NameCensus.

UK surname

Skimming

In the 1881 census there were 173 people recorded with the Skimming surname, ranking it #14,112 among surnames in the records. By 2016, the modern count was 141, ranked #24,753, down from #14,112 in 1881.

The strongest historical links point to Sorbie, Govan Combination and Kirkinner. In the modern distribution records, the strongest local clusters include Allerdale, Ayr South Harbour and Town Centre and New Abbey.

Across the surname records, the highest recorded count for Skimming is 173 in 1881. Compared with 1881, the name has fallen by 18.5%.

1881 census count

173

Ranked #14,112

Modern count

141

2016, ranked #24,753

Peak year

1881

173 bearers

Map years

8

1851 to 2016

Key insights

  • Skimming had 173 recorded bearers in 1881, making it the #14,112 surname in that year.
  • The latest modern count shown here is 141 in 2016, ranked #24,753.
  • Within the historical census years, the highest count was 173 in 1881.
  • The contemporary neighbourhood profile most associated with the surname is Legacy and Demographically Mixed Communities.

Skimming surname distribution map

The map shows where the Skimming surname is concentrated in each census or modern distribution year. Darker areas mean a stronger local concentration.

Distribution map

Skimming surname density by area, 1881 census.

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Lower densityMedium densityHigh density

Timeline

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Skimming over time

The table below tracks recorded surname counts and rank from the 19th-century census years through the modern adult-register period.

Year Period Count Rank
1851 historical 119 #15,247
1861 historical 133 #16,835
1881 historical 173 #14,112
1891 historical 149 #18,420
1901 historical 163 #17,205
1911 historical 51 #27,708
1997 modern 143 #21,761
1998 modern 145 #22,139
1999 modern 146 #22,202
2000 modern 136 #23,155
2001 modern 135 #22,945
2002 modern 140 #22,876
2003 modern 138 #22,823
2004 modern 142 #22,573
2005 modern 143 #22,473
2006 modern 140 #22,948
2007 modern 139 #23,377
2008 modern 132 #24,476
2009 modern 139 #24,161
2010 modern 147 #23,809
2011 modern 129 #25,673
2012 modern 137 #24,731
2013 modern 134 #25,525
2014 modern 136 #25,452
2015 modern 139 #24,956
2016 modern 141 #24,753

Geography

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Where Skimmings are most common

Historical parish links are strongest around Sorbie, Govan Combination, Kirkinner, Old Luce and Glasgow. These are the places where the surname stands out most clearly in the older records.

The modern local-area list points to Allerdale, Ayr South Harbour and Town Centre, New Abbey, Machars South and Summerville. Treat these as concentration signals, not proof that every family line began there.

Some modern areas include a three-digit suffix, such as Leeds 110. The suffix is a small-area code, so it stays in the table while the prose uses the plain place name.

Top historical parishes

Rank Parish Area
1 Sorbie Wigtown
2 Govan Combination Lanark
3 Kirkinner Wigtown
4 Old Luce Wigtown
5 Glasgow Lanark

Top modern areas

Rank Area District
1 Allerdale 010 Allerdale
2 Ayr South Harbour and Town Centre South Ayrshire
3 New Abbey Dumfries and Galloway
4 Machars South Dumfries and Galloway
5 Summerville Dumfries and Galloway

Forenames

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First names often paired with Skimming

These lists show first names that appear often with the Skimming surname in historical and recent records.

Modern profile

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Neighbourhood profile for Skimming

Modern surname records can be compared with neighbourhood classifications. For Skimming, this points to the kinds of places where the surname is most concentrated today.

These neighbourhood labels describe areas, not individual people. They are useful because surnames often cluster through family history, migration, housing patterns and local work. A surname can be strongest in one type of neighbourhood even when people with that name live across the country.

The UK classification gives the national picture. The London classification is more specific to the capital, where housing, age profile, tenure and population mix can look quite different from the rest of the UK.

UK neighbourhood type

UK Output Area Classification

Supergroup

Legacy Communities

Group

Legacy and Demographically Mixed Communities

Nationally, the Skimming surname is most associated with neighbourhoods classed as Legacy and Demographically Mixed Communities, within Legacy Communities. This does not mean every Skimming household fits that profile, but it gives a useful signal about where the modern surname distribution is strongest.

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Group profile

Households in these areas often include divorced or separated parents and commonly include children and young adults. The age structure is heavily skewed towards the most advanced age groups. Individuals identifying as members of ethnic minorities are not present in large numbers. Flats predominate, with some terraced, semi-detached, and detached units. Multiple car ownership is low, and housing is predominantly in the private and social rented sectors. Employment is less skewed towards traditional routine industrial occupations. Levels of educational attainment are generally low. The Group occurs principally in the Central Lowlands of Scotland and other Scottish towns.

Wider pattern

These neighbourhoods characteristically comprise pockets of flats that are scattered across the UK, particularly in towns that retain or have legacies of heavy industry or are in more remote seaside locations. Employed residents of these neighbourhoods work mainly in low-skilled occupations. Residents typically have limited educational qualifications. Unemployment is above average. Some residents live in overcrowded housing within the social rented sector and experience long-term disability. All adult age groups are represented, although there is an overall age bias towards elderly people in general and the very old in particular. Individuals identifying as belonging to ethnic minorities or Mixed or Multiple ethnic groups are uncommon.

London neighbourhood type

London Output Area Classification

Supergroup

Social Rented Sector Families with Children

Group

Social Rented Sector Pockets

Within London, Skimming is most associated with areas classed as Social Rented Sector Pockets, part of Social Rented Sector Families with Children. This gives the surname a London-specific profile rather than forcing the capital into the same pattern as the rest of the country.

