Assessing Representativeness

# Load required libraries
library(tidyverse)
library(readxl)
library(knitr)
library(kableExtra)
library(gtsummary)
library(patchwork)

## Original microbiome_dataset values:

## 
##   No  Yes <NA> 
## 3656  203    0

## Data loaded successfully!

## Total participants: 3859

## Group distribution:

## 
## Excluded Included     <NA> 
##     3656      203        0

Overview

This report assesses the representativeness of the selected Microbiome dataset cohort relative to the overall cohort (hereafter referred to as the “Microbiome” and “overall” cohorts).

Tables and plots are presented to assess the frequency, distribution, etc. for each variable.

Assess representativeness according to demographic/baseline variable set: - Outlined in the “Variable Category” column of the data dictionary sheet in the data set.

Summary of Results

We find the distributions for most “primary” variables broadly similar between the Microbiome and overall cohorts, with some notable differences:

Primary Variables: - Maternal age at birth differs significantly (p<0.001), with the Microbiome cohort being slightly older (mean 33.0 vs 31.8 years) - Maternal asthma shows a significant difference (p=0.037), with lower prevalence in the Microbiome cohort (3.9% vs 8.1%) - DASS domains show some differences, with the Microbiome cohort having slightly better mental health scores at 36 weeks - Other demographic variables (gender, birth weight/length, BMI, diabetes, etc.) are well-balanced

Sample Availability: - The Microbiome cohort shows significantly higher engagement across all questionnaire measures (all p<0.001) - Much higher completion rates for ASQ questionnaires at all time points - Greater participation in follow-up assessments

Key Differences: - Twin births are over-represented in the Microbiome cohort (8.9% vs 3.2%, p<0.001) - Child age differs significantly, with Microbiome children being older (mean 4.5 vs 3.8 years, p<0.001) - BMI at 3 years is significantly lower in the Microbiome cohort (15.5 vs 15.9, p=0.004)

Data & Methods

DEIDENTIFIED Full Participant list Perron - Final dataset July 2025.xlsx
- Contains data and data dictionary.
After some cleaning and the assignment of variable names, we get the following dimensions (rows, columns):

dim(dat)

## [1] 3859   86

We assess the variable similarity between Microbiome cohort (N = 203) and overall cohort (N = 3859) using:

Summary tabulations
Distributional plots
Simple statistical tests
- Note: the p-values presented can be interpreted with a grain of salt. Often in cases with large sample sizes, non-meaningful differences (in reality) return “significant” p-values.

Variable Breakdown

There are ~79 candidate variables that can be used to assess the similarity between the Microbiome and overall cohorts. - These variables are broadly “sample availability”, “child/maternal demographic”, “child/maternal characteristics”.

Firstly, let’s select just a handful candidate variables with the aim of getting an overall “snapshot” of the similarity between the sub-cohort and overall cohort. - For example, we want to ensure the sub-cohort is not entirely female, born in a single year, of a single ethnic origin, etc.

“Primary” variables (amended to include the 19 variables outlined) - Gender of child - Maternal age at birth - Maternal pre-pregnancy weight - Maternal pre-pregnancy height - Maternal pre-pregnancy BMI - Infant weight - Infant length - Infant BMI at birth - Infant ethnic origin - Indigenous status of baby - Vaginal or C-section birth - Maternal gestational diabetes status - Maternal Type 2 Diabetes - Maternal mental health diagnosis (Depression, Anxiety disorder, Bipolar, Schizophrenia, OCD, Anorexia Nervous, Specific Phobias, Behavioural Disorders) - Individual disorder breakdown: Each mental health condition is now analyzed separately, allowing participants with multiple conditions to be counted in each relevant category - Any mental health diagnosis: Overall indicator of any mental health condition - Depression: Depressive disorders - Anxiety: Anxiety disorders
- Bipolar: Bipolar affective disorder - OCD: Obsessive-compulsive disorder (includes various spellings) - Anorexia: Anorexia nervosa - Behavioural: Behavioural disorders - Maternal Asthma - Number of 18wk DASS domains with “Severe” or “Extremely Severe” - Number of 18wk DASS domains with “Normal” - Number of 36wk DASS domains with “Severe” or “Extremely Severe” - Number of 36wk DASS domains with “Normal”

