Summary Notes course 'Introduction analytical epidemiology and public health' (HNH-28803)

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Notes‌‌course‌‌‘Introduction‌‌analytical‌‌
epidemiology‌‌and‌‌public‌‌health’‌‌
(HNH-28803)‌ ‌
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Content‌ ‌

Learning‌‌goals‌‌HNH-28803‌ 2‌ ‌

Notes‌‌week‌‌1‌ 3‌ ‌
1.1‌‌Association‌‌and‌‌causation‌ 3‌ ‌
1.2‌‌Study‌‌designs‌‌in‌‌analytical‌‌epidemiology‌ 4‌ ‌
1.3‌‌Internal‌‌and‌‌external‌‌validity‌ 8‌ ‌
1.4‌‌Measures‌‌of‌‌association‌ 15‌ ‌
1.5‌‌Measures‌‌of‌‌public‌‌health‌‌impact‌ 19‌ ‌
1.6‌‌Individual‌‌or‌‌population?‌‌The‌‌prevention‌‌paradox‌ 24‌ ‌
1.7‌‌Measures‌‌in‌‌analytical‌‌epidemiology‌ 27‌ ‌
1.8‌‌Self-test‌ 27‌ ‌
Summary‌‌of‌‌the‌‌moderator‌ 28‌ ‌

Notes‌‌week‌‌2‌ 30‌ ‌
2.1‌‌Cohort‌‌study‌ 30‌ ‌
2.2‌‌Case‌‌control‌‌study‌ 33‌ ‌
2.3‌‌Intervention‌‌trial‌ 38‌ ‌
2.4‌‌Risk‌‌factor‌‌non-communicable‌‌diseases‌ 42‌ ‌
2.5‌‌Instruction‌‌poster‌‌presentation‌ 49‌ ‌
Summary‌‌of‌‌the‌‌moderator‌ 49‌ ‌
Notes‌‌week‌‌3‌ 51‌ ‌
3.1‌‌Disease‌‌screening‌ 51‌ ‌
3.2‌‌Self-test‌ 58‌ ‌
3.3‌‌Poster‌‌presentation:‌‌peer‌‌review‌ 58‌ ‌
3.4‌‌Exercises‌‌to‌‌practice‌ 58‌ ‌
3.5‌‌Follow‌‌group‌‌discussions‌ 58‌ ‌
Summary‌‌of‌‌the‌‌moderator‌ 58‌ ‌
Appendix‌‌I‌‌-‌‌Assignment‌‌1.7‌ 59‌ ‌
1.7‌‌Measures‌‌in‌‌analytical‌‌epidemiology‌ 59‌ ‌
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Introduction‌‌analytical‌‌epidemiology‌‌and‌‌public‌‌health‌‌‌(HNH-28803)‌ 1‌ ‌

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Note:‌‌All‌‌reading‌‌chapters‌‌in‌‌this‌‌summary‌‌are‌‌derived‌‌from:‌ ‌
Webb‌‌C.‌‌&‌‌Bain‌‌P.‌‌(2017).‌‌Essential‌‌epidemiology:‌‌an‌‌introduction‌‌for‌‌students‌‌and‌‌health‌‌
professionals.‌‌Cambridge‌‌University‌‌Press,‌‌3nd‌‌or‌‌4th‌‌edition.‌ ‌
Wageningen‌‌University‌‌and‌‌Research‌‌(WUR).‌‌ ‌
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Introduction‌‌analytical‌‌epidemiology‌‌and‌‌public‌‌health‌‌‌(HNH-28803)‌ 2‌ ‌