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Group profile

Found in pockets across London, residents are less likely to live in private sector rentals and fewer adults are students. Fewer individuals work in transport and communications occupations relative to the Supergroup average. More individuals identify as Black and were born in Africa.

Wider London pattern

Residents of these neighbourhoods include sizable numbers identifying with ethnicities originating outside Europe, particularly in Africa or Bangladesh. The proportion of residents identifying as White, Indian or Pakistani is well below the London average. Neighbourhood age profiles are skewed towards younger adults, and above average numbers of families have children. Rates of use of English at home are below average. Marriage rates are low, and levels of separation or divorce are above average. Housing is predominantly in flats, and renting in the social rented sector the norm - few residents are owner occupiers. Housing is often overcrowded, and neighbourhoods are amongst the most densely populated in London. Disability rates are above average, although levels of unpaid care provision are about average. Employment is in caring, leisure, other service occupations, sales and customer service, or process, plant, and machine operation. Part time working and full-time student study are common. Levels of unemployment are slightly above average. Most residents have only Level 1 or 2 educational qualifications or have completed apprenticeships.

Healthy neighbourhoods

Access to healthy assets and hazards

Skimming is most concentrated in decile 1 for access to healthy assets and hazards. This places the surname towards the less healthy end of the index.

Lower deciles point towards weaker access to healthy assets or stronger exposure to local hazards. Higher deciles point towards stronger access and fewer hazards.

1
Lower access Higher access

Neighbourhood deprivation

Index of Multiple Deprivation

Skimming falls in decile 9 for neighbourhood deprivation. This puts the surname towards the less deprived end of the index.

Decile 1 represents the more deprived end of the scale. Decile 10 represents the less deprived end.

9
More deprived Less deprived

Broadband speed

Fixed broadband download speed

The modern neighbourhood pattern for Skimming is most associated with a typical fixed broadband download band of 25-30 mbit/s.

The scale below places that band in context, from slower local download bands through to faster ones.

5
Slower band Faster band

Area snapshot

Ethnic group estimate

Most common ethnic group estimate
White - British

This describes the area pattern most associated with Skimming, not the ethnicity of every person with the surname.

1881 census detail

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Skimming families in the 1881 census

These tables use 1881 census entries for people recorded with the Skimming surname. Use the location tables for concentration, then the name and occupation tables for the people behind the surname.

Top counties

Total is the county count. Frequency and index adjust for local population size, so they are better concentration signals. Wigtownshire leads with 63 Skimmings recorded in 1881 and an index of 284.42x.

County Total Index
Wigtownshire 63 284.42x
Kirkcudbrightshire 38 157.42x
Lanarkshire 22 4.08x
Ayrshire 12 9.61x
Cumberland 9 6.27x
Dunbartonshire 9 20.08x
Lancashire 6 0.30x
Somerset 5 1.86x
Perthshire 4 5.34x
Argyllshire 1 2.15x
Buteshire 1 9.89x
Middlesex 1 0.06x

Top districts and towns

Districts give a more local view than counties. Total shows raw records, while frequency and index show local concentration. Minnigaff in Kirkcudbrightshire leads with 23 Skimmings recorded in 1881 and an index of 2527.47x.

Place Total Index
Minnigaff 23 2527.47x
Govan 19 14.24x
Kirkcolm 11 1037.74x
Stewarton 11 445.34x
Row 9 155.17x
Sorbie 9 927.84x
Kirkinner 8 879.12x
Old Luce 8 571.43x
Tongland 8 1702.13x
Wigtown 8 634.92x
Cleator 6 100.33x
Kirkmabreck 6 566.04x
Kirkmaiden 6 428.57x
Chorlton On Medlock 5 15.90x
Congresbury 5 735.29x
Leswalt 4 263.16x
Perth East Church 4 56.66x
Stoneykirk 4 253.16x
Lamplugh 3 416.67x
Penninghame 3 132.74x
Barony 2 1.47x
Girvan 1 31.95x
Gorbals 1 31.25x
Inch 1 46.30x
Lochgilphead 1 10000.00x
Parton 1 243.90x
Rothesay 1 20.45x
St George Hanover 1 4.59x
Wardleworth 1 8.84x
Whithorn 1 59.17x

Top female names

These are the female first names most often recorded with the Skimming surname in 1881. Names are not merged, so initials, variant spellings and transcription quirks can appear as separate rows.

Name Count
Elizabeth 2
Sarah 2
Caroline 1
Grace 1
Jane 1
Mary 1

Top male names

These are the male first names most often recorded with the Skimming surname in 1881. Names are not merged, so initials, variant spellings and transcription quirks can appear as separate rows.

Name Count
John 6
David 2
James 2
Harry 1
Hugh 1
William 1

Top occupations

Occupational titles are kept as recorded and later transcribed, so related jobs, spelling variants and mistakes stay separate. Scholar was the census term for a child in education. That means the other rows often tell you more about adult work in Skimming households.

FAQ

Skimming surname: questions and answers

How common was the Skimming surname in 1881?

In 1881, 173 people were recorded with the Skimming surname. That placed it at #14,112 in the surname rankings for that year.

How common is the Skimming surname today?

The latest modern count shown here is 141 in 2016. That gives Skimming a modern rank of #24,753.

What does the Skimming map show?

The map shows local surname concentration for the selected year. Darker areas have a stronger concentration of Skimming bearers relative to the surrounding population.

What records is this surname page based on?

The historical counts come from census surname records. The modern counts and neighbourhood summaries come from later surname distribution records. Counts are recorded bearers in those records, not a live estimate of everyone with the name today.