the result of a combination of genetic, physiological, environmental and behavioural factors.\""))
story.append(P("<b>Major NCDs:</b> Cardiovascular diseases, Cancers, Chronic respiratory diseases, Diabetes mellitus, Mental health disorders."))
story.append(P("NCDs account for <b>63% of all deaths in India</b> and 74% globally."))

story.append(H2("2. Common Risk Factors for NCDs"))
rf_data = [
    [Paragraph("<b>Modifiable (Preventable)</b>", body), Paragraph("<b>Non-modifiable</b>", body)],
    [Paragraph("• Tobacco use\n• Physical inactivity\n• Unhealthy diet\n• Harmful alcohol use\n• Obesity/overweight\n• Chronic stress", body),
     Paragraph("• Age\n• Sex\n• Family history/genetics\n• Ethnicity (South Asians at higher risk)", body)],
]
story.append(make_table([], rf_data, col_widths=[W/2, W/2]))

story.append(H2("3. Epidemiology of Diabetes Mellitus"))
story.append(H3("Classification"))
dm_type = [
    [Paragraph("<b>Type</b>", body), Paragraph("<b>Mechanism</b>", body), Paragraph("<b>Features</b>", body)],
    ["Type 1 DM", "Autoimmune destruction of beta cells", "Insulin-dependent; mostly children/young adults"],
    ["Type 2 DM", "Insulin resistance + inadequate secretion", "Most common (~90%); adults; lifestyle-related"],
    ["Gestational DM", "Develops during pregnancy", "Risk of Type 2 later in life"],
]
dm_rows = [[Paragraph(r[0], body), Paragraph(r[1], body), Paragraph(r[2], body)] for r in dm_type[1:]]
story.append(make_table([Paragraph(h, body) for h in ["Type","Mechanism","Features"]], dm_rows,
                        col_widths=[3*cm, 5*cm, W-8*cm]))

story.append(H3("Burden in India"))
story.extend(bullets([
    "537 million diabetics worldwide (IDF, 2021); projected 783 million by 2045",
    "India: ~101 million diabetics (ICMR INDIAB, 2023) - 'Diabetes Capital of the World'",
    "Prevalence: ~11.4% of adults; urban > rural (12.4% vs 7.2%)",
    "<b>57% of diabetics in India are UNDIAGNOSED</b> - a major public health crisis",
]))

story.append(H3("Diagnostic Criteria (WHO/ADA)"))
diag_dm = [
    [Paragraph("<b>Test</b>", body), Paragraph("<b>Normal</b>", body), Paragraph("<b>Pre-diabetes</b>", body), Paragraph("<b>Diabetes</b>", body)],
    ["Fasting Blood Glucose", "<100 mg/dL", "100-125 mg/dL", "≥126 mg/dL"],
    ["Post-prandial (2hr)", "<140 mg/dL", "140-199 mg/dL", "≥200 mg/dL"],
    ["HbA1c", "<5.7%", "5.7-6.4%", "≥6.5%"],
    ["Random Blood Glucose", "-", "-", "≥200 + symptoms"],
]
diag_dm_rows = [[Paragraph(r[0], body), Paragraph(r[1], body), Paragraph(r[2], body), Paragraph(r[3], body)] for r in diag_dm[1:]]
story.append(make_table([Paragraph(h, body) for h in ["Test","Normal","Pre-diabetes","Diabetes"]], diag_dm_rows,
                        col_widths=[4*cm, 3*cm, 3*cm, W-10*cm]))

story.append(H3("Complications of Diabetes"))
comp_data = [
    [Paragraph("<b>Complication</b>", body), Paragraph("<b>Description</b>", body)],
    ["Diabetic Retinopathy", "Leading cause of blindness in adults"],
    ["Diabetic Nephropathy", "Leading cause of chronic kidney disease"],
    ["Diabetic Neuropathy", "Numbness, tingling, nerve damage in feet"],
    ["Diabetic Foot", "Ulcers, gangrene, risk of amputation"],
    ["Cardiovascular Disease", "2-4x higher risk of heart attack and stroke"],
    ["Hypoglycaemia", "Sweating, trembling, confusion from excess insulin"],
]
comp_rows = [[Paragraph(r[0], body), Paragraph(r[1], body)] for r in comp_data[1:]]
story.append(make_table([Paragraph(h, body) for h in ["Complication","Description"]], comp_rows,
                        col_widths=[4.5*cm, W-4.5*cm]))

story.append(H2("4. Nursing Management of Diabetes in Community"))
story.append(H3("A. Health Assessment"))
story.extend(bullets([
    "Complete history: symptoms, family history, lifestyle, medications",
    "Measure: weight, BMI, waist circumference, blood pressure",
    "Assess feet: ulcers, neuropathy (monofilament test)",
    "Check blood glucose (FBS, PPBS, HbA1c)",
]))