Sample availability variables - Availability of maternal/child urine/blood/stool samples (20 weeks, 2 months, 6 months, 12 months, 3 years) - ASQ completion (4 month, 9 month, 1 year, 3 year, 5 year) - Early Connors assigned and completed - REDCap questionnaires assigned and completed - Availability of MNS data - Total questionnaires completed

Outcome variables - 1yr child wheeze - 1 year BMI - 1 year Ferritin results - 1 year count of positive SPT wheals - 1 year any positive food SPT wheals - 1 year any positive airborne/enviro SPT wheals - 3 year count of positive SPT wheals - 3 year any positive food SPT wheals - 3 year any positive airborne/enviro SPT wheals - 3 year BMI - 3 year wheeze - 3 year asthma - 3 year ferritin - 5 year BMI - 5 year asthma - 5 year Ferritin - 5 year any positive food SPT wheals - 5 year any positive airborne/enviro SPT wheals - 3 year count of Connors domains equal to, or above 65 - 3 year count of other clinical indicators parent reported as “3” highest

Remaining variables - Variables not contained in the primary nor sample availability variable set.

1) Primary Variables

Broadly, the distribution “primary” variable set between the Microbiome and overall cohorts is similar.

Notes - Child sex is well-balanced between groups (46.8% vs 47.9% female, p=0.799) - Maternal age at birth differs significantly, with the Microbiome cohort being older (mean 33.0 vs 31.8 years, p<0.001) - Maternal pre-pregnancy characteristics (weight, height, BMI) are well-balanced between groups - Infant birth characteristics (weight, length, BMI) show no significant differences - Ethnic origin and indigenous status are approximately balanced - Birth type, maternal gestational diabetes, and Type 2 diabetes show no significant differences - Mental health diagnosis patterns: - Overall mental health diagnoses are similar between groups (10.8% vs 14.5%) - Individual disorders show similar distributions across both cohorts - Maternal asthma shows a significant difference (p=0.037), with lower rates in the Microbiome cohort (3.9% vs 8.1%) - DASS mental health scores: - 18-week assessments show the Microbiome cohort trends toward better mental health (more “Normal” scores) - 36-week assessments show significantly more “Normal” scores in the Microbiome cohort (p=0.042) - Generally fewer severe mental health symptoms in the Microbiome group

# Primary continuous variables
primary_continuous <- list(
  list("gender_child", "Child sex assigned at birth"),
  list("maternal_age_birth", "Maternal Age (Birth)"),
  list("maternal_prepreg_weight", "Maternal pre-pregnancy weight"),
  list("maternal_prepreg_height", "Maternal Pre-pregnancy height"),
  list("maternal_prepreg_bmi_calc", "Maternal Pre-pregnancy BMI (Calc.)"),
  list("infant_weight", "Infant Weight"),
  list("infant_length", "Infant Length at birth"),
  list("infant_bmi_calc", "Infant BMI at birth (Calc.)"),
  list("ethnic_origin", "Ethnic Origin"),
  list("indigenous_status", "Indigenous Status of Baby"),
  list("birth_type_derived", "Vaginal or C section birth (Deriv.)"),
  list("maternal_gest_diabetes_derived", "Maternal Gestational Diabetes? (Deriv.)"),
  list("maternal_diabetes_t2_derived", "Maternal Type 2 Diabetes? (Deriv.)"),  # UPDATED
  list("mh_any", "Any Maternal Mental Health Diagnosis"),
  list("mh_depression", "Maternal Depression"),
  list("mh_anxiety", "Maternal Anxiety Disorder"),
  list("mh_bipolar", "Maternal Bipolar Disorder"),
  # REMOVED: list("mh_schizophrenia", "Maternal Schizophrenia"),
  list("mh_ocd", "Maternal OCD"),
  list("mh_anorexia", "Maternal Anorexia"),
  # REMOVED: list("mh_phobias", "Maternal Specific Phobias"),
  list("mh_behavioural", "Maternal Behavioural Disorders"),
  list("maternal_asthma_derived", "Maternal Asthma? (Deriv.)"),
  list("dass21_18w_severe_count", "Number of 18wk DASS domains with \"Severe\" or \"Extremely Severe\""),
  list("dass21_18w_normal_count", "Number of 18wk DASS domains with \"Normal\""),
  list("dass21_36w_severe_count", "Number of 36wk DASS domains with \"Severe\" or \"Extremely Severe\""),
  list("dass21_36w_normal_count", "Number of 36wk DASS domains with \"Normal\"")
)