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Learning‌‌goals‌‌HNH-28803‌ ‌
● Describe‌‌the‌‌main‌‌nutrition-related‌‌and‌‌other‌‌risk‌‌factors‌‌of‌‌major‌‌communicable‌‌and‌‌
non-communicable‌‌diseases:‌‌ ‌
○ diabetes‌‌mellitus;‌ ‌
○ cancer;‌ ‌
○ cardiovascular‌‌diseases;‌ ‌
○ mental‌‌health‌‌disorders‌‌in‌‌elderly‌‌people;‌ ‌
○ osteoporosis;‌ ‌
● Calculate‌‌and‌‌interpret‌‌basic‌‌measures‌‌used‌‌in‌‌epidemiology‌‌and‌‌public‌‌health,‌‌
including:‌‌ ‌
○ various‌‌measures‌‌of‌‌association,‌‌e.g.,‌‌IRR,‌‌IPR,‌‌RR,‌‌and‌‌OR;‌ ‌
○ (Population)‌‌attributable‌‌risk‌‌and‌‌fraction‌‌(PAR‌‌and‌‌PAF);‌ ‌
● Explain‌‌basic‌‌study‌‌designs‌‌used‌‌in‌‌epidemiology‌‌and‌‌public‌‌health‌‌and‌‌indicate‌‌
major‌‌(dis)advantages‌‌of‌‌the‌‌various‌‌study‌‌designs,‌‌including:‌ ‌
○ ecological‌‌study;‌ ‌
○ cross-sectional‌‌study;‌ ‌
○ cohort‌‌study;‌ ‌
○ case-control‌‌study;‌ ‌
○ randomized‌‌controlled‌‌trial;‌ ‌
● Explain‌‌selection‌‌bias,‌‌information‌‌bias,‌‌and‌‌confounding;‌ ‌
● Explain‌‌the‌‌difference‌‌between‌‌internal‌‌and‌‌external‌‌validity‌‌of‌‌epidemiological‌‌
findings‌‌and‌‌interpret‌‌precision‌‌measures;‌ ‌
● Explain‌‌the‌‌difference‌‌between‌‌population‌‌and‌‌individual‌‌prevention‌‌strategies,‌‌and‌‌
the‌‌role‌‌of‌‌early‌‌detection‌‌in‌‌primary‌‌prevention,‌‌and‌‌calculate‌‌various‌‌measures‌‌
used‌‌for‌‌disease‌‌screening,‌‌including‌‌sensitivity,‌‌specificity,‌‌and‌‌diagnostic‌‌value.‌ ‌‌