story.append(H3("B. Non-Pharmacological Management (Lifestyle Modification)"))
lifestyle = [
    ("Medical Nutrition Therapy", "Reduce refined carbs/sugar; increase fibre; limit fat; small frequent meals (5-6/day); increase millets (jowar, bajra)"),
    ("Physical Activity", "150 min/week moderate exercise (brisk walking); resistance exercises 2-3x/week; break sitting every 30 min"),
    ("Weight Management", "5-10% weight loss significantly improves glucose control; BMI target <23 kg/m²"),
    ("Tobacco Cessation", "Smoking worsens all diabetic complications; refer to qCessation helpline 1800-11-2356"),
    ("Stress Management", "Yoga, meditation, deep breathing; psychological support and counselling"),
]
for name, desc in lifestyle:
    story.append(Paragraph(f"• <b>{name}:</b> {desc}", bullet_style))

story.append(H3("C. Foot Care Education (Critical)"))
story.extend(bullets([
    "Inspect feet DAILY for cuts, blisters, redness, swelling",
    "Wash with lukewarm water, dry between toes thoroughly",
    "Never walk barefoot - always wear well-fitting diabetic footwear",
    "Trim nails straight across; do not cut corners",
    "Report any wound immediately - do not self-treat",
]))

story.append(H3("D. Regular Follow-Up Schedule"))
fu_data = [
    [Paragraph("<b>Investigation</b>", body), Paragraph("<b>Frequency</b>", body)],
    ["Blood glucose (FBS/PPBS)", "Monthly"],
    ["HbA1c", "Every 3 months"],
    ["Kidney function + urine microalbumin", "Every 6 months"],
    ["Eye examination (fundus)", "Annually"],
    ["Lipid profile", "Annually"],
    ["Foot examination", "Every visit"],
    ["Blood pressure monitoring", "Every visit"],
]
fu_rows = [[Paragraph(r[0], body), Paragraph(r[1], body)] for r in fu_data[1:]]
story.append(make_table([Paragraph(h, body) for h in ["Investigation","Frequency"]], fu_rows,
                        col_widths=[6*cm, W-6*cm]))

story.append(H3("E. Linking with National Programs"))
story.extend(bullets([
    "Register patient under NP-NCD at Ayushman Arogya Mandir",
    "Ensure access to free antidiabetic drugs from government supply",
    "Link elderly patients with NPHCE services",
    "Connect with PM-JAY (Ayushman Bharat) for inpatient coverage",
    "Motivate community participation in NCD Screening Campaign",
]))

story.append(H2("5. Prevention of Diabetes (Community Level)"))
story.extend(bullets([
    "Organize NCD screening camps for all adults 30+ years",
    "Mass health education on diet, physical activity, and obesity prevention",
    "School health programs - teach children healthy eating habits early",
    "Promote millets under India's Millet Mission (Shree Anna)",
    "<b>Diabetes Prevention Programme trial:</b> Lifestyle modification reduces onset by 58%",
]))
story.append(TIP("For diabetes questions: Include diagnostic criteria table, all 6 complications, and the NP-NCD program. The 57% undiagnosed statistic and India as 'Diabetes Capital of the World' are important facts to mention."))

# ── Final summary box ────────────────────────────────────────────
story.append(PageBreak())
story.append(H1("Quick Revision - Key Facts at a Glance"))
summary_data = [
    [Paragraph("<b>Topic</b>", body), Paragraph("<b>Key Points to Remember</b>", body)],
    [Paragraph("Epidemiology", body), Paragraph("Triad: Agent + Host + Environment | Levels: Primary, Secondary, Tertiary | Leavell & Clark", body)],
    [Paragraph("PHC", body), Paragraph("Alma-Ata 1978 | 8 Elements | 5 Principles | 'Health for All' | ANM at SHC", body)],
    [Paragraph("Tuberculosis", body), Paragraph("AFB | DOTS | Eliminate by 2025 | Nikshay ₹500/month | MDR-TB resistant to HR", body)],
    [Paragraph("Air Pollution", body), Paragraph("Indoor (biomass) + Outdoor | 7 million deaths/year | Air Act 1981 | PM Ujjwala Yojana", body)],
    [Paragraph("Diabetes", body), Paragraph("101 million in India | 57% undiagnosed | HbA1c ≥6.5% | NP-NCD | Foot care daily", body)],
]
story.append(make_table([], summary_data, col_widths=[3.5*cm, W-3.5*cm]))
story.append(Spacer(1, 0.5*cm))
story.append(Paragraph("Answer Structure for ALL Essay Questions:", section_heading))
story.append(DEF("Definition → Classification/Types → Epidemiology → Causes/Risk Factors → Clinical Features → Management → Nursing Role → Prevention → Conclusion"))
story.append(Spacer(1, 0.5*cm))
story.append(P("<b>All the best for your exams!</b>"))

# ── BUILD PDF ───────────────────────────────────────────────────
doc.build(story, onFirstPage=page_number, onLaterPages=page_number)
print(f"PDF created: {OUTPUT}")