for(var_info in primary_continuous) {
  var_name <- var_info[[1]]
  title <- var_info[[2]]
  
  if(var_name %in% numeric_vars) {
    analyze_continuous(dat, var_name, title)
  } else {
    analyze_categorical(dat, var_name, title)
  }
}

Child sex assigned at birth

**P-value:** 0.799 (Chi-squared test)
Characteristic	Included N = 203	Overall N = 3859
Female	95 (46.8%)	1849 (47.9%)
Male	108 (53.2%)	2010 (52.1%)
Total	203 (100.0%)	3859 (100.0%)

Maternal Age (Birth)

**P-value:** <0.001 (Wilcoxon rank sum test)
Characteristic	N	Mean (Min, Max)	Median (Q1, Q3)
Included	203	33 (24, 44)	32 (30, 35)
Overall	3859	31.8 (17, 50)	32 (29, 35)

Unknown: Included = 0 , Overall = 0

Maternal pre-pregnancy weight

**P-value:** 0.662 (Wilcoxon rank sum test)
Characteristic	N	Mean (Min, Max)	Median (Q1, Q3)
Included	191	69.6 (47, 128)	67 (60, 75)
Overall	3633	70.5 (38, 134)	68 (60, 79)

Unknown: Included = 12 , Overall = 226

Maternal Pre-pregnancy height

**P-value:** 0.595 (Wilcoxon rank sum test)
Characteristic	N	Mean (Min, Max)	Median (Q1, Q3)
Included	194	1.7 (1.5, 1.8)	1.7 (1.6, 1.7)
Overall	3698	1.7 (1.4, 1.9)	1.6 (1.6, 1.7)

Unknown: Included = 9 , Overall = 161

Maternal Pre-pregnancy BMI (Calc.)

**P-value:** 0.587 (Wilcoxon rank sum test)
Characteristic	N	Mean (Min, Max)	Median (Q1, Q3)
Included	191	25.4 (17.3, 42.3)	24.1 (21.9, 28.5)
Overall	3623	25.7 (14.7, 47.3)	24.7 (21.9, 28.6)

Unknown: Included = 12 , Overall = 236

Infant Weight

**P-value:** 0.315 (Wilcoxon rank sum test)
Characteristic	N	Mean (Min, Max)	Median (Q1, Q3)
Included	186	3317.7 (1480, 4500)	3355 (3071.2, 3652.5)
Overall	3578	3369.2 (1095, 5410)	3390 (3062.8, 3695)

Unknown: Included = 17 , Overall = 281

Infant Length at birth

**P-value:** 0.096 (Wilcoxon rank sum test)
Characteristic	N	Mean (Min, Max)	Median (Q1, Q3)
Included	186	50 (39, 57)	50 (48, 52)
Overall	3574	50.3 (31, 60)	50 (49, 52)

Unknown: Included = 17 , Overall = 285

Infant BMI at birth (Calc.)