Introduction‌‌analytical‌‌epidemiology‌‌and‌‌public‌‌health‌‌‌(HNH-28803)‌ 3‌ ‌

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Notes‌‌week‌‌1‌ ‌
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1.1‌‌Association‌‌and‌‌causation‌ ‌
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1.1a‌‌Website‌‌-‌‌Spurious‌‌correlations‌ ‌
N/A‌ ‌
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1.1b‌‌Association‌‌and‌‌causation‌ ‌
The‌e ‌ tiology‌‌‌studies‌‌the‌‌causes‌‌and‌‌origins‌‌of‌‌diseases.‌‌What‌‌causes‌‌a‌‌disease?‌‌The‌‌
causes‌‌mostly‌‌don’t‌‌exist‌‌in‌‌isolation,‌‌but‌‌are‌‌multifactorial.‌‌A‌s ‌ ufficient‌‌cause‌‌‌is‌‌a‌‌
(combination‌‌of)‌‌factor(s)‌‌that‌‌will‌‌inevitably‌‌lead‌‌to‌‌a‌‌disease.‌‌A‌c ‌ omponent‌‌cause‌‌‌is‌‌a‌‌
factor‌‌that‌‌contributes‌‌towards‌‌disease‌‌causation,‌‌but‌‌cannot‌‌do‌‌it‌‌alone‌‌(aids,‌‌poor‌‌nutrition,‌‌
exposure‌‌to‌‌infection).‌‌Elimination‌‌of‌‌a‌‌component‌‌cause‌‌will‌‌not‌‌fully‌‌eradicate‌‌disease.‌‌
When‌‌you‌‌prevent‌‌one‌‌component‌‌cause,‌‌not‌‌all‌‌sufficient‌‌causes‌‌are‌‌blocked.‌‌A‌n ‌ ecessary‌‌
cause‌‌‌is‌‌any‌‌component‌‌cause‌‌that‌‌is‌‌required‌‌for‌‌the‌‌development‌‌of‌‌the‌‌disease‌‌
(exposure‌‌to‌‌TBC‌‌bacteria).‌‌ ‌
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In‌‌public‌‌health‌‌practice,‌‌you‌‌usually‌‌need‌‌to‌‌intervene‌‌on‌‌multiple‌‌risk‌‌factors‌‌
simultaneously:‌‌so-called‌‌‘complex‌‌interventions’.‌P ‌ revention‌‌‌is‌‌only‌‌possible‌‌for‌‌risk‌‌factors‌‌
that‌‌are‌c ‌ ausally‌‌‌related‌‌to‌‌the‌‌disease.‌‌ ‌
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Cause‌‌and‌‌effect,‌‌what‌‌came‌‌first;‌‌the‌‌chicken‌‌or‌‌the‌‌egg?‌C ‌ ause‌‌‌must‌‌precede‌‌the‌‌effect‌‌
(absolute‌‌requirement).‌‌In‌‌epidemiology,‌‌we‌‌mostly‌‌do‌‌not‌‌observe‌‌cause‌‌and‌‌effect,‌‌but‌‌
associations‌‌‌between‌‌exposure‌‌and‌‌outcomes.‌‌Before‌‌you‌‌think‌‌about‌‌a‌‌cause,‌‌think‌‌about‌‌
non-causal‌‌associations.‌‌Non-causal‌‌associations‌‌can‌‌be‌‌due‌‌to‌‌bias,‌‌confounding‌‌or‌‌
because‌‌of‌‌an‌‌artefact‌‌due‌‌to‌‌change.‌‌There‌‌could‌‌also‌‌be‌‌a‌r‌ everse‌‌causation‌.‌‌Is‌‌a‌‌
disease‌‌causes‌‌by‌‌a‌‌risk‌‌factor,‌‌or‌‌is‌‌a‌‌risk‌‌factor‌‌the‌‌consequence‌‌of‌‌the‌‌disease?‌‌ ‌
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The‌‌role‌‌of‌‌time‌‌is‌‌very‌‌important.‌‌During‌‌life,‌‌you‌‌gather‌‌more‌‌and‌‌more‌‌component‌‌causes.‌‌
At‌‌a‌‌point‌‌of‌‌time‌‌you‌‌have‌‌a‌‌complete‌s ‌ ufficient‌‌cause‌,‌‌after‌‌which‌‌a‌d ‌ isease‌‌‌will‌‌occur.‌‌
This‌‌can‌‌be‌‌a‌‌long‌‌process,‌‌therefore‌‌the‌d ‌ iagnosis‌‌‌can‌‌be‌‌on‌‌a‌‌much‌‌later‌‌point‌‌of‌‌time.‌‌
The‌‌period‌‌between‌‌the‌‌onset‌‌of‌‌the‌‌disease‌‌and‌‌the‌‌diagnosis‌‌is‌‌called‌‌the‌l‌atency‌‌time‌.‌‌
The‌‌period‌‌before‌‌the‌‌onset‌‌of‌‌a‌‌disease‌‌is‌‌called‌‌the‌i‌nduction‌‌time‌.‌‌This‌‌can‌‌already‌‌start‌‌
at‌‌preconception‌‌(think‌‌about‌‌the‌‌role‌‌of‌‌genetics).‌‌Note‌‌that‌‌not‌‌all‌‌exposures‌‌increase‌‌the‌‌
risk‌‌of‌‌a‌‌disease,‌‌some‌‌prevent‌‌it‌‌(like‌‌vaccinations).‌‌ ‌
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Introduction‌‌analytical‌‌epidemiology‌‌and‌‌public‌‌health‌‌‌(HNH-28803)‌ 4‌ ‌