**P-value:** 0.917 (Wilcoxon rank sum test)
Characteristic	N	Mean (Min, Max)	Median (Q1, Q3)
Included	186	13.2 (7.6, 17.6)	13.2 (12.3, 14.1)
Overall	3574	13.3 (7.6, 32.3)	13.2 (12.3, 14.2)

Unknown: Included = 17 , Overall = 285

Ethnic Origin

**P-value:** 0.543 (Fisher’s exact test)
Characteristic	Included N = 203	Overall N = 3859
Unknown	17 (8.4%)	285 (7.4%)
1	158 (77.8%)	2951 (76.5%)
3	8 (3.9%)	177 (4.6%)
4	2 (1%)	116 (3%)
5	2 (1%)	18 (0.5%)
8	16 (7.9%)	288 (7.5%)
10	0 (0%)	8 (0.2%)
6	0 (0%)	4 (0.1%)
7	0 (0%)	12 (0.3%)
Total	203 (100.0%)	3859 (100.0%)

Indigenous Status of Baby

**P-value:** 1.000 (Fisher’s exact test)
Characteristic	Included N = 203	Overall N = 3859
Unknown	17 (8.4%)	283 (7.3%)
4	186 (91.6%)	3563 (92.3%)
1	0 (0%)	12 (0.3%)
2	0 (0%)	1 (0%)
Total	203 (100.0%)	3859 (100.0%)

Vaginal or C section birth (Deriv.)

**P-value:** 0.392 (Fisher’s exact test)
Characteristic	Included N = 203	Overall N = 3859
Unknown	17 (8.4%)	281 (7.3%)
Caesarean Elective	58 (28.6%)	964 (25%)
Caesarean Emergency	41 (20.2%)	804 (20.8%)
Vaginal	87 (42.9%)	1810 (46.9%)
Total	203 (100.0%)	3859 (100.0%)

Maternal Gestational Diabetes? (Deriv.)

**P-value:** 0.695 (Chi-squared test)
Characteristic	Included N = 203	Overall N = 3859
Unknown	17 (8.4%)	281 (7.3%)
FALSE	172 (84.7%)	3271 (84.8%)
TRUE	14 (6.9%)	307 (8%)
Total	203 (100.0%)	3859 (100.0%)

Maternal Type 2 Diabetes? (Deriv.)

**P-value:** 1.000 (Fisher’s exact test)
Characteristic	Included N = 203	Overall N = 3859
Unknown	17 (8.4%)	281 (7.3%)
FALSE	186 (91.6%)	3572 (92.6%)
TRUE	0 (0%)	6 (0.2%)
Total	203 (100.0%)	3859 (100.0%)

Any Maternal Mental Health Diagnosis

**P-value:** 0.151 (Chi-squared test)
Characteristic	Included N = 203	Overall N = 3859
FALSE	181 (89.2%)	3298 (85.5%)
TRUE	22 (10.8%)	561 (14.5%)
Total	203 (100.0%)	3859 (100.0%)

Maternal Depression

**P-value:** 0.239 (Chi-squared test)
Characteristic	Included N = 203	Overall N = 3859
FALSE	192 (94.6%)	3557 (92.2%)
TRUE	11 (5.4%)	302 (7.8%)
Total	203 (100.0%)	3859 (100.0%)

Maternal Anxiety Disorder

**P-value:** 0.278 (Chi-squared test)
Characteristic	Included N = 203	Overall N = 3859
FALSE	186 (91.6%)	3437 (89.1%)
TRUE	17 (8.4%)	422 (10.9%)
Total	203 (100.0%)	3859 (100.0%)

Maternal Bipolar Disorder

**P-value:** 1.000 (Fisher’s exact test)
Characteristic	Included N = 203	Overall N = 3859
FALSE	203 (100%)	3845 (99.6%)
TRUE	0 (0%)	14 (0.4%)
Total	203 (100.0%)	3859 (100.0%)

Maternal OCD

**P-value:** 1.000 (Fisher’s exact test)
Characteristic	Included N = 203	Overall N = 3859
FALSE	203 (100%)	3855 (99.9%)
TRUE	0 (0%)	4 (0.1%)
Total	203 (100.0%)	3859 (100.0%)

Maternal Anorexia

**P-value:** 1.000 (Fisher’s exact test)
Characteristic	Included N = 203	Overall N = 3859
FALSE	203 (100%)	3843 (99.6%)
TRUE	0 (0%)	16 (0.4%)
Total	203 (100.0%)	3859 (100.0%)

Maternal Behavioural Disorders

**P-value:** 1.000 (Fisher’s exact test)
Characteristic	Included N = 203	Overall N = 3859
FALSE	203 (100%)	3849 (99.7%)
TRUE	0 (0%)	10 (0.3%)
Total	203 (100.0%)	3859 (100.0%)

Maternal Asthma? (Deriv.)

**P-value:** 0.037 (Chi-squared test)
Characteristic	Included N = 203	Overall N = 3859
Unknown	17 (8.4%)	281 (7.3%)
FALSE	178 (87.7%)	3264 (84.6%)
TRUE	8 (3.9%)	314 (8.1%)
Total	203 (100.0%)	3859 (100.0%)

Number of 18wk DASS domains with “Severe” or “Extremely Severe”

**P-value:** 0.171 (Wilcoxon rank sum test)
Characteristic	N	Mean (Min, Max)	Median (Q1, Q3)
Included	177	0.1 (0, 2)	0 (0, 0)
Overall	2781	0.1 (0, 3)	0 (0, 0)

Unknown: Included = 26 , Overall = 1078

Number of 18wk DASS domains with “Normal”

**P-value:** 0.064 (Wilcoxon rank sum test)
Characteristic	N	Mean (Min, Max)	Median (Q1, Q3)
Included	177	2.7 (0, 3)	3 (3, 3)
Overall	2781	2.6 (0, 3)	3 (2, 3)

Unknown: Included = 26 , Overall = 1078

Number of 36wk DASS domains with “Severe” or “Extremely Severe”

**P-value:** 0.285 (Wilcoxon rank sum test)
Characteristic	N	Mean (Min, Max)	Median (Q1, Q3)
Included	119	0.1 (0, 3)	0 (0, 0)
Overall	1570	0.1 (0, 3)	0 (0, 0)

Unknown: Included = 84 , Overall = 2289

Number of 36wk DASS domains with “Normal”

**P-value:** 0.042 (Wilcoxon rank sum test)
Characteristic	N	Mean (Min, Max)	Median (Q1, Q3)
Included	119	2.8 (0, 3)	3 (3, 3)
Overall	1570	2.6 (0, 3)	3 (3, 3)

Unknown: Included = 84 , Overall = 2289

2) Sample Availability

In general, sample availability and engagement in the Microbiome cohort is substantially higher relative to the overall cohort, with significant differences across virtually all measures.

# Sample availability variables
sample_vars <- list(
  list("mns_data_available", "MNS Data Available?"),
  list("asq_assigned", "ASQ Questionnaires Assigned"),
  list("asq_completed", "ASQ Questionnaires Completed"),
  list("early_connors_assigned", "Early Connors Assigned"),
  list("early_connors_completed", "Early Connors Completed"),
  list("aes_assigned", "AES Questionnaires Assigned"),
  list("aes_completed", "AES Questionnaires Completed"),
  list("redcap_assigned", "RedCap Questionnaires Assigned"),
  list("redcap_completed", "RedCap Questionnaires completed"),
  list("questionnaires_total_completed", "Total Questionnaires Completed"),
  list("asq_4m_completed", "ASQ 4 Month Completed"),
  list("asq_4m_paed_review", "ASQ 4 Month Review with Paediatrician"),
  list("asq_9m_completed", "ASQ 9 Month Completed"),
  list("asq_9m_paed_review", "ASQ 9 Month Review with Paediatrician"),
  list("asq_1yr_completed", "ASQ 1 Year Completed"),
  list("asq_1yr_paed_review", "ASQ 1 Year Review with Paediatrician"),
  list("asq_3yr_completed", "ASQ 3 Year Completed"),
  list("asq_3yr_paed_review", "ASQ 3 Year Review with Paediatrician"),
  list("asq_5yr_completed", "ASQ 5 Year Completed"),
  list("asq_5yr_paed_review", "ASQ 5 Year Review with Paediatrician"),
  list("asq_paed_review_count", "Number of times ASQ has prompted review with PAED")
)

for(var_info in sample_vars) {
  var_name <- var_info[[1]]
  title <- var_info[[2]]
  
  if(var_name %in% numeric_vars) {
    analyze_continuous(dat, var_name, title)
  } else {
    analyze_categorical(dat, var_name, title)
  }